Introduction
A catastrophic earthquake and tsunami, that occurred on 11 March 2011,
severely damaged the Fukushima Dai-ichi Nuclear Power Plant (FDNPP). The loss
of power and the subsequent overheating, meltdowns, and hydrogen explosions
at the FDNPP site resulted in the uncontrolled release of radioactivity into
the air and ocean (Povinec et al., 2013). The atmospheric fallout over the
land and the ocean peaked in mid-March whereas the direct release to the
ocean from FDNPP peaked in the beginning of April. Approximately 80 % of the
radioactivity released due to the accident in March–April 2011 was either
directly discharged into the ocean or deposited onto the ocean surface from
the atmosphere. The concentration of 137Cs in the ocean reached a
maximum in mid-April of 2011 and has thereafter declined (by a factor of
105), except for the area around the FDNPP, where continuous leaks of
contaminated water have been reported (Kanda, 2013). However, the
concentration of 137Cs in the bottom sediment that was contaminated by
water with high concentrations in April–May 2011 remains quite high and is
showing signs of very slow decrease with time (Otosaka and Kobayashi, 2013;
Kusakabe et al., 2013; Ambe et al., 2014; Black and Buesseler, 2014). The
concentration of organically bound 137Cs in coastal areas is several
times higher than that of the bulk sediment (Otosaka and Kobayashi, 2013; Ono
et al., 2015) due to 137Cs adsorption onto organic matter. It is worth
noting that organic matter content in the shelf of Fukushima and Ibaraki
prefectures varies in the range of 0.1–25 % (Otosaka and Kobayashi, 2013;
Ambe et al., 2014; Ono et al., 2015). The preferential adsorption of
137Cs onto organic matter can be explained by the partial coverage of
fine mineral sediment by organic substances and subsequent blocking of
sorption (Kim et al., 2006; Ono et al., 2015). Comparison of the
concentration of 137Cs in the sediment and benthic invertebrates
(Sohtome et al., 2014) and in the demersal fishes (Buesseler et al., 2012;
Wada et al., 2013; Tateda et al., 2013) suggests that the continual ingestion
of organic matter from sediments can be an important contamination pathway
for all components of the benthic food web. However, in most of the benthic
food web models applied to the FDNPP accident, the deposit feeding is not
included as a transfer mechanism in the food chain (Tateda et al., 2013, 2015, 2016; Keum
et al., 2015; Vives i Batlle, 2016; Vives i
Batlle
et al., 2016).
Several models were used to perform long-term assessments of the radiological
impact in the marine environment due to the FDNPP accident (Nakano and
Povinec, 2012; Maderich et al., 2014a, b). In particular, the compartment
model POSEIDON-R (Maderich et al., 2014a, b) correctly predicted the
concentration of 137Cs and 90Sr in water and sediments in the
coastal box (30×15 km) around the FDNPP for 2011–2013. In these studies, the
flux of radionuclides due to the groundwater leakage of contaminated waters
from FDNPP (Kanda, 2013) was taken into account. However, the version of the
dynamic food chain biological uptake model of radionuclides (BURN) coupled to the POSEIDON-R model (Heling et al., 2002; Lepicard et al.,
2004; Maderich et al., 2014a, b) did not take into account the benthic food web
processes. Notwithstanding, the results of simulations still agreed well with
observations for the first months and years when transfer from water was
dominant (Maderich et al., 2014a, b). Measurements following the Fukushima
Dai-ichi accident suggest that transfer of radioactivity from bottom deposits
through the benthic food web over longer timescales can be an increasingly
important factor in the radiological assessment of released radioactivity.
Another relevant example is the significant contamination of the Baltic Sea
in 1986 by the deposition of activity originating from the Chernobyl
accident. Unlike the coastal sea region near FDNPP, the Baltic Sea is a
semi-enclosed relatively shallow sea filled by brackish waters and connected
with the ocean by the narrow and shallow Danish Straits (Leppäranta and
Myrberg, 2009). Within HELCOM (Helsinki Convention on the Protection of the
Marine Environment of the Baltic Sea Area, http://www.helcom.fi) the
group MORS (Monitoring of Radioactive Substances) established an
internationally agreed monitoring network in 1986 and deposited all the data
in a common database (MORS, 2015). Therefore, this event also represents a
good test case to validate models and study the benthopelagic coupling
effects on radionuclide dynamics (Periañez et al., 2015).
