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ArticleAnalysis of Groundwater Flows under the Fukushima Daiichi
Nuclear Power Plant Reactors Using Contaminated Water from 42
Subdrain Pits
Tamao Tanji, Makoto Furukawa, Seiji Taguma, Katsushige Fujimoto, Hikaru Sato, Naoaki Shibasaki,
and Yoshitaka Takagai*

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sı Supporting Information*

ABSTRACT: We analyzed groundwater collected from 42 subdrainpits (wells) located around the reactor buildings of plant units #1 to #4of the Tokyo Electric Power Company Fukushima Daiichi Nuclear
Power Plant (F1-NPP) to understand the groundwater dynamics andwater flows around F1-NPP. Since water samples collected from thissmall area exhibit very similar water quality, there are difficulties inunderstanding the flow dynamics of the groundwater using conventional
chemical analyses. In this study, we clarified the groundwater flows using
an altitude-modified principal component analysis (PCA) with a total of
798 data items (19 factors × 42 pits) in the chemical analyses. The PCA
results showed that six specific pits deviated from the common values
and that the others contained contributions from both the naturalelements and radioactive nuclides. The groundwater flows under units#1−#4 into two flow lines originating from two main water sources were classified, and these lines merged around the bayside of unit
#2 due to the lower groundwater head. This method proved suitable for elucidating the groundwater dynamics and water flows inthis small area by the proposed altitude-modified PCA.
KEYWORDS: groundwater analysis, multichemical components, principal component analysis, Fukushima Daiichi Nuclear Power Plant■

INTRODUCTION
Understanding groundwater dynamics and water flows is very
important for predicting future issues related to contaminationof water so that suitable measures can be implemented inadvance and/or for taking effective actions in advance toalleviate undesired future issues like discharging contaminatedwater into the ocean. However, it is not easy to understand thegroundwater dynamics and flows in a small area because of thesmall differences in the chemical species and their concentrations (i.e., the water quality) obtained using conventional
chemical analyses.
The Tokyo Electric Power Company (TEPCO) Fukushima
Daiichi Nuclear Power Plant (F1-NPP) were damaged in 2011,
and the area of the site covers only 3.5 square km. There are 42
subdrain pits (wells) around reactor buildings of units #1−#4.
The role of the pits is to control water levels, and samplingfrom the pits and monitoring of the radioactivity concentration
have been conducted regularly since the accident.1,2 Oddly
enough, the hotspots that contain contaminated water (in thesubdrain pits) are scattered all over the site, and it has beendifficult to find any continuities or relationships between thecontaminated locations and the groundwater flows from theresults of the radioactivity analyses. So far, hydrological© 2022 American Chemical Society

research has been performed only for groundwater flows thatspan large areas around the F1-NPP like a unit of stratum
across counties3 or neighboring prefectures;4 however, theanalytical data from the subdrain pits in the site have neverbeen connected to their radioactivity. If characteristic
constituents, such as molybdenum,5 arsenic,6 and highconcentrations of silicates,7 are eluted into the groundwaterand if the distribution of the concentration gradients of theseions can be detected, analyses of the flows or dynamics would
be relatively understandable. However, since the chemical
properties of even stable isotopes are very similar in such asmall area, it is difficult to find the differences. Although many
researchers are aware of the importance of such discrimination,
understanding the dynamics of groundwater flows for a small
area remains challenging.
Received: September 15, 2022
Revised: November 19, 2022
Accepted: November 21, 2022
Published: December 8, 2022

