EPA 560/5-85-008
September, 1986
METHODS FOR ASSESSING EXPOSURE
TO CHEMICAL SUBSTANCES
Volume 8
Methods for Assessing Environmental
Pathways of Food Contamination
by
Joanne Perwak, Joo Hooi Ong
and Richard Whelan
EPA Contract No. 68-02-3968
EPA Contract No. 68-01-6271
Project Officer
Elizabeth F. Bryan
Exposure Evaluation Division
Office of Toxic Substances
Washington, DC 20460
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF PESTICIDES AND TOXIC SUBSTANCES
WASHINGTON, DC 20460
U.S. Environmental Protection Agency
Region 5, library (PL-12J)
77 West Jackson Boulevard, 12th Floor
Chicago, IL 60604-3590
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DISCLAIMER
This document has been reviewed and approved for publication by
the Office of Toxic Substances, Office of Pesticides and Toxic
Substances, U.S. Environmental Protection Agency. The use of trade
names or commercial products does not constitute Agency endorsement or
recommendation for use.
iii
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FOREWARD
This document is one of a series of volumes, developed for the
U.S. Environmental Protection Agency (EPA), Office of Toxic Substances
(OTS), that provides methods and information useful for assessing
exposure to chemical substances. The methods described in these
volumes have been identified by EPA-OTS as having utility in exposure
assessments on existing and new chemicals in the OTS program. These
methods are not necessarily the only methods used by OTS, because the
state-of-the-art in exposure assessment is changing rapidly, as is the
availability of methods and tools. There is no single correct approach
to performing an exposure assessment, and the methods in these volumes
are accordingly discussed only as options to be considered, rather than
as rigid procedures.
Perhaps more important than the optional methods presented in
these volumes is the general information catalogued. These documents
contain a great deal of non-chemical-specific data which can be used
for many types of exposure assessments. This information is presented
along with the methods in individual volumes and appendices. As a set,
these volumes should be thought of as a catalog of information useful
in exposure assessment, and not as a "how-to" cookbook on the subject.
The definition, background, and discussion of planning exposure
assessments are discussed in the introductory volume of the series
(Volume 1). Each subsequent volume addresses only one general exposure
setting. Consult Volume 1 for guidance on the proper use and
interrelations of the various volumes and on the planning and
integration of an entire assessment.
The titles of the nine basic volumes are as follows:
Volume 1 Methods for Assessing Exposure to Chemical Substances
(EPA 560/5-85-001) (PB86-107083)
Volume 2 Methods for Assessing Exposure to Chemical Substances in the
Ambient Environment (EPA 560/5-85-002)(PB86-107067)
Volume 3 Methods for Assessing Exposure from Disposal of Chemical
Substances (EPA 560/5-85-003) (PB86-107059)
Volume 4 Methods for Enumerating and Characterizing Populations
Exposed to Chemical Substances (EPA 560/5-85-004)
(PB86-107042)
Volume 5 Methods for Assessing Exposure to Chemical Substances in
Drinking Water (EPA 560/5-85-005) (PB86-1232156)
Volume 6 Methods for Assessing Occupational Exposure to Chemical
Substances (EPA 560/5-85-006) (PB86-157211)
Volume 7 Methods for Assessing Consumer Exposure to Chemical
Substances (EPA 560/5-85-007)
v
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Volume 8 Methods for Assessing Environmental Pathways of Food
Contamination (EPA 560/5-85-008)
Volume 9 Methods for Assessing Exposure to Chemical Substances
Resulting from Transportation-Related Spills (EPA
560/5-85-009)
Because exposure assessment is a rapidly developing field, its
methods and analytical tools are quite dynamic. EPA-OTS intends to
issue periodic supplements for Volumes 2 through 9 to describe
significant improvements and updates for the existing information, as
well as adding short monographs to the series on specific areas of
interest. The first four of these monographs are as follows:
Volume 10 Methods for Estimating Uncertainties in Exposure Assessments
(EPA 560/5-85-014)
Volume 11 Methods for Estimating the Migration of Chemical Substances
from Solid Matrices (EPA 560/5-85-015)
Volume 12 Methods for Estimating the Concentration of Chemical
Substances in Indoor Air (EPA 560/5-85-016)
Volume 13 Methods for Estimating Retention of Liquids on Hands
(EPA 560/5-85-017)
Elizabeth F. Bryan, Chief
Exposure Assessment Branch
Exposure Evaluation Division
(TS-798)
Office of Toxic Substances
VI
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ACKNOWLEDGEMENTS
This report was prepared by Arthur D. Little, Inc., under
subcontract to Versar, Inc., of Springfield, Virginia, for the EPA
Office of Toxic Substances, Exposure Evaluation Division, Exposure
Assessment Branch (EAB) under EPA Contract No. 68-01-6271 (Task 12) and
Contract No. 68-02-3968 (Tasks 40 and 149). The EPA-EAB Task Managers
were Stephen Hoey, Stephen Nacht, and Lynn Delpire; their support and
guidance is gratefully acknowledged. A special thanks is due Michael
A. Callahan, Director of the Exposure Assessment Group in the EPA
Office of Research and Development, who initiated and directed the
majority of the methodology work performed under these contracts while
he was Chief of EAB.
A number of Versar and Arthur D. Little personnel have contributed
to this task over the three-year period of performance as shown below:
Program Management - Gayaneh Contos
Douglas Dixon
Joanne H. Perwak
Task Management - Joanne H. Perwak
Technical Support - Joo Hooi Ong
Richard Whelan
David Wheat
Muriel Goyer
Warren Lyman
Editing - Linda M. Nappi
Secretarial/Clerical - Linda M. Nappi
vii
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TABLE OF CONTENTS
Page
FOREWARD v
ACKNOWLEDGEMENTS vii
Table of Contents ix
List of Tables x
List of Figures xii
1.0 INTRODUCTION 1
1.1 PURPOSE AND SCOPE 1
1.2 ORGANIZATION OF THE REPORT 2
2.0 EXISTING METHODOLOGIES 5
2.1 U.S.EPA OFFICE OF RADIATION PROGRAMS 5
2.2 U.S.EPA OFFICE OF PESTICIDE PROGRAMS 6
2.3 FDA 9
2.4 SUMMARY 9
3.0 OVERALL METHODOLOGICAL FRAMEWORK 11
3.1 APPROACH 11
3.1.1 General Discussion 11
3.1.2 Step-by-Step Approach 19
3.1.2.1 Step 1 Determine the Scope of the
Assessment 19
3.1.2.2 Step 2 Collect Available Residue Data
for Food 19
3.1.2.3 Step 3 Pathways Approach 22
3.1.2.4 Step 4 Estimate Concentrations
in Food 22
3.1.2.5 Step 5 Compile Food Concentration
Data 23
3.1.2.6 Step 6 Collect Appropriate
Consumption Data 23
3.1.2.7 Step 7 Estimate Individual Dietary
Intake 23
3.1.2.8 Step 8 Consider Population Exposed 24
3.2 DATA SOURCES 24
3.2.1 Concentration Data 25
3.2.2 Consumption Data 26
3.2.3 Population Data 36
4.0 SUMMARY AND EXAMPLE 39
5.0 REFERENCES 45
APPENDIX A - PATHWAYS OF FOOD CONTAMINATION 51
APPENDIX B - QUANTITATIVE METHODS 83
APPENDIX C - EXAMPLE OF PATHWAYS APPROACH AND QUANTITATIVE
METHODS 121
ix
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LIST OF TABLES
Table Number Page
1 Summary of Exposure for Dummycide Calculated
Using the TAS Routine Chronic Analysis Protocol 8
2 Food Groups 13
3 Consumption of Fruits and Vegetables (1980) 16
4 Step-by-Step Approach 20
5 Meat, Poultry, Fish - Average Intake per
Individual in a day 27
6 Beef Steaks Consumed in 3 days by Individuals 28
7 Average Daily Intake of Food and Drinking
Water for Specified Age-sex groups (gms/day) 30
8 Food Consumption - Age - Sex Group - 25 to 30
Year Old Females 31
9 Fish Consumption Patterns for Sport Fishermen
as Compared to the U.S. Population 37
10 Levels of Benz(a)anthracene in Food 40
11 Significant Pathways of Contamination and
Estimated Concentrations - Benzanthrone 41
12 Compilation of Food Concentration Data and
Food Consumption Data - Benzanthrone 42
13 Summary of Hypothetical Individual Dietary
Exposure - Benzanthrone 44
14 Food Chain Access Points - Food Generation Stages
(Pre-Harvest) 52
15 Food Chain Access Points - Food Processing/Consump-
tion Stages (Post-Harvest) 53
16 Post-Harvest Food Chain Access Points 54
17 Pathways Identification for Indirect Routes
of Contamination 56
18 Chemical Applications which May Result in
Releases to Indoor Air 63
19 U.S. Commercial Landings by State 66
20 U.S. Commercial Landings by Port 67
x
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LIST OF TABLES (continued)
Table Number Page
21 Prioritization Scheme for Relevant Pathways 71
22 Food Generation in Two Counties 75
23 Food and Beverage Plants in Two Counties 76
24 Food Contamination Incidents 79
25 Common Accidental Food Contamination Pathways 80
26 Summary of Quantitative Methods 84
27 Important Physical/Chemical Properties Needed
for Quantification of Each Pathway 92
28 Bioconcentration Factors of Chemicals in Beef 96
29 Screening Levels for Bioconcentration in Birds,
Ruminant and non-Ruminant Mammals 97
30 Recommended Regression Equations for Estimating
log BCF, Based on Flow-through Laboratory Studies 100
31 Concentration of Compounds in Plants as a Result
of Interception 104
32 Water, Protein, Fat and Carbohydrate Distribution
of Fresh Uncooked Foods 114
33 Removal of Pesticide Residues from Spinach by
Blanching and Washing Plus Blanching 118
34 Pathways of Pollutant Loss from Food 119
35 Relevant Contamination Pathways for Benzanthrone 123
36 Scoring of Relevant Contamination Pathways for
Benzanthrone 124
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LIST OF FIGURES
Figure Number Page
1 Simple Framework for Estimating Dietary Intake 12
2 Framework for Estimating Dietary Exposure From
Foods or Food Groups 14
3 Estimation of Dietary Exposure from Vegetables 15
4 Pathways of Food Contamination 17
5 Pathways Identification Methodology 59
6 Example of Geographical Distribution of Food
Production 65
7 Prioritization of Relevant Contamination
Pathways 69
8 Scenarios of Food Concentration 108
9 Evaluation of Numerical Estimation Procedures
of Food Post-Harvest (Diffusion vs Partitioning) 115
XII
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1.0 INTRODUCTION
1.1 PURPOSE AND SCOPE
This document is one of a series of methodologies prepared for the
U.S. Environmental Protection Agency, Office of Toxic Substances* (OTS),
presenting methods for estimating exposures to toxic substances from
various exposure routes. This report is intended to provide an approach
for estimating human exposure to toxic substances in food when those
substances enter the food through environmental pathways.
The goal of this methodology is to provide a basis for examining
environmental pathways of food contamination, and for estimating human
exposure by those pathways. "Food" includes a variety of animal,
vegetable, and mineral substances produced under a wide range of
conditions. This report does not include water in its consideration of
food, as that is considered in a companion volume. Potential pathways
of food contamination are numerous, and methods for estimating
contamination from environmental sources are almost nonexistent. This
report is presented as a first attempt at an examination of the
environmental pathways of food contamination. Many complex issues, such
as crop uptake of chemicals, and fish bioconcentration of chemicals, are
considered briefly in this report, to the extent necessary to introduce
the important aspects of each issue.
This methodology presents guidelines and methods for assessing
exposure to toxic substances in food, in the form of a step-by-step
approach, with an explanation of the approach to and methods available
for each step. Because many of the data required by each step are
uncertain or unknown, the user must frequently exercise considerable
judgement in completing each of the steps in the methodology.
OTS intends to use this methodology in order to assess the
potential for humans to ingest certain toxic substances in their food.
OTS will use such an assessment to compare the magnitude of exposures
from food to the magnitudes of exposures by other routes, and determine
the more important routes of exposure.
This methodology may be used by OTS to estimate food exposures to
toxic substances already in commercial production (existing chemicals),
or to predict potential food exposure to toxic substances before their
commercialization (premanufacturing chemicals). In the case of an
existing chemical, the assessment may be based on actual monitoring of
environmental media, or it may be based on estimated environmental
concentrations, using actual or estimated releases of the existing
chemical from manufacturing, processing, industrial use, commercial use,
consumer use, or accidents. For a premanufacturing chemical, the
assessment may be based on monitoring data for a structure and use
analogue to the premanufacturing chemical, although there are a number
of problems with this approach; or it may be based on estimated
environmental concentrations, using release estimates projected for the
time after commercial production begins.
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Depending on the scope of the assessment, OTS may use the
methodology to predict food exposure from releases over a long term,
e.g., manufacturing releases, or over a short term, e.g., spills. OTS
may use the methodology to estimate food contamination in small
geographic areas, e.g., one city, or in large geographic areas, e.g.,
the entire United States.
An example of a situation in which OTS has considered food
contamination in some detail is a recent exposure assessment for PCBs as
a result of typical spills of dielectric fluid from electrical equipment
(Versar 1986). In this report, food exposure was considered in several
situations, including PCBs spilled on grazing lands and farm land used
to produce animal feed, on farm land used to produce vegetables, and on
residential lands used to produce vegetables. The PCB assessment used
some of the methods included in this methodology and many of the data
sources.
It is the intent of this methodology to provide a consistent
framework and a documentation of available resources for estimating food
exposure.
1.2 ORGANIZATION OF THE REPORT
Section 2.0 of this report describes some approaches that have been
taken by other agencies in estimating food exposure. The Food and Drug
Administration (FDA), and the Office of Pesticide Programs (OPP) and the
Office of Radiation Programs (ORP) in the Environmental Protection
Agency all have programs which require estimates of food exposure.
Generally, the approaches of FDA, OPP, and ORP are similar in that they
use available data on chemical residues in food and available data on
food consumption to estimate concentrations in food. ORP does attempt
to estimate concentrations of radionuclides in food, but these methods
are not applicable to other chemicals.
Section 3.0 describes the overall methodology, the step-by-step
approach, and data sources. The basic information and methods used to
estimate food exposure are described. The step-by-step approach leads
the user through the process, describing the data needed, the procedures
to be followed, and the results of each step. The eight steps are as
follows:
1. Determine Scope of the Assessment
2. Collect Available Residue Data
3. Pathways Approach
4. Estimation of Concentration
5. Compile Concentration Data
6. Collect Consumption Data
7. Estimate Individual Dietary Intake
8. Consider Population Exposed
Section 3.0 also contains a discussion of data available on
concentrations of contaminants in food, consumption patterns, and
population sizes.
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Section 4.0 contains a summary and examples of the use of the
methodology. The step-by-step approach is applied using the chemical
benzanthrone. Available monitoring data are summarized, important food
contamination pathways are identified and exposures estimated for those
pathways. The population exposed through the diet is also considered.
Appendix A describes the Significant Pathways Identification
Methodology. This approach can be used to identify the most significant
pathways for the chemical of concern by considering the production and
use characteristics of the chemical, the media of release, the location
and magnitude of release, and the area impacted. The physical/chemical
properties of the chemical as well as the quantity of food potentially
contaminated are also considered.
Appendix B describes calculational approaches for assessing the
potential of pollutant migration into food. Four unique contamination
pathways are identified. In the food generation stages, pathways to
meat, crops, and fish/shellfish are considered. Food in the
post-harvest stages is considered generally.
Appendix C describes the application of the pathways approach to
the chemical benzanthrone. Quantitative methods are applied to estimate
food concentrations for the most significant contamination pathways.
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2.0 EXISTING METHODOLOGIES
Three government offices (U.S. Food and Drug Administration (FDA),
U.S. EPA Office of Radiation Programs (ORP), and U.S. EPA Office of
Pesticide Programs (OPP)) have developed approaches for evaluating
exposure to chemicals in the diet. These approaches all use a
combination of food consumption data (amount and type of food eaten) and
information about contamination levels in those foods to estimate
exposure.
The OTS methodology and the three existing approaches are most
similar in their consideration of food consumption data, although the
food consumption data used by FDA, OPP, and ORP are in slightly
different forms. The OTS methodology draws heavily on the food
consumption data used by the other offices, and it can be adapted to use
food consumption data in the form used by any of these offices. The
three methodologies summarized below and the OTS methodology described
in Section 3 take somewhat different approaches to evaluating
contaminant concentrations in foods.
2.1 U.S. EPA OFFICE OF RADIATION PROGRAMS (ORP)
ORP has developed a computer program (AIRDOS) to estimate human
exposure to radioactive materials through food as a result of
atmospheric releases (US EPA 1979). The doses are calculated in three
phases. First, the air concentrations and deposition rates are
calculated. Second, the concentrations in food items are calculated.
Third, the food concentration data are used in combination with
agricultural production data and food consumption data to estimate human
exposure. The computer code may be used to estimate either individual
exposures or annual population exposures at grid locations around the
source.
Radionuclide concentrations in meat, milk, leafy vegetables, and
other vegetables are calculated for two principal routes: (1) direct
interception of a fraction of the deposited activity by plant surfaces,
and (2) uptake of deposited activity from the soil through the plant's
root system. The contamination of animal feed crop (pasture grass or
stored feeds) can also be transferred to milk and meat. The
concentration in vegetation is a function of the deposition flux and the
fraction which is intercepted by the plant, the vegetation yield, the
removal rate of the radionuclide from the vegetation, a translocation
factor which relates the radionuclide concentration in the edible
portion to that in the entire plant, and the time of vegetation
exposure. Concentrations in plants from soil are estimated from the
soil concentration and a soil-to-plant transfer factor. Concentrations
in meat and milk are also calculated using transfer factors. Some
statistical data are available providing these transfer factors for some
radionuclides. However, such compilations have not been done for other
chemicals.
The population exposed is determined by using the 1970 census
enumeration district data. The consumption by the exposed population is
based upon agricultural production and utilization factors large enough
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to ensure that all items produced are consumed. The user can specify
the fraction of vegetables, meat, and milk that are home grown, produced
in the assessment area, or imported from outside the assessment area.
The average consumption values used for adults are as follows (USEPA
1979):
Food Consumption
Leafy vegetables 18 kg/yr.
Other fresh produce 176 kg/yr.
Meat (excluding fish) 94 kg/yr.
Milk 112 liters/yr.
A more recent model to estimate risk to humans from radioactive
releases has been developed at Oak Ridge National Labortory. This model
(ANDROS) incorporates TERRA, a computer code that simulates terrestrial
transport of radionuclides. This model functions in basically the same
way as AIRDOS, however, the foods are grouped differently, and 1980
census data are used. In addition, this model can be used in
conjunction with two agricultural data libraries. Agricultural
production and land-use information are provided by county (AGDATC) or
by h by H degree longitude-latitude grid cell (AGDATG) (Baes et al.
1985).
A similar model (POPFOOD) was developed by Nair et al. (1980) for
calculating ingestion collective doses from continuous atmospheric
releases of radionuclides in the United Kingdom. Their model has the
same basic elements, but considers ten food products; milk; beef and
veal; pork, bacon and ham; poultry meat; eggs; mutton and lamb; root
vegetables; green vegetables; fruit; and cereals.
2.2 U.S. EPA OFFICE OF PESTICIDE PROGRAMS (OPP)
OPP considers dietary exposures as part of the pesticide
registration process, in setting pesticide tolerances in crops and
livestock, and in the process of considering the restriction of certain
uses of a particular product. Their estimates of dietary exposure are
based upon residue data for the food item of concern and relevant
consumption data. For these purposes, OPP has developed a new Tolerance
Assessment System (TAS) (USEPA 1984a). This system uses a data bank of
individual food consumption patterns compiled by the U.S. Department of
Agriculture to provide a system better suited to their needs. The
system also contains tolerances and residue data. An exposure analysis
using TAS can provide the following results on either a long term or
daily basis:
mean exposure for U.S. population and for 22 subgroups
expressed as mg pesticides/kg body weight/day;
distributions of exposure among individuals in each subgroup;
individual commodity contributions to exposure;
crop group contributions to exposure; and
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exposure based upon anticipated residue at the time the food
is eaten
Table 1 shows a summary of a TAS exposure assessment for a
hypothetical chemical using a routine chronic analysis. In this
analysis, a Theoretical Maximum Residue (TMRC) is calculated from the
average consumption multiplied by the prior tolerances. The average
consumption for each food is multiplied by a conversion factor to get a
"farm gate" as opposed to an "as eaten" basis. A second calculation is
done using the proposed new tolerances. Both of these are compared to
some relevant dose value (RDV), which is usually an Acceptable Daily
Intake (ADI). A detailed chronic analysis can be conducted, which will
show a distrubtion of exposures within the subgroups. In addition, TAS
can estimate acute exposure, in which food consumption estimates are for
users only.
This system could be useful for assessing exposures to toxic
substances if the food items in TAS are relevant to a particular
exposure assessment. Access to this system can be obtained by
contacting Stephen Saunders, Toxicology Branch, Hazard Evaluation
Branch, OPP (703-557-2320).
As an example of OPP's approach prior to the development of TAS,
Position Document 4 for ethylene dibromide (EDB) contained estimates of
exposure of persons in California to this compound in fresh fruit
shipped from Florida (USEPA 1983a). The mean residue level of EDB in
treated oranges was 0.048 ppm. It was assumed that 1.5 kg food was
consumed per day and that 1.35% of the average diet in California is
fresh fruit. In addition, it was assumed that 17% of the fresh fruit
consumed in California was treated. The average body weight assumed was
60 kg. Thus, the average dietary burden was estimated to be 2.75x10
mg EDB/kg body weight/day for persons in California. In addition, the
USEPA (1983a) estimated exposure for "tropical fruit eaters" consuming
12 fruits/ year. This scenario was hypothetical and did not appear to
be based upon consumption data. However, such assumptions can provide
an upper bound on exposure. OPP also uses very localized consumption
data in some cases. For the toxaphene decision document, OPP used a
fish consumption survey from three counties in the Mississippi Delta
area (USEPA 1982). This survey showed that 46.1% of the respondents
consumed fish 1-2 times/week, and 24.5% consumed fish 2-3 times/week.
The survey also showed that about 48% of the fish-eaters ate only
locally caught fish, mostly from noncommercial individual fisherman.
Thus, OPP's estimate of exposure to persons in this area assumed that
all fish eaten were caught locally and that fish were consumed three
times per week. They also assumed that each fish serving was 0.5 Ibs.
