United States
           Environmental Protection
           Agency
           Office of Water
           (4305)
EPA 823-R-98-002
February 1998
vvEPA
National Sediment
Bioaccumulation
Conference

Proceedings

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      • National Sediment Bioaccumulation Conference \
              Proceedings

National Sediment Bioaccumulation
              Conference
              September 11-13,1996
               Bethesda, Maryland
                 Printed on Recycled Paper

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                                                             National Sediment Bioaccumulation Conference
Abstract
      During September 11-13, 1996, the U.S.-Environmental Protection Agency (EPA)
      sponsored the National Sediment Bioaccumulation Conference in Bethesda, Mary-
      land. The assessment of bioaccumulative sediment contaminants has become an
important issue for EPA and other agencies. Data compiled to date for EPA's National
Sediment Quality Survey  and the National Listing of Fish and Wildlife Consumption
Advisories  indicate that the presence of bioaccumulative substances in sediments is a
potentially serious national problem. EPA uses bioaccumulation data to make regulatory
decisions in a number of its programs. The Superfund Program uses bioaccumulation data
to assess contaminated sites for cleanup. Results of bioaccumulation tests are used in the
assessment of new and existing industrial chemicals under the Toxic Substances Control Act
(TSCA) and in the review process for National Pollutant Discharge Elimination System
(NPDES) permits and dredged material discharge permits. Bioaccumulation studies are also
required to  support registration of pesticides under the. Federal Insecticide, Fungicide, and
Rodenticide Act (FIFRA).  Advances in the science of bioaccumulation testing and
assessment and interpretation of test results will benefit all of these programs.
     The purpose of this conference was to present the current state of our knowledge of
assessment of bioaccumulative sediment contaminants and to discuss how bioaccumulation
data are integrated into EPA's decision-making processes. The conference was organized
into the following seven sessions:

Session One         Field and Laboratory Methods for Measuring Bioaccumulation
Session Two         Interpretation and Applications of Bioaccumulation Results
Session Three        Modeling Bioavailability of Sediment Contaminants
Session Four         Food Chain Models and Bioenergetics
Session Five        , Human Health-Based Risk Assessment
Session Six         Ecological-Based Risk Assessment
Session Seven       Integrating Bioaccumulation Results into EPA's Decision-
                    Making Process

     Each session consisted of individual presentations and a discussion period  with
questions and comments from the audience and responses by the speakers. The Proceedings
document contains a paper and graphics summarizing each speaker's presentation and a
summary of audience questions and panel responses during the discussion period. It also
contains the conference agenda and additional information developed for the conference.
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             National Sediment Bioaccumulation Conference •
Contents
          Acknowledgments	,..:......	 ix

Day One:  Wednesday, September 11    ,

          Welcome and Introduction	.....1-1
          Dr. Elizabeth Souther/and and Dr. Thomas Armitage

   BIOACCUMULATION OVERVIEW AND APPROACHES

      Bioaccumulation Overview and Approaches	.1-3

          Contaminated Sediments:
          State of the Science and Future Research Directions	 1-5
          Dr. Oilman D. Veith

      Field and Laboratory Methods for Measuring Bioaccumulation	.1-9
      Dr. Peter Chapman, Moderator

          Methods for Assessing Sediment Bioaccumulation
          in Marine/Estuarine Benthic Organisms	 Irll
          Dr. Henry Lee II
          Methods for Assessing Bioaccumulation of
          Sediment-Associated Contaminants with Freshwater Invertebrates	 1-25
          Dr. Christopher-G. Ingersoll                                ,
          Kinetic Models  for Assessing Bioaccumulation ..;	 1-47
          Dr. Peter Landrum                                      ,
          Session One: Questions and Answers	 1-51

      Interpretation and Applications of Bioaccumulation Results	2-1
      Dr. Richard Pnfell, Moderator

          Reference Sediment Approach for Determining Sediment Contamination	2-3
:          Mr. Norman I. Rubinstein
          Development of Tissue Residue Threshold Values	2-9
          Dr. David R.Mount
          Use of Tissue Residue Data in Exposure and
          Effects Assessments for Aquatic Organisms...	,2-21
          Mr. L Jay Field                                              .'•'•'

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           Comments on the Significance and Use of
           Tissue Residues in Sediment Toxicology and Risk Assessment	2-25
           Dr. Lynn S. McCarty

           Quantification of Ecological Risks to
           Aquatic Biota from  Bioaccumulated Chemicals	2-31
           Mr. Burt K. Shephard
           Session Two: Questions and Answers	2-53

      Modeling Bioavailability of Sediment Contaminants	3-1
      Mr. Nelson Thomas, Moderator

           Equilibrium Partitioning and Organic Carbon Normalization	3-3
           Dr. Dominic M. Di Toro
           Estimating Bioaccumulation Potential in Dredged Sediment Regulation	3-7
           Dr. Victor A. McFarland
           Development of Bioaccumulation Factors for
           Protection of Fish and Wildlife in the Great Lakes	3-19
           Dr. Philip M. Cook
           From Modeling to Criteria: Integrated Approach to Criteria Development	3-29
           Ms. Mary C. Reiley
           Session Three: Questions and Answers	3-33


Day Two:  Thursday, September 12


      Food Chain Models and Bioenergetics	.....4-1
      Dr. Lawerence Burkhard, Moderator

          Food Chain Models for Predicting Bioaccumulation	4-3
          Dr. Frank Cobas
          Use of Food Web Models to Evaluate Bioaccumulation Data	4-5
          Dr. John P. Connolly
          Bioaccumulation Modeling of PCBs
          in the Hudson Estuary: A Review and Update	4-19
          Dr. Robert V. Thomann
          Session Four: Questions and Answers	4-23


   BIOACCUMULATION AND RISK ASSESSMENT

          Risk Assessment Overview	 5-1
          Dr. Dorothy Patton
                                         vi

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      Human Health-Based Risk Assessment....	.................5-3
      Dr. Marc Tuchman, Moderator                         .

          Methodology for Assessing Human Health-Based Risks	5-5
          Dr. Judy L. Crane
          Bioaccumulation Models and Applications:
          Setting Sediment Cleanup Goals in the Great Lakes	5-9
          Ms. Amy Pelka
          Use of Human Health-and Ecological-Based
          Goals in Developing a Whole River
          Sediment Strategy: Fox River, Wisconsin	:...	5-31
          Mr. Robert L. Paulson   .
          Development of Health-Based Sediment Criteria for Puget Sound	>....	5-35
          Ms. Laura B. Weiss
          Development of Bioaccumulation  Guidance for
          Dredged Material Evaluations in EPA Region 2	.;....	5-47
          Mr. Alex Lechich
          Session Five: Questions and Answers	•.	5-61

      Ecological-Based Risk Assessment	6-1
      Dr. James Andreasen, Moderator

          Use of Bioaccumulation Data in Aquatic Life Risk Assessment	 6-3
          Dr. Wayne R. Munns, Jr.
          Wildlife Risk Assessment	6-9
          Dr. David Charters
          Session Six:  Questions and Answers	—	6-15

Day 3:  Friday, September 13


BIOACCUMULATION RESULTS AND DECISION-MAKING

      Integrating Bioaccumulation Results into EPA's
      Decision-Making Process	.	7-1
      Dr. Elizabeth Southerland, Moderator

          Opening Remarks	7-3
          Dr. Elizabeth Southerland
          Bioaccumulation Testing and Interpretation for the Purpose of
          Sediment Qualify Assessment: Status and Needs....	,..	7-5
          Mr. Michael Kravitz
                                         vii

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    Panel Presentations	7-15

        Bioaccumulation Results and Decision-Making:
        The Superfund Program	7-17
        Dr. Lawrence Zaragoza

        Sediment Bioaccumulation—A National Pollutant Discharge
        Elimination System (NPDES) Program Perspective	7-23
        Mr. James Pendergast

        Integrating Bioaccumulative Results into EPA's Decision-Making Process	7-31
        Mr.  Thomas Murray

        U.S. EPA/OPPT and Sediments:  Screening New and Existing Chemicals for
        Potential Environmental Effects	„	7-35
        Dr. Maurice Zeeman

        Dredged,Material Management Program	7-49
        Mr.  Craig Vogt

        Dredged Material Management:  A Regional Perspective	 7-51
        Mr. Mario Del Vicario

        Session Seven: Questions and Answers	7-53
        $
   Speakers'Biographies	8-1
ATTACHMENTS

       Agenda
       List of Attendees
                                     viii

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                                                       National Sediment Bioaccumulation Conference
Acknowledgments
     The National Sediment Bioaccumulation Conference was funded jointly by two
     offices in the U.S. Environmental Protection Agency, the Office of Science and
     Technology (in the Office of Water) and the Office of Research and Development
(ORD).  The Standards and Applied Science.Division  in the Office of Science and
Technology (OST) organized the conference. Tetra Tech, Inc. provided logistical support
for the conference and production support for the proceedings under EPA contract number
68-C3-0374.        .                            '
   , A planning workgroup consisting of representatives from OST, ORD, Great Lakes
National Program Office (GLNPO), and EPA Region 5  participated in developing the
agenda and identifying speakers for the conference. The workgroup members were: Tom
Armitage, EPA^OST; Ed Earth, EPA ORD; Mike Kravitz, EPA OST; Amy Pelka, EPA
Region 5;  Rich Pruell, EPA ORD; Lara Pullen, EPA Region 5; Dave Redford, EPA
OWOW; Leanne Stahl, EPA OST; Marc Tuchman, GLNPO; Howard Zar, EPA Region 5;
and  Chris  Zarba, EPA ORD.  The contributions of these individuals in planning the
conference are ..greatly appreciated.
     Finally, the contributions  of the invited speakers  and  moderators are  gratefully
acknowledged. Then- efforts were critical to the success of the conference and.production
of the proceedings.
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                                                            National Sediment Bioaccumulation Conference
Welcome  and  Introduction
Dr. Elizabeth Southerland
Acting Director, Standards and Applied Science Division
Office of Science and Technology
U.S. Environmental Protection Agency

Dr. Thomas Armitage
Acting Chief, Risk Assessment and Management Branch
Office of Science and Technology
U.S. Environmental Protection Agency
 Dr. Southerland
 D
i. Southerland welcomed the participants  and
turned the podium over to Dr. Thomas Armitage
to outline the agenda for the conference.
 Dr. Armitage

      I would like to take this opportunity to welcome
 you to the National Sediment Bioaccumulation Confer-
 ence sponsored jointly by the Office of Water and the
 Office of Research and Development. I would also like
 to acknowledge the assistance we received in planning
 the conference from the Great Lakes National Program
 Office and EPA Region 5.
      We are very pleased to  finally be holding this
 conference.  Planning for this conference began over a
 year ago.  We persevered through the federal budget
 crisis and government shutdowns,  and are delighted to
 finally have all  of you here to participate. The response
 to our announcement of this bioaccumulation conference
 was  overwhelming.  When we started planning this
 conference, we had no idea that so many people would be
 interested in attending. Over 400 people are here today,
 which  clearly  indicates   that  assessment  of
 bioaccumulative sediment  contaminants. is an issue of
 major interest and importance in the scientific'and regu-
 latory community.
      For the next two and one-half days,  we will be
 hearing  from a number of distinguished experts in the
 . field of assessment of bioaccumulative sediment con-
 taminants.   We have  organized  the conference into
 several  sessions.  Each session will be chaired by  a
 moderator who will lead a discussion "and question and
 answer session following the presentations. We encour-
 age  audience participation during the discussion period
 and have provided microphones in the aisles for your
 comments and questions. During the first two days of the
 conference,  there will  be sessions covering field and
laboratory methods for measuring bioaccumulation, in-
terpreting and applying bioaccumulation results, model-
ing bioavailability of sediment contaminants, and assess-
ing human health and ecological risks associated with
bioaccumulative contaminants.  On the final day of the
conference, an EPA  program panel  will address how
results of bioaccumulation assessments are being inte-
grated into EPA's decision-making process. '
     The assessment of bioaccumulative contaminants
in sediment has become an important issue for EPA and
other Federal agencies.  From our work to date on the
National Sediment Quality Survey and the Listing of Fish
and  Wildlife Advisories, it is becoming increasingly
apparent that the presence of bioaccumulative substances
in sediments is a potentially serious widespread national
problem.   EPA evaluated more than 21,000 sampling
stations nationwide to develop the National Sediment
Quality Survey. Of the sampling stations evaluated, 26
percent were classified as Tier I and 49 percent were
classified as Tier 2.  Tier I  is a category indicating that
associated adverse effects are probable, and Tier II is a
category  indicating that associated adverse effects  are
possible, but expected  infrequently.  The classes of
bioaccumulative contaminants most frequently associ-
ated with contaminated sediment sites include metals,
polychlorinated biphehyls (PCBs), organochlorine pesti-
cides; and polynuclear aromatic hydrocarbons  (PAHs).
The 1996 update of the Listing of Fish and  Wildlife
Advisories includes all available information describing
state-, tribal-, and federally-issued fish consumption
advisories for the 50 states, the District of Columbia, four
U.S. territories, and  several Native American tribes. It
has been expanded to also include fish advisories issued
for the 12 Canadian  provinces and territories.  The total
number of advisories in the United.States increased by 26
percent from 1995 to 1996.  Advisories increased for four
major contaminants, including  mercury, PCBs,  chlor-
 dane, and DDT. More monitoring accounts for part of the
 increase in the number of advisories, but it also indicates
 a greater awareness  of the problem and underscores the
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                                                               National Sediment Bioaccumulation Conference
need for increased monitoring and reliable techniques for
assessing the risks of exposure to these chemicals.
      EPA uses information and data on bioaccumulation
to support program responsibilities in a number  of its
regulatory programs. The Office of Pesticide Programs
requires bioaccumulation studies for the registration of
pesticides under the Federal Insecticide, Fungicide, and
Rodenticide Act  (FIFRA).  The Office of Pollution
Prevention and Toxics  uses bioaccumulation data to
assess new and existing industrial chemicals under the
Toxic Substances Control Act (TSCA). The Superfund
Program in the Office of Solid Waste and Emergency
Response uses bioaccumulation data to assess contami-
nated sites for cleanup. The Office ofWater incorporates
results of bioaccumulation tests in the review process for
dredged material disposal permits and National Pollution
Discharge Elimination System (NPDES)  permits.   Ad-
vancing the state of our  knowledge in bioaccumulation
testing and assessment will benefit all of these programs.
     A number of important unresolved issues remain
for bioaccumulation assessment, including uncertainties
in test procedures and  limited understanding of the
 relationships between contaminant body burdens and
 adverse ecological effects.  I would like  to  again
 acknowledge the Office of Research and Development
 (ORD) cosponsorship of this conference and stress that
 we are looking to ORD to maintain leadership in answer-
 ing some of these questions.
      We organized this conference to provide a forum
,.to discuss the current state of our knowledge of assess-
 ment of bioaccumulative sediment contaminants and to
 examine how bioaccumulation data are integrated into
 EPA's decision-making processes.  We will be publish-
 ing a conference proceedings and are currently working
 on a report  summarizing the status of bioaccumulation
 testing and  interpretation  for- the purpose of  sediment
 quality assessment.  This conference and our status
 report will help us to better understand the state of the
 science, to  identify the data and knowledge  gaps,  to
 focus  research efforts on providing answers to the
 most important questions, and to  eventually develop
 consistent cross  program guidance on interpretation
 of bioaccumulation data for use in EPA's regulatory
 programs.

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                                National Sediment Bioaccumulation Conference
Bioaccumulation Overview
and Approaches
Gilman D. Veith
U.S. EPA, Office of Research and Development,
Research Triangle Park, North Carolina
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                                                           National Sediment Bioaccumulation Conference
                        lied Sediments: State of
the Science  and  Future  Research
Directions
 Gilman D. Veith
 U.S. Environmental Protection Agency, Office of Research and Development, National Health and
 Environmental Effects Research Laboratory, Research Triangle Park, North Carolina
    It is a real pleasure to be here today and speak at the first
    National Sediment Bioaccumulation Conference. As
    many of you know, when Bob Huggett came into the
 Office of Research and Development (ORD) as the Assis-
 tant Administrator,  he brought with him a strong belief
 that sediment contamination is one of the compelling
 research issues that we face as a nation. He still holds that
 belief. Bob is at an international meeting for the Agency,
 so I  am presenting for him today on behalf of ORD.
 However, my comments reflect my own perspective.
      This conference is exciting because it represents the
 culmination of many years of work related to sediments.
 It also demonstrates, better than many other examples in
 environmental research, how science can be applied in a
 partnership of researchers, risk managers, regulators, pri-
 vate interest groups, and agencies at all levels of govern-
 ment to  accomplish risk reduction.
      Abouttenyearsago,JimFalco,Director of Environ-
 mental Processes Research in EPA, asked that I meet with
 himandseveralmembersoftheOfficeofWater.Hewanted
 to discuss building  the scientific framework necessary to
- establish the concept of sediment quality criteria.  The
 existing methods then were highly empirical and often
 unreproducible,  and  they did  not allow us to predict
 effects.  We needed  criteria to make sense of the field
 measurements we were making.  He asked if  the ORD
 laboratories could  provide support for development of
 sediment quality criteria, and we agreed to get the labora-
 tories involved.
       Soon after we organized scientists familiar with
 sediment issues and began research, a Senator involved hi
 revising the Clean Water Act visited our laboratory and
 wanted to know about sediment contamination and why it
 needed attention.  After giving a technical presentation
  that included an explanation of bioaccumulation factors
  under steady-state conditions, he surprised us by asking
  "what is a sediment?"  There is a communication chal-
  lenge, in addition to the challenge of developing a work-
  able regulatory strategy for contaminated sediments.  In
  the last ten years, research has taught us how to begin
  making sense out of the data on sediment effects.
     In addition to developing sediment toxicity tests,
we  have  established  methods  to measure the
bioaccumulation potential of sediment contaminants.
When we published our first work on bioaccumulation,
we chose the term "bioaccumulation  potential" rather
than "bioconcentration factor" because kinetics and ther-
modynamics really intersect in bioaccumulation testing.
It is very difficult to predict the kinetics of uptake because
it is largely experimentally controlled and most of the
bioaccumulation methods  are operationally  defined.
"Bioaccumulation potential" is primarily a thermody-
namic term that separates chemicals that bioaccumulate
from those that do not. If organic chemicals are unlikely
to bioaccumulate, they would probably not even be in the
sediments. The "bioaccumulation potential" represents
the probability that a chemical is going to penetrate an
ecosystem by dispersing from a source and moving up
food chains to cause effects at levels we might not have
anticipated.
      Sediments were recognized as the final repository
for contaminants as early as the 1970s. During that decade
we were still struggling to define toxicity and to establish
permitting and  control programs.  Today, the issue of
reducing risks from  sediments that have already been
contaminated is an important problem that merits atten-
tion. Right now we are making good progress on work in
dredged material management, food chain modeling, and
development of tissue-based residue methodologies to
address this problem.  The academic community and
agencies at all levels of government have efforts under-
way to describe the dynamics of food chains and to define
how to use this information in a risk assessment.  The
 Office of Water is spearheading' one such effort by devel-
 oping the bioaccumulationpaperentifledBzoaccwmwtozon
 Testing and Interpretation for the Purpose of Sediment
' Quality Assessment: Status and Needs.  About 40 people
 from several EPA offices are collaborating to draft that
 report, which will include information on chemicals of
 concern and methods for assessing bioaccumulation, an
 Agency summary on bioaccumulation data collection and
 interpretation, and recommendations for further research.
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                                                                 National Sediment Bioaccumulation Conference
  Another sediment-related effort being conducted at an
  ORD laboratory is the development of toxicity identifica-
  tion  evaluation (TIE)  procedures to analyze complex
  chemical mixtures.
       Iwanttosummarizebrieflyhowweformulatepriori-
  ties for budgeting in ORD and how conferences like this
  can help. Surprisingly enough, when we went through the
  budget planning process, some participants expressed the
  belief that contaminated  sediments are not a serious
  national problem, that sediments do not present a signifi-
  cant risk to the envkonment, and that sediments do not
  merit further research based on their negligible risks. At
  first I laughed because I did not think they were serious,
  but then I realized that they were serious. They made their
  case using some of the same data we were using to try to
  show that sediment contamination is a significant prob-
  lem.  Data from a spatially subsampled survey conducted
  under the Environmental  Monitoring  and Assessment
  Program (EMAP) hi ORD covered estuaries in the Virgin-
  ian, Louisianan, and Carolinian provinces. Looking at the
  benthic condition with some of the EMAP indicators, one
  could see that about 29 percent of the estuaries had
  degraded benthic condition.
       That  information alone, however, does not con-
  vince skeptics that sediment contamination is a significant
  problem. The skeptics viewed 29 percent of our estuaries
  as impacted to mean 71 percent were not.
       I realized that we have not clearly answered the "So
  what?" questions with respect to ecological consequences.
  How much impact is too much?  When are fisheries and
  the productivity of coastal  waters affected? How much
  degradation could exist in the benthic systems to streams
  and lakes before there are  ecological consequences and
 loss of integrity? We can say that there are 17,000 square
 kilometers in our estuaries where you can measure an
 effect in the benthos, compared to reference conditions.
 That is a large area.  So what?  Similarly in the Great
 Lakes, many have overlooked the fact that reproduction in
 major species of the food chain has been shut off sincethe
 1940s due to chemical residues. EMAP combines measures
 of effect with stressors and has associated the degraded
 communities with sediment contaminants. For example,
 when  you link some of the areas of degraded benthic
 condition with measures of observed toxicity, you will
 find that these are the sites where survival of benthic
 organisms in bioassays was below 80 percent This evidence
 establishes an association strong enough to say that parts
 of the benthic community degradation are due to contami-
 nated sediments. The question that remains is how we can
 establish a cause-effect relationship between the loss of
 integrity and the sediment residues over large areas.
      The importance of these field studies in strengthen-
 ing  the risk assessment  process for sediment certainly
 plays into the risk-based priority setting in ORD. The new
 strategic plan for ORD is based on the risk paradigm. We
 now evaluate a problem based on whether or not we think
 the science can reduce the uncertainty associated with
 estimating effects, exposure, the assessment capability,
 and risk management There are some issues where ORD
 has concluded that we do not need to do more effects
research, because further effects research  would not
  contribute significantly to our understanding of the prob-
  lem. Contaminated sediments is one issue where major
  uncertainties still exist in effects and exposure  assess-
  ment. In the process of planning the budget according to
  risk-based priorities, we have consolidated the intramural
  research hi ORD to focus on contaminated sediments by
  designating this area as a budget subcomponent. ORD has
  created a work force of about 45 full-tune equivalents
  (FTEs), which represents an increase in the level of effort
  for sediment issues in the laboratories. We are revising the
  research  strategy for contaminated sediments,  and
  research recommendations that come out of this confer-
  ence will be considered hi developing the plan, particu-
  larly for projects directed at the Office of Water's needs.
       I would also like to  direct your attention to the
  extramural research program, known as the Science to
  Achieve Results (STAR) Program, that ORD initiated in
  1995.  STAR is a competitive research grants program
  being run by ORD's National Center for Environmental
  Research and  Quality Assurance in Washington, D.C.
  This year the grants program  included  only  about
  $2 million specifically for issues involving contaminated
  sediments.  There were more than 40 proposals and 8 of
  these proposals received high rankings by the peer review
 panel.  The small STAR budget for the sediment program
 could only fully fund four or five grants this year, but it is
 a start. We anticipate a modest increase in funding for
 contaminated sediment research grants in FY 1997.
      We may have temporarily won the battle to con-
 vince planners that contaminated sediments are impacting
 a significant part of our resources.  Through the ORD
 planning  process,  ORD has agreed to focus more re-
 sources on research related to contaminated sediments. In
 FY 1998 there may even be an increase of about $3 million
 of extramural money to support the laboratories in the
 ORD intramural research program. We need .to maintain
 this focus and increase our effectiveness through partner-
 ships with other interested EPA offices and federal agen-
 cies,  including Office of Water, the Superfund Program,
 the Great Lakes National Program Office, the Chesapeake
 Bay  Program,  the National Oceanic and Atmospheric
 Administration (NOAA), the U.S. Army Corps of Engi-
 neers, and the U.S. Geological Survey. We also need to be
 refining approaches that are implementable at the state
 level  and work with the states to achieve risk reduction.
 Today is a good time to rededicate ourselves to working
 as partners and to make the contaminated sediment issue
 the best example of how we can work together to solve the
 environmental problems.
      The ORD research program will continue support
 for pollution prevention efforts.  We will be addressing
 the issues remaining for sediment quality criteria, includ-
 ing data to support the guidelines and response to public
 comment on the technical basis for the criteria. Another
 area ORD will support is applying what we know about
 the sediment effects of chemicals to a cleanup strategy for
 a particular Superfund site.  There are some excellent
presentations coming up in this conference on how to
apply the concept of criteria to restoration.
      The management of risks associated with the dis-
posal  of dredged material will  require a strong  EPA

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Proceedings
collaboration with the U.S. Army Corps of Engineers arid
the States in order to develop a workable process. ORE)
will support that effort. We have identified research needs
such as tissue-based effects models to  understand the
bioavailability and pharmacokinetics  that explain why
residues bring about long-term damage to ecosystems.
Food chain models are becoming ever more sophisticated,
but they need further development. There is a critical need
to develop population level assessment methods to link up
the "So  what?"  questions  of the declining biological
diversity and loss of certain species. Assessment of the
impact of complex chemical mixtures will be necessary to
unravel the causative agents in the chemical mixtures that
are often found in sediments.
      Finally, I would like to emphasize the importance of
the development and application of remediation methods.
There has been much progress on remediation of contami-
nated sediments, with mitigation success at Superfund
sites. However, the mitigation options are still too limited
for larger areas.  In terms of communication challenges,
we need a breakthrough to instill hope in our political
leaders  that we can actually remediate contaminated
sediments. We have to overcome what seems to be an
overwhelming pessimism that we will ever reduce the
risks posed by sediments except by waiting decades. The
work that our Region 2 Office is doing on treating harbor
sediments in the New York area is resulting in some of the
most exciting new developments in the last five years.
They appear to be setting  the stage for the future in
sediment remediation.
      As we participate in this conference and prepare for
thenextdecadeofworktoreducethe impacts of sediments
in the environment, I encourage you to avoid letting our
energies become fragmented by using data to support a
personal or organizational interest. The danger I see in the
sediment literature is the number of papers designed to
support hypotheses rather than test hypotheses. There is
a need for debate in risk management, certainty among
uncertainties in our scientific understanding of sediment
interactions which merit debate, but the objective applica-
tion of the scientific method in gathering data to support
these debates is crucial.                   '   •

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                                         National Sediment Bioaccumulatton Conference
Session One:
Field  and Laboratory Methods  for
Measuring Bioaccumulation
Peter Chapman, Panel Moderator
EVS Environment Consultants, Ltd.,
North Vancouver, British Columbia

Henry Lee II
U.S. EPA, Office of Research and Development,
Newport, Oregon
Methods for Assessing Sediment Bioaccumulation
in Marine/Estuarine Benthic Organisms

Christopher G. Ingersoll
U.S. Geological Survey,
Columbia, Missouri
Methods for Assessing Bioaccumulation of
Sediment-Associated Contaminants with
Freshwater Invertebrates
                 >
Peter Landrum
NOAA, Great Lakes Environmental
Research Laboratory,
Ann Arbor, Michigan
Kinetic Models for Assessing Bioaccumulatipn
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                                                        National Sediment Bioaccumulation Conference
Methods for Assessing Sediment
Bioaccumulation  in Marine/Estuarine
                                                                          *
Benthic  Organisms
Henry. Lee II
U.S. Environmental Protection Agency, Office of Research and Development, Coastal Ecology
Branch, Western Ecology Division, Newport, Oregon
Introduction

        Organic pollutants can be divided into two
        general classes (see-page  1-15).  The first •
        consists of compounds with high water solubil-
ity and low Kow values, such as acetone, that do not tend
to adsorb to particulates. Their major reservoir is the
water column, where they are accumulated through
bioconcentration. The second suite of organic pollutants
are the low water solubility, high Kow compounds, such as
DDT, dieldrin, and polychlorinated biphenyls (PCBs),
that readily partition to particulates. They accumulate in
the sediment where  they can be bioaccumulated by
benthic organisms. From the benthos, these high Kow
compounds  can be introduced into higher trophic levels
through trophic transfer. Other presentations at this confer-
ence are addressing, the trophic transport and the effects of
these pollutants. This presentation will focus on methods
to, measure/predict the bioavailability of sediment-asso-
ciated contaminants to marine/estuarine benthos, and the
use of sediment bioaccumulation tests hi particular.
      When designing any test method, it is critical to
assess how are "the data are going to be used. Tissue
residue data can be used in risk assessments in a number
of ways, which are summarized in the figure on page
 1-16. "The column labeled "Steady-State?" refers to
whether, estimates of steady-state tissue residues are
required to  adequately address the particular component
of a risk assessment.  For the sediment bioaccumulation
tests, the need for steady-state data defines how long the
 test needs to be conducted to assure that steady-state
 tissue residues have been approached. The column la-
 beled "Max Residue?" refers to whether an upper limit
 estimate of the tissue residue is required to address the
 particular risk assessment component. That is, is it nec^
 essary to use a duration, species, or test method that tends
 to maximize uptake?
      As suggested in the figure on page 1-16, residues
• approaching steady-state are required for quantitative
 ecological or human  health risk assessments other than
 hazard identification and identifying specific  uptake
 routes. Tissue residues substantially less than steady-state
 residues will underestimate both exposure and effects,
 and this error will propagate through the risk assessment
 (e.g., estimate of trophic transport). The need for the
 more stringent requirement of an upper-limit estimate of
 tissue residue depends upon the specific question. For
 example, amphipods metabolize PAHs to a greater ex-
 tent than most bivalves. If the goal is to assess PAH
 exposure to amphipods, an amphipod would be a suitable
 test species. However, if the goal is to extrapolate PAH
 bioavailability to other species, an upper limit estimate
 would be more appropriate, and a bivalve species should
, be used.
 Bioaccumulation Methods

      There are a suite of methods available to assess or
 to predict bioaccumulation that will be discussed in
 various presentations during the conference (see listing
 on page 1-16). Two approaches provide direct measures
 of existing conditions: the field approach and the bioac-
 cumulation test. Both approaches  involve measuring
 tissue residues in  either field-collected or laboratory-
 exposed organisms. These direct approaches have high
 ecological relevance but can be costly, and they have
 limited ability to predict tissue residues resulting from
 changes in sediment contamination (e.g., after a clean-up).
      Sediment bioaccumulation models can serve as
 cost-effective "screens" to determine when direct mea-
 surements are required and as a method to predict tissue
 residues when direct measurements are not practical. The
 two general types  of sediment bioaccumulation models
 are equilibrium-based and kinetic  approaches (see
 Landrum et al., 1992). The equilibrium-based approaches
 assume steady-state, conditions between the organism
 and the environment, whereas, the kinetic approaches
 describe bioaccumulation as the net effect of rate processes.
 The two equilibrium models are bioaccumulation factors
 (BAF = tissue residue/sediment concentration) and the
 equilibrium partitioning model. The two basic types of
                                              1-11

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 1-12
                                                              National Sediment Bioaccumulation Conference
 kinetic approaches  are kinetic process  models and
 bioenergetically based toxicokinetic models. Kinetic mod-
 els can be more accurate than the steady-state models, but
 they require extensive data. A decision tree has been
 developed to guide the risk assessor in choosing which
 tests or models should be used to assess  or  predict
 bioaccumulation given the project goals (Boese and Lee,
 1992) (see figure on page 1-17).


 Equilibrium Partitioning
 Bioaccumulation Model

      The equilibrium partitioning model is based on the
 theory that neutral organic pollutants partition between
 the lipid phase in  the organism, sediment carbon, and
 interstitial  water  until equilibrium is obtained (see
 page 1-18). Assuming that organic carbon is the only sink
 for neutral organics in the sediment and that lipids are the
 only sink in the organism, the model becomes:

  '    Ctss/L = (Cs/TOC) * BSAF

      where:

      Ctss = tissue concentration at steady-state  (|ig/g)
      L = lipid content (g/g)
      Cs = sediment concentration ((ig/g)
      TOC = total  organic carbon in sediment (g/g)
      BSAF = biota-sediment accumulation  factor
      (g carbon/g lipid)

      The biota-sediment accumulation factor (BSAF)
 has also been referred to as the "accumulation factor"
 (AF). BSAFs can  be  determined empirically for each
 pollutant from laboratory exposures or field surveys. If
 partitioning  is not a function of lipid or carbon type, the
 value of the BSAF for a compound should not vary
 among sediments or  species.  However, data from
 bioaccumulation tests indicate that differences  in the
 sediment can affect the BSAF values. Tests were run
 with spiked  sediments using the deposit-feeding clam
 Macoma nasuta, one of the bioassay animals for marine
 and estuarine systems. Two sediment types were spiked
 with 13 PCB congeners and hexachlorobenzene (HCB)
 at concentrations of about 50 parts per billion for each
 congener or compound. Test results show differences in
 the BSAFs for the two sediment types (see page 1-18),
 so the equilibrium model did not completely account
 for sediment differences. The results also show dra-
 matic differences in BSAF values among congeners. A
 possible kinetic  explanation for these results are that
 PCB congeners with lower Kow values undergo rapid
 degradation  whereas  PCB  congeners with higher Kow
 values have  limitations moving across membrane sur-
 faces which can result in low uptake. Nor does the
 equilibrium  partitioning bioaccumulation model to-
 tally account for species differences. In a study of a
 DDT-contaminated site, we found that field-collected
Macoma nasuta had tissue residues of total-DDT and
dieldrin 7 to  9 times higher than filter-feeding bivalves
 (Lee et al., 1994, see Figure 15, page 1-22). It seems,
 then, that there is about a 2- to 10-fold uncertainty in
 BSAF values. Even with these uncertainties, BSAFs
 have utility as a screening tool and in extrapolating
 among species or sediments. Additionally, this uncer-
 tainty can be reduced by extrapolating among similar
 feeding and sediment types.
 Sediment Bioaccumulation test

      A laboratory test is often the preferred method to
 evaluate a specific sediment and to  generate BSAFs
 under controlled conditions. Although these tests had
 been conducted for over a decade, there was no stan-
 dardized methodology. Scientists at the U.S. Environ-
 mental Protection Agency (EPA) in Newport, Oregon
 developed a sediment bioaccumulation test for marine
 and estuarine systems, published it in a guidance manual
 in 1989, and revised it in 1993 (Lee et al., 1993, see
 page 1-19). Since then, the EPA scientists have worked
 with Peter Landrum of NOAA to develop a guide for
 sediment bioaccumulation tests for marine and fresh-
 water benthic invertebrates (ASTM, 1995). The
 bioaccumulation test includes six key procedures (see
 page 1-19):  (1) 28-day exposure duration, (2) use of
 sediment-ingesting organisms, (3) no supplemental food
 added, (4) independent exposure of species, (5) recom-
 mended accuracy of 80 percent of steady-state tissue
 residues, and (6) use of long-term tests or toxicokinetic
 approaches for greater than 80 percent accuracy or for
 slowly accumulated compounds. Information used to
 support the recommended procedures is discussed below.
      The recommendation for testing 28 days  was
 based on a literature review of percentage of steady-
 state residue levels achieved in 10 days (the period then
 used for testing dredged materials) and 28 days. Results
 were available  for a  variety of compounds such as
 PCBs, dioxins, furans, PAHs (orPNAs), and metals (see
 page  1-20).  These compounds generally achieved 80
 percent of steady-state tissue residues within 28 days.
 We evaluated the adequacy of the 28-day duration in the
 experiment exposing Macoma nasuta  to the sediments
 spiked with  13 PCBs and HCB  (see discussion under
 Equilibrium Partitioning Bioaccumulation Model). The
 experiment was run for 120 days. The figure on page
 1-20 shows the results for PCB congeners 153 and 209.
 Though bioaccumulated to different amounts, both PCB
 congeners approached or exceeded 80 percent of steady-
 state residue after 28 days, as did the  other congeners.
      Data from other studies indicate that a period of 28 days
 can be insufficient for bioaccumulation testing. The
 United Heckathorn Superfund site in San Francisco Bay is
 highly contaminated  with DDT and  dieldrin. A
bioaccumulation test was conducted with Macoma nasuta
 for 90 days using sediment from the most contaminated
 site. Test results for total DDT (DDT, DDE, and ODD)
 are displayed on page 1-21. At 28 days, the tissue residues
only reached about one-third of the steady-state residues.
The graphs of the tissue residues for the three most abundant
compounds show even worse results (see page 1-21).

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Proceedings
                                                                                                     1-13
These results raise the question of whether DDT and its
metabolites  are  different than PCBs or whether  the
difference is due to field versus spiked sediments. It also
raises the question about the adequacy of the 28rday test.
There are practical limitations to consider in setting the
length of any laboratory test. A proposal to resolve this
problem is to maintain 28 days as the standard duration,
but to multiply the 28-day residues .by an "adjustment
factor" which is the ratio of the steady-state residue to the
28-day residue. Adjustment factors would be developed
through long-term lab studies.  For the DDT compounds
and dieldrin, these adjustment factors ranged from 1.7 to
10.8, with a value of 2.9 for total DDT. For compounds
which  accumulate rapidly, such as  the low molecular
weight  polycyclic aromatic hydrocarbons (PAHs), the
adjustment factor should  approach 1.
     Several criteria  for organism selection for use in
marine/estuarine  bioaccumulation tests  are listed on
page 1-22. Of these, the requirement for using sediment-
ingesting organisms to maximize uptake of sediment-
associated contaminants is critical. The figure on page
1-15 (modified from Landrum, 1989) helps  illustrate
why. An organism can accumulate sediment-associated
contaminants from the interstitial water or from ingested
particles.  Compounds with higher .Kow values will be
associated mainly with the particulate phase, so particle  '
ingestion  will be the primary uptake route for these
chemicals; A series  of  experiments conducted with
hexachlorobenzene, a low solubility compound, showed
that at least 70 percent of the uptake in Macoma nasuta
was from ingested particles. Although it can be argued
that if all the phases are in equilibrium the uptake phase
does not matter, the 7- to 9-fold higher residues  in the
sediment-ingesting Macoma, nasuta compared to filter-
feeding bivalves at the United Heckathorn site (see page
1-22) clearly demonstrates the importance of sediment
ingestion on bioaccumulation. Based on similar reason-
ing, supplemental feeding is  not recommended as the
addition of uncontaminated food could "short-circuit"
the'solid-phase uptake route and result in an erroneously
low evaluation of bioavailability. The marine/estuarine
environment contains a number of deposit-feeding ani-
mals (various bivalves and polychaetes) that meet the
criteria, particularly with respect to providing sufficient
.biomass for chemical  analysis at the end of the test. The
1993 guidance manual and the ASTM guide .identify
animals suitable for bioaccumulation  testing, in marine
and estuarine  systems.
      With any laboratory test there is the  question of
whether it accurately predicts tissue residues in field organ-
isms. At the United Heckathorn Superfund study site,
we were able to compare tissue residues in laboratory-
exposed Macoma nasuta and Macoma collected at sev-
eral of the field sites. As mentioned above, the 28-day
exposure underestimated  steady-state of DDT and dield-
rin,  so it was necessary to use the adjustment factors from
the 90-day test at station 1 to correct the 28-day residues
from the other  five  sites. After adjustment, ratios of
laboratory to  field tissue residues  for total DDT and
dieldrin at each station (see graph on page 1-23) ranged
from about 0.5 to 3.  At least for this  suite of high Kow
neutral organics, the standard test appears to predict field
residues within 2- to 3-fold.
Research Needs

     Areas requiring further study  to  advance  the
science related to sediment bioaccumulation assessment
are  summarized  on page  1-23.  They include:
(1) interlaboratory round-robin testing; (2) field valida-
tion  of the bioaccumulation test,  particularly for PAHs
and metals; (3) identification of local test species, espe-
cially for subtropical, subarctic, and oligohaline habitats;
(4) "standardization" of lipid methods  for derivation of
BSAFs; (5) evaluation of effects of sediment storage and
spiking on bioavailability; (6) refinement of the experi-
mental design, including criteria for controls and refer-
ences;  and (7) evaluation of kinetic and physiological-
based alternatives to the 28-day bioaccumulation test. Of
these,  perhaps the most troubling question is whether
there is slower uptake or a lower bioavailability with
field-contaminated sediments compared to spiked sedi-
ments, as suggested by the slow  uptake rates for DDT
compared to the rates from the spiked  PCBs. Enhanced
bioavailability of spiked sediment could potentially result
in erroneously high BSAFs and toxicity.
     The above research needs address how to conduct
tests and their accuracy and precision. The overriding
question, however,  is: "What is  the ecological signifi-
cance of tissue residues?" This needs to be addressed at
several .scales. At the scale of individual benthos, the
question is, "What  are the effects of the accumulated
toxicants on  growth,  fecundity, and survival?" Use of
critical body residues, as are being developed for neutral
narcotics, is a promising  approach. However, in nearly
all cases, the goal  of marine/estuarine ecological risk
management is to protect a resource or higher levels of
biological organization (e.g., "ecological integrity"). To
achieve this goal, we will need to develop the insights and
methods to translate  toxic effects on individuals into
effects on populations and communities.  Addressing
these higher levels of biological organization will require
assessments at larger  spatial scales than the classical
"end-of-the-pipe" evaluations, and will  often require
evaluation of contaminated sediment effects in the con-
text of multiple stressors. This will be a critical challenge
for the future.
 References

 ASTM.  1995. Standard Guide for  Determination of
      the Bioaccumulation of Sediment-Associated
     .Contaminants  by  Benthic  Invertebrates.
      E  1688-95.
 Boese, B. and H. Lee II.  1992. Synthesis of Methods to
      Predict Bioaccumulation of Sediment Pollutants.
      ERLN  N232. U.S.  Environmental Protection
      Agency, Newport, OR. 87 pp.      .
 Landrum, P.  1989. Bioavailability and toxicokinetics
      pf polycyclic aromatic  hydrocarbons sorbed to

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1-14
        National Sediment Bioaccumulation Conference
     sediments for the amphipod Pontoporeia hoyi.
     Environ. Sci. Technol. 23:588-595.
Landrum, P., H.  Lee II, and  M. Lydy. 1992.
     Toxicokinetics in aquatic systems: Model
     comparisons  and  use in hazard assessment.
     Environ. Toxicol. Chem.  (Annual Review).
     11:1709-1725.
Lee II, H. et al. 1993. Guidance Manual: Bedded Sedi-
     ment Bioaccumulation Tests. EPA/600/R-93/183.
     U.S. Environmental Protection Agency, Office of
     Research and Development, Washington, D.C.
Lee II, H.,  et al. 1994. Ecological Risk Assessment
     of the Marine  Sediments  at the  United
     Heckathorn Superfund Site. ERLN N269. U.S.
     Environmental Protection Agency,  Newport,
     OR. 298 pp. + appendices.

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     BIOAVAILABILITY OF SEDIMENT-ASSOCIATED POLLUTANTS
                AQUEOUS AND PARTICULATE POOLS
       Ingestible Particles
          (HighTOC)
                         Non-ingestible Particles
                              (lowTOC)
     rapidly
    desorbed
      pool
 slowly
desorbed
  pool
 rapidly
desorbed
  pool
                          freely
                         dissolved
                           pool
                   DOM bound
                       pool
                         Organism
 slowly
desorbed
  pool
Idealized  Pollutant Pathways in Marine Ecosystems
                          Bioconcentration
          Water
    Dissolved
            Sorption
       Runoff
     Discharge
     Deposition
    Particulate
          Particles
          SEDIMENT
        "interstitial' Water"
    - = High water solubility, low Kow, rapidly metabolized
    - = Low water solubility, high Kow, slowly metabolized

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1-16
National Sediment Bioaccumulation Conference
                         USE OF TISSUE RESIDUE DATA IN
                               RISK ASSESSMENTS
I. HAZARD IDENTIFICATION
  •  Identify bioavailable compounds

  •  Quantitative measure of bioavailability

II. EXPOSURE ASSESSMENT
  •  Quantify exposure to assessment endpoint
     species.(e.g., edible clam)

  •  Test species is an indicator (measurement
     endpoint) for exposure to other species

  •  Test species is prey for higher trophic levels

DI. ECOLOGICAL EFFECTS ASSESSMENT
  •  Tissue residue effects on benthos

  •  Derive "Tissue Residue Criteria"

IV. HUMAN HEALTH EFFECTS ASSESSMENT

V. RESEARCH
  •  Evaluate Sediment Quality Criteria and
     bioaccumulation models

  •  Determine importance of uptake routes
Steady-
State?
No
No
Yes
Yes
Yes
Yes
Yes
Yes
Yes
No
"Max"
Residue?
. No
No
No
Yes
Yes
Yes/No
Yes
No
Yes
Yes/No .
                        PREDICTING BIOACCUMULATION OF
                  SEDIMENT POLLUTANTS BY BENTHIC ORGANISMS
  •  FIELD APPROACH

  •  BIOACCUMULATION TEST

  •  STEADY-STATE MODELS

     -   BIOACCUMULATION FACTORS (BAFs)

     -   EQUILIBRIUM PARTITIONING (BSAFs)

  •  KINETIC MODELS

     -   COMPARTMENT-BASED MODELS (1ST-ORDER KINETIC MODEL)

     -   PHYSIOLOGICAL- & ENERGETIC-BASED MODELS

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Proceedings
                                                           i-17
                 SUMMARY OF QUESTIONNAIRE CHOICES.  NUMBERS ABOVE
                     DECISION BOXES REFER TO QUESTIONNAIRE CHOICES.
       Use EqPB Model
       Section 4
       Use BAF Model
       Section 3
               Yes
       Are site-specific
       BAFs available?
                                             Predict or model
                                             tissue residues.
                    No
                                                    Yes
Use a standard model
to predict residues.
                                          3
                                     Yes
No
                                                    Yes
Model used as quick
screening tool for
bioaccumulation?
                                                    No'
                                        Model more than one uptake
                                        route (as opposed to
                                        modeling uptake only from
                                        bedded sediment)?
                        Yes
                                           Predict time to specific
                                           tissue residue value
                                           (time to steady-state
                                           or elimination time)?
                     Yes
         No
                                            Will organism grow
                                            substantially during
                                            test or modeling?
                    Yes
                                         Yes
                                            Is measured AF
                                            available for
                                            compound and sedi-
                                            ment of concern?
                                                    Yes
                                             Use EqPB Model
                                             Section 4
                I  Go to Next Page  j
                \  for Field or Lab  j
                j  questions (15).   j
Collect field samples
to derive regression
Section 11
                 Use bioenergetics-
                 based toxicokinetic
                 model. Section 5
                                                                                          Yes
                                      Changes in test organism
                                      behavior are likely due
                                      to changes in sediment
                                      characteristics.
                                                                                          No
                                                                                          Yes
                                                                                          No
                                   Accurate estimate not possible.
                                   Either make screening prediction
                                   (Box 4) or make site-specific  ,
                                   measurement (Box 15).

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1-18
National Sediment Bioaccumulation Conference
       EQUILIBRIUM PARTITIONING BIOACCUMULATION MODEL
            Sediment   \
                    Ctss/L = (Cs/TOC) *AF
                   AF = (Ctss / L) / (CS / TOC)
             Where:

               . Ctss = Tissue cone, at steady-state (ug/g)
                L = Lipid content (gig)
                TOC = Total organic carbon in sediment (gig)
                Cs = Sediment cone,  (ug/g)
                AF = Accumulation Factor (g carbon/g lipid)

      1) Tissue residues cannot exceed the concentration set by partitioning (AF < = 2)
      2) AFs do not vary among species, sediments, or compounds
                       PCB Congener AFs in
                     Fine and Bulk Sediments
11-,
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                            Log Kow
                                                     8

-------
Proceedings
                                1-19
                           United States
                           Environmental Protection .
                           Agency
Office of Research and
Development
Washington, DC'20460
EPA/600/R-93/183
September.! 993
                 5ER&    Guidance Manual

                           Bedded Sediment
                           Bioaccumulation Tests
                      SEDIMENT BIOACCUMULATION TEST
                              KEY PROCEDURES


 1.  28-DAY EXPOSURE DURATION.


 1.  SEDIMENT-INGESTING ORGANISM REQUIRED.


 3.  NO SUPPLEMENTAL FOOD USED.


 4.  SPECIES EXPOSED INDEPENDENTLY.


 5.  80% OF STEADY-STATE TISSUE RESIDUES RECOMMENDED ACCURACY.
 6.  LONG-TERM TESTS OR TOXICOKINETIC APPROACHES USED FOR >80% ACCURACY
    OR SLOWLY ACCUMULATED COMPOUNDS.            .

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1-20
                         National Sediment Bioaccumulation Conference
                       Percent of Steady-State
     100
         % of Steady-State
     80-


     60-


     40-


     20-


      0
'lit 5
            PCBs (N=26)   PCDD/PCDFs (N=4)   METALS (N=9)
                              Pollutant Type

                        I    | 10 Day       28 Day
                                     PNAs (N=14)
   UPTAKE OF PCB CONGENERS 153 VS 209 BY MACOMA NASUTA
         1200
         1000
       OQ
          800
       1  600

       o>
          400
          200
            0
                                        I PCB 153
                                        I PCB 209
             0    20   40   60   80   100  120  140
                      Exposure Length (Days)

-------
Proceedings
           1-21
     PPB
   100000


    80000


    60000


    40000


    20000

        0
                   SUM DDT UPTAKE
                 20       40       60
                     EXPOSURE TIME (DAYS)
80
100
                   TISSUE UPTAKE
                                              4,4 DDE

                                              2,4 ODD
             20     40      60      80
               EXPOSURE TIME (DAYS)
100

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1-22
                                National Sediment Bioaccumulation Conference
                         CRITERIA FOR ORGANISM SELECTION
1.  Sediment ingester
2.  Infaunal (preferably non-tubicolous)
3.  Hardy
4.  Easily collected or cultured
5.  Sufficient biomass for chemical analysis
6.  High bioaccumulation potential
7.  Feeding behavior understood
8.  Suitable for mechanistic/kinetic studies
                 BSAFs IN FIELD-COLLECTED MACOMA NASUTA VERSUS
                   FILTER-FEEDING BIVALVES IN RICHMOND HARBOR
ZDDT
DIELDRM
Macoma
  0.75
  1.13
Filter-Feeding
  Bivalves
    0.10
    0.13
Difference
  7.5X
  8.7X

-------
                                                            i-23
        LAB/FIELD TISSUE RESIDUE RATIOS
   LAB/FIELD RATIO
    3
   2.5
    2
   1.5
    1
   0,5
    0
DDT
Dieldrin
                         3.4
                          STATION
    8
                 SEDIMENT BIOACCUMULATION       '     %
                      RESEARCH NEEDS
INTERLABORATORY ROUND-ROBIN
FIELD VALIDATION (PAHs, METALS)      ,
LOCAL TEST SPECIES, ESP. FOR SUBTROPICAL, SUBARCTIC, AND
OLIGOHALINE HABITATS
"STANDARDIZATION" OF LIPID METHODS FOR BSAFs
EFFECTS OF SEDIMENT STORAGE AND SPIKING ON BIOAVAILABILTY ,
REFINEMENT OF EXPERIMENT DESIGN, INCLUDING CRITERIA FOR
CONTROLS AND REFERENCES
EVALUATION OF KINETIC & PHYSIOLOGICAL-BASED ALTERNATIVES TO
28-DAY TEST

               WHAT IS ECOLOGICAL SIGNIFICANCE?
PREDICT TISSUE RESIDUE EFFECTS
INTEGRATE TISSUE RESIDUE EFFECTS INTO ECOLOGICAL RISK
ASSESSMENTS
-  ECOLOGICALLY RELEVANT SPATIAL SCALES
-  MULTIPLE STRESSORS - MULTIPLE ENDPOINTS  ,
-  COMPARATIVE RISK TO OTHER TRADITIONAL & NON-TRADITIONAL
   STRESSORS                 ,

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                                                      National Sediment BioaocumufatJon Conference
Methods for Assessing
Bioaccumulation  of Sediment-
Associated Contaminants with
        t                    :     -         '             '
Freshwater Invertebrates
Christopher G. Ingersoll, Eric L. Brunson, and F. James Dwyer
U.S. Geological Survey, Columbia, Missouri
       Over the past 10 years, a variety of methods have
       been described for evaluating the toxicity of
       sediment-associated contaminants with freshwa-
ter invertebrates (i.e., USEPA, 1994; ASTM,  1997a).
Howevex, only a limited number of standard methods are
currently available for assessing bioaccumulation of con-
taminants from field-collected or laboratory-spiked sedi-
ments (see page 1-31). Standard guides have recently
been published for conducting 28-day bioaccumulation
tests with the oligochaete Lumbriculus variegatus includ-
ing determination of bioaccumulation kinetics for differ-.
ent compound classes (USEPA, 1994; ASTM,  1997b),
These methods have been applied to a variety of sediments
to address issues ranging from site assessments to
bioavailability of organic  and inorganic contaminants
using field-collected and laboratory-spiked samples
(Schuytemaet al., 1988; Nebeker et al., 1989;.Ankley et
al., 1991; Call etaL, 1991; Carlson et al., 1991; Ankleyet
al., 1993; Kukkonen and Landrum, 1994; Brunson et al.,.
1998; see ASTM, 1997b for a listing of these citations).
Results  of laboratory bioaccumulation studies  with
L. variegatus have been confirmed with comparisons to
residues (polychlorinated biphenyls,-PCBs; polycyclic
aromatic hydrocarbons, PAHs) present from field popula-
tions of oligochaetes collected from the same  sites as
sediments used in the laboratory exposures (Ankley et al.,
1992; Brunson etal., 1998). Additional method develop-
ment is under way to evaluate bioaccumulation  kinetics
and to provide additional data confirming responses ob-
served in laboratory sediment tests with benthic commu-
nities in the field.
Selection of test Organisms

     The choice of a test organism has a major influence
on the relevance, success, and interpretation of a test.
Various organisms have been suggested for use in studies
of chemical bioaccumulation from freshwater sediments
(Table 1). The following criteria outlined in Table 1 were
used to select L: variegatus for bioaccumulation method
development by USEPA  (1994) and ASTM  (1997b):
(1) ease of culture and handling, (2) known chemical
exposure history, (3) adequate tissue mass for chemical
analyses, (4)tolerancetoawiderangeofsedimentphysico-
chemical characteristics, (5) low sensitivity to contami-
nants associated with sediment, (6) amenability to long-
term exposures without,feeding, (7) ability to accurately
reflect concentrations of contaminants in field-exposed-
organisms  (i.e., exposure is realistic), and (8) data con-
firming  the response of laboratory test organisms with
natural  'benthic populations.  Thus far, extensive
interlaboratory  testing has not been conducted with
L. variegatus. Other organisms did not meet many of the
selection criteria outlined in Table 1, including mollusks
(valve closure), midges (short life cycle), mayflies (diffi-
cult to culture), amphipods (i.e., Hyalella azteca: small
tissue mass, too sensitive), cladocerans and  fish (not in
contact with sediment).
Testing Procedures for Lumbriculus
variegatus

     The 28-day bioaccumulation test with L. variegatus
described in USEPA (1994) and ASTM (1997b).is conducted
with adult oligochaetes at 23°C with a 16L:8D photoperiod
at an illuminance of about 500 to 1000 lux. Test chamber
size ranges from 4 to 6 L, and the chamber contains 1 to
2 L of sediment and 1 to 4 L of overlying water with five
replicates recommended for routine testing. To minimize
depletion of sediment contaminants, a ratio of 50:1 total
organic carbon in sediment to dry weight of organisms is
recommended. A minimum of 1 g(wetweight)/replicate,
with up to 5 g/replicate should be tested. Organisms are
not fed during a bioaccumulation test (see page 1-36).
                                            1-25

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1-26
                                                               National Sediment Bioaccumulation Conference
Table 1.  Selection criteria for sediment bioaccumulation  test organisms (EPA, 1994; ASTM, 1997b;
Ingersoll et al., 1995). A "+" or "-" rating indicates a positive or negative attribute; "NA" is not applicable;
and "?" is unknown.
Criterion


Laboratory culture

Known chemical exposure

Adequate tissue mass

Low sensitivity to
contaminants

Feeding not required
during testing

Realistic exposure

Sediment physico-
chemical tolerance

Response confirmed with
benthic populations
                       Lumbriculus    Mollusks   Midges    Mayflies
                        variegatus              .         •
Amphipods   Cladocerans   Fish
                                                                                       NA       NA
      If sediments could be toxic to L. variegatus, a 4-day
toxicity screening test should be conducted before starting
a bioaccumulation  test (ASTM, 1997b).  Endpoints
monitored in the toxicity test are  survival and behavior.
Test organisms should burrow into test sediment because
avoidance of test sediment by L. variegatus may reduce
bioaccumulation. Survival of L. variegatus in the toxicity
screening test should not be significantly reduced in the
test sediment relative to a control sediment.  Additional
requirements for test acceptability are outlined in USEPA
(1994) and ASTM (1997b).
      At the end of the bioaccumulation test, live oli-
gochaetes are  transferred to a 1-L beaker containing
overlying water without sediment for 24 hours to elimi-
nate gut contents (oligochaetes clear more than 90 percent
of the gut contents in 24 hours). A correction for the extent
of elimination from the body burden may need to be made
for compounds with log Kow less than 5. Oligochaetes are
not placed in clean  sediment to eliminate gut contents
because clean sediment can contribute 15 to 20 percent to
the dry weight of the oligochaetes, resulting in a dilution
of contaminant concentrations on a dry weight basis.
Minimum tissue mass required for various analyses at
selected lower limits of detection are listed in USEPA
(1994) and ASTM (1997b).  Depending on study objec-
tives, total lipids can be measured on a subsample of the
total tissue mass of each replicate sample. Dry weight of
oligochaetes can be determined on a separate subsample
from each replicate.
      Because  bioaccumulation tests are often used in
ecological or human health risk assessments, the proce-
dures are designed to generate estimates of steady-state
tissue residues.  Eighty percent of steady state is used as
the general goal for a test (ASTM, 1997b).  An option
when conducting a bioaccumulation test is to perform a
                                                      kinetic study to estimate steady-state concentrations in-
                                                      stead of conducting a 28-day bioaccumulation test (e.g.,
                                                      sample on Days 1,3,7,14,28). A kinetic test can be used
                                                      when  80  percent of steady state  will not be obtained
                                                      within 28 days or when more precise estimates of steady-
                                                      state tissue residues are required (see page 1-37).
                                                      Case Studies

                                                           Methods for conducting bioaccumulation tests with
                                                      L. variegatus have varied slightly over the years; how-
                                                      ever, test conditions (e.g., test length, exposure systems)
                                                      have been consistent enough for evaluation of the robust-
                                                      ness of the guidance outlined in USEPA (1994) and
                                                      ASTM (1997b). In a study with sediments from the lower
                                                      Fox River in Green Bay, Wisconsin, Ankley et al. (1992)
                                                      compared   the bioaccumulation  of  PCBs  by
                                                      L. variegatus exposed in the laboratory to PCB residues
                                                      in collections of oligochaetes from  the field.  Good
                                                      agreement was observed between PCB concentrations in
                                                      the laboratory and field organisms, particularly for those
                                                      congeners  with Kow values <7 (see  Figure 1).  This
                                                      indicates that for super-hydrophobic chemicals, labora-
                                                      tory exposures longer than  28  days may be required to
                                                      reach equilibrium.
                                                           Good agreement  was  also  observed   in
                                                      bioaccumulation between L. variegatus exposed in the
                                                      laboratory for 28 days and field-collected oligochaetes
                                                      from sediments collected from the upper Mississippi
                                                      River (Brunson et al., 1998).  About 90 percent of the
                                                      corresponding  concentrations  of PAHs  were within a
                                                      factor of 3  between the laboratory-exposed and field-
                                                      collected oligochaetes (see Figure 1).  Concentrations
                                                      that  differed by more than  a factor of 3 included

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Proceedings
                                                                                                  1-27
 u>

 o
 DC
 m
 o
 UJ
 (0

                         Brunson et al. (1998)
Ankley et al. (1992)
       O
         •O
            00
                        o
          o
                o
                              I
                                       I
                                               I
                              3       4       5      6
                             FIELD-COLLECTED OLIGOCHAETES
                          8
Figure  1.  Biota-sediment accumulation factors (BSAFs) for labbratory-exposed
Lumbriculus variegatus and field-collected pligochaetes for PAHs (Brunson et al.,
1998) and PCB homologs (Ankley et al., 1992).
naphthalene, l-methylnaphthalene, 2-methylnaphthalene,
2,6-dimethylnaphthalene, 1,6,7-trimethylnaphthalene,
phenanthrene,  1-methylphenanthrene, and  benz(a)an-
thracene. Tissue concentrations of naphthalenes were gen-'
erally higher in field-collected oligochaetes relative to
laboratory-exposed oligochaetes (naphthalenes are low
molecular weight (LMW) PAHs with log Kow values less
than 4.5).  Compounds with similar concentrations in.
both the laboratory-exposed and field-collected oligo-
chaetes  included a similar number of high molecular
weight (HMW) and LMW PAHs.  These compounds
included biphenyl, fluorene, 1-methylphenanthrene,
pyrene, fluoranthene, chrysene, andbenzo(e)pyrene. Most
of these compounds are intermediate in molecular weight
and log Kow (except for benzo(e)pyrene,  which has the
highest molecular weight and log Kow compared to these
other compounds).  Compounds with concentrations
typically higher in the laboratory-exposed oligochaetes
compared to field-collected oligochaetes were primarily
HMW PAHs. These compounds included phenanthrene,
benz(a)anthracene, benzo(b,k)fluoranthene, andperylene
(with log Kow greater than 4.5).
     Differences between tissue concentrations in the
laboratory-exposed and field-collected oligochaetes may
be the result of differential exposure, including the fol-.
lowing factors: (1) LMW PAHs imay be lost during the
sampling of sediments from the field; (2)  spatial hetero-
geneity of contaminants in the field may have resulted in
differential  accumulation; (3) the route of exposure for
oligochaetes in the field is through sediment, food, and
overlying water, while the primary route of exposure to
oligochaetes  in  the laboratory is sediment;  and
(4) species^specific
differences in expo-
sure exist between L.
variegatus and the
native oligochaetes.
      Concentra-
tions    of   DDT
reached  90 percent
of  steady  state by
Day 14 of a 56-day
test with L. varie-
•gatus exposed  to
field-collected  sedi-
ments (unpublished
data).   However,
LMW PAHs (i.e.,
acenaphthylene,
fluorene,  phenan-
threne)  generally
peaked by Day 3 and
tended'  to  decline
to Day 56. Concen-
trations  of  HMW
PAHs (i.e., benzo
(b)fluoranthene,
benzo(e)pyrene,
indeno ( 1,2,3-
c,d)pyren'e)   typi-
cally either peaked
        by Day 28 or continued to increase during the 56-day
        exposure.  Bioaccumulation of contaminants by indig- •
        enous oligochaetes that were recovered on Day 28 from
        the same chamber with introduced L. variegatus were
        also evaluated. Peak concentrations of select PAHs and
        DDT were similar in the indigenous oligochaetes and in
        L. variegatus exposed in the same chamber (unpublished
        data).  Bioaccumulation  of metals from sediments has
        also been evaluated using L. variegatus. Ankley et al.
        (1991) reported elevated concentrations of Cd and Ni in
        worms after 10-day exposures to field-collected sedi-
        ments where the metal (Cd + Ni):acid-volatile sulfide
        ratio exceeded 1, but not in samples where the ratio was
        <1. Ankley et al. (1994) also found that worms did not
        bioaccumulate metals from three sediments containing
        elevated concentrations of Cd, Ni, Zn, Cu and Pb, when
        there was sufficient acid-volatile sulfide to complex
        metals.
        Biota-Sediment Accumulation Factors

             Biota-sediment accumulation factors (BSAFs) were
        calculated for L. variegatus by dividing the lipid-normal-
        ized tissue concentrations by the organic carbon-normal-
        ized sediment concentrations (Table 2; Brunson et al.,
        1998). Forlaboratory-exposedoligochaetes,meanBSAFs
        ranged from 1.1 for benz(a)anthracene to 5.3 for naphtha-
        lene. Forfield-collected oligochaetes, meanBSAFs ranged
        from 0.5 for benz(a)anthracene to'8.8 for naphthalene.
        For individual samples,  BSAFs for .naphthalene ranged
        from 1.6 to 10.1 in laboratory-exposed oligochaetes and

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1-28
                                                               National Sediment Bioaccumulation Conference
Table 2. Mean biota-sediment accumulation factors (range in parentheses) reported by Lee
(1992) and by Brunson et al. (1998). NR is not reported.
Compound

Naphthalene
2-methyl naphthalene
Pyrene
Fluoranthene
Chrysene
Benz(a)anthracene
Benzo(b,k)fluoranthene
Perylene
Lee (1992)

NR
NR
, 0.4(0.18-0.5)
NR
NR
0.4 (0.2-0.6)
0.4 (0.2-1.0)
NR
Brunson et al. (1998)
Lab-exposed oligochaetes
. 5.3 (1.6-10.1)
2.6 (0.9-5.1)
2.3 (0.8-3.9)
1.8(0.9-3.9)
1.5 (0.7-2.4)
1.1 (0.4-2.5)
NR
2.24 (0.5-4.7)
'Brunson el al.. (1998)
Field-collected oligochaetes
8.8 (2.5-26.6)
6.7 (2.2-12.2)
2.2 (0.7-5.6)
1.6 (0.6-4.9)
1.1 (0.3-2.0)
0.5 (0.4-0.7)
NR
1.02 (0.3-1.9)
2.5 to 26.6 in field-collected oligochaetes. The BSAFs for
pyrene, benz(a)anthracene, and benzo(b,k)fluoranthene
were typically greater that BSAFs reported for marine
organisms in Lee (1992) for these compounds (Table 2).
BSAFs were  also calculated using PCB homolog data
reported in Ankley et al. (1992) for laboratory-exposed
L. variegatus and field-collected oligochaetes (Figure 1).
BSAFs were  similar between  laboratory-exposed  and
field-collected oligochaetes in both Ankley et al. (1992)
and Brunson et al. (1998); however, BSAFs reported in
Brunson et al. (1998) were typically greater (0.5 to 8.8)
than  BSAFs from Ankley et al. (1992; 0.17 to 2.26;
Figure 1).
     A theoretical value of 1.7  for BSAFs  has been
estimated based on partitioning of nonionic organic com-
pounds between sediment carbon and tissue lipids (ASTM;
1997b). A BSAF of less than 1.7 indicates less partition-
ing into lipids than predicted, and a value greater than
1.7 indicates  more uptake  than can be explained by
partitioning theory alone (Lee, 1992). The majority of the
BSAFs in Figure 1 and Table 2 were within a. range of
about 0.5 to 2.6, suggesting the theoretical BSAF value of
1.7 could be used to predict these mean BSAFs with a fair
amount of certainty. However, meanBSAFs for naphtha-
lene (8.8) and 2-methyl naphthalene (6.7) in  the field-
collected oligochaetes were elevated relative to a theoreti-
cal BSAF of  1.7 (Table 2), with BSAFs for individual
samples as high  as 10.1 for laboratory-exposed oligo-
chaetes and 26.6 for field-collected oligochaetes.  The
higher BSAFs in  the field-collected oligochaetes may be
the result of (1) exposure to contaminants in the overlying
water;  (2) spatial differences in sediment contamination
(i.e., sediments were not sampled from a depth represen-
tative of the habitat of the oligochaetes); or (3) taxon-
specific differences in exposure.  BSAFs substantially
different from the theoretical value of 1.7 may also result
from the system not being at equilibrium (i.e., depletion or
release of contaminants in pore water).
     In summary, procedures, for evaluating  the
bioaccumulation  of contaminants associated with fresh-
water sediment using the oligochaete L.  variegatus have
been well described. Results of laboratory studies using
these  procedures  are  generally similar to  the
bioaccumulation of contaminants exhibited  by oligo-
chaetes in the field. Ongoing research includes further
evaluations of bioaccumulation kinetics and field valida-
tion of  laboratory bioaccumulation methods, use of
formulated sediments and sediment spiking,  and stan-
dardization of micro-lipid analytical methods.
References

Ankley G.T., G.L. Phipps, E.N. Leonard, D.A. Benoit,
     V.R.  Mattson,  P.A. Kosian,  A.M. Cotter,  J.R.
     Dierkes, D.J. Hansen, and  J.D. Mahony. 1991.
     Acid-volatile  sulfide as  a  factor  mediating
     cadmium and nickel bioavailability in contami-
     nated sediment. Environ. Toxicol. Chem. 10:1299-.
     1307.
Ankley, G.T., P.M. Cook, A.R. Carlson, D.J. Call, J.A.
     Swenson, H.F.  Corcoran, and R.A. Hoke. 1992.
     Bioaccumulation of PCBs from  sediments by
     oligochaetes and fishes: Comparison of laboratory
     and field studies. Can. J. Fish. Aquat. Sci. 49:2080-
     2085.
Ankley, G.T., E.N. Leonard, and V.R. Mattson. 1994.
     Prediction of bioaccumulation of metals from con-
     taminated sediments by the oligochaeteLwmfcn'cK/KS
     variegatus. Water Res. 28:1071-1076.
ASTM. 1997a. Standard test methods for measuring the
     toxicity of sediment-associated contaminants with
     freshwater  invertebrates.  E1706-95b. In ASTM
     annual book of standards, Vol. 11.05, American
     Society for Testing and Materials, Philadelphia,
     PA, pp. 1138-1220.
ASTM. 1997b. Standard guide for determination of bio-
     accumulation of sediment-associated contaminants
     by benthic invertebrates. E1688-97a. In ASTM an-
     nual book  of standards, Vol. 11.05, American
     Society for Testing and Materials, Philadelphia,
     PA, pp. 1072-1121.
Brunson, E.L., TJ. Canfield, F.J. Dwyer, N.E. Kemble,.
     and C.G. Ingersoll. 1998. An evaluation of bioac-
     cumulation with sediments from the upper Missis-
     sippi River using field-collected oligochaetes and

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                                                                                                1-29
     laboratory-exposed Lumbriculusvariegatus. Arch.
     Environ. Contam. Toxicol. In press.
Ingersoll, C.G., G.T. Ankley, D.A. Benoit, G.A. Burton,
     F.J. Dwyer, I.E. Greer, T.J. Norberg-King, and
     P.V. Winger. 1995. Toxicity and bioaccumulation
     of sediment-associated contaminants with fresh-
     • water invertebrates: A  review of. methods and
     applications. Environ. Toxicol.  Cheiri. 14:
     1885-1894.
Lee, H. EL  1992.  Models, muddles and mud.  In
     Sediment toxicity assessment, ed. G.A. Burton,
     Lewis  Publishers,  pp. 267-293.   Chelsea,
     Michigan.
USEPA. 1994. Methods for measuring the toxicity and
     bioaccumulationofsediment-associated contami-
     nants with freshwater invertebrates. EPA 600/R-
     94/024. U.S. Environmental Protection Agency,
     Duluth, MN.
USEPA/USDOI. 1997. An assessment of sediments from
     the upper Mississippi River. Final report.  EPA
     823-R-97-005.  U.S. Environmental Protection
     Agency, Office of Water, Washington, DC.

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1-30
National Sediment Bioaccumulation Conference
           Methods for Assessing
             Bioaccumulation of
     Sediment-Associated Contaminants
        with Freshwater Invertebrates

            USEPA National Sediment
           Bioaccumulation Conference
          Wednesday September 11,1996
           Hyatt Regency, Bethesda, MD

      Chris Ingersoll, Eric Brunson, Jim Dwyer
             U.S. Geological Survey
                 Columbia, MO
     Objectives:
      • Standard methods
      •Approaches
      • Laboratory exposures
       -Methods
       - Lab to Field comparisons
       -Kinetic studies
      • Differences among standard methods
      • Future directions

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                                         1-31
Standard sediment methods
^^^1- ' • " •-.. v
^M F^liwSer
^^^^| Estuarine & Marine
^^H Toxicity: Soil
^^^^| Bioaccumulation
H^^H Collection
^^H Manipulation
^^^| Guidance
^H A^Sce
ASTM
E1706
E1367,
E1611
El 676
E1688
E1391
E1391
E1525
E1525*
EPA
1994a
1994b
1986
1989,19943
1995,1996?
1995,1996?
1994a,b
1995
EC ^^^H
1996a,b JJ
1999972aa? ^H
1994a, 1999? ^^^1
— s~^^B
1995 l^^l
1996b. 1997b ^^^H
isolooo ^H
' -
- ' , . ' - - '
Approaches:
 • Laboratory-exposed organisms
 • Field-collected organisms
 • Bioaccumulation factors (BAF)
 • Equilibrium partitioning models (BSAF)
 • Kinetic models
 • Bioenergetic models

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1-32
                              National Sediment Bioaccumulation Conference
      Approaches (cont.)::
       • Bioaccumulation factor:

        BAF = [tissue]/[sediment]

       • Equilibrium partitioning models:

        Biota-sediment accumulation factor

        BSAF =  [tissue/lipid]/[sediment/TOC]
              ~ 1.7 (4.0 USEPA-USCOE; 1991)
     Approaches (cont.):

      •Assumptions associated with BSAFs:
       -sediment only source
       -equilibrium & not kinetically limited
       - no metabolic degradation
            = lipid, TOC = TOC

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Proceedings
                                                                     1-33
            Selection criteria: Toxicity testing organisms
                        HA   DS   CT  CR  LV  TT  HS  MQ  GL
          Sensitivity
         Round robin
         Contact sed.
          Taxonomy
          Ecological
         Geographical
        Physico-chem.
        Field validation
          Peer review
           Endpoints
SGM  SBA  SGE   BS  BR  SR  | SG

                      Selection Criteria: Freshwater
                    bioaccurnulation testing organisms
                                 Mol   Mdg   May   Amp  Cla  Fish
            Tissue mass
             Sensitivity
              Feeding
          Realistic exposure
            Physico-chem.
           Field validation
                   LV: Lumbriculus variegatus, Mol: Mollusks, Mdg: Midges,
                      May: Mayflies, Amp: Amphipods, Cla: Cladocerans

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                                   National Sediment Bioaccumulation Conference
    Selection Criteria: Recommended freshwater
         bioaccumulation testing organisms
   Species
 Chironomus
    tentans
 Chironomus
   riparius
 Diporeia spp.
Hexagenia spp.
Hyalella azteca
 Lumbriculus
  variegatus*
 Earthworms
Feeding I Biomass I Sensitive I Culture I Data
  rr/   -    T-    -          -   TT   I  -t--t-
  SDF
  FF/
  SDF
 SSDF
 SSDF
 SSDF
  FF = fitter feeder; SDF = surface deposit feeder
  SSDF = subsurface deposit feeder; Adapted from ASTM E1688
Relative sensitivity: water 10-d LCSOs (ug/L
I'hemical
Copper
Zinc
Nickel
Cadmium
Lead
>,p'-DDT
>,p'-DDD
),p'-DDE
Dieldrin
lorpyrifos
Hyalella Chironomus
azteca tentans
35 54
73 1125
2.8 NT
780 NT
<16 NT
0.07 1.23
0.17 0.18
1.39 3.0
7.6 1.1
0.086 0.07
; ASTM E1 706)
Lumbriculus ^^H
••^•H











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Proceedings
                                               1-35
      Lumbriculus variegatus (oligochaeta):
      • Location: North America and Europe
      • Habitat: tunnels aerobic sediments
       lakes, rivers, ponds
      • Behavior:
       -buries anterior portion in sediment and
        undulates posterior end in overlying
        water for respiration
       -processes  >12 x weight/day
       Lumbriculus variegatus (cont.):
       •Adults:
        -40 to 90 mm length
        -1.0 to 1.5 mm diameter
        -5 to 12 mg wet weight
        -about 1%  lipid
       • Reproduction: asexual (i.e., architomy)
       • Culture:
        -adults of various size
        -population doubles in about 8 to 12
         days at 23C

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1-36
                                     National Sediment Btoaccumulation Conference
      Laboratory exposures:
       • Single sampling time:
         -steady state (i.e., Day 28?)
         - ANOVA and BSAFs
       • Kinetic study:
         -time course (i.e., Day 1, 3, 7,14, 28, 56)
         -regression models (i.e., Ks and Ka)
       • Depuration:
         -experimental (i.e., 24-h gut purge)
         -regression models (i.e., Ks and Ka)
      BIOACCUMULATION
Lumbriculus:
EPA & ASTM
 Macoma:
EPA & ASTM
 Polychaetes:
 EPA & ASTM
        Temperature (C)
        Luminance (lux)
          Photoperiod
          Chamber (L)
         Sediment (L)
           Water (L)
         Water renewal
            Age
           Loading
           Feeding
          Replicates
        Duration (days)
          Endpoints
         Acceptability
          16:8 to 12:12
                        10-25
            16:8 to 12:12
  adult
 >1 g/rep.
;  adult
1 g/50 g sed.
  juvenile
1 g/200 g sed.
                         No
28/kinetics
 T,A,B,R

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Proceedings
                                                          1-37
           Percent of steady state (ASTM E1688)
              Compound
Day  Day
 10   28
             Phenanthrene
            Benzo(a)pyrene     !
            Benzo(a)pyrene     '
            Benzo(a)pyrene     :
               Chrysene       '
          Hexachlorobenzene
          Hexachlorobiphenyl   88   100
             Aroclor1242      1!
              Total PCBs
               Cadmium       ',.  ,  .
Organism
            amphipod
             'mayfly
              clam
            amphipod
              clam
              clam
              mayfly
            polychaete
              clam
             shrjmp
         Percent loss during gut purging (ASTM E1688)
               Compound      24 h   72 h
                  PCB          :
            Hexachlorobenzene    <
              Benzo(a)pyrene
              Phenanthrene      ..   |
              Benzo(a)pyrene   14-26  43-99
              Phenanthrene
                 HCBP
77-100
14-26  43-99
              Organism
               shrimp
                clam
              amphipod
              amphipod
               mayfly
   mayfly
   mayfly

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1-38
                                National Sediment Bioaccumulation Conference
      Errors associated with gut purging:
      • Gut sediment error greatest:
       -selective ingest high TOC
       -large gut
       -early in exposure (low uptake)
       -cmpds. not bioaccumulated
      « Purging error greatest:
       -rapidly depurated/metabolized cmpds.
       -dilution by uncontammated sediment
     Performance-based criteria:
     • Survival (should; 4-d screening test for LV)
     •Avoidance (should)
     • Food (should; measure chemicals of concern)
     •Water quality (should)
     • Culture conditions (should)
     • Reference toxicants (must: monthly/start of test)
     • Physico-chemical characteristics (should)
     •Temperature (must; i.e., consistent life stage)
     •Storage sediment (2-8 weeks; no consensus)
     •Spiked sediment (1 month holding before testing)

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Proceedings -••--
                                                                1-39
              Mean BSAFs for PCBs (Lee 1992)
                        ORGANISM
                       Yoldia limatula
                       Nereis virens
                      Macoma nasuta
                       Yoldia limatula
                       Nereis virens
                      M acorn a nasuta
                       Nereis virens
                       Nereis virens
                      Macoma nasuta
                       Nereis virens
                      Macoma nasuta
                       Oligochaetes*
            BSAF
             10.6
             10.0
            0.8/0.9
                Mean BSAFs for other compounds
             COMPOUND
              Chlordane
          Hexaehlorobenzene
                 ODD
                 DDE
             2,3,7>TCDD
                Pyrene
         Ben zo (b, k)f iu pranthe he
              Chrysene      ;
           Benz(a)anthracene
            Benzo(a)pyrene  : ;
BSAF1  RANGE  BSAF2  RANGE
  4.7   4.0-5.9         '
  3.1  |  2.1-4.1 I        ,
  2.1    0.4-4.8         '
  1.3    0.7-2.8         '
  0.7    0.5-0.8         '
  0;4    0.2-0.5  1.1-2.3  0.7-5.6
  0,4/0.2-1.0  0.6-0.8  0.3-1.5
  0.4    0:2-0.6  i.0-1.4  0.3-2.4
  0,4    0.2-0.6  0.5-1.0  0.4-2.5
  0.2   0.05-0.9'
                 BSAF1 (Lee 1992) and BSAF2 (Bruhson et al. 1998)

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1-40
                                      National Sediment Bioaccumulation Conference
               Mean BSAFs for oligochaetes
         COMPOUND
     2-rnethyInaphthalene
       Benz(a)anthracene
    Benzo(b,k)fluoranthene
          Chirysene
         Fluoranthene
         Naphthalene
           Perylene
            Pyrene
LAB   RANGE   FIELD I  RANGE
       0.9-5.1
       0.4-2.5
2.2-12.2
 0.4-0.7
       0.6-1.5
       0.7-2.4
      0.85-3.9
      1.6-10.1
       0.5-4.7
 0.3-1.5
 0.3-2.0
0.6-4.9
2.5-26.6
 0.3-1.9
       0.8-3.9
0.7-5.6
                                        Brunson etal. 1998
       Frequency of Detected Concentrations:
      Tissue vs sediment (Brunson et aL, 1998)

   Lab-exposed Lumbriculus    Field-collected Oligochaetes
                H Detect in tissue, no detect in sediment
                • No detect in tissue, detect in sediment
                D Detect or no detect in tissue and sediment

-------
Proceedings
                                                                       1-41
                BSAFs for PCBs: Oligochaetes and fish
             2.5
          W

          (0
          o
          Q
          UJ
          CO
             1.5
          2   1
             0.5
                                              Lumbriculus
                                                  •

                                               Fatheads

                                                  o
Line of Unity
Line of unity ±40%-

Ankleyetal.(1992)
                     0.5     1     1.5    2     2.5

                     FIELD-COLLECTED OLIGOCHAETES
BSAFs for oligochaetes
.
1
o
DC
m
!4
Q
III
f3
I*
<
DC
O -•
<
_1
0

Brunson etal. (199,8) for PAHs Ankleyetal. (1992) for PCBs 0
, • o


i -

' • ' • ' *
- • • , - -
•
*
Q*
^ . , '
r "o o 
-------
1-42
                                                National Sediment Bioaccumulation Conference
             Mean PAH concentrations (ug/g lipid; Brunson et ai. 1998)
               0.1   0.2   0.5   1    2     5   10  20    50  100
                      FIELD-COLLECTED OLIGOCHAETES
10
9
8
Q 7
f-
A
2 4
3
2
1
2
3
A 5
3 6
111


10





























i
i
i
i

i





















































i

















i
















1 1
1





<


















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i



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i
i















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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
AAABABACCBBBCCCB
COMPOUND #




-------
Proceedings
                                                                                   1-43
                  Tissue Concentrations (ug/g of lipid)
                10

                 8
                          Pyrene
                      2   4   6   8  . 10
                         FIELD COLLECTED

                      —  Line of Unity
                            1-Methyl Phenanthrene
                         2.5
                       Q
                       111



                       | 1.5




                       •^ 0.5


                          0
                                                                    (5.7)
                           0   0.5  1  1.5   2  2.5
                                 HELD COLLECTED

                           	  Line of unity ± 40%
                     Other compounds displaying a similar pattern (i.e. field ~ lab):
                       Fluoranthene, Fluorene, Benzo(e)pyrene
                  Tissue Concentrations (ug/g of lipid)
                          Chrysene
                               Perylene
                                             200
                                             150
                                             100
                                           1C
                                           O
                                           CD
                                           3  50
12   3   4   5   6
  FIELD COLLECTED
                                                    50  100  150  200
                                                     HELD COLLECTED
                            Line of Unity    -----	  Line of unity ± 40%
                         Other compounds displaying a similar pattern (i.e. lab>fie!d):
                           Benzo(a)anthracene, Benzo(b,k)fluoranthene

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1-44
                                      National Sediment Bioaccumulation Conference
            Tissue Concentrations (ug/g of lipid)
              2-methyl Naphthalene
                                 30
  Naphthalene
                                 25
                                8
                                §20

                                §15
                                S
                                oc
                               -§1°
                                3
                                  5
              24  6  8  10  12
                FIELD COLLECTED
5 10  15 20 25  30
  FIELD COLLECTED
                   Line of Unity   	   Line of unity ± 40%
                Other compounds displaying a similar pattern (i.e. field>lab):
                  other Naphthalenes
       Differences among standard
       sediment methods:

        • Static vs. flow-through (fresh vs. marine)
        • Type & quantity of food (toxicity vs. bioaccum.)
        •Age (Hyalella and Chironomus: EC vs. EPA)
        • Duration & endpoints (Hyalella: EC vs EPA)
        • Sieving sediment (EC vs. EPA and ASTM)
        • Sediment storage (2 to >8 weeks; consensus?)

-------
Proceedings
                                                          t-45
           Future directions:
            • Spiking & formulated sediments
            • Quality assurance:
             - Lab certification (EC)
             -Reference toxicants
            • Standardization of micro-lip id methods
            • Kinetics and bioenergetics models
            • Field validation

-------

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                                                            National Sediment Bioaccumulation Conference
Kinetic Models for  Assessing
Bioaccumulation
 Peter Landrum                                   -
 National Oceanic and Atmospheric Administration^ Ann Arbor, Michigan
 WW'inetic models for exposure of aquatic organisms
 •fc- were developed for  water-only exposures to
 M^Ldeyelop a method for shorter-term studies to
 estimate steady state (Branson et al., 1975; Neely, 1979).
 The toxicokinetics were assumed to be driven primarily
 by the thermodynamic differences in the chemical
 activities in the storage compartment (organism) and the
 source compartment (water). The driving force for the
 ultimate  storage may be limited  through a number of
 kinetically limiting steps representing a number of
 potential mechanisms.  Some of these limits are external
 to the  organism, some are external but driven by the
 interaction of the organism with its environment, and
 some represent  internal physiological processes of
, the organism.
     What are some of these physiological and environ-
 mental limitations?  The rate of presentation of the
 contaminant to the uptake membrane may be limited by
 diffusion within the source compartment. The extreme
 example of a diffusion-restricted environment is
 sediment, where the diffusion path can be very tortuous.
 Such diffusion limitations can be reduced by organism
 behavior including increases in respiration, resulting in
 the active pumping of water across the gills and increased
 ingestion rates, which exposes the organism to a larger
 volume or mass of the source compartment and thus the
 contaminant. Environmental factors such as temperature
 may alter physiological processes and result in changes in
 physiological features  such as respiration and metabo-
 lism. These in turn may alter the volume of the source
 compartment encountered and the resultant exposure.
 The balance may result in greater or lower concentrations
 over time.  Limitations at the physiological level also
 include limitations of compound transport from the site of
 accumulation to the ultimate storage site within the organ-
 ism. Such processes can limit or enhance the transport
 from the site of uptake. If the transport from the site of
 uptake is limited, then the apparent difference in chemical
 activity forcing the transport into the organism may be
 reduced  and the rate process slowed.  Likewise,  if the
 internal  distribution is rapid, a large chemical activity  ,
 gradient can be maintained and the rate will be  rapid.
, Changes in the metabolic rate within the organism can
also  alter the rate of biotransformation, and thus
the ultimate rate and potential for the accumulation of the
parent compound. However, in these cases the flux into
the organism  remains high,  and if the metabolite is
the toxic form, its flux and accumulation will be
enhanced.
     Using the simplest model of accumulation and loss,
some of these various factors can be demonstrated, e.g.,
the effect of respiration rate'on the uptake process. As-
suming no biotransformation:
                     = Flux.m - Fluxmt
                At
     In this form, it is difficult to quantitate the changes
in concentration in the organism or predict them, but by
making additional restrictions, quantitation and predic-
tion become possible. The formalisms available for this
simple model can be represented in compartment, clearance
volume, or fugacity forms.  In this  simple model, the
various formalisms can be interconverted (Landrumetal.,
1992a).  However, each of the approaches has slightly
different assumptions to yield mathematically equivalent
results.
   :  In addition to compartment-based kinetic models,
both physiologically andbioenergetics-basedmodels have
been employed to describe the accumulation and distribu-
tion of contaminants in aquatic organisms (Landrum et al.,
1992a). For instance, a bioenergetics model for the clam,
Macoma nasuta, was  studied with the  contaminant
hexachlorobiphenyl(Boeseetal., 1990). In this case, the
routes and rates of accumulation and loss could be well
defined. The difficulty with these approaches is the need
for a large amount of data to parameterize the  model.
These models  are particularly useful for relating the
exposure of organisms to fundamental processes such as
respiration and feeding rates.                  ,
     In the compartment-based formalism and the ab-
sence of biotransformation:.

JFluxIn |

ED

JFluxOut|

                                               , 1-47

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1-48
         National Sediment Bioaccumulation Conference
                   dCa
                    dt
Where:
        ku = uptake clearance (ml g'1 br1)
        Cs = concentration in the source (ng ml'1)
        ke = elimination constant (bf1)
        Ca = concentration in the organism (mg g'1)

     In this form, some restrictions that are not usually
recognized come into play. First, the concentration in the
source is  the bioavailable concentration.  If the total
concentration is included  as the source concentration, it
will affect the estimate of k^.  This is useful for assessing
differences in bioavailability assuming that the conditions
of the experiment do not vary significantly. In water with
little complexing capacity, it is generally the concentra-
tion in the  water that is the source concentration.
However, there are examples where water concentrations
are modified by the presence of dissolved organic carbon
(DOC) (Landrum et al., 1992a). In sediment, the fraction
that is bioavailable is less clear and often the total sedi-
ment concentration or  a  concentration  on some
normalized basis, i.e., carbon, is employed. It is generally
understood that C5 is not limiting and that the system is
homogeneous. If this is not true, then the flux into the
organism will vary considerably over time.   Such
variation would  preclude  exact integration of the
differential equation and  make it necessary to perform
numerical integration, for which  substantially  more
information  is required.
     In the compartment formalism, ku is the clearance of
the source compartment  by  the organism, usually ex-
pressed on a weight-specific basis for the organism and a
volume- or mass-specific basis for the source compart-
ment. It is assumed to remain constant over the course of
a study or prediction.  Whether it actually remains con-.
slant over longer predictions or measurements is ques-
tionable. This term includes  the interaction between the
source compartment and  the organism and distribution
rates for both the internal and external distribution of the
compound.  Ku is also conditional based on factors that
affect the physiology of the organism, the chemistry of the
source compartment, and the interaction between these
two. Thus if k is to be used for comparison of differences
in bioavailabihty, as it often is in many sediment contami-
nant evaluations, the conditions of the experiment need to
be constant across a range of conditions, such as across a
range of sediments, so that the comparisons will be valid.
In addition, ke is also assumed to remain constant and is
subject to many of the physiological changes that occur in
the organisms.
     With aqueous exposures, there is an exact conver-
sion between the compartment model and both the clear-
ance volume model and a fugacity model.  There are,
however, some subtle  differences in assumptions and-
definitions in these models. For the fugacity model, the
system tracks the differences in chemical activity within
the system.  The  concentrations are given in terms of
moles  per volume,  and the relative capacities of the
systems for the compound are expressed in terms of both
partition coefficients and fugacity capacities. The model
could work as well in sediment exposures as in aqueous
exposures for it is really a compartment model in which
the terms are redefined.  In the case of the  clearance
volume model, there are some assumptions that are usu-
ally notreadily recognized. In the aqueous case, the fluxes
into and out of the organism  are assumed to primarily
occur across the same membrane or at least the membrane
resistance is assumed to be equal.  This leads to the
description of the steady-state condition as the  relative
capacity of the organism compared to the source compart-
ment.   For sediments, it would be necessary to add
additional routes of exposure to be accurate with this
model.  The  volume of distribution would reflect the
relative capacity of the aqueous phase of the  system.
Thus, it is not  as easy to directly apply the clearance
volume model to the sediment environment without modi-
fication of the mathematical formalism.
      The simple compartment model approach to
toxicokinetics in sediments has been employed to demon-
strate differences in bioavailability among  classes of
contaminants, sediments, the effects of concentration, and
the impact of normalization procedures. The toxicokinetics
approach has  shown that two major classes of contami-
nants, polychlorinated biphenyls (PCBs) and polycyclic
aromatic hydrocarbons (PAHs) seem to have differential
bioavailability when the log KOW values are essentially the
same  (Landrum and Faust, 1991). This also seems to be
the case for the relative bioavailability of other chlori-
nated hydrocarbons and PAHs as well (Harkey et al.,
1994).  This approach was also useful in attempting to
evaluate the relative importance of exposure to interstitial
water versus the exposure to whole sediment, suggesting
that multiple routes can be important (Harkey et al., 1994).
In this case, the relative ku normalized for the  organic
carbon content in the media was much greater for expo-
sure to whole sediment than for exposures to interstitial
water, suggesting that the exposure in sediment employed
additional sources (routes)  of exposures compared to
simple exposure to interstitial water. Exposures to  vary-
ing concentrations of sediment-associated contaminants
can cause accumulation of sufficient doses that the uptake
is affected. When Diporeia spp. were exposed to pyrene,
ku increased to a maximum and then tended to decline at
doses that produced mortality (Landrum et al., 1994).
Finally, the relative bioavailability among sediments of
individual contaminants has been estimated through ex-
posures under essentially identical conditions but with
differing amounts of DOC in water and among sediments.
In one study,  the variation in the bioavailability as  mea-
sured using uptake clearance demonstrated that for sedi-
ments collected in Lake Michigan normalization to or-
ganic carbon removed essentially all the variability
(Landrum and Faust, 1994). However, in the comparison
to materials from another source, in this case a soil from
Florissant, Missouri, the carbon normalization was not
adequate to describe the difference in bioavailability
and the differences increased  with log  Kow. Additional
work  has shown that the range of variability among

-------
Proceedings
                                                1-49
sediments  after carbon normalization  is somewhat
greater than a factor of 10 for  selected  organic
contaminants.
     . The compartment approach has dembnstrated some
limitations to our ability to understand and measure the
accumulation of contaminants from sediments. The first
appearance of complications  with  this approach was
demonstrated in the accumulation of a series of PAHs
from a single sediment. The shapes of the kinetics curves
varied, with log  Kow of the compound. It was originally
thought that this was an equilibrium problem between the
sediment particles and the interstitial water (Landrum,
1989) similar to the observed chemical equilibrium and
extraction problem with chemical analyses (Karickhoff,
1980). Experimental designs seemed to indicate that this
disequilibrium was avalidissue (Landrum, 1989; Landrum
et al., 1992b). However, exposures of organisms to field-
collected sediments also seemed to show some of the same
kinetic complications where organisms would in some
cases rapidly accumulate a compound only to lose con-
centration over  time.  Since the sediments were field-
collected, it was  thought that they were less out of equilib-
rium than those dosed in the laboratory. Experimentally,
it appears that the concentration of biologically available
material is  changing over time.  If the desorption of a
compound is inadequate to maintain the interstitial water
concentration from the surface easily desorbed concentra-
tion, then the bioavailable  component of the total con-
taminant load in the sediment will  decline because diffu-
sion within the sediment is limited. When the interstitial
water is a greater source than sediment ingestion, as is
probably the case early in the exposures, then the potential
for depletion of the bioavailable fraction would seem
more likely. This issue seems to be more problematic for
compounds with log Kow values less thap about 5. When
pyrene was studied with a laboratory-dosed sediment, the
shape of the kinetic curve appeared to be a classic first-
order curve with steady state.  However, when the elimi-
nation estimated from such a curve was compared to'
directly measured elimination  values, it appeared to be
inordinately fast. This suggests that the depletion process
is  important from these sediments (Landrum, 1989;
Landrum etal.,  1992b).  The issue becomes more pro-
nounced with phenanthrene, a compound with a smaller
log Kow value. Compounds  with larger log Kow values do
not generally show such depletion.  However, in some
work with oligpchaetes, which have a faster initial uptake
rate than Diporeia, an initial uptake with a subsequent
plateau or decline was evident. Overall, it would appear
that the rate of accumulation  from the aqueous phase
dictates some of this process and likely itis the relative rate
of uptake versus the rate of desorption that is important
since diffusion in sediment should be slow. In most of the
work that has been performed to date, it is not possible to
separate out the  mechanisms that may. be contributing to
such observed variation in the kinetics. Some of the data
that would be necessary to evaluate this include good
estimates of the  desorption rate constants from sediment
and estimates'of the feeding rate on sediment particles and
the associated assimilation efficiencies.
       Another feature of the kinetics with Lumbriculus
 •• variegatus that produced an apparent increase with a
  subsequent decline in contaminant concentration was
  found to result from loss of weight by  the organisms.
  Lumbriculus from the culture are healthy and fat. When
  exposed in sediments,  they  sometimes lose weight and
  lipids with subsequent losses of contaminant, while in one
  study, the kinetics on a lipid basis formed a standard first-
  . order uptake that approached steady state (Kukkonen and'
  Landrum, 1994). In addition to the impact on the weight,
  when Lumbriculus were exposed in different ratios rela-
  tive to the organic carbon content of the sediment, but at
  the same organic carbon-normalized concentrations, the
  kinetics changed, suggesting an interaction (Kukkonen
  and Landrum, 1994).  At least by performing a kinetic
  study, the relationship to steady state for these organisms
  can be observed instead of assumed and variations in the
-  conditions that impact the steady state determined.
       Because of the limitations—in particular, the poten-
  tial absence of homogeneity of sediment systems— mov-
  ing from a concentration-based to a mass balance-based
  model that incorporates more of the physical-chemical
  processes can help demonstrate which processes are im-
  portant in the accumulation process.  A mass balance'
  model was established to examine the accumulation of
  sediment-associated contaminants. The model attempted ••
  to parameterize the partitioning phenomena as well as the
  accumulation by several routes for Diporeia (Landrum
  and Robbins, 1990).  This first pass at a mass balance
  model did demonstrate the importance  of the role  of
  desorption of contaminants from  sediment,  perhaps
  coupled with diffusion limits:, on the accumulation pro-
  cess. Further, the desorption rate from particles seemed to
  be very slow compared to the uptake processes and may
  well  dictate  $ie bioavailability of sediment-associated
  contaminants along with the ingestion rate and .assimila-
  tion efficiency.  In the model as originally formulated,
  there was a general absence of data on desorption rates,
  assimilation efficiencies, and feeding rates.
       Today, the ability to estimate the assimilation effi-
  ciency for ingested sediment remains extremely difficult.
  The difficulties are essentially twofold. Fkst, it is nearly
  impossible to determine the concentration of contaminant
  in the ingested fraction of sediment for many inverte-
  brates. For oligochaete worms that are general feeders,
  e.g., they do not strongly select particles, estimating the
  ingested contaminant concentration is easier. The second
  issue is to estimate the fraction of material that is retained
  by the organism. This is generally performed using anon-
  assimiiated tracer. Polydimethylsiloxane and 51Cr have
  been used, but in both cases the tracers do not sorb to the
  same particles or in the same proportion as the contami-
  nants (Lydy andLandrum, 1993; Kukkonen andLandrum,
  1995). Another approach has been to estimate the relative
  loss of carbon and subsequently  estimate contaminant
  loss (Lee et al., 1990; Lydy and Landrum, 1993). How- ,  .
  ever, there are not even good assimilation values for the
  carbon from sediments, so this approach is limited. Over-  .
  all, development of good assimilation efficiencies is re-
  quired to improve the  estimation  of contaminant

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1-50
         National Sediment Bioaccumulation Conference
accumulation from sediments through kinetic models
except with compounds with large log Kow values, where
desorption and uptake from interstitial water is of lesser
importance.


