NUREG/CR-6910

 PNNL-15872

Alternative Conceptual Models 

for Assessing Food Chain 

Pathways in Biosphere Models 

Pacific Northwest National Laboratory

U.S. Nuclear Regulatory Commission

Office of Nuclear Regulatory Research 

Washington, DC 20555-0001
 

 

 

 NUREG/CR-6910 

 PNNL-15872

Alternative Conceptual Models

for Assessing Food Chain

Pathways in Biosphere Models

Manuscript Completed: June 2006

Date Published: June 2006

Prepared by

B. A. Napier

Pacific Northwest National Laboratory

Richland, WA 99352

P. R. Reed, NRC Project Manager

Prepared for

Division of Fuel, Engineering, and Radiological Research 

Office of Nuclear Regulatory Research 

U.S. Nuclear Regulatory Commission

Washington, DC 20555-0001

Job Code Y6469
ii
iii

Abstract 

This report describes alternative approaches to modeling the key processes in 

radionuclide transport in the biosphere. Because the focus of the NRC project 

Assessment of Food Chain Pathway Parameters in Biosphere Models is the food-chain 

models used in performance assessments of radioactive waste disposal facilities, models 

and approaches applicable over relatively long periods (more than one year) are 

evaluated, as opposed to approaches detailing radionuclide behavior over the shorter 

periods applicable to acute, accident-type, calculations. There are a number of important 

features and processes that all terrestrial biosphere models must address: these include 

radionuclide behavior in soils, interception of deposition onto vegetation, weathering of 

intercepted material from plant surfaces, foliar absorption and translocation within plants 

to other vegetative structures, uptake from soil by plant roots, and transfer from plants to 

animals and animal products. 

The report provides a detailed discussion of possible alternative approaches to 

modeling the food-chain pathway in biosphere models and recommends the following: 

• For soil, an annual average model incorporating: 

o Accumulation from irrigation or atmospheric deposition; 

o Leaching to deeper soil, using a Kd-modulated leach rate; 

o Harvest removal, averaged over crop types 

o Uniform mixing in a reasonable (15-25 cm) upper soil surface layer, 

implicitly caused by plowing, bioturbation, and leaching; 

o Neglecting radionuclide fixation, because appropriate long-term 

measurements of distribution coefficient and concentration ratio will 

already incorporate the effects; 

o Neglecting surface-soil erosion losses, because eroded material from one 

location may accumulate in another, cancelling any perceived benefit. 

• For resuspension, a mass-loading approach, because it has the lowest variability 

and is the most easily defended. 

• For foliar interception, models incorporating: 

o Dry interception following the basic model suggested by Chamberlain 

(1967) as updated by Adriano et al. 1982; 

o Wet interception considering one of the algorithms derived from the data 

of Hoffman et al. (1989) or Prohl and Hoffman (1993). 

• For plant contamination with soil, an adhesion model applied so that material 

translocated is not subject to weathering (e.g., IAEA 2003; Wu 2003). 

• For weathering, a single exponential model with a half-time between about 10 

and 20 days, applied to material on the surface of the plant only. 

• For translocation, a radionuclide-specific (or chemical-class-specific) 

implementation allowing translocated materials to avoid being removed via 

weathering processes (e.g., IAEA 2003; Wu 2003). 

• For soil-to-plant transfer, a radionuclide- and plant-type-specific concentration 

ratio, where available, with: 

o Site-specific application of additional crops, such as mushrooms; 
iv

o The specific-activity model of Peterson and Davis (2002) for elemental 

and oxide forms of tritium; 

o A general specific-activity model for 14C in air, adapted to the RESRAD 

family of codes (Yu et al. 2001) model for transfer from irrigation water to 

air as 14CO2; 

o Perhaps site-specific application of specific-activity models for iodine and 

other micro-nutrient and macro-nutrient elements and their chemical 

analogues. This is a simplification of the need to allow for homeostatic 

regulation of some elements. 

• Until a simple, robust Fruit Tree model is developed, continue to use the 

concentration ratio approach for fruits. 

• For animal products, a transfer factor approach applied to average daily feed, 

water, and soil intake by the animal where data are available. 

o For element/animal combinations where data are lacking, a justified mix 

of specific-activity and allometric models should be considered. 

• For food processing, because the data are sparse and the reduction is generally 

small, modelers are justified in ignoring losses (which is equivalent to using a 

food-processing transmission factor of 1.0). 

This type of information is directly useful in formulating inputs to radioecological and 

food-chain models used in performance assessments and other kinds of environmental 

assessment. This food-chain pathway data may be used by the NRC staff to assess dose 

to persons in the reference biosphere (e.g., persons who live and work in an area 

potentially affected by radionuclide releases) of waste disposal facilities and 

decommissioning sites. 
FOREWORD

The food chain pathway contributes to the potential dose received by members of the public as

a result of the potential release of radionuclides to the environment from many facilities licensed

by the U.S. Nuclear Regulatory Commission (NRC). To quantify the contribution of this

pathway, NRC developed performance assessment strategies involving biosphere computer

codes to evaluate the potential dose to humans. These biosphere codes incorporate parameters

for radionuclideuptake in plant roots and leaves, as well as animal products, to aid in predicting

the radionuclide concentrations that humans would ingest in the event of an environmental

release.

This report describes alternatives to current approaches for modeling key features and

processes to assess radionuclide transport and behavior in food-chain pathways in the

biosphere. Section 2 describes some important concepts, features and processes that all

biosphere models must address. Section 3 provides descriptions of various ways of modeling

these important features and processes. Finally, Section 4 discusses the types of modeling

approaches that are most applicable to assess doses to persons who live and work in areas

affected by potential radionuclide releases from nuclear facilities.

Included in this report are detailed discussions on approaches to modeling long-lived radionuclide

behavior in soils in and near the plant root system, soil resuspension, and wet and dry leaf

interception of deposition onto vegetation. There are also discussions on weathering of

intercepted material from plant surfaces, foliar absorption and translocation within plants to other

vegetative structures, uptake in fruit and nut trees, radionuclide uptake from soil by plant roots,

and t/Je transfer of radionuclides from plants to animals and animal products.

For some of the processes described in this report, several methods of different levels of

complexity are described depending on the type of analyses being performed. For other

processes, limited information was available and the report includes only one or two alternative

approaches to the calculations.

NRC is currently using the results described in this report to interpret the results of ongoing

experiments at Pacific Northwest National Laboratory to determine radionuclide uptake factors

in plants and animals. For the future, the Commission expects to use the data and information

presented in this report to reduce uncertainties in food-chain-pathway dose assessments. The

results of the biosphere research prograrh improve the NRC staff's understandingof the features

and processthat affect estimates of dose from important long-lived radionuclidesin the food-chain

pathway.

Brian W. Sheron, Director

Office of Nuclear Regulatory Research

v
vi
vii

Contents 

Abstract.............................................................................................................................. iii 

Foreword............................................................................................................................. v 

List of Figures..................................................................................................................viii 

List of Tables ..................................................................................................................... ix 

Acknowledgements ............................................................................................................ x 

1.0 Introduction..............................................................................................................1-1 

2.0 Concepts in Biosphere Modeling.............................................................................2-1 

3.0 Modeling Key Processes.......................................................................................... 3-1 

3.1 Modeling Radionuclides in Soil............................................................................ 3-1 

3.2 Modeling Resuspension ........................................................................................ 3-8 

3.3 Modeling Radionuclides in Vegetation............................................................... 3-10 

3.3.1 Modeling Foliar Interception and Retention.......................................... 3-11 

3.3.2 Modeling Contamination of Plant Surfaces with Soil ........................... 3-16 

3.3.3 Modeling Weathering from Plant Surfaces............................................ 3-17 

3.3.4 Modeling Foliar Absorption and Translocation..................................... 3-19 

3.3.5 Modeling Soil-to-Plant Uptake.............................................................. 3-22 

3.4 Modeling the Uptake of Radionuclides in Animal Products .............................. 3-41 

3.4.1 Feed to Animal Product Transfer Factors.............................................. 3-41 

3.4.2 The Observed Ratio in Animal Products ............................................... 3-42 

3.4.3 Unusual Animal Products ...................................................................... 3-43 

3.4.4 Specific Activity Models for Animal Products...................................... 3-44 

3.4.5 Kinetic Modeling for Animals............................................................... 3-46 

3.4.6 Allometric Models for Uptake by Animals ........................................... 3-50 

3.5 Modeling the Effects of Food Processing on Radionuclide Concentrations.......3-51 

3.6 Modeling Other Terrestrial Exposure Pathways................................................. 3-56 

3.6.1 Unique Direct Pathways ........................................................................3-56 

3.6.2 Unique Indirect Pathways...................................................................... 3-57 

4.0 Recommendations....................................................................................................4-1 

5.0 References................................................................................................................ 5-1 
viii

List of Figures 

Figure 1. Idealized Behavior of Radionuclide Concentration in Soil Following 

Long Periods of Irrigation for Mobile and Immobile Radionuclides ............ 3-7 

Figure 2. A Basic Model for Contamination of Plants................................................ 3-11 

Figure 3. Relationships are shown between tissue concentrations and 

environmental concentrations for non-nutrient and nutrient compounds ... 3-33 
ix

List of Tables 

Table 1. Biotic Transport Quantities (adapted from McKenzie et al. 1986) ............... 3-8 

Table 2. Probable Bioavailability/Cuticular Transfer of Selected Elements ............. 3-21 

Table 3. Aggregate transfer coefficient for cesium for 4 mushroom classes............. 3-32 

Table 4. In a biological classification of metals, shaded cells are non-nutrient 

analogs; bold cells are nonessential metals.................................................. 3-34 

Table 5. Weight Fractions of Hydrogen and Carbon in Environmental Media, 

Vegetation, and Animal Products ................................................................. 3-36 

Table 6. Parameter values for calculating HTO and OBT concentrations in plant 

products........................................................................................................ 3-37 

Table 7. Suggested parameter values for calculating HTO and OBT 

concentrations in animal products. .............................................................. 3-46 

Table 8. Recommended Values of Food Processing Retention Factors for Most 

Contaminants ............................................................................................... 3-55 

Table 9. Recommended Values of Food Processing Retention Factors for Tritium . 3-55 
x

Acknowledgements 

The author is particularly grateful for the technical guidance, review, and encouragement 

provided by P. R. Reed of the U.S. Nuclear Regulatory Commission. The author thanks 

W.E. Kennedy, Jr. (Dade Moeller and Associates), K.A. Higley (Oregon State 

University), F.O. Hoffman and J. R. Trabalka (SENES Oak Ridge), C.A. Brandt 

(PNNL), and NRC staff for detailed review comments on the draft of this report. 
1-1

1.0 Introduction 

The U.S. Nuclear Regulatory Commission’s project Assessment of Food Chain Pathway 

Parameters in Biosphere Models has been established to assess and evaluate a number of 

key parameters used in the food-chain models used in performance assessments of 

radioactive waste disposal facilities. The objectives of the research program include: 

• Provide data and information for the important features, events, and processes of 

the pathway models for use in biosphere computer codes. These codes calculate 

the total effective dose equivalent (TEDE) to the average member of the critical 

group and/or reasonably maximally exposed individual, for example, from 

radionuclides in the contaminated ground water release scenarios in NRC's 

performance assessments of waste disposal facilities and decommissioning sites, 

• Reduce uncertainties in food-chain pathway analysis from the agriculture scenarios 

of biosphere models in performance assessment calculations, 

• Provide better data and information for food-chain pathway analyses by: 

o Performing laboratory and field experiments, including integral and 

separate effect experiments, to evaluate the potential pathways and uptake 

mechanisms of plants and animals contaminated by long-lived 

radionuclides, 

o Presenting food-chain pathway data and information by regional and local 

geographical locations, 

o Quantifying uncertainties in the radioactive contamination of food crops 

and long-term build up of radionuclides in soils with contaminated ground 

water from water irrigation systems, 

o Determining data on factors affecting radionuclide uptake of food crops 

including irrigation water processes, soil physical and chemical properties, 

soil leaching and retention properties near crop roots, soil resuspension 

factors and other soil and plant characteristics. 

The results of this research program will provide needed food-chain and animal product 

pathway data and information for important radionuclides that may be used by the NRC 

staff to assess dose to persons who live and work in areas potentially affected by 

radionuclide releases from waste disposal facilities and decommissioning sites. 

The biosphere model is the last model in a series of models used by the NRC staff in 

performance assessments of waste-disposal facilities and decommissioning sites. The 

biosphere models used by the NRC staff in its performance assessments are based on 

conceptual models, their mathematical representation, and the implementing computer 

codes. The biosphere models used by the NRC, and their implementing computer codes, 

include hypotheses, assumptions, and simplifications that describe the reference 

biosphere in the vicinity of the waste-disposal facilities and decommissioning sites. 

These computer codes consider (1) radionuclide transport through many food-chain 

pathways such as irrigation-water deposition on vegetation and soil surfaces, (2) crop 

interception and retention, (3) radionuclide buildup in soils as a result of long-term 
1-2

irrigation deposition, (4) soil radionuclide leaching and retention mechanisms in plant 

root zones, (5) resuspension of radionuclide-contaminated soil onto vegetation, and 

transfer via gaseous phase radionuclides arising from soil, (6) soil to plant uptake via 

roots, (7) uptake by stems/leaves of soil-derived gaseous contaminants, (8) feed-toanimal product transfer, and (9) individual food product consumption rates. Biosphere 

models used in performance assessments provide the long-term, time-dependent 

concentrations of radionuclides in soil, plants, and animal products that could be 

consumed by future human residents of the biosphere. When coupled with projections of 

human behavior, they also provide estimates of annual or lifetime radiation dose; that 

component of the biosphere modeling is not addressed in this report. 

Section 1of this report is this introduction. 

Section 2 of this report describes some key concepts in biosphere modeling - important 

features and processes that all biosphere models must address in some manner. For 

terrestrial models, these include radionuclide behavior in soils, interception of deposition 

onto vegetation, weathering of intercepted material from plant surfaces, foliar absorption 

and translocation within plants to other vegetative structures, uptake from soil by plant 

roots, and transfer from plants to animals and animal products. 

Section 3 of this report provides descriptions of various ways of modeling these 

important features and processes. For some processes, various methods of different 

levels of complexity are applied depending on the type of analyses being performed. For 

other processes, very limited information allows only one or two alternative approaches 

to the calculations. 

Section 4 makes recommendations on the types of modeling approaches that are most 

applicable for models to be used to assess doses to persons who live and work in areas 

potentially affected by radionuclide releases from waste disposal facilities and 

decommissioning sites. 

The results are expected to be useful in: 

• supporting the development of regulatory criteria (e.g., guidance, technical 

positions) for food-chain pathway issues involving biosphere models 

• providing a basis for evaluating and auditing an applicant’s or licensee’s 

biosphere and food-chain pathway data, information, analyses, conceptual 

models, and computer codes used in license submittals 

• providing NRC staff with data and information for resolving biosphere issues 

involving irrigation pathways, food and animal transfer factors, and groundwater 

radionuclide release scenarios. 
1-3

The results of the research program improve the NRC staff’s understanding of the 

features and processes for some important long-lived radionuclides in biosphere 

modeling of the performance-assessment process. 
2-1

2.0 Concepts in Biosphere Modeling 

There are a number of important features and processes that all biosphere models must 

address in some manner (UNSCEAR 2000). For terrestrial models, these include 

radionuclide behavior in soils, interception of deposition onto vegetation, weathering of 

intercepted material from plant surfaces, foliar absorption and translocation within plants 

to other vegetative structures, uptake from soil by plant roots, and transfer from plants to 

animals and animal products. Because different models and model types approach these 

features and processes differently, some of the reasons for the different approaches are 

discussed in this section in general terms before specific methods of computation are 

described. 

The primary inputs to estimating radiation doses to individuals and populations are the 

concentrations and availabilities of radionuclides in air, water, soil, and foods, and the 

level of exposure of the individuals or groups to each radionuclide in each medium. 

Because it is not possible to completely characterize the radiological environment, and 

because in many practical cases the concentration of radionuclides in the environment 

resulting from reactor operations is too low to measure, mathematical models are 

employed to go from what is known to what needs to be known. 

Many different types of models have been developed. The various models are directed to 

answering different questions. Different models have different levels of detail, different 

degrees of accuracy, and different temporal or spatial scales. Some are used for 

retrospective analyses (to analyze what has happened - as for determining compliance 

with annual radiation dose limits) or for prospective analyses (to project what may 

happen - as for demonstrating compliance with licensing requirements). 

Two general classes of environmental transport models have evolved: dynamic (transient) 

and equilibrium (steady-state). Both tend to describe the environment in terms of various 

“compartments” such as soil layers, plant types, and animal types (some environmental 

media may be described in terms of more than one compartment, such as the roots, trunk, 

branches, and fruit of trees). The dynamic models consider the time-dependent quantities 

of radionuclides in various environmental compartments. The structure of the model is 

represented by a series of coupled differential equations that describe the rate of change 

of the amount of the radioactive material in each compartment as a function of the 

various transfer paths into (e.g. irrigation) and out of it (e.g., radioactive decay, harvest). 

When the equations are evaluated over sufficiently long times with unvarying values of 

the inputs and rate constants, the ratios of the concentrations of the radionuclides in the 

various compartments approach constant values. The system then is considered to be in 

equilibrium or in a steady state. Dynamic models are frequently used as research tools to 

investigate the detailed phenomena and mechanisms of environmental transport of 

radionuclides. For example, they are beneficial in evaluating the consequences of pulse 

inputs to selected compartments, as might happen following an accidental release. 

However, because of the temporal resolution demanded of the output, a great deal of 
2-2

information is required as input to this type of model, and extensive computer resources 

are required for implementation. By using assumptions of quasi-equilibrium (that is, 

relatively small changes from year to year in local conditions), the dynamic models may 

be simplified into equilibrium models. The equilibrium models lose the ability to answer 

certain temporally-based questions, but are generally simpler to use, because many of the 

detailed rate constants required by the dynamic models can be treated as lumped 

parameters. Because most regulations dealing with nuclear waste are written in terms of 

annual doses to people, most routine radiological evaluations are performed using the 

equilibrium models with annual-average values for the input parameters.
3-1

3.0 Modeling Key Processes 

Alternative approaches to modeling the key processes in radionuclide transport in the 

biosphere are presented in this section. Because the focus of the NRC project Assessment 

of Food Chain Pathway Parameters in Biosphere Models is the food-chain models used 

in performance assessments of radioactive waste disposal facilities, models and 

approaches applicable over relatively long periods (more than one year) are evaluated, as 

opposed to approaches detailing radionuclide behavior over the shorter periods applicable 

to acute, accident-type, calculations. International reviews of models of this type that 

have been performed in the past decade include the IAEA BIOMASS (IAEA 2003) 

program and the European BIOPROTA program (Albrecht et al. 2005). 

3.1 Modeling Radionuclides in Soil 

Surface soils tend to be compartments for long-term retention and accumulation of 

radionuclides released into the accessible environment, either from atmospheric or liquid 

releases or from localized depositions. Soils typically are made up primarily of mineral 

components with additional organic material incorporated from decomposing plant 

matter, hosting numerous microorganisms and small invertebrates. The surface layer of 

soils may be mixed by small animals, and in agricultural systems is usually mixed 

annually by tillage. Radionuclides may become incorporated in vegetation; the mineral 

and organic constituents of vegetation cycle in the soil and serve as a reservoir as the 

organic component decomposes. On small spatial scales, soils may erode, thus moving 

contamination from one location to another. Percolating water may transport 

contaminants from shallow to deeper soils. 

The concentrations, mobility, and bioavailability of radionuclides in surface and 

subsurface geologic systems are controlled by numerous hydrologic and geochemical 

processes. These include hydrologic factors, such as dispersion, advection, and dilution; 

and geochemical processes, such as aqueous complexation, oxidation/reduction (redox), 

adsorption/desorption and ion exchange, precipitation/dissolution, diffusion, colloidfacilitated transport, and anion exclusion (Langmuir 1997; Sposito 1989; 1994). 

Additionally, in the uppermost layer of surface soil, the mobility of radionuclides can 

also be increased by biological activity and by the drying and subsequent cracking of 

soils. Colloid-facilitated transport and anion exclusion have received considerable 

attention recently in that they can enhance the transport of certain radionuclides. 

However, these processes are hard to quantify, and the extent to which they occur is 

difficult to determine. The importance of colloid-facilitated migration, especially in 

aquifer systems that do not involve fracture flow of groundwater, is still a subject of 

debate. 

Some radionuclides, such as technetium, uranium, or plutonium, may be present in more 

than one oxidation state in the environment. The adsorption and precipitation behavior of 

different oxidation states of a particular radionuclide are usually very different. For 

example, in environmental systems, the most stable oxidation states of technetium are +7 

and +4 under oxidizing and reducing geochemical conditions, respectively. The chemical 
3-2

behavior of technetium in these two oxidation states differs drastically. Dissolved 

Tc(VII) exists as pertechnetate anion, TcO4

-

, over the complete pH range of natural 

waters under oxic conditions. Because the pertechnetate anion is highly soluble and is 

not strongly sorbed, it is highly mobile in most oxidizing systems. Under reducing 

conditions, however, Tc(IV) exists as hydrolyzed cations and is relatively immobile in 

the absence of strongly complexing ligands. Technetium(IV) is highly sorbed and forms 

the sparingly soluble TcO2@nH2O solid (Krupka 2003). 