These examples of OPP's approach illustrate that they use available
concentration data and develop the consumption data most appropriate to
This is part of the system, but guidelines for considering pesticide
dissipation or concentration due to processing are under development.
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the situation. In many cases, the consumption data have been gathered
for a particular food item in a particular area of the country.
2.3 U.S. Food and Drug Administration (FDA)
The FDA has several approaches which estimate or actually measure
human exposure through food. The agency conducts yearly Total Diet
Studies. These studies represent a monitoring program intended to
provide an estimate of the actual dietary intake of pesticides, PCBs,
toxic elements, radionuclides, essential minerals, and other contaminant
residues. Market baskets representative of foods consumed are collected
from various parts of the country, prepared as for consumption, and
analyzed. Intakes are estimated for various age groups based upon
consumption patterns in the USDA's Nationwide Food Consumption Survey
(NFCS) and the Health and Nutrition Examination Survey (NHANES II). The
total diet study now includes representative diets for eight age and
sex groups, including infants, toddlers, teenage males, teenage females,
adult males and females and older males and females. Foods are
purchased in four geographic regions of the country. The diets
consist of 234 foods which represent 90% or more (by weight) of the
foods generally consumed by persons in the U.S. The consumption
patterns are based on the NCFS and the NHANES food consumption studies
(see Section 3.2.2). The agency also carries out extensive monitoring
of domestic and imported foods for these residues with emphasis on the
raw agricultural commodity.
The Division of Food and Color Additives of FDA reviews petitions
for marketing of new compounds, including food additives, color
additives, and animal drugs. They also conduct retrospective reviews of
approved compounds. In the review of additives, they assess human
exposure by considering the proposed use and consumption data for the
food of interest (USFDA 1982).
FDA developed a food consumption model to estimate dietary intake
of lead, an inadvertent contaminant in food (Beloian 1981). This model
used three variables. The number of eating occasions and mean serving
size were used along with mean lead content of foods. This approach is
slightly different than most other approaches, which use USDA food
consumption data.
2 .4 SUMMARY
In the broad sense, the approaches of FDA, OPP, and ORP are
basically the same in that they use available data (or estimates based
on available data) of levels of chemical residues in food, and available
data on food consumption to estimate exposures from food. ORP also
attempts to estimate concentrations of radionuclides in food where
residue data are not available, but ORP's methods are not immediately
useful for other chemicals, for which chemical-specific transfer factors
are unavailable.
The approach presented in this methodology draws from the existing
FDA, OPP, and ORP approaches where possible. None of these approaches
-------
is completely applicable to the types of exposure estimates envisioned
in this methodology. Where residue data are not available, the approach
in this methodology is to attempt to predict concentrations of residues,
unlike the approaches of FDA and OPP. Although ORP also attempts to
predict residue concentrations where necessary, the methods for
radionuclides are not easily used for other chemicals. This methodology
presents ORP's estimation techniques, but it also presents a number of
other techniques more useful for the chemicals of interest to OTS.
Although, as mentioned above, the approach in this methodology can
use food consumption data in the form it is used by FDA, OPP, or ORP, it
can also be adapted to use other types of food consumption data, such as
data from surveys made in a limited geographic area on one food item.
10
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3.0 OVERALL METHODOLOGICAL FRAMEWORK
3.1 APPROACH
3.1.1 General discussion
The basic framework for estimating exposure to a pollutant in the
diet is shown in Figure 1. This very simple diagram illustrates that
estimating dietary intake (E in mg/day) requires information on the
concentration (C,. in mg/kg) of the pollutant in the food or food group
at the time of consumption and on the amount of the contaminated food
consumed (L in kg/day). The concentration of the pollutant in various
food items may represent measured values or estimated concentrations.
The consumption of the food item may be an average value for the U.S.
population or region-specific, or may be a distribution of values for
individuals. This section will describe how measured concentrations
can be used to estimate food exposures, as well as how a pathway
approach can be used to identify potential mechanisms of food
contamiation. Estimates of food concentrations can then be developed
specifically for these pathways.
While using measured values for L and Cf in Figure 1 can be
simple, trying to estimate values for E is complex, because each food
and food group has different characteristics and processing methods
associated with it. Thus,
n
E - Z (C ) (L) (3-1)
i-1
for all the different foods or food groups to be considered, where E
equals total dietary exposure. The food groups used in food
consumption studies provide a good basis for estimating exposure (USDA
1980) . Table 2 shows the food groups used as a framework for
estimating exposure. Also shown in this table are the consumption,
percent fat, and the major food items of the group. This table points
out foods of particular interest because of high consumption rates or
high fat content. The latter foods might be important to consider due
to the tendency of some pollutants to bioconcentrate in fats. For a
particular assessment of food exposure, it may be necessary to consider
specific food items. For example, it may be of interest to separate
leafy vegetables from root crops. The food groups in Table 2 are
provided as a basis for a general consideration of food exposure.
Figure 2 shows how dietary intake would be estimated from the
intakes calculated for various foods or food groups. The primary food
within a food group, as identified in Table 2, is shown in the boxes in
Figure 2.
It may be necessary to consider different processing methods
within a food group, especially for fruits and vegetables. As an
example, Figure 3 shows how E , the dietary intake from vegetables,
would be estimated; the estimation of E , the dietary intake from
fruit, would be similar. Table 3 shows tne per capita consumption of
11
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Dietary Intake
(E)
rag/day
Concentration in
Food or Food Group
(Cf) mg/kg
Consumption of
Food or Food Group
(L) kg/day
FIGURE 1. SIMPLE FRAMEWORK FOR ESTIMATING DIETARY INTAKE
12
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TABLE 2
FOOD GROUPS
Food Group
Meat
Poultry
Fish/Shellfish
Milk & Milk Products
Eggs
Fats & Oils
Legumes, nuts, seeds
Grain Products
Sugar & Sweeteners
Vegetables
Fruit
Beverages
Consumption*
gram/day
Major Food Item
% Fat (consumption grams/day)
169
27
11
352
27
14
26
204
23 +
201
142
667
5-45
5-20
0.3-3
0.1-4
11.5
100
40-65
1-2
0
0.1-0.7
0.2-0.6
0
beef (54j
chicken (24)
milk (242)
eggs
shortening
wheat or whole wheat
cane and beet sugar
potatoes (64)
citrus fruit juices
coffee (262)
flour
(57)
Source: USDA (1980, 1981).
* Average consumption per individual including all age groups (USDA 1980)
Does not include sugar or sweeteners which are ingredients in other foods.
13
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meat
beef-fresh
poultry
chicken-fresh
fish/
shellfish
fish
milk/
milk products
milk-fresh
EM
eggs-fresh
E,,
fats & oils
legumes, nuts
seeds
oils
E0
beans
ED
grains
wheat flo'ir
EG
sugar/
sweeteners
sugar
Es
vegetables
vegetables
£
fruit
fruit
beverages
coffee
£
Total Dietary
Intake
FIGURE 2. FRAMEWORK FOR ESTIMATING DIETARY EXPOSURE FROM FOODS OR FOOD GROUPS
14
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TABLE 3 CONSUMPTION OF FRUITS AND VEGETABLES (1980)
Product
Vegetables
fresh
canned
frozen
Per Capita
Consumption
(grams/day)
260.6
185.9
61.8
12.9
Fruits
fresh
processed (mostly frozen citrus juices
and canned fruits and juices)
174.1
104.2
69.9
(fresh equivalent)
Note: These consumption values are slightly different from those shown
in Table 3-1 due to differences in food group definition used in
the two documents.
Source: USDA (1981).
16
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fruits and vegetables by process category. Thus, various combinations
of these intakes might be utilized, although in general it would be
important to consider the food/process category with the highest
consumption.
The above discussion may imply that in order to estimate dietary
intake, one must have concentration data for all the food groups shown
in Table 2 and Figure 2. While this may be the ideal, such data are
rarely available. In order to provide a focus to an assessment, a
pathway approach can be used. The goal of this approach is to identify
the most important pathways of contamination for food. These pathways
may be specific to type of food, process, or area of the country,
depending on the nature of the uses and releases of the compound. Once
the most significant pathways are identified, monitoring data can be
evaluated for its relevance and completeness and estimation techniques
can be focused on these pathways, thus limiting the scope of the
assessment as desired.
Figure 4 shows the potential contamination pathways of a pollutant
to food. This diagram is for illustrative purposes only, as the
complexity of this diagram reinforces the need to prioritize the
pathways in some way. There are several factors which influence the
significance of contamination pathways:
the nature of the chemical use
the chemical and physical properties of the pollutant
the nature of the food
The nature of the chemical's uses will affect where it is released
and potential points of contact with food, as shown in Figure 4. The
physical and chemical properties of the compound will affect its
persistence in any media contacting food, and its propensity to be
associated with particular food items. The nature of the food would
affect its ability to take up, absorb, or otherwise accumulate the
compound of concern.
The significance of various contamination pathways needs to be
evaluated on several different levels. On the simplest level, the
magnitude of the resultant concentration in food is the criterion, with
a higher concentration reflecting a more significant contamination
pathway. On another level, consumption patterns must be considered to
judge the significance, based on actual human exposure (see Figure 1).
In addition, however, the proportion of the total food supply (or the
size of the subpopulation) potentially affected is an important
criterion in establishing the significance of a given pathway. All of
these criteria must be accommodated at some point in a methodology to
identify significant pathways of food contamination.
It should be pointed out that the pathways described above and
shown in Figure 4 imply that a chemical will be used in a certain way.
However, the potential for an accident or misuse always exists. In
fact, many of the significant food contamination incidents are a result
of unexpected pathways. This methodology addresses some possible
17
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routes of accidental contamination, but does not provide specific
methods for estimating exposure resulting from such contamination.
3.1.2 Step-by-Step Approach
This section provides a step-by-step approach for assessing human
exposure to chemical contaminants in food. It makes use of any
available monitoring data as well as a pathways approach to identify
food items that might be contaminated. Quantitative methods are
presented to provide what is generally a rough estimate of
concentrations in food.
The step-by-step approach is summarized in Table 4 and discussed
by step in the following Sections.
3.1.2.1 Step 1 Determine the Scope of the Assessment
The scope of the assessment is a function of the objectives of the
study, which may range widely. It may be important to provide a very
rough estimate of food exposure for comparison with other exposure
routes. In contrast, a very detailed analysis of food exposure may be
required in some situations. The scope also needs to be consistent
with the data available. For example, in the evaluation of a new
chemical, no monitoring data are available for food. In addition,
limited information is available on the chemical's potential uses and
releases. Therefore, the scope and objective of such an analysis must
be realistic. For an existing chemical, a considerable amount of data
may be available, and the scope is limited by other constraints.
The determination of the objectives also involves a consideration
of the desired type of representation of exposure. Both residue data
and food consumption data may be utilized as an average or mean, a
distribution, or a maximum. While it is desirable to use a consistent
approach throughout the analysis, this is not always possible. For
example, in many cases mean residue data are used in combination with a
distribution of consumption patterns or a mean and worst case. Such an
approach was used by EPA in their consideration of exposure to EDB in
citrus, as described in Section 2.2.
The population exposed can also be considered on different levels.
In some cases, a site-specific assessment may be required, while a
national assessment is required in other cases.
The result of Step 1 should be a well-defined scope for the
assessment of food exposure, as shown in Table 4. Of course, as the
assessment progresses, modification to the scope may be needed, based
upon unforeseen data gaps or other unexpected problems.
3.1.2.2 Step 2 Collect Available Residue Data for Food
This section involves a search of the literature, if it is an
existing chemical, for data on residues of the chemical in items of the
U.S. diet. The extent to which the literature is searched and food
items are included may be limited by Step 1, the scope of the
19
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assessment. The sources of information for concentrations of
pollutants in food can be found in Section 3.2.1. For a new chemical,
it may be possible to use available data on a structure and use
analogue. At this point, it may be important to consider possible
metabolites or degradation products of the chemical. Additional data
may be available for levels of these compounds in food.
The results of Step 2 will provide a compilation of residue data
in food by food type or group. If no data are available, the user
should proceed to Step 3. When data are available, Step 3 can be used
to confirm or supplement it. If this is not desirable, the user should
go to Step 5.
3.1.2.3 Step 3 Pathways Approach
If monitoring data collected in Step 2 are inadequate and if the
scope of the assessment and the time available allow, the pathways
approach can be used to identify the most significant pathways of
contamination for food. This approach is described in Appendix A in
detail and will result in an assessment of the type of food, and the
areas of the country which are most likely to be contaminated based
upon the chemical's use and release characteristics and its physical
and chemical properties.
The results of Step 3 can be used in one of two ways. First, the
results can be used to evaluate the residue data in order to determine
whether the available data are representative of the contamination
pathways predicted to be the most significant. If not, then the second
approach could be used to estimate concentrations by these pathways
using quantitative methods in Step 4.
3.1.2.4 Step 4 Estimate Concentrations in Food - As Eaten
Step 1 and Step 3 will determine the extent to which quantitative
methods should be applied. The methods available are described in
Appendix B in four major categories. In the food generation stages,
pathways to meat, crops, and fish/shellfish are considered. In the
post-harvest stages, food is considered as a whole, as contamination
pathways are more dependent on processing method than on food types.
It is important in this process to consider the food from the point of
contamination to the consumer. For example, if wheat in the growing
stages is thought to be contaminated, then various products need to be
evaluated such as wheat flour or ready-to-eat baked goods. In
addition, while it is recognized that metabolism or degradation of
chemicals may result in more toxic compounds, such considerations are
far too complex for the general methodology at this time. If data
exists on a specific chemical being considered, these data should be
incorporated into the assessment.
Of the methods that are provided in Appendix B, some have been
empirically developed, while others are presented based upon similar
processes in other media. Most have not been validated for the
purposes which they are intended in this methodology, and none have
been developed using a data base including a large set of chemicals.
22
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These qualifications are presented as a caution for the use of these
models and the precision which can be attached to the results. With
these qualifications in mind, however, the results of Step 4 can be
used to provide concentration data for exposure estimates.
3.1.2.5 Step 5 Compile Food Concentration Data
In Step 5, the concentration data from Steps 2 and 4 will be
compiled. It should be organized by food group (See Table 2) , with
data on specific foods together. At this point, it would be useful to
present the concentration data as they will be used in the exposure
assessment. This presentation has been determined in Step 1, i.e.,
mean, maximum, or distributions of data. The results from this step
can then be used directly to estimate exposure.
3.1.2.6 Step 6 Collect Appropriate Consumption Data
In the previous steps, the foods or food groups of interest have
been determined. In order to estimate exposure, the levels of
consumption are needed for these foods. The types of data available on
consumption patterns are described in Section 3.2.2. The particular
data chosen will depend upon the scope of the assessment as determined
in Step 1. It may be desirable to use an average consumption for the
U.S. or an average consumption for those persons consuming the product
(users). In a more detailed analysis, a. distribution of consumption
patterns may be used. In some situations, the use of a maximum
consumption value may be the most appropriate. Consumption patterns
that are very limited, either geographically or by food, may be
desirable and available in some cases. In other cases, assumptions
must be made based upon available information.
The result of Step 6 is a set of consumption levels corresponding
to the concentration data for food items developed in Step 5 and in the
desired format as specified in Step 1.
3.1.2.7 Step 7 Estimate Individual Dietary Intake
The estimation of individual dietary intake using Equation 3-1 is
straightforward once Steps 5 and 6 have been completed. Of course,
these estimates represent intakes as defined by the concentration data
and consumption data. For example, if concentrations vary
geographically or with distance from a source, exposures would be
estimated to correspond to the various concentration levels. Step 1
will define these considerations to some extent. In addition, the
variation in food concentrations as determined by the monitoring data
or the fate analysis will affect the ability or need to differentiate
exposure groups.
The result of Step 7 will be a quantification to the extent
possible of the dietary intake of the chemical of interest. The intake
should be presented as defined in Step 1. It may be presented by food
or food group and may be specific to exposure groups or populations.
23
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3.1.2.8 Step 8 Consider Population Exposed
Step 7 estimates the individual exposure for a variety of exposure
groups or populations. Step 8 involves the evaluation of the numbers
of persons in each of these groups. The amount of food potentially
contaminated, as estimated in Step 3, will determine the minimum
potential population size exposed (although the maximum exposure) . The
example of OPP's exposure assessment described above in Section 2.2
showed that they had specific information on the distribution of citrus
fruits shipped from Florida to California. In general, however, such
information is not easily obtainable. Two different options for
quantifying the population exposed can be used, depending upon the
consumption pattern information utilized. These options are as
follows :
Pf - Z
Where P,. - the number of persons exposed to the pollutant from
consuming a particular food, T,. = the total amount of the food
potentially contaminated in kg/year, and ~Lf= the consumption pattern
for that food in kg/day. This method obviously assumes that all food
produced is consumed and that 100% of the person's diet of the
particular food item is contaminated. Alternatively, all users of the
food item in the U.S. could be exposed, with the contaminated product
representing a portion of their consumption of that food item:
Tf
F - R (3-3)
where F = the fraction of the food item produced yearly that is
contaminated, and R = the total amount of the food produced per year
(kg). On the average, the actual consumption of the contaminated
product (A in kg/day) can be estimated by:
Af - F Lf (3-4)
These two options represent a wide range for the exposed
population. The first alternative is more appropriate when production
and consumption are confined to a local area. The second alternative
should be used when the contaminated product is known to be widely
distributed.
The population exposed would be determined by food or food group and
would be consistent with assumptions made about consumption patterns.
3.2 DATA SOURCES
There are many pieces of data that are needed in the application
of the methodology for estimating the dietary intake of a chemical.
The two parts of the equation are the concentration in the food and the
consumption of the food as shown in Figure 1. In general, three types
of data are needed, each at various points in the general methodology
described. They are: concentration data, consumption data, and
24
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population data. Data sources and data bases for each of these
categories are described below.
3.2.1 Concentration Data
Information on concentrations of pollutants in foods or food
groups is very scattered in the literature. There is no data base
containing a compilation of the existing data on residues. The
following list gives some potential sources of concentration data:
Pesticides Monitoring Journal, Journal of the Association of
Official Analytical Chemists
Results of FDA's Total Diet Studies, primarily for pesticides and
industrial chemicals such as PCB's and toxic elements. Results of
FDA's monitoring of domestic and imported food, primarily for
pesticides, industrial chemicals and toxic elements.
STORET
U.S. EPA Monitoring and Data Support Division, Office of Water -
Water Quality Data Base - contains fish tissue data from a variety
of sources for a number of pollutants.
USDA
Food Safety and Inspection Service - collects nationwide samples
of meat and poultry at slaughter establishments, analyzed for
animal drugs, pesitides, and other chemicals. Date can be
retrieved by zip code of the seller or packing plant.
U.S. EPA - Office of Pesticide Programs
Residue Chemistry Branch - residue data for registered pesticides
in raw agricultural commodities.
States
Some states have monitoring programs particularly for pesticides
and a few other chemicals; monitoring data for fish may also be
available.
In searching for data for a particular contaminant in food, a
literature search would be required, covering both agricultural and
environmental journals. Several journals publish data on measurements
of pollutant concentrations in fish, animals, and crops. Among these
are journals such as Residue Reviews, Journal of Agriculture and Food
Chemistry, Environmental Science and Technology, Bulletin of
Environmental Contamination and Toxicology, Journal of Food Technology,
and Journal of Food Science. However, many of the surveys are very
region-specific and may be found in journals published and distributed
in that region. A comprehensive literature search would be required to
ensure the collection of all food monitoring data. In some
assessments, regulatory levels can be used instead of actual monitoring
data. Tolerances that are established for toxic substances in or on
25
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raw agricultural commodities or in processed foods could be used in an
exposure assessment. These levels are used in exposure assessments by
OPP as shown in Table 2. The GRAS allowable levels could be used in a
similar manner. The use of such indices would provide a worst case
assessment, as they represent maximum allowable levels.
3.2.2 Consumption Data
Depending on the contamination pathway under consideration,
different types of data on food consumption patterns will be required
as input into the equation to estimate dietary intake. The primary
data source for food consumption patterns is the 1977-78 household
survey of food consumption conducted by the U.S. Department of
Agriculture, the Nationwide Food Consumption Survey - NFCS (USDA 1980).
A sample of 15,000 households and 34,000 individuals was included in
the basic survey of the 48 conterminous states for each of four
quarters from April 1977 through March 1978. Supplemental surveys were
conducted to include: elderly persons; households eligible for the
Food Stamp Program; urban households; and households in Alaska, Hawaii
and Puerto Rico. In all cases, except the supplemental survey of
elderly persons, dietary intake was recorded for three consecutive
days. The food data base contains 3727 foods. This report (USDA 1980)
provides average consumption levels for individuals (by age) or
households, region of the country, income, season of the year, and
level of urbanization. Food items are covered quite specifically, and
food sources (i.e., bought, home produced) are considered to some
degree. Food processing methods are also differentiated, including
data on fresh, frozen, dried, and canned foods. Table 2 summarizes
results for all individuals for major food groups and Table 5 shows an
example of data on consumption of meat, poultry, and fish for all age
categories. While these data should be adequate for most purposes,
there are some deficiencies. For example, USDA (1980) presents average
daily consumption patterns. The data base, however, contains all the
individual consumption patterns, so distributions are possible as the
data base has been computerized by USDA.
Pao et al. (1982) has published a report based upon the USDA
Nationwide Food Consumption Survey. Their report summarizes the
percent of individuals using particular food items in the three days
for which dietary information was available (users) and the average
consumption per day by users at specified percentiles. The maximum in
any one day, as well as the maximum over three days is also reported.
Consumption patterns are differentiated by age and sex of individual,
but not by area of the country. Specific foods which were most
commonly reported by individuals are included in this report. Table 6
shows an example of these data for beef steaks.
In general, these two data compilations are adequate for most
exposure assessments. The NFCS data provide average intakes by various
groups for a wide variety of foods. The data from this survey
summarized by Pao provides additional information an average and
distribution of intakes for users, as well as a maximum intake for one
day. These data would be useful for worst-case assessments or where
acute affects are of concern.
26
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The National Center for Health Statistics also conducted a
national dietary survey, the National Health and Nutrition Examination
Survey (NHANES II) from 1976-1980. This survey obtained 24-hour
dietary recalls from 20,325 individuals. The data base from this
survey contains 2,614 food items. This survey was less comprehensive
than the NFCS survey, and in most cases the NFCS survey would provide
the consumption data necessary.