Summary

     Kinetic studies can demonstrate factors that affect
the accumulation process and the relationship between
the length of exposure and steady state.
     Kinetic studies do not seem to be able to determine
steady-state potential hi all cases due to complications
with changes in bioavailability or  the length of  time
required  to achieve steady state, which is coupled to
changes hi physiology.
     Mass balance models  or models incorporating
more of  the processes suggest that the desorption rate
from sediment particles is an important kinetically limit-
ing process.
     Ingestion as the primary route of exposure com-
pared with interstitial water is a less dominant route for
chlorinated hydrocarbons compared to PAHs and a less
dominant route for more hydrophilic compounds.
     To improve kinetic models, data on ingestion rates,
assimilation efficiency, desorption rates, feeding selec-
tivity, and measure of contaminant concentrations on
ingested  particles need improved description and un-
proved chemical measurement techniques.  It will be
important to move from bulk sediment measures to  mea-
sures that reflect the exposure environment.


References

Boese, B.L., H. Lee, D.T. Specht, R.C. Randall, and M.
     Windsor. 1990. Comparison of aqueous and  solid
     phase uptake for hexachlorobenzene in the tellinid
     clam, Macoma nasuta (Conrad): A mass balance
     approach. Environ. Toxicol. Chem. 9:221-231.
Branson, D.R., G.E. Blau, H.C. Alexander, and W.B.
     Neely. 1975. Bioconcentration of 2,2',4,4'-
     tetrachlorobiphenyl hi rainbow trout as  measured
     by an accelerated test. Trans. Am. Fish. Soc. 4:785-
     792.
Harkey,  G.A.,  P.F. Landrum, and S.J. Klanie.  1994.
     Comparison of whole  sediment, elutriate, and
     porewater for use in assessing sediment-associated
     organic contaminants hi bioaccumulation assays.
     Environ. Toxicol. Chem. 13:1315-1329.
Karickhoff, S.W. 1980. Sorption kinetics of hydrophobic
     pollutants in natural sediments. In R.A. Baker, ed.,
     Contaminants and sediments, Vol. 2, Ann Arbor
     Science Publishers, Ann Arbor, MI, pp. 193-206.
Kukkonen, J., and P.F. Landrum. 1994. Toxicokinetics
     and toxicity of sediment-associated pyrene to
     Lumbriculus  variegatus (Oligochaeta). Environ.
     Toxicol. Chem. 13:1457-1468.
Kukkonen, J., and P.P. Landrum. 1995. Effects of sedi-
     ment-bound  polydimethylsiloxane on  the
     bioavailability and distribution of benzo(a)pyrene
     in lake sediment to Lumbriculus variegatus. Environ.
     Toxicol. Chem. 14:523-531.
Landrum, P.F. 1989. Bioavailability andtoxicokinetics of
     polycyclic aromatic hydrocarbons sorbed to sedi-
     ments for the amphipod Pontoporeia hoyi. Environ.
     Sci. Technol.  23:588-595.
Landrum, P.P., and J.A. Robbins. 1990. Bioavailability of
     sediment-associated contaminants to bentbic inver-
     tebrates. In R. Baudo, J.P. Giesy, and H. Muntau,
     eds., Sediments: Chemistry and toxicity ofin-place
     pollutants, Lewis Publishers, Boca Raton, FL, Chap-
     ter 8, pp. 237-263.
Landrum, P.P., and W.R. Faust. 1991. Effect of variation
     in sediment composition on the uptake rate coeffi-
     cient for selected PCB and PAH congeners by the
     amphipod, Diporeia spp. In M. A. Mayes and M.G.
     Barren, eds.,  Aquatic toxicology and risk assess-
     ment: Fourteenth volume, ASTM STP1124, Ameri-
     can Society for Testing and Materials, Philadelphia,
     PA, pp. 263-279.
Landrum,  P.P., and W.R. Faust.  1994.   The role of
     sediment composition on the bioavailability of labo-
     ratory-dosed sediment-associated organic contami-
     nants to the amphipod, Diporeia (spp.) with sedi-
     ment aging. Chem. Speat. Bioavail.  6:85-92.
Landrum, P.F.,  H. Lee II, and  M.J.  Lydy.  1992a.
     Toxicokinetics hi aquatic systems: Model compari-
     sons and use in hazard assessment. Environ. Toxicol.
     Chem. 11:1709-1725.
Landrum, P.P., W.R. Faust, and B.J. Eadie.. 1992b. Varia-
     tion in the bioavailability of polycyclic aromatic
     hydrocarbons to the amphipod Diporeia (spp.) with
     sediment aging. Environ. Toxicol. Chem. 11:1197-
     1208.
Landrum,  P.P., W.S. Dupuis, and J. Kukkonen.  1994.
     Toxicokinetics and toxicity of sediment-associated
     pyrene and phenanthrene  hi Diporeia (spp.): Ex-
     amination of equilibrium-partitioning theory  and
     residue-based effects for assessing hazard. Environ.
     Toxicol. Chem. 13(11):1769-1780.
Lee, H. II, B.L. Boese, R.C. Randall, and J. Pelletier. 1990.
     A method for determining gut uptake efficiencies of
     hydrophobic pollutants in a deposit-feeding clam.
     Environ. Toxicol. Chem. 9:215-219.
Lydy, M.J., and P.F. Landrum.  1993. Assimilation effi-
     ciency for sediment-sorbed benzo(a)pyrene by
     Diporeia spp. Aquat. Toxicol. 26:209-224.
Neely, W.B. 1979.  Estimating rate constants for uptake
     and  clearance of chemicals by fish. Environ. Sci.
     Technol. 13:1506-1510.

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                                                            National Sediment Bfoaocumufatfon Conference
  Day One:  September 11,  1996
 Session  One:
 Questions and  Answers
 A
fter each session, there was an opportunity for
questions and answers and group discussions per-
.taining to the speakers' presentations.
 Q(MauriceZeemon, U.S.EPA, Office of Pollution Preven-
, tion and Toxics): I heard Gil Veith talk this morning and
 I would like to comment briefly on a point he-made. At a
 gut level, I believe issues related to bioaccumulation and
 sediment assessment are important issues. I would like to
 seek reactions from this panel or others to the following
 comments. Most of us are scientists.  We deal with a
 Cartesian system where we have divided things up into
' little discrete parts, because they are too complex to try to
 handle as a group. The risk assessment paradigm is a
 perfect example. The key issue is how and when to start
 putting the parts back together to make some sense out of
 it.  Throughout the conference, I would like to ask that you
 focus again and again on what Gil Veith said in his
 presentation where he got that "So what?" reaction from
 a fairly knowledgeable group of people to the statement
 that 29 percent of the sediments in major estuaries were
 being impacted. As we go through our methods and our
 models for bioaccumulation and sediment assessment, try
 to  think about  what additional research will provide
 essential data to help the public, lawmakers, and regulatory
 agencies make sound decisions and take sensible actions.

 Betsy Southerland:

      We are looking for ecological significance.  What
 we are going to try to do, as we go through the next couple
 days of this conference, is look at the tissue residues from
 bioaccumulative pollutants and see what impact they have
 on aquatic life, what impact they have on wildlife consum-
 ers of that aquatic life, and their potential for human health
 impacts. We already have some field studies conducted
 by Rick Swartz that show a significant impact on popula-
 tions of other benthos if there is acute toxicity in the
 amphipod test species. That certainly gives us an indica-
 tion that at least the acute toxicity tests have ecological
 significance. What I want to. hear today, which was one of
 the prime drivers for organizing this conference, is what
 information is available on bioaccumulation tests and
tissue residue measurements to make equally important
interpretations of ecological significance. Interpretation
is the key. We can all do laboratory tests, but then we have'
to determine what the tests mean. Would anyone else care
to comment?

Peter Landrum:

     I will add a few comments. It has been my observa-
tion that whenever a particular group studies some aspect
of the lower end of the food web, there is generally less
interest in the work than if it involves fish or fish-
consuming wildlife and birds. There seems to be a general
lack of recognition of the supporting ecosystem required
to maintain the reproduction and the  productivity of the
higher levels of the food chain. I do not know if it is within
the purview of this group to be able to drive -that point
home. This point applies to studying  phytoplankton pro-
ductivity or contaminants at the lower end of the food
web. The issue remains that the connections between the
lower food web and the upper food web get lost, particularly
when you move into the regulatory realm of lawmakers
responsible for environmental legislation.

Q (Peter ^Chapman, EVS Environment Consultants): I
would like to address a question to any of the panel
members.  We have talked about bioaccumulation in
terms of relating it to toxicity effects we already  see
occurring. One of the attractions bioaccumulation has to
me  is the possibility of anticipating  things before they
occur.  At this point, do we have any examples where
bioaccumulation datd'have really enabled us to predict
impacts, and, if not, how much further do you think we
have to go before we can do that?

Henry Lee:

   . One example would be the work Rick Swartz did on
the sum PAH model. Since these are neutral narcotics, we
discussed bypassing sediment concentration and just going
directly to thetissue residues. Thatwouldelrminate the issue
ofbioavailability. I think that is possible, if we can get good
relationships between tissue residues  and some
                                                1-51

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 1-52
         National Sediment Bioaccumulation Conference
ecologically Significant effects. I would also like to add
to some of Peter Landrum's earlier comments.  Peter, I
think the onus is on us to show that these changes in the
benthos are important enough that they have affected
fisheries populations or wildlife.  The public is not
primarily interested in amphipods, oligochaetes, or clams,
but in fisheries and wildlife. If we cannot protect these
populations, then we have failed.

Q (Norm Rubinstein, U.S. EPA,  Office of Research and
Development): The session this morning really focused on
the issues of measuring bioaccumulation and predicting
bioavailability. I imagine as the meeting progresses, we
will get into the  other side of the issue, which is the
corresponding effects. But I am curious to see how you
gentlemen feel about  our current ability to predict
bioavailability and bioaccumulation, either thermody-
namically or kinetically. Do you have a sense of confidence
in our ability to identify bioavailable fractions and go on
from there to identify the corresponding ecological effects?

Peter Landrum:

      My feeling about that, Norm, is that if we are talking
about neutral organic compounds from sediments, we can
probably predict bioaccumulation within a factor of ten to
twenty, if that is adequate. I think trying to get any better
predictions than that right now is not possible because, as
I pointed out earlier, we do not have a complete under-
standing of how contaminants partition among sediment
size fractions and the degree of feeding selectivity by the
organisms. Without this information, we really do not
know how much contaminant an organism is exposed to.

Chris Ingersoll:

      We have been focusing quite a bit this morning on
the nonpolar organics, but what you have not seen today
is some of the work that has been done relative to metals
and acid volatile sulfides (AVS). Some of the metals are
able to be predictive of bioaccumulation that we are
seeing. A series of papers on AVS andmetalbioavailability
will be published hi the December 1996 Society of Envi-
ronmental Toxicology and Chemistry (SETAC) journal.
That issue will also include a good review article by Gary
Ankley and others for a variety of studies to address the
question of whether or not we can predict bioaccumulation
relative to AVS andSEM (simultaneously extractedmetal).
He found that the SEM/AVS approach offers a more
reliable and predictable tool than  what is currently
available.

Q (Steve Bay, Southern California Coastal Water Re-
search Project):  Peter Chapman listed coupling tissue
residues with toxicity responses as one of the key issues for
this session. But I was wondering about how the recom-
mendations to often use insensitive or hardy test animals
will impact this issue. Are we going to end up with a really
nice data set, but no ability to couple residue levels with
toxicity responses because we do not understand how to
predict the responses from uptake residues in insensitive
organisms? Are we in danger of that, or will we be able
to figure that out once we get a good data set together?

Peter Landrum:

     I think  we could be somewhat in danger because
these insensitive organisms are going to tell us that they
can accumulate more than some of the sensitive organ-
isms will. The sensitive animals will pass the toxicity
threshold and produce a response.  Insensitive organisms
should give you some idea of what the maximum amount
that could accumulate in an organism would be.  This
would allow you to at least define the level that you would
have to drive down to protect against responses in other
organisms.

Chris Ingersoll:

     We, as lexicologists, need to develop adequate
designs for studies  involving water or sediment to
measure toxic effects and bioaccumulation in the  same
exposures. I  am really looking forward to hearing from
some of the  panelists later  this  afternoon about their
databases. Some data are available, but you really have to
search  the literature to find those kinds of data sets.

Peter Chapman:

     I have found it useful in toxicity tests, where the
chemicals and organisms are appropriate, to measure
bioaccumulation and toxic effects. Among other things,
it can help me sort out what may be causing any effects I
see. We are trying to move in that direction, but it is a very
valid concern.

Q (Joe Greenblott,  U.S. EPA,  Office of Research and
Development): I would like to ask a question about how
models fit into the experimental work within the decision-
making and risk assessment framework.  What level of
attention is being given  to developing and researching
these models and developing  laboratory data to the
conservative level required for decision-making, in light
of the  variability in laboratory data  and the  large
uncertainty associated with the predictive models?

Henry Lee:

     I will give you a  different perspective. We are
working now to determine ecosystem responses and cu-
mulative effects, The variability is even greater for this
work than for the data you saw here. • I think you have to
go to a risk aversion philosophy or a more environmentally
protective approach. We cannot accurately predict a dose
response, a stressor response, but we know it is bad to lose
prey in a system or to lose a wetland. The direction we are
going to have to go is to  a risk aversion strategy. That is
where comparative risk factors in, so we can determine how
important one risk is versus another. Even if we cannot be
quantitative, we can at least rank the risks.

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 Proceedings
                                               1-53
 Q (Eric Rifkin, Rifkin & Associates):  A number of the
 panelists today  referenced BSAFs, biota-sediment
 accumulation factors, and how  they  varied based on
 whether or not you were using lipid-normalized organ-
 . isms and carbon-normalized sediment.  Could the panel-
 ists comment on whether BSAFs can be used in a generic
 context or whether they need to be used in a site-specific
 context?  I would also be interested in hearing how they
 can  be used in developing sediment quality  criteria
 in general.  -

 Henry Lee:

       It comes down to how well you  need to know
 the answer.  I agree with Peter that we can  predict
 bioaccumulation within an order of magnitude. If that is
 good enough for the neutral organics, then you are home
 free.   If you need  a better answer, then  you have
 a problem.  The better the answer you need, the more
 expensive and more site-specific  it  gets.   But  I
 am'  comfortable working within the  order of
 magnitude range.

 Q (Lynn McCarty, L.S. McCarty Scientific Research and
 Consulting): I would like ta raise a question related to an
 earlier question. The question is about sensitivity. I am
 always concerned that we do not really define what
 sensitivity is.  Are we referring to sensitivity  defined
 according to exposure-based tests or, since we have been
 discussing tissues  residues, are we referring to sensitivity
 on a residue basis or received dose effect? In fact, as I will
 show this afternoon, you can consider these things for the
 same set of data and come to quite different conclusions.
 Most of the differences in sensitivity that I have seen in the
 literature can  be  readily'* expected and predicted from
 differences in modifying factors such as  the size of the
 organism, the metabolic activity, and temperature. Until
 we clearly define what sensitivity means, we should not be
 making comparisons about which animals are more sen-
 sitive than others.  In sediment testing, as we have seen
 from some of the discussions this morning, the variability
 that results from the differences in media and conditions
 •of those  media dramatically affects the accumulation
 rates and amounts of accumulation. Therefore, sensitivity
 is  a confusing factor that needs  to be clearly identified
' before we make some final pronouncements about it.

 Peter Landrum:

      I think if you go back and look at the toxicological
 literature, sensitivity had to do with differences between
 species. Sensitivities were usually determined, at least in
 the mammalian literature, with a defined dose approach.
 A known dose of something was given to two different
 species by the same route. There is no doubt that the route
 of exposure is going to alter the response that you expect,
 particularly for sediment where there are a lot of con-
 founding  factors that can influence the dose received.
 You can take one animal and move it from sediment to
 sediment with the same compound and get a change in
 response,  because factors change that influence the
 bioavailability and, therefore, the received dose. If we are
 going to talk about sensitivity between  organisms,
 we  need to talk  about the  sensitivity based  on the
 received dose.

 Henry Lee:

      I would like to add a comment on sensitivity. When
 Chris arid I talk about sensitivity, we are referring to a
 value that is empirically derived. That was the basis for
 the sensitivity Chris snowed in his diagram during his
 talk.  In determining the sensitivity of potential test
 animals, we need to find animals that will survive for 28
 days or however long it takes to reach steady state.

 Q (Tom O'Connor, NOAA, National Ocean Service):
 Two of you have agreed with each other that the predic-
 tions based on equilibriumpartitioning are good to within
 one order of magnitude. How would you assess the
 imprecision of extending the equilibrium partitioning
 methodology to body burdens in fishes?

 Henry Lee:

      In general, the imprecision is greater.  We derived
 BSAFs for two fish that have limited home ranges in our
 DDT Superfund study.  These BSAFs turned out to be
 relatively close to the values we derived for Macoma and
 other benthic organisms. However, these values are more
 variable for fish like  flatfish  that have extensive home
 ranges. But I think we can at least determine a maximum
 value for demersal fishes.

 Q (Tom O'Connor): So the imprecision is in the range of
 the fish, not in the equilibrium between a given sediment
 and a fish?         .

 Peter Landrum:

   •-'   I think you have to consider the routes of exposure
 as well. If you have a pelagic fish and it is not feedi'ng on
 things that are well connected with the sediment, then it is
 inappropriate to try to make  a connection between the
 sediment and that fish. Whereas if you have an organism
 like a flatfish that is feeding on benthic organisms, it might
 be easier to make the connection. But you still  have
 additional routes  of exposure  that   you need
 to consider.                               •

 Q (Tom O'Connor): Yes, but equilibrium does not matter
for this.                                          .

 Peter Landrum:

      But that is assuming the process is passive. All the
 models I talked about imply a passive process. When we
 look at fish in particular, we may no longer be considering
 a passive process  as  the sole driving force. So, the
 thermodynamics that you are trying to consider in terms of

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1-54
                                                               National Sediment Bioaccumulation Conference
sediment to the fish are no longer applicable. If feeding
is taking place and the benthic organism is in equilibrium
with the sediment, we could make the assumption that
there is a connection between fish and sediment.  But if
feeding and digestion  are taking place, they are active
processes that may change the thermodynamics that apply
to a particular fish.
Q (Tom O'Connor): So, the answer to my original question
is that you cannot apply equilibrium at all to extrapolate
the fish.

Peter Landrum:

     Not unless they are eating the sediment.

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                                              National Sediment Bioaccumulation Conference
Session Twos
Interpretation and Applications  of
Bioaccumulation Results
Richard Pruell, Panel Moderator
U.S. EPA, Office of Research and Development,
Narragansett, Rhode Island

Norman I. Rubinstein
U.S. EPA, Office of Research and Development,
Narragansett, Rhode Island
Reference Sediment Approach for Determining
Sediment Contamination           "

David R. Mount
U.S. EPA, Mid-Continent Ecology Division,  .
Duluth, Minnesota
Development of Tissue Residue Threshold Values

L. Jay Field
NOAA, National Ocean Service,
Seattle, Washington
Use of Tissue Residue Data in Exposure and Effects
Assessments for Aquatic Organisms

Lynn S. McCarry
L.S. McCarty Scientific Research and Consulting,
Oakville, Ontario, Canada
Comments on the Significance and Use of Tissue
Residues in Sediment Toxicology and Risk Assessment

Burt K. Shephard
URSGreiner, Inc.,
Seattle, Washington
Quantification of Ecological Risks to Aquatic Biota
from Bioaccumulated Chemicals       . .
                                    2-1

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                                                          National Sediment Bioaccumulation Conference
 Reference  Sediment Approach for
 Determining  Sediment  Contamination
 Norman I. Rubinstein
 U.S. Environmental Protection Agency, Office of Research and Development
 Atlantic Ecology Division, Narragansett, Rhode Island
       One of the more contentious and highly publicized
       regulatory programs.capturing headlines today
       is the dredging and dredged material disposal
program, which is jointly administered by the US. Army
Corps of Engineers (USACE), the U.S. Environmental
Protection Agency (EPA) and, in inland waters, therespec-
,tive state and local authorities. Within this regulatory
program, one of the more controversial issues is the iden-
tification and use of reference sediments to facilitate the
permitting process for dredged material disposal.
     The application of a reference sediment approach to
identify sediment contamination in dredged materials was
developed more than twenty years ago for the ocean
dumping program. In this discussion, which reflects my
personal views and should not be construed as Agency
policy, I will review the statutory basis for the dredged
material program, the rationale used to develop this refer-
ence-based regulatory approach, and the operational defi-
nition of reference sediment as described in the current
testing manual. I will also identify how the reference
approach is applied today, how it can be improved, and
what future research is needed to support the program.


Program Statutes

     Section 103 of the Marine Protection, Research, and
Sanctuaries Act (MPRSA) stipulates that all operations
involving the  transportation and  dumping of dredged
material into ocean waters must be evaluated to determine
the potential environmental impacts of these activities. Simi-
lar legislation  in Section ,404 of the Glean Water Act
(CWA) addresses dredging and disposal operations in
inland waters.  There is a pending rule change that will
make program operations and use of reference sediments
consistent for both ocean and inland waters. This discus-
sion, however, will focus on the existing requirements in
the ocean dumping regulations.
The Green Book

     The testing manual for Section 103 of the MPRSA
is commonly referred to  as the Green Book(USEPA/
USAGE, 1991). It was first developed in 1977 and later
revised in  1991 by a joint USEPA/USACE technical
committee. The Green Book provides specific guidance
for conducting the evaluative protocols used to assess the
suitability of dredged materials for open water disposal. It
also defines testmaterials, reference sediments, and control
treatments, and specifies details on test methodologies
and provides guidance for the interpretation of data gen-
erated by these tests. Much of the remaining discussion
will be based on material from Ibis manual.
Reference Sediment Approach

     In 1976 the ocean disposal regulatory program
adopted the reference  sediment comparison approach
because at that time it was considered the most direct and
pragmatic way to satisfy the requirements of the MPRSA.
The statutory language of the MPRSA prohibits dumping
of dredged materials containing certain constituents  as
other than trace contaminants unless they are "rapidly
rendered harmless."  This regulatory language comes
directly from the London Convention which represents
international agreements  on ocean disposal activities.
The reference comparison approach provides a mecha-
nism that allows regulators to make decisions, that take
into account existing background or baseline conditions
in tile vicinity of the disposal site as defined by the specific
test endpoints selected. The rationale as originally ap-
plied viewed dredging and  disposal activities  not  as
remediation activities  aimed specifically at improving
existing condition, but as activities that at a minimum
must be conducted in a manner that would not further
degrade environmental conditions at the disposal site.
     Evaluation of benthic impacts for  the dredged ma-
terial program  employs  sediment toxicity tests and
bioaccumulation tests (Green Book). The benthic sediment
toxicity tests consist of 10-day whole sediment exposures
conducted  with appropriately sensitive species and fo-
cuses on mortality as  the test endpoint.  The standard
bioaccumulation test involves a 28-day exposure with
tissue residue contaminant levels in selected biota as the
test endpoint.
                                              2-3

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2-4
                                                                National Sediment Bioaccumulation Conference
     The reference sediment is the key to making regu-
latory decisions concerning dredged material disposal
(Figure  1).   Results from benthic  toxicity and
bioaccumulation tests using representative biota and ref-
erence sediments are compared to results from tests using
dredged sediments (test material).  These comparisons
serve as the basis for determining the potential for adverse
ecological impacts resulting from dredged material dis-
posal at the environs of the disposal site.
Initiating the Dredging Process

      The dredging process begins with identifying the
need for dredging a navigation channel.  The decision on
whether or not to dredge is based primarily on economic
and societal issues.  Navigation channels must be main-
tained to  support marine transportation, which  is the
primary mode for global tirade, currently estimated at
about three trillion dollars annually. The management of
dredged material, however, is an environmental issue that
is further defined by applying the federal standard which
stipulates  that disposal occur according to the  least cost
option that is en vironmentally appropriate. Once the need
to dredge is determined, a disposal site is identified
(USEPA,  1990).
      The next step in the process is to identify and collect
appropriate reference sediment. There are two approaches
for identifying the reference material. One approach is to
physically locate a reference site, define its location and
boundaries, and collect sediments from the site.  The other
approach, referred  to as the reference area approach,
involves collecting sediment samples using a grid overlay
which provides a composite of sediments representative
of the disposal site. The reference material represents the
existing benthic environmental conditions in the vicinity
of the disposal site. The reference material must satisfy
the definition in the Green Book, particularly with respect
to three critical requirements (Figure 2). Reference sedi-
ment should be:   (1) substantially free of contaminants;
(2) as similar as possible to the grain size of the sediment
in the dredged materials and at the disposal site; and
(3) reflective of conditions that would exist at the disposal
site if no dredged material disposal had taken place and
that represent all other influences on sediments in the area.
The test material  (dredged material) is then collected in
a manner representative of the sediments from the reach
and depth of the project area to be dredged.  Finally a
control  sediment is identified which is free  of contami-
nants and known to satisfy the physical requirements (i.e.
grain size) of the test organism. This material  serves as the
laboratory control treatment.
Program Testing

      As  stated above, testing consists of conducting
benthic toxicity and bioaccumulation tests on the refer-
ence material and the test dredged material with appropri-
ate laboratory controls and comparing the results of each
test. Interpretation of the benthic toxicity test data is fairly
straightforward.  Dredged material  is predicted to be
acutely toxic to benthic organisms when mean test organ-
ism mortality is statistically greater than the reference
sediment and exceeds mortality in the reference sediment
by at least 10 percent. Statistical differences between test
and reference treatments can be greater than 10 percent
depending on the inherent variability measured in specific
test species (e.g., a 20 percent value for mortality can be
used for amphipods).
     Interpretation of the benthic bioaccumulation test
results is more complicated.  Comparisons between the
test material and the reference treatments do not provide
pass/fail criteria, but rather serve as a screen for a more
comprehensive analysis. Results are compared initially to
determine whether there are statistically significant dif-
ferences in contaminant residue levels between the test
treatments and the reference treatment. This comparison
indicates that contaminants are present in greater than
trace quantities with the potential for bioaccumulation
and possible trophic transfer.  A more comprehensive
analysis involves comparisons of tissue residue levels to
FDA action levels and consideration of the lexicological
properties of the contaminants of concern.  If tissue
concentrations of one or more contaminants of concern
are statistically  greater than the FDA action levels, then
the test dredged material is predicted to result in benthic
bioaccumulation of contaminants. If tissue concentra-
tions are either statistically less than FDA action levels or
there are no FDA action levels for the contaminants of
concern, the information is considered insufficient .to
reach a conclusion about the potentialfor bioaccumulation.
In these cases further evaluation, including assessment of
additional  factors  such as  the magnitude  of
bioaccumulation relative  to biota indigenous to the ,dis-
posal site, may  be necessary to address the potential for
biomagnificationandtrophictransferandassociatedhealth
risks.
      The test endpoints (percent mortality and level of'
contaminant bioaccumulation), as measured in laboratory
tests with reference sediment, serve as de facto standards
in making regulatory decisions regarding the disposal of
dredged material. Obviously, the selection of appropriate
reference  sediment  is of paramount importance if the
goals of environmental protection are to be realized.
Reference Site Selection

      Current practice in selecting a reference site inevi-
tably requires some degree of compromise to meet the
somewhat ambiguous requirements of a reference mate-
rial  (i.e., "substantially free" of contaminants, yet "as
similar as possible" to the dredged material and disposal
site  sediments,-and reflective of conditions "had no dis-
posal occurred").  In some areas of the country, groups
responsible for dredging and dredged material manage-
ment are exploring ways to insure consistency and suit-
ability of reference materials selected for dredged material
evaluation. This is a function, in part, of the open process
employed by the  USAGE and USEPA to solicit and
promote involvement of the states, the local communities,

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Proceedings
                                                                                                    2-5
and stakeholders in establishing what they believe
represents environmentally appropriate and acceptable
reference material for their localities.
     A review of data generated by benthic toxicity and
bioaccumulation tests in reference sediments from major
dredging projects  in New York, Boston, San Francisco,
and Puget Sound (personal communication with regional
ocean disposal coordinators) indicate that the reference
sediments employed in  these areas reasonably reflect
baseline conditions characteristic of minimally impacted
environments  Amphipod survival in  the 10-day acute
toxicity tests averaged around 90 percent in the first three
areas (Figure 3).  Survival was slightly lower in Puget
Sound where a more regionally integrated approach is
applied. Tissue residue data from bioaccumulation tests
conducted on reference material in all four areas using the
polychaete Nereis yirens and the clamMacoma nasuta for
polychlorinated biphenyls (PCBs), cadmium, and mer-
cury are shown in Figure-4. PCB tissue concentrations
measured 20 to 30 ppb, and mercury and cadmium tissue
concentrations measured less than 0.05 ppm on a wet
weight basis.  These concentrations also approximate
current background  levels typically measured  in mini-
mally impacted aquatic systems (USEPA, 1997). These
data support the contention that selection of reference
sediments in these major U.S. ports  are serving their
intended purpose of providing appropriate levels of envi-
ronmental protection for the dredged  material disposal
program. However, given the subjectivity inherent in the
reference sediment selection process, I believe establish-
ment of national criteria for identification of appropriate
reference material would further promote greater consis-
tency in regulatory  decision making,  and perhaps en-
hance the margin  of environmental protection provided
by. the current regulatory protocol.


Future Needs   ,     •
                  ,  '                  ?
     Criteria which defrne the minimum requirements for
reference material selection that will maintain environ-
mental integrity and sustainability at the environs of the
disposal site should be developed as additional guidance
for the dredged material evaluation process. An example
 of where this is already happening is Puget Sound where
 regulators  have developed an extensive database that
 accurately represents background conditions. This data-
 base provides the basis for selecting reference materials
 andestablisbing statistically basedcriteriausedfor dredged
 material evaluation. Although development of such data-
 bases is expensive and time consuming, this approach
 could serve as a model for insuring appropriate reference
'standards are employed for dredged material evaluation.
      Additional research needs include improving our
 ability to predict community, population and ecosystem
 level impacts  from existing effects test endpoints (i.e.,
 acute toxicity), and development of tissue residue-effects
 linkages for contaminants of concern (Figure 5). What
 does a whole-body residue concentration mean in terms
 of the health of the organism, its ability to reproduce, and
 the propensity for a contaminant to biomagnify? Suffi-
 cient data to  answer these questions currently do not
 exist.  Predictive models that elucidate residue effects
 linkages along with the data to validate these modeling
 efforts should be developed.  Efforts to develop tissue
 residue databases must also continue to ensure effective
 interpretation of bioaccumulation data.
 References

 USEPA.  1990.  Site designation,  monitoring, and
      management guidance for ocean disposal of
      dredged material (working draft).  U.S. Environ-
      mental Protection Agency, Office of Water Regula-
      tions and Standards, Washington, DG.
 USEPA. 1997. The incidence and severity of sediment
      contamination in surface waters  of the United
      States, Volume 1: National sediment quality sur-
      vey. EPA 823-R-97-006. U.S. Environmental Pro-
      tection Agency, Office of Science and Technology,
      Washington, DC.
 USEPA/USACE. 1991. Evaluation of dredged material
      proposed for ocean  disposal—Testing  manual.
      EPA-503/8-91/001. U.S. Environmental Protection
      Agency, Office of Marine and Estuarine Protection,
      Washington, DC.

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2-6
                            National Sediment Bioaccumulation Conference
                   Figure 1.
     How is the reference sediment
   approach used to make decisions?
    Potential adverse impacts are determined
    on the basis of comparison of test endpoints
    (benthic toxicity and bioaccumulation)
    between test and reference treatments
                   Figure 2.
     Reference Sediment: Definition
    ^ Substantially free of contaminants

    • As similar as possible to the grain size of the
    dredged material and sediment at the disposal
    site

    > Reflects conditions at the disposal site that
    would exist had no dredged material disposal
    taken place; reflects all other influence on
    sediments in the area

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Proceedings
2-7
               Figure 3*
   Amphipod Survival in Reference
   Sediments from Major U.S. Ports
               Figure 4.
Bioaccumulation in Reference Sediment
        ;   (mg/kg wet wt.)
       0.05
                       PS

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                             National Sediment Bioaccumulation Conference
                    Figure 5.
            Reference Approach
         Suggested Improvements
    Establish minimum criteria for reference site
    selection that insures environmental integrity
    and sustainability are preserved (i.e., background
    database approach used in Puget Sound)

    Develop extrapolation models for single
    species toxicity endpoints that provide
    meaningful ecological interpretation at the
    community and population levels

    Elucidate residue-effects relationships to
    provide meaningful interpretation of
    bioaccumulation data.

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                                                            National Sediment Bioaccumulation Conference
Development  of Tissue  Residue
Threshold Values
Alfred W. Jarvinen, David R. Mount, and Gerald T. Ankley,
U.S. Environmental Protection Agency, Mid-Continent Ecology Division, Duluth, Minnesota
Background

       chemical residue-based, approach for evaluating
       dose, also called critical body residue (CBR) or
      Llethal body burden (LBB), has been advocated as
an improvement for prediction of toxicity to organisms in
the environment (Friant and Henry, 1985; McCarty, 1986;
Cook et al., 1987; Van Hoogen and Opperhuizen, 1988;
Cook et al., 1991; McCarty, 1991; McCarty et al., 1991;
Tas et al., 1991; Landrum etal., 1992; andMcCarty and
MacKay, 1993). The correlation of body residues to toxic
effects (residue-based dose) has a number of advantages
over using  an exposure-based 'approach (i.e., water or
food concentrations that cause toxic effects).  As outlined
by McCarty and MacKay (1993), these advantages include
the  following: (1) bioavailability is explicitly considered;
(2) accumulation kinetics are considered, which reduces the
confounding effect of exposure duration when interpreting
results; (3) uptake from food (as distinct from water) is
explicitly considered; (4) toxic potencies are expressed in
a less ambiguous manner, facilitating identification and
investigation of different modes of toxic action; (5) effects
of metabolism on accumulation are  considered; (6) mix-
ture toxicity can be more readily assessed; and (7) experi-
mental verification can be more readily determined be-
tween laboratory and field.
     Bioaccumulation testing is being used increasingly
in various environmental monitoring and regulatory pro-
grams  involving sediments,   m these tests, sediment
organisms are  exposed to sediment samples for  a pre-
scribed time period (e.g., 28 days). Following this uptake
period, exposed organisms are analyzed for chemicals of
interest. While these tests are one mechanism for assess-
ing  the bioavailability and accumulation of sediment
contaminants, they do not intrinsically predict the toxico-
logical effects  of bioaccumulative toxicants.  For this
prediction, some association between tissue residues and
lexicological effects must be developed. Thus, bioaccu-
mulation tests are a natural application  for residue-based
effects assessment.               •              .
      To help evaluate the basis for, and applicability of,
residue-based effects assessment, we have undertaken the
development of a comprehensive  database containing
                                                   literature data on tissue concentrations of toxicants and
                                                   associated biological effects for aquatic animals.  The
                                                   purpose of this presentation is to describe the database and
                                                   provide some examples of analyses that can be conducted
                                                   from these data.
                                                   Database Content and Development

                                                        Pertinent literature was identified through several
                                                   search mechanisms, including electronic databases (e.g.,
                                                   POLTOX I®; Cambridge Scientific Abstracts),' in-house
                                                   literature files, Current Contents®, and other assorted
                                                   sources.  For all literature, hard copies of the primary
                                                   literature were obtained and are maintained in the project
                                                   files.                            '       ..••'•
                                                        From this literature, residue/effect information was
                                                   manually extracted. General  inclusion criteria were:
                                                       •  Organism was a marine or freshwater fish, inver-
                                                          tebrate, or aquatic lifestage of amphibian (terres-
                                                          trial, animals, birds, and plants were not included);
                                                       •  There was a measured chemical concentration in
                                                          the whole body or in a specific tissue;  and
                                                       •  There was some observation of biological effect in
                                                          the form of survival, growth, or reproduction
                                                          (physiological and biochemical endpoints were
                                                        .  not considered).
                                                         In general, only data from exposures using a single
                                                   chemical were used; information from mixture studies
                                                   was not used unless the mixture contained only related
                                                   chemicals (same, mode of action).  Control  treatments
                                                   were required  as a basis for comparison of biological
                                                   effect, except in studies where survival was >90 percent
                                                   (thus-survival was not reduced). All chemical types (e.g.,
                                                   organic  and inorganic, ionic and  nonionic)  were
                                                   included.
                                                         For references meeting these  criteria, specific
                                                   information was extracted for inclusion in the database.
                                                   Database fields are as follows: ".       \
                                                        •  Study Type:, acute or chronic   ^
                                                       •  Chemical  Name:  exact chemical form (e.g.,
                                                          metal salt) is included parenthetically
                                                        •  CAS Number
                                                 2-9

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 2-10
                                                                National Sediment Bioaccumulation Conference
     * 1*8 K*.
     • Molecular Weight
     • Species
     • Life Stage: life stage exposed, or range if multiple
       life stages were exposed
     • Lab/Field: whether exposures were conducted in
       the laboratory or in the field
     • Test Conditions:   static, static-renewal, flow-
       through, microcosm, mesocosm, etc.
     • Exposure Route: water, sediment, diet, injection,
       maternal
     • Exposure Concentration:  measured if given,
       otherwise nominal
     • Test Duration: in days
     • Tissue Analyzed:  whole body, soft parts, blood,
       carcass, organ(s)
     • Tissue Residue: in ug/g wwt and umol/wwt
     • Biological Response:  survival, growth, or repro-
       duction; no effect observations included
     • Reference: literature source
     • Comments:  flags on unusual conditions (e.g.,
       control performance problems, discrepancies in
       the data, etc.)
      As of September 1996, the database contained resi-
 due data from more than 480 literature sources, spanning
 237 chemicals, and resulting in approximately 3,000 indi-
 vidual residue/effect pairs.  Chemicals with the greatest
 number of residue/effect pairs at this time are:
    • More than 400 residue/effect pairs
       cadmium
    • 100 to 250 residue/effect pairs
       DDT, TCDD,  hexachlorobenzene, mercury,
       PCB(s), selenium
    • 40 to 100 residue/effect pairs
       aminocarb, arsenic, copper, 2,4 dinitrophenol, en-
       dosulfan, endrin, fenvalerate, kepone, lead, Un-
       done, nickel, 4-nitrophenol, pentachlorophenol,
       terbufos, toxaphene, tributyltin, zinc
                these chemicals were for whole-body analyses, the expo-
                sure regimes varied widely with regard to species, lab
                versus field, and route of exposure, among other vari-
                ables.  Regardless of these differences, these values do
                suggest a range of chemical residues associated with
                biological effects, with the threshold for reported effects
                in the vicinity of 1 ug/g wwt for both chemicals.
                     Once data entry, accuracy checking, and initial
                analysis are complete, it  is our intention  to make this
                database available to the scientific community for further
                analysis.
                References

                Buckler, D.R., A. Witt, F.L. Mayer, and IN. Huckins.
                      1981.  Acute and chronic effects of Kepone and
                      Mirex on the fathead minnow.  Trans. Am. Fish.
                      Soc.  110:270-280.
                Cook, P.M., A.R. Carlson, and H. Lee.  1987.  Tissue
                      residue approach. Sediment classification methods
                      compendium, Chapter 7. EPA 823-R-92-006.
                Cook, P.M., M.K. Walker, D. W. Kuehl, and R.E. Peterson.
                      1991.  Bioaccumulation and  toxicity of 2,3,7,8-
                      tetrachlorodibenzo-p-dioxhiandrelated compounds
                      in  aquatic ecosystems.  In Banbury report 35:
                      Biological basis for risk assessment ofdioxins and
                      related compounds. Cold Spring Harbor Labora-
                      tory Press, Plainview, NY, pp. 143-167.
                Fisher, D.R., M.E. Bender, and M.H. Roberts.  1983.
                   •   Effects of ingestipn of Kepone-contaminated food
                      by juvenile blue  crabs.   Aquat.  Toxicol.
                      4:219-234.
                Fisher, D.R., J.R. Clark, M.H. Roberts, J.P. Connolly, and
                      L.H. Mueller. 1986. Bioaccumulation of Kepone by
                      spot: Importance of dietary accumulation and in-
                      gestionrate. Aquat. Toxicol.  9:161-178.
Example Data Sets

      Compilation and analysis of the
data are ongoing at this time. However,
as an example of data analyses than can
be performed using the database, we ex-
tracted data for chlorpyrifos (Jarvinen et
al., 1983; Macek et al., 1972; Serrano et
al., 1995; Hansen et al., 1986; Montanes
et al., 1995) and kepone (Buckler et al.,
1981;Hansenetal., 1977a, 1977b; Fisher
and  Clark, 1990; Sanders  et al., 1981;
Stehlik and Merriner, 1983; Fisher et al.,
1983; Fisher etal., 1986; Goodman etal.,
1982).
      Figures 1 and 2 display the resi-
due/effect pairs for chlorpyrifos and
kepone, segregated by biological  end-
point (survival,  growth,  or reproduc-
tion). Although all residues reported for
Chlorpyi
10,000
1,000
In
§» 100
to
| 10
1
1 1
o
0.1
0.01
-ifos Residues Versus Biological Responses
*
S3
* '
»
if ' •'
# m
m m • •
m , *
H
NO Effect/Effect No Effect/Effect No Effect/Effect






Survival Growth Reproduction
Figure 1. No effect (squares) and effect (diamonds) concentrations
for chlorpyrifos in tissues.

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Proceedings
Kepo
50
20
^ 10
ro 5
• 3^
S 2
o
a ,.
0.5
0.2
ne Residues Versus Biological Responses
" * ' ' '•'•".
" - « * '• •" *
• ' . ! *
* * H
s m ^
1 , » .
* "
No Effect/Effect No Effect/Effect No Effect/Effect
Survival Growth Reproduction



 Figure 2. No effect (squares) and effect (diamonds) concentrations
 for kepone in tissues.
 Fisher, D.R., and J.R. Clark.  1990. Bioaccumulation of
      Kepone by grass shrimp: Importance of dietary
      accumulation and food ration.  Aquat.  Toxicol.
      17:167-186.
 Friant, S.L., and L. Henry. 1985. Relationship between
      toxicity of certain organic compounds and their
      concentrations in tissues of aquatic organisms: A
      perspective. Chemosphere 14:1897-1907.
 Goodman, L.R., D.J.  Hansen, C.S. Manning,  and L.F.
      Faas. 1982. Effects of Kepone on the sheepshead
      minnow in an entire life-cycle toxicity test. Arch.
      Environ. Contain. Toxicol.  11:335-342.
 Hansen, D.J., L.R. Goodman, and AJ. Wilson. 1977a.
      Kepone: chronic effects on embryo, fry, juvenile,
      and adult sheepshead minnows.  Chesapeake Sci,
       18:227-232.
 .Hansen, D.J., D.R. Nimmo, S.C. Schimmel, G.E. Walsh,
       and A.J. Wilson.  1977b:  Effects of Kepone on
      estuarine organisms, pp. 20-29. In R.A. Tubb, ed.
      Recent advances in fish toxicology. EPA/600/3-77/
       085.   U.S. Environmental Protection Agency,
       Corvallis, OR.
 Hansen,  D.J., Goodman, L.R., G.M. Gripe,  and S.F.
    '   McCauley.   1986.  Early life-stage toxicity  test
       methods for gulf toadfish  and results  using
       chlorpyrifos. Ecotoxicol. Environ. Saf.  11:15-22.
 Jarvinen, A.W., B.R. Nordling, and M.E. Henry.  1983.
       Chronic toxicity of Dursban to the fathead minnow
       and the resultant acetylcholinesterase inhibition.
       Ecotoxicol. Environ. Saf. 7:423-434.
             Landrum, P.F., H. Lee, and M.J. Lydy.
                    1992. Toxicokinetics in aquatic
                    systems: Model comparisons and
                    use  in hazard  assessment.
                    Environ.   Toxicol.   Chem.
                    11:1709-1725.
             Macek, K.J., D.R. Walsh, J.W. Hogan,
                    and D.D. Holz. 1972.  Toxicity
                    of the insecticide Dursban to fish
                    and aquatic invertebrates in
                    ponds.  Trans. Am. Fish.  Soc.
                    101:420-427.
             McCarty, L.S. 1986.  The relationship
                    between  aquatic   toxicity
                    QSARs and bioconcentration
                    for some organic chemicals.
                    Environ.   Toxicol.   Chem.
                    , 5:1071-1080.
             McCarty, L.S.  1991.  Toxicant body
                    residues: Implications for aquatic
                    bioassays with  some organic
                    chemicals.   Aquat.  Toxicol.
                     14:183-192.
McCarty, L.S., D. Mackay, A.D. Smith, G.W. Ozburn,
     andD.G. Dixon.  1991. Interpreting aquatic toxic-
     ity QSARs: the significance of toxicant body resi-
     dues at the pharmacologic endpoint.  Sci. Total
     Environ. 109/110:515-525.
McCarty, L.S., and D. Mackay.  1993.  Enhancing
     ecotoxicological modeling and  assessment.
     Environ. Sci. Tech. 27:1719-1728.  .
Montanes, J.F.C., B. Van Hattum, and J. Deneer. 1995.
     Bioconcentration of chlorpyrifos by the freshwater
     isopod Asellus dquaticus .in outdoor experimental
     ditches.  Environ. Pollut.  88:137-146.
Sanders, H.O., J. Huckins, B.T. Johnson, and D. Skaar.
      1981.  Biological effects of Kepone and Mirex in
     freshwater invertebrates. Arch. Environ. Contam.
      Toxicol. 10:531-539.
Serrano, R., F. Hernandez, J.B. Pena, V. Dosda, and J.
      Canales. 1995.  Toxicity and bioconcentration of
      selected organophosphorus pesticides in Mytilus
      galloprovincialisand Venus gallina. Arch. Environ.
      Contam. Toxicol. 29:284-290.
Stehlik, L.L., and J.V.  Merriner. 1983. Effects of accu-
      mulated dietary Kepone on spot. Aquatic Toxicol.
      15:53-62.
Tas,J.W.,W.Seinen,andA.Opperhuizen. 1991. Lethal
      body burden of  triphenyltin chloride hi  fish: Pre-
      liminaryresults. Comp. Biochem. Physiol. 100C:59-
      60.
VanHoogen, G. and A. Opperhuizen. 1988. Toxicokinetics
      ofchlorobenzenesinfish. Environ. Toxicol. Chem.
      7:213-219.                 ;

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2-12
                              National Sediment Bioaccumulation Conference
            Development of Tissue
               Residue Threshold
                     Values

      Alfred W. Jarvinen, David R. Mount, and
                 Gerald T. Ankley

                      USEPA
         Office of Research and  Development
            Midcontinent Ecology Division
                    Duluth, MN
             Impetus for Research

         Need for interpretive guidance for
         bioaccumulation testing
         Desire for decision criteria that are based on
         biological effects

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Proceedings
                                                  Z-13
              Impetus for Research

          Proposal that risk assessment be based on
          tissue residues rather than concentrations in
          environmental matrices
          Assemble data necessary to evaluate a
          tissue residue approach
          Evaluate tissue residue approach relative to
          mode of action or other characteristics
       Tissue Residue/Toxicity Database

       •   Exhaustive search of literature for residue
           data linked to biological effect observations
       •   Selection criteria designed to maximize
           quality, comparability, and interpretability of
           resulting data

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2-14
                                National Sediment Bioaccumulation Conference
            Scope of Data Collection

          marine and freshwater, fish and invertebrates
          - does not include amphibians, terrestrial
            vertebrates or birds
          endpoints focused on survival, growth, and
          reproduction
          - histological/biochemical/physiological
            endpoints not included
          virtually all chemicals included, regardless of
          mode of action
                 Database Fields
        Acute/chronic
        Chemical name
        CAS number
        Log Kow
        Molecular weight
        Species
        Life stage
        Lab/field
Test conditions
Exposure route
Exposure concentration
Test duration
Tissue analyzed
Residue
Effect
Reference
Comments

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Proceedings
                                                  2-15
           Criteria for Data Inclusion

          Measured tissue residue (whole body or
          specific tissue)
          Effect data or statement concerning the
          health of the test organisms
          Mixture papers used only if no effect was
          observed
          Control not necessary if no mortality was
          observed
                Database Content

           Currently, the database contains
           approximately:
           -485 references
           -  200 chemicals
           -  2,552 residue/effect pairs

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2-16
                                    National Sediment Bioaccumulation Conference
                   Largest Datasets
    More than 400
    - cadmium
    100-250
    - DDT
    - TCDD
    - hexachlorobenzene
    - mercury
    - PCB(s)
    - selenium
• 40 to 100
  - aminocarb
  - arsenic
  - copper
  - 2,4 dinitrophenol
  - endosulfan
  - endrin
  - fenvalerate
  - kepone
  - lead
  - lindane
- nickel
- 4-nitrophenol
- pentachlorophenol
- terbofbs
-toxaphene
- tributyltin
- zinc
                     Kepone Data

       32 residue/effect pairs
       -  8 references
       -  6 species (3 fish, 3 invertebrate)
       -  lab exposures only
       -  water, diet, parental exposures
       -  exposures 4 to 141 days

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:edings
                                                                                                  2-17
Chldrpyrifos Data
Species (n)
Fathead minnow (6)
Bluegill (2)
Largemouth Bass (2)
Mussel (Mytilus) (2)
Mussel (Venus) (1)
Gulftoadfish(4)
Isopod (Asellus) (3)

Age
Larva
Juvenile
Juvenile
Adult
Adult
ELS
Adult

Days
Lab 200
Field 63
Field 63
Lab 4
Lab 4
Lab 49
Field 23

S/G/R
S,G,R
S
S
S
S
S,G
S,G

Source
Jarvinen etal. 1983
Macek etal. 1972
Macek etal. 1972
Serrano etal. 1995
Serrano etal. 1995
Hansenetal. 1986
Montanes & Hattum
1995
Chlorpyr
10,000
1,000
"§> 100
(0
1 10
I 1
0.1
0.01
ifos Residues Versus Biological Responses
V ; ' • '
m • ' [
S ' ' -
A ' • ' • ' ' .
f w
- ' • -
No Effect/Effect No Effect/Effect No Effect/Effect
Survival Growth Reproduction

;



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2-18
                                        National Sediment Bioaccumulation Confe
Kepc
50
20
-. 10
D) 5
3^
¥ 2
o
0.5
0.2
0.1
me Residues Versus Biological Responses

*
m *
i !
m
~ m
1
m
m
No Effect/Effect
Survival

« I m
m ^
m .
m
m
No Effect/Effect No Effect/Effect
Growth Reproduction




       u.
       <
       m
                 BAF versus Exposure Duration
                        Kepone (water exposures)
50,000
20,000
10,000
 5,000
 2,000
 1,000
             500
I
                0    20   40   60   80   100  120  140  .160
                         Exposure Duration (days)

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Proceedings
                                                              1-19
                BAF versus Exposure Duration
                     Chlorpyrifos (water exposures)
          10,000
   5,000 :
   2,000
it   1,000
m    500
     200
     100
      50
                 0
                                               I
                50   ,  100     150    200
                 Exposure Duration (days)
                                                      250
Paired Effect/No Effect Data
Chlorpyrifos

Survival
Gulf toadfish
Mussel (Mytilus)
Fathead minnow
Isopod (Asellus)
Bluegill
Largemouth Bass
Growth
Fathead minnow
'Gulf toadfish
Reproduction
Fathead minnow
Effe,ct

770
53
5.11
1 ;79
3.82
2.55

3.03
0,95

0.95
No Effect

175
4
3.03
0.97
0.42
0.4Z

0.95
0.14

0.47
Geo. Mean

367
14.6
3.93
1.32
1.27
1.09

1.70
0.36

0.67

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2-20
                                  National Sediment Bioaccumulation Conference
Paired Effect/No Effect Data
Kepone

Survival
Sheepshead minnow
Fathead minnow
Sheepshead minnow
Sheepshead minnow
Spot
Fathead minnow
Growth
Fathead minnow
Sheepshead minnow
Sheepshead minnow
Effect

11
3.8
2.3
2.5
2.7
1.7

3.8
2.2
0.41
No Effect

4.7
2.6
1.3
0.9
0.7
0.26

2.6
1.2
0.30
Geo. Mean

7.19
3.14
1.73
1.50
1.37
0.66

3.14
1.62
0.35
              Interpretation Issues

          Quantity and type of data varies greatly
          between chemicals
          Target tissue data not available consistently
          Relatively few data for individual PAH
          PCB mixtures vs. single congeners

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                                                          National Sediment Bioaccurnulation Conference
Use of Tissue  Residue  Data  in
Exposure  and Effects Assessments
for Aquatic  Organisms
L Jay Field
National Oceanic and Atmospheric Administration, Hazardous Materials Response arid.
Assessment Division, Coastal Resources Coordination Branch, Seattle, Washington
      Under the Comprehensive Environmental Response,
      Compensation, and Liability Act (CERCLA, or
      Superfund),meNationalOceanicandAtmospheric
Administration (NOAA) is responsible for protecting and
restoring natural resources that may be injured by releases
fromSuperfund sites in coastal areas. As part of NOAA's,
role of  providing EPA with technical  support  in the
evaluation of natural resource  concerns at hazardous
waste sites, NOAA's Coastal Resources Coordination
Branch often recommends collecting tissue residue data.
     Tissue residue data can play an important  role at
different stages in the process of evaluating hazardous
waste sites, including ecological  risk assessment, model-
ing conducted to evaluate different remedial alternatives,
and the monitoring necessary to  determine the effective-
ness of remediation.  An ecological risk assessment is a
major component of hazardous waste site evaluations..
For an ecological risk assessment to provide useful infor-
mation for remedy selection, exposure should be  related
both to the source of contamination and to an important
toxicity endpoint. This means that it is necessary to link
any estimated or observed adverse effects to site-related
contamination, which enjphasizes the importance of iden-
tifying and quantifying major exposure pathways. Be-
cause bioaccumulation  is often more of a concern for
higher-trophic level organisms, which may receive much
of their contaminant exposure via the food web, any effort
to develop bioaccumulation-based criteria should iden-
tify and address significant, sensitive toxicity endpoints in
 fish and other higher-trophic level  organisms. For ex-
 ample, reproductive or early life stage toxicity in fish is
 both a .sensitive toxicity endpoint and an endpoint with
 potentially significant implications for the health of a fish
 population.
      The appropriate application of tissue residue data
 depends upon the type of contaminant under consider-
 ation. For some contaminants, tissue residue concentrations
 may be directly linked to toxicity endpoints.  Also, the
concentrations of contaminants in the tissues of aquatic
organisms often provide a direct measure of bioavailability
that integrates exposure overtime and integrates exposure
from water, sediment, and food web pathways.  In this
presentation, I will be focusing primarily on the use of
field-collected tissue residue data in exposure and effects
assessments for aquatic ecological risk assessment. Be-
cause of the importance of bioaccumulation for higher-
trophic level organisms, I will focus my discussion on the
use of tissue residue data in assessing toxicity and expo-
sure in fish. Addressing these issues is particularly impor-
tant since currently available criteria for sediment explic-
itly exclude any consideration of contaminant exposure
through the food web. "These [sediment] criteria do not
address, the question of possible contamination of upper
trophic level organisms..." (USEPA, 1993a). And, "...a
site-specific investigation appears to be the only available
method for performing an evaluation of the effect'of
contaminated sediments on the body burdens of upper-
trophic level organisms" (USEPA, 1993b).
     Aquatic risk assessment requires information on the.
bioavailable fraction of the contaminants, in the system.
Accurate and meaningful  assessments of exposure from
water and sediment are difficult due to a potentially high
degree of temporal and/or spatial variability. Because of
high biocqncentration factors, particularly for hydropho-
bic organic contaminants, very low analytical detection
limits are required to ensure that concentrations below
analytical detection limit  values could not contribute to
significant exposure concentrations. Determining the
bioavailable contaminant fraction is also complicated by
partitioning suspended particulates and dissolved organic
carbon.   Modeling food web exposure in fish requires
making many assumptions for which there is frequently
little site-specific or reliable information available. Col-
lection of site-specific tissue residue concentrations can
be used to reduce some of this uncertainty in the applica-
tion of the exposure models used in the assessment. In
                                               2-21

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 2-22
                                                                National Sediment Bloaccumulation Conference
 many cases, tissue residue data can be used to provide
 time-integrated and location-specific information on bio-
 available contaminant concentrations.
 Metals

      The bioaccumulation of metals in benthic
 macroinvertebrates can provide a useful measure of the
 extent and magnitude of contamination that temporally
 integrates exposure via the water column and sediment.
 Because  benthic invertebrates  represent an important
 source of food for fish, the accumulation of metals in
 invertebrates, which may have some tolerance to chronic
 exposure to metals, may also serve as a significant source
 of exposure to fish. Exposure via the food web may be
 particularly important for fish early life stages, which are
 also very sensitive to waterborne exposure to metals.
      Thecombined effects ofreducedsurvival and growth
 in fish early life history stages, which may have important
 implications for adverse effects on the health of alocal fish
 population, is one of the most sensitive toxicity endpoints
 for waterborne exposure to a variety  of metals (such as
 cadmium, copper, lead, mercury, and zinc).  Laboratory
 studies on the effects of metals contamination on young of
 the year fish La the Clark Fork River in Montana demon-
 strated that feeding metals-contaminated invertebrates (at
 concentrations comparable to those found in the river)
 resulted in reduced growth and survival hi rainbow trout
 (Woodward et al., 1994) and reduced  growth and physi-
 ological abnormalities hi rainbow trout and brown trout
 (Woodwardetal., 1995).'These studies also Indicated that
 the exposure via dietary intake could be at least as impor-
 tant as aqueous exposure in age-0 fish.  Another study,
 however, found no effects on survival  or growth in age-0
 rainbow trout that were fed metals-contaminated brine
 shrimp at similar concentrations (Mount et al.,  1994).
 Additional studies are needed to more  clearly resolve the
 relative importance of additional dietary exposure and to
 develop a method for determining the total effective dose
 that includes all exposure pathways.
      In conducting arisk assessment for metals-contami-
 nated sites, tissue residue concentrations in invertebrate
 prey organisms may reduce the uncertainty in estimating
 exposure via the water column and sediment (by integrat-
 ing exposure over time at specific locations) as well as also
 providing information on exposure via the food web. This
 may be particularly important in assessments involving
 vulnerable receptor populations  (for example, the early
 life history stages of threatened and endangered salmonid
 populations).
Polycyclic Aromatic Hydrocarbons
(PAHs)

      Because fish rapidly metabolize and excrete PAHs,
fish tissue  residue concentrations of parent PAH
compounds do not provide a useful measure of exposure
to fish (Varanasi  et al., 1989).  However, exposure to
PAHs has been  linked to reproductive  impairment,
 immune dysfunction, increased incidence of liver lesions,
 and other histopathological endpoints hi fish (Malms et
 al., 1987; Johnson et al.,  1988; Varanasi et al.,  1992).
 High concentrations of PAHs in stomach contents offish
 from a PAH-contaminated harbor indicate that the con-
 sumption of contaminated benthic invertebrates can be an
 important exposure pathway (Malms et al., 1985).
      Measuring tissue  concentrations  hi invertebrates
 that have minimal capacity for metabolism of PAHs, such
 as bivalve shellfish, can provide location-specific and
 temporally integrated information on bioavailable PAH
 concentrations," which can be used hi food web models of
 exposure to fish and other higher trophic level organisms.
 Using tissue residue concentrations from caged bivalves
 allows  for more control of specific  location and other
 variables such as organism size or age. Other methods for
 determining the relative differences hi PAH exposure
 include measuring concentrations of PAH metabolites in
 fish bile (Krahn et al., 1984, 1986),  which can provide
 useful information on recent exposure to PAHs, and semi-
 permeable membrane devices (SPMDs), which provide
 temporally integrated measurements of dissolved and
 presumably bioavailable PAHs in the water column at
 specific locations (Lebpetal., 1992;HuckhisetaL, 1996).
 The patterns of PAH concentrations in field-collected or
 caged bivalves and SPMDs can also play an importantrole
 in linking exposure to the source of PAHs  using various
 fingerprinting methods.
 Poly chlorinated Biphenyls (PCBs)

      Fish tissue residue PCB  concentrations, unlike
 PAHs, can provide useful information on both exposure
 and toxicity. Reproductive and early life stage effects
 (e.g., reduced larval growth or survival), where the pri-
 mary exposure to the developing larvae results from the
 maternal transfer of accumulated PCBs to the eggs, is one
 of the most sensitive toxicity endpoints for PCB effects in
 fish.  Consequently, PCB concentrations hi the ovaries of
 mature female fish immediately prior to spawning may be
 the most  useful measurement for estimating potential
 reproductive effects in species of concern. Higher-trophic
 level  species, which tend to accumulate the highest con-
 centrations of PCBs, may be at the greatest risk.
      Field-collected  tissue residue PCB concentrations
 hi fish can play an integral role hi exposure assessments,
 since they provide a measure of exposure via all exposure
 pathways. This is particularly important since fish gener-
 ally receive much of their PCB exposure via the food web.
 The composition  of the PCBs found in environmental
 samples often differs substantially from the original PCB
 source (e.g., commercial Aroclor mixtures). This differ-
 ence results from physicochemical and biological pro-
 cesses that differentially affect individual PCB congeners
 (Safe et al.,  1987).  For example, the solubility and
volatility of individual PCB congeners range over several
orders of magnitude and greatly affect partitioning be-
tween sediment-water and water-air interfaces. Thus, less
chlorinated congeners tend to be more soluble in water
and are more quickly removed from sediment into water.

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Proceedings
                                                                                                    2-23
Biological processes  also alter the pattern of congener
distributions in tissue residue samples.  Differences in
uptake, depuration, metabolism, and efficiency of assimi-
lation among individual congeners may result in large
differences between the PCB mixtures in samples and in .
commercialAroclormixtures.andthesedifferenceswould •
be expected to increase with increasing trophic level.
     Because of the major differences between the PCB
congener distributions in environmental samples and in
commercial mixtures, analysis methods based on Aroclor
standards can provide only a semi-quantitative estimate of
total PCBs (Safe etal., 1987). Modeling PCB behavior in
the environment, monitoring trends in .PCB concentra-
tions, and relating fish tissue PCB residues to their sources
can be considerably enhanced by congener-specific analy-
sis. 'Samples  of several species of fish collected from
multiple locations over 170 miles of the Hudson River
were analyzed for PCB congeners as part of the ecological
risk assessment for a Superfund Remedial Investigation.
Samples of the same species at a given location had very
similar congener compositions, although their total PCB
concentrations sometimes varied by a factor of 2 or more
on either a wet weight or lipid-normalized basis, The PCB
congener compositions and concentrations in fish tissue
are being  used in the ecological risk assessment to help
clarify the relationship between the PCB sources in the
river and the fish body burdens.
     Two general screening approaches are available to
evaluate the potential toxicity of PCBs to fish based on
PCB body burdens:' comparison to total PCB concentra-
tions associated with adverse  effects, or estimation of
dioxin toxic equivalent concentrations and comparison to
No Observable Adverse Effect Levels (NOAELs) for
2,3,7,8-tetrachloro-dibenzo-p-dioxin (TCDD). A variety
of field and laboratory studies provide evidence of repro-
ductive and other adverse effects hi different fish species
at low total PCB tissue residue concentrations.  The total
PCB concentrations in fish tissue residue samples associ-
ated with adverse effects range over several orders of
magnitude, which may reflect the differences in toxicity
among  different PCB mixtures and/or a high degree of
inter-species difference in sensitivity  to the effects of
PCBs. The combination of these factors results in consid-
erable uncertainty in estimating the risk of reproductive
toxicity to selected fish species based on total PCB tissue
residue concentrations.
      The coplanar PCBs—a group of PCB congeners
that is similar in structure and biological "activity to the
highly toxic polychlorinated dioxins and dibenzofurans—
are considered to be the most toxic PCBs (Safe, 1984).
Although most of these coplanar PCBs are found at
relatively low concentrations  hi the commercial PCB
mixtures, several have been identified as important com-
ponents of PCB tissue residues in aquatic biota and may
be preferentially accumulated, particularly by highef-
\ trophic level organisms (Safe, 1984; Hansen, 1987; Smith
etal., 1990; Schwartz etal., 1993). Recentstudies suggest
that only the non-or tho substituted PCB congeners exhibit
dioxin-lifce activity in fish (Walker and Peterson, 1991;
Newsted et al.,, 1995; Zabel et al.~, 1995).  The early life
 stage toxicity of these individual PCB congeners has been
investigated in .trout and compared to  the toxicity of
dioxin to develop fish-specific toxic equivalent factors, or
TEFs (Walker and Peterson, 1991;  Zabel et al., 1995).
The TEFs for the non-ortho congeners calculated for trout
are 1 to 2 orders of magnitude less than the TEFs deter-
mined for mammalian systems. Thus, using mammalian-
based TEFs for PCBs may overestimate the potential for
dioxin-like reproductive toxicity in fish.
Conclusions

     Tissue residue data can play an important role in
aquatic ecological risk assessments at hazardous waste
sites, in part by linking exposure to the source of contami-
nation  and to important toxicity endpoints.
     The development of bioaccumulation-based criteria
should identify, .and address toxicity endpoints hi fish that are
both sensitive and ecologically significant This is particu-
larly important for higher-trophic level species, which may
receive much of their contaminant exposure via the food web.
     For some contaminants, such as PAHs and possibly
metals, dose-response models that include all exposure
pathways need to be developed. Tissue residue concentra-
tions in macroinvertebrates may provide key  input into
exposure models for these types of contaminants.
     Tissue  residue PCB concentrations in  fish have
important applications to both exposure and toxicity as-
sessments. Because  the PCB .congener distributions in
environmental samples often differ considerably from the
original  commercial PCB mixtures, congener-specific
PCB analysis of fish tissue samples provides more useful
information on exposure than a standard Aroclor analysis.
PCB concentrations in the ovaries of .mature female fish
immediately prior to spawning may be the most useful
measurement for estimating potential reproductive toxic-
ity in fish species of concern.
 References

 Hansen, L.G. : 1987.,  Food chain modification of the
      composition and toxicity of polychlorinated biphenyl
      (PCB) residues. Rev. Environ. Toxicol. 3: 149-212.
 Huckins, J.N., J.D. Petty, J.A. Lebo, C.E. Orazio, H.F.
      Prest, D.E. Tillitt,  G.S. Ellis, B.T. Johnson, and
      O.K. Manuweera.  1996.  Semipermeable  memr
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      assessment of bioavailable organic contaminants in
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      niques in aquatic toxicology,  CRC Press,  Boca
      Raton, FL, pp. 625-655.
 Johnson, L.L., E. Casillas, T.K. Collier, B.B. McCain, and
      U. Varanasi. 1988.  Contaminant effects on ovarian
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      the bile of fish from polluted waterways.  Xenobiotica
      14: 633-646.

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         National Sediment Bioaccumulation Conference
Krahn, MM., L.D. Rhodes, M.S. Myers, L.K. Moore,
     W.D. MacLeod, Jr., and D.C.Malins. 1986.  Asso-
     ciations betweenmetabolites of aromatic compounds
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Lebo, J.A., J.L. Zajicek, J.N. Huckins, J.D. Petty, andP.H.
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Malins, D.C., M.M. Krahn, M.S. Myers, L!D. Rhodes,
     D.W. Brown, C.A. Krone, B.B. McCain, and S.-L.
     Chan.  1985.  Toxic chemicals in sediments and
     biota from a creosote-polluted harbor:  Relation-
     ships with hepatic neoplasms and, other hepatic
     lesions in English sole. Carcinog. 10: 1463-1469.
Malins, D.C., B.B. McCain, M.S. Myers, D.W. Brown,
     M.M.  Krahn, W.T. Roubal, M.H  Schiewe, J.T.
     Landahl, and S.-L. Chan.  1987. Field and labora-
     tory studies of the etiology of liver neoplasms in
     marine fish from Puget Sound.  Environ. Health
     Perspectives 71: 5-16.
Mount, D.R., A.K. Earth, T.D. Garrison,  K. A. Barten, and
     J.R. Hockett. 1994. Dietary and waterborne expo-
     sure of rainbow trout  (Onchorynchus mykiss) to
     copper, cadmium, lead, and zinc using a live diet.
     Environ. Toxicol.  Chem. 13:2031-2041.
Newsted, J.L., J.P. Giesy, G.T. Ankley, D.E. Tillitt, R.A.
     Crawford,  J.W. Gooch,  P.D. Jones, and M.S.
     Denison. 1995. Development of toxic equivalency
     factors for PCB cogeners and the assessment of
     TCDD andPCB mixtures inrainbow trout. Environ.
     Toxicol. Chem. 14: 861-871
Safe, S.  1984.  Polychlorinated biphenyls  (PCBs) and
     polybrominated biphenyls (PBBs): Biochemistry,
     toxicology, and mechanism of action. CRC Crit.
     Rev. Toxicol. 13:319-393.
Safe, S., L. Safe, and M. Mullin. 1987.  Polychlorinated
     biphenyls: Environmental occurrence and analysis.
     Environ. Toxin. Ser. 1:  1-14.
Schwartz, TJR., D.E. Tillitt, KP. Feltz, and P.H. Peter-
     man.  1993.  Determination of mono-and non-0,0'-
     chlorine substituted polychlorinated biphenyls in
     Aroclors and environmental samples. Chemosphere
     26:1443-1460.
Smith, L.M., T.R. Schwartz, and K. Feltz. 1990. Deter-
     mination and occurrence of AHH-active polychlo-
     rinated biphenyls, 2,3,7,8-tetrachloro-p-dioxin and
      2,3,7,8-tetrachlorodibenzofuran in Lake Michigan
      sediment and biota: The question of their relative
      lexicological significance. Chemosphere 21:1063-
      1085.
USEPA. 1993a. Sediment quality criteria for the protec-
      tion of benthic organisms:  Fluoranthene.  EPA-
      822-R-93-012. U.S. Environmental Protection
      Agency, Office of Water, Washington, DC.
USEPA. 1993b.  Technical basis for deriving sediment
      quality criteria for nonionic organic contaminants
     for the protection of benthic organisms by using
      equilibriumpartitioning.EPA.-&22-R-93-On. U.S.
      Environmental Protection Agency, Office of Wa-
      ter, Washington, DC.
Varanasi,  U., I.E. Stein,  and M.  Nishimoto.   1989.
      Biotransformation and  disposition of polycyclic
      aromatic hydrocarbons  (PAHs)  in fish.   In U.
      Varanasi, ed., Metabolism of polycyclic aromatic
      hydrocarbons in  the aquatic  environment, CRC
      Press, Boca Raton, FL, pp. 94-149.
Varanasi, U., I.E. Stein, L.L. Johnson, T.K. Collier, E.
      Casillas, and M.S. Myers.  1992. Evaluation of
      bioindicators of contaminant exposure and effects
      in coastal ecosystems.  In D.H. McKenzie, D.E.
      Hyatt, and V.J. McDonald, eds., Ecological indicators,
      Vol.1. Proceedings of an international symposium,
      Fort Lauderdale, Florida, October 16-19, 1990.
Walker, M.K., and R.E. Peterson.  1991. Potencies of
      polychlorinated dibenzo-p-dioxin, dibenzofuran,
      and biphenyl congeners, relative  to 2,3,7,8-
      tetrachlorodibenzo-p-dioxinforproducing early life
      stage mortality in rainbow trout (Oncorhynchus
      mykiss). Aquatic Toxicol. 21: 219-238.
Woodward, D. F., W.G. Brumbaugh, A.J. DeLonay, E.E.
      Little, and C.E. Smith.  1994.  Effects on rainbow
      trout fry of a metals-contaminated diet of benthic
      invertebrates from the Clark Fork River, Montana.
      Trans. Amer. Fish. Soc. 123: 51-62.
Woodward, D. F., A. M.  Farag, H.L. Bergman, AJ.
      DeLonay,  E.E. Little, C.E. Smith, and F.T. Bar-
      rows. 1995. Metals-contaminated benthic inverte-
      brates in the Clark Fork River, Montana: Effects on
      age-0 brown trout and rainbow trout. Can. J. Fish.
     Aquat. Sci. 52: 1994-2004.
Zabel, E.W., P.M. Cook, andR.E. Peterson.  1995.  Toxic
      equivalency factors of polychlorinated dibenzo-p-
      dioxin, dibenzonfuran, and biphenyl cogeners based
      on early life  stage mortality in rainbow trout
      (Oncorhynchus  mykiss).  Aquatic  Toxicology
      31: 315-328.

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                                                        National Sediment Bioaccumulation Conference
 Comments  on the Significance  and
 Use  of Tissue  Residues in  Sediment
 Toxicology and Risk Assessment
 Lynn S. McCarty
 L.S. McCarty Scientific Research 8^ Consulting, Oakville, Ontario, Canada
 Introduction

 ^^Whe explicit use of body residues in ecotoxicology
  • and risk assessment  is  relatively new and is
  Jft. cuirently' hampered by the limited availability of
 residueTeffect data. However, the body-residue-based
 approach is theoretically sound and ultimately lies at the
 heart of existing enyironmental-media-based method-
 ologies. It is expected that residue-effect methodologies
 will soon supplant toxicity-only and bioaccumulation-
 only based procedures. In. the interim, methods to Com-
 bine and exploit existing  tbxicity and bioaccumulation
 knowledge are being developed and refined. However,
 there is still an opportunity to examine and direct how
 residue-based approaches may  be best employed. Five
 topics are reviewed and recommendations offered.


 What are the assumptions,
 applications, and limitations for each
 bloaccumulation or risk assessment
 methodology being described?

     All bioaccumulation-related approaches make.the
 assumption that bottom-up extrapolation is valid and,has
 been validated. That is to say that results  and information
 obtained in laboratory or controlled testing can be readily
 generalized and .extrapolated to population/community/
 ecosystem levels of organization.  This  is essentially a
 matter of faith or at best a policy decision. Such ap-
 proaches may be useful and/or effective in protecting the
 environment, but they are not firmly based in science
. since most such ecological organization theories have not
 been validated.         .  -
     For example, the conventional levels of a biologi-
 cal organization model are presented by Odum (1971).
 However, the practical ability to exploit this model for
 environmental protection and environmental risk assess-
 ment is not universally accepted.  Consider Fry's Para-
 digm, which addresses it:  "You take the properties of a
 level of organization and use those observations to ana-
 lyze the next level of organization below it. If you take
, the properties too many steps down, you're being stupid;
 and you cannot go the other directio'n." (Kerr, 1976)
     Fry's Paradigm clearly indicates that the very
 essence of much of the current risk assessment process—
 extrapolation from laboratory testing at the level of the
 individual organism (and below) to effects in the field at
 the population, • community, and ecosystem levels of
 organization—is unwise if not impossible. Furthermore,
 it should be pointed out that the model presented by
 Odum is not the only model for looking at how ecology
 is organized.  In fact, there is no single, generally ac-
. cepted ecosystem paradigm (Botkin, 1990 as cited by
 •Suter, 1993).  Less than half of about two dozen ecosys-
 tem concepts proposed by ecologists  have been em-
 ployed by risk managers/assessors and only about one-
. third are used with any regularity (Vigerstad, manuscript).
     Munkittrick and McCarty (1995) examined the
 uneasy relationship between  ecology  and toxicology
 known as ecotoxicology. They point out that such con-
 ceptual models of environmental impacts, although
 considering direct and indirect factors, do not usually
 consider wh.at they term nondirect factors, or induced
 factors as they are called in other disciplines. Nondirect
 factors are those which dp not originate with a response
 to a chemical stressor and cannot be expressed in terms of
 a lexicological dose.  For example, what is the dose
 metric of loss of half of the habitat of a species and how •
 is it quantitatively combined with the direct and indirect
 effects of toxicant stress?
     Basing a comprehensive and extensive regulatory
 framework on using a risk assessment process that
 depends heavily on the discipline of ecology, which
 itself is in turmoil and undecided on  a generally ac-
 cepted paradigm, and toxicology, which is struggling to
 expand beyond the  boundaries of the laboratory, is
 clearly policy rather than science. The biblical warning
 about building an edifice on a foundation of sand ap-
 pears appropriate. It niay be good policy, but scientists
                                             2-25

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 2-26
                                                              National Sediment Bioaccumulation Conference
 and risk assessors should be wary of confusing science-
 policy with science.
 How can bioaccumulation assessment
 be effectively applied to human
 health and ecological risk
 assessments?

      Bioaccumulation in and of itself is not an adverse
 environmental effect. Only accumulation that is associ-
 ated with an adverse effect in organisms  which have
 accumulated the material, either directly or via the food
 chain, is of importance.  Furthermore,  many materials
 produce adverse effects without any significant accumu-
 lation.  For environmental protection  and associated
 regulations bioaccumulation is not the issue, adverse
 effects are!
      More work has been done on examining dose-
 response relationships for changes and adverse effects in
 the lab, effects that are possible, than for changes and
 adverse effects in the field, effects that are probable.  As
 too little is known about ecosystems and effects at higher
 levels of organization (Calow,  1994), it is not surprising
 that relationships between lab  effects at the individual/
 population  levels  and field effects  at the  community/
 ecosystem levels are poorly understood.
     Furthermore, science policy must  provide techni-
 cal definitions of significant adverse effects in the field
 that are quantifiable by ecologists and risk assessors and
 consistent with current ecological theories.  It is safe to
 say, with the multiplicity of changes andputative adverse
 effects being studied and reported in the literature, that
 currently there is no general agreement on what consti-
 tutes significant adverse environmental effects.  Risk
 assessment is useful only in a comprehensive risk man-
 agement framework where risk management goals are
 specified in the technical terms that scientists practicing
 risk assessment can quantitatively address (McCarty and
 Power, in press).
What are the requirements for
selecting species for bioaccumulation
testing?  Are indigenous species
necessary?

     Using residue information and appropriate bioas-
say interpretation, real differences in species sensitivity
can be separated from differences associated with bio-
availability and toxicokinetics: Indigenous species may
be useful and  may provide important information but
only when thenature of "sensitivity" differences are clear
and sensitivity itself is clearly defined. For example, the
influence of bioavailability, exposure medium, and vari-
ous modifying factors  (e.g.,  body size) is  often  not
considered  in toxicity test interpretation.   There is an
almost mythical belief that a most sensitive species can be
determined and that this determination will be useful.
However, most sensitivity examinations use exposure-
medium-based  LCSOs or similar estimates  and do not
 fully interpret toxicity test results to remove the effects of
 modifying factors. Such efforts are largely futile (Power
 and McCarty, manuscript).
      Some headway can be made with a residue-based
 approach. Lanno and McCarty (in press) discuss a case
 comparing  pentachlorophenol toxicity to a freshwater
 fish, a freshwater benthic invertebrate, and the common
 earthworm.  Based on exposure-based LC50 bioassay
 results, it appears that the fish is more sensitive (threshold
 LC50 of 0.00039 mmol/L) than the benthic invertebrate
 (threshold LC50 of 0.0019 mmol/L).  The threshold
 LC50 of 0.14 mmol/kg dry soil for the earthworm is not
 comparable due to the differences in exposure media.
 However,, when the lethal body residues (LR) are exam-
 ined, a sensitivity comparison is possible between the
 three organisms.  The LR50 range is 0.08-0.17, 0.33-
 0.79, and 0.3-101  mmol/kg wet weight for the fish,
 earthworm, and benthic invertebrate, respectively. The
 fish appears to be slightly more sensitive, but the effect of
 differing body lipid contents has yet to be determined and
 may alter the relationship.
How can tissue-specific residue levels
be coupled with chronic toxicity
response data to develop dose-
response relationships for
bioaccumulative contaminants?

     This issue is examined in detail in McCarty and
Mackay (1993) and in Rand et al. (1995).  The basic
approaches are estimation using existing toxicity data
and bioaccumulation relationships (i.e., exposure-based
toxicity estimate* bioconcentration factor = whole-body
residue-based toxicity estimate) and generation of resi-
due-effect data from new experimental testing.
     Work by Mayer (Mayer et al., 1986, 1992) on the
relationship between acute and  chronic toxicity  end-
points is particularly valuable in both approaches.   He
has established that, in many cases, the lower tail (specifi-
cally, LC0.01) of the distribution of acutely lethal toxic-
ity is equivalent to the maximum acceptable toxicant
concentration (MATC)/lowest observed effect concen-
tration (LOEC) obtained in chronic toxicity  testing for
growth/survival but not reproduction endpoints.  Figure
1 (modified from Figure 5, McCarty and Mackay, 1993)
illustrates the point.  When the toxicity data from a test
are transformed to a linear relationship using the log-
probit transformation, any proportional response can be
interpolated or extrapolated. When measured exposure-
based (LCx) or residue-based  (LRx) toxicity data are
available, values can be directly estimated.   Similarly,
LRx data can be  estimated from LCx data  where
bioconcentration factor information is available.
     This approach provides many additional insights
due to a more complete exploitation  of toxicity test
information. It was the basis for the suggestion that the
current separate acute toxicity,  chronic toxicity, and
bioconcentration tests be combined into a single aquatic
toxicity test protocol (McCarty, 1991). Such a combined
approach would require an alteration in direction from

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 Proceedings'
                                                                       2-27
     99.9
           LCx and LRx  Approach to  Chronic  Toxicity
          %  Mortality at  Incipient Tox-icity                      Probit
     .84  H

     50

     16  H
              CBR = TOX  '  BCF
              LRx =  LCx * BCF
                                             interpolation
                         LC50 = 5.5 umol/L
                         LR50 - 5.5 mmol/kg
LC0.01  = 1 umol/L.
LR0.01  = 1 mmol/kg
     0.01
                                                       LC10
                                                       LR10
                         extrapolation
-.3.2 umol/L
••3.2 mmol/kg
                                                                    8
-7

-6

-5

-4

-3

-2
                                                                    1
                      Exposure Concentration (umol/L)
                            BODY RESIDUE {mmol/kg)
                                                                               10
 Figure 1. LCx and LRx approach to chronic toxicity.
 the current minimalistic trend in testing protocols.
 Despite the additional observations and sampling that
 would be required, it is still likely to be less costly than the
 current trio of tests. As well, when conducted as scien-
 tific research experiments, such an approach  will ulti-
 mately be more informative than abbreviated "regula-
 tory" testing.
     Although there is an increasing demand for more
 chronic toxicity data, both exposure-based and residue-
 based chronic information have a number of limitations.
 These include the following: chronic data are  more ex-
 pensive to collect, chronic results usually have greater
 uncertainty, some chronic endpoints are not readily inter-
 pretable, relationships between whole body levels versus
 those found in selected tissues have not been worked out,
 and differences in body lipid content confound precise
 residue-based interpretation.
      It should be possible to, develop protocols and
 procedures to address these limitations.  The current
 limited availability of chronic residue-effect data can be
 overcome by estimation and new experimentation. How-
 ever, the desirability of shifting the bulk of ecotoxicq-
 logical testing to chronic effects is based on the largely
. my thical belief that chronic data are somehow "better" as
 the basis of environmental regulations.  This appears to
                                 be largely based on the assumption that chronic effects in
                                 the laboratory are equivalent to and readily comparable
                                 to chronic effects in actual field situations. .This issue is
                                 addressed in the next section.
                                 How can bioaccumulation assessment
                                 methods, including testing and
                                 models, be used to address
                                 population-level effects?

                                     At the present time only acutely toxic effects and
                                 major growth or reproductive effects can be effectively
                                 modeled by population modelers. The major difficulty is
                                 density-dependent responses, which are poorly known.
                                 The objective of environmental protection is protection
                                 of communities and local ecosystems. However, density-
                                 dependent and other interspecies interactions, which are
                                 largely unknown, represent a poorly quantified level of
                                 complexity that effectively renders extrapolation from
                                 bioassay to field largely an exercise in professional
                                 judgment, not quantitative analysis and modeling (Power .
                                 and McCarty, manuscript).
                                     Laboratory toxicity testing is focused primarily on
                                 addressing bioavailability,. kinetics, and the resistance/

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                                                               National Sediment Bioaccumulation Conference
tolerance of organisms exposed under highly controlled
conditions. The density-dependent factors that influence
toxic effects in the field are rarely studied in the lab. An
exception is work by Arthur and Dixon (1994). Juvenile
fathead minnows were placed in 1-L screen cages at a
density of  1, 5,  and  10 individuals per cage and then
placed in a flow-through system exposure apparatus. The
chronic growth effects of pentachlorophenol and 2,4,5-
trichlorophenol were examined for 28 days. Up to about
twofold differences in chronic toxicity were found, e.g.,
low-density LOEC = 71 ug/L PCP; high-density LOEC
= 121ug/LPCP.
     There is a significant effect of density  on the
outcome  of a toxicity test in ,tightly controlled experi-
mentation in the lab with a single species over a relatively
short time period.  It is clear that, with the myriad of
opportunities for confounding influences in field situa-
tions of multiple populations under varying conditions,
density-dependent factors remain a serious obstacle to
extrapolating laboratory testing data to the field.   The
severity of the problem increases as consideration moves
from short-term acute effects to long-term chronic effects
as there is more opportunity for density-dependent fac-
tors to  operate the longer organisms are stressed but still
living.  Thus, more chronic residue-based toxicity infor-
mation alone will not improve the success of extrapolat-
ing such information to the field. A much better under-
standing of the influence of density-dependent factors is
also required before any substantial improvement can be
expected.
Conclusions

1. Basic ecological theories need further development
   and clear separation from science policy.
2. Bioaccumulation is not intrinsically an adverse effect
   endpoint.
3. Body residues can help identify true differences in
   species sensitivity by improving the understanding of
   modifying factors.
4. Chronic body residue data can assist in interpretation
   of toxicity testing results if improved methods and
   analyses are adopted.
5. Improvementinlab-to-fieldextrapolationrequiresboth
   greater residue-based toxicity knowledge and a better
   understanding of the  density-dependent modifying
   factors acting within and between species in the field.


Recommendations

Policy.     Separate science from science-based policy
            by use of a clear risk management frame-
            work.
Toxicity 1.  Develop a single generic bioassay protocol
            that integrates acute and chronic toxicity as
            well as bioconcentration.
Toxicity 2.  Do not use a local species unless at least
            one standard species, selected  from a very
            restricted list, is also tested. Clarify that an
Ecology.
indigenous species is actually more sensi-
tive than the standard species using tissue
residue-effect relationships to determine the
influence of modifying factors such as body
size, temperature, behavior, and nutritional
characteristics.
Furtherdevelopabasicecological paradigm
and enhance population/community knowl-
edge, especially  for density-dependent
interactions.
Acknowledgments

     The content of this paper draws on past and ongoing
work with  R.  Lanno, K. Munkittrick, M. Power,  and
T. Vigerstad.
References

Arthur, A.D., and D.G. Dixon.  1994. Effects of rearing
     density on the growth response of juvenile fathead
     minnow (Pimephales promelas) under toxicant-
     induced stress. Can. J. Fish. Aquat. Sci. 51:365-371.
Botkin,  D.B.   1990.  Discordant  harmonies.  Oxford
     University Press, New York, NY.  Cited in Suter,
     1993.
Calow, P. 1994. Ecotoxicology: What are we trying to
     protect? Environ. Toxicol. Chem. 13:1549.
Kerr, S.R.  1976. Ecological analysis and the Fry para-
     digm. /. Fish. Res. Bd. Can. 33:329-339.
Lanno, R.P.,  and L.S. McCarty. In press.  Earthworm
     bioassays: Adopting techniques from aquatic tox-
     icity testing.  Soil Biol. Biochem.
Mayer, Jr., F.L., K.S. Mayer, and M.R. Ellersieck. 1986.
     Relation of survival to other endpoints in chronic
     toxicity tests with fish. Environ. Toxicol. Chem.
     5:737-748.'
Mayer, F.L., G.F. Krause, M.R. Ellersieck, and G. Lee.
     1992. Statistical approach to predicting chronic
     toxicity of chemicals to fishes from acute  toxicity
     test data. EPA/600/R-92-091. U.S. Environmental
     Protection Agency, Gulf Breeze, FL. 94 p.
McCarty, L.S.  1991. Toxicant body residues: implica-
     • tions for aquatic bioassays with some organic chemi-
     cals. In M. A. Mayes andM.G. Barron, eds., Aquatic
     toxicology and risk assessment, Vol. 14, ASTM
     ' STP1124, American Society for Testing and Mate-
     rials, Philadelphia, PA, pp. 183-192.
McCarty, L.S., and D. Mackay.   1993. Enhancing
     ecotoxicological modeling and assessment: Body
     residues and  modes of toxic  action. Environ. Sci.
     Technol. 27:1719-1728.
McCarty, L.S., and M. Power. In press.  Environmental
     risk assessment within a decision-making frame-
     work. Environ Toxicol Chem.
Munkittrick, K.R.,  and L.S. McCarty.  1995. An inte-
     grated approach to ecosystem health management:
     Top-down, bottom-up or  middle-out? /.  Aquat.
     Ecosys. Health 4:77-90.

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Proceedings
                                                                                               2-22
Odum, E.P.  1971. Fundamentals of ecology. 3rd ed.
     W.B. Saunders Company,  Philadelphia, PA.
     574pp.
Power, M., andL.S. McCarty. Manuscript. Ecotoxicology in
     Wonderland: Myths arid misconceptions. Presen-
     tation at SETAC '95, Vancouver, BC, Nov., 1995.
Rand G.M,  P.O. Wells, and L.S. McCarty.  1995.
     Chapter 1: Introduction to aquatic toxicology. In
      G.M. Rand, ed. Fundamentals of aquatic toxi-
      cology II: Effects,  environmental fate, and risk
      assessment, Taylor and Francis, Bristol, PA, pp.
      3-67.
. Suter, G.W.  II.   1993.  Ecological  risk assessment.
      Lewis Publishers, Boca Raton, FL. 538 pp.
 Vigerstad, T.J.  Manuscript. Ecosystem assessment:
      Paradigms and applications.

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                                                         National Sediment Bioaccumulation Conference
Quantification  of  Ecological  Risks to
Aquatic Biota from  Bioaccumulated
Chemicals
Burt K. Shephard
URS Greiner, Inc., Seattle, Washington
Abstract

  JA   simple sounding yet difficult to answer question
 Mi^L  is "What concentration of a chemical in fhe tis-.-
JiTLsues of aquatic biota is harmful to the biota
itself?"  This question is  of particular importance in
ecological risk assessment, where measurements of chemi-
cal residues in aquatic biota are often available, but the
interpretation of their effect on biota is difficult.  The
objective of this work was to define tissue residues for a
number of chemicals which, if not exceeded, pose little
threat of risk to aquatic biota.  These  tissue screening
concentrations  (TSCs) were designed to be nonsite- or
species-specific indicators of low risk residue levels.
TSCs have been derived for 152 chemicals, both metals
and organics, using a one-compartment first-order ki-
netic model. These TSC values are currently being used
in ecological risk assessments to identify chemicals of
potential concern, thus narrowing the focus of the risk
assessment. To confirm the validity  of the TSCs, a
literature review of whole body tissue residues associated
with adverse lexicological or ecological effects was per-
formed. The review currently contains over 1400 records
of tissue residues associated with adverse effects of 120
of the TSC chemicals. For chemicals where the TSC
values  are  applicable, 94 percent of the literature re-
viewed indicates that adverse effects occur only at tissue
residues higher than the TSC values. This is comparable
to the U.S. Environmental Protection Agency's (USEPA)
ambient water quality criteria, which are designed to be
protective of 95 percent of aquatic genera. Analysis of
this literature indicates that as groups (1) marine and
freshwater biota are equally  sensitive to chemical
residues in their tissues, and (2) benthic and pelagic biota
are equally sensitive to chemical residues in their tissues.
Sufficient literature is available for a number of chemi-
cals to permit direct estimates of the likelihood residues
in aquatic  biota from a site pose adverse  risks.   The
existence of a tissue residue literature database relating
adverse effects to residue levels eliminates one of the
primary shortcomings preventing the use of the tissue
residue approach in sediment quality criteria develop-
ment: lack of documentation of tissue residues related to
adverse toxicological effects. The database also provides
indirect confirmation  of a primary assumption of the
equilibrium partitioning approach to sediment quality
criteria development: benthic biota have a similar range
of sensitivity to chemicals as do pelagic biota.  .
Introduction

     Historically, the primary use of aquatic biota tissue
residue data in ecological risk assessments has been to
provide an indication that the biota have been exposed to
chemicals at a site.  Seldom have, efforts been made to
directly quantify ecological risks from bioaccumulated
chemicals.                        •
     The most common approach to quantifying eco-
logical risks to aquatic biota is to divide the concentration
of a chemical hi water or sediment by a toxicity reference
value (TRV), a concentration which if exceeded is ex-
pected to result in adverse ecological effects. The result-
ing hazard quotient is used'as a measure of risk to biota,
with  the likelihood of adverse effects increasing with
increasing  magnitude of the hazard quotient.  TRVs
available for use in ecological risk assessment include
ambient water quality criteria (AWQC) and sediment
quality values from several sources. Unfortunately, there
is not a comparable set of TRVs-for use in assessing
ecological risks from tissue residues in the biota themselves,
despite a sizable amount of research relating body bur-
dens  to toxic effects and the availability of several litera-
ture reviews of this information (McGarty and Mackay,
1993; McKim and Schmieder, 1991; Dillon, 1984).
     Chemical concentrations in water and sediment are
surrogates for the actual dose of chemical at the site of toxic
action in biota. The use of these surrogates for the actual
                                              2-31

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2-32
                                                              National Sediment Bioaccumulatlon Conference
dose has many limitations and introduces uncertainties in
assessing adverse effects of chemicals on aquatic biota,
some of which are outlined below.  ,
    •  The bioavailable fraction of the total chemical
       concentration in exposure media may  not be
       known.
    •  Surrogates do not consider multiple uptake routes
       of chemicals by biota.
    •  Intermittent, pulsed, or varied exposures cannot
       be readily assessed.
    •  Short exposure times can result in nonsteady-
       state tissue residues and variable toxicity.
    •  Metabolic transformations of toxicants which en-
       hance or reduce toxicity are not considered.
    •  Animal behavior (i.e., seasonal migration or toxi-
       cant avoidance) is not accounted for.
    •  Analytical  chemistry  limitations   (e.g.,
       nondetectable concentrations hi exposure media)
       mean the dose is often unknown.
     By quantifying risks based on tissue residues asso-
ciated with adverse toxicological or ecological effects,
the above complicating factors are largely eliminated and
a more accurate risk assessment can be performed. .
     The objectives of this work were  as follows:
1. To  derive risk-based screening  concentrations
   (RBSCs) for assessing ecological risks from chemi-
   cal residues in  aquatic biota tissues to the aquatic
   biota themselves.
2. To confirm the utility of the derived RBSCs in eco-
   logical risk assessment.


