Assessmentof Environmental
Radioactivity
and Radiationfor Human
Health Risk
Edited by

Shinji Tokonami and Ikuo Kashiwakura
Printed Edition of the Special Issue Published inInternational Journal of Environmental Research and Public Healthwww.mdpi.com/journal/ijerph

Assessment of Environmental
Radioactivity and Radiation for
Human Health Risk

Assessment of Environmental
Radioactivity and Radiation for
Human Health Risk

Editors
Shinji Tokonami
Ikuo Kashiwakura

MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin

Editors
Shinji Tokonami

Ikuo KashiwakuraInstitute of Radiation Emergency Vice president
Medicine

Hirosaki University

Hirosaki University

Aomori

Aomori

Japan

Japan

Editorial Ofﬁce
MDPI
St. Alban-Anlage 664052 Basel, Switzerland

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Contents
About the Editors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Preface to ”Assessment of Environmental Radioactivity and Radiation for Human HealthRisk” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ix

Shinji Tokonami
Characteristics of Thoron (220 Rn) and Its Progeny in the Indoor Environment
Reprinted from: Int. J. Environ. Res. Public Health 2020, 17, 8769, doi:10.3390/ijerph17238769 . . .

1

Yohei Fujishima, Yasushi Kino, Takumi Ono, Valerie Swee Ting Goh, Akifumi Nakata,
Kentaro Ariyoshi, Kosuke Kasai, Tadashi Toyoda, Toru Akama, Hirofumi Tazoe, Masatoshi
Yamada, Mitsuaki A. Yoshida and Tomisato Miura
Transition of Radioactive Cesium Deposition in Reproductive Organs of Free-Roaming Cats inNamie Town, Fukushima
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 1772, doi:10.3390/ijerph18041772 . . . 21
Oumar Bobbo Modibo, Yuki Tamakuma, Takahito Suzuki, Ryohei Yamada, Weihai Zhuo,
Chutima Kranrod, Kazuki Iwaoka, Naofumi Akata, Masahiro Hosoda and Shinji Tokonami
Long-Term Measurements of Radon and Thoron Exhalation Rates from the Ground Using the
Vertical Distributions of Their Activity Concentrations
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 1489, doi:10.3390/ijerph18041489 . . . 35
Alicia Fernández, Carlos Sainz, Santiago Celaya, Luis Quindós, Daniel Rábago and Ismael
FuenteA New Methodology for Deﬁning Radon Priority Areas in Spain
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 1352, doi:10.3390/ijerph18031352 . . . 47
Tetsuya Sanada
Measurement of Indoor Thoron Gas Concentrations Using a Radon-Thoron Discriminative
Passive Type Monitor: Nationwide Survey in Japan
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 1299, doi:10.3390/ijerph18031299 . . . 63
Shunya Nakasone, Akinobu Ishimine, Shuhei Shiroma, Natsumi Masuda, Kaori Nakamura,
Yoshitaka Shiroma, Sohei Ooka, Masahiro Tanaka, Akemi Kato, Masahiro Hosoda, Naofumi
Akata, Yumi Yasuoka and Masahide Furukawa
Temporal and Spatial Variation of Radon Concentrations in Environmental Water from
Okinawa Island, Southwestern Part of Japan
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 998, doi:10.3390/ijerph18030998 . . . 71
Koya Ogura, Masahiro Hosoda, Yuki Tamakuma, Takahito Suzuki, Ryohei Yamada, Ryoju
Negami, Takakiyo Tsujiguchi, Masaru Yamaguchi, Yoshitaka Shiroma, Kazuki Iwaoka,
Naofumi Akata, Mayumi Shimizu, Ikuo Kashiwakura and Shinji Tokonami
Discriminative Measurement of Absorbed Dose Rates in Air from Natural and Artiﬁcial
Radionuclides in Namie Town, Fukushima Prefecture
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 978, doi:10.3390/ijerph18030978 . . . 83
Eka Djatnika Nugraha, Masahiro Hosoda, June Mellawati, Untara Untara, Ilsa Rosianna,
Yuki Tamakuma, Oumar Bobbo Modibo, Chutima Kranrod, Kusdiana Kusdiana and Shinji
Tokonami
Radon Activity Concentrations in Natural Hot Spring Water: Dose Assessment and Health
Perspective
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 920, doi:10.3390/ijerph18030920 . . . 99v

Mohammademad Adelikhah, Amin Shahrokhi, Morteza Imani, Stanislaw Chalupnik andTibor Kovács
Radiological Assessment of Indoor Radon and Thoron Concentrations and Indoor Radon Mapof Dwellings in Mashhad, Iran
Reprinted from: Int. J. Environ. Res. Public Health 2020, 18, 141, doi:10.3390/ijerph18010141 . . . 107
Jun Hu, Guosheng Yang, Chutima Kranrod, Kazuki Iwaoka, Masahiro Hosoda and Shinji
Tokonami
An Improved Passive CR-39-Based Direct 222 Rn/220 Rn Progeny Detector
Reprinted from: Int. J. Environ. Res. Public Health 2020, 17, 8569, doi:10.3390/ijerph17228569 . . . 123
Hiroshi Terada, Ikuyo Iijima, Sadaaki Miyake, Kimio Isomura and Hideo Sugiyama
Total Diet Study to Assess Radioactive Cs and 40 K Levels in the Japanese Population before andafter the Fukushima Daiichi Nuclear Power Plant Accident
Reprinted from: Int. J. Environ. Res. Public Health 2020, 17, 8131, doi:10.3390/ijerph17218131 . . . 137
Yuki Tamakuma, Chutima Kranrod, Takahito Suzuki, Yuki Watanabe, Thamaborn
Ploykrathok, Ryoju Negami, Eka Djatnika Nugraha, Kazuki Iwaoka, Mirosław Janik,
Masahiro Hosoda and Shinji Tokonami
Passive-Type Radon Monitor Constructed Using a Small Container for Personal Dosimetry
Reprinted from: Int. J. Environ. Res. Public Health 2020, 17, 5660, doi:10.3390/ijerph17165660 . . . 155
Aoife Kinahan, Masahiro Hosoda, Kevin Kelleher, Takakiyo Tsujiguchi, Naofumi Akata,
Shinji Tokonami, Lorraine Currivan and Luis León Vintró
Assessment of Radiation Dose from the Consumption of Bottled Drinking Water in Japan
Reprinted from: Int. J. Environ. Res. Public Health 2020, 17, 4992, doi:10.3390/ijerph17144992 . . . 165
Hirofumi Tazoe, Takeyasu Yamagata, Kazuki Tsujita, Hisao Nagai, Hajime Obata, Daisuke
Tsumune, Jota Kanda and Masatoshi Yamada
Observation of Dispersion in the Japanese Coastal Area of Released 90 Sr, 134 Cs, and 137 Cs fromthe Fukushima Daiichi Nuclear Power Plant to the Sea in 2013
Reprinted from: Int. J. Environ. Res. Public Health 2019, 16, 4094, doi:10.3390/ijerph16214094 . . . 177
Naofumi Akata, Masahiro Tanaka, Chie Iwata, Akemi Kato, Miki Nakada, Tibor Kovács and
Hideki Kakiuchi
Isotope Composition and Chemical Species of Monthly Precipitation Collected at the Site of a
Fusion Test Facility in Japan
Reprinted from: Int. J. Environ. Res. Public Health 2019, 16, 3883, doi:10.3390/ijerph16203883 . . . 193
Masahiko Matsuo, Yasuyuki Taira, Makiko Orita, Yumiko Yamada, Juichi Ide, Shunichi
Yamashita and Noboru Takamura
Evaluation of Environmental Contamination and Estimated Radiation Exposure Dose Rates
among Residents Immediately after Returning Home to Tomioka Town, Fukushima Prefecture
Reprinted from: Int. J. Environ. Res. Public Health 2019, 16, 1481, doi:10.3390/ijerph16091481 . . . 205
Van-Hao Duong, Thanh-Duong Nguyen, Miklos Hegedus, Erika Kocsis and Tibor Kovacs
Study of Well Waters from High-Level Natural Radiation Areas in Northern Vietnam
Reprinted from: Int. J. Environ. Res. Public Health 2021, 18, 469, doi:10.3390/ijerph18020469 . . . 217

viAbout the Editors
Shinji Tokonami
Professor Shinji Tokonami is director of the Institute of Radiation Emergency Medicine,
Hirosaki University, Japan. He specializes in radiation measurement and dose assessment. In 1995,
Dr. Tokonami earned his Ph.D. in engineering from Waseda University. Throughout his career he has
been involved with radiation research at Waseda University, the National Institute of Radiological
Sciences, and Hirosaki University. In addition, he is a member of several International Organizationsfor Standards’committees regarding radon and radiation measurements.

Dr.

Tokonami also

developed multiple measurement techniques and equipment related to his ﬁeld. In particular,
he established a passive measurement technique for detecting radon-222 and radon-220.

This

discriminative measurement technique for radon isotopes was published as ISO 16641.
Ikuo Kashiwakura
Professor Ikuo Kashiwakrua is the Vice President of Hirosaki University, Japan and is incharge of radiation emergency medicine-related activities. In addition, his specialty is radiation
biology, especially on radiation’s effects on the differentiation and proliferation of hematopoietic
stem cells and the development of radiomitigative protocols. Dr. Kashiwakura earned his Ph.D.
in Pharmacology from Hokkaido Pharmaceutical University School of Pharmacy. Throughout his
career he has been involved with radiation education and research at Hokkaido Pharmaceutical
University School of Pharmacy and Hirosaki University for about 40 years. Meanwhile, he served asa program ofﬁcer of the Science Center for Science Systems established within JSPS for three years(2009–2011). Currently, his research is focusing on the development of radiomitigative protocols
utilizing domestically approved pharmaceutical drugs.

viiPreface to ”Assessment of Environmental
Radioactivity and Radiation for Human Health Risk”
In 2010, the Institute of Radiation Emergency Medicine (IREM) was established as a strategic
research institute at Hirosaki University, Japan. Subsequently, the Great East Japan Earthquake
occurred on 11 March 2011, and consequently a nuclear accident occurred at Tokyo Electric Power’s
Fukushima Daiichi Nuclear Power Plant. We played an important role in the response to the disasterand transmitted a wide range of academic information. This achievement has been highly rated, notonly in Japan but also internationally. In parallel, we have started a human resources development
project for the Nuclear Regulation Authority and other projects that aim to create a hub institution
for domestic utilization and collaborative research.
This Special Issue book of the International Journal of Environmental Research and Public Health,titled “Assessment of Environmental Radioactivity and Radiation for Human Health Risk”, is the oneof IREM’s accomplishments and is published to commemorate the 10th anniversary of the Instituteof Radiation Emergency Medicine. This book provides a collection of high-quality research papers inradiation-related ﬁelds, such as environmental radioactivity, environmental radiation, measurement
data, methodology, monitoring, and risk assessment. Finally, we thank all the reviewers, editors andauthors for their important anonymous contributions under a very strict time constraint, and wewould like to acknowledge all of the authors for their excellent research.
Shinji Tokonami, Ikuo Kashiwakura
Editorsix

International Journal ofEnvironmental Researchand Public Health
Review

Characteristics of Thoron (220Rn) and Its Progeny in
the Indoor Environment
Shinji Tokonami
Institute of Radiation Emergency Medicine, Hirosaki University, Hirosaki 036-8564, Aomori, Japan;
tokonami@hirosaki-u.ac.jp; Tel.: +81-172-39-5404
Received: 19 October 2020; Accepted: 23 November 2020; Published: 25 November 2020

