Development of an analytical method for estimating three-dimensional

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Development of an analytical method for estimating three-dimensional distribution of sediment-associated radiocesium at a reservoir bottom KOTARO OCHI, Yoshimi Urabe, Tsutomu Yamada, and Yukihisa Sanada Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b01746 • Publication Date (Web): 17 Aug 2018 Downloaded from http://pubs.acs.org on August 18, 2018

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Development of an analytical method for estimating three-dimensional distribution of sediment-associated radiocesium at a reservoir bottom Kotaro Ochi, *, † Yoshimi Urabe,‡ Tsutomu Yamada,§ and Yukihisa Sanada† †

Fukushima Environmental Safety Center, Japan Atomic Energy Agency, 45-169, Sukakeba, Kaibama-aza, Haramachi, Minamisoma, Fukushima 975-0036, Japan ‡ NESI Inc., 1-9-3, Saku-machi, Taira-aza, Iwaki, Fukushima 970-8026, Japan § Japan Radiation Engineering Co., Ltd, 1-5-20, Sakuragawa-cho, Hitachi, Ibaraki 316-0002, Japan ABSTRACT: After the Fukushima Daiichi Nuclear Power Station accident, the distributions of sediment-associated radiocesium were investigated to evaluate the dispersion and accumulation of radiocesium in the reservoir field. To develop an analytical method for measuring the horizontal and vertical distributions of radiocesium on a wide scale, we obtained 253 gamma-ray spectra at the bottoms of 64 ponds in Fukushima during 2014–2016 by using a NaI(Tl) scintillation detector. For visualizing horizontal distribution, correlation between detector counting rate and radiocesium concentration of the bottom sediment was confirmed. In estimating vertical distribution, the depth profile of sediment-associated radiocesium was found to be correlated to the intensities of scattered and photo peaks. Good agreement was observed between the results of in situ spectrometry and core sampling. These results indicate that the developed method is suitable for understanding the behavior of radiocesium and determining whether decontamination of reservoirs is required.

Large amounts of radiocesium (134Cs and 137Cs) were released into the atmosphere after the Fukushima Daiichi Nuclear Power Station (FDNPS) accident. This radiocesium was deposited onto the ground in Eastern Japan.1 In Fukushima prefecture, the area northwest of the FDNPS was highly contaminated by radiocesium deposition.2-3 The air dose rate around the river line decreased after hydraulic flushing of soil-associated radiocesium and other decontamination efforts.4 However, the accumulation of sediment-associated radiocesium was reported in the reservoir fields, such as dams, lakes, and ponds. To address these concerns, these fields are considered for decontamination in accordance with the criterion of “specified radioactive waste,” which is more than 8000 Bq kg-1 of radiocesium concentration.5 It is quite difficult to demonstrate the effectiveness of decontamination efforts because the affected areas are large. An easy and rapid method for estimating the distribution of sedimentassociated radiocesium would help determine whether radiocesium decontamination is required. In Fukushima prefecture, more than 3500 reservoir fields supply water for agriculture and drinking. In addition, reservoir fields play a role in reducing sediment fluxes downstream.6 The behavior of radiocesium in reservoirs was investigated in the coastal region (Hama-dori), which is in the eastern part of Fukushima prefecture. It is estimated that radiocesium is stable because it binds to the inner sphere of clay minerals in soil.7-9 Yoshimura et al.10 investigated soil erosion for various cases of land use to estimate the migration of radiocesium into rivers. Fan et al.11 indicated that river sediment has high fixation ability to 137Cs. Under rainy conditions, temporal increase in radiocesium activity in river water has been observed owing to