Methodology

     USEPA's ambient water quality criteria are de-
signed to be protective of 95 percent of all aquatic genera
(Stephan et al., 1985). By 'extension of this principle,
tissue residues bioconcentrated from criteria concentra-
tions should also,  if  not  exceeded, be  protective  of
95 percent of all aquatic genera. This is the fundamental
assumption behind  the approach used to derive toxicity
reference values for bioaccumulated chemicals in aquatic
biota.
     Tissue residues hi aquatic biota which, if exceeded,
may describe residues associated with adverse toxico-
logical or ecological effects are termed tissue screening
concentrations (TSCs) in this paper.  This is because the
primary use of the TSC values is as a screening tool to
select chemicals of potential concern (COPCs) in eco-
logical risk assessments. COPC identification shortens
the list of chemicals carried through the entire ecological
riskassessmentprocess. TSCs are intended to be nonsite-
or species-specific indicators of tissue residues which, if
not exceeded, pose little threat of adverse risk to aquatic
biota.
     TSCs  were derived  from the "one-compartment
first-order kinetic (1CFOK) toxicological model given in
Equation 1.
     where:
        Cb = chemical concentration in biota (mg/kg)
        t  = time (hours)
        ku = chemical uptake rate constant (L/kg/hr)
        Cw= chemical concentration in water (mg/L)
        ke = chemical elimination rate constant (hour1)
     If the chemical concentration in water is assumed to
be constant, Equation 1 may be exactly integrated to yield
Equation 2.
         =    x
                   x    _
     If it is further as sumed that the animal starts with no
tissue residue of the chemical of interest and the tissue
residue is at steady state with respect to the water concen-
tration, Equation 2 reduces to Equation 3.
                 ^   „   ku
                 C>=C»*Te                   <»

     By redefining the terms in Equation ,3, Cb becomes
the tissue screening concentration, Cw becomes an ambi-
ent water quality criterion (AWQC), ku/ke is a bioconcen-
tration factor (BCF), and the redefined Equation 3 can be
used to derive tissue screening concentrations, as shown
hi Equation 4.
             TSC=AWQC-X,BCF,
(4)
               dC,
                dt
                 * —i
                                               (1)
     Although the derivation of TSCs is based on sound
toxicological concepts, in practice they are derived sun-
ply by multiplying a water quality criterion by a biocon-
centration factor.
     To provide a more conservative screening value,
water quality criteria used in the calculations are  the
lower of USEPA's freshwater or chronic ambient water
quality criteria. Since some of USEPA's water criteria
documents are for classes of chemicals (e.g. PAHs, chlo-
rinated benzenes, chlorinated phenols), a single criterion
value may be used in the derivation of multiple TSC
values.  For metals with hardness-dependent criteria, a
hardness of 50 mg/L CaCO3 was assumed.  If only an
acute criterion was available for a given  chemical,  the
acute criterion was divided by 8  to estimate a chronic
criterion. The bioconcentration factors used were taken
from the human health portion of the USEPA water
quality criteria documents.  For metals, the BCFs  are
geometric means of measured BCF values, whereas for
organics, the criteria BCFs were calculated using a re-
gression equation relating octanol-water partition coeffi-
cient to BCF. Most of the BCF values used are found hi
the SuperfundPublic Health EvaluationManual (USEPA,
1986).
     To confirm the validity of the TSC values, a litera-
ture review was performed of papers relating measured
whole body, wet weight tissue residues to adverse toxico-
logical or ecological effects.  For papers  where  dry
weight tissue residues were reported, a conversion to wet
weight was made assuming 80 percent water content if
the actual water content was'not given  in the  paper.
Effects considered in the review were population and
community  effects, mortality, reproduction, growth,

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 Proceedings
                                                                                                        2-33
 behavioral, cellular,  biochemical,  or physiological
 changes.
      The literature database' currently contains the fol- _
 lowing information for each citation: chemical name,
 tissue screening concentration, tissue residue associated
 with effect (or the,no effect residue), common, and scien-
 tific names of the species studied, lexicological or eco-
 logical effect, a safety factor (defined in Equation 5), a .-
 footnote field that contains information on the exposure
 Conditions of the study, and the full literature citation.
      To describe the difference between TSC values and
 the  tissue residues associated with  adverse effects, a
 safety factor (Equation 5) was calculated.

  ™,-r  f ^ r  * •    Tissue concentration associated with effect
 ISC safety factor =  - — - : — - - ^ —   (5)


      The safety factor provides qualitative evidence of
 the level of protection T.SCs  provide aquatic biota from
 adverse effects.  Computationally, the safety factor can
 also be considered a hazard quotient for a measured tissue
 residue associated with a specified effect as given in the
 literature.
      It must be noted that the TSC values are intended to
 identify tissue residues which, if not exceeded, pose little
 or no risk to aquatic biota. They are not intended to define
 tissue residues that are protective of avian, mammalian,
 or other wildlife  species that prey upon aquatic biota.
Results

      Table 1 provides a representative example of the
152 currently available tissue screening concentrations.
All tissue residues given in Table 1 have units of mg/kg
whole body, wet weight. As shown in Table 1 , the TSC
values span a wide range of .tissue residues predicted to
have little or no effect on aquatic biota.
      The literature review currently contains nearly 500
citations and 1400 records associating tissue residues to

Table 1. Derivation of selected tissue screening concentration values.
Chemical
Aldrin
Benzo(a)pyrene
Cadmium
Copper
4,4'-DDT ,
Dieldrin
Dioxin (2,3,7,8-TCDD)
Hexachlorobenzene
Mercury
PCB
/
Tributyltin
1 ,2,4-Trichlorobenzene
Zinc . . •
AWQC
"g/L
1.3
300
0.66
2.9
0.00 1
0.0019
0.00001
3.68
0.012
0.014
0.01
50
59
AWQC Source
Marine acute
PAH marine acute
Freshwater chronic
Marine acute
Freshwater chronic
Freshwater chronic
Freshwater chronic
Freshwater chronic
Freshwater chronic
Freshwater chronic
Marine chronic
Freshwater chronic
Freshwater chronic
BCF
L/kg
4,670
11,100
64
200
53,600
4,760.
5,000
8,690
4,994
31,200
693
2,800
47
TSC
mg/kg
0.71
416
0.042
0.17 ,
0.054
0.0090
0.000050
32
0.060
0.44
0.0069
140
2.8
AWQC - USEPA Ambient Water Quality Criterion
BCF - Bioconcentration Factor
TSC - Tissue.Screening Concentration
adverse effects. Of these, approximately 10 percent of the
individual records describe no observed adverse effect
.tissue residues. A range of tissue residues have been
associated with adverse ecological or lexicological effects.
Figure 1 shows the distribution of tissue residues associated
with adverse cadmium effects. The distribution in Figure 1
is typical of that for most chemicals, where no or only a few
citations indicate that effects occur below  the  tissue
screening concentration, but most adverse effects occur at
tissue residues above the tissue screening concentration.
      At least one literature citation is available for 120
of the 152 chemicals for which TSCs exist., Ten or more
residue-effect records are available for about 40 chemicals.
Cadmium has the most literature information available of
any chemical in the database, while PCBs have the most
information available for any organic chemical.  Other
chemicals  that have a substantial amount of literature
available include  mercury, copper,  zinc, dioxin, pen-
tachlorophenol, and several chlorinated insecticides.
      Once the no observed adverse effect residues are
removed from the database,  83 percent  of the  tissue
residues associated with adverse-effects are concentra-
tions higher than the tissue, screening concentrations.
Over half of the tissue residues associated with adverse
effects at concentrations  lower than the TSCs are for
chemicals that are rapidly (within a few hours or days)
metabolized to more toxic compounds.   The rapidly
metabolized chemicals are mostly PAH compounds, al-
though the chlorinated insecticide aldrin is also rapidly
converted to a. more toxic metabolite, dieldrin. Figure 2
shows tissue residues of benzo(a)pyrene associated with
adverse effects. For benzo(a)pyrene, every citation avail-
able shows an adverse effect at a whole body concentra-
tion below its TSC value.
      Once chemicals rapidly metabolized to more toxic
forms are  removed from the literature database, the
predictive ability of the TSC values to identify residue
levels below which adverse  effects are  unlikely im-
proves. By performing the TSC to adverse effects litera-
                         ture comparison  without
                         chemicals rapidly metabolized
                         to more toxic forms, 94 percent
                         of the tissue residues associ-
                         ated with adverse effects are
                         higher than the tissue screen-
                         ing  concentrations.
                              The calculated safety
                         factors (Equation 5) provide
                         a qualitative indication of the
                         conservative nature of the
                         TSC values.  For all residue
                         effect citations in the litera-
                         ture database, the geometric
                         mean safety factor is 15, while
                         the  arithmetic mean safety
                         factor is 41.  The safety fac-
                         tors for individual literature
                         citations are generally largest
                         for measures of mortality and
                         smallest  for  biochemical
                         endpbints.

-------
r
                    2-34
                                                                                   National Sediment Bioaccumulation Conference
s
'(I)
 CO
 tn
 CD

1
 tn

I
 CO
CC
                                      100

                                        90

                                        80

                                        70
                                                  TSC = 0.042 ng/g
         0.001    0.01     0.1        1        10      100
                                    [Cadmium], ng/g
                                                                                                  1000   10000
                    Figure 1. Tissue residues associated with adverse effects:  Cadmium.
on
OU -
^. OK
.3*  ~
•-B I
'c 90 "
1 2°:
tn
.* -IK "
o 10 ~
Q.
w
» 10 :
^
§ :
°- 5





^





i—











i —





-m





_--
TSC = 416ng/g




,v




jf
s




• ''





^J




^
I




j r
r




r
'



i
i










..











••
0.001 0.01 0.1 1 10 100
[Benzo(a)pyrene], ng/g
Tissue screening approach does not work for chemicals rapidly
metabolized to more (or less) toxic forms












1000
                    Figure 2.  Tissue residues associated with adverse effects: Benzo(a)pyrene.
                          The safety factors have been used to make several
                    statistical comparisons among various subsets of the litera-
                    ture data. These comparisons have found that, as groups:
                    1. There are no significant differences in residue levels that
                       cause adverse effects in freshwater or marine biota.
                    2. There are no significant differences in residue levels
                       that cause  adverse  effects  in benthic compared to
                       pelagic biota.
                                           3.  There are no significant differences in the sensitivity
                                              of biota to chemicals under field or laboratory expo-
                                              sure conditions.
                                                Although the results given above appear broadly
                                           applicable based on the literature review, there are exceptions
                                           in some instances. For example, arsenic residues associated
                                           with adverse effects in freshwater biota are much lower
                                           than arsenic residues that adversely affect marine biota.

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 Proceedings
                                                                                                 2-35
Table 2. Human health exposure scenario used to derive toxicity reference values (TRVs) for comparison of TSC
values to TRVs for consumers of fish and shellfish.
Exposure Scenario Parameter
Exposure frequency
Exposure duration
Body weight
Value
350 days/year
30 years
70 kilograms
Exposure Scenario Parameter
Fish and shellfish ingestion rate
Target noncancer risk
Target cancer risk
. Value
6.5 grams/day
1
1 x 10-6 ,
   .   Tissue screening concentrations have also been
compared to human health toxicity reference values
(TRVs) for chemicals hi fish and shellfish consumed by
humans. The exposure scenario and risk assumptions
used to derive the human health TRVs are presented in
Table 2. For noncarcinogenic chemicals where compari-
sons could be made, the ecological TSC values were
lower than the human health TRVs in 61 of 67 compari-
sons (91 percent). For carcinogenic chemicals, the hu-
man health TRVs were lower than the ecological TSCs in
36 of 42 comparisons (86 percent).


Discussion

      To date, TSCs have been used as a screening tool in
ecological risk assessments at several Superfund sites. In
all cases, they have identified chemicals of potential
concern (COPCs) that have also been identified as COPCs
in at  least one other human health or ecological risk
assessment scenario at the same site. This type of agree-
ment  with other risk  assessment procedures provides
corroborative evidence that the TSCs are successfully
identifying chemicals worthy of detailed investigation in
ecological risk assessments.
     The largest shortcoming of the procedure appears
to be its lack of applicability to chemicals that are rapidly
metabolized to more toxic forms.  Many PAH com-
pounds elicit adverse effects at tissue residues several
orders  of magnitude below the PAH tissue screening
concentrations (Figure 2).  Although this may be due in
part to the use of an old water quality criterion (USEPA,
1980a) for PAHs, a mechanistic reason for this observa-
tion can also be given.
     Many PAHs are known to be rapidly metabolized
to more toxic compounds (USEPA, 1980a).  A tissue
screening concentration based on residues of a less toxic
parent compound will not represent a safe concentration
of a more toxic metabolite. For rapidly metabolized
chemicals, a TSC for the more toxic metabolite should be
used to assess risks, rather than the TSC for the parent
compound. An example of this approach is shown in
Figure 3. Aldrin is rapidly metabolized by many species
to dieldrin (USEPA, 1980b).  The limited amount of
TSC = 0.009 jig/g '
25
••^ oh
.> 20 -
0)
w 15 -
.,8
'8
£• 10
•". '• 1
ro 5 -
o: °
0 -

-












i




j




/'

"i


•^








r"
.



• i
ji


^
I
•



1



i
-=








. -•














0.001 0.01 0.1 i 10 100 1000 10000
[Dieldrin], ng/g
The toxicity of a metabolic product of aldrin is correctly predicted by the TSC of
the metabolic product.
figure 3. Tissue residues associated with adverse effects:  Dieldrin.

-------
2-36
                                                                National Sediment Bioaccumulation Conference
aldrin residue data associated with adverse effects brack-
ets  the  aldrin TSC value.  A substantial amount of
literature is available for dieldrin residue toxicity (Figure
3). In all cases, dieldrin residues associated with adverse
effects are higher than the dieldrin TSC value.  Unfortu-
nately,  TSC values do not currently exist for PAH
metabolites, limiting the utility of the TSC approach to
chemically and metabolically stable toxicants.
     They are also not applicable for chemicals whose
toxicity does not result from an internally absorbed dose.
Examples of chemicals in this second  category may be
aluminum and iron, whose toxicity largely comes from
formation,  under certain water quality conditions, of a
flocculent material that suffocates aquatic biota.
      Several of the TSC values appear to be overly
conservative based on the literature review. In particular,
no  adverse effects have been associated with  copper
residues below 3 mg/kg  or zinc  residues  below
20 mg/kg, considerably higher than the respective calcu-
lated TSC values of 0.17 and 2.8 mg/kg. In practice, we
are now using the 3 mg/kg copper and 20 mg/kg zinc
values as screening concentrations in ecological  risk
assessments.  Many aquatic species can  regulate their
body burdens of copper and zinc. The 3 and 20 mg/kg
screening values for copper and zinc are much closer to
the known or estimated physiological requirements of
these two elements in aquatic biota (van Tilborg and van
Assche, 1996; White and Rainbow, 1985) than are the
TSC values in Table 1.
      At least one TSC is not sufficiently conservative
for use as a screening tool in ecological risk assessment.
The hexachlorobenzene TSC of 32 mg/kg is higher than
9 of the 10 literature citations  associating hexachloro-
benzene residues with adverse effects. If the hexachloro-
benzene TSC is  recalculated using the bioconcentration
factor from Table 1  and the Canadian  Water Quality
Guideline of 0.0065 jag/L instead of the draft USEPA
ambient water quality criterion of 3.68 |ig/L, the resulting
TSC is 0.056 mg/kg. This recalculated TSC is lower than
all 10 hexachlorobenzene adverse effect residue levels
reported in the literature. Use of the Canadian Water
Quality Guidelines is currently under investigation for
use in calculation of additional TSC values for chemicals
where USEPA currently has no ambient water quality
criteria.
      The  availability of a literature database of tissue
residues associated with adverse effects permits the use
or derivation of several other ecological risk estimation
methods. The hazard quotient approach has already been
discussed. For aquatic species where asubstantial amount
of literature is available, the best approach may be the
direct identification of tissue residues associated  with
adverse effects.  Rainbow trout (Oncorhynchus  mykiss)
and blue mussels (Mytilus edulis) are the freshwater and
marine species with the most tissue residue information
available in the literature. By comparing the distribution
of tissue residues associated with adverse effects (Figures
 1-3) to the residue distribution in animals from a site of
interest, probabilistic risk assessments could  be per-
formed. Other endpoints analogous to sediment or water
quality criteria  or guidelines, such as apparent effects
thresholds (AETs), lowest observed adverse effect lev-
els (LO AELs), or tissue residues above which effects on
a defined percentile of species occur could all be calcu-
lated from the literature database. The defined percen-
tile approach could be the tissue residue equivalents of
the Long and Morgan (1991) effects range-low (ER-L)
and effects  range-median (ER-M) sediment quality
guidelines.
      Although the primary focus of this paper has been
on the use of tissue residue information to define eco-
logical risks to aquatic biota, the tissue residue approach
also has applicability to the derivation of sediment
quality criteria. USEPA (1993) has identified the tissue
residue approach as a technically valid approach for the
derivation of sediment quality criteria. One of the major
identified shortcomings of the tissue residue approach
to sediment criteria development is the absence of a
database of  residue levels  associated with toxicity
(USEPA, 1993).  The database developed to confirm the
utility of the TSC values could also serve to eliminate
this identified shortcoming of the tissue residue approach
to sediment criteria development.  The database also
provides indirect evidence that benthic biota, as a group,
are equivalent in their response to toxicants to pelagic
biota, a fundamental assumption  of the equilibrium
partitioning approach to deriving sediment quality criteria.


Summary and Conclusions

      Although the literature database compiled during
this study allows a number of hypotheses to be tested
and conclusions to be drawn, the three primary conclu-
sions that have been  drawn to date  are:
1.  Tissue residues of chemicals in aquatic biota can, for
    many chemicals, be used to directly assess ecologi-
    cal risks to aquatic biota.
2.  Chemicals for which tissue residues cannot be used
    to quantify risks can be identified from mechanistic
    considerations.
3.  The level of protection from adverse risk provided
    by the tissue screening concentration approach  is
    comparable to that provided by USEPA's ambient
    water quality criteria.
      The TSC method appears to provide a conservative
initial screen capable of eliminating from an ecological
risk assessment chemicals that,do not pose significant
risks to aquatic biota. Exceedance of a tissue screening
concentration does not automatically imply that an ob-.
served tissue residue poses an adverse risk to biota. It does,
however, identify those chemicals  which require more
detailed investigation in an ecological risk assessment.
      The existence of an interpretive tool for assessing
risks or hazards to aquatic biota from bioaccumulated
chemicals has many potential applications in addition to
ecological risk assessment.  Environmental assessments,
dredging bioassessments, and criterion and standard
development are three of the many  possible uses. Inter-
pretation of tissue residues has the potential to provide
 substantially more information than its current primary
 use, which is as an indicator of exposure to chemicals.

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Proceedings	^_	

References

Dillon, T.M. 1984. Biological consequences of bioaccu-
     mulation in aquatic animals: An assessment of the
     current literature. Technical Report D-84-8. U.S.
     Army Corps of Engineers, Waterways Experiment
     Station, Vicksburg, MS.
Long, E.R. and L.G. Morgan. 1991. The potential for
     biological effects of sediment-sorbedcontaminants
     tested in the National Status and Trends Program.
     NOAA Technical Memorandum NOS  OMA 52,
     National Oceanic and Atmospheric Administra-
     tion, Seattle, WA.
McCarty, L.S.,  and D.  Mackay.   1993.  Enhancing
     ecotoxicological  modeling and assessment.
     Environ. Sci. Technol. 27:1719-1728.
McKim,J.M., andP.K. Schmieder. 1991. Bioaccumula-
     tion:  Does it reflect  toxicity? In R. Nagel and
     R. Loskill, eds., Bioaccumulation in aquatic sys-
     tems.  Contributions to the assessment, VCH Pub-
     lishers,Weinheim, Germany, p. 161-188.
Stephan, C.E., D.I.  Mount, D.J. Hansen, J.H. Gentile,
     G.A. Chapman and W.A. Brungs. 1985. Guidelines
   •  for deriving numerical national water quality cri-
     teria for the protection of aquatic organisms and
   -            	          2-37

     their uses. U.S. Environmental Protection Agency,'
   - Office of Research and Development, Duluth, MN.
USEPA. 1980a. Ambient water quality criteria for poly-
     nuclear aromatic hydrocarbons. EPA 440/5-80-
     069. U.S. Environmental Protection Agency, Of-
     fice of Science and Technology, Washington, DC.
USEPA.  1980b.  Ambient water quality criteria for
     aldrin/dieldrin.  EPA 440/5-80-019.   U.S. Envi-
     ronmental Protection Agency, Office of Science
     and Technology, Washington, DC.
USEPA.  1986.  Superfund public health evaluation
     manual. EPA/540/1-86/060. U.S. Environmental
     Protection Agency, Office of Emergency and Re-
     medial Response, Washington, DC.
USEPA.  1993.  Sediment classification methods com-
     pendium. EPA 823-R-92-006. U.S. Environmen-
     tal Protection Agency, Sediment Oversight Tech-
     nical Committee, Washington, DC.
van Tilborg, W.J.M., and F. van Assche.  1996.  Risk
     assessment of essential elements: Proposal for a
     fundamentally new approach. SETACNews 16(5),
     September 1996:
White, S.L., and P.S. Rainbow. 1985. On the metabolic
     requirements for copper and zinc in molluscs and
     crustaceans.  Mar. Environ. Res. 16:215.

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2-38
                           National Sediment Bioaccumulation Conference
                Question

    Can contaminant tissue residues in
    aquatic biota be used to define
    ecological risks to aquatic biota?
               Objectives
     O  To derive risk-based screening
        concentrations (RBSCs) for assessing
        ecological risks of chemical residues in
        aquatic biota tissues

     0  To confirm the utility of the RBSCs in
        ecological risk assessment

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•' Proceedings
                                     2-39
         A Newer Objective
      To directly quantify ecological risks from
      chemical residues in aquatic
      biota tissues
   Available Toxicity Reference
   Values in Aquatic Toxicology

    • Ambient water quality criteria (AWQC)
    • Sediment quality criteria

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2-40
National Sediment Bioaccumulation Conference
  The Fundamental Principle of
             Toxicology
  The magnitude of the toxic response is
  proportional to the toxicant concentration at
  the site of toxic action
         Tissue Screening
      Concentrations (TSCs)
  Whole body, wet weight tissue residues of
  chemicals which, if not exceeded, pose little
  chance of causing adverse toxicological or
  ecological harm to aquatic biota. TSCs are
  intended to be non-site or species specific.

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Proceedings
                                        2-41
     Uses of Tissue Screening
           Concentrations
       Primary use is as a screening tool to
       select chemicals of potential concern in
       ecological risk assessment

       Can also be used as the denominator in
       hazard quotient calculations
  Toxicological Basis for Tissue
    Screening Concentrations

                1CFOK model
  (integrating form assuming constant water concentration)
   Where:
    Cb= chemical cone, in biota (mg/kg)
    t  = time (hours)
    Cw= chemical cone, in water (mg/L)
    k™= chemical uptake rate constant (L/kg/hr)
    k" = chemical elimination rate constant (hour1)

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                       National Sediment Bioaccumulation Conference
 lexicological Basis for Tissue
   Screening Concentrations


  If it is further assumed that:

  O  The initial tissue residue is zero, and
  ©  The animal is at steady state
  The 1CFOK model reduces to...
      Calculation of Tissue
   Screening Concentrations
  Where:
  TSC =
  WQC =
  BCF =
        TSC = WQC x BCF
tissue screening concentration
water quality criterion (mg/L)
3% lipid normalized
bioconcentratipn factor (Ukg)

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Proceedings
                                          2-43
        Example TSC Values
    (All values mg/kg whole body, wet weight)
  Chemical
  Arsenic
  Cadmium
  4,4'-DDT
  Dioxin (2,3,7,8-TCDD)
  Mercury
  PCB
  Tributyltin
  1,2,4-Trichlorobehzene
TSC
1.6
0.042
0.054
0.00005
0.12
0.44
0.006
140
  TSCs currently available for over 150 chemicals
   "The direct prediction of chronic toxic
   effects from measured or predicted tissue
   residues requires validation before it can be
   widely endorsed."
   p.7-7, USEPA Sediment Classification
   Methods Compendium (1993)

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2-44
                            National Sediment Bloaccumulation Conference
    Performed literature review of measured
    tissue residues associated with
    toxicological effects. It currently contains
    about 1400 records, 490 literature citations,
    and information on 118 of the 152 chemicals
    for which TSCs exist
         Database Structure
    O Chemical name
    © TSC value
    © Residue concentration associated with
       effect
    O Species
    © Toxicological or ecological effect
    © Safety factor
    O Footnote
    © Literature citation

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                                       2-45
          Safety Factor


        Effect tissue concentration
                 TSC

Provides qualitative evidence of the level of
protection TSCs provide aquatic biota from
a specific effect. Also could be considered a
hazard quotient for the specified effect at a
given tissue residue.
     Criteria for inclusion in
              Database
  Had to report measured tissue residues
  Only papers reporting whole body residues
  No limitation on toxicological endpoint
  No limitation on route of exposure
  Included both laboratory and field studies
  Minor limitations on aquatic species
  included

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2-46
                         National Sediment Bioaccumulation Confe
            Distribution of
    Tissue Residue Literature
   Range of citations
        1-9
       10-19
       20-29
       30 - 39
       40-49
       50-59
        60+
No. of chemicals
     82
     20
     8
     3
     1
     2
     2
    Assumptions in Validating
            Utility of TSCs
    No difference in sensitivity of freshwater,
    estuarine or marine biota
    No differences in sensitivity of benthic,
    epibenthic or pelagic biota
    No differences in response of laboratory
    and field exposed biota
    Interested only in identifying risks to aquatic
    biota—TSCs  not designed to be protective
    of piscivorous birds and wildlife

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                                  2-47
     IT WORKS!
     (At least for most chemicals)
Results of Literature Review
 About 10% of results describe no observed
 effect at a given tissue residue
 For the entire database, 83% of adverse
 effects occur at concentrations above TSC
 values
 When chemicals which are rapidly
 metabolized to more toxic compounds are
 removed, 94% of reported effects occur at
 concentrations above TSC values

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2-48
                         National Sediment Bioaccumulation Conference
   Results of Literature Review
    Geometric mean TSC safety factor for
    entire database is 15

    Arithmetic mean TSC safety factor for
    entire database is 41
  Possible Approach for Chemicals
  Rapidly Metabolized to More Toxic
             Compounds

                 Aldrin
  TSC = 0.71 mg/kg
  2 of 2 records show adverse effects below
  TSC (4 no effect records)

                 Dieldrin
  TSC = 0.009 mg/kg
  0 of 19 records show adverse effects below
  TSC (1 no effect record)

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Proceedings
                                      2-49
 Care Must be Taken When Using

     TSCs in Risk Assessment

            Hexachlorobenzene
 •  TSC = 32 mg/kg
 •  Derived from USEPA AWQC of 3.68 ug/L
 •  9 of 10 records show adverse effects below TSC
    (11 no effect records)
 •  Deriving a TSC from the Canadian Water Quality
    Guideline of 0.0065 ug/L
 •  TSC = 0.056 mg/kg
 •  0 of 10 records show adverse effects below TSC
  Care Must be Taken When Using
     TSCs in Risk Assessment

  Copper and zinc are two examples where
  TSCs may be overly conservative

                  Copper
  TSC = 0.17 mg/kg, toxicity threshold at 3 mg/kg

                   Zinc
  TSC = 2.8 mg/kg, toxicity threshold at 20 mg/kg

  Many aquatic species can regulate their Cu and
  Zn burdens

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2-50
National Sediment Bioaccumulation Conference
     Methods for Quantifying
    Ecological Risks of Tissue
              Residues

   O  Hazard quotients
   ©  Apparent Effects Threshold (AET)
   ©  Effects on defined percentile
   O  Direct assessment
   0  Probabilistic risk assessment
        Results from Risk
           Assessments
        Performed to Date
  Tissue residue approach and TSCs have
  identified only chemicals of concern (COCs)
  which have also been identified as COCs by
  one or more other human health or
  ecological risk scenarios

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"Proceedings
                                         Z-Si
    Results Derived from Literature
 Review and Analysis of Safety Factors
    No significant difference in residue levels
    causing adverse effects in freshwater and
    marine biota (arsenic an exception)
    No significant difference in residue levels
    causing adverse effects in benthic and
    pelagic biota
    No significant difference in response of
    biota in field and laboratory exposures
 Comparison of Human Health Toxicity
  Reference Values to Ecological TSCs
 Compared TSCs to TRVs for a defined human
 health exposure scenario for seafood consumers
   Exposure frequency
   Exposure duration
   Body weight
   Target noncancer risk
   Target cancer risk
   Seafood ingestion rate
350 days/year
30 years
70kg
1
1x10*
6.5 grams/day

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                           National Sediment Bioaccumulation Conference
     Results of Comparing Human
  Health TRVs and Ecological TSCs

  O  Ecological TSCs were lower than human
      health TRVs for 61 to 67 (91%) of
      chemicals where a comparison could be
      made
  ©  Human health TRVs were lower than
      ecological TSCs for 36 of 42 (86%) of
      chemicals where a comparison could be
      made
             Conclusions

    Tissue residues of chemicals in aquatic biota
    can, for many chemicals, be used to directly
    assess ecological risks to aquatic biota

    Chemicals for which tissue residues cannot be
    used to quantify risks can be identified from
    mechanistic considerations

    The level of protection from adverse risk
    provided by the tissue residue approach is
    comparable to that provided by USEPA's ambient
    water quality criteria

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                                                           National Sediment Bioaccumu/ato'on Conference
 Day One:   September  11,  1996
Session Two:
Questions  and  Answers
A
fter each session, there was an opportunity for
questions and answers and group discussions per-
.taining to the speakers' presentations.
Q (Dave Michaud, Wisconsin Electric Power Company):
Dr. Rubinstein, on your last slide you referencedthe need
to perhaps establish a minimum criteria for reference site
selection. What are your thoughts in terms of groups of
chemicals, or on a chemical-specific basis?

Norm Rubinstein:

     Without having the residue effects data, we are
limited in regard to interpreting chemicals and concentra-
tions. I am talking more in terms of determining what
represents a healthy ecosystem.  What are the things we
are measuring that satisfy our  need to insure we are
maintaining environmentally consistent conditions? This
involves developing much broader databases, much like
is done hi the Puget Sound Dredged Disposal Analysis
(PSDD A) Program. From information developed by this
program, we know that the  benthic  communities are
functioning and the animals that are supposed to be there
are there.

Q (Dave Michaud): So, the  concept might be, for ex-
ample, going to an area where you have a healthy benthic
community, taking sediment samples, andanalyzing them
for a suite of possible contaminants.

Norm Rubinstein: >

     Right, and then using that as your point of compari-
son. This is known as a reference comparison.

Q (John Zambrano, NYS Department of Environmental
Conservation):  Dr. Rubinstein, in your definition of
reference sediment you have three components. The first
and the third could be in conflict. The first component is
one  that is  substantially free of contaminants, and the
third component reflects the site if no material had been
disposed of there. What do you do when they are in
conflict, and could you explain how those two compo-
nents relate to the purpose of using a reference sediment?

Norm Rubinstein:

     I will be the first to admit that I think the definition
does need to be revisited.  The intent, when we started
thinking about this issue, was to recognize the fact that
many of the areas that require maintenance dredging are
in highly industrialized and urbanized areas where the
benthic habitat has been degraded over long periods of
time.  We have never looked at  this program as a
remediation program. The intent was to insure that we do
not cause further degradation. So, as impractical as the
language sounds, it was hi fact a realistic way of getting
a handle on what was there.  We do have to go back, look
at this definition, and establish what we are now consid-
ering to be environmentally acceptable material.

Q (Gayle Garman, NOAA): Dr. Rubinstein, I am familiar
with the PSDD A program. I think it is interesting that you
hold that up as an example for us, and yet the data you
showed indicated that there was a lower survival rate for
the amphipods at the control or reference sites in Puget
Sound than for the other harbors. So, the Puget Sound
approach did not seem to be the most protective ap-
proach for the data that you showed us. I would also like
you to address the fact that you are talking about a
healthy benthic community, and what we are focusing on
here is bioaccumulation.[ A healthy benthic community
does not necessarily indicate whether or not there is a
potential for bioaccumulation.

Norm Rubinstein:

     Yes, amphipod mortality was a little higher in
Puget Sound and that is exactly the point of the utility of
a toxicity endpoint in a given species. Mortality at 20 or
23 percent in a test species may not be indicative of a
significant impact at a population level. When you look
.at the sediments in Puget Sound> it is my understanding
that for factors other than chemical constituents like grain
                                               2-53

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 2-54
                                                                National Sediment Bioaccumulation Conference
 size or ammonia, this is about the typical response in
 terms of the toxicity exposure for these animals. So, it is
 consistent with what I am saying, which is that percent
 mortality alone may not be a useful tool. Mortality has to
 be put into a more ecologically relevant context And I
 agree with your statement that a healthy benthic commu-
 nity does not necessarily indicate whether or not there is
 a potential for bioaccumulation.

 Q (Edward Zillioux, Florida Risk-Based Priority Coun-
 cil): Dr. Mount, I noticed that you said you limited your
 data collection to fish and invertebrates.  I realize that
 this is a tremendous undertaking and there may be
 logistical reasons thatyou did not go further. But I would
 recommend that  you  consider including wading birds,
 because not only do they provide  useful residue effect
 relationships that are in the literature, but they could also
 be a good link to higher trophic levels.  We looked at this
 for  mercury and found quite  useful relationships that
 showed up in work conducted by Don Porcella and Jani
 Benoit. And we also found that the residue effect rela-
 tionships derived from the field samples correlated fairly
 well with residue effects derivedfrom laboratory studies
 with a typical white rat and mallards.

 David Mount:

      You raise a good point. I should emphasize that our
 decision to limit our database to aquatic species was not
 any sort of biological judgment, but purely a logistical
 decision.  And you are absolutely right that there are lots
 of issues  regarding bioaccumulation that  extend well
 beyond the aquatic community.

 Q(Arthur Asaki, U.S. Army Center for Health Promotion
 and Preventive Medicine):  Dr. Mount, I congratulate
 your work in this area.  It is something that has been
 needed for a long  time, and I am glad somebody has done
 it. I looked at your data, your effect data and no-effect
 data, graphically represented.  You had yellow squares
for no-effect data and red diamonds for effect levels.
 There was quite a bit of overlap in those datapoints, which
 is to be expected. Later in your presentation, you showed
 a table for chlorpyrifos andkepone where the lowest effect
 level and the  highest no-effect level did not overlap.
 Could you explain that?

 David Mount:

     I will try to explain what I think you are asking. The
 figure I presented included all data that were reported for
 that chemical, regardless of whether it was just one data
 point or several datapoints. The tables showed results of
 individual studies. If you look at the sheepshead minnow
 data for kepone, you will see several entries for sheeps-
 head minnow in the table with different values for differ-
 ent studies. Each line of the table corresponded to a single
 study.  The comparisons were reduced to just effect/no-
effect pairs, in a sense kind of culling the data set, which
probably reduced some of the variability. But all sources
 of variability, such as intra-species and intra-experiment,
 were represented in the figure.

 Q (Maurice Zeeman): This question is for Dr. McCarty.
 There is a lot of talk going on  today about dose-
 response relationships and tissue residue-based para-
 digms for toxicity assessment. I was wondering if we
 are going to have to start looking at some of these old
 chemicals in new ways, because of some new ways of
 looking at endpoints.  Endocrine disrupters research
 is getting to be very interesting and it is suggesting, in
 essence, that dose-response relationships may not be
 all that important for these kinds of chemicals. When
 you are exposed to this trivial level of chemical maybe
 more important than giving it to an adult later on at a
 much higher level or at different levels.  What effects
 do you think that will have, if any,  in terms of looking
 at dose-response relationships, tissue residue concert-.
 trations, and bioconcentration?

 Lynn McCarty:

      I do not think that the endocrine modulator people
 really believe  they are going  to modify the basic
 assumptions of toxicology. The description, you pre-
 sented is that their perception  of dose response is
 giving a strong dose and getting  a strong response.
 Everything is clear and understood.  I think it is even
 more important in the sorts of things they are talking
 about for low level responses.  We are still talking
 about a dose response.  It is just down at low doses and
 at different endpoints than what we have previously
 looked ati  I do not think it is any different at all. The
 standard lexicological paradigm applies.  We do not
 have  to throw out the paradigm because we do not
 understand the specifics of this case.  I think the
 paradigm applies; we just have to get a greater under-
 standing of what is going on. I think we see the echoes
 of this problem with PAHs. The residue for PAHs is no
 longer a marker of exposure for the organism, because
 it is so readily metabolized that what you measure
 today is not what the organism got a year ago. It may
 not be the dose that was reflective of what is causing
 effects to the organism today. That is  the very same
 problem that the endocrine people are talking about,
 and it is simply the next level of effort.  We have been
 very lucky in that we have many  organic chemicals
 which are very recalcitrant to degradation, arid so they
 can serve as their own markers of exposure. For these
 chemicals, the tissue residue that we see today is fairly
reflective of the exposure that the organism received in
the past and, therefore, is recently attributable to the
effect that we see today. But we know there are situa-
tions where that does not occur. However,  it still does
not negate  the need to know what the dose was at the
time that the effect was initiated, and we have to
develop procedures for estimating that.  But I think
there are people suggesting to simply bypass the whole
scientific process and assessment of this. I think there
is good science to be done and, if you throw out dose

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Proceedings
                                                                                                    2-55
response, then you throw out all science that is appli-
cable to things.  That certainly can be done, but I am
not suggesting that.                               .

Q (Peter Chapman):  All chemicals are not the same for
a variety of reasons.  Do you think it is possible that we
will be able to develop body burden-to-effect relation-
ships for all chemicals within a reasonable time frame
with reasonable effort?  Or should we dedicate our
efforts to those chemicals we think we will be able to do
that for? Some of them may require so much effort and
time it may not be worthwhile.

Lynn McCarty:

      We are'not going to look at every chemical. There
is no question about that. I used the example I took from
the EPA laboratory in Duluth on the modes of action. I
think it is a brilliant piece of conceptual work in saying
that we, as lexicologists* have been oppressed by the
chemists for so long, because they are the.people doing all
of the chemical work and they always tell us the chemical
relationships in terms of chemical descriptors. Well, I am
a toxicologist and I want to have groupings according to
toxicology groupings. I do not care what the structure of
the chemical is. I want to know about the chemical based
on effects. That is.the first step in going hi that direction.
I think as we apply this tissue residue approach, it is going
to allow us to get better estimates of those things and
begin to categorize things on the basis of the effects that'
they have.  We will be able to classify those effects into
mechanistically related groups.  It will also allow us the
ability to look at mixtures, and hopefully that will allow
us to address larger, groups of things, conserve the limited
resources available, and still improve curability to do the
tasks that have been set for us.

Q (Phillip Rury, Arthur D. Little, Inc.):  Burt, since the tissue
screening concentration (TSC) method seems to have vali-
dated the pertinence  of aquatic water quality  criteria to
protecting aquatic biota from residue effects, how would
you respond to Lynn McCarty's assertion that the superior-
ity of chronic tests as a basis for regulatory criteria is a
 "myth?"    ,

Burt Shephard:

      I do not know if I would totally call it a myth. We
are really measuring different sides of the same coin.  If
we expose the animal to the same concentration of chemi-
cal for a longer time, you begin to see chronic effects first
And if you keep exposing that hypothetical animal to that
saine concentration for a longer and  longer time, you
keep bioaccumulating more and more chemical.  Eventu-
ally you will begin to run into acute toxicity, where you
will reach a lethal body burden and the animal will expire.
So, I think what we are really looking at is a temporal
difference involving how long organisms are exposed to
a given  concentration.  This is especially the  case for
chemicals that just keep on bioaccumulating the longer
we expose them. You can start to see chronic effects at
 low tissue residues. As you gain more and more residue,
 you begin to get mortality.

 Q (Phillip Rury): Lynn had not really elaborated on that
 comment, that zinger up there about it being a myth, and
• perhaps he would care to take this time to do so now?

 Lynn McCarty:

      What I was trying to caution against was the feeling
 that all we need is more chronic toxicity data and We will
 be able to solve all our problems. I definitely think that,
 is not the case. And I think that there are better ways of
 obtaining'that information than doing chronic toxicity
 testing in the way that we are doing it now. The point I
 am trying to make is that I think there are better ways of
 achieving the same end more cost-effectively using our
 knowledge,"rather than having to create specific data
 points  for every chemical and every situation that  we
 want to look at. Chronic toxicity testing will not be our
 salvation and it is not the holy grail. It has to be taken into
 context.           .

 Q (Peter Chapman): When I look at chemicals, including
 organics thai come in via lipids and metals that are taken
 up via evolutionary mechanisms for uptake, I view them
 for our purposes here in two ways. Some chemicals that
 accumulate in organisms can be measured and this
 information may  tell  us something we can relate  to
 effects. An example would be PCBs. Other chemicals,
 such as PAHs, accumulate in some organisms, but not in
 others because they are metabolized. Either we can look
 at the metabolites for organisms that  metabolize  the
 parent compounds or, as Jay pointed out, we can measure
 these chemicals in an organism that does not metabolize
 them.  But in addition  to that, within the group  of
 chemicals that accumulate in organisms without forming
 metabolites, there are also chemicals that are regulated
 and those that are not.  For instance,  consider  the
 essential metals. I think Burt made my point very well in
 his talk when he mentioned that copper and zinc proved
 to be problems for him.  They proved to be problems
 because he was using bioconcentration factors that will
 not work for essential metals. These organisms must take .
 up the essential metals  to survive,  and they will fight,
 against the concentration gradient to retain them. I am
 wondering if we really should not look at the way  the
 chemical acts. Maybe certain chemicals work better than
 others and we shouldfocus our attention on these. Some
 chemicals may be a lost cause, and we should not put our
 effort into them for a variety of reasons.  They have  got
 complications that we should leave until later to address.
 Is that a reasonable way to look at this situation, or do
 you  think, as a panel,  that we should just go for it as a
 whole lot? What are your feelings?

 Lynn  McCarty:              • •   '

       I think that the sort of thing you want to do is what
 Burt has done. I only wish that I had done what he  has
 done.   I would have at least liked to have had  the

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                                                                 National Sediment Bioaccumulation Conference
 opportunity, because I think it is an excellent example of
 how you both improve the understanding of the situation
 and point out the limitations. You have the opportunity to
 see where things work and, more importantly, to under-
 stand why they work.  It also allows you to focus on the
 exceptions, yet they happen to be particularly problematic
 based on other information. So, I think the general danger
 in doing any of this residue-based approach is simply that
 we are looking at the basic paradigm of toxicology dose
 response and are trying to get a better understanding of the
 dose so we understand where our response comes from.
 There are situations where trying to make the methodol-
 ogy apply to all chemicals will make it so incredibly
 complicated and expensive that it is almost impossible to
 do. We basically do as is done in the sediment program by
 applying a tiered-testing approach.  Essentially you focus
 on chemicals that can be addressed by simple assumptions
 with simple approaches. You only use more complicated
 evaluations and approaches to address the chemicals that
 do not fit into a simplified scheme. Understanding that
 they all are basically surrogates, it is simply a matter of not
 picking the right surrogate.  This is related to Maurice's
 point earlier about hormone modulators.  It does not
 negate the whole concept of the dose response in toxicol-
 ogy. It simply means  that the dose surrogate you were
 using is not good enough for this particular situation.

 Q (Peter Chapman): I know, but I think you are simply
 adding to my point that we need to be very careful and not
 delude people. If we do go to a tissue residue versus effects
 relationship,  this is  not going to work for everything.
 Tliere are going to be some exceptions, and I think some
 very important exceptions. People get deluded in their
 thinking when they look at some of the data, because we
 are not always clear that we are talking about organics,
 lipids, and relationships that may be a little easier, than
 say, for the essential metals. And we have to be very clear
 about this. I agree with you whole-heartedly about the
 tiering approach, but I think my working hypothesis at this
point is that we are going to reach the end of the rainbow.
Eventually, we will develop a relationship for some chemi-
 cals under some circumstances, between effects and tissue
body burdens.  But we will not successfully do it for a
number of others for a variety of reasons.

Lynn McCarty:

      I appreciate that, but I just wanted to point out that
I recognize that problem.  I have been very careful hi
writing about this to try not to make it a be all and end all.
The appropriate cautions or caveats are hi there. Whether
people actually see them, when they read it, is another
story. But at least I think it is very, very important to do
exactly what you said. The worst thing that could happen
is to present this as the solution to everything, because it
is not.

Burt Shcphard:

      I just might add to that a little.  There is certainly no
holy grail in  this  business.  Clearly, the tissue residue
 approach is not going to work for everything. If we want
 to take the time and effort and money to quantify residues
 of metabolites of PAHs that are related to adverse effects,
 we can certainly do that. But if, on'the other hand, we
 already have an approach in sediment quality criteria that
 seems to be pretty protective of our biological resources
 from the effects of PAHs, why do we need  to look at
 metabolites at all? We have a method that works, so we
 should use it. If we need to use multiple methods for the
 laundry  list of chemicals that we have to look at in this
 business, I certainly do not have a problem with using
 multiple methods.  We should use  sediment criteria
 where they are appropriate. If tissue residues work better
 for some chemicals or some situations, we should use
 them.

 Q (John Connolly, HydroQual, Inc.): I have a comment
 and then a question that I think is related to the comment.
 The comment is that we have been using the term "eco-
 logical risk assessment" a lot, and yet everything I have
 heard is really referring to some sort of screening  to
 evaluate chemicals of potential concern. I do not know if
 that is ecological  risk assessment as much as it is just
 deciding whether or not there is a potential problem at a
 site.  I  think we need to make that  distinction.  The
 question is directed to Dave Mount.  When we look at
 body burden relationships to toxicity, there have been
 some studies that have looked at relationships across the
 population, and they have shown that there is a range of
 body burdens.   So there is a sensitive organism  that
 responds at a low body burden, and then there is a very
 hardy organism that does not respond until you get to a
 very high body burden. That distribution of body burdens
 gives us information about population response  that
 presumably would allow us to take  the step beyond the
 screening tool to evaluate whether or not body burdens
 are potentially going to have a population effect.  Given
 the way are you structuring the database, are you going
 to incorporate some of that kind of information that may
 allow us to take that step?

 David Mount:.

      The answer, of course, is yes and no. There are several
 issues that you bring up. One is where there were ranges of
 concentrations for individual organisms within the popula-
 tion that were evaluated.   You can  consult the original
 citation to get more information on the ranges given in the
 database.  There is also some variation in the  literature.
 Studies either analyze the organisms that died, those that
 survived, or some combination thereof. Those notations are
 made hi the database, so we may be able to use this hi our
 analysis.  I really believe that one of the critical uses of the
 database  will be more as a  pointer to answer specific
 questions and less as the endpoint hi itself.
     I might diverge a little bit and address the previous
 question. Certainly we are looking very actively at tissue
residue-based approaches, but I think you have to bear in
mind a couple things. One is they are most effective when
you already have the tissue residue, which indicates they
are directly  applicable.  An  example would be  a

-------
 yrpceedlngs
                                              2-57
 bioaccumulation test that is done as part of a dredged
 material management monitoring program. A lot of the
 decisions that get made are not related, or are not dealt
 with, at the level of the tissue residue. You still have to
 bridge back to environmental concentrations that relate
 to, those residues. And that reopens the whole bag of
 worms that we were trying to avoid by jumping to tissue
 residues. So, we cannot fool ourselves that there are no
 problems, just because  some data that seemed disparate
 collapse when we look  at it on the basis of tissue residue.
 There is still the fact that those chemicals that collapse on
 the basis of tissue residue did not necessarily collapse on
 the basis of environmental exposure.
      So, the tissue residue approach is not so much a
 direct interpretive tool,  but  it may teach us  about
 groups of chemicals or making estimates of acute or
 chronic effect thresholds for chemicals that we have
 relatively little data for.  It does straighten out some
 QS AR relationships that were formerly based on water
 concentrations, but. were muddled by  differences in
 uptake or something else. And to me that is the real
 scientific importance of the concept. I think the direct
 regulatory significance is almost secondary.  We need
.to make use of all the  information we have. But there
 are a relatively small  number of instances where that
 information is necessarily directly relevant.  For ex-
 ample, in a risk assessment, if you have extremely high
 residues, you  have  some information about  existing
 risk,  Almost always what is of interest in a risk
 assessment is future risk or risk under various manage-
 ment alternatives. And unless you can link those up, it
 will not do all the good you want it to.

 Q (Hector Laguette, Brown and Root Environmental): A
 considerable amount of the discussion so far on tissue
 residues has been-based on lipid-normalized values, and
 I wonder  if any consideration has been given to the
 possible effect of the  contaminants themselves on the
 lipid metabolism of the organisms prior  to the moment
 when we do this normalization of concentrations. How
 may this artifact be affecting some of the approaches that
 we are talking  about?               ' •  -

 Burt Shephard:

      On the database that we compiled, less than 25 per-
 cent of the papers that we compiled reported the lipid
 content of the  species.  So, it is really hard to make a
 judgement, at least on  what I have looked at. I do not
 know how Dave feels about that.

 David Mount:

      Very true. Somebody mentioned this morning that
 if they report lipid data, there are some issues of how it
 was measured and how  relevant that measure may be. To
 support your point, I think Peter Landrum presented data
 this  morning to  show exactly how lipid metabolism
 affectedinterpretationofresidue-baseddata. In that case,
 lipid normalization tended to explain the variation rather
 than confound it. 'But, it is a relevant point.
Lynn McCarty:

     One of the things I have a great deal of concern
about is actual lipid normalization of toxicity test results.
It is perfectly reasonable to do it for bioaccumulation
purposes, but when you normalize whole body residue
levels to a standard lipid content, you are making the
assumption that the whole body lipid content is reflective
of the lipid content at the site of toxic action. This is not
an assumption I would care to make. And we have very
little information about that sort'of thing. So, I think you
have to be very cautious in normalizing the data when you
are talking about toxicity. However, Burt has done this
and I think it has worked out. But we are doing it out of
ignorance, not necessarily out of knowledge.  The fact that
it worked is not a reflection of whether it is right or not.
Maybe we were just lucky that time. Until we understand
that, we will have to be very careful about normalizing
toxicity data to lipid content.

Burt Shephard:

     I am not sure I would agree that it was luck. There
is good reason to suspect that it would work out, but it is
an assumption.  I will grant you that.

Q (Hector Laguette): I guess just from the point of view
of ecological risk assessment, it is one more of those things
that ends up being in  the uncertainty analysis.   It is
something that should be considered at the end.

Burt Shephard:       •  '.  '

     Another problem with lipid normalization is that
the lipid content of many species varies seasonally or
annually, so how do you take that into account as well?
The types  of lipids also vary.  There are a lot  of
assumptions. I do not know if I was lucky or if the
EPA data that I based my data on was good. It might
be a little bit of both.  In this case, it seemed to work
out, but there is. certainly  some concern  about lipid
normalization.

David Mount:

     I think one of the issues that really comes to the floor.
when we start talking about all these other variables is that
some of these principles work very well, in general, and
they make good predictions  of mean responses across
groups of chemicals. But there are subtleties in organisnial
factors, physical and chemical factors, or all sorts of other
things that cause individual chemicals to deviate from that
behavior. In a lot of regulatory programs, that deviation
is not considered acceptable. Making your best estimate
and constructing a worst reasonable case are  two very
different tasks. There are exceptions that people consider
to be quite relevant.  Some of these exceptions are not
accounted for in some of the very generalized models that we
useinthissortofanalysis. We all use log log plots, and the
noise around a log log plot is important to the decision that
gets made.

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2-58
                                                               National Sediment Bioaccumulation Conference
Bart Shephard:

     The decision is also based in part on what you are
going to use your data for. Dave and I both did literature
reviews, but, in some cases, we had very different criteria
as to how we decided a paper could or could not be used in
ourliteraturejustbecause we had different uses forthedata.

Q (Tom O'Connor,  NOAA):  I did have a question for
Burt Shephard that addresses this issue of how extensive •
the problem of coastal contamination is.  Your toxic
threshold concentration for cadmium, as I recall, was
about 0.04 parts per million. If I convert that to a dry
weight number, that is something like 0.2 parts  per
million. I think that number is exceeded by most of the
mussels and oysters in the United States.  Are we to
conclude that the contamination has put all these animals
at risk?

Burt Shephard:

     We have run  into the same problem.  I will use
cadmium as an example. I have spent part of the summer
up in the Aleutian Islands where very few point sources
occur. We have some blue mussel data from up and down
the Aleutian Island chain that we have been collecting for
background information for use in a risk assessment at a
military base closure site in the Aleutians.  As fate would
have it, the typical  cadmium concentrations are about
half a part per million. We have a number of mussels
from various sites with no known point sources over one
part per million. That may be just the natural background.
For some reason, the mussels seem to be doing fine there.
Something  I did not talk about at all, especially for
metals, is naturally occurring compounds.  It is very
important in the risk assessment to do a proper back-
ground comparison with your site data.  Background
comparisons can be done several ways. You can do the
mean of your sample population versus your background
population. You can also do, for lack of a better term, hot
spot comparison, comparing a high end mussel versus
some part of your distribution. You asked if I thought the
mussels are contaminated nationwide and showing ef-
fects. No, I do not. But very clearly, some other species
is going to show an effect at half a part per million. I
mentioned earlier that if you have species specific infor-
mation, that is obviously the  best way to do a  risk
assessment. If you havearange of data for blue mussels,
and you know thathalf a part per million cadmium causes
no  adverse lexicological or ecological effect on blue
mussels, then you would certainly use that in preference
to a tissue screening number.

David Mount:

     I think that addresses  a real hazard and what I
consider a real abuse of a lot of assessment tools. We had
a discussion last week about one-tailed and two-tailed
criteria. If you are below a one-tailed criteria, for ex-
ample, you are confident mat there is no effect. But there
is no implication of effect if you exceed that. If you look
at the derivation of the tissue screening number, they are
entirely one-tailed from the way that they were devel-
oped. There is no reason to infer effect from an exceed-
ance. In fact, if you look at the way water quality criteria
were developed and the way they were written, they are
really one-tailed criteria. But people consistently infer
effect from an exceedance of a criterion, which  is not
completely wrong. You should recognize, though, that
when you make that inference, you are buying into a set
of assumptions that may or may  not apply.  So, the
exceedance of one of the screening levels hi a healthy
organism should not come as a surprise to any of us. The
question is whether or not you consider the generaliza-
tions that went into the derivation of that number.

Q (Tom O'Connor): In that light at the other extreme, Jay
Field had a lot of data for PCBs in the fishes of the
Hudson River. Jay, what did you have for effects of these
PCBs?

Jay Field:

     We were comparing tissue concentrations of PCBs
to literature-derived effect concentrations for total PCBs
and dioxin, using dioxin equivalent values for coplanar
PCBs.  We did not measure effects in Hudson River fish
directly.

Q (John Haggard, General Electric Company}: Jay, one
of the things we are planning on the Hudson River is to
investigate and remediate active water column sources of
PCBs.   We believe they are influencing the top surface
sediments.  The subject of a lot of the- debate over the
years on remediation has been buried sediments,  which
have different PCB congener signatures. In your work,
Jay,  with the congeners and the fish, have you been able
to sort out the sources of the PCBs based on the congener
distributions, or are you still working on that?

Jay  Field:

     No, we did not attempt to distinguish among water
column, surface sediment or subsurface sediment sources.
I think you need other information to do that. You have
in-place sediment, recent releases of material through
ground water or non-aqueous phase layers as you have at
Bakers Palls. You also have sediment that is resuspended
and/or transported down river in every spring flood. So
separating out what is coming to the fish via the water
column (either suspended or dissolved) from recent re-
leases or sediment transport from past years is difficult to
determine based  on  congener pattern alone. But the
congener patterns in fish show a clear signal of what they
are exposed  to at different locations along  the river
gradient.

-------
                                             National Sediment Bioaccumulation Conference
 Session Three:
 Modeling Bioavailability of
 Sediment Contaminants
 Nelson Thomas, Panel Moderator
 U.S. EPA, Office of Research and Development,
 Duluth, Minnesota

 Dominic M. Di Toro
 HydroQual, Inc,
 Mahwah, New Jersey
 Equilibrium Partitioning and Organic Carbon
 Normalization

 Victor A. McFarland
 U.S. Army Corps of Engineers
 Waterways Experiment Station,
• Vicksburg, Mississippi
 Estimating Bioaccumulation Potential in Dredged
 Sediment Regulation

 Philip M. Cook
 U.S. EPA, Office of Research and Development,
 Duluth, Minnesota
 Development of Bioaccumulation Factors for
 Protection of Fish and Wildlife in the Great Lakes

 Mary C. Reiley
 U.S. EPA, Office of Science and Technology,
 Washington, DC
 From Modeling to Criteria: Integrated Approach to
 Criteria Development
                                    3-1

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                                                          National Sediment Bioaccumulation Conference
Equilibrium  Partitioning and  Organic
Carbon  Normalization
Dominic M. Di Toro and Laurie D. De Rosa
HydroQual, Inc., Mahwah, New Jersey
     Establishing sediment quality criteria (SQC) requires
     a determination of the extent of the bioavailability
     of sediment-associated chemicals., A full discus-
sion of the Equilibrium Partitioning (EqP) approach to
developing SQC is presented elsewhere (Di Toro et al.,
1991; USEPA, 1993). The main focus of this presenta-
tion is field observations of partitioning in sediments.
Consider a sediment sample that is segregated into vari-
ous size classes after collection. The particles in each
class were in contact with the pore water. If sorption
equilibrium has been attained for each class, then letting
Cs(j) be the particle chemical concentration of the jth size
class, it is true that
                                          (D
where foc(j) is the organic carbon fraction for each size
class j, KOC is the partition coefficient for sediment organic
carbon, and Cd is the pore water concentration. On an
organic carbon-normalized basis, this equation becomes
where Cjoc(j) =
                                          (2)
                       Tnis result indicates that the
organic carbon-normalized sediment concentration of a
chemical should be equal in each size class because Koc
and Cd are the same for each size class. Thus a direct test
of the validity of both organic carbon normalization and
EqP would be to examine whether C  (j) is constant.
across size classes in a sediment sample.
     Data from three field studies, Prahl (1982), Evans
et al. (1990), and Delbeke et al. (1990), can be used to
test this prediction. In Prahl's study,  sediment cores
were collected  at three stations near the. Washington
State coast (Stations 4, 5, and 7). These were sieved into
a silt-and-clay-sized fraction (<64 |jm) and a sand-sized
fraction (>64 |im).  This latter fraction was  further
separated into a low-density fraction (<1.9 g/cm3) and
the remaining higher-density sand-sized particles. The
concentrations  of  13 individual polycyclic aromatic
hydrocarbons (PAHs) were measured in each size fraction.
     It is important to realize that these size fractions are
not pure clay, silt, or sand, but are natural particles in the
                                                               Organic Carbon Fractions
                                                      100.0
                                                       10.0
                                                        .1.0
                                                        0.1
                                                                                   • Sta. 4
                                                                                   D Sta. 5
                                                                                   • Sta.'7
                                                                   LOW     SAND   SILT/CLAY

                                                                      Sediment Fraction


                                                                       Source: Prahl, 1982
Figure 1. Organic carbon fractions:
         Sediment fraction.
size classes denoted by clay, silt, and sand. The organic
carbon fractions,  shown on Figure  1, range from
0,2 percent for the high-density sand-sized fraction to
greater than 30 percent for the low-density fraction. This
exceeds two orders of magnitude and essentially spans
the range usually found in practice. For example, 90
percent of the estuarine and coastal sediments sampled
for the National Status and  Trends program exceed
0.2 percent organic carbon (NOAA, 1991).
     Figure 2 (top) compares the dry weight-normalized
clay/silt-sized fraction sediment PAH  concentrations,
Cs(j), to the sand-sized high- and low-density PAH conr
centrations on a dry weight  basis.  The dry weight-
normalized data have distinctly different concentrations—
the low-density high-organic  carbon fraction is highly
enriched, whereas the sand-sized fraction is substantially
below the clay/silt fraction concentrations.  Figure 2
(bottom) presents the same data but on an organic carbon-,
normalized basis, Csoc(j).  In contrast to dry weight
normalization, the PAH concentrations are essentially
                                               3-3

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3-4
                                                                National Sediment Bioaccumulation Conference
                           Dry Weight Normalization

              Sand vs Clay/Silt                     Low Density vs Clay/Silt
     1000

 ?
 $   100

 i   10


       1
                10      100
              PAHfrgfgdiywt)
                              1000
                                       10000


                                        1000


                                        •100


                                         10
                                                  10      100
                                                 PAHfpg/gdiywt)
                                                                 1000
                         Organic Carbon Normalization
   100000

  g-10000
              Sand vs Clay/Silt
                                               Low Density vs Clay/Silt
     1000
      100.
        100
               1000    10000   100000
               PAH (na'g oc)
                               Source: Prahl, 1982
                                            100
Figure 2. Dry weight normalization and organic carbon normalization.
the same in each size class, as predicted by Equation 2.
The lines in Figure 2 represent equality and have been
added as a visual aid.
      In the field data from Evans et al. (1990), sedi-
ments were  collected at five sites along the River
Derwent, Derbyshire, United Kingdom, and separated
into six sediment size classes. The size
classes were representative of clay and
silt (<63 |im) to coarse sand (1.0 to 2.0
mm). Organic carbon content and total
PAH  were measured in each sediment
size class.  Figure 3 presents the size
classes  and associated organic  carbon
content.  Evans et al. attribute the bimor
dal distribution of f^. to  two types of
organic matter. Organic  matter in the
1.0 to 2.0 mm size class  may be from
fragmentary  plant  material,  while  the
size classes less than 500 pm have organic
carbon content that is'the result of aging
humic material. The organic content in
this study ranges from 2.0  to 40 percent.
      Figure 4 presents a comparison of
PAH concentrationfordifferentsediment
classes for dry weight normalization and
organic carbon normalization. The top
left panel compares PAH concentrations
on sand  (63-500  |im)  and clay/silt
(<63  um) on a dry weight basis.  The
top  right  panel  compares  PAH
                  dry weight basis.  The data indicate
                  that the PAH concentration is higher
                  in the coarse sand fraction of sedi-  '
                  ment. Recall from Figure 3 that the
                  clay/silt and coarse sand  fractions
                  contain higher fraction organic car-
                  bon content.  The bottom panels of
                  Figure 4 present the organic carbon-
                  normalized comparison of PAH con-
                  centrations by sediment class.  For
                  both panels,  the organic carbon-nor-
                  malizedPAH concentrations are simi-
                  lar regardless of the sediment size
                  class as predicted by Equation 2. The
                  lines in Figure 4 represent equality and
                  have been added as a visual aid.
                       Lastly, Delbeke et al.  (1990)
                  collected sediments from seven sites in
                  the Belgian continental shelf and the
                  Scheldt estuary.  These sites were
                  analyzed for eight polychlorinated
                  biphenyl (PCB) congeners and organic
                  carbon in the bulk sediment and clay/
                  silt (<63  um) sediment fraction.  In
                  addition, analyses of the samples were
                  done to determine the percent of size
                  fractions ranging from 500 um to 3 um
                  that made up the sample. The PCB
               -  congeners tested for in this study were
IUPAC numbers 28,52,101,118,153,138,170, and 180.
      Using concentrations reported for bulk samples,
concentrations for clay/silt samples, and  percent size
fractions of each  sample, calculations  were done to
estimate concentrations on the  >63 um portion of the  .
sample.  Similar calculations were done to determine
                                                  1000    10000   100000
                                                  PAH (ng/g OC)
                                                                Organic Carbon Fractions
                                             10
                                         J
                                                   DstaC   0StaH
                                                   • staDa  IZJStaK
                                                   BstaG
                                                     63 ^m   63-125 \m  125-250 pm 250-500 pm  ,0,5-1 mm   1-2 mm


                                                                SEDIMENT SIZE CLASS



                                                                  Source: Evans et al., 1990
concentrations   on   coarse   sand  p.      3  Q      carfe   fractions. Sediment size class.
(0.5-2.0 mm) and clay/silt (<63 um) on a    6           &

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Proceedings
                                                                                              3-5
                             Dry Weight Normalization
     1000
      100
              Sand vs Clay/Silt
  I
  1
       10
      0.1
                                             1000
                                          =-   100
                                          Course Sand vs Clay/Silt
                                      10
                                              0.1
        0.1
               1     10    100
              PAH (tig/g dry wt)
                       1000
                                       0,1     1     10    100
                                             PAH(ng/gdrywt)
                               1000
   10000
  _ 1000
  1  ioo
      10
                           Organic Carbon Normalization
             Sand vs Clay/Silt                         Course Sand vs Clay/Silt
E O 63-125 urn
- A125-250 (i
-V 250-500 urn
                                           10000
_ 1000
                                 !
                                 I
   100
                                              10
              10    100    1000
               PAHfrg/gOC)
                       10000
                                Source: Evans et al., 1990
                                             10    100    1000
                                               PAH (ng/g OC)
                              .10000
Figure 4.  Dry weight normalization and organic carbon normalization.
      Figure 5 presents the
 percent organic carbon on the
 <63 nm portion of the sample
 (blackbar)andonthe>63 um
 portion of the sample (white
 bar). Comparisons of the PCB
 congener concentrations on a
 dry weight basis (top) and on
 an organic carbon basis (bot-
 tom) are shown in Figure 6.
 Organic carbon content in the
 >63 um class size at stations
 2 and 4 is 0.01 percent  and
 0.06 percent, respectively, as
 indicated in Figure 5.  The
 data for these  stations  are
 shown on Figure 6 using
 filled  symbols.   Though an
 foc >0.2 percent has been pre-
 sented as the value for which
 organic carbon normalization
 applies; normalization at
' these f^ values seems appro-
.priate for this data set.
      The top panel of Fig-
 ure 6 indicates no evident re-
 lationship between PCBs in
 the <63 um sample andPCBs
 in the >63 |jm sample oh a dry
 weight basis. When concen-
               Organic Carbon Fractions
        100 F
        10 ;
          1 =
   J
       0.01
       0.001
= 1 1
1 1 1 1 =
: P >63nm • • -
I
1 <
63
\im
-
-

-i •'
' =
           0.1    2   3    4    56    7-8

                         Station


                 Source: Delbeke et al., 1990
Figure 5. Organic carbon fractions:  Station.

organic carbon content on the >63 um portion of the
sample.  Organic content varied from 0.01 percent to
10 percent inclusive of both <63 um and >63 jam portions
of the sediment.
                                              trations in either class size, are normalized to organic
                                              carbon content, the concentrations are similar for both
                                              class sizes as shown in the bottom paneL This indicates
                                              that PCB concentrations are similar across sediment class
                                              sizes, which supports organic carbon normalization. The
                                              lines in Figure 6 represent equality and have been added
                                              as a visual aid.
                                                   .The data from Figures 2, 4, and 6 are analyzed to.
                                              quantify the reduction in variability when the data are
                                              carbon-normalized. The variation of the y-axis values
                                              from the line of unity presented hi Figures 2, 4, and 5
                                              represents the residual difference 6f the y values from the-
                                              x values. Coefficients of variation for these residuals are
                                              presented in Figure 7 for dry  weight- (black bar) arid
                                              organic carbon-normalized (gray bar) data. The coeffi-
                                              cients of variation  are reduced significantly.  It can be
                                              concluded from the data of Prahl (1982), Evans et al.
                                              (1990), andDelbeke etal. (1990) that the organic carbon-
                                              normalized PAH and PCB concentrations are relatively
                                              independent of particle size class and that organic carbon
                                              is the predominant  controlling factor hi determining the
                                              partition coefficient of the different  sediment size par-
                                              ticles hi a sediment sample. The organic carbon concen-
                                              tration of the high-density sand-sized fraction in Prahl's
                                              data  (0.2 to 0.3 percent) suggests that  organic  carbon
                                              normalization is appropriate at these low levels. The data
                                              from Evans et al.  suggest that EqP can be applied to
                                              organic carbon originating from more than one source, '
                                              that is, fragmentary plant matter and aging humic material.

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3-6
                                                               National Sediment Bioaccumulation Conference
            Dry Weight Normalized
 CO
 to
  A
     100
      10
      0.1
 o  0.01
 o.
Q QQ-| IX I tllHtK 1 MMfHI  I I M I1W  I I I IMHI  1 I.

   0.001   0.01    0.1    1     10
                                     I1H

                                     100
              PCB (ng/g) <63 |
          Organic Carbon Normalized
        0.1    1     10    100   1000   10000

            PCB (ng/g OC) <63 urn

               Source: Delbeke etal., 1990
References

Delbeke, K., RJ.  Claude, and M. Bossicart.  1990.
     Organochlorides in  different fractions of sedi-
     ments and different  planktonic compartments of
     the Belgian Continental Shelf and Scheldt Estuary.
   --Environ. Pollut. 66:325-349.
Di Toro, D.M., C. Zarba, DJ. Hansen, W. Berry, R.C.
     Swartz, C.E. Cowan, S.P. Pavlou, and H.E. Allen.
     1991.  Technical basis for establishing  sediment
     quality criteria for nonionic organic chemicals us-
     ing equilibrium partitioning.  Environ. Toxicol.
     Chem. 10:1541-1583.
Evans, K.M., R.A. Gill, andP.WJ. Robotham. 1990. The
     PAH and organic content of sediment particle size
     fractions. Water Air Soil Pollut.  51:13-31.
NOAA. 1991. National Status and Trends Program—
     Second summary of data on chemical  contami-
     nants in sediments from the National Status and
     Trends Program. NOAA Technical Memorandum
     NOS OMA 59. National Oceanic and Atmospheric
     Administration, Office of Oceanography and Ma-
     rine Assessment, Rockville, MD.
Prahl, F.G.   1982.  The  geochemistry of polycyclic
     aromatic hydrocarbons  in  Columbia River and
     Washingtoncoastalsediments. Ph.D.thesis. Wash-
     ington State University, Pullman, WA.
USEPA.  1993.  Technical basis for deriving sediment
     qualify criteria for nonionic organic contaminants
     for the protection of benthic organisms by using
     equilibriumpartitioning. EPA822-R-93-011. U.S.
     Environmental  Protection Agency, Office of
     Water, Washington,  DC.
Figure 6.  Dry weight  normalized  and  organic
           carbon normalized.
           1000
                     Prahl, 1982      Prahl, 1982     Evans et al., 1990   Evans etal., 1990   Delbeke et at., 1990
                    Sand vs Clay/Silt  Low Density vs Clay/Silt Sand vs Silt/Clay Coarse Sand vs Clay/Silt  >63 urn vs <63 urn


                                  B- Dry Wt Normalized Concentrations
                                  - Organic Carbon Normalized Concentrations
Figure 7.  Coefficients of variation.

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                                                         National Sediment Bioaccumulatlon Conference
Estimating  Bioaccumulation Potential
in  Dredged  Sediment Regulation
Victor A. McFarland
U.S. Army Corps of Engineers Waterways Experiment Station, Vicksburg, Mississippi
     The bioaccumulatipn potential of neutral organic
     chemicals in dredged sediments is estimated from
     sediment chemistry.. A simple model is used in
which concentration data are normalized on sediment
organic carbon and organism lipid and a biota/sediment
accumulation factor (BSAF) is applied. This presenta-
tion describes an experiment comparing predicted with
actual measured tissue concentrations of polynuclear
aromatic hydrocarbons (PAH) bioaccumulated from sedi-
ments by the clam Macoma nasuta.
Testing Requirements

     Open water disposal of sediments dredged for
navigation purposes in the United States is regulated
under provisions of section 103 of the Ocean Dumping
Act (Marine Protection, Research, and Sanctuaries Act,
MPRSA, of 1972) and section 404 of the Clean Water Act
(CWA of 1972). Both laws require that the potential for
bioaccumulation of toxic chemicals associated  with
dredged sediments be assessed as part of the regulatory
process when such chemicals are suspected or known to
be present. The guidance manuals for Implementation of
the laws use a tiered approach (USEPA/USACE, 1991,
1994). In the  first tier, historical data, if it exists, is used
to judge whether there  is  a reason to believe that
bioaccumulating chemicals may be present and may be,
bioavailable to exposed organisms. In the second .tier,
bioaccumulation potential is estimated from sediment
chemistry data.  If the potential for bioaccumulation
appears to exist, then 28-day laboratory' exposures of
benthic organisms and analysis  of their tissues  may
follow in the  third tier. A fourth tier exists for  special
situations in which a decision could not be made in any
earlier tier.
Theoretical Bioaccumulation Potential

     The Tier II sediment screening test is referred to as
"Theoretical Bioaccumulation Potential" (TBP) and is
based on equilibrium partitioning. TBP is used only for
neutral organic chemicals and is simply the application of
a BSAF to sediment concentration data in order to estimate
the concentration that would result in an organism ex-
posed to the sediment as its only source of contamination.
In aquatic systems, neutral organic chemical contami-
nants such as the PCBs, PAHs, dioxins, etc. primarily
partition to the organic carbon of sediments and the lipids
of biota. Recognition of this fact led to the convention of
normalizing concentrations of neutral chemicals in sedi-
ments on  the basis of their total organic carbon (TOC)
content and similarly normalizing concentrations in biota
on the basis of their lipid content. BS AFs are the ratio of
the normalized concentrations.  Multiplying the TOC-
normalized concentration of a neutral chemical in sedi-
ment by the BSAF provides an estimation of the steady-
state body burden of that chemical in a sediment-exposed
organism:
     TBP = 4(Cs/%TOC)%L
(1)
where Cs = concentration in- whole sediment, L = tqtal
ex'tractabie lipids in an organism of interest, and "4" is the
value assigned representing a generalized BSAF for all
neutral chemicals and biota.
     In theory, the BS AFs for individual neutral chemi-
cals should not differ greatly from one another and can be
approximated by a single value. However, the model is
a simplification that does not accOunt for differences hi
bioavailability, the metabolism of compounds, disequi-
librium and non-constancy of exposure, organism feed-
ing behavior, or any of the other kinetic or measurement
processes that influence bioaccumulation. As such, TBP
is protective but not necessarily predictive.
Empirical BSAFs

     B S AF data are compiled in a database accessible by
modem through an electronic Bulletin Board System at
the U.S. Army Corps  of Engineers Waterways Experi-
ment Station, Vicksburg, MS (The Contaminants BBS,
601-634-4380).  Entries include data on organism lipid
content, lipid extraction method, organic carbon content
of sediment, length of exposure, etc., and the source of the
data is given. The data are severely skewed, with most
                                             3-7

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3-8
                                                              National Sediment Bioaccumulatlon Conference
BSAF values reported as less than 1.0. The frequency
distribution of all BSAF entries presently in the database
is shown in Figure 1. These data contrast sharply with the
universal AF used in the Tier IITBP calculations.  The
universal  BSAF (4) is at the 94th percentile of the
database and is about 12-fold greater than the median. .
Table 1 shows the medians and the interquartile ranges of
the BSAFs in the database by group.  It can be seen that
the medians for the chlorinated groups (PCBs, dioxins/
furans, other chemicals) did not differ statistically. How-
ever, the median PAH BSAF ranged 16- to 22-fold lower
than any of these and is lower than the universal BSAF by
a factor of 125. The BSAF data were compiled with the
expectation that their use in  Tier II dredged sediment
bioaccumulation potential calculations would provide
more predictiv^estimations than does the current practice.
This assumption was tested using the priority pollutant
PAH data of two studies conducted at the Waterways
Experiment  Station (McFarland et al., 1994a, 1994b;
McFarland,  1995).
Field Study

      Sediments and their resident infaunal and benthic
polychaetes and bivalve mollusks were collected at a
location on the continental shelf of the New York Bight
Apex. The location had low, but in most cases detectable,
concentrations of PAH compounds.   Sediment TOC
content averaged 0.5 percent in the four samples taken.
The biota were pooled by taxonomic group and their
tissues analyzed for PAHs and for lipids.  Three to five
replicates of the seven taxonomic groups were possible,
resulting in a total of 24 samples.  The sediment and
organism PAH data were used to calculate BSAFs for the
15  individual PAHs and  for the total of the 15 using
"Bootstrap" estimation methods (Manly, 1991).
Laboratory Study

      Two sediments were collected in the San Francisco
Bay system. One was surficial material from the central
Bay (designated "Reference") and the other was from an ,
inner harbor turning basin known to be contaminated
(designated "Contaminated"). The total PAH concentra-
tion of Reference was about  1.6 (jg g"1  and that of
Contaminated was about 50 |ag g'1. TOC contents were
similar (0.926  and 1.10 percent).  Bentnose clams,
Macoma  nasuta, were  collected from a clean  area
(Tomales Bay, California) and exposed to the sediments
in a flow-through facility for 28 days. Exposures were to
either bedded sediment or to sediment continuously
suspended at about 50 mgL"1. At the end of the exposures
the tissues of the clams were analyzed for the 15 priority
pollutant  PAHs, as in the field study  sediments and
organisms. Lipids were also measured.
      Bioaccumulation potential of the PAH compounds
in the San Francisco Bay sediments was estimated using
the TBP model and the PAH BSAFs generated by the
New York Bight field study.  The lipid input data were
 the mean concentrations of lipids in the Tomales Bay
 clams at the end of the 28-day exposures in each treat-
 ment.  The predicted (TBP) PAH  concentrations are
 plotted against the concentrations measured at the end of
 the 28-day exposures in Figure 2  for the Reference
 sediment and Figure 3 for the Contaminated sediment.
 Vertical and horizontal bars and caps  are standard errors.
 The diagonal line represents perfect agreement between
 predicted and observed concentrations.  Observations
 falling below the line are cases in which measured values
 exceed predicted. Observations above the line are the
 reverse. Overestimates and underestimates are nearly
. equal in the Reference sediment exposures (15  and 17,
 respectively) and are equal in the Contaminated sediment
 exposures (16 and 16).
      Figure 4 identifies the PAH compounds and shows
 the distribution of the ratioed means. In the Reference
 sediment exposures, 56 percent of the predicted concen-
 trations were within a factor of 2 of the measured concen-
 trations.  In  the Contaminated sediment  exposures,
 63 percent were within a factor of 2.  For the Reference,
 72 percent were within a factor of 3 and 75 percent of the
 Contaminated were within a factor of 3. PAH compounds
 for which the predicted/measured  concentration ex-
 ceeded or was less than a factor of 3 were acenaphthylene,
 naphthalene, fluorene, dibenz[a,h]anthracene, andpyrene
 in the Reference sediment exposures. In Contaminated
 sediment exposures similar results  were observed for
 acenaphthylene, anthracene, fluorene, and indeno[ 1,2,3-
 cd]pyrene.  Only for anthracene, fluorene, and naphtha-
 lene  were statistically significant (P<0.05)  differences
 found when t-tests were performed comparing the boot
 strap mean ,TBPs  with the  mean  measured  28-day
 concentrations.
      Although there were individual cases showing large
 differences between predicted and measured concentra-
 tions, Figures 2 through 4 reveal numerous close corre-
 spondences. In the case  of the total (of the 15) PAH, the
 'effect of averaging over- and underestimations results hi
 very good correspondence. For the totals, the poorest
 correspondence was 0.76 for the suspended Contami-
' nated sediment exposures, and the  closest correspon-
 dence was a ratio of 0.97 for total PAH in the suspended
 Reference sediment exposures.
 Acknowledgments

      This work was sponsored by the U.S. Army Corps
 of Engineers Long-term Effects of Dredging Operations
 Program. Permission was granted by the Chief of Engi-
 neers to publish this information.
 References

 Manly, B.F.J.  1991.  Randomization and Monte Carlo
      methods in biology. Chapman and Hall, New York,
      NY.
 McFarland, V.A.   1995.  Evaluation of field-gen-
      erated accumulation factors predicting the

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Proceedings
                                             3-9
     bioaccumulation  potential  of  sediment-
     associated PAH compounds.   Technical Report
     D-95-2. U.S. Army Corps of Engineers Waterways
     Experiment Station, Vicksburg, MS.
McFarlarid, V.A., G.H. Lutz, and F.J. Reilly, Jr. 1994a.
     Bioaccumulation data and analysis  for selected
     contaminants in sediments and biota of the New
     York Bight Apex Mud Dump Reference Site. Re-
     port to U.S. Army Engineer District, New York.
McFarland, V.A., J.U. Clarke, C.H. Lutz, A.S. Jarvis,
     B. Mulhearn, andFJ. Reilly, Jr. 1994b. Bioaccu-
     mulation potential of contaminants from bedded
     and suspended Oakland Harbor Deepening Project
     sediments in San Francisco Bay flatfish and bi-
     valve  mollusks.   Miscellaneous -Paper EL-94-7.
     U.S. Army Corps of Engineers Waterways Experi-
     ment Station, Vicksburg, MS.
USEPA/USACE. 1991. Evaluation of dredged material
     proposed for ocean disposal (testing manual).
     EPA-503/8-91/001. USEPA Office of Marine and
     Estuarine Protection, Washington, DC.
USEPA/USACE. s [1994]. Evaluation of dredged mate-
     rial proposed for discharge  in inland and near
     coastal waters (draft) (Inland testing manual).
     USEPA Office  of Water, Washington, DC. In
     review.

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3-10
                                        National Sediment Bioaccumulation Conference

TABLE 1. DESCRIPTIVE STATISTICS
AND COMPARISONS OF GROUPED
DATA
Group
All BSAF
Invertebrates
Fish
Field Studies
Laboratory Studies
PCBs
PAHs
Dioxins/Furans
Other Chemicals
n
689
608
81
492
197
404
110
129
46
Median
BSAF
0.520
0.440
1.600
0.337
0.670
0.718
0.032
0.514
0.598
25%ile
0.139
0.101
0.735
0.065
0.428
0.230
0.006
0.269
0.065
75%ile
1.453
1.120
2.600
1.525
1.393
1.820
0.299
1.275
1.800
t-test
on
rankits
A*
A
B
A
C
C
D
C
AC
*Groups with same letter are not significantly different, P < 0.05

      FIGURE 1. FREQUENCY DISTRIBUTION OF BIOTA/SEDIMENT
 ACCUMULATION FACTORS (BSAF) IN CONTAMINANTS BBS DATABASE
              140
           UJ  100-1
           H
           5  so :
           111
           CQ  40
           &
           Z>  20 -

                0
            n = 689
            median = 0.520
                       _TL
                  0.0
1.0
2.0
3.0 '  4.0
BSAF
5.0
6.0  .7.0

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Proceedings
                                                                 3-11
  FIGURE 2.TBP-PREDICTED vs MEASURED PAH BIOACCUMULATION IN

             CLAMS EXPOSED TO REFERENCE SEDIMENT
                          Bedded Sediment

                          Suspended Sediment
                      0.01    0.1      1      10


                          Measured Concentration, ng g"
  FIGURE 3. TBP-PREDICTED vs MEASURED PAH BIOACCUMULATION IN

            CLAMS EXPOSED TO CONTAMINATED SEDIMENT
8
=0"
                   10000
                 O)
                 O)  1000 -
                 £=


                 .g

                 CO  100 -
                 •I— •



                 I
                 o
                 O
     10 -
                      1 H
                     0.1
                       0.1
                           •  Bedded Sediment

                           •  Suspended Sediment
                                  Line of Unity
                                  10
                                        100
                                             1000
                                                   10000
                          Measured Concentration, ng g
                                                ,-t

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3-12
                       National Sediment Bloaccumulation Conference
    FIGURE 4. AGREEMENT BETWEEN PREDICTED AND MEASURED
          BIOACCUMULATION: TBP/TISSUE CONCENTRATIONS
 acenaphthene
acenaphthylene
   anthracene
benz[a]anthrace
benzo[a]pyrene
benzo[b+k]fluor
 benzo[g,h,i]per
    chrysene
 dibenz[a,h]ant
  fluoranthene
     fluorene
indeno[1,2,3-cd]
  naphthalene
 phenanthrene
     pyrene
Total of 15 PAH
                -  D AJ7
                          O

                          a
a
                       P)
                -  (D
                      OL$7
                         O
                         . a o
                        ^ o
                              A
                         D REF-BEDDED
                         O REF-SUSPENDED
                         A CONTAM-BEDDED
                         V CONTAM-SUSPENDED
     AV
                               a
                   o
                 -101  2  3  4  5  6  7  8  9  10 11  12  13  14
                 PREDICTED/MEASURED BIOACCUMULATION

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Proceedings
3-13
    ESTIMATING BIOACCUMULATION
    POTENTIAL IN DREDGED SEDIMENT
    REGULATION
    Victor A. McFarland

    USAE Waterways Experiment Station
    Vicksburg, Mississippi
     OPEN-WATER DREDGED
     MATERIAL DISPOSAL IS
     REGULATED BY:

     • Section 103 of PL-532 of 1972, the
       Marine Protection, Research and
       Sanctuaries Act (coastal waters)
       !                -
     • Section 404 of PL-530 of 1972, the
       Clean Water Act (inland and coastal
       waters)

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3-14
                              National Sediment Bioaccumulation Conference
        THE IMPLEMENTATION MANUALS
      USE A TIERED-TESTING APPROACH
       TIER I

       TIER II

       TIER III

       TIER IV
    HISTORI
  "REASON
28-DAY BIOACCUMULATION TEST
  (MEASURE OF RELATIVE
   BIQAVAILABILITY) J „
DEFINITIVE BIOACCUMULATION
    (STEADY STATE}
       APPROPRIATE USE OF TBP:
       "The TBP calculation in Tier II is applied
       as a coarse screen to predict the magnitude
       of bioaccumulation likely to be associated
       with nonpolar organic contaminants in the
       dredged material."*
   'Draft Inland Testing Manual, June 1994, p. 120.

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Proceedings
                                         3-tS
        TBP:

        Is based on equilibrium partitioning
        Applies only to neutral chemicals
        Uses sediment chemistry data
        Normalizes concentration data on:
        > Organic carbon in sediments
        > Lipid in exposed organisms
    EQUILIBRIUM PARTITIONING

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3-16
National Sediment Bioaccumulation Conference
SOLUBILITIES OF SOME ORGANIC SOLUTES
IN ORGANIC SOLVENTS OR IN WATER, g/mL




NAPHTHALENE
PHENANTHRENE
LINDANE
DDT
TOLUENE
OR
BENZENE

0.29
0.42
0.29
0.78

OLIVE OIL
OR
PEANUT
OIL
0.13
NA
NA
0.11

CHLORO-
FORM


0.50
NA
0.24
NA
•
CARBON
TETRA-
CHLORIDE

0.50
0.42
NA
'0.45

WATER



8.80E-7
1.06E-9
1.70E-9
3.10E-12





              TBP = 4(Cs/%TOC)%L

  TBP  =  Estimated tissue concentration
  4     =  An "appropriate" bioaccumulation
           factor
  Cs    =  Chemical concentration in sediment
  TOC  =  Sediment total organic carbon
  L     =  Organism lipid

        #The factor, 4, is a universal
         biota/sediment accumulation
         factor (BSAF)

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Proceedings
                                                                   3-17

DESCRIPTIVE STATISTICS AND
COMPARISONS OF GROUPED DATA
Group
AH BSAF
Invertebrates
Fish
Field Studies
Laboratory Studies
PCBs
PAHs
Dioxins/Furans
Other Chemicals
n
689
608
81
492
197
404
110
129
46
Median
BSAF
0.520
0.440 '
1.600
0.337
0.670
0.718
0.032
0.514
0.598
25%ile
0.139
0,101
0.735
0.065
0.428
0.230
0.006
0.269
0.065
75%ile
1.453
1.120
2.600
f.525
1.393
1.820
0.299
1.275
1.800.
t-test
on
rankits
A*
A
B
A
C
C
D
C
AC
*Grdups with same letter are not significantly different, P < 0.05

      TWO STUDIES:
      East Coast
      Field study
      Collected benthic infauna
      and sediments
      Analyzed both and
      calculated BSAFs
West Coast
Lab study.
Collected high and low
contamination sediments
and analyzed
Collected mussels and
clams from clean site
Used field study BSAFs to
calculate TBPs
Exposed bivalves to the
sediments
Compared TBP estimations
with actual bioaccumulation

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3-18
                            National Sediment Bloaccumulation Conference
   MEANS COMPARISONS

   • Performed t-tests on bootstrap mean TBP
    and measured mean 28-day tissue
    concentration for each compound in each
    treatment
   • 5-6 replicates of each treatment
   • 1,024 bootstrap iterations for each
    comparison
   • only anthracene, fluorene, and naphthalene
    were significantly different at P < 0.05
     CONCLUSION

     • For PAH compounds and probably for
       other neutral organics empirical
       BSAFs can provide reasonably good
       estimates of bioaccumulation
       potential
     • Estimates for total PAHs are very
       good

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                                                          National Sediment Bioaccumulation Conference
Development  of Bioaccumulation
Factors  for  Protection of Fish  and
Wildlife  in  the Great  Lakes
 Philip M. Cook and Dr. Lawrence P. Burkhard
 U.S. Environmental Protection Agency, Office of Research and Development,
 Duluth, Minnesota                .
      Bioaccumulation factor (B AF) development for ap-
      plication to the Great Lakes, and in particular for
      the recent Great Lakes Water Quality Initiative
 (GLWQI) effort of U.S. EPA and the respective Great
 Lakes states, illustrates the importance of the linkage
 between sediments and the water column and its influence
 on exposure of all aquatic biota. This presentation in-
 cluded a discussion of the development and application of
. bioaccumulation factors for fish, both water-based BAFs
 and biota-sediment accumulation factors (BSAFs), with
 emphasis on the role'of sediments in bioaccumulation of
 persistent, hydrophobic non-polar organic  chemicals by.
 bothbenthic and pelagic organisms. Choices of bioaccu-
 mulation factors are important because they will strongly
 influence predictions of toxic effects,in aquatic organ-
 isms, especially when chemical residue-based dose-re-
 sponse relationships are used.
       There were two  principal bioaccumulation  factor
 expressions used by the GLWQI. TheBAFfis based on
 Upid-normalized concentration of the chemical  in the
 organism,with respect to the.concentration of  freely
 dissolved (bioavailable) chemical in the water. The BSAF
 is the lipid-normalized concentration hi  the organism
 with respect to organic carbon-normalized concentration
  in the sediments. BSAFs were used to determine BAFf s
  for chemicals with concentrations  which have not been
  measured in Great Lakes water but  are detectable hi
  sediments and fish. Equilibrium partitioning of persis-
  tent non-polar organic chemicals  generally occurs be-
  tween sediments and benthic invertebrates and a thermo-
  dynamic equilibrium or fugacity approach is useful for
  describing the degree of equilibrium (or disequilibrium)
  associated with bioaccumulation in fish. However, mea-
  suredB AFf s and BSAFs generally indicate a state of non-
  equilibrium partitioning from sediments to fish. BAFfs
  and BSAFs may be determined and applied as steady-
  state relationships which incorporate degrees of disequi-
-  librium, such as normally  present between water and
  sediment or between  fish and water due  to the
  biomagnification phenomenon.    ;,
        The bioaccumulation cube (Figure  1) is a concep-
  tual model which includes the most important  generic
  factors that must be considered when predicting bioaccu-
  mulation from measured or predicted concentrations of
  chemicals in the water and sediments of the ecosystem.
  The bioavailability considerations that remain, after in-
  corporating the influence of organism lipid, organic car-
  bon in water and sediments, and trophic level into B AFf s
  and BSAFs to reduce uncertainty for site-specific
  bioavailability conditions, are shown on the z-axis. Ba-
  sically, this residual bioavailability factor is the chemical
  distribution between water and sediment .which can vary
  between ecosystems or vary temporally and spatially
  within an ecosystem. Chemical properties which influ-
  ence bioaccumulation are shown on the x-axis. The
  octanol-water partition coefficient  (Kow)  is the primary
  indicator of chemical hydrophobicity and bioaccumula-
  tion potential. A second chemical factor is metabolismby
  organisms in the food chain.  Metabolism is strongly
  related to chemical structure as well as the presence or
  absence of specific metabolizing enzymes in different
  organisms in the food chain. The rates of metabolism of
  a bioaccumulative chemical by the different organisms in
  a food chain will determine the.extent to which rates of
  elimination of the chemical will be faster than that pre-
  dicted on the basis of Kow in the absence of metabolism.
  Conceptually, the cumulative effect of metabolism in the
  food chain can be equated to a factor K^^ which could
  be subtracted from Kow to correct for the degree of reduced
  bioaccumulation associated with metabolism.
        Ecosystem conditions, such  as riverine/lacustrine
   character, temperature, and trophic condition, as illus-
   trated on the y-axis of the bioaccumulation cube, may be
   an important consideration when  trying to  extrapolate
   from one ecosystem to another.  The degree to which
   quantitative differences in bioaccumulation  may be at-
   tributable to particular ecosystem conditions, apart from
   the influence of organic carbon which is handled  as a
   bioavailability variable, is not well known. Bioaccumu-
   lation data of the quality neededfor quantitative measure-
   ment  of these relationships for different ecosystems are
   very limited. Finally, recognition that the food chain has
    to be.defined when modeling bioaccumulation and
    biomagnification creates a fourth dimension, the trophic

3-19                 ,

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   3-20

   level, within the bioaccumulation cube; i.e. the bioaccu-
   mulation cube exists for each trophic level or more spe-
   cific definition of food chain.
        The procedures used in the GLWQI for predicting
   bioaccumulatation are reported in the form of a  technical
   support document (U.S. EPA, 1995) which is  available
   from NTIS.  Although bioaccumulation factors can be
   specific for ecosystem conditions and for the structure of
   the food chain, they may be less site-specific hi regard to
   bioavailability conditions.   However, in the  GLWQI,
   BAFf s were developed based upon the concentration of
   freely dissolved chemical in water because this greatly
   reduces bioavailability conditions as a source of variabil-
   ity between sites.  The fraction of the chemical in water
   which is not partitioned to particulate organic carbon and
   dissolved  organic carbon  (fraction freely dissolved) is
   considered to be the fraction which is bioavailable. The
   fractionfreelydissdlved(ff'1) chemical can beestimated as:
                                                 (1)
  where POC is the concentration of particulate organic
  carbon, DOC is the concentration of dissolved organic
  carbon.andK^andK^ are therespectiveorganic carbon-
  water partition coefficients. FortheGLWQI, K  was set
  equal to Kow for each chemical, and K^, basecfon Great
  Lakes water data, was set equal to one-tenth of K
  reflecting the lesser partitioning power of dissolved or-
  ganic carbon.
       The distribution of chemicals between the sedi-
  ment and water column can be characterized with a
  sediment-water concentration quotient (TI^J which is
  the ratio of the organic carbon-normalize'd'concentra-
  tion in surface sediments to the freely dissolved chemical
  concentration  in water. With Lake Ontario data (Oliver
  and Niimi, 1988) and the POC and DOC partitioning
  model (equation 1), U^ can be related to the degree of
  chemical equilibrium or disequilibrium (Figure 2). The
 values of log E^, for chemicals with varying log K  are
 above the line which represents a fugacity ratio of one,
 or AW eg"31 to !°g K  •  This reflects a  degree of
 chemical disequilibrium in Lake Ontario which is prob-
 ably common to most of the Great Lakes since the early
 1970s. Based on linear regression,  the H   value for
 these data would be about 25 times Kow, or about 25-fold
 theoretical disequilibrium between the sediment and the
 water column under recent conditions in Lake Ontario.
 A significant portion of this disequilibrium may be an
 ecosystem characteristic as a consequence of the differ-
 ence between the fraction of organic carbon in sediments
 and the fraction of organic carbon associated with par-
 ticulate material in the overlying water.
      BAFfpredictionsforchemicalswithlogK s greater
 than 5 are quite sensitive to variations in II  when II   /
 Kw =  25 (Figure 3).  Using the Gobas bScumulatton
model  (Gobas, 1993), Burkhard (1997) demonstrated that
a 10 percent increase in the Lake Ontario fl^, which is
            National Sediment Bioaccumulation Conference

   the same as increasing the sediment concentration by 10
   percent while holding the  water column concentration
   steady, results hi nearly a 10 percent change in BAF^s.
   Predictions of bioaccumulation in the form of the BAFfds
   for organisms throughout  the food chain are strongly
   influenced by change in the 11^ value when water is at
   disequilibrium with surface sediments (Burkhard, 1997).
   In other words, B AFf s for chemicals with log K  s > 5 are
   strongly benthicaUy linked under this condition of dis-
   equilibrium, even when the benthic food chain connec-
   tion may be small. If the ratio of U^ to Kow is close to one
   (equilibrium between the water and sediment which theo-
  retically could occur in other locations), the sensitivity of
  to6 nso™is quite different (Figure 4). The relationship for
  sculpin is more sensitive, reflecting its stronger benthic
  connection to the sediments.  The BSAF sensitivity to
  change in IIsocw is the opposite of the BAFf sensitivity;
  i.e., when the BAFf sensitivity is large, the BSAF sensi-
  tivity is small. This is not surprising since H   equals the
  ratio of theBAFf totheBSAF. In summary (figure 5) the
  sensitivity of BAFf s and BSAFs to II30CW depends on the
  Kow of to6 chemical, the benthic/pelagic relative contribu-
  tion to the food chain, and the degree of disequilibrium
  between the  sediment and  the  overlying  water.  The
  relative sensitivity of BAFf s and BSAFs to IIS   could be
  an important determinant, under particular site-specific
  conditions and chemical Kows, of whether a water-based or
  a sediment-based bioaccumulation factor should be used
  for prediction of bioaccumulation.
      SelectionofBAFfsfortheGreatLakesWaterQual-
  ity Initiative involved a tiered approach. Preference was
  given to high-quality, field-measured values. Unfortu-
 nately, for many chemicals  these values do not exist.
 Second preference was given to BAFf s predicted using a'
 BSAF methodology, which is described below. The third
 and fourth tier procedures involved calculation  of food
 chain multipliers to account for biomagnification. In the
 third tier, the food chain multiplier is multiplied by a
 measured bioconcentration factor (BCF) and, in the fourth
 tier when BCFs are not available, the octanol-water parti-
 tion coefficient is used as a surrogate for the lipid-normal-
 ized bioconcentration factor  based on freely dissolved
 chemical in water (BCFf).
     The second tier method, which uses BSAFs to cal-
 culate BAFf s, was derived using the following relation-
 ship between BAFf, BSAF, and H   :
                n     =
                  •socw    BSAF
(2)
For many chemicals hi the Great Lakes, under present-day
conditions, ratios of U^ to Kow (fugacity ratios between
sediment and water) are similar:
                      /   en    ),
                socw   a  _  socw
                                               (3)

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 Proceedings	•                     	:	

 With this condition,  equation 2 can be substituted into
 equation 3 and, following rearrangement, the resulting
 equation 4 can be  used to calculate  (BAFfs)j for
 chemicals (I) such as TCDD which cannot be routinely
 measured in water at this time:
            fd  _
      (BAF,  ){-

      TheBSAF method uses reference chemicals (r), such
. as PCB congeners, for which (BAFf )rs carioften be accu-
 rately measured. If areferencechemicalthathasthesame   ,
 K  as the unknown chemical is chosen, the Kpw ratio in the
 equation becomes one and the calculation is simplified
 further. Figure 6 illustrates BAFf s calculated from Lake
 Ontario data with the B'S AF method. The distribution of
 the PCB congener B AFf s (circles) provides the expected
 increase in bioaccumulation and biomagnification with
 respect to magnitude of Kow. In contrast, the dioxins and
 furans are predicted to have quite smaller bioaccumulation
 factors (on the basis of Kow). This is primarily because of
 the effect of  metabolism in fish which is effectively
 measured by theBSAFs and incorporated into theBAFfs.
 Even though metabolism rates are slow, the increase in
 elimination rate of the parent chemical is significant and
 dramatically reduces the bioaccumulation potential  with
 respect to PCB s with the same Kow.
       To evaluate the BSAF method, BAFf s measured in
  Lake Ontario  were compared to predicted BAFf s calcu-
  lated from Lake Ontario BSAFs (Figure 7) and were in -
  good agreement.  A further evaluation was performed by
  comparing BAFf s  calculated from BSAFs for PCBs. in
  Lake Ontario for trout to B AFf s independently calculated
  fromBSAFsinGreenBay forbrowntrout(Figure8). These
  values were also in agreement despite the disparate eco-
  systems and measurements involved.       >
        The determination of food chain multipliers (ratio
  of BAFf to Kow) for prediction of BAFf s from Kows was
  accomplished with a food chain model (Gobas, 1993)
'  using Lake Ontario data and conditions.  The objective
  was to calculate food chain multipliers for bioaccumulative
  organic chemicals and use : them .with Kow to estimate
  BAFfds. Figure 9 illustrates how the predictions with food
  chain multipliers compared to measured B AFf s with the
  datareportedby Oliver andNiimi (1988) for Lake Ontario.
   The agreement is very good, particularly for the higher Kow
   chemicals which are not metabolized, which in this case
   are primarily PCBs. The food chain multipliers that were
   calculated using the .Gobas 'model reflect -a biomag-
   nification potential that is a function of Kbw for the two top
   trophic levels of predator fish and forage fish. Under the
   conditions of the model, the zooplankton are considered
   to be at equilibrium with respect to the water and benthic
   invertebrates at equilibrium with respect to the sediment.
         Bioaccumulation factors can facilitate bio-
   accumulation predictions in ecological risk assessments
   involving impacts of complex mixtures of chemicals. The
   joint toxicity of chemicals that share similar structure and
   common mode of toxic action with TCT3D (2,3,7,8-
   tetracholorodibenzo-rp-dioxin) can be predicted with an
                                                                                                   3-21
additivity model using the  TCDD toxicity equivalence
approach. TCDD toxicity equivalence factor's (TEFs) are
essentially toxicity potency estimates relative to TCDD
such that a chemical with a TEF of 1 has a potency equal  •
to that of TCDD* The toxicity equivalence concentration
(TEC) is calculated as the sum of the products of the TEF  , ,
times the concentration for each chemical in a mixture.
Often a key question involves what media the concentra-
tions should be based upon. TECs have been calculated
based on chemical concentrations in effluents, sediments,
or water. TECs based on concentrations of the chemicals
in tissue are preferable because of the direct connection
between concentration in the tissue and the dose-response
relationship for a toxic effect. If a TEC associated with a
contaminant mixture in sediments is desired, the TEC can
be expressed in terms of the concentrations expected in a
fish as a result of bioaccumulation (TEC^). TheTEC^h
can be directly related to the potential for toxic effects in
the fish (Cook etal., 1997a),ortowUdlifeorhumans,that.,
eat the fish, arid is calculated as the sum of products of the
 brgariic carbon-normalized concentration  in sediment
 (C  ) tunes the BS AF (equation 5) and the TEF for each of
 n chemicals. The fraction lipid(f) in the fish is included
.when the TECfish is calculated on the basis of whole fish,
 rather than lipid-normalized concentration. A TECf]sh can
 similarly be calculated for chemical concentrations in
 water with B AFf s.