Several other agencies have modified the NFCS and the NHANES data
for their own purposes. OPP has used the NFCS data to provide
consumption data as part of their Tolerance Assessment System (USEPA
1984a) as described in Section 2.2. FDA used average values for
consumption from the two national surveys in order to provide a basis
for sampling in the Total Diet Study and for estimating exposure (USEPA
1983b) . They used total food consumption as shown in Table 7. Food
consumption data were then reported as an average (from the average of
the two surveys) percent of the total diet for the eight age-sex
groups. No food was included in the Total Diet study which equaled
less than 0.02 percent of the total diet by weight. Table 8 shows an
example of the daily intakes for 25-30 year old females.
U.S. EPA (1980a) used the 1965-1966 NFCS data to analyze food
consumption habits in terms of home grown vs commercially produced
fruits and vegetables. Consumption of fruits and vegetables by
non-meat eaters was also examined.
These systems could provide useful consumption data for this
methodology. TAS was developed for setting pesticide tolerances, and
therefore, the NFCS data had to be converted to raw agricultural
commodities. If contamination is thought to occur during the food
generation stage, TAS would be the most appropriate system to use. The
Total Diet Study, on the other hand, is oriented towards providing
consumption data for foods as they are prepared and consumed. These
data are based on the NFCS and NHANES data, and would not generally
provide additional information. The OTS (USEPA 1980a) data, although
limited in scope, would be very useful if exposure through home gardens
was of interest.
Another source of food consumption data is USDA (1981, 1985).
These data provide average intake per capita for a number of food
groups. No subpopulations by age or location are considered. This
report may, however, contain information on some foods or processing
methods not included in NFCS. Table 3 summarized data on consumption
of fruit and vegetables from this source.
Section 2.1 describes the ORP dietary exposure assessment methods.
The consumption patterns developed for this system are specific to
airborne radionuclides and are based on very general food groups.
However, these consumption data may be used if airborne contamination
is expected, and a great degree of food specificity is not necessary.
One major inadequacy in the consumption pattern data sources
discussed above is that they do not consider consumption patterns in
different areas of the country aside from the four census regions,
29
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TABLE 8 FOOD CONSUMPTION
AGE-SEX GROUP - 25 TO 30 YEAR-OLD FEMALES
Average NHANES grams/day - 1938
Average NFCS grams/day - 1615
Average of NHANES and NFCS grams/day - 1777
001
002
003
004
005
006
007
008
009
010
on
012
013
014
015
016
017
018
019
020
021
022
023
024
025
026
027
028
029
030
031
032
033
034
Food
Whole milk
Lowfat milk, 2%
Chocolate milk
Skim milk
Buttermilk
Yogurt, plain
Chocolate milkshake
Evaporated milk
Yogurt, strawberry
American cheese
Cottage cheese, 4%
Cheddar cheese
Ground beef
Beef chuck roast
Beef round steak
Beef loin steak
Pork ham
Pork chop
Pork sausage
Pork bacon
Pork roast
Lamb chop
Veal cutlet
Chicken, fried
Chicken, roasted
Turkey, roasted
Liver, fried
Frankfurters
Bologna
Sal ami
Cod, baked
Tuna, canned in oil
Shrimp, fried
Fish sticks, frozen
NHANES
(%)
5.310
3.381
.332
.816
.108
.172
.074
.033
.118
.358
.189
.287
.788
.521
.059
.706
.410
.270
.094
.075
.140
.100
.089
.416
.408
.010
.293
.253
.223
.033
.340
.200
.138
.076
NFCS
(%)
6.569
2.506
.888
.880
.011
.104
.298
.013
.242
.369
.355
.335
1.112
.738
.113
1.063
.361
.402
.249
.167
.177
.050
.060
.615
.714
.170
.111
.344
.402
.034
.364
.287
.163
.125
NHANES
(g)
102.908
65.524
6.434
15.814
2.093
3.333
1.434
.640
2.287
6.938
3.663
5.562
15.271
10.097
1.143
13.682
7.946
5.233
1.822
1.454
2.713
1.938
1.725
8.062
7.907
.194
5.678
4.903
4.322
.640
6.589
3.876
2.674
1.473
NFCS Average Average
(g) (g) (%)
106.059
40.458
14.334
14.206
.179
1.682
4.816
.217
3.905
5.957
5.734
5.402
17.947
11.911
1.831
17.171
5.821
6.483
4.019
2.701
2.859
.810
.965
9.926
11.531
2.750
1.797
5.560
6.492
.546
5.877
4.630
2.636
2.011
104.484
52.991
10.384
15.010
1.136
2.508
3.125
.428
3.096
6.448
4.698
5.482
16.609
11.004
1.487
15.427
6.883
5.858
2.920
2.077
2.786
1.374
1.345
8.994
9.719
1.472
3.738
5.232
5.407
.593
6.233
4.253
2.655
1.742
5.880
2.982
.584
.845
.064
.141
.176
.024
.174
.363
.264
.309
.935
.619
.084
.868
.387
.330
.164
.117
.157
.077
.076
.506
.547
.083
.210
.294
.304
.033
.351
.239
.149
.098
31
-------
TABLE 8 FOOD CONSUMPTION
AGE-SEX GROUP - 25 TO 30 YEAR-OLD FEMALES (continued)
-MANES KPCS NHJNES »PCS Aver.,, Averse
035
036
037
03S
039
040
041
042
043
044
045
046
047
048
049
050
051
052
053
054
055
056
057
058
059
060
061
062
063
064
065
066
067
068
069
070
Eggs, scrambled
Eggs, fried
Eggs, boiled
Pinto beans
Pork and beans, canned
Cowpeas
Limas, mature
Limas, immature
Navy beans
Red beans
Peas, canned
Peas, frozen
Peanut butter
Peanuts
Pecans
White rice
Oatmeal
Farina
Corn grits
Corn, fresh/frozen
Corn, canned
Corn, creamed style,
canned
Popcorn
White bread
White rolls
Cornbread
Biscuits
Whole wheat bread
Tortilla, flour
Rye bread
Muffins
Saltines
Corn chips
Pancakes
Noodles
Macaroni
.389
.343
.208
.492
.178
.066
.005
.063
.038
.054
.237
.124
.054
.039
.078
.784
.216
.085
.124
.253
.150
.066
.147
1.883
.639
.185
.156
.166
.148
.108
.070
.207
.045
.212
.089
.223
.745
.336
.339
.379
.469
.128
.045
.083
.042
.108
.374
.058
.086
.044
.026
1.028
.283
.136
.239
.424
.125
.121
.033
2.004
.478
.257
.192
.318
.108
.082
.033
.183
.046
.301
.124
.290
7.539
6.647
4.031
9.535
3.450
1.279
.097
1.221
.736
1.047
4.593
2.403
1.047
.756
1.512
15.194
4.186
1.647
2.403
4.903
2.907
1.279
2.849
36.493
12.384
3.585
3.023
3.217
2.868
2.093
1.357
4.012
.872
4.109
1.725
4.322
12.028
5.425
5.470
6.117
7.569
2.059
.721
1.344
.684
1.745
6.045
.939
1.381
.705
.416
16.595
4.574
2.194
3.856
6.846
2.012
1.951
.531
32.356
7.726
4.152
3.102
5.139
1.744
1.328
.537
2.952
.745
4.855
1.994
6.302
9.783
6.036
4.751
7.826
5.509
1.669
.409
1.282
.710
1.396
5.319
1.671
1.214
.731
.964
15.895
4.380
1.921
3.130
5.875
2.460
1.615
1.690
34.424
10.055
3.869
3.063
4.178
2.306
1.711
.947
3.482
.809
4.482
1.859
5.312
.551
.340
.267
.440
.310
.094
.023
.072
.040
.079
.299
.094
.068
.041
.054
.895
.247
.108
176
* A ' \>
.331
.133
.091
.095
1.937
566
*J \J \J
.218
172
« A f £.
235
C. J J
130
X %J \J
096
* \J .s \J
053
\J
-------
TABLE 8 FOOD CONSUMPTION
AGE-SEX GROUP - 25 to 30-YEAR-OLD FEMALES (continued)
NHANES
Food (%)
071
072
073
074
075
076
077
078
079
080
081
082
083
084
085
086
087
088
0*9
090
091
092
093
094
095
096
097
098
099
100
101
102
103
104
105
106
107
108
109
110
111
112
Cornflakes
Fruit type cereal
Shredded wheat
Raisin bran
Crisped rice
Granola
Oat ring cereal
Apple, raw
Orange, raw
Banana, raw
Watermelon, raw
Peach, canned
Peach, raw
Applesauce, canned
Pear, raw
Strawberries, raw
Fruit cocktail, canned
Grapes, raw
Cantaloupe, raw
Pear, canned
Plums, raw
Grapefruit, raw
Pineapple, canned
Cherries, raw
Raisins, dried
Prunes, dried
Avocado, raw
Orange juice, frozen
Apple juice, canned
Grapefruit juice,
frozen
Grape juice, canned
Pineapple juice, canned
Prune juice, bottled
Orange drink, canned
Lemonade, frozen
Spinach, canned
Spinach, fresh/frozen
boiled
Collards, boiled
Lettuce
Cabbage, boiled
Coleslaw
Sauerkraut, canned
.071
.015
.073
.051
.045
.045
.019
.761
.454
.301
.237
.102
.186
.088
.148
.094
.245
.080
.220
.014
.048
.476
.084
.025
.006
.004
.091
2.938
.358
.428
.190
.060
.000
.902
.396
.030
.130
.039
1.135
.166
.108
.040
MFCS
{%)
.076
.014
.100
.091
.042
.019
.035
.819
.443
.363
.195
.175
.252
.197
.087
.120
.191
.052
.125
.081
.033
.197
.072
.043
.025
.006
.053
2.733
.370
.326
.335
.081
.020
.878
.626
.067
.152
.065
1.554
.177
.170
.033
NHANES
(g)
1.473
.291
1.415
.988
.872
.872
.368
14.748
8.799
5.833
4.593
1.977
3.605
1.705
2.868
1.822
4.748
1.550
4.264
.271
.930
9.225
1.628
.485
.116
.078
1.764
56.938
6.938
8.295
3.682
1.163
.000
17.481
7.675
.581
2.519
.756
21.996
3.217
2.093
.775
NFCS Average Average
(g) (g) (%)
1.224
.230
1.615
1.473
.680
.301
.566
13.221
7.150
5.865
3.141
2.827
4.064
3.176
1.411
1.942
3.086
.841
2.013
1.316
.538
3.177
1.164
.699
.398
.104
.859
44.123
5.969
5.258
5.411
1.309
.328
14.171
10.106
1.081
2.450
1.051
25.084
2.854
2.750
.536
1.348
.260
1.515
1.231
.776
.587
.467
13.985
7.974
5.849
3.867
2.402
3.834
2.441
2.140
1.882
3.917
1.196
3.138
.794
.734
6.201
1.396
.592
.257
.091
1.311
50.531
6.454
6.776
4.547
1.236
.164
15.826
8.890
.831
2.485
.903
23.540
3.036
2.422
.656
.076
.015
.085
.069
.044
.033
.026
.787
.449
.329
.213
.135
'.216
.137
.120
.106
.220
.067
.177
.045
.041
.349
.079
.033
.015
.005
.074
2.844
.363
.381
.256
.070
.009
.891
.500
.047
.140
.051
1.325
.171
.136
.037
33
-------
TABLE 8 FOOD CONSUMPTION
AGE-SEX GROUP - 25 TO 30 YEAR-OLD FEMALES (continued)
NHANES
Food (%)
153 Pork chow mein
154 Frozen dinnner, fried
chicken
155 Bouillon
156 Chicken noodle soup
157 Creamed tomato soup
158 Vegetable beef soup
159 Gravy
160 White sauce
161 Dill pickles
162 Margarine
163 Salad dressing, Italian
164 Butter
165 Corn oil
166 Mayonnaise
167 Cream, 1/2 and 1/2
168 Cream substitute
169 Sugar
170 Corn syrup
171 Grape jelly
172 Honey
173 Catsup
174 Ice cream, chocolate
175 Pudding, chocolate
176 Ice cream sandwich
177 Ice milk, vanilla
178 Chocolate cake and
chocolate icing
179 Yellow cake and
white icing
180 Coffeecake
181 Doughnut
182 Danish pastry
183 Chocolate chip cookies
184 Sandwich cookies
185 Apple pie
186 Pumpkin pie
187 Chocolate candy
188 Carmel candy
189 Chocolate powder
190 Gelatin dessert,
strawberry
.085
.062
.295
.219
.326
.512
.144
.091
.051
.220
.289
.136
.127
.054
.097
.072
.337
.091
.149
.026
.095
.497
.133
.030
.149
.190
.331
.034
.259
.099
.255
.118
.285
.168
.212
.076
.079
.154
MFCS
(%)
.372
.099
.639
.616
.953
.133
.284
.012
.101
.193
.345
.140
.016
.098
.102
.033
.270
.165
.095
.029
.092
.563
.171
.046
.056
.186
.295
.051
.146
.133
.159
.063
.264
.208
.092
.111
.205
.229
34
NHANES
(g)
1.647
1.202
5.717
4.244
6.319
9.923
2.791
1.764
.988
4.264
5.601
2.636
2.461
1.047
1.880
1.395
6.531
1.764
2.888
.504
1.841
9.632
2.578
.581
2.888
3.682
6.415
.659
5.019
1.919
4.942
2.287
5.523
3.256
4.109
1.473
1.531
2.985
NFCS Average Average
(g) (g) (%)
6.009
1.597
10.309
9.940
15.390
1.817
4.593
.194
1.629
3.119
5.576
2.254
.263
1.581
1.647
.529
4.365
2.662
1.535
.475
1.482
9.087
2.766
.741
.911
3.002
4.763
.829
2.362
2.140
2.561
1.010
4.269
3.351
1.486
1.793
.401
3.701
3.824
1.399
8.013
7.092
10.854
5.870
3.692
.979
1.309
3.691
5.558
2.445
1.362
1.314
1.763
.962
5.448
2.213
2.211
.489
1.662
9.359
2.672
.661
1.899
3.342
5.589
.744
3.691
2.030
3.751
1.648
4.896
3.303
2.797
1.633
.966
3.343
.215
.079
.451
.399
.611
.330
.208
.055
.074
.208
.315
.138
.077
.074
.099
.054
.307
.125
.124
.028
.094
.527
.150
.037
.107
.188
.315
.042
.208
.144
.211
.093
.276
.186
.157
.092
.054
.188
-------
TABLE
AGE-SEX GROUP
FOOD CONSUMPTION
25 TO 30 YEAR-OLD FEMALES (continued';
NHANES
Food (%)
MFCS
(%)
NHANES
(g)
NFCS
(g)
Average
(g)
Average
(%)
191 Soda, cola 7.420
192 Soda, lemon-lime 2.927
193 Soft drink, cherry 2.250
194 Soda, low calorie, cola 3.346
195 Coffee beverage
196 Coffee beverage,
decaffeinated
197 Tea beverage
198 Beer
199 Wine
200 Whisky
201 Water
7.548
1.642
1.324
2.697
143.800
56.725
43.605
64.846
121.878
26.518
21.375
43.546
132.839
41.622
32.490
54.196
7.476
2.342
1.823
3.050
18.227 13.230 353.239 213.615 283.427 15.950
1.031 .900 19.981 14.527 17.254 .971
9.037 9.385 175.137 151.528 163.333 9.195
2.481 1.307 48.082 21.100 34.591 1.947
.775 .547 15.020 8.830 11.925 .671
.229 .337 4.438 5.433 4.936 .278
Source: U.S. EPA 1983b
35
-------
northeast, north central, south, and west; and the three urbanizations,
central city, suburban, and non-metropolitan. In addition, specific
subpopulations (e.g., vegetarians) are not generally considered. While
these variations would be reflected in the distribution of intakes, any
geographic patterns would not be differentiated. For example,
consumption of home grown produce or locally caught fish may be
important in very localized areas. Of interest in this regard is a
report by Puffer et al. (1982), which examined the fish consumption
rates by fishermen and their families in the metropolitan Los Angeles
area. Table 9 shows the distribution of consumption reported in this
study. These data show an interesting pattern. The median consumption
of fish by the sport fishermen is somewhat lower than that by the users
among the U.S. population (those persons reporting consumption of
fish). Fish consumption at the high end of the range, however, is much
higher for the sport fishermen. Similar studies have been conducted in
a few other areas, e.g., Puget Sound (Pierce et al. 1981) and the
Mississippi Delta area (USEPA 1982). Such examples show the potential
variation in consumption patterns by different subpopulation groups.
If specific information not available from the National Surveys is
needed, a search of the literature may provide more specific data.
Unfortunately, such information is rarely available, and the national
data must be used directly or modified by some assumptions about
specific food items or areas of the country.
3.2.3. Population Data
The size of the population is determined to some extent by the
amount of food potentially contaminated. Appendix A describes methods
for determining the quantity of food contaminated. Numerous sources of
data are available for assessing such quantities:
Census of Agriculture (USDOC 1981)
- areas where foods are grown; extensive statistics on number of
head of stock or acres of crop production by county for entire
U.S.; livestock and poultry--numbers/county; crops--acres/
county;location and production of fish farms (not commercial or
sport fishing acres)
National Marine Fisheries Service (NMFS) of NOAA (NMFS 1980a)
Fishery Statistics of the United States 1976
- Commercial fisheries statistics
National Marine Fisheries Service. Fisheries of the United States
1982. (NMFS 1983)
U.S. Commercial landings by state, and at about 120 major U.S.
ports, in pounds and dollars
National Marine Fisheries Service. Marine Recreational Fishery
Statistics (NMFS 1980b)
36
-------
TABLE 9
FISH CONSUMPTION PATTERNS FOR SPORT FISHERMEN
AS COMPARED TO THE U.S. POPULATION
Consumption Rate (g/dav/person)
Percentile
5
25
50
75
90
95
LA Sport
2.
11.
36.
100.
244.
338.
Fishermen
3
9
9
3
8
8
Nationwide
USDA Survey
11
27
47
80
128
165
The USDA data are for males 19-34 since this was the age group most
comparable to the Los Angeles study population. Fish was consumed at least
once in three days. In the LA study, 68% of the respondents reported
eating fish one time per week or more. The median daily consumption was
127.2 g/day for frequent eaters (3-7 times/week) and 27.2 g/day for
infrequent eaters.
Source: Pao et al. 1982; Puffer et al. 1981
37
-------
Summaries of fish caught by state and by various other
characteristics
AGDATC and AGDATG (Baes et al. 1985). Contact: B.L. McGill, Oak
Ridge National Laboratories, Oak Ridge, TN 37831 (615-574-6176).
Two agricultural data libraries containing agricultural
production for vegetables and produce, livestock and livestock
feeds. Intended for use in exposure assessment, specifically for
radionuclides. Data by county or long/lat grid cell.
Office of Drinking Water, The Federal Reporting Data System --
Public Water Systems. Contact: Mr. Avrum W. Marks, USEPA, Office
of Drinking Water (202-382-5513).
Database documents public water supplies by county or city,
giving source information, population served, and treatment
techniques used.
The Chilton Company (1981) Directory of U.S. Food and Beverage
Plants
Lists all food and beverage plants within a county, products
produced, peak employment; no volume of production
Trinet, Inc. (Economic Information Systems, Inc.)
Trinet market share data base (% sales) for each plant within a
given SIC category. Contact: Trinet, Inc. 9 Campus Drive,
Parsippany, NJ 07054.
Census of Manufacturers, USDOC (1980)
Total volume of shipments for the U.S. within the SIC code
Data addressing population sizes (or users) for the U.S. are
contained in USDA (1983) as described above. In addition, if the
population exposed is defined geographically, the total population in
an area can be obtained from U.S. Census data as described in Dixon et
al. (1985). In some cases, it may be useful to determine the total
population in a specific area and then to estimate the user population
using the national or regional data developed by USDA (1983) .
38
-------
4.0 SUMMARY AND EXAMPLE
The previous section has described a step-by-step approach to
assessing dietary intake. This approach uses available monitoring
information, but may be supplemented by a pathways approach which is
intended to identify the more significant situations of food contact.
This seems like a straightforward procedure, but in practice, many
unexpected situations may arise. The best way to further describe the
approach is by example. This section therefore describes a
hypothetical application of the step-by-step approach using the
chemical benzanthrone.
Step 1 Determine the Scope of the Assessment
Benzanthrone is an existing chemical, primarily used as an
intermediate. Therefore, monitoring data are expected to be scarce and
estimation of contamination resulting from significant pathways will be
conducted when possible. Mean residue data and consumption data will
be used. The assessment will be on a national basis.
Step 2 Collect Available Residue Data
No residue data were available for benzanthrone. For the purpose
of this example, data on benz(a)anthracene were used as shown in Table
10. It is not suggested that these chemicals are structurally
similiar. The monitoring data was used to show how such data could be
incorporated into an analysis. These residues are generally attributed
to formation during cooking. In such a case, the pathways approach
cannot be used to compare predicted results with measured results since
residues produced during cooking will not be predicted in the pathways
approach. These measured values are included here to show the
associated consumption patterns and the populations exposed as compared
to the consumption patterns and populations exposed for the predicted
exposure pathways.
Step 3 Pathways Approach
The detailed application of the pathways approach for benzanthrone
is described in Appendix C. The results of this method are shown in
Table 11.
Step 4 Estimate Concentrations in Food
Appendix C details the quantification methods used for estimating
concentrations of benzanthrone in food. The results are shown in Table
4-2.
Step 5 Compile Food Concentration Data
In Step 5, the available concentration data should be compiled by
exposure group as well as by food group. Table 12 shows a hypothetical
summary for benzanthrone.
39
-------
TABLE 10
LEVELS OF BENZ(A)ANTHRACENE IN FOOD
Food Item
Charcoal-Broiled Steak
Smoked Pork
Smoked Sausage
Smoked Fish
Oil
Average Concentration (ug/kg)
3
3
0.2
1
1
Source: Perwak et al. (1981b)
40
-------
TABLE 11
SIGNIFICANT PATHWAYS OF CONTAMINATION AND ESTIMATED CONCENTRATIONS
--BENZANTHRONE
Estimated
Source of Contamination Concentration
Human Exposure Pathway fug/kg)
Meat Ingestion of Drinking Water 0.045 (beef)
Beef
Dairy
Hogs and Pigs
Sheep and Lamb
Poultry
Fish Absorption From Water 4500
Food- Post Harvest Absorption/Addition of Water 1 fruits and
used in Processing vegetables
10 beverages
Source: Appendix C
41
-------
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Step 6 Collect Appropriate Consumption Data
Table 12 also shows average U.S. consumption data for the foods
included in the assessment. This table shows that assumptions are
commonly made about the nature of the food in a particular group. In
the example, assumptions were made about the portion of the total
consumption that was charcoal-broiled or smoked. For the population
exposed to food contaminated in the area of the production releases, it
was assumed that their total consumption of these items was from the
contaminated area. This implies a worst case in terms of exposure, but
a minimum number of persons exposed.