inflowing contaminated riverside soil.12-15 After rainfall, the radiocesium in catchments has been found to be transported downstream.16-19 Through these processes, sediment-associated radiocesium can accumulate in reservoir fields. Continuous monitoring of sediment-associated radiocesium has been performed in several fixed reservoirs to quantify the rate of decrease in its activity.20-21 Moreover, the activity of sediment-associated radiocesium in various reservoirs has been examined to evaluate the deposition record of radiocesium and reservoir trapping efficiency.22-24 Model simulations have been developed for long-term investigation of sediment-associated radiocesium in the targeted water environment, along with actual monitoring data.25-28 The results predicted by a few simulations were compared to actual measurement results to validate the models. These horizontal distributions of sediment-associated radiocesium have been used to understand the process of radiocesium transport from upper catchments to downstream locations over time. Vertical distribution of sediment-associated radiocesium was investigated to quantify the downward transport of radiocesium with sediment disturbance.29-32 Collection of core sediment samples is a common technique for investigating the deposition record as a function of time. These distributions of radiocesium were found to be highly affected by reservoir use, sediment characteristics, and amount of radiocesium. It is crucial to estimate the three-dimensional distribution of radiocesium at the reservoir bottom to better understand the behavior of radiocesium after deposition. The present study focuses on the detailed distribution of radiocesium in a selected reservoir, despite difficulties associated with the collection and analysis of sediment.


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125°E

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Deposition of radiocesium (kBq m-2) 3000 < 1000 - 3000 600 - 1000 300 - 600 100 - 300 60 - 100 30 - 60 10 - 30 < 10 Sampling point × FDNPS

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Figure 1. Location of the study site in Fukushima prefecture in Eastern Japan. Measurement points are shown as black circles (64 ponds). The distribution map of radiocesium deposition was created by aerial radiation monitoring data.

Plastic scintillation fibers are good tools for determining the position of radionuclide hotspots on the surface of sediment in a line pattern.23 It cannot distinguish the pulse of radiocesium from that of other nuclides because this approach does not measure and identify gamma-ray spectra. In situ spectrometry is suitable for estimating the activity of each nuclide in environmental samples by measuring the intensity of each peak. We have developed a waterproof scintillation detector that is available for in situ measurement of sediment-associated radiocesium concentration.23 For estimating the vertical distribution of radiocesium, the peak-to-vary (PTV) method is generally used to estimate the position of the radiation source from the surface ground by examining the ratio of the photo peak counting rate to the vicinity valley peak counting rate.33-35 Tyler et al. 33 investigated the vertical distribution of 137Cs in salt marsh environment using a NaI(Tl) detector. We developed an analytical method for aerial radiation monitoring (ARM) method based on the characteristics of gamma-ray spectra to estimate the vertical distribution of radiocesium in soil.36 In the present study, we developed an analytical method for estimating three-dimensional distribution of sediment-associated radiocesium at reservoir bottoms without collecting core sediment. To confirm the validity of the obtained in situ result, core sediments were collected in parallel. In this paper, we discuss the three-dimensional distribution of sediment-associated radiocesium based on the interpolation map, which is created based on the relationship between the result of in situ measurement and core sampling.

on the ending date of ARM, that is, Nov. 7, 2014. Sixty-four ponds, that were located in the residential area, were selected for study. In situ measurement. In situ measurements were performed at the bottom of the ponds by using a waterproof NaI(Tl) scintillation detector (Hitachi Ltd., Tokyo, Japan). The detector is shown in Figure 2. The NaI(Tl) crystal is a 2-cm cube. A depletion space exists between the detector and the bottom of the device. The distance from the center of the detector to the bottom of the device is 6 cm. A bell-like box is installed under the detector for moderating radiation attenuation by water. The diameter of bottom face of device is 25 cm. The tipping angle is set at 33° for stable measurement. The total mass of the device is approximately 11 kg. The outer shield comprises a stainless plate. The tube connector is a pressure-resistant structure. Figure 3a shows an image of how measurements are taken, and Figure 3b shows a schematic diagram of the apparatus. Measurement points were determined based on the position of core collection points by using a Real-Time Kinematic Global Positioning System (Hiper-V, TOPCON Co., Tokyo, Japan). We selected the data of the points at which the distance of

15.0 cm

b) Tube Connector a)