Abstract: The present paper outlines characteristics of thoron and its progeny in the indoor
environment. Since the half-life of thoron (220 Rn) is very short (55.6 s), its behavior is quite
diﬀerent from the isotope radon (222 Rn, half-life 3.8 days) in the environment. Analyses of radon andlung cancer risk have revealed a clearly positive relationship in epidemiological studies among miners
and residents. However, there is no epidemiological evidence for thoron exposure causing lung cancer
risk. In contrast to this, a dosimetric approach has been approved in the International Commission
on Radiological Protection (ICRP) Publication 137, from which new dose conversion factors for radon
and thoron progenies can be obtained. They are given as 16.8 and 107 nSv (Bq m−3 h)−1 , respectively.
It implies that even a small quantity of thoron progeny will induce higher radiation exposurecompared to radon. Thus, an interest in thoron exposure is increasing among the relevant scientiﬁccommunities. As measurement technologies for thoron and its progeny have been developed, they are
now readily available. This paper reviews measurement technologies, activity levels, dosimetry andresulting doses. Although thoron has been underestimated in the past, recent ﬁndings have revealed
that reassessment of risks due to radon exposure may need to take the presence of thoron and its
progeny into account.
Keywords: thoron; thoron progeny; indoor environment; measurement technique; radioactivity;
dose assessment

1. Introduction
Radon (222 Rn), thoron (220 Rn) and their progeny can be regarded as the largest contributor
annually to an eﬀective dose for the public globally [1,2]. According to the United Nations Scientiﬁc
Committee on the Eﬀects of Atomic Radiation (UNSCEAR) 2008 report, an annual eﬀective dose fromnatural radiation sources is calculated to be 2.4 mSv as the worldwide average, whereas radon andthoron contribute 1.2 and 0.1 mSv, respectively. When they are inhaled, although radon and thoron
gases are not signiﬁcant, their progeny particularly aﬀect the lung tissue due to alpha particles emitted
in their decay chains deposited in the airways. In the past, lung cancer incidence had been found only
among miners as shown in many epidemiological studies, whereas recent investigations have revealed
that even indoor radon resulted in lung cancer among residents [3]. These surveys were carriedout in Europe, North America and China. Therefore, the World Health Organization (WHO) issued
a handbook where special attention was paid to indoor radon [3]. Subsequently, the International
Commission on Radiological Protection (ICRP) has recently published two publications and one
statement related to radon. In these documents, the upper value of the reference level for radon gas
in homes was revised downward from the value in the 2007 Recommendations of 600 Bq m−3 to300 Bq m−3 [4,5]. The International Atomic Energy Agency (IAEA) revised the previous Basic Safety
Standard (BSS) in the same manner as the ICRP and a related guide was issued [6,7]. The WHO further
advised a reference level of 100 Bq m−3 though it may be impossible to achieve such a low radon gas
concentration in many countries. Such recommendations depend on results of an indoor radon survey.
IJERPH 2020, 17, 8769; doi:10.3390/ijerph17238769

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IJERPH 2020, 17, 8769

In most cases, these surveys were carried out using passive radon monitors so as to obtain an annual
indoor radon concentration. Even in epidemiological surveys, the same type of radon monitor wasused, because lung cancer incidence was closely related to long-term exposure to radon. Previous
recommendations were given based on not the dosimetric, but on the epidemiological approach. It had
been previously believed that the epidemiological approach was more reliable than the dosimetric.
In ICRP Publication 65, the risk estimate was given based on the epidemiological approach [8]. As wasconcluded according to studies of miners, however, the conversion convention, though scientiﬁcallyvague, needed to be used when applied to indoor radon studies. There was a large diﬀerence between
the two approaches by a factor of more than three and many technical issues to be solved. After thedata analyses on the indoor radon and lung cancer study were vigorously carried out, the risk estimatesin residential radon studies were eventually concluded without using the conversion convention andcame close to those given by the dosimetric approach. This is why many authoritative publications
were issued and revised. However, they still state that the eﬀect of thoron is negligible compared tothat of radon, though the amount of related data is limited. It should be noted that measurement
techniques for thoron are not so easy as those for radon. As the half-life of thoron atoms is much
shorter than that of radon, they immediately decay, followed by 216 Po with a half-life much shorter
than thoron. A question arises here. Many passive radon monitors have been used in both nationaland epidemiological surveys. If thoron is present together with radon, are these well designed so as toeﬀectively detect radon only? If high diﬀusion barriers are used, they depress the detection of thoron.
Otherwise they may mislead and lead to wrong calculation of radon concentrations. In epidemiologicalsurveys, this will result in incorrect lung cancer risk estimates. Most passive radon monitors havenever been examined from the viewpoint of thoron interference on radon measurements. Limited dataon thoron is given in UNSCEAR reports and indoor thoron surveys have never been systematicallyconducted. It is well known that there is no epidemiological evidence for thoron risk related to lungcancer. The risk can be estimated based only on the dosimetric approach. Under the current situationin which the dosimetric approach has become more reliable, it is important to know how large thetotal lung cancer risk is when inﬂuenced by thoron and its progeny. This paper comprehensively
describes characteristics of thoron and its progeny in the indoor environment from the viewpoint of
measurements, dose assessment and health risk.
2. Physical Property and Behavior
Figure 1 illustrates the radioactive decay series for thorium-232 [9] where the half-life and emitted
energies are given. After Ra-224 decays, Rn-220 is formed. It is commonly called thoron, an inert gas.
In the uranium-238 decay series, on the other hand, radon-222 is formed as an inert gas. There is a great
deal of diﬀerence in the half-life between radon-220 and radon-222. Although Po-216 is formed withalpha decay of Rn-220, it can almost be regarded as a gas because its half-life is very short. Subsequently
Pb-212 and Bi-212 are formed, which need mainly to be considered for dose assessment when they areinhaled. These concentrations are collectively expressed in the equilibrium equivalent concentration(EEC). The EEC for thoron progeny (Equilibrium Equivalent Thoron Concentration: EETC [Bq m−3 ])can be approximately calculated by the Equation (1) after considering the contribution of Po-216:
EETC = 0.913 × CB + 0.087 × CC

(1)

where CB : Pb-212 is activity concentration [Bq m−3 ]; CC : Bi-212 is activity concentration [Bq m−3 ].
If the equilibrium factor for thoron (FTn ) is deﬁned in the same manner for radon, it can be expressedas the Equation (2):
EETC
wFTn =(2)CTn
where CTn is thoron concentration [Bq m−3 ]. The signiﬁcance of the equilibrium factor for thoron is
discussed in this paper from the viewpoint of dose assessment.

2

IJERPH 2020, 17, 8769

Figure 1. Radioactive decay series for thorium-232.

Figure 2 exempliﬁes the exhalation process of thoron from macro surfaces such as walls containing
its parent nuclide 224 Ra. The exhalation and diﬀusion of thoron is approximately described as a
one-dimensional phenomenon. When the exhalation rate of thoron from the wall is considered,for instance, the indoor thoron concentration (CTn (x) [Bq m−3 ]) at distance x from the wall can be
expressed by the Equation (3) [10,11]:√E
CTn (x) = √ Tn e(− λTn /Dx)
λTn D

(3)

where ETn is surface exhalation rate of thoron from the wall [Bq m−2 s−1 ]; λTn is decay constant ofthoron [s−1 ]; and D is diﬀusion coeﬃcient of thoron [m2 s−1 ]. If the thoron concentrations are measured
at two diﬀerent locations, respectively, the exhalation rate of thoron can be estimated. As the half-lifeof Po-216 is much shorter than that of the parent nuclide thoron, there is a radioactive equilibrium
between the two isotopes.

Figure 2. Exhalation process of thoron from macro surface.

Figure 3 illustrates the behavior of radon/thoron and their progeny in indoor air. After radon
and thoron decay, their progenies are formed. Most of these are positively charged and they rapidly
capture water molecules, thus forming clusters. They move so quickly in air that some of them attach
to ambient aerosols and the others deposit on the wall, ceiling, ﬂoor and macro-surfaces. Therefore
3

IJERPH 2020, 17, 8769

radon/thoron progeny are generally classiﬁed into two fractions: unattached and attached fractions.
As unattached progenies have a high diﬀusive velocity, they deposit on available surfaces very quickly.
Even progeny attached to ambient aerosols may eventually deposit on the surface. Before Po-216
atoms are captured by ambient aerosols, they decay to Pb-212 atoms. After considering the half-life of
Pb-212, the negligible outdoor Pb-212 activity concentration, and the attachment process to aerosols,
Pb-212 activity concentration (CB [Bq m−3 ]) in a room can be obtained by the Equation (4):CB =λa λ ES· B Tn 
λTn λB + λv + λad λB + λa + λTn (λB + λa ) V(4)where λB is decay constant of Pb-212 [s−1 ]; λa is attachment rate of unattached thoron progeny onto
ambient aerosols [s−1 ]; λv is ventilation rate of the room [s−1 ]; λad is deposition rate of attached thoron
progeny [s−1 ]; S is surface area where thoron atoms are emitted [m2 ]; and V is inner volume of theroom [m3 ]. Based on the same manner, Bi-212 activity concentration (CC ) is subsequently given by the
Equation (5):
λC CB
CC =
(5)
λC + λv + λad
where λC is decay constant of Bi-212 [s−1 ]. When the typical parameters are given in Table 1 [10,12,13],
EETC can be estimated with the exhalation rate of thoron as shown in Figure 4. De With et al. [14]reported the thoron exhalation rate from the wall against the EETC value in the room. As the physicalparameters except Surface-to-Volume (S-V) ratio are not expected to be much diﬀerent in any indoor
environment, EETC can be simply expressed along with the exhalation rate of thoron and S-V ratio as
the Equation (6):S
(6)
EETC = 3.36ETn
V
Note that the EETC may change if another value of each parameter is adopted from the range.

Figure 3. Behavior of radon/thoron and their progeny in indoor air.

4

IJERPH 2020, 17, 8769

Table 1. Physical parameters for indoor model [10,12,13].
Parameter 1

Range

TypicalDecay constant of thoron [h−1 ]Decay constant of Pb-212 [h−1 ]Attachment rate of unattached thoron progeny
onto ambient aerosols [h−1 ]Ventilation rate of the room [h−1 ]Deposition rate of attached thoron progeny [h−1 ]Surface-to-Volume ratio [m−1 ]

3–110

44.74
0.065
50

0.1–1
0.015–0.35
-

0.5
0.2
0.36

1 Unit is expressed in h−1 so as to easily compare with previous studies.

Figure 4. The relationship between Equilibrium Equivalent Thoron Concentration (EETC) and exhalation
rate of thoron.

3. Measurement Techniques
3.1. Spot Measurement
3.1.1. Thoron
As the half-life of thoron is shorter than 1 min, thoron gas measurement needs to start immediately
after sampling. In this section, the measurement method using one scintillation cell is brieﬂy
introduced. Tokonami et al. [15] developed a discriminative measurement technique for radon andthoron concentrations with time-sequential counting. Prior to the measurement, alpha counting
eﬃciencies for radon, 218 Po, 214 Po, thoron and 216 Po were estimated by a Monte Carlo Calculation
after taking their range into account based on their emitted energies as well as the size of the cell.
In their study, Pylon scintillation cells of 300A and 110A were used. Their inner volumes are 270 [mL]and 151 [mL], respectively. As this technique can be completed within 15 min, contribution fromany other alpha emitters of the remaining thoron progeny, such as 212 Bi and 212 Po, can be ignored
for the determination of thoron concentration. In order to validate justiﬁcation of the alpha counting
eﬃciencies by the Monte Carlo simulation, the conversion factor theoretically drawn was comparedwith that experimentally given by the manufacturer. The large cell conversion factor (300A) provided
by the manufacturer is the value at radioactive equilibrium, which is given as 27.9 [Bq m−3 cpm−1 ].
After radon gas is drawn into the cell, it takes 3.5 h to reach the equilibrium between radon and its
progeny. With the latest nuclear data, the theoretical conversion factor is eventually estimated to be
28.3 [Bq m−3 cpm−1 ], where there is only a small diﬀerence between the two approaches. Zhang et al.