Step 7 Estimate Individual Exposure
With the information in Table 12, individual exposure can be
calculated using Equation 3-1. The hypothetical results are summarized
in Table 13. Exposure in this hypothetical example is greater to those
people consuming food contaminated in the vicinity of benzanthrone
production facilities than to those consuming charcoal-broiled or
smoked meats (using the data for benz-(a)anthracene). It should always
be noted that such a conclusion is based upon a long series of
estimation procedures in the pathways approach, from the fate processes
to the food contamination situations, with uncertainties associated
with each step. On the other hand, limited monitoring data must
sometimes be used to represent average U.S. concentrations. In most
cases, however, the use of monitoring data is preferable, if available.
Step 8 Estimate Population Exposed
In this example, two populations were identified. One population
was persons exposed to this compound in meats that are charcoal-broiled
or smoked. The population size must be considered on a food-by-food
basis. For example, Pao et al. (1982) showed that 67.3% of the
individuals in the food consumption survey consumed beef at least once
in three days. These persons are designated as the users and are the
exposed population (67.3% of the U.S. population) for beef. Similarly
49.9% of the population consumed pork, and 13.5% of the population
consumed sausage.
The population sizes of the second group (food contaminated near
the production facility) are more difficult to quantify. Again, the
sizes should be considered on a food-by-food basis. The actual sizes
are dependent upon the amount of each food type contaminated and the
distribution patterns for each. In this example, the amount of food
contaminated was not quantified, but benzanthrone production is limited
to eight sites. In addition, it was assumed that the exposed
population received 100% of their consumption of the identified foods
from the contaminated area. Considering these assumptions, the exposed
population would be quite small.
43
-------
TABLE 13
SUMMARY OF HYPOTHETICAL INDIVIDUAL DIETARY
EXPOSURE -- BENZANTHRONE
Exposure Group
General Population
Food Group
Meat
Fish/Shellfish
Oil
Total
Exposure (ug/day)
0.009
0.0001
0.01
0.02
Persons Consuming Food
Generated or Processed
near Production Facilities
Meat
Fish/Shellfish
Vegetables
Fruit
Beverages
Exposure to General
Population
Total
0.002
50
0.2
0.07
6
0.02
60
44
-------
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USDA. 1981. U.S. Department of Agriculture. Food consumption,
prices, and expenditures. Statistical Bulletin No. 672. USDA,
Economic Research Service. PB 82-114315.
USDA. 1983. U.S. Department of Agriculture. Food consumption:
Households in the United States, Seasons and year 1977-1978.
USDA. 1985. U.S. Department of Agriculture. Food consumption,
prices, and expenditures 1963-1983. USDA, Economic Research Service
PB 85-134617.
USDOC. 1980. U.S. Dept. of Commerce. 1977 Census of Manufacturers,
Industry Series. USDOC, Bureau of the Census.
USDOC. 1981. U.S. Dept. of Commerce. 1978 Census of Agriculture.
USDOC, Bureau of the Census.
USDOC. 1982. U.S. Dept. of Commerce. 1978 Census of Agriculture,
Vol. 5. Special Reports. Part 1 Graphic Summary. USDOC, Bureau of
the Census.
USEPA. 1979. U.S. Environmental Protection Agency. AIRDOS-EPA. A
computerized methodology for estimating environmental concentrations
and dose to man from airborne releases of radionuclides. Oak Ridge
National Laboratory, Prepared for Office of Radiation Programs.
PB80-147838.
USEPA. 1980a. Dietary consumption distributions of selected food
groups for the U.S. population. Office of Toxic Substances, U.S.
Environmental Protection Agency. EPA 560/11-80-012.
USEPA. 1980b. U.S. Environmental Protection Agency. Water Quality
Criteria Documents. Availability. FR 45:79318-79379.
49
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USEPA. 1982. U.S. Environmental Protection Agency. Toxaphene:
Position Document. Office of Pesticide Programs, USEPA.
USEPA. 1983a. U.S. Environmental Protection Agency. Ethylene
Dibromide (EDB) Position Document 4. Office of Pesticide Programs.
U.S. Environmental Protection Agency. September 27, 1983.
USEPA. 1983b. U.S. Environmental Protection Agency. The human food
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Environmental Monitoring Systems Laboratory, USEPA. Prepared for
Office of Toxic Substances. EPA 600/X-83-001.
USEPA. 1984a. U.S. Environmental Protection Agency. Tolerance
Assessment System: Background information. USEPA, Hazard Evaluation
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USEPA. 1984b. U.S. Environmental Protection Agency. User's manual
for TOX-SCREEN: A multimedia screening-level program for assessing
the potential fate of chemicals released to the environment. Oak
Ridge National Laboratory ORNL-6041, Washington, D.C.: USEPA, Office
of Toxic Substances, EPA-560/5-83-024.
USEPA. 1984c. U.S. Environmental Protection Agency. Radionuclides:
Background information document for final rules. Vols I and II.
Washington D.C.: USEPA, Office of Radiation Programs. EPA
520/1-84-022-1.
USFDA. 1982. U.S. Food and Drug Administration. Toxicological
principles for the safety assessment of direct food additives and
color additives used in food. Washington, D.C.: USFDA, Bureau of
Foods.
USNRC. 1977. U.S. Nuclear Regulatory Commission. Calculation of
annual doses to man from routine releases of reactor effluents for the
purpose of evaluating compliance with 10 CFR Part 50, Appendix I.
Regulatory Guide 1.109. Washington, D.C.: USNRC, Office of Standards
Development.
Vaughan BE, Soldart JK, Schreckhise RG, Watson EC, et al. 1981.
Problems in evaluating radiation dose via terrestrial and aquatic
pathways. Environ. Hlth. Perspec. 42:149-161.
Versar, Inc. 1986. PCB Spill Clean up: Estimates of potential
exposure of humans to PCBs as a result of typical spill of dielectric
fluid from electrical equipment. Revised draft report to Office of
Toxic Substances, U.S. EPA. EPA Contract No. 68-02-3968.
Wanniger LA, Jr. 1972. Mathematical model predicts stability of
ascorbic acid in food products. Food Technology. June: 42-45.
Williams MP, Nelson PE. 1974. Kinetics of thermal degradation of
methylmethionine sulfonium ions in citrate buffers and in sweet corn
and tomato serum. J. Food Sci. 39: 457-460.
50
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APPENDIX A
PATHWAYS OF FOOD CONTAMINATION
A.I INTRODUCTION
There are many pathways by which a chemical can find its way into
food. Not all of these pathways are equally significant. The main
objective of this appendix is to present a methodology that can be
used to identify the most significant pathways based on chemical
properties, use characteristics, and chemical release characteristics.
A.2 PATHWAYS OF FOOD CONTAMINATION
Figure 4 showed the potential contamination pathways of a
pollutant to food. Besides the pathways shown, pathways due to
accidents or misuse should also be considered. There are two types of
pathways by which food may become contaminated, direct and indirect
pathways. Indirect pathways involve release of a pollutant to another
medium, while direct pathways involve the direct addition of the
chemical to food, for example, food additives or pesticides. Table 14
shows the food chain access points during food generation stages
(pre-harvest) by food groups. This table shows the points and the
nature of media contact with food (indirect pathways) and any
additions that may occur (direct pathways). Table 15 shows the food
chain access points in the food processing and consumption stages
(post-harvest). In this table, the points of contact are described by
step, rather than by food groups, since the type of contact does not
depend as much on the food group as on the step. Table 15 also
eliminates soil/sediment as a potential pathway, and contact surfaces
are added for the post-harvest stages. Table 16 expands on the nature
of these access points for food in the post-harvest stages. Table 17
relates the food chain access points to food contamination pathways;
these pathways are used as a starting point for Appendix B,
Quantitative Methods. Tables 14, 15, 16 and 17 show where
contaminants can enter food, by food group or by processing step.
While this information is useful in understanding the scope of the
problem, it does not provide any insight into which pathways are
potentially important for a given chemical. The important pathways
can be identified only by relating characteristics of the chemical and
its uses to pathways.
A.3 SIGNIFICANT PATHWAYS IDENTIFICATION METHODOLOGY
Figure 5 shows the Pathways Identification Methodology, which can
be used to identify the most significant pathways for the chemical of
concern. For a particular chemical, the first step is to identify all
the situations of release from the production and use characteristics
of the chemical. The production of the chemical as a degradation
product or in treatment processes should also be considered. The
first result of this is the identification of all the situations of
direct contact, i.e., direct addition of the chemical to food at some
51
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TABLE 16 . POST HARVEST FOOD CHAIN ACCESS POINTS
HARVES T/SLAUGHTER
Air
Water
STORAGE
Air
Other
During the harvest process, air is blown onto fruits
and vegetables to separate them; they are also sepa-
rated by gravimetric techniques. Meat and poultry
are exposed to the ambient air during transporta-
tion to slaughter (usually in trucks) and in the area
in which they are slaughtered. Additionally, hogs are
exposed to carbon dioxide to desensitize them to pain
before slaughter.
Some field crops are harvested with the aid of water
for washing (e.g., cranberries). There exists, in
this situation, a potential for both soil and water
contamination. Animal carcasses which will be pro-
cessed for meat consumption are washed once they
have been eviscerated. Hogs, however, are "scalded"
following bleeding, by being immersed in water at
140° F.
Potential exists for exposure to contaminated air
during storage of harvested fruits and vegetables.
Animal carcasses, once they have been eviscerated,
are refrigerated for up to 48 hours.
There is some likelihood that crops will come into
contact with surfaces of treated wood used in storage
areas, as well as pesticides and sanitation compounds
sprayed in these areas.
RAW MATERIAL CONVERSION
Air
Water
Other
Field crops are potentially exposed to air contaminants
in the area in which they are processed; this is also
true of meat and dairy products which are aged or cured.
Exposure to contaminated water during raw material
conversion of crops, meat, and dairy products is
a possibility duringf00d processing.
Other sources of exposure during post-harvest processing
are cutting, and the use of waxes and colorings and
potentially contaminated additives in food processing.
54
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TABLE 16 POST-HARVEST FOOD CHAIN ACCESS "POINTS
(CONTINUED)
FORMULATION TECHNIQUES
Air The use of compressed air in food preparation (e.g.,
steaming and blanching) is a potential pathway for
contamination of foods, both meat and vegetable.
Water Contaminated water used during food formulation/
preparation is a potential source of contamination.
Additionally, surfactants, lubricants, and residual
sanitizers can result in contamination during food
processing.
Packaging The air, water, and plastics used in food packages
are also potential sources of food contamination.
PRESERVATION TECHNIQUES
Water Potential pathways of contamination in this area
are tainted cooking media, and contact with surfaces
which have been washed with contaminated water.
A.ir Liquid carbon dioxide, liquid nitrogen^and air used
in the dehydration process of crop and meat products
represent potential sources of contamination.
55
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CHEMICAL
Use
Characteristics
I
1. Identify Situations of Release
\
Media of Release, Locations
Magnitude, Area Impacted
X
2. Identify Situations
of Direct Contact or
Addition
Direct Pathways
3. Identify Relevant
Pathways for
Indirect Contamination
Routes
Concentration in Mediy.
Physical/Chemical-
Properties
Amount of Food Potentially
Contaminated
A. Identify Most Significant Pathways
FIGURE 5 PATHWAYS IDENTIFICATION METHODOLOGY
59
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stage of food production and processing. The second result of the
first step involves collecting information regarding the media of
release, locations, magnitude of release, and the area impacted. This
information allows the identification, using Table 17, of the relevant
pathways for indirect contamination routes. From the relevant direct
and indirect pathways, the most significant pathways may then be
identified using such considerations as the concentration in the
media, the physical/chemical properties, and the amount of food
potentially contaminated. With this small number of pathways,
quantitative methods as described in Appendix B may be used, if
necessary, to estimate concentrations found in food from these
pathways.
A.3.1 Situations of Release (Step 1)
The intent of Step 1 of the methodology is to identify situations
in which the chemical is released to or formed in the environment.
The production and use characteristics of the chemical serve as input
to this step. The expected outcome of this step is as much detail as
possible on the locations and media of releases, magnitude of the
releases, and the expected area impacted. A companion volume to this
report contains a discussion of sources and releases (Freed et al.
1985).
The extent to which the releases of the compounds can be
elaborated will greatly affect the user's ability to limit the scope
of the food methodology. If situations of release can be identified,
the consideration of pathways can be limited and more definitive.
A.3.2 Situations of Direct Contact (Step 2)
Chemicals may come into direct contact with foods either as
additives during formulation of the food product or as processing
aids, pesticides, cleaning compounds, sanitizers or other such
products used in the production, processing, packaging and
distribution of food. All of the above food contact situations are
regulated by federal, state, and local laws, rules, and regulations.
Each new situation of contact is evaluated on its merit, based first
on the functionality of the additive and then on the safety of the
use .
The two basic laws regulating food production and processing in
the U.S. are the Federal Meat Inspection Act and the Federal Food,
Drug, and Cosmetic Act. The latter of these two Acts (laws) provides
the basic definitions and regulations regarding the addition of
substances to foods. Section 201(s) defines the term "food additive,"
section 409 addresses the issues of food additive approvals, sections
401, 402, and 403 define the food standards and classes of compliance
deviations, and sections 301 to 307 describe the remedies for
violations. Additionally, the responsibility for the regulation of
compounds such as pesticides and sanitizers is administered by EPA
60
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under FIFRA in cooperation with USDA and FDA. Tables 14 to 16 outline
many of these use situations.
Lists of the currently regulated food additives are contained in
a myriad of titles of the Code of Federal Regulations. Also, some
proprietary listing services such as the Food Chemical News Guide and
Commerce Clearing House keep abreast of the currently approved and
pending (petitioned) uses. Food grade chemicals are generally
produced, or segregated, based on purity specifications more stringent
than their industrial counterparts. "Food Grade, "U.S.P.", "P.C.C."
or other standards generally describe them; their industrial
counterparts, however, may contain trace impurities which are quite
toxic and underline the seriousness of a possible mislabeling
occurrence. Many compounds are also only suitable at specific use
levels. At lower or higher levels than the approved usage, or if not
used strictly in accordance with approved procedures, they may not
function properly or may become very toxic. Thus, the potential for
misuse is also a serious concern.
A.3.3 Identification of Relevant Contamination Pathways (Step 3)
Contamination pathways are defined as pathways of pollutant
migration from the source to food, including the food chain access
point(s). Contamination pathways, as defined previously, are of two
basic types: indirect and direct. A chemical has the potential for
contaminating food by one, both, or neither of these types of
pathways. Direct pathways have been described in Step 2.
For indirect pathways, the major goal is to determine whether the
chemical is or could be found in any media contacting food. Table 17
showed the relationship of release characteristics to food chain
access points and the pathways of potential contamination. The output
of Step 1 is a description of release characteristics of the chemical.
This description corresponds to the left column of Table 17. The
second column lists all the specific food access points of contact.
For each particular release situation, there is a sub-set of possible
food access points. The implication of this column is that a fate
analysis has been conducted and the distribution of the chemical from
the source has been determined. A fate analysis in this context is an
assessment of the chemical distribution from the source to various
media, and chemical transformations occurring during the distribution.
Such an analysis can be conducted using a wide variety of techniques
and levels of detail. In general, this distribution can be evaluated
either through modeling or through the collection of monitoring data.
Methods for conducting such a fate analysis are described in Freed et
al. (1985). Once the type of release and the distribution of the
chemical has been determined, the points of contact with food items
can be evaluated.
For example, if releases to air from production of a particular
chemical have been confirmed, a fate analysis will show the extent and
61
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level of contamination. The second column in Table 17 can then be
used to direct the identification of points of food chain access based
primarily on geographical considerations, especially for pathways
including food generation areas. If contact is possible, that is,
certain foods or food types are generated or processed in the area,
the third column indicates the contamination pathways that are
possible. The ability to locate areas of release, and thus
concentrations of a pollutant in various media, will depend to some
extent on the uses. If the use is limited to the production site
(e.g., it is used as an intermediate), the locations are likely to be
known. If, on the other hand, use is widely distributed, such as with
a paint additive, locations are likely to be numerous and
geographically disperse. Pathways can sometimes be eliminated on the
basis of the nature of the use, i.e., a chemical used as an industrial
binder for magnetic tape. In such a case, environmental releases
during use are not likely to be in the vicinity of food generation
areas, as the chemical would be used indoors, primarily in
urban/suburban areas. However, there is some potential for releases
to indoor air, and these releases may occur in food processing areas.
Releases of this compound from production, could also be in the
vicinity of food generation areas. Therefore, the consideration of
contamination during food generation stages is limited to the
consideration of a few sites. For contamination during food
processing, it must first be determined in the fate analysis whether
such a compound would be released to the air during use. Then, the
potential for this chemical occurring in food storage, processing, or
preparation areas can be evaluated.
The identification of relevant contamination pathways can be
conducted on several different levels, depending on the specificity of
the release characteristics. In this step there is no attempt to
prioritize pathways, but simply to eliminate the ones which are
clearly impossible based upon expected locations of the chemical in
the environment and the locations of food generation, storage,
processing, and preparation areas.
The releases to indoor air and to water in storage, distribution,
and use (in-plant releases to water used in processing or preparation)
are treated somewhat differently than those releases to the ambient
environment. This type of release is primarily dependent on the
intended use of the compound. The question then is, do releases from
such a use have the potential for contacting food in storage,
processing, and preparation areas. For example, solvent used in
machine degreasing could potentially be used for food processing
machinery and may result in releases to air in food storage,
processing or preparation areas. Such uses would generally be
regulated by FDA, although this may not always be the case.
Table 18 shows chemical applications which may result in releases
to indoor air. SRI (1980) contains numerous chemical functions which
62
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TABLE 18
CHEMICAL APPLICATIONS WHICH MAY RESULT IN
RELEASES TO INDOOR AIR
Construction
Textiles and Textile Finishing
Apparel and Other Fabricated Textile Products
Lumber and Wood Products
Furniture and Fixtures
Paper and Allied Products
Rubber and Plastic Products
Stone, Clay, Glass, and Concrete Products
Machinery*
Electrical and Electronic Equipment*
*These applications are not likely to be found in food preparation
areas, but could be found in food processing areas.
Source: Taken from SRI (1980)
63
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may be used in these applications, but they are too numerous to list
here.
The use of the pathway identification approach depends on
knowledge of the location of food generation areas and food storage,
processing, and preparation areas. While the location of releases may
not be known, knowledge of the distribution of food generation areas
is useful in determining the probability of chemical contact with
food. The location of food generation areas is largely discussed in
the Census of Agriculture (USDOC 1981). This multi-volume report
compiles extensive statistics on the number of livestock or acres of
crop production by county for the entire U.S. Figure 6 shows an
example of a graphic summary of some of these data. While cattle and
calves and dairy cows, for example, are widely distributed, growing
areas for some crops are very limited. The food grown in a given area
can be determined roughly by using the maps in the graphic summary, or
more specifically by using the county summaries for each state.
Livestock and poultry are reported as number per county. Crops are
reported by acres per county in the state summaries. More recently,
these data have been converted to a more usable form for risk
assessment. Two data bases exist that contain agricultural production
on a county or lat/long basis. The livestock data are very useful in
this data base, but the crop data are combined into groups which may
or may not be useful for a particular assessment. (For access
information see Section 3.2.3, Baes et al. 1985).
The Census of Agriculture (USDOC 1981) gives information on the
location and production of fish farms, but not of commercial or sport
fishing areas. The National Marine Fisheries Service (NMFS) of NOAA
publishes various fishery statistics. NMFS (1980a) contains the most
recent compilation of commercial fisheries statistics (1976). In
addition, however, they publish annually "Fisheries of the United
States" (NMFS 1983). This volume summarizes U.S. commercial landings
by state and at about 120 major U.S. ports in pounds and dollars as
shown in Tables 19 and 20. Marine recreational fishing is also
summarized by the same agency in the "Marine Recreational Fishery
Statistics" (NMFS 1980b). These statistics also summarize fish caught
by state and various other characteristics.
Fresh-water recreational fishing statistics are not as well
documented. The available information is summarized independently by
each state and would not be practically accessible for a national
analysis.
These data are not always in ideal form for use in this
methodology. At this point in the methodology, however, it is
important only to identify whether fish/shellfish, for example, are in
the vicinity of a source at some point in their life-cycle. The
compilations referenced above will provide data adequate for this
purpose, at least for commercially important species.
64
-------
-
H
u
O
Pi
p
O
O
0)
O
S-i
3
c
O
I<
H
g
M
pi
H
en
O
O
w
O
w
fj
O
><;
w
w
OS
00 H
iH
v^
O
C/5
65
-------
TABLE 19
U.S. COMMERCIAL LANDINGS
n. 'CI/L LA NT'TV^, nv STATED.
