Download Element transport in aquatic ecosystems – modelling general

Element transport in aquatic
ecosystems – modelling general and
element-specific mechanisms
Lena Konovalenko
©Lena Konovalenko, Stockholm University 2014
ISBN 978-91-7649-026-6
Printed in Sweden by US-AB, Stockholm 2014
Distributor: Department of Ecology, Environment and Plant Sciences
Cover illustration: Lena Konovalenko
This thesis is devoted to my family.
“Uncertainty is everywhere and you cannot
escape from it.” Dennis Lindley
Abstract
Radionuclides are widely used in energy production and medical, military and
industrial applications. Thus, understanding the behaviour of radionuclides
which have been or may be released into ecosystems is important for human
and environmental risk assessment. Modelling of radionuclides or their stable
element analogues is the only tool that can predict the consequences of
accidental release.
In this thesis, two dynamic stochastic compartment models for
radionuclide/element transfer in a marine coastal ecosystem and a freshwater
lake were developed and implemented (Paper I and III), in order to model a
hypothetical future release of multiple radionuclides from a nuclear waste
disposal site. Element-specific mechanisms such as element uptake via diet
and adsorption of elements to organic surfaces were connected to ecosystem
carbon models. Element transport in two specific coastal and lake ecosystems
were simulated for 26 and 13 elements, respectively (Papers I and III). Using
the models, the concentration ratios (CR: the ratio of the element or
radionuclide concentration in an organism to the concentration in water) were
estimated for different groups of aquatic organisms. The coastal model was
also compared with a 3D hydrodynamic spatial model (Paper II) for Cs, Ni
and Th, and estimated confidence limits for their modelled CRs. In the absence
of site-specific CR data, being able to estimate a range of CR values with such
models is an alternative to relying on literature CR values that are not always
relevant to the site of interest.
Water chemistry was also found to influence uptake of contaminants by
aquatic organisms. Empirical inverse relationships were derived between CRs
of fish for stable Sr (CRSr) and Cs (CRCs) and water concentrations of their
biochemical analogues Ca and K, respectively (Paper IV), illustrating how
such relationships could be used in the prediction of more site-specific CRCs
and CRSr in fish simply from water chemistry measurements.
Key words: radionuclides, elements, concentration ratio, bioaccumulation,
biomagnification, fish, modelling, aquatic food web, ecosystem, Cs, Sr,
environmental risk assessment.
List of papers
Paper I
Konovalenko L., Bradshaw C., Kautsky U., Kumblad L., 2014. Radionuclide
transfer in marine coastal ecosystems, a modelling study using metabolic
processes and site data. Journal of Environmental Radioactivity, 133, pp. 4859
Paper II
Erichsen A.C., Konovalenko L., Møhlenberg F., Closter R., Bradshaw C.,
Aquilonius K., Kautsky U., 2013. Radionuclide Transport and Uptake in
Coastal Aquatic Ecosystems: A Comparison of a 3D Dynamic Model and a
Compartment Model. AMBIO, 42(4), pp. 464-475.
Paper III
Konovalenko L., Andersson E., Bradshaw C., Kautsky U. Transfer of 13
elements in a lake using a process-based ecosystem model. (Manuscript for
Ecological Modelling).
Paper IV
Konovalenko L., Bradshaw C., Andersson E., Lindqvist D., Kautsky U.
Evaluation of factors influencing accumulation of stable Sr and Cs in lake and
coastal fish. (Manuscript for Journal of Environmental Radioactivity).
My contribution to the papers:
Paper I: Main writer of the paper, implemented the marine compartment
model and carried out calculations, reviewed the literature.
Paper II: One of the main writers of the paper together with A.C. Erichsen
and C. Bradshaw, carried out calculations for the compartment model,
reviewed the literature.
Paper III: Main writer of the paper, developed the lake compartment model
and run simulations and evaluated results, reviewed the literature.
Paper IV: Main writer of the paper, analysed results of chemical analysis of
water and fish, produced calculations and regression data analysis, reviewed
the literature.
Table of contents
Introduction .................................................................................................. 1
Objectives of the thesis ............................................................................................ 3
Study regions ............................................................................................... 4
Modelling as a tool in environmental risk assessment ........................ 7
Key parameters in radionuclide transport models .............................................. 8
Distribution coefficient (Kd) ................................................................................ 8
Concentration ratio (CR)..................................................................................... 9
3-D hydrodynamic transport models ..................................................................... 9
D- Model: hydrodynamic-ecological model ................................................... 10
Compartment model ............................................................................................... 11
K-model: ecological compartment model for coastal environments ........ 12
L-model: ecological compartment model for lakes ...................................... 14
Discussion ................................................................................................... 16
Conclusions ................................................................................................. 22
Future research .......................................................................................... 24
Acknowledgment ....................................................................................... 25
References .................................................................................................. 26
Abbreviations & definitions
CI
CR
D-model
DHI
DIC
DOC
HD
IAEA
K-model
L-model
PDF
PM
POC
SD
SFR
SKB
NPP
3D
Confidence Interval
Concentration ratio - the ratio of the element or
radionuclide concentration in an organism to the
concentration in surrounding media
Hydrodynamic spatial model for element transfer
in a marine coastal ecosystem (Paper II)
Danish Hydraulic Institute
Dissolved inorganic carbon
Dissolved organic carbon
Hydrodynamic model
International Atomic Energy Agency
Stochastic compartment model for element
transfer in a marine coastal ecosystem (Papers I,
II)
Stochastic compartment model for element
transfer in a fresh water lake (Paper III)
Probability Density Function
Particulate matter
Particulate organic carbon
Standard Deviation
Swedish repository for low and intermediate
radioactive waste
Swedish Nuclear Fuel and Waste Management
Co, Svensk Kärnbränslehantering AB
Nuclear Power Plant
3 Dimensional
Introduction
A number of accidents have resulted in radionuclide contamination of the
environment. Due to the accidents in Kyshtym (1957), Three Mile Island
(1979), Chernobyl (1986) and recently Fukushima (2011) there is a need for
better descriptions and understanding of the transfer of radionuclides in food
webs, and the availability of these radionuclides to humans. Many efforts are
currently being made to improve environmental protection capabilities by
comparing and validating dose assessments models for biota that have been
developed for planned, existing and emergency radionuclide releases.
Radiation protection programmes have traditionally focused on the protection
of humans. However, during the last few years there have been more efforts
made to develop better evaluation tools to specifically assess the potential risk
to non-human biota (ICRP 2007; Beresford et al., 2008).
The importance of tools to adequately predict radionuclide concentration in
aquatic biota and their surrounding media has been emphasized by several
authors (Yankovich, 2005; Monte et al., 2009b; IAEA 2012a; Avila et al.,
2013). These predictions are fundamental for internal and external dose
estimates to aquatic biota in models developed for use in environmental
protection. The prediction can either be based upon field measurements or
model assessments. Since field measurements or literature values may not
always be available for the particular ecosystem or radionuclide of interest
(Copplestone et al., 2013; Howard et al., 2013), especially when considering
future hypothetical releases (Kautsky et al., 2013; Lindborg et al., 2013), a
modelling approach to evaluate these concentrations is essential.
Radionuclides are assumed to have the same chemical properties as their
stable isotopes, except for the slight differences resulting from the difference
in mass (Santschi & Honeyman, 1989). In the aquatic environment,
radionuclides are therefore transported and taken up by biota in a similar way
to their stable element analogues. If stable and radioactive isotopes of a
particular element have the same chemical form, they are thought to be
indistinguishable to organisms (Sazykina 2003). Bioaccumulation or sorption
of a certain radionuclide by living organisms is not linked to its radioactivity,
but reflects the difference between the content of the stable chemical element
in the environment and in the organism (Sazykina 2000). Modelling concepts
based on stable elements are therefore applicable to radionuclide modelling.
1
Anthropogenic radionuclides present in the Baltic Sea and its catchment area
have two main sources: 1) During 1950-1980 the United States and the Soviet
Union carried out atmospheric nuclear weapons tests (UNSCEAR, 2000); 2)
The accident at the Chernobyl nuclear power plant in 1986 caused
considerable fallout of Cs-137 and Sr-90 over the Baltic Sea and areas of
eastern Sweden (HELCOM, 2009; Håkanson et al., 1992). However, it should
be remembered that there are other potential sources of a wide range of
different radionuclides.
