Hazard Ranking System Issue Analysis:
Potential Human Food Chain Exposure
               MITRE

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Hazard Ranking System  Issue Analysis:
Potential Human Food Chain Exposure
                    Ming P. Wang
                 Thomas F. Wolfinger
                    Sharon Saari
                   November 1987
                     MTR-86W142
                      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:
MITRE Project Approval:  _±
                            ii

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                              ABSTRACT
     This report examines the feasibility of incorporating factors
into the U.S. Environmental Protection Agency Hazard Ranking System
(HRS) that reflect the potential risks posed to humans by food chain
contamination arising from releases from uncontrolled waste sites.
The literature on contaminant migration through the human food chain
was reviewed.  Significant gaps in scientific knowledge were
identified in the terrestrial component of the human food chain.
The aquatic component is better understood at this time.  Five
systems other than the HRS were examined to determine if any methods
developed by others could be adapted.

     Several options for incorporating aquatic food chain assessment
factors into the HRS are presented.  Deficiencies in empirical data
and limitations in knowledge of the terrestrial food chain preclude
the development of options for the terrestrial food chain.
Important factors that should be incorporated into a future
terrestrial food chain factor are discussed.

Suggested Keywords:  Bioaccumulation, Food Chain, Hazardous Waste
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                          TABLE OF CONTENTS

                                                                 Page

LIST OF ILLUSTRATIONS                                            vii

LIST OF TABLES                                                  viii

1.0  INTRODUCTION                                                  1

1.1  Background                                                    1
1.2  Issue Description                                             3
1.3  Objectives and Approach                                       7
1.4  Organization of Report                                        8

2.0  OVERVIEW OF THE HUMAN FOOD CHAIN                             11

2.1  Exposures to Hazardous Substances Through the                11
     Aquatic Food Chain
2.2  Exposures to Hazardous Substances Through The                13
     Terrestrial Food Chain

     2.2.1  Loadings                                              14
     2.2.2  Availability                                          15
     2.2.3  Plant Uptake and Translocation                        17
     2.2.4  Animal Uptake and Translocation                       24
     2.2.5  Human Intake                                          26
     2.2.6  Conclusions                                           33

3.0  EXISTING SYSTEMS FOR EVALUATING FOOD CHAIN EXPOSURES         35
     FROM UNCONTROLLED WASTE SITES

3.1  Hazard Assessment Ranking Methodology II (HARM II)           36
3.2  Prioritization of Environmental Risks and Control Options    37
     (PERCO)
3.3  Action Alert System (AAS)                                    38
3.4  Remedial Action Priority System (RAPS)                       39
3.5  Preliminary Pollutant Limit Value (PPLV) System              40
3.6  Summary                                                      41

4.0  OPTIONS FOR INCORPORATING FOOD CHAIN RISK FACTORS            43
     INTO THE HRS

4.1  Structure of the Current HRS                                 43
4.2  Aquatic Food Chain Methodology                               44

     4.2.1  Overview of the Proposed Methodology                  44
     4.2.2  Waste Characteristics Factors                         47
     4.2.3  Target Factor Evaluation                              60

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                    TABLE OF CONTENTS (Concluded)

                                                                 Page

4.3  Terrestrial Food Chain Methodology                           76

     4.3.1  Factors for Inclusion in Terrestrial Food             77
            Chain Options
     4.3.2  Conclusions and Recommendations                       88

4.4  Additional Issues Concerning Human Food Chain Risks          88
     and the HRS

5.0  CONCLUSIONS                                                  93

6.0  REFERENCES AND BIBLIOGRAPHY                                  95

APPENDIX A—CLASSIFICATION OF HAZARDOUS SUBSTANCES               115

APPENDIX B—AVERAGE FISH STANDING CROPS REPORTED                 133
                                 vi

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                        LIST OF ILLUSTRATIONS

Figure Number                                                    Page

     1          THE COMPONENTS OF THE PROPOSED AQUATIC FOOD        45
                CHAIN METHODOLOGY

     2          DECISION TREE FOR RANKING SUBSTANCES FOR          48
                POTENTIAL TO BIOACCUMULATE IN THE FOOD CHAIN
                                 vii

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                           LIST OF TABLES

Table Number                                                     Page
      1         SOIL TO PLANT UPTAKE FACTORS FOR SELECTED         20
                ORGA1NC COMPOUNDS

      2         CADMIUM AND ZINC CONCENTRATIONS IN DIFFERENT      21
                CULTIVARS OF SOYBEAN, LETTUCE, AND CORN

      3         PLANT PHYTOTOXICITY AS A BARRIER TO ANIMAL        23
                CONTAMINATION

      4         CONCENTRATION OF HEXACHLOROBENZENE (HCB) AFTER    27
                12 WEEKS OF ADMINISTRATION TO PIGS

      5         PLATEAU LEVEL ORGAN CONCENTRATIONS IN RHESUS      28
                MONKEYS AFTER CHRONIC FEEDING OF 1 PPM HCB
                OR 2 PPM PCNB IN DAILY DIET

      6         DISTRIBUTION OF PCB AMONG BODY PARTS OF CATTLE    29
                (ppm Arochlor 1260)

      7         U.S. CONSUMPTION OF MAJOR FOOD COMMODITIES PER    30
                PERSON (1980) (Pounds per person per year)

      8         EVALUATING WASTE CHARACTERISTICS FOR AQUATIC      52
                FOOD CHAIN OPTION—OPTION I

      9         WASTE CHARACTERISTICS EVALUATION SHEET FOR THE    55
                AQUATIC FOOD CHAIN METHODOLOGY-OPTION II

     10         RATING MATRIX FOR TOXICITY/BIOACCUMULATION        57
                FACTOR VALUE FOR THE AQUATIC FOOD CHAIN
                METHODOLOGY—OPTION II

     11         METHOD FOR EVALUATING THE BIOCONCENTRATION        58
                FACTOR VALUE

     12         BIOACCUMULATION RATING MATRIX FOR AQUATICS        59
                FOOD CHAIN METHODOLOGY—OPTION II

     13         RATING MATRIX FOR TOXICITY/PERSISTENCE/           61
                BIOACCUMULATION VALUE FOR THE AQUATIC FOOD
                CHAIN METHODOLOGY—OPTION III
                                vlil

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                     LIST OF TABLES  (Concluded)

Table Number                                                      Page

     14         PROPOSED FISH PRODUCTION FACTOR EVALUATION         65
                TABLE

     15         PROPOSED FISHERY RESOURCE FACTOR EVALUATION        67
                TABLE

     16         EXAMPLE TARGET FACTOR EVALUATION TABLE  FOR.         70
                AQUATIC FOOD CHAIN METHODOLOGY

     17         FOOD CHAIN POPULATION VALUE                        74

     18         FOOD PRODUCTION VALUE TABLE                        75

     19         CORRELATION COEFFICIENTS (R2) FROM                 79
                LOGARITHMIC REGRESSION ANALYSES PERFORMED BY
                GARTEN AND TRABALKA

     20         TRANSFER FACTORS FOR SELECTED ORGANIC COMPOUNDS    82
                                 Ix

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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 NPL.

     •  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 toxicity
        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

     The issue examined in this report is whether it is feasible to

define and implement factors reflecting human food chain contamin-

ation risks into the HRS.  The emphasis is on risks relating to human

health, although resource loss risks are addressed as warranted.

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     Human consumption of substances clarified as hazardous by EPA




can cause severe illness or death.  Inadvertent comsumption of such




substances by consuming contaminated food is a serious public health




issue.




     The danger of contamination  of the human food chain by releases




of hazardous substances into the  environment and  resulting human




consumption of hazardous  substances in food are well  established




world-wide.  Methyl mercury contamination of fish and other




foodstuffs in Japan has  resulted  in several outbreaks of Minamata




Disease, named after  the  bay in Japan  where the disease was first




identified.  The  first outbreak in Japan was  in  the early  1950s; the




most  recent was in 1973  (Fbrstner and  Wittmann, 1983).  Symptoms of




methyl  mercury poisoning  have  also been identified in native




communities in Canada, apparently resulting from  the  presence  of




methyl  mercury in fish.   Several  instances of  human consumption of




food  (primarily rice) contaminated with PCBs have occurred in  Japan




and Taiwan, resulting in a disfiguring condition known as  Yusho.




      In the United States,  relatively  strict  control  of commercial




food  quality and  a relatively  high dependence  on commercial food




have  probably interacted  to limit the  occurrence  of adverse human




health  affects from food  contamination by hazardous chemicals.




Nonetheless, numerous instances have been recorded of human food



chain contamination sometimes  coupled  with human  health impacts that



have  resulted from releases of contaminants that  could be  addressed

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under CERCLA.  These instances include numerous fishkills (as many




as 1 million fish in one instance in Warrior Creek Alabama),




closings of commercial fisheries (e.g., PCB contamination in Lake




Weiss and the Coosa River in Alabama and Georgia in 1976, kepone




contamination in the James River in 1975, and mirex contamination in




Lake Ontario), animal poisonings (such as the death of 56 cattle in




Newton, Kansas from PCB poisoning and the quarantining of 20,000




head of cattle in Louisiana due to HCB contamination), and crop




damage (contamination of 550 acres of farmland near Baton Rouge,




Louisiana in 1979).




     Two instances of human health impacts from food contamination




can be identified as well.  As reported by EPA (1980), three




children living in Albuquerque, New Mexico became seriously ill in




1971 after eating a pig that had been fed feed contaminated with




mercury.  An investigation located additional bags of contaminated




feed in a local dump.  The Superfund Section 30l(e) Study Group




indicated that hundreds of people in Michigan exhibited persistent




illness probably associated with the contamination of animal feed by




PCBs and subsequent migration up the food chain through meat, milk,




and eggs (Superfund Section 301(e) Study Group, 1982).




     The following three reports list numerous other examples of




releases of hazardous substances into the environment that have




resulted in contamination of the human food chain:

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     •  Congressional Research Service, Resource Losses from Surface
        Water,  Groundwater,  and Atmospheric Contamination;  A
        Catalog,  (Serial No.  96-9),  prepared for the Senate
        Committee on Environment and Public Works, 96th Congress,
        U.S.  Government Printing Office, Washington, DC, 1980.

     •  Superfund Section 301(e) Study Group,  Injuries and Damages
        from Hazardous Wastes—Analysis and Improvement of Legal
        Remedies, Parts 1 and 2, (Serial No.  97-12), prepared  for
        the Senate Committee on Environment and Public Works,  97th
        Congress, U.S. Government Printing Office, Washington, DC,
        September 1982.

     •  U.S. Environmental Protection Agency, Damages  and Threats
        Caused By Hazardous Material Sites,  (EPA-430/9-80-004), U.S.
        Environmental Protection Agency, Washington, DC,  January
        1980.

     Congress, recognizing the  potential for human food  chain

contamination by uncontrolled waste sites required modification to

the National Contingency Plan as part of the The Superfund Amendments

and Reauthorization Act of 1986.  The Act modifies Section 105,

expressing Congress's desire to protect human health from exposure

to hazardous substances through the food chain.  On the issue of

setting criteria and priorities among releases or threatened

releases, CERCLA (as amended) now directs that the criteria used  in

determining priorities among sites take into account,  "to the extent

possible the population at risk, the hazard potential of the

hazardous substances at such facilities, the potential for

contamination of drinking water supplies,  the potential for direct

human contact, the potential for destruction of sensitive

ecosystems, the damage to natural resources which may  affect the

human food chain and which is associated with any release or

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threatened release, the contamination or potential contamination of



the ambient air which is associated with the release or threatened




release, ..." (emphasis added).




     Currently, the HRS explicitly addresses risks to human health




through direct ingestion of contaminated water and through




inhalation of contaminated air (47 FR 31180, July 16, 1982).  The




HRS also addresses risks of environmental damage and resource loss




in many of its factors (e.g., the sensitive environments factors in




the surface water and air pathways).  The only factors in the HRS




that address food chain-related risks are contained in the ground




water and surface water target population factors.  Food chain




contamination risks from the use of potentially contaminated




irrigation water are reflected in the procedure for estimating the




target population:  an additional 1.5 persons per acre of irrigated




land are added to the population total in evaluating the target




population factors.




1.3  Objectives and Approach




     This study has two objectives.  The first is to examine the




feasibility of evaluating human food chain-related risks within the




context of the HRS.  The second is to develop options for evaluating




these risks in the HRS.




     A multi-stage approach was taken to fulfill these objectives.




In the first stage the NPL data base and site files were reviewed to




identify both the potential threat to the public health from food

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chain exposure and the substances that are of principal concern at

the NPL sites.  Second, a literature review was conducted addressing

the structure and other characteristics of the aquatic and

terrestrial human food chain.   There are several purposes to the

review:

     •  To identify the important mechanisms of transfer for toxic
        substances from the contaminated environment to the food
        consumed by humans.

     •  To identify methods for estimating the concentration of the
        hazardous substance in the human foodstocks from the
        concentration of hazardous substances in the environment
        (i.e., estimating the chemical concentration in fish from
        the chemical concentration in water, estimating the chemical
        concentration in plants from the concentration in air or
        soil).

     •  To compile the important parameter values needed for the
        hazardous substances found at NPL sites.

     In the third stage, several existing schemes were reviewed that

evaluate risk through human food chain exposures, in order to

evaluate their usefulness as a basis for developing HRS options.

     Finally, the present structure of the HRS was examined and

options of incorporating human food chain factors within the HRS

were developed, where feasible.

1.4  Organization of Report

     This report is organized into six chapters.  Section 2 presents

an overview of the human food chain, reflecting the results of the

review of the literature on human food chain risk assessment.

Section 3 presents the results of the review of the existing waste

site ranking systems that address human food chain risks.  Options


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for incorporating human food chain factors, where feasible, into the




HRS are discussed in Section 4.  This chapter also includes a




discussion of issues that must be resolved if the options are




implemented.  Section 5 presents the conclusions of the report.




Section 6 presents the references and a selected bibliography.




Appendix A contains bioaccumulation factor evaluations for over 300




contaminants found at uncontrolled waste sites.  Appendix B contains




estimates of fish standing crops for selected surface water bodies




in the United States.

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2.0  OVERVIEW OF THE HUMAN FOOD CHAIN

     This chapter presents an overview of the human food chain.   The

purpose of this overview is to identify those aspects of the human

food chain that would need to be reflected in options for evaluating

food chain risks in the HRS.  Due to differences in the complexity

of the aquatic and terrestrial food chains and due to resulting

differences in the state-of-knowledge of critical components in  the

two food chains, separate sections are presented addressing each.

2.1  Exposures to Hazardous Substances Through the Aquatic Food  Chain

     Hazardous substances enter the aquatic food chain by

contaminating the surface water environment in which the aquatic

organisms live.  The surface water environment includes both the

water column and underlying sediment.  Once the surface water

environment is contaminated, aquatic organisms may accumulate

hazardous substances in their tissue.  These accumulated substances

may harm the organisms directly or they may pose a threat to animals

which feed upon the organisms.

     Aquatic organisms may accumulate substances from their

environment via at least three different pathways (Swartz and Lee,

1980):

     •  Direct adsorption to the body wall or exoskeleton.

     •  Direct absorption through the integument, gills, or other
        respiratory surfaces.

     •  Ingestion of contaminated sediment, food, or water followed
        by absorption through the gut.
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     Soluble forms of contaminants are considered to  be



bioavailable, thus sorptlon is an important uptake mechanism for




aqueous-phase contaminants.  Dietary uptake via ingestion of




contaminated organisms may also be a major route of uptake.   For




example, Weininger (1978) has estimated that approximately 98 percent




of the total PCB residues in lake trout in Lake Michigan results




from dietary uptake.  Contaminated sediments can also be an important




source of contaminants for biological uptake.  Uptake from sediment




can occur via two potential avenues:   (1) desorption to interstitial



and interfacial water followed by bioaccumulation, either by




sorption through gills or  epithelial tissue; or  (2) through




ingestion of contaminated  sediment particles.  The relative




contribution of those two  mechanisms has not been estimated, but




depends upon the feeding and respiratory patterns of the organism.




Deposit-feeding is of primary interest with respect to uptake from




sediment.




     The extent of the elevation  of contaminant  concentration in




biota with respect to the  aquatic medium they reside in is often




expressed by the bioconcentration factor (BCF).  The bioconcentra-




tion factor is the ratio of contaminant concentration in the biota




to the contaminant concentration in water, independent of the



process of biological uptake.   This definition is consistent with



the definition used by McBrien,  Saari, and Goldfarb (1987) and is



adopted for use in this report.   That is,  the term BCF in this
                                12

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report includes the result of bioconcentration and bioaccumulation.

With the exception of controlled environments in which the organism

is only allowed to be in contact with water, the reported BCF for an

organism in a natural environment is most appropriately considered

as the result of bioaccumulation.  McBrien, Saari, and Goldfarb

(1987) give a more detailed description on factors affecting BCF and

potential surrogates for BCF, as well as BCF data collected for more

than 300 hazardous substances.

     The health risk to an individual human from ingesting

contaminated fish and shellfish is often compared with the risk from

drinking water.  Because of the tendency for an aquatic organism to

bioaccumulate contaminant in its body, the threat to human health

from an aquatic food chain exposure has the potential to be more

serious than that from drinking water even though the amount of fish

and shellfish consumed is much less.  For example, Black (1983)

estimated that eating one pound of fish, contaminated at average PCB

levels for the Great Lakes, presents a risk equal to drinking the

water for about 1,000 years.

2.2  Exposures to Hazardous Substances Through The Terrestrial
     Food Chain

     Exposure to hazardous substances through the human terrestrial

food chain is somewhat more complex than its aquatic counterpart.