3 Late
108'
dollnrs
record landings
iear
Tr.oc'^nd Thc'iggnd T>-'".. 3a" J
pounds dollars pounds
AJaba-ia 23,677 44,148 ?7,3^2 47,3'JS '973 39,749
Alaska 975,i45 6j9,797 870,035 575,569 1930 1,053,396
Arkansas 19,060 6,305 13,844 7,390 - (2)
California 7/5,171 273,196 695,423 2'-1,188 1936 1,750, 183
Connecticut ',272 2,128 5,526 9,6!o 1930 83,012
Delaware 3,033 1,662 3,677 2,267 1953 367,500
Florida 215,281 172,72J 195,060 165,003 1933 241, UU3
Georgia 18,569 13,158 ?0,075 22,344 ;:,:7 47,607
Hawaii 13,3°* 18,333 14,245 14,4,:6 1954 20,610
Idaho 496 28 496 28 - (2)
Illinois 14,453 994 5,925 1,410 - (2)
Indiana 185 129 112 53 - (2)
Iowa 3,741 Q45 4,326 1,266 - (2)
Kansas 170 11 219 '5 - (2)
Louisiana 1,158,597 193,549 1,718,663 23T.S83 i ^: 1,713,668
Maine 238,107 103,945 217,379 100,900 1950 356,266
Maryland '15,115 56,640 100,478 51,433 '5)0 141,607
Massachusetts 369,640 196,654 343,955 20'i,223 19»S 649,696
Mlonigan '2,523 5,S47 n,S95 S.H8 1930 35,580
Minnesota 8,236 1,960 11,146 2,831 - r2)
Mississippi 264,891 30,159 383,767 39,377 19<"1 400,576
Missouri 970 231 1,251 310 - (2)
Neoraska 111 29 143 3G - (2)
New Hampshire 7,690 4, 152 7,586 3,776 - (2^
Nev Jersey 168,396 4^,283 90,190 45,007 1956 540,C60
New f"-< 36,522 45,555 35,773 45.392 'oCC 3?5,COO
North Carolina .... 432,006 57,520 307,968 63,82'i 'Q?1 432,C06
North Dakota 727 117 9j3 157 - (2)
Ohio 7.577 2.193 5,957 2,'--4 -,026 3L033
Oregon 134,626 52.461 127,625 57,"93 '~-~S '34.557
Pennsylvania 3''3 1?9 108 79 - (-')
Hhode Island 80,288 48,761 112,893 55,40' 1839 US,056
South Carolina .... 16,232 14,151 19,902 23,73' 1965 26.611
South Dakota 2,?59 357 2,914 -;73 - (2)
Texas 113,103 174,787 89,2'? 1C5,19~ i?50 22~,(r^
Virginia 487,919 69,124 690,6-77 63,763 lQq- f}0,677
Washington 184,593 95,995 170,160 90,07' 1941 197,253
West Virginia 31 16 40 21 - f)
Wisconsin 38,231 c,502 3' , 356 3,129 - (2)
Other 4,265 3,9-1 Hi,533 ^.'06 - (2) ..
Total 5.977.069 2,387.739 6.367,310 P.3fq,°'73 '980 6,^2.35''
(1) Landings are reported in round (liv-?) weight for all itecs except univalve and tivalv«
mollusks, such as clams, oysters, and scallops, which are reported in woight of seats (excluding
the shell).
(2) Not determined.
Note:Data are preliminary. Data do not Include landings by U.S.-fl<^ vessels at Puerto Rico
and other ports outside the ^0 Jtntes, or .-.itches by U.S.-flag ver-Tels unloaded onto foreign
vesaels within the U.S. FCr (Joint venture). Therefor", they will not a^ree with "U.S.
CoEUEerc^al Landings" table on pags 8. D?ta do not include aquaculture products, except oysters
and clams.
Source: NMFS (1983)
66
-------
TABLE 20
U.S. COMMERCIAL LANDINGS
CO.'. EPICAL FlSMERI LANDINGS AND V LL'F AT MAJOR U S PORTS. 1979 "2
- ----- ,j
Quantity
Ca.-r-on La
Port
Los Antje'es Ar-3, Ca if (1)
Pas^gouls Mosi Point, Miss
Fi'-ye Venice, La
DulJC-Chauvm, La ...
'97J
593 1
373 2
2833
278 J
2463
1930
M.I., on t
470 3
35J 1
2J1 9
2754
2553
Gloicsster, Ms«. . . 1tiO 2 2'00
BeTjfort-rVcreheKl City. N C.
San Diego, d
hf .
Kodiak, Aia
171 5
199 1
2074
99.5
5-4 9
560
429
136i
364
3^8
51 5
(2i
1C. 0
12)
323
270
(2)
34 5
589
238
39 5
34 .1
400
223
230
(2)
21 6
22 1
199
12)
(2)
15 4
198
(2!
11 1
12)
(21
(2)
11 1
86
100
15 4
(2)
121
135
10 1
11 S
95
159
S2
(2!
9 1
12)
12'
ia-ii
447 6
3"3 6
22J5
221 5
201 9
1 60 1
1770
149 ;
193 2
76 2
399
41 7
41 7
730
467
44 ft
42 7
498
250
35 7
??9
-" 5
48 1
300
406
29 1
390
23 *
270
234
240
IS 1
239
<4 4
25 1
15 7
15 7
18 5
17 1
170
14 7
9 5
14 1
Cl
139
11 0
3 1
ISO
10 8
12)
150
14 9
120
7 (j
90
62
8 i
7 'j
70
7 1
Iu32
7' '. 7
33: 3
331 C
2G7 3
263 6
144 3
1 16 4
1068
1T33
82 3
66 6
5/ 2
55 7
470
46 7
450
44 9
44 5
J4 4
435
3o8 '
370
364 :
160
334
J32
325 |
T- ->
26 n
21 1
IS 9
190
IPO :
173
1? 7
15 3
14 2
140
125
11 9
!1 9 '
110 j
106 !
105
104
10 1
100
J9 '
9 5 i
h
M
92
90 !
JO |
7 -> I
7 i !
7 1 :
"T '
65 i
50 ,|
5 6 '
Pon
L' s A" 't-s Ar"? Calif (1)
Vjd.a' , Aia-.na .
r;t-,v C~dtnrd. Mass .
1 San D'fjo, Ci.'f
rVowo-.wile Port lsaU.1, Tex.
Oulac C'lauvin, La
1 'i^uf-i Hartcr LHalaska, Alaska .
G'oucester. Miss ...
j Ar'nsas Pasi Rockport. Tsx
i Canneion, La. ...
I
Enipiro-Ventce, La
B.iyou La Batre, Ala
Frteport. Tex
Ld':ltf Oai.uaria La
Golden fv'e.idow'Leev.He, La ....
Be^ufortMorehead City, N.C.
Point Jjd'th, R 1
Petersburg, Aljska
j Key W»st. FIs . .
PaiCjyoulj Voss Point V'ss
San Francisco Area Ca:>f .
Ca>' May Wilri«ood. U J .
i Delcarnbr*1, La . .
Hampton Hoads Area, Va 13) .
R"Mmijham, VVjsn . . ...
Astopj, Of eg .
Seattle, '.Vosh . . .
Akutjn, Alaska .... .
Galves;on, Tex. . . . , .
Newport. Oreg
T-XJS B.iy Charleston. Oreg
Portland. '.>i,e .
\Vjnchese Stumpy
Po",t, N C
Cap* Canaveral, Fla
Eureka. Calif . . .
Bon Secour Gulf Shores, A'a. . .
Fort Myirs Fla
Bost'in, Mass
Rockland. Mime . . . .
Apalarhicola, Fla . ...
Port Arthur Sob'ie, Tex
Or°i,i Cit/. Md
Crescent City, Calif
Delacroix Y-clcskcy, l.a . .
Monterey, Cjlif
PManos. Tex . ...
Atlantic City, N J .
\Ustport. VVjsh
*.n?cortes Wisn
Djnc.i Bellvillo Ga . .
Oriental Vandernere, N.C. . .
Fort Oragg, Cahf . ...
Port Lavjcca. Tex ...
Blame V;a>h . . . .
C.rond Isle, La ...
S~nta Barbjrj, Cilif.
3"cokin5s. Oreg .
Pumt P'cjs-r-t. N J
C'»ncjt>!jg.e V3 .
?c>rt Hu'-ie^'v OxnorJ sn'j
Ve turo CdMf
1979
893
734
57 '
P2 7
£.T 0
41 5
32 7
29 7
40.0
343
288
349
250
166
225
22.7
11.0
237
259
18 1
(2)
32 2
'4.8
31.1
163
13 2
65
28.2
(2/
12.6
8 2
10 1
130
c;
14 J
160
17 3
10 7
(2)
10 1
12)
3 2
(2)
(2)
(21
(21
12)
10S
6.1
8 7
66
(21
(2)
12)
(2)
(21
(2)
68
65
(2)
V
j
- ,/Vlic
121 9
84 5
71 3
1106
122
COO
91 3
34 7
402
3J3
31 0
237
1a9
148
12 2
225
11 5
170
183
18 j
C,
26 Q
13 3
27 5
15 2
13 1
CO
428
(2)
13 7
135
13 6
130
(2!
11 0
7 7
10 9
123
84
11 3
(2!
99
(2)
(2)
12)
(2 1
12;
11 5
S 4
" 5
9.1
(2)
(2)
40
i2!
(21
33
5 0
80
(2)
ilue
1981
dolio-s-
110 5
'1329
77 P
330
434
51 5
576
40 1
41 0
2rl9
305
31 4
268
208
199
17 2
132
220
270
1c 8
180
ros
IK 8
228
120
150
150
29 2
13 3
14 0
13 2
17 0
12 7
159
135
11 6
13 0
124
134
12 3
8 2
10 5
8 2
1 i)
10 4
(Ti
7 9
100
7 2
4 6
65
03
(2)
36
7 8
59
33
4 7
5 1
4 6
1982
92 9
U0 1
34 6
537
520
51 7
47 d
44 5
41 0
40 4
364
338
260
21 9
21 5
200
199
195
190
!85
16 3
13 1
17 6
17 5
16 3
15 7
156
156
ISO
14 5
14 3
13 7
13 0
128
124
12 4
1 1 9
11 8
11 1
:02
;oo
39
9 e
9 8
3 3
90
88
85
30
7 9
7 7
64
60
5 7
5 7
4 9
46
4 5
39
33
U1 P-eviously cd'>d San PeJro Ci> .f ;2) Nit i.ail-^'e (Jl Prcvru>'v gii. il M .motcn Norfoi1 . Va
'«ecoi>' Record n^jnuty Js 848 J m.lhon ib Un>l«M n Sjn P.'du Cj i . n ;,-losure of I'ri.ai* >-nn-'pr,se, the tclluwr; ports font rot included Fernf-'iinj Beach, f\i
lnt«rco»stsi City am. Mor-jjn C.ty. La.. Chathjr^ J S^rid*ich M, ,s 3.'i> f.'.ss . Fort Mon"-,ooth-3^iford, N J.. Southport CaUuash. N C , Newpo't. R I..
no Reedvnle. Va
Source: NMFS (1983)
67
-------
The potential for contact with water supplies used as drinking
water for livestock and poultry and as irrigation water for crops can
be identified to some extent by using a data base kept by the Office
of Drinking Water, the Federal Reporting Data System--Public Water
Systems. This data base documents public water supplies by county or
city, giving source information, the population served, and the type
of use. For access information, see Section 3.2.3.
The location of food storage and processing plants can be used to
determine if products in storage or processing may become
contaminated. The Chilton Company (1981) publishes annually a
"Directory of U.S. Food and Beverage Plants." This compilation lists
all food and beverage plants within a given county, along with the
products produced and the peak employment. While this source provides
the locations and products, it does not give volumes of production.
Trinet, Inc. publishes share-of-market data (in percent sales) for
each plant within a given SIC category. This information would
provide an indication of the magnitude of production at a given
facility which could later be used in estimating exposure. For access
information see Section 3.2.3. The Census of Manufacturers (USDOC
1980) can provide the total volume of shipments for the U.S. within a
SIC code. Thus, if desired, the volume of food shipped from a
particular plant can be estimated.
Food preparation areas can include homes, restaurants, etc. so
that almost any use that may result in releases to air or water has
the potential for food contamination via this pathway.
A.3.4 Identification of Most Significant Contamination Pathways
(Step 4)
The relevant contamination pathways have been identified in Steps
2 and 3. This merely implies that given the nature of the chemical
and its particular uses and releases, contact with food via a
particular pathway may occur. While some pathways have been
eliminated in this process, it is obvious that some of the remaining
pathways are more significant than others. This section will address
methods of assessing the significance of the relevant pathways using
two criteria, the physical/chemical properties of the compound, and
the amount of food potentially contaminated. Figure 7 summarizes the
three factors which must be considered in this step.
1. The media contacting food can be prioritized by concentration of
the chemical in the media (either quantitatively or
qualitatively) for indirect pathways.
2. The relevant pathways can be prioritized using the
physical/chemical properties of the compound and the pathway
characteristics. The properties, as discussed below, are
intended to provide a surrogate measure of concentrations in
food.
68
-------
FIGURE 7
PRIORITIZATION OF RELEVANT CONTAMINATION PATHWAYS
Prioritize media based
upon estimated
concentrations for
various situations
or
If concentration unknown
prioritize media based
upon estimated magnitude
of use and release
or
Identify pathways where
chemical properties
suggest concentration
in food highest
Identify pathways
where largest amount
of food contacted
69
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3. At the same time, the amount of food potentially contaminated
must be considered.
The estimation of concentrations in environmental media is
considered in Freed et al. (1985). The consideration of use and
release characteristics in lieu of estimated concentrations is
addressed below, as are the remaining two factors.
A.3.4.1 Prioritization of Relevant Pathways Based Upon Chemical
Properties and Pathway Characteristics
This section presents a simple scheme that can be used to
prioritize various food contamination pathways based upon the
concentration of the toxicant expected in the contaminated food. The
scheme requires consideration of the following:
(1) The amount of the chemical released;
(2) The chemical's persistence in the compartment(s) traversed;
(3) The chemical's rate of movement along a pathway;
(4) The chemical's mobility from the environmental compartment
to food; and
(5) The number of steps in the pathway.
A simple scoring system is used since more sophisticated
approaches (e.g., modeling) are not warranted due to their complexity
and the unavailability of input data. The implementation of this
scheme will require some subjective judgements. If this is done in a
reasonable manner, the scheme should allow the user to identify
pathways that are clearly more important than others, Small
differences in scores for different pathways are not significant.
Some of the elements to be considered in this scheme (items 1-5
in the list above) may have already been considered in the initial
selection of pathways. This may need to be taken into account in the
implementation of this scheme. The next subsection of this report
(A.3.4.2) will provide the prioritization scheme that will be based
upon an assessment of the amount of food potentially contaminated.
Table 21 provides a summary list of the elements of the
prioritization scheme. Each of the five items to be considered is
listed along with a series of scores (1-3 or 0-3) to be assigned based
upon the user's assessment of the item. It is suggested that when two
or more pathways are to be scored (and the results compared) , they
should be scored by the same person. If no information is available
on a particular item, or if it does not appear pertinent, then a
mid-level score of 2 may be assigned.
After considering each of the five items, a summary score is
obtained for each pathway by simple addition of the individual scores.
These summary scores may then be used to identify high priority
pathways. The maximum possible score is 15; the lowest, 4. Any
chemical with a score of 3 on item 4 (i.e., there is some form of
70
-------
TABLE 21 PRIORITIZATION SCHEME FOR RELEVANT PATHWAYS'
Amount Released to Compartment
Amount
3
Large ( > 10 kg/vr)
Moderate (10 - 10 kg/yr)
Small ( < 10 kg/yr)
Score
3
2
1
2. Persistence in Compartment
Mean Lifetime
Long ( >1 year)
Moderate (1 week - 1 yr)
Short ( < 1 week)
Score
3
2
1
3. Rate of Movement Along Pathway
Rate
Fast
Moderate
Slow
Score
3
2
1
4. Mobility from Compartment to Food
Mobility (or Partition Coefficient)
High
Moderate
Low
Score
3
2
1
5.
Number of Steps in Pathway
No. Steps
Direct Contamination of Food Storage
processing or preparation area
1 Step
2 Steps
3 or more Steps
Score
3
2
1
0
For guidance in scoring, see text
71
-------
direct food contamination possible) should be given added priority in
the final evaluation of pathways.
Each of the five criteria for scoring are briefly discussed
below.
1) Amount Released to the Initial Compartment - To a first
approximation, it can be assumed that the eventual concentration of
the pollutant in food will be directly proportional to the amount
released to a given compartment. For purposes of scoring, however, it
may be easier to consider the logarithmic scale implied in Table 21
(10 kg/yr; 10 - 10 kg/yr; and 10 kg/yr) . As long as different
pathways are scored by the same criteria, the exact nature (linear vs
logarithmic) should not be crucial.
2) Persistence in Compartment - The user should also consider
the potential for degradation, by all reasonable mechanisms, within
each compartment of each pathway. Degradation mechanisms may include,
for example, biodegradation, hydrolysis, oxidation, and photolysis.
While it is unlikely that appropriate rate constants for each of these
reaction types will be available, it should be possible to assign a
score to a chemical/compartment scenario based upon analogy with other
known systems. If the persistence is deemed to be so significant
that the mean lifetime of the chemical in the compartment (excluding
considerations of bulk transport) would be longer than one year, a
score of 3 is given. A mean life of 1 week - 1 year is scored 2; a
mean life of less than 1 week is scored 1. A score of 0 might be
appropriate for some chemicals with a mean life less than 1 day; such
chemicals, unless involved in some direct food contamination incident,
are unlikely to pose a problem.
3) Rate of Movement Along Pathway - Within a compartment or
pathway, chemicals may have a wide range of mobilities due to both
chemical and environmental properties. Just which properties will
predominate will depend on the specifics of the food contamination
pathway. In some cases, for example, bulk transport (with flowing
water, air or sediment) may cause the chemical to be quite mobile and,
thus, capable of reaching and contaminating the food item. On the
other hand, transport out of the compartment may decrease mobility
along the food contamination pathway. For example, volatilization
from surface soils could reduce availability for plant uptake. In
some cases, the mobility (or lack of it) will be tied primarily to
chemical properties. For example, a chemical with a very high soil
adsorption coefficient will not be very mobile in the unsaturated soil
zone. Scoring for mobility in soil-groundwater systems using K
might be as follows: A compound with K less than 100 might be
scored as 3, 100-10,000 as a 2, and greateS: than 10,000 as a 1. In
scoring, the food contamination pathway must be considered for the
properties and/or bulk transport mechanisms that are relevant and how
they may affect the chemical's movement along the pathway. Where a
pathway actually consists of two or more distinct subpathways (which
72
-------
must be traversed in series) , the mobility in each
subpathway/compartment should be assessed and a score (1-3) assigned
based upon the slowest pathway.
4) Mobility from Compartment to Food - The ease with which the
chemical can actually be taken up by plants and animals (food sources)
is considered as a separate scoring item. No clear rules, based on
species type and chemical properties, can be given that will allow a
prediction of mobility in all cases. As noted in Section B.4 of this
report, however, ease of uptake in plants is often strongly correlated
with water solubility, even for cases where - as in foliar uptake -
the uptake is not directly from water. The correlation of uptake in
aquatic and terrestrial organisms with the octanol-water partition
coefficient is described in Sections B.2.1 and B.3. Other factors
which may be considered in assigning a score for this criterion are
the probable differences in ease and rate of uptake via different
routes, e.g. ingestion, inhalation, gill transport, skin absorption
for animals, and root, stem, and foliar uptake by plants. As an
example, scoring for fish bioaccumulation might be as follows: A
compound with a BCF of less than 100 might be scored a 1, 100-1000 as
a 2, and greater than 1000 as a 3.
5) Number of Pathway Steps - If direct contamination of food in
food storage, food processing and/or food preparation areas is
involved, a score of 3 is assigned. Lower scores (cf. Table 21) are
assigned for pathways that are less direct and involve one, two or
three (or more) steps. This criterion may involve some redundancy
with the first four criteria. If so, the scoring here may be
eliminated. However, the general concept here is that the more
complex the overall pollutant transport pathway is, the more dilution
and/or degradation there will be prior to possible food contamination.
It appears reasonable to assign a very low priority to any pathway
involving three or more subpathways (in series) unless the scores on
the other criteria are all high.
The scorings suggested above are somewhat arbitary and may need
to be revised based upon experience with the prioritization scheme.
The important factors in scoring the mobility from compartment to food
will also become evident with further use of the methodology.
A.3.2 Prioritization of Relevant Pathways Based Upon the Amount of
Food Potentially Contaminated
The methodology described above, although somewhat subjective,
allows the identification of pathways of contamination that are
relevant for a given chemical and its uses and potential releases. In
some situations the location of releases, the resultant
concentrations, and the area of impact will be quantified. In these
situations it would be possible to examine the amount of food
potentially contaminated by various pathways. In many situations,
however, the location will not be known specifically, but may be known
73
-------
generically. For example, a compound used as an adhesive may be
released during production, the locations of which would probably be
known. If this chemical were used in the manufacture of tires, the
locations of releases from use would probably not be specifically
known, and releases from tires themselves would be widely dispersed.
In this example, concentrations would be expected to be greatest in
both water and air around the production facilities. Use in tire
manufacture would be expected to be more widely dispersed, resulting
in lower environmental concentrations. The area impacted would be
greater, however. Releases from tires would be widely dispersed and
could be expected to result in relatively low concentrations in any
medium and thus can probably be discounted as an important starting
point for contamination pathways.
Where production locations are known, the examination of data
sources can allow one to document the food items grown in the area,
the water supplies used for drinking water for livestock or
irrigation, and the food processing facilities located in the area.
Many of these data sources are indexed by county. Two examples of
such information are shown in Table 22. This table shows that a wide
variety of products are grown even in areas that are not considered
agricultural. If a production facility were to be located in
Montgomery Co., OH, emissions to air and water would be considered for
pathways resulting in contamination of meat and field crops. In
comparison, meat and orchard fruit would be important considerations
in Worcester Co., MA. The identification of food processing plants in
these two counties is shown in Table 23. These data suggest that a
variety of food products can be produced in a given county, although
bread and dairy products appear to be common, at least in these two
counties. Not surprisingly, corn syrup and other corn by-products are
produced in Montgomery Co., OH. Also of interest is that soft drink
bottling plants are found in both counties. Therefore, releases which
may contaminate water supplies for these facilities would be of
particular interest.
At this point in the methodology it is difficult to provide
guidelines for prioritizing pathways by the amount of food potentially
contaminated for several reasons:
Some situations of release or contact are geographically defined,
but many are not.
For those situations that are geographically defined, Tables 22
and 23 show that collected information is in a wide variety of
forms, and is not strictly comparable. To prepare such a table
so that the units are consistent, for example, pounds of edible
product present, would be extremely time-consuming and may not
always be warranted.
For those situations that are not easily geographically defined,
for example, the use of an adhesive in tire manufacture,
74
-------
Food generated
Meat
cattle and calves
hogs and pigs
sheep and lambs
poultry
laying
broilers
TABLE 22
FOOD GENERATION IN TWO COUNTIES
MONTGOMERY CO., OH
19,381 head
19,763 head
3,781 head
41,499
351
WORCESTER CO., MA
23,918 head
13,368 head
1,317 head
589,116
220
Fish/Shellfish
commercial
sport
probably none
limited
probably none
limited
'lants
Field Crops
field corn (total)
field corn for grain
sorghum
wheat for grain
soybeans for beans
36,282 acres
34,471 acres (2,819,796
bushels harvested)
97 acres
14,091 acres (534,065
bushels harvested)
36,562 acres (1,209,695
bushels harvested)
hay (excluding sorghum hay) 8,617 acres (17,976 tons dry)
Vegetables
irish potatoes
5 acres (287 cwt harvested)
vegetables, sweet corn, melons 522 acres
berries 84 acres
land in orchards 499 acres
7,802 acres
453 acres (35,380
bushels harvested)
43 acres
0
0
29,234 acres
(59,204 tons dry)
53 acres (13,712
cwt harvested)
1,316 acres
81 acres
3,838 acres
Source: USDOC (1981)
75
-------
TABLE 23
FOOD AND BEVERAGE PLANTS IN TWO COUNTIES
PLANT
Ohio - Montgomery Co.
