Technical Reports SeriEs No.

472

Handbook of Parameter
Values for the Predictionof Radionuclide Transfer in
Terrestrial and Freshwater
Environments

HANDBOOK OF PARAMETERVALUES FOR THE PREDICTION OF
RADIONUCLIDE TRANSFERIN TERRESTRIAL AND
FRESHWATER ENVIRONMENTS

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TECHNICAL REPORTS SERIES No. 472

HANDBOOK OF PARAMETERVALUES FOR THE PREDICTION OF
RADIONUCLIDE TRANSFERIN TERRESTRIAL AND
FRESHWATER ENVIRONMENTS

INTERNATIONAL ATOMIC ENERGY AGENCY
VIENNA, 2010

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IAEA Library Cataloguing in Publication Data
Handbook of parameter values for the prediction of radionuclide transfer interrestrial and freshwater environments. – Vienna : International Atomic
Energy Agency, 2010.
p. ; 24 cm. – (Technical reports series, ISSN 0074–1914 ; no. 472)
STI/PUB/472
ISBN 978–92–0–113009–9
Includes bibliographical references.
1. Radioisotopes – Migration. 2. Radioisotopes – Environmental aspects.
3. Radioactive pollution. 4. Environmental impact analysis – Mathematicalmodels. I. International Atomic Energy Agency. II. Series: Technical reports
series (International Atomic Energy Agency) ; 472.
IAEAL

10–00619

FOREWORD
For many years, the IAEA has published materials aimed at supporting theassessment of radiation impacts on human beings and the environment. Two
major publications, Sediment Kds and Concentration Factors for Radionuclides in
the Marine Environment (Technical Reports Series No. 247), published in 1985,
and the Handbook of Parameter Values for the Prediction of Radionuclide
Transfer in Temperate Environments (Technical Reports Series No. 364),
published in 1994, together provided a full set of available transfer parametervalues for the marine, freshwater and terrestrial environments. For many years,
these two publications have served as key references for radioecologists,
modellers and authorities, providing data for use in environmental impact
assessments.
Since the publication of these two collections of data, a number ofpublications on transfer parameter values have been produced and meritconsideration. Therefore, in 2000 the IAEA initiated a revision of Technical
Reports Series No. 247 which resulted in the publication, in 2004, of SedimentDistribution Coefficients and Concentration Factors for Biota in the Marine
Environment (Technical Reports Series No. 422), covering newly obtained data
as well as changes in the regulatory framework.
In 2003, within the framework of the Environmental Modelling for
Radiation Safety (EMRAS) programme, the IAEA undertook a revision ofTechnical Reports Series No. 364. The current publication was prepared by themembers of Working Group 1 of the EMRAS programme, chaired by P. Calmon(IRSN, France). This publication focuses on transfer parameter values; themodels in which they are used generally are not described here. It is therefore
supported by IAEA-TECDOC-1616, which accompanies this report and contains
the full collection of the reviewed data and provides radioecological concepts andmodels facilitating the use of these values in specific situations. This publication
is intended to supplement existing IAEA reports on environmental assessment
methodologies.
The IAEA wishes to express its gratitude to all the experts who contributed
to this report, and to the International Union of Radioecologists for its support.
The IAEA officer responsible for this publication was S. Fesenko of the
Agency’s Laboratories (Seibersdorf and Headquarters).

EDITORIAL NOTE
Although great care has been taken to maintain the accuracy of information contained inthis publication, neither the IAEA nor its Member States assume any responsibility forconsequences which may arise from its use.
The use of particular designations of countries or territories does not imply any
judgement by the publisher, the IAEA, as to the legal status of such countries or territories, of
their authorities and institutions or of the delimitation of their boundaries.
The mention of names of specific companies or products (whether or not indicated asregistered) does not imply any intention to infringe proprietary rights, nor should it beconstrued as an endorsement or recommendation on the part of the IAEA.

CONTENTS
1.

2.

3.

4.

INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1

1.1.
1.2.
1.3.
1.4.

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1
3
3
3

DEFINITIONS AND DATA ANALYSIS . . . . . . . . . . . . . . . . . . . . .

4

2.1.
2.2.
2.3.
2.4.

Basic definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Time dependence of radionuclide transfer factors . . . . . . . . . . .
Soil and plant classifications . . . . . . . . . . . . . . . . . . . . . . . . . . .

4
4
7
9

AGRICULTURAL ECOSYSTEMS: FOLIAR UPTAKE . . . . . . . . .

11

3.1. Interception . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.1. Definitions and parameters . . . . . . . . . . . . . . . . . . . . . .
3.1.2. Interception fractions . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2. Weathering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.1. Definitions and parameters . . . . . . . . . . . . . . . . . . . . . . .
3.2.2. Weathering half-lives . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.2.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3. Translocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.1. Definitions and parameters . . . . . . . . . . . . . . . . . . . . . . .
3.3.2. Translocation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.3.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4. Resuspension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.1. Definitions and parameters . . . . . . . . . . . . . . . . . . . . . .
3.4.2. Resuspension factor . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

11
11
12
16
17
17
17
17
18
18
18
21
23
23
23
24

RADIONUCLIDE INTERACTION IN SOILS . . . . . . . . . . . . . . . . .

25

4.1. Concepts and processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1.1. The solid-liquid distribution coefficient concept . . . . . .
4.1.2. Vertical transfer of radionuclides in undisturbed
soil profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

25
25
26

5.

6.

7.

4.1.3. Relationship between Kd and other parameterscharacterizing radionuclide mobility . . . . . . . . . . . . . .
4.2. Solid-liquid distribution coefficient values . . . . . . . . . . . . . . . .
4.3. Vertical migration in undisturbed soil profiles . . . . . . . . . . . . . .
4.4. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

27
30
30
37

ROOT UPTAKE OF RADIONUCLIDES IN AGRICULTURALECOSYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

39

5.1. Definitions and processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2. Temperate environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.2.1. Radionuclide transfer to plants . . . . . . . . . . . . . . . . . . .
5.2.2. Radionuclide transfer to fruits . . . . . . . . . . . . . . . . . . . .
5.3. Tropical and subtropical environments . . . . . . . . . . . . . . . . . . .
5.4. Radionuclide transfer to rice . . . . . . . . . . . . . . . . . . . . . . . . . . .
5.5. Time dependence of radionuclide transfer to plants . . . . . . . . .
5.6. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

40
41
41
63
68
78
78
81

AGRICULTURAL ECOSYSTEMS: TRANSFER TO ANIMALS . . .

82

6.1. Gastrointestinal fractional absorption . . . . . . . . . . . . . . . . . . . .
6.1.1. Absorption in ruminants . . . . . . . . . . . . . . . . . . . . . . . . .
6.1.2. Absorption in monogastrics . . . . . . . . . . . . . . . . . . . . . .
6.2. Transfer to animal products . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2.1. Transfer coefficients . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2.2. Concentration ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.2.3. Transfer values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

83
83
85
85
86
87
88
96

RADIONUCLIDE TRANSFER IN FORESTS . . . . . . . . . . . . . . . . .

99

7.1. Radionuclide transfer to trees . . . . . . . . . . . . . . . . . . . . . . . . . .
7.1.1. Interception of radionuclides in tree canopies . . . . . . . .
7.1.2. Aggregated transfer factors for soil–tree transfer . . . . .
7.2. Radionuclide transfer to mushrooms . . . . . . . . . . . . . . . . . . . . .
7.3. Radionuclide transfer to berries . . . . . . . . . . . . . . . . . . . . . . . . .
7.4. Radionuclide transfer to game . . . . . . . . . . . . . . . . . . . . . . . . . .
7.4.1. Factors affecting transfer values . . . . . . . . . . . . . . . . . .
7.4.2. Aggregated transfer coefficient and half-life values
in game and reindeer . . . . . . . . . . . . . . . . . . . . . . . . . . .
7.5. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

99
99
100
102
104
105
105
106
109

8.

9.

ARCTIC AND ALPINE ECOSYSTEMS . . . . . . . . . . . . . . . . . . . . .

109

8.1. Definitions and processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.1.1. Polar regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.1.2. Upland regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.1.3. Application of transfer factors and ecological half-lives
8.2. Radionuclide transfer in polar regions . . . . . . . . . . . . . . . . . . . .
8.2.1. Transfer to lichens . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.2.2. Transfer to reindeer . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.2.3. Transfer to ruminants . . . . . . . . . . . . . . . . . . . . . . . . . . .
8.3. Radionuclide transfer in alpine ecosystems . . . . . . . . . . . . . . . .
8.3.1. Soil to plant transfer in alpine ecosystems . . . . . . . . . . .
8.3.2. Transfer to ruminants in alpine ecosystems . . . . . . . . . .
8.4. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

109
110
110
111
111
111
112
113
114
114
115
115

RADIONUCLIDE TRANSFERS IN FRESHWATERECOSYSTEMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

117

9.1. Freshwater Kd values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.2. Transfer to freshwater biota . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.2.1. Concentration ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.3. Radionuclide partitioning into edible biotic tissues . . . . . . . . . .
9.3.1. Application of the specific activity model approach
to aquatic ecosystems . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.3.2. Parameters for radionuclide partitioning into edible
biotic tissues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9.4. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.

117
120
121
127
127
130
131

SPECIFIC ACTIVITY MODELS AND PARAMETER VALUESFOR TRITIUM, 14C AND 36Cl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

131

10.1. Tritium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.1.1. Release of HTO to air . . . . . . . . . . . . . . . . . . . . . . . . . .
10.1.2. Release of HTO to water bodies . . . . . . . . . . . . . . . . . .
10.2. Carbon-14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.2.1. Release of 14C to air . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.2.2. Release of 14C to water bodies . . . . . . . . . . . . . . . . . . . .
10.3. Chlorine-36 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10.4. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

132
132
138
139
139
141
141
144

11.

FOOD PROCESSING . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

144

11.1. Definitions and processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11.2. Processing factor values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
11.3. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

144
146
146

USE OF ANALOGUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

156

12.1. Analogue isotopes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.2. Analogue elements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.3. Analogue species . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.4. Other analogue approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12.5. Application of data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

157
157
158
159
159

APPENDIX I: REFERENCE INFORMATION ON TERRESTRIALPLANTS AND ANIMALS . . . . . . . . . . . . . . . . . . . . . . . .

163

APPENDIX II: PLANT GROUPS AND ASSOCIATED CROPS . . . . . .

168

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
CONTRIBUTORS TO DRAFTING AND REVIEW . . . . . . . . . . . . . . . . .

173
191

12.

1. INTRODUCTION
1.1. BACKGROUND
The impacts of planned discharges of radionuclides to the environment areassessed by means of mathematical models that approximate the transfer ofradionuclides through the compartments of the environment [1]. These models
can be used as tools to evaluate the effectiveness of countermeasures applied toreduce the impacts of accidental releases of radionuclides and to predict the
future impact of releases from underground waste repositories. In all theseapplications, the reliability of the predictions of the models depends on thequality of the data used to represent radionuclide transfer through theenvironment. Ideally, such data should be obtained by measurements made in theenvironment being assessed. However, this is often impracticable or overly
costly, and thus there is heavy reliance on data obtained from the literature. Oftensuch data can provide an estimate of the radiological impact of a planned releaseto satisfy regulatory requirements. Only when the estimated radiation doses tohumans approach nationally established regulatory limits is a more site specificapproach needed. Similarly, the potential impact of accidental releases and of
releases in the far future can usually be adequately assessed using such genericdata sets.
The International Atomic Energy Agency (IAEA) has for many years
supported efforts to develop models for radiological assessments [1, 2] and toassemble sets of transfer parameter data, and in 1994 it published a collection ofdata for estimating radionuclide transfer in the terrestrial and freshwater
environments (Technical Reports Series No. 364) [3]. The IAEA also published asimilar collection relevant to transfer in the marine environment, which was
updated in 2004 [4]. These data collections draw upon data from many countriesof the world and have come to be regarded as international reference values.
Since the publication of TRS-364 [3], new data sets have become available,
and an update of the report was considered appropriate. The present publication
supersedes TRS-364 [3] and includes considerably expanded information on
ecosystems other than temperate ecosystems, on radionuclides, and on processes
to be taken into account in the assessment of the radiation impact of radionuclide
discharges to the terrestrial and freshwater environments.
The data included here relate mainly to equilibrium conditions, that is, they
relate to the conditions where equilibrium has been established between the
movements of radionuclides into and out of the compartments of the environment.
Such a situation may exist during the controlled and continuous release ofradionuclides to the environment from a nuclear facility. In the case of short term1releases, as might occur in the event of an accident, equilibrium cannot beassumed, and the rate of transfer between compartments must be assumed to varywith time. Some data relevant to time dependent radionuclide transfer in theenvironment are also included in this publication, for example, data on weatheringand translocation for foliar uptake, on the long term dynamic of transfer factors forroot uptake, and on some processes in semi-natural ecosystems.
The data contained here are generally presented as ranges of observed
values; where the available data permit, mean values determined by statisticalmethods are also included. The statistical approach is described in Section 2. The
data can be used for various purposes, in particular:
(a)

(b)

To derive transfer parameters for screening purposes, that is, to evaluate, ina preliminary and approximate way, the radiological significance of aplanned environmental release. For this purpose, modelling assumptions
and data are chosen conservatively so that there is only a small probabilityof underestimation of detrimental environmental effects. If regulatory
targets are met by using this approach, then usually no further assessment isneeded. This is the approach described in Generic Models for Use in
Assessing the Impact of Discharges of Radioactive Substances to theEnvironment (IAEA Safety Reports Series No. 19) [1]. The conservativevalues of the transfer parameters used in that publication were mainly
obtained from the upper end of the ranges of data given in TRS-364 [3].
To obtain realistic estimates of the radiation dose to humans by using themean of the observed values and realistic modelling assumptions. However,it must be noted that generic data sets are no substitute for site specific datafor obtaining realistic estimates of radiation dose.

A specific task of the revision of TRS-364 [3] was to provide the transfer
parameter values that are the most commonly used in radiological assessment
models. However, some important details and recommendations on how to use
these parameters were omitted from TRS-364, which constrained its usefulness in
helping assessors to make appropriate choices of necessary transfer parameters.
Moreover, the data sets reviewed for the purpose of producing the present
publication are very extensive, and in some topic areas the tables contain only
summaries of the available data. Therefore this handbook is supported by theaccompanying TECDOC-1616 [5], which contains the full collection of thereviewed data and the methods used to obtain the tabulated data values. ThisTECDOC also gives necessary clarifications of how the tabulated values were
derived and provides radioecological concepts and models facilitating the use of
these values in specific situations.

21.2. OBJECTIVE
This publication is primarily intended to provide IAEA Member States withdata for use in the radiological assessment of routine discharges of radionuclides tothe environment. Some of the data may also be useful for assessing the impact ofaccidental releases and of releases in the far future.

1.3. SCOPE
This report covers radionuclide transfer in the terrestrial and freshwater
environments. The data collected here are relevant to the transfer of radionuclides
through food chains to humans and are not specifically addressed to radionuclidetransfers to non-human species. However, in many situations they are also
applicable for assessments of radionuclide transfer to non-human species. The
data relate mainly to equilibrium conditions, that is, conditions where equilibrium
has been established between the movements of radionuclides into and out of thecompartments of the environment. However, some data relevant to time dependentradionuclide transfer in the environment are also included.
The focus of this publication is on transfer parameter values; the models inwhich they are used generally are not described here. Typical models applied in
the context of the control of routine releases are described in Ref. [1].

1.4. STRUCTURE
This report consists of 12 sections and 2 appendices. Definitions and units,classifications used and necessary details of data analysis are given in Section 2.
The nine sections that follow provide data relevant to parameters for a range ofdifferent environmental transfer processes. Sections 3, 4 and 5 addresscontamination of plants, focusing on foliar uptake, mobility in soil and uptake fromsoil by plants, respectively. Section 6 considers radionuclide transfers toagricultural animal products. Parameters for modelling radionuclide transfer toproducts from semi-natural extensive ecosystems (forests, uplands and polar
ecosystems) are given in Sections 7 and 8. Section 9 is devoted to the transfer ofradionuclides to food products in freshwater ecosystems. For some radionuclides,
in particular for H, 14C and 36Cl, transfer parameters and models are normallyformulated in terms of specific activity concepts. Therefore, data for theseradionuclides were treated separately and are presented in Section 10. Section 11
gives information on the impact of different methods of food processing on
decontamination of food. Finally, the application of analogue approaches to filling3

data gaps is described in Section 12. The appendices provide reference information
applicable to one or more of the preceding sections. The accompanying TECDOC[5] is included on the CD-ROM at the end of this publication.

2. DEFINITIONS AND DATA ANALYSIS
2.1. BASIC DEFINITIONSGeneric quantities and units used throughout this publication are given in
Table 1. Generic quantities and terms are as defined in the International
Commission on Radiation Units and Measurements (ICRU) report on quantities
and units [6], as used by the IAEA, or are those in common usage. The definitionsof specific terms are also given in each section.

2.2. DATA ANALYSISInternational databases of bibliographical references, reports from scientificinstitutions and a number of relevant national databases were consulted to derivevalues for radionuclide transfer in the environment. Priority was given to datafrom original publications rather than to data from review sources, although thelatter were used in some cases.
In this publication, transfer parameters are normally given for dry weight.
When these parameters are expressed relative to fresh weight, the fresh weight/dry
weight conversion factors given in Appendix I have been applied.
The data presented here are derived from TECDOC-1616 on Quantificationof Radionuclide Transfers in Terrestrial and Freshwater Environments forRadiological Assessments [5], where the available data were analysed to (a)estimate a representative value for a given parameter and (b) obtain an indicationof the extent of uncertainty about this estimate. International databases ofbibliographical references and some national databases were consulted by using
relevant key words. Such bibliographical searches were limited to (a) publisheddocuments within the international scientific literature and, depending on theiraccessibility, (b) reports from different scientific institutions. Priority was given todata from original publications and all the information that they contained, rather
than to summaries of such information. During the second step, databases were
elaborated, where necessary (see Ref. [5] for details).

4

TABLE 1. GENERIC QUANTITIES AND UNITS USED IN THIS
PUBLICATION
SymbolNameDefinition

Unit

Foliar uptakeaInterception
coefficient

ftr

Translocation ratio, The mass activity density (Am, in Bq kg–1) in one
Dimensionless,translocation factor, tissue, typically an edible tissue, divided by the mass m2 kg–1
–1
translocation
activity density (Am, in Bq kg ) in another tissue ofcoefficient
the same plant or crop. The translocation ratio can becalculated as the mass activity density in the edible
tissue (Bq kg–1) divided by the activity contained on
the mass foliage covering a square metre of land
surface (Bq m–2).

Ks

Resuspension
factor

m–1
The ratio of the volumetric activity density (Av, in
Bq m–3) measured in air or water to the areal activity
density (A, in Bq m–2) measured on the soil orsediment surface.

Distribution
coefficient

The ratio of the mass activity density (Am, in Bq kg–1) L kg–1of the specified solid phase (usually on a dry mass
basis) to the volumetric activity density (Av, in
Bq L–1) of the specified liquid phase.

The ratio of the initial mass activity density on the
m2 kg–1
plant (Am, in Bq kg–1) to the unit area activity density(Ain Bq m–2) on the terrestrial surface (soil plus
vegetation).

Soil mobility
Kd

Soil to plant transfer
Fv

Concentration ratio The ratio of the activity concentration of radionuclide Dimensionlessin the plant (Bq kg–1 dm) to that in the soil (Bq kg–1
dm).

Herbage to animal transfer
F1

Absorbed fraction

The fraction of the intake by an animal that istransferred to a specified receptor tissue.

Fm , F f

Feed transfer
coefficientd kg–1 or d L–1,
The mass or volumetric activity density in thereceptor animal tissue or animal product (Bq kg–1
where d is the
fresh weight or Bq L–1) divided by the daily intake of time in days
–1
radionuclide (in Bq d ).

DimensionlessTransfer in semi-natural ecosystems
Tag

Aggregated transfer The ratio of the mass activity density (Bq kg–1) in a
m2 kg–1
factorspecified object to the unit area activity density (Aa, in
Bq m–2).

Transfer in freshwater ecosystems
CR

Concentration ratio, The ratio of the radionuclide concentration in the
Dimensionlesswater–biota
receptor biota tissue (fresh weight) from all exposure
pathways (including water, sediment andingestion/dietary pathways) mass relative to that inwater.

CRs-b

Concentration ratio,  The ratio of the concentration of a radionuclide in
sediment–biota
biota tissue (fresh weight) to that in the sediment(Csed) (fresh weight).

Dimensionless

5

TABLE 1. GENERIC QUANTITIES AND UNITS USED IN THIS
PUBLICATION (cont.)
SymbolNameDefinition

Unit

Specific activity approaches
CRs-a

Concentration ratio, The ratio of the tritiated water (HTO) concentration in Dimensionlesssoil water to air
soil water to that in air moisture.
moisture for HTO

Rp, RfPartition factor

CRaHTO, CRaOBT

Concentration ratio CRaHTO is the ratio of the total tritium concentration(HTO + OBT) in an animal product to the average
HTO concentration in the water taken in by the
animal via feed, drinking water and inhaled air.
CRaOBT is the ratio of the total tritium concentration in
the animal product to the average OBT concentrationin the animal’s feed.

Bq kg–1 fresh
weight/(Bq L–1)
for HTO intake;
Bq kg–1 fresh
weight/(Bq kg–1
dry weight) for
OBT intake

Fr

Food processing
retention factor

The ratio of the total amount of a radionuclide in agiven food item when ready for consumption to thetotal amount of the radionuclide in the original raw
food before processing and preparation.

Dimensionless

Pf

Processing factor

The ratio of the radionuclide activity concentration in Dimensionlessa given food item when ready for consumption to theactivity concentration before processing andpreparation.

Pe

Processing
efficiency

The ratio of the fresh weight of processed food to the Dimensionlessweight of the original raw material.

Rp for plants is the ratio of the concentration of non- Dimensionlessexchangeable organically bound tritium (OBT) in the
combustion water of plant dry matter to theconcentration of tissue free water tritium in plantleaves. Rf for fish is the ratio of OBT concentration in
the combustion water of fish dry matter to the HTO
concentration in fish flesh.

Food processing

Estimations of the transfer parameter values and the extent of uncertainty
about each such value were carried out by applying statistical analysis, where
possible. In the ideal case, where three or more values were available (N > 2), ageometric mean was given in the tables as the mean value. The uncertainties
assigned to the geometric mean were estimated by using the geometric standard
deviation. If only two values were available, the parameters were shown inreported ranges with minimum and maximum values, along with the arithmetic
mean and the standard deviation.
Thus, depending on the number of values used for the statistical analysis, themean given in the tables included here may be a geometric mean or an arithmetic
mean, with the corresponding uncertainties. The number of data is also reported.
In some cases, the values were given without a statement of uncertainty or a range,
because of the limited data available. The values in such cases should be used witha great caution.

6

2.3. TIME DEPENDENCE OF RADIONUCLIDE TRANSFER FACTORS
By definition, concentration ratios and aggregated transfer factors assume
that the activity concentration of the radionuclide in the organism is in equilibriumwith that in the relevant environmental medium (soil, sediment or water).
However, for many radionuclides, transfer to foodstuffs will change over time as aresult of changes in the extent of uptake due to soil fixation (‘ageing’) processes
and to migration of radionuclides into the soil profile and finally out of the rooting
zone. The rate of increase in the extent of radionuclide activity concentrations inanimal tissue will depend not only on ingestion quantities but also on the rate of
uptake and loss from tissues. Such changes over time in radionuclide activity
concentrations in environmental compartments are often termed biological or
ecological half-lives.
The biological half-life, T1bio, is a measure of the rate at which radionuclides/2
are excreted from an organism, and it is defined as the time required for a twofold
decrease of the radionuclide activity concentration in a given organ (or tissue)
resulting from the action of all possible factors except radioactive decay. For
example, if a sheep contaminated with radiocaesium is fed uncontaminated feed
for a period of time, the radiocaesium in the sheep’s body will decline at a rate
determined by the biological half-life. If the initial concentration of radionuclide in
the sheep is C(0), then after time t the activity concentration C(t) of radionuclide in
the body of sheep is given by:C(t) = C(0) exp[– (r + bio)t](1)

where λr is the radioactive decay constant and λbio is the rate of excretion of theradionuclide from the organism. Then, T1bio
can be calculated as:
/2

T1bio
/2 =

ln 2
l bio

(2)

In most cases, however, animals (or plants) remain in the contaminatedenvironment, ingesting contaminated food, so they continue to take inradionuclides. Thus, long term declines in activity concentrations in plants andanimals occur at rates slower than the biological half-life, being controlled by soil
‘ageing’ and redistribution processes. The long term, time dependent behaviourof radionuclides in the environment is often quantified using the ecological halflife, T1eco/ 2 , which is an integral parameter that lumps together all processes (except
radioactive decay) that cause a reduction of activity in a specific medium. The
processes involved in determining the value of the ecological half-life are specific7to the medium considered; for example, for the reduction of activity in game,losses of radionuclides from the root layer of the soil, fixation to soil particles anduptake by plants are the most relevant processes. Assuming that the decline inradioactivity concentration C from an initial concentration C(0) is exponential:

C (t ) = C (0) ◊ e - ( l r + leco )t(3)

The rate of decline, λeco, is related to the ecological half-life, T1eco, which/2
can be calculated as follows:

T1eco
/2 =

ln 2
l eco

(4)

If radioactive decay (characterized by physical half-life Tr) is included in
the reduction of the content or concentration of a particular radionuclide in asystem, then the effective ecological half-life T eff is given by:

1
T

eff

=

1
T

eco

+

1
Tr

(5)

Environmental compartments often exhibit declining parameter values (e.g.
Tag values, concentrations) that cannot be described by a single term exponentialfunction; often, two exponential models are needed to describe the data
adequately. The time dependence of the aggregated transfer coefficient (or any
other quantities, such as the radionuclide concentrations in some environmental
compartments) then can be expressed as:
ln 2
ln 2
Ê
- eff ◊t- eff ◊t ˆ
T1
T1
Tag (t ) = Tag (0) ◊ Á a1 ◊ e+ (1 - a1 ) ◊ e˜ÁË˜¯= Tag (0) ◊ e

ln 2
◊t
Tr

Ê
◊ Á a1 ◊ eÁËln 2- eco ◊tT1

+ (1 - a1 ) ◊ e

(6)
ln 2
- eco ◊t ˆ
T2

˜
˜¯

where T1eff is the fast loss component, T2eff is the slow loss component, Tag(0) is theinitial value of the aggregated transfer coefficient and a1 is the initial fraction ofthis coefficient associated with the fast loss term. The estimates for the fast loss
term depend on the definition of time zero, and care must be taken whencomparing results from different studies.

82.4. SOIL AND PLANT CLASSIFICATIONS
It is often possible to reduce the uncertainty in the estimate of the expectedvalue by categorizing parameters according to food type, soil group, type ofdeposition or environmental conditions. Where possible, this has been done inthis handbook; however, where data were few, or are not specified in sufficientdetail to permit such grouping, only general categories were used to derive atransfer parameter value.
The transfer of radionuclides through the food chain varies considerably,
depending on soil properties [7]. In the soil classification of the Food andAgriculture Organization of the United Nations (FAO)/United Nations
Educational, Scientific and Cultural Organization (UNESCO), there are 28 units
and 125 subunits [8]. Fv values are not available for all units or subunits, even forthe most extensively studied radionuclides. Therefore, a more broadly basedclassification is adopted here that permits some distinction on the basis of texture
and organic matter content, while ensuring that a reasonable amount of data isavailable for each category. For this handbook of parameter values, four soil
groups were defined: sand, loam, clay and organic (Table 2).
Soils were grouped according to the percentages of sand and clay in themineral matter, and the organic matter (OM) content in the soil. This defined the‘texture/OM’ criterion, which is similar to the criterion followed in TRS-364 [3].
For the mineral soils, the following three groups were created according to thepercentages of sand and clay in the mineral matter [9]: sand (sand fraction ≥65%,
clay fraction <18%), clay (clay fraction ≥35%) and loam (all other mineral soils).
A soil was included in the ‘organic’ group if the organic matter content was≥20%. Finally, an ‘unspecified’ soil group was created for soils without
characterization data, and for mineral soils with unknown sand and clay contents.
More details of the typical textures of the mineral soil classes are given in theaccompanying TECDOC [5].
TABLE 2. TYPICAL RANGES OF VALUES OF SELECTED SOIL
PARAMETERS FOR THE FOUR SOIL GROUPS
Soil group

pH

Organic
mattercontent(%)

Cationexchange
capacity(cmolc/kg)

Sand content in themineral matter fraction(%)

Clay content in themineral matter fraction
(%)

Sand

3.5–6.5

0.5–3.0

3.0–15.0

≥65

<18

Loam

4.0–6.0

2.0–6.5

5.0–25.0

65–82

18–35

Clay

5.0–8.0

3.5–10.0

20.0–70.0—≥35

Organic

3.0–5.0≥20

20.0–200.0

—

—

9

Based on the analyses of available information on radionuclide transfer toplants [5, 9, 10], 14 plant groups were identified (Table 3).
The individual plants assigned to these groups are shown in Appendix II;
plant compartments are shown in Table 3.

TABLE 3. PLANT GROUPS AND PLANT COMPARTMENTS
Plant group
Cereals

Plant compartment
Grains, seeds and pods
Stems and shoots

Maize

Grains, seeds and pods
Stems and shoots

Rice

Grains, seeds and pods
Stems and shoots

Leafy vegetables

LeavesNon-leafy vegetables

Fruits, heads, berries and buds

Leguminous vegetables

Grains, seeds and pods

Root crops

Roots

TubersTubersFruitsFruits, heads, berries and buds

Grasses (cultivated species)

Stems and shootsLeguminous fodder (cultivated species)

Stems and shoots

Pasture (species mixture — natural or cultivated)

Stems and shoots

Herbs

LeavesGrains, seeds and pods
Fruits, heads, berries and buds

Other crops

Grains, seeds and pods
LeavesStems and shoots
Fruits, heads, berries and buds
Roots
Tubers10

3. AGRICULTURAL ECOSYSTEMS: FOLIAR UPTAKE
The deposition of radionuclides on vegetation and soil represents thestarting point of their transfer in the terrestrial environment and in food chains.
There are two principal deposition processes for the removal of pollutants fromthe atmosphere: dry deposition is the direct transfer to and absorption of gases
and particles by natural surfaces such as vegetation, whereas wet deposition is thetransport of a substance from the atmosphere to the ground in snow, hail or rain.
Once deposited on vegetation, radionuclides are lost from plants due to removal
by wind and rain, either through leaching or by cuticular abrasion. The increaseof biomass during growth does not cause a loss of activity, but it does lead to adecrease of activity concentration due to effective dilution. There is also systemictransport (translocation) of radionuclides in the plant subsequent to foliar uptake,leading to the redistribution of a chemical substance deposited on the aerial partsof a plant to the other parts that have not been contaminated directly.

3.1. INTERCEPTION
3.1.1.

Definitions and parameters

There are several possible ways to quantify the interception of depositedradionuclides (see also Section 1). The simplest is the interception fraction, f(dimensionless), which is defined as the ratio of the activity initially retained by
the standing vegetation immediately subsequent to the deposition event, Ai, to thetotal activity deposited, At:
f =

Ai
At

(7)

The interception fraction is dependent on the stage of development of theplant. To take account of this, in some experiments and models the interception
fraction is normalized to the standing biomass B (kg m–2, dry mass). This quantity
is denoted as the mass interception fraction fB (m2 kg–1):

fB =

f
B

(8)

11

Since the leaf area represents the main interface between the atmosphereand the vegetation, the interception fraction is sometimes normalized to the leaf
area index, which is defined as the ratio of the (single sided) leaf area to the soil
area.
Chamberlain and Chadwick [11] defined the interception fraction (Eq. (7))
for dry deposition in terms of a dependence on the standing biomass and theempirically derived mass interception coefficient:f = 1 – exp (–a ·B)(9)

The mass interception fraction (Eq. (8)) is then derived to take into accountthe dependence of the interception fraction on the biomass using:fB =1 - exp( -a ◊ B)
B

(10)

For low density standing biomass, there is little difference between fB
and a.
3.1.2.

Interception fractions

The interception of radionuclides is the result of the interaction of various
factors, including the stage of development of the plant, the capacity of the
canopy to retain water, elemental properties of the radionuclide, and the amountof rain during a rainfall event and the intensity of the precipitation.
The interception of rain by vegetation is closely linked to the water storage
capacity of the plant canopy. The interception increases during a rainfall event
until the water storage capacity is reached and the weight of more rain overcomes
the surface tension holding the water on the plants.
Water storage capacity is quantified in terms of the thickness of the water
film (in millimetres) that covers the foliage. Since the capacity of the plant
canopy to retain water is limited, the interception fraction decreases in generalwith increasing amounts of rainfall in a rainfall event. The interception of aradionuclide deposited by wet deposition is controlled by the storage capacity ofwater and the interaction of the radionuclide with the leaf surface, which strongly
depends on the chemical form of the deposit.
The differences in interception between different elements are due to theirdifferent valences. As plant surfaces are negatively charged, they have theproperties of a cation exchanger. Therefore, the initial retention of anions such as
iodide is less than that of polyvalent cations, which seem to be effectively

12retained on the plant surface. More details on processes governing interception ofradionuclides by plants, including all available information sources, are given in
the accompanying TECDOC [5]; summaries of available interception fraction
values for wet and dry depositions are given in Tables 4 and 5, respectively.
TABLE 4.
INTERCEPTIONDEPOSITION
Element

Crop

Standing biomass(kg m–2)

FRACTION
Amount of
rainfall(mm)

VALUESInterception
fraction
(f)

FOR

Mass
interception
fraction(fB, m² kg–1)

Chernobyl deposits
Ba

Grass

1.7

Cs

Grass
Grass

0.7

Ru

Grass

0.48

1.1

Simulated rain

[16–18]

Be
Grass

1

3.2 ± 0.91

10

1.4 ± 0.86

1

4.3

2

1.6

4

1.1

1

7.6

2

5.1

4

4.8

1

6.2

Clover

8.7

Grass
Clover

4.1

Grass
Clover
Sr

2.5

Grass
Clover8.2

Grass
Clover

8.0

Grass
CloverPure waterb

8.2

Grass
Clover

11.1

Grass

2

4.3

4

1.8

8.5

1.8

Clover5.9

Grass
Clover
Be
Cd
Cr
Sr
Ce
S
I

¸
Ô
ÔÔ
˝
Ô
Ô
Ô˛

References[12–15]

n.a.a

I

I

WET

4.0
n.a.

[19]

1.8
Mean of 5
species

1.3
1.0
0.94
0.35
0.27

13

TABLE 4.
INTERCEPTIONDEPOSITION (cont.)
Element

Crop

Standing biomass(kg m–2)

Csc

Wheat

n.a.

Beans

Grass

n.a.

n.a.

FRACTIONVALUES

FOR

Amount of
rainfall(mm)

Interception
fraction(f)

Massinterception
fraction(fB, m² kg–1)

0.4
0.7

0.03d
0.074

1.4
3.5

1.5

0.029

1.4

4.4

0.024

1.2

8.9

0.014

0.5

0.34
0.68

0.059
0.031

2.1
1.1

1.4

0.039

1.4

4.1

0.01

0.4

8.2

0.013

0.5

0.45
0.9
1.8
5.4
10.8

0.18
0.21
0.11
0.036
0.027

4.6
5.5
2.8
0.9
0.7

0.48
0.79
0.88
0.87
0.94
0.94
0.34
0.83
0.93
0.88
0.84
0.45
0.16
0.59
0.77
0.83
0.87
0.18
0.67
0.82
0.86
0.86

6.0
2.1
0.95
0.84
0.55
0.49
17
6.6
2.1
1.2
1.1
0.71
30
19
7.8
5.6
3.0
16
15
9.3
5.9
5.2

Simulated very fine drizzle, no water run-off from the foliage
Mixture of
nuclidesRice

SoybeanChinesecabbage

Radish

a

0.079
0.39
0.93
1.04
1.7
1.9
0.021
0.13
0.44
0.74
0.79
0.63
0.005
0.032
0.10
0.15
0.29
0.011
0.044
0.089
0.15
0.17

n.a.: not available.
Retention of radionuclide free water.
Rainfall intensity: 4.4 mm h–1.
d
LAIF: Interception fraction per unit leaf area.
bc

14

0.03–0.04

WET

References[20][21–23]
[21]

[22]

[23]

[21]

TABLE 5. INTERCEPTION FRACTION VALUES FOR DRY DEPOSITION
Deposited material

Particlediameter (µm)

Lycodium spores

32

Crop

f or fB (m² kg–1), or (α) or ( fLAI)a(arithmetic mean ± SD)

Reference

Grass

3.1 ± 0.15 (α)[11]Wheat, dry

3.2 ± 0.5 (α)[11]Wheat, moist

9.6 ± 3.7 (α)[11]Quartz particles

44–88

Grass

2.7 ± 0.3 (α)[24]Sand particles

40–63

Grass, dry

0.44 ± 0.15 (α)[25]Grass, wet

0.88 ± 0.13 (α)[25]63–100

Grass, dry

0.23 ± 0.07 (α)[25]Grass, wet

0.69 ± 0.16 (α)[25]

100–200

Grass, dry

0.24 ± 0.07 (α)[25]Grass, wet

0.46 ± 0.11 (α)

[25]

Corn

3.6 ± 0.05 (α)[26]I vapourGrass

2.8 ± 0.14 (α)[26]

Pb vapour

Artificial grass

13 (α)[27]

3.5

Beans: 30 dc
45 dc
65 dc
85 dc

1–1.2 (α)
1.1 (α)0.85–0.93 (α)
0.3 (α)

[28]
[28]
[28]
[28]

3.5

Grass

Pu particles

Ba, Cs, Srb

1

Ba, Cs, Sr, Teb
Ba, Cs, Sr, Teb
Cs, Srb
Spherical porous
silica particles

Wheat

Cs, Sr[28]

f = 1 – exp(–0.316 · LAI )

[3]
[3]

0.71 ± 0.1 (f )

[29]

10

0.88 ± 0.07 (f )

[29]

18

0.88 ± 0.08 (f )

[29]

22

0.81 ± 0.23 (f )[29]

0.56 ± 0.29 (f )

[29]

4

Lettuce

Wheat

22

Uranium particles(wind tunnel)[28]

f = 0.85 · (1 – exp(–13.1 · B))d4
Spherical porous
silica particles

0.84 ± 0.06 ( f )3.27 ± 1.15 (α)

4

Wheat

22
0.82

0.65 ± 0.13 (f )[29]

1.6 (f )[30]

1.2 (f )[30]

Spruce(LAIe = 3.1)

0.97 (f )

[31]

Rice

0.04–0.12 (fLAI), n = 6

[32]

Wheat

0.05–0.09 (fLAI), n = 2[32]

Carrot0.1–0.3 (fLAI), n = 2[32]

Cabbage

0.18–0.2 (fLAI), n = 2[32]

Tomato0.08–0.9 (fLAI), n = 2

[32]

a

f : Interception fraction; fB: mass interception fraction.
Dissolution in rainwater after 2 h: Cs, Ba — 95%; Sr — 75%, Te — 8%.
Days after sowing.
d
B: Yield (kg m–2 dry mass).
e
LAI: Leaf area index.
bc

15

For dry deposition, particle size is the other key parameter. Interception ismore effective for small particles and reactive gases. Interception ofradionuclides deposited by wet depostion is a result of the complex interaction of
the chemical form of the element, the development of the plant and the amount of
rainfall. Rainfall intensity appears to be of minor importance in determining
interception.
3.1.3.

Application of data

For the interception of dry and wet deposits by vegetation, the developmentof the plant canopy is a key factor [18]. The biomass density or the leaf area index
may be used to quantify plant development. During vegetative growth, both
approaches are equally appropriate, whereas during the generative phase, the leaf
area index is a more suitable basis for interception modelling. In this phase, thebiomass increases whereas the leaf area declines. Variations in the degree ofinterception of both dry and wet deposits can be reduced if interception isnormalized to the standing biomass or to the leaf area index.
The existing data show that the interception of both dry and wet deposits
depends on the chemical form of the deposit and its interaction with the plantsurface and the canopy structure. Deeper knowledge of the processes involved
would considerably improve the predictive power of the models applied so far.
For wet deposits, the amount of rainfall is a key factor.
The values for , f, fB and fLAI have all been determined from single
experiments; before they are used, it should be checked whether the experimental
conditions are consistent with the conditions of the deposition underconsideration. The parameter f represents absolute interception, whereas  and fB
are normalized to the biomass and fLAI is normalized to the leaf area index;
therefore the variability of the last three parameters is less pronounced.
The interception of wet deposits decreases with increasing amounts ofrainfall, during which the deposition occurs. For wet deposits, this dependence on
rainfall is taken into account in the approach described by Müller and Pröhl (seeRef. [128]), who model the interception fraction for wet deposits as a function of:
the leaf area index, LAI; the storage capacity of the plant, S; an elementdependent factor, k, that quantifies the ability of the element to be attached to theleaves; and the total amount of rainfall, R, that falls during a single event:ln( 2 )
Ê LAI ◊ k ◊ S È◊R ˘ ˆ
f = min Á1;
Í1 - e 3◊k◊S ˙˜
R
ÍÎ
˙˚¯
Ë

16

(11)

For k, values of 0.5, 1 and 2 are assumed for anions (iodide, sulphate),monovalent cations (e.g. Cs) and polyvalent cations, respectively. For water
storage capacity, 0.2 mm is assumed for grass, cereals and corn, and 0.3 mm isassumed for all other crops.
For continuous depositions, the amount of rainfall per precipitation event isneeded. Such data are not readily available; an upper limit can be obtained by
dividing the total monthly rainfall by the number of days with precipitation>0.1 mm. Those values are given in climate statistics.
For continuous releases, average values for the standing biomass or for theleaf area indices should be applied for both dry and wet deposits. If the growth
function is for a specific crop at a specific site, the use of monthly averages forbiomass and leaf area index could be used.

3.2. WEATHERING
3.2.1.

Definitions and parameters

Weathering is the loss of material from leaf surfaces after wet or dry
deposition. In radioecological models, weathering is normally described by asingle exponential function characterized by a first-order rate constant, lw, or aweathering half-life, Tw:lw =3.2.2.

ln (2)
Tw(12)

Weathering half-lives

Results from numerous studies show limited differences between cationicspecies (Mn, Co, Sr, Ru, Cs) for most plant species, but also show that Tw values
are dependent on plant characteristics such as the plant growth stage at the time ofdeposition [33]. The available data, summarized based on information presented
in the accompanying TECDOC [5] for different elements and plant groups, aregiven in Table 6.

3.2.3.

Application of data

The magnitude of the weathering loss of a radionuclide depends on manyfactors, including its solubility, strength of adsorption to the plant surface, degree

17TABLE 6. WEATHERING HALF-LIVES OF SELECTED ELEMENTS AND
FOR GENERIC PLANT TYPESa (d) [12]Element

Plant group

N

Arithmetic mean

Minimum

Maximum

Cs

Cereal

1

35

Cs

Grass

4

10

7.9

11.1

I

Grass

9

13

8.3

29

I

Rice

1

14
12.8

49

Sr

Grass

4

24

Sr

Cereals

1

21

Mn-Ce

Cereals

1

30

Pu

Cereals

1

12

Pu

Fruits143aIncluding growth dilution.

of penetration into the inner flesh and ability to leach from the interior. Biologicalfactors such as the structure of the epidermis, plant senescence and defoliation,and shedding of old epicuticular wax also play a part in the weathering process. It
can be inferred that the highly complex interaction of these factors may be thecause of the observed differences in weathering loss among radionuclides, andamong plant species and their growth stages.

3.3. TRANSLOCATION
3.3.1.

Definitions and parameters

Translocation is the process leading to the redistribution of a chemical
substance deposited on the aerial parts of a plant to other parts that have not been
contaminated directly. Translocation factors have been defined differently bydifferent authors. Here, the translocation factor is defined as the ratio of theactivity, on a ground area basis, of the edible part of a crop at harvest time
(Bq m–²) to the foliage activity of the crop at the time of deposition (Bq m–²),
expressed as a percentage.
3.3.2.

Translocation

The direct contamination of plants by radionuclides or other elements andthe transfer of these contaminants from the foliage to edible parts of the plants
depend on many physical, chemical and biological factors [18, 34]. Physicalfactors include characteristics of the deposition regime, the contaminants (rain18duration, size of particles) and the plant (foliage layout, leaf size and cuticular
structure). Chemical factors include the speciation of the element watercomposition and cuticle composition [35–37]. Biological factors are mainly
associated with the vegetative cycle at the time of the foliar deposit [38–41].
Experimental protocols for measurement of translocation have not yet beenstandardized; hence they vary widely and results remain very heterogeneous. The
main contamination scenarios include:
(a)

(b)
(c)
(d)

Simulations of sprinkling irrigation of contaminated water or contaminatedrain at various timescales and intensities over the whole vegetation cover,with or without soil protection, followed or not by non-contaminated rain.
This operating mode is the most realistic for investigation purposes.
Sprays of contaminated solution over the foliage, followed or not, after
drying, by non-contaminated rain.
Foliar contamination by a deposit of dry or wet aerosols, followed or not,after drying, by non-contaminated rain.
Deposit of droplets over part or all of the plant foliage, with a view to detecting
translocation and mobility mechanisms within the plant. This method cannot
be used to determine a translocation factor as defined in this document.

Few authors specify the plant growth stage at the time of deposit. The data
given in this section were derived from the database with all available literature
information. More details on source data and data analysis, as well as a
description of the factors governing translocation, are given in the accompanying
TECDOC [5]. Translocation factor values, as defined above, for cereals, root
crops, tubers and fruits are presented in Tables 7–11.
TABLE 7. TRANSLOCATION FACTORS (ftr) FOR CAESIUM IN CEREALS(GRAIN) (%)
Plant growth stage

N

Mean

Minimum

Maximum

Wheat, barley and rye
Leaf development/tillering

21

0.6

0.06

7.9

Stem elongation

21

4.6

0.45

24.3

Earing/flowering

15

6.1

1.1

27.0

Grain growth

11

5.5

1.1

27.1

Ripening

11

2.7

1.1

7.7

1.2

3.4

Rice
Leaf development/tillering2

2.3

Stem elongation

1

4.3

Earing/flowering

1

8.4

Grain growth1

11

Ripening

1

2.2

19

TABLE 8. TRANSLOCATION FACTORS (ftr) FOR STRONTIUM IN
CEREALS (GRAIN) (%)
Plant growth stage

N

Mean

Minimum

Maximum

Wheat, barley and rye
Leaf development/tillering

2

0

0

Stem elongation

13

0.1

0.008

0
1.6

Earing/flowering

5

0.4

0.1

1.3

Grain growth

6

2.0

0.6

8.5

Ripening

8

1.2

0.3

5.1

0.021

0.024

Rice
Leaf development/tillering

2

0.02

Stem elongation

1

0.02

Earing/flowering

1

0.6

Grain growth1

1.3

Ripening

1

1

TABLE 9. TRANSLOCATION FACTORS (ftr) FOR OTHER ELEMENTS IN
CEREALS (GRAIN) (%)
Element

Plant growth stage

N

Mean

Minimum

Maximum

Wheat, barley and rye
MnCo

Leaf development/tillering

3

0.3

0.08

1.6

Stem elongation

8

2.1

0.21

10.7

Earing/flowering

6

2.3

0.47

12.7

Grain growth

6

2.0

0.46

8.6

Ripening

6

1.0

0.2

4.9

Leaf development/tillering

5

0.5

0.06

3.4

Stem elongation

3

1.0

0.24

4.6

Earing/flowering

4

2.0

0.3

18.0

Grain growth

4

2.8

0.3

29.0

Ripening

3

1.5

0.5

6.6

Zn

n.a.a

6

15.8

7.6

32

Fe

Leaf development/tillering

4

0.8

0.65

1.2

Stem elongation

3

1.0

0.57

1.5

Earing/flowering

3

1.9

1.3

2.6

Grain growth

3

2.7

1.0

7.5

Ripening

3

1.5

0.35

9.2

Ru

n.a.

8

0.11

0.04

1.18

Ce

Stem elongation

8

0.1

0.02

0.8

Grain growth

4

0.6

0.1

7.8

Ripening

4

1.3

0.3

6.0

20

TABLE 9. TRANSLOCATION FACTORS (ftr) FOR OTHER ELEMENTS IN
CEREALS (GRAIN) (%) (cont.)
Element

Plant growth stage

Sb

Leaf development/tillering

5

0.02

0.002

0.6

Stem elongation

3

0.1

0.034

1.0

Cd

N

Mean

Minimum

Maximum

Earing/flowering

3

1.2

0.3

5.2

Grain growth

3

2.2

1.0

7.5

Ripening

2

0.6

0.3

1.3

n.a.

6

0.7

0.025

3.8

Ba

n.a.

6

0.2

0.001

4.3

Hg

n.a.

6

0.5

0.01

8

Na

n.a.

6

2.0

0.17

7.0

Cr

n.a.

7

1.0

0.02

7.4

Be

n.a.

6

0.2

0.001

2.7

Pb

n.a.

3

2.0

0.2

8.2

0.04

0.052

0.06

0.2

0.005

0.006

Rice
Mn

Co

Ru

a

Leaf development/tillering

2

0.05

Stem elongation

1

0.03

Earing/flowering

1

0.6

Grain growth

1

1.6
0.7

Ripening

1

Leaf development/tillering2

0.2

Stem elongation

1

1.6

Earing/flowering

14Grain growth

1

6.6
0.8

Ripening

1

Leaf development/tillering

2

0.005

Stem elongation

1

0.02

Earing/flowering

1

0.12

Grain growth

1

0.38

Ripening

1

0.35

n.a.: not available.

3.3.3.

Application of data

The majority of the available data relate to caesium and strontium. Other
radionuclides have been insufficiently investigated, and it is difficult to obtainreliable values even for the most important plants.
Many radioecological models use values based on inadequately justified
extrapolations or chemical analogies. This method is arbitrary insofar as chemical
analogy refers only to the chemical properties of the elements; it does not, forexample, necessarily imply that the elements will behave similarly inside the21TABLE 10. TRANSLOCATION FACTORS (ftr) FOR ROOT VEGETABLES
AND TUBERSa (%)
Element

N

Mean

Minimum

Maximum

Cs

17

Sr

14

4.6

0.7

13.0

0.5

0.2

Mn

1.6

5

0.24

0.2

0.4

Co

5

8

4.9

12

Ru

5

0.15

0.1

0.4

Te

1

0.8

Ba

1

2.2

Cs

23

11.6

1.3

46.0

Sr

9

0.1

0.02

0.5

Root crops

TubersaPlant growth stages are not given; it can be assumed that the values are for mature vegetables.