This complexity is reflected in the somewhat larger number of

exposure paths.  In part as a result of its greater complexity, less

is known about the terrestrial food chain than the aquatic food


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chain.  Five semi-independent but interrelated topics of importance




in assessing food chain contamination risks are discussed below:



     •  Loadings (e.g., routes of exposure)




     •  Availability for uptake




     •  Plant uptake and translocation




     •  Animal uptake  and  translocation




     •  Human uptake




These topic  areas  correspond generally to the major  components  of




the terrestrial  food chain.




      2.2.1  Loadings




     Loadings addresses the routes by which contaminants  enter  into




the terrestrial  food chain.   Various authors (e.g.,  Chaney, 1983;




Dixon and Holton,  1984; Dreesen et al.,  1982; Edwards,  1983; Ritter




and Rinefierd, 1983; Ronneau et al., 1983;  Thomas, Ruhling, and




Simon,  1984; Wagstaff, McDowell, and Paulin, 1980; and  Walton and




Edwards,  1986) have identified the following as potentially




important pathways for environmental contaminants  to enter into the




terrestrial  food chain:




      •  Direct deposition  of contaminants onto soils and  crops.




     •  Deposition of  airborne contaminants onto soils  and crops.




     •  Use  of contaminated  irrigation water.



     •  Ingestion  of contaminated soils and water by animals.



     •  Inhalation  of  airborne contaminants  by animals.
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     •  Volatilization of contaminants from ground water into the
        soil and the near soil air zone.

     •  Ingestion of contaminated feed.

The overall relative importance of these loading mechanisms in

determining food chain risks for both organic and inorganic

contaminants migrating through plants and animals is unknown.

Several authors indicate direct ingestion of contaminated soil poses

the greatest risk to the grazing animal portion of the food chain

(e.g., Chaney, 1983; Ronneau et al., 1983; and Walton and Edwards,

1986).  This position is supported by the observation made by Chaney

(1983) that livestock have been poisoned by ingesting lead from

soils at natural background concentrations.  The importance of the

contaminated soil ingestion mechanism is compounded by the potential

for concurrent inhalation of contaminated soil gases.

     2.2.2  Availability

     Once contaminants have been deposited onto soils, several

factors interact to determine the availability of the contaminants

for plant uptake.  Contaminants may bind to soil, may continue to

migrate (e.g., through leaching or volatilization), may degrade or

transform (e.g., through photolysis, hydrolysis, or other chemical

or biological transformation processes), or they may enter into the

food chain.  Lack of knowledge of soil degradation kinetics was

identified as a major deficiency in terrestrial food chain modeling

at the 1983 workshop on food chain modeling for risk analysis (Breck

and Baes, 1985).


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     The possibility for binding of contaminants in soil has



received considerable attention in the literature since the ratio of



plant contaminant concentrations to soil contaminant concentrations




is used by many to define the plant bioconcentration factor (see,




for example, Breck and Baes, 1985; Dixon and Holton, 1984; and




Schaeffer, 1985).




     Contaminant availability depends  on the interaction between




contaminant, soil, and other environmental characteristics.




Numerous authors have investigated the dynamics of  plant uptake of




both organic and inorganic  compounds.   More is  known about the




dynamics of inorganic contaminant  (particularly radionuclide) uptake




by plants  than is known  about organic  uptake.   However,




investigations of plant  uptake  of  certain organics  (e.g., many




pesticides such as DDT,  their derivatives, and  other contaminants




such as TCDD)  have been  performed  (e.g., Bollag and Loll, 1983).




     Contaminants deposited onto soil  may either become bound to




soil constituents (either loosely  or tightly) or they may continue




to migrate.  Several soil characteristics have  been identified as




important  in determining the ability of the soil to bind




contaminants:




     •  Organic matter content



     •  Clay content




     •  Cation exchange  capacity



     •  Soil pH
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     •  Soil texture




     •  Soil moisture content




     •  Soil particle size and surface area




     •  Soil temperature




Bollag and Loll (1983) note that binding of contaminants to soils




may be temporary due to changes in the soil chemistry over time.




These authors also caution that under some conditions bound




contaminants also may persist in the soil.  These authors state,




however, that most researchers doubt that bound contaminants pose




immediate health threats, although the contaminants may accumulate




in the food chain over time.




     Contaminant characteristics of particular importance in regard




to availability include:




     •  Contaminant concentration




     •  Phase (e.g., gaseous)




     •  Polarity




     •  Persistence




     •  Solubility and lipophilicity




It is important to remember that contaminant characteristics may




change as a result of environmental factors, further complicating




assessments of availability.




     2.2.3  Plant Uptake and Translocation




     Available contaminants may assimilate into plants through two




basic routes, root uptake from soils and soil water, and foliar
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absorption.  Recent studies have indicated that foliar absorption is




an important entry route for such substances (see, for example,




Breck and Baes, 1985; Chaney, 1983; and Schaeffer, 1985).




Adsorption for many contaminants also is important since limited




available information indicates that some contaminants  (particularly




in sludges) may not be  removed by rainfall  (Chaney, 1983).  Thus,




contaminants on edible  surface areas may be consumed.




     Once a contaminant has  entered into a  plant,  it may migrate




(translocate)  to  a portion of  the plant other  than in the area in




which it entered.   If  the portion of  the plant  to which the




contaminant has translocated is inedible for both animals and




humans, it would  not  constitute a threat to the  remainder of the




human food chain.   An example of such  tissue are the leaves of




tomato  plants.  Otherwise, the threat  from  the contaminant to the




food chain would  continue.  Translocation,  therefore, may result in




differences in contaminant concentrations between different parts of




plants.  High  concentrations in edible portions  are of  concern in




the human food chain.




     As in the case of  soil  availability, plant  uptake  and




translocation depend  on the  interplay  of several plant  and




contaminant characteristics.  However, less is known about plant




uptake and translocation than about soil availability on a



micro-scale.   Plant uptake and translocation processes are known to



depend on several plant characteristics:
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     •  Plant species and cultivar




     •  Plant growing rate




     •  Time




     •  Relative humidity




as well as several contaminant characteristics such as concentration,



solubility, and phase.




     The extent of variation in uptake between contaminants and




plants is indicated in Tables 1 and 2.  As indicated in Table 1,




plant uptake varies considerably among polychlorinated biphenyls



(PCS), dioxin (TCDD), benzo-A-pyrene (BaP), and trichloroethylene




(TCE).  Furthermore, Table 1 shows that the variation between




studies for a single contaminant is even greater than the variation




between contaminants.  Table 2 indicates that zinc and cadmium




concentrations vary significantly among species of plant and plant




tissue.  Further, Chaney (1983) notes that zinc, cadmium, manganese,




molybdenum, selenium, and boron are easily absorbed by plants and




tend to translocate to edible tissues within the plant.  In




contrast, several other heavy metals (e.g., lead and trivalent




chromium) either are strongly bound to soil or are retained in plant




roots and hence do not migrate to plant foliage in injurious




amounts.  Finally, citing other studies, Carey et al., (1973)




indicate evidence of translocation of pesticides residues has been




found for corn, soybeans, alfalfa, carrots, potatoes, turnips,
                                 19

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                     TABLE 1

        SOIL TO PLANT UPTAKE FACTORS* FOR
            SELECTED  ORGANIC  COMPOUNDS
Compound
PCS
TCDD
BaP
TCE
Best
Estimate
1.0
0.001
0.1
0.1
Minimum
3 x 10~3
3 x 10~5
7 x 10~6
1 x 10~5
Maximum
10
1
40
10
*Soil to plant uptake factor is defined as the
 ratio of contaminant concentration in the plant
 to the contaminant concentration in the soil.

Source:  Schaeffer, 1985.
                      20

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                                                TABLE 2




       CADMIUM AND ZINC  CONCENTRATIONS  IN DIFFERENT CULTIVARS OF SOYBE
Soybean

Cultivar

Clark 63
Mandarin
Corsoy
Amsoy 71
Grant
Jackson
Richland
Dunfield
Arksoy
Harosoy 63



T.pttuce
Cd in
shoot
me/kg
1.4
2.0
2.2
2.4
2.9
3.2
3.5
4.3
4.8
6.0




Cultivar

Romaine
Boston
Bibb
Valmaine
Tania
Dark Green
Boston
Belmay
Butterhead 1033
Butterhead 1044
Buttercrunch
Butterhead 1034
Summer Bibb
Zn in
leaf
ma/kg
51
63
68
77
72

68
89
100
124
94
104
125
Cd in
leaf

1.8
1.9
4.2
3.8
4.4

5.0
5.2
5.3
5.7
5.8
6.2
8.1
Inbred
line

B77
R177
H96
H99
H100
R805
B37
Oh545
A619
H98
Oh43


Zn in
leaf

61.8
88. C
94.2
102. S
140.]
148.]
164.2
170. <
193.:
217.2
281.2


Source:  Council for Agricultural Science and Technology, 1981.

-------
and peanuts.  The authors indicate that pesticide residues in corn



tend to appear in the leaves rather than in the edible kernels.



     The existence of a "soil-plant barrier" for many plants and




contaminants that tends to protect humans and animals from




contamination in the lower levels of the food chain is important in




assessing terrestrial food chain risks  (Chaney 1983).  This barrier




arises for  three basic reasons.  First,  the low  solubility of




certain contaminants prevents  their uptake by plants.  Second,




certain contaminants are  immobilized  in fibrous  roots preventing




their translocation to edible  plant tissues.  Third, contaminant




phytotoxicity is  sometimes  lower  than animal and human toxicity.




Thus, the plant will die  before its contaminant  concentration




reaches high enough levels  to  warrant concern.   The potential




importance  of phytotoxicity in protecting human  and animal health is




illustrated in Table 3.   However,  as  indicated by Chaney  (1983), and




as  shown in Table  3, the  soil-plant barrier does not protect animals




from contaminants  such as cadmium, selenium, and molybdenum.  Food




is  considered to be the major  source  of cadmium  ingestion by humans




in  the general population (Hammons, Huff, and Braunstein, 1978).




     The final aspect of  plant  uptake and translocation is of




uncertain importance.  As indicated in Edwards (1983), plants may



contain substances that effect or transform assimilated




contaminants, rendering the contaminants less toxic.   Citing other
                                 22

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                                  TABLE 3

          PLANT PHYTOTOXICITY AS A BARRIER TO ANIMAL CONTAMINATION
                                       Maximum Levels  Chronically Tolerated*
                  Phytotoxic Level     	(mg/kg dry diet)
Element
As, inorganic
B
Cd**
Cr+3, oxides
Co
Cu
F
Fe
Mn
Mo
Ni
Pb**
Se
V
Zn
(mR/kR/drv foliage)
3-10
75
5-700
20
25-100
25-40
-
-
400-2,000
100
50-100
-
100
10
500-1,500
Cattle
50
150
0.5
(3,000)
10
100
40
1,000
1,000
10
50
30
(2)
50
500
Sheep
50
(150)
0.5
(3,000)
10
25
60
500
1,000
10
(50)
30
(2)
50
300
Swine
50
(150)
0.5
(3,000)
10
250
150
3,000
400
20
(100)
30
2
(10)
1,000
Chicken
50
(150)
0.5
3,000
10
300
200
1,000
2,000
100
(300)
30
2
10
1,000
 *Based on data presented in National Research Council,  1980.   Mineral
  Tolerance of Domestic Animals, National Academy of Sciences,  Washington,
  DC.  Continuous long-term feeding of minerals at the maximum  tolerable
  levels may cause adverse effects.  Levels in parentheses  were derived by
  interspecific extrapolation by NRG.

**Maximum levels tolerated based on human food residue consideration,
  rather than toxicity to livestock.

Source:  Chaney, 1983.
                                     23

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sources, Edwards (1983) states that many polyarometic hydrocarbons




(PAHs) are innocuous by themselves but may form epoxides that are




carcinogenic or mutagenic when biologically activated.   The author




also indicates that some research indicates that green plants contain




a substance (ellagic acid) that may inactivate the carcinogenic and




mutagenic potential of the diol epoxide form of BaP.  The extent of




similar phenomena for other contaminants is unknown.




     2.2.4  Animal Uptake and Translocation




     Animals take in contaminants  through at least five basic



mechanisms.  First, is direct ingestion of contaminated plant




tissues  (including feed).  A  second mechanism  is through the




ingestion of contaminated animal products such as milk.  A third




mechanism is through the ingestion of  contaminated soil.  Fourth, is




the direct  ingestion of contaminated surface or ground water.  A




fifth  is through the inhalation of contaminated air.  This last




mechanism is not considered in the following discussion as there is




little information in  the literature concerning its importance.




However, the possible presence of  volatile organic contaminants in




the air very near the soil surface indicates that this intake




mechanism may warrant further study.



     The relative importance of the four other intake mechanisms is



unknown.  Each is potentially important depending on the animals and




contaminants under study.   Wagstaff, McDowell,  and Paulin (1980)




state that contaminated feed is the primary source of  organochloride

-------
pesticide ingestion in animals.  Chaney (1983) presents the thesis




that soil ingestion is important, especially for persistent,




lipophilic, toxic organic compounds.  Chaney also observes that




cattle have been poisoned by lead at naturally occurring concen-




trations due to soil ingestion.  According to Chaney, 20 percent of




the diet of cattle is soil, since cattle consume complete plants




including soil-laden roots.  It is also important to note that




contaminants adsorbed on plant surfaces may be ingested.




     Chaney*s thesis is supported in part by Walton and Edwards




(1986).  These authors state that direct contact with soil is the




most important route for transfer of contaminants from soil to




livestock in particular, and herbivores in general.  These authors




also indicate that lactation provides a route for the elimination of




polybrominated biphenyls (PBBs) from the bodies of cows thus




providing an intake route for PBBs into the bodies of dairy or beef




calves.  Similarly, consumption of contaminated water is an




important intake route for soluble substances.




     As in the case of plants, once within the body of an animal,




contaminants may translocate to different parts of the animal and,




potentially, accumulate there.  These body parts include fat or




nonfat tissue, including bone tissue.  Alternately, the contaminants




may be temporarily stored in organs such as the liver or kidneys and




eventually excreted.  These various storage patterns are important




since humans consume both animal fat and nonfat tissues and animal
                                 25

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products such as milk.  The information in Tables 4 through 6 is



presented as an indication of the potential extent of differential




migration and accumulation in body parts.  Numerous other examples of




contaminant concentrations in various  animal  body parts can be found




in Cone, Faust, and Baldauf  (1984)  and Cone et al.,  (1986).




     Accumulation in animals occurs through both lipid partitioning




and  covalent  bonding (Trabalka and Garten, 1982).   The applicable




accumulation  mechanism depends on the characteristics of  the




contaminant;  some contaminants, such as pentachlorophenol (PCP), are




readily metabolized and eliminated from the body and do not




accumulate.   Contaminants such as polychlorinated biphenyls  (PCS)




accumulate by lipid partitioning.  Such bioaccumulation can  be




predicted  by  octanol-water partition coefficients.   Contaminants such




as methyl  mercury, which accumulate through covalent bonding, tend to




invalidate the universal use of octanol-water partition coefficients




in assessing  bioaccumulation in animals.




      2.2.5 Human Intake




      Table 7  presents an overview of the average yearly diet (in 1980)




of an  individual  in the United States, by major food commodity.  As




indicated  in  this table,  an  average individual in the United States




consumes over 1,220 pounds of  food yearly.  The largest commodity




groups are dairy  products (24  percent),  vegetables  (23 percent), and




meat and poultry  (17 percent).   Most of  dairy product consumption  is



in the form of milk.   Fresh  vegetable  and potato consumption  are the
                                 26

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N3
                                                  TABLE 4

             CONCENTRATION OF HEXACHLOROBENZENE (HCB) AFTER 12 WEEKS OF AD
Feed Rate
(mz HCB/ke/dav}
0 (control)
0.05
0.50
5.00
50.0**
Organ Concentration (me HC
Blood
9 ± 1
29 + 5
235 ± 18
2,520 ± 400
30,600 ± 3,900
Fat
4 ± 0.8
14.3 ± 1.2
121.2 ± 16.1
1,286 ± 200
15,453 + 7,851
Liver*
0.12 ± 0.06
0.27 ± 0.02
3.3 ± 1.3
42.3 ± 15.9
NA
        Concentration determined after 13 weeks after sacrifice of animali
       **Concentration determined after 8 weeks.  No animals in this group

       Source:   Adapted from den Tonkelaar et al., 1978.

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                        TABLE 5

      PLATEAU LEVEL ORGAN  CONCENTRATIONS IN RHESUS
         MONKEYS AFTER CHRONIC FEEDING OF 1 PPM
            HCB OR  2 PPM PCNB IN DAILY DIET
Organ
Blood
Muscle
Brain
Liver
Kidney
Adrenal Cortex
Thymus
Lymph nodes*
Bone marrow
Omental fat
HCB
(ppm)
0.22
0.1
0.6
0.7
0.2
2.7
3.8
2.0
7.7
13.6
PCNB
(ppm)
0.07
0.01
0.03
0.19
0.14
0.08
0.20
0.12
0.13
0.21
*Large intestine

HCB:    Hexachlorobenzene
PCNB:  Pentachloronitrobenzene

Source:  Muller et al.,  1978.
                          28

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                       TABLE 6

   DISTRIBUTION OF PCB AMONG BODY PARTS OF CATTLE*
                  (ppm Arochlor 1260)
Body Part
Adipose
Heart
Kidney
Liver
Lung
Muscle
Spleen
Number of
Cases
7
8
8
8
7
7
8
Mean
924
9.4
4.8
11.9
3.8
10.5
5.3
Range
170-1,900
2-26
1.8-7.5
2.7-36
1.9-8.5
1.4-26
1.3-8.6
*Previously taken tailhead fat biopsy levels 120-2,200 ppm.
 Feedlot cattle.