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Article■EXPERIMENTAL SECTION
Apparatus. NexION 300S ICP-MS (PerkinElmer, Inc.,
Shelton, CT) equipped with a dynamic reaction cell (DRC)and a quartz baffled cyclonic spray chamber with a concentric
nebulizer was used. We employed ultrapure argon (Ar) gas(>99.999%) for the Ar plasma and helium (He) gas(>99.999%) as the collision/reaction gas to remove mass
spectral interference. The kinetic energy discrimination(KED)14 mode in the DRC was employed, and the resultant
concentrations were obtained without the influence ofinterference.
Reagents and Preparation. We prepared mixture
solutions of 15 elements by mixing Multielement Calibration
Standard series #2, #3, #4, and #5 as the standard stock
solutions for the metal-ion mixtures (stable isotopes withconcentrations of 10 mg/L; PerkinElmer). We also used
ultrapure concentrated HNO3 (ultrapure-grade, 61 w/w %;Kanto Chemical Co., Inc., Tokyo, Japan) and perfluoroalkoxy
alkane (PFA) bottles and containers (AS-ONE Co. TokyoJapan). We obtained ultrapure water (18.2 MΩ·cm) from a
PURELAB Ultra purifier (ELGA, Bucks, U.K.).
Sampling and Sample Preparation. Groundwater
samples collected from 42 subdrain pits around reactor
buildings of units #1−#4 of F1-NPP during 2016 were used.
The samples were stored at temperatures below 4 °C. We
performed the sample treatments and measurements in a hot
lab inside F1-NPP.
Figure 2A shows a map with the geomorphological locations.
The sampling locations are shown as a map of the wells in
Figure 2B. In addition, Table S1 in the Supporting Information
provides other information about the samples, such as the
sampling date, type of well,15 and grid data. There are three
types of subdrain pits in F1-NPP. One is a normal type ofsingle well; the second also is a normal type, but it is connected
to neighboring wells; and the third is much deeper than anormal type of single well.
The concentrations of radioactive 3H, 134Cs, 137Cs, andGross β were measured by TEPCO, and we measured thesame samples again using the ICP-MS method to quantify theisotopes. Table 1 shows the input data for 3H, 134Cs, 137Cs, andGross β radioactivity, which were provided by TEPCO. [Note:
Based on legal regulations, the numerical data for theradioactivity concentrations were publicly press-released inadvance via the TEPCO website.2 For the Gross β radioactivity, the radioactivity might be influenced by the detection
efficiency of individual radionuclides (e.g., energy region).
Hirayama previously reported the analysis of Gross β values in
the methods of TEPCO from the viewpoints of thedependence for radionuclides to get a detector response, andthe actual activity of 134Cs contributed 66% values to the valuesof Gross β.16] We converted the radioactivity concentration(Bq L−1) to mass concentration (g L−1) using eq 1

To classify water quality, researchers commonly use a hexadiagram method. In this method, the ion equivalents for six orseven typical chemical species are plotted as a hexa-diagram (asshown in Figure 1). The water quality can then be recognizedvisually from the shape of the diagram, which depends on theconcentrations of the typical species.8

Figure 1. Typical hexa-diagram characterization method for environmental water.

While a hexa-diagram is advantageous when there are great
differences in its shape (i.e., for the case with typical differencesin water quality), it is not easy to detect differences in the
shape of the diagram visually for water samples collected fromvery closely spaced locations that have almost the same water
quality. Even if we add more variables to the diagram, thisdifficulty in discrimination basically does not change. Thus, theconventional hexa-diagram method is fundamentally not able
to elucidate the analysis of water dynamics or the flows in asmall area, even when many data from various chemical
analyses are provided.
Principal component analysis (PCA)9 is a typical method for
multivariate analyses, and it is used in combination withchemical analyses in many fields, including authenticity
determination,10 origin determination,11 and bioinformatics.12
While a plethora of reports have been published concerning
the combination of PCA and chemical analyses, mostapplications to inorganic analysis commonly use quantitative
data for a few elements focusing on the target (e.g., somepollutants or their isotope ratios in the natural elements aremainly used).13 This differs from bioinformatics, in which
there are certain regularities in the pairings�such as aminoacid or base sequences in DNA�that make it easy to apply to
informatic analysis. In contrast, there is no literature
concerning applications to the analysis of groundwater
dynamics using large amounts of data that contain many
chemical components from many sampling locations; consequently, the abovementioned hexa-diagram method has beencommonly used as a traditional method. The PCA can reducemany variables into a smaller number of derived variables that
may be readily visualized in two- or three-dimensional space.
In this study, we measured the concentrations of 15 isotopes
and 3 anthropogenic radionuclides and Gross β radioactivity ingroundwater samples obtained from 42 subdrain pits aroundreactor buildings of units #1−#4 of F1-NPP during 2016 using
inductively coupled plasma mass spectrometry (ICP-MS) andradioactivity analysis. We analyzed the resulting 798 data items
using both a normal PCA and a modified PCA thatincorporated elevations. We used this approach to clarify thegroundwater dynamics and flows under the F1-NPPs, which
are all located in a small area.