In this study, an extended food web model is presented that considers both
pelagic and benthic food chains. This dynamic model was implemented into the
compartment model POSEIDON-R and applied to the north-western Pacific for the
period of 1945–2020 to assess the radiological consequences from the
137Cs released as a result of global fallout and the Fukushima Dai-ichi
accident. The model was also applied to the Baltic Sea for the period
1945–2020 to show the applicability of this model to other systems. The paper
is organized as follows. Descriptions of the compartment model and the
extended dynamic food web model are given in Sect. 2. Section 3 presents
the model application and results for the Fukushima Dai-ichi accident. The
results of the model application to the Baltic Sea are given in Sect. 4.
Section 5 summarizes our findings.
Model description
In this study, the dynamic model BURN was extended to describe transfer
pathways of 137Cs from bottom sediments to marine organisms. The model
was developed to assess doses from marine products in the decision-support
system RODOS for off-site nuclear emergencies (Lepicard et al., 2004). For
such aim it was necessary to use a robust and generic model requiring a
minimal number of parameters. Therefore, in the model, marine organisms are
grouped into a few classes based on trophic levels and types of species. The
radionuclides are also grouped in several classes depending on the type of
tissues in which a specific radionuclide accumulates preferentially. These
simplifications allow for a limited number of standard input parameters. The
transfer scheme of radionuclides through the marine food web is shown in
Fig. 1 where transfer of radionuclides through the food web is shown by arrows
whereas the direct transfer from water is depicted by the shadowed rectangle
surrounding 11 biotic compartments (i=1, ..., 11). Pelagic organisms are
divided into primary producer, phytoplankton (i=1), and consumers which
consist of zooplankton (i=2), foraging (non-piscivorous) fish (i=3), and
piscivorous fish (i=4). The benthic food web includes three primary
pathways for radionuclides: (I) transfer from water to macroalgae (i=5),
then to grazing invertebrates (i=6, 7, 8); (II) transfer through the vertical
flux of detritus and zooplankton faeces (Fowler et al., 1987) to
detritus-feeding invertebrates (i=8); and (III) transfer through
contaminated bottom sediments to deposit-feeding invertebrates (i=6).
External boxes in Fig. 1 show the concentrations of radionuclides in water
and in the upper layer of bottom sediment calculated using the box model
POSEIDON-R described further down. The radionuclides adsorbed on the organic
matter in the sediments are bioavailable for benthic organisms but the
mineral component of sediments is not (Ueda et al., 1977, 1978).
However, Koyanagi et al. (1978) found relatively rapid and more intensive
transfer of several sediment-adsorbed radionuclides (54Mn, 60Co,
65Zn) to particular organs of the demersal fishes in contrast to flesh.
We assume that (i) radioactivity concentrations in organic and mineral
fractions of bottom deposit are in mutual equilibrium, (ii) radioactivity
concentrations in microbial biota and non-living organic matter also are in
equilibrium, and (iii) only organic matter in the bottom deposit is
bioavailable. The benthic invertebrate group includes mollusks (e.g.
filter feeders) (i=7), crustaceans (e.g. detritus feeders) (i=8), and
subsurface and surface deposit feeders (e.g. annelid)(i=6). In the model,
radioactivity is transferred from benthic invertebrates to demersal fishes
(i=9) that feed on them, and on to omnivorous bottom predators (i=10)
(Fig. 1). The marine food web also includes “coastal predators” (i=11)
feeding in the whole water column in shallow waters.
Biological compartments with corresponding numbers (reported in the
text and tables) and radionuclide transfer (arrows) for extended dynamic food
chain BURN model. Compartments within the shadowed rectangle also exchange
radionuclides directly with the surrounding water. The output from the
compartment POSEIDON-R model is shown by the external boxes, namely water and
bottom deposit.
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In the extended model utilized in this study, the concentration of
radioactivity in phytoplankton C1 is calculated using the biological
concentration factor (BCF) approach due to
the rapid uptake from water and the short retention time of radioactivity:
C1=CFphCw,
where Cw is concentration of radioactivity in water and CFph the BCF for phytoplankton.