The future potential release of radionuclides from nuclear facilities is an issue
that will be important for the coming centuries or more. Radionuclides have
military, industrial and medicinal applications as well as being used to produce
electricity through nuclear power production. After use, these radionuclide
sources become radioactive waste that must be stored safely, for example in a
repository, and isolated from the environment as long as they pose a risk for
humans and biota. The amount of radioactive waste is predicted to increase in
the future, as energy needs grow and many countries (e.g. Vietnam, South
Africa, India, China, Finland) are building new nuclear power plants, of which
many will be situated in coastal areas (Fowler and Fisher, 2005). As a
consequence, authorized discharge into the sea will increase, as well as the
probabilities of new nuclear accidents. The whole nuclear fuel cycle, from
radionuclide mining through production and use of the fuel, also includes
possibilities for environmental contamination. The risk of radionuclide
releases to the environment will exist as long as society continues to actively
use anthropogenic radionuclides. Thus, we require knowledge about
radionuclide behaviour in the different types of ecosystems, especially in
aquatic environment, because water helps to transfer and distribute elements
in the ecosystem.
The main focus of this thesis is to describe and model the transfer of
radionuclides in the aquatic environments of a specific marine coastal region,
including brackish water bays and freshwater lakes, located in the Forsmark
area, eastern Sweden. This area is the location of one of Sweden’s nuclear
power plants, as well as one existing and one proposed facility for nuclear
waste storage. The site was chosen for the good availability of ecosystem and
element concentration data from previous and on-going work by the Swedish
Nuclear Fuel and Waste Management Company (SKB). The thesis takes as its
starting point the potential release of radionuclides from nuclear facilities, but
it also advances our knowledge and expertise in ecosystem modelling in
general, and also its application to the transport of non-radioactive elements
in aquatic ecosystems.
2
Objectives of the thesis
The main aim of this thesis is to model radionuclide and element transfer in
aquatic food webs (using generic and element-specific processes) in order to
improve assessment of environmental risk.
The specific objectives are to:



develop ecological element transport models for lake and coastal
ecosystems and simulate concentration ratios (CRs) of biota which
are widely used in risk assessment to estimate element
concentrations in biota from measured water concentrations (Paper I
and III).
compare the compartment model described in Paper I with a 3D
spatial dynamic model (Paper II) and investigate how the two
different models can complement each other and for what situations
the models are most applicable.
evaluate how environmental factors such as water chemistry and
seasonal variation may influence bioaccumulation of Sr and Cs in
fish (Paper IV) and impact on the range of the CR values that are
used in risk assessment.
3
Study regions
The main study area is the Forsmark area in eastern Sweden, including both
coastal brackish water areas (Öregrundsgrepen) and freshwater lakes (Fig. 1).
In June 2009, the Swedish Nuclear Fuel and Waste Management Co. (SKB)
decided to put forward the Forsmark area as the suggested site for the
geological repository of Sweden’s spent nuclear fuel and carried out an
extensive safety assessment analysis (SKB, 2011). The sketch of this planned
repository is illustrated in Fig. 2 (b). The study area is ideal for element
transport modelling, because of the detailed descriptions and large amount of
field data available (Lindborg et al., 2008, 2010; Aquilonius et al., 2010).
The model presented in Paper I was applied to a specific area of
Öregrundsgrepen, one of 28 sub-basins referred to as number 116 (Fig. 1).
This area was also used in simulations by a 3D spatial dynamic model in Paper
II. Basin 116 is located above the existing final repository for radioactive
operational waste (SFR) which is embedded in the bedrock 50 m under the
seabed, and stores low- and intermediate level radioactive waste (Fig. 2, a).
The area is shallow (mean depth c. 10 m) and salinity is low (c. 5 psu); this
brackish water results in a combination of marine and freshwater species being
present in the coastal area. A more detailed description of marine ecosystem
Forsmark area is available in Aquilonius et al. (2010) and Kumblad et al.
(2003, 2006).
In Paper III, Lake Eckarfjärden was studied and for model comparison data
from two other Forsmark lakes were used, Bolundsfjärden and Fiskarfjärden
(Fig. 1). A detailed description of these lakes is available in Andersson (2010).
These same three lakes were also considered in Paper IV, together with Lake
Frisksjön in the Laxemar-Simpevarp area in south-east Sweden (Fig. 1) where
another of Sweden’s nuclear power plants is located. In Paper IV, data from
the coastal areas of Forsmark and Laxemar-Simpevarp were also included in
the analyses.
4
Figure 1. Maps showing the location of the Forsmark and Laxemar-Simpevarp study
areas, situated on the Swedish Baltic Sea coast. Top left: the locations of the coastal
site sub-basin 116 in Forsmark that was modelled in Papers I and II. Top right: the
three lakes in the Forsmark area used for modelling (Paper III) and for fish and water
samples (Paper IV), and the coastal area used in Paper IV. Bottom: the lakes and
coastal bays where data for Paper IV were collected. NPP − Nuclear Power Plant.
5
Figure 2. (a) Swedish repository for low and intermediate radioactive waste (SFR)
and an example of the planned extension for low-level radioactive waste. SFR is
located in the vicinity of Forsmark Nuclear Power Plant (NPP) (from Berner et al.
2009). (b) Sketch of the planned future final repository for spent nuclear fuel, 500m
below ground in the Forsmark area, Sweden (sketch by SKB).
6
Modelling as a tool in environmental risk
assessment
With the help of a modelling approach it is possible to describe and identify
element transport processes (both specific and generic) and make predictions
for risk assessment about transport and cycling of both naturally-occurring
and human-introduced elements, including radionuclides. Many European
countries have implemented models of radionuclide release into the
atmosphere and aquatic environment that are imbedded in Decision Support
Systems such as RODOS (Hofman et al., 2011) and MOIRA (Monte et al.,
2009a). Models are the only tools to predict the consequences of accidental
release and to support decision makers for remediation action.
This thesis considers hypothetical future releases from a high level radioactive
waste repository. For long-term risk assessment of the impact to humans and
biota in case such releases, more than 40 radionuclides need to be considered
(Kautsky et al. 2013). In Sweden, Canada and many other countries it is
obligatory for the waste disposal company to demonstrate that the
environment is adequately protected.
In radioecological modelling, several methodological approaches have been
applied to describe radionuclide migration in aquatic ecosystems. The most
common are compartment models (Paper I, III) and spatial and temporal
hydrodynamic models (Paper II). The structure of a model can be increased
almost indefinitely by incorporating more fluxes (mass/time), amounts (mass)
and concentrations (mass/volume) to and from the defined compartments, but
one of the main tasks is to find the most important processes and optimum
amount of parameters adequate to characterise the system, which are capable
of keeping the model’s robustness. Inter-comparisons of a range of modelling
approaches from different countries (Beresford et al., 2008) have recognised
that variation in estimates of final radiation dose to organisms depends
significantly on the prediction of whole-body activity concentrations, which
are in turn defined by concentration ratios (CRs; see below). The main reason
for some of the observed variability is the inclusion in assessments of
inappropriate CR values, especially when site-specific data are not available
(e.g., CR values are taken from a biogeochemically similar element or a
‘similar’ organism). Instead of using CRs of analogue organisms or elements,
7
which are often misleading, a modelling approach for the prediction of a range
of site-specific CRs for different functional groups of aquatic organisms is
proposed in Papers I-III.
Key parameters in radionuclide transport models
Aquatic systems are influenced by a complex variety of physical, geochemical
and biological processes, which influence the behaviour, transport and fate of
radionuclides released into the water or sediment. Two of the key parameters
that are used extensively in environmental risk assessment analysis to describe
geochemical and biological processes in transport models are distribution
coefficients (Kd) and concentration ratios (CR).
Distribution coefficient (Kd)
Radionuclides in the aquatic environment occur in two phases: dissolved
radioactive substances which are redistributed by the flow field in a
conservative form more or less passively, and particle reactive radionuclides
which tend to attach to particles or suspended material in the water column.
Particle reactive and non-reactive radionuclides/elements are classified
according to a radionuclide/element specific distribution coefficient Kd (m3 kg
dw-1 (dry weight)) which is defined as the ratio of the concentration of
radionuclide/element in solid phase of sediment (Cs) or particulate matter
(CPM) and in liquid phase in water (Cw) in an equilibrium state (Harms et al.,
2003):
𝐵𝑞
𝑘𝑔
(
)
𝐶𝑃𝑀 (𝑘𝑔 𝑑𝑤 )
𝑚3
𝑘𝑔 𝑑𝑤
𝐾𝑑 =
=
or
=(
)
𝐵𝑞
𝑘𝑔
𝐶𝑤
𝑘𝑔 𝑑𝑤
( 3)
( 3)
𝑚
𝑚
Particle reactive elements with high distribution coefficient (Kd >10 m3 kg-1)
have a tendency to attach to suspended particles or to the sediment strongly
enough to change their dispersion behaviour in the aquatic ecosystem. Nonreactive elements which have low (Kd ≤10 m3 kg-1) mainly dissolve in the
water and can be transported long distances from the release point with water
currents. The measured Kd values of stable elements for marine and freshwater
ecosystems recommended by IAEA for modelling radionuclide transport can
be found in reports (IAEA 1985a, 2004, 2009, 2010).