Bluebird Baking Co., Dayton
Borden, Inc., Dayton
Car-Mi Inc., Dayton
Cargill Inc., Dayton
Coca-Cola Bottling Co., Dayton
Esther-Price-Candies, Inc., Dayton
ITT Continental Baking Co., -
Wonder Bread Div., Dayton
Liberal Markets Inc., Concord
Provision Co. Div., Dayton
Mikesell Daniel W. Inc. -
Mike Sells Potato Chip Co., Dayton
Milking Marketing Inc., Dayton
Monsanto Co., Miamiburg
National Industries Inc. -
Hawthron Mellody Inc., Dayton
Pepsico Inc. - Holiday General Corp.,
Dayton
Siegler Bottling Co., Inc., Dayton
Superior Beef Inc., Dayton
United Belton, Inc., Dayton
MA - Worcester Co.
Acme Boneless Beef Co., Inc.
Wilkinsonville
American Potato Co., Roger Bros. Co. -
Lunenburg
Automatic Rolls of New England,
Auburn
Deary Bros. Inc., Webster
Family Bakery Co., Inc., Worcester
Hillcrest Dairy, Inc., Auburn
Home of the Herbert Candies, Shrewsbury
Mai or Product
Bread, cakes, pies
Milk, cottage cheese, butter
Corn syrup
Corn syrup, corn starch,
other corn by-products
Soft drinks
Chocolate confections
Bread
Processed beef
Chips, snacks, popcorn
Canned milk products
Hdqts.
Milk
Soft drinks
Soft drinks
beef (made in same estab. as
basic materials) meat
sauces, chocolate and cocoa
extracts
Flavoring, extracts
Processed beef--made from
purchased material or mat.
transferred from another
establishment
Processed pork--made from
purchased material or mat.
transferred from another
establishment
Bakery products
Milk
Bakery products
Dairy products
Candy
76
-------
TABLE 23 CONTINUED
FOOD AND BEVERAGE PLANTS IN TWO COUNTIES
PLANT
MA - Worcester. Co.
Larpson MH & Co., Inc., Worcester
Leroux Meats Inc., Holden
Lundgren & Jonaitis Dairy, Shrewsbury
Miles BF & Co., Millbury
Millbrook Inc. Worcester
Mt. Wachusett Dairy Inc., W. Boylston
Near East Food Products Inc., Leominster
Nissen John J. Baking Co., Worcester
Pepsi-Cola Bottling Co., Holden
Polar Corp. Worcester
Portion Control Meat Pro.,
Wilkinsonville
Snider Bros., Inc., Wilkinsonville
Squibb Corp. Dolbs-Life Savers,
Worcester
Squibb Corp. Dolbs-Life Savers,
Harvard
Trappist Preserves, Spencer
Tri-Sum Potato Chip Co., Inc.
Leominster
United Crop Farmers Inc., Fitchburg
Van Erode Milling Co., Clinton
Mai or Product
Milk
Sausage & Similar Prod.--made
from purchased material or
material transferred from
another establishment
Milk
Fresh Packed Vegetables &
Juices
Fresh Packed Vegetables &
Juices
Milk
Other Food Prep.
Bread and Rolls
Soft Drinks
Soft drinks
Meat Packing Prod.--made in
same estab. as basic
materials
Prepared Meats--made from
purchased material or
materials transferred from
another estab.
Pies
Bakery Products
Jams, jellies, preserves
Chips, snacks, popcorn
Poultry Feeds
Cereals, ready to serve
Source: Chilton Company (1981)
77
-------
specific information on pathways cannot be developed by location.
Prioritization in this case will depend on the chemical
properties and the expected volume of release or resultant
concentration in various situations.
As a result, prioritization of pathways will depend on the amount
and type of information developed for a given chemical and will
require judgement by the user in evaluating which pathways to consider
for quantitative assessment. Depending on the scope of the
assessment, it may be reasonable to identify the pathway that is
likely to result in the highest concentration in food. This analysis
can be carried through in order to determine whether food represents a
significant exposure route to humans compared to other exposure
routes. If food appears to be a significant exposure route, then
further analysis of other contamination pathways is required.
A.4 ACCIDENTAL PATHWAYS OF CONTAMINATION
The previous section addressed the potential pathways of food
contamination when a chemical is used as intended. However, there is
a possibility of misuse or accidents. This section applies to
chemicals not used as intended. The nature of these incidents is
limitless and this methodology cannot detail all the possibilities,
nor even suggest which ones are the most probable. This section will
attempt to describe some common types of accidents. Using this
information, scenarios for specific chemicals or products could be
developed to evaluate the potential for food contamination in these
situations.
It should be noted that knowledge regarding food contamination
incidents is extremely limited (OTA 1979). Their detection is not
common, and those that are detected generally involve widespread
exposure problems, such as PCBs or methylmercury. Table 24 shows the
reported food contamination incidents and the estimated cost
associated with each incident. Most of the reported incidents involve
pesticides, with the exception of PCBs, PBBs, and mercury. Some of
these are probably isolated incidents and can be viewed as accidental
in the context of this report. Problems associated with the more
persistent compounds have involved normal use practices which resulted
in contamination of the environment and resultant contamination of
food.
Section A-2 divides the food preparation process into two major
stages: food generation stages, and post-harvest stages. In this
context, it is useful to divide the post-harvest stages into
in-process stages and post-process stages. The following discussions
will address common contamination problems in each of these three
stages. Table 25 summarizes these accidental pathways.
A.4.1 Food Generation Stages
The food generation stages are probably the least controlled
stages in the food process and almost all incidents described by the
78
-------
TABLE 24
FOOD CONTAMINATION INCIDENTS
Reported incidents
Total estimated Cost ($)
STATE
Idaho....
Colorado.
Maryland,
Texas....
Indiana..
Michigan.
FEDERAL
USDA/FSQS
.Dieldrin
PCP
.Dieldrin
Mercury
.Mercury
.Mercury
.Dieldrin
Dieldrin
.Mercury
PCB
PCNB
PBB
Picloram
Chlordane
DDT
Toxaphene
Parathion
Diazinon
Pentachlorophenol
PCB
Dieldrin
Pesticides
Mercury
PCB
Phenol
Total United States.
100,000
3,000
100
3,700
23,000
85,000
25,027
250,000
10,000,000
30,000,000
100,000
215,000,000
12,000
2,500
2,000
2,000
328
13,700
28,468
150,000
12,500
$255,813,323
18,900,000
63,000
7,450,000
350
26,413.350
$282,226,673
Source: OTA (1979)
79
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OTA (1979) occurred in these stages. Accidents primarily seem to
involve the purposeful addition of some product (pesticides, animal
health care products, feed additives, etc.)- Misapplication of these
products is a common problem. Mislabeling is also common. While
chemicals added to food in the generation stages are approved for this
use, many of them also have other uses. Thus, the mislabeling of the
same chemical intended for another use can occur. This may result in
the food use of a formulation not intended for food. The presence of
low level contaminants in these purposeful additions can also present
a food contamination problem. This problem is compounded when
mislabeling occurs, since the levels of impurities are likely to be
higher in a non-food-grade chemical.
Spills occurring in the vicinity of food or feed generation
areas, drinking water supplies for livestock and poultry, and
irrigation water supplies can result in food contamination. Probably
the most common occurrence of this type is a spill resulting in
contamination of aquatic organisms.
Transportation represents another accidental pathway. Improper
cleaning, or the carrying of unapproved substances in vehicles used
for food can also result in contamination.
A.4.2 In-Process Stages
The in-process stages include steps from storage to packaging or
preparation for consumer distribution. The nature of the accidents
occurring at this stage is similar to those in the food generation
stages. Mislabeling is still a problem, although this could include
food ingredients as well as sanitizers, building maintenance
compounds, and pesticides used in food storage areas. Misuse and
improper storage of these chemicals can also result in food
contamination. Backflow of sewage or other substances to process
water can occur, as well as drip back from stacks.
Cross-contamination, or the use of improperly cleaned containers for
other purposes can also be a problem. Similarly, the use of steam for
blanching or cooking can result in food contamination problems in
commercial operations, particularly if the steam is not intended for
food, and boiler additives not approved for food have been used.
Packaging represents a point of contact with food, sometimes for
extended periods. Mislabeling or misuse of chemicals in the packaging
material or adhesives, can coatings, etc. can result in contamination
of the food item.
A.4.3 Post-Process
Contamination of food in the post-process stage basically
consists of contamination of consumer goods. Contamination can result
81
-------
from spills, transportation, and improper formulation, especially
related to mislabeling. Food may be contaminated in warehouses where
storage of items may occur, in grocery stores, or in the home.
Contamination occurring at this stage would not be likely to result in
exposure to a large number of people.
82
-------
APPENDIX B QUANTITATIVE METHODS
B.I INTRODUCTION AND SUMMARY
This section presents calculational approaches for assessing the
potential of pollutant migration into food. These approaches have not
been presented in the form of a step-by-step procedure or a model,
because of the uncertainty governing pollutant migration related to food.
The intent is to provide a basis for estimation and an understanding of
the factors that influence food contamination.
Table 17 showed that there are four major categories of food that
can be segregated in terms of having unique contamination pathways. In
the food generation stages, pathways to meat, crops, and fish/shellfish
will be considered. In the post-harvest stages, food is considered as a
whole, as contamination pathways are more dependent on processing method
than on food type. Chemical losses are also discussed in this section.
The pathways of chemical losses are similar to those of contamination
transfer in the post-harvest stages.
A summary of the quantitative methods described in this section is
shown in Table 26. The equations and relationships shown are to be used
with caution. Table 26 gives a reference to the section in which more
detail is provided. Table 27 summarizes the important physical/chemical
properties that are needed to quantify contamination from each pathway.
Quantification methods for each of these pathways will be considered
below.
B.2 PATHWAYS TO ANIMALS
There are several pathways that can result in pollutant
contamination of edible animal products in the environment as shown in
Table 17. Among these contamination pathways to animals one might
include:
ingestion of feed grown in contaminated soil or from areas in which
pollutant deposition has occurred on plants and/or soil,
ingestion of drinking water originating from contaminated ground or
surface water sources (from pollutant releases to soil or water) or
from areas in which deposition has occurred (from pollutant releases
to air),
inhalation of pollutants released to air, and
dermal absorption of vapors released to air or absorption of
pollutants from contact with soil or contaminated water.
Residue levels found in edible animal tissues and products reflect
the digestive and metabolic processes inherent in the species of concern,
the time elapsed since exposure ceased, the biological half-life of the
contaminant and its various metabolites that may appear as residues in
food, the contaminant's lipid affinity or tissue binding, and its
stability. The least desirable contaminant from a human health
83
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TABLE 27 IMPORTANT PHYSICAL/CHEMICAL PROPERTIES NEEDED FOR
QUANTIFICATION OF EACH PATHWAY
Pathway
PATHWAYS TO ANIMALS
Section in
Appendix
B.2
Physical/Chemical
Property and Definition
Unit
Ingestion of Feed or Water B.2.1 S Water solubility, or
K Octanol-water partition
coefficient, or
K Organic carbon soil adsorption
coefficient, or
BCF Bioconcentration factor in
fish in flowing water tests, or
BCF Bioconcentration factor in
fish in static water systems
ppm
Inhalation of Pollutants B.2.2
Released to Air
No Available Method
Dermal Absorption
B.2.3
K Permeability constant
S
I/cm2 hr
PATHWAYS TO FISH/SHELLFISH B.3
K Octanol-water partition
ow
coefficient, or
S Water solubility, or
K Soil (or sediment) adsorption
coefficient
ppm
PATHWAYS TO CROPS
Uptake from Air
Root Uptake
B.4
B.4.1
B.4.2
H Henry's Law Constant
K Octanol-water partition
ow
coefficient, or
K Soil adsorption coefficient
m atm/mol
92
-------
TABLE 27 IMPORTANT PHYSICAL/CHEMICAL PROPERTIES NEEDED FOR
QUANTIFICATION OF EACH PATHWAY
Section in
Pathway Appendix
PATHWAYS TO FOOD-POST-HARVEST B.5
B.5.1.1.1
B.5.1.1.2
Physical/Chemical
Property and Definition
Diffusion from Air to Food
Air
Diffusion from External
Liquid to Food Liquid
Moisture-Solid B.5.1.2.1
Partitioning
D Diffusion coefficient of
o
pollutant in air
D Diffusion coefficient of
w
pollutant in water
K Adsorption (partitioning)
coefficient
K Octarol-water partition
coefficient
Moisture-Air Partitioning
Food in Contact with
Surfaces
Additives
B.5.1.2.2 H Henry's Law Constant
B.5.2
Da Diffusion coefficient in air
K Adsorption (.partitioning)
coefficient, or
K Octanol-water partition coefficient
ow
Unit
cm2/sec
cm2/sec
(ug/g)/(ug/tnl)
m3 atm/mol
cm2/sec
(ug/g)/(ug/ml)
B.5.3
CHEMICAL LOSSES
B.6
As in Pathways to Food-Post-Harvest
93
-------
perspective is a toxic compound that is very stable or degrades to
persistent and toxic residues in edible products.
B.2.1 Ingestion of Contaminated Feed or Water
Dairy cattle, beef cattle, swine, sheep, and poultry can all be
inadvertently exposed to contaminated feed or water. This can occur from
ingestion of contaminated water or plants and/or soil which contain
pesticide residues or other pollutants, ingestion of plants capable of
accumulating toxic materials from soil (e.g., selenium in cereal crops),
or forage along highways or around industrial areas.
Use of municipal sludge as crop fertilizer and the practice of
allowing food animals to graze on croplands after sewage sludge has been
applied is another source of possible contamination. Municipal sludges
typically contain heavy metals such as cadmium, chromium, nickel, copper,
and lead as well as refractory organic compounds such as PCBs. Elevated
levels of metals, particularly cadmium, have been found in sheep fed
silage corn grown in municipal sludge-amended soil (Telford et al. 1982)
and in steers fed a normal cattle ration plus 12% by weight of air-dried
municipal sewage sludge (Boyer et al. 1981). The levels of lead and
cadmium in kidneys, and of lead, cadium and copper in liver from these
steers were high enough to cause toxicological concern for human
consumption of these tissues.
Another point to keep in mind with respect to contamination of human
food supplies is that ruminants may react to toxicants quite differently
than non-ruminants due to differences in digestive structure and function
between these two groups of animals. For example, ability to vomit
effectively is different in ruminants and non-ruminants. Many
monogastric animals (man, dog) vomit easily. Ruminants can vomit but the
reflex is not as easily stimulated and the degree to which vomiting is
effective in removing poisonous materials from the gut is much less in
ruminants than in non-ruminants.
Determinations of human exposure to contaminants in edible animal
tissues and products require information about the nature and amount of
residues in the principal edible tissues (i.e., muscle, liver, kidney and
fat; skin for poultry) and products (eggs, milk). Perhaps the most
useful tool in this regard is data on the partition coefficients in
octanol and water, which can be used as an indication of lipid affinity.
A lipophilic tendency is a primary consideration in identifying compounds
with long biological half-lives and thus potential animal residue
problems for humans.
Theoretically, the concentration of a chemical in animal tissues may
be estimated by:
CT = (BFf) (F) CD (B-l)
where C = concentration of chemical in tissue (ug/kg)
bioconcentration factor (fat basis) for organism of concern
(ug/kg of fat)/(ug/kg of diet)
F = fat content of tissue (kg fat/kg tissue)
C = concentration of pollutant in diet (or drinking water)
(ug/kg)
94
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Kenaga (1980) attempted to relate the bioconcentration factor of
chemicals in terrestrial organisms with physical and chemical properties
(water solubility, S; octanol-water partition coefficient, K ; organic
carbon soil adsorption, K ); and bioconcentration factors in fish.
Using 23 chemicals, the regression equations obtained for beef fat are
shown in Table 28.
Garten and Trabalka (1983) criticized the regression equations
derived by Kenaga (1980) for the use of questionable data for some
independent variables. The bioaccumulation data for fish were derived
from a variety of different methods, and data from unpublished reports
were used. The confidence limits for Kenaga's predicted bioaccumulation
factors covered nearly 4 orders of magnitude as shown in Table 28.
Garten and Trabalka (1983) proposed screening levels as alternatives to
estimation. A screening level was defined as the value of log K below
(or log S above) which no compound tested exhibited appreciable
bioaccumulation in terrestrial organisms (birds, ruminants,
non - ruminants). An arbitrary log BFf of -0.5 was chosen as the limit
which corresponded to 0.3 mg/kg in fat. The screening levels developed
by Garten and Trabalka (1983) by this method are shown in Table 29.
Garten and Trabalka (1983) also tested Kenaga's (1980) suggestion to use
measured bioconcentration factors in aquatic test systems to predict
bioaccumulation in terrestrial vertebrates. They found that
bioconcentration in mammals and birds was very weakly correlated or
uncorrelated with pollutant bioconcentration factors from fish studies
(correlation factors 0.09-0.43), indicating that accurate prediction of
bioaccumulation in birds or mammals cannot be obtained from fish tests
alone. They did find, however, that bioaccumulation factors in sheep,
poultry, rodents, dogs, cows and swine were significantly correlated and
that bioaccumulation factors in rodents were highly correlated with
bioaccumulation factors in poultry and cows.
The model TOX-SCREEN (USEPA 1984b) uses the screening method
developed above by Garten and Trabalka, without attempting to quantify
the actual level of bioaccumulation in terrestrial organisms.
B.2.2 Inhalation of Pollutants Released to Air
Livestock can potentially absorb pollutants via inhalation of
vapors, respirable dust particles, or aerosols such as the spray drift
from insecticide usage. Indeed, many agricultural processes involve
actions which generate airborne dust. Unfortunately, there is an almost
total lack of data regarding this route of animal exposure and there are
no available methods to quantify resultant animal concentrations.
The types of information needed to adequately assess exposure of
animals via this pathway and allow estimation of human exposure via food
would include:
the form of exposure - vapor or aerosol,
if an aerosol, the particle size distribution,
95
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TABLE 28 . BIOCONCENTRATION FACTORS OF CHEMICALS IN BEEF
Equation 95% Confidence Correlation
Regression Equation No. Limits Coeff. = j:
log BFf = -1.476 - 0.495 log S (B-2) 1.85 -0.817
log BF = -3.457 + 0.500 log K (B-3) 1.97 0.790
i ow
log BF = -3.825 + 0.701 log K (B-4) 2.19 0.732
i oc
log BFf = -3.839 + 0.869 log BCFf (B-5) 2.05 0.771
log BFf = -2.842 + 0.674 log BCFt (B-6) 1,58 0.879
Regression using 23 chemicals, mainly chlorinated herbicides and pesticides,
where: S = water solubility, 0.002 - 502,000 ppm
K = octanol-water partition coefficient, 0.02-1,400,000
ow
K = organic carbon soil adsorption coefficient, 2-468,000
BCF,. = bioconcentration factor in fish in flowing water tests, 0.6-61,600
BCF = bioconcentration factor in fish in static water terrestrial
ecosystem tests, 0-84,500
BF = bioconcentration factor (fat basis), 0.0003-3.5 (ug/kg of
fat)/(ug/kg of diet)
Source: Kenaga (1980)
96
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TABLE 29 SCREENING LEVELS3 FOR BIOCONCENTRATION IN BIRDS,
RUMINANT AND NON-RUMINANT MAMMALS
False positive/False negative
Screening Level Log BF Error Rate
log K <3.5 No appreciable bioacc. in fat, 25% with 68 different
°W logBFf<-0.5 (or BF <0.3) chemicals
log S>4 No appreciable biaocc. in fat, 25% with 68 different
(or S > 10 mg/1) BF < 0.03 chemicals
an order of magnitude less than
screening levels
a. Value of log K below or log S above which log BF < -0.5 (or 0.3 mg/kg
c M- \ OW 1
in fat).
b. Particularly with respect to bioaccumulation of chemicals that can
covalently bond or otherwise bind to proteins rather than fat (e.g.,
methylmercury).
Source: Garten and Trabalka (1983)
97
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the degree of absorption at the site of original contact,
the rate and pattern of extracellular and intercellular
distribution,
metabolism, if any, at the absorbing and target tissues, and
the rate of excretion and bioaccumulation.
The likelihood of having this information is small. However, some
generalities can serve as guides for making estimates of exposure.
Absorption of lipid-insoluble substances from the lung is a fairly rapid
process, possibly more so than from the gastrointestinal tract.
Lipid-soluble substances appear to be absorbed from the lungs even more
rapidly, at rates that are presumably dependent on lipid/water partition
coefficients. If exposure is to an aerosol or dust, knowledge of the
particle size can help to define exposure. The filtering mechanisms of
the respiratory tract are capable of excluding larger particles (diameter
greater than 10 urn) and only particles below 2 um actually reach the
alveoli.
B.2.3 Dermal Absorption
Cutaneous penetration depends largely on the nature of the agent and
is primarily a function of solubility and the rate of diffusion. The pH,
extent of ionization, molecular size, temperature, humidity, and skin
site also affect absorption through skin. In addition, the status of the
exposed skin is important. Breaks in the skin, scratches, cuts, and
scabs represent sites of easy entry for materials which might otherwise
be excluded.
In general, lipid-soluble compounds as a group are better absorbed
through skin than are water-soluble compounds. In the absence of
skin-compound partition coefficients, solvent systems such as
octanol-water or mineral oil-water partition coefficients can be used as
models for estimating skin penetration of xenobiotic materials. It
should be noted, however, that considerable variation exists among
available solvent models and that no one system has been validated over a
broad range of unrelated chemical structures. In addition, issues such
as changing skin characteristics with abrasion, solvent exposure, or
variations in the thickness of the stratum corneum are not approached in
any of these solvent models.
To estimate the rate of diffusion of a pollutant from the surface of
skin into the underlying tissue, Fick's law as expressed below may be
used:
F - K AC (B-2)
2
where: F = flux or permeation rate through the skin (mg/cm - hr)
K = permeability constant (I/cm - hr)
AC = concentration difference across the skin (mg/1)
C may be approximated to be equal to the concentration in the
solution in contact with the skin of the animal. Brown et al. (1984)
calculated permeability constants for ethylbenzene, styrene and toluene
from experimental data for human skin at high concentrations. Data for
98
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permeability is not likely to be available for the chemical of concern.
