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Journal of Environmental Radioactivity 136 (2014) 218e228

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Journal of Environmental Radioactivity

journal homepage: www.elsevier .com/locate / jenvrad

Factors controlling the spatiotemporal variation of 137Cs in seabedsediment off the Fukushima coast: implications from numericalsimulations

Kazuhiro Misumi a, *, Daisuke Tsumune a, Takaki Tsubono a, Yutaka Tateda a,Michio Aoyama b, Takuya Kobayashi c, Katsumi Hirose d

a Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry, 1646 Abiko, Abiko, Chiba 270-1194, Japanb Institute of Environmental Radioactivity, Fukushima University, 1 Kanayagawa, Fukushima, Fukushima 960-1296, Japanc Nuclear Science and Engineering Directorate, Japan Atomic Energy Agency, 2-4 Shirakata-Shirane, Tokai, Ibaraki 319-1195, Japand Department of Materials and Life Sciences, Faculty of Science and Technology, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo 102-8554, Japan

a r t i c l e i n f o

Article history:Received 3 February 2014Received in revised form9 May 2014Accepted 3 June 2014Available online 27 June 2014

Keywords:CesiumFukushima accidentSedimentNumerical model

* Corresponding author. Tel.: þ81 7065689803.E-mail address: misumi@criepi.denken.or.jp (K. M

http://dx.doi.org/10.1016/j.jenvrad.2014.06.0040265-931X/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

We used numerical simulations to investigate major controls on spatiotemporal variations of 137Cs ac-tivities in seabed sediments off the Fukushima coast during the first year after the Fukushima DaiichiNuclear Power Plant accident. The numerical model we used includes 137Cs transfer between bottomwater and sediment by adsorption and desorption, and radioactive decay. The model successfullyreproduced major features of the observed spatiotemporal variations of 137Cs activities in sediments. Thespatial pattern of 137Cs in sediments, which mainly reflected the history of 137Cs activities in bottomwater overlying the sediments and the sediment particle size distribution, became established during thefirst several months after the accident. The simulated temporal persistence of the 137Cs activity in thesediments was due to adsorption of 137Cs onto the sediment mineral fraction having a long desorptiontimescale of 137Cs. The simulated total 137Cs inventory in sediments integrated over the offshore area,where most of the monitoring stations were located, was on the order of 1013 Bq; this value is consistentwith a previous estimate based on observed data. Taking into account 137Cs activities in sediments inboth the coastal area and in the vicinity of the power plant, the simulated total inventory of 137Cs insediments off the Fukushima coast increased to a value on the order of 1014 Bq.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

On 11 March 2011, the Tohoku earthquake and subsequenttsunami caused serious damage to the Fukushima Daiichi NuclearPower Plant (1F NPP) operated by the Tokyo Electric Power Com-pany (TEPCO), resulting in the accidental release of radiocesium,134Cs (half-life 2.06 years) and 137Cs (half-life 30.2 years), to theenvironment. Ocean contamination likely occurred via two majorpathways (Japanese Government, 2011): atmospheric depositionand direct release of radioactivity-contaminated water to theocean. The estimated total amount of 137Cs released to the atmo-spherewas 15 PBq (Japanese Government, 2011); much of this 137Csis presumed to have been subsequently deposited on the oceansurface by both wet and dry deposition (Takemura et al., 2011;

isumi).

Morino et al., 2011; Stohl et al., 2012). Estimates of the totalamount of 137Cs discharged directly to the ocean range from 3.5 to16.2 PBq (Kawamura et al., 2011; Tsumune et al., 2012, 2013;Estournel et al., 2012; Miyazawa et al., 2013; Rypina et al., 2013).It is noteworthy that equal amounts of 134Cs and 137Cs werereleased into the ocean (Buesseler et al., 2011). Observed 137Cs ac-tivity in seawater near 1F NPP was on the order of 108 Bq m�3 (wedescribe ‘on the order of’ as O(10x) hereafter) in early April 2011;during the first month after the accident, activity decreased rapidlyto O(105) Bq m�3 (Buesseler et al., 2011) and one year after theaccident it had decreased to O(103) Bq m�3 (TEPCO, 2012).

In contrast, clear decreases of 137Cs activities in the coastalsediments were not observed even one year after the accident(Otosaka and Kobayashi, 2013; Kusakabe et al., 2013). Suchpersistence suggests that incorporation of 137Cs into sediments wascontrolled by slow reversible reactions (Otosaka and Kobayashi,2013). Observed 137Cs activities in the sediments showed aspatially heterogeneous distribution, which was determined

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228 219

mainly by two factors: 1) the spatiotemporal variation of the 137Csactivities in the overlying bottom water, and 2) the physical prop-erties of the sediment, such as grain size and bulk density (Otosakaand Kobayashi, 2013; Kusakabe et al., 2013). Additional processesthat might also have contributed to the observed 137Cs distributionin sediments include resuspension and lateral transport of fine-grained sediments from coastal to offshore regions (Otosaka andKobayashi, 2013) and precipitation via the biological pump(Honda et al., 2012; Buesseler et al., 2012).