Adsorption/desorption (including ion exchange) and precipitation/dissolution are 

considered the most important processes affecting radionuclide interactions with soils. 

Precipitation/dissolution is more likely to be an important process where elevated 

concentrations of dissolved radionuclides exist, such as in the near-field environment of 

radioactive waste disposal facilities or the spill sites of radionuclide-containing wastes or 

where steep pH or redox gradients exist. Adsorption/desorption will likely be the key 

process controlling radionuclide retardation in areas where trace concentrations of 

dissolved radionuclides exist, such as those associated with far-field environments of 

disposal facilities or spill sites or in areas of where soils are to be irrigated using 

radionuclide-contaminated water. 

The term “sorption” is used as a generic term devoid of mechanism and used to describe 

the partitioning of dissolved aqueous-phase constituents to a solid phase. When a 

radionuclide is associated with a geologic material, however, it is usually not known if 

the radionuclide is adsorbed onto the surface of the solid, absorbed into the structure of 

the solid, precipitated as a three-dimensional molecular structure on the surface of the 

solid, or partitioned into the organic matter (Sposito 1989). The term “sorption” 

encompasses all of the above processes. 

The sorption of radionuclides on soils is frequently quantified by the partition (or 

distribution) coefficient (Kd). The Kd parameter is a factor related to the partitioning of a 

radionuclide between the solid and aqueous phases and is defined as the ratio of the 

quantity of the adsorbate adsorbed per mass of solid to the amount of the adsorbate 

remaining in solution at equilibrium. Radionuclides that adsorb very strongly to soil have 

large Kd values (typically greater than 100 mL/g) compared to those values for 

radionuclides that are not significantly retarded by adsorption. Radionuclides that do not 

adsorb to soil and migrate essentially at the same rate as the waterflow have Kd values 

near 0 mL/g. The Kd model is the simplest yet least robust sorption model available. 

However, the Kd metric is the most common measure used in hydrologic transport and 

biosphere codes to describe the extent to which contaminants are sorbed to soils. The 

primary advantage of the Kd model is that it is easily inserted into computer codes to 

quantify the reduction in the extent of transport of a radionuclide relative to groundwater. 

The Kd is an empirical unit of measurement that attempts to account for various chemical 

and physical retardation mechanisms that are influenced by a myriad of variables. As 

such, the Kd model is often the subject of criticism (EPA 1999). 

Because of recharge from precipitation or irrigation, radionuclides deposited on soils may 

leach through the surface layer with percolating water, eventually reaching depths below 
3-3

the surface where they are no longer available for uptake by plants and animals. Sorbed 

materials may also travel with soil particles as they are physically transported via wind or 

water erosion. 

Deposition of radioactive material from the air or irrigation water onto the earth’s surface 

is a function of surface area. Atmospheric dispersion model outputs generally deal with 

depletion of plumes or puffs of material in terms of mass per unit area per unit time. 

Irrigation deals with quantities of water per unit area (e.g., acre-feet) per unit time. 

Although a fraction of depositing activity usually is intercepted by vegetation, it is 

generally assumed that all deposition eventually works its way to the soil surface. The 

initial problem is to convert this initially infinitesimally-thin layer into a bulk 

concentration in soil, and then to describe its subsequent behavior. 

This problem was first addressed in projections of nuclear weapon fallout (Burton 1966; 

Ng and Thompson 1966). The initial conversion was to assume instantaneous mixing of 

deposition in a soil “root zone” with a depth of 20 cm and a soil density of 2 g/cm3

. Here 

the radionuclides remain except for radioactive decay. 

This basic concept was adopted in early radiological models (e.g., Soldat and Harr 1971) 

which used a 15 cm plow depth and resulting area density of 224 kg/m2

. This approach 

was adopted by the NRC in Regulatory Guide 1.109 (1977), with a soil plow layer 

mixing depth of 15 cm and effective surface density of 240 kg/m2

 (equivalent to a soil 

density of 1.6 g/cm3

). This is assumed to represent the depth to which plowing or other 

agricultural practices mix the soil on an annual basis (so that 1-year’s deposition is mixed 

into the rooting zone and available for plant uptake). This became the default approach 

for many computer codes written to implement the concepts of this regulatory guide (e.g., 

FOOD (Baker, Hoenes, and Soldat 1976), AIRDOS (Moore et al. 1979), RSAC (Wenzel 

1993)). This basic model became the international standard with the issuance of 

International Atomic Energy Agency publication Safety Series 57 (IAEA 1982). In the 

GENII code (Napier et al. 1988), the mixing depth is defined to be a constant 15 cm (6 

in.). The code MEPAS (Strenge and Chamberlain 1995) allows user inputs, but the 

defaults are 15 cm (6 in.) for agricultural soils, and 4 cm (1.6 in.) for residential soils. 

The PATHWAY (Whicker and Kirchner 1987) model uses 25 cm (10 in.). ECOSYS 

(Mueller and Prohl 1993) uses 10 cm (4 in.) for pastures and 25 cm (10 in.) for plowed 

soil. The NCRP screening model (NCRP 1999) conservatively uses 5 cm (2 in.). 

Because of its primary use as a code for remediation of previously contaminated soils, the 

RESRAD family of codes (Yu et al. 2001) default is 200 cm (79 in.). The calculated soil 

concentration is inversely related to this assumption. Similarly, the assumed soil density 

has a direct influence on the estimated concentrations. 

It is unlikely that long-lived radionuclides introduced into surface soil would remain in 

one location forever. Therefore, additional processes of radionuclide migration have 

been considered in various models. The first mechanism considered is leaching of 

contaminants out of the root zone and into deeper soils, effectively taking them out of the 

system. This approach is used in models such as GENII (Napier et al. 1988), RESRAD 

(Yu et al. 2001), the model of Peterson (1983), and PATHWAY (Whicker and Kirchner 
3-4

1987). Leaching (as caused by overwatering for example (Schreckhise 1980)) is treated 

as an average loss rate term, generally using a first-order rate constant. The leaching 

term is thought to be dependent on the type of soil, the radionuclide, and the amount of 

water percolating through the surface and into the deeper soil. The format of Baes and 

Sharp (1981) is frequently used: 

⎥

⎦

⎤ ⎢

⎣

⎡

+

+ − =

si

s

s

s s

si

d Kd

P I E

θ

ρ θ

λ

1

 (1) 

where λsi = removal rate constant for activity of radionuclide i in the surface soil layer 

(yr-1) 

 P = total annual precipitation (cm/yr) 

 I = total irrigation rate (cm/yr) 

 E = total evapotranspiration rate (cm/yr) 

 ds = depth of soil rooting zone (cm) 

 ρs = surface soil bulk density (g/cm3

) 

 θs = surface soil volumetric water content (mL/cm3

) 

 Kdsi = surface soil distribution coefficient for radionuclide i (mL/g). 

In general, because precipitation is variable and because it is difficult to calculate the 

evapotranspiration, the P+I-E term is approximated as a constant “overwatering” term.

The factor describing mobility (or transportability) of radionuclides in soil is the Kd. 

This term is empirical and rarely easily available for specific soils in specific locations. 

Frequently, measurements may be poor; for very insoluble materials, sometimes 

experiments may measure precipitation into a solid rather than reversible sorption. The 

models in GENII, in RESRAD, in MEPAS (Strenge and Chamberlain 1995), described in 

NUREG/CR-5512 (Kennedy and Strenge 1992), and Peterson (1983) all follow the same 

structure. (The MILDOS model [Strenge and Bander 1981] is similar, but uses a constant 

50-year leaching half-time for all contaminants.) No current biosphere models have 

addressed solubility limits, which are considered to be potentially important in some 

circumstances (NRC 2002). The IAEA Safety Series 19 model (IAEA 2001) makes a 

distinction between anionic radionuclides, isotopes of strontium and cesium, and all 

other radionuclides. Anions such as TcO4 –, Cl– and I–

 are leached quickly; the default 

value for λs is 0.5 yr–1. For strontium and cesium the default value is 0.05 yr–1. For all 

other nuclides (also non-anionic Tc) the default value is zero. 

Some models have slightly more sophisticated surface soil zone models. The ECOSYS, 

PATHWAY, and MACCS (Jow et al. 1990) models include a second mechanism for 

effective removal of radionuclides from the soil for plant uptake. These models include 

an additional rate constant for “fixation” of contaminants. In these models, the 

radionuclide is bound to receptor sites in the soil and immobilized. In these models, the 

radionuclide is no longer mobile, so it is not available for plant uptake, although it still 

contributes to external exposure. 
3-5

Measurements of depth profiles of 137Cs, 239Pu, 241Am, and 237Np in undisturbed soils 

from both Chernobyl and weapons' fallout indicate that removal times can be derived that 

are considerably faster than those derived from the distribution coefficient Kd. It is 

interesting to note that the residence times of the radionuclides investigated are relatively 

similar although their chemical properties are different. Apparently, element independent 

transport mechanisms such as the transport of radionuclides attached to clay particles or 

bound to soil colloids may also play a role. Since the main transport mechanisms for 

strongly bound radionuclides may be to a large extent element-independent, the value for 

the residence half-time for the upper soil layer in the European emergency response code 

RODOS (Müller, Gering, and Pröhl 2004) is applied for all other elements with high Kd 

as zirconium, niobium, ruthenium, cerium and plutonium - a soil half-life of 100 years is 

assumed.

Another potential mechanism for loss of material from the surface soil is harvest removal 

(sometimes referred to as cropping), the process by which contaminants leave a local 

system by being harvested with the crop and removed. Hoffman and Baes (1979) 

proposed a linear rate constant to be applied annually as 

P

Biv M h Hn λhi = (2) 

where 

λhi = the harvest removal rate constant (yr-1) 

Biv = the ratio of concentration of radionuclide i in the harvested plant compared 

to that in soil (Bq kg-1 plant per Bq kg-1 soil) 

Mh = the harvested biomass of vegetation per unit surface area per harvest (kg 

m-2), the amount of plant material which is removed at harvest and not 

returned as recycle 

Hn = the number of harvests per year (yr-1) 

P = the soil area density discussed above (kg m-2). 

The ERB2A model from the IAEA BIOMASS program (IAEA 2003) uses a similar 

formulation, including averaging over all crop types with the assumption that long-term 

agriculture would include crop rotation. A similar expression is used also by Willans 

(2003) in the MONDRIAN code used at British Nuclear Fuels Limited, as well as by 

EPRI (2002). These models assume that, over long periods of time, crops will be rotated, 

and so each uses the average of the soil and crop parameters for all of the agricultural 

pathways assumed. 

In the GENII computer codes (Napier et al. 1988; 2002), loss of activity from the surface 

soil zone by harvest is modeled as a step function applied at the end of each calculational 

year. The amount of loss is calculated from the plant concentration at harvest, the annual 

plant yield, and the soil concentrations at harvest. The calculation is represented by the 

following equation. 

[ ] si si si ci Yc Csi C (t ) = C (t ) (C − C (t) )/ + − (3) 

where 
3-6

Csi(t+) = surface-soil concentration for radionuclide i after correction for harvest removal 

at time t (Bq/m2

) 

Csi(t-) = surface-soil concentration for radionuclide i before correction for harvest 

removal at time t (Bq/m2) 

Cci(t) = crop-c concentration derived from soil uptake for radionuclide i at time of 

harvest (Bq/kg) 

Yc = annual yield of crop c (kg/m2

). 

The term in brackets represents the average fraction of the contaminant in soil to that in 

crops over the year; this term is used rather than a simple subtraction of amount harvested 

because, for short-lived radionuclides, the amount harvested over the year may actually 

be larger than the amount remaining in the soil at the end of the year. Note that this 

formulation assumes that harvested materials are removed from the system, and not 

returned (for instance, as manure or fertilizer). 

Under natural conditions, the rate of soil removal by erosion generally is in approximate 

equilibrium with the rate of soil development from soil forming processes, and under 

these conditions, soil depth is relatively constant (Troeh et al. 1980). Human activities 

tend to accelerate the rate of soil removal. The removal of surface soil by erosion would 

result in the loss of radionuclides attached to the soil particles. Most models ignore this 

loss, assuming that soils lost from one location would re-accumulate in another. The 

model used for analyses for the proposed repository at Yucca Mountain, Nevada, which 

is designed to evaluate conditions over periods of thousands of years, does include a 

wind-erosion term (Wu 2003). The rate of radionuclide removal from surface soils is 

quantified in that model using a first-order surface soil erosion rate constant, defined in 

terms of the surface soil erosion rate as 

λe E ρ s ds = / (4) 

where 

λe = the surface soil erosion rate constant (yr-1) 

E = the soil surface erosion rate (kg m-2

 yr

-1) 

 ds = depth of soil rooting zone (m) 

 ρs = surface soil bulk density (kg/m3

). 

Application of the soil model for the case of continuous irrigation with a contaminated 

source results in the estimated concentration of contaminant in soil increasing with time 

until it reaches equilibrium. At equilibrium, the input rate equals the combined loss rates 

through decay, leaching, erosion, and harvest. For mobile radionuclides (those with 

small Kd values), the equilibrium can occur within a few years of the initiation of 

irrigation, as illustrated in Figure 1. However, for radionuclides with a large Kd, and a 

small soil-to-plant uptake (which minimizes harvest loss), the approach to equilibrium 

soil concentration can take hundreds to thousands of years (Figure 1). This leads to the 

requirement for an additional input—the length of time irrigation is assumed to occur 

before the exposure of the individual under consideration. Most codes, such as GENII, 

MEPAS, or RESRAD, can be set to assume that the irrigation begins either at the time 

the exposure scenario begins, or at some time before that to allow for buildup. Once 
3-7

irrigation starts, it is assumed to continue at a constant annual rate (there may be seasonal 

starts and stops).

Figure 1. Idealized Behavior of Radionuclide Concentration in Soil Following Long 

Periods of Irrigation for Mobile and Immobile Radionuclides

An example application of an irrigation model is provided by the Hanford Site System 

Assessment Capability (SAC) (Bryce et al. 2002). In the most recent modeling 

application using the SAC, irrigation is assumed to start at all locations simultaneously at 

some fixed time following Hanford Site closure and continue indefinitely (Bryce et al. 

2002). A slightly different example is provided by the analyses performed for the Yucca 

Mountain Project. In these analyses, the start time for the irrigation scenario was 

generated randomly, followed by a random period of time before exposure. Because the 

Yucca Mountain analyses use pre-calculated Biosphere Dose Conversion Factors, the 

analyses fit a set of factors generated for different periods of time following initiation of 

irrigation to an exponential curve. The analyses also used the curve fit as a simple means 

of evaluating the impacts of long periods of irrigation (Wasiolek 2001). Both the Hanford 

and Yucca Mountain analyses are projected for very long times into the future (up to 

10,000 years). Continuous irrigation using groundwater has taken place for much shorter 

periods (about 100 years) in the United States. Increasing salinity in soils is a long-term 

problem. It is still an open question whether irrigation can continue for millennia.

Some radionuclides may be released from soil to air as gasses. This mechanism is only of 

concern for radionuclides that are gases, produce gaseous progeny, or form gaseous 

compounds (e.g., 222Rn and 14C). This removal mechanism is not usually included in 

0

5

10

15

20

25

30

35

40

45

50

0 20 40 60 80 100

Time Since Irrigation Started

Soil Concentration High Kd

Low Kd

0

5

10

15

20

25

30

35

40

45

50

0 20 40 60 80 100

Time Since Irrigation Started, Years

Relative Soil Concentration

High Kd

Low Kd
3-8

most general models. It would result in non-equilibrium concentrations of decay progeny 

in the case of radon emanation. The RESRAD model includes estimation of radon fluxes 

from soils; the result is not used to deplete the soil of radon progeny. 

Most of the models described above deal with tillage or plowing in an implicit manner. 

The surface layer of soil is assumed to be uniformly mixed with the radionuclide. 

Cultivated soil is assumed to be ploughed, if not every year then every few years. This 

general concept is also used for residential soils not used for raising crops. Another 

mechanism for mixing of surface soils is bioturbation, the disturbance of soil layers by 

biological activity. These biotic pathways include transport of contaminants through 

various soil horizons by plant root systems and by burrowing insects and small mammals. 

Bishop (1989) noted that the maximum amount of soil moved by earthworms in 

established pastures is in the order of 10 kg/m2

/y (equivalent to a soil depth of around 7 

mm). In soil science, bioturbation is modeled as a diffusive process, adopted to avoid 

quantifying the numerous types of mixing resulting from flora and fauna. The diffusion 

coefficient describing bioturbation can be determined by fitting results to vertical 

distributions of natural tracers, radionuclides from fallout, or introduced particles. A 

more mechanistic approach was developed by McKenzie et al. (1986), which explicitly 

evaluated the transport of soil from various subsurface layers to the surface soil. The 

McKenzie et al. (1986) approach provides the amount of soil moved, and the fraction 

from various depth layers, per year. This is summarized in Table 1 for various 

environmental conditions, which indicates that even in relatively undisturbed soils 

without plowing, mixing will occur to substantial depths relatively rapidly. 

Table 1. Biotic Transport Quantities (adapted from McKenzie et al. 1986)

 

 Volume Transported to the Surface (m3

 m

-2

 yr

-1) 

 Environmental Condition 

 Depth of Soil Layer Arid Humid Agricultural 

 < 0.15 m 9.41E-4 7.48E-4 7.48E-4 

 0.15 - 0.5 m 7.62E-4 6.73E-4 6.73E-4 

 0.5 - 1.0 m 1.79E-4 7.18E-5 7.18E-5 

 1.0 - 1.5 m 1.88E-5 4.49E-6 4.49E-6 

 1.5 - 2.0 m 7.53E-6 3.74E-8 3.74E-8 

 > 2.0 m 1.88E-6 3.74E-8 3.74E-8 

3.2 Modeling Resuspension 

Resuspension relates the concentration of contaminants in air above a contaminated 

surface resulting from losses from that surface to the air. Resuspension occurs when 

wind exerts a force on surface material or when there is a mechanical action that disrupts 

the surface (such as agricultural operations or vehicular movement). Modeling 

resuspension is not easy because of the large number of potential variables. The main 

ones include: 
3-9

• Particle size, shape and adherence; 

• Wind speed, 

• Surface type and cover (measured in terms of “roughness”); 

• Time since deposition; 

• Intensity of the mechanical action. 

To quantify the suspension of contaminated soil/sediment into the atmosphere, three main 

approaches have been usually used: - resuspension rates, resuspension factors, or mass 

loading. The resuspension rate is a measure of the fraction of material entering the air 

per unit time, and has units of s-1. The resuspension factor relates the radionuclide 

concentration in soil (per unit area) to the concentration in air and has units of m-1. The 

resuspension rate is a mass of soil, assumed to have a contaminant concentration directly 

related to the source soil, suspended in a volume of air. The mass loading approach 

essentially assumes that the amount of radioactive contamination in the air is associated 

with dust having the same concentration as local soil. The resuspension factor for food 

crop and animal product pathways is representative of conditions on farmland, which 

may be different from the resuspension factor for the inhalation exposure pathway. 

Farmland would be expected to be tilled and have soil generally looser than soil for the 

general residential exposure situations. 

The use of resuspension rate approach is based on the transfer of contamination from the 

soil surface into the air. The resuspension rate is defined to be the ratio between particle 

flow density and soil contamination, thus, the resuspension rate dimension is a reciprocal 

time. This method provides a rate constant for loss from the surface soil; an additional 

model is required to convert this into an air concentration. 

The use of resuspension factors in the dose assessments is based on the assumption that 

the particulate matter in the air has the same activity as the soil at the location. The 

resuspension factor is defined to be the ratio between air concentration and soil 

contamination, thus, the resuspension factor dimension is a reciprocal length. This is 

represented mathematically as follows. 

Ca = RF Cs (5) 

where Ca = air concentration of radionuclide (Bq/m3) 

 RF = resuspension factor (m-1) 

 Cs = average surface soil concentration (Bq/m2

). 

Resuspension factors have been found to cover a wide range (10-10 to 10-3 m-1), 

depending on many factors, although this variability is based on short sampling times and 

long-term variability will be less (Garger, Hoffman, and Thiessen 1997). This approach 

allows a convenient method of expressing the observed relationship between surface and 

air contamination, but with a number of limitations. There is an implicit assumption that 

the air concentrations are a result of the local surface contamination, however, the air 

concentration usually includes resuspended materials from upwind sources, which may 

be contaminated at different levels. In addition, the time scale of the measurements 

(generally short) may not correspond to long-term average needed for annual-averaged 

models. A decrease in the amount of resuspension has been observed with time, caused 
3-10

by weathering, erosion, or migration of materials down into the soil. This time 

dependence has been considered by modelers (e.g., Anspaugh et al 1975; CEC 1995; 

Linsley 1978) and experimentalists (e.g., Garland et al. 1982). Many authors have 

described the time dependence using exponential factors, but Garland (1979) found that 

an inverse power function fitted wind tunnel data over a period of several months. A 

recent review (Walsh 2002) recommends the Garland approach modified to account for 

long-term resuspension, given as 

[ ] ti RF t e − − − −λ = × + 6 1 9 1 (6) .2 10 10

where 1.2x10-6 = resuspension factor at the time of initial deposition to soil (m-1) 

 t = time after initial deposition of material to soil (d) 

 10-9 = resuspension factor after a long time (m-1). 