TABLE 11. TRANSLOCATION FACTORS (ftr) FOR FRUITSa (%)
Element

Type of fruit

N

Mean

Minimum

Maximum

Cs

Apples, beans, grapes,
tomatoes, strawberries

53

4.6

0.1

29.0

Sr

Apples, beans, grapes,
tomatoes, strawberries

35

0.44

0.01

12.1

Ba

Beans

4

0.13

0.04

1.6

Zn

Tomatoes

2

4.3

2.6

7.0

Am

Beans

1

0.0005

Pu

Beans

1

0.0003aPlant growth stages are not given; it can be assumed that the values are for mature fruits.

plant, as has been shown for calcium and strontium [42], and for caesium,
potassium and rubidium [43]. Moreover, it does not take into account the various
physiological and physicochemical mechanisms inside the plant that govern thetranslocation processes.
Moreover, some authors do not make a distinction between plant types andrecommend a single default value, whatever the element and plant type. Data
given without a growth stage indication should be used with caution, as its
absence indicates a wide range of associated uncertainty.

22

3.4. RESUSPENSION
Resuspension occurs when the wind exerts a force exceeding the adherenceof particles to the surface material. The forces in action are the weight of theparticle, the adherence and the aerodynamic loads related to the flow of wind.
According to wind erosion models, three types of process are used to describe thedispersion of particular contaminants deposited on surface soil [44–46]: surface
creep, saltation and (re)suspension. Another process for resuspension is themixed effect of wind and rain on particle detachment. Rain splash transport ofsoil particles in windless conditions has been studied in detail. The overall resultof these studies is that the contribution of rain splash transport alone is small
compared with that of overland flow transport [47–49].
3.4.1.

Definitions and parameters

Resuspension is the process by which previously deposited radionuclides
are re-entrained into the atmosphere by the action of wind on soil and vegetation
surfaces. The resuspension factor K is the ratio of the volumetric air
concentration (Cv(t), Bq m–3) above the soil/vegetation surface to the initial
surface soil contamination (CS,0, Bq m–2):

K (t ) =C v (t )(m -1 )C S ,0(13)

The resuspension factor approach makes it possible to directly obtain theradionuclide concentration in the air.
3.4.2.

Resuspension factor

Resuspension of radionuclides from accidentally contaminated sites has
been documented with in situ measurements concerning plutonium and caesium
contamination from the Chernobyl accident. The characterization of resuspension
factors is a complicated task because of the number of processes involved. The
extent of the resuspension depends on the material (particle size, shape,adherence), the surface type (roughness, humidity), the time elapsed since
deposition and the intensity of soil processing.
As with measurements, resuspension models can be distinguishedaccording to the environmental context. It is recommended that models tested on
the data collected after the accident at Chernobyl be used in the context of
accidental releases to air. However, other types of model may be more

23

appropriate in other contexts, for example, in assessing the radiological impacts
of contaminated land at sites that currently or formerly handle(d) or process(ed)radioactive materials [50].
For rural conditions, the model suggested for use is that of Garland et al. [51]:Ks(t) = 1.2·10–6 t–1 (m–1)(14)

where t is the time in days since deposition.
In this and subsequent models discussed in this section, the model
formulations are not independent of the unit in which time is expressed.
Generally, time is given in days unless otherwise stated. Garland et al. [51]advised that this formula be applied to deposits older than 1 day.
For urban environments, the Linsley model [52] provided the best results in
the intercomparison exercises:

K s (t ) = 10 -6 exp( -0.01◊ t ) + 10 -9 (m -1 )(15)

This expression yields a resuspension factor that lies within the range of
those estimated in in situ experiments. However, it tends to overestimate shortterm concentrations and to underestimate the long term values. Moreover, theexponential decrease with time is difficult to justify because it is rarely measured
in experiments.
For arid and desert conditions, it is recommended that the model discussed
in Ref. [45] be used. This model gives values that are intermediate between thoseobserved for urban and rural environments in the long term. The model form is:

K s (t ) = 10 -6 exp( -0.15 t ) + 10 -9 (m -1 )(16)

In the first days and months that follow deposition, the value of theresuspension factor generally ranges between 10−5 m–1 in residential areas, onsites undergoing cleanup operations and on arid sites, and 10−6 m–1 on rural sites[46, 53, 54]. In humid or semi-humid climates, resuspension is generally more
important under urban conditions than in rural systems. However, this might not
be the case in desert or semi-desert environments. More details about processes
governing resuspension as well as main achievements in resuspension modellingare given in the accompanying TECDOC [5].
3.4.3.

Application of data

The values and models presented here are adapted for impact studies
focusing on the resuspension of radionuclides deposited accidentally in the24natural environment. The measurements carried out in the context of theChernobyl accident provide a relatively homogeneous base for estimating theresuspension factor. The order of magnitude established is suitable for theestimation of average values over long periods of time and in a large area.
Some of the data sources cited here are well established, and the parametervalues represent our best quantitative understanding of the processes considered.
However, before using any of these parameters, it is advisable to consult theoriginal publication(s) to ensure that the way the parameter values were originallyobtained is compatible with the way they are to be used in assessment
calculations. This is particularly important with regard to the consistent use of theunits in which individual parameters are expressed.

4. RADIONUCLIDE INTERACTION IN SOILS
4.1. CONCEPTS AND PROCESSES
4.1.1.

The solid-liquid distribution coefficient concept

Dissolved radionuclide ions can bind to solid surfaces by a number ofprocesses that are often classified under the broad term of sorption. The
behaviour and ultimate radiological impacts of radionuclides in soils are largely
controlled by their chemical form and speciation, which strongly affect theirmobility, the residence time within the soil rooting zone and uptake by biota.
The degree of radionuclide sorption on the solid phase is often quantified
using the solid-liquid distribution coefficient, Kd , which can be used when
making assessments of the overall mobility and likely residence times ofradionuclides in soils. Kd is the ratio of the concentration of radionuclide sorbed
on a specified solid phase to the radionuclide concentration in a specified liquid
phase [55]:Kd =activity concentration in solid phase Ê Bq kg -1 ˆ
(L kg -1 )activity concentrattion in liquid phase ÁË Bq L-1 ˜¯(17)The Kd approach takes no explicit account of sorption mechanisms but
assumes that the radionuclide on the solid phase is in equilibrium with theradionuclide in solution and that exchange between these phases is reversible.

25However, the time elapsed since the incorporation of the radionuclide in the soil
is known to affect the magnitude of Kd, since a fraction of the incorporated
radionuclide may become fixed by the solid phase (an aging effect related tosorption dynamics) [56, 57].
Kd values for specific radionuclides are commonly obtained from field andlaboratory studies. Since radionuclides in the field may have been present in thesoil for a long period of time (e.g. from atmospheric nuclear weapons testing orfrom the Chernobyl accident), Kd values determined in situ may be higher thanthose determined in short term laboratory experiments [55].
For some well studied radionuclides the influence of specific co-factors on
Kd values can be evaluated. Co-factors are soil properties involved in themechanisms responsible for radionuclide sorption [58–64], and they can be used
to group Kd values and can reduce the variability of these values when thegrouping is based on fundamental properties, such as soil texture and organic
matter. More details concerning the use of co-factors in Kd grouping are provided
in the the accompanying TECDOC [5].
4.1.2.

Vertical transfer of radionuclides in undisturbed soil profiles

The basic processes controlling the mobility of radionuclides (and othertrace elements) in soil include convective transport by flowing water, dispersion
caused by spatial variations of convection velocities, diffusive movement within
the fluid, and physicochemical interactions with the soil matrix. In addition toabiotic processes, soil fauna may contribute to the transport of radionuclides insoils [65], and their action under general conditions results in the dispersion ofradionuclides within the soil profile [66].
Two approaches are widely applied for modelling the migration ofradionuclides in soils:(1)(2)

The serial compartment model;
The convection-dispersion equation (CDE).

Results from the serial compartment models for describing verticalmigration in soil are generally expressed as migration rates (cm a–1). In contrast,
the CDE approach considers that the input of the radionuclide can beapproximated by a single pulse-like function. In this case, for a large time t, thefirst two moments of the depth distribution function are asymptoticallyapproximated by:E[z]  vs·t

26

(18)

var [z]  2·Ds·t(19)

where Ds is the effective (or apparent) dispersion coefficient (cm² a–1), and vs is
the convection velocity (cm a–1) [67]. The parameters vs and Ds are estimatedfrom the position of the peak concentration in soil, zM, and the distance, ∆z,between zM and the depth where the concentration reduces to approximately–
0.6 = 1/ e of its maximum:

vs =
Ds =

zM
t

( Dz ) 2
2t

(20)

(21)

Values of Ds and vs can be used in the CDE for a chosen time t to produce a
vertical profile of the radionuclide. In some cases, authors reported not only vsand Ds but also the migration rate, derived from the peak of the vertical
distribution (or half-depth, i.e. the soil depth above which 50% of the total
activity is present) at a given time t.
This migration rate is directly comparable with that resulting fromcompartment model calculations. Therefore, both kinds of migration rate may be
combined (see Table 16).
4.1.3.

Relationship between Kd and other parameters characterizing
radionuclide mobility

4.1.3.1. Relationship between Kd and vertical migration
In a porous medium such as soil, the radionuclide diffusion process differsfrom diffusion in free water. An effective diffusion coefficient, De(m2 s–1), should
therefore be defined. Only those pores that contribute to the transport of the
dissolved radionuclide species have to be considered, although in most cases(mainly when the relative saturation tends to 1, and for cationic radionuclides),the total porosity, , is an adequate approximation. In the case of radionuclides
with significant sorption, an apparent diffusion coefficient, Da (m2 s–1), can becalculated from the diffusion profile of the sample.

27

The apparent diffusion coefficient takes into account the retardation of theradionuclide due to interactions with the porous material:

Da =

De
f ret

(22)

where fret is the retardation factor. If we hypothesize a linear sorption pattern, witha constant Kd in the range of concentrations studied, fret can be defined as:

Ê rˆ
f ret = 1 + Á ˜ ◊ K d
Ëe¯

(23)

where r (kg m–3) is the dry bulk density of the soil.
If sorption of a radionuclide on soil is instantaneous, reversible andindependent of its concentration (i.e. the Kd concept applies), this process isreflected in the CDE model by the following relations of the model parameters ofa sorbing and a non-sorbing trace substance, respectively:

Ds =

D
f ret

(24)

vs =

vw
f ret

(25)

where Ds and vs are respectively the effective dispersion coefficient and theconvective velocity of the radionuclide showing sorption, D is the dispersion
coefficient of a non-sorbing trace substance, vw is the mean pore water velocity
and fret is the retardation factor.
4.1.3.2. Relationship between Kd and root uptake
Soil to plant radionuclide transfer is assessed by measuring the soil to planttransfer factor or concentration factor, Fv, defined as the ratio of the radionuclide
content in the plant (or in part of the plant) to that in the soil (Bq kg–1 dry weightplant tissue/Bq kg–1 dry weight soil). The concentration factor can be assumed tobe controlled mostly by root uptake, since other sources of plant contamination(i.e. foliar uptake, soil adhesion by resuspension) are often of less significance.

28

The radionuclide concentration in the plant, Cv, is assumed to be linearlycorrelated to the radionuclide level in the soil solution, Css. This relationship iscontrolled by the selectivity of the plant root system, represented by thebioaccumulation factor, Bp:
Cv = Css ·Bp(26)

where Bp refers to the radionuclide plant to soil solution ratio (Bq kg–1 dry weightplant tissue/Bq L–1 soil solution). The process of ion uptake from the soil solution to
the plant by its roots includes physiological aspects of the plant related to nutrient
uptake and selectivity, and depends on both the plant and the element considered.
Therefore, the soil solution–plant bioaccumulation factor is assumed to be
dependent on the concentrations of radionuclide competitive species in the soil
solution [68], as has been fully described for the K-Cs pair [69–71].
Concentrating on soil chemical factors, Css may be written as:
Css = Cs frev /Kd(27)

where Cs is the radionuclide concentration in the soil (Bq kg–1, dry weight soil)
and frev is the reversibly sorbed radionuclide fraction (dimensionless), which also
refers to the time dependent potential of the soil to fix the radionuclide to thesolid phase.
Combining these equations results in the following:
Fv = Cv /Cs = Css · Bp /Cs = frev Bp /Kd(28)

Attempts to correlate field data on Fv to any one of the parameters in
Eq. (28) should be made with caution and are rarely justified.
However, for a given radionuclide and in the medium term after thecontamination event, the reversibly sorbed fraction can be expected to bereasonably similar for a given set of soils, except when the set contains soils ofcontrasting properties (e.g. high clay content soils and peat soils) [72, 73]. In any
case, the range of variation will be much narrower than that of Kd. Therefore,
radionuclide availability may be quantified solely in terms of Kd.
To summarize, when comparing the concentration factors in the medium
term for a set of similar soils, Eq. (28) may be simplified as follows:
Fv = Bp /Kd

(29)

29

After a log transformation of this equation, the result is:log Fv = log Bp – log Kd(30)

The resulting log equation has been successfully used to predict
radiocaesium and radiostrontium transfer factors from Kd, both measured incontaminated soils and calculated from soil properties [70, 74]. For otherradionuclides — for example, actinides and transuranides — this approach may
not be valid and should be tested further.

4.2. SOLID-LIQUID DISTRIBUTION COEFFICIENT VALUESThe Kd values were classified on the basis of four main soil groups (sand,loam, clay and organic) defined according to the sand and clay mineralpercentages, referred to as the mineral matter, and the organic matter content in
the soil (see Section 2.4 for details).
Table 12 provides Kd values for selected radionuclides grouped according tothis criterion; Kd values for the same radionuclides are grouped according to cofactors in Table 13. Table 14 provides a compendium of Kd values for a large
number of elements, grouped according to the ‘texture/OM’ criterion [9].
Although the texture/OM criterion defines five soil groups, soil groups in
Tables 12–14 have been combined when differences between values were notstatistically significant. However, independent values for mineral and organicsoils are given in most cases.

4.3. VERTICAL MIGRATION IN UNDISTURBED SOIL PROFILES
The data compilation in Table 15 takes into account data from the literatureon the vertical migration of radionuclides in undisturbed meadow soils(agricultural and semi-natural) [75–77]. Most data refer to 137Cs and 90Sr fromfallout from the Chernobyl accident and weapons fallout. Other radionuclides arecovered in very few literature sources.
Values for deeper layers, derived by compartment models, are excluded
from this compilation because there is evidence that such data are artefacts andoverestimate the real velocities of radionuclides in soil [75] (for details, see theaccompanying TECDOC [5]). Table 16 gives values for the parameters of the
CDE model, mostly for radiocaesium and radiostrontium, derived fromundisturbed grassland soil profiles.
Text cont. on p. 37.

30

TABLE 12. Kd VALUES FOR SELECTED RADIONUCLIDES IN SOILSGROUPED ACCORDING TO THE TEXTURE/ORGANIC MATTER
CRITERION (L kg–1)
Element
Sr

Cs

Soil groupAll soils

2.2×10

6.4

4.0×10

2.4×103

Loam + clay +organic176

6.9×101

5.4

2.0

6.5×103All soils

469

1.2×103

7.0

4.3

3.8×1051142

5.3×10

5.8

9.6

227

2

3.7×10

3.6

3.9×10

3.8×1051082

2.7×10

6.8

4.3

9.5×1041782

2.0×10146

2

1.8×10Organic9

1.2×103All soils

46

1.9×10325

3

2.6×101052MineralOrganic
All soils

250

6.7×104–1

7.0×10

6.7×104

6.1

3.3×102

7.6×10310

1.8×101

2.5×105

3.5×101

2.5×105

1.8×101

8.0×104–2

5.8×102

–2

12
13

44
5.4

7.0×10

1.0×10

1.0×10

5.4×10211

3.2×10

3.3

8.5

5.8×102

All soils

612

1.5×10

9.4

2.0

7.0×103

Mineral39

1.1×102

8.1

2.0

2.7×103

Organic13

6.5×102

6.0

9.6

7.0×1031182

4.8×1016

2.0

1.0×105892

6.4×10

16

2.0

10

3

3.8×10

5.7

5.4×109.9×104

171

8.7×109.5

4.0

5.8×103642

2.8×10

7.0

3.0

7.2×103

Sand + loam

402

1.4×10

7.8

3.0

7.2×103

Clay + organic

20

9.8×1022.1

2.5×102

5.0×103All soils

92

9.5×10211

9.0×10–1

1.5×105

172

1.1×1023–1

2.8×10456

3

2.4×10

3.6

2

2.1×10

1.5×105

12

2

7.6

9.7

7.6×104

All soils
Sand + loam
Clay
Organic
All soils

Sand
Loam + clay
Organic
a

6.9

–1

5.2

196

Organic

Zn

7.3×10

3.5×104
1

1

MineralNi

6.5×103–1

4.0×1065

MineralCo

Maximum–1

Sand

All soils

Cd

5.9

Minimum

1

OrganicI1

5.2×10Loam + clay

Th

GSDa

Mean

255

Sand

U

N

7.0

5.6×10

1.0×1052

9.0×10

GSD: Geometric standard derivation.

31

TABLE 13. Kd VALUES FOR SELECTED RADIONUCLIDES FOR SOILSGROUPED ACCORDING TO THE CO-FACTOR CRITERION (L kg–1)
Element

Soil group

Sr

b

c

CEC /Mss <15
15<CEC/Mss<150
150<CEC/Mss<500
CEC/Mss>500

Cs

1.8×103
3.4×10472

2.4×10

4.1

6.2×10

9.5×10460

3

7.2×102.2×102

3.8×105

361

7.1×10

11–1

7.0×10

6.7×103

78

2

8.0

2.6

6.7×104

7.4×101

4.0

6.2×1031

1.0×105

6.5×10pH<511

1.3×103

15

1.8×10

5≤pH<826

3.3×103

8.0

1.3×1022.5×105pH≥8

6

3.1×102

7.1

3.5×101

3.2×104

6.1–2

5.7×101

–1

75

2.3

8.3

–1

60

9.0×10

1.0×10

3.4

6.0×10

5.4×10246

1

2.3×10

3.6

2.0

5.8×102191

1.5×10

3.5

2.0

2.5×102242

3.8×10

6.2

3.7

4.4×103

pH<5

21

1

1.2×10

4.7

2.0

1.5×102

5≤pH<6.550

1.9×103

5.2

2.9×101

9.9×104

pH≥6.526

4.6×103

4.2

5.5×102

1.0×105

101

1.4×102.2

3.0

4.8×101

11

1

4.2

7.0

pH<6.5

pH<5

pH<5

106

30
9
49
17

9.1

5.8×102

8.2×108.2
1.6×103
3

4.3×10

GSD: Geometric standard deviation.
CEC: Cation exchange capacity.
cMss: Sum of Ca and Mg concentrations in soil solution.
d
RIP: Radiocaesium interception potential.
eMean values are for mineral soils only.

32

8.1×101

pH≥6.5b2.0

3

5≤pH<6.5a

2.7×1021

7.3×102

pH≥6.5Zn

7.7×101.5

1.0×101

5≤pH<6.5e

3.2×101.1×1021

1.0×101

pH≥6.5

Ni

25

2

4.0

5.6

OM≥5

e

1.7×102.5

2.4

2≤OM<5Co

182

1.5×101

7.4×101OM<2e

2.2×10

4×10

3.2×102

pH≥7

Cd

28

2.4

Maximum47

5≤pH<7

e

1

–1

78

pH<5

I

4.2

Minimum

150<RIP<1000
RIP>2500

Th

25

GSDa

Mean

RIPd<150
1000<RIP<2500

U

N

3.1

1.1×1031

7.2×103–1

3.0×102

4.0×107.9

0.9×10

5.7

6.2

3.8

4.4×10

3.0×1042

1.5×105TABLE 14. Kd VALUES FOR RADIONUCLIDES IN SOILS GROUPEDACCORDING TO THE TEXTURE/ORGANIC MATTER CRITERION(L kg–1)
Element
Ac

Ag

Am

As
Ba
Be

Bi

Br

Ca

Ce

Cl
Cm
Cr

Cu

Dy
Fe

Soil groupb

All soils
MineralOrganic
All soils
MineralOrganic
All soils
Sand
Loam + clay
Organic
All soils
All soils
All soils
Mineralb
Organicb
All soils
MineralOrganicb
All soilsb
MineralOrganic
All soils
MineralOrganic
All soils
Sand
Loam + clay
Organicb
All soils
All soils
All soils
MineralOrganic
All soils
Sand + loam
Clay
Organic
All soils
All soils
Sand
Loam
Clay

N
4
3
1
9
5
2
62
17
32
13
7
1
5
3
1
6
4
1
4
3
1
34
33
1
11
3
7
1
22
18
31
23
6
11
3
2
4
2
23
4
12
4

Mean
3

1.7×101.2×103
5.4×103
3.8×102
1.4×102
9.7×103
2.6×103
1.0×103
4.3×103
2.5×103
5.5×102
4.0×10–1
9.9×102
6.3×102
3.0×103
4.8×102
3.5×102
1.5×103
5.5×101
4.0×101
1.8×1028
7
1.1×1021.2×103
4.0×102
1.8×103
3.0×103
3.0×10–1
9.3×103
4.0×101
1.8×101
1.6×102
5.3×102
2.7×1022.1×103
3.2×102
1.5×103
8.8×102
3.2×1028.9×102
1.6×103

GSDa

Minimum

Maximum

2.8
2.4
—
7.1
3.0
—
6.1
6.7
5.6
4.6
5.5
—
2.5
2.8
—
2.3
2.1
—
2.8
2.3
—
3.4
3.2
—
5.1
1.2
6.4
—
3.0
3.8
20
15
10
3.0
2.0
—
3.0
—
2.3
1.3
2.0
1.4

4.5×102
4.5×102—
3.6×101
3.6×101
4.4×103
5.0×101
6.7×101
5.0×101
2.1×1022.5×101—
2.4×1022.4×102—1.2×1021.2×102—
1.5×101
1.5×101—
7.0×10–1
7.0×10–1—
1.2×102
3.2×1021.2×102—
4.0×10–2
1.9×102
1.0
1.0
8.3
7.6×102
1.3×102
1.4×103
7.6×1028.2×1022.2×1022.2×102
2.9×1021.2×103

5.4×103
2.4×103—
1.5×104
7.0×102
1.5×104
1.1×105
3.7×104
4.8×104
1.1×105
3.0×103—
3.0×103
1.3×103—
1.5×103
6.7×102—
1.8×102
7.4×101—
1.1×1028.9×101—
2.0×104
4.9×102
2.0×104—
1.2
5.2×104
7.9×103
1.6×103
2.9×103
2.7×103
4.8×102
2.7×103
8.8×1022.1×103
4.9×103
4.2×1022.2×1032.2×103

For footnotes see p. 36.

33

TABLE 14. Kd VALUES FOR RADIONUCLIDES IN SOILS GROUPEDACCORDING TO THE TEXTURE/ORGANIC MATTER CRITERION(L kg–1) (cont.)
Element
Fe
Ga
H
Hf

Hg
Ho

In
Ir
K

La
Lu
Mg
Mn

Mo
Na
Nb

Np

P
Pa

Pb

Pd

34

Soil group
Organic
All soils
All soils
All soils
MineralOrganicb
All soils
All soilsb
MineralOrganic
All soils
All soils
All soils
Sand
Loam + clay
Organic
All soils
All soils
All soils
All soils
MineralOrganic
All soils
All soils
All soils
Sand
Loam + clay
Organicb
All soils
MineralOrganic
All soils
All soilsb
MineralOrganic
All soils
Sand
Loam + clay
Organic
All soils
MineralOrganicb

N
3
2
1
6
4
1
1
4
3
1
2
15
237
60
93
76
1
1
30
83
79
3
9
30
11
2
8
1
26
22
4
6
4
3
1
23
9
7
5
6
4
1

Mean
3

1.4×10
3.0×102
1.0×10–1
2.5×103
1.5×103
5.4×103
6.3×103
9.3×102
6.3×102
3.0×103
4.8×1023
1.3×101
3.4
2.2×101
1.9×101
5.3×103
5.1×103
3.8
1.2×103
1.3×103
1.6×102
4.0×101
3.4
1.5×103
1.7×1022.5×103
2.0×103
3.5×101
2.0×101
8.1×102
9.0×101
2.0×103
1.4×103
6.6×103
2.0×1032.2×102
1.3×104
2.5×103
1.8×102
1.4×102
6.7×102

GSDa

Minimum

Maximum

3.1
—
—
2.8
2.4
—
—
2.9
2.4
—
—
—
4.3
2.6
3.6
2.8
—
—
3.5
9.4
9.4
3.8
2.8
3.1
3.7
—
2.5
—
6.1
3.6
1.4
5.2
2.8
2.3
—
9.9
3.6
3.6
2.5
2.3
2.0
—

5.2×1022.8×102—
4.5×102
4.5×102——2.4×1022.4×102—2.4×1021
7.0×10–1
7.0×10–1
1.8
2.5
—
—
4.0×10–1
3.6×101
4.0×101
3.6×101
7
2.0×10–1
1.6×102
1.6×102
5.4×102—
1.3
1.3
5.0×102
9.0
5.4×102
5.4×102—2.5×101
2.5×101
3.6×103
8.8×102
5.5×101
5.5×101—

4.9×103
3.1×102—8.5×103
3.3×103——
3.0×103
1.3×103—
7.3×102
1.1×101
9.1×102
1.8×102
9.1×102
1.3×102——
4.5×101
7.9×104
7.9×104
4.9×102
1.3×102
2.6×101
8.4×103
1.9×1028.4×103—
1.2×103
1.2×1021.2×103
7.6×102
6.6×103
2.7×103—
1.3×105
1.3×103
1.3×105
1.0×104
6.7×102
2.7×102—TABLE 14. Kd VALUES FOR RADIONUCLIDES IN SOILS GROUPEDACCORDING TO THE TEXTURE/ORGANIC MATTER CRITERION(L kg–1) (cont.)
Element
Pm
Po

Pt
Pu

Ra

Rb

Rh
Ru

Sb

Sc
Se

Si

Sm

Sn

Ta

Soil groupAll soils
All soils
MineralOrganicb
All soils
All soils
Sand
Loam + clay
Organic
All soils
Sand + loam
Clay
Organic
All soilsb
MineralOrganic
All soils
All soils
Sand
Loam + clay
Organicb
All soils
Sand
Loam
Clay
Organic
All soils
All soils
Sand
Loam + clay
Organic
All soilsb
MineralOrganic
All soilsb
MineralOrganic
All soils
MineralOrganicb
All soils
MineralOrganicb

GSDa

Minimum

Maximum

2
44
43
1
15
62
11
37
6
51
39
6
2
4
3
1
12
15
3
7
1
152
19
92
18
3
2
172
15
134
2
4
3
1
4
3
1
12
4
1
5
4

2

4.5×102.1×102
1.9×102
6.6×103
2.4×101
7.4×102
4.0×102
1.1×103
7.6×1022.5×103
1.9×103
3.8×104
1.3×1032.1×102
1.4×102
6.7×102
4.0
2.7×102
3.6×101
4.0×102
6.6×104
6.2×101
1.7×101
6.1×101
1.4×102
7.5×101
2.1×103
2.0×102
5.6×101
2.2×102
1.0×103
1.3×1028.7×101
4.0×102
9.3×102
6.3×102
3.0×103
1.6×103
2.8×102
1.6×103
7.8×102
5.6×102

—
5.4
5.1
—
—
4.0
4.0
3.3
3.7
13
12
12
—
2.8
2.3
—
—
8.1
6.1
2.5
—
3.9
6.4
3.1
2.3
8.4
—
3.3
5.2
3.0
—
2.8
2.4
—
2.9
2.4
—
6.2
2.2
—
2.7
2.1

4.5×1021.2×101
1.2×101—
1.2×101
3.2×101
3.3×101
1.0×102
9.0×101
1.2×101
1.2×101
7.0×102
2.0×102
5.5×101
5.5×101—
6.0×10–1
5.0
5.0
8.2×101—
6.0×10–1
6.0×10–1
4.0
3.8×101
8.0
6.7×102
4.0
4.0
1.2×101
2.3×102
3.3×101
3.3×101—
2.4×1022.4×102—
1.3×102
1.3×102—2.4×1022.4×102

4.5×102
7.0×103
7.0×103—
8.3×101
9.6×103
6.9×103
9.6×103
3.0×103
9.5×105
1.2×105
9.5×105
2.4×103
6.7×102
2.7×102—
2.9×101
6.6×104
1.7×102
9.9×102—2.1×103
4.7×1022.1×103
6.1×102
5.4×102
3.5×1032.1×103
1.6×1032.1×103
1.8×103
4.0×102
1.8×102—
3.0×103
1.3×103—
3.1×104
6.7×102—
3.0×103
1.3×1031

3.0×103

—

—

—

N

Mean

For footnotes see p. 36.

35

TABLE 14. Kd VALUES FOR RADIONUCLIDES IN SOILS GROUPEDACCORDING TO THE TEXTURE/ORGANIC MATTER CRITERION(L kg–1) (cont.)
Element
Tb
Tc

Soil groupAll soils

N

Mean

2

All soils

6.0×1033

2.3×10

3

–1
–2

GSDa

Minimum

Maximum—

5.4×103

6.6×103

9.3

1.0×10–2

1.1×101–2

Mineral22

6.3×103.7

1.0×10Organic

11

3.1

2.9

9.2×10–1

1.1×101Te

All soils

2

4.8×102—

1.8×102

7.9×102Tm

All soils

1

3.3×102

—

—

—

V

All soils2

3.0×102—

1.8×102

4.1×102Y

All soils

7

4.7×101

4.0

1.0×101

3.8×1025

2.2×101

1.9

1.0×101

4.7×101

3.2×102—

2.6×102

3.8×102

2

MineralOrganic
Zr

a
b

2

1.2

1.0×104

All soils

11

4.1×10

21

2

Sand

4

3.2×101

162

6.0×102

Loam + clay

4

5.0×1032.1

2.2×103

1.0×104

Organic2

3.7×103—

2.3×101

7.3×103

GSD: Geometric standard deviation.
Kd value from TRS-364 [3].

TABLE 15. MIGRATION RATES (cm a–1) FOR 137Cs AND 90Sr IN
UNDISTURBED MEADOW SOIL PROFILES, DERIVED BY VARIOUS
CALCULATION METHODS
(calculation methods include compartment models, half-depth, repeated measurements, convection dispersion equation approaches)
GSDa

Minimum

Maximum

All soils
103
Sand
43
Loam
34
Clay
7
Organic
11
Unspecified
8
All soils
19
Sand
6
Loam
9
Clay
1
Organic1
Unspecified
2

Cs
0.31
0.23
0.35
0.17
0.82
1.07
0.28
0.30
0.30
0.20
0.30
0.19

2.7
1.9
2.5
1.9
3.2
3.0
2.0
2.6
1.8
—
—
2.9

0.07
0.08
0.07
0.08
0.14
0.38
0.09
0.09
0.09
—
—
0.09

10.0
1.2
2.0
0.6
8.7
10.0
0.85
0.85
0.50
—
—
0.40

Chernobyl fallout

All soils

16

90
Sr
0.48

2.0

0.12

1.54

Weapons fallout

All soils

12

0.80

1.6

0.46

1.36

Artificial contamination

All soils

24

0.89

2.5

0.20

9.50

Case study

Soil group

N

Mean/value
137

Chernobyl
fallout

Weapons
fallouta

GSD: Geometric standard deviation.

36

TABLE 16. PARAMETERS OF THE CONVECTION DISPERSIONEQUATION MODEL FOR 137Cs AND 90Sr FROM DIFFERENT SOURCES OF
CONTAMINATION
Case study
137

Cs

Parameter2–1

D (cm a )Chernobyl
fallout137

Cs

D (cm2 a–1)

Weapons
fallout137

Csv (cm a–1)

Chernobyl
fallout137

Csv (cm a–1)

Weapons
fallout

Soil group

N

Mean/value

GSDa

Minimum

Maximum

All soils

31

0.22

3.1

0.02

1.9

Sand

11

0.11

2.3

0.03

0.6

Loam

4

0.20

4.6

0.02

0.8

Organic

3

0.94

1.8

0.63

1.9

Unspecified 12

0.27

2.6

0.04

0.8

All soils

12

0.22

4.3

0.04

2.9

Sand

3

0.13

5.9

0.04

1.0
2.9

Loam

2

1.06

4.1

0.39

Organic

1

1.60

—

—

—

Unspecified

6

0.12

2.2

0.05

0.4

All soils

31

0.18

3.3

0.00

0.9

Sand

11

0.15

1.7

0.07

0.6

Loam

4

0.06

18

0.00

0.6

Organic

3

0.69

1.6

0.40

0.9

Unspecified 12

0.22

1.6

0.09

0.5

All soils

11

0.09

3.3

0.01

0.7

Sand

2

0.20

6.1

0.06

0.7
0.1

Loam

2

0.01

3.6

0.01

Organic

1

0.10

—

—

—

Unspecified

6

0.13

1.4

0.09

0.2

90

Sr

D (cm2 a–1)

All soils

10

0.38

2.9

0.05

1.73

Chernobyl falloutv (cm a–1)

All soils

10

0.22

2.2

0.06

0.92

106

Ds (cm2 a–1) All soils

105

2.6×10–1

2.7

vs (cm a–1)

55

3.5×10–1

3.1×10–1

2.9×10–1

2.7×10–1

8.4×10–1

4.7×10–1

6.8×10–1

8.4×10–1

Ru

125

Sb

110m

Ag

144

Ce

a

2

All soils–1

Ds (cm a ) All soils

87vs (cm a–1)

53

2

All soils–1

Ds (cm a ) All soils

10vs (cm a–1)

4

2

All soils–1

Ds (cm a ) All soils

4vs (cm a–1)

3

All soils

2.6×10–1

3.1×10–1

7.6×10

–1

3.0
3.5
10

GSD: Geometric standard deviation.

4.4. APPLICATION OF DATA
The data for Kd are from a variety of different sources; these include field
and laboratory experiments with various contamination sources, and references,mostly from 1990 onwards, including TRS-364 [3] and related reports, reviewed
papers, and ‘grey literature’ (PhD theses, reports).

37

Data originating from experiments using other materials (e.g. sediments,
pure soil phases such as clays or Fe–Mn–Al oxides, rock materials) or stableelements have not been considered. Data from radioisotopes of the sameradioelement have been pooled.
There are still evident gaps in Kd values for a large number of radionuclides
and soil types, which restricts the possibility of proposing expected values forindividual soil groups in most cases. When expected values are proposed, theymust be considered only as approximate values that are suitable for screening
purposes but not for specific risk assessments. For these gaps, the use ofanalogues (data on other elements or media such as pure soil phases or sediments)
can be considered, although such analogues must be used with care.
The wide ranges of Kd values obtained for similar soil and radionuclide
combinations arise both because of the inherent variability derived from grouping
the soils according to soil properties not directly related to the mechanisms
governing the soil–radionuclide interaction and because of the large number ofapproaches and contrasting experimental conditions used.
There is a need for information on the reversibility of sorption and on how
the sorption rate may change over time. The dynamics of the soil–radionuclide
interaction is especially significant for radionuclides such as radiostrontium andradiocaesium.
Soil–radionuclide interactions are governed by multiple factors that dependon the radionuclide and on various soil properties. As the quality and quantity ofthe mineral matter are among the key soil properties affecting sorption,
classification of Kd values according to soil groups based on soil texture andorganic matter content is a satisfactory approach to establish Kd values for a large
number of radionuclides. However, it is recommended that additional soil andradionuclide properties (co-factors) that govern soil–radionuclide interactions
also be considered to the extent possible.
The main soil parameters controlling the interaction should be measured
and monitored to improve the prediction of Kd, and they should also be included
in models of environmental decision support systems. Modellers can choose to
use the geometric mean values derived from soils grouped according to texture
and organic matter or, where available, according to other criteria such as specificsoil properties (cation exchange capacity, radiocaesium interception potential,
pH). Moreover, modellers and end users can also consider using existing single
and multiple correlations between soil properties and Kd, especially in those cases
where the mechanisms behind radionuclide interaction are well known.
Regarding vertical migration parameters, soil characteristics, including
texture composition, have a distinct influence on the migration behaviour ofradionuclides; thus they need to be considered in parameter selection.

38

Some studies have pointed out the time dependence of migration rates. The
fixation of radionuclides to soil components like clay minerals or humus takessome time, and migration rates tend to decrease with increasing time due toirreversible fixation of part of the radionuclide content.
The presence of hot particles can have a significant influence on the
migration velocity of radionuclides into the soil profile, as radionuclides
contained in hot particles are protected against leaching until they are released
from the particles by weathering (for details, see the accompanying
TECDOC [5]).
No data are currently available for v and D in tropical meadow soils. Only a
few values have been derived from Arctic soils and for subtropical climate
conditions. Therefore, at present it is not possible to give separate values fordifferent ecosystems, although distinct differences may exist in the ecologicalconditions driving vertical migration of radionuclides in soil.
Results from recent studies show that mathematical constraints exist thatcan lead to artefacts when compartment models are applied to describe vertical
distributions of radionuclides in soil profiles. In particular, the arbitrarily chosen
thickness of layers can yield unrealistic results. Therefore, literature values of
migration rates derived from compartment models should be considered as roughestimates that are valuable as a means to compare radionuclides in different soil
types but not as a first choice for predictive purposes. For the modelling ofvertical migration in undisturbed soils, reliance on CDE approaches or other
innovative calculation methods is strongly preferred, because these approaches
and methods offer a more realistic representation of the observed processes.

5. ROOT UPTAKE OF RADIONUCLIDES IN
AGRICULTURAL ECOSYSTEMSThe transfer of radionuclides along food chains has been studied
extensively over the past 50 years, following nuclear weapons testing, releases
from military sites and civilian uses of nuclear energy. Based on information fromthese studies, extensive databases of soil to plant transfer factors from theliterature worldwide were compiled to obtain the values and ranges included in
the tables presented here, while basic details of the data selection and processing
are given in the accompanying TECDOC [5].

39

5.1. DEFINITIONS AND PROCESSESThe transfer factor, Fv, for the uptake of any radionuclide from soil to plant isdefined as the ratio of the dry weight concentration in the plants to the dry weight
concentration in the specified soil layer. The dry weight concentration was used forall plants, with the exception of fruits (see Section 5.2.2.), in order to reduce
uncertainty. When the transfer factor (concentration ratio) values or the plant
concentrations reported in the literature were expressed relative to fresh weight, thefresh weight to dry weight conversion factors given in Appendix I were applied.
Fresh weight to dry weight ratios will vary somewhat around the adopted
values, making this an additional source of uncertainty in the data. In some cases,
foodstuff fresh weight is used in dose assessment calculations; in these situations,the fresh weight to dry weight conversion factors (see Appendix I) can be applied
to convert the dry weight based values given here.
In defining soil to plant transfer factors, this publication follows theInternational Union of Radioecologists (IUR) [10] standardization of rooting
depth. Thus, instead of the real rooting depth, a standardized soil layer is adopted.
All roots and all activity present in the actual rooting zone are assumed to bepresent in the standardized zone. For grass, this soil depth value is 10 cm; for allother crops (including fruit trees), it is 20 cm. When applying the transfer factors
presented here, estimates of the activity concentration in the standardized soil
layer should therefore be used.
Soil to plant transfer is influenced by several factors: the physicochemical
characteristics of the radionuclides, the form of the fallout or the waste, the timeafter fallout, soil properties, the type of crop, and the soil management practices[78, 79].
Different types of radioactive material in routine or accidental releases fromthe nuclear fuel cycle can be identified according to their mobility in soil–plantsystems [9, 79–84]. The transfer factor values given here apply to the soluble
form of radionuclides.
Radionuclides in the particulate state (usually oxides or carbonates) often
have low solubility [85, 86]. Leaching of 137Cs from fuel matrices can be asignificant factor affecting the bioavailability of the radionuclide over time after
deposition [85–88]. The recommended Fv values given here address the soluble
form of radionuclides. Information on 137Cs and 90Sr transfer to plants when fuelparticles are present in the environment is given elsewhere [9, 85–88].
The accumulation of radionuclides in farm crops varies considerably for
different soils [89, 90]. The difference in transfer factors to farm crops for different
soils may be one or two orders of magnitude. Soil properties that are likely to affectradionuclide transfer values include mineralogical and granulometric composition,organic matter content, pH and fertility [9, 79, 89–92].

40

The biological variability inherent in plants and distinctions between
different varieties and species are also a likely source of much of the variability intransfer factors. Other sources of the variability in transfer factor values are:(a) the chemical nature of the radionuclide; (b) variations in metabolic andbiochemical mechanisms of radionuclide uptake by plants; (c) detoxification
mechanisms; (d) hydrological conditions within the soil; and (e) plant available
concentrations in soil within the rhizosphere [5, 9, 78, 79, 90].
Soil fertility, the duration of the vegetative period and the character of theroot distribution in soil also influence radionuclide transfer factors. Radionuclide
accumulation across the root interface can vary among species by a factor of 100[93]. Radionuclides often transfer in greater concentrations to leaves and stems,
and in much lower concentrations to the generative parts of plants [5, 78, 93].
Cultivation of agricultural crops is based on the application of various
methods of soil processing, different doses and combinations of fertilizers,
irrigation in dry areas and drainage in boggy territories. Crop cultivation
technologies can change soil properties or lead to redistribution of radionuclides
in the root zone, and consequently change radionuclide accumulation in crops[9, 79, 94].
A decrease in the radionuclide content in farm crops over time is aphenomenon typically observed in agricultural ecosystems [79, 85–89, 94–96]. A
variety of processes are involved, including fixation to soil minerals,
incorporation by microorganisms and migration within the rooting zone [30]. As
a result, the biological availability of radionuclides for incorporation into foodchains is reduced. A detailed discussion of the properties and factors governing
root uptake of radionuclides is given in the accompanying TECDOC [5].

5.2. TEMPERATE ENVIRONMENTS
5.2.1.

Radionuclide transfer to plants

Over 1100 information sources on radionuclide transfer to plants intemperate environments were used in the development of this handbook,including books, journals, conference proceedings, institutional reports, andinternational and national databases including the IAEA’s Classification of Soil
Systems on the Basis of Transfer Factors of Radionuclides from Soil toReference Plants [9] and the IUR-1989 database [96] used in TRS-364 [3]. The
most extensive information obtained relates to cereals, vegetables and pasturegrasses. With respect to soil groups, most of the information found was for sandand loam soils. Information on organic soils was rather limited.

41

To minimize artefacts and misinterpretations, the recommendations given
in TRS-364 [3] have been retained and used for data selection. In particular, theserecommendations included the following:
(a)
(b)
(c)

Measures to ensure sufficient equilibrium between the radionuclide applied
and the corresponding stable nuclides present in the soil;
Application of fertilizers at rates used in routine agriculture;
Use of data from lysimeters or pot experiments only if other data areunavailable.

Soil to plant transfer factor values for the temperate environment are given
in Table 17. In comparison with TRS-364 [3], the present publication contains
many more data for radionuclide transfers to crops of various plant groups and forthe four different soil types used here; it also allows better differentiation betweensite specific contamination scenarios.
TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv)Element
Ag

Plant
group
Leafy
vegetables

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

LeavesAll

5

1.8×10–4

3.3

5.9×10–5

1.3×10–3

2

1.7×10–4–5

2.5×10–4

2.0×10–4–5

1.3×10–3–4–4

2.5×10

2.0×10–3

1.1×10–3

2.0×10–3

Sand
Loam

Non-leafy
vegetables
Root crops

Fruits, heads,
berries, buds
Roots

Grain

5

6.4×102

1.6×10–3

Loam

3

3.7×10–4

1.4

2.5×10–4

4.7×10–4

All

6

1.3×10–3

2.0

5.7×10–4

3.9×10–3

3

1.7×10

–3

2.4

–4

3.9×10–3

1.0×10–3–4

1.7×10–3

2.2×10–5–7

3.4×10–2

2.7×10–5–6

8.0×10–3–4

2.0×10

1.0×10–6

3.4×10–2

2.5×101

7.4×10–7

4.0×10–3

81.5

3.0×10–7

5.8×10–2

14.9

3.0×10–7

1.0×10–4

5.5–5

1.2×10–2–5

1.2×10–2

All
Sand

Stems andshoots
Maize

Stems andshoots

5.9×10

Sand

Loam
Cereals

5.0

All

Sand
Am

3

9.6×10

3
83
66

Loam

7

4.0×10Clay

9

1.6×10–5

Organic1

1.5×10–7All

5

7.9×10–5Sand1

5.8×10

–2

Clay

4

1.5×10–5

64

2.6×10–4

2.6×10

–4

All
Sand

64

2.3

6.8×10

1.7

5.7×10

11.0

7.4×10

4.1

2.7×102

5.5

1.1×101.1×10

Text continues on p. 63.

42

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Am

Ba

Be

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Leafy
vegetables

LeavesFruits, heads,
berries, buds

Leguminous
vegetables

Seeds andpods

Root crops

Roots

TubersTubersGrasses

Stems andshootsLeguminous
fodderStems andshoots

10
5
2
2
9
8
12
12
4
3
78
65
8
2
2
7
7
20
12
1
7
27
10
11
5
1
1

2.7×10–4
5.3×10–4
1.6×10–4
1.5×10–7
3.6×10–4
3.9×10–4
3.8×10–4
3.8×10–4
6.7×10–4
1.0×10–3
2.1×10–4
2.1×10–4
1.5×10–4
3.3×10–3
8.1×10–4
3.3×10–2
3.3×10–2
6.5×10–4
9.9×10–4
3.1×10–3
2.5×10–4
1.5×10–3
5.1×10–3
1.0×10–3
1.7×10–4
1.0×10–3
5.0×10–3

3.3
2.7

Non-leafy
vegetables

All
Sand
Loam
Organic
All
Sand
All
Sand
All
Sand
All
Sand
Loam
Clay
Organic
All
Sand
All
Sand
Loam
Clay
All
Sand
Loam
Clay
All
All
All

1

5.0×10–3

All
All
All
Sand
Loam
Organic
All
Sand
Loam
Organic
All

1
1
3
1
1
1
3
1
1
1
1

5.0×10–3
5.0×10–3
2.0
1.3
1.2
3.6
9.1×10–1
3.7×10–1
2.8×10–1
2.1
4.2×10–1

PastureStems andshoots

Cereals
Leafy
vegetables
Non-leafy
vegetables
Root crops
TubersGrasses

Grain
LeavesLeguminous
fodderStems andshootsPastureStems andshootsFruits, heads,
berries, buds
Roots
TubersStems andshootsMinimum

Maximum

9.0
9.0
2.7
2.5

4.0×10–5
1.7×10–4
6.0×10–5
1.3×10–4
2.3×10–5
2.3×10–5
2.2×10–5
2.2×10–5
2.0×10–4
7.3×10–4
1.1×10–5
1.1×10–5
1.1×10–5
9.0×10–5
2.1×10–5
4.2×10–4
4.2×10–4
1.8×10–4
1.9×10–4

1.5×10–3
1.5×10–3
4.1×10–4
2.3×10–4
1.9×10–3
1.9×10–3
7.9×10–4
7.9×10–4
1.7×10–3
1.7×10–3
3.4×10–2
3.4×10–2
4.7×10–3
6.5×10–3
1.6×10–3
2.6×10–1
2.6×10–1
3.1×10–3
2.9×10–3

1.4
4.1
2.6
5.0
2.2

1.8×10–4
1.0×10–4
1.3×10–3
5.3×10–4
1.0×10–4

4.8×10–4
4.8×10–2
2.9×10–2
2.0×10–2
3.0×10–4

1.3

1.2

3.6

1.0

2.8×10–1

2.1

5.0
5.5
2.6
2.6
2.4
1.6
6.0
5.5
9.0

For footnote see p. 62.

43

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ca

Plant
group
Cereals

Leguminous
vegetables
Cd

Cereals

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Stems andshoots

All

6

8.7

3.7

2.3

3.8×101

Leguminous
vegetables

Ce

3.0×101.2

2.5×10

3.8×101

3

2.6

1.1

2.3

2.9

All

6

2.0×101

3.7

5.9

7.5×101

Sand

3

6.5×101

1.2

5.3×101

7.5×101

Loam

3

6.2

1.0

5.9

6.5

All

11

8.8×10–1

2.7

1.4×10–1

2.×9

Sand

5

1.2

2.1

4.8×10–1

2.5

Loam

4

1.3

2.2

5.6×10–1

2.9

Clay

2

2.1×10–1

1.4×10–1

2.8×10–1

All

24

2.1

2.2

1.9×10–1

5.4

Sand

8

3.2

1.4

2.2

5.1

Loam

12

2.2

2.1

5.8×10–1

5.4

Clay

4

7.1×10–1

2.4

1.9×10–1

1.3

Grain

All

1

5.0×10–2

Stems andshoots

All

2

1.3

3.5×10–1

2.2

Sand

1

2.2

Clay

1

3.5×10–1

All1

2.7×10–1

2.7×10–1

8.0×10–2

4.6×10–1

Sand2

4.6×10

–1

Clay

1

8.0×10–2
3.7

2.4×10–4

2.0×10–2

2.6–3

2.0×10–2–4

7.0×10–3

4.1–4

2.8×10

6.0×10–3

Grain

Seeds andpods

TubersTubers

All

1

1.5

Cereals

Grain

All

20

3.1×10–3

5

1.1×10–2

2.8×10–3

1.6×10

–3
–4

Sand
Loam
Clay
Stems andshoots

44

3

1

Loam
Stems andshootsStems andshoots

Maize

Sand

1

7
6

3.3

2.0×10
2.4×10Organic1

8.0×10All

13

3.9×10–2

5.5

3.0×10–3

6.8×10–1

Sand4

2.8×10–1

2.5

8.0×10–2

6.8×10–1

Loam

6

7.0×10–3

2.4

7.0×10–3

6.0×10–2

Clay3

3.0×10–3

3.0

3.0×10–3

2.7×10–2–3

6.0×10–3

2.0×10–2

Leafy
vegetables

LeavesAll1

6.0×10Leguminous
vegetables

Seeds and
pods

All

2

1.3×10–2

Sand1

2.0×10

–2

Loam

1

6.0×10–3
6.0×10–3

Root crops

Roots

All

1

TubersTubersAll1

4.0×10–3

Grasses

Stems andshootsAll2

2.0×10–2

1.0×10–2

3.0×10–2

Loam2

2.0×10–2

1.0×10–2

3.0×10–2

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ce

Cm

Co

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Leguminous
fodderStems andleavesPastureStems andshoots

All
Loam
All
Sand
Loam
Clay
Organic
All
Sand
All
Sand
All
Sand
All
Sand
All
Sand
All
Sand
All
Sand
Loam
Clay
All
Sand
All
Sand
Loam
Clay
Organic
All
Sand
Loam
Clay
All
Sand
Loam
Clay
All
Sand
Loam

4
4
10
1
4
3
1
67
66
7
6
8
8
17
17
6
5
66
65
17
6
8
2
71
71
61
30
16
12
2
27
8
12
7
40
26
10
4
37
36
1

8.0×10–3
8.0×10–3
3.7×10–1
9.6×10–1
4.0×10–1
2.9×10–1
3.5
2.3×10–5
2.3×10–5
1.4×10–3
1.9×10–3
3.2×10–4
2.9×10–4
7.5×10–4
7.5×10–4
8.5×10–4
1.1×10–3
1.5×10–4
1.5×10–4
1.0×10–3
2.1×10–3
8.3×10–4
2.5×10–4
2.0×10–4
2.0×10–4
8.5×10–3
1.4×10–2
4.9×10–3
5.4×10–3
3.4×10–3
1.1×10–1
5.8×10–1
6.4×10–2
3.6×10–2
1.0×10–2
1.5×10–2
7.2×10–3
2.0×10–3
3.5×10–2
3.4×10–2
5.0×10–2

2.1
2.1
5.0

4.0×10–3
4.0×10–3
2.0×10–2

2.0×10–2
2.0×10–2
3.5

3.3
3.3

1.2×10–1
1.4×10–1

1.2
1.2

3.3
3.3
4.5
3.7
4.5
4.5
1.5
1.5
3.0
2.5
3.7
4.1
2.4
1.7
1.4

1.4×10–6
1.4×10–6
2.0×10–4
3.0×10–4
3.6×10–5
3.6×10–5
4.2×10–4
4.2×10–4
2.0×10–4
4.1×10–4
1.1×10–5
1.1×10–5
1.0×10–4
1.1×10–3
4.6×10–4
1.0×10–4
5.7×10–6
5.7×10–6
4.0×10–4
1.0×10–3
4.0×10–4
8.0×10–4
1.7×10–3
1.0×10–2
1.1×10–1
1.0×10–2
2.0×10–2
9.0×10–4
3.0×10–3
1.6×10–3
9.0×10–4
6.0×10–3
6.0×10–3

2.0×10–4
2.9×10–4
8.1×10–3
8.1×10–3
1.4×10–3
1.4×10–3
1.6×10–3
1.6×10–3
3.9×10–3
3.9×10–3
2.1×10–3
2.1×10–3
3.6×10–3
3.6×10–3
1.4×10–3
4.0×10–4
4.4×10–3
4.4×10–3
7.2×10–1
7.2×10–1
6.0×10–2
3.0×10–2
5.0×10–3
4.9
4.9
2.9×10–1
5.0×10–2
5.6×10–1
5.6×10–1
1.6×10–2
4.0×10–3
2.0×10–1
2.0×10–1

Cereals

Grain

Leafy
vegetables

LeavesNon-leafy
vegetables

Fruits, heads,
berries, buds

Leguminous
vegetables

Seeds andpods

Root crops

Roots

TubersTubersPastureStems andshoots

Maize

Stems andshoots

Cereals

Grain

Stems andshoots

Maize

Grain

Stems andshoots

5.0
5.0
5.5
6.0
5.0
4.1
5.0
4.1
3.3
1.4
4.1
4.5
1.9
2.0
2.2
2.2

For footnote see p. 62.

