Hazard Ranking System Issue Analysis:
   Classification of Hazardous Substances
for Potential to Accumulate in the Food Chain
                   MITRE

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     Hazard Ranking System Issue Analysis:
     Classification of Hazardous  Substances
for  Potential to  Accumulate in the Food Chain
                      Stephen V. McBrien
                       Alan S. Goldfarb
                       Sharon D. Saari
                         June 1987
                         MTR-86W114
                          SPONSOR:
                    U.S. Environmental Protection Agency
                        CONTRACT NO.:
                         EPA-68-01-7054
                      The MITRE Corporation
                       Civil Systems Division
                        7525 Colshire Drive
                      McLean, Virginia 22102-3481

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Department Approval:
                  i:  "m
                          ii
MITRE Project Approval:

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                              ABSTRACT

     This report, prepared for the Office of Emergency and Remedial
Response (OERR) of the Environmental Protection Agency, contains an
option for rating the relative potential of hazardous substances to
bioaccumulate.  This rating scheme is intended as a component of a
human food chain exposure methodology which is being separately
developed for possible inclusion in the EPA Hazard Ranking System
(HRS).  This rating scheme makes use of available data on
bioconcentration factors, n-octanol-water partition coefficients,
and water solubility.  In addition, the rating scheme makes use of
available information on potential biomagnification of hazardous
substances.  The system makes use of data in order of its
reliability and its availability, as well as on its ability to
describe, quantitatively, the potential of a substance to
bioconcentrate.

Suggested Keywords:  Superfund, Hazard ranking, Hazardous waste,
Bioconcentration, Bioconcentration factor surrogates.
                                iii

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                          TABLE OF CONTENTS
                                                                 Page

LIST OF FIGURES                                                  vii
LIST OF TABLES                                                   vii

1.0  INTRODUCTION                                                  1

1.1  Background                                                    1
1.2  Issue Description                                             3
1.3  Scope                                                         4
1.4  Approach                                                      6
1.5  Organization of Report                                        9

2.0  MEASURES OF BIOACCUMULATION POTENTIAL                        11

2.1  Biomagnification                                             12

     2.1.1  Definition                                            12
     2.1.2  Discussion                                            13

2.2  Bioconcentration                                             17

     2.2.1  Definition                                            17
     2.2.2  Bioconcentration Factor                               18
     2.2.3  Potential Surrogates for Bioconcentration Factor      19

3.0  THE PROPOSED RANKING SCHEME                                  27

3.1  Overview of the Ranking Scheme                               27

     3.1.1  Classification Based on Bioconcentration Factor       29
     3.1.2  Classification Based on Logarithm of the              30
            n-Octanol-Water Partition Coefficient
     3.1.3  Water Solubility                                      32

3.2  Decision Procedures for Ranking Hazardous Substances         33
3.3  Illustration of Proposed Ranking Scheme                      35

4.0  BIBLIOGRAPHY AND REFERENCES                                  37

APPENDIX A - CLASSIFICATION OF HAZARDOUS SUBSTANCES FOR           53
             POTENTIAL TO BID-ACCUMULATE

APPENDIX B - SUMMARY OF DATA COLLECTED ON HAZARDOUS SUBSTANCES    55

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                    TABLE OF CONTENTS  (Concluded)


                                                                 Page

APPENDIX C - ECOLOGICAL FACTORS WHICH AFFECT BIOACCUMULATION      87

APPENDIX D - CHEMICAL/PHYSICAL FACTORS WHICH AFFECT               99
             BIOACCUMULATION

APPENDIX E - GLOSSARY OF TERMS USED                              109

APPENDIX F - OTHER METHODS REVIEWED                              115
                                 vi

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                           LIST OF FIGURES
Figure Number

      1


      2


      3


      4
Biomagnification of DDE, PCBs and Toxaphene
in Lake Providence, Louisiana

Lake Powell, Arizona Trophic Levels with Mean
Parts per Billion Mercury

Example Correlations of Log BCF versus Log P
for Bioaccumulation

Decision Tree for Ranking Substances for
Potential to Bioaccumulate in the Food Chain
Page

 14


 16


 22


 28
Table Number
                           LIST OF TABLES
                Summary of Values Found in the Literature
                For the Constants a and b in the
                Equation log BCF = a log Poct + b
                                                 Page

                                                  23
                                vii

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1.0  INTRODUCTION




1.1  Background




     The Comprehensive Environmental Response, Compensation, and




Liability Act of 1980 (CERCLA) (PL 96-510) requires the President to




identify national priorities for remedial action among releases or




threatened releases of hazardous substances.  These releases are to




be identified based on criteria promulgated in the National




Contingency Plan (NCP).  On July 16, 1982, EPA promulgated the




Hazard Ranking System (HRS) as Appendix A to the NCP  (40 CFR 300;




47 FR 31180).  The HRS comprises the criteria required under CERCLA




and is used by EPA to estimate the relative potential hazard posed




by releases or threatened releases of hazardous substances.




     The HRS is a means for applying uniform technical judgment




regarding the potential hazards presented by a release relative to




other releases.  The HRS is used in identifying releases as national




priorities for further investigation and possible remedial action by




assigning numerical values (according to prescribed guidelines) to




factors that characterize the potential of any given release to




cause harm.  The values are manipulated mathematically to yield a




single score that is designed to indicate the potential hazard posed




by each release relative to other releases.  This score is one of




the criteria used by EPA in determining whether the release should




be placed on the National Priorities List (NPL).

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     During the original NCP rulemaking process and the subsequent

application of the HRS to specific releases, a number of technical

issues have been raised regarding the HRS.  These issues concern the

desire for modifications to the HRS to further improve its

capability to estimate the relative potential hazard of releases.

The issues include:

     •  Review of other existing ranking systems suitable for
        ranking hazardous waste sites for the NFL.

     •  Feasibility of considering ground water flow direction and
        distance, as well as defining "aquifer of concern," in
        determining potentially affected targets.

     •  Development of a human food chain exposure evaluation
        methodology.

     •  Development of a potential for air release factor category
        in the HRS air pathway.

     •  Review of the adequacy of the target distance specified in
        the air pathway.

     •  Feasibility of considering the accumulation of hazardous
        substances in indoor environments.

     •  Feasibility of developing factors to account for
        environmental attenuation of hazardous substances in ground
        and surface water.

     •  Feasibility of developing a more discriminating toxiclty
        factor.

     •  Refinement of the definition of "significance" as it relates
        to observed releases.

     •  Suitability of the  current HRS default value for an unknown
        waste quantity.

     •  Feasibility of determining and using hazardous substance
        concentration data.

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     •  Feasibility of evaluating waste quantity on a hazardous
        constituent basis.

     •  Review of the adequacy of the target distance specified in
        the surface water pathway.

     •  Development of a sensitive environment evaluation
        methodology.

     •  Feasibility of revising the containment factors to increase
        discrimination among facilities.

     •  Review of the potential for future changes in laboratory
        detection limits to affect the types of sites considered for
        the NPL.

     Each technical issue is the subject of one or more separate but

related reports.  These reports, although providing background,

analysis, conclusions and recommendations regarding the technical

issue, will not directly affect the HRS.  Rather, these reports will

be used by an EPA working group that will assess and integrate the

results and prepare recommendations to EPA management regarding

future changes to the HRS.  Any changes will then be proposed in

Federal notice and comment rulemaking as formal changes to the NCP.

The following section describes the specific issue that is the

subject of this report.

1.2  Issue Description

     Tbe U.S. Congress, EPA personnel, and the public have expressed

the concern that public health and welfare are potentially

threatened by exposure through the human food chain to hazardous

substances released from CERCLA sites, and that this route of

exposure is not adequately considered in the HRS.  In order to

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evaluate the potential exposure of humans to hazardous substances



through the food chain, it is necessary to evaluate those substances



that have the capability to accumulate in parts of the food chain at




levels substantially higher than in the surrounding environment.



This capability, often referred to as bioaccumulation, has been



demonstrated most clearly in the aquatic food chain, although there



is reason to believe it also exists in the terrestrial food chain.



This paper addresses the issue of how to evaluate those substances



which may pose a substantial danger due to their capability to



concentrate in the food chain.



1.3  Scope



     This paper presents a methodology for classifying substances in



order to identify those of primary concern should they enter the



human food chain.  Specifically, the paper presents a classification



scheme based on the potential of the substances to accumulate in the



human food chain.  This paper is restricted to consideration of the



accumulation of hazardous substances in the human food chain; it



does not address the relative toxicity of these substances.  DeSesso




et al.  (1986) addresses the toxicity of these substances.



     The likely availability  (and cost) of the required data was a



major consideration in the development of this classification



methodology.  The methodology presented here is based on the

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assumption that the level of data available will continue to be




those data obtained during a CERCLA site inspection.  This paper is



restricted to the potential of substances to accumulate in the food




chain.  It is not intended to be used to establish a comprehensive




human food chain rating methodology for the HRS.  Saari (1986)



addresses the broader questions of developing a comprehensive human




food chain rating methodology for use in the HRS.



     In addition, the focus of this paper is primarily on the



accumulation of hazardous substances In the surface water pathway




component of the food chain.  This focus is largely a function of




available data.  Although a review of the research reported in the



literature revealed that aquatic and terrestrial ecosystems both




exhibit bioconcentratlon and, in some cases, biomagnlfication, there




are many references to the potential threat to humans through the



aquatic food chain, but none indicating a serious threat via the




terrestrial food chain.  As a result, it was possible to more




readily identify aquatic human food chain impacts, and, therefore,




the scope of this paper was largely restricted to the surface water




pathway.




     In this paper, common definitions are used for processes



related to the uptake of hazardous substances (Appendix E contains a




comprehensive glossary for all terms in this report).  The following




four definitions are particularly important:

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     •  Bioconcentration;   The process whereby chemical substances
        enter aquatic organisms through the gills or epithelial
        tissue directly from water,  and are accumulated at levels
        that exceed the concentration of the substance In the
        surrounding environment.

     •  Bioaccumulatlon;  A broader  term referring to a process
        which includes bioconcentration but also any uptake of
        chemical residues from dietary sources.

     •  Biomagniflcation;   A process by which the tissue
        concentrations of bioaccumulated chemical residues increase
        as these materials run up through the food chain through two
        or more trophic levels.  Historically implicit in the use of
        this term is the connotation that residue concentrations at
        successively higher trophic  levels increase by integral
        multiples (e.g., by factors  of 3, 4, 5, etc.).

     •  n-Octanol-Water Partition Coefficient:  A measure of the
        preferential partitioning of a substance between n-octanol
        and water.

     •  Solubility;  A property of a substance by virtue of which it
        forms chemically and physically homogeneous mixtures with
        other substances.

1.4  Approach

     In brief, the approach taken to examine the question of which

hazardous substances are of most concern in the human food chain

incorporated four steps.  These steps were:  (1) a literature search

for indicators which could be used to identify substances with the

potential to accumulate in the human food chain, (2) a review of

those methods found in the literature search for classifying

hazardous substances as to their potential to accumulate in the food

chain, (3) the development of a classification scheme suitable for

hazardous substances found at waste sites, and (4) the application

of the scheme to Illustrate the classification of several substances

typically found at NPL facilities.

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     As a result of the literature search and the review of other




methods of ranking hazardous substances, several measures were




identified as indicators of the potential for a substance to




accumulate in food chain organisms.  The most important of these are:




     •  Biomagnification factor



     •  Bioconcentration factor




     •  n-octanol-water partition coefficient



     •  Solubility



     As mentioned in Section 2, the occurrence of biomagnification




far in excess of reported bioconcentration levels has been documented




in the literature for a few substances  (e.g., methylmercury, DDT,



PCBs).  For other substances, however,  there is some evidence that




the process of  biomagnification of chemical residues in the aquatic




food chain is quantitatively insignificant when compared to the



process of bioconcentration (Macek, 1979).




     Bioconcentration factors (BCF) are well documented in the




literature for  a number of substances.  The U.S. Environmental



Protection Agency, for example, reports BCFs (when available) in




their water quality criteria documents.  Reported BCFs range from




less than one up to a million.  A BCF of 1,000 or more for a given




substance indicates a potential for significant bioaccumulation



(Trabalka and Garten, 1982), that could cause substantial human



exposure to that substance, even if relatively small amounts of food




in which the substance is concentrated  are ingested.

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     Unfortunately, BCFs are not available for all of the hundreds



of substances found at CERCLA sites.  For those substances for which



BCFs are not available, it is necessary to estimate BCFs.



     The logarithm of the n-octanol-water partition coefficient (log



Pow) has been used as a surrogate measurement for the BCF.  While



the direct measurement of bioconcentratlon from the environment is



preferred, the log Pow commonly is recommended as a surrogate in



evaluating the bioconcentratlon potential of hazardous substances in



the absence of direct measurement (e.g., Van Gestel et al., 1985).



     The water solubility of a substance is an important character-



istic for establishing that substance's potential environmental



movement and distribution.  In the absence of log Pow data, it is



possible to make use of water solubility data to determine the



extent to which a substance is inclined to bioconcentrate in an



organism (Verschueren, 1983).



     Of these four types of data, data on the biomagnification of



substances are the least available; BCFs are more commonly



available; and log Pow and/or water solubility data are most readily



available for a majority of the hazardous substances of concern



under CERCLA.  A classification scheme using all four types of data



is proposed in this report.  The scheme uses a hierarchy based on



data reliability and availability.  Using this hierarchy of data,



selected hazardous substances are classified for their potential to



bioaccumulate.
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     Results presented in this report have been used in developing




a proposed methodology for incorporating the potential for exposure




to hazardous substances via the human food chain in the HRS (Saari,




1986).




1.5  Organization of Report



     This report presents a proposed scheme developed to classify the




bioaccumulation potential of hazardous substances.  The scientific



basis of the proposed method is documented and the results of



applying the scheme to selected hazardous substances are presented.




     The concepts of biomagnification and bioconcentration factors



are discussed in Section 2.  Examples from field and laboratory




studies are provided to support the use of these factors in the



classification scheme.




     A classification scheme which could be used in the HRS is



presented in Section 3.  The scheme incorporates a decision tree




based on the availability of biomagnification, BCF, log Pow, or



solubility data.  Using this decision tree, several substances were



classified; the results are reported in Appendix A.




     Section 4 contains a bibliography of references.




     Appendix B provides, for several hundred substances, BCF and



log Pow data obtained from the literature and other available data




bases.




     Appendices C and D provide background material applicable to



the proposed ranking scheme.  These appendices provide an

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explanation for why the reported BCF data have such wide




variations.  Ecological factors which affect bioaccumulation are




explained in Appendix C and chemical factors are explained in




Appendix D.




     Appendix E is a glossary of ecological terms, acronyms, and




other technical terms used in this paper.




     Appendix F contains a summary description of other existing




methods used to rank hazardous substances and which were reviewed in




preparing this report.
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2.0  MEASURES OF BIOACCUMULATION POTENTIAL

     Many hazardous substances may be concentrated in the aquatic

food chain from low ambient levels in water to much higher levels in

various species of fish.*  For example, fish and shellfish are able

to bioaccumulate some organic compounds to levels thousands of times

greater than the concentration in the water in which they live.

Thus, even substances with very low solubility in water have the

potential to achieve high concentrations in aquatic organisms.

     The process of bioaccumulation is an especially important

consideration in evaluating whether a fish population has

accumulated a substance in concentrations which might pose a health

hazard to humans eating the fish.

     Unfortunately, data providing direct measurement of the ability

of a given substance to bioaccumulate in a given species of fish are

very limited.  Indeed, the very large number of fish species, coupled

with the extremely large number of potentially hazardous substances,

makes any comprehensive compilation of such measurements

impractical.  As a result, scientists have developed several methods

for estimating the potential of hazardous substances to

bioaccumulate in aquatic life.  While these methods have their

inadequacies, they do provide an indication of the relative hazard
*The term fish as used throughout this report includes fish,
 shellfish and other aquatic human food chain organisms.
                                 11

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posed by the potential bioaccumulation of hazardous substances,




based on data which are readily available.




     This section provides information on the processes and chemical




characteristics which can be used to describe, in a quantitative




manner, the potential for bioaccumulation.  These are



biomagnification, bioconcentration, the n-octanol-water partition




coefficient, and solubility.  This section provides technical




definitions for each of these, and illustrates how data on each




could be used in a hazardous substance food chain impact




classification scheme.




     Several studies were reviewed to determine possible approaches




to estimating bioaccumulation potential.  Summary discussions of




these studies may be found in Wolfinger and Haus (1986).




2.1  Biomagnification




     2.1.1  Definition




     Biomagnification is a biological process whereby a substance




becomes increasingly more concentrated in the tissue of different




species as the substance moves up the food chain through two or more




trophic levels.  For example, the environment (e.g., a specific body




of water) may have a very low concentration of a substance, but




aquatic insects living in it have higher concentrations.  The small




fish that eat those insects may concentrate the substance even




further.  Near the top of the food chain, large predator fish may



have very high concentrations of that substance.
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     Figure 1 (from Niethammer et al., 1984) illustrates the classic




biomagnification process as it occurs in freshwater lakes of




Louisiana.  The vertical axes represent the concentrations (in parts




per million) of DDE, PCBs, and toxaphene.  The horizontal axes,




reading from left to right, represent the trophic levels of the




animals sampled.  For example, on the left are lower order crayfish




and frogs which show very low residues.  In the middle are small




consumers such as bluegills and shiners, which have low




concentrations.  As one moves up the food chain (to the right),




predatory fish, such as the gar and largemouth bass, have higher




concentrations of these residues.