Handle 1 cmΦ Eyebolt

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EXPERIMENTAL SECTION

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Study site. To select a study site in the highly contaminated area, ARM data37 were used to create an interpolation map of the total radiocesium deposition on the surface ground. The study site was plotted on the radiocesium deposition distribution map obtained based on ARM, as shown in Figure 1. The map was created using a mapping software (ArcGIS, ESRI Japan Co., Tokyo, Japan) and an inverse distance weighted method. Decay correction of radiocesium was performed based

5.0 cm

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


25.0 cmΦ

Figure 2. The composition of the in situ NaI(Tl) scintillation detector. a) Image of the device, b) Reduced scale of each parts.



b) Battery

1002 10

Box for data collection PC

Figure 3. The image of the in situ measurement. a) Image of measurement, b) Image of measurement system.

the measurement point of the in situ detector from the core collection point was within 1 m. The reference station was settled on land near the measurement point. All measurements were performed in a grid pattern, except for the outer edges of the ponds, where the measurement conditions were unstable. The pulse height distribution was measured every second for 120 s. The counting rate data were transferred from the detector to a personal computer through a metal cable. Gamma-ray spectrum data were obtained in CSV format. The detector was powered with a 12 V battery that lasts for approximately 6 h. These devices, which were placed on a boat, were used to record measurements while floating over each point. Sample Collection. From 2014 to 2016, we collected 253 core sediments by using a HR type core sampler (Cat. 5172, RIGO Co., Tokyo, Japan) by settling based on weight of core sampler. Approximately three sediment cores were collected from each pond. Core samples were divided into 5 cm layers and transferred into a cylindrical polystyrene bottle (U8, Sekiya Rika Co., Ltd., Tokyo, Japan). The external diameter of the vessel was 5 cm, and its height was 6.8 cm. Radiocesium concentration of radiocesium in samples were measured using a HPGe detector (SEG-EMS, SEICO EG&G Co., Ltd., Tokyo, Japan). We determined the activity concentration of 134Cs and 137Cs based on the intensity of gamma-rays as 606 and 662 keV, respectively. The measurement time was varied depending on the activity of the sample. Because all samples were not all obtained at the same time, decay correction of the activity was performed. Analytical schema for conversion from counting rate to radiocesium concentration. The net counting rates of 134Cs and 137Cs of the in situ gamma-ray spectra were calculated using the Covell method.38 Analytical schemas of the Covell method are shown in Figure 4. The baseline of each peak is shown as a colored line. This method is a typical approach for calculating the net counting rates of gamma-rays, which are then used to evaluate the intensities of radionuclides accurately. The net counting rate of 134Cs at 796 keV was calculated within an energy range of 745–845 keV. The background of this peak was set to 730–745 and 845–860 keV and is shown as a blue box in Figure 4. The net counting rate of 137Cs at 662 keV was calculated by subtracting the net counting rate of 134Cs at 605 keV from the sum of the net counting rate in the energy range of 550–725 keV. The net counting rate of 134Cs at 605 keV was calculated based on the contribution ratio of the photo peak of 134 Cs at 605 keV to that at 796 keV based on the source test result. The background of this peak was set to 530–550 and 725–745 keV, and it and shown by a red box in Figure 4. To investigate the horizontal distribution of radiocesium at the bottom of a pond, we calculated the conversion factor from the net counting rate of radiocesium to the radiocesium concentration in surface sediment. The relationships between the net counting

134Cs+137Cs

Counting rate (cps)

a)

1010 134Cs

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0.1-1 10 500

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650 700 750 Energy (keV)

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Figure 4. Analytical schema of the calculation of net counting rate of radiocesium on gamma-ray spectrum using the Covell method. 60 60

Net counting rate (cps)

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50 50 40 40

250 250

[134Cs] y = 0.0172 x r = 0.98 n = 17

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[137R² Cs] = 0.9641 y = 0.0153 x r = 0.98 n = 17

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00

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Figure 5. Relationship between the net counting rate of radiocesium and actual radiocesium concentration in surface sediment (0–10 cm).