45

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Co

Plant
group
Leafy
vegetables

Non-leafy
vegetables
Leguminous
vegetables

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

LeavesAll

185

1.7×10–1

2.7

1.3×10–2

1.0

Sand

66

2.5×10–1

2.4

1.7×10–2

1.0

Loam

85

1.5×10–1

2.5

1.8×10–2

8.6×10–1

Fruits, heads,
berries, buds
Seeds and
pods

Clay

33

9.7×10–2

3.0

1.3×10–2

6.9×10–1

All

7

1.4×10–1

1.6

5.7×10–2

2.3×10–1

Sand2

1.4×10–1

5.7×10–2

2.3×10–1

Clay4

1.6×10–1

1.2

1.3×10–1

1.9×10–1

105

3.6×10

–2

2.3

–3

5.0×10–1

5.7×10–2–2

5.0×10–1

2.8×10–2–3

2.2×10–1

2.2×10–2–3

5.3×10–2

–1

–2

All
Sand
Loam
Clay

Root crops

Roots

LeavesTubersLeguminous
fodderPastureStems andshootsStems andshootsStems andshoots

5.0×101.9

6.0×101.1×10

2.2

4.7×107.2×10–1

7

1.4×10–1

2.7

5.5×10–2

7.2×10–1

Loam

4

6.5×10–2

1.4

4.7×10–2

9.9×10–2

Clay2

1.0×10–1

1.0×10–1

1.0×10–1

2

2.4×10–1

2.4×10–1

2.4×10–1

2.4×10–1

2.4×10–1

2.4×10–1

5.4×10–2–2

6.7×10–1

8.0×10–2–2

6.7×10–1

–2

–2

All
All

2
56
39

3.0

1.0×10

3.0

1.1×10Loam

11

2.1×101.7

1.0×10

6.3×10–2

Clay5

2.2×10–2

2.0

1.2×10–2

7.0×10–2

All

4

7.7×10–2

2.2

4.0×10–2

1.7×10–1

Sand1

1.3×10–1

Loam1

1.7×10–1

Clay2

4.0×10–2

4.0×10–2

4.0×10–2

38

6.6×10–2–3

7.2×10–1

1.4×10–1–2

7.2×10–1

–2

–3

All
Sand

15

3.3

1.0×10

2.2

4.4×10Loam

10

2.9×10

6.0

1.0×10

1.8×10–1

Clay9

6.9×10–2

1.5

3.7×10–2

1.2×10–1

Organic4

2.8×10–2

1.6

1.9×10–2

5.3×10–2

All

88

4.5×10–2

3.7

2.1×10–3

8.4×10–1

49

8.6×10

–2

3.0

–2

8.4×10–1

1.7×10–2–3

1.3×10–1

1.3×10–1–2

1.7×10–1

–4

Sand
Clay

46

2.3

14

Loam
Cr

22

2.2×10

Sand

Sand

Grasses

40

2.1

All

Clay
Tubers43

5.0×1036
2

Cereals

Grain

All

1

2.0×10

Leafy
vegetables

LeavesAll1

1.0×10–3

Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

1.0×10–3

Root crops

Roots

All

1

1.0×10–3

TubersTubersAll1

5.0×10–4

1.4×10

2.7
6.4×102.1×10–2

8.0×10TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

All

1

2.0×10–3

Cr

PastureStems andshoots

Cs

Cereals

Grain

470

2.9×10–2

4.1

2.0×10–4

9.0×10–1

156

3.9×10–2

3.3

2.0×10–3

6.6×10–1

158

2.0×10

–2

4.1

–4

2.0×10–1

1.1×10–2–4

9.0×10–2

4.3×10–2–2

7.3×10–1–1–3

Organic

Grain

1.5×10

5.0

4.3×10

3.7

2.1×10–1

3.3

4.1×10–2

1.9

Loam

36

1.1×10–1

4.5

6.5×10–3

1.5

Clay

37

5.6×10–2

3.7

4.3×10–3

5.3×10–1

All

67

3.3×10–2

3.0

3.0×10–3

2.6×10–1

47

4.9×10

–2

2.4

–3

2.6×10–1

1.6×10–2–3

7.0×10–2

1.2×10–2–3

7.0×10–2

7.3×10–2–3

4.9×10–1

–1

–2

All

Roots

3.0

3.0×10
3.0×1077

1.0×102.3

1.4×10

4.9×10–1

1.5×10–2

2.5

3.0×10–3

5.2×10–2

Clay11

2.2×10–2

2.1

7.8×10–3

6.0×10–2

Organic3

1.4×10–1

1.3

1.0×10–1

1.6×10–1

290

6.0×10

–2

6.0

–4

9.8×10–1

1.2×10–1–3

9.8×10–1

7.4×10–2–4

7.3×10–1

1.8×10–2–4

7.2×10–1

–2

–3

All

96
119
67

4.1
5.0
6.7

3.0×102.1×10
3.0×10
5.0×10Organic7

2.3×10

7.4

4.0×10

4.6×10–1

All38

2.1×10–2

4.1

7.0×10–4

7.3×10–1

Sand

17

3.5×10–2

4.1

1.2×10–2

7.3×10–1

Loam

5

3.3×10–2

5.5

6.3×10–3

3.0×10–1

14

9.1×10

–3

2.2

–4

1.6×10–2

4.0×10–2–3

7.1×10–1

8.7×10–2–3

7.1×10–1

2.0×10–2–3

4.2×10–1

–2

–3

All
Sand
Loam

Root crops

101

3.3

3.2×1010

ClaySeeds and
pods

11

2.7

Loam

Clay

Leguminous
vegetables

14

8.0×10Sand

Sand

Fruits, heads,
berries, buds

1.0×1035

Loam

Non-leafy
vegetables

2.7

2.0×10130

Clay

Leaves

28

2.7

All

Loam

Leafy
vegetables

110

8.0×10Sand

Sand

Stems andshootsMaximum

All

Clay

Maize

Minimum

Sand
Loam

Stems andshoots

GSD/
SDa

126
66
42

3.7
2.5
3.3

7.0×10
1.0×10
3.5×10
1.0×10Clay

18

1.3×10

3.0

2.0×108.1×10–2

All

81

4.2×10–2

3.0

1.0×10–3

8.8×10–1

Sand37

6.2×10–2

2.5

8.0×10–3

4.0×10–1

Loam

21

3.0×10–2

3.7

1.0×10–3

1.6×10–1

Clay17

2.4×10–2

2.2

5.0×10–3

6.0×10–2

5

–2

5.0

–2

8.8×10–1

Organic

5.9×10

1.6×10For footnote see p. 62.

47

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Cs

Plant
group
Root crops

Plantcompartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

LeavesAll

12

3.5×10–2

3.0

6.0×10–3

4.5×10–1

3

1.1×10

–1

3.3

–2

4.5×10–1

2.6×10–2–3

4.3×10–2

2.6×10–2–3

4.7×10–2

5.6×10–2–3

6.0×10–1

9.3×10–2–3

6.0×10–1

3.5×10–2–3

1.4×10–1

2.5×10–2–3

9.0×10–2

–2

–2

Sand
Loam
Clay
TubersTubers

All
Sand
Loam
Clay

Grasses

Stems andshootsPastureHerbs

Stems andshootsStems andleaves

138
69
40
21

3.0
3.0
2.3
2.2

6.0×10
4.0×10
4.0×10
4.8×10
5.0×107

5.8×10

3.7

1.6×10

5.4×10–1

64

6.3×10–2

36.6

4.8×10–3

9.9×10–1

Sand

41

8.4×10–2

3.3

1.0×10–2

9.9×10–1

Loam

10

4.8×10–2

2.3

1.2×10–2

2.1×10–1

9

1.2×10

–2

2.1

–3

4.3×10–2

2.8×10–1–1

3.4×10–1

–1

–2

4

1.2

4.8×102.1×10All

85

1.6×103.3

1.0×10

1.8

Sand

29

2.4×10–1

3.7

1.8×10–2

1.8

Loam

51

1.5×10–1

3.0

1.0×10–2

1.2

Clay

4

4.6×10–2

4.1

1.3×10–2

3.0×10–1

All

401

2.5×10–1

4.1

1.0×10–2

5.0

Sand

169

2.9×10–1

4.1

1.0×10–2

4.8

Loam

124

1.9×10–1

4.1

1.0×10–2

2.6

Clay

75

1.8×10–1

3.7

1.0×10–2

1.2

Organic

31

7.6×10–1

2.2

3.0×10–1

5.0

All

4

6.6×10–2

14.9

4.8×10–3

2.8

4.5

3.6×10–2

2.2

2.2×10–1

3.5×10–1

3.0×10–1

4.8×10–1

Other cropsAll

9

3.1×10–1

Cu

Not specified

All

1

0.8

Fe

Cereals48

2.1

Organic

Organic
Stems andshoots7

9.0×10All

ClayLeguminous
fodder2

5.1×10

Grain

All

1

2.0×10–4

Stems andshootsAll1

2.9×10–1

Leafy
vegetables

LeavesAll1

1.0×10–3

Non-leafy
vegetables

Fruits, heads,
berries, buds

All3

1.0×10–3

Leguminous
vegetables

Stems andshootsAll1

3.7×10–1

Root crops

Roots

All

1

1.0×10–3

TubersTubersAll1

5.0×10–4

PastureStems andshootsAll1

2.0×10–3

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element

Plant
group
Cereals

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Grain

All
Sand
Loam
Clay
All

13
2
5
6
16

6.3×10–4
5.8×10–3
3.6×10–4
5.7×10–4
5.2×10–2

2.3

Sand

2
7

Stems andshootsLoam
Leafy
vegetables

K

La

LeavesMinimum

Maximum

1.0×10–4
1.0×10–3
1.0×10–4
2.0×10–4
7.0×10–3

1.1×10–2
1.1×10–2
1.2×10–3
1.6×10–3
7.5×10–1

4.3×10–1

1.1×10–1

7.5×10–1

3.6×10–2–3

2.0×10–1

–2

2.5

–2

1.0×10

1.9×10–1

3.7

1.1×10–3

1.0×10–1

1.9

1.1×10–3
1.6×10–3

8.0×10–3
1.3×10–2

2.0×10–4
3.3×10–3
3.0×10–4
2.0×10–4

1.4×10–1
3.7×10–3
7.0×10–4
3.0×10–4

Clay7

4.5×10

All
Sand
Loam
Clay

12
1
8
2

6.5×10–3
4.0×10–2
4.1×10–3
4.6×10–3

2.5
2.3
3.3
3.3

7.0×10Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

1.0×10–1

Leguminous
vegetables

Seeds and
pods

All
Sand
Loam
Clay

23
2
3
2

8.5×10–3
3.5×10–3
4.4×10–4
2.5×10–4

7.4

3.0
1.5
2.1
3.0

1.4×10–3
1.2×10–2
1.5×10–3
1.4×10–3

4.7×10–2
4.7×10–2
1.6×10–2
2.8×10–2

6.0
2.1

9.0×10–4
9.0×10–4
8.4×10–3

5.0×10–1
8.5×10–3
9.0×10–3

7.3×10–1

7.4×10–1

Root crops

Roots

All
Sand
Loam
Clay

28
9
12
7

7.7×10–3
2.3×10–2
4.7×10–3
4.5×10–3

TubersTubersAll1

1.0×10–1

PastureStems andshoots

All
Sand
Clay

12
9
2

3.7×10–3
1.8×10–3
8.7×10–3

Cereals

Grain

All

2

7.4×10–1

1.5–1

Stems andshoots

All

2

1.1

9.3×10

1.2

Leafy
vegetables

Leaves

All

2

1.3

1.2

1.3

PastureStems andshootsAll1

7.3×10–1

Cereals

Grain

All

1

2.0×10–5

Maize

Stems andshootsAll2

8.8×10–5

7.6×10–5

9.9×10–5

Leafy
vegetables

LeavesAll7

5.7×10–3

1.1×10–3

1.5×10–2

Non-leafy
vegetables

Fruits, heads,
berries, buds

All2

6.0×10–3

5.9×10–3

6.0×10–3

Leguminous
vegetables

Seeds and
pods

All

4

4.2×10–4

3.0

1.6×10–4

1.8×10–3

Root crops

Roots

All

9

1.6×10–3

2.7

4.5×10–4

6.0×10–3

2.7

For footnote see p. 62.

49

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
La

Mn

Plant
group
TubersPlant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

TubersAll

8

3.9×10–4

3.7

7.0×10–5

4.0×10–3

–5

2.3

–6

6.0×10

4.7×10–5

Grasses

Stems andshootsAll

4

1.8×10

PastureStems andshootsAll1

2.0×10–2

Cereals

Grain

All

78

2.8×10–1

3.3

1.4×10–2

2.7

Sand

33

3.4×10–1

3.3

1.4×10–2

2.7

Loam

22

2.0×10–1

2.6

5.6×10–2

1.1

Clay

15

2.2×10–1

4.1

2.4×10–2

1.0

Organic

66.5×10–1

2.1

2.7×10–1

1.7

All

30

2.2

4.1

2.0×10–1

2.7×101

Sand

9

9.0

1.9

4.8

2.7×101

Stems andshoots

Maize

Grain

Loam

16

1.2

3.0

2.0×10Clay

5

9.8×10–1

4.1

2.0×10–1

8.3

All

19

7.5×10–2

2.1

1.8×10–2

3.0×10–1

LeavesNon-leafy
vegetables

Fruits, heads,
berries, buds

Leguminous
vegetables

Seeds andpods

Root crops

TubersRoots

Tubers7

1.4×10–1

1.8

6.4×10–2

3.0×10–1

Loam

9

5.6×10–2

1.6

3.1×10–2

1.1×10–1

3

4.5×10

–2

2.4

–2

9.9×10–2

–1

–2

50

Stems andshoots

1.8×10All

103

4.1×102.4

5.2×10

3.0

Sand

35

8.5×10–1

1.8

2.5×10–1

3.0

Loam

49

3.4×10–1

1.9

7.4×10–2

1.0

Clay

18

1.7×10–1

2.3

5.2×10–2

7.7×10–1

All3

3.1×10–1

4.1

1.0×10–1

1.5
2.8

All

92

2.2×10–1

2.5

2.2×10–2

Sand37

5.0×10–1

1.9

1.6×10–1

2.8

Loam

43

1.4×10–1

1.6

5.0×10–2

3.4×10–1

Clay12

7.8×10–2

2.3

2.2×10–2

6.0×10–1

All

13

4.2×10

–1

5.5

–2

1.5×10

Sand

8

1.3

2.4

3.9×10–1

3.9

Loam

4

6.7×10–2

3.7

1.5×10–2

3.1×10–1

3.9

All

23

4.7×10–2

2.2

1.2×10–2

3.0×10–1

Sand

9

8.1×10–2

2.2

2.6×10–2

3.0×10–1

Loam

9

3.6×10–2

1.6

1.6×10–2

7.6×10–2

4

–2

2.2

–2

7.3×10–2–1

1.2×101–1

1.2×101–1

Clay
Leguminous
fodder

6.2

Sand
Clay
Leafy
vegetables

–1

All
Sand

32
15

2.4×10
1.5
2.7

3.3
3.0

1.2×10

2.4×10
3.4×10

Loam

6

1.4

4.1

3.9×10

8.4

Clay

7

6.3×10–1

2.2

2.4×10–1

1.3

Organic4

9.2×10–1

2.1

4.9×10–1

2.6

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Mn

Mo

Na

Nb

Plant
group
PasturePlant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Stems andshootsAll

83

6.4×10–1

1.9

1.1×10–1

2.7

Sand

42

9.7×10–1

1.5

4.0×10–1

2.7

Loam

40

4.3×10–1

1.7

1.1×10–1

1.8

Cereals

Grain

All

1

8.0×10–1

Maize

Stems andshootsAll3

7.3×10–1

1.0×100

3.8×101

Leafy
vegetables

LeavesAll1

5.1×10–1

2.1×10–1

8.0×10–1

Root crops

Roots

All

3

3.2×10–1

2.3×10–2

4.2×10–1

0

Leguminous
fodderStems andshootsAll1

5.4×10

Cereals

Grain

All

1

1.0×10–2

Leafy
vegetables

LeavesAll1

3.0×10–2

Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

3.0×10–2

Root crops

Roots

All

1

3.0×10–2

TubersTubersAll1

3.0×10–2

PastureStems andshootsAll1

1.0×10–1

Cereals

Grain

All

2

1.4×10–2

2.0×10–3

2.5×10–2–2–3

2.5×10–2

8.0×10–3

2.5×10–2

Leafy
vegetables

LeavesAll2

1.7×10Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

8.0×10–3

Root crops

Roots

All

2

1.7×10–2–3

8.0×10TubersTubersAll1

4.0×10

PastureStems andshootsAll1

2.0×10–2

All1

2.0×10–2

Grain

All

44

2.7×10–2

2.7

3.1×10–3

1.7×10–1

Sand

26

3.7×10–2

2.4

8.2×10–3

1.7×10–1

4

7.6×10

–3

1.7

–3

1.6×10–2

3.2×10–2–3

9.3×10–2

6.1×10–3–3

1.0×10–2

1.7×10–1–2

5.8×10–1

–1

–2

Nd

Not specified

Ni

Cereals

Loam
Clay
Organic
Grasses

Stems andshoots

All

9
4
38

2.4
1.6
2.6

4.9×10
6.3×10
3.1×10
1.8×10Sand

18

2.6×10

1.6

8.2×105.1×10–1

Loam

5

1.1×10–1

1.6

5.6×10–2

1.7×10–1

Clay10

2.5×10–1

1.8

1.1×10–1

5.8×10–1

Organic5

2.4×10–2

1.5

1.8×10–2

5.0×10–2

For footnote see p. 62.

51

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ni

Np

Plant
group
Leguminous
fodder

Cereals

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Stems andshootsAll

27

4.0×10–1

2.5

7.3×10–2

2.6

Sand

14

6.5×10–1

1.8

2.8×10–1

2.6

Loam

3

2.5×10–1

2.6

1.2×10–1

7.4×10–1

Grain

Clay

6

3.2×10–1

2.4

1.1×10–1

7.3×10–1

Organic4

1.5×10–1

3.3

7.3×10–2

9.1×10–1

All85

2.9×10–3

5.0

2.3×10–5

7.1×10–2

Sand

79

3.5×10–3

4.1

2.5×10–4

7.1×10–2

2

8.5×10–4

2.9×10–4

1.4×10–3

3.9×10–5

2.3×10–5

5.4×10–5

–5

Loam
Clay
Maize

Grain

Organic1

9.7×10All

2

4.8×10–3

1.0×10–4

9.4×10–3–2–3

Stems andshootsAll

58

1.9×10

3.3

1.4×101.1×10–1

Sand58

1.9×10–2

3.3

1.4×10–3

1.1×10–1

Leafy
vegetables

LeavesAll

5

2.7×10–2

3.0

5.0×10–3

8.0×10–2

Non-leafy
vegetables

Fruits, heads,
berries, buds

All

9

1.8×10–2

2.4

4.0×10–3

5.7×10–2

Leguminous
vegetables

Seeds and
pods

All

17

1.7×10–2

1.8

4.0×10–3

3.8×10–2

17

1.7×10

–2

1.8

–3

3.8×10–2

2.2×10–2–3

3.6×10–2

2.9×10–2–2

3.6×10–2–3–4

Root crops

Roots

Sand
All
Sand

TubersTubers1.2

5.0×102.1×1057

5.7×10

2.5

7.1×10

2.7×10–2

56

5.8×10–3

2.5

7.1×10–4

2.7×10–2

Grasses

Stems, leaves All

3

3.1×10–2

3.7

7.2×10–3

8.6×10–2

Leguminous
fodderStems andshoots34

2.5×10–2

3.3

2.0×10–3

1.2×10–1

23

4.6×10

–2

1.8

–2

1.2×10–1

6.1×10–2–2

6.3×10–2

4.1×10–3–3

8.1×10–3

6.1×10–2–2

4.7×10–1

–1

2.0

–2

8.9×10

4.7×10–1

1.7

1.3×10–2

5.7×10–2

Pasture

52

6

2.0

All

All
Sand
Clay

Pb

7

4.0×10

Sand

Loam

P

2

Stems andshoots

All

2
9
16

Sand

5

2.1×10Loam

10

3.4×10–2

1.6×10
5.9×101.5
2.7

2.0×10
1.3×10

Cereals

Grain

All

1

2.0×10–1

Leafy
vegetables

Leaves

All

1

1.0

Non-leafy
vegetables

Fruits, heads,
berries, buds

All

1

1.0

Root crops

Roots

All

1

1.0

TubersTubersAll1

5.0×10–1

PastureStems andshoots

All

1

2.0

Cereals

Grain

All

9

1.1×10–2

3.6

1.9×10–3

4.8×10–2

Stems andshootsAll

4

2.3×10–2

3.5

5.1×10–3

9.6×10–2

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Pb

Plant
group
Maize

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Grain

All

9

1.2×10–3

2.3

5.2×10–4

3.8×10–3

–3

6.6

–4

6.0×10

2.3×10–2

Stems andshootsAll

3

2.8×10

Leafy
vegetables

Leaves

All
Sand
Loam
Clay

31
4
3
7

8.0×10–2
7.3×10–2
8.2×10–1
2.8×10–2

1.3×101
1.5
1.0
4.1

3.2×10–3
4.9×10–2
7.9×10–1
4.1×10–3

2.5×101
1.1×10–1
8.6×10–1
1.2×10–1

Non-leafy
vegetables

Fruits, heads,
berries, buds

All5

1.5×10–2

2.6×101

1.5×10–3

3.9

Stems andshootsAll2

8.8×10–3

5.8×10–3

1.2×10–2

Seeds and
pods

All
Sand
Loam
Clay

17
3
5
4

5.3×10–3
2.7×10–3
1.4×10–3
8.0×10–4

1.2×101
3.2
4.4
1.0

4.6×10–4
6.5×10–4
6.5×10–4
4.6×10–4

4.9
8.9×10–3
8.9×10–3
1.0×10–2

Stems andshootsAll1

8.0×10–4

Roots

All
Sand
Loam

27
5
5

1.5×10–2
6.4×10–2
2.3×10–3

1.6×101
1.6
4.7

2.4×10–4
4.2×10–2
2.4×10–4

3.3
1.2×10–1
1.7×10–2

Stems andshootsAll

12

6.3×10–2

1.5×101

3.0×10–3

1.6×101

TubersTubers

All
Sand
Loam

30
5
17

1.5×10–3
6.4×10–3
5.2×10–4

7.4
3.5
2.4

1.5×10–4
1.6×10–3
1.5×10–4

2.6
3.9×10–2
2.3×10–3

Grasses

Stems andshootsAll

17

3.1×10–1

1.8

1.1×10–1

1.0

PastureStems andshootsAll

34

9.2×10–2

4.8

2.2×10–3

1.0

Leguminous
fodderStems andshootsAll1

1.6×10–2

Cereals

Grain

All
Sand
Loam
Clay

17
10
6
1

1.4×10–2
6.6×10–3
4.6×10–2
2.0×10–2

6.0
6.0
2.7

1.7×10–3
1.7×10–3
1.0×10–2

2.4×10–1
2.4×10–1
1.3×10–1

Stems andshoots

All
Sand
Loam
Clay

19
10
7
2

2.3×10–1
1.2×10–1
5.8×10–1
2.8×10–1

4.1
5.0
1.8

2.2×10–2
2.2×10–2
2.9×10–1
1.3×10–1

1.4
1.4
1.2
4.2×10–1

Leguminous
vegetables

Seeds and
pods

All
Sand
Loam

4
1
1

1.7×10–1
5.0×10–2
2.0×10–2

7.4

2.0×10–2

1.2

Root crops

Roots

All

5

4.2×10–2

1.2

3.6×10–2

6.0×10–2

Leguminous
vegetables

Root crops

Pm

Plant
compartment

For footnote see p. 62.

53

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Pm

Plant
group
TubersRoot crops

Po

Cereals

Pu

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

TubersAll

3

1.0×10–2

1.3

7.5×10–3

1.2×10–2

5

1.9×10

–1

1.2

–1

2.5×10–1

2.4×10–4

2.2×10–4

2.6×10–4–4

1.8×10–5

4.7×10–4

2.5×10–4

5.0×10–2

1.6×10–5

3.7×10–4

Leaves
Grain

All
All

Grain

All

2

2.4×10

Leafy
vegetables

LeavesAll

12

7.4×10–3

Non-leafy
vegetables

Stems andshootsAll2

1.9×10–4

Leguminous
vegetables

Seeds and
pods

All

4

2.7×10–4

3.9

6.0×10–5

1.0×10–3

Root crops

Roots

All

10

5.8×10–3

4.3

2.4×10–4

4.9×10–2–2–2

9.7×10–2

5.8

1.4×10–4

3.4×10–2

4.2–2

Stems andshootsAll2

7.7×10TubersAll

9

2.7×10–3–1

PastureStems andshootsAll

10

1.2×10Leguminous
fodderStems andshootsAll2

1.1×10–2

Cereals

Grain

All

1

2.0×10–2

Leafy
vegetables

LeavesAll1

2.0×10–2

Root crops

Roots

All

1

2.0×10–2

Cereals

Grain

All

105

9.5×10–6

76

3.3×10–5

4.9×10–6

7.4×10

–6
–4

Sand
Loam
Clay
Stems andshoots

Maize

Leafy
vegetables

Non-leafy
Vegetables
Leguminous
vegetables

10
16

Organic2

5.4×10All

10

4.4×10–5

Sand1

4.0×10–5

Loam

5

4.5×10–4

4

2.4×10

–6
–6

Clay

54

2

1.6×10

Maize

TubersPr

Plant
compartment

6.9

5.8×102.2×10

1.0

2.6×10–5

2.2×10–4

2.0×10–7

1.1×10–3–7

3.6×10–4–7

3.1×10–4–7

5.1×10–4–6

1.1×10–3

16.4

4.4×10–7

9.0×10–4

2.0

1.5×10–4

9.0×10–4

5.5–7

4.4×10

2.0×10–5

2.7

2.0×10–6

3.2×10–4

2.7–6

3.2×10–4–5

6.7
6.6×10
11.0
14.9

–5

5.0×10

3.5×10
2.0×10
2.3×10

Grain

All

1

3.0×10

Stems andshootsAll

58

5.2×10–558

5.2×10–5–5

2.7

1.0×10

2.9×10–4

2.7

2.9×10–5

2.9×10–4

2.7

6.0×10–6

2.0×10–4

2.7–6

2.0×10–4–5

1.5×10–4–5

1.5×10–4

LeavesFruits, heads,
berries, buds
Seeds and
pods

Sand
All

13

8.3×10Sand

4

1.1×10–4

Loam1

2.8×10–4

Organic1

2.7×10–5All

9

6.5×10–5

8

6.2×10–5

6.3×10–5

6.3×10

–5

Loam
All
Sand

18
18

1.4
1.4

2.0×10

6.0×10
3.7×10
3.7×10TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Pu

Ra

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Roots

All
Sand

5
4

3.9×10–4
5.5×10–4

10.0
10.0

7.0×10–5
7.0×10–5

5.8×10–3
5.8×10–3

Leaves

All
Sand
Loam
Organic10
451

1.2×10–3
7.7×10–4
2.2×10–3
2.5×10–4

2.5
1.9
1.8

2.5×10–4
3.4×10–4
1.1×10–3

4.9×10–3
1.6×10–3
4.9×10–3

TubersTubers

All
Sand
Loam
Clay
Organic

87
72
9
3
2

1.1×10–4
1.0×10–4
1.5×10–4
3.6×10–4
4.1×10–4

5.5
5.0
11.0
3.7

3.8×10–6
3.8×10–6
6.2×10–6
8.0×10–5
1.3×10–5

5.0×10–3
2.0×10–3
5.0×10–3
9.4×10–4
8.0×10–4

Grasses

Stems andshootsAll2

1.6×10–4

5.0×10–5

2.7×10–4

Leguminous
fodderStems andshoots

All
Sand
Loam
Clay

74
33
25
16

4.9×10–4
4.8×10–4
5.8×10–4
4.1×10–4

2.2
2.2
2.4
1.9

1.1×10–4
1.1×10–4
1.1×10–4
1.2×10–4

2.9×10–3
2.0×10–3
2.9×10–3
1.1×10–3

PastureStems andshoots

All
Sand
Loam
Clay
Organic

22
5
10
5
1

5.5×10–4
4.6×10–4
3.0×10–4
2.0×10–3
1.1×10–3

3.0
1.8
3.0
1.5

6.3×10–5
2.1×10–4
6.3×10–5
1.2×10–3

3.9×10–3
9.4×10–4
3.3×10–3
3.9×10–3

Cereals

Grain

All
Loam
Clay

24
7
10

1.7×10–2
2.9×10–2
3.9×10–2

1.2×101
9.7
9.9

8.0×10–5
8.0×10–4
2.4×10–4

6.7×10–1
6.7×10–1
5.0×10–1

Stems andshoots

All
Loam

20
10

3.6×10–2
5.2×10–2

4.8
4.4

1.6×10–3
7.2×10–3

4.3×10–1
4.3×10–1

Grain

All
Loam
Clay

28
4
16

2.4×10–3
1.7×10–3
1.4×10–3

5.4
1.8
4.8

1.2×10–4
9.0×10–4
1.2×10–4

1.1×10–1
3.0×10–3
1.1×10–1

Stems andshootsAll

6

1.8×10–2

5.2

9.6×10–4

8.5×10–2

Leafy
vegetables

Leaves

All
Loam
Clay
Organic

77
10
20
9

9.1×10–2
1.2×10–1
4.0×10–2
4.9×10–2

6.7
2.5
4.5
2.1

1.8×10–3
1.6×10–2
1.8×10–3
2.0×10–2

1.3×102
4.4×10–1
4.2×10–1
1.4×10–1

Non-leafy
vegetables

Fruits, heads,
berries, buds

All
Sand
Loam
Clay

44
3
4
17

1.7×10–2
2.2×10–3
4.8×10–2
2.2×10–2

8.4
2.1
5.6
2.8

2.4×10–4
1.1×10–3
6.9×10–3
3.9×10–3

6.3
5.0×10–3
3.4×10–1
2.1×10–1

Stems andshootsAll

13

6.1×10–2

6.4

6.7×10–3

1.8

Root crops

Maize

For footnote see p. 62.

55

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ra

Plant
group
Leguminous
vegetables

Root crops

Plantcompartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Seeds and
pods

All

40

1.4×10–2

8.2

3.2×10–4

6.2

Loam

12

9.8×10–3

4.5

4.8×10–4

8.7×10–2

Clay15

9.3×10–3

4.2

8×10–4

1.1×10–1

–2

All

18

2.8×101.1×101.1×10Loam

6

1.1×10–2

3.2×101

1.1×10–5

Roots

All

60

7×10–29.2

2.0×10–3

5.6×101

Sand

3

4.8×10–3

2.3

2.0×10–3

1.1×10–2

Loam

8

9.1×10–2

1.9

2.9×10–2

2.0×10–1

23

3.9×10

–2

2.9

–3

2.2×10–1

7.1×10–2–3

7.1×10–1

1.5×10–1–3

7.1×10–1–2

Stems andshootsTubers

Shoots

All
Loam

6

4.6
5.6

2.5×10
9.6×10

–4

All

45

1.1×10

6.8

2.4×10

3.9

Loam

8

1.2×10–2

1.1×101

2.4×10–4

6.2×10–1

Clay24

5.4×10–3

2.5

1.3×10–3

8.0×10–2

All6

1.6×10–1

2.2

4.3×10–2

3.3×10–1

–2

4.5

–3

5.3×10

3.3

3.0

8.5×10–2

1.1
1.6

Herbs

Herbs

All

20

6.9×10

SunflowerAll

4

4.2×10–1

Tea leavesAll1

3.3×10–2

Stems andshootsAll

62

1.3×10–1

4

3.6×10–3

Sand

24

1.4×10–1

4.2

5.4×10–3

1.6

Loam

14

2.6×10–1

2.00

9.6×10–2

7.2×10–1
6.1×10–2

PastureStems andshootsClay3

4.2×10–2

1.5

2.7×10–2

All

42

7.1×10–2

7.6

5.1×10–5

1.6

Sand

3

8.0×10–3

3.8

1.8×10–3

2.3×10–2

Loam

6

8.8×10–3

1.9×101

5.1×10–5

1.1×10–1–1–2

Leguminous
fodderStems andshootsAll

16

1.7×10

3.1

3.4×10

1.5

Sand

5

1.7×10–1

2.5

8.0×10–2

5.7×10–1

Loam

8

1.2×10–1

3.9

3.4×10–2

1.5

Cereals

Grain

All

1

9.0×10–1

Leafy
vegetables

LeavesAll2

6.2×10–1

3.4×10–1

9.0×10–1

Root crops

Roots

All

1

9.0×10–1

All1

9.0×10–1

All

12

3.0×10–3

6.0×10–4

1.0×10–2

2

6.5×10–3–3

1.0×10–2

3.4×10–3–3

8.0×10–3

–3

–4

Rh

Not specified

Ru

Cereals

Grain

Sand
Loam
Stems andshoots56

22

3.2×101.5
1.1×10–1

Other
GrassesRb–5

Stems andshootsClay

Tubers1

Maximum6

2.6

3.0×102.2

1.0×10Clay3

1.3×10

3.3

6.0×10

5.0×10–3

All

19

1.6×10–1

2.7

3.0×10–2

1.0

Sand

3

5.9×10–1

1.9

3.0×10–1

1.0

Loam

10

2.0×10–1

2.2

5.0×10–2

6.5×10–1

Clay5

6.2×10–2

1.7

3.0×10–2

9.5×10–2

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ru

Sb

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Leafy
vegetables

LeavesAll

3

9.0×10–2

3.7

2.0×10–2

2.3×10–1

Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

2.0×10–2

Leguminous
vegetables

Seeds and
pods

All

2

1.5×10–2

1.0×10–2

2.0×10–2

Root crops

Roots

All

1

1.0×10–2

TubersTubersAll1

5.0×10–3

Cereals

Grain

All

24

1.8×10–3

2.7

3.0×10–4

9.0×10–3

Sand4

1.2×10–3

3.7

4.5×10–4

7.8×10–3

19

2.0×10

–3

2.7

–4

9.0×10–3

–2

1.6

–2

1.2×10

5.3×10–2

2.6

2.2×10–5

2.3×10–4–4

2.3×10–4

–5

Loam

Leafy
vegetables

Sr

3.0×10

Stems andshootsAll

7

2.5×10

LeavesAll

5

9.4×10–5

2

2.2×10–4–5

2.2

2.2×10

1.0×10–4

6.7

1.5×10–5

1.6×10–3

4.0×10–4

1.1×10–3
1.0

Sand
Loam

3

5.5×10Non-leafy
vegetables

Fruits, heads,
berries, buds

All5

1.3×10–4

Leguminous
vegetables

Seeds and
pods

All

1

7.0×10–3

Root crops

Roots

All

5

6.2×10–4

2.0×101.5

TubersTubersAll

1

Cereals

Grain

All

282

1.1×10–1

2.7

3.6×10–3

Sand

123

1.4×10–1

3.0

3.6×10–3

1.0

Loam

71

1.1×10–1

2.4

1.6×10–2

7.2×10–1

Stems andshoots

Maize

Grain

Stems andshoots

2.0×10

–3

Clay

72

7.8×10–2

2.4

5.3×10–3

7.1×10–1

Organic10

9.7×10–2

4.1

1.2×10–2

3.6×10–1

All

37

1.1

2.5

1.5×10–1

9.8

Sand

11

2.1

2.3

9.3×10–1

9.8

Loam

3

1.8

2.3

7.2×10–1

3.6

Clay

20

7.5×10–1

2.4

1.5×10–1

2.8

All

39

3.2×10–1

4.1

2.0×10–3

2.6

Sand

19

5.2×10–1

3.3

4.0×10–2

2.6

Loam

13

3.6×10–1

1.6

1.5×10–1

8.6×10–1

Clay7

6.9×10–2

6.7

2.0×10–3

3.9×10–1

All

36

7.3×10–1

6.0

1.2×10–1

3.0

Sand

23

8.2×10–1

2.6

1.2×10–1

3.0

Loam

7

7.0×10–1

1.7

2.8×10–1

1.4

Clay

6

5.0×10–1

1.9

1.8×10–1

1.1

For footnote see p. 62.

57

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Sr

Plant
group
Leafy
vegetables

Non-leafy
vegetables

Leguminous
vegetables

Root crops

TubersGrassesLeguminous
fodderPasture

Herbs
Other crops

58

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

LeavesAll

217

7.6×10–1

6.0

3.9×10–3

7.8

Sand

72

1.7

4.1

6.4×10–2

7.8

Loam

84

1.2

4.1

4.1×10–2

5.0

Clay

54

1.5×10–1

6.0

3.9×10–3

2.2

Organic6

2.1×10–1

1.4

1.5×10–1

3.0×10–1

Fruits, heads,
berries, buds

Seeds and
pods

Roots

TubersStems andshootsStems andshootsStems andshootsStems andshootsAll

19

3.6×10–1

5.5

7.1×10–3

7.9

Sand

5

8.7×10–1

4.1

2.0×10–1

7.9

Loam

3

1.4

1.6

9.0×10–1

2.3

Clay

8

1.3×10–1

6.0

7.1×10–3

8.6×10–1

Organic2

2.2×10–1

4.2×10–2

1.9×10–1

2.5×10–1

–1

6.0

All

148

1.4

2.3

1.3×10

Sand

55

2.2

2.1

3.0×10–1

6.0

Loam

68

1.3

1.9

1.7×10–1

4.6

Clay

25

6.2×10–1

2.2

1.3×10–1

2.6

All

56

7.2×10–1

4.1

3.0×10–2

4.8

Sand

26

1.1

3.7

3.0×10–2

4.8

Loam

16

6.1×10–1

4.5

4.4×10–2

4.5

Clay

13

4.1×10–1

4.5

5.2×10–2

3.9

All

106

1.6×10–1

3.0

7.4×10–3

1.6

Sand

39

2.2×10–1

2.6

2.6×10–2

1.6

Loam

41

1.3×10–1

3.0

7.4×10–3

4.5×10–1

Clay21

1.3×10–1

2.3

2.6×10–2

6.7×10–1

Organic

4

5.8×10–2

4.5

8.0×10–3

2.3×10–1

–1

–1

All

50

9.1×101.9

2.5×10

2.8

Sand

34

1.1

1.7

2.6×10–1

2.8

Loam

6

6.0×10–1

2.5

2.9×10–1

2.0

Clay

7

7.9×10–1

1.3

4.8×10–1

9.7×10–1

Organic3

2.6×10–1

1.1

2.5×10–1

2.8×10–1

All

35

3.7

1.9

1.3

1.8×101

Sand

14

4.9

2.0

1.3

1.8×101

Loam

11

3.3

1.8

1.4

9.8

Clay

10

2.8

1.7

1.3

5.8

Organic1

3.9×101

All

172

1.3

2.2

5.6×10–2

7.3

Sand

87

1.7

5.5

9.8×10–2

7.3

Loam

58

1.1

1.6

3.7×10–1

2.6

Clay

22

8.0×10–1

2.2

9.0×10–2

2.8

Organic

4

3.5×10–1

3.7

5.6×10–2

1.2

All

1

4.5

All

9

8.8×10–1

6.0

2.0×10–2

8.2

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Te

Th

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

Cereals

Grain

All

1

1.0×10–1

Leafy
vegetables

LeavesAll1

3.0×10–1

Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

3.0×10–1

Root crops

Roots

All

1

3.0×10–1

TubersTubersAll1

2.0×10–1

PastureStems andshoots

All

1

1.0

Cereals

Grain

All

36

2.1×10–3

4

4.4×10–3

2.7×10–3

1.2×10–3

6.1×10

–3
–2

Sand
Loam
Clay
Stems andshoots

Maize

Grain

All

Non-leafy
vegetables

LeavesFruits, heads,
berries, buds

28

Maximum

3.4

1.6×10–4

2.2×10–2

1.4–3

6.0×10–3–4

2.2×10–2–4

2.6×10–3–3

3.7×10–2–2

3.0×10

3.4

2.1×101.6

7.0×10

2.4

1.6×104

1.4×101.3

1.1×10

1.8×10–2

Loam

11

6.6×10–3

1.9

2.4×10–3

1.3×10–2

Clay8

3.6×10–3

1.6

2.0×10–3

6.0×10–3

Organic3

2.0×10–3

1.5

1.6×10–3

3.2×10–3

18

6.4×10

–5

9.2

–6

1.1×10–2

2.0×10–4–5

1.1×10–2

1.5×10–5–6

5.4×10–5

1.8×10–3–4

3.0×10–3

All
Clay

Leafy
vegetables

9

Minimum

Sand

Loam
Stems andshoots

18

GSD/
SDa

All

10
7
2

1.2×10

9.3

1.4×10

3.7

1.2×10
5.4×10All

24

1.2×10–3

6.0

9.4×10–5

2.1×10–1

Loam

13

8.6×10–4

3.3

9.4×10–5

5.8×10–3

Clay7

4.9×10–4

2.8

1.9×10–4

4.1×10–3

All

17

7.8×10–4

6.8

6.2×10–5

1.6×10–2

10

2.0×10

–4

9.3

–5

1.1×10–2

1.5×10–5–6

5.4×10–5

–3

5.1

–4

3.3×10

2.4×10–2

9.4

2.5×10–5

4.8×10–1

–4

Loam
Clay

7

1.4×10

3.7

1.2×10

Stems andshootsAll

6

2.2×10Leguminous Seeds andvegetables
pods

All

22

5.3×10–4

Loam

14

1.8×10–3

3.9

1.7×10

2.4×10–2

Clay10

4.1×10–4

2.3×101

2.5×10–5

4.8×10–1

Organic

44.5×10–4

7.6

8.0×10–5

4.0×10–3

Stems andshootsAll

7

4.3×10–3

4.0

5.3×10–4

2.4×10–2

Roots

All

33

8.0×10–4

1.3×101

8.2×10–6

9.5×10–2

14

1.1×10–3

1–6

5.3×10–2

2.6×10–4–5

2.3×10–2

8.7×10–3–3

7.8×10–2

Root crops

Loam
Clay
Stems andshootsAll

148

1.6×10
5.4
4.4

8.2×10

4.5×102.1×10For footnote see p. 62.

59

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Th

Plant
group
TubersPlant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

TubersAll

24

2×10–49.9

1.3×10–5

1.8×10–2

10

2.5×10

–4

6.4

–5

3.6×10–3

9.6×10–5

1.3×10–5

1.8×10–2

1.9×10–2

4.8×10–3

3.2×10–2

Loam
Clay
Stems andshootsU

All2

1.1×10

Other crops

Tea leaves2

3.4×10–3

Grasses

Stems andshootsAll1

4.2×10–2

3.1

7.4×10–4

6.5×10–1

PastureStems andshootsAll

64

9.9×10–2

5.5

2.9×10–3

2.7

Leguminous
fodderStems andshootsAll

36

2.6×10–3

1.6

1.5×10–3

4×10–3

Cereals

Grain

All

59

6.2×10–3

7.7

1.6×10–4

8.2×10–1

6

8.9×10–3–4

6.2×10–2

7.7×10–3–4

6.2×10–2–3–4

5.0×10–2

Sand
Loam
Stems andshoots

Maize

Leafy
vegetables

Non-leafy
vegetables

Grain

20

1.1×105.1

1.9×10

1.6×1011

3.8×10

4.0

7.6×10All

55

2.7×10–2

7.5

3.0×10–5

3.5

Sand

6

3.4×10–2

6.0

2.1×10–3

1.7×10–1

Loam

25

5.4×10–2

6.30

7.4×10–4

3.5

Clay

8

1.0×10–2

3.6

2.8×10–3

9.8×10–2

All

9

1.5×10–2

1.2×101

5.0×10–4

7.1×10–1

–3

1

–4

9.6×10–1

Stems andshootsAll

11

7.8×10

LeavesAll

108

2.0×10–2

Sand7

1.7×10

–1

Loam

14

Fruits, heads,
berries, buds

1

Clay

1.4×10

1.6×10

7.3

7.8×10–5
1

8.8

1.5×10

1.5×10–3

8.8

4.3×10–2

3.9

7.7×10–3

2.7×10–1
4.3×10–2

Clay9

3.6×10–3

4.2

7.6×10–4

Organic6

1.8×10–1

9.7

7.9×10–3

8.0

All

38

1.5×10–2

4.2

5.2×10–4

2.0×10–1

Sand7

1.9×10–2

5.5

1.3×10–3

1.6×10–1

4

2.3×10

–2

2.2

–3

4.7×10–2

1.8×10–2–3

2.0×10–1

–2

9.9

–3

4.3×10

7.1×10–1

Loam
Clay

7

7.6×104.2

5.0×10

Stems andshootsAll

6

5.3×10Leguminous Seeds andvegetables
pods

All

19

2.2×10–3

1.2×101

5.4×10–5

1.5×10–1

Loam

4

3.0×10–3

1.8×101

5.4×10–5

4.7×10–2

Clay7

5.5×10–4

4.7

5.7×10–5

5.0×10–3–2

Stems andshoots60

121.3×10
1

1

–4

All

21

6.4×10

1.4×10

7.4×10Sand

6

2.8×10–1

2.0×101

5.3×10–3

8.7
8.7

Loam

6

1.2×10–2

6.2

7.4×10–4

1.4×10–1

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
U

Plant
group
Root crops

Plantcompartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Roots

All

46

8.4×10–3

6.2

4.9×10–4

2.6×10–1

9

7.8×10

–3

5.9

–4

2.3×10–1

2.5×10–2–3

1.2×10–1

–3

–4

Sand
Loam
Stems andshootsTubers5

6.8×10

6.2

7.9×109.2×10–2

37

2.8×10–2

5.4

2.0×10–3

7.0×10–1

Sand

9

2.5×10–2

5.6

2.0×10–3

2.4×10–1

Loam

11

5.0×10–2

3.0

1.3×10–2

3.2×10–1

5

1.1×10

–2

4.3

–3

5.8×10–2

5.0×10–3–4

8.0×10–2

1.9×10–2–3

7.8×10–2

2.8×10–2–3

8.0×10–2

–4

3.0

–4

1.9×10

4.8×10–3

All
Loam

Herbs
Other crops

Sunflower(leaves)

Sunflower(grain)Grasses

PastureStems andshootsStems andshoots28
43

2.0×10

6.4

1.8×10

3.8

4.3×10

3.2

8.2×10Clay

6

9.2×10All1

1.9×10–1

All

9

3.6×10–2

4.9

8.6×10–3

4.1×10–1

All

39

7.1×10–2

3.9

8.9×10–3

7.8

Sand

5

4.1×10–1

5.3

1.6×10–1

7.8

Loam

22

7.1×10–2

2.9

1.0×10–2

6.4×10–1

Clay11

2.7×10–2

2.1

8.9×10–3

1.0×10–1

All2

1.5×10–2–3

2.9×10–2

8.2×10All

147

1.7×10–2

9.4

2.0×10–4

Sand

19

1.6×10–2

1.7×101

5.5×10–4

1.8

Loam

34

9.8×10–3

8.4

3.1×10–4

4.6×10–1

All

53

4.6×10–2

5.3

1.3×10–3

1.4×1013

2.7×10

–3

1.8

–3

3.9×10–3

7.2×10–2–3

1.4×101–2

4.2

2.0×101.6

2.0

2.0×10–3

2.1×10–2

Sand
Loam

Leguminous
fodder

2.6×10All

Sand

Stems andshoots

3.2

Clay

Clay
Tubers10

9.9×107

Stems andshootsAll

15

1.5×10Sand

12

1.0×10–2
1.0×10–1

W

Unspecified

All

1

Y

Cereals

Grain

All

5

5.0×10–4

Leafy
vegetables

LeavesAll1

2.0×10–3

Non-leafy
vegetables

Fruits, heads,
berries, buds

All1

2.0×10–3

Root crops

Roots

All

1

2.0×10–3

TubersTubersAll1

1.0×10–3

PastureStems andshootsAll1

5.0×10–3

1.3×101

3.3×10

1.8×10–3

5.5

For footnote see p. 62.