                    ) f (BSAFfish) i               (5)

       Equation 5, as adapted for lake trout eggs, was used
  retrospectively to determine the influence of TCDD and.
  related chemicals on lake trout reproduction and popula-
  tion dynamics of lake trout in Lake Ontario since 1920
  (Cooketal., 1994,1997). Radionuclide-dated  sediment
  sections from sediment cores were essential for construc-
  tion of a historical exposure record which was then linked
  to effects on lake trout through the lake trout egg TCDD
  dose-early life  stage mortality response relationship
  (Walkeretal., 1994). The use of the lake trout egg TCDD
  .dose-response relationship requires use  of TEFs  and
  BSAFs basedonconcentrationsofchemicalsintrouteggs
  to calculate TCDD toxicity equivalence concentrations
  which were based on lake trout eggs (TECeggs). Figure 10
  summarizes  the information that was generated by  this
  analysis. The y-axis represents the chronology in years for •
   Icmincrementsfromthekeyreferencesedimentcorefrom
  eastern Lake Ontario which were analyzed by high reso-
  lution gas chromatography/high resolution mass spec-
  trometry.  This core was selected to represent trends in
  Lake Ontario exposure conditions in this century.  The
   toxicity equivalents of the more important congeners
   present in the 1 cm increments of sediment are plotted
   cumulatively on the x-axis such that each horizontal bar
   represents the TECe  predicted for lake trout on the basis
   of equations. Thee§SAFeggs were adjusted to accommo-
   date the effect of differences in [!„„,, attributable to greater
   chemical loadings to the lake prior to 1970.
11

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   3-22    	

        The relationship between predicted TEC  s and
   predicted degree of lake trout early life stage mortality is
   also indicated in Figure  10.  For example, during the
   period from the 1940s to the 1970s, 100 percent early life
   stage mortality is predicted for this very sensitive fish
   species. The epidemiological records from Lake Ontario
   are consistent with this prediction, despite complications
   associated with the presence of non-chemical stressors
   such as sea lamprey predation and over-fishing during the
   period in which the  lake trout population declined  to
   virtual extinction by 1960. During the period of recovery
   of Lake Ontario after 1970, when lake trout were stocked
   and large populations of adult trout were restored, natural
  reproduction has not been achieved. However, eggs were
  collected from the stocked fish, fertilized, and early life
  stage development and survival monitored under labora-
  tory conditions. The incidence of mortality due to blue-
  sac syndrome associated with TCDD was observed in the
  laboratory and is in good agreement with  the percent
  mortality predicted with the TECe  model. After 1985,
  measured concentrations of TCDD8and related chemicals'
  in lake trout eggs were below the threshold for mortality
  associated with the blue-sac syndrome, and field observa-
  tions of lake trout sac fry presence on spawning reefs
  increased with the first observations of 1- to 2- year old
  lake trout from natural reproduction occurring in 1994.
         BAFjds and BSAFs can be critical components of
  water and sediment criteria development. For example, to
  create a sediment criterion for the protection of future lake
  troutpopulations in the GreatLakes, the following factors
  should be considered: (1) the concentration of TCDD in
  the eggs that would be associated with no adverse effects
  to early life stages of lake  trout  (this includes effects at
  sublethal exposures that reduce  survival of sac fry and
 alvins) and (2) theBSAF  s  for lake trout under a IT
 condition expected during the time period of interest. The
 concentration of TCDD in sediment that would be associ-
 ated with a lack of adverse effects (sediment criterion) can
 be calculated from the concentration of TCDD in the egg
 associated with the threshold for toxic effects divided by
 the BS AF  . Similarly, a water criterion can be calculated
 using the BAFf for TCDD.
      To relate  these TCDD criteria, whether they be
 sediment criteria or water criteria, to organisms exposed
 to complex mixtures of TCDD and related chemicals,
 differences in bioaccumulation must be considered along
 with the differences in  toxic potency as expressed with
 TEFs. Bioaccumulation potentials of the different chemi-
 cals contributing to dioxin toxicity risks can be referenced
 to TCDD as with TEFs.  In the GLWQI these were named
 bioaccumulation equivalency factors. The sum of TCDD
 toxicity equivalents is directly comparable to  the water
 quality criterion or sediment quality criterion for TCDD
 under the TCDD toxicity equivalence model.
     In conclusion, BAFfs  and BSAFs are essential for
 application of chemical-residue-based criteria in risk as-
sessments and are interrelated through the sediment-water
concentration quotient (fl^J, particularly for the more
            National
                           :Bic
  hydrophobic organic chemicals.  They can incorporate
  elements of site-specific bioavailability. They are a spe-
  cific interface between exposure assessments and effects
  assessments. They are a primary output in food chain
  bioaccumulation models used for validation of the mod-
  els and comparisons to field data.  Finally,  measured
  bioaccumulation factors are effective for prediction of
  bioaccumulation in association with water or sediment
  quality criteria when used appropriately with time-aver-
  aged exposure estimates for persistent organic chemicals,
  especially those with a higher K
                        0     ow


  References

  Burkhard, L.P.  1997. Comparison of two models for pre-
       dicting bioaccumulation  of hydrophobic organic
       chemicals in a Great .Lakes food web.  Environ.
       Toxicol. Chem., in press.
  Cook, P.M., B.C. Butterworth, M.K. Walker, M.W.
       Hornung, E.W. Zabel and R.E. Peterson.   1994.
       Lake trout recruitment in the Great Lakes: Relative
       risks for chemical-induced early life stage mortal-
       ity. Soc. Environ. Toxicol Chem. Abstr.  15: 58.
  Cook, P.M., E.W. Zabel and R.E. Peterson. 1997a.  The
       TCDD toxicity equivalence approach for character-
       izing risks for early life stage mortality in trout. In
       Chemically-induced alterations in the functional
       development and reproduction  of fishes, eds. R.
       Rolland, M. Gibertson and R. Peterson, Chapter 2.
       SETAC Press, Pensacola, FL, in press.
 Cook, P.M.,  D.D. Endicott, J. Robbins, P.J. Marquis, C.
      Berini, J J. Libal, A. Kizlauskas, P.D. Guiney, M.K.
      Walker, E.W. Zabel, and  R.E.  Peterson. 1997b.
      Effects of chemicals with an Ah receptor mediated
      mode  of early  life stage  toxicity on  lake trout
      reproduction in Lake Ontario: Retrospective and
      prospective risk assessments.  Submitted for publi-
      cation.
 Gobas, F.A.P.C.  1993.  A model for predicting the
      bioaccumulation of hydrophobic organic chemi-
      cals  in aquatic food-webs: Application to Lake
      Ontario. Ecological Modeling 69: 1-17.
 Oliver, E.G. and  A.J. Niimi.  1988.  Trophodynamic
      analysis of polychlorinatedbiphenyl congeners and
      other chlorinated hydrocarbons in the Lake Ontario
      ecosystem.  Environ. Sci. Technol. 22: 388-397.
 U.S. EPA. 1995.  Great Lakes Water Quality Initiative
      technical support document for the procedure to
      determine bioaccumulation factors.  EPA-820-8-
      005, NTIS  PB95187290, 185pp.
Walker,  M.K.,  P.M.  Cook,  A.R.  Batterman,
      B.C. Butterworth, C. Berini, J. J.Libal, L.C. Hufhagle
      and R.E. Peterson. 1994. Translocation of 2,3,7,8-
      tetrachlorodibenzo-p-dioxin from adult female lake
      trout (Salvelinus namaycush) to oocytes: Effects on
      early life stage development and  sac fry survival.
      Can. J. Fish. Aquat. Sci. 51: 1410-1419.

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Proceedings
                                                                                              3-23
     Figure 1.
                      Framework for Predicting Bioaccumulation Factors
                          Applicable to Different Aquatic Ecosystems
           •  Food
             Chain
             Model
          /EcosystemS
          V Conditions/
                               4.5  5.0  5.5  6.0  6.5  7.0  7.5  8.0  8.5
                                             log (K0^ - Kmetab)
                                             (Chemical Properties)
      Figure 2.
         10
        JTe
                     Sediment-water column chemical concentration quotient
                          for Lake Ontario data of Oliver and Niimi (1988)
                               Pesticides  Cl-benzene^C.-to.uenes pCBCongenere

                                  •  .          O              *
                                                LogKow
                                                                       DOC = 2 mg/L & Kdoc= Kow/10
                                                                 Sediment organic carbon content = 2.7%

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3-24
                                                               National Secttment Bioaccumulatton Conference
Figure 3.
1.2
1
0.8
0.6
1 0.4
.1
w
0.2
o
(0.2)
(0.4)

2
Sensitivity of Food Chain
to nsocw (+1 0%) (Gobas 1 993 Model)
HSOCW /Kow = 25
1 Sensitivity = ...^
IIsocwABAFf //?
(-0.1)nSOCw-BAFjd ///
// /
// •/'
// ,.'
,/,'.-•'
	 -«^-:-'

Zooplankton Dlporeiasp. Sculpin' Atewifa Smelt Piscivorous Fish
	 ' 	 ' 	 ' 	 ' ' ' ' ' ' ' • |
3 4 5 '6 7 8 9
Log Kow








Rgure 4.
1.2
1
0.8
0.6
.-&
4» 0-4
* 0.2
0
(0.2)
^n /IN
lu-iv

2
Sensitivity of Food Chain
to nsocw (+1 0%) (Gobas 1 993 Model)
nsocw/Kow= 1
- . ... , nsocw • ABAFjd
Sensitivity™ •
^ ""'. (-O.I)nsocwBAFf1 ^ 	 ' 	
/
1
..-.r.-.rvr....
•• #•*' 	 •"».•-...
/ f .„..„..„.....-..— _._.— ,.T-Si.^,.r.:.r..'.r.:.
_-l— ^^"

Zooplankton Diporeiasp. Sculpin Alewife Smelt Piscivorous Fish
— — - -..._..
	 1 	 1 	 1 	 1 	 . l.l.i. |
3 4 5 6 789
Log Kow











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Proceedings
                                                                                    3-25
    Figure 5
     Sensitivities of BAFJjd s and BSAFs to changes in nSOcw  depend on:
       1. Kow of chemical
       2. Benthic/pelagic contribution to food chain
       3. Disequilibrium between sediment and overlying water (SOC - POC - C™)
                          Predicted Lake Ontario Lake Trout BAFs
                                               PCDDs.PCDFs chlordanes/nonachlors
                                                  *          •   •
           3
      Referenced to O-N BAF for PCB 52
      Doc=2mg/L & Kdoc=Kow/10

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3-26
                               National Sediment Bioaccumulation Conference
     Figure 7.
                                  Lake Ontario Salmonid BAFs
                          Correlation of Measured BAFs to BSAF Predicted
        OKvor & NUml - Refereread to BAF for PCB 52
        Doo=2mgrt. & KdociKbwflO
                                       6            7           8
                                    Oliver & Niimi measured log BAFs
                                                             10
     Figure 8.


        10
Correlation of L. Ont. & G. Bay log BAFs
                        5            6    •         7             8

                                 Mean Lake Ontario log BAFs from BSAFs
     ERLD GB B.Trout Region 3A/3B BAFs rsf. PCB 52                   '          '
     Doc=2-5mg/L & Koc=Kow/10
                                                               10

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Proceedings
                                                                                       3-27
     Figure 9.
                     Measured and Predicted BAFs for Piscivorous Fishes
                       •  Measured BAFs from Oliver and Niiml (1988)
                                                               * *
                                                                    Pesticides
                                                                   •  '  •
                                                                Cl-benzenes, Cl-toluenes
                                                                     &HCBD
                                                                     .  'O; •
                                                                   PCB Congeners
                                                                       *
                                                                 BAFs Predicted using
                                                                      FCMs
                                                                       8
     Figure 10.
                      Lake Ontario Lake Trout Egg RTEC Retrospective
                               Contribution of Individual Chemicals   .
                                                                      D 2378 TCDD
                                                                      • PCB 126
                                                                      E3 23478 PeCDF
                                                                      • T2378PeCDD
                                                                      • 123478 HxCDF
                                                                      H PCB 77
                                                                      • 2378 TCDF
                                                                      GO Other  •
                   50        100       150       200   .    250
                      CUMULATIVE TCDD TEQ (pg TCDD/g egg)
300

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                                                       National Sediment Bioaccumulation Conference
From Modeling to  Criteria:   Integrated
Approach to  Criteria Development
Mary C. Reiley
U.S. Environmental Protection Agency, Office of Science and Technology, Washington, DC
JPB^he Office of Water's Water Quality Criteria Program
 I  (CWA Section 304(a)) is at a major crossroads in its
 .M.  evolution. The national program currently develops
chemical criteria from the priority pollutant list (CWA
Section 307(a)) based on toxicity testing with little or no
consideration of mixtures, bioaccumulative potential, or
exposurepathway. Individual criteria (aquaticlife, human
health, sediment, andwildlife) were developed for a host of
chemicals, often with the result of several criteria types for
a given chemical. The most stringent of these criteria, was
then used to derive the water quality goals of an aquatic
system or a permit limit.  To develop assessment methods
and criteria that will align more closely with the stated
objective of the Clean Water Act,"... to restore and main-
tain the chemical, physical, and biological integrity of the
Nation's waters," the program would like to integrate
criteria development using the risk assessment paradigm. '
The goal is to develop criteria and methods more efficiently
and with more insight into the effects of chemicals on
             aquatic systems (including-those terrestrial organisms
             which are aquatic dependent, e.g., fish eaters).
                  The Office of Science and Technology (OST) pro-
             poses to develop water quality criteria by evaluating the
             different possible pathways of exposure and determining
             the pathway that is most critical for a particular chemical.
             To accomplish this task, OST will develop a strategy to
             merge the technical and programmatic aspects of water
             quality criteria programs (human health, drinking water,
             aquatic life, wildlife, sediments, biocriteria) to address
             ecosystem threats for a specific chemical (or class of
             chemicals). Theproductdevelopedunder this strategy will
             be a multi-pathway model(s) for establishing human health
             and ecological criteria, with particular attention paid to the
             most sensitive pathway. The program is working with the,.
             Society for Environmental Toxicology and .Chemistry
             (SETAC) to design a Pellston Workshop that will address
             the state of the science and research needed to be able to
             construct integrated assessment tools.  The figure below
             is a conceptual diagram of how this may be achieved.
                          Integrated Pathways to Criteria
               Target Organism
            (NOEL for: Wildlife Effects
                     Human Health
                     Aquatic Life)
          Current
        Water Quality
                 Prey Quality
              (Tissue concentration
               that protects target)
                                                 BSAF
                                                 SLSA
                               Regulatable
                               Sediment or
                               Water Quality
                               Value/Method
    Program & Knowledge
Models
\
                                                                                Source
                                                                                Control
                      Implementation
                         Guidance
                                            3-29

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3-30
                          National Sediment Bioaccumulation Conference
      From Modeling to Criteria:
      Integrated Approach to Criteria
             Development for
        Bioaccumulative Chemicals
  5 Types of Water Quality Criteria

               Aquatic Life
              Human Health
             Sediment Quality
                 Wildlife
                Biocriteria

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Proceedings
3-31
            Integrating Criteria
                  Chemicals
        Designated Use/Target Organism
                  Fish Tissue
             Measurement Media
          Regulatory Implementation
   Research and Implementation Issues

  Incorporate metabolism into the model(s).
  Change residue values into acceptable loadings.
  Account for multiple sources.
  What level of protection do we strive for?
  Package model(s) and guidance for practicality.

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                                                            National Sediment Bioaccumulation Conference
  Day One:  September  11,  1996
Session  three:
Questions  and Answers
A
fter each session, there was an opportunity for
questions and answers and group discussions per-
taining to the speakers' presentations.
.Q (Bob Barrick, PTI Environmental Services): Dom, I
was going to just sit here and listen, but you brought  up
Fred Praul 's work and it is such a central part of your talk
that I really need to speak. As you know I work with Fred.
His conclusions from his research are 100 percent oppo-
site of your conclusions.

Dominic Di Toro:

     Exactly right. You can conclude what you like.

Q (Bob Barrick): I want to make three points here. One
is that when you are going ahead and using bulk organic
carbon to normalize sediments, it misses the fact that
organic carbon.is disproportionately found in the different
fractions. It is not a weighted average. Unless you quan-
tify the organic carbon  in each of those size and density
fractions,  you are going to come up -with the wrong
answer. Bulk organic carbon is not necessarily appropri-
ate, even if organic carbon works. That is also the case
with what Fred found, which was  a  disproportionate
amount of PAH versus organic carbon in those fractions.
Now, that is obscured  a bit because Fred did present
arithmetic plots in his thesisandyou have converted those
to log plots, which has dampened down the variability. If
you take that out, it is a pretty big scatter in there.

Dominic Di Toro:

     Bob, we have, as you know, organic carbon mea-
surements. He made measurements in each of the size
classes, so we know what the organic carbon concentra-
tion in each size class is.  So, you divide, by the organic
carbon concentration in each size class.

Q (Bob Barrick);  Dom, my point was that Fred did it
properly.  What I am saying is that when you are taking
the organic carbon fractions and applying them out in the
real world, where everybody has a TOC number, that
number is not according to a particular compartment
within the sediment. It is abulk sediment number, andto use
that to measure against some kind of chemical that may be.
foundonlyinonecompartmentisnotwhatFredfound.IfFred
found that, that may be an erroneous way to proceed.

Dominic Di Toro:

     Let me just comment on the comment.  If you
actually take the bulk  organic carbon concentration and
take the chemistry per unit carbon, it also works for all the
size fractions.  That is because it is the same in each
fraction. So, if you add up the same numbers, you get the
same number.

Q (Bob Bar rick): It works better if you put it analog plot.
The third thing I wanted to say was that in discussing all
these things,  it also ignores the difference in something
else that Fred found in his research. This was the differ-
ence between labile and refractive panicles, even though
you may be able to extract organic compounds out of both
of those using organic solvents in a laboratory. In fact,
in nature where exposure is actually happening, there
may be no exchange from the refracted particles and
considerable exchange from labile particles. And to use
the  data to say that it supports equilibrium in the environ-
ment, when it is looking at -an organic 'carbon-extracted
system, is also making a little simplification.  The only
reason I really wanted to bring, this 'up is because it is
something that is now a part of your talk, and it is really
counter to the conclusions of his dissertation work.

Dominic Di Toro:

     I think the data analysis stands on its own. And you
are  right.. Fred concluded exactly the opposite, which
struck us as  a little peculiar since the data seemed to
indicate what I presented to you. There is a problem, by
the way, with bioavailability. All organic carbon is not the
same and all phases of sediments and chemicals are not the
same. The issue is whether the difference is so large as to
make  organic carbon normalization useless, or are we
arguing about the extent to which we can collapse, responses
                                               3-33

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3-34
          National Sediment Bioaccumulation Conference
and understand what we are seeing? If the variability was
so large as to be useless, then I would say fine, use dry
weight normalization. In fact, why not use wet weight
normalization in sediments? People have used it for biota.
Why is it not a good idea in sediments? The point is you
have to have  some  kind of database and theoretical
understanding of what you are doing. The data speak for
themselves.

Q(Dennis Leonard, Detroit Edison): Dr. Cook, couldyou
comment briefly on  the development of the BAF for
mercury in the Great Lakes? The BAF model that you.
discussed required the steady-state assumptions to be
present. The mercury concentrations that we have in the
Great Lakes vary by about a factor of 100.  Tributary
littoral concentrations are influenced by high concentra-
tions of mercury in rainfall.  Open water concentrations
are affected by transfer of mercury back to. the atmo-
sphere; therefore, we have concentrations ranging from
about 15 ng/m3 to 0.5 ng/tn3 at any point in time and space.
Is the steady-state assumption really valid, and how do
you  develop a mercury criterion when you have this
hundred-fold variation?

Philip Cook:

      I would love to answer your question, but I cannot.
I do not know that much about the mercury bioaccumula-
tion. If there is someone else here who feels they have .that
knowledge, I would welcome their participation.

Bob Barrick:

      We have done quite a bit of work on mercury and
mercury uptake. Mercury is a totally different  animal
because how it is associated hi cells is quite different from
other metals. It is pretty complicated. There is literature
available, and I think there is a whole conference  on
mercury that focuses on its uptake hi the environment.
Mercury does not fit neatly into these models. Consult the
literature because there is information on how that should
be done differently.

Philip Cook:

      I can agree with that.

Q (Gayle Gorman, NOAA): lampleased to hear someone
talk about the fact that the environment is not really in
equilibrium. Yet you are still making an assumption of
steady state and this is for the Great Lakes.  Generally, I
workin estuaries andtheyare very dynamic systems.  lam
wondering  if you could comment on our assumptions of
steady state or equilibriumfor estuaries, and whether you
think the modeling-approach that you have taken for the
Great Lakes is applicable in an estuarine situation?  ,

Philip Cook:

      I certainly would not advocate using a steady-state
model where we know it would not produce a valid result.
 There is obviously a need for nonsteady-state models. To
 some extent, these empirical tools that I have discussed
 here today may be usable, when necessary, in nonsteady-
 state conditions. I think you have to get a good prediction
 of an average exposure relationship, whether it be sedi-
 ment or water, and then take into consideration the prop-
 erties of the chemical that you are trying to model. If it is
 a lower Kow chemical, I think the fluctuating  exposure
 problem becomes more severe.

 O_(CharlesKovatch, University of'South Carolina): Could
 you further explain your food chain multiplier model
 parameter?

 Philip Cook:

      Essentially, the food chain multiplier is an expres-
 sion for the organism that you are trying to model, which
 represents the increase in the BAF over the octanol-water
 partition coefficient. So, it is an expression of the total
 effect (in  the  food chain) of biomagnification on  the
 bioaccumulation factor.  It is applied when you do  not
 have the bioaccumulation factor specific for that chemi-
 cal, so you use a bioconcentration factor or an octanol-
 water partition coefficient as the surrogate for the equilib-
 rium accumulation. The food chain multiplier, when
 applied to either the BCF or  Kow, predicts  what  the
 biomagnification effect would be on the bioaccumulation
 factor.

 Q (Doug Hotchkiss, Port of Seattle): The comment was
, made in this last talk and in others that we have a lot of
 data out there. When we make these lists of data, like the
 compilations of data by URS and others, it looks like we
 have a lot of data. I have been involved recently in trying
 to use some of that data on a very site-specific regulatory
 basis.   This is just a word of caution and a note to
 everybody out there.  These lists may be very good for
 screening purposes to identify what  we should really
 worry about.  But when you apply them to regulating in
 a site-specific situation, you need to take a really close
 look at each individual paper. If you look at the specifics
 of how that number was generated, you will find that some
 of those numbers can be very soft for regulatory purposes.
 For example, in a study using a spiked sediment, you
 should check if they rinsed out the interstitial spike before
 they ran the tests. Some of the numbers can also be listed
 incorrectly from a paper. These lists can be a great help,
 butyou ought to reexamine thevalues that are going to be
 critical in the decision-making process for both the regu-
 lated and the regulatory community. You should sit down
 and take a critical look at what those numbers really mean
 before just automatically moving ahead with them.

 Q (Weldon Bosworth, Dames and Moore): I would like to
 direct questions to Dr. McFarland and Dr. Di Toro. For
 those of us that work in wetlands, we occasionally  see
 organic carbonlevels that are substantially higher than
 the data you presented on your slides.  There are also
 substantial amounts of dissolved organic matter. When
 we apply this on a screening level or for a Tier I risk

-------
Proceedings
                                                                                                    3-35
assessment, weneedtodeterminewhatthepotentialisfor
bioavailability. Referring just to neutral chemicals, we
•might want to go to carbon normalization. How comfort-
able would you feel about applying your theoretical bioac-
cumulation potential estimate to something that would
range up to 30 or 40 percent organic carbon?  What
empirical or theoretical data do you have to support your
answer?

Victor McFarland:

      At 30 or 40 percent organic carbon, you might have
quite a lot of something that is not natural organic carbon.
But it could also be natural material like peat. What we
ordinarily encounter is what you see in ship channels.  I
have riot tried to measure anything like you have de-
scribed. What we have done is to see how low you can go,
rather than how high you can go. In the types of situations
that we generally see, we have material containing up to
3 percent and occasionally up to 5 percent TOC. But, in
fact, I have had to search hard to find anything that I could
use in doing those kinds of studies that was much above
3 percent. We have some idea of how low you can go,
which kind of agrees with Dom, but I could not answer
about higher TOC ranges.

Dominic Di Tpro:

   '   Weknowaiittlebitaboutthat. The carbon fraction-
ation data that I showed  you went as high as  10  or 20
percent.  The theoretical limit is 40 percent, meaning that
40 percent on a dry weight basis of organic matter, sludge,
or other material is carbon.  So, that  is the upper limit.
Quite a  bit of work has been done on partitioning  of
hydrophobic chemicals to digested sewage sludge. We
used a fair amount of that data in  the mid-1980s  to
establish the partitioning  relationships that we use. For
partitioning experiments  and suspensions, I know that
carbon normalization appears to work up to 20,or 30
percent.

Q (Weldon Bosworth): I do  not mean to suggest that
you could probably get away with a Tier 1 assessment
on a situation like that.  The result of carbon normal-
izing and then adjusting bioavailability for that would
show that there would not be much that is bioavailable.
It becomes a critical issue, when you  consider the
relative risks of leaving material there that may not be
bioavailable compared  to tearing up the whole wet-
land and trying to restore  it.  There is not much work
being done on bioavailability in conditions when the
organic carbon is that high.   ,

Q (PaulJacobson, Langhei Ecology, Inc.): I have to say I was
a bit bemused by Dom's comments regarding the role of
ecology in this whole process.  I feel compelled to make a
short comment on that. I think it is true that toxicology was
developed as a science and applied to pollution control
decades ago, because ecology was really not up to the task.
However, I think that hardly validates the assertion that
ecology process and content really is not relevant toddy and
into the future.  And I think that for the past 20 years or so,
pollution control has really been defined in toxicological
terms.  The upshot of the Edgewater consensus was that the
approach of the last 25 years is not going to get us where
we need to go. There is aneedfora more ecologically oriented
perspective.

Dominic Di Toro:

     I did not mean to say that I  think ecology  is
irrelevant. What I meant to say was I did not see ho w the
type of ecological work  that I think is being thought
about would get us there any quicker. I think that simple
observations of disturbed ecosystems, with no idea of
what the causality  is about  and without the  sort of
toxicological information that we have and need to
develop, is awasteof time. That was the caution, notthat
we should not do ecology, but rather if you look in the.
risk assessment paradigm and open the tool box to find
what methods actually exist to do this problem, you find
a remarkable lack of quantitative methods.

PaulJacobson:

     Well, then, perhaps we are in complete agreement.
I think that the need is for good ecology.

Dominicpi Toro:

     Yes, exactly right. I am railing against what I see as
a return'to an approach that I would call Victorian natural-
ism. That approach involves observing, making measure-
ments, and trying to make some elaborate arguments
linking observed changes  to causation.

Q (Peter Landrum, NOAA, Great Lakes Environmental
Research Laboratory): twos inierestedinyour talk, Dom,
since we have done some of that particle size separation
and carbon normalization. I would say that the variance
in our laboratory-dosed 'sediments is somewhat larger
than what you showed on your log log plots.  We see at
least an order of magnitude. And, in some cases, we see
the condition where the big organic particles do not seem
to adsorb as much material.

Dominic Di Toro:

     I think what that says, Peter, is that your lab simula-
tions are not at equilibrium. The data I .showed you are
field data sets.

Q (Peter Landrum):  Right, but I still thinkwhereyou have
bigger panicles, they are not necessarily going to be at
equilibrium.    .    '.          *•

Dominic Di Toro:  .

     Well, I ask you to look at three data sets that strongly
suggest  that large particles with high  organic  carbon
concentrations look just like small particles,  and that kind
of equilibrium must have been there for that relationship

-------
 3-36
         National Sediment Bioaccumulation Conference
 to work. That relationship tests two very interesting asser-
 tions:  that the system is at equilibrium and that carbon
 normalization gets rid of the effect of other sedimentolpgi-
 cal properties.

 Q (Peter Landrurn): If you put that on a linear plot, you
 will see that there is still quite a lot of variance there.

 Dominic Di Toro:

      There is no doubt about that, but put the raw data
 on a linear plot.

 Q (Peter Landrum): Well, that is what I do.

 Dominic Di Toro:

      Well, then it looks like hash. If you do not carbon
 normalize, then it is all over the place.

 Q (Peter Landrum):  Carbon normalization actually
 does, in most cases, reduce the variance.  I will not say
 in all cases. The other thing, though, that we have seen
 is even though you look at that carbon normalization,
 what we see for the bioavailability in the selection of
 particles by the organism is that they  are  selecting
 particles that we cannot even distinguish on a carbon-
 normalizedbasis. We see this basedon the measurement
 of concentrations in the fecal pellets, where they are
 actually selecting particles at a much higher concen-
 tration than we can measure relative to our bulk chemi-
 cal measurements. That is another issue that needs to
 be considered relative to what we get out of carbon
 normalization relative to bioavailability.

 Dominic Di Toro:

      It occurs to me, Peter, that maybe the problem is
 that you have to incubate your  lab sediments long
 enough to get equilibrium  across  the  particle
 spectrum.

 Q (Bob Barrick):  I am glad that  Peter Landrum
 spoke up because the major conclusions from Fred's
 thesis directly support a particle-selective model.
 It says the particles are important, and if there is
feeding on a particle^selective basis, then you will
 have dramatically different results. His thesis di-
 rectly supports that rather than supporting an equi-
 librium perspective.
Dominic Di Toro:

      My.only comment is Fred's data are what they are.

Q (Susan  Kane Driscoll, Virginia Institute of Marine
Science):  Dr. McFarland, I was interested in the BSAF
database that you showed where the median value for the
PAHs was lower than for the chlorinated compounds.
Do you have any impression about whether, it is more
important  that there is metabolism of the PAHs, or if you
are seeing some sort of kinetic limitation to accumulation,
or if it is a  bioavailability question like for soot particles?

Victor McFarland:

      Well, fish certainly tear PAHs up, and I do not
think that the bivalves are totally devoid of  some
metabolic capability there, too. But I do not think that
is the whole answer.  Anthropogenic PAHs are associ-
ated primarily with soot. The chemical is going to be
distributed throughout the soot particle.  In  order to
desorb from the interior of a soot particle, I think you
would have to imagine something  like a chromatogra-
phy column, where you have many steps of desorption,
sorption, desorption, and so on, which would make the
process quite slow. I think there is some evidence for this
in the literature.  It is a complex process! There is
certainly much more to it than just one or two things that
determine bioavailability and the BSAFs that we have
measured  for organisms  and chemicals.

Q(G. Fred Lee, G. Fred Lee & Associates): I would like
to ask Mary, what, if any, timetable EPA has for putting
where we  are now into a regulatory framework?

Mary Reiley:

     A long one. If we look at the past history, it is a long
process frdm the time we have data and come up with the
theory, to  moving that into something that can be prac-
tically implemented into a regulatory program, and then
to actually getting it implemented. There is an introduc-
tory period to get the research accomplished, about 5
years to make it practical, and then another 5 to 10 years
to get it implemented.  I think a lot of people believe that
if we publish something today, it is implemented tomor-
row. That  is not the way it works. It takes a lot of time to
get the bugs out.  Five years would  be nice, but I would
say to actually see it being implemented in a regulatory
program on a routine basis would take longer than that.

-------
                                            National Sediment Bioaccumulatton Conference
Session  Four:
Food  Chain Models and
Bioenergetics
Lawrence Burkhard, Panel Moderator
U.S. EPA, Office of Research and Development,
Duluth, Minnesota

Frank Gobas
Simon Fraser University,
Burnaby, British Columbia, Canada
Food Chain Models for Predicting Bioaccumulation

John P. Connolly
HydroQual, Inc.,    .
Mahwah, New Jersey
Use of Food Web Models to Evaluate
Bioaccumulation Data

Robert V. Thomann
Manhattan College,.
Riverdale, New York
Bioaccumulation Modeling ofPCBs in the Hudson
Estuary: A Review and Update
                                  . 4-1.

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-------
                                  National Sediment Bioaccumulation Conference
Food Chain Models for Predicting
Bioaccumulation
Frank Gobas
Simon Fraser University, Burnaby, British Columbia, Canada
Please contact the speaker for information on this presentation.
                            4-3

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                                                        National Sediment Bioaccumulation Conference
Use of Food Web  Models  to  Evaluate
Bioaccumulation  Data
John P. Connolly and David Glaser
HydroQual, Inc., Mahwah, New Jersey
Introduction

       Atypical use of bioaccumulation factors is to derive
       clean up levels or criteria/standards for water and
       sediment. Thetargetsedimentorwaterconcentra-
tion (TSC or TWC) is established by dividing a maximum
allowable tissue level (MATL) by either a biota-to-sedi-
ment accumulation factor (BSAF) or a bioaccumulation
factor (B AF). Where possible, the BSAF and the B AF are
defined by measurement (USEPA, 1995). The implicit
assumption is that the BSAF and the B AF are estimates of
an invariant steady-state relationship between tissue con-
centration and sediment or water concentration.  By that
we mean the following: the BSAF and BAF are applicable
to conditions that differ from the measurement conditions
such that achieving a sediment concentration equal to the
TS C or a water concentration equal to the TWC will result
in a tissue concentration, equal to the MATL.


Applicability of Measured BSAFs
and BAFs                                 -

     Measured BSAFs and BAFs can be applied to the
clean up level or criteria/standards problem only if they
describe the invariant steady-state relationship that is
implied by their use. Numerous examples exist where this
is evidently not the case.


BSAFs and BAFs vary with location

     In the Hudson River, the polychlorinated biphenyl
(PCB) BAFs measured in 1990  for largemouth bass
decline from ca. 40xl06 to lOxlO6 L/kg lipid with  dis-
tance from the PCB source.  Conversely, the BSAFs
increase from about 1 to 2 g OC/g lipid (see page 4-9). In
Green Bay,  the PCB BSAFs for carp  increase with
distance from the source by factors of 5 to 10 (see page 4-
9). The ratio of ppDDE (p,p'-DDE) inkelp bass toppDDE
in white croaker from the Southern California Bight
increases with  distance from the source, changing by
more than a factor of 7 (see page 4-10).
BSAFs and BAFs vary with time

     At Stillwater in the upper Hudson River, large-
mouth bass  BAFs vary  among years from about
3xl06to 30xl06 L/kg lipid. Similarly, the BSAFs vary
,from about 2 to 4 g OC/g lipid (see page 4- 10).


BSAFs and BAFs vary among species at
similar trophic levels

     Green Bay carp and alewife are at similar trophic
levels, as indicated by similar levels of PCB accumulation
relative to particles at the base of the food web (see
page 4-1 1). Yet, alewife have much lower PCB concen-
trations. Southern California Bight dover sole and white
croaker both consume benthic invertebrates, yet the PCB
and ppDDE BSAFs of the sole are 2 to 3 times lower than
those of the croaker (see page 4-11).
     To explore the potential causes of the variability in
BSAFs and BAFs, consider that they are presumed to
reflect a steady-state relationship among contaminant
concentrations in biota (v), dissolved water (cdl), and/or
sediment  (r2).  In general, both sediments and water
column may contribute to fish contaminant loads, so
     Because the use of a BSAF or a BAF implies an
invariant relationship between the biota and media consid-
ered (i.e., sediment or dissolved water), a constant relation-
ship must exist between dissolved water and sediment:
where Kws is the water-sediment partition coefficient.
     These equations yield the following expressions for
BSAF and BAF:
                   BSAF = —+b
                        = a+bKws

     The coefficients a and b are functions of food web
structure, bioenergetics, and toxicokinetics; The partition
coefficient KTO is a function of contaminant loading and all
                                             4-5

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4-6
                                                             National Sediment Bloaccumulation Conference
of the fate and transport processes. Lack of steady-state
conditions is an obvious cause for BSAF and BAF vari-
ability. BS AF and BAF variation with location could also
be attributable to variations hi Kws or food web structure.
BSAF and  BAF  variation with time may result from
variations hi  KM or in bioenergetics that result from
physiological changes (e.g., lipid content). BSAF and
BAF variation among species may be due to food web
structure, bioenergetics, or toxicokinetic differences.
      Interpretation of BSAF and BAF data must involve
an assessment of whether the implicit assumption of an
invariant steady-state  condition is accurate.  Is a
measured BSAF or BAF value appropriate for regulatory
application or should it be adjusted or discarded? Such
interpretation is hampered because of the probable site-
specificity of BSAFs and BAFs and the many factors that
can invalidate the invariant steady-state assumption.
Use of Food Web Models to Validate
Bloaccumulation Data

      Food web models provide a means for validation
because they mechanistically describe the bioaccumu-
lation process and can ascribe causality to observed rela-
tionships between biota and sediment or water. The utility
of models as validation tools for data is predicated on (he
accuracy of the models.  Two issues are important: (1) is
the bioaccumulation process sufficiently well character-
ized to permit the use of models as diagnostic tools? and
(2) is the uncertainty of model calculations small enough
to allow discrimination among measured BSAF or( BAF
values? A model of PCBs in Green Bay and DDE and
PCBs in Southern California Bight illustrate the robust-
ness of the models. In Green Bay, a single model structure
with one set of bioenergetic and toxicokinetic parameters
accurately reproduced congener and SPCB concentra-
tions in five fish species in five locations that extend over
an  order of magnitude gradient in exposure concentra-
tions (see page 4-14).
      Monte Carlo analysis of a model of ppDDE in dover
sole indicates that model uncertainty is not greater than
the uncertainty of field BAF data, about  a factor of
2 (see page 4-16).


Example

      Green Bay carp PCB data were used as an  example
of  spatial variability in estimated BSAF values.  To
interpret these  data  a  bioaccumulation model was
developed using the same toxicokinetic parameters as
used for the other Green Bay species. The computed
BSAFs are consistent with those observed hi Zone 3B. hi
contrast, the model was  not capable of reproducing the
Fox River and Zone  4  BSAF data while maintaining
parameter  values within  experimental limits (see
page4-17). Thus, the modeling suggests that the Zone 3B
data represent a steady-state relationship between carp
and sediment. Further, it appears that in the other zones
the carp were not at  steady state with the sediments,
possibly because the sampled sediments do not properly
describe the exposure concentrations seen by the carp.
     Southern California Bight ppDDE and PCB data
in three species of birds were used to assess from what
location the birds received their contaminants.  To
interpret these  data,  a bioaccumulation model was
developed using the same toxicokinetic framework
for all three species!  Measured prey  and predator
concentrations were consistent for the peregrine fal-
con and bald 'eagle, suggesting that our view of the
feeding behaviors and feeding locations of these spe-
cies is reasonable. However, prey and predator levels
were not consistent for  the double-crested cormorant
on Santa Barbara Island, suggesting that the  cormo-
rants feed in less  contaminated areas than previously
assumed.


Conclusions

    •  Food web models provide a means to interpret
       bioaccumulation data.
    •  Models are necessary to test assumptions implicit
       hi data-based  BSAF and BAF values used for
       regulatory purposes.
    •  Two potential applications of models are:
       (1) to refine the database of BAF and BSAF values
       used for regulatory purposes and
       (2) to increase confidence in regulatory decisions
       having substantial economic implications.


References

USEPA.   1995. Great Lakes Water  Quality Initiative
     technical support  document for the procedure  to
     determine bioaccumulation factors.  EPA-820-B-
     95-005. U. S. Environmental Protection Agency,
     Washington, DC.

-------
Proceedings
                                                    4-7
    A typical use of bioaccumulation factors is in the
    derivation of clean up levels or criteria/standards for
    water and sediment:

          Sediment Target Level (STL in mg/kg)
                   STL = vc/BSAF

         Water Column Target Level (WTL in jjg/l)
                    WTL = v /BAF
              '       •       C        ,               •

    Where possible, the BSAF and the BAF are defined by
    measurement.
    The implicit assumption is that the BASF and BAF
    values are estimates of an invariant steady-state
    relationship between tissue concentration and
    sediment or water concentration

    i.e., achieving a sediment concentration equal to the
    STL or a water column concentration equal to the WTL
    will result in a tissue concentration equal to vr

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4-8
National Sediment Bioaccumulation Conference
The steady-state relationship among contaminant
concentrations in biota (v), dissolved water (cd1) and
sediment (r2) is:
                      v = acd1 + br2
If a and b are both non-zero, an invariant relationship
requires that:
which yields:
                    BSAF = aK  +b
                               ws
                     BAF=a+ _b
                                K
                                 ws
and, thus, requires that a, b and Kwsare invariant
                     (2)





                     (3)



                     (4)
The constraints are restrictive, because:

•   Equation (1) is only valid at steady-state

•   a and b are functions of food web structure,
    bioenergetics and toxicokinetics
    Kws is a function of contaminant loading and all of the
    fate and transport processes
Thus, it is probable that many BSAF and BAF values
calculated from measurements do not reflect an invariant,
steady-state condition.

How can we interpret BSAF and BAF data ?

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Proceedings
                                                                       4-9
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-------
4-10
                                    National Sediment Bioaccumulation Conference
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-------
Proceedings
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-------
 4-12
                                                       National Sediment Bioaccumulation Conference
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                	« i '"«ni itnnm i lumn i in inn i mini
               -  U = -2.332
               S  s =  1.107
                  HUI in IHIII 11 niiiiii—11 mum 11 mum—rmra
               -  u = 2.373
               I  s = .471
                i mmi miniii 11nmn i mmii i
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                                                        10   10   10   10   10   10   10
                           Kow
                                                                      Kow
Water-Sediment partitioning  for PCB homologs and congeners (L/kg OC)

-------
Proceedings
                                                    4-t3
How can we interpret BSAF and BAF data ?

    By using food web bioaccumulation models.

Models provide this capability because:

•   They describe the process of bioaccumulation and can
    account for water & sediment exposure, time variability
    and food web structure

•   They are credible: capable of reproducing field data
    using parameterizations that are supported by
    experimental data and are consistent within and across
    food webs

•   Their uncertainty is not overwhelming

-------
4-14
                                              National Sediment Bloaccumulatlon Conference
        GREEN BAY WET WEIGHT-BASED CONCENTRATION
                               TOTAL PCBs
10

 8

 6

 4

 2

 0
                    Walleye
                                           Brown Trout
                 1  2a,b  3a  3b 4
                     Zone
I   I   I   I   T
         I   i
    1 2a,b 3a  3b 4

         Zone
                      1.0

                      0.8

                      0.6

                      0.4

                      0.2

                      0.0
                                                  III
                                   Alewife
                                  ~i—i—i—r
 1 2a,b 3a  3b  4
     Zone


  Zooplankton
i   i   i   i   r
                                1 2a,b 3a 3b 4

                                    Zone
                                          1  2a,b 3a  3b  4
                                                Zone
                                                           Rainbow Smelt
                                                          "i—r~n—i—r
                            1 2a,b 3a 3b 4

                                 Zone
50

40

30

20

10

 0
Phytoplankton (ug/gOC)
          —n—r~
T
                                                              I ^T—I	1
                                                      1  2a,b  3a  3b  4

                                                           Zone
          Food Web Model Calibration. Computed and observed total PCB
          concentrations, ng/g whole body wet weight, for all spatial zones.
          Lines: model calculations. Filled circles: data.

-------
                                                                      4-J5
                   GREEN BAY LIPID-BASED BAFs
                  Walleye
                                        io9
                                              Brown Trout
                                        ™6;r
                                        io5;i
             4   5  6   7   8   9
                   Log (Kow)
                                           456   7   8   9
                                                 Log (Kow)
     Gizzard Shad
10
io8i
10
10
10
10
      5   6   789
        Log (Kow)
                                  Alewife
                             4   567   8  9
                                  Log (Kow)
                                 Zooplankton
                             4   56   78   9
                                   Log (Kow)
                                                         Rainbow Smelt
                                                       4   56   7   89
                                                             Log (Kow)
                                                      Phytoplankton (UKgOC)
                                                     10
                                                     10
                                                     10
                                                     10
                                                     10'
                                                     10
                                                           i    r  i    i
                                                        4-5   6.7   89
                                                              Log (Kow)
           Food Web Model Calibration. Computed and observed lipid-based
           bioaccumulation factors for zone 3A. l_/Kg lipid.

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 4-16
                                       National Sediment Bioaccumulatton Conference
       O

       I?
       ij
       0 I
       o
       a.
       a.
                              DOVER SOLE
                                  Year

           Comparison of Predicted and Observed ppDDE Concentrations in Dover Sole
           Solid Lines are Model Results
           Dashed Lines are 95% Confidence Intervals around the Mean (Monte Carlo)
           Data are Arithmetic Means and 95% Confidence Intervals around the Mean
Using a model to examine the Green Bay carp data we
conclude the BSAF values in the Fox River and zone 4
represent non-steady state between the fish and the
sampled sediment

•    Differences in toxicokinetics and bioenergetics do not
     account for the spatially variable BSAFs

•    Differences in food web structure do not account for the
     spatially variable BSAFs

-------
,PI
                                                       4-17
            O
            O
            Q.
           ?°
            O
            O
           U- ™
                    FOX RIVER
                                  EASTERN ZONE 3B

60.0
40.0
20.0



	 1 	 1 	 1 	 1 	 1 'III!

'. . -
^rnr.

80.0
60.0
40.0
20.0
0.0

•

. -
T
' /'uJ-^Hl , "

                  WESTERN ZONE 4!  "  „„„   EASTERN ZONE 4
                                     ' Log Kow
                Bioaccumulatiori Factors for RGBs in Green Bay Carp
                PCB Congeners Grouped into 0.5 Log Kow Bins
                Data are Arithmetic Means and 95% Confidence Intervals
                    Conclusions
      Models provide a means to interpret bioaccumulation
      data

      Models are necessary to test assumptions implicit in
      data-based BAF and BSAF values

      -   to refine the  database of BAF and BSAF values
          used for regulatory purposes
                                     -•            *•«

      -   to increase confidence in regulatory decisions
          having substantial economic implications

-------

-------
                                                     National Sediment Bioaccumulation Conference
Bioaccumulation Modeling of  PCBs  in
the Hudson Estuary:  A Review and
Update
Robert V.Thomann and Kevin J. Farley
Manhattan College, Environmental Engineering Department, Riverdale, New York
 Introduction

     Theissueof polychlorinatedbiphenyl (PCB) accumu-
     lation in the striped bass of the Hudson estuary
     has been a matter of concern for several decades.
 Early discharges of PCBs to the estuary resulted in total
 PCB concentrations in the striped bass during 1978 to
 1982 of 5 to 10 times the U.S. Food and Drug Adminis-
 tration (FDA) action level of 2 (ig/g(wet). The fishery has
 been closed to commercial harvesting since the mid-
 1970s.
 Bioaccumulation Model

      A linked homolog-specific, physicochemical bib-
 accumulation model was constructed (Thomann et al.,
 1989,1991) to help address questions of the effectiveness
 of upstream controls on PCBs in reducing the PCB con-
 centration in the striped bass or, if no
 action is taken, the time it would take to
 reach acceptable levels in  the fish.
 Model calibration was accomplished
 with stripedbassdatafrom 1978 through
 1987 and indicated that more than 90
 percent of the observed PCB' concentra-
 tion was due to food web transfer. Pro-
 jections were made of the expected de-
 crease in PCB concentration in the
 striped  bass from 1987 to 2010.  The
 projections were based on a PCB ho-
 molog-specific modeling framework
 that included a time-variable, age-de-
 pendent striped bass bioaccumulation
 model.   Those results indicated that
 under a no-action scenario, the average
 PCB concentration in the striped bass
 in the mid to lower estuary would de-
 cline below  the FDA action level of
 2 ug/g(wet) by about 1994 to 1995.
   10
.«•  8
 GQ
 o
 a.

1
              Model Post-Audit

                  Data obtained by the New York State Department
              of Environmental Conservation (as stored in TAMS ,1996)
              are now available to check the projections up through
              1994. Observed mean total PCB. concentrations in 2- to
              5-year-old striped bass in the  mid-lower estuary
              (designated SB2 group) declined from about 3.5 ug/
              g(wet) in 1988 to about  1.6 ug/g(wet)  in 1994.  A
              correction of the original projection was necessary due to
              a numerical error in exposure concentration hi Food Web
              Region #4, the Long Island Sound and New York Bight
              area. This correction resulted in a reduction of less than
              about 0.5 ug/g(wet) from the original projection. Using the
              original input load projections, the comparison to the
             " observed data for SB2 is shown in Figure 1 and indicates
              that the model underestimated the mean in 1989 and 1990
              but adequately reproduced the means in 1992 and 1994.
              The variability in the data is large with 5 to 95 percentile
o
1987
                     5% tile [4-
                              _i_
1988   1989    1990
                             1991
                            YEAR
                                   1992   1993   1994   1995
 Figure 1. Comparison of original (as corrected) model projection
 (solid line) made in 1987 to observed data of striped bass (2-5 yr old),
 Food Web Region #2.
                                            4-19

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  4-20
                                                                 National Sediment Bioacci
                                                                                                Confe
  range in individual samples of about an order of magni-
  tude distributed approximately lognormally. Projections
  of the percent frequency of samples below a target level
  mean of 2 ug/g(wet) were also made, and comparison to
  observed data (Figure 2) indicated that the original model
  overestimated the frequency =< 2 fjg/g(wet) in 1990 but
  tracked the general trend in the data of an increasing
  frequency=<2 |ig/g(wet) in the years 1992 to 1994.
       The model has been updated in two areas: assessment
  of the effect on striped bass from a temporary increase in
  upriver loading and an evaluation of a varying migration
  pattern of the striped bass.  To assess the effect of the
  increase in loading, a fivefold increase over the originally
  projected load from the upper river was added for the one year
  of 1991. Preliminary results indicate a calculated increase of
  total PCB concentration of about 0.4 to 0.8 ug/g(wet) for
  1992 to 1994 in the SB2 group. The effects of theincreased
  load are dissipated in about 5 years in the mid-lower estuary.
       For the effect of varying migration, recent research
  by Secor and Piccoli (1996), who estimated .the exposed
  salinity regime in striped bass from measurements of the
  Strontium/calcium (Sr/Ca) in the otolith, has indicated that
  some male striped bass remain in the mid to upper estuary
  anddonotmigratetotheocean. Figure 3 shows acomparison
  of female and male SB2 total PCB concentrations from the
  data base. The higher median concentration in the males is
  observed, as well as considerably higher extreme concen-
  trations in the male SB2 over the female SB2 group. The
  model results for nonmigratory behavior, shown in Figure
 4, indicate an approximate doubling of the concentration in
 the striped bass and help explain the elevated concentra-
 tions that have been observed.


 Projections to Year 2010

      Revised long-term projections based on varying
 bass migration patterns and the original load projections
 are shown in Figure 5 for the mean and Figure 6 for the
 estimated frequency of occurrence =< 2 |ag/g(wet). The
 revised projections indicate that by the year 2000, the
 mean total PCB concentration is estimated to be between
 0.8 and 1.8 ug/g(wet) with an estimated 75 to 95 percent
 of the  total  PCB concentrations in  the SB2 group =
 < 2 ug/g(wet). However, for the mid-upper estuary, cal-
 culated  mean total  PCB concentration is  about
 2.1 ug/g(wet) for 2- to 5- year-old bass, indicating that
 this region can be expected to have elevated concentrations
 over a longer a period of time than the mid estuary region.


 Conclusions

      Forthis work, which is still in progress, it is concluded
 that the original model generally tracked the  observed
 decline in mean total PCB concentrations in the striped bass
 for the mid to lower estuary although there are year-to-year
 variations  in the mean that are not captured by the model.
 A simulation of a 1-year "pulse" load of five times the
 estimated load in 1991 indicated that such an input persists
 in the SB2 group for about a 5-year  period. Migration
 behavior is particularly significant and contributes to the
 observed variability in the SB2 data. The revised projections
 estimate that SB2 total PCB concentrations will continue to
 decline to levels below the FDA action level. It should be
 noted, however, that such projections are strictly related to
 the projections of the load and, of course, the model itself.
 Reevaluation of the loading using contemporary estimates
 and model recalibration are currently under way. There is a
 continual need to monitor the input PCB loads and the
 concentration in the striped bass and couple such monitoring
 with periodic model post-audits and updates.
References
     1987
                                                      1994   1995
Figure 2. Comparison of observed vs. model exceedance frequencies
(%=< 2 pg/g). Striped bass (2-5 yr old), Food Web Region #2.
              Secor, D., and Piccoli. 1996. Age and sex
                dependent migrations of the Hudson
                River striped bass population deter-
                mined   from   otolith   chemical
                microanalsis. The Univ. of Maryland
                System, Center for Environmental and
                EstuarineStudies, CBL, Solomons, MD.
              TAMS. 1996. Data base for the Hudson
                River PCBs reassessment RI/FS. Data
                base report, Vol. 2A. TAMS Cons.,
                Inc. and Gradient Corp. USEPA Con-
                tract No. 68592001. CD ROM.
              Thomann, R.V., J.A. Mueller,  R.P.
                Winfield, and C-R. Huang.  1989.
                Mathematical model of the long-term
                behavior of PCBs in the Hudson River
                estuary. Final report to the Hudson'
                River Foundation, New York, NY.
             Thomann, R. V., J. A. Mueller, et al.
                1991. Model of the fate and accumu-
                lation of PCB homologues in Hudson
                estuary. ASCE, J. Env. Eng.  Div.
                117(2): 161-177.

-------
Proceedings
                                                                                          4-zr
           10 •—.
                   30
                   20
                   10
                           FEMALE
                                                                 MALE
                                                Sf
                                                      30
                                                       20
                                                       10
                                                         86 87  88  89  90  91  92 93 94
                    86  87  88  89 90 91 92 93 94
                                YEAR
            Figure 3. Variation in total PCS concentration in striped bass (2-5 yr old), Food
            Web Region #2. Line in box = 50th %tile, box boundaries = 25th and 75th %tile,
            symbols = outliers.
                                   MIGRATION
                                    OUT OF
                                   ESTUARY
                      1987  1988  1989   1990  1991   1992  1993   1994   1995
                                               YEAR
                  Figure 4.  Calculated effect of varying migration of striped bass (2-5
                  yr old), Food Web Region #2.

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4-22
                                                            National Sediment Bioaccumulatlon Conference
                    1988   1990   1992  ,1994   1996  1998   2000   2002  2004   2006  2008   2010
                                                YEAR
              Figure 5. Long term model projection using original (1987) load projections
              with varying migration by striped bass. Solid line: striped bass migrates out
              of estuary; dashed line: fish remains in estuary. Striped bass (2-5 vr old),
              Food Web Region #2.
                    1988  1990   1992  1994  1996  1998  2000  2002  2004  2006  2008  2010
                                              YEAR

             Figure 6. Long term model projection of frequency of striped bass =< 2ug/g
             with varying migration by striped bass. Solid line: striped bass migrates out
             of estuary; dashed line: fish remains in estuary. Striped bass (2-5 yr old),
             Food Web Region #2.

-------
                                                            National Sediment Btoaccumu/atfon Conference
  Day Two:  September  12,  1996
 Session  Four:
 Questions  and Answers
 A
fter each session, there was an opportunity for
questions and answers and group discussions per-
taining to the speakers' presentations.
 Q (Ron Sloan, NYS Department of Environmental Con-
 servation): One of the things that Bob brought up, which
 is very interesting from our standpoint as researchers in
 a regulatory agency, is the possibility of regulating on the
 basis of sex in fish. This would be very difficult to do, but
. it raises a very valid point in terms of male and female
 differences, not only for accumulation and behavior in the
 estuary, but also in other systems and for other species of
 fish. Fora number of years we have noted tremendous sex
 differences, with the males always being higher in con-
 centration than the females for striped bass, American
 shad, white perch, the Pacific salmon in Lake Ontario,
 and a number of other species.  Bob, isthereasmuchwork
 going on with you and other researchers as it relates to sex
 differences?

 Robert Thomann:

       I am not doing anything myself, but I have been
 following the literature rather closely. There is a lot more
 information now. I think John has done some work on
 seals! Recently, the Dutch did some work on exposing
 males and females and looking at bioaccumulation in the
 laboratory, which showed significant differences.  But I
 have a question back to you. Did I understand your
 opening comment to mean that you really are  thinking
 about regulating by sex?   •  . . J

 Q (Ron Sloan): No, no.  There is no real way to be able
 to do that, but it is very bothersome that we do not have any
 good explanation/or why the males are so much higher in
 concentration, even controlling for gamete production
 and the lipid consequences associated with voiding of egg
 material from the females. The sex'differences are still
 there and they are very dramatic.

 Robert Thomann:

      Well, I think it is because they are staying in the
 estuary.         '
Q (Ron Sloan): Maybe for striped bass, but even if you
look at the males in the lower part of the estuary that are
freshly migrating in from the ocean, the males will tend to
be higher in concentration.  That still does not explain the
sex differences that we see very dramatically in Pacific
salmon and white perch.  One of the reasons I raised the
point is because we have been looking the past few days
now at the uncertainties associatedwith BAFs andBSAFs,
and I think a lot of the uncertainty and the variability is
associated with sex differences when we start looking at
fish.               •.          •

Robert Thomann:

     Well, I think that is true. The sex differences, atleast
for this case, do contribute significantly to the variation.
If you calculated BAFs here, they would be all over the lot. •
As John pointed out, part of it is the disequilibrium
between the fish and the water. This would be the same for
BSAFs.  They would be very time variable and very
spatially variable.

Q (Ron Sloan): We have looked at that to some extent, and
we cannot really account for it because the lipid concentra-
tions are so low. Gamete loss cannot explain the differences.
/    '                            '      '          •
John Connolly:

      We have looked at a lot of data in a more generic
sense and it seems to be  a mixed bag.  We do see a
difference for some species, but we do  not for other
species.  You, particularily see it in aquatic mammals.
Milk production  and the Joss due to' that explains the
differences for the. aquatic mammals. But I do not think
we understand the reason for those differences in fish.

Q (Ron Sloan): My primary reason for bringing this up as
a question or an issue  is that,  if  we are interested in
explaining a lot of the variability that we are observing, we
need to take into account the sex differences.

Q  (Nelson Thomas,  U.S. EPA, Office of Research and
Development): This is a question for John and Bob. In
Frank's presentation, he alluded to an uncertainty factor
                                                4-23

-------
 4-24
          National Sediment Bioaccumulation Conference
 of 3 at the 95 percent confidence level. Did you look at
 your 95percent confidence-level in your calculations and
figure out how far off you would be like Frank did?

 John Connolly:

      The one that I showed, which was for Dover sole,
 was about a factor of 2. In a couple of other calculations,
 where we have done uncertainty factors, the factor of 2 to
 3 is pretty robust. That is what we are generally seeing in
 these calculations.

 Robert Thomann:

      That is true.  If you look closely at those percent
 exceedance frequencies, you will see about the same kind
 of variability.

 Larry Burkhard:

      John, I have a slide of the probability distribution
 for the 2-year  old  flounders from your New Bedford
 harbor model.  This figure is from a publication in the
 SETAC Journal.  It illustrates  the uncertainty that they
 found using a Monte Carlo simulation for his model. You
 can see here that a factor of 2 to 3 is right on line. I just
 wanted to point out the kind of uncertainties that you have
 with these models.

 Robert Thomann:

      I interpreted Nelson's question as asking what our
 uncertainty was in the 95th percentile estimate, or hi other
 words, in the tail of the distribution. We have the ability
 to project or analyze for the 95th percentile to a factor of
 about 2 or 3.

 Q (Jay Field, NOAA):   In situations where we have
 vertical gradients in terms of sediment concentrations,
 has anybody looked into the implications of biological
activity, which may vary seasonally or by location, and
 the impact  it might have on some of the models? How
would any  effects that we see affect the way we collect
information?

John Connolly:

      With some of the work I have done, I have seen more
location differences. I have not paid a lot of attention to
the seasonal differences that might exist.  So, I  cannot
comment on seasonal differences within a system.  But
clearly, we see differences from system to system, de-
pending to a large extent on the type of organisms com-
prising the benthic infauna. In determining whether or not
we are worried about the top  centimeter or the top 5
centimeters as being biologically available material, that
is more of an issue for higher level organisms.  This is
something that again introduces considerable uncertainty,
both in models and into the B AF and BS AF. That was one
of the points I was trying to make with the Fox River. The
model results suggest that the carp are seeing material
 recently deposited in the river, as opposed to material that
 is buried a few centimeters down. If carp were exposed to
 material a few centimeters down, they should have been at
 much higher concentrations than they were.

 Robert Thomann:

      The only calculation I have done in that area was
 associated with the cadmium and the blue crab in Foundry
 Cove, where there was a considerable amount of sediment
 mixing and sediment bioturbation. In that particular case,
 bringing up deep sediment to the surface and then letting
 that get into the food chain, actually retarded or slowed
 down the recovery of the cove.  Recovery was delayed
 because you are just accessing higher concentrations over
 a longer period of time. It is very interesting. It increases
 the flux to the water column, so you are actually depurat-
 ing out the sediment with a higher flux. But, because you
 are also reaching down into higher concentrations, you
 also retard the response.

 Q (Ken Finkelstein, NOAA): Dr. Thomann, you presented
 a figure early in your talk that showed the concentrations
 in the striped bass with a no-action  or as is.  You also
 showed on the same figure one that would indicate that
 there was  no change  at all, even with some kind of
 decrease in the load.  Actually, I think you decreased it
 down to zero, or in other words,  it was remediation. I was
 wondering if you could shed some light on that because it
puts some question in remediation plans, both there and
 elsewhere. I have seen this at other sites with models
 where  the models  do  not show any  kind of significant
 change with drastic cleanup operations.

 Robert Thomann:

     What you are focusing on is the calculation that was
 done in 1987 and  1988.  There actually is a difference
 between remediating the upstream sediment and the no-
 action. The difference is only in the_sense that it takes you
 a little bit longer to get to a certain percent'frequency
below 2, if you do not do anything. But eventually they
 come together. The reason for that is we have projected in
the calculation, which I showed in the load projection, that
the upstream load will continue to decline whether you do
something or not in a no-action case.   So, that was that
load projection going down.  That is what we did in 1987,
and that is what we are still doing today. That is  being
revised, but we are still in the process  of doing that.  That
load is declining, but there are also downstream loads,
including loads in the metropolitan area, nonpoint source
loads, and atmospheric loads.  That calculation essentially
said that, after a period of time, the relative contribution
from the downstream sources became more dominant,
and the upstream source became less dominant. So, its
impact  became less and less  as time went on, and
remediating it had less and less  of an  impact.

Q (Ken Finkelstein): Maybe I can also relate a little bit of
a different experience that we have had in doing similar
types of calculations.  Consider the case where the

-------
Proceedings
                                                                                                     4-25
remediation is remote to where you are looking.  For
example, you are remediating in the upper Hudson River
and looking at benefits in the lower Hudson River.  In
many cases, you do not, see a big bang because that load ,
is not controlling the concentrations and the exposure in
the remote area.  In the case of the lower Hudson, it may
be because there is another load. In other cases, it may be
that past historical discharges are controlling the system,
rather than the current discharges  coming from an up-
stream area.   In these cases, eliminating the upstream
source will not show an impact in the downstream area
since that source was not contributing to contaminant
levels in the fish downstream.

Robert Thomann:                       ,

      That says nothing about the advantage of remediating
for the upriver area. There is a local benefit from that.

Q (Arnold Kuzmack,  U.S. EPA,  Office of Science and
Technology): I would like to make a couple of comments
of a somewhat philosophical nature. First, in terms of the
discussions of the uncertainty being within a factor 'of 2 or
3, I think we have to be careful of how we use the
terminology here, particularly when distinguishing be-
tween variability and uncertainty. Uncertainties tend to
deal more with things thai we do not know. For example,
lam sure when you were doing your original models in the
1980s, you assumed that the fish were homogeneous in a
^migration pattern. You probably did not realize you were
making that assumption.  If you had listed your assump-
tions, that probably would not have appeared, there, and
it turned out to.be wrong. That is an example of uncer-.
tainty. There are other uncertainties in just how well can
we measure, what all we are including in the models, and
so forth. The second comment I would like to make relates
to  John's discussion  of the data  versus  modeling.   I
absolutely agree with your comment that whenever you
use data you have some sort of implicit model. I would
indicate caution  on the part where you said that  the
models incorporate everything we know about the sci-
ence.  I think almost by definition they do not include
everything. They include some sort of schematization and
rationalization of our knowledge. And we sort of discard
the things we do not understand that are in the data.  I
think  because of that we have to  be careful to do ah
appropriate degree of ground truthing ~of the models,
which you all did in your research.  I think 'one could
criticize regulatory agencies in perhaps putting too much
 reliance on models that do not have that kind of ground
truthing, particularly for situations like some permit pro-.
 cess applications or decision-making based on model results
 that.are not clearly understood. I think in these sorts of
 situations, you have to be pretty careful about having the
 models run away with things, I think that is what probably
 the data advocates are trying say.  ,    '

 Robert Thomann:

       I think the other point, too, is deciding when a model is
 useful for regulatory or management purposes.  Who
makes the decision that models are'ready for use hi some
kind of decision-making process? I have always felt that
regulators and lawyers do not make that decision. They are
not in a position to evaluate it. The people who ultimately
make the determination of whether a model is suitable for
management purposes or decision-making are members
of this community. It is the  scientific community that
determines when the model can account fpr all the impor-
tant factors and produce results that make sense relative to
the data. This is the group that throws holy water on it.

Q (Dave Michaud, Wisconsin Electric Power Company):
John, in looking at the carp data from the Fox River and
Green Bay system that you-presented, I am not surprised
about whatyousaw. The carp population in the Fox River
is a'restricted population that lives in a highly regulated
environment with a number of pools controlled by dams.
You see greater-variability in Green Bay becausethere is
an intense depositional gradient along the east coast, and
the carp can and do move freely between Green Bay and
Lake Michigan.  I would guess that you were probably
sampling fish that were 10 to 15 years old) so they have a
unique uptake history relative to the alewife. That leads
me to my second comment. At one point in your presen-
tation you grouped alewife and carp together in terms of
trophic levels. I am not sure I understand the logic behind
•that.   Except for an occasional amphipod or mysid,
alewife feed primarily on plankton.  The food habits work
that we have done on carp in Lake Michigan suggests that
it feeds almost exclusively on benthic organisms. We have
found very little plankton in examining the gut contents. I
would not call these the same  trophic levels. How would
you also factor in the obvious age differences in terms of
exposure? Typically, alewife live only 3years, while carp
can survive for more than 25 years.

John Connolly:                         .

      The data that we had was for carp over a rather wide
range of ages, so we were not looking specifically at carp
that were 14 or 15 years old. When I was talking about the
Fox River, I was referring to the lower Fox River below
DePere Dam, where the carp are not confined in pools.
But you just raised a lot of questions that I think are all
valid. The point I was trying to make is that models .allow
you to explore those questions, as opposed to just  using
them to generate a number you can run around and
extrapolate  with.

Q (John Zambrano): This is a question for the panel from
a regulator. Yesterday Philip Cook described the work
 that EPA did for the Great Lakes Initiative (GLI)for the
purposes of establishing BAFs for setting water quality
 standards.  What, does the panel think of that  work,
particularly its applicability to the rest of the nation and
 the use of a disequilibrium constant of 25?

 Frank Gobas:

      My understanding of the process is that they used a
 bioaccumulation model for a particular system to derive

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 4-26
                                                               National Sediment Bioaccumulation Conference
 bioaccumulation factors,  food chain multipliers, and
 BSAFs.  Then  they applied these values to different
 systems, assuming that they are applicable for these other
 systems. What we try to do in our modeling is exactly the
 opposite. We are providing people with models that allow
 them to put hi site-specific factors so that they can derive-
 these values, the food chain multipliers, BSAFs, and
 BAFs,  for various  systems.  We believe that not all
 systems are the same and that you cannot extrapolate from
 one system to another.  So, my feeling is that the models
 can be used much more effectively when they are applied
 on a site-specific basis to  work out these  important
 bioaccumulation properties.

 John Connolly:

         I think you have to put the GLI work into context.
 What the GLI work was attempting to do was to develop
 bioaccumulation factors that could be applied to the Great
 Lakes.  I do  not think they had it in mind to use these
 factors for national criteria. So, I do not think that there is
 any intent to say that this  approach  is automatically
 applicable nationwide. I think that the GLI documents are
 very careful to point out a lot of the things that came out
 in these talks, in terms of the cautions in the use of this
 data. They are very clear in talking about site-specific
 application. They provided a generic number because it
 was their responsibility to do that. But they also provided
 all of the cautions associated with the application of those
 generic numbers.

 Larry Burkhard:

      I might add that in the GLI itself there is a tiering,
 starting with field data from the Great Lakes and ending
 with something that is totally model-derived from very
 generic kind of parameters from Lake Ontario.  That is
 reflective of the knowledge that we had at the time that that
 was constructed and advanced.

 Q (Mike Kravitz, U.S. EPA, Office of Science and Tech-
 nology): This is sort of along the lines of the last question.
 What happens in terms of marine -waters?  What is the
 value of using things like BSAFs in systems that are so
 dynamic? Will we be able to do that?

 Robert Thomann:

     BAFs and the BSAFs have served us well and
 will continue to serve us well as kind of a first-order
 screening.  There will always be a utility to BAFs and
 BSAFs combined with the kinds of calculations we
 have been showing.  So, I do  not think it is totally a
 question of discarding entirely the BAF and BSAF
 concept. That is not the point. The point is to be aware
 of the kinds of variability that can exist and the causes
 of that variability in those two numbers. In marine
 systems, I think ultimately we would get to the point of
 looking much more specifically at fully time-variable
 calculations, which,  up to  a point, are entirely
doable today by just about anybody. Again, we must
 recognize all of the caveats and all of the assumptions
 that have been made.  But I think we may be heading
 in the direction of working on those kinds of systems,
 supplemented by the BAF and BSAF concepts.

 Q(Gayle Gartnan, NOAA): I have spent most of my career
 dealing with issues of whether a site should be remediated
 and to what degree it should be remediated, particularly
 sites  with PCB contamination.  So,  I was particularly
 interested in Dr. Thomann's presentation and his projec-
 tions for the Hudson River. I found it a little disturbing
 since it seems to imply that the PCBs in the Hudson River
 are going to essentially be assimilated. Am I going to end
 up doing calculations of assimilative capacity for PCBs?
 I think about that and also about some data we have for
 Puget Sound, which show that the salmon that return to
 Puget Sound actually have higher levels of PCBs in their
 tissue than the salmon that leave  Puget Sound.   So, I
 wonder again, if your models are very accurate for the
 little part of our system that you are modeling, but that
 they do not show us what happens outside of that system.
 I would like you to comment on that  and  what you
 think your  models  imply for  decisions about
 remediation.

 Robert Thomann:

      Again,  I think remediation has an  impact locally.
 There is no doubt about that, since that has been shown
 any number of times.  This was a question of remediating
 an upriver site and its impact on a migratory fish popula-
 tion.  So that is the focus. One should not conclude from
 the results that remediation does not affect a population or
 the concentration of PCB sin a population. It does. But it
 depends on its relationship to the target organism. I do not
 mean to imply the question, why remediate? Why do the
 PCBs seem to be declining? Fundamentally, what hap-
 pens in this calculation is the PCBs ultimately are being
 flushed out into the ocean and the exchange with the ocean
 is diluting it. There is also a continual burial of PCBs. If
 you look at the rate of decline of the striped bass over time
 and make an estimate of average burial  rates  over that
 period of time (and this is  the crudest calculation), you
 find out that PCBs are continually being buried. Also, the
 assumption here is that the upstream load is declining.
 Why is that declining? It is declining for similar kinds of
 reasons.  But remember, this is a long-term projection.
 There are two issues you need to be aware of. One is this
 calculation assumes that the loads to the system from point
 sources and nonpoint sources will  continue to decline.
 That may not be the case.  They may level off at some
 point.  The second is that this calculation assumes when
 the fish goes out to the ocean, it sees zero PCBs. That is
 what we did in the old days. We are revisiting that part of
 the calculation, now that much better data are available for
 what is going out into the ocean. So we send these larger
 fish out 8 or 9 months of the year, and they see zero PCBs.
If the  concentrations out there are now higher than zero,
 which in fact they are, then those fish are going to come
back at a different concentration than we had originally
calculated.

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                                          National Sediment Bioaccumulation Conference
Risk Assessment Overview
Dorothy Patton
U.S. Environmental Protection Agency, Office of Research and Development,
Washington, DC
Please contact the speaker for information on this presentation.
                                  5-1

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                                               National Sediment Bioaccumulation Conference
Session  Five:
Human  Health-Based Risk
Assessment
Marc Tuchman, Panel Moderator
U.S. EPA, Great Lakes National Program Office,
Chicago, Illinois

Judy L. Crane
MnnesotaPollutionControl Agency,
St. Paul, Minnesota
MethodologyfbrAssessingHumanHealth-Based'Risks

Amy Pelka
U.S. EPA Region 5,
Chicago, Illinois
Bioaccumulation Models and Applications: Setting
Sediment Cleanup Coals in the Great Lakes

Robert L. Paulson
Wisconsin Department of Natural Resources,
Madison,  Wisconsin.
Use of Human Health- and Ecological-Based Goals in
Developing a Whole River Sediment Strategy: Fox
River, Wisconsin

Laura B.  Weiss
Washington Department of Ecology,
Olympia, Washington
Development of Health-Based Sediment Criteria for
Puget Sound

Alex Lechich
U.S. EPA Region 2,
New York, New York
Development of Bioaccumulation Guidance for
Dredged Material Evaluations in EPA Region 2
                                      5-3

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                                                          National Sediment Bioaccumulatioh Conference
 Methodology for  Assessing Human
 Health-Based  Risks
 Judy L. Crane                 .
 Minnesota Pollution Control Agency, Water Quality Division, St. Raul, Minnesota
^•Hhe purpose of this presentation is to discuss how and
  • why human health risk assessments are conducted
  M. at contaminated sediment sites. The main compo-
nents of risk assessments (i.e., site  characterization,
toxicity  assessment, exposure assessment, and risk
characterization) are described. In addition, the advan-
tages  and  limitations of using  a risk assessment
approach, as it applies to bioaccumulative contaminants,
are discussed. The variety of methods by which human
health risk assessments can be conducted are described,
and these methods are  illustrated with examples from
baseline and comparative risk assessments conducted as
part of the GreatLakes National Program Office's (GLNPO)
Assessment and Remediation of Contaminated  Sedi-
ments (ARCS) program.


Why Use a Risk Assessment
Approach?

      Risk assessmentprovides a scientific basis by which
estimates of noncarcinogenic and carcinogenic risks can
be estimated at a contaminated site. These risk estimates
can be used to address  management questions about a
site; for example, what are the baseline (i.e., current) risks
to residents living in the Sheboygan River, Wisconsin,
Area of Concern (AOC)? or how would risks change at the
Buffalo River,  New York, AOC if various remediation
alternatives were implemented? A risk assessment ap-
proach can  also be used for regulation and enforcement
purposes, as well as for the selection of clean-up criteria.
      In the United States, the triggers that initiate a risk
assessment include regulatory action leading to place-
ment on the National Priorities List or a state-equivalent
list of contaminated sites.  Thus,  human health risk
assessments are conducted at all Superfund sites. In,.
contrast, Canada has additional trigger mechanisms for
risk assessment, including real estate transactions, rezoh-
ing/redevelopment, regulatory placement on a priority
list, new legislation, or regulatory orders (Golder Asso-
• elates, 1993). .Canadians also have the option of using a
criteria-based approach instead of a risk-based approach
at contaminated sites.
     The primary advantages of using a risk assessment
approach include the following:
    • Provides a quantitative basis for comparing and
      prioritizing risks.
    • Improves the understanding of risk.
    • Acknowledges the inherent .uncertainty in
      estimating risk.
    • Estimates clear, consistent endpoints (e.g., cancer).
    • Separates risk assessment from risk management.
     The limitations and uncertainties associated with
human health  risk assessments  are discussed in the
following sections.
Components of Human Health Risk,
Assessments

     The specific components of human health risk
assessments are described in this section. The U.S.
Environmental Protection Agency (EPA) has developed
exposure and risk assessment guidance for use  at
Superfund sites (USEPA,  1988, 1989a, 1989b, 1991)
which can be applied to other  contaminated sediment
sites.  Refer to this guidance for detailed information
about how to perform a site characterization, toxicity
assessment, exposure assessment, and risk characteriza-
tion for a contaminated site. A brief review of these steps
is given below.            .


Site Characterization

     Available site information is reviewed,  and rel-
evant site samples are gathered, analyzed, and evaluated
for appropriate quality assurance measures in this step.
Potential site-related contaminants are compared with
background values. In addition, potential contaminants
of concern are identified, and a set of data is developed for
use in the risk assessment.
                                              5-5

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5-6
          National Sediment Bioaccumulation Conference
Toxicity Assessment

     Verified toxicity values are obtained from EPA's
Integrated Risk Information System (IRIS) database. For
chemicals lacking a ''verified value," interim toxicity
values can be obtained fromEPA's Health Effects Assess-
mentSummaryTables(HEAST)andfromtheh'terature. The
reference dose (RfD) is the toxicity value used to evaluate
noncarcinogenic effects (e.g., neurotoxicity, reproductive
and developmental toxicity, immunotoxicty, organ-specific
toxicity). The slope factor is the toxicity value used in
evaluating carcinogenic effects. It quantitatively defines
therelan'onshipbetweendoseandresponse. TheEPAweight-
of-evidence classification scheme indicates the strength of
evidence that the contaminant is a human carcinogen.


Exposure Assessment

     This component involves the greatest use  of as-
sumptions and professional judgment when site-specific
information is lacking. The major parts of an exposure
assessment include the following: characterize the physi-
cal setting, identify potentially exposed populations,
identify potential exposure pathways, estimate exposure
concentrations, and estimate chemical intakes. The most
important  exposure pathways identified at five Great
Lakes AOCs included the consumption of contaminated
fish and/or waterfowl (Crane, 1996). In addition, most of
the carcinogenic risk was due to elevated concentrations
of polychlorinated biphenyls (PCBs) in fish tissue. In the
exposure assessment, it is important to identify sensitive
subpopulations such as sport anglers, ethnic groups that
consume a greater proportion of fish in then- diet, and
pregnant women who consume contaminated fish. Dur-
ing the past few years, the Agency for Toxic Substances
and Disease Registry (ATSDR) hasiunded a Great Lakes
Human Health Effects Research Program that will pro-
vide more exposure information about sensitive sub-
populations in the Great Lakes area, as well as how fish
preparation and cooking  practices can reduce bioaccu-
mulative contaminants in fish tissue.


Risk Characterization

     In this step, the exposure and toxicity estimates are
combined into an integrated expression of human health
risk. Noncarcinogenic effects are evaluated by compar-
ing an exposure level over a specified tune period with an
RfD derived from a similar exposure period. • Carcino-
genic effects are estimated as the incremental probability
of an individual developing cancer over a lifetime as a
result of exposure to the potential carcinogen. This risk
is computed using average lifetime exposure values that
are multiplied by the oral slope factor for a particular
chemical.  Noncarcinogenic and carcinogenic risk esti-
mates are summed separately for all chemicals in an
exposure pathway (e.g.,  fish consumption).  The risk
estimates are then summed for multiple exposure pathways.
This summation does not account for any synergistic or
antagonistic effects that  may occur among chemicals.
The risk characterization  also includes an evaluation of
 the  uncertainties associated with the risk estimate.
 Uncertainty is reduced by using as much site-specific
 information as possible. Refer to USEPA (1989a), Colder
 Associates (1993), and Crane (1996) for additional infor-
 mation on evaluating uncertainties.
 Risk Assessment Methodologies

      Given the risk assessment framework described
 above, human health risk assessments can vary in their
 complexity and scope. Risk assessments can be conducted
 in a qualitative, semi-quantitative, or quantitative way.
 The level of detail and cost associated with conducting a
 risk assessment increase as more quantitative results are
 needed. The human health risk assessments conducted for
 the ARCS program (Crane, 1996) were done in a semi-
 quantitative way because uncertainty was expressed in a
 qualitative way and quantitative risk estimates were esti-
 mated.  Semi-quantitative risk assessments compose the
 greatest proportion of risk assessments conducted in the
 United States.
      Semi-quantitative risk assessments are conducted
 using a deterministic approach (see Table  1). In this
 approach, a single number is used from each parameter
 set to calculate a single value of risk.  Quantitative risk
 assessments are conducted using a stochastic approach
 (see Table 1), whereby a distribution of values for each
 parameter set is used in the risk calculation and a distri-
. bution of risk is produced. Some jurisdictions, such  as
 British Columbia, are starting to require quantitative risk
 assessments at some contaminated sediment/soil sites.
      Human health risk assessments conducted for the
 Superfund Program include baseline conditions and future
 land use exposure scenarios. Future land uses do not need
 to be considered if the management questions for the non-
 Superfund site are concerned only with current risk
 conditions to the public. Comparative risk assessments can
 be conducted  to assess the risk, relative to the baseline
 risk, that would result from the implementation of various
 sediment remedial alternatives. The ARCS Risk Assessment
 and Modeling Workgroup developed a comparative risk
 assessmentframewprk to integrate theresultsfrombaseline
 risk assessments, field data, and mass balance modeling to
 provide estimates of the  potential impact of  remedial
 actions onhumanhealth, aquatic life, and wildlife (USEPA,
 1993). A demonstration of this approach was conducted
 for the Buffalo River, New York, AOC (Crane, 1995).
 Problems with Current Risk
 Assessment Practice

      Risk assessment is an evolving science and is not
 without its limitations.  Some of the major problems
 associated with human health risk assessments include
 the following:
     •  Use of arbitrary exposure scenarios.
     •  Excessive  credence to  the   carcinogen
       classification.

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Proceedings
                                             5-7
Table 1. Components of deterministic and stochastic risk .assessments (Golder Associates, 1993).
   Deterministic

   Low degree of public interest
   Relatively low degree of site-specific uncertainty

   Deterministic result is far from action level
   Small-scale project (scope, budget, schedule)
   Routine application
   Large number of potential contaminants and/or
   pathways (rapid screening or triggering tool)
   Initial model development
  Stochastic
                          >

  High degree of public interest
  Relatively high degree of site-specific
  uncertainty    ;      :
  Deterministic result is close to action level
  Large-scale project (scope, budget, schedule)
  Non-routine application
  Small number of potential contaminants and/or
  pathways
  Model refinement
  Quantification of uncertainty
  Detailed value-of-information analysis  (project
  planning)
    • Excessive  reliance on findings from animal
      cancer tests.
    .• Lack of toxicity data for many components/me-
      tabolites  of bioaccumulative contaminants
      (e.g., PCB congeners,, some  PCB  Aroclors,
      polynuclear, aromatic hydrocarbons).
   • • Lack of a quantitative level  of risk that is
      universally acceptable or unacceptable.
    •. Poor assessment of  noncarcinogenic  health
      effects.
    • Uncertainty of risk estimate'may be poorly
      characterized.
    * Risks may not be communicated well  to
      the public.
    • Environmental inequity not always considered
      for low-income and minority populations.
     Despite the above limitations, risk assessment has
been demonstrated as an effective way to prioritize how
scarce funding sources should be spent to provide the
most benefit to human and ecological health!  EPA has
adopted a risk assessment approach, as has the Minnesota
Pollution Control Agency, for determining priorities and
shaping regulatory planning/policy making. As the sci-
entific and policy issues associated with conducting and
communicating human health risk assessments are
strengthened, the public will benefit from this increased
level of confidence in risk estimates.
References

Crane, J.L.  1995.  Comparative  human  health and
     wildlife risk assessment: Buffalo River, New York,
     Area  of  Concern.   EPA 905-R-95-008.  U.S.
     Environmental Protection Agency, Great Lakes
     National Program Office, Chicago, IL.
Crane, LL.  1996.  Carcinogenic human health risks
     associated with consuming contaminated fish from
     five Great Lakes Areas of Concern. J. Great Lakes
     Res. 22:653-668.,
Golder Associates. 1993.  Quantitative human health
     risk assessment. Phase 1 - Review of methods and
     framework recommendation.   Prepared  for
     Ministry of Environment, Lands andParks, Victoria,
     BC, by Golder Associates, Burnaby, BC.
USEPA.  1988. Superfund exposure assessment manual.
     EPA/540/1-88/001.  U.S. Environmental Protection
     Agency, Office of Remedial Response, Washington,
     DC.
USEPA. 1989a. Risk assessment guidanceforsuperfund:
     Human health evaluation manual part A.  Interim
     final. OSWERDirective9285.7-01a.U.S.Environ-
     mental Protection Agency, Washington, DC.
USEPA.  1989b. Exposure factors handbook. EPA/600/
     8-89/043. U.S. Environmental Protection Agency,
     Office of Health and Environmental Assessment,
     Washington, DC.                         ^
USEPA.  1991. Risk assessment guidance for Superfund.
     Volume  I:   Human health  evaluation manual.
     Supplemental guidance: "Standard default expo- '
     sure factors."  Interim final (March 25,  1991).
     OSWER Directive 9285.6-03. U.S. Environmen-
     tal Protection Agency, Washington, DC.
USEPA.  1993. Risk assessment and modeling overview
     document. EPA 905-R93-007.. U.S. Environmen-
     tal  Protection Agency, Great Lakes National
     Program Office, Chicago, IL.

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                                                       National Sediment Bioaccumulation Conference
Bioaccumulation Models and
Applications:   Setting Sediment
Cleanup  Goals in the  Great  Lakes
Amy Pelka
U.S. Environmental Protection Agency Region 5, Chicago, Illinois
Background

     The Great Lakes, much of which is within Region 5
     of the U.S. Environmental Protection Agency
     (USEPA), has significant contamination of hydro-
phobic organic compounds such as PCBs and dioxins.
Because much of this contamination is found in sedi-
ments, consideration of bioaccumulation is required when
making environmental decisions.  Regulatory actions
that deal with bioaccumulative hydrophobic organic com-
pounds are generally either waterway management (Clean
Water Act section 404) decisions or remedial decisions
under statutes  such as Superfund, and the Resource
Conservation and Recovery Act (RCRA). The focus of
this talk will be on  the latter category of remedial
decision-making.
     The presentation will discuss the following:
    •  The need  and precedent  for  the use  of
      bioaccumulation methods in a regulatory setting.
      Region  5  evaluation  of bioaccumulation
      methodologies using  Great  Lakes  data
      (sediments to fish workgroup, or S2F).
    •  S2F-recomfnended process of using bioaccum-
      ulation methods in  combination  with risk
     ' assessment.
    •  Case studies and lessons learned.
Summary

     Environmental decisions often require that sedi-
ment cleanup goals be developed. Issues such as what
level is safe to leave behind, which sediments need to be
removed for it  to be safe, and which remedial  option
offers the best risk reduction, need to be addressed at the
many sites with bioaccumulative hydrophobic organic
compounds. In general, there are few sediment regula-
tory levels that directly address human health. PCBs, a
frequent contaminant in the Great Lakes, are regulated
under the Toxic Substances Control  Act at 50 ppm or
greater, which is not, however, considered to be health-
based.  In some cases there are mandates to return to
background levels, and there are also the  ecological
guidelines developed by the Province of Ontario and the
National Oceanic and Atmospheric Administration
(NOAA).  While these are all useful and relevant, there
was. a perceived gap in having actions that use these as
cleanup goals to be protective of human health.
     A Regional workgroup was formed that sought to
address the issue of how to address bioaccumulative
compounds such as PCBs and dioxins in order to be
protective of human health. To promote consistency
and clarity on the topic, the workgroup developed Re-
gional guidance based on their deliberations. Because.
of the concern about PCB bioaccumulation, the scope of
the workgroup's efforts  was  always on  hydrophobic
organic compounds. Because in general it is not appro-
priate to extrapolate methods or recommendations to
other contaminants that behave differently in the envi-
ronment (such as metals), the workgroup and document
only addressed methods appropriate to  hydrophobic
organic compounds. The workgroup, named Sediments
to Fish, or S2F, contained technical  staff from several
disciplines and areas of the agency. The goal of the
workgroup was to: (1) review relevant  literature on
bioaccumulation; (2) evaluate various methodologies
using Great Lakes data and include a discussion of data
issues; and (3) recommend how best to develop cleanup
goals or, more accurately, how to best use bioaccumu-
lation methodologies in regulatory actions.
     A draft guidance document was completed in
1994. The basic structure of the document is:
    •  Overview.
    •  Review  and discussion of methods.
    •  Evaluation and validation of methods (includes
      discussion of data issues).
    •  Recommended process for how to use the biota-
      to-sediment accumulation factor (B SAP) method
      with risk assessment procedures for specific use
      in a regulatory setting.
  .   The document was reviewed extensively, includ-
ing Region 5 states, the State of Washington, USEPA
                                            5-9

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5-10
                                                              National Sediment Bioaccumulation Conference
Headquarters, and NOAA.  Overall, the reviews were
supportive and recommended refining the document fur-
ther and adding more information.  The document has
been revised based on this review, and changes include a
new appendix on BSAFs found in the literature,(values
were checked in the primary reference) and additional
case studies. Currently, one of the case studies is being
revised to incorporate additional  data made available
recently.  When this revision is made, the document will
go through academic peer review.
     It is clear that the best way to accurately assess
bioaccumulation is to use more complex models utilizing
pharmacokinetic parameters. However, for purely prac-
tical reasons, they were hot considered to be useful at
present in a regulatory setting where the data needs of
these models would not be met  and  time would also be
insufficient.  Three  methods, then, were analyzed in
detail—BCF, BAF, and BS AF. It is useful to note that in
general the BCF and BAF methods relate fish tissue
levels to  the water column, whereas the BSAF method
relates fish contamination to sediment (often the medium
where levels need to be set and where  contamination
more likely lies).
     Methods were tested  by comparing predicted fish
levels (using the various methods) with actual fish data.
This was done at four locations—Saginaw, Michigan;
Buffalo,  New York; Ontario, Canada; and Manistique,
Michigan. Data needs were.considerable for this process;
data were needed to input into all methods (water column,
sediment, etc.) and a separate data set was  needed to
determine site-specific BSAFs.  Conclusions from this
process were as follows:
    • When considering all case studies as a whole,
      BSAF consistently  gave the most reliable esti-
      mates  of fish tissue concentrations relative to
      other methods.  However, for specific case stud-
      ies, some of the other methods were slightly more
      or about as accurate (e.g., BAF—using a mea-
      sured BAF and dissolved values in the Buffalo
      case; and BCF—using a measured BCF and total
      concentration values in the Saginaw case).
    • In all of the studies, the modified BAF was the
      least accurate method.
    • How data were used was found to have a signifi-
      cant impact.  Accuracy in predicting fish levels
      depended on whether all data  were available, how
      one decided to handle heterogeneously distrib-
      uted data, and which bioaccumulation  factors
      were used and how they were developed. From
       this limited review, it appears that site-specific or
       field-derived bioaccumulation factors improve
       the accuracy of the  results.
    •  In general, BCF tended to  underestimate fish
       levels and BAF tended to overestimate fish levels.
      Another important conclusion from this method
validation chapter was how to appropriately use data.
Major recommendations are shown in Table 1. Specific
results of the data validation using Great Lakes data are
shown in Tables 2 through 4.
     The document also discusses  how to incorporate
human health  issues,  applying the BSAF method, in
conjunction with risk assessment. In this way, one can
develop options in a regulatory setting such as setting
sediment cleanup goals. The general process for setting
cleanup goals is shown in Figure 1. Essentially, using the
basic exposure  and risk equations from the Risk
Assessment Guidance for  Superfund (RAGS), a target
level in fish is set  It is important to note that the process
shown assumes that the contaminant of concern (PCBs,
or other hydrophobic organic compound) is appropriate,
and no other compound that would not be assessed in this
way is important in making a cleanup decision. It also
assumes that the only pathway of concern is ingestion of
contaminated fish.  (No other pathway is discussed here,
such as ingestion of sediment or surface water.) Note, in
addition, that setting the target level in fish using risk
assessment  requires decisions be  made regarding
acceptable levels of risk (e.g., 10"6). The target fish level
can also  be a regulatory level such as a threshold for
setting a fish advisory (e.g., 0.05 ppm).
      The target fish level is put into the BSAF equation
and solved for concentration in sediment. Important
issues to consider when doing this analysis are: (1) choos-
ing a BSAF, which can be site, specific or can be chosen
from the literature (variations will arise and can have
great impact on results); (2) quality  of total organic
carbon (TOC)  data, which can  have a great impact on
results as well; (3) using appropriate species of fish and
keeping  species-specific considerations throughout
(lipid values, range, etc.); and (4) applying  the risk
assessment process carefully and considering many
options, such as different exposure scenarios for different
fishing behaviors.
      This process has been applied in several cases in
Region 5. Two that will be discussed are Saginaw and
Manistique.   Results  shown were used in decision-
making in Saginaw, as  part  of a Natural Resource
Damage Assessment (NRDA). USEPA looked at current
health risks, developed cleanup goals, and assessed how
a possible action could address human health risk. The
lower Saginaw River is characterized as having wide-
spread lower level (less than 5 ppm on average) sediment
contamination at the surface  and somewhat  more
contamination  at depth in sediment. Site-specific BSAFs
were calculated for two species, walleye and carp.
Although a range of BSAFs  could be calculated
depending on data considerations  (averaging of
sediment data, etc.), they can be summarized as being 0.3
for walleye and 0.6  for carp. This  information  is
contrasted to Manistique, which is characterized as
having localized  sediment  "hot  spots" of PCB
contamination, the majority of which is not  at the
surface. Site-specific BSAFs were also calculated al-
though sediment and  fish data were somewhat more
limited.  Again a range  of site-specific BSAFs were
considered due to possible data handling  choices, but
they  can be summarized as 0.4 for carp and .07 for
walleye. Sediment cleanup goals for these two sites
obviously follow from the BSAF differences. Saginaw
cleanup  goals are much lower than  those calculated
from Manistique, Michigan. A summary is provided in
Figure 2.

