Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-1

10.0 Farm Food Chain and Terrestrial Food

Web Data

This section presents the data compilation strategies and methods implemented to

develop the representative national data set for the Farm Food Chain and Terrestrial Food Web

Modules. Data were collected to quantify parameters required to develop exposure profiles for

receptors in these respective food webs. These parameters include bioconcentration factors,

biotransfer factors, partitioning coefficients, and ingestion rates that the modules use to estimate

movement of constituents through food webs. The Farm Food Chain Module is used to assess

exposure to humans that may occur through consumption of beef, milk, and agricultural

products, while the Terrestrial Food Web Module is used to assess exposure to wildlife through

ingestion of typical terrestrial prey items.

Because many of the parameters required for the farm food chain also were applied to the

terrestrial food web, the databases that were developed contain the necessary parameters for both

food webs. The selected receptors and their respective prey preferences constitute the primary

differences between the farm food chain and the terrestrial food web; however, many of the

exposure relationships are similar. Two general databases were generated for these food webs: 

a chemical-specific database and an exposure-related database. The chemical-specific

parameters vary depending on the constituent evaluated, whereas the exposure-related database

consists of parameters that represent uptake and deposition rates, empirical correction factors,

and adjustment fractions to account for reductions in potential exposures. Sections within this

report were constructed using the two database categories (i.e., chemical-specific and exposurerelated). In reviewing the methods used to develop the chemical-specific database and the key

uncertainties (Sections 10.3 and 10.4), however, discussions are further categorized by food web. 

For this documentation, the overlapping parameters between the farm food chain and the

terrestrial food web are reviewed within the farm food chain discussions, while the parameters

specific to the terrestrial food web are the only parameters reviewed in discussions of the

terrestrial food web. 

10.1 Parameters Collected

This section presents the parameters included in each database. Parameters included in

the chemical-specific database are presented in Table 10-1, and exposure-related parameters are

presented in Table 10-2. A brief description of each parameter is provided for clarity. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-2

Table 10-1. Farm Food Chain and Terrestrial Food Web Chemical-Specific Parameters

 Parameter Unit Description Module

ChemBa_{item} d/kg These biotransfer factors quantify the

fraction of constituents transferred

from food stocks (e.g., vegetation) into

beef and milk products 

FFC

ChemBs fraction Fraction of contaminant in soil that is

bioavailable relative to vegetation

FFC and TFW

ChemBr_{plant category} [μg/g DW plant]/

[μg/g soil]

Fraction of constituents in soil taken up

into plant tissues. Assessed for the

following plant categories: exposed

fruits, exposed vegetables, forage,

grain, protected fruits, protected

vegetables, roots, silage

FFC and TFW

ChemBv_ecf_plant unitless Empirical correction factor for air-toplant biotransfer factorFFC and TFW

ChemBv_{plant category} [μg/g DW plant]/

[μg/g air]

Fraction of constituents in air taken up

into plant tissues. Assessed for the

following plant categories: exposed

fruits, exposed vegetables, forage,

silage

FFC and TFW

ChemHLC (atm m3

)/mol Henry’s law constant FFC and TFW

ChemKd L/kg Soil/pore water partition coefficient FFC and TFW

ChemKoc mL/g Organic carbon partition coefficient FFC and TFW

ChemKow N/A Octanol-water partition coefficient FFC and TFW

ChemkpPar_{plant category} 1/yr Loss coefficient of particle-bound

contaminants on plant surfaces. 

Assessed for the following plant

categories: exposed fruits, exposed

vegetables, forage, silage

FFC and TFW

ChemkpVap_{plant category} 1/yr Loss coefficient of vapor-phase

constituents on plant surfaces. 

Assessed for the following plant

categories: exposed fruits, exposed

vegetables, forage, silage 

FFC and TFW

ChemRCF [μg/g WW plant]/

[μg/mL sl water]

Fraction of constituents in soil pore

water taken up into root tissue 

FFC and TFW

ChemBAF{prey type} unitless Bioaccumulation factors for small

birds, herbivorous vertebrates, small

herpetofauna, invertebrates, small

mammals, omnivorous vertebrates, and

earthworms

TFW

FFC = Farm Food Chain

TFW=Terrestrial Food Web.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-3

Table 10-2. Farm Food Chain and Terrestrial Food Web Exposure-Related Parameters

 Parameter Unit Description Module

F{item}_{cattle type} fraction Fraction of food stock (e.g., forage, grain, silage)

grown in contaminated soil. Identified for beef and

dairy cattle

FFC

Qp_{item}_{cattle type} kg DW/d Consumption rate of food stock (e.g., forage, grain,

silage) by cattle. Assessed for beef and dairy cattle

FFC

Qs_{cattle type} kg/d Consumption rate of soil by cattle. Assessed for beef

and dairy cattle

FFC

Qw_{cattle type} L/d Consumption rate of water by cattle. Assessed for

beef and dairy cattle 

FFC

Fw_{plant category} unitless Fraction of wet deposition that adheres to plant

surfaces. Assessed for the following plant categories: 

exposed fruits, exposed vegetables, forage, silage

FFC and TFW

MAF{plant category} percentage Moisture adjustment factor used to convert plant

tissue data from dry weight to wet weight. Assessed

for the following plant categories: exposed fruits,

exposed vegetables, wet leaf, protected fruits,

protected vegetables, roots

FFC and TFW

rho_leaf g/L FW Leaf density FFC and TFW

Rp_{plant category} unitless The fraction of deposition that intercepts plant

surfaces. Assessed for the following plant categories: 

exposed fruits, exposed vegetables, forage, silage

FFC and TFW

tp_{plant category} yr Duration of plant exposure to deposition on an annual

basis. Assessed for the following plant categories: 

exposed fruits, exposed vegetables, forage, silage

FFC and TFW

VapDdv cm/s Vapor-phase dry deposition velocity FFC and TFW

VGag_{plant category} unitless Empirical correction factor that accounts for

volumetric differences among aboveground

vegetation parts. Assessed for the following plant

categories: exposed fruits, exposed vegetables,

forage, silage, root.

FFC and TFW

VGbg_root unitless Empirical correction factor that accounts for

volumetric differences among roots of different plant

categories

FFC and TFW

Yp_{plant category} kg DW/m2 Crop yield for plant categories: exposed fruit,

exposed vegetables, forage, silage

FFC and TFW

FFC = Farm Food Chain

TFW=Terrestrial Food Web.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-4

10.1.1 Chemical-Specific Database

The chemical-specific parameters used in the farm food chain and the terrestrial food web

are provided in Table 10-1. The terrestrial food web uses the same chemical-specific parameters

as the farm food chain, with the exception of biotransfer and bioavailability factors that are used

to quantify uptake in farm food chain receptors (i.e., ChemBa and ChemBs). In the terrestrial

food web, these parameters were not applied; rather, parameters were included to characterize

the uptake of constituents into various terrestrial prey items (e.g., ChemBAF{prey type}). 

10.1.2 Exposure-Related Database

The exposure-related parameters in the farm food chain and the terrestrial food web are

provided in Table 10-2. The exposure-related parameters for the terrestrial food web are the

same as the farm food web parameters, except that the parameters specific to cattle type, which

are relevant only to human exposure, are not included in the terrestrial food web (i.e.,

F{item}_{cattle type}, Qp_{item}_{cattle type}, Qs_{cattle type}, and Qw_{cattle type}). 

10.2 Data Sources

This section presents the primary data sources identified to develop the databases and

information by food web type rather than by database type. In general, data were compiled for

the farm food chain and terrestrial food web database from data reviews, as well as the primary

literature. 

10.2.1 Farm Food Chain

The majority of the information for the farm food chain database was take from two

U.S. Environmental Protection Agency (EPA) documents: 

(1) Methodology for Assessing Health Risks Associated with Multiple Exposure

Pathways to Combustor Emissions (U.S. EPA, 1998) and 

(2) Parameter Guidance Document (U.S. EPA, 1997a). 

Although both were draft documents currently under review, they were the preferred data

sources because they were developed in accordance with EPA’s policies and standards. All

available data from these two sources were compiled, and then the remaining data gaps were

filled using values derived in data base development for the 1995 Hazardous Waste

Identification Rule (HWIR) (Research Triangle Institute [RTI], 1995) and other more current

primary references. The data sources consulted to assemble the databases are presented in

Tables 10-3 and 10-4 for chemical-specific and exposure-related parameters, respectively. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-5

Table 10-3. Data Sources for Farm Food Chain Chemical-Specific Parameters

ChemBa_{item}

Dioxin and Organics

Travis, C.C., and A.D. Arms. 1988. Bioconcentration of Organics in Beef, Milk, and Vegetation. 

Environmental Science and Technology, 22:271.

Mercury and Metals

Baes, C.F., III, R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. A Review and Analysis of Parameters for

Assessing Transport of Environmentally Released Radionuclides Through Agriculture. Oak Ridge National

Laboratory, ORNL-5786. Oak Ridge, TN.

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center

for Environmental Assessment, NCEA-0238.

ChemBs

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center

for Environmental Assessment, NCEA-0238.

ChemBr_{plant category}

Organics

Travis, C.C., and A.D. Arms. 1988. Bioconcentration or Organics in Beef, Milk, and Vegetation. 

Environmental Science and Technology, 22:271.

Mercury

U.S. EPA (Environmental Protection Agency). 1997d. Mercury Study Report to Congress. Volume III - Fate

and Transport of Mercury in the Environment. EPA 452/R-97/005. Office of Air Quality Planning and Standards

and Office of Research and Development, Washington, DC.

Metals

Baes, C.F., III, R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. A Review and Analysis of Parameters for

Assessing Transport of Environmentally Released Radionuclides Through Agriculture. ORNL-5786. Oak Ridge

National Laboratory, Oak Ridge, TN. September. pp. 1–150.

U.S. EPA (Environmental Protection Agency). 1999. Estimating Risk from the Use of Agricultural Fertilizers

(Draft Report). Office of Solid Waste, Washington, DC. August. Available online at

http://www.epa.gov/epaoswer/hazwaste/recycle/fertiliz/risk/index.htm

ChemBv_ecf_plant

U.S. EPA (Environmental Protection Agency). 1998. Methodology for Assessing Health Risks Associated with

Multiple Exposure Pathways to Combustor Emissions. EPA, National Center for Environmental Assessment,

NCEA-0238.

ChemBv_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center

for Environmental Assessment, NCEA-0238.

Simonich, S.L., and R.A. Hites, 1994. Vegetation-atmosphere partitioning of polycyclic aromatic hydrocarbons. 

Environmental Science and Technology 28:939-943.

ChemkpPar_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center

for Environmental Assessment, NCEA-0238.

(continued)
Table 10-3. (continued)

Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-6

ChemkpVap_{plant category}

U.S. EPA (Environmental Protection Agency). 1998. Methodology for Assessing Health Risks Associated with

Multiple Exposure Pathways to Combustor Emissions. EPA, National Center for Environmental Assessment,

NCEA-0238.

ChemRCF

RTI (Research Triangle Institute). 1995. Technical Support Document for the Hazardous Waste Identification

Rule: Risk Assessment for Human and Ecological Receptors, Volumes 1 and 2, 1995. Prepared for U.S.

Environmental Protection Agency, Office of Solid Waste. Prepared by Research Triangle Institute.

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center

for Environmental Assessment, NCEA-0238.

Table 10-4. Data Sources for Farm Food Chain Exposure-Related Parameters

F{item}_{cattle type}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

Fw_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

MAF{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

Qp_{item}_{cattle type}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

Qs_{cattle type}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

Qw_{cattle type}

Harris B., Jr., and H.H. Van Horn. 1992. Water and Its Importance to Animals. Circular 1017, Dairy Production Guide, Florida

Cooperative Extension Service. Available online at http://hammock.ifas.ufl.edu/txt/fairs/2607.

University of Nebraska Cooperative Extension. 1998a. Water Requirements for Beef Cattle. Cooperative Extension, Institute of

Agriculture and Natural Resources, University of Nebraska-Lincoln. 

Available online at http://www.ianr.unl.edu/pubs/beef/g372.htm.

University of Nebraska Cooperative Extension. 1998b. Water Quality and Requirements for Dairy Cattle. Cooperative Extension,

Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln. Available online at 

http://www.ianr.unl.edu/pubs/dairy/g1138.htm.

USDA (U.S. Department of Agriculture. 1998. Statistical Highlights 1997-98: Livestock. USDA National Agricultural Statistics

Service. Available online at http://www.usda.gov/nass/pubs/stathigh/1998/lv-ca-sl.htm.

rho_leaf

U.S. EPA (Environmental Protection Agency). 1998. Methodology for Assessing Health Risks Associated with Multiple Exposure

Pathways to Combustor Emissions. EPA, National Center for Environmental Assessment, NCEA-0238.

(continued)
Table 10-4. (continued)

Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-7

Rp_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

tp_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

VapDdv

U.S. EPA (Environmental Protection Agency). 1998. Methodology for Assessing Health Risks Associated with Multiple Exposure

Pathways to Combustor Emissions. EPA, National Center for Environmental Assessment, NCEA-0238.