Source:  Cone, Faust, and Baldauf, 1984.
                         29

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                           TABLE 7

U.S. CONSUMPTION OF MAJOR FOOD COMMODITIES PER PERSON (1980)
                (Pounds per person per year)
Commodity
Dairy Products
Fluid Milk
Other
Vegetables
Freshb
Potatoes0
Sweet Potatoes0
Cannedd
Frozen6
Meat and Poultry
Beef
Pork
Poultry
Other
Fruit
Fresh
Processed*
Wheat Flour
Refined Sugar
Eggs
Other Food CommoditiesS
Fishh
Rice
Other Grains
TOTAL
Consumption
288.7
250
38.7
277.9
99.5
112.8
5.4
49.8
10.4
208.2
76.5
68.3
60.6
2.8
141.0
85.7
55.3
126.4
83.7
34.6
38.1
12.8
9.4
NA
1,220.8
Percent of
Total3
24
20
3
23
8
9
0
4
1
17
6
6
5
0
12
7
5
10
7
3
3
1
1
NA

                             30

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                         TABLE 7  (Concluded)
                              FOOTNOTES
aTotals may not add due to rounding.
"Commercial production for sale as fresh produce.
clncludes fresh equivalent of processed.
"Excludes potatoes and sweet potatoes.
eExcludes potatoes.
fIncludes canned fruit and juices, frozen juices, chilled citrus
juices, and dried fruit.
^Includes coffee, tea, cocoa, shelled peanuts, dry edible beans,
 and melons.
^Edible portion only.
Source:  Newspaper Enterprise Association, Inc., 1984.
                                 31

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principal components of vegetable consumption.   Meat and poultry




consumption is about equally split among beef,  pork and poultry.




Fruit, meat, and wheat flour constitute somewhat over 10 percent




each of the average diet.  Consumption of fresh fruit is slightly




over half of total fruit consumption.




     It is important to note that the dietary patterns of the




individuals in the United States may be changing, as illustrated by




a decline in pork consumption between in recent years (World Almanac




of Facts).  Further, these data do not account for potential




regional differences in food consumption patterns (e.g., per capita




consumption of fish is likely to be higher in coastal regions than




in the interior).




     An important consideration concerning the potential ingestion




of hazardous substances through human food intake is the role of the




U.S. Department of Agriculture and State and local public health




agencies in protecting the public food supply.   Two of the main




objectives of these programs are to ensure, to the extent possible,




that contaminated food does not enter the food distribution system




and, failing that, to identify and remove contaminated food from the




commercial food distribution system before widespread effects are




felt in the general population.  For example, the USDA Food and




Safety Inspection Service inspects 94 percent of the meat that




enters the commercial food distribution system (United States




Department of Commerce, 1983).  This system of public health
                                 32

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protection would play an important role in preventing adverse human




health effects from contamination of the human terrestrial (and




aquatic) food chains arising from uncontrolled waste sites.   The




protection of human health from noncommercial food contamination




(e.g. consumption arising from subsistence agriculture,  hunting, and




fishing) is more uncertain.




     2.2.6  Conclusions




     Several conclusions can be drawn from this discussion




concerning the terrestrial food chain and the potential  for



incorporating terrestrial food chain factors in the HRS.  First, the




terrestrial food chain is very complex.  A relatively large  body of




information is available on the potential for and mechanisms of




terrestrial food chain contamination by metallic inorganics  and many




pesticides.  Relatively little is known about other classes  of




compounds.  As summarized by Chaney (1983) in regard to  the  question




of risks from land application of toxic organic compounds (TOs),




"insufficient information is available to assess food chain  risk of




waste-borne TOs.  Environmentally relevant information on TOs is




quite limited, even among pesticides.  Little is known about fate




and potential for food chain effects of industrial TO wastes and




by-products that may be considered for application to land treatment




sites."  The extent of current knowledge concerning food chain risks




associated with toxic organics and other uncontrolled waste  site




contaminants is also limited.  As discussed in below, the
                                33

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limitations in knowledge about the terrestrial food chain make the




development of options for incorporating terrestrial food chain




risks into the HRS impractical at this time.



     However, given the quantity of food consumed by individuals,




the high levels of contamination sometimes found in and around




uncontrolled waste sites, and the demonstrated potential for




bioaccumulation in the terrestrial food chain, the potential exists




for some sites to adversely affect human health through the




terrestrial food chain.  The magnitude of this potential is unknown.
                                34

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3.0  EXISTING SYSTEMS FOR EVALUATING FOOD CHAIN EXPOSURES FROM
     UNCONTROLLED WASTE SITES

     Five systems which evaluate potential risk of hazardous

substances to human health through the food chain were identified

and reviewed as part of this effort.  They are:

     •  Hazard Assessment Rating Methodology I (HARM II)

     •  Prioritization of Environmental Risks and Control Options
        (PERCO)

     •  Action Alert System (AAS)

     •  Remedial Action Priority System (RAPS)

     •  Preliminary Pollutant Limit Value (PPLV) System.

The first four of these systems are reviewed in greater detail in

Haus and Wolfinger (1986).

     The review of each of these systems undertaken in this effort

focused on whether each of the five systems addressed the aquatic

and/or the terrestrial food chain in their ranking system, the

general methodology used in each of the systems which did address

the food chain, and the data requirements for addressing food chain

contributions to potential exposure.  This review indicated that

each of the five systems did address at least some aspect of food

chain exposures from waste sites, although only three addressed both

aquatic and terrestrial food chains as a composite input to their

overall ranking system.
                                35

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     Because of differences between the systems,  each is discussed




separately below.  A final section presents a summary of the results




of the examination.




3.1  Hazard Assessment Ranking Methodology II (HARM II)



     The HARM II ranking system is the only one of the five systems




considered which does not attempt to take into account any aspect of




the terrestrial food chain in its calculations.  Rather, HARM II




calculates hazard scores for the ingestion of contaminated fish.




This contaminant intake is calculated as a function of the estimated



consumption of fish by individuals, the contaminant concentration in




relevant surface waters, and fish bioconcentration factors.




     This calculation of food chain hazard potential is a part of




the HARM II process of evaluating overall human health and ecological




hazard potential.  The results of these calculations are fed into




the contaminant hazard score which, in turn, makes up a portion of




the overall model structure designed to provide a single site score




for comparison with other sites under investigation.




     The primary data requirements for the food chain portion of the




HARM II system are related to site-specific collection of




information on the concentrations of contaminants in surface waters




near the site.  This information, combined with species-specific




information on bioconcentration factors taken from the literature




and data on individual fish consumption,  is the basis of all data




used to calculate potential human contaminant intake.  Once hazard
                                 36

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quotients for all detected contaminants have been derived in this

manner, they are summed and a single health hazard index is derived

from the model documentation and used in remaining calculations.

3.2  Prioritization of Environmental Risks and Control Options
     (PERCO)

     The PERCO system has the capability to evaluate both the

terrestrial and the aquatic food chain in its evaluative structure,

but only the information related to the terrestrial food chain is

carried through the final calculations of the system.  The

information derived for the aquatic food chain is designed to be

used by individual analysts as an additional subjective input to the

total evaluation conducted with the aid of PERCO.

     The basic analytic structure for calculation of both the

terrestrial and the aquatic food chain components in PERCO relies on

the use of bioconeentration factors in both fish and in surface

vegetation.  The factors are combined with information on usage

rates for agricultural and fishing grounds, and with information on

individual contaminants, to form two distinct components of a health

score used by the PERCO system.

     The data requirements for the food chain in PERCO are limited

to information on bioconcentration factors as well as use rates for

items such as number of acres tilled or the number of fish which are

(or could have been, were a site not contaminated) harvested.  This

information is combined with toxicity data for individual contami-
                                37

-------
nants to form a final score, which is forwarded to the remainder of




the PERCO system.




3.3  Action Alert System (AAS)




     The AAS provides a framework to determine risk to human health,




focusing on the impact of waterborne pollutants. Within the AAS,




risk is expressed as a potential per capita effect.




     The primary mechanism of estimating risk in AAS is to determine




the potency of a pollutant and the exposure (or average daily




intake/ingestion) of an individual to that pollutant.  The per




capita risk is then defined in terms of the product of the exposure




and the potency.  In those instances in which it is not possible to




directly estimate exposure, a supplementary module of AAS uses




exposure through both the aquatic and terrestrial food chains to




form a part of the calculations determining total exposure.  These




calculations rely on estimates of per capita per day consumption of




various categories of foodstuffs, along with bioconcentration




factors for each contaminant being considered at a site.  The




results of these calculations are an estimate of the amount of an




individual contaminant ingested through the food chain; these




estimates are in turn fed into the per capita risk calculations.




     The primary data required for calculations involved in the




aquatic food chain exposure module are the amounts of each food type




ingested by an individual and the bioconcentration factors for each




pollutant.   For the terrestrial food chain,  data on the residue of a
                                38

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pollutant in that food is used in lieu of the bioconcentration




factor along with consumption data to determine the amount of a




pollutant ingested along with the food being considered.




3.4  Remedial Action Priority System (RAPS)




     The RAPS system was designed to rank sites according to their




relative hazard potential; it is not designed to be used to simulate




actual risks at a particular site resulting from the release of




contaminants.  Within the RAPS system, risk is expressed as a




fraction from zero to one on a per person basis.




     The basic computational structure of the model is to derive




exposure to the aquatic and terrestrial food chains through four




distinct transport pathways.  Exposure derived from these




calculations is used, in turn, to estimate the potential exposure of




the surrounding population from both the food chains and from other




exposure routes. Exposure through the food chain is calculated as




the product of the daily usage rate (e.g., amount of food eaten),




the concentration of a contaminant in the media of exposure (e.g., mg




of contaminant per kg of food), and appropriate conversion factors




which take concentrations and convert to dose rates.  The sum of all




such exposures is then normalized to determine an overall average




individual risk factor, which indicates the level of potential risk




to an average member of the exposed population.




     Once again, the major data requirements for determining the




potential exposure for the food chains include information on the
                               39

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bioconcentration of individual contaminants in each  food  item and




the quantity of food consumed by an individual.   Other  conversion




data is obtained from both model documentation and from the




literature.




3.5  Preliminary Pollutant Limit Value (PPLV) System




     The primary goal of the PPLV System is to provide  a  simplified




method to establish limits on allowable pollutant exposure from




hazardous waste sites.  The primary focus of the system is to




establish an acceptable individual daily dose of each contaminant




associated with an individual site, and to calculate whether the




site meets these requirements.  The use of the aquatic and terres-




trial food chain as exposure paths to these contaminants is an




integral portion of the overall system.




     Within the PPLV System, the primary focus is to determine the




amounts of contaminant which might be allowed through each of the




various exposure routes, and still not exceed the total allowable




dose for that contaminant.  These relationships are formed as a




series of equations which bring together all exposure components,




expressed as a function of the allowable exposure and concentrations




which are found in various media, including the water and soil,




surrounding a site.  The exposure through the food chain  routes is




calculated as a function of the concentration of a contaminant in a




type of food, and the amounts of that  food which are ingested.
                                40

-------
     The data requirements for the PPLV System are the most extensive




of the five systems included in this study.  Data on parameters for




chronic human exposure to contaminants, including information on




body weight, food intake and the fraction of different food types is




required.  In addition, the System requires information on values




for acceptable daily doses of toxic pollutants, and information on




bioconcentration factors.  Finally, the System requires data on the




chemical properties of each of the contaminants of concern.




3.6  Summary




     Although there are some very real differences among each of the




systems examined above, it is clear that, insofar as treatment of




the food chain exposure route, there are fundamental similarities.




     Each of the systems uses essentially the same method to




determine exposure through the food chain.  That is, bioconcentration




factors must be derived for each of the pollutants and food types




involved, these factors are coupled with the amount of the food




ingested, and the resulting product provides the exposure of an




individual to a specific contaminant.




     While the uses which each of the models makes of these data,




once they have been calculated, is somewhat different, the




fundamental use of food chain as an exposure route is identical.




Even for those models which consider only a portion of the food




chain, the basic structure remains unchanged.  The exposure through




the food chain is expressed as the concentration of a contaminant in
                                41

-------
the food (a value typically estimated from the concentration of the




contaminant in surrounding water bodies),  coupled with the volume of




food ingested.
                               42

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4.0  OPTIONS FOR INCORPORATING FOOD CHAIN RISK FACTORS INTO THE HRS




     This chapter examines options for incorporating food chain risk




factors into the HRS.  Completed options for aquatic food chain




factors are described.  As mentioned in Section 2, limits in the




state-of-knowledge of certain aspects of the terrestrial food chain




make development of terrestrial food chain options inpratical at




this time.  However, several aspects of the terrestrial food chain




that should be included in future options, should the state-of-




knowledge improve, are discussed.




4.1  Structure of the Current HRS




     The current HRS (47 FR 31180, July 16, 1982) considers three




migration pathways; ground water, surface water and air, in evalu-




ating the risks to human health or the environment from releases of




contaminants from uncontrolled waste sites.  Within each migration




path, the HRS considers three categories of factors:  release, waste




characteristics, and targets.  The release characteristics reflect




the probability that a release has occurred, is occurring, or will




occur based on either monitoring data or similar evidence (observed




release) or based on route characteristics and containment practices




(potential to release).  No "potential to release" option is




incorporated in the current HRS air pathway.  The waste




characteristics category reflects the hazard posed by the




contaminants that may be released from the site (either in the past,




currently, or in the future).  The targets category reflects the
                                 43

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characteristics of the population and environmental resources that



might be affected by releases from the site.  A total of 32 rating



factors are evaluated in these categories.



     The factor category values are multiplied and normalized to a



scale of 0-100 to yield a route score for each pathway:




     •  Ground water (S  )
                       gw


     •  Surface water (S  )



     •  Air (Sfl)



The  total migration score (S ) is calculated using a root mean



square algorithm:



     S - (1/1.73) x (S2  + S2  + S2)1/2                          (1)
      m               gw    sw    a


4.2  Aquatic Food Chain Methodology



     Due to deficiencies in the state-of-knowledge of intermedia



transfer of many contaminants of concern to the HRS, no options for



evaluating aquatic food chain risks associated with releases of



contaminants to ground water or air could be developed.  This



section presents options for incorporating only aquatic food chain



factors in the HRS surface water pathway.



     4.2.1  Overview of the Proposed Methodology




     Figure 1 presents the structure of the proposed aquatic food chain



methodology in the surface water pathway.  The options envision changes



to the waste characteristics and targets factor categories.  The release



category would remain unchanged.

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   Observed
   Release
    or
   Waste
Characteristics
                                                     Targets
    Route
Characteristics
      X
  Containment
Consider the same
factors as those
in the current surface
water route of the HRS
Consider BCF in addition
to the factors currently
in the surface water
Consider population
affected through
consumption of
contaminated fish
in addition to current
factors
                           FIGURE 1

          THE COMPONENTS OF THE PROPOSED
           AQUATIC FOOD CHAIN METHODOLOGY
                              45

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     The waste characteristics factors in the surface water pathway




account for important parameters affecting the concentration and




toxicity of hazardous substances in water.  The waste characteristics




factors in the aquatic human food chain component account for



important parameters affecting the concentration and toxicity of




hazardous substances in aquatic organisms.  No information was




identified indicating that  the toxicity of a particular dose of a




substance is different if that substance  is ingested from water as




compared with its  being ingested from such an aquatic organism.




Thus, the assumption is made  that the fish ingestion toxicity of a




substance is the same as the  water ingestion toxicity.  The




concentration of a contaminant in fish can be estimated using the




bioconcentration factor and the water concentration, as discussed in




Section 2.  Therefore, the  waste characteristics category in the




aquatic human food chain component is the same as that of the surface




water pathway with the addition of a  factor reflecting




bioconcentration potential.   Options  for  evaluating waste




characteristics in the aquatic human  food chain component are




described in Section 4.2.2.




     The population at risk from eating contaminated fish, shellfish




and other seafood  is the logical target in an aquatic human food



chain component.   This population is not necessarily the same as those




who might be at risk from drinking contaminated  water,  although some
                                46

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overlap is likely.  However, the risks to those people potentially

exposed through the ingestion of both contaminated drinking water

and contaminated food would be greater than those exposed to only

one contamination source.  The risk to those people doubly exposed

should conservatively be estimated to be the sum of the risks from

each exposure.  Thus, separate target factors are discussed for

drinking contaminated water and eating contaminated food for the

aquatic human food chain options.  Options for aquatic human food

chain target factors are discussed in Section 4.2.3.

     4.2.2  Waste Characteristics Factors

     Three options were developed as possible modifications to the

waste characteristics category.

     4.2.2.1  Option I.  McBrien, Saari, and Goldfarb (1987) proposed

an evaluation scheme for assessing the differential potential of

substances found at uncontrolled waste sites to bioconcentrate in the

aquatic food chain.  Substances were evaluated on a 1 to 6 scale*

based on measured or estimated bioconcentration factors.  The

maximum value of 6 indicates the substances which are most likely to

accumulate in fish tissue and a value of 1 indicates little

accumulation in fish tissue.