     2.1.2  Discussion




     There are a number of studies (see Appendix B) which report




biomagnification of substances in the aquatic ecosystem.  It is not




so clear that this process occurs in terrestrial ecosystems (Garten




and Trabalka, 1983; Walton and Edwards, 1986).  In those cases where




there is some indication of biomagnification in the terrestrial




ecosystem (e.g., the biomagnification of pesticides in birds of




prey), very often the top predator is a fish eater.




     Measurement of a hazardous substance in all parts of the




ecosystem and at all trophic levels of the food chain is both




difficult and expensive.  While not all research results agree, it




is clear that some substances do biomagnify.  For example, published
                                 13

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1  -
                               DDE
                               (ppm)
                                   15 -
                                   10
                                                           -2i
                                   A^
                                     /
                                      ^
**
y
         Toxaphene
          (ppm)
                15
                10
                                          18.8
                            —••••illl
               0<'
                                          V
            ^
             /
               /
                            Species
Source:  Niethammer et al.,  1984.
                          FIGURE 1
               BIOMAGNIFICATION OF ODE, PCBs
        AND TOXAPHENE IN LAKE PROVIDENCE, LOUISIANA
                            14

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research almost universally supports the concept of biomagnlfication




of DDT and its metabolites, PCBs, and mercury.  Numerous studies




show that DDT biomagnifies in the food chain  (Carey et al., 1973;




Daly, 1984; Domsch, 1984; Hatfull, 1983; Keene, 1983; Kenaga, 1980;



Kodric-Smit et al., 1980; Niethammer et al., 1984; Niewiadowska and



Sosyniak, 1983; Ofstad and Martinsen, 1983; U.S. Environmental




Protection Agency, 1983).  However, Kay (1984) concludes that while




there appears to be biomagnification potential for PCBs,



methylmercury, kepone, mirex, benzo-a-pyrene, and naphthalenes,




"compounds which probably do not biomagnify include DDT and its




derivatives."



     Kay  (1984) describes the biomagnification (Figure 2) of mercury




in Lake Powell, Arizona  (from Potter et al., 1975).  In this case,



the water and sediments had relatively low concentrations; small



consumers and producers  (plants) had slightly higher levels, and the




top predator fish  (walleye and bass) had the highest concentrations.




In countries where fish are a major diet component, methylmercury



poisoning of human populations is possible (Ditri and Ditri, 1976).




     PCBs have also been demonstrated to biomagnify, especially in




large predatory fish  (Ray et al., 1984).  O'Connor  (1984) reports




that while fish can take PCBs directly from water  (bioconcentration),




for striped bass at least, diet  appears to be the most significant




source of PCBs.  Both Larsson (1984) and Rubenstein et al.  (1984)



conducted laboratory experiments with fish and found food uptake  of
                                 15

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jj
c.
Q.
     T3 i»
     £ °
       E
       w
     £••2
       CO
     •p a)
       in
       o>
       DC
                  Walleye
                  427 ppb
 Bass
314 ppb
                                                    Trout
                                                    84ppb
                                 Crappie
                                 204 ppb
1 1
lad Bluegill
ppb 19 ppb
ppb 85 ppb
! l


Flannelmouth
Sucker *—
99 ppb
I

252
113


I

rp
ppb
ppb

Catfish
126 ppb



Invertebrates
10 ppb
I
^

»
Young Fish

Phytoplankton

Periphyton
32 ppb
I

I
Water
0.01 ppb




Terrestrial
Plants
19 ppb
I

I
Bottom
Sediments
30 ppb
*-»•
Torres
Subst
10 p
                                                                     Plant
                                                                    Debris
                                                                    148 ppb
   Source: (Modified from Kay, 1984)
                                   FIGURE 2
                 LAKE POWELL, ARIZONA TROPHIC LEVELS
                 WITH MEAN PARTS PER BILLION MERCURY
                                     16

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PCBs to be the most important route of exposure.  In the example of




FCB bioaccumulation at the top of the food chain (e.g., lake trout),



the older and larger individuals usually have the greatest




concentrations of the substance (Thomann and Connolly, 1984).  Black




(1983) compared the human consumption rates for drinking water and



eating fish from the Great Lakes, and he concluded "the relative




importance of the fish versus drinking water in this situation can




be a little better appreciated if one considers that given a fish




contaminated with PCS at 5 ppm, a human would have to drink Great




Lakes water for about 1,000 years in order to equal the amount of




PCB that you get in a single one pound serving of these contaminated



fish."




2.2  Bioconcentration



     2.2.1  Definition



     Bioconcentration refers to a process through which an organism




accumulates a substance to levels that exceed the concentration of



the substance in its environment (U.S. Environmental Protection




Agency, 1982b).  This can also be regarded as the first step in




biomagnification.  Bioconcentration is most often expressed in terms




of a bioconcentration factor (BCF), the ratio of the concentration



of the substance in an organism, for example in fish tissue, to the




concentration of the same substance in the ambient water.  Another,




less common measure of bioconcentration is the ratio of the



concentration of a substance in plant tissue to its concentration in
                                 17

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the soil the plant grows In.  A little used measure of




bioconcentration is the ratio of the concentration in animal tissue




(e.g., beef) to the concentration in feed.




     2.2.2  Bioconcentration Factor




     There is a large volume of scientific literature in which the




BCFs for a number of substances are reported.  Data have been




reported on bioconcentration of radionuclides since the 1950s, of




pesticides since the 1960s, and of heavy metals since the 1970s.




More recently, in the 1980s, ecologists have been reporting




measurements of complex organics in food chains.  The reports on




complex organics include uptake rates and modes of transfer from the




environment to biota via food, and directly from water or air.




     Research results are available from controlled laboratory




experiments as well as from measurements of biota in the field.




While some food chain studies may report on only a single segment of




the food chain (e.g., uptake from sediment by worms), others report




on the entire food chain from producers to consumers, to first order




predators, and finally to top predators.  Some studies show uptake




of residues in a matter of days, while others report uptake only




after a year or more of exposure.  In some instances where actual




measured concentrations in the field or laboratory are unavailable,




it may be possible to calculate the BCF by one of several methods




described in Moriarty (1983).
                                 18

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     Table B-l of Appendix B summarizes bioconcentration factor data




from EPA criteria documents and the peer reviewed literature for over




130 substances reported to be present at NPL sites.  Most of these




data are reported for aquatic ecosystems, and the BCF values were




calculated as the ratio of the concentration of the chemical in fish




tissue to the concentration of the chemical in the aquatic habitat



of the fish.  In many cases, different authors report different BCF




values for the same substance (even for the same species), and




opinions vary as to the specific value which should be used for the




bioconcentration factor.




     The wide range in BCFs reported in the literature (see



Appendix B) can be explained by a number of ecological and chemical




factors.  They include:




     •  Mobility and availability of a particular compound




     •  Species role or niche in the environment




     •  Physiological differences among species




     •  Testing and measurement protocols



These factors are discussed in more detail in Appendices C and D.




     2.2.3  Potential Surrogates for Bioconcentration Factor




     A number of different factors which might indicate the potential




of a substance to bioconcentrate have been considered as surrogates



for the BCF.   These factors have included the n-octanol-water partition




coefficient,  solubility, and the soil adsorption coefficient.  Each of




these has been found to correlate with the bioconcentration factor and
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may, therefore, be useful as surrogates when direct bloconcentration




measurements are not available (Geyer et al., 1984; Lyman et al.,  1982;




Veith et al., 1980).  For the purposes of classifying bioconcentration




potential in the HRS, the n-octanol-water partition coefficient (Pow)




and solubility factors have been included in the ranking scheme as




surrogates for the BCF for reasons discussed below.  The soil




adsorption coefficient has not been used for reasons also discussed




below.  Appendix D discusses other potential surrogates that were




considered and rejected because they have not been found to correlate




with bioconcentration.




     2.2.3.1  n-Octanol-Water Partition Coefficient.  When n-octanol,




water, and an organic substance are mixed together until equilibrium




has been reached, and then allowed to stand, the n-octanol and water




will separate into two distinct phases, each of which contains some of




the organic substance.  The n-octanol-water partition coefficient  (Pow)




is the ratio of the concentration of the organic substance in the




n-octanol to its concentration in water when the system is in




equilibrium.  In addition to the direct measurement of the Pow, a




method of calculating the Pow from information on the chemical




structure of a substance has been developed by Lyman et al. (1982).




     In general, higher values of the logarithm of the Pow for a




substance correlate with higher values of its BCF in fish, and




consequently, its bioaccumulation potential.  For example, compounds




such as DDT and some PCBs which have high BCF values in fish have  log
                                 20

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Pow values above 5.  Compounds such as monochlorobenzene and




tetrachloroethylene which have low BCFs also have log Pow values of




less than 3.  Garten and Trabalka (1983) suggested that for screening




purposes, substances with a log Pow of 3.5 or more should be considered




as having the potential to bioaccumulate in mammals or birds.




     Many researchers have stated that the logarithm of the Pow has




a statistically significant linear correlation with the logarithm of




the bioconcentration factor of organic chemical compounds (e.g., Chiou,




1985; Geyer et al., 1984; Lyman et al., 1982; Veith et al., 1980).




This relationship is illustrated in Figure 3.  Table 1 presents a




range of values which various researchers have presented as indicators




of this relationship.




     This linear relationship occurs because many organic substances




bioconcentrate by incorporation into fatty tissue, and the n-octanol-




water partition coefficient provides a measure of the preferential




partitioning of substances between water and organic or fatty tissue.




Based on these relationships and the correlations indicated above,




many researchers (e.g.,  Trabalka and Garten, 1982) have concluded that




the log Pow is a highly satisfactory indication of bioaccumulation




potential in aquatic systems.




     The log Pow cannot, however, be used as a predictor of




bioconcentration for inorganic substances, because the mechanism by




which inorganic substances accumulate in food chain organisms is




different from that for organic substances.   Where metals are involved,
                                 21

-------
     a (Geyer et al., 1984)
b (Veith et al., 1980)
o

8
LU

c
g

31

|



I  *
o

en

O)
o
                              o

                              8
                              c
                              o
                              c  3

                              g

                              o  2
                              o
                              o
                                        1.0    2.0   3.0   4.0   5.0


                                               Log Pow
                     6.0
       234


       Log Pow
                        c (Lyman et al. 1982)
O

CO
C
O
•H
4-1
rt
o
a
cfl
o
•H
PQ
       * = Radio-tagged chemicals
                       FIGURE 3

         EXAMPLE CORRELATIONS OF LOG BCF

        VERSUS LOG P FOR BIOACCUMULATION
                          22

-------
                               TABLE  1

              SUMMARY OF VALUES FOUND IN THE LITERATURE
                  FOR THE CONSTANTS a AND b IN THE
                 EQUATION log  BCF  -  a log  Poct +  b
     Value of
              b"        r        *  n             Reference
0.76
0.85
0.858
0.542
1.1587
0.6335
0.935
1.53
1.022
0.997
0.84
0.86
0.79
-0.23
-0,70
-0.808
0.124
-0.7504
0.7285
-1.495
-3.03
-0.632
-0.869
-0.057
-0.333
-0.40
0.907
0.947
0,955
0.948
0.9771
0.7879
0.87
0.843
0.993
0.993
0.976
0.984
0.928
84
59
16
8
9
11
26
15
n
11
12
12
122
Veith et al., 1980
Veith et al. 1979
Geyer et al. 1982
Neeley et al. , 1974
Metcalf et al., 1975
Lu and Metcalf, 1975
Kenaga and Goring, 1980
Kanazawa, 1981
Oliver and Niimi, 1983
Oliver amd Niimi, 1983
Oliver and Niimi, 1983
Oliver and Niimi, 1983
Veith and Kosian, 1983
Note:  BCF is based on wet weight concentrations.
       r « correlation coefficient; n • number of  chemicals tested.

Source:  van Gestal et al., 1985.
                                 23

-------
the BCF typically is available from direct measurements (Hildebrand




and Cushman, 1976).




     For a variety of reasons discussed in Appendices C and D, the




relationships indicated in Table 1 do not always provide reliable




estimates of the BCF.  In addition to being inapplicable for metallic




substances, log Pow is generally considered a poor indicator of BCF




in those instances where it is greater than 6 (Hawker and Connell,




1985).  The table illustrates that different authors have developed




different regression equations relating BCF to the Pow.  Figure 3




illustrates the potential for outliers.  The number of substances




used to develop the correlation, the biological organism used, and




the accuracy of the measurement technique appear to contribute to




the differences in results.




     As a result of these and other difficulties, many researchers




have warned against indiscriminate use of the Pow.  Several authors




(e.g., Chiou, 1985; Garten and Trabalka, 1982) have noted, for




example, that the bioaccumulation of organic substances that bind to




proteins (e.g., methylmercury) is not adequately predicted by




generalized relationships based on chemical characteristics such as




the Pow.  Some substances with a low log Pow (e.g., organometallic




compounds), will, in fact, have a high BCF, while other substances




with a high log Pow may not show much evidence of bioaccumulation,




either because they are not absorbed by the organism,  are  present in




an unavailable form,  or are readily metabolized and excreted.   These
                                 24

-------
possibilities are graphically illustrated by the fact that about




25 percent of 68 substances studied by Garten and Trabalka (1983) were




classified on the basis of their log Pow values as having a higher




bioconcentration potential than their actual measured bioconcentration




factors.  Additional considerations are generally necessary to




establish the potential for bioaccumulation of a substance in the food




chain.  Only chronic feeding tests can adequately predict the




bioaccumulation of a substance.  Such tests, however, are both




time-consuming and expensive.




     As a result, although problems remain in using the n-octanol-water




partition coefficient to predict bioconcentration (most notably, log




Pow is not applicable for inorganics), it is widely used to rapidly




screen organic substances to identify those with potential for




bioconcentration.




     2.2.3.2  Other Chemical Parameters.  Besides the n-octanol-water




partition coefficient, water solubility and soil adsorption




coefficients are the properties most commonly used to predict the




bioconcentration of organic compounds in food chain organisms.




Substances with low water solubility are likely to bioconcentrate.




Substances with high soil adsorption are also likely to bioconcentrate.




Both measures have been used to predict BCFs in a manner similar to




the Pow.  Both are well correlated with log Pow;  however, because




solubility data are more readily available than soil adsorption




coefficients, the solubility data have been adopted for use in this




classification scheme.




                                 25

-------
     The measurement of water solubility does not usually impose



particularly complicated demands on standard chemical techniques,



although measurement for some barely soluble substances can require



specialized equipment.  However, since the design of many chemical



and environmental tests requires precise information on water



solubility, these tests are standard for the chemical industry, and



data are widely available.



     Unfortunately, there are many variables which can affect the
                                                                 »


solubility of a substance in water, including other chemicals in the



water, the temperature, and the molecular structure of a substance



and the associated purity of the substance.  In addition, there are



some difficulties in conducting measurements of low solubility



substances.  As a result of these factors, specific values reported



for water solubility may be suspect (Verschueren, 1983).



     Chiou et al. (1977) and others have noted nonetheless that



there is a good correlation between the logarithm of water



solubility of organic compounds and the logarithm of their



n-octanol-water partition coefficient.  Furthermore, this



correlation has been extended to determine a correlation between the



BCF and the solubility of a substance.  Overall, while there are a



variety of factors which make the correlation between solubility and


BCF less certain than the correlation between log Pow and BCF, the

                              2
correlation is quite strong (R  greater than .66),  and these


solubility values can be used effectively when Pow data are not


available.


                                 26

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3.0  THE PROPOSED RANKING SCHEME

     This chapter contains a scheme for classifying the potential of

substances to bioaccumulate in the food chain.  The proposed

methodology meets the following conditions:

     •  Supported by published scientific literature.

     •  Uses readily available data.

     •  Able to differentiate among different levels of potential
        bioaccumulation.

     •  Easily calculable by, or available to, a nonchemist.

     •  Easily applied to a large number of substances.

3.1  Overview of the Ranking Scheme

     The proposed scheme is illustrated as a decision tree in Figure 4.

The guiding principle of this scheme is that it is adaptable to the

data available for a substance.  Within this context, data obtained

from direct measurements of bioconcentration factors are considered to

be most reliable, and should be used first.  Within this category,

field measurements should be used before laboratory measurements.  If

BCF data are not available, data on n-octanol-water partition

coefficient should be used, if these data are not available

information on solubility should be used.  Although information on

biomagnification is considered somewhat controversial, available data

on this process are included in the scoring system to slightly elevate

the rating for those substances which may biomagnify.  If none of

these data are available, the substance is given a score of zero.  If

available data show that the substance is not found in food or biota,


                                 27

-------
               Bioconcentration
             Factor (BCF) Known'
               n-Octanol Water
             Coefficient (Log Row)
                Available and
                 < 6.00
    BCF

  > 10,000
> 1,000-9,999
  > 100-999
  >10-99
     1-9
Assigned
Value (V)

   6
   5
   4
   3
   2
   1
NO
00
                 Value = 0
Value = V +
                                                                                                                   Value = V

Yesb .