For the macroalgae, a dynamic model is used to describe radionuclide concentrations due to the longer retention times
dC5dt=(CFmaCw-C5)ln2T0.5,5-1,
where C5 is the concentration of radioactivity in the macroalgae and
CFma the corresponding BCF, T0.5,5 is the biological half-life of
the radionuclide in the macroalgae, and t is the time. The concentration of
a given radionuclide in the zooplankton (i=2), invertebrates (i=6, 7, 8),
and fish (i=3, 4, 9, 10, 11; see Table 1 for a description of the different
fish groups in the model) is described by the following differential
equation:
dCidt=aiKf,iCf,i+biKw,iCw-ln2T0.5,i-1Ci,
where Ci and Cf,i are the concentrations of radioactivity in the
marine organisms and their food, respectively,
ai is the assimilation efficiency, bi is the water extraction coefficient,
Kf,i is the food uptake rate, Kw,i is the water uptake rate, and T0.5,i is the biological half-life of the radionuclide in the organism.
Parameters of dynamic food chain model BURN.
i
Organism
drw
Kf,i
ai
Kw,i
bi
T0.5,i
d-1
m3 kg-1 d-1
d
1
Phytoplankton
0.1
2
Zooplankton
0.1
1.0
0.2
1.5
0.001
5
3
Non-piscivorous fish
0.25
0.03
0.5
0.1
0.001
Table 3
4
Piscivorous fish
0.3
0.007
0.7
0.075
0.001
Table 3
5
Macroalgae
0.1
0.6
0.001
60
6
Deposit-feeding
0.1
0.02
0.3
0.1
0.001
15
invertebrate
7
Mollusk
0.1
0.06
0.5
0.15
0.001
50
8
Crustacean
0.1
0.015
0.5
0.1
0.001
100
9
Demersal fish
0.25
0.007
0.5
0.05
0.001
Table 3
10
Bottom predator
0.3
0.007
0.7
0.05
0.001
Table 3
11
Coastal predator
0.3
0.007
0.7
0.075
0.001
Table 3
The activity concentration in the food of a predator Cf,i is expressed
by the following equation, summing up for a total of n prey types
Cf,i=∑j=0nCprey,jPi,jdrwpred,idrwprey,j,
where Cprey,j is the activity concentration in prey of type j,
Pi,j is preference factor for prey of type j, drwpred,i is the
dry weight fraction of predator of type of i, and drwprey,j is the dry
weight fraction of prey of type j. The index “0” corresponds to the bottom
deposit in sediment (Fig. 1). The concentration of assimilated radioactivity
from the organic fraction of sediment is related with the radioactivity
concentration of the upper layer of bulk sediment as
Cprey,0=ϕorg⋅Cs. Here ϕorg is an empirical
parameter ϕorg=(1-p)forgCorgCs-1, where p is porosity,
forg is the organic matter
fraction, CorgCs-1 is the ratio of
concentration Corg (Bq kg-1-dry) in the organic matter to the
bulk sediment concentration Cs (Bq kg-1-dry). The value of
ϕorg is in the range of 0.1–0.01 (Ono et al., 2015).
Values of the model parameters are given in Table 1. The parameters for
pelagic and benthic food webs were compiled from published data (Baptist and
Price, 1962; Cammen, 1980; Coughtrey and Thorne,
1983; Tateda, 1994, 1997; Vives i Batlle et al., 2007; Tateda et al., 2013;
Iwata et al., 2013; Sohtome et al., 2014). The biological half-life data for
fish flesh (Baptist and Price, 1962; Coughtrey and Thorne, 1983; Tateda,
1994, 1997; Zhao et al., 2001) show variability in a large range (35–180
days) due to the differences between species and due to the differences in
the experiment methodology. In this generic model, values of T0.5,i were
divided into two groups: T0.5,i=75 d for non-piscivorous fishes and
demersal fishes feeding on invertebrates (i=3, 9), and T0.5=150 d for
predatory fishes (i=4, 10, 11). This is based on the assumptions that (a)
larger fishes have longer T0.5,i due to the slower metabolic rates, and
(b) predatory fishes are generally larger than prey fishes. The results of a
sensitivity study to assess the robustness of these assumptions for
T0.5,i are given in next section. An additional constraint on the values
of the model parameters is the condition that, at equilibrium state, the BCF of
the components of the food chain should be relevant to the values from
IAEA (2004). The biological half-life for the bone was calculated for
non-piscivorous and piscivorous fish using Eq. (3) and data for
90Sr (known to accumulate mainly in bone tissue) using an equilibrium
approximation to satisfy BCF values from IAEA (2004). The values of prey
preference are given in Table 2. They are compiled from data on feeding
habits of organisms (Fujita et al., 1995; Kasamatsu and Ishikawa, 1997; Iwata
et al., 2013; Sohtome et al., 2014).