The ^alues obtained by Brown et al. (1984) range from 0.0006 - 0.001
I/cm - hr. K is directly related to the diffusivity of the chemical
and may be estimated from:
Ksi - Ksj
2
where: K . = permeability constant of chemical i (I/cm - hri
K . = known permeability constant of chemical j (I/cm - hr)
MW. = molecular weight of chemical i
MW. = molecular weight of chemical j
The method described above has not been tested and is based on very
little information. The method is expected to provide very rough
estimates of concentrations.
B.3 PATHWAYS TO FISH/SHELLFISH
Table 15 showed that the primary contamination route for aquatic
species is absorption from water. While ingestion of contaminated food
represents a possible contamination route, such a pathway would be
difficult to quantify.
Pollutant concentrations in aquatic organisms are estimated using
the concentration in water and a bioconcentration factor, BCF, for fish:
C = (BCF) C /p (B-4)
ao w' w
where C = concentration of pollutant in aquatic organism at
equilibrium (ug/kg)
BCF - concentration of pollutant in aquatic organism/
concentration in water
C = concentration of pollutant in water (ug/1)
p density of water (kg/liter)
w
Bioconcentration factors have been measured for certain fish species
under specific conditions. There are also several methods for estimating
bioconcentration factors as described in Bysshe (1982) . The methods
recommended by Bysshe are summarized in Table 30. Before using the
regression equations given, Bysshe (1982) and any recent review articles
on actual measurements of the bioconcentration of the chemical of concern
should be reviewed in case a measured value for bioconcentration is
available. If measured values for independent variables are not
available, estimation methods are available in Lyman et al . (1982). The
order of preference for independent variables is K , S and K in
, ,. , ow oc
descending order.
TOX-SCREEN (USEPA 1984b) a screening- level program for assessing
potential fate of chemicals released to the environment, and developed in
the Office of Toxic Substances, EPA, uses the regression equation
developed by Mackay (1982):
BCF = 0.048 K (B-5)
ow
99
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The estimation methods available are based on regression of data to
obtain straight-line correlations. A fair degree of scatter exists in
the data. Discrepancies have been found between estimates and laboratory
data or field situations. In particular, bioaccumulation of covalently
bonded chemicals cannot be predicted by these methods. The estimates
provide some means of identifying chemicals which are likely to
bioaccumulate in fish and the likely extent of bioconcentration.
The Criteria and Standards Division in the Office of Water
Regulations and Standards of the U.S. EPA, in the determination of
Ambient Water Quality Criteria, adjusts the equation shown above for
lipid soluble compounds. The bioconcentration factor is adjusted for the
lipid content of the fish/ shellfish consumed in the diet, as compared to
that in the test species, if it was a measured value, or to the species
on which estimated values were based. EPA uses a weighted average lipid
content of the U.S. fish/shellfish diet of 3% for the protection of human
health (USEPA 1980b). For calculating the Final Residue Levels to meet
FDA levels, the appropriate lipids value is 100% for fish oil, 11% for
freshwater fish and 10% for saltwater species (Stephen et al. 1983).
The latter levels are higher because FDA action levels are applied on a
species-by-species basis. The highest lipid contents of edible tissue
are 11% for freshwater fish (chinook salmon and lake trout) and about 10%
for saltwater Atlantic herring.
B.4 PATHWAYS TO CROPS
Very little quantitative guidance (predictive equations and models,
etc.) can be provided to assist in assessing the importance of
contamination pathways leading to crops. The number of variables is
large (crop type, environment, chemical type), and the available data and
knowledge are small. In some cases, an order-of-magnitude estimate of
the pollutant's concentration in the crop may be made. This may be
sufficient for a rough screening of pathways to crops.
Three distinctions are important when assessing pathways to crops:
Terrestrial vs aquatic environment
Surface contamination vs uptake
Organic vs inorganic chemicals
Terrestrial vs Aquatic Environment - Most edible crops are grown in
conventional, terrestrial environments (i.e., a field or greenhouse soil
plot). These plants "see" two quite different environments: the
atmosphere above the soil, and the air/water/nutrient/soil mixture below
the soil surface. Uptake of pollutants may differ markedly for these two
environments. By contrast, there are plants that grow (or are grown)
primarily in an aquatic environment. Examples include algae, seaweed,
and some plants grown wholly or partially underwater (e.g., rice).
There is, perhaps, an additional classification for plants grown via
hydroponics (i.e. , where rooting plants are grown, without soil, in a
mineral-rich solution or mist). There should be a special concern for
crop contamination in this case for any chemical that is added, or might
be added by mistake, to the formulated nutrient solution. In the case of
101
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hydroponics and aquatic plants, it may be appropriate to consider the
probable (equilibrium) distribution of the pollutant between the aqueous
solution (not pure water) and the plant. For neutral organic chemicals
it is likely that the plant bioconcentration factor (under these aquatic
conditions) will be strongly correlated with the octanol-water partition
coefficient and, thus, inversely proportional to water solubility. The
correlation equations provided by Baughman and Paris (1981) show this
clearly. The lipid content of the plant will clearly have an effect,
with higher lipid contents leading to higher bioconcentration factors.
Surface Contamination vs Uptake - A pollutant may easily reach, and
adhere to, some surface of a plant (leaf, stem, root), yet not be taken
up by the plant. Thus, any crop contamination pathway assessment should
clearly distinquish between surface contamination and uptake. The former
may be mitigated by subsequent crop washing and processing, the latter
might not.
Conventional, terrestrial plants may take up pollutants in three
ways: (1) through the stomatal pores of the leaves (foliar uptake); (2)
through the stems; and (3) through the roots. For gaseous pollutants
released into the air, foliar uptake is likely to be the most important
pathway (Vaughan et al. 1981; Guthrie 1980). This may even be the most
important pathway for non-volatile pollutants dispersed in the air if the
chemical is of moderate to high water solubility and the particles are
small enough to penetrate the stomatal pores. In any case, chemicals
with high water solubility will be more easily absorbed through the pores
into the water-rich plant body.
For pollutants that have become incorporated into the soil, uptake
by the roots or tubers may involve more complex processes, especially for
ionized species. In this case, especially for inorganic chemicals, there
may be relatively little tendency for the plant to accumulate the
pollutant to concentrations above that in the surrounding soil.
Bioconcentration of neutral organic compounds from soil into plants is
still a possibility, but the bioconcentration factors would not be
expected to be as large as those found for aquatic biota. This is
because soil contains an appreciable amount of organic matter (typically
1-10% by weight in top soils) that will compete as sorption sites for the
organic pollutants. In some cases the bioaccumulation factor
(concentration in plant/concentration in soil) may be substantially less
than 1.0 due to such factors as high soil organic content, high soil
adsorption coefficient for the chemical, and the chemical's difficulty in
penetrating the root or tuber. For example, a bioaccumulation factor of
about 0.001 was found for corn (Zea mays) grown in soil contaminated with
up to 20,000 mg/kg di-n-butyl phthalate (Shea et al. 1982).
Organic vs Inorganic Chemicals - A number of distinctions have
already been made with regard to organic vs inorganic chemicals and the
associated difference in plant uptake. It is worth repeating here,
however, the general admonition to consider the chemical nature of the
pollutant in assessing the potential uptake by crops. The specific
considerations should include, for example:
102
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water solubility
dissociation in water (speciation)
octanol-water partition coefficient
soil adsorption coefficient
reactivity in solution (e.g., oxidation, reduction, complexation,
and precipitation of metals; hydrolysis, oxidation, biodegradation
of organics)
volatility (including Henry's law constant)
The pathways to crops are assessed by two separate routes: uptake
from air and uptake from roots. Depending on the properties of the
chemical and the nature of release of the chemical, one or both of these
routes may be important.
B.4.1 Foliar Uptake from Air
As a very crude theoretical estimate, plant tissue may be considered
to be a reservoir of water contained by a sheath that is permeable to the
chemical. The uptake from air may be approximated by the use of the
chemical's Henry's law constant (H).
C RT
Cp - Y- (B-6)
'
C = concentration of pollutant in plant (ug/ml)
C = concentration of pollutant in air (ug/ml)
a 3
H = Henry's Law Constant (m atm/mol)
R = gas constant (8.2x10" m atm/mol °K)
T = temperature (°K)
This method could overestimate the absorption of a chemical into
foliar solution because the latter is not pure water and the solubility
of the chemical in it could be lower than in pure water. In addition,
the action of the cuticle as a barrier is ignored. On the other hand,
there may be a favorable partition of a chemical into plant solution if
the chemical is more soluble in the plant solution than in water.
As an example, assume a plant is exposed to contaminated air
containing 0.001 ug/ml methylene chloride. J5ince H for methylene
chloride (@ 25°C) is about 3x10 atm m /mol, the equilibrium
concentration in pure water is about 0.01 ug/mL.
The model used by TOX-SCREEN (USEPA 1984b) is an interception model
developed by Chamberlain (1970). This model and suggested parameters are
shown in Table 31. A factor, T , has also been included in some models
(USEPA 1984c) to relate radionuclide concentration in the edible portion
of a crop to that calculated in the equation shown in Table 27. Baker et
al. (1976) suggested a value of 1.0 for leafy vegetables and fresh
forage, and 0.1 for all other produce. A factor of 1.0 should probably
be used for a conservative approach.
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TABLE 31
CONCENTRATION OF COMPOUND IN PLANTS AS
A RESULT OF INTERCEPTION
where
ei
1 -
1 - e
-A .t
ei e
. t
ei e
x [deposition
C = concentration of pollutant in plant (ug/g)
empirically determined initial interception fraction
2
vegetative productivity (g/m )
Y
v
A .= empirical weathering constant (day )
t = crop growth period before harvest or grazing, (days) deposition
e 2
rate in g/m -day.
Values
r/Y
average of 2.0 m /kg for grasses based on a dry-weight
2
value of Y of about 0.1 kg/m (Chamberlain, 1970)
0.25 for deposition of radionuclides on pasture (USNRC 1977)
0.4 may be more appropriate for organics than values above
(Morton et al. 1967)
Y
v
0.7 kg/m fresh weight for radionuclides on pasture (USNRC,
1977)
= 0.15 kg/m default value
X . = 0.05 day"1(Chamberlain 1970; USNRC 1977), value probably
smaller for organics
= 30 days for grasses (USNRC 1977)
Source: USEPA (1984b,c)
104
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B.4.2 Root Uptake
Briggs et al . (1982) used a Root Concentration Factor (RCF) and a
Transpiration Stream Concentration Factor (TSCF) to describe uptake into
roots and subsequently into shoots.
RCF = (concentration in roots)/(concentration in
external solution) (B-7)
TSCF = (concentration in transpiration stream)/(concentration in
external solution) (B-8)
The RCF is generally independent of concentration for dilute
solutions and the TSCF has a maximum value of 1.0 for passive uptake.
The regression equations obtained for 18 compounds (non- ionic
o-methylcarbamoyloximes and substituted phenylureas) in barley shoots are
as follows :
log (RCF - 0.82) = 0.77 log KQW - 1.52 (B-9)
TSCF = 0.784 exp - [(log K -1 . 78)2/2 .44] (B-10)
RCF = 0.82 (for polar species) (B-ll)
The measured value of the TSCF for 3- (methyl thio)phenylurea was much
less than its predicted value. The regression equations above will not
provide accurate values , but appear to apply reasonably well to some crop
species including rice, lettuce, turnip, and wheat. Root physiology or
rapid metabolism in roots, e.g., in carrots or parsnips, may reduce
translocation, leading to higher predicted TSCF values than would be
measured.
The regression equations by Briggs et al. (1982) were obtained from
experiments with barley shoots in nutrient solutions. For plants in
soil, the concentration of a chemical in the soil solution may be
estimated by:
C = - - (B-12)
S Kd
where :
C concentration in soil solution (g/ml)
S
C = total concentration in soil (g/g)
K, = bulk soil partition coefficient
For compounds whose partitioning is governed largely by organic
matter, the soil solution concentration can be estimated as follows.
(B-13)
105
S
where :
C
o
K (OC)
oc
-------
OC = the fractional organic carbon content (g/g) /
K = Organic carbon adsorption coefficient (ug/g /ug/ml)
Redefining, RCF = (concentration in roots)/(total concentration in soil)
s
TSCF = (concentration in transpiration stream)/(total
concentration in soil)
we obtain:
log [RCF K (OC) - 0.82] = 0.77 log K - 1.52 (B-14)
TSCF K (OC) = 0.784 exp - [(log K -1.78)2/2.44] (B-15)
RCF K (OC) - 0.82 (for polar species) (B-16)
The work of Briggs et al. (1982) is incorporated into the Pesticide
Root Zone Model (PRZM). This model simulates the vertical movement of
pesticides in the unsaturated zone. Various processes are incorporated
into the model, including plant uptake. The model uses an uptake
efficiency factor calculated using Equation B-10 (Carsel et al. 1984).
However the use of these equations for compounds and concentrations
outside the range tested by Briggs et al. (1982) may produce questionable
estimates. Experimental data for DDT from Nash et al. (1970) and Onsager
et al. (1970) were substantially lower than levels predicted using
Equation B-14.
In TOX-SCREEN (USEPA 1984b) the relationship used was between K
(soil-water partition coefficient) and a bioconcentration factor,
BC .defined as the ratio of the mature plant parts concentration of a
chemical (ug/g dry weight) to the soil concentration (ug/g dry weight).
C . = BC n x C (B-17)
pi pi o v '
K is related to K approximately by:
K, = K x (OC) (B-18)
d oc
The regression equation used in TOX-SCREEN for radionuclides was
developed by Baes (in press) and is as follows:
In K, = A+B In (BC ,) (B-19)
d pi
or In [K x OC] = A+B In (BC ,) (B-20)
oc pi
The values used for A and B in TOX-SCREEN are 3.02 and -0.85,
respectively, derived from a literature review of 21 elements.
B.5 PATHWAYS TO FOOD--POST-HARVEST STAGES
There are four major pollutant food chain "access points" in the
post-harvest stages: (1) Food in contact with air (2) Food in contact
with water or another liquid, (3) Food to which something is added and,
(4) Food in contact with a surface. Relevant or significant pollutant
pathways in the environment have been identified and discussed in
106
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Sections A-3 and A-4. These pathways eventually involve contact of the
food or feed with one or more of the above media.
For all of these pathways, food contamination can occur via a number
of pollutant pathways in the food matrix. A food matrix will consist, in
general, of one or more homogeneous phases. The phases are food-air,
food-water, and food-solids, as shown in Figure 8. This figure shows
that a substance can diffuse from external air to food air (Pathway 1) ,
or from external liquid to food liquid (Pathway 2) . Once in the food,
the pollutant can be partitioned between the phases within the food
matrix. The following sections consider contamination via the four
access points, considering the different pathways in the food matrix as
appropriate.
B.5.1 Food in Contact with Air. Water or Liquid
It is documented that pollutants can migrate from air, water, or
other liquid designated as "external" media -- into food in a variety of
situations (see Table 15) and in a number of post-harvest stages. The
situations of contact are numerous, but the mechanisms -- and governing
algorithms --of pollutant migration are similar in many cases. The rate
and extent of migration are dependent on a multiplicity of factors,
including pollutant concentrations in the external media, pollutant
characteristics, time of food exposure, food characteristics, and
temperature.
In the following analysis, it is assumed that a pollutant is
uniformly present in the external media of the food, and that the food is
impacted by a constant concentration unless stated otherwise. In that
respect, contamination of the food may take place (Morrill et al. 1982)
as a result of two sequential major processes:
(1) Diffusion of the pollutant (from the air or water) through the
surface of the food into the food moisture (water) , the
food-air, or the food-solid as a result of a concentration
gradient between the external media and the food,
(2) Partitioning of the pollutant molecules into the various phases
of food, either by adsorption or dissolution in the organic
fraction of the food.
The above processes are time and temperature dependent, but in the
following section, only steady-state and temperature independent
conditions are described. When necessary, however, a separate discussion
on the effects of these parameters is given.
B.5.1.1 Diffusion
For non-homogeneous foods, like an apple or a piece of meat,
diffusion of the pollutant may have to take place through more than one
layer, for example through both the apple peel and the apple body. In
addition, diffusion can take place across any section of different media,
for example, from the air of an external medium to the air of the food
pores, or from the air of an external medium to the moisture of the food.
107
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Food periphery
WATER
OR
LIQUID
AIR
#2
#1
Equivalent Circle/
sphere
EXTERNAL
MEDIA
PATHWAYS TO
FOOD MATRIX
FOOD MATRIX
# 1 External air to food air
it 2 External water or liquid to food moisture
// 3 Food water to food solid
# 4 Food air to food water
FIGURE 8
SCENARIOS OF FOOD CONTAMINATION
108
-------
The mass of a diffusing pollutant along a direction (x) and passing
through a given cross section per unit time is described by Pick's first
law, which says that the pollutant flux is directly proportional to the
concentration gradient:
F = - D (dc/dx) (B-21)
where:
2
F = pollutant mass flux along a direction x (ug/cm s) ~
D = diffusion coefficient of pollutant in the food phase (cm /s)
c = concentration of pollutant in a medium (ug/ml)
dc/dx = concentration gradient in direction x
Equation B-21 applies to all media and any type of diffusion process
(e.g., air-to-air, air-to-moisture) and represents the basic equation for
estimating pollutant migration into food from air, water or liquid
(external media). Although diffusion can occur in all three phases (air,
moisture, solids) of a food piece; it takes place most rapidly in the
food-air, and least rapidly in the food-solids. In general, diffusion of
contaminants in the vapor phase (air) occurs 10 times faster than in
water. Diffusion in the solid phase may be very slow compared to other
pollutant transport processes. The same principle can be assumed to
apply in food, therefore, diffusion in solids is neglected in the
sections to follow.
B.5.1.1.1 Diffusion from Air to Food Air
The Farmer formula for estimating pollutant flux from soil-air to
the air is adapted for spherical (or circular) food pieces:
Fl - °fa* (Ca - Cfa>/r (B'22)
where:
F,. = pollutant mass flux across food surface in pathway #1
in Figure B-l (ug/cm s);
*
D,- = apparent diffusion coefficient of pollutant in food air
(cm /s);
C = concentration of the pollutant in the air (external
medium) of the food (ug/cm )
C,. = concentration of the pollutant in the food air (ug/cm )
r approximate radius of the food piece as shown in Figure
B-l (cm).
For a particular pollutan^, the apparent diffusion Coefficients may
be required for food-air (D,- ) and food-moisture (D.. ) . An apparent
diffusion coefficient accounts for the reduction in the rate of diffusion
due to the particles of the food substance. The estimation of both
109
-------
apparent diffusion coefficients is discussed in Bonazountas and Wagner
(1981). A brief discussion is included here. Apparent diffusion
coefficients can be estimated from food porosity via the relationship
Millington and Quirk (1961) developed for porous media, principally
soils :
Dfa* - Da ("air
where :
*
D,. = apparent diffusion coefficient of compound in food-air
ra , / . .
(cm /s) ; 2
D = diffusion coefficient of compound in vapor (air) (cm /s) ;
3.
air = food-air-filled porosity (ml/ml);
n_ = food (total) porosity (ml/ml)
The food-air-filled porosity (n . ) in equation (B-23) can be
estimated from the (total) food porosity (nf) and the food water content
m (ml/ml) :
n . = n_ - m (B-24)
air f v
Food porosity is not a commonly reported parameter, however, it may
sometimes be found in the literature. For example, Roman et al . (1979)
reported a porosity of 0.225 for apples. The diffusion coefficient for
the pollutant in air (D ) must also be obtained in order to use equation
B-27. It is not expected that these would generally be available. Such
coefficients can, however, be estimated using the methods described in
Tucker and Nelken (1982). The duration of time that a food particle is
exposed to contaminated air is dependent on the processing of the food.
For example, air is blown onto fruits to separate them after harvesting.
Each fruit may only be exposed to the air for a brief period of less than
an hour. On the other hand, storage of the fruit in a warehouse which
has been sprayed with a pesticide will expose the fruit for a longer
period of time. The mass and surface area of the food piece exposed
depends on the type of food, the processing method, and the processing
stage .
Additional relationships between diffusion coefficients and
temperature or pressure have been developed for soils by Farmer et al .
(1980) and Hamaker (1972) and could probably be employed in this type of
analysis if desired. In general, however, equations B-22 and B-23 should
be used with caution, since their validity for food is uncertain.
The flux (F ) is a function of the concentration in the food air,
Cf , and of time. In order to present this _variable rate for a
non-contaminated food piece, an average flux rate F.. is used.
F = Fj^/2 for Cfa = 0 at t=0 (B-25)
While an exponential function could be used to estimate a flux F. ,
the rate constant is unknown, and it would be necessary to calculate it
110
-------
iteratively over time. As a simplication, it was assumed that the use of
an average flux would provide an adequate representation of the system.
Once FI has been estimated, the pollutant concentration in the food
can be estimated from:
C = C. + (F A t)/M (B-26)
where
C = concentration of the pollutant in the food after time t
(ug/kg)
C. = initial pollutant concentration in food (ug/kg) .
FI - average pollutant mass flux across food surface (ug/cm s)
t = time (s)
M = mass of food piece (kg) -
A = surface area of the food piece (cm )
This method estimates an average concentration in the food. The
concentration at various points in the food piece will vary, however,
depending on the time exposed. In addition, for the irregularly-shaped
food piece, a radius can be calculated assuming a spherical piece of
equal volume.
This model does not consider the deposition of particulates, which
would largely depend upon particle size. Once deposited on the food, the
chemical may be absorbed. This could occur through solubilization or
volatilization and diffusion into the food item. For methods of
estimating uptake from particulate deposition, see Section B.4.1.
In addition, this model considers diffusion through air spaces in
the food to be the only mechanism for absorption from air. It is unknown
how accurately this may represent the actual case. It is presented here
as a first attempt at representing the diffusion of vapors in food
pieces.
B.5.1.1.2 Diffusion from External Liquid to Food Liquid
Equations similar to the equations above may be used for
liquid-to-liquid diffusion:
F2 - °fm (Cel
where:
F_ = pollutant mass flux across food surface in Pathway 2
^ (ug/cm s); 2
D,, = apparent diffusion coefficient in food moisture (cm /s) ;
C . = concentration of the pollutant in the external liquid medium
(ug/ml);
C,- - concentration of the pollutant in the food moisture (ug/ml)
r = approximate radius of food particle (cm)
111
-------
Equations to estimate apparent diffusion coefficients, average flux,
and concentration in food after time t, are similar to those above for
air-to-air diffusion.