-------
Proceedings
5-J]
Table 1.  Data Issues and Recommendations for Sediment to Fish Predictive Methods
Data Issue
Averaging offish or sediment data (geometric vs.
arithmetic mean)
Use of sediment organic carbon data
Handling of non-detect data
Uneven clustering of sediment samples
Calculating site specific BSAF value using sediment
and fish data
Type of fish sample
Bioaccumulation method
Recommendation
Geometric Mean
Point normalize
Use one-half the detection limit
Surface area weighting
Temporarily matched sediment and fish data
Filet (human health endpoint)
Whole fish (ecological endpoint)
BSAF
Table 2.  Comparison of Predicted Fish Tissue Concentrations (from draft S2F document)
All values shown are ppm PCBs
BCF (meas./total)
BAF (meas./diss.) .
BAF (meas./total)
BSAF
Actual
Saginaw (walleye)
1.4
38
38
1:4
1.5
Buffalo (carp)
0.35
0.42
3.5
-0.871
2.8
(Using geometric means of relevant data)

-------
5-12
                                                                      National Sediment Bioaccumulation Conference
Table 3. (from draft S2F document)
Manistique, MI
WATER-TO-
FISH
OR
SEDIMENT-
TO-FISH
PREDICTIVE
MODEL
BAF-modified
TBP (pf=4)
BSAF
(value in
parentheses is
site-specific
BSAF used)
Actual Fish
Tissue
Concentration
PREDICTED FISH CONCENTRATIONS IN CARP (in rag/kg)
SAW
SEDIMENT;
ARITHMETIC
MEANS



390 - 550
88
9.0
(0.41)



6.5


SAW
SEDIMENT;
GEOMETRIC
MEANS



380-550
86
8.6
(0.40)



6.2


ARITHMETIC
POINT-
NORMALIZED
SEDIMENT;
ARITHMETIC
MEANS

520 - 740
120
13
(0.45)


-
6.5

"•
ARITHMETIC
MEANS FOR
ALL
PARAMETERS



230 - 330
52
4.6
(0.35)



6.5


GEOMETRIC
MEANS FOR
ALL
PARAMETERS



79-110
18
2.9
(0.64)



6.2


'SAW = surface area weighted
'Values in this column are the same regardless if sediment data are normalized before or after calculating geometric means.
Table 4. (from draft S2F document)
Manistique, MI
WATER-TO-
FISH
OR
SEDIMENT-
TO-FISH
PREDICTIVE
MODEL
BAF-modified
TBP(pf=4)
BSAF
(value in
parentheses is
site-specific
BSAF used)
Actual Fish
Tissue
Concentration
PREDICTED FISH CONCENTRATIONS IN WALLEYE (in mg/kg)
SAW
SEDIMENT;
ARITHMETIC
MEANS



200-340
24
0.99
(0.16)



0.34


SAW
SEDIMENT;
GEOMETRIC
MEANS



180-310
, 22
0.87
(0.16)



0.25


ARITHMETIC
POINT-
NORMALIZED
SEDIMENT;
ARITHMETIC
MEANS

270 - 460
33
1.5
(0.18)



0.34


ARITHMETIC
MEANS FOR
ALL
PARAMETERS



120 - 204
15
0.51
<0.14)



0.34


GEOMETRIC
MEANS FOR
ALL
PARAMETERS



37-64 •
4.6
0.29
• (0.25)



0.25


 'SAW = surface area weighted
 'Values in this column are the same regardless if sediment data are normalized before or after calculating geometric means.

-------
Proceedings
                                                                                           5-13
                            1) Set acceptable contaminant level in fish
                        •i     set risk target level (i.e. lO"6 cancer, HI=1)
                            determine appropriate exposure parameters
                                    for fish ingestion pathway
                        2) Calculate total organic carbon (TOO in the area
                                   determine fish exposure area
                                  use most recent sediment data
                                       use surface samples
                              3) Determine fish which are consumed
                                            Consider:
                                  local fish consumption patterns
                                   at least two species to target           '
                                    species-specific lipid levels
                                    4)  Calculate/Select BSAF
                              use site-specific data to.calculate BSAF
                                             and/or
                             choose literature value from Appendix £
                                     (match species and site)
                                5) Calculate sediment cleanup goal
                                      Cs = Cf (I) x TOC (2)
                                         BSAF (4) x Lipid (3)
 Figure 1.  Recommended Methodology for Determining Sediment Cleanup Goals.


Cancer Risk
Level

10E-6

10E-5

10E-4
Exposure
Assumptions

sport fisher
eating average of
20 g walleye/day,
25% from site

sport fisher
eating average of
15 g walleye/day,
25% from site

subsistence fisher
eating average of
75 g walleye/day,
50% from site
Site

Saginaw
Manistique

Saginaw
Manistique

Saginaw
Manistique
CUGs for
PCBs (ppm)

0.06
1

0.8
13

0.8
13

[
•
 Figure 2.  Comparison of Saginaw and Manistique Cleanup Goals (CUGs).

-------
5-14
National Sediment Bioaccumulation Conference

















Bioaccumulation Models and Applications: ijy
Setting Sediment Clean Up Goals in the Great Lakes

Overview
• need and precedent for use of bioaccumulation methods
in regulatory setting (linking sediment levels with
health endpoint)
• Region 5 evaluation of bioaccumulation methodologies
• Region 5 recommended process in use of methodology and
in linking with risk assessment
• Case Studies/lessons learned
National Bioaccumulation Conf.
A.E.. PeOca
9/12/96


Bioaccumulation Models and Applications H^


4 Need and precedent for bioaccumulation methods 1
for regulatory purposes 1
• assessing bioaccumulation potential
• setting cleanup goals
• evaluating remedial options
• estimating risks when limited data are available
9/IW6

















-------
Proceedings
                                                                    5-tS
   Bioaccumulation Models and Applications
           Alternative Clean Up Goals/Remedial Targets for \
             Contaminated Sediments
             . TSCA (50 ppm for PCBs)

              Ontario Sediment Quality guidelines

              NOAA Sediment Thresholds
                                  \
              background

            If gap in having actions protective of human health
                                                             9/12/96
     Bioaccumulation Models and Applications
           Region 5 Workgroup - Sediments to Fish (S2F)
       •  multi-media and-division

       •  focused on hydrophobic organic compounds
             - e.g., PCBs, PCB-like compounds, dioxins

       •  Guidance document
          -reviewed literature and several methodologies
          -tested methods using Great Lakes data
          -recommended process using BSAF

       •  draft completed in 1994, reviewed by States and
          Federal agencies; significant revisions;
          interim final by end 1996; academic peer review.
                                                               9/1V96

-------
                                        National Sediment Bioaccumulation Conference
 Bioaccumulation Models and Applications
                S2F Workgroup:

                John Dorkin
                Al Fenedick
                Diane Ragler
                Lee Gorsky*
                Linda Hoist*
                Gary Kohlhepp*
                Amy Pelka*
                Marc Tuchman
                Dolly Tong
                (Lara Pullen)

                * authors of the guidance document
                                                           9I1W6
Bioaccumulation Models and Applications
      Key Questions/Issues that Emerged from S2F J
 O Which methodology is most accurate in predicting fish
    tissue concentrations?

 O Appropriately handling data

 O Science Policy Issues
                                                            9/12/96

-------
Proceedings
    Bioaccumulation Models and Applications
                                                                       5-17
            Methodologies Available to Assess Bioaccumulation of
              Contaminated Sediments
               BAF

               BCF

               BSAF
relates fish tissue concentration to water column
relates fish tissue concentration to sediment
               biokinetic models -requires pharmacokinetic parameters
                                                                 9/12/96
     Bioaccumulation Models and Applications
            Testing methodologies I
     The ability of the various models to accurately predict fish tissue
     concentrations were tested using actual fish tissue, water column,
     and sediment data from the following sites:

                   • Saginaw

                   •Buffalo

                   • Ontario

                   • Manistique        .
                                                                  9/12196

-------
5-18
                                                     National Sediment Bioaccumulation Conference

                 Testing Methodologies    |
          Data needs were considerable
          -need data to input into all methodologies (BAF, BCF, BSAF)
           and solve for cone, in fish
          -compare estimated level in fish to actual fish data

ter column \
+ •/

BAFs
BCF
BSAF
•^ conc.infish
/
          bioacc. factors
                    ra separate data set was needed to develop site-specific
                    bioaccumulation factors
                                                                             9/1V96
Bioaccumulation Models and Applications

PS*
L «•**•> /
fc.,,«aa
t^Equations used for Evaluating Bioaccumulation Methods:
BCF = Cf
cw
BAF = Cf Modified BAF => Cf =
cw
c^ ' •
(BCF*FC)*C0
f * K
•''OC "^OC
' where: Cf = concentration in fish; Cw=concentration in the water column;
Cs concentration in the sediment; FC=food chain multiplier;
f^ =fraction organic carbon;
Koc= partitioning coefficient (between water and organic carbon)

-------
5-19
Bioaccumulation Models and Applications
K^^
m

i^ Comparison of Predicted Fish Tissue Concentrations
from draft S2F document
. • all values shown are ppm
PCBs
>•
BCF dneas./total)
BAF (meas./diss.)
BAFdneas./total)
BSAF
Actual
Saginaw
(walleye)
1.4
38
38
1.4
1.5
Buffalo
(carp) .
.35
.42
3.5
.87-1.7
2,8.
(Using geometric means of relevant data)
9/12/96
Bioaccumulation Models and Applications

•
^Predicted PCB carp tissue concentrations
for the Manistique River
(from draft S2F document)
•
WATER-TO-FISH
CHI SEDIMENT-TO-FISH
PREDICTIVE MODEL


BSAF
(value in paientheses is site-
specific BSAF used)
Actual Fish Tissue
PREMCTED FISH CONCENTRATIONS (in vug/kg
SAW1 SEDIMEOT:
ARITHMBmC
MEANS
390-550
88
9.0
(0.41)
6.5
SAW SEDIMENT:
GEOMETRIC
MEANS
380-550
86
.8.6
(0.40)
6.2
ARITHMETIC PCHNT-
NOKMAUZED
SEDIMENT:
ARITHMETIC MEANS
520-740
120
13
(0.45)
6.5
ARITHMETIC
MEANS FOR ALL
PARAMETERS
230-330
52
4.6
(0.35)
6.5
GEOMETRIC2
MEANS FOR ALL
PARAMETERS
79-110
18
2.9
(O.M)
6.2
*^A**
m

1 SAW = surface area weigned
2 Values in thiscotam are die sanEreganHess if sediment data are nonnalized before or after calculating geometric means. a/ring

-------
5-20
                                                            National Sediment Bloaccumulation Conference
Bioaccumulation Models and Applications

!51
C^ Predicted PCS walleve tissue concentrations
for the Manistique River
(from draft S2F document)
3
WATER-TO-FISH
OR SEDJMENT-TO-FISH
PREDICTIVE MODEL
BAF.modifKd
TBP(pf-4)
BSAF
(vtlue in Duaxbaes is she-
spccific BSAF used)
Acaul Fish Tissue
Conccncruion
PREDICTED FISH CONCENTRATIONS (in mg/kg)
SAW1 SEDIMENT:
ARITHMETIC
MEANS
200-340
24
0.99
'(0.16)
0.34
SAW SEDIMENT:
GEOMETRIC
MEANS
180-310
22
0.87
(0.16)
0.25
ARITHMETIC POINT-
NORMALIZED
SEDIMENT:
ARITHMETIC MEANS
270-460
33
1.5
(Oil 8)
0.34 '
ARITHMETIC
'MEANS FOR ALL
PARAMETERS
120-204 '

0.51
(0 14)

SAW - ui&ce uea weighted
V«lu« in tlis coiunm ire the sune regardless if sediment data are nonnalized before or after calculadnu geometric means.
GEOMEtRIC1
MEANS FOR ALL
PARAMETERS


0.29
(0 25)

-
9/1W6
Bioaccumulation Models and Applications


Cj^ Data Issues & Recommendations |
.
Data Issue
Averaging data
(geometric vs. arithmetic mean)
Use of sediment
organic carbon data
Non-detect data
Uneven clustering of sediment
samples
Calculating site specific BSAF
Type of fish sample
Bioaccumulation method
Recommendation
Geometric Mean
Point normalize
Use one-half the detection limit
Surface area weighting
Temporally matched sediment and fish data
Fillet (human health endpoint)
Whole fish (ecological endpoint)
BSAF

tH

9/12/96

-------
Proceedings
                                                                        5-21
     Bioaccumulation
          iioaccumulation Method Evaluation Conclusions:
       •when evaluating all the case studies as a whole, BSAF consistently
       gave reliable estimates; although other methods in some cases were
       slightly more or as accurate as BSAF

       •estimates using measured values for bioaccumulation factors
       were more accurate than those using calculated factors

       •accuracy in predicting fish levels strongly depended on data quality,
       availability, and handling of data (e.g., heterogeneously distributed
       data)                                               -

       •in most cases: BAF-modified was least accurate, BCF tended to
       underestimate, and BAF tended to overestimate
                                                                   9/12/96
     Bioaccumulation Models and Applications
               Recommended Methodology for Determining
                        Sediment Cleanup Goals
                    1) Set acceptable contaminant level in fish  ,

                2) Calculate total organic carbon (TOC) in the area

                     3) Determine fish which are consumed

                          4) Calculate/Select BSAF

                       5) Calculate sediment cleanup goal
                              = Cf(DxTOC(2)
                              BSAF (4) x Lipid (3)
                                                                    9/12/96

-------
5-22
                                            National Sediment Bioaccumulation Conference
     Bioaccumulation Models and Applications
         Evaluating Remedial Options I
         • Consider several options, for example:

             -dredge sediments greater than 50 ppm, 10 ppm

             -leave sediment in place

             -other options


         4 Calculate surface area weighted sediment concentration
          for each scenario under evaluation
                                  [Cs]

         • Determine BSAF for representative fish specks
         (literature, site specific)
                                 [BSAFJ
    Bioaccumulation Models and Applications
         Evaluating Remedial Options, cont'dl
          •   Use BSAF to model contaminant
          concentration in fish under each scenario
                    Cf = (BSAF) x (C«) x T
                         (Organic Carbon)
          4   Use exposure equation to calculate human
          intake of contaminant
          4  Use toxicological risk information (IRIS) to
          calculate, human health risk under each scenario
                                                                9/12196

-------
Proceedings
                                                                               5-23
Bioaccumulation Models and Applications
••.%

Determining an Appropriate BSAF Value I
Species Specific Issues , I

Issue
Foraging Range '•"'•
Pisciverous vs.
Bottom Feeding
Lipid Content
Presence of Species •
at Site
Consumption of
Species :-
Consideration
Consult with fish biologist to help confirm that
the average contaminant concentration in the
sediment is representative of the fish's range.
Bottom feeding fish will likely have a Higher
BSAF and thus should be included to represent
• a more conservative scenario.
Fatty fish tend to accumulate more contaminants
and thus inclusion will add a more conservative
scenario. .
Choose a species endpbint that is actually found
at the site. ..••''•.
Choose a species which is being consumed by
the local population.'


- i>*rs
: . k2tf

      Bioaccumulation Models and Applications
           Critical Science Policy Decisions
              •   Choice of bioaccumulation model
                  Choice of fish species (e. g. pelagic, bottom-feeding)
                  Choice of BSAF value
                  Determining appropriate sediment concentration term
              •   Defining fish exposure area/site boundary
                                                                         9/12&6

-------
5-24
                                                 National Sediment Bioaccumulation Conference
     Bioaccumulation Models and Applications
          Critical Science  Policy Decisions, cont'd
                   4  Handling of "non-detect" data
                  4   Choice of fish consumption rate
                  4   Determination of endpoints of concern
                  4   Accurately estimating TOC

**$*
feT^a
USEPA Region 5



Current Potential Health Risks
(MDEQ 1986-1993)
Species
jvra
lleye^ ,
carp
\bass
[whitegsh
£erch_
pjjce
\ trout
Concentrati on | Cancer Risk Range
0.43
3.1
0.21
0.04
0.13!
0.15J
0.08
3.04E-05
2.19E-04
(2.64E-03
1.90E-02
1.46E-05 1.27E-03
2.94E-06J 2.55E-04
9.16E-06
i.07E-65
5.64E-06
7.94E-04
9.25E-04
4.89E-04
HQ Ranee
0.20
1.42
0.10
0.02
0.06
0.07
0.04
17.11!
123.371
8.241
1.65!
5.161
6.01!
o i o 1
j 1 O '



-------
                                              5-25
USEPA Region 5
        22-Mile Surface- Present
            Average


           90% UCL    /
                      "i

           95% UCL  /
   cV iX"^-^
   /~ >v   H:'...,.: .^ . .
        V, . '"'""I.- ,
        Is    -^,  , ,
      .^;^       "S,. •
   pt.jflorm PCB(mg/kg)


          78.2


          96.6


         104.7
USEPA Region 5
      22-Mile Surface - Post Dredge
pt. norm P
                                 TOC(%)
          Average       55.8p


         90% UCL       7i6
                        *&
                     ,  •£

         95% UCL  ,-^  /82.2
                  2.3


                  4.1


                  4.6

-------
                             National Sediment Bioaccumulation Conference
 USEPA Region 5
  Calculating Risk-Based Cleanup Goals
- Set Target Fish Tissue Level
	 	
,E!o4jrweight
Afcep^leRiskjLevel j 1.00E-06r l.OOE-06]
cancer slope factor 1 7.7! 7.7!
(kg)
Averaging time (days)
Ingestion rate (kg/day)
Fraction ingest ion (%)
Absorption (%)



	 ••-
Exp. frequency (days/year)
Exposure duration (years)
Concentration in Fish
I

70J 70?
25550
255501
0.02f OJ3|
. 0.25
365
9
~0.6l41~
._-| _
365J
30J
0.00021
1 1 !
Haz. Index • -l! 1
^Ref. Dose 	 lOO&OSl 	 ioO&OS
70i 70
	 . 	 ^Jo^Sl "70950
6.02! OJ3
	 	 0.25! 	 _ 	 _J_
365! 365
30! 30
I ' b"28i b.oio&
	 1 	 ,,__, 	
 USEPA Region 5
 Calculating Risk-Based Cleanup Goals
 Input Target Fish Levels into BSAF=>CUGs
Sediment Qeanup(»oa] ->
^nccr(&6
fetl-i
carp


'
CF itoc
ab'iii'i'iV
	 , f
CF itoc
00301632
„ 	 | .
iBSAF
..?:.?1...9^J9693
1
iBSAF
2.3: 0^319693
Csi5tocxCF)/(BSAJFxlirid) '

lipid


lipid

d I i INoncanc

i.ys
122


I.Vdl
122
CS
0.0583901
0.0050116

CS
5.783&05
walleye
carp
AWCT
babsK," .
( walleye
•carp
er (HI=n j
028
028,
•f. I
I CF toe
f 00107692,
00107692:
" BSAF
i
i lipid
23_ 02813299^
23* 05319693*
i
BSAF ilioid
23 02813299
2.3* 05319693

196
198

198
I 9R
....
CS
1.1679221

CS

-------
Proceedings
                                                                                                   5-27

Rgh USEPA Region 5


Post-Remediation Health Risks
- Input Sediment Levels into BSAF=>Resulting Levels in Fish
range walleye CS I toe Ilipid 1BSAF
, 0.9! .2.3! 1.961 0.28
1.3! 2.3! 1.96! 0.28
55.81 l! 6.0196! 0.28
812! l! 0.0196! 0.28
CF
0.2157678
0.1558323
0.3076849
0.4532563
'. . I ' ' ! 1 ''I ' •
1 • !. 1 ' -M
range carp CS Itoc ' Ilipid IBSAF
0.9! 2.3! 12.2! 0.53
1.3| - . 2.3J_ , 12.2! _ 	 0.53
; '" 	 ™ ."*"" """~55.8[ " 1! o!l22|~~ . 6.53
82.2! 1! •;'•' 0.122! a53

CF
2.5395752
1.8341377
3.6214343
5.334801




(normal)
(normal.)

	

(normal)
(normal)







*|p USEPA Region 5 , ' • '.

Post-Remediation Health Risks
Define Exposure Scenarios and Calculate Risk
walleye §£Sf6!Sti<% low high
CF _ 0307685 0453256^
!BW • 1 70! . 70|
AT 25550^ 25550
IR 002' 013,
JFI * 025__ l'
"AB " V i
" 	 EF~" f 365"" 3~65,,
ED * 9, 30,
slope 7?' 77
RISK 218E-05 278E:03_
••''.' carp ftas^^"'low high
CF 3 621434_ 5334801
BW 70~ 70
,AT " 25550 25550*
. llR ' 1 0.021 0.13i
FI _ 025 1
^AB 1_ _ 1
IED ? 9! " "so?
Aslope 7 7_ 77
IRISK ! 0.000256! 0.032695i
l^^tl
	 JCF ___ j
IBW 1
,AT
IR
JEF "" T
JED 1
?RfD .!
_„. HQ _ _,
- .C* ',
BW !
AT
im !
FI , ;
AB
?EF ]
"IED" "" "T
,RfD
!HQ 1
ow 'high !
0.307685J 0.45325_6i
?6l " io
25550, 25550
002! 013
___0.25! 	 1
~ ~~365p ' 365|
9! 30|
2.00E-051 2.00E-05
0 M128_£_18 03775
X
f •;
3 621434^ 5 334801
70° 70
25550 25550
0.02! 0.13
025 L
1_ 1
365J _ 365J
"9]"" 30!
000002^ 000002
1.662903 1 212.3033


-------
5-28
                                                        National Sediment BJoaccumulation Conference
     JWpacoim^^
     ^ Exposure Assumptions used at Manistique
         Variable
Value
         -mgestion rate
          (kg/day)

         -fraction ingested
          from area
-exposure frequency
   (days/year)

-exposure duration
   (years)

-body weight
   (kg)

-averaging time
   (days)
.015 - .054
.075 - .130

25%
50%
100%

365
9
30

70
                                  3285
                                  10950
                                  25550
-recreation "average" - "high end"
-subsistence "average" - "high end"

-recreation "average"
-recr. "high end" & subsis. "avg."
-subsistence "high end"

(IR's are daily rates)
                                                   "average" scenarios
                                                   "high end" scenarios
                 "average" noncancer
                 "high-end" noncancer
                 cancer
Bioaccumulation Models and Applications
*
^Manistique Sediment Cleanup Levels Summary (PCBs)
Cancer
Recreational
fishing
Subsistence
fishing
"Average" Scenario
risk target sediment
level (ppm)
10'6 1.3
Iff4 130
10"° 0.13
10"4 13
"High End" Scenario
risk target sediment
level (mm)
10'6 0.0096
lO'4 0.96
10'6 0.002
W4 0.2

Noncancer
(Tmmuno-
toxicitv and
Reproductive
Effects)
Haz, Index - 1
Recreational
fishing
Subsistence
fishing
"Average" Scenario
target sediment level
(ppm)
25
2.5
"High End" Scenario
target sediment level
(ppm)
0.63
0.13


H
9/1206

-------
Proceedings
                                                            5-29
'• ITS'
fe8>'
] USEPA Region 5 ''.'', ...•'' ' ' :
Comparison of Saginaw and Manistique
Cleanup Goals (CUGs)
Cancer Risk
Level

10E-6

10E-5
Exposure
Assumptions

sport fisher
eating average of
20 g walleye/day,
25% from site .

sport fisher
eating average of
15 g walleye/day,
25% from site
Site

Saginaw
Manistique

Saginaw
Manistique
CUGs for
PCBs (ppm) I

0.06
1

0.8
13

10E-4
subsistence fisher
eating average of
75 g walleye/day,
50% from site
Saginaw
Manistique
0.8
13
X
I

       USEPA Region 5
         Biota To Sediment Accumulation Factors
            (BSAFs) in Saq'maw and Manistique
                       Carp   Saginaw   41.6/78.2
                             Manistique 102.2/245
                       Walleye Saginaw  v 22/78.2
                        	Manistique 16.7/245
            Carp
         Walleye
                                                I Saginaw
                                                i Manistique
                          0.2      0.4
                             BSAF
0.6

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5-30
                                                      National Sediment Bioaccumulation Conference
                   Conclusions:
         -bioaccumulation models applied in a regulatory setting, with careful
         consideration, appear to provide reasonably accurate results and
         allow actions to consider human health
         [note: models evaluated for hydrophobic organic compounds only]

         -data quality and quantity clearly are critical to usability and accuracy

         -important considerations include:
                 -accurately estimating: TOC, fish species differences (% lipid,
                 range, etc.), concentrations of contaminant at the surface that fish
                 are/were exposed to, and bioaccumulation factors;
                 -fish ingestion rates,
                 -setting acceptable risk levels (cancer vs noncancer)
                 -critically and clearly communicating limitations, assumptions,
                 and uncertainties.
                                                                               9/12/96

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                                                       National Sediment BioaccumuJation Conference
Use of Human  Health- and  Ecological-
Based  Goals in  Developing  a  Whole
River  Sediment  Strategy:  Fox  River,
Wisconsin
Robert L. Paulson
Wisconsin Department of Natural Resources, Madison, Wisconsin
^•ffhe Wisconsin Department of Natural Resources
 I  (WDNR) has been working with the Fox River
 M.  Coalition (FRC), a planning and implementation
group composed of local, state, and federal partners, to
develop a whole river sediment strategy.  It was evident
early in the process that numeric criteria alone would not ,
suffice in developing a cost-effective whole river sedi-
ment strategy. Numeric criteria alone cannot address .
issues regarding loc'al benefits of remediation in numer-
ous riverreach'es or evaluate benefits of reducing PCB
transport to Green Bay in lieu of local fish tissue reduc-
tions. Other techniques that could factor in the size of the
existing problem and unique features of the Fox River
Basin were needed,                    t
     This presentation reviews one alternative approach.
The  approach relies  on the tools and data generated
during the Green Bay Mass Balance Study (GBMBS) to
help  identify and prioritize remediation areas and at-
tempts to quantify the benefits of remediation in terms of
reduced PCB transport to Green Bay and reductions in
fish tissue concentrations. To date, efforts have focused
on developing a basic set of remediation scenarios that
illustrate the environmental benefit and implementation
considerations of varying levels of sediment remediation.
The next step will be to develop preliminary  costs for
these scenarios.  With "ballpark" costs linked  to the
associated environmental benefits and implementation
issues, these  scenarios will help the FRC and WDNR
develop a whole river sediment strategy: The strategy
will  strive for cost-effective progress toward achieving
established water quality goals and  elimination of fish
consumption advisories.
     The Fox River and Green Bay were studied as part
of the 1989 Green Bay Mass Balance Study (GBMBS)
(Beltran, 1992). The study focused on the transport and
fate of PCBs from the outlet of Lake Winnebago through
the entire Lower Fox River and into  Green Bay, as well
as the accumulation of PCBs in the aquatic food web of
Green Bay and the Fox River downstream of DePere.
One significant conclusion of the GBMBS is that the
source of essentially all (>99 percent) of the PCBs trans-
ported by the river originates from the river sediments.
Further, a 1989 inventory of sediment PCBs estimates the
Fox River sediments contain 4,000 kg (8,800 Ibs) and
26,000 kg (57,200 Ibs) of PCBs upstream (32 miles) and
downstream of the DePere dam (7 miles), respectively. ,
    Sediment remedial action scenarios for the Fox
River were simulated by using the WASPS model (Water '
Quality Analysis Program) for the Fox River upstream of
DePere  (WDNR, 1995) and the IPX (In-Place Pollutant
eXport) model for downstream of DePere (Velleux et al.,
1996). These water quality models developed during the
GBMBS were  useful tools  for evaluating how PCBs
moved through the Fox River/Green Bay System during
1989. As demonstrated through a post-auditing proce-
dure, the Fox River water quality models can predict PCB
concentrations  to within 20  percent to 30 percent of
observed PCB  concentrations.  The post-audit results
indicate that the Fox River models are excellent tools for
evaluating the impact and effectiveness of proposed sedi-
•ment remediation efforts.
     With the intent of making model simulations real-
istically represent implementation issues, two assump-
tions were made. The post-remediation residual PCB
concentration used for the simulations was set to 2.5 ppm
for the uppermost sediment layer.  Also, to simplify the
simulation of multiple remediation scenarios, all
remediation was assumed to occur at one point in time—
July 1, 2000. July 1, 2000, was chosen to represent the
midpoint of a 5-year period from early 1998 through th&
end of 2002.
     The Fox River PCB transport models were used to
predict PCB concentrations in fish for different reaches
of the river as well as PCB  mass transported over the
                                            5-31

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  5-32
                                                              National Sediment Bioaccumulation Conference
  DePere dam and to Green Bay from January 1,1996, to
  December 31,2020. Both models predict surface sediment
  PCB concentrations and PCB mass transport over time.
  Predicted surface sediment PCB concentrations were
  used to calculate PCB concentrations in fish tissue using
  a  simple model, biota-sediment accumulation factor
  (BSAF)(DiToroetal., 1991). The BSAF is a measure of
  site-specific bioaccumulation potential of fish from ex-
  posure to contaminated sediments. The model is rela-
  tively simple, and describes bioaccumulation based on
  the lipid (fat) content in fish and the amount of contami-
  nation and organic carbon content of the sediment. A site-
  specific BSAF can be calculated as:
         BSAF= (C/f,)/(C/fJ
               (1)
 where Cf is the pollutant concentration in fish, f, is the
 fraction of lipid content in fish, Cs is the pollutant concen-
 tration in sediment, and f^. is fraction of organic carbon in
 sediment. For ease of evaluating the remedial scenarios,
 the BSAF was applied instantaneously to simulated sur-
 face sediment PCB concentrations to simulate fish tissue
 concentrations over the 25-year model simulation. The
 fraction of lipid in fish and the fraction of organic carbon
 in sediment were assumed  to remain  equal to
 preremediation conditions.


 Site Selections

      A nonparametric statistical model, based on fuzzy
 set theory, was  employed to prioritize  contaminated
 Table 1. Variables used for fuzzy set ranking of contaminated sediment sites
  PCB mass
  PCB mass/area
  PCB mass/volume
  Mercury concern
  River position
Bioavailability Index (OC-normalized PCB in top layer)
PCB mass remaining—25-yr "no action" scenario
PCB mass delivery during Mass Balance Study year
PCB mass delivery under a modeled 100-yr storm event
PCB mass delivery—25-yr "no action" scenario
 individual model's configuration. Upstream of DePere,
 the sites were prioritized byriver segment. ThelPXmodel
 used downstream of DePere artificially divides the last 7
 miles of river into 96 Sediment Management Units (SMU).
 Site prioritization downstream of DePere was by SMU.
 Upstream of DePere, the five top-ranked river segments
 contain Deposits A, POG, C, D/E, N, and EE/GG/HH.
 Deposits A, C, D/E, and POG are all within the first river
 reach from the outlet of Lake Winnebago, which is locally
 known as Little Lake Butte des Morts (LLBdM).
     The site rankings were  used to assemble four sedi-
 ment remediation scenarios that attempt to accommodate
 remediation  upstream  of DePere while  balancing  the
 importance of reducing PCB bioaccumulation into fish
 tissue downstream of DePere with reductions of PCB
 transport to Green Bay. The four scenarios are:
    •  No Action [Figure 1 (1)].
    •  Deposits A, C, POG upstream of DePere and the 3
       top SMUs downstream of DePere [Figure 1 (2)].
    •  Deposits A, C, POG upstream of DePere and the 17
       top SMUs downstream of DePere [Figure 1 (3)].
    •  Deposits A, D/E, POG, N upstream of DePere and
       the 50 top SMUs  downstream of DePere
   --  [Figure 1 (4)].
Endpoints

     To provide a base level of communication that
should be easily recognized and understood by the major-
ity of the public, changes in risk associated with the three
scenarios were expressed in terms of allowable fish con-
                           sumption rates. The pro-
                           posed  Uniform Great
                           Lakes Sport Fish  Con-
                           sumption Advisory Pro-
                           tocol (GLSFATF, 1993)
                           was selected because it
                           recognized the  limita-
                           tions and inadequacy of
                           the FDA tolerances for
                           marketplace fish and set
sediment sites both upstream of DePere and in the 7 river
miles downstream of DePere. This fuzzy set analysis
provides a systematic technique for comparing a set of
alternatives and identifying more preferable ones based
on multiple decision criteria or factors (Table 1).
      In general, PCB mass delivery under a simulated
25-yr "no action" scenario
and  bioavailability  were  Table 2.  Proposed uniform Great Lakes sport fish consumption advisory levels.
the most important  vari-
ables while river position
and mercury were the vari-
ables of least importance.
                                                       forth a protocol based on
                           a weight-of-evidence health protection value.  The pro-
                           tocol provides a range of consumption advice expressed
                           in consumption terms, which provides adequate protec-
                           tion but also allows people to selectively eat sport fish as
                           often as they wish. The advisoiy categories for PCBs are
                           listed in Table  2.
     The prioritizing of
sediment sites was con-
ducted separately for up-
stream and  downstream
of DePere based on the
  Consumption Rate (227g/meal)
                     Tissue PCB concentration
  Unrestricted consumption (225 meals/year)
  One meal per week
  One meal per month
  Six meals per year
  Do Not Eat
                     <0.05 ppm
                     0.05 to 0.22 ppm
                     0.22 to 0.95 ppm
                     0.95 to 1.89 ppm
                     > 1.89 ppm

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Proceedings
                                                                                                 5-33
     To incorporate ecological concerns into the evalu-
ation of the three remediation scenarios, fish tissue con-
centrations that would be protective of fish-consuming
birds and mammals were also included. Using method-
ologies from the Great Lakes  Water Quality Initiative
(USEPA,  1995), an ecologically protective fish tissue
concentration of 0.023 ppm derived from mink data was
included in the evaluations of the scenarios.
Typical Model Simulation Results

     Figure 1 illustrates the type of results generated
by this modeling approach.  Results have been limited
to single fish species in only two distinct river.segments
(LLBdM  and downstream of DePere)  and PCB
transport to Green Bay. Similar results can be generated
for any parameter listed in Table 1  (except river
position) in any particular river reach.  Other fish
species or tissue types (i.e., whole fish) can be easily
substituted for the species analyzed provided there are
enough data to estimate the average PCB concentration
around 1990  for locations above DePere and around
1995 for below DePere.
Conclusions

     General conclusions of the modeling done to date
include:
    • The problem is large and environmental benefit
      of sediment remediation is directly proportional
      to the effort expended.
    • Remediation of select "hot spots" upstream of the
      DePere dam has little influence on transport to
      Green Bay.
    • Remediation upstream of .the DePere dam has little
      influence on fish tissue downstream of DePere.
    • Remediation  of large areas  with  low PCB
      concentrations achieves greater reductions in
      transport with similar reductions in fish tissues.
    • Remediation of areas downstream of DePere has
      greatest influence oh fish tissue concentrations
      downstream of DePere and PCB  transport to
      Green Bay.
       Remediation decreases the time necessary to
       achieve a specific fish tissue endpqint.
Next Steps

     With the goal of a cost-effective whole river sediment
strategy in mind and the environmental benefits of these
scenarios in hand, attention will shift toward developing
total costs of these scenarios. Critical to this step will be
developing unit costs for the remedial techniques most
likely to be used. These costs could be applied across the
board to each scenario, resulting in "ballpark" costs.
Alternatively, each scenario could be reviewed in detail
and specific techniques and costs applied to each sediment
area or group of areas. Most likely, an iterative combination
of these approaches will be attempted.  Ultimately, with
discussions focused on  the cost of  achieving specific
environmental benefits, a cost-effective whole river strategy
can be refined from this  basic set of scenarios.
References

Beltran, R.F.   1992.  The Green Bay/Fox River mass
     balance study - management summary. USEPA
     GLNPO, Chicago, IL.  24pp.
DiToro,D.M.,etal. 1991. Technical basis of establishing
     sediment quality criteria for nonionic organic chemi-
     cals using  equilibrium partitioning.   Environ.
     Toxicol. Chem.  10:1541-1583.
GLSFATF. 1993.  Protocol for a uniform Great Lakes
     sport fish consumption advisory. Great Lakes Sport
     Fish Advisory Task Force Protocol Drafting Com-
     mittee, September 1993. 81 pp.
USEPA.   1995. Final water quality guidance for the
     GreatLakes system. 40 CFRParts 9,122,123,131
     and 132.
Velleux, M.,  J.  Gailani, and D. Endicott.  1996.
     Screening-level approach for estimating contami-
     nant export from tributaries. J. Env. Engrg. Div.,
     ASCE 122(6), 503-514.
WDNR.  1995. A deterministic PCB transport model for
     the Lower Fox River between Lake Winnebago and
     DePere, Wisconsin. WDNR PUBL WR 389-95.

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5-34
                                                     National Sediment Bioaccumulation Conference
                               Cumulative PCB Transport to Green Bay
                      6000
                         1995     2000     2005     2010     2015     2020
                                                Year            -
                              PCB in LLBdM 20" Walleye Fillets
                        0.1
                    8
                       0.01
                      0.001
                          1995     2000     2005     2010     2015     2020
                                                 Year

                             Ave 20-25" Walleye Fillet Below DePere
                                  2000
2005    2010
      Year
2015'     2020
                       Figure 1. Typical remediation simulation results.
                                                                                             _

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                                                        National Sediment Bioaccumulation Conference
Development of Health-Based
Sediment  Criteria for  Puget Sound
Laura B. Weiss
Washington State Department of Ecology, Olympia, Washington
Problem Statement

      Discharge of many industrial, agricultural, and
      domestic chemicals into Puget Sound has
      resulted in sediments with elevated levels of pol-
lutants, especially in urban bays and estuaries. Many of
these pollutants accumulate in fish and shellfish. As a result,
there is  concern that. contaminated sediments pose  a
health threat to humans  through the consumption of sea-
food that has bioaccumulated chemicals directly or indi-
rectly from sediments.
     To address the problem of contaminated sediments,
the Washington State Department of Ecology (Ecology)
adopted  the Sediment Management Standards (SMS)
(Chapter 173-204 WAG) in 1991. The purpose of these
standards is to "reduce and ultimately eliminate adverse
effects on biological resources and significant human
health threats."


Sediment Management Standards
(SMS)  Background

     The SMS currehtly establish 47 chemical-specific
sediment quality standards (SQS), which are designed to
protect benthic organisms.   No human health-based
criteria were available for inclusion at the time of SMS
adoption. As a result,  standards for the protection of
human health from contaminated sediments  are being
developed on a case-by-case basis. To increase consis-
tency and allow for more timely decision-making, Ecol-
ogy is developing human health-based sediment quality
criteria (HHSQC) that will be incorporated into the cur-
rent SMS.
     Once adopted into the SMS, human health criteria
will be used in conjunction with existing ecological
criteria to make cleanup, source control, and dredging
decisions.  The rule presently includes two levels of
criteria: (1) the Sediment Quality Standards (SQS), which
set a goal of "no  adverse impacts," and (2) a higher
Regulatory Limit (RL), which allows for "minor adverse
impacts." Regulatory decisions are made on a site-
specific basis in the range between these two levels. The
HHSQC will also include two criteria levels, based on
different levels of risk.
Implementation Framework

     Ecology's proposed construct for human health
criteria relies on a tiered approach. "Tier I" is intended to
allow for an initial evaluation to determine if sediment
chemical concentrations pose a significant human health
risk. If so, additional site-specific analysis would be
available under "Tier II" to verify the results of the tier I
analysis and to take into account any uncertainties asso-
ciated with Tier I values. In addition, Ecology is propos-
ing the use of tissue data as a confirmatory step under
Tier H to validate assumptions regarding bioaccumula-
tipn potential.
Criteria Calculation/Methodology

     The primary human route of exposure to contami-
nated sediments is via the consumption of contaminated
fish and/or shellfish. Human health criteria are devel-
oped by applying U. S. EPA's risk assessment methodol-
ogy to calculate risk from consumption of potentially
contaminated fish/shellfish. To quantitatively establish
the link between  sediment and biota, a biota-sediment
accumulation factor (BSAF) is used.
     The following formula and input parameters are being
proposed to develop HHSQC for carcinogenic compounds:
where:
     HHSQC   =      R*BW* AT* 1000
                  CPF * ED * ER * BSAF * FL
     R = risk level of 10-6for SQS (a lO'5 risk level is
     proposed for the RL)
     B W = adult body weight of 70 kg
     AT = averaging time of 75 years
     CPF = chemical-specific cancer,potency factor as
     defined by EPA (IRIS)
     ED = exposure duration of 30 years
     IR = fish ingestion rate of 52 grams/day (based on
     results of consumption studies of Native American
     populations in the Puget Sound region (Toy, 1995))
     BSAF =  chemical-specific biota-sediment
     accumulation factor
     FL = fish lipid of 3%
                                            5-35

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5-36
                                                             National Sediment Bioaccumulation Conference
Technical Development Work

     Several technical reports have been completed to
support the development of HHSQC. One of these, Tier
I Report: Development of Sediment Quality Criteria for
the Protection of Human Health, completed by the Wash-
ington State Department of Health (DOH), investigated
technical issues related to the development of health-
based sediment criteria (DOH, 1995). The report de-
scribes four areas of research: (1) determination of back-
ground concentrations; (2) a prioritization of chemicals
of concern; (3) development of recommended BSAFs;
and (4) fish consumption rates and recommendations.
     DOH identified over 200 potential chemicals  of
concern based on data In Ecology's SEDQUAL database.
These chemicals were prioritized into one of three groups
(Groups  I,' 2, and 3) based on whether they had EPA
toxicity values (CPFs or RfDs), the frequency with which
they were detected in urban areas, and their ability to
bioaccumulate in aquatic biota (as measured by their Kow).
     Ecology is focusing its efforts on  developing
HHSQC  for six organic chemicals or chemical groups
from the  Group 1 chemicals of concern list which are of
primary human health concern in Puget Sound and for
which our confidence in the toxicity and the BSAF is the
highest.  These chemicals are known to bioaccumulate,
have been found in Puget Sound fish or shellfish, and are
likely to present a risk to humans at levels that are lower
than current ecologically based sediment criteria. These
chemicals are:
       DDT and metabolites
       Hexachlorobenzene
       Hexachlorobutadiene
       HPAHs (high molecular weight polycyclic aro-
       matic hydrocarbons)
       PCBs
       Polychlorinated dibenzodioxins and furans
     There are other chemicals of concern for which a
scientifically defensible BSAF could not be developed at
this time, including several inorganic compounds such as
mercury. For these chemicals, Ecology is proposing to
develop  target tissue levels that can be used  to make
source control and cleanup decisions in the absence of an
HHSQC.
BSAF Development

      Initial efforts by DOH focused on the use of a
bioenergetics-based equilibrium-partitioning model
(Thomann et al., 1992). However, an empirically based
approach, relying on information from both the pub-
lished and gray literature, was developed "and recom-
mended. This was due to the availability of empirical
data as well as a lack of appropriate Input parameters for
the model.  This approach is described in the final DOH
Tier I Report (DOH, 1995).
      DOH compiled empirically derived. BSAF values
from a variety of sources for a range of aquatic species
and chemicals.  Over 1,200 BSAFs for upper trophic
level fish were identified for a set of organic chemicals of
concern. These BSAFs were primarily field-derived and
represent both marine and freshwater species.
     DOH derived BSAFs  from these literature values
using descriptive statistics based on grouping chemicals
by chemical class and log Kow.  DOH recommended the
use of the 75th percentile BSAF values for criteria
development.
     To provide additional support for BSAF develop-
ment, Ecology hired an outside contractor (PTI Environ-
mental Services) to analyze the data set compiled by
DOH. PTI used linear and nonlinear multiple regression
analysis to investigate the effects  of chemical-specific
and species-specific characteristics on BSAF values and
to estimate BSAFs (PTI Environmental Services, 1995).
     Based on the results of the multiple linear regres-
sion analysis, separate BSAF calculation equations were
developed for different chemical classes, feeding types,
and taxonomic groups.  A variety of upper confidence
limits were calculated for  these prediction equations.
Regressions were found to be statistically significant for
PCBs and dioxins in finfish and for PAHs and PCBs in
shellfish. However, the R2 ranged from 0.70 for dioxins
in finfish to 0.058 for PAHs in shellfish.
     Using the results of the DOH  and PTI  analyses,
Ecology has developed preliminary  HHSQC. BSAFs
developed by regression analysis for PCBs and dioxins in
finfish, as well as those for PAHs in shellfish,  are being
applied. BSAFs for other compounds, such as  DDT and
metabolites,  are based on  the results of a descriptive
statistical analysis (using the 90th upper confidence limit
on the mean).
Technical/Policy Implications

      Several technical andpolicy issues have been raised
in the process of developing HHSQC.   Debate over
criteria development has focused primarily on three input
parameters: (1) level of risk for cancer-causing chemi-
cals, (2) fish consumption rates, and (3) BSAFs. Each of
these issues involves both technical and policy decisions.
      Because of the controversial nature of these crite-
ria, Ecology has been working closely with an advisory
committee made up of representatives from industry,-the
environmental community, tribes, ports, and other gov-
ernment agencies, in the development of the criteria. The
committee has been providing input on Ecology's technical
development work and the related implementation issues.
      In addition to questions about the technical/scien-
tific methods being applied, concerns about the cost and
liability implications of the HHSQC have been expressed
by some potentially affected groups. In an attempt to
respond to these concerns, Ecology is currently conducting
"case studies." These case studies are areview of existing
sediment cleanup site decisions to assess the potential
impact of the HHSQC on these (and other) sites. The case
studies will also allow the agency to  improve the imple-
mentation strategy based on lessons learned in the field.
      After completion of the case studies, Ecology ex-
pects to continue with the rule'development process,
which includes proposal of a draft rule in mid-1997 and

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Proceedings
                                            '5-37
completion of a cost/benefit analysis '(as required by state
law). Ecology is looking toward adoption of HHSQC by
the end of 1997.
References

DOH (Washington State Department of Health), 1995.
     Tier I report: Development of sediment quality
     criteria for the protection of human health.  Office
     of Toxic Substances, Olympia, WA.
PTI Environmental Services.  1995. Analysis ofBSAF
     values for nonpolar organic compounds in finfish
     and shellfish, final report.  Prepared  for the
     Washington State Department of Ecology, Central
     Program, Environmental Review and Sediments
     Section.
Thomanri, R.,  J. Connolly, and T. Parkerton.  1992.
     An equilibrium model of organic chemical accu-
     mulation in  aquatic food  webs with sediment
     interaction. Environ. Toxicol. Chem. (ll):615-629.
Toy, K.A., G.D. Gawne-Mittelstaedt, N.L. Polissar, and
     S. Liao.  1995. A fish consumption survey of the
     Tulalip and Squaxin Tribes of the Puget Sound
     region (draft). Tulalip Tribes, Natural Resources
     Department, Marysville, WA.

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5-38
                            National Sediment Bioaccumulation Conference
       Development of Health-Based
          Criteria for Sediments in
                 Puget Sound
                  WASHINGTON  STATE
                  DEPARTMENT  OF
                  ECOLOGY
              Laura B. Weiss, M.P.H.

      Washington State Department of Ecology
         Environmental Review and Sediments Section
     Sediment Management Standards
              Application Model
       "Minor
       Adverse
       Effects"
       Goal:
       "No Effects"
Regulatory
Limit
Sediment
Quality
Standard
                  Increasing Sediment
                   Contamination

-------
Proceedings
                                                       5-39
     HHSQC Implementation Framework
              Initial Sediment Characterization:
              Compare to Tier I HHSQC

               Optional Tier II Analysis:
               Collect Site-Specific Data

       Exceed Standards:
       Regulatory
       action initiated
    Meet Standards:
    No regulatory
    action required
            Derivation of Health-Based
                SQC for Carcinogens
        Sediment
Risk x BW x AT
        Concentration = CPF x BSAF x IR x FL x ED

        where:
        Risk = 1 in a million (1Q-6) /1 in 100,000 (10s)
        BW - body weight of 70 kg
        AT = lifetime of 75 years
        CPF = chemical-specific cancer potency factor (IRIS)
        BSAF = chemical-specific biota-sediment accumulation factor
        IR = fish ingestion rate of 52 grams/day
        FL = fish lipid of 3%
        ED = exposure duration of 30 years

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5-40
                               National Sediment Bioaccumulation Conference
      Technical Development Work

       Tier I Report (DOH, 6/95)
       Use of Distributional Analysis (Male, 6/94)
       Fish Tissue Regulatory Options Paper
       (Male, 9/94)
       Analysis of BSAFs for Metals (PTI, 10/95)
       Analysis of BSAFs for Organics (PTI, 11/95)
       Chemicals of Concern Analysis/Display
       (PH, 10/95)
       DOH Tier II Report (DOH, 5/96)  -
       BSAF Validation for Puget Sound (PTI, 9/96)
          Tier I Report (DOH, 1995)
       Patrick, McBride, Hardy and LaFlamme

    • Areas of Research:
       - Determination of background concentrations
       - Chemicals of concern (3 groups)
       - BSAF development
       - Fish consumption review and recommendations

    • SQC calculated based on DOH
      recommendations

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Proceedings
5-41
             Chemicals of Concern = All chemicals detected in
             Puget Sound sediments (SEDQUAL)  .
                 no
                       EPA Toxicity Value?
                                  yes
                    >5% Detection Frequency in
                    Urban Bay Sediments?
                                  yes
                  no
                         logKow>3.5?
                               V- yes
                          ( Group 1
                  Human Health
             Chemicals of Concern
    * Aldrin
    • DDD, DDE, and DDT
    • Hexachlorobenzene
    • Hexachlorobutadiene
    • HPAHs(TEQ)
    • PCBs
    • Pentachlorophenol
    • Polychlorinated dibenzodioxins and furans (TEQ)
    (Note: This list includes only Group 1 organic chemicals with the highest  '
      bioaccumulation potential. Confidence in calculated BSAF values for these 8
      chemicals or chemical groups ranges from high to low.)

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5-42
                               National Sediment Bioaccumulation Conference
                 Approaches for
              BSAF Development
     • Thomann Food-Web Model
        - Requires further data collection
        - Validation recommended

     • Empirical, Literature-Based Values
        - Regression analysis
       . - Descriptive statistics

     • Use Fish Tissue Data
       to Validate
              BSAF Analysis for
         Nonpolar Organics — DOH
       Compiled data from:
       - Parkerton (1991)
       - COBIAA (1992)
       - EPA GLWQI (1994)
       Mostly field data, from marine and freshwater
       1,200 BSAF values for upper trophic level fish
       - Grouped by chemical class
          • Found too much variability among chemicals
       - Grouped by Kow and chemical class
          • Accounts for important chemical characteristics

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.Proceedings
                                                    5-43
         An Alternative BSAF Analysis
              for Nonpolar QrgaBics
      Alternative statistical analysis of data compiled by
      DOH (linear and non-linear regression analysis)
      Included a total of 1,5.91 data points (finfish and
      shellfish)
      Found significant regressions for PCBs and dioxins in
      finfish and for PCBs and PAHs in shellfish (variable
              '
      Results for PCBs in finfish consistent with DOH
      Less consistency for other chemicals of concern
            Managing Uncertainty
       Criteria Development
       - Monte Carlo Analysis
       Implementation
       - Two Tiers allow for site-specific
        data collection and analysis
       - Tissue collection and analysis

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5-44
                             National Sediment Bioaccumulatlon Conference
   HHSQC, Ecological Criteria and
      Background Concentrations
    1000 n
     100
      10 -
      1 -
     0.1 -
     0.01
                   D Ecological
                    Criteria
                   mHHSQC
                    (preliminary)
                   • "Background"
                    Concentrations
          HCB
Hcbd
PCBs   B(a)P
            Issues/Concerns Raised
        Technical/scientific methods
        Consistency between Ecology programs
        Liability and cost associated with cleanup
        Statutory authority
        Implications for source control
        Environmental equity
        Speed of rule development
        Protection of resource and future
        generations

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Proceedings
5-45
                  What Next?

        •Case Studies:
          To answer specific questions about
          implementation and rule impacts

        •  Draft rule proposal in mid-1997
                             •           •
        •  Complete cost/benefit analysis

        •  Rule adoption in late 1997

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                                                        National Sediment Bioaccumulation Conference.
Development of  Bioaccumulation
Guidance  for  Dredged  Material
Evaluations  in  EPA  Region 2
Alex Lechich
U.S. Environmental Protection Agency Region 2, New York, New York
Introduction

    The work described here was done under the auspices
    of the New York/New Jersey Harbor Dredging
    Forum, which was convened in the Summer of 1993
by the U.S. Environmental Protection Agency Region 2
(Region 2), the New York District Corps of Engineers
(NYDCOE), the New York State Department of Environ-'
mental Conservation (NYSDEC) and the State of New
Jersey Department of Environmental Protection (NJDEP).
The Forum was convened to try to solve the serious prob-
lems facing dredgrng'and disposal of dredged material from
the Harbor. The problems stem from the implementation of
revised dredged material testing procedures, which resulted
in many more proposed projects being found not suitable for
ocean disposal, and the lack of regional alternatives to ocean
disposal. The Forum drew together representatives of all of
the local interested parties, including government, industry,
shipping, labor, and public environmental interests. In early
Forum meetings, eight general areas to be addressed, were
identified and defined by the participants, and workgroups
were assembled which were tasked to address these specific
areas.                   .
     The Disposal Criteria Workgroup, chaired by Mario
Del Vicario, Chief of the Place-Based Protection Branch
in Region 2, was tasked to address the perceived "gaps" in
criteria for evaluating tests for ocean disposal of dredged
material. The workgroup initially identified eleven issues
to address. The issue  of evaluation of bioaccumulation
test results was number one on the list. In prioritizing all
eleven issues, however, the workgroup realized that some
of the other eleven issues could be resolved more quickly
and would address  outstanding issues relating to the
regional testing manual. After some of these issues were
addressed, the Bioaccumulation Subgroup of the Disposal
Criteria Workgroup was formed in the Spring of 1994,
and began to seriously address bioaccumulation after
evaluating the status of other ongoing efforts, including
national efforts.  The subgroup included a representative
each fromRegion 2, NYDCOE, NYSDEC, NJDEP, Exxon
Biomedical Services (as an industry representative), and
from a consortium of environmental groups that included
the Environmental Defense Fund, the American Littoral
Society and Clean Ocean Action.
     This discussion will describe the methods that were
developed by the subgroup, the current status of the work,
including other related work on development of BS AFs
from project test results, and the actions that are antici-
pated in the future. -
General Approach

     The workgroup decided to develop information in
two general areas, risk-based evaluation methods and
field background data on benthic invertebrate tissue
residues from areas around the ocean disposal site. This
approach follows the general guidance on evaluation of
bioaccumulation test results in the Green Book (1991),
using eight  guidance  factors   for' evaluating
bioaccumulation results  (see 1991 Green Book
Bioaccumulation Factors on page 5-53). Of these eight
factors, the workgroup felt there were important informa-
tion needs for factors four and eight, the. toxicological
importance of contaminants which exceed reference ma-
terial and exceedance of concentrations found in organ-
isms living hi the vicinity of the disposal site.
     The various toxicological measures of a contami-
nant (i.e.,  human health, ecological endpoints) are the
most important  indicators of its potential for adverse
effects, while information on background concentrations
in benthic organisms is necessary to evaluate the potential
for significantly degrading the existing conditions in the
area around the disposal site.  The toxicological impor-
tance of a contaminant needs to be related to the potential
risk to an  end receptor, which, for  dredged material
evaluations, is measured at the benthic invertebrate level
of the food chain.  The workgroup  decided to use a
method for estimating human health and wildlife risk
proposed and developed by John Zambrano of NYSDEC
with workgroup involvement.  The method is a "stan-
dards"-based assessment, as opposed to a site-specific or
                                             5-47

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5-48
         National Sediment Bioaccumulation Conference
case-specific risk assessment.  Since the workgroup had
been tasked to develop an approach on its own resources,
a phased approach was recommended that initially used
available information and established methods  where
possible. Information was readily available in the EPA
IRIS (1994,1995) database and elsewhere to derive risk-
based guidance values with the principles that EPA used
to derive water quality criteria. This would be compared
to other risk-based  information and field background
tissue data, and combined in an overall strategy for evaluation
of test results.  As new information or national guidance
values became available, the approach would be modified.
      Depending on the level of confidence that could be
placed on guidance values synthesized from the risk-
based and background information, an overall evaluation
strategy would probably still be necessary. This is because
the level of confidence hi guidance values that would be
appropriate for passing or failing a proposed ocean disposal
project based on exceedance of,  for instance, one con-
taminant (essentially setting "bright line" standards) would
be difficult to achieve, given  the uncertainties  and
assumptions in the  available methods.  A  weight-of-
evidence type strategy would be necessary if the resulting
guidance values do not have this level of confidence. The
overall approach, then, would include a human health and
ecological (aquatic and wildlife) risk-based component,
a field background tissue component and a combined
evaluation strategy.
Human Health Approach

     The risk-based approach for carcinogens starts with
effects data and, after consideration of consumption and
other exposure factors, ends with concentration-related
levels of risk. In a site-specific approach, actual "project"
concentrations are used through hazard and exposure.
assessments to result in a description of levels of risk for
the project. For noncarcinogens, reference doses (RfDs)
are used with the same exposure factors as hi the cancer
risk method The standards approach usedbroad assumptions
regarding exposure, although the method does include
site-specific information that was developed for a repre-
sentative food chain and wildlife species at potential risk.
     The human health model first calculates an accept-
able  lexicological dose for carcinogens  by dividing a
selected cancer risk by the cancer potency factor and
multiplying  by  a 70 kg body weight and  a 103  unit
conversion factor (see Human Health Method on page 5-
53).  For noncarcinogens, an RfD is multiplied by body
weight. Toxicological data was obtained from IRIS, and
information from the National Toxics Rule (1992) was
used for a total PCB reference dose (RfD). An acceptable
concentration in seafood is  calculated by dividing an
acceptable lexicological dose by a seafood consumption
factor. This is then converted to an acceptable concentration
in benthic invertebrates using a food chain factor, a whole
fish-to-filet ratio,  and a lipid adjustment (to 2 percent
lipid).
     EPA  has  recommended 6.5 g/day,as a national
average fish consumption rate in its guidance to the states
and has utilized that value in the National Toxics Rule
(1992).  It is recognized that other values may be appro-
priate to reflect any regional differences; however, there
was no effort made to determine a different regional rate.
This issue involves extensive consideration of either re-
gional survey data or comparable data, and of average
versus higher percentile consumers.  The Workgroup felt
that, for this initial effort, the procedures in the method
includes other cancer and noncancer risk components that
can account for geographic variables and population
extremes.


Trophic Transfer

      Initially,  the workgroup evaluated food chain mul-
tipliers (FCMs) used in the EPA Water Quality Standards
Handbook, which used a food chain model developed by
Thomann (1989). Scientists from EPA's Office of Re-
search and Development (ORD) recommended that the
Gobas model (1993) be used-, which was used in the EPA
Great Lakes Initiative (GLI). The ORD recommendations
came in a meeting held in Region 2 that was chaired by
Bob Huggett, EPA Assistant Administrator for ORD, and
included researchers from various ORD research labora-
tories as well as representatives from several EPA Head-
quarters offices and Regions to support Region 2 in this
effort. The Gobas model assumes equilibrium partition-
ing in benthic organisms, and it was determined that this
model reasonably represented field study data for the GLI.
To use the Gobas model in our effort, a regional food chain
with representative lipid values and organism masses for
all trophic levels  needed to be developed.  A representa-
tive coastal ocean demersal food chain for the region was
developed in consultation with National Marine Fisheries
Service and other experts. It includes information on lipid
and mass  for each trophic level organism, as well as
average values by trophic level for input into the model.
      Larry Burkhard .of EPA's Mid-Continent Ecology
Division (Duluth, MN) performed the model  runs.  The
resulting multipliers are applied on the basis of log Kow,
which were obtained from EPA guidance for the GLI
(1993).  Humans were assumed to eat primarily from the
fourth trophic level, so the multipliers from level  2 to 4
were used to calculate the increase in concentration from
benthos to human seafood  (see Tables 5  and 6 on
page 5-55).  Since the Gobas model is considered appli-
cable for lipophilic organics mat do not metabolize, it is
not applicable for metals and PAHs. For cadmium, it was
assumed that bioaccumulation occurs through water, and
biomagnification does not occur.  The trophic transfer
factor for methyl mercury was obtained from the GLI
(1995).  PAHs are metabolized in many higher trophic
organisms, but not in some benthic organisms. A trophic
transfer  factor  of one was initially assumed; however,
since there is little evidence for the potential of a signifi-
cant pathway to humans, the workgroup has  not  as yet
decided whether to include PAHs in the human  health
method. Information from several studies on PAHs in
lobsters, including hepatopancreas concentrations, is be-
ing evaluated with respect to modeling a potential human
pathway.  An ingestion  rate adjustment, as  well as

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                                                                                                   5-49
adjiistments according to EPA PAH Toxic Equivalences,
will probably be used if the workgroup decides to include
the carcinogenic PAHs in the human health method.
These adjustments would  result in higher human health
guidance values than were initially calculated (see Table 7
on page 5-56).,

 Whole Body/Met Ratio
     A whole body-to-filet ratio was used hi the human
health method. New York State data indicated a range of
1.2 to 1.5 as being applicable to lipophilic substances. The
mid-range of 1.35 Was used in the model for all lipophilic
substances.  A value of one was used for cadmium and
methyl mercury. A lipid adjustment to 2 percent lipid was
used to reflect the average lipid content of trophic level 2
in the representative demersal food chain.
Wildlife Approach

      Initially, the workgroup considered developing
wildlife protection values similarly to the human health
model, but including adjustments for less stringent effects
protection and reflecting the need to protect populations
instead of individuals. There was no consensus reached
by the workgroup on appropriate adjustments.  Also;
recommendations by ORD GLI reviewers to address their
concerns related to mis technique could not, in the opinion
of the workgroup, be implemented within the scope of this
effort.  Therefore, the workgroup decided  to calculate
wildlife reference doses (WRfD) from the GLI informa-
tion for three compounds common to the GLI and regional
contaminants being addressed, DDT, PCB and mercury.
The WRfDs  were calculated using the test doses and
uncertainty factors from the GLI Tier 1 wildlife criteria
equation and criteria documents for protection of wildlife.
The WRfDs  are conceptually equivalent to the human
RfDs. An acceptable lexicological dose is calculated by
multiplying the WRfDs by the body weights of species to
be protected  (see Wildlife Method and related informa-
tion on pages 5,-56 through 5^57).
      Representative wildlife species information was
developed that included body weight and fish consump-
tion rate at each trophic level. A variety of sources were
used to develop the wildlife species information, includ-
ing discussions with marine observers and scientists and
the EPA Wildlife Exposure Factors Handbook.
      Based on observations and review of studies in the
area, it was determined that the harbor seal would be a
good representative mammal potentially at risk, since it
has been observed in the dump site vicinity.- Other marine
mammals and sea turtles were not determined to  be at
much risk in this scenario, based on information from
sightings  regarding their regional residence times and
feeding behavior.   Studies  of food consumption and
weights of harbor seals in the wild were not available, so
mformation was obtained from the NY Aquarium, which
has held several specimens at different times.
      Discussions were held with seabird observers, in-
cluding the Mahomet Observatory and Cape  May,
Observatory in New Jersey, and available information on
avian species potentially at risk was compiled. A critical
factor for evaluating species at risk was the ability to feed
from the demersal food chain at the depths found at the
Mud Dump Site (50-80 feet).  Cormorants, old squaw
duck and red-throated loons were observed in the area and
can dive to these depths. Since there was no information
available on body weights or food consumption for these
species, input parameters used in the GLI for the belted
kingfisher were used hi the model.  Although it is ac-
knowledged that these birds have different body weights
and  probably different ingestion rates than the -belted
kingfisher, the ingestion rate to body weight ratios, which
are used in. the'model, are probably within reasonable
limits.  The herring gull data as used in the GLI was used
directly for New York Bight apex gulls to compare with
the other wildlife results., A full description and assess-
ment of the above information is available upon request.
     , The food chain for wildlife  was assumed to be
similar to the one constructed for humans. Wildlife values
for individual species are calculated using the acceptable
doses, aquatic food consumption rates and trophic transfer
factors. The trophic transfer factors are weighted according
to the relative food consumption at each trophic level. As
was done in the GLI, the final wildlife value is considered
the most stringent of the mammalian and avian results.
Aquatic Risk-Based Approach

      An aquatic risk-based approach was also proposed
that would estimate risk levels-for finfish, which were
considered the upper trophic level predators in the aquatic
system. In this approach, toxicity mformation in the EPA
AQUIRE (Aquatic Toxicity Information Retrieval) and
other databases would be evaluated and the appropriate
data compiled and manipulated to yield benthic organism
guidance levels (see Aquatic Risk-Based  Approach on
page 5-58). An order of preference for acceptability of
toxicity mformation was developed, with the key prefer-
ence being tissue residue-based lexicological data.  Un-
certainty factors would be obtained from Calabrese and
, Baldwin (1993). Bioconcentration factors, if necessary,
would be obtained from the GLI or other sources, as
available.  The food chain multipliers developed for the
other risk-based approaches would be used here  also.,  ,
      Additional databases are currently being reviewed for
tissueresidue-based toxicity information, since the amount
of information that has been identified thus far is meager
for many compounds.  It  is hoped that information on
aquatic risk will be completed in the near future and can be
incorporated with any additional information or modifi-
cations that are identified for the overall evaluation strategy.
 Background Tissue Residue Database

      There were benthic tissue contaminant data avail-
 able from various studies that had been conducted in the
 vicinity of the Mud Dump Site. This information was
 preliminarily evaluated and summarized, but  it was

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5-50
         National Sediment Bioaccumulation Conference
determined by the workgroup that a dedicated sampling
survey should be conducted to get a better representation
of overall field background benthos concentrations. Sam-
pling stations for this effort were located farther from the
disposal site than the existing studies, but included areas
of potential contamination from other sources.  Surveys
were conducted in the Spring and  Summer of 1995. The
data has been evaluated by the workgroup, and the appro-
priate statistical representation and use of the data will be
determined.  An interesting finding in this effort is that,
although the preliminary information was carefully se-
lected  to exclude data from potentially contaminated
sediments, the more recent data is generally lower in
concentrations for most contaminants.  This seems to
indicate a general improvement in the benthic conditions
of the New York Bight apex since cessation of sewage
sludge disposal in June 1992. This is, in fact, the determi-
nation  of  NOAA's National Marine Fisheries  Service
laboratory in Sandy Hook, New Jersey, from studies
conducted in the area since cessation of sludge disposal
(NOAA.1995).


Future Actions

     An example of the issues that will  need to  be
resolved in completing an overall evaluation strategy is
illustrated by the results for PCS and DDT. For DDT, the
lower bound (10*) human health risk level at 20 ppb is
within reasonable proximity to the wildlife value and the
background range. For PCB, however, an approximation
to these other values is only seen at the upper bound risk
range of 70 ppb. For many of the contaminants,  the risk
levels are in the range of the more recent (lower) background
levels.  For PAHs, as was noted above, if it is decided that
PAHs should be included in the human health risk method,
application of other factors would raise the preliminary
human health risk levels. The upper bound risk levels
would then range considerably greater than background
values. These varying factors will have to be weighed by
the workgroup in completing an evaluation strategy.
     Bioaccumulation tests are expensive and time-
consuming.  Biota-sediment accumulation  factors
(BSAFs) are being developed from some of the regional
testing results.   This  could enable  the estimation of
bioaccumulation in benthos from sediment chemical
analyses using the theoretical bioaccumulation potential
(TBP) relationship, expressed as

     TBP = AF (Cs/%TOC) %L ,

where TBP is expressed on a whole-body wet weight basis
in the same units of concentration as Cs, and
     Ca = concentration of nonpolar organic contami-
     nant in sediment
     %TOC = total organic carbon content of sediment
     expressed as a decimal fraction
     %L = organism lipid content expressed as a decimal
     fraction
      A suite of tests that were conducted for federal
navigation projects in New York/New Jersey Harbor has
produced a large and comparable data set. Preliminary
results are promising; calculated BSAFs for 2,3,7,8-TCDD
in sandworms were in the range of 0.11 to 0.19, with a
standard deviation of 0.03. Pruell et al. (1993) conducted
a long-term bioaccumulation study using sediments with
high dioxin content (-600 pptr 2,3,7,8-TCDD) and sev-
eral benthic species, anddetermined the time to steady state
and accumulation factors for PCBs, dioxins and furans. Ap-
plying an empirically derived 28-day to steady-state expo-
sure ratio factor for sandworms (~4.0) from this study, the
calculated 28-day BSAFs compare closely to the steady-
state accumulation factor for sandworms (0.46) derived
from the 1993 study.
      As additional data for other projects are incorporated
for dioxin and other contaminants, the level of confidence
in the ability to accurately estimate tissue accumulations from
sediment concentrations should be such as to greatly reduce
the need to conduct individual bioaccumulation tests.


References

Calabrese, E.J., and L.A. Baldwin.  1993.   Performing
      ecological risk assessments.   Lewis  Publishers,
      Chelsea.
Gobas, F.A.   1993.  A model for predicting the
      bioaccumulation of hydrophobic organic  chemi-
      cals in aquatic food webs:  application to Lake
      Ontario.  Ecological Modeling 69: 1-17. Elsevier
      Science Publishers B.V., Amsterdam.
NOAA.  1995. Effects of cessation of sewage sludge
      dumping at the 12-Mile Site.  NOAA Technical
      Report NMFS  124.
Pruell, R.J., N.I. Rubenstein,  B.K.  Taplin, J.A. LiVolsi,
      R.D.  Bowen. 1993.  Accumulation of polychlbri-
      nated organic contaminants from sediment by three
      benthic marine species. Arch.  Environ. Contam.
      Toxicol. 24: 290-297.
Thomann,R.V.  1989. Bioaccumulation model of organic
      chemical distribution in aquatic food chains. Envir.
      Sci. Technol 23: 699.
USEPA. 1992. Water quality standards; establishment of
      numeric criteria for priority toxic pollutants; states
      compliance. Federal Register 57:60848-60923.
USEPA. 1993. Derivation of proposed human health and
      wildlife bioaccumulation factors for the Great Lakes
      Initiative. Draft.  U.S. Environmental Protection
      Agency, Washington, DC.
USEPA.  1994 and 1995.   On line.  Integrated  Risk
      Information System (IRIS). Office of Research and
      Development, Environmental Criteria and Assess-
      ment Office, Cincinnati, OH.
USEPA. 1995.  Great Lakes Water Quality Initiative
      technical support documentfor the procedure to deter-
      mine bioaccumulation factors, Appendix E. U.S. Envi-
      ronmental Protection Agency, Washington, DC.
USEPA/USACE. 1991. Evaluation of dredged material
     proposed for ocean  disposal  - Testing manual.
      EPA-503/8-91/001.

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Proceedings
                                                                           5-51
                        NEW YORK/NEW JERSEY HARBOR
                               DREDGING FORUM
                                 EPA REGION 2

                    NEW YORK DISTRICT CORPS OF ENGINEERS

                       NEW YORK STATE DEPARTMENT OF
                        ENVIRONMENTAL CONSERVATION

                     STATE OF NEW JERSEY DEPARTMENT OF
                         ENVIRONMENTAL PROTECTION
             REPRESENTATIVES FROM GOVERNMENT, INDUSTRY, PUBLIC
                  ENVIRONMENTAL INTERESTS, SHIPPING, LABOR
                              Disposal Criteria Workgroup
                         (Chair/Mario Del Vicario, EPA Region 2)

                              Bioaccumulation Subgroup

              EPA REGION 2 - Alex Lechich

              NYD CORPS OF ENGINEERS - Lisa Rosman/Oksana Yaremko
              NEW YORK STATE DEPT. OF ENVIR. CONSERVATION -
              John Zarnbrano

              STATE OF NEW JERSEY DEPT. OF ENVIR. PROTECTION -
               Ruth Prince, Ph.D.      ,

              EXXON BIOMEDICAL SERVICES - Tom Parkerton, Ph.D.
              (Industry representative)

              RAMAPO COLLEGE - Angela Christini, Ph.D.
              (Representing public environmental interests including Environmental
              Defense Fund, American Littoral Society and Clean Ocean Action)

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5-52
                                           National Sediment Bioaccumulation Conference
                             CRITERIA WORKGROUP
                   BIOACCUMULATION STRATEGY DEVELOPMENT
           THREE COMPONENTS:

                1. Human health & ecological (aquatic and wildlife) - risk-based


                2. Field benthic (background) tissue level


                3. Combined evaluation strategy
            NY DREDGED MATERIAL FORUM CRITERIA WORKGROUP
                      (BIOACCUMULATION SUBGROUP)

       GENERALLY USED GREEN BOOK PROCEDURES:
       IF STATISTICALLY ABOVE REFERENCE, GO TO 8 FACTORS
       FOCUSED ON COMBINATION OF FACTORS ASSOCIATED WITH TOXICOLOGI-
       CAL IMPORTANCE AND TISSUE LEVELS IN VICINITY OF DISPOSAL SITE
       (BACKGROUND) COMPARISON
       WORKGROUP DECIDED ON "STANDARD" AS COMPARED TO "SITE SPECIFIC"
       RISK-BASED APPROACH BECAUSE OF TIME AND RESOURCE CONSTRAINTS
       INFORMATION FROM THIS EFFORT CAN BE USED TO LATER "FEED INTO" A
       SITE SPECIFIC RISK APPROACH
       TOXICOLOGICAL INFORMATION USED IN RISK-BASED APPROACHES FOR
       HUMAN HEALTH (CANCER AND NON-CANCER)
       AQUATIC RESOURCES
       WILDLIFE RESOURCES
       ALL APPROACHES BEGIN WITH CALCULATION OF ACCEPTABLE CONCEN-
       TRATION IN FISH, THEN APPLICATION OF ADJUSTMENTS FOR TROPHIC
       TRANSFER, LIPID AND OTHERS, RESULTING IN BENTHIC INVERTEBRATE
       TISSUE LEVEL                                •

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                                                                                5-53
                1991 GREEN BOOK BIOACCUMULATION FACTORS
 (1) number of species in which bioaccumulatiori from the dredged material is statistically greater
than bioaccumulation from the reference material
 (2) number of contaminants for which bioaccumulation from the dredged material is statistically
greater than bioaccumulation from the reference material
 (3) magnitude by which bioaccumulation from the dredged material exceeds bioaccumulation
from the reference material              ;
 (4) toxicological importance of the contaminants whose bioaccumulation from the dredged
material exceeds that from the reference material
 (5) phylogenetic diversity of the species in which bioaccumulation from the dredged, material
statistically exceeds bioaccumulation from the reference material          ,
 (6) propensity for the contaminants with statistically significant bioaccumulation to biomagnify
within aquatic food webs
 (7) magnitude of toxicity and.number and phylogenetic .diversity of species exhibiting greater
mortality in the  dredged material than in the reference material
 (8) magnitude by which contaminants whose bioaccumulation from the dredged material exceeds
that from the reference material also exceed the concentrations found in comparable species living
in the vicinity of the proposed disposal site.                                     (
                            HUMAN HEALTH METHOD

 ACCEPTABLE TOXICOLOGICAL DOSE
.1.  CANCER  -  CANCER RISK LEVEL X  BODY WEIGHT
              CANCER SLOPE FACTOR

 2.  NONCANCER - (RfD) (BODY WEIGHT)
 ACCEPTABLE TOXICOLOGICAL DOSE  =  ACCEPTABLE CONCENTRATION IN FISH
 FISH CONSUMPTION
 (ACCEPT. CONG. IN FISHY (WHOLE BODY/FILET FACTORY = ACCEPTABLE
 (TROPHIC FACTOR)                             !          CONCENTRATION IN
                                                          BENTHIC INVERTE-
                                                          BRATES

 BODY WEIGHT -70 Kg
 FISH CONSUMPTION - 6.5 g/day
 WHOLE BODY/FILET RATIO -1.35         •
 LIPID ADJUSTMENT - to 2%

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5-54
                                            National Sediment Bioaccumulatton Conference
                           FOOD CHAIN MODEL
      INITIALLY USED FCMs IN EPA WATER QUALITY STANDARDS (1993) HAND-
      BOOK - THESE USED THOMANN 1989 FOOD CHAIN MODEL
      - DOES NOT INCLUDE BENTHIC COMPARTMENT
      - USED 10% LIPID FOR ALL TROPHIC LEVELS
      BOB HUGGETT (AA, ORD) MEETING HELD ON MARCH 22-23, 1995 WITH ORD
      SCIENTISTS, HQ OFFICES AND REGIONS IN SUPPORT OF REGION 2 EFFORT
      - RECOMMENDED USE OF GOBAS 1991 MODEL
      GOBAS MODEL
      - ASSUMES EQUILIBRIUM BETWEEN SEDIMENT AND BENTHOS
      - EPA FOUND GOOD CORRELATION FOR EQUILIBRIUM AND USED MODEL IN
        THE GREAT LAKES INITIATIVE (GLI)
      - CONSIDERED APPLICABLE FOR LIPOPHILIC ORGANICS THAT AREN'T
        METABOLIZED - WASN'T ASSUMED APPLICABLE FOR METALS OR PAHs
        • FOR CADMIUM, BIOAC THRU WATER, NO BIOAMAG TTF =1
        • FOR MERCURY, TTF FROM GLI TSD, APPENDIX E
        • FOR PAHs, METABOLIZED IN MANY HIGHER ORGS  TTF == 1
      Adjusted results to reflect two percent lipid - as was found for trophic level two (benthos)
      in the representative food chain
moraic LEVEL
ifoo4 prtftnixti)
11.IV
•


•


•


•


•


Hole (summer floonder)
(and hue. juvenile fish.
mrsldlfcrtap)
hake (rak red. silver, othera)
(UM« crabs, myslds.
btarvee, pefyduetes)
blstCah
0Wv trniH crita, iqyaidi.
poiydfflettt, squid)
UtttOf
(ratnute, benides. mytEds.
cntx)
ktcter (hepito+muiele)
livtanddodllih,
fnsJttilVt*
%LIPID
(»ret wt)

1.2


LI


11


3.8


6

•Wna.^nJT «
•



•




ffrn*
TLB
•



•


•




Juven^e flnflili/iaadlmtce
(ocpepods, my^dt.
cbdoeom, fkh eg^.
nollittca bcvae)
oiutaceani (crabi, ihriin[))
(unall pdyehacM* 4t
Rothliis, d^xxtleduid
•uapendcd organic mutter.
smaller cnutoceana)
•unjt

potychies. (Nq*ty>)
Cdeposn and >edlm«nt
kvestinK or organic matter.
eimirorea of mintite
bivalve noNu^cx (Nucule.)
(decnik acid filer [cedera-
pbYtopSinktoR, orjanlc
cnutacdant (Crancoo, roysids)
(deposit and filler feeders-
decriliK. carnivores of
Ealnuw orsiinisina)
ivtnte
4.2



43




*A

2.0



3.0


1.0



2
MASS(gms)
(vretwt)

500


200


1000


800


500

600
10



10




10

I



0.1


0.1



OA

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Proceedings
                                                                                                      5-55




Log Kow
4.0
4.1
' : 4.2 '
4.3 ••'-.'
• 4.4
4.5
4.6
4.7
4.8 •
4.9
5.0
5.1 '
, 5.2
5.3
5.4
5.5
,5.6
. . 5.7
5.8
5.9,
6.0
6.1 .
6.2
6.3
. .: ,6.4-
6.5
TableS
TROPHIC TRANSFER FACTORS
-- • • vs. •• : . • •
LOG KOW
Level 3 to 2
1.0
• 1.0
•:•-,. i.o
1.0 '
1.0
1.0
1.0 •
1.0,
. 1.0
,1.0
1.0 .....
1.0 .
: ••1-° '
'•". .• . ' ' -• ' ' s u • . •
••••• • '•••''• . 1:1 •• :
l.l
'l.l " '
• •• "1.1 "..•""• •"
1.1
- •. • . 1.1 • . '.-•-••
1.1 .-•-....
' - • • . - • - 1.2
1.2 . .




Level4to2 '
1.0
1.1
1.1
1.1
,1-1
1.1
1.2
1.2 •
1.3
1.3
1.4
1.5
, 1.5
• 1.6 -
1.8
1.9
2.0
2.1
. 2.3 "
2.4
2.6
2.7
2.8
2.9
3.0
3.0


Substance
aldrin
anthracene-
benzo(a)anthracene
benzo(k)fluoranthene
benzofluoranthene, 3,4- ,
benzo(a)pyrene
cadmium - i '• .
chlordaneS.8
chrysene -
ODD
DDE
DDT
dibenz(a,h)anthracene
dieldrin
fluoranthene
fluorene -
heptachlorS.O
heptachlor epoxide :
inden(l,2,3-cd)pyrene
methyl mercury
,PCBs
pyrene
Table 6
Trophic Transfer Factors


Trophic Transfer Factor
Log Kow Level 4 to 2 Levek3'to2
6.0
•• . • 1
-
- .
,
-
1
2.3
1
6.1
6.4
6.2
-
5.0
-
1
1.4
4.1
."
.
6.1
., - - •
2.6 1.1 .
1
1 1
1- 1
1 1
1 1
1
1-1
1
2.7 1.1
2.9 1.2
2.8 1.1
1 1
1.4 1.0
' 1 1
, 1 .
1.0 .
1.1 1.0
'1 • 1
6.3 1.3
2.7 1.1
1 1
'Factors for trophic level 4 to 2 are used to derive the criteria for human health.

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5-56
                                                               National Sediment Bioaccumulation Conference
    Substance

  aldrin
  benzo(a)anthracene*
  benzo(k)fludranthene*
  benzofluoranthene,3,4*
  benzo(a)pyrene*
  cadmium
  chlordane
  chrysene*
  ODD
  DDE
  DDT
  dibenz(a,h)anthracene*
  dieldrin
  heptachlor
  heptachlor epoxide  •
  indeno(l,2,3-cd)pyrene*
  methyl mercury
  PCBs, Total
                                                  Table?

                        PRELIMINARY BENTHIC ORGANISM GUIDANCE VALUES, ug/kg
                                               (Human Health)
                     Cancer (10-6)

                          0.3
                          2*
                          2*
                          2*
                          2*

                          5
                          2*
                          20
                          10
                          20
                          2*
                          0.7
                          2 .
                          1
                          2*

                          0.7
                                             Noncancer

                                                 200
                                                10,000
                                                 300
                                                1,000

                                                 500
                                                5,000
                                                 200

                                                 200
                                                 100
  *NOTE: Values for 7 carcinogenic PAHs will be either revised upward (by incorporation of lower ingestion rate - based on Quincy
  Bay study of lobster hepatopancreas consumption - and application of TEFs), or will not be included in human health assessment.
                                          WILDLIFE METHOD


 INITIALLY, CONSIDERED USING ADJUSTMENTS TO HUMAN HEALTH METHOD, FOR LESS STRINGENT OVER-
 ALL EFFECTS PROTECTION AND REFLECTING NEED TO PROTECT POPULATIONS INSTEAD OF INDIVIDUALS
 -NO CONCENSUS; IMPRACTICAL

 USED EPA GREAT LAKES INITIATIVE (GLI) INFORMATION
 FOR 3 COMPOUNDS (DDT, PCS, MERCURY) IN THIS EFFORT

 CALCULATED WRfDs WITH TEST DOSES AND UFs FROM GLI
 TIER 1 WILDLIFE CRITERIA EQUATION AND CRITERIA DOCUMENTS FOR PROTECTION OF WILDLIFE
 Species

 mammalian
 avian
DDT

 80
 9
            Calculated WRfDs fug/kg-dl

PCS        Mercury
 30
200
16
13
 harbor seal       9600
 belted kingfisher    1.4
 herring gull        9.9
                               (WrfD)(body weight) = Wildlife Acceptable Dose
                     Wildlife Acceptable Dose fug/d")

           3600         1920
             30            2
            220          14.3

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Proceedings
                                                                                                  5-57
                                        WILDLIFE PARAMETERS
                                                                Aquatic Food
                                                    Ingestion Rate (F), (kg/day)
                                                   Troph.Lev.3 ,

                                                         0
                                                         0.0672
                                                   .      0.192
                                                       troph.Lev.4

                                                           9.6
                                                           0
                                                           >0.0480
  Selected                 'Adult Body
  Species      '     ,      Weight (Kgl

Harbor Seal              '        120
Belted King Fisher                0.15
HerringGull                     1.1

Example Computation                           .
Acceptable Doses (AD), divided by the aquatic food consumption rates (F) and the trophic transfer (TT) factors. The
trophic transfer factors are weighted according to the relative food consumption at each trophic levels An example ,
computation is presented below for the Herring Gull and DDTr.
                   Species Criterion =
                           (Gull, DDTr)
                   Species Criterion =
                           (Gull, DDTr)
                                                    AD
                        [(FTL3)(TT3.2)+(FtM)(TT4r2)]
                               9.9
                        [(0.192)(1.1)+(0,0480)2.8]
Species Criterion (Gull, DDTr) = 29.2 ug/kg,
                               WILDLIFE GUIDANCE VALUES fug/kg)
                                           Individual Species
                                           DDTr                Mercury
    Harbor Seal
    Belted King Fisher
    Herring Gull
                        357
                         18
                        29.2
                                                               31.7
                                                               22.2
                                                                26
134
405
637
    DDTr
    Mercury
    PCBs, Total
                         PRELIMINARY
               FINAL WILDLIFE VALUES (ug/kg)
               20               •'•"..        ,
               20
               100-      '•  f    '..'_
    DDT and PCB values are based on two percent lipid. Concentrations are based on wet weight.

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5-58
                                                                       National Sediment Bioaccumulation Conference
                                            AQUATIC RISK-BASED APPROACH

    1. Using EPA AQUIRE (Aquatic Toxicity Information Retrieval) database, searched for information on BCCs encompassing all finfish species -
    (Class Osteichthyes - bony fishes)

             -also used review chapter in CRC Critical reviews in Aquatic
             Sciences, entitled "Effects of Environmetnal Pollutants on Early
             Fish Development"
    2. AQUIRE Data: Order of Preference

             Chemical Reporting:

             1. Tissue Concentrations
             2. Water Concentrations

             Effects Reporting:

             1. Reproductive Endpoints
                      a) Embryonic or Larval Malformation
                      b) Egg Production
                      c) Hatchability/Survivorship
                      d) Embryonic or Larval Mortality
            2. Adult Chronic
            3. Adult Acute

            Endpoints Reporting:

            1. NOAEC
            2. MATC
            3. LOAEC
            4. Effects Concentrations
            5. EC50.LC50
                         - UFs from Calabrese and Baldwin
                         (1993). Performing Ecological Risk Assessments
                         - BCFs from GLI Derivation of Proposed HH and
                         WldlfBCFsforGLI
                        40°40'-
                        40°30'-
                        40°20'
                        40°10'-
                                                               73°40'       73°30'
                                    .  May 1995 Station
                                      Reference Site
                                      Mud Dump Site
                                            11^
                                                       Long Island Inshore  •
              • 20   4,19
             ~-~	
            .14
                                                         15
•            IChristiaerisen         *
            .Basin   I
       .    '     * i     Cholera      ^1
       *   I   16            Bank    W
       10  I     -m „_
New Jersey   \
Inshore       |
            r
            \
                                                              Hudson Shelf
                                                                 Valley
                                                                                    \
   Figure 1.   Map showing the five New York Bight Apex Regions and sampling locations for
                May 1995 Body Burden Survey.

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Proceedings
                                                                                          5-59
                                 ISSUES TO BE ADDRESSED


          try to reach concensus on appropriate statistical use of background data


          try to reach concensus on contaminant-specific guidance values that include human health,
          ecological and background values           .

          how do they compare?

          in some cases, roughly comparable @ 10'6 HH care, risk level                .

          for PCBs and PAHs, HH care, values are comparable only @ 10'5 - 10"4 risk levels
          will evaluate comments from peer/public review on acceptability of approach and on deriva-
          tions and conclusions
                               Biota-Sediment Accumulation Factors
                                 From Regional Dredging Projects
          (draft) results of bioaccumulation tests of nine NY/NJ Harbor dredging sites (federal
          projects) plus a reference site
                        BSAF  =   (Tc/L)
                                   Sc/TOG

          Dioxin/Furan 28-day BSAFs

              TCDD- 0.11 -0.19 (mean 0.14, SD 0.03)                   ,

              TCDF- 0.14 - 0.28 (mean 0.20, SD 0.04)

          Comparable to Pruell et al. 1993 AFs for dioxins/furans 28-day and steady state results

          Validation with other project results         ,       .

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5-60
                                   National Sediment Bioaccumulation Conference
  COMPOUND



  PCB

  DDT
HUMAN HEALTH
   10-4     10-6
   70     0.7

  2000    20
WILDLIFE
   1     2


300    110

 20    260
FIELD BKGRD
  (rough approx.)


   50-150

   10 - 20
  Wildlife:
  1.   Sub-group effort
  2.   New York State Dept. Of Envir. Conser. - Niagara River Biota Contamination Project: Fish
      Flesh Criteria for Piscivorous Wildlife, Newell, et al., July 1987

-------
                                                           National Sediment Bioaccumulation Conference
  Day Two:   September  12,  1996
Session  Five:
Questions and Answers
 A
fter each session, there was an opportunity' for
questions and answers and group discussions per-
taining to the speakers' presentations.
 Q (John Connolly, HydroQuol, Inc.): Amy, in your work
 •with BSAFs, are you assuming that if you cut the sediment
 concentration in half, the fish concentration -will drop by
 a factor of 2? How do you know that is true?

 AmyPelka, U.S. EPA Region 5:

     It probably is not true. It depends on where the site
 is. The BSAFs are not linear at one site that has 20,000
 parts per million PCBs! Here, as the concentration in-
 creases, it does not go up with the BSAFs. Similarly, as
 the concentration decreases, it does  not go down by half.
 Looking at this further, we decided that it is very Impor-
 tant to consider when arid where you are taking  your
 sediment sample. This sample represents what you.think
 ^presently and in the future or what you are trying to create
 theoretically. I am not sure whether we can do  that,
 because we do not always'have the data. We are seeing
 that there is some kind of curve where the concentration
 tops out and the BSAF is  not going to increase or
 decrease. The way to deal with this issue presently is by
 deciding whether the samples represent what we think are
 steady-state levels. Sometimes we have looked at caged
 fish data from upstream to see if that represents what the
 bioaccumulation might look like  at these low levels
 versus the high levels. You do not want to do BASFs on
 a hotspot, for example. You  would want to look at
 something lower. '         .

 Q (John Connolly): My big concern is that it is not a
 conservative assumption. For example, suppose  there
 are sources you do not know about, as in Puget Sound. We
 .have contaminated fish, and we say we are going to go in '
 and remove sediment and expe,ct contaminant levels in
 the fish, to decrease.. But what we do not realize is that
 some residual sources are contributing to the problem.
, We remove, sediment and it does not get better, because
 we did not address those sources. If we are talking about
 particular issues that may have significant economic.
 costs (for example,- dredging that costs $50 million or
 $100 million), is it worth spending $500,000 or $1
 million to find out that cutting the sediment concentra-
 tion is going to be protective of the ecosystem and human '
 health, before you make the decision based on the son of
 routine procedure that has been outlined?


 Amy Pelka:

      I agree that you should be clear about where your
 sources are before you go about trying to attack a problem
 and setting cleanup goals. And you are right that it is not
 a conservative assumption. I do not know if it was clear,
 but for Saginaw there were very low levels of PCBs on the
 surface. I showed you only normalized numbers, but, on
 average, the Saginaw levels are only 2 parts per million.
 The fish are a lot more contaminated there than they were
 in Manistique, which was much more contaminated. The
 curve for this example actually flattens down at the,
 bottom as well as at the top. I am trying to  show that, if
- you get a lot of contamination, it does not mean there will
 be more bioaccumulation at the bottom.. It never really
 goes away. You need to see where you are and look at the
 system to decide what you are going to do. Sometimes
 that is a question of whether just modeling should be
 done. There are a lot of Superfund sites in Region 5 where
 this is a problem, and you may not have the option of
 modeling to come up with an answer due to the high cost.
 It may not reduce enough of the uncertainty. So you could
 spend nothing, if you consider me free, or you could
 spend $12 million like they did to model Green Bay. In
 some cases that make sense and, in other cases, it does
 not. It really depends on the circumstances.

 Q (John Connolly): I thinkyou do have to approach it on
 a  case-by-case  basis. I have one last question. You
 mentioned offhandedly that mass removal was a good
 thing. I am not sure why that is true.

 Amy Pelka:

       I wanted to make it clear that risk assessment is one
 way to look at whether or not a site has bioaccumulation
 at levels of concern, but it is not the only way to assess
                                                5-61

-------
 5-62
                                                                National Sediment Bioaccumulation Conference
 whether or not you have a problem. In some cases, you
 wiU  not see the differences in a risk assessment. For
 example,  with  Saginaw, the levels are not going to
 decrease in the surface concentrations in sediment and
 the levels in fish populations probably will not decrease
 significantly either. From a risk assessment perspective,
 this is because the uncertainty is too large when estimat-
 ing the different ingestion rates associated  with risk
 assessments. Therefore, it is appropriate to look at mass
 as well. Maybe it is appropriate for EPA or a state agency
 to remove PCBs because they do not want loadings to the
 Great Lakes. I do not want people to think risk assessment
 is the only approach, because sometimes mass can be a
 reasonable approach.

 Q (John Connolly): For your case in Saginaw, consider
 an example where you may have 2 parts per million on the
 surface and 100 parts per million at depth. If you go in
 and dredge, you may end up with a residual concentra-
 tion of 5 parts per million. In this example, you may have
 made the problem worse.

 Amy Pclka:

      The  goal of the removal project is to remove the
 surface material. But there are  cases  where dredging
 probably will increase the surface concentrations, and
 how  do we mitigate that? The problem with Saginaw
 was that it had 22 miles of contamination at 2 parts per
 million. There would not be enough money to pay EPA
 Region 5 to bring it down to 0.5 parts per million. That
 was the point. I agree with you. We worry about that a
 lot. Sometimes  with  the dredging,  what you actually
 think you  are going  to  get as a result will often be
 higher than  what you started with.  A big issue is
 whether that is good.

 Robert Paulson, Wisconsin Department of Natural
 Resources:

      It can also certainly affect transport into the future
 with  whatever residual you leave behind, if the residual
 is at a level that will work itself up into the system a little
 bit more. You can reduce significantly the transport into
 the future  by  dealing with just mass. This is just one
 variable.

 John Connolly:

      I agree, but I think that is really on a case-by-case
 basis. If your contaminants are high 2  feet down, they
 may  really be locked away forever. But you have to
 evaluate that on a site-by-site basis.

 Q (Robert Paulson): Are they really all locked away
forever? This is the point we are questioning.

 Amy Pelka:

      There is another set of modeling you can do. With
 the risk assessment, you can try to determine whether or
 not certain storm events are going to reveal that and what
 the bioaccumulation will be after that. So, you can torture
 yourself with that consideration, too, if you want to.

 Q (EdPfau, Ohio EPA): My question is directed to Laura
 Weiss. "You had mentioned that, as part of your uncer-
 tainty analysis,  you had gone back and  revisited the
 numbers using uncertainty analysis with the stochastic
 model. You alluded to the fact that it was surprising that
 your point values came out at about the 80th percentile
from the final stochastic analysis. What particular inputs
 in the equation in the algorithm did you use distributions
for, and were the distributions from the same original
 database that the point values  were derived from?

 Laura Weiss, Washington Department of Ecology:

      We distributed as many input parameters as we
 could that were appropriate to be distributed. S orne param-
 eters were fairly simple and obvious like body weight and
 exposure duration. We also distributed fish  consumption
 rate, fish lipid, and BSAFs. We kept risk level constant and
 evaluated one of the more controversial factors, the cancer
 potency factors (CPFs). A consultant was hired to evaluate
 CPFs. This is something EPA has been grappling with over
 time as Monte Carlo analysis has become more popular.
 The results of this analysis showed that there was too much
 uncertainty and none of the approaches that were evaluated
 were really defensible. So, ultimately the toxicity factor
 was held constant as well.

 Q (Ed Pfau): Was the database for the point values
 basically the same from which the distributions were
 drawn?

 Laura Weiss:

      Yes, it basically was. We relied on local data as
much as possible, especially for parameters like fish
consumption rate.

 Q (EdPfau): You talked about using various methodolo-
gies to determine an effective concentration both in fish
tissue and for sediments. You also talked about the
surface area weighted average and use of geometric
means. Is it appropriate at some point in the future, if the
stochastic approach becomes more viable, that use of the
distribution  with its appropriate shape of distribution
would be a reasonable substitute for either one of those
methods of trying to average out concentrations in fish
tissue or in sediment concentrations?

Laura Weiss:

     On a site-specific basis, it is a potential option we
might want to look at. There might be a place for it in the
Tier 2 analysis.  However, I think it affects the other
programs in our agency as far as how they deal with
Monte Carlo analysis, particularly how the results are
analyzed and whether the input parameters are appropri-
ate. We will need to develop guidance for its use.

-------
Proceedings
                                                                                                    5-63
Amy Pelka:

     You want to make sure the set of data that you have
is representative of what you want to look at, which may
be the sediment concentration at the surface. If you have
varying spacial intensities where there are several samples
around the rot spots, your distribution still is not repre-
sentative of the true distribution, even if you have run a
Monte Carlo analysis. It all depends'on how the distribu-
tion was done. A distribution, or Monte Carlo analysis, is
not inherently evil. It just depends on how it is used. It can
be useful.

Q (Ed Pfau): So the surface area weighting is to remove
the bias in sampling, and that would not be something
that would be addressed in a Monte Carlo distribution?
Is that correct?

Amy Pelka:

     I am not sure that just because you have a surface
area weighting means that you cannot use a  Monte
Carlo distribution.  I do  not think Monte Carlo takes
away that bias in sampling. If it shows you the mean
and if you are still using a  distribution that is based on
a small subset of the data, you are still going to have the
same problem.