 

The second term in this equation is added based on the assumption that no further 

measurable decrease in the resuspension factor process occurs after the longest period for 

which there are data available. In the implementation, an assumption is made that only 

the top thin layer of soil is available for resuspension. 

The atmospheric mass loading of soil in air approach equates the radionuclide 

concentrations in soil to measured or estimated dust levels in air. Mass loading is used to 

estimate the resuspension factor as follows: 

s ds

S RF

ρ = (7) 

where S = mass loading of soil in air (g/m3

), 

 ρs = surface soil density (g/m3

), 

 ds = thickness of surface soil layer (cm). 

Different resuspension models may be recommended for different contexts (Garger, 

Hoffman, and Thiessen 1997). The resuspension rate and resuspension factor models may 

be betters suited for analyses following single acute depositions. The simple massloading model may be better suited, and more stable, for analyses of long-term soil 

accumulation, because it is not based on measurements from single deposition events, as 

is the resuspension factor approach. 

3.3 Modeling Radionuclides in Vegetation 

Radioactive contamination of vegetation may be a major contributor to human health 

impacts through both direct ingestion and/or indirect transfers via the food chain. Plants 

may become contaminated by various processes including direct deposition, external 

contamination with local contaminated soil via resuspension or splashup, incorporation 

into edible parts of contamination deposited on leaves or stems, and uptake via the roots. 

The basic components to be modeled are illustrated in Figure 2. 
3-11

Outside

Inside

Decay

Dry Wet

Weathering

Decay

Soil

Outside

Inside

Decay

Dry Wet

Weathering

Decay

Soil

Figure 2. A Basic Model for Contamination of Plants

3.3.1 Modeling Foliar Interception and Retention 

Deposition of airborne contamination is largely a function of particle size and 

precipitation. Radionuclides can be present in air as single atoms, as chemical 

compounds, or as contaminants attached to dust or other aerosol particles. As a general 

rule, one can expect the deposition of radionuclides to be governed by the physical 

processes involving aerosol-land surface interactions. The rate of radionuclide deposition 

from the atmosphere to the ground is proportional to concentrations in air, although the 

actual deposition is also affected in complex ways by particle characteristics, receiving 

surface properties, and weather conditions. 

Airborne radionuclides can be deposited onto soil or vegetation by “dry” mechanisms 

such as gravitational settling, surface impaction and electrostatic attraction and by “wet” 

mechanisms such as washout or rainout during precipitation events (Kinnersley and 

Scott, 2001). As a general rule, particles with diameters larger than about 20 μm and 

densities higher than 1 g cm–3 are affected more by gravity than atmospheric turbulence 

(Whicker and Schultz, 1982). Deposition of these larger particles can be predicted using 

Stoke’s law to evaluate a gravitational settling velocity. Smaller particles that are 

affected more by atmospheric turbulence than gravity can travel great distances before 

depositing. Deposition of these smaller particles is affected not only by particle size and 

density, atmospheric turbulence and precipitation, but also by the nature of the plant 

surfaces that the particles land on. 

Contaminants may also be deposited through human activities such as irrigation. The 

typical irrigation cycle can be from one to many hours. Once plant surfaces are initially 

wetted, subsequent water flows to soil as run-off. The question is how much of a 

particular element can be entrained, adsorbed, and/or absorbed during an irrigation event. 

Nair (Nair et al. 1996) found in rainfall simulation experiments that larger particles 

tended to adhere to the surface of vegetation and that subsequent rainfall was ineffective 

in removing what had interacted with the leaf surface during an initial rain event. For 

anions, like various forms of iodine, the radionuclides followed the water. But, if drying 
3-12

occurred, then subsequent rainfall was ineffective in removing iodine from the leaf 

surface. This would likely be true for chemical forms having low to intermediate 

absorption rates and for elements with low adsorption rates, or with high absorption rates 

with limited leaf-surface binding sites. It may not be true for elements with exceptionally 

high bioavailability, as would possibly be the case for technetium and nickel. 

Many models, e.g., RESRAD, MEPAS, and CAP88-PC (Chaki and Parks 2000), use a 

constant dry interception fraction of 0.25. The MILDOS code uses 0.2. The IAEA 

(2001) Safety Standard model uses a mass interception factor, defined as the fraction of 

deposited activity intercepted by the edible portion of vegetation per unit mass (or mass 

interception factor, m2

/kg), which is set equal to 3 m2/kg (dry weight) for forages and 0.3 

m

2

/kg (wet weight) for foods consumed directly by humans. 

For a specific deposition event, the interception fraction is higher the more developed the 

plant canopy, which is accompanied with an increasing contact surface between the 

falling rain and the plant surface. There are two principal approaches to parameterize the 

plant development, the standing biomass per unit soil surface area and the leaf area per 

unit soil surface area (leaf area index). The advantage of the standing biomass is that it is 

easy to determine. The sample has simply to be taken from a known area of ground, 

dried, and the dry mass has to be determined. However, the biomass does not really 

represent the size of the interface rain/plant, which is the case for the leaf index. Whereas 

in the first period of growth, in general a good relationship between biomass and leaf area 

can be observed, the correlation fades away towards the end of growth. Then, the 

biomass still increases due to growth of storage organs as seeds or tubers while the leaf 

area already decreases substantially due to dying off of the foliage. The disadvantage of 

the leaf area index is that quantification is a complicated determination that requires 

specific optical devices which are usually not available. However, a wide variety of data 

on leaf area indices for terrestrial systems has recently become available from NASA 

satellite imagery as a result of their involvement in carbon cycle and climate research, 

which may simplify this problem. 

Models that at least account for biomass have been proposed. An empirical relationship 

between biomass and interception fraction from atmospheric dry deposition was 

originally suggested by Chamberlain (1967). This model has been expanded by Pinder et 

al. (1988) for grasses and other species. The following form of the equation is suggested: 

c c A Y f

dc r e− = 1 (8) −

where 

rdc = interception fraction for atmospheric dry deposition to crop type c (dimensionless) 

A = empirical constant, about 2.9 for grasses, leafy vegetables, and grains, and 3.6 for 

fruits and other vegetables 

Yc = standing biomass of the growing vegetation for crop type c (kg wet weight/m2

) 

fc = dry-to-wet weight biomass ratio for crop type c (kg dry weight per kg wet weight). 
3-13

The dry-to-wet ratio is required because the Pinder formulations are given in terms of dry 

biomass. This formulation results in the need to define the growing biomass as well as 

the harvested yield. 

The interception of material in irrigation water is not well studied. Thus, a default value 

of 0.25 is often used for all materials deposited on all plant types by irrigation. The 

results described above for irrigation are probably applicable. An empirical equation for 

the interception fraction, rw, used in the Yucca Mountain model ERMYN (Wu 2003) 

derived from data from Hoffman et al. (1989), which is based on the results of 

experiments with 7

Be and 131I, is expressed as 

2 3 4

1

K K

c

K

wc c r = K Y IA I (9) 

where 

rwc = interception fraction of irrigation water for crop type c (dimensionless); 

K1, K2, K3, and K4 = empirical constants (K1 is in units of (kg/m2

)

-K2 (mm)-K3

(cm/hr)-K4,and K2, K3 and K4 are dimensionless); 

Yc = standing biomass of crop type c (kg dry weight/m2

); 

IAc = amount of irrigation per application event for crop type c (mm); 

I = irrigation intensity (value in units of cm/hr). 

Because this is a regression equation from experimental data, values for the input 

parameters must be used in the units specified above. The empirical constants in this 

equation were developed based on given parameter units for standing biomass, irrigation 

amount, and irrigation intensity, depend on the plant type and contaminant form. The 

recommended values (Hoffman et al. 1989) are: 

K1 = 2.29 for beryllium (Be+); K1 = 1.54 for iodine (I-) 

K2 = 0.695 for beryllium (Be+); K2 = 0.697 for iodine (I-) 

K3 = -0.29 for beryllium (Be+); K3 = -0.909 for iodine (I-) 

K4 = -0.341 for beryllium (Be+); K4 = -0.049 for iodine (I-)

The interception fraction for wet deposition can be also evaluated as a function of the 

rainfall rate and standing biomass based on experimental observations of Prohl and 

Hoffman (1993). The data by Prohl and Hoffman were used to develop relationships for 

anions, cations, and for insoluble particles for the GENII Version 2 application (Napier et 

al. 2002). For anions, such as iodide and sulfate, the interception fraction is evaluated as 

follows: 

0.92 2.3 − rwc = Yc f c R (10) 
3-14

where 

rwc = interception fraction from wet deposition to crop type c (dimensionless) 

Yc = standing biomass of the growing vegetation for crop type c (kg wet weight/m2) 

fc = dry-to-wet weight biomass ratio for crop type c (kg dry weight per kg wet weight) 

R = rainfall rate (mm/d), 

and the numbers are regression parameters. 

For cations and particles, Prohl and Hoffman (1993) presented the following relationship 

based on experiments using microspheres (essentially the same data as Hoffman et 

al.1989): 

0.191 2.95 − rwc = Yc f c R (11) 

where terms are as previously defined. In both equations, the numerical term is a fitting 

parameter with units of m2

/kg. A potential disadvantage of this approach based on 

biomass is that it is intended primarily for leafy-type produce; its indiscriminate use 

could result in the more massive fruits such as apples, melons, tomatoes intercepting 

more irrigation water than the less massive but more expansive (e.g., surface area, leaf 

index) lettuce or spinach plant. The selection of which biomass to use is important. 

Beyeler et al. (1999) also evaluated the results of Prohl and Hoffman (1993). Beyeler et 

al. (1999) decided that it was difficult to assign anion/cation status without site-specific 

knowledge of groundwater chemistry and elected to use a single range of interception 

fractions. They recommend a central value of about 0.35 within a uniform range of from 

0.1 to 0.6 for all crop types. 

The ECOSYS code uses a formulation based on Leaf Area Index (LAI) and the waterstorage capacity of plant leaves. Buildup of the water film on the leaves during wetting 

events, the total amount of water deposited, and the radionuclide’s ability to be fixed on 

the leaf (another interpretation of the data of Prohl and Hoffman) are considered. In this 

formulation, the wet interception fraction is estimated as 

⎥

⎦

⎤ ⎢

⎣

⎡

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ − = − R

S

r LAI S R

i

wc i i 3

ln 2 / (12) 1 exp

where LAI is the leaf area index of plant i, Si is the retention coefficient for plant type i 

(mm), and R is the amount of rainfall (mm). 

If this equation results in an interception fraction greater than one, the value is set to one. 

Muller and Prohl (1993) provide estimates for the retention coefficient. As for the 

modified Chamberlain model described above, these vary for grasses, cereals, and corn, 

and for other plants. 
3-15

Measured interception fractions for a limited number of radionuclides are becoming 

available for Asian food types not usually included in American risk assessments such as 

rice, radish, soybeans, and Chinese cabbage (Choi et al. 1998; 2001; 2002; Lim et al. 

2001). 

Many investigators have commented that the plant biomass and the interception fraction 

are directly correlated, and a more stable estimate of interception may be obtained using 

the quotient r/Y as a single variable (IAEA 1982). The interception fraction r rapidly 

increases with the increasing plant biomass during the first half of the growing period and 

thereafter it is almost constant or even decreases (Vandecasteele et al. 2001). In contrast 

to r, the biomass-normalized interception fraction r/Y decreases as plants grow from the 

beginning. The r/Y values at the early growth stages are conspicuously high, because 

most of the young leaves are directly exposed to deposition with comparatively low 

mass-to-area ratios. Accordingly, the r/Y is a useful parameter in estimating the initial 

plant concentration after an accidental deposition but it is unnecessary during routine 

conditions for which such an initial concentration cannot, and need not, be calculated. For 

assessing continuous deposition, instead, an averaged value of r/Y can be used, or simply 

a lumped parameter that is a ratio between the deposition rate and the steady state 

concentration per gram of plant material. 

Kinnersley and Scott (2001) suggest that the complex three-dimensional structure of crop 

canopies is such that no purely mechanistic model yet exists which can predict the 

turbulent transport of airborne particulate contamination into, and onto, them. While 

theoretical understanding of the processes involved in particle dry deposition has 

advanced considerably in the last decade or so, a gap remains between theory and the 

practical prediction of particle deposition, particularly under non-laboratory conditions. 

Bonka and Horn (1983) produced a thorough review of the mechanisms governing 

deposition of aerosols to vegetation, from which it can be deduced that analytical 

deposition models are currently limited by uncertainty in the aerosol collection efficiency 

term. This term must be determined experimentally for canopies consisting of anything 

but regular arrays of the simplest geometrical shapes. The review describes the model of 

Slinn (1982), in which the maximum possible deposition velocity (assuming the canopy 

to be a perfect sink) is attenuated by a term, ultimately empirical in derivation, allowing 

for the particle collection efficiency of the canopy. Data requirements for this model 

include a “vegetative hair fraction”, a “small vegetative diameter” and a “large vegetative 

diameter”. Another well-known model for deposition to vegetation is that of Sehmel and 

Hodgson (1978). This model takes into account the underlying physics of particle 

interception in some detail, including amongst its input data requirements details of the 

turbulence, boundary layer and surface layer resistances, but again it is ultimately 

dependent on empirical terms determined in a wind tunnel. A third approach has been 

adopted in the Imperial College (IC) model. This is based on multiple regression analyses 

of a considerable database of deposition values generated under wind tunnel conditions. 

The regressions use the three parameters - particle size, turbulence levels and canopy size 

- which theory suggests should dominate control of the deposition process. These three 

models give broadly similar results, which are compatible with the few reliable field 

measurements of deposition to crop canopies which currently exist. Despite data 
3-16

requirements which can become complex, current deposition models ultimately retain a 

dependence upon experimentally determined factors. However, there is a lack of reliable 

data of this sort. This is particularly so for the interception of particles less than 40 μm in 

diameter (Chamberlain & Garland, 1991) and for larger canopies such as those of fruit 

crops. 

For prolonged deposition to vegetation (as occurred after weapons testing), Chamberlain 

introduced the concept of normalized specific activity (NSA), defined as the ratio of 

radionuclide concentration in foliage (Bq/kg dry weight) to the rate of deposition to 

ground (Bq/m2

/d). A value of 40 m2d/kg was considered appropriate for herbage in good 

growing conditions; much lower values have been found for grains (Simmonds and 

Linsley 1982). NSA values are much higher for poor growing conditions and some types 

of native vegetation (Martin and Coughtrey 1982). 

3.3.2 Modeling Contamination of Plant Surfaces with Soil 

Plants may acquire surficial contamination in the form of dust or soil particles; the source 

is the soil in which the plant is growing. Certain types of plants, such as leeks, are 

frequently associated with soil carryover. 

Contaminants sorbed to soil particles may be resuspended by wind, human, animal, 

mechanical disturbances and redeposit locally on the plant surfaces. Such redeposition 

occurs when soil is displaced by wind (Anspaugh et al. 1975), animal disturbance 

(Hinton et al. 1995; Sumerling et al. 1984) or mechanical disturbance (Milham et al. 

1976; Pinder and McLeod 1988; 1989). Another physical mechanism for contamination 

of plant surfaces with soil particles is raindrop splash (Dreicer et al. 1984). In the 30-km 

zone around Chernobyl, rainsplash of contaminated soil contributed significantly to 

overall plant contamination, with 60 to 70% of the activity concentrated on the basal 

parts (10 to 20 cm above the soil surface) of cereals and perennial grasses (Kryshev 

1992).

Plant contamination may also be caused by mechanical disturbances that raise dust, such 

as occur during weeding and harvesting. Adriano et al. (1982) and Pinder and McLeod 

(1988; 1989) have reported this to be a major source of plutonium contamination in grain 

grown on contaminated soils. Plants may acquire surficial contamination in the form of 

dust or splashed-up soil; the source is the soil in which the plant is growing. Soil-to-plant 

transfer values via the roots for some actinide elements are on the order of 10-6 to 10-5

(Bq/kg dry crop)/(Bq/kg dry soil). This very low transfer from soil via the roots means 

that the contamination of a crop due to contaminated soil resuspended or splashed on the 

leaf surface may easily dominate the plant physiological uptake. A contamination of only 

1 mg soil per kg fresh weight crop can cause an apparent transfer value of 10-5 for 

splash-up and resuspension transfer factors. Thus this pathway may be of importance in 

some analyses of radionuclides that are biologically discriminated against. 

The simplest approach is to define a soil adhesion quantity for each type of crop plant. 

This combines the effects of interception of locally-resuspended material and the 

splashing of rain and irrigation water droplets, and allows averaging of the effects of 
3-17

various factors such as height and type of plant canopy, wind, rain, and soil type. This 

approach is suggested by IAEA (1994) and used by Kennedy and Strenge (1992). The 

later IAEA model (IAEA 2001) combines this mechanism with the soil-to-plant transfer 

into a single transfer parameter (see below) - to account implicitly for soil adhesion, a 

minimum value of 0.1 is assigned to the soil-to-plant transfer factor for forages and 0.001 

to the transfer factor for human foods. However, this approach is not recommended by 

the International Union of Radioecologists, who state that “Values of soil adhesion 

depend so much on environmental conditions that it is not realistic to propose a default 

value. However, an estimate for a low value of soil adhesion is 4 g soil per kg dry 

vegetation for leaves and grass taken from 40 cm or more above the soil surface. Below 

40 cm, 10 g per kg might be a reasonable estimate for leaves and grass. Considerably 

lower values are expected for products such as grain, which are protected by plant parts 

which are not consumed. A reasonable upper limit for soil adhesion is 250 g per kg.” 

The processes of suspension and deposition are parameterized as consisting of 

resuspension of contaminated soil followed by local redeposition in some models. This is 

the approach taken by the GENII family of codes, as well as the RESRAD family of 

codes, PATHWAY, and ECOSYS. The resuspension factor for food-crop and animalproduct pathways is representative of conditions on farmland, which may be different 

from the resuspension factor for the inhalation exposure pathway. Farmland would be 

expected to be tilled and have soil generally looser than soil for the general residential 

exposure situations. 

Many models circumvent the necessity of dealing with soil adhesion by specifying 

amounts of soil ingested by humans and domestic animals. However, this approach then 

neglects the potential for transfer from the plant surface to the internal portions of the 

plant. It also complicates the modeling of weathering of deposited material off of plant 

surfaces, discussed below. 

3.3.3 Modeling Weathering from Plant Surfaces 

Material deposited on vegetation may be lost from the plant through a variety of different 

processes in addition to radioactive decay, such as removal by wind or rain, 

volatilization, plant senescence (leaf drop), and others. Wind is thought to dominate the 

field-loss process for particulate contamination, with the contribution of rainfall being 

significantly less (Kinnersley and Scott 2001). In fast-growing vegetation, a decrease in 

concentration may be seen as a result of dilution by new vegetative material, and ascribed 

to a removal process. 

Losses from plant surfaces are frequently represented by a weathering rate constant, λwi. 

Several processes may be involved. Some measurements of this process have implicitly 

included plant growth. Volatile materials may evaporate back into the air. If 

precipitation occurs, or there is heavy irrigation, physical washoff processes may be 

present. Because of the combination of potential processes, this phenomenon is 

sometimes called field loss. 
3-18

The lack of detailed measurements of contamination loss over time has led to the use of a 

simple exponential model for weathering (Chadwick and Chamberlain 1970). The 

NRC’s Regulatory Guide 1.109 (NRC 1977) uses a weathering half-time of 14 days. The 

default-rate constant in GENII, and in PATHWAY for all radionuclides other than 

iodines, is based on a weathering half time of 14 days. The values in IAEA Safety Series 

57 (IAEA 1982) are 15 days for particulates and 10 days for iodines; that used in the 

IAEA Safety Reports Series 19 (IAEA 2001) is 14 days. The value in RESRAD (20 

year-1) is equivalent to a half-time of about 12.6 days. ECOSYS uses a half-time of 25 

days; the ECOSYS model attempts to account also for dilution via plant growth in 

pasture grasses. When combined, the ECOSYS results are in the range of 10 to 16 days. 

Statistical analysis of data from literature shows a log-normal distribution for half-lives 

and gives a default value (geometric mean) for estimating the removal of radionuclides 

from vegetation based on a half-life of 17 days1

. 

Kinnersly and Scott (2001) report that the dominant weathering/field loss processes are 

the resuspension of particles into the air by atmospheric turbulence, and loss through 

biological processes such as leaf-loss and cuticular wax-shedding. In recent years much 

higher resolution studies have been carried out (Ertel, Voigt, and Paretzke 1989; Fraley, 

Chaveg, and Markham 1993; Kirchner 1994; Kinnersley et al. 1996), and it is now clear 

that field loss is best described in terms of rapid and slow loss components. The slow loss 

component can be so slow as to be negligible, such that it can be treated as a fixed 

fraction of contamination that will not be lost over time, yielding a model (not including 

radioactive decay) of the form (Kinnersley et al. 1997): 

t

t r r A A A A e −λ = + ( + ) 0 (13) 

where A0 is the initial level of contamination, At is the level of contamination at time t, Ar 

is the fraction of the original deposit not subject to loss, and λ is the time constant for the 

fraction of initial deposit subject to exponential loss. This particular empirical 

formulation may also represent the fraction of material that is absorbed and/or 

translocated by the plant versus that which remains on the surface and is available for 

weathering (see the next section). 