     The proposed scheme is illustrated as a decision tree in

Figure 2 (McBrien, Saari, and Goldfarb, 1987).  The data used to
*The scale employed in McBrien, Saari, and Goldfarb, 1987 served
 solely to illustrate the evaluation method.
                                47

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

Yesa



BCF
> 10,000
> 1,000-9,999
> 100-999
> 10-99
1-9
<1
Assigned
Value (V)
6
5
4
3
2
1

^ ,



                 Value = 0
                                                                                                          Value = V + r
                                                                                                                    Value = V
. Yesb ^

Log Pow
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
^ t

^^Tboes it Biomagnify'
                                                                                                          Value = V + 1
                                                                                                                     Value = V
. Yes ^

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

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



Value = v + 1

Value = V
b Use EPA bioconcentration values provided in EPA Water Quality Criteria documents if available, otherwise use maximum value found in literature.
c Either as reported from published literature; or calculated by Leo's Fragment Constant Method; or from Log P Data Base.
 " " -= 6, then final score is 6, regardless of biomagnification.
           If V
                                                                FIGURE 2
                             DECISION  TREE  FOR  RANKING  SUBSTANCES  FOR  POTENTIAL
                                           TO BIOACCUMULATE  IN  THE  FOOD  CHAIN

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evaluate substances Include:  biomagnlfication data, biocon-




centration data, logarithm n-octanol-water partition coefficient




(log Pow) data, and water solubility data.




     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 in Figure 2 (e.g., if the BCF is




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




     If information on BCF is not available, the substance is ranked




on the n-octanol-water partition coefficient, if log Pow data are




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 biomagnify through the food chain.  If the substance




has been shown to biomagnify, 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.
                                49

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     For those substances for which there Is no information on BCF,




Pow, or S, a score of zero would be assigned.  The 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.  Also,  it is possible  to  "tag"




substances for which there are no  data available  for further




investigation.  This-identification would allow,  at  least, a




laboratory analysis  of  the water solubility  of  the substance, and




could  lead to a preliminary  score for that  substance.




     Hazardous substances which  biomagnify  in the food  chain are a




great  concern, since,  at  each level in the  food chain,  substance




concentrations will  increase significantly.   Examples of substances




which  biomagnify  significantly in the aquatic food chain include DDT,




DDE, toxaphene  (Niethammer et al., 1984); PCBs  (Thomann and Connolly,




1984);  mercury, kepone, mirex, benzo-A-pyrene,  and naphthalene  (Kay,




1984).  These would  be  assigned  a value  of  6 using the  approach of




McBrien,  Saari and Goldfarb  (see Appendix A for further examples of




scoring with this method).




     The bioaccumulation  factor  value can be  added to the current




toxicity and persistence  factor  values to form  the surface water waste




characteristics category  value.  This value could be expressed as:



                             3 (TP) + B                           (2)




where TP equals the toxicity-persistence factor value in the surface



water pathway and B equals the bioaccumulation potential factor







                                 50

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value determined as indicated above.  Note that the implied weighting




of "3" is arbitrary and would need to be established by EPA, as well




as the numerical values assigned in the bioaccumulation factor scale.




     Another method of incorporating bioaccumulation potential is to




use a matrix like that shown in Table 8.  Based on the surface water




toxicity/persistence factor value and the bioaccumulation potential




factor value, a factor value for toxicity/persistence/bioaccumulation




is then read from the table.  For example, a substance with a surface




water toxicity/persistence value of 18 and a bioaccumulation poten-




tial value of 4 would receive a toxicity/persistence/bioaccumulation




factor value of 17.  This value would then be added to the waste




quantity factor value to yield the waste characteristics category




value in the aquatic human food chain component.




     4.2.2.2  Option II.  Option II also employs the BCF of a




hazardous substance to calculate the waste characteristics factor




value in the aquatic human food chain component.  The difference is




that, in assigning the waste characteristics value in the aquatic




food chain component, Option II considers the relative risks between




ingesting drinking water and consuming fish from the same




contaminated surface water body.  Under this option, the risk for




salt water fish is calculated as though the water was drinkable.




     The relative risk to an individual between the two ingestion




routes—fish and drinking water—depends on the relative amount of




contaminants ingested via the two ingestion routes.  If the amounts
                                 51

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                         TABLE  8

         EVALUATING WASTE CHARACTERISTICS FOR
          AQUATIC FOOD CHAIN OPTION—OPTION I
HRS SW Toxicity/
Persistence* Value
0
3
6
9
12
15
18
Bioaccumulation Potential**
1
0
3
5
7
9
11
13
2
0
4
6
8
10
12
14
3
0
5
7
9
11
13
15
4
0
6
8
10
12
14
16
5
0
7
9
11
13
15
17
6
0
8
10
12
14
16
18
 *The toxicity/persistence value of the substance in
  in the surface water pathway.
**As evaluated according to methodology presented in
  McBrien, Saari, and Goldfarb,  1987.
                          52

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of contaminant ingested are the same for the two ingestion routes,

the risk is assumed to be the same, lacking information to the

contrary.  For example, ingesting 0.1 kg of fish with a contaminant

concentration of 20 ppm is equivalent to drinking 2 liters of water

with a 1 ppm contaminant concentration because the amounts of

contaminant ingested are the same (i.e., 2 milligrams).  Therefore,

in assigning a waste characteristic factor value to the aquatic

human food chain component, the factor value should be the same as

that in the surface water methodology if the amount of contaminant

ingested is the same.

     Several concepts must be explained before the Option II

methodology can be discussed.  The first is equivalent concentration

(EC).  Equivalent concentration here is defined as the concentration

of a contaminant in drinking water that would result in the same

amount of contaminant being ingested by an individual from eating

fish.  Thus, EC is calculated as:

     E£ - (cone, in fish) x (amount of fish ingested)             (3)
               (amount of drinking water ingested)

In the absence of actual measurements in fish, the contaminant

concentration in fish may be estimated from contaminant

concentration in water (C) and the BCF for the contaminant:

                   concentration in fish = BCF x C                (4)

Substituting equation (4) into equation (3):

     — = BCF x     amount of fish ingested	                  (5)
     C          amount of drinking water ingested
                                53

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     The ratio EC/C reflects the multiplicative increase in the risk




to an individual if the route of exposure is changed from drinking




contaminated water to eating contaminated fish from the same surface




water body.  For purpose of simplicity, the ratio EC/C is referred




to as the fish factor (FF).  If FF is 1, it means the individual is




exposed to the same risk from drinking water and eating fish.  If FF




is greater than 1, the individual is exposed to higher risk from




eating fish.  If FF is less than 1, the risk is lower for the




individual from eating fish.




     As indicated  in equation 5, the value  of  FF depends on the




relative quantities of fish and water  ingested and  the bioconcen-




tration factor for the contaminant  in  question.  Assuming that




2 liters (2  kg) of drinking water are  ingested by an individual each




day  (Barnthouse et al., 1985) and that 0.016 kg of  fish is ingested




by an individual each day  (Thompson, 1984), FF is equal to




0.8  percent  of the BCF.




     Equivalently, for the assumed  ingestion rates  (2 liters of




water and 0.016 kg of fish), if BCF is greater than 125 for the




ingested fish, the individual is exposed to a  higher risk from




ingesting fish than drinking water.  If BCF is equal to 125, the




risk is the  same;  and if BCF is less than 125  the risk is lower from




ingesting fish.




     The Option II waste characteristics factor value in the aquatic




food chain component is shown in Table 9.   The hazardous waste
                                 54

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                                   TABLE 9

          WASTE  CHARACTERISTICS EVALUATION SHEET FOR THE AQUATIC
                      FOOD CHAIN METHODOLOGY-OPTION II
1
1 Rating Factor
1
1 Waste Characteristics
1
1 Toxicity/Bioaccumulation
1
I Hazardous Waste**
1 Quantity
1
|Multi-|
Assigned Value* Iplier I Value
0 3 6 9 12 15 18 21 24
012345678
1
1
Total Value


Max
Value
24
8
32
 *Numerical values shown are  for  illustrative purposes only.
**Same as the Hazardous  Waste Quantity Factor Value in surface water route.
                                      55

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quantity factor value is the same as that in the current HRS (47 FR




31180, July 16, 1982).  A toxicity/bioaccumulation factor value,




ranging from 0 to 24, is used in place of the toxicity/persistence




factor value of the surface water route in the aquatic human food




chain component.




     The toxicity/bioaccumulation factor value would be calculated




from the toxicity factor value of the substance and the bioaccumu-




lation factor value of  the substance using Table 10.  The toxicity




factor value would be the same as that used in the drinking water




component of the surface water pathway because it reflects ingestion




toxicity.  The bioaccumulation factor value may be evaluated differ-




ently depending on the  approach  used to evaluate the persistence of




the contaminant as described in  Wang (1986).  If the persistence




factor value is based on the expected concentration change (C/C )




over the target distance limit (as  proposed in Wang, 1986), the




bioaccumulation factor  value would  be that indicated in Table 11.




     If, however, the persistence ranking is not explicitly related




to the expected concentration change, then the bioaccumulation




factor value may be obtained using  the matrix shown in Table 12.




For example, if a substance receives a persistence factor value of 3




in the surface water pathway, and its FF value is 50,  it receives a




bioaccumulation factor value of 4.




     4.2.2.3  Option III.   In the third  option,  the bioconcentration




factor would not be used to determine a waste  characteristics  factor
                                 56

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                              TABLE 10

             RATING MATRIX FOR TOXICITY/BIOACCUMULATION
              FACTOR VALUE* FOR THE AQUATIC FOOD CHAIN
                       METHODOLOGY—OPTION II
                            Bioaccumulation***
Toxicity** 1 1
1
0 | 0
1
1
1 1 3
1
1
2 1 6
1
1
3 | 9
1
2
0
6
9
12
3
0
9
12
15
4
0
12
15
18
5
0
15
18
21
6 1
1
0 1
1
1
18 I
1
1
21 I
1
1
24 |
1
  *Numerical values shown are for illustrative purposes.
 **Toxicity factor value of the substance in surface water pathway.
***Bioaccumulation factor value of the substance in aquatic food
   chain methodology.
                                57

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                       TABLE 11

METHOD FOR EVALUATING THE BIOCONCENTRATION FACTOR VALUE
         Criteria
Rank*
Factor Value**
     (C/C0 x FF)

     Greater than 10         Very High
        1 to 10               High
     0.5 to less than 1      Moderate
   0.11 to less than 0.5      Low
   0.001 to less than 0.1    Very Low
     Less than 0.001          None
                 5
                 4
                 3
                 2
                 1
                 0
   *Note  that for the four lower ranks (i.e., with factor
   value of 0, 1, 2, or 3), the numerical ranges (i.e., less
   than  0.001; 0.001 to 0.1; 0.1 to 0.5; and 0.5 to 1) for
   the criteria are identical to that in the proposed
   persistence ranking method.
 **Numerical values shown are for illustrative purposes.
                         58

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                               TABLE 12

                  BIOACCUMULATION RATING MATRIX FOR
              AQUATICS FOOD CHAIN METHODOLOGY—OPTION II

Persistence**
3
2
1
0

0.1
1
0
0
0
Fish Factc
0.1 to 1
2
1
0
0
>r*
1 to 10
3
2
1
0

10 to 100
4
3
2
1

100
5
4
3
2
 *Fish Factor, calculated as:

    bioconcentration factor x daily fish per capita consumption
           per capita daily drinking water consumption

**Persistence factor value of the substance in surface water pathway.

Note:  Numerical values shown are for illustrative purposes.
                                 59

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value.  Rather, it would be used to select the contaminant(s)  to be




used in assigning a value to the toxicity/persistence value.   Those




chemicals with the highest combined toxicity/persistence/



bioconcentration values as indicated in Table 13, would be used to




evaluate the toxicity/persistence factor, the value assigned to the




toxicity/persistence factor, however, would be based on the toxicity




and persistence of the contaminant(s) only.




     4.2.3  Target Factor Evaluation




     Since the emphasis in the human food chain issue analysis is on



human health impacts of food chain contamination, the number of




people potentially affected (target population) by consumption of




fish contaminated by a release from a site is a logical basis for a




target category factor.  The target population in the aquatic food




chain component may be distinctly different from the local




population, particularly if the contaminated fish are caught for




nonlocal commercial distribution.  The potentially wide distribution




of contaminated fish in the commercial food distribution system




(assuming no USDA intervention) makes the direct accounting of the




people who consumed the contaminated fish infeasible.  One feasible,




surrogate approach to estimating the target population is to




estimate the amount of fish harvested from the contaminated surface



water body.




     The amount of fish harvested is commonly referred to as  "catch




data," "commercial landings,"  or "yield."  Yield  data for a specific
                                 60

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                             TABLE 13

      RATING MATRIX FOR TOXICITY/PERSISTENCE/BIOACCUMULATION
                 VALUE FOR THE AQUATIC FOOD CHAIN
                     METHODOLOGY—OPTION III
Bioaccumulation Potential**
HRS Toxiclty/
Persistence Value*
0
3
6
9
12
15
18
1
0
1
2
3
4
5
6
2
0
2
3
4
5
6
7
3
0
4
4
5
6
7
8
4
0
4
5
6
7
8
9
5
0
5
6
7
8
9
10
6
0
6
7
8
9
10
11
 *The toxicity/persistence value of the substance in the surface
  water pathway.
**As evaluated according to methodology present in McBrien,  Saari,
  and Goldfarb, 1987.
                              61

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region affected by a release would, therefore, Indicate the maximum




amount of contaminated fish which could be consumed.  Commercial




catch data are available and are reported annually by the National




Marine Fisheries Services  (e.g., Thompson, 1984).  However,




commercial landings are recorded by the port where  the fishing boat




enters and does not necessarily reflect the catch taken from the




vicinity of the port.  Thus, the geographic location associated with




commercial catch data may  bear only a  tenuous  relationship to the




location of the contamination.  Since  the proposed  methodologies




would require catch data for a host of water bodies which are in the




proximity of a hazardous waste site, available fish landings data




may be of little use in evaluating the target  population.  However,




other information  can be employed.




     A surrogate for yield data could  be the productivity of a given




body of water, expressed as production of fish in pounds per acre




and modified by percent of production  harvested.  Unfortunately,




specific data on productivity are  also very difficult to obtain.  It




is desirable to use a common measure of fish which  could be used as




an indicator of yield.




     One common method of  reporting fish statistics is "standing




crop" or the biomass of all fish present in a given area at one time.




Measures of standing crop  are strongly correlated with the annual




fish productivity,  (as defined above)  (Whiteside and Carter,  1972).




Measures of standing crop are relatively easy to obtain.   Appendix B







                                62

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provides a table with estimates of fish standing crops for a wide




variety of habitats.  These data could be used as an indicator of




yield for a given area.




     Yield data generally represent only a portion of the




productivity.  Henderson, Ryder and Kidhongania (1973) estimate that




30 to 50 percent of the production in lakes and reservoirs is




harvestable.  Carline (1975) reported that for wild brook trout, the




harvest ranged from 13 to 69 percent of annual productivity.  Snow




and Beard (1972) reported 9 percent harvest for pike in a northern



lake.  These figures indicate that it is necessary to incorporate an




explicit or implicit estimate of the percentage of the fishery




exploited to determine the amount of fish taken from a body of




water, given productivity.  In order to use a surrogate such as




standing crop for yield, the standing crop data would have to be




adjusted to obtain productivity, and adjusted again to obtain yield.




     The following sections describe two options for evaluating the




target factor in the aquatic food chain component of the surface




water pathway.  In both options the target factor value is based on




two independent factor values:  a resource factor value and a




fishery use factor value.




     4.2.3.1  Option I.  In Option I, the resource factor value is




based on the area affected and the standing crop of the affected




area.  The fishery factor value indicates the extent of the fishery




that is exploited.
                                63

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     Resource Factor.  To determine the fish resources which would




potentially be affected by a release from a site, two parameters




must be estimated.  One is the fish productivity, based upon




standing crop in pounds per acre.  The other is the acreage




affected.  Table 14 presents a method for evaluating the first of




these two parameters.




     To determine the standing crop of fish in pounds per acre, one




would contact the State Game and Fish Department, the State




University's Fishery Unit or Department of Fishery Science to see if




local data were available.  If not, literature data could be used




for the particular body of water in question.  If site-specific data




are not available, one could use the information contained in




Appendix B (or similar data from the literature), choosing a site




similar to the one being assessed.  Given an estimate of fish




production, fish production would then be evaluated using Table 14.




     To evaluate the area potentially affected by the release from




the site, one could using site-specific data on the extent of




contamination from the site.  Such data might include sampling data




from points downstream for water, sediments or biota.   In using such




data,  care must be taken to ensure that the contamination is attri-




butable to releases from the site in question.  Such data might be




available as part of the site inspection.  Alternately, information




on the areal extent of previous episodes of fish contamination




might  be obtained from a number of sources, including:  State
                                 64

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                    TABLE 14

PROPOSED FISH PRODUCTION FACTOR EVALUATION TABLE



    Standing Crop               Fish Production
  (pounds per acre)	Value*

    More than 500                       3

      51-500                            2

     50 or less                         1
  *Numerical values are for illustrative
   purposes only.
                      65

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Game and Fish Department, U.S. Fish and Wildlife Service, County




Health Department, Food and Drug Administration, National Marine



Fisheries Service, Office of Oceanography and Marine Science within




NOAA, or local fisheries laboratories.  If the extent of actual or




past contamination were unknown, the potential area could be




estimated as  the  surface area  of the potentially contaminated reach




as defined  in the current surface  water pathway  (47 FR  31180,




July 16, 1982).   Alternately,  the  area could be calculated as the




product of  the  surface water  target distance limit and  the average




width of the  surface water  body  in question over the reach defined




by the surface  water target distance limit.  In estimating the areal




extent of potential  contamination, surface water bodies which cannot




be connected  to the  site  by an overland flow or surface water body




flow pathway  (e.g.,  a surface  water connection or a known ground




water connection to  the  site)  should not  be included.