5

IJERPH 2020, 17, 8769

made a similar approach in the conversion factor of the same scintillation cell [16]. The alpha counting
eﬃciencies for thoron and its progeny are close to those given by Tokonami et al. [17]. As the theoretical
approach has been justiﬁed, it can be also applicable to the determination of thoron concentration withthe alpha counting eﬃciencies of thoron and 216 Po. Furthermore, it can be regarded that 216 Po atoms
behave like a gas in the cell and that thoron and 216 Po are at equilibrium because its half-life is very
short. The thoron concentration (CTn [Bq m−3 ]) is given by the Equation (7):
CTn =

NTn
 t +tm
Vc × (ηTn + ηThA ) t 0
e−λTn t dt

(7)0

where NTn is counts during the period; V c is inner volume of the cell [m−3 ]; ηTn is counting eﬃciencyof thoron; ηThA is counting eﬃciency of 216 Po; t0 is beginning of the measurement [s]; and tm ismeasurement period [s]. If radon is present together with thoron, however, counts derived from radonand its progeny need to be subtracted from NTn . In order to obtain net counts derived from thoron andits progeny, another measurement is therefore necessary after thoron and 216 Po completely decay. NTn
can be expressed as the Equation (8):NTn = N1 − kN2(8)where N1 is counts during the ﬁrst period; N2 is counts during the second period. The constant kdepends on the existing ratio of radon and its progeny in the cell and the measurement timetable.
In the previous study, an optimal timetable with a 15 min time interval was discussed. The following
timetable was proposed: twenty seconds after sampling, the ﬁrst measurement is made over 100 s.
Ten minutes after sampling, a 5 min counting, as the second measurement, is made.
3.1.2. Thoron Progeny
The measurement technique for thoron progeny is similar to that for radon progeny. In general,an alpha counting method is preferable. As 212 Pb and 212 Bi concentrations are assigned to the subjectof dose assessment in thoron progeny measurement, the counting method is simpler than that forradon progeny. Two time-sequential counts are necessary to measure two kinds of thoron progeny
concentration in both gross alpha counting and alpha spectroscopic methods. As the half-life of 212 Pb is
as long as 10 h, however, it takes a signiﬁcant amount of time to measure thoron progeny concentrations
precisely. In the gross counting method, a ZnS(Ag) (siliver-activated zinc sulﬁde) scintillation counting
system is commonly used. As this technique has no alpha energy discrimination, however, it will be
impossible to complete the determination of thoron progeny concentration in a natural environment
because radon will also be present together with thoron. Therefore, the measurement timetable needs tobe optimized so as to determine thoron progeny concentrations. Unless radon progeny concentrations
are the subject of measurement, the measurement can begin after radon progeny completely decay(practically after 6 h). Note that accuracy of 212 Bi activity concentration will be diminished when
considering the half-life of 212 Bi (60 min). In order to overcome such practical problems, the least-square
method will be suitable. This can give any activity concentrations regardless of the number of unknown
concentrations. In contrast, the alpha spectroscopic method can quickly terminate the measurement for
both radon and thoron progeny, because the alpha particles emitted from them can be identiﬁed due tothe high resolution of the alpha spectrum. Information on the highest alpha particle energy emitted from212 Po is available via this technique without any interference from any other alpha emitters. When thedose assessment is referred, determination of 212 Pb will be emphasized because the contribution from212 Bi is much smaller than that from 212 Pb as shown in the Equation (1). Tokonami et al. [17] developed
a simple measurement technique for the equilibrium equivalent thoron concentration with a solid-state
nuclear track detector. A poly allyl diglycol carbonate (PADC), commercially named CR-39, is used as
the detecting material [17]. This passive technique is applicable to determine the radioactivity level
anywhere without electricity supply. The following procedure, before chemical etching and track
reading, can be introduced for the determination of thoron progeny:
6

IJERPH 2020, 17, 8769

1.
2.
3.

4.

Air samples are taken over several hours with a membrane ﬁlter (Millipore AA) or glass microﬁber
ﬁlter (Whatman GF/F) installed in an open-faced ﬁlter holder and a DC powered air pump;
The ﬁlter is left until radon progeny completely decay (more than 6 h);
An aluminum foil (4.0 mg cm−2 ) as the energy absorber is directly placed on the ﬁlter so as todetect alpha energy emitted from thoron progeny, and then a CR-39 plate is attached for alphatrack registration;
The time is recorded when the CR-39 plate is removed. This is the end of the measurement process.

3.2. Continuous Measurement
3.2.1. Thoron
There are two main ways to continuously identify thoron even though radon is present as well.
Falk et al. [18] developed a delayed coincidence method. The method separates the fraction of alphacounts emitted from 216 Po from all the other alpha counts. This method is based on the short half-life of
150 ms of 216 Po. Bigu and Elliot [19] developed a continuous monitor based on their concept. Althoughsimilar monitors were also developed, a ﬂow-through scintillation cell is used in any measurement
system. Alternatively, alpha spectrometry is used. A RAD7 monitor, commercially available, is basedon an electrostatic collection method (for instance, Takeuchi et al., 1999) [20]. In this monitor, air isdrawn into the decay chamber through the drying column. As radon and thoron progeny are positively
charged, they will be neutralized by vapor and subsequently will not be collected on the surface of thesilicon semiconductor detector as the electrode unless air is dried. In addition, the half-life of 216 Po is
so short that a large mobility will be required by high voltage to obtain a suﬃcient sensitivity to thoron.
The voltage cannot be changed in the above monitor. Therefore, a sampling ﬂow rate is one of theimportant parameters for thoron sensitivity due to its short half-life. Special attention must be paid tothe ﬂow rate when determining thoron concentrations with this monitor.
3.2.2. Thoron Progeny
There are several commercial products for continuous working level monitoring. Note that any
signals derived from thoron progeny cannot be separated from those of radon progeny unless alpha
spectroscopy is used. In principle, the alpha spectroscopic method can specify information regarding
thoron progeny though it cannot determine the concentration. In a speciﬁc continuous monitor,
the EETC can be simply determined using the count rate (CPM) and an experimentally obtained
conversion factor (CF) as in the Equation (9):EETC =

CPM
CF

(9)

As the conversion factor is obtained under the condition where the EETC is constant, however, the EETC
does not always correspond to an actual variation. On the contrary, a special algorithm for potentialalpha energy concentrations (PAEC) developed by Tokonami et al. [21] would be applicable in this case.
3.3. Time-Integrated Measurement
3.3.1. Thoron
Passive monitors are available for long-term measurement for both radon and thoron.
This technique is commonly used in nation-wide or regional surveys. Solid state nuclear track
detectors and electrets are installed in such a passive system. As they cannot separate radon andthoron signals, however, a dual measurement system needs to be chosen. This dual system is derived
from the large diﬀerence of the half-life between two radioisotopes. For this purpose, the system
accommodates two diﬀerent diﬀusion chambers where detectors are installed and in each the entry
rate of gas is well controlled by a gap or ﬁlter. In this section, two types of monitor are introduced.

7

IJERPH 2020, 17, 8769

Eappen and Mayya developed a twin cup radon-thoron dosimeter [22] (Figure 5). Three pieces of
LR-115 Type II detector are ﬁxed in the twin chamber radon dosimeter having three diﬀerent mode
holders. The exposure of the detector is termed as the cup mode whereas the one exposed as open istermed the bare mode. The right chamber is covered with a glass ﬁber ﬁlter and therefore both radon
and thoron gases can easily enter the chamber. The left chamber is covered with a membrane ﬁlter so
as to reduce the entry of thoron. Thus, there is less sensitivity for thoron in the left chamber than theright chamber. The third detector ﬁlm exposed in the bare mode registers alpha tracks contributedby concentrations of radon, thoron and their progeny. Thereafter another type of passive monitor(Figure 6) was developed by Sahoo et al. [23]. A pin-hole based 222 Rn/220 Rn discriminator was installedin the monitor. For discriminative measurement of two radon isotopes, a pin-hole diﬀusion barrier
was used [24,25]. This is because diﬀerent entry rates of 222 Rn were pointed out through two entrancesof the dosimeter which might arise from turbulence or air ﬂow in one direction. The new device wasdesigned to overcome the limitation of the conventional twin cup dosimeter. Currently this pin-hopemonitor has been widely used in India.

Figure 5. A twin cup radon-thoron discriminative monitor [22].

Figure 6. A pin-hole based radon-thoron measurement device [23].

Tokonami et al. [26] also developed a passive 222 Rn and 220 Rn discriminative monitor for alarge-scale survey (Figure 7). The measurement principle is almost the same as the Indian monitor
except for their bare mode. PADC, commercially CR-39, is used as the detecting material. This monitor
and its prototype have been widely used in various countries [27–30]. The above two monitors can becalibrated in the calibration chamber at Hirosaki University Institute of Radiation Emergency Medicine,Japan [31]. For determination of radon and thoron activity concentrations with passive solid-state
8

IJERPH 2020, 17, 8769

nuclear track detectors, ISO 16,641 [32] is currently available. The detection threshold, detection limit andconfidence lower/upper limits in this technique are calculated based on ISO 11,929 [33]. A comparative
performance test of Indian and Japanese-Hungarian monitors was carried out in the environment [34].

Figure 7. A passive type radon (222 Rn) and thoron (220 Rn) discriminative monitor [26].

3.3.2. Thoron Progeny
A prototype of the passive type thoron progeny monitor was developed by Zhuo and Iida basedon diﬀusive deposition on the surface [35]. Among thoron progeny, 212 Po atoms emit alpha energy of
8.8 MeV, which is the highest alpha energy of all the natural radionuclides. It is, hence, obvious that it
will be easy to detect this high energy by separating diﬀerent energies emitted from other radionuclides
if an alpha energy absorber with a proper thickness is prepared. Figure 8 shows an overview of athoron progeny monitor. For radiation detection, CR-39, one of the solid-state nuclear track detectors,
is mounted in the monitor. The body is made of stainless steel. As shown in Figure 8, four pieces are
installed in the monitor and they are covered with an aluminized Mylar ﬁlm and a polypropylene ﬁlm
in this order (thickness: 7.1 mg cm−2 ; air-equivalent thickness: 71 mm). By adjusting the thickness
properly, only alpha energy of 8.8 MeV can be detected. Figure 9 exempliﬁes the detecting principle ofalpha energy emitted from 212 Po [36].
The monitor is hung on the wall for a certain period. In a usual survey, it is exposed for a
few months. Radon and thoron progeny in indoor air deposit on the wall over the time period.
After they are deposited, tracks of alpha particles are recorded in the CR-39. After retrieving themonitors, they are chemically etched to identify alpha tracks with a track reading system. The etchingcondition for CR-39 (Baryotrak; Nagase Landauer Ltd., Japan) is as follows: solution: 6.0 M NaOH;
temperature: 60 ◦ C; time: 24 h. Using a track reading system such as a microscope, track density
is determined. The relationship between track density (D) and thoron progeny concentration,i.e., equilibrium equivalent thoron concentration, is expressed as the Equation (10):
EETC =

D
C×T

(10)

where D is track density (tracks mm−2 ); C is conversion factor experimentally obtained (0.017 tracks mm−2
(Bq m−3 day)−1 in our monitor); T is exposure period (day); and EETC: equilibrium equivalent thoron
concentration (Bq m−3 ).
9

IJERPH 2020, 17, 8769

Figure 8. An overview of a thoron progeny monitor [11].

Figure 9. A detecting principle of alpha energy emitted from 212 Po [36].