The simple one-exponential approach or the NSA are the easiest to implement in 

situations with continuing deposition; the Kinnersly et al. (1997) formulation is better 

suited to single deposition events. Similarly, models such as that in ECOSYS that 

attempt to account for dilution of contamination in growing crops are better suited for 

single depositions; a long-term average field loss is better suited for continuous 

depositions where the intended use is determination of ultimate concentration at harvest. 

 

1

 E. Leclerc, unpublished data prepared for the IAEA’s Environmental Modeling for Risk 

Assessment coordinated research program. 
3-19

3.3.4 Modeling Foliar Absorption and Translocation 

Above-ground parts of plants (leaves, blossoms, fruits, and branches) can directly absorb 

water and minerals as well as soluble radionuclides. This process is called foliar 

absorption. Some radionuclides, once absorbed into the body of the plant, will remain at 

or very near the location from which they were absorbed. Other radionuclides may be 

transported via the phloem of the plant to other plant structures, organs, or fruits. This 

process is referred to as translocation. 

The processes of absorption and translocation are dependent on the physical and chemical 

forms of the contaminating radionuclides. Materials incorporated in relatively large 

particles are not easily absorbed, and so are unlikely to be affected by translocation. 

Contaminants in ionic form are more likely to be absorbed. 

The foliar absorption of 137Cs that was sorbed to resuspended soil particles was quantified 

at two sites contaminated by the Chernobyl accident. Although measurable, this foliar 

absorption was considered inconsequential relative to other plant contamination 

pathways, which led to the recommendation that it not be considered a critical pathway in 

routine radionuclide transport models (Hinton et al. 1996).

Once absorbed, the processes of weathering from the plant are changed; transport by 

wind and rain are much reduced, although physical losses such as leaf drop will remain. 

The translocation factor indicates the fraction of total deposition to plant surfaces that is 

incorporated into edible parts of the plant. This mechanism incorporates two processes - 

Initial uptake by the leaf and subsequent translocation throughout the plant is dependent 

on the cuticular properties of the plant, its wetability, strength of absorption onto the 

cuticle, the radionuclide in question, its solubility, size, speciation, and the time between 

contamination and harvest. The importance of uptake and translocation will be 

dependent on what part of the crop is to be eaten and what species of radionuclide has 

been intercepted. 

In many models, e.g., GENII (Napier et al. 1988; 2002), RESRAD (Yu et al. 2002), and 

CAP88-PC (Cahki and Parks 2000), the translocation factor is defined to be the fraction 

of total deposition to plant surfaces that is incorporated into edible parts of the plant. A 

value of 1 is assumed for leafy vegetables and forage crops where the whole aboveground portion of the plant is eaten, and 0.1 for all other vegetation. The value of 0.1 is 

assigned on the basis of very little information and is assumed to be an upper bound. 

The IAEA (1994) provides two alternative definitions for the translocation factor, as 

1 ( / )

( / )

2 2 activity retained on m of foliage at the time of deposition Bq m foliage

activity concentration in the edible parts at harvest Bq kg T = (14)

1 ( / )

1 ( / )

2 2

2 2

activity retained on m of foliage at the time of deposition Bq m foliage

activity concentration in the edible parts of m at harvest Bq m Ta = (15) 
3-20

Note that each of these formulations has different units. IAEA (1994) recommends using 

the first approach, normalized to the yield in kilograms, as having less measurement 

variability. A later IAEA safety series model (IAEA 2001) includes translocation 

implicitly in the definition of the foliar interception factor used in that (intentionally 

conservative) model. 

The relative rates of absorption of chemical elements from cuticular structures are 

difficult to quantify. First, absorptive capacity differs from root processes in that there 

are apoplastic/tricome routes of entry into the foliar interior, which are less 

discriminating (with respect to species discrimination) than for roots. Secondly, the 

transfer of individual elements is very dependent on chemical form and stability. For 

example, free cations and stable anions may be readily absorbed, while reactive or 

unstable species may not be absorbed, or absorbed to a lesser extent. The transfer 

process is basically a molecular level interfacial film flow. Thus, only molecular-sized 

materials can move. Finally, refractory particles, i.e., oxides, carbonates, and hydroxides, 

of any size will not likely be transferred to the tissue interior unless a significant rate of 

solubilization is occurring, e.g., complexation agents in irrigation waters. These particles 

can and will, however, be entrained within the complex cuticular structures associated 

with most surface foliage. 

There has been much research into agricultural chemicals applied to foliage, some of 

which has been performed with radioactive tracers (e.g. starting with Tukey and Wittwer 

1956; Tukey et al. 1956). Potassium and sodium were found to be rapidly absorbed and 

highly mobile. Phosphorus, sulphur, and chlorine were absorbed at a slower rate, but 

were also mobile and were transported at a rapid rate. Manganese, zinc, copper, and 

molybdenum were found to be slightly mobile. Calcium, strontium, barium, iron, and 

magnesium were readily absorbed but did not move out of the leaf to which they were 

applied. McFarlane and Berry (1974) reported that the rate at which cations penetrate the 

cuticle is inversely related to the radius of the hydrated ion, which occurs in the order 

Cs>Rb>K>Na>Li>Mg>Sr>Ca. Aarkrog (1975) reported that different radionuclides were 

translocated to a varying rate and degree in the order: 

Zn>Fe>Cs>Co>Mn>Na>Cd>Sb>Cr>Sr~Ce~Ru>Ba~Hg~Pb. This pattern may vary 

with the chemical state of the element and the presence of complexing agents. The 

solution sprayed on the crops had a pH of 1.6 and solubilities would be diferent from 

those in actual rainfall. Also, only the activity rather than the species of the radionuclides 

applied is known so the results may not be representative of a realistic situation. Bukovac 

and Wittwer (1957) suggested mobility in the order: 

Rb>Na>K>P>Cl>S>Zn>Cu>Mn>Fe>Mo>Ca>Sr>Ba. Distribution of Rb, Na, K, Cl, P, 

S and possibly Zn appeared proportional to the metabolic activity of various plant tissues. 

Foliar absorption is time dependent, i.e., the longer a contaminant is retained on a leaf the 

greater is its absorption. Higher absorption rates have been documented in younger leaves 

(Hull et al., 1975), and significant percentages of the total cesium intercepted by foliage 

can be absorbed within a few days (Carini and Bengtsson 2001).
3-21

While little data exist to demonstrate or quantify foliar absorption processes and 

particularly rates of transfer, a list of probable behaviors for priority radionuclides is 

given in Robertson et al. 2003. This categorization is based on known behavior in

soil/plant systems and likely chemical speciation in groundwaters. This listing is based

on many assumptions. Although much data exist for nickel and technetium, little is 

known of the foliar routes of entry for any of these elements. The intermediate category 

is questionable, but the limited data available would indicate that there is a need for study 

of particularly uranium, iodine, and americium. In the proposed Low Transfer category, 

little is known about the behavior of beryllium and niobium.

In the RODOS code (Müller, Gering, and Pröhl 2004), the translocation process is 

quantified by a translocation factor defined as the fraction of the activity deposited on the 

foliage being transferred to the edible parts of the plants until harvest. It is dependent on 

the element, the plant type, and the time between deposition and harvest. In this 

formulation, only a single deposition is assumed, so the time from deposition to harvest is 

important. The elements are grouped into two sets, mobile and immobile; the most 

reliable data for translocation are available for Cs and Sr. Therefore, as long as no other 

quantitative data are available, the translocation of mobile elements assumes that they 

behave like Cs, except for Mn, for which translocation factors are assumed to be lower by 

a factor 0.6 than for Cs. Strontium is considered to be representative for immobile 

elements. The RODOS assignments are also shown in Table 2; it can be seen that there is 

some coincidence of interpretation with Robertson et al. (e.g., Tc, Pu, Sr), and some 

disagreement (e.g., Np). Note that the RODOS implementation tends to focus on 

radionuclides with shorter half-lives.

Table 2. Probable Bioavailability/Cuticular Transfer of Selected Elements. This refers to 

foliar uptake, and not specifically phloem mobility and redistribution (adapted 

from Robertson et al. 2003 and Müller, Gering, and Pröhl 2004) 

High Transfer Intermediate Transfer Low Transfer 

Np Am Pu 

Tc Cs Th 

Ni U Be 

 Cm Nb 

 I Sr 

 Se 

 Ag 

 Sn 

Mobile Immobile 

Co, Cs, I, Mn, Mo, Na, 

Rb, Sb, Tc, Te 

Ag, Am, Ba, Ce, Cm, La, 

Nb, Nd, Np, Pr, Pu, Rh, 

Ru, Sr, Y, Zr 
3-22

There is unfortunately no in-depth compilation of the rates of retention nor uptake of 

radionuclides into the plant via foliar contamination. Kinnersley and Scott (2001) 

undertook model parameterization for wet and dry deposition processes to plant surfaces. 

This theoretical parameterization is reasonable, but there is a nearly total lack of 

supporting data. The IAEA (1994) provides a limited number of rate constants for a few 

elements for a few crop types.

Translocation and weathering are, in some senses, competing processes for transport of 

material off of plant surfaces. This is often overlooked in model formulation: material 

translocated may be affected by the weathering terms if not separately considered. The 

ERB2A model from the IAEA BIOMASS program (IAEA 2003) and the Yucca 

Mountain ERMYN model (Wu 2003) are examples that specifically separate these two 

effects. This is done by developing a fraction of the surface contamination to which 

weathering processes apply – the difference between the total and the translocation 

fraction. These models do this by adding additional parameters in the following fashion: 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛

+ − =

−

c

abs p trans

c

p

T

abs

c irr wc Y

F F F

Y

F e F

C r S

w

3 2

,

(1 ) λ

 (16) 

Cc,irrig = radionuclide concentration in the edible part of the crop due to irrigation water 

deposited on crop leaf surface (Bq/kg fresh weight of crop) 

rwc = fraction of radionuclides in spray irrigation water initially deposited on standing 

biomass (dimensionless) 

S = annual irrigation deposition (Bq m-2); 

Ftrans = fraction of absorbed activity translocated to edible portions of the plant by the 

time of harvest (translocation fraction) 

Fabs = fraction of intercepted radionuclide initially deposited onto plant surfaces 

absorbed from external surfaces into plant tissues (dimensionless) 

Fp2 = fraction of internal contamination in the edible parts of plants at harvest that is 

retained after food processing (dimensionless) 

Fp3 = fraction of external contamination from interception retained on edible parts of 

the plant after food processing (dimensionless) 

λw = removal (weathering) rate for radionuclides deposited on plant surfaces by 

irrigation (weathering processes include mechanical weathering, wash-off, and 

leaf fall) (yr-1) 

T = interval between irrigation and harvest (yr) 

Yc = biomass of the crop (kg fresh weight/m2). 

3.3.5 Modeling Soil-to-Plant Uptake 

Terrestrial plants, as sessile organisms, have adapted to derive essential nutrients from 

their environments. Plants absorb nutrients through their roots and transport them via the 

phloem to active portions of the plant. Biotic factors are likely the source of much of the 

variability seen in concentrations of contaminants in plants. This variability results from 

the nature of the sessile terrestrial plant and its relationship with its environment: the need 

to compete and acquire specific nutrient species from soils (or to avoid uptake of 
3-23

excesses of potentially toxic materials), the need of individual plant types for specific 

levels of individual nutrients, and the use of certain metals in tissues as agents to 

discourage herbivory. Thus, the uptake is affected by the following biotic factors: 

1. the plant-available concentration in soils within the rhizosphere (the soil zone that 

surrounds and is influenced by the roots of plants), which is governed by soil 

adsorption processes, chemical solubility, microbial/fungal activity, and stability of 

the chemical complexes 

2. the chemical nature and stability of the cation-anion/complex with respect to the 

plant’s capability to metabolically alter and/or absorb the elemental form into the 

plant 

3. a series of plant adaptive/evolutionary processes for survival; this can include, but not 

be limited to, protective root processes (exclusion or complexation of an ion for 

detoxification, sequestration within the plant to regulate both ion levels and for 

detoxification, redox to alter solubility and transport when necessary, organic 

complexation in the case of all but mono-cationic elements, and uptake capacity 

being dependent on metabolic needs). 

Under these chemical and biotic constraints, uptake can be expected to vary based on 

source term, kinetics of solubilization/speciation, the relative ability of a plant to view a 

non-nutrient ion as an analogue to a nutrient species, and the relative need by the 

individual plant genus/species for specific levels of a particular ion. 

Transfer of radionuclides from soils into plants is one of the key mechanisms for longterm contamination of the human food chain. There are several methods that may 

potentially be used. The most common is through the use of soil-to-plant transfer factors 

(or concentration ratios), but others may also be used. 

3.3.5.1 Development of Soil-to-Plant Transfer Factors 

Research on the relationship between radionuclides in soil and in the plants grown in that 

soil began soon after the establishment of the major radionuclide production centers of 

the Manhattan Engineer District. In the early period (through the early 1950s), the 

potential for root uptake was recognized (Cline and Porter 1951) but not appreciated; the 

main concern was foliar deposition (Parker 1955). However, some studies were 

originally undertaken at the Hanford Site to investigate this pathway (e.g., Seiders, Cline, 

and Rediske 1955). Hanford’s Botany Field Station was established in 1949 and used 

Columbia River water from downstream of the reactor outfalls for an irrigation source. 

Minor increases in gross radioactivity were noted in crops in 1949 and 1950 (Cline and 

Porter 1951), but individual radionuclides were not identified. However, by 1953, work 

had been done at Hanford to determine the concentration factor of several key 

radionuclides from soils contaminated elsewhere by fallout (Rediske and Selders 1953a; 

1953b; Selders, Rediske, and Palmer 1953). 

Weapons testing was conducted in the United States and elsewhere and a number of 

countries became concerned about world-wide fallout, particularly of 90Sr. Results of 
3-24

surveys of contaminated biota on contaminated islands in the Pacific Proving Grounds 

were first published in 1956 (Atomic Energy Commission 1956). Meanwhile, agricultural 

scientists in the U.S. and Great Britain began investigations and field studies on the 

factors governing uptake of 90Sr and its transport into food chains that led directly to 

humans. Concern about uptake through plant roots, as opposed to foliar deposition from 

fallout, first arose at Oak Ridge in the mid-1950s following the draining of White Oak 

Lake (Auerbach and Reichle 1999; Stannard 1988). Recognition of root uptake of 

selected contaminants (primarily related to situations concerning waste disposal in nearsurface soils) was wide-spread by the early 1960s; interestingly, however, papers 

presented at the first major conference on radioecology (Shultz and Klement 1963) 

contain data on radionuclide concentrations in plants – but no soil-to-plant concentration 

factors per se. Senate hearings in 1963 focused on radioactive fallout from the weapons 

tests and food chain contamination (Stannard 1988). The initial attempts to model uptake 

of radionuclides by plants were driven by unanticipated contamination events following 

atmospheric nuclear weapons testing. 

Menzel (1965) presented results of a literature study of various soil science experiments 

of soil to plant transfer at the 1965 Hanford Biology Symposium. This is one of the first 

uses of the term “concentration factor” with regard to plant/soil ratio. Menzel used this 

ratio to summarize a large amount of data for several elements (in terms of ppm of dry 

plant per ppm of dry soil). He was more interested in exploring the effects of radiation 

on the plants and the mixing of radionuclides in soil by plants than on the actual uptake. 

(At this same Symposium, Mistry et al. (1965) gave detailed measurements of various 

herbs, shrubs, trees, fruits, and tubers grown in areas of high natural background – but did

not provide either concentration ratios or soil measurements from which concentration 

ratios could be computed.) 

The concept of using nuclear explosives for excavation, particularly of a sea-level canal 

across the Isthmus of Panama, with the potential for associated fallout, led to several 

attempts to predict the potential environmental affect. Martin et al. (1970, as reprinted in 

Klement (1982)) proposed a series of physics-based, differential equations to describe the 

transport of radioactive contaminants resulting from canal-building fallout. This effort 

included estimation of transfer of radionuclides from soil water into plants that was 

related to the growth rate of the plant and the stable element content of the plant. No 

examples are given for this mechanistic approach; it does not appear to have been too 

successful. 

The document series Prediction of the maximum dosage to man from the fallout of 

nuclear devices (Tamplin 1967; Ng and Thompson1966; Burton and Pratt 1968; Ng et al. 

1968) also came about because of concerns about predicting doses from canal-building 

fallout. This series was intended to provide input to design of nuclear explosives to 

minimize the impacts of fallout; one segment of the calculation was to develop a “unitrad” value that related normalized fallout amounts by radionuclide to committed internal 

doses. While the “unit-rad” calculation did not directly involve estimation of 

radionuclide transfer from soil to plants, a series of appendices to Ng et al. (1968) did 

describe how global average concentrations of stable elements in soils and plants could 
3-25

be ratioed to give an estimate of uptake of radionuclides in plants from contaminated 

soils. In this description, Ng used the symbol (CP/CS) for what he called the plant-to-soil 

concentration ratio. The data in this report became the basis for many later models and 

calculations, such as NRC Regulatory Guide 1.109 (1977). 

The concept pioneered by Ng has been given many names over the years. 

• Plant-to-soil concentration ratio – a generic term in ecology, used by Whicker 

and Schultz (1982), Peterson (1983), Faw and Shultis (1999), and others; 

• Soil-to-plant transfer factor – used to describe the direction of radionuclide 

migration “from soil into plants”, adopted by Martin Frissell and the International 

Union of Radioecologists (1989), IAEA (1994), and others; 

• Vegetable/soil transfer factor – used in documents related to the RESRAD family 

of computer codes (e.g., Yang, Biwer, and Yu 1993; Yu et al. 2001); 

• Soil-to-plant concentration ratio – a variant used by NCRP (1984); 

• Soil-to-plant concentration factor – a variant used by IAEA (1982), Ng, Colsher, 

and Thompson (1982); 

• Concentration factor – a variant used by Soldat in Fletcher and Dotson (1971); 

Miller et al. (1980); 

• Transfer ratio – Stannard (1988); 

• Concentration ratio – a commonly-used variant (e.g., Cataldo, Wildung, and 

Garland 1983; Napier 2003; numerous others); 

• Plant uptake factor – Eisenbud (1987); 

• Relative ratio – Dahlman and Van Voris (1976); 

• Uptake ratio – Grummitt (1976); 

• Plant bioconcentration factor – a definition more usually used for aquatic uptake 

processes, but sometimes used with terrestrial vegetation (e.g., Wolterbeek, van 

der Meer, and Dielemans 2000); 

• Plant bioaccumulation factor - a definition more usually used for aquatic uptake 

processes, but sometimes used with terrestrial vegetation (e.g., Wolterbeek, van 

der Meer, and Dielemans 2000) 

• Discrimination factor – the name sometimes given to the ratio of the steady state 

output to input of a compartment model, when applied to the ratio of 

concentration in soil to concentration in plant, also accumulation factor (Peterson 

1983; Faw and Shultis 1999). 

All of these concepts are the same; the notation generally used is Bv for the ratio of the 

concentration of an element in a plant of interest to the concentration in the source soil. 

The transfer factor applies to long-term, chronic exposures and is ideally measured at 

equilibrium. Transfer factors are used in risk assessments to estimate the amount of 

radioactivity that could be present in a food crop based on the calculated concentration in 

the source soil. By calculating the concentration in the food, the total intake can be 

estimated and a dose calculated as a result of the annual intake. In terms of 

radionuclides, the transfer factor is used to calculate how many becquerels per kilogram 

of soil are transferred to the edible dry plant product (Bq per kg). Although the concept 

is occasionally questioned for some of its underlying assumptions (e.g., Centofani et al. 

2005), it is the most commonly used approach in radiological environmental assessments. 
3-26

The concentration ratio depends on the radionuclide, the soil type (which may include 

soil chemistry and concentrations of nutrients and analogues), and the plant type. The 

transfer factors are empirically derived; they are based on measurements made for 

various chemical forms of the radionuclide on selected types of plant in selected soil 

types. Experimental data are not available for all elements for all food types. Frequently, 

a few measurements on a very limited number of plant types are used to infer a transfer 

factor for all crops. Often, when no referenceable documents are available, data are 

derived based on chemical groupings in the periodic table of the elements, such that 

chemically similar elements are assigned similar values.

In researching concentration ratios, it is necessary to fully understand the nature of the 

experiment or natural system in which it was measured. The type of plant, the type of 

soil, the quantity of naturally occurring chemical analogues in the soil, and the stage of 

growth all influence the amount of contaminant absorbed into the plant through the roots. 