It is well established that the uptake of caesium decreases with increasing
salinity due to the increase in concentration of competing potassium ions.
This was taken into account when introducing the salinity-dependent
correction factor FK for phytoplankton and macroalgae as caesium enters
the food web primarily through the lowest trophic level whereas the
contribution of direct uptake from water is minor (Heling and Bezhenar,
2009). The correction factor for Cs, based on laboratory experiments with
marine plants, was verified against field measurements in the Dnieper–Boog
estuary (Heling and Bezhenar, 2011). It is expressed as
FK=0.05exp(0.73ln(K+/39.1)-1.22×103Θ-1),
where K+ is the potassium concentration (mg L-1) and Θ is temperature (K).
For water with a K+ concentration above 1.5 mg L-1,
the potassium concentration could be linked to the salinity using the following relationship (Heling and Bezhenar, 2009):
K+=11.6S-4.28,
where S is the salinity in g L-1.
The BCF for phytoplankton and macroalgae can be expressed by
CFph=FKCFph*,CFma=FKCFma*,
where CFph*=20 L kg-1 and CFma*=50 L kg-1 are standard BCFs for marine environments (IAEA, 2004).
According to a review of radiological data (Coughtrey and Thorne, 1983;
Yankovich et al., 2010), every radionuclide in fish accumulates mostly in a
specific (target) tissue. According to data from Yankovich et al. (2010),
amounts of radiocaesium in flesh, bone, and organs are 90, 9, and 1 %,
respectively. Hence, Cs turnover in bones and organs is negligible. The
target tissue (bone, flesh, organs, and stomach) is assumed to control the
overall elimination rate of the nuclide (T0.5,i) in the organisms. The
radioactivity in the food of a predator is therefore the activity
concentration in the target tissue diluted by the remaining body mass of the
prey, calculated by multiplying the predicted level in the target tissue by
its weight fraction. For radiocaesium, the target tissue is flesh. To
calculate the concentration in the edible part of fish from the calculated
levels in the target tissues, a target tissue modifier (TTM) is introduced.
This is based on tissue distribution information (Coughtrey and Thorne, 1983;
Yankovich et al., 2010). Values of the described parameters for fish in a
dynamic food chain model are given in Table 3.
Preference factor of predator of type i for prey of type j.
Predator
2
3
4
6
7
8
9
10
11
Prey
0
0.5
0.1
1
1.0
0.6
0.1
2
1.0
0.2
0.8
3
1.0
0.2
5
0.5
0.2
0.1
6
0.7
0.3
0.25
7
0.1
0.2
0.1
8
0.1
0.2
0.2
9
0.3
0.25
The dynamic food chain model is part of the POSEIDON-R (Lepicard et al.,
2004; Maderich et al., 2014a, b) model where the marine environment is
modelled as a system of compartments representing the water column, bottom
sediment, and biota. The compartments describing the water column are
subdivided into a number of vertical layers as shown in Fig. S1 in the Supplement. The model
assumes partition of the radionuclides between the dissolved and particulate
fractions in the water column, described by a distribution coefficient. The
radionuclide concentration for each compartment is governed by a set of
differential equations including the temporal variations of concentration,
the exchange with adjacent compartments and with the suspended and bottom
sediments, radioactive sources, and decay. The exchange between the water
column boxes is described by fluxes of radionuclides due to advection,
sediment settling, and turbulent diffusion processes. The activity loss in
suspended sediments occurs through settling in underlying compartments and,
finally, to the bottom. A three-layer model describes the transfer of
radionuclides in the bottom sediments. The transfer of radioactivity from the
upper sediment layer to the water column is described by diffusion in the
interstitial water and by bioturbation. Radioactivity in the upper sediment
layer migrates downwards by diffusion and by burial at a rate assumed to be
the same at which particles settle from the overlying water. The upwards
transfer of radioactivity from the mid-sediment layer to the top sediment
layer occurs only by diffusion. Burial causes an effective loss of
radioactivity from the middle to the deep sediment layer, from which no
upward transfer occurs. The model equations are given in the Supplement. The model for the pelagic food web component was implemented for
the whole area of study, whereas the benthic component was included in the
shallow, single-water-column layer compartments adjacent to the shore.