The distribution coefficient of suspended particulate matter, Kd PM, in marine
or freshwater environments is usually expressed in the units m3 kg-1, but can
also be converted into m3 gC-1 by multiplying by the ratio of dry weight to
carbon content for particulate matter (PM), e.g. 0.006 kg dw gC-1 (Kumblad
8
et al., 2006). This is more suitable for some models, because biomass is often
presented in mass of carbon since this is a more ecologically relevant unit than
dry weight.
Concentration ratio (CR)
In the latest IAEA reports (IAEA 2004; IAEA 2010) and the online database
www.wildlifetransferdatabase.org the concentration ratio (CR) is defined as
the ratio of the radionuclide concentration in the organism tissue (fresh weight,
fw) from all exposure pathways (including water, sediment and ingestion
pathways) relative to that in water:
CR (L kg-1) = Caquatic biota/ Cw= (Bq kg fw-1)/(Bq L-1),
where Caquatic biota is the concentration per unit mass of organism (kg/kg fw or
Bq/kg fw); Cw is the concentration per unit volume of sea water (kg L-1 or Bq
L-1). The CR definition assumes that the radionuclide in the organism is in
equilibrium with its surrounding media. The time required to achieve such
equilibrium is dependent on both the biological half-life of the radionuclide in
the organism and the radionuclide physical half-life.
The CR can be also presented in the units m3 kg C-1 where the mass of biota
is expressed as the carbon content (e.g. kg C), for example, the models in
Paper I and Paper III and in site assessments carried out by the Swedish
Nuclear Fuel and Waste Management Company (SKB) (e.g., Nordén et al.,
2010; Tröjbom & Nordén, 2010; Avila et al., 2010; Kumblad & Bradshaw,
2008). The units m3 kg C-1 can be useful when the mass balance of aquatic
ecosystems is calculated in carbon and it is assumed that pollutant follows
organic fluxes in the food web. Conversion coefficients for all marine biota in
the study area for converting data from wet weight, dry weight or carbon
weight are published in Kumblad and Bradshaw (2008). In some cases, it is
adequate for modelling purposes to use average CR values and assume
equilibrium over the spatial and temporal scales examined. However, in other
cases it may be more appropriate to use or estimate ranges of CR in space and
time. This is discussed further in all four thesis papers.
3-D hydrodynamic transport models
Three-dimensional hydrodynamic radioecological models (e.g., Paper II) are
often used for short term assessment of accidental release; these models can
model pollution in the ecosystem with great spatial and temporal resolution,
and identify areas of concern such as likely hotspots of contamination. For
instance, models described by Erichsen et al. (2010) or Margvelashvili et al.
9
(2002) can produce the results of simulations in terms of maps of radionuclide
distribution in the water, sediment and biota, but they are computationally
heavy and quite complicated. Also, in order to make model predictions more
accurate, site-specific input parameters are desirable, which can be time
consuming and costly.
Hydrodynamic models for the dispersion of elements (e.g., Paper II) typically
involve two coupled models: a hydrodynamic model (HD model) and a
transport model. The HD models are models that consist of mathematical
equations that are solved at discrete time steps on a regular or irregular grid
that covers the model domain, i.e. the region of interest. HD models are able
to calculate three-dimensional flow fields based on the realistic topography of
the area and realistic forcing functions like wind or water density. In some
cases, time steps of less than one hour are able to resolve a spectrum that
ranges from tidal motions to decadal variability. Numerical transport models
of dissolved elements/radionuclides calculate the advection and the diffusion
of a substance or a tracer. Combined HD and transport models are able to
provide results with a high spatial and temporal resolution (Harms et al.,
2003). They are also able to model transport of contaminants both in the
dissolved and particulate phase. Suspended particles may play an important
role
as the carriers of contaminants over long distances from the release areas with
water currents, or alternatively transport contaminants down to the bottom
where they may be buried in the sediment.
D- Model: hydrodynamic-ecological model
Erichsen et al. (2010) developed the hydrodynamic-ecological-radionuclide
model (referred to here and in Paper II as the D-model) for Öregrundsgrepen,
Sweden. The D-model was used to predict the spread of radionuclides and
subsequent accumulation in sediments and biota following a hypothetical loss
of radionuclides from a repository for nuclear waste at Forsmark nuclear
power plant. The D-model assumes that radionuclides are introduced to the
pore water of the lower sediment layer via groundwater inflow. Seven
radionuclides Cl-35, Cs-135, Nb-94, Ni-59, Ra-226, Th-230 and C-14 were
modelled explicitly. The model coupled ecosystem and radionuclide food web
models with a hydrodynamic model for the area. Conceptually, the ecosystem
model and the radionuclide model were developed based on the general food
web structure developed in earlier modelling studies within the area (Kumblad
& Kautsky, 2004; Kumblad et al., 2006). The results from the hydrodynamic
model provide inputs to the coupled ecosystem model and the results from the
ecological model provide inputs to the radionuclide models. The ecosystem
model is used to illustrate the spatial and temporal variation in important
processes and parameters. In the biotic components, radionuclides are either
10
adsorbed to surfaces or accumulated internally in the organisms.
In autotrophic organisms radionuclide uptake and accumulation are driven by
and scaled to their photosynthetic activity. In heterotrophic organisms
radionuclides are taken up through the food chain by grazing or predation. The
D-model was applied and validated in Paper II, where it was also compared
with a compartment model (L-model, see below).
Compartment model
Compartment models (Papers I, II, III) are used to estimate the impact on the
environment of long-term release when equilibrium between organisms and
the surrounding sea or freshwater can be expected. These models belong to
the category of the so-called “fully mixed” hydrological dispersion models
that have been well described in the scientific literature (e.g., IAEA, 1985b;
1994; Håkanson & Monte 2003). Many of them are physical compartment
models, e.g. models by Avila et al. (2010), Bird et al. (1993), IAEA (2000),
BIOMOVS II (1996a, b), for predicting the radionuclide concentration in
aquatic biota based on the steady-state approach, which assumes a constant
equilibrium between the radioactivity concentration in water and in
organisms, through the concentration ratio (CR). Thus, physical models
estimate elements/radionuclide concentrations in abiotic compartments, and
then the concentrations in aquatic organisms are assessed by multiplying
measured CR with the element/radionuclide concentration in water (or
sediment).
More complicated models are ecological/radioecological compartment
models which include biological processes and are based on the equations for
biomass dynamics of populations or ecological groups of species. The
ecological equations describe the transfer of chemical elements
(radionuclides) from the environment to the food chains of organisms and
back to the environment (ecological cycles of the elements). The compartment
models in this thesis are based on the fluxes of carbon in the ecosystem. One
model of this type (K-model), applicable for the simulation of element
transport in a coastal ecosystem, is discussed in Paper I and further examined
in Paper II. Another one was developed for element transport in a freshwater
lake (L-model) and implemented in Paper III. The compartment models
(Paper I, Paper III) are computationally faster than 3D hydrodynamic models
(Paper II) and can allow estimates for more than for 100 years into the future,
which is important when considering long-lived radionuclides.
11
K-model: ecological
environments
compartment
model
for
coastal
Historical model development
Kumblad et al. (2003) first presented an ecosystem model describing the flows
of carbon and C-14 through a coastal food web in the ecosystem above the
underground nuclear waste repository (SFR) in the Forsmark area. From the
carbon flow model, additional parameters and assumptions were made in
order to estimate the flow of C-14 in the same area in 2000 years from the
present (Kumblad et al., 2004a) and for 25 other radionuclides present in the
nuclear waste repository (Kumblad et al., 2006). In this thesis, this multiradionuclide model was then implemented in the new software Ecolego
(http://ecolego.facilia.se/), updated with newly available site-specific data and
verified with concentration ratios (CR) for 26 elements (Paper I) and
compared with simulation results of a 3D hydrodynamic transport (Paper II).
The conceptual approach of this model was then used as the basis for a lake
ecosystem model (Paper III).