Several modeling studies have investigated the spatiotemporalvariation of Fukushima-derived 137Cs in sediments (e.g., Peri�a~nezet al., 2012; Choi et al., 2013). These studies, however, simulated137Cs contamination in sediments only until July 2011, and theycompared the simulated results with observed data only qualita-tively. By September 2011, many new monitoring sites had beenestablished (Fig. 1), and data are now available for a full year afterthe accident (Kusakabe et al., 2013). Moreover, these previousmodeling studies did not take into account the spatial distributionof sediment properties such as grain size, even though sedimentproperties are considered to be a major factor controlling 137Csdistribution in sediments (Otosaka and Kobayashi, 2013; Kusakabeet al., 2013). Incorporation of sediment properties into the modelshould improve simulation of observed data by the model and shedlight on the major factors controlling the 137Cs distribution inseabed sediments.

In this study, we conducted numerical simulations of 137Cs inseabed sediments off the Fukushima coast. We then compared thesimulation results with observed data reported by Kusakabe et al.(2013). We also evaluated the importance of sediment particlesize and bulk density in determining the distribution of 137Cs ac-tivities in sediments. We used the developed model to hindcast thespatiotemporal variation of the 137Cs activities in sediments and toevaluate the total 137Cs inventory in seabed sediments off theFukushima coast.

In Section 2, we explain the model formulation and experi-mental design. We describe the simulated results and compare

Fig. 1. (a) Map of the area around the Fukushima power plant (1F NPP). Ibaraki, Fukushima, ared dashed line show the location of 1F NPP and the sea area within a radius of 30 km of 1shown by crosses (Kusakabe et al., 2013). (c) Median sediment particle diameters, expresse(small black dots; Aoyagi and Igarashi, 1999; Otosaka and Kobayashi, 2013; Ambe et al., sulimeters. Note that smaller f values indicate larger particle diameters. (d) Region masks for cthe “offshore” area, where most of the monitoring stations were located. Green shading sh

them with the observed data in Section 3. We also discuss factorscontrolling 137Cs activities in seabed sediments and summarize theradioactivity contamination process. In the final section, we presentour conclusions.

2. Materials and methods

2.1. Model

We formulated a model simulating 137Cs activities in seabedsediment by simplifying the model presented by Peri�a~nez (2008).We neglected 137Cs transfer by settling particles because cesiumhas a relatively low affinity to biogenic particles (Nyffeler et al.,1984) and the role of that process in the transfer of dissolved ce-sium into sediment is minor (Otosaka and Kato, 2014). Also, we didnot consider burial of 137Cs below the surface mixed layer becausemost monitoring of 137Cs activities in sediments has been restrictedto the surface mixed layer. The prognostic equation for the 137Csactivity in surface sediment is thus written as follows:

dCseddt

¼ k1HrsL

Cwat � k2fCsed � lCsed; (1)

where Csed and Cwat are 137Cs activity in sediment and bottomwater, respectively; k1 and k2 respectively represent kinetic co-efficients for adsorption onto and desorption from sediments; H isthe thickness of the bottom layer of an ocean model; rs is sedimentbulk density; L is the thickness of the sediment mixed layer; 4 is acorrection factor; and l is the decay constant of 137Cs. The kineticcoefficient k1 can be represented as the product of the exchangevelocity c and the exchange surface S (Peri�a~nez, 2008). Assumingspherical particles, k1 for seabed sediments can be expressed as

k1 ¼ cS ¼ c3LRH

fð1� pÞ; (2)

nd Miyagi are prefectures. (b) Simulation region and bathymetry. The red circle and theF NPP, respectively. The locations of the monitoring stations of sedimentary 137Cs ared as Wentworth f values, estimated by interpolation from the available observed databmitted for publication). Here, f≡�log2Dm, where Dm is the median diameter in mil-alculating total inventories of 137Cs in sediments (see Section 3.4): Blue shading showsows the coastal area (water depth < 30 m) and the area within 30 km of 1F NPP.

Table 2Monitoring station locations and sediment properties (Kusakabe et al., 2013).

Latitude (�N) Longitude (�E) Depth (m) rs (kg L�1) w (%) Dm (mm)

A1 38.50 141.83 208 1.70 33.0 0.189B1 38.08 141.26 45 1.94 16.2 0.703C1 37.75 141.26 56 1.86 14.7 0.843D1 37.58 141.37 126 1.51 45.4 0.105E1 37.42 141.37 136 1.51 44.8 0.108F1 37.25 141.37 143 1.59 39.4 0.136G1 37.08 141.25 140 1.44 48.7 0.0920H1 36.92 141.13 134 1.57 41.7 0.123I1 36.75 140.95 99 1.40 52.5 0.0803J1 36.42 140.72 48 1.72 23.9 0.343K1 36.07 140.72 29 1.79 25.5 0.304L1 35.75 140.95 41 1.90 12.2 1.18a1 38.25 141.83 214 1.70 31.6 0.204A3 38.50 142.08 488 1.56 39.9 0.133B3 38.08 141.49 120 1.19 70.6 0.0463C3 37.75 141.49 135 1.76 30.7 0.216D3 37.58 141.60 226 1.69 33.4 0.185E3 37.42 141.61 234 1.66 35.4 0.166E5 37.50 142.00 536 1.65 36.9 0.154F3 37.25 141.61 237 1.64 36.3 0.158G0 37.08 141.14 108 1.41 51.4 0.0833G3 37.07 141.49 212 1.85 27.0 0.274G4 37.00 141.75 667 1.41 53.1 0.0786H3 36.92 141.37 235 1.60 39.5 0.136I0 36.75 140.88 73 1.43 49.4 0.0897I3 36.75 141.18 186 1.86 26.0 0.294J2 36.42 140.95 291 1.52 44.5 0.109J3 36.42 141.07 576 1.24 67.4 0.0505K2 36.07 140.95 210 1.54 42.5 0.118L3 35.75 141.18 167 1.55 43.0 0.116Avg. 1.61 38.6 0.227

