Similarities and differences of 137Cs distributions in the marine environments of the Baltic and Black seas and off the Fukushima Dai-ichi nuclear power plant in model assessments

Marine Pollution Bulletin 135 (2018) 895–906

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Marine Pollution Bulletin journal homepage: www.elsevier.com/locate/marpolbul

Similarities and differences of 137Cs distributions in the marine environments of the Baltic and Black seas and off the Fukushima Dai-ichi nuclear power plant in model assessments

T

⁎

V. Madericha, , R. Bezhenara, Y. Tatedab, M. Aoyamac, D. Tsumuneb a

Institute of Mathematical Machine and System Problems, Kiev, Ukraine Nuclear Risk Research Center, Central Research Institute of Electric Power Industry, Chiba, Japan c Institute of Environmental Radioactivity, Fukushima University, Fukushima, Japan b

A R T I C LE I N FO

A B S T R A C T

Keywords: Marine environment 137 Cs Chernobyl accident Fukushima accident Food chains Compartment modeling

The compartment model POSEIDON-R with an embedded food web model was used to assess 137Cs distributions in the Baltic and Black seas and off the Pacific coast of Japan during 1945–2020 due to the weapon testing and accidents at the Chernobyl and Fukushima Dai-ichi nuclear power plants. The results of simulations conducted with generic parameters agreed well with measurements of 137Cs concentrations in the water, bottom sediments, and in fish. In the Black and Baltic seas, salinity variations affected the transfer of 137Cs through the food web. The contamination of pelagic fish followed the water contamination with some delay, whereas demersal fish depuration was found to be related to decreasing 137Cs concentrations in the upper sediment layer. On the Pacific shelf off Japan, intensive currents and eddies caused the simulated depuration rates in fish to be one-two orders of magnitude larger than those in the semi-enclosed Black and Baltic seas.

1. Introduction The Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in 2011 attracted much attention to the marine pathways of the released radionuclides because about 85% of the 134Cs and 137Cs activity was released to the ocean (Buesseler et al., 2017). Less attention was paid to the impact of the Chernobyl Nuclear Power Plant (ChNPP) accident in 1986 on the marine environment, even though the total release of radionuclides by the ChNPP accident exceeded that by the FDNPP accident by an order of magnitude (Steinhauser et al., 2014). This lack of attention can be explained by the fact that most of the radioactivity released by the ChNPP accident was deposited on land, and the maximum radionuclide concentration in the marine environments of the Baltic and Black seas was smaller by several orders of magnitude than the maximum concentration in the coastal area around the FDNPP. However, because the areas of the Baltic and Black seas are small compared with the area of the North Pacific Ocean, radiocesium concentrations in these two seas were higher during the initial accident period than concentrations in the North Pacific, except in the coastal waters off the FDNPP. Radionuclide transfer processes in the marine environment differed between the ChNPP and FDNPP accidents because of differences in (i) pollution sources, (ii) marine basin geometry, (iii)

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circulation, (iv) bottom sediment composition, and (v) food chains of marine organisms. There were several major sources of 137Cs contamination to the marine environment due to these accidents (Table 1). The largest source was atmospheric deposition of radionuclides onto the sea surface. The second largest source in the case of the FDNPP accident was direct release of radionuclides to the ocean. Releases from land via river and coastal runoff and groundwater were much lower than those due to the first two sources. Because of the global scale of the ChNPP and FDNPP accidents, corresponding fallout was identified in the northwest Pacific and in European seas. According to Aoyama et al. (1987), the cumulative deposition in May 1986 of 137Cs on land in Japan after the ChNPP accident was 130 ± 26 Bq m−2, which is 2.5% of the total cumulative deposition from 1960 to 1982. The FDNPP accident resulted in the deposition of 4 Bq m−2 of radiocesium onto the Baltic Sea surface, and the estimated total input into this sea was 1.6 TBq (HELCOM, 2013), < 0.1% of the total input from the ChNPP accident. The three marine basins have very different geometries: shelf waters off the Japanese Islands are open to the deep ocean, whereas the semienclosed Black and Baltic seas are each connected to the ocean through a system of shallow and narrow straits. Circulation in the Black Sea is characterized by two seasonally varying gyres, whereas there are no

Corresponding author. E-mail address: [email protected] (V. Maderich).

https://doi.org/10.1016/j.marpolbul.2018.08.026 Received 2 April 2018; Received in revised form 8 August 2018; Accepted 12 August 2018 0025-326X/ © 2018 Elsevier Ltd. All rights reserved.