     Given  estimates of  the affected acreage and the fish production




factor value, the resource  factor  value can be evaluated using




Table 15.




     It should  be noted that this  approach might not include the




impact on migratory  fish which spend only a portion of  their lives




in the contaminated  zone.   This potential underestimate probably is




acceptable given  the  overall uncertainty in this screening procedure.




     Fishery Use  Factor.  The  type of area potentially  contaminated




will significantly affect the number of people  potentially exposed
                                 66

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                    TABLE 15

PROPOSED FISHERY RESOURCE FACTOR EVALUATION TABLE
Area Affected
10 acres or less
11-100
101-1,000
1,001-10,000
Fish
1
1
2
3
4
Production Value*
2
2
3
4
5

3
3
4
5
6
  *Numerical values are for illustrative  purposes
   only.
                        67

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to contaminated fish.  Assuming no intervention by the USDA, fish




harvested from a contaminated commercial fishery will affect




significantly more people than fish caught by  subsistence  or sport




fishermen.  The fishery use factor is a scalar value which reflects




the effect  that the  type of fishery has on the size of the




population  at risk.




     If an  area potentially or actually contaminated were  harvested




commercially, it would be considered to be in  the commercial




category and would be assigned a  fishery use factor value  of 3.  The




commercial  category  could also include areas which were previously




fished commercially  (within the past 10 years), but which  have been




closed because of contamination of fish from a release.




     If the area were used locally as a source of food for




subsistence or if the area were used for year-round recreational




fishing, it could also receive a  fishery use factor value  of 3.




However, if the area were used only seasonally, for example when a




locally popular fish run is evident, then it would be assigned a




fishery use factor value of 2.




     Finally, if the area were used infrequently, illegally, had no




public access, or was used only on a "catch and release" basis, it




would be assigned a  fishery use value of 1.   Generally, this low




factor value reflects the belief that the exposed population would




be small in size.   In areas where there is a significant amount of



illegal fishing (for reasons  other than contamination),  this
                                68

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approach might lead to an underevaluation of the size of the




population potentially exposed.




     Combined Target Population Factor Value.  The combined target




population factor value would be evaluated using the resource factor




value and the fishery use factor value as indicated in Table 16.




Note that the numerical values shown are for illustrative purposes




only.




     Effects of Consumption Patterns for Different Fisheries.  In




the options discussed above, no consideration was given to the




difference in consumption patterns of catch from different fisheries.




The size of the catch from different fisheries is assumed to reflect




the number of people potentially affected by the contaminated fish.




United States sources of fish are diverse.  Therefore, the consumer




of fish purchased commercially rarely consumes fish from only one




area.  On the other hand, subsistence and sport fishermen do consume




a large portion of their catch and might be assumed to obtain a




large portion of their overall fish consumption from their own




fishing activities, and thus from a single fishery.




     The overall result of these differences is that although the




number of people exposed to contamination from a commercial fishery




is larger than that from a subsistence fishery, the overall




contaminant dose received by an individual consuming commercially




harvested fish may be lower.  Similarly, subsistence fishermen and




those depending on subsistence fishing in a contaminated fishery
                                 69

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                     TABLE 16

EXAMPLE TARGET FACTOR EVALUATION TABLE FOR AQUATIC
               FOOD CHAIN METHODOLOGY
Fishery Use*
Resource Value
1
2
3
4
5
6
1
1
2
3
4
5
6
2
2
4
6
8
10
12
3
3
6
9
12
15
18
*1 = Infrequent, illegal, or "catch and release"
     fishing.
 2 = Seasonal fishery.
 3 = Subsistence or year-round recreational
     fishing or commercial use in past ten years
     for either fish or shellfish.

Note:  Numerical values are for illustrative
       purposes only.
                       70

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would be smaller in number but would receive a higher total dose,

since a larger fraction of their total fish consumption would be

contaminated.

     If the consumption pattern is to be included as a factor, the

evaluation methods proposed above for the waste characteristics and

target categories could be modified to reflect the smaller dose

(therefore, lower toxicity) but wider distribution (therefore, more

people affected) of the fish distributed through commercial fishing.

     A simple modification of the previously described options is to

reduce the waste characteristics score value but to increase the

target score according to the following:

     •  Waste Characteristics Category:

        - No change for subsistence and recreational fisheries.

        - Lower the toxicity/bioaccumulation factor value by 3 for
          commercial fisheries.

     •  Target Category:

        - No change for subsistence and recreational fisheries.

        - Increase the target factor value by 3 for commercial
          fisheries, but maintain the maximum target score of 18.

     4.2.3.2  Option II.  Under this option, a human food chain

population value is assigned based on the production of the fishery

under consideration (pounds per year) and the bioconcentration

potential of the contaminants that might escape from the site.  For

a given fishery production level and bioconcentration potential, the

value assigned to the human food chain production factor represents
                                71

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the equivalent number of people exposed through contaminated

drinking water to the same exposure level as is indicated by the

fishery production level.  This relationship can be expressed

mathematically as:

                       P  = S. x (D  x P )/BCF                    (6)
                        tr     w    w

where:   Sf = unit conversion factor approximately equal to 804.69
         Pf = annual fish production (pounds per year)
         Dw = daily personal  drinking water consumption (liters
              per day)
         Pw = the number of people drinking the water
        BCF = bioconcentration factor  (as per McBrien, Saari, and
              Goldfarb, 1987)

It is  important  to note that  this relationship is independent of

both the ambient concentration of the  contamination and the daily

personal fish consumption rate.

     As an example of the use of this  equation, a food chain

production level of approximately 1,000,000 pounds of fish per year

would  be expected to result in the same exposure in the population

consuming the fish (assuming  a BCF of  10), as would occur in a

population of 6,214 people drinking 2 liters of water per day.

     This equation allows the human food chain population value to

be employed in the same fashion as the drinking water population in

determining a target factor category value for a site.  Thus, a food

chain production level of 1,000,000 pounds per year coupled with a

BCF of 10,  would be assigned  the same factor value for food chain

production as might be assigned to 6,214 people in a drinking water

factor (e.g.,  the population served  by  drinking water factor in the
                                72

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current HRS).  Based on the evaluations in the current HRS, a site

affecting a fishery with a production of 1,000,000 pounds of fish

per year with contaminants having a BCF of 10 might receive a human

food chain production factor value of 24, given a distance of

between 1 and 2 miles from the probable point of entry or from the

point of known contamination (47 FR 31180, July 16, 1982).

     Given the uncertainties in the data for fishery production and

the uncertainties in available estimates of bioconcentration

factors, this option employs Table 17 rather than the exact equation

described above in determining the human food chain population

value.  The values in this table were derived using the equation and

the midpoints of the indicated ranges.

     In this option, the fishery production is the annual production

(in pounds) of human food chain organisms (e.g., fish, shellfish)

from within the fishery under evaluation.  Fishery production is

estimated using the following hierarchy of data and assigned a value

using Table 18:

     •  Actual data on yield from the surface water body or on the
        stocking rate for the surface water body.

     •  Actual data on productivity of the surface water body.

     •  Default values on standing crop from Appendix B.*
*Standing crop (measure of productivity) needs to be converted to
 pounds of fish per year within fishery by multiplying by the acreage.
 Additionally, standing crop data also needs to be multiplied by 0.2 to
 convert the standing crop data to human food chain yield.
                                 73

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                                         TABLE 17

                                 FOOD CHAIN POPULATION VALUE
09
LJ
o
o
§ 6
H
§ 4
8 ,
H 3
M
3 2
g 1

0 160
0 16
0 1.6
0 0
0 0
0 0
0 1



1,600 16,000
160 1,600
16 160
1.6 16
0 1.6
0 0
2 3
HUMAN


160,000 1
16,000
1,600
160
16
1.6
4
FOOD CHAIN


.6 X 106 1.6 x 107
160,000 1.6 x 106
16,000 160,000
1,600 16,000
160 1,600
16 160
5 6
PRODUCTION VALUE


2.0 x 107
1.6 X 107
1.6 X 106
160,000
16,000
1,600
7



2.0 X 107
2.0 x 107
1.6 x 107
1.6 x 106
160,000
16,000
8

*A value of 2.0 x 107 or greater will result in the maximum value for the human exposure
 factor for all dilution weighting factors.

-------
                   TABLE 18

         FOOD  PRODUCTION VALUE TABLE

Human Food Chain Production                 Assigned
    (Pounds per Year)	                   Value

          0                                      0
Greater than 0 to 10                             1
Greater than 10 to 100                           2
Greater than 100 to 1,000                        3
Greater than 1,000 to 10,000                     4
Greater than 10,000 to 100,000                   5
Greater than 100,000 to 1,000,000                6
Greater than 106 to 107                          7
Greater than 107                                 8
                   75

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This value is then combined with the bioconcentration potential




value (as described in McBrien, Saari, and Goldfarb, 1987) to yield




a human food chain population value, as indicated in Table 18.




4.3  Terrestrial Food Chain Methodology




     As indicated in Section 2.0, options for incorporating factors




into the HRS reflecting terrestrial food chain risks could not be




developed.  This is primarily due to the lack of an empirical data




base and limitations in knowledge of bioaccumulation processes and




the resulting impracticality of developing bioaccumulation factors



for use in a terrestrial food chain option.  Additional difficulties




of lesser importance were also encountered.  Similar information




gaps exists in knowledge about the aquatic food chain.  However,




these gaps in information are of considerably less importance for the




purposes of the HRS since, for the most part, the bioconcentration




factor can be employed to estimate fish contamination levels




adequately.  No such single factor is known that can be similarly




employed for the terrestrial food chain.




     Despite the failure to develop options, several factors and




categories of factors were identified that should be incorporated




into any future options that might be developed.  This section




presents a discussion of these factors, and, where available, data




sources that could be used to evaluate these factors in the context




of the HRS.
                                76

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     4.3.1  Factors for Inclusion in Terrestrial Food Chain Options

     Based on an examination of terrestrial food chain risk

assessment methodologies and the phenomenology of terrestrial food

chain bioaccumulation, the following six factors and factor

categories were identified as important in assessing terrestrial

food chain risks:

     •  Bioaccumulation factors

     •  Soil characteristics

     •  Agricultural characteristics

     •  Distance

     •  Food consumption patterns

     •  Hunting purposes and practices

     Bioaccumulation Factors.  Bioaccumulation factors reflect the

migration of contaminants into and through the terrestrial food

chain.  They or their equivalent are an essential part of any system

designed to reflect the risks posed by terrestrial food chain

contamination.  Bioaccumulation factors reflect the transfer of

contaminants between components of the human food chain, including:

     •  From the atmosphere to plant tissues.

     •  From soil to plant tissue.

     •  Among plant tissues.

     •  From soil to animals (via both direct ingestion and through
        plant ingestion).

     •  Within animals (e.g., from forage to milk).
                                 77

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Current approaches to terrestrial food chain modeling (e.g., Dixon




and Holton, 1984; Schaeffer, 1985; the aquatic food chain methodology




discussed in Section 4.0; McBrien, Saari, and Goldfarb, 1987),




employ either measured bioaccumulation factors for a limited number




of contaminants  or employ estimation  approaches  based on structure/




activity relationships (SARs).  As indicated in  the previous




discussion, measured bioaccumulation  factors for the terrestrial




food chain are available for only a few  contaminants.  Charles Garten




and John Trabalka of Oak Ridge  National  Laboratory conducted an




extensive analyses of the potential for  employing SARs in estimating




bioaccumulation  factors for use in terrestrial food chain modeling




(Trabalka and Garten, 1982  and  Garten and Trabalka, 1983).  As a




result of their  examination of  data originally presented by Kenaga




(1980) and from  analysis of additional data, they concluded that




neither water solubility nor the octanol-water partition coefficient




(the two parameters most commonly used in SARs for bioaccumulation)




could be used to accurately predict the  bioaccumulation of




contaminants in  the terrestrial food  chain.  These authors also




investigated the possibility of using bioaccumulation factors for




fish to estimate terrestrial vertebrate  bioaccumulation factors.




They concluded that this also is not  reasonable.   Table 19 presents




the results of their regression analysis.




     In regard to the results listed on Table 19, the question can




be raised as to whether the regression equation relating the natural
                                 78

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                              TABLE 19

     CORRELATION COEFFICIENTS (R2) FROM LOGARITHMIC REGRESSION
             ANALYSES PERFORMED BY GARTEN AND TRABALKA
                                         Independent Variable
     Dependent Variable           SOL        ROW       FW      ME

     Ruminant Fat BF              54          34       39      43
     Nonruminant Fat BF           49          35        9      39
     Bird Fat BF                  48          54       20      35
     Overall BF                   60          37
SOL:  Water Solubility
KOW:  Octanol-Water Partition Coefficient
 FW:  Fish under flowing water conditions
 ME:  Fish under model ecosystems conditions
 BF:  Bioaccumulation Factor

Source:  Adapted from Trabalka and Garten, 1982 and Garten and
         Trabalka, 1983
                                 79

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logarithm of the water solubility of a contaminant to bioaccumu-




lation factor for the contaminant is sufficiently accurate for the




purposes of the HRS.  According to Trabalka and Garten (1982),




variations in the common logarithm of water solubility account for




60 percent of the variations in the common logarithm of the




bioaccumulation factor through the following equation:




        log BF = 0.596 - 0.694 log (water solubility)             (7)




Garten and Trabalka caution that the equations they developed do not




reflect very well the bioaccumulation of contaminants by other than




lipid partitioning (e.g., covalent bonding).  They note that their




equations would indicate that methyl mercury has a relatively low




bioaccumulation factor when in fact it is highly bioaccumulative.




The equations are prone to sometimes sizeable errors.




     Further, the use of SARs to reflect bioaccumulation in plants




and between animal tissues has not been investigated in detail.  As




discussed previously, little information is available on the




partitioning of contaminant concentrations between fat and nonfat




tissues and among nontissue components of animals.  Further, few




data are available on plant bioaccumulation factors.  Dixon and




Holton (1984) employ the octanol-water partition coefficient to




estimate all of the bioaccumulation factors (ingestion-to-beef,




ingestion-to-milk, and soil-to-vegetable plant)  used in the




FOODCHAIN model (Dixon and Holton,  1984)  despite the results of




Garten and Trabalka.   Dixon and Holton also assume  that  the
                                 80

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soil-to-reproductive plant factor is one-tenth of the soil-to-




vegetable plant factor.  The validity of this approach is not well




established, given the results of Garten and Trabalka.




     Schaeffer (1985) also compiled information on bioaccumulation




factors for PCB, BaP, TCDD, and TCE for use in food chain modeling.




His information is summarized in Tables 1 and 20.  His estimates




indicate the great degree of uncertainty associated with




bioaccumulation factors for even these four relatively extensively




studied contaminants.  Values ranged as much as six orders of




magnitude.




     Overall, the authors believe that an insufficient amount is




currently known about bioaccumulation in the terrestrial food chain




to support the development of bioaccumulation factors that are




sufficiently accurate for a sufficient number of chemicals to




support their use in the HRS.




     Soil Characteristics.  As discussed in Section 2, the ability




of soils to bind contaminants is an important factor in reducing




migration through the terrestrial food chain.  This indicates that




the incorporation of a factor that reflects the ability of soils in




and around the uncontrolled waste site under evaluation to bind




contaminants into an HRS terrestrial food chain factor would be




needed.  Based on the review of the literature, such a factor should




be based on the organic matter and clay content of the soil; the




first to reflect availability of lipophilic compounds, the second to
                                81

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                              TABLE 20

          TRANSFER FACTORS FOR SELECTED ORGANIC COMPOUNDS

                  Forage to Meat  Transfer Factors*

         Compound   Best Estimate    Minimum    Maximum

         PCB            0.005        1 x 10~4     0.1

         TCDD           0.0001      0.1 (sic)     0.1

         BaP           1 x 10~5       1 x 10~7     0.001

         TCE           1 x 10~6       1 x 10~8   1 x 10~6
                 Forage  to Milk Transfer Factors**

         Compound   Best  Estimate     Minimum     Maximum

PCB
TCDD

BaP
TCE

0.01
0.01

0.0001
1 x 10"6
-4
1 x 10 *
1 x 10~5
-6
1 x 10 °
1 x 10~6

0.1
1.0

0.01
1 x 10~6
 *Forage to meat transfer factor is defined as the ratio of the
  concentration of the contaminant in animal meat to the product of
  the concentration in the animal feed (or forage) and the daily
  feed rate.
**Forage to milk transfer factor is defined as the ratio of the
  concentration of the contaminant in animal milk to the product of
  the concentration in the animal feed (or forage) and the daily
  feed rate.
Source:  Schaeffer,  1985.
                                 82

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reflect availability of nonlipophilic compounds.  A description of




such a factor is presented in Sayala (1986), which could be adapted




for use as part of a terrestrial food chain factor.




     Further, as indicated in Breck and Baes (1985), factors




reflecting the potential for contaminants to persist or degrade in




the soil are also needed to adequately assess terrestrial food chain




risks.  These factors should reflect both soil-specific and




contaminant-specific characteristics relating to the potential for




the contaminants to transform or degrade as a result of processes



such as hydrolysis, photolysis, and biodegradation.  Suitable




approaches for reflecting these processes in the HRS cannot be




developed based on the available information on soil kinetics.