VGag_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

VGbg_root

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

Yp_{plant category}

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA, National Center for Environmental

Assessment, NCEA-0238.

10.2.2 Terrestrial Food Web

Terrestrial food web parameters not included in the farm food chain discussion consisted

of chemical uptake factors for terrestrial prey items. The search strategy implemented for

identifying terrestrial uptake factors consisted of two basic steps: surveying current compendia

and databases and conducting a focused online literature search to identify key resources specific

to constituents and prey items. 

# Survey of current compendia and databases: This step consisted of identifying

databases compiled by other government agencies outside EPA (e.g., the National

Oceanic and Atmospheric Administration [NOAA]) and private laboratories and

ongoing database development at RTI in support of other Office of Solid Waste

(OSW) projects. The survey of compendia helped to identify key review papers

and current work being conducted on particular receptors and constituents. In

addition, EPA and other government Web sites were searched to identify new or

updated databases that could be easily accessed.

# Focused online literature searches: The survey results identified papers on

uptake factors that were used to inform and focus the online literature search. 

Online searching primarily used the Toxline/Medline reference databases. 

The key sources identified to collect uptake data for the terrestrial food web are presented in

Table 10-5. To quantify uptake into terrestrial plants, the farm food chain parameters for

ChemBr forage parameters were adopted. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-8

Table 10-5. Data Sources for Terrestrial Food Web Chemical-Specific Parameters

Vertebrates1

Garten, C.T., Jr., and J.R. Trabalka. 1983. Evaluation of models for predicting terrestrial food chain behavior of xenobiotics. 

Environmental Science and Technology 590-595.

Rowe, C.L., O.M. Kinney, A.P. Fiori, and J.D. Congdon. 1996. Oral deformities in tadpoles (Rana catesbeiana) associated

with coal ash deposition: Effects on grazing ability and growth. Freshwater Biology 36:723-730.

Sample, B.E., J.J. Beauchamp, R.A. Efroymson, and G.W. Suter, II. 1998. Development and Validation of Bioaccumulation

Models for Small Mammals. ES/ER/TM-219. Oak Ridge National Laboratory, Oak Ridge, TN.

RTI (Research Triangle Institute). 1995. Technical Support Document for the Hazardous Waste Identification Rule: Risk

Assessment for Human and Ecological Receptors - Volumes I and II. Prepared for the Office of Solid Waste, U.S.

Environmental Protection Agency under Subcontract No. 801-01.

Earthworms

Sample, B.E., J.J. Beauchamp, R.A. Efroymson, G.W. Suter, II, and T.L. Ashwood. 1998. Development and Validation of

Bioaccumulation Models for Earthworms. ES/ER/TM-220. Oak Ridge National Laboratory, Oak Ridge, TN.

U.S. EPA (Environmental Protection Agency). 1997b. Risk Assessment for the Waste Technologies Industries (WTI)

Hazardous Waste Incineration Facility. Volume VI: Screening Ecological Risk Assessment. EPA-905-R-97-002f. Region 5

Waste, Pesticides and Toxics Division. Chicago, IL.

Van Gestel, C.A.M. and W. Ma. 1988. Toxicity and bioaccumulation of chlorophenols in earthworms, in relation to

bioavailability in soil. Ecotoxicology and Environmental Safety 15:289-297. 

Invertebrates

U.S. DOE (Department of Energy). 1998b. Biota Sediment Accumulation Factors for Invertebrates: Review and

Recommendations for the Oak Ridge Reservation. BJC/OR-112. Oak Ridge, TN.

Wu, L., J. Chen, K.K. Tanji, and G.S. Banuelos. 1995. Distribution and biomagnification of selenium in a restored upland

grassland contaminated by selenium from agricultural drain water. Environmental Toxicology and Chemistry 14(4):733-742.

1 Vertebrates include small mammals, small birds, small herpetofauna, omnivorous vertebrates, and herbivorous vertebrates.

10.3 Methodology

The review of methods implemented for developing these databases was first organized

around the two types of data generated (i.e., chemical-specific and exposure-related); within

these descriptors, methods are presented for the farm food chain and the terrestrial food web. 

Because parameters unique to the terrestrial food web comprise chemical-specific parameters

only, a discussion of the terrestrial food web was not necessary under the exposure-related

database. Methods are presented on a parameter-specific basis. The final values adopted into

the databases are presented in Appendix 10A for the chemical-specific database and Appendix

10B for the exposure-related database. Note that some chemical-specific parameters included in

the database are not included in the methods discussion. These parameters include ChemHLC,

ChemKow, ChemKd, and ChemKoc. Values for these parameters were supplied by EPA’s

Office of Research and Development (ORD), Athens, Georgia. 

10.3.1 Chemical-Specific Database

This section presents the methods used to identify chemical-specific data for the Farm

Food Chain and Terrestrial Food Web Modules. Parameters related to each food web are

discussed separately. The farm food chain parameters are reviewed in Section 10.3.1.1 and the

terrestrial food web parameters are reviewed in Section 10.3.1.2. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

1 The algorithms presented below for calculating the beef (Babeef) and milk (Bamilk) biotransfer factors for

organics, respectively, are based on the work by Travis and Arms, 1988. The Agency has reevaluated these models

and developed alternatives using some of the original data and more recent studies. This work is presented in the

Ecological Soil Screening Level Guidance - Draft (EPA, 2000). In addition, OSW and the EPA Office of Research

and Development are conducting a joint investigation of Travis and Arms to continue the development of alternative

methods to predict biotransfer factors. Based on the results of that research, these models may be revised in future

versions of the 3MRA modeling system. 

10-9

(10-1)

(10-2)

10.3.1.1 Database Compilation and Processing for Farm Food Chain 

10.3.1.1.1 Biotransfer Factors.

1

 Biotransfer factors - ChemBa_beef and ChemBa_milk,

and ChemBa_water - are specific to cattle type (e.g., beef and dairy). The Farm Food Chain

Module uses biotransfer factors to calculate the total contaminant concentration in beef and milk

resulting from consumption of contaminated vegetation and drinking water. Contaminant

concentrations in plant tissue are presented in mg contaminant per kg DW of vegetative matter,

and the contaminant concentration in drinking water (either surface or groundwater) refers to the

dissolved fraction. Typically, experimentally derived biotransfer factors are preferred, but in

cases where sufficient data are unavailable, biotransfer factors are estimated based on log Kow.

For organic compounds, the following approach was implemented to develop biotransfer

factors. The octanol-water partition coefficient, Kow, can be used to estimate biotransfer factors

for beef and milk in the absence of experimental data. Travis and Arms (1988) derived empirical

relationships between Kow and biotransfer factors for beef and milk to produce estimates of

ChemBa that predict whole-beef and whole-milk concentrations on a freshweight basis given

dietary uptake of organic contaminants in terms of mass ingested/d. Equations 10-1 and 10-2

were used to estimate the biotransfer of constituents into milk and beef.

where

ChemBa_milk = biotransfer factors from plant to milk.

ChemBa_beef = biotransfer factors from plant to beef.

Kow = octanol-water partition coefficient.

These correlations were derived from experimental uptake data for milk and beef. Correlations

derived for milk were based on 28 organic constituents with Kow values ranging from 2.8 to 6.5. 

For beef, correlations were based on 36 organic constituents with log Kow values ranging from

1.3 to 6.9. The equations were applied to organics and special constituents with log Kow values
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-10

within the respective ranges. Constituents with Kow values outside the range were assigned the

default value of 1 d/kg animal tissue.

The equations used for organics were inappropriate for dioxins because the correlations

tend to overestimate the transfer of dioxins to milk and beef. For dioxins, the milk biotransfer

factor of 1E-02 d/kg animal tissue was taken from U.S. EPA (1998). This value was based on

measured biotransfer factors and was considered more representative than predicted values. The

milk biotransfer factor was converted to a beef biotransfer factor based on the assumed fat

content in beef and milk. Dioxins tend to bioconcentrate equally in the fat of beef and milk. For

this reason, the excretion of dioxins in milk is expected to be matched by the dilution of the

contaminant in beef tissue. Assuming that milk is 3.5 percent fat and beef is 19 percent fat, the

biotransfer factor for beef would be 5.4, times higher (i.e., 19/3.5) than for milk. Therefore, the

Babeef was calculated by multiplying Bamilk by 5.4, resulting in a biotransfer factor of 5.4E-02

d/kg animal tissue. This value was adopted as the beef biotransfer factor for dioxins. 

Beef and milk biotransfer factors for metals were adopted from Baes et al. (1984). Baes

et al. (1984) developed regression equations to predict the transfer of metals into beef and milk

in cattle. The total mercury biotransfer factors recommended in U.S. EPA (1997d) were adopted

for this analysis. For other metals, where data were insufficient to develop a biotransfer factor,

the default value of 2E-02 d/kg of tissue was used.

10.3.1.1.2 Bioavailability Fraction. The bioavailability fraction for soil, ChemBs,

accounts for the bioavailability of a contaminant in the soil relative to its bioavailability in

vegetation. This parameter indicates the fraction of the total chemical concentration in soil that

is predicted to be in a chemical form that is not bioavailable. In the absence of data regarding

constituent bioavailability in these respective media, this factor was assigned a default value

of 1, as recommended by U.S. EPA (1997a). 

For dioxins, a mean value derived from a reported range was adopted for this parameter. 

The fraction of dioxin that remains bioavailable as it moves from soil to plant ranged from 0.5 to

0.8; the mean of 0.65 was adopted for this analysis (U.S. EPA, 1997a). This data range was

derived from studies reporting the oral bioavailability of dioxins in rats fed dioxin-contaminated

soil. Because of the lack of data reporting the likely bioavailability of dioxin in soil, it was

concluded that rat exposures were a reasonable surrogate for cattle.

10.3.1.1.3 Soil-to-Plant Bioconcentration Factor and Root Concentration Factor. The

soil-to-plant bioconcentration factor (ChemBr) was calculated from the ratio of contaminant

concentrations in plant tissues (on a dry weight basis) to those in the soil. This parameter

accounts for uptake through the roots into all plant tissues above- and belowground. In contrast,

the root concentration factor (RCF) is the ratio of contaminant concentrations in the root tissue

of plants (on a fresh weight basis) to those in the soil. The significant difference between these

uptake factors is that RCFs are based only on the concentration of constituents in the root tissue. 

Some contaminants, such as dioxins, are taken up in plant roots and not translocated to

aboveground tissues; hence, an RCF uptake factor is more appropriate. The methods for

deriving these plant uptake factors are discussed separately here.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-11

Soil-to-Plant Biotransfer Factor

Different approaches were used for metals, organics, and dioxins. For metals, an

extensive uptake database was used to generate uptake factors for various plant categories. For

organics, uptake factors were calculated based on an empirical relationship between uptake and

log Kow. Dioxin uptake is addressed in the RCF discussion.

For metals, values for this parameter were adopted from a plant uptake database

developed by RTI for Estimating Risk from the Use of Agricultural Fertilizers, draft (U.S. EPA,

1999). The database was compiled using field and greenhouse studies of terrestrial plants

exposed to metals in which concentrations of metals in stems, roots, leaves, and fruits were

measured. The geometric mean of the compiled uptake factors was the final value adopted for

this analysis. The plant uptake database was compiled from data identified from the following

primary sources: 

# Risk-Based Concentrations for Arsenic Cadmium, and Lead in Inorganic

Commercial Fertilizers (California Department of Food and Agriculture [CDFA],

1998)

# Oak Ridge National Laboratory’s Methods and Tools for Estimation of the

Exposure of Terrestrial Wildlife to Contaminants (Sample et al., 1997)

# Oak Ridge National Laboratory’s Empirical Models for the Uptake of Inorganic

Chemicals from Soil by Plants (U.S. DOE, 1998a)

# Chaney and Ryan’s Risk Based Standards for Arsenic, Lead, and Cadmium in

Urban Soils (1994).

In developing this database, RTI evaluated plant uptake values used in similar assessments,

including the analysis conducted for EPA’s Standards for the Use or Disposal of Sewage Sludge

(40 Code of Federal Register [CFR] Part 503). Uptake factors derived for the Part 503 standards

are specific to sewage sludge matrices and as such are less applicable for estimating uptake for

this analysis. Uptake data from sewage sludge application were not included in the database

because the phytoavailability of metals is significantly lower in sewage sludge-amended soils. 

The metal adsorption capacity of sewage sludge (presumed to have different characteristics than

industrial sludge, such as more organic carbon) results in increased metal adsorption in sludgeamended soils and, thus, a decreased availability of metals for plant uptake (U.S. DOE, 1998a;

Chaney and Ryan, 1994). This is assumed to occur due to the presence of hydrous iron,

manganese, and aluminum oxides within the biosolids matrix. Therefore, considerable binding

capacity of sewage sludge may result in uptake factors that are biased toward the low end of the

range; these factors may not adequately represent typical terrestrial soil matrices.

The plant uptake database includes measured uptake values for commercial agricultural

crops as well as for native plant species. The crop data are generally taken from fertilizeramended soil, while the native species data are more likely exposed to nonamended soil. 