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differential equations that describe the temporal variation in the concentration, the exchange of radionuclides between adjacent compartments and between radionuclides in suspension and in the bottom sediment, and radioactivity sources and decay. Exchanges among the water column boxes are described by radionuclide fluxes due to advection, sediment settling, and turbulent diffusion. The bottom sediment compartment is divided into three layers, and the transfer of radioactivity between the upper sediment layer and the water column resulting from resuspension, diffusion and bioturbation, and between the upper and middle sediment layers, resulting from diffusion only, are described. Downward burial processes operate in all three sediment layers. It was found (Bezhenar et al., 2016a) that the standard parameterization of exchange between water column and bottom sediments, which includes sorption/desorption reactions, molecular diffusion and bioturbation, downplays fluxes of activity in shallow areas of Japan shelf with energetic currents. Therefore, the model was complemented by parameterization of resuspension mechanism allowing more accurately description of upper bottom sediments self-cleaning. The resuspension was parameterized as an additional flux directed from upper sediment layer to the water, which is proportional to the near-bottom velocity in shallow boxes. The POSEIDON-R compartment model equations and parameters are described in detail by Bezhenar et al. (2016a) and Maderich et al. (2018). The POSEIDON-R model can handle different types of radioactive releases: atmospheric fallout, river runoff of land-deposited radionuclides, point sources associated with both routine direct releases and accidental releases from nuclear facilities located on the coast or inland in rivers (Lepicard et al., 2004). A dynamic food web model that includes pelagic and benthic food chains is implemented within the POSEIDON-R compartment model (Bezhenar et al., 2016a). In the food web model, marine organisms are grouped into classes according to trophic level and species type (Fig. 1b). Radionuclides are also grouped into classes according to the fish tissue type in which they are preferentially accumulated (e.g., 137Cs tends to accumulate in muscle). These simplifications allow for a limited number of standard input parameters. The food chains differ between the pelagic zone and the benthic zone: pelagic organisms comprise primary producers (phytoplankton) and consumers (zooplankton, non-piscivorous (forage) fish, and piscivorous fish). In the benthic food chain, radionuclides are transferred from contaminated bottom sediments to deposit-feeding invertebrates, demersal fish, and benthic predators. Bottom sediments include both organic and inorganic components. Radioactivity is assumed to be assimilated by benthic organisms from the organic component of the bottom deposits. Thus, one important parameter is the ratio of the assimilated 137Cs concentration in the organic fraction to the bulk 137Cs concentration in the upper layer of bottom sediments ϕorg, which can range from 0.1 to 0.01 (Ono et al., 2015). In the present study, ϕorg was set to 0.02 in all three basins. The pelagic food web component was implemented in the upper layer of all compartments, whereas the benthic component was implemented only in the shallow one-layer compartments. Other food web components are crustaceans (detritus feeders), molluscs (filter feeders), and coastal predators, which feed throughout the water column in shallow coastal waters. All organisms take in radionuclides both via the food web and directly from the water. Because the uptake of cesium is higher in brackish water than in more saline seawater, a salinity-dependent correction factor was used to model the uptake of radiocesium by phytoplankton and macroalgae (Heling and Bezhenar, 2009). Details of the transfer of radiocesium through the marine food web in the food web model are presented in the Supplementary data (Section S1).

Table 1 Estimated sources of 137Cs from the ChNPP and FDNPP accidents to the marine environment. Source of marine contamination

Black Seaa (TBq)

Baltic Seab (TBq)

NW Pacific Oceanc (TBq)

Atmospheric fallout Direct release River runoff Groundwater Total

1700–2400 – 23 ? 1723–2423

3800–4800 – 300 ? 4100–5100

11,700–14,800 3500 60–70 60–70 15,200–18,300

a b c

Egorov et al. (1999). HELCOM (2009). Aoyama et al. (2016, 2018).

noticeable permanent currents in the Baltic Sea. In contrast, in the North Pacific, intensive eddies and flows associated with the Kuroshio Current and the Kuroshio Extension control Japanese offshore currents. In addition, freshwater from inflowing rivers reduces salinity in the Black and Baltic seas more than in the Pacific Ocean, and the reduced salinity in those seas affects biogeochemical reactions. These differences between the marine basins and the circumstances of the nuclear accidents raise a number of issues that require consideration about (i) the universality of models simulating the transport and fate of radionuclides released by the accidents, (ii) the applicability of model calibrations using data collected after previous releases of radioactivity to accidents that might occur elsewhere in the future, and (iii) the degree of isolation of regions, which are treated as homogeneous in models. A large number of models have been developed for simulating the transport and fate of radionuclides in the marine environment (see for example reviews by Tateda et al., 2013; Periañez et al., 2015a,b; Bezhenar et al., 2016a; Maderich et al., 2017; Periañez et al., 2016, 2018; Vives i Batlle et al., 2016, 2018). However, most of these issues have not yet been addressed, with the exception of Bezhenar et al. (2016a,b), who applied the same model to different marine basins. In this study, our objective was to assess long-term changes in 137Cs distributions in the marine environments of the Baltic and Black seas and off Japan following the ChNPP and FDNPP accidents by conducting simulations with a compartment model, POSEIDON-R (Lepicard et al., 2004; Maderich et al., 2014a), coupled with a dynamic food web model (Bezhenar et al., 2016a). We evaluated similarities and differences in the transfer of 137Cs due to differences in the geometry, salinity distribution, and currents in the three basins as well as to differences in the sources. In addition, we aimed to estimate the limits of applicability of a generic model developed to predict the long-term consequences of accidental releases of radionuclides into the marine environment. The paper is organized as follows. The compartment model and the dynamic food web model are briefly described in Section 2. The modeling results for the Black and Baltic seas after the ChNPP accident are presented in Sections 3 and 4, respectively, and those for the Pacific Ocean off Japan after the FDNPP accident are presented in Section 5. Section 6 discusses the similarities and differences of 137Cs distributions in three marine basins. Our findings are summarized in Conclusions. 2. POSEIDON-R model The POSEIDON-R compartment model (Lepicard et al., 2004; Maderich et al., 2014a,b; Bezhenar et al., 2016a) simulates the marine environment as a system of 3D compartments for the water column, bottom sediment, and biota (Fig. 1). The water column compartment is vertically subdivided into layers. The suspended matter is settling in water column. Radionuclides in the water column are assumed to be partitioned into dissolved and particulate fractions, and this partitioning is described by a distribution coefficient. The radionuclide concentration in each water compartment is governed by a set of

3. Contamination of the Black Sea by the ChNPP accident 3.1. Model setup The Black Sea is a deep, semi-enclosed marine basin connected with the Mediterranean Sea via the Turkish Straits system (Bosphorus, Sea of 896