ij t1/2M yz
z/V
C = jjjA
j ln 2N zzz
A{
k

(1)

where C is the mass concentration of the target nuclide (gL−1), A is the radioactivity (Bq), t1/2 is the half-life of thenuclide (s), M is the mass number of the target nuclide, NA is
Avogadro’s number, and V is the sample volume (L).
In addition, Gross β is pure β-particle emission, which might
be contributed from mainly 134Cs, 137Cs, 90Sr (t1/2 = 28.8 y),
and its daughter nuclide 90Y (t1/2 = 64 h, 100% β-emitter).17
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ArticleFigure 2. Map and overview of the Fukushima Daiichi Nuclear Power Plant (F1-NPP). [A] Overview of F1-NPP showing its geomorphologicalsetting. The aerial photograph provided by the Geospatial Information Authority of Japan (GSI). [B] Locations of the subdrain pits (wells). The
assigned pit numbers correspond to those given in the official announcement reported by the Japanese government and TEPCO.18 The blue, green,
yellow, and red dots represent the pits belonging to reactor buildings of units #1, 2, 3, and 4, respectively. The red lines are horizontal pipes
connected to each pit.

[Note: U and Th did not impact on PCA due to their lower
concentration and even inclusion in all samples.]Data Analysis. For the data analysis, the information ofconcentrations of alkali metal elements, alkaline earth metalelements, and the elements up to the third period in the
periodic table (Li, Be, B, Mg, Ti, Cr, Mn, Ni, Cu, Ga, As, Rb,
Sr, Cs, Ba) was obtained using ICP-MS, and the factors wereselected from reliable data, which shows that the concentrations were certainly quantified using calibration curves withgood linearity of the correlation coefficient of 0.975 or higher
and using values over the limits of detection (LODs). The dataof the anthropogenic radionuclides (3H, 134Cs, 137Cs) and
Gross β radioactivity in the sample water collected from
subdrain pits presented by TEPCO were used. We thus
inputted 19 factors to the PCA as the dataset (15 isotopes and3 anthropogenic radionuclides and Gross β radioactivity)
obtained from each of 42 sampling points; i.e., 798 data items.
We performed the PCA using the computer software
analytics platform TIBCO Spotfire (Palo Alto, CA). For thedata analysis, we standardized the mean and the variance of thequantitative values for each isotope as 0 and 1, respectively.

■

RESULTS AND DISCUSSION
Simultaneous Multielement Quantification. Table S2in the Supporting Information shows the concentrations of 15
elements measured using ICP-MS in the contaminated waterfrom 42 subdrain pits. To perform this quantification, we usedcalibration curves with correlation coefficients of at least 0.975.
This table also shows the LOD for each element. To avoid MS
spectral interference, we employed the KED mode using He
gas. 14 The interferences were not confirmed in thequantification. In the PCA, we did not use any of the data
for those elements with concentrations below their respective
LODs.
Principal Component Analysis (PCA). Table 2 shows the
PCA loading values for 19 factors from 42 sampling points.
The contributions from the 1st, 2nd, and 3rd principal

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Table 2. Loadingsa

Table 1. Input Data of the Concentration of Anthropogenic
Radionuclides and Gross β Radioactivity1,3loadings

radioactivity/Bq L−1
subdrainpit # 2

3

1
2
8
9
18
19
20
21
22
23
24
25
26
27
31
32
33
34
40
45
51
52
53
55
56
58
59
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215

26,00011,000<LOD(120)
770
290
510
740
<LOD(110)
190
160
240
130
<LOD(120)<LOD(110)<LOD(120)<LOD(110)<LOD(120)
170
270<LOD(100)<LOD(100)<LOD(130)<LOD(130)<LOD(130)150<LOD(130)150<LOD(120)<LOD(120)<LOD(120)<LOD(120)<LOD(120)<LOD(110)<LOD(110)<LOD(110)<LOD(110)<LOD(100)<LOD(100)<LOD(100)<LOD(100)
400<LOD(130)elements

comp. 1comp. 2comp. 3

Cs
134
Cs
63
Cu
7
Li
11
B
69
Ga
gross β
25
Mg
85
Rb
138
Ba
48
Ti
75
As
55
Mn
88
Sr
52
Cr
9
Be
58
Ni
133
Cs
3
H
contributing factor rate, %cumulative contribution factor rates, %

0.21
0.20
0.14
0.13
0.12
0.11
0.11
0.10
0.09
0.09
0.07
0.02
0.01
−0.02
−0.04
−0.13
−0.50
−0.52
−0.52
16.70
16.70