The conversion factor was experimentally obtained by the comparison between the monitor
and intermittent thoron progeny measurement. The experiment was carried out in actual dwellings.
Using the proposed technique, the lowest detection limit of the EETC is estimated to be 0.005 Bq m−3
with 90-day exposure.
Similar techniques were found in Indian studies [37–43]. Instead of CR-39, LR-115 nuclear track
detectors are used in their monitors. Not only thoron progeny sensors but also radon progeny sensors
are installed by diﬀerentiating the thickness of energy absorbers. Furthermore, metal wire screens are
introduced to detect ﬁne and coarse progeny aerosols separately [44].
4. Dosimetry
When assessing the annual eﬀective dose due to radon/thoron progeny inhalation, dose conversion
factors are used. International bodies such as UNSCEAR and ICRP have their own values.
The dose conversion factors (DCF) for radon are derived from both epidemiological evidence anddosimetric models, whereas the DCF for thoron is given only by the dosimetric model because
there is no epidemiological evidence of lung cancer incidence due to thoron progeny inhalation.
Table 2 summarizes eﬀective dose conversion factors (mSv WLM−1 ) (WLM: Working Level Month)
for thoron. The DCF for thoron is about two–three times smaller than that for radon [1,45–51].
When rewriting the DCF, expressed in dose per unit equilibrium equivalent activity concentration
10

IJERPH 2020, 17, 8769

of thoron/radon exposures, however, the DCF for thoron is more than two times larger than that forradon. According to the latest DCF for thoron and radon in ICRP Publ. 137 [51], they can be given as
107 nSv (Bq h m−3 )−1 and 16.8 nSv (Bq h m−3 )−1 , respectively. On the contrary, UNSCEAR has recently
decided to use the conventional values of 40 nSv (Bq h m−3 )−1 and 9 nSv (Bq h m−3 )−1 , respectively,
despite the inconsistency. This needs more consideration in order for them to correspond each other.
Table 2. Summary of eﬀective dose conversion factors for thoron.
References

Eﬀective Dose Conversion Factors(mSv WLM−1 ) 1

Marsh and Birchall [45,46]
UNSCEAR [1]Porstendoerfer [47]Ishikawa et al. [48]Kendall and Phipps [49]Hofmann et al. [50]International Commission on RadiologicalProtection (ICRP) Publ. 137 [51]

3.8
1.9
2.4
5.4
5.7
4.6
5.6 (Indoor workplace)
4.8 (Mine)

1 Working Level Month (WLM) is a historical unit of alpha potential energy exposure. 1 WLM = 3.45 mJ h m−3 .

5. Radioactivity and Resulting DoseAs mentioned above, thoron activity concentration is not uniformly distributed in the environment,
which is far from the case for radon. It is considered that thoron concentration in air exponentiallydecreases with distance from the source. This behavior is derived from the very short half-life ofthoron (55.6 s). The exponential change of thoron concentration is deﬁned via the diﬀusion coeﬃcient,strongly aﬀected by the air turbulence condition.
Table 3 summarizes thoron and thoron progeny concentrations (EETC) in various countries. As canbe seen from the presented data, their number is more restricted than that of radon [27,39,41,42,52–67].
In Cameroon, radon, thoron and its progeny concentrations were measured in residential areas inuranium and thorium bearing regions [52]. UNSCEAR presents the typical value of the equilibrium
factor of thoron as 0.02 and this equilibrium factor of thoron is often used to estimate the annual eﬀective
dose due to thoron, in the same manner as in the case of radon. In the present study, the authors
estimated a total annual eﬀective dose derived from radon and thoron using actual measurement
data on thoron progeny and compared it with that given by the UNSCEAR method. Consequently,
the result based on the direct measurement was 1.5 times larger than the indirect one. They concluded
that the direct measurement of thoron progeny is important for dose assessment.
The results of two surveys in Canada were tabulated. In one survey, long-term thoron and progeny
measurements were simultaneously carried out for three months in two cities [53]. The simultaneous
measurement of thoron and thoron progeny concentrations yielded a thoron equilibrium factor of
0.002 and therefore the authors concluded that the typical value given by UNSCEAR is reasonable fordose assessment. In contrast to a Cameroonian study, the Canadian study justiﬁed the consistency of
the thoron equilibrium factor via the UNSCEAR method. In the other survey, results of simultaneousradon and thoron measurements were shown in 33 metropolitan areas [54]. The study demonstrates
that thoron contributes around 3% of the eﬀective dose due to indoor radon and thoron exposurein Canada.

11

IJERPH 2020, 17, 8769

Table 3. Thoron and thoron progeny concentration (EETC) in various countries.
Thoron(Bq m−3 )EETC(Bq m−3 )

GM 2
Range

173 (13)118 (6)23–72410.7 (0.9)
7.4 (4.8)
0.4–37.6

Canada

AM 1
GM 2
Range

114 (303)
51 (2.93)
6–1977

1.23 (1.51)
0.75 (2.64)
0.11–7.45

Canada (33metropolitans)

AM 1
Range

9 (11)
ND–164

-

[54]

AM 1
MedianRange

1247 (1189)
859
65–3957

7.8 (9.1)
4.2
0.6–36.2

[55]

China
(Gansu)

AM 1
GM 2
Range

433 (210)
347 (2.29)
19–820

-

[56]

China
(Shanxi)

AM 1
GM 2

160
130 (2.0)

1.4
1.2 (1.8)

[57]

China
(Shaanxi)

AM 1
GM 2

202
181 (1.6)

2.3
2.1 (1.6)

[57]

GM 2
Range

341 (2.59)
40–2514

-

GM 2
Range

41
11–212

1.81 (1.9)
0.36–8.00

[59]

AM 1
GM 2
Range

123 (105)
95 (1.95)
15–585

3.19 (2.75)
2.37 (2.15)
0.44–15.40

[27]

AM 1
Range

22
<1–1740.47<0.05–3.8

[60]

AM 1

195 (36)
BDL–973

11.5 (2.1)
0.8–29.1

[61]

GM 2
Max

40 (56)
11 (2.9)731

0.89 (0.70)
0.6 (0.41–0.78)-[62]

Macedonia

AM 1
GM 2
Range

37 (36)28 (2.12)
3–272

-

[63]

Mexico

AM 1
GM 2
Range

82 (75)55
8–234

Netherlands

AM 1
95-Percentile
Max

-

0.64
1.37
13.3

Slovenia

AM 1
Range

87
21–368-

Srpska

AM 1
GM 2
Range

63 (40)51 (2.07)
7–198

0.52–0.34
0.40 (2.20)
0.09–1.16

Kosovo

AM 1
GM 2
Range

136
90
18–1313

2.06
1.90
0.87–4.38

Serbia

AM 1
GM 2
Range

116
89
10–412

1.1
0.86
0.1–3.4

152 (indoor)
139 (outdoor)
141 (indoor)
121 (outdoor)
20–618 (indoor)
23–457 (outdoor)

13 (indoor)
15 (outdoor)
13 (indoor)
15 (outdoor)
4–40 (indoor)
4–37 (outdoor)

Country
AM 1
Cameroon

China(Yangjiang)

Hungary
India (Kerala)
India(Odisha)Ireland
Kenya

Range
AM 1

Korea

AM 1
Indonesia

GM 2
Range

Remarks

Reference[52]

Halifax andFredericton

Bauxite mine

[53]

[58]

[64]

[65]
Elementary
School

[41]

[39]

[42]
West Sulawesi(HNBR)
Number of
dwellings
Indoor: 45
Outdoor: 18

1 AM: Arithmetic mean, 2 GM: Geometric mean.

12

[66]

[67]

IJERPH 2020, 17, 8769

The US National Cancer Institute and the China Ministry of Health conducted an epidemiologicalsurvey for residential radon and lung cancer in Gansu Province, China [68]. This study can berecognized as one of the main studies of residential radon by pooling the analyses of European [69,70],
North American [71,72] and Chinese [73] residential case-control studies. They used alpha track
detectors, but the monitors were proved to be inﬂuenced by thoron and overestimated radon
concentrations [74]. Thereafter radon measurements were made with the above mentioned improved
detectors, discriminating two radon isotopes [56]. Remarkably high thoron levels were observed inthese areas. This ﬁnding suggests two key points, as follows: (1) their previous radon data and thelung cancer risk were incorrect; (2) the thoron contribution to radiation exposure will be importantin those areas. Another Gansu survey was conducted with simultaneous measurements of radon,
thoron and thoron progeny [75]. Correlation analyses were made among three activity concentrations.
There was no correlation whenever any two concentrations were chosen. This means that thesethree concentrations are so independent that it is diﬃcult to estimate one concentration from theother. If the thoron dose needs to be considered, direct measurement of thoron progeny is required.
This further implies that thoron progeny concentration cannot be accurately obtained with a ﬁxed
thoron equilibrium factor.
Simultaneous measurements of radon, thoron and thoron progeny were made in other provinces
close to Gansu province, namely Shanxi and Shaanxi provinces [57]. From the topographical andgeological points of view, the same radiological features were obtained. Compared to thoron
concentrations, thoron progeny concentrations were so low that it resulted in small thoron equilibrium
factors (arithmetic mean = 0.01). Tokonami [36] evaluated the inﬂuence on the risk estimate ofmisleading radon data. Annual eﬀective doses due to radon and thoron were estimated in the UNSCEAR
manner. Comparison of the annual eﬀective dose was made between misleading radon concentrations
and modiﬁed, i.e., to achieve correct radon concentrations. Misleading radon concentrations resulted
in an arithmetic mean of 6.4 mSv, whereas correct ones gave 1.7 mSv. When the contribution of thoron
was included, the total dose was calculated to be 2.4 mSv. A series of these ﬁndings revealed that theGansu study gave incorrect or misleading lung cancer risk estimates.
Yangjiang, Guangdong province, is famous for being one of the areas with the highest backgroundradiation in the world. Kudo et al. [55] demonstrated how residents there are being exposed to naturalradiation. As monazite sands are widely distributed in this area, high gamma dose rates are often
observed. However, there is less information on internal exposure, particularly due to radon andthoron. Based on collected data on these activity concentrations using the UNSCEAR method, annual
eﬀective doses due to radon and thoron progenies were estimated to be 3.1 (SD = 2.0) mSv and2.2 (SD = 2.5) mSv, respectively. This revealed that indoor thoron and its progeny levels were fairly
high and even thoron exposures are not negligible compared to radon exposures.
Kovacs [58] summarized radon and thoron surveys in Hungary. Dwellings and workplaces weresurveyed with passive radon-thoron discriminative monitors. The monitors were placed 15–30 cm
from the wall. Table 2 gives examples of thoron concentrations observed in underground bauxite
mines. It was concluded that the dose contribution from thoron progeny was not negligible considering
all the data and consequently further surveys of thoron progeny would be required for accurate
dose assessment.
Omori et al. [59] presented radon, thoron and progeny concentrations for dwellings in Kerala,
India. Their study area was classiﬁed into high (3–5 mGy y−1 ) and low (1 mGy y−1 ) backgroundradiation areas, respectively. In a six-month measurement, it was found that there was no majordiﬀerence between the two areas. The geometric mean of the annual eﬀective dose due to radon andthoron was estimated to be 0.10 and 0.44 mSv, respectively. The internal dose derived from thoron
progeny is more signiﬁcant than that from radon. However, the doses were quite small and the external
dose can be regarded as the major contributor in Kerala.
Omori et al. [27] also conducted long-term measurements of indoor radon, thoron and thoron
progeny concentrations in Odisha, India. They revealed that radon and thoron concentrations diﬀer by