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Fig. 1. (a) Structure of a generic compartment system in the POSEIDON-R model (Maderich et al., 2014a). (b) Radionuclide transfer from the water and bottom sediment boxes to marine organisms (Bezhenar et al., 2016a). The radionuclide transfers among marine food web compartments are given for 11 types of marine organisms. Fig. 2. The box system for the Black Sea, the Sea of Azov (box 50), and the Sea of Marmara (box 3). Boxes with deeper bathymetry have more layers: four-layer boxes are blue, three-layer boxes are indicated by diagonal blue and white stripes, two-layer boxes are marked by vertical blue and white stripes, and one-layer boxes are white. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 2 Parameters of sediments. Parameter

Black Sea Shallow areas −3

−3

Suspended sediment concentration, kg m

6 ⋅ 10

Sedimentation rate, kg m−2 y−1 Thickness of upper sediment layer, m Bioturbation coefficient, m2 y−1 Diffusion coefficient, m2 y−1 Porosity Density of sediment particles, kg m−3

0.15 0.1 3.6 ⋅ 10−5 0.0315 0.75 2600

Baltic Sea Deep areas 1 ⋅ 10

−3

East Japan coast Shallow areas −3

Deep areas 1 ⋅ 10−4

6 ⋅ 10

0.075

Variable in range 3 ⋅ 10−4 − 1 ⋅ 10−3 0.15–0.6

0.15

0.01

0.1 3 ⋅ 10−8 0.0315 0.75 2600

Ranged from 0.2 (Skagerrack) to 0.05 (Bothnian Bay) 3.6 ⋅ 10−5 0.0315 0.75 2600

0.1 3.6 ⋅ 10−5 0.0315 0.75 2600

0.1 3 ⋅ 10−8 0.0315 0.75 2600

897

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and in non-piscivorous fish (Black Sea sprat, Clupeonella cultriventris, and Black Sea anchovy, Engraulis encrasicolus ponticus) (Fig. 3) show two maxima, one related to the global fallout in 1963 associated with weapons testing (see Fig. S1), and another, larger maximum related to the ChNPP accident in 1986. The constants of exponential functions fitted to the simulated decreases in the 137Cs concentration after the ChNPP accident indicated that the rate of decrease was 0.07 y−1 for both the surface water layer and non-piscivorous fish; this rate is consistent with the rates estimated from measurements during 1990–2005 (0.07 and 0.09 y−1 for water and non-piscivorous fish, respectively). The decreases in the 137Cs upper layer concentration over time resulted from dilution due to 137Cs downward diffusion and outflow from the upper layer through the Turkish Straits (Eremeev et al., 1993; Polikarpov et al., 2008). The concentration of 137Cs in non-piscivorous fish was nearly in equilibrium with the concentration in the water, except during 1986–1990. The rate of decrease of radioactivity in the bottom sediments of the northwestern and western shelfs was similar in the simulation (0.04 y−1) and in observations (0.05 y−1) (Fig. 4). The predicted decrease in the 137Cs concentration in coastal predators of the northwestern and western shelf (0.05 y−1) was close to the predicted rate of decrease in the sediments, because invertebrates and demersal fishes, which are in contact with bottom sediments, are important components of their diet. The effect of salinity variations in the Black Sea was not large, except in river estuaries. We compared calculated and observed 137Cs concentrations in seawater and in non-piscivorous (Roach: Rutilus rutilus, Rutilus lacustris) and piscivorous fish (Zander: Sander lucioperca; Perch: Perca fluviatilis; and Asp: Leuciscus aspius) in the Dnieper–Bug estuary (box 49; in Figs. 3 and 5) between the observed salinity (S = 3) and Black Sea proper salinity (S = 18). The results (Fig. 5b and c) showed that the simulation reproduced the transfer of 137Cs through the food web in the estuary better when the low salinity in the estuary was taken into account. In general, the model predicted well the 137Cs concentrations in the water, bottom sediments, and different species of fish in the Black Sea, as shown by the geometric means of the simulated-to-observed ratios (GM) and the geometric standard deviation (GSD) (Table 3).