Q (Malcolm Watts, Zeneca,  Inc.): I am pleased that
one person, Mr. Paulson, did at least mention cost in
passing,  and I am very upset that the cost issues have
largely been ignored. I am  part of the handful  of
people here from the regulated community, and we see
these models being generated  with inordinate'costs
possibly associated with the results. This is  very dis-
turbing.  The methodology of the models  seems to  be
quite good, except when conservative factors are in-
troduced which build upon one another to give inordi-
nately cautious results. In particular, with those sites
that I have been  involved with, I have found the
science base is not worth anything. The data that Ms.
Pelka  referred to as being very difficult to find and
evaluate, I believe, is characteristic of the basis on which
the decisions are  made. This produces results which
cause high costs. I propose to you to use the models and
the data you have, and see what the results are. If they are
easy to work with, like no action or modest action, then
that is fine. If, on the other hand,  the costs are very high,
you should reverse tracks. You should find the  most
sensitive parameters,  look  at the data for those param-
 eters,  and focus the  research on that. The scientific
 community is not doing bad work. It is just that they are
 not being funded to do it  correctly,  so scientists often
 make do with what they have, not with what they should
 have.

 Victor McFarland, U.S.  ACE, Waterways Experi-
 ment Station:
between neutral chemicals  and their concentration in
sediments and in organisms based on organic carbon and
lipid normalization, we called that a preference factor.
Later, the preference factor was changed to an accumula-
tion factor, which was essentially the same thing. Then it
became a biota-sediment accumulation  factor, and we
were still talking about the same thing, although the term
got stretched to include a disequilibrium situation for fish
instead of applying it to just-invertebrates and such. Now
wearetalkingaboutaBSAFformetals.andlam unable to
figure out how things are going to be done or what the
rationale is.  .

Laura Weiss:

      I assume you are addressing me regarding the slide
that alluded to BS AFs from metals. That was probably an
oversight in terms of the terminology. The report focused
on the bioaccumulation of certain metals, such as meth-
ylmercury and tributyltin. These chemicals are of concern
from a human health perspective as they are known to
bioaccumulate in aquatic biota. The definition of BSAF
includes TOC and lipid normalization, and clearly that is
not appropriate for metals. Therefore, that was an error on
my part since the term BSAF is not strictly applicable to
metals.            •

Q (Victor McFarland): Is it too late to change it and
call it something else  like a  biota/sediment metals
factor?                                  *

Laura Weiss:

      I am interested in some terminology for that. Like
I mentioned, it seems that our biggest challenge is quan-
tifying the factor so a sediment level can be determined to
protect human health.

Q (Philip Cook, U.S. EPA, Office of Research and Devel-
opment): Amy, I am concerned about one part of your '
presentation, which dealt with the comparison of predic-
tions from the site-specific BSAFs to predictions from
BAFs. You described the BAFs as being consistent with
the Great Lakes Water Quality Initiative methodology.
However, if I followed your equations correctly, my
impression was that you were applying those BAFs to
predicted concentrations in the water and that resulted
from an assumption that there was an equilibrium be-
tween the sediments and the water. How didyou calculate
the water concentration so that you could apply the
BAFs?

Amy Pelka:

      I did not do those calculations. For Buffalo and
 Saginaw, I.think we had water column concentrations
that came from the ARCS  program. The water column
 concentrations were measured.
      I would like to mention a word about terminology.
 When  we first started talking  about the relationship
 Q (Philip Cook): Were those water concentrations based
 on freely dissolved chemicals?

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5-64
                                                               National Sediment Bidaccumulation Conference
AmyPelka:

      Both. When it was available, we looked at freely
dissolved and total.

Q (Philip Cook): How didyou calculate freely dissolved?

Amy Pelka:

      I am not sure of that. I think that would have been
operationally defined, where freely dissolved was what
passed through a filter.   \

Q (Philip Cook): The point I would make, in conclu-
sion, is that the BAFs that you used are based on freely
dissolved chemicals. You  have to  be very concerned
about what  model  you use to predict that exposure
concentration. In this case, fluctuations in concentra-
tions over time have to be considered, and, if there is
a disequilibrium between the sediments and the water
column, that would factor into the analysis. So, I have
some  concern that  the high values you predicted for
some  of the fish may have resulted from improper use
of BAFs.

Amy Pelka:

      I would have to go back and look more carefully
at those  specific  calculations. I want to make sure I
understand your point. Your point is that the BAFs are
based  on the dissolved portions,  and we should be
consistent  in terms  of the water  measurements  that
are used.

Philip Cook:

     Yes.

AmyPelka:

     I believe that was taken into account, but those
calculations were done a while ago. You are right, though.
It is important to be consistent.

Laura Weiss:

     I would like to address Mr. Watts. I  believe  you
made a comment about cost, and  I would like to
reiterate that, in Puget Sound, cost does  play a role in
our decision-making process.  In addition, before we
can adopt criteria, we have to go through a  cost-benefit
analysis as required by our legislature. Cost is some-
thing we cannot ignore.

Amy Pelka:

    . Cost is also considered in the Superfund remedial
process. The costs and implications for different cleanup
goals  and remediations are an important  part of the
negotiation discussions. They are, by no means, forgot-
ten in any sense of the word.

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                                         National Sediment Bioaccumu/atton Conference
Session  Six;
Ecological-Based Risk  Assessment
James Andreasen, Panel Moderator
ILS. EPA, Office of Research and Development,
Washington, DC

Wayne R. Munns, Jr.
U.S. EPA, Office of Research and Development,
Narragansett, Rhode Island   .
Use of Bioaccumulation Date in Aquatic Life Risk
Assessment

David Charters       .               .
U.S. EPA, Office of Solid Waste and Emergency Response,
Edison, New Jersey
WildlifeRiskAssessment
                                 6-1

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                                                           National Sediment Bioaceumufation Conference
 Use of Bioaccumulation Data  in
 Aquatic Life Risk  Assessment
 Wayne R. Munns, jr.
 U.S. Environmental Protection Agency, Office of Research and Development,
 Atlantic Ecology Division, Narragansett, Rhode Island
 Introduction

      Problems of sediment contamination are being
      viewed increasingly from a risk assessment per-
      spective.  Environmental managers with regula-
 tory responsibility for hazardous waste sites, sediment
 dredging and disposal, and similar problems are begin-
 ning to use the tools and approaches of risk assessment to
 evaluate adverse effects  associated with chemical  con-
 centrations measured in sediments.  In the most general
 sense, accurate estimation of ecological risks requkes both
 quantification of environmental exposure conditions and
 understanding of the biological and ecological effects
 resulting from that exposure. Ecological risk involving
 chemical stressors is a function of chemical concentration.
 or dose at the site of toxic action (DSTA) and the biologi-
 cal or ecological effects occurring at that chemical  con-
 centration. Historically, external exposure has been used
 in aquatic toxicology as a surrogate for internal dose.
 Body burden and tissue residue data  are thought to
 provide more direct measures of DSTA. Without com-
 plete understanding of the internal dynamics of chemical
 stressors and their mechanisms of toxic effect, however,
 these measures are still but estimates (although hopefully
 improved) of DSTA.         .
     So what, then, are the uses of bioaccumulation and
 tissue residue data in assessing ecological risk?  The
 value of this kind of information obviously is limited to
 assessments involving chemical stressors. Further, the
 data confer insight solely  about exposure, just one part of
 the risk assessment puzzle. Sediment risk assessments in
 which bioaccumulation is an issue presently focus on the
 biological responses  of  individual  organisms or. their
 component cells and tissues.  However, organismal re-
 sponse can be extrapolated to population-level impacts,
 and given the appropriate ecological relationships,  bio-
 accumulation can be related to community and ecosystem
 responses. Assessments involving these levels of ecologi-
.cal organization require trophic transfer models and mod-
 els involving  species interactions.  '.  •
     The objectives of this presentation are threefold;
 (1) to describe ecological risk assessment and to present
EPA's approach for conducting such assessments; (2) to
identify how bioaccumulation and tissue residue data are
used in each of the steps of ecological risk assessment
with respect to aquatic life; and (3) to highlight some of
the key uncertainties associated with uses of bioaccumu-
lation data in making risk-based management decisions.
Although EPA's framework is by no means the  sole
approach used to evaluate risks, description of this para-
digm will help to illustrate the uses of bioaccumulation
data in the various components of any risk assessment.
By enumerating uncertainties, I hope to identify general
areas of future research that could improve the utility of
bioaccumulation information in evaluating the ecologi-
cal risks of contaminated sediments. Much of the infor-
mation provided here is obvious; yet it is important to.
keep these ideas in the forefront of discussions concern-
ing bioaccumulation to ensure that misconceptions are
not propagated as part of environmental management and
the communication of risks.

Ecological Risk Assessment

     Ecological risk assessment can be described  as a
process for estimating the likelihood of adverse ecological
impact resulting from anthropogenic stress. Risk assess-
ments can be retrospective, prospective, or a combination
of both.  In the context of sediment contamination,
retrospective assessments attempt to quantify the impacts
of past releases of contaminants on sediment-associated
receptors to enhance understanding of current ecological
condition. This often is the type of application used when
evaluating impacts associated with hazardous waste sites.
Prospective assessments involving sediment contamina-
tion attempt to predict future impacts based upon the
nature and behavior of chemical stressors and potentially
exposed ecological systems.  Prospective assessments
have utility, for example, when selecting among various
dredged sediment disposal  options. A combination of
both retrospective and prospective approaches is  useful
for evaluating risks of in-place contaminated sediments
when both current  and future conditions (for example,
under various remediation scenarios) are cogent
                                               6-3

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                                                               National Sediment Bloaccumulatlon Conference
     As proposed by the U.S. Environmental Protection
Agency'sRiskAssessmentForum(USEPA, 1992,1995),
ecological riskassessmentconsists of three primaryphases
or steps: Problem Formulation, Analysis, and Risk Char-
acterization (Figure 1).  Some of the goals of Problem
Formulation are  (1) to evaluate existing information
concerning stressors, receiving ecosystems, and potential
ecological effects; (2) to identify assessment endpoints
(valued ecological conditions or processes) to be pro-
tected; and (3) to develop a conceptual model describing
potential risks to assessment endpoints.  Discussions
among the risk assessors, environmental managers, and
other stakeholders are crucial in the process to ensure that
the assessment addresses the important regulatory and
societal concerns and that the information generated is
useful in making environmental management decisions.
The Analysis step involves characterization of exposure
conditions  in time and space, as well as  evaluation of
ecological effects potentially resulting from those levels
of exposure. Analysis involves a variety of empirical and
modeling activities, with the ultimate goal of developing
profiles of exposure andeffect. These profiles are synthe-
sized into estimates of ecological risk during the Risk
Characterization step. Characterization activities may be
either qualitative or quantitative, and are directed toward
providing the information necessary to make informed
environmental management decisions. An analysis of the
uncertainties associated with the assessment is a critical
part of Risk  Characterization.  EPA's framework is
intended to be general with respect to the nature of the
stressor(s)  and the ecological systems involved in any
given assessment. It is therefore useful in assessments
involving either chemical or nonchemical stressors, and
all types of ecological systems.  How bioaccumulation
and tissue residue data are used in the specific steps of risk
assessment is described in the next three sections.
Uses in the Problem Formulation Phase

     Bioaccumulation and tissue residue data play three
somewhat related roles in Problem Formulation: (1) to
identify those stressors which may impact biological
receptors, particularly at higher trophic levels (including
humans); (2) to aid in initial descriptions of the potential
extent and magnitude of sediment contamination;  and
(3) to assist in identifying the range of potential biologi-
cal and ecological effects resulting from exposure. Infor-
mation concerning important stressors, their concentra-
tion distributions, and the effects they potentially elicit
supports development of a conceptual model that focuses
the remainder of the risk assessment.
      Appreciation of  bioaccumulation potentials  can
lead to identification of contaminants that might be
available to biological receptors, and may affect organisms
at higher trophic levels. The potential for highly lipophilic
organic compounds to bioaccumulate, for instance, identi-
fies trophic transfer as an important exposure route when
these compounds are present. Not only does this suggest
that ecological receptors removed from immediate contact
with the.sediment should be considered, but it also leads
to hypotheses concerning the biological transport of
                              Ecological Risk Assessment
                              PROBLEM FORMULATION
                              ANALYSIS
                                        Characterization i Characterization
                                             of     !      of
                                          Exposure   '   Ecological
                                                    I     Effects
                              RISK CHARACTERIZATION
                                           Discussion Between Risk
                                          Assessor and Risk Manager
                                Data
                             Acquisition,
                             Verification,
                                and
                              Monitoring
                                             | Risk Management \
 Figure 1. EPA's framework for ecological risk assessment (from USEPA, 1995).

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Proceedings
                                                                                                    6-5
 contaminants away from the immediate site of contami-
 nation.  Conversely, chemicals with low potential to
 bioaccumulate  (some metals, for example), cannot be
 eliminated as stressors of concern, since die toxic effects
 of some chemicals are not tightly linked to body burden.
      A requirement for adverse impact is the co-occur-
 rence  of the stressor with biological receptors.   For
 chemical stressors associated with sediments, environ-
 mental exposure (external to biological receptors) is
 controlled by a number of geochemical factors.  Histori-
 cally, environmental exposure had been quantified as the
 chemical's bulk concentration in the sediment. Recent
 advances in understanding the partitioning of chemicals
 among various  environmental phases has enhanced the
 accuracy of predictions of the availability of chemicals to
 biological receptors, particularly those in intimate con-
 tact with the sediment. In many cases, tissue residue data
 provide  independent verification  of these  predictions
 and support description of the extent of contamination.
 As importantly, tissue residues support, evaluation of the
 extent of exposure to those receptors somewhat removed
 from direct contact with the sediment.  For example,
 elevated contaminant levels.in deployed blue mussels or
 pelagic finfish indicate contaminant transport from the
 sediment to the water column or through trophic transfer.
 This in turn implies that ecological effects  may not be
 limited to benthic organisms.
     Knowledge of the degree to which contaminants
 bioaccumulate,  and the tissues in which they accumu-
 late, can provide insight to potential  biological effects.
 PCBs, for example, are known to accumulate in lipid-rich
                                                     tissues such as gonads and have been associated with
                                                     reproductive impairment.  They also can be transferred
                                                     during oogenesis to potential offspring, and can cause a
                                                     number of developmental and survival effects. Thus, hi
                                                     addition to effects resulting from trophic transfer, poten-
                                                     tial transgeneratipnal effects may be possible.
                                                          In combination, the information above can be used
                                                     to  define a conceptual model of exposure leading to
                                                     potential ecological effects. The conceptual model can
                                                     incorporate hypotheses of how  contaminants  move
                                                     through the physical environment and biotic food webs,
                                                     thereby identifying key exposure pathways and exposure
                                                     media for further evaluation.  Figure 2 illustrates
                                                     a generalized conceptual model relating  potential
                                                     contaminant sources in a watershed to ecological receptors
                                                     in an estuary.  In this model, a chemical released to the
                                                     environment through anthropogenic activity enters the
                                                     estuary via surface water, ground wafer, and atmospheric
                                                     routes. Phase partitioning, water movement, and transport
                                                     of  particulates redistribute the chemical to various
                                                     environmental compartments (including  sediments)
                                                     within the estuary, leading to potential exposure of a
                                                     variety of aquatic organisms. Geochemical and biological
                                                     processes influence uptake  of the chemical by biological
                                                     receptors, which in turn may result in its transfer to
                                                     organisms at  higher  trophic levels.  In addition to
                                                     providing a description of environmental exposure pathways
                                                     (primarily transport and fate), fully developed concep-
                                                     tual models communicate hypotheses concerning the
                                                     potential adverse effects that may result from
                                                     exposure. This often requires greater detail in,
                             Exposure Pathway Analysis
                                               Bioconcentration   ,
   > ^^ *~ *  >   ^
 ,^'ssf -~~r* f  --  -
, _    ,   ,„„    Redistribution in " [
^"{f'','•.''^   ^~'\   Aquatic Environment "
Figure 2. Generalized conceptual model relating contaminant sources to estuarine receptors.

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6-6
                                                               National Sediment Bioaccumulatlon (Conference
the description of chemical uptake by receptors, and can
involve conceptual understanding of the toxicokinetics
and toxicodynamics of the contaminant within receptor
organisms (Figure 3).
     When developed on an assessment-specific basis, the
conceptual model can be used to guide the activities in the
Analysis phase. Forinstance, should the chemical of interest
be persistent and display a high potential for biological
uptake,  me conceptual model  would dictate analysis of
trophic transfer (either empirically or through modeling
efforts).  Conversely, conceptual models hypothesizing
little potential of risk to key consumer organisms, as a result
of low bioaccumulation potential or the absence of impor-
tant trophic pathways, may focus analysis activities on the
direct toxicological effects on benthic organisms.

Uses  in the Analysis  Phase

     The Analysis phase of ecological risk assessment
involves characterization of exposure and characteriza-
tion of ecological effects. Legitimately, bioaccumulation
data are primarily restricted to evaluations  of exposure.
Tissue residues can be used,  however, as  independent
variables in models relating exposure to effects.
     As discussed previously, bioaccumulation data can
help define the availability of chemicals  to receptor
organisms, improving the accuracy of estimates of exposure
over bulk measures made in sediments.  For some
contaminants, tissue residues can be used to quantify
exposure along pathways leading to consumer organisms
(including humans).  This information is most useful in.
models of trophic transfer. Residue data  also support
analysis of the fate of chemical stressors when significant
biotransformation or biological transport is possible.
These kinds of information support development of a
profile describing the nature, extent,  and severity of
exposure to contaminants found in sediments.
     Use of bioaccumulation data to characterize effects
in the Analysis step is limited to quantifying internal dose
in development of dose-response relationships.  These
models relate the degree of exposure to levels of biologi-
cal/ecological response,  typically generated through
laboratory or field experimentation.   Although true
DSTA-response models theoretically provide the most
accurate predictions of likely biological effect, exposure-
response and residue-response models can also be useful.
Promising approaches for developing relationships be-
tween residues and toxicity have been proposed by
McCarty (see McCarty and Mackay, 1993) and others,
and several efforts are under way to construct databases
containing residue-effects information. Extrapolations
to threshold residue values from ambient water quality
criteria (Shephard, this conference) and similar toxicity-
based benchmarks also hold promise. However, attempts
to relate internal dose of chemical stressors to biological
effects have met with varying degrees of success.
     Bioaccumulation usually is considered a phenom-
enon relevant to individual  organisms, and past
assessments of contaminated sediments have tended to
focus on effects manifested in individuals (mortality,
reproduction, growth, and development).  Residue data
can also be linked to responses at higher levels of ecologi-
cal organization. For instance, Munns et al. (1997) used
a modeling approach to extrapolate survival and reproduc-
tive effects  of PCBs  on mummichogs  (Fundulus
heteroclitus) to estimates of population growth rate as
                      Bioconcentration
                      & Trophic Transfer
 Figure 3. Detail of conceptual model showing contaminant kinetics within an organism.

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Proceedings
                                                                                                    6-7
 a function of liver PCB burden (Figure 4).  Despite
 involving many assumptions, such approaches can be
 subjected to verification through manipulative laboratory
 and field experimentation. Similar extrapolations can be
 made to responses manifested athigher levels of ecological
 organization (for example, shifts in community structure
 and function mediated by direct toxic effects on individu-
 als and indirect effects resulting from changes in species
 interactions) by applying ecological models that incorpo-
 rate residue-response relationships.  .

 Uses in the Risk Characterization Phase

     The exposure and ecological effects profiles devel-
 oped during Analysis ultimately are used to develop under-
 standing of the risks posed by contaminated sediments. The
 utility of bioaccumulation and tissue residue data in  this
 process therefore plays out directly from the exposure  and
 effects analyses.  Similarly,  the limitations on their  use
 alluded to above also apply in Risk Characterization.
    . Both qualitative and  quantitative methods have
 been used to  characterize risk. One of the qualitative
 approaches involves calculation of simple ratios of the
 environmental exposure concentration (measured or
 modeled) to biological benchmark concentrations.
 Biological benchmarks can be receptor-specific toxicity
 thresholds, sediment quality criteria  or  standards, or
 other sediment quality assessment guidelines.  Critical
 body residues or other derived toxicity thresholds based
 on residue burdens  offer  a  means  to  incorporate
 bioaccumulation data into this characterization approach.
 This so-called risk or hazard quotient approach is most
 useful in  screening-level assessments, since "the
            magnitudes of likely  impact are difficult to ascertain
            from simple ratios. Other qualitative techniques include
            weight-of-eyidence approaches that base conclusions
            about contaminant-associated risks  on the preponder-
            ance of information evaluated during the assessment.
            Residue data are often included as evidence of exposure.
                 Quantitative characterization methods attempt to
            provide information concerning the realized or expected
            severity of impact, often in terms of the probability of
            a "particular  level of effect.  Dynamic simulation
            modeling, static assessment, and distributional analysis
            are examples of techniques providing quantitative estimates
            of impact, Most complete with respect to analysis of the
           . full range of impact are simulation models that incorporate
            both direct (toxicity) and indirect (species interactions)
            responses potentially resulting from contaminant exposure.
            Trophic transfer submodels are useful in this  context
            when the effects of oral dose can be described. Quantitative
            techniques are often useful for evaluating the conse-
            quences of various remediation  alternatives.
            Key Uncertainties and Areas for Future
            Research

                 As  reported  during  this conference  (and
            elsewhere), our  understanding of environmental
            processes leading to contaminant availability and uptake
            has improved substantially over the past 5 to 10 years.
            We have a fairly firm grasp of the sediment factors and
            partitioning dynamics which influence bioavailability,
            can model uptake and depuration kinetics with plausible
            accuracy, and can describe transfer of contaminants from
       HI
                1  -
       s
       o
            0.96
       C   0.92  -
       a.
       O
       Q.
            0.88
—i—
 10
—i—
 20
                                                                                            30
                                    PCB  LIVER  BURDEN (ug/g)
Figure 4. Population-level effects on mummichogs as a function of PCB liver burden (from Munns et al.,
1997). •  •'""  ""  ;  ". •   '     "     ••                .     •,       .-,:         ;             •       •

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                                                             National Sediment Btoacoumulation Conference
prey  to predator with reasonable confidence.
Although additional research is still needed in these areas,
perhaps the greatest uncertainties associated with the use of
bioaccumulation data hi risk-based environmental man-
agement are associated with linking tissue residues to
biological/ecological effect.  While advances are being
made in this area (for example, the critical body residue
and similar empirical approaches), risk assessments will
continue to rely primarily on appropriately normalized
sediment concentrations as the measure of exposure until
this nut is cracked.
     In a general sense, factors that hinder our ability to
develop residue relationships include: the rates at which
contaminants are metabolized or eliminated; the toxici-
ties of intermediate metabolites relative to parent com-
pounds; dose-related induction of enzymatic systems;
the modes and time course of toxic action; homeostatic
processes resulting hi immobilization/sequestration; and
the environmental factors that mediate toxic effect.
Toxicokinetic and toxicodynamic studies would appear
to be fruitful approaches for addressing these issues.
These, then,  are some of the areas on which  future
research should focus.

Acknowledgments
     W. Berry, D. Hansen, R. Johnston, and T.  Dillon
helped develop some of the ideas hi this presentation.
W. Berry, G. Pesch, and B. Brown kindly provided timely
reviews of this paper. NHEERL AED Contribution no.
1807. Mention of trade names or commercial products
does not constitute endorsement or recommendation for
usebyUSEPA.
References


McCarty, L.S.,  and D. Mackay.  1993. Enhancing
     ecotoxicological modeling and assessment: Body
     residues and modes of toxic action. Environ. Sci.
     Technol. 27:1719-1728.
Munns, W.R., Jr., D.E. Black, T.R. Gleason, K. Salomon,
     D. Bengtson, andR. Gutjahr-Gobell. 1997. Evalu-
     ation of the effects of dioxinandPCBs onFundulus
     heteroclitus populations using a modeling ap-
     proach. Environ. Toxicol. Chem. 16:1074-1081.
Shephard, B.K. 1998. Quantification of ecological risks
     to aquatic biota from bioaccumulated chemicals.
     This conference.
USEPA.  1992. Framework for ecological risk assess-
     ment.  EPA/630/R-92/001.  U.S. Environmental
     Protection Agency, Washington, DC.
USEPA.  1995. Proposed guidelines for ecological risk
     assessment. EPA/630/R-95/002B. U.S. Environ-
     mental Protection Agency, Washington, DC.

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                                                               National Sediment Bioaccumulation Conference
 Wildlife  Risk Assessment
 David  Charters                                                     ,-    "
 U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response,
 Superfuhd Program Environmental Response Team Center, Edison, New Jersey
      This presentation will cover the Superfund ecologi-
      cal risk assessment process and an ecological risk
      assessment conducted at the LCP Chemicals site in
 Brunswick, Georgia  by  the Superfund Program.  The
 focus will be  on the. wildlife risk assessment part of the
 much larger ecological risk assessment conducted at the
 site under the Superfund removal program.  Ecological'
 risk assessment is the process that evaluates the likelihood
 that adverse ecological effects may occur or are occurring
 as a result of exposure to one or more stressors. The risk
 assessment process at this site involved applying the
 eight-step draft Superfund  risk assessment guidance
 (USEPA, 1997) at the site to obtain information to answer
 important risk questions. This approach contrasts with the
 former process of collecting extensive data initially at a
 site and playing what was once referred to as "Million
 Dollar Jeopardy." The result of the past process was that
 the Superfund Program literally spent millions of dollars
 on sites to collect data, but often made decisions based on
, a small fraction of relevant data.
 Risk Assessment Process

      The current approach to risk  assessment'in the
 Superfund Program is for the risk assessors to work with
 risk managers during the initial site assessment to meet
 two objectives: (1) to identify the questions theriskmanagers
 need to have answered and (2) to build the scientific
 framework to support the risk assessment. This up-front
 planning will avoid the pitfall of reaching the end of the
 risk assessment process with only the general conclusion
 that it is a bad site where something needs to be done. The
 outcome of  the ecological risk assessment should be
 cleanup goals, not lines around the site that define areas
 where everything inside the boundaries must be cleaned up.
      In the Superfund ecological risk assessment process
 there are eight steps  and five decision points which are
 referred to individually  as a scientific management deci-
 sion point (SMDP). At each decision point, it is the risk
 assessor' s j ob to explain to the risk manager what has been
 done. It is critical that the risk manager understands all the
 information.  This is also an  appropriate time to share the
 assessment information with the community and other
 stakeholders in the process. The risk assessor must be able
 to communicate clearly to the public what is being done on
 the site and why it is being done.
      The eight-step ecological risk assessment process
 for Superfund can be summarized as follows:
      1. Preliminary problem formulation and eco-
        logical effects evaluation
      2. Preliminary  exposure estimates and risk
        calculation                 .    •
      3. Problem formulation
      4. Study design and data quality objective process
      5. Field verification of sampling design
      6. Site investigation and analysis phase
      7. Risk characterization
      8. Risk management
 Below is  a brief  description of each step  in the risk
 assessment process.
      The process  begins with a preliminary risk assess-
 ment (steps 1 and 2) which is the equivalent of a screening
 risk assessment. The first step in the preliminary assess-
 ment includes the site visit, problem formulation, and
 toxicity evaluation; the second step involves develop^
 ment of preliminary exposure estimates and risk calcula-
 tion. A preliminary assessment normally includes about
 240 chemicals.  These chemicals are run through a very
 preliminary and conservative screen initially to elimi-
 nate all the chemicals that show no indication that they
 need to be considered in the full risk assessment. In rare
 cases, a preliminary risk as ses sment can result in termina-
 tion of the risk assessment if data indicates that there is no
 significant risk at the site. Both the risk assessors and the
 risk managers must agree on this determination.  This
 determination is the first scientific management decision
 point.
     The decision  to  continue the risk assessment
 initiates the'full  risk  assessment process  which is
 described in program-specific guidance, but follows the
 Agency framework for risk assessment (USEPA, 1997). •
     The decision  to  continue the risk assessment
initiates the full risk assessment process, beginning with
problem formulation (step 3). The problem formulation
phase involves several activities including toxicity evalu-
 ation, selection of assessment endpoints, and devel-
opment  of  the  conceptual  model and testable
hypotheses. The second SMDP occurs at the end of prob-
lem formulation. At this point the involved parties must
agree on the assessment endpoints, the conceptual model,
the exposure pathways, and questions or risk hypotheses.
     The risk asssessment continues with development
of the  study design  and identification of data  quality
                                                  6-9

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                                                               National Sediment Bioaccumulation Conference
objectives and statistical considerations (step 4).  This
process produces a work plan and sampling and data
analysis plan.  Agreement on the content of both plans
constitutes the third SMDP.
     The fifth step in the risk assessment process is
verification of the field sampling plan. Field activities
during this  step will determine sampling feasibility.
This step ends with the approval of the work plan and
the sampling  and analysis  plan which is  the  fourth
SMDP. With work plan approval, the risk assessment
moves into  the site investigation and analysis phase
(step 6). The plans define how these activities will be
conducted, but they may require modification depend-
ing on circumstances such as changing field  condi-
tions.  An additional SMDP may be necessary to ap-
prove  plan  modifications.
     The risk assessment process continues with the risk
characterization (step 7). The three primary components
of risk characterization are risk estimation, risk descrip-
tion (threshold for effects on assessment ehdpoints and
other risk information), and uncertainty analysis.  And
finally, the process culminates in risk managers using the
results of the risk characterization to make the record of
decision (ROD). This decision is the final SMDP.
 Site Summary

      The LCP  Chemicals site in Brunswick, Georgia
 offers a case study for Superfund wildlife risk assessment.
 The site initially contained a petroleum refinery which
 operated for more than 10 years. In 1955 it was sold to a
 chemical  company that built a chloralkali plant on the
 property to manufacture caustic soda, chlorine, and hy-
 drochloric acid.  The plant continued to produce these
 chemicals at the site through the 1980s. Early in the risk
 assessment process some highly contaminated areas were
 identified within the site that all parties agreed needed
 remediation. PCBs measuring in the thousands of parts
 per million (ppm) were found hi sediments from these
 areas. The Superfund removal program initiated some
 actual cleanups in these areas prior to the completion of
 the risk assessment Elevated levels of mercury and lead
 were also found in sediments near the site.
      The site is tidally influenced with a tidal range of
 .about 8 feet. The tidal marsh at the site covers about 500
 acres.  It provides a very diverse habitat for wildlife,
 including a number of endangered species. Contaminants
 from the outfall area have been released through tributar-
 ies into the marsh. The question being addressed here was
 what needed to be done to restore the habitat not only for
 aquatic life, but also for wildlife. In this case, the primary
 objective was to restore and maintain  the ecological
 health of the salt marsh community, particularly with respect
 to the structure and function of the marsh.
 Assessment Endpoints and Results

       The assessment endpoints are what risk assessors
 and managers target for ecological protection.  Results
from other sites indicate that current wildlife assessment
endpoints  are  not particularly good.  The  Superfund
Program is providing additional resources to ecologists to
determine more specifically the critical ecological func-
tions that require protection to maintain diverse wildlife
habitats such as salt marshes. This information would
allow risk assessors to derive better assessment endpoints
and to define better measurement endpoints for wildlife
risk'assessment.
     [Dr. Charters discussed how they evaluated con-
taminant concentrations in wildlife at the LCP Chemicals
site, particularly for terrapins, otters, and racoons.  His
discussion focused on evaluation of mercury measure-
ments.  Selected data sets and related graphics presented
at the conference are not available for publication in this
paper.   Please contact Dr. Charters directly for further
information on the  site-specific  wildlife data for this
Superfund site in Brunswick,  Georgia.  For additional
information on EPA's Environmental Response Team,
you may visit their website on the Internet at http://
www.ert.org]
Summary

      The LCP Chemicals site is one of the first Superfund
sites to undergo evaluation using the eight-step risk as-
sessment process.  It is a site where the Superfund Pro-
gram expanded the scope of the risk assessment to con-
sider impacts to semi-aquatic and terrestrial animals living
around the aquatic environment.  That was a point of
departure from the normal EPA approach of being heavily
oriented to protection of aquatic organisms. The Superfund
Program has recognized that a lot of sites have some
terrestrial component associated with them. The program
is working very hard to come up with appropriate numbers
to use  for screening aquatically or terrestrially.  This
would allow the program to do a better job of identifying
semi-aquatic and terrestrial species that are •significantly
impacted by bioaccumulative compounds at these sites.
      Going through the eight-step process, the Superfund
Program is starting to address some of the issues that have
been addressed in  the aquatic community up to the fish
level.  The program is beginning to focus on higher
species that utilize fish as forage and introduce contami-
nation into the terrestrial envkonment, including ones that
have not been evaluated in the past. Sediment bioaccumu-
lation is an important part of the wildlife evaluation not
 only from a question of sediment uptake  directly into
 these species, but also from the view that significant
 impacts can result from contaminant-induced changes in
 behavior.
 References

 USEPA.  1997.  Process for designing and conducting
      ecological  risk assessments—interim final.  EPA
      540/R-97/006. U.S. Environmental Protection
      Agency, Office of Emergency and Remedial Re--
      sponse, Washington, DC.

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Yroceedlngs
                                       6-ri
        Ecological  Risk Assessment
          Guidance for Superfund:
         Process for Designing and
        Conducting Ecological Risk
                Assessments
                      David W. Charters, Ph.D.
                       Mark D. Sprenger, Ph.D.
 Ecological Risk Assessment Framework (U.S. EPA, 1992a)
               PROBLEM FORMULATION
                fl
                ft
              Characterization
             Characterization
             Ecolog cal Effects
               RISK CHARACTERIZATION
                                     I

                                     (Q
  &EPA
Discussion Between the Risk Assessor and Risk Manager (Results)

"           "A": ''•   "
        	Y
                   Risk Management

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6-12
                                 National Sediment Bioaccumulatlon Conference
       Eight-Step Ecological  Risk
        Assessment Process for
                   Superfund
liEZI;
     O
   —
STEP1:
PRELIMINARY
Site Visit
Problem Formulation
Toxicity Evaluation
    a
  ii* Tu^u- ™
  i<§	:
  i	"S	!
  ill	i
        STEP 2:   PRELIMINARY
                 Exposure Estimate
                 Risk Calculation
        STEP 3:   PROBLEM FORMULATION
                     Toxicity Evaluation
          Assessment Endpoints
                       Conceptual Model
                       Exposure Pathways
                    Questions/Hypotheses
STEP 4:  STUDY DESIGN AND DQO PROCESS
         Lines of Evidence
         Measurement Endpoints

Work Plan and Sampling and Analysis Plan
         STEP 5:  VERIFICATION OF FIELD SAMPLING PLAN
         STEP 6:  SITE INVESTIGATION AND DATA ANALYSIS
         STEP 7:  RISK CHARACTERIZATION
         STEP 8:  RISK MANAGEMENT
                                                 \fj&i*ftf ' '•'**->" *• f

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Proceedings
                                                   6-13
               STEP1:  PRELIMINARY
                 •  Site Visit
                 •  Problem Formulation
                 •  Toxicity Evaluation
               STEP 2:  PRELIMINARY
                •  Exposure Estimate
                •  Risk Calculation
          STEPS:  PROBLEM
                   FORMULATION
                  Toxicity Evaluation
          Assessment
           Endpoints
 Conceptual Model
Exposure Pathways
                 Questions/Hypotheses

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6-14
                              Ncitional Sediment Bioaccumulation Conference
r>

STEP 4: STUDY DESIGN AND
DQO PROCESS
• Lines of Evidence
• Measurement Endpoints
Work Plan and
Sampling Analysis Plan
-a
'
STEPS: VERIFICATION OF FIELD
SAMPLING PLAN

      STEP 6: SITE INVESTIGATION
              AND DATA ANALYSIS
      STEP 7:  RISK
               CHARACTERIZATION
       STEP 8:  RISK MANAGEMENT

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                                                          National Sediment Bioaccumulation Conference
 Day Two:  September 12,  1996
Session  Six?
Questions and  Answers
A
 fter each session, there was an opportunity for
 questions and answers and group discussions
^pertaining to the speakers' presentations.
Q (Arnold Kuzmack, U.S. EPA Office of Water): Dave, I
could not tell on your mercury charts whether you were
distinguishing .inorganic from organic mercury.   You
really should.

David Charters:

     We are not. That is a nice toxicological issue, but
it is not a cleanup issue.

Q (Arnold Kuzmack): Whether or not the hazard quotient
is really greater than one, I think, compels -what kind of
mercury it is. In terms of the process you are laying out,
I noticed that at the step of risk characterization there
was not a scientific management decision point (SMDP),
and it strikes me as extremely important to have one.

David Charters:            ;

     The difference there is that the discussion on what
is risk characterization is pretty much the risk assessors
trying to figure out how it is done. In risk management,
it is more consideration of the risk communication issues.
We need to keep these separate. ,We do not want risk
management and risk communication to be confused any
more than has historically been done.  So it is the same
thing once again. It is whether it is in step seven of in step
eight.
Q (Todd Bridges, COE Waterways): David, you did not
say what you did with the threatened and endangered
species. Did you treat them in the same way that you did
the raccoon?

David Charters:

     No, the threatened and endangered species were
done through  the two trust agencies, U.S. Fish and
Wildlife and NOAA. We do not have a legal responsibil-
ity there, but we must comply with the spirit of that law
in working with Fish and Wildlife and NOAA. It is not
a unilateral EPA decision. At this point, those decisions
have not been made.

Q (Participant): I noticed you used a LOAEL when you
were calculating your hazard quotient rather than a
NOAEL.

David Charters:                         .

     We had better information on the LOAEL. We also
have the no-observed-adverse-effect level (NOAEL) and
we can take it down to that. This was for illustration
purposes.  It is not the standard way that is taken. If you
want to turn those into NOAEL numbers, multiply them
by 10. What we .are really looking for is not only to be
reasonable, but also to use the best  data available to
address the question, "Is there a realistic probability of an
adverse impact or not?" This is the real part of the risk
assessment, not the'screening anymore. We felt that we
were working with the best information and that it was
very solid.
                                             6-15

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                                   National Sediment Bioaccumulation Conference
Session Seven:
Integrating Bioaccumulation Results
into EPA's Decision-Making Process
Elizabeth Southerland, Panel Moderator
U.S. EPA, Office of Science and Technology,
Washington, DC
Opening Remarks

Michael Kravitz
U.S. EPA, Office of Science and Technology,
Washington, DC
Bioaccumulation Testing and Interpretation for the
Purpose of Sediment Quality Assessment: Status
and Needs
                            7-1

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                                                            National Sediment Bioaccurnulation Conference
Opening Remarks
Elizabeth Southerland
U.S. Environmental Protection Agency, Office of Science and Technology, Washington, DC
      During the first two days of the conference, we
      heard technical presentations.  Today we will be
      focusing on policy.  I would like to  review
today's agenda.  We will open with speakers from four
regulatory programs in EPA that use bioaccumulation
data. The speakers will describe the current use of this
data in their regulatory programs. After the program
presentations, I will begin the panel discussion by asking
the panelists to identify barriers to using bioaccumula-
tion data in their programs and additional needs to allow
more efficient use of bioaccumulation data. Once each
panelist has had an opportunity to address those issues,
I will.open the discussion  up to the entire audience.
During mis time you can share your ideas about future
needs and comment on any of the information that has
been presented.    •   '
     Before we  begin the  panel presentations,' I will
give a brief overview of the programs in EPA that use
bioaccumulation  data.  Then Mike  Kravitz  from my,
Division in the Office of Science and Technology will
talk about an EPA report-that is currently under develop-
ment on bioaccumulation testing and interpretation for
assessing sediment quality.  The report is being devel-
oped by an Agency workgroup that is co-chaired by the
Office of Water and the Office of Solid Waste.
     The program representatives speaking today will
explain how bioaccumulation data is used in EPA regu-
latory programs.  The data may be from laboratory
                           assays that we heard abput on the first day of the
                           conference, or it may be from field studies similar to
                           those presented on the  second day of the conference.
                           Once these programs have collected the data, their pri-
                           mary concern is determining what it means in the context
                           of their regulations.  The interpretation issue has been
                           raised a number of times at this conference. There are
                           fundamental questions that we are still trying to answer
                           about bioaccumulation data. One of the critical issues to
                           help resolve these questions is to define tissue residue
                           levels of concern for regulatory programs.  All of us feel
                           that we need to have a better idea of how to interpret this
                           data. Once we can interpret it by applying better scien-
                           tific information, we can move to the next step and
                           determine how to use it in regulatory decision-making.
                                Our panelists today are representatives of the Super-
                           fund remediation program in the Office of, Emergency
                           and Remedial Response, the industrial chemicals pro-
                           gram in the Office of Pollution Prevention and Toxics,
                           and the permitting (National Pollutant Discharge Elimi-
                           nation System) and dredged  material programs  in the
                           Office of Water.  Again, they will be giving you  an
                           overview of how they currently use bioaccumulation
                           data in these, programs.  But before we hear from our
                           panelists, let me introduce Mike Kravitz, who  is our
                           Office of Water  chair of the Bioaccumulation Analysis
                           Workgroup. He will tell us about the bioaccumulation
                           report that the workgroup is preparing.
                               BIOACCUMULATION DATA
                                      What does it mean?
                                                                 Interpretation
                        How is the information used in EPA decision-making?
      Remediation
                            z
Permitting
Pesticides
                                    \
                                            Risk Management
  Toxic
Substances
Dredged
Material
                                                 7-3

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                                                      National Sediment Bioaccumulation Conference
Bioaccumulation  Testing and
Interpretation for the Purpose  of
Sediment Quality  Assessment:   Status
and  Needs
Michael Kravitz
U.S. Environmental Protection Agency, Office of Science and Technology, Washington, DC
Problem Statement

    I ediments serve as both a sink and a reservoir for
       sistent chemical contaminants, some of-which
       bioavailable or .become bioavailable as condi-
tions change naturally or anthropogenically. For instance,
metals bioavailability can change in estuaries depending
on seasonal changes in the influences of riverine flows and
oceanic tides (Geesey et al., 1984). Bioturbation (mixing
and movement of sediments by organisms) can also affect
bioavailability of sediment contaminants by increasing
oxygen and nutrient exchanges, and increasing exchange
of contaminants with overlying  water.  Increased or
sufficient bioavailability of contaminants can result in
bioaccumulation and^ depending on the contaminant and
level of bioaccumulation, can also  result in  toxicity
and/or in transfer to consumers through dietary uptake. In
the case of certain contaminants (i.e., arsenic, mercury,
methyl mercury,  PCBs, DDT, DDE, toxaphene),
biomagnification  up the food chain can  occur,
affecting higher trophic levels (Suedel et al., 1994;
USAGE, 1995).     .
     Bioaccumulation of toxic persistent organic con-
taminants by aquatic organisms is a concern for several
federal agencies, including the U.S. Environmental Pro-
tection Agency (EPA), U.S. Army Corps of Engineers
(USAGE), National Oceanic and Atmospheric Adminis-
tration (NOAA), U.S. Fish arid Wildlife Service (FWS),
and'U.S. Geological Survey (USGS). EPA's National
Sediment Quality Survey (USEPA,  1997a) has shown
that these contaminants are widely distributed in sedi-
ments throughout the United States. The National Study
of Chemical  Residues in Fish (USEPA,  1992a) has
demonstrated that^ these  compounds are detectable in
fish tissues, and many states have issued fish consump-
tion bans as  a result of bioaccumulative compounds
reaching concentrations in fish tissue that may pose a
threat to humans that consume them (USEPA, I997b).
For these reasons, EPA and other Federal and State
agencies have -identified a need to find  solutions to
problems associated with bioaccumulative compounds
in sediments.
Scope of the Document

     The EPA document, "Bioaccumulation Testing and
Interpretation for the Purpose of Sediment Quality As-
sessment: Status and Needs" is intended to summarize the
current status of our knowledge of bioaccumulation and
recent developments in bioaccumulation research that
might improve our ability to use bioaccumulation testing
to evaluate sediment quality. Chapter 2 discusses the
information compiled in chemical-specific summary tables
(Appendix) mat represent bioaccumulation research con-
ducted during the past 10 years. The .summary tables
cpntain information associating the presence and quantity
of potentially bioaccumulative chemicals in sediment
with uptake in the tissues of aquatic and terrestrial organ-
isms and with the effects of those  chemicals on the
organisms. Chapter 3 discusses factors affecting the bio-
availability of sediment-associated contaminants. Chap-
ter 4 describes methods and techniques that have  been
developed for measuring and modeling bioaccumulation.
Chapter 5 presents brief synopses of current research on
and uses of bioaccumulation testing in  several Federal
' agency programs to support regulatory activities. Finally,
Chapter  6 summarizes further research needs for the
development of guidance for interpreting bioaccumula-
tion of persistent organic pollutants to assist in protecting
aquatic and terrestrial biota and humans from toxic effects
of bioaccumulative chemicals in sediments.
                                            7-5

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 7-6
          National Sediment Bioaccumulation Conference
 Purpose

      A number of sediment assessment methods have
 been developed to determine the bioaccumulation poten-
 tial of contaminants in sediments, but overall guidance on
 interpretation of test results in the evaluation of ecological
 and human health effects, is lacking. To begin to address
 this concern, EPA's Office of Science and Technology
 (OST) and Office of Solid Waste (OSW) formed a "Bio-
 accumulation  Analysis Workgroup" consisting of
 40Headquartersandregionalparticipants. Thisworkgroup
 has overseen the production of the present "status and
 needs paper," the purpose of which is to provide back-
 ground information and report on the status of bioaccu-
 mulation testing and interpretation in various EPA pro-
 grams (and other federal agencies).   EPA's Office of
 Water envisions that the paper will serve as the basis for
 EPA-wide cross program guidance on interpretation of
 bioaccumulation tests for the purpose of sediment quality
 assessment. Ultimately, integration of interpretable bio-
 accumulation tests into  a regulatory decision-making
 framework will be required, with the understanding that
 this would be subject to case-specific modifications based
 on individual program needs.
Regulatory Uses

      A brief synopsis of possible uses of bioaccumula-
tion data in EPA programs implementing a variety of
statutes is presented on page 7-9. More detailed informa-
tion on how bioaccumulation data is used by various
programs is provided in Chapter 5. Typical applications
of bioaccumulation guidance might be the characteriza-
tion of sediment contamination at Superfund sites, the
verification of contaminants of concern in sediment for
purposes of NPDES permitting, or the selection of dis-
posal options for dredged material.
      The Office of Enforcement and Compliance Assur-
ance (OECA) is responsible for developing and imple-
menting enforcement and compliance assurance strate-
gies for the National Environmental Policy Act (NEPA)
and other federal regulations. As such, OECA may use
bioaccumulation data under a broad range of statutes to
determine the environmental acceptability of proposed
Federal actions.
      The Office of Prevention, Pesticides, and Toxic
Substances (OPPTS) uses the results of bioaccumulation
tests to support review of new arid existing chemicals
under the Toxic Substances Control Act (TSCA) and the
registration/re-registration of chemicals under the Federal
Insecticide, Fungicide, and Rodenticide Act (FIFRA).  In
addition biaccumulation information may be used  to
provide guidance on the design of new chemicals  to
reduce bioavailability and partitioning of toxic chemicals
to sediment.
      The Office of Solid Waste and Emergency Re-
sponse (OSWER) is responsible for controlling hazard-
ous wastes and remediating hazardous waste sites under
the Resource Conservation and Recovery Act (RCRA)
and the  Comprehensive Environmental Response
 Compensation and Liability Act (CERCLA).  Under
 CERCLA, the Office of Emergency and Remedial Re-
 sponse  (OERR)—the  Superfund Program—uses sedi-
 ment assessment methods, including bioaccumulation
 data, as a standard part of initial sampling during the
 preliminary site assessment and the more in-depth reme-
 dial investigation/feasibility study for  Superfund  sites
 where sediment contamination may be present.  Under
 RCRA, OSW is preparing a rule that  addresses listed
 hazardous wastes, and mixtures of and residues derived
 from managing the hazardous wastes that pose low risks
 to human health and the environment.  The rule will
 establish chemical-specific concentrations in wastes to be
 eligible for a self-implementing exemption from the haz-
 ardous  waste management system requirements under
 Subtitle C of RCRA. A risk-based methodology is under
 development that will be used as the basis for the exit
 concentrations. The methodology considers the bioaccu-
 mulative potential of relevant chemicals in the evaluation
 of potential exposures from multiple pathways, in multi-
 media, and from a variety of waste management units.
      In response to the Hazardous and Solid  Waste
 Amendments of 1984 (HSWA), which amended RCRA,
 and the Pollution Prevention Act of 1990 (PPA), EPA
 released the Waste Minimization National Plan (WMNP)
 in November 1994. The WMNP focuses on reducing the
 generation and subsequent release to the environment of
 the most persistent, bioaccumulative, and toxic chemicals
 in hazardous wastes. One of the objectives of the WMNP
 was to develop a flexible risk-based screening tool that
 would assist stakeholders in identifying source reduction
 and recycling priorities.  EPA committed to fulfill this
 objective by developing a tool mat would prioritize chemi-
 cals based on their persistence, bioaccumulation poten-
 tial, toxicity,  and quantity.  This screening tool—the
 Waste Minimization Prioritization Tool (WMPT)—has
 been developed by OSW  and the Office of Pollution
 Prevention and Toxics (within OPPTS). It is  currently
 under public review.
     The Office of Water (OW) is responsible for EPA's
 water quality activities, which represent a coordinated
 effort to restore the nation's waters. The functions of this
 program include developing national programs, technical
 policies, and regulations relating to drinking water, water
 quality,  and ground water; establishing environmental
 and pollution source standards; and providing for the
 protection of wetlands.  In addition, this Office furnishes
 technical direction, support, and evaluation of regional
 water activities; enforces  standards; and develops pro-
 grams for technical assistance and technology transfer.
 The Office oversees the provision of training in the fields
 of water quality, economic and long-term environmental
 analysis, and marine and estuarine protection.
     OW and the USAGE developed joint technical
guidance for evaluating the potential for contaminant-
related impacts associated with the discharge of dredged
material in the ocean under the Marine  Protection,  Re-
 search,  and Sanctuaries  Act (MPRSA) (USEPA  and
USAGE, 1991).  Similar updated guidance has been
drafted  for evaluating  dredged material discharges in
fresh, estuarine, and saline (near-coastal) waters under

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Proceedings	1_	

Section 404 of the Clean Water Act (CWA) (USEPA and
USACE, 1994). These documents employ a tiered testing
protocol in which bioaccumulation data figures promi-
nently.
     Under Sections 301,304,306, and3Q7 of theCWA,
the Office of Science and Technology (OST) (within OW)
promulgates technology-based national effluent limita-
tions guidelines that control the discharge of toxic chemi-
cals and other pollutants by categories of industrial dis-
chargers. Bioaccumulation data and modeling are used in
support of this effort.         .
     In response to the Water Resources Development
Act (WRDA) of 1992 requirement that EPA conduct a
national survey of data regarding sediment quality in the
United States, OST prepared the National Sediment Qual-
ity Survey (NSQS) (USEPA, 1997a).  For calculations
related to bioaccumulation, the Survey makes use of fish
tissue  residue data, and models bioaecumulation from
 sediment using the theoretical bioaccumulation potential
 approach. A national database containing information in
 the NSQS, i.e., the National Sediment Inventory, will be
 maintained and updated on a regular basis so that it can be
 used to assess  trends in both sediment quality and the
 effectiveness of existing regulatory programs at the Fed-
 eral, State, and local levels.
      Section 403 of the CWA requires determination of
 the quantities of and potential for bioaccumulation of
 released chemicals, the potential  for pollutant transport,
 potential harm to biological communities, and direct and
 indirect effects on humans.   The "CWA Section 403:
 Procedural and Monitoring  Guidance" (USEPA, 1994)
 developed by the Office of Wetlands, Oceans, and Water-
 sheds  (OWOW) (within OW) discusses the qualities of
 target, species and methods for assessing bioaccumulation;
 monitoring program design, including sampling of caged
 or indigenous indicator species; the type of tissue to be
 analyzed in invertebrates and fishes; and techniques for
 extracting and analyzing chemical contaminants. USEPA
 (1995) provides additional information on some of these
 topics.
       EPA's National Estuary Program (NEP), autho-
 rized under CWA Section 320, is a national demonstration
 program that uses a comprehensive watershed manage-
 ment approach to address water quality and habitat prob-
 lems  in designated estuaries on  the Atlantic, Gulf, and
 Pacific coasts and in the Caribbean. OWOW developed
 guidance for  this program  (USEPA, 1992b) which is
 similar to that for Section 403 (above) and which includes
 the design and conduct of bioaccumulation monitoring
  studies to link exposure and effects and to examine risks
  to target species and humans.
       Section 402 of the CWA  authorizes the National
  Pollutant Discharge Elimination, System (NPDES) per-
  mitting program, administered by the Office of Wastewa-
  ter Management (OWM) (within OW), to regulate the
  discharge of pollutants from point sources into navigable
  waters. Bioaccumulation screening methods can be used
  to identify  chemicals of potential concern in the sedi-
  ments, followed by chemical-specific analysis for confir-
  matory purposes. Until the States adopt numeric criteria
  into their standards for sediment contaminants based on
                                                                                                   7-7
•bioaccumulation, the NPDES program would not require
 permitting authorities to include, in their NPDES permits,
 sediment bioaccumulation-based numeric limits. However,
 States have the discretion to include such limits in permits
 based on an interpretation of thek narrative standards for
 toxics. To establish such permit limits, it will be necessary,
 for permitting authorities to develop Waste Load Alloca-
 tions (WLAs) for the relevant sediment contaminants.
      Section 118(c)(2) of the CWA (Pub. L. 92-500 as
 amended by the Great Lakes Critical Programs Act of
 1990 (CPA), Pub. L. 101-596, November 16,  1990)
 required EPA to publish proposed and final water quality
 guidance on  minimum water quality standards,
 antidegradation policies, and implementation procedures
 for the Great Lakes System. In response to these require-
 ments, EPA developed the Final Water Quality Guidance
 for the Great Lakes System; Final Rule, 40 CFRpart 132;
 Federal Register, Thursday, March 23,1995. The Guid-
 ance incorporates bioaccumulation factors (BAFs) in the
 derivation of criteria and values to protect human health
 and wildlife.
       Section 118(c)(3) established the Assessment and
' Remediation of Contaminated Sediments (ARCS) Pro-
 gram to assess.the extent of sediment contamination in the
 Great Lakes and to demonstrate bench- and pilot-scale
 treatment technologies for contaminated sediment. Un-
 der the ARCS program, the Great Lakes National Program
 Office (GLNPO) used bioaccumulation data and models
 to estimate  comparative human health risks  associated
 with direct and indirect exposures to contaminated sedi-
 ments in the lower Buffalo River under selected remedial
  alternatives.  It was shown that risks could be reduced
  under the different remedial alternatives compared to no
  action, particularly if dredging was the selected option.
       Ongoing work in the State of Washington provides
  an example of the use of bioaccumulation data to imple-
  ment a state regulation. Sediment Management Standards
  (SMS) for the State of Washington were promulgated by
  the Washington State Department of Ecology under Chap-
  ter 173-204 WAC in March 1991. The purpose of these
  standards is to "reduce and ultimately eliminate adverse
  effects on biological resources and significant human
  health'threats" resulting from  contaminated sediments.
  The  State of Washington is developing human health
  sediment quality criteria for bioaccumulative compounds
  in Puget Sound sediments which will be incorporated into
  the State's existing SMS.  These criteria (not to be con:
  fused with Sediment Quality Criteria for the Protection of
  Benthic Organisms  proposed  by, EPA in the Federal
  Register in 1994) are based on standard risk assessment
  methodologies in conjunction with empirically derived
  biota-sediment accumulation factors (BSAFs).


  Important Issues Involved in
  Generating and Interpreting
  Bioaccumulation Data

        The following general and specific issues should be
   addressed before agencies can effectively consider bioac-
   cumulative compounds when developing guidance  on

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 7-8
                                                              National Sediment Bioaccumulation Conference
 sediment contamination.  Each of these issues will be
 addressed in the "status and needs" paper.


 General Issues

     •  What are the assumptions, applications, and limi-
       tations for each bioaccumulation methodology?
     •  What are the major uncertainties related to the
       assessment of bioaccumulation of sediment-asso-
       ciated contaminants?
     •  Do these uncertainties affectregulatory decisions?
       Will they be resolvable in the near term or will
       they require a much longer period for resolution?
     •  How can bioaccumulation assessment results be
       effectively applied to human health and ecologi-
       cal risk assessments?
Specific Issues

    •  What are the most appropriate definitions of terms
       related to bioaccumulation?
    •  What are the requirements for selecting species for
       bioaccumulation testing?
    •  What species are potentially available for use in
       testing?
    •  What are the most appropriate methods for testing
       bioaccumulation?
    •  Are there alternative tests that can be considered
       for assessing bioaccumulation?
    •  How can tissue-specific residue levels be coupled
       with chronic  toxicity response data to develop
      dose-response relationships for bioaccumulative
      contaminants?
    • How can bioaccumulation  methods be used to
      assess population level effects (i.e., in order to
      allow for regulatory cost-benefit analysis)?
    • How should we account for the bioaccumulation
      of metabolites of contaminants, such as PAHs?
    • When should  theoretical models be used rather
      than testing to assess bioaccumulation?
    •  How much site-specific information is required to
      apply models to predict bioaccumulation?
    •  What model parameters are more broadly appli-
      cable rather than site-specific?
   •  What bioaccumulation model components  are es-
      sential for food chain modeling?
   •  Is contaminant partitioning behavior related to
      biomagnification?
   •  Can log K^ help determine the trophic level at
      greatest risk from bioaccumulation of specific
      sediment contaminants?
   •  How should we account for differential partitioning
      of bioaccumulative contaminants among tissues?
   •  Do steady-state equilibrium model assumptions
      represent prevailing conditions in the long term
      for risk assessment purposes?
   •  What are the most sensitive exposure parameters
      that drive the outcome of human health and eco-
     logical risk assessments?
        How are different programs using bioaccumula-
        tion data and what do they need from the data to
        address their program responsibilities?
  References

  Geesey, G.G., L. Borstad, and P.M. Chapman. 1984.
       Influence of flow-related events on concentration
       and phase distribution of metals in the lower Fraser
       River and a small tributary stream in British Colum-
       bia, Canada.  Water Res. 18:233-238.
  Suedel, B.C., J. A. Boraczek, R.K. Peddicord, P. A. Cliffort
       and T.M. Dillon.   1994.  Trophic transfer  and
       biomagnification potential of contaminants in
       aquaticecosystems. Rev.Enviwn. Contam. Toxicol.
       136:21-89.
 USAGE.  1995.  Trophic transfer and biomagnification
      potential of contaminants in aquatic systems. Envi-
      ronmental Effects of Dredging Technical Notes,
      EEDP-01-33 January 1995. U.S. Army Corps of
      Engineers, Waterways Experiment Station,
      Vicksburg, MS.
 USEPA.  1992a.  National study of chemical residues in
      fish. Volume I. EPA 823-R-92-008a. U.S.Environ-
     , mental Protection Agency,  Office of Science  and
      Technology, Washington, DC.
 USEPA.  1992b.  Monitoring guidance for the National
      Estuary Program. EPA 842-B-92-004. U.S. Envi-
      ronmental Protection Agency, Office  of  Water,
      Washington, DC.
 USEPA.  1994.  CWA Section  403:  Procedural and
      monitoring  guidance-. EPA 842-B-94-003. U.S.
      Environmental Protection Agency, Office of Wa-
      ter, Washington, DC.
 USEPA.  1995.  Guidance for assessing chemical con-
      taminant data for use in fish advisories.  Volume 1.
      Fish sampling and analysis. Second edition. EPA
      823-R-95-Q07. U.S. Environmental Protection
      Agency, Office of Water,  Washington, DC.
 USEPA. 1997a. The incidence  and severity of sediment
    ' contamination in surface waters of the United
      States, Volume 1: National  sediment quality sur-
      vey.  EPA 823-R-97-006. U.S. Environmental Pro-
      tection Agency, Office of Science and Technology,
      Washington, DC.
 USEPA. 1997b. Listing of fish and wildlife consumption
      advisories.  EPA-823-C-97-004.  "U.S. Environ-
      mental Protection Agency, Office of Science and
      Technology, Washington,  DC.
 USEPA and USAGE.   1991.   Evaluation of dredged
      material proposed for ocean  disposal  - Testing
      manual. EPA-503-8-91-001. U.S. Environmental
      Protection Agency and U.S. Army Corps of Engi-
      neers, Washington, DC.
USEPA and USAGE,   1994.   Evaluation of dredged
      material proposed for discharge in waters  of the
      U.S.  - Testing manual (Draft). Inland Testing
     Manual. EPA-823-B-94-002. U.S. Environmental
     Protection Agency and U.S. Army Corps of Engi-
     neers, Washington, DC.

-------
Proceedings
                                                     7-9
   Some Major Issues Involved in Generating
     and Interpreting Bioaccumulation Data
          Laboratory vs. field methods of assessing
          bioaccumulation         •
          Feeding during testing
          Uncertainties in test procedures
          Lack of test organisms
          Relationship between contaminant body burdens and
          adverse ecological effects
          Relationship between bioassay organisms and
          procedures and natural populations
          Relationship between bioassay organisms and human
          health
   Some Major Issues Involved in Generating
     and Interpreting Bioaccumulation Data
                        (cont.)
          Need to take home range/foraging area into account
          when estimating exposure concentrations
          Weight to give to various effects endpoints
          Presence of bioaccumulative chemicals in sediments
          may pose risks to aquatic life, wildlife, and humans
          Overall guidance on interpretation of bioaccumulation
          data in the evaluation of ecological and human health
          effects is lacking
          To begin to address this concern, EPA formed a
          Bioaccumulation Analysis Workgroup consisting of 40
          Headquarters and regional participants

-------
7-10
                                   National Sediment Bioaccumulation Conference
    Bioaccumulation Analysis Workgroup is
          Overseeing the Production of:
     •   "Bioaccumulation Testing and Interpretation for the
          Purpose of Sediment Quality Assessment: Status
          and Needs"

     Document will:

     •   Provide background information and summarize
          current research that might improve our ability to use
          bioaccumulation data to evaluate sediment quality
     •   Report on the status of bioaccumulation testing and
          interpretation in various EPA programs for the
          purpose of sediment quality assessment
                      Contents
     Executive Summary

     1. Introduction
         •   The Problem
         •   Purpose and Scope of the Document
         •   Major Issues Involved in Generating and
              Interpreting Bioaccumulation Data
         •   Uncertainties

     2. Important Bioaccumulative Chemicals
         •   Rationale for Choice of Chemicals
         •   Factors Affecting Bioavailability
         •   Potential Toxicity of Bioaccumulative Chemicals

-------
Proceedings
7-11
                   Contents (cont.)
      3.  Methods for Assessing Bioaccumulation
         •  Introduction
         •  Field and Laboratory Methods for Measuring
            Bioaccumulation
         •  Approaches for Modeling Bioaccumulation

      4.  Summary of Agency Information on Bioaccumulation
         Data Collection and Interpretation
         •  U.S. Environmental Protection Agency
         •  Other Federal Agencies
         •  International Efforts
         •  Similarities and Differences
                     Contents (cont.)
      5. Further Research Needs for Understanding
         Bioaccumulation and Sediment Quality
         •   Data Gaps
         •   Uncertainties
         •   Improvements Required
         •   Summary and Conclusions

      APPENDIX A.  Chemical-specific Summaries of
                    Bioaccumulation Information

-------
7-12
                                        National Sediment B^oaccumulatjon' Conference
Biaccumulation Summary                                    Cadmium
Chemical Category: METAL (Divalent)
Chemical Name (Common Synonyms): CADMIUM    CASRN: 7440-43-9
                      Chemical Characteristics
                                                 Half-Life:
                                                 Log K^.:
                           Human Health
                                    Confidence:
  Solubility in Water:
  Log Kow:
  OralRfD:
  Critical Effect:
  Oral Slope Factor:
                                    Carcinogenic Classification:
                               Wildlife
  Partitioning Factors:
  Food Chain Multipliers:
                          Aquatic Organisms
  Partitioning Factors:
  Food Chain Multipliers:
              Tbxicitv/Bioaccumulation Assessment Profile

-------
Proceedings
                                                                                                       7-13








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-------
                                                  National Sediment Bioaccumu/ation Conference
Session Seven:
Panel Presentations
Lawrence Zaragoza
U.S. EPA, Office of Emergency and Remedial Response,
Washington, DC
Bioaccumulation Results and Decision-Making:
The Superfund Program-

James Pendergast
U.S. EPA, Office of Wastewater Management,
Washington, DC
Sediment Bioaccumulation—-A National
Pollutant Discharge Elimination System (NPDES)
Program Perspective

Thomas Murray
U.S. EPA, Office of Pollution Prevention and Toxics,
Washington, DC
Integrating Bioaccumulative Results into EPA's
Decision-Making Process

Maurice Zeeman
U.S. EPA, Office of Pollution Prevention and Toxics^
Washington, DC
U.S. EPA/OPPTand Sediments: Screening New
and Existing Chemicals for Potential Environmental
Effects

Craig Vogt                        ,
U.S. EPA, Office of Wetlands, Oceans, and Watersheds,
Washington, DC                        ,
Dredged Material Management Program

Mario Del Vicario
U.S. EPA, Region 2,
New York, New York
Dredged Material Management: A Regional Perspective
                                        7-15

-------

-------
                                                          National Sediment Bioaccumulation Conference
Bioaccumulation  Results  and
Decision-Making:
The  Superfund  Program
Lawrence  Zaragoza
U.S, Environmental Protection Agency, Office of Emergency and Remedial Response,
Washington, DC    \       -
I   have been following sediment issues -with Betsy
   Southerland and other people at EPA for a number of
   years. During that time I have been involved with a
variety of sediment projects,  including the Agency's '
Contaminated Sediment Management Strategy and sedi-
ment quality criteria. It has been an interesting experi-
ence. What I will try to do.for the next several minutes is
provide you with a reflection of my experience in working
through these issues with the Office of Water and with the
EPA Regions:
     I am sure that many of you are familiar with the
Superfund Program. The Superfund Program is designed
to protect both public health and the environment, so we
are interested in looking holistically at environmental
issues for all media. This means we are concerned with ,
air, water, and soil. In dealing with the environmental
issues at Superfund sites, we try to be consistent in our
approach to assessment of risks and cleanups.  We also .
seek to be consistent with the activities of other program
offices.  That is one of the reasons why we look to the
Office of Water to provide direction  for the type of
approaches, we should apply for contaminated sediments.
     The places where we tend to do some innovative
things are generally areas that bridge between different
program media. We especially need to consider how to
focus between different program media and how to make
sure that we are looking at everything in a consistent
manner.  Coming to the decision about what is actually
going to be protective can also be challenging. You have
to look at what happens under different programs with
different statutes, and it can be difficult to reconcile issues
from a technical perspective that have different legislative
histories and requirements.
     Superfund reauthorization has been a subject of
discussion over the last couple of years.  One of the most
striking points that I have heard expressed at some of the.
reauthorization meetings is that Superfund is a program
thatprovides significantcleanup leverage for other.cleanup
programs. We are told that the EPA's efforts complement
 stateefforts and that EPA work is especially useful on some
 of the larger and more difficult sites.
      Superfund reauthorization activities have been
 going on for several years. Bills have been drafted that did
 not make it through the political process. We hope to see
 a reauthorization bill passed in the next year.
      What about bioaccumulation data? If we are really
 seeking to effectively assess risk to public health in the
 environment, we should be looking at all the available
 information to assist us hi making better decisions. This
 would  include  bioaccumulation  information,
 bioavailability data, information on  exposure, and infor-
 mation on routes of exposure to either humans or sensitive
 species. One of the activities that we are encouraged to see
 moving forward is the work,that Mike Kravitz in the
• Office of Science and Technology is undertaking to assess
 the different methodologies that exist for measuring bio-
 accumulation and to build scientific consensus on these
 methods so they can be used more broadly.  Right now,
 each program is usually faced with having to synthesize
• that kind of information on a case-by-case basis.
      I would like to briefly describe Superfund's hazard
 ranking system (HRS), which is the primary tool we use
 to screen sites for placement on the National Priorities List
 (NPL). The HRS was revised and published as a Federal
 Register Notice on December 14, 1990.  We track the
 number of sites  hi the Superfund  universe  through a
 database called CERCLIS. Last year, we removed 28,000
 sites from CERCLIS, which left about 13,000 sites in the
 database. As of June, 1997, we have further reduced the
-number of sites in CERCLIS to 10,735. These steps have
. helped to identify those sites mat need additional assess-
 ment and possible cleanup.  Within the CERCLIS uni-
 verse, the NPL represents those sites that are.likely to
 require long-term cleanup efforts. Over 1,200 sites are on
 the NPL.  These sites tend to be complex and costly to
 clean up and many include sediment contamination. The
 HRS screening process for these sites relies on readily
 available information, because we want the process to be
                                             7-17

-------
7-18
                                                               National Sediment Bioaccumulatton Conference
cost effective in identifying sites that warrant further
attention. Sites undergo an in-depth evaluation once they
are listed. Bioaccumulation is included in this evalution,
but only the surface water exposure pathway is evaluated
for humans and other sensitive species.
     Under the HRS, three factors are examined for con-
taminants at a site.  We use bioconcentration data to
determine whether contaminants  accumulate  up food
chains. We look at water solubility data, particularly the
logarithm of the octanol-water partition coefficient Kow ,
to consider the potential for and consequences of chemical
partitioning. We also distinguish between freshwater and
saltwater environments and the resulting impacts on the
receptors (humans or other sensitive organisms) being
evaluated. Since the budget for an HRS evaluation is very
limited, the data must be collected over a relatively short
period of time.
     Risk  assessments for Superfund sites involve a
longer and more costly process than a HRS  evaluation.
Depending on the site, a risk assessment can cost a few to
several hundred thousand dollars.  Human  health risk-
assessments are conducted more frequently than ecologi-
cal risk assessments.  The risk assessment stage involves
more extensive data collection and detailed analysis of the
data. Results from standard bioassays and other assess-
ment techniques discussed at this conference are used at
this stage of analysis. These comprehensive studies are
performed atNPL sites and other areas to assess the impact
of contaminated materials on humans and other sensitive
species.
     Finally, I would like to mention a Government
Accounting Office (GAO) study that was conducted a
couple of years ago. The report included a summary of
results that we got on risk information for a number of
different pathways. We found it interesting for sediments
which drove the cleanup for 14 out of about 200 sites that
were evaluated.  Traditionally, the Superfund Program
has been driven by impacts to ground water. I definitely
see some changes that have taken place in scoring sites
using the revised HRS, which allows for more equal
consideration of risks among all media. We are also trying
to be much more comprehensive about evaluating all the
potential risks from all the media.  Some of the bases for
cleanups at Superfund sites include maximum contami-
nant levels (MCLs), MCL goals, Resource Conservation
andRecovery Act (RCRA) risklevels, and state standards.
In some instances, state standards are more restrictive than
federal criteria. You may end up being more protective in
some states than you would be in others because of the
differences in state standards. These are all issues that will
be debated significantly during reauthorization. The costs
and complications of dealing with sediment problems are
often significantly more challenging than many of the
other media. This is true not only from a risk assessment
perspective, but also from the perspective of what to do
with the material once you determine that it is a problem.

-------
Proceedings
7-iV
             What is Superfund?

     Protect health and the environment as outlined in
     the Comprehensive Environmental Response,
     Compensation and Liability Act (CERCLA) as
     amended by the Superfund Amendment and
     Reauthorization Act of 1986 (SARA)

     To be consistent with the legislative direction and
     the policies of other EPA offices (e.g., the National
     Air Quality Standard for lead), OSWER lead policy
     has targeted protection

     Available scientific information to establish
     protective levels plays a key role in policy
     formulation

     Superfund complements State cleanup programs
     and has been reported to provide an incentive for
     responsible parties to dean up environmental
     problems

     Superfund is in the process of reauthorization—we
     hope within the next year

-------
7-20
                             National Sedirhent Bioaccumulatioh Conference
           What is Needed to Use
          Bioaccumulation  Data?

     The Superfund Program seeks  to effectively assess
     risks to health and the environment

     Costs and feasibility may preclude some
     assessments for bioaccumulation or risks

     The expectation  is that Superfund will seek to
     improve risk assessments and the confidence that
     can be placed in risk assessment results
    How Does the Superfund Program
        Use Bioaccumulation Data?

     Protect health and the environment as outlined in
     the Comprehensive Environmental Response,
     Compensation and Liability Act (CERCLA) as
     amended by the Superfund Amendment and
     Reauthorization Act of 1986 (SARA)

     Superfund is in the process of reauthorization—we
     hope within the next year

-------
Proceedings
                                              7-21
    Assessing Bioaccurnulation within

        the Hazard Ranking System

  • The Hazard Ranking System (MRS) is a screening
     tool                   :

  • The MRS is the primary tool for supporting the
     addition of sites to the National Priorities List (NPL)

  • The MRS employs readily available information and
     information that can be collected

  • Bioaccurnulation is evaluated in the human food
     chain treat and environmental threats within the
     Surface Water Pathway
        A Tiered System is Used to
        Determine Bioaccurnulation
                  Potential

    Logarithm of the n-octanol-water partition coefficient
    OogKow)              ,

    Water solubility data

    Direction is provided to distinguish between fresh
    and saltwater

-------
7-22
                            National Sediment Bloaccumulation Conference
     Risk Assessments Provide for a
           Detailed Examination

     Bioassays and site specific Sediment Quality
     Criteria are assessed

     The types of standard bioassays employed by
     others support risk assessments
         SUMMARY OF THE BASIS FOR
                   CLEANUP
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-------
                                                         National Sediment Bioaccumulation Conference
 Sediment  Bioaccumulation—A
 National  Pollutant Discharge
 Elimination  System   (NPDES)
 Program  Perspective
 James  Pendergast
 U.S. Environmental Protection Agency, Office of Wastewater Management, Washington, DC
I    am going to. talk briefly about what the National
    Pollutant Discharge Elimination System (NPDES)
    Program does in the area of sediment and bioaccumu-
 lation and what we think we are going to be doing in the
 future. For all of you who have dealt with the NPDES
 Program, you may believe that half of the program staff
 are engineers and the other half are attorneys. You could
 .probably ask why these people are talking about bioaccu-
 mulation and whether they know enough to talk about it
 in the first place. We would respond that bioaccumulation,
 is of interest to us both in terms of setting permit limita-
 tions and collecting information that may be needed for
 making future watershed assessments.
     I am going to spend most of my time talking about
 both of these, but will preface my talk with a couple
 important points. One is that what I will be talking about
 is going to be in the future. And the future does not mean
 tomorrow and maybe not even next year.  In a couple of
 instances, I will be referring to what is occurring now, but
 in most cases I will be talking about activities in the 5- to
 10-year horizon. That is when the majority of permits
 may have to be .dealing with these considerations where
 necessary. The second is a point of clarification that, in
 contrast to the Superfund Program which deals with
 remediation, the NPDES Program deals with discharges
 today. By that I mean we take care of current point source
 pollutant discharges in the waters of the United States.
 For example, a facility that had discharged high levels of
 pollutants in their wastewater years ago may be discharg-
 ing  very good quality wastewater today. We regulate
 their discharge today without taking into account dis-
 charges that polluted the environment 10 to 20 years ago.
     In the ideal surface'water protection program, water
quality criteria are first developed by a combination of
Agency research and program staff. The Of fice.of Science
and Technology's (OST's) Health and Ecological Criteria
Division (HECD) is responsible for criteria development.
States then use that information to adopt water quality
standards. States are assisted in this process by the EPA
Regions and  program staff in OST's Standards and
 Applied Science Division (S ASD). The next step is to take
 that information and devise a total maximum daily load
 (TMDL) and a waste load allocation (WLA) using water
 quality models. That process will produce a number in
 terms of how many pounds of a pollutant a facility can
 discharge without exceeding water quality standards.
 Finally, the NPDES permit writer incorporates that infor-
 mation into the terms of the permit to be issued.
     The problem with the ideal world is that it is so
 seldomrealized. In the last 22 years of my experience, the
 three steps prior to issuing permits are not always there.
 For example, we do not have water quality criteria for
 every pollutant. We especially do not have criteria for all
 the pollutants that bioaccumulate". We may have some raw
 data and results from some good studies conducted  at
 universities, but we do not have criteria for every contami-
 nant. Even where we have the criteria, the states may not
 have adopted a numeric water quality standard mat in-
 cludes all those criteria. There is a catch-all phrase in
 water quality standards called a narrative standard. It is
 worded something like this: "There should be no toxics in
 toxic amounts." This gives the states a standard that can
 be used, but it puts the burden on someone to figure out
 what "toxic" and "toxic amounts" mean.
     Not many waste load allocations have been devel-
 oped for the bioconcentratable, bioaccumulative types of
 pollutants. This means that permit writers now have to
 figure out what to do. All of a sudden, they have to become
'someone who knows water quality criteria, who knows
 how things bioconcentrate, and who knows the chemistry
 and biology behind that. They must also become a math-
ematical modeler and figure out how pollutants  cycle
through the environment. And, of course, they do not
usually have the training for that, except for a 5-day course
that the Permits Division conducts. But nevertheless, that
is the type of information they must learn to integrate.
     Let us consider how sediments fit into the permit-
ting process.  In dealing with sediments, we look at
bioaccumulation data when we try to interpret the nar-
rative for those "no toxics in toxic amounts" standards.
                                            7-23

-------
 7-24
                                                               National Sediment Bioaocumulation Conference
 If you have sediment quality criteria, and you can figure
 out the fate and transport, you can walk through the same
 process of interpreting  nontoxic and  toxic amounts,
 figuring out the cause-effect relationships, and deter-
 mining which facilities  are discharging which pollut-
 ants that are causing problems in the sediments. But you
 also have to recognize that when you are dealing with
 the impact of discharges on sediments, you are having
 to take into consideration a number of different factors
 from discharges into water. For sediments, you have to
 consider important factors like the physical composi-
 tion of the  sediment and chemical interactions  with
. sediments. If you find a hot spot below a facility, you
 also need to determine whether it is due to the facility's
 discharge or to something that happened 20 years ago
 that just  got washed downstream in the last flood.
 Bioaccumulative pollutants in sediments may not al-
 ways originate from point source discharges. They may
 originate from agricultural uses where there is runoff and
 erosion from farms. This is another factor that the permit
 writer must consider.
       When we look at the information we have available
 to address sediments today in the NPDES Program, we
 have some challenges or barriers to overcome. No official
 sediment criteria have been published, although we have
 five proposed criteria. We do not find TMDLs that deal
 with sediments because you have to have sediment crite-
 ria to develop them. It is a difficult challenge to factor hi
 unquantified nonpoint source contributions.  It is also
 difficult to accurately define fate and transport when you
 deal  with physical things that scour during flooding
 events.  The calculations done by the typical NPDES
 permit writer are steady-state calculations, and  storm
  events do not fit into a steady-state calculation. So what
  do we do?
       Right now we are focusing more on the aqueous part
  of the equation. We are not doing much with sediments
  in our program today. On the  aqueous side, we have put
  out some guidance on how to deal with that "no toxics in
  toxic amounts" phrase. We have two sources of informa-
  tion that we refer people to. One is a technical support
  document produced  in 1991 for water  quality-based
  toxics control. In there, we have laid out the equation
  similar to the  water quality criteria program approach
  where they are primarily protecting human health from
  adverse affects for either a cancer or noncancer endpoint.  .
  We start out with how many ounces of fish a person can
  eat a year, the typical weight of an American who eats that
  fish, etc. From that information, you can determine what
  a water quality standard should look like. The technical
  support document also talks about a bioconcentration
  factor. Since that was  1991, we know the information
  needs to be updated. In the intervening years, we have
  been working on how to bring bioaccumulation into that
  evaluation process.
        Through some work with our Office of Research
  and Development, we have worked out how to estimate
  or calculate bioaccumulation factors that can be added
  to the equation.  The  best source of that information
  today is the Great Lakes Initiative (GLI) rule. The rule
  only applies to the Great Lakes basin, but the science in
it is universal and can be used across the country. So, this ,
is the type of guidance that we point people to when they
want to use bioaccumulation in making assessments in
the NPDES Program. There is also some discussion in the
GLI rule about what to do with fish tissue data. If you
have nothing in your aqueous phase chemistry, but you
find fish tissue that is high in a certain pollutant, can you
make regulatory decisions based on the fish tissue data?
The GLI rule shows how to translate the fish tissue data
and determine what its equivalent water quality concen-
tration would be.
     That is where we are today. We are trying to work
out a companion process for dealing with sediments hi
developing permits. Some of the focus is on simplifying
modeling that currently works  on  a  large mainframe
computer to an assessment tool that an average permit
writer can use. This could take five to ten years.  Another
important area of focus  is to conduct evaluations on  a
watershed scale rather than the traditional approach of
evaluating each individual facility.-The NPDES Program
was initiated under the Clean Water Act of 1972 to permit
facilities to reduce pollutants. At this time, it was easier
to identify major sources of pollutants.  The program
targeted the most obvious sources of pollution from the
big pipes or from areas with signs of pollution like foam
on the rivers.  The program was successful in getting
treatment technology established at plants to  combat
pollution. Now the program is  in a more difficult stage.
Every two years the states are required to provide assess-
ments of their water quality that are compiled in the
305(b) reports. Lately, they are indicating that nontradi-
tional  sources are causing more problems. These are
either urban point sources such as discharges from a storm
sewer or a combined sewer overflow (CSO) or nonpoint
 source runoff from agricultural lands or forestry sites.
 Now we are having to open our doors for the first time and
begin talking to programs in the Bureau of LandManage-
 ment and the Forest Service to decide how we are going
 to apply a holistic approach hi protecting our waters.
 Working with programs that are entirely  voluntary  to
 develop responsible water quality  management is  per-
 haps our biggest challenge.  NPDES is still part of the
 equation, but no longer the primary part of the equation.
 Sediments come into play in this process.  We need to
 identify watersheds where sediment contamination is the
 greatest source of impairment and to work with other
 agencies to deal with the sources of sediment problems.
 And we may find out that, in some cases, NPDES may not
 be the answer.
       What do we expect today? We still expect that the
 permit writers use their best judgement on how to deal
 with bioaccumulation and sediments. And best judge-
 ment  does not mean to find an ounce of science and start
 leaping miles ahead of that. What best judgement means
 is taking the current science, taking the current data, and
 using it responsibly to  take a look at watershed-based
 water management decisions:  If in looking at this infor-
 mation, a permit writer  determines that a point source is
 not the cause of the problem, then their best professional
 judgement will say, "Don't deal with it." But if the permit
 writer  finds  that a point source  is  discharging a

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Proceedings
                                                                                                  7-25
biocohcentratable or bioaccumulative pollutant at lev-
els causing impairment today, then they should use the
information to include the right requirement in the permit
to limit that pollutant.
     We do believe that NPDES permits still need to
be issued. We do not want to spend 25 years studying
•ssues before we can take any action.  But we also
recognize that issuing permits on time does not neces-
sarily mean every 5 years regardless of the situation.
Issuing permits on a timely basis means doing it when
you have enough data that it makes good sense.  And
that we will do.

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7-26
                           National Sediment Bioaccumulation Conference
       WHY IS A NPDES PROGRAM MANAGER
       TALKING ABOUT SEDIMENT
       BIOACCUMULATION?	

       Is sediment bioaccumulation a permitting
       issue?
       Is sediment bioaccumulation strictly a
       monitoring  issue?
       PERMIT ISSUANCE (WITHOUT SEDIMENT
       CONTAMINATION FACTORED IN)

Permit Writing Factors:
•   Develop criteria
    Adopt Water Quality Standards (WQS)
•   Develop Waste Load Allocation (WLA)
•   Issue permits, based on the WLA, for each point.
    source

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Proceedings
                                       7-27
     '*  PERMIT ISSUANCE (WITH SEDIMENT
     *f  CONTAMINATION FACTORED IN)
Sediment Characteristics to Consider:
•   Different sediment types (physical and chemical
    composition)
•   Sediments are not stationary
    (Fate/Tranport Issue)
•   Sediments may
    have pre-existing contaminant
    contributions from:
    natural, point or non-point sources
 '*
PERMIT WRITER'S CHALLENGE
Permit Writer's Challenges When Developing a
Permit with Sediment Contamination Factored in:
•   No sediment criteria, therefore no WQS for sediment
•   No total maximum daily loads (TMDLs)
•   Non-point source contributions not factored in
•   Transport-Fate issues are not addressed
    for sediments

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7-28
                                National Sediment Bioaccumulation Conference
        ADDRESSING THE CHALLENGES
What's Available:
    •   National Guidance
            Technical Support Document (TSD)
            (pages 36-44)
            Great Lakes Initiative (GLI)
            (pages 15400- 15406)
    •   Watershed Permitting Approach
        PERMITTING BY WATERSHEDS
          Land-Use Categories
          Forestry
       I	I Agriculture
  NPDES Facility
© CSO Stormwater Facility
/\ _ Watershed Number
~>-' Watershed Boundary

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                                           7-29
     \ WHAT IS EXPECTED FROM EPA, STATE,
     ** AND TRIBAL PERMIT WRITERS?
Minimum:
       Using all available EPA permitting guidance, issue
       permits based on Best Professional Judgement
       (BPJ).
       Issue NPDES Permits on time.

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                                                       ,  National Sediment BioaccumuJation {Conference
Integrating  Bioaccumulative  Results
into EPA's Decision-Making Process
Thomas Murray
U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC
     Premanufacture Notifications (PMNs) are required
     under section 5 of the Toxic Substances Control
     Act (TSCA) from anyone who intends to manufac-
ture or import a new chemical substance.  A new
substance is defined as one not on the Chemical Inven-
tory created under TSCA section 9.  Once  the U.S.
Environmental Protection Agency (EPA) receives a
PMN document, Agency staff normally have 90 days to
review it.  First, the PMN substance is sent through an
initial screening-level risk assessment process. A major
objective of this review process is to determine whether
the PMN substance may present an unreasonable risk of
injury to human health or the environment during its
lifetime.          .          .      ,
   .. The  Office of Pollution Prevention and Toxics
(OPPT) uses  a similar process for those chemicals al-
ready in the marketplace.  Priorities are established for
selecting existing chemicals from the chemical inven-
tory for review. There is no statutorily imposed time
schedule for these reviews.
     Coming out of the screening-level risk assessment
process, those chemicals which are found to present the
potential for unreasonable risk to human health or the
environment  are scrutinized more thoroughly.  OPPT
sometimes requires testing  in response  to identified
concerns before reaching a decision for a chemical under
review.                          ,
     Professionals from many different disciplines take
part in reviewing the various aspects of the life cycle of
a  chemical under  review.  In  his remarks, Maurice
Zeeman describes those things considered when assess-
ing risk to ecological communities.  My remarks will
focus on the human health exposures.    ,
     When a chemical is introduced into OPPT's risk
screening process, a Structure Activity Team convenes
to discuss  its potential health and eco.toxicity concerns.
This Team provides, direction to the review, process that
follows.  Of  concern to us in this discussion are those
chemicals which result  in human exposures through
surface water.  Here, OPPT engineers quantify surface
water releases of these chemicals-from point sources or
estimate these releases where monitoring data are ab-
sent. We do not routinely assess nonpoint sources.
OPPT chemists then assess the fate of these chemicals
and describe likely or known transport processes. Asses-
sors then use these fate estimates to assess the potential
human health risks associated with the expected releases.
     The process of evaluating each potential route of
exposure can be complicated.  To perform the calcula-
tions necessary for exposure evaluations, assessors make
use of simple formulas, complex mathematical models,
and a number of basic assumptions. Sound monitoring
data are always preferred but are rarely available. Much
of the work involved in the assessment process involves
frequently encountered exposure scenarios. This has
allowed OPPT to standardize most of the assessment
•process. A number of thresholds have been developed
which  help .determine whether a given chemical or
exposure route will present significant:potential expo-..
sures.  OPPT relies heavily on the efforts of other EPA
program offices and academia in updating its exposure
assumptions and models.                 .
Sediment/Bioaccumuiation Results

     When a chemical under review is believed to have
the potential to pose a risk to human health through the
surface water pathway,  several exposure assessment
steps are set in motion. First, a fate review is done to ,
determine, among other things, how much of the chemi-
cal is likely to be removed in the wastewater treatment
process.  With an: estimate of chemical loading to the
receiving stream, instream processes (hydrolysis, pho-
tolysis, biodegradation, etc.) are explored to assess the
ultimate fate of the chemical. Exposure models are then
deployed to track the. chemical downstream to drinking
water facilities. The fate chemists will also calculate the
Bioconcentration Factor (BCF) for the chemical if expo-
sure through fish ingestion is indicated. Potential Dose
Rates are calculated through this pathway only when the
log BCF is greater than 2. When the BCF is less than 100
(or the log BCF is less  than 2), the resulting human
exposure is considered negligible. If the  log Kow  is
greater than 8, human exposure is not calculated. Values
for  log K  that are higher than 8 are considered
                                              7-31

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7-32
         National Sediment Bloaccumulation Conference
unreliable; therefore, the BCF estimate is  deemed
unreliable and is not used.
      OPPT has also determined that in addition to
having the potential to bioaccumulate, the chemical
must also remain in the environment long enough to be
absorbed into fish tissue. For our purposes, degradation
of the chemical must be estimated to take months or
longer to allow uptake by fish tissue to occur. Potential
dose rates (PDR, a measure of exposure) for fish inges-
tion are calculated using the stream concentration of the
chemical at mean flow (see pages 7-33 and 7-34).  For
discharges to saline waters, chronic  mixing zone dilu-
tion factors are used, when available.  OPPT currently
assumes a fish ingestion rate of 16.9 grams per "day. To
be consistent with the most recent draft of the Exposure
Factors Handbook, we will adjust this rate. For subsis-
tence fishers a rate of 140 grams per day can be used; for
sport fishers 39 grams per day is reasonable.
      Where  our calculations  indicate that potential
exists for unreasonable risk to humans  through  fish
ingestion, we can reach several decisions.  Oftentimes,
we will require testing by the industry to refine our fate
estimates. Dialogue with industry is routinely employed
and frequently leads to other refinements in our assess-
ment process.  In extreme cases where sufficient risk is
anticipated and uncertainty low, TSCA allows OPPT to
initiate actions to limit or ban the production or use of a
chemical.
     Most recently, where potential risk is indicated,
we engage industry in discussions designed to encour-
age voluntary  efforts to reduce or eliminate the risk.
These range from suggestions to recycle waste or seek
disposal practices other than  wastewater discharge to
intensive efforts to work with industry to redesign their
processes to eliminate problems upstream in the process
through chemical substitution or process change.
     As science advances our understanding of the fate
and transport processes of chemicals in the environment
and as new testing protocols are developed and standard-
ized, OPPT will embrace these new developments and,
where appropriate, will update its assessment process
accordingly.

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Proceedings
                                                                                  7-33
                                WATER RELEASE CYCLE
                                PART 4: FISH INGEST10N PDR'S
                                    DOES SAT
                                  REQUIRE (FISH)
                                 INGESTION PDR'S?
                   ISPMNIN
                EXPOSURE-BASED
                  (YX) REVIEW?
                                  IS MOLECULAR
                                  WEIGHT <1,000
                                    DALTONS?
                IS THE LOG OF BCF \ NO
               GREATER THAN 2 AND
                  LESS THAN 6?
                                                   NOTE ON CONCENTRATION
                                                     PAGE AND CONTINUE
IS BIODEGRADATION
RATED MONTHS OR
    LONGER?
                                                                       GO TO PART 5:
                 CALCULATE FISH
                  INGESTIONPDR
                                                      AQUATIC SPECIES
           NOTES:

           Calculate fish ingestion PDRs for releases to saline, tidal, or "still" waters
           using chronic mixing zone dilution factors when available.