Parameters for fish in a dynamic food chain model.
Target tissue
Bone
Flesh
Organs
Stomach
Weight fraction
0.12
0.80
0.05
0.03
Target tissue modifier
0.5
1.0
0.5
0.5
Biological half-life of
500
75
20
3
non-piscivorous fish (d)
Biological half-life of
1000
150
40
5
piscivorous fish (d)
Biological half-life of
500
75
20
3
demersal fish (d)
Biological half-life of
1000
150
40
5
bottom predator fish (d)
Biological half-life of
1000
150
40
5
coastal predator fish (d)
The POSEIDON-R model can handle different types of radioactive releases:
atmospheric fallout, runoff from land deposited radionuclide by river
systems, point sources associated with routine releases from nuclear
facilities located either directly on the coast or inland at river systems,
and point sources associated with accidental releases (Lepicard et al.,
2004). For coastal discharges occurring in the large (“regional”) boxes,
“coastal” release boxes are nested into the regional box system.
Advection and diffusion of zooplankton are not taken into account due to the short biological half-life (5 days) of Cs in these organisms,
except in the coastal box, where diffusion exchange between coastal and regional compartments was considered.
It was assumed that crustaceans, mollusks, and fish are not transported by ocean currents.
When calculating the radionuclide concentration in fish in small coastal boxes,
random fish migration is taken into account as in Maderich et al. (2014a, b).
For this purpose, the right hand side of Eq. (3) for radionuclide concentration in fish,
both in the inner (Cin,i) and outer (Cout,i) compartments,
is extended by the term -(Cin,i-Cout,i)/Tmigr,i for the coastal compartment
and by the term (Cin,i-Cout,i)/(δTmigr,i) for the outer compartment.
Here Tmigr,i is the characteristic time of fish migration from a coastal compartment,
depending on compartment scale and fish species,
and δ is the ratio between the volumes of the outer and the coastal compartments.
Application to the Fukushima Dai-ichi accident
Model setup
The model was customized for the north-western Pacific Ocean, the East China
and Yellow seas, and the Sea of Japan (East Sea). A total of 176 boxes cover
this entire region (Fig. S2). In the deep-sea regions a three-layer box
system was built to describe the vertical structure of the radioactivity
transport in the upper layer (0–200 m), intermediate layer (200–1000 m),
and deeper layer (> 1000 m). The compartments around the FDNPP
are shown in Fig. 2. The “coastal” box (placed at “F” in Fig. 2) covers
15×30 km and is nested into a large “regional” box (box 90) in
order to provide more detailed description in the area around the FDNPP. It
covers a circular-shaped surface area of a radius 15 km centred at the FDNPP
where observation data were collected. The coastal box has one vertical layer
for the water column and three bottom sediment layers. It is shallower than
the single-layer outer box 90. The water exchanges with the outer box are
equal in both directions. The averaged advective and diffusive fluxes between
regional compartments were calculated for a 10-year period (2000–2009) using
the Regional Ocean Modeling System (ROMS). The parameters of the coastal box
are given in Table S1 in the Supplement. Details of customization are given
by Maderich et al. (2014a, b). The values for parameters
ϕorg=0.01 and Tmigr,i=0.7 yr for i=3, 4, 9,
10, 11 were used.