Furthermore, some of the data are derived from greenhouse or “pot” studies, while some data are

from field studies. Comparative studies have shown that plant uptake rates can be significantly
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

2 The algorithm shown for calculating the soil-to-plant biotransfer factor for organics (Br) is taken from

Travis and Arms, 1988. The Agency has reevaluated this model and developed an alternative model using some of

the original data and more recent studies. This model is presented in the Ecological Soil Screening Level Guidance -

Draft (EPA, 2000), and will be considered for future versions of the 3MRA modeling system.

10-12

(10-3)

higher in greenhouse and pot studies as opposed to field studies (U.S. DOE, 1998a; CDFA,

1998; Chaney and Ryan, 1994). Consideration was given to including each of these types of

data in the database. Both amended and nonamended soil data are considered appropriate

because both conditions are assumed under the exposure scenarios modeled by the 3MRA

modeling system. Regarding field versus greenhouse data, exclusion of greenhouse data reduces

the amount of useful data and, because the level of uncertainty in pot studies has not been

quantified for uptake studies, it is more desirable to work with a larger data set within the

constraints of the uncertainty. Therefore, both field and greenhouse data have been included. 

The inclusion of greenhouse data introduces uncertainty and likely alters the true distribution for

uptake factors relative to field exposures, because greenhouse data tend to result in more

conservative uptake values. The data derived from these literature searches were categorized

into the respective plant categories: vegetables (i.e., protected and exposed), fruits (i.e., protected

and exposed), forage, grain, root, and silage. 

For mercury and methylmercury, values were taken from U.S. EPA (1997d). Data were

derived from experiments conducted under reasonable garden conditions, with edible portions of

plants grown in control soil and sludge-amended soil. The values were averaged and applied

across the various plant types. Insufficient data were identified to develop mercury uptake

factors for specific plant categories.

For organics, uptake from soil and transport to aboveground plant parts depend on the

solubility of a chemical in water, which is inversely proportional to the octanol-water partition

coefficient, Kow. Travis and Arms (1988) developed an empirical relationship from field 

experiments on 29 organic chemicals to estimate uptake factors.2

 Values were calculated using

Equation 10-3 as follows:

For dioxin and furan congeners, uptake into plants through the roots was assessed using root

concentration factors (RCFs). The approach is outlined in the following section.

Root Concentration Factors (RCFs)

The RCF is an alternative estimator of the soil-to-plant uptake factor, which is used for

root crops. The RCF is defined as the ratio of the contaminant concentration in roots (fresh

weight) to that in the soil pore water ([μg contaminant/g plant root FW]/[μg contaminant/mL

pore water]). For metals and mercury translocated across the whole plant, ChemBr uptake

values for plants are more appropriate; however, in some cases (e.g., dioxins) most of the

constituent remains in plant roots and is not translocated to other tissues. For these constituents,

an RCF is a more appropriate uptake factor. For dioxins, the EPA-recommended RCF of 5,200

was used (U.S. EPA, 1997a). These values were calculated using Equation 10-4, as follows: 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-13

(10-4)

(10-5)

(10-6)

(10-7)

This relationship also was used to derive RCFs for organic and special constituents with log Kow

values less than or equal to 2. For constituents with log Kow values greater than 2, the empirical

relationship in Equation 10-5 was applied (U.S. EPA, 1997a), as follows:

10.3.1.1.4 Mass-Based Air-to-Plant Biotransfer Factor and Empirical Correction

Factor. The parameter ChemBv was used to estimate the plant contaminant concentration due to

air-to-plant transfer. This parameter was calculated from the ratio of the contaminant

concentrations in aerial plant parts (on a dry weight basis) to the concentrations in the air as

vapor. Air-to-plant transfer is likely to be important for exposed produce but not for protected

produce or root crops, because only aboveground exposed vegetation encounters deposition from

the air. With the exception of mercury, values for metals are set equal to zero because metals do

not exist in the vapor phase. 

There are few experimental determinations of ChemBv. Simonich and Hites (1994)

determined an air-to-plant biotransfer factor of 4.7E+4 for benzo(a)pyrene. All other special

chemicals were given a default of 1. Mercury and dioxin values were taken from the geometric

mean of measured values presented in U.S. EPA (1997a).

For organic constituents, air-to-plant biotransfer factors were derived according to

Equation 10-6 as recommended by U.S. EPA (1998). 

The volumetric transfer factor (Bvol) is correlated with the octanol-water partition

coefficient (Kow), Henry’s law constant (H), ideal gas constant (R), and ambient temperature (T).

The result of these calculations (Bvol) is transformed into a mass-based biotransfer factor

considering leaf density, air density, and percentage of moisture in the leaf. Bv is calculated

using Equation 10-7, as follows:
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-14

(10-8)

where

Dair = density of air (constant at 1.19 g/L)

Bvol = biotransfer factor ([μg/L FW leaf]/[μg/L air])

MAFleaf = moisture content in leaf (percentage)

Dleaf = density of leaf (g/L FW)

Bvecf = empirical correction factor for Bv (unitless). plant

For organics, the air-to-plant biotransfer factors calculated using this approach are

divided by the empirical correction factor (Bv_ecf_plant) of 100. Predicted values generated

using these equations usually result in overly conservative estimates of air-to-plant biotransfer

factors. In some cases, the difference can be up to 40 times higher than measured biotransfer

factors (McCrady and Maggard, 1993, as cited in U.S. EPA, 1998). Other research has indicated

that field-derived biotransfer factors were about 2 to 5 times lower than the values generated

using equation 10-7 (Lober, 1995, as cited in U.S. EPA, 1998). Therefore, the U.S. EPA (1998)

recommended correction factor of 100 was applied in this analysis. The rationale for using the

correction factor is based on evidence derived from dioxin exposures, but this correction factor

also was applied to ChemBv values derived for organic constituents. 

10.3.1.1.5 Plant Surface Loss Coefficients. This parameter is used to account for

environmental processes that could reduce the concentrations of constituents deposited onto

plants. The dynamics of deposition change depending on whether the constituent is in a vapor or

particulate form. The two variables required are kpPar for particulate deposition and kpVap for

vapor deposition. The methods applied to derive these parameters are presented separately.

Particulate Deposition

The plant surface loss coefficient of particle-bound contaminants, kpPar, is used by the

module to calculate plant concentration due to direct deposition. This coefficient reflects the rate

of loss of deposited constituents from the plant surface due to environmental processes (i.e.,

wind removal, water removal, and growth dilution). The coefficient is directly related to the

environmental half-life (Equation 10-8) (Miller and Hoffman, 1983, as cited in U.S. EPA,

1997a): 

In this equation, the t1/2 value (environmental half-life in days) is strongly influenced by

local conditions related to wind and precipitation. Because these data were not available on a

site-specific and chemical-specific basis, this equation could not be applied. Rather, the EPArecommended default value of 18.07 yr-1 was used for all constituents, with the exception of

mercury and dioxin (U.S. EPA, 1997a). 

For mercury and dioxin, values recommended in U.S. EPA (1997a) were applied. 

Parameters of 40.41 and 27.06 yr-1 for mercury and dioxin, respectively, were adopted for this
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-15

analysis. These values were derived as the mean of a data range that were assumed to be

lognormally distributed (U.S. EPA, 1997a).

Vapor Deposition

The plant surface loss coefficient of vapor-phase contaminants, kpVap, was used as a

variable in calculating plant tissue concentrations due to vapor deposition. The degradation of

constituents on the plant’s surface is due to environmental processes similar to the processes

mentioned earlier. For organics, dioxins, and special constituents, this coefficient was derived

by taking the midpoint of the range of 58 to 180.7 yr -1 reported in U.S. EPA (1998), which

resulted in a kpVap of 119.35 yr-1. For metals and mercury constituents, this vapor-related

parameter was not required; hence, in the database, a placeholder value of 1 was substituted. 

10.3.1.2 Database Compilation and Processing for Terrestrial Food Web

10.3.1.2.1 Bioaccumulation Factors. The only parameters exclusive to the terrestrial

food web were the chemical-specific bioaccumulation factors (referred to herein as uptake

factors) for prey items (ChemBAF). Following a short review of data selection guidelines that

were implemented in identifying appropriate uptake factors, the parameters are presented on a

prey-specific basis: vertebrates, worms, and invertebrates. 

Two general guidelines were used to identify uptake factor studies. These guidelines

were not used as strict data standards; rather, they were used to increase the level of confidence

and consistency in the values used in the database.

1. Field studies were preferred to laboratory exposures. Because field studies tend to

more accurately represent the types of exposures and uptake that occur in natural

systems, field-generated uptake factors are regarded with higher confidence than

those estimated from laboratory exposure data. For example, uptake factors

measured during laboratory exposures may overestimate uptake because biota may

be exposed to a more bioavailable form of the constituent. In contrast, processes

such as degradation and sorption that occur under field conditions tend to reduce

the uptake of constituents (e.g., by limiting bioavailability). Both field and

laboratory exposures were used because available field study data are not adequate

to develop all of the uptake factors for this analysis. Pooling both types of values,

however, introduces some uncertainty into the database.

2. For use in the 3MRA modeling system, the following units for the uptake values

were required. In terrestrial ecosystems, uptake factors were in units of kg soil (dry

weight)/kg tissue (wet weight) for most prey items. These results were calculated

by the ratio of mg constituent/kg body weight (wet weight) to mg constituent/kg

soil (dry weight).
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-16

Vertebrate Uptake Factors

Terrestrial vertebrate prey receptors included small mammals, small birds, small

herpetofauna, omnivorous vertebrates, and herbivorous vertebrates. Similar approaches were

implemented to identify uptake factors for all categories of vertebrates. A few key sources were

identified that reported uptake factors for vertebrates. In addition to the primary literature, an

additional compendium reference was used that reported uptake factors for metals and 2,3,7,8-

tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) in small mammals representing various dietary

preferences (i.e., insectivores, herbivores, and omnivores) (Sample, Beauchamp, Efroymson, and

Suter, 1998). Sample, Beauchamp, Efroymson, and Suter (1998) provided data for a general

category of small mammals. The median uptake factor generated for small mammals was

applied in this analysis. Sample, Beachamp, Efroymson, and Suter (1998) developed

mammalian uptake factors as screening estimates, and, as such, these values do not reflect

national distributions for these parameters. These uptake factors were derived from relatively

large databases, however, and the values represent some of the variability in uptake seen across

different species and dietary habits. 

Significant data gaps remained for categories of vertebrates other than small mammals. 

The values identified for small mammals were, therefore, used for other categories of

vertebrates. The variability associated with rates and physiological regulation of uptake

introduces considerable uncertainty in applying small mammal uptake factors to other vertebrate

categories. Nevertheless, these values serve as the most reasonable placeholders until exposureroute and species-specific uptake factors become available. 

Additional uptake factors for small herpetofauna were identified through primary

literature searches. The uptake factors indicating sediment exposures to amphibians that were

added to the database are presented in Table 10-6. Because sediments were the only media

exposure pathway identified for herpetofauna, these uptake factors were adopted into the

database until further soil-based uptake factors are identified. There is uncertainty with applying

sediment uptake exposures to represent soil uptake; however, these values act as reasonable

placeholders until more representative data are identified. 

Table 10-6. Uptake Factors Identified for Small Amphibians

Constituent Species Lab/Field Uptake Factors Source

Arsenic Tadpole Field 0.10 Rowe et al., 1996

Cadmium Tadpole Field 0.58 Rowe et al., 1996

Chromium Tadpole Field 0.04 Rowe et al., 1996

Lead Tadpole Field 0.17 Rowe et al., 1996

Selenium Tadpole Field 0.83 Rowe et al., 1996
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-17

(10-9)

Earthworms

Measured uptake factors for earthworms were identified in both the primary literature

and review compendia. Sample, Beauchamp, Efroymson, Suter, and Ashwood (1998) reported

uptake factors for metals in earthworms. Median uptake factors were adopted from this source

for the following constituents: arsenic, cadmium, chromium, mercury, nickel, lead, selenium,

zinc, barium, beryllium, silver, and vanadium (see Appendix 10A). Worm tissue concentrations

in Sample, Beauchamp, Efroymson, Suter, and Ashwood (1998) were reported on a dry weight

basis and, as such, had to be converted to wet weight to be consistent with 3MRA modeling

system requirements. These values were converted assuming an 84 percent moisture content in

earthworms (Sample et al., 1997). 

Additional values for 2,3,7,8-TCDD and pentachlorophenol (PCP) identified through

primary literature searches are presented in Table 10-7. Final uptake factors for 2,3,7,8-TCDD

and PCP were generated by taking the geometric mean of values presented in Table 10-7. 