LogPow
5.5-6.0
4.5-5.49
3.2-4.49
2-3.19
0.8-1.99
<0.8
Assigned
Value (V)
6
5
4
3
2
1

k-t




                                                                       Value = V +
                                                                                                                    Value = V
Yes

Water
Solubility
>1500mg/1
501-1500 mg/1
25-500 mg/1
< 25 mg/1

Assigned
Value (V)
1
4
5
6
^ — ^^Xw Yes
I No ^


Value = V + 1C

Value -V
           Use EPA bioconcentration values provided in EPA Water Quality Criteria documents if available, otherwise use maximum value found in literature.
          __ Either as reported from published literature; or calculated by Leo's Fragment Constant Method; or from Log P Data Base.
          'If V = 6, then final score is 6, regardless of biomagnification.
                                                               FIGURE 4
                             DECISION  TREE  FOR  RANKING  SUBSTANCES  FOR  POTENTIAL
                                           TO  BIOACCUMULATE  IN THE  FOOD  CHAIN

-------
the substance is assumed to not bioaccumulate, and is assigned a




score of one in the evaluation scheme.




     Within each of the data classes (i.e., BCF, Pow, solubility),




evaluation classes of 1 to 6 are used to indicate the relative




potential of substances to bioaccumulate.  On this relative scale, a




value of 1 means that the substance probably does not bioaccumulate




in tissues, while a value of 6 indicates a high bioaccumulation




potential.  A hazardous substance would receive a value of 6 because




available data indicates that it has a very high bioconcentration




factor.  If the literature indicates that a substance may biomagnify,




then an enhancement factor of +1 is added to the value obtained from




either the BCF, Pow, or solubility data.  In no case is a value




greater than 6 assigned to a substance.  That is, if the BCF of a




substance is high enough that the substance is given a score of 6,




and the literature indicates that the substance may biomagnify, the




final score for the substance under this scheme would be 6.




     3.1.1  Classification Based on Bioconcentration Factor




     Bioconcentration factors reported in the literature range from




less than one (no bioconcentration) to a million.  For ranking




purposes within the HRS, the scheme presented in this paper uses




powers of 10 to create classes, with a BCF of 10,000 set as the




upper level (i.e., substances with a BCF of 10,000 or greater




receive a score of 6).  Ihis ranking reflects the fact that




substances such as DDT, dioxin, and PCBs, known to present high risk
                                 29

-------
to human health, have a BCF of 10,000 or higher.  For purposes of

ranking In the HRS, an assumption is made that the higher the

bioconcentration factor, the greater the potential for humans to

ingest, or for seafood to accumulate, significant amounts of a

substance, and the greater the potential threat of significant

exposure to humans via the food chain.

     3.1.2  Classification Based on Logarithm of the
            n-Octanol-Water Partition Coefficient

     If bioconcentration data are not available for a substance, the

first choice for a surrogate is log Pow data.  While log Pow data

allow a good approximation of log BCF,  they must be used with care.

     For example,  Veith  (1979) has noted that several researchers

have suggested  the relationship presented in Section 2 be used with

caution for chemicals with a molecular  weight greater than 600.

Spacie and Hamerlink (1985) have suggested that there are

limitations in  using log Pow data which are outside the 2-5 range.

Hawker and Connell (1985) have suggested that for compounds with log

Pow greater than 6, the log BCF/log Pow relationship breaks down due

to the lengthy  time required to reach equilibrium.  Others (e.g.,

Van Gestal et al., 1985) have suggested that substances with very

high values for log Pow (e.g., greater than 6.0) may not tend to

bioconcentrate due to their (potentially)  large  molecular size.   In

addition to these factors,  it has  been reported  that it is  extremely

difficult to accurately measure substances with  log  Pow greater  than

6.0 (MacKay, 1982).


                                30

-------
     Based on these considerations, substances for which log Pow




data are available, and whose log Pow is greater than 5.5 and less




than 6.0 are assigned a ranking value of 6 (see Figure 4).  This




practice is consistent with both the Michigan Site Assessment System




(1984) and Veith et al. (1980), who use a log Pow of 6.0 as the




highest (worst case) score for log Pow.  It also is consistent with




the assignment of the value of 6 to compounds with a BCF greater




than 10,000.  Furthermore, this approach will flag those substances




whose log Pow values are high enough to suggest that this value may




not be a good surrogate for the BCF of a substance.  While using a




log Pow value of 6.0 may include some substances whose BCF is lower




than might be predicted from the log Pow Information (Garten and




Trabalka, 1982), the value of 6.0 has been selected to make maximum




use of available data in the MRS screening process.  Substances for




which actual BCF data are not available and whose log Pow in greater




than 6.0 should be ranked based on solubility data (see below).  The




remaining assigned values presented in Figure 4 are derived from




Veith's (1979) regression equation and the assigned values based on




BCF data.




     In summary, this scheme would assign the highest rating values




(on the 1-6 scale) to those substances with a log Pow from 5.5




to 6.0.  The lowest value (1) would be assigned to substances with




log Pow less than 0.8.  Overall, this ranking scheme matches the six




classification categories established using bioconcentration factors




and provides a reliable indicator of potential bioaccumulation.




                                 31

-------
     Using the log Pow value for organic substances tends to err on




the conservative side; i.e., it may predict an  organic substance




will bioaccumulate when in fact it does not.  For example,  as  noted




earlier, Garten and  Trabalka (1983) found that, using log Pow  data




to predict bioconcentration, 25 percent of the  organic compounds




reviewed were "false positive" classifications  (i.e., overrated with




regard to their bioconcentration factor).  As a result, use of the




log Pow is recommended only when BCF data are not available.   It




should also be remembered that log Pow data cannot be used  for




inorganic substances.




     3.1.3  Water Solubility




     In those instances in which neither BCF nor log Pow data  are




available (or where log Pow exceed 6.0), data on water solubility




(S) can be used as a surrogate for BCF data.  In general, water




solubility is inversely related to BCF, following the general




equation (Garten and Trabalka, 1982):




              log BCF - -0.48 log S + 4.42   R2 - 0.66




     Using this relationship, BCF is projected  to be less than 100




if S is greater than about 25 mg/liter.  Although the constants in




the above equation have been subject to some dispute, van Gestal




et al. (1985), while recognizing the uncertainty in the regression,




have concluded that log Pow would be less than  3 and BCF less  than




100, if S is greater than 25 mg/liter.
                                 32

-------
     Similarly, the BCF of a substance is expected to be less than



10 if the solubility of that substance is greater than about 1,500




mg/liter.



     Once again, in order to be conservative, in this scheme a rating




value of 4 is assigned to those substances with solubility greater



than or equal to 25 mg/liter.  Again, to provide for a conservative




measure, a rating value of 1 is assigned to substances with an



S value greater than or equal to 1,500 mg/liter.




     Unfortunately, data on the S value for various organic



substances does not reliably discriminate among those substances




which tend to most strongly bioconcentrate.  In order to provide as




conservative a screening mechanism as is reasonable in this scheme,




a rating value of 6 has been assigned to substances with S values




less than 25 mg/liter.  The literature does not support further




subdivision based on solubility, so none has been attempted.



Furthermore, it has been noted that it is extremely difficult to



measure S below 10 mg/liter, so concentrations below this level may




be suspect.  It should be emphasized that under this scheme



solubility data would be used only if BCF and log Pow data are not



available.




3.2  Decision Procedures for Ranking Hazardous Substances




     This section presents the procedures for using the proposed




classification methodology.   These procedures were used to evaluate
                                 33

-------
several substances reported present at NPL facilities as an



illustration of the classification scheme.




     With reference to Figure 4, the first question in the decision




tree is to determine whether information on bioconcentration for a




specific substance is available.  If this data is available, the




substance is ranked according to the scheme presented above (e.g.,




if the BCF is greater than 10,000, the substance is scored as 6).




     Similarly, if information  on BCF is not available, the




substance is ranked on the n-octanol-water partition coefficient, if




data for it is available and log Pow is less than 6.0.  If data on




the n-octanol-water partition coefficient are not available or if




the log Pow is greater than 6.0, the substance is ranked on water




solubility.




     At each stage in the decision tree, it is necessary to ask a




second question after a "yes" response is obtained and an initial




estimate of a score for a specific substance is generated.  That is,




it is necessary to determine if the substance being considered has




been shown to blomagnify through the food chain.  If the substance




has been shown to biomagnlfy, and if the initial score obtained from




using BCF, Pow, or S data is less than 6, than 1 should be added to



the initial score to elevate the rating value because of the



biomagnification potential.   In no instance should a substance be



scored higher than 6.
                                 34

-------
     For those substances for which there is no information on BCF,




Pow, or S, a score of zero would be assigned under this scheme.   The



general rationale for assigning a "zero" in this instance is that in




employing a screening mechanism, it is not desirable to impute



knowledge concerning a substance when there is none.  Finally, it is



possible to "tag" substances for which there are no data available



for further investigation.  This investigation would allow, at




least, a laboratory analysis of the water solubility of the




substance, and could lead to a preliminary score for that substance.




     The scheme for ranking substances for which only solubility




data are available reflects the fact that this information is less



certain than either the BCF or Pow data.  Specifically, solubility




data provide a good indication of those substances which are not



likely to bloaccumulate, but information on the extent to which a



substance may bioaccumulate is not easy to determine from solubility




data alone.  If a more refined screening is desired for those



substances for which only S data is available, a detailed laboratory




analysis of either the Pow or the BCF of the substance is required.



3.3  Illustration of Proposed Ranking Scheme



     Appendix A contains a series of examples of how this scheme




would be used to rank substances.



     Table B-l gives the measured BCFs for over 130 hazardous




substances.  It also indicates substances believed to biomagnify.




Tables B-2 and B-3 present data on the log Pow.  Table B-2 is taken
                                 35

-------
from a computerized data base which is maintained by and available




from Technical Database Services, Inc. (1985).  Table B-3 relies on




either values reported in the open literature or on calculations




performed by The MITRE Corporation.  Data on water solubility are




available in publications such as Verschueren (1983).  Using these




data, a. series of substances were ranked to illustrate the use of




the decision tree in Figure 4.  This illustration is contained in




Appendix A.




     In this ranking scheme, hazardous substances with a high




potential to bioaccumulate in the food chain would have one or more




of the following characteristics:



     •  BCF of 10,000 or more




     •  Log Pow of greater than 5.5 to 6.0




     •  S less than 25 mg/liter




     This classification of a substance in terms of its potential for




bioaccumulation in the food chain is intended to be factored into a




methodology for rating human food chain exposure in the HRS.  This




rating methodology is explained separately (Saari, 1986).
                                 36

-------
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Cooley, R.V. and P.L. McCarty, 1977.  Kinetics of Microbiological
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Massachusetts.  Environmental Science and Technology 18(1):22A-27A.

Whelan, Gene and Yasuo Onishi, 1983.  In-Stream Contaminant Interaction
and Transport.  1983 International Symposium on Urban Hydrology,
Hydraulics and Sediment Control, Lexington, KY.

Whelan, G. and B.L. Steelman, 1984.  Development of Improved Risk
Assessment Tools for Prioritizing Hazardous and Radioactive Mixed
Waste Disposal Sites.  PNL-SA-12708 (in) Proceedings of the 5th DOE
Environmental Protection Information Meeting, Albuquerque, NM.

Whelan, G., B.L. Steelman, D.L. Strenge, and J.G. Droppo, 1986.
Overview of the Remedial Action Priority System (RAPS).   Pacific
Northwest Laboratories.  Presented at the First Workshop on Pollutant
Transport and Accumulation, Los Angeles, CA.

Wiedemeyer, Gary, 1986.  U.S. Fish and Wildlife Service, National
Fishery Laboratory, Personal Communications.  Seattle, WA.
                                 51

-------
Wood, J.M., 1980.  The Role of pH and Oxidation Reduction Potentials
in the Mobilization of Heavy Metals (in) Polluted Rain.  Edited by
T.Y. Toribara, M.W. Miller, and P.E. Morrow, Plenum Press, NY.

Wood, J.M., 1982.  Chlorinated Hydrocarbons:  Oxidation in the
Biosphere.  Environmental Science and Technology 16(5):291A-297A.

Wood, W.P., 1981.  Comparisons of Environmental Compartmentalization
Approaches.  OECD Chemicals Group, Exposure Analysis (EXPO) Room.
Doc. 80.21.  Organization for Economic Cooperation and Development,
Paris, France.

Wong, M.L. and F.Y. Tarn, 1984.  Sewage Sludge for Cultivating
Freshwater Algae and the Fate of Heavy Metal at Higher Trophic
Organisms.  Archives Hydrobiology 100(4) :423-30.

Young, D.R., Tsu-Kai J., and G.P. Hershelman, 1980.  Cycling of Zinc
in the Nearshore Marine Environment (in) Zinc in the Environment.
Edited by J.O. Nriagu.  John Wiley and Sons, NY.
                                 52

-------
                             APPENDIX A

               CLASSIFICATION OF HAZARDOUS SUBSTANCES
                   FOR POTENTIAL TO BIOACCUMULATE
     This appendix illustrates the use of the decision tree presented

in Figure 4 (Section 3).  The substances included in this appendix

were selected for their ability to illustrate the use of the decision

tree rather than for any particular importance of the individual

substances.  Fifteen substances were chosen for this illustration.

These substances include:

      1.  Acenaphthene
      2.  Benzo(a)pyrene
      3.  Cadmium
      4.  DDT
      5.  Dichlorome thane
      6.  Dichlorobiphenyl
      7.  Copper
      8.  Vinyl chloride
      9.  Xylene
     10.  N-Pentane
     11.  Lorsban
     12.  Dichlorobiphenyl
     13.  Lead
     14.  Thiourea
     15.  Cyclohexanone

     The process for following the decision tree presented in Section 3

is illustrated in Table A-l.  In all instances, the BCF data should be

used first, then the log Pow data, and if neither of these is

available, the S data.  For Benzo(a)pyrene, for example, the score

based on the BCF would be 5.  Since the substance has been reported to

bioaccumulate, 1 is added to this factor for a final score of 6.  For

DDT, the score based on the BCF would be 6, the maximum allowable

regardless of the fact the substance bioaccumulates.

                                 53

-------
                                  TABLE A-l
          BIOACCUMULATION RATING BASED ON PROPOSED RATING SCHEME
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
Substance
Acenaphthene
Benzo( a)pyrene
Cadmium
DDT
Dichloromethane
DI chlorobisphenyl
Copper
Vinyl chloride
Xylene
N-Pentane
Lorsban
Di chlorobiphenyl
Lead
Thiourea
Cyclohexanone
BCF
387
2,177
1,000-3,999
10,000
5
214
1,000
1.2
21-23
—
—
215
924
—
—
Log Pow S Biomagnify
— * — No
— 0.003 mg/1 Yes
Yes
0.0031 mg/1 Yes
20,000 mg/1 No
— No
— — No
— 1,100 mg/1 No
3.15 198 mg/1 No
3.39 — No
4.96 — No
— No
No
— 91.8 mg/1 No
3.44 55 mg/1 No
Rating
Value
4
6
6
6
1
4
5
2
3
3
5
4
4
4
3
*Indicates data not readily available for inclusion in table.
                                      54

-------
                             APPENDIX B




         SUMMARY OF DATA COLLECTED ON  HAZARDOUS SUBSTANCES






     Table B-l presents the findings  from a literature review to




identify substances which may bioaccumulate in food chains.   The




automated EPA NPL technical data base was queried to identify




substances found at NPL sites.  Most  of the substances subsequentially




researched were found at five or more NPL sites.  The collected




literature was scanned to determine which of these substances have




been reported to bioaccumulate in biota.   Most of the tabulated BCF




data are for fish,  but several reflect measurements of plants or




animals.  Some BCFs contained in Table B-l are generic values as




presented in the referenced literature.  BCFs are for edible  tissue




(e.g., meat or whole fish)  not for liver  concentrations.




     Table B-2 presents a range of log Pow values from a  computerized




database (Technical Database Services, Inc., 1985).