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7-34
                               National Sediment Bioaccumulation Conference
   PDRf = C  * ING. * BCF * FQ * IE'6
   where
    Csw  = concentration in surface water (ug/1)
    ING{is = ingestion rate
    BCF = As calculated
    FQ  = frequency of exposure (days/year)
  Decisions
  •Testing
  •Dialogue
  •Voluntary Actions
  •TSCA Regulatory Actions

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                                                      National Sediment Bioaccumulation Conference
U.S.  EPA/OPPT and  Sediments:
Screening New  and Existing
Chemicals  for Potential
Environmental  Effects
Maurice Zeerrian, jerry Smrchek, Joseph Nabholz, and Donald Rodier
U.S. Environmental Protection Agency, Office of Pollution Prevention and Toxics, Washington, DC
Introduction

     Since 1976, the Office of Pollution Prevention and
     Toxics (OPPT, formerly the Office of Toxic
     Substances, OTS) at the U.S. Environmental Protec-
tion Agency (U.S. EPA), has been the office that is
responsible for assessing new and existing industrial
chemicals.  Prior to a reorganization within OPPT in
1997, the Environmental Effects Branch was the princi-
pal ecological group within that office,  hi the past, that
group had been concerned primarily about the ecological
effects  of industrial  chemicals in the water  column
(Zeeman and Gilford; 1993; Zeeman, 1995). However,
in the last five to ten years, there has been more and more
concern expressed about the possible effects of industrial
chemicals upon organisms in the sediments (Clements et
al., 1994; U.S. EPA, 1994; Nabholz et al., in press;
Smrchek et al., 1995;  Smrchek  and  Zeeman, 1997;
Zeeman, 1993; Zeeman  et al., 1995 and in press).
     Following is a brief introduction to the U.S. EPA,
the responsibilities of OPPT, especially the new and
existing chemical programs, and the kind of assessments
of these chemicals that are required under the Toxic
Substances Control Act (TSCA, the law under which
OTS [now OPPT] was formed in 1976). After this is a
description of how OPPT went  about requiring and
getting sediment toxicity testing  for a new industrial
chemical. And finally, an example is presented on how
OPPT developed a methodology that was used to Screen.
thousands of existing chemicals to try to develop a list of
higher priority chemicals for possible ecological testing
concerns, including possible sediment testing.
 Background

     For those who think of the U.S. EPA as some sort
 of monolithic agency, it is not. .It has about 17,000 to
 18,000 employees in numerous, programs and offices that
were each set up at different times and for different
purposes.  The Agency's various programs and offices
address responsibilities defined by several different envi-
ronmental laws that were passed over decades by differ-
ent legislative actions (Clean Air Act, Clean Water Act,
TSCA, etc.). The Offices in the U.S. EPA were organized
under broad legislative or environmental categories,'such
as Ak and Radiation, Water, Pesticides and Toxic Sub-
stances, Solid Waste and Emergency Response
(Superfund), and Research and Development. The fig:
ures on page 7-40 [U.S. EPA, OPPT] illustrate how,.the
U=S. EPA is organized, with OPPT residing  within the
Office of Prevention, Pesticides, and Toxic Substances
and the Environmental Effects Branch (EEB) residing
within OPPT.                            v-
     The ecological hazard and risk assessment func-
tions of that Branch used to be in the Health and Environ-
mental Review Division (HERD), and those functions
now reside in the newly formed Risk Assessment Divi-
sion (RAD, formed hi 1997 from the combination of the
staff and functions of'both HERD and the Chemical
Screening and Risk Assessment Division, CSRAD)- The
Economics, Exposure, and Technology Division (EETD)
contains the staff responsible for performing the engi-
neering and exposure assessment portions of the ecologi-
cal risk assessments that are done in OPPT.   .
     Why does/should OPPT care about bioaccumula-
tion, bioconcentration, and sediments? Because there are
industrial chemicals which adsorb strongly to sediments
and which are quite likely to also bioaccumulate or
bioconcentrate. When introduced into the food chain,
they could be detrimental not only for those organisms in
the sediment and water  column environments, but also
for humans.  TSCA was passed in 1976 to regulate
industrial chemicals, those chemicals used in commerce
that were not regulated  by other statutes, meaning that
they are not pesticides, pharmaceuticals, food additives,
or substances covered under other  laws (see figure on
page 7-41 [watering can]).  For example, industrial
                                            7-35

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7-36
                                                              National Sediment Bioaccumulation Conference
chemicals are substances like solvents, plastics, dyes,
adhesives, detergents, monomers, and polymers.  They
are chemicals that are widely used in commerce and are
around us all of the time. An independent calculation of
a partial sum of the 1989 production volumes of industrial
chemicals in the United States was around 6 trillion pounds
and it is undoubtedly even more now (Zeeman, 1997).
      One of the first activities after TSCA was passed in
1976 was to develop an inventory of the industrial chemi-
cals already in commerce in the U.S., the existing chemi-
cals  (see figure on page 7-42 [TSCA (Passed 1976)]).
After more than two years, over 60,000 chemicals were
identified as being in commerce and these became the
TSCA Inventory of existing chemicals. These chemicals
were basically grandfathered and the Agency was to look
at them for environmental concerns on an ongoing basis.
      By definition,  anything that was not an existing
chemical (i.e., on the Inventory) was a new industrial
chemical, and if anyone wanted to make it or import it into
the U.S., they would have to submit an application for its
assessment to the U.S. EPA. This assessment program is
not a registration program. Industry (the potential manu-
facturer or importer) submits a notice to OPPT called a
Premanufacture Notification (PMN).  OPPT  receives a
large number of these notices from industry each year (see
figure on page 7-42). They need to submit only the data
that they have or know about. They do not have to do any
testing. OPPT then has 90 days to make a decision based
on the available information or provide risk-based reasons
for not allowing it to be made or imported.
      The number of new chemicals that have gone
through this process in OPPT and have become existing
chemicals on the TSCA Inventory is currently around
15,000, which brings the Inventory total to about 75,000.
OTS/OPPT has received around 30,000 new chemical
notices from 1979 to 1996. From 1986 to the present, the
average has been about 2,300 new chemical notices  per
year. ThatisalmostSOnoticesperweekor lOperworkday
that are received and must be assessed hi a short lime frame.
      As mentioned earlier, OPPT does not receive a lot
of information. What is required to be submitted with
these PMNs?  Manufacturers must furnish information
such as the name of the chemical, the chemical structure,
the amount to be produced, disposal and human exposure
information, and any available test data since testing is
not required (see figure on page 7-43 [Required Submis-
sion]). Nevertheless, OPPT staff must make these risk-
based decisions in 90 days or the manufacturer will be
able  to make or import that chemical unless a risk-based
case is made by OPPT that they should not.
      The consistent experience of OPPT is that we sel-
dom receive the land of data that is needed for  ecological
risk assessment. About 95 percent of the PMNs received
by OPPT contain no ecotoxicity or environmental fate data
(Zeeman and Gilford, 1993; Zeeman, 1995; Zeeman etal.,
1995). The engineers and fate chemists in OPPT only get
physical, chemical, or environmental fate data about 1 to 5
percent of the time (Zeeman et al., 1993 and 1995). They
seldom get any bioaccumulation or bioconcentration data.
      A retrospective was performed on the ecotoxicity
data  received for new chemicals and it was found that
OPPT received ecotoxicity data less than five percent of
the tune, and the vast proportion of the data received was
acute toxicity data (Zeeman, 1995). That means that 19
out of 20 times no ecotoxicity data are provided for new
chemicals. Therefore,  OPPT has been forced to rely
heavily upon a modeling approach that uses structure-
activity and quantitative structure-activity relationships
(S AR/QS AR, or (Q)S AR) to estimate chemical properties,
chemical fate, and the ecotoxicity of a chemical to organ-
isms hi the aquatic environment (Clements, 1988 and
1994;Nabholzetal., 1993; Zeeman etal., 1993 and 1995).
     How does OPPT make decisions for ecological risk
assessment in the new chemical program? A number of
PMNs for new chemicals are received each week and they
are generally assessed in groups.  Within two or three
weeks of receipt of a group of PMNs, OPPT holds what
is called a FOCUS meeting (see figure on page 7-43
[Flow Chart]).  That is the first level of risk assessment
where a comparison is  made of the hazard assessments,
i.e., toxicity  profile, and the exposure assessments for
each chemical.   What is important for ecotoxicity is
whetherthe predicted environmental concentration (PEC,
from the exposure assessment) exceeds what is called the
concern concentration (CC, hazard assessment value(s)
adjusted for uncertainty).  In at least 90 percent of the
cases, the PEC is not exceeded  and a risk is not inferred.
These chemicals are dropped from further evaluation. In
the remaining five to ten percent of the cases, we proceed
to standard review or a request for testing and perhaps
through risk management, which can result in iterations
to obtain additional data (Wagner et al., 1995).
Sediment Assessment of an OPPT
New Chemical

     Portions of the following specific new chemical
sediment assessment example have been previously pre-
sented at a Society of Environmental Toxicology and
Chemistry (SETAC) national meeting (Zeeman, 1993),
and were also used as one case study of ecological risk
assessment methods used by the Agency (U.S. EPA,
1994). Further elaborations of this sediment assessment
will also be corning out soon as publications, hi both a
SETAC book on Uncertainty in Ecological Risk Assess-
ment (Nabholz et al., in press), andin a White House OSTP
publication on Ecological Risk Assessments in the Federal
Government (Zeeman et al., in press).
     The following describes the decision-making pro-
cess for a specific new chemical where OPFI was able to
get aquatic toxicity data, some generic and site-specific
data (so predictions could be made on whether or not it
would get into the sediments), and some sediment toxicity
data.  The figure on  page 7-44 shows the physical and
chemical properties of the chemical.  This new chemical
would be produced at the level of 100,000 kg per year, so
it is not a trivial compound in terms of how much is going
to be manufactured or imported. It is  an alkylated diphe-
nyl, and was classified into the SAR chemical class of
neutral organic chemicals.  OPPT is very comfortable in
using  its structure-activity relationship and quantitative

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Proceedings
                                                                                                    7-37
structure-activity relationship [(QJSARJ models for mak-
ing predictions on neutral organic chemicals (Clements,
1988 and 1994; Nabholz et al., 1993; Zeeman et al., 1993).
      B ased upon the chemical structure, an estimate was
made of the  Kow value (the octanol to water partition
coefficient, often used to estimate both ecotoxicity and
bioconcentration ability) and it was fairly high.   An
'estimate of the K^ value .(the water to organic carbon
partition coefficient, often used to estimate ability to
partition to sediments),was also made, and it was  rela-
tively high.  The water solubility was estimated to be
fairly low.  These are all strong indications that this
chemical will be very likely to distribute selectively.from
the water column and into the sediments.
      A hazard assessment (stressor-response) or toxic-
ity profile for this chemical was prepared (see the figure
on page  7-44).   OPPT's structure-activity methods
(Clements, 1988 and 1994; Nabholz et al., 1993)  were
used tq predict the acute and chronic aquatic toxicity and
to make a risk-based case'that eventually resulted in test
data. From this estimation information, OPPT inferred
that this new chemical would be a highly toxic compound
on a chronic exposure basis and that  it would be very
likely to be transported to sediments. A case was subse-
quently made through refined exposure assessment esti-
mates that sediment toxicity testing was needed, and it
 was eventually provided (see below).
      How well did the OPPT (Q)SAR estimates predict
 aquatic toxicity to fish and aquatic invertebrates? It was
 estimated that there would be no effects at .saturation for
 acute toxicities, which was confirmed by the testing.
 Such short-tenn tests do  not provide a long enough,
 exposure time to observe any acute effects. It was also
 estimated that the longer term chronic toxicity values
 would be somewhere in the low parts per billion  (ppb)
 range.  The test data subsequently received confirmed
 that the OPPT (Q)S ARs were very accurate with the actual
 chronic values of 13 ppb for fish and 7 ppb for daphnids
 being very close to the predicted ecotoxicity results.
      OPPT went through a number of iterations  to
 characterize the risk associated with this new chemical
 (see the figure on page 7-45 [Summary...]).  Initially it
 was thought that fish would be the most sensitive species.
 This did not turn out to be the case. However, the concern
 concentration (CC, the level in the water below which
 OPPT would not take any regulatory action) turned out to
 be  around 1 ppb  using either the fish  or the aquatic
 invertebrate toxicity data.  A risk-based pase was then
 made through our. initial and subsequent iterations as-
 sessing exposures.  Generic production data and some
 site-specific data were then obtained to improve the input
 for our exposure models.  The resulting estimates  of
 exposure were contrasted with  estimates of benthic tox-
 icity and the estimates of risk to organisms indicated that
 the manufacturer should consider chronic testing in sedi-
 ments. The manufacturer did perform a 28-day sediment
 .toxicity test with chironomids, which showed that there
 would be a moderate level of toxicity.
       What risk management decision was made about
 this new chemical? It was decided that this new chemical
 could be used only at the three  sites for which they
 provided specific information and that they should limit
the water column concentrations of the chemical to 1 ppb
or less.  OPPT also warned the manufacturer that this
chemical would, over the years, be likely to accumulate
in sediments.             ..   -
Existing Chemicals and Sediments

     The TSCA Inventory of existing chemicals con-
sists of about 75,000 chemicals that include polymers,
mixtures and salts, organometallics, and discrete organic
chemicals. A focus on discrete organics was used for an
approach  that was developed by OPPT for  screening
possible persistent bioaccumulative chemicals on the
TSCA Inventory.  Using this approach, thousands of
discrete existing chemicals were screened to identify
those that might have the chemical characteristics to be
persistent and bioaccumulate, and therefore, have poten-
tial for concern for selectively partitioning into sediments
(Zeeman etal., 1995).
     In. 1990, OPPT asked the EPA research laboratory
in Duluth, MN to screen the TSCA Inventory for discrete
organic chemicals which could have log Kow values
greater than 3.5. For this screening effort, the Duluth lab
created a database and estimated the log Kow (also known
as log P).  They started the screening process with about
20,000 chemicals and ended it with 6,668 chemicals with
log Kow values greater than 3.5 (see figure on page 7-45
 [Screening for Persistent Bioaccumiilators]).  The log
K  value of 3.5 was chosen as  a lower limit because it
represents a fish bioconcentration factor of about 250,
which was derived'using  an equation from research
performed at the Duluth lab (Veith and Kosian, 1982).
That limit approximately defines the subset of chemicals
 that should be cause for moderate or greater concern for
 bioconcentration in aquatic organisms such as fish.
      After this initial screening, OPPT continued with a
 series  of steps to reduce the list of chemicals to a more
 manageable size. The first step was to do an intersection
 between the Duluth database and the OPPT Chemical
 Update System (CUS) database, which includes about
 8,600  industrial chemicals that industry reports produc-
 ing in quantities of more than 10,000 pounds per site per,
 year (see  figure on page 7-46). The intersection resulted
 in  the identification of about 1,000 chemicals with this
 level of production and log Kow values greater than 3.5.
 The next levelof assessment was to consider chemicals
 with log Kow values between 3.5 (initially 4.3 was used)
 and 8.0 to focus on those chemicals that had the highest
 probability of causing  the most critical problems. Then
 persistence was evaluated using a degradation half-life of
 greater than 30 days as the threshold. This reduced the list
 to  about 80 chemicals. Finally, we considered chemicals
 that were being produced in quantities greater than 1
 million pounds per year. Applying this final criterion, a
 list of 34 chemicals resulted and these chemicals were
 examined further because they could be of concern for
 •persistence, bioaccumulation, and partitioning into sedi-
 ments (Zeeman et al.,  1995).
       What are the next steps? Obviously, one of the
 things that would be important is to obtain information on
 actual environmental loadings. It has been suggested that

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                                                               National Sediment Bioaccumulation Conference
 OPPT list some of these chemicals on the Toxics Release
 Inventory (TRI) to find out if those chemicals that were
 proposed to be only chemical intermediates were actually
 being released into the environment. When this list of 34
 chemicals was presented at a SETAC Workshop on the
 Environmental  Risk Assessment of Organochlorine
 Chemicals (Clements et al., 1994), one of the chemicals
 was supposed to be a chemical intermediate that would
 not be released into the envkonment. A researcher from
 Canada came up after the presentation and said that they
 had been finding this chemical in gull eggs along the
 Great Lakes.
      OPPT has also developed a sequence of tests that
 persistent bioaccumulative chemicals should be consid-
 ered for (see figure on page 7-46 [Potential Testing...]).
 First, we would like to determine whether or not these
 chemicals are likely to degrade in a sediment and water
 system. Chemicals that do not degrade should be evalu-
 ated further for bioconcentration in fish. Finally, for the
 chemicals whose  results  indicate that they  can
 bioconcentrate, then these chemicals need to be consid-
 ered  for testing to  estimate their chronic toxicity to
 aquatic and sediment dwelling organisms (e.g., see figure
 on page 7-47 [Preliminary Testing Scheme ...], adapted
 from Smrchek and Zeeman, 1997).
 Discussion and Summary

      Sediment issues for both new and existing indus-
 trial chemicals are becoming more and more important to
 OPPT (see figure on page 7-48 [OPPT Sediment Issues]).
 OPPT has asked for, received, and evaluated the results
 of sediment toxicity testing for both new and existing
 industrial chemicals (Smrchek et al., 1995; Smrchek and
 Zeeman, 1997).  It has also been interested in the sedi-
 ment toxicity test methods being developed nationally
 through the American Society for Testing and Materials
 (ASTM) and the U.S. EPA, and internationally through
 the Organization for Economic Cooperation and Devel-
 opment — the OECD (Ingersoll,  1995; OECD, 1997;
 Smrchek and Zeeman, 1997). OPPT also continues to
 have an interest in and support the  ongoing refinements
 in true chronic toxicity testing of sediment organisms,
 i.e., longer duration chronic testing, such as the 65-day
 life-cycle test recently developed for Chironomus tentans
 (Benoit et al., 1997).
      In summary, sediment issues have been a concern
 for both OPPT's new and existing industrial chemicals
 for almost a decade. OPPT receives notices iromindustry
 for about 2,300 new chemicals per year. Most of the time
 there  does not appear  to be a problem related to sedi-
 ments. But in those few cases where we are concerned
 that there could be such problems, OPPT has been able to
 either get results from sediment toxicity testing, or iden-
 tify ways to mitigate the concerns  for those chemicals.
 Sediment toxicity testing has also been requested and
 received for existing chemicals.  However, the current
 focus with existing chemicals is likely to continue the use
 of screening methods to identify those high production
volume chemicals that might have characteristics  that
 result hi concerns for partitioning into the sediments and
 having the potential to adversely affect organisms in the
 envkonment.
 Disclaimer

      This document has been reviewed by the U.S.
 EPA's Office of Pollution Prevention and Toxics, and
 approved for publication. Approval neither signifies that
 the contents  necessarily reflect the official views and
 policies of the Agency, nor does mention of trade names
 or commercial products, constitute endorsement or rec-
 ommendation of these products for use.
 References

 Benoit, D.A., P.L.  Sibley, J.L. Juenemann and G.T.
      Ankley. 1997. Chironomus tentans life-cycle test:
      Design and evaluation for use in assessing toxicity
      of contaminatedsediments. Environ. Toxicol. Chem.
      16(6): 1165-1176.
 Clements, R.G. (Ed.),   1994.  ECOSAR:   Computer
      program and user's guide for estimating  the
      ecotoxicity of industrial chemicals based on struc-
      ture activity relationships.  EPA-748-R-93-002.
      U.S. Environmental Protection Agency, Office of
      Pollution Prevention and Toxics, Washington, DC.
 Clements, R.G. (Ed.).   1988.  Estimating toxicity of
      industrial chemicals to aquatic  organisms using
      structure-activity  relationships.  EPA-560-6-88-
      001. U.S. Environmental  Protection Agency, Of-
      fice of Toxic Substances, Health and Environmen-
      tal Review Division, Environmental Effects Branch,
      Washington, DC.  286pp.
 Clements, R.G., R.S. Boethling, M. Zeeman and C.M.
      Auer. 1994. Persistent bioaccumulative chemicals:
      Screening the TSCA Inventory. Handout for pre-
      sentation at the SETAC Foundation Workshop on
      the Environmental  Risk  Assessment for Orga-
      nochlorine Chemicals, Alliston, Ontario, Canada.
      July 24-29, 1994.  13pp.
 Ingersoll, C.G. 1995. Sediment tests. Pp. 231-255, Chap-
      ter 8 In: Fundamentals  of aquatic toxicology:
      Effects,  environmental fate, and risk assessment,
      2ndEd., G. Rand, Ed., Taylor & Francis, Washing-
      ton, DC.
 Nabholz, J.V., R.G. Clements, M. Zeeman, K.C. Osborn
      and R. Wedge. 1993. Validation of structure activ- ,
      ity relationships used by the USEPA's Office of
      Pollution Prevention and Toxics for the envkon-
      mental hazard assessment  of industrial chemicals.
      Pp. 571-^590 In: Environmental toxicology and risk
      assessment,  2nd  Vol. ASTM STP  1216. J.W'.
      Gorsuch, F.J.  Dwyer, C.G. Ingersoll and T.W.
     LaPoint, Eds.,  American Society for Testing and
     Materials, Philadelphia, PA.
Nabholz, J.V., M. Zeeman and  D.  Rodier. Case study
     no. 3: Dealing with uncertainty  when assessing
     ecological risks of a new chemical under the Toxic

-------
Proceedings
                                                                                                7-39
     Substances Control Act.  In: Uncertainty in eco-,
     logical risk assessment. W. Warren-Hicks and D.
     Moore, Eds., SETAC Press, Pensacola,  FL. (In
     press).
OECD. 1997. OECD guideline for testing of chemicals:
     Proposal for toxicity test with Chironomidae. Or-
     ganization for Economic Cooperation and Devel-
     opment, Paris. (May 1997 Draft).   .   '
Smrchek,  J.C.,  M. Zeeman and R.  Clements. 1995.
     Ecotoxicity and the assessment of chemicals at the
     USEPA/OPPT: Current activities and future needs.
     Pp. 127-158 In: Making environment science. J.R.
     Pratt, N. Bowers and J.R. Stauffer, Eds., Ecoprint,
     Portland, OR.
Smrchek, J.C., and M. Zeeman. 1997. Assessing risks to
     ecological systems from' chemicals.  Pp. 24-90,
     Chapter 3 In: Handbook of environmental risk
     assessment  and management. P. Calow,  Ed.,
     Blackwell Science Ltd., London.
U.S. EPA. 1994. Assessing the ecological risks of a new  ,
     chemical under the Toxic Substance Control Act.
     Pp. 1-1 to 1-35 In: A review of ecological assess-
     ment case studies from a risk assessment perspec-
     tive,  Vol. II. EPA/630/R-94/003. U.S. Environ-
     mental Protection Agency, Office of .Research and
     Development, Washington, DC.
Veith, G.D., andP. Kosian. 1982. Estimating bi'oconcen-
     tration potential from octanol/water partition coef-
     ficients.Pp. 119-132In: Physical behaviorof'PCB's
     in the Great Lakes. D. MacKay et al., Eds., Ann
     Arbor Science, Ann Arbor, MI.
Wagner, P.M., J.V. Nabholz and R.J. Kent. 1995. The
     new chemicals process, at the Environmental Pro-
     tection Agency (EPA): Structure-activity relation-
      ships for hazard indentification and risk assess-
     ment. Toxicol. Lett. 79: 67-73.
Zeeman,M. 1993. Assessing the ecological risks of anew
      chemical   under  the   Toxic  Substance
      Control Act (TSCA). Invited presentation at the
      SETAC Symposium on the EPA Framework For
      Ecological Risk Assessment, SETAC 14th Annual
      Meeting, Houston, TX. November 14-18, 1993.
Zeeman, M.  1995. Ecotoxicity testing and estimation
      methods developed under Section  5 of the Toxic
     • Substances  Control Act (TSCA). Pp..703-715,
      Chapter 23  In: Fundamentals of aquatic toxicol-
      ogy: Effects, environmental fate, and risk assess-
      ment, 2nd Ed. G. Rand, Ed.,  Taylor  & Francis,
      Washington, DC.
 Zeeman, M. 1997. Aquatic toxicology and ecological
      risk  assessment: US-EPA/OPPT perspective and
      OECD interactions. Pp. 89-108 In: Ecotoxicology:
      Responses,  biomarkers, and risk assessment. J.T.
      Zelikoff, J. Lynch and  J.  Schepers, Eds.,
      Organization for Economic,  Cooperation and
      Development, Paris (published for the OECD by
      SOS Publications, Fair Haven,  NJ).
 Zeeman,  M., and J. Gilford.  1993. Ecological hazard
      evaluation and risk assessment under EPA's Toxic
      Substances  Control Act (TSCA): An introduction..
      Pp. 7-21 In: Environmental toxicology and risk
    • assessment, 1st Vol. ASTM STP 1179. W. Landis,
    . J. Hughes and M. Lewis, Eds., American Society
     for Testing and'Materials, Philadelphia, PA.
Zeeman, M., J.V. Nabholz andR.G. Clements. 1993. The
     development of SAR/QSAR for use under EPA's
     Toxic Substances Control Act (TSCA): An intro-
     duction. Pp. 523-539 In: Environmental toxicol-
     ogy and risk assessment, 2nd  Vol. ASTM STP
     1216. J.W.  Gorsuch, F.J. Dwyer, C.G.. Ingersoll
     and T.W. LaPoint, Eds., .American Society for
     Testing and Materials, Philadelphia, PA.
Zeeman, M., C.M. Auer, R.G. Clements, JiV. Nabholz
   .and R.S. Boethling. 1995.  U.S. EPA regulatory
     perspectives on the use of QSAR for new and
     existing chemical evaluations.  SAR & QSAR in
     Environ. Res. 3: 179-201.
Zeeman, M., D. Rodier, J.V. Nabholz, D:G. Lynch, G.J.
     Macek, S.M. Sherlock and R. Wright. Ecological
     risks of new'industrial chemicals under TSCA. In:
     Ecological risk assessment in the Federal Govern-
     ment. White House Office of Science and Technol-
     ogy Policy (OSTP), Committee on Environment
     and Natural Resources (CENR), Washington, DC.
     (In press).
Graphic References

Clements, R.G., R.S. Boethling, M. Zeeman and C.M.
      Auer.  1994. Persistent bioaccumulative chemi-
      cals: Screening the TSCA Inventory. Handout for
      presentation at the SETAC Foundation Workshop
      on the Environmental Risk Assessment for Orga-
      riochlorine Chemicals, Alliston, Ontario, Canada.
      July 24-29,1994. 13 pp.  ,
Nabholz, J.V., M. Zeeman and D. Rodier. The use of
      assessment (uncertainty) factors in estimating the ,
      ecological risks of a new chemical under the Toxic
      Substances Control Act. Invited submission for the
      Proceedings of the SETAC Foundation Workshop
      on Uncertainty Analysis in  Ecological  Risk As-
      sessment, Pellston, MI. August 23-28,1995.28pp.
      + figures/tables (Submitted).
U.S. EPA. 1994. Assessing the ecological,risks of anew
   .   chemical under the Toxic Substance Control Act.
      Pp.  1-1 to 1-35 In: A review of ecological assess-
      ment case studies from a risk assessment perspec-
      tive, Vol. II. EPA/630/R-94/003. U.S.  Environ-
      mental Protection Agency, Office of Research and
      Development, Washington, DC.
Zeeman, M. 1993. Assessing the ecological risks of anew
      chemical under .the Toxic Substance Control Act
      (TSCA). Invited presentation at the SETAC Sym-
      posium on the EPA Framework .For Ecological
      Risk Assessment, SETAC 14th Annual Meeting,
      Houston, TX. November 14-18,  1993.
 Zeeman, M., C.M. Auer, R.G. Clements, J.V. Nabholz
      and R.S. Boethling. 1995. U.S. EPA regulatory
      perspectives  on the use of QSAR for new  and
      existing chemical evaluations.  SAR &  QSAR in
      Environ. Res. 3: 179-201.

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7-40
National Sediment Bioaccumulation Conference
               U.S. Environmental Protection Agency




1
Assistant Administrator
for Administration and
Resources Management


1
Assistant Administrator
for International Activities

1
Assistant Administrator for
Prevention, Pesticides, and
Toxic Substances






ADMINISTRATOR
DEPUTY ADMINISTRATOR



Assistant Administrator
for Enforcement







Inspector General

1
Assistant Administrator for
Air and Radiation















General Counsel



1



Science Advisory
Board

1


Assistant Administrator
for Policy, Planning,
and Evaluation



Assistant Administrator for
Research and Development









1
Assistant Administrator
for Water
Regions


Assistant Administrator for
Solid Waste and Emergency
Response

                             Office of Pollution
                           Prevention and Toxics

1
TSCA
Interagency
Testing
Committee


Office Director
1
Deputy Office Director


1
Office of
Program
Manage-
ment and
Evaluation

Chemical
Control
Division
Chemical
Screening &
Risk
Assessment
Division
Health &
Environ-
mental
Review
Division

Economics,
Exposure,
and
Technology
Division

Information
Manage-
ment
Division
Environ-
mental
Assistance
Division
Chemical
Manage-
ment
Division
Pollution
Prevention
Division
                 Environmental Effects Branch
                   Health Effects Branch
                    Senior Science Staff

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Proceedings
                                     7-41
    TSCA: The Gap Filling Law
                  Toxic Substances Control Act

-------
7-42
                                National Sediment Bioaccumulation Conference
          TSCA (Passed 1976)
  Existing Chemicals Inventory (1979)
   ~ 60,000 Chemicals (Grandfathered)
   ~ 10,000 Chemicals Added (by 1991)
  New Chemicals (PMN'sJi
   Chemical PMN's ~ 2,500/yr (currently)
   Genetically Engineered Microbe PMN's
   Submit Extant Data Only
   90-Day Clock (after submit PMN)
     [§8, etc.]
     [§5]
            PMNs Received/Fiscal Year
              and FY90-FY95 Budget
                       $6.6M (FY90)
                       FTE:168
          3000

          2500

          2000
          1000
           0
                         r
                                       D Number of
                                        Submissions
$2.6M (FY95)
FTE: 114
            79 81  83  85  87  89  91  93 95

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Proceedings
                                                        7-43
              Required Submission in
               New Chemical  Notice

              Chemical Name
              Chemical Structure
              Production Volume
              Uses and Disposal Methods
              Human Exposure Estimates
              Any Extant Test Data
              (Testing Not Required)
         P
         B
         LU
         o
         t
         a
               Flow Chart and Decision Criteria for
               the Ecological Risk Assessment '
               of a PMN Substance
                    STEP 1. FOCUS MEETING
                      Worst Case Analysis
                    Does the PEC exceed the CC?
                                    No
                            Yes
   STEP 2. STANDARD REVIEW
   Obtain More Information/Data
    A More In-Depth Analysis
                 Is the CC exceeded 20 or more
                 days out of one year?
                                   No
                            Yes
STEP 3. RISK MANAGEMENT OPTIONS
 Allow Manufacture
• Controls Pending Testing
 Significant New Use Rule (SNUR)
 Ban
                        DROP or Issue
                        a Significant New
                        Use Rule (SNUR).

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7-44
National Sediment Bioaccumulation Conference
          PHYSICAL/CHEMICAL PROPERTIES
                  OF PMN SUBSTANCE
Chemical Class: Neutral Organic
Chemical Name & Structure: CBI
Physical State: Liquid
Molecular Weight: 232
Log Kow: 6.7 [Via CLOGP program (Leo and Weininger, 1985)]
Log Koc: 6.56 [Via regression equation (Karickhoff et al., 1979)]
Water Solubility: 0.30 mg/L [Measured]
Vapor Pressure: < 0.001 Torr @ 20° C.
                 PMN SUBSTANCE
       STRESSOR-RESPONSE PROFILE
                 QSAR ESTIMATED TOXICITY
                      (Clements, 1988)
         Fish 96 hr. LC: No effects at saturation
                    50
         Daphnid 48 hr. LC50: No effects at saturation
         Green Algae 96 hr. EC50: No effects at saturation
         Fish Chronic Value: 0.002 mg/L
         Daphnid Chronic Value: 0.004 mg/L
         Algal NOEC: No effects at saturation
               ACTUAL MEASURED TQXICITY
    Fish Acute Test (FHM; 96 hr): No effects at saturation
    Fish Early Life Stage Test (FHM; 31 -day):
         Chronic Value (growth, mean wet weight): 0.013 mg/L
         Chronic Value (survival, growth (length)): 0.061 mg/L
    Daphnid Reproduction Test (D. magna; 21 -day):
         Chronic Value (survival, growth, reprod.): 0.007 mg/L

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Proceed\ngs
                                                                 7-4-5
                  Summary of Five Risk
               Characterization Iterations
ITERATION
1
2
3
4
5
ESTIMATES / ASSUMPTIONS
Fish are the most sensitive species. CC = 1 ug/L. PMN
substance mixes instantaneously in water. No losses.
Actual test data for Daphnids still yield a CC of 1 ug/L.
Determine how often this concentration is exceeded
using PDM3.
Estimate risk to benthic organisms using Daphnid
chronic value and mitigation by organic matter.
EXAMS II used to estimate concentrations.
Site specific data obtained on use and disposal.
EXAMS II rerun with new data.
Actual test data for benthic organisms obtained.
UNCERTAINTY
Worst case. Actual test
data not available.
Worst case. Other species
may be more sensitive.
Generic production sites.
Actual data for benthic
invertebrates not available.
Estimated toxicity for
benthic invertebrates.
Best estimates for identified
sites. May not hold for
other sites or uses.
             Screening for Persistent Bioaccumulators
                             TSCA INVENTORY
                              Estimate Log P
                             Using CLOGP 3.3
                                        LogP Not Calculated
                                        Missing Fragment(s)
                             Potential Candidates for
                            Persistent Bioaccumulators
                              Duluth Database
                              6668 Chemicals
            Initial screening process performed by ERL, Duluth to
            identify potential bioconcentrators.

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7-46
   National Sediment Bioaccumulation Conference
                 DULUTH DATABASE
                 6668 CHEMICALS
  CUS DATABASE
  8592 CHEMICALS
              LOG P GREATER THAN 4.3
                 744 CHEMICALS
 LOG P LESS THAN 4.3
   290 CHEMICALS
                 LOG P 4.3 TO 8.0
                 495 CHEMICALS
LOG P GREATER THAN 8.0
   249 CHEMICALS
               M.W. LESS THAN 600
                 473 CHEMICALS
M.W. GREATER THAN 600
   22 CHEMICALS
                                       HALOGENS (48)
                          EVALUATE PERSISTENCE
              EVALUATION COMPLETED
                 48 CHEMICALS
EVALUATION COMPLETED
   32 CHEMICALS
                          EST. HALF-LIFE >30 DAYS
                            80 CHEMICALS
        Application of criteria to screen the Duluth database for
        potential bioaccumulators
              POTENTIAL TESTING OF
       PERSISTENT BIOACCUMULATORS
              Sediment/Water Biodegradation
              •  Fish Bioconcentration
                 • Chronic Aquatic Toxicity
                   • Chronic Sediment Toxicity

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Proceedings
                                                                      7-47
              Preliminary Testing Scheme For
               Determining Sediment Effects
                                  TIERI
                            TOXICITY TESTS
            Fish Acute
             Toxicity

               I  •
 Daphnid Acute   Algal
 (Pore waters/  (Pore waters/
  elutriates)    elutriates)
   Toxicity .     Toxicity
         Amphipod
          Sediment
           Acute
          Toxicity
            I
                                  TIER II
                            TOXICITY TESTS
          Chironomid
           Sediment
          Subchronic
           Toxicity
         ;	I
              Fish
             Chronic
             Toxicity

              •  I	
          Invertebrate/
          Fish Full Life
          Cycle Chronic
            Toxicity
                I  	
   Daphnid     Higher    Amphipod   Chironomid
   Chronic      Plant      Chronic     Chronic
   Toxicity     Toxicity     Toxicity    (emergence)
                                  TIER III
                             TOXICITY TESTS
    Fish
Bioconcentration
Higher
 Plant
Uptake
Invertebrate
 Sediment
 Chronic
 Toxicity
  Invertebrate
 Lumbriculus.
Macoma. Nereis
   Sediment
Bioaccumulation
	I
                                 TIER IV
                              FIELD TESTS
                   (Adapted from Smrchek & Zeeman, 1997)

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7-48
                      National Sediment Bioaccumulatlon Conference
    OPPT SEDIMENT ISSUES
NEW CHEMICALS
  •  90 % Minimum Risks
  •  5-10 % Further Review
  •  PMN Case Study — Sediments
    [EPA/630/R-94/003]

EXISTING CHEMICALS
  •  ITC Recommendations [e.g. OMCTS]
  •  Screening Methods [e.g., PB's see
    SAR/QSAR Env. Res. 3:179-201; 1995]
   'The work will teach
      you how to do it."
        (Estonian Proverb)

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                                                            National Sediment Bioaccumulation Conference
 Dredged Material
 Management  Program
 Craig Vogt
 U.S. Environmental Protection Agency, Office of Wetlands, Oceans, and Watersheds,
 Washington, DC
     The  Dredged Material Management Program is
     jointly managed by EPA and the U.S. Army Corps
     of Engineers. Today, I  want to give you a brief
overview of the pertinent statutes, regulations, and guide-
lines and how we implement  the program, including a
discussion about testing, particularly what tests we do
and how we make decisions based on the results.
     In dredged material  management, there are two
statutes that we must follow:  the Marine Protection,
Research, and Sanctuaries Act (MPRSA) and the Clean
Water Act (CWA). There  is some overlap between the
statutes, but generally speaking, the MPRSA  applies to
ocean waters and the. CWA applies to inland waters,
including estuaries and fresh  waters.  Related to this
activity is the London Convention of 1972 which is the
international.treaty on ocean dumping.  We implement
the terms of the London Convention through the MPRSA,
which is commonly referred to as the Ocean Dumping
Act.  The London Convention essentially sets forth a
permitting regime that includes a black list and a gray list.
The black list specifies chemicals that cannot be dumped
into the ocean unless they are present only as  trace
contaminants or they are  rapidly rendered  harmless;
examples include mercury,  cadmium, crude oil, organo-
halogens, and chemical or biological warfare agents.
The gray list includes a group of chemical contaminants
that require a permit if they are present in dredged
material (or any other material) that  is proposed to be
dumped into the ocean.
     For dredged material management, there are spe-
cific regulations and guidelines on how to make deci-
sions regarding  issuance of a permit for disposal of
dredged material in ocean or fresh/estuarine waters, and
they include consideration of acute and chronic toxicity,
including bioaccumulation;  Under the two statutes, EPA
is  charged with developing the environmental criteria
that form the basis for judgements on the acceptability of
dredged material disposal  in the  aquatic environment.
The Corps of Engineers is  the permitting authority and
the Corps determines whether or not the dredged material
meets the environmental criteria.  EPA has a review and
concurrence role in the permit issuance process.   For
ocean  waters, EPA has site designation responsibility
which means that we designate an actual site in the ocean
where dredged material can be disposed.
      The statutes and regulations require that dumping
 of dredged material will not unreasonably degrade or
 endanger human health or the environment.  Results of
 biological effects-based testing (i.e., bioassays) are the
 basis  for decision-making in the Dredged Material
 Program. We consider both acute and chronic toxicity.
 EPA and the Corps jointly develop the testing procedures
 to assess the potential risks to human  health and the
 environment of disposal of dredged material in aquatic
 environments. Testing manuals have been developed by
 the Corps and EPA; the manual for ocean disposal is
 commonly referred to  as the Green Book.  The Inland
 Testing Manual is a companion document currently in
 draft form; the final document should be available soon.
 Methods are included  in the testing manuals for acute
• toxicity and bioaccumulation.
      The overall framework that is used in the Dredged
 Material Management Program to make determinations
 on acceptability for aquatic disposal is provided below.
 We use a reference site approach. This approach has
 already been described by Norm Rubinstein in an earlier
 session at this conference; briefly, we compare the results
 of testing of the dredged material to those of a reference
 site. For acute toxicity, we use a criterion for decision-
 making of an increase of 20 percent acute toxicity due to
 the dredged material compared to the reference material.
 For bioaccumulation,  we  proceed through a logical
 progression of evaluations to determine the acceptability
 of dredged material for aquatic disposal. One tool that is
 available are U.S. Food and Drug Administration (FDA)
 action levels.   If contaminant  levels in the dredged
 material exceed the FDA action level, then the material
 would fail the criteria for open water disposal.  If con-
 taminant levels in the dredged material do not exceed the
 FDA action level, then further evaluation is required.
 The dredged material is then evaluated for additional
 factors, including  such factors as how many contami-
 nants  have  bioaccumulated, the magnitude of that
 bioaccumulation, the lexicological importance of the
 contaminants,  and the potential  for biomagnification.
 Evaluations.of potential impacts upon both human and
 ecological health are carried out.
     Progress is being made in regard to assessing the
 results of bioaccumulation tests to determine the accept-
 ability for dredged material aquatic disposal.  However,
                                               7-49

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7-50
                                                             National Sediment Bioaccumulation Conference
there is a need for better information and data, such as
has been presented in this conference. The Corps of
Engineers and EPA sponsored a joint workshop a year
ago on interpreting the consequences of bioaccumulation.
Those proceedings should be out soon.  The Corps of
Engineers is also developing a bioaccumulation database
that should be on the Internet in the next few months.
EPA is contributing to that database. And finally, EPA
has worked jointly with the Corps of Engineers to
develop a  manual  for  making  better decisions  on
bioaccumulation. This manual will define a framework
for decision-making focusing on a much more formal-
ized risk assessment and risk  management approach
for dredged material containing bioaccumulative
contaminants. EPA and the Corps of Engineers are also
collaborating on development of a chronic test using an
amphipod with  survival,  growth,  and reproduction
as endpoints.
     In summary, we do need more information. I think
this conference will help in pulling together important
information.

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                                                            National Sediment Bioaccumulation Conference
 Dredged  Material  Management:
 A Regional  Perspective
 Mario Del Vicario
 U.S. Environmental Protection Agency Region 2, New York, New York
I   would like to focus my talk on problems we are having
   with the dredged material program in the New York/
   New Jersey area, particularly for the marine environ-
ment.  I will be describing issues related to dredged
material disposal at the ocean disposal site (known as the
Mud Dump Site) located about 6 miles east of Sandy
Hook, NJ. We are devoting considerable attention to this
site because of its close proximity to a densely populated
coastal area. -The annual volume of dredged materials
deposited at this  site typically ranges from four to six
million cubic yards.
     Dredged material in our program is classified into
three categories for ocean disposal. This regional classi-
fication scheme is based on requirements in the testing
manual for Section 103 of the Marine Protection, Re-
search, and Sanctuaries Act  (MPRSA).   This testing
manual, which was developed jointly by the U.S. Envi-
ronmental Protection Agency (EPA) and the U.S. Army
Corps of Engineers (USAGE) in 1977, is commonly
referred to as the Green Book. We designate dredged
material that is suitable for unrestricted ocean disposal as
category  1 material. This material does not show acute
toxicity or potential bioaccumulation. Category 2 mate-
rial does  not show acute toxicity, but does show some '
potential  for bioaccumulation. This material requires
capping with either category 1 material or sand for ocean
disposal.  Category 3 material shows both acute toxicity
and bioaccumulation potential. There can be no disposal
of category 3 material in the ocean environment.
     In  addition to  testing for toxicity and  bio-
accumulation, we analyze bulk sediments to. help us
determine which chemicals we need to test for bioaccu-
mulation. Based on the 1977 Green Book testing require-
ments, dredged material in our program was generally
classified as about 95 percent category 1 material, 5 per-
cent category 2 material, and less than 1 percent category
3 material! Before 1991, we also had matrix values for
mercury,  cadmium, PCBs, and DDTs that delineated
category,! and category 2 materials^ Material that ex-
ceeded the matrix values was classified as category  2
rather than category 1.  During this same period, toxicity
test results and U.S. Food and Drug Administration (FDA)
action levels delineated category 3 material.
     The, Green  Book was  revised in 1991.  These
revisions  contained changes in testing, including more
 specificity for bioaccumulation testing and identification
 of more sensitive test species for toxicity testing. The new.
 Green Book requirements had a dramatic impact on the
 dredged material program hi our region.  Based on the
 revised testing requirements, the distribution of material
 in each category changed from 95 percent to 40 percentin
 category 1, from 5 percent to 30 percent in category 2, and
 from less than 1 percent to 30 percent in category 3. We
 are still trying to address difficulties related to these
 changes, including the substantial increase in the cost of
 disposing of much larger quantities  of category 2 and
 3 material and the lack of availability of disposal sites for
 category 3 material.  Today an annual volume  of
 1.7 million cubic yards of material is not being dredged
 because disposal sites are hot available.
      One cost concern is. the cost of testing. We have
 seen the cost go up dramatically in recent years. It is fairly
 typical for someone that needs to dredge in the New York
 area to spend $80,000 to $150,000 to determine whether
 the material would be classified as category 1,2, or 3. That
 price range covers the cost of sediment chemistry and
 conducting bioassays to generate toxicity information.
 We have tried to minimize the need to do extensive
 testing, but we still must meet the requirements in the
 Green Book and the program regulations.  As more
 information becomes available linking sediment chemis-
 try to biological impacts, We hope that application of this
 information will reduce the cost of testing.
      Another cost concern is the cost of disposal. Before
 1991, the cost of disposing unrestricted dredged material
"at the ocean disposal site was $5.00 per cubic yard. The
 current cost of disposing category  2 dredged material at
 this site, including capping, ranges from $30.00 to $50.00
 per cubic yard.  The cost differences span an order of
 magnitude.  Disposal costs are even greater for dredged
 material at sites that  serve as alternatives to ocean dis-
 posal. The cost  of disposing at these:alternative'sites
 currently ranges between $60.00 and  $120.00 per cubic
 yard.
     Increasing costs, coupled with the shift in classifica-
 tion of dredged material to categories with more disposal
 restrictions, could pose a difficult dilemma for maintain-
 ing the viability of the ports in the New York/ New Jersey
 Harbor area and the regional economy tied to those port
 activities. We are working on a regional level to develop
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                                                               National Sediment Bioaccumulation Conference
contaminant guidance levels that we can use to make
decisions on a case-by-case basis.  Alex Lechich de-
scribed our regional process in bis earlier presentation at
this conference. However rigorous our process is for
defining values to categorize dredged material, we can
expect to be challenged. There is too much at stake in this
area. All the individual aspects of our work will likely be
questioned and we need to be prepared to meet mat
challenge. The work we are doing, including derivation
of biota-sediment accumulation factors (BSAFs) and an
impact analysis on ecological and human health, must be
sound and scientifically defensible.
     You can help us meet that challenge.  We need
sound science to support our process in developing re-
gional guidance levels and the decision-making that will
follow from that process. We were very fortunate to have
Bob Huggett and several of his senior scientists meet with
us about our dredging issues and discuss how to address
them. We hope to see national guidance levels developed,
but will continue with our regional work in the interim. I
have been  hearing  timelines mentioned like 5 years,
10 years, or even longer. But I appeal to you to make the
progress we need in this area sooner, because the chal-
lenge is already there for us.   ,

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                                                          National Sediment Bioaccumulation Conference
  •Day Three:  September 13;  1996
 Session  Seven:
 Questions and Answers
 A
fter each session, there was an opportunity for
questions and answers and group discussions per-
.taining to the speakers' presentations.
 Q (Susan Svirsky, U.S. EPA Region 1):  I would just
 like to make a couple of clarifying points, and perhaps
 the last one is a question for Larry Zaragoza to see if
 you have experienced what we have.  First, in some
 parts of the country, we are doing ecorisk assessments
 with more frequency  than human health risk assess-
 ments at this point because of the tailing off of issues
' related to human health. Now we are dealing with the
 tougher issues,  and that leads into my second point
 concerning your slide. The number of sediment clean-
 ups (14) is extremely misleading  in that we have
 practiced avoidance behavior and put off the sediment
 cleanups to subsequent operable units for the sites.
 We are just now getting into the really tough problems,
 and we are going to be  having a hug-e number of
 sediment-driven operable units to work with.  I was
 wondering  if that is your understanding as well?

 Larry Zaragoza:

 Our analysis included over 200 sites from all over the
 country. I would need to go back and see how many of
 those sites had final records of decision (RODs) at the
 time this analysis was done.  I agree with you that
 basically we have found sediments to be very difficult
 to deal with.- I have reviewed a lot of RODs and there
 are a number of them that have not yet dealt with  the
 sediment issues because they were waiting for techno-
 logical or other reasons. I am also encouraged by  the
 comments you made that we are having more ecorisk
 assessments done. I think that is something probably
 everyone in this room is glad to hear.

 Betsy Southerland:

 Senator Levin is planning some amendments to  the
 Superfund bill directed at encouraging more contami-
 nated sediment cleanups.  We do not know what  the
 bill is going to look like, because they  have not  re-
 leased the language yet.  I know that was one of  his
 prime concerns since he is from the Great Lakes area.
Q (Nelson Thomas, U.S. EPA, Office of Research and
Development): Jim, 5 to 8 years ago your office was a
leader in trying to deal  with the whole  subject of
bioaccumulation. Now you say it is going to be 5 or 10
years before you can factor this information into the
permitting process.  Why do we need this 10- to 15-
year delay to account for bioaccumulation in NPDES
permits?                     ,

Jim Pendergast:

About six winters ago, I visited Nelson in Duluth to work
with him to develop guidance on how to bring bioaccu-
mulation into NPDES decisions. We can do things today
if we are talking about bioaccumulation in the aqueous
phase.  When I was  talking about 5 to 10 years in the
future, I was referring to sediment bioaccumulation.
What we have learned since that day in Duluth is that the
fate and transport of sediments is a lot more difficult to
grapple with than we originally thought. Back then we
thought that it would work to add sediment into the model
using a steady-state approach. When we did field studies
in Lake Charles (LA) and the Blackstone River (MA and
RI), the  steady-state approach worked fine in the water
column, but it did not work well in the sediment. Since
then, we have learned from the modelers that the steady-
state models do not deal well with sediments.  Models for
sediments must account for flooding events and other
dynamic processes. That is the technology we need to
develop. I think it is  going to take 5 to 10 years to work
that out in a way that is simple enough to put into a mass
production process like NPDES permitting.

Q (Nelson Thomas): So, you do not see anything in the
interim that will be able to handle bioaccumulation in
the NPDES permits?

Jim Pendergast:

Not for the sediments.

Q (Phillip Rury, Arthur D. Little, Inc.): Tom, has EPA
considered shifting this 90-day risk assessment burden
to industry, which would put EPA in more of a review
capacity? This might be a little more manageable.
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                                                              National Sediment Bioaccumulation Conference
Tom Murray:

Yes, we are actually involved in that right now. One
of the things we have been trying to do over the last few
years, with some degree of success, is to make the various
tools that we use available to industry. We recently did
a pilot project with Kodak where we provided them with
about six  different modeling packages.  They applied
them within their own business to make decisions about
what the environmental Impacts might be for the chemi-
cals they use in their photographic processes. They felt
that the pilot was a great success since the models allowed
them to make their own decisions. They do not have to
come into our complex program and wait for a decision.
We are going through a process this year and next year to
build on that experience and distribute information to
other chemical manufacturers.  We will probably work
with the Chemical Manufacturers Association and other
trade associations to see about  getting more people in-
volved with this.  We are also going through a data
integration process within  OPPT to bring together the
arsenal of tools that we use and create acontext to educate
a broader audience on how we use them. We are planning
to make this information available on the Internet so
people can  access it,  learn how to  use  it, and begin
applying the models themselves.

Maurice Zeeman:

The 90-day time frame is statutory.  It is not something
that we chose. Nevertheless, we have been very creative
in doing things to meet that deadline.   For example,
because our group relies so heavily on structure-activity
relationships (SARs), we have developed a PC program
called ECOS AR that is available from the National Cen-
ter for Environmental Publication and Information
(NCEPI) in Cincinnati (OH). If you know the chemical
class of a compound, it will predict the toxicity of that
compound and produce a hazard profile. The program is
a tool for making predictions, not a data base.  We have
made this program available to industry and they use it to
determine whether or not they should submit a chemical.
If they find out that a substance is going to be really toxic
on a chronic basis, then they might decide not to submit
it We have already started to see safer chemicals being
submitted to us from that application.

Q (MickDeGraeve, Great Lakes Environmental Center):
Craig, how do you determine what types of bioaccum-
ulative chemicals might potentially be present in dredged
material?  What process do you use?

Craig Vogt:

We go out and take a sample of dredged material, run a
bulk chemistry analysis on it,  determine what kind of
chemical contaminants are there, and then take the next
step of looking at the bioaccumulation.

Q (G.  Fred Lee, G. Fred Lee & Associates):  The Mud
Dump Site has been studied a number of times.  The last
I heard, they have not found a problem after dumping
from 5 to 10 million cubic yards a year for how many
years?

Mario Del Vicario:

The Mud Dump Site has been an area for historical use
since the 1930s. We have measured background levels
for sediment chemistry and tissue analysis, both in the
site and in areas outside the site mat are not influenced by
disposal in the site. What we have found is certain levels
of contamination  out there. Do we find terrible things
going on? As far  as bioaccumulation measurements go,
a lot of the sediment and the tissue data are not at levels
that you would say are startling, considering that a lot of
material  went out years ago without our having the
knowledge that contaminants were even in the material.
Dioxin is the classic; example.  Millions of cubic yards of
dioxin-contaminated material  went out to that disposal
site in the past. We do not see tremendous accumulations
out there in worm, lobster, or fish tissue.  We do see
accumulations, but not what you would expect based on
what you would see if you  went to our Superfund site.
What we have seen when we go out to areas surrounding
the Mud Dump Site are places where toxicity test results,
particularly for amphipods, indicate that Category III
material is sitting on the bottom. Weplan to do remediation
using Category I material to improve the areas where we
see high levels of toxicity or accumulation. The Category
I material will consist of clean dredged material from the
harbor, and  maybe some sand,  depending on  benthic
community structure.  I believe that much of the problem
here is a perceived problem.  Newspapers in the Northeast
have described the terrible dilemma with sediment con-
taminants in the New York area. I think a lot of the news
coverage was exaggerated, but unfortunately, we now
have to prove that each regulatory decision made by EPA
, and the Corps of Engineers results in safe disposal of
dredged material. That is why we need the science.

Q (G. Fred Lee):  The science should be based on what you
find at the site and not extrapolated from some other
place.

Mario Del Vkario:

Well, we do look at the site conditions to make decisions,
but part of what we have done in the last 10 years is use
capping as a tool to minimize bioaccumulation at the site.
I  feel it has been  a very effective tool.

 Q (Betsy Southerland): I am going to have the panelists
 tell us their biggest problem with using bioaccumulation
data today in their regulatory programs and what high
priority needs they have to improve their use of bioaccu-
 mulation data.  Then I am going to open it up to the
 audience to  address  what  the future needs are. It is
 important to document this discussion because  ORD is
 currently preparing its next big grant proposal for con-
 taminated sediments. Any  high priority needs that you
 identify at this conference -will be included in the request

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                                                                                                     7-55
 for application (RFA) for the grant.  They will also be
 incorporated into the ORD Research Strategy to direct
 the use of their own in-house resources. If the panel does
 not mention a high priority need that you have perceived
 after listening to the discussion in the past two  days,
 please speak up and let us add this issue to the priorities.
 I will ask Mario Del Vicario to begin.

 Mario Del Vicario:

 A  critical need for the Dredged Material Program is to
 ensure that the information we have available to help us
 make decisions is truly supportable and defensible.; We
 have been able to apply work completed on food chain
 multipliers, and trophic models to generate information
 for decision-making In our program.  We need to con-
 tinue to use information like that and work to make the
 information better. We also need to continue to improve
 how we are looking at chronic values, aquatic effects
 data, dose-response relationships, and concentration ef-
 fects data. A concern I have is being able to make good
 regulatory decisions without someone having to pay for
 elaborate and expensive tests when we can perhaps de-
 velop simpler ways to get abetter, quicker answer. Tothe
 extent possible, we should attempt to provide easier ways
 for people to get decisions.

 Tom Murray:

 I think, programmatically speaking, we have very few
 barriers. If I had to describe some of the problems that we
 might have with the use of bioaccumulation information,
 one wouldbeobtaininginformationthathas good QA/QC.
 We are dealing  directly with industry and with  their
. economy in terms of producing and manufacturing chemi-
 cals. We want to try to provide as reasonable an assess-
 ment as we can. When you move into problematic areas
 such as bioaccumulation and sediment toxicity, it be--
 comes more questionable.  We. are looking both for the
 availability of data and for good quality information.  I
 know there is probably a lot of information in the  EPA
 Regions and states that we do not have access to.  It would
 be nice to figure out how  to get'those data.   Another
 problem we have is that, unlike programs in the Regions,
 states, and the Office of Water to some extent, we do not
 do site-specific analyses. In some instances, we go into
 a particular area and do an analysis. If bioaccumulation
 data are available there, we might be able to use them.
 Much of the work we do on a chemical is really more of
 a generic population-type estimate, where we are looking
 at manufacturing/processing user sites all across the coun-
 try. The sediment situations may differ at these sites and
 we are trying to come up with a generic answer.  That
 would cause a problem for us with the bioaccumulation
 data.

 Q (Betsy Southerland):  Tom, when you say you need
 more data, do you want tissue residue effects levels in
 aquatic life, wildlife, and humans, or bioaccumulation
factors-and fate and transport information?  ,     -
 Tom Murray:    >

 All of the above. We basically are; scavengers looking for
 a way to get good information in our hands. Any and all,
 of that data would be helpful.;           ,   ,',

 Jim Pendergast:

 Like Tom Murray's program, the NPDES Program does
 not have any legal regulatory barriers, but there are three
 data gaps that I see. First, we need to find a better way of.
 being able to  identify existing and  future potential
 bioaccumulative problems. When Craig Vogtwas asked
 how.they determine the pollutants for the dredged mate-
 rial program, he responded that they use chemistry. That
 approach would not be practical for the NPDES Program
 where we  must work  with  hundreds  of  thousands of
 chemicals. Instead, we are working :with the Office, of
 Research and Development to develop a screening meth- ,
 odology. We currently have a draft guidance that needs
 some refinements, but  it  is about 95 percent complete.
 We need to finish.the  guidance and get it distributed.
 Second, we need to have  a better handle on the fate and
 transport  of  sediments.  For programs involving
 remediation or dredging, you  can identify where the .
 pollutants are and determine appropriate ways to remove
 and dispose of the contaminated material.  For TSCA
 programs, you work with a facility to keep pollutants
 from being released into the environment.  But in the
 NPDES Program, we are working with mixtures ,and
 multiple sources in attempting to regulate close to 3 00,000
 sources. We.must be able to use fate and transport to link
 the sources with the problems, and we need, a tool to do
 that.  If possible, we need to develop  something, more
 simplistic than the WASP model that.is.a little bit easier
 to run and a little less data intensive. We began to develop
 this tool 3  or 4 years ago, but we need more  time to
 complete the effort The last problem is trying to look at
 things holistically. It is much easier to get data on point
 sources.  Getting data on nonpoint sources can be more
 difficult. You have to put all that information together to
 try to get the picture of what we need to do. We really
 have to start using geographic information systems (GIS)
 more widely to determine what goes into the watershed
 and what sources are contributing to the predominant
 problems. A lot of work has already been done in this
 area, but much more still  needs to be done. It will take
 some tune not only to fit together the existing pieces of
 the puzzle,  but also to fill in the missing puzzle pieces.

 Latry Zaragoza:

 I see a couple different needs for the Superfund Program.
 One is.the kind of work Mike Kravitz is undertaking to
 understand the meaning of different testing. This will be
very useful. It is difficult when you have several tests
 available, but you are not really sure how to interpret the
results and determine what is significant. Traditionally,
we have tended to look to other offices for guidance on
that issue. Another issue for our program, is determining

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                                                               National Sediment Bioaccumulation Conference
how the significant risks in the water column or sedi-
ments compare with risks in other media. We would like
to be consistent in the way that we are addressing risks for
a particular site.  If we find that we are much more
sensitive in one medium than another, we need to balance
how we are addressing all the factors we consider. Better
science could help us balance those factors, even with the
added complication of having to incorporate cost/benefit
analyses into our evaluations. Finally, there is the issue
of what to do with contaminated sediment once it has
been identified at a site. If it is dredged, the material may
be difficult to dispose of. This is an issue because there
are a lot  of sites in our program with contaminated
sediments.

Q (Betsy Southerland):  Are you talking about develop-
ing new remedial technologies or improving existing
technologies for remedial alternatives like capping or
disposal in confined disposal facilities (CDFs)?

Larry Zaragoza:

I am talking about all those things. There are problems
with existing technologies  to deal With contaminated
materials. Not only are there limitations in terms of
places that can hold the sediments, but there are also
debates about what would be an appropriate disposal site.
And the question has been raised about whether CDFs
are an appropriate place for disposal of certain types of
sediments. We have been involved in intensive discus-
sions on all of these issues. It is really important to have
an open dialogue on this subject now, because Superfund
legislation is being considered for reauthorization and it
is likely that the reauthorization package will include
amendments to address anumber of different issues. One
set of amendments will target facilitating the process for
addressing contaminated  sediments.  It will probably
include a research component that can help us  resolve
outstanding issues.  But the cost/benefit question will
come up again if we focus more on sediments or the water
column than on soil.

Maurice Zeeman:

I will begin and end with the same question, "What
sediment and bioaccumulation data?" I say that because
a lot of monitoring is being done today for the  same
chemicals we have been looking at for over thirty years.
These typically include  organochlorine insecticides,
PAHs, PCBs, dioxins, furans, and heavy metals. The
Toxics Release Inventory, which was established as a
result of Superfund, required industry to report on their
emissions for only  300 chemicals.  The reporting re-
quirement focused on chemicals that were highly toxic,
but not necessarily persistent and bioaccumulative. In
the late 1980's, industry reported several billion pounds
of emissions for just 300 of the 75,000 existing chemi-
cals. These reports indicate that a lot of chemicals are
being released into the air or water. Not all of them will
necessarily be a problem, but a fair portion could end up
in the sediment. We need to move beyond looking at the
usual suspects. My group is responsible for conducting
ecotoxicity assessments, but we rarely have bioaccumu-
lation data to use in these assessments. We have a tiered
testing approach in our program for  both  new  and
existing chemicals. We require testing for acute toxicity
and if we think a chemical is likely to bioaccumulate, we
move to chronic  toxicity testing.  There are cases,
especially for high log P chemicals, where acute toxicity
testing may not always be appropriate.  In these cases,
we need to consider moving right to chronic toxicity
testing. So, I go back to my original question, "What
sediment and bioaccumulation data?"

Craig Vogt:

There  are a lot of needs for the Dredged Material
Management Program. Mario Del Vicario summarized
some of those needs very well, but I am going to expand
on them in terms of tissue residue effects levels, chronic
tests, and fate and  transport models. We basically need
more information  to be able to get better answers for
several important program questions. For example, we
have a site designated in the ocean for disposal of
dredged material.  When dredged material is dumped
there, where does it go? Does it stay on the site or does
it move to another location? Better fate and transport
models would help us answer these questions.   The
Dredged Material  Management Progam is moving into
a more formalized process for risk assessment that will
involve looking at  exposure, characterizing  risk and
managing based on the risk assessment results. We have
the Green Book and the Inland Testing Manual, but we
need help on exposure and exposure analyses. We also
need to determine  what  tissue residue effects levels
mean on  an ecological scale.  Without that type of
information, decision-making  gets difficult.  As we
continue to develop the science, we can rely more fully
on science as the basis for decision-making, rather than
politics and misinformation that has influenced public
perception. The public currently considers the oceans to
be a sacred place where nothing should be dumped. But
disposal of dredged material at ocean sites is a  very
minor source of contaminants that enter the ocean com-
pared to other sources such as surface water runoff and
some point source discharges. It is a matter of balance
and how you achieve that balance. I would like to see
better risk assessments conducted for the various media.
We can use this additional information to involve stake-
holders and together  make more scientifically sound
decisions for managing dredged material.

Betsy Southerland:

I would like to open the panel  discussion  up to the
audience. Please  state your name and affiliation before
you begin to address the panel.

 Q (Susan Svirsky, U.S. EPA Region 1,  Superfund Pro-
gram):  Maurice Zeeman, do you  have analytical

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 Proceedings
                                              7-57
 methods available for some of these chemicals that are
 outside the normal sweep of what we look for? If so, can
 you make them available  to us so we can further our
 analytical capability and look for some, of them?

 Maurice Zeeman:

 I am a biologist, so I am not a good source of information
 about analytical chemistry.  Let me refer  you to Bob
 Boethling of my  office for that information. But I do
 know, for example, that chlorinated paraffins are com-
 pounds like PCBs that are'a messy mixture of chemicals.
 The analytical chemistry for these mixtures can be very
 complex. I am convinced that these chemicals are ex-
 tremely hazardous to organisms in the environment, but
 manufacturers are producing hundreds of millions of
 pounds of them  each year worldwide.  Some limited
 monitoring data  from a few places  around the world
 indicate that they are causing problems. However, there
 are a fair number of more  simple compounds where the
 analytical methodology should not be so  complex to
 develop and apply.

 Betsy Southerland:

 Susan, *there are two studies I am aware of that might
 provide some useful information for you.   One was a
 study that Bob Huggett conducted with the Virginia
 Water Control Board when he was still at the Virginia
 Institute of Marine Science. It was a big study where they
 collected sediments downstream of some urban indus-
 trial areas and analyzed the chemicals in the sediments
 using some kind of library scan.  They were able to
 identify over 300 compounds that were persisting in the
 sediments. You can locate literature on the study to see what
 method they used. There is also the screening procedure
 for wastewater being developed by our Duluth laboratory
 that Jim Pendergast mentioned earlier.  For this proce-
 dure, wastewater is  fractionated based on octanol-water
 partition coefficients and the fractions are run across a
 library  scan to identify any potential bioaccumulatives
 that could  be in a waste stream. They are doing some
 additional testing before they release the protocol.

 Steve Cibik, ENSR:

 We have come a long way in taking the "pseudo" out of
 pseudo science and replacing it with good science, espe-
 cially with recent developments for BCFs, bioaccumula-
 tion, trophic modeling, and food chain modeling.  We
 made a big advance when EPA issued the Wildlife
 Exposure Handbook  to help standardize  risk assess-
 ments.  What we need now is better information on tissue
 residue values, because  I  heard that  we  are
 approaching a factor of 2  or 3 in accuracy  for many of
 these things, but adding one safety factor to a risk assess-
 ment will give you a factor of 5 or 10. Decisions in risk
. assessment have to be based on good tissue residue
 values. We already have a Ipt of aquatic toxicity numbers
 available. I hope EPA will be able to help develop more
information for wildlife. We need tissue residue values
for both terrestrial and avian wildlife.

Q(Catherine Fox^U.S. EPA, Office of Enforcement and
Compliance Assurance): The 1992 mandate of the Water
Resources Development Act (WRDA) called for the de-
velopment of the Rational Sediment Inventory, a national
data base which is now available.  Many of you have
evaluated it to identify hot spots based on a number of
factors, including fish tissue data. What we can do right
now is to look at these hot spots based on fish tissue data,
and for the various programs, to address the current
sources of contaminants to prevent the discharge of these
contaminants from point sources, nonpoint sources, and
sediments.  I have looked at this using a GIS and found
some really interesting things that are happening right
now with discharges. I would like to go_ upstream and
look at the sediments. I am asking the panel to consider
this as a need that we could, address  now.  We have the
people and we have a lot of the tools.  Jim Pendergast
lookedat this 5 years ago. He probably knows a lot that could  •
help us now. This is an area of interest for enforcement
and I am requesting assistance from other offices.

Tom Murray:

As Maurice has mentioned, there are many chemicals on
the inventory that OPPT has not had a chance to look at.
OPPT is setting up a priority system to look at these
chemicals.  A couple of things are happening in OPPT
right now to advance that process.  One is that we are
moving away from a single chemical approach to life and
trying to look at chemicals as use clusters or clusters of
chemicals that might be found in a product. We have
developed some systems within our organization to help
us set those priorities. For example, we are looking at
indoor air sources as one system. We are ranking various
chemicals in this system to figure' out which indoor air
chemical products or chemical products that might lead
to indoor air problems are the most important to look at.
We have also developed the use cluster scoring system to
look at a variety of information and  help identify what
areas or what chemicals we should focus on.  Catherine,
maybe we can help generate more information about the
sediment contaminants you are concerned about  We
could perhaps consider a cluster of chemicals that may
find its way into sediments or tissue and factor that
additional area into our priority-setting process.

Betsy Southerland:

Enforcement actions based on data in the National Sediment
Inventory or fish advisory data base must be based on the
fate and transport modeling which Jim Pendergast men-
tioned earlier.  There is a lot of concern that it would be
difficult to take the ambient data and trace it back to 'a
source. None of the data that we have  either in the
sediment inventory or in our fish advisory data base, will
prove cause and effect. We need additional studies to be
able to take the presence of a contamination problem and

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                                                               National Sediment Bioaccumulation Conference
work it back to a responsible source. If that responsible
source is a point source in violation of permit limits on
those toxicants, then it certainly would be appropriate to
take an enforcement action.  But again, the  ambient
information in our data bases will not allow you to link to
sources.  You will have to demonstrate cause* and effect
from additional studies.

Jim Pendergast:

I would like to add one other thing to that. Catherine, you
may want to talk with Louise Wise in the Office of
Wetlands, Oceans, and Watersheds. She helps chair a
Division Director group on watersheds. All of the Office
of Water divisions are working to fry to figure out how to
do things on a watershed basis, so we avoid the sector-by-
scctor approach and try to look at things holistically. A
Minnesota example can illustrate one of the reasons why
this is important when you are dealing with fish adviso-
ries  and sediments.  There are a number of  lakes in
Minnesota with fish advisories for mercury, but no iden-
tifiable point  source for mercury.  Mercury  may be
transported into the area in the air and deposited in the
lakes when it rains. You should start to address  these
Issues with the watershed group.

Q (John Haggard, General Electric Company): Robert
Paulson brought up a new term that I think is particularly
appropriate for sites where companies with liability and
regulatory agencies are dealing with difficult sediment
problems. That term is potentially reasonable parties or
PRPs.  We are one of the PRPs at a number of these sites
and we clearly have concerns with the liability manage-
ment.  How do we manage these problems in a  cost-
effective way? These sites are presenting unique prob-
lems to regulatory agencies, because there are no simple
solutions to sediment problems. Where are you going to
put this vast volume of contaminated material?  What is
science telling us about what we can really achieve?
What damage might we cause by removing the material?
There is a lot of positive research going on to help reduce
the uncertainty. This is very important to industry since
we would like to see some actual benefits from the money
expended.  I  would like to make a recommendation
related to a chart Larry Zaragoza presented that showed
the basis for decisions at sediment sites. 1 was surprised
to see that 9 of the 14 sites involved risk-based decisions.
We have looked at 80 or 90 contaminated sediment sites
and found that only about a dozen have gone through a
record of decision process and some remediation. When
we look at sites, we can rarely figure out the basis for the
decision.  Documentation on these sites is a serious
problem.  In addition, when we look at how  well the
technology performed, we see clear problems with dredg-
ing.  I would recommend strongly to this group that you
look at the capabilities of the technology within d com-
parative riskframework at these contaminated sediment
sites. It is an important issue that I hope somebody will
take a shot at.
Betsy Southerland:

A group from our Office of Research and Development
laboratory in Cincinnati, Ohio just informed me that they
are organizing the National Conference on Management
and Treatment of Contaminated Sediments to be held
during May 1997 in Cincinnati. They are inviting speak-
ers to present a series of case studies ranging from bench-
scale remediation projects to full-scale remediation ef-
forts. They are also inviting a large variety of vendors to
display and demonstrate new equipment developed for
remediation projects and' equipment that has proven
successful for previous projects. The conference will be
a good opportunity to hear about experiences with sedi-
ment remediation. Since a number of the case studies will
involve Superfund sites, we can request that the speakers
include details in their presentations about how they
reached the decision for remediation and how they deter-
mined the volume of sediment for removal.

Larry Zaragoza:

1 think that one of the things we need to do is to begin
operating in an environment where people can actually
see the logic and consistency behind a particular pro-
gram.  We have been confronted by a whole host of
challenges in the area of contaminated Sediments.  Susan
Svirsky raised some of the issues in her earlier comments
about people avoiding dealing with sediment problems to
date because of these challenges. But for sediment sites
that have been addressed, these efforts might be consid-
ered successful if all the parties involved in the site agree
to. clean it up and the community  is pleased  about the
actions being taken at the site. That is very different from
having a national profile that shows you benefits infor-
mation and  consistency in cleanup levels across the
country. As a result of looking at how we have operated
as a program and hearing comments like yours, we are
seeking to collect that information in a more systematic
and consistent manner. We have already collected some
information, but we are  trying  to do a better job of
obtaining more information. I think you can expect that
in the future more comprehensive information about our
sites will be readily available.

Maurice Zeeman:

We also have to realize that there has been a bias in many
cases for "we have to do something" action. Certainly in
the past, there have been cases where actions other than
removal were appropriate. An example that comes to
mind is the case in Triana, Alabama where people were
being exposed to high levels of DDT. The highest levels
were found on an Army base that produced a lot of DDT.
The  Army Corps of Engineers solution was to reroute
part  of the river and cover the most contaminated areas
with topsoil. That may not have been the best solution,
but it was the most cost-effective approach under the
circumstances.  I have been teaching  a  course in

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                                                                                                   7-59
 environmental toxicology at the National Institutes of
 Health (NIH) since 1982. One of the things I have found
 really remarkable with that experience is how ignorant
 we can become over time.  I have asked my classes
 recently about what happened with the Kepone spill in
 the James River, and virtually nobody is aware of the
 incident any more. Many people think the problem has
 gone away. It was going to cost many millions of dollars
 to dredge after the spill, so the lower river was closed to
 a number of activities and allowed to recover naturally
 with deposition of clean sediments'. It is a solution that
 has worked over time.  But, Bob Huggett has presented
 results of studies that show Kepone-contaminated sedi-
 ments have been moving out into Chesapeake Bay. All
 we need is the right kind of hurricane to redistribute these
 sediments for the problem to occur all over again.

 Q (Helder .Costa, Inchcape Testing Services, Aquatec
 Laboratory): Several EPA-sponsoredstudies have shown
 close associations between alkylated PAHs in petroleum-
 influenced systems and adverse effects to benthic organ-
 isms and habitat. In the Delaware Estuary, for instance,
 the alkylated PAHs accounted for typically 50 to 70
 percent, or even 80 percent, of the total PAH loading.  I
 want to comment that we can only begin to understand the
 importance of PAHs as a chemical compound class when
 we begin to consider the alkylated PAHs in petroleum-
 influenced systems.

 Betsy Southerland:

 I know that Rick Swartz from our laboratory in Newport,
 Oregon  will soon be publishing a total PAH analysis
 based on narcosis effects. He is trying to help us analyze
 PAHs as a whole chemical group  instead of having to
'consider each PAH with its individual toxicity.

 Q (Helder Costa): I particularly applaud the work Rick
 Swartz has done in developing the sum PAH model and
publishing the results in the SETAC journal (Environ-
 mental Toxicolpgy and Chemistry, Vol. 14, No. 11, pp.
 1977-1987, 1995).  In his paper, he acknowledged the
 importance of alkylated PAHs  in petroleum-influenced
 regimes as a temporary limitation to the model.

 Betsy Southerland:

 An individual from the Metropolitan Washington Coun-
 cil of Governments has conducted some studies that show
PAHs are coming not only from products of combustion,
but also from ground water contaminated by leakage
 from automobiles and other sources. That is new infor-
 mation to me in terms of sources.

 Q (John Zambrano, New York State Department of Envi-
 ronmental Conservation): If we agree that contaminated
sediments are a problem that we want to do something
about, we are going to have to know the relative amounts
of various sources of contamination.  We also need to
know Whether past contaminants that'we may not be able
to do much about are circulating within the system, or
  whether new contaminants are being introduced by cur-
  rent sources. Could these sources be point sources that
  we are hot regulating sufficiently such as stormwater or
  combined sewer overflows? Could land runoff or atmo-
  spheric deposition be contributing to the problem?  It
  seems to  me that unless you know the amounts from
  various sources, you will not be able to make intelligent
  decisions within  the Superfund Program, the NPDES
  Program, or the Dredged Material Program. I think we
  need to do more sampling  and modeling to get that
  information.

  Larry Zaragoza:

  Your commends very well taken. I agree that it is worthwhile
,  to have thatkind of information. For a Superfund site, we
  would specifically look for that kind of information to see
  what is going on at the site level. But that only speaks to
  a particular site. It does not tell you about what is going
•  on in  the  rest  of the country.   Sediment assessment
  generally needs to be site-specific, but that complicates
  comparing a site to other sites across the country.

  Betsy  Southerland:

  The best mass balance study done to date that I know of
  was the work conducted for PCBs on the Fox River in
  Wisconsin. I think they had a budget of about $}5 million
  for monitoring.  I  know that EPA programs are trying to
  look at mass balances, particularly in the Office of Air
  and Radiation.  The air program has worked with us in
  preparing their  second report to Congress on deposition
  of air pollutants to the Great Waters. They are trying to
  do large-scale mass balances for substances like mercury
  and PCBs  to determine  how much mercury  and PCB
•  contamination can be attributed to air emissions.

  Q (Don Porcella,  Electric Power Research Institute): I
  have enjoyedthis conference very much.  Therehavebeen
  some new  approaches developed and presented  here,
 particularly the food chain modeling.   Will these ap-
 proaches be incorporated into future analyses?  All the
  approaches we  have heard about include the concept of
  models. For example, a bioassay is a physical model as
  opposed to a mathematical model. I think it is really >
  important to do  groundtruthingfor these models, as well
  as to address the "So what?" question Gil Veith raisedat
  the beginning of the conference. This question particu-
  larly relates to Fred Lee's comment about whether there
  has in fact been any damage in the New,York Harbor area
 from dredged material disposal.

  Mick DeGraeve:

  I just want to reinforce  the importance of what Betsy
  Southerland and Jim Pendergast .mentioned about
  finalizing-the screening procedure for bioconcentratable
 contaminants. Larry Burkhard, who is in the audience, is
 the principal author of the method.  One thing'that Betsy
 and Jim did not mention is that the method works not only
 for effluents in water, -but also for tissues and sediments.

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                                                                National Sediment Bioaccumulation Conference
In terms of some of the dredging-related issues, it can be,
applied to address the likelihood of bioconcentratable
contaminants being present in sediments and certainly in
tissues. We have used the procedure commercially to
address some very interesting questions and it has worked
quite well.

Q (Betsy Southerland): Have you used it on sediments or
just wastewater?

Mick DeGraeve:

We have used it on sediments.  I am glad that efforts are
going forward to finalize it.

Jim Pendergast:

My focus at EPA has been primarily on wastewater. But
for one year in the 1980s, I worked with the Superfund
Program. While I was there, it would have really helped
to have had that methodology available  to assess sedi-
ments at Superfund  sites. The guidance also includes
information about integrating fish tissue data in the
decision-making  process to determine whether or not
there is a problem.   We tried to make it a one-stop
document to deal with multimedia.

Q (Lynn McCarty, LS. McCarty Scientific Research &
Consulting): My opinions are entirely my own since I do
not represent an agency. There are two areas I would like
to comment on. The first one is technical.  If you continue
to go down the toxicological route, you are eventually
going to have to deal with molar units. Since toxicology
is a function of the number of molecules of a compound,
not its weight, you will find that many relationships that
would be obscured by using weight-based measures will
become much clearer when you use molar weight. The
second issue is a philosophical one at the very end of the
scale of what we are talking about today.  I was pleased
to hear Dr. Patton indicate in her discussion that both
science and policy are included in the EPA risk assess-
ment process.  That is an explicit recognition of some-
thing that I think a number of people have realized for a
long time, but it is an important distinction. We must keep
the science and the policy separate or at least identify
themassuch. In this whole process of becoming open and
transparent, making this distinction is particularly im-
portant. What we are trying to do in this whole exercise
is risk management.  We are trying to achieve some sort
of environmental protection.   As scientists, we  need
technical decision criteria to do that and to fit into the
decision-making process.  In other words, we need to be
able to define what a significant adverse effect is. It is
great to say that we have to protect the environment, but
when it comes down to scientific measurements,  what
does that mean? We have some difficulties because we
are trying to  define future problems from an existing
problem perspective and from a modeling perspective.
 The objective of risk assessments providing information
to make choices among alternatives.  So, what is  the
framework? What are the effects that we are concerned
about and what are the alternatives that we are choosing
among?  Developing information for risk assessments
involves specific goals that change from the research
emphasis being presented here to regulatory utility. If we
do not have risk management directions that are framed
in technical terms, we cannot make decisions.  That is
what this is all about.  This is a policy  issue, and the
science  is guiding the decisions.  I found the  list  of
questions Dr. Southerland provided for the speakers  to
be very useful because it addressed many of the important
technical issues. Unfortunately, I do not think we have
coalesced those into a useful decision-making frame-
work. I would like to encourage the panel and EPA  to
consider that, because I think that many of the people  at
this meeting are looking for very specific directions.
What is it that we want to do, and how can the science that
we have available help us in making the decisions and
choosing among those alternatives?

Alex Lechich:

As a scientist  regulator, I sometimes feel that research
scientists do not carry the same burden as we do, so I do
not have any  qualms  about trying to lay a little more
weight on their shoulders. In terms of the data bases that
are being developed for the' specific effects, I think it
would be helpful to go beyond just assembling, compil-
ing, and presenting this information.  Have the people
who are most familiar with the studies and the data itself
become involved where there are conflicts.  In some
cases,  we can look at the data and make fairly clear
decisions. In other cases where the results conflict with
each other, it would be nice to have the people closest to
those studies review them and provide a recommendation
as to where to go from there.

Phillip Rury, Arthur D. Little, Inc.:

I would like to thank and commend all of the people who
contributed to this excellent conference.  It is probably
one of the better conferences I have been to in many years.
I would also like to say that I feel it is long overdue and
I hope that we can see a sequel to this very soon. In terms
of some of the gaps that I see and the future research needs
that some of the speakers have identified, those same gaps
were reflected in the presentations here. I would hope
that we could address them in future conferences. I would
implore everyone to look in these directions. In a kind of
evolutionary-speak sense, perhaps our research needs to
crawl up onto the land again. The aquatic focus of this
conference was obvious, but I am concerned mat issues
such as amphibian bioaccumulation are not being ad-
dressed. The questions concerning wetland species also
need to be addressed more vigorously.  For example, the
data base presentations at this conference specifically
excluded amphibians with the exception of tadpoles. We
have found this lack of information on amphibians to be
a major constraint in several risk assessments. Mink food
chain exposure models, for example, are highly sensitive
to the frog elements in the diet. We also have a dearth of
bioaccumulation factors. Several that do exist are quite

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Proceedings
                                                                                                   7-61
high and they are driving the cleanup goals. I would also
like to get on my soapbox about the lack of integration of
ecological and human health risk assessment.  I would
hope that maybe in another 10 or 20 years, as the pace of
regulatory change proceeds, that we might see a shift to
an  ecosystem-level approach to risk assessment that
includes consideration of both human health and eco-
logical risks. This approach should allow us to realize
some efficiencies of costs and some enhancements of
understanding by integrating humans into an ecosystem
risk assessment as a mandatory indicator species in
every case.

Burt Shephard, URS Greiner, Inc.:

There are two areas I would like to comment on. One is
to respond to the remarks about the .data bases. I think
those of us who are putting the data bases together are
very much aware of the conflicting data. You might not
see it at the first level of building thedata bases, butl think
that shortly thereafter you will see some attempt by those
of us putting the databases together to resolve conflicts.
Some of the data quality issues are very important to us.
Some of the data are not very good, but some are excel-
lent. Initially, we will be putting out summaries of the
data with a lot of data qualifiers saying how things were
done and let the end users make their own judgments
about whether the data is good or bad for their own
purposes. I certainly concur with the comments and think
we will be making some efforts to resolve some of the
conflicts within the data at some point down the road.
Second, before we can really define a  contaminated
sediment, we need to know something about what ah
uncontaminated sediment is.  There were some talks here
about defining background reference area sediment con-
centrations. Within the risk assessment area, that is a very
large need right now.  The  guidance today within the
various EPA Regions for defining background or refer-
ence area concentrations is, inconsistent.  I think it is very
important to have a defined  statistical guidance that
 describes 'how to  compile reference area data and com-
pare site data to it to see if the site data are exceeding the
 reference or background data to a degree that indicates
 contamination problems.  The RCRA  guidance docu- .
 ments on statistical comparisons are the best ones that I
 have seen within EPA.   They look at  sample mean
 comparisons between sites and background areas. They
 also have, for lack of a better term, a hot spot out on the
 tail of the distribution to see if very high concentrations
 fall within a distribution or within a confidence limit of
 a  distribution.   I" think  some consistency with
 comparing backgrounds  or calculating backgrounds
 would  be very useful to everyone who has to do risk
 assessments.

 Q:(MalcolmWatts,Zeneca,inc.): I want to support the
 comments that have been  made by Fred Lee, Lynn
 McCarty, and John Haggard.  Lynn McCarty asked;
 "What do we want to do and how does science help us? "
 What we want to do  is to maintain or clean  up the
 environment. That is pretty obvious. We are all breathing
out carbon dioxide and contributing to global warming.
Shall we all remove ourselves from the planet? Clearly
not.  I suggest that it is a matter of cost-effectiveness.
How much does it cost and what are the benefits? Fred
Lee said this morning that there seemed to be very little
damage from the New York Harbor dredging.  So, I
question the costs.  /; also question the effectiveness,
versus the benefits. I would like your comments on cost-
effectiveness and the extent to which we have tried to look
at the  costs of doing nothing and the benefits of doing
something.

Betsy  Southerland:

We did do a few case studies where we looked at the costs
and benefits of remediation. I am sure everyone here is
aware that the science of analyzing benefits is an area
where we lack monetization methods.  We have three
tiers of benefits analysis that we do for environmental  ,
projects. The first tier, which is a qualitative discussion
of benefits, is the one we generally have to use.  If you
have more data you can move up to tier two, which is a
quantitative description of benefits.  Only at the third tier
do you have monetization of benefits.  No matter which
of our programs is doing a regulation of other action, we
always have a tough time at EPA doing monetization of
benefits, whereas monetization of costs is a very well-
defined area. We have disagreements with the regulated
community about our cost estimates, but we have plenty
of procedures to provide us with costs.  At any rate, when
we have done cost/benefit* analyses on some remediation
projects, we have been  able to demonstrate that the
benefits have met or exceeded the cost of the remediation.
There were studies at three Supermnd sites where the
costs were in the area of $25 million to $50 million for the
sediment remediation and the benefits were at or above
$50 million. Those are the only cases  that I know of
where the focus has been on  calculating the costs and
benefits of sediment cleanup. Since they have state water
quality sediment standards, Washington  State is doing
similar work.

Larry Zaragoza:

I did not want to give any site-specific information, but I
did want to say that Superfund  is not a cost/benefit
 statute. In making the request that decisions be put into
 a cost/benefit framework, I think you need to look at what
 the  legislative direction is for the program.  Basically,
 each of our programs has a different framework and a
 different legislative history. We are supposed to admin-
 ister each program based on what the law says.  We
 should also coordinate among programs to be efficient
 and to learn from each other. The last Congress had a lot
 of discussion about costs and benefits, and I expect that
 we are going  to see that reflected in the next set of
 legislation. I would also like to  reinforce what Betsy
 Southerland said about  the monetization of benefits.
 Quantifying benefits in monetary terms is not something
 we have done a lot of. It is controversial, so that will make
 it challenging in many cases  to develop a number that

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         National Sediment Bioaccumulation Conference
may be accepted. There are anumber of issues in this area
that will continue to be debated.

Maurice Zeeman:

As Mother Nature says, "Pay me now or pay me later, but
a lot more later." If the Great Lakes area is any example,
the time frame for many ecological concerns is decades.
If you are talking about the need to know this week how
much it is going to cost and what the benefits are, you are
going to end up with nearly intractable problems. The
Chesapeake Bay is another example.  We are seeing
examples around us of problems where their scope and
scale is virtually beyond all the small management and
cost/benefit decisions we are making. I concur with what
the prior two people said.  We are getting better at it, but
so far the environment has been virtually free: That is the
reason that it is so contaminated.

Betsy Southerland:

If there is no further discussion, I will close this session
with a few summary remarks. I want to reiterate that the
future needs raised by speakers and other participants in
this conference will be factored into ORD research plan-
ning and included in our bioaccumulation report.  If you
are not already on the mailing list, I also want to remind
you to sign up for the Contaminated Sediments News, a
newletter that we produce and distribute from our office.
We will provide follow up information for several things
mentioned during this conference in future issues  of our
newsletter.

It has been tremendously informative and enjoyable for
all of us that have worked for more than a year to organize
this conference.  We especially appreciate the commit-
ment of all the speakers and  moderators to continue
working with us when we had to reschedule the confer-
ence due to the Federal furlough in the fall of 1995.  It was
a challenge we were finally able to overcome. We thank
you for your interest and participation in this conference.
My staff will be available after the conference to listen to
any additional comments and suggestions you may have
before you leave. Again, thank you for coming. We will
be keeping in touch with you  through the Contaminated
Sediments News.

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                                                            National Sediment Bioaccumulation Conference
Speakers9  Biographies
James K. Andreasen, Ph.D.

     Dr. Andreasen  is. the leader of the pcological
'Assessment Team at the National Center for Environ-
mental Assessment within the Office of Research and
Development of the U.S. Environmental Protection
Agency (EPA).   He works in Washington,  D.C.
Dr. Andreasen'received his Ph.D. from the Department
of Fisheries and Wildlife at Oregon State University in.
1975. Following a short teaching career at the University
of Alaska, he secured a position with the Federal Govern-
ment and has been conducting research on the effects of ,
contaminants and other environmental stressors on eco-
systems for the past 20 years. He came to the Office of
Research and Development 3 years ago from the Fish and
Wildlife Service, where he worked in the environmental
contaminants program. Dr. Andreasen is active in the
Society of Environmental Toxicology  and Chemistry
and currently serves as the president of the Chesapeake-
Potomac Regional Chapter.  During his free  time he
enjoys genealogy, family history research, and wood-
working. His 17 grandchildren enjoy the toys and other
creations he makes in his shop. One of his goals  in life is
to someday return to the wide open spaces of the West.
 Lawrence P. Burkhard, Ph.D.

      Dr. Burkhard is a research chemist hi the Ecologi-
, cal Toxicology Research Branch  of EPA's National
 Health and Environmental Effects Research Laboratory,
 Mid-Continent Ecology Division, in Duluth, Minnesota,
 He received his B.S. in Civil Engineering from Pennsyl-
 vania State University and his M.S. and Ph.D. in Water
 Chemistry from the University of Wisconsin-Madison.
 His research interests include the behavior and effects of
 bioaccumulative  organic contaminants  in aquatic eco-
 systems, analytical methodologies for the detection and
 quantification of known and unknown organic contami-
 nants in environmental samples,  and  lexicologically
 based analytical methodologies  for the detection and
 identification of unknown toxicants in environmental
 samples.
 Peter M. Chapman, Ph.D.

      Dr. Chapman is a senior principal atEVS Environ-
 ment Consultants, North Vancouver, British Columbia.
He received his B.Sc. in Marine Biology, his M.Sc. in
Biological Oceanography, and his Ph.D. in Benthic
Ecology from the University of Victoria (1979),  His
experience and expertise since graduation have centered
on ecotoxicology and aquatic ecology, which he has
combined into integrative assessments such as the Sedi-
ment Quality Triad.  He has published over 90 peer-
reviewed journal publications and book  chapters  and
over 200 technical reports on a wide variety of subjects,
including sediment bioaccumulation.
David W. Charters, Ph.D.

     Dr. Charters is  an environmental' scientist with
EPA's Environmental Response Team located in Edison,
.New Jersey.  He attended undergraduate school at Syra-
cuse University and continued his education at the State
University of'New York at Binghamton,  where he re-
ceived  a Doctorate in Biology specializing in Environ-
mental Pathology. Dr. Charters' dissertation study was
conducted at Love Canal, Niagara Falls, New York, and
he investigated the demographic structure of the small
mammal populations in the area and the histopathologi-
cal responses of these indigenous mammals. .Dr. Char-
ters joined EPA's Environmental Response Team in.
1985 and has worked on ecological risk assessment since
then hi the  Superftmd  program.  He has conducted
investigations on many of the National Superfund sites
and has conducted studies and investigations internation-
ally. He is presently completing Superfund guidance on
conducting, ecological risk assessments ,and is involved
in the reauthorization  of the Superfund law.
 John P. Connolly, Ph.D., P.E.

      Dr. Connolly  is "a principal engineer with
 HydroQual, Inc., in Mahwah, New Jersey.  He received
 his B.E. in Civil Engineering and his M.E. in Environ-
 mental Engineering from Manhattan College. His Ph.D.
 hi Environmental Health engineering is from the Univer-
 sity of Texas  at Austin.  Prior to his  Ph.D. studies,
 Dr. Connolly worked for more th,an 2 years at Manhattan
 College on the development and application of a model
 of eutrophication in Lake Erie. His thesis research on the
 fate of sediment-associated hydrophobic organics was
 conducted at the U.S. EPA Environmental Research Lab
 in Gulf Breeze, Florida, where he also was involved in
                                                 8-1

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 8-2
                                                              National Sediment Bioaccumulatlon Conference
 microcosm studies of the transport and degradation of
 toxic organics in sediment.  Upon completion of his
 Ph.D., he accepted a faculty position in the Environmen-
 tal Engineering and Science Program at Manhattan Col-
 lege.  During his 14 years at Manhattan, Dr. Connolly
 conducted research in several areas, including the devel-
 opment  of models of toxic  chemical fate and
 bioaccumulation, eutrophication modeling,  and model-
 ing the fate and effects of genetically engineered micro-
 organisms introduced to surface waters.  While at Man-
 hattan he consulted  with HydroQual, Inc., on a wide
 range of problems. In June 1994 he left Manhattan to join
 HydroQual full-time.  His recent  work has included
 several bioaccumulation projects.   Among these are
 detailed analysis of bioaccumulation field data for EPA
 and modeling assessments of DDE bioaccumulation
 from sediments  on the  Palos  Verdes Shelf and PCB
 bioaccumulation from sediments in Green Bay.
 Philip M. Cook, Ph.D.

      Dr. Cook is the Acting Chief of the Ecological
 Toxicology Branch at the Mid-Continent Ecology Divi-
 sion of EPA's National Health and Environmental Ef-
 fects Laboratory in Duluth, Minnesota. Dr. Cook re-
 ceived a B.S. in Chemistry from Tufts University, an
 M.S. in Geochemistry from Colorado School of Mines,
 and a Ph.D. in Physical  Inorganic Chemistry from the
 University of Wisconsin.  Following graduate school in
 1972, he accepted a position as a research chemist at the
 U.S. EPA National Water Quality Laboratory at Duluth,
 where his initial work involved evaluation of risks asso-
 ciated with mining wastes in Lake Superior. His manage-
 ment positions since then have included Chief of the
 Hazardous Waste Research Branch and Associate Direc-
 tor for  Research  Operations.  Dr. Cook  has  diverse
 research experience that includes effects of fine particles
 such as asbestos; sediment contaminant bioavailability;
 ecological risks of organochlorine chemicals, especially
 PCDDs, PCDFs and PCBs; and methods for ecological
 risk assessment in the Great Lakes.
Judy L. Crane, Ph.D.

      Dr. Crane is the Team Leader of the Toxics Unit hi
the Division of Water Quality at the Minnesota Pollution
Control Agency (MPCA) in St. Paul, Minnesota. She
received a B.S. in Animal  Ecology from Iowa State
University, an M.S. in Ecology and Behavioral Biology
from  the University of Minnesota-Minneapolis, and a
Ph.D. in Water Chemistry from the University of Wis-
consin-Madison.  Her professional work experience in-
cludes contractual work with  the U.S. EPA Environmen-
tal  Research Laboratories in Duluth,  Minnesota
(1983-1985) and Athens, Georgia (1990-1992), as well
as consulting work with EVS  Consultants (1992-1995) in
Vancouver, British Columbia.  Dr. Crane was actively
involved in the Great Lakes  National Program Office's
Assessment and Remediation of Contaminated Sediments
 (ARCS) Program from  1990 to  1995, where she was
 responsible for conducting baseline and comparative
 human health risk  assessments for selected Areas of
 Concern.  She has also been involved in developing
 ecological risk assessment guidance for contaminated
 sites in Canada and developing interim sediment quality
 criteria for the Province of British Columbia. Dr. Crane
 is currently working as a research scientist for the MPCA,
 where she is leading several federally funded contami-
 nated  sediment investigations in the Duluth/Superior
 Harbor.
 Tudor T. Davies, Ph.D.

      Dr. Davies joined EPA in 1972, in the Office of
 Research and Development (ORD). From 1975 to 1979
 he was the Deputy Laboratory Dkector of the ORD Gulf
 Breeze Environmental Research Laboratory in Gulf
 Breeze, Florida.  He then became the  Director  of the
 Narragansett Environmental Research Laboratory from
 1979 to  1983;  during that time he also served  as the
 director of the EPA Chesapeake Bay Program. Prior to
 his current position as Dkector of the Office of Science
 and Technology, he was the Director for the Office of
 Water's Office of Marine and Estuarine Protection for 7
 years. Dr. Davies attended  the University of Wales in
 Swansea, and he holds a Bachelor of Science  and  a
 Doctorate in Geology.  He was an Associate Professor of
 Geology at the University of South Carolina.
Mario P. Del Vicario, M.S.

      Mr. Del Vicario serves as the Chief of the Place-
Based Protection Branch (PBPB) for Region 2 of the U.S.
Environmental Protection Agency. He began his em-
ployment at EPA in 1985 as the Assistant Chief of the
Marine and Wetlands Protection Branch and was Chief
of that branch from 1987 to 1996. Prior to his service with
EPA, Mr. Del Vicario was employed by the  U.S. Army
Corp of Engineers in the New York District from 1975 to
1985, where  he served as the Assistant  Chief of the
Environmental Analysis Branch.  He was a microbiolo-
gist with the NYC Health Department from 1973 to 1975.
      Mr. Del Vicario received a B.A. in biology from
Adelphi  University in 1971 and an M.S.  in  Marine
Science in 1973. From 1980 to 1986, he was  enrolled in
a Ph.D.  program in  Ecology in the  City  University
system.
Dominic M. Di Toro, Ph.D.

     Dr. Di Toro is aprincipal consultant for HydroQual,
Inc., in Mahwah, New Jersey. He received his B.E.E. in
Electrical Engineering from Manhattan College, and his
M.A. and Ph.D. in Electrical Engineering and Civil and
Geological Engineering from Princeton University.
Dr. Di Toro has specialized in the development and
application of  mathematical and statistical  models  to

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Proceedings
                                                                                                    8-3
stream,  lake, estuarine, and coastal water quality and
sediment problems.  He has published over sixty techni-
cal papers  and has  participated as Expert Consultant,
Principal Investigator, and Project Manager on numer-
ous water quality studies for industry and governmental
agencies. Recently,-his work has focused on the devel-
opment of sediment quality criteria and the development
of eutrophication and sediment flux models for nutrients
and metals.
L. fay Field, M.S.

      Mr. Field received a bachelor's degree1 from the
University of Michigan and an M.S. in Fisheries from the
University of Washington. Since 1986, he has worked as
a marine biologist for the National Oceanic and Atmo-
spheric Administration (NOAA), Office of Ocean Re-.
sources Conservation and Assessment, Hazardous Mate-
rials  Response and  Assessment  Division,  Coastal
Resources Coordination Branch in Seattle, Washington.
His responsibilities include providing technical support
to NOAA Coastal Resource Coordinators and EPA in the
evaluation of ecological risk to coastal marine resources
from hazardous waste sites.           .
Christopher G. Ingersoll, Ph.D.

      Dr. Ingersoll is a fisheries biologist with the U.S.
Geological Survey at the Environmental Contaminants
Research Center in Columbia, Missouri. He received his
bachelor's (1978) and master's (1982) from Miami Uni-
versity in Oxford, Ohio, and his doctorate (1986) from
the University of Wyoming in Laramie, Wyoming.  His
current research is focused on investigating the toxicity
and bioavailability of contaminates in sediment. He has
coordinated the development of chronic toxicity meth-
ods for the ampbipodHyalella azteca that.have been used
to evaluate contaminated sediments in ..several areas,
including the Great Lakes, the upper Mississippi River,
and the Clark Fork River in Montana. A second area of
research that  he has been working on with EPA is
developing  a  sediment bioaccumulation test  with the
oligochaete Lumbriculus variegatus. Dr. Ingersoll also
chairs the  ASTM Subcommittee  E47.03 on Sediment
Toxicology.  This subcommittee,  in  coordination with
EPA and Environment Canada, has developed a variety
of standard methods for evaluating sediment toxicity and
bioaccumulation.
 Michael J. Kravitz, MJV.

      Mr. Kravitz is a biologist in the Standards and
 Applied Science Division of the Office of Science and
 Technology at U.S. EPA Headquarters.  In this capacity
 he consults with, coordinates,  and provides technical
 support to EPA personnel and programs related to con-
 taminated sediment issues.  As  co-chair of EPA's
 Bioaccumulation Analysis Workgroup, Mr. Kravitz is
helping to lead the development of an EPA report on the
current status of bioaccumulation testing and interpreta-
tion for the purpose of sediment quality assessment.  He
has been responsible for the development of a number of
EPA and EPA/Army Corps of Engineers guidance docu-
ments, including the Draft Inland Testing Manual and:
QA/QC Guidance for Sampling and Analysis of Sedi-
ments, Water, and Tissues for Dredged Material Evalu-
ations. Prior to joining EPA, Mr. Kravitz worked in the
field of marine/estuarine benthic ecology at laboratories
in New York, Oregon, Florida, Virginia, and Massachu-
setts.  Mr. Kravitz received a B.S. in Biology from the
State  University  of New York at Stony Brook,  and an
M.A.  in Marine Science (major in Biological Oceanog-
raphy) from the College of William and Mary School of
Marine Science in Gloucester Point, Virginia.
Peter F. Landrum, Ph.D.

      Dr. Landrum is the head of the Biogeochemical
Sciences Division of NOAA's Great Lakes Environmen-
tal Research Laboratory in Ann Arbor, Michigan, where
he  oversees  research on  aquatic contaminants, bio-
geochemistry, and ecosystems studies directed to exam-
ine the effects of anthropogenic impacts on the Great
Lakes as well as the day-to-day  administration for the
division. He received his B.S. in Chemistry from Cali-
fornia State College, San Bernadino,  and Ph.D. in Phar-
macology and Toxicology from the University of Cali-
fornia, Davis. He spent the next 2 years working as a
research associate for the University "of Georgia at the
Savannah River Ecology Laboratory, Aiken, South Caro-
lina.  His research focused on the fate, transport, and
bioaccumulation of polycyclic aromatic hydrocarbons in
freshwater stream systems.  He then moved to the Great
Lakes Environmental Research Laboratory as a research
chemist to conduct research in  the bioavailability and
bioaccumulation of  organic contaminants by aquatic
invertebrates with an emphasis on the benthos.  Over the
last 15 years, his research has  examined the role of
dissolved organic matter on the bioavailability of water-
borne contaminants and the influence of sediment char-
acteristics on sediment-associated contaminants. More
recent work has examined the utility  of whole-body
residue levels to determine the dose required to produce
contaminant toxicity.  In addition to his  research,
Dr. Landrum served as a part-time instructor in environ-
mental toxicology at Eastern Michigan University.
 Alex Lechich, M.S.

      Mr. Lechich has been an environmental scientist
 with EPA Region 2 since 1988, principally working on
 ocean disposal, contaminated sediment, and dredging
 issues. Prior to that, he worked for 3 years with the New
 York District Corps of Engineers in its regulatory pro-
 gram. Mr. Lechich received a B.S. in Biology from the
 State University of New York at Stony Brook in 1983 and
 an M.S. in Marine Environmental  Science from Stony

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8-4
         National Sediment Bioaccumulation Conference
Brook's Marine Sciences Research Center in 1984.  He
served in the U.S. Army for 3 years hi the late 1970s,
where he collected and analyzed ambient air samples
from nerve gas de-commissioning areas on a base near
Denver.  Prior to completing  his  undergraduate and
graduate work, Mr. Lechich worked for several industrial
chemical companies, mainly doing organic chemistry
product development and quality control. Following his
graduate work, he worked for  the New York Power
Authority.
Henry Lee II, Ph.D.