Table 10-7. Uptake Factors Identified for Earthworms

Constituent Species Lab/Field Uptake Factors N Source

2,3,7,8-TCDD Not specified Not specified 15, 9.4, 0.68, 0.64, 0.47 5 U.S. EPA, 1997c

PCP E. andrei Lab 0.85, 0.54 2 Van Gestel and Ma, 1988

PCP L. rubellus Lab 0.64, 1.28 2 Van Gestel and Ma, 1988

PCP Lumbricus caliginosa Both 0.03, 0.02, 0.04, 0.14 4 Haimi et al., 1992

For organics, current methods of estimating uptake into earthworms were identified;

however, their use in the Terrestrial Food Web Module has not been reviewed. The literature

reports numerous algorithms to calculate uptake into earthworms; however, the changes in soil

composition, water content, and chemical equilibria between different soils makes applying one

uptake equation for all soils somewhat unsatisfactory. A widely used method of estimating

uptake summarized by Jager (1998) also has been applied in other EPA screening ecological risk

assessments (U.S. EPA, 1997b). The method addresses uptake into earthworms as a function of

the partitioning between soil and pore water. Concentrations of constituents in pore water are

correlated with concentrations in earthworm tissues. Jager (1998) presents the simplified

bioconcentration relationship for earthworms (Equation 10-9), as follows:

where

BCF = bioconcentration factor (L/kg worm tissue)

Fwater = concentration of constituent in the pore water (mg/L)
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-18

Flipid = fraction of lipid in earthworm tissue (unitless)

Kow = octanol-water partition coefficient for the constituent 

Pworm = bulk density of the worm tissue.

This equation results in uptake factors based on pore water exposures in units of L/kg

tissue. The Terrestrial Food Web Module requires exposures for earthworms to be converted

into units of kg soil/kg tissue. Therefore, earthworm uptake factors based on pore water

exposures need to be converted into soil exposure estimates using a soil-water partition

coefficient (Kp). The parameter Kp uses the relationship between the fraction of organic carbon

(foc) in the soil and the constituent-specific Koc to estimate the partitioning of constituents from

the soil phase to the pore water phase. Given that site-specific foc data are available, estimation

of earthworm uptake would be best represented on a site-specific basis. In addition, an

earthworm uptake factor based on site-specific foc would better reflect site-specific conditions,

increasing the resolution of exposure to terrestrial receptors. Using an uptake algorithm for

earthworms would fill some of the remaining data gaps for this prey item. 

Invertebrates

Uptake factors for invertebrate prey items were the least well-represented in the database. 

Invertebrate prey species include taxa such as terrestrial and flying arthropods and terrestrial

mollusks. The invertebrate prey item category excludes earthworms because they are considered

as a separate prey item in the database. The data collection effort evaluated peer-reviewed

approaches and data to estimate invertebrate uptake. The most relevant database identified was

developed by Oak Ridge National Laboratories (ORNL): a biota-sediment accumulation factor

(BSAF) database for aquatic insects (U.S. DOE, 1998b). 

The BSAF database contains metal uptake factors primarily for emergent insects that

spend a portion of their life in water (usually larval) before metamorphosis into terrestrial insects

(e.g., mayflies). The data address uptake of arsenic, cadmium, chromium, mercury, nickel, lead,

and zinc. The analysis done by Oak Ridge compared BSAF uptake values measured in aquatic

insects to a smaller data set of measured concentrations in terrestrial flying insects. Their

findings indicate a correlation between BSAFs in aquatic insects and accumulation in terrestrial

insects. The data suggest that BSAFs for benthic aquatic insects can be used to estimate uptake

in emergent insects. Some of the comparisons done between aquatic and emergent insect uptake

factors indicate that aquatic insect uptake factors tend to underestimate uptake in emergent

insects; therefore, the more conservative 90th percentile of the data was recommended for

screening-level assessments. The recommended values were adopted as uptake factors for

invertebrates in the Terrestrial Food Web Module. Because these data were presented in terms

of dry weight, they were converted to wet weight assuming an 80 percent moisture content for

aquatic insects (Sample et al., 1997).

Uptake factors for invertebrates were reported for depurated insects, nondepurated

insects, and both combined. The category that combined both types of data were used for this

analysis. Typically, uptake factors based on depurated organisms are preferred, but given the

lack of data for this category, the variability in this parameter was better represented by

combined data.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-19

Uptake factors for selenium in terrestrial insects based on soil concentrations were

derived from an additional source (Wu et al., 1995). A summary of the selenium uptake factors

identified and incorporated into the database for terrestrial invertebrates is presented in

Table 10-8. The geometric mean of the reported data was used in the Terrestrial Food Web

Module (see Appendix 10A for final values).

Table 10-8. Uptake Factors Identified for Invertebrates

Constituent Species Lab/Field Uptake Factors N Source

Selenium Grasshopper Field 1.0, 1.0, 1.9, 4.0, 0.11, 11, 0.21 7 Wu et al., 1995

Selenium Mantis Field 1.1, 0.78, 4.0, 9.5, 0.23, 29, 0.53 7 Wu et al., 1995

10.3.1.3 Assumptions and Uncertainties for Chemical-Specific Database. This

section reviews the key overall uncertainties as well as the parameter-specific uncertainties

associated with the chemical-specific database developed in support of the Farm Food Chain and

Terrestrial Food Web Modules. Discussions are outlined for the specific food webs. 

10.3.1.3.1 Farm Food Chain Database 

Variability

The data that were gathered did not consistently represent national distributions of

parameters. Instead, the data selected were those recommended by EPA and typically used for

diverse risk assessment applications. These data are generally thought to be representative under

most regional and climatic conditions. The fact that recommended central tendency values do not

always represent regional or national distributions introduces some uncertainty into the data

identified. 

Biotransfer Factors

The recommended default values used for milk and beef biotransfer factors have a great

deal of uncertainty (U.S. EPA, 1997a). Default values were derived based primarily on the

biotransfer of pesticides data. Evidence suggests that these data may not be appropriate for

dioxins or for organics with log Kow values outside the prescribed range for milk (log Kow range

2.8 to 6.5) and beef (log Kow range 1.3 to 6.9). Experimentally derived values are uncertain to

the extent that conditions of the study differ greatly from expected conditions in the field. Within

the constraints of these uncertainties, these values are the standard for estimating biotransfer

relationships in the farm food chain and are accepted as reasonable estimates for risk assessment

applications. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-20

Bioavailability Fraction

The bioavailability fraction has some uncertainty associated with use of the default

estimate because some chemicals may be much less bioavailable from soil than from plant

tissues. Adopting the default of 1 introduces significant conservatism in this parameter. 

Soil-to-Plant Bioconcentration Factor

Soil-to-plant bioconcentration factors are strongly influenced by the chemical and

physical properties of the soil as well as the plant species. Experimental uptake factors for

metals derived from the plant uptake database were, in some cases, higher than previously

applied uptake factors calculated using correlations developed by Baes et al. (1984). This was

probably an artifact of including both field and greenhouse studies. In spite of the added

conservatism generated by including greenhouse studies, the plant uptake database was preferred

because it contains measured uptake factors that more likely reflect typical exposure scenarios

for terrestrial plants.

Plant Surface Loss Coefficient

Estimated values for the plant surface loss coefficient for particle-bound contaminants

were taken from U.S. EPA (1997a) even though locally measured values are preferable because

of the strong influences of local conditions. U.S. EPA (1997a) noted that there was no

speciation provided for mercury in the data used to derive this coefficient; therefore, the

assumption was made that the values for each mercury species (total, elemental, and methyl)

were equal. In addition, the plant surface loss coefficient for vapor-phase contaminants is

uncertain because it is based on limited data.

10.3.1.3.2 Terrestrial Food Web Database

Data Gaps and Default Values

The large number of data gaps in the terrestrial food web data contribute to the

uncertainty in estimating exposures to upper-trophic-level consumers in the terrestrial

ecosystem. A default uptake factor of 1 was applied when uptake factors were not available. 

The default value may be high for some constituents that do not significantly bioaccumulate. 

For example, food chain impacts associated with the transfer of constituents to higher trophic

levels are not expected to occur for volatile compounds and semivolatile compounds (e.g., vinyl

chloride, methylene chloride, trichloroethylene). Typically, compounds with log Kow values less

than 3.5 do not bioaccumulate to a significant degree. Moreover, many of these compounds

volatilize before they are taken up into biota. Further, some of these compounds can be

metabolized by enzymatic detoxification mechanisms. In these cases, the default of 1 may

overestimate uptake into the tissue. For other compounds, such as benzo(a)pyrene, which have a

higher log Kow value and may bioaccumulate to a more significant degree in prey items, the

default value of 1 may underestimate uptake. Data gaps introduce uncertainty into the analysis

by limiting the ability to capture the true nature of ingestion exposure for some receptors.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-21

Parameter Variability

Uptake factors used in the terrestrial food web are not derived from national or regional

distributions and, therefore, do not necessarily reflect the variability inherent in these parameters. 

Rather, the data identified represent median point estimates of uptake for each prey item

category. Uptake factors for a particular prey item vary across species, dietary preferences,

seasonal resource requirements, and climatic conditions. For instance, Sample, Beauchamp,

Efroymson, and Suter (1998) indicated that vertebrates of varying dietary preferences (i.e.,

herbivores, omnivores, insectivores) accumulate contaminants to different degrees. There is

uncertainty associated with the uptake factors derived for prey items in the representative

national data set because the variability in parameters is not represented in a central tendency

value. 

Vertebrate Uptake Factors

For vertebrate prey items, values identified for small mammals also were applied to other

vertebrate prey items. The variability associated with rates and physiological regulation of

uptake introduces considerable uncertainty in applying small mammal uptake factors to other

vertebrate categories. Nevertheless, these values serve as reasonable placeholders until

exposure-route and species-specific uptake factors become available. 

Invertebrate Uptake Factors

For invertebrates, uptake factors based on sediment exposure were adopted in the

absence of data quantifying exposure through the soil. This approach introduces uncertainty

because these exposure pathways are not equivalent. The primary literature reports uptake

factors on various terrestrial insects such as beetles, especially for metals; however, these data

are difficult (i.e., costly) to locate through traditional search methods because they are generally

found as secondary assessments conducted within larger site-specific risk analyses. The uptake

factors adopted from the Oak Ridge work (U.S. DOE, 1998b) represent the best alternative in the

midst of current data limitations. 

Amphibian Uptake Factors

As indicated in the discussion of uncertainty for invertebrates uptake factors, amphibian

uptake factors identified during primary literature searches were based on sediment exposures

rather than the preferred exposure medium of soil (Canton and Sloof, 1982). The fact that

amphibians are semiaquatic, spending some of their developmental stages in water, explains the

abundance of uptake data associated with sediment exposures. Because only sediment exposure

data were identified for herpetofauna, these uptake factors were adopted until further soilderived uptake factors are identified; however, there is uncertainty with applying sediment

exposures to estimate soil uptake values.

The uptake data for amphibians were used to generate uptake factors for the prey

category of small herpetofauna. This prey category consists of both reptile and amphibian prey

items; however, the uptake factors identified in the primary literature were derived from studies
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-22

exposing amphibians. Because only amphibians are represented in the uptake data, there is

uncertainty that the uptake factors adequately represent the range for reptiles.

Finally, the values identified for small herpetofauna represent only the tadpole life stage. 

Given the differences that occur during amphibian metamorphosis, uptake rates and tissue

burden could change significantly from the tadpole to the adult life stage. The uptake factors

identified do not address this source of potential variability. 

10.3.2 Exposure-Related Parameters

This section presents the methods used to identify exposure-related data for the Farm

Food Chain and Terrestrial Food Web Modules. Because the same parameters are used for the

farm food chain and the terrestrial food web, discussions are combined. 

10.3.2.1 Database Compilation and Processing for Farm Food Chain and

Terrestrial Food Web

10.3.2.1.1 Consumption Rate of Food Items, Soil, and Water by Cattle

Plant Consumption Rate

The consumption of grain, forage, and silage (Qp) by beef and dairy cattle, expressed as a

daily rate, were adopted from U.S. EPA (1997a). Cattle ingestion rates of seven types of grain,

two types of forage, and two types of silage for both beef and dairy cattle were used to derive

this parameter. For beef cattle, the average grain, forage, and silage consumption rates are 0.47,

8.8, and 2.5 kg DW/d, respectively. For dairy cattle, the average grain, forage, and silage

consumption rates are 2.6, 11, and 3.3 kg DW/d, respectively. These measured values represent

average consumption rates for various vegetation types (i.e., grain, forage, and silage) and should

be used as defaults in the absence of site-specific values.

Soil Consumption Rate

The consumption of soil (Qs) by livestock, expressed as a daily rate, was adopted from

U.S. EPA (1997a). Soil consumption rates were used to estimate uptake of constituents into

animal tissues from inadvertent consumption of soil while feeding. Reported soil ingestion by

cattle varies from 1 to 18 percent of dry matter intake (U.S. EPA, 1997a). The EPArecommended average soil ingestion rates of 0.39 kg DW/d for beef cattle and 0.41 kg DW/d for

dairy cattle were adopted for this analysis. These values approximate 3 percent of the total dry

matter intake.

Water Consumption Rates

Water consumption rates (Qw) vary according to many factors, such as breed, body size,

air temperature, humidity, and moisture content of feed (Harris and Van Horn, 1992). In general,

dairy cattle consume 2 to 4 pounds of water for each pound of feed (dry weight) consumed and

an additional 3 to 5 pounds of water per pound of milk produced (Harris and Van Horn, 1992). 