     For a limited number of substances found at  waste sites, and




which are not included in the computerized data base, MITRE calculated




log Pow values or found log Pow values in the literature.  These




values are reported in Table B-3.
                                 55

-------
                              TABLE B-l




DATA COLLECTED ON HAZARDOUS SUBSTANCES AND POTENTIAL BIOACCUMULATION
Substance Name
Acenaphthene
Acrolein
Acrylonitrile
Aldrin
Aluminum and
compounds
Aniline
Anthracene
Antimony and
compounds , NOS
Antimony trioxide
Arsenic and
compounds
CAS Number
00083-32-9
0107-02-8
00107-13-1
00309-00-2
07429-70-5
0062-53-3
00120-12-7
07440-36-0
1309-64-4
07440-38-2
Bioconcentration
Factor Biomagnifies
387 fish
242
344 fish
215
48 fish
30
greater than 4000
13,390 clam
2-3.5 cattle
3,000-11,000 fish
4,600-6,300
10,000-15,000 yes
10 in fish
6 fish
0.5
917
100-10,000
greater than 4,000
less than 1
40 fish
16,000 invertebrates
700-999
1-3 plants
10,000 fish
0-4 fish
333 fish
44 fish
Source
Number
3/22
42
3/22
42
3/22
42
4
31
11/38
11
22
10
39
26
42
25
32
4
42/22
32
32
4
9
17
22
39
42
                                 56

-------
TABLE B-l (Continued)
Substance Name
Atrazine


Barium

Benzene


Benzidine


Benzoic acid
Benzo(a)pyrene
Beryllium and

Biphenyl
Bis (2-chloroethyl)
ether
Boron and compounds
Bromine
Butylbenzyl
phthalate
CAS Number
01912-24-9


07440-39-3

0071-43-2


0092-87-5


00065-85-0
00050-32-8
7440-41-7

00092-52-4
0011-44-4
07440-42-8
07726-95-6
00085-68-7
Bioconcentration
Factor Biomagnifies
2-4 no
less than 8
3
0.6-5.2
4
3.5 eels
less than 10 fish
5.2
38-44
83
87 fish
21 fish no
37 mosquito
2,177 snail
930 fish yes
less than 1 plant
30
2-100 fish no
19
100
340
437
11 fish
6.9 fish
0.22 in fish
0.015-420 fish
772 fish
279
Source
Number
17
25
33
30
35
21
33
42
22
33
28
26
20
20
20
38
42
20/39
22
32
24
25
3
28
39
23
3
22
          57

-------
TABLE B-l (Continued)
Substance Name
Cadmium








Cap tan
Carbon
tetrachloride


Cerium
Chlordane




Chlorobenzene




Chlorobiphenyl
Chloroform
2-Chlorophenol
CAS Number
074409-43-9








00133-06-2
0056-23-5



07440-45-1
00057-74-9




00108-90-7




02051-62-9
00067-66-3
00095-57-8
Bioconcentration
Factor Biomagnifies
1,000-3,999 yes
1,100-2,400 fish
30,000 algae no
7.5 fish
8.9 muscle
649 freshwater fish
226 saltwater fish
1,220-2,040 oyster
64-81 fish
less than 300
30 fish
17-39 fish
30
18
1-10 fish
0.1-0.5 cattle
8,000-11,400 fish
4,702
4,810 clam
14,000
645 fish
1,000-10,000
12
10
650
490
6 fish
214 fish
Source
Number
4
13
17
17
17
22
22
22
42/28
4
3
13
22
42
23
11
11
22
31
42
12
32
24
42
26
24
3/22
3/22
          58

-------
TABLE B-l (Continued)
Substance Name
Chromium and
compounds


Cobalt and
compounds

Copper and
compounds




Cyanides (NOS)

DDD

DDE,p,p'


DDT,p,p'





1, 2-Dichlorobenzene

1 , 3-W.chlorobenzene
1 , 4-Dichlorobenzene

CAS Number
07440-47-3



07440-48-4


07440-50-8





00057-12-5

72-54-8

00072-55-9


00050-29-3





00095-50-1

00541-73-1
00106-46-7

Bioconcentration
Factor Biomagnifies
8,500 algae
300 algae no
less than 1-2.5 fish
125-200 salt oyster
6-10 plants
6,760 fish yes
320 fish
1 plant
1,000-5,000 marine
1-290 fish
9,960 shellfish no
200-320 in fish
36
none
2.3
80 x 103
1,000-100,000 yes
62 x 102-103 . yes
51,000 fish
10,000-100,000
greater than 4,000
0.9 cattle
61,600-84,500 fish
17,870
16,950 yes
54,000 fish
56-89 fish
60-215
66 fish
37-60 fish
89-215
Source
Number
22
10
22/17
22
9
34
39
9
10
22
22
39
42
22/43
36/38
10
32
18
28
32
4
11
11
22
26/18
28
42/3
22/24
3
42/3
22/24
         59

-------
TABLE B-l (Continued)
Substance Name
3, 3-Dlchlorobenzene
Dichlorobiphenyl
1 , 2-Dichloroe thane
1 , 1-Dichloroethylene
Dichlorome thane
2 , 4-Dichlorophenol
2 , 4-Dichlorophenoxy-
acetic acid (2-4-D)
1 , 3-Dichloropropene
Dieldrin
Diethyl phthalate
Diethylhexyl
phthalate
Di-N-butyl
phthalate
Di-N-octyl phthalate
Dimethyl phthalate
2 , 4-Dimethylphenol
Dinitrotoluene
CAS Number


00107-06-2
00075-35-4
00075-09-2
00120-83-2
00094-75-7
00542-75-6
00060-57-1
00084-66-2
00117-81-7
00084-74-2
00117-84-0
00131-11-3
00105-67-9
2532-114-6
Bioconcentration
Factor Biomagnifies
312 fish
215
2 fish
1.2
5.6 fish
5 fish
41 fish
17-45xlO~5 cattle no
20 fish
1.9 fish
greater than 4,000 yes
1.6-3 cattle no
4,400-5,800 fish
1,557
3,540 clam
117 fish
38
14
9,400
57 fish
150 fish
3.8 fish
Source
Number
28
24
3
42
28
28
28
11
11
28
4
11
11
22
31
3
22
22
22
3
3/22
28
          60

-------
TABLE B-l (Continued)
Substance Name
Dioxin
Diphenylamine , N,N
1 , 2-Diphenylhydrazine
Endosulfan
Endrin
Ethylbenzene
Fluor anthene
Fluorene
Heptachlor
Heptachlor
epoxide
CAS Number
01746-01-6
00122-39-4
00122-66-7
00115-29-7
00072-20-8
00100-41-4
00206-44-0
00086-73-7
00076-44-8
01024-57-3
Bloconcentratlon
Factor Biomagnifies
10,000
5,800
greater than 4,000
5,000 fish
130-9,000 plants
30 fish
25 fish
50-30,000 no
greater than 4,000
1.2-1.3 cattle
1,400-4,050 fish yes
0.4 lobster
1,324
37.5 fish
1,150 fish
100-10,000
1,300 fish
10,630 clam
15,700 fish
greater than 4,000
0.4-0.6 cattle
2,000-17,400 fish
9,500 freshwater fish
7,500 saltwater fish
102-10*
2,330 clam
14,400 fish
Source
Number
32
42
4
28
32
28
28
32
4
11
11
15
22
28
28
32
28
31
28
4
11
11
22
22
32
31
28/22/27
         61

-------
TABLE B-l (Continued)
Substance Name CAS Number
Hexachlorobenzene 00118-74-1
Hexachlorobutadiene 00087-68-3
Hexachlorocyclo- 00608-73-1
hexane (NOS)
Hexachlorocyclo- 00077-47-4
pentadiene
Hexachloroethane 00067-72-1
Iron and compounds 07439-89-6
Isophorone 00078-59-1
Kepone 00143-50-0
Bioconcentration
Factor Biomagnifies
1,166 fish yes
8,600
22,000
1,166
5,500-21,900
19
3-4.3
1000
10-500
480 fish
130 oyster
352 fish
300-699
448 fish
11
300-2,000
139 fish
87
1,000-5,000 fish
10,000-100,000
invertebrates
100 fish
7 fish
7-16 fish
5,000-7,000 oyster
440-1,060 crab
4,500-11,700 shrimp yes
3.9-10.5 yes
8,400 (estimate from
water solubility)
2,600-7,600
Source
Number
12/43
24
22
24
27
22
42/28
32
20
20
20
22
4
20
22
32
3
42
10/38
10
39
22/3
36
40
40
35/40
17
24
29
          62

-------
                           TABLE B-l (Continued)
Substance Name
Lead







Lindane





Magnesium and
compounds
Manganese and
compounds
Mercury



Mercuric chloride

Methoxychlor



Bioconcentration
CAS Number Factor Biomagnifies
07439-92-1 0.1 plants
17 snail
0.2-2 plants
0.1-0.3 fish
42-45 fish
924 bivalves
300 fish
49
00058-89-9 0.4-0.7 cattle
2,610
325-560 fish
130-170 shellfish
352 fish
754
07439-95-4 50-93

07439-96-5 0.2-0.3 fish
660 fish no
10045-94-0 greater than 4,000- yes
5,500
13,000 yes
1,000-10,000
07487-94-7 1,800-4,994 fish
10,000 oyster
00072-43-5 less than 300
0 cattle
185-1,550 fish
8,300
Source
Number
14
22
9
14
22
22
39
42
11
31
11
20
22
33
39

14
39
4/28

42
10/22
22
22
4
11
11
25
Methyl mercuric
chloride

Metfiyl parathion
11,000-85,700 fish
45 fish
yes
           22
           28
                                     63

-------
                           TABLE  B-l  (Continued)
Substance Name
Mirex
Molybdenum


Naphthalene




Nickel and
compounds





Nitrobenzene

4-Nitrophenol

N-Nitrosodi-
phenylamine
Parathion
Pentachlorobenzene



CAS Number
02385-85-6
07439-98-7


00091-20-3




07440-02-0






00098-95-3

00100-02-7

00086-30-6

00056-38-2
00608-93-5



Bioconcentration
Factor Biomagnifies
84 fish yes
44-50 plants
10 fish
20-100 marine
100
131
427
5,000 copepods yes
10
greater than 4,000
425-467 plants
100-200
300 fish no
30 fish
84 oyster
47
29 fish
3
57
3
217 fish

24
3,400 fish
5,000
3,400
2,125 fish
Source
Number
15
9
39
10
20
25
25
22/17
42
4
9
10
17
22
22
42
26
42
33
42
3

42
1
24
22
28
Pentachloroethane
00076-01-7
67 fish
                                    64

-------
TABLE B-l (Continued)
Substance Name
Pentachlorophenol





Phenanthrene


Phenol
Plutonium
Plutonium-238

Plutonium-239



Polychlorinated
biphenyls




Pyrene



Radium and
compounds
Bioconcentration
CAS Number Factor Biomagnifies
00087-86-5 greater than 4,000
296 fish
770
200 (approximately)
1,050 fish
31
00085-01-8 325
2,630
100-10,000
00108-95-2 1.4
350
1-15 fish
230-520 shellfish
15117-48-3 6 x 10~5 land
1,000 marine yes
2-15 fish muscle
1,100 fish gut
01336-36-3 4 x 10^
greater than 4,000
2,500 shrimp
105-106
10,400 yes
31,200 yes
00129-00-0 2,700
2,800 (log Pow
estimate)
10,000
07440-14-4 0.9 x 103
5-16 plants
Source
Number
4
12/26
25
22
33
33
25
28
32
42
34
1
1
5
13
13
13
2
4
2
16
22
42
25
22

32
6
9
          65

-------
TABLE B-l (Continued)
Substance Name
Selenium




Silver


Sodium
Strontium



Sulfur
1,2,4, 5-Te trachloro-
benzene

1,1,2, 2-Tetrachlor o-
ethane
1,1,2, 2-Tetrachlor o-
ethene

2,3,4,6 -Tetrachlor o-
phenol
Thallium

CAS Number
07782-49-2




07440-22-4


07440-23-5
07440-24-6



07704-34-9
00095-94-3


00079-34-5

00127-18-4


00058-90-2

07440-28-0

Bioconcentration
Factor Biomagnifies
1-40
16 fish
78-104 plants
8-20 fish yes
167 fish no
10-3,000 fish
3,080 fish
28 fish
0.067-100 fish
171 yes
1-10 soft tissue
1,000 bone
200
2-5 marine
1,800 fish
1,125 fish
4,500
5-8 fish
42 fish
100 no
greater than 100 in
liver
240 fish

100,000
116
Source
Number
8
28
9
22/41
39/17
20
28
22
23
6
10
10
34
10
3
28
24
3/42
28
32/20
32/20

28

32
42
          66

-------
                           TABLE B-l  (Continued)
Substance Name
Tin and compounds
Titanium and
compounds
Toluene
Toxaphene
Trichlorobenzene
1,2,3-Trichloro-
benzene
1,2,4-Trichloro-
benzene
1,1,1-Trichloro-
e thane
Bioconcentration
CAS Number Factor Biomagnifies
07440-31-5 0.5 fish
3.5 invertebrates
3,000 fish
1,000
07440-32-6 40-1,000 marine
00108-88-3 13.2 eel
11
08001-35-2 greater than 4,000
10,000 fish yes
4,372-6,150
26,400
13,100
00050-31-7 1,700 in fish
00087-61-6 182 fish
890-2,300
00120-82-1 100-1,000
2,800 fish
491
183 fish
890-2,300
00071-55-6 9 fish
11
5-5.6 fish
Source
Number
17
17
39
39
10
21
42
4
18
22
24
42
39
22
24/33
32
28
24/33
17
27
3
42
28
1,1,2-Trichloro-
ethane
00079-00-5
4.5
3/42
                                     67

-------
                           TABLE B-l (Continued)
Substance Name
Trichloroethylene
Trichlorophenol
Trichlorophenoxy
acetic acid (2,4,5-T)
Tris
Uranium and
compounds
Vanadium and
compounds
Vinyl chloride
Xylene
CAS Number
00079-01-6
25167-82-2
00093-76-5
00126-72-7
07440-61-1
07440-62-2
00075-01-4
01330-20-7
Bioconcentration
Factor Biomagnifies
88 fish
11-17
2.7
110-150 fish
4-19x10"* cattle no
25-43 fish
2.7
3-6 plants
10 fish
less than 0.03 animals
7-11 plants
20-100 marine
2-28 fish
1.2
21.4-23.6 eel
Source
Number
33
42/22
23
28
11
11
23
9
9/39
9
9
10
13
42
21
Zinc and compounds    07440-66-6
Zirconium
07440-67-7
less than 300
47
1,000-5,000
0.33-0.48
60-100

3.3-200
                                     no
                                                           yes
4
42
10
14/37
22

23
                                     68

-------
                       TABLE B-l (Concluded)
Sources:
 (1)  National Research Council, 1975
 (2)  Thomann & Connolly, 1984
 (3)  Veith et al., 1980
 (4)  Michigan Water Resources Commission, 1984
 (5)  Garten & Dahlman, 1978
 (6)  Lemons, 1975
 (7)  Dawson et al., 1983
 (8)  Robberecht et al., 1983
 (9)  Dreesen & Williams, 1982
(10)  Wilber, 1969 (in Brown, 1985)
(11)  Kenaga, 1980
(12)  U.S. EPA, 1977
(13)  Holdway et al., 1983
(14)  Drifmeyer & Odum, 1975
(15)  Reish et al., 1982
(16)  Weaver, 1984
(17)  Kay, 1984
(18)  Niethammer et al., 1984
(19)  Oliver and Nicol, 1982
(20)  Callahan et al., 1979
(21)  Ogata & Miyake, 1978
(22)  U.S. EPA, 1980 (updated with 1985 final)
(23)  U.S. NRC, 1977
(24)  Kenaga & Goring (in Lyman, 1982)
(25)  Southworth et al., (in Lyman, 1982)
(26)  Lu & Metcalf, 1975
(27)  Vieth et al., 1979
(28)  ICF, Inc., 1985
(29)  Reish et al., 1983
(30)  Guthrie & Davis, 1979
(31)  Hartley and  Johnson, 1983
(32)  Ghisalba, 1983
(33)  Klein et al., 1984
(34)  Oakes et al., 1982
(35)  Banner et al., 1983
(36)  U.S. EPA, 1979
(37)  Guthrie et al., 1979
(38)  U.S. EPA, 1985
(39)  Hildebrand and Cushman, 1976
(40)  Macek et al., 1979
(41)  Wiedemeyer,  1986
(42)  ICF, Inc., 1985b
(43)  Oliver and Niimi, 1983
                                69

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               TABLE B-2




LOGARITHM N-OCTANOL-WATER COEFFICIENTS
Substance Name
1,1,1-TRICHLOROETHANE /BPA/
1,1,2, 2 -TETRACHLOROETHANE
1,1, 2 -TRICHLOROTRIFLUOROETHANE
1,1-DICHLOROETHANE /BPA/
1 , 1-DICHLOROETHYLENE/VINYLIDINE CHLORIDE/
1 , 2 , 3-TRICHLOROBENZENE
1,2, 3 -TRIMETHYLBENZENE
1,2,4, 5 -TETRACHLOROBENZENE
1 , 2 , 4-TRICHLOROBENZENE
1,2,4- TRIMETHYLBENZENE
1,2,5 , 6-DIBENZANTHRACENE
1,2-DIBROMOETHANE
1,2-DICHLOROETHANE /BPA/
1,2-DICHLOROETHYLENE -CIS
1,2-DICHLOROETHYLENE -TR
1,3, 5 -TRIMETHYLBENZENE/MESITYLENE/
1,3, 5 -TRINITROBENZENE
1,3-BUTADIENE /BPA/
1,3-DICHLOROBENZENE
1 , 4-NAPHTHOQUINONE
(Source: Technical Database Services, Inc., 1985)
70
CAS Number
71-55-6
79-34-5
76-13-1
75-34-3
75-35-4
87-61-6
526-73-8
95-94-3
120-82-1
95-63-6
53-70-3
106-93-4
107-06-2
156-59-2
156-60-5
108-67-8
99-35-4
106-99-0
541-73-1
130-15-4