The simulation of dispersion and fate of 137Cs was carried for the
period 1945–2010 to provide background concentrations of radiocaesium for the
radiological assessment of the FDNPP accident for the period 2011–2020 and to
verify the model with available data. The main source of 137Cs in the
north-western Pacific in the period 1945–2010 was from fallout due to
atmospheric nuclear weapon tests. The fallout includes a global component,
caused by the transport of radioactivity due to the general atmospheric
circulation and subsequent deposition on the surface of the ocean and a
regional component, caused by fallout from weapon tests carried out in the
Marshall Islands, resulting in the contamination of the surface layer of the
ocean. The annual deposition of 137Cs for the period 1945–2005, compiled
from Nakano (2006) and Hirose et al. (2008), is shown in Fig. S3a. The
concentrations of 137Cs at the eastern and southern boundaries (Fig. S3b) of the computational domain (Fig. S2) were estimated by using both
observations from the MARiS (Marine Information System) database (MARiS,
2015), and observations from Kang et al. (1997) and Nakano and Povinec
(2003). These values represent both the effect from global deposition of
137Cs on the north-eastern Pacific and the regional effect of weapon
tests carried out in the Marshall Islands. For the prediction of the
concentration of 137Cs for the period 2005–2020, 5-year averaged
deposition and the boundary concentrations during the period of 2000–2004
were extrapolated and corrected for radioactive decay. The simulation for the
period 1945–2010 was continued for the period of 2011–2020 with a source term
estimated from the Fukushima accident. It was assumed that the release of
activity directly to the ocean took place over the period 1–10 April 2011.
Amounts of 5 PBq of 134Cs, and 4 PBq of 137Cs were transferred
directly into the coastal box. These quantities are in accordance with widely
accepted source terms for the Fukushima accident simulations (see Povinec et
al., 2013). The atmospheric deposition data were obtained from simulations
with the MATCH model (Robertson et al., 1999) where the dispersion of
137Cs for the period 12 March–5 April was computed (Maderich et al.,
2014a). The ECMWF meteorological data with a source term reported by Stohl et al. (2012) were used in the simulation. The amount of deposited 137Cs in
the computational domain was 8.5 PBq. The deposition of 134Cs was
estimated at 10.2 PBq using an activity ratio 134Cs/137Cs=1.2. The atmospheric deposition was distributed between compartments
as shown in Fig. 2. The continuous leakage into the coastal box from the
middle of 2011 with a release rate of 3.6 TBq yr-1 (Kanda, 2013) was
taken into account.
The box system for the area close to Fukushima Dai-ichi Nuclear
Power Plant (FDNPP). The shaded boxes represent the deep-sea water boxes
divided on three vertical layers. The NPPs are shown by filled circles.
Coastal box around the FDNPP (marked by “F”) is inside box 90. A thick line
delimits the area of the Fukushima accident fallout.
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Results
The results from the modelling of the 137Cs concentration in the water
and in the upper layer of sediments of the coastal box are shown in Fig. 3.
Model results for the water demonstrate good agreement both with yearly
averaged observations by MEXT (the Japanese Ministry of Education, Culture,
Sports, Science and Technology) for the period 1950–2010 (MEXT, 2010) and
with observation by TEPCO (Tokyo Electric Power Company) for the period of
2011–2016 (TEPCO, 2016). Comparison of Fig. 3a with Fig. 9a from Maderich et al. (2014a) confirms that the model correctly simulated the almost constant
concentration of 137Cs in the water in the FDNPP vicinity due to the
continued leak of radioactivity from FDNPP (Kanda, 2013). The geometric mean
of the simulated-to-observed ratios is 1.03 with a geometric standard
deviation (GSD) of 1.89 for a total number of observations N=51 in the
period 1984–2016 when data are available.
The model also predicts well the concentration of 137Cs in the bottom
sediment before the accident and the sudden increase in concentration by more
than 3 orders of magnitude as a result of the accident. However, after 2013
(Fig. 3b) the observed concentration decreases faster than the model
prediction when a correction for vertical transfer is not included (see text
below). The estimated decrease constant of the fitted exponential function of
the measured sediment concentrations for 2012–2015 is λs=0.44 yr-1. The concentrations of 137Cs in the bottom sediment of the
coastal areas (B, C, D) with a depths less than 50 m in the Fukushima
Prefecture (Sohtome et al., 2014) show a similar decrease. The decrease
constant for area B located north of FDNPP is 0.44 yr-1 whereas for the
smaller areas C and D located south of the FDNPP it is 0.63 and
0.7 yr-1, respectively. For the deeper offshore area F adjacent to the
areas C and D the value of the decrease is much slower (0.24 yr-1).