61

TABLE 17. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Zn

Plant
group
Cereals

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Grain

All

86

1.8

2.7

2.0×10–2

1.4×101

2.5–1

1.4×101–1

Sand

Stems andshoots

Maize

Grain

Loam

21

1.5

2.5

5.2×10

7.0

17

1.4

1.6

6.6×10–1

3.6

Organic4

8.6×10–1

1.7

4.7×10–1

1.6

All

28

5.3

1.7

2.0

1.5×101

Sand

6

8.2

1.5

4.2

1.2×101

Loam

14

4.4

1.5

2.5

9.5

Clay

8

3.8

1.6

2.0

7.2

All

17

5.8×10–1

1.4

2.8×10–1

9.1×10–1

7

5.6×10

–1

1.5

–1

8.8×10–1

–1

–1

7

5.8×10

1.3

3.4×108.0×10–1

Clay3

6.6×10–1

1.4

4.8×10–1

9.1×10–1

Stems andshoots

All

2

5.8

1.8

4.5

7.0

Leaves

All

112

2.4

2.4

1.0×10–1

1.7×101

2.0–1

1.7×101

–1

9.3

Sand

39

4.2

7.4×10

Loam

53

1.8

2.1

3.4×10

Clay

19

2.1

2.5

3.2×10–1

8.6

3

4.2×10–1

3.7

1.0×10–1

9.5×10–1

Fruits, heads,
berries, buds

All
Organic2

8.6×10–1

7.8×10–1

9.5×10–1

Leguminous
vegetables

Seeds and
pods

All

86

9.1×10–1

2.4

2.5×10–1

1.3×101

Sand

31

9.7×10–1

1.8

2.7×10–1

5.9

Loam

14

3.9×10–1

1.2

2.5×10–1

4.7×10–1

Clay

13

1.6

PastureTubersStems andshoots2.5

2.5×10–1

8.8

–1

1.8

5.0×10–2

6.3×10–1

1.5

1.9×10–1

6.3×10–1

1.6–1

5.8×10–1

–1

All

20

3.0×10Sand

6

3.5×10–1

10

3.0×10–1–1

1.5×10Clay

3

3.7×101.4

2.4×10

4.6×10–1

All

73

1.0

1.9

5.4×10–2

3.2

Sand

38

1.3

1.4

4.8×10–1

2.5

Loam

34

7.8×10–1

2.1

5.4×10–2

3.2

Cereals

Grain

All

1

1.0×10–3

Leafy
vegetables

LeavesAll1

4.0×10–3

Non-leafy
Vegetables

Fruits, heads,
berries, buds

All1

4.0×10–3

Root crops

Roots

All

1

4.0×10–3

TubersTubersAll1

2.0×10–3

PastureStems andshootsAll1

1.0×10–2

GSD/SD: Geometric standard deviation/standard deviation.

62

2.8×10

Loam

Loam

a

3.9×10Non-leafy
vegetables

Tubers

Zr

2.0

Clay

Sand

Leafy
vegetables

42

By definition, the soil to plant transfer factors concept implies equilibriumor quasi-equilibrium conditions in the soil–plant system. This precondition is met
in most cases when flows of the radionuclide from soil to plants are negligible
compared with the total amount of the radionuclide in soil. In selecting data forthe current publication, special care was taken to avoid data obtained under nonequilibrium conditions due to interference by soil sorption/adsorption processes,
and thus, indirectly, it was assumed that radionuclide flows from soils to plants
were low compared with the available pool of the radionuclide in the soil.
However, this is not the case for very mobile radionuclides, such as chlorine
and technetium, that have soil to plant transfer factor values of around 100 oreven higher. Also, chlorine and technetium are very mobile in soil and may besubject to considerable migration to deeper soil layers, making the soil activities
at the end of the vegetation growth period much lower than those at the beginningof the growth period. Such a decline was observed in the study by Kashparov
et al. [97, 98], where the chlorine activity dropped by a factor of 10–100 due toheavy rainfall during the growth period.
However, the activity in plants is due to radionuclide uptake from soil
during the whole vegetation growth period. Transfer factors derived from theradionuclide activity concentrations in the soil and plants are usually determinedat the end of this period, which may lead to very high transfer factor values.
Applying those transfer factor values to radionuclide activity concentrations insoil determined at the start of the vegetation growth period may lead to serious
overestimations.
Therefore, for the present publication, average values for chlorine andtechnetium concentrations in soil were selected (Table 18). For someradionuclides (e.g. 3H, 14C, 36Cl), transfer parameters and models are normallyformulated in terms of specific activity. Data for these particular radionuclides
are therefore treated separately here (see Section 10).
For five radionuclides (Сu, Nd, Pr, Rh, W), no additional information was
obtained. Thus the database only contains Fv values from TRS-364 [3]; these are
given in italics in Table 17. The reference values for these radionuclides aremainly a product of expert judgement and are based on a single reference(Ref. [80]). Therefore, results of radiological assessments based on these values
should be interpreted with caution.
5.2.2.

Radionuclide transfer to fruits

Data presented in this section relate to fruit plants grown in agricultural
ecosystems in temperate regions. Data on fruits growing in tropical andsubtropical environments are reported in Section 5.3. As information on thesubject is scarce, all available information has been included here. Details on the63TABLE 18. TEMPERATE ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) FOR CHLORINE AND TECHNETIUM
Element
Cl

Plant
group
Cereals

Plant
compartment

Soil
group

N

Mean/
value

Grain

All

7

3.6×1012

2.5×101

4.7×101

Sand

Stems andshootsLeguminous Seeds and pods
vegetables

Root crops

Roots

8.6×1011

2.0×10

2.9×1011

2.6×10

8.6×101

2.8×101

4.5×101

2.1×102

6.2×1022

3.7×1017

3.4×1022

3.0×102

2

2.1×10

3.9×102

3.4×102

2

2.2×106.2×102

4.0×102

2

3.4×10

4.5×102

2.6×101

1.7

1

1.4×10

4.8×1011

1.7

1.4×101

4.8×101

1.3

7.0

1.5×101

Sand

All

3
2
6

Sand

1

1.6×10Loam

4

2.5×101Clay1

4.5×101All

7

1.1×101

Sand2

1.3×10

1

Clay

2

9.0

All

14
4
6

1.8
1.5
1.7

1

1.1×10

1.5×101

7.0

1.1×101

1.2×10

1

1.8

4.8

3.6×101

1.2×10

1

1.4

8.6

1.7×101

1.1×10

1

2.0

4.8

Grain

All

2

1.3

Maize

Grain

All

8

3.8

8.2

5.0×10–1

5.2×101

Stems andshoots

All

20

6.4

3.3

8.4×10–1

3.7×101

LeavesAll

10

1.8×102

13.5

4.5

3.4×1034

1.1×10

2

33.1

4.5

2

Sand

Leguminous Seeds and pods
vegetables

Root crops
TubersRoots
TubersStems andshoots

3.4×103

4.3

5.2

1.1

3.0×101

3

1.3

1.1

1.1

1.4

2

2.6×101

2.3×101

3.0×1012

4.6×101

1.4×101

7.9×1018–1

1.3×10–2

6.5×10–1

1.8×10–1

6.5×10–1

1.3×10–2

1.8×10–1

2.5×10

All

5

Sand
Loam
All

Loam
All

2.9×103

2.5×10

6

All

2.4

8.2

Loam

Sand
Pasture1.8×10

3.6×101–1

CerealLeafy
vegetables

6
2
18

GSD/SD: Geometric standard deviation/standard deviation.

64

2.0×101

Clay

Loam

a

1.6

All

Sand
Tc

Maximum

3

Clay
LeavesMinimum

Loam

Loam
Leafy
vegetables

GSD/SDa

2.3×10–1

3.9×10

3.7
1.6

–2

9.4×10

7.6×10

1

3.0

1

7.9

4.7×102information sources and processes governing radionuclide transfer to fruits arereported elsewhere [5, 99–102].
Data on root uptake are reported as Fv values related to fresh weight,
because consumption data for fruits are usually given in fresh weight (converted
from dry weight where necessary; see Appendix I, Table 83):Fv =Bq fresh fruit weight
Bq dry soil weight

In the absence of this information, an average water content of 80% has
been assumed, as proposed in Ref. [102].
Fruits are derived from plants having widely varying growth features andmorphological and physiological traits. The data have therefore been divided into
three groups: woody trees, shrubs and herbaceous plants. The ‘woody trees’
group includes apple, pear, peach, apricot, olive, orange and grapevine. The‘shrubs’ group includes gooseberry, blackcurrant, red raspberry and red currant.
The ‘herbaceous plants’ group includes strawberry, melon, watermelon andrhubarb [5]. This subdivision is more extensive than that of the plantclassification scheme used elsewhere in this handbook.
The variability of the transfer factors for fruits is attributable primarily tothe different properties of soils. For example, the highest transfer factors for
caesium are specific to peat or light sandy soils. The lowest transfer factors forstrontium are specific to organic soils, such as peat, and to soils with high calcium
content. The transfer of both plutonium and americium is lower in loam, organicand calcareous soils [99–101].
The type of plant makes a smaller contribution to the variability of transfer
factors. Given the paucity of data, it is difficult to determine which species
generally has the highest soil to fruit transfer of radionuclides [100].
Contamination of fruits borne by woody trees in the years following an initialdeposition can occur by remobilization of radionuclides from the storage organsof the tree. However, the relative importance of the processes of transfer from soil
to plant and re-translocation from storage organs has not yet been welldetermined [99, 100].
Generally, the activity concentrations in fruits in the years following adeposition show a decrease of several orders of magnitude, depending not only
on the kind of radionuclide and the species of plant but presumably also on
different human interventions in the soil–plant system [100].
Radionuclide activity concentrations in fruit depend on the yield. Low yieldcorrelates with high concentrations of radionuclides [99]. The radionuclide
concentration in fruit also varies with time to ripening. It may increase because of65

leaf to fruit translocation or soil to fruit transfer, decrease because of growth
dilution, and then increase again closer to ripening because of water loss due toageing [100].
Transfer factors for fruits, evaluated on the basis of information presented
in the accompanying TECDOC [5], are given in Table 19.

TABLE 19. TEMPERATE ENVIRONMENT: SOIL TO FRUIT TRANSFER
FACTORS (Fv)Element
Am

Plant
group
Woody trees

ShrubsHerbaceous
plantsCe

Cm

Woody trees

Soil
group

N

Mean/
value

GDS/
SDa

Minimum

Maximum

2.4

1.3×10–6

6.2×10–4

1.8×100

2.2×10–5

6.2×10–4

6.5×10–5

2.3×10–4

4.1×10–5

7.2×10–4

4.1×10–5

7.2×10–4–4

6.2 ×10–4

1.3×10–4

4.4×10–4

6.2×10–4

1.5×100

8.6×10–4

8.0×10–2–4

1.4×10–3

All

6

3.1×10–5

Loam1

8.0×10–6

Sand1

1.5×10–5

Organic1

1.3×10–6

Unspecified

3

1.8×10–4

2–4

Unspecified
All

8

1.5×10–4

1.1×10

–5

Loam

1

7.3×10Sand

1

1.7×10–4

Organic1

6.8×10–5

Unspecified

5

2.3×10–4

2–4

Unspecified

1.0×100

5.3×10

2.9×10–4

4.4×10–4

Herbaceous
plants

Unspecified

1

3.0×10Woody trees

Unspecified2

5.3×10–4–4

Herbaceous
plants

Unspecified

1

3.0×10Co

Woody tree

Loam

1

4.8×10–3

Cs

Woody trees

All

15

5.8×10–3

Clay

2

–3

1.1×10Loam

5

3.5×10–3

8.8×10–1

9.4×10–4

9.2×10–3

Sand4

1.5×10–2

1.6×100

1.9×10–3

8.0×10–2

Organic1

3.7×10–2

Unspecified

3

6.0×10–3

1.7×100

8.6×10–4

1.9×10–2

6

–3

–1

6.9×10–4

5.7×10–3

9.8×10–4

3.3×10–3

1.8×10–3

5.7×10–3

6.9×10–4

3.3×10–3

3.3×10–3

4.1×10–4

8.9×10–3

1.3×100

4.1×10–4

8.9×10–3

Shrubs

All
Clay
Loam

Herbaceous
plants66

22

2.1×108.8×108.1×10–3

2.2×10–3

3.8×10–3

Unspecified

2

2.0×10All

8

2.9×10–3

Loam1

9.0×10–4

Sand1

4.2×10–3

Organic1

6.4×10–3

Unspecified

5

1.0×10–3

TABLE 19. TEMPERATE ENVIRONMENT: SOIL TO FRUIT TRANSFER
FACTORS (Fv) (cont.)
Plant
group

Soil
group

N

Mean/
value

Cu

Herbaceous
plants

Unspecified

1

6.6×10–5

I

Woody trees

Unspecified

5

6.3×10–3–2

Element

Herbaceous
plants

Unspecified

1

1.5×10

Mn

Fruit

Unspecified

1

3.9×100

Na

Woody trees

Loam

1

2.4×10–2

Pu

Woody trees

All

10

1.4×10–4

Loam1

8.0×10–6

ShrubsHerbaceous
plantsRu

Sr

Woody trees

Sand

1

2.0×10–5

Organic1

1.0×10–6

Unspecified

7

5.5×10–4

2–4

Unspecified
All

Minimum

Maximum

1.6×100

4.1×10–4

3.1×10–2

2.9×100

1.3×10–6

2.1×10–2

2.2×100

2.8×10–5

2.1×10–2

6.4×10–5

2.7×10–4

2.7×10–5

8.3×10–4

2.7×10–5

8.3×10–4

1.1×10–3

1.6×10–3

1.7×10–4

1.2×101.2×10

0

–5

Loam

1

8.8×10Sand1

1.6×10–4

Organic1

7.3×10–5

Unspecified

6

1.3×10–4

Unspecified2

1.3×10–3–4

1.5×100

Herbaceous
plants

Unspecified

1

7.4×10Woody trees

All

18

1.7×10–2

9.7×10–1

1.2×10–3

7.0×10–2

4

–2

–1

–2

7.0×10–2

Loam

ShrubsHerbaceous
plants

3.9×108.2×101.2×10

–2

Sand

1

2.5×10Organic1

1.2×10–3

Unspecified

12

1.6×10–2

6.1×10–1

4.3×10–3

3.4×10–2

All

9

4.4×10–2

7.6×10–1

1.4×10–2

1.1×10–1

Clay2

5.4×10–2

2.6×10–2

8.1×10–2

Loam2

3.6×10–2

1.7×10–2

5.5×10–2

5–2

1.4×10–2

1.1×10–1

1.0

1.2×10–2

2.1×10–1

3.7×10–1

1.5×10–2

4.0×10–2

Unspecified

a

9

GDS/
SDa

All

8

5.0×10–2

3.3×108.5×10

–1

–1

Loam

1

1.0 ×10Sand1

2.1×10–1

Organic1

1.2×10–2

Unspecified

5

2.2×10–2

GSD/SD: Geometric standard deviation/standard deviation.

675.3. TROPICAL AND SUBTROPICAL ENVIRONMENTS
To a large extent, the climate and parent rock material determine thecharacteristics of soil development. In tropical areas, several soil types occur inwhich radionuclide uptake by crops consistently deviates from that characteristicof temperate environments. In a typical tropical environment, almost all organic
materials that reach the soil surface decompose rapidly, and the surface
accumulation of organic matter in soil is minimal. Consequently, there is rapid
recycling of nutrients and contaminants into the vegetation. In temperate zones,
the decomposition of organic debris is usually slower, and the accumulation ofsoil organic matter is greater than the rate of decomposition, resulting in highlyorganic surface soil [5, 103–106]. In the tropics, due to high mineral weathering
rates, clays having low exchange activity, such as kaolinite, are more common
than in the temperate zone. This leads to soils with a low exchange capacity
despite their high clay content [103].
From new data it appears that, although the direct influence of climaticconditions on radioecological transfer parameters seems to be minimal, theindirect effects of climatic conditions, through changes of soil and crop
properties, can be significant [103–105]. Transfer factor values for tropical andsubtropical environments are given in Tables 20 and 21, respectively.

TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv)Element
Am

Plant
group
FruitsPlant
compartment
Fruits

Other
c

b

N
2

Mean/
value

GSD/
SDa

–5

3.7×10

Minimum

Maximum–5

4.8×10–5

2.6×10–5

Coconut milk

Other

1

3.7×10

FruitsOther1

1.1×10–5

Leguminous Seeds and pods All
vegetables
Clay

19

6.6×10–1

2.3

2.0×10–3

18–1

6.5×102.3

2.0×10–1

3.6

Leafy
vegetables

LeavesAll

41

9.2×10–2

1.9

3.2×10–2

2.8×10–1

Clay39

9.1×10–2

2

3.2×10–2

2.8×10–1

Non-leafy
vegetables

Fruits, heads,
berries, buds

All

28

3.1×10–1

1.7

1.4×10–1

6.9×10–1

Clay26

3.1×10–1

1.7

1.4×10–1

6.9×10–1

Root crops

Roots

All

7

1.2×10–1

1.7

6.3×10–2

2.1×10–1

5

–1

1.7

6.3×10–2

2.1×10–1

3.6×10–1

3.9×10–1

3.6×10–1

3.9×10–1

Non-leafy
vegetables
Co

Soil
group

Clay
TubersTubers

All
Clay

4
3

1.2×10–1

3.7×10–1

3.7×10

1.0
1.2

3.6

Text cont. on p. 80.

68

TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
K

Plant
group
FruitsPlant
compartment
Fruitsc

LeavesGrasses

Stems andshootsOther crops Leaves
Stems andshoots
Cs

Soil
group

N

Mean/
value

Organic

2
2

All

Minimum

Maximum

5.5×101

4.0×101

7.0×1011–1

6.2×101

3.2×10Loam

1

Organic1

9.0×106.2×101

Loam1

8.7×10–1

Loam

13

1.4

2.0

4.9×10–1

5.6

Loam

5

1.7

1.3

1.2

2.3

3.4

6.0×10–2

1.0

5.7

5.0×10–2

8.7

TubersTubers

Loam

1

2.7

Grain

All

4

2.3×10–1

Sand

1

–1

1.3×10Loam

1

3.3×10–1

All

13

4.8×10–1

1–1

FruitsSand

Grasses

Herbs

9.0×10–1

Cereals

Fruits

GSD/
SDa

3.6×10

Unspecified

5

2.6

Coconut milkc

Unspecified

2

4.3

Leaves

Unspecified

1

5.8

Grain

All

34

1.4×10–2–3

3.6×10–1

8.7

3.2×10–1

8.2

2.9×101

1.5×10–4

1.3×101

1

–4

3.6

Sand

24

6.6×10

Unspecified2

1.2×101

Stems andshootsSand

24

1.1×10–2

LeavesAll3

5.3×10–1

Other

1

1.9

2.8×10

1.5×108.6

1.0×101

1.3×101

2.5×101

4.2×10–4

9.60

1.4×101

2.×10–2

3.20

All

7

1.1

4.5

1.9×10–1

4.1

Sand

6

1.4

4.1

2.2×10–1

4.1

Loam

1

1.9×10–1

Stems andshoots

Sand

4

7.3

1.3

5.4

9.6

LeavesAll

61

1.1×10–1

3.9

1.0×10–2

3.9

Sand

1

–1

4.4×10Clay53

1.0×10–1

3.7

1.0×10–2

7.7×10–1

Leguminous Grain
vegetables

Other crops Leaves

Unspecified

1

3.9

All

19

5.9×10–1

7.2

4.0×10–2

2.1×101

2.7

1.1

2.1×101

Unspecified

6

5.6

Fruits

Unspecified

2

6.6

Stems andshootsLoam

4

7.0×10–2

1.1

4.2

9.0

6.0×10–2

8.0×10–2

For footnotes see p. 73.

69

TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Cs

Plant
group

Plant
compartment

Non-leafy
vegetables

Fruits, heads,
berries, buds

Pb

GSD/
SDa

Minimum

Maximum38

7.0×10–1

3.3

5.0×10–2

1.1×101

–1

–1

Clay

26

9.3×10

1.7

3.6×10Sand

4

5.6×10–2

1.1

5.0×10–2

2.3
6.3×10–2

Unspecified

2

7.3

3.6

1.1×101All

9

4.3×10–1

2

1.3×10–1

8.1×10–1

Clay5

6×10–1

1.3

4.5×10–1

8.1×10–1

TubersTubersAll

8

4.3×10–1

3.4

6.0×10–2

3.0

Sand

1

2.0×10–1

Clay4

3.7×10–1

3.5

6.0×10–2

10×10–1

Leaves

Unspecified

1

3.0

All

49

9.8×10–1

2.3

1.1×10–1

2.9

Clay

39

1.3

1.5

3.6×10–1

2.9

Unspecified1

4.1×10–1

Maize

Grain

Unspecified

2

2.0

1.4

2.5

FruitsFruits

Unspecified

2

2.3×10–5

1.6×10–5

2.9×10–5

Coconut milkc

Unspecified

1

3.2×10–5

Other crops Unspecified

Unspecified

1

6.7×10–5

Non-leafy
vegetables

Fruits, heads,
berries, buds

Unspecified

1

1.7×10–5

Cereals

Grain

Sand

1

2.5×10–3

Grasses

LeavesSand

92.1×10–1

2

–1

2.2

3.7×10

5.9×10–2

1.00

2.0×10–2

7.1×10–1

LeavesSand

Leguminous Grain
vegetables

All

9

3.3×10–3

2.4

6.5×10–4

8.9×10–3

Sand3

3.4×10–3

1.3

2.8×10–3

4.4×10–3

Loam

6

3.2×10–3

3.0

6.5×10–4

8.9×10–3

–1

2.7

–2

Other crops

Sand

18

2.3×10Non-leafy
vegetables

All2

7.0×10–3

PastureStems andshoots

Unspecified

1

3.0×10–1

Root crops

Roots

Loam

3

2.4×10–3

16–4

Tubers

Maize

TubersGrain

CerealsAll

5.7×10

1.4×10

1.0

7.0×10–3

7.0×10–3

1.5

1.8×10–3

4.0×10–3

2.4

1.5×10–4

2.3×10–3

–3

Sand

1

1.6×10Loam

15

5.3×10–4

2.4

1.5×10–4

2.3×10–3

All

6

8.5×10–4

2.1

5.2×10–4

3.8×10–3

Sand1

5.2×10–4

Loam

5

9.3×10–4

2.2

5.9×10–4

3.8×10–3

3

–3

2.5

1.7×10–3

1.0×10–2

1.7×10–3

2.0×10–3

1.8×10–2

5.8×101

All
Sand

70

Mean/
value

Roots

Herbs

Ra

All

N

Root crops

Leafy
vegetables

Pu

Soil
group

2

3.5×10–3

2.1×10–1

FruitsLeavesLoam1

1.0×10

Grasses

Stems andshoots

All

33

1.7

Loam

1

4.3
–1

1.9×10TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Ra

Plant
group
Herbs

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Stems andshoots

Unspecified

4

7.5×10–2

1.4×101

1.0×10–2

3.0

Leaves

Unspecified

11

1.1×10–1

4.8

1.1×10–2

1.0

All

31

–2

2.1×10

4.3

7.6×10–4

2.7×10–1

Sand

5

3.6×10–2

3.0

5.7×10–3

8.7×10–2–2–4

2.7×10–1

Leguminous Grain
vegetables
Other crops Leaves
Roots

26

1.9×10

4.5

7.6×1012
11

1.1×10–1
1.2×10–1

2.1
2,0

3.7×10–2
4.0×10–2

3.7×10–1
3.7×10–1

All3

9.8×10–2

5.8

1.3×10–2

2.7×10–1–1–2

Stems andshoots

All
Loam
All
Loam

6
5
57
1

1.2×10
1.6×10–1
2.6
8.0×10–2

2.5
1.4
5.5

2.0×10
1.0×10–1
5.7×10–2

2.7×10–1
2.7×10–1
1.3×102

Non-leafy
vegetables

Fruits, heads,
berries, buds

All
Loam

9
6

3.2×10–3
1.4×10–3

5.6
3.4

5.2×10–4
5.2×10–4

7.0×10–2
1.4×10–2

PastureStems andshoots

Unspecified
Loam

1
22

7.0×10–2
1.1×10–2

4.9

1.2×10–3

2.2×10–1

TubersTubers

All
Sand
Loam

42
1
41

1.9×10–3
1.6×10–3
2.0×10–3

3.8

2.6×10–4

1.9×10–1

3.9

2.6×10–4

1.9×10–1

Loam

22

–2

2.7×10

4.5

3.0×10–3

4.3×10–1

2.4
2.0
2.0

1.9×10–4
2.0×10–3
1.9×10–4

8.3×10–3
8.3×10–3
3.8×10–3

4.4×10–1

7.6×10–1

Leafy
vegetables

Sr

Loam
All
Loam

Maize

Grain

All
Sand
Loam

18
3
15

1.1×10–3
3.8×10–3
8.7×10–4

Cereals

Grain

All
Sand
Loam

2
1
1

6.0×10–1
4.4×10–1
7.6×10–1

FruitsFruitsOthers3

1.7×10–2

6.2

3.7×10–3

1.3×10–1

Grasses

Grain

Sand

24

1.9×10–1

7.9

1.4×10–2

6.8

LeavesSand

24

3.0×10–1

7.6

2.8×10–2

9.7

Leaves

All

1

3.6

Leguminous Grain
vegetables

All
Sand
Loam

6
5
1

3.7
3.9
2.7

1.9
2.0

1.8
1.8

8.2
8.2

Leaves

All
Sand
Loam

2
1
1

5.0×101
3.7×101
6.3×101

3.7×101

6.3×101

Stems andshoots

Sand
Clay

4
17

7.5
1.2

6.0
7.9×10–2

9.5
5.9

Others1

4.8×10–1

Herbs

Other crops

1.3
6.2

For footnotes see p. 73.

71

TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Sr

Th

U

Plant
group

Plant
compartment

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Non-leafy
vegetables

Fruits, heads,
berries, buds

4.2
4.2

1.6

TubersTubers

1.2
1.2
6.6×10–1

2.8
2.8
7.0×10–1

Leafy
vegetables

Leaves1.2
1.2
2.6×10–1
1.8
2.0
6.8×10–1
6.6×10–1
3.6
3.6
5.8×10–2
1.8×10–1

2.6×10–1
3.9×10–1

Roots

16
13
1
4
2
2
1
34
32
3
9

2.6
2.6

Root crops

All
Clay
Others
All
Clay
All
Clay
All
Clay
Unspecified
Unspecified

1.9
1.9
1.1×101
5.5

1.4
1.4
1.2×10–2
1.8×10–2

1.2×101
1.2×101
9.2×10–1
1.2

Loam

4

6.3×10–5

2.5

2.6×10–5

2.1×10–4

Loam2

5.3×10–6

3.3×10–6

7.3×10–6

Unspecified
Unspecified

3
3

5.8×10–2
2.6×10–1

2.3
1.1×101

3.5×10–2
5.3×10–2

1.5×10–1
3.9

Unspecified
Loam
Loam
Loam

4
5
13
6

8.2×10–3
1.9×10–5
8.9×10–6
3.4×10–5

1.6
1.7
2.6
1.9

5.0×10–3
9.0×10–6
2.9×10–6
1.8×10–5

1.5×10–2
3.9×10–5
3.5×10–5
7.6×10–5

Loam
All
Sand
Unspecified
Unspecified
Unspecified
Unspecified

6
3
1
1
3
1
10

1.2×10–5
1.8×10–2
6.0×10–4
4.6×10–1
4.4×10–2
6.2×10–1
6.4×10–1

3.5
3.8×101

1.9×10–6
6.0×10–4

5.0×10–5
8.2×10–1

3.9

1.1×10–2

1.6×10–1

1.5

2.5×10–1

8.8×10–1

Unspecified
Unspecified
Unspecified
All
Sand
Loam
Unspecified
Unspecified
Unspecified
Unspecified
Unspecified

5
1
3
7
2
1
2
8
10
7
27

7.8×10–3
3.7×10–1
4.9×10–2
3.8×10–2
3.4×10–3
3.2×10–3
8.5×10–1
4.9×10–3
2.5×10–2
8.9×10–3
2.2×10–1

1.4

5.0×10–3

1.2×10–2

1.9
1.1×101

2.8×10–2
2.3×10–3
2.3×10–3

9.8×10–2
9.2×10–1
4.4×10–3

8.5×10–1
3.3×10–3
1.1×10–2
2.9×10–3
8.0×10–4

8.6×10–1
8.4×10–3
5.5×10–2
2.6×10–2
9.4×10–1

Herbs

LeavesStems andshootsLeguminous Grain
vegetables
Non-leafy Fruits, heads,
vegetables berries, buds
Other crops Leaves
Stems andshoots
Unspecified
Root crops Roots
TubersTubers
Leafy
Leavesvegetables
Maize
Grain
Cereals
Grain

FruitsGrasses
Herbs

All plant
FruitsAll plant
Stems andshootsLeavesFruitsLeguminous Grain
vegetables
All plant
Other crops Leaves
Roots
TubersAll plant

72

1.5
1.9
2.0
6.1

TABLE 20. TROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
U

Plant
group
Non-leafy
vegetables
Roots

Zn

Plant
compartment
FruitsAll plant

Soil
group

N

Mean/
value

GSD/
SDa

Minimum

Maximum

Unspecified

14

2.6×10–2

2.8

4.3×10–3

1.8×10–1

2

–1

–1

7.1×10–1

5.1

8.3×10–3

2.6×10–1

Unspecified

7.0×10

7.0×10–1

Leaves

Unspecified

1

2.5×10Roots

Unspecified

6

4.7×10–2

Stems andshoots

Unspecified

1

1.7×10–1

TubersTubers

Unspecified

4

2.0×10–2

2.3

7.3×10–3

4.3×10–2

Leafy
vegetables

Leaves

Unspecified

19

4.8×10–2

3.2

4.4×10–3

4.1×10–1

All plant

Unspecified

1

6.8×10–1

Maize

Grain

All

2

8.7×10–2

1.5×10–3

1.7×10–1–3

1.8×101

2.6×101

Cereals
GrassesSand1

1.5×10All plant

Unspecified

1

9.6×10–1

Grain

All

2

2.2×101
1

Loam

1

2.6×10

Grain

Sand

12

2.2×10–1

1.8

1.1×10–1

7.0×10–1

Stems andshootsSand

12

2.0×10–1

1.9

9.5×10–2

5.7×10–1

All2

1.8×101

1.5×101

2.0×101

Sand1

1.5×101

Loam1

2.0×101All2

1.9×101

1.5×101

2.2×101

Sand1

1.5×101

Loam

1

2.2×101

Clay

18

1.5

1.4

9.3×10–1

2.5

All

28

1.7

1.6

5.8×10–1

3.4

Clay

26

1.7

1.6

5.8×10–1

3.4

All

7

1.2

1.8

5.6×10–1

2.2

Clay

5

1.3

1.8

5.6×10–1

2.2

All

4

1.1

1.2

9.2×10–1

1.5

Clay

3

1.1

1.3

9.2×10–1

1.5

All

41

1.7

1.4

7.3×10–1

4.8

Clay

39

1.7

1.4

7.3×10–1

4.8

Leguminous Grain
vegetables
LeavesNon-leafy
vegetables

FruitsRoot crops

Roots

TubersLeafy
vegetables

TubersLeaves5.0aGSD/SD: Geometric standard deviation/standard deviation.
b‘Other’ refers to soils that are outside the classification scheme used here, such as Marshall Island soils, classified
by the authors as coral sand soil.
cThis plant compartment is outside the classification scheme used here.

73

TABLE 21. SUBTROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv)Element
Ag

Co

Plant group
Herbs

Plant
compartment
Grain

Sand

Mean/
value

2

1.1×10–2–3

GSD/SDa

Minimum

Maximum

1.1×10–2

1.1×10–2

8.0×10–3

8.0×10–3

Grain

Sand

2

8.0×10Non-leafy
vegetables

Stems, shoots

Sand

1

3.0×10–3

FruitsSand1

1.0×10–2

TubersSand2

1.2×10–2

9.0×10–3

1.5×10–2–3–3

1.5×10–2

2.3×10–2

2.3×10–2

Sand4

8.0×10

Root crops

Roots

Sand

2

2.3×10–2

Leafy
vegetables

LeavesSand

8

2.1×10–2

5.8

2.0×10–3

1.2×10–1

Sand

19

2.6×10–1

2.5

4.0×10–2

9.2×10–1

3

1.1×10–1

1.5

8.0×10–2

1.8×10–1–2

1.2

6.0×10–1

7.8×10–1

1.1–1

8.8×10–1

Grasses
Grain

Other crops

Loam
Unspecified

1

5.5×10Loam

3

6.7×10–1

Loam

3

–1

3.0×10

FruitsPastureStems, shoots

Loam

2

2.8×10–1

2.7×10–1

2.8×10–1

Root crops

Leaves

Unspecified 10

1.3×10–3

3.8

1.9×10–4

8.4×10–3

Roots

Unspecified 11

1.3×10–3

4.8

1.7×10–4

3.3×10–2

LeavesAll

19

1.1×10–1

5.8

4.8×10–3

1.5

Loam

7

5.1×10–1

2.0

2.0×10–1

1.2

Roots

Loam

2

4.7×10–2

1.1×10–2

8.3×10–2

Stems, shoots

Loam

2

1.1×10–2

1.0×10–2

1.2×10–2

23

3.1×10–3

1.0×10–3

2.6×10–2–3–3

2.6×10–2

Cereals

Fruits

Grain

All
Loam

15

2.5×102.4

1.0×10Loam

11

1.0×10–2

1.9

3.4×10–3

2.0×10–2

FruitsAll

20

2.0×10–2

4.3

2.8×10–3

6.6×10–1

Loam

12

2.1×10–2

6.3

2.8×10–3

6.6×10–1

8

1.7×10–2

2.0

6.0×10–3

3.5×10–2

2.7×10–3

1.9×10–3

4.0×10–3

–1

–3

3.7

Grain
Stems, shoots

Herbs

Leguminous
vegetables

2.4

7.3×10

Stems, shoots

Clay
Grasses

7.9×102.0

Non-leafy
vegetables

Leafy
vegetables

Loam

9

1.3

All

51

2.5×10

6.3

6.0×10Loam

21

2.7×10–1

1.6×101

6.0×10–3

3.7

All

18

1.1×10–1

3.9

5.4×10–3

8.9×10–1

Loam

8

9.6×10–2

1.7

4.6×10–2

1.9×10–1

Clay8

2.4×10–1

2.9

5.1×10–2

8.9×10–1

Fruit

Clay

1

7.0×10–4

Stems, shoots

Unspecified

1

6.8×10–3

Grain

All

31

1.6×10–2

4.1

2.0×10–3

3.1×10–1

28

1.5×10–2

4.1

2.0×10–3

3.1×10–1

5.9×10–2

8.0×10–3

1.1×10–1

Leaves

Loam
Clay

74

N

Leguminous
vegetables

Leguminous
vegetables

Cs

Soil group2

TABLE 21. SUBTROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Cs

Plant group
Other crops

Plantcompartment
Grain
LeavesPastureStems, shoots

Root crops

LeavesRoots

TubersTubersLeafy
vegetables

Leaves

Maize
Cereals

Grain
Grain
LeavesStems, shoots
Leaves
Grain

Clay
All
Sand
All
Sand
Loam
Unspecified
All
Loam
Clay
Otherb
All
Loam
Clay
Loam
Loam
All
Loam
Clay
All
Loam
Unspecified
All
Loam
All
Sand
Loam
Clay
All
Sand
Loam
Clay
Clay
Unspecified
Unspecified
Unspecified
Unspecified
Unspecified

FruitsLeavesRoots

Unspecified
Unspecified
Unspecified

Roots

Stem, shoots

Non-leafy
vegetables

Fruits, heads,
berries, buds
Leaves
Roots

I

Soil group

Herbs
Leguminous
vegetables
Non-leafy
vegetables

N

Mean/
value

GSD/SDa

Minimum

Maximum

1.1×101
2.4

3.7×10–3
3.7×10–3
4.0×10–2

1.9
2.9×10–2
8.3×10–2

2.4
9.6
4.6

2.1×10–1
3.0×10–3
2.6×10–2
3.0×10–3
3.8
2.3×10–3
2.3×10–3
4.0×10–3
1.0×10–2
1.0×10–3
2.0×10–3
5.0×10–2
2.0×10–3
2.0×10–2
2.0×10–2
3.9×10–3
1.4×10–3
2.1×10–2
9.0×10–3
4.8×10–2
9.0×10–3
3.0×10–2
1.1×10–3
1.1×10–3
6.0×10–3

1.5
1.0×101
8.9×10–1
1.1×10–1
1.0×101
3.0×10–1
3.0×10–1
1.2×10–2
8.0×10–2
2.3×10–2
1.1×10–1
5.0×10–2
3.1×10–2
6.3×10–1
2.2×10–1
3.5×10–1
2.3×10–1
3.0×10–2
4.1×10–1
4.1×10–1
8.0×10–2
8.0×10–2
1.4
8.9×10–2
8.9×10–1

2.0×10–3

8.0×10–3

4.5

4.1×10–3

5.8×10–2

2.1

6.5×10–4

2.7×10–3

–4

1
10
4
2
1
1
9
18
6
2
3
13
10
3
6
6
6
2
2
34
6
10
15
2
34
8
8
4
35
6
22
1
2
1
1
3
1
1

3.0×10
1.3×10–1
8.9×10–3
6.2×10–2
8.3×10–2
4.0×10–2
5.5×10–1
6.9×10–1
2.4×10–1
5.7×10–2
7.3
1.9×10–2
2.5×10–2
7.3×10–3
2.6×10–2
5.3×10–3
3.2×10–2
5.0×10–2
1.7×10–2
1.9×10–1
7.5×10–2
3.5×10–2
1.5×10–2
2.6×10–2
6.5×10–2
1.5×10–1
4.2×10–2
4.7×10–2
3.8×10–2
1.0×10–2
4.1×10–2
8.0×10–3
5.0×10–3
1.5×10–4
2.0×10–2
1.0×10–2
2.4×10–1
3.0×10–3

3
1
1

1.2×10–3
4.5×10–2
1.1×10–2

1.8
6.5
7.8
1.8
2.1
3.3
4.1

2.5
2.8
4.5
4.4
2.4
2.3
2.0
1.6
6.2
5.49
6.0

For footnotes see p. 77.

75

TABLE 21. SUBTROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
I

Plant group
Root crops
Leafy
vegetables

K

Mn

Grasses
Other crops
TubersGrassesLeguminous
vegetables
Root crops
Leafy
vegetables

Pu

Sr

Non-leafy
vegetables
Root crops
TubersLeafy
vegetables
Cereals
FruitsGrasses
Herbs
Leguminous
vegetables
Other crops
Non-leafy
vegetables

Plant
compartment
Leaves
Roots
LeavesN

GSD/SDa

Minimum

Maximum

2.4
2.0

5.1×10–2
6.7×10–3
1.2×10–2

6.1×10–2
8.0×10–2
6.3×10–2

1.5
2.3
1.5
1.5
1.3
1.4
2.4

6.7×10–1
1.6
1.0×10–1
1.0×10–1
1.8×10–1
1.5×10–1
4.0×10–1

2.8
7.2
4.1×10–1
2.7×10–1
4.1×10–1
3.0×10–1
3.3

4.8
9.7
6.4

2.9×10–3
4.7×10–4
2.3×10–1
1.5×10–1
9.0×10–2
4.3×10–4

2.9×10–1
1.5
1.3×101
6.2×10–1
2.2×10–1
1.2×10–3

5.3×10–4
6.2×10–4
1.9×10–4

8.6×10–3
4.8×10–3
2.0×10–3
6.5×10–2
4.2×10–1
8.8×10–1
8.8×10–1
1.9×10–1
2.5×10–1
8.0×10–1
3.3×10–2
2.5
2.4×10–1
6.5×10–1
6.5×10–1
1.3×10–1
1.5×10–1
2.5
1.1

–1

Stems, shoots
Grain

1.2×10
5.6×10–2
3.0×10–2
3.5×10–2
1.3×10–1
3.0×10–3
1.5
2.8
2.4×10–1
1.8×10–1
2.9×10–1
2.4×10–1
1.04
1.0×10–1

Leaves
Roots
Leaves
Roots
Stems, shoots
Fruits

Unspecified 10
Unspecified 11
Unspecified 4
Unspecified 2
Unspecified 2
Unspecified 2

3.7×10–2
6.0×10–3
1.0
3.9×10–1
1.6×10–1
8.2×10–4

Roots
TubersLeaves

Unspecified
Unspecified
Unspecified

2
6
2

4.6×10–3
1.5×10–3
1.1×10–3

Grain
Stems, shoots
Fruits

Loam
Loam
All
Loam
Clay
Loam
Loam
Clay
Loam

8
7
16
10
6
9
9
2
26

5.1×10–2
1.5×10–1
1.0×10–1
1.5×10–1
5.2×10–2
3.4×10–2
5.2×10–1
2.0×10–2
2.8×10–1

1.3
2.5
3.7
3.7
3.0
2.3
1.4
3.0

3.6×10–2
4.2×10–2
1.1×10–2
2.9×10–2
1.1×10–2
1.7×10–2
2.9×10–1
7.1×10–3
2.0×10–2

Loam
All
Loam
Clay
Loam
Loam
Loam

4
15
10
5
3
3
3

2.1×10–1
1.1×10–1
2.1×10–1
3.2×10–2
1.1×10–1
1.7
9.7×10–1

1.2
3.7
2.8
2.2
1.4
1.5
1.1

1.8×10–1
1.9×10–2
4.8×10–2
1.9×10–2
8.2×10–2
1.2
8.5×10–2

Roots
Stems, shoots
Stems, shoots
TubersGrain
Stems, shoots
FruitsGrain

Fruits

Unspecified
Unspecified
All
Sand
Unspecified
Unspecified

Mean/
value

1
2
8
5
1
1
33
Other
3
All
18
Sand
6
Loam
8
Clay
4
Unspecified 6
Unspecified 1

Grain
Leaves
Roots

76

Soil group

2.4

TABLE 21. SUBTROPICAL ENVIRONMENT: SOIL TO PLANT TRANSFER
FACTORS (Fv) (cont.)
Element
Sr

Plant group
PastureRoot crops

Plantcompartment
Stems, shoots

LeavesRoots

TubersLeafy
vegetables

Tc

Zn

TubersLeaves

Mean/
value

5

7.8×10

–1
–1

Sand

1

7.2×10Loam

4

8.0×10–1

Unspecified 10

1.4×10–1

4.1×10

–2
–2

All

12

GSD/SDa

Minimum

Maximum

1.1

6.9×10–1

9.1×10–1

1.1

6.9×10–1

9.1×10–1

5.4

1.3×10–2

9.4×10–1

5.4

3.2×10–3

8.7×10–1

Clay1

5.4×10All

29

4.5×10–1

3.0

5.3×10–2

3.6

Sand

6

8.2×10–1

1.9

3.5×10–1

1.9

Loam

8

3.6×10–1

2.50

9.0×10–2

1.1

Clay

7

4.0×10–1

5.73

5.3×10–2

3.6

All

36

9.8×10–1

3.5

5.2×10–2

5.0

Loam

22

1.8

1.9

6.6×10–1

5.0

Clay

2

8.6×10–2

5.2×10–2

1.2×10–1

2.2×10–2

4.5×10–2

Grain

Clay

2

3.4×10–2

Cereals

Grain

Unspecified

1

3.0×10–2

Leguminous
vegetables

Grain

Unspecified2

5.0×10–1

2.0×10–1

8.0×10–1

Non-leafy
vegetables

Fruits

Unspecified2

3.0×10–1

3.0×10–1

3.0×10–1

All plant

Unspecified

2

–1

–1

5.0×10–1

Root crops

Roots

Unspecified

1

1.9

TubersTubers

Unspecified

3

5.0×10–1

7.2

8.0×10–2

4.0

–1

2.1

1.7×10–1

1.3

3.0×10

1.0×10

Leafy
vegetables

Leaves

Unspecified

6

7.2×10Leguminous
vegetables

Grain, seeds,
pods

All

4

6.3×10–1

2.0

2.2×10–1

1.0

Loam

3

8.9×10–1

1.13

8.0×10–1

1.0

Loam

3

1.1

1.1

9.8×10–1

1.3

1.3

1.1

1.2

1.5

Non-leafy
vegetables

Fruits, heads,
berries, buds

Loam

3

PastureStems, shoots

Loam

3

1.8

1.1

1.7

1.9

Root crops

Leaves

Unspecified 10

1.1×10–1

3.5

2.2×10–2

8.7×10–1

Roots

Unspecified 11

1.1×10–1

3.2

2.4×10–2

1.4

–1

3.8

1.1×10–1

1.4×101

2.1

Leafy
vegetables

b‘

All

N

Maize

Other cropa

Soil group

LeavesAll

18

8.9×10

Loam

6

1.5

7.1×10–1

3.1

Roots

Unspecified2

3.3×10–1

2.5×10–1

4.1×10–1

Stems, shoots

Unspecified2

2.2×10–1

1.5×10–1

2.9×10–1

GSD/SD: Geometric standard deviation/standard deviation.
Other’ refers to sawdust as a substrate where this plant group was grown.

77

Between 30% (tropical) and 50% (subtropical) of the data lacked
information about soil classification or textural composition. Moreover, about
20% of the data are related to plants that are outside the classification scheme
used here for temperate ecosystems. This emphasizes the need for alternative
guidance on soil and plant classifications for tropical plants.

5.4. RADIONUCLIDE TRANSFER TO RICEOne of the critical foods with respect to intake of radionuclides by humans
is rice (Oryza sativa L.), which is the dominant staple food crop in humid tropicalcountries around the globe [5]. Although rice is also grown in temperateenvironments, the primary source is tropical and subtropical environments.
Most rice is produced under flooded conditions, in fields covered by a 5–15 cm
layer of water. Cultivation methods have important effects on plant uptake ofradionuclides from soil. Under flooded conditions, oxygen is depleted quickly by
the respiration of soil microorganisms and plant roots [107–109]. After thedisappearance of oxygen, various degrees of anaerobiosis occur and chemical
reduction of mineral nutrients takes place. In addition, the pH increases with soil
reduction [107–109]. This farming practice is significantly different from thecultivation of cereals in unflooded fields. Therefore, there is a need to consider
the soil to rice transfer factors separately from the transfer factors of othercrops [105].
Transfer factor values for rice were evaluated on the basis of theinformation presented in the accompanying TECDOC [5]. The values derived
from radionuclide studies are given in Table 22; the values derived from stableelement data are presented in Table 23. Transfer factor values for both brown andwhite rice are reported separately in Ref. [5]. It should be mentioned that,compared with other crops, the difference in transfer factor values between brown
and white rice is generally rather small for the majority of elements; therefore, thevalues reported here combine information for both types of rice.

5.5. TIME DEPENDENCE OF RADIONUCLIDE TRANSFER TO PLANTS
This section primarily describes radionuclide transfer from soil to plants inequilibrium conditions, that is, at a time long enough after deposition forequilibrium conditions to be approached. However, radionuclides can also betransferred to plants from soil in the year of deposition. Such a situation can be ofimportance, particularly in the case of acute deposition during the plant growth
period. Many models allow the contamination of plants to be calculated for this78

TABLE 22. TRANSFER FACTORS (Fv) FROM SOIL TO RICE
Element

Soil type

N

Co

All

Cs

Minimum

Maximum

1.7–3

2.2×10

1.0×10–2

8.3×10–3

6.2

1.3×10–4

6.1×10–1

7–2

5.9×103.5–3

7.1×10

1.7×10–1

Loam

24

7.5×10–3

4.1

1.1×10–3

2.8×10–1

Clay

23

–2

2.2×105.7–3

1.1×10

1.5×10–1

I

All

8

3.8×10–3

2.1

1.1×10–3

7.6×10–3

Mn

All

5

–1

2.6×101.7–1

1.2×105.2×10–1

Sand1

2.3×10–1

Loam

4

2.6×10–1

1.9

1.2×10–1

5.2×10–1

Pb

All

2

–3

8.4×10–3

4.7×101.2×10–2

Po

All

2

1.3×10–2

9.4×10–3

1.7×10–2

Ra

All

40

–4

8.7×103.1–4

2.2×102.8×10–2

Loam

14

7.8×10–4

2.4

2.7×10–4

8.8×10–3

Clay

18

–4

5.7×101.7–4

2.5×10

2.9×10–3

All71

2.3×10–2

4.7

2.1×10–3

6.0×100

Sand

6

–2

6.0×102.6–2

1.2×102.2×10–1

Loam

4

9.5×10–2

8.1

5.5×10–3

8.3×10–1

Clay

14

–2

3.2×103.0–3

2.1×101.1×10–1

Sr

Mean/value

5–3

5.1×10

All

466

Sand

GSD/SDa

Tc

All

2

<2×10–4

Th

All

57

1.6×10–4

3.3

2.2×10–5

3.0×10–2

Loam

22

–4

1.5×103.1–5

2.2×10

4.0×10–3

Clay31

1.4×10–4

2.5

2.6×10–5

8.3×10–4

–2

U

Zn

a

Organic1

3.0×10All

65

2.43×10–4

5.98

8.56×10–6

9.00×10–2

Sand

3

5.38×10–3

2.58

1.93×10–3

1.26×10–2

Loam

23

2.07×10–4

6.73

8.56×10–6

2.42×10–2

Clay

29

1.79×10–4

3.57

2.31×10–5

1.80×10–3

Organic

1

9.00×10–2

All5

1.5×100

1.96

5.80×10–1

2.70×100Sand1

2.3×100

Loam

3

1.5×100

2.28

5.80×10–1

2.70×100

GSD/SD: Geometric standard deviation/standard deviation.