Symbols rs and w represent sediment bulk density and water content, respectively,and Dm is the estimated median particle diameter. Values of rs and w are the tem-poral means of the observed data at each monitoring station (Kusakabe et al., 2013),and Dm was estimated as 121 w�1.85 (Equation (6)).

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228220

where R is the radius of the sediment particles and p is sedimentporosity. By substituting Equation (2) into Equation (1), we obtain

dCseddt

¼ c3Rrs

fð1� pÞCwat � k2fCsed � lCsed: (3)

Otosaka and Kobayashi (2013) showed that 137Cs is adsorbedonto both mineral and organic sediment fractions; thus, we sepa-rate Csed into two pools:

dCminseddt

¼ c3Rrs

fð1� pÞfCwat � kmin2 fCmin

sed � lCminsed ; (4)

dCorgseddt

¼ c3Rrs

fð1� pÞð1� f ÞCwat � korg2 fCorgsed � lCorg

sed; (5)

where Cminsed and Corg

sed represent the mineral and organic sedimentfractions, respectively, and f represents the proportion of 137Csadsorbed onto the mineral fraction; we assumed f ¼ 0.8, based onthe observed data (Otosaka and Kobayashi, 2013). Several studieshave pointed out that cesium is strongly adsorbed on interlayersites of clay minerals (Ciffroy et al., 2001; Bostick et al., 2002;Lujanien _e et al., 2005; Qin et al., 2012; Otosaka and Kobayashi,2013). We therefore assumed a slow desorption rate for kmin

2(Table 1); the effective desorption timescale considering thecorrection factor 4 is 1000 days. We assumed a desorption rate anorder of magnitude faster for korg2 (Table 1), supposing reminer-alization of semi-labile organic matter in sediment (Kirchmanet al., 1993; Carlson and Ducklow, 1995; Carlson et al., 2000). Inthe simulations, Cwat was externally set and Cmin

sed and Corgsed were

obtained by solving Equations (4) And (5). Here, we discuss onlytotal 137Cs activity, Csed ¼ Cmin

sed þ Corgsed, because Kusakabe et al.

(2013) report only the total observed 137Cs activity in sedimentsamples.

Kusakabe et al. (2013) reported the sediment bulk density rs andwater contentw data at eachmonitoring station (Table 2). AlthoughKusakabe et al. (2013) did not report sediment particle size, Ambeet al. (unpublished data) showed a strong correlation between themedian particle diameter Dm and the water content w of sedimentssampled off the Fukushima coast (Fig. 2), obtaining the followingregression curve:

Dm ¼ 121w�1:85: (6)

Therefore, we used Equation (6) and w (Table 2) to estimate themedian particle diameter at each monitoring station (Table 2).Thus, the sediment particle radius, R ¼ Dm/2, is used in Equations(4) And (5).

The value of cwas determined from experimental data reportedby Nyffeler et al. (1984). The exchange surface of suspended par-ticles is written as S¼ 3m/Rrs (Peri�a~nez, 2008), wherem represents

Table 1Parameter values used in the model simulations.

Parameter description Value Reference

Exchange velocity c ¼ 35.0 mm day�1 Nyffeler et al. (1984)Correction factor f ¼ 0.01 Peri�a~nez and

Martínez-Aguirre (1997)Proportion of 137Cs

adsorbed onto themineral fractionof the sediment

f ¼ 0.8 Otosaka andKobayashi (2013)

Sediment porosity p ¼ 0.6 Auffret et al. (1974)Remineralization rate korg2 ¼ 1.16 � 10�5 s�1 Peri�a~nez (2008)Desorption kinetic

coefficientkmin2 ¼ 1.16 � 10�6 s�1

Decay constant of 137Cs l¼ln2/30 yr�1 Standard value

the concentration of suspended matter. By substituting thisexpression into Equation (2), we obtain the relationship

c ¼�k1m

�Rrs3

: (7)

Nyffeler et al. (1984) estimated the value k1/m to be140e600 L kg�1 day�1. By using the average particle radiusR ¼ 0.114 mm and the bulk density rs ¼ 1.61 kg L�1 (Table 1), theexchange velocity c can be estimated to range from 8.56 to36.5 mm day�1. For our simulations, we adopted a high-end esti-mate, c ¼ 35.0 mm day�1, because the observed data were betterreproduced when a higher value was used for c. The remainingparameters used in Equations (4) And (5) were obtained frompreviously published studies (see Table 1).