Log Pow
2.49
2.39
3.16
1.79
2.13
3.99
3.66
4.82
4.12
3.78
6.50
1.96
1.48
1.86
2.09
3.42
1.18
1.99
3.38
1.78



-------
TABLE B-2 (Continued)
Substance Name
1-BUTENE /BPA/
1-CHLOROBUTANE /BPA/
1- ETHYL- 1-NITROSOUREA/ENU/
1 - ETHYL- 2 -METHYLBENZENE
L-METHYL-1-NITROSOUREA
1-PROPENE.l-PHENYL
2,2' -DICHLOROETHYLETHER
2,2,2- TRICHLORO -1,1- ETHANEDIOL/CHLORALHYDRATE
2,3,4, 5 -TETRACHLOROPHENOL
2,3,4,6- TETRACHLOROPHENOL
2 , 3 , 4-TRICHLOROPHENOL
2 , 3 , 4-TRICHLOROPHENOL
2,3,5, 6 -TETRACHLOROPHENOL
2,3, 5 -TRICHLOROPHENOL
2,3, 6 -TRICHLOROPHENOL
2,3-DICHLOROPHENOL
2,4,5- TRICHLOROPHENOL
2,4, 6 -TRICHLOROPHENOL
2,4, 6 -TRINITROTOLUENE
2 , 4-DICHLOROPHENOL
CAS Number
106-98-9
109-69-3
759-73-9
611-14-3
684-93-5
637-50-3
111-44-4
302-17-0
4901-51-3
58-90-2
15950-66-0
15950-66-0
935-95-5
933-78-8
933-75-5
576-24-9
95-95-4
88-06-2
118-96-7
120-83-2
Log Pow
2.40
2.64
-0.15
3.53
-0.16
3.35
1.29
1.61
5.05
4.10
3.51
3.51
4.88
4.56
3.46
2.52
3.72
3.62
1.60
3.30
         71

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TABLE B-2 (Continued)
Substance Name
2,4- DIMETHYLPHENOL
2,4-DINITROPHENOL
2,4- DINITROTOLUENE
2,5-DICHLOROPHENOL
2 , 6-DICHLOROPHENOL
2-BUTANONE
2-HEXANONE
2-NITROGUANIDINE
2-PENTANONE
2 -PICOLINE/2 -METHYL PYRIDINE/
3,3' -DICHLOROBENZIDINE
3,4,5- TRICHLOROPHENOL
3 , 4-DICHLOROPHENOL
3-METHIO-4-AMINO-6-T-BU-l,2,4-TRIAZINE-5-ONE
3-METHIO-4-AMINO-6-T-BU-l,2,4-TRIAZINE-5-ONE
4 , 4 ' - 1 - PROPYLIDENE-DIPHENOL/DIPHENYLOLPROPANE
4,4'-PCB
4,4'-STILBENEDIOL,A,A'-DIETHYL/DES/
4-AMINOPYRIDINE
4 - NITROQUINOLINE - 1 - OXIDE
CAS Number
105-67-9
51-28-5
121-14-2
583-78-8
87-65-0
78-93-3
591-78-6
556-88-7
107-87-9
109-06-8
91-94-1
609-19-8
95-77-2
21087-64-9
21087-64-9
80-05-7
2050-68-2
56-53-1
504-24-5
56-57-5
Log Pow
2.30
1.50
1.98
3.20
2.34
0.29
1.38
-0.89
0.91
1.11
3.51
4.01
2.86
1.70
1.70
3.32
5.58
5.07
0.26
1.02
          72

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TABLE B-2 (Continued)
Substance Name
6-AMINOCHRYSENE
7 , 12 -DIMETHYLBENZ( A) ANTHRACENE
A , A , A- TRICHLOROTOLUENE
A-CHLOROTOLUENE
A-NAPHTHYLAMINE
A- NAPHTHYLTHIOUREA/ANTU/
ACENAPHTHENE
ACETANILIDE , 4 - ETHOXY/PHENACETIN/
ACETIC ACID
ACETIC ACID, ETHYL ESTER
ACETIC ACID, METHYL ESTER
ACETIC ACID .BUTYL ESTER
ACETIC ACID.PROPYL ESTER
ACETONE
ACETONITRILE
ACETOPHENONE
ACETYLENE /BPA/
ACRIDINE
ACRYLAMIDE
ACRYLIC ACID, BUTYL ESTER
CAS Number
218-01-9
57-97-6
98-07-7
100-44-7
134-32-7
86-88-4
83-32-9
62-44-2
64-19-7
141-78-6
79-20-9
123-86-4
109-60-4
67-64-1
75-05-8
98-86-2
74-86-2
260-94-6
79-06-1
141-32-2
Log Pow
4.98
5.80
2.92
2.30
2.25
1.66
3.92
1.58
-0.17
0.73
0.18
1.82
1.24
-0.24
-0.34
1.73
0.37
3.40
-0.67
2.36
         73

-------
TABLE B-2 (Continued)
Substance Name
ACRYLIC ACID, METHYL ESTER
ACRYLIC ACID, ETHYL ESTER
ACRYLONITRILE
ADIPIC ACID
ALACHLOR/LASSO/
ALACHLOR/LASSO/
ALDICARB/TEMIK/
ALLYL ALCOHOL
ANILINE
ANILINE ,N -METHYL
ANTHRACENE
ARGON /BPA/
AZOBENZENE , 4 - DIMETHYLAMINO
B-NAPHTHYLAMINE
BENZALDEHYDE
BENZENE
BENZIDINE
BENZO(A)PYRENE
BENZOIC ACID
BENZONITRILE
CAS Number
96-33-3
140-88-5
107-13-1
124-04-9
15972-60-8
15972-60-8
116-06-3
107-18-6
62-53-3
100-61-8
120-12-7
7440-37-1
60-11-7
91-59-8
100-52-7
71-43-2
92-87-5
50-32-8
65-85-0
100-47-0
Log Pow
0.80
1.32
-0.92
0.08
3.52
3.52
0.70
0.17
0.90
1.82
4.45
0.74
4.58
2.28
1.48
2.13
1.34
5.97
1.87
1.56
          74

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TABLE B-2 (Continued)
Substance Name
BENZOPHENONE
BENZOTHIAZOLE
BIPHENYL
BROMOBENZENE
BROHOCHLOROMETHANE
BUTANE /BPA/
BUTANOL
BUTOXYETHANOL
BUTYL BENZOATE
BUTYLAMINE
BUTYLBENZENE
BUTYLBENZYLPHTHALATE
BUTYRALDEHYDE
CAPTAN
CARBOFURAN
CARBON TETRACHLORIDE /BPA/
CHLORAMBUCIL/NCS 3088/
CHLOROBENZENE
CHLORODIFLUOROMETHANE/FREON - 2 2/ BPA/
CHLOROFORM
CAS Number
119-61-9
95-16-9
92-52-4
108-86-1
74-97-5
106-97-8
71-36-3
111-76-2
136-60-7
109-73-9
104-51-8
85-68-7
123-72-8
133-06-2
1563-66-2
56-23-5
305-03-3
108-90-7
75-45-6
67-66-3
Log Pow
3.18
2.01
3.95
2.99
1.41
2.89
0.88
0.83
4.21
0.88
4.26
3.97
0.88
2.35
2.32
2.83
1.70
2.84
1.08
1.97
         75

-------
TABLE B-2 (Continued)
Substance Name
CHLOROTRIFLUOROMETHANE/FREON 13/BPA/
CYCLOHEXANE /BPA/
CYCLOHEXANOL
CYCLOHEXANONE
CYCLOHEXYLAMINE
CYCLOPROPYLBENZENE
CYTOXAN/CYCLOPHOSPHAMIDE/
DDE
DDT
DECANE
DEMETONTHIOL
DI - ( P - AMINOPHENYL) METHANE
DI - 2 - ETHYLHEXYLPHTHALATE
DI - I - PROPANOLAMINE
DIBENZOFURAN
DIBUTYL ETHER
DICHLORODIFLUOROMETHANE/FREON - 12/BPA/
DICHLOROFLUOROMETHANE/FREON - 2 1/ BPA/
DICOFOL
DIETHANOLAMINE
CAS Number
75-72-9
110-82-7
108-93-0
108-94-1
108-91-8
873-49-4
50-18-0
72-55-9
50-29-3
124-18-5
298-04-4
101-77-9
117-81-7
110-97-4
132-64-9
142-96-1
75-71-8
75-43-4
115-32-2
111-42-2
Log Pow
1.65
3.44
1.23
0.81
1.49
3.27
0.63
4.87
3.98
5.01
1.93
1.59
3.98
-0.82
4.12
3.21
2.16
1.55
3.54
-1.43
          76

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TABLE B-2 (Continued)
Substance Name
DIETHYLAMINE
DI ETHYLPHTHALATE
DIMETHOATE
DIMETHOXYMETHANE
DIMETHYLAMINE
DIMETHYLFORMAMIDE
DIMETHYLPHTHALATE
DINOSEB
DIOXANE
DIPHENYLAMINE
DIPHENYLNITROSAMINE
DIPROPYLAMINE
DIPROPYLNITROSAMINE
DODECANOIC ACID/LAURIC ACID/
ETHANE /BPA/
ETHANE -1,2- DIOL/ETHYLENE GLYCOL/
ETHANOLAMINE
ETHION
ETHYL CHLORIDE/BPA/
ETHYL ETHER
CAS Number
109-89-7
84-66-2
60-51-5
109-87-5
124-40-3
68-12-2
131-11-3
88-85-7
123-91-1
122-39-4
86-30-6
142-84-7
621-64-7
143-07-7
74-84-0
107-21-1
141-43-5
563-12-2
75-00-3
60-29-7
Log Pow
0.57
2.47
0.50
0.00
-0.38
1.01
1.56
2.30
-0.42
3.34
3.13
1.73
1.36
4.20
1.81
-1.93
-1.31
5.07
1.43
0.77
         77

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TABLE B-2 (Continued)
Substance Name
ETHYLAMINE
ETHYLBENZENE
ETHYLENE
ETHYLENE OXIDE /BPA/
FLUORANTHENE
FLUORENE
FLUOROACETAMIDE
FLUOROFORM/BPA/
FORMALDEHYDE
FORMALDEHYDE
FORMIC ACID
FURAN /BPA/
FURFURAL
GLYCEROL /BPA/
GLYCERYL TRINITRATE
HEPTANE
HEXACHLORO -1,3- BUTADI ENE
HEXACHLOROBENZENE
HEXACHLOROCYCLOHEXANE , ALPHA ISOMER//124/356/
HEXACHLOROCYCLOHEXANE , BETA ISOMER//135/246/
CAS Number
75-04-7
100-41-4
74-85-1
75-21-8
206-44-0
86-73-7
640-19-7
75-46-7
50-00-0
50-00-0
64-18-6
110-00-9
98-01-1
56-81-5
55-63-0
142-82-5
87-68-3
118-74-1
319-84-6
319-85-7
Log Pow
-0.13
3.15
1.13
-0.30
5.20
4.18
-1.05
0.64
0.35
0.35
-0.54
1.34
0.41
-1.76
1.62
4.66
4.74
4.13
3.80
3.78
          78

-------
TABLE B-2 (Continued)
Substance Name
HEXACHLOROCYCLOHEXANE/BHC/ GAMMA ISOMER
HEXACHLOROCYCLOPENTADIENE
HEXACHLOROETHANE
HEXACHLOROPHENE /PKA2=11.33/
HEXANE
HYDRAZINE
HYDRAZOBENZENE
HYDROCYANIC ACID /BPA/
I-BUTANOL
I-PROPANOL
I-PROPYLAMINE
IMIDAZOLIDONE , 2 -THIO/ETHYLENETHIOUREA/
INDENE
ISOPROPYLBENZENE
M-CHLOROPHENOL
M-DIHYDROXYBENZENE/RESORCINOL/
M-DINITROBENZENE
M-XYLENE
MALATHION
MALEIC ACID HYDRAZIDE /3 , 6-DIHYDROXYPYRIDAZIN
CAS Number
58-89-9
77-47-4
67-72-1
70-30-4
110-54-3
302-01-2
122-66-7
74-90-8
78-83-1
67-63-0
75-31-0
96-45-7
95-13-6
98-82-8
108-43-0
108-46-3
99-65-0
108-38-3
121-75-5
123-33-1
Log Pow
3.61
5.04
3.82
2.62
3.90
-2.07
2.94
-0.25
0.76
0.05
-0.03
-0.66
2.92
3.66
2.50
0.80
1.49
3.20
2.89
-0.84
          79

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TABLE B-2 (Continued)
Substance Name
METHACRYLIC ACID, ETHYL ESTER
METHACRYLIC ACID, METHYL ESTER
METHACRYLONITRILE
METHANE /BPA/
METHANOL
METHOMYL
METHOMYL
METHOXYCHLOR
METHYL BROMIDE /BPA/
METHYL CHLORIDE/BPA/
METHYL IODIDE
METHYLAMINE
METHYLHYDRAZINE
METOLACHLOR
METOLACHLOR
MORPHOLINE
MUSCIMOL
N , N - DIMETHYLANILINE
N - METHYLCARBAMATE , 1 - NAPHTHYL
N-NITROSODIBUTYLAMINE
CAS Number
97-63-2
80-62-6
126-98-7
74-82-8
67-56-1
16752-77-5
16752-77-5
72-43-5
74-83-9
74-87-3
74-88-4
74-89-5
60-34-4
51218-45-2
51218-45-2
110-91-8
2763-96-4
121-69-7
63-25-2
924-16-3
Log Pow
1.94
1.38
0.68
1.09
-0.64
1.08
1.08
3.31
1.19
0.91
1.69
-0.57
-1.05
3.13
3.13
-1.08
-2.39
2.31
2.36
1.92
          80

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TABLE B-2 (Continued)
Substance Name
N-NITROSODIETHYLAMINE
N-NITROSODIMETHYLAMINE
N-NITROSOPIPERIDINE
N-NITROSOPYRROLIDINE
NAPHTHALENE
NITROBENZENE
NITROETHANE
NITROMETHANE
NONANE
0-AMINOPHENOL
0-CHLOROPHENOL
0-CHLOROTOLUENE
0-DIBUTYLPHTHALATE
0 - DICHLOROBENZENE
0-DINITROBENZENE
0 - DIOCTYLPHTHALATE
0- ETHYL CARBAMATE/URETHANE/
0-HYDROXYBENZOIC ACID/SALICYLIC ACID/
0-METHYLBENZENESULFONAMIDE
0-NITROPHENOL
CAS Number
55-18-5
62-75-9
100-75-4
930-55-2
91-20-3
98-95-3
79-24-3
75-52-5
111-84-2
95-55-6
95-57-8
95-49-8
84-74-2
95-50-1
528-29-0
117-84-0
51-79-6
69-72-7
88-19-7
88-75-5
Log Pow
0.48
-0.57
0.63
-0.19
3.59
1.85
0.18
-0.33
4.51
0.62
2.17
3.42
4.72
3.38
1.58
5.22
-0.15
2.26
0.84
1.26
         81

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TABLE B-2 (Continued)
Substance Name
0-PHTHALIC ACID
0-TOLIDINE
0-XYLENE
OCTANE
OCTANOL
P-AMINOPHENOL
P-CHLOROANILINE
P-CHLOROBIPHENYL
P-CHLOROPHENOL
P-DICHLOROBENZENE
P - DIHYDROXYBENZENE/HYDROQUINONE/
P-DINITROBENZENE
P-NITROANILINE
P-NITROPHENOL
P-NITROTOLUENE
P-XYLENE
PARALDEHYDE
PARAOXON
PARATHION
PENTACHLOROBENZENE
CAS Number
88-99-3
119-93-7
95-47-6
111-65-9
111-87-5
123-30-8
106-47-8
2051-62-9
106-48-9
106-46-7
123-31-9
100-25-4
100-01-6
100-02-7
99-99-0
106-42-3
123-63-7
311-45-5
56-38-2
608-93-5
Log Pow
0.73
2.34
2.77
5.18
3.15
0.04
1.83
4.90
2.35
3.39
0.59
1.46
1.39
0.76
2.37
3.15
0.67
1.69
2.15
5.52
          82

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TABLE B-2 (Continued)
Substance Name
PENTACHLOROETHANE
PENTACHLORONITROBENZENE/QUINTOZENE/
PENTACHLOROPHENOL
PENTANE /BPA/
PENTANOL
PHENANTHRENE
PHENOL
PHENOL , 4 - CHLORO , 3 - METHYL
PHENOXYACETIC ACID, 2 ,4, 5-TRICHLORO
PHENOXYACETIC ACID , 2 , 4 - DICHLORO
PHENTERMINE
PHENYLARSONIC ACID /PKA2-8.48/
PHENYLMERCURIC ACETATE
PHENYLTHIOUREA
PHORATE/THIMET/
PHOSPHINE SULFIDE,TRIS-(1-AZIRIDINYL)/NSC 639
PHOSPHORIC ACID
PHTHALIC ANHYDRIDE
PIPERAZINE
PROARGYL ALCOHOL/2 -PROPYN-1-OL/
CAS Number
76-01-7
82-68-8
87-86-5
109-66-0
71-41-0
85-01-8
108-95-2
59-50-7
93-76-5
94-75-7
122-09-8
98-05-5
62-38-4
103-85-5
298-02-2
52-24-4
7664-38-2
85-44-9
110-85-0
107-19-7
Log Pow
3.05
4.22
5.01
3.23
1.40
4.46
1.48
3.10
3.13
2.81
1.90
0.06
0.71
0.73
3.56
0.53
-1.86
1.60
-1.17
-0.38
         83