Rations high in salt or protein increase water intake. Total water intakes consist of direct water
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-23

ingestion and water intake through feed stocks containing moisture. For instance, feeds such as

silage, green chop, or pasture have a high moisture content and contribute to overall water

intake, while grains and hays have a low moisture content (University of Nebraska Cooperative

Extension, 1998a).

In beef cattle, the average daily water intake of a 1,200-pound cow ranges from 9.5 gal/d

(36 L/d) in December and January to 23.0 gal/d (87 L/d) in July (University of Nebraska

Cooperative Extension, 1998a). Table 10-9 summarizes water consumption rates of beef cattle

across different body weights. For beef cattle, the water intake value of 14.0 gal/d (53 L/d) was

used for this analysis. This value was derived as the average water intake on an annual basis of a

1,200-pound beef cow. The water consumption rate was appropriate because it reflected a fully

mature beef cow, and it accounted for the annual variation of water intake in this farm food chain

receptor.

In dairy cattle, a value of 24.2 gallons of water per day (92 L/d) was derived for this

analysis by taking the average of data measured by Harris and Van Horn (1992) (Table 10-10). 

These data reflect the variability in water consumption of dairy cows across different

temperatures and milk production rates. This value falls within the water consumption ranges

reported for other cow breeds by the University of Nebraska Cooperative Extension (1998b). In

these data, the average daily water intake of Jersey cows producing 30 pounds of milk per day

ranged from 13.0 to 15.5 gallons of water per day (49 to 59 L/d). The average daily water intake

of Ayrshire, Brown Swiss, and Holstein cows producing up to 100 pounds of milk per day

ranged from 48.0 to 52.0 gallons (182 to 202 L/d) of water per day (University of Nebraska

Cooperative Extension, 1998b). 

Table 10-9. Daily Water Intake of Beef Cattle (gal/d)

Month

Average

Maximum

Temperature

Body Weight of Finishing Cattle

600 lb 800 lb 1,000 lb 1,200 lb

January 36 °F 5.5 7.0 8.5 9.5

February 40 °F 6.0 7.5 9.0 10.0

March 50 °F 6.5 8.0 9.5 10.5

April 64 °F 8.0 9.5 11.0 12.5

May 73 °F 9.0 11.0 13.0 14.5

June 78 °F 9.5 12.0 14.0 16.0

July 90 °F 14.5 17.5 20.5 23.0

August 88 °F 14.0 17.0 20.0 22.5

September 78 °F 9.5 12.0 14.0 16.0

October 68 °F 8.5 10.0 12.0 14.0

November 52 °F 6.5 8.0 10.0 10.5

December 38 °F 6.0 7.0 8.5 9.5

Source: University of Nebraska Cooperative Extension, 1998a.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-24

10.3.2.1.2 Fraction of Food Items Grown in Contaminated Soil. The fraction of each

food item (i.e., forage, grain, silage) (F) is used in the Farm Food Chain Module to account for

the dietary fraction of contaminated cattle feed. This parameter varies depending on sites,

regions, or, moreover, resource availability. A conservative default value of 1 is assumed in the

absence of data available to indicate that some portion of the feed used for livestock is not

contaminated. No data were located regarding the origin of feed stocks for livestock; hence, a

default value of 1 was adopted from U.S. EPA (1997a). 

10.3.2.1.3 Fraction of Wet Deposition that Adheres to Plants. The fraction of wet

deposition (Fw) that adheres to a plant as a result of direct deposition was used in the calculation

of plant contaminant concentrations. All contaminants that contact plant surfaces due to dry

deposition are assumed to remain on the plant surfaces until removed by weathering. Not all 

Table 10-10. Daily Water Intake of Milk-Producing Dairy Cows (gal/d)

Breed

Volume

of Milk

Produced

Mean Daytime Temperature, degrees F

Reference

Not

Specified 10-40 °F 50 °F 60 °F 70 °F 80 °F 90 °F

Jersey 30 lb/d 13 to 15.5 -- -- -- -- -- -- University of

Nebraska, 1998b

Guernsey 30 lb/d 13.8 to 16 -- -- -- -- -- -- University of

Nebraska, 1998b

Ayrshire, Brown

Swiss, Holstein

30 lb/d 14.5 to 17 -- -- -- -- -- -- University of

Nebraska, 1998b

Ayrshire, Brown

Swiss, Holstein

50 lb/d 24 to 27 -- -- -- -- -- -- University of

Nebraska, 1998b

Ayrshire, Brown

Swiss, Holstein

80 lb/d 38 to 42 -- -- -- -- -- -- University of

Nebraska, 1998b

Ayrshire, Brown

Swiss, Holstein

100 lb/d 48 to 52 -- -- -- -- -- -- University of

Nebraska, 1998b

1,400 lb cow 40 lb/d -- 15.5 17.2 18.9 20.6 22.4 24.1 Harris & Van

Horn, 1992

1,400 lb cow 60 lb/d -- 18.4 20.1 21.9 23.6 25.3 27 Harris & Van

Horn, 1992

1,400 lb cow 80 lb/d -- 21.4 23.1 24.8 26.5 28.3 30 Harris & Van

Horn, 1992

1,400 lb cow 100 lb/d -- 24.3 26 27.7 29.5 31.2 32.9 Harris & Van

Horn, 1992

contaminant material that intercepts plant surfaces from wet deposition adheres; rather, a portion

is assumed to wash off almost immediately. This parameter is a measure of the amount of wet

deposition that adheres to the plant surface. The EPA recommends a value of 0.6 for the fraction

of wet deposition that adheres to plant surfaces based on data collected during simulated

precipitation studies conducted by Hoffman et al. (1992, as cited in U.S. EPA, 1997a).
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-25

(10-10)

10.3.2.1.4 Moisture Adjustment Factor to Convert Dry Weight to Wet Weight. The

moisture adjustment factor (MAF) is used in the Farm Food Chain Module to convert a given

quantity of plant material from a fresh weight basis to a dry weight basis or vice versa. The

EPA-recommended moisture contents (as percentages) were adopted for the following plant

categories: 92 percent for exposed vegetables, 80 percent for protected vegetables, 87 percent

for root vegetables, 85 percent for exposed fruits, and 90 percent for protected fruits (U.S. EPA,

1997a).

10.3.2.1.5 Leaf Density. The plant density (rho_leaf) of 770 g/L provided in U.S. EPA

(in press) was used for this analysis. This plant density value reflects the density reported in

grasses. This density more adequately represents the types of vegetation seen in the farm food

chain than other available values. 

10.3.2.1.6 Interception Fraction for Plant. The interception fraction (Rp) for plants is

the fraction of contaminant particles deposited on the edible portion of plants. Atmospheric

deposition is a potential route of exposure for unprotected produce and forage but not for root

crops or protected produce (including grains). Plant interception fractions were adopted from

U.S. EPA (1997a) for the following plant categories: 0.052 for exposed fruits and vegetables,

0.47 for forage, and 0.44 for silage. Baes et al. (1984) estimated these average interception

fractions by taking into account the following variables: recommended field spacing of plants,

average plant/fruit sizes, growth, and exposure durations.

10.3.2.1.7 Length of Plant Exposure to Deposition. This parameter quantifies the

duration of plant exposure (tp) to the deposition of constituents per harvest in years. The

parameter only accounts for the edible portion of plants; therefore, this parameter is only applied

to exposed produce and forage, not to root crops or protected produce (including grains). Values

used in this analysis were taken from U.S. EPA (1997a). Values were derived from data

collected by the South Coast Air Quality Management District (SCAQMD) on average growing

seasons and from data collected by Belcher and Travis (1989) on the average time between hay

harvests (as cited in U.S. EPA, 1997a). The values for different plant categories are as follows:

0.123 yr for exposed vegetables, exposed fruits, and forage and 0.164 yr for silage. Insufficient

data were available to estimate exposure duration for other plant categories, and the default tp

value of 0.164 yr was used.

10.3.2.1.8 Vapor-Phase Dry Deposition Velocity. The dry deposition velocity

(VapDvd) for vapor-phase contaminants can be derived using Equation 10-10 (U.S. EPA, in

press) as follows:

where

Ra = atmospheric resistance, a function of vertical turbulent transport (s/cm)
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-26

Rb = surface boundary layer resistance, a function of molecular diffusivity (s/cm)

Rc = plant canopy/leaf resistance, a function of vegetative density, stomatal uptake,

surface effects, and humidity (s/cm).

Atmospheric resistance values, however, are difficult to assign and data are limited. Calculated

VapDvd values range from 0.01 cm/sec to 1 cm/s (Smith et al., 1995; Trapp and Matthies, 1995;

and Sehmel, 1980 as cited in U.S. EPA, in press). The EPA-recommended default value of 1

cm/s was used for this analysis (U.S. EPA, in press). As apparent from the range of values

indicated across different studies, this parameter is a conservative estimate of the velocity of dry

vapor deposition. 

10.3.2.1.9 Empirical Correction Factor for Plants. Different correction factors were

applied for aboveground and belowground plant uptake values. Each is described separately

here.

Aboveground Correction Factors

An empirical correction factor (VGag) was used to account for volumetric differences in

aboveground plant tissues in exposed fruits and vegetables, forage, and silage. Values to

quantify this parameter were taken from U.S. EPA (1997a) for the following plant categories:

0.01 for exposed fruits and vegetables, 1.0 for forage, and 0.5 for silage. The parameter VGag is

a correction factor used in calculating the contaminant concentration in plant tissue due to air-toplant transfer for organic chemicals. Vgag adjusts for differences in air-to-plant uptake between

thin leaves and bulky fruits (U.S. EPA, 1997a). This adjustment, which can be estimated as the

surface-area-to-volume ratio, is necessary because lipophilic organic chemicals transferred from

the air tend to remain localized in the surface portions of the plant rather than being distributed

to the interior portions.

Belowground Correction Factors

The empirical correction factor for belowground vegetation (Vgbg) is analogous to Vgag

and adjusts the belowground constituent concentrations for differences in root volume. The

recommended default value of 0.01 was used in this analysis (U.S. EPA, 1997a). 

10.3.2.1.10 Crop Yield for Plants. The yield or standing crop biomass (Yp) values of

the edible portion of exposed fruits and vegetables, forage, and silage as recommended by U.S.

EPA (1997a) were used to quantify this parameter. Crop yield was only assessed for vegetation

likely to be exposed through direct atmospheric deposition (aboveground plant categories). As

summarized in U.S. EPA (1997a), data reflecting average crop productivity for unprotected

produce, forage, and silage at the county level were used to quantify this parameter. The

following national average crop yields were used for this analysis: 0.18 for exposed vegetables,

0.09 for exposed fruits, 0.31 for forage, and 0.31 for silage (Baes et al., 1984; Shor et al., 1982;

and Travis, 1989, as cited in U.S. EPA, 1997a).

10.3.2.2 Assumptions and Uncertainties for Exposure-Related Parameters. In this

section, the uncertainties associated with the development of the exposure-related database are
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-27

reviewed. The uncertainty discussion is organized by parameter. Only parameters indicating

key uncertainties are discussed. 

10.3.2.2.1 Consumption Rate of Food Items, Soil, and Water by Cattle. Most of the

EPA-recommended values for consumption rates of plants, soil, and water are default values that

estimate national averages for these parameters. There are accepted limitations associated with

the use of national averages that do not reflect the variability inherent in consumption rates. The

consumption rates of food, water, and soil vary with region, physical conditions, climate, breeds,

and local agricultural practices. Therefore, there is uncertainty associated with adopting average

point estimates for these parameters; however, these values are currently the accepted standard

for determining farm food chain exposures. 

10.3.2.2.2 Fraction of Food Item Grown in Contaminated Soil. The default value of 1

used for the fraction of food items grown in contaminated soil assumes that the entire cattle diet

is equally contaminated. This assumption generates a conservative estimate of exposure because

in many cases, some portion of the diet may not contain contaminants. Some uncertainty is

introduced by assuming that a receptor’s entire diet is derived from contaminated food stocks.

10.3.2.2.3 Fraction of Wet Deposition that Adheres to Plants. The primary uncertainty

associated with this parameter is the paucity of data available to derive the value. The default

parameter was derived using one study. The scarcity of relevant data generates low confidence

in the default value generated. In spite of evidence suggesting that water acts to wash

contaminants from the surface of the plant, the fraction of constituents that are actually removed

has not been well-quantified. 

10.3.2.2.4 Moisture Adjustment Factor to Convert Dry Weight to Wet Weight. Based

on the narrow range of MAF values across various plant groups, limited variability is reflected in

this parameter; however, considerable variability within each plant type is apparent. This

evidence suggests that site-specific data could possibly vary significantly from default values

(U.S. EPA, 1997a). Because the default moisture adjustment was derived as a central tendency

value, there is considerable uncertainty that it represents the true variability within plant

categories. Lacking site-specific data, the MAF is a reasonable estimate for plant categories, and

it is generally accepted for risk assessment applications. 