Model description
Details of the model are described in Paper I, but a short description is given
here to demonstrate the similarities and differences with the other modelling
approaches. The food web model describes the biomass distribution and the
carbon dynamics of the ecosystem. It was conceptualized with eight
compartments, 6 biotic and 2 abiotic (Fig. 3). In the biota compartments,
organisms having the same ecological function and residing in the same
habitat were grouped together. Initial data were determined at species or
family level, either from site-specific in situ measurements or derived from
site-specific biomass data. The carbon flows were constrained by temperature,
light intensity and inorganic carbon available for photosynthesis, and these
parameters were based on field data from the site. The basic biological
processes respiration, consumption, faeces production and excess excretion
are represented in the model (Fig. 3). The main model input parameters were:
 biomass of each compartment
 net productivity (primary producers) and consumption, respiration
rates and assimilation efficiencies (AEs) of consumers
 dietary composition of fish
 average radius of species in each functional group and of particulate
matter
These parameters and their distributions were used in probabilistic
simulations. A water exchange mechanism was connected to all pelagic
components of the ecosystem, i.e. phyto- and zooplankton, dissolved
inorganic matter (DIM) or dissolved inorganic carbon (DIC) and particulate
matter (PM) or particulate organic carbon (POC), to be able to model import
12
and export of matter to and from the system. DIC was defined as entering the
food web through photosynthesis (primary production) and to be transferred
to higher trophic levels via grazing and predation according to the food web
structure. The biomass of the compartments (standing stock) was assumed to
remain constant between years.
Radionuclides were then assumed to follow the flow of organic matter in the
food web and radionuclide relocation was regulated by two radionuclide
specific mechanisms: adsorption to organic surfaces and uptake by primary
producers. Radionuclide-specific dynamics depended on distribution
coefficients, Kds, between radionuclides in suspended particulate matter. In
most cases, element site-specific Kd data were applied (Nordén et al., 2010).
For those elements where element-specific site data were lacking, literature
data were used. Kds were converted into the units m3 gC-1, since all organic
transport in the food web model was based on carbon flow.
Uptake of radionuclides by consumers was subdivided into two processes:
 adsorption to the organisms’ body surface which are estimated using Kd;
 accumulation through the ingestion and assimilation of contaminated
food.
Radionuclides were retained in the organisms, and release took place only
when organisms died, were consumed or were released from organisms with
the faeces.
13
Figure 3. Visualization of element transport and cycling in the coastal marine
ecosystem compartment model (K-model) (Paper I, Paper II). The arrows illustrate
the element flows, shapes illustrate model compartments.
L-model: ecological compartment model for lakes
The adsorption of elements from water on to the surfaces of organisms and
particles was taken into account, additionally assuming that pollutants follow
proportionally to flows of organic matter via the food web. The model was
partly descriptive, rather than predictive, mainly because input site-specific
data were only available for modelling and there was not enough data for
complex model validation. The element-specific parameters implemented in
the model were Kd PM and Kd sed, which were derived based mainly on measured
site-specific data and accessible for 13 elements from an earlier study
(Tröjbom et al., 2013). The key concepts of the lake transport L-model (Paper
14
III) were identical with the K-model for the coastal area (Paper I; Kumblad et
al., 2003, 2006), though additional processes and compartments that were
specific for the lake were included. The lake ecosystem was subdivided into
16 compartments, 5 abiotic and 11 biotic (Fig. 4). Major differences to the Kmodel were to include the process of sedimentation of organic matter and
additionally 4 abiotic compartments: Sediment gyttja, Burial sediment, DOC
and POC. Moreover, two biotic compartments, bacterioplankton and benthic
bacteria, were considered separately in the L-model, while in the K-model
they were taken into account as a part of phytoplankton and benthos,
respectively. Fish were subdivided into three compartments, zooplanktivorous
(Fish-Z), benthivorous (Fish-B) and piscivorous (Fish-P), in contrast to the
coastal K-model where only one general fish compartment was considered
and included all three fish groups.
Figure 4. The carbon budget of Lake Eckarfjärden showing carbon fluxes (kgC/y) and
initial biomasses (kgC).
15
Discussion
For long-term risk assessment of impact to humans and biota from a high level
radioactive waste repository in the case of a hypothetical release in future,
multiple radionuclides need to be considered (Kautsky et al., 2013). CR values
are the most commonly used parameters in many estimates of radionuclide
concentrations in organisms. However, a major source of error in the
prediction of these concentrations is the use of inappropriate CR values, taken
from the literature or extrapolated from other sources. Thus modelling
approaches that can estimate a likely range of CRs are a preferable method.
Development of compartment models of element transport for lakes and
marine coastal ecosystems
Estimations of radionuclide redistribution between water, sediment and their
transport with water currents, as well as the uptake by aquatic organisms, are
fundamental for concentration and dose assessments. The studies in this thesis
have contributed to assessment the fate of the radionuclides and elements in
the aquatic environment and their transfer to biota. Prior to this thesis
considerable research has been devoted to modelling and prediction of
radionuclide transport of Cs-137 and Sr-90 (Heling & Bezhenar., 2009;
Lepicard et al., 2004) but less attention has been paid to predicting other
ecologically significant radionuclides such as I-131, Zr-95, Nb-95, Pu-239
and Po-210 in marine and freshwater environments. Only occasionally have
uptake of a few elements by a specific species (Baines et al., 2002; Vives i
Batlle et al., 2008) or transfer via a simple food chain (Smith, 2009) been
considered. However, consideration of a set of radionuclides/elements is
particularly important for evaluating the radioecological and ecological
consequences of accidents in the early critical period of accidental
contamination and for long-term assessment (Kryshev et al., 1999). In this
thesis, the coastal food web model in Paper I modelled and verified the transfer
of 26 elements (Ac, Am, Ag, Ca, Cl, Cm, Cs, Ho, I, Nb, Ni, Np, Pa, Pb, Pd,
Po, Pu, Ra, Se, Sm, Sn, Sr, Tc, Th, U, Zr) and 8 compartments, and the lake
transport model in Paper III modelled 13 elements (Al, Ca, Cd, Cl, Cs, I, Ni,
Nb, Pb, Se, Sr, Th, U) and 16 compartments. Both models were able to
estimate ranges of CR for the radionuclides and organisms that generally
agreed well with the data available for verification, especially those elements
with high Kd. The models also allow extrapolation to future altered ecosystems
(e.g. through land rise or climate change) since they provide a method that can
16
be scaled to ecosystem properties and where element-specific processes are
separated from generic processes which are equally valid for all elements.
The main structural difference between the lake (L-model, Paper III) and
marine (K-model, Paper I) element transport models are that sedimentation
processes of particulate organic matter were taken into account in the lake
model, because the lake is a more isolated water system with lower water
retention time (328 days) and much greater sedimentation rate than coastal sea
area. In the K-model for the coastal area, where water retention time is very
short (1 day), water currents are more important since they transport
particulate organic carbon (POC), phyto- and zooplankton, together with
adsorbed contaminants, in and out of the modelled area.
This short retention time in the model, and the use of measured stable element
CRs for comparison, may have been responsible for the low predicted
zooplankton CRs of low Kd PM radionuclides. The model assumes that
adsorption of elements on zooplankton surfaces from the water happens
immediately and the concentration on their surfaces reaches equilibrium with
the water concentration. Thus for elements with high Kd PM where adsorption
is mainly responsible for total element accumulation of zooplankton and the
dietborne pathway is less important, the calculated CRs for zooplankton were
close to measured CRs (Paper I, Fig. 4). In the model, the clean zooplankton
which had previously fed on uncontaminated food outside the modelled area,
are transported with water currents into the area where radionuclide release
occurs. The retention time in the study basin is only one day, while the lifetime
of zooplankton is around one month; thus, they are unlikely to reach a steadystate condition for dietborne contaminant exposure. This could be a reason
why predicted CRs were lower than measured CRs for elements with low Kd
PM, where dietary uptake is important. This could be tested by ‘turning off’ the
flux of zooplankton to and from the modelled area and comparing the new
modelled values with measured CRs.
Another difference between the coastal and lake models was that dissolved
organic carbon (DOC), microphytobenthos, and heterotrophic bacteria
compartments were included in the lake L-model. The L-model (Paper III)
estimated that benthic bacteria has the largest surface adsorption of all
functional groups for the studied lake, up to 89% of total surface adsorption,
though their biomass is only 11% of the total biomass in the lake. Because of
the large surface to volume ratio of bacteria, they can absorb a large amount
of pollutants on their surface, especially particle-reactive elements
characterized by high Kd PM. Thus, pollutants once adsorbed on to bacterial
surfaces from the surrounding water or sediment pore water could be
incorporated into the food web via mixotrophic phytoplankton and benthic
fauna. The benthic part of the ecosystem was much more important in element
transfer in the lake ecosystem than the marine ecosystem due to its dominance
17
in terms of biomass and surface area and due to differences in water depth and
water exchange between the two. The fact that essentially the same model
could be applied to two such different ecosystems is evidence of its robustness
and flexibility.