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TABLE B-2 (Continued)
Substance Name
PROPANOL
PROPENAL/ACROLEIN/
PROPIONALDEHYDE
PROPIONIC ACID
PROPIONITRILE
PROPYLAMINE
PROPYLENE /BPA/
PROPYLENE OXIDE
PYRENE
PYRIDINE
QUINOLINE
QUINONE
STYRENE
TEREPHTHALIC ACID
TETRACHLOROETHYLENE
TETRAFLUOROMETHANE /BPA/
TETRAHYDROFURAN /BPA/
THIOPHENOL
THIOUREA
TOLUENE
CAS Number
71-23-8
107-02-8
123-38-6
79-09-4
107-12-0
107-10-8
115-07-1
75-56-9
129-00-0
110-86-1
91-22-5
106-51-4
100-42-5
100-21-0
127-18-4
75-73-0
109-99-9
108-98-5
62-56-6
108-88-3
Log Pow
0.30
-0.01
0.59
0.33
0.16
0.48
1.77
0.03
4.88
0.62
2.02
0.20
2.95
2.00
3.40
1.18
0.46
2.52
-0.98
2.69
         84

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TABLE B-2 (Concluded)
Substance Name
TRI CHLOROETHYLENE
TRICHLOROFLUOROMETHANE/FREON - 11/BPA/
TRIETHYLAMINE
TRI ETHYLPHOS PHATE
TRIFLURALIN
TRIMETHYL ORTHOFORMATE
TRIS- (2 , 3-DIBROMOPROPYL) -PHOSPHATE
UREA
VINYL ACETATE
WARFARIN
CAS Number
79-01-6
75-69-4
121-44-8
78-40-0
1582-09-8
149-73-5
126-72-7
57-13-6
108-05-4
81-81-2
Log Pow
2.29
2.53
1.44
0.80
3.06
0.25
3.71
-1.09
0.73
0.05
         85

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                                TABLE B-3

         LOGARITHM OF N-OCTANOL-WATER COEFFICIENTS (LOG POW) FOR
   SELECTED ORGANIC  CHEMICALS  FOUND AT  NATIONAL PRIORITIES  LIST SITES
  Substance  Name
Log Pow
Source
Mr- ,
Acenaphthalene
Benz (A) an thr acene
Benzo (B ) f luoranthene
Benzo(K) f luoranthene
1 , 12-Benzoperylene
Creosote (coal tar)
Chrysene
Dibenz(A,H)acridine
m-Dichlorobenzene
Beta hexachlorocyclohexane (Beta BHC)
Delta hexachlorocyclohexane (Delta BHC)
3-Methylcholanthrene
1-Me thylphenanthr ene
Methylnaphthalene
Napthol
2-Pentanone (Methyl propyl ketone)
2 , 3-Phenylene pyrene
1,2,3 ,4-Tetrachlorobenzene
Tribromome thane (Bromoform)
Trlmethyl benzene
2,3, 4-Trinitro toluene (TNT)
2,4,5-Trinitrotoluene (TNT)

3.74
5.61
6.06
6.06
6.51
3.98
4.98
5.73
3.44
3.80
4.14
6.97
5.00
4.22
2.84
0.84
6.51
4.60
2.39
4.04
2.01
2.01

U.S. EPA, 1981
U.S. EPA, 1981
U.S. EPA, 1981
U.S. EPA, 1981
U.S. EPA, 1981
Callahan et al. ,
Leo et al., 1971
U.S. EPA, 1981






1979


Veith et al. , 1980
Callahan et al. ,
Callahan et al.,
U.S. EPA, 1981
U.S. EPA, 1981
MITRE*
Leo et al., 1971
MITRE*
U.S. EPA, 1981
Chiou, 1985
MITRE*
MITRE*
MITRE*
MITRE*
1979
1979











*Calculated by Leo's  Fragment Constant Method as specified in Lyman et al.,
 1982.
                                    86

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                             APPENDIX C




          ECOLOGICAL FACTORS WHICH AFFECT BIOACCUMULATION






     The biological processes and ecological interactions within




aquatic and terrestrial systems are complex and not completely




understood.  Figure C-l (Whelan and Steelman, 1984) is a simple




schematic which shows the various environmental factors that can affect




the transport of a chemical through the environment to eventually




reach man.  As Figure C-l illustrates, the ecosystem involves complex




interactions among the biotic and abiotic (non-living) components of




the environment.  The food chain is only one of those interconnected




links.  The physical/chemical fate of pollutants in the ecosystem




influences, and is influenced by, the biological processes.




     Because of the complexity of ecosystems and the diversity of




organisms, there is no easy method to evaluate the availability of




substances to either aquatic or terrestrial plants and animals or to




man (Jenne and Luoma, 1977; Fraser and Lum,  1983).  Nonetheless, a




large body of scientific information, reflected in the tables in




Appendix B, points out the potential for substances to bioaccumulate




from the environment to human food organisms.  Some substances clearly




are found in biotic tissues at concentrations thousands of times




greater than in the environment.




     The preferred method of assessing the potential for a substance




to enter the food chain is the direct measurement of the
                                 87

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      Figure C-1

      Schematic Diagram Illustrating the Interactions Between Media and the Movement
      of Contaminants to Human Targets
oo
00
      Groundwaler Environment
     Source:  Whelan and Steelman, 1984.

-------
bioconcentration factor and/or the biomagnification of the substance




in food organisms.  However, as Table B-l illustrates, there can be




a wide diversity of bioconcentration factors measured for a specific




substance reported in the literature.  The reasons for such wide




diversity are discussed below.




C.I  Ecological Factors




     The ecological factors which affect the behavior of pollutants



through the food chain include diversity, competition, niche, uptake




modes, mobility, availability, and trophic level.  It is the latter




which is most important, especially for those substances which



biomagnify in the food chain.  If, at each increasing trophic level




from producer (plants) to consumer (grazer) to predator (carnivore),




the substance is concentrated at levels higher than in the food




source or the surrounding environment, and if man is at the top of




the food chain, then the threat to man is of concern.




     Not all hazardous substances show consistent results for




measurements of bioconcentration and subsequent magnification.




Furthermore, some substances act differently in terrestrial




ecosystems than they do in aquatic environments.  For example,




plutonium has a reported bioconcentration factor of over 1,000 in




the marine ecosystem, but it is virtually unavailable to biota in




terrestrial ecosystems (because it remains in the soil) (Corey and




Boni, 1977; Garten and Dahlman, 1978; Hanson, 1975; National




Research Council, 1975).
                                 89

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     Ecosystems can change the form of the hazardous substance from




that which was released into the environment to another form in




tissue.  For example, antimony may be released into the water in its




elemental form or in any of a variety of compounds, but it is found




in fish as antimony trioxide.  Another example is mercury, which




when converted to methylmercury in the environment, becomes more




toxic (see Appendix D).  The organism itself may take compound X and




convert it to compound Y.  For example, fish convert benzo(a)pyrene,




a pollutant reported at many NPL sites, into metabolites strongly




suspected of being carcinogenic and which have been found in edible




portions of fish (Harshbarger, 1983; Melius, 1981).




C.2  Species and Individual Variability




     There are distinctive characteristics of species which




complicate the uptake process even further.  Separate species have




different niches in the environment; they eat different foods and




live in widely varied habitats.  Sole or flounder, for example, are




bottom feeders and are more likely to be exposed to toxic substances




found in sediments.  Salmon, on the other hand, are anadromous



(spawn in rivers) and may pass through a contaminated bay only once




or twice in a lifetime.  Menhaden are found in estuaries mainly in




the juvenile stage, and so would only be exposed to coastal




pollution as a juvenile, not as an adult.  Various species are found




on different trophic levels, and some, mullet for example, can feed




at several trophic levels (Odum, 1970).  A fish in a natural
                                 90

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environment may alter its feeding habits, eating vegetation one




season, insects during another, and juvenile fish when available.




     Within one species, there may also be wide individual



variations which influence the levels of substances found in




tissues.  Physiological factors such as size, age, sex, condition,




and metabolism all affect the results reported in the literature.




Many hazardous substances concentrate in fatty tissue.  Therefore, a



female or an animal in good condition may store these substances.  A




starving individual, however, may be forced to use its fatty tissue



and release the stored substances.  In the case of FCB



bioaccumulation in lake trout, older and larger individuals would be




expected to have the greatest body burden because they are the top



predator (Thomann and Connolly, 1984).  Some individuals may




metabolize a chemical, change it to another form, or excrete it




rapidly (McKim et al., 1976).



     Another factor which influences the results of biotic




measurements is the tissue analyzed.  Some authors report results




from analyses of whole fish, some from fatty tissue, and some from




edible meat, while others report the results from liver tissue.  One




study (Versar, 1985) reported that the worst-case scenario from a




risk analysis for the Commencement Bay (Washington) food chain was




for ingestion of fish liver.  Although the population that eats fish




liver is believed to be small, no data were available for the amount




of liver consumed (Versar, 1985).  Liver concentrations of hazardous
                                 91

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substances are usually high, because that is where those substances




are metabolized.  It is also easily measured.  However, as mentioned




above, fish liver is rarely ingestedj therefore, the majority of




results reported in Appendix B are for concentrations found in




edible tissue or muscle.




C.3  Experimental Methods Used in Ecology



     Bioconcentration factors reported in the literature also vary




widely based on whether the data were collected in the laboratory or




collected in the field.  In the field, the uptake into the food web




is influenced by numerous natural phenonmena including water




quality, weather, trophic level, population competition, and




availability of other food.  In a laboratory experiment, the




researcher is able to control many of the variables, including the




water quality (pH, temperature, salinity) as well as the number of




species present.  He may, for example, set up a simple food chain




from water to Daphnia to bluegills.




     One important environmental variable which affects results is




the duration of exposure.  Die exposure can be controlled in the



laboratory where fish for instance, may be held in the experimental




tank for as little as a few hours or days.  In the field the




duration is generally unknown, but similar fish could be exposed to




the pollutant over a lifetime.  Duke (1982) cautions scientists




about the risks of extrapolating the results from laboratory




experiments to the environment.  Fish, when removed from a
                                 92

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contaminated environment, may be able to depurate or to purify their




tissues when placed in clean water.  Ihis protective feature




complicates field data, where the fish may live only a portion of




their entire life cycle in a polluted environment.




     Bourquin and Pritchard (1983) reported that certain organics




(e.g., phthalates) are known to degrade biologically in the




laboratory; however, in the field they tend to accumulate in the




environment, even within ecological niches which appear to be



optimal for degradation.  In addition, the degradative processes in




estuarine and marine environments may differ significantly from



those in other aquatic environments.



     Another variable, which makes comparisons of direct



measurements difficult, is that the sampling and analysis methods




used are quite often unique to a given study.  One researcher might




collect samples from local fishermen, while another uses random




sampling from an entire bay.  One researcher might collect samples




over a four-day period, while another might collect his samples over




a four-season period.  One study may have results from 10 samples,




while another reports results from 100 samples.  All of these




variations in sampling protocol may yield different results.



     After sampling, additional variables are introduced by the




preparation of the sample and by the analytical method used, further




diversifying results.  For some of the newer organic chemicals




introduced into the environment (xenobiotics), there may not be an
                                 93

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analytical method of detection yet developed, there may be only one




technique known, or the analysis may be very expensive.  Hie results




reported in the literature may, therefore, be very limited.  On the




other hand, data on many pesticides and metals are relatively easy




to obtain, so there are a number of published studies available for




these substances.  For example, there are dozens to hundreds of




published research reports on the bioaccumulation of DDT and




cadmium, but very few on dioxins (TCDD), and none were found on




asbestos.  Substances, such as pesticides, which biologists have




known about for decades, have a large body of research data published




to support the conclusion that they do or do not biomagnify in the




food chain.  For other hazardous substances, data are limited and




their biomagnification potentials are unknown at this time.




C.4  Metals in Sediments and Their Availability to Biota




     Metals are persistent, remaining in the ecosystem for a very




long time.  Scientific debates continue as to whether or not those




metals are available to biota for uptake into the food chain.




     Sinderman et al. (1982) report that all three media (i.e., the




settled particles, interstitial waters, and water immediately




overlying the bottom) can provide major sources of metals to benthos




in their natural habitat.  Metals which are dissolved or adsorbed to




particles are both potentially available, since filter feeders take




in both sediments and water while feeding.  The result is that the




filter feeding organisms taken from contaminated zones have, on
                                 94

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average, ten times more metals in them than those biota found in




other regions (Sinderman et al., 1982).  The same result was




reported by Taymaz et al. (1984) whose data suggest that a




relationship exists between heavy metal content in shoreline




sediments and in benthic fish.




     The heavy metals may be either in dissolved form or adsorbed to




particles.  If dissolved, then the likely route of exposure in fish




is across gill membranes or by direct ingestion.  When water is




ingested, both suspended solids and dissolved metals can be




ingested.  When food is ingested, particularly for bottom feeding




fish, the adsorbed metals are ingested along with the benthos.  Some




benthic organisms, for example filter feeders and detritis feeders,




ingest the sediments themselves.  When an animal takes in the slurry




mixture at the interface between sediments and water, the slurry




contains the solid sediments, the organic detritis, as well as the




interstitial waters between the particles.  Metals may be found in




all of those components, and since the sediment layer acts as a




"sink" for heavy metals, this sediment interface becomes an




important consideration (Taymaz et al., 1984).




     The persistence of metals in sediments is related to the




presence of organic matter and clay fractions since these affect




sorption (Drifmeyer and Odum, 1975; Sinderman et al., 1982).  This




would be particularly important in the food chain of detritis




feeders (e.g., shrimp and crabs).  Even sandy sediments have a
                                 95

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proportion of silt and clay and retain metals, though in lesser



amounts.  Clay and silty bottom sediments may constitute a



considerable reservoir of heavy metals in the ecosystem.  In their



food chain studies, Drifmeyer and Odum (1975) found there was a



decrease in metal content within sediments as the particle size



increased, which is consistent with the metals being adsorbed on the



surface of the particles.



     As noted above and discussed further below, a number of



researchers have shown that adsorbed metals are available and are



incorporated into biotic tissue.  This is particularly true for



bottom feeders, filter feeders, and immobile shellfish.  However,



the U.S. Army Corps of Engineers studies on dredged material (Lee



and Jones, 1977; Montgomery and Palermo, 1983) report metals are not



released to water, but instead remain tightly bound to the sediments.



     Hardy et al. (1981) reported sediments serve as a "sink" for



removal of dissolved cadmium from water.  Bioaccumulation was


                         +2
related to the soluble Cd   ion concentration.  The interstitial



waters in sediments are high in dissolved organics which may complex



with the cadmium and thus reduce availability.



     Drifmeyer and Odum (1975) studied dredged spoil pond ecosystems



and the uptake of lead, zinc and manganese via the detritis food



chain.  Detritus was a significant factor in the bioaccumulation of



lead in that one-third to one-half of the lead was passed on via the



detritis food chain.  Tne grass shrimp, for example, eat
                                  96

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particulates with a high lead content, and thus, serve as a source




of heavy metals to the mummichog fish.  Ihe mummichogs, in turn, had




high levels of lead in those areas where sediments were contaminated.




     Guthrie and Davis (1979) reported results from water, sediments,




and benthos in the Gulf of Mexico, Texas.   Data from the Gulf




revealed that concentrations of 9 out of the 10 heavy metals studied




were higher in the sediments than in the water column.  Furthermore,




zinc was present in higher concentrations in bottom organisms (e.g.,




worms and oysters) than in sediments.  Oysters had significantly




higher concentrations of zinc, copper, and arsenic than were present




in the water samples.  Clams had significantly higher concentrations




of arsenic when compared to water samples taken from the same




locations.  Crabs had high levels of both arsenic and copper, which




were believed to have come from both water and sediment sources.




     O'Connor and Rachlin (1982) report different results for the




Atlantic coast.  The sediment concentrations did not correlate with




metals measured in exposed organisms.  However, these authors did




indicate the geographic trends in metals in benthos of the Atlantic




coast tend to correspond with the general trends for metals in those




coastal sediments.  O'Connor and Rachlin (1982) further suggest that




increasing levels of metals in the environment would result in




increased levels of metals in organisms.




     These illustrations serve to explain why such diverse results




are found in Appendix B, where the bioconcentration factors are
                                 97

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listed for both organic and inorganic hazardous substances.  While




not an invariant paramater for a given substance, the




bioconcentration factor is well documented by published research




papers, and it is an accepted indicator of which hazardous




substances are relatively more important in the food chain.
                                 98

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                             APPENDIX D




       CHEMICAL/PHYSICAL FACTORS WHICH AFFECT BIOACCUMULATION






     As discussed in Appendix C, direct measurement of the




bioaccumulation of hazardous substances in food chain organisms is




complex, expensive and not always consistent.  Furthermore, data are




not available for all substances.  In Section D.I, physical/chemical




characteristics which may be used as indicators of the potential for




an organic substance to bioaccumulate in the food chain are




examined.  Such characteristics could be used for assessing the




potential for a substance to enter the food chain in the absence of




the more direct measurements described in Section 2 of the main body




of this report.  These alternative characteristics could also be




used to confirm direct measurement data in cases where there may be




some question concerning the validity of those measurements.