10.3.2.2.5 Interception Fraction for Plant. Available data indicate that interception

fractions vary across vegetation types. Methods presented in U.S. EPA (1997a) suggest that sitespecific interception fractions are preferred. This analysis is not site-specific, however. Rather,

data that reflect national distributions are preferred. No suitable data were identified that

represent national distributions for specific plant categories; therefore, default values were

applied. Using a single value for all vegetation types introduces some uncertainty into the

analysis.

10.3.2.2.6 Length of Plant Exposure to Deposition. The default values adopted to

estimate the length of vegetation exposure to deposition have considerable uncertainty due to

substantial regional variability in the duration of the growing season, insufficient data available

to derive default values, and lack of knowledge of the true representativeness of these data (U.S.

EPA, 1997a). This parameter is highly dependent on regional conditions, growing practices, and
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-28

crop types. Because these factors were not accounted for in the derivation of this parameter,

there is uncertainty in the values used.

10.3.2.2.7 Empirical Correction Factors for Plants. In deriving default values for this

parameter, all organic chemicals are assumed to be equally lipophilic, even though organic

chemicals differ with regard to their lipophilicity. This simplification contributes to the

uncertainty associated with the default values, particularly for the less lipophilic organics that

may have limited distribution into the interior plant tissues. This leads to conservative correction

factors for less lipophilic constituents (U.S. EPA, 1997a).

10.3.2.2.8 Crop Yield. For crop yield, there is considerable uncertainty associated with

the use of average values because crop yield varies significantly from one region to another,

depending on growing conditions. The average values, however, are based on very extensive

databases that capture a large amount of the national variability.

10.4 Quality Assurance and Quality Control

The QA/QC functions for data collection of farm food chain parameters can be thought of

in terms of ensuring that data have been interpreted and extracted correctly (technical QA/QC)

and verifying that data have been entered correctly (data entry QA/QC). The QA/QC activities

implemented for the Terrestrial Food Web and Farm Food Chain Module data collection are

described in the following sections.

10.4.1 Technical QA/QC

Sources used to obtain data for the Terrestrial Food Web and Farm Food Chain Modules

are generally accepted as authoritative references. Although both U.S. EPA (in press) and U.S.

EPA (1997a) are draft documents currently under review, they were the preferred data sources

because they were developed in accordance with EPA’s policies and standards. Sources

consulted to fill the remaining data gaps were reviewed and approved by the technical lead staff

member for the data collection task. Once all the data were entered into the database, a second

technical staff member manually verified correct data interpretation and accurate data entry. 

Primary data sources used to derive databases for HWIR95 also were reviewed and verified

before being included in the database.

10.4.2 Data Entry QA/QC

Data entry was performed by hardcopy data entry. A QA/QC check of all values was

performed by a second staff member to ensure that the numbers had been correctly entered into

the database.

10.5 References

Baes, C.F., III, R.D. Sharp, A.L. Sjoreen, and R.W. Shor. 1984. A Review and Analysis of

Parameters for Assessing Transport of Environmentally Released Radionuclides through

Agriculture. Oak Ridge National Laboratory, ORNL--5786. Oak Ridge, TN.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-29

Canton, J.H., and W. Sloof. 1982. Toxicity and accumulation studies of cadmium with

freshwater organisms of different trophic levels. Ecotoxicology and Environmental

Safety 6:113-128.

CDFA (California Department of Food and Agriculture). 1998. Development of Risk-Based

Concentrations for Arsenic, Cadmium, and Lead in Inorganic Commercial Fertilizers.

Prepared by Foster and Wheeler Environmental Corporation, Sacramento, CA.

Chaney, R.L., and J.A. Ryan. 1994. Risk Based Standards for Arsenic, Lead, and Cadmium in

Urban Soils. DECHEMA Deutsche Gesellschaft fur Chemisches Apparatewessen,

Chemische Technik und Biotechnologie e. V., Frankfurt am Main.

Garten, C.T., Jr., and J.R. Trabalka. 1983. Evaluation of models for predicting terrestrial food

chain behavior of xenobiotics. Environmental Science and Technology 590-595.

Haimi, J., J. Salminen, V. Huhta, J. Knuutinen, and H. Palm. 1992. Bioaccumulation of

organochlorine compounds in earthworms. Soil Biol. Biochem. 24(12):1699-1703.

Harris, B., Jr., and H.H. Van Horn. 1992. Water and Its Importance to Animals. Circular 1017,

Dairy Production Guide, Florida Cooperative Extension Service. Available online at

http://hammock.ifas.ufl.edu/txt/fairs/2607.

Jager, T. 1998. Mechanistic approach for estimating bioconcentration of organic chemicals in

earthworms (Oligochaeta). Environmental Toxicology and Chemistry 7(10):2080-2090.

Rowe, C.L., O.M. Kinney, A.P. Fiori, and J.D. Congdon. 1996. Oral deformities in tadpoles

(Rana catesbeiana) associated with coal ash deposition: Effects on grazing ability and

growth. Freshwater Biology 36:723-730.

RTI (Research Triangle Institute). 1995. Technical Support Document for the Hazardous Waste

Identification Rule: Risk Assessment for Human and Ecological Receptors, Volumes 1

and 2, 1995. Prepared for U.S. Environmental Protection Agency, Office of Solid Waste. 

Prepared by Research Triangle Institute.

Sample, B.E., J.J. Beauchamp, R.A. Efroymson, G.W. Suter, II, and T.L. Ashwood. 1998. 

Development and Validation of Bioaccumulation Models for Earthworms. ES/ER/TM220. Oak Ridge National Laboratory, Oak Ridge, TN.

Sample, B.E., J.J. Beauchamp, R.A. Efroymson, and G.W. Suter, II. 1998. Development and

Validation of Bioaccumulation Models for Small Mammals. ES/ER/TM-219. Oak Ridge

National Laboratory, Oak Ridge, TN.

Sample, B.E., M.S. Aplin, R.A. Efroymson, G.W. Suter, II, and C.J.E. Welsh. 1997. Methods

and Tools for Estimation of the Exposure of Terrestrial Wildlife to Contaminants. Oak

Ridge National Laboratory, Oak Ridge, TN. 
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-30

Simonich, S. L. and R. A. Hites. 1994. Vegetation-atmosphere partitioning of polycyclic

aromatic hydrocarbons. Environmental Science and Technology 28:939-943.

Travis, C.C., and A.D. Arms. 1988. Biocenconcentration of Organics in Beef, Milk, and

Vegetation. Environmental Science and Technology, 22:271.

University of Nebraska Cooperative Extension. 1998a. Water Requirements for Beef Cattle. 

Cooperative Extension. Institute of Agriculture and Natural Resources, University of

Nebraska-Lincoln. Available online at http://www.ianr.unl.edu/pubs/beef/g372.htm.

University of Nebraska Cooperative Extension. 1998b. Water Quality and Requirements for

Dairy Cattle. Cooperative Extension, Institute of Agriculture and Natural Resources,

University of Nebraska-Lincoln. Available online at

http://www.ianr.unl.edu/pubs/dairy/g1138.htm.

USDA (U.S. Department of Agriculture). 1998. Statistical Highlights 1997-98: Livestock.

USDA National Agricultural Statistics Service. Available online at

http://www.usda.gov/nass/pubs/stathigh/1998/lv-ca-sl.htm.

U.S. DOE (Department of Energy). 1998a. Empirical Models for the Uptake of Inorganic

Chemicals from Soil by Plants. BJC/OR-133. Prepared for U.S. Department of Energy,

Oak Ridge National Laboratory, Oak Ridge, TN.

U.S. DOE (Department of Energy). 1998b. Biota Sediment Accumulation Factors for

Invertebrates: Review and Recommendations for the Oak Ridge Reservation. BJC/OR112. Oak Ridge, TN.

U.S. EPA (Environmental Protection Agency). 1998. Methodology for Assessing Health Risks

Associated With Multiple Exposure Pathways to Combustor Emissions. EPA, National

Center for Environmental Assessment, NCEA-0238.

U.S. EPA (Environmental Protection Agency). 2000. Ecological Soil Screening Level Guidance

- Draft. Office of Emergency and Remedial Response. July, 2000.

U.S. EPA (Environmental Protection Agency). 2000b. Exposure and Human Health

Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related Compounds. 

Part I: Estimating Exposure to Dioxin-Like Compounds. Volume 4: Site-Specific

Assessment Procedures. Draft. Exposure Assessment and Risk Characterization Group,

Office of Research and Development, Washington, DC. September.

U.S. EPA (Environmental Protection Agency). 1997. Mercury Study Report to Congress. 

Volume III - Fate and Transport of Mercury in the Environment. EPA 452/R-97/005. 

Office of Air Quality Planning and Standards and Office of Research and development,

Washington, DC.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-31

U.S. EPA (Environmental Protection Agency). 1999. Estimating Risk from the Use of

Agricultural Fertilizers (Draft Report). Office of Solid Waste, Washington, DC. August. 

Web site at http://www.epa.gov/epaoswer/hazwaste/recycle/fertiliz/risk/index.htm.

U.S. EPA (Environmental Protection Agency). 1997a. Parameter Guidance Document. EPA,

National Center for Environmental Assessment, NCEA-0238.

U.S. EPA (Environmental Protection Agency). 1997b. Risk Assessment for the Waste

Technologies Industries (WTI) Hazardous Waste Incineration Facility. Volume VI:

Screening Ecological Risk Assessment. EPA-905-R-97-002f. Region 5 Waste, Pesticides

and Toxics Division. Chicago, IL.

U.S. EPA (Environmental Protection Agency). 1997c. Protocol for Screening Level Ecological

Risk Assessment at Hazardous Waste Combustion Facilities. EPA/R-6-096-003. Office

of Solid Waste, Dallas, MN.

Van Gestel, C.A.M., and W. Ma. 1988. Toxicity and bioaccumulation of chlorophenols in

earthworms, in relation to bioavailability in soil. Ecotoxicology and Environmental

Safety 15:289-297.

Wu, L., J. Chen, K.K. Tanji, and G.S. Banuelos. 1995. Distribution and biomagnification of

selenium in a restored upland grassland contaminated by selenium from agricultural drain

water. Environmental Toxicology and Chemistry 14(4):733-742.
Section 10.0 Farm Food Chain and Terrestrial Food Web Data

10-32

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Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-33

Appendix 10A

Chemical-Specific Database Developed for

the FFC and TFW Modules

10-1. Farm Food Chain and Terrestrial Food Web Chemical-Specific Parameters . . . . . . . . 10-2

10-2. Farm Food Chain and Terrestrial Food Web Exposure-Related Parameters . . . . . . . . 10-3

10-3. Data Sources for Farm Food Chain Chemical-Specific Parameters . . . . . . . . . . . . . . . 10-5

10-4. Data Sources for Farm Food Chain Exposure-Related Parameters . . . . . . . . . . . . . . . . 10-6

10-5. Data Sources for Terrestrial Food Web Chemical-Specific Parameters . . . . . . . . . . . . 10-8

10-6. Uptake Factors Identified for Small Amphibians . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-16

10-7. Uptake Factors Identified for Earthworms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-17

10-8. Uptake Factors Identified for Invertebrates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-19

10-9. Daily Water Intake of Beef Cattle (gal/d) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-23

10-10. Daily Water Intake of Milk-Producing Dairy Cows (gal/d) . . . . . . . . . . . . . . . . . . . 10-24

Table 10A-1. Beef and Milk Biotransfer Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-35

Table 10A-2. Soil-to-Plant Bioconcentration Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-38

Table 10A-3. Root Crop Bio-uptake Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-41

Table 10A-4. Air-to-Plant Biotransfer Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-44

Table 10A-5. Plant Surface Loss Coefficients – Particulate . . . . . . . . . . . . . . . . . . . . . . . . 10-47

Table 10A-6. Plant Surface Loss Coefficients – Vapor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10-49
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-34

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10-35

Table 10A-1. Beef and Milk Biotransfer Factors

Constituent CAS

Chem

Type

Chem Ba_beef

(d/kg)

Chem Ba_milk

(d/kg) Chem Ba Reference

ChemBs

(fraction) 

TCDD, 2,3,7,8- 1746-01-6 D 0.054 0.01 U.S. EPA, 1998 0.65 Mercury 7439-97-6 Hg 0.0077 0.0026 U.S. EPA, 1997d 1 Mercury (elemental) 7439-97-6e Hg 0.0077 0.0026 U.S. EPA, 1997d 1 Methyl mercury 7439-97-6m Hg 0.0077 0.0026 U.S. EPA, 1997d 1 Antimony 7440-36-0 M 0.001 0.0001 Baes et al., 1984 1 Arsenic 7440-38-2 M 0.002 0.00006 Baes et al., 1984 1 Barium 7440-39-3 M 0.00015 0.00035 Baes et al., 1984 1 Beryllium 7440-41-7 M 0.001 0.0000009 Baes et al., 1984 1 Cadmium 7440-43-9 M 0.00055 0.001 Baes et al., 1984 1 Chromium (total) 7440-47-3 M 0.0055 0.0015 Baes et al., 1984 1 Chromium III (insolublesalts)