rate of radiocesium, as measured by the in situ detector, and the average radiocesium concentration in surface sediment (0–10 cm), as measured by the HPGe detector in the laboratory, are shown in Figure 5. We selected 17 data points to highlight that uniform radiocesium distribution in surface sediment (0–10 cm) was observed in core sediment. The range of average water contents of these sediment samples (0–10 cm) was 60.2 % (Min: 43.0 %, Max: 82.4 %). The conversion factors (CF) (cps (Bq kg-1)-1) were calculated based on the slope of the approximation formula obtained from the above-mentioned relationship (134Cs: 0.0172 and 137Cs: 0.0153). The length of the core samples was 10–40 cm. We calculated the average radiocesium concentration in the surface sediment (0–10 cm) as a criterion for decontamination work. Good correlations were observed between the two radionuclides. The activity concentration of 134Cs in surface sediment was found to be lower than that of 137Cs because of its shorter half-life. To confirm the validity of the estimated result, relative deviation (R. D.) of the estimated radiocesium concentration measured by the in situ detector to radiocesium concentration in the core sediment was calculated as follows: 𝑅. 𝐷. = (𝐴𝑐𝐸 − 𝐴𝑐𝑀 ) / 𝐴𝑐𝑀 , (1) where AcE is estimated radiocesium concentration based on net counting rate, and AcM is radiocesium concentration based on core sediment. Analytical schema of gamma-ray spectra. Contribution of direct gamma-rays from radiocesium to scattered gamma-rays


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is large when radiocesium exists in surface sediment. By contrast, the contribution of scattered gamma-rays is higher than that of direct gamma-rays when radiocesium exists at a greater depth in sediment. A schematic of our method is shown in Figure 6. The gamma-ray spectrum was divided into two sections (scattered peak and photo peak) with three patterns (A, B and C), as shown in Fig. 7. First, the detection efficiency of each count with energy was calculated by using a radiation source 152 Eu (Eu402, Japan Radioisotope Association, Tokyo, Japan) to unify this method. From source test result, detection efficiency below 100 keV was found to be low. In all of three patterns, we defined the photo peak as 550–850 keV. The range of the scattered peak was varied to discuss about the effects of 134 Cs decay. In pattern A, we defined the scattered peak as 100–500 keV because we fully considered the effect of the Compton scattered gamma-rays. In pattern B, we defined the scattered peak as 100–200 keV due to avoid the influence of the minor gammaenergy of 134Cs (233, 243, 327, and 475 keV). In pattern C, we defined the scattered peak as 150–250 keV to evaluate the influence of the minor gamma-energy of 134Cs (233 and 243 keV). Each estimated pattern was compared to establish an effective analytical schema. To quantify the variations of these contributions, we calculated the ratio of sums of counting rate in scattered peak to that in photo peak (RPC) as follows: 120

120

𝑖=1

(2)

where Cs is the counting rate of scattered peak, and Cp is the counting rate of photo peak. We calculated the sum of each counting rate for 120 s. In this method, the value of RPC

: Direct gamma-ray : Scattered gamma-ray Radiocesium concentration High

Low

Figure 6. Image of the variation of contribution of gamma-ray. with position of radiation source. A) 100-500 keV

B) 100-200 keV

Scattered gamma-ray

0

∞

𝐷 = ∫0 𝐴𝑚,0,𝑒𝑓𝑓 exp (−

𝜁 𝛽𝑒𝑓𝑓

) 𝐼𝛾 𝐶(𝜁)dζ ,

(3)

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changes with the abundance ratio of 134Cs and 137Cs because the 134 Cs peak overlaps in scattered energy range of the 137Cs. To address these concerns, we focus on the variations in the intensity of the photo and scattered peaks as a function of the position of radiocesium in the sediment from 3 to 5 years after the FDNPS accident. During the measurement period, the rate of increase in the value of RPC was found to be lower than 1% from the result of preliminary calculation using the Monte Carlo simulation. Relaxation mass depth. To quantify the vertical distribution of radiocesium in core sediment, we used a distribution parameter called relaxation mass depth, β.39 Relaxation mass depth is the depth at which the concentration of radiocesium concentration decreases to 1/e of the radiocesium concentration at the surface. In general, the radiocesium concentration decreases exponentially with soil depth. It is suitable to quantify the vertical distribution of radiocesium in soil in accordance with soil characteristics, such as water content and soil density. However, the vertical distribution of radiocesium was affected by inversion tillage and presence of wild animals in the land field.36,39 To cope with these situations, Matsuda et al.39 proposed a distribution parameter, effective relaxation mass depth, βeff. βeff is calculated as follows:

𝑧

𝑅𝑃𝐶 = ∑ ∑ 𝐶𝑠𝑖 / ∑ ∑ 𝐶𝑝𝑖 ,

Log relative counting rate (cps)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


550-850 keV Direct gamma-ray

𝐴𝑖𝑛𝑣. = 𝛽𝑒𝑓𝑓 𝐴𝑚,0,𝑒𝑓𝑓 ,

(5)

where D is the air kerma rate at 1 m above surface soil (μGy h1 ), Am, 0, eff is the effective radiocesium concentration (wet weight) in surface soil (Bq kg-1), ζ is the relaxation mass depth (g cm-2), Iγ is the branching ratio of gamma ray from each nuclide, C(ζ) is the conversion factor proposed by Saito40, z’ is the depth from surface soil (cm), ρ is the soil density (g cm-3), and Ainv. is the measured inventory (Bq m-2).36,39 We determined the soil density based on the mass (wet weight) and volume of each layer of sediment sample. It was not possible to collect core samples from layers containing rocks. Two hundred thirty-five data points were selected to estimate the validity of our method. To discuss about the uncertainty associated with our method, 34 data points were selected from the entire dataset, wherein the radiocesium concentration in deeper layers was below the detection limit for evaluating total radiocesium inventory in core sediment. Mapping. To confirm the effectiveness of this measurement technique, distribution of radiocesium concentration and effective relaxation mass depth in two ponds in Fukushima prefecture were measured. Measurements were conducted at 30 and 42 points, respectively, in Ara-ike (Koriyama, Ikenodai) and Zenpo-ike (Koriyama, Fukuyama-machi), which are in an urban area, by using a waterproof NaI(Tl) scintillation detector. Total measurement times in these two ponds were approximately 60 and 84 min., respectively. Mapping was performed by supplementing unmeasured areas via an interpolation of the measured results. Methods such as the Kriging and the spline approaches have been proposed as interpolation methods. The

100 200 300 400 500 600 700 800 900 Energy (keV)

Figure 7. Gamma-ray spectrum with dividing into two sections.



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Frequency : 134Cs Cumulative frequency : 134Cs

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Figure 8. Accuracy of the estimated radiocesium concentration in surface sediment (0–10 cm) compared with the result of core sampling.

1.0 1

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0.5 y = 0.174 x – 0.127 0.5 r = 0.56 n = 235 00 00 5 6 7 9 10 2 5 6 7 88 9 10 2 RPC 2 2 2.0 2.0 RPC a)-2 b)-2 b)-2

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c)-2

33 RPC

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: Upper prediction interval 95% : Upper confidence interval 95% : Regression line : Lower confidence interval 95% : Lower prediction interval 95%

y = 0.849 x – 1.39 r = 0.83 n = 34

33 RPC RPC

4 4

Figure 9. Relationship between βeff and RPC in three calculation methods. a) Pattern A (scattered peak, 100-500 keV), b) Pattern B (scattered peak, 100-200 keV) and c) Pattern C (scattered peak, 150-250 keV), 1) Entire dataset, 2) Selected dataset wherein the radiocesium concentration in deeper layers was below the detection limit.

Kriging approach provides an estimate of a variable at an unobserved location based on the weighted average of observed values at neighboring sites within a given area. The interpolation error can be evaluated by a semivariogram. In this study, the spatial resolution of the contour maps was 5 m. The properties of these two ponds are shown in Figure 10. The surface area of the pond and catchment were calculated using ArcGIS in the selected mesh. The water depth in Ara-ike and Zenpo-ike were measured at 413 and 233 points, respectively on the sampling date. The water volume of each pond was calculated based on the surface area and the average water depth.