     Bioaccumulation information for inorganic chemicals is often




reported in terms of a particular element present (usually a metal




cation such as mercury, copper, etc.) and not in terms of a




particular chemical species.  Tne uptake and accumulation of the




metal elements usually depends on the particular chemical species




present (i.e., whether it is a hydrated or unhydrated ion, a




covalent compound such as methylmercury, or a soluble ionic compound




such as mercury chloride).  However, as discussed in Section D.2,




once a substance is released into the environment, it is likely to




be physically and/or chemically and/or biologically altered by
                                 99

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complex natural processes.  Therefore, the particular chemical




species initially present at a site is not necessarily of importance




in an initial ranking of its potential to accumulate in the food




chain.




D.I  Organic Chemicals




     A literature review indicated that for organic chemicals, the




characteristics which may affect their potential to bioaccumulate




include biodegradability, volatility, solubility, soil adsorption




coefficient, and n-octanol-water partition coefficient.  Bie first




two influence the persistence of the substance in the environment;




the more persistent substances have a greater opportunity to




bioaccumulate.  These two characteristics are discussed in the




following two sections.  Ihe latter three characteristics are




discussed in Section 2.




     D.I.I  Biodegradability




     Biodegradability refers to the propensity of a chemical to be




degraded by microorganisms in the environment.  It is an important




characteristic to be considered in evaluating the fate of a chemical




because if a chemical is biodegradable in a few hours or days, then




the likelihood of its causing harm to public health through the food




chain is reduced in comparison with chemicals that persist for




months or years (Wood, 1982).  If a substance is not biodegraded,




then it is more likely to be persistent and more available for



biotic uptake.
                                 100

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     For a variety of reasons, however, biodegradation does not




appear to be useful as a measure of the accumulation of a substance




in food chain organisms.  Laboratory biodegradation study results




may not reflect conditions in the field where oxygen, oxidation




reduction potential, temperature, pH, competing organisms, and




chemical concentrations all affect the biodegradation process




(Kobayashi and Rittmann, 1982).  Residual concentrations of a




substance left after the bulk of the substance has been degraded



may still be subject to bioconcentration and could accumulate in the




food chain to harmful levels.  Finally, no published correlations




relating bioaccumulation to biodegradability were identified.




     D.I.2  Volatility




     The volatility of a chemical substance is its propensity to



vaporize and enter the atmosphere and is recognized as another



indicator of the environmental fate of that substance (Mackay et al.,




1982; Gillett, 1983; Suffet, 1975; Filov et al., 1979).  Volatility




could also be considered as a measure of persistence in the local




environment.  Substances which volatilize and dissipate quickly are




not as readily available to biota for uptake.




     The fundamental physical property of a chemical substance,




which is an indicator of its tendency to volatilize, is its vapor




pressure.  However, vapor pressure data are not always readily




available for substances or for mixtures of substances.  Further,



Mackay et al. (1982) report that many of the published vapor
                                 101

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pressure data may be erroneous.  The limited availability of




volatility or vapor pressure data and the lack of any reported




consistent relationship between volatility and accumulation in food




chain organisms limits the usefulness of volatility as a measure of




the potential of a substance to accumulate in the food chain.




     Thus, volatility and biodegradation were judged not to be




useful as indicators of the bioaccumulation potential of hazardous




substances in food chain organisms.  They are considered to be more



a measure of environmental persistence than of bioaccumulation, but




they could be useful for fine tuning the food chain hazard




classification of a chemical as suggested by Gillett (1983).  For




example, if two or more substances have similar bioconcentration




factors, consideration of their environmental persistence based on




biodegradeability or volatility could be used to establish a hazard




ranking relative to each other.  More persistent substances are




usually those which are more likely to be taken up into the food




chain.  Thus, substances which volatilize or which degrade in the




environment are not as potentially available to man via the food




chain as are more persistent substances.  Note however, that the




current HRS includes a persistence factor and the use of persistence




to rank substances in the proposed bioaccumulation ranking factor




might be undesirable if the current HRS persistence factor were to



remain unchanged.
                                 102

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D.2  Inorganic Chemicals




     Among the elements identified at NPL sites are:  aluminum,




antimony, arsenic, boron, cadmium, chromium, cobalt, copper, iron,




lead, manganese, mercury, molybdenum, nickel, plutonium, radium,




selenium, silver, strontium, tin, titanium, uranium, vanadium, and




zinc.  The uptake and accumulation in the food chain of such




elements may depend on the particular chemical species present,




i.e., whether it is the pure element or a compound such as



methyMercury, mercury chloride, copper sulphate, etc.  However,




once a substance is placed in a waste site or subsequently released




into the environment, it is likely to be physically and/or




chemically and/or biologically altered by natural processes into




other forms that may be more or less available for uptake and




accumulation in the food chain.  Thus, even if a substance is




initially present in a waste site in a form that is not readily




biologically available, there is potential for it to be transformed




to one that is readily available, and vice versa.




     For example, natural waters are complex systems containing a




variety of organic and inorganic matter from the natural decay and




degradation of plants and animals, from soil erosion, and from human




activities.  The chemical and physical interaction of released




chemical elements and their compounds with the organic and inorganic




matter affects the behavior of the substances and their impact on




the environment.  Humic and fulvic acids, which constitute the major
                                 103

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portion of natural organic matter present in natural waters, reduce




the biological availability of many metals by forming complexes with




them (Neubecker and Allen, 1983; Morel et al., 1974).




     Oily organic pollutants can concentrate at the surface of a




body of water.  The elements iron, lead, copper, and nickel have




been found to concentrate in this organic surface layer (Andelman,




1973).  Once concentrated, the metal and organic pollutants can




enter the food chain when surface feeders ingest the hazardous




substances along with food.




     Natural waters also contain a number of inorganic compounds




which can react with another inorganic substance that is released




into the water.  Chlorides, sulfates, fluorides, sulfides,




phosphates, carbonates, and bicarbonates are among the more common




species of inorganic compounds found in natural waters.  A wide




variety of soluble and insoluble compounds of released metals, for




instance, can be formed depending on the inorganic compounds present




in the water and on such factors as the acidity or alkalinity of the




water and the oxidation-reduction environment.  In a reducing




environment, for example, toxic hexavalent chromium is reduced to




less harmful trivalent chromium.  In an acidic environment with




sulfide present, mercuric ions combine with sulfides to form




insoluble mercuric sulfide.  If the water is alkaline, soluble




mercury-sulfide complexes can form (Leckie and James, 1974).




Insoluble substances tend generally to be less biologically
                                 104

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available than soluble substances.  However, If they remain




suspended in the water (e.g., in a fast moving stream) they can be




ingested by fish or adsorbed onto the fish gills.  In quiescient




water, insoluble substances will settle in the sediment, where they




may be taken up by benthic organisms and bottom feeding fish.




     Physical adsorption of metal ions on suspended clay particles



is another important process that can affect the bioavailability of




the metal as discussed in Appendix C.  Metal uptake varies with clay




characteristics, the concentration and chemical form of the metal



species, and the solution pH (Beveridge and Pickering, 1983).




     Microorganisms present in the environment can also alter the



form and availability of inorganic chemicals introduced into the




environment.  Bacteria are involved in the immobilization of iron by




transforming the ferrous form of iron to the ferric form which




precipitates as ferric hydroxide (Berthelin and Dommergues, 1976).




Microbial immobilization of aluminum and silicon also occurs




(Berthelin and Dommergues, 1976).  Bacteria are also implicated in




the conversion of mercury to methylmercury.  Microorganisms are also




present in the environment that can convert methylmercury into




inorganic mercury forms (Cooley and McCarty, 1977).




     The physical form in which a potentially hazardous substance is




released to the environment is another factor that must be




considered in evaluating its fate and effect in that environment.




Its initial form may inhibit or delay the conversion process;
                                 105

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conversely, it may enhance the likelihood of transport and rapid




conversion in the environment.  For example, solid massive forms of




metals such as iron, aluminum, copper, or zinc will slowly corrode




from exposure to air and other chemicals in the natural environment.




Leachate containing the metals can subsequently enter the soil and




nearby waterways.  Aqueous solutions of inorganic chemicals, if




accidentally released, can move relatively quickly into the soil




and/or nearby waterway.  Once in the environment, the fate of the




substance will be affected by the local environmental conditions as




well as its initial chemical form.




     In natural waters, the behavior and bioavailability of released




inorganic compounds will be controlled by the chemical, physical,




and biological characteristics of the particular body of water.




These characteristics can be different for the same body of water at



different times of the year.  They will be different for lakes,




estuaries, and oceans.  They will also differ among aquatic




ecosystems and soil types in different geographical locations



(Andelman, 1973; Troup and Bricker, 1975).




D.3  Summary




     Characteristics of a chemical substance which might be used in




the absence of bioconcentratlon factor data to assess the potential




of the substance to accumulate in the food chain were examined.




Characteristics examined included biodegradability, volatility,




n-octanol-water coefficient, solubility, and soil adsorption
                                 106

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coefficient.  For organic substances, the logarithm of the n-octanol-



water partition coefficient (log Pow) provides a satisfactory



alternative measurement, because a significant correlation has been



found between it and the bioconcentration factor.  Ihe correlation



shows that, in general, as the bioconcentration factor Increases the



log Pow increases.



     Biodegradation and volatility are measures of the persistence



of a substance in the environment and may affect the potential of a



substance to bioaccumulate, in that more persistent chemicals have a



greater opportunity to bioaccumulate.  However, the persistence of a



substance in the environment is already considered in the HRS, and



therefore, use of these characteristics in a bioaccumulation ranking



factor was considered redundant.



     As discussed in Section 2, the properties of water solubility



and soil adsorption partition coefficients have been shown to have



significant correlations with the bioconcentration factor,



comparable to those of the log Pow.



     Bioaccumulation information for inorganic compounds is usually



reported in terms of a particular element present, usually the metal



cation (e.g., mercury, copper, etc.), and not in terms of the



particular chemical species.  Uptake and accumulation of the metals



generally depends on the particular species present, i.e., whether



the pure element or a particular compound of the element is



present.  However, once a substance is released into the environment
                                 107

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it is likely to be physically, chemically, or biologically altered




by natural processes into other forms.  Even if a substance is




initially present at a wastes site in a biologically unavailable




form, it is possible for it to be transformed to another form which




is biologically available.  For this reason, it is considered




unnecessary to consider the specific chemical species present at




a hazardous wastes site in an initial ranking of the potential for




an inorganic substance to accumulate in the food chain.  Biis




methodology is for use as a screening tool when very little data is




available at a site.
                                108

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                             APPENDIX E

                       GLOSSARY OF TERMS USED
accumulation

anadromous
                   - Uptake of a substance from the environment

                   - Fish which spawn in rivers,  but live in the
                     ocean
annual production  - Amount or rate of energy storage by plants over
                     a year
availability



BCF

benthic

benthos

bioaccumulation
                   - Being present in a physical or  chemical form
                     that allows the substance  to be taken up by
                     biota

                   - Bioconcentration factor

                   - Bottom dwelling

                   - Bottom dwelling organisms

                   - Uptake of a substance from the  environment
                     (including the food chain) via  a biological
                     process to be incorporated into tissue at
                     concentrations higher than those found in the
                     surrounding environment

bioconcentration   - The process by which substances present in
                     solution enter aquatic organisms directly
                     through the gills or epithelial tissue.  This
                     process causes an increase in concentration of
                     the substance in biota above that in its
                     ambient environment (e.g., fish have higher
                     concentrations than water; worms have higher
                     concentrations than soil)
bioconcentration
factor (BCF)
biodegradability


biodegradation
                     Ratio of the concentration of a substance
                     biota to its concentration in the ambient
                     environment
in
                     Extent to which a substance can be decomposed
                     by organisms

                     Decomposition of an organic substance by living
                     organisms
                                 109

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biological
half-life
biomagnification




body burden


chemical index


competition


complexation
consumers

default value


diversity



food web


log Pow


magnification



methylated metal


mobility
- Time it takes an animal (organism) to degrade,
  metabolize, convert or excrete 50% of a
  substance

- Process whereby the tissue concentration of a
  bioaccumulated substance increases at each step
  in the food chain, as the substance moves
  through two or more trophic levels

- The total amount of pollutant measured in all
  tissues

- Score developed by NOAA which compares the
  toxicity of a compound to its persistence

- The struggle by individuals or populations for
  resources in short supply

- Loosely defined as the reaction of two soluble
  species to form a third.  In this report, it
  refers to the combination of metal cations with
  molecules or anions containing free pairs of
  electrons

- Grazers or herbivores in the food chain

- A value to assign when no other data are
  available

- Number of species (richness) compared to the
  numbers of individuals of each species present
  (evenness) in a community

- Interconnected food chains in a complex
  ecosystem

- Logarithm of the n-octanol-water partition
  coefficient

- Increase in concentration of a substance in
  higher tropic levels of the food chain, also
  known as biomagnification

- An organometallic compound in which the organic
  molecular group is a methyl radical, i.e., CH3

- Ability of a substance to be transported through
  the environment
                                 110

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net production
niche
n-octanol-water
partition
coefficient
nonessential
element

Automated EPA
NPL technical
data base

organometallic
                     Total biomass produced and stored by all plants
                     and animals over an area during a specified
                     time, usually over a year

                     The role of a species role in the environment,
                     i.e., where it lives and what it eats

                     This partitition is a measure of the
                     preferential partitioning of a substance
                     between n-octanol and water (measured in a
                     laboratory test or calculated by one of
                     several methods)

                     An element that is not necessary for nutrition
                     in biota

                     The automated EPA National Priorities List
                     technical data base contains information on
                     information on sites evaluated with the HRS

                     Referring to a class of compounds made up of
                     the combination of an organic molecular group
                     and a metallic atom where the metallic atom is
                     bonded to the carbon atom of the organic
                     molecular group, e.g., tetraethyl lead

                     In the HRS, a possible migration route (i.e.,
                     ground water, surface water, or air)

                     Long lasting in the environment, not easily
                     degraded

                     An oxidation reaction activated by light energy

                     n-octanol-water partition coefficient

                     Organisms (e.g., plants) which can synthesize
                     organic compounds from inorganic compounds.
                     The source of energy is either light or
                     chemical energy derived from the oxidation of
                     inorganic compounds

primary production - The organic material produced by the primary
                     producers
pathway


persistent


photoxidation

Pow

primary producers
                                 111

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protocol
secondary
production

soil adsorption
coefficient
solubility



species



standing crop


steric effects



targets


translocation


trophic level



uptake


unavailable
waste
charact eri s t i cs
score
- Series of specified steps followed in scientific
  procedure from the gathering of samples to
  analytical technique used and recording of
  results

- The production of herbivorous animals
  A ratio of the concentration of a substance on
  the soil adsorbent to the concentration of the
  substance in the environment surrounding the
  soil

  A property of a substance by virtue of which it
  forms mixtures with other substances which are
  chemically and physically homogeneous throughout

  May refer to a subcategory of classification of
  organisms, lower than genus; or may refer to a
  specific chemical compound

  Total amount of biomass of all aquatic species
  within an area

  The size and the shape of a molecule, affecting
  its uptake, e.g., ability to pass through a
  membrane

  Population potentially affected by releases of
  hazardous substances

  Movement of materials in solution in plants
  from one location to another

  Position in the food chain; e.g., plants
  (producers), herbivores (consumers), predators
  (carnivores)

  Absorbing or incorporating substance into
  living tissue

  Being present in a physical or chemical form
  that does not allow the substance to be taken
  up by biota

  In the HRS, a point score currently based upon
  rating factors such as waste quantity, toxicity
  and persistence
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xenobiotics        - Exogenously derived substances with no
                     nutritive value to organisms,  especially the
                     synthetic organic chemicals (Walton and
                     Edwards, 1986)

yield              - Part of the biotic production  which is removed
                     or expected to be harvested by man
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                             APPENDIX F

                       OTHER METHODS REVIEWED


     In examining the human food chain issue, a review of the technical

literature was made to determine if there was an existing method of

assessing the potential threat to humans due to exposure to hazardous

substances in the human food chain.  This appendix discusses why and

how some existing methodologies incorporate bioaccumulation as a factor

in assessing or ranking hazardous substances.  It also presents a

brief discussion of sources which discuss the use of bioaccumulation

in hazard ranking systems.

F.I  Hazard Assessment Rating Methodology II (HARM II)

     HARM II (Barnthouse et al., 1986) is an extension of the HARM

system, intended to "permit the use of site-specific monitoring data

to refine priorities for further study" at U.S. Air Force waste

sites.  Bioaccumulation is considered in order to estimate the total

human intake of hazardous substances from the site per day.

Bioaccumulation is defined using three terms:

Concentration Factor    - The ratio of concentration of a substance in
                          fish to the concentration in water.

Bioaccumulation Factor  - The multiplier when an organism's  pathways
                          of exposure include both direct uptake from
                          water and uptake from contaminated food.