We simulated 137Cs activities in the seabed sediment off theFukushima coast from 1 March 2011 to 29 February 2012 by usingthe simulated 137Cs activities in bottom waters (Cwat) reported byTsumune et al. (2013) and solving Equations (4) And (5). The hor-izontal resolution of both the sediment and ocean models was1 km. Tsumune et al. (2013) used a regional ocean model tosimulate 137Cs activities in seawaters of the region35�540Ne40�000N, 139�540E�147�000E to a maximum ocean depthof 1000 m. Our simulations covered the same region, but werelimited to a depth shallower than 1000 m (Fig. 1b). This area coversall of the monitoring stations used by Kusakabe et al. (2013).

Initial 137Cs activity in the seabed sediment was assumed to be1.0 Bq kg�1 (NRA, 2014). The simulation by Tsumune et al. (2013)contained 137Cs input processes to the ocean from direct release,atmospheric deposition, and inflow from outside the modeldomain. They assumed a scenario for direct release that started on

Fig. 2. Relationship between water content and median particle diameter. The solidcircles represent data observed off the Fukushima coast (Ambe et al., submitted forpublication), and the solid line is a regression curve fitted to the data with Equation(6) (Dm ¼ 121 w�1.85). R2, coefficient of determination.

Table 3Experimental cases.

Case name Sediment parameters (rs and R)

Simulations with station data (STN series)STN_VARYING rs and R in each stationa

STN_CONST Average values (rs ¼ 1.61 kg L�1 and R ¼ 0.114 mm)Hindcast simulations (HIND series)HIND_VARYING rs ¼ 1.61 kg L�1 and R from compiled observed

data (Fig. 1c)HIND_CONST Average values (rs ¼ 1.61 kg L�1 and R ¼ 0.140 mm)

a Parameter values are listed in Table 2. Sediment particle radius Rwas calculatedby dividing Dm by two.

Fig. 3. Relationship between the median particle diameters obtained by interpolationfrom the available observed data and those estimated from the water content by usingEquation (6) (Table 2). The median diameters at stations outside the interpolation areaare excluded. N, number of data; R, correlation coefficient, and RMSE, root mean squareerror.

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228 221

26 March 2011, based on analysis of 131I/137Cs activity ratios(Tsumune et al., 2012). Because the observed 137Cs activities inseawater near the 1F NPP site changed sharply at certain timepoints, different release rate curves were assumed for the followingfour periods: from 26 March to 6 April 2011; from 7 to 26 April2011; from 27 April to 30 June 2011; and from 1 July 2011 to 29February 2012 (Tsumune et al., 2013). The effectiveness of themodel in simulating observed 137Cs activities in seawater is re-ported by Tsumune et al. (2013).

Our model simulations have some limitations. Because weadopted offline simulation, total 137Cs activities in seawater andsediment are not conserved. Further, the model does not contain137Cs transfer via the biological pump or sediment redistributiondue to the resuspension of fine particles and bioturbation. Wediscuss the effects of these limitations on our results in Section 3.

2.2. Experimental design

We conducted two sets of simulations (Table 3). In the first set,the temporal variation of the observed 137Cs activities in sedimentsat eachmonitoring station (Kusakabe et al., 2013) was simulated fortwo cases, called STN_VARYING and STN_CONST. In STN_VARYING,we used the rs and R values at each individual station (listed inTable 2), whereas in STN_CONST, we used constant rs and R values,averaged over all stations.

In the second set, the spatiotemporal variation of 137Cs activitiesin sediments was hindcasted (HIND series; Table 3). In these sim-ulations, the 137Cs activities in sediments in all grids of the simu-lation domain shallower than 1000 m (Fig. 1b) were simulated fortwo cases, HIND_VARYING and HIND_CONST. Because the STN ex-periments revealed that the distribution of sediment particle sizeplayed an important role in determining 137Cs distribution in sed-iments, we compiled observed data on median particle diametersof sediment off the Fukushima coast (Aoyagi and Igarashi, 1999;Otosaka and Kobayashi, 2013; Ambe et al., submitted forpublication) and interpolated them to the model grid using thebilinear method (MATLAB, 2013) (Fig. 1c). Where no data wereavailable, we used the averagemedian diameter calculated using all

the available observed data. We used the resulting data set tocharacterize the sediment distribution off the Fukushima coast(Fig. 1c): the sediments consisted dominantly of sand (�1 < 4 < 4,where 4 is the Wentworth 4 value; Wentworth, 1922); those in thecentral part of Sendai Bay (Fig. 1a) were dominated by coarse sand(4 < 1), whereas very fine sand (4 > 3) was distributed southeast of1F NPP and near the shore in Sendai Bay. The interpolated data arewell consistent with the estimated median diameter at eachmonitoring station (Table 2, Fig. 3). In the HIND_VARYING case, forparameter R in Equations (4) And (5) we divided the median di-ameters displayed in Fig. 1c by two, whereas in the HIND_CONSTcase, we used constant R ¼ 0.140 mm, obtained by averaging thevalues at all grid points. In both HIND_VARYING and HIND_CONST,we assumed a constant bulk density of rs ¼ 1.61 kg L�1.