RESULTS AND DISCUSSION Horizontal distribution of sediment-associated radiocesium. To confirm the validity of our estimates, we compared the accuracy to the actual measurement result (253 data), as shown in Figure 8. Because the average and median R. D. of the estimates compared to the actual measurements were nearly zero, it can be concluded that both CFs of radiocesium incorporated well-fit parameters, respectively. The cumulative frequency of the R. D. exhibited approximately 15% bias toward larger. With this method, it was possible to evaluate the


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radiocesium concentration of the bottom sediment with an uncertainty of approximately 40% in terms of standard deviation, as shown in Figure 8. In the present study, in calibration of the in situ detector, radiocesium concentration was assumed to be homogeneous at depths of 0–10 cm from the surface sediment, and water content was assumed to be 60.2 %, as explained in section “Analytical schema for conversion from counting rate to radiocesium concentration”. As shown in Figure 8, factors of the numerical unevenness were 1) to deviate from assumption of the depth profile of radiocesium and water content, 2) are not consistent between in situ detector and sediment, and 3) inconsistent with measurement location of in situ detector and sediment sample collection location. Vertical distribution of sediment-associated radiocesium. The relationships between βeff and RPC for Pattern A, B and C peaks are shown in Figure 9 using the entire dataset (235 data) and a selected part of the dataset by sediment sampling situation (34 data). These graphs are on the logarithm axis. These plots were drawn by applying linear approximation by the least squares method to the data. To confirm the validity of our method, 95% of the confidence and prediction intervals calculated using a statistical software R were plotted. The βeff of the bottom of sediment (4.5–52.8 g cm-2) was higher than that of the soil condition. On land, the β value was 0.65–7.57 g cm-2 in 2016.41 This method was effective to estimate the vertical profile of radiocesium in the sediment because all scatter diagrams showed strong positive correlations. The correlation coefficient of the approximation formula between βeff and RPC over the

Measurement point Inlet Outlet Surface area of pond: 1.7×104 m2 Water depth: 1.2-3.0 m Water volume: 3.4×104 m3 Water system: Abukuma River Surface area of catchment: 9.5×105 m2

a)-2 N a)-2 a)-2

entire dataset in Figure 9 is smaller than that in selected dataset. This indicates that the value of RPC increased when radiocesium was highly distributed in deeper layers below the collecting depth. In the case of pattern A in the selected dataset, the slope of the formula is smaller than that in the cases of patterns B and C. In pattern A, the Compton scattered gamma-rays were fully considered. In the high dose area, the minor peak of 134Cs (233, 243, 327 and 475 keV) was detected on the lower end of the energy of spectrum (100–500 keV). In the case of pattern B, the slope calculated using the equation and the correlation coefficient are lower than those in the case of pattern C. It can evaluate the vertical distribution of radiocesium in the sediment over the long-term by using pattern B because the photo peak of 134Cs is not included the range of scattered gamma-rays. The correlation coefficient of pattern C was higher than that of patterns A and B, and the former’s RPC of pattern C exhibited a stronger logarithmic dependence on βeff. This indicates that the characteristics of the gamma-ray spectra strongly influence the actual vertical distributions of sediment-associated radiocesium in pattern C. It is estimated that it is possible to use each pattern depending on their appropriateness for a given scenario. We determined a conversion factor from RPC to βeff to create an interpolation map of the estimated βeff. Pattern C was selected to interpolate the value of βeff because the correlation coefficient of the equation between βeff vs. RPC is higher than that in the cases of the other patterns. Application of radiocesium distribution map. Figure 10 shows two interpolation maps: the radiocesium concentration and effective relaxation mass depth calculated using the approximation formula in Figures 5 and 9 (pattern C). In situ measurement was performed on a grid pattern over the entire area of the

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Measurement point Inlet Outlet Surface area: 4.7×104 m2 Water depth: 0.2-1.8 m Water volume: 4.1×104 m3 Water system: Abukuma River and Atago River Surface area of catchment: 1.2×106 m2 b)-1