16065-83-1 M 0.0055 0.0015 Baes et al., 1984 1 

Chromium VI 18540-29-9 M 0.0055 0.0015 Baes et al., 1984 1 Lead 7439-92-1 M 0.0003 0.00025 Baes et al., 1984 1 Nickel 7440-02-0 M 0.006 0.001 Baes et al., 1984 1 Selenium 7783-79-1 M 0.015 0.004 Baes et al., 1984 1 Silver 7440-22-4 M 0.003 0.02 Baes et al., 1984 1 Thallium 7446-18-6 M 0.04 0.002 Baes et al., 1984 1 Vanadium 7440-62-2 M 0.0025 0.00002 Baes et al., 1984 1 Zinc 7440-66-6 M 0.1 0.01 Baes et al., 1984 1 Acetonitrile 75-05-8 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Acrylonitrile 107-13-1 O calculated calculated Calculated based on Travis

and Arms, 1988

1 
10-36Table 10A-1. (continued)

Constituent CAS

Chem

Type

Chem Ba_beef

(d/kg)

Chem Ba_milk

(d/kg) Chem Ba Reference

ChemBs

(fraction) 

Aniline 62-53-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Benzene 71-43-2 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Carbon disulfide 75-15-0 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Chlorobenzene 108-90-7 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Chloroform 67-66-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Dichlorophenoxyaceticacid, 2,4- (2,4-D)

94-75-7 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Ethylene dibromide 106-93-4 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Hexachloro-1,3-butadiene

87-68-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Methoxychlor 72-43-5 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Methyl ethyl ketone 78-93-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Methyl methacrylate 80-62-6 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Methylene chloride 75-09-2 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Nitrobenzene 98-95-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Pentachlorophenol 87-86-5 O calculated calculated Calculated based on Travis

and Arms, 1988

1 
10-37

Table 10A-1. (continued)

Constituent CAS

Chem

Type

Chem Ba_beef

(d/kg)

Chem Ba_milk

(d/kg) Chem Ba Reference

ChemBs

(fraction) 

Phenol 108-95-2 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Pyridine 110-86-1 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Tetrachloroethylene 127-18-4 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Thiram 137-26-8 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Toluene 108-88-3 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Trichloroethane, 1,1,1- 71-55-6 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Trichloroethylene 79-01-6 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Vinyl chloride 75-01-4 O calculated calculated Calculated based on Travis

and Arms, 1988

1 

Benzo(a)pyrene 50-32-8 S calculated calculated Calculated based on Travis

and Arms, 1988

1 

Bis(2-ethylhexyl)phthalate

117-81-7 S calculated calculated Calculated based on Travis

and Arms, 1988

1 

Dibenz(a,h)anthracene 53-70-3 S calculated calculated Calculated based on Travis

and Arms, 1988

1 
10-38 Table 10A-2. Soil-to-Plant Bioconcentration Factors

Constituent CAS

Chem

Type

Chem

Br_exfruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_Exveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_profruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_proveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_forage

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_grain

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_silage

(ug/g DW

plant)/

(ug/g soil) 

TCDD, 2,3,7,8- 1746-01-6 D NA NA NA NA NA NA NA Mercury 7439-97-6 Hg 1.80E-02 1.00E-01 1.40E-02 1.40E-02 2.50E-01 8.90E-02 7.80E-0Mercury (elemental) 7439-97-6e Hg 1.80E-02 1.00E-01 1.40E-02 1.40E-02 2.50E-01 8.90E-02 7.80E-0

Methyl mercury 7439-97-6m Hg 2.30E-02 2.30E-02 3.30E-02 3.30E-02 2.50E-01 1.90E-02 7.80E-0

Antimony 7440-36-0 M 2.00E-01 2.00E-01 2.00E-01 2.00E-01 2.00E-01 2.00E-01 2.00E-0Arsenic 7440-38-2 M 4.00E-02 3.20E-03 NO DATA NO DATA 7.10E-02 4.00E-02 1.80E-02 Barium 7440-39-3 M 1.50E-01 1.50E-01 1.50E-01 1.50E-01 1.50E-01 1.50E-01 1.50E-0Beryllium 7440-41-7 M 1.00E-02 1.00E-02 1.00E-02 1.00E-02 1.00E-02 1.00E-02 1.00E-02 Cadmium 7440-43-9 M 5.50E-01 6.00E-01 NO DATA NO DATA 3.10E-01 5.50E-02 2.10E-0Chromium (total) 7440-47-3 M 7.50E-03 5.70E-04 NO DATA NO DATA 1.90E-03 8.50E-05 9.30E-03 

Chromium III (insolublesalts)

16065-83-1 M 7.50E-03 5.70E-04 NO DATA NO DATA 1.90E-03 8.50E-05 9.30E-03 

Chromium VI 18540-29-9 M 7.50E-03 5.70E-04 NO DATA NO DATA 1.90E-03 8.50E-05 9.30E-03 Lead 7439-92-1 M 1.50E-01 3.80E-02 NO DATA NO DATA 8.30E-02 7.40E-03 6.70E-02 

Nickel 7440-02-0 M 6.00E-02 5.10E-02 6.00E-02 6.00E-02 4.30E-02 7.00E-02 1.70E-0

Selenium 7783-79-1 M 2.50E-02 2.50E-02 2.50E-02 2.50E-02 2.50E-02 2.50E-02 2.50E-02 Silver 7440-22-4 M 4.00E-01 4.00E-01 NO DATA NO DATA 4.00E-01 4.00E-01 4.00E-0Thallium 7446-18-6 M 4.00E-03 4.00E-03 4.00E-03 4.00E-03 4.00E-03 4.00E-03 4.00E-03 Vanadium 7440-62-2 M 5.50E-03 5.50E-03 5.50E-03 5.50E-03 4.80E-03 5.50E-03 5.50E-03 
10-39

Table 10A-2. (continued)

Constituent CAS

Chem

Type

Chem

Br_exfruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_Exveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_profruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_proveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_forage

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_grain

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_silage

(ug/g DW

plant)/

(ug/g soil) 

Zinc 7440-66-6 M 1.50E+00 3.70E-01 NO DATA NO DATA 2.90E-01 1.80E-01 1.60E+0

Acetonitrile 75-05-8 O calculated calculated calculated calculated calculated calculated calculated 

Acrylonitrile 107-13-1 O calculated calculated calculated calculated calculated calculated calculated 

Aniline 62-53-3 O calculated calculated calculated calculated calculated calculated calculated Benzene 71-43-2 O calculated calculated calculated calculated calculated calculated calculated Carbon disulfide 75-15-0 O calculated calculated calculated calculated calculated calculated calculated 

Chlorobenzene 108-90-7 O calculated calculated calculated calculated calculated calculated calculated 

Chloroform 67-66-3 O calculated calculated calculated calculated calculated calculated calculated 

Dichlorophenoxyaceticacid, 2,4- (2,4-D)

94-75-7 O calculated calculated calculated calculated calculated calculated calculated 

Ethylene dibromide 106-93-4 O calculated calculated calculated calculated calculated calculated calculated 

Hexachloro-1,3-butadiene 87-68-3 O calculated calculated calculated calculated calculated calculated calculated 

Methoxychlor 72-43-5 O calculated calculated calculated calculated calculated calculated calculated 

Methyl ethyl ketone 78-93-3 O calculated calculated calculated calculated calculated calculated calculated 

Methyl methacrylate 80-62-6 O calculated calculated calculated calculated calculated calculated calculated 
10-40 Table 10A-2. (continued)

Constituent CAS

Chem

Type

Chem

Br_exfruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_Exveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_profruit

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_proveg

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_forage

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_grain

(ug/g DW

plant)/

(ug/g soil)

Chem

Br_silage

(ug/g DW

plant)/

(ug/g soil) 

Methylene chloride 75-09-2 O calculated calculated calculated calculated calculated calculated calculated 

Nitrobenzene 98-95-3 O calculated calculated calculated calculated calculated calculated calculated 

Pentachlorophenol 87-86-5 O calculated calculated calculated calculated calculated calculated calculated 

Phenol 108-95-2 O calculated calculated calculated calculated calculated calculated calculated 

Pyridine 110-86-1 O calculated calculated calculated calculated calculated calculated calculated Tetrachloroethylene 127-18-4 O calculated calculated calculated calculated calculated calculated calculated 

Thiram 137-26-8 O calculated calculated calculated calculated calculated calculated calculated 

Toluene 108-88-3 O calculated calculated calculated calculated calculated calculated calculated Trichloroethane, 1,1,1- 71-55-6 O calculated calculated calculated calculated calculated calculated calculated Trichloroethylene 79-01-6 O calculated calculated calculated calculated calculated calculated calculated 

Vinyl chloride 75-01-4 O calculated calculated calculated calculated calculated calculated calculated 

Benzo(a)pyrene 50-32-8 S calculated calculated calculated calculated calculated calculated calculated 

Bis(2-ethylhexyl)phthalate

117-81-7 S calculated calculated calculated calculated calculated calculated calculated 

Dibenz(a,h)anthracene 53-70-3 S calculated calculated calculated calculated calculated calculated calculated 
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-41

Table 10A-3. Root Crop Bio-uptake Factors

Constituent CAS

Chem

Type

ChemRCF

(ug/g WW

plant)/(ug/mL

soil water)

ChemRCF

Reference

ChemBr_root

(ug/g DW

plant)/

(ug/g soil)

ChemBr_Root

Reference

TCDD, 2,3,7,8- 1746-01-6 D 5.20E+03 U.S. EPA,

1997a

NA NA for dioxins

Mercury 7439-97-6 Hg NA NA for metals 3.50E-02 U.S. EPA,

1997d

Mercury (elemental) 7439-97-6e Hg NA NA for metals 3.50E-02 U.S. EPA,

1997d

Methyl mercury 7439-97-6m Hg NA NA for metals 9.90E-02 U.S. EPA,

1997d

Antimony 7440-36-0 M NA NA for metals 3.00E-02 Baes et al.,

1984

Arsenic 7440-38-2 M NA NA for metals 6.70E-02 Calculated from

U.S. EPA, 1999

Barium 7440-39-3 M NA NA for metals 1.50E-02 Baes et al.,

1984

Beryllium 7440-41-7 M NA NA for metals 1.50E-03 Baes et al.,

1984

Cadmium 7440-43-9 M NA NA for metals 4.00E-01 Calculated from

U.S. EPA, 1999

Chromium (total) 7440-47-3 M NA NA for metals 6.60E-04 Calculated from

U.S. EPA, 1999

Chromium III

(insoluble salts)

16065-83-1 M NA NA for metals 6.60E-04 Calculated from

U.S. EPA, 1999

Chromium VI 18540-29-9 M NA NA for metals 6.60E-04 Calculated from

U.S. EPA, 1999

Lead 7439-92-1 M NA NA for metals 3.00E-02 Calculated from

U.S. EPA, 1999

Nickel 7440-02-0 M NA NA for metals 2.70E-02 Calculated from

U.S. EPA, 1999

Selenium 7783-79-1 M NA NA for metals 2.50E-02 Baes et al.,

1984

Silver 7440-22-4 M NA NA for metals 1.00E-01 Baes et al.,

1984

Thallium 7446-18-6 M NA NA for metals 4.00E-04 Baes et al.,

1984

Vanadium 7440-62-2 M NA NA for metals 3.00E-03 Baes et al.,

1984

Zinc 7440-66-6 M NA NA for metals 2.30E-01 Calculated from

U.S. EPA, 1999

(continued)
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-42

Table 10A-3. (continued)

Constituent CAS

Chem

Type

ChemRCF

(ug/g WW

plant)/(ug/mL

soil water)

ChemRCF

Reference

ChemBr_root

(ug/g DW

plant)/

(ug/g soil)

ChemBr_Root

Reference

Acetonitrile 75-05-8 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Acrylonitrile 107-13-1 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Aniline 62-53-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Benzene 71-43-2 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Carbon disulfide 75-15-0 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Chlorobenzene 108-90-7 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Chloroform 67-66-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Dichlorophenoxyacetic

acid, 2,4- (2,4-D)

94-75-7 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Ethylene dibromide 106-93-4 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Hexachloro-1,3-

butadiene

87-68-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Methoxychlor 72-43-5 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Methyl ethyl ketone 78-93-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Methyl methacrylate 80-62-6 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Methylene chloride 75-09-2 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

(continued)
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-43

Table 10A-3. (continued)

Constituent CAS

Chem

Type

ChemRCF

(ug/g WW

plant)/(ug/mL

soil water)

ChemRCF

Reference

ChemBr_root

(ug/g DW

plant)/

(ug/g soil)

ChemBr_Root

Reference

Nitrobenzene 98-95-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Pentachlorophenol 87-86-5 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Phenol 108-95-2 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Pyridine 110-86-1 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Tetrachloroethylene 127-18-4 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Thiram 137-26-8 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Toluene 108-88-3 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Trichloroethane, 1,1,1- 71-55-6 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Trichloroethylene 79-01-6 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Vinyl chloride 75-01-4 O calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Benzo(a)pyrene 50-32-8 S calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Bis(2-ethylhexyl)

phthalate

117-81-7 S calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics

Dibenz(a,h)anthracene 53-70-3 S calculated Calculated

based on U.S.