To evaluate the model's skill in simulating the observed data, wecalculated the modeling efficiency (MEF) (Stow et al., 2009),

MEF ¼ 1�Pn

i¼1ðPi � OiÞ2Pni¼1

�Oi � O

�2; (8)

where n is the number of observations, Oi and Pi are the i th of nobservations and predictions, respectively, and O is the average ofthe observations. The second term of the right-hand side representsthe ratio between the sum of squared residuals and the variance ofthe observations. Consequently, MEF represents the percentage ofthe variance in the observed data that is represented by the model.Mathematically, MEF has the same form as the coefficient of

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228222

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228 223

determination (R2), which is extensively used to measure goodnessof fit for regression models. Kvålseth (1985) pointed out that thismeasure is sensitive to extreme values and proposed an alternativeequation for R2

R2 ¼ 1�8<:

MðjPi � OijÞM���Pi � O

���9=;

2

; (9)

where M represents the sample median. Because of the largescatter of the observed data of the 137Cs activities in sediments, weused Equation (9) to calculate MEF.

3. Results and discussion

3.1. Simulations of station data

Simulated 137Cs activities in the bottom water (Cwat) showedcomplicated short-term variations whose amplitude sometimeschanged by more than an order of magnitude within a few days(Fig. 4). Before September 2011, observed Cwat values were availableonly for station B1. Simulated Cwat at station B1 in this early periodwas consistent with the field data, O(100) Bq m�3, but the temporalvariation was not captured (Fig. 4, B1). After September 2011,simulated Cwat generally decreased at all stations, and the ampli-tudes of the simulated temporal Cwat variations were attenuated.

The simulated Cwat values averaged separately for the shelf andopen ocean depths (<200 m and �200 m, respectively) clearlydepict the general simulated Cwat trend (Fig. 5a and b). In the shelfregion, the simulated Cwat level was O(100) Bq m�3 beforeSeptember 2011, and it decreased exponentially thereafter,declining to O(1) Bq m�3 by one year after the accident. In the openocean region, the simulated Cwat level was O(10) Bq m�3 beforeSeptember 2011 and it subsequently decreased to the same activitylevel, O(1) Bq m�3, as was simulated in the shelf region after oneyear. Point-by-point comparison showed that model-simulatedCwat values were within an order of magnitude of observedvalues, except at station B1 (Fig. 6). At station B1, there was a largedisagreement between the modeled and observed values becausethe model failed to reproduce the temporal variation of Cwat beforeSeptember 2011.

We describe the results of the sediment model by focusing onthe STN_VARYING case. Owing to the slow desorption rate of 137Csfrom sediment assumed in the model, the simulated 137Cs activitiesin sediment (Csed) followed relatively smooth curves, in contrast tothe temporal variations of Cwat (Fig. 4). In the shelf region, wherethe bottomwater was highly contaminated (Fig. 5a), the simulatedCsed increased rapidly to O(100) Bq kg�1 by May 2011 (Fig. 5c), andthat Csed level was maintained subsequently through the entiresimulation period. In the open ocean, the simulated Csed increaseduntil September 2011 (Fig. 5d). The model reproduced the generaltemporal trend seen in the field data, though the simulated Csedlevel in the open ocean region was underestimated by an order ofmagnitude. Point-by-point comparison showed that the simulatedCsed values were within an order of magnitude of the observedvalues (Fig. 7a). The simulated geometric mean of Csed was some-what underestimated (Fig. 7a), but the arithmetic mean corre-sponded well to the average of the observed data (not shown).When the reproducibility of Cwat used as the external forcing is

Fig. 4. Time series of 137Cs activities in the bottom water (Bq m�3) in the simulated (solid li137Cs activities in the sediment (Bq kg�1) in the simulated (dashed lines, STN_VARYING caindicated in the upper right corner of each panel (see Fig. 1b for station locations). The val

taken into account (Fig. 6), the sediment model reproduced theobserved data well.

The correlation between the simulated and observed data inSTN_VARYING was significantly better than that in STN_CONST(p < 0.01), and the root mean square error was lower (Fig. 7). TheMEF values for STN_VARYING and STN_CONST were 0.584 and0.301, respectively; thus, STN_VARYING accounted for ~60% of thevariance in the observed data, whereas STN_CONST accounted foronly ~30%. Introduction of the spatial distributions of sedimentproperties (R and rs) into the model led to a difference in theadsorption rates of 137Cs onto sediment (see Equation (5)), whichimproved themodel skill in simulating the field data. The estimatedmedian sediment particle radius varied by an order of magnitudeamong themonitoring stations, whereas bulk density remained thesame within several tens of percent (Table 2). Thus, the model skillin simulating the observed data was mainly improved by consid-ering the spatial variation of the median radius.