−0.34
−0.34
−0.23
0.39
−0.18
0.44
−0.20
−0.04
0.02
0.45
−0.02
0.09
0.23
−0.14
−0.04
−0.04
−0.05
−0.04
−0.04
13.77
30.47

0.42
0.41
0.08
0.23
0.09
0.37
0.24
0.02
−0.04
0.37
−0.24
−0.14
−0.17
−0.14
−0.10
−0.01
0.19
0.20
0.20
12.59
43.06

137

H

134

Cs

11
<LOD(3.6)
14<LOD(4.3)
190
130<LOD(5.6)<LOD(4.8)
6.6
77
45
61
11
21
12
<LOD(5.9)
7.0
27
210
<LOD(4.1)<LOD(3.5)<LOD(8.9)<LOD(9.3)<LOD(10.0)<LOD(4.1)<LOD(10.0)<LOD(3.5)<LOD(5.8)<LOD(4.6)<LOD(5.6)<LOD(4.3)<LOD(4.7)<LOD(6.9)<LOD(4.4)<LOD(4.4)<LOD(3.6)<LOD(3.9)<LOD(4.2)<LOD(3.7)<LOD(4.5)<LOD(4.4)<LOD(11)137

Csgross β

75
4.3
83
18
1200
850
<LOD(4.4)
14
44
460
270
400
88
150
92
<LOD(6.4)
27
180
1300
<LOD(4.3)<LOD(5.0)<LOD(15)<LOD(18)<LOD(16)<LOD(5.2)
18
6.7<LOD(5.2)<LOD(4.4)<LOD(5.6)
5.9<LOD(3.8)
15<LOD(5.4)<LOD(3.8)<LOD(4.9)
3.6
16<LOD(3.9)<LOD(3.4)
8.0<LOD(14)83<LOD(11)
82
20
1400
970
17
14
36
1100
350
600
130
250
250
<LOD(12)
44
190
1500
<LOD(12)<LOD(12)<LOD(18)<LOD(11)<LOD(11)<LOD(10)<LOD(12)<LOD(15)<LOD(10)<LOD(10)<LOD(10)21<LOD(10)20
17<LOD(12)<LOD(13)<LOD(12)54<LOD(12)12
15<LOD(18)

Articlea

The loadings are shown in descending order of the first principal
components.

tions lower than 40% were reported.19−21 These values(<40%) were reported even in wide-area investigations.
Compared with these values, our value of 43.06% is entirely
satisfactory for our small-area investigation.
Figure 3 shows a plot of the principal component scores foreach subdrain pit. Since the subdrain pits are located adjacent1

The data presented by the Tokyo Electronic Power Company
Holding Ltd 2. 2Identification numbers of the subdrain pits
corresponding to the number on the map in Figure 2B. 3<LOD:
the value is less than the limit of detection (LOD). The values inparentheses are LOD.

Figure 3. PCA score plot in subdrain waters of F1-NPP. The blue,
green, yellow, and red colored points represent the subdrain pits
around reactor buildings of units #1, #2, #3, and #4 (cf., the map in
Figure 2B). [Attention] The plot size is not related to any factors. Allplots are the same size; however, the different sizes of plots dependingon the perspective may be seen.

components are listed as Comp. 1, Comp. 2, and Comp. 3, andthey were 16.70, 13.77, and 12.59%, respectively. The increasesof the radioactivity concentration contributed to the positive
value of Comp. 1 and also the negative value of Comp. 2. The
isotopes originated from the environment contributed to thenegative way of Comp. 3. The cumulative contributions fromthese three principal components totaled 43.06%. In previous
applications that used PCA to identify various organic
substances for environmental analysis, cumulative contribu-

to each reactor building, the plots are color-coded for eachbuilding. For 36 of the 42 subdrain pits, the main contribution
to the PCA score came from Comp. 1. It is considered thatComp. 1 indicates the similarity of groundwater.
For pits #1, #2, #18, #19, #34, and #40, the PCA score plots
were obviously different from those of other samples. Fromthese PCA results, pits #1, #2, #18, #19, #34, and #40 wereplotted out of the main population mostly due to142