A large fraction of the observed variability may be due to the fact that analytical methods 

do not account for bioavailability of materials in soil – how much of the concentration 

measured in the soil is actually available to the plant and not bound to the soil matrix. In 

addition, it is important to know whether the concentration measurements are made in 

terms of wet or dry plant. Vegetation is a large percentage water, and the degree of 

turgor in the harvested plant has a strong influence in the measured concentration. The 

intent in most codes is to use a concentration ratio between dry soil and dry plant matter 

and to adjust to the full mass of the plant with a dry-to-wet mass ratio. When taking 

transfer factors from the literature, it is important to note whether the values are reported 

in wet or dry weight. Some researchers differentiate between the concentration ratio for 

plants consumed as feed by animals (designated as Bv1 and given in units using dry 

weight of vegetation and soil) and for plants consumed fresh by humans (designated Bv2

and given in units of fresh [or wet] weight of vegetation and dry weight of soil) (Miller et 

al. 1980). A conversion of these two concepts is given in Peterson (1983) as 

⎟

⎠

⎞ ⎜

⎝

⎛ = FW

DW Bv2 Bv1 (17) 

where DW is the dry weight and FW is the fresh weight. 

Since the handbook prepared by Ng et al. (1968), numerous studies have been undertaken 

to quantify transfer factors (or concentration ratios) for specific chemical elements as a 

function of food type. These studies have been compiled in several publications. Most 

computer codes reference one or more of these compilations as the source of their 

transfer factors. Several frequently referenced compilations include the International 

Atomic Energy Agency’s Technical Report Series #364, Handbook of Parameter Values 

for the Prediction of Radionuclide Transfer in Temperate Environments (IAEA 1994). 

This document encompasses a wide variety of plant types and is the result of extensive 

background investigations. It is based on data compiled by the International Union of 

Radioecologists. Work is currently underway coordinated by the IAEA to update this 

document. A second frequently cited reference is the NUREG/CR-5512, Residual 

Radioactive Contamination From Decommissioning: Technical Basis for Translating 
3-27

Contamination Levels to Annual Total Effective Dose Equivalent (Kennedy and Strenge 

1992) because of its large set of data and traceable references. Other references include 

the National Council on Ionizing Radiation and Protection (NCRP) Report #123 (1996), 

Screening Models for Releases of Radionuclides to Atmosphere, Surface Water, and 

Ground, and the series of documents by Coughtrey and Thorne (1983), Radionuclide 

Distribution and Transport in Terrestrial and Aquatic Ecosystems, Vols. 1-6. 

The National Council on Radiation Protection and Measurements developed a set of soilto-plant transfer factors for screening applications (NCRP 1999), basing it largely on the 

International Atomic Energy Agency/International Union of Radioecologists 

(IAEA/IUR) publication (IUR 1989). However, the NCRP specifically assigned 

uncertainty ranges to the parameters in the form of geometric standard deviations for 

assumed lognormal distributions. The assigned geometrical standard deviations (GSDs) 

ranged from 2.5 to 3.0. However, the transfer factor values adopted by NCRP are 

described as being “close to the top of the measured range for most nuclides,” with higher 

values used for sparsely vegetated soils. Because the screening intent was to be 

conservative, the actual uncertainty range could be larger (with a higher possibility of 

lower values.) Biwer et al. (2000) adopted the NCRP ranges for use in the RESRAD 

family of codes. Beyeler et al. (1999) independently evaluated the CR values for the 

NUREG/CR-5512 model. They report GSDs ranging from a minimum of 2.47, based on 

1250 measurements of 23 nuclides as reported by Sheppard and Evenden (1990), to as 

high as 9.5. Most nuclides were assigned the 2.47 default; interestingly, those 

radionuclides with some conflicting data often had higher GSDs than those with no data. 

Here, the GSD was used to represent experimental variability, not necessarily uncertainty 

in an annual average value that is representative of time and space averaging over some 

defined area. Somewhat different results were obtained using an expert elicitation process 

(Brown et al. 1997). It is apparent that there is a large potential variability in the CR

values as a result of “numerous and complex underlying processes such as climate, 

growing conditions, plant metabolism, plant rooting traits, soil type, soil moisture, soil 

texture, and soil pH (Beyeler et al. 1999).” 

Some models make additional assumptions involving root uptake and the surface soil 

layer when a clean non-contaminated layer of soil is applied over contaminated upper soil 

layer. The GENII family of codes (Napier et al. 1988; Napier 2003) and RESRAD 

family of codes (Yu et al. 2001) also allow the root uptake transfer factor to be modified 

if not all of the plants’ roots are in the contaminated soil layer. The GENII and RESRAD 

codes assume that uptake is directly proportional to the fraction of roots growing in the 

contaminated zone. In GENII, this is accomplished using an input root-penetration 

factor, usually set to 1.0 for surface contamination and a lower value for contamination 

covered with a clean surface layer. A similar approach is taken in RESRAD, which 

derives cover and depth modifying factors as a function of the thickness of the clean 

overburden above a contaminated layer. Biwer et al. (2000) investigated rooting depths 

for various types of plants, and suggested that for stochastic simulations this be varied 

uniformly from 0.3 to 4.0 meters. However, Biwer et al. did not consider the actual 

appropriateness of the assumption of linearity of uptake with root fraction.
3-28

Root uptake is important for biologically active or mobile contaminants; other 

contaminants are discriminated against by biological systems, and their root uptake is 

minimal. For these types of radionuclides, other mechanisms may be the dominant ones 

for vegetation contamination. As discussed above, such mechanisms include simple 

physical contamination of the external surface of the plant, such as resuspension and 

deposition of dust or splashup of contaminated particles of soil during rain or irrigation 

episodes. In the recent IAEA recommendations (IAEA 2001), an aggregated transfer 

factor was developed that implicitly includes the soil adhesion term. To account 

implicitly for soil adhesion, a minimum value of 0.1 is assigned to the transfer factor for 

animal feeds and 0.001 to the concentration ratio for humans. The IAEA’s (2001) 

concentration ratio for human foods is given in terms of wet weight. To differentiate 

these from the Bv1 and Bv2 terms defined above, the IAEA gives these the symbols Fv1

and Fv2. 

It is important to remember that, for all of the different definitions and applications listed 

here, the modeling of transfer of radionuclides from soils to plants is based entirely on 

empirical observation. For combinations of plant type and soil type that have not been 

directly observed, any factor used is at best an approximation. 

The model of Baes (1982) and Sheppard (1985) attempted to correlate soil-to-plant 

concentration ratios with the distribution coefficient Kd. The approach, introduced by 

Baes (1982) and further developed by Sheppard (1985), presents the relationship between 

Kd and concentration ratio (CR) in the form 

ln Kd = a + b (ln CR) (18) 

where a and b are constants, b having a negative value. Sheppard found that this model 

was generally able to estimate the CR to within about an order of magnitude (perhaps 

because the Kd is an implicit measure of bioavailability). Its use does require a 

measurement of the soil Kd, which is simpler to obtain than a site-specific estimate of the 

CR values; however, it is not specific to various types of crops. A related model 

specifically for cesium, introducing even more unknown parameters related to potassium 

concentrations, was attempted by Absalom et al. (1999). This type of approach has 

limited utility and has not caught on in the assessment community. However, it does 

indicate that in when quantifying uncertainty using Monte Carlo sampling procedures, the 

soil to plant uptake should be correlated with the soil Kd. 

3.3.5.2 The Observed Ratio 

A different approach to estimating uptake of radionuclides into plants (and animals, see 

below) is based on the observation that the presence of chemically similar stable elements 

in soils can have a significant impact on radionuclide uptake in plants. In soils having 

low concentrations of analogous stable elements, radionuclide uptake by plants may be 

enhanced, sometimes by orders of magnitude above the levels ordinarily found. 

Similarly, in soils with high concentrations of analogous elements, uptake may be 

significantly depressed. This effect has been characterized by the use of elemental ratios 

to predict the transport of radionuclides in the food chain. The ratio of the radionuclide-
3-29

to-stable-element concentration in one medium to the radionuclide-to-stable-element in 

another medium (for instance, soils and plants) has been named the observed ratio (OR) 

(Comar et al. 1957). The OR is defined as 

OR = ([Rs] / [Rp]) ([Ap] / [As]) (19) 

where 

[Rs] = radionuclide concentration in sample; 

[Rp] = radionuclide concentration in precursor; 

[As] = analogue concentration in sample; and 

[Ap] = analogue concentration in precursor. 

This equation may be rearranged to yield an equation for radionuclide concentration in 

the sample based on the observed ratio and the analogue concentrations. 

This approach was developed in the 1950s prior to the concentration ratio approach and 

was applied successfully to strontium and its analogue calcium, and somewhat less 

successfully to cesium and its analogue potassium. However, it may be made more 

successful if, instead of using concentrations of radionuclides in soil, the concentration in 

soil solutions is used instead (see discussion below on non-linear responses). 

3.3.5.3 Uncommon Food Products 

Farm products commonly included in radiological assessment models include leafy 

vegetables and produce (NRC Regulatory Guide 1.109 ([NRC 1977]; RESRAD family of 

codes [Yu et al. 2002]), or perhaps leafy vegetables, other vegetables, cereal grains and 

fruit (used in the GENII family of codes [Napier et al. 1988; Napier et al. 2003] and its 

derivatives such as the ERMYN code developed for Yucca Mountain [Wu 2003]). Early 

computer codes developed from the HERMES model (Fletcher and Dotson 1971) such as 

FOOD (Baker, Hoenes, and Soldat 1976) used a longer list including 

• Leafy above-ground vegetables; 

• Other above-ground vegetables; 

• Potatoes; 

• Other below-ground vegetables; 

• Berries; 

• Orchard fruit; 

• Wheat and wheat products; and 

• Other grains. 

The longer list was reduced because it was observed that soil-to-plant concentration ratios 

were not available for most of the crop types, and generic values were being used for all 

foods (e.g., Napier et al. 1988). 

The limited number of food crops is beneficial to the analyst, because it minimizes the 

number of parameters that must be determined. However, this approach may be seen as 

ethnocentric and biased by members of some groups in the public. In the Columbia River 

Comprehensive Impact Assessment (CRCIA) (DOE 1997), which attempted to 

incorporate public inputs in its development, the lack of specific mention of other food 

types – and in particular, Native American natural foods - and the lack of a wide range 

of “other” foods was seen as a severe limitation. It was not considered to be useful to 
3-30

investigate specific ingestion rates of roots, fruits, etc., unless uptake parameters to 

specific plant parts (roots versus leaves) or specific plant species were available. 

Medicinal and other uses of plant material also provided reasons to increase ingestion 

rates of specific plant types. The generic approaches to radionuclide uptake in plants are 

useful for uncommon foods, but it must be recognized that plant-specific uptake ratios are 

probably not going to be available, and uncertainty ranges must be expanded to obtain 

public acceptance. 

Following the accidental release of radionuclides at the Chernobyl Power Plant in 1986, 

the contamination of natural forest products became an issue. Non-cultivated foods such 

as berries (noted above) and mushrooms were found to be important. Forests are very 

efficient at trapping atmospheric aerosols. The aerosol radionuclides fall on the aerial 

parts of trees (leaves, branches and trunks), understory, and on the soil (litter, mosses and 

soil horizons). Tree canopies can represent large foliar surfaces, up to ten times greater 

than in agricultural areas. The long residence time of radionuclides in forests implies an 

increase in potential internal and external doses for decades. The progressive 

decomposition of leaves fallen onto the soil constitutes the so-called litter that represents 

a trap that fixes the radionuclides and slows their migration deep into soil. The large 

numbers of mycorhizae and the intense microbial activity in forest soils are the main 

causes of cycling of radionuclides and stability of transfer factors for several years after 

deposition. The forest products consumed by humans (mushrooms, berries, so-called 

“tree juices” such as maple syrup, birch juice) can be up to 250 times more contaminated 

than the equivalent agricultural products2

. The Chernobyl experience has resulted in the 

availability of soil-to-plant aggregated transfer coefficients for a few major forest 

products such as berries and mushrooms, for a limited number of radionuclides (primarily 

nuclides of cesium and strontium). The aggregated transfer coefficient relates the activity 

concentration in the forest product (Bq/kg) to the activity of the surface deposit per unit 

area (Bq/m2). The unit is then m2 kg-1. Values for aggregated transfer factors can be 

notably higher than the equivalent ones for agricultural products. It has to be stressed that 

it is difficult to get a precise value, because variability is large in such uncontrolled 

ecosystems. Uncertainties of one order of magnitude higher or lower on the estimations 

are normal. 

The aggregated transfer coefficient for mushrooms is widely variable (up to 3 orders of 

magnitude). This variability is due to several reasons: 

• Species plays a role of prime importance. The high transfers of cesium in some 

mushrooms species could be related to the existence in the carpophore of 

substances with a great affinity for cesium. Transfer factors have been related to 

the species as shown in Table 3. 

• The type of mushroom is an indicator of the cesium transfer. Saprophytic 

mushrooms develop on decomposing materials on the surface of the soil, which 

means that these kinds of mushrooms will be the first contaminated following 

deposition. Transfer factors will diminish as the deposit migrates into the soil. The 

symbiotic mushrooms associate with trees. Due to their extended mycelium, these 

 

2

 P. Calmon, personal communication of data collected for the IAEA EMRAS Program. 
3-31

mushrooms bring minerals to the tree and trees provide the mushrooms with 

organic substrates from photosynthesis. Most of the edible mushrooms are 

symbiotic ones. Unfortunately, this characteristic does not give any information 

about the ability to accumulate cesium by mushrooms. The parasitic mushrooms 

develop at the expense of the trees and are most of the time characterized by low 

transfer factors. 

• Mycelium depth plays a crucial role in the contamination chronology. Mushrooms 

with surface mycelia will be contaminated quickly after deposition; deep 

mycelium mushrooms will be contaminated later. 

For radionuclides other than cesium, such high transfer coefficients are not observed, nor 

is there as large a variability in the transfer factors – it is generally comparable to that for 

vegetative plants. 

For berries, there is not as large a variability in the transfer factor for cesium as in the 

case for mushrooms. However, transfers to berries are higher than those for agricultural 

plants. 

Soil to plant concentration ratios are being measured for a few radionuclides (primarily 

strontium and cesium) for common Asian food types such as rice, Chinese cabbage, 

radish, and soybean (Choi et al. 1991; 1992; 1995; 1998). Cultivating systems are an 

important factor for plant uptake of radionuclides from soil. One of the critical foods for 

the intake of radionuclides by humans, especially in the monsoon Asian regions, is rice. 

Rice is usually planted under flooded conditions because they provide the best 

environment for the rice plants. No crop rotation is necessary, so that rice has been 

planted in the same places for hundreds of years. Also, the crop can be grown 

continuously twice a year in the same paddy fields in tropical or subtropical areas and in 

some parts of the temperate zones. Because rice is essentially emergent (from the water) 

vegetation, the main uptake route may not be through the roots. In a tropical area, 

cropping five times in two years or triple cropping in one year is possible if irrigation 

water is available. 
3-32

Table 3. Aggregate transfer coefficient for cesium for 4 mushroom classes (Calmon, 

personal communication of data collected for the IAEA EMRASW Program) 

Description Value (m2.kg-1) 

fresh weight 

Mushroom species in the class 

Mushrooms with 

low transfer 

coefficient for 

cesium 

1.10-2

Agaricus arvensis, Agaricus sylvaticus, Armillaria 

mellea, Boletus appendiculatus, Boletus elegans, 

Cantharellus cornucopiensis, Leccinum aurantiacum, 

(Macro) Lepiota procera, Lepista nuda, Lepista saeva, 

Lycoperdon perlatum, Psalliota campestris, Sarcodon 

imbr.

Mushrooms with 

medium transfer 

coefficient for 

cesium 5.10-2

Boletus aestivalis, Boletus edulis, Cantharellus 

cibarius, Cantharellus palens, Clitocybe nebularis, 

Collybia buthyracia, Collybia confluens, Collybia 

dryophylla, Collybia maculata, Collybia peronata 

Hydnum repandum, Kuehneromyces mutabilis, 

Lactarius deterrimus, Lactarius helvus, Lactarius 

odoratus, Lactarius picinus, Leccinum sp., Leccinum 

versipelle, Lepiota naucina, Oudemansiella sp., 

Oudemansiella radicata, Pholiota aegerita, Russula 

decolorans 

Mushrooms with 

high transfer 

coefficient for 

cesium 

1.10-1

Boletus cavipes, Cantharellus lutescens, Cantharellus 

tubaeformis, Clitocybe infundibuliformis 

Lactarius lignyotus, Lactarius quietus, Lactarius 

torminosus, Lactarius turpis, Leccinum scabrum, 

Russula nigricans, Suillus grevillei, Tricholoma aurata, 

Trichomolopsis rutilans

Mushrooms with 

very high transfer 

coefficient for 

cesium 5.10-1

Clitocybe cavipes, Dermocybe sp., Hebeloma sp., 

Hygrophorus sp., Hygrophorus olivaceoalbus, 

Laccaria amethystina, Laccaria laccata, Laccaria 

proxima, Lactarius sp., Lactarius camphorates, 

Lactarius necator, Lactarius porninsis, Lactarius rufus, 

Lactarius theiogalus, Lactarius trivialis, Rozites 

caperata, Russula sp., Russula badia, Russula 

erythropoda, Russula ochroleuca, Russula turci, Suillus 

bovinus, Suillus granulatus, Suillus luteus, Suillus 

variegatus, Xerocomus badius, Xerocomus 

chrysenteron, Xerocomus subtomentosus

(Data from Amundsen, Gulden, and Strand 1996; Baeza et al. 2000; Bakken and Olsen1990; 

Barnett et al. 1999; Battiston et al. 1989. Borio et al. 1991; Byrne 1988; Djingova and Kuleff 

2002; Fraiture, Guillitte, and Lambinon 1990; Gaso et al. 1998; Gaso et al. 2000; Giovani, Nimis, 

and Padovani 1990; Grueter 1971: Guillitte, Fraiture, and Lambinon 1990; Heinrich 1992; 

Heinrich 1993; Horyna and Randa 1988; Kammerer, Hiersche, and Wirth 1994; Kirchner and 

Daillant 1998; Lambinon et al. 1988; Mascanzoni 1990; Mietelski et al. 2002; Pietrzak-Flis et al. 

1996; Randa et al. 1990; Rantavaara 1990; Roemmelt, Hiersche, and Schaller 1988; Römmelt et 

al. 1990; Rühm et al. 1998; Seeger and Schweinshaut 1981; Steiner, Linkov, and Yoshida 2002; 

Svadlenkova, Konecny, and Smutny 1996; Tsukada, Shibata, and Sugiyama 1998; Vinichuk, 

Johanson, and Taylor 2003) 
3-33

3.3.5.4 Potential Non-Linear Uptakes 

A key assumption of the concentration-ratio approach is that the CR is a constant as a 

function of concentration; that is, the uptake is linear. This may not be true for 

contaminants that are nutrients or are chemical analogues for them. Non-linear responses 

may be possible if plants scavenge essential elements at low concentrations but maintain 

a homeostatic balance at higher soil concentrations (Sheppard and Sheppard 1985). The 

assumption of linearity may be appropriate for elements that are not essential to 

biological function, are not analogues of such elements, or are not absorbed by organisms 

via nutrient pathways. These latter elements seldom exhibit linearity at very low 

environmental concentrations (Figure 3). For such elements (Table 4), organisms often 

are able to homeostatically regulate their tissue concentrations over a range of 

environmental concentrations. In some cases, these concentrations may be 40 to 200 

times greater than the amount needed to sustain life (Förstner and Wittmann 1981). 

There is generally little information to evaluate this concept except for a few 

radionuclides such as cesium, which mimics potassium, or strontium, which mimics 

calcium. 

The differences in predicted effects between these two models can be substantial. 

Experience in assessing risks of metals in sediments and groundwater indicates that, for 

certain metals and species, the linear model can overestimate exposure by up to six orders 

of magnitude (DOE 1997). 

Figure 3. Relationships are shown between tissue concentrations and environmental 

concentrations for non-nutrient and nutrient compounds (adapted from 

personal communication with C. A. Brandt). 
3-34

Table 4. In a biological classification of metals (modified from Beeby 1991) shaded cells 

are non-nutrient analogs; bold cells are nonessential metals. 

Period Macronutrient Micronutrient Non-essential 

3 Na Mg 

4 K Ca Cr Mn Fe, 

Co, Ni 

Cu Zn 

5 Sr Cd 

6 Cs Hg Pb

7 Eu, U Np 

(a) Period is from the Periodic Table of the Elements.

To date, few models have been developed to deal with this problem. A possible 

alternative for radionuclides with this behavior would be to treat them with a specificactivity type model, wherein the atom ratio of the radioactive to stable atoms of an 

element are assumed to be the same in the plant as in the soil (see below). The model 

proposed by Norden et al. (2005) is essentially a specific-activity type model; they 

suggest that transfer rates of contaminants would mimic analogue nutrient transfer rates. 

Their suggestion is that for the case of radionuclides that are analogues of macronutrients, 

it can be assumed that the plant uptake of the nutrient modulates the uptake of the 

radionuclide. This means, that the radionuclide and the corresponding analogue nutrient 

are taken up by plants in an identical manner. Furthermore, assuming that only ions in the 

soil solution near the roots are available for transition into the roots, the transition of the 

radionuclide from soil to plant roots can be represented as an independent Poisson 

process with the following rate: 

( ) [ ] [ ]

[ ] ( ) TR A

RN A

RN TR RN

ss ss

ss

+ = (20) 

where, 

TR(RN) is the transition rate of the radionuclide from the soil solution into the roots 

[mol/yr], 

TR(A) is the overall transition rate of the analogue from the soil solution into the 

roots [mol/yr] 

[RN]ss is the radionuclide concentration in the soil solution near the roots [mol/m3

] 

[A]ss is the analogue nutrient concentration in the soil solution near the roots 

[mol/m3

]]. 