79

TABLE 23. TRANSFER FACTORS (Fv) OF STABLE ELEMENT TRANSFERFROM SOIL TO RICE
Element
Ba
Ca

Soil type
All
All

N
87
87

Mean/value–4

9.4×10–3

6.4×102.8
2.2

Minimum

Maximum–5

7.8×10–3–3

4.6×10–2

8.5×10
1.3×10

Cd

All

87

9.3×103.2

9.0×101.2×100

Ce

All

60

3.3×10–5

2.7

1.9×10–5

5.7×10–4

Co

All

86

6.8×10–4

2.1

1.3×10–4

6.4×10–3

Cr

All

87

1.8×10–3

3.5

1.1×10–4

1.9×10–2

83

–4

2.7

–4

1.6×10–2–4

1.6×10–2–4

3.4×10–3–5

1.3×10–3

–4

Cs

All
Loam
Clay

Fe

All

26
36
87

–2

GSDa

7.3×10–3

1.0×10–4

6.7×10–4

1.8×102.2
2.2

1.1×101.1×10
1.4×10
3.8×10IAll

40

2.7×103.2

1.3×10

2.0×10–2

K

All

87

1.3×10–1

2.3

1.8×10–2

7.8×10–1

La

All

79

4.2×10–5

2.2

4.6×10–6

1.4×10–3

Mn

All

87

2.9×10–2

2.1

5.4×10–3

1.2×10–1

87

–4

2.0

–4

6.9×10–3–3

8.7×10–2–1

9.4×100–5

5.9×10–3

–5

Na
Ni
P

All
All
All

Pb

All

87
50
63

–3

3.7

–3

8.4×10–2

1.4×10

2.4×100–4

2.9×101.8
2.6

3.0×10
3.7×10
3.6×10Loam

26

2.4×102.1

7.2×101.1×10–3

Clay35

3.0×10–4

2.6

3.6×10–5

3.5×10–3

Rb

All

87

8.6×10–2

3.1

7.3×10–3

2.2×100

Se

All

67

6.1×10–2

1.9

9.0×10–3

2.9×10–1

Sr

All

63

1.9×10–3

2.2

3.8×10–4

8.2×10–3

26

–3

2.1

–4

6.4×10–3–4

8.2×10–3–2

6.8×10–1

Loam
Clay
Zn
a

All

34
87

–4

2.2

2.0×10

1.6×10–3

2.1×10–1

2.2×10

2.3
1.6

4.1×10
3.8×10
6.1×10

GSD: Geometric standard deviation.

scenario with some uncertainty. Radionuclides acutely deposited during the plant
growth period are localized within the soil surface until harvest, because
farmland is not ploughed during this period. In such cases the use of Fv values isinappropriate, and it is necessary to use aggregated transfer factors (Tag) specified
for the time from deposition until harvest [110–113]. The Tag values for such timedependent scenarios for selected radionuclides (T, Co, Mn, Sr, Cs) are given in
the accompanying TECDOC [5].
The rate of decrease of radionuclide uptake by plants is irregular by nature,and several time periods should be considered when applying a half-life approachfor data evaluation. In the first years after deposition, the bioavailability of someradionuclides in soil reaches its maximum, resulting in the maximum

80radionuclide transfer rate to plants. From the data it can be concluded that theecological half-live of 137Cs in plants is in the range of 1–2 years in the first years
after deposition, increasing to 12–20 years in the long term. The ecologicalhalf-live of 90Sr tends to be slightly longer, at an estimated 20–30 years.
Unfortunately, data are rather scarce in the literature, even for 90Sr and 137Cs, andany such estimates should be interpreted with caution.
Evaluation of radionuclide transfer in the environment implies
consideration of the decrease of radionuclide activity concentrations in plants
over time after a single release of radionuclides to the environment. This decrease
occurs because radionuclides transferred to the environment are gradually fixedby natural sorbents (soils, bottom sediments in water ecosystems, etc.) and are
lixiviated to lower soil layers, becoming less biologically available for inclusion
in food chains.
Time dependent behaviour of radionuclides is often quantified by reference
to the ecological half-life, which is an integral parameter relating to the reductionof activity or activity concentration in a specific medium. According to thedefinition given in Section 2, the ecological half-life is equal to the period of timeover which the concentration of a radionuclide, in a given component of a trophic
chain, is decreased by a factor of two, excluding the effects of radioactive decay.
Although field data on variations in radionuclide transfer factors over time after
clearly defined depositions are rather scarce, there are three prime sources of
information on radionuclide half-lives in plants: global fallout, and the Kyshtym
and Chernobyl accidents [87, 89, 91, 94, 95, 114–116].

5.6. APPLICATION OF DATA
Assessment of Fv values based on sources in the literature is always
associated with various constraints, and often considerable judgement must be
exercised in evaluating the available data. First, some data are based on studies
that were not originally intended for transfer factor assessments. Second, theexperimental design of the research may deviate from the design required by thetransfer factor definition. For example, vertical distribution of radionuclides insoil profiles can depart from the uniform distribution assumed by the transfer
factor definition. Radionuclide transfer to plants depends on numerous factors
including the physical and chemical forms of the radionuclide in the soil, soil
properties, plant species, plant compartments and farming practices. Such factors
result in high variability, and the individual Fv values themselves can vary byover five orders of magnitude [5].
To decrease the uncertainty associated with soil and/or plant factors, several
classifications were developed, and soil to plant transfer factors were reviewed

81

and grouped according to the selected plant and soil categories. These data,
providing information for specific plant and soil groups, allow more preciseradiological assessments in different areas around the world. However, even fortemperate environments, clear gaps in transfer factor values remain for a
substantial number of radionuclides, plants and soil groups.
Far fewer data are available for tropical and subtropical ecosystems than fortemperate environments. Additional uncertainty in the application of the tropicaland subtropical data provided in this handbook can be assigned with the use ofdifferent climate classification schemes. Fv values are highly variable, whichconstitutes a strong limitation for their application. The concentration of aradionuclide in a soil is not the only factor influencing its uptake by plants. Meanvalues reported in this section should be used only as an indication of thetendency of the radionuclide transfer from soil to plants.
Soil and plant classifications facilitate application of the recommended Fv
values for radiological assessments and increase the robustness of such estimates.
However, site specific information on soils, plants and climatic conditions should
be considered when using the Fv values from the tables given in this section.
Transfer factors are not appropriate for natural and semi-natural ecosystems
because of the layered structure of those soils and the highly inhomogeneous
distribution of root systems. Therefore, as an alternative, aggregated transfer
factors (Tag) are used to quantify radionuclide availability to various types ofnatural or semi-natural vegetation and animal products. Tag is defined as the ratioof the radionuclide activity concentration in the plant (Bq kg–1 fresh weight or
Bq kg–1 dry weight) or any other food product, divided by the total deposition on
the soil (Bq m–2). The concept of Tag is adopted as a reasonable empirical measure
to normalize radionuclide accumulation in semi-natural products, regardless ofvariations in the vertical radionuclide distribution and availability in the soil
profile, which greatly depend on the site.

6. AGRICULTURAL ECOSYSTEMS:
TRANSFER TO ANIMALS
Animals can be contaminated by radionuclides via three different routes:
through the skin, by inhalation and by ingestion. The most important transfer
pathway to animals is ingestion of contaminated feed and soil. Radionuclide
intake via soil can be significant, but the availability for absorption of soil
associated radionuclides may be low. Hence, it is the ingestion of contaminated82feed and processes influencing absorption and retention that determine theradionuclide content in animals.
The most commonly applied transfer parameter for agricultural animal
products is the transfer coefficient, which incorporates all the processes fromingestion of a radionuclide in herbage or soil to its incorporation into a specifictissue. Values for gastrointestinal fractional absorption are also given, owing to
the importance of this process in determining the extent of radionuclide
contamination of tissues and its application in a number of models.

6.1. GASTROINTESTINAL FRACTIONAL ABSORPTION
The degree of fractional absorption from the gastrointestinal tract is a key
factor in determining the extent of radionuclide contamination of animal tissues
and milk. Where possible, absorption is reported as the true absorption
coefficient, At [117]. When At values are not available, the apparent absorption
coefficient, Aa , is used (where Aa, is generally defined as the difference in dietaryintake and faecal output, expressed as a proportion of dietary intake). However,this approach is too insensitive to measure absorption from sources with a low
availability, and negative values of absorption can be derived. Furthermore, Aa
does not take into account endogenous secretion of absorbed radioactivity fromthe body to faeces, which may be important for some radionuclides.
6.1.1.

Absorption in ruminants

The gastrointestinal fractional absorption values for ruminants given in
Table 24 were derived either from a database compiled for this purpose or from
authoritative animal nutrition reviews [118, 119]. Agricultural review sourceswere used for those radionuclides that are isotopes of essential nutrient elements.
The data source is specified for each element included in the tables [5].
The values given in Table 24 were derived from data for ruminants older
than 100 d, because there is some evidence of enhanced absorption in young
animals [120]. The table excludes data where: (a) there may have been effects on
absorption of high stable element intakes (e.g. cadmium); (b) reduced absorption
occurs for radiocaesium sources of low bioavailability; and (c) absorption may beunderestimated due to unquantified losses in excreta and milk. Detailed
discussion of the derivation of these values and of the literature used can be foundin Ref. [121].
Fractional absorption of the three major dose forming radionuclides —iodine, strontium and caesium — is complete for radioiodine, and higher forradiocaesium than for radiostrontium. Fractional absorption of radiocaesium83TABLE 24. GASTROINTESTINAL FRACTIONAL ABSORPTION VALUESa
FOR ADULT RUMINANTS
(taken from the database and agricultural reviews)
Element

N

Mean

Ag

1

5.6×10–2

Am

2
2

Ba
Ca

Minimum

Maximum

1.4×10–4

1.4×10–4

1.4×10–4–2

5.5×105.0 ×10–2

6.0×10–2

3.0×10–1

8.0×10–2

4.2×10–1

1.9×10–4

3.0×10–3

Cd1

1.2×10–3

Ce

5

6.1×10–4

Cl

GSDb

2.9

–1

–1

7.1×101.0

Co

9

4.7×10–2

2.9

1.5×10–2

1.1×10–1

Cs

14

8.0×10–1

1.1

6.7×10–1

9.3×10–1–2

2.0×10–1

9.0×10FeI

9.8×10–1

2.0×10
7.0×10

1.1

7.5×10–3

5.0×10–3

4.0×10–2

Na

9.0×10–1

7.4×10–1

1.0

6.7×10–1

5.8×10–1

1.0

–2

2.2

–2

1.0×101.1×10–1

1

P
Pb

9

1.4

–1

Mn
Nb

13

1.0×10–1>1.4×10–3
4.0×10–4Pm

1>5.2×10Pu

3

8.5×10–5

1.4

6.5×10–5

1.2×10–4

Ru

6

5.8×10–3

4.9

1.4×10–3

7.1×10–2–1

6.5×10–1–2

5.5×10

2.7×10–1

Se
Sr

21

5.2×10–1

1.1×10–1

4.0×10
2.0

–1

Te

1

>1.6×10Y2

1.2×10–3

5.0×10–4

1.9×10–3

U2

1.1×10–2

1.0×10–2

1.2×10–2–1–2

3.1×10–1

Zn
Zr

1.5×101

5.3×10–3

6.8×10aSome values are apparent absorption coefficients; see Ref. [121].
b
GSD: Geometric standard deviation.

varies with the chemical form, ranging from <0.10 to >0.80. The extent ofcalcium absorption in the ruminant gastrointestinal tract is governed by the
animal’s calcium requirement, which depends on factors such as age, growth rate
and milk yield [118, 119, 122].
The absorption of essential elements is relatively high compared with thatof other elements. In contrast, elements with high atomic weights, which are notessential elements or analogues of essential elements, are poorly absorbed. For84example, the absorption of transuranic elements, such as plutonium, is low
compared with that of many other elements.
6.1.2.

Absorption in monogastrics

Gastrointestinal fractional absorption values for use in assessments ofradionuclide transfer to humans have been reported by the International
Commission on Radiological Protection (ICRP) [123]; these values are relevant
for monogastric animals. The ICRP values for selected radionuclides are shown in
Table 25. For most radionuclides, the ICRP reference values recommended forhumans are similar to those given in Table 24 for ruminants. However, directcomparisons with the values given in Table 24 are difficult because: (a) the ICRP
reference values are sometimes based on data for both ruminants and nonruminants; and (b) the procedures for deriving the values differ.
Recently, data for the fractional absorption of a small number ofradionuclides in pigs and hens have become available from Russian language
publications [120]. These data are generally in agreement with the ICRP values,
with the exception of a strontium fractional absorption value in laying hens of 0.6(probably as the consequence of a high requirement for calcium).

6.2. TRANSFER TO ANIMAL PRODUCTS
Two alternative methods of quantifying transfer to animal products are
given below. The transfer coefficient has been the main approach in use since the1960s. The concentration ratio approach is an alternative that has potential
advantages, but for which there are currently fewer relevant data.
TABLE 25. RECOMMENDED GASTROINTESTINAL FRACTIONAL
ABSORPTION VALUES FOR ADULT HUMANS [123]Element

Fractional absorption

H, C, Cs, S, Mo, I

1

Se

0.8

Zn, Tc, Po

0.5

Te, Sr, Ca

0.3

Ba, Ra, Pb

0.2

Co, Fe, Sb

0.1

Ru, Ni, Ag

0.05

U

0.02

Zr, Nb0.01

Ce, Th, Np, Pu, Am, Cm

0.000585

6.2.1.

Transfer coefficients

The transfer coefficient has been widely adopted for quantifying
radionuclide transfer to both milk (Fm, d L–1 or d kg–1) and meat (Ff, d kg–1) as theequilibrium ratio of the radionuclide activity concentration in milk/meat to thedaily dietary radionuclide intake [124, 125].
Ward et al. [126] reported that this parameter exhibited less variability
between individual animals within the experimental herd than when transfer was
expressed as the total amount of caesium excreted in milk as a percentage ofintake. They also defined the meat transfer coefficient as the ratio of the 137Cs
activity concentration in boneless meat to the dietary daily 137Cs intake [127].
To estimate transfer coefficients, the composition of the animal’s diet must
be quantified. For agricultural animals, this varies according to feeding strategies(including whether the animals graze or are kept indoors), maintenancerequirements, agricultural practices, and diet composition and characteristics
such as dry matter digestibility. The typical diet of agricultural animals varies
between and within countries, and with the season.
The relative proportion of grass, grain and other dietary constituents isimportant in determining radionuclide intake by agricultural animals, sincegrassy vegetation tends to be more highly contaminated. It is therefore mostappropriate to consult data from animal nutrition reviews relevant to the region
and farming system being considered, to derive dietary intake information.
Details of how the transfer coefficient values provided here were derived
can be found in the accompanying TECDOC [5].
6.2.1.1. Factors affecting transfer values: Duration of intake
Confidence in estimates of the feed intake of experimental animals isclearly greater in experimental studies under controlled conditions than in mostfield studies, where intake often is not measured. In the latter, different
approaches are used for estimating mass intake — some based on agricultural
production criteria but others using ‘expert’ judgement — which can lead tovariability in reported Ff and Fm values.
By definition, a transfer coefficient needs to be in equilibrium with the
dietary intake of the radionuclide. There can be considerable temporal variationin an animal’s intake of radionuclides, and hence tissue concentrations may beconstantly changing. In the case of milk an approximate equilibrium is reachedrapidly for many radionuclides.
However, experimental observations, from which transfer coefficients arederived, often are not conducted long enough for equilibrium to have beenreached in tissues or milk. The requirement of equilibrium conditions often is not86met for radionuclides with short physical half-lives or for those radionuclides
with long radioactive and biological half-lives in tissues (e.g. plutonium), so that
activity concentrations in tissues will not have equilibrated with the diet by thetime of slaughter.
For this reason, dynamic models describing the behaviour of radionuclides
within animal tissues have been developed. These models can be used to predict
radionuclide activity concentrations in different tissues following continuous,
single or varying intakes [128–132].
6.2.1.2. Other factors affecting transfer values
A number of authors have reported variations in transfer coefficients forsome radionuclides. The best documented example is for radiocaesium, wheretransfer coefficients vary with chemical form and metabolic factors including
dietary intake rates [133].
Transfer coefficients of radionuclides are generally higher for animals withlower body mass and dietary intake rates; thus the transfer coefficients for lambs,
for instance, will generally be larger than those for ewes.
Stable element status can affect the behaviour of a radionuclide analogue.
For example, the transfer coefficient for radiostrontium transfer to milk declines
as calcium intake increases [134–138].
The physical and chemical form of ingested radionuclides can affect theextent of gastrointestinal absorption and subsequent transfer to animal products.
This is most clearly shown for radiocaesium [120, 139, 140].
There are relatively few estimates of the bioavailability of particle
associated radionuclides in animals, and transfer is likely to be highly dependent
on the type of particle and its origin. Therefore, estimates of absorption andtransfer coefficients for one source are not necessarily likely to be relevant toanother source. This also applies to different soil types, which may bindradionuclides to different extents and may be ingested by grazing animals.
6.2.2.

Concentration ratios

Transfer coefficients for smaller animals are higher than those for larger
animals, and those for adults are lower than those for (smaller) young livestock. It
is likely that much of this difference is because transfer coefficients incorporate
dry matter intake, which increases with animal size [141].
An alternative method for quantifying transfer from herbage to animal
products is the concentration ratio, CR, which is the equilibrium ratio of theradionuclide activity concentration in the food product (fresh weight) divided by
the radionuclide concentration in the feed (dry matter). Transfer coefficient87

values can be derived by dividing a CR value by the daily dietary intake(in kg d–1), and CR values can be derived by multiplying the transfer coefficientvalue by the daily dietary intake (in kg d–1). It has been suggested that, unlike
transfer coefficients, the CR for a given element may be generally consistentacross species [141].
The CR has the advantage in field studies that dietary dry matter intake does
not need to be calculated or, as is more often the case, have a value assumed forit. However, when the diet consists of a number of foodstuffs, the relative
proportions of all dietary components will be required to be known in order toapply CR values in assessments.
6.2.3.

Transfer values

6.2.3.1. Transfer to milk
Tables 26–28 provide Fm values for cow’s, sheep’s and goat’s milk,
respectively. All data for the Fm values given in the tables are in units of d L–1.
More detailed information on derivation of the values is available in Refs [5,133].
In addition to experimentally derived values, the agricultural/animal
nutrition literature contains a wealth of data on many stable elements in milk andherbage that can be used to derive transfer parameters. Where appropriate, anumber of key reviews [118, 119, 122, 142–147] have been used to identify
typical concentrations of elements in milk and herbage. In turn, theseconcentrations have been used to derive transfer coefficients for milk by
assuming dry matter intake rates of 16 kg of dry matter per day for lactating cows
and 1.5 kg of dry matter per day for sheep and goats.
This may potentially overestimate transfer, as for some nutrient elements a
considerable proportion of the dietary nutrients may be supplied in feed
supplements within developed farming systems (i.e. the nutrient intake rate may
have been underestimated). There is obviously variation in dry matter intake, but
this is unlikely to influence the derived Fm values by more than a factor of 2–3.
Many of the stable elements considered will be under homeostatic control,
and the transfer will therefore not be linear with the intake rate. However, given
the large databases on which these values have been based, they are likely to be
representative of ‘typical values’, taking into account the provisos above. Where
this method has been used to select the recommended Fm value, that fact isindicated in the tables included here.
For cow’s milk there were adequate data in the database to derive values formost of the elements, whereas for sheep’s and goat’s milk the stable element
compilation was used more often. Where reference values are derived from the88TABLE 26. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO COW’S MILK (d L–1)
Element

N

Mean

GSDa

Minimum

Maximum

2.7

3.8×10–5

7.3×10–4

–7

Am

1

4.2×10Ba

15

1.6×10–4

Be

1

–7

8.3×10Ca

15

1.0×10–2

1.7

4.0×10–3

2.5×10–2

Cd8

1.9×10–4

15

1.8×10–6

8.4×10–3

Ce

6

2.0×10–5

5.8

2.0×10–6

1.3×10–4

4

–4

2.0

–5

3.0×10–4–5

4.3×10–3–4

6.8×10–2–5

9.7×10–5–4

2.5×10–2

–6

Co
Cr

3

Cs
Fe

288
7

I

104

Mn

4

1.1×10–4

4.3×10–3

4.6×10–5

3.5×1026
2.0
2.0

6.0×10
1.0×10

6.0×10
1.0×10

5.4×10–3

4.1×10–5

4.9

7.0×10

3.3×10–4

2.4

4.0×10Mo

7

1.1×10–3

2.3

4.3×10–4

5.2×10–3

Na

7

1.3×10–2

2.0

5.0×10–3

5.0×10–2

Nb1

4.1×10–7Ni2

9.5×10–4

6.5×10–4

1.3×10–3

1.0

7.3×10–6

1.2×10–3

1.8–5

8.9×10

3.0×10–4

P

2.0×10

Pbb
Po
Pu

–2

15

1.9×10–4

4–4

c

2.1×10–5

1.0×10Ra

11

3.8×10–4

2.3

9.0×10–5

1.4×10–3

Ru

6

9.4×10–6

8.5

6.7×10–7

1.4×10–4

S1

7.9×10–3

Sb

3

3.8×10–5

2.5

2.0×10–5

1.1×10–4

12

–3

2.1

–3

1.6×10–2–4

4.3×10–3–5

1.0×10–3

–4

Se
Sr
Te

154
11

4.0×10–3

1.3×101.7

1.5×10
3.4×10

3.4×10–4–3

3.5

5.0×10

6.1×10–3

2.4

7.8×10U

3

1.8×10W

7

1.9×10–4

3.1

3.4×10–5

6.8×10–4

Zn

8

2.7×10–3

3.9

1.3×10–4

9.0×10–3

6

–6

4.3

–7

1.7×10–5

Zr

3.6×10

5.5×10a

GSD: Geometric standard deviation.
Value taken from the animal nutrition literature.
cValue taken from a recent review paper [148].
b

89

TABLE 27. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO GOAT’S MILK (d L–1)
Element
Am
Ba

N
2
3

Mean

GSDa

–6

6.9×10–2

1.1×10–2

9.9

Maximum

3.7×10–6

1.0×10–5

2.1×10–3

1.5×10–1

1.2×10–2

1.4×10–1

Ca

12

7.3×10Cd1

1.6×10–2

Ce1

4.0×10–5Co1

5.0×10–3

Cr2

1.5×10–2

2.9×10–3

2.8×10–2

28

–1

2.2

7.0×10–3

3.3×10–1

2.9

2.7×10–2

7.7×10–1

1.4

5.0×10–3

1.1×10–2

3.2×10–3

1.6×10–1

1.8×10–3

2.7×10–3

1.6×10–2

6.8×10–2

Csb

1.1×101.9

Minimum–2Fe

5.2×10

I

24
b

–3

Mn

Mo

2.2×10–1
1.0×104

Nab

8.2×10–3
1.2×10–1

Nb1

6.4×10–6

Ni2

8.3×10–2

1

–5

Np
Pb

5.3×10

2.9×10–1

Pb1

6.0×10–3

Pm

1

2.7×10–5

Po2

2.3×10–3

S

12

3.8×10–2

Se2

6.9×10–2

5.9×10–2

7.9×10–2

21

–2

–3

8.1×10–2

Sr

1.6×101

4.4×10U

1

1.4×10–3

1

2.0×10–5bab

5.8×10

6.4×10–2

Zn
Zr

2.0

–3

Te
Y

1.7

1

5.5×10–6

GSD: Geometric standard deviation.
Value taken from the animal nutrition literature.

database, summary statistics are provided in the tables; if the values were derived
from stable element review data, only a best estimate is given as the reference
value.
CR values for the milk of cows, sheep and goats have been derived from thedatabase compiled to derive Fm values. If data were not available in the database,the stable element review values were used, from which it was also possible toestimate CR values for horse milk. Table 29 compares the CR values for the fouranimal species; as has been suggested [140], the CR values for a given element
are broadly similar across the species.

90

TABLE 28. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO SHEEP’S MILK (d L–1)
Element
Ba

N
1

Cab

Mean

2.7×10–3

Cr1

2.0×10–2

Cs

28

5.8×10–2b

2.3×10–1

Mn1

2.4×10–3

Na1

1.0×10–1

Ni

1

Pb

3.2×10–1

3.3

3.0×10–2

9.4×10–1

1.2

1.3×10–2

4.0×10–2

2.8×10–1
3.1×10–1

Pbb

3.5×10–2
1

Sba

6.0×10–3

7.9×10
7

b

2.3

–2

Fe

Znb

4.1×10–3

4.9×10–2

2

Te

1.2×10–3

2.3×10–1
1

Sr

Maximum

4.1×10Co

Pu

Minimum

–2

Cd

I

GSDa

1.0×10–4
1.5×10–1

4

2.7×10–2

1–3

2.9×108.1×10–2

GSD: Geometric standard deviation.
Value taken from the animal nutrition literature.

6.2.3.2. Transfer to meat and eggs
Approaches to deriving Ff values for meat were as described above for thecompilation of Fm values. Exceptions were that: (a) no additional stable element
review of the animal nutrition literature was conducted, although the databaseincludes some stable element values; and (b) single (acute) administration studies
were not used unless sufficient time series data were available.
In summarizing Ff values, only results reported for pigs, sheep and goatsaged six months or older (where this information was given) were used; for cattle,
only data from animals aged 1 year or older were included; and for poultry, only
data for animals older than 40 d were used. However, if no data for animals
meeting these age criteria were available for an element, data for younger animals
were used (on only two occasions).
Data from experiments of less than 20 days’ duration were not used forsheep, goats, pigs or poultry; for cattle, experiments of less than 60 days’ duration
were not used. Few single administration data were used; among the experimentsthat were included are those reported by Beresford et al. [149, 150], where

91

92

SD

Minimum

Cow

MaximumNCR

1.3×10–2 1.6×10–3 1.2×10–2 1.5×10–2
3 1.2×10–1
2.5×10–1
2.0×10–1
–2
–2
–5
–1
4.3×10 7.4×10 2.7×10 1.3×10
3 2.4×10–2
6.9×10–2
1
3.2×10–3
1
2.5×10–3
1 7.6×10–3
4.0×10–2
3.7×10–2 4.3×10–2
2 4.1×10–2
1.1×10–1 1.2×10–1 3.6×10–3 6.9×10–1 119 1.8×10–1
1.2×10–3 2.4×10–4 1.0×10–3 1.5×10–3
3 3.4×10–2
3.0×10–1 2.8×10–1 3.0×10–3 7.9×10–1 44 5.0×10–1
4.5×10–3
8.6×10–4 8.2×10–3
2 1.5×10–3
–2
–2
–2
–2
2.8×10 1.3×10 1.9×10 4.3×10
3 2.7×10–2
3.7×10–1
2.3×10–1 5.0×10–1
2 1.8×10–1–5
1.0×101 1.9×10–5
8.2×10–2
2.5×10–1
3.1×10–1
4.3×10–1
–3
–3
–4
–3
2.4×10 1.3×10 9.9×10 4.3×10
7 9.0×10–3
2.4×10–3
1
1.4×10–1
1 6.1×10–2–3
2.7×101
5.7×10–2 4.5×10–2 2.6×10–2 1.5×10–1
7 3.5×10–2
2.3×10–2 2.2×10–2 5.0×10–3 1.4×10–1 43 4.4×10–2
8.0×10–3
4.8×10–3 1.1×10–2
2 1.2×10–2
5.0×10–3
7.5×10–2 1.6×10–2 5.5×10–2 9.5×10–2
6 9.6×10–2–5
1.4×101 1.7×10–5

CR

CR

SD

Minimum

Sheep
Maximum
CR

Horse

1

4.4×10–2 1.6×10–2 1.2×10–1 51

3.0×10–2 3.5×10–2 1.0×10–1 4

1

1
1

1.2×10–1

2.3×10–1

4.2×10–1
4.7×10–1
3.0×10–2

1

1

5.5×10–2

4.4×10–2

1.8×10–1

1 3.5×10–3
1.5×10–1
1

N

6.2×10–31
3.0×10–2
1
1.7×10–1 1.3×10–1 2.0×10–2 5.8×10–1 17
5.2×10–2
1 9.3×10–3
5.8×10–1 2.5×10–1 2.5×10–1 8.8×10–1 5
3.6×10–3
1 1.6×10–3
2.1×10–2
1.6×10–1
6.0×10–2

N1
1
6.5×10–2 6.3×10–2 3.0×10–1 121
5.8×10–1 8.4×10–2
1.2
3
1
1

Maximum
6.1×10–2
3.4×10–1
7.4×10–2

Minimum

Goat

1.4×10–2 2.3×10–1 2
8.3×10–2 1.3×10–1 2.9×10–1 4
1

SD

Note: Shading denotes values estimated from the stable element review.

Ba
Ca
Cd
Cl
Ce
Co
Cr
Cs
Fe
I
Mn
Mo
Na
Nb
Ni
P
Pb
Po
S
Sb
Se
Sr
Te
U
Zn
Zr

Ele-
ment

TABLE 29. CONCENTRATION RATIOS (CR) FOR THE MILK OF DIFFERENT ANIMALS (kg L–1)

5.0×10–2
2.4×10–1
4.7×10–2
6.9×10–2
3.2×10–3
5.4×10–3
3.7×10–2
1.5×10–1
2.4×10–2
4.6×10–1
2.8×10–3
2.5×10–2
1.9×10–1
1.5×10–5
2.5×10–1
3.5×10–1
1.4×10–2
2.4×10–3
1.4×10–1
2.7×10–3
4.6×10–2
3.7×10–2
1.0×10–2
5.0×10–3
8.7×10–2
1.5×10–5AllspeciesMean

4.6×10–1
8.3×10–1

6.2×10–1
5.2×10–1
6.7×10–1

2.7×10–1

3.3×10–1
7.2×10–1
6.4×10–1
2.4×10–2
5.2×10–1
3.2×10–1
7.5×10–1
1.6×10–1
5.3×10–1
1.9×10–1
3.8×10–1
7.9×10–2

2.9×10–2
4.4×10–1
3.3×10–1

Min/
Max

Ratio

models were fitted to data for consecutive slaughter dates over approximately one
year after a single administration. Subsequent predictions of Ff were made fordifferent periods of continuous administration; values incorporated into the
database were equilibrium or 1000 d predictions. In some cases, data are
available for a series of different sample times after continuous feeding (seeRef. [151]). In this case, transfer values derived for the shorter time periods havebeen excluded from the database.
Transfer coefficients for the meat of a range of domestic animals are given
in Tables 30–34. All data for Ff values are in units of d kg–1 fresh weight. If it wasnecessary to convert reported dry weight values to fresh weight, it was assumed

TABLE 30. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO BEEF (d kg–1)
Element

N

Mean

GSDa

Minimum

Maximum–4Am1

5.0×10Ba2

1.4×10–4

5.0×10–5

2.3×10–4

Ca3

1.3×10–2

30.0

1.0×10–3

6.1×10–1

Cd8

5.8×10–3

7.8

1.5×10–4

6.0×10–2

Cl

1

–2

1.7×10Co

4

4.3×10–4

2.3

1.3×10–4

8.4×10–4

58

–2

2.4

–3

9.6×10–2–3

2.5×10–2

–3

Cs
Fe

4

2.2×10–2

1.4×10

1.5

4.7×109.0×10–3

3.2

2.0×10

3.8×10–2

1.2

1.1×10–4

1.5×10–4

6.0×10–4

6.0×10–4

1.0×10–2

2.0×10–2

2.5

2.0×10–4

1.6×10–3

24.8–8

8.8×10

3.0×10–4

I

5

6.7×10La3

1.3×10–4

Mn2

6.0×10–4

Mo1

1.0×10–3

Na2

1.5×10–2

Nb1

2.6×10–7P1

5.5×10–2

Pb

5

7.0×10–4

Pu

5

–6

1.1×10Ra

1

1.7×10–3

Ru3

3.3×10–3

2.2×10–3

6.4×10–3

Sbb

2

1.2×10–3

1.1×10–3

1.3×10–3

35

–3

2.9

–4

2.0×109.2×10–3

2.9

4.0×10–5

9.6×10–4

1.6–4

6.3×10–4–2

6.3×10–1

Sr

1.3×10–3

Te1

7.0×10Th

6

2.3×10–4

3–4

U

3.9×10–1

Zn6

1.6×10Zr

1

1.2×10–6

a
b

1.8

3.2

2.5×10
4.0×10

GSD: Geometric standard deviation.
Young animals (5–6 months old).

93

that the dry matter content of meat for all animal types was 25%. Data for poultry
meat are largely for chickens but also include some data for duck. More detailed
information is available in the accompanying TECDOC [5].
The Ff values for egg contents, that is, excluding the shell, are presented inTable 35 (data are largely for chickens, but some values for duck are included).
Data for most radionuclides are relatively scarce. The values in Table 35 are
generally similar to those proposed in TRS-364 [3], because many of the
TRS-364 values were based on Ref. [152], which continues to be a major sourceof data.
TABLE 31. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO MUTTON (d kg–1)
Element

N

Mean/value

GSDa

Minimum

Maximum

8.0×10–3

1.6×10–2

5.3×10–2

1.3

–4

Ag

1

4.8×10Am

1

1.1×10–4

Cd1

1.2×10–3

Ce1

2.5×10–4

Co2

1.2×10–2

Cs

41

1.9×10–1

I1

3.0×10–2

Mn1

9.0×10–3

Na1

1.1×10–1

Pb2

7.1×10–3

4.0×10–3

1.0×10–2

Pu

2

–5

5.3×10–5

2.0×108.5×10–5

Ru2

2.1×10–3

6.3×10–4

3.6×10–3

S

3

1.7

1.3

1.2

2.1

Sr

25

1.5×10–3

1.7

3.0×10–4

4.0×10–3

Zn

6

4.5×10–2

2.2

2.0×10–2

1.4×10–1

a2.2

GSD: Geometric standard deviation.

TABLE 32. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO GOAT MEAT (d kg–1)
Element

N

Mean

Ba

1

1.3×10Cs

11

3.2×10–1

Nb1

6.0×10–5Sr

8

2.9×10–3

Te

1

–3

2.4×10Y1

5.4×10–2

Zr1

2.0×10–5aGSD: Geometric standard deviation.

94

GSDa

Minimum

Maximum

2.5

1.2×10–1

1.9

1.2

2.0×10–3

3.7×10–3–5

TABLE 33. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFER
TO PORK (d kg–1)
Element

N

Mean

Ca

1

2.0×1022

2.0×10–1

Fe

1

–3

3.0×10I2

4.1×10–2

Mn1

5.3×10–3

P1

2.7×10–2

Ru1

3.0×10–3

Se1

3.2×10–1

Sr

12

2.5×10–3

2

–2

U
Zn
a
b

2

Minimum

Maximum

1.5

1.2×10–1

4.0×10–1

1.5×10–2

6.6×10–2

5.0×10–4

8.0×10–3–2

6.2×10–2–1

2.0×10–1

–3

Cs
b

GSDa

4.4×10

2.7

2.6×10–1

1.7×10

1.3×10

GSD: Geometric standard deviation.
Young animals (2 months old).

TABLE 34. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFER
TO POULTRY MEAT (d kg–1)
Element
Ba

N
2

Mean

GSDa

–2

Minimum

Maximum–3

2.9×10–2–2

4.4×10–2

9.2×10

1.9×10–2

Ca2

4.4×10

4.4×10

Cdb

2

1.7

1.7

1.8

Cob

2

9.7×10–1

3.0×10–2

1.9

Csb

13

2.7

1.6

1.2

5.6

I

3

8.7×10–3

2.0

4.0×10–3

1.5×10–2

Mn2

1.9×10–3

1.0×10–3

2.8×10–3

Mo

1

–1

Nab

1

7.0

Nb

1

3.0×10–4

Po

1

2.4

Se

4

9.7

2.3

4.1

2.8×101

Srb

7

2.0×10–2

1.8

7.0×10–3

4.1×10–2

Te1

6.0×10–1

U2

7.5×10–1

Zn

3

–1

4.7×10Zr1

6.0×10–5ab

1.8×101.2

3.0×10–1

1.2

3.8×10–1

5.3×10–1

GSD: Geometric standard deviation.
Includes values for duck.

95

TABLE 35. TRANSFER COEFFICIENTS FOR RADIONUCLIDE TRANSFERTO EGG CONTENTS (d kg–1)
Element

N

Mean

GSDa

Minimum

Maximum–3Am1

3.0×10Ba1

8.7×10–1

Ca1

4.4×10–1

Ce1

3.1×10–3

2

3.3×10–2

2.6×10–2

4.0×10–2

11

–1

–1

7.1×10–1

–1

2.8

b

Co

b

Cs

4.0×101.5

1.6×10

Fe

2

1.8

I

4

2.4

1.3

8.5×10
1.9

3.2

Mn

3

4.2×10–2

1.4

3.2×10–2

6.2×10–2

Mo3

6.4×10–1

1.3

5.2×10–1

8.7×10–1

Nab

2

4.0

1.9

6.0

Nb

1

1.0×10–3

P1

6.4×10–1

Po

1

3.1

Pu

2

1.2×10–3

9.9×10–6

2.3×10–3

Ru

1

–3

4.0×10Se

4

1.6×101

1.9

8.8

2.8×101

Srb

9

3.5×10–1

1.4

2.5×10–1

6.4×10–1

9.2×10–1

1.2

1.2

1.9

Te

1

5.1

U

2

1.1

Zn

4

1.4

Zr

1

2.0×10–4

ab1.2

GSD: Geometric standard deviation.
Includes values for duck eggs, which, with the exception of Sr, included the shell.

CR values for the meat of a number of species are given in Table 36. The data
are only extensive for cow meat, and therefore comparisons across species for theelements are fewer but still encouraging. In addition to the data given, values forhorse meat of 3.8 × 10–1 for iron and 5.3 × 10–1 for zinc can be derived using stabledata from the agricultural nutrition review sources described above. These values
are in reasonable agreement with the values for other species given in Table 36.

6.3. APPLICATION OF DATA
The data compilation for gastrointestinal absorption in ruminants can beused as an additional data source or as an alternative to the ICRP data. Additional
analysis is required of the underlying data of both sources to critically evaluate
whether current differences are significant.

96

97

1
1

1.3×10–3

9.4×10–2

4.6×10–3–2

9.5×10

1.6×10–3 2.4×10–4

1.4×10–1

8.0×10–3

–2

–1

–6

–2

I

La

Mg

Mn

Mo

Na

Nb

Ni

Ru

Rb

3.0×10–1

Ra

1.8×10–1

3.8×10–1

1.3×10–3

3.7×10–2

1.4×10–1 1.3×10–1

PuPo

2.5×10

3.2×10

1.0×10–3

8.2×10

6.0×10

7.7×10–2 1.8×10–1

1.3

2

8.0×10

6.5×10

9.7×10

9.6×102.2×10–2

2.2×10

Pb

P

1

–2

–2

–2

Fe

2.5×10–1–1

2.3×101.3

4.1×10–1

6.2×10–1

1.7×10–1

1.1×10–2

1.9×10–1

1.8×10–3

1.9×10–1

7.2×10–1

7.3×10

1

11

7

11

2

2

2

3

3

6

17

2

Cs

–1

7.8×10–2

7.2×10–1–1

Co

3.9×10–3–1

4.8×10–2

–1

2

7

2

2.4×10–1

4.3×10–1

3.5×10–1

2.6×10–2

Cl

1.7×10

2.3×10–3

1.7×10–1 1.5×10–1

CdCe

2.1×10–2

2.3×10–2

Ca

1.0

5.3×10–2

5.7×10–4

3.9×10–5 2.4×10–5 1.5×10–5

1.2×10–2 4.0×10–3 9.2×10–3

2.7×10–1

6.4×10–1

2.3×10–1

2.2×10–4

1.2×10–2

1.4×10–2
1.3×10–3

6.3×10–5

1.6×10–2

7.5

2.3×10–2

Minimum Maximum

N

1

3

3

1

1

51

1

2

1

SD
1

CR
4.3×10N
1.1×10–4

Minimum Maximum

Ag

SD

Sheep

Am

CR

Beef

–4

Element

6.6×10–1

9.3×10–2

9.2×10–2

1.3×10–1

CR–1

1.0×10SD

2.3×10–1

3.5×10–2

8.3×10–3

1.1

1.5×10–1

2.4×10

–1

2

2

4

1

Minimum Maximum N

Pork

TABLE 36. CONCENTRATION RATIOS (CR) FOR THE MEAT OF DIFFERENT ANIMALSa

Min/ Max

Ratio

5.7×10–4

3.0×10–1

1.8×10–1

3.9×10–5

1.4×10–1

2.5×10–1 1.8×10–2

1.3

8.0×10–2

6.5×10–6

9.7×10–1

9.6×10–2

8.0×10–3

1.4×10–1

1.6×10–3

9.4×10–2 9.8×10–1

2.5×10–1 8.2×10–1

3.9×10–1 1.4×10–1

3.1×10–1 5.9×10–1

2.4×10–1

2.2×10–4

9.2×10–2 6.9×10–2

1.9×10–2 6.0×10–1

1.1×10–4

4.3×10–4

Generic98

1.2×10–2

1.7

Zn

1.1

6.1×10

3.2

4.7×101.7–1

3.0×10
9

8

–1

2.1

5.0×10

CR

SD

1.3

a

2.9

Minimum Maximum

Sheep

Note: Shading denotes values estimated from the stable element review.
For goats, the value of 6.2×10–1 for caesium (N = 4) is included in the generic value.

3.3×10

U

–3

3

–1

6.2×10–3 5.0×10–3

Th

–1

1

Se

1.8×10–1

NTe

1.7×10–3

Minimum Maximum
1SD

2.7×10–1

CR

Beef

Sb

S

Element

2

N

1.1

CR

SD

1

Minimum Maximum N

Pork

TABLE 36. CONCENTRATION RATIOS (CR) FOR THE MEAT OF DIFFERENT ANIMALSa (cont.)

5.0×10

1.9

3.3×10–1

6.2×10–3

1.8×10–1

1.1

2.7×10–1–1

Generic

8.2×10–1

Min/ MaxRatio

It is proposed here that the concentration ratio would be a more robust andgeneric parameter than the transfer coefficient. For most radionuclides, theconcentration ratio data compiled vary little between the species considered(sheep, goats, cattle and horses). Therefore, concentration ratios derived for one
species could be applied to another. Unfortunately, however, many authors whoreport transfer coefficients do not provide the information required to estimate
concentration ratios.

7. RADIONUCLIDE TRANSFER IN FORESTS
7.1. RADIONUCLIDE TRANSFER TO TREES
7.1.1.

Interception of radionuclides in tree canopies

Forests are managed as timber crops, with rotation periods of 50–100 years
between planting and harvesting. Alternatively, they can be managed for wildlife
conservation with no major removal of trees. Both types of forest, however, arelong term features of the environment that, once contaminated withradionuclides, represent long term sources of radiation exposure to forest workers
and to the general public. Forests are used as sources of natural foodstuffs,
particularly wild fungi, fruits (berries) and game, which, since the Chernobyl
accident, have all tended to have relatively high levels of radiocaesium
contamination in comparison with agricultural food products.
During deposition of atmospheric radioactive fallout onto forests, the tree
canopy is contaminated directly by dry or wet interception of aerosol-derived
radionuclides (Table 37). This is followed by translocation from foliar surfaces tothe trunk, branches and roots of the tree. Decontamination of the exterior surfacesof the tree canopy occurs with time as a result of weathering of interceptedradioactive materials by wind and rain, and the natural loss of leaf litter. These
canopy processes are followed, or accompanied, by root uptake, which is the
predominant route of tree contamination over the longer term. Two stages of thecontamination of the forest system can be distinguished:(1)(2)

The ‘early’ phase, lasting 4–5 years and characterized by a rapid
redistribution of the initial deposits between trees and soil;
The ‘steady state’ phase, characterized by slow changes in biologicalavailability, with root uptake determining the degree of contamination of
the trees.

99TABLE 37. CANOPY INTERCEPTION FRACTIONS FOR DIFFERENTTYPES OF FOREST [153]
Forest type

Deposition type89

Interception (%)

Pine forest, 6–10 years of age

Artificial injection of Sr in a watersoluble form into the crowns of trees

90–100Pine forest, 60 years of age

Deposition of radioactive particles lessthan 50 µm in size

80–100Pine forest, 25 years of age

Deposition of radioactive particles lessthan 100 µm in size

70–90

Pine forest, 30 years of age

Deposition of resuspended radioactive
particles

40–60

Birch forest, 40 years of age, winter period

Deposition of resuspended radioactive
particles

20–25

Birch forest, 35–40 years of age, summer period

Global fallout

20–60

Pine forest, 50–60 years of age

Global fallout

50–90

Tropical rain forest

Global fallout

100Over the first few days of radioactive discharges from the accident at the
Chernobyl nuclear power plant, about 70–80% of all the radioactive fallout was
retained by the above ground parts of trees. Over this period, coniferous trees
trapped radioactivity 2–3 times as effectively as did deciduous forests and7–10 times more effectively than other types of natural or semi-natural
ecosystems (meadow, mire) [154].
Over the course of the active growth of trees, ecological half-lives varyfrom 3–4 weeks to 3 months, depending on the type and age of the trees. In
phases of physiological dormancy (autumn and winter), the half-lives are in therange of 4–6 months [154].
7.1.2.

Aggregated transfer factors for soil–tree transfer

The relationship between radionuclide activity concentrations in forest soils
and in trees is influenced by many factors, and thus Tag values are highly variable[155, 156]. The most realistic use of Tag values is for forest systems whereradionuclide fluxes have stabilized (i.e. in the medium to long term after
depositions), and in such cases Tag values remain a satisfactory tool for simple
screening models.

100The aggregated transfer coefficient, Tag, is expressed according to thefollowing relationship:

Tag =activity concentration in tree compartments or forest products Ê Bq kg -1 ˆÁË Bq m -2 ˜¯total deposition to forest floor(31)

Tables 38 and 39 provide available data on the Tag values for radiocaesium
and radiostrontium in foliage and wood as recorded under different ecologicalconditions with varying ages and species of trees. More details, including therelated information sources, are given in the accompanying TECDOC [5].
TABLE 38. RADIOCAESIUM TRANSFER FACTORS (Tag, m2 kg–1, dryweight) TO FOREST TREES
(Measured under apparent steady state conditions)
Species

Wood

Needles/leaves
Range

Geometric mean

Range

2.8×10–4–3.9×10–3

8.6×10–3

5.7×10–4–5.2×10–2

7

—

—

—

1

Spruce1.5×10–3

Fir tree1.2×10–4

Pine

1.7×10–3–4

1.1×10–4–2.1×10–2–4–3

1.0×10–2

2.4×10–4–9.2×10–2

–2

–2

3

2.3×10–3–2.7×10–3

3

Oak

8.6×107.2×10–4

Birch

9.4×10–4–4–3

2.4×10 –3.8×10

8.7×10–3

2.8×10 –3.0×10

2.5×10

–5

–5

–5

–2

—

1.1×10 –3.8×10

1.2×10

1.8×10–4–1.6×10–3

2.5×10–3

1.0×10 –6.8×10

22

–2

Beech
WillowN

Geometric mean

1.1×10 –1.2×10
–3

2×10

–2

3
4

TABLE 39. RADIOSTRONTIUM TRANSFER FACTORS (Tag , m2 kg–1, dryweight) TO FOREST TREES
(measured following the Chernobyl (1991–1992) and Kyshtym (1966–1972)
accidents; main reference: [157])
Species

Wood

Needles/leaves

Geometric mean

Range

Geometric mean

Range

N

Alder

9.5×10–4—

5.7×10–3—

Fir tree

4.4×10–3—

1.3×10–2

—

1

Pine

1.6×10–3

5.7×10–4–1.0×10–2

4.9×10–3

1.5×10–3–3.0×10–2

5

Oak

1.3×10–3

4.7×10–4–2.8×10–3

4.2×10–3

1.9×10–3–1.0×10–2

3

–3

Aspen

2.1×10Birch

2.4×10–3–2—

1.7×10

5.8×10–4–6.2×10–3

1.8×10–2

1—

1

4.3×10–3–7.8×10–2

5101

7.2. RADIONUCLIDE TRANSFER TO MUSHROOMS
Uptake of radionuclides by mushrooms is also commonly quantified using
the aggregated transfer coefficient, Tag, because of the difficulty of knowing theexact location within the soil, both vertically and horizontally, of theradionuclides being absorbed. The transfer coefficients to mushrooms are highlyvariable (3–4 orders of magnitude). This variability arises for several reasons:
(a)
(b)
(c)

The intensity of caesium transfer is highly dependent on the species.
The mycelium depth determines the contamination chronology.
The type of mushroom can affect the degree of caesium transfer.

Saprophytic mushrooms develop on decomposing materials in the surface
layers of a soil, and thus these kinds of mushroom will be contaminatedimmediately following the deposition. Transfer coefficients will subsequently
decrease as the deposit migrates deeper into the soil. Symbiotic or mycorrhizal
mushrooms live in a mutually beneficial association with trees. Most of the edible
mushrooms are symbiotic and can be at their most contaminated in the medium
and long terms after deposition. Parasitic mushrooms develop at the expense of
the host trees. Very few are edible, and their radionuclide concentration isdependent on the degree of host tree contamination. Parasitic mushrooms tend to
be characterized by low transfer coefficients.
The majority of the information available addresses 137Cs (Table 40);
however, such data are also available for some other long lived radionuclides,
although to a lesser extent (Tables 41, 42). In Tables 40–42, it is assumed that the
average dry matter content of mushrooms is equal to 10%. More accurately, thedry matter content of mushrooms varies from around 5 to 15%, depending on thespecies and weather conditions [160].
Aggregated transfer factors are presented here for edible species ofmushrooms that contribute directly to human radiation doses. Data for ‘nonedible’ mushroom species, details of the relevant studies and the full set ofreferences containing the data presented here are given in the accompanying
TECDOC [5].
Some authors have used the conventional soil to plant transfer factor toquantify radionuclide absorption by mushrooms, especially for naturalradionuclides. These data are presented in the accompanying TECDOC [5].
Changes in the contamination of mushrooms over time reflect thebioavailability of radionuclides in the various relevant nutrient sources used bydifferent species. Figure 1 indicates the tendency of a slow decrease of 137Cs inmushroom contamination during the 1990s.

102TABLE 40. AGGREGATED TRANSFER FACTORS FOR 137Cs IN EDIBLE
MUSHROOMS (m2 kg–1, dry weight)
Transfer coefficient(m2 kg–1, dry weight)

Type ofmushroom

Mushroom species

GMa

Range

N

–4

Agaricus (arvensis, campestris, silvatica)

Humus saprophytic

0.005

5×10 –0.01

3

Agrocybe (aegerita)

Saprophytic

0.1

—

1

Amanita (rubescens)

Symbiotic

0.2

0.03–4

4

Armillaria (mellea)

Parasitic/xylophyte saprophytic

0.04

1×10–4–1×10–1

4

Boletus (aestivalis, appendiculatus, edulis)

Symbiotic

0.08

4×10–3–1.4

10Cantharellus (cibarius, lutescens, pallens,tubaeformis)

Symbiotic

0.3

0.015–1.5

10

Clitocybe (gibba or infundibuliformis)

Litter saprophytic

0.6

—

1

Coprinus (comatus)

Saprophytic

0.005

4×10–4–0.015

1

Cortinarius (praestans)

Symbiotic

0.02

—

1

Craterellus (cornucopioides)

Symbiotic

0.03

—

1

Hydnum (repandum)

Symbiotic

0.4

—

1

Hygrophorus (sp.)

Symbiotic

2—

1

Kuehneromyces (mutabilis)

Saprophytic

0.3

—

1

Laccaria (amethystea, laccata, proxima)

Symbiotic/humus saprophytic5

2.0–8.1

5Lactarius (deliciosus, deterrimus, lignyotus,
necator or turpis, porninsis, torminosus)

Symbiotic

0.7

8×10–4–6.0

7

Leccinum (sp., aurantiacum, rotundifoliae,
scabrum, versipelle)

Symbiotic

0.2

8×10–4–1.1

11

Leucoagaricus (leucothites) or Lepiota(naucina)

Humus saprophytic

0.1

—

1

Macrolepiota procera

Humus saprophytic

0.006

7×10–5–4×10–2

3

Lepista (nuda, saeva)

Litter saprophytic

0.01

2.5×10–4–0.1

3

Lycoperdon (perlatum)

Humus saprophytic

0.04

0.003–0.07

2

Oudemansiella (sp.)

—

0.1

—

1

Rozites (caperatus)

Symbiotic

2.3

0.4–8

7

Russula (sp., erythropoda)

Symbiotic

0.5

0.03–4.2

6

Sarcodon (imbricatum)

Symbiotic

0.03

—

1

Suillus (elegans or grevillei, luteus, variegates)

Symbiotic

0.7

0.07–3.0

7

Xerocomus (badius, chrysenteron,subtomentosus)

Symbiotic

1.2

2×10–3–7.0

13a

GM: Geometric mean.