Marmara, and Dardanelles). It is also connected with the small, shallow Sea of Azov via the Kerch Strait. A box system was built for the Black Sea by using bathymetry data from the Copernicus Marine Environment Monitoring Service (CMEMS, 2018) (Fig. 2). The water column in each box is divided vertically into up to four layers according to water depth, 0–25, 25–100, 100–600 m, and from 600 m to the bottom; the number of layers in each box depends on the total water depth in that box. Boxes for the Sea of Marmara and the Aegean Sea (not shown) allow the exchange of radiocesium between the Black Sea and the Mediterranean Sea to be described. Advective and diffusional water fluxes between boxes were calculated by averaging three-dimensional currents in the CMEMS (2018) reanalysis data over 10 years (2006–2015). The water budget of the Black Sea includes evaporation/precipitation, runoff from the Danube and Dnieper rivers as well as exchanges with the Sea of Azov and the Aegean Sea The two-layer water fluxes from the Black Sea to the Marmara Sea and in the opposite direction are 429.4 km3y−1 and 176.3 km3y−1, respectively, whereas water fluxes from the Marmara Sea to the Aegean Sea and in the opposite direction are 742.9 km3y−1 and 489.8 km3y−1, respectively (Maderich et al., 2015). The water exchange rates of the Azov Sea with the Black Sea and the Black Sea with the Azov Sea are 47.5 and 33.1 km3y−1, respectively (Maderich et al., 2015). The surface salinity S of the Black Sea proper was set to 18, whereas over the northwestern shelf (boxes 45–47) and in the Azov Sea (box 50), it was set to 16 and 12, respectively. The salinity in boxes 44 (near the mouth of the Danube River) and 48 (mouth of the Dnieper River) was set to 14, and that in box 49 (Dnieper–Bug estuary) was set to 3. The parameters of sediments based on estimates obtained by Simmonds et al. (1995) are given in Table 2. The simulation of the dispersion and fate of 137Cs was carried out for the period 1945–2020. The main source of 137Cs before the ChNPP accident was global fallout from atmospheric nuclear weapons tests. The annual deposition density of 137Cs between 40°N and 50°N latitude (UNSCEAR, 2000) for 1945–2000 is shown in Fig. S1 (Supplementary data). To estimate the 137Cs deposition rate during 2001–2020, 5-year averages during 1995–1999 were extrapolated and corrected for radioactive decay. There are no data on deposition over the Black Sea due to the ChNPP accident in May 1986, but Nikitin et al. (1988) reported that 137Cs contamination of surface waters during June–July 1986 was non-uniform and was higher along the path of the radioactive cloud transported in the atmosphere from the damaged ChNPP reactor. To reconstruct deposition following the accident, we assumed that the 137 Cs deposition density in the Black Sea at the beginning of May 1986 was proportional to the 137Cs surface concentrations measured in June–July 1986. Then we normalized these values by the total amount of 137 Cs deposited on the sea surface, conservatively estimated as 2400 TBq (Egorov et al., 1999). The resulting distribution of the atmospheric deposition density and inventory of 137Cs among the boxes of the Black Sea and adjacent seas in 1986 due to the ChNPP accident is given in Table S3. Deposition onto the surface of the Aegean Sea box from Chernobyl fallout was set following Kritidis and Florou (1990). Because data are lacking for the period 1945–1985, the influx of 137Cs into the Black Sea from the Danube and Dnieper rivers was estimated by using a generic river runoff model (Smith et al., 2004) to calculate the 137Cs concentration in the river runoff. Observation data (Voitsekhovych, 2001) were used for the period 1986–1997, but the generic model was used again for the period 1998–2009. Data for 2010–2020 were estimated by extrapolation (Fig. S2).

4. Contamination of the Baltic Sea due to the ChNPP accident 4.1. Model setup The transport and fate of 137Cs in the Baltic Sea were simulated for the period 1945–2020. The POSEIDON-R model was customized for the Baltic Sea, the North Sea, and the North Atlantic Ocean with a total of 81 regional boxes (Fig. 6). The volume and average depth of the 47 boxes describing the Baltic Sea were derived from bathymetric data. A water column with a depth of > 60 m was divided into two layers (surface and bottom) to describe radioactivity stratification in the water column. The exchange of water among boxes in the Baltic Sea was based on the 10-year average (1991–2000) of three-dimensional currents from a reanalysis dataset (CMEMS, 2018). The exchange rates for the other boxes were adopted from the standard POSEIDON-R configuration (Lepicard et al., 2004). So that the water balance of the Baltic Sea and the inflow of radioactivity from river runoff could be described, an additional 16 boxes were defined to represent the main rivers flowing into the Baltic Sea basin. The inflow of river water into each box was based on information reported by Leppäranta and Myrberg (2009). Concentrations of suspended sediments (different for each box) were calculated with the 3D hydrodynamic THREETOX model (Maderich et al., 2008). The range of values for sediment parameters is given in Table 2. More details of the customization are given by Bezhenar et al. (2016a). The main sources of 137Cs during 1945–2020 in the model simulation were global deposition from weapons testing and the Chernobyl

3.2. Simulation results The simulation results for 1950–2020 for six boxes across the Black Sea where 137Cs concentration data for the water and fish are available (MARiS, 2018; Aoyama et al., 2018) are shown in Fig. 3. Aoyama et al. (2018) compiled these data from various publications, including books and reports (e.g. Eremeev et al., 1993; Polikarpov et al., 2008). The temporal variations of 137Cs concentrations in the surface water layer 898

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Fig. 3. Comparison between simulated (solid lines) and observed (filled circles) 137Cs concentrations in (a) water and (b) non-piscivorous fish in six boxes across the Black Sea. The measurement data were compiled by Aoyama et al. (2018). Values in fish are given in becquerels (Bq) per kilogram (kg) of wet weight (WW).