13

IJERPH 2020, 17, 8769

one order of magnitude whereas thoron progeny concentrations were nearly constant throughout thewhole year. Thoron and its progeny concentrations were higher than those in Kerala. Exposure tothoron is equal to or exceeds exposure to radon in internal doses. The internal dose from radon andthoron was comparable to the external dose.
In Ireland, indoor concentrations of radon, thoron and its progeny were measured in 205 dwellings
during the period 2007–2009 [60]. Radon activity concentration ranged from 4 to 767 Bq m−3 withan arithmetic mean of 75 Bq m−3 . Based on these concentrations and the UNSCEAR approach,the corresponding estimated annual eﬀective doses are 0.1 (min), 19.2 (max) and 1.9 (mean) mSv. On theother hand, the estimated annual eﬀective doses corresponding to thoron progeny concentrationsare 2.9 (max) and 0.35 (mean) mSv with the dose conversion factor based on the two dosimetricmodels [39,40]. Although the dose from thoron tends to be negligible in most cases worldwide,
it should be noted that in some dwellings in this study the annual dose from thoron progeny exceededthat from radon. This result is the ﬁrst case where two annual eﬀective doses from radon and thoron
were measured on a nationwide scale in Europe.
Nyambura et al. [61] carried out indoor radon, thoron and thoron progeny surveys in several
diﬀerent types of houses in Kilimambogo, Kenya, and thereafter assessed the annual eﬀective dose
attributed to inhalation of their progeny. Housing structure was classiﬁed into three categories,
i.e., mud, metal and stone-walled houses. The highest mean thoron and its progeny concentrations
were observed in mud-walled houses with 195 and 11.5 Bq m−3 , respectively, whereas the highest radon
concentration was found in stone-walled ones with 75 Bq m−3 . Assessing the annual eﬀective dose,the highest was given by mud-walled houses with 0.9 (min), 8.5 (max) and 3.7 (mean) mSv, respectively.
Activity concentrations of thoron and its progeny were measured in 450 houses from 2002 to2004 in Korea [62]. The annual arithmetic and geometric means of thoron concentration were 40.4
and 10.7 Bq m−3 , respectively. The annual arithmetic and geometric mean were 0.89 and 0.60 Bq m−3 ,respectively. High thoron concentrations were observed in Korean-style houses built with mud block.
The average annual eﬀective dose due to inhalation exposure to thoron and its progeny was estimatedto be 0.25 mSv.
Indoor thoron concentrations were measured in 300 houses for one year, from December 2008 to
December 2009 in Macedonia. using passive radon-thoron discriminative monitors [63]. They were
deployed at a distance of more than 50 cm from walls. The geometric means of indoor thoron
concentration in winter, spring, summer and autumn were obtained as 39 (3.4), 32 (2.8), 18 (2.8) and
31 Bq m−3 (2.9), respectively. Seasonal variations of thoron appear to be smaller than those of radon.
Indoor thoron concentrations in 50 houses were measured in the Metropolitan Zone of Mexico
City using a passive electret system [64]. The annual arithmetic and geometric means of indoor thoron
concentration were estimated to be 82 and 55 Bq m−3 , respectively, ranging from 8 to 234 Bq m−3 . As tothe seasonal variation, the lowest value was found in summer.
Thoron progeny concentrations, namely equilibrium equivalent thoron concentrations (EETCs),
were measured in 2900 houses, Netherlands [65]. The arithmetic mean of EETC was 0.64 Bq m−3 .
Thoron progeny concentrations show correlations with year of construction and smoking behavior.
A pilot study was also conducted to determine the relationship between the exhalation of thoron andthe concentration of thoron progeny in the room. The authors pointed out that thoron might be a more
important contributor to the population dose in other regions with low radon levels.
A limited number of measurements were carried out about 1 m away from any wall and 1.5 m
above the ﬂoor in various environments in Slovenia using passive radon-thoron discriminative
monitors [66]. Thoron and radon concentrations in 35 elementary schools ranged from 21 to 368 and
40 to 4609 Bq m−3 , respectively. The authors pointed out that there was a weak correlation between the
two activity concentrations though both of them followed a lognormal distribution.
Results of the ﬁrst investigation on indoor radon, thoron and their progeny concentrations were
given in 25 primary schools of Republic Srpska [41]. For their measurements, Japanese and Indian
techniques were introduced in the survey. The monitors were deployed at 10 cm distance from the14

IJERPH 2020, 17, 8769

wall. A weak correlation was found between radon and thoron concentrations as well as thoron andthoron progeny concentrations.
Gulan et al. [39] carried out indoor radon, thoron and their progeny survey in scattered locations
around Kosovo. Estimated arithmetic mean values of concentrations in 48 houses are 122 Bq m−3 forradon and 136 Bq m−3 for thoron. This might be attributed to building materials involving bricks,
sand and stones from the local area where 232 Th concentration in soil is higher than that of 226 Ra.
Simultaneous long-term measurements of radon, thoron and their progeny were conducted in 40
rural houses in Serbia [42]. The EETC was found to be relatively higher than the worldwide averagevalue. Signiﬁcant positive correlation between thoron and EETC was found, whereas there was no
signiﬁcant correlation between radon and EERC.
Recently, a high natural background radiation area (HNBR) due to terrestrial radiation has beenreported in West Sulawesi, Indonesia [76]. EETC was measured using the thoron progeny monitor
shown in Figure 4 in a total of 45 dwellings [67]. The EETC ranged from 4 to 40 Bq m−3 and the annual
eﬀective dose due to thoron inhalation was reported to be 5.1–17.7 mSv.
Future authors should discuss these results and how they can be interpreted from the perspectiveof previous studies and working hypotheses. The ﬁndings and their implications should be discussed
in the broadest context possible. Future research directions may also be highlighted.
6. Conclusions
As thoron is a very short half-lived radionuclide, though it is an isotope of radon, it is not easy tomeasure its activity in air and consequently to assess the resulting dose in the same manner as for radon.
Nationwide indoor radon surveys have been conducted in many countries. The annual eﬀective dose
for the public is calculated using the indoor radon concentration and an equilibrium factor for radon.
The equilibrium factor of radon is typically 0.4 but such an approach is not applicable or meaningful
in the case of thoron. The spatial distribution of thoron is so unique that a single value of thoron
concentration cannot be given even in a room, due to the short half-life of less than 1 min. Thus, thoron
concentrations should not be used for radiation protection purposes because the thoron concentration
varies widely with space. Therefore, a direct measurement of thoron progeny concentration will be
more eﬀective and useful whereas several assumptions are required in the measurement techniquespresented in this paper. As another approach, the surface exhalation rate of thoron may be an index
for thoron dose assessment. Although thoron was underestimated in the past, recent ﬁndings haverevealed that reassessment of risks due to radon exposure may need to take the presence of thoron
into account.
Funding: This research was funded by JSPS KAKENHI, grant number JP18KK0261 and JP20H00556.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleTransition of Radioactive Cesium Deposition in Reproductive
Organs of Free-Roaming Cats in Namie Town, Fukushima
Yohei Fujishima 1 , Yasushi Kino 2 , Takumi Ono 2 , Valerie Swee Ting Goh 3 , Akifumi Nakata 4 , Kentaro Ariyoshi 5 ,Kosuke Kasai 3 , Tadashi Toyoda 6 , Toru Akama 7 , Hirofumi Tazoe 8 , Masatoshi Yamada 9 , Mitsuaki A. Yoshida 10
and Tomisato Miura 11
1

2

3

4

5

6
7

8

Citation: Fujishima, Y.; Kino, Y.; Ono,T.; Goh, V.S.T.; Nakata, A.; Ariyoshi,

910K.; Kasai, K.; Toyoda, T.; Akama, T.;
Tazoe, H.; et al. Transition of

11

Radioactive Cesium Deposition in
Reproductive Organs of*Department of Radiation Biology, Tohoku University School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai,
Miyagi 980-8575, Japan; yohei.fujishima@med.tohoku.ac.jp
Department of Chemistry, Tohoku University Graduate School of Science, 6-3 Aramaki Aza-Aoba, Aoba-ku,
Sendai, Miyagi 980-8578, Japan; yasushi.kino.e5@tohoku.ac.jp (Y.K.); takumi.ono.s4@dc.tohoku.ac.jp (T.O.)
Department of Bioscience and Laboratory Medicine, Hirosaki University Graduate School of Health Sciences,66-1 Hon-cho, Hirosaki, Aomori 036-8564, Japan; h19gg801@hirosaki-u.ac.jp (V.S.T.G.);
kokasai@hirosaki-u.ac.jp (K.K.)
Department of Pharmacy, Faculty of Pharmaceutical Science, Hokkaido University of Science, Sapporo,
7-Jo 15-4-1 Maeda, Teine, Sapporo, Hokkaido 006-8590, Japan; nakata_a@hus.ac.jp
Integrated Center for Science and Humanities, Fukushima Medical University, 1 Hikariga-oka,
Fukushima 960-1295, Japan; ariyoshi@fmu.ac.jp
Toyoda Animal Hospital, 402-7 Kanairo, Nihonmatsu, Fukushima 964-0915, Japan; tadashit@violin.ocn.ne.jp
Akama Industry Co., Ltd., 259-3 Babauchi, Kakura, Namie, Fukushima 979-1536, Japan;
kra9791536@yahoo.co.jp
Department of International Cooperation and Collaborative Research, Institute of Radiation Emergency
Medicine, Hirosaki University, 66-1 Hon-cho, Hirosaki 036-8564, Japan; tazoe@hirosaki-u.ac.jp
Central Laboratory, Marine Ecology Research Institute, 300 Iwawada, Onjuku, Isumi, Chiba 299-5105, Japan;
m-yamada@kaiseiken.or.jp
Institute of Chromosome Life Science, 11-5-409, Fukuokachuo 2-Chome, Fujimino-shi,
Saitama 356-0031, Japan; mtak_yoshidad1955@axel.ocn.ne.jp
Department of Risk Analysis and Biodosimetry, Institute of Radiation Emergency Medicine,
Hirosaki University, 66-1 Hon-cho, Hirosaki, Aomori 036-8564, Japan
Correspondence: tomisato@hirosaki-u.ac.jp; Tel./Fax: +81-172-39-5966

Free-Roaming Cats in Namie Town,
Fukushima. IJERPH 2021, 18, 1772.
https://
doi.org/10.3390/ijerph18041772
Academic Editor: Paul B. Tchounwou
Received: 31 December 2020
Accepted: 7 February 2021
Published: 11 February 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional afﬁliations.

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.

Abstract: We investigated the internal contamination by radioactive cesium associated with the
FDNPP accident, in the testes or uterus and ovaries of free-roaming cats (Felis silvestris catus),which were protected by volunteers in the Namie Town, Fukushima. A total of 253 samples (145 testes
and 108 uterus and ovaries) obtained from adult cats and 15 fetuses from 3 pregnant female catswere measured. Free-roaming cats in Namie Town had a higher level of radioactive contaminationin comparison to the control group in Tokyo, as the 134 Cs + 137 Cs activity concentration ranged
from not detectable to 37,882 Bq kg−1 in adult cats. Furthermore, the radioactivity in the fetuses
was almost comparable to those in their mother’s uterus and ovaries. The radioactivity was also
different between several cats protected in the same location, and there was no signiﬁcant correlation
with ambient dose-rates and activity concentrations in soil. Moreover, radioactive cesium levels incats decreased with each year. Therefore, it is likely that decontamination work in Namie Town
and its surroundings could affect radioactive cesium accumulation, and thus possibly reduce theinternal radiation exposure of wildlife living in contaminated areas. It is hence necessary to continue
radioactivity monitoring efforts for the residents living in Namie Town.
Keywords: Fukushima; free-roaming cat; radioactive cesium; reproductive organ; internal
contamination