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anthropogenic radionuclides and Gross β radioactivity. Figure
S2 in the Supporting Information shows the result of
hierarchical cluster analysis; however, it was difficult to identify
groundwater flows. The six pits (#1, #2, #18, #19, #34, and#40) were classified as the category of high radioactivity
concentrations by the hierarchical cluster analysis; however, it
was obvious before the PCA. At the F1-NPP site, three types ofsubdrain pits exist, as noted before; they are normal single
wells, normal wells that are connected to neighbor wells, anddeeper wells. The PCA scores show that there is noapprehension with these types of wells, as shown in Figure
S3 in the Supporting Information. In addition, Figure S4 in the
Supporting Information shows that the plotted points areroughly correlated with the reactor buildings (that is, by color),
according to the scores of the first three principal components.
Although the climate often impacts the quality of groundwater,22,23 the sampling date did not influence the results ofscores as shown in Figure S5 in the Supporting Information.
PCA Including Environmental Considerations.
Although we identified specific elements that contributed to
the PCA score, the connections between PCA and thecontinuity of fluid flows with each pit were not clear in thatanalysis (cf. Figure 4 and Table 2). However, the PCA
approach was able to distinguish two regions between units #1
and 2 and units #3 and 4. This is reasonable because thereactor buildings and turbine buildings of unit #1 and unit #2
are architecturally connected buildings, and they are built on
the same stratum. Similarly, units #3 and #4 are alsoarchitecturally connected buildings, and they are separated
from the building containing units #1 and 2 (cf. Figure 2A). In
addition, Figure S4 in the Supporting information shows thescore plots that have similar trends between units 1 and 2 aswell as between units 3 and 4. Meanwhile, the groundwaterflows continuously in the higher (water level) to lower
direction.24 Based on this natural order, we recalculated the
PCA results after adding a new absolute variable into theprevious PCA. Figure 4 shows the modified plot of principal
component scores after adding an axis for direction. There
have been no reports to date concerning PCA thatincorporates absolute values such as elevation as one of theaxes of the PCA score plot. Figure 4A shows the connectedbuilding for units #1 and #2, and Figure 4B shows theconnected building for units #3 and #4. The clusters ofprincipal component scores capture the characteristics of theslight changes in each connected building. This confirms thetendency of water to flow continuously from a higher altitude(i.e., mountain side) to a lower altitude (i.e., sea side). Notably,
two continuous flows are obviously confirmed. It is clear fromthe consideration of loading that the difference in water quality
can be found in Comp. 3.
Figure 4C shows a map of the classification of groundwaterflows specified by the PCA score values and altitude (using
data from Figure 4A,B). We had expected a simple flow passing
from the mountain side (west side) to the sea side (east side)and basically the simple flow was observed; however, contrary
to our expectations, we actually found the following two
different types of flows (as shown in Figure 4C). Namely, inthe condition of the pits, which corresponded to the value ofComp. 3, the water-flow orders basically following the blue
arrows were exhibited, which were formed based on theelevations, as shown in Figure 4A,B. Finally, the two flows are
merged around pits [#25/#33]. There appear to be two main
origins of groundwater flows from the mountain side to the

ArticleFigure 4. PCA score plots in subdrain waters collected around eachbuilding. [A] Connected buildings for units #1 and 2, [B] theconnected buildings for units #3 and 4, and [C] groundwater flows
presented by this study. The plotted colors correspond to grid datameasured from the west side. See text for explanations of the flows
indicated by the blue arrows. The red-border pits are determined to
be stagnant from the results of PCA. [Attention] The plot size is not
related to any factors. All plots are the same size; however, thedifferent sizes of plots depending on the perspective may be seen.

reactors. Groundwater flows from the northwest (pits #203−#207) and the other flows from the west−southwest (pits #45
and #209−#213), and flows in the case of these latter pits are
considered to have the same origin. It may be necessary toinvestigate the west side of the reactors to confirm thishypothesis; however, it has not been investigated in this study.
We also investigated pits #1, #2, #18, #19, #34, and #40,
which were significantly different from other pits in the PCA.
Pits #1 and #2 showed high concentrations of radioactivity andexhibited great differences not only from the properties ofadjacent pits around units 1 and 2 but also from those of theother pits in the PCA classification. These results show thatgroundwater on pits #1 and #2 barely flows. Highly radioactive
water samples contaminated by 3H exist in pits #1 and #2;
however, no impact on other pits was found (cf. Table S1 in
the Supporting Information).
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Articlerespectively.25,26 The lowest level of T.P. is around unit #2.
Figure 5B shows an east−west cross section (a slice containing
unit #3). The groundwater head slopes drastically from themountain side (west side) to the sea side (east side), and thereis 450 m from unit #3 to the sea. These facts show that the
groundwater basically flows from the mountain side (westside) to the sea side (east side). Since T.P. for unit #2 is lower
than that for any of the other units (north−south), and theslope of the groundwater head is steeper (west−east), it isobvious that the groundwater gathers easily around unit #2.
These hydrogeological considerations support the PCA results
obtained in this study, which show that each groundwater flow
congregates around pits #25/#33.
At the F1-NPP site, TEPCO built seaside impermeable walls(the wall is composed of 594 steel pipe sheet piles driven into
the earth across a width of about 780 m) in October 2015 as acountermeasure to prevent the inflow of contaminated waterfrom the surroundings into the sea.27,28 For pits #58−59 (asshown in Figure 4C), the drastic change in the direction of thewater flow is probably due to the blocking by this wall,29 whichchanges the direction of migration of the water toward thelower groundwater head of unit #2.