B.5.1.2 Partitioning
A food matrix may consist of three phases: Food-air, food-moisture,
or water, and food-solids. A pollutant impacting a food matrix can be
"partitioned" and the pollutant can be present in all three phases: mixed
in food-air, dissolved in food-moisture, or sorbed on food particles.
The equilibrium concentration of the pollutant in each phase can be
related to the equilibrium concentration of the same pollutant in the
other phases via partition coefficients. As a result, partition
coefficients may be derived for pollutants in the various phases (e.g.,
in the air as the external medium and the food-air, the food-air and the
food-moisture, the food-moisture and the food-solids).
Partition coefficients are derived from laboratory experiments
conducted under constant temperature and primarily for pollutants
partitioning between liquid (moisture) and solid phases in a porous
medium (i.e., adsorption experiments). The experimental results lead to
formulation of partitioning, isotherm, or adsorption equations.
B.5.1.2.1 Moisture-Solid Partitioning
The moisture - solid partitioning coefficient often used is the
Freundlich isotherm expressed by:
x/M - KC (B-28)
where:
s = adsorbed concentration of contaminant on food particles;
(ug/g food)
x = adsorbed pollutant mass on/in food; (ug)
M = mass of food; (g)
K = adsorption (partitioning) coefficient; (ug/g)/(ug/ml)
C = dissolved concentration of pollutant in external liquid;
(ug/ml)
n = Freundlich isotherm parameter.
Equation (B-28) can also be used for internal partitioning between
any two phases (e.g., pathway #3, Figure 8).
B.5.1.2.2 Moisture-Air Partitioning
The moisture-air partitioning coefficient used is the Henry's law
Constant, expressed by:
C,. = C,. H/RT (B-29)
fa rm
112
-------
where:
C,. = concentration in food-air (ug/ml) ;
13.
C,_ = concentration in food-moisture (ug/ml) ;
tm
3
H = Henry's law constant (m atm/mol);
R = gas constant (8.2xlO~ m atm/mol. °K)
T = temperature (°K).
B.5.1.2.3 Partitioning Coefficient. K
The value of the partitioning (adsorption) coefficient K of equation
(B-28) can be measured in laboratory experiments. Food/water partition
values, however, are not commonly reported in the literature. Of the
more common solvents, n-octanol is believed to best imitate the lipid
content in plants (Kenaga and Goring 1980). Therefore, partitioning may
be estimated from an octanol/water partitioning coefficient (K ) and the
relationship:
K - K (% lipid)/100 (B-30)
The above equation has been adapted from a similar equation derived
for organic soils, which may have an organic content of 0.2-6%. In
comparison, Table 32 summarizes the components of various food items.
Note that the organic content of foods spans a much wider range than does
the organic content of soil.
The above equation assumes equilibrium conditions, and that the
surface area of the food is equivalent to that of soil particles for
which the K is measured. This may be a reasonable assumption for small
food particles, but may have to be corrected for larger chunks of food
with a low surface/volume ratio.
B.5.1.3 Application of Methods
The above sections have presented a variety of equations that
purport to represent pollutant migration. It is assumed that they apply
to food, since they have been shown to apply to other porous substances.
However, the validity of these models is unknown for the situations
described above.
Independent equations for diffusion and partitioning have been
described, when, in fact, they are interrelated. Figure 9 shows how to
apply the various equations described above. These terms are all
relative, and will take some practice to determine the best methods to
use. This diagram is intended to indicate that if the size of the food
piece is small, and the time is large, partitioning assumptions can be
used. If the time of contact is short and the food piece is large,
diffusion considerations are more appropriate. The concentration of the
pollutant in the external medium, the apparent diffusion Coefficient in
the food, and the organic content of the food must also be considered in
choosing the most appropriate method.
113
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TABLE 32
WATER, PROTEIN, FAT, AND CARBOHYDRATE DISTRIBUTION OF
FRESH UNCOOKED FOODS
Approximate Range of Composition (%)
Food Group
Grain and
legume seeds
Fatty nuts
Vegetablegreen
foliage, stems,
roots
"Juicy" fruit
(pome, citrus,
berries, etc.)
Fatty, juicy
fruits (coconut
and avocado)
Meat (beef,pork)
Poultry
Fish
Seafood
Water
74-94
74-94
Protein
Fat
Carbohydrate
11-12.6 7.5-23.8 1-1.8 59.4-78.8
2.6-5.3 3.4-26.9 34.5-73.0 11-23.6
0.1-7.5
0.3-1.4
0.2-1.4
0.1-1.4
1.9-31.
4.0-14.9
45-67
33-71
66-77
72-81
78-85
1.7-3.4
9-21
16-30
17-30
9-18
26.4-34.7
6-66
2-18
0.1-8
0.2-2
5.1-14.
0
0
0
0.5-3
0
Source: Kenaga (1975, adapted from Spector 1956) and
USDA (1975)
114
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Equations: B-28
Or B-29
No Actio
Equations: B-28 or B-29 and
B-22 or B-27
Equations: B-22 or
B-27
C
D
Size
OM
t
Given
C: External medium concentration = high-to-low
D: Apparent diffusion coefficient (compound/food piece) = high-to-low
Size: Size of food piece = small to large
OM: Organic matter content of food = high-to-low
t: Time of food exposure to C = low-to-high
Example (indicated by *)
FIGURE 9 EVALUATION OF NUMERICAL ESTIMATION PROCEDURES
FOR FOOD POST-HARVEST
(DIFFUSION VS. PARTITIONING)
115
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B.5.2 Food in Contact with Surfaces
Food may contact various surfaces, including harvesting equipment,
preparation or storage surfaces, and packaging. The potential for
contamination occurring via these pathways depends upon the likelihood of
the chemical migrating out of the material contacting the food, and the
propensity of the food for taking it up. These issues are described in
detail in a methodology for estimating migration rates of additives and
impurities from porous materials (Schwope et al . 1984). This methodology
was specifically designed for the migration of pollutants from polymeric
materials. These substances would commonly contact food, but the
methodology may apply to other porous materials as well.
2
The maximum amount of chemical (g/cm ) that could migrate out of a
porous surface at any time, t, is given by:
Mt - 2 %
-------
where:
Cf = the final concentration of the pollutant in the food (ug/kg);
C. = the initial concentration of the pollutant in the food
(ug/kg);
C = the concentration of the pollutant in the substance being
added to the food (ug/kg);
M = the mass of the substance being added (kg);
M- the mass of the food to which the substance is added (kg) .
B.6 CHEMICAL LOSSES
B.6.1 Potential Pathways of Pollutant Loss
Previous sections of the report have concentrated on the
identification of pathways of food contamination and the presentation of
quantitative methods for assessing these pathways. The intent was to
provide methods for determining a chemical's potential for food
contamination. The implicit assumption has been that if a food item is
contaminated at one stage, that pollutant persists at the same
concentration and in the same form until it is consumed. Obviously this
is not a realistic assumption, although it provides a simple means of
estimating exposure. Pollutants can be lost or degraded in food during
the same stage in which they are contacted, or in subsequent stages. In
fact, these losses can be quite substantial. Ferreira and Seiber (1981)
reported about 36% loss by root exudation, and 6% by volatilization from
rice plants that had been systemically treated with carbofuran. Table 33
shows losses of some pesticides from spinach in washing and blanching.
These results suggest that losses can be great. However, these situations
represent a foliar application of a pesticide, and probably largely
surface contamination. Similarly, peeling has been shown to decrease
pesticide residues up to 90% (Geisman 1975). However, if the pollutant
is taken up through the roots, surface treatments (i.e., washing and
peeling) are not likely to have a significant effect on residues.
Chemical losses from food have been considered to a large extent in
the context of vitamin loss or the reduction of pesticide residues
(Geisman 1975; Lund 1975; Krochta and Feinberg 1975). While this work
provides insight into the possible pathways of pollutant loss, the
sources of contamination and the chemical properties may be different for
many other compounds. Table 34 shows the potential pathways for
pollutant losses from food. The relative importance of these pathways
depends upon the type of food, the conditions, and the physical and
chemical properties of the chemical.
B.6.2 Methods for Assessing Chemical Losses From Food
Most of the methods discussed in Section B-5 describing migration of
contaminants into food can be utilized to assess losses. In the case of
diffusion, the concentration gradient would force movement of the
pollutant from the food. Where partitioning or equilibrium conditions
are utilized, movement in both directions is assumed. The pathways of
loss for which no methods are available are those involving chemical
degradation. Thermal degradation appears to be an important loss
117
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TABLE 33 REMOVAL OF PESTICIDE RESIDUES
FROM SPINACH BY BLANCHING AND WASHING PLUS BLANCHING
Compound Removal (%) by
Blanching Washing and Blanching
DDT 48 60
Carbaryl 84 97
Parathion 61 71
Source: Farrow et al. 1969
118
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TABLE 34
PATHWAYS OF POLLUTANT LOSS FROM FOOD
Stage
Loss Pathway
Food Generation Stages
Plants
Guttation and
volatilization
Root exudation
Photolysis
Metabolism
Animals
Metabolism
Post Harvest Stages
Plants
Animals
Volatilization
Thermal degradation
Leaching (diffusion)
Physical - peeling,
trimming
Volatilization
Thermal degradation
Leaching (diffusion)
119
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mechanism for some chemicals (Geisman 1975). Empirical models have been
developed to predict loss of some chemicals in food. For example,
Williams and Nelson (1974) presented rate constants for the thermal
degradation of methylmethionine sulfonium ions (precursor of dimethyl
sulfide) in sweet corn and tomatoes, and Wanninger (1972) predicted the
stability of ascorbic acid in food products. However, these models have
empirically-derived rate constants and are not generalizable for other
chemicals.
120
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APPENDIX C
EXAMPLE OF PATHWAYS APPROACH AND QUANTITATIVE METHODS
C.1 INTRODUCTION
This appendix describes the application of the pathways
identification methodology and quantitative methods from Appendices A
and B, respectively, to benzanthrone. The other parts of the overall
methodology to assess dietary intake are described in Section 4.0. The
application of the pathways identification methodology (Step 3 of the
overall methodology) will be described first. The relevant quantitative
methods (Step 4 in the overall methodology) are then applied to the
significant pathways from the pathways methodology.
C.2 PATHWAYS IDENTIFICATION METHODOLOGY
Chemical - Benzanthrone
Production - Benzanthrone is produced by up to 6 companies in eight
locations. The current production volume is unknown, but was 376 kkg in
1974.
Uses - The primary use of benzanthrone is as an intermediate in the
production of dyes. It is also used to manufacture 3-methoxybenzan-
throne, which is used as a luminophore.
Important Properties
Water solubility 1.5 x 10 moles/L
Vapor Pressure 6.9 x 10 mm Hg @ 25° C
Physical State at Room Temperature . Solid
Log K 3.88 ..
ow -11
Henry s Law Constant 6.0 x 10 atm m3/mol
Soil Adsorption Coefficient (K ) 3700
oc
Bioconcentration factor (fish) 523
C.2.1 Identify Situations of Release
Since the chemical is used only as an intermediate, releases would
be largely from production facilities, the locations of which are known.
Locations where it may be used in the production of dyes are unknown.
For the purposes of an example it was assumed that the chemical is
released to surface waters in the vicinity of production facilities,
resulting in a concentration of about 10 ug/L in surface water. No
other situations of release are expected for this chemical. The low
vapor pressure of benzanthrone suggests that releases to air would not
be significant. In addition, the extremely low Henry's Law constant
suggests that volatilization from water would be unimportant.
C.2.2 Identify Situations of Direct Contact or Addition
No situations of direct contact are anticipated for this chemical
since it is not used as a food additive in any of the food chain access
stages.
121
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C.2.3 Identify Pathways for Indirect Contamination Routes
An examination of Table 17 shows the various pathways of food
contamination which can result upon release to ambient waters. While
the locations of the production facilities are known, the identification
of uses of receiving waters for fishing, irrigation or as a drinking
water supply for livestock and poultry is not easily accomplished.
Therefore, since the pathways were limited by the types of release, it
was thought useful to include as relevant all pathways originating from
contaminated surface waters. The relevant contamination pathways are
shown in Table 35.
C.2.4 Identify Most Significant Pathways
A prioritization scheme for relevant pathways is found in Table 23.
Since an estimate of the concentration of benzanthrone in ambient water
is available, this scheme can be started at (4) Mobility from
compartment to food. Table 36 shows the scorings for the relevant
pathways. While this table is done on a very subjective basis, it does
provide a framework for prioritization. The ingestion of drinking water
by poultry and livestock is shown as a more significant pathway than the
others, as the octanol-water partition coefficient is greater than 3.5,
suggesting that the substance may bioaccumulate in animals (Garten and
Trabalka 1983). The bioconcentration factor in fish is not particularly
high, thus the score of 2 for mobility. Uptake from irrigation water
was thought to be limited, due to the low solubility and the high
adsorption coefficient. Adsorption to soils may, however, be important.
Food in the post-harvest stages was scored as a 3 because in some cases
the water may be a component of the food item. All pathways received a
score of 2 for the number of steps because the compound was directly
released to water which contacted food in some form.
The amount of food contaminated cannot be evaluated at this point
in the analysis as described above in C.2.3. Thus, the most significant
pathways appear to be ingestion of drinking water by livestock and
poultry, the contamination of food in the post-harvest stages by
processing water which may contact or be incorporated into the food
item, and absorption from ambient water by fish.
C.3 QUANTITATIVE METHODS
Estimation methods may be applied to each of the significant
pathways identified above.
C.3.1 Ingestion of Drinking Water By Livestock and Poultry
The screening value discussed in Appendix A of K =3.5 suggests
that this pathway can justifiably be identified as significant. The
equation for estimating pollutant concentration in edible tissue is:
CT - BFf (F) CD
Using the method of Kenaga (1980) and a log K of 3.88,
122
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TABLE 35 RELEVANT CONTAMINATION PATHWAYS FOR BENZANTHRONE
Source of Human Exposure
Meat - beef
dairy cows
hogs and pigs
sheep and lamb
poultry
Pathway of Contamination
ingestion of drinking
water
dermal absorption from
water
Fish
absorption from water
Plant - field crops
vegetables
berries
orchard fruits
uptake from irrigation
water
Food Post Harvest
absorption/addition of
water used in processing
123
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TABLE 36 SCORING OF RELEVANT CONTAMINATION PATHWAYS
FOR BENZANTHRONE
Pathways
Ingestion of
drinking water
Source of
Human Exposure
Beef
Dairy
Hogs and Pigs
Sheep and Lamb
Poultry
Fish
Field crops
Vegetables
Berries
Orchard Fruit
Food Post absorption/addition
Harvest of water used in processing
Absorption from
water
Uptake from
irrigation water
Score
Mobility
to Food
3
3
3
3
3
2
1
1
1
1
i 3
Number of
Steps
2
2
2
2
2
2
2
2
2
2
2
Total
5
5
5
5
5
4
3
3
3
3
5
124
-------
log BF - -3.457 + 0.500 log K = -1.5
BF* = 0.03 °W
Assuming a fat content in beef of 15%
C = 0.03 (0.15) (10)
= 0.045 ug/kg in beef.
The screening level of Garten and Trabalka (1983) is log K <3.5
for no appreciable bioaccumulation. The value calculated above shows
very little bioaccumulation in beef, which is consistent with this
screening level.
Such an estimation involves numerous assumptions. The first
assumption is that the animal consistently receives drinking water
containing 10 ug/L. In addition, the use of Kenaga's method has
limitations, as discussed in Appendix B. It is not recommended, but is
included here only as an example of the method. It is rarely likely
that BCF- values for livestock and poultry will be available, and
concentrations resulting in these organisms cannot generally be
estimated. These BCF,. values are well correlated with those in rodents,
so that such values obtained in the laboratory may be used when
available.
C.3.2 Food -- Post-Harvest
The manufacture of beverages probably represents the largest source
of direct addition of water in food processing operations. In addition,
Table 23 suggests that bottling operations are prevalent in the U.S.
Since soft drinks, coffee and tea are 90-100% water, concentrations
close to 10 ug/L would remain in these beverages, assuming no losses.
Other items such as bread, rice, etc. incorporate water, but
concentrations would not generally be as high.
The use of process water containing benzanthrone could also result
in food contamination. Since no information was available on the types
of food potentially contaminated, apples soaking in water were chosen as
an example.
Apples contact water frequently during processing and transport in
the plant as described in Perwak et al. (1981a) and in Tables 15 and 16.
It is assumed here that an apple is totally immersed in water for 1
hour. Section B.5.1.1.2 describes the estimation methods available for
such a situation. Figure 9 displays the various processes which may be
assessed. An hour seems a short time and the food piece is relatively
large, thus diffusion would seem the more appropriate process to model.
However, for the purposes of example, partitioning will be considered as
well. Consider the flux from the liquid into the food as follows:
F2 - °fm* (Cel - Cfm>/r
- Dfm* (0'01)/5
- D,- 0.002 ug/cm sec
rm
125
-------
where C,, =0 and r - 5 cm.
fm
Jf
The apparent diffusion coefficient in food moisture Df is related
to the diffusion coefficient in water (D ) . This equation is used for
calculating D , although its applicability is unknown.
* 10/3 2 2
D_ = D (n ,. ' /n- ) cm /s
fm w wat f
The total porosity (n ) of an apple is estimated to be 0.3. (Roman
et al. 1979) The water-filled porosity n is expected to be close to
that and assumed to be 0.25. In addition, Schwope et al. (1984) showed
that D is related to a compound's molecular weight. D for
benzanthrone (mol. wt. 230) can be estimated by:
D = 2.5 x 10"5/ MW1/6 cm2/sec
w '
-5 2
= 1 x 10 cm /sec
The effective diffusivity is estimated by:
D*m = 1 x 10"5 ((0.25)10/3/ (0.3)2) cm2/sec
= (9.8xlO~3/0-09) x 10"5 cm2/sec
r o
= 1 x 10 cm /sec
-9 2
Therefore, F_ = 2x10 ug/cm /sec
-92
The average flux, F~ = F./2 = 10 ug/cm -sec.
The resulting concentration can be estimated as:
Where
Ct = °i + (F2 A t)/M
C. = 0
F^ = 10 ug/cm2 s
A 314 cm (for apple of r=5cm)
t = 360s
C = 10"9 ug/cm2 s (314 cm2) 360s/0.1kg
= 0.0011 ug/kg
If partitioning was assumed:
S = K C "
el
As shown in Equation B-30, the adsorption coefficient may be
estimated from the octanol-water partition coefficient.
K = K (% lipid)/100
= 7§90 (0.6)/100
- 45
Where apples are assumed to be 0.6% fat.
126
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The Freundlich isotherm parameter (n) Is assumed to be 1, unless
other information is available, thus
S = 45 (10 ug/L)
= 450 ug/kg
It is apparent that in this example, time has not been adequate,
and the food piece is too large, for partitioning assumptions to be
reasonable .
The uncertainties involved in this analysis are primarily
associated with the estimation of an apparent diffusion coefficient and
the adsorption coefficient required for equations B-27 and B-28,
respectively. Another important point that should be made is that most
of the compound that has diffused will be at or near the surface of the
apple. Thus, subsequent peeling and trimming could remove these
residues almost entirely. The question of time is also important. One
hour was chosen as a reasonable estimate of water contact during
processing. It would probably be similar for other fruits and
vegetables, as few fruits and vegetables are soaked for long periods of
time. In any case, a small difference in time would not affect the
result greatly. In conclusion, 1 ug/kg could probably be used as an
upper limit concentration in fruits and vegetables contaminated from
process water containing 10 ug/L benzanthrone .
C.3.3. Absorption from Ambient Water by Fish
A BCF of 523 was estimated using log K =3.88. The equation used
log BCF - 0.76 log K - 0.23 (See Table 30)
ow
Using BCF=0.048 K , a value of 364 is obtained
Using log BCF= 1.?$ log K - 1.579
BCF = 465 °°
The value for BCF therefore ranges from 360 to 520.
Using Equation B-4, and an estimated BCF of 450:
C = (BCF) C / p
ao w' w
where: C = concentration of pollutant in aquatic organism at
equilibrium (ug/kg)
BCF = bioconcentration factor for fish u
was :
thus ,
C = concentration of pollutant in water (ug/L)
p = density of water (1 kg/L)
C = 450 (10) /I
= 4500 ug/kg
127
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50272 101
REPORT DOCUMENTATION
PAGE
1. REPORT NO.
EPA 560/5-85-008
3. Recipients Accession No.
4. Title end Subtitle Methods for Assessing Exposure to Chemical
Substances - Volume 8: Methods for Assessing Environmental
Pathways of Food Contamination
5. Report Oete
9/86
7. Authorts)
Joanne H. Perwak, Joo Hooi Ong, Richard Whelan
8. Performing Organization Rept. No.
9. Performing Organization Neme end Address
Arthur D. Little, Inc.
Acorn Park
Cambridge, MA 02140
10. Project/Task/Work Unit No.
Task 149
11. Contrect(C) or Grent(G) No.
ra 63-01-6271
12. Sponsoring Organization Neme end Address
United States Environmental Protection Agency
Office of Toxic Substances
Exposure Evaluation Division
Washington. D.C. 20460
13. Type of Report & Period Covered
Final Report
14.
15. Supplementary Notes
EPA Project Officer was Elizabeth Bryan
EPA Task Manager was Lynn Delpire
Task performed under Subcontract 867-2 with Versar, Inc., Springfield, VA
16. Abstract (Limit: 200 words)
This report, one of a series of reports concerning exposure assessment, describes
methods for evaluating exposure to chemical substances in food. It is intended to
provide an approach for estimating human exposure to toxic substances in food when
those substances enter the food through environmental pathways. This methodology
provides guidelines and methods in the form of a step-by-step approach. It allows
the use of available residue data, but also provides methods for identification of
important contamination pathways based on chemical uses and properties. Estimation
methods for some contamination pathways are suggested as well as sources of informa-
tion to assist the user. An example of the application of the methodology is
provided.
17. Document Analysis e. Descriptors
b. Identlfters/Opon-Ended Terms
Exposure Assessment/Food
Toxic Substances/Food Contamination
e. COSATI Field/Group
1*. Availability Statement
Distribution unlimited
19. Security Class (This Report)
Unclassified
20. Security Class (This Page)
, Unclassified
21. No. of Paces
140
22. Price
(See ANSI-Z39.18)
See Instructions on Reverse
OPTIONAL FORM 272 (4-77)
(Formerly NTIS-35)
Department of Commerce
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