Because [RN]ss is generally very small with respect to [A]ss, the overall transition rate 

from the soil solution into the roots equals the analogue uptake rate. These authors also 

suggest that a selectivity coefficient may be added to this equation if the radionuclide has 

a slightly lower uptake than the analogue. This model is very similar in concept and 

application to the Observed Ratio, except that it is based on soil solutions rather than soil 

concentrations. 
3-35

3.3.5.5 Specific-Activity Models 

Some key biologically-active elements are modeled in a separate way through the use of 

specific activity models. The behavior of the radionuclides tritium and 14C in exposure 

pathways must be handled in a special manner, because the behavior of these 

environmentally mobile radionuclides mimics that of stable hydrogen and carbon in 

biological processes, respectively. The concentrations of tritium or 14C in environmental 

media (soil, plants, and animal products) are assumed to have the same specific activity 

(curies of radionuclide per kilogram of soluble element) as the contaminating medium (air 

or water). The fractional content of hydrogen or carbon in a plant is then used to compute 

the concentration of tritium or 14C in the food product under consideration. The hydrogen 

content in both the water and the nonwater (dry) portion of the food product is used when 

calculating the tritium concentration. For airborne releases, it is assumed that plants obtain 

all their carbon from airborne carbon dioxide. 

In the simplest implementation, tritium in the environment is assumed to be in the oxide 

(HTO) form, and to behave in a manner identical with water. For HTO releases, 

concentrations in air moisture (Bq L-1) are found by dividing the concentration in air (Bq 

m-3) by the absolute humidity (kg or L m-3). The concentration of tritium in vegetation is 

calculated (Baker, Hoenes, and Soldat 1976) as 

 CTp = 9 CwT FHp (21) 

where CTp = the concentration of 3

H in plant type p (Bq/kg); 

 CwT = the concentration of tritium in the environmental water (Bq/L); and 

 FHp = the fraction of hydrogen in total vegetation of plant type p. 

The coefficient, 9, converts tritium concentration in environmental water to concentration 

in hydrogen (this is approximate, but applicable to water with dilute solutions of HTO). 

Note that 1 kg of water equals 1 L in the above equation. The fractions of hydrogen in 

various food types are given in Table 5. (Some additional parameters are included in Table 

4 for the discussion of animal products given below). 

Murphy (1986) and Raskob (1994) have developed models designed specifically to 

calculate doses from chronic releases of elemental tritium (HT) and HTO, taking into 

account the formation of organically-bound tritium (OBT). Both models are similar in 

that they model dispersion of HT and HTO, deposition of HT and HTO through dry 

deposition, and deposition of HTO through wet deposition. Treatment of the soil 

compartment includes such processes as diffusion and resuspension. In NORMTRI 

(Raskob 1994), air concentrations due to resuspension are calculated by treating the area 

of deposition as an array of ground-level area sources. For an HT release, 20% of the 

deposited tritium is assumed to remain in the soil; the rest is re-emitted. In the Murphy 

model, HT is oxidized in the leaf as well as in the soil. Both models account explicitly 

for the transfer of OBT in plants to OBT in animal products. However, both of these 

models require extensive information and operate on a limited time scale. For 

assessments of a more general nature, the model of Peterson and Davis (2002) that 

includes both HTO and HT is useful. 
3-36

Table 5. Weight Fractions of Hydrogen and Carbon in Environmental Media, Vegetation, 

and Animal Products (Napier et al. 2003) 

 Food or Carbon Hydrogen Carbona

 Hydrogenb

 Fodder Water dry dry wet wet 

 fw fc fh Fcv , Fca Fhv , Fha

Fresh fruits, 0.80 0.45 0.062 0.090 0.10 

vegetables, 

and grass 

Grain and 0.12 0.45 0.062 0.40 0.068 

stored animal 

feed 

Eggs 0.75 0.60 0.092 0.15 0.11 

Milk 0.88 0.58 0.083 0.070 0.11 

Beef 0.60 0.60 0.094 0.24 0.10 

Poultry 0.70 0.67 0.087 0.20 0.10 

a

 Fcv or Fca = fc (l - fw ). Fcv applies to plants and Fca applies to animal products. 

b

 Fhv or Fha = (fw /9) + fh (l - fw). Fhv applies to plants and Fha applies to animal products. 

To estimate HTO concentrations in plant products, Peterson and Davis (2002) assumed 

conservatively that the concentration of HTO in plant water equals 0.9 times the HTO 

concentration in air moisture (Cam) for leafy vegetables and pasture and 0.8 Cam for fruit, 

root crops and other vegetables, and grain. These reduction factors account for dilution 

from soil water, which has a lower tritium concentration than does air moisture and 

which affects fruit and root crops more than leaves. OBT concentrations are estimated 

from a plant water concentration of 0.9 Cam for all plant types, since OBT is assumed to 

form exclusively in the leaves and to be translocated to other plant parts. Then, isotopic 

discrimination occurring in the formation of OBT (Table 6) is assumed conservatively to 

result in an OBT concentration 0.9 times the concentration of HTO in plant water. 

The Peterson and Davis (2002) equation for calculating concentrations of HTO in plant 

products (Bq kg-1 fw) is: 

Cpp_HTO = RFpp Cam Ffw_pp (22) 

where 

Cpp_HTO = concentration of HTO in plant products (Bq kg-1 fresh weight) 

Ffw_pp = average fresh weight (fw) fraction of plant products (kg kg-1) (Note, this 

is essentially the same as fw in the preceding equation) 

RFpp = reduction factor that accounts for low soil water concentrations relative 

to concentrations in air moisture and varies by vegetable type 

Cam = HTO concentration in air moisture (Bq L-1) 
3-37

Table 6. Parameter values for calculating HTO and OBT concentrations in plant products 

(adapted from Peterson and Davis 2002).

 Leafy 

vegetables 

Fruit Root and 

other 

vegetables 

Grain Pasture 

Reduction factor (RFpp) 0.9 0.8 0.8 0.8 0.9 

Reduction factor for leaves (RF1) 0.9 0.9 0.9 0.9 0.9 

Isotopic discrimination factor (IDpp) 0.9 0.9 0.9 0.9 0.9 

Fresh matter fraction (Ffw_pp) 0.906 0.853 0.824 0.117 0.8 

Dry matter fraction (Fdm_pp) 0.094 0.147 0.176 0.883 0.2 

Water equivalent factor (Weq_pp) 0.6 0.59 0.58 0.577 0.616 

The Peterson and Davis (2002) equation for calculating concentrations of OBT in plant 

products (Bq kg-1 fw) is: 

Cpp_OBT = RFl IDpp Cam Fdm_pp Weq_pp (23) 

where 

RFl = reduction factor for plant leaves 

IDpp = isotopic discrimination factor for plant products 

Cpp_OBT = concentration of OBT in plant products (Bq kg-1 fresh weight) 

Fdm_pp = average dry matter fraction of the plant products (kg dry mass kg-1 fresh 

mass) 

Weq_pp = water equivalent factor of plant products (L kg-1) 

HT is a biologically inert gas and imparts an extremely low dose relative to tritiated 

water. However, HT is converted in the environment to HTO, in which form it moves 

through the food chain to dose. Therefore, a model of dose from HT releases is 

necessary. Ratios of the HTO concentrations in soil, air and plants to the HT 

concentration in air recommended for screening level assessments by Peterson and Davis 

(2002) are 8 Bq L-1 / (Bq m-3) for the ratio of HTO in air moisture to HT in air, and 12 Bq 

L-1 / (Bq m-3) for the ratio of HTO in plant water to HT in air. Doses from HT are then 

modeled using the recommended HTO / HT ratios for air moisture and plant water. 

Concentrations in air moisture are calculated by multiplying the HT concentration in air 

(CaHT; Bq m-3) times eight. Concentrations of HTO and OBT in plant and animal 

products are calculated for releases of HT by replacing RFpp in the above equations with 

a factor of 1.5. Thus the plant water concentration in these equations becomes 1.5 Cam = 

12 CaHT. 

Using the specific activity model for 14C in air, the concentration of 14C in crops from 

atmospheric contamination CCp is calculated (Baker, Hoenes, and Soldat 1976) as 

 CCp = Ca,C FCp/PC (24)
3-38

where Ca,C = the concentration of 14C in air (Bq/m3); 

 FCp = the fraction of carbon in the plant (dimensionless); and 

 PC = the concentration of carbon in air (kg/m3

). 

Plants obtain most of their carbon via photosynthesis of CO2 from the air. Therefore, it is 

difficult to estimate the transfer of radioactive 14C from irrigation water or soil to plants. 

The approach adopted by Napier et al. (1988) is to assume that plants obtain a small 

fraction of carbon from soil, and to use that activity ratio. The approach used by Yu et al. 

(2001) is to assume that carbon in the soil slowly converts to CO2 and to then estimate a 

14CO2 concentration in the air near crops. Due to the volatility of 14C in soil, it is quickly 

released via gaseous emission as 14CO2. Sheppard et al. (1991) measured the rate of 14C 

loss from soil in outdoor lysimeter experiments. Carbon loss from the soil, measured by 

the emission rate (the “evasion rate” in RESRAD), is 12/yr for clay and loamy soils, and 

22/yr for sandy and organic soils (Yu et al. 2001). Thus, 14C concentrations in surface 

soil reach equilibrium within 1 to 2 months. Emission is the dominant mechanism for 

removing 14C from the soil. In comparison, losses due to leaching, radioactive decay, and 

soil erosion are slight. 

Specific activity models have been recommended for other radionuclides. Attributes that 

lead to this type of recommendation are long half-life, high mobility, biologically 

essential element, and massive isotopic dilution in the geosphere and biosphere. 129I and 

36Cl are some of the most critical radionuclides to consider in intermediate- and highlevel nuclear-waste management, and both have these attributes. Uptake in plants can be 

simulated using equations similar to those above for tritium or 14C, using the measured 

concentrations of the stable elements in local soil and plants. The specific-activity 

approach has also been suggested for 35S; however, its half-life is only about 3 months, 

and so is unlikely to be present in radioactive wastes. 

3.3.5.6 Uptake in Fruit Trees 

The standard uptake model described above using concentration ratios was originally 

developed for annual crops (leafy vegetables, root vegetables, forages, and grains). The 

vast majority of available observations, either laboratory or field studies, are for a limited 

number of crop types. In addition, observations are not available for all crop types for all 

chemical elements, and most compendiums of transfer factors use surrogates, relying on 

similar plant types, soil types, or chemical behavior to fill gaps in the knowledge (e.g., 

Staven et al. 2003; Yu et al. 2001). 

The standard model is also used for perennial plants, including fruit trees. The model 

may not be appropriate for trees, considering their longer life and potential for 

accumulating contaminants in roots, trunks, and leaves, with transport to fruits possibly 

delayed for periods of over 1 year. The British Ministry of Agriculture, Fisheries, and 

Food (MAFF, since 2001 called the Department for Environment, Food, and Rural 

Affairs) has noted that such “models for fruit are extremely conservative... Extensive 

research is underway to produce more appropriate data. However, a review for MAFF 

concludes that no better fruit models currently exist” (MAFF 1999). 
3-39

The International Union of Radioecologists and the International Atomic Energy Agency 

jointly prepared a major review of soil-to-plant transfer factors (IAEA 1994), which is 

used as a basic reference world-wide. In this review, soil-to-plant transfer factors are 

presented for many radionuclides and crop types. None of them refer to fruit or nut trees. 

A more recent compilation for tropical ecosystems does include some fruit trees 

(primarily apples), but the only nut is the coconut (IAEA-IUR 1997, quoted in Carini 

2001). This state of affairs has been discussed in the international arena for several years; 

the IAEA’s Validation of Model Predictions (VAMP) Program Multiple Pathways 

Assessment Working Group noted in the early 1990s that many participants 

overestimated concentrations of 137Cs in fruit trees, and that models for predicting the 

contamination of fruit were in need of further improvement (IAEA 1995). The sequel to 

VAMP, the IAEA’s Biosphere Modeling and Assessment (BIOMASS) Program, 

included a Fruits Working Group (IAEA 1996). As part of the work of the Fruits 

Working Group, a review was undertaken of the experimental, field and modeling 

information on the transfer of radionuclides to fruit. The results of this work were 

published as a special issue of the Journal of Environmental Radiation (Ventner 2001). 

In this special issue, Mitchell (2001) reports that there are three generic types of models 

that are applicable to fruit trees: 

• Simple mathematical functions describing declining concentration in fruit based 

on observations following deposition (e.g., Antonopoulos-Domis et al. 1990); 

• Models that attempt to predict temporal distribution in soil-plant systems through 

descriptions of the processes involved, e.g. a model postulated by Frissell at the 

1994 VAMP meeting in Vienna; 

• Radiological dose assessment models that use a mixture of equilibrium and/or 

dynamic modeling approaches to predict concentrations in edible products, e.g. 

SPADE (Thorne and Coughtrey 1983). 

Antonopoulos-Domis et al. (1990) developed a model structure for perennial fruit trees 

describing distribution, retention, transfer and rejection of radionuclides, based on 

experimental determinations of 137Cs in apricot fruit trees. The original concept for the 

model was based on the fact that the leaves and fruits developing each year are only 

contaminated by a portion of the 137Cs in the body of the tree. A fraction of this available 

reservoir is removed each year, part is lost from the tree through leaves and fruit and part 

becomes irretrievably associated with the body of the tree. This model requires 

knowledge of the contaminant inventory in the soil and the tree, as well as the deposition. 

The model is not immediately transferable to other types of trees, radionuclides, and 

locations, but it does indicate that at least two compartments are probably necessary to 

adequately describe the long-term accumulation and transfer of contaminants from trees 

into fruits. 

A model for radiocesium transfer to tree fruit described by Frissel (1994) considers the 

homeostatic control of potassium within fruit trees. The model structure has four 

compartments and was designed to consider the long-term fate of cesium in soil as 

affected by changes in the supply of potassium to soil. The four compartments are soil, 

the easily accessible part of a tree, the poorly accessible woody part, and the fruit or leaf. 
3-40

The model is homeostatic, i.e. all cesium concentrations and fluxes are controlled by 

potassium concentrations and fluxes, respectively. In determining the various transfer 

parameters, it is assumed that there is no difference in the behavior of potassium and 

cesium, but that discrimination occurs between the compartments. The loss of plant 

material, termed debris by Frissel, via branches, leaf fall and fruit loss is included and 

returned to the soil, but because uptake is homeostatically controlled, this has minimal 

influence on the tree contents. Frissel (1994) concluded that the model was probably not 

sufficient to describe cesium transfer to fruit. In particular, the use of three compartments 

was not sufficient to model availability within the plant. The model results do indicate 

that important processes are likely to be the biological half time of cesium in wood, the 

discrimination between cesium and potassium, cycling of potassium (through falling 

leaves, etc.), and uptake of potassium. 

The fruit plant model in the SPADE computer code (Thorne & Coughtrey 1983) has six 

compartments, representing internal leaf, external leaf, stem, fruit, storage organs and 

root. Movement of radionuclides within the plant model is controlled by empirically 

derived rate constants and parameters are derived for three broad categories of fruit plant: 

herbaceous, shrub and tree. Foliar absorption is represented by transfers between the 

external leaf and internal leaf compartments. Interception by plants takes account of 

changes in plant biomass with season. The original default parameters were based 

largely on data for cereals but were modifed in the case of tree and shrub fruits to allow 

for more rapid transfer from stem to root so that the root store could serve as a reservoir 

through subsequent seasons. Loss of radionuclides from external plant surfaces to the soil 

is modeled as transfer to the surface layer of the soil model. The process of root uptake is 

modeled as the transfer of radionuclides from soil solution to the plant root compartment. 

The transfer rate is also assumed to vary with soil layer depth, both as a function of the 

root distribution throughout the soil profile and as a function of the deposit distribution in 

soil. Consequently, the transfer of radionuclides from the soil solution to root is 

represented by a discrete transfer from each of the 10 layers in the soil model. The soil 

solution to root rate constant in each soil layer is a function of the root uptake rate 

constant and the assumed distribution of root activity in each layer. Three plant 

absorption mechanisms are responsible for the transfer of radionuclides at the soil-root 

interface: plant-base absorption, main root system absorption and tap root absorption. 

The actual value of the soil solution to root transfer coefficient for each root layer

corresponding to the soil layer of the soil model is calculated as the product of the 

specified rate coefficient and the normalized root shape modifier. 

None of these models appears to be suitable for generic use in long-term radiological 

assessments without substantial modification and simplification, and all require 

additional development of parameters before general use. Again, it was noted that 

measurements of radionuclide uptake in trees were lacking (Carini 2001), and 

recommended that “There is a need for research on the behavior of radionuclides in fruit 

crops to drive model development, not simply to parameterize existing models. Research 

should focus on understanding the key processes” (Coughtrey et al. 2001). As a result of 

these recommendations, the IAEA initiated the Environmental Modeling for Radiation 

Safety (EMRAS) program in 2003. This program has a Working Group on Revision of 
3-41

IAEA Technical Report Series No. 364 “Handbook of parameter values for the prediction 

of radionuclide transfer in temperate environments” and attempted to establish another 

Fruits Working Group. However, the participation in the Fruits group was so low that 

these participants joined with the Handbook group. 

3.4 Modeling the Uptake of Radionuclides in Animal Products 

In general, animals and animal products may become contaminated through a wide 

variety of pathways, in ways similar to humans. Pathways by which animal products 

may become contaminated include animal ingestion of plants, water, and soil (the 

animals’ inhalation is usually neglected as contributing little to the total as discussed 

below). However, as with people, the source of the foods and water may be quite varied, 

and include contributions from contaminated soil as well as, for predators, other 

potentially-contaminated animals. 

Absorption of radionuclides by animals via inhalation is of limited importance. Hvinden 

et al. (1964) showed clearly that the intake of radionuclides through inhalation was at 

least three orders of magnitude less than that from pasture. Since the respiratory tract is 

not usually an edible product for man, the significance of the inhalation route for food 

chain contamination is further reduced. 

3.4.1 Feed to Animal Product Transfer Factors 

The various routes of ingestion by animals (plants, water, prey) can be combined through 

the use of a transfer coefficient. The transfer coefficient is widely used in the literature to 

predict the transfer of radionuclides to animal food products. Ward and colleagues first 

used the transfer coefficient to describe the relationship between 137Cs in animal feed and 

its concentration in milk of dairy cows (Ward and Johnson 1965; Stewart et al. 1965; 

Johnson et al. 1968). They subsequently described the validation of this term as 

conceived (Ward and Johnson 1986). Ward and colleagues expressed their results as a 

ratio of the daily 137Cs intake (Bq/day) to the concentration of 137Cs per liter of milk 

(Bq/L). This term was used to successfully describe the relationship of 137Cs levels in 

feed and milk under varying environmental management conditions. Subsequently, this 

approach was found to provide a convenient method to describe the relationship between 

137Cs in feed and meat products (Johnson et al. 1969). 

A detailed mathematical derivation of the animal product transfer function is provided in 

Peterson (1983). Much of the early development of this function was done by Ng and 

associates (Ng and Thompson 1968; Ng et al. 1977; Ng, Colsher, and Thompson 1979; 

Ng 1982; Ng, Colsher, and Thompson 1982a; Ng, Colsher, and Thompson 1982b). 

This relationship (Fm) has subsequently been expressed in the literature by the following 

equation: 

( / ) ( / )

( / ) ( / ) Feed Concentration Bq kg Feed Intake kg day

Radionuclide Milk Concentration Bq L Fm day L

× = (25) 
3-42

For appropriate estimations, the feed concentration and the feed intake should be longterm averages of what is eaten rather than point measurements. Since the inception of 

this concept, transfer coefficients have been applied to many of the radionuclides; 

nevertheless, Ward and Johnston (1986) cautioned regarding the general applicability of 

the use of transfer coefficients for a wide number of radioelements and animal species. 

Others argue about the use and abuse of transfer coefficients, but according to Shaw 

(2001), “no one has yet come up with a better idea” for expressing this relationship. The 

same relationship is used for other animal products such as meat and eggs. 

Transfer to animal products has been expressed using various quantitative terms, 

sometimes with different dimensional units. These have included terms such as 

bioconcentration factor, transfer coefficients, transfer factor, concentration factor, 

concentration ratio, and aggregated transfer coefficient (ICRU 2001). In an effort to 

simplify and standardize this widely differing terminology, the International Commission 

on Radiation Units and Measurements has adopted a broad term called the concentration 

ratio, or Cr, which is defined as the ratio of the activity density of a radionuclide in the 

receptor compartment to that in the donor compartment (ICRU 2001). In the case of plant 

to animal transfers, the concentration ratio in this case is defined as the steady-state 

concentration in an animal tissue divided by the average concentration in feed. 

The concept of the transfer factor may be applied to essentially all routes of ingestion by 

animals: soil-to-animal, plant-to-animal, water-to-animal, and prey animal-to-predator 

animal. 