and reflected global fallout from weapons testing (see Fig. S3). A second maximum observed in the Kattegat (boxes 35–40) and the southern Baltic (boxes 44–47) during 1980–1985 was caused by the inflow of contaminated water from the Sellafield and La Hague reprocessing plants (see Fig. S4). The Chernobyl deposition in April–May 1986 was non-homogeneously distributed over the Baltic Sea (see Table S4). The corresponding concentration maximum in the surface water was observed in the Åland and Bothnia seas (boxes 68–79). The constant of the exponential function fitted to the simulated decrease of the 137Cs concentration in water after the ChNPP accident indicated that the rate of decrease was 0.08 y−1, which is somewhat larger than the rates estimated from observations (0.05–0.06 y−1), but both are close to the Black Sea values, despite the differences in the basin geometries. The observed distribution of 137Cs concentrations in the upper layer of bottom sediments (MORS, 2018) is very patchy. Comparison of the calculated and observed concentrations averaged over the western Baltic (boxes 37–44), the southern Baltic (boxes 45–61), and the northern Baltic (boxes 69–81) (Fig. 8) showed good agreement between them. The northern Baltic, including the Gulf of Bothnia, was the most contaminated. The constants estimated from exponential functions fitted to the simulated 137Cs concentrations decreased in the sediments after the ChNPP accident as well as those estimated from measured values, which ranged from 0.04 to 0.06 y−1. The temporal variation of the 137Cs concentration in a non-piscivorous fish (sprat, Sprattus sprattus) (Fig. 7b) corresponds in general to that in the upper water layer (Fig. 7a). However, because the diet of demersal fish includes organic deposits and deposit-feeding invertebrates (Bezhenar et al., 2016a), the temporal variations of the concentration in European flounder, Platichthys flesus (Fig. 7c) correlate with the concentration of 137Cs in the bottom sediments (correlation coefficient, 0.7). Further, the rate of decrease in the demersal European flounder was almost the same as that in the sediment. The similar to demersal fish behaviour of temporal and spatial variations of 137Cs contamination in a coastal predator (Atlantic cod, Gadus morhua; Fig. 7d) can also be explained by its diet, which includes, along with non-piscivorous fish, molluscs, crustaceans, and demersal fishes. The general agreement between simulated and observed 137Cs concentrations in water, bottom sediment, and different types of fish in the Baltic Sea is confirmed by the GM and GSD values, which varied from 0.86 to 0.91 and from 1.32 to 2.17, respectively (Table 3). The salinity of the brackish water of the Baltic Sea varies over a large range, from 25 to 5. Therefore, it is important to take account of

Fig. 4. Comparison between simulated and observed 137Cs concentrations in bottom sediment of the northwestern shelf of the Black Sea. The measurement data were compiled by Aoyama et al. (2018). Values are given in becquerels (Bq) per kilogram (kg) of dry weight (DW).

accident (HELCOM, 1995), releases from the Sellafield (Cumbria, England) and La Hague (northern France) reprocessing plants (HELCOM, 2009), regional deposition from the Chernobyl accident in May 1986 (HELCOM, 1995), and river runoff. Details are given in the Supplementary data (global deposition, Fig. S3; Sellafield and La Hague releases, Fig. S4; regional Chernobyl accident deposition, Table S4). River runoff from each catchment area was calculated by using the generic model of Smith et al. (2004). Salinity in the Baltic Sea gradually decreased from S = 25 in the Kattegat boxes (boxes 35–40), to S = 15 in the Baltic Sea proper, to S = 5 in the Gulf of Finland (boxes 65–67) and the Gulf of Bothnia (boxes 80–81).

4.2. Simulation results Simulation results for 1950–2020 for six boxes in the Baltic Sea where measurement data for 137Cs concentrations in the water, bottom sediment, and fish were available (MORS, 2018) are shown in Fig. 7. Temporal variations of the 137Cs concentration in the surface water layer depended on the distance from the North Sea (Fig. 7a). The first concentration maximum observed in the whole sea occurred in 1963 899

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a coastal predator (Atlantic cod, Gadus morhua) in box 68 for the observed salinity (S = 6) and without any salinity correction showed that it is essential to take account of the influence of low salinity on the transfer of 137Cs in the food web to reproduce observed values of 137Cs concentrations (Fig. 9). Bezhenar et al. (2016a) found that use of the standard model without considering salinity for brackish waters for whole Baltic Sea can lead to a considerable underestimation of 137Cs concentrations in non-piscivorous fish.

5. Contamination of the marine environment off Fukushima due to the FDNPP accident 5.1. Model setup The POSEIDON-R model was customized for the northwestern Pacific Ocean, the East China and Yellow seas, and the Sea of Japan (188 boxes, Fig. S5), similar to the customization of Maderich et al. (2014a,b), except for the coastal waters off the FDNPP (Fig. 10), where boxes A–J correspond to areas defined by Wada et al. (2016), who reported 137Cs concentration measurement data for marine organisms. To describe the vertical structure of radioactivity transport in deep-sea regions, a three-layer box system was constructed. The model consisted of an upper layer from 0 to 200 m water depth, an intermediate layer (200–1000 m), and a deep layer (water depth > 1000 m). The averaged advective and diffusive fluxes between compartments were calculated for a 3-year period (2011–2014) by using FORA-WNP30, a fourdimensional variational ocean reanalysis dataset spanning 30 years for the western North Pacific (Usui et al., 2017). Main sediment parameters are given in Table 2. The main source of 137Cs in the northwestern Pacific during 1945–2010 was fallout from atmospheric nuclear weapon tests, which included (i) a global component and (ii) a regional component due to fallout from weapon tests carried out in the Marshall Islands that contaminated the surface layer of the ocean. The annual deposition density of 137Cs during 1945–2005 due to global atmospheric circulation was compiled from Nakano (2006) and Hirose et al. (2008) and extrapolated to 2020 (Fig. S6). The 137Cs concentrations at the eastern and southern boundaries (Fig. S7) of the computational domain (Fig. S5) were estimated by using observations from the Marine Information System (MARiS) database (MARiS, 2018), Kang et al. (1997), and Nakano and Povinec (2003), and extrapolations of those data to 2020. The simulation for 1945–2010 was continued during the period 2011–2020, and for the latter period it included as sources (i) atmospheric deposition of 137Cs on the sea surface, (ii) direct release from the FDNPP, and (iii) river runoff. The atmospheric deposition data were obtained from simulations by Tsumune et al. (2013). The temporal variations of the 137Cs release from the FDNPP to the ocean are shown in Fig. S8. Initially (April 2011), the 137Cs activity flux was dominated by direct releases from the power plant; subsequently, although leakage from the FDNPP continued, the release rate decreased (Fig. S8). In this study, we set the activity fluxes in boxes affected by river runoff as follows: Abakuma River, box 90; Mano and Niida rivers, box B; Ota and Ukedo rivers, box C; and Fujiwara and Same rivers, box E. The annual average release of 137Cs via these rivers was estimated from measurements made during 2013–2015 and extrapolated for the periods from July 2011 to the end of 2012 and from the beginning of 2016 to 2020. In total, 3.4 PBq of 137Cs was deposited from the atmosphere in the computational domain (area shown in Fig. S5; 34–41°N, 140–146°E), 3.5 PBq was directly released into box C in April 2011, 80 TBq was released into box C as a result of leakage during 2011–2020, and 2.9 TBq was released into the domain in river runoff. These quantities are in accordance with widely accepted source terms for Fukushima accident simulations (see Table 1).

Fig. 5. Comparisons between 137Cs concentrations simulated using two different salinity levels (S = 3 or S = 18) and observed 137Cs concentrations (Katrich et al., 1992; EMRAS, 2006) in (a) seawater, (b) non-piscivorous fish, and (c) piscivorous fish in the Dnieper–Bug estuary. Values in fish are given in becquerels (Bq) per kilogram (kg) of wet weight (WW). Table 3 Geometric mean simulated-to-observed ratios (GM) and geometric standard deviations (GSD) of each model variable for the Black and Baltic seas and the northwestern Pacific. Model variable

Water Sediment Non-piscivorous fish Piscivorous fish Demersal fish Bottom predator fish Coastal predator fish

Black Sea

Baltic Sea

NW Pacific

GM

GSD

GM

GSD

GM

GSD

1.07 0.99 1.06 1.12 – – 1.27

1.34 1.49 1.47 1.92 – – 1.73

0.89 0.86 0.91 – 0.92 – 0.91

1.42 2.17 1.32 – 1.67 – 1.37

1.16 0.96 2.6 – 0.68 0.77 0.85

2.05 2.35 3.63 – 2.17 2.22 2.46

the effect of salinity variations on the transfer of 137Cs through the food web in this sea. Comparisons between calculated and observed 137Cs concentrations in a non-piscivorous fish (herring, Clupea harengus) and 900

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Fig. 6. Box system in the Baltic Sea (right) and connecting boxes in the northeastern Atlantic Ocean (boxes 3–5) and the North Sea (boxes 27–33) (left) in the POSEIDON-R model (Bezhenar et al., 2016a). Boxes with two layers in the water column are blue, and white boxes have only one layer. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

FDNPP (box C). These results can be explained by the fast propagation of the contamination plume southward by currents and eddies in the initial stage; this fast propagation could not be captured by the timeaveraged exchanges among boxes in the compartment model. Notice that observed 137Cs concentration the bottom sediments (Fig. S10) demonstrates strong patchiness inside of box due to the mesoscale bottom relief inhomogeneity (Maderich et al., 2017) and intermittence of plumes of contaminated water in the initial period of radioactivity release. Therefore, a comparison with averaged over the boxes measurement data in Fig. 11b was carried out to reduce effects of the smallscale patchiness. Qualitatively, the model correctly reproduced observed temporal variations of the contamination in Japanese jack mackerel (Trachurus japonicas), a non-piscivorous fish (Fig. 11c). Similar to the results for non-piscivorous fish in the Black and Baltic seas, contamination of this type of fish in the northwestern Pacific followed the water contamination with some delay. The rates of decrease (depuration rates) of 137Cs concentrations in this non-piscivorous fish during 2011–2012 and 2012–2018 were 2.8 y−1 and 0.4 y−1, respectively. However, the temporal shift between observed and calculated concentrations resulted in large GM and GSD values for non-piscivorous fish (Table 3). These results can be explained by the inaccurate representation of short-term transport processes in the box model, but they might also reflect the seasonal migration of this species of fish (Yamanaka, 1988). The temporal variations of 137Cs concentrations in demersal fish are similar to those of the contaminated bottom sediments because of the diet of the demersal fish. Therefore, the calculated rate of decrease (0.3 y−1) was the same as that for the sediment contamination. The observed concentration in the demersal slime flounder (Microstomus achne) also decreased similarly to the sediment concentration (Fig. 11b and d). The observed depuration rates in 2012–2015 were greater in the southern boxes D and E (0.9 and 0.9 y−1), in agreement with the higher observed rate of decrease in the upper sediment layer (0.7 and 0.5 y−1).

5.2. Simulation results Maderich et al. (2014a) and Bezhenar et al. (2016a) compared the simulation results with measurements in the northwestern Pacific and adjacent seas for the period 1945–2020. Here we consider in more detail temporal and spatial variations of 137Cs concentrations in the water, bottom sediments, and fish in the coastal boxes off the FDNPP during 2005–2020. We compared the simulation results with measurement data compiled from the NRA (2018), Sohtome et al. (2014), Fievet et al. (2017), Wada et al. (2016), and Aoyama et al. (2018) for boxes A–E and 90 and averaged over the boxes (Fig. 11). Results of our simulation compared with measurements for boxes A–M, 90, 91, and 170 are given without averaging in the Supplementary data (Figs. S9–S14). The 137Cs concentration in the water decreased quickly after April 2011 as a result of dilution by currents and eddies (Fig. 11a). The constants of the exponential functions fitted to the decreasing 137Cs concentrations in water during 2011–2012 varied from 3.5 to 4.5 y−1 for coastal boxes A–E (Fig. 11a); these values exceed approximately 50 times the corresponding constants for water contamination in the Black and Baltic seas. However, after 2012, the rate of decrease was considerably smaller (0.6 y−1) because of the continuing influx of contaminated water from the FDNPP. The 137Cs concentration in the coastal boxes was predicted to return to the pre-accident level (2 Bq m−3) in 2020. The 137Cs concentration in the upper layer of sediment decreased much more slowly than the concentration in the water (Fig. 11b); the simulated rate of decrease in the upper sediment was about 0.3 y−1. This result indicates that the 137Cs concentration in the water was not in equilibrium with that in the sediment after the FDNPP accident. Note that the model underestimated the concentration in the sediment south of the FDNPP (boxes E and D) and overestimated the concentration north of the FDNPP (boxes A and B), whereas calculations and observations agreed well near where radioactivity was released from the

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Fig. 7. Comparison between simulated (solid lines) and measured (filled circles) 137Cs concentrations in (a) water and (b–d) fish in six boxes in the Baltic Sea: (b) a non-piscivorous fish (sprat); (c) a demersal fish (European flounder); and (d) a coastal predator (Atlantic cod). The measurement data were compiled by MORS (2018).

Tateda et al. (2016) attributed the slow 137Cs depuration in demersal fish in part to continuing radiocesium transfer to the fish from benthic detritivorous invertebrates. The transfer of 137Cs from bottom sediments though the benthic food chain also accounted for the temporal variation of 137Cs contamination in the rockfish (Sebastes cheni), a bottom predator (Fig. 11e). Because of the mixed diet of the bottom predator, the depuration rate varied, but over time, the rate approached the rate of decrease in the bottom sediment (0.3 y−1). The diet of coastal predators typically includes both pelagic and benthic organisms. Therefore, temporal variations of 137Cs concentrations in the coastal predator (fat greenling, Hexagrammos otakii) were complicated (Fig. 11f). Initially, the 137Cs concentration corresponded to that in the pelagic component of its diet, but as the contamination of pelagic organisms (fish, crustaceans, and molluscs) decreased over time, the coastal predator depuration rate approached the depuration rate of benthic deposit or filter feeders (e.g. several species of Polychaeta), in which the concentration of 137Cs remained relatively high for a longer time. These findings qualitatively agree with estimates of the ecological half-life of 137Cs in marine organisms; for example, its ecological half-life in the olive flounder (Paralichthys olivaceus) in the first two years after the accident was 140–160 d, which is longer than its biological half-life in that species

Fig. 8. Comparison between simulated (solid lines) and observed (symbols) 137 Cs concentrations in bottom sediment averaged over the western, southern, and northern Baltic and over the year. The measurement data were compiled by MORS (2018). Values are given in becquerels (Bq) per kilogram (kg) of dry weight (DW).

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Fig. 9. Simulated concentrations of 137Cs in a (a) non-piscivorous fish and (b) coastal predator for two levels of salinity in box 68 compared with observed concentrations compiled by MORS (2018). Fig. 10. Boxes along the eastern coast of Japan; note the fine resolution in the area of the FDNPP. Boxes A–J are similar to area defined by Wada et al. (2016). Red circles show nuclear power plant locations in Japan. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

n

(Tateda et al., 2015, 2016).

Cf , i =

∑ Cprey,j Pi,j j=1

drwpred, i drwprey, j

(2)

6. Discussion where Cprey,j is the radioactivity concentration in prey of type j, Pprey,j is the preference for prey of type j in the diet of a predator, drwpred,i is the dry weight fraction of the predator, and drwprey,j is the dry weight fraction of prey of type j. Note that BCF1 (the factor for phytoplankton) has been prescribed by the International Atomic Energy Agency (IAEA, 2004). Other model details are given in Section S1. The BCF model calculations were carried out for a constant salinity value of S = 18 in the Black Sea proper, for a range of salinities in the Baltic Sea (S = 5–25), and for a constant salinity value of S = 34.5 in the western Pacific. The BCF values estimated from measurements in the Black Sea and the southern and central Baltic Sea were obtained for the period 1992–2010, when concentrations in the water and biota were close to equilibrium. Data from the shelf along the Pacific coast of eastern Japan for the period 1988–2010 (i.e. before the accident) were used (JCAC, 2018) because strong non-equilibrium conditions prevailed in these areas after the FDNPP accident. In Table 4, these BCF values are compared among these three marine environments and also with IAEA (2004) data. In the Black Sea, the salinity effect was moderate, except in the Dnieper–Bug estuary, whereas in the Baltic Sea, BCFs varied by a factor of two from south-west to north-east. The basin- and fish-averaged values are consistent with the globally averaged values from the IAEA (2004). Thus, in general, the estimates obtained from observations confirm the reliability of the generic model.

Our simulation results showed that differences in the geometry of marine basins, intensity of marine circulation, the freshwater budget, and the related salinity distribution influence the transfer of radioactivity in the marine environment. For example, ion competition leads to increases in the uptake of cesium with decreasing salinity (Heling and Bezhenar, 2009) because the concentration of competing potassium ions decreases (Figs. 5 and 9). Here, we consider the difference between bioconcentration factors calculated with the model and those estimated from 137Cs concentration measurements in the Black and Baltic seas and along the Pacific coast of eastern Japan. The bioconcentration factor BCF (L kg−1) is calculated by assuming that concentrations in water, sediments, and organisms are in equilibrium. In the framework of the model (Bezhenar et al., 2016a), BCFi for the i-th organism shown in Fig. 1b (i = 2 … 11) is calculated as

Cf , i T0.5, i BCFi = ⎧ai Kf , i + bi Kw, i ⎫ ⎨ ⎬ Cw ⎩ ⎭ ln 2

(1)

where Kf,i is the food uptake rate, ai is assimilation efficiency, Kw,i is the water uptake rate, bi is the water extraction coefficient, Cf,i is the radioactivity concentration in food, Cw is the radioactivity concentration in the water, and T0.5,i is the biological half-life. The value of Cf,i can be expressed by the following equation for a total of n prey types, 903

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Fig. 11. Comparisons between simulated (solid lines) and measured (filled circles) 137Cs concentrations in (a) water, (b) bottom sediments, and (c–f) fish in the boxes along the coast off the FDNPP: (c) non-piscivorous fish (Japanese jack mackerel); (d) demersal fish (Slime flounder); (e) bottom predator (Rockfish); and (f) coastal predator (Fat greenling). The box-averaged measurement data were compiled from Sohtome et al. (2014), Fievet et al. (2017), Wada et al. (2016), Aoyama et al. (2018), and NRA (2018).

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salinity distribution, sea currents, and sources of contamination. The simulation results obtained by using the same model with generic parameters generally agreed with 137Cs concentration measurements in the water, bottom sediments, pelagic non-piscivorous fish, demersal fish, and predatory fish in all three marine environments. An important factor in the brackish Baltic sea was salinity variation, which affected the transfer of 137Cs through the food web. The contamination in the pelagic fish followed the water contamination with some delay, whereas calculated depuration rates in demersal fish corresponded to 137 Cs concentration decreases in the upper layer of sediments; this result was inferred to be due to the ingestion of organic sediment components and invertebrates in the contaminated organic sediment by the demersal fish. Because of the intensive currents and eddies on the shelf of the Pacific coast of eastern Japan, depuration rates in non-piscivorous fish were two orders of magnitude larger than those in the semienclosed Black and Baltic seas, and depuration rates in demersal fishes were an order of magnitude larger. Generally, the results of our comparisons between simulations by the compartment model with embedded dynamic food web model and measurements indicate that, with some restrictions, the model can be used with generic parameter values in radiation emergency situations in areas where limited information is available. An example is the implementation of the POSEIDON-R model in the decision support system JRODOS (Bezhenar et al., 2016b).

Table 4 Bioconcentration factors for biota calculated by the model and estimated from observations. Model variable

Crustaceans Molluscs Non-piscivorous fish Piscivorous fish Demersal fish Bottom predator fish Coastal predator

Black Sea S = 18

Baltic Sea S = 5–25

NW Pacific S = 34.5

IAEA (2004).

Calc.

Obs.

Calc.

Obs.

Calc.

Obs.

72 86 81

– – 62

64–166 75–201 73–171

– – 87

64 75 73

– – –

50 60 100

95 56 106

– – –

87–187 55–66 99–182

– 114 –

87 55 99

– 48 86

100 100 100

131

–

123–220

132

123

104

100

Table 5 Depuration rates (y−1) calculated by the model and estimated from observations. The high values in parentheses are the depuration rates during one year after the FDNPP accident. Model variable

Water Bottom sediments Non-piscivorous fish Piscivorous fish Demersal fish Bottom predator Coastal predator

Black Sea

Baltic Sea

NW Pacific

Calc.

Obs.

Calc.

Obs.

Calc.

Obs.

0.07 0.04 0.07 0.07 0.06 0.07 0.05

0.07 0.05 0.09 – – – –

0.08 0.06–0.04 0.08 0.08 0.08 0.07 0.05–0.07

0.05–0.06 0.06–0.04 0.07 – 0.06 – 0.02–0.05

(4) 0.6 0.3 (2.6) 0.4 (1.5) 0.3 (1) 0.4 (1.1) 0.3

(3) 0.4 0.3 – – (0.6) (0.9) (0.7)

Acknowledgments This work was supported by the State Fund for Fundamental Research project SFFR 868/12879 on the Ukraine side, and by Japan Society for the Promotion of Science under the Japan - Ukraine Research Cooperative Program #16932059 entitled “Transfer of radioactivity between contaminated bottom sediment and the marine environment after Fukushima and Chernobyl accidents” on the Japanese side. This work was also supported by IAEA CRP K41017 “Behaviour and Effects of Natural and Anthropogenic Radionuclides in the Marine Environment and their use as Tracers for Oceanography Studies”.

The constants of the exponential functions fitted to observed rates of decrease or depuration of 137Cs concentrations after the accidents greatly varied both among the marine basins and among species of marine organisms (Table 5). The rates of decrease of upper water layer contamination were similar in the Black and Baltic seas because water exchange with the ocean was limited, whereas in waters off the FDNPP, initial rates (shown in parentheses) were almost two orders of magnitude larger than they were in the Black and Baltic seas. Even long after FDNPP accident when depuration rates became governed by the weak FDNPP radioactivity source, they were an order of magnitude larger than the depuration rates in the Black and Baltic seas. The depuration rate of non-piscivorous fish was close to the water concentration decrease rate in all three marine basins. The depuration rate in bottom sediments was similar between the Black and Baltic seas, whereas selfcleaning processes in the bottom sediments along the Pacific coast of eastern Japan due to intense currents resulted in the resuspension of contaminated sediments and the depuration rate an order of magnitude larger than rates in the Black and Baltic seas. The demersal fish depuration rate was close to the bottom sediment depuration rate, a result inferred to be due to the diet of these fish species, which includes both organic sediment components and bottom-dwelling organisms. Depuration rates varied in coastal predators, the diet of which includes both pelagic and benthic organisms.

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