This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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IJERPH 2021, 18, 1772. https://doi.org/10.3390/ijerph18041772

https://www.mdpi.com/journal/ijerph

IJERPH 2021, 18, 1772

1. Introduction
After the accident in the TEPCO Fukushima Daiichi Nuclear Power Plant (FDNPP),
the surrounding areas were contaminated by large amounts of released radionuclides [1,2].
A 20-km radius around the FDNPP was initially established as a restricted zone to avoid
unnecessary radiation exposure to residents. As the evacuation order was issued with noadvanced warning, all residents living within the 20-km radius had to evacuate immediately without packing and were not allowed to bring along their companion animals
during evacuation. Emergency animal shelters were launched in Iino Town, Fukushima
Prefecture in April 2011 and in Miharu Town, Fukushima Prefecture in October 2011, to rescue companion animals left behind at the time of evacuation. Large-scale trap and rescue
operations for cats were also performed several times by the Ministry of Environment, local government, and local veterinary medical association. Despite multiple efforts to rescue
abandoned companion animals, cats (Felis silvestris catus) in particular have been reproducing in the restricted zones and Namie Town [3]. Since September 2013, volunteers in Namie
Town are managing abandoned (now free-roaming) cats from uncontrolled reproduction
and possible disruption to the area’s ecosystem, using the “Trap-Neuter-Vaccinate-Return(TNVR) [4]” program.
With regards to radiation, although the ambient dose-rates are gradually decreasing,prolonged effects of chronic low-dose exposure on animals are expected to be seen in
the coming years. Therefore, by assessing biological effects from radioactive substances,
we are able to understand any possible health effects caused by radiation. To date, several
species of animals were evaluated (livestock bulls [5], wild boars [6–8], wild Japanesemonkeys [9–11], wild rodents [12–14] and freshwater ﬁsh [15–17]) around the evacuation
zone of the FDNPP. Furthermore, some studies [18] suggested that some negative biologicaleffects seen in wild animals were likely caused by the release of radionuclides from the
FDNPP accident.
Decontamination efforts gradually started from October 2013 to remove radioactive
substances released by the FDNPP accident, such that the impact of environmental pollution and radiation exposure on human health and the surrounding environment could
be reduced. For example, decontamination work in urban areas involves the removalof contaminated topsoil (0–5 cm) and replacing the surface with non-contaminated soil.
As a result, evacuation orders in some parts of Namie Town were able to be lifted on
31 March 2017, due to low ambient dose-rates after decontamination. However, there arefewer reports focusing on the biological effects before and after decontamination work.
Moreover, in existing research, the deposition of the radioactive substances in wild animals
was not studied in urban areas. Although radioactive substances were heterogeneously
distributed, detailed surveys of privately owned land would be difﬁcult in urban areas
when evacuated residents return in the future.
Radioactive substances released by the FDNPP accident includes radioisotopes ofiodine (131 I, 132 I and 133 I), cesium (134 Cs, 136 Cs and 137 Cs), tellurium (132 Te), and inert
gases (such as 133 Xe) [19,20]. These radionuclides can contribute to ambient dose-rates
and be potential health risks immediately after the accident. Among these radionuclides,
radioactive cesium has longer half-lives (134 Cs, t1/2 = 2.06 years; 137 Cs, t1/2 = 30.1 years),
and are most likely the major contributors to radioactive contamination from 2013 to 2016.
Hence, in this study, we monitored radioactive cesium (134 Cs and 137 Cs) derived fromthe FDNPP accident, in free-roaming cats caught in urban areas. We also measured theambient dose-rates and soil cesium levels to verify the effectiveness of decontamination
work and to evaluate how decontamination work changes the deposition of radioactive
cesium in animals. In addition, we also evaluated feline leukemia virus (FeLV) and feline
immunodeﬁciency virus (FIV) infections in free-roaming cats, as they are among the mostcommon infectious diseases in domestic cats and are known to cause immunosuppression.

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2. Materials and Methods
2.1. Animal Collection
Free-roaming cats in Namie Town were caught in humane live traps from September
2013 for TNVR [4]. Through surgical castration or ovariohysterectomy, reproductive organs,such as testes or uterus and ovaries, were extracted. In this study, we analyzed 253 samples(145 testes and 108 uterus and ovaries) from free-roaming cats rescued in October 2013
to December 2016 from 18 areas in Namie Town (Figure 1, Table 1). As a control, 10 samples (5 testes and 5 uterus and ovaries) from spayed and neutered free-roaming cats inTama-area, Tokyo were also analyzed (Figure 1, Table 1). Samples were stored at –20 ◦ C,
until radioactivity measurements were performed.

Figure 1. Sampling areas of free-roaming cats protected in Namie Town, Fukushima, and Tama area, Tokyo. The magniﬁed
map shows Namie Town and the sampling areas [(A) Tsushima, (B) Murohara, (C) Suenomori, (D) Tatsuno, (E) Karino,(F) Tajiri, (G) Obori, (H) Kakura, (I) Midorigaoka, (J) Uenohara, (K) Sakata, (L) Kawazoe, (M) Ushiwata, (N) Nishidai,(O) Gongendo, (P) Hiwatashi, (Q) Takase and (R) Kiyohashi], as well as the TEPCO Fukushima Daiichi Nuclear Power Plant(FDNPP). The maps were modiﬁed shapeﬁles from the National Land Numerical Information download service (data wasretrieved from http://nlftp.mlit.go.jp/ksj/index.html on 5 February 2016). The heat map shows the ambient dose-rates on
7 November 2014 provided by the Nuclear Regulation Authority 9th airborne monitoring survey (data were retrieved fromhttp://radioactivity.nsr.go.jp/ja/list/362/list-1.html on 5 February 2016).

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IJERPH 2021, 18, 1772

Table 1. Locations and decontamination status of sampling areas.
GPS Location
Latitude (◦ )Longitude (◦ )Sampling Areas

Distance from
F1-NPP (km)Decontamination
Status †Namie,
Fukushima(A) Tsushima(B) Murohara(C) Suenomori(D) Tatsuno(E) Karino(F) Tajiri(G) Obori(H) Kakura(I) Midorigaoka(J) Uenohara(K) Sakata(L) Kawazoe(M) Ushiwata(N) Nishidai(O) Gongendo(P) Hiwatashi(Q) Takase(R) Kiyohashi

37◦ 33 30.8 N
37◦ 30 24.4 N
37◦ 28 56.9 N
37◦ 30 40.3 N
37◦ 30 18.1 N
37◦ 29 10.0 N
37◦ 28 38.0 N
37◦ 29 59.4 N
37◦ 29 26.7 N
37◦ 29 29.0 N
37◦ 30 10.5 N
37◦ 29 44.1 N
37◦ 29 11.3 N
37◦ 30 08.1 N
37◦ 29 48.2 N
37◦ 29 20.5 N
37◦ 28 57.3 N
37◦ 29 54.9 N

140◦ 45 04.4 E
140◦ 56 11.0 E
140◦ 56 37.0 E
140◦ 56 40.6 E
140◦ 57 32.9 E
140◦ 57 18.0 E
140◦ 57 25.3 E
140◦ 57 47.7 E
140◦ 57 41.5 E
140◦ 58 00.8 E
140◦ 58 39.1 E
140◦ 58 53.7 E
140◦ 58 37.4 E
140◦ 59 31.3 E
140◦ 59 32.4 E
140◦ 59 34.0 E
141◦ 00 01.8 E
141◦ 00 59.5 E

29.1
12.6
10.3
12.5
11.2
9.8
9.0
10.5
9.8
9.6
10.1
9.3
8.6
9.5
8.9
8.1
7.2
8.5

Non-decontaminatedDecontaminatedNon-decontaminatedNon-decontaminatedDecontaminatedDecontaminatedNon-decontaminatedDecontaminatedDecontaminatedDecontaminatedDecontaminatedDecontaminatedNon-decontaminatedDecontaminatedDecontaminatedDecontaminatedDecontaminatedDecontaminated

Tama area,Tokyo

Chofu Airport *35◦ 39 58.0 N

139◦ 31 54.0 E

236.8

–

* The nearest monitoring post from the sampling point (data was retrieved from https://radioactivity.nsr.go.jp/map/ja/download.html on
15 March 2017). † This column represents the decontamination status of each sampling point as of 10–11 September 2016.

2.2. Tests for FeLV and FIV
To evaluate FeLV and FIV, blood from the cephalic antebrachial vein was used. Viral infections were detected with commercial immunochromatography kits of Checkman
FeLV (Kyoritsu Seiyaku Corporation/Adtec, Tokyo, Japan) and Checkman FIV (Kyoritsu
Seiyaku Corporation/Adtec, Tokyo, Japan).
2.3. Ambient Dose-Rate Measurements
Ambient dose-rates were measured at 4–5 points in a 20 m2 area centered aroundthe location, where the feline trap was installed on 30–31 July 2014, 22–23 July 2015,
and 10–11 September 2016, using a NaI(Tl) scintillation survey meter (TCS-171B, Hitachi
Aloka Medical, Ltd., Tokyo, Japan). The measurements were expressed as micro-grays
per hour at 1 m above the ground with the time constant of the survey meter set to
10 s. Measurements were recorded after a minimum wait of 30 s for the readings to bestabilized. The ambient dose-rate in Tama area was referenced from the nearest monitoring
post data provided by Nuclear Regulation Authority, Japan (data was retrieved fromhttps://radioactivity.nsr.go.jp/map/ja/download.html on 15 March 2017).
2.4. Measurements of Activity Concentrations in Reproductive Organ and Soil Samples
For reproductive organs, samples were homogenized in separate plastic containers(U-8 container, SANPLATEC Co., Ltd., Osaka, Japan) after thawing. As for the soil samples,
ﬁve surface soil samples of 5 cm depth were collected at each sampling point. The soil
samples were completely dried at 120 ◦ C, for 20 h before measurement. Each sample wastransferred into separate U-8 plastic containers. The weight and height of the samples in
the U-8 container was measured in order to calculate the sample density.

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IJERPH 2021, 18, 1772

2.5. Gamma-Spectrometry
The activity concentration for the collected samples was determined by gamma-ray
spectrometry, using a hyperpure germanium (HPGe) detector (ORTEC GEM-40190, SEIKOEG&G Co., Ltd., Tokyo, Japan), as previously shown by Fukuda et al. [21]. 134 Cs and
137 Cs were detected using 604.6 and 795.8 keV gamma-ray energies, respectively, to satisfy measurement uncertainty from counting statistics to below 5% of the corresponding
activity concentration. Activity was decay-corrected to the sampling date, and activity
concentration was calculated as per kilogram of dry weight of the soil samples.
2.6. Statistics
Correlation analysis was carried out by calculating the Pearson’s product-moment
correlation coefﬁcient or Spearman’s rank correlation coefﬁcient, based on Shapiro-Wilk
normality tests. Wilcoxon rank sum test was applied to assess differences between two
groups. The results were considered statistically signiﬁcant if p-values below 0.05 wereobtained. All statistical analyses were performed using the R version 4.0.3 (R Development
Core Team, Austria) [22].
3. Results
3.1. Ambient Dose-Rates and Radioactive Cesium Activity Concentrations in Soil at Namie Town
Ambient dose-rates and radioactive cesium (134 Cs + 137 Cs) activity concentrations insoil of specimen collection sites were represented in Figure 2A (2014 vs. 2015), Figure 2B(2015 vs. 2016), Figure 2C (2014 vs. 2015), Figure 2D (2015 vs. 2016), respectively. In particular, decontamination work was performed only in 2015 and 2016. The ambient dose-rates
in Namie Town in July 2015 decreased by approximately 39%, as compared to July 2014
(Figure 2A). Comparing July 2015 and September 2016, the ambient dose-rates decreased
sharply in the decontaminated areas, with an average decrease of 62%. On the other hand,even in the areas where decontamination was not performed, the ambient dose-rates decreased moderately to an average of 38% (Figure 2B). A similar tendency was observedfor 134 Cs + 137 Cs activity concentration in soil, but its distribution was extremely heterogeneous. 134 Cs + 137 Cs activity concentration in soil at July 2015 decreased by approximately
40%, as compared to July 2014 (Figure 2C). In the decontaminated areas, 134 Cs + 137 Cs
activity concentration in soil signiﬁcantly reduced by 90% in September 2016 as comparedto July 2015. However, in areas where decontamination was not carried out, the average
decrease was 44%, and if the points where low 134 Cs + 137 Cs activity concentration wasomitted, the average rate of decrease was only 5% (Figure 2D). In addition, a strong correlation was observed between ambient dose-rate and 134 Cs + 137 Cs activity concentration insoil (2014: r = 0.67, p < 0.01; 2015: r = 0.68, p < 0.01; 2016: r = 0.60, p < 0.01).
3.2. Infection of FIV/FeLV
Immunochromatography tests for FIV and FeLV were performed on 211 cats. Fifteen
cats (7.1%) were positive for FIV antigen and 16 cats (7.6%) were positive for FeLV antibody.
Only 2 cats were positive for both FIV and FeLV antigens.
3.3. Radioactive Cesium Activity Concentration in Testes/Uterus and Ovaries
There was no macroscopic abnormality in the testes/uterus and ovaries. Gamma
spectrometry was performed in uterus and ovaries (108 samples) and testes (145 samples)of free-roaming cats captured in both non-decontaminated and decontaminated areas
in Namie Town. 134 Cs + 137 Cs activity concentration accumulated in each organ ranged
from not detectable to the maximum of 37,882 Bq kg−1 (Figure 3A). Cats from Hiwatashi,
Kiyohashi, Nishidai, Sakata, and Ushiwata areas showed low 134 Cs + 137 Cs activity concentrations of 1500 Bq kg−1 or less, while cats with high 134 Cs + 137 Cs activity concentrations
were seen in Gongendo, Uehara, Kawazoe, Midorigaoka, and especially, in Tsushima areas(Figure 3B). Moreover, 134 Cs + 137 Cs activity concentrations differed greatly even in catscaught in the same collection area. As 134 Cs + 137 Cs activity concentrations were monitored
25

IJERPH 2021, 18, 1772

in cats from October 2013 to December 2016, the half-life was approximated to 310 days
(Figure 3). On the other hand, all 10 cats from Tama area of Tokyo, which served as thecontrol area, showed radioactive cesium activity concentrations below the detection limit(16.6 Bq kg−1 , maximum 35.7 Bq kg−1 , minimum 10.6 Bq kg−1 ), and were signiﬁcantly
lower than cats in Namie Town, Fukushima (p < 0.01).