     Agricultural Characteristics.  Several agricultural




characteristics of the area surrounding the site are important in




determining the human terrestrial food chain risk posed by the site:




     •  Purpose of agriculture




     •  Types of agriculture




     •  Agricultural productivity




     •  Agricultural acreage




     •  Agricultural practices




     The first is the purpose of the agriculture.  It is important




to distinguish between subsistence and commercial agriculture since




the risks posed as a result of each are different.  Contamination of




subsistence agricultural products probably would result in relatively
                                83

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high  exposures to contaminants for relatively few people, all other




factors being equal.  Total dietary contaminant levels would most




likely be  relatively high since the contaminated food would probably




constitute a relatively large fraction of the diet of the exposed




individuals.  However, by its definition, subsistence agriculture is




designed to feed a relatively small number of people.  Conversely,




commercial agricultural contamination would probably expose a




relatively large number of people to possibly low average exposure




concentrations (although high individual exposures would be



possible).  For contaminant/effect combinations characterized by




linear, no-threshold dose response functions arising from chronic




exposures, these distinctions are probably unimportant.  However,




for contaminant/effect combinations arising from nonchronic




exposures, these distinctions are important.  It should be possible




to determine the purposes of the agriculture being conducted around




a site during a CERCLA site inspection.  Thus, the evaluation of




subsistence versus commercial agricultural factors should be




feasible.  This distinction also indicates that resident farmers,




ranchers, and their families should be accorded heavier weight in




evaluating population-based factors since a higher fraction of their




diet would be their own agricultural products and hence they may be




exposed to a higher overall dose than consumers outside the local




marketplace.
                                84

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     The type of agriculture is also important.  The risk posed by a




site via terrestrial food chain contamination depends on whether the




affected biomass is animal or plant.  The risk further depends on




whether the animals are used for meat or milk production and also




depends on the type of animal (e.g., cattle, sheep, pigs, chickens)




or plant (e.g., corn, wheat, soybeans).  These dependencies arise




jointly from differences in bioaccumulation characteristics among




these types of agriculture as well as differences in human dietary




patterns.  Again, development of such information would be possible




as part of a CERCLA site inspection.  Sources for this type of data




include direct inspection, the local agricultural extension service




agents, the Soil Conservation Service, and general literature




sources such as Shor et al. (1982).




     The total quantity of food product potentially (or actually)




contaminated is an important factor in determining risk from food




contamination.  The total quantity of food product is an indicator




of both the size of the potentially exposed population and the value




of the resource at risk.  Since production is the product of




productivity and acreage, agricultural productivity and acreage are




important factors that should be included.  This information should




also be available during a site inspection, either from direct




inspection or by contacting the local agricultural extension service




agent or the Soil Conservation Service.  Alternately a general




literature source such as Shor et al. (1982) could be employed.
                                85

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     As indicated by Breck and Baes (1985), agricultural management




practices are very important in evaluating the risk of terrestrial




food chain contamination.  Of particular importance are practices




that would indicate the degree of contaminated soil and water




ingestion by food and milk animals as well as the extent of




irrigation by contaminated or potentially contaminated water.  For




example, it would be important to evaluate the extent to which




animals are allowed to graze freely over potentially contaminated




fields and the extent to which they are fed uncontaminated feed.



Information on animal feeding practices might be difficult to




obtain.  However, information should be readily available on the




extent of irrigation water use.




     In total, the risk posed by a site will depend in part on the




activities of the farmers and ranchers whose production would be




potentially affected.  Each of the factors discussed is potentially




important, although which are most important is unknown.




     Distance.  As is the case in any assessment of potential




exposure, the distance from the source of contamination to the point




of exposure is an important consideration.  Distance factors are




included in all of the HRS target categories to account for, among




other things, a decline in exposure concentrations among people




living further from the sources of contamination.  Similar




considerations indicate that the distance from the source of




contamination to the potentially affected agriculture is an







                                 86

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important consideration that should be reflected in any HRS




terrestrial food chain factor.  The evaluation of distance has been




found to be relatively straightforward in the existing applications




and there is no reason to believe that distance would be difficult




to evaluate as part of a food chain factor.




     Actual methods for incorporating distance into such factors




would depend on characteristics of the factors such as the migration




pathway associated with the factor.  A general question would have^




to be addressed regardless; at what distance from the site would the



potential for contamination be considered acceptable (i.e., what is




the target distance limit).  No information is readily available in




the literature that would indicate such limits.




     Food Consumption Patterns.  The table discussed in Section 2.2.5




(Table 7) illustrates the average per person consumption of food




commodities in the United States.  It is possible that there is




significant regional variation in these patterns, although such data




could not be identified during this investigation.  If significant




variations exist, then such information might be incorporated into a




HRS terrestrial food chain factor.  The need for this would depend




on the extent of the variation and the geographic extent of the




distribution of the potentially contaminated food.




     Hunting Purposes and Practices.  The type and extent of hunting




in the area around a site is an important determinant of the risk




from contamination of the non-commercial-food portion of the human
                                87

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terrestrial food chain.  There are two general forms of hunting:




subsistence and sport.  Subsistence hunters would generally be at



increased risk as compared with sport hunters for reasons similar to




those discussed previously for subsistence farmers.  Generally,




sport hunters would be at risk only in potentially acute exposure




situations.  It is uncertain whether it is important to include such




considerations in an HRS food chain factor.




     4.3.2  Conclusions and Recommendations




     Several factors have been discussed that could be employed in a



human terrestrial food chain factor in the HRS.  Lack of information,




however, regarding the processes of bioaccumulation and soil kinetics




as they affect the terrestrial food chain, preclude the development




of HRS options in this area at this time.  Given that contamination




of the terrestrial food chain by waste site contaminants is possible,




the approach of screening potential sites for public health advisory




investigations should be investigated as one way to provide for




these sites under the National Contingency Plan.




4.4  Additional Issues Concerning Human Food Chain Risks and the HRS




     In the course of investigating options for incorporating human




food chain factors in the HRS, two issues arose regarding the




implementation of the options.  The first of these two issues is the




relative importance of food chain contamination as compared with




ingestion of contaminated water and inhalation of contaminated air.




The resolution of this issue is necessary before the second issue of
                               88

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how to incorporate food chain factors into the HRS can be resolved.




Specifically, if food chain contamination is of equal concern with




the direct ingestion of contaminated water, then an argument can be




made, for example, for including food chain as a fourth "migration




pathway" in the HRS.  This section discusses these issues and, where




possible, presents possible resolutions.




     As stated above, the first issue is the relative importance of




food chain contamination as compared with other routes of human




exposure to hazardous substances released from uncontrolled waste




sites.  The limited discussion of food contamination incidents




presented in Section 1 indicates that food chain contamination may




be of concern for some sites.  It is possible that food chain




contamination may exceed other contamination routes in importance in




some locations, e.g., where contaminated surface water bodies are




used for commercial and sport fishing but not for drinking.  In




addition, there are two subsidiary issues concerning the relative




importance of exposure routes:  subsistence and sport versus




commercial food production routes and crop versus livestock




consumption routes.




     As indicated in the previous chapters, these issues of the




relative importance of various exposure routes cannot be resolved at




this time.  As a result, the question of whether a separate food




chain pathway should be developed in the HRS cannot be completely
                                89

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resolved at this time.  However, a partial resolution of this issue




is possible.



     As discussed previously, it is not possible at this time to



develop methodologies addressing food chain contamination except in



the case of aquatic food chain contamination arising from surface



water migration of contaminants.  Tentatively, it seems improbable




that risks from aquatic food chain contamination would routinely be




of the same degree as risks about other exposure routes such as




drinking water ingestion.  Thus, the methodologies presented above



address incorporation of aquatic food chain factors within the HRS



surface water pathway.  This decision on the placement of the



aquatic food chain factors raises the issue of the relative degree



of concern about contaminated surface water ingestion and surface



water/aquatic food chain contamination.  This issue raises the



practical problem of how to combine aquatic food chain contamination



risk evaluations with surface water ingestion risk evaluations



within the framework of the HRS.  Several integration methods were



examined, as discussed below.  No decision was made as to which is



preferable.




     The proposed surface water aquatic food chain methodologies



envision a branching with the surface water pathway.  The surface



water ingestion route score would be the product of a release




category value, an ingestion-based waste characteristics category



value and an ingestion-based targets category value.  The surface
                                90

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water aquatic food chain route score would be the product of the
same release category value, aquatic food chain-based waste
characteristics category value and an aquatic food chain-based
targets category value.  For purposes of discussion, let the
nonnormalized ingestion-based route score be RS , and the
nonnormalized aquatic food chain-based route score be RS
                                                        aq
Similarly, let the normalized ingestion-based route score be S.
(i.e., 100 x RS./RS.    ), and the normalized aquatic food
               1   1 j D13.X
chain-based route score be S  .  In these terms, the challenge is
to express the combined surface water pathway score (S  ) in terms
                                                      sw
of S. and S   .
    i      aq
     The simplest approach is to combine the nonnormalized scores by
adding them (e.g., nonnormalized combined route score equals RS  +
RS  ).  A combined normalized route score (S  ) could then be
  aq                                        sw
calculated as that sum divided by the sum of the maximum possible
scores.  This approach is basically the same as is used in
determining the combined targets category score in the current
surface water pathway.  It is important to note, however, that this
approach would require the determination of the relative importance
of the two routes so that appropriate factor weighting values could
be developed.
     Several approaches employing the normalized scores can be
developed.  The simplest is to employ the maximum of the two as the
                                 91

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combined value.  A second alternative is embodied in the following
equations:
        S   = minimum (K, 100)                                    (8)
         sw
          K = (S? + S2 )1/2                                       (9)
                i    aq
     All of the above approaches share two important characteristics.
First, the combined score is always at least the larger of the two
subsidiary scores.  This reflects the principle that the combined
risk should be at least as large as the individual risks.  The second
is that the maximum possible nonnormalized score does not exceed 100.
     A third alternative is to employ the root mean square algorithm
used to combine pathway scores in the current HRS, i.e.:
                                o     o      1/0
                      Ssw = [(Si + Saq)/2]                       (10)
In this approach, the combined score may be less than the largest of
the individual scores.  However, the maximum possible score is less
than 100.  As stated earlier, no decision was made as to the
desirability of any of these approaches.
                                 92

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5.0  CONCLUSIONS




     Several conclusions can be drawn from the preceding




discussions.  First, there is clearly a potential for human food




chain contamination arising from CERCLA releases of hazardous




substances into the environment.  The relative importance of the




risks to human health and of resource loss associated with human




food chain contamination in comparison with risks from sources such




as ingestion of contaminated ground water is problematic.  Second,




the state-of-knowledge of the aquatic food chain is sufficient to




support the development of aquatic food chain options for the




surface water pathway in the HRS.  Options for reflecting aquatic




food chain risks in the surface water pathway are presented,




although some issues associated with implementing the options remain




unresolved.  Third, development of options for the ground water and




air pathways cannot be undertaken at this time due to limitations in




empirical data and knowledge of important intermedia transfer




processes (e.g., contaminant specific deposition rates).  Finally,




development of options for reflecting terrestrial food chain risks




in the HRS is not possible at this time, again due to deficiencies




in data and knowledge of important processes.  Of particular




importance are gaps in knowledge about the bioaccumulation of




substances in the terrestrial food chain and the resulting lack of




an acceptable method for reflecting bioaccumulation of waste site




contaminants in terrestrial plants and animals.
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6.0  REFERENCES AND BIBLIOGRAPHY

Adriano, D. C., 1986.  Trace Elements In the Terrestrial Environment,
Springer-Verlag, New York, NY.

Arthur D. Little, Inc., 1983.  PERCO;  A Model for Prioritization of
Environmental Risks and Control Options at Hazardous Waste Sites,
Arthur D. Little, Inc. Cambridge, MA.

Astrand, I., 1975.  "Uptake of Solvents in the Blood and Tissues of
Man," Scandinavian Journal of Environmental Health, Vol.  1,
pp. 199-218.

Barnthouse, L. W. et al., 1986.  Development and Demonstration of
Hazard Assessment Rating Methodology for Phase II of the Installation
Restoration Program, (ORNL/TM-9857), Oak Ridge National Laboratory,
Oak Ridge, TN.

Baughman, G. L. and R. R. Lassiter, "Prediction of Environmental
Pollutant Concentration," Estimating the Hazard of Chemical
Substances to Aquatic Life, ASTM STP 657, J. Cains, Jr.,
D. L. Dickson, and A. W. Maki (eds.), American Society for Testing
and Materials, pp. 35-54.

Benson, W. W., B. Pharaoh, and P. Miller, 1974.  "Lead Poisoning in
a Bird of Prey," Bulletin of Environmental Contamination and
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Bergheim, A. and H. Hustveil, 1984.  "Estimated Pollution Loadings
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Bidleman, T. F. and C. E. Olney, 1974.  "Chlorinated Hydrocarbons in
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Boethling, R. S., 1984.  "Biodegradation Testing of Insoluble
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Bollag, J. M. and M. J. Loll, 1983.  "Incorporation of Xenobiotics
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Breck, J. E. and C. F. Baes III, 1985.  Report on the Workshop on
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Brown, J., (eds.), 1985.  Compound Evaluation and Analytical
Capability Annual Residue Plan, U.S. Department of Agriculture, Food
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Brown, M. P., M. B. Werner, R. J. Sloan, and K. W. Simpson, 1985.
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Buck, N. A., B. J. Estsesen, and G. W. Ware, 1983.  "DDT Moratorium
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Bureau of National Affairs, 1985.  "Evidence of Slow Dioxin Soil
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Calabrese, A., F. P. Thurberg, and E. Gould, 1977.  "Effects of
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Carey, A. E. and J. A. Gowen, 1986.  "PCBs in Agricultural and Urban
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Carey, A. E. et al., 1973.  "Pesticides in Soil:  Organochlorine
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Carline, R. F., 1975.  Influence of Recruitment Rates on Production
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Carter, A., 1983.  "Cadmium, Copper, and Zinc in Soil Animals and
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Chaney, R. L., 1983.  "Food Chain Pathways for Toxic Metals and
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Chen, D. F., P. G. Meier, and M. S. Hilbert, 1984.  "Organochlorine
Pesticide Residues in Paddy Fish in Malaysia and Associated Health
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Clayson, D. B., Krewski, D., and I. Munro (eds.), 1985.
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Clayson, D. B., D. Krewski, and I. Munro (eds.), 1985.
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Clement Associates Inc., 1977.  Initial Report of the TSCA
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Cleveland, M. E., 1983.  Biotic and Abiotic Factors Affecting
Sorption of Toxic Compounds to Natural Sediments,  M. S. Thesis,
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Cohen, Y. and P. A. Ryan, 1985.  "Multimedia Modeling of
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Cone, M. V., R. A. Faust, and M. F. Baldauf, 1984.  Chemicals
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Cone, M. V. et al., 1986.  National Body-Burden Database Chemicals
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Congressional Research Service, 1980.  Resource Losses  from Surface
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Congressional Research Service, 1980.  Six  Case Studies of
Compensation for Toxic Substances Pollution;  Alabama,  California,
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Connolly, J. P., M. E. Cleveland, and P. H. Pritchard,  1983.
Validity of Partition Coefficient as the Absorption Descriptor in
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Copeland, B. J., 1965.  "Fauna of the Arkansas Pass Inlet,  TX;
Emigration as Shown by Tide Trap Collections," Institute of Marine
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Corsi, R. L. and P. D. Allen, 1986.  "Post  Application  Pesticide
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Cossa, D., M. Picardberube, and J. P. Gouygou, 1983.  "Polynuclear
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Council for Agricultural Science and Technology,  1981.   Effects of
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Daly- 0. G., 1984.  "Water Pollution from Agriculture,"  Farm Food
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Dawson, S. V., H. Cabrera, and N. Y. Kado,  1983.  "Toxic Substances
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den Tonkelaar, E. M. et al., 1978.  "Hexachlorobenzene Toxlcity in
Pigs," Toxicology and Applied Pharmacology, Vol. 43, pp. 137-145.