Some dynamic models such as PATHWAY( Whicker and Kirchner 1987) use 

assimilation fractions for ingested materials and biological elimination rates; however, 

these are also directly derived from the steady state or equilibrium transfer factors. 

As with radionuclide uptake into plants, some elements in animals may be 

homeostatically controlled. Very little work has been done to quantify the effect that this 

might have on animal product transfer factors.

3.4.2 The Observed Ratio in Animal Products 

A different approach to estimating uptake of radionuclides into animals is based on the 

observation that the presence of chemically similar stable elements in feed can have a 

significant impact on radionuclide uptake in animals. The ratio of the radionuclide-tostable-element concentration in one medium to the radionuclide-to-stable-element in 

another medium (for instance, feed and animals) has been named the observed ratio 

(OR). Early work developed the OR to predict the transfer of 90Sr uptake by milk (Comar 

et al. 1961; Comar et al. 1966). In this sense, the OR is described as the ratio of 

strontium to calcium in the milk following consumption of 90Sr-contaminated feed. 

Likewise, the cesium/potassium ratio was used to describe the uptake of 137Cs in milk, 

assuming that the relationship would be similar for cesium and potassium as for 

strontium and calcium. 
3-43

Although this approach has not been widely used for many years, it could potentially be 

used to simulate the uptake of radionuclides that are analogues of stable elements that are 

homeostatically regulated in animals. Homeostatic control via major routes allows the 

animal to regulate the tissue content of the various elements taken into the body, mostly 

via ingestion. These control systems include gastrointestinal absorption, urinary 

excretion, tissue deposition (storage pools or organ uptake such as the thyroid), secretion 

into milk, and endogenous excretion via feces. Some radionuclides have dietary essential 

stable isotopes (such as iodine) or analogues (such as calcium in the case of strontium), 

which are under homeostatic control by the animal. For other nuclides, control may be 

by the mechanisms controlling other essential elements. The intestine, thyroid gland, and 

mammary gland all have unique mechanisms for controlling many elements. For 

elements that are homeostatically controlled, the uptake and excretion is set to maintain 

the plasma or milk concentration. In this case, the transfer coefficient will not be 

constant over a wide range of conditions, and milk or tissue concentration may not vary 

as the intake changes. An increase in feed concentration of a radionuclide may not 

equate to an increase in tissue concentration for these contaminants. 

3.4.3 Unusual Animal Products 

The animal products commonly modeled include meat, milk, poultry, and eggs (e.g., 

GENII [Napier et al 2003], ERMYN [Wu 2003]). Beef is frequently the representative 

animal product for all meat (including beef, pork, wild game, and other meat), cows are 

the representative milk-producing animal, and chicken is the representative poultry 

animal and egg producer. Some compilations of transfer factor values are available for 

other animals, such as pork and lamb (e.g., Ng, Colsher, and Thompson 1982). As a 

general rule, transfer factors are not explicitly available for other meat animals such as 

deer, goats, rabbits, wild game birds, or other animals occasionally consumed by humans. 

A limited amount of data are available for transfer of contaminants to goat’s milk 

(primarily for iodine). In an appendix to their report, Ng, Colsher, and Thompson (1982) 

provide information on scaling reported values of the transfer factor for animals with 

characteristics different from those of the reference livestock. Such information could be 

used to scale estimates of transfer factors for other types of animal product, such as eggs 

from birds like ostriches or emus (see discussion below on allometric approaches). 

Arctic mammals such as seals, walrus, and whales are a unique subset of animals 

consumed by humans. A review by Layton et al. (1997) provides transfer factors for a 

few natural and artificial radionuclides for these types of animals. 

Some nomadic societies consume products from herded sheep and horses. Some limited 

data are available for actinides and long-lived fission products in these animals from 

measurements made at the Semipalatinsk Test Site in Kazakhstan. The Semipalatinsk 

Test Site, known as the “polygon”, is a 19,000 km2

 zone located in the northeast of 

Kazakhstan, 800 km north of the capital Almaty. Between 1949 and 1989, the former 

USSR conducted about 456 nuclear explosions at STS. Until 1963, most of the 

explosions were carried out on the surface and in the atmosphere (including 126 

atmospheric tests with 30 surface bursts). During the 40 years of testing, the total energy 

released in the testing was equivalent to 17.4 megatons of TNT. After the breakup of the 
3-44

Soviet Union, effective control over the area by local governments was lost. The region 

is a combination of arid plains and lightly forested mountains. Between 30,000 and 

40,000 people live near the site, and a small number of people actually live on the site, 

primarily semi-nomadic herders and farmers. Following the breakup of the Soviet Union, 

the Russian military moved out of the STS, and took nearly all records of activities and 

resulting contamination with them. The National Nuclear Center, Institute of Radiation 

Safety and Ecology (IRSE), in the city of Kurchatov, Kazakhstan, carries out research on 

radiation safety at the STS and radioecology of plants and animals. Preliminary contacts 

(personal communication, Dr. Larisa Ptitskaya to Bruce Napier) indicate that information 

may be available for the radionuclides of tritium, cobalt, strontium, cesium, europium, 

plutonium, americium, and radon. 

A few other animal products consumed by humans are not amenable to estimation using 

transfer factors. An example is honey from honey bees (e.g., Bonazzola et al. 1991; 

Fulkery et al. 1998). Accumulation of radionuclides in honey has been reported; 

however, no models for estimating concentration from environmental contamination 

levels are known. Bonazzola et al. (1991) reported that honey can be contaminated by 

radionuclides accumulating in soils or plants. The primary pathway of contamination is 

plant nectar; pollen did not appear to be a dominant contributor. However, the 

radionuclide content did not appear to be correlated between radionuclides. In addition, 

the plant concentration varied sufficiently that multifloral honeys could not be traced. 

These researches concluded that consideration of the botanical sources of the honey was 

also insufficient to allow use of honey as a bioindicator. 

3.4.4 Specific Activity Models for Animal Products 

Some key biologically-active elements are modeled in a separate way through the use of 

specific activity models. The behavior of the radionuclides tritium and 14C in exposure 

pathways must be handled in a special manner, because the behavior of these 

environmentally mobile radionuclides mimics that of stable hydrogen and carbon in 

biological processes. The concentrations of tritium or 14C in environmental media (soil, 

plants, and animal products) are assumed to have the same specific activity (curies of 

radionuclide per kilogram of soluble element) as the contaminating medium (air or water). 

The fractional content of hydrogen or carbon in an animal product is then used to compute 

the concentration of tritium or 14C in the food product under consideration. The hydrogen 

content in both the water and the nonwater (dry) portion of the food product is used when 

calculating the tritium concentration. For airborne releases, it is assumed animals obtain all 

their carbon through ingestion of plants. 

The simplest model for tritium in animal products (Baker, Hoenes, and Soldat 1976) 

defines the concentration of tritium in the animal product as 

ha

hf f w

Tp f Tw w

Ta F

F Q Q

C Q C Q C

+ / 9

+ = (26) 

where CTa = the concentration of 3

H in animal product (Bq/kg or Bq/L); 

 CTp = the concentration of 3

H in animal product feed crop p (Bq/kg); 
3-45

 CTw = the concentration of 3H in animal drinking water (Bq/L); 

 Fhf = the fraction of hydrogen in animal feed (dimensionless); 

 Fha = the fraction of hydrogen in animal product m (dimensionless); 

 Qf = the quantity of feed consumed per day (kg/d); and 

 Qw = the quantity of water consumed by the animal per day (L/d) 

 9 = coefficient converting concentration of tritium in water to concentration 

of tritium in hydrogen, valid for dilute solutions. 

For the variant of this model proposed by Peterson and Davis (2002), the generalized 

equations for calculating HTO and OBT concentrations in animal products (Bq kg-1 fw) 

are: 

Cap_HTO = [RFpp Ffr+ RFl IDpp Dfr + Wfr RFdw + ISAfr] Cam Ffw_ap (27) 

where 

Ffr = water fraction contributed to the diet by the water fraction of food; 

Dfr = water fraction contributed to the diet by the dry matter fraction of food; 

Wfr = water fraction contributed to the diet by drinking water; 

RFdw = fraction of HTO concentration in drinking water relative to that in air 

moisture; 

ISAfr = water fraction contributed to the diet by inhalation and skin absorption, 

and the other parameters are as defined for plants. 

The equation to calculate OBT in animal products assumes the specific activity in organic 

material equals the specific activity in the aqueous phase apart from a discrimination 

factor (Weq-ap). 

Cap_OBT = [RFpp Ffr+ RFl IDpp Dfr + Wfr RFdw + ISAfr] Cam Fdm_ap Weq_ap (28) 

Recommended default values for parameters in these equations are presented in Table 7. 

Values for fresh and dry matter fractions and for water equivalent factors are from Geigy 

(1981). 

As with Peterson and Davis’ (2002) model for HT in plants, the ratios of the HTO 

concentrations in soil, air and plants to the HT concentration in air recommended for 

screening level assessments by Peterson and Davis (2002) are 8 Bq L-1 / (Bq m-3) for the 

ratio of HTO in air moisture to HT in air, and 12 Bq L-1 / (Bq m-3) for the ratio of HTO in 

plant water to HT in air. Doses from HT are then modeled using the recommended HTO 

/ HT ratios for air moisture and plant water. Concentrations in air moisture are calculated 

by multiplying the HT concentration in air (CaH; Bq m-3) times eight. Concentrations of 

HTO and OBT in animal products are calculated for releases of HT by replacing RFpp in 

the above equations with a factor of 1.5. 
3-46

Table 7. Suggested parameter values for calculating HTO and OBT concentrations in 

animal products (adapted from Peterson and Davis 2002).

 Eggs Milk Beef Pork Poultry 

Fraction water ingested from fresh 

weight food (Ffr) 

0.034 0.371 0.409 0.031 0.034 

Fraction water ingested from dry 

weight food(Dfr) 

0.149 0.065 0.074 0.135 0.149 

Fraction water ingested from 

drinking water (Wfr) 

0.781 0.544 0.490 0.782 0.781 

Fraction water from inhalation and 

skin absorption (ISAfr) 

0.036 0.021 0.028 0.052 0.036 

Drinking water HTO / air moisture 

HTO (RFdw) 

0.5 0.5 0.5 0.5 0.5 

Fresh weight fraction (Ffw_ap) 0.74 0.897 0.668 0.50 0.67 

Dry matter fraction (Fdm_ap) 0.26 0.103 0.332 0.50 0.33 

Water equivalent factor (Weq_ap) 0.835 0.669 0.795 0.904 0.796 

The concentration of 14C in animal products is calculated as 

ca

cf f cw w

cp f cw w

ca F

F Q F Q

C Q C Q C

+

+ = (29) 

where Cca = the concentration of 14C in animal product (Bq/kg or Bq/L); 

 Ccp = the concentration of 14C in crop used for animal feed (Bq/kg); 

 Ccw = the concentration of 14C in animal drinking water (Bq/L); 

 Fcf = the fraction of carbon in animal feed (dimensionless) (Fcv in Table 5); 

 Fcw = the fraction of carbon in animal drinking water (dimensionless); 

 Fca = the fraction of carbon in animal product m (dimensionless) (Table 5); 

 Qf = the quantity of feed consumed per day (kg/d); and 

 Qw = the quantity of water consumed by the animal per day (L/d). 

3.4.5 Kinetic Modeling for Animals

Animals may be exposed to a contaminant via ingestion of contaminated water, soil, and 

food. The ECEM (Ecological Contaminant Exposure Model) is a food-web based 

ecological exposure assessment tool (Eslinger et al. 2004). ECEM is a detailed, food-web 

based, chronic exposure model intended for use in situations where an organism’s 

exposure to contaminants in the environment are of sufficient duration to result in 

contaminant uptake by the organism. This model was developed to allow estimation of 

concentrations and doses to biota for both hazardous chemicals and radionuclides; 

however, its structure allows its use in estimating concentrations in animals that humans 

might consume as well. The ECEM equations to estimate tissue concentration are 

described below for ingestion (similar sets of equations are also used to estimate animal 
3-47

exposures from dermal contact and inhalation – these are not regularly used for 

radionuclides). The basic ECEM structure is predicated on equilibrium absorption and 

loss rates from the animal. 

Water Ingestion: The equilibrium contaminant tissue concentration in species i from 

ingestion of water is calculated from the following expression: 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

i

i water

ingwi ingwi K

C D

α , (30) 

where 

Cingwi = tissue concentration in species i from ingestion of water (μg/kg wet tissue 

or pCi/kg wet tissue) 

Dingwi = applied daily dose to species i from water ingestion (μg/kg wet tissue/day 

or pCi/kg wet tissue/day) 

αi,water = ingestion absorption factor for species i from water ingestion (unitless) 

Κι = loss rate of contaminant for species i, including depuration and metabolism 

(1/day). 

The applied daily dose to species i from water ingestion is calculated from the equation 

(modified from EPA [1993]): 

⎥

⎦

⎤ ⎢

⎣

⎡ =

i

water i

ingwi i i W

EC WI D θ ψ (31) 

where 

Dingwi = applied daily dose to species i from water ingestion (μg/kg wet tissue/day 

or pCi/kg wet tissue/day) 

ECwater = concentration in surface water (μg/L or pCi/L) 

WIi = water ingestion rate of species i (L/day) 

Wi = body weight of species i (kg wet tissue) 

θi = area use factor for species i (ratio of contaminant area to home range – 

unitless) 

ψi = seasonality factor for species i (fraction of year spent at the contaminated 

site – unitless) 

Soil Ingestion: The contaminant body burden to species i from ingestion of soil is 

calculated from the equation: 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

i

i soil

ingsi ingsi K

C D

α , (32) 

where 

Cingsi = contaminant tissue concentration in species i from ingestion of soil (μg/kg 

wet tissue or pCi/kg wet tissue) 

Dingsi = applied daily dose to species i from soil ingestion (μg/kg wet tissue/day or 

pCi/kg wet tissue/day) 
3-48

αi,soil = ingestion absorption factor for species i from soil ingestion (unitless) 

Ki = loss rate for species i, including depuration and metabolism (day-1). 

 

The applied daily dose to species i from soil ingestion is calculated from the equation 

(modified from EPA [1993]): 

Dingsi = ECsoil SIi NIRtotali Fdwi θ i ψ i (33) 

where 

Dingsi = applied daily dose to species i from soil ingestion (μg/kg wet tissue/day or 

pCi/kg wet tissue/day) 

ECsoil = concentration in soil (μg/kg dry or pCi/kg dry) 

SIi = soil ingestion rate of species i (kg soil ingested/kg dry diet) 

NIRtotali = total normalized ingestion rate for species i (kg prey wet tissue/kg 

predator wet tissue/day). “Prey” may include plant species in this 

definition. 

Fdwi = conversion factor, dry diet to wet diet for species i (kg dry tissue/kg wet 

tissue) 

θi = area use factor for species i (ratio of contaminant area to home range – 

unitless) 

ψi = seasonality factor for species i (fraction of year spent at the contaminated 

site – unitless) 

The total normalized ingestion rate for species i is calculated from the equation (EPA 

1993): 

∑≠

=

j i

i ij j

i

totali W P ME

FMR NIR

( )

 (34) 

where 

NIRtotali = total normalized ingestion rate for species i (kg prey wet tissue/kg 

predator wet tissue/day) 

FMRi = free-living metabolic rate of predator species i (kcal/day) 

Wi = body weight of species i (kg wet tissue) 

Pij = wet weight or volume fraction of i’s diet consisting of prey j (unitless) 

MEj = metabolizable energy from prey j (kcal/kg prey wet tissue) 

The metabolizable energy from prey j is calculated from (EPA 1993): 

MEj = GEj AEj (35) 

where 

MEj = metabolizable energy from prey j (kcal/kg prey wet tissue) 

GEj = gross energy from prey j (kcal/kg wet tissue) 

AEj = assimilation efficiency of prey j (unitless) 
3-49

Food Ingestion: The equilibrium contaminant tissue concentration in species i from 

ingestion of food is calculated from the following expression: 

⎟

⎟

⎠

⎞

⎜

⎜

⎝

⎛ =

i

ij

ingfi ingfi K

C D

α

 (36) 

where 

Cingfi = equilibrium tissue concentration in species i from ingestion of food (μg/kg 

wet tissue or pCi/kg wet tissue) 

Dingfi = applied daily dose to species i from food ingestion (μg/kg wet tissue/day 

or pCi/kg wet tissue/day) 

αij = ingestion absorption factor for species i from ingestion of food species j

(unitless) 

Ki = loss rate of contaminant for species i, including depuration and 

metabolism (1/day) 

The applied daily dose to species i from food ingestion is calculated from the equation 

(modified from EPA [1993]): 

= ∑

j

Dingfi i i Cj NIRj θ ψ ( ) (37) 

where 

Dingfi = applied daily dose to species i from food ingestion (μg/kg wet tissue/day 

or pCi/kg wet tissue/day) 

θi = area use factor for species i (ratio of contaminant area to home range – 

unitless) 

ψi = seasonality factor for species i (fraction of year spent at the contaminated 

site – unitless) 

Cj = average contaminant concentration in j

th food item (μg/kg wet tissue or 

pCi/kg wet tissue) 

NIRj = normalized ingestion rate of j

th food type on a wet-weight basis (kg prey 

wet tissue/kg predator wet tissue/day) 

The normalized ingestion rate of j

th food type on a wet-weight basis is calculated (EPA 

1993) as: 

NIRj = Pij NIRtotali (38) 

where 

NIRj = normalized ingestion rate of j

th food type on a wet-weight basis (kg prey 

wet tissue/kg predator wet tissue/day) 

Pij = wet weight or volume fraction of i’s diet consisting of prey j (unitless) 

NIRtotali = total normalized ingestion rate for species i (kg prey wet tissue/kg 

predator wet tissue/day) 

The term Pij is a large matrix describing which animal eats which plant or other animal. 
3-50

Total Terrestrial Animal Burden: The equilibrium tissue concentration for a 

contaminant in terrestrial animal species i is then calculated from the sum of the dermal, 

inhalation, and ingestion exposures. As can be seen from these equations, this model 

requires a great deal of information, including the absorption and depuration rates and the 

predation (food source) matrix. Much of this can be approximated, or estimated using 

allometric analyses (see below). 

3.4.6 Allometric Models for Uptake by Animals 

A key limitation to the use of transfer factors to relate intake of contaminants by various 

animal types to concentrations in animal products is the lack of measurements of various 

radionuclides in most animals. A developing technique for estimating the transfer of 

contaminants in animal products is allometry (Higley, Domotor, and Antonio 2003). 

The application of transfer factors for many types of animal products is problematic 

because of the wide range of organisms potentially exposed. For example, there are very 

limited data available for riparian and terrestrial animals (i.e. very few terrestrial 

animal:water and riparian animal:sediment concentration ratios). An alternative approach, 

called the kinetic/allometric method, was developed. Among other objectives, this work 

filled in data gaps in the literature on transfer factors for specific riparian and terrestrial 

animal receptors. 

Allometry, or the biology of scaling, is the study of size and its consequences. There are 

several allometric equations that relate body size to many parameters, including ingestion 

rate, life span, inhalation rate, home range and more (Schmidt-Nielsen 1977; West et al. 

1997; Wilkie 1977). The most common form of allometric equation is the power 

function 

β Y = α X (39) 

where Y and X are size related measures, and α and β are constants. Allometric equations 

provide a way to estimate a biological process given a specific set of parameters. While 

these equations were originally derived from empirical observations, there is a growing 

body of evidence to suggest that these relationships have their origins in the dynamics of 

energy transport mechanisms. For example, allometry has been used to estimate the daily 

rate of consumption by an animal in relation to its body size. Metabolic rate is known to 

scale to body mass to the 3⁄4 power (Calder 1984; Reiss 1989; West et al. 1997). This 

scaling has been found to extend to poikilothermic and ectothermic animals ( Bennett and 

Dawson 1976) as well as unicellular ones (Wilkie 1977). Intraspecific scaling of 

metabolism has been found to vary somewhat, with the exponent of body weight larger 

for juveniles than adults (Reiss 1989). However, allometric equations are meant to 

represent qualitative trends over orders of magnitude of body mass. Consequently, these 

general allometric relationships can be used as general predictors regardless of age, or 

phyla to provide species-independent estimates of uptake. 
3-51

Higley, Domotor, and Antonio (2003) have developed equations to predict concentrations 

of radionuclides in tissues for terrestrial and riparian animals exposed to contaminated 

soil, sediment or water. The equations were developed as a means to provide estimates of 

transfer factors in the absence of data for particular species for radionuclides in soil, 

water or sediment. The allometric approach provides a potentially useful method to 

extrapolate radionuclide behavior across multiple species. While the method is simplistic, 

variations of this technique can be used to roughly estimate tissue concentrations, 

biological elimination rates, and uptake factors across a wide range of organisms. In the 

absence of measured data it can provide a starting point for modeling environmental 

exposure to contaminants. 