TABLE 41. MEAN AGGREGATED TRANSFER FACTORS FOR 90Sr IN
MUSHROOMS (m2 kg–1, dry weight) [158]Mushroom species

Type of mushroom90

Sr transfer coefficient [158]

Boletus edulis

Symbiotic

6×10–3

Boletus appendiculatus

Symbiotic

5×10–3Cantharellus cibarius

Symbiotic

6×10–3103

TABLE 42. AGGREGATED TRANSFER
MUSHROOMS (m2 kg–1, dry weight) [159]Mushroom species

Type of mushroom

FACTORS
N

Mean
–5

FOR

Pu

IN

Range

Armillaria mellea

Parasitic/xylophyte saprophytic

1

9×10

—

Boletus edulis

Symbiotic

4

3×10–4

1.4×10–4–4.5×10–4

Symbiotic

1

2×10–2—

Humus saprophytic

2

4×10–4

3.2×10–4–5.7×10–4

Suillus luteus

Symbiotic

1

9×10–4—

Xerocomus badius

Symbiotic

6

1×10–3

8×10–5–0.038

Xerocomus badius
Russula paludosa
Suillus luteus
Cantharellus cibarius
Boletus edulis137

Cs activity concentration (Bq kg–1, dry weight)

Cantharellus cibarius
Macrolepiota procera

FIG. 1. Cs-137 activity concentrations (Bq kg–1, dry weight) in selected mushroom species.
Cs-137 soil deposition at the site in 1986 was around 555 kBq m–2 [161].

7.3. RADIONUCLIDE TRANSFER TO BERRIES
Uptake of radiocaesium by forest berries is high in comparison with uptake
by foodstuffs grown in agricultural systems. Aggregated transfer factor values forradiocaesium in different berry species are given in Table 43.

104

TABLE 43. AGGREGATED TRANSFER FACTORS FOR RADIOCAESIUM
IN BERRIES (m2 kg–1, dry weight) [162]
Berry species

N

Arithmetic mean

Range

Bilberry (Vaccinium myrtillus)

952

0.05

0.002–0.3

Cowberry (Vaccinium vitis-idaea)

170

0.03

0.005–0.1

Cranberry (Vaccinium oxycoccus)

65

0.12

0.003–0.2

Cloudberry (Rubus chamaemorus)

45

0.1

0.008–0.15

Raspberry (Rubus idaeus)

241

0.03

0.005–0.1

Blackberry (Rubus fruticosus)

686

0.02

0.005–0.07

Wild strawberry (Fragaria vesca)

466

0.004

0.002–0.007

Data on 90Sr transfer to berries in areas affected by the Chernobyl accident
are more limited than those for 137Cs. The only available information was for
1992–1993 and 1999, with reported Tag values of (7.1 ± 4.1) × 10–3 m2 kg–1 and(9.2 ± 3.0) × 10–2 m2 kg–1 to bilberry and wild strawberry, respectively [163].
After the Chernobyl accident, the evolution of the 137Cs content in all plantorgans of all berry species shows a clear decreasing trend. The mean effective
half-life (T eff ) for 137Cs in berries calculated for the period from 1991 to 2006 is
close to 10 years for most of the berry species [164].

7.4. RADIONUCLIDE TRANSFER TO GAME
7.4.1.

Factors affecting transfer values

Radionuclide activity concentrations in meat depend strongly on thefeeding habits of the animal. Variability in contamination of game arises due to:
(a)
(b)

(c)

Heterogeneous deposition of radionuclides onto forests and associatedterrain.
Different dietary composition and feeding behaviour of game species. For
example, some species can utilize produce from neighbouring cultivatedareas or can be reared with additional feed (e.g. brown hare, moose,pheasant).
Seasonal variations in diet and/or feeding behaviour (e.g. roe deer, wildboar, reindeer, moose).

This variability means that the use of a single aggregated transfer
coefficient may substantially underestimate or overestimate radionuclide activity
concentrations in the muscles of game. To address such variability, more105

emphasis has been given in this section to the changes in transfer with habitat andover time.
Annual game bags are often reported as numbers of animals. For regional
assessments of human ingestion dose via game meat, the edible fraction ofcarcass weight is needed (see Appendix I).
7.4.2.

Aggregated transfer coefficient and half-life values in game andreindeer

Consumption of game meat from natural and semi-natural areas by thegeneral population is low, but groups such as hunters may consume relatively
large quantities, which can add up to critical dose levels. Early reports described
relationships between radionuclide concentrations or amounts in precipitation,soil and animals, and their intake by humans [165, 166]. A review of studies
conducted before and after the Chernobyl accident on the transfer ofradiocaesium to ruminants provides an overview of such information for thatradionuclide [167]. A general review of the parameter values for radionuclidetransfers from soil to game provided for TRS-364 is given in Ref. [3]. The
updated aggregated transfer factors in game are presented in Table 44. The rangeof the mean values of Tag (3 × 10–4 – 0.10 m2 kg–1, fresh weight) represents typicalgame animals hunted for food for humans and the variability in the compositionof feed. Data for game species, details of the relevant studies and the full set ofreferences containing the data presented here are given in the accompanying
TECDOC [5].
Roe deer (Capreolus capreolus) consume a wide variety of herbs andgrasses, as well as fungi when they are available. Radiocaesium levels in roe deer
peak in August and September when fungi are abundant, causing a seasonal
contamination pattern. Geometric mean values of Tag for roe deer from Austria,
the Czech Republic and Germany are given in Table 44. Radiocaesium activity
concentrations in roe deer respond quickly to changes in the ingestion rate ofradiocaesium, because the biological half-life in muscle is generally less than one
month (reported values vary between 10 and 35 days [5]). All mammals exhibit
fast and slow components of retention. A typical value for the fast component is
1 day for all mammalian species, although this typically relates to only about 10%of the retained activity. It was found that the interspecies variation in the half-lifeof the long term component of retention is determined by body mass, as
discussed, for example, in Ref. [168]. Ecological half-lives of roe deer meat vary
between 6 and 13 years. Soil properties have a significant influence (e.g. organic
matter fraction in peat or spruce forest).
Red deer (Cervus elaphus) in Central Europe are for the most part managed
game and live in deciduous or mixed forests. Few data exist concerning the time106

TABLE 44. AGGREGATED TRANSFER COEFFICIENT (m² kg–1, fresh
weight) FOR 137Cs FROM ACCUMULATED DEPOSITION IN GAMEMEAT AND MEAT OF SEMI-DOMESTICATED REINDEER (based on post-Chernobyl data, representing typical game meat consumed overthe hunting season)
Species or group of game animals

Range of geometric mean values–3

Number of references

Roe deer (Capreolus capreolus)–2

5×10 –5×10

8

Red deer (Cervus elaphus)

1×10–2–5×10–2

4

Wild boar (Sus scrofa)

5×10–4–2×10–1

3

Range of arithmetic mean values
Reindeer (Rangifer tarandus), Aug.–Sept.

0.04–0.35

2Reindeer (Rangifer tarandus), winter0.06–0.84

7

Moose (Alces alces), adult

0.010–0.016

6

Moose (Alces alces), calf

0.013–0.02

6

GMa

GSDb

White-tailed deer (Odocoileus virginianus)

0.03

1.5

1

Arctic hare (Lepus timidus)

0.03

2.2

1

Brown hare (Lepus europaeus)

0.009

1.6

1

Pheasant (Phasianus colchicus)

3×10–4

1.3

1Forest birds

0.014

2.0

Waterfowl (freshwater)
1986
1988
1989
a
b

1
1

0.013
0.005
0.002

3.8
5
3

GM: Geometric mean.
GSD: Geometric standard deviation.

dependence of the aggregated transfer coefficient value with respect to 137Cs in
red deer (Table 44). Ecological half-lives of 137Cs in red deer range from 5 to18 years; for 90Sr in antlers, values of about 22 years are reported. Geometricmean values of Tag for red deer from Austria, the Czech Republic and Germany
are given in Table 44.
Chamois (Rupicapra rupicapra) feed on grass and shrubs in summer and on
buds and lichen in winter. Tag values for chamois are not reported in the literature;
however, ecological half-lives in the range of 8–26 years are mentioned.
Wild boar (Sus scrofa) feeds over a very large area. Omnivorous, the wildboar changes its diet with the seasons. It is nearly totally herbivorous in spring andsummer, but behaves mainly as a burrower when grass is scarce in winter, feedingon roots, tubers, larvae and earthworms, from which the transfers of caesium arehigher than from green plants. Hence, increased levels of contamination (of theorder of 50%) are usually observed from October to March (see Table 44). Decades
after a contamination event with radiocaesium, the activity concentration in wild107

boar can be very high, and it can even show no decline over time because of thespecial feeding habits of wild boar. Geometric mean values of Tag for wild boar
from Austria, the Czech Republic and Germany are given in Table 44; minimum
values are valid for birch forests, maximum values for spruce forests.
Moose (Alces alces) is mostly hunted in boreal forests, and winterconditions inevitably change its diet and metabolism. The pastures of moose insummer and autumn largely determine the intake of 137Cs in the months
preceding hunting. Regional soil types are reflected in the Tag values, and thepost-Chernobyl decrease in these values has been almost negligible in Northernareas (Table 44), while a small decreasing trend has been observed in part ofCentral Europe. Overall, the bioavailability of radiocaesium in ecosystems
grazed by moose seems to be rather constant, with no obvious reduction inradiocaesium activity over time other than that due to the caesium’s physical halflife, which therefore determines the effective half-life [167, 168]. However, data
for moose, or elk, from Poland show a gradual decline in 137Cs activity
concentrations during 1986–1991, thus implying the existence of processes that
reduce the bioavailability of 137Cs in soil in regions south of the boreal forest
zone [5].
Among the species or groups of small game, the Tag values for 137Cs werehighest for Arctic hare (Lepus timidus), which is also hunted in winter, when barkand branches of trees are its main source of food. Brown hare (Lepus europaeus)
and particularly pheasant (Phasianus colchicus) feed off cultivated land, reflectedby the low Tag values. The group of forest birds characterized by consistent longterm Tag values comprises a mixture of species. For the group of waterfowl from
freshwater ecosystems, the Tag values for 137Cs decrease exponentially over time,corresponding to an ecological half-life of 1.1 year during the first few years after
the contaminating deposition. The 10–11 day biological half-life of 137Cs in red
grouse (Lagopus lagopus) was obtained for captive birds.
The seasonal composition of reindeer feed explains why the 137Csconcentration in reindeer meat during summer and early autumn is only 10–20%(or less) of the winter concentration. Since the Chernobyl accident, the ecologicalhalf-life of 137Cs in reindeer meat has ranged from 3 to 17 years; where fast andslow components have been estimated, the ranges were 1–3 years and
16–18 years, respectively. Estimates of ecological half-lives reveal a significant
dependence on the type and condition of pastures, as well as a need to consider
seasons, with their specific Tag values. Values for the biological half-life ofradiocaesium in reindeer are given as a fast component (1 day), and a season
dependent slow component (ranging from 18 to 33 days).

108

7.5. APPLICATION OF DATA
The transfer of radionuclides to game and the rate of activity reduction,
given as the ecological half-life, reflect the soil and pasture conditions. Forests intemperate and boreal regions differ by soil type and vegetation, and a faster
decline of activity concentration in muscle often occurs in deer in temperatezones.
The parameter most widely used to quantify radionuclide transfers to wild
foodstuffs in forests is the aggregated transfer coefficient. This simplified
approach is adopted because of the complexity of transfer pathways in forests.
Unlike domestic animals, game animals have diets that are difficult to identify
because they vary between locations and between seasons. Edible fungi are an
ecologically complex group of organisms that obtain their nutrition in widelydifferent locations. Similarly, understorey plants producing edible berries canhave complex root distributions, making it difficult to understand exactly where
they absorb radionuclides in the soil profile.
The simplicity of the Tag approach may lead to inappropriate application of
Tag values in dose assessment calculations. Tag values should only be used in
calculations for forest systems in which radionuclide fluxes have stabilized, thatis, in the medium or long term after depositions. Where effective or ecologicalhalf-life data are available, Tag values should not be considered to be constantover time. Finally, in all cases, Tag values should be considered as a means ofcarrying out screening calculations, rather than as providing a definitive method
for calculating transfers in forests under all conditions. Detailed, site specificdose assessments will require more careful consideration of local transfer
processes, pathways and rates than Tag values can provide.

8. ARCTIC AND ALPINE ECOSYSTEMS
8.1. DEFINITIONS AND PROCESSES
Arctic (or polar) and alpine (upland) areas typically are extensive, andinclude forests, upland areas, polar regions and unimproved pastures (e.g. semiarid steppe). Due to the poor nutrient status of the soils, there is little agriculture
involving crop production other than of herbage for animals. The main foodstuffs
from these areas are wild products collected by humans, such as mushrooms andberries, a variety of game, and semi-domesticated animals including reindeer andother ruminants [5, 169, 170].

109

8.1.1.

Polar regions

Owing to their specific environmental conditions, Arctic ecosystems are
extremely vulnerable to radioactive contamination. Local dietary habits and thehigh utilization of semi-natural ecosystems for local production of foodstuffs maylead to high doses to the local population due to radiocaesium, strontium andpolonium contamination, with significant contributions persisting long after the
initial environmental contamination [171]. These areas are characterized by apronounced diversity of environmental conditions, types of land use and dietary
habits, which lead to high variability both of contamination levels in products andof transfer parameters.
As in other semi-natural environments, the transfer of radiocaesium to foodproducts is higher in polar regions than in intensively cultivated land and persists
long after deposition. This is because, owing to the low temperatures, soilbuilding processes and litter decomposition in Arctic ecosystems are slower,
leading to low pH values and nutrient deficient soils. In general, biogeochemical
processes are slower, and contaminants remain available for biota longer than intemperate environments [5, 169–171].
The lichen–reindeer–human food chain has been the main object of study interrestrial Arctic radioecological research. The high interception by lichen ofradionuclides, particularly radiocaesium and polonium, is one of the key factors
contributing to the high vulnerability of the Arctic food pathway. Lichen
represents the main accessible reservoir of radionuclides in the Arctic
environment, and 65% of the overall radionuclide burden is accumulated in the
top 3 cm of lichen, which is consumed by reindeer [172].
8.1.2.

Upland regions

In upland ecosystems, radiocaesium is efficiently stored in superficial soil
layers and in plant litter; its storage in some areas is caused by the presence ofhigh amounts of fungal biomass (in acid soils) [5, 173]. Deposited radiocaesium
remains available for root uptake by meadow vegetation and can enter thegrass–ruminant–human food chain. Upland regions can have a highsocioeconomic value and serve as the basis for extensive agriculture. In summer,
upland grass pastures are used as free range areas for cows, sheep and goats (milkand meat production) and, to a limited extent, for the production of winter feed
for animals [5]. In this section, data from alpine areas are taken to represent themain features and parameters of radionuclide transfer in upland areas.

1108.1.3.

Application of transfer factors and ecological half-lives

Tag values are highly variable between seasons and years. Similarly, using asingle Tag value for lamb neglects the seasonal pattern of sheep grazing in
Norway (in the winter, sheep are stabled and fed stored feed) and assumes the
exclusive consumption of locally produced feed. However, the slaughter ofreindeer and sheep typically occurs during the autumn and/or winter of a given
year. These temporal variations make it difficult to compare Tag values betweensites for different years [174, 175]. To predict changes over time, Tag values need
to be combined with effective ecological half-lives. When using Tag values, major
sources of variability must be taken into account, in particular [5]:
(a)
(b)
(c)

Variation over time;
Seasonal variability;
Spatial variability and dietary variability of grazing animals.

The reduction of the concentration of radionuclides in both Arctic andalpine ecosystems is commonly described as an exponential decay with aneffective half-life (see Section 2). For the transfer of radionuclides from feed tomilk or the muscles of animals, the parameters Fm (d L–1) and Ff were used, which
are the equilibrium ratio of the activity concentration in milk or muscles to thedaily dietary radionuclide intake (see also Section 6).

8.2. RADIONUCLIDE TRANSFER IN POLAR REGIONS
8.2.1.

Transfer to lichens

Lichens are a major component of the diet of reindeer. They do not have a
rooting system and take up nutrients and associated pollutants from the air andfrom precipitation. The deposited radionuclides are retained by the lichen, and thecontamination level is thereafter reduced through dilution by fresh lichen growth,
removal by grazing and/or leaching. Depending on their physical and chemical
properties, radionuclides may also be translocated to fresh growth. Strontium-90
is more mobile than 137Cs in lichens, and is washed out from lichens more rapidly
than is 137Cs [5]. Table 45 gives examples of mass interception fractions (fl)estimated for lichens on the Kola Peninsula for 1961–1999 [176].
In a situation with deposition onto snow (in winter), lichen will only
become contaminated during snowmelt, with some of the deposited radioactivity
being lost via runoff, effectively decreasing the lichen interception fraction. In
contrast, if radionuclide deposition occurs as a single-pulse dry deposition, the111TABLE 45. 137Cs AND 90Sr LICHEN MASS INTERCEPTION FRACTIONS (fl, dryweight) ON THE KOLA PENINSULA AND ECOLOGICAL HALF-LIVES (T1eco,
T2eco) IN LICHENS
fl (m2 kg–1)

a1a

T1eco
(year)

T2eco(year)

137

Cs

1.4

0.80

2.0

20

90

Sr

0.7

0.72

1.0

20

Radionuclideaa1: The fraction of the initial concentration in lichen declining with the fast loss component.

interception fraction may exceed the annual values. If the season when deposition
occurs and the type of deposition (dry or wet) are not considered, significant
underestimation and overestimation, respectively, can influence radiologicalassessments. Post-Chernobyl studies of radiocaesium in lichens indicate effective
half-lives of 3–6 years [5].
8.2.2.

Transfer to reindeer

The diet of reindeer changes from a summer diet of a wide range of plants
to a lichen based diet during winter. The autumn change towards a more highly
contaminated lichen diet deficient in mineral elements like potassium isaccompanied by a two- to threefold increase in the biological half-life ofradiocaesium from about 7 to about 20 d [177, 178]. All three factors contributesignificantly to the increased winter radiocaesium activity concentrations inreindeer. However, the seasonal variability also depends on the variable
deposition levels in the grazing areas of these nomadic animals. Furthermore, inautumn, reindeer can eat large quantities of mushrooms and attain radiocaesium
levels comparable with those of winter [179, 180]. A review of radionuclide
contamination levels in reindeer and caribou due to fallout from nuclear weapons
testing is presented in the accompanying TECDOC [5]. Some representativevalues from Golikov et al. [176], who analysed 137Cs transfer to reindeer during
winter on the Kola Peninsula (Russian Federation) and in northern Norway in the
1960s, are given in Table 46.
Observed 137Cs concentrations in reindeer in central Sweden and Norway also
indicate that concentrations declined faster during the initial period after the
Chernobyl fallout than later [5], as suggested by a double exponential model. As analternative approach, Åhman [177] divided the time period after the accident into
the first 10 years (years 0–10) and the second 10 years (years 10–20). Analysis ofdata from all herds combined showed that the effective half-life during the first
period was considerably shorter than that during the latter period (Table 47).

112

TABLE 46. INITIAL 137Cs AGGREGATED TRANSFER FACTORS FOR
REINDEER MEAT (Tag(0) m2 kg–1, fresh weight), AND ECOLOGICAL (T1eco, T2eco,
years) AND EFFECTIVE (T1eff, T2eff) HALF-LIVES IN REINDEER MUSCLE [176]
Area

a1a

Tag(0)

T1eco

T2eco

T1eff

T2eff

Kola Peninsula

1.7

0.82

2.0

18

1.9

11.3

Nenets Aut. Okrug

1.2

0.81

1.8

15.6

1.5

10.3

Kautokeino (Norway)

1.8

0.89

1.2

18

1.2

11.3

a

a1: The fraction of the initial concentration in lichen declining with the fast loss component.

TABLE 47. 137Cs AGGREGATED TRANSFER FACTORS FOR REINDEERMEAT IN THE FIRST YEAR AFTER FALLOUT (Tag, m2 kg–1, fresh weight) AND
EFFECTIVE HALF-LIVES (T eff, years) FOR DIFFERENT PERIODS AFTER THE
CHERNOBYL ACCIDENT
(after Åhman [177] and Skuterud et al. [179])
Country and herd

SeasonSweden:September
Vilhelmina norra, OctoberUbmeje, Ran
Nov.–Dec.
Jan.–Apr.
Norway: Østre Namdal,
Vågå
a
b

Tag , 1986–1987
0.11–0.24
0.27–0.39
0.47–0.81
0.92–1.21

September
Nov.–Jan.

a

T eff, years 1–10 T eff, years 10–20

T eff, years 1–20

2.5–3.1
2.1–2.5
2.8–4.8
4.5–7.0

7.6–no decline
11.4–20.6
4.9–6.9
7.5–10.4

4.5–6.7
5.8–7.9
5.0–6.6
5.1–6.8

4.1–4.9
3.9–4.1

No decline
6.6b

9.2–12.4
4.8–5.0

Ranges are given for the individual herds.
The estimate is 6.6 years for both sites, with standard errors of 0.8 and 1.5 years.

More detailed data on aggregated transfer factors and ecological half-livesof 137Cs and 90Sr in reindeer are given in the accompanying TECDOC [5], which
also includes references to studies of 210Po, 210Pb and 226Ra in reindeer andcaribou in Alaska.
8.2.3.

Transfer to ruminants

For animal products in the Arctic other than reindeer meat, radiocaesium
activity concentrations decrease rapidly in the first year after deposition and thendecrease more slowly. Seasonal variations occur, with higher 137Cs and 90Sr
activity concentrations in summer, when cows are put out to pasture or are fed
fresh grass. Tables 48 and 49 provide the available data on Tag values for cow’s
milk (for early and late periods after deposition) as well as appropriate
information on the variability of the effective ecological half-lives in milk. A
compilation of Tag values for lamb meat is given in Table 50.

113

TABLE 48. SUMMARY OF Tag VALUES FOR COW’S MILK (m2 kg–1, fresh
weight) [5]Phase

Region

Early period (Tag (0))
after deposition

Year(s)Fennoscandia and northwest Russian Federation

1.0×10–2

Arctic regions (esp. Norway)

1.0×10–2

Finnmark (Norway)

2.0×10–2

Troms (Norway)

9.0×10–3
1.4×10–2

Nordland (Norway)
1965

7.6×10–3

Lovozero (Russian Federation)

1998–1999

0.24×10–3

Kola region (Russian Federation)

1998–1999

0.15×10–3

Kola region (Russian Federation)

1974–1978

0.14×10–3

Nenets AO (Russian Federation)

1974–1978

0.12×10–3

IcelandLate period
after deposition

Tag

Kola region (Russian Federation)

1978–1985

0.082×10–3

Nenets AO (Russian Federation)

1978–1985

0.062×10–3

Iceland2001–2004

1.1×10–3

TABLE 49. EFFECTIVE HALF-LIVE VALUES (years) FOR 137Cs AND 90Sr
ACTIVITY CONCENTRATIONS IN MILK FROM VARIOUS ARCTIC
AREAS [5, 170, 181]
137

Area

Cs — Global fallout
T

Faroe Islands

eff

137

Cs — Chernobyl fallout

90

Sr — Chernobyl fallout

T1eff

T2eff

T1eff

T2eff
5.2–5.5

1.0–1.8

1.3–1.8

6.5–8.8

1.0–1.4

Finland1.0

0.7–3.4

4.5

1.3

8.4

Norway1.1–1.9—

4.5–6.1

1.5–1.8

4.0–4.6

Sweden1.4–1.8—

6.2–9.1

1.4–3.0

8.5–9.0

8.3. RADIONUCLIDE TRANSFER IN ALPINE ECOSYSTEMS
8.3.1.

Soil to plant transfer in alpine ecosystems

As with other semi-natural systems, the use of aggregated transfer factors isquite effective for assessments of radionuclide transfer in alpine ecosystems. Thisis because the variability of conventional transfer factors is extremely high [182].
Factors influencing this variability include the high variability of microclimaticconditions, the small scale variability of soil properties and the changing
hydrological conditions [182, 183]. The available peer reviewed data for alpine
ecosystems are given in Table 51.

114

TABLE 50.SUMMARY OF INITIAL AND LATE PHASE Tag VALUES FORLAMB (SHEEP) MEAT (m2 kg–1, fresh weight)
Phase

Region

Early period
after deposition(Tag (0))

Late period
after deposition

8.3.2.

Years

Tag

Fennoscandia and northwest Russian Federation

3.8×10–1

Arctic regions (esp. Norway)

1.5×10–1

Finnmark (Norway)

1.6×10–1

Troms (Norway)

6.3×10–1

Nordland (Norway)

1.4×10–1

Northern Sweden

1990–1997

4.7×10–2

Faroe Islands

1990–1997(5.5–2.5)×10–3

Finland1990–1993

0.83×10–3

Iceland1990–1993

1.5×10–2

Norway1990–1993

3.9×10–2

Transfer to ruminants in alpine ecosystems

Table 52 gives the feed transfer coefficients that were determined for milk
from alpine regions with calcareous and silicate bedrock [182–184], along withthose from a lowland region with intensive production for comparison [183].
The feed transfer coefficients for 137Cs in the lowland region are
significantly lower than those for alpine production sites; however, no difference
was found in the feed transfer coeffients for 90Sr. Moreover, no significant
differences were found between milk feed transfer factors on silicate andcalcareous bedrock for either radionuclide.
Considerably longer ecological (or effective) half-lives have been observedin cow’s milk from alpine pastures than in cow’s milk from lowland production
sites. For the period 1988–2006, Lettner et al. [185] derived ecological half-livesof 0.7–1.4 years for the fast loss component and of 9.3–12.7 years for the slow
loss component of 137Cs concentrations in cow’s milk. Allowing for thedifference between ecological and effective half-lives, these values are similar to
those for Arctic environments, discussed below.

8.4. APPLICATION OF DATA
Both the transfer of radiocaesium to game and the ecological half-lives
reflect the soil and pasture conditions in semi-natural environments. The data forboth parameters show considerable variability resulting from seasonality effects,

115

TABLE 51. AGGREGATED TRANSFER FACTORS (Tag, m2 kg–1, fresh
weight) FOR 137Cs AND 90Sr FROM SOIL TO GRASSLAND VEGETATIONIN ALPINE ECOSYSTEMS
Soil type

N

GMa

GSDb

AMc

137

SDd

Minimum

Maximum

Cs

Sand

8

0.014

3.1

0.021

0.015

0.002

0.043

Loam

4

0.003

2.9

0.004

0.006

0.001

0.013

Unspecified

1

0.006

All soils

13

0.008

0.015

0.015

0.001

0.043

0.030

0.018

0.011

0.047

3.7
90

Sr

All soils

3

0.026

2.1

a

GM: Geometric mean.
b
GSD: Geometric standard deviation.
c
AM: Arithmetic mean.
d
SD: Standard deviation.

TABLE 52. TRANSFER COEFFICIENTS TO COW’S MILK (Fm, d L–1) FOR
137
Cs AND 90Sr IN UPLAND ALPINE AREAS
Site

Arithmetic mean

Standard deviation
137

Minimum

Maximum

Cs

Lowland0.00090.0008——

Silicate bedrock

0.00710.00090.00350.0114

Calcareous bedrock

0.00690.00130.0025

0.02

90

Sr

Lowland0.00080.0003——

Silicate bedrock

0.00110.00040.00050.0017

Calcareous bedrock

0.00100.00080.00050.0010small scale heterogeneity in soil and climate parameters, and the specific habitsof free ranging animals. Nevertheless, the use of aggregated transfer factors
seems to be the most practical approach for the prediction of contamination levels
in food products from such environments. Also, the long term development ofradionuclide concentration in foodstuffs can generally be estimated by twocomponent exponential models.
The simplified approach of using Tag values has been adopted because of
the complexity of transfer pathways in semi-natural ecosystems, which may, inturn, lead to inappropriate application of Tag values in dose assessment
calculations. Tag values should only be used in calculations for those semi-natural

116

systems in which radionuclide fluxes have stabilized, that is, in the medium orlong term after deposition. Where effective or ecological half-life data are
available, Tag values should not be considered to be constant over time. Finally, inall cases, Tag values should be considered as a means of carrying out screening
calculations, rather than as providing a definitive method of calculating transfer.
Detailed, site specific dose assessments will require greater consideration of local
transfer processes, pathways and rates than Tag values can provide.

9. RADIONUCLIDE TRANSFERSIN FRESHWATER ECOSYSTEMSRadionuclides dispersed in the environment can be deposited onto the water
surface or onto the surface of the catchment (watershed). Washoff of radionuclides
from the catchment can represent a long term source of radionuclides in freshwater
ecosystems. Once in the water, some radioactivity is typically adsorbed by solid
particles; this partitioning between the solid particles and the water affects bothtransport and biological uptake. Solid particles can settle to the bottom of the lakeor river and be removed from the water column. Radionuclides dissolved in water
can also be adsorbed by the bottom sediments, transferring to the deep sedimentlayers. However, adsorbed radionuclides can also be remobilized, becoming
available again for uptake by freshwater biota. Detailed information on thephysical processes listed above and transfer parameters are provided in theaccompanying TECDOC [5]. Here, information is confined to parameters relating
to availability of radionuclides sorbed to sediments and to data on radionuclidetransfer to freshwater food products.

9.1. FRESHWATER Kd VALUES
The residence time of radionuclides in freshwater streams is strongly
affected by their interaction with suspended particulate matter and by settlementin the sedimentation zones of a water system. The uptake of radionuclides byaquatic organisms depends on the concentration and on the speciation of thoseradionuclides remaining in the dissolved phase. Partitioning of radionuclides
between water and suspended matter is often described in terms of distribution
coefficients, Kds, expressed as the concentration ratio of the particulate phase to117the dissolved phase under equilibrium conditions (in Bq kg–1 of supspended
particulate matter per Bq L–1).
Sorption of radioactivity on natural particles results from several kinetic
processes, involving rapid, but also slow, processes (e.g. oxidation processes,
inner sphere complexation and migration of cations in the clay structure)[5, 186–196]. Kinetics in the interactions of radionuclides at the interface
between the water and the suspended particulate matter depends on the element
under consideration, but also on other environmental co-factors such as thesuspended particulate matter concentration [186, 189, 192], and the ionic strengthand age of the contamination (termed an ageing effect) [186–188].
Desorption kinetics may be highly governed by the inner speciation ofbound radionuclides (i.e. distribution among easily accessible versus lessaccessible binding sites) [190].
For sorption of some radionuclides in freshwater ecosystems, theseasonality effect (and the associated biological activity in the water) is
important. For cobalt or manganese, for example, oxidation processes, which arepartially microbially mediated, govern their slow uptake by suspended particulatematter. Seasonal differences may then reflect strong seasonal variation in theabundance of oxidizing bacteria [190, 196].
The Kd values for all radionuclides were divided into four groups on thebasis of data availability [5], namely, Kd values for radionuclides for whichlarge amounts of data are available, Kd values for radionuclides for which
moderate amounts of data are available, Kd values for radionuclides for which
only single values are available, and Kd values for radionuclides which aremainly the product of expert estimates, primarily given in a review published in1991 [197]. The fourth group of Kd values were also quoted in TRS-364 [3],without clear referencing. The database used to derive values for the present
publication (see Ref [5] for details) contains Kd values in natural freshwater
bodies (rivers and lakes) from suspended particulate matter or superficial
sediment (top 0–5 cm).
In addition, information on potential co-factors and on criteria allowing
estimation of the quality of each referenced datum was collected, especiallyconcerning the following: pH, suspended matter concentration, contact time
between water and particles, method for the determination of Kd values (in situ
measurements or laboratory experiments under adsorption or desorption
conditions with spiked solutions) and redox conditions (especially for iodine).
The methodology for data processing in the case where large amounts of data
were available (Ag, Am, Co, Cs, I, Mn, Pu, Sr) was as follows: (1) construction of
the database with available Kd data and information on corresponding
environmental co-factors; (2) application of quality criteria; and (3)determination of non-conditional and (4) conditional probability density

118

functions by a bootstrap statistical procedure to account for parametric
uncertainty [5]. For the second group of radionuclides (Be, Ba, Ce, Ra, Ru, Sb,
Th), the approach was similar in that steps (1)–(3) were used, but only nonconditional probability density functions were defined (i.e. step (4) was omitted)
to reduce the uncertainty over a given range of values for any parameter. Simple
statistical data processing was applied for the third group of radionuclides, andthe data for the fourth group of radionuclides (Cr, Fe, Zn, Zr, Tc, Pm, Eu, U, Np,Cm) were taken as reproduced in Refs [3, 197].
Reference Kd values with the associated geometric standard deviation are
given in Table 53. The data were obtained from field measurements (“Field”) andlaboratory adsorption (“Ads”) or desorption (“Des”) experiments. Where

TABLE 53. Kd VALUES IN FRESHWATER ECOSYSTEMS (L kg–1)
N

GMa

GSDb

Minimum

Maximum

91
41

4

9.5  10
4.4  105

2.3
1.7

4

2.2  10
1.9  1055Ag

3.3  101.0  106

Ads
Des

Am

99
42

2.1  105
1.2  105

3.7
5.7

2.5  104
6.9  103

1.9  106
2.0  106

Ads
Field

Ba

49

2.0  103Be

Element

Data origin

3.6

2.5 × 102

1.6 × 104

Various29

4

4.2  103.6

3

5.1 × 10

3.4 × 105

VariousCe

15

2.2  105

2.9

4.2 × 104

1.2 × 106

Various

Co

534
74
29

4.3  104
4.9  105
4.4  104

9.5
4.9
3.9

1.1  103
3.5  104
4.9  103

1.7  106
6.6  106
3.9  105

Ads
Des
Field

Cs

569
119
219

9.5  103
2.9  104
2.9  104

6.7
2.4
5.9

3.7  102
6.9  103
1.6  103

1.9  105
1.2  105
5.2  105

Ads
Des
Field

I

124

4.4 × 103Mn

14

5.9 × 101

3.4 × 105

Adsc

190
46
17

5

1.3  10
6.9  105
7.9  104

12
6.6
1.9

3

2.1  10
3.2  104
3.1  1046

7.4  10
1.5  107
1.9  105

Ads
Des
Field

Pu

37
41
79

7.9  104
3.0  105
2.4  105

2.2
4.2
6.6

2.1  104
2.9  104
1.1  104

2.9  105
3.2  1065.2  106

Ads
Des
Field

Ra

75

7.4  103Ru

3.1

1.1 × 103

5.2 × 104

Various74

4

3.2  101.9

4

1.1 × 10

9.3 × 104

VariousSb

23

5.0  103

3.9

5.5 × 102

4.6 × 104

Various

Sr

156
34
13

1.9  102
6.2  102
1.2  103

4.6
2.1
2.7

1.4  101
1.9  102
2.3  1022.2  103
2.1  103
6.3  103

Ads
Des
Field

Th

63

1.9  10521

1.2 × 103

2.7 × 107

Variousa

GM: Geometric mean.
b
GSD: Geometric standard deviation.
cGiven for oxic conditions.

119

appropriate, separate Kd values are presented for these three types ofmeasurement.
Information related to additional elements (i.e. Cr, Fe, Zn, Zr, Tc, Pm, Eu,
U, Np, Cm) is given in Table 54 and reported in TRS-364 [3]. These values are
based on a single publication [197] and must be used with caution.

9.2. TRANSFER TO FRESHWATER BIOTA
Although it is generally recognized that accumulation of radionuclides byedible aquatic organisms is a dynamic process, many bioaccumulation models
assume that the aquatic organisms are in equilibrium with reference media, suchas water or sediments, in their surrounding environment. As a result, radionuclide
accumulation in aquatic biota is often represented by simplified ratios that relate
radionuclide concentrations in biotic tissues to concentrations in the reference
media [5, 198–200].
The steady state models can be subdivided into two categories on the basisof the chemical behaviour of a given radionuclide and its associated transfer
processes to edible biotic tissues. These categories are: (1) models that are basedon simple radionuclide partitioning between organisms and reference phases(such as surface water or sediments); and (2) specific activity models, whichassess partitioning of radionuclides relative to stable analogues in the body [5].

TABLE 54. GROSS AVERAGE Kd VALUES IN AQUEOUS SYSTEMS(L kg–1) [3]Element

Expected value

Minimum

Maximum

Cr

Low

—

—

Fe

5.0×103

1.0×103

1.0×104

Zn

5.0×102

1.0×102

1.0×103

Zr

1.0×103

1.0×103

1.0×104Tc

5.0×100bPm

5.0×103

1.0×103

1.0×104Eu

5.0×102

2.0×102

9.0×102

5.0×101

2.0×101

1.0×103

1.0×101–1

1.0×102

5.0×1031

7.0×104

U
Np
Cm
a
b

Reproduced according to Ref. [3].
n.d.: Not detectable.

120

a

n.d.

2.0×10

1.0×102

1.0×109.2.1.

Concentration ratios

Depending on the radionuclide uptake pathway being considered, a numberof representations of partitioning can be defined. These include: (1) theconcentration ratio (CR), which is the ratio of the radionuclide concentration inbiota (Cb) from all exposure pathways (including water, sediment andingestion/dietary pathways) on a per unit tissue fresh weight basis to that in water(Cw); and (2) the biota sediment concentration ratio (CRs-b), which is the ratio of
the concentration of a radionuclide in an organism (Cb) on a fresh weight basis to
the radionuclide concentration (fresh weight) measured in the sediment (Csed).
Fresh weight to dry weight ratios for selected aquatic organisms are given in
Table 87 in Appendix I.
CRs-b is appropriately derived from studies in which only the sediment iscontaminated, where the contribution of sediment associated radionuclides can beof particular importance with respect to radionuclide uptake by benthic species.
Most contaminant transfer factors in the literature do not distinguishbetween uptake pathways, and therefore represent CR values (also called thebioaccumulation factor, BAF). Water to biota values from the literature have been
compiled for radionuclides and their stable analogues, and are listed inTables 55–58; sediment to biota concentration ratios (CRs-b) are provided inTables 59 and 60 (largely based on the data from Refs [198, 199]). Additional
information on tissue specific radionuclide transfer factors can be found in theaccompanying TECDOC [5].
In general, CR and CRs-b values for stable elements are conservative whenused to represent radionuclides with relatively short radiological half-lives andrelatively long biological half-lives, since physical decay of short lived
radionuclides can significantly reduce their concentration in biota tissues [203].
To account for this, CR and CRs-b values can be multiplied by a factor K that
accounts for the radionuclide specific half-lives, as described by:K=

lb
lb + l r(32)

where λb is the biological decay constant (0.693 tb–1 (d–1)); λr is the radioactive
decay constant (0.693 tr–1 (d–1)); tb is the biological half-life (d); and tr is theradiological half-life (d). For screening purposes, a tb of 30 d (or a λb of 0.023 d–1)
can be assumed [203].
Details outlining how these transfer factors were defined can be found in
the accompanying TECDOC [5].

121TABLE 55. SUMMARY OF CONCENTRATION RATIOS (CR) FOR EDIBLE
AQUATIC PLANTSa (L kg–1, fresh weight)
N

Meanb

16

3

3.7×10

9.3×1010

4

1.6×101

1.5×10Cd

54

1.9×100Cm1

9.0×103

Co

19

Cs

Element

GSDc

Minimum

Maximum

7.5×100

3.9×104

4.4×101

9.9×104

6.9×101.1×104

2.3×104

—

n.a.d

n.a.

7.1×102

5.1×100

5.0×101

2.0×10426

9.7×101

1.6×101

1.9×100

3.3×10353

3.0×102

3.2×10

2.4×103

3.6×103

53

9.1×100

1.9×105.2×103

1.5×10432

1.3×100

3.7×10

7.9×101

2.7×1026

4

1.2×102

7.2×10

3.1×10–1

1.5×105Ni

52

7.7×102

1.3×10

2.5×102

1.1×103Np2

7.2×103—

6.5×103

9.0×103Pb

5

1.9×103

7.6×101

1.3×1032.2×103Pu

40

2.6×104

1.4×101

1.2×102

4.9×10793

2.9×100

4.1×10

6.4×102

1.1×10492

2.9×100

2.0×10

7.4×101

6.7×10231

3

1.4×100

5.4×10

9.4×100

9.2×103172

4.1×100

3.3×10

3.9×101

1.9×103Tc

90

5.5×100

4.9×10

2.9×10–1

9.9×101U

4

2.1×102

1.9×100

9.1×101

5.2×102Zn

5

2.1×104

1.3×101

1.4×104

2.7×104

Am
C

Cu
Fe
I
Mn

Ra
Ru
Se
Sr

0

a

All types of aquatic plant are included in the assessments.
For N = 2, the mean is the arithmetic mean.
GSD: Geometric standard deviation.
dn.a.: Not available.
bc

TABLE 56. SUMMARY OF CONCENTRATION RATIOS (CR) FOR FRESHWATER INVERTEBRATES (L kg–1, fresh weight)
Element
Ag

N

Meana

2

2.3×102
3

GSDb

Minimum

Maximum

1.3×102

3.3×102

3.1×103

3.7×103

5.9×101

9.0×104Al2

3.4×10Am

17

2.4×103As2

1.5×103

1.0×103

2.0×103Au2

1.4×103

1.0×103

1.5×10322

1.4×101.1×102

1.6×1022

3

1.3×107.2×102

1.9×10324

4

6.5×10

1.3×104

5.7×105

31

3.4×101.2×101

6.6×101

Cd

149

2

1.0×10–2

3.1×104Ce2

4.3×102

2.9×102

5.6×102

Ba
Br
C
Ca

122

7.0×100

2.6×100

2.5×100

3.9×101

1.4×10TABLE 56. SUMMARY OF CONCENTRATION RATIOS (CR) FOR FRESHWATER INVERTEBRATES (L kg–1, fresh weight) (cont.)
N

Meana

2

2

1.6×1029

1

2.2×10Cr

2

2

3.0×10Cs

29

2.3×101

Cu

92

4.2×101Cm

2
2

2.2×102

3

2.0×102

3Element
Cl
Co

Eu
Fe
Hf
Hg

GSDb

Minimum

Maximum2

1.9×102-3

4.1×1042

3.9×102

7.5×101

5.4×10-3

6.1×103

1.1×101

5.6×101

1.4×103

9.5×103

9.0×103

1.0×1042

2.0×102

2.3×102

1.9×103

2.1×103
1.5×103

1.4×102

1.3×10
1.3×102

1.9×102.1×10

1.3×103

2.7×100

2.0×102

5.2×103

1.1×101-1

1.3×10331

7.5×10I

991

1.7×10K

2

5.9×102

5.4×102

6.1×102La2

3.5×102

3.3×102

3.7×102Lu1

1.1×103Mg

2

3.2×101Mn

4

2.1×10133

4.5×10–1

3.4×10

0
3

Mo
Na

4

—

4.0×10——2.1×101

4.3×101

3.9×102

1.1×10–1

3.7×103

1.3×101–2

3.0×103

3.6×101–1

1.4×101.1×1023

1.0×104

2.9×10Np

2

9.5×10Pb

79

2.2×101

2.0×101

4.5×10–2

7.0×102Pu

100

7.4×103

2.9×101

3.6×10–1

5.5×106Ra

5

1.0×102

3.0×101

1.9×100

1.9×1032

3

3

2.2×103–3

1.9×10

9.3×101

7.4×101

3.5×102

3.3×103

3.7×103

1.2×101

6.9×104

5.0×102

2.7×103

Rb
Ru
Sb

9

9.0×10

2.0×10
3.9×10–2

1.9×102.1×101

2

2

2.1×102

3

3.5×10Se

162

5.7×10Sm2

1.6×103Sr

5

2.7×102

3.2×100

7.7×101

1.3×103Tc

10

2.6×101

9.9×100

1.9×100

4.0×1022

3

2.9×10

2.9×103

2.9×10392

1.7×10

3.6×100

6.0×10422

3.9×10

3.6×102

4.0×10292

1–2

1.5×103

Sc

Th
U
V
Zn
a
b

9.2×10

1.5×10

1.9×10
2.9×10

1

1

1

6.3×10For N = 2, the mean is the arithmetic mean.
GSD: Geometric standard deviation.

123

TABLE 57. SUMMARY OF CONCENTRATION RATIOS (CR) FOR
FRESHWATER FISH TISSUES (L kg–1, fresh weight)
Whole body
Element

MuscleMinimum

Maximum

N

Meana

GSDb

23

1.1×102

1.3×100

5.7×101

1.9×102Al

931

6.6×10

7.1×10

0

0

3

Am

n.a.c

n.a.

n.a.

Ag

n.a.

27

1.1×102

1.5×100

4.0×101

2.1×1025.2×10311

5.1×1000

3.0×102n.a.

2

2.4×1027.2×101

4.0×102152

3.3×10

5.0×101

9.5×1022

5.0×101

9.0×1022.3×10
2.3×100

5.0×101

2.1×100

17

2.4×10

4.7×10

1.7×100

5.0×1002

2.2×10111

01.2×10

3.3×10

0–2

1.6×1022.3×100

1.5×101

7.9×10215

5.3×10

3.2×101

9.1×101

2.3×100

1.9×101

n.a.

n.a.

n.a.

n.a.

n.a.

3.7×1026

4.0×105

2.9×100

1.9×105119

1.0×103

3.4×100

9.4×101

5.6×103

3.2×106104

1.2×101

2.5×100

2.0×100

901

1.2×10

2.7×100

3.0×1002

9.7×101711

2.5×10

9.5×100

9.0×101

1.1×10371

9.5×10

1.6×100

2.5×1012

1.2×103

161

4.7×102.2×100

9.9×100

2.3×10119

2

4.0×10

1.6×100

2.3×101

3

1.2×102651

7.6×10

2.4×100

9.0×100

2.4×1051

2

2.1×102×10

03.5×101

2

5.6×10257

1

4.0×100

1.3×101

7.6×10Cs

145

3

3.0×10

2.6×100

7.5×101

4

1.2×1022.4×10106

3

2.5×10

2.4×100

1.4×102

Cu

102

2.7×102

1.5×100

9.6×101

1.5×104

1.2×10396

2.3×102

1.7×100

9.9×101Dy1

3.0×102—7.2×102——2

6.5×102

2.0×102Eu

53

1.5×102

1.1×103

3.2×100

7.6×100

2.2×10324

1.3×102

4.9×100

1.1×101114

2

7.2×102

5.7×100

1.6×101

3

5.3×1096

2

1.7×10

6.9×100

6.6×100

1.4×1020

3

2.0×103

3.2×100

3.0×102

4

2.9×1010

3

1.1×10

1.9×100

3.3×102

2.1×1020

3

2.0×1032.2×100

1.1×103

4

2.2×1014

3

1.9×100

1.9×103

4.5×1094

2

1.7×104

2.1×100

1.0×102

4

4.5×1050

3.0× 102.5×100

1.1×101

6.5×10K

120

3

4.0×102

4.0×10

2.0×100

5.7×102

4

1.5×1097

3

3.2×10

1.6×100

1.2×103

La102

9.0×103

1.6×101

3.2×100

3.6×100

3.4×10274

3.7×101

4.9×100

1.1×100

Mg

6.6×102111

1.1×102

3.0×100

1.4×101

4.3×10296

3.7×101

2.2×100

7.9×100

Mn

1.9×102110

4.5×102

4.0×100

4.9×101

7.0×10397

2.4×102

6.7×100

1.3×101

1.4×105

911

2.7×10

1.9×100

2.1×1002

1.9×1064

01.9×102.1×100–3

4.0×10

2.0×101422

1.4×102.1×100

3.4×101

2

6.0×10

971

7.6×10

3.0×100

1.7×101

6.1×102241

2.1×100

1.9×101

2

51

2.1×10

1.9×100

1.1×101

4.4×10139

5

1.4×101.1×100

1.2×105

1.7×105

1

0

–1

13

2

2.9×10

Ba

92

1

Br

37

C
Ca

Au

Ce
Cl
Co
Cr

Fe
Hf
Hg
I

Mo
Na
Ni
P

n.a.

7.1×10n.a.

n.a.

1.0×103

1.0×10

n.a.

n.a.

92

3.7×10

3.0×10

5.7×1039

2.5×10

2.9×10

1.0×10

2.7×102

n.a.

n.a.

n.a.

n.a.

n.a.

5

3.6×101

4.3×100

6.0×100

1.7×102

Pu

n.a.

n.a.

n.a.

n.a.

n.a.

3

2.1×104

2.6×100

7.7×103

5.0×104Ra2

2.1×102

1.6×1022.5×10221

4.0×100

6.9×100

6.0×10–2 1.5×102

Rb

113

6.1×103

1.2×103

1.6×10392

4.9×103

1.7×100

1.0×103

1.4×1042

1

5.5×10

1.0×101

1.0×102201

3.7×10

1.9×100

3.6×1022

3.3×101

7.3×102

3.5×103

9.4×103

Sb

n.a.

n.a.
1

n.a.

9.9×10
3.6×100

6.7×101

14

1.9×10

6.9×10

1.3×100

3.6×103

4

1.2×1014

3

1.9×1022.2×100

2.2×101

7.1×10299

7.5×102

2.6×100

9.0×101

2.4×10311

7.1×1030

2

9.3×10

Se

29

3

Sr

116

Tb

19

124

n.a.

3

0

37

Sc

1.6×100

5.9×10

1

1

Po

n.a.

0

6.6×10

6.1×10

2×10

Pb

Ru

2

9.1×10

5.9×102.1×10

3.9×103

3.9×10

0

33

1

GSD

Maximum

Mean

0

As

2

4.5×10

MinimumN

4.7×100

6

9.3×104

3.7×10

4.5×100

2.1×100

6.0×10

1.3×100

2.9×100

3.9×100

1.4×10–1 6.9×101

4.1×102

1.9×100

2.0×102

1.7×103

TABLE 57. SUMMARY OF CONCENTRATION RATIOS (CR) FOR
FRESHWATER FISH TISSUES (L kg–1, fresh weight) (cont.)
Whole body
Element

Muscle

N

Meana

GSDb

Minimum

9

4.2×102

1.5×100

2.2×102

9.9×102Th

2

2

1.9×10

1

3

Ti

30

3.7×102

1.9×100

1.2×102Tl

91

5.9×102

1.9×100

U2

2.4×100

V

103

2.9×102121

3.1×10114

3

4.7×10

9

1

Te

Y
Zn
Zr
a
b
c

9.5×10Maximum

GSD

Minimum

1.5×100

9.6×101

2.1×102—

6.0×100

6.0×100

1.4×100

1.1×102

3.5×102

9.0×102

2.6×100

6.6×101

1.0×104

99.6×10–1

12×100

2.0×10–2 2.0×101

91

9.7×101

1.9×100

1.0×101

2.4×102191

4.0×10

2.5×100

4.5×100

1.2×10296

3

3.4×10

2.9×100

3.3×102

1.6×104101

2.4×100

9.2×100

1.2×102

N

Mean

3

1.5×102

3.9×103

0

6.0×10

1.3×10313

1.9×102

6.4×101

3.1×10359

1.5×100

3.3×100

2.0×100

3.0×101

1.1×103

1.6×100

1.1×101

1

6.2×10

1.9×100

1.2×103

4

1.9×10

1.5×100

5.7×101

2

3.9×10

2.4×102.2×10Maximum

For N = 2, the mean is the arithmetic mean.
GSD: Geometric standard deviation.
n.a.: Not available.