Figure 2. Ambient dose-rates and 134 Cs + 137 Cs activity concentrations in soil. Comparison ofambient dose-rates measured in (A) 2014 vs. 2015, (B) 2015 vs. 2016, and of 134 Cs + 137 Cs activity
concentrations in soil measured in (C) 2014 vs. 2015, (D) 2015 vs. 2016. Red and blue circles represent
areas that are non-decontaminated and decontaminated, respectively. Decontamination work in our
research location in Namie Town started from September 2015.

There was also no clear correlation between the areas of where the cat was captured(ambient dose-rates and 134 Cs + 137 Cs activity concentration in soil) and 134 Cs + 137 Cs
activity concentration in the reproductive organs of cats (Figure 4).

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IJERPH 2021, 18, 1772

Figure 3. Change in 134 Cs + 137 Cs activity concentrations in reproductive organs of cats, with respect to (A) date caught and(B) area caught. In panel (B), each boxplot represents its distribution and black dots shows individual 134 Cs + 137 Cs activity
concentrations in reproductive organs. N.D.; not detected.
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IJERPH 2021, 18, 1772

Figure 4. 134 Cs + 137 Cs activity concentrations in reproductive organs of cats compared with (A) ambient dose-rates and(B) 134 Cs + 137 Cs activity concentrations in soil. Grey dots represent individual 134 Cs + 137 Cs activity concentrations in
reproductive organs.

When 134 Cs + 137 Cs activity concentration in testes and uterus and ovaries werecompared, 134 Cs + 137 Cs activity concentration was higher in male than female cats (p < 0.01,
Figure 5A). In addition, some age-dependency was observed as younger male cats tended
to have a higher accumulation of radioactive cesium in their testes (Figure 5B).
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IJERPH 2021, 18, 1772

Figure 5. (A) An overall comparison and (B) a comparison with available estimated age of 134 Cs + 137 Cs activity concentrations in reproductive organs between male and female cats. Boxplot represents its distribution and black dots shows
individual 134 Cs + 137 Cs activity concentrations in reproductive organs.

3.4. Radioactive Cesium Activity Concentrations Compared between Mother and Fetuses
In this study, we were also able to compare 134 Cs + 137 Cs activity concentrations in
mother’s uterus and fetus, as three female cats (caught in February 2014) were discovered to
be pregnant while spaying. Only Case 3 (caught in Gongendo area) showed a signiﬁcantly
higher 134 Cs + 137 Cs activity concentration in the fetus than the maternal uterus. In the othertwo cases (caught in Kawazoe and Midorigaoka areas), there was no difference in 134 Cs +137 Cs activity concentration between the fetus and maternal uterus (Figure 6). There wasalso no association seen between the areas of where the cats were caught (ambient dose-rate
and 134 Cs + 137 Cs activity concentrations in the soil) and accumulated 134 Cs + 137 Cs activity
concentrations in the fetus and maternal uterus.

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IJERPH 2021, 18, 1772

Figure 6. Comparison of 134 Cs + 137 Cs activity concentrations in the cat maternal uterus and fetuses. Dashed line in Case 2
and 3 represents mean activity concentrations of fetuses.

4. Discussion
Due to the sudden evacuation orders issued to Namie Town residents after the FDNPP
accident, the evacuees had to leave their companion animals behind. Companion animals
including cats left behind at the time of the evacuation were rescued and neutered byvarious organizations [3]. However, many free-roaming cats are still found in Namie
Town and its surroundings. As evacuation orders are slowly lifting and more residents are
returning, population control of free-roaming cats is thus necessary. As proper managementof cat population control is required, a volunteer group in Namie Town is now continuing
the initial efforts previously carried out by the local government, as recommended by the
Ministry of the Environment’s Guidelines [23].
No notable deformities such as malformations or growth retardations in reproductive
organs of cats were seen with macroscopic observations. In addition, FeLV and FIV infections, which are common infectious diseases in domestic cats, were 7.1% and 7.6% respectively. In comparison to previous reports (FeLV: 0–8.1%; FIV: 0–12.8% [24–29]), FeLV and
FIV infection rates in Namie Town were very similar to other non-contaminated areas.
In Minamisoma City, dogs were reported to be aggressive and to bite humans. Their aggressiveness could be attributed to intermittent aftershocks and mental stress caused byowner abandonment as a result of immediate evacuation [30]. In contrast, cats rescued
in Namie Town were not wary of us based on personal observations. Moreover, as theinfection rates of FeLV and FIV were comparable to other general populations of domestic
cats, the health of free-roaming cats was well controlled in Namie Town.
From our results, we showed that radioactive cesium activity concentrations in reproductive organs of cats was higher than that of the control area. With regards to the
dynamics of radioactive cesium in the body, a model was proposed where radioactive
cesium absorbed in the body through the digestive tract was transferred to visceral tissues
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IJERPH 2021, 18, 1772

via blood and ﬁnally excreted as urine [31]. Even though reproductive organs were only
analyzed in this study, we could also expect radioactive cesium accumulation in otherunanalyzed organs. According to a report in radioactive cesium distribution in cattle
after the FDPP accident [5], activity concentrations were higher in skeletal muscle, kidney,
and liver, as compared to blood, despite individual variations. In addition, as the testis
showed the same activity concentration as the kidney and liver [5], it was thus highly
likely that high radioactive cesium would be present in the skeletal muscle of free-roamingcats. Furthermore, the activity concentration of the feline testes was higher than that of
the uterus and ovaries. Some studies also showed the same tendency in pigs and wildboars [32,33], but the underlying reason why 134 Cs + 137 Cs activity concentrations between
males and females differed so markedly remains unclear. Furthermore, age effect was
not observed on the cesium concentration in cats, although some young cats showed
high radioactive cesium concentrations in both testes and uterus and ovaries. Wada et al.
reported that the biological half-life of the 137 Cs in cats was 30.8 days [34]. In this study,
the youngest cat analyzed was 3-months old (3 biological half-lives elapsed). Therefore,
we speculated that a high amount of radioactive cesium in young cats was likely notdependent on mother–fetus transition.
A slight correlation was seen when ambient dose-rates was compared with 134 Cs +137 Cs activity concentrations in reproductive organs, but no correlation was seen with
134 Cs + 137 Cs activity concentrations in the soil. The weak correlation could be due to (1)heterogeneous contamination by radioactive substances in different habitats, (2) wide homerange and movement between habitats (including movement between decontaminated andnon-decontaminated areas), and (3) uncontaminated cat food fed to rescued cats. According
to previous reports, the home range of cats could range from several hundred meters toseveral kilometers [35–38], suggesting that extreme outliers of highly contaminated catscaught in some areas (e.g., Uenohara and Gogendo areas in 2014) could be due to cat
movement. Furthermore, as decontamination work was carried out in each administrative
district, radioactive cesium accumulation in the body could also be affected when a cat
moves between non-decontaminated and decontaminated areas.
Moreover, the transfer of radionuclides from mother to fetus was one of the major
concerns of exposure to internal radiation. As radioactive cesium was also detected in thefetus, this ﬁnding suggests that cesium was able to transfer freely from mother to fetus.
5. Conclusions
Since October 2013, we have been continuously monitoring radioactive cesium activity
concentrations in reproductive organs of free-roaming cats in Namie Town. We showedthat radioactive cesium levels decreased with each year. Therefore, it is likely that decontamination work in Namie Town and its surroundings could affect radioactive cesium
accumulation, and thus possibly reduce the internal radiation exposure of wildlife living
in contaminated areas. These ﬁndings suggest that analyzing radioactive substance deposition in animals and soil is useful to evaluate the effectiveness of decontamination workand to monitor the environment of urban areas.
Author Contributions: Y.F., T.T., and T.M. designed the study; T.A. and T.T. protected free-roaming
cats; T.T. performed tests for FeLV and FIV; Y.F., V.S.T.G., A.N., K.A., K.K., and T.M. measured theambient dose rate, and collected the soil samples; Y.F., Y.K., T.O., H.T., and M.Y. conducted the
gamma spectrometry; Y.F., V.S.T.G., and T.M. processed the data; Y.F., V.S.T.G., M.A.Y., and T.M.
wrote the manuscript; M.A.Y. and T.M supervised the study. All authors reviewed and approved theﬁnal manuscript.
Funding: This work was supported in part by the Environmental Radioactivity Research Network
Center (F-19-31).
Institutional Review Board Statement: Ethical review and approval were waived for this study,as this study was approved by Namie Town local government and conducted by veterinarians and a
volunteer group as part of a large-scale trap and rescue operations for cats.
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Informed Consent Statement: Not applicable.
Data Availability Statement: The data presented in this study are available on request from thecorresponding author.
Acknowledgments: The authors express our deep appreciation to the local government in Namie
Town, Fukushima Prefecture, Japan. We are also grateful to Sanae Akama for her continuous care andprotection of free-roaming cats in Namie Town. We also thank Ikue Asari, Naomi Sasaki, Yuki Sato,and other members of the laboratory staff for their technical and secretarial support.
Conﬂicts of Interest: The authors have no conﬂict of interest to disclose.