Several possible mechanisms could be responsible for the observed
time–spatial redistribution of radioactivity in the surface layer of the
sediments. According to Ambe et al. (2014) the vertical transfer of
137Cs by resuspension and redeposition by ocean currents and waves,
desorption to the pore water, and bioturbation can result in a decrease of
137Cs concentration in the upper layer of sediments. Resuspension and
lateral transport of the fine-grained sediments also can redistribute
radiocaesium in the coastal sediments (Otosaka and Kobayashi, 2013). The
simplified representation of the exchange processes in the upper layer of the
sediment and the lack of re-suspension in the POSEIDON-R model cannot account
for these processes. Therefore, to take into account the vertical transfer of
137Cs we added the exchange terms (Cs,1-Cs,2)λs and
-(Cs,1-Cs,2)λs to the right hand side of the Eqs. (S3)
and (S4) for the concentration of radioactivity in the upper (Cs,1) and
medium (Cs,2) layers of sediment in the coastal box, respectively. Here
λs is an empirical parameter. The value of λs=0.4 yr-1 was found to best fit observational data for Cs,1. As
seen in Fig. 3b the concentrations of 137Cs are described well in period
2008–2015 when an additional exchange term is incorporated into the model.
The geometric mean of the simulated-to-observed ratios is 0.97 with GSD = 1.26
(N=46) for the period 1984–2015.
Comparison between calculated and observed 137Cs concentration
in seawater (a) and in bulk bottom sediment (b) in the coastal box around the
FDNPP. Values in (b) are given in becquerels (Bq) per kilogram (kg) of dry weight (DW). The dashed line
in (b) shows results of simulations using standard POSEIDON-R model,
whereas the solid line presents simulation with the correction term in Eq. (S3).
![]()
Comparison between calculated and observed 137Cs concentration
in deposit-feeding invertebrate (a), demersal fish (b), bottom predator
(c), and coastal predator (d) around the FDNPP. Values are given in becquerels (Bq)
per kilogram (kg) of wet weight (WW).
![]()
The simulated 137Cs concentrations in deposit-feeding invertebrates,
demersal fishes, bottom predators, and coastal predators in the coastal box
(placed at “F” in Fig. 2) are shown in Fig. 4 along with observed
concentrations by the Japan Fisheries Research Agency (JFRA, 2015). The
symbols in Fig. 4 are observation data for sea urchins
(Strongylocentrotus nudus) (a), flounders (Microstomus achne, Kareius bicoloratus, Pleuronectes yokohamae) (b), and Japanese rockfish
(Sebastes cheni) (c). The open and filled symbols in Fig. 4d are data
for seabass (Lateolabrax japonicus) and fat greenling
(Hexagrammos otakii), respectively. Just after the accident, the
simulated 137Cs concentration in the deposit-feeding invertebrates and
the observed concentration in the sea urchin increase due to the high
concentration of 137Cs in the water (Fig. 4a). After that, the
concentration trend becomes similar to trends in the sediments (Fig. 3b).
This is consistent with model diet that includes macroalgae and deposit
organic matter grossly representing the diet of S. nudus (Lawrence,
2007). The macroalgae contribution to contamination from feeding first
prevails. After 2012, the contamination from ingestion of bottom deposits
dominates. The decrease constant of the fitted exponential function of
simulated concentration (depuration constant) is 0.45 yr-1, which is
close to the decrease constant for the sediment observations
(0.44 yr-1). It agrees with observations by Sohtome et al. (2014) that
concentration in sediment and in deposit-feeding benthic invertebrates show
almost identical rates of decrease. The predicted transfer coefficient from
bulk sediment to deposit-feeding benthic invertebrates for the period of
2012–2020 is approximately 0.07. The field studies of several species of
Polychaeta (deposit or filter feeders: Flabelligeridae,
Terebellidae, and Opheliidae; herbivore or carnivore feeders:
Glyceridae, Eunicidae, and Polynoidae) off the coast of
Fukushima and rearing experiment for Perinereis aibuhitensis
demonstrated that 137Cs concentration in all specimens was much lower
than that in the sediment (Shigenobu et al., 2015). Results of experiments
using contaminated sediments from near the FDNPP showed that wet weight (WW)-based transfer coefficient (concentration ratio) between P. aibuhitensis and contaminated sediment
was less than 0.1.
The geometric mean of the simulated-to-observed ratios is 0.98 with GSD = 1.41 (N=21) for the period 2011–2015.