DeSesso, J., 1982.  Technical Report to EPA, Evaluation of Human and
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Dixon, E. and G. A. Holton, 1984.  "Foodchain:  A Monte Carlo Model
to Estimate Individual Exposure to Airborne Pollutants Via the
Foodchain Pathway," Computer Application in Health Physics,
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Domsch, K. H., 1984.  "Effects of Pesticides and Heavy Metals on
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Dreesen, D. D. et al., 1982.  "Mobility and Bioavailability of
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Duke, T. W., J. T. Lowe, and A. T. Wilson, 1970.  "A Polychlorinated
Biphenyl in Water, Sediment, and Biota of Escambia Bay, FL,"
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Duncan, K. L. et al., 1980.  "Pollutant Flow in a Marine Web in the
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Edwards, N. T., 1983.  "Polycyclic Aromatic Hydrocarbons (PAHs) in
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Eisenreich, S. J., B. B. Looney, and J. D. Thornton, 1981.
"Airborne Organic Contaminants in Great Lakes Ecosystem,"
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Farm Chemicals Handbook, 1981.  Farm Chemicals, Meister Publishing
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Fiksel, J. and M. Segal, 1980.  An Approach to Prioritization of
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Filov, V. A. et al., 1979.  Quantitative Toxicology, John Wiley and
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Forstner, U. and G. T. W. Wittmann, 1983.  Metal Pollution in the
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Fox Consultants, Inc., 1984.  Whitewood Creek Study-Phase II;
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Fraser, J. L. and K. R. Lum, 1983.  "Availability of Elements of
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Frederick, K. D. et al., 1984.  Project Summary;  Trends in United
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Galloway, W. B., J. L. Lake, and Phelps, 1983.  "The Mussel Watch:
Intercomparisons of Trace Level Constituents," Environmental
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Garten, C. T., Jr. and J. R. Trabalka, 1983.  "Evaluation of Models
for Predicting Terrestrial Food Chain Behavior of Xenobiotics,"
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Garten, C. T., Jr., R. H. Gardner, and R. C. Dahlman, 1978.  "A
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Gerike, P. and W. K. Fischer, 1981.   "A Correlation Study of
Biodegradabllity Determinations with  Various Chemicals in Various
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Gerike, P. and W. K. Fischer, 1979.   "A Correlation Study of
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Geyer, H., G. Politzki, and D. Freitag, 1984.  "Prediction of
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Ghisalba, 0., 1983.  "Chemical Wastes and Their Biodegradation,"
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Gillett, J. W., 1983.  "A Comprehensive Prebiological Screen for
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Giordano, P. M. et al., 1983.  "Mobility in Soil and Plant
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Grimmer, G., W. Stober, and J. Jacob, 1983.  "Inventory and
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Gunnarsson, 0., 1983.  "Heavy Metals  in Fertilizers:  Do They Cause
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Hanson, W. C., 1975.  "Ecological Considerations of the Behavior  of
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Hardy, J. T., R. L. Schmidt, and C. W. Apts, 1981.  "Marine Sediment
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Hushon, J. M. et al., 1983.  Use of OECD Premarket Data in
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Hushon, J. M. and M. R. Kornreich, 1984.  "Scoring Systems for
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Jelinek, C. F. and P. E. Corneliussen, 1976.  "Levels of PCBs in the
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Koch, R.,  1984.   "A Theoretical-Methodological  Approach Towards
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McEwen, F. L. and G. R. Stephenson, 1979.  The Use and Significance
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                                106

-------
Oliver, B. G. and K. D. Nicol, 1982.  "Chlorobenzenes in Sediment,
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                                  107

-------
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                                 108

-------
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                                 109

-------
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                                 110

-------
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                                                                   *
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                                 Ill

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                                114

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                             APPENDIX A




               CLASSIFICATION OF HAZARDOUS SUBSTANCES






     Appendix A contains an alphabetical listing of approximately




300 hazardous substances found on NPL sites together with the




bioaccumulation values that would be assigned to them using the




methods discussed in Section 2.2.2.
                                 115

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              APPENDIX A

CLASSIFICATION OF HAZARDOUS SUBSTANCES
     FOR  POTENTIAL BIOACCUMULATION
    Name of Substance
                      Reason for Rating
Value
1,1 Dichloroethylene (vinylidene
chloride)

1,1,2,2 Tetrachloroethane

1,1,2,2 Tetrachloroethene

1,2 Dichloroethylene (trans; cis)

1,2 Dichloropropane

1,2 Diethylthydrazine

1,2,3-Trichloropropane

1,2,4 Trichlorobenzene

1,2,4,5 Tetrachlorobenzene

1,2,7,8-Dibenzopyrene

1,2-Dibromo-3-chloropropane
(Dibromochloropropane) (DBCP)

1,2-Diphenylhydrasine

1,2-Trans-dichloroethylene

1,3 Dichloropropene

1,3 Dinitrobeneze

1,3,5-Trinitrobenzene

1,3-Butadiene
                     BCF  6  in fish


                     BCF  42 fish

                     BCF  10-100  tissue

                     BCF  2  in fish

                     Log  Pow 2.00

                     Not  reported  in biota

                     Not  reported  in biota

                     BCF  2,800 fish

                     BCF  up to 4,500

                     Solubility  .11

                     Log  Pow 2.29


                     BCF  25 in fish

                     Log  Pow 1.54

                     BCF  2  in fish

                     Log  Pow 1.62

                     Not  reported  in biota

                     Log  Pow 1.99
  3

  3

  2

  3

  1

  1

  5

  5

  6

  3


  3

  2

  2

  2

  1

  2
                 116

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                       APPENDIX A (Continued)
    Name of Substance
 Reason for Rating
Value
1,3-Dichlorobenzidine




1,4 Dioxane




1-Butanol




1-Napthol




1-Napthylamine




2,3 Dinitrotoluene




2,4 Dinitrophenol




2,4, D




2,4, DimethyIphenol




2,4,5 T




2,4-Diaminotoluene




2,4-Dichlorophenol




2,4-Dinitrotoluene (DNT)




2,6-Dinitrotoluene (DNT)




2-Ac etylaminofluorene




2-Chlorophenol




2-Napthylamine




3,3 Dichlorobenzene




4,6 Dinitro-o-cresol




4-Aminobiphenyl
BCF 312 in fish




Log Pow -0.27-0.42




Log Pow 0.32-0.89




Log Pow 2.84




Log Pow 2.07




BCF 4 in fish




Log Pow 1.53




BCF 20 in fish




BCF 150 in fish




BCF 25-43 in fish




Not reported in biota




BCF 41 in fish




Not reported in biota




Not reported in biota




Log Pow 3.7




BCF 214 in fish




Log Pow 2.07




BCF 312 in fish




Log Pow 2.70




Log Pow 2.78
  4




  1




  1




  3




  3




  2




  2




  3




  4




  3




  1




  3




  1




  1




  4




  4




  3




  4




  3




  3
                                 117

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                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
4-Methyl-2,6 di-tert-butyl
phenol (BHT)

4-Nitrophenol

7,12 Dimethylbenz(a) anthracene

Abietic acid

Acenaphthene

Acenapthylene

Acetaldehyde

Acetate

Acetic acid

Acetone

Acetophenone

Acrolein

Acrylonitrile

Adipic acid

Alcohol

Aldrin

Alkyl benzenes

Allyl alcohol

Aluminum and compounds
Solubility 0.4                6


BCF 57                        3

Solubility 5.6                6

Not reported in biota         1

BCF 242 in fish               4

BCF 387 in fish               4

Not reported in biota         1

Not reported in biota         1

No data found                 1

Log Pow -0.24                 1

Not reported in biota         1

BCF 344 in fish               4

BCF 48 in fish                3

Log Pow 0.08                  1

No data found                 1

BCF 4,600-6,300               5

Not reported in biota         1

Log Pow 0.17                  1

BCF up to 10,000, bio-        6
magnifies in marine ecoystem
                                 118

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                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Amitrole

Ammonium picrate

Aniline

Anthracene (Paranaphthalene)

Antimony

Arochlor (polychlorinated
biphenyls, PCB)

Arsenic and compounds

Arsenic trisulfide

Asbestos

Atrazine

Aziridine

BHT  (4 methyl-2,6 di-tert-butyl
phenol)

Barium

Benz  (c) acridine

Benz(a) anthracene

Benzene

Benzene carbonyl chloride

Benzidine

Benzo (DEF) phenanthrene (Pyrene)
Not reported in biota

Not reported in biota

BCF 6 in fish

BCF 917 in fish

BCF 1 (EPA)

Solubility 0.057,
biomagnifies

BCF 350 oyster (EPA)

Not reported in biota

Found only in Lung

BCF 2-8

Not reported in biota

Solubility .4


BCF 4

Log Pow 4.56

Log Pow 5.60

BCF 10 in fish

Not reported in biota

BCF 87.5 in fish

BCF up to 10,000
  1

  1

  2

  4

  2

  6


  4

  1

  1

  2

  1

  6


  2

  5

  6

  3

  1

  3

  6
                                 119

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                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Benzo (J,K) fluorene
(Fluoranthene)

Benzo(b) fluoranthene

Benzo(ghi) perylene

Benzo-a-pyrene (BAP)


Benz ophenanthrene

Benzothiophene

Benzyl chloride

Beryllium

Biphenyl

Bis (2-chloroethoxy) methane

Bis (2-chloroethyl) ether

Bis(2-chloroisopropyl) ether

Bis(2-ethylhexyl)phthalate

Bis(chloromethyl) ether

Borax

Boron

Bromine

Bromobenzene

Bromochlorobenzene

Bromochloromethane
BCF up to 10,000


Solubility .004

Solubility .0007

BCF 930, Biomagnifies
in aquatic ecosystem

Not reported in biota

Not reported in biota

Log Pow 2.63

BCF 19

BCF 340-437

Not reported in biota

BCF 11 in fish

Log Pow 2.10

Log Pow 5.11

Not reported in biota

Not reported in biota

BCF 0.22 in fish

BCF 420 in fish

Log Pow 2.99

Not reported in biota

Not reported in biota
  6

  6

  5


  1

  1

  3

  3

  4

  1

  3

  3

  5

  1

  1

  1

  4

  3

  1

  1
                                 120

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                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Bromodichloroethylene

Bromodichloromethane

Bromoform (tribromomethane)

Bromomethane

Bromoxylene

Butadiene

Butane

Butyl cellosolve

Butylbenzyl phthalate

Cacodylic acid

Cadmium and compounds

Calcium chromate

Captan

Carbofuran

Carbon

Carbon disulfide

Carbon tetrachloride
(tetrachloromethane)

Cerium

Chlordane

Chloride
Not reported in biota         1

Not reported in biota         1

Log Pow 2.39                  3

Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

BCF 279-772 in fish           4

Not reported in biota         1

BCF 81, Biomagnifies          4

Not reported in biota         1

BCF 300                       4

Log Pow 4.02                  4

BCF 1,800-4,600 in fish       5

Log Pow 2.00                  3

BCF 30                        3


BCF 1-10 in fish              2

BCF 14,000                    6

No data found                 1
                                 121

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                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Chlorobenzene

Chlorobenzilate

Chlorodibromomethane

Chlorodifluoromethane

Chloroform

Chloromethane

Chloromethyl methyl ether

Chromium and compounds

Chrysene

Cis-1,2 dichloroethene

Cobalt

Copper and compounds


Creosote (Coal tar)

Cresol

Cumene

Cyclohexane

Cyclophosphanide

DDD (IDE)

DDE p,p' DDE
BCF 650 in fish               4

Log Pow 4.51                  5

Log Pow 2.09                  3

Not reported in biota         1

BCF 6 in fish                 2

Log Pow 0.91                  2

Not reported in biota         1

BCF 134-320 in bivalves       4

Log Pow 5.61                  6

Log Pow 1.54                  2

Insoluble                     6

BCF in shellfish              5
9,960

Log Pow 3.98                  4

Log Pow 1.97                  2

No data found                 1

Log Pow 3.44                  4

No data found                 1

BCF 80,000, Biomagnifies      6

BCF 51,000, Biomagnifies      6
                                 122

-------
                       APPENDIX A (Continued)
    Name of Substance
 Reason for Rating
Value
DDT p,p' DDT

Di-n-butylphthalate

Di-n-octyl phthalate

Diallate

Dibenzo(a,h) anthracene

Dibromochloromethane

Dibutyl phthalate

Dichlorobenzene

Dichlorobiphenyl

Di chlorodi fluo romethane

Dichloroethane
1,2 or 1,1

Dichloroethylene

Dichloromethane

Dicyclopentadiene

Dieldrin

Diethyl arsine

Diethyl phthalate

Diethylnitrosamine

Diethylstilbestrol (DBS)

Dihydrosafrole
BCF 54,000, Biomagnifies      6

BCF 14 in fish                3

BCF up to 9,400               5

Not reported in biota         1

Solubility .0005              6

Not reported in biota         1

Log Pow 5.60                  6

BCF 60-89 in fish             3

Log Pow 4.65-6.00             6

Not reported in biota         1

BCF 2 in fish                 2


Not reported in biota         1

BCF 5 in fish                 2

Not reported in biota         1

BCF 1,557-4,760 in fish       5

Log Pow 2.97                  3

BCF 117 in fish               4

Not reported in biota         1

Log Pow 5.46                  5

Log Pow 2.56                  3
                                 123

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Dimethyl formamide

Dimethyl phthalate

Dimethyl sulfate

Dimethylaminobenzene

Dimethylaniline

Dimethylcarbamoyl chloride

DimethyIhydrazine

DimethyInitrosamine

Dinitrotoluene (DNT)

Dioxin (2,3,7,8-Tetrachlorodibenzo
p-dioxin)

Dipropylnitrosanine

Disulfoton

Endosulfon

Endrin

Epichlorohydrin

Ethanol

Ethion and oxygen analog

Ethyl methanesulfonate

Ethyl acetate

Ethyl chloride
Log Pow -1.01

BCF 57 in fish

Not reported in biota

Log Pow 3.72

Not reported in biota

Not reported in biota

Not reported in biota

Not reported in biota

Not reported in biota

BCF up to 10,000


Log Pow 1.50

Log Pow 2.90

Log Pow 3.55

BCF 1324

Not reported in biota

Log Pow -0.30

Log Pow 4.72

Not reported in biota

Log Pow 0.66-0.73

Log Pow 1.54
  1

  3

  1

  4

  1

  1

  1

  1

  1

  6


  2

  3

  4

  5

  1

  1

  5

  1

  1

  2
                                 124

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Ethyl dibromide

Ethyl ether

Ethylbenzene

Ethylene oxide

Ethylene glycol

Ethylenethiourea

Fluoranthene

Fluorene

Formaldehyde

Furfural

HCB (Hexachlorobenzene)
(Perchlorobenzene)

Heptachlor

Heptachlor epoxide

Hexachlorobenz ene
(Perchlorobenzene)(HCB)

Hexachlorobutadiene

Hexachlorocyclohexane (except
lindane)

Hexachlorocyclopentadiene

Hexachloroethane

Hexachlorophene
Log Pow 1.76                  2

Log Pow 0.83                  2

BCF 95                        3

Not reported in biota         1

Log Pow -1.93                 1

Not reported in biota         1

BCF 1,150                     5

BCF 1,300                     5

Log Pow 0.35                  1

Log 0.23-0.80                 1

BCF 8,690, Biomagnifies       6


BCF up to 15,700              6

BCF up to 14,400              6

BCF 8,690, Biomagnifies       6


BCF 3 in fish                 2

BCF 352 in fish               4


BCF 11 (EPA)                  3

BCF 87 in fish                3

Solubility .004               6
                                 125

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Hexane

Hydrazine

Hypochlorlc acid

Indeno (1,2,3-cd) pyrene

Indomethane

Iron and Iron compounds

Isopropopanol (isopropyl alcohol)

Isosafrole

Kepone



Lasiocarpine

Lead and compounds


Lindane

Malathion (Carbethoxy malathion)

Manganese

Mercury and compounds

Methane

Methoxychlor

Methyl acetate

Methyl parathion

Methyl chloride
Log Pow 3.94                  4

Log Pow -2.07                 1

Log Pow -0.25                 1

Solubility .00053             6

Log Pow 1.69                  2

BCF in fish 1,000-5,000       5

Log 0.05                      1

Log Pow 2.66                  3

Solubility .0099,             6
Biomagnifies in aquatic
ecosystem

Not reported in biota         1

BCF 49, Biomagnification      4
potential

BCF 352 (EPA)                 4

Log Pow 2.89                  3

BCF 400-550 in fish           4

BCF 3750, Biomagnifies        6

Not reported in biota         1

BCF up to 8,300               5

Log Pow 0.18                  1

BCF 45 in fish                3

No data found                 1
                                 126

-------
                       APPENDIX A (Continued)
    Name of Substance
 Reason for Rating
Value
Methyl ethyl ketone

Methyl isobutyl ketone

Methyl mercury

Methyl methacrylate

Methylcyclohexane

Methylene chloride
(dichloromethane)

Methylnaphthalene

Methylnitrosourea

Methylvinylnitrosamine

Mirex


Molybdenum and compounds

Mustard Gas

N-Nitro sodiphenylamine

N-Nitrosopiperidine

N-Nitrosopyrrolidine

N-butyl acetate

N-pentane

Naphtha

Naphthalene
Log Pow 0.29-0.50             1

Not reported in biota         1

Solubility  25, Biomagnifies  6

Not reported in biota         1

Not reported in biota         1

Log Pow 1.25                  2


Log Pow 4.22                  4

Not reported in biota         1

Not reported in biota         1

Solubility  25, Biomagnifies  6
in aquatic ecosystem
BCF 20-100 marine

Log Pow 1.37

BCF 217 in fish
  3

  2

  4
Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

Not reported in biota         1

Log Pow 3.01, Biomagnifies    4
in aquatic ecosystem
                                 127

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Nickel

Nitroaniline

Nitrocellulose

Octane

Olefinic hydrocarbons

0-tolidine

P-chloro-M-cresol

PCBs (Polychlorinated biphenyls)


PCP (Pentachlorophenol)

Paranaphthalene (Anthracene)

Parathion

Pentachlorobenzene

Pentachlorobutadiene

Pentachloroethane

Pentachloronitrobenzene

Pentachlorophenol (PCP)

Perchlorobenzene (Hexachlorobenzene)
(HCB)

Phenanthrene

Phenobarbitol

Phenol
BCF 380 in shellfish          4

Log Pow 1.39                  2

No data found                 1

Log Pow 5.02                  5

No data found                 1

Log Pow 2.88                  3

Not reported in biota         1

Solubility 0.57,              6
Biomagnifies

BCF up to 1,050 in fish       5

BCF 917 in fish               4

Log Pow 3.81                  4

BCF in fish 3,400             5

Log Pow 2.58                  3

BCF 67 in fish                3

Log Pow 5.45                  5

BCF up to 1,050 in fish       5

BCF 8,690, Biomagnifies       6


BCF up to 10,000              6

Not reported in biota         1

Log Pow 1.47                  2
                                 128

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Phorate

Phosgene (carbonyl chloride)

Phosphate

Phosphoric acid

Phthalic anhydride

Plutonium and compounds

Polychlorinated biphenyls(PCBs)


Propenylbenzene

Pr opylenimine

Pyrene  (Benzo DBF phenanthrene)

RDX  (Cyclonite)

Radon

Resorcinol

Safrole

Selenium and compounds


Silver  and compounds

Silvex  (2,4,5 TP)