Most radiological models have difficulty in estimating confidence intervals
for their model predictions, because of the absence of a standard methodology
for uncertainty assessment and its application for environmental predictions
(Iosjpe et al. 2006, Mardevich et al. 2014, Periáñez et al. 2015). The models
in Paper I and III are capable of estimating the range of concentration ratios
(CRs) for marine coastal and freshwater biota. The uncertainty intervals in the
predictions in most cases overlapped the uncertainty intervals of the
observations for CRs of zooplankton, grazers of macroalgae and benthos. In
the context of risk assessment of radionuclides centuries or millennia in the
future, this level of agreement is acceptable (Avila et al., 2013). The
development and use of probabilistic radioecological models should be
prioritized in the future, because they are more suitable for the prediction of
the range (confidence intervals) of calculated results than simple deterministic
models which give only average estimated values that can lead to under- or
overestimation of radionuclide transfer. There is also a need for more
standardised criteria for model verification, which is currently lacking. Results
of deterministic models are usually verified with average measured data, or
modelled results are considered acceptable if they are within the error bars of
the measured data (Tateda et al., 2013, Periáñez et al., 2012, 2015). For
probabilistic models, authors usually consider predicted values of the median
(50% percentile) and 95% confidence interval (CI) and check how much these
overlap with measured average and standard deviation (SD) (Kryshev et al.,
1999; IAEA 2012b; IAEA 2012c).
Estimation of concentration ratios (CRs) in aquatic biota
Uptake and elimination of radionuclides, many of which are metals and heavy
metals, are not governed by simple diffusion processes, but are rather a
function of the exposure concentration, the geochemical form, the biology of
the species and physiological mechanisms (Chapman & Adams, 2007). The
process is controlled by complicated biological mechanisms. Most of the
metal transport proteins present in biological cell membranes are involved in
ion regulatory processes and the uptake of essential elements (Simkiss &
Taylor, 1995).
The models in this thesis give a reasonable prediction of CRs for most
functional groups of marine and freshwater organisms for large set of elements
(Paper I and III). At least in the context of risk assessment of radionuclides
centuries or millennia in the future, this level of agreement is acceptable
(Avila et al., 2013). However, the models in Papers I and III estimated CR
18
values for fish that were higher by up to one order of magnitude compared to
measured CRs for many of investigated elements. This is probably largely
because of the assumption that the excretion rate is zero, a simplification made
since it is very difficult to precisely simulate complex accumulation and
elimination mechanisms. Besides, assimilation of metals by fish is determined
both by subcellular metal distribution in the prey, as well as the feeding
process and digestive physiology of the fish (Wang & Rainbow, 2008). The
estimation of the role of trophic transfer in metal bioaccumulation is important
in the context of hazard evaluation. Effects of dietary exposure are metal- and
species-specific, and therefore, are most accurately assessed through studying
specific food-consumer relationships. Thus, in order to produce more realistic
estimates by modelling, it may be necessary to take into account additional
element-specific mechanisms and parameters, e.g. element assimilation
efficiency (AE) and elimination rates for the investigated organisms.
However, an assumption of zero excretion may be appropriate to ensure
conservative estimates of radionuclides in fish that may be subsequently be
eaten by humans.
The atmospheric fallout from the Chernobyl and Fukushima accidents
consisted largely of the radionuclide Cs-137, which was discharged into the
environment and taken up by organisms into the food chain. Thus Cs-137 can
be potentially one of the radionuclides most responsible for internal exposure
from contaminated food for people eating products coming from polluted
sites. Many models (e.g., Kryshev & Ryabov, 2000; Tsumune et al., 2011)
have therefore been developed for predicting transfer of Cs-137 in
ecosystems, and estimating doses and possible adverse effects on human
health and wildlife from Cs-137. Such models are often assumed to work
equally well for other radionuclides. Both of the models developed in this
thesis (K-model and L-model, Paper I and III) reproduced CRs and ranges of
variation for Cs well for most investigated organism groups. Nevertheless, the
difference between the modelled and measured CRs values for some other
elements was more than one order of magnitude. Consequently, it was
demonstrated that a model verified only for one element (e.g., Cs), does not
necessarily guarantee the same satisfactory results for other elements.
Environmental factors influence bioaccumulation of Sr and Cs in fish
The concentration ratio definition assumes that the radionuclide in the
organism is in equilibrium with its surrounding media (IAEA 2004). However,
in reality the relationship between the concentration of an element or
radionuclide in a living organism and the surrounding water is dynamic. Rates
of both uptake and excretion are known to be affected by body size, rate of
change of body size, temperature, salinity, etc. Moreover, seasonal variation
in the biological uptake of elements may be great. Relatively little effort has
been made to quantify the seasonal variation in CRs in aquatic organisms. It
19
is to be expected, consequently, that real differences exist between some CRs,
even for the same element and species, and that the variability in the data
reflects true environmental fluctuations in any area (IAEA 2004).
Paper IV explored variation in the CRs of stable Sr and Cs for freshwater and
brackish-water fish species based on field observations in the Forsmark area,
Sweden. There were significant seasonal variations (factor of 3-7) in the
measured concentrations in lake water for K, Ca, Sr and Cs. Thus, relying on
single measurements or extrapolating from other datasets may result in
misleading CR values. The determination of these element concentrations in
water is important, because it can be crucial for further calculation of CR for
fish. The determined range of CRs for lake fish using the L-model (Paper III)
overlapped with the range of CRs derived from measured data (Paper IV) for
fish muscle tissue: simulated Cs was 4.9 – 840 m3 kg dw-1 and measured Cs
was 1.1 – 23.6 m3 kg dw-1; simulated Sr was 0.019 – 7.8 m3 kg dw-1 and
measured Sr 0.002 – 0.043 m3 kg dw-1. Hence, the lake L-model (Paper III)
was verified for the estimation CR of Sr and Cs for fish. The L-model takes
seasonal variation into account by calculating probability distribution
functions of CR; the estimated range covers this variation.
Inverse relationships between CRs of fish for Sr and Cs and water
concentrations of Ca and K.
Water chemistry may also influence uptake of contaminant by aquatic
organisms. Calcium (Ca) and potassium (K) are biological macroelements,
and also the analogues of strontium and caesium, respectively (Vanderploeg
et al., 1975; Smith et al., 2003, 2009). In Paper IV, in contrast to the other
modelling Papers I, II and III, empirical inverse relationships were derived
between CRs of fish for stable Sr and Cs and water concentrations [Ca] and
[K], respectively. These CRs were based on site-specific measured
concentrations of water and fish from lakes and coastal area in Forsmark, and
these relationships agreed well with previous studies for isotopes Sr-90 and
Cs-137 (Outula et al., 2009; Kryshev, 2006; Smith et al., 2000). Using these
empirical equations from Paper IV, it should be possible to estimate
accumulation of Sr in fish only by measuring the levels of Sr and Ca in the
water (and for Cs in fish using only concentration Cs and K in the water).
Applications and comparison of the different model approaches
The comparison of the compartment K-model described in (Paper I) with the
3D spatial dynamic D-model (Erichsen et al., 2010) exposed strengths and
weaknesses of the two model approaches (Paper II). Using these two models,
the CRs were estimated for Ni, Cs and Th for phytoplankton, zooplankton and
fish. The agreement between empirical data and model predictions was good
for most observations, suggesting that both models are robust. However, the
models showed different levels of complexity with one based on a simple
20
compartment approach to the other making use of transport-diffusion
equations and finite element method.
The model comparison gives the possibility to evaluate: i) which models are
more appropriate for the management of complex environmental problems; ii)
how to provide more effective environmental monitoring; iii) how uncertainty
of model input parameters influences the output results; and iv) what kind of
model is better to apply for specific contamination scenario.
In the case of new accidental releases, dynamic models are essential to capture
the temporal variation in transport and radioactive decay or radionuclides. For
example, the environmental impact of the nuclear accident at Fukushima has
been estimated by applying different radionuclide transport models, in
combination with extensive field sampling. In the course of the Fukushima
nuclear accident the majority of the radionuclides were transported offshore
and deposited in the Pacific Ocean (Steinhauser et al., 2014). Many field
samples of water, sediment and biota were carried out and analysed for
radioisotopes in order to assess risk for aquatic organism and dose for human
via ingested marine food (Buesseler et al., 2012; Tagami & Uchida, 2012;
Takahashi 2014). Three dimensional hydrodynamic transport models have
been used to simulate distribution of Cs-137 (Periáñez et al., 2012; Tsumune
et al., 2014) in the marine coastal water and sediment near Fukushima. A
dynamic compartment food chain transfer model has been developed for
simulation of Cs-137 transfer in the southern Fukushima coastal biota (Tateda
et al., 2013). A dynamic compartment transfer model for Cs-134, Cs-137, I131 has been applied to predict concentrations and dose for different aquatic
organism in the Fukushima Dai-Ichi South Channel (Vives i Batlle et al.,
2014).