Bioconcentration Factor - The multiplier used when the organism's
                          pathway of exposure is only direct uptake
                          from water.

All three are based on the concentration in fish at steady state.  A

hierarchy is established in HARM II for determining the

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bioaccumulation factor to be used in scoring a site.  Concentration




factors based on field data are most preferable.  Bioaccumulation




factor or bioconcentration factor data measured in the laboratory may




be used if concentration factors based on field data are not available.




Finally, if no other data are available, a regression equation and log




n-octanol-water partition coefficient data are used.




     The bioaccumulation factor (BAF) determined above is then used to




determine a final contaminant hazard score.  This is done differently




depending on whether or not an observed release of contaminants has




occurred at the site.  If an observed release has occurred, the BAF is




used to calculate the estimated human daily food intake of contaminated




food each hazardous substance presents at the site.  Ffciman health




hazard quotients for all substances are eventually summed, indexed,




normalized, and multiplied by a waste quantity factor to determine a




final contaminant hazard score.




     If an observed release has not occurred, each substance at the




site is evaluated independently.  The logarithm of the health effects



benchmark and the BAF are indexed.  The index values are then summed




for each substance.  Tne sum for the highest scoring substance is




normalized and multiplied by a persistence factor value and a waste




quantity multiplier to determine the final contaminant hazard score.




     Principal differences between the HARM II and proposed scheme




presented in Figure 4 are:
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     •  HARM II does not use biomagnification data.

     •  HARM II states that a log Bow of less than 5 will not be
        important in food chains.  Figure 4 assumes a log Pow of 3.2
        or greater is important.

     •  HARM II uses log Pow to calculate the log BCF using a
        regression equation.  Figure 4 uses the log Pow directly.

F.2  Remedial Action Priority System (RAPS)

     RAPS is a computer-based methodology to integrate and analyze

complex processes on DOE mixed waste sites.  It was developed

by Whelan et al. (1986) at Pacific Northwest Laboratory to prioritize

hazardous and radioactive waste sites for further site investigation.

When first presented in 1984, the RAPS did not consider the food

chain.  However, in the 1986 version of the model, RAPS uses the

concentration of the contaminant in the media of exposure, daily

ingestion rates, and a conversion factor to determine an individual

risk factor.  Instead of a bioconcentration factor, RAPS uses a

"transfer factor" (e.g., water-feed-meat) for agricultural systems,

as presented in U. S. Nuclear Regulatory Commission (1977).

     The data used as a basis for the transfer factor data are from

1968 and 1972 reports on radioactive material transfer, and only

data on elements are included.  NRG (1977) reports bioaccumulation

factors (using 1972 data) as calculated from concentrations of

elements in fish compared to concentrations of those elements in

invertebrates.  These factors are to be used in absence of

site-specific data.  This is not the way BCFs are generally

calculated today, as it disregards direct uptake from water.
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     The NRC does use a more standard bioaccumulation factor to




calculate doses to man via liquid effluent pathways.  This



bioaccumulation factor is for nuclides in the pathway, expressed




"as the ratio of the concentration in biota (in pGL/kg) to the




radionuclide concentration in water (in pCi/liter) in liters/kg"




(NRC, 1977).




     RAPS calculates the dose to man from aquatic food chains also.




Average daily intake is estimated using bioconcentration factors and




the average daily ingestion rates for aquatic foods.  One must have




the concentration data for the contaminant in the food (e.g., mg/kg




or pCi/kg) to complete the calculated risk factor.




     In Whelan et al. (1986), it appears the NRC transfer factors are




used to determine concentrations in meat and milk.  Bioconcentration




factors are used to the aquatic food chain to estimate average daily




intake of substances.  Whelan et al. (1986) does not state how to




determine bioaccumulation, but other "standard parameter values" in




RAPS are from NRC (1977), so we assume RAPS uses the NRC data on




bioaccumulation factors.  RAPS does not address the individual




differences between substances which have biomagnification potential




or those with high bioconcentration factors.



F.3  Food Chain Model




     Dixon and Holton (1984) of Oak Ridge National Laboratory




developed a model called FOODCHAIN, a Monte Carlo computer model for



estimating exposure to airborne pollutants via the food chain




pathway.  The model calculates regression equations for ingestion of



                                 118

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milk and beef based on the log Pow correlations with bioconcentration




factors from Kenaga and Goring (1980).




     Garten and Trabalka (1983) and Trabalka and Garten (1982) raised




several questions concerning practices used by Kenaga (1980) in his




correlations for 'substances in terrestrial systems.  In fact, such




dependence upon the Pow for a terrestrial methodology may be the



weakest point in the FOODCHAIN model.  Furthermore, this model



requires data on the concentration of substances in foods.   The




Monte Carlo modeling then generates 1,000 exposure results through



random sampling of food concentrations.  The results are applicable




to individual exposures to pollutants.  This model requires site




specific data in order to be able to rank sites.  It does not address




the real differences between substances known to biomagnify and does




not use bioconcentration factors as measured in the field or




laboratory.




F.4  Action Alert System



     The "Action Alert System" (Fiksel and Segal, 1982) was



developed to rank environmental pollutants for further study.  For




the calculation of ingestion risk, Fiksel and Segal depend upon the




correlation of solubility with bioconcentration factors based on




Kenaga (1980).  While food chain effects is beyond the scope of this




system, the authors state it is possible to derive a bioconcentration




factor for fish.  They multiply the BCF with ambient water




concentrations to estimate the contamination levels in fish.  This
                                 119

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is then used with average consumption rates to estimate the amount of




the pollutant ingested in food.  There are two weaknesses in this




approach:  (1) one needs to know ambient water concentrations, and (2)




dependence solely upon water solubility to estimate the BCF.  No use




is made of log Pow data, measured BCF data, or the biomagnification




process.



     An optional module to the Action Alert System was designed to




assess food residues based upon the bioaccumulation factor and ambient




water concentration for estimating fish contamination.  These data




then were used to predict amount of residue ingested in food to



estimate per capita risk.  Action Alert uses an experimentally-derived




bioaccumulation factor (BF), which measures the ratio in equilibrium




of pollutant concentration in fish to the concentration in the




surrounding aquatic medium.  The BF multiplied by the water



concentration would give the fish contamination (ppm).  This is then




multiplied by per capita fish consumption to give the amount of




contaminant ingested in fish per day.  This is added to terrestrial




residues consumed in foods to estimate risk.




     To estimate risk from pesticides on food, Action Alert depends




upon water solubility, based upon Kenega (1980) who correlated




solubility with bioconcentration.  To calculate water solubility the




model estimates from regression equations using n-octanol-water




partition coefficients following correlations by Chiou et al. (1977).
                                 120

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F.5  Predictive Model for Xenobiotic Bioaccumulation  in  Terrestrial
     Ecosys terns

     Trabalka and Garten (1982) provided a critical review  of

.predictive models for xenobiotic bioaccumulation in terrestrial

ecosystems.  This analysis of models for estimating the  fate of

xenobiotics was directed toward those substances transferred from

environmental sources to terrestrial vetebrates (i.e., birds and

mammals) via the ingestion pathway (e.g., soil to plant  to

consumers).  This was done to determine the  "necessary and  sufficient

information required to predict, within reasonable limits,  toxicity

and environmental fate prior to manufacture" of such  toxic  materials.

The review included a number of models which correlate the

bioconcentration factor to the log n-octanol-water coefficient and

water solubility.

     Trabalka and Garten (1982) developed a  Terrestrial  Hybrid

Model, based on NRC regulatory models, which used several types of

bioconcentration factors (BF).  These BFs were used to predict the

concentration of xenobiotics in carnivorous animals.  Examples of

how bioconcentration factors (BF) are defined in the  terrestrial

model are listed below:

                      Simple Compartment Model

     BFpA = BF of xenobiotic in product (tissue, organ,  secretion)
            of herbivorous animal from consumption of plant product

     BFWp = BF of xenobiotic in product of plant from uptake from
            soil interstitial water
                                 121

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                      Complex  Compartment Model

     BF^ = BF of xenobiotic in carnivorous animal product from
            consumption of herbivorous animal product

     BFpp = BF of xenobiotic in product of plant from exposure to
            foliar contamination

     BFg^ = BF of xenobiotic in herbivorous animal product from
            incidental ingestion of soil

These are applied in estimating uptake through the terrestrial food

chain (e.g., pasture to cattle).

     Trabalka and Garten (1982) then go on to analyze aquatic food

chain models and correlations.  In their data base, used to

determine bioaccumulation in fish, the following BFs are defined,

with methods given for BF determination in the laboratory:

     1.  BF(FW) = BF in freshwater fish from water-only exposure
         systems, typically flowing-water systems which maintain a
         reasonably constant exposure regime and continually removing
         metabolities; ratio of concentration of parent xenobiotic in
         fish (wet weight)/concentration of parent xenobiotic in water.

     2.  BF(ME) = BF in fish from static-model ecosystems which
         receive a single dose of the contaminant, which were
         maintained for approximately 30 days following initial
         exposure, and which contained a sand or soil substrate; ratio
         of concentration of parent xenobiotic in fish (wet
         weight)/concentration of parent xenobiotic in water.

     3.  BF(MA.) = BF in fish from static-model aquatic systems which
         differed from the above in not having a sand or soil substrate
         and which were exposed for a total time of three days or less;
         BF calculated in the same manner.

     4.  BF(MP) = BF in fish from static-model ecosystems; ratio of
         concentration of total xenobiotic (including metabolites) in
         fish (wet weight)/concentration of parent xenobiotic in water.

     5.  BF(MM) = BF in fish from static-model ecosystems; ratio of
         concentration of total xenobiotic (including metabolites) in
         fish (wet weight)/concentration of total xenobiotic in water.
                                 122

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     These bioconcentration factors are then included in a number of

correlations with water solubility and log n-octanol-water coefficients.

These authors concluded the n-octanol-water partition coefficient is a

"highly satisfactory index of bioaccumulation potential in fish and

terrestrial vertebrates (uptake from diet) for xenobiotics which do not

accumulate by covalent reaction."

F.6  Michigan Site Assessment Systems (SAS)

     The State of Michigan uses the SAS to rank the relative hazard

posed by release sites for purposes of assigning priority for site

evaluation and response actions (Michigan, 1983).

     In scoring environmental fate, the SAS uses the following for

bioaccumulation evaluation:

    Score                                 Criteria

     10              Fish Bioconcentration Factor* greater than 4,000
                                            or
                                   Log Pow greater than 6

      5                     Fish Biocentration Factor = 700-4,000
                                             or
                                        Log Pow = 4.5-6

      0               Fish Bioconcentration Factor less than 700
                                          or
                                      Log Pow 4.5


This score is then used with other factors to calculate a potential

toxicity score for each chemical.  This factor is then normalized and

added to other site assessment screening factors for a total score.
*No guidance is given concerning derivation of the fish
 bioconcentration factor.
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F.7  U.S. Department of Agriculture (USDA)




     The U.S. Department of Agriculture (USDA, 1985) uses a compound




evaluation ranking method for pesticides, animal drugs, and




"unavoidable environmental contaminants."  This method applies an




A-B-C-D score to substances found in meat and poultry.  Tne main




reasons for a high score of A are high toxicity and carcinogenicity.




Other criteria include:  amount of actual or probable use; conditions




of use related to residues at slaughter; potential for misuse to




result in harmful residues; and the toxicity of the residue.  While




bioaccumulation is not mentioned in those criteria, background




information on these substances ranked may includes statements, such




as for FCBs, concerning bioaccumulation in the food chain.  A proposed




new ranking scheme, the Prototype Compound Evaluation System (CES)




will subdivide these A-B-C-D categories further based upon hazard and




exposure data.  No mention is made of bioaccumulation potential.




F.8  National Academy of Sciences (NAS)




     In 1975, a comprehensive review "Assessing Potential Ocean



Pollutants," was published by the NAS (National Research Council,




1975).  This report summarizes a number of earlier studies and reports




biological concentration factors for many chemicals and radioisotopes.



This report also summarizes fate and effect data for many compounds in




soils and air, biodegradation processes, toxicity, and effects of the



chemicals in the marine environment.
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F.9  U.S. Food and Drug Administration (USFDA)

     While the USDA monitors meat and poultry, the U.S. Food and Drug

Administration Surveillance Index (USFDA, 1983) was developed for

monitoring substances in other foods.  About 160 pesticides have been

classified in categories I to V, mainly on the basis of potential

health risk and potential for occurrence as residues in foods.  Use of

the FDA method would be applicable to only a portion of the food chain

problem.  The FDA monitors foods other than meat and poultry, and their

ranking index only applies to pesticides in foods.

     The criteria used by FDA to score pesticides include:

     •  Annual production

     •  Use on corps

     •  Potential for environmental contamination and entering food
        chains

     •  Types of food containing residue

     •  Relative toxicity

     •  Chemistry, including metabolites

     •  Propensity to biomagnify in edible tissue

     •  Biological half-life

     •  Persistence

     •  Non-dietary exposure

     •  Per capita consumption

     •  Knowledge of existing incidence

     •  Special regulatory interests
                                 125

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     Using these criteria, USFDA assigns a pesticide to one of five




classes to determine priority for monitoring in human foods.  Class I




represents a high health hazard based on toxicological data or




bioaccumulation potential.




     Lombardo (1979) described another FDA program, the Chemical




Contaminants Program, which selects industrial chemical types for




study.  Criteria used in this program included in bioaccumulation




potential and oil-water partition coefficients.  FDA's "primary



indicator organism is freshwater fish, as most problem contaminants




evenually find their way into this segment of the human food chain"




(Lombardo, 1979).  Using these data, FDA then establishes Action




Levels or Tolerances for deleterious substances in seafood.




F.10  Inter-Governmental Maritime Consultative Organization (IMCO)




     In 1973 IMCO published Annex II of the International Conference




on Maritime Pollution.  Appendix I of the Annex provides guidelines




for the categorization of noxious liquid substances into four groups




(A, B, C, and D) based upon probable tainting of seafoods and




reduction of amenities.  Cateogry A substances are bioaccumulative




and are liable to produce a major health hazard.




     These categories of noxious liquid substances are then used to




regulate discharges from ships to the sea.  No definitions of




bioaccumulation are given, nor are methods given for determining




this factor.  Substances which bioaccumulate are either categorized
                                 126.

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as A or B.  This list of substances was used initially to indicate




which ones may be found in fish.




F.ll  Other Ranking Methods




     Almost 60 methods for ranking the degree of hazard of substances




are reviewed in Review and Analysis of Hazard Ranking Systems (U.S.




Environmental Protection Agency, 1984c).  In those methods which




used bioaccumulation as one of the criteria for ranking hazardous




substances, it was most often used as a modifier to address the




fate of a substance in the environment.  The more complex and




sophisticated models require concentration data in water, and this




is multiplied by the bioconcentration factor of the substance.  Where




the bioconcentration factor is unknown, the n-octanol-water partition




coefficient is often used as a backup.  One method recommended a




laboratory test to determine the potential accumulation of




substances into biota.




     Hushon et al. (1983) and Hushon and Kornreich (1984) provide




an extensive list of internationally published methodologies for




ranking substances based upon the degree of hazard.  A majority of




these methods rely heavily on the n-octanol-water partition




coefficient (Bro-Rasmussen and Christiansen, 1984; Mackay, 1981 and




1982; Wood, 1981; Hushon et al., 1983; Lu and Metcalf, 1975; Veith




et al., 1979).  The following methods use bioaccumulation as a




scoring factor in ranking the degree of hazard of substances:
                                 127

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     1.  Ranking for European Economic Community Water Pollutants:
         to select chemicals for further study.

     2.  American Society for Testing and Materials Committee (d-19):
         to determine impacts of chemicals an aquatic life.

     3.  EPA Action Alert:   previously discussed.

     4.  MITRE (for Federal Republic of Germany):  to select
         chemicals for environmental trends monitoring.

     5.  Office of Technology Assessment:   to identify possible food
         contaminants.

     6.  Michigan Critical Materials Register:  to score chemicals
         of concern.

     7.  EPA Office of Toxic Substances:  to select chemicals
         presenting environmental risk under TSCA.

Many other methods, however, were developed to rank substances based

upon toxicity criteria but not bioaccumulation.

     The reportable quantities support documents (EPA, 1985;  ICF,

1985) provide substantial data on the CERCLA hazardous substances,

including their toxicity and other factors which influence the fate

of the substances in the environment.   The documents consider the

bioaccumulation potential,  but do not quantify or apply the data.

The tables only list substances which bioaccumulate in biota.

     Some ranking methods,  such as the "reportable quantities"

documents (ICF, 1985) or those reviewed by Hushon and Kornreich

(1984), use bioaccumulation as a "yes it does" or "no it does not"

factor, and instead place more emphasis on toxicity to distinguish

among substances.
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     In 1975, a comprehensive review "Assessing Potential Ocean




Pollutants," was published by the MAS (National Research Council,




1975).  This report summarizes a number of earlier studies and reports




biological concentration factors as reported in the literature for




many chemicals and radiolsotopes.  The report also summarizes fate




and effect data for many compounds in soils and air biodegradation




processes, toxicity, and effects of the chemicals in the marine




environment.
                                 129

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