3.2. Hindcast simulations

Simulated Csed in HIND_VARYING reflected the record of the137Cs activities in the overlying bottom water (Fig. 8). Before thedirect release began, 137Cs input derived from atmospheric depo-sition resulted in increases of both Cwat and Csed in the coastal re-gion (Fig. 8a and e). On 10 April, highly contaminated bottomwaterderived from the direct release extended along the coast south of 1FNPP and the northeastern region of 1F NPP (Fig. 8b). However,whereas simulated Csed increased greatly (~O(104) Bq kg�1) in thesouthern coastal region, in the northeastern region it remainedrelatively low (~O(102) Bq kg�1) (Fig. 8f). This contrasting responseis due to differences in sediment particle size, which is fine in thesouthern coastal region but coarse in the northeastern region(Fig. 1c). Comparison of the distributional differences in sedimen-tary 137Cs activities between the HIND_VARYING and HIND_CONSTcases (Fig. 9) with the median sediment diameter distribution(Fig. 1c) highlights the impact of sediment particle size on thesimulated spatial pattern of 137Cs activities in seabed sediments.FromMay to June 2011, waters with high Cwat extended over SendaiBay (Fig. 8c), whereas simulated Csed increased mainly along thecoast of Sendai Bay, where fine-grained sediment dominated(Figs. 8g and 1c). Nearly one year after the accident, simulated Cwat

values were less than 10 Bq m�3 in most of the simulation regionowing to strong mixing by ocean currents (Fig. 8d), whereas thesimulated Csed maintained the levels reached by 1 June 2011(Fig. 8h).

3.3. Factors controlling 137Cs in sediments off the Fukushima coast

Our simple model, which considers only adsorption/desorptionbetween bottom water and sediment, and radioactive decay, suc-cessfully simulated the major features of the observed 137Cs activ-ities in seabed sediments off the Fukushima coast. Radioactivedecay hardly contributed to the results presented here, owing tothe long-half life of 137Cs. Therefore, adsorption/desorption pro-cesses mainly control the spatiotemporal variations of 137Cs activ-ities in sediments. Taking into account sediment properties(especially grain size) at each monitoring station significantlyimproved the model's simulation of the observed data, indicatingthat sediment properties are important influences on the spatialdistribution of 137Cs activities in sediments. Previous observational

nes; Tsumune et al., 2013) and the observed (crosses; Oikawa et al., 2013) data, and ofse) and observed (solid circles; Kusakabe et al., 2013) data. The monitoring station isue to the left of each station designation is the water depth at the station.

Fig. 5. Time series of 137Cs activities in (a, b) bottomwater and (c, d) sediment: (a, c) < 200 mwater depth: (b, d) � 200 mwater depth. Solid lines represent the simulated results ofthe STN_VARYING case. The dashed lines in the bottom panels show the results for the STN_VARYING case, but with a desorption rate smaller by an order of magnitude(kmin

2 ¼1.16 � 10�5 s�1; see Section 3.3). Circles represent 137Cs activities in the observed data averaged over each month. When the number of the data points averaged exceeded five(solid circles), the standard deviations are shown by vertical bars.

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228224

studies have suggested that both 137Cs activities in the overlyingbottomwater and sediment properties are important (Otosaka andKobayashi, 2013; Kusakabe et al., 2013); our model results supportthe conclusions of those studies.

Fig. 6. Scatter plot comparing observed and simulated 137Cs activities in bottomwater.Circles and crosses are data for stations at water depth <200 m and �200 m,respectively. Triangles represent data from station B1, from which observed data wereavailable before September 2011 (See Fig. 4, B1). R and RMSE values are calculated forlog10 of the data.

We assumed a long desorption timescale (1000 days) for themineral sediment fraction on the basis of strong adsorption of 137Csto interlayer sites (Ciffroy et al., 2001; Bostick et al., 2002; Lujanien _eet al., 2005; Qin et al., 2012; Otosaka and Kobayashi, 2013). Whenwe used a desorption timescale an order of magnitude shorter,namely, kmin

2 ¼ korg2 ¼ 1:16� 10�5 s�1, then the simulated 137Csactivities in the sediments decreased in the latter part of thesimulated period (dashed lines in Fig. 5c and d), and the RMSEincreased from 0.570 to 0.747. Consequently, desorption of 137Csfrom sediments is likely small. Our results are consistent with themodel results reported by Peri�a~nez et al. (2012), who found thatincorporation of a slowly reversible 137Cs pool increased the modelskill in simulating observed data.

Precise simulation of the 137Cs activities in bottom waters maynot be necessary to reproduce the 137Cs activities in sediments. The137Cs activities simulated in bottom waters for before September2011 were scattered, and they differed from the observed data bymore than an order of magnitude (Fig. 6, B1). This inconsistencywas caused by the failure of the model to reproduce the observedshort-term temporal variations of the 137Cs activities in bottomwaters at station B1 (Fig. 4). The ocean model likely also failed toreproduce the temporal variations of the 137Cs activities in bottomwaters at the other stations in the first part of the simulationperiod. Despite this limitation of the ocean model, the sedimentmodel successfully simulated the observed data (60% of the vari-ance in the observed data), even including the data observed beforeSeptember 2011 (stations A1, B1, C1, D1, E1, F1, G1, H1, I1, J1, K1, andL1 in Fig. 4; Fig. 7a). This result suggests that, because of the slow

Fig. 7. Scatter plots comparing observed and simulated 137Cs activities in the sediment in (a) STN_VARYING and (b) STN_CONST, respectively. Red and green circles are data fromstations at water depth <200 m and �200 m, respectively. The black circle represents the average of all data of each case, and the cross represents the average when a low-end valuewas used for the exchange velocity (c ¼ 8.56 mm day�1) (see Section 3.3). Average, R, and RMSE values are calculated for log10 of the data. (For interpretation of the references tocolour in this figure legend, the reader is referred to the web version of this article).