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0

50 100 150 200

Radiocesium concentration (0-10 cm) (Bq kg-1) 10000 9500 9000 8500 8000 7500 7000 6500 6000 5500 5000 4500 4000 3500 3000

Effective relaxation mass depth (g cm-2) 50 45 40 35 30 25 20 15 10 5 0

m

Figure 10. Interpolation map of radiocesium concentration in surface sediment (0–10 cm) and effective relaxation mass depth. a) Araike, b) Zenpo-ike, 1) Geographical situation of pond, 2) Radiocesium concentration (0–10 cm), 3) Effective relaxation mass depth.



pond. From Figure 10, the impacts of the FDNPS accident were observed in the two ponds because Ochi et al. 9 reported that the activity concentration of 137Cs in the soil before the FDNPS accident in Kanto region was approximately 9.0 Bq kg-1. Ochiai et al.20 was reported to temporal changes in sedimentation flux of radiocesium after the accident by investigating the contribution of the impact of the FDNPS accident in Western Japan. In our results, radiocesium distribution on the surface sediment was found to have been decreased after the accident owing to water run off process. To estimate the initial inventory of radiocesium (β42): 0.1–3 g cm-2) virtually, the average inventory of radiocesium (0–10 cm) in the two ponds was calculated using the following equations: 𝐴𝑖𝑛𝑣 = 𝐷𝑝 𝜌𝑎𝑣 ∑ 𝐴𝑐𝐸 ,

(6)

where Ainv. is the estimated average inventory of radiocesium (0–10 cm), Dp is depth of sediment collection (10 cm), ρav is average soil density of sediment (0–10 cm) (g cm-3), and AcE is estimated radiocesium concentration (0–10 cm) in selected mesh (Bq kg-1). The surface area in the selected meshes in Araike and Zenpo-ike were 1.7 and 4.7×104 m2, respectively. Four and five sediment cores were collected in Ara-ike and Zenpoike. The average soil density (wet) in the surface sediments (0– 10 cm) collected from Ara-ike and Zenpo-ike were 1.24 and 1.35 g cm-3, respectively. The sum of AcE in all meshes in Araike and Zenpo-ike were 6.4 and 9.0 MBq kg-1. The average radiocesium inventories (0–10 cm) in Ara-ike and Zenpo-ike were 0.80 and 1.2 GBq m-2. The horizontal and vertical distributions of sediment-associated radiocesium are necessary for calculating the radiocesium inventory in the reservoir field. These results indicated that our method would be evaluation method for comparing the spread status of radiocesium in various reservoirs. Our method would be helpful for evaluating the radiocesium inventory over time by varying the selected sediment depth. In Ara-ike, the radiocesium concentration in the western area was found to be higher than that in the eastern area. It is estimated that radiocesium was transported from the watershed to this site by water discharge. Field observations indicated the presence of many water plants in the west side. These plants could have helped reduce sedimentation flux downstream. Distribution of the effective relaxation mass depth indicated that the sediment disturbance mainly occurred on the western side. Sediment was found to be highly mixed with water in heavy rain conditions such as typhoons. In addition, horizontal transport of sediment-associated radiocesium would have been prohibited by the water plants on the western side. In Zenpo-ike, the radiocesium concentration in surface sediment was found to be lower than that in Ara-ike. However, according to the ARM result, the radiocesium deposition in Zenpo-ike is nearly equivalent to that in Ara-ike. This discrepancy can be ascribed to differences in the geographical features of each pond. Because there are three inlets in Zenpo-ike, it is indicated that sedimentassociated radiocesium was transported by water discharge more quickly compared to that in the case of Ara-ike. This is supported by field observations indicating a lack of water plants. On the eastern side, accumulation of sediment-associated radiocesium was observed. In a nearby outlet, the radiocesium concentration in the sediment was low because of water discharge. Heterogeneous vertical distribution of sediment-associated radiocesium was observed in the entire area without water plants. Because inlet water flows into the pond via three paths, the

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sediment transport process is complex. At the nearby southwest inlet, radiocesium was found to have migrated to a deeper layer of sediment layer. By contrast, water discharge from other inlets caused radiocesium to migrate mainly out of the middle layer of the sediment in the nearby north inlet. Owing to these strong water discharge currents, radiocesium migrated to a deeper sediment layer on the eastern side. It is necessary to understand that the radiocesium concentration in surface sediment can increase owing to migration from deeper layers after heavy rain. For precise decontamination work, the effective relaxation mass depth is an important parameter in addition to the surface radiocesium concentration.