TABLE 58. SUMMARY OF CONCENTRATION RATIOS (CR) FOR
EDIBLE HERPETOFAUNA (L kg–1, fresh weight) [201]Element

N

Meana

GSDb

4

Minimum

MaximumAl

Tadpole (whole)
Frog (muscle)
Frog (carcass)32
2

1.0×10
1.3×102
1.3×102

1.3×100

7.5×103
1.2×102
1.1×102

1.3×104
1.3×102
1.5×102

As

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

1.4×1025.2×101
1.2×102

1.3×100

1.1×1022.4×101
7.4×101

1.9×102
9.0×101
1.6×102

Ca

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

4.5×101
3.5×100
2.9×102
1.6×102

1.6×100

2.6×101
3.4×100
2.9×1025.2×101

6.3×101
3.5×100
2.9×102
3.4×102

Cd

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

2.1×1021.2×1022.4×102

1.4×100

1.4×102
1.1×1022.2×102

2.9×1021.2×1022.5×102

Co

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

9.3×103
5.5×1022.4×103
2.6×103

1.1×100

7.3×103
1.9×102
1.9×103
1.6×103

9.5×103
9.0×102
3.0×103
4.2×103

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

2.9×1029.2×101
2.6×103

1.5×100

2.1×1029.2×101
1.9×102

4.4×102
9.3×101
4.9×103

Cr

Biota type (tissue)

1.1×101

1.9×100

125TABLE 58. SUMMARY OF CONCENTRATION RATIOS (CR) FOR
EDIBLE HERPETOFAUNA (L kg–1, fresh weight) [201] (cont.)
N

Meana

GSDb

Minimum

Maximum

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

3

3.0×10
2.6×1022.1×102
2.9×102

1.3×100

2.5×103
1.7×102
1.6×102
1.3×102

4.0×103
3.4×1022.5×102
5.0×102

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

2.2×102
1.1×102
4.4×102

1.3×100

1.7×102
1.1×102
2.9×102

2.6×102
1.1×102
6.0×102

Fe

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

2.4×103
3.5×101
1.0×103

1.2×100

1.9×103
1.9×101
3.0×102

2.9×103
5.0×101
1.7×103

K

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

4.7×102
1.5×103
1.6×103
1.4×103

1.5×100

3.1×102
1.4×103
1.5×103
9.9×102

7.0×102
1.5×103
1.6×103
2.0×103

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

2.7×101
1.5×101
2.4×101
3.4×101

1.2×100

2.3×101
9.4×100
2.3×101
1.5×101

3.4×101
2.1×101
2.4×101
7.2×101

Mn

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

5.6×102
2.0×100
3.0×102

2.9×100

1.7×102
9.3×10–1
2.6×102

1.1×103
3.1×100
3.3×102

Na

Tadpole (whole)
Frog (muscle)
Frog (carcass)
Reptile (carcass)

3
2
2
9

1.1×102
1.4×102
7.7×101
7.3×101

2.5×100

4.0×101
9.9×101
7.5×101
5.6×101

2.5×102
1.9×102
7.9×101
1.3×102

Ni

Tadpole (whole)
Frog (muscle)
Frog (carcass)32
2

3.9×1022.4×101
2.0×104

1.9×100

1.9×1022.1×101
6.6×1027.2×102
2.7×101
1.0×104

Pb

Tadpole (whole)
Frog (muscle)
Frog (carcass)32
2

6.4×101
5.5×100
1.7×101

1.2×100

5.3×101
2.1×100
1.2×101

7.6×101
9.9×100
2.1×101

Zn

Tadpole (whole)
Frog (muscle)
Frog (carcass)3
2
2

5.7×102
9.0×102
1.0×104

2.7×100

2.7×102
2.0×102
9.5×103

1.9×103
1.5×103
1.1×104

Element
Cs

Cu

Mg

a
b

Biota type (tissue)

For N = 2, the mean is the arithmetic mean.
GSD: Geometric standard deviation.

126

1.3×100

2.3×100

7.0×100

5.9×100

1.1×100

TABLE 59. SUMMARY OF SEDIMENT TO BIOTA CONCENTRATIONRATIOS (CRs-b) FOR WHOLE FRESHWATER INVERTEBRATES [200, 202]
Element

N

Mean

GSDa

MinimumAg40

7.3×10–1

2.6×100

4.0×10–2

7.1×100

Al

136

3.9×10–4

3.9×100

9.5×10–6

1.7×10–1

As

139

1.5×10–1

2.2×100

4.3×10–3

5.7×10–1

B1–2

1.9×10

—

—

—

Ba

137

1.6×10–2

3.6×100

1.7×10–3

1.7×100

Be1

4.0×10–2

—

—

—

Cd

115

7.9×10–1

4.4×100

1.9×10–4

9.7×100

Co

136

3.1×10–2

2.0×100

3.7×10–3

2.0×10–1

Cu149

4.7×10–1

3.3×100

9.6×10–4

3.3×101Fe

140

3.4×10–3

2.5×100

2.2×10–4

3.5×10–1

Hg

109

9.4×10–1

3.5×100

5.6×10–2

1.1×10115–2

1.7×100

3.6×10–2

1.9×10–1

3.9×100

2.1×10–3

1.6×103

4.6×100

4.9×10–4

4.5×100

Mo
Ni

7.4×10

–2

131

Pb

2.1×10–3

75

9.6×10–1

MaximumSb1

1.5×10

—

—

—

Se

103

1.3

2.2×100

6.5×10–2

6.0×100

Sr

135

4.4×10–2

3.0×100

1.9×10–3

6.2×10–1

Tl1

2.3×103

—

—

—

U

6

1.7×10–2

2.9×100

2.9×10–3

6.4×10–2

V

66

2.4×10–3

2.1×100

5.3×10–4

1.4×10–2

151

–1

0

–4

2.3×101Zna

5.2×10

3.0×10

9.3×10

GSD: Geometric standard deviation.

9.3. RADIONUCLIDE PARTITIONING INTO EDIBLE BIOTIC TISSUES
9.3.1.

Application of the specific activity model approach
to aquatic ecosystems

Although accumulation factors are utilized to estimate the transfer of many
radionuclides from environmental media to edible non-human biota, thisapproach is not applicable in cases where radionuclides have stable,
non-decaying analogues that represent a relatively large proportion of thechemical composition of biotic tissues. In such situations, stable isotopes canessentially ‘dilute’ radioisotopes in the body. To account for this effect, a specificactivity model can be applied which assesses concentrations of radionuclides
relative to all isotopes of that element found in biotic tissues, such that:SAm, r =C m, rC m, a◊ C b, a

(33)

127

128

c

b

a

9
113
226
103
2
2
134
751
71
353
7
n.a.
2
139
365
9
61
2
35
1
13
29
703

N

6.9×10–1
9.0×10–3
1.4×10–1
4.9×10–2
1.6×10–1
2.6×102
1.3×10–1
2.9×10–1
4.3×10–3
5.3×100
3.7×100
n.a.
4.6×10–2
2.1×10–1
2.9×10–1
6.6×10–1
1.6×100
7.9×10–1
1.4×10–2
1.6×10–2
2.9×1022.1×10–3
2.1×100

Meana

6.9×100
4.2×10–4
9.1×10–3

5.6×100
2.4×100
4.0×100

1.5×101

5.4×100
5.2×100
5.3×100
3.4×100

5.9×100
4.3×100
9.7×100
5.9×100
2.9×100
n.a.

1.2×10–1
3.6×10–6
7.9×10–4
4.7×10–5
1.3×10–1
9.7×101
2.1×10–6
7.1×10–4
9.3×10–7
3.1×10–4
3.6×10–1
n.a.
6.0×10–3
2.9×10–3
9.4×10–6
4.9×10–2
9.4×10–2
7.5×10–1
1.9×10–4

Minimum

3.5×100
2.0×101
5.9×100
9.3×100

GSDb

Whole fish

For N = 2, the mean is the arithmetic mean.
GSD: Geometric standard deviation.
n.a.: Not available.

Ag
Al
As
Ba
Be
Ca
Cd
Co
Fe
Hg
Mg
Mo
Na
Ni
Pb
Sb
Se
Sn
Sr
Ti
Tl
V
Zn

Element

2.9×103
1.3×10–2
1.3×102

4.9×100
4.3×101
6.6×100
1.9×100
1.9×10–1
4.3×102
3.2×103
2.9×101
2.3×10–1
1.3×102
9.0×100
n.a.
9.6×10–2
2.9
6.3×101
9.9
4.0×101
9.0×10–1
9.5×10–1

Maximum
n.a.c
15
13
3
n.a.
2
20
206
3
129
2
n.a.
1
14
20
n.a.
16
n.a.
n.a.
n.a.
1
n.a.
179

N

n.a.
1.0×101
4.6×10–1
1.1×10–1
n.a.
4.9×100
n.a.
n.a.
n.a.
7.5×101
n.a.
1.1×100

6.1×10–1
2.0×10–1
3.9×10–3
7.3×100

n.a.
6.0×10–3
2.7×10–1
1.2×10–1
n.a.

Mean
n.a.
4.1×100
9.5×100
2.3×100
n.a.
2.2×101
3.7×100
4.4×100
5.2×100
6.5×100
1.1×100
n.a.
n.a.
4.0×100
9.5×100
n.a.
2.9×100
n.a.
n.a.
n.a.
n.a.
n.a.
4.1×100

GSD
n.a.
1.2×10–3
7.1×10–3
4.5×10–2
n.a.
1.9
2.2×10–2
3.0×10–4
7.5×10–4
2.3×10–2
7.3×10–1
n.a.
n.a.
4.1×10–2
9.2×10–4
n.a.
2.6×10–1
n.a.
n.a.
n.a.
n.a.
n.a.
1.1×10–3

Minimum

Fish muscle

n.a.
9.3×10–2
13
2.0×10–1
n.a.
3.4×101
3.3×100
5.9×100
2.0×10–2
1.9×102
7.9×10–1
n.a.
n.a.
2.9×100
1.2×100
n.a.
1.6×101
n.a.
n.a.
n.a.
n.a.
n.a.
4.4×101

Maximum
43
41
56
39
1
n.a.
72
133
79
64
n.a.
6
n.a.
45
21
2
73
n.a.
71
n.a.
n.a.
51
90

N
3.5×10–1
1.3×10–5
1.9×10–2
6.3×10–5
1.4×10–1
n.a.
4.7×10–1
6.1×10–2
2.0×10–3
7.0×10–1
n.a.
2.0×10–2
n.a.
2.9×10–3
2.2×10–3
2.4×10–1
1.0×100
n.a.
4.7×10–4
n.a.
n.a.
1.3×10–3
2.2×10–1

Mean

2.3×100
n.a.
2.2×100
n.a.
n.a.
2.1×100
4.9×100

3.2×100
2.6×100
4.6×100
2.4×100
n.a.
n.a.
4.1×100
1.1×101
3.4×100
4.4×100
n.a.
2.3×100
n.a.
2.7×100
7.4×100

GSD

Minimum
2.4×10–2
2.2×10–6
2.7×10–3
1.9×10–5
n.a.
n.a.
1.7×10–2
1.3×10–3
3.3×10–4
3.0×10–2
n.a.
7.1×10–3
n.a.
2.6×10–4
1.9×10–4
1.9×10–1
2.1×10–1
n.a.
9.9×10–5
n.a.
n.a.
2.1×10–4
5.3×10–3

Fish liver

1.5×101
1.0×10–4
4.4×100
1.9×10–3
n.a.
n.a.
1.4×101
9.7×101
3.2×100
6.4×101
n.a.
6.0×10–2
n.a.
7.3×10–2
4.4×10–1
2.9×10–1
9.6×100
n.a.
2.6×10–3
n.a.
n.a.
5.4×10–3
1.2×102

Maximum

TABLE 60. SUMMARY OF SEDIMENT TO BIOTA CONCENTRATION RATIOS (CRs-b) FOR EDIBLE TISSUES OFFRESHWATER FISH [191, 193]

where SAm,r is the specific activity of a given radionuclide, r, in a given
environmental medium, m; Cm,r is the concentration of a given radioisotope, r, ina given environmental medium, m; Cm,a is the concentration of all isotopes of agiven element, a, in that same environmental medium, m; and Cb,a is theconcentration of all isotopes of a given element, a, in a given type of biota or
tissue. This approach inherently assumes that the organism is at steady state with
its environment, whereby the ratio of the radioisotope of interest relative to all
isotopes in the reference environmental medium m is equal to the ratio of theradioisotope to all isotopes in the biota or tissue being considered.
Notable examples of radionuclides for which a specific activity model
should be used include tritium, 14C and 36Cl, which are discussed in Section 10. A
specific activity approach can also be applied for radionuclides that are analogues
to stable elements that have high concentrations in tissues or whole organisms.
For example, this is the case for 90Sr and other bivalent cations which are being
exchanged for calcium in bone and other hard tissues [204–206].
The fish to water CR for radiocaesium and radiostrontium can be tabulated
accounting for the inverse relationship between the CR and the analogous
potassium and calcium concentration, respectively, in the surrounding water[207–209].
For radiocaesium in predatory/omnivorous fishes, the CR can be estimatedusing the following equation [209]:CR(predatory/omnivorous) =4880[K + ](34)

where [K+] is the concentration of potassium (K+) in lake water (in mg L–1).
For non-predatory fishes, the following relationship can be applied:CR(non-predatory) =3290[K + ](35)

Similarly, strontium concentrations can be tabulated based on calcium
concentrations in water ([Ca], in mg L–1), since both elements behave in a similarmanner, primarily partitioning in the bony parts of aquatic biota (e.g. skeleton,
head, fins, bone, fish scales), as follows [198, 207]:CR(muscle) = exp(5.2 – 1.2 ln[Ca])(36)

CR(bone) = exp(9.7 – 1.2 ln[Ca])

(37)

129

Assuming that 20% of the wet weight of a fish is composed of bony parts,
the whole fish CR can be estimated using the following equation [199]:
CR(whole fish) = exp(9.13 – 1.2 ln[Ca])(38)

An important consideration in the application of specific activity models is the
choice of environmental medium. Indeed, in some instances, organisms may obtain
their supplies of an element from multiple sources, for example, from both water andsediments. In such cases, the specific activity in the organism will be some weighted
average of the specific activities in the source media, and this weighted average mayvary in time and space depending on the relative availability of the different sources.
9.3.2.

Parameters for radionuclide partitioning into edible biotic tissues

Depending on the species, radionuclide and tissue under consideration, it
may be necessary to estimate the per cent radionuclide loading in specific edible
tissues and/or, in cases where whole organisms are consumed, to estimate theradionuclide load in the whole body of an organism based on data that have beencollected for individual tissues [210–212].
Such calculations require biomass estimates for biota and their internal
components, and concentration measurements for each tissue, as follows:

Per cent loading in tissue ==C tissue ◊ mtissue◊1
100%
C whole ◊ m whole
C tissue ◊ C Reference Tissue ◊ mtissue◊100%
C whole ◊ m whole(39)

where C tissue is the element concentration in a given tissue (in mg kg–1 fresh weightor Bq kg–1 fresh weight); m tissue is the mass of that tissue (in kg fresh weight); Cwholeis the element concentration in the whole organism (in mg kg–1 fresh weight or
Bq kg–1 fresh weight); mwhole is fresh weight (in kg); CRtissue is the concentration
ratio of the tissue of interest relative to the reference tissue for a given type of biota(based on data from the literature); and CReference Tissue is the concentration of theelement of interest measured in the reference tissue (i.e. muscle).
With such information, it becomes possible to estimate the concentration ofa given radionuclide in whole fish based on measurements taken for fish muscle
tissue, for example, which could be relevant for fish species that humans eat
whole. Available information and parameter values for various types offreshwater biota, as well as the data selection criteria that were applied in theirdevelopment, are summarized in the accompanying TECDOC [5].

130

9.4. APPLICATION OF DATA
The process of interaction of dissolved radionuclides with solid particles,
either in suspension or deposited, is usually modelled according to the ‘Kdconcept’, where Kd is the ‘particulate form/dissolved form’ partition coefficient
based on the hypothesis of a reversible and rapid equilibration between the
dissolved and the adsorbed radionuclides. However, this is not generally andrigorously true for every radionuclide. The equilibrium between theconcentrations of the dissolved radionuclides and the attached phases may be notinstantaneously achieved, and the adsorption and desorption processes are notalways rapidly reversible [213, 214].
Although it is generally recognized that accumulation of radionuclides byedible aquatic organisms is a dynamic process, many contaminantbioaccumulation models assume that the aquatic organisms are in equilibriumwith reference media, such as water or sediments. In such models, radionuclide
accumulation in aquatic biota can be represented by simplified ratios that relate
radionuclide concentrations in biotic tissues to concentrations in the reference
media (water or sediments).
Radionuclide bioaccumulation factors are often highly variable, being
influenced by such factors as water chemistry, and fish feeding rate, size andposition on the food chain. It is recommended that, where possible, estimates ofradionuclides in water be used to predict accumulation in fish (i.e. that the CR beused), as these estimates are expected to be more reliable than fish–sedimentaccumulation factors. In most cases, radionuclide activity concentrations in theaquatic food chain are controlled by activity concentrations in water, although forsediment dwelling organisms and benthic (bottom dwelling) fish, the sediments
may of course play an important role.

10. SPECIFIC ACTIVITY MODELS AND PARAMETERVALUES FOR TRITIUM, 14C AND 36Cl
The data for parameter values described in the previous sections are basedon element partitioning and accumulation concepts, which are expressed
quantitatively in terms of transfer factors that describe the transport ofradionuclides between different environmental compartments. Under equilibrium
conditions, the specific activity model provides an alternative approach for long
lived isotopes of biologically regulated, essential elements that are highly mobile131

in the environment. The specific activity of a given radionuclide is defined as theactivity per unit mass of the corresponding stable element. Specific activity
models are used here for tritium, 14C and 36Cl, based on the environmental
behaviour of the stable elements hydrogen, carbon and chlorine, respectively.
In the specific activity model, the radioisotope of interest is assumed to mix
physically and chemically with its corresponding stable element within somecompartment of the environment, resulting in a certain specific activity. Anyorganism drawing the stable element from this compartment draws theradioisotope in proportion, and attains the same specific activity as the sourcecompartment. Isotopic exchange with relatively uncontaminated pools of thestable element results in progressive dilution of the isotope with distance from thesource.
A brief description of specific acitivity models and parameter values for thetransfer of tritiated water (HTO) and 14C through the environment following
release to air and water, and for the transfer of 36Cl to animal products, is given
below. More details on these models can be found in the accompanying TECDOC[5], which also discusses models and parameter values for the environmental
transfer of tritiated hydrogen gas (HT) following release to air, and for HTO and14
C transfer from contaminated soils.

10.1. TRITIUM
Following traditional usage, the specific activity model for tritium isformulated in terms of the tritium concentration in water rather than the ratio oftritium activity to the mass of hydrogen in a given compartment. The
concentration of organically bound tritium (OBT, the tritium fixed in the organic
matter of plants and animals) is expressed as the activity in the water equivalentof the dry matter (the water produced by complete combustion of the drymaterial).
10.1.1. Release of HTO to air
HTO released to the atmosphere mixes with air moisture and exchanges
with water pools in plants, soil and animals. Tritium is transferred from air to soil
through wet and dry deposition from the airborne plume. Here, the soil water
concentration (Csw, Bq L–1) is given by:
Csw = CRs–a Cair /Ha

132

(40)

where Cair (Bq m–3) is the concentration in air (assumed to be known throughmeasurement or modelling), CRs-a is an empirical constant and Ha is the absolute
humidity (L m–3). Equation (40) may underestimate the soil concentration close
to an elevated source where air concentrations are low or zero but where soil
concentrations are high due to wet deposition from the elevated plume. This is nota serious restriction in practice because the model is usually applied to membersof the public, who are located far enough from the source that the plume has
already descended to the ground.
CRs-a is difficult to estimate, and it depends on a number of local factors.
The geometric mean of the available data [215, 216] is 0.23, but a slightly larger
value (0.3) is used as the reference value because of the uncertainties involved. A
value of 0.5 is likely to be conservative, although values as high as 1.0 are
possible. The data suggest that southern or wetter regions may have higher CRs-avalues. Values based on local measurements should be used, wherever possible.
The recommended CRs-a value is shown in Table 61, which gathers
together, for the ease of the user, values for all parameters in the tritium and 14C
models for which fixed values are suggested.
–1
The HTO concentration in fresh weight plant material ( C HTO
ffw , Bq kg fresh
weight) is calculated using a model [217] that explicitly considers contributions
to the plant from air moisture (via diffusion through the stomates) and soil water(via the transpiration stream):

È
˘
C
HTO
C pfw
= WC p Í RH air + (1 - RH )C sw ˙ /g
Ha
Î
˚

(41)

Here, WCp is the fractional water content of the plant (L kg–1 fresh weight), RH is
the relative humidity and  = 0.909 is the ratio of the HTO vapour pressure to thatof H2O.
The partitioning between air and soil in Eq. (41) in terms of relative
humidity applies specifically to plant leaves, which draw the majority of theirtritium from the air. The equation is conservative for fruits, tubers and root crops,
which draw a larger fraction of their tritium from the soil, which has a lower
concentration than air moisture for an atmospheric release.
Relative and absolute humidities are commonly measured by national
weather services, and site specific values for these parameters are usually readily
available and are preferred. Water content values for a number of broad plant
categories are listed in Table 62.
These are the same categories defined in Section 4, except that some groups
have been combined (leafy with non-leafy vegetables, cereals with rice, and grasswith fodder and pasture), and the categories for herbs and ‘other’ plants are not133TABLE 61. MODEL PARAMETERS FOR WHICH FIXED VALUES ARE
SUGGESTED
Parameter

SymbolEquation

Value
a

Unit

Soil water to air moisture ratio for HTO

CRs-a

40

0.3

DimensionlessPartition factor for plants

Rp

42

0.54

Dimensionless

Water content of fish

WCf

45

0.78

L kg–1 fresh weight

Partition factor for fish

Rf

46

0.66

Dimensionless

Water equivalent factor for fish

WEQf

46

0.65

L kg–1 dry weight

Stable carbon content of air

Sair

47

0.20

g C m–3

Fraction of feed that is contaminated

fc

48

1.0a

Dimensionless

Stable carbon content of fish

Sf

49

117

g C kg–1 fresh weightaNominal value; a site specific value should be used, if available.

TABLE 62. WATER CONTENT VALUES (WCp, L kg–1, fresh weight) FORTERRESTRIAL PLANTS [218–228]
Plant category

N

Geometricmean

Geometric
standard
deviation

Minimum

Maximum

Leafy and non-leafy vegetables

88

0.92

1.0

0.84

0.97

Leguminous vegetables:
Seed
Vegetative mass

11
16

0.12
0.81

1.2
1.1

0.09
0.69

0.17
0.91
0.95

Root crops

39

0.87

1.1

0.77

Tubers

10

0.75

1.1

0.62

0.82

Fruit

102

0.85

1.1

0.73

0.96

Grass, fodder, pasture

33

0.76

1.1

0.67

0.90

Cereals (including rice)

22

0.12

1.2

0.10

0.16

Maize:
Sweetcorn
Feed corn

4
11

0.71
0.16

1.1
1.5

0.68
0.10

0.76
0.25

Silage

13

0.66

1.2

0.55

0.82

considered. The dry matter contents reported in Appendix I for individual species
have been synthesized, converted to water contents and combined with data fromother sources to produce the values in Table 62. These values apply to the edible
part of the plant as harvested. Some grasses are dried before use as animal feed, inwhich case their water contents become more representative of the value forcereals (0.12). A value for silage is also provided, since this is commonly used foranimal feed.
The OBT concentration in the combustion water of the plant dry matter isthe same as that in the free water of the leaves reduced by a partition factor, Rp,
that accounts for isotopic effects and the presence of exchangeable hydrogen in134the combustion water. The OBT concentration in the fresh weight plant ( C OBT
pfw ,Bq kg–1) is given by:
HTO
C OBT
pfw = (1 - WC p )WEQ p R p C pfw /WC p(42)

where Rp is a partition factor and WEQp is the water equivalent factor (kg of waterproduced per kg dry weight combusted). Rp values must be determined
empirically for steady state conditions. The most reliable estimates come fromcontrolled laboratory experiments, where the plant is exposed to an HTO
concentration that is held constant or monitored continuously. The values
obtained in such experiments [229–231] are all less than 1, with a geometricmean of 0.54 and a geometric standard deviation of 1.16 for the crops considered(maize, barley and alfalfa). In the absence of other information, a value of 0.54 isassumed to apply to all plant types (Table 61). Regardless of the plant in question,
the plant concentration used in Eq. (42) should be the concentration in the plantleaves, the primary location of dry matter production.
The water equivalent factor is difficult to measure but can be calculated
reliably from the hydrogen contents of protein, fat and carbohydrate (7, 12 and
6.2%, respectively) and the fractions of protein, fat and carbohydrate in the dry
matter of the plant in question. The calculated values, which are shown in Table
63, vary little among the various plant categories.
Animals can ingest tritium as HTO in feed and drinking water and as OBT
in the organic fraction of feed. Inhalation and skin absorption are also possible
routes of HTO intake. Exchangeable organic tritium and HTO rapidly equilibratewith body water. Most of the HTO taken in by an animal remains as HTO in its
body, with a small fraction converted to OBT. In contrast, about half the OBT
taken in is converted to HTO, with the other half remaining in organic form.

TABLE 63. WATER EQUIVALENT FACTORS (WEQp, L kg–1 dry weight) FORTERRESTRIAL PLANTS
(calculated from data in Refs [221, 224, 228])
Plant category

N

Geometricmean

Geometric
standard
deviation

Minimum

Maximum
0.55

Leafy vegetables

10

0.51

1.1

0.47

Non-leafy vegetables

12

0.53

1.0

0.50

0.55

Root crops

11

0.52

1.1

0.45

0.55

All others

91

0.56

1.0

0.50

0.60

135

Here, concentrations in animal products are based on a metabolic model[232], the output of which is the ratio CRa of the concentration in the animal
product to the concentration in the feed, drinking water and inhaled air. Separate
ratios are determined for HTO and OBT intakes. The total tritium concentrations(HTO + OBT) in the animal product are given by:
T _ HTO
C afw= CR aHTO CR HTO
f(43)

T _ OBT
C afw= CR aOBT CR OBTf(44)

T _ HTO
where C afw
is the total tritium concentration in the animal product from HTO
intake (Bq kg–1 fresh weight), CRaHTO is the concentration ratio for HTO intake((Bq kg–1 fresh weight)/(Bq L–1)), CRfHTO is the average HTO concentration in
T _ OBT
ingested water (Bq L–1), C afw
is the total tritium concentration in the animal–1
product from OBT intake (Bq kg fresh weight), CRaOBT is the concentration ratio
for OBT intake ((Bq kg–1 fresh weight)/(Bq kg–1 dry weight)), and CRfOBT is theaverage OBT concentration in feed (Bq kg–1 dry weight).
CRfHTO is the sum of the HTO concentrations in the water taken in with feed,
drink and respiration (including skin absorption), weighted by the fractional
contribution of each of these sources to the total water intake. Generally
speaking, inhalation contributes about 2–5% of the total water intake of theanimal, and metabolic water about 10%. The fraction of water coming from thediet varies among practices and must be user defined. CRfOBT is a weighted
average that includes uncontaminated as well as contaminated feed, since local
sources supply only a fraction of the total animal feed in modern industrial
farming.
Representative concentration ratios for a number of animal products fortemperate climates are given in Tables 64 and 65.
For a given product, the central value of the concentration ratio pertains tothe specific mass, production rate and intake rate shown in the table. The ranges
were derived by considering the variability in animal mass, production level anddiet under temperate climate conditions. Larger values are conservative andshould be used for animals that are raised in cold climates or have high fat content
in their products.
The OBT concentration in the animal product can be found by multiplying
the total concentration by fOBT from Tables 64 and 65, where fOBT is the fraction of
the total tritium in the animal product in the form of OBT; the HTO concentration
is found by multiplying the total concentration by (1– fOBT).

136

TABLE 64. CONCENTRATION RATIOS FOR HTO INTAKE (CRaHTO) [232]
Product

Animalmass(kg)

Intake rate
(kg d–1)

Production
Fractionrate (kg d–1
OBT (fOBT)or L d–1)

CRaHTO(Bq kg–1 fresh weight product per
Bq L–1 intake)Best estimate

Minimum

Maximum

Milk
Cow

550

14

15

0.04

0.87

0.81

0.92

Sheep

50

1.8

1.3

0.06

0.78

0.76

0.89

Goat

50

2.5

2.5

0.07

0.83

0.81

0.87
0.82

Meat
Beef

500

9.3

0.7

0.11

0.66

0.64

Veal

160

4.85

0.8

0.08

0.69

0.64

0.82

Mutton

50

1.22

0.08

0.1

0.74

0.67

0.78

Lamb

20

1.0

0.2

0.08

0.78

0.60

0.81

Goat

50

1.2

0.08

0.1

0.67

0.62

0.81

Pork

100

2.7

0.8

0.13

0.67

0.61

0.77

Hen

2.5

0.12

0.01

0.1

0.76

0.70

0.80

Broiler

1.7

0.11

0.03

0.1

0.76

0.70

0.90

Egg

2.5

0.15

0.05

0.08

0.76

0.63

0.81

TABLE 65. CONCENTRATION RATIOS FOR OBT INTAKE (CRaOBT) [232]
Product

Animalmass(kg)

Intake rate
(kg d–1)

Production
Fractionrate (kg d–1
OBT (fOBT)or L d-1)

CRaOBT (Bq kg–1 fresh weight product per
Bq L–1 dry weight intake)Best estimate

Minimum

Maximum

Milk
Cow

550

14

15

0.47

0.24

0.17

0.37

Sheep

50

1.8

1.3

0.57

0.32

0.23

0.39

Goat

50

2.5

2.5

0.40

0.32

0.25

0.38

Meat
Beef

500

9.3

0.7

0.80

0.40

0.35

0.53

Veal

160

4.85

0.8

0.72

0.35

0.31

0.45
0.56

Mutton

50

1.22

0.08

0.75

0.40

0.35

Lamb

20

1.0

0.2

0.78

0.55

0.35

0.67

Goat

50

1.2

0.08

0.60

0.43

0.36

0.46

Pork

100

2.7

0.8

0.74

0.64

0.45

0.77

Hen

2.5

0.12

0.01

0.55

0.50

0.42

0.60

Broiler

1.7

0.11

0.03

0.55

0.50

0.42

0.70

Egg

2.5

0.15

0.05

0.78

0.64

0.53

0.69

137

10.1.2. Release of HTO to water bodies
Fish are the only aquatic organisms considered here, since they are the only
aquatic organisms that play a major role in the human diet. The assumption of full
specific activity equilibrium is a good approximation to HTO concentrations inmost aquatic compartments [233, 234]. The water pools to which freshwater fish
are exposed, including lake water and water derived from foods at different
trophic levels, all have similar HTO concentrations. This implies that the HTO–1concentration in the fresh weight fish ( C HTO
ffw , Bq kg , fresh weight) is given by:

C HTO
ffw = WC f ◊ C w(45)

where Cw (Bq L–1) is the HTO concentration in the water column (assumed to be
known through measurement or modelling) and WCf is the fractional watercontent of the fish (L kg–1 fresh weight). The water content is roughly constant at
0.78 for most fish that form part of the human diet [221] (see Table 61).
Because fish are immersed in an environment of uniform HTO
concentration, it is reasonable to assume that the OBT concentration in the
combustion water of the fish is the same as the HTO concentration, apart from apartition factor that takes account of the presence of exchangeable hydrogen in
the combustion water and of isotopic effects arising both in the fish and in the
different components of its food and water intakes. The OBT concentration in the
fresh weight fish is given by:

C OBT
ffw = (1 - WC f ) ◊ WEQ f ◊ R f ◊ C w(46)

where WEQf is the water equivalent factor of the fish and Rf is the partition factor.
Values of Rf must be determined empirically. The data for steady state
conditions have a geometric mean of 0.66, which is the reference value for all
fish, and a geometric standard deviation of 1.5 [233–238]. The water equivalent
factor is difficult to measure but can be calculated reliably from the hydrogencontents of protein, fat and carbohydrate (7%, 12% and 6.2%, respectively) andthe fractions of protein, fat and carbohydrate in the fish in question. The
calculated values for four fish species [221] show a small geometric standard
deviation of 1.06, and the geometric mean of 0.65 is the reference value forgeneric assessments (see Table 61).

138

10.2. CARBON-14
10.2.1. Release of 14C to air
The assumption of full specific activity equilibrium throughout the terrestrial
environment is completely satisfactory for 14C releases to the atmosphere if, as is
usual, the 14C is emitted as 14CO2. Accordingly, the 14C concentration in Bq g–1
stable carbon is the same in the plant as it is in air, and the 14C concentration in the
fresh weight plant (Cpfw, Bq kg–1 fresh weight) is given by:

Cpfw =

Cair ◊ Sp
Sair

(47)

where Sp is the concentration of stable carbon in the plant (g C kg–1 fresh
weight), Cair is the concentration of 14C in air (Bq m–3) (assumed to be known
through measurement or modelling), and Sair is the concentration of stablecarbon in air (g C m–3). The only parameters required for the model are thestable carbon concentrations in air and in the plants of interest. Sair is currently
about 0.20 g/m3 (see Table 61). Measured values of the carbon contents for thevarious plant categories are shown in Table 66. The data are augmented byvalues calculated from the carbon contents of protein, fat and carbohydrate(52%, 77% and 42%, respectively) and the fractions of protein, fat andcarbohydrate in the plant [221].
Similarly, the 14C concentration in animal products (Cafw, Bq kg–1 fresh
weight) is given by:

Cafw =

fc ◊ Cpfw ◊ Sa
Sp

(48)

where fc is the fraction of animal feed that is contaminated and Sa is theconcentration of stable carbon in the animal product (g C kg–1 fresh weight). Sp
values are given in Table 66.
The factor fc is introduced to allow for the fact that animals may be fed
supplementary concentrates or feed from remote sources that areuncontaminated. The fc value should be set based on consideration of local
farming practices; if a site specific value is not available, fc should beconservatively set to 1 (see Table 61).
The carbon contents of various animal products are shown in Table 67. A
few of these values were measured directly [239, 241], but most were calculated

139

TABLE 66. CONCENTRATION OF STABLE CARBON IN TERRESTRIAL
PLANTS (Sp)
(from Refs [221, 224, 228, 239–241])
Stable carbon content (g C kg–1 fresh weight)
N

Geometricmean

Geometric
standard
deviation

Minimum

Maximum

Leafy and non-leafy vegetables

49

3.0×101

1.40

1.8×101

6.5×101

Leguminous vegetables:
Seed
Vegetative mass

7
5

4.1×102
5.9×101

1.08
1.46

3.8×102
4.1×101

4.7×102
1.1×102

Root crops

23

4.6×101

1.46

2.2×101

9.5×101

6

2

1.20

1

8.6×10

1.3×102

1

Plant category

TubersFruit

10.3×1048

6.2×101

1.27

3.1×10

1.0×102

2

1

Grass, fodder, pasture25

1.0×101.31

4.0×10

1.6×102

Cereals (including rice)29

3.9×102

1.05

3.6×102

4.3×102

Maize:
Sweet corn 
Feed corn

31

1.2×102
3.8×102

1.00—

1.2×102—1.2×102—

Silage13

1.3×102

1.42

6.5×101

1.8×102

TABLE 67. CONCENTRATION OF STABLE CARBON IN TERRESTRIALANIMAL PRODUCTS (Sa)
Stable carbon content (g C kg–1 fresh weight)
Animal productN

Geometricmean

Geometric standard
deviation

Minimum

Maximum8

6.5×101

1.03

6.2×101

6.9×101

Sheep1

1.1×10

2

—

—

Goat

1

7.1×101——14

2.0×102

1.19

1.6×102

2.9×1023

1.6×102

1.21

1.3×102

1.9×102

2

—

—

1.26

2.3×102

3.2×102

Milk
Cow

Meat
Beef
Veal
Mutton1

2.9×10Lamb

2

2.8×102Goat1

1.7×10

2

—

—

Pork

12

3.0×102

1.39

1.7×102Hen1

2.4×102——

Broiler5

1.5×102

1.23

1.1×102

2.0×102Egg

2

1.6×102

1.01

1. 6×102

1.6×102140

5.5×102

from the carbon contents of protein, fat and carbohydrate and the fractions ofprotein, fat and carbohydrate in the product [221].
10.2.2. Release of 14C to water bodies
Modelling 14C in aquatic systems is complicated by the existence of several
carbon pools. Here, the fish are assumed to be in full specific activity equilibriumwith dissolved inorganic carbon (DIC):
Cffw = CDIC·Sf(49)

where Cffw is the 14C concentration in fresh weight fish (Bq kg–1 fresh weight),
CDIC is the 14C concentration in DIC in the water column (Bq gC–1) (assumed tobe known through measurement or modelling), and Sf (g C kg–1 fresh weight) isthe concentration of stable carbon in the fish.
As was the case for terrestrial animal products, the carbon contents of fish
are most reliably determined from the carbon contents of protein, fat andcarbohydrate, and the fractions of protein, fat and carbohydrate in the fish [221].
The calculated values have a relatively low geometric standard deviation of 1.18,
and the geometric mean of 117 g C kg–1 fresh weight is the reference value for use
with all species (see Table 61).

10.3. CHLORINE-36
As in the case of 3H and 14C, specific activity modelling for 36Cl takes
advantage of stable element contents in the environment and isotopic equilibrium
between compartments to generate reliable estimates of 36Cl concentrations.
Specific activity is especially important for 36Cl, owing to the lack of
discrimination among chlorine isotopes by organisms and the large amount of
stable chlorine available for dilution.
Studies of the transfer of 36Cl to beef and to cow’s milk have shown that theisotopic ratio in animal products is the same as that in their foodstuffs [242]. The
average equilibrium chlorine isotopic ratio in the daily dietary intake cantherefore be used to predict the contamination of animal products with 36Cl, as
long as the different inputs are well defined. The specific activity in the animal
product is given by:

C animal q water ◊ C water + q foodstuff ◊ C foodstuff=
S animal q water ◊ S water + q foodstuff ◊ S foodstuff

(50)

141

where q is the intake rate (L d–1 or kg, fresh weight, d–1), C is the 36Cl concentration(Bq L–1 or Bq kg–1 fresh weight) and S is the stable chlorine concentration (g L–1 or
g kg–1 fresh weight). All inputs of stable chlorine to each environmental
compartment (fertilizers for plants, salt licks for animals, etc.) should be taken into
account in the model, if they contribute significantly to dilution.
Table 68 lists stable chlorine concentrations for various environmental
compartments for use in specific activity modelling. These correspond to themeans of the data in the literature. They should be used with caution and only
when site specific data are not available.

TABLE 68. STABLE INORGANIC CHLORINE CONTENT IN ENVIRONMENTAL MEDIA [243–247]
(as summarized in Ref. [248])
Environmental media/object

Content

Unit

Content

Unit

Gaseous

0.06

mg/m3

Root vegetables

0.50

g/kg

Beet

1.30

Aerosol

0.03

g/kg

mg/m3

Sugar beet

0.35

g/kg

0.010

g/L

Potatoes

1.00

g/kg

Groundwaterb

0.016

g/L

Red beet

0.60

g/kg

Riverc0.007

g/L

Carrot

0.50

g/kg

Raind

0.011

g/L

Celery

0.50

g/kg

0.2

g/kg
(dry weight)

Turnip

0.55

g/kg

Onion

0.25

g/kg

Cereals (grains)

0.50

g/kg
(fresh weight)

Radish

0.30

g/kg

Oat

0.50

g/kg

Horseradish

0.17

g/kg

Wheat

0.50

g/kg

Rutabaga

0.30

g/kg

Maize

0.45

g/kg

Salsify

0.31

g/kg

Millet (bird seed)

0.19

g/kg

Barley1.04

g/kg

Artichoke

0.22

g/kg

Rice

0.23

g/kg

Celery1.37

g/kg

Saracen

0.30

g/kg

Cabbage

1.08

g/kg

Brussels sprout

0.10

g/kg

a

Air

WateraSoil
Terrestrial plants

Cereals (flour)

Leafy vegetables

Oat

0.49

g/kg

Cauliflower

0.29

g/kg

Wheat

0.50

g/kg

Red cabbage

0.45

g/kg

0.50

g/kg

Chives0.43

g/kg

Apricot

0.02

g/kg

Watercress

1.00

g/kg

Almond0.20

g/kg

Endive0.71

g/kg

Pineapple

0.30

g/kg

Spinach

0.75

g/kg

Peanut0.17

g/kg

Curled salad

0.25

g/kg

Eggplant

0.50

g/kg

Lettuce

0.50

g/kg

Fruits and nuts

142

Environmental media/object

TABLE 68. STABLE INORGANIC CHLORINE CONTENT IN ENVIRONMENTAL MEDIA [243–247]
(as summarized in Ref. [248]) (cont.)
Environmental media/object

Content

Unit

Banana1.00

g/kg

Nectarine

0.05

g/kg

Cherry0.03

g/kg

Fruits and nuts

Environmental media/object

Content

Unit

Corn salad

0.10

g/kg

Sorrel

0.60

g/kg

Parsley

1.25

g/kg

Leafy vegetables

Chestnut

0.10

g/kg

Dandelion

1.00

g/kg

Lemon

0.03

g/kg

Leek

0.40

g/kg

Pumpkin

0.18

g/kg

Animal products
Milk

Quince

0.02

g/kg

1.00

g/L

Cucumber

0.27

g/kg

Human

0.40

g/L

Pickle

0.27

g/kg

Cow

1.00

g/L

Courgette

0.18

g/kg

Sheep

1.00

g/L

Date

2.50

g/kg

Buffalo

0.62

g/L

Fig

0.16

g/kg

Camel

1.05

g/L
g/L

Strawberry

0.12

g/kg

Goat

0.50

Raspberry

0.22

g/kg

Horse

0.30

g/L

Guava

0.45

g/kg

Eggs

1.20

g/kg

Meat

Currant

0.10

g/kg

Bean

0.23

g/kg

Beef

0.75

g/kg

0.70

g/kg

Mandarin

0.02

g/kg

Horse

0.09

g/kg

Melon

0.43

g/kg

Mutton1.00

g/kg

Blackberry

0.20

g/kg

Lamb

0.85

g/kg

Medlar

0.03

g/kg

Veal

0.75

g/kg

Coconut

1.17

g/kg

Pork

0.60

g/kg

Olive

0.04

g/kg

Turkey1.20

g/kg

Grapefruit

0.02

g/kg

Chicken

0.60

g/kg

Pig liver

0.90

g/kg

0.50

g/kg

Watermelon

0.08

g/kg

Peach

0.03

g/kg

Aquatic plants

Pear

0.02

g/kg

Aquatic animals
Freshwater fish

Pea

0.36

g/kg

1.00

g/kg

Bell pepper

0.19

g/kg

Bream

1.22

g/kg

Apple

0.03

g/kg

Pike

1.00

g/kg

Plum

0.05

g/kg

Perch

0.85

g/kg
g/kg

Grape

0.03

g/kg

Tench

0.95

Rhubarb

0.53

g/kg

Trout

1.00

g/kg

Tomato

0.40

g/kg

1.00

g/kg

Freshwater invertebratesaDependent on distance from the sea.
Variation: 0.001–0.070.
cVariation: 0.001–0.035.
d
Variation: 0.001–0.020.
b143

10.4. APPLICATION OF DATA
The specific activity concepts upon which the tritium, 14C and 36Cl models
depend are theoretically sound for long term safety assessments with constantrelease rates. However, the models do not apply to short term (accidental)
releases where concentrations are time dependent. For example, the 36Cl content
of soils varies by more than an order of magnitude between winter and thegrowing season, and plant uptake depends on the growth stage. This contributes
some uncertainty to the predictions of 36Cl concentrations in animal products
calculated using the specific activity approach.
In applying the models, all inputs of the stable and active forms of theisotope to each environmental compartment must be taken into account. For
example, the stable chlorine taken up by animals from salt licks should be
accounted for in calculating 36Cl concentrations.

11. FOOD PROCESSING
11.1. DEFINITIONS AND PROCESSESThe concentration of radionuclides in food can be affected by foodprocessing activities, for example, radionuclide extraction during boiling,
removal of certain parts of the raw food (e.g. bran, peel, shell, bone) and drying or
dilution [3, 249]. Neglecting radionuclide losses during food processing can leadto overestimation of the calculated dose. Technological food processing allows
significant reduction in the radionuclide contamination of foodstuffs. This
reduction can be achieved by many of the normal practices used in the
preparation, cooking and processing of food. The effects of technologicalprocessing on contaminated food depend on the radionuclide, the type offoodstuff and the method of processing. The effectiveness of radionuclide
removal from raw material during processing can vary widely; however,processing of raw materials of vegetable and animal origin is often considered themost effective countermeasure for reducing the radioactive contamination of thefoodstuff to or below permissible levels, and can be applied both domesticallyand in industrial processing of food [249–254].
In reporting the quantitative results of food processing, the following foodprocessing transfer parameters are applied: the food processing retention factor,
Fr , is the fraction of radionuclide activity that is retained in the food after

144

processing; the processing efficiency, Pe, is the ratio of the fresh weight of theprocessed food to the weight of the original raw material; the processing factor1,
Pf , for a foodstuff is the ratio of the radionuclide activity concentrations(analogous to the concentration ratio).
There is a simple relationship among these three factors. Fr is the product of
Pf and Pe:
Fr = Pf ·Pe(51)

Application of these various factors is illustrated here with reference tocaesium and strontium. Thus, an Fr value of 0.4 for caesium in boiled meatindicates that only 40% of the caesium in raw meat is retained after boiling andthat 60% is removed into the boiling liquid (see Table 74). In the case of dairy
products (see Table 75), the yield of each product is important. For example, an
Fr value of 0.61 for strontium in goat cheese indicates that 39% is removed by theconversion of goat’s milk to cheese, but, owing to the 12% yield of cheese, theconcentration of strontium in goat cheese is 0.61/0.12 = 5 times the concentrationin goat’s milk. Therefore, the processing factor (Pf) is 5 [3].
Fr values for animal food products are all based on contamination in vivo.
All data on plants refer to contamination of the edible product, generally
contaminated via root uptake followed by translocation. However, often theradionuclide transfer factors from soil to plant are experimentally determined andreported for the washed and peeled vegetables and fruits (e.g. for potato). In thiscase, application of the radionuclide losses at washing and peeling toconcentrations estimated using experimentally determined transfer factors willlead to underestimation of the predicted activity of radionuclides in foodstuffs.
Therefore, it is important to know if the transfer factor values were obtained for
washed and peeled vegetables and fruits.
For vegetables, Fr values based on ‘external contamination’ are alsopresented. A product is said to be externally contaminated if the leaves arecontaminated by spraying, painting, deposition, etc., and the time lag between
contamination and processing is short enough to ensure that the majority of theradionuclides have not migrated from the surface into the plant.

1

In ICRU Report 65 [6], this value is called the ‘food processing retention factor’.

145

11.2. PROCESSING FACTOR VALUES
Data on the behaviour of many radionuclides during food processing are
scarce. The exceptions are caesium, strontium and iodine. Some measurements
were made in the 1960s at a time when there was concern about the consequencesof radionuclide transfer from nuclear weapons testing into the human food chain.
Following the accident at the Chernobyl nuclear power plant, new measurements
have become available. Noordijk and Quinault [251] reviewed the existing
literature within the framework of the CEC and the IAEA VAMP programmes[51, 255]. These results were mainly reported in TRS-364 [3]. This updated
version includes the more recent results and information from various reviews[252–254], as well as the experimental data from the database of the UK FoodStandards Agency (for 137Cs, 90Sr and stable Na, K, Ca, Mg, P, Fe, Cu, Zn, Cl,
Mn, Se, I, Cd and Pb) [256] and from the database created within the frameworkof the Franco–German Initiative (FGI) [249, 250]. The main results obtained,focusing on the most effective methods, are shown in Tables 69–80.
Long storage and processing times will reduce the activity contents of short
lived radionuclides in foodstuffs, with implications for assessments of doses fromreleases of radionuclides to the environment [252]. The delay between harvestand consumption is important for short lived radionuclides such as 131I. For
instance, processing of milk with a high concentration of 131I during the acutephase of the Chernobyl accident into foodstuffs stored for long periods (such asbutter, cheese and dried milk) ensured significant decreases of 131I concentrationsin these foodstuffs due to radioactive decay before their eventual consumption.
For this reason, storage and processing times for the main foodstuffs are also
reported here (see Table 81). More details on processes governing foodprocessing, including all available information sources used for evaluation of thedata presented here, are provided in the accompanying TECDOC and in otherrelated publications [5, 257–260].

11.3. APPLICATION OF DATA
The food processing retention factor, Fr , is mainly applied for assessment of
the total loss of radionuclides during processing (removal of a radionuclide fromthe food chain and/or estimation of discharges to waste streams) and for
calculations of collective dose [3]. For some processes where the activity remains
in the waste product rather than being removed from the foodstuff, notably the
production of oil from olives and rapeseed, and of wine from grapes, theparameter Pf is more appropriate [252].

146

TABLE 69. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR VEGETABLES AND FRUIT
(data are based on total contamination of the plant)
Method of processing
Washing of vegetables, berries
and fruits

Peeling of vegetables

Boiling in water of vegetables,
berries and fruits

Canning, blanching and picklingof vegetables
Production of sugar from beetroot
Production of starch from potato
Pressing of olives
Oil
Cake
Processing of rapeseed to oil
a

Fr

Pe

Element

Value

Cs
I
Ru
Sr
Am, PuCs
Po
Sr
Am, Ca, Cu, Fe, K, Mg, Na,
P, Po, Pu, Ru, S, Zn
Cl, T
Cs
Sr
Cs

0.6–1.0
0.8
0.7–0.9
0.4–1.0
0.1–1.0
0.5–0.9
0.3–0.5
0.5–0.9
0.3–1.0

1.0
1.0
1.0
1.0
0.7–0.9
0.7–0.9
0.7–0.9
0.7–0.9
0.8–1.0

0.3–0.6
0.4–0.9
0.6–1.0
0.1–1.0

0.8–1.0
0.8–1.0
0.8–1.0
0.5–0.9

0.3–1.00.001–0.01
0.02–0.03

0.5–0.9
0.12
0.18

0.13
0.43
Pf = 0.004a
Pf = 0.002a

0.2
0.5

Sr
Cs
Cs
Cs
Cs
Cs
Sr

Value given is for food processing.