The results of simulation of the 137Cs concentration in the demersal
fishes (Fig. 4b) agree well with observations documented for several species
of flounders. The geometric mean of the simulated-to-observed ratios is 1.16
with GSD = 1.31 (N=49) for the period 1984–2015. The simulated value of the
depuration constant is 0.46 yr-1 whereas the value estimated from the
field data for 2012–2015 (Fig. 4b) is 0.48 yr-1. The gradual decrease of
activity in demersal fish caused by the transfer of activity from organic
matter deposited in the sediment is similar to observations by Wada et al. (2013). Notice that the predicted transfer coefficient from bulk sediment to
demersal fish for the period of 2012–2020 is approximately 0.13. This value
is larger than that for deposit-feeding invertebrates. The observed BCF for
demersal fish (flounders) in this area between 2013 and 2015 is 0.9 m3 kg-1, whereas the standard value of BCF for fish is
0.1 m3 kg-1 (IAEA, 2004). This confirms the importance of transfer of
radiocaesium to demersal fish from the sediments. Comparison of simulations
with observations for a bottom predator (Japanese rockfish) in Fig. 4c shows
also good agreement. The geometric mean of the simulated-to-observed ratios
is 0.84 with GSD = 1.73 (N=48) for the period 1984–2015. The comparison of
simulated and observed concentrations of 137Cs in coastal predators is
given in Fig. 4d. The open and filled symbols are data for seabass and fat
greenling, respectively. The geometric mean of the simulated-to-observed
ratios is 1.16 with GSD = 1.89 (N=69) for the period 1984–2015. As seen in
Fig. 4d, the simulated concentration of 137Cs in coastal predators
feeding on both pelagic and benthic organisms is similar to the simulated
concentration in pelagic piscivorous fish during the period of 2011–2013.
After 2013, the concentration in coastal predators decreases more slowly than
in piscivorous fish due to the omnivorous predation diet of coastal predators
which includes benthic organisms.
The model output can be sensitive to the model parameters that have a high
uncertainty. Therefore, a sensitivity study was carried out for the major
benthic food web parameters including the water uptake rate Kw,i, the
food uptake rate Kf,i, the biological half-life of 137Cs in the
organism T0.5,i, and for the concentration ratio of assimilated
radioactivity from the organic fraction in bottom sediment to the
radioactivity in bulk bottom sediment ϕorg. The effects of variations
in these parameters were estimated for the following model output: maximum
137Cs concentration in the organisms (i=2, ..., 11) in the coastal box
after the FDNPP accident. The range for Kw,i, Kf,i, T0.5,i,
and ϕorg is defined following Keum et al. (2015) as follows: minimum
value were set to half the reference value and maximum value were set to
twice the reference value. The reference values for Kw,i, Kf,i, and
T0.5,i are given in Tables 1 and 3, and ϕorg=0.01. The model
output sensitivity was estimated using a sensitivity index (SI) calculated
following Hamby (1994):
SI=Dmax-DminDmax,
where Dmax and Dmin are the simulation results for maximal and minimal parameter values, respectively.
Compartment system of POSEIDON-R model for the north-eastern part of
the Atlantic Ocean, the North Sea, and the Baltic Sea. The shaded boxes
represent boxes with two vertical layers. All other boxes in the Baltic Sea
consist of one vertical layer in the model.
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Figure S4a shows that all organisms (except primary producers) are most
sensitive to the variation of Kf,i, however, sensitivity is higher for
the pelagic components (i=2, 3) than for the benthic components
(i=7, ..., 11) of the food web, due to the higher diversity in the diet in
bottom-feeding organisms. The effect of variations of the biological
half-life for zooplankton T0.5,i is highest both for the pelagic and
benthic food webs (Fig. S4b). The maximum 137Cs concentration for
zooplankton using the maximal value of T0.5,i increased by a factor 2.7
compared to the concentration when the minimum value of T0.5,i was used.
For pelagic fish and coastal predators this factor ranged between 1.7 and 2.4,
whereas for the rest of the organisms it was smaller. The biological half-life
T0.5,6 of deposit-feeding invertebrates essentially influences
137Cs concentration in demersal fish (i=9). Figure S4c shows that the
effect of variations in the water uptake rate for zooplankton Kw,2
decreased in organisms at higher trophic levels, showing good agreement with
results by Keum et al. (2015). The concentrations of 137Cs in macroalgae
and deposit-feeding invertebrates are found to be 3 times more sensitive
to the variations in water uptake rates than other food web compartments. The
benthic organisms were less sensitive to the changes in ϕorg (Fig. S4d).