CONCLUSIONS We estimated the three-dimensional distribution of sedimentassociated radiocesium in ponds by measuring gamma-ray spectra in the horizontal and vertical directions. Good agreement was observed between the characteristics of measured gamma-ray spectra and the results of core sampling. From the interpolation map of the distribution of sediment-associated radiocesium, variations in these distributions were visually observed with water runoff. The present analytical schema would be a good approach for understanding the behavior of cesium and determining whether decontamination work is necessary in a water environment. Future work could involve using the present analytical method to measure three-dimensional distributions of sediment-associated radiocesium in other reservoirs.

AUTHOR INFORMATION Corresponding Author * E-mail: [email protected]. Tel: +81-244-25-2072. Fax: +81-244-24-2011

ORCID Kotaro Ochi: 0000-0002-3753-9718

Author Contributions The manuscript was written through contributions of all authors.

Notes The authors declare no competing financial interest.

ACKNOWLEDGMENT The authors thank member of Midori net, OYO Corporation, Japan Radiation Engineering Corporation, NESI Corporation and Japan Atomic Energy Agency with measuring gamma-ray spectra and collecting sediment samples. We gratefully acknowledge their cooperation.

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A

B

C

D

In situ detector Cs conc. High

Low

Peak identification

Counting rate (cps)

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66 55

Scattered gamma-ray

Direct gamma-ray

:D :C :B :A

44 33 22 11 00 0

200 200

400 600 800 400 600 800 Energy (keV)

1000 1000

How radiocesium distribute in the bottom of reservoir?


9

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Figure 1. Location of the study site in Fukushima prefecture in Eastern Japan. Measurement points are shown as black circles (64 ponds). The distribution map of radiocesium deposition was created by aerial radiation monitoring data. 338x190mm (300 x 300 DPI)



Figure 2. The composition of the in situ NaI(Tl) scintillation detector. a) Image of the device, b) Reduced scale of each parts. 338x190mm (300 x 300 DPI)


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Figure 3. The image of the in situ measurement. a) Image of measurement, b) Image of measurement system. 338x190mm (300 x 300 DPI)



Figure 4. Analytical schema of the calculation of net counting rate of radiocesium on gamma-ray spectrum using the Covell method. 338x190mm (300 x 300 DPI)


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Figure 5. Relationship between the net counting rate of radioce-sium and actual radiocesium concentration in surface sediment (0–10 cm). 338x190mm (300 x 300 DPI)



Figure 6. Image of the variation of contribution of gamma-ray. 338x190mm (300 x 300 DPI)


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Figure 7. Gamma-ray spectrum with dividing into two sections. 338x190mm (300 x 300 DPI)



Figure 8. Accuracy of the estimated radiocesium concentration in surface sediment (0–10 cm) compared with the result of core sampling. 338x190mm (300 x 300 DPI)


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Figure 9. Relationship between βeff and RPC in three calculation methods. a) Pattern A (scattered peak, 100-500 keV), b) Pattern B (scat-tered peak, 100-200 keV) and c) Pattern C (scattered peak, 150-250 keV), 1) Entire dataset, 2) Selected dataset wherein the radiocesium concentration in deeper layers was below the detection limit. 338x190mm (300 x 300 DPI)



Figure 10. Interpolation map of radiocesium concentration in surface sediment (0–10 cm) and effective relaxation mass depth. a) Ara-ike, b) Zenpo-ike, 1) Geographical situation of pond, 2) Radiocesium concentration (0–10 cm), 3) Effective relaxation mass depth. 338x190mm (300 x 300 DPI)


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Development of an analytical method for estimating three-dimensional

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