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33

International Journal ofEnvironmental Researchand Public Health
ArticleLong-Term Measurements of Radon and Thoron Exhalation
Rates from the Ground Using the Vertical Distributions ofTheir Activity Concentrations
Oumar Bobbo Modibo 1,2 , Yuki Tamakuma 1,3 , Takahito Suzuki 1 , Ryohei Yamada 1 , Weihai Zhuo 4 ,Chutima Kranrod 3 , Kazuki Iwaoka 5 , Naofumi Akata 3 , Masahiro Hosoda 1,3 and Shinji Tokonami 3, *
1

2
3

4

5

*

Citation: Modibo, O.B.; Tamakuma,
Y.; Suzuki, T.; Yamada, R.; Zhuo, W.;
Kranrod, C.; Iwaoka, K.; Akata, N.;
Hosoda, M.; Tokonami, S. Long-Term
Measurements of Radon and Thoron
Exhalation Rates from the Ground
Using the Vertical Distributions ofTheir Activity Concentrations.
IJERPH 2021, 18, 1489.
https://doi.org/10.3390/
ijerph18041489
Academic Editor: Paul B. Tchounwou

Department of Radiation Science, Graduate School of Health Sciences, Hirosaki University, 66-1 Honcho,
Hirosaki, Aomori 036-8564, Japan; h19gg701@hirosaki-u.ac.jp (O.B.M.); tamakuma@hirosaki-u.ac.jp (Y.T.);
suzuki-takahito@fujielectric.com (T.S.); yamada.ryohei@jaea.go.jp (R.Y.); m_hosoda@hirosaki-u.ac.jp (M.H.)
Nuclear Technology Section, Institute of Geological and Mining Research, P.O. Box 4110, Yaoundé, Cameroon
Institute of Radiation Emergency Medicine, Hirosaki University, 66-1 Honcho, Hirosaki,
Aomori 036-8564, Japan; kranrodc@hirosaki-u.ac.jp (C.K.); akata@hirosaki-u.ac.jp (N.A.)
Institute of Radiation Medicine, Fudan University, 2094 Xietu Road, Shanghai 200032, China;
whzhuo@fudan.edu.cn
National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage,
Chiba 263-0024, Japan; iwaoka.kazuki@qst.go.jp
Correspondence: tokonami@hirosaki-u.ac.jp; Tel.: +81-172-39-5404

Abstract: A long-term measurement technique of radon exhalation rate was previously developed
using a passive type radon and thoron discriminative monitor and a ventilated type accumulationchamber. In the present study, this technique was applied to evaluate the thoron exhalation rate
as well, and long-term measurements of radon and thoron exhalation rates were conducted for
four years in Gifu Prefecture. The ventilated type accumulation chamber (0.8 × 0.8 × 1.0 m3 )with an open bottom was embedded 15 cm into the ground. The vertical distributions of radon
and thoron activity concentrations from the ground were obtained using passive type radon-thoron
discriminative monitors (RADUETs). The RADUETs were placed at 1, 3, 10, 30, and 80 cm above
the ground inside the accumulation chamber. The measurements were conducted from autumn
2014 to autumn 2018. These long-term results were found to be in good agreement with the values
obtained by another methodology. The radon exhalation rates from the ground showed a clearlyseasonal variation. Similar to ﬁndings of previous studies, radon exhalation rates from summer toautumn were relatively higher than those from winter to spring. In contrast, thoron exhalation rates
were not found to show seasonal variation.

Received: 24 December 2020
Accepted: 30 January 2021

Keywords: exhalation rate; radon; thoron; long-term measurement; seasonal variation

Published: 4 February 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims in

1. Introduction

published maps and institutional afﬁl-Radon (222 Rn) and thoron (220 Rn) are naturally occurring radioactive gases generated
from the 238 U- and 232 Th-series. It is well known that radon and thoron are the biggest
contributors to human radiation exposure from natural sources [1]. The World HealthOrganization (WHO) has recognized them as the second largest cause of lung cancer aftersmoking [2]. Indoor and outdoor radon and thoron concentrations vary widely from place
to place depending on geological features and meteorological condition of an area (see,e.g., [3]). In general, indoor radon concentration is continuously supplied by a portionof outdoor radon, an inﬁltration rate of 10 Bq m−3 h−1 was reported [1]. In addition to
the health effect assessment due to its inhalation, outdoor radon monitoring is usefulin several scientiﬁc disciplines as a radioactive tracer. Its half-life of T1/2 = 3.82 days iscomparable to the air masses’ transit time across the major continents. Outdoor radon
monitoring serves also on earthquake forecasting, geological faults identiﬁcations or ore

iations.

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

35

IJERPH 2021, 18, 1489. https://doi.org/10.3390/ijerph18041489

https://www.mdpi.com/journal/ijerph

IJERPH 2021, 18, 1489

exploration, and environmental reprocessing in mining [4–7]. Some researchers havereported a positive correlation between outdoor radon concentration and radon exhalation
rate from the ground [8–10]. Therefore, the exhalation rates of radon and thoron, which areoften called ﬂux or ﬂux density, are useful parameters to understand human health risk
due to radon and thoron inhalation, and many researchers have reported data obtainedby ﬁeld and experimental studies [11–14]. Generally, a common technique for exhalation
rate measurement is based on placing an accumulation chamber on the ground surface
to accumulate radon gas exhaling from the ground and using radon monitor to measureradon concentration and deduce radon exhalation rate, the technique has been applied
for short- and long-term radon exhalation rate measurements [15]. However, it is difﬁcult
to evaluate both radon and thoron exhalation rates simultaneously using this method
due to short half-life of thoron (T1/2 = 55.6 s). Alternatively, Zhuo et al. [10] reported on
the long-term measurement technique of radon exhalation rate using a passive type radon
and thoron discriminative monitor and a ventilated type accumulation chamber. However,their report did not evaluate thoron exhalation rate. It was reported that thoron activity
concentrations from a source such as the materials of building walls and the ground havea unique distribution [16–19]. In the present study, long-term radon and thoron exhalation
rates from the ground were simultaneously measured for a period of four years by applying
the previously reported technique of ventilated type accumulation chamber [9]. From
the results obtained, the seasonal variations of radon and thoron exhalation rates fromthe ground were discussed.
2. Materials and Methods
2.1. Ventilated-Type Accumulation Chamber System for Measuring Radon-Thoron Exhalation
Rates from the GroundA naturally ventilated accumulation chamber (0.8 × 0.8 × 1.0 m3 ) which is a stainlesssteel box with an open bottom was embedded 15 cm into the ground on the campus of
the National Institute of Fusion Science (NIFS) located in Gifu Prefecture, Japan (N35.325◦ ,E137.168◦ ), as shown in Figure 1. Two rectangle openings (20 × 10 cm2 ) were perforated
at the upper right and lower left walls of the stainless-steel box to get air ventilation,and each opening was covered on the inside side by a ﬁber ﬁlter (Whatman® No. 41)
and the outside side by a rain/wind shelter. Thus, the change of particles (dust) outside
cannot interfere with the inside environment of the stainless-steel box as the two openings
are covered with ﬁlters. According to the report by Zhuo et al. [10], wind speed insideand outside of the ventilated accumulation chamber was monitored, and it was found thatthe inside wind speed could hardly be affected by the change of outside winds. Additionally, the air and soil conditions (pressure, temperature, relative humidity, and water
potential) monitored simultaneously inside and outside of the stainless-steel box showedthat except for the air humidity both the soil and air conditions inside and outside were
nearly the same throughout the year, and it showed that the passive radon-thoron monitor used here is not affected by air humidity [10]. The vertical distributions of radon
and thoron concentrations inside the accumulation chamber were obtained using a passive type radon-thoron discriminative monitor (RADUET, Radosys Ltd., Budapest, Hungary) [20]. The Raduets are composed of two different diffusion chambers of the same
inner volume of about 30 cm3 . The chambers are made of electroconductive plastic witha cylindrical form. The radon–thoron discrimination principle is based on the diffusion
characteristics of each chamber. Radon in the air with its longer diffusion length is able
to diffuse through an invisible air gap of one of the chambers located between its lid
and bottom. Thoron can scarcely diffuse into that chamber with such a small pathway due
to its very short half-life and lower diffusion length compared to that of radon. The second
chamber has 6 holes of 6 mm of diameter opened at the side of the chamber which allow
the diffusion of thoron as well as radon, the 6 holes are recovered by an electroconductive
sponge to block the passage of charges particulate in the diffusion chamber [20]. The detection limits for the typical measurement period (3 months) were estimated to be 3 and 14 Bq
m−3 for radon and thoron, respectively [21]. The RADUETs were placed at heights of 1, 3,
36

IJERPH 2021, 18, 1489

10, 30, and 80 cm from the ground surface inside the accumulation chamber. For laboratory
analysis, the RADUETs were exchanged every three months: spring, March–May; summer,
June–August; autumn, September–November; winter, December–February. The solid-state
track detectors (CR-39; BARYOTRAK, Nagase Landauer, Ltd., Tsukuba, Japan), whichwere installed in the RADUETs, were taken out and chemically etched for 24 h in a 6M
NaOH solution at 60 ◦ C [21]. The number of alpha tracks was counted using an optical
microscope and image analysis software (ImageJ, National Institutes of Health, Bethesda,
Maryland, USA). Radon and thoron concentrations were calculated according to the International Organization for Standardization (ISO) 16641 [22]. The conversion factors fromtrack densities of CR-39s to radon and thoron concentrations had been already evaluatedusing the radon-thoron calibration chamber in Hirosaki University [23]. Environmental
parameters of temperature, relative humidity and atmospheric pressure inside the accumulation chamber were measured continuously using a portable type meteorological monitor(TR-73U, T&D Corp., Matsumoto, Japan).

Figure 1. Photo and schematic drawing of the ventilation-type accumulation chamber system for measuring radon
and thoron exhalation rates from the ground.

2.2. Evaluation of Radon and Thoron Exhalation Rates Using the Ventilated TypeAccumulation Chamber
According to Zhuo et al. [10], the radon exhalation rate ERn (mBq m−2 s−1 ) obtainedusing the ventilated type accumulation chamber can be calculated by Equation (1).
ERn = 1000 × CRn × Zmax ×Q + λRn
3600(1)

Here, CRn is the average radon concentration at each height (Bq m−3 ), Zmax isthe height of the chamber from the ground surface (=0.85 m), Q is air exchange ratein the accumulation chamber, and λRn is the decay constant of radon (7.6 × 10−3 h−1 ). Air
exchange rate in the chamber was evaluated using carbon dioxide (CO2 ) gas and a CO2
monitor (TR-76Ui, T&D Corporation). Generally, the air exchange rate is much larger thanthe decay constant of radon. Therefore, the decay constant of radon can be neglected (Q >>λRn , Q + λRn ≈ Q).
According to the one-dimensional diffusion equation reported by Katase et al. [24],the thoron concentration CTn (z) at a height z (m) above the ground is given by Equation (2).
CTn ( Z ) = 37ETn( Q + λTn ) De 

· exp −

Q + λTn
Z
De


(2)

IJERPH 2021, 18, 1489

Here, ETn is the thoron exhalation rate from the ground (Bq m−2 s−1 ), λTn is the decay
constant of thoron (44.9 h−1 ), and De is the effective diffusion coefﬁcient in free air (1.2
× 10−5 m2 s−1 ) [25]. In this study, the following exponential regression formula wasapplied to the vertical distribution of thoron concentration in each season for the simpliﬁed
estimation of thoron concentration at 0 m.
CTn ( Z ) = a · exp(−bz)(3)

Thoron concentration at the ground surface (z = 0 m) was estimated by Equation (3).
Then, thoron exhalation rate ETn (mBq m−2 s−1 ) was evaluated by Equation (4) obtainedby substituting z = 0 into Equation (2).

ETn = 1000 × CTn,0 ×

D·( Q + λTn )
3600

(4)

Here, CTn,0 is the thoron activity concentration at 0 m (Bq m−3 ).
2.3. Soil Parameters and Its Activity Concentrations of 226 Ra and 228 Ra
Five soil core samples from the ground surface to 5 cm depth were collected using
a stainless-steel soil sampler, which had a volume of 100 mL [26]. Dry bulk density, soil
particle density, porosity, and soil textures were evaluated after drying samples for 24 h
at 110 ◦ C. The dry bulk density ρb was calculated as the mass of the dried soil divided by
the soil volume. The soil particle density ρs was evaluated using a speciﬁc gravity bottle
according to the test procedure of Japan Industrial Standards (JIS) A1202 [27]. The porosity ε was calculated by ε = 1−ρb /ρs . Soil particle size distribution was evaluated using
a standard stainless-steel sieve for 0.075–2.0 mm particle size range and the sedimentation analysis for particles below 0.075 mm was made according to the test procedure of
JIS A1204 [28] to determine the soil textures of the samples. The percentages of sand,silt, and clay for each soil sample were evaluated using the sample particle size distribution curves.
The activity concentrations of 226 Ra and 228 Ra were evaluated using a high-purity
germanium semiconductor detector (GEM-100210, ORTEC, USA) with a relative efﬁciencyof 30%, 1.85 keV energy resolution (FWHM) at 1.33 MeV of 60 Co. The efﬁciