Unfted States
Environmental Protection
Office of Water
Regulations and Standards
Criteria and Standards
Washington, DC 20460
EPA 440/549-002
April 1989
Water
Briefing Report
to the
EPA Science Advisory Board
on the
Equilibrium  Partitioning Approach
to  Generating  Sediment
Quality Criteria

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             BRIEFING REPORT

                  to the

       EPA SCIENCE ADVISORY BOARD

                  on the

    EQUILIBRIUM PARTITIONING APPROACH
 TO GENERATING SEDIMENT QUALITY CRITERIA
                April 1989
  U.S. ENVIRONMENTAL PROTECTION AGENCY
             OFFICE OF WATER
OFFICE OF WATER REGULATIONS AND STANDARDS
     CRITERIA AND STANDARDS DIVISION

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                                 DISCLAIMER
This report has been  reviewed by  the  U.S.  Environmental  Protection Agency  and
approved  for  publication.   Approval does  not  signify that  the  contents
necessarily reflect the views and  policies of the U.S. Environmental Protection
Agency.

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                                   CONTENTS

Section

         FIGURES	       ill

         TABLES	        x

         SUMMARY	        1

   1     INTRODUCTION  	      1- 1

   2     SELECTION OF A METHODOLOGY  	      2- 1
         2.1  STATUTORY BASIS - CLEAN WATER ACT  	      2- 1
         2.2  AVAILABLE APPROACHES FOR DEVELOPING SEDIMENT QUALITY
              CRITERIA 	      2- 2
         2.3  RATIONALE FOR SELECTING THE EQUILIBRIUM PARTITIONING
              METHOD 	      2- 3
         2.4  RELATIONSHIP TO WATER QUALITY CRITERIA METHODOLOGY  	      2-3
         2.5  APPLICATIONS OF SEDIMENT CRITERIA	      2- 5
         2.6  COMPUTING SEDIMENT QUALITY CRITERIA	      2-8

   3     TOXICITY AND BIOAVAILABILITY OF CHEMICALS IN SEDIMENTS 	      3-1
         3.1  TOXICITY EXPERIMENTS 	      3- 1
         3.2  BIOACCUMULATION 	      3- 6
         3.3  CONCLUSION  	      3-10

   4     NON-IONIC ORGANIC CHEMICALS 	      4- 1
         4.1  PARTITIONING IN PARTICLE SUSPENSIONS 	      4- 1
              4.1.1   Particle Concentration Effect 	      4- 2
         4.2  DISSOLVED ORGANIC CARBON (DOC) COMPLEXINC  	      4-8
         4.3  PHASE DISTRIBUTION IN SEDIMENTS  	      4- 9
         4.4  BIOAVAILABILITY OF DOC COMPLEXED CHEMICALS  	      4-14
         4.5  FIELD OBSERVATIONS OF PARTITIONING IN SEDIMENTS  	      4-14
              4.5.1   Organic Carbon Normalization 	      4-17
              4.5.2    Sediment - Pore Water Partitioning  	      4-26
         4.6  ORGANIC CARBON NORMALIZATION OF BIOLOGICAL RESPONSES  	      4-28
              4.6.1   Toxicity Experiments 	      4-30
              4.6.2    Bioaccumulation and Organic Carbon
                      Normalization  	      4-30
         4.7  DETERMINATION OF THE ROUTE OF EXPOSURE 	      4-44
         4.8  FIELD VALIDATION 	      4-45
              4.8.1    Screening Level Methodology 	      4-47
              4.8.2    Determining Screening Level Concentrations  	      4-49
         4.9  CONCLUSION  	      4-53

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                                   CONTENTS
                                  (Continued)

Section                            "                                         Page

   5     APPLICABILITY OF USING WATER QUALITY CRITERIA AS THE EFFECTS
         LEVEL FOR BENTHIC ORGANISMS 	     5- I
         5.1  METHOD - RELATIVE ACUTE SENSITIVITY	     5-1
         5.2  BENTHIC COMMUNITY COLONIZATION EXPERIMENTS 	     5-5
         5.3  COMPARISON OF THE SENSITIVITY OF BENTHIC AND WATER
              COLUMN SPECIES 	     5- 5
         5.4  WATER QUALITY CRITERIA CONCENTRATIONS VERSUS COLONIZATION
              EXPERIMENTS 	     5-10
         5.5  CONCLUSIONS 	     5-16

   6     APPROACH FOR DEVELOPMENT OF SEDIMENT QUALITY CRITERIA
         FOR METALS	     6- 1
         6.1  THE PROBLEM 	     6- 1
         6.2  TOXICITY CORRELATES TO METAL ACTIVITY 	     6-2
         6.3  METAL SORPTION MODELS 	     6- 8
              6.3.1   Three Phase Metal Sorption Model 	     6- 8
         6.4  EXTRACTION AND PHASE NORMALIZATION 	     6-11
              6.4.1   Bioavallable Fraction	     6-11
              6.4.2   Partition Coefficients	     6-12
         6.5  DEVELOPMENT OF SEDIMENT QUALITY CRITERIA FOR METALS 	     6-14
              6.5.1    Extraction Methodology 	     6-14
              6.5.2   Sorption Model 	     6-16
         6.6  ONGOING STUDIES 	     6-16
              6.6.1   Sediment Toxicitv Experiments 	     6-16
              6.6.2   Metal Partitionine	     6-17
              6.6.3   Sulfide Precipitation	     6-17
         6.7  CONCLUSION  	     6-17

   7     GENERATION OF SEDIMENT QUALITY CRITERIA 	     7- 1
         7.1  METHOD TO CALCULATE SEDIMENT QUALITY CRITERIA
              UNCERTAINTY 	     7- 1
         7.2  PRELIMINARY SEDIMENT QUALITY CRITERIA VALUES FOR
              NON-IONIC ORGANIC CHEMICALS 	     7- 3
         7.3  CONCLUSIONS 	     7- 7

   8     REFERENCES  	     8- 1
                                       ii

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                                    FIGURES

Number

 3-1     Comparison of percent survival (left) and growth rate
         reduction (right) of Chironomus tentans to kepone
         concentration in bulk sediment (top) and pore water (bottom)
         for three sediments with varying organic carbon
         concentrations	     3- 4

 3-2     Comparison of percent survival of Rhepoxvnlus abronius to
         fluoranthene (left) and cadmium (right) concentration in bulk
         sediment (top) and pore water  (bottom) for sediments with
         varying organic carbon concentrations	     3- 6

 3-3     Comparison of percent survival of Hyalella to DDT (left) and
         endrin (right) concentration in bulk sediment (top) and pore
         water (bottom) for sediments with varying organic carbon
         concentrations	     3- 8

 3-4     Comparison of percent survival of Ampelisca (left) and
         Rheooxvnius (right) to concentrations of cadmium in bulk
         sediment (top) and pore water (bottom).  Also presented is
         water-only exposure data, identified with open circles	     3-9

 3-5     Comparison of Chironomus tentans body burden of permethrin
         (left) and cypermethrin (right) versus concentration in bulk
         sediment (top) and pore water (bottom) for sediments with
         varying organic carbon concentrations	     3-12

 3-6     Comparison of Chironomus tentans body burden of kepone versus
         concentration in bulk sediment (top) and pore water (bottom)
         for sediments with varying organic carbon concentrations.
         (Body Burdens calculated from average bioaccumulation factors.
         Data:  Adams et al. , 1983)	     3-13

 4-1     Comparison of observed partition coefficient to calculated
         partition coefficient using Equation (4-2) (Di Toro, 1985)	     4- 4

 4-2     Comparison of the adsorption (top) and reversible component
         (bottom) organic carbon normalized partition coefficient, Koc,
         to the octonal-water partition coefficient. Kou, for
         experiments with low solids concentrations:  mfoc Kow < 1.
         The line represents equality (Di Toro, 1985)	     4- 5
                                      iii

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                                    FIGURES
                                  (Continued)
Number
 4-3     Partition coefficients of chemicals to particulate organic
         carbon (POC), Aldrich humic acid  (AHA), and natural DOC.
         Benzo(a)pyrene (BaP); 2,2',4,4',5,5' hexachlorobiphenyl
         (HCBP); DDT; 2,2',5,5' tetrachlorobiphenyl (TCBP); pyrene
         (PYR); 4 monochlorobiphenyl (MCBP).  (Data:  Eadie et al.,
          1988)	     4-10

 4-4     Phase distribution of a chemical  in the three phase system:
         water, sediment, and DOC (Equation .4-11),  KQC -  KDOC ~ Kow ~
         106 L/kg, foc - 2.OX and m - 0.5  kg/L	     4-12

 4-5     Average uptake rate of chemicals  by Pontoporeia hoyi with
         (filled) and without (hatched) DOC present.  Benzo(a)pyrene
         (BaP); 2,2',4,4' tetrachlorobiphenyl (TCBP); Pyrene (Pyr);
         Phenanthrene (Fhen) (Data:  Landrum et al., 1987)	     4-15

 4-6     Comparison of logio of the DOC partition coefficient
         calculated from the suppression of chemical uptake versus the
         C-18 reverse phase HPLC column estimate.  Circles are Aldrich
         humic acid;  triangles are interstitial water DOC.  Chemicals
         are listed on Figure 4-3 and Figure 4-5 captions  (also
         anthracene and benzo(a)anthracene)	     4-16

 4-7     The organic  carbon fractions (X dry weight) in the unseparated
         sediment (BULK) and separated sediment fractions: the low
         density fraction >64 urn, <1.9 gm/cc (LOW); the sand sized
         fraction >64um, >1.9 gm/cc (SAND); the silt/clay  sized
         fraction <64um.  In one case (station 4) this fraction was
         further separated into the clay and silt sized faction.
         Numbered stations as indicated; Wells Dam, (WD);  Tongue Point
         (TP)  (Data:  Prahl, 1982)	     4-19

4-8A     Sediment chemical concentrations  for each chemical on a dry
         weight (left side) and an organic carbon basis (right side)
         for the bulk sediment concentration (filled) and  the sediment
         fractions for each station.  The  bars in the plot are ordered
         as follows:  for Station 4) bulk,  low density, clay, silt, and
         sand;  Stations 5 and 7) bulk, low density, silt/clay, and
         sand;  Wells  Dam and Tongue Point) bulk, and low density (Data:
         Prahl, 1982)	     4-20
                                       iv

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                                    FIGURES
                                  (Continued)

Number                                                                       Page

4-8B     Sediment chemical concentrations  for each chemical on a dry
         weight (left side) and an organic carbon basis  (right side)
         for the bulk sediment concentration (filled) and the sediment
         fractions for each station.  The bars  in the plot are ordered
         as follows:  for Station 4) bulk, low density,  clay, silt, and
         sand; Stations 5 and 7) bulk, low density, silt/clay, and
          sand; Wells Dam and Tongue Point) bulk, and low density
         (Data: Prahl, 1982)	      4-21

 4-9     Dry weight normalization.  Comparison of (top panel) the bulk
         sediment concentration for all PAHs (x axis) with the sane
         chemical concentration in the individual sediment fractions  (y
         axis) on a dry weight basis.  Bottom panel presents a
         probability plot of the ratio of these quantities for the
         three size fractions (Data:  Prahl, 1982)	      4-22

4-10     Organic carbon normalization.  Comparison of (top panel) the
         bulk sediment concentration for all PAHs (x axis) with the
         same chemical concentration in the individual sediment
         fractions (y axis) on an organic carbon basis.  Bottom panel
         presents a probability plot of the ratio of these quantities
         for the three size fractions (Data:  Prahl, 1982)	      4-23

4-11     Dry weight normalization with foc > 0.5Z.  Comparison of (top
         panel) the bulk sediment concentration for all PAHs (x axis)
         with the same chemical concentration in the individual
         sediment fractions (y axis) on a dry weight basis.   Bottom
         panel presents a probability plot of the ratio of these
         quantities for the three size fractions (Data:  Prahl,  1982).       4-24

4-12     Organic carbon normalization with foc > 0.5Z.  Comparison of
         (top panel) the bulk sediment concentration for all PAHs (x
         axis) with the same chemical concentration in the individual
         sediment fractions (y axis) on an organic carbon basis.
         Bottom panel presents a probability plot of the ratio of these
         quantities for the three size fractions (Data:  Prahl,  1982-).      4-25

4-13     Observed partition coefficient versus the product of organic
         carbon fraction and octanol-water partition coefficient.   The
         line represents equality.  The partition coefficients are
         computed using total dissolved PCB  (*) and using free PCB (o)
         computed using Equation (4-20) with KDOC ~ Kow	     4-27

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                                    FIGURES
                                  (Continued)

Number                                                                      Page

4-14     Observed partition coefficient versus the product of organic
         carbon fraction and octanol-water partition coefficient.  The
         lines represent the expected relationship for DOC
         concentrations of 0, 1, 10 and 100 mg/L and KQQC ~ Kow.  Data
         from Oliver (1987) for PCB congeners and other chemicals (A),
         from Socha and Carpenter (1987) for Phenanthrene (B),
         Fluoranthene (C) and Perylene (D) and from Kadeg and Pavlou
         (1987) for Naphthalene (E), Phenanthrene (F), Pyrene (G),
         Anthracene (H) and Flouranthene .(I)	     4-29

4-15     Comparison of percent survival (left) and growth rate
         reduction (right) of Chironomus tentans to kepone
         concentration in pore water (top) and in bulk sediment using
         organic carbon normalization (bottom) for three sediments with
         varying organic carbon concentrations	     4-31

4-16     Comparison of percent survival of Hyalella to DDT (left) and
         endrin (right) concentration in pore water (top) and in bulk
         sediment using organic carbon normalization (bottom) for three
         sediments with varying organic carbon concentrations	     4-32

4-17     Comparison of percent survival of Rhepoxvnius abronius to
         fluoranthene concentration in pore water (top) and bulk
         sediment using organic carbon normalization (bottom) for
         sediments with varying organic carbon concentrations	     4-33

4-18     Comparison of body burden of Chironomus tentans to kepone
         concentration in pore water (top) and bulk sediment using
         organic carbon normalization (bottom) for sediments with
         varying organic carbon concentrations.  (Body burdens
         calculated from average bioaccumulation factors.  Data:  Adams
         et al., 1983.)	     4-35

4-19     Probability plots of the bioaccumulation factor (ratio of
         organism to sediment concentration) of a 2,2',4,4'tetrachloro
         biphenyl using dry weight normalization for both organism and
         sediment (top panels); organic carbon normalization for the
         sediment (middle panels); and organic carbon and lipid
         normalization (bottom panels).  Two experiments (A and B)
         involving four benthic organisms: Yoldia (A), Nephtys (A),
         Nereis (A and B), and Macoma (B) and five sediments (1,2,3 for
         A; 1,4,5 for B) are shown	     4-39
                                      vi

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                                    FIGURES
                                  (Continued)

Number                                                                       Page

4-20     Probability plots of the bioaccumulation factor  (ratio of
         organism to sediment concentration) of a 2,2'3,5,5',6
         hexachloro biphenyl using dry weight normalization for both
         organism and sediment (top panels); organic carbon
         normalization for the sediment (middle panels);  and organic
         carbon and lipid normalization (bottom panels).  Two
         experiments (A and B) involving four benthic organisms: Yoldia
         (A), Nephtys (A), Nereis (A and B), and Macoma (B) and five
         sediments (1,2,3 for A; 1,4,5 for B) are shown	      4-40

4-21     Plots of the bioaccumulation factor (ratio of organism to
         sediment concentration) of a series of PCB congeners versus
         Log Kow for that congener using dry weight normalization for
         both organism and sediment (top panels); organic carbon
         normalization for the sediment (middle panels);  and organic
         carbon and lipid normalization (bottom panels).  Two
         experiments (A and B) involving four benthic organisms: Yoldia
         (A), Neohtvs (A), Nereis (A and B), and Macoma (B) and five
         sediments (1,2,3 for A;  1,4,5 for B) are shown	      4-42

4-22     Plots of the bioaccumulation factor (ratio of organism lipid
         to  sediment organic carbon concentration) for a  series of PCB
         congeners versus Log Kow (Data:  Oliver, 1987 and Rubenstein
         et  al., 1988)	      4-43

4-23A    Probability distribution of organic carbon normalized
         benzo(a)pyrene sediment concentration for sediments in which
         the indicated species was found to coexist (see  SCO 7 for the
         species identification)	      4-50

4-23B    Probability distribution of organic carbon normalized
         benzo(a)pyrene sediment concentration for sediments in which
         the indicated species was found to coexist (see  SCO 7 for the
         species identification)	      4-51

4-24     Probability distribution of the 90th percentile sediment
         ..concentrations for benzo(a)pyrene (third panel on left, with
         data  from Figure 4-23A and 4-23B) and for ten other other
         compounds	      4-52

  5-1     Comparison of LC50 or EC50 acute values for the most sensitive
         benthic and water column species from 30 saltwater water
         quality criteria documents.  Benthic species are defined as
         infaunal species (habitat types 1 and 2) and water column
         species are defined as those species having a lesser
         association with sediments (habitat types:  3 to 8).   The line
         is  the line of equal sensitivity	      5- 7

                                      vii

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                                    FIGURES
                                  (Continued)

Number                                                                       Page

 5-2     Comparison of LC50 or EC50 acute values for the most sensitive
         benthic and water column species from 36 freshwater and 30
         saltwater quality criteria documents.  Benthic species are
         defined as infaunal species  (habitat types 1 and 2) and water
         column species are defined as those species having a lesser
         association with sediments (habitat types 3 to 8).  Only
         chemicals for which species  from 3 or more infaunal phyla have
         been tested are included.  The line is the line of equal
         sensitivity	      5- 8

 5-3     Comparison of LC50 or EC50 acute values for the most sensitive
         benthic and water column species from 36 freshwater and 30
         saltwater water quality criteria documents.  Benthic species
         are defined as infaunal and  epibenthic species (habitat types
         1 to 4) and water column species are defined as those species
         having a lesser association  with sediments (habitat types 5 to
         8).  The number of freshwater benthic species tested ranged
         from 2 to 26.  The number of saltwater benthic species tested
         ranged from 5 to 26.  The line is the line of equal
         sensitivity	      5- 9

 5-4     Comparison of histograms of  the relative acute sensitivity
         (Equation 5-1) of benthic and water column freshwater species
         as derived from the 36 water quality criteria documents.
         Histograms show the percentage of benthic and water column
         species with acute values within the indicated percentile
         ranges of the pooled data.   Benthic species are defined as
         infaunal species	      5-11

 5-5     Comparison of histograms of  the relative acute sensitivity
         (Equation 5-1) of benthic and water column saltwater species
         as derived from the 30 water quality criteria documents.
         Histograms show the percentage of benthic and water column
         species with acute values within the indicated percentile
         ranges of the pooled data.   Benthic species are defined as
         infaunal species	      5-12

 5-6     Comparison of histograms of  the relative acute sensitivity
         (Equation 5-1) of benthic and water column freshwater species
         as derived from the 36 water quality criteria documents.
         Histograms show the percentage of benthic and water column
         species with acute values within the indicated percentile
         ranges of the pooled data.   Benthic species are defined as
         infaunal and epibenthic species	      5-13
                                     viii

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                                    FIGURES
                                  (Continued)

Number                                                                       Page

 5-7     Comparison of histograms of the relative acute sensitivity
         (Equation 5-1) of benthic and water column saltwater species
         as derived from the 30 water quality criteria documents.
         Histograms show the percentage of benthic and water column
         species with acute values within the indicated percentile
         ranges of the pooled data.  Benthic species are defined as
         infaunal and epibenthic species	      5-14

 6-1     Acute toxicity to Palaemonetes of total cadmium (top) and
         cadmium activity (bottom) with different concentrations of the
         complexing agents NTA (left) and chloride as salinity (right).      6- 4

 6-2     Acute toxicity to a dinoflagellate (left) of total copper
         (top) and copper activity (bottom), with and without EDTA.
         Chronic toxicity of zinc to Microcystis aeruginosa (right)
         showing growth as cells/ml versus time with different levels
         of EDTA and NTA (top) and number of cells at five days as a
         function of free zinc concentration (bottom)	      6- 5

 6-3     Specific growth rate of a diatom (left) and Monochrysis
         lutheri (right) versus total copper (top) and copper activity
         (bottom) for a range of concentrations of the complexing
         ligands tris and natural DOC	      6- 6

 6-4     Body burden of copper in oysters versus total copper (top) and
         copper activity (bottom) with different levels of the
          complexing ligand NTA	      6- 7

 6-5     Copper (left) and zinc (right) body burdens in molluscs versus
         total sediment metal concentration (top) and extracted
         metal/Fe ratio (bottom)	      6-13

 6-6     Zinc (left) and nickel (right) partition coefficients versus
         pH in comparison to a single phase model of sediment sorption
         (dashed line)	      6-15
                                      ix

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                                    TABLES
Number
 2-1     SUMMARY OF POTENTIAL APPLICATIONS OF SEDIMENT CRITERIA IN
         IMPLEMENTING KEY SECTIONS OF SOME MAJOR ENVIRONMENTAL LAWS	     2-6

 3-1     SEDIMENT TOXICITY DATA	     3- 2

 3-2     DOSE-RESPONSE PARAMETERS	     3- 3

 3-3     BIOACCUMULATION FACTORS	     3-10

 4-1     DOSE-RESPONSE PARAMETERS	     4-34

 4-2     BIOACCUMULATION FACTORS	     4-36

 5-1     DRAFT OR PUBLISHED WATER QUALITY CRITERIA DOCUMENTS AND
         NUMBER OF INFAUNAL (HABITATS 1 AND 2), EPIBENTHIC (HABITATS 3
         AND 4), AND WATER COLUMN (HABITATS 5 TO 8) SPECIES TEST FOR
         EACH OF THE WATER QUALITY CRITERIA DOCUMENTS	     5-2

 5-2     HABITAT CLASSIFICATION SYSTEM FOR LIFE-STAGES OF ORGANISMS	     5- 3

 5-3     COMPARISON OF WATER QUALITY CRITERIA (WQC) FINAL CHRONIC
         VALUES (FCV) AND CONCENTRATIONS AFFECTING (OEC) AND NOT
         AFFECTING (NOEC) BENTHIC COLONIZATION	     5-15

 7-1     COMPARISON OF INTERIM SEDIMENT QUALITY CRITERIA WITH
         SCREENING LEVEL CRITERIA (SLC)	     7-4

 7-2     TABULATION OF FLUORANTHENE SEDIMENT TOXICITY RESULTS PORE
         WATER CONCENTRATIONS AND EP VALUES	     7- 6

 7-3     TABULATION OF FLUORANTHENE SEDIMENT TOXICITY RESULTS ORGANIC
         CARBON NORMALIZATIONS AND EP VALUES	     7- 6

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                                ACKNOWLEDGMENTS

    This document  is  a summary of- the combined efforts  of many persons over a
number of years.  The mention of all who have contributed in one way or another
would be a significant  if  not  impossible  task.   However, there are a number of
individuals who  have  had significant input into  the  technical development and
content of this document. These persons are as follows:
Principal author

    Dominic M. Di Toro

Contributors  (alphabetical order)

    Herbert E. Allen

    Christina E. Cowan

    David J.  Hansen

    Paul R. Paquin

    Spyros P. Pavlou

    Alexis E. Steen

    Richard C. Swartz

    Nelson A. Thomas

    Christopher S. Zarba
Manhattan College/HydroQual.  Inc.
Drexel University

Battelle

EPA Laboratory Narragansett, RI

HydroQual,  Inc.

Envirosphere

Battelle

EPA Laboratory Newport, OR

EPA Laboratory Duluth, MN

EPA Headquarters, Office of
Water Regulation and Standards

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                                                                        Page 1
                                   SUMMARY

    This report has been prepared to  assist  the  EPA Science Advisory Board with
its evaluation of  the  Equilibrium Partitioning  method for generating sediment
quality criteria.   Sediment  quality  criteria as used in  this  report  refer to
numerical values for individual chemicals that are applicable across the range
of sediments encountered  in  practise.   They are intended  to be predictive of
biological effects and  protective  of  the presence  and  uses  of benthic
organisms.  As a consequence  they could be  used in much the  same way as water
quality criteria -  as  the concentration of a chemical  which is protective of
the intended use.

    The specific regulatory  uses of sediment quality criteria have  not been
established.  However,  the range  of potential applications is quite large since
the need  for the  evaluation  of  potentially contaminated sediments arises  in
many  contexts.    Sediment quality criteria are not  meant to  replace  direct
toxicity testing of sediments as a method of evaluation, but  rather to provide
a chemical  by chemical  specification of what  sediment concentrations  would be
protective of aquatic life and their  uses.

TOXICITY AND BIOAVAILABILITY  OF CHEMICALS  IN SEDIMENTS

    The principal  technical  difficulty  that must be  overcome  in establishing
sediment  quality  criteria is  to determine the  extent  of bioavailability  of
sediment  associated  chemicals.   It has frequently been observed  that similar
concentrations of a chemical  in units of mass of chemical  per mass of  sediment
dry  weight (e.g.  /ig  chemical/g sediment) can produce widely different
biological effects in different sediments.  If the purpose of sediment quality
criteria is to establish chemical concentrations that apply across sediments of
differing types   it   is  essential  that  the  reasons  for  this  varying

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Page 2

bioavailability  be understood and  that they  be  explicitly  included  in the
criteria.  Otherwise  the criteria .cannot be presumed  to be applicable across
sediments of differing properties.

    The importance of  this  issue  cannot  be  underestimated.   For example,  if 1
ppm of  kepone  is the LC50  for  an organism  in one sediment and  40  ppm is the
LC50  in another  sediment,  then unless  the cause of  this difference  can be
associated with some explicit sediment properties it is not possible to decide
what the LC50 would be of a third sediment, without a direct toxicity test.

    An  additional  difficulty is  that  the  results of  toxicity  tests  used to
establish the toxicity of chemicals in sediments would not be generalizable to
other sediments.   Imagine  the  situation if the results of  toxicity  tests in
water depended strongly  on the particular water source  -  e.g.,  Lake  Superior
versus  well  water.   Until  the  source  of the differences were understood,  it
would be fruitless to  attempt  to  establish  water quality criteria.  It is for
this  reason  that the  issue of bioavailability  is  a  principal  focus  of  this
report.

    The observation  which  provided   the  key insight to  the  problem  of
quantifying the bioavailability of  chemicals in  sediments  was that  the
concentration-response curve for  the  biological effect  of concern could be
correlated  not  to  the  total  sediment   chemical concentration  (/*g  chemical/g
sediment) but  to the  interstitial water (i.e.,  pore water)  concentration (pg
chemical/liter  pore  water).   Organism  mortality,  growth  rate,   and
bioaccumulation  data were  used to demonstrate  this  correlation,  which  is  a
critical  part of  the  logic behind  the  equilibrium partitioning approach  to
developing  sediment  quality  criteria.   A substantial  amount  of  data  is
presented in the  report  to  illustrate the generality of this finding (Sections
3.1 through  3.3).

    This correlation can be interpreted  in a number of ways.   In particular it
is  premature to  conclude that the route of  exposure for  the  organism  is  only

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                                                                        Page 3

via Che pore water.  The reason is that the solid phase is in equilibrium with
the liquid phase and  the  effective exposure concentration  is  likely to be the
same via  either route.   However" from  a purely empirical  point of  view the
correlation suggests  that  if  it were possible to either (1)  measure  the pore
water  chemical  concentration or  (2)  predict it  from  the total  sediment
concentration  and  the relevant  sediment  properties,  then  that  concentration
could be  used  to quantify the exposure concentration for an  organism.   Thus,
the partitioning of  chemicals  between  the solid  and the  liquid phase  in  a
sediment becomes a necessary component of sediment quality criteria.   It is for
this reason  that the  methodology is called the  equilibrium partitioning (EF)
method.

    In addition,  if it were  true that  benthic  organisms  are  as  sensitive  as
water  column  organisms -  and  as  shown in Section  5  the evidence  appears  to
support  this  supposition  -  then  a  sediment quality  criteria  could be
established  using  the  water  quality  criteria,  C^QC.   as  the  effects
concentration,  and the partition coefficient,  Kp,  to relate the pore  water
concentration  to  the sediment quality criteria concentration,  rgqc via  the
partitioning  equation.   The  calculation procedure is  as follows.   If  CUQC
(pg/L) is  the  water quality  criteria for the chemical of interest,  then the
sediment  quality  criteria,  rgqc  (Mg/kg sediment)  is  computed  using  the
partition coefficient, Kp  (L/kg sediment) between sediment and  water:
         rSQC " KpCWQC

This  is the  fundamental equation  from which  sediment  quality criteria are
generated.    Its  utility depends  upon the  existence of  a methodology  for
quantifying partition coefficients.

PARTITIONING OF NON-IONIC ORGANIC CHEMICALS

    The partitioning of non-ionic organic chemicals between particles  and water
is  reasonably  well  understood  and  a standard model exists for  describing the

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process.    The  chemical property of  importance  is the octanol-water partition
coefficient, Kow.   The  important .particle property  is  the  mass  fraction of
organic carbon, foc.   For  particles  with foc  > 0.5 percent the organic carbon
appears to  be  the predominant sorption  phase.  The partition coefficient, Kp,
the ratio of sediment to pore water concentration is given by:
         K  - f  K
          p    oc oc
where Koc is the partition coefficient for particle organic carbon.

    The  only  other environmental variable  that has a  dramatic  effect on
partitioning  appears  to  be the  particle concentration itself.   There is
considerable controversy  regarding  the  mechanism responsible  for the particle
concentration effect and a number of explanations have been offered.  However,
all  the  interpretations yield the  same  result  for  sediment-pore  water
partitioning,  namely  that KQC  - K
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                                                                         Page 5

as Che organic carbon normalized sediment concentration (fig chemical/kg organic
carbon) then:

         rSQC,OC " KowCWQC

Hence we arrive at the following important conclusion: for a specific chemical,
with a specific KOW, the organic carbon normalized total sediment concentration
is proportional to  the  dissolved  free  effects  concentration,  cyqc, for  any
sediment for foc > 0.5 percent.

    Hydrophobic chemicals  tend to partition to colloidal  sized  organic  carbon
particles   (DOC)  as  well.   Although DOC  affects  the  apparent  pore water
concentrations  of highly hydrophobic chemicals the DOC-bound  chemical  appears
not  to be  bioavailable  and the  above  equation still  applies   (Sections  4.2
through 4.4).   The  available field data for sediment partitioning  is reviewed
and related to the model presented above.

    The above  discussion suggests  that toxicity  and bioaccumulation data  for
sediments should be normalized by the sediment organic carbon concentration.  It
is found  that responses which are quite variable  on a dry weight  normalized
basis are either statistically  equivalent or  the  differences  are significantly
reduced on  an  organic  carbon  basis.   The  low carbon sediments  are seen  to
depart from the normalized results as is expected (Section 4.6).

FIELD VALIDATION OF SEDIMENT QUALITY CRITERIA

    The most convincing  demonstration  that sediment quality criteria are sound
would  be  a  demonstration  that  they  can predict  the degree of toxicity  of
natural sediments.   There are  three technical  difficulties  that apply to  all
field  data  based approaches:   bioavailability,  chemical  mixtures and control
sediments.

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Page 6

Bioavailabilitv

    Contaminated  sediments  contain many  chemicals.    In order  to use  the
magnitude  of the  chemical  concentration  as  a measure  of its potential  to
have  biological effects, it is necessary that its bioavailability in  that
particular  sediment  be assessed.   For  toxic  metals  and  ionic organic
chemicals  there   is  as  yet no  comprehensive  partitioning theory that
identifies the normalization  quantities  and provides  the  parameters  to
predict  free dissolved  concentration.   Hence  bioavailability  cannot  be
directly assessed.

Chemical Mixtures  and  Causality

    If the bioavailability problem were  solved there remains a difficulty with
using naturally  contaminated  sediments.   Just as  with water quality criteria  it
is always possible that there is present another  chemical or chemicals that are
biologically  very active but,  which have yet to  be  identified.   If this
chemical is the  cause  of significant toxicity then it would cause a biological
effect that  would not be predicted from the application of  sediment quality
criteria.

Control Sediments  and  Non Toxic Variations

    Variations  in  sediment  toxicity  test results and  community  structure
can be  caused by  variations  in sediment  characteristics other than
chemical  contamination.   Grain  size  distribution  and  organic  carbon
content are well known examples.   In order  to judge the toxicity of a sediment
it  is  necessary that  a comparative control response  be obtained.   The perfect
control is the same sediment  without any ',chemical contamination.  Since this  is
not available, sediments from an unimpacted site  are assumed to approximate the
response  of  the perfect control.   The  degree to which  this  approximation  is
inappropriate limits the assessment of comparative  toxicity.

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                                                                         Page 7

    These three major  difficulties  appear  to render a direct  field validation
of sediment  criteria beyond current  capabilities.   Nevertheless  it would  be
helpful if some evidence  that  criteria  developed  from  laboratory toxicological
data are at  least  reasonable.   A methodology is presented that  can be  used  to
establish lower bounds for sediment quality criteria from field observations  of
organism presence and sediment chemistry.

EFFECTS CONCENTRATION

    The  other principal  assumption  in the  development  of sediment  quality
criteria  is  that  the water  quality criteria  are  adequate  estimates  of the
effects  concentrations   for  benthic organisms.    Two  sets of  analyses are
presented  to examine  this  question.    The  acute  toxicity data  base from the
water quality criteria are segregated into  benthic and  water  column species and
the  relative  sensitivity of  each  group are  compared  for  the  water  quality
criteria chemicals.    In  addition,  saltwater benthic colonization  experiments
for six chemicals are examined.

    The conclusion  from  this  examination  is that  the sensitivities  of  benthic
species are  sufficiently similar  to  those of  water column  species   to
tentatively  permit the use  of water quality  criteria  for  the  derivation  of
sediment quality criteria in  the equilibrium partitioning approach. The  acute
toxicity data base  derived from the water quality criteria  documents suggests
that the most sensitive  infaunal species  is typically less  sensitive than the
most sensitive  water column (epibenthic and water  column)  species. When both
infauna and  epibenchic species are  classed as  "benthic," the sensitivities  of
the most sensitive benthic  and water column species are  on the average  similar
(Section 5).

UNCERTAINTY

    The  sediment  quality criceria  methodology  employed above  relies on  an
empirical  model  to compute the free interstitial  water  concentration from the
solid  phase  measurements.   As  a consequence  there is an  uncertainty associated

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Page 8

with the  use  of the model.   In addition there is uncertainty  with respect to
the KQW  associated with  the  specific chemical since  it is  an experimentally
determined  quantity.  Finally  the  assumption  that water  column  and  benthic
organisms have similar sensitivities has a level of uncertainty.

    The  quantification  of  the  level  of uncertainty for  sediment  quality
criteria has only been accomplished  in a preliminary way (Section 7.1).   It is
anticipated that  a complete  uncertainty analysis will accompany a  sediment
quality criteria  and that, for example,  95  percent confidence limits  will be
specified as well as the most probable value.

PRELIMINARY SEDIMENT QUALITY CRITERIA

    An  initial attempt   to  compute  equilibrium  partitioning  based  sediment
quality criteria for 13 chemicals is  presented  in  Section 7.2.  The 95  percent
confidence  limits  are  computed from a method which is known  to exaggerate  the
uncertainty.   For  chemicals  where  either field data  derived lower bounds  or
sediment  toxicity experiments are available the results are  reasonable.

TOXIC METALS

    The  rationale  for  establishing  sediment quality criteria for  toxic  metals
is similar  to that  developed for non-ionic organic  chemicals.  The bioavailable
fraction  is identified and a partitioning model will be investigated  in order
to  predict  the bioavailable  fraction.   Water  column experiments point  to  the
fact  that biological effects can be  correlated to the  divalent metal  activity
[Me2+] .   The  implication to be drawn  from  these experiments   is  that  the
partitioning  model required for establishing sediment quality  criteria  should
predict  [Me2+]  in  the pore water (Section 6.1 - 6.2).

METAL SORPTION  MODELS AND EXTRACTIONS

    The  state-of-the-art  of modeling metal  sorption  in laboratory systems  is
well  developed.  Models for natural  soil and sediment particles  are less well

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                                                                         Page 9

developed.   However,  recent applications  suggest that similar  models can  be
applied  to  soil systems.  An  approach  is  presented  which  envisions  three
sorption phases in aerobic sediments (Section 6.3).

    In addition  to  the  sorption  phase  concentrations  it  is  necessary  to
quantify  the  fraction of total sediment  metal  that is chemically  interacting
with  the  pore water.   A substantial  effort is needed over  several years  to
determine the bioavailable portion of trace metals in soils and sediments  using
chemical extractions.  Initial results are reviewed  and preliminary directions
are suggested (Section 6.4).

CONCLUSION

    Methodologies are  being  developed to  establish  sediment  quality criteria
using sediment equilibrium partitioning.   The importance of bioavailability and
the role  of partitioning between sediment and  pore water  is  clarified.   The
effects concentration  for benthic  organisms  can  be estimated from the water
quality criteria.   For  non-ionic  organic chemicals  an  adequate partitioning
model exists  and  is  presented  in  this document.   As a result sediment quality
criteria  can  be  computed.   For metals, initial  studies indicate  that the same
rationale can  be  used.    The development   of  sediment  criteria  for  metal
contaminants  using  equilibrium partitioning   is  the focus  of  future sediment
criteria development activities.

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                                                                       Page  1-1
                                  SECTION 1.

                                 INTRODUCTION

    Under the Clean Water Act  (CWA)  the Environmental Protection Agency (EPA)
is responsible for protecting the chemical, physical, and biological integrity
of the nation's waters.   In  keeping with this responsibility, EPA has published
ambient  water  quality  criteria (WQC)  in 1980  for  64  of  the 65  priority
pollutants and  pollutant categories  listed as  toxic  in the CWA.   Additional
water  quality documents that update  criteria  for  selected  consent  decree
chemicals and new  criteria  have  also been published  since  1980.   These water
quality  criteria  are  numerical  concentration  limits  that are  protective  of
human health and aquatic life.   While these criteria play an important role in
assuring a healthy aquatic environment,  they alone are not sufficient to ensure
appropriate levels of environmental and  human health protection.

    Toxic contaminants in bottom sediments of  the nation's  lakes,  rivers,  wet
lands,  and coastal  waters  create the  potential for  continued  environmental
degradation even where water-column contaminant levels comply with established
water quality criteria.  In addition, contaminated sediments can  lead to water
quality degradation,  even when pollutant  sources are  stopped.  The  absence  of
defensible sediment  quality  criteria makes it difficult to accurately assess
the extent of  the  contaminated sediment problem  and  to identify  and implement
appropriate remediation activities when  needed.   As  a result of the  need for a
procedure to  assist  regulatory agencies  in making decisions  concerning
contaminated  sediment  problems, a EPA Office  of  Water Regulations and
Standards,  Criteria and  Standards  Division  (OWRS/CSD)   research  team was
established to review alternative approaches.  Each approach had both strengths
and weaknesses  and no  single  approach was found to be  most applicable  in  all
situations.   The  equilibrium partitioning  method  was selected,  because  it
appeared  to provide  the most  practical  and  effective regulatory tool  for
addressing contaminated  sediments on a  national basis.   The  three  principal

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Page 1-2

observations that underlay the  equilibrium  partitioning method of establishing
sediment quality criteria are:

    1.   for sediment  dwelling organisms,  the pore  water  concentration  of  a
         chemical correlates  to observed biological effects across  a  range of
         sediments,

    2.   the range  of  sensitivities  of benthic  organisms  to  chemicals  are
         similar  to  water-column organisms_sQ .jthat. the currently  established
         water quality  criteria can be  used  to define acceptable  pore  water
         levels; and,

    3.   partitioning  models  which  relate  pore water  concentrations  to  bulk
         sediment concentrations either exist (for  non-ionic organic chemicals)
         or can be developed  (for toxic  metals and, perhaps, for ionic organic
         chemicals).

    The  data  that support these  observations will be  examined  in  subsequent
sections of this report.

    Sediment  quality  criteria generated using the  equilibrium partitioning
method  are suitable for  use  in providing  guidance  to  regulatory  agencies
because they are:

         1.  numerical values,
         2.  chemical specific,
         3.  applicable across sediments.
         4.  predictive of biological effects, and
         5.  protective of the presence and uses of benthic  organisms.

    As  is  the  case  with water quality criteria, the  sediment  quality  criteria
reflect  the use of available  scientific  data  to:   (1) assess the likelihood of
significant environmental  effects  from  contaminants  in sediments,  and to  (2)
derive regulatory requirements which will protect against these effects.

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                                                                      Page 1-3

    Over  the past  several  years research  activities  have focused on  the
evaluation  and  development  of the  equilibrium partitioning methodology  for
generating  sediment quality criteria for  use  in providing  guidance  to
regulatory agencies.   It  is the purpose of this report to describe results  that
support the  equilibrium  partitioning method for  establishing  sediment quality
criteria.   This  report is structured in the following way:

    The historical  framework and  statutory basis  for  developing  sediment
quality criteria are discussed in Section 2.  Toxicity  and  bioavailability  of
chemicals  in sediments are discussed  in  Section  3 where  the  importance of  pore
water concentration  is established.  This leads to a discussion of partitioning
behavior of  chemicals  and their division into  two  major classes:  non-ionic
organic chemicals  and metals,  for which partitioning models have  been proposed.

    Non-ionic organic chemicals  are discussed  in  Section  4.   Sections 4.1
through  4.5  concentrate on  partitioning and  the  role of  particulate and
dissolved organic  carbon. The models available to evaluate the partitioning  of
chemicals  in sediments are presented  in Section 4.1 for  particle  suspensions
and Sections 4.2 through 4.4  for in-place sediments,  including a discussion  of
the  effect  of  DOC  complexing.   Field data,  related  to  partitioning  in
sediments,   are  analyzed  in Section  4.5.    The results of organic carbon
normalization  of toxicity and bioaccumulation  experiments  are presented  in
Section 4.6.  The issue of pore water versus  sediment as  the route  of  exposure
is addressed in Section 4.7.  This  section concludes with  a review of the field
validation  of  sediment  criteria  in Section  4.8,   where a  screening level
methodology is presented.

    The  applicability  of  using  water, quality criteria   for the  effects
concentration in  sediments  is examined  'in  Section  5.   A  discussion of the
overall similarity of the sensitivities  of benthic and water column species  is
included in this section.

    Section 6  reviews  the  current status  of sediment  quality  criteria
development  efforts  related to toxic  metals.   The  difficulties  in using pore

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Page 1-4

water metal concentration directly are discussed in Section 6.1.   This  leads  to
a discussion of the data demonstrating the correlation of  toxicity  to  divalent
metal  activity  which is  presented in Section 6.2.   The  state-of-the-art  of
metal  sorption  models  is  discussed in Section  6.3.    The  suitability  of
extraction methodologies to  quantify  the bioavailable fraction is  examined  in
Section 6.4.  The remainder  of Section 6  describes  the initial  approaches  that
are being pursued in order to establish sediment metal criteria.

    Finally, Section  7 describes - -the generation .of  interim sediment quality
criteria for non-ionic organic chemicals.  The uncertainty associated  with the
criteria  is discussed (Section  7.1) and  preliminary  values are presented
(Section 7.2).

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                                                                       Page 2-1
                                  •SECTION 2.

                          SELECTION OF A METHODOLOGY

    This section presents an  overview of the statutory basis for  establishing
sediment  quality criteria  and  the historical  evolution  of the  equilibrium
partitioning  method.   The relationship of this  approach  to  methodologies
adopted for generating national  water quality criteria is discussed and  areas
of application  described.   The rationale for  selecting  this approach and  the
procedure for utilizing it are summarized.

2.1  STATUTORY BASIS - CLEAN WATER ACT

    The statutory basis for the development of sediment quality criteria is  the
Clean  Water Act.    Section 104  of the  Act authorizes  the Administrator to
conduct  and promote research into  the causes,  effects,  extent,   prevention,
reduction and  elimination of pollution, and to  publish relevant  information.
Section 104(n)(l) in particular provides for  study of  the  effects of pollution,
including sedimentation,  on aquatic life in estuaries.

    Pursuant to  the Act  the Administrator is  required to develop  and publish
"criteria for water  quality" reflecting the  latest scientific knowledge on  the
kind and extent of  effects  on plankton, fish, shellfish and  wildlife which  may
be expected from the presence of pollutants in any  body of water, including
ground water,  and  on the effects  of  pollutants  on  biological community
diversity, productivity and stability (Section 304(a)(l)>.

    The  Administrator is also  directed by  the Act  to develop  and publish
information on the  factors necessary  for the protection  and  propagation of
shellfish,  fish and wildlife for  different classes and categories  of receiving
waters  (Section  304(a)(2)).   Additionally, the  Administrator  is authorized

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Page 2-2

under  Section  303 to  provide for  states  to adopt  state sediment  standards.
These requirements of  the  Act provide for the development of a  scientifically
defensible methodology or setting sediment quality  criteria.

2.2  AVAILABLE APPROACHES FOR DEVELOPING SEDIMENT QUALITY  CRITERIA

    The sediment criteria development effort was initiated in November 1984 as
a result  of concerns expressed by  EPA  regions  and program offices,  state and
local government  agencies,  environmental  organizations. and others with regard
to  contaminated  sediments  in the  nation's water bodies.   Concerns  about
contaminated sediments  also focused on the  fact  that  no  effective  regulatory
tool was available that would address the  wide variety of  contaminated areas.

    The concern  over  these  and  related problems  were  the subject  of  a 1984
conference  entitled,  "Fate  and Effects  of Sediment-Bound  Chemicals in Aquatic
Systems."   The  conference proceedings  (Dickson  et  al. ,  1987)  record  the
alternative approaches  to  establishing  sediment quality criteria as  they were
perceived  at the   time  (Pavlou  and  Ueston,  1983)   and their  merits  and
deficiencies  (Chapman,  1987).   Following  this  conference an  EPA  sponsored
workshop  was convened  that focused  on developing a means  by which  EPA  and
others could address this problem.   This workshop was supported by reports that
identified  the  scope  of  national sediment  contamination  (SCD  3)1   and that
reviewed  approaches  investigated  by other efforts  addressing  contaminated
sediments  (SCD  0; SCD  1) .   The workshop  was  attended by  personnel from  EPA
regional  offices, headquarters and laboratories,  state  and local governments,
the  environmental  community,   industry,  universities,  laboratories  and
contractors.  A consensus was  reached by the participants  of the workshop that
the  equilibrium partitioning  approach was  most  likely  to  provide the EPA with
an  effective  regulatory tool that was  technically  sound  and  could be readily
incorporated into a variety of agency regulatory activities  (SCD 2).
 IThe citation SCD refers to the sediment criteria  development reports listed in
  Section 9.

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                                                                       Page 2-3

2.3  RATIONALE FOR SELECTING THE EQUILIBRIUM PARTITIONING METHOD

    The equilibrium partitioning method was  selected as  the most likely method
to provide  the EPA with an  effective  regulatory tool because  it  reflects the
needs  of regulators  and  because  it  incorporates  the  most useful  technical
aspects of a variety of approaches.  The principal reasons for the selection of
the equilibrium partitioning approach were as follows:

    1.   It  was  likely that  the equilibrium-partitioning method would yield
         sediment  criteria that were predictive  of biological effects  in the
         field.  They address the issue of bioavailability and are based on the
         extensive biological  effects data base  used  to establish  national
         water quality criteria.

    2.   The  developed criteria could  be readily  incorporated into  existing
         regulatory operations  since  a  unique  numerical  sediment  specific
         criteria  can  be   established for any chemical  and compared  to field
         measurements to assess the likelihood of significant adverse effects.

    3.   The developed criteria could provide a simple and cost effective means
         of  screening  sediment measurements to  identify areas of concern and
         could provide regulators with information in a short period of time.

    4.   The method took  advantage of the large  amount  of data and  expertise
         that went  into the development of the National Water Quality Criteria.

2.4  RELATIONSHIP TO WATER QUALITY CRITERIA METHODOLOGY

    Perhaps  the first  question to be  answered  is:  why not  use  the  already
existing procedure for the  development  of water quality criteria to  develop
sediment  quality  criteria?   A  detailed  methodology has  been developed  that
presents the supporting logic, establishes the required  minimum  toxicological
data  set,  and specifies the numerical procedures to be  used to calculate the

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Page 2-4

criteria values  (Scephan  et al.,  1985).   Furthermore,  water quality criteria
developed  using this  methodology,  have found  utility in  the  regulation of
effluent  discharges.    A natural • extension would be  to  apply  these  methods
directly to sediments.

    The water quality criteria are based upon total chemical concentration and
the transition  to  using dissolved chemical concentration for  those chemicals
that partition to a significant extent would not be difficult.   The experience
with site  specific modifications  .of  the  national. water quality  criteria has
demonstrated that the  water  effect ratio -  the ratio of chemical concentrations
in  site water  versus  laboratory  water that  produces  the  same  effect  -  has
averaged 3.5 (Spehar and Carlson,  1984;  Carlson et al.,  1986).  The implication
is that differences of this magnitude due  to variations in site specific water
chemistry are not an overwhelming  impediment to nationally applicable numerical
water  quality  criteria.    In  addition,  application of  site  specific  water
quality  criteria  guidelines  suggest site  specific differences  in
bioavailability of  substances  associated  with  water can be  measured and site
specific water quality criteria can  be developed.

    In  contrast to the use of total water  column concentration,  the use  of
total  sediment  chemical concentration as  a measure of bioavailable -  or even
potentially bioavailable - concentration is not supported by the available data
(see,  for  example,  the  review  by  Luoma,  [1983]).   A  summary of  recent
experiments is presented in  Sections 3 and  4.  The results  of these experiments
indicate  that  different  sediments can differ  in toxicity  by factors of  10  to
100  for  the  same  total  chemical  concentration of a toxicant.   This  is  a
significant  obstacle  since  without  some  quantitative  estimate  of  the
bioavailable chemical concentration  in a sediment it is impossible to predict a
sediment's toxicity based on chemical measurements.  This is true regardless of
the methodology used  to assess biological impact - be  it  laboratory  toxicity
experiments  or  field  data  sets  comprising benthic biological and  chemical
sampling  (Chapman  and  Long,  1983;  Long  and Chapman,   1985;  Barrick et  al. ,
1985).

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                                                                       Page  2-5

    Without a  unique relationship between  the chemical  measurements  and  the
biological end  points which -applies  across the range  of sediment properties
that affect bioavailability, the  cause  and  effect  linkage is not supportable.
If the same total chemical concentration is  10  times more  toxic in one  sediment
than  another,  how  does  one  set a  universal  sediment quality  criteria that
depends only on  the total sediment chemical concentration?   Thus,  it appears
that  bioavailability must  be explicitly considered  in  the  establishment  of
sediment quality criteria.  Further,  any sediment quality criteria methodology
that depends on chemical measurements  in the sediment must address this issue.

2.5  APPLICATIONS OF SEDIMENT CRITERIA

    Any method capable  of generating  sediment  criteria that are  reasonably
accurate in their ability to  predict  the potential  for biological  impacts are
likely to  be  useful in many of  the  activities  currently  being pursued within
EPA.   Table  2-1  (SCD  10)  identifies a  variety  of likely  statutes and
applications under  which sediment criteria could be  used.    Sediment  quality
criteria  are  likely  to play a  significant  role in the  identification,
monitoring and clean up of contaminated sediment sites  on a national basis and
in ensuring that those  sites that are uncontaminated will remain so.   In some
cases sediment criteria alone would be sufficient to identify and to establish
clean  up  levels  for contaminated sediments.   In other cases  the  sediment
criteria should be supplemented with biological sampling and testing,  or other
types of analyses, before decisions are made.   Sediment criteria  can provide a
basis for determining whether contaminants are accumulating in sediments to the
extent that an unacceptable  contaminant  level  is being  approached or has been
exceeded.    By monitoring contaminants in  the vicinity  of  a -discharge,
contaminant levels can  be compared  to  sediment  criteria  to assess the
likelihood of impact.  Sediment criteria will  be particularly valuable  in site
monitoring applications  where sediment contaminant concentrations  are gradually
approaching  the criteria over  time.    Comparison  of  field measurements  to
sediment criteria will  be a reliable method  for providing early warning  of

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      TABLE 2-1.  SUMMARY OF POTENTIAL APPLICATIONS OF SEDIMENT CRITERIA IN IMPLEMENTING KEY SECTIONS OF  SOME  MAJOR ENVIRONMENTAL LAWS


                                                                                                 Clean-up Clean-up                                 
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                                                                       Page 2-7

potential problems.  Such an early warning would provide an opportunity to take
corrective action before adverse impacts occur.

    Evaluation of  in-place  pollutants in aquatic  sediment will be  one  of the
most appropriate  and  immediate  applications of  sediment  criteria.   Sediment
criteria will  be  useful  in evaluating the  potential  risks posed  by in-place
pollutants.  For example, under  Section 303  of the CWA sediment criteria could
be  used  to help  determine whether an  area  might  benefit  from clean  up
activities.  Sediment criteria will be useful in:

    1.    assessing the need for clean up,

    2.    setting numerical goals for clean up, thereby helping to establish the
         size of the area to be remediated and the cost of the clean up effort,
         and

    3.    assessing the degree of benefit to  be  realized by cleaning up an area
         to meet the criteria.

    In many ways sediment criteria developed using the equilibrium partitioning
methodology are similar  to  existing water quality  criteria.   However,  in their
application  it is likely that  they may vary significantly.    Contaminants  at
levels of  concern  (exceeding a water quality criteria) in  the  water column  in
most cases need only  be controlled  at the  source to eliminate  unacceptable
adverse  impacts.   Contaminated  sediments  often have been in place  for  quite
some time  and controlling  the  source of that  pollution  (if the source  still
exists)  will  not  be  sufficient  to  alleviate  the problem.    The  problem  is
compounded due  to  the  fact  that the safe removal  and  treatment or  disposal  of
contaminated sediments can  be difficult and expensive.  For this reason  it  is
not  anticipated  that  sediment  criteria  will  be  used as  mandatory clean  up
levels,  but as a  means  for predicting or  identifying the degree  and  spatial
extent of  contaminated areas such that regulatory decisions can be made.

-------
Page 2-8

    Regulatory frameworks  for  the application of these criteria  are currently
being  considered by the  policy oriented  EPA  Contaminated Sediment  Steering
Committee.   Public  input  is  expected prior  to  the adoption  of  any  formal
regulatory framework for deriving and implementing sediment criteria.
             \
2.6  COMPUTING SEDIMENT QUALITY CRITERIA

    The  sediment  quality criteria  for  a specific chemical  is defined as  the
solid phase concentration that will result in an uncomplexed.interstitial  water
concentration  equal  to the water quality  criteria  for that  chemical.    The
justification  for   the use  of  the  water quality  criteria as  the effect
concentration for benthic  organisms is  that the species sensitivity range  for
this subclass appears to be similar to  the  water column organisms  (Section  5).
With remarkable foresight this approach was suggested for  establishing  sediment
quality  criteria by  Pavlou and  Ueston (1983)   before  the  evidence discussed
herein was available.

    The  calculation procedure  is as follows.   If  cyqc  (pg/L)  is the  water
quality  criteria for  the  chemical  of interest,  then the sediment quality
criteria, rgqc (/*g/kg sediment) is computed using the partition coefficient, Kp
(L/kg sediment) between sediment and water:

          rsqc ' VWQC                                                   (2'1)

Hence,  the  development of sediment quality criteria is directly dependent on
the availability of a methodology that relates the  partition coefficient of  the
chemical  or class of  chemicals  to measurable properties  of the sediments in
question.

    The  three principal observations  that underlay this method of  establishing
sediment  quality criteria are:

-------
                                                                       Page 2-9

    1.    For sediment  dwelling organisms, the  pore water  concentration of  a
         chemical correlates to  observed biological effects,  and the  effects
         concentration is the same' as that observed in  a water-only exposure.

    2.    Partitioning models either exist (for non-ionic organic  chemicals) or
         can be  developed (for toxic  metals  and,  perhaps,  for ionic  organic
         chemicals).

    3.    The range  of  sensitivities  of benthic  organisms to chemicals  are
         similar co  water column organisms.

    The data  supporting each  of these  observations will  be  examined in  the
following sections of this report.

-------
                                                                      Page 3-1
                                  SECTION  3.

            TOXICITY AND BIOAVAILABILITY OF CHEMICALS IN SEDIMENTS

    The  observation that  provided  the key insight into  the  problem  of
quantifying the  bioavailability of  chemicals  in  sediments  was that  the
concentration-response  curve for  the  biological effect  of concern could  be
correlated not to the total sediment chemical concentration (jig chemical/g dry
sediment) but to  the interstitial water  (i.e., pore  water)  concentration (/ig
chemical/liter  pore water).   In  retrospect  it has  become clear  that  these
results  do not  necessarily  imply that  pore  water is  the primary route  of
exposure.  This  is because all exposure  pathways are at equal chemical activity
in an equilibrium experiment.  Hence the route of exposure cannot be determined
(Section 4.7).   The difficulty  of establishing the primary route  of exposure
does not diminish the importance of the empirical fact that the concentration-
response  curve  is  correlated to pore water concentration.   Further,  this
observation  is  a  critical part of  the development  of the  equilibrium
partitioning approach to formulating sediment quality criteria.

3.1  TOXICITY EXPERIMENTS

    A  substantial  amount  of data  has  been assembled that  addresses  the
relationship between toxicity and pore  water concentration.  Table  3-1  lists
the sources and characteristics of these  experiments.  The  data are presented
in a uniform fashion on Figures 3-1 to 3-4.  The biological response - survival
rate or growth rate - is plotted versus  the total sediment concentration on the
top  panel, and  versus  the  measured  pore water  concentration  on  the  bottom
panel.   Table  3-2  summarizes  the LC50  and EC50  estimates and  95  percent
confidence limits for these data on a total sediment and pore water basis.

    The results from kepone experiments  (Figure 3-1) are  particularly dramatic
(Adams et al., 1985; Ziegenfuss et al.,  1986). For the low organic carbon sedi-

-------
Page  3-2
                                      TABLE 3-1.  SEDIMENT TOXICITY DATA
Chemical Organism
Kepone
Keponc
Cadmium
Chironomus
Chlronomus
tentans
tentans
Rhepoxvnius abronius
Flouranthene Rhepoxvnius abronius
DDT
Endrin
Cadmium
Cadmium
Hvalella azteca
Hyallella azteca
Rhepoxynius abronius
Amoelisca abdita
Cypermethrin Chironomus
Permethrin Chironomus
Kepone
Chironomus
tentans
tentans
tentans
Sediment
Source
Soil
Soil
Yaquina Bay, OR
Yaquina Bay, OR
Soap Creek,
Mercer Lake
Soap Creek
Mercer Lake
Yaquina Bay, OR
Long Island
Sound
River and Pond
River and Pond
Soil
Exposure
Duration
(days)
14
14
4
10
10
10
4
10
1
1
14






















Biological
Endooint
Mortality
Growth
Mortality
Mortality
Mortality
Mortality
Mortality
Mortality
Body Burden
Body Burden
Body Burden
Reference
Adams et al., 1985
Adams et al.. 1985
Kemp and Suartz, 1986
Suartz et al., 1987
Nebeker and Schuytema,
1988
Nebeker and Schuytema ,
1988
Suartz et al., 1985
Di Tore et al.. 1989
Muir et al., 1985
Muir et al., 1985
Adams et al.. 1983
and 1985
Figure
3-1
3-1
3-2
3-2
3-3
3-3
3-4
3-4
3-5
3-5
3-6
TABLE 3-2. DOSE-RESPONSE PARAMETERS*





Chemical
(End Point)
Kepone
1985
(Mortality)
Kepone
1985
(Growth)
Fluoranthene
1987
(Mortality)
DDT
(Mortality)
Endrin
(Mortality)
JSL
0.09
1.50
12.0
0.09
1.50
12.0
0.2
0.3
0.5
3.0
7.2
10.5
3.0
6.1
11.2

LC50 and
EC50
Total Sediment
(Jjq/q)
0.97
7.89
42.0
0.40
9.87
48.9
3.3 ( 3.0 -
6.2 ( 5.4 -
10.5 ( 8.3 -
11.0 (10.1 -
19.6 (15.6 -
49.7 (44.2 -
4.4 ( 3.9 -
4.8 ( 3.7 -
6.0 ( 4.7 -


3.7)
7.1)
13.4)
12.7)
24.3}
56.3)
5.2)
6.3)
7.4)
32
35
18
15
48
21
22
31
23
0
1
0
2
1
1
.0
.4
.7
.0
.8
.9
.0
.1
.6
.9
.5
.8
.1
.9
.8
Pore Water
(ua/L)


(19.8 -
(27.3 -
(18.5 -
( 0.8 -
( 1.3 -
( 0.7 -
( 1.8 -
( 1.6 -
< 1.4 •
Reference
Adams et a I.,
Adams et a I.,
24.5) Suartz et al.,
35.4)
30.2)
1.0) Nebeker and
1.8) Schuytema, 1988
0.9)
2.5) Nebeker and
2.4) Schuytema, 1988
2.2)





         •95X confidence  limits shown in parentheses

-------
cc
in
        ACUTE  TOXICITY  OF KEPONE TO
              CHIRONOMUS TENTANS
    100
CC
3
l/l
    BO
    60
40
% ORGANIC CARBON
       .09   •
       1.5   •
       12.0  *
           \
           %
            «^.
          20 O       40.0       60 0

          SEDIMENT  KEPONE  (ug/g)
                  so           100
              PORE WATER KEPONE  (ug/L)

              DATA:  AOAHS. et.al..  1983
                                           BO 0
                                            ISO
                                                          CHRONIC TOXICITY OF KEPONE  TO
                                                                CHIRONOMUS TENTANS
                                                          ISO,
                                                      o
                                                      cc
                                                 o
                                                 u
                                                      o
                                                      DC
                                                      ID
                                                     -K*
                                                                            %  ORGANIC  CARBON
                                                                                   .09   •
                                                                                   1.5   •
                                                                                   12.0  *
                                                          75
                                                          SO
                                                            !  \
                                                                 V
                                                           0 0
                                                                    20.0       40.0       60 0

                                                                    SEDIMENT KEPONE (ug/g)
                                                          ISO.
                                                      -,   I?!
                                                      o
                                                      cc
                                                      o
                                                      u
                                                      o
                                                      cc
                                                      ID
                                                                          SO         75

                                                               PORE  WATER  KEPONE  (ug/L)


                                                               DATA-   ADAMS, et.al .  1983
                                                                                             BO 0
                                                                       i o
                      FIGURE 3-1.   Comparison of percent survival  (left) and growth  rate  reduction
                      (right) of Chtronomus  tentans to kepone  concentration in bulk  sediment (top)
                      and  pore water  (bottom) for  three  sediments  with  varying organic carbon
                      concentrations.

-------
Page 3-4

raent  (0.09  percent)  the  50th  percentile total  kepone  concentration for  both
Chrironomus  tentans  mortality  (LC50)  and growth  rate  reduction  from  a  life
cycle test  (EC50)  are <1 pg/g.   -By contrast,  the 1.5  percent organic  carbon
sediment EC50 and LC50 are approximately 8 and  10  pg/g respectively.  The  high
organic carbon sediment (12 percent) exhibits still higher LC50  and EC50  values
on a  total  sediment  kepone  concentration basis  (42 and 49 Mg/g)•   However, as
shown in  the bottom panels,  essentially all the  data collapse into a  single
curve when the  pore  water  concentrations  are used  as  the  correlating
concentrations.  On a pore water basis  the biological  responses  are essentially
the same  for the  three different sediments:  the EC50 - 23  pg/L and LC50 - 28
pg/L, whereas  when they  are  evaluated on a  total sediment kepone basis  they
exhibit an almost 50-fold range in kepone toxicity.

    Laboratory experiments have  also been  performed  to characterize  the
toxicity  of  fluoranthene (Swartz  et   al.,  1987), cadmium  (Kemp  and Swartz,
1986),  and  DDT (SCD 7:   Word et  al.,  1987) to the  sediment  dwelling marine
amphipod  Rhepoxvnius abronius.   Figure 3-2 presents the Rhepoxynius mortality
data  for  the  fluoranthene  and cadmium experiments.   The  results of  the
fluoranthene experiments parallel  those  for kepone.    The  sediment  with  the
lowest  organic carbon fraction  (0.2 percent)  exhibits the lowest LC50 on a
total sediment concentration  basis  (3.1  pg/g)  and as  the   organic  carbon
concentration  increases  (0.3 and 0.5 percent)  the  LC50  increases  (6.7 and 11.
Mg/g)•  On a pore water basis the data  again  collapse  to a  single concentration
response curve.

    The cadmium experiments  (Kemp and  Swartz,  1986)  were  done  using constant
pore  water  concentrations and a sediment amended with varying quantities of
organic carbon.   The unamended and  0.25 percent additional  organic  carbon
exhibit essentially  similar responses.   However,  the  one and  two percent
amended sediments  had much  different  LC50 concentrations based on the  total
sediment concentration.  Using the pore water concentrations  as  the  correlating
variable again  collapses the data into  one dose-response curve.

-------
II
ID
in
tr
tn
       ACUTE  TOXICITY  OF  FLUORANTHENE  TO
            RHEPOXYNIUS ABRONIUS
    10Q_
                           % ORGANIC  CARBON
                                 0.2   •
                                 0.3   •
                                 0.5
                                                           100^
        ACUTE TOXICITY  OF  CADMIUM TO
              RHEPOXYNIUS ABRONIUS
    20
     0.0
tr
3
i/i
     BOL
                                                           GoL
                                                 40
                                                                        % ORGANIC CARBON
                                                                         Unamended  •
                                                                             +0.25  •
                                                                             +1.00  A
                                                                             +2.00 -«
     50        10 0       IS 0

SEDIMENT  FLUORANTHENE  (ug/g)
                                           20.0
                                                            0 _
                                                            0.0
          10 0   20.0   30.0   40.0   BO.O   60.0   70.0

             SEDIMENT CADMIUM   (ug/g)
     00       20 0       40 0       bO 0

          PORE WATER FLUORANTHENE (ug/L)



                DATA  SMARTZ.  et a)  . 19B7
DC

in
                                           BO.O
            1000     POOO     3000      4000

             PORE  WATER CADMIUM  (ug/L)

            DATA  KFMP and SWARTZ.  1986
                     FIGURE  3-2.    Comparison  of percent  survival  of Rhepoxvnlus  abronlus to
                     fluoranthene  (left) and cadmium (right)  concentration  in  bulk  sediment  (top)

                                  "             *"

-------
Page 3-6

    Figure 3-3 presents  survival  data for DDT and endrin using  the  freshwater
amphipod Hvalella (Nebeker and Schuytema, 1988).  The responses  are  similar  to
that  observed for  kepone,  cadmium,  and fluoranthene.   On  a total  sediment
concentration basis  the  organism responses differ  for  the various  sediments,
but on a pore water basis the responses are again similar.

    Cadmium  toxicity data  are   compared on  Figure 3-4  to  demonstrate one
additional  point.   The  responses  of Rhepoxvnlus  (Swartz  et al.,  1985) and
Ampelisca  (Di Toro  et  al.,  1989)  to  cadmium in  seawater  exposures without
sediment and  to  the measured pore  water concentrations in sediment  exposures
(lower  panels).    The survival   responses  are  similar with  or without the
sediment  present.   The  concentration  response curves  using  total cadmium
concentrations are also shown (top panels).   It is interesting  to note that two
organisms exhibit similar  sensitivity to cadmium in water only exposures (0.3
mg/L  for  Ampelisca  and  -  1  mg/L for Rhepoxynius - bottom panels):   yet the
total sediment cadmium LC50s  differ by almost two orders of magnitude (25 and
2,000 pg/g  respectively)  for   the  different  sediments.    These  dramatic
differences  demonstrate  the need  to explicitly consider  bioavailability  of
sediment cadmium  and,  by  implication, any toxicant  of  concern,  in  developing
sediment quality criteria.

3.2  BIOACCUMU1ATION

    A  direct measure  of chemical  bioavailability  is  the amount  of  chemical
retained  in organism  tissues.    Tissue  bioaccumulation data  are  examined  to
address the  issue of chemical bioavailability.   The results  are presented on
Figures  3-5  and  3-6  and the mean and  95  percent confidence  limits  of the
bioaccumulation  factors  associated with each set  of  data are  summarized  in
Table 3-3.

    Chironomus tentans were exposed to two synthetic pyrethroids, cypermethrin
and permethrin that were added to three  sediments, one of which was  laboratory
grade sand  (Muir  et al.,  1985).    The bioaccumulation from  the  sand was
approximately an  order  of magnitude higher than  the organic carbon-containing

-------
     ACUTE  TOXICITY  OF DDT  TO  HYALELLA

    too*.
QC

in
% ORGANIC CARBON
        3.0    •
        7.2    •
       10.5    *
     20.
cc
in
                               ACUT.E  TOXICITY  OF  ENDRIN  TO  HYALELLA

                                 100..
                                                                                     X ORGANIC CARBON
                                                                                             3.0   •
                                                                                             6. 1   •
                                                                                            11.2   *
                             cr
                             en
                         100        ISO

                SEDIMENT DDT  (ug/g)
                                             200
                                                              o.o
                                                                                  10.0
                                                                                                      20 0
                                            SEDIMENT  ENDRIN (ug/g)
                                                             100,.
                                     4 00
               PORE WATER  DDT  (ug/L)

             DATA. NEBEKER and SCHUYTEMA.  1988
                                            5.00
                                                              0.0
                                          2.0       40      6.0      BO

                                           PORE WATER ENDRIN (ug/L)

                                          DATA: NEBEKER and SCHUYTEHA.  1988
                                                                                                       0.0
                    FIGURE 3-3.   Comparison  of percent  survival  of Hvalella to  DDT  (left)  and
                    endrin (right) concentration In bulk sediment (top) and pore water (bottom) for
                    sediments with varying organic carbon concentrations.

-------
          ACUTE  TOXICITY  OF CADMIUM
                     TO AMPELISCA
                                                       ACUTE  TOXICITY  OF  CADMIUM
                                                               TO  RHEPOXYNIUS
en
M
                                                           cc
                                                           in
                                                               too
                                                               ao
                                                               60.
                                                  40 .
                                                               20.
     10"
I01      10*      101      10"
  SEDIMENT CADMIUM  (ug/g)
                                             10°
                                                                10"
                                                                   10'
10*
10'
10*
10a
                                                                         SEDIMENT  CADMIUM  (ug/g)
    100
     BO
>    60
t-i

CC
In    «
                           MATER ONLY       o
                           SEDIMENT EXPOSURE •
10"
          10'*  10**   10"'   10°   101   10*   103
             PORE  WATER CADMIUM (mg/L)

             REFERENCE:  DITORO. «t.6l..  1989
                                to*
                                                                   MATER ONLY        o
                                                                   SEDIMENT EXPOSURE  •
                                                           PORE  WATER CADMIUM  (mg/L)

                                                           REFERENCE: SMARTZ. et.al..1985
               FIGURE  3-4.     Comparison  of percent  survival  of  Ampelisca  (left)  and
               Rhepoxyntus  (right)  to concentrations of cadmium  In bulk  sediment  (top) and
               pore water (bottom).   Also  presented  is  water-only exposure data,  identified
               with open circles.

-------
                                                                       Page 3-9

sediment for both  cypermethrin and permethrin  (Figure  3-5  top panels).   On  a
pore water basis the bioaccumulation appears to be linear (the lines have slope
- 1) and independent of sediment type (bottom panels).

                         TABLE 3-3.  BIOACCUMULATION FACTORS8
Bioaccunulation Factors
Chemical
Kepone
Cypermethrin
Permethrin
B95X confidence
Jn
.09
1.50
12.
2.3
3.7
2.3
3.7
limits
Total Sediment
ug/g organism
ug/g sediment
600
20
3.3
6.21
0.50
0.60
( 308 -
( 4.8 -
( 0.3 -
(0.30 -
(0.37 -
4.04 (2.89 •
0.38 (0.17 -
0.23 (0.18 -
shown in
892}
35.2}
6.3)
8.01)
0.71)
0.83)
5.20)
0.59)
0.28)
Pore Water
ug/kg organism
UQ/L
17,600
5,180
5,790
80.1
51.3
92.9
39.7
52.5
29.7
(6,540
(1,970
(2,890
(73.5
(43.8
(87.0
(25.0
(22.6
(15.6
- 28,600)
- 8,390)
- 8,700)
- 86.7)
- 58.8)
- 98.8)
- 54.3)
- 82.4)
• 43.7)
Reference
Adams. Kimerle
and Mosher,
1983 and 1985
Muir et al.,
1985
Muir et al.,
1985
parentheses
    Bioaccumulation was  also  measured by Adams et  al.  (1983  and 1985) in  the
Chironomid - kepone experiments discussed in Section 3.1.  Figure 3-6  presents
the  organism  body  burden  (/*g chemical/g organism)  versus  total   sediment
concentration  (top  panel) and  pore  water concentration  (bottom  panel)  for a
range of sediment organic carbon levels.  The body  burdens used on  this figure
are not the actual measurements, which were  not reported,  but  are  computed from
the reported average bioaccumulation factor  for each sediment  type.  Again,  the
variation on a total sediment basis is over  two orders  of  magnitude  whereas  the
pore water bioaccumulation factor is within  a factor of three  with the  very  low
organic carbon sediment exhibiting the deviation.

3.3  CONCLUSION
    These  observations  -   that  organism  concentration  response  and
bioaccumulation from  different sediments can  be reduced  to  essentially one
curve  if  pore  water  is considered  as  the  exposure concentration  -  can be

-------
Page 3-10

interpreted in  a  number of ways.   However,  from a  purely empirical point of
view, it  suggests  that if it  were  possible  to either  measure  the pore water
concentration  of  a  chemical,  or to  predict  it  from  the  total  sediment
concentration and  the  relevant  sediment properties, then that concentration
could be used to quantify the exposure concentration for an organism.  Thus an
examination of the state-of-the-art  with  respect to predicting the partitioning
of  chemicals  between  the  solid and  the liquid phase  is  required.   This is
examined in Section 4.

-------
  BIOACCUMULATION OF  PERMETHRIN  IN

           CHIRONOMUS  TENTANS
   1000
a>
at
c
a
DC

m
a
o
m
    too
     10
    O.I
             i inn	1—i  i i inn	1—i i i inn	1—i i mil
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                    i  i i inn
% ORGANIC C:
 < 0.1   •
   2.3   •
   3.7   *
                                i i nil  i  i i i i in
               10         100       1000


              SEDIMENT PERMETHRIN (ng/g)
                                            10000
                            BIOACCULUMATION OF CYPERMETHRIN  IN

                                     CHIRONOMUS  TENTANS
                                                           10000
                          en
                          ^
                          CD
                                                            1000
                          £   100

                          cr

                          m
a
o
CD
                                                             10
% ORGANIC C:
 < 0.1   •
   2.3   •
   3.7   *
                                                                               i i mi   i  i i i i mi
                                I         10        100        1000

                                     SEDIMENT CYPERMETHRIN  (ng/g)
                                                                                                     10000
   1000
en
at
c
a
cr

m
0
O
m
    too
     10
    o il—
    o 01
                                                           10000
               01        I         10


           PORE  WATER PERMETHRIN (ug/L)



             DATA MUIR. et a) .  1985
                                             100
                                                         en
                          en
                          c
                          UJ
                          0
                          cr

                          m
                          0
                          o
                          m '
                                                            1000
                                                            100
                                                             to
                               i
                              o 01
                                         o.i         i         10

                                    PORE  WATER CYPERMETHRIN  (ug/L)


                                       DATA: MUIR. et al .  1985
                                              100
                    FIGURE 3-S.  Comparison  of Chlronomus tentans body burden of permethrin (left)

                    and  cyperraethrin (right)  versus concentration  in bulk sediment  (top)  and  pore

                    water (bottom)  for sediments  with varying organic carbon concentrations.

-------
       BIOACCULUMATION  OF  KEPONE .IN
               CHIRONOMUS  TENTANS
   10000
Ol
\
01
LU
Q
DC
Z)
CD
O
o
CD
1000
 100
      10
           I  I I I I I III   I  ! I I I I III   I  I I I I I III  I  I  I I I I III   I I  I I I ll±
NOTE:

  BODY BURDEN ESTIMATED
  FROM REPORTED AVERAGE
  BAF FOR EACH SEDIMENT TYPE. _
                                   % ORGANIC  C:
                                     < 0.09   •
                                       1.50   •
                                      12.00   A
       1J   I  I I I I I III   I  I I I I I III   I  I I I I I III   I  I I I I Illl   I I  I I I III
       0.1
              1         10        100        1000

               SEDIMENT  KEPONE  (ug/g)
                         10000
    10000
 Q>
    1000
LU
D
OC
Z3
CD
O
O
CD
 100
      10
            \  \  i i M 111   I   i i i i 11 n    I  I  i i i 11 ii    I  I  i i i i
                           NOTE:

                             BODY BURDEN ESTIMATED
                             FROM REPORTED AVERAGE
                             BAF FOR EACH SEDIMENT TYPE.
       1!    i  i  i i i 1111    i  i i  i i 11 n   i  i  i i i 11 n    i  i  i i ii 11
        1            10          100          1000         10000

                  PORE  WATER KEPONE  (ug/L)
  FIGURE 3-6.  Comparison of Chironomus tentans body burden of kepone  versus
  concentration in bulk sediment (top) and pore water (bottom) for sediments with
  varying organic carbon  concentrations.  (Body Burdens calculated from average
  bioaccumulation factors. Data:  Adams et al., 1983.)

-------
                                                                      Page 4-1
                                  SECTION 4.

                         NON-IONIC ORGANIC CHEMICALS

    A discussion of the  state-of-the-art of modeling  sorption  to particles is
best  organized by  classes of  chemicals.   Non-ionic  organic  chemicals  are
discussed in  this section and metals  and  charged organic  chemicals  are
discussed in Section 6.

4.1  PARTITIONING IN PARTICLE SUSPENSIONS

    For non-ionic hydrophobic organic  chemicals  sorbing to natural  soils  and
sediment  particles, a  number  of empirical models have  been suggested  (see
Karickhoff, 1984 for an excellent review).  The characteristic that indexes  the
hydrophobicity of the  chemical is the octanol-water partition coefficient, Kow.
The important  particle  property is  the mass fraction of organic carbon, foc.
For particles  with foc  > 0.5  percent  the organic carbon  appears  to be  the
predominant sorption phase  (Karickhoff,  1984).  The  only  other  important
environmental  variable  appears to  be the  particle  concentration itself
(O'Connor and Connolly,  1980).

    The  particle  concentration effect  is an  observable fact.    In many
experiments using  particle suspensions the  partition coefficients have been
observed  to decrease  as the particle concentration used in the  experiment  is
increased.   Unfortunately very  few experiments  have been  done  using bedded
sediments.   Therefore  the correct interpretation  of particle• suspension
experiments is  of  critical importance.   It is  not uncommon for  the  partition
coefficient to  decrease  by two  to three orders of magnitude at  high  particle
concentrations.   If  this partitioning behavior  is  characteristic of bedded
sediments  then quite  low  partition coefficients would  be  appropriate.   This

-------
Page 4-2

would result  In lower  sediment concentrations for  sediment quality criteria.
However, if this phenomena is an artifact or it is due to a new phenomenon that
does not apply to bedded sediments, then a quite different partition coefficient
would be  used.   The practical importance of  this  issue requires  a detailed
discussion of the particle concentration effect.

4.1.1    Particle Concentration Effect

    For  the  reversible  (or  labile)  component  of sorption,  a model  has been
proposed which accounts  for  the particle concentration effect and predicts the
partition coefficient of non-ionic hydrophobic chemicals over a range of nearly
seven orders  of magnitude with a  logio prediction standard error  of 0.38 (Di
Toro, 1985).   The partition coefficient,  Kp,  which is the  ratio of particle-
bound chemical concentration, r, and dissolved chemical concentration, c
-------
                                                                      Page 4-3

The regression of Koc to Kow yields:

          lo*10Koc ' °-°°28  +  °'983  lo*10Kow                              <4'3>

For the equations  that  follow this  relationship is approximated by Koc  - Kow.
However Equation  (4-3)  is used  for numerical  computations  of r§qc  presented
subsequently.    Figure 4-1  presents  the  predicted versus observed  reversible
component partition coefficients  using  this model  (Di  Toro,  1985).   A
substantial  fraction of  the data in  the  regression  is  at  high particle
concentrations (m  foc Kow > 10)  where the partitioning is determined only by
the solids concentration and  i/x.   The low particle concentration data  (m  foc
KQW <  1)  is  presented  on  Figure 4-2 for both the  reversible component  and
conventional  adsorption partition  coefficients normalized by  f0c-   The
relationship:  Koc = KOW is demonstrated from  the agreement between the line of
perfect equality and the data.

    A  number of explanations  have  been offered regarding the  mechanism
responsible for  the particle concentration  effect.   The most  popular  is to
posit  the existence of an  additional  third sorbing phase  or  complexing
component which  is associated with  the adsorbent, but which  is  inadvertently
measured  as part of the dissolved  chemical  concentration due to experimental
limitations.   Colloidal  particles which  remain  in  solution after particle
separation  (Benes  and  Majer, 1980;  Gschwend and Uu; 1985),  and  dissolved
ligands  or macromolecules  which  desorb  from the particles and  remain in
solution  (Carter and Suffet, 1982; Voice et al., 1983;  Curl and Keolelan,  1984;
Nelson et al.,   1985) have  been suggested as  the cause of  the  influence of
particle  concentration on the partition  coefficient.    It has  also been
suggested that  increasing  particle  concentration increases the  degree of
particle  aggregation,  decreasing the surface  area,  and hence  the  partition
coefficient (Karickhoff  and  Morris,  1985).  The effect  has also been attributed
to kinetic effects (Karickhoff, 1984).

-------
         REVERSIBLE COMPONENT PARTITION COEFFICIENTS
         COMPARISON TO PARTICLE INTERACTION MODEL
                 NEUTRAL ORGANIC CHEMICALS
             1.40    loO|0Koc' 0-00028 +0.983 .
 O.
 o
O
u
CO
CD
O
 6

 5

 4

 3

 2

 I

 0

-I

-2
         -2-101     2345
                  CALCULATED loglo Kp  (L/kg)
FIGURE 4-1.  Comparison of  observed partition coefficient to calculated
partition coefficient using Equation (4-2) (Di Tore, 1985).

-------
                 RELATIONSHIP  OF Koc  TO  Kow
                          m  focKow<1
                          ADSORPTION
                  •

                  7

                  e

                  s

                  4

                S 3

                          294
                            109.  K«w
                     REVERSIBLE COMPONENT
                       12948478
                            •ofl»Kow
FIGURE  6-2.   Comparison  of  the adsorption  (top)  and  reversible  component
(bottom) organic carbon normalized partition coefficient, Koc,  to the oc tonal -
water partition coefficient, Kow,  for  experiments  with low  solids
concentrations:  m f
                 oc
                       < 1.  The line represents equality (Di Tore,  1985).

-------
Page 4-6

    Sorption  by non-separated  particles  or  complexing by  dissolved organic
carbon  can  produce  an  apparent  decrease  in partition  coefficient  with
increasing particle  concentration  if the  operational method of  measuring
dissolved chemical concentration does not properly discriminate the dissolved,
free chemical concentration from  the  complexed or  colloidally sorbed portion.
However,  the  question  is  not whether  improperly measured  dissolved
concentrations can lead  to an apparent decrease in partition coefficient with
increasing particle concentrations.   The question is whether these third phase
models explain all (or most) of the observed partition coefficient  - particle
concentration relationships.

    An  alternate  possibility  is  that  the  particle concentration effect  is  a
distinct phenomena which is  a ubiquitous feature of aqueous  phase  - particle
sorption.   A number of  experiments  have been  designed  to  explicitly exclude
possible third phase interferences.   The  resuspension  experiment  for PCBs (Di
Toro  and Horzempa,  1983) and metals  (Di Toro  et  al., 1986; Mcllroy  et  al.,
1986) in which particles are resuspended into a reduced volume of supernatant,
and the dilution experiment (Di Toro and Horzempa,  1983) in which the particle
suspension  is diluted  with supernatant  from  a parallel vessel, both display
particle concentration effects.   It is difficult to see how third phase models
can  account  for  these results  since  the  concentration  of  the  colloidal
particles  is  constant  while  the  concentration  of  the  sediment  particles  vary
substantially.

    The  model  (Equation  4-2)  is  based on  the  hypothesis  that  particle
concentration effects are due to  an additional desorption  reaction  induced by
particle-particle  interactions  (Di  Toro,  1985).   It  has been  suggested  that
actual  particle  collisions  are responsible  (HacKay and Powers, 1986).   This
interpretation relates  i/x to  the  collision  efficiency for  desorption  and
demonstrates  that  it is  independent of the chemical and particle properties,  a
fact  that has been  experimentally  observed (Di Toro,  1985;  Di Toro  et  al.,
1986)

-------
                                                                       Page 4-7

    It is not necessary to decide which of these mechanisms are responsible for
the effect  if  all the interpretations yield the same  result  for sediment-pore
water partitioning.   Particle  interaction models would predict  that  KQC  - KQW
since the particles are stationary in sediments.  Third phase  models would also
relate free  (i.e.  uncomplexed) dissolved  chemical  concentration  to particulate
concentration via  the  same  equation.   As for kinetic  effects, the equilibrium
concentration  is  again given  by the relationship  KQC - KQW.   Thus there  is
unanimity on the proper partition coefficient to be used in order to relate the
free dissolved  chemical  concentration to the sediment concentration, that is,
    As  discussed  previously,  the  unifying  feature  that  allows  for  the
development of  sediment  quality criteria that are applicable to a broad  range
of  sediment  types  is  the  organic  carbon content  of  the  sediments .    The
equations  that  apply are developed below.   The sediment-pore water  partition
coefficient, K« is given by:

          K  - f  K   - f  K                                              (4-4)
           p    oc oc    oc ow

and the solid phase concentration is given by:

          r - f   K  c.                                                   (4-5)
               oc  ow d

An important observation can be made  which  leads to the  idea  of  organic carbon
normalization.   Equation  (4-5)  indicates that the  partition coefficient  for
non- ionic organic chemicals is  linear in  the organic carbon fraction,  fOc-  As
a  consequence,  the relationship  between  solid  phase  concentration,  r,  and
uncomplexed or free dissolved concentration, c^, can be expressed as:
           r
          T~ ~  K   c .                                                   (4-6)
          f       ow  d
           oc

-------
Page 4-8

If we define:
          V ' £-                                                      <4'7)
                 oc
as the organic carbon normalized sediment concentration (/ig chemical/g organic
carbon) then from Equation (4-6):

          r   - K  c.                                                    (4-8)
           oc    ow d                                                    v   '

Therefore,  for a  specific chemical  with  a  specific  KQW the  organic  carbon
normalized total sediment concentration,  roc, is proportional to the dissolved
free concentration, cj, for any sediment with foc  > 0.5  percent.   This  latter
qualification  is  judged  to  be necessary because  at  foc  <  0.5  percent,  the
factors controlling second order effects on partitioning  (e.g.,  particle size
and  sorption to  non-organic mineral  fractions) become  relatively  more
important.   Using  the proportional relationship given by  Equation  (4-8),  the
concentration of free dissolved chemical can be  predicted  from the  normalized
sediment concentration and KOW.  This  concentration  is of  concern since  it is
in this form that contaminants are  bioavailable.  It  is also this concentration
which can be used to quantify sediment quality.

4.2  DISSOLVED ORGANIC CARBON (DOC) COMPLETING

    In addition to partitioning to particulate organic  carbon (POC)  associated
with suspended and sediment particles,  hydrophobia chemicals can also partition
to  the organic carbon  in colloidal sized  particles as  well.   Because  these
particles  are too  small to  be  removed by  conventional  filtration  or
centrifugation they  are  operationally  defined as  dissolved organic  carbon
(DOC).   Since  sediment  interstitial waters frequently  contain significant
levels of DOC, it oust be considered in evaluating the  phase  distribution of a
chemical.    A  distinction must be made between the free dissolved  chemical
concentration, cj,   and  the  DOC-complexed  chemical,  CQQC-   The partition

-------
                                                                       Page 4-9

coefficient for DOC, KDOC« i-s analogous to KOC since it quantifies the ratio of
DOC-bound chemical, cnoc> to c^e frjee dissolved concentration, c AHA >  natural  DOC.  The  upper  bound on Knoc  would
appear to be KQC - KOW, the POC partition coefficient.

4.3  PHASE DISTRIBUTION IN SEDIMENTS

    Chemicals in  sediments  are  partitioned into  three phases:   free  chemical,
chemical sorbed to POC,  and chemical  sorbed  to  DOC.    To  evaluate  the
partitioning among these three phases consider the total concentration cj.   The
mass balance equation for CT is:

          c_ • ^c. •+• mf  K  c. + ^m_r._K_.__c.                           (4-10)
           T     O     OC OC d     DOC ^}OC Q

where 4>  is  the  sediment  porosity  (volume  of water/volume of water plus solids)
and m is the sediment solids concentration (mass  of solids/volume of water  plus
solids).   The  three  terms  on the right  side  of the equation  are  the
concentration of  free  chemical in the  interstitial  water,  and that sorbed to
the POC  and DOC respectively.   Hence, from Equation (4-10) the  free  dissolved
concentration can be expressed as:

-------
*£
            PARTITIONING OF POC AND DOC
        8
        6
        4  -
                BaP  HCBP  DDT  TCBP   PYR  MCBP
                             CHEMICALS
FIGURE 4-3.   ParciCion coefficients of chemicals to particulate organic carbon
(POC),  Aldrich hunic acid (AHA), and natural DOC.   Benzo(a)pyrene  (BaP);
2,2",4,4',5,5'  hexachlorobiphenyl  (HCBP);  DDT;  2,2',5,5<  tetrachlorobiphenyl
(TCBP);  pyrene (PYR);  4 monochlorobiphenyl  (MCBP).   (Data:   Eadie  et  al..
1988).

-------
                                                                       Page  4-11
                         CT
                   mfocKoc
As discussed  previously the concentration associated  with the particle carbon
and DOC are:
               Kowcd
          CDOC
The  total  pore water  concentration  is the sum  of the free  and DOC complexed
chemical so that:

          Cpore " Cd   CDOC
    Figure  4-4  illustrates the phase  partitioning  behavior of a  system for a
unit concentration  of a chemical with the following properties:   Koc -
KOW  - 106  LAg.  foe  ~ 2.0  percent,  m -  0.5 kg  solids/L sediment  and
varying  from 0  to  50  mg/L.   With no DOC present the  pore  water concentration
equals the  free concentration.   As DOC  increases the  pore  water concentration
increases due to  the increase in complexed chemical,  CDOC-   Accompanying this
increase in CDOC *s a  slight  - in fact insignificant - decrease in c& (Equation
4-11) and a proportional decrease in roc (Equation 4-12).

    Normally when  field measurements of bulk  sediment chemical concentration,
r, and total pore water chemical  concentrations,  Cp0re,  are made,  the value of
the  "apparent"  field  partition  coefficient  is  calculated directly  from  the
ratio of these  quantities.   As  a  consequence  of DOC complexaclon,  the apparent
partition coefficient,  Kp, defined as:

-------
                      PHASE DISTRBUTION

                 EFFECT OF DOC COMPLEX1NG
        1000000


         uooooo
         Q10000  •
         001000  -
         000100  -
         000010
         000001
                      10    20    30    40    60    60
                        DOC CONCENTRATION (nx>/U
      4-4.  Phase distribution of a chemical in the three phase system: water,
sediment, and DOC (Equation 4-11).   KOC - KDOC " KOW - 106 L/kg,  foe - 2. OX
and m - 0.5 kg/L.

-------
                                                                      Page 4-13
                                                                         (4-15)
                pore
is given by:

                  oc ow
                  "DOC^OC
                                                                         (4-16)
As mQoc  increases,  the quantity  of DOC complexed  chemical  increases and  the
apparent partition coefficient approaches:

              f  K
               oc ow
             mDOCKDOC
which is just the ratio of sorbed to complexed chemical.

    It  is  important  to  realize that  the  ratio of  organic carbon  normalized
chemical concentration,  roc,  to free  pore water concentration,  eg, is  still
constant  (Equation 4-12)  despite  the presence  of  DOC.   This  is  a critical
point.   The free  chemical  concentration,  eg, can be  estimated directly  from
roc, the organic carbon normalized  sediment concentration, and  the estimate  is
independent of the DOC concentration.  Using CnOre to estimate Cjj requires  that
the DOC concentration and KQQC be known.   The  assumption Cp0re  - c
-------
Page 4-14

4.4  BIOAVAILABILITY OF DOC COMPLEXED CHEMICALS

    The proportion of a chemical  in pore water that  is complexed to DOC can be
substantial as shown previously  (Figure 4-4).   The question of bioavailability
of DOC complexed chemical  can be  important  in assessing toxicity directly from
pore water determinations.  A significant quantity of data indicates that DOC-
complexed chemical is not bioavailable.   McCarthy and Jimenez (1985) using fish
and Landrum et al.  (1987)  using an amphipod demonstrate that by adding DOC the
uptake of  PAHs  are  significantly  reduced  (Figure  4-5).   For  a highly
hydrophobia chemical such as benzo(a)pyrene the effect is substantial while for
less hydrophobic chemicals, e.g., phenanthrene, the reduction in uptake rate is
insignificant.  This  is the expected result  since for a  fixed  amount  of DOC,
the quantity of DOC complexed chemical decreases with decreasing KQQC (Equation
4-13).

    The  quantitative  demonstration  that  DOC complexed chemicals  are  not
bioavailable  requires  an  independent  determination  of the concentration  of
complexed chemical.  Landrum et  al. (1987)  have developed a C-18 reverse-phase
HPLC  column technique  which separates the complexed and  free chemical.   Thus,
it  is  possible  to compare the measured DOC-complexed  chemical  to  the  quantity
of  complexed  chemical  inferred  from  the uptake experiments,  assuming  that all
the complexed chemical  is not bioavailable (Figure 4-6).   Although  the uptake
suppression is larger  than that  inferred from the  reverse phase separation,  it
appears that  the DOC complexed fraction, cnoc«  *-s  not  bioavailable.  Hence the
bioavailable form of dissolved chemical is  c^, the free uncomplexed component.
This  is  an important observation since  it is  c
-------
              800
              200
         i
         i
               100
                     UPTAKE OF CHEMICALS BY
                          PONTOPOREIA HOYI
                         WITH DOC
                         WITHOUT DOC
BeP   TCBP   Pyr
                                              Phan
                          DATA LANDRUM ET AL 1987
FIGURE 4-5.  Average uptake rate of chemicals by Pontoooreia hovi with (filled)
and without  (hatched) DOC present.   Benzo(a)pyrene  (BaP);  2,2',4,4'
tetrachlorobiphenyl  (TCBP); Pyrene (Pyr);  Phenanthrene  (Phen)  (Data:   Landrum
et al.f 1987).

-------
                    DOC PARTITION COEFFICIENT
   UPTAKE SUPPRESSION VS REVERSE PHASE  DETERMINATION
         §      7
                6
                                             6
                      LOQ10 REVERSE PHASE Krp d/kg OC)
                DATA:  L*NDRUM ET AL. 1985; LANDRUM ET AL 1987
FIGURE 4-6.   Comparison of logic  of the DOC partition coefficient calculated
from  the  suppression of chemical uptake versus the  C-18 reverse  phase HPLC
column estimate.  Circles are Aldrich humic  acid;  triangles  are interstitial
water DOC.  Chemicals are listed  on Figure  4-3 and Figure 4-5 captions (also
anthracene and benzo(a)anthracene).

-------
                                                                      Page 4-17

partitioning  equation:  roc  -  Kow c64 pm).   This latter fraction was  further separated into a low

-------
Page 4-18

density  fraction  (<1.9 g/cm^)  and  the remaining  higher density  sand sized
particles.  It  is  important to realize  that  these size fractions are not pure
clay, silt  or sand but are natural particles  in the  size  classes  denoted by
clay, silt and sand.  The organic carbon fractions of the bulk sediment samples
and each of the  fractions  are  shown on Figure 4-7.   The organic carbon content
of the bulk sediments range from foc - 0.3 to 1.6 percent.  The fractions range
from  less  than  0.5  percent (the  horizontal line)  for the high  density sand
fraction to greater than 10 percent  for the low density fraction.   This is a
substantial range in organic carbon content foc.

    Figures 4-8A and 4-8B compare the sediment concentrations for each chemical
on a dry weight  (left hand side) and an organic carbon basis (right hand side).
The  concentrations  across  the  sediment fractions at  each station  are  nearly
constant on an  organic  carbon basis.  In contrast the  concentrations on a dry
weight basis are dramatically different.

    Figure 4-9  compares the dry weight  normalized bulk sediment concentration
to the individual dry weight normalized class concentrations, rj, (upper panel)
and  as a frequency distribution of their ratio (lower  panel).   The  dry weight
normalized data  have distinctly different concentrations - the low density high
organic  carbon fraction  is  highly enriched whereas  the sand fraction  is
substantially below the bulk concentration.  Figure 4-10 presents the same data
but  on  an organic carbon  normalized basis,  rocj.   In  contrast  to  Figure 4-9
essentially all the organic carbon normalized low density  and silt/clay data
are  within a factor of three  of the bulk  data (lower  panel).   A significant
fraction of the  sand data  exceeds the bulk concentration.

     Since  the validity  of  organic  carbon normalization appears to be  limited to
foc  > 0.5 percent,  Figures 4-11 and 4-12 present  the  data restricted to foc >
0.5  percent.    Again,   the  dry weight normalization does not  account  for the
chemical concentration  in the low density fraction,  whereas the organic carbon
normalization is reasonably consistent  and the consistency of the ratios of the
organic  carbon  normalized concentrations  is  apparent.   It is  concluded from

-------
                 ORGANIC CARBON FRACTIONS,
         10QO
          10.0
    s
           0.1

I
                  B STA TP
                  Z3 STA WD
                  0 STA 7
                  Q STA 5
                  • STA 4
                                     FRACTION
                      ^^                             the Unseparated
    <1.9 gm/cc (LOW); the sand sized fraction >6±  £ ?nSity f"Ction >64
silt/clay  sized fraction  <64um   In onl c«e  fc,?-' >l,\9 ^/CC  (SAND>: the
further separated into the cl^ and  silt Sft H  £Sta,tlOn A> this  fraction was
indicated; Wells Da*, 
-------
i"
M
8"
                        FLUORANTHENE



                           §"4
LJ
                           I,.-
                                tntm  *nt« nnMi
                                  4    •    »
                      BENZO FLUORANTHENE
^* w'
                  J
                           I..
         ««m  rum
                                IIMIBI IMIOI  tutm nut  lawi
                                  4    (    I   MM  MM
                        ANTHRACENE
                  j
                     BENZO (A) ANTHRACENE
I-
l-
                  I
     nnm nui«  rtuai
      «   •    r
                                    •mm  maim
                                                                                    DATA: PRAHL. 1982
                                u  ^'8^'    Sedlment chemical  concentrations  for each chemical  on  a  dry

                           weight (left  side)  and an organic  carbon  basis  (right  side)  for  the bulk

                           sediment  concentration  (filled)  and the  sediment fractions  for  each  station

                           The  bars  in the  plot are ordered as follows:  for Station 4) bulk, low density'

                           ft ??'  n    '  !    Sand:  Statlons 5 and 7) bulk, low density,  silt/clay,  and sand-
                           Wells  Dam and  Tongue Point)  bulk, and low density (Data- Prahl   1932)

-------
                            PERYLENE
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                    DM  Mint
                                              Hfi« t*u»  mm*
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                         BENZO PERYLENE
                        I
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     ntttai  HMIM  nmai
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 INDENOPERYLENE
ntttoN  «rm«  tutiai mu*  TBM
 «    •    7   am   Min
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                              W—  *
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                               1C1
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          luiiw  nmai mat TDM
                                   •MTIW  nUI«  tt»l«  «U.t • TOM
                                     •    •    I   OM  MIW
                                             itHiM  n«i« mil  TMM
                                                                       miiw IMTIM  IUIIOM mil TMUI
                                                                                               BENZO (A)PYRENE
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                                                                                IllllM  IU1IOH  «U«  NMUi
                                                                                 •    r   DM  mm
J
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                                                                        4     •     T   DM   MINI
                                                                                              BENZO (E)PYRENE
                                       IUTIM nmai  ITMIM «u«  IOMM
                                                                      10'
                                                                                                          •MUCH ItXIM ITAIIW H1U  tO««
                                                                                                           «     D     >    OM   mn
                          FIGURE 4-8B.    Sediment  chemical  concentrations for  each  chemical on a  dry
                          weight (left  side)  and  an organic  carbon  basis  (right  side)  for  the  bulk
                          sediment  concentration  (filled) and the  sediment  fractions  for  each station.
                          The  bars    in  the plot  are ordered as  follows:    for  Station  4)  bulk,  low
                          density,  clay,  silt,  and  sand;  Stations 5 and 7) bulk,  low density, silt/clay,
                          and  sand;  Wells  Dam  and  Tongue  Point)  bulk,  and low density  (Data-   Prahl
                          1982).

-------
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                             I  I I II Ml    I  I  I I I I III   I   I I I I I
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SAND           x
                           I  I  I I I III!    I  I  I I I I
                                                          III    I  I I  I I I II
                                   10          100         1000


                             BULK  SEDIMENT  PAH  (ug/g)
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g i i mini i i iiiiiii
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1 1 Illllll 1 1 1 1 1 1 III
1
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          0.1
                          10   20      50


                                  PROBABII1TY
                                    BO   90
gg     gg. g
 FIGURE  4-9.   Dry weight normalization.   Comparison  of (top panel)  the bulk

 sediment  concentration  for all  PAHs  (x axis)  with  the same  chemical

 concentration in  the  individual sediment fractions  (y axis)  on a dry weight

 basis.    Bottom panel presents  a  probability plot  of the ratio  of these

 quantities for the three size fractions (Data:  Prahl,  1982).

-------
   1000000
                           ORGANIC CARBON  NORMALIZATION
8
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    100000
     10000
      1000
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           LOW DENSITY  +
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           SAND          x
         \c\\/ i   i i 111111    i  i i  i 11111   i  i  i 11 mi   i   i i i i mi    i  i  i i 11 u
          10          100        1000        1.0000       100000      1000000
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                          10   20      50      80   90

                                  PROBABILITY
                                                              99
99.9
  FIGURE 4-10.   Organic carbon normalization.  Comparison of  (top panel)  the bulk
  sediment concentration for  all  PAHs  (x  axis)  with  the same  chemical
  concentration  in  the individual sediment  fractions  (y axis)  on an  organic
  carbon basis.   Bottom panel  presents a probability plot of the  ratio  of these
  quantities for the three size fractions (Data:  Prahl,  1982).

-------
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  3
  X

  CL

  cn
  CO
  u

  LJ
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  10
     10000
    1000
     100
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                i nun—i  i i mm—i  i  i mm—r—r
LOW  DENSITY   +
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foc  > °-5%
                 . .  mm   i  i  i nun - 1  I I  Illlll - 1  I  I Mllll - 1  I I  Mil
                       i           10          100         1000        10000
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1 =
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=
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          0.1
                           10   20      50       BO  90

                                  PROBABILITY
                                                                 99     99.9
 FIGURE 4-11.   Dry weight normalization  with  foc  > 0.5X.   Comparison  of (top
 panel) the bulk  sediment concentration  for all PAHs (x axis) with  the same
 chemical  concentration in the individual sediment  fractions (y axis)  on a dry
 weight basis.   Bottom panel presents a probability plot of the ratio of these
 quantities for the three size  fractions (Data:  Prahl, 1982).

-------
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  CO


  3
  0

  UJ
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   1000000
    100000
     10000
      1000
       100
                          ORGANIC CARBON  NORMALIZATION
                    I III
                           I  Illllll
                                       I  I I I I III    I  I I I I III!
LOW DENSITY   +
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          10          100
                             Minn   i  i i  111111    i  i i 111111   i  iiiiin

                                1000       10000      100000     1000000
                         BULK  SEDIMENT PAH  (ug/g OC)
      1000
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|8

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                           10   20     50      BO  90


                                  PROBABILITY
                                               99    99.9
                          ^
 chemical  concentration  in  the  individual  sediment  fracti^s (y

-------
Page 4-26

these  data chat  the organic  carbon  normalized  measurements  are  relatively
independent of  particle  size class  and that organic  carbon is a  controlling
factor in establishing the level of contamination of sediment particles.

4.5.2    Sediment - Pore Water Partitioning

    Since  the solid phase chemical  concentration  is  proportional  to the  free
dissolved  portion  of the pore  water concentration, eg,  the actual partition
coefficient, Kp, should  be  calculated using the free  dissolved concentration.
The  free  dissolved  concentration  will  typically  be lower than  the  total
dissolved  pore water chemical  concentration  in the  presence  of  significant
levels of  pore water  DOC.  So,  the actual partition coefficient is  higher  than
the apparent partition coefficient.

    Direct observations of pore  water partition  coefficients  are restricted to
the  apparent  partitioning  coefficient,  Kp (Equation  4-15),  because  total
concentrations in the pore water are reported and DOC complexing is  expected to
be significant  at  the DOC concentrations  found in pore waters.   Data reported
by  Brownawell  and  Farrington  (1986) demonstrate  the importance  of  DOC
complexing in  pore water.   Figure  4-13 presents  the  apparent  organic carbon
normalized partition coefficient that  was  measured  for  10  PCB  congeners at
various  depths  in  the sediment  core versus  foc  KOW,  the calculated partition
coefficient (solid  symbols).   The line corresponds to the relationship,  KOC -
KOW.  which is  the  expected result if DOC complexing were not significant.
Since  DOC  concentrations were  measured for  these data it is  possible  to
estimate eg using Equation (4-14) in the form:
                 °pore
and  to  compute  the  actual partition coefficient: Kp - r/C(j.  The data indicate
that if KDQC  ~ KOW  *-s  used, the  results  shown on  Figure 4-13 as  the open

-------
   O)
  Q
  LU
  DC

  co
  <
  LU
             - 0 ACTUAL Kg  (BASED ON FREE DISSOLVED PCB)
                * APPARENT K  (BASED ON TOTAL DISSOLVED PCB)
                          DATA: BRONNANELL AND FARRINOTON.  isse
        4-13.   Observed partition  coefficient  versus  the product of  organic
carbon  fraction and  octanol -water partition coefficient.   The line  represents

equality.   The  partition coefficients are  computed using  total dissolved PCB

(*) and using  free PCB (o) computed using Equation (4-20) with KDOc - K<>w.

-------
Page 4-28

symbols, agree with the expected partition equation, namely that Kp -  foc  KQW.
A similar  three  phase model  has  been presented  by Brownawell and Farrington
(1985).

    Other  data with  sediment • pore  water partition  coefficients  which  are
based on total dissolved concentrations (Kadeg and  Pavlou, 1987), or for which
the  DOC concentrations  have  not been  reported (Socha  and  Carpenter, 1987;
Oliver, 1987), are available  to assess the significance of DOC partitioning on
the  apparent  sediment partition  coefficient.   Figure  4-14 presents these
apparent  partition coefficients  versus  foc  Kow using  individual  ratios of
sediment  and pore water  concentrations.    The expected  relationship  for  DOC
concentrations of 0,  1, 10,  and 100 mg/L is shown on Figure 4-14 and  the  data
roughly conform  to  DOC  levels of  10 to  100 mg/L.   These  DOC levels  are
representative of pore waters (Brownawell  and Farrington,  1986; Bricker et  al.,
1977).   Further,  the results do not refute the hypothesis that Koe  - KQW in
sediments but show the need to account for DOC complexing.

    It  is  concluded  from the  results  of  this section  that the  effect of  DOC
complexing can be  significant  in  aquatic  sediments  and  that it  should be
assessed when  evaluating the  distribution of chemicals  in sediments.    As shown
above,  methods are available to make this  assessment.

4.6  ORGANIC CARBON NORMALIZATION  OF BIOLOGICAL RESPONSES

    The results discussed above suggest that  if a concentration-response curve
correlates  to pore water concentration,  it should correlate  equally  well to
organic carbon normalized total chemical  concentration,  independent of  sediment
properties.   This is based on  the  partitioning  formula roc  - Kowcd (Equation
4-12)  which  relates  the  free  dissolved  concentration  to the  organic carbon
normalized  particle concentration.   This only  applies to  non-ionic hydrophobic
organic chemicals since the  rationale is  based on a partitioning  theory  for
these   chemicals.   To  demonstrate  this  relationship,  concentration-response
curves for  the data  presented  in  Section  3  were  used to   compare

-------
         10'
     O)
    Q
    LU
    DC
    Z)
    CD
    <
    LU
          10'
                   i i 11 mi    I  i i 11 mi   I   i i 11 mi
                            1  T
           I Illl
                       T I  I I III
                                   B  C
  B
                                 iiiINI
i  i  i
                                               INI
                             i  i i i inn
                      i mi
                                                  DOC:
                                                 (mg/L)
                                                  o
                                                                          10
                                                                          100
            10
10'
                                     ,3
10
                  10'
10'
                                  focKow   (L/kg)
FIGURE 4-14.   Observed partition  coefficient  versus  the product  of  organic
carbon fraction and octanol-water partition coefficient.   The lines represent

the expected relationship  for DOC concentrations  of  0,  1,  10 and 100 mg/L and

KDOC - KOW   Data from OU-ver  (1987) for PCB congeners and other chemicals (A),
from  Socha  and Carpenter  (1987)  for Phenanthrene  (B), Fluoranthene  (C)  and
Perylene (D) and from  Kadeg and Pavlou (1987) for  Naphthalene  (E), Phenanthrene

(F), Pyrene  (G),  Anthracene (H) and Flouranthene (I).

-------
Page 4-30

results on a pore water-normalized and organic  carbon-normalized  total chemical
concentration basis.   These results are described below.

4.6.1    Toxicitv Experiments

    The results of a number of laboratory experiments can be used to assess the
correlation of observed  data with concentration-response  curves  based on both
pore  water concentration  and  organic  carbon  normalized  total  chemical
concentration.  Figures 4-15  to 4-17 present these comparisons for kepone, DDT
and fluoranthene.  The mean and 95 percent confidence  limits  of the LC50 and
EC50 values for each set of data are shown in Table 4-1.  The top panels repeat
the response  - pore water  concentration plots shown previously in  Section 3
while the lower panels present the response versus  total sediment concentration
data which  is  organic  carbon normalized 
-------
         ACUTE  TOXICITY  OF  KEPONE  TO
               CHIRONOMUS TENTANS
    100
4
>
t-H
>
a.

in
                            %  ORGANIC CARBON
                                  .09   •
                                  1.5   •
                                  12.0
            29     SO     75     1DO     125

             PORE WATER KEPONE  lug/L)
ISO
    too,
cr
in
     o
      o
                    CHRONIC  TOXICITY OF  KEPONE TO
                           CHIRONOMUS  TENTANS
               ISO,.
           o
           cr
           i-
           o
                                                        O
                                                        CC
                                                        CD
              % ORGANIC  CARBON
                     .09   •
                     1.5   •
                     12.0  A
  25         50         75

PORE WATER KEPONE  (ug/L)
                                                            ISO,.
                                                        o
                                                        cr
                                                        o
                                                        LJ
                                                        o
                                                        cr
                                                        CD
                  1000          2000

             SEDIMENT KEPONE (ug/g OC)


              DATA- ADAMS, et  a)..  1983
                                    1000
                         SEDIMENT KEPONE  (ug/g OC)


                          DATA:   ADAMS, et.al.. 1983
                                                                                                     100
                                                        2000
                              4-1?.   Comparison of percent survival  (left) and growth rate reduction
                       (right)  of  Chironomus tentanq to kepone  concentration in pore water (top)  and
                       in bulk  sediment using  organic carbon  normalization  (bottom)  for  three
                       sediments with varying organic carbon concentrations.

-------
     ACUTE  TOXICITY  OF  DDT  TO  HYALELLA
    100
                            % ORGANIC CARBON
                                   3.0   •
                                   7.2   •
                                   10 5
                                               ACUTE TOXICITY  OF  ENDRIN TO HYALELLA

                                                  I00r
                                                           cc
                                                           in
     o oo
    too*
i oo      ?oo      3.00      4.00

  PORE  WATER DDT  (ug/L)
                                            5 00
                                                                           % ORGANIC CARBON
                                                                                  3.0    •
                                                                                  6.1    •
                                                                                  11 2
cc
in
                                                               90.
                                                                0.0
                                                  too,
20      40      60      BO

 PORE MATER ENORIN  (ug/L)
                                                                                                         10 0
                  soo           1000

               SEDIMENT  DDT (ug/g OC)

             DATA  NEBEKEH and SCHUVTEMA. 1988
                                1500
                                                           100      200       3OO      400

                                                           SEDIMENT  ENDRIN  (ug/g  OC)

                                                           DATA. NEBEKER and SCHUYTEMA.  1988
                                                                                            500
                   FIGURE 4-16.   Comparison  of percent  survival  of Hyalella to  DDT  (left)  and
                   endrin (right) concentration in pore  water (top) and  in  bulk sediment using
                   organic carbon normalization (bottom)  for three  sediments with varying organic
                   carbon concentrations.

-------
                  ACUTE TOXICITY  OF FLUORANTHENE  TO
                        RHEPOXYNIUS ABRONIUS
           cr
           t/i
           X
                                      %  ORGANIC  CARBON
                                             0.2   •
                                             0.3   •
                                             0.5   «•
                0.0       20.0       40.0      "50.0       60.0
                    PORE WATER FLUORANTHENE  (ug/L)
           cc
           in
40
                20.
                .
                 0     1000   2000   3000   4000   9000   6000   7000
                    SEDIMENT  FLUORANTHENE  (ug/g  OC)

                           DATA FROM 5NARTZ. et.al..  1987
FIGURE 4-17.   Comparison of  percent  survival  of Rhepoxvntus abronius to
fluoranthene concentration in pore water (top) and bulk sediment using organic
carbon normalization  (bottom) for  sediments  with varying organic  carbon
concentrations.

-------
TABLE 4-1. DOSE-RESPONSE PARAMETERS3
Chemical
(End Point)
Kepone
(Mortality)
Kepone
(Growth)
Fluoranthene
(Mortality)
DDT
(Mortality)
Endrin
(Mortality)
foe
M
0.09
1.50
12.0
0.09
1.50
12.0
0.2
0.3
0.5
3.0
7.2
10.5
3.0
6.1
11.2




Total Sediment
(uz/e.)
0.97
7.89
42.0
0.40
9.87
48.9
3.3
6.2
10.5
11.0
19.6
49.7
4.4
4.8
6.0


( 3.0 -
( 5.4 -
( 8.3 -
(10.1 -
(15.6 -
(44.2 -
( 3.9 -
( 3.7 -
( 4.7 -


3
7
13
12
24
56
5
6
7


.7)
.1)
.4)
.7)
.3)
.3)
.2)
.3)
-4)

LC
-------
       BIOACCULUMATION  OF  KEPONE-IN
              CHIRONOMUS  TENTANS
   10000
01
D
LJJ
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Z)
CD
Q
O
CO
    1000
100
      10
           i  i i  i iT m    i  i  i i MiM    i  i  i i M 111    i  i  i i iiit
        NOTE=
          BODY BURDEN ESTIMATED
          FROM REPORTED AVERAGE
          BAF FOR EACH SEDIMENT TYPE.
% ORGANIC C:
 <  0.09   •
    1.50   •
  12.00   A
                   n
                               n
                   10          100         1000

                 PORE  WATER KEPONE   (ug/L)
                                                 10000
   10000
01
\ 1000
O)
^D
g 100
CC
Z)
CO
D 10
0
CO
1
= 1
-
I
1
FIGURE 4-18.
I 1 I 1 I 1 II 1 1 I 1 1 1 1 II 1 I 1 I I
A
x
1 1 ll l l l l i
•
•
k M
V~
^
A m NOTE:
BODY BURDEN ESTIMATED
FROM REPORTED AVERAGE
BAF FOR EACH SEDIMENT TYPE.
i i i i 1 1 n i i i i i 1 1 ii i i i i i 1 1 M i i i i i
10 100
1000
1 l±
=
1 > '



10000
SEDIMENT KEPONE (ug/g OC)
Comparison of body burden of Chironomus tentans to kepc
  concentration in pore water  (top) and bulk sediment using organic carbon
  normalization  (bottom)  for  sediments  with varying  organic  carbon
  concentrations.  (Body burdens calculated from average bioaccumulacion factors.
  Data:  Adams et al.,  1983.)

-------
                                                                                                                     V
                                                                                                                    00
                                                                                                                     ID
                                           TABLE 4-2.   BIOACCUMULATION FACTORS8
Bioaccumulation Factors
Total Sediment
Chemical
Kepone
Cypermethrin
Permethrin
foe
m
.09
1.50
12.
2.3
3.7
2.3
3.7
iig/g organism
utL/tL sediment
600
20
3.3
6.21
0.50
0.60
4.04
0.38
0.23
( 308
( 4.8
( 0.3
(4.41
(0.30
(0.37
(2.89
(0.17
(0.18
- 892)
- 35.2)
- 6.3)
- 8.01)
- 0.71)
- 0.83)
- 5.20)
- 0.59)
- 0.28)
Pore Water
/ig/kg organism
t»g/L
17,600
5,180
5,790
80.1
51.3
92.9
39.7
52.5
29.7
(6,540
(1,970
(2,890
(73.5
(43.8
(87.0
(25.0
(22.6
(15.6
- 28.600)
- 8.390)
- 8,700)
- 86.7)
- 58.8)
- 98.8)
- 54.3)
- 82.4)
- 43.7)
Organic Carbon
Normalized
utL/ti organism
ue/g sediment OC
.54
.30
.40
<.006
.012
.022
<.004
.009
.008
(.277 -
(.072 -
(.036 -
(.004 -
(.008 -
(.012 -
(.002 -
(.005 -
(.006 -
.803)
.528)
.756)
.008)
.016)
.032)
.006)
.013)
.010)
Reference
Adams, Kimerle
and Mosher,
.1983 and 1985
Muir et al., 1985
Muir et al., 1985
a95Z confidence limits shown in parentheses

-------
                                                                     Page 4-37

organic  carbon  normalization  for  sediments and to  examine organism
normalization  as well.   The  use . of organism  lipid as  the phase  which is
analogous to POC has become  conventional  (see  references  in Chiou,  1985).   If
corg is  tne chemical concentration per  unit dry weight,  then the partitioning
equation is:
         c    - K_f_c.
          org    L L d

where:

    KL - lipid-water partition coefficient  (L/kg lipid)
    fL - weight fraction of lipid (kg lipid/kg organism)
    eg - free dissolved chemical concentration (pg/L)

The lipid-normalized organism concentration, corg,L, is:
                  c
                   org
         cwL--r--K.c.                                           (4-22)
          org.L    f     T. d
If the  organic  carbon normalized sediment concentration is used  to  compute  a
bioaccumulation factor (BAF),  then:
                                                                        (4-23)
                     oc     ""
where the second equality results from using the partitioning Equations (4-12)
and  (4-22).   The BAF is the partition coefficient between  organism  lipid  and
sediment organic  carbon.   If  the  equilibrium  assumptions  are valid  for both
organisms and sediment particles,  the BAF should be independent of particle  and

-------
Page 4-38

organism properties.    In  addition  if lipid  solubility  of a  chemical  is
proportional to its  octanol  solubility,  KL « KOW, then the  lipid  normalized -
organic carbon normalized  BAF should be a constant, independent of  particles,
organism, and chemical  properties  (McFarland,  1984;  Lake et al.,  1987).   This
result can be directly tested.

    The representation of benthic organisms  as passive encapsulations  of  lipid
that  equilibrate with  external chemical  concentrations  is  certainly only  a
first order approximation.    Biomagnificatlon effects  via ingestion  of
contaminated food and  the dynamics  of internal  organic  carbon metabolism  are
ignored.  Nevertheless it is an appropriate initial assumption since  deviations
from  the  first  order representation  will  point  to necessary  refinements,  and
for many purposes this approximation may suffice.

    A  comprehensive  two-part experiment  (labeled  A and  B)  involving four
benthic  organisms:  species of Yoldta  (A), Nephtvs  (A), Nereis (A and B),  and
Macoma  (B) and five  sediments  (1, 2,  3 for A;  1,  4,  5  for B) has recently been
performed  (Rubinstein et  al.,  1988).   The uptake of various PCB congeners  was
monitored until  steady state  body  burdens were reached.   Sediment organic
carbon and organism lipid content were measured.   The utility of organic carbon
normalization is  examined on Figures  4-19  and 4-20 which present probability
plots  of the BAF  (ratio of  organism to sediment concentration)  of a tetra-
chloro  and hexa-chloro biphenyl  congener  using  dry weight normalization  for
both  organism and  sediment (top panels); organic carbon normalization for  the
sediment (middle panels);  and  both  organic carbon  and  lipid normalization
(bottom  panels).  The  individual sediments are separately identified.  The  two
experiments  are  presented separately since there is an unexplained  systematic
difference  between  the  results  -  even  when comparing the  same  organism  and
sediment.   The  BAFs based on dry weight normalization are quite different  for
each  of the  sediments.   Organic  carbon normalization essentially collapses  the
BAFs  for  each  sediment  and also  reduces  the  variability  somewhat (middle
panel).   There  is no statistically significant difference between the BAFs  of
the organisms in each test.  A summary of all data versus Kow,  a measure of  the

-------
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    FTCURE  4-19    Probability plots  of  the bioaccumulation factor  (ratio  of
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    dry weight normalization  for both organism and  sediment  (top  panels);  organic
    carbon normalization  for  the sediment (middle panels); and organic  carbon and
    lipid normalization  (bottom panels).  Two experiments (A  and  B)  involving four
    benthic organisms:  Yoldia  (A), Neohtvs  (A),  Nereis  (A and B), and  Hacpi^a (B)
    and five  sediments (1,2,3 for A; 1,4,5 for B) are shown.

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FIGURE  4-20.    Probability  plots of  the bioaccumulation  factor  (ratio of
organism to sediment concentration) of a 2,2'3,5,5',6 hexachloro biphenyl using
dry weight normalization for both organism and  sediment (top panels); organic
carbon normalization  for the sediment (middle panels);  and organic carbon and
lipid normalization (bottom  panels).  Two  experiments (A and B) involving  four
benthic organisms:  ^sl^i& (A), Nephtvs  (A),  Nereis (A  and B),  and Macoma (B)
and five sediments (1,2,3 for A; 1,4,5 for B) are shown.

-------
                                                                      Page 4-41

 degree  of hydrophobicity of  the  congeners,  are presented on  Figure  4-21.  The
 log means are shown for the  same sequence of  normalizations.   The variability
 due  to  sediment  type is  significantly  reduced with  organic  carbon
 normalization.   Also,  the BAFs  are  reasonably  constant although  some
 suppression  at  the high KQW range is evident.

     Results  of a similar though  less extensive experiment using  one sediment
 and Oligochaete worms  has been  reported  (Oliver, 1987).   A plot of the  organic
 carbon  and  lipid normalized  BAF  versus  KQW from  this experiment is shown  on
 Figure  4-22, together  with the previous data.  There appears  to be a systematic
 variation  with respect  to  Kow which suggests  that  the  simple  lipid
 equilibration  model  with a  constant lipid-octanol  solubility  ratio  is not
 completely descriptive for all chemicals.

     A further  conclusion can  be reached  from these results.   It  has  been
 pointed out  by Bierman  (1988)  that  the  fact that  the  lipid-carbon normalized
 BAF is  of order 1 to 10 supports  the  contention that the  partition coefficient
 for sediments is  Koc and that the particle concentration effect does not appear
xto be affecting the free concentration  in sediments.   The reason is that the
 lipid-carbon normalized BAF is the ratio of the solubilities  of the chemical  in
 lipid and in particle carbon,  Equation  (4-23).   Since the solubility of non-
 ionic organic chemicals  in various non-polar solvents is similar, it would  be
 expected that the lipid-organic carbon solubility ratio should  be  of order  one.
 If this ratio is taken to be  one  then the conclusion from the  BAF data is  that
 indeed  Koc - Kow for sediments (Bierman,  1988).

     A final observation can be made.   The  data  analyzed in  this section
 demonstrate  that organic carbon normalization accounts for much of the reported
 differences  in bioavailability of chemicals  in sediments for  deposit feeding
 organisms.  By contrast, the  data presented in previous sections are limited  to
 amphipods and  midges.  Hence  they  provide important  additional support for
 organic carbon normalization  as a determinant  of bioavailability  for  two quite
 different classes of organisms.

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                             DATA:   RUBENSTEIN ET AL.,  1988

       FIGURE  4-21.   Plots  of the  bioaccumulation  factor  (ratio of  organism  to
       sediment  concentration)  of a series  of PCB congeners versus  Log KQW for that
       congener  using dry weight  normalization for both  organism and  sediment (top
       panels);  organic carbon  normalization for the  sediment (middle panels);  and
       organic carbon and lipid normalization  (bottom panels).   Two experiments (A and
          involving four benthic organisms: v^ldia. (A), Neohtvs (A), Nereis (A and B)
       and Mflsojjfi (B) and five sediments (1,2,3 for A;   1,4.5 for B) are shown.

-------
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FIGURE 4-22.  Plots  of the bioaccumulation factor (ratio of organism  lipid  to

sediment organic carbon concentration)  for a series  of PCS congeners  versus Log

Kow (Data:  Oliver, 1987 and Rubenstein et al.,  1988).

-------
Page 4-44

4.7  DETERMINATION OF THE ROUTE OF EXPOSURE

    The  exposure route  by which  organic  chemicals are  accumulated has  been
examined in some detail for water column organisms (e.g.,  Thomann and Connolly,
1984) .   It  might be  supposed  that the  toxicity  and bioaccumulation data
presented above  can be  used to examine the question of the  route  of exposure.
The  initial  observations were that  biological  effects appear to  correlate  to
the  interstitial water  concentration,  independent of sediment type.  This  has
been  interpreted to mean that exposure is primarily via pore water.  However,
the  data correlate  equally  well to  the organic  carbon normalized sediment
concentration.  This suggests  that the sediment organic carbon is  the route  of
exposure.  In fact neither of these conclusions  necessarily follow  from these
data.   The  reason is  that  an alternate  explanation  is available  that  is
independent of the exposure pathway.

     Consider the  hypothesis that  the  chemical potential (fugacity)  of  a
chemical controls  its biological activity.  The chemical potential,  ^4,  of  the
free  concentration of chemical in pore water,  c^,  is:

          Md - /*Q + RT ln(cd)                                            (4-24)


where no is the standard state chemical potential, and  RT  is  the  product  of  the
universal gas constant  and absolute  temperature (Stumm and Morgan, 1970) .   For
a  chemical dissolved in organic  carbon  -  assuming that particle  organic  carbon
can  be characterized as a homogeneous phase -  its  chemical  potential  is:

          p.   - n  + RT ln(r  )                                          (4-25)
          *oc   'o          oc

where  roc  is the weight fraction  of chemical  in  organic  carbon.  If the pore
water is in equilibrium with the sediment organic  carbon then:
             ' "oc

-------
                                                                      Page 4-45

    The chemical potential  that  the organism experiences from either  route of
exposure (pore water or sediment) is the same.   Hence,  so  long as the  sediment
is in  equilibrium  with the  pore water, the  route  of exposure  is  immaterial.
Equilibrium  experiments  cannot  distinguish between different  routes  of
exposure.  Furthermore, if chemical potential  (or fugacity)  is proportional to
biological effects  then the issue becomes:   in which phase  is n most easily and
reliably measured?   Pore  water  concentration is one option.   However it  is
necessary  that chemical  complexed  to  DOC  be a  small fraction  of the  total
measured  concentration or  that  the free  concentration is  measured.    Total
sediment  concentration normalized  by  sediment  organic carbon  fraction is  a
second option.  This measurement is not affected by DOC complexing.  The  only
requirement is  that  sediment organic carbon be  the only sediment  phase  which
contains significant amounts of the chemical.  This  appears  to be a reasonable
assumption for aquatic sediments  with foc > 0.5 percent.

4.8  FIELD VALIDATION

    The  most  convincing  evidence  that sediment quality  criteria based  on
equilibrium partitioning theory are technically sound would  be a  demonstration
that the criteria can predict the degree of toxicity of natural sediments.   The
measure  of sediment  toxicity  could be either sediment bioassays  or benthic
community  structure  alteration.   Sediment  data  collected  following the  triad
approach (Long and Chapman, 1985) could provide such information.

    There  are  three  technical  difficulties  that  impede  this  demonstration.
Since  they apply to  all  field  data  based approaches  (e.g. , Barrick  et al. ,
1985) they are discussed in some  detail.

1.  Btoavailability

    Contaminated sediment contains measurable concentrations  of many chemicals.
    In order  to apply a sediment quality criteria  or  to use the magnitude  of
    the chemical concentration as a measure of its potential  to have biological

-------
Page 4-46

    effects,  it is necessary that the bioavailability of that chemical  in that
    particular  sediment  be  determined.   For  non-ionic  organic chemicals
    sediment  organic  carbon  normalization can  be  used.   However for  toxic
    metals  and  ionic organic  chemicals  there  is  no currently available
    comprehensive partitioning theory that  identifies  the  normalization
    quantities  and provides  the  parameters  to permit the  free dissolved
    concentration to be calculated.   Hence  bioavailability  cannot  be assessed.
    As demonstrated above, bioavailability can vary  as  much as two orders of
    magnitude.   Therefore,  dry weight  normalization  cannot  be  expected to
    suffice.

2.  Chemical Mixtures  and  Causality

    There  is a  fundamental  difficulty with  using naturally contaminated
    sediments.   Assume that the list  of  chemicals  that  are identified and
    quantified cover  the  known  range of potentially  toxic  chemicals.   It is
    always possible that there is present another chemical,  or chemicals, which
    are  biologically  very  active  but  have  yet  to  be  identified.   If  this
    chemical  is   the  cause of  significant toxicity then  it would cause  a
    biological effect that  would  not  be  predicted  from  the application of
    sediment quality criteria.  This result might be  interpreted as a  failure
    of the criteria when  in fact it  is  a  failure in identification of toxic
    chemicals.

3.  Control Sediments  and  Non-toxic Variations

    To judge the  relative toxicity  of a sediment  it  is  necessary  that  a
    comparable  control  response be  obtained.   The perfect control  is an
    identical sediment without any chemical contamination.   Since  this  is not
    possible, sediments from an unimpacted  site are assumed  to  approximate the
    response of the perfect control.  The degree to which this approximation is
    correct  limits the assessment of  comparative  toxicity.   Variations in
    sediment  toxicity  test  results  and ecological community structure  can be

-------
                                                                      Page 4-47

    caused  by  variations  in sediment characteristics other  than  chemical
    contamination.   For  example,  the  effect  of  grain  size  distribution and
    organic carbon content on habitat are well known.

    In view of these three technical difficulties an alternative means to field
validation was  used.   The section below describes the alternative use  of the
screening level methodology.

4.8.1    Screening Level Methodology ...

    A  straightforward  check of  the validity of sediment  quality  criteria
appears to be precluded.   However,  it would be helpful  if  some  evidence could
be  found that  criteria developed from laboratory  toxicological  data  are  at
least reasonable.  The concept of a screening level concentration provides some
help in this regard.

    The approach for computing a  screening level concentration  for  chemicals
was developed at the same workshop that selected  the  Equilibrium Partitioning
Methodology  (SCD 2).   During the discussion  it became apparent that  a  direct
approach which  correlated some  measure of biological  impairment  to  increasing
concentrations of various  chemicals  was subject to the criticisms outlined  in
the previous  section.   Consider, for example,  data on the simple presence  or
absence  of  a  particular  species  of benthic  organism in  a sediment  sample.
Assume, also,  that the proper  normalization  to quantify bioavailability  were
known.   Suppose an  organism is present  in  one  sediment sample with a low
concentration of a  particular  chemical and  absent in another  with a  higher
concentration of the same  chemical.  It would  be  tempting  to  conclude  that the
cause of the absence  of the  organism is that  the  higher  concentration  exceeded
the threshold of tolerance of that organism for that chemical.   However there
is no way of proving the  causal  link between  that chemical's  concentration and
the absence  of  the organism in that sample.   Mere covariation does not prove
causality.   The  multiple  chemical  -  correlation approach using this same  data

-------
Page 4-48

would  also determine  covariation  but  not causality.   The  absence  of the
organism  cannot unequivocally be. related  to the  concentration  of certain
chemicals.

    Consider an alternative possibility.  An organism  is  present  in a sediment
sample and co-exists with a  suite of  chemicals.   One  can conclude that  the
organism can tolerate  those  concentrations  of chemicals  -  again  assuming that
bioavailability has  been  accounted  for  by proper normalization.  Some care  is
still required since the  organism may be on the verge of exhibiting an  effect
or it may  have just  come  into  contact with  the sediment  and not yet responded.
However these possibilities are likely  to be rare.   For  the majority of cases
the co-occurrence  of an organism and a chemical  at a specific  (bioavailable)
concentration implies that the organism  can tolerate that exposure.   It  is  the
co-occurrence of  chemical concentration  and organism  presence -  not organism
absence -  that is not subject to the criticisms enumerated above.

    The utility of this observation can be seen from the  following hypothetical
situation.   Suppose many  species  of benthic  organisms  are found  to co-exist
with  concentrations of  a chemical  that are  well  in excess  of  the sediment
quality  criteria  for  that chemical.    This situation would  surely call  into
question the criteria for that chemical  since the  field observations contradict
the presumption of biological  effects at concentrations  well in excess  of the
criteria.  On the other hand, if the criteria were well above the  concentration
which co-exists with many  organisms  it  only confirms  that field concentrations
have not yet reached levels at which effects would be  seen.

    It  is concluded,  therefore,  that   the  highest  (or nearly  the highest)
concentration that co-exists  with many  benthic species  is  the lower bound  of
the criteria concentration.  The criteria can be a higher concentration if only
relatively uncontaminated  sediments  are  examined.   It is for this  reason that
this  concentration is  called  a  Screening Level  Concentration or SLC.
Concentrations below the  SLC are known  to  be  tolerated  and therefore it is a
lower bound on the criteria concentration.

-------
                                                                      Page  4-49

4.8.2    Determining Screening Level Concentrations

    The application  of  these idea's to available  field data sets is  presented
in SCD 7.   The following discussion is a  summary of  the two  quantitative  issues
that  need to  be addressed.   First, a  determination  must be  made  of the
concentration level  to be used as  the highest co-existence  concentration.  For
a particular  species a  tabulation of the co-existence  concentrations  can be
made.   Choosing  the highest concentration  ignores  the possibilities  of an
incorrectly  reported high   concentration,  incipient  biological  effects,  and
other  causes  of a  statistical  outlier.    A better procedure  is to  choose  a
specific percentile  -  in this  case the  90tn  percentile was chosen  -  as the
maximum concentration that co-exists with that species.  This concentration is
referred  to  as the  Species Screening Level  Concentration  or SSLC.  For each
species for which  at least  20 occurrences were recorded in the  data base, an
SSLC  was  computed.   Figures  4-23A and 4-23B illustrate the  probability
distributions of the concentrations of Benzo(a)Pyrene  (BaP)  that co-exist with
the  various  species  (see  SCD  7 for  the  species  identification).    The
distributions  occasionally  include  an  outlier but,   for  the  most  part,  are
lognormally distributed.

    The methodology  used for calculating the SLC from.the  SSLC  is  similar to
Che methodology for  generating water  quality  criteria  (Stephan  et al. ,  1985).
The level of protection adopted  for water  quality  criteria is 95 percent of the
species represented  in the data set used to define the criteria.   The sediment
quality criteria analog  to this procedure is to choose the  5C^ percentile SSLC
for  the SLC.   The  probability  distributions  of the  SSLCs for  11  chemicals
including BaP are shown on Figure 4-24.  The procedure  used  to estimate the 5Cn
percentile is the same as is recommended  for generating water quality criteria.
The  resulting  organic  carbon  normalized  concentration  is  the  SLC.    The
probability distributions for the SSLC values for  the other  chemicals for which
field  data  were available are also shown  on  Figure 4-24.   The SSLCs  for  the
PAHs   are  remarkably  similar  with  only  a  factor  of   two  variation in
concentration across the species.   The PCBs are  much  more  widely distributed
reflecting, perhaps, their presence in a  larger  fraction  of  the data base.  The
actual values that result will be discussed in Section  7.

-------
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-------
                                                                      Page 4-53

4.9  CONCLUSION

    This  section reviewed  the general  approach for  development  of sediment
quality  criteria for  non-ionic  organic  chemicals  using  the  equilibrium
partitioning approach.   The theory of partitioning  of chemicals in  sediments
between the pore water and solid phase was described and equations derived for
organic carbon normalization and DOC complexing.  The partitioning of  chemicals
in  sediments  into free, sorbed  to POC  and  sorbed to DOC  components is also
presented.   This information  is  used to  examine  the bioavailability  of DOC
complexed non-ionic organic chemicals and  it is  shown that the free  dissolved
component is the bioavailable fraction.   Similarly, field data confirm that the
free  dissolved  component  is  the fraction which  controls  partitioning  to
sediment  organic carbon as  well.    In  view  of  the difficulty  with directly
measuring the free  dissolved  chemical  concentration,  it is  shown that  an
equivalent method is  to use  the organic carbon normalized sediment chemical
concentration.  Due to the difficulties of direct field validation of sediment
quality criteria  an  alternative method is proposed  using  the  screening level
methodology.  Preliminary sediment  quality  criteria are presented in Section 7.

-------
                                                                       Page 5-1
                                  SECTION 5.
             APPLICABILITY OF USING WATER QUALITY CRITERIA AS THE
                      EFFECTS  LEVEL  FOR BENTHIC ORGANISMS
    The  equilibrium partitioning method  for derivation  of sediment  quality
criteria utilizes  equilibrium  partitioning theory to predict the  biologically
reactive  chemical  concentrations in  pore  water,  and  uses published water
quality  criteria concentrations  to  define  concentrations  of contaminants  in
sediments that will protect the presence and uses of benthic organisms.   Use  of
water quality  criteria  assumes that:   (1)  the sensitivity of benthic  species
and species  tested to  derive water  quality  criteria  are similar,  and  (2) the
levels  of protection afforded by water  quality criteria  are  appropriate  to
benthic organisms.  This section examines the appropriateness  of  the  assumption
of  similarity  of sensitivity  through  a preliminary comparative toxicological
examination  of  selected data bases  on  the  acute and chronic sensitivities  of
benthic and water column species.

5.1  METHOD  - RELATIVE ACUTE SENSITIVITY

    The  relative acute  sensitivities of benthic  and  water column species are
examined  using the data bases  from  the freshwater  and  saltwater  sections  of
draft or  published water quality criteria documents that contain minimum  data
base requirements  for  calculation of "Final Acute  Values"  (Table  5-1).   This
data  base  was  selected because  exposures  were via  water, durations were
similar, and data and test conditions have been scrutinized for quality  through
review  of  all  original  references. For each of the 2,180 tests on 218  species
in  the  36  freshwater criteria  documents and the 1,074 tests on 102  species  in
the 30  saltwater  criteria documents,  the  substance,  species,  life-stage,
salinity,  hardness, temperature, pH,  acute  value,  and  test condition  (i.e.,
static,  renewal, flow-through,  nominal,  or  measured),  were  entered into the
data base.   If necessary,  original  references were consulted to determine the

-------
                           TABLE  5-1.  DRAFT OR PUBLISHED HATER QUALITY CRITERIA DOCUMENTS
                               AND NUMBER OF  INFAUNAL  (HABITATS  1 AND 2). EPIBENTHIC
                               (HABITATS 3 AND 4).  AND WATER COLUMN (HABITATS 5 TO 8)
                           SPECIES TESTED FOR  EACH OF THE HATER QUALITY CRITERIA DOCUMENTS
Number of Saltwater Species

Chemical
Acenaphthene
Acrolein
Aldrin
Aluminum
Ammonia
Antimony III
Arsenic III
Cadmium
Chlordane
Chloride
Chlorine
Chlorpyrifos
Chromium VI
Copper
Cyanide
DDT
Dleldrin
2,4-dimethylphenol
Endosulfan
Endrin
Heptachlor
Hexachlorocyc lohexane
Lead
Mercury
Nickel
Parathion
Parathlon - Methyl
Pentachlorophenol
Phenanthrene
Phenol
Selenium IV
Selenium VI
Silver
Thallium
Toxaphene
Trlbutyltin
1,2,4-trichlorobenzene
2,4.5-trichlorophenol
Zinc
Date of
Publication
9/87°
9/87°
1980
1988
5/88°
9/87°
1985
1985
1980
1988
1985
1986
1985
1985
1985
1980
1980
6/88°
1980
1980
1980
1980
1985
1985
1986
1986
10/88°
1986
9/87°
5/88°
1987
1987
9/87°
ll/88b
1986
9/87
9/BBb
9/87°
1987

Total*
_
-
16
-
16
11
12
38
8
-
20
IS
23
25
9
17
21
10
12
21
19
19
13
33
23
-
-
18
10

16
-
21
-
15
19
10
11
32

Infaunal
_
-
0
-
1
3
2
10
1
-
1
2
8
6
1
1
1
2
2
1
1
2
2
10
7
-
-
6
4

1
-
1
-
2
1
4
4
9

Epibenthlc
_
-
10
-
4
6
3
16
6
-
7
7
8
4
4
10
13
2
6
12
13
13
3
6
9
-
-
3
4

4
-
6
.
6
8
4
4
7
Hater
Column
_
-
9
.
13
5
a
17
5
-
13
9
9
18
5
10
12
6
7
13
10
9
10
18
8
-
.
11
4

12
-
16

9
14
4
S
17
Number of Freshwater Spades

Total*
10
13
21
16

9
17
57
14
15
38
19
-
-
23
41
19
11
10
26
18
22
14
29
17
39
31
44
g
33
25
12
19
7
43
8
14
10
48

Infaunal
.
1
2
-
_
1
1
13
1
3
1
2
-
.
1
3
1
1
1
3
2
1
-
11
2
7
1
9
2
6
2
1
1
1
S
1
2
1
5

Eplbenthic
3
5
9
S

2
6
IS
4
6
8
8
-
-
6
IS
9
3
4
12
8
4
4
a
6
14
a
11
i
9
5
4
g
3
12
1
5
2
11
Water
Column
7
B
IS
12

6
13
37
9
8
31
12
-
-
18
29
12
7
7
17
12
18
11
12
13
25
26
26
Q
21
21
10
13
3
24
5
8
7
36
•The total numbers  of species tested may not  be the same  as  the sum of  the number of  species from each  habitat tyne
because a species may occupy more than one habitat.

°Draft
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-------
                                                                       Page 5-3


life stage tested and  any other missing information.  Each of the species/life-
stages tested were  classified into.one of eight habitat  types listed in Table
5-2, each of which has a different-degree of association with bedded sediments.
                   TABLE 5-2.   HABITAT CLASSIFICATION SYSTEM
                         FOR LIFE-STAGES OF ORGANISMS
Habitat
 Type      	Description	

   1       Life-stages that usually  live  in the sediment and obtain their food
           by ingesting sediment or organisms living in the sediment, (infaunal
           non-filter feeders)

   2       Life-stages that usually  live  in the sediment but obtain their food
           from  the  water column.   These infaunal filter  feeders  may consume
           plankton and suspended detritus.

   3       Life-stages that usually  live  on the surface of sediment and obtain
           their food from the sediment.

   4       Life-stages that usually  live  on the surface of sediment but obtain
           their food  from the water column.   This food  may  include plankton
           and suspended detritus.

   5       Life-stages that usually live in the water column but mostly consume
           food  that is on or in the sediment.

   6       Life-stages  that usually  live in  and obtain  their  food  from  the
           water column but sometime rest  or  sit on the sediment.   These life-
           stages have slight contact with sediment (resting on the surfaces of
           plants, rocks, etc.).

   7       Life-stages that are  usually in or on an  inorganic substrate,  such
           as sand, rocks, and gravel,  spend  all their  time at the bottom of a
           body  of water, but have negligible contact with sediment.

   8       Life-stages that have  negligible contact with the  bottom  of a body
           of water.  These life-stages spend essentially all their time in the
           water column (i.e., pilings,  zooplankton and fish),  in the air, etc.
    If  for  any chemical a life-stage was  tested more than once,  or  more than

one  life-stage was  tested,  data  were  systematically sorted  in  a  three-step
process  to  arrive at  the  acute value based  on the most  experimentally sound

-------
Page 5-4

testing methodology and most sensitive life-stages.   First,  if a life-stage for
species was  tested  more  than  once,  flow-through  tests  with  measured
concentrations had precedence, and.data from other tests were  omitted.   If the
remaining acute values for that life-stage differed by greater than a factor of
four, the  geometric  mean of the  lowest acute  values was calculated  to  derive
the  acute  value  for that  life-stage.   Second, life-stages were classified as
"benthic" (i.e.,  infaunal species [habitats 1 and 2]  or infaunal and epibenthic
species  [habitats  1,  2,  3 and  4])  or  "water  column" (remaining  habitats).
Third,  if  two or more life-stages were classified as benthic or water  column
and  their acute values differed by a  factor of four,  the geometric  mean  of the
lowest  acute  values  was  calculated to derive the acute value  for  that benthic
or  water  column life-stage/species.   The acute  value was  converted  into  a
natural  logarithm  to normalize the  value.   Finally,  the  natural  logs  of  the
acute values  for  any  one  chemical  were  transformed  into  Z-values using  the
equation:
             log(c   .  )-p
               °  acute  rc
         z - 	                                               (5-1)
                   o
                    c
where /ic  and  ac are  the  log mean and  standard  deviation  of  the acute
concentrations  for that chemical.

    This normalization  permits  the pooling of  all  data .for all chemicals  and
the selective  separation  of data on  the relative sensitivities of benthic  and
water column species  relative to the entire spectrum of sensitivities  for  all
species;  i.e.,  benthic  plus water column species.  This data base was  used  to
compare  the (1)  acute  sensitivities  of the most  sensitive benthic and water
column species, and (2) the frequency distributions of the  sensitivities of  all
tests with benthic  and  water  column  species relative  to that expected based  on
the pooled data from both benthic plus water column species.

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                                                                       Page 5-5

5.2  BENTHIC COMMUNITY COLONIZATION EXPERIMENTS

    Toxicicy tests that determine  the effects  of  chemicals  on the colonization
of communities of benthic saltwater species (Hansen and Tagatz,  1980)  appear to
be particularly  sensitive at measuring  the impacts  of substances on  benthic
organisms.  This  is  probably because the most sensitive life-stages  of a wide
variety  of benthic  saltwater  species  are exposed  and the exposure  is of
sufficient duration  to  maximize response.  The  test typically  includes  3
concentrations of a substance and a control, each  with 6 to  10 replicates.  The
test substance is  added to incoming raw seawater containing  planktonic larvae
and other  life-stages  of  marine organisms  which can settle onto  clean  sand in
each replicate aquarium.  The  test typically lasts from two to four months  and
the  number of  species and  the abundance  of  individuals  of  each species  in
aquaria  receiving  the  substance  are compared to  controls.   If  this  test  is
extremely  sensitive  and concentrations  in interstitial and overlying  water
rapidly  reach  equilibrium,  then the effect and no effect concentrations  from
this test  can be  compared  with the final  chronic  value (FCV) from  saltwater
water  quality criteria  documents  to gain insight into the  applicability of
water quality criteria to protect benthic organisms. A FCV is  the  concentration
derived  from  acute  and  chronic  toxicity  data that   is predicted to  protect
organisms  from  chronic  effects  of a  substance  (Stephan  et al.,  1985). In
addition,  similarities  in sensitivities of  taxa  tested as  individual  species
and  in  the  colonization  experiment  can indicate  reasonableness  of  the
conclusion of  similarity  of  sensitivities  of benthic  species  relative to  water
quality  criteria data bases.

5.3  COMPARISON OF THE SENSITIVITY OF BENTHIC AND  WATER COLUMN SPECIES

    The  acute sensitivities  of the most;  sensitive benthic  and  water column
species  were  compared  using  acute values  from the 36  freshwater  and  the 30
saltwater  water  quality criteria  documents.   When benthic  species are  defined
as just  infaunal organisms (habitat types:  1  and 2)  and water column  species
were defined  as  all others  (habitat types:  3  to  8),  the acute values  for  the
water  column  species  indicated  that they were typically  the most sensitive.

-------
Page 5-6

The results  are  cross plotted  on Figure 5-1.   In most instances where  acute
values for saltwater  benthic  and water column species appear  identical,  it is
because penaeid  shrimp were  classified as  infaunal  (benthic) and  epibenthic
(water column) and are most sensitive  to  insecticides.   Clearly, data on  the
sensitivities of  benthic  infaunal species are limited.   Of the  36  substances
for which water  quality  criteria for freshwater organisms are available, 2 or
fewer infaunal species were  tested against 25 (69 percent) of the substances,
and 5 or  fewer species were  tested against 30 (83 percent) of the substances.
Of the 30  substances  for which water quality criteria for saltwater organisms
are available, 2  or fewer  infaunal species were  tested against 19 (63 percent)
of the substances, and 5  or  fewer species were tested against 23 (77 percent)
of the  substances.   Of  these  chemicals  only 3 (8 percent)  have been tested
against freshwater infaunal  species  from 3 or more phyla,  and 7 (23  percent)
have  been tested against saltwater  infaunal  species  from  3 or  more  phyla
(Figure 5-2).   Therefore, it  is probably premature  to  conclude  that benthic
species are  more  tolerant than water column species, that  only  sensitive  or
insensitive  benthic  species  were tested,  or that sediment  quality  criteria
derived from water quality criteria are over-restrictive.

    A  similar examination of  the most  sensitive benthic  and  water column
species, where the definition of benthic  includes both infaunal and  epibenthic
species (habitat  types: 1  to 4),  is based on  more data and begins to suggest a
similarity in sensitivity on the average (Figure  5-3).  In this comparison,  the
number  of acute  values  for  freshwater  benthic  species  for each   substance
averaged 12, with a range  of 2  to 33;  the number of acute values  for saltwater
benthic species  for each  substance averaged  10,  with  a range  of  4 to  26.    The
variability of these  data  is high suggesting  that for some substances, benthic
and water column  species  may  differ  in  sensitivity,  that  additional testing
would be  desirable, or that  this approach to examining species sensitivity  is
not sufficiently  rigorous.  Examination of individual criteria documents  where
benthic species were markedly less sensitive  than water column  species  suggests
that  the major  factor  for   this  difference  is  that  benthic  species
phylogenetically  related  to sensitive water column species have   not  been
tested.   Apparent differences  in sensitivity, therefore,  are likely not  real,

-------
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• Freshwater
^Saltwater
         0.01   0.1   1.0   10   102   103  104   105   106
                         Water Column
   FIGURE 5-1.   Comparison of LCSO or EC50 acute values  for the most
   sensitive  benthic and water column species from 30  saltwater water
   quality criteria documents.   Benthic species are defined as infaunal
   species (habitat types 1 and 2) and water  column species are defined as
   those  species having a lesser association with sediments (habitat
   types:  3 to 8).  The line is the line of  equal sensitivity.

-------
4O
-*-•
 c
DD
      10°1

      105J
   3
    •

102-J


10

1.0

0.1
     0.01
                        Benthic=lnfaunal
                 Lowest Acute Value
                                   2 Phyla Tests Also Removed

                                           • Freshwater
                                           ^Saltwater
         0.01   0.1    1.0   10    102   103 104   105   106
                          Water Column
   FIGURE 5-2.   Comparison of 'LC50 or  ECSO acute values  for the  most
   sensitive benthic and water column 'species from 36 freshwater and 30
   saltwater quality criteria documents.   Benthic species are defined as
   infaunal species (habitat types 1 and 2)  and water column species are
   defined as  those species having a lesser association with sediments
   (habitat types 3 to 8).  Only chemicals  for which species from  3 or
   more  infaunal phyla have been tested are included.  The line is the
   line of equal sensitivity.

-------
,2    1CT-I
 Q)
CD
10  -
      1.0 -
      0.1 -
     0.01
              Benthic=lnfaunal  + Epibentftic
                 Lowest Acute Value
                               dP
                                     • Freshwater
                                     aSaltwater
         0.01   0.1
                 1.0    10    10^    10'
                    Water  Column
104  105
   FIGURE  5-3.   Comparison of LC50 or EC50 acute values for the  most
   sensitive benthic and water column  species from 36 freshwater and 30
   saltwater water quality criteria  documents.  Benthic species are
   defined as infaunal and eptbenthic species (habitat types  1 to 4) and
   water  column species are  defined  as those  species having a lesser
   association  with sediments (habitat types 5 to 8).   The number of
   freshwater benthic species  tested ranged from 2  to 26.  The number of
   saltwater benthic species tested ranged from  5 to 26.  The line is the
   line of equal sensitivity.

-------
Page 5-10

but reflect  an absence of  sufficient data.   Data that are  available  suggest
that on  the  average,  benthic and water column species  are  similarly sensitive
and support  the  initial  use of.water quality criteria  to derive  sediment
quality criteria.

    A second method of comparing the relative sensitivities  of water column and
benthic  species  from freshwater and  saltwater habitats compares  the  relative
sensitivities  of  acute values from  toxicity data for  all  species to that  of
benthic  or water  column species.   Histograms of  the relative  sensitivities  of
infaunal species  (Figures 5-4 and 5-5; habitat types 1  and  2)  and infaunal and
epibenthic species (Figures  5-6 and 5-7; habitat  types  1 to 4) were remarkably
similar.  Histograms  of the  relative  sensitivities of water column species
(habitat types 3  to  8 or 5 to 8) were also  similar  (Figures  5-4  through  5-7).
For these  two habitat  groupings,  frequency  distributions  suggest that  water
column species are only slightly more sensitive than benthic species.  Overall,
this  similarity  suggests  that  sediment  quality criteria  derived from  water
quality  criteria would  protect  benthic species.  These data, along with  the
comparisons  of  the  most  acutely sensitive species  (Figures 5-1 and  5-3),
suggest  that some over protection may occur.

5.4  WATER QUALITY CRITERIA CONCENTRATIONS  VERSUS COLONIZATION EXPERIMENTS

    Comparison of the concentrations  of six chemicals  that affected (OEC)  and
did not  affect (NOEC) benthic colonization  with  the FCVs  either  published  in
saltwater  portions  of water  quality  criteria  documents  or estimated   from
available  toxicity  data (Table  5-3)  suggests  that the level  of  protection
afforded by  water quality  criteria  to benthic  organisms may be  appropriate.
The  final   chronic  value  from the water quality  criteria  document for
pentachlorophenol of 7.9 /ig/L is  less than the  OEC for  colonization  of  16.0
/ig/L  and the  NOEC  of  7.0  /jg/L  is similar  to the  FCV.   Although  no  FCV  is
available for  Aroclor 1254,  the  lowest concentration causing no effects on the
sheepshead  minnow  and pink shrimp  as  cited in the  water  quality criteria
document is  about 0.1 Mg/L.   This  concentration is less than the OEC of 0.6
Mg/L and is  similar to the NOEC of <0.1 pg/L in a colonization experiment.  The

-------
          Water Column Species
          (N=692)
          Benthic Species = Infaunal
          (N=98)
      0-5    5-10   10-25  25-50  50-75   75-90  90-95  95-100
               Percentile Ranges of Pooled Data
              MORE
           SENSITIVE
   LESS
SENSITIVE
FIGURE 5-4.  Comparison of histograms of the relative acute sensitivity
(Equation 5-1)  of benthic and water column  freshwater species as
derived from the 36 water quality criteria  documents.  Histograms  show
the percentage of benthic  and water column species with acute  values
within the  indicated  percentile  ranges of  the pooled data.    Benthic
species are defined as infaunal species.

-------
      I   I Water Column Species
      L—' (N=465)
          Benthic Species = Infaunal
          (N=102)
      0-5    5-10   10-25  25-50   50-75   75-90  90-95  95-100
               Percentile Ranges of Pooled Data
             MORE
           SENSITIVE
   LESS
SENSITIVE
FIGURE 5-5.  Comparison of histograms of the relative acute sensitivity
(Equation 5-1)  of benthic and water column saltwater species as derived
from the 30 water quality  criteria documents.   Histograms  show the
percentage of benthic and water column species with acute values within
the indicated percentile ranges of the  pooled data.  Benthic species
are defined as  infaunal species.

-------
50

45-

40-

35-

30-

25-

20-

15-

10-

 5-
Water Column Species
(N=514)
Benthic Species = Infaunal + Epibenthic
(N=300)
      0-5    5-10   10-25   25-50  50-75   75-90  90-95  95-100
               Percentile  Ranges of Pooled Data
              MORE
           SENSITIVE
                                     LESS
                                 SENSITIVE
FIGURE 5-6.  Comparison of histograms of the relative acute sensitivity
(Equation 5-1)  of benthic and water column  freshwater species as
derived from the 36 water quality criteria  documents.  Histograms  show
the percentage of benthic and water column species with acute  values
within  the indicated percentile ranges of  the pooled data.   Benthic
species are defined as infaunal and  epibenthic  species.

-------
50

45-

40-

35-

30-

25-

20-

15-

10-

 5

 0
Water Column Species
(N=317)
Benthic Species = Infaunal + Epibenthic
(N=328)
      0-5    5-10   10-25   25-50  50-75   75-90  90-95  95-100
               Percentile  Ranges of  Pooled Data

                                               LESS
                                           SENSITIVE
    MORE
 SENSITIVE
FIGURE 5-7.  Comparison of histograms of Che relative acute sensitivity
(Equation 5-1)  of benthic and water column saltwater species as derived
from the 30 water quality  criteria documents.   Histograms  show  the
percentage of benthic and water column species with acute values within
the indicated percentile  ranges of the pooled data.  Benthic species
are defined as  infaunal and epibenthic species.

-------
                                                                             Page 5-15
lowest  concentration  tested  with  chlorpyrifos  of  0.1 /ig/L and  fenvalerate of
0.01  /Jg/L  affected  colonization of  benthic  species.   Both values  are  greater
than  either  the FCV  for chlorpyrifos  of 0.01  ng/L  or a FCV of  0.002 pg/L for
fenvalerate  estimated  from acute and'  chronic effects data.  Insufficient data
are available in the draft water quality criteria  document  for  1,2,4  trichloro-
benzene;  however,  data  from  single  species  tests  suggest the  FCV  should be
<73.0 pg/L.   This value is  consistent with the conclusion from  a colonization
experiment  that  the  NOEC  is  <40.0  pg/L.   Finally,  a  colonization  experiment
with  toxaphene  provides the  only  evidence from . these  tests  that a  FCV from a
water quality  criteria document might  be markedly over  protective  for  benthic
species;  the FCV is 0.2 MgA versus  the NOEC for colonization of  0.8
           TABLE 5-3.  COMPARISON OF WATER QUALITY CRITERIA (HOC) FINAL CHRONIC VALUES (FCV)
           AND  CONCENTRATIONS AFFECTING (OEC) AND NOT AFFECTING (NOEC) BENTHIC COLONIZATION
Substance
Pentachlorophenol
Aroclor 1254
Chlorpyrifos
Colonization
versus WOC"
Colonization (OEC)
WOC (FCV)
Colonization (NOEC)
Colonization (OEC)
WOC (Estimated FCV)
Colonization (NOEC)
Colonization (OEC)
WOC (FCV)
Cone.
ua/l
16.0
7.9
7.0
0.6
-0.1
<0.1
0.1
0.01
Sensitive Taxa
Molluscs, Abundance
Molluscs, Crustaceans, Fish
Crustaceans
Crustaceans, Fish
Crustaceans, Molluscs,
Species Richness
Crustaceans
Colonization Reference
Tagatz et a I., 1977, 1983
Hansen, 1974;
Hansen and Tagatz, 1980
Tagatz et al., 1982
Fenvalerate
 1,2,4-
 Triehlorobenzene
Toxaphene
Colonization (NOEC)
Colonization (OEC)
WOC (Estimated FCV)
Colonization (NOEC)
WOC (Estimated FCV)
Colonization (OEC)
Colonization (NOEC)
Colonization (OEC)
Colonization (NOEC)
WOC (FCV)
 0.01   Crustaceans, Chordates
-0.002  Crustaceans
<73.0   Crustaceans, Fish
 40.0   Molluscs, Abundance
Tagatz and Ivey, 1981
Tagatz et al., 1985
 11.0   Crustaceans, Species Richness   Hansen and Tagatz, 1980
 0.8
 0.2   Crustaceans, Fish
aSix day exposure to established benthic community
     Taxa  most  sensitive  to  substances as  reported in  saltwater  portions  of
water quality criteria documents and  from results of  colonization experiments
are generally similar although,  as might be  expected, differences  occur.   For
example,  for   both  water  quality  criteria  documents  and  colonization

-------
Page 5-16

experiments,  crustaceans  were most  sensitive to  Aroclor 1254,  chlorpyrifos,
fenvalerate, and  toxaphene.   Colonization experiments indicated  that  molluscs
were particularly sensitive to three substances, an  observation noted  only for
pentachlorophenol in  water quality criteria  documents.   Fish, which  were not
tested in a colonization experiment,  were particularly sensitive to four of the
six substances.

5.5  CONCLUSIONS

    Comparative  toxicological  data on the acute  and chronic  sensitivities  of
freshwater  and saltwater  benthic  species as published in  the water  quality
criteria  documents  are limited.   Acute values  are available  for  only 34
freshwater  infaunal species from 4 phyla and  only 23  saltwater infaunal species
from 4 phyla.   Only 4 freshwater  infaunal species  and 16  freshwater  epibenthic
species  and 3  saltwater  infaunal  species and 5  saltwater epibenthic  species
have been  tested with 5 or more  of  the 30 water  quality  criteria  substances.
In  spite of  the paucity  of  acute  toxicological data  on  benthic  species,
available data  suggests their sensitivities  are  sufficiently  similar  to  those
of  water column species and  that sediment quality  criteria  could be  derived
from water  quality criteria.

    Based  on  the results  described  in this   section  it  is concluded  that  the
sensitivities  of benthic  species  are  sufficiently similar to those of  water
column species  to tentatively permit the  use  of water quality  criteria for the
derivation of sediment   quality criteria   in  the   equilibrium  partitioning
approach.   The acute  toxicity  data  base derived from 36  freshwater and  30
saltwater  water quality criteria  documents  suggests  that the most sensitive
infaunal  species is  typically less sensitive  than  the  most sensitive  water
column  (epibenthic  and  water  column)  species.    When both infaunal and
epibenthic  species  are  classed  as  "benthic,"  the sensitivities  of the  most
sensitive  benthic  and water  column  species are  similar,   on  average.    A
comparison  of  the frequency distributions of the  sensitivities of all  benthic
versus all  water column species indicates that water  column species may be only
slightly more  sensitive  than  benthic  species.   Finally,  in experiments  to

-------
                                                                      Page  5-17

determine  the effects  of  substances on  colonization  of benthic  saltwater
organisms,  concentrations affecting colonization  were  always greater than  the
five estimated or  actual FCVs for saltwater  organisms water quality criteria
documents.    Concentrations  not  affecting  colonization were  similar to final
chronic values for the three substances where  data are  available.

-------
                                                                       Page 6-1
                                  SECTION 6.
                     APPROACH FOR DEVELOPMENT OF SEDIMENT
                         QUALITY CRITERIA FOR METALS
    The rationale for  establishing  sediment  quality criteria for toxic  metals
is similar to that developed for non-ionic organic  chemicals.  The bioavailable
fraction is  identified and  a partitioning model will be investigated in order
to predict the bioavailable  fraction.

6.1  THE PROBLEM

    The equilibrium partitioning methodology for establishing sediment quality
criteria requires  that the  chemical potential  of  the chemical  be determined.
The experimental results presented in Section 3 (Figure 3-4) suggest that pore
water concentrations of metals as well  as  non-ionic organic chemicals correlate
to  biological  effects.    Based on  this observation a  direct approach  to
establishing sediment quality  criteria  for metals  would be to apply the water
quality criteria to measured pore water concentrations.   The validity of this
approach depends  on the degree  to  which pore  water concentration represents
free metal activity.  Some metals readily  bind to DOC,  and DOC complexes  do not
appear to be bioavailable.    Hence, for  metals with  significant DOC 'complexing,
the direct use of pore water concentration is precluded in the same way  as for
non-ionic organics with DOC  complexing  (Section  4.4).

    By inference  this  effect of complexation on metal bioavailability extends
to any complexing ligand that  is present  in sufficient quantity.   The decay of
sediment organic  matter can  cause  substantial  changes  in  interstitial  water
chemistry  (e.g.,  Berner,   1980).   In  particular,  bicarbonate  concentration
increases  due  to  sulfate   reduction  complicate  the  determination of  the
bioavailable specie(s)  because  it can  result in increases  in the  metal-
carbonate complexes.

-------
Page 6-2

    To  implement the  equilibrium  partitioning approach  to  setting  sediment
criteria for metals, pore water concentrations must be measured.  However,  the
sampling of sediment interstitial water for metals is not  a routine procedure.
The least  invasive  technique employs  a diffusion sampler which has  cavities
covered  with a  filter membrane  (Hesslein,  1976; Carignan  et  al.,  1984  and
1985).   The  sampler  is  inserted  into  the  sediment  for a  period  of time
sufficient  to allow  the concentrations on  either  side  of  the  membrane to
equilibrate.  when  the sampler is  removed the  cavities contain filtered pore
water  samples.    Use  of  this  technique requires  that  the time required  for
equilibration be determined.

    The alternate technique is to obtain a sediment core,  slice  it, and  filter
or centrifuge the slice to separate  the pore water  from  the bulk  sediment.   For
anaerobic sediments this  must be  done  in a nitrogen  atmosphere to prevent  the
precipitation of iron hydroxide which would  scavenge the  metals  and yield
artificially low dissolved concentrations (Troup,  1974).

    Although either  of  these   techniques  are   suitable  for  research
investigations  they  require  more than  the normally  available  sampling  skills
and time.   If solid phase chemical  measurements were  available from which pore
water metal activity could be deduced,  it would  obviate  the need  for pore water
sampling and analysis, and it would  circumvent the  need  to  deal with complexing
ligands.

6.2  TOXICITY CORRELATES TO METAL ACTIVITY

         The  results  from  a substantial  number  of  water column experiments
indicate that  biological effects  can  be  correlated  to  the  divalent metal
activity [Me2+].  This is not meant  to  imply  that  the  only  bioavailable form is
Me2*  (for  example MeOH+  may  also be bioavailable), but  rather  that the DOC or
other  ligand complexed fractions are not bioavailable.   Data  to support this
are discussed below.

-------
                                                                       Page 6-3

    The  acute toxicity of  cadmium  to  grass  shrimp (Palaemonetes)  has been
determined at various concentrations of the complexing agents chloride and NTA,
both of  which form  cadmium complexes  (Sunda et al., 1978).   The results are
shown on Figure  6-1.    The  top panels are concentration-response curves as a
function of total cadmium.  The responses differ at different concentrations of
chloride,  indexed  by salinity,  and NT A.   When the  concentration-response is
evaluated with respect to Cd2+ activity in the solution,  then the dose response
curves collapse  into  a  single  curve  (bottom  panels).  Comparable results have
been reported for  copper-EDTA  complexes  (Anderson and Morel,  1978)  for which
dose response correlates to Cu2+ activity (Figure 6-2, left).

    Chronic toxicity, with growth as the endpoint,  has also been examined.  The
results  of an  experiment  in  which  the concentration  of  Cu  and Zn is  held
constant  and  the complexing ligand is varied are  shown on  Figure 6-2 (right)
(Allen et al.,   1980).   As NTA  is  added the  toxicity of zinc  to Microcvstis
decreases:    the cell  density  increases rather  than  decreases in  time  and
reaches  control  levels  at  the  highest NTA concentration  (top panel).   These
data can be correlated  to  free  zinc activity  as shown (bottom panel).   Similar
results  for  copper  and the complexing  ligand  tris  are shown on Figure  6-3
(left) (Sunda and  Guillard, 1976).   Variations in tris concentrations  and pH
produce  markedly different growth  rates  (top)  which can all be  correlated to
the Cu2+ activity  (bottom).  Similar  results have been obtained  by  Sunda  and
Lewis (1978) with DOC as the complexing ligand, Figure 6-3 (right).

    Metal bioavailability  as measured by organism uptake  is also related' to
metal ion activity.   Uptake of  copper by oysters  (Zamuda and  Sunda,  1982)  is
correlated not  to  total copper concentration  (Figure  6-4, top),  bur  to  copper
activity (bottom).

    The  conclusion to be  drawn  from these experiments is that the partitioning
model required for establishing sediment quality criteria should predict  [Me?*]
in  the  pore  water.   The  next section discusses  one  possible approach  to
developing such  a partitioning model.

-------
            ACUTE TOXICITYOF CADMIUM TO
             GRASS SHRIMP ( Polaemonetes )
             EFFECT OF NTA COMPLEXATION

               (AFTER W.6. SUNOA et al., 1978 )
                                                                ACUTE TOXICITYOF CADMIUM TO
                                                                 GRASS SHRIMP (Palaemonetet )
                                                                     EFFECT OF SALINITY

                                                                  (AFTER W.6. SUNDA etol., 1978 )
S
                                                            10-
                   TOTAL CADMIUM ( -toe C«f )
                                         4.0
                                                                  A	A 4.1*0.4
                                                                  •	• I 410 1
                                                                  »	»I4 J^O J
                                                                  •	•lOOtO.l
                                                                           TOTAL CADMIUM (-LOO C«r I
 >
 •
 3
 •-
    to
*o •
 m   40 •
              40
              CADMIUM ACTIVITY
                                        7.0




4 *°
2
>
•
2 40
1-
m
u
S 40
&
10

I.I-,fT (X.I
A4J » * « 	 *-* 	 »
• i.4 ^x- "^"
^ ^ ^
• 200 ,• 4>
4>2i.t '
/
"I

/*

• •* • /
	 " * - ' fc tf)^ 	 ,
                                                                         CADMIUM ACTIVITY l»[c«*+])
                      FIGURE 6-1.  Acute toxlclty to Palaemonetes of total cadmium (top) arid cadmium
                      activity  (bottom)  with different concentrations  of the complexing  agents NTA
                      (left) and chloride as salinity (right).

-------
         ACUTE TOXICITY OF COPPER
            TO A  DINOFLAGELLATE

      (FROM ANDERSON AND MOREL. 1978)
CHRONIC TOXICITY OF ZINC
ON MICRO'CYSTIS AERU6INOSA

  (FROM ALLEN, et.al., 1980)
              56    T    B     9

              TOTAL COPPER (-LOG(CuT) 1
                       to
                                                                    o-CMOS
                                                                     -Builder M
                                                                    •-Control
                 10   II    12    13
                COPPER ACTIVITY (pCu)
 T	I—
 1.0  2.0   JO   4.0   1.0
    Fro* Zinc (molet/lit«r HO7)
FTC           Acute  toxicity  to a dlnoflagellate (left) of total copper  (top)
and copper activity (bottom),  with and without  EDTA.   Chronic  toxicity  of zinc
to Mtcroevstis ^rueinosa (right) showing growth as cells/ml versus  time  with
different levels of EDTA and  NTA (top)  and  number  of  cells at five  days
function of free zinc  concentration  (bottom).

-------
                 CHRONIC TOXICITY OF COPPER

                 	TO A DIATOM	




                (FROM SUNDA AND 6UILLARD, 1976)
                 CHRONIC  TOXICITY OF COPPER

                   TO MONOCHRYSIS LUTHEHI

                 (FROM SUNDA AND LEWIS. 1978)
S
Q-
M
          «3U
          ss.
                                                               2.00
                    TOTAL COPPER (-L06 CuT)
go  1-00

taut
 H
u>

•.a
                                                    -T4
                                                               0.00
                                                                 4.00
                                                                        lOt HIVEH HATCH


                                                                        301 RIVER MATER


                                                                        901 RIVER MATER
                      S.OO            6.00


                     TOTAL COPPER  (-log CuT)
                                                                                                               7.00
U


to




0
j, \±
.|,|. -
1
li
1 lrf*T=E:~
-*H4*f*~
1
+
4-
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~1
•
e.uu
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Ui
si
is '•°°
UIA
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• 10* RIVER MATER
• Ml RIVER MATER
* MB RIVER MATER

	 	 •
• -"^
•
/
/
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^^.m^
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                      COPPER ACTIVITY 
-------
              UPTAKE OF COPPER BY OYSTERS


              ISOi	—_____
              .00
           >
           *•
         w v
         K 9
         U U


         IS
         U
               0--

               0.01
   0.1          1.0



TOTAL COPPER CONC. { M M )
          i
                                    10        11



                         COPPER ACTIVITY (pCu)
               AFTER CD. ZAMUDA AND W.6. SUNDA

               USING (Crassostreo virginco), 1962
10.0

200

180

160

140
120

100
60
40
20
0
TOTAL NTA
Winter
A 1.0
610.0
Summer
A 1.0
• 8.1
• 10.0
m
T I
•
I 1
1 *
.
- ii
1
i \,f.
1 *~
(uM)













-\
             Body  burden of copper in oysters  versus total copper (top)  and
copper activity (bottom) with different levels of the complexing  ligand NTA.

-------
Page 6-8

6.3  METAL SORPTION MODELS

    The state-of-the-art  of modeling metal  sorption  to oxides  in laboratory
systems is  well developed  and detailed models  are  available for  cation and
anion sorption  (refer to  articles  in  Stumm,  1987,  for recent summaries).   The
models  consider  surface  complexation  reactions  as  well  as  electrical
interactions  via models  of the double  layer.   Models  for natural  soil and
sediment  particles are  less  well developed.   However,  recent applications
suggest  that similar  models  can  be applied to  soil systems  (Goldberg and
Sposito,  1984;  Barrow,  1986a,b; Barrow and  Ellis,  1986a,b;  Sposito  et  al.,
1988).   Since  the  ability to  predict  partition coefficients is  required  if
pore  water  metal  ion  concentrations   are   to  be inferred from the  total
concentration, a theoretically based model that is relatively easy to apply  in
practice  is  required.  An approach is presented  which uses the  three sorption
phases in aerobic sediments.

6.3.1    Three Phase Metal Sorption Model

    The initial  difficulty  that one confronts  in using a  metal  sorption model
is  that the  available models  are quite  complex and many of the  parameters are
specific  to  individual  soils or sediments.   However, the  success  of organic
carbon  based non-ionic  chemical  sorption models  suggests  that  a  model  of
intermediate complexity  that is  based  on an identification  of  the  most
important sorption phases  may  be  generally  applicable to metal  sorption  as
well.

    A start  in this direction was made recently (Di Toro et al..  1987; Jenne  et
al., 1986).   Instead of considering only one sorption phase, as  is assumed for
non-ionic  hydrophobic   chemical  sorption,  multiple sorption  phases are
considered.   In  oxic soils  and  freshwater sediments these  sorption phases  have
been  identified as  POC  and  the  oxides of  iron and manganese  (Jenne,  1968;
Jenne,  1977;  Luoma  and Bryan,  1981; Oakley et al.,  1980).   They are important
because of  their large  sorptive capacity.  Further they appear  as  coatings  on

-------
                                                                       Page 6-9

the particles and  occlude  the other mineral components.   These phases provide
the primary  sites  for  sorption  of. metals and  restrict the importance  of the
clay and  other  mineral components of  soils  and sediments.  For more reducing
sediments, sulfide precipitation may .also be important.

    The following  discussion  is  restricted to aerobic  sediments.   Let [FeOx],
[MnOx] ,  and  [POC]  be  the concentration of  solid phase reactive  iron and
manganese  oxides,   and POC,  respectively.   Define the  mass   action sorption
coefficients for the divalent metal cation, Me2+, as:

                [Me-FeOx]
         KFe - - 2T -                                               (6'1}
               [Me  ][FeOx]

                [Me-MnOx]
         KMH * - T+ -                                               <6'2>
               [Me* ] [MnOx]

                [Me-POC]
        K_.r -- 57 -                                                (6-3)
         POC   [Me*+][POC]

where  [Me2+]  is the metal  activity,  and [Me-FeOx] ,  [Me-MnOx] ,  [Me-POC] are the
concentrations of metal sorbed to iron and manganese oxide, and POC.

    In order  to examine the importance of pore  water  ligand complexation,  let
[Li],  [L2l,...  be  the concentration  of  complexing ligands  (e.g.,  OH* ,  Cl~ ,
DOC) .  The  mass balance equation for the total  metal  in both  the  sediment and
pore water is:

          NeT - (1 - 4)([Me-FeOx] + [Me -MnOx]  + [Me-POC])
                             [MeL1] + [MeLg]  + ...)                        (6-4)

-------
Page 6-10

where Me?  is  the concentration of total desorbable  metal per unit bulk volume
of sediment, and 0 is the porosity of the sediment.

    The key observation  is  that the  absolute quantity  of metal  in  the pore
water (the second line of Equation 6-4), is negligible relative to  the quantity
of  sorbed metal (the  first line).   The  mass balance  equation  can  then be
simplified to:

         MeT - (1 - 0)([Me-FeOx] + [Me-MnOx] +  [Me-POC])                  (6-5)


Using the equilibrium Equations (6-1) to (6-3) yields:

          MeT -  (1 - *)[Me2+](KFe[FeOx] + ^[MnOx] + K^IPOC])          (6-6)


so that:
            2+    	f	
          IMe  ] ' KFe[FeOx] + K^tMnOx] + Kp()C[POC]                       (6'7)
where  Hes  - Hef/(l-^)  is  the total  sorbed  metal per  unit  dry weight  of
sediment.

    It  is  important to realize that Equation (6-7)  gives  the  pore water metal
activity directly in readily measurable quantities:  the total desorbable metal
Mes,  and the sorption  phase concentrations  [FeOx],  [MnOx],  and  [POCj.   Pore
water complexing  ligand concentrations  do  not affect the partitioning Equation
(6-7)  for  exactly  the  same reason that DOC  concentrations do not  affect the
validity of organic carbon normalization for non-ionic  organic  chemicals.   Of
course  the metal sorption  constants:  Kpe, K^n,  and KPQC. are  also required.
The  practical  utility  of  this three  phase  sorption  model  depends upon the

-------
                                                                     Page 6-11

availability of  these  coefficients  and either  their  relative independence of
the details of the remaining sediment chemical and physical properties, or the
existence of suitable correlations ' which relate these coefficients to sediment
properties .

    It  is known  that  the  interstitial  water pH  will  affect the  sorption
constants.  This is conventionally modeled by including the species MeOH+ as a
sorbed  species  as well.   The  result  is that  the sorption constants  are
replaced by expressions of the  form:
          KFe -   e  +KFe[OHl                                          (6'8)
The utility of these models will be  examined below.

6.4  EXTRACTION AND PHASE NORMALIZATION

    In  addition  to  the sorption  phase concentrations  it  is  necessary  to
quantify  the  fraction of total  sediment metal  that  is  chemically interacting
with the  pore water.   The modeling of metal  partitioning  involves  not  only a
determination of the principal sorption phases, but also. a determination of the
corresponding chemical  extraction technique  to be  applied to  the  sediment
sample.   It  would be  convenient  if the same extraction  could be used  to
determine both  the  desorbable metal  and the  phase  concentrations.    This
possibility is examined below.

6.4.1     Bioavailable Fraction

    A  substantial  effort has  been  expended over the  years in  attempting  to
determine the bioavailable portion  of  trace  metals  in soils  and sediments
using chemical extractions (refer to Jenne, 1987 [SCD 13]),  for a review.   The
use  of  a relatively mild  reductant  (hydroxylamine  hydrochloride) which
dissolves the Fe  and  Mn oxides and liberates  the sorbed metals is recommended
(Jenne, 1987).

-------
Page 6-12

    The reported results using this procedure have been very encouraging.  An
example is shown  on  Figure 6-5 (Te.ssier et al.,  1984).   The copper and zinc
body burden  in Elliptic complanata.  a sediment  dwelling mollusc,  roughly
correlates with   the  total metal  in  the  sediment  (top  panels) .    The
relationship  greatly  improves  when the  ratio  of metal  to iron  in  a
hydroxylamine  extract is used (bottom panel).  Similar results, using an acid
extraction,   have been found for  arsenic  in  Nereis,  a  deposit  feeding
polychaete. and Macoma.  a deposit-feeding bivalve  (Langston, 1980); and copper
in  aquatic plants  (Campbell et  al.,  1985).   For  mercury  body burdens in
various  benthic  species  a  strong  correlation exists  between  the  sediment
concentration normalized by organic matter content (Langston,  1986).

    The  success   of these  extraction-normalization  procedures  can  be
rationalized as follows.  Assume that  the primary sorption phase for a metal,
He, is amorphous iron.  Then the extraction, which only dissolves  the amorphous
iron coating, removes only  that quantity of Me and Fe in  equilibrium with the
interstitial water.  Further, it follows from Equation  (6-7) that the ratio of
Me/Fe  in  the extract   (i.e.,  Mes/[FeOx]),  would  be  proportional  to  the
interstitial water concentration of the metal:
                     Me
 From  the  data presented in Section 6.2, the  interstitial water  concentration
 appears to correlate to toxicity and bioaccumulation.  Thus the fact that body
 burden is proportional to the  phase-normalized metal concentration supports its
 use for predicting interstitial water metal activity.

 6.4.2    Partition Coefficients

    The most  direct  evidence  in support of the use of the extraction - phase
 normalization procedure comes from simultaneous observations of the oxic layer

-------
                       SEDIMENT BOUND METAL
                         UPTAKE BY MOLLUSCS
                          (TESSIERet ol., 1984)
 K
 UJ
 Q.
 Q.
 O
 U
    IOO
    80
60
40
    20
                     TOTAL SEDIMENT METAL

                                  500
          * 0.63
             I
               I
   400


   300
o

S  200


    IOO
                                        R2= 0.53
            I
I
I
I
            50    IOO   ISO   200
              Cu(/tg/g)
                                          IOO  200  300 400  500
                                             Zn ('/i,g /g)
UJ
o
(E
CD
£ loo
o
0 80
£ 60
a
a.
0 40
20
0

EXTRACTE
R2* 0.96 /
/
(D/®


/^
X®
^
1 1 1 1
                                  500


                                  400


                                  300


                                  200


                                   IOO


                                    0
                                            R2= 0.71
                                              I
                                              I
                       I
           I
            3   6    9    12
              Cu/Fe (mg/g)
                          IS
           10  20  30  40  50  60
             Zn/Fe(m /g)
FIGURE 6-S.   Copper  (left)  and zinc  (right)  body burdens in molluscs versus
total sediment metal concentration (top) and extracted metal/Fe ratio (bottom;.

-------
Page 6-14

interstitial water,  and sediment metal  concentrations.    Initial  data of  this
type for metals  with small DOC complexing capacity  (Tessier et al. ,  1985) and
more recent results  (Tessier,  personal communication) demonstrate its utility.
Figure 6-6 presents  the  relationship of the  observed nickel and zinc partition
coefficient, KA, versus pH where:

               [Me-FeOx]
         KA - 	JT                                               (6-10)
              [FeOx][Me/+]


[Me-FeOx] and [FeOx]  are  the  extracted Me and Fe concentrations,  and [Me2+] is
the estimated aqueous nickel  and  zinc  activity.   The linear relationship to pH
can be used  to predict  interstitial  water metal  concentrations in  the  oxic
layer of sediments given the extraction data and pH.  This is a one-phase model
of sediment sorption.  Some of the remaining scatter in the relationship may be
related to the  presence of  other  sorption phases such as amorphous Mn and POC.
Similar  results have  been obtained  for the  sorption of  copper and  zinc to
suspended solids in streams (Johnson, 1986).

6.5  DEVELOPMENT OF SEDIMENT QUALITY CRITERIA FOR METALS

    The solution to  the bioavailability problem  for sediment associated metals
is more  complex than for  non-ionic organic chemicals.   The  requirements for a
methodology based on equilibrium partitioning are an extraction methodology and
a multiple phase sorption model.  Initial steps have been taken to evaluate the
state-of-the-art of each of these components.

6.5.1     Extraction Methodology

    The selection of  an appropriate  extraction methodology that quantifies the
portion of the  total sediment metal that is chemically reactive with respect to
pore  water  has been made  (Jenne,  1987  [SCD  13]).    In addition a  series of
experiments have been performed that examine the details of the method and make

-------
                          Zn
     lo« *o» -33* l.3pH
      Tessier. 1987
60 -
                                  7
SO
4.0-
              /•
                     /
                            t
 3.0
       |

./
     /
    /
Z0\
                                     '  /
                       «0
                     pH
                                    ..7.0
:  A -02
MA-OI
MC-OI
:CH- 01
 SW-OI
: L8 - Ol
:  H-OI
BC-OI
•CC-05
:BC-03
:BR-OI
:8R-04
:  J-Oi
it*-02
:TA-OI
                                          CI.-OI
                                         : WI-OI
                                          uc-oi
                                          HE 01
                                          BR 01
                                         : 80-01
                                         :MO-OI
                                                   80
                                                               7.0
                                                                                         Ni
                                                               6.0
                                                               S.O
                                                            .2  40
                                                               SO -
                                                               20
                                                                      log Ko ••2,5+ 1.1 PH
                                                                     Tessier. 1987

                                                                                            V
                                                                                     x      •
                                                                                                        .
                                                                                                      X
                                                                                     4
                                                                             4
                                                                        S.O
                                                                                      6.O
                                                                                       PH
                                                                                                     70
                                                                                                            : *-OI
                                                                                                            . *-02
                                                                                                            MA-OI
                                                                                                            :ME-OI
                                                                                                            :CH-OI
                                                                                                            CE-05
                                                                                                            :CL-03
                                                                                                            :CL-OI
                                                                                                            WI-OI
                                                                                                            MC-OI
                                                                                                            :NC-OI
                                                                                                            BR-OI
                                                                                                            :MO-OI
                                                                                                                   a.o
                FIQURE
                             Zinc  (left)  and nickel  (right)  partition coefficients versus pH in
                comparison  to  a single phase model of sediment  sorption (dashed  line).

-------
Page 6-16

final recommendations with respect to experimental protocol  (Crecelius et  al.,
1987 [SCO 16]).

6.5.2    Sorption Model

    The practical utility of  the  three  phase model of metal sorption rests on
the availability of reasonably universal phase-specific  sorption constants.  As
an  initial  screening exercise,  reviews were  prepared of  the  available
literature information  for  POC (Allen  and Mazzacone,  1987  [SCO  9])  and  iron
oxides (Jenne,  1987  [SCO  12]).   The  tabulations for POC protonation and metal
binding reactions show order of magnitude consistency with  occasional outliers.
The major difficulty is the lack of a consistent model with which the data can
be  interpreted.    As  a  consequence,  the  degree of  consistency cannot be
established.

    The review by Jenne (1987), of sorption constants for  iron oxide indicated
some degree of  consistency  but also  some widely variable constants.  However,
it has been shown that a universal set  of  constants can produce a credible fit
of almost all iron oxide protonation  and sorption data (Dzombak, 1986).

6.6  ONGOING STUDIES

    Additional studies are planned or are  currently being conducted to gain an
improved understanding of the fate and  toxicity of metals  in sediments.   These
efforts are described subsequently.

6.6.1    Sediment Toxicitv Experiments

    Very few metal  toxicity experiments have been conducted for which the pore
water  metals concentration has been  measured.    The  two cadmium  -  seawater
experiments  discussed  above  (Figure  6-1) are the  extent of  the laboratory
toxicity data that  support  the contention that pore water metal concentration
(actually metal activity)  correlates  to  toxicity.   Ongoing  experiments

-------
                                                                      Page  6-17

utilizing  diffusion  samplers and  specific  ion  electrode  determinations of
cadmium and  subsequently  copper activity are planned  for both freshwater and
marine sediments in order to examine this question.

6.6.2    Metal Partitioning

    The  development  of  a three  phase partitioning  model  requires  the
generation of  a reasonably large sorption data base with both extraction and
pore water sampling.   The  use of laboratory and field data sets is envisioned
with  an emphasis  on  the  latter if  possible.   Laboratory  investigations of
amorphous  manganese oxide  are  ongoing  in  order  to compliment  the  available
iron oxide data.  Detailed  base  titration data for sediment organic carbon are
being  generated and early  indications  are  that a  consistent set  of model
parameters can  describe  the results.   Titrations  of sediment samples are also
proceeding.  Field data collection programs  are being discussed as well.

6.6.3    Sulfide Precipitation

    Recent  experimental  work  has  reinforced  the  importance  of  sulfide
precipitation  as  a sink for  metals in marine and  even freshwater sediments.
The dramatic difference  in the  toxicity of the two  sediments  shown on Figure
3-4 has been tentatively attributed to the presence of  acid volatile sulfide in
the Long Island Sound  sediment and  not in the sandy oxic Yaquina Bay  sediment.
The sulfide precipitates the cadmium as cadmium sulfide which appears  not to be
bioavailable.   It is only when the  available sulfide is exhausted that cadmium
toxicity is  exhibited.  This  first  order effect will be examined in detail for
both marine  and freshwater sediments.

6.7  CONCLUSION

    This section examines  the use of the equilibrium partitioning approach in
the development of  sediment quality criteria for metals.  It is shown that the
activity  of  metals must  be determined in order  to  properly  quantify  the
bioavailable  concentration.   A  three  phase  metal  sorption model was  presented

-------
Page 6-18

as a means to determine metal activity  in  pore  waters  and was used to estimate
the bioavailable  fraction  of .metals.   Preliminary results  suggest  that  the
extraction partitioning methodology can be used to establish metals criteria in
a way that directly addresses bioavailability.  Ongoing work being conducted to
gain an improved understanding of  the factors affecting the toxicity of metals
in sediments was described.

-------
                                                                       Page 7-1
                                  SECTION 7.

                   GENERATION OF SEDIMENT QUALITY CRITERIA

    The approaches for development of sediment  quality  criteria were developed
in Section 4 for non-ionic organic chemicals and in Section  6  for metals.   The
technical evidence indicates  that  sediment quality criteria can  be  determined
and in this section preliminary sediment quality criteria for organic chemicals
are presented.   The uncertainty associated with calculation of sediment quality
criteria is addressed prior to providing the  sediment  quality criteria values.

7.1  METHOD TO CALCULATE SEDIMENT QUALITY CRITERIA UNCERTAINTY

    The sediment quality  criteria  methodology  relies  on an empirical  model  to
compute the interstitial water concentration (actually  the chemical  potential)
from the  solid phase measurements.  As  a  consequence there  is an uncertainty
associated with  the  use  of the model.   In addition there is uncertainty with
respect  to the  Kow associated with  the specific  chemical  since  it is  an
experimentally determined quantity.  Finally, the assumption that water column
and benthic organisms have similar sensitivities has a level  of  uncertainty.

    The equation from which sediment quality  criteria  are calculated  is:

          rSQC' KocCBQC                                                   (7-L)

where  cgqc  is  the effects  concentration for benthic species.   A first  order
uncertainty analysis of rgqc  can be  computed  from   the  variance  of this
equation:

                                           CBQCJ                         (7'2)

-------
Page 7-2

where the notation V{z) denotes the variance of z.   The  variance  of KQC can be
obtained from the uncertainty of the regression that relates Koc to Kow.  If it
is assumed that Kow is known exactly  then  the  variance of KQC  can be estimated
from the nonlinear regression  fit.   However,  since KQW  is not  known exactly -
and for high Kow chemicals the estimates can vary  over an order of magnitude -
the  uncertainty of Kow  must  be  explicitly included  in  the  analysis.   This
uncertainty analysis  has  not yet  been  performed.   Further,  the variance
associated  with  the assumption that  benthic  and  water  column species
sensitivities are equal:  CBQC ~ CWQC.  is required.

    An initial analysis of the uncertainty has  been made  for the Koc regression
(Pavlou et al.,  1987;  SCD  14).  However the problem of  uncertainty  in  Kow has
not been included in the regression uncertainty analysis.

    For the  generation of  interim  sediment criteria  values  (Cowan  and Di  Toro,
1988, SCD 17), the sediment quality criteria formula used is:
          rSQC ' KocCWQC
or in logarithmic form:

          1°S
-------
                                                                       Page 7-3

uncertainty in log Kow itself.  The uncertainty of the equality of water column
and  benthic  species  sensitivity  was not included  in this  preliminary
uncertainty analysis.  The  resulting  confidence  limits  are included in Section
7.2.   The range  in uncertainty that results is  quite  large with  95  percent
confidence limits spanning  roughly an order  of magnitude.   This  is primarily a
result  of the  rather  large regression standard  error:  SE  (log Kp) -  0.38
reported previously (Di Toro, 1985).   However, this regression analysis assumed
that all KQWS were  precisely known.   That assumption artificially  inflated the
regression variance since that lack of fit which may be  due to an uncertain Kow
is attributed to regression error.   The solution to this problem is to redo the
regression analysis with  the uncertainty of  KQW  explicitly included.   Thus the
confidence limits of  the  interim criteria are conservative and  a  more  refined
analysis will reduce the uncertainty range.

7.2  PRELIMINARY SEDIMENT QUALITY CRITERIA VALUES
     FOR NON-IONIC ORGANIC CHEMICALS

    An  initial  attempt to  compute sediment  quality criteria for  13  non-ionic
organic chemicals is presented.  The  95  percent  confidence limits  are computed
from  a method  which is  known to   exaggerate  the  uncertainty.    For these
chemicals, where either field data derived  lower bounds  or  sediment toxicity
experiments are  available,  the results seem reasonable.

    The  procedure  followed  for the  computation  of interim sediment  quality
criteria  is presented  in  SCO 17.  The purpose of  this section is  to  present  a
summary analysis of the  results and  to  compare  them to  SLCs where  possible.
Table  7-1 presents  the sediment quality criteria  and SLC values  based on the
FCV and final  residue value  (FRV)  water  quality criteria.  The  freshwater and
saltwater  sediment  quality  criteria  results are  listed  together  with the  95
percent confidence  limits.   The  quantification of  the level of uncertainty has
only been accomplished in a  preliminary way.   It is anticipated that a complete
uncertainty analysis  will accompany  the  final development  of  sediment  quality
criteria  and that,  for example,  95 percent confidence limits  will  be specified
as well as the most probable  value.