TABLE 70. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR VEGETABLES AND FRUIT
(data are based on external contamination only)
Method of processing
Washing of vegetables, berries and fruits

Boiling of vegetables and berries

Fr
Element

Value

Cs
I
Ru
Sr
Ba
Cs
I
Ru, TeSr
Zr

0.1–0.9
0.1–0.9
0.2–0.8
0.1–0.5
0.6–0.9
0.1–0.5
0.1–0.5
0.3–0.7
0.1–0.2
1.0

Pe
1.0
1.0
1.0
1.0
0.8–1.0
0.8–1.0
0.8–1.0
0.8–1.0
0.8–1.0
0.8–1.0147

TABLE 71. FOOD PROCESSING RETENTION FACTOR (Fr) AND THE
PROCESSING EFFICIENCY (Pe) FOR CEREALS
Raw material
Wheat, rye, barley, oats, grain

Milling to white flour

Milling to dark flour

Rice grain

Element

Value

Pe

Am, Pu0.1–0.2

0.6–0.8

Cd, Pb

0.5–0.6

0.6–0.8

Cs

0.2–0.6

0.6–0.8

Sr

0.1–0.6

0.6–0.8

Cs

0.05–0.2

0.05–0.1
0.05–0.1

Sr

0.1–0.2

Milling to semolina

Cs

0.15–0.5

0.1–0.3

Milling to branCs

0.4–0.7

0.1–0.4

Sr

0.6–0.9

0.1–0.4

Cooking wheat sprouts

Cs

0.8–0.9

1.8–2.4

Shredding or puffing wheatCs

0.1–0.15

0.9–0.95

Polishing

Brown, savoury,‘easy cook’ white rice

Boiling

Pasta

Boilinga

Fr

Method of processing

Ca, Fe, K, Mg, P

0.1–0.6

Cs

0.2–0.4

Cu, Na, Zn

0.7–0.9Mg, P

0.1–0.6

Sr

0.1–0.4

Ca, Cl, Cu, Fe, K,
Mg, Na, P, Se, Zn

0.3–0.4

Cs

0.1–0.4

Ca, Cl, Cu, Fe, K,
Mg, Na, P, Zn

0.1–0.4a

Value given is for food processing .

TABLE 72. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR DRINKS
Raw material

Method of processing

Surface wastewater

Conventional
treatment
to tap water

Tea

Herbal tea

148

Brewing 2–8 minutes

Brewing

Fr

Pe

Element

Value

Co

0.4

Cs

0.7

1.0

Ru

0.3

1.0

Sr

1.0

1.0

I

0.8

1.0

Cs

0.4–0.6Cs

0.9 for external
contaminationCs

0.4–0.6

1.0

TABLE 72. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR DRINKS (cont.)
Raw material

Method of processing

Berries and fruits

Juice

GrapesFr
Element

Pe

Value

Am, Pu0.5

0.3–0.9

Cs

0.2–0.9

0.3–0.9

S

0.2

0.3–0.9

T

0.6

0.3–0.9Sr

0.2–0.6

0.6–0.8

Cs

0.3–0.7

0.6–0.8

Cu, K,
P, Zn

0.3–0.8

0.6–0.8

Wine

TABLE 73. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe ) FOR TRITIUM
Raw material

Method of processing

Fr
HTO

Pe

OBT

Blackberries

Washing and stewing

0.55

0.56

0.59

Broad beans

Boiling

0.28a

0.69b

0.91

Cabbage

Washing and steaming

0.28a

—

0.98

Carrots

Washing and boiling

0.28a

0.43b

0.85

New potatoes

Scrubbing and boiling

0.55b

—

0.92

Peeling and roasting

0.22b

—

0.62

Peeling and boiling

0.55

0.74

0.92

Peeling and roasting

0.21

—

0.65

Hulled rice

Boiling

0.84

—

—

SoybeanBoiling

0.77

—

—

Old potatoes

Rice flour

Boiling

0.69

—

—

Soybean flour

Boiling

0.74

—

—

a

Some data are below the detection limit.
b
Not significant at the 5% level.

TABLE 74. FOOD PROCESSING FACTORS FOR 14C
Raw material

Method of processing

Food processing retention factor (Fr)Processing efficiency (Pe )0.92

New potatoes

Scrubbing and boiling

0.69

Hulled wheat

Boiling

0.82—

Hulled rice

Boiling

0.98—

SoybeanBoiling

0.86—

Wheat flour

Boiling

0.92

—

149

TABLE 75. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR DAIRY PRODUCTS (bold font denotes recommended values)
Product

Element

Cream

Ca, Cl, K, Na, Mg
Cd
Cs
I
Fe
P
Pb, Zn
Sr
Cs
Sr
I
Cs
Sr
Ca, Cl, K, Na, Mg
Cd
Cs
I
P
Pb
Sr
Zn
Cs
I
Sr
I
Sr
Ca, Cl, K, Na, Mg, Zn
Cs

Sour cream
Skimmed milk

ButterButtermilk

Butterfat
Milk powder (dried)

Condensed milk

Cheesea
Goat

150

Sr
I
Ca, Cl, Cu, Fe, K,
Mg, Na, Zn
Cs
I
Sr
I
Cs
Sr

Fr
Ref. value

0.05
0.06

0.04
0.1
0.1
0.95
0.93

0.01
0.02

0.006
0.05
0.06

1.0

Pe
Range

Ref. value

Range

0.03
0.06–0.1
0.03–0.16
0.006–0.19
0.07
0.02
0.05
0.02–0.25
0.1–0.2
0.1–0.13
0.81–0.94
0.85–0.99
0.75–0.96
0.008
0.1
0.003–0.02
0.01–0.035
0.004
0.02
0.0025–0.012
0.01
0.02–0.13
0.05–0.13
0.03–0.07
0.02
0.001–0.002
1.0
1.0

0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.08
0.1
0.1
0.92
0.92
0.92
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.12
0.12
0.12

0.03–0.24
0.03–0.24
0.03–0.24
0.03–0.24
0.03–0.24
0.03–0.24
0.03–0.24
0.03–0.24
0.1–0.2
0.1–0.2
0.76–0.97
0.76–0.97
0.76–0.97
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.05
0.03–0.14
0.03–0.14
0.03–0.14
0.04–0.04
0.04–0.04
0.11–12
0.11–12

1.0
1.0

1.0
1.0
1.0

0.12
0.4

0.11–12
0.11–12
0.37

1.0
1.0
1.0

1.0
1.0
1.0

0.4
0.4
0.4

0.37
0.37
0.37

0.08–0.14
0.07–0.15
0.61

0.12
0.12
0.12

0.08–0.17
0.08–0.17
0.08–0.17

TABLE 75. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR DAIRY PRODUCTS (cont.) (bold font denotes recommended values)
Product
Cow, rennet

Cow, acid

Cottage cheese, rennet
Cottage cheese, acid
Wheya, rennet

Whey, acid

Caseina, rennet

Casein, acid

Casein wheya, rennet

Casein whey, acid

Milkb, ion exchangeabElementCa
Cd, Fe, Mg, Pb, P
Cs
Cu
I
K, Cl
Sr
Zn, Se
Cs
I
Sr
Cs
Sr
Cs
Sr
Cs
I
Sr
Cs
I
Sr
Cs
I
Sr
Cs
I
Sr
Cs
I
Sr
Cs
I
Sr
Cs
I
Sr

Fr
Ref. value

0.07
0.20
0.7
0.06
0.08

0.1

0.05
0.1
0.1

Pe
Range

Ref. valueRange

0.5–0.7
0.2–0.4
0.05–0.23
0.4–0.6
0.11–0.53
0.1
0.025–0.80
0.7–1.0
0.01–0.12
0.22–0.27
0.04–0.08
0.01–0.05
0.07–0.17
0.1
0.2–0.7
0.73–0.96
0.47–0.89
0.20–0.80
0.75–0.90
0.60–0.73
0.70–0.90
0.01–0.08
0.02–0.12
0.10–0.85
0.01–0.04
0.03–0.04
0.05–0.08
0.77–0.83
0.69–0.82
0.08–0.16
0.83–0.84
0.78–0.80
0.67–0.86

0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.10
0.10
0.10

0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.18
0.08–0.12
0.08–0.12
0.08–0.12

0.12
0.12
0.90
0.90
0.90

0.1–0.14
0.1–0.14
0.70–0.94
0.70–0.94
0.70–0.94
0.82
0.82
0.82
0.03–0.06
0.03–0.06
0.03–0.06
0.01–0.06
0.01–0.06
0.01–0.06
0.73–0.79
0.73–0.79
0.73–0.79
0.75–0.79
0.75–0.79
0.75–0.79
1.0
1.0
1.0

0.04–0.06

0.76
0.76
0.76
0.78
0.78
0.78
1.0
1.0
1.0

Separate values are given for the rennet and acid coagulation processes.
Decontamination of milk by ion exchange on a commercial scale.

151

TABLE 76. FOOD PROCESSING RETENTION FACTOR (Fr) AND THE
PROCESSING EFFICIENCY (Pe) FOR MEAT
(bold font denotes reference values)
Rawmaterial
Mammals(cow, pig,
sheep, deer,
rabbit)

Method of processing
Boiling meat

Element
Cs

Fr
Ref. value
0.4

I
Sr

0.5

Ru
Boiling bone

Frying, roasting or grilling
meat

Cs

Microwave baking

Pickling wet (salting),
marinating
Birds

Fish

a

0.5–0.7

0.6

0.5–0.7

0.4–0.9

0.5–0.7

0.3

0.5–0.7

0.2–0.3

1.0

0.98

1.0

Sr

0.99

1.0

Ru

0.7

1.0

Ca, Cu, Cl, Fe, K, Mg,
Na, P, Se, Zn,

0.5–1.0

0.4–0.7

0.5–0.8

0.4–0.7

0.7

I

0.2–0.6

0.4–0.7

Sr

0.8

0.4–0.7

Ca, Cl, Fe, K, Mg, Na,
P, Se Zn

0.5–1

0.4–0.7

Cs

0.5

0.4–0.5

0.4–0.7

Cs

0.5

0.1–0.7

0.9–1.0

Sausage productionCs

0.4–1.0

Boiling meat

Sr

0.5

Baking meatCs

0.7–0.8

Roasting

Ca, Cl, Cu, Fe I, K,
Mg, Mn, Na, P, Se, Zn

0.5–1.0

0.4–0.7
0.5–0.9

Boiling fleshCs

0.2–0.9

Sr

0.9

Frying fleshCs

0.8–0.9

Grilling

Ca, Cl, Cu, I, K, Fe,
Mg, Mn, Na, P, Se, Zn

Value given is for food processing.

152

0.2–0.7

I

Cs

0.3

Pe

Range

Pf = 1.1–1.2

0.7–0.8aTABLE 77. FOOD PROCESSING RETENTION FACTOR (Fr) FOR 137Cs
AND 90Sr, AND PROCESSING EFFICIENCY (Pe), FOR FOREST PLANT
PRODUCTS (MUSHROOMS AND BERRIES) (data are based on total contamination of the plant)
Raw material
Berries (bilberry,
blackberry)Mushrooms

Method of processing

Element

Fr

Pe

Washing

137

0.8–1

1

Boiling137

0.5–0.6

1

Drying

137

1

0.1

Soaking of dried berries in water

137

0.8

0.1

Washing

137

0.4

1

Drying

137

Cs

1.0

0.1–0.12

90

Sr

1.0

Cs
Cs
Cs
Cs
Cs

Washing of dried mushrooms

137

0.5

0.1

Soaking of dried mushrooms in water

137

0.1–0.2

0.1

Salting

137

0.07–0.1

0.6–0.9

Boiling (30–60 min)137

0.1–0.3

0.6–0.8

Cs
Cs
Cs
Cs

90

Sr

0.2–0.9

Boiling of dried mushrooms

137

0.1

0.15

Pickling

137

Cs

0.06–0.1

0.6

90

Sr

0.5

Cs

Milk products may require careful consideration owing to the variety ofprocesses employed and products generated. It should be determined which
coagulation process is used for cheese making — the acid or rennet process.
Further, it should not be assumed that all whey will be discarded as waste oranimal feed. The food industry uses whey as an additive to human food. If all thewhey and the buttermilk is used for human consumption, it is more accurate touse an Fr value of 1.0 for all milk for collective dose assessment. However, suchan approach may not be appropriate for individual dose assessments, dependingon the mix of milk products consumed by the individuals of interest, and it may
be more appropriate to use the food processing factors for the different products
and assess the doses to the population groups separately, using their specificconsumption rates of the different products.
The values given in this section assume that the water used in cooking is
uncontaminated, which may not always be the case. Moreover, it is the custom insome cultures to consume the cooking water, in which case any tritium lost to thewater would still be ingested. For these reasons, in the absence of specificinformation, the reference food processing factor for 14C and T radionuclides
should be 1 (i.e. concentrations in food products should not be assumed to be
reduced when the food is processed).

153

TABLE 78. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR 137Cs IN SELECTED EDIBLE
MUSHROOM SPECIES
Mushroom species
Boletus edulis (dry weight)

Suillus variegatus(fresh weight)

Xerocomus badius(fresh weight)

Lactarius deliciosus,
L. necator, Russula delica(fresh weight)

Type of processing
Consecutive processing
Washing in flowing water for 10 min
Soaking in 0.85% salt solution for 10 h, followed
by washing in flowing water
Boiling for 5 min with extract removal
Boiling for 20 min with extract removal
Consecutive processing
Cleaning of mushroom cap
Washing in flowing water for 10 min
Boiling for 20 min. and washing in flowing waterfor 10 min
Pickling
Boiling for 5 min
Boiling for 10 min
Boiling for 20 min
Soaking for 20 min
Soaking for 40 min
Soaking for 60 min
Consecutive processing
Cleaning of mushroom cap
Washing in flowing water for 10 min
Soaking for 24 h
Soaking for 48 h
Soaking for 72 h
Salting in 2–3% salt solution for 72 h

FrPe

0.90–0.95
0.15–0.20

1.1
1.5–1.7

0.08–0.10
0.03–0.05

0.8–0.9
0.7

0.80–0.85
0.50–0.55
0.15–0.20

1.0
1.3
0.8

0.05–0.10
0.25–0.30
0.15–0.20
0.05–0.07
0.80–0.85
0.60–0.70
0.30–0.40

0.5
0.9
0.8
0.8
1.3
1.3
1.3

0.70–0.75
0.65–0.70
0.25–0.30
0.10–0.12
0.02–0.03
0.003–0.005

1.0
1.0
1.2
1.2
1.2
1.0

TABLE 79. 137Cs AND 90Sr PROCESSING RETENTION FACTORS (Fr) FOR
PREPARATION OF LIQUID WATER MEDICINAL FORMS (INFUSIONSAND BROTHS) FROM AIR DRIED MEDICINAL PLANT RAW MATERIAL
Fr

Group of medicinal plantraw material

N

FruitsFlowers

137

90

Cs

Sr

a

AM

SD

b

Min

Max

AM

SD

Min

25

0.49

0.27

0.11

0.87

0.43

0.09

0.29

0.59

20

0.60

0.29

0.15

0.93

0.47

0.21

0.16

0.73

Buds

20

0.55

0.08

0.44

0.58

0.50

0.10

0.40

0.55

Grass, leaves and shoots

115

0.57

0.15

0.20

0.92

0.46

0.12

0.22

0.75

Max

Rhizomes and roots

20

0.48

0.20

0.19

0.89

0.23

0.06

0.14

0.31

Bark

15

0.29

0.06

0.18

0.38

0.16

0.05

0.12

0.28

a
b

AM: Arithmetic mean.
SD: Standard deviation.

154

TABLE 80. FOOD PROCESSING RETENTION FACTOR (Fr) AND
PROCESSING EFFICIENCY (Pe) FOR LOWER SEA ORGANISMS
Raw material
Shrimp

Method of processing

Element

Washing with tap water
Washing with 1–3% solution of NaCl
Cooking

OysterMusselsClam

Washing with 1–3% solution of NaCl
Washing and removal of flesh

Washing with tap water
Washing with 1–3% solution of NaCl

Algae

Alginate production

Satiagum production

Fr

Pe

Ca

0.9

1.0

90

0.7

1.0

Sr

Ca

0.9

1.0

90

Sr

0.3–0.4

1.0

Pb

0.0–0.4

0.35

Po

0.04–0.8

0.35

Ra

0.04–0.5

0.35

Ca

0.8

1.0

90

0.7–0.8

1.0

Sr

Pb

0.5

0.25

Po

0.02

0.25

Ra

0.01

0.25

Ca

0.8

1.0

90

0.7

1.0

Sr

Ca

0.7–0.5

1.0

90

0.3–0.6

1.0

SrRu, Rh

0.07

0.04

Sr

0.6

0.04

Te

0.02

0.04

Co

0.04

0.08

Ru, Rh0.04

0.08

TABLE 81. DELAY TIMES (STORAGE AND PROCESSING TIMES) BETWEENHARVESTING AND CONSUMPTION OF FOOD PRODUCTS
Raw material

Typical delay time

Minimum

Maximum
1 year

Cereals and cereal products

6 months

45 days

Potatoes and beets

3 months

7 days6 months

Leafy vegetables

4 days

1 day

7 daysRoot vegetables

10 days

7 days14 days

Fruit vegetables

7 days2 days14 daysFresh apples and pears

3.5 months0

8 months

Fresh drupe fruits, soft fruit, rhubarb

4 days0

8 daysCanned fruit

1 year14 days

2 years

Frozen fruit

6 months

7 days1 yearJams and jellies

1 year

1 day

2 years
6 daysMilk

2 days

1 day

Butter1 month

3 days3 months

Cream

5 days2 days10 daysCondensed milk

6 months

7 days1 year155

TABLE 81. DELAY TIMES (STORAGE AND PROCESSING TIMES) BETWEENHARVESTING AND CONSUMPTION OF FOOD PRODUCTS (cont.)
Raw material

Minimum

Maximum

Pasteurized skimmed milk

Typical delay time
2 days

1 day

6 daysCheese (rennet coagulation)

1.5 months

30 days

3 months

Cheese (acid coagulation)

1 month

7 days2 months

Fresha beef

20 days

14 days

28 daysFresh a pork, veal

4 days2 days7 daysFresh a chicken

4 days2 days7 daysFresh a lamb

10 days

7 days14 daysFresh a game

10 days

2 days20 daysEggs

14 days

2 days28 daysaRefers to fresh meat; frozen meat would have longer delay times of up to 6 months.

12. USE OF ANALOGUES
In cases where there are no data or relatively few data for environmental
transfers of a radionuclide, an analogue, either for a process or for an isotope,
may be used to provide relevant information on environmental behaviour. The
use of analogues is not an accurate way of modelling, but it may be used inscreening models if few or no other data are available. Relevant knowledge suchas timescales of processes, physical, chemical and biological properties of theenvironment, and relevant media, is required to derive parameter values fromstable isotopes [5].
There are three main types of analogue that can be used for derivation ofvalues if measured or reference values are not available:
(1)
(2)
(3)

Analogue isotopes. Use of a parameter value for a related or similar
isotope2;
Analogue elements. Use of a parameter value for a related or similarelement;
Analogue species. Use of a parameter value for a related or similar species.

2

156

This approach was widely used in the current publication.

12.1. ANALOGUE ISOTOPES
Application of analogue isotopes is the most common form of analogue use
and is often used without any specific justification or even recognition that data
for an analogue are being used. Short lived fission products whose environmental
behaviour has been extensively studied in the context of reactor accidents or
routine discharges may be used as analogues for long lived isotopes of relevancefor solid waste disposal. For example, data for 131I may be used to predict the
behaviour of long lived 129I, or data for the well studied 134Cs or 137Cs may be
used to predict the behaviour of long lived 135Cs. Similarly, short lived andreadily available tracer radionuclides are often used in experiments as analogues
for isotopes found in radioactive discharges or waste.
In general, the behaviour of isotopes of the same element is identical,
except for light elements such as hydrogen. An important limitation andconsideration when using stable analogues is whether the timescale over which
behaviour of a short lived radionuclide can be studied is sufficient to reveal thesignificance of long term processes that may influence the behaviour of a long
lived radioisotope or stable isotope of the same element. In particular,
equilibration of a short lived isotope in environmental media may be strongly
influenced by its physical decay, whereas equilibration of a long lived or stable
isotope may be almost entirely determined by biogeochemical transfer
processes [5].

12.2. ANALOGUE ELEMENTS
The chemical properties of elements follow well established patterns thatcan sometimes be used as a basis for identifying potential analogues. Elements inthe same group (column) of the periodic table usually exhibit similar chemical
behaviour, because they have the same number of outer electrons available toform chemical bonds (i.e. they form compounds in the same valence state). In thecase of essential macroelements for plants located in soil, the uptake and transfer
of a chemically similar element (i.e. the element under study) will be influenced
by any lack or excess of the essential macroelement. However, generally similar
chemistry does not necessarily imply similar metabolic characteristics in plants
and animals, because of the high specificity of biochemical pathways. Thus,
although chlorine and iodine have many chemical similarities, their behaviour inmammals is very different because of the role of iodine in the production of
thyroid hormones [5].

157The most commonly used analogue element pairs are K and Cs, Ca and Sr,and Ba and Ra. Ba, Ca and K are regarded as elements that indicate the influenceof metabolic processes. Transition elements in the same period (row) of theperiodic table also tend to be chemically similar to one another [5]. Lanthanides
are oxidation state analogues for actinides, so their distribution can give an
indication of the long term behaviour of the radioactive transuranic elements;
however, there are exceptions, such as cerium and europium with their 4+ and 2+
oxidation states contrasting with the 3+ oxidation state common to alllanthanides.
Chemical similarity does not necessarily translate into similar behaviour inthe environment; sometimes the size of the ionic form of a radionuclide can cause
differences, particularly in the association processes.

12.3. ANALOGUE SPECIESFor plants, some analogues may seem relatively obvious, such as pasturegrass and forage. However, closer inspection may show that the analogy is not
close and may be misleading. Similarly, generic data for ‘grain’ might be
expected to provide a good analogue for fruits or rice, but the growing conditions
for rice are so different from those for cereals that the analogue is not, in general,a good one (see Section 5).
When making comparisons between animals of different types,
consideration also has to be given to the mass of the animal. Conventionally,transfers to animal products have been expressed through the use of transfer
factors that are the ratio of the concentration in the product to the rate of intake ofthe radionuclide. For unit rate of intake, the concentration in a particular producttends to be higher for animals of smaller mass, although this effect may be
counteracted by more rapid metabolic turnover in smaller animals.
In the case of different products from the same animal, the assumption ofsimilar transfer factors, for example, between checken and eggs, might seem
tempting, but is not appropriate. In the most common of these cases, one product(milk or eggs) is collected during the life of the animal whereas another (meat) isavailable only after the animal has been slaughtered, and the two products arevery different in nature. Other examples are different parts of the slaughteredanimal (flesh, liver, etc.): as with humans, many elements concentratepreferentially in certain tissues or organs. In particular, because of the major roleof the liver in detoxification, many transition metals, heavy metals, lanthanides
and actinides are concentrated in it, giving rise to concentrations that may be anorder of magnitude (or more) higher than concentrations in meat.

158

12.4. OTHER ANALOGUE APPROACHES
Soil Kd values can vary significantly with soil type (see Section 4). Where
knowledge of soil characteristics is not available, a generic soil Kd value can be
adopted. This may be an average over soil types, a value for the soil type
expected to maximize doses, or simply a value for the soil type for which data aremost extensive. If data are limited, the Kd for a soil can sometimes be used for asediment with similar characteristics (pH, Eh, etc.).

12.5. APPLICATION OF DATA
The use of analogues is not the preferred approach to modelling, but it isnecessary in those contexts in which directly applicable data are not available orare of dubious quality.
Although care is needed when considering the characteristics of eachindividual case, the general order of preference for data sources is as follows:
(1)
(2)

(3)
(4)

(5)

Data for the specific parameter for the specific radionuclide.
Data for the specific parameter for another isotope of the same element(preferably not a short lived isotope for a long lived isotope, as it may not
persist for long enough in the environment to reveal the characteristic
behaviour).
Data for the specific parameter for an analogue element.
Data for a related parameter (e.g. different plant type or animal product) for
the specific radionuclide/element. In general, plant type analogues tend to
be more reliable than animal product analogues.
Data for a related parameter for an analogue element.

The ordering of options (3) and (4) in particular will depend on the specificcase, and judgement will be necessary. For example, the order shown above
would be valid if the choice were between a well recognized element analogue
and a cross-species animal product analogue; on the other hand, the order would
be reversed if the choice were between data for a similar plant type for an elementwith high plant uptake and a speculative element analogue.
One can never be sure exactly how good any specific analogue is. An
analogue can only be proved to be valid by comparing its behaviour in theconditions of interest with that of the parameter for which it is an analogue.
Hence, while confidence in the validity of an analogue will increase as the qualityof the justification increases, there will always be some residual uncertainty.

159

As with any other choice of parameter values for modelling, decisions on
using analogues must take account of the assessment context and particularly thelevel of realism or conservatism of the assessment. The best analogue for a
realistic assessment might not be the best for a conservative assessment.
It is preferable to use elemental analogues that lie close to each other in achemical series; for example, among the lanthanides it could be samarium andeuropium. However, in practice, by far the most extensive data among thelanthanides are for cerium, so it is often most appropriate to use this as theanalogue when information is lacking for other lanthanide elements.
There are two main issues that could affect the validity of using an isotope
analogue. The timescales for experiments or observations on short lived isotopes
may be limited by radioactive decay and so might not reflect all aspects ofenvironmental behaviour in the long term. An important example is that of iodine
isotopes. The majority of experimental data relate to 131I, which is of great
importance in the context of accidental releases from nuclear power plants, andhas a half-life of about 8 days, whereas the isotope of interest for solid waste
disposal is 129I, with a half-life of 17 million years. Observations on 131I are
limited by radioactive decay to a period of a few months at most, and so may beof little value for identifying and characterizing long term behaviour, because thetimescale of the relevant processes in the environment is much longer than thehalf-life of 131I. In the opposite case, data for an analogue isotope that is long
lived or stable should exhibit the same short term behaviour as a short lived
isotope (with the exception of radioactive decay, which is generally modelled
explicitly), provided that observations of the long lived species have been madeon short enough timescales. However, although some care is needed in cases
where there are large differences in half-life — and especially when the analogue
isotope is short lived — isotopic analogues can normally be assumed to be morereliable than element or media analogues.
In addition to consideration of the effects of radioactive decay, it should berecognized that although isotopes of an element have similar chemical behaviour,
this chemical similarity is not exact and the differences will translate into subtle
differences of behaviour in the environment. This effect is demonstrated by theabsorption of common elements from the atmosphere — most plants show higher
ratios of 12C/13C, 14N/15N and 16O/18O than are found in the atmosphere, owing to
the difference in their chemical behaviour. These differences tend to be more
important for lighter elements because the relative mass differences are larger(e.g. the relative difference between the 7Be and 10Be nucleus is higher than the
difference between 226Ra and 228Ra, which is less than 1% regarding the mass).
Except for hydrogen and several light elements, biochemical differences causedby these isotopic differences will in general be much smaller than most otheruncertainties in the system. The environmental behaviour of different isotopes

160

may differ even simply because their modes of release or more general entry into
the biosphere, and consequently their distribution in the biosphere, are different.
The simplest example is the different chemical behaviour of released CH4 andCO2 regarding carbon, and from the point of view of hydrogen isotopes, released
as CH4 and H2O.
For element analogues, chemical similarity does not necessarily translate
into similar behaviour in the environment. For chemical group analogues, such asalkali earths, these differences will normally be large. For period analogues, suchas the lanthanides, the differences may be much smaller. Key considerations
include variations in valence and ionic radius. Thus, in the case of thelanthanides, there is a consistent trend across the series from predominantly 2+
through to 4+, and this trend may be reflected in trends in environmental
behaviour. A problem of element analogues is that the initial distribution ofelements in the environment can affect the behaviour of the radionuclides being
modelled. If the soil is naturally (or as a result of past activities) poor or rich in aparticular element that is (or behaves like) an important plant or animal nutrient,then the uptake and transfer of chemically similar radionuclides released to theenvironment will be affected. This may be a significant factor in selecting data
values, but should not affect the selection of analogues, because, by definition, if
the analogue is good, it will behave in the same way as the radionuclide ofinterest would.

161

.

Appendix I
REFERENCE INFORMATION ON TERRESTRIAL PLANTS
AND ANIMALSTABLE 82. DRY MATTER CONTENT IN PLANTS (%) [3, 261]
Crop

Seeds

Vegetative mass

Spring vetch

87

24Winter vetch

88

22

Field pea

85

17

Garden pea

83

16

Grass pea vine

86

21

Soya

87

26

Lupin yellow

85

14

Lupin blue86

Seradella
Broad beans

Grain

18
22

88

18.3

Bean (field, kidney and French)

28

Lentil25Winter rye

23

Wheat

18

88

Oats

28

87

Barley34

87

Maize (corn)

1985

Sudan grass

90

87

20

Sorghum

25

Annual rye grass

20

Millet23

Alfalfa

26

Sickle alfalfa

33

Bastard lucerne

23

Red clover

22

Ladino clover

26

Sainfoin23

White sweet clover

22

Yellow sweet clover

22

Fussian brome grass

21

Slender wheat grass

34

Couch grass

37

Standard crested grass

39

Timothy grass

26

87
88

163

TABLE 82. DRY MATTER CONTENT IN PLANTS (%) [3, 261] (cont.)
Crop

Seeds

Vegetative mass

Meadow fescue

20

Cock’s foot grass

22

Meadow grass

22

Cabbage

12

Lettuce

8.0

Leek

11

Onion (above ground part)

11

Spinach8.0

Celery6.0

Cauliflower

11

Kohlrabi

6.0

Tomato6.0

Cucumber

5.0

Pumpkin (English)

7.5

Vegetable marrow (English)

9.0

Zucchini

5.0

Beetroot (red beet)

16

Sugar beet

22

Radish9.0

Carrot14

Potato21

Turnip (swede)

12

Jerusalem artichoke

22

Tapioca38

Raspberry
Watermelon

16
7.0

TABLE 83. DRY MATTER CONTENTIN FRUITS [262]

164

Feed

Dry matter content (%)

Apple

15.6

Pear

16.8

Peach

10.9

Apricot
Orange

14.7
14

Grape

18.4

Strawberry
Watermelon

10.1
7.4

Grain

TABLE 84. DRY MATTER CONTENTIN FEED [263]Feed

Dry matter content (%)

Concentrate feed

88

Grass silage

26

Pasture20

Grass hay86

Lucerne hay

86

Lucerne silage

34

Corn silage

25

TABLE 85. DRY MATTER CONTENT OF WILD BERRIES (%) [264–266]
English name

Arithmetic Standard
mean
deviation

Latin nameN

Minimum

Maximum

Blueberry

Vaccinium myrtillus

307

13.2

Lingonberry

Vaccinium vitis-idaea

254

14.1

1.9

8.6

21

1.3

11.3

Cranberry

Vaccinium oxycoccus

16

10.8

18.8

0.9

9.3

12.1

Bog bilberry

Vaccinium uliginosum

6Black crowberry

Empetrum nigrum

1

12.1

1.1

10.5

13.5

7.4

—

—

Cloudberry

Rubus chamaemorus

26

—

14.0

1.6

9

18

Wild raspberry

Rubus idaeus

21

Wild strawberry

Fragaria vesca

1

17.3

1.8

14.4

21.9

15.4

—

—

—

TABLE 86. CARCASS WEIGHT (kg) AND MEAT FRACTION OF GAME
[264–268]
Species of animal

Carcass weight (kg)Fraction of meat in carcass weight

1.9×102

0.80

Moose, calf

8.3×101

0.78White-tailed deer

5.0×101

0.78

3.3×101

0.78

Roe deer

1.8×101aBrown hare

2.4

Arctic hare

1.8

0.90

Capercaillie

1.9

0.90

Black grouse

6.6×10–1

0.90

Hazel grouse

2.4×10–1

0.90

Willow grouse

3.6×10–1

0.90

Partridge

2.4×10–1

0.90

Moose, adult

Fallow deer

0.78
0.90

165

TABLE 86. CARCASS WEIGHT (kg) AND MEAT FRACTION OF GAME
[264–268] (cont.)
Species of animal

Carcass weight (kg)Fraction of meat in carcass weight–1

Pheasant

6.9×10

Goose

2.3

0.90

Eider

1.3

0.90

Long-tailed duck

3.8×10–1

0.90

6.6×10–1

0.90Goldeneye

4.5×10

–1

0.90

Teal

1.8×10–1

0.90

Mallarda

0.90

Roe deer gain more weight in Northern than in Central Europe.

TABLE 87. WATER CONTENT IN FRESHWATER AND RIPARIAN DIETARYITEMS AND TISSUES CONSUMED BY HUMANS (%) [269, 270]
Food type

Arithmetic mean

Standard deviation

Minimum

Maximum

Algae

84

4.7

71

97

Aquatic macrophytes

87

3.1
45

93

Aquatic macrophyte tubers

90

0.030

86

92

Emergent vegetation tubers

90

0.020

81

93

82

4.5

Isopods

71

80

Cladocerans

79

87

67

79

Aquatic primary producers

Emergent vegetation

Aquatic invertebrates
Bivalves (without shell)

Aquatic vertebrates
Bony fishes

75

5.1

Reptiles and amphibians
Snakes/lizards

66

Frogs/toads

85

4.7

68

1.6

Mammals
Mice/voles/rabbits
Birds
Passerines (with typical fat 
reserves)

68

Mallard duck (flesh only)

67

166

TABLE 88. CARBON AND PERCENTAGE HYDROGEN CONTENT IN FRESHWATER AND RIPARIAN DIETARY ITEMS AND TISSUES CONSUMED BY
HUMANS [271–274]
(on a per unit dry weight basis)Type of
organism

Type oftissuePercentage C (per unit dry weight)
N

AMa

SDb

Mini- Maximum mum

Percentage H (per unit dry weight)
N

AM SD

Mini- Maximum mum

Algae

Whole

29 47.5

11.5

29.3

70.2

2

4.4

0.4

4.1

4.6

Aquatic macrophytes

Not specified

19 31.0

3.1

25.8

37.6

n.a.c

n.a. n.a.

n.a.

n.a.
6.6

Animals

Not specified

2

46.7

2.4

45.0

410.0

2

6.6

0.1

6.5

Invertebrates

Whole

43 47.5

5.2

34.3

55.1

5

5.6

1.2

4.5

7.3

Molluscs

Soft tissue

1

n.a.

n.a.

n.a.

1

6.0

n.a.

n.a.

n.a.

39.9

a

AM: Arithmetic mean.
SD: Standard deviation.
cn.a.: Not available.
b

167

Appendix II
PLANT GROUPS AND ASSOCIATED CROPSTABLE 89. PLANT GROUPS, WITH COMMON AND LATIN NAMES OF
ASSOCIATED CROPS [5]Plant group
Cereals

Common name

Latin nameRye

Secale cereale L. subsp. cereale

Wheat

Triticum aestivum L. non. cons. subsp. aestivum

Oats

Avena sativa L.

BarleyHordeum vulgare L. subsp. vulgare

Maize (corn)

Zea mays L. subsp. mays

Sorghum

Sorghum bicolor (L.) Moench

MilletPanicum L.

Buckwheat

Fagopyrum esculentum

Foxtail millet, Italian millet

Setaria italica L.

Maize (corn)

Zea mays L. subsp. mays

Rice

Rice

Oryza sativa L.

Leafy vegetables

Hiroshimana (pot herb, mustard)

Brassica rapa L.

Kikuna (chop suey green)

Chrysanthemum coronarium L. var. Spatiosum
L.H. Bailey

Mizuna (green)

Brassica rapa L. subsp. nipposinica
(L.H. Bailey) Hanelt (Mizuna Group)

Burdock (great burdock)

Arcitum lappa L.

Asparagus

Asparagus officinalis L.

PurslanePortulaca oleracea L.

Cabbage, flowering

Brassica rapa L. var. parachinensis
(L.H. Bailey) Hanelt

Chinese spinach

Amaranthus tricolor L.

Cauliflower

Brassica oleracea L. var. botrytis L.

Cabbage

Brassica oleracae L. var. capiatata L.

Pak-choi, Chinese cabbage

Brassica rapa L. chinensis (L.) Hanelt

Kale

Brassica oleracea L. var. viridis L.

KohlrabiBrassica oleracea L. var. gonylodes L.

Lettuce

Lactuca sativa L.

Leek

Allium porrum L.

Swiss chard

Beta vulgaris L. subsp. cicla (L.) W.D.J. Kochvar. flavescens (Lat.) Lat&DC

SpinachSpinacia oleracea L.

CeleryApium graveiolus L. var. dulce (Mill.) Pers.

Chinese lettuce

Lactuca sativa L. var. angustana L.H. Bailey

Maize

Sorrel168

TABLE 89. PLANT GROUPS, WITH COMMON AND LATIN NAMES OF
ASSOCIATED CROPS [5] (cont.)
Plant group
Non-leafy
vegetables

Leguminous
vegetables

Root crops

Common name

Latin nameTomatoLycopersicon esculentum Mill.

Ladies’ fingers (gumbo, okra)

Abelmoschus esculentus (L.) Moench

Eggplant (brinjal)

Solanum melongena L.

Bottle gourd

Lagenaria siceraria (Molina) Standl.

Pepper, banana pepper

Capsicum annuum L. var. annuum

Amaranthus (pigweed)

Amaranthus L. spp.

Red chili (pepper)

Capsicum frutescens L.

Eggplant

Solanum melongena L.

Cucumber

Cucumis sativus L. var. sativus

Squash (American)

Cucurbita pepo L.

Pumpkin (English)

Cucurbita pepo L.

Vegetable marrow

Cucurbita pepo L.

Zucchini

Cucurbita pepo L.

Onion

Allium cepa L.

GarlicAllium sativum L.

American artichoke

Helianthus tuberosus L.

PepperCapsicum annuum L. var. annuum

Peas (garden pea, field pea)

Pisum sativum L.

Chickpea, garbanzo

Cider arietinum L.

Hyacinth bean

Lablab purpureus (L.) Sweet subsp. purpureus

Soybean, soya

Glycine max (L.) Merr.

Soya (wild soybean)

Glycine max (L.) Merr. (= Glycine hispida L.)

Bean (field, kidney, French)

Phaseolus vulgaris L. cultivars

LentilLens culinaris Medik. subsp. culinaris (Ervum
lens L.)

Asiatic haricot bean (mung bean)

Phaseolus aurens Roxb. = Vigna radiate (L.)
R. Wilczek

Horse beans

Vicia faba L., var. equina Pers.

Beet, beetroot, red beet/mangold

Beta vulgaris L. subsp. vulgaris (Crassa Group)

Sugarbeet

Beta vulgaris L. subsp. vulgaris

Turnip (swede)

Brassica napus L. var. napobrassica (L.) Rchb.

RadishRaphanus sativus L.

CarrotDaucus carota L. subsp. Sativas (Hoffm.)
Arcang.

Manioc, manihot; cassava, yucca, tapioca Manihot esculenta Crantz,
Manihot ultissima
TubersPotatoSolanum tuberosum L. subsp. tuberosum

Yam

Dioscorea L. spp.

Arrowhead

Sagittaria sagittifolia L. subsp. Leucopetala(Miq.) Hartog

Sweet potato

Ipomoea batatas L.

169

TABLE 89. PLANT GROUPS, WITH COMMON AND LATIN NAMES OF
ASSOCIATED CROPS [5] (cont.)
Plant group
FruitsGrasses(cultivated
species)170

Common name

Latin nameApple

Malus domestica Borkh.

Date palm

Phoenix dactylifera L.

BananaMusa L. spp.

PapayaCarica papaya L.

Pear

Pyrus L. spp.

CherryPrunus L. spp.

Apricot

Prunus armeniaca L.

Peach

Prunus persica (L.) Batsch var. Persica

Prunes or plums

Prunus domestica L.

Strawberry

Fragaria ananassa Duchesne

Black currant

Ribes nigrum L.

Red currant

Ribes rubrum L.

Gooseberry

Ribes uva-crispa L.

Raspberry

Rubus ideaus L.

Blackberry

Rubus L. spp.

Melon

Cucumis melo L.

Watermelon

Citrullus lanatus (Thunb.) Matsum. & Nakai

Lemon

Citrus limon (L.) Burm.

OrangeCitrus sinensis (L.) Osbeck

Grapefruit

Citrus paradisi Macfad.

Mandarin

Citrus reticulate Blanco

Avocado

Persea Americana Mill. var. americana

Mango

Mangifera indica L.

GrapesVitis L. spp.

Olive

Olea europaea L. subsp. europaea

Blueberry

Vaccinium L. spp.

Pineapple

Ananas comosus (L.) Merr.

Pomegranate

Punica granatum L.

Sudan grass

Sorghum sudanensis (Piper) Sterf.

Perennial ryegrass

Lolium perenne L.

Annual ryegrass

Lolium multiflorum Lam. var. Westerwoldicum

Bromegrass (smooth brome)

Bromus inermis (Leyss.) Holib.

Smooth bromegrass

Bromus racemosus L.

Quack grass, couch grass

Elytrigia repens (L.) Desv. ex Nevski.

Siberian crested wheatgrass

Agropyron fragile (Roth) P. Candargy subsp.
sibircum (Willd.) Melderis

Standard crested wheatgrass

Agropyrum desertorum Fisch. ex Link Schult.

Fairway crested wheatgrass

Agropyrum cristatum (L.) Gaertn.

Timothy grass

Phleum pratense L.

Meadow fescue

Festuca pratensis Huds.

TABLE 89. PLANT GROUPS, WITH COMMON AND LATIN NAMES OF
ASSOCIATED CROPS [5] (cont.)
Plant group
Grasses(cultivated
species)Leguminous
fodder(cultivatedspecies)

Pasture(species
mixture)Common name

Latin name

Redtop (Am.) creeping bent grass (Eur.) Agrostis gigantean Roth (American) or Agrostis
stolonifera L. (European)
Orchard grass, cocksfootDactylis glomerata L.

Bluegrass, meadow grass

Poa annua L.

Bluegrass, meadow grass

Poa steppe (Kryl.) Roshev.

“Grass”

Gramineae

Reed grass

Calamagrostis Adans. spp.

Sedge

Carex L. spp.

Sheep fescue

Festuca ovina L.

Spring vetch (common vetch)

Vicia sativa L.

Leucaena

Leucaena leucocephala (Lam.) de Wit

Desmodium

Desmodium Desv. spp.

Winter vetch (hairy vetch)

Vicia villosa Roth.

Peas (field pea)

Pisum sativum L. subsp. sativum var. arvense(L.) Poir.

Grass peavine, grass pea

Lathyrus sativus L.

Lupin yellow

Lupinus luteus L.

Lupin (blue lupin)

Lupinus angustifolius L.

Seradella

Ornytorus sativus L. Ornithopus satious Brot.

Bean (fava bean, broad bean)

Vicia faba L.

Clover (crimson clover)

Trifolium incarnatum L.

Alfalfa (Black Medic)

Medicago lupulina L.

Alfalfa blue

Medicago sativa L.

Alfalfa yellow

Medicago sativa L. falcate (L.)

Alfalfa hybrid

Medicago sativa L. varia (Martyn)

Clover red

Trifolium pratense L.

Clover (hybrid clover)

Trifolium hybridum L.

Clover white

Trifolium repens L.

Esparsetter (animal forage)

Onobrychis Mill.

Sweet clover, white

Melilotus albus Medik.

Sweet clover, yellow

Melilotus officinalis Lam.

Grass–leguminous mixture (festuca +timothy–clover, oats–clover….)
Natural grasses mixture
Undefined mixture
Canadian thistle

Cirsium arvense (L.) Scop.

171

TABLE 89. PLANT GROUPS, WITH COMMON AND LATIN NAMES OF
ASSOCIATED CROPS [5] (cont.)
Plant group
Herbs

Common name

Latin nameWhite mustard

Sinapis alba L.

Basil, sweet basil

Ocimum basilicum L.

NigundiVitex negundo L.

Coriander, cilantro

Coriandrum salivum L.

Parsley

Petroselinum crispum (Mill.) Nyman ex
A.W. Hill

Spearmint

Mentha spicata L.

Dill

Anethum graveolens L.

African spider flower

Cleome gynadra L.

Milkweed, crownplant (giant milkweed) Calotropis gigantea (L.) Dryand. ex W.T. Aiton
CassiaCassia tora L.

Seaside clerodendrum (tubbeflower,
Turk’s turban)

Clerodendrum indicum (L.) Kuntze

Wild indigo, fish poison

Tephrosia purpurea (L.) Pers.,
T. sinapou (Buc’hoz) A. Chev.

Hogweed (red hogweed, red spiderling) Boerhavia L.

Other crops

172

Indian and leaf mustard

Brassica juncea L.

Tea

Camella sinensis L.

Thyme

Thymus L.

Rape (winter rape)

Brassica napus L.

Margosa

Azadirachta indica A. Juss.

WalnutJuglans regia L.

Canola, rape

Brassica napus L. napus

Sunflower

Helianthus annuus L.

PeanutArachis hypogaea L.

Flax

Linum usitatissiumum L.

TobaccoNicotiana tabacum L.

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.

CONTRIBUTORS TO DRAFTING AND REVIEW
Balonov, M.

St Petersburg Institute of Radiation Hygiene, RussianFederation

Barnett, C.L.

Centre for Ecology and Hydrology, United Kingdom

Belli, M.

Istituto Superiore di Ricerca per la Protezione
Ambientale (ISPRA), Italy

Beresford, N.A.

Centre for Ecology and Hydrology, United Kingdom

Berkovsky, V.

International Atomic Energy Agency

Bossew, P.

Institute for Environment and Sustainability, DG Joint
Research Centre, European Commission, Italy

Boyer, P.

Institut de radioprotection et de sûreté nucléaire, France

Brittain, J.E.

University of Oslo, Norway

Calmon, P.

Institut de radioprotection et de sûreté nucléaire, France

Carini, F.

Università Cattolica del Sacro Cuore, Piacenza, Italy

Choi, Y.H.

Korea Atomic Energy Research Institute,
Republic of Korea

Ciffroy, P.

Electricité de France, France

Colle, C.

Institut de radioprotection et de sûreté nucléaire, France

Conney, S.

Food Standards Agency, United Kingdom

Davis, P.

Chalk River Laboratories, Atomic Energy of Canada
Limited, Canada

Durrieu, G.

CEREGE, France

Ehlken, S.

Klinikum Bremen-Mitte, Germany

Fesenko, S.

International Atomic Energy Agency

191

Galeriu, D.C.

“Horia Hulubei” National Institute for Physics andNuclear Engineering, Romania

Garcia-Sanchez, L.

Institut de radioprotection et de sûreté nucléaire, France

Garnier, J.-M.

CEREGE, France

Gerzabek, M.H.

University of Natural Resources and
Applied Life Sciences, Austria

Gil-García, C.J.

Universitat de Barcelona, Spain

Golikov, V.

St Petersburg Institute of Radiation Hygiene,
Russian Federation

Gondin Fonseca, A.M.

International Atomic Energy Agency

Howard, B.J.

Centre for Ecology and Hydrology, United Kingdom

Hubmer, A.

Institute of Physics and Biophysics, University ofSalzburg, Austria

Isamov, N.

Russian Institute of Agricultural Radiology andAgroecology, Russian Federation

Jourdain, F.

Commissariat à l’énergie atomique, France

Jova Sed, L.

International Atomic Energy Agency

Juri Ayub, J.

GEA-IMASL, Universidad Nacional de San
Luis/Conicet, Argentina

Kashparov, V.

Ukrainian Institute of Agricultural Radiology, Ukraine

Kirchner, G.

Federal Office for Radiation Protection, Germany

Krasnov, V.

Ukrainian Institute for Forestry and Agro-Forest
Amelioration, Ukraine

Leclerc, E.

Agence nationale pour la gestion des déchets
radioactifs, France

Lettner, H.

Institute of Physics and Biophysics, University ofSalzburg, Austria

192

Linsley, G.

Consultant, United Kingdom

Louvat, D.

International Atomic Energy Agency

Madoz-Escande, C.

Institut de radioprotection et de sûreté nucléaire, France

Martin, P.

International Atomic Energy Agency

Melintescu, A.

“Horia Hulubei” National Institute for Physics andNuclear Engineering, Romania

Monte, L.

Ente per le Nuove Tecnologie, l’Energia e l’Ambiente,
Italy

Olyslaegers, G.

SCK•CEN Belgian Nuclear Research Center, Belgium

Orlov, O.

Ukrainian Institute for Forestry and Agro-Forest
Amelioration, Ukraine

Palsson, S.E.

Icelandic Radiation Protection Institute, Iceland

Periañez, R.

University of Sevilla, Spain

Peterson, S.R.

Lawrence Livermore National Laboratory, UnitedStates of America

Pröhl, G.

Institute of Radiation Protection, Germany

Rantavaara, A.

Radiation and Nuclear Safety Authority, Finland

Ravi, P.M.

Bhabha Atomic Research Centre, India

Reed, E.

SENES Oak Ridge Inc., Centre for Risk Analysis,
United States of America

Rigol, A.

Universitat de Barcelona, Spain

Sansone, U.

International Atomic Energy Agency

Sanzharova, N.

Russian Institute of Agricultural Radiology andAgroecology, Russian Federation

Saxén, R.

Radiation and Nuclear Safety Authority, Finland

193

Shang, Z.R.

Nuclear Safety Centre of SEPA, China

Shaw, G.

University of Nottingham, United Kingdom

Shubina, O.

Russian Institute of Agricultural Radiology andAgroecology, Russian Federation

Siclet, F.

Electricité de France, France

Skuterud, L.

Norwegian Radiation Protection Authority, Norway

Smith, J.T.

University of Portsmouth, United Kingdom

Strebl, F.

Austrian Research Centres, Austria

Tagami, K.

National Institute of Radiological Sciences, Japan

Tamponnet, C.

Institut de radioprotection et de sûreté nucléaire, France

Thiry, Y.

SCK•CEN, Belgian Nuclear Research Center, Belgium

Uchida, S.

National Institute of Radiological Sciences, Japan

Vandenhove, H.

SCK•CEN, Belgian Nuclear Research Center, Belgium

Varga, B.

Agricultural Authority, Hungary

Velasco, H.

GEA-IMASL, Universidad Nacional de San
Luis/Conicet, Argentina

Vidal, M.

Universitat de Barcelona, Spain

Voigt, G.

International Atomic Energy Agency

Yankovich, T.

EcoMetrix Incorporated, Canada

Zeiller, L.

International Atomic Energy Agency

Zibold, G.

Hochschule Ravensburg-Weingarten, Germany

194

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7HOHSKRQH RU )D[(PDLOVDOHVSXEOLFDWLRQV#LDHDRUJ:HEVLWHKWWSZZZLDHDRUJERRNVThis report provides data for use in assessments of routine discharges of radionuclides toterrestrial and freshwater environments. Someof the data may also be useful for assessing theimpacts of accidental releases and releases in
the future. The report provides information onradionuclides and on processes to be taken into
account in assessments of the radiation impact
of radionuclide discharge to terrestrial andfreshwater ecosystems. The data collected here
are relevant to the transfer of radionuclides
through food chains to humans. Radionuclidetransfers to non-human species are not specifically addressed; however, in many situations
the data are also applicable for assessmentsof such transfers. Although the data primarily
relate to equilibrium conditions — that is, conditions where equilibrium has been establishedbetween movements of radionuclides into andout of compartments of the environment —some data relevant to time dependent radionuclide transfer in the environment are also
included.

INTERNATIONAL ATOMIC ENERGY AGENCY
VIENNA
ISBN 978–92–0–113009–9
ISSN 0074–1914