Although pits #207 and #208 were not almost contaminatedby radioactive nuclides, we classified them with pits #18 and#19, which showed quite high concentrations of radioactive
Cs. We consider that the groundwater from pits #207 and#208, which is supplied from the mountain side, merges withthe highly contaminated water from pits #18 and #19.
Therefore, pits #18 and #19 were affected more intensely bycontamination from the reactor than from the minerals thatoriginated from the groundwater. For pits #18, #19, #34, and#40, other PCA trials were conducted (i.e., substituting thevalues of the radioactivity concentration to other different
values obtained from adjacent pits around unit building [#18
and #19 were for units 1 and 2; #34 and #40 were for units 3
and 4]). As a result, the waters of those pits were revealed asoriginating from the same source as other pits around each
unit; however, the high concentration of the radionuclides was
suggested to be stagnated into these pits by the results of the
PCA score. Namely, a possibility is considered that groundwater is flowing into those pits but not flowing out from thosepits.
Geological Validity. Among all 42 subdrain pits, themajority�38 pits�are 12−16 m deep. The other four pits are
40 m deep wells. Figure 5 shows cross sections around the F1NPP together with the groundwater heads. In Figure 5, T.P.
meters is the annual mean sea level values of Tokyo. Figure 5A
shows a north−south cross section, with T.P. = 6.5, 5.0, 5.9,
and 6.5 m for bottom of units #1, #2, #3, and #4,■

CONCLUSIONSIn conclusion, it is difficult to specify groundwater flows thatoriginate from the same stratum in a small area using theconcentrations of various chemical components and water
qualities (e.g., the use of a hexa-diagram). For F1-NPP,
contaminated pits exist randomly, and the water quality due tothe mineral content is very similar due to very close proximityof the sampling points. Consequently, the significance ofcontinuous flows of groundwater and water dynamics was notpreviously recognized. This study successfully clarified theflows of groundwater below the small 3.5 square km site of F1NPP using a modified PCA with a total of 798 data items (19factors × 42 pits) obtained using ICP-MS and radioactivity
analysis. The PCA showed that six specific pits were different
from others. The score plots and their loadings led to theidentification of contributing factors that originated fromgeology rather than from radioactive materials. We discussed
these 6 pits individually. Contrary to our expectations, thePCA revealed two groundwater flows and two origins of thegroundwater (from the northwest and from the west−
southwest). We found that groundwater for those 6 pits (#1,
#2, #18, #19, #34, and #40) is stagnant, and the active flows ofeach pit are analyzed. In addition, two major flows migrate in
the direction of unit #2 (i.e., pits #25/#33). For flow units 3
and 4, the seaside impermeable wall built in October 2015 may
prevent the flow of the contaminated water from leaking into
the ocean; it changed the direction of water migration toward
the direction of units #3−#4, which has a lower level of T.P.
These results are consistent with the geological considerations.
In 2022, the concentrations of Gross β in seawater (at thebay entrance in front of units #1−#4) were about 10−30 Bq
L−1 (LOD: 8.7 Bq L−1).31 This suggests that it may be difficult
to prevent completely a large amount of groundwater that
contains a small amount of radioactive nuclides such as 3Hfrom leaking into the ocean. At present (2022), thecircumstances of F1-NPP regarding groundwater may bedifferent from the results obtained in this study because ofboth the decommissioning of F1-NPP and a variety ofcountermeasures to prevent rainwater and groundwater fromflowing into the buildings. However, it is important to know

Figure 5. Cross sections of the simulated groundwater heads as of 11
March 2011.30 [A] North−south and [B] west−east.
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Author Contributions

the original underground flows at the site as an archival
reference. In particular, this study has demonstrated theexistence of groundwater flows using water samples collectedfrom closely spaced sampling points. In addition, our results
enable the visualization and estimation of the circumstances ofgroundwater. For environmental analyses, this method
provides an effective means for the visual recognition of slightdifferences in chemical components at levels that are different
to recognize by other methods. In addition, knowing the
migration patterns of groundwater not only enables predictionsof the migration of pollutants but also enables an understanding of the dynamic nature of such flows.