21
Conclusions
Two models were developed and evaluated: the element transport
compartment K-model (Paper I) for coastal food-webs for 26 elements and the
lake L-model (Paper III) for 13 elements. The uncertainty intervals in the
predictions, in most cases, overlapped the uncertainty intervals of the
observations for CRs of zooplankton, grazers of macroalgae, benthos and fish,
indicating that such a method is suitable for estimating CRs where site data is
not available. These models estimations may be preferable to using CR data
from the literature, which may come from very different environments and is
often only available as averages or best estimates. The distribution coefficients
(Kd PM) suspended particulate matter and upper sediment (Kd sed) played an
important role in modelling and were largely responsible for the different
resulting output values for different elements, because these parameters are
element-specific. The distribution coefficients that were applied with
probability density functions (PDF) in probabilistic simulations also
contributed to the CR ranges obtained. In the absence of site-specific CR data,
being able to estimate a range of possible CR values with such models is more
robust than relying on single CR values from the literature or extrapolating
from data that are not always relevant to the site of interest. CRs modelled in
this way also indirectly take into account temporal variation in environmental
element concentrations, such as those found in Paper IV.
In the case of radioactive waste disposal, it is required that environmental
protection and human safety is demonstrated for at least 10 000 years into the
future. In this situation, biosphere assessment models are necessary to make
quantitative predictions of risk, because this cannot be demonstrated directly.
The marine and lake ecosystem models (Papers I and III) described in this
thesis can be part of the biosphere model which can then be applied to estimate
possible total doses to humans and biota. These food-web models are able to
assess the range of bioaccumulation of radionuclides (or elements) in aquatic
organisms, so they can also be of great use in environmental toxicology,
determining environmental quality criteria and establishing effective
countermeasures for, in particular, metals.
The models in Papers I and III demonstrated the possibility to combine a large
amount of different measured data collected for the same region, but
22
distributed in time and space. Such modelling can help to better understand
and assess the ecological risk associated with dietborne and waterborne
exposure of radionuclides and metals to aquatic organisms.
The K-model (compartment) and D-model (3D dynamic) (Paper II) could be
used to complement each other in different ways: the D-model, with its greater
spatial and temporal resolution, could identify areas of concern, and then this
area could be modelled on a longer time scale with the K-model; the D-model
can serve as a partly independent validation of the K-model.
Paper IV concluded that stable Cs and Sr may be used for the determination
of CR of fish as an analogue for Cs-137 and Sr-90, respectively. Thus, the
results of estimation CR of Sr and Cs for freshwater and marine fish can be
included as additional values for assessment of the range of variation in CRs.
In addition, it demonstrated the strong inverse relationship between CRCs and
water [K] and between CRSr and water [Ca], illustrating how such
relationships could be used in the prediction of more site-specific CRCs and
CRSr in fish simply from water chemistry measurements.
23
Future research
Further work is required to gain a better understanding of the factors that
influence radionuclide/element transfer to biota, particularly for less wellstudied species (e.g. invertebrates, mixotrophic phytoplankton), for less wellstudied radionuclides/elements, also for types of biota that show wide ranges
of radionuclide transfer factors (e.g. macroalgae, phyto- and zooplankton). For
further validation of the developed lake model (Paper III) it is important to
simultaneously collect samples for water and lake organisms from all
functional groups in L. Eckarfjärden, and to chemically analyse a wide set of
elements, in order to determine CRs. The CRs based on site-specific measured
data will be possible to compare with predicted and estimated more precisely
transfer via food chains.
In the aquatic models developed in this thesis (Paper I−III) the simulations
were executed separately for every element, thus it was assumed that one
element concentration did not influence another element’s assimilation or
adsorption by organisms. However, in future models the water chemistry
needs to be taken into account because, for example, concentrations of K (an
analogue of Cs) and Ca (an analogue of Sr) may influence uptake by aquatic
organisms, as demonstrated in Paper IV. It is also known that the analogue of
Ra is Ba, and of Th is Pu, but it would be useful to identify other analogues
and evaluate how the presence of one may influence the uptake of the other
by biota. More processes that affect aquatic organisms uptake and excretion,
such as body size, temperature, light (in the case of algae) and salinity need to
be included in future models.
24
Acknowledgment
This thesis would not have been possible without the help, support, friendship
and patience of my principal supervisor, Associate Professor Clare Bradshaw,
not to mention her advice and unsurpassed knowledge of marine biology. The
good advice and support of my supervisors Dr. Ulrik Kautsky, Dr. Linda
Kumblad and Dr. Peter Saetre have been invaluable on both an academic and
a personal level, for which I am extremely grateful.
I would like to acknowledge, SKB who provided the necessary financial
support for this research. I thank participants of SR-Site SKB project for
useful discussions, particularly Eva Andersson, Karin Aquilonius, Sara
Nordén and Mats Tröjbom. I thank the staff at Facilia AB for their help and
assistance, particularly Rodolfo Avila, Per-Anders Ekström, Kristofer
Stenberg, Per-Gustav Åstrand, Erik Johansson and Robert Broed for their
advice concerning implementation of the compartment model in the software
Ecolego. I am most grateful to Sara Grolander, Jesper Torudd and Idalmis De
la Cruz for providing me with computer files of site-specific data and
references to publications, which have been valuable and reliable.
I would specially like to thank my article co-authors Anders Christian
Erichsen and Flemming Møhlenberg from DHI for their extremely valuable
experiences, support, and insights.
I am indebted to my many colleagues from the Department of Ecology,
Environment and Plant Sciences who supported me, especially Josefin
Segerman, Hanna Oskarsson, Ben Jaeschke, Göran Samuelsson, Nadja
Stadlinger, Charlotte Berkström and Nils Hedberg. Another special thanks
goes to Prof. Nisse Kautsky and Olle Hjerne for useful comments on the
manuscripts.
I would like to extend my sincerest thanks and appreciation to my parents
and sister for their emotional support no matter what path I choose. My sister
Galyna has been my best friend all my life and I love her dearly and thank her
for all her advice and support.
I wish to give my heartfelt thanks to my beloved Andrej, whose
unconditional love, patience, and continual support of my academic
endeavours especially over the last year of my study enabled me to complete
this thesis. Finally, there are my children, who have given me much happiness
and funny moments in my life.
25
References
Andersson E., (2005). Benthic-pelagic microbial interactions and carbon
cycling in clear water Lakes. Ph.D. thesis. Uppsala University, Sweden.
Aquilonius, K., (Ed), (2010). The marine ecosystems at Forsmark and
Laxemar-Simpevarp. SR-Site Biosphere. SKB Report, TR-10-03.
Swedish Nuclear Waste Management Co., Stockholm, Sweden.
Avila, R., Ekström, P. A., Åstrand, P.G., (2010). Landscape dose conversion
factors used in the safety assessment SR-Site. SKB TR-10-06, Swedish
Nuclear Waste Management Co., Stockholm, Sweden.
Avila, R., Kautsky, U., Ekström, P.-A., Åstrand, P.-G., Saetre, P., (2013).
Model of the long-term transport and accumulation of radionuclides in
future landscapes. AMBIO, 42(4): 497-505.
Baines, S.B., Fisher, N.S., Stewart, R., (2002). Assimilation and retention of
selenium and other trace elements from crustacean food by juvenile
striped bass (Morone saxatilis). Limonology and Oceanography,
47: 646–655.
Beresford, N.A., Balonov, M., Beaugelin-Seiller, K., Brown, J., Copplestone,
D., Hingston, J.L., Horyna, J., Hosseini, A., Howard, B.J., Kamboj, S.,
Nedveckaite, T., Olyslaegers, G., Sazykina, T., Vives i Batlle, J.,
Yankovich, T.L., Yu, C., 2008. An international comparison of models
and approaches for the estimation of the radiological exposure of nonhuman biota. Applied Radiation and Isotopes, 66: 1745-1749.
Berner, B., Drottz-Sjöberg, B.-M., Holm, E. (2009). Inledning. I
Samhällsforskning 2009. Betydelsen för människorna, hembygden och
regionen av ett slutförvar för använt kärnbränsle. Swedish Nuclear
Waste Management Co., Stockholm, Sweden. pp. 4-17.
26
BIOMOVS II, 1996a. Validation test for carbon-14 migration and
accumulation in a Canadian Shield Lake. Technical Report no. 14.
Swedish Radiation Protection Institute, Stockholm, Sweden, p. 40.
BIOMOVS II, 1996b. Assessment of the consequences of the radioactive
contamination of aquatic media and biota. Technical Report no. 10.
Swedish Radiation Protection Institute, Stockholm, Sweden, p. 70.
Bird, G.A., Stephenson, M., Cornett, R.J., (1993). The surface water model
for assessing Canada's nuclear fuel waste disposal concept. Waste Mgmt,
13: 153-170.