3.5 Modeling the Effects of Food Processing on Radionuclide 

Concentrations 

Changes in concentration in foods as a result of food preparation practices and activities 

are not commonly included in assessment models. Although such processes are routinely 

acknowledged, there is a relative scarcity in the literature of information as to how they 

should be handled. Evidence exists that soaking, peeling, boiling, or baking can 

effectively halve concentrations in consumed food. (NRPB 1995; Watterson and 

Nicholson 1995; Jackson and Rickard 1998). For instance, the EPA Exposure Factors 

Handbook does not even include a section about this process (EPA 1997). “Dose 

calculations do not normally make allowance for such reductions, partly on the basis that 

considerable variability may exist between individuals and that, for instance, water or fats 

used for cooking may themselves be contaminated, so that any dose saving overall would 

be marginal” (Jackson et al. 1998). In addition to that, there is a growing segment of the 

general population that tend to reduce its consumption of the heavily processed 

foodstuffs, as well as meat, poultry and other products.

Most radiological assessment codes use a simple approach to determining contaminant 

concentrations in food crops; the concentrations in the crops are determined using a 

surface-deposition-to-concentration translocation factor for above-ground deposition, and 

a soil-to-edible-plant concentration ratio for growth in contaminated soils. This differs 

somewhat from the EPA approach to the same problems for dioxins and other lipophilic 

contaminants (EPA 1994, EPA 1998). The EPA approach uses a soil-water-to-bulk 

contamination ratio rather than a soil-to-bulk ration, and uses a Kd to relate soil 

contamination to soil-water concentrations. A further assumption in the EPA method for 

these contaminants is that these compounds do not transfer from contaminated surfaces 

(leaves or roots) into the vegetation, but are sorbed onto the surface. They then define an 

“empirical correction factor” (VG) that is essentially the ratio of the mass of the skin of 

the vegetable to the mass of the whole vegetable, further simplified with the assumption 

that the densities of the skin and bulk volume are the same, so that the ratio is of the 

volume of skin to total volume of vegetable. This correction factor is then adjusted for 

washing and peeling. The justification given in EPA (1994) is “Additional reductions in 

concentration result from peeling, cooking, or cleaning, for example. Wipf, et al. (1982) 

found that 67% of unwashed carrot residues of 2,3,7,8-TCDD came out in wash water, 

and 29% was in the peels. A peeled, washed carrot correction factor might ... be, ... 0.04, 
3-52

(... 0.04 = 100% - 67% - 29%). A 96% reduction in the estimated VG for the potato (the 

potato is cleaned and the skin is not eaten; additional reductions possibly when cooking 

the potato) would equal 0.01. In a site-specific application, the type of vegetation, 

preparation, and so on, should be considered.” The adjustment given by EPA is thus a 

combination of the washing and peeling and the assumption that nearly all contamination 

is in the skin. This sort of correction factor should not be used with the soil-to-edibleplant concentration ratio models, because the CR used should already contain the 

assumption of low translocation and soil-to-plant transfer. Only the fraction of the 

reduction due to washing is always pertinent, and the peeling portion should be 

considered. 

The NATO Manual FM-8-10-7 (Army 1993), Appendix F, gives decontamination 

procedures for foods contaminated by nuclear, chemical, and biological (NBC) agents. 

The procedures are designed for contamination resulting from NBC combat, and the 

decontaminated foods are intended for consumption by soldiers or civilians in a postcombat situation; however, the processes and techniques are common ones that also 

could apply to home uses. As described in this manual, “some products can be 

decontaminated by washing, peeling, or trimming the outer skin or leaves. Decontaminate 

potatoes and hard-skinned fruits and vegetables by washing or scrubbing under running 

water, followed by peeling or scraping, then washing again. Potatoes, carrots, beets, and 

turnips can be washed at the supply depot. However, do not wash beans, rice, and onions 

until they are delivered to the field kitchen; washing reduces their storage quality and 

shelf life. Citrus fruits, pineapples, corn, peas, beans, melons, pumpkins, cabbage, and 

nuts can be peeled. Decontaminate cucumbers, tomatoes, cherries, cranberries, grapes, 

pears, plums, and thin-skinned squash by soaking in a water or detergent solution and 

rinsing with vigorous agitation or brushing. Apricots, peaches, most berries, asparagus, 

broccoli, and leafy vegetables cannot be satisfactorily decontaminated because of fuzzy 

surfaces, irregular shapes, or small size which makes washing difficult. It is not practical 

to decontaminate food contaminated through the food-chain. Meat and milk are the two 

most common foodstuffs contaminated in this way. 

 “Milk may be decontaminated to a safe level by a complicated ion exchange process. 

The I-131 activity will decline rapidly during storage of milk and milk-products, although 

the Cesium and Strontium activity will remain almost constant for years. In an area with 

high-level fallout, milk is withdrawn from human consumption. The duration of 

withdrawal will be dependent upon the type of fallout and levels. Meat may be 

decontaminated to a safe level by soaking in water or brine. Cesium is loosely bound in 

the meat. By repeated soaking of meat cut in small pieces, most of the Cesium activity 

will be removed. Traditional meat preserving, such as salting with brine, will remove up 

to 60 to 70 percent of the Cesium activity.” (Army 1993). 

A fairly extensive review of available literature was conducted in association with the 

VAMP program of the IAEA (Noordijk and Quinalt 1992). This reference introduces a 

food processing retention factor, Fr, which is defined as the total amount of a contaminant 

in processed food divided by the total amount of contaminant in the original raw food. 

This report also introduces a related parameter, the processing efficiency Pe, which is the 
3-53

mass of prepared product divided by the mass of raw material. Numerous tables of these 

values for various foods processed via various methods are presented. Averages and 

ranges are presented in these tables. The ranges tend to be broad, and the average Fr

values appear to be around 0.5. 

Noordijk and Quinalt (1992) stress that all Fr values referring to extraction procedures 

such as cooking, frying, etc., are only valid when the extraction liquid is removed and not 

used for other culinary purposes. The same applies to fractionation processes which take 

place, such as in the dairy industry or during the milling of grains. For example, the byproduct of cheese making, whey, was formerly regarded as a waste or used to feed 

animals. A large part of produced whey today is used as an additive for food for humans. 

Similarly, all fractions of the milling process are usually used to produce food. In these 

cases, an Fr value of 1.0 should be used. 

Noordijk and Quinalt (1992) summarize that the effects of processing on the behavior of 

contaminants depends on the contaminant, on the type of product, and on the method of 

processing. Processing effects are rather small for root crops, whereas milling cereal 

grains to flour will often remove about 70% of the contamination. The effects of 

processing on vegetables and fruits are rather unpredictable, especially when the 

contaminants are adsorbed on the surface of the plants. 

Green and Wilkins (1995) extend the efforts of the IAEA study by Noordijk and Quinalt 

(1992). This review of the literature uses the same concepts (while renaming Fr as Rt) 

and adds additional references. This review also has reasonably detailed discussions of 

the applicability of the reported values for application to critical group analyses. In 

general, Green and Wilkins recommend values of 1.0 because of uncertainties in whether 

liquids used in food processing would be consumed. 

A possible method of handling the complexities of the food processing retention factor 

was developed for this report. The method incorporates the uncertainties of both the 

retention in food of the contaminants, the variabilities in retention factor Fr for different 

types of cooking technique, as well as the uncertainties in whether the cooking liquors are 

consumed. The concept can be described as: 

Ceaten = Craw [ Fr + ( 1 – Fr ) S ] (40) 

where Ceaten = the concentration in cooked or processed foods, 

 Craw = the concentration in raw or unprocessed foods, and 

 S = the fraction of cooking liquids and sauces that is consumed. 

This formulation assumes that the contaminants lost in the food preparation process are 

released into the cooking liquids. 

A complication to the process is that there are different types of food preparation 

processes. In evaluation of the data in the various reports, it appears that “dry cooking” 

techniques such as broiling, baking, or frying have different removal efficiencies than 
3-54

“wet cooking” techniques such as boiling, steaming, or stewing. In addition, different 

types of foods will have different proportions of each preparation technique. These can 

be accommodated by expanding the general equation for specific applications, as: 

Ceaten = Craw [ fdry { Fr_dry + ( 1 – Fr_dry ) Sdry } + 

fwet { Fr_wet + ( 1 – Fr_wet ) Swet } + fraw ] (41) 

In this formulation, the total intake of each type of food is subdivided into raw or 

unprocessed, wet cooked, and dry cooked. The approach may also be expanded to 

include other types of processing, as for milk, which includes fresh milk, cheeses, and 

whey. 

It seems apparent that this approach is impractical, because it has introduced 3 fractions, 

two processing retention factors, and a fractional consumption of cooking liquors for 

each food type. It is unlikely that data will be available to populate such a model, 

although there might be data available in the 1977 National Food Consumption Survey to 

begin defining such parameters. However, in a stochastic model, wide ranges of 

uncertainty may be combined into a single compound distribution. 

A Crystal Ball® enabled EXCEL spreadsheet was used to evaluate the possible 

distributions that might be encountered. The fractions of foods eaten in raw, wet-cooked, 

and dry-cooked states were broadly estimated by the author. The ranges for each of the 

possibilities were assigned uniform distributions. Most are wide enough to accommodate 

nearly all eventualities; none of the results are overly sensitive to the assumptions. The 

total fraction of foods consumed for each type was normalized to 1.0; this ensures 

conservation of mass, but it also tends to minimize the sensitivity of the answer to the 

specific distributional assumptions of the consumption fractions. The ranges of food 

retention parameters are taken from Green and Wilkins (1995). Using the above general 

equation, food processing retention factor distributions were generated for the common 

food types used in risk assessments: leafy vegetables, other vegetables, fruits, grains, 

meat, and milk. 

The results of the computations confirm that for deterministic, maximum individual or 

critical group calculations, a processing retention of 1.0 is a reasonable and not overlyconservative assumption. A value of 1.0 is always possible, and mean values for most 

food types are around 0.8 to 0.9. For leafy vegetables and other vegetables, the mean is 

about 0.8, ranging from 0.4 to 1.0. For fruits and grains, the mean is nearly 0.95, and the 

range is well under a factor of 2. The range for meat is from 0.3 to 1.0, with a mean of 

about 0.8. Only for milk is there a substantial variability and non-linearity: the result 

depends heavily on how much cheese is eaten in proportion to milk, because the making 

of cheese tends to reduce the contaminant concentrations. 

As a result of the investigation, the distributions developed for the analysis are available 

for use. All of them are quite stable, except for the milk-processing factor. The results 

are summarized in Table 8. All distributions are simple – either uniform or triangular. 

Several approach right triangles, where the mode equals the maximum at 1.0. For milk, a 
3-55

triangular distribution is suggested, but the mode (most likely) value is essentially 

equivalent to the adjusted fraction of milk intake assigned to fresh milk; i.e., if 80 percent 

of milk intake is fresh, the mode of the triangle should be at 0.8, and if 50 percent of milk 

intake is fresh, the mode of the triangle should be at 0.5. This is the only parameter with 

sufficient sensitivity to warrant case-specific consideration in developing of exposure 

scenarios. 

Table 8. Recommended Values of Food Processing Retention Factors for Most 

Contaminants 

Food Type Distribution Type Minimum Mode Maximum 

Leafy 

Vegetables 

Uniform 0.5 0.85 1.0 

Other 

Vegetables 

Triangular 0.6 0.95 1.0 

Fruits Triangular 0.9 1.0 1.0 

Grains Uniform 0.9 - 1.0 

Meat Triangular 0.5 0.95 1.0 

Milk Triangular 0.25 0.8* 1.0 

* Distribution for milk is dependent on the fraction of milk intake assigned to cheese. 

The case here assumes 20 percent of milk intake results from consumption of locallymade cheese. 

The radionuclide tritium (3

H) is a special case. The food processing retention factors for 

tritium could be lower, because cooking tends to drive off water in foods, wherein most 

of the tritium resides. The spreadsheet calculations described above for other 

contaminants were modified and performed for tritium. The results are presented in 

Table 9. Note that there is relatively little difference from Table 1, indicating that it may 

not be necessary to have any contaminant-specific inputs. 

Table 9. Recommended Values of Food Processing Retention Factors for Tritium 

Food Type Distribution Type Minimum Mode Maximum 

Leafy 

Vegetables 

Uniform 0.5 0.85 1.0 

Other 

Vegetables 

Triangular 0.6 0.9 1.0 

Fruits Triangular 0.75 1.0 1.0 

Grains Uniform 0.99 - 1.0 

Meat Triangular 0.6 0.9 1.0 

Milk Triangular 0.5 1.0 1.0 
3-56

3.6 Modeling Other Terrestrial Exposure Pathways 

In the preparation of this report, a few unique examples of terrestrial human exposure 

pathways were identified. Although not part of standard food-chain pathways, these 

additional pathways deserve attention. 

3.6.1 Unique Direct Pathways 

The pathway of showering with contaminated water, leading to inhalation exposure, is 

common to non-radiological assessments dealing with volatile chemical compounds (US 

EPA 1997); however, with the notable exception of radon, it is infrequently examined in 

radiological assessments because most radionuclides are not considered to be volatile. 

Even non-volatile contaminants can become entrained in water droplets and inhaled. For 

some radionuclides with very low GI-tract uptake, lung doses from this mechanism can 

be higher than other organ doses from direct drinking of the water. The concentration of 

radionuclides in the air of the shower can be related to the quantity of mist droplets 

generated, using the absolute humidity of the air (Andelman 1990). As a general rule, 

radionuclide intakes via this pathway tend to be small. However, tritiated water can 

transpire through the skin, and some models (e.g. GENII) sometimes multiply the 

nominal inhalation dose conversion factor by a factor of 1.5 to account for it (Napier et 

al. 1988). 

A similar exposure pathway is Sweat bathing as part of the Sweat Lodge Ceremony, a 

traditional Native American custom (DOE 1997; Harris and Harper 1997). Based on 

tribal descriptions, between 0.5 and 3 hours/day on a weekly basis is assumed to be spent 

inside a sweat lodge kept at 60 - 80 degrees Centigrade (145 - 180 degrees Fahrenheit). 

No or very limited clothing is worn by the Ceremony participants. A large amount of 

wood is used to heat up the rocks in an open outside fire adjacent to the Lodge. The sweat 

lodge is heated with these hot rocks, onto which water is poured to create steam. Air 

inside the sweat lodge is assumed to be saturated with water (equivalent to 0.3 kilograms 

of water per m3

 of air, and 0.3 L/m3 of semivolatiles and 2.5 L/m3 of volatiles), which are 

then available for inhalation and dermal absorption over the entire body. During the 1 

hour of use, 4L of water is used. Doses resulting from intakes of some radionuclides via 

this pathway can be larger than the associated doses via drinking water if the 

radionuclides have low GI-tract absorption, since this is a mechanism for inhalation of 

large amounts of water. 

Evaporative coolers are commonly used in the hot, arid American West. Evaporative 

coolers cool air by evaporating a stream of water into a stream of air. These coolers 

might transfer water-borne contaminants to the indoor air. Thus, modeling must include 

an estimate of the radionuclide concentrations in indoor air when evaporative coolers are 

in operation so that the radiation dose for the human receptor who inhales the 

contaminated air can be evaluated. Based on how evaporative coolers operate and the 

conservation of radioactivity (i.e., activity transferred to air is equal to the loss of activity 

from water), radionuclide concentrations in indoor air are estimated for this pathway by 

Wu (2003) as 
3-57

i

air

water

ei evap Cw

F

M Ca = f (42) 

where 

Caei = activity concentration of radionuclide i in the air resulting from the operation 

of an evaporative cooler (Bq/m3

) 

fevap = fraction of radionuclides in water transferred to indoor air (dimensionless) 

Mwater = water evaporation rate (water use) for an evaporative cooler (m3

/hr) 

Fair = air flow rate for an evaporative cooler (m3

/hr) 

Cwi = activity concentration of radionuclide i in the groundwater (Bq/m3

). 

The fraction of radionuclides that remain in the reservoir, bleed-off water, or in the pads 

of evaporative cooler are not further modeled because it becomes a regular water source 

for irrigation or sewage, or is removed when the pads are replaced, and therefore may not 

cause direct exposure (although for the case of continuous deposition of gamma emitters 

on the pad when the pad is replaced only once in every several years, there might be 

some concern of the long-term continuous direct exposure to the radionuclides deposited 

on the pad, depending on the location of the evaporative cooler inside the dwelling). 

Evaporation and air flow rates are estimated based on specifications of residential 

evaporative cooling units. The typical evaporation rate is about 20 L/hr, and typical air 

flow rates range from 2,000 to 10,000 m3

/hr (BSC 2003). The fraction of radionuclides 

transferred from the water to the indoor air is an important parameter that is not available 

in the literature, but the theoretical range is from 0 to 1 (BSC 2003). The calculation of 

activity concentrations in the air resulting from evaporative coolers does not include 

consideration of radionuclide buildup in the indoor air, because the air flow associated 

with the use of these coolers is such that during operation the windows of the building 

remain open and the number of air exchanges per hour is quite large. The calculated 

indoor air concentrations are usually low because the air flow rate of the coolers is so 

high. 

3.6.2 Unique Indirect Pathways 

Contamination of trees In Europe with 137Cs following the Chernobyl accident has led to 

detectable concentrations of radionuclides in wood. In villages in Ukraine and Belarus, 

wood is a common kitchen fuel. Wood ashes have been found to routinely exceed 50,000 

Bq/kg. Besides being a source of direct external exposure, the wood ashes were being 

distributed in kitchen gardens as soil amendments. The total administration of ashes in 

one year was equivalent to about 25% of the total 137Cs deposition on the garden from the 

initial accident. Over a period of many years, this process resulted in reconcentration of 

cesium and creation of an ingestion pathway (Dubreuil et al. 1999) that could be 

multiples of 2 or 3 greater than the initial fallout soil contamination in the gardens. 

Groundwater beneath the Hanford Site in eastern Washington State is contaminated with 

tritium at levels several times that of the drinking water standards (Poston, Hanf, and 

Dirkes 2005). Trees near the Columbia River have roots that penetrate to the 

groundwater. The trees have been found to not only contain tritium, but to transpire it to 

the atmosphere. A similar source was documented at the Oak Ridge Site under Solid 
3-58

Waste Storage Area Five. In essence, the trees are a source of atmospheric release of 

groundwater tritium. However, the resulting atmospheric concentrations are low because 

of the large dispersion.
4-1

4.0 Discussion

A number of alternative conceptual models for the key processes and mechanisms related 

to modeling the transport of radionuclides through the terrestrial biosphere have been 

presented. Several of the processes are not well known (e.g., foliar absorption and 

translocation, non-linear uptake of nutrient analogues, numerous transfer factors for 

understudied radionuclide plant/animal combinations) and offer areas for fruitful 

research. 

As a summary of the presentations, the following currently available techniques are the

most likely to be successful in generic applications.

• For soil, an annual average model incorporating: 

o Accumulation from irrigation or atmospheric deposition; 

o Leaching to deeper soil, using a Kd -modulated leach rate; 

o Harvest removal, averaged over crop types 

o Uniform mixing in a reasonable (15-25 cm) soil surface layer, implicitly 

caused by plowing, bioturbation, and leaching; 

o Neglecting radionuclide fixation, because appropriate long-term 

measurements of distribution coefficient and concentration ratio will 

already incorporate the effects; 

o Neglecting surface-soil erosion losses, because eroded material from one 

location may accumulate in another, cancelling any perceived benefit. 

• For resuspension, a mass-loading approach, because it has the lowest variability 

and is the most easily defended. 

• For foliar interception, models incorporating: 

o Dry interception following the basic model suggested by Chamberlain 

(1967) as updated by Adriano et al. 1982; 

o Wet interception considering one of the algorithms derived from the data 

of Hoffman et al. (1989) or Prohl and Hoffman (1993). 

• For plant contamination with soil, an adhesion model applied so that material 

translocated is not subject to weathering (e.g., IAEA 2003; Wu 2003). 

• For weathering, a single exponential model with a half-time between about 10 

and 20 days, applied to material on the surface of the plant only. 

• For translocation, a radionuclide-specific (or chemical-class-specific) 

implementation allowing translocated materials to avoid being removed via 

weathering processes (e.g., IAEA 2003; Wu 2003). 

• For soil-to-plant transfer, a radionuclide- and plant-type-specific concentration 

ratio, where available, with: 

o Site-specific application of additional crops, such as mushrooms and 

berries; 

o The specific-activity model of Peterson and Davis (2002) for elemental 

and oxide forms of tritium; 
4-2

o A general specific-activity model for 14C in air, adapted to the RESRAD 

(Yu et al. 2001) model for transfer from irrigation water to air as 14CO2; 

o Perhaps site-specific application of specific-activity models for iodine and 

other micro-nutrient and macro-nutrient elements and their chemical 

analogues. This is a simplification of the need to allow for homeostatic 

regulation of some elements. 

• Until a simple, robust Fruit Tree model is developed, continue to use the 

concentration ratio approach for fruits. 

• For animal products, a transfer factor approach applied to average daily feed, 

water, and soil intake by the animal where data are available. 

o For other element/animal combinations, a justified mix of specific-activity 

and allometric models should be considered. 

• For food processing, because the data are sparse and the reduction is generally 

small, modelers are justified in ignoring losses (which is equivalent to using a 

food-processing transmission factor of 1.0). 

Site-specific models for additional little used or unusual pathways (e.g., honey, 

evaporative cooling systems) may need to be developed, justified, and used as appropriate for 

the system and environment being analyzed.
5-1

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