EPA, 1997a

NA NA for organics
10-44 Table 10A-4. Air-to-Plant Biotransfer Factors

Constituent CAS

Chem

Type

Chem

Bv_exfruit

(ug/g DW

plant)/

(ug/g air)

Chem

Bv_exveg (ug/g

DW plant)/

(ug/g air)

Chem

Bv_forage (ug/g

DW plant)/

(ug/g air)

Chem

Bv_silage (ug/g

DW plant)/

(ug/g air)

Chem_Bv

Reference

B

(u

TCDD, 2,3,7,8- 1746-01-6 D 6.55E+04 6.55E+04 6.55E+04 6.55E+04 U.S. EPA, 1997a Mercury 7439-97-6 Hg 1.97E+04 1.97E+04 1.80E+04 1.80E+04 U.S. EPA, 1997a Mercury (elemental) 7439-97-6e Hg 1.97E+04 1.97E+04 1.80E+04 1.80E+04 U.S. EPA, 1997a 

Methyl mercury 7439-97-6m Hg 3.30E+03 3.30E+03 5.00E+03 5.00E+03 U.S. EPA, 1997a Antimony 7440-36-0 M NA NA NA NA NA for metals Arsenic 7440-38-2 M NA NA NA NA NA for metals Barium 7440-39-3 M NA NA NA NA NA for metals Beryllium 7440-41-7 M NA NA NA NA NA for metals Cadmium 7440-43-9 M NA NA NA NA NA for metals Chromium (total) 7440-47-3 M NA NA NA NA NA for metals Chromium III (insolublesalts)

16065-83-1 M NA NA NA NA NA for metals 

Chromium VI 18540-29-9 M NA NA NA NA NA for metals Lead 7439-92-1 M NA NA NA NA NA for metals Nickel 7440-02-0 M NA NA NA NA NA for metals Selenium 7783-79-1 M NA NA NA NA NA for metals Silver 7440-22-4 M NA NA NA NA NA for metals Thallium 7446-18-6 M NA NA NA NA NA for metals Vanadium 7440-62-2 M NA NA NA NA NA for metals Zinc 7440-66-6 M NA NA NA NA NA for metals Acetonitrile 75-05-8 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Acrylonitrile 107-13-1 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998
10-45

Table 10A-4. (continued)

Constituent CAS

Chem

Type

Chem

Bv_exfruit

(ug/g DW

plant)/

(ug/g air)

Chem

Bv_exveg (ug/g

DW plant)/

(ug/g air)

Chem

Bv_forage (ug/g

DW plant)/

(ug/g air)

Chem

Bv_silage (ug/g

DW plant)/

(ug/g air)

Chem_Bv

Reference

B

(u

Aniline 62-53-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Benzene 71-43-2 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Carbon disulfide 75-15-0 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Chlorobenzene 108-90-7 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Chloroform 67-66-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Dichlorophenoxyaceticacid, 2,4- (2,4-D)

94-75-7 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Ethylene dibromide 106-93-4 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Hexachloro-1,3-butadiene 87-68-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Methoxychlor 72-43-5 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Methyl ethyl ketone 78-93-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Methyl methacrylate 80-62-6 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Methylene chloride 75-09-2 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Nitrobenzene 98-95-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998
10-46 Table 10A-4. (continued)

Constituent CAS

Chem

Type

Chem

Bv_exfruit

(ug/g DW

plant)/

(ug/g air)

Chem

Bv_exveg (ug/g

DW plant)/

(ug/g air)

Chem

Bv_forage (ug/g

DW plant)/

(ug/g air)

Chem

Bv_silage (ug/g

DW plant)/

(ug/g air)

Chem_Bv

Reference

B

(u

Pentachlorophenol 87-86-5 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Phenol 108-95-2 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Pyridine 110-86-1 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Tetrachloroethylene 127-18-4 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Thiram 137-26-8 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Toluene 108-88-3 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Trichloroethane, 1,1,1- 71-55-6 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Trichloroethylene 79-01-6 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Vinyl chloride 75-01-4 O calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Benzo(a)pyrene 50-32-8 S 4.70E+04 4.70E+04 4.70E+04 4.70E+04 Simonich and

Hites, 1994

Bis(2-ethylhexyl)phthalate

117-81-7 S calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998

Dibenz(a,h)anthracene 53-70-3 S calculated calculated calculated calculated Calculated based

on U.S. EPA, 1998
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-47

Table 10A-5. Plant Surface Loss Coefficients – Particulate

Constituent CAS

Chem

Type

Chem

kpPar_

exfruit

(1/yr)

Chem

kpPar_

exveg (1/yr)

Chem

kpPar_

forage (1/yr)

Chem

kpPar_

silage (1/yr) Reference

TCDD, 2,3,7,8- 1746-01-6 D 27.06 27.06 27.06 27.06 U.S. EPA, 1997a

Mercury 7439-97-6 Hg 40.41 40.41 40.41 40.41 U.S. EPA, 1997a

Mercury (elemental) 7439-97-6e Hg 40.41 40.41 40.41 40.41 U.S. EPA, 1997a

Methyl mercury 7439-97-

6m

Hg 40.41 40.41 40.41 40.41 U.S. EPA, 1997a

Antimony 7440-36-0 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Arsenic 7440-38-2 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Barium 7440-39-3 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Beryllium 7440-41-7 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Cadmium 7440-43-9 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Chromium (total) 7440-47-3 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Chromium III

(insoluble salts)

16065-83-1 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Chromium VI 18540-29-9 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Lead 7439-92-1 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Nickel 7440-02-0 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Selenium 7783-79-1 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Silver 7440-22-4 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Thallium 7446-18-6 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Vanadium 7440-62-2 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Zinc 7440-66-6 M 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Acetonitrile 75-05-8 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Acrylonitrile 107-13-1 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Aniline 62-53-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Benzene 71-43-2 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Carbon disulfide 75-15-0 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Chlorobenzene 108-90-7 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Chloroform 67-66-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Dichlorophenoxyacetic

acid, 2,4- (2,4-D)

94-75-7 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Ethylene dibromide 106-93-4 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Hexachloro-1,3-

butadiene

87-68-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Methoxychlor 72-43-5 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Methyl ethyl ketone 78-93-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Methyl methacrylate 80-62-6 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Methylene chloride 75-09-2 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

(continued)
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-48

Table 10A-5. (continued)

Constituent CAS

Chem

Type

Chem

kpPar_

exfruit

(1/yr)

Chem

kpPar_

exveg (1/yr)

Chem

kpPar_

forage (1/yr)

Chem

kpPar_

silage (1/yr) Reference

Nitrobenzene 98-95-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Pentachlorophenol 87-86-5 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Phenol 108-95-2 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Pyridine 110-86-1 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Tetrachloroethylene 127-18-4 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Thiram 137-26-8 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Toluene 108-88-3 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Trichloroethane, 1,1,1- 71-55-6 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Trichloroethylene 79-01-6 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Vinyl chloride 75-01-4 O 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Benzo(a)pyrene 50-32-8 S 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Bis(2-ethylhexyl)

phthalate

117-81-7 S 18.07 18.07 18.07 18.07 U.S. EPA, 1997a

Dibenz(a,h)anthracene 53-70-3 S 18.07 18.07 18.07 18.07 U.S. EPA, 1997a
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-49

Table 10A-6. Plant Surface Loss Coefficients – Vapor

Constituent CAS

Chem

Type

Chem

kpVap_

exfruit

(1/yr)

Chem

kpVap_

exveg

(1/yr)

Chem

kpVap_

forage

(1/yr)

Chem

kpVap_

silage

(1/yr) Reference

TCDD, 2,3,7,8- 1746-01-6 D 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Mercury 7439-97-6 Hg NA NA NA NA NA for metals

Mercury (elemental) 7439-97-6e Hg NA NA NA NA NA for metals

Methyl mercury 7439-97-6m Hg NA NA NA NA NA for metals

Antimony 7440-36-0 M NA NA NA NA NA for metals

Arsenic 7440-38-2 M NA NA NA NA NA for metals

Barium 7440-39-3 M NA NA NA NA NA for metals

Beryllium 7440-41-7 M NA NA NA NA NA for metals

Cadmium 7440-43-9 M NA NA NA NA NA for metals

Chromium (total) 7440-47-3 M NA NA NA NA NA for metals

Chromium III (insoluble

salts)

16065-83-1 M NA NA NA NA NA for metals

Chromium VI 18540-29-9 M NA NA NA NA NA for metals

Lead 7439-92-1 M NA NA NA NA NA for metals

Nickel 7440-02-0 M NA NA NA NA NA for metals

Selenium 7783-79-1 M NA NA NA NA NA for metals

Silver 7440-22-4 M NA NA NA NA NA for metals

Thallium 7446-18-6 M NA NA NA NA NA for metals

Vanadium 7440-62-2 M NA NA NA NA NA for metals

Zinc 7440-66-6 M NA NA NA NA NA for metals

Acetonitrile 75-05-8 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Acrylonitrile 107-13-1 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Aniline 62-53-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Benzene 71-43-2 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Carbon disulfide 75-15-0 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Chlorobenzene 108-90-7 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Chloroform 67-66-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Dichlorophenoxyacetic

acid, 2,4- (2,4-D)

94-75-7 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Ethylene dibromide 106-93-4 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Hexachloro-1,3-

butadiene

87-68-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Methoxychlor 72-43-5 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Methyl ethyl ketone 78-93-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Methyl methacrylate 80-62-6 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Methylene chloride 75-09-2 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

(continued)
Appendix 10A Chemical-Specific Database Developed for the FFC and TFW Modules

10-50

Table 10A-6. (continued)

Constituent CAS

Chem

Type

Chem

kpVap_

exfruit

(1/yr)

Chem

kpVap_

exveg

(1/yr)

Chem

kpVap_

forage

(1/yr)

Chem

kpVap_

silage

(1/yr) Reference

Nitrobenzene 98-95-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Pentachlorophenol 87-86-5 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Phenol 108-95-2 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Pyridine 110-86-1 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Tetrachloroethylene 127-18-4 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Thiram 137-26-8 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Toluene 108-88-3 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Trichloroethane, 1,1,1- 71-55-6 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Trichloroethylene 79-01-6 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Vinyl chloride 75-01-4 O 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Benzo(a)pyrene 50-32-8 S 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Bis(2-ethylhexyl)

phthalate

117-81-7 S 119.35 119.35 119.35 119.35 U.S. EPA, 1998

Dibenz(a,h)anthracene 53-70-3 S 119.35 119.35 119.35 119.35 U.S. EPA, 1998
Appendix 10B Exposure-Related Database Developed for the FFC and TFW Modules

10-51

Appendix 10B

Exposure-Related Database Developed for the

FFC and TFW Modules

Table 10B-1. Exposure-Related Database Developed for the FFC and TFW Modules . . . . 10-53
Appendix 10B Exposure-Related Database Developed for the FFC and TFW Modules

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Appendix 10B Exposure-Related Database Developed for the FFC and TFW Modules

10-53

Table 10B-1. Exposure-Related Database Developed for the FFC and TFW Modules

Data_Group_Name Variable_Name Units Central_Tendency

terrestrial foodweb Bv_ecf_plant unitless 100

terrestrial foodweb Rp_forage unitless 0.47

terrestrial foodweb MAFroot percent 87

terrestrial foodweb VGag_exfruit unitless 0.01

terrestrial foodweb VapDdv cm/sec 1

terrestrial foodweb tp_silage y 0.16

terrestrial foodweb tp_forage y 0.12

terrestrial foodweb tp_exveg y 0.123

terrestrial foodweb tp_exfruit y 0.123

terrestrial foodweb Rp_silage unitless 0.44

terrestrial foodweb Fw_silage unitless 0.6

terrestrial foodweb Fw_forage unitless 0.6

terrestrial foodweb Yp_silage kg DW/m2 0.31

terrestrial foodweb Yp_forage kg DW/m2 0.31

terrestrial foodweb Yp_exveg kg DW/m2 0.18

terrestrial foodweb Yp_exfruit kg DW/m2 0.09

terrestrial foodweb VGbg_root unitless 0.01

terrestrial foodweb VGag_silage unitless 0.5

terrestrial foodweb VGag_forage unitless 1

terrestrial foodweb Fw_exveg unitless 0.6

terrestrial foodweb Fw_exfruit unitless 0.6

terrestrial foodweb Rp_exveg unitless 0.05

terrestrial foodweb MAFexveg percent 92

terrestrial foodweb MAFforage percent 92

terrestrial foodweb MAFgrain percent 90

terrestrial foodweb MAFleaf unitless 85

terrestrial foodweb MAFexfruit percent 85

terrestrial foodweb VGag_exveg unitless 0.01

terrestrial foodweb rho_leaf g/L FW 770

terrestrial foodweb Rp_exfruit unitless 0.052

terrestrial foodweb MAFsilage percent 92
Appendix 10B Exposure-Related Database Developed for the FFC and TFW Modules

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