Buesseler, K., Jayne, S., Fisher, N., (2012). Fukushima-derived radionuclides
in the ocean and biota off Japan. Proceedings of the National Academy
of Sciences 109(16), 5984-5988
Chapman, P.C., Adams, W.J., (Eds.) (2007). Assessing the Hazard of Metals
and Inorganic Metal Substances in Aquatic and Terrestrial Systems.
CRC Press. 146 pp.
Copplestone, D., Beresford, N.A., Brown, J.E., Yankovich, T., (2013). An
international database of radionuclide concentration ratios for wildlife:
development and uses, Journal of Environmental Radioactivity, 126:
288-298.
Erichsen, A.C., Møhlenberg, F., Closter, R.M., Sandberg, J., (2010). Models
for transport and fate of carbon, nutrients and radionuclides in the
aquatic ecosystem at Öregrundsgrepen. DHI, SKB R-10-10. Swedish
Nuclear Waste Management Co., Stockholm, Sweden.
Fowler, S.W., Fisher, N.S., (2005). Chapter 6 Radionuclides in the biosphere,
in: Hugh, D.L. (Ed.), Radioactivity in the Environment. Elsevier, pp.
167-203.
Harms, H. I., Karcher, M.J., Burchard, H., (2003). Modelling radioactivity in
the marine environment: The application of hydrodynamic circulation
models for simulating oceanic dispersion of radioactivity. Chapter 3,
pp.55-85. Modelling radioactivity in the environment, E. Marian Scott
(Editor), © 2003 Elsevier Science Ltd.
HELCOM 2009. Radioactivity in the Baltic Sea 1999-2006, Baltic Sea
environment proceedings, No 117: 47-49.
27
Heling, R., Bezhenar, R., (2009). Modification of the dynamic radionuclide
uptake model BURN by salinity driven transfer parameters for the
marine foodweband its integration in POSEIDON-R. Radioprotection
44(5): 741–746.
Hofman, D., Monte, L., Boyer, P., Brittain, J., Donchyts, G., Gallego, E.,
Gheorghiu, D., Håkanson, L., Heling, R., Kerekes, A., Kocsy, G.,
Lepicard, S., Slavik, O., Slavnicu, D., Smith, J., Zheleznyak, M., (2011).
Computerised Decision Support Systems for the management of
freshwater radioecological emergencies: assessment of the state-of-theart with respect to the experiences and needs of end-users. Journal of
environmental radioactivity, 102: 119–27.
Howard, B. J., Beresford, N. a, Copplestone, D., Telleria, D., Proehl, G.,
Fesenko, S., Jeffree, R. A., Yankovich, T. L., Brown, J. E., Higley,
K.,Johansen, M P, Mulye, H., Vandenhove, H., Gashchak, S., Wood,
M. D., Takata, H., Andersson, P., Dale, P., Ryan, J., Bollhöfer, A.,
Doering, C., Wells, C. (2013). The IAEA handbook on radionuclide
transfer to wildlife. Journal of Environmental Radioactivity, 121: 55–74.
Håkanson, L., Monte, L. (2003) Radioactivity in lakes and rivers. In Scott,
E.M. (ed.), Radioactivity in the Environment. Elsevier, pp.147-200.
Håkanson, L., Andersson, T., Nilsson, Å., (1992). Radioactive Caesium in
Fish in Swedish Lakes 1986-1988. General Pattern Related to Fallout
and Lake Characteristics Tord Andersson & Ake Nilsson, Journal of
environmental radioactivity, 15: 207–229.
IAEA 1985a. Sediment Kds and concentration factors for radionuclides in the
marine environment. Technical Report Series No. 247., p.76.
International Atomic Energy Agency, Vienna, Austria.
IAEA 1985b. Hydrological Dispersion of Radioactive Material in Relation to
Nuclear Power Plant Siting. A Safety Guide. Safety Series, 50-SG-S6.
International Atomic Energy Agency, Vienna, Austria.
IAEA 1994. Handbook of Parameters Values for the Prediction of
Radionuclide transfer in temperate Environments. Technical Reports
series, 364. International Atomic Energy Agency, Vienna.
IAEA 2000. Modelling of the transfer of radiocaesium from deposition to lake
ecosystems. Report of the VAMP Aquatic Working Group. IAEATECDOC-1143. International Atomic Energy Agency, Vienna, Austria.
28
IAEA 2004. Sediment distribution coefficients and concentration factors for
biota in the marine environment. Technical reports series no. 422.
International Atomic Energy Agency, Vienna, Austria.
IAEA 2009. Calmon, P., Fesenko, S., Voigt, G., & Linsley, G. (2009).
Quantification of radionuclide transfer in terrestrial and freshwater
environments for radiological assessments. Report IAEA-TECDOC1616. International Atomic Energy Agency, Vienna.
IAEA 2010a. Handbook of parameter values for the prediction of radionuclide
transfer in terrestrial and freshwater environments. Technical reports
series no 472. International Atomic Energy Agency, Vienna, Austria.
IAEA 2012b. Environmental Modelling For Radiation Safety (EMRAS).
Summary Report of the Results of the EMRAS Programme (2003–
2007). IAEA-TECDOC-1678. © International Atomic Energy Agency,
Vienna.
IAEA 2012c.Testing of Models for Predicting the Behaviour of Radionuclides
in Freshwater Systems and Coastal Areas. Report of the Aquatic
Working Group of EMRAS Theme 1. IAEA-TECDOC-1678.
International Atomic Energy Agency, Vienna, Austria. http://wwwns.iaea.org/downloads/rw/projects/emras/final-reports/aquatic-tecdocfinal.pdf
IAEA 2012b. Modelling radiation exposure and radionuclide transfer for nonhuman species: report of the Biota Working Group of EMRAS Theme
3. Vienna, International Atomic Energy Agency, 244pp. http://wwwns.iaea.org/downloads/rw/projects/emras/final-reports/biota-final.pdf
ICRP 2007. Recommendations of the international commission on
radiological protection. Ann. ICRP 37, 2e3. Publication 103.
Iosjpe, M. (2006). Environmental modelling: Modified approach for
compartmental models. in: P.P. Povinec, J.A. Sanchez-Cabeza (Eds.),
Radionuclides in the Environment. Radioactivity in the Environment,
Series Ed, 8, M.S. Baxter, pp. 463–476
Kautsky, U., Lindborg, T., Valentin, J. (2013). Humans and ecosystems over
the coming millennia: overview of a biosphere assessment of radioactive
waste disposal in Sweden. AMBIO, 42(4): 383-392.
Kryshev, A. I. (2006). 90Sr in fish: a review of data and possible model
approach. The Science of the total environment, 370, 182–9.
29
Kryshev, A. I., & Ryabov, I. N. (2000). A dynamic model of Cs-137
accumulation by fish of different age classes. Journal of Environmental
Radioactivity, 50, 221–233.
Kryshev, I.I., Sazykina, T.G., Hoffman, F.O., Thiessen, K.M., Blaylock, B.G.,
Feng, Y., Galeriu, D., Heling, R., Kryshev, A.I., Kononovich, A.L.,
Watkins, B., (1999). Assessment of the consequences of the radioactive
contamination of aquatic media and biota for the Chernobyl NPP cooling
pond: model testing using Chernobyl. Journal of Environmental
Radioactivity, 42: 143–156.
Kumblad L., Kautsky U., (2004a). Effects of land‐rise on the development of
a coastal ecosystem of the Baltic Sea and its implications on the long‐
term fate of C‐14 discharges. Hydrobiologia, 514: 185‐196.
Kumblad, L., Kautsky, U., (2004b). Models for transport and fate of carbon,
nutrients and point source released radionuclides to an aquatic
ecosystem. SKB TR-04-13, Swedish Nuclear Waste Management Co.,
Stockholm, Sweden.
Kumblad, L., (2004). Radionuclides in the Baltic Sea. Ecosystem models and
experiments on transport and fate. Doctoral Thesis, Department of
System Ecology, Stockholm University.
Kumblad, L., Bradshaw, C., (2008). Element composition of biota, water and
sediment in the Forsmark area, Baltic Sea. Concentrations,
bioconcentration factors and partitioning coefficients (Kd) of 48
elements. SKB TR-08-09, Swedish Nuclear Waste Management Co.,
Stockholm, Sweden.
Kumblad, L., Gilek, M., Næslund, B., Kautsky, U., (2003). An ecosystem
model of the environmental transport and fate of C-14 in a bay of the
Baltic Sea, Sweden. Ecological Modelling, 166: 193-210.
Kumblad, L., Kautsky, U., Næslund B., (2006). Transport and fate of
radionuclides in aquatic environments: the use of ecosystem modelling
for exposure assessments of nuclear facilities. Journal of Environmental
Radioactivity, 87: 107-129.