■

T.T.: Method setup, investigation, and writing paper draft.
M.F.: ICP-MS analysis, investigation of PCA, and discussion.
S.T: analysis of radioactivity concentration in Fukushima NPP.
K.F: discussion and analysis of PCA analysis. H.S and N.S:
discussion and drawing in local geology. Y.T.: conceptualization, supervision, and project administration. CRediT: Tamao
Tanji formal analysis (lead), investigation (equal), methodology (equal), writing-original draft (lead); Makoto Furukawa
formal analysis (equal), investigation (equal), methodology(equal); Seiji Taguma formal analysis (equal); Katsushige
Fujimoto data curation (equal), validation (equal); Hikaru
Sato data curation (equal), software (equal); Naoaki
Shibasaki data curation (equal), investigation (equal),
software (equal); Yoshitaka Takagai conceptualization(lead), data curation (equal), funding acquisition (lead),
investigation (equal), methodology (lead), project administration (lead), supervision (lead), validation (lead), writingoriginal draft (equal), writing-review & editing (lead).

ASSOCIATED CONTENT* Supporting Information
sı

The Supporting Information is available free of charge athttps://pubs.acs.org/doi/10.1021/acsestwater.2c00455.
Information of sampling waters (Table S1); element
concentrations of subdrain pits (Table S2); diagrams ofthe 32 factors for subdrain water (Figure S1); dendrogram of the hierarchical clustering for subdrain water(Figure S2); PCA score plot for subdrain waters (FigureS3); PCA score plot of subdrain waters in each building(Figure S4); and PCA score plot of subdrain waters foreach sampling date (Figure S5) (PDF)■

ArticleNotes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS■

REFERENCES

The authors gratefully acknowledge funding by the JAEA
Nuclear Energy S&T and Human Resource Development
Project through concentrating wisdom Grant Number
JPJA19H19210081 and the Japan Society for the Promotionof Science (JSPS) Grant-in-Aid for Scientific Research (B)20H04352.

AUTHOR INFORMATION

Corresponding Author

Yoshitaka Takagai − Faculty of Symbiotic Systems Science,
Cluster of Science and Technology, Fukushima University,
Fukushima 960-1296, Japan; Institute of Environmental
Radioactivity, Fukushima University, Fukushima 960-1296,
Japan; orcid.org/0000-0002-7760-5636; Email: s015@
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Authors

Tamao Tanji − Faculty of Symbiotic Systems Science, Clusterof Science and Technology, Fukushima University, Fukushima
960-1296, Japan
Makoto Furukawa − Faculty of Symbiotic Systems Science,
Cluster of Science and Technology, Fukushima University,
Fukushima 960-1296, Japan; PerkinElmer Japan Co., Ltd.,
Yokohama, Kanagawa 240-0005, Japan
Seiji Taguma − Tokyo Power Technology Ltd., Ohkuma,
Fukushima 979-1305, Japan
Katsushige Fujimoto − Faculty of Symbiotic Systems Science,
Cluster of Science and Technology, Fukushima University,
Fukushima 960-1296, Japan
Hikaru Sato − Faculty of Symbiotic Systems Science, Cluster of
Science and Technology, Fukushima University, Fukushima
960-1296, Japan; Present Address: Faculty of Life andEnvironmental Sciences, University of Tsukuba, Ibaraki
305-8572, Japan
Naoaki Shibasaki − Faculty of Symbiotic Systems Science,
Cluster of Science and Technology, Fukushima University,
Fukushima 960-1296, Japan; Institute of Environmental
Radioactivity, Fukushima University, Fukushima 960-1296,
Japan; orcid.org/0000-0001-5213-2994
Complete contact information is available at:https://pubs.acs.org/10.1021/acsestwater.2c00455
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