Sodium

Sodium  cyanide

Sodium  hydroxide
Log Pow 2.59                  3

No data found                 1

BCF up to 100,000             6

Log Pow -1.86                 1

Log Pow -0.62                 1

Insoluble                     6

Solubility .057,              6
Biomagnifies

No data found                 1

Not reported in biota         1

BCF up to 10,000              6

Not reported in biota         1

Found only in lung tissue     1

Log Pow 0.80                  1

Log Pow 2.53                  3

BCF 16, Biomagnifies in       4
aquatic ecosystem

BCF 3,080 in fish             5

Log Pow 1.39                  2

No data found                 1

No data found                 1

No data found                 1
                                 129

-------
                       APPENDIX A  (Continued)
    Name of Substance
 Reason for Rating
Value
Strontium and compounds

Styrene

TCDD (dioxin)

Tetrachloroethane

Tetrachloroethylene

Tetrachloromethane
(Carbon tetrachloride)

Tetrachlorophenol

Tetrahydrofuran

Thallium

Thioacetamide

Thiourea

Tin and compounds

Titanium and compounds


Toluene

Toxaphene


Tribromomethane (Bromoform)

Tributyltin (TBTO)

Trichloroethane

Trichloroethylene (TCE)
BCF 1,000 in bone tissue      5

Log Pow 2.95                  3

BCF up to 10,000              6

BCF 42 in fish                3

BCF 31 in fish                3

BCF 30                        3


BCF 240 in fish               4

Log Pow 0.46                  1

BCF up to 100,000             6

Not reported in biota         1

No data found                 1

BCF in fish 1,000             5

BCF 40-1,000 marine           3
ecosystem

BCF 13.2 in eels              3

BCF 13,100, Biomagnifies in   6
aquatic ecosystem

Log Pow 2.39                  3

BCF 1,500-6,000               5

BCF 9 in fish                 2

Log Pow 2.42-3.3              3
                                 130

-------
                       APPENDIX A  (Concluded)
    Name of Substance
 Reason for Rating
Value
Trichlorofluoromethane (freon-ll)

Trichlorophenol

Trlmethylbenzene

Trinitrotoluene (TNT)

Tris

Uracil Mustard

Uranium and compounds

Vanadium and compounds

Vinyl chloride

Vinylidene chloride
(1,1 dichloroethene)

Xylene

Zinc and compounds


Zirconium
Log Pow 2.53                  3

BCF 110-150 in fish           4

Log Pow 4.04                  4

Log Pow 2.01                  3

BCF 2.7                       3

Not reported in biota         1

BCF 10 in fish                3

BCF 20-100 marine             3

BCF 1.2 in fish               2

BCF 6 fish                    2


BCF 21-24 aquatic ecosystem   3

BCF 47, Biomagnification      4
potential

BCF up to 200                 4
                                 131

-------
                             APPENDIX  B




                AVERAGE  FISH STANDING  CROPS REPORTED






Introduction




     Appendix B contains a listing of surface water bodies in the




United States and the average standing crops estimated in the




literature for the water bodies.  Data are presented in pounds per




acre for different classifications of water body and geographic




region.
                                 133

-------
             APPENDIX B




AVERAGE FISH STANDING CROPS REPORTED
Habitat
River/Stream
(Cold)
WI Rivers
PA trout stream
CA trout stream
WI Rivers
WY tailwaters
Mountain stream
Trout streams
Mt. trout streams
MI streams
WI streams
OH streams
MO streams
MD streams
(Midwestern)
Chariton River, MO
Chariton River, MO
Chariton River, MO
OH streams
MO streams
Midwestern
smallmouth stream
Midwestern
largemouth stream
IN streams
IN streams
IL streams
OK streams
(Warm)
Warmwater Streams
Warmwater Streams
Warmwater Streams
Warmwater Streams
River backwaters
and oxbows
Tropical rivers
Pounds
per Acre


14
24
41
26
46
51
55
40-226
195
33
11
8
16

53
304
152
56
72

114

168
158
124
164
174

9-43
72
56-90
120

500
979-1600
Source


Paragamian, 1975
Hoopes, 1975
Card, 1972
Paragamian, 1976
Wiley & Dufek 1980
Dumas, 1976
Carlander, 1955
Elser, 1968
Clepper, 1975
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a

Congdon, 1973
Congdon, 1973
Congdon, 1973
Clepper, 1975
Clepper, 1975

Clepper, 1975

Clepper, 1975
Clepper, 1975
Clepper, 1975
Clepper, 1975
Clepper, 1975

Carlander, 1955
Fajin, 1975
Fajin, 1975
Johnson, 1965

Carlander, 1955
Lambou, 1959
Comments


bass only
trout only
trout only
pike only
trout only
not US
average
average
bass streams
smallmouth bass
smallmouth bass
smallmouth bass
smallmouth bass

channelized
unchannelized
carp only
average
average

average

average
average
largemouth
average
average

average
Courtois Creek
Ozarks ave.
Northern streams

average
lagoons
                134

-------
                            APPENDIX B  (Continued)
                      Pounds                                     ~~~
   Habitat	per Acre	Source	Comments	

River/Stream (Concluded)

  (Other)

Upper Mississippi      7-8      Rasmussen, 1979       all species (1962-1973)
Lower Mississippi               U.S. Army Corps of    all species
  borrow pit          51-3199   Engineers
Lower Mississippi      530      U.S. Army Corps of    Mosey Lake (mostly shad)
  (delta region)                Engineers, 1984
Lower Mississippi     51-299    U.S. Army Corps of    Wolf Lake (mostly shad)
  (delta region)                Engineers, 1984

  (River Basin)

Atchafalaya R.B., LA   767      Lambou, 1985          lower basin stations
Atchafalaya R.B., LA   495      Lambou, 1985          upper basin stations
                                      135

-------
                            APPENDIX B  (Continued)
Habitat
Pounds
per Acre Source
Comments
Lakes
Backwater lakes        397
NY lake                47
Northern lake          51
Cold trout lakes       50
Lakes & ponds          58
FL bass lake           97
10 lake                123

MI lakes               46

MI lakes               88
MI lakes               104

Lake Tohopekaliga,
  FL                 59-127

Warmwater lakes     125-150
MS oxbow lakes         202
Natural lakes        50-150
KY lakes             49-200
WI lakes               210

Lake Wingra, WI        440
AR lakes             89-445
Alpine lakes         .6-7
Tropical lakes       45-178
Atchafalaya Basin      270
Atchafalaya Basin      624
Floodplain lakes       440
6 oxbow lakes, LA    156-267

7 backwater lakes      397

Wallum Lake, RI        14-17
Floa Lake, WI            3
IL Lakes               18-36
Third Sister Lake,MI   86
Lambou, 1985
Green & Smith, 1976
Carlander, 1969
Carlander, 1955
Carlander  1977b
Smith, 1975
Albertson & Schultz,
  1968
Schneider, 1973

Schneider, 1973
Schneider, 1973
Wegener, 1975

Carlander, 1955
Lambou, 1959
Cooper, 1966
Pfeiffer, 1967
Kempinger &
  Christenson, 1978
Churchill, 1976
Baily, 1978
Lambou, 1985
Lambou, 1985
Lambou, 1985
Lambou, 1985
Lambou, 1985
U.S. Army Corps of
Engineers, 1984
U.S. Army Corps of
Engineers, 1984
Guthrie, 1977
Carlander, 1977a
Carlander, 1977a
U.S. Army Corps of
Engineers, 1984
largemouth bass
perch & bass
suckers
average
mixed species
all fish

bullheads
slow growing
  perch
avg. diversity
unusual
  populations

before and after
  drawdown
average
average
average
average

64% are minnows
large fish
ave. range
average
average
crawfish
finfish
no overflow
mostly channel cat &
centrarchids
average

combined fish species
pumpkinseed & bluegill

rotenone catch
                                      136

-------
                            APPENDIX B (Continued)
   Habitat
 Pounds
per Acre
Source
Comments
Lakes (Concluded)

Third Sister Lake,
  MI                    13
5 Lakes, FL (l-10ha)     7

Backwater lakes, LA     24
Lower Lock Alpine       30
Wintergreen Lake, MI    48
Cuba lakes, Cove
  Sampling              83
5 Lakes, FL            22-110
           Carlander,  1977a
           Carlander,  1977a

           Carlander,  1977a
           Carlander,  I977a
           Carlander,  1977a

           Carlander,  1977a
           U.S.  Army Corps of
           Engineers,  1984
                  bass (avg.)
                  bass (avg.)
                  only legal size
                  bass  250mm
                  bass
                  bass

                  bass (avg.)
                  Ocala National Forest
                                      137

-------
                            APPENDIX B (Continued)
                      Pounds
                     per Acre
Habitat
Source
     Comments
Reservoirs

West VA reservoir      9
IL, artificially
  heated              8-18

170 reservoirs         23
GA reservoir           48
CO reservoir           82
LA reservoirs          73
127 reservoirs      180-186
Reservoirs and
  ponds             200-300
Impoundments        200-400
Midwest
  reservoirs           400
Barkley Lake, KY       771
Power plant cooling
  lake in Texas     1000-2000
Bobwhite Lake, IA        7
Red Hawk Lake, IA       24
3 reservoirs , OK        8
Carl Blackwell
  Lake, OK               1
Buds Lake, IA            3
Lanier Lake, GA          8
34 reservoirs TX & MA   19
IA reservoirs
                       112

Fast Osceola, IA        29
Bastrop Lake, TX        33
Ridgelake, IL           49

North American Lakes
  & reservoirs          15

Clear Lake               1
Clear Lake              15
68 Gamefish Lakes,MN     7
44 Roughfish Lakes, MN   6
FL, WI 30 lakes          7
                             Woodrum, 1978

                             Tranguilli et al.,
                               1981
                             Jenkins, 1975
                             Sandow, 1970
                             Carlander, 1969
                             Lambou, 1959
                             Jenkins, 1975

                             Carlander, 1955
                             Cooper, 1966

                             Carlander, 1955
                             Aggus et al., 1979

                             Noble et al., 1975
                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander, 1977a

                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander, 1977a

                             Carlander, 1977a

                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander, 1977a
                             Carlander,
                             Carlander,
                             Carlander,
                             Carlander,
                             Carlander,
       1977a
       1977a
       1977a
       1977a
       1977a
                  largemouth bass
                  bass and carp
                  all bass
                  all species
                  average
                  average
                  ave., all species

                  average
                  average

                  average
                  small bay

                  bass & tilapia
                  largemouth bass
                  largemouth bass
                  largemouth bass (avg.)

                  largemouth bass
                  largemouth bass
                  largemouth bass (avg.)
                  largemouth bass (avg.)

                  largemouth bass (avg.)
                  average
                  largemouth bass
                  largemouth bass
                  largemouth bass (avg.)
bass (avg.)

bass
bass (avg.)
bass (avg.)
bass (avg.)
bass (mean)
                                      138

-------
                            APPENDIX B  (Continued)
   Habitat
 Pounds
per Acre
Source
Comments
Reservoirs (Concluded)

Brown's Lake, WI        24
Cacapon Lake, WV         9
14 Lakes, MI 0.3-
  8.7 ha)                7
Deep Creek
  reservoir, MD        100

Cherokee Reservoir,    1,550
  TX
           Carlander, 1977a
           Carlander, 1977a

           Carlander, I977a

           U.S. Army Corps of
           Engineers, 1984
           U.S. Army Corps of
           Engineers, 1984
                  bass (avg.)
                  bass (avg.)

                  bass (avg.)

                  mixed species

                  mixed species
                                      139

-------
APPENDIX B (Continued)
Habitat
Ponds
Cold ponds
Carp ponds
Bullhead ponds
Small desert pond
Kansas pond
Ml ponds

Southern ponds
AL ponds

Stocked AL pond
Ashville pond, RI
Pounds
per Acre

69
356
178
133
168
289

230-330
498

527
48
Meshanticut pond, RI 500


MA ponds (23)
OK ponds
IL ponds
NY ponds
IA ponds (balanced)

IA ponds

IA ponds
IA ponds

MI ponds
IL ponds
Ridge Lake, IL
Ridge Lake, IL
Breon's pond, PA

Rearing ponds U.S.
MI ponds
NY ponds
AL pond
MO ponds
Lake Toho Pekaligo,
Lake Toho Pekaligo,
WV pond
AL ponds


86
91
88
118
13

14

23
2

21
125
357
48
15,771

18,787
147
72
255
72
FL 43
FL 46
88
2,360
Source

Carlander, 1969
Carlander, 1969
Carlander, 1969
Mannes & Jester, 1980
Carlander, 1969
Beyerle & Williams,
1972
Carlander, 1955
Forester & Lawrence,
1978
Habel, 1975
Guthrie, 1977a
Guthrie, 1977a


Guthrie, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a

Carlander, 1977a

Carlander, 1977a
Carlander, 1977a

Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a

Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Carlander, I977a
Carlander, 1977a
Carlander, 1977a
Carlander, 1977a
Comments

Grebe Lake
unfertilized
unfertilized
eutrophic
channel catfish

bluegills
average

bass & bluegill
tilapia
combined fish sp.
combined fish sp.
few catchable bass/
pickerel
average
sunfishes
smallmouth bass
smallmouth bass
largemouth bass
(average)
largemouth bass (avg.)
overpopulated w/bluegill)
largemouth bass (avg.)
largemouth bass
(overpopulated w/bass)
largemouth bass
only "large" bass (avg.)
largemouth bass (avg.)
(over 254 mm)
largemouth bass
all sizes
largemouth bass
largemouth bass (avg.)
largemouth bass (avg.)
largemouth bass
no harvest
littoral zone
limnetic zone
largemouth bass
bass fed
         140

-------
                            APPENDIX B (Continued)
                      Pounds
   Habitat	per Acre	Source	Comments	

Fertilized Ponds

Carp & bullhead        1070     Carlander, 1969       southern
3 ponds, IL             447     Carlander, 1977a      largemouth bass  (avg.)
3 ponds, IL              69     Carlander, 1977a      largemouth bass  (avg.)
3 ponds, IL              60     Carlander, 1977a      only "large" bass (avg.)
                                      141

-------
                            APPENDIX B  (Continued)
   Habitat
 Pounds
per Acre
Source
Comments
Coastal

Newport River, NC        8

Mystic River, MA        18

Narragansett Bay, RI    28
Gulf of Mexico          54
Beach canals, LA      3-367
LA estuary             351
Chesapeake Bay         250
Chesapeake Bay         750
South Atlantic         286

Gulf Coast             432

Guadalupe Bay, TX       11
CA (3-mi zone)         293
OR (3-mi zone)         152
WA (3-mi zone)         444
AL Coastal              60
LA Coastal             314
MS Coastal            1011
FL Coastal              48
GA Coastal              35
NC Coastal             128
SC Coastal              26
TX Coastal            57-68*
MA Coastal            1267
NH Coastal             320
MA Coastal            1984
Rl Coastal            1209
CT Coastal              19
NY Coastal              90
NJ Coastal             155
DE Coastal              14
MD Coastal              84
VA Coastal             751

*Includes fish and shellfish.
           Turner & Johnson,
             1973
           Haedrick & Haedrick,
             1974
           Oviatt & Nixon, 1973
           Perry, 1983
           Perry, 1983
           Perry, 1976
           Stroud, 1978
           Stroud, 1978
           US Fish & Wildlife,
             1981
           US Fish & Wildlife,
             1981
           Adams, 1976
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
           NOAA/NMFS, 1985
                  littoral area
                    estuary

                  polluted estuary
                  demersal fish
                  ave.  Gulf
                  Gulf  canals
                  all estuary fish
                  nearshore saltwater
                  all finfish

                  fish & shellfish
                  fish  & shellfish
                  commercial catch
                  commercial catch
                  commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                  estuary commercial catch
                                      142

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                            APPENDIX B  (Concluded)
                      Pounds
   Habitat	per Acre	Source	Comments	

Coastal (Concluded)

Laguna Madre, TX     18-337     FWS, 1977             range-winter minimum/
                                                      summer maximum

Caminada estuary, LA   649      FWS, 1977
LacDes Allemands, LA    87      FWS, 1977             channel  catfish
Barataria-Caminada
  Bay, LA                9      FWS, 1977             shrimp only  (1967-1972)
                                      143

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Aggus, L. R. et al., 1979.  "Evaluation of Standing Crop of Fishes
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Albertson, R. D. and F. Schultz, 1968.  "Fishes of Little Wall
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Bailey, W. M, 1978.  "A Comparison of Fish Populations Before and
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Beyerle, G. B. and John E. Williams, 1972.  Survival, Growth and
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Carlander, K. D., 1977a.  Handbook of Freshwater Fishery Biology.
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Carlander, K. D., 1977b.  "Biomass, Production and Yields of Walleye
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Carlander, K. D., 1969.  Handbook of Freshwater Fishery Biology.
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Carlander, K. D., 1955.  "The Standing Crop of Fish in Lakes,"
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Carline, R. F., 1975.  Influence of Recruitment Rates on Production
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Churchill, W. S., 1976.  Population and Biomass Estimates of Fishes
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Clepper, H., ed., 1975.  Black Bass Biology and Management, Sport
Fishing Institute, Washington, DC.
                                 144

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Congdon, J. C., 1973.  Fish Populations of Channelized and
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Cooper, G. P., 1967.  Fish Production in Impoundments, (Michigan
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Fajen, 0., 1975.  "The Standing Crop of Smallmouth Bass and
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                                 145

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Haedrich, R. L. and S. 0. Haedrich, 1974.  "A Seasonal Survey of the
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                                 146

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Paragamian, V. L., 1976.  "Population Characteristics of Northern
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Paragamian, V. L., 1977.  Fish Population Development in Two Iowa
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                                 147

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                                 148

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                                 149

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