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228 225

sorption/desorption timescale, the simulated temporal variation of137Cs activities in sediments is smoothed relative to that in theoverlying bottomwater. Therefore, it is not necessary to simulate indetail the short-term variations of 137Cs activities in the bottomwater.

Our model systematically underestimated the 137Cs activities insediments of the open ocean region (Fig. 7), although this bias wassomewhat ameliorated by the introduction of sediment propertydifferences into the model. Because the simulated 137Cs activities inbottom waters did not show a corresponding systematic underes-timation (Fig. 6), processes that are not considered in our simula-tion might be responsible for this underestimation. Otosaka andKobayashi (2013) suggested that lateral transport of fine particlesfrom the coast to offshore regions likely redistributes 137Cs insediments. The finding that the simulated 137Cs activities in sedi-ments of the shelf region were roughly an order of magnitudehigher than those simulated in sediments of the open ocean regionsuggests that lateral transport of high 137Cs-bearing sedimentparticles from the coast to the offshore region would result in anincrease of 137Cs activities in sediments of the open ocean regionand reduce the model bias.

By referring to the experimental data reported by Nyffeler et al.(1984), we estimated the exchange velocity of sediments off theFukushima coast to be c ¼ 8.56e36.5 mm day�1, and adopted ahigh-end value for the exchange velocity in the model(c ¼ 35.0 mm day�1; Table 1) because it enabled the model toreproduce better the observed 137Cs activity level in sediments(Fig. 7a; black filled circle). Use of a low-end value for the exchangevelocity (c ¼ 8.56 mm day�1) caused the simulated 137Cs activitylevel in sediments to decrease by a factor of four (Fig. 7a; blackcross). The high optimal c value may indicate an influence ofsediment resuspension caused by the tsunami. When sedimentsare resuspended, the exchange surface S (see Equation (2)) be-comes larger than that under normal conditions. Thus, the use of ahigh-end value for the exchange velocity may compensate for un-derestimation of the exchange surface.

We simulated 137Cs activities in the surface mixed layer(defined as the uppermost 3 cm of sediment), fromwhere most ofthe available observational data were obtained. Recent observa-tional studies providing detailed vertical profiles of cesium ac-tivities in sediments after the 1F NPP accident have revealed that

they extend to deeper than 3 cm (Otosaka and Kato, 2014; Ambeet al., submitted for publication), particularly near the coast.Ambe et al., submitted for publication provided three possiblemechanisms for the transfer of radiocesium into these deeperlayers: 1) resuspension and redeposition by ocean waves andbottom currents, 2) downward penetration via pore water, and 3)bioturbation. We cannot assess the relative importance of thesemechanisms because our model does not consider verticaltransport of 137Cs in sedimentary layers. Future studies should usea model that includes vertical transfer of radiocesium in sedi-mentary layers.

Because the model successfully simulated the spatiotemporalvariation of 137Cs in sediment without considering the effect of thebiological pump, it is likely that the transfer of 137Cs from seawaterto sediments by the biological pump plays at most a minor role indetermining the total 137Cs activities in sediments off the Fukush-ima coast. This is also consistent with an estimate based onobserved data (Otosaka and Kato, 2014). It is noteworthy, however,that 137Cs transfer by the biological pump may play an importantrole in determining 137Cs activities in the organic fraction ofsediments.

Buesseler et al. (2012) and Tateda et al. (2013) reported thatcontaminated seabed sediments are a possible source of continuedcontamination of benthic fish. Our results suggest that the influenceon benthic fish of 137Cs desorbed from sediments is small becauseour model employing a low desorption rate simulated well theobserved 137Cs activities in sediments. Although the contribution ofthe organic fraction to total 137Cs activity in sediments off Ibarakiwasrelatively small (roughly 20%; Otosaka and Kobayashi, 2013), 137Csmay be transferred from the organic sediment fraction, which has ahigh 137Cs content per unit mass (Otosaka and Kobayashi, 2013), toorganisms through the food chain (Tateda et al., 2013). To clarifywhether or not organically bound 137Cs in sediment is an importantsource of radioactive contamination of marine organisms, a sensi-tivity analysis should be performed with a model that incorporates137Cs transfer processes, including sedimentebiota transfer. Toinvestigate the collective dose rate in the fish catch due to theirconsumption of marine products, it is important to simulate theopen ocean region, because the fish catch integrated over the openocean region is larger than that integrated over the coastal regionnear 1F NPP, where 137Cs activity is higher (Maderich et al., 2014).

Fig. 8. Spatial distributions of simulated 137Cs activities in (aed) the bottom water and (eeh) the sediment in HIND_VARYING. Time advances from left to right, and dates aredisplayed at the top of each column. The location of the Fukushima Daiichi Nuclear Power Plant is denoted by cross mark.

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228226

3.4. Spatiotemporal variation of 137Cs in sediments after theaccident

Our hindcast simulations yielded insights into the spatiotem-poral variation of 137Cs activity in sediments off the Fukushimacoast after the accident. Initially, 137Cs derived from atmosphericdeposition contaminated coastal sediments, though at the rela-tively low level of O(10) Bq kg�1. After direct release began, thesediments recorded the history that water highly contaminatedwith radiocesium passed over the sediments. The grain-size dis-tribution of the sediments off the Fukushima coast can explain thelarge-scale spatial pattern of the 137Cs activities in the sediments.Our model simulation projected particularly high 137Cs activities insediments in the coastal region south of 1F NPP and along the coast

of Sendai Bay. The large-scale spatial distribution of 137Cs in sedi-ments was established during the first several months after theaccident, and the 137Cs activity level hardly changed subsequently.

Our model simulation results also allow estimation of the total137Cs inventory in sediments off the Fukushima coast. Assuming asediment mixed layer depth of 3 cm and using an average sedimentbulk density rs ¼ 1.61 kg L�1, we calculated a conversion factor toconvert the activity in a unit mass of sediment to a unit area(48.3 kg m�2). By multiplying the simulated 137Cs activities in thesediments (Fig. 8) by this conversion factor and integrating thevalues over the offshore area (21,498 km2; the blue area in Fig. 1d),where all of the monitoring stations except station K1were located,we obtained total 137Cs inventory values in the sediments(HIND_VARYING offshore in Fig. 10) that varied temporally in a very

Fig. 9. Spatial distributions of the difference in simulated sedimentary 137Cs activities between HIND_VARYING and HIND_CONST.

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228 227

similar manner to those estimated for a region of similar size(22,177 km2) by using the observed data of Kusakabe et al. (2013)(solid circles in Fig. 10).

Our hindcast simulations showed higher 137Cs activities insediments in some areas, especially in the coastal area and near thepower plant (Fig. 8). When the higher 137Cs activities in sedimentsof these areas are taken into account, the estimated total 137Cs in-ventory in sediments of the whole region (the sum of the green andblue areas in Fig. 1d; 25,032 km2) is O(0.1) PBq. This value is severaltimes that in the offshore region alone (HIND_VARYING whole vs.offshore; Fig. 10). Further observations of the 137Cs activities in

Fig. 10. Time series of the total 137Cs inventory in sediments integrated over the areasdefined in Fig. 1d. Thick and thin lines represent the inventories of the HIND_VARYINGand HIND_CONST cases, respectively. Solid and dashed lines represent the inventoriesintegrated over the offshore area (blue shaded area in Fig. 1d) and the whole area (thesum of the green and blue shaded areas in Fig. 1d), respectively. Black solid circlesrepresent the total inventories of 137Cs in sediments estimated from the observed data(Kusakabe et al., 2013).

sediments, especially in the coastal area and in the vicinity of thepower plant are therefore desirable to obtain a better estimate ofthe total 137Cs inventory in sediments off the Fukushima coast.

The simulated total 137Cs inventories in the VARYING cases wereseveral tens of percent higher than those in the CONST cases, eventhough the average sediment particle size was the same for both(Fig. 10). This result means that water highly contaminated withradiocesium preferentially passed through regions with finergrained sediments, which raised the total 137Cs inventory in thesediments.

Because we used an offline simulation method, the sum of thetotal 137Cs inventories in seawater and sediment was increased bythe total 137Cs inventory in sediment. As the simulated total 137Csinventory in sediment was only about 10% of the simulated 137Csinventory in seawater (Tsumune et al., 2013), the model bias causedby the use of the offline method was at most 10% of the simulatedresult. Thus, our general conclusions remain valid.

4. Conclusion

We conducted numerical simulations of 137Cs in sediments offthe Fukushima coast by using a model that incorporated adsorp-tion/desorption processes of 137Cs to/from sediments and radioac-tive decay. Themodel successfully reproduced themajor features ofobserved spatiotemporal variation of 137Cs activities in sediments.We found that adequate simulation of the 137Cs activity level in theoverlying bottom water and consideration of sediment propertieswere essential for simulating the spatiotemporal variation of 137Csactivities in sediments, but that it was not necessary to simulate indetail the short-term temporal variations of 137Cs activity in theoverlying bottom water, owing to the long desorption timescale insediment. In offshore regions, it may be important to considerlateral transport of fine sediments from the coast to offshore. Thebroad-scale distribution of 137Cs activities in sediments wasestablished during the first several months after the accident, andthe level of 137Cs activity changed little afterward. Relatively high

K. Misumi et al. / Journal of Environmental Radioactivity 136 (2014) 218e228228

137Cs activities remained in sediments in the coastal region south of1F NPP and along the coast of Sendai Bay even one year after theaccident. Our model indicated a total 137Cs inventory off theFukushima coast on the order of 1014 Bq one year after the accident.To better quantify the 137Cs inventory in sediments, investigation ofvertical profiles of 137Cs activity in the sediment column at variouslocations is essential. A sensitivity analysis using a model that in-cludes sedimentebiota transfer processes is necessary to under-stand the role of sediment as a source of contamination of marineorganisms.

Acknowledgments

This paper has benefited from insightful comments from H.Kutsukake (IDEA Consultants, Inc.), D. Ambe and T. Ono (FisheriesResearch Agency, Japan), M. Kusakabe (Marine Ecology ResearchInstitute), and S. Otosaka (Japan Atomic Energy Agency). We thankF. Taguchi and R. Niwa (Denryoku Computing Center) and T. Chuda(MRI Research Associates) for technical support.

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