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: _±
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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
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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
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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
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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
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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
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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,
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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.
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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.
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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.
-------
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
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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
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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
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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.
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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.
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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).
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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
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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
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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
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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
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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.
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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
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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.
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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.
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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
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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
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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
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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
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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
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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
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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.
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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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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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
-------
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
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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
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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
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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
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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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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., 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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Clepper, H., ed., 1975. Black Bass Biology and Management, Sport
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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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Dumas, J., 1976. "Dynamics and Sedentariness of a Naturalized
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Fajen, 0., 1975. "The Standing Crop of Smallmouth Bass and
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Forester, T. S. and J. M. Lawrence, 1978. "Effects of Grass Carp
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Card, R., 1972. "Persistence of Headwater Check Dams in a Trout
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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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Wiley, R. W. and D. J. Dufek, 1980. "Standing Crop of Trout in
Fontenell Tailwater of Green River, WY," Transactions of the
American Fishery Society, Vol. 109, No. 2, pp. 168-173.
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149
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