Lepicard, S., Heling, R., Maderich, V., (2004). POSEIDON/RODOSmodels
for radiological assessment of marine environment after accidental
30
releases: application to coastal areas of the Baltic, Black and North Seas.
Journal of Environmental Radioactivity, 72(1-2):153-161.
Lindborg, T., (ed.), (2010). Landscape Forsmark - data. methodology and
results for SR-Site. SKB Report, TR-10-05. Swedish Nuclear Waste
Management Co., Stockholm, Sweden.
Lindborg, T., (ed.) (2008). Surface system Forsmark Site descriptive
modeling SDM-Site Forsmark. SKB Report, TR-08-11. Swedish
Nuclear Waste Management Co., Stockholm, Sweden.
Margvelashvili, N., Maderich, V., Yuschenko, S., Zheleznyak, M., (2002). 3D numerical modelling of mud and radionuclide transport in the
Chernobyl Cooling Pond and Dnieper-Boog Estuary. Proceedings in
Marine Science. Fine Sediment Dynamics in the Marine Environment,
5: 595–609.
Maderich, V., Bezhenar, R., Heling, R., Jung, K.T., Myoung, J.G., Cho, Y.K., Qiao, F., Robertson, L., (2014). Regional long-term model of
radioactivity dispersion and fate in the Northwestern Pacific and
adjacent seas: application to the Fukushima Dai-ichi accident. Journal
of Environmental Radioactivity, 131: 4–18
Meyer J.S. Ed., (2005).Toxicity of Dietborne Metals to Aquatic Organisms.
Publisher: Pensacola, FL: Society of Environmental Toxicology and
Chemistry.
Monte, L., Brittain, J.E., Gallego, E., Håkanson, L., Hofman, D., Jiménez, A.,
(2009a). MOIRA-PLUS: a decision support system for the management
of complex fresh water ecosystems contaminated by radionuclides and
heavy metals. Computers & Geosciences, 35: 880-896.
Monte, L., Periañez, R., Boyer, P., Smith, J.T., Brittain, J.E., (2009b). The role
of physical processes controlling the behaviour of radionuclide
contaminants in the aquatic environment: a review of state-of-the-art
modelling approaches. Journal of Environmental Radioactivity, 100:
779–784.
Nordén, S., Avila, R., de la Cruz, I., Stenberg, K., Grolander, S., (2010).
Element-specific and constant parameters used for dose calculations in
SR-Site. SKB Report, TR-10-07. Swedish Nuclear Waste Management
Co., Stockholm, Sweden.
31
Outola, I., Saxén, R.L., Heinävaara, S., (2009). Transfer of 90Sr into fish in
Finnish lakes. Journal of Environmental Radioactivity, 100: 657–64.
Periáñez, R., Suh, K.-S., & Min, B.-I. (2012). Local scale marine modelling
of Fukushima releases. Assessment of water and sediment contamination
and sensitivity to water circulation description. Marine Pollution
Bulletin, 64(11), 2333–9.
Periáñez, R., Bezhenar, R., Iosjpe, M., Maderich, V., Nies, H., Osvath, I.,
Outola I., de With, G. (2015). A comparison of marine radionuclide
dispersion models for the Baltic Sea in the frame of IAEA MODARIA
program. Journal of Environmental Radioactivity, 139: 66–77.
Periáñez, R., Suh, K.-S., & Min, B.-I. (2012). Local scale marine modelling
of Fukushima releases. Assessment of water and sediment contamination
and sensitivity to water circulation description. Marine Pollution
Bulletin, 64(11), 2333–9.
Santschi, P.H., Honeyman, B.D., (1989). Radionuclides in aquatic
environments. Radiation Physics and Chemistry, 34: 213-240.
Sazykina, T., (2003). Radioactivity in aquatic biota. Modelling radioactivity
in the environment. pp. 201-222, E. Marian Scott (Ed.). © 2003 Elsevier
Science Ltd.
Sazykina, T.G., (2000). ECOMOD: an ecological approach to radioecological
modelling. Journal of Environmental Radioactivity, 50: 207-220.
Simkiss, K., Taylor, M.G., (1995). Transport of metals across membrenes. In:
Tessier, A., Turner D.R. (Eds.), Metal Speciation and Bioavailability in
Aquatic Systems, UK: John Wiley & Sons, Wallingford, Chichester. 44
pp.
SKB 2011. Long-term safety for the final repository for spent nuclear fuel at
Forsmark. Main report of the SR-Site projectSKB Report, TR-11-01.
Swedish Nuclear Waste Management Co., Stockholm, Sweden.
Steinhauser, G., Brandl, A., & Johnson, T. E. (2013). Comparison of the
Chernobyl and Fukushima nuclear accidents: A review of the
environmental impacts. The Science of the Total Environment, 470471C, 800–817.
32
Smith, C.N., Clarke, S., McDonald, P., Goshawk, J.A., Jones, S.R., (2000).
Reconstructing historical radionuclide concentrations along the east
coast of Ireland using a compartmental model. Science of the Total
Environment, 254: 17-30.
Smith, J.T., Kudelsky, A.V., Ryabov, I.N., Hadderingh, R.H., & Bulgakov,
A.A. (2003). Application of potassium chloride to a chernobylcontaminated lake: Modelling the dynamics of radiocaesium in an
aquatic ecosystem and decontamination of fish. The Science of the
Total Environment, 305, 217–227.
Smith, J.T., Sasina, N.V., Kryshev, A.I., Belova, N.V., Kudelsky, A.V.,
(2009). A review and test of predictive models for the bioaccumulation
of radiostrontium in fish. Journal of Environmental Radioactivity, 100:
950–954.
Tagami, K. & Uchida, S. (2012) Marine and freshwater concentration ratios
(CRwo-water): review of Japanese data. Journal of Environmental
Radioactivity 126, 420–6.
Takahashi, S., (Ed.), (2014). Radiation Monitoring and Dose Estimation of
the Fukushima Nuclear Accident. (S. Takahashi, Ed.). Tokyo: Springer
Japan.
Tateda, Y., Tsumune, D., & Tsubono, T. (2013). Simulation of radioactive
cesium transfer in the southern Fukushima coastal biota using a
dynamic food chain transfer model. Journal of Environmental
Radioactivity, 124, 1–12.
Tröjbom, M., Nordén, S., (2010). Chemistry data from surface ecosystems in
Forsmark and Laxemar-Simpevarp. Site specific data used for
estimation of CR and Kd values in SR-Site. SKB R-10-28, Swedish
Nuclear Waste Management Co., Stockholm, Sweden. Svensk
Kärnbränslehantering AB.
Tröjbom M., Grolander S., Rensfeldt V., Nordén S., (2013). Kd and CR used
for transport calculations in the biosphere in SR-PSU. SKB Report, R13-01, Swedish Nuclear Waste Management Co., Stockholm, Sweden.
Svensk Kärnbränslehantering AB, pp.363.
Tsumune, D., Tsubono, T., Aoyama, M., & Hirose, K. (2011). Distribution
of oceanic 137 Cs from the Fukushima Dai-ichi Nuclear Power Plant
simulated numerically by a regional ocean model. Journal of
Environmental Radioactivity, 3, 1–9.
33
Wang, W.-X., Rainbow, P.S. (2008). Comparative approaches to understand
metal bioaccumulation in aquatic animals. Comparative biochemistry
and physiology. Toxicology & pharmacology: CBP, 148: 315-23.
Vives i Batlle, J., Wilson, R.C., Watts, S.J., Jones, S.R., McDonald, P.,
Vives-Lynch, S. (2008). Dynamic model for the assessment of
radiological exposure to marine biota. Journal of environmental
radioactivity, 99: 1711-30.
Vives I Batlle, J., Aono, T., Brown, J. E., Hosseini, A., Garnier-Laplace, J.,
Sazykina, T., Steenhuisen, F., Strand, P. (2014). The impact of the
Fukushima nuclear accident on marine biota: retrospective assessment
of the first year and perspectives. The Science of the Total
Environment, 487, 143–53
Vanderploeg, H.A., Parzyck, D.C., Wilcox, W.H., Kerchner, J.R., Kaye,
S.V., 1975. Bioaccumulation Factors for Radionuclides in Freshwater
Biota. ORNL-5002. Oak Ridge National Laboratory, Oak Ridge,
Tennessee.
Yankovich, T.L., (2005). EMRAS Biota Working Group (BWG): The Perch
Lake Freshwater Scenario Description (Revision 2). ETB-05–86 (Rev.
2), Atomic Energy Canada Limited, Chalk River, Canada. Available
from: /http:// www-ns.iaea.org/projects/emras/emras-biota-wg.htm
34