-------
OJ
OQ
a
TABLE 7-1. COMPARISON OF INTERIM SEDIMENT QUALITY CRITERIA WITH SCREENING LEVEL CRITERIA (SLC) ^
I
*•
Interim Sediment Quality Criteria (lig/R OC)
Freshwater or
Saltwater
F or S
PAHs:
Acenapthene
Anilene
Fhenanthrene
Other
PESTICIDES:
Chlordane
Chlorpyrifoa
DDT
Dieldrln
Endrin
Ethyl Parathlon
Beptachlor
Heptachlor Ep
Llndane
OTHER:
PCB
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
F
S
Residue Basis
Median 951 Confidence Limits
-
-
-
-
-
0.828 .183 - 3.80
0.828 .183 - 3.80
0.130 .00976 - 1.79
0.130 .00976 - 1.79
0.0532 .0065* - 0.443
0.0532 .00654 - 0.443
-
0.110 .0148 - 0.840
0.104 .0140 - 0.796
-
-
19.5 3.87 - 99.9
41.8 6.29 - 214.
Chronic Effect Basis SLC (UB/K OC)
Median 9SX Confidence Limits Median
730. 180. - 3030.
4.74
O.OB62 0.0169 - 0.262
0.248 0.0635 - 0.984
139. 32.6 - 605.
102. 23.8 - 442. 36.8
10.1 - 66.5
' .098
3.22 0.831 - 12.7
0.440 0.114 - 1.73
.190
SO. 5
19.9 1.49 - 273. .021
5.77 0.431 - 79.2
1.04 0.128 - 8.68
0.215 0.0264 - 1.79
0.081 0.016 - 0.416
-
.008
0.157 0.0394 - 0.636
.290
3.66

-------
                                                                       Page 7-5

    The differences between freshwater and saltwater sediment quality criterion
are a direct reflection of the differences in water  quality  criteria since the
partition  coefficient is not  significantly affected  by the  change in  ionic
strength.   The  range  in 95 percent confidence  limits  reflects  mainly  the
inflated regression uncertainty estimate  as discussed above.   The  comparison to
screening  level  criteria can  be made  in only  two cases using  chronic  data
(Table  7-1).  The  median saltwater chronic  sediment  quality  criteria  for
phenanthrene is  102 pg/gOC (23.8 -  442  /ig/gOC)  and the SLC is 36.8 ng/g  OC.
Since  the  lower  bound  of the 95 percent confidence  limits  (23.8  jig/gOC)  is
below  the  SLC  it  appears  that  the confidence  limits  range  perhaps  is  too
conservative.    In contrast, the median freshwater chronic sediment quality
criteria for dieldrin is  19.9 jig/g OC (1.49 - 273 pg/gOC) while the  freshwater
SLC  is only  0.021 pg/gOC.   The  low freshwater SLCs are  attributed  to  the
particular data base  that  was  assembled  (SCD 7).   If  the sediments  are
relatively uncontaminated then SLCs  are bound to  be  small numbers.

    A more detailed comparison of the available information for  fluoranthene is
presented  in  Table 7-2 using interstitial water concentrations.   The chronic
lowest observed  effect  level  (LOEL)  for  saltwater organisms  is 16 pg/L.   This
can be  compared  to the  range  of the pore  water concentrations from sediment
exposures associated with chronic responses:  8 to 26 pg/L.   The acute LOEL  (40
/ig/L) is also comparable to the acute mortality concentrations  (41 to 62 pg/L).

    A  similar  presentation  for  organic  carbon normalized  sediment
concentrations is  presented in Table  7-3.  The equilibrium partitioning values
corresponding to  the chronic  LOEL  is  1,330  /tg/gOC.   The screening  level
concentration (43  /Jg/gOC) is well below  that value.   The Amphipod AETs (on an
organic  carbon  normalized basis) are closer (160  and 891 /ig/gOC)  as  is  the
reported LC50  (817 pg/gOC).    The equilibrium partitioning  acute  LOEL (3,330
/jg/gOC) compares well with the available  acute sediment toxicity data (2,130 to
6,700  Mg/gOC).   It appears,  therefore,  from this  preliminary evaluation  that
equilibrium partitioning generated sediment quality  criteria  are reasonable  and
in conformity with  the available information.

-------
Page 7-6
        TABLE 7-2.  TABULATION OF FLUORANTHENE SEDIMENT TOXICITY RESULTS
                     PORE WATER CONCENTRATIONS AND EP VALUES
Fluoranthene
 Pore Water
Concentration
     62
     42
     41
     40

     26
     19
     16
     12
      8

aEagle Harbor
 Response
 Criterion

96 hr LC100
10 d LC100
10 d LC95
Acute LOEL

10 d LC50
96 hr LC65
Chronic LOEL
10 d LCOS
10 d LCO
     Exposure
      Medium
Interstitial water9
Sediment8
Sediment spike
Saltwater

Sediment spike
Interstitial watera
Saltwater
Sediment spike
Sedimenta
                                                              Reference
Swartz et al., 1989
Barrick et al.. 1986
Swartz et al., in prep.
USEPA, 1980
Swartz et al.
Swartz et al.
USEPA, 1980
Swartz et al.
in prep.
1989

in prep.
Barrick et al., 1986
        TABLE 7-3.  TABULATION OF FLUORANTHENE SEDIMENT TOXICITY RESULTS
                   ORGANIC CARBON NORMALIZATIONS  AND EP VALUES
Fluoranthene
Concentration
   (ae/g PC)

    6700
    3437

    3330
     2130
     1330
      891
      817
      160
       43
               Method
   LC100, Eagle Harbor Sediment
   LC95 Sediment spike

   Equilibrium partitioning,
     Acute LOEL

   LC50 Sediment spike

   Equilibrium partitioning,
     Chronic LOEL

   Araphipod AET II
   LCOS Sediment spike
   Araphipod AET I
   Screening Level Concentration
                              Reference
                      Barrick et al., 1986
                      Swartz et al.,  in prep.

                      USEPA, 1980
                      Swartz et al., in prep.

                      USEPA, 1980
                      Barrick et al.,  1986
                      Swartz et al., in prep.
                      Seller et al., 1986
                      Neff et al., 1986

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                                                                       Page 7-7

    The  interim residue  based  criteria  in Table  7-1  should be  used  with
caution.   The  problem is whether  the  water quality criteria concentration is
computed from  a bioconcentration  factor  (BCF)  - which  is  derived from  water
only exposure - or from a field BAF which incorporates  food  chain magnification
effects.   The  PCB and  DDT residue  criteria are  derived  from BCFs  and  are
therefore underprotective.

7.3  CONCLUSIONS

    The  technical basis  and  data which support  the  use  of  the equilibrium
partitioning method to generate sediment quality criteria have been previously
presented for  both non-ionic  organic  chemicals (Sections  3  and  4),  and  for
metals  (Section 6).    The  justification for using water quality  criteria  to
define the effects level for benthic organisms was also discussed  (Section 5).
This  section  presents preliminary sediment  quality  criteria  for 13 non-ionic
organic chemicals and  in cases where comparisons are made with screening  level
criteria, the sediment quality criteria appear reasonable.  The development  of
sediment quality  criteria for  metals  using  the  equilibrium  partitioning
approach also appears  to be  viable.   Additional work is required to develop a
reasonably large sorption data base, with both extraction and pore water  data,
prior to generating sediment quality criteria for metals.

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                                                                      Page 8-1
                                 SECTION 8.
                                 REFERENCES
SEDIMENT CRITERIA DOCUMENTS

SCD 0      Pavlou,  S.  P.  and D.  P. West on,  1983.  "Initial Evaluation of
           Alternatives  for  Development of  Sediment Related Criteria for Toxic
           Contaminants  In Marine Waters (Puget Sound)  -  Phase  I and Phase II."

SCD 1      JRB Associates,   1984.  "Background And  Review Document On  The
           Development Of Sediment Criteria."

SCD 2      Battelie,  1984. "Sediment Quality Criteria  Development Workshop."

SCD 3      Bolton, S. H., R.  J. Breteler, B. W. Vigon. J. A. Scanlon and S. L.
           Clark 1985. "National Perspective On Sediment  Quality."

SCD 4      Kadeg, R.  D. ,  S.  P.  Pavlou  and A.  S.  Duxbury,  1986.  "Sediment
           Criteria  Methodology Validation  Work  Assignment  37  Task  II
           Elaboration  Of  Sediment  Normalization  Theory For  Nonpolar
           Hydrophobic Organic Chemicals-Final Report."

SCD 5      Poston,  T.  M.  and L.  A.  Prohammer,  1986.  "Sediment Criteria
           Methodology  Validation  Work Assignment  56,  Task  1 Protocol  For
           Sediment Toxicity  Testing of Nonpolar Organic  Compounds."

SCD 6      Jenne. E.  A., D. M. Di Tore, H. E. Allen and C.  S. Zarba, June 1986.
           "An Activity Based  Model  for  Developing Sediment Criteria  for
           Metals, Part  I:  A New Approach."

SCD 7      Neff,  J.  M.,  D. J. Bean, B. W.  Cornaby, R.  M.  Vaga,  T. C. Gulbransen
           and J.  A. Scanlon,  1986. "Sediment  Quality Criteria  Methodology
           Validation:  Calculation  of  Screening  Level Concentrations  From
           Field Data."

           Neff,  J. M. .  J.  Q. Word and T.  C. Gulbransen, 1987. "Recalculation
           of Screening  Level Concentrations For Nonpolar Organic  Contaminants
           In Marine Sediments."

SCD 8      Cowan, C. E.  and  R. G.  Riley,  1987.  "Guidance  For  Sampling of  And
           Analyzing For Organic Contaminants On Sediments."

SCD 9      Allen, H. E.  and J. M. Mazzacone, 1987. "Sediment Quality Criteria
           For Metals:  III.   Review of Data on  the Complexation of  Trace
           Metals By Particulate Organic Carbon."

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Page 8-2


SCO 10     Cowan,  C.  E.  and  C. S.  Zarba,  1987.  "Regulatory Applications  of
           Sediment Quality Criteria - Final Report."

SCO 11     Word, J. Q.,  J.  A. Ward,  L.  M.  Franklin,  V.  I  Cullinan and S.  L.
           Kiesser, 1987.  "Evaluation of the  Equilibrium Partitioning Theory
           for Estimating the Toxicity of the   Nonpolar Organic  Compound DOT  to
           the Sediment Dwelling Amphipod Rhepoxynius  Abronius."

SCD 12     Jenne,  E.  A.,  1987.  "Sediment Quality  Criteria   For  Metals:   IV.
           Surface Complexation And Acidity Constants For Modeling  Cadmium and
           Zinc Adsorption onto Iron Oxides."

SCD 13     Jenne,  E.  A.,  1987. "Sediment  Quality Criteria For Metals:  II.
           Review  of  Methods  For Quantitative  Determination  of Important
           Adsorbents and Sorbed Metals In Sediments."

SCD 14     Pavlou, S.,  R. Kadeg, A.  Turner and M. Marchlik, 1987. "Sediment
           Quality  Criteria  Methodology Validation:   Uncertainty Analysis  of
           Sediment Normalization Theory For Nonpolar  Organic  Contaminants."

SCD 15     Kadeg, R. D. and S. P. Pavlou, November  1987.   "Reconnaissance Field
           Study  for  Verification  of  Equilibrium  Partitioning:   Nonpolar
           Hydrophobic Organic Chemicals."

SCD 16     Crecelius,  E.  A.,   E.  A.  Jenne and J.  S.   Anthony,  December 1987.
           "Sediment Quality Criteria  for  Metals:    V.    Optimization   of
           Extraction Methods  for  Determining  the  Quantity of  Sorbents  and
           Adsorbed Metals in Sediments."

SCD 17     Cowan,  C.  E.  and  D. M.  Di  Toro,   March  1988.   "Interim Sediment
           Criteria Values for Nonpolar Hydrophobic Organic Compounds."

OTHER REFERENCES

Adams, W. J., R. A. Kimerle and R.  G.  Mosher.   1983.   Aquatic  Safety Assessment
  of  Chemicals Sorbed  to Sediments.    Special Study  Report  No.  ES-EAG-83-1.
  Monsanto Company, Environmental Sciences Center,  St.  Louis,  Missouri.

Adams.  W.  J.,  R.  A.  Kimerle  and  R.  G.  Mosher.   1985.   "Aquatic  Safety
  Assessment  of Chemicals Sorbed to  Sediments."   In:  Aquatic  Toxicology  and
  Hazard  Assessment:  Seventh  Symposium,  pp. 429-453.  Editors: R.  D. Cardwell,
  R. Purdy and R. C. Banner.  Am. Soc. for Testing  and Materials,  Philadelphia,
  Pennsylvania.

Adams, W.  J.   1987.    "Bioavailability of Neutral Lipophilic Organic Chemicals
  Contained  in Sediments:"  A  Review.  In: Fate and Effects  of Sediment-Bound
  Chemicals  in Aquatic Systems, pp.  219-244.   Editors: K. L.  Dickson,  A.  W.
  Maki and W. A. Brungs.  Pergamon Press, New York, New York.

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                                                                       Page 8-3


Allen, H. E.,  R. H. Hall and T. D. Brisbin.   1980.   "Metal Speciation.   Effects
  on Aquatic Toxicity."  Environ. Sci.  Technol.  14:  pp.  441- 443.

Allen, H. E. and J. M. Mazzacone, January 1987.  "Sediment Quality Criteria For
  Metals:  III.    Review of  Data  on  the  Complexation  of Trace  Metals  By
  Particulate Organic Carbon." Prepared for USEPA,  Office of Water Regulations
  and Standards, Criteria and Standards Division. (SCD 9)

Anderson, D. M.  and F. M. M.  Morel.   1978.   "Copper Sensitivity  of Ganyaulax
  tamarensis."  Limnol. Oceanogr. 23:  pp.  283-295.

Barrick, R. C., D.  S. Becker,  D.  P. Weston and  T. C.  Ginn.   1985.  Commencement
  Bay Nearshore/tideflats Remedial  Investigation.   Final Report.   Prepared by
  Tetra  Tech,  Inc. for  the Washington Department of Ecology and the US  EPA.
  EPA-910/9-85-134b.  Tetra Tech, Inc., Bellevue, Washington.

Barrick, R.C., H.  R.  Beller and M.  Meredith.   1986.  Eagle Harbor Preliminary
  Investigations.   Final  Report  EGHB-2,  TC-3025-03.    Tetra  Tech,  Inc.,
  Bellevue. Washington.  192 p.

Barrow,  N.  J.   1986a.   "Testing a Mechanistic Model.   I.    The Effects of  Time
  and Temperature on the Reaction of Fluride  and Molybdate with a  Soil."  J.  of
  Soil Science 37: pp. 267-277.

Barrow,  N.  J.  1986b.   "Testing a Mechanistic  Model.  II.    The Effects of  Time
  and Temperature on the Reaction of Zinc  with a Soil."  J.  of Soil Science 37:
  pp. 287-295.

Barrow,  N.  J.  and A.  S.  Ellis.   1986a. " Testing  a  Mechanistic  Model.    III.
  The Effects  of  pH on Fluoride Retention by  a Soil."  J.  of Soil Science  37:
  pp. 287-295.

Barrow,  N.  J.  and  A.  S. Ellis.   1986b.   "Testing a Mechanistic  Model.    IV.
  Describing  the  Effects  of  pH  on Zinc  Retention by  a  Soil."   J.  of  Soil
  Science 37: pp. 295-302.

Barrow,  N.  J.  and A.  S. Ellis.   1986c.   "Testing a Mechanistic  Model. V.  The
  Points Of Zero Salt  Effect  For  Phosphate Retention  and  For Acid/alkali
  Titration Of A Soil."  J. of Soil Science  37:  pp.  303-310.

Battelle,  February  1984.  "Sediment  Quality  Criteria  Development  Workshop."
  Prepared  for  USEPA,  Office  of Water Regulations and Standards,   Criteria  and
  Standards Division. (SCD 2)

Beller.  H.  R. ,  R.  C.  Barrick  and D. S.  Becker.   1986.  Development of  Sediment
  Quality  Values  for  Puget  Sound.   Final  Report  DACW67-85-0029,  Work Order
  0001C, TC3090-02; Task 6.  Tetra Tech, Inc., Bellevue, Washington.  129 p.

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Page 8-4


Benes, P. and V. Majer.   1980.   Trace Chemistry of Aqueous Solutions.  Elsevier,
  New York.

Berner,  R.  A.   1980.    Early  Diagenesis.  A  Theoretical  Approach.   Princeton
  Univ. Press, Princeton, New Jersey.

Bierman, V.  J.,  Jr.,   1988.   Partitioning of Organic Chemicals  in Sediments:
  Estimation of Interstitial  Concentration Using  Organism Body  Burden.    In
  Press.

Bolton, S. H., R. J. Breteler,  B. W.  Vigon, J.  A.  Scanlon  and S.  L.  Clark,  July
  1985. "National Perspective On Sediment Quality."   Prepared for USEPA,  Office
  of Water Regulations and Standards, Criteria and Standards Division.  (SCD 3)

Bricker, 0.  P.,  G.  Matisoff and G.  R. Holdren, Jr.  1977.   Interstitial Water
  Chemistry  of  Chesapeake  Bay  Sediments.   Department of Natural Resources,
  Maryland Geological Survey, Basic Data Report No.  9.

Brownawell, B. J. and J.  W.  Farrington.   1985.   "Partitioning of  PCBs  in Marine
  Sediments."   In:  Marine and  Estuarlne Geochemistry, pp.  97-119.  Editors:   A.
  C. Sigleo and A. Hattori.  Lewis Publishers,  Inc.,  Chelsea,  MI 48118.

Brownawell,  B.  J.  and J. W.  Farrington.   1986.   "Biogeochemistry of PCBs  in
  Interstitial Waters Of A  Coastal Marine  Sediment."  Geochimica  et Cosmochim.
  Acta  50: pp. 157-169.

Campbell, P.  G.  C., A. Tessier,  M. Bisson  and  R.  Bougie.   1985.   "Accumulation
  of  Copper  and Zinc  in  the Yellow Lily, Nuphar variegatum:  Relationships  to
  Metal Partitioning in the Adjacent Lake Sediments." Can. J. Fish. Aquat  Sci.
  42: pp. 23-32.

Carignan, R.   1984.   "Interstitial Water Sampling by Dialysis:   Methodological
  Notes."  Limnol. Oceanogr. 29(3):  pp.  667-670.

Carignan, R.,  F. Rapin  and A. Tessier.   1985.   "Sediment  Porewater  Sampling
  for  Metal  Analysis: A  Comparison of Techniques."   Geochimica  et Cosmochem.
  Acta  49: pp. 2493-2497.

Carlson,  A.  R., H.  Nelson and D.   Hammermeister.   1986.   "Development  and
  Validation  of  Site - Specific  Water  Quality Criteria  for Copper."
  Environmental  Toxicology and Chemistry 5: pp. 997-1012.

Carter,  C.  V. and I.  H.  Suffett, 1983.   "Interactions Between Dissolved Humic
  and Fulvic  Acids  and  Pollutants  in  Aquatic Environments."   ACS Symposium
  Series, No.  225,  Fate  of  Chemicals in the Environment.  Ed. Swann, R. L.  and
  A.  Eschenroeder.

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                                                                       Page  8-5


Chapman,  G.  A.    1987.   "Establishing Sediment Criteria  for  Chemicals  -
  Regulatory Perspective."  In: Fate and Effects of Sediment - Bound Chemicals
  in Aquatic Systems,  pp.  355-376. 'Editors:  K.  L. Dickson, A. W. Maki and W. A.
  Brungs.  Pergamon Press, New York.

Chapman, P.  M.  and E.  R. Long.   1983.  "The  Use  of  Bioassays  as Part  of  a
  Comprehensive Approach  to Marine Pollution Assessment."   Mar.  Pollut. Bull.
  14: pp. 81-84.

Chiou,  C.  T.   1985.   "Partition Coefficients  of  Organic  Compounds in Lipid-
  Uater Systems and Correlations with Fish Bioconcentration Factors."   Environ.
  Sci. Technol.  19: pp.  57-62.

Cowan, C. E. and D. M. Di Toro, March 1988.  "Interim Sediment Criteria Values
  for Nonpolar Hydrophobic  Compounds."    Prepared  for USEPA, Office  of Water
  Regulations and Standards,  Criteria and Standards Division.  (SCD  17).

Cowan,  C.  E.  and R. G. Riley,  January  1987.  "Guidance  For  Sampling  and
  Analyzing For Organic Contaminants On Sediments." Prepared for USEPA, Office
  of Water Regulations and Standards, Criteria  and  Standards Division.  (SCD 8)

Cowan,  C.  E.  and  C.  S.  Zarba, June 1987. "Regulatory Applications of  Sediment
  Quality  Criteria  -  Final  Report."  Prepared for  USEPA, Office of  Water
  Regulations and Standards,  Criteria and Standards Division. (SCD 10)

Crecelius,  E.A.,   E.  A.  Jenne and  J.  S.  Anthony,  Decembe 1987.   "Sediment
  Quality  Criteria for  Metals:   V. Optimization of Extraction  Methods  for
  Determining  the Quantity   of  Sorbents and  Adsorbed Metals  in Sediments."
  Prepared for USEPA, Office  of Water Regulations  and Standards,  Criteria and
  Standards Division.   (SCD 16)

Curl, R. L. and G. A. Keolelan.  1984.   "Implicit-Adsorbate Model for Apparent
  Anomalies  with  Organic Adsorption on  Natural  Adsorbents."    Environ.  Sci.
  Technol. 18(12): pp. 916-922.

Dickson, K.  L. , A. W.  Maki and W. A. Brungs,  Ed., 1984.   Fate  and Effects of
  Sediment-Bound Chemicals in Aquatic Systems.  Pergamon Press, New York.

Di  Toro,  D.  M.  1985.    "A Particle  Interaction  Model of  Reversible  Organic
  Chemical Sorption."  Chemosphere 14(10): pp.  1503-1538.

Di  Toro,  D.  M. ,   F.  Harrison,  E.  Jenne, S.  Karickhoff and W.  Lick.   1987.
  "Synopsis of  Discussion  Session 2:  Environmental   Fate  and
  Compartmentalization."  In:  Fate and  Effects of  Sediment-Bound Chemicals in
  Aquatic  Systems.  pp.  136-147.  Editors: K. L. Dickson, A.  W. Maki and W.  A.
  Brungs.  Pergamon Press, New York.

Di  Toro, D.M., J.D.  Mahony,  D.J. Hansen  and  J.K. Scott,  1989.  "Preliminary
  Experimental Results."  EPA Environmental Research Laboratory,  Narragansett,
  RI. Manhattan College,  Bronx, New York.

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Page 8-6


Di  Toro,  D.   H. ,  L.  M.  Horzempa,  M.  Casey and  V.  Richardson.    1982b.
  "Reversible  and Resistant Components on FCB Adsorption-Desorption:  Adsorbent
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Oi Toro, D. M., J. D. Mahony, P. R.  Kirchgraber, A. L.  0'Byrne,  L.  R.  Pasquale
  and D.  C.  Piccirilli.   1986.   '" Effects  of  Nonreversibility,  Particle
  Concentration, and Ionic Strength on Heavy Metal Sorption."    Environ.  Sci.
  Technol.  20: p.  55.

Di Toro, D. M. and  L.  Horzempa.   1983.    "Reversible  and  Resistant Component
  Model  of Hexachlorobiphenyl  Adsorption-Desorption:   Resuspension  and
  Dilution."  In:  Physical  Behavior of  PCB's  in  the Great  Lakes.   p.  89.
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Dzombak, D. A.   1986.   Toward  a Uniform  Model for the  Sorption of Inorganic
  Ions on Hydrous Oxides.   Ph.D.  Thesis.  M.I.T., Cambridge, Massachusetts.

Eadie,  B.   J., N.  R.  Morehead  and  P.   F.  Landrum.    1988.    "Three-Phase
  Partitioning  of  Hydrophic  Organic  Compounds  in Great  Lakes Waters."
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Goldberg, S. and G.  Sposito.   1984.   "A Chemical Model of Phosphate Adsorption
  by Soils.  II.  Noncalcareous  Soils."  Soil Sei. Soc.  Am.  J. 48: pp.  779-783.

Gschwend,  P.   M.  and  S.  Uu.   1985.    "On the  Constancy  of  Sediment-Water
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Hansen,  D. J.   1974.   "Aroclor 1254:  Effect  on Composition  of  Developing
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Hansen,  D.  J. and M.  E.  Tagatz.  1980.   A Laboratory  Test for Assessing  the
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Hesslein,  R.   H.   1976.  "An In  situ  Sampler  for Close  Interval  Pore Water
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Jenne, E. A.   1968.   "Controls on Mn,  Fe,  Co,  Ni,  Cu,  and Zn Concentrations in
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Jenne, E. A.  1977.   "Trace  Element  Sorption by Sediments  and Soil -- Sites  and
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Jenne,  E.  A.   1987.  "Sediment  Quality Criteria  for Metals:  II.    Review of
  Methods  for Quantitative  Determination  of  Important  Adsorbents  and  Sorbed
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Jenne,  E.  A.,  D. M.  Di  Toro,  H.  E.  Allen,  and  C.  S. Zarba.   1986.  "An
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Jenne, E. A., August 1987. "Sediment Quality Criteria For Metals:  IV.  Surface
  Complexation And Acidity Constants For Modeling Cadmium and  Zinc Adsorption
  onto  Iron Oxides."   Prepared for USEPA,  Office  of  Water Regulations  and
  Standards, Criteria and Standards Division (SCD 12)

Jenne, E. A., August 1987. "Sediment Quality Criteria For Metals:  II. Review of
  Methods  For Quantitative  Determination  of  Important  Adsorbents  and  Sorbed
  Metals In  Sediments."   Prepared for  USEPA,  Office of  Water Regulations  and
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                                             •
Johnson, C.  A.  1986.  "The Regulation of Trace Element Concentrations in River
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JRB Associates, June 1984.  "Background  And Review Document On The  Development
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Kadeg, R.  D., S.  P.  Pavlou and A.  S. Duxbury,  January 1986.  "Sediment Criteria
  Methodology Validation,  Elaboration Of Sediment Normalization  Theory  For
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Kadeg, R.  D.  and  S.  P. Pavlou, November 1987.   "Reconnaissance  Field Study  for
  Verification  of  Equilibrium  Partitioning:    Nonpolar Hydrophobic Organic
  Chemicals."  Prepared for  USEPA,  Office  of Water  Regulations and Standards,
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Karickhoff,  S.  W.   1984.     "Organic Pollutant Sorption in Aquatic Systems."
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Karickhoff,  S. W.  and  K.  R.  Morris.   1985.  "Sorption Dynamics of  Hydrophobic
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  pp. 469-479.

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Kemp, P.  F.  and R.  C.  Swartz.   1986.   "Acute Toxicity of  Interstitial  and
  Particle-Bound Cadmium to a Marine Infaunal Amphipod."  Submitted to J.  EXP.
  Marine Biol.  Ecol.

Lake,  J.  L. ,  N.  Rubinstein  and  S.  Pavignano.    1987.    "Predicting
  Bioaccumulation:  Development  of a  Simple  Partitioning Model  for  Use as  a
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  Effects  of  Sediment-Bound  Chemicals  in Aquatic  Systems.   pp.   151-166.
  Editors: K.L.  Dickson,  A.W.  Maki  and W.A.  Brungs.   Pergamon Press,  New
  York.

Landrum, P.  F., S.  R. Nihart, B. J. Eadie and L. R. Herche.   1987.  "Reduction
  in Bioavailability of Organic Contaminants  to  the  Amphipod  Pontoporeia hovi
  by Dissolved Organic  Matter of  Sediment  Interstitial  Waters."   Environ.
  Toxicology and Chem.  6:  pp.  11-20.

Landrum,  P.  F. ,  M.  D.  Reinhold, S.  R.  Nihart  and  B.  J.  Eadie.   1985.
  "Predicting the Bioavailability  of Organic Xenobiotics to Pontoporeia hovi in
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Langston,  W.  J.    1980.   "Arsenic  in  U.K. Estuarine Sediments   and  Its
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Langston, W. J.   1985.   "Assessment  of the Distribution and Availability  of
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Langston, W. J.    1986.    "Metals  in  Sediments and  Benthic  Organisms in  the
  Mersey Estuary."   Estuarine.Coastal  and Shelf Sci. 23: pp.  239-261.

Long, E. R.  and P. M. Chapman.  1985.   "A Sediment Quality Triad:  Measures  of
  Sediment  Contamination,  Toxicity  and Infaunal Community  Composition   in
  Puget Sound."  Mar. Pollut.  Bull. 16(10): pp. 405-415.

Luoma,  S. N.   1983.  "Bioavailability  of Trace Metals to  Aquatic  Organisms  - A
  Review."  The Science  of the Total Environment 28: pp. 1-22.

Luoma,  S. N.  and W.  Bryan.   1981.   "A Statistical Assessment of the  Form  of
  Trace Metals in Oxidized Sediments Employing Chemical Extractants."   The  Sci
  of the Total Environment 17: pp.  165-196.

MacKay,  D. and B.  Powers.   1987. "Sorption of Hydrophobic Chemicals from Water:
  A  Hypothesis  for the  Mechanism  of the  Particle  Concentration  Effect."
  Chemosphere 16(4):  pp.  745-757.

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                                                                      Page 8-9


McCarthy, J. F.  and B. D. Jimenez.   1985.   "Reduction  in Bioavailability to
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