      Dr. Lee is with the Pacific Northwest Estuarine
Ecosystem Study of the Western Ecology Division of
EPA, located at the Newport, Oregon, laboratory. He
received his B.S. in Biology from Rollins College and his
Ph.D. in Marine Sciences from the University of North
Carolina. After a postdoctoral position at the University
of Maryland and an NRC postdoctoral position with
EPA, Dr. Lee joined the EPA staff at Newport, Oregon.
He spent the next decade working on bioaccumulation
and contaminated sediments, including investigations on
the  application of equilibrium  partitioning  and
toxicokinetic models to benthic invertebrates, and the
development of bioassay methods. His work on contami-
nated sediments culminated when Dr. Lee directed an
ecological risk assessment of sediment-associated DDT.
During this period, Dr. Lee also was the Program Man-
ager for EPA's Marine Stratospheric Ozone  Depletion
Program. He is presently directing a research program to
assess the cumulativeeffects of chemical andnonchemical
(e.g., sedimentation, introduced species) stressors on an
ecosystem scale.
Lynn Scott McCarty, Ph.D.

     Dr.  McCarty operates L.S.  McCarty Scien-
tific Research & Consulting, an ecotoxicological con-
sulting business based in Oakville, Ontario, Canada. He
received B.S. and M.S. degrees from Brock University
and a Ph.D. from the University of Waterloo.  He has
spent over 18 years examining various aspects of envi-
ronmental contamination, ecotoxicology,  and environ-
mental risk assessment.  This included a number of years
as an environmental scientist and ecological studies
group manager at MacLaren-Plansearch (Lavalin), sci-
entific consultant for the Health Studies Service of the
Ontario Ministry of Labour,  and senior scientist with
CanTox, Inc. He has been involved in a wide variety of
projects  examining environmental impacts and/or hu-
man health effects for an assortment of situations and
contaminants/stresses.  This included the production or
critical review of a number  of air and water quality
guidelines, as well as risk assessments hi Canada and the
USA.
      Dr. McCarty's scientific interests include Quanti-
tative Structure-Activity Relationships  (QSAR),
toxicokinetics, mixture toxiciiy, residue-based potency
estimation, and risk assessment.  He has been an invited
expert dealing with human and environmental health at
a number of workshops sponsored by CNTC, SETAC,
U.S. EPA, and U.S.  Army  Corps of Engineers:  In
addition to reports for clients, he continues to publish in
the primary scientific literature, contribute to book chap-
ters, and make presentations at professional  scientific
meetings, as well as hi courts, regulatory hearings, and
public meetings.
David R. Mount, Ph.D.

      Dr. Mount is a research fishery biologist with
EPA's Office of Research and Development, Mid-Con-
tinent Ecology  Division,  Duluth, Minnesota.  He  re-
ceived his B.A. hi Biology with a statistics concentration
from St. Olaf College in Northfield,,Minnespta, and his
Ph.D. in Zoology and Physiology (emphasis in aquatic
toxicology) from the University of Wyoming.  After a
year of postdoctoral research at the Fish Physiology and
Toxicology Laboratory at the  University of Wyoming,
Dr. Mount worked for 5 years  at ENSR Consulting and
Engineering as a senior aquatic toxicologist, and as  the
manager of the Environmental Toxicology Department.
Dr. Mount joined the federal government in 1993 as  the
Deputy Chief Biologist  at the  National  Biological
Service's National Fisheries Contaminant Research Cen-
ter, before transferring to his current position with EPA.
Dr. Mount's research interests include-effluent and sedi-
ment toxicology, and the effects of major ions on fresh-
water organisms. His  current research centers on sedi-
ments,  including  the  development  of  Toxicity
Identification Evaluation (TIE) procedures and evalua-
tion of the bioavailability  of sediment contaminants.
Wayne R. Munns, Jr., Ph.D.

     Since 1995, Dr. Munns has been a Research Ecolo-
gist (Ecological Risk Assessor) and Leader of the Eco-
logical Significance Team in EPA's National Health and
Environmental  Effects  Research  Laboratory,
Narragansett, Rhode Island, which is responsible for
conducting ecological effects research  to reduce the
uncertainties associated with risk assessment.  He re-
ceived his B.A. in Biology from the University of Wash-
ington  and his Ph.D. in Biological Sciences from the
University of Rhode Island.  In 1983, he joined Science
Applications International Corporation,  ultimately ac-
cepting positions as senior scientist, division manager,
and assistant vice president. Over the past 13 years,
Dr. Munns has served as  principal  investigator in  a
number of marine and estuarine ecological risk assess-
ment case studies involving contaminated  sediments,

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Proceedings
                                              8-5
and has  conducted research evaluating the effects  of
chemical stressors on the population dynamics of aquatic
organisms.


Thomas M. Murray, M.S.

      Mr. Murray is Chief of the Exposure Assessment
Branch in the Office of Pollution Prevention and Toxics
at EPA Headquarters.  In this capacity, he is responsible
for integrating the assessment of total chemical exposure
to humans and the environment in support of OPPT's
regulatory ,and nonregulatory  program activities; sup-
porting OPPT's testing and existing chemical programs
by  providing integrated assessments of chemical  expo-
sure to humans and the environment; providing scientific
assessment of total chemical exposure, including chemi-
cal and biological fate; and providing exposure assess-
ment and project management support to various OPPT
Design for the Environment and Pollution Prevention
Program activities. Mr. Murray has been with the Office
of Pollution Prevention and Toxics since 1985. Prior to
that he spent 14 years with EPA's Office of Water.
He received his  B.S. in Biology from Mt. St. Marys'
College  and   an  M.S.  in  Biology  from the
American University.


Dorothy E. Patton, Ph.D.

      Dr. Patton  holds several positions at the U.S.
Environmental Protection Agency. She is the Executive
Director of EPA's Science Policy Council, a new Agency
organization established to address significant science
policy issues that go beyond program and regional bound-
, aries. She also directs the Office of Science Policy and the
Office of Regulatory  and Science Integration.  From
1985 through July 1994, Dr. Patton was  the Executive
Director  of EPA's Risk Assessment Forum, a standing
committee of senior EPA scientists charged with devel-
oping Agency-wide guidance on selected risk science
issues. She also chaired that group from  1989 to 1995.
Dr. Patton began her EPA career in 1976  as an attorney
in the Office of General Counsel, where she worked on
legal and scientific issues arising under the laws relating
to  pesticides, toxic substances, and the air  program.
Before joining EPA, Dr. Patton was an Assistant Profes-
sor of Biology in the City University of New York (York
College), and she did postdoctoral research in cellular
and developmental biology at the Albert Einstein Col-
lege of Medicine in New  York.  She has a J.D. from
Columbia University School of Law, aPh.D in develop-
mental biology from the University of Chicago,  and a
bachelor's degree in chemistry from the University of
Wisconsin.
Robert L. Paulson, M.S.

     Mr. Paulson is an environmental toxicologist in the
Water Quality Modeling Section of the Wisconsin De-
partment of Natural Resources'  Bureau of Watershed
Management. He received his B.S. in Water Resources
from the University of Wisconsin-Stevens Point and his
M.S. in  Fisheries  from the University of Missouri.
Mr. Paulson's thesis research focused on field validation
and predictability of laboratory methods of assessing the
effects of  contaminants. "Prior to  joining  WDNR,
Mr. Paulson was a staff toxicologist with The Johns
Hopkins University, Applied Physics Laboratory, where
his work centered on effluent and single-chemical estua-
rine and freshwater toxieity testing.  Mr. Paulson also
spent a  brief period  of time in  private  consulting;
Mr. Paulson joined WDNR as the coordinator  of .the
whole effluent toxieity testing for the point source dis-
charge permit program.  His current assignment is to
coordinate WDNR's technical staff in conjunction with
the efforts of the Fox River Coalition to develop a whole-
river sediment strategy.
Amy E. Pelka, M.S.

     Ms, Pelka is an environmental health scientist in
the Office of Strategic Environmental Analysis in EPA
Region 5, Chicago, Illinois.  She received her B.S. in
Zoology  (specialization in cellular biology) from  the
University of Wisconsin-Madison and her M.S. in Mi-
crobiology/Immunology from Northwestern University.
After graduate school she began working with Region 5,
in the Water Division, on sedirnents and  water quality
standards. She has worked for the Water Division and
now the Strategic Analysis office for the past 5 years,
primarily as a human health risk assessor.  She has
worked on several Superfund and other enforcement
cases, as well as various technical and risk policy issues.
Her primary areas of focus have been sediment sites,
bioaccumulation, risk assessment policy,  and commu-
nity-rbased environmental protection.
James F. Pendergast, M.S.

     Mr. Pendergast is currently  Acting Director
of the NPDES Permits Division at U.S. EPA Headquar-
ters. In this capacity, he directs national activities and
initiatives for the NPDES permits, pretreatment, and
sludge programs.  He has worked on reauthorization of
the Clean Water Act as a special assistant to EPA's
Assistant Administrator for Water and as Chief of the
Wafer  Quality and  Industrial Permits Branch in  the
NPDES Permits Division. He has also worked in EPA

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8-6
         National Sediment Bioaccumulation Conference
Region 6 in the NPDES permit and Superfund programs.
Prior to joining EPA, Mr. Pendergast  was a project
manager at Limno-Tech, Inc., in Michigan, where he
developed models of water quality impacts from nonpoint
and point sources. He received a B.S. in  Environmental
Engineering  and  an  M.S. in  Water Resources
Engineering from the  University of Michigan and is a
registered engineer.
Richard J. Pruell, Ph.D.

      Dr. Pruell is a research chemist at the Atlantic
Ecology Division (Narragansett, Rhode Island) of EPA's
National Health and Ecological Effects Laboratory.  He
received a B.A. hi Biology from Merrimack College, an
M.S.  in Marine Biology from Southeastern Massachu-
setts University, and a Ph.D. in Chemical Oceanography
from the Graduate School of Oceanography of the Uni-
versity of Rhode Island. Since receiving his degree in
1984, Dr. Pruell has  worked at the Narragansett EPA
laboratory on issues related to the biogeochemistry of
organic contaminants in marine ecosystems.
Mary C. Reiley, M.S.

      Ms. Reiley is the Team Coordinator for the Eco-
logical Criteria Team within the Health and Ecological
Criteria Division. She received her B.S. in Biology from
the College of William and  Mary  and her M.S. in
Environmental Biology from George Mason University.
Ms. Reiley joined the Office of Science and Technology
in 1991 to coordinate the sediment quality criteria pro-
gram. Prior to that she spent 7 years in the Office of Water
Enforcement Program, where she was the Team Leader
for the Toxics Team and involved in a variety of issues
including  permitting limits set below  detection, whole
effluent toxicity, and compliance negotiations. Her
current role  as Ecological Criteria Team Coordinator
maintains  her involvement in methodology and criteria
development and technical support for aquatic life as-
sessments, sediment quality assessment, and whole ef-
fluent toxicity testing.  The team works closely with the
Surface Water Assessment Team, on which Ms.  Reiley
serves as  the program lead for integrated  pathways
analysis for criteria development.
Norman I. Rubinstein, M.S.

     Mr. Rubinstein is the Acting Division Director for
the National Health and Environmental Effects Research
Laboratory, Atlantic Ecology Division, in Narragansett,
Rhode Island. He received his B.S. in Biology from the
City College of New ,York and his M.S. in Marine
Science from the University of West Florida. He joined
EPA in 1976 as a research aquatic biologist at the
Environmental  Research Laboratory,  Gulf Breeze,
Florida. In 1983 Mr. Rubinstein joined the research staff
at the Environmental Research Laboratory, Narragansett,
Rhode Island where he focused his  studies on the
bioavailability of contaminants in sediments. He became
Chief of the Research Exposure Branch at the Narragansett
Laboratory in 1989 and was appointed Deputy Director for
Research in 1994.  He has  been the  apting Division
Director at Narragansett since the ORD laboratory reorga-
nization in 1995. Mr. Rubinstein has been associated with
EPA's research efforts in support of the Ocean Disposal
Program since the development of the original dredged
material testing manual (the "Green Book") in 1976.
Burt K. Shephard, M.S.

     Mr. Shephard is a senior ecotoxicologist with URS
Greiner, Inc., in Seattle, Washington.  He received his
B.S. in  Chemistry and M.S. in Environmental Health
from Purdue University.  He also has completed course
work toward a Ph.D. in Fisheries Biology from Iowa State
University, where he is a past recipient of the Society of
Environmental Toxicology and Chemistry Pre-Doctoral
Fellowship Award. Mr. Shephard has nearly 20 years of
experience working to evaluate the environmental im-
pacts  or ecological risks of metals, nutrients, PCBs,
chlorinated insecticides, and PAHs for both environmen-
tal consulting firms and EPA.  This work has taken him
throughout the United States, as well as to several foreign
countries. Mr. Shephard's current work involves defin-
ing ecological risks to aquatic biota from bioaccumulated
chemicals.
Elizabeth Southerland, Ph.D.

     Dr. Southerland is Acting Director of the Standards
and Applied Science Division in EPA's Office of Water
in Washington, D.C. Dr. Southerland received her Ph.D.
in Environmental Science and Engineering from Virginia
Polytechnic Institute and State University. Over the past
25 years, she has held a variety of positions in state and
local government, consulting engineering, and EPA. Dr.
Southerland  is currently the Acting Director of EPA's
Standards and Applied Science Division, which is re-
sponsible for the national water quality standards pro-
gram and environmental assessments in support of water
quality- and sediment quality-based controls.
Robert V. Thomann, Ph.D.

     Dr. Thomann is Professor of Environmental Engi-
neering at Manhattan College.  He received a bachelor's
degree in Civil Engineering from Manhattan College hi
1956, a master's degree in Civil Engineering from New
York University in 1960, and a Ph.D. in Physical Ocean-
ography from New York University in 1963. He spent 10
years with the U.S. Public Health Service from 1956 to
1966, during which time he was Technical Director for
the Delaware Estuary Study.  Dr. Thomann joined the
faculty of Manhattan College in 1966. His work has been
in mathematical modeling of water quality and ecosystem

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, Proceedings	

 fate, transport,  and transformation processes.   He has
 published about 50 papers and two books, has lectured at
 a variety of institutions, and has received several honors
 for his research work. Dr. Thomann has worked on many
 major water bodies in the United States and abroad and
 is currently doing research on modeling bioaccumulation
 processes including the transfers of PCBs in the Hudson
 estuary aquatic  food web.
                                              8-7
 Ecology in Olympia, Washington, for the past 3 years.
 She received a B.S. in Human Ecology/Public Policy
 from Rutgers University and an M.P.H. in Environmental
 Health from the University of California, Berkeley. Prior
 to working for the Department of Ecology, Ms. Weiss
 worked as a pesticide policy specialist and organizer for
 the environmental and consumer group Public Citizen in
 Washington, D.C,
 Nelson A. Thomas, B.S.

      Mr. Thomas received bis B.S. in Natural Resources
 (fisheries) from the University of Michigan. He was the
 limnologist for the State of Ohio when Lake Erie was
 discovered to be greatly affected by eutrophication. He then
 joined the U.S. EPA and served as chief biologist for the
 Office of Enforcement and Standards. After 10 years, he
 assumed a research position to conceive, supervise, and
 conduct large lakes research. Currently, as senior advisor
 for national programs with EPA, he develops and coordinates
 freshwater research for the control of toxic chemicals. His
 areas of responsibility  include water quality criteria,
 complex effluent toxicity testing, sediment quality criteria;
 and integrated watershed assessment for  ecosystem
 protection.
Marc L. Tuchman, Ph.D.

     Dr. Tuchman received his B.S. in Biology from
Colgate University and his Ph.D. in Natural Resources
from the University of Michigan. He has been with EPA
for the past 12 years, working in the Waste Division and
Water Division prior to his current position in the Great
Lakes National Program Office (GLNPO). Over the past
10 years, Dr. Tuchman has been involved in a variety of
contaminated sediment and dredging issues.  For 6 years
he was actively involved  in EPA's Assessment and
Remediation of Contaminated Sediments (ARCS) Pro-
gram, having served as Program Manager for the latter 2
years of the program. Dr. Tuchman currently serves as
team leader  of GLNPO's  Sediment Assessment and
Remediation Team, where he is responsible for coordi-
nating  GLNPO's sediment assessment and remediation
activities in the Great Lakes basin.
Laura B. Weiss, M.P.H.

     Ms: Weiss is a toxicologist who has been the
project manager for the development of health-based
sediment criteria for the Washington State Department of
 Lawrence J. Zaragoza, Ph.D.

      Dr. Zaragoza received his doctorate in Environ-
 mental Science and Engineering from the University of
 California at Los Angeles in 1982. He started with EPA
 in  1979 in the  Office of Air Quality  Planning and
 Standards.  Today, Dr. Zaragoza works for EPA's
 Office of Emergency and  Remedial Response, which
 administers  the Headquarters • component  of the
 Superfund Program.  His responsibilities at EPA have
 included representing the OERR on issues related to
 contaminated sediments, the identification of research
 needs for- the air and hazardous waste programs, and
 Project Officer  responsibilities for the Interagency
 Agreements with the Agency for Toxic.Substances and
 Disease Registry (ATSDR) and the National Institute
 for  Environmental Health  Statistics .(NIEHS).
 Dr. Zaragoza has experience in drafting of EPA regula-
 tions (e.g., National Ambient Air Quality Standards, air
 toxics, revisions to the Hazard Ranking System) and
 guidances (e.g., Risk Assessment Guidance for
 Superfund and Capacity Assurance Guidance).
Maurice Zeeman, Ph.D.

     Dr. Zeeman is Chief of the Environmental Effects
Branch in the Health and Environmental Review Divi-
sion of OPPT at EPA Headquarters.  He  directs  16
professional experts in their assessment of the potential
ecological hazards  and risks of thousands of new and
existing industrial chemicals evaluated under the Toxic
Substances Control Act (JSCA).  He also teaches a
course in environmental toxicology in the Department
of Pharmacology and Toxicology for  the Graduate
School at the National Institutes  of Health. Prior to
joining EPA, he was an expert toxicologist for the U.S.
Food and Drug Administration, where he evaluated the
effects of chemicals on humans (under the FD&C Act)
and on the environment (under NEPA).  Dr. Zeeman
received  a Master's in Zoology/Ecology  from
UCLA and a Ph.D.  in Biology from Utah  State
University.

-------

-------
            National  Sediment  tSioaeeumulation
                                    September 11-13,1996
                                         Hyatt Regency
                                      Bethesda, Maryland

                                      FINAL AGENDA
 Sponsored by:
 Office of Water/Office of Science and Technology
 Office of Research and Development
Wednesday,  September  1 1

7:30-8:30   Registration

8:30-8:45   Welcome and Introduction
           Dr. Elizabeth Southerland and
           Dr. Thomas Armitage
           Office of Science and Technology
           U.S.  Environmental Protection Agency

BIOACCUMULATION OVERVIEW AND APPROACHES

8:45-9:15   Contaminated Sediments: State of the
           Science and Future Research Directions
           Dr. Oilman D. Veith, Associate Director for
           Ecology
           National Health and Environmental Effects
           Research Laboratory
           Office of Research and Development
           U.S.  Environmental Protection Agency

Field and Laboratory Methods for Measuring
Bioaccumulation
           Moderator: Dr. Peter Chapman
           EVS  Environmental Consultants, Ltd.

9:15-9:40   Methods for Assessing Sediment
           Bioaccumulation in Marine/Estuarine
           Benthic Organisms
           Dr. Henry Lee
           Office of Research and Development
           U.S.  Environmental Protection Agency

9:40-10:05  Methods for Assessing Bioaccumulation
           of Sediment-Associated Contaminants
           with  Freshwater Invertebrates
           Dr. Christopher Ingersoll
           Environmental Contaminants Research Center
           U.S. Geological Survey
10:05-10:20 Break

10:20-10:45 Kinetic Models for Assessing
          Bioaccumulation
          Dr. Peter Landrum
          Great Lakes Environmental Research
          Laboratory
          National Oceanic and Atmospheric
          Administration

10:45-11:15 Discussion/Question and Answer
          Session

11:15-12:30 Lunch

Interpretation and Applications of
Bioaccumulation Results           '
          Moderator: Dr. Richard Pruell
          Office of Research and Development
          U.S. Environmental Protection Agency

12:30-12:55 Reference Sediment Approach for
          Determining Sediment Contamination
 '  '   -    Mr. Norman Rubinstein
          Office of Research and Development
          U.S. Environmental Protection Agency

12:55-1:20  Development of Tissue Residue
          Threshold Values
          Dr. David Mount
          Office of Research and Development
          U.S. Environmental Protection Agency

1:20-1:45   Use of Tissue Residue Data in Exposure
          and Effects Assessments for Aquatic
          Organisms
          Mr. L. Jay Field
          National Ocean Service
          National Oceanic and Atmospheric
          Administration

-------
                                  Final Agenda
1:45-2:10  Comments on the Significance and Use
          of Tissue Residues in Sediment
          Toxicology and Risk Assessment
          Dr. Lynn McCarfy
          LS McCarty Scientific Research & Consulting

2:10-2:35  Quantification of Ecological Risks to
          Aquatic Biota from Bioaccumulated
          Chemicals
          Mr. Burt Shephard
          URS Greiner, Inc.

2:35-3:05  Discussion/Question and Answer
          Session

3:05-3:25  Break

Modeling Bioavailability of Sediment
Contaminants
          Moderator: Mr. Nelson Thomas
          Office of Research and Development
          U.S. Environmental Protection Agency

3:25-3:50  Equilibrium Partitioning and Organic
          Carbon Normalization
          Dr. Dominic Di Toro
          HydroQual, Inc.

3:50-4:15  Estimating Bioaccumulation Potential in
          Dredged Sediment Regulation
          Dr. Victor McFarland
          Waterways Experiment Station
          U.S. Army Corps of Engineers

4:15-4:40  Development of Bioaccumulation Factors
          for Protection of Fish and Wildlife in the
          Great Lakes
          Dr. Philip Cook
          Office of Research and Development
          U.S. Environmental Protection Agency

4:40-5:00  From Modeling to Criteria: Integrated
          Approach to Criteria Development
          Ms. Mary Reiley
          Office of Science and Technology
          U.S. Environmental Protection Agency

5:00-5:30  Discussion/Question and Answer
          Session

6:00-7:00  Welcome Reception
Thursday, September 12
Food Chain Models and Bioenergetics
          Moderator: Dr. Lawrence Burkhard
          Office of Research and Development  .
          U.S. Environmental Protection Agency

8:30-9:00  Food Chain Models for Predicting
          Bioaccumulation
          Dr. Frank Gobas
          Simon Fraser University

9:00-9:30  Use of Food Web Models to Evaluate
          Bioaccumulation Data
          Dr. John Connolly
          HydroQual, Inc.

9:30-10:00 Bioaccumulation Modeling of PCBs in
          the Hudson Estuary: A Review and
          Update
          Dr. Robert Thomann
          Manhattan College

10:00-10:30 Discussion/Question and Answer
          Session

10:30-10:45 Break

BIOACCUMULATION AND RISK ASSESSMENT

10:45-11:15 Risk Assessment Overview
          Dr. Dorothy Patton
          Office of Research and Development
          U.S. Environmental Protection Agency

Human Health-Based Risk Assessment
          Moderator: Dr. Marc Tuchman
          Great Lakes National Program Office
          U.S. Environmental Protection Agency

11:15-11:45 Methodology for Assessing Human
          Health-Based Risks
          Dr. Judy Crane
          Minnesota Pollution Control Agency

11:45-1:00 Lunch

-------
                                  Final Agenda
 Case Studies:

 1:00-1:45  Bioaccumulation Models and
           Applications: Setting Sediment Cleanup
           Goals in the Great Lakes
           Ms.AmyPelka
           Region 5
           U.S. Environmental Protection Agency

 1:45-2:15  Use of Human Health- and Ecological-
           Based Goals in Developing a Whole
           River Sediment Strategy: Fox River, Wl
           Mr. Robert Paulson
           Wisconsin Department of Natural
         .  Resources

 2:15-2:45  Development of Health-Based Sediment
           Criteria for Puget Sound
           Ms. Laura Weiss
           Washington Department of Ecology

 2:45-3:15  Development of Bioaccumulation
           Guidance for Dredged Material
           Evaluations in EPA Region 2
           Mr. Alex Lechich
           Region 2
           U.S. Environmental Protection Agency

 3:15-3:45   Discussion/Question and Answer
           Session

 3:45-4:00   Break

 Ecological-Based Risk Assessment
           Moderator: Dr. James Andreasen
           Office of Research and Development
           U.S. Environmental Protection Agency

 4:00-4:30   Use of Bioaccumulation Data in Aquatic
           Life Risk Assessment
           Dr. Wayne Munns
           Office of Research and Development
           U.S. Environmental Protection Agency

4:30-5:00   Wildlife Risk Assessment
           Dr. David Charters
•          Office of Solid Waste and Emergency
           Response
           U.S. Environmental Protection  Agency

5:00-5:30    Discussion/Question and Answer
           Session
 Friday, September  13  	

 BIOACCUMULATION RESULTS AND DECISION-
 MAKING

 Integrating Bioaccumulation Results into EPA's
 Decision-Making Process
           Moderator: Dr. Elizabeth Southerland
           Office of Science and Technology
           U.S. Environmental Protection Agency

 8:30-8:40   Opening Remarks
           Dr. Elizabeth Southerland
           Office of Science and Technology
           U.S.^Environmental Protection Agency

 8:40-9:00   Bioaccumulation Testing and
           Interpretation for the Purpose of
           Sediment Quality Assessment: Status
           and Needs
           Mr. Michael Kravitz
           Office of Science.and Technology
           U.S. Environmental Protection Agency

 9:00-10:30  Panel Presentations

           •  Superfund Program
             Dr. Lawrence Zaragoza
           •  NPDES Program
             Mr. James Pendergast
           •  Office of Pollution Prevention and Toxics
             Mr. Thomas Murray
             Dr. Maurice Zeeman
           •  Dredged Material Program
             Mr. Craig Vogt
             Mr. Mario Del Vicario

10:30-10:45 Break

10:45-12:00 Panel Discussion

          •  Common Elements Among  Programs
          •  Barriers to Decision-Making
          •  Recommendations

12:00-12:30 Future Needs/Conference Wrap Up

-------

-------
                                       National Sediment Bioaccumulation Conference

                                                      September 11-13,1996
                                                        Bethesda, Maryland

                                                      LIST OF ATTENDEES
ToddAbel
McLaren/Hart - ChemRisk
1685 Congress Street
Portland, ME 04102
PH 207/774-0012
FX 207/774-8263
JimAhl    _/;..   '  -'.  •
Maryland D^R/Tawes State Office Building
580 Taylor Ave (Building E-2)
Annapolis, MD 21401
PH 410/974-2985,..:'
FX 410/974-2833
 Robert Allen
 Delaware DNREC
 715 Grantham Lane.
 Newcastle, DE 19720
 PH 302/323-4540
 FX 302/3234561
David Altfater  •
Ohio EPA
1685 Westbelt Drive
Columbus, OH 43228
PH 614/728-3400
FX 614/728-3380
James Andreasen (8623)
U.S. EPA/ORD/NCEA
401 M Street, SW
Washington, DC 20460
PH 202/260-5259
FX 202/260-8719
Alan Anthony
VA Department of Environmental Quality
P.O. Box 10009
Richmond, VA 23240-0009
PH 804/698-4114
FX 804/698-4522
Thomas Ardito
NOAA/NMFS
1315 East-West Highway, SSMC3, F/HP5
Silver Spring, MD 20910-3282
PH 301/713-0174x106
FX 301/713-0184'
Thomas Armitage (4305)
U.S.EPA/OST
401 M Street, SW
Washington, DC 20460
PH 202/260-5388
FX 202/260-9830
Ray Arnold
Exxon Biomedical Sciences
Mettlers Road, CN 2350
East Millstone, NJ 08875
PH 908/873-6305
FX 908/873-6009    '
ArtAsaki                           •
U.S. Army Ctr for Health Prom. & Prev. Medicine
ATTN: MCHB-DC-ES, 5158 Blackhawk Road
Aberdeen Proving Ground, MD 21020-5422
PH 410/671-3816   .
FX 410/671-8104               ,    •
Denise Baker
U.S. Fish and Wildlife Service
3704 Griffin Land, SE, Suite 102
Olympia, WA 98501
PH 360/753-5821
FX 360/753-9008   .   •    ,
Michael Barbachem
URS Consultants, Inc.
5606 Virginia Beach Blvd.
Virginia Beach, VA 23462-5631
PH 757/499-4224
FX 757/473-8214
Robert Barrick   ,
PTI Environmental Services
15375 SE 30th Place, #250
Believue, WA 98007
PH 206/643-9803-'
FX 206/643-9827  •
Justine Barton (ECO-083)
U.S. EPA Region 10
1200 6th Ave.
Seattle, WA 98101
PH 206/553-4974
FX 206/553-1775
Steven Bay
So. California Coastal Water Research
7171 Fenwick Lane
Westminster, CA 92683
PH 714/894-2222
FX 714/894-9699
Chris Beaverson
U.S. EPA Region 10/NOAA
1200 Sixth Avenue
Seattle, WA 98101
PH 206/553-2101
FX 206/553-0124
Russell Bellmer
NOAA/NMFS •  -
1315 East-West Highway
Silver Spring, MD 20910-3226
PH 301/713-0174
FX 301/713-0184
Joanne Benante
U.S. EPA Region 4
345 Courtland Street, NE
Atlanta, GA 30365
PH'404/347-3555
FX 404/347-3058

-------
                                               LIST OF ATTENDEES (continued)
Channing Bennett
US. EPA Region 4
345 Courtland Street
Atlanla, GA  30365
PH 404/347-3555, X6317
FX 404/347-1918
 Walter Berry
'U.S. EPA
 27 Tarzwell Drive
 Narragansett, Rl 02882
 PH 401/782-3101
 FX 401/782-3030
Jeff Bigler (4305)
U.S. EPA/SASD
401 M Street, S.W.
Washington, DC  20460
PH 202/260-1305
FX 202/260-9830
David Bleil
Maryland Department of Natural Resources
580 Taylor Ave (Tawes State Office Bldg)
Annapolis, MD 21401
PH 410/974-2988
FX 410V974-2833
 Robert Boethling (7406)
 U.S. EPA/EETD/EAB
 401 M Street, S.W.
 Washington, DC 20460
 PH 202/260-3912
 FX 202/260-0981
Callie Bolattino (G-9J)
U.S. EPA Region 5/Great Lakes Nat'l Prog. Ofc
77 W. Jackson Blvd
Chicago, IL 60604
PH 312/353-3490
FX 312/353-2018
Suzanne Bollon
NOAAMMFS/ST2
2421 S.Dinwiddie Street
Arlington, VA 22206
PH 301/713-2367
FX 301/713-2813
 Weldon Bosworth
 Dames and Moore
 5 Industrial Way
 Salem, NH 03079
 PH 603/893-0616
 FX 603/893-6240
Dumont Bouchard
U.S. EPA/ORD
460 College Station Road
Athens, GA 30605
PH 706/546-2248
FX 706/546-2459
Lisa Bradford
U.S. EPA Region 3
841 Chestnut Street
Philadelphia, PA 19107
PH 215/566-3363
FX 215/566-3001
 Todd Bridges
 U.S. Army Corps of Engineers
 USAE WES ES-F, 3909 Halls Ferry Road
 Vicksburg, MS 39180
 PH 601/634-3626
 FX 601/634-3713
Tom Brosnan
New York City Department of Env. Protection
RM 213, New Administration Bldg
Wards Island, NY 10035-6096
PH 212/860-9378
FX 212/860-9570
 Dail Brown
 National Marine Fisheries Service
 1315 East-West Highway
 Silver Spring, MD 20910-3226
 PH 301/713-2325
 FX 301/713-1043
  Kurt Buchholz
  Battelle Ocean Sciences
  2101 Wilson Blvd., Suite 800
  Arlington, VA  22201-3008
  PH 703/875-2947
  FX 703/527-5640
 Al Buoni
 Labat-Anderson Incorported
 8000 Westpark Drive, Suite 400
 McLean, VA 22102
 PH 703/506-9600
 FX 703/5064646
 Kelly Burch
 PA Dept. of Environmental Protection
 230 Chestnut Street
 Meadville, PA 16335
 PH 814/332-6816
 FX 814/332-6125
  Lawrence Burkhard
  U.S. EPA/ORD/NHEERL
  6201 Congdon Blvd
  Duluth, MN 55804
  PH 218/720-5554
  FX 218/720-5539
 John Burleson
 Marine Corps Base Quantico/Nat. Res. Env. Affr Br
 3040 McCawley Ave., Suite 2              ,
 Quantico.VA 22134
 PH  703/784-4030
 FX  703/784-4953
 Janet Burn's
 ChemRlsk
 109 Jefferson, Suite D
 Oak Ridge, TN 37830
 PH 423/483-5081
 FX 423/482-9473
  Dennis Burton
  University of Maryland
  P.O. Box 169
  Queenstown, MD 21658
  PH 410/827-8056
  FX 410/827-9039    ,
 Scott Burton
 Maxus Energy Corporation
 1015 Belleville Turnpike
 Kearny.NJ 07032
 PH 201/955-0855
 FX 201/955-1063

-------
                                                LJST:QF ATTENDEES (continued)
 Jonathan Butcher
 The Cadmus Group
 1920 Highway 54, Suite 100
 Durham, NC 27713
 PH  919/544-6639
 FX 919/544-9453
 Richard Cahill
 Illinois State Geological Survey
 615 East Peabody Drive
 Champaign, IL 61820   '••
 PH  217/244-2532
 FX  217/244-2785
 Teresa Caputi
 Malcolm Pirnie, Inc.
 One International Blvd.
 Mahwah, NJ 07495
 PH 201/529-0858 ext 303
 FX 201/529-0855
 Norman Carlin
 Sidley and Austin
 875 Third Avenue
 New York, NY 10022
 PH 212/908-2325
 FX 212/908-2021'
•Thomas Carpenter
 ICF Kaiser
 9300 Lee Highway
 Fairfax, VA 22031
 PH 703/218-2757
•FX 703/934-3178
 JodiCassell.  '            ' .   .
 UC Sea Grant Extension
 300 Piedmont Avenue, Room 305A
 San Bruno, CA '94066
 PH 415/871-7559
 FX 415/871-7399         '.'"'..
 Peter Chapman         .,-...
 EVS Environmental Consultants -
 195PembertonAve            ,
 North Vancouver, Brit.Cq.,  V7P 2Ri
 PH 604/986-4331
 FX 604/662-8548
 Dave Charters
 U.S. EPA, Environmental Resp. Branch
 2890 Woodbridge Avenue, Bldg 18, MS:101
 Edison, NJ 08837-3679
 PH 908/906-6825     "•' ' '   ,    ,•
 FX 908/321-6724       ,   '
 Eugenia Chow
 U.S. EPA Region.5
 77 West Jackson Blvd
 Chicago, IL 60604
 PH 312/353:3156    '
 FX 312/886-4071'
 Karen Chytalo
 NYS Department of- Eny. Conseryation  ,
 205 S. Belle Meade Road
 EastSetauket, NY 11733    •-,  .
 PH 516/444-0468.'        --'•../ '   ,
 FX 516/444-0474          -'•    '
 Stephen Cibik
 ENSR .   • -   _      ,
 35'NagpgPark '   ,
 Acton, MA 01720
 PH 508/635-9200x3072
 FX 508/635-9180
David Clarke  .    "    ..  '.  '
Inside Washington Publishers, Risk Policy Rpt
1225 Jefferson Davis Highway, Suite 1400
Arlington, VA 22207
PH 703/416-8564
FX 703/416-8543          '.     ••'.-'
 Rosita Clarke-Moreno
 U.S. EPA/SFD
 77 W.Jackson Blvd.
 Chicago, IL 60604
 PH 312/886-7251
 FX 312/353-5541
John Clayton
Ogden Environmental and Energy Services
5510 Morehouse Drive.
SanDeigo.CA 92121'".-""'"
PH 619/458-9044x338    '   ,
FX 619/458-0943                  '
James Collier
District of Columbia
2100 Martin Luther King, Jr.. Drive, SE
Washington, DC 20020 •'  ••.
PH 202/645-6601 ".
FX 202/645-6622     '       .   •
JoanColson               •  -
,y,S.,EPA/ORD, Natl Risk Mgmt Res. Lab.
26 M L King Drive        ."...'...
Cinncinati,OH 45268       ',.'   '  ..''.
PH 513/569-7501          '-.-. ; .  .'•'
FX 513/569-7585                 '.;-'
John Connolly
HydroQual, Inc.
1 Lethbridge Plaza
Mahwah, NJ 07430
PH 201/529-5151
FX 201/529-5728
Phil Cook
Mid-Continent Ecology, Division/U.S. EPA/ORD
6201 Congdon Blvd        •         ,   '
Duluth, MN 55804
PH 218/720-5553
FX 218/720-5539
Marjorie Coombs (4305)
U.S. EPA/OST/SASD
401 M Street, SW '  ''. ,
Washington, DC 20460
PH 202/260-9821
FX 202/260-9830
Jack Cooper
NYS DEC, Bureau of Eny. Protection
50 Wolf Road-
Albany, NY 12233-4756     -
PH 518/457-1769  .
FX 518/485-8424            ,   .
Helder Costa
ITS Environmental Labs
375 Paramount Drive, Suite B
Raynham, MA 02767-5154
PH 508/990-1424
FX 508/990-1424'-

-------
                                               LIST OF ATTENDEES (continued)
Bcmie Counts
Ohio EPA
1685 Weslbelt Drive
Columbus, OH 43228
PH 614/728-3399
FX 614/728-3380
Martin Coyne
Inside Washington Publisher
1225 Jefferson Davis Highway, Suite 1400
Arlington, VA 22207
PH  702/416-8564   '
FX  702/416-8543
David Cozzie (5307W)
U.S. EPA/OSW    .
401 M Street, SW
Washington, DC 20460
PH 703/308-0479  '
FX 703/308-0511
Greg Cramer
U.S. Food and Drug Administration. HFS-416
2SOC Street, SW
Washington, DC 20204
PH 202/418-3160
FX 202/418-3196
Judy Crane
MN Pollution Control Agency, Water Quality Div.
520 Lafayette Road
St. Paul, MN 55155-4194
PH 612/2974068
FX 612/297-8683
Philip Crocker.
U.S. EPA Region 6
1445 Ross Avenue
Dallas, TX 75202-2753
PH 214/665-6644
FX 214/665-6689
Rico Cruz
Nez Perce Tribe
P.O. Box 365
Lapwal, ID 83540
PH 208/843-7375
FX 208/843-7378
John Cubit
NOAA - Damage Assessment Center
501 West Ocean Blvd., Suite 4470
Long Beach, CA 90802
PH 310/9804081
FX 310/9804084
Linda Cummings .
Terra Consulting Group
8900 Anselmo Lane
Baton Rouge, LA 70810
PH 504/769-1141
FX 504/769-1724
Jerome Cura
Menzle-Cura and Assoc., Inc.
One Courthouse Lane, Suite 2
Cheimsford, MA 01824
PH 508/4534300
FX 508/453-7260
Bradford Gushing
Applied Environmental Management, Inc.
16 Chester County Commons
Malvern, PA 19355
PH 610/251-0450
FX 610.251-0711
Visty Dalai
Maryland Department of the Environment
2500 Broening Highway
Baltimore, MD 21224
PH 410/631-3689
FX 410/631-7034
 Bernard Daniel
 U.S.EPA/NERL
 26 West Martin Luther King Drive
 Cincinnati, OH 45268
 PH 513/569-7401
 FX 513/569-7609
 Paul Danielson
 Nez Perce Tribe
 P.O. Box 365
 Lapwai, ID 83540
 PH 208/843-7375
 FX 208/843-7378
 Patrick Dargan
 ALCOA
 ALCOA Massena OPNS, Park Ave.
 Massena, NY 13662
 PH 315/7644287
 FX 315/7644444
 Jim Davenport (MC-150)
 Texas Natural Resource Conservation Comm.
 P.O. Box 13087
 Austin, TX 78711-3087
 PH 512/2394585
 FX 512/2394420
 Tudor Davies (4301)
 U.S. EPA/OST
 401 M Street, SW
 Washington, DC 20460
 PH 202/260-5400
 FX 202/260-5400
 Helen Davies
 NSW EPA
 799 Pacific Highway
 Chatswood, NSW Australia,
 PH 61.29325.5715
 FX 61.29325.5788
2057
 Mick DeGraeve
 GlEC
 739 Hastings
 Traverse City, Ml 49686
 PH 616/941-2230
 FX 616/941-2240
 Tod DeLong
 Roy F. Weston, Inc.
 OneWestonWay
 West Chester, PA  19380-1499
 PH 610/701-7304
 FX 610/701-7401
 Ted DeWitt
 Battelle Marine Sciences Laboratory
 1529 W.Sequim Bay Road
 Sequim, WA 98382
 PH 360/681-3656
 FX 360/681-3681

-------
                                                LIST OF ATTENDEES (continued)
 Cynthia Decker
 New York State Department of Env. Conserv.
 205 N. Belle Mead Road
 East Setauker, NY 11733
 PH 516/444-0462         '   .
 FX 516/444-0474 '  •'
Mario Del Vicario •
U.S. EPA Region II
250 Broadway
New York, NY 10007
PH 212/637-3781
FX 212/637-3889
 Edward Demarest
 NJ Department of Enviornmental Protection
 4th floor, west, CN413
 Trenton, NJ 08625-0413
 PH 609/633-1348
 FX 609/292-0848
 TedDewitt
 Battelle Marine Sciences, Marine Eco. Proc. Group
• 1529 W.Sequim Bay Road
 Sequim, WA 98382
 PH 360/681-3656
 FX 360/681-3681
DomDiToro
HydrbQual, Inc.
Onelethbridge Plaza
Mahwah, NJ 07430
PH 201/529-5928
FX 201/529-5728
 Lisa DiPinto
 NOAA - Damage Assessement Center
 1305 East-West Highway, Rn\ 10218
 Silver Spring, MD 20910
 PH 301/713-3038x187
 FX 301/7134387
 Rebecca Dickhut
 College of William and Mary  '_ '
 Virginia Institute of Marine Science
 Gloucester Point, VA 23062
 PH 804/642-7247
 FX 804/642-7186
Tom Dillon
EA Engineering, Science and Technology
11019McCormickRoad
Hunt Valley, MD 210'3f
PH 410/584-7000
FX 410/785-2309
 L.K. Dixon
 Mote Marine Laboratory
 1600 Thompson Parkway
 Sarasota, FL 34210
 PH 941/388-4441 .
 FX 941/3884312
 Charles Dobbs
 ALCOA Tech Center
 100 Technical Drive
 Alcoa Center, PA 15069
 PH 412/337-2164
 FX 412/337-1860
Chuck Dobroski
Roy F. Weston, Inc.
OneWestonWay  •
West Chester, PA  19380-1499
PH 610/701-7216
FX 610/701-7401
Philip Dorn
Shell Development Company
P.O. Box 1380
Houston, TX 77251-1380
PH 713/544-7855
FX 713/544-8727
 Barbara Douglas
 Navy Facilities Engineering Command
 10 Industrial Highway, MSC #82
 Lester, PA 19113            '
 PH 610/595-0567x188
 FX 610/595-0555
Philip Downey, Ph.D.
Inchcape Testing Services
55 South Park Drive
Colchester, VT 05446
PH 802/655-1203x11
FX 802/658-3189
Kelly Eisenman
U.S. EPA Chesapeake Bay Program
'410 Severn Ave., Suite 109 '
Annapolis, MD 21403
PH 410/267-5728
FX 410/267-5777
 Jim Eldridge
 SAIC
 18706 North Creek. Parkway, Suite 110
 Bothell, WA 98011
 PH 206/485-5800
 FX 206/485-5566
Bonnie ElederT-17J
U.S. EPA Region 5
77 W. Jackson Blvd.
Chicago, IL 60102
PH 312/8864885
FX 312/886-2737
Michael Elias
ICF Kaiser
9300 Lee Highway
Fairfax, VA 22031
PH 703/934-3838
FX 703/934-3315
 Steve Ells (5204G)
 U.S. EPA/Superfund
 401 M Street, SW •
 Washington, DC 20460
 PH 703/603-8822
 FX 703/603-9100
Alex Ellwood
Penn State University, Applied Research Lab
331 W. College Avenue
State College, PA  16801  ••'''.'
PH 814/237-8120
FX 814/863-7304
Mohamed Elnabarawy   ..       .      '
3M Environmental Technology and Services
879 East 7th St., Bldg. 41-01-05 P.O. Box 33331-
St. Paul, MN 55133-3331  '   -   •
PH 612/778-5151
FX 612/778-7203          .    .

-------
                                               LIST OF ATTENDEES (continued)
Vaiten Emery, Jr. ((ES-)F)
USAGE
3909 Halls Ferry Road
VJcksburg, MS 39180-6199
PH 601/634-4302
FX 601/634-3713
 David Engel
 NOAA/NMFS/Beaufort Lab.
 101 Rivers Island Road
 Beaufort, NC 28516
 PH 919/728-8741"
 FX 919/728-8784
 David Evans
 NOAA/NMFS/Beaufort Lab.
 101 Piversjsland Road
 Beaufort, NC 28516,
 PH 919/728-8752
 FX 919/728-8784
Jane Marshall Farris (4305)
U.S. EPA/OST
401M Street, SW
Washington, DC  20460
PH 202/260^8897
FX 202/260-9830
 James Felkel( 7507C)
 U.S. EPA
 401 M Street, SW
 Washington, DC 20460
 PH 703/305-5828
 FX 703/305-6309 '
 Jay Field
 NOAA/HMRAD N/ORCA 32
 BINC15700
 Seattle, WA 98115
 PH 206/526-6404
 FX 206/526-6941
John Fifkins
U.S. EPA/ORD/MED, Large Lakes Res. Station
9311 Groh Road
Grosselle.MI 48138
PH 313/692-7614
FX 313/692-7603
 Ken Finkelstein
 NOAA
 c/o EPA, JFK Federal Building (HIO)
' Boston, MA 02203
 PH 617/223-5537
 FX 617/573-9662
 Dan Fisher
 University of Maryland
 P.O. Box 169
 Queenstown, MD  21,601
 PH 410/827-8056
 FX 410/827-9039
Bob Fotey
U.S. Fish and Wildlife Service
177 Admiral Cochrane Drive
Annapolis, MD 21401
PH 410/573-4519
FX 410/269-0832
 Catherine Fox (2222A)
 U.S. EPA/OECA
 401 M Street, SW
 Washington, DC 20460
 PH 202/5644299
 FX 214/564-0031
 Rick Fox
 H^rt Crowser
 One O'Hare Centre, 6250 River Road, Suite 3000
 Rosemont, IL 60018
 PH 847/292-4426
 FX 847/292-0507               .
LeoFrancendese
U.S. EPA Region 4
345 Courttand Street, NE
Atlanta, GA 30365
PH 404/3474931 x6104
FX 404/347-7817
 Ronald French
 Camp Dresser and McKee, Inc.
 One Woodward Ave., Suite 1500
 Detroit, Ml 48226
 PH 313/963-1313
 FX 313/963-3130
Alyce Fritz (N/ORCA 32}
DOC/NOAA/HAZMAT
7600 Sand Point Way, NE'
Seattle, WA 98115
PH 206/526-6305
FX 206/526-6865
Awilda Fuentes 5202G
U.S. EPA
401 M Street, SW
Washington, DC 20460
PH 703/603-8748
FX 703/603-9133
 Taku Fuji
 Hart Crowser
 1910 Fairview Ave., East
 Seattle, WA 98102
 PH 206/324-9530
 FX 206/328-5581
Cris Gaines (4305)
U.S. EPA/OST/SASD
. 401 M Street, SW
Washington, DC 20460
PH 202/260-6284
FX 202/260-9830
William Gala
Chevron Res. and Technol. Co.
100 Chevron Way
Richmond, CA 94802
PH  510/242-4361
FX  510/242-5577
 Gayle Carman
 NOAA; Hazmat, Coastal Res. Coord. Branch
 7600 Sand Point Way, NE
 Seattle, WA 98115
 PH 206/5264542
 FX 206/526-6865
Mary Jo Garreis
MD Department of the Environment
2500 Braening Highway  ,
Baltimore, MD 21224
PH 410/631-3906
FX 410/633-0456

-------
                                               LIST OF ATTENDEES (continued)
Tony Giedt
NOAA.
One Blackburn Drive
Gloucester, MA 01930
PH 508/281-9289    '
FX 508/281-9389
 JohnGiga
 Baltec Associates
 130 Business Park Drive
 Armonk, NY 10504
 PH  914/273-2626
' FX  914/273-7350
Frank Gpbas
Simon Fraser University
School of Res. & Envir. Mgmt
Burnaby, BC Canada,  V7K1S6
PH  604/291-5928
FX  604/291-4968 .
Todd Goeks
NOAA Hazm'at
77 West Jackson Blvd,SRT-4J
Chicago, IL 60604
PH 312/886-7527
FX 312/353-9281
 Ibrah'ima Goodwin
 U.S. EPA/OW
 401 M Street, SW
 Washington, DC  20460
 PH 202/260-1308
 FX 202/260-9830
Joseph Gorsuch
Eastman Kodak Company, Kodak Env. Services
1100 Ridgeway Avenue
Rochester, NY 14652-6255  '
PH  716/588-2124
FX  716/722-3173      .       •
Barry Graham
Beta Gamma Services
841 Vale View Drive
Vista, CA 92083 •
PH 619/941-8093
FX 619/941-3252
 Emily Green
 Sierra Club
 214 N Henry Street, Suite 203
 Madison, Wl 53703
 PH  608/257-4994
 FX  608/257-3513
Andrew Green
Waterways Experiment Station, USAGE (NRG)
3909 Halls Ferry Road
Vicksburg, MS 39180-6149
PH  601/634-3889   .
FX  601/634-3120        '         •   '    .
Joseph Greenblott (8104)
U.S. EPA/ORD/ORSI .
401 M Street, SW
Washington, DC 20460. '
PH 202/260-0467
FX 202/260-6932
 Richard Greene
 Delaware Dept. Nat. Res. & Env. Control
 89 Kings Highway, P.O. Box 1401
 Dover, DE  19903
 PH 302/739-4590
 FX 302/739-6140
Chuck Grimm
Natural Resources and Env. Affairs Branch
3040 McCawley Ave.,  Suite 2
Quantico.VA 22134
PH  703/784-4030
FX  703/784-4953
Daniel Grpsse
Terr Aq Env.
3754 Jennifer Street, N.W.
Washington, DC 20015
PH 202/244-4300
FX 202/244-4667
 Donald Grothe
 Monsanto Company - U4E
 800 N. Lindbergh Blvd
 St. Louis, MO 63167
 PH  314/6944940
 FX  314/694-1531
Jeff Grovhoug
NCCOSC-NRaD (U.S.. Navy R&D)
53475 -Strother Road
San Diego, CA.92152-6310
PH  619/553-5425
FX  619/553-6305
Barry Gruessner
ICPRB
6110 Executive Blvd, Suite 300
Rockville, MD  20852
PH 301/984-1908
FX 301/984-5841
 Samuel Hadeed
 AMSA
 1000 Connecticut Ave., NW, Suite 410
 Washington, DC 20036
 PH 202/833-4655
 FX 202/8334657
John Haggard
General Electric Company
1 Computer Drive South
Albany/NY 12205
PH 518/458-6619  '
FX 518/458-1014
Simeon Hahn .
Navy      ,    -
10 Industrial Highway, MS 82
Lester, PA 19113-2090
PH 610/595-0567
FX 610/595-0555
 Rob Hale
 VIMS/College of William and Mary-
 Route 1208 '
 GloucsterPt.VA 23062
 PH 804/642-7228
 FX 804/642-7186
Eve Halper
Interstate Sanitation Commission
311 W. 43rd Street, Room 201
New York City, NY 10036
PH 212/582-0380   .'
FX 212/581-5719

-------
                                               LIST OF ATTENDEES (continued)
Ian Hartwell
NOAA/NMFS
1315 East-West Highway
Silver Spring, MD 20910-3282
PH 301/713-2325
FX 301/713-1043
Timothy Hassett
Hercules Incorporated
9282 SW Hercules Plaza
Wilmington/DE 19894
PH  302/594-7656
FX  302/594-7255
Fred Hauchman (MD-51A)
U.S. EPA
Research Triangle Park, NC 27711
PH  919/541-3893
FX  919/541-0642
Melvin Hauptman
Caribbean Superfund Section II
U.S. EPA Region 2
NewYonXNY 10007-1866
PH 212/637-3952
FX 212/637-3966
Steven Hawthorne
Hampton Roads Sanitation District
P.O. Box 5911
Virginia Beach, VA 23471-0911
PH  804/460-2261
FX  804/460-2372
Wendy Hayes
U.S. Army Ctrfor Health Prom. & Prev. Medicine
ATTN: MCHB-DC-ES, 5158 Blackhawk Road
Aberdeen Proving Ground, MD 21010-5422
PH 410/671-3816
FX 410/671-8104
JeffBenning
NOAA
841 Chestnut Building (3HW41)
Philadelphia, PA 19107
PH 215/566-3329
FX 215/566-3001
Lisa Herschberger
4809 W. 99th Street
Bloomington, MN 55437
PH 612/851-8112
Helen Hillman
NOAA c/o U.S. EPA Region 9
75 Hawthorne Street, 9th floor
San Francisco, CA 94105
PH 415/744-2273
FX 415/744-3123
MHock
Alaska DEC
410 WittoughbyAve., Suite 105
Juneau,AK 99801
PH 907/465-5185
FX 907/465-5274
Erika Hoffman (W-3-3)
U.S. EPA Region 9
75 Hawthorne Street
San Francisco, CA 94105
PH 415/744-1986
FX 415/744-1078
Rick Hoffmann (4305)
U.S. EPA/OST
401 M Street, SW
Washington, DC 20460
PH 202/260-0642
FX 202/260-9830
David Hohreiter
Blasland, Bouck & Lee, Inc.
6723 Towpalh Road, Box 66
Syracuse, NY 13214
PH 315/446-9120
FX 315/446-7485
Stewart Holm
Georgia-Pacific
1875 Eye Street NW, Suite 775
Washington, DC 20006
PH  202/659-3600
FX  202/233-1398
William Honachefsky
NJ Department of Environmental Protection
CN422
Trenton, NJ  08625
PH  609/292-0427
FX  609/633-1095
Doug Hotchkiss
Port erf Seattle
P.O. Box 1209
Seattle, WA 98111
PH 206/728-3192
FX 206/728-3188
Timothy lannuzzi
ChemRisk
1685 Congress Street
Portland, ME 04102
PH  207/774-0012
FX  207/744-8263
Chris Ingersoll
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
PH 573/875-5399x1819
FX 573/876-1896
Andrew Jacobson
Rohm and Haas Company
727 Nofristown Road
Spring House, PA 19477
PH 215/841-7361
FX 215/619-1624
Paul Jacobson
Langhei Ecology, LLC
14820 View Way Court
Gleneig, MD 21737
PH 410/489-3675
FX 410/489-4523
Kathryn Jahn
U.S. Fish and Wildlife Service
3817 Luker Road
Cortland, NY 13045
PH 607/753-9334
FX 607/753-9699

-------
                                                 LIST OF ATTENDEES (continued)
 Paul Jiapizian    .„  '
 Maryland Department of the Environment
 2500 Broening Highway         ."..   .
 Baltimore, MD 21224           '   '  ''.
' PH  410/631-3906             "   - '
 FX  410/633-0456              "   '
 Douglas Johnson  :
 U.S. EPA Region 4...
 100 Alabama Street
 Atlanta, GA 30303
 PH 404/562-9386
 Isabel Johnson
 KBN Engineering
 6241  N.W., 23rd Street, Suite 500
 Gainesville,FL 32653       • •'
 PH 352/336-5600
 FX 352/336-6603
 Robert Jones (7405)
 U.S.EPA
 401 M Street, S.W.
 Washington, DC  20460
 PH 202/260-8150*
 FX 202/260-1906
Krzysztof Jop
SAIC   ;   ' ."•    .   .
165 Dean Knauss Drive
Narragansett; Rl 02882
PH 401/782-1900
FX 401/782-2330
 Matt Kadlec    '        • i-
 ETRP -RIPS/Phamiacology
 Dept. of Pharmacology
 University, MS 38677   •
 PH 601/232-5759
 FX 601/232-5148
 Robert Kaley, II
 Monsanto Company -A2NE
 800 North Lindbergh Blvd
 St. Louis, MO  63167 •
 PH  314/694-8558  ,-
 FX  314/694-6858
 Susan Kane Driscoil
 Virginia Institute of Marine Science
 P.O. Box 1346         •'.;•'    ;
 Gloucester Point, VA'23062 ' ;
 PH 804/642-7190
 FX 804/642-7097
 Hamid Karimi               '
 Environmental Regulation Administration
 2100 Martin Luther King, Jr: Ave.; SW > .
 Washington, DC 20020-5732 -
 PH 202/645-6611
 FX 202/645-6622               •     '
 Maureen Katz          - •••  '-'•
 U.S. Department of Justice
 P.O. Box 7611, Ben Franklin Station-
 Washington,DC 20044.  •  '••'."..
 PH  202/514-2468   .
 FX  202/616-6584.         '"  •''.'-
Jim Keating(4305)'
U.S. EPA/OST/SASD
,401 M Street, SW
Washington, DC 20460
PH 202/260-3845
FX 202/260-9830
'Karen Keeley(CL-111)
•U.S. EPA Region-10
 1200 Sixth Ave •••••-
 Seattle, WA 98119
 PH 206/553-2141
 FX 206/553-0124
 Mark Kennedy           :  •  •• .   .
 Greeley and Hansen  •
 8905 Presidential Parkway, Suite 230
 Upper Marlboro, MD 20772-2653  .
 PH 301/817-3700  •
 FX 301/817-3735    .   ' -
 John Kern         '         ".-..-
 U.S. Dept. of Commerce/NOAA •, ••     ;;
 9721 Executive Center Drive N;, Suite 134:
 St. Petersburg, FL 33702
 PH 813/570-5391           ' '    '
 FX 813/570-5390  •     •-'-'  •-''••'. •'
 Charles King
 U.S. EPA/RPM Region 4
 100 Alabama Street, N.W.
 Atlanta, GA 30303
 PH 404/562-8931
 FX 404/562-8896
 Hal Kirk
 Dow Chemical
 1803Bldg.
 Midland, Ml 48674
 PH 517/636-2425
 FX 517/638-2425
 DeniseKlimas             •    ?
 U.S.'EPA Region 4, Waste Mgmt Div.
 100 Alabama Street   ' :   - -• •'••   '
 Atlanta, GA 30303         • :'"   ••
 PH 404/562-8639   .  •           •
 FX 404/562-8662      .  ' •
 Alfred Korndoerfer, Jr.             .'•'••
 NJ Department of Environmental Protection
 CN 427 - WMM/Bureau of Water-Monitoring
 Trenton, NJ  08625-0427'*''
 PH 609/292-0427      ' '            '
 FX 609/633-1095         ' '•  '••'••
 Charles.Kovatch   •
 Univ. of SC, Department of Env. Health Sciences -
 .713 South Holly Street    '   '   :'
 Columbia, SC 29205         '    •      :
 PH 803/777-6452
 Bill Kramer (301)
 U.S. EPA/OW/OST     •
 401'M Street, SW .
 Washington, DC 20460
 PH 202/260-5824
 FX 202/260-5394
 Mike Kravitz (4305)
 U.S. EPA/OST      ••;
 401-M Street, SW
 Washington, DC 20460
 PH 202/260-8085  -
 FX 202/260-9830

-------
                                               LIST OF ATTENDEES (continued)
 Stephen Kroner (53Q7W)
 U.S. EPA
 401M Street, SW
 Washington, DC 20460
 PH 703/308-0468
 FX 703/308-0511
Tim Kubiak
U.S. FWS (ARLSQ 330)
4401 N. Fairfax Drive
Arlington, VA 22203
PH 703/358-2148
FX 702/358-1800
 Brent Kuenzli
 Ohio EPA
 347 N. Dunbrigde Road
 Bowling Green, OH 43402
 PH' 419/352-8461
 FX 419/352-8468
AmddKuzmack(4301)
U.S. EPA/OST
401 M Street, SW
Washington, DC 20460
PH 202/260-5821
FX 202/260-5394
Hector Laguette
Brown and Root Environmental
55 Jonspin Road
Wilmington, MA 01887-1062
PH 508/658-7899
FX 508/658-7870
 Dan Landeen
 Nez Perce Tribe
 P.O. Box 365
 Lapwai, ID 83540
 PH 208/843-7375
 FX 208/843-7378
Peter Landnim
NOAA, Great Lakes Environmental Res. Lab.
2205 Commonwealth Blvd.
Ann Arbor, Ml 48105
PH 313/741-2276
FX 313/741-2055
Gunnar Lauenstein
NOAA/NOS/ORCA21
1305 East West Highway
Silver Spring, MD  20910
PH 301/713-3028x152
FX 301/7134388
 Drew Lausch( 3HW50) -
 U.S. EPA Region 3
 841 Chestnut Building
 Philadelphia, PA  19107
 'PH 215/566-3359
 FX 215/566-3001
AlexLechich
P.O. Box 08742
Point Pteasant Beach, NJ 08742
Henry Lee
Coastal Ecology Branch
U.S. EPA/ORD
Newport, OR 97365-5260
PH 503/867-5000
FX 503/867-4049
 G. Fred Lee, P.E., D.E.E.
 G. Fred Lee & Associates
 27298 E. El Macero Drive
 El Macero, CA  95618-1005
 PH  916/753-9630
 FX  916/753-9956
Sandra Lemlich
USAGE
P.O. Box 3755
Seattle, WA 98124-2255
PH 206/764-6930
FX 206/764-6795
Dennis Leonard
Detroit Edison
2000 2nd Avenue
Detroit, Ml 48070
PH  313/235-8714
FX  313/235-5018
 Deborah Lester
 Parametrix, Inc.
 5808 Lake Washington Blvd
 Kirkland, WA 98033
 PH  206/822-8880
 FX  206/889-8808
Ann Levine
Oregon DEQ
2020 SW 4th Avenue
Portland, OR 97201-4987
PH 503/229-6540
FX 503/229-6945
Wilbert Lick
University of California
Dept. of Mech. Engineering
Santa Barbara, CA 93106
PH  805/8934295
FX  805/893-8651
. Tom Lopes
 U.S. Geological Survey
 1608 Mountain View Road
 Rapid City, SD 57702
 PH 605/394-1780x240
 FX 605/394-5373
Michael Ludwig
NOAA/NMFS
212 Rogers Ave.
Milfford, CT 06460-6499
PH  203/7834228
FX  203/7834295
Warren Lyman
Camp Dresser and McKee, Inc.
10 Cambridge Center
Cambridge, MA  02142
PH 617/252-8829
FX 617/621-2565
 Jeffrey Lynn
• International Paper
 6400 Poplar Avenue
 Memphis, TN  38147
 PH 901/763-6721
 FX 901/763-6939

-------
                                               LIST OF ATTENDEES (continued)
Wayne Magley
FL Department of Environmental Protection
2600 Blairstone Road .
Tallahassee, FL 32399-2400
PH  904/921-9487
FX  904/487-3618   '
Amal Mahfouz, Ph.D. (4304)
U.S. EPA/OW/OST
401 M Street, Room #1003
Washington, DC  20460
PH 202/260-9568
FX 202/260-1036
John Malinowski
Chester Engineers
600 Clubhouse Drive
Moon Township, PA  15108
PH  412/269-7716
FX  412/269-5865
Carol-Ann Manen
NOAA - Damage Assessment Center
1305 East-West Highway
Silver Spring, MD 20910
PH 301/713-3038 ext 196
FX 301/713-4387
 R. Shawn Martin
 St. Regis Mohawk Tribe
 RRIBoxSA
 Hogansburg, NY 13655
 PH 518/358-5937
 FX 518/358-6252
Robert Martino
Normandeau Associates
3450 Schuylkill Road
Spring City, PA  19475
PH 610/948-4700
FX 610/948-4752
Dave McBride
Washington State Dept. of Health
P.O. Box 47825
Olympia, WA 98504
PH 360/586-8734
FX 360/586-4499
 Lynn McCarty
 L.S. McCarty Scientific Research & Cons.
 280 Glen Oak Drive     '   .  '
 Oakville, Ontario, L6K2J2
 PH 905/842-6526
 FX 905/842-6526
Victor McFarland
CEWES, USAGE Waterways Experiment Station
3909 Halls Ferry Road
Vicksburg, MS 39180
PH 601/639-3721
FX 601/634-3120
 Beth McGee            ,   •  "  '
 University of Maryland, Wye Research Ctr.
 P.O. Box 169
 Queentown, MD 21658
 PH 410/827-8056
 FX 410/827-9039        ' -
1 David McHeriry
 Weyerhaeuser Co.
 P.O. Box 1391
 New Bern, NC 28563
 PH 919/633-7632 -:
 FX 919/633-7634
 Douglas Mclaughlin
 Fort Howard Corporation
 P.O. Box 19130
 Green Bay, Wl 54307-9130
 PH 414/435-8821
 FX 414/435-2325
 Pat McMurray
 VA Department of Environmental Quality
 629 E. Main Street
 Richmond, VA  23219
 PH 804/698-4186
 FX 804/698-4234
 James Meador
 NMFS/NOAA
 2725 Montlake Blvd. E,
 Seattle, WA 98112
 PH  206/860-3321
 FX  206/860-3335
 Kelly Mecum
 Chesapeake Bay Program/CRC
 410 Severn Ave., Suite 109
 Annapolis, MD 21403
 PH 410/267-5719
 FX 410/267-5777
 David Melfi
 U.S: Army Corps of Engineers
 1776 Niagara Street   "
 Buffalo, NY 14207
 PH 716/879-4349
 FX 716/8794355
 Margaret Metcalf
 Louisiana Office of •Public Health
 234 Loyola Avenue, Suite 620
 New Orleans, LA 70112
 PH 504/568-7309
 FX 504/568-7035      ;
 Ossi Meyn( 7403)
 U.S. EPA
 401 M Street, SW
 Washington, DC 20460
 PH 202/260-1264
 FX 202/260-1236
 David Michaud
 Wisconsin Electric Power Company
 333 W. Everett Street
 Milwaukee, Wl 53201
 PH 414/221-2187
 FX 414/221-2169
 Ron Miller (M/222-A)
 NASSCO
 P.O. Box 85278
 San Diego, CA 92186-5278
 PH 619/544-7780
 FX 619/232-6411
 John Miller (4304)
 U.S. EPA
 401 M Street, SW
 Washington, DC  20460
 PH 202/260-1038
 FX 202/260-1,036  .

-------
                                                LIST OF ATTENDEES Continued)
 Geoff Mills
 NIWA
 P.O. Box 11-115
 Hamilton, New Zealand,
 PH +64-7-8567026
 FX +64-7-856-0151
 Michael Montgomery
 U.S. EPA Region 9
 75 Hawthorne Street
 San Francisco, CA 94105
 PH 415/744-2242
 FX 415/7442180
 David Moore
 USAGE WES
 3909 Halls Ferry Road
 Vicksburg, MS  39180
 PH 601/637-2910
 FX 601/634-3713
 Raymond P. Morgan, II
 University of Maryland (AEL-CEES)
 GunterHall
 Frostburg, MD 21532
 PH 301/689-3115
 David Mount (8101)
 U.S. EPA/ORD .
 6201 Congdon Blvd.
 Duluth, MN  55804
 PH 218/720-5616
 FX 218/720-5539
•Greg Mullen
 MT'Department of Justice
 NRDLP
 Helena, MT 59601
 PH, 406/444-0228     •
 FX 406/444-0236
 Wayne Munns
 Allanlic Ecology Division
 U.S. EPA/ORD
 Narraganselt, Rl 02882
 PH 401/782-3017
 FX 401/782-3099
 Deirdre Murphy
 MD Department of Environment
 2500 Broening Highway
 Baltimore, MD 21224
 PH 410/631-3906
 FX 410/633-0456
 Thomas Murray (7406)
 U.-S: EPA/OPPT
 401 M Street, SW
 Washington, DC 20460
 PH 202/260-1873
 FX 202/260-0981
Lewis Nagy
NJ Department of Environmental Proteciton
401 East State Street, 74 West Wing
Trenton, NJ 08625
PH 609/984-1817
FX 609/777-0942
Jerry Neff
Battelle Ocean Sciences
397 Washington Street • -
Duxbury, MA 02332
PH 617/934-0571
FX 617/934-2124
Tony Neville
LABAT
5521 N. 23rd Street
Arlington, VA 22205
PH. 703/506-1400x506
Arthur Newell
NYS Department of Env, Conservation
205-S N. Belle Meade Road
EastSelauket.NY 11733
PH 516/444-0430
FX 516/444-0434
Annette Nold( 7406)
U.S. EPA/OPPTS/OPPT
401 M Street, SW
Washington, DC 20460 -
PH 202/260-3920
FX 202/260-0981
Cynthia Nolt( 8104)
U.S. EPA
401 M Street, SW
Washington, DC  20460
PH 202/260-1940
FX 202/260-15932   ;'
Ralph NorthrorX 7405)
U.S. EPA
401M Street, SW
Washington, DC 20460
PH 202/260-5023
FX 202/260-1096
Dale Norton
Washington State Dept. of Ecology
300 Desmond Drive, P.O. Box 47710
Olympia, WA 98504-7710
PH  360/407-6765
FX  360/407-6884
Charles Noss
LERF  '.•   •
601 Wythe Street
Alexandria, VA 22314
PH 703/684-2470
FX 703/684-2492
Thomas O'Connor
MOM  N/ORCA21
1305 East West Highway
Silver Spring, MD 20910
PH 301/71^3028x151
FX 301/713-4388
Steve O'Rourke
Environmental Enforcement, Justice Dept.
P.O. Box 7611
Washington, DC 20044
PH  202/514-2779
FX  202/514-2583    •'
Bill Olsen
US Fish and Wildlife Service
1 DON. Park, Suite 320   "
Helena, MT 59601
PH 406/449-5225
FX 406/449-5339    ;

-------
                                               LIST OF ATTENDEES (continued)
AmyOnufrbck
Maryland Department of the Environment
2500 Broening Highway
Baltimore, MD 21224
PH 410/631-3601
FX 410/6334)456
Steven Osborn
City of San Jose, Environmental Services Dept
4245 Zanker Road
San Jose, CA 95134
PH 408/945-3714  '
FX 408/934-0491                       ,
Randy Palachek
.Parsons Engineering Science
8000 Centre Park Drive, Suite 200
Austin, TX 78754
PH 512/719-6000
FX 512/719-6099'
Richard Park
Eco Modeling
20302 Butterwick Way
Montgomery Village, MD  20879
PH 301/527-0545
FX 301/527-0545
TomParkerton
Exxon
CN 2350 Mettlers Road
East Millstone, NJ 08875
PH 908/873-6367
FX 908/893-6009
Dorothy Patton( 8101)
U.S. EPA/ORD 8101
401 M Street, SW
Washington, DC 20460
PH 202/260-5900   .
FX 202/260-0744
 Robert Paulson
 Wisconsin Oept. of Natural Resources
 P.O. Box 7921              ,
 Madison, Wl 53707-7921
 PH 608/266-7790
 FX 608/267-2800
 Katherine Pease
 NOAA
 501 W. Ocean Blvd., Suite 4470
 Long Beach, CA 90802
 PH 310/9804080
 FX 310/980-4084
 AmyPelka
 U.S. EPA Region 5
 77 W. Jackson Blvd
 Chicago, IL 60604
 PH 312/886-9858
 FX 312/353-5374
 James Pendergast (4203)
 US EPA/OWM
 401 M Street, SW
 Washington, DC 20460
 PH 202/260-9545
 FX 202/260-1460
 Robert Pennington
 Uls. Fish & Wildlife/Ches. Bay Prog. Ofc.
 177 Admiral Cochrane Road
 Annapolis, MD 21401
 PH 410/573-4546 " •  .
 FX 310/269-0832          •
 Christopher Penny.
 US Navy Atlantic Division, Code 1823
 1510 Gilbert Street (BldgN-26)
 Norfolk, VA  23511
 PH  804/322-4815'
 FX  804/322-4805
 Esther Peters
 Tetra Tech, Inc.
 10306 Eaton Place, Suite 340
 Fairfax, VA 22030
 PH 703/385-6000
 FX 703/385-6007
 Edward Pfau
 Ohio EPA
 P.O. Box 1049
 Columbus, OH 43216
 PH  614/644-2295
 FX  614/644-3146
 Loren Phillips
 U.S. Army Ctr for Health Prom. & Prev. Medicine
 ATTN:  MCHB-DC-ES, 5158 Blackhawk Road
 Aberdeen Proving Ground, MD  21010-5422  •
 PH 410/671-3816
 FX 410/671-8104      '   ,
 Scott Pickard
 U.S. Army Corps of Engineers
 1776 Niagara Street
 Buffalo, NY  14207-3199
 PH 716/8794404
 FX 716/8794357
 Brian Pickard
 U.S. Army Ctr for Health Prom. & Prev. Medic.
 Building 1675         '  '      .
 Aberdeen Proving Ground, MD  21010-5422
 PH 410/671-3816                  -
 FX 410/671-8104
 Fred Pinkney
 U.S. Fish and Wildlife Service
 177 Admiral Gochrane Drive
 Annapolis, MD 21401
 PH 410/5734521
 FX 410/269-0832
  D.B. Porcella
  EPRI
  PO Box 10412
  Palo Alto, CA  94304
  PH 415/855-2723
  FX 415/855-1069
 Damian Preziosi
 The Weinberg Group, Inc.
 122019th Street, NW, Suite 300
 Washington, DC 20036-2400
 PH 202/833-8077x8090
 FX 202/8334257
  Riph Pruell
  U.S. EPA
 . 27 Tarzwell Drive
  Najragansett, Rl 02835
  PH 401/782-3091    .
  FX 401/782-3030

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                                                LIST OF ATTENDEES (continued)
 Lara Pulton (WA-16J)
 U.S. EPA Region 5
 77 West Jackson Blvd.
 Chicago, IL 60604
 PH 312/886-0138
 FX 312/886-7804
Thomas Purcell
The Silver Council
5454 Wisconsin Ave, Suite 1510
Chevy Chase, MD 20815
PH 301/664-5150
FX 301/664-5156
Terry Quill
Beveridge and Diamond, P.C.
13501 Street, NW, Suite 700
Washington, DC 20005-3311
PH 202/789-6061
FX 202/789-6190
 James Quinn
 University of Rhode Island
 Narraganselt, Rl 02882
 PH 401/874-6219
 FX 401/874-6811
Dave Rabbe
Chemical Land Holdings
1015 Belleville Turnpike
Keamy, NJ 07032
PH 201/955-0855
FX 201/955-1063
Tirumuru Reddy
U.S. EPA/NERL
26 West Martin Luther King Drive
Cincinnati, OH  45268
PH 513/569-7295
FX 513/569-7609
Danny Reib!e
Hazardous Substance Research Center
3418 CEBA
Baton Rouge, LA 70816
PH 504/388-6770
FX 504/388-5043
Dianne Reid
NC DEM/Water Quality Planning
P.O. Box 29535
Raleigh, NC 27626-0535
PH 919/733-5083x568
FX 919/715-5637
Mary Reiley (4304)
U.S. EPA
401 M Street, SW
Washington, DC -20460
PH 202/260-9456
FX 202/260-1036   ,
PatrlRe!!!y(G.MRO)
do USCG HQ (Commandant)
2100 2nd Street, SW
Washington, DC 20593
PH 202/267-0568
FX 202/267-4497
Mark Reimer
Fort Howard Corporation
1919 S. Broadway
Green Bay, Wl 54304
PH 414/435-8821
FX 414/498-3225
Eli Reinharz     ,   .
NOAA - Damage Assessment Center
1305 East-West Highway, S SMC #4, Rm 10229
Silver Spring, MD 20910
PH 301/713-3038x193
FX 301/7134387
Mark Relss
U.S. Army Corps of Engineers, NY
26 Federal Plaza, Room 1937
New York, NY 10278
PH 212/264-1852
FX 212/264-4260
Gene Revelas
Striplin Enviornmental Associates
6541 Sexton Drive, N.W., Suite E-1'
Olympia, WA 98502
PH 360/866-2336   '
FX 360/866-4816
Steven Rice
U.S. Fish and'Wildlife Service
728 Grove Street
Hampton, VA 23664
PH 804/693-6694
FX 804/693-9032
Mark Richards
VADEQ
P.O. Box 10009
Richmond, VA 23240
PH 804/698-4207
FX 804/698-4234  ,
Erik Rifkin
Rifkin and Associates  •
401 East Pratt Street, Suite 2332
Baltimore, MD 212202
PH 410/962-1401
FX 410/962-1065
Christine Rioux
Camp Dresser and McKee, Inc.
Ten Cambridge Center
Cambridge, MA 02142
PH 617/252-8761
FX 617/252-0998
Blto Rockier
U.S. Department of Justice
P.O.Box 7611
Ben Franklin Station
Washington, DC 20044
Kathryn Rowland
Brown and Root Environmental
661 Andersen Drive
Pittsburgh, PA 15220-2745
PH 412/921-8942
FX 412/921-4040
Norni Rubinstein
Atlantic Ecology Division
U.S. EPA/ORD
Narragansett, Rl  02882
PH 401/782-3001
FX 401/782-3030

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                                               LIST OF ATTENDEES (continued)
3ete Rude
.andau Associates, Inc.
'3107 100th Ave., W., P.O. Box 1029
Edmonds, WA 98020-9129
>H 206/778-0907
:X 206/778-6409          ;
Hal Runke      .
Barr Engineering Company
8300 Norman Ctr. Drive, Suite 300,
Minneapolis,'WIN 55437-1026
PH 612/832-2804
FX 612/832-2601
Phillip'Rury
Arthur D. Little, Inc.  -  '
Acorn Park .
Cambridge, MA 02140-2390
PH 617/498-5380
FX 617/498-7040
^arl'Rutz
Myeska Pipeline Service Company
I835 S. Bragaw Street
\nchorage, AK  99512
3H  907/265-8142
:X 907/265-8832  •  •
Gary Salmon
Illinois State Geological Survey
615 E. Peabody Drive
Champaign, IL 61820   '
PH  217/244-2752       '  '
FX  217/244-2785
David Sanders
RMTInc.
4351 W. College Ayenue, Suite 210
Appleton.WI 54914
PH 414/830-0209  ,       "  .
FX 414/830-1996
Stephanie Sanzone 1400 •'   •
U.S. EPA/Science Advisory Board
401 M Street, SW           -•  '
Washington, DC  20460   .  .
PH 202/260-6557
FX-202/260-7118
Tom Schadt        .  .. .
Parametrix, Inc.
5808 Lake Wash. Blvd.NE
Kirkland, WA 98033
PH 206/822-8880 ,'
FX 206/822-5245
Dan Schechter
Water Environment Federation
601 Wythe Street ,
Alexandria, VA 22314  .
PH 703/684-2423
FX 703/684-2492
JohnSchell     '            .  ,
 ferra, Inc.     .           ....'.
Magnolia Centre 1,1203 Gov. Sq. Blvd..
Tallahassee, FL 32301
PH  904/422-0253    '          <  -
FX  904/422-0333
Glen Schmiesing
Hercules Incorporated
.1313 N. Market Street
Wilmington, DE 19894-0001
PH 302/594-6581
FX 302/594-7255
Thomas Schultz  .       •         .    •    -
U.S. Fish and Wildlife Service
c/o TAMU-CC, Campus Bx 338,6380 Ocean P'riv.e
Corpus Christ!, TX 78412       ..            .
PH 512/994-9005                  .   - '
FX 512/994-8262     .    "      '      '     .
Glen Schuster
ATTN: CESAJ-PD-EE (Schuster)
P.O. Box 4970
Jacksonville, FL  32232
PH 904/232-3691
Dick Schwer
DuPo'nt          ,-
1007 MarketStreet
Wilmington, DE 19713
PH 302/774-8024
FX 302/774-8110  ,
Jennifer Scott
EVS Environmental Consultants
290 Broadway, #1831
New York, NY 10007
PH. 212/637-3257    '
FX 212/637-3253
 Wary Searing    .   •   . .
 Maryland DNR/Tawes State Office Building
 580 Taylor Ave                  •.  .
 Annapolis, MD 21401,         '• -    .
 PH 410/974-2988
 FX 410/974-2833
Burt Shephard
URS Greiner, Inc,
1100 Olive Way, Suite 200
Seattle, WA 98101-1832
 Dave Shepp
 MWCOG  "
 777 N. Capitol Street, NE  Suite 300
 Washington, DC. 20002-4201
 PH 202/962-3349       ' .  .   :
 FX 202/962-3201        .    .
Cynthia Shoemaker
University, of Maryland, Ches. Biol. Lab.
P.O. Box 38'
Solomons, MD  20688
PH 410/326-7384
FX 410/326-7341
 Mohsin Siddique  r          ....
 Environmental Regulation Administration
 2100 Martin Luther King Jr. Avenue, SE, Suite 203
 Washington, DC 20020'
 PH 202/645-6622
 FX 202/645-6617                    •  "'  ,
 Debbie Siebers (G-9J)
 U.S. EPA/GLNPO
 77 W.Jackson Street
 Chicago, IL 60604
 PH 312/353-9299.   .
 FX 312/353-2018

-------
                                                LIST OF ATTENDEES (continued)
Gajlndar Singh
Environmental Regulation Administration
2100 Matin Lute King Jr. Ave,, SE, Suite 203
Washington, DC 20020
PH 2021645-6622
FX 202/645-6617
Tim Sinnott
NYS DEC, Bureau of Env. Protection
50 Wolf Road
Albany, NY 12233-4756
PH 518/457-1769  •
FX '518/485-8424
 Michael Sivak.
 Maryland Department of the Environment
 2500 Broening Highway
 Baltimore, MD 21224
 PH 410/631-3603
 FX 410/633-0456
Jim Slzwnor e
Alexandria Sanitation Authority
P.O. Box 1987
Alexandria, VA  22313
PH 703/549-3381
FX 703/519-9023
Chris Skalski
Ohio EPA, Div. of Surface Water
1800 Watermark Drive, P.O. Box 1049
Columbus, OH 43216-1049
PH 614/644-2144
FX 614/644-2329
 Ron Sloan
 NYS DEC, Bureau of Env. Protection
 50 Wolf Road
 Albany, NY 12233-4756
 PH  518/457-1769
 FX 518/485-8424
Paul Slum (C-}3
Maryland DNR, Power Plant Research Prog. (B-3)
Tawes State Office Building
Annapolis, MD 21401-2397
PH 410/974-2261
FX 410/974-3770
Patty Smith (5204G)
U.S. EPA/OERR, Analytical Operations Center
401 M Street, SW
Washington, DC  20460
PH 703/603-9019
FX 703/603-9112
John Smith
Aluminum Company of America, ALCOA Tech. Ctt
100 Technical Drive
ALCOA Center, PA  15221
PH 412/337-5432'.
FX 412/337-5315
Lany Smith
Los Angetes Harbor Department
P.O. Box 151
San Pedro, CA 90733-0151
PH 310/732-3914
FX 310/547-4643
Jerry Smrchek (7403)
U.S. EPA/OPPT
401 M Street, SW
Washington, DC  20460
PH 202/260-1268
FX 202/260-1236
Jean Snider
NOAA/HAZMAT c/o USCG (G-MRO)
2100 20th Street, SW
Washington, DC 20593
PH 202/267-0605
FX 202/267-4497
StanSobczyk
NezPerce Tribe
P.O. Box 365
Lapwai, ID 83540
PH 208/843-7375
FX 2081843-7378
Betsy Southerland (4305)
U.S. EPA/OST
401 M Street, SW
Washington, DC  20460
PH 202/260-3966
FX 202/260-9830
Leanne Stahl (4305)
U.S. EPA/OST/SASD
401 M Street, SW
Washington, DC 20460
•PH 202/260-7055
FX 202/260-9830
John Stansbury
University of Nebraska
W384 Nebraska Hall, UNL
Lincoln, NE 68588
PH 402/554-3896
FX 402/554-3288
Bill Starkel
Brown and Root Environmental
900 Trail Ridge Road
Aiken, SC 29803        •   .
PH  803/649-7963
FX  803/642-8454
Jeff Steevens
University of Mississippi
Department of Pharmacology
University, MS 38677
PH 601/232-5720
FX 601/232-5148
Robert Stein
Aware Environmental, Inc.
9305-J Monroe Road
Charlotte, NC 28270
PH 704/845-1697
FX 704/845-1759
Dianne Stephan
Atlantic State Marine Fisheries Comm.
1444 Eye Street, NW, 6th floor
Washington, DC 20005
PH  202/289-6400
FX  202/289-6051
 Marty Stevenson
 Kinnetic Laboratories, Inc.
 55-1 Puapake Place
 Lahaina, HI 96761
 PH 808/661-1110
 FX 808/661-0766

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                                                LIST OF ATTENDEES (continued)
 Stephanie Stirling  •
 U.S. ACE/CENPS-Operations
 P.O. Box 3755
 Seattle, WA 98124-2255
 PH 206/764-6945
 FX 206/764-6602
  Edwal Stone
  MD Dep't. of the Env., Indust. Dis. Perm. Div.
  2500 Broening Highway
  Baltimore, MD 21224
  PH 410/631-3323
  FX 410/6314894
 Betsy Stripiin
 Striplin Environmental Associates
 6541 Sexton Drive NW, Suite E-1
 Olympia, WA 98502   •
 PH 360/866-2336
 FX 360/866-4816
 Janet Stull
 Los Angeles County Sanitation Districts
 1955 Workman Mill Road
 Whittier, CA 90601-1400
 PH 310/699-7411x7411     •
 FX 310/692-5103
 Anthony Sturtzen
 ALCOA
 4879 State Street (BldgSOOB)
 Riverdale, IA 52722
 PH" 319/344-1628
 FX 319/344-1967
 LoreleiSuit
 The Weinberg Group, Inc.'   '
 122019th Street, NW, Suite 300
 Washington, DC  20036
 PH  202/833-8077
 FX  202/833-4157
 Jesse Suit
 815 Beverly Avenue
 Bethlehem, PA 18018
 PH 610/868-8333
 Laurie Sullivan
 NOAA/U.S. EPA Region 9
 75 Hawthorne Street
 San Francisco, CA  94105
 PH 415/744-3126
 FX 415/744-3123'
 Susan Svirsky
 US EPA Region 1.0SRR
 HBS, JFK Building
 Boston, MA 01966
 PH 617/573-9649
 FX 617/573-9662
 James Swart
 NYS Department of Env. Conservation
 Rm 302,50 Wolf Road
 Albany, NY 12233-3503
 PH 518/457-0720
 FX 518/485-7786   v '
 Chris Swenson
 U.S. Fish and Wildlife Service   '
 300 Ala Moana Blvd.; Room 3108
 Honolulu, HI 96850
 .PH 808/541-3441
 FX 808/541-3470
 Michael Swindell
 DuPont Environmental
 231 OOldfield Point Road
 Elkton, MD 21921
 PH 302/992-6767
 FX 302/892-7637
Stephanie Syslo (47507 C)
U.S. EPA
401 M Street, SW
Washington, DC 20460
PH 703/305-6355
FX 703/305-6309
 Bill Tate( 4305)
 U.S. EPA/OST
 401 M Street, SW
• Washington, DC 20460
 PH 202/260-7052
 FX 202/260-9830
Kok-Leng Tay
Environment Canada
45 Alderney Drive
Dartmouth, Novia Scotia, CAN  B2Y 2N6
PH 902/426-8304
FX 902/426-3897'
Emmit Taylor
Nez Perce Tribe, Environ. Rest. & Waste Mgmt
P.O. Box 365
Lapwai, ID 83540
PH 208/843-7375
FX 208/843-7378                 '
 Patti Tenbrook
 East Bay Municipal Utility District
 P;0. Box24055
'Oakland, CA 94623
 PH 510/287-1427
 FX 510/465-5462
JeffThielker
Plexus Scientific Corporation
12501 Prosperity Drive, Suite 401
Silver Spring, MD  20904
PH 301/622-9696
FX 301/622-9693
Robert Thomann
Manhatten College
4513 Manhatten College Pkwy
Riverdale, NY  10471
PH  718/862-7947   '  . •
 Nelson Thomas
 Mid-Continent Ecology Division/US EPA/ORD
 6201 Congdon Blvd
 Duluth.MN 55804"
 PH 218/720-5702
 FX 218/720-5539  . "  -'           •   '
Emmy Thomee
NYS DEC, Bureau of Env. Protection
50. Wolf Road
Albany, NY  12233-4756
PH 518/457-8825
FX 518/485-8424

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                                                LIST OF ATTENDEES (continued)
Dennis Tiniberlake
U.S. EPA/ORD/Naltonal Risk Mgmt Res. Lab
26 W.Martin Luther King Drive
Cindnali,OH 45268
PH 513669-7547
FX 513/569-7676
 Lial Tischler
 Tischler/Kocurek
 107 South Mays Street
 Round Rock, TX 78664
 PH 512/244-9058
 FX 512/388-3409
Erick Tokar
Rayonier Inc.
409 E. Harvard Ave."
Shelton, WA 98584
PH 360/427-8245
FX 360/426-7537
AIToimsoff
PPG Industries Inc. - Chemicals
One PPG Race
Pittsburgh, PA 15272
PH 412/434-2084
FX 412/434-2137
 Douglas Tomchuk
 U.S. EPA Region 2
 290 Broadway, 20th floor
 New York, NY  10007-1866
 PH 212/637-3956
 FX 212/637-4284
 Dave Tomey
 U.S. EPA Region 1
•JFK Federal Building, CWQ
 Boston, MA 02203
 PH 617/565-3573
 FX 617/565-4940
Greg Tracey
SAIC
165 Dean Knauss Drive
Narragansett, RI 02882
PH 401/782-1900
FX 401/782-2330
 Wayne Trulli
 Battelle Ocean Sciences
 397 Washington Street
 Duxbury, MA  02360
 PH 617/934-0571
 FX 617/934-2124
 Marc Tuchman
 Great Lakes National Program Office
 77 W. Jackson Blvd
 Chicago, IL 60604
 PH 312/353-1369     .          ;'
 FX 312/353-2018
PaitiLynne Tyler
U.S. EPA New England
60 Westview Street
Lexington, MA 02173
PH 617/860-4342
FX 617/860-4397
 Philip Valent 7401
 Naval Research Laboratory
 Stennis Space Center, MS 39529-5004
 PH  601/688-4650
 FX  601/688-4093
 Pablo Valentin
 U.S. EPA Region 5
 77 West Jackson Blvd
 Chicago, IL 60604
 PH 312/353-5592
 FX 312/886-4071
 Paul Vandermeer
 Ohio EPA
 1685 Westbelt Drive
 Columbus, OH  43228
 PH 614/728-3392
 FX 614/728-3380
• Oilman Veith(MD-51)
 US EPA/ORD
 Ecology/Natl Health & Env. Effects'Res. Lab.
 Research Triangle Park, NC 27711
 PH 919/541-3554
 FX 919/5444621
 David Velinsky
 Academy of Natural Sciences
 1900 Ben Franklin Parkway
 Philadelphia, PA  19103
 PH  215/299-1147
 FX  215/299-1079
 Carlos Vktoria-Rueda
 Parsons Engineering Science
 8000 Centre Park Drive, Suite 200
 Austin, TX 78754
 PH 512/719-6000
 FX 512/719-6099
 Ching Volpp
 NJ Department of Environmental Protection
 401 East State Street
 Trenton, NJ 08625-0418
 PH 609/292-0687               '
 FX 609/292-0687
 Tony Wagner
 Chemical.Manufacturers Association
 1300 Wilson Blvd              ..   ,
 Arlington, VA 22209
 PH  703/741-5248 '  :   :
 FX  703/741-6099  '
 Sherry Waiker
 Environment Canada
 351 St. Joseph Blvd., 8lh floor
 Hull, Quebec,  K1AOH3
 PH 819/953-3117
 FX 819/953-0461
 Claudia Walters 5204G
 U.S EPA/OERR/AOC
 401 M Street, SW  .
 Washington, DC 20460
 PH 703/603-8847  '
 FX 703/603-9112
 James Warchall
 Sidley and Austin
 One First National Pjaza
 Ghicago.JL  60603'  •
 PH 312/853-7692    .
 FX 312/853-7036 .

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                                                 LIST OF ATTENDEES (continued)
 Kimberly Warner
 University of Maryland, Ches. Biol. Lab.
 P.O. Box 38
 Solomons, MD 20688
 PH 410/326-7409
 FX 410/326-7341
  Malcolm Watts
  Zeneca, Inc.  •
  Concord Pike
  Wilmington, DE 19897
  PH 302/886-3085
  FX 302/886-5933
 JeffWaugh
 Army Environmental Center
 Restoration Division, SFI17-AEC-RPO
 Aberdeen Proving Ground, MD 21010
 PH 410/671-1615
 FX 410/671-1635
 PeddrickWeis
 UMDNJ - New Jersey Medical-School
 Department of Anatomy
 Newark,  NJ 07103         ,
 PH  201/982-4409
 FX  201/982-7489
  Laura Weiss                    .
  Washington Department of Ecology/Central Prog
  Olympia, WA 98504-7703
  PH 360/407-7446
  FX 360/407-6904
 Lynn Wellman
 U.S. EPA Region 4,4 WD^OTS
 100 Alabama Street, S.W.
 Atlanta, GA 30303
 PH 404/562-8647
 FX 404/562-8627
 Steve Wharton    ,' •
 U.S. EPA Region 7   '
 726 Minnesota Avenue
 Kansas City, KS 66101
 PH 913/551-7819
 FX 913/551-7063
  Ray Whittemore
  NCASI-Tufts University
  Anderson Hall
  Medford, MA 02155
  PH 617/627-3254
  FX 617/627-3831
 Lyman Wible
 RMTlnc.  '     .
 744 Heartland Trail •
 Madison, Wl 53717
 PH  608/831-4444
 FX  608/831-3334
 Sheila Wiegman
 American Samoa EPA
 Executive Office Building
 Pago Pago, AS 96799
 PH 011/684-633-2304
 FX 011/684-6335801
  Steve Willey
  U.S. Department of Justice
  P.O. Box 7611
  Ben Franklin Station
  Washington, DC 20044
  PH 202/514-2807
 Les Williams        ,
 Foster Wheeler Environmental Corp.
. 10900 NE 8th Street, Suite 1300
 Bellevue, WA 98004-4405
 PH 206/688-3717   -
 FX 206/688-3942
 Philip Williams
 Ohio EPA
 347 R.Dunbridge Road
 Bowling Green, OH 43402
 PH 419/373-3047
 FX 419/352-8468
 Donald Wilson
 D.E. Wilson and Associates
 9600N.E.'Timberlane
 Bainbridge Is., WA 98110
 PH 206/780-2124
 FX 206/780-1147
 Parley Winger
 Dept. Interior National Biological Service     •
 Univ. of Georgia, School of Forest Resources
 Athens, GA 30602  '
 PH 706/546-2146,
 FX 706/546-2186
Trevor Winton
Sinclair Knight.Merz Pty Lt2
P.O. Box 164 St. Leonards
Sydney,.NSW, Australia, 2065
PH (2)99282100
FX (2)99282504
 Stephen Woock
 Weyerhaeuser Southern Env. Field Station
 Box 1391
 New Bern, NC 28563
 PH 919/633-7351              '
 FX 919/633-7634
Jack Word
Battelle Marine Sciences Laboratory
1529 W. Sequim Bay Road
Sequim, WA 98382
PH 360/681-3668
FX 360/681-3681
David Young
Naval Research Laboratory   •
Stennis Space Center, MS 39529
PH .601/688-5507
FX 601/088-5379
 Allison Yuhas
 Ogden Environmental
' 239 Littleton Road, Suite 7C
 Westford, MA 01886
 PH  508/692-9090
 FX  508/692-6633
Drew Zacherle  .
Tetra Tech, Inc.
10306 Eaton Place, Suite 340
Fairfax, VA 22030   .
PH  703/3853000
FX  703/385-6007

-------
                                              LIST OF ATTENDEES (continued)
John Zambrano
NYS Department of Env. Conservation
50 Wolf Road
Albany, NY 12233-3502
PH  518/457-6997
FX  518/485-7786
Lawrence Zaragoza (5204G)
U.S. EPA/OERR
401 M Street, SW
Washington, DC 20460
PH 703/603-8850
FX 703/603-9103
Chris Zarba (8101)
U.S. EPA/ORD
401 M Street  ,   '
Washington, DC 20460
PH 202/260-1326
FX 202/260-9761
Jennifer Orme Zavaleta
U.S. EPA
401 M Street, SW
Washington, DC 20460
PH 202/260-7586
FX 202/260-1036
Maurice Zeeman (7403)
U.S. EPA/OPPT
401 M Street, SW
Washington, DC 20460
PH 202/260-1240
FX 202/260-1236
Xin Zhang
Alpha-Omega Chemical Company
9311 Groh Road
Grosselle.MI 48138
PH 313/692-7631
FX 313/692-7622
Edward Zillfoux
Florida Risk-Based Priority Council
P.O. Box 088801
N, Palm Beach, FL 33408
PH  561/625-7621
FX  561/625-7665
Roger Zirk
Normandeau Associates
3450 Schuyklll Road
Spring City, PA 19475
PH 610/948-4700
FX 610/948-4752
* U. S. GOVERNMENT PRINTING OFFICE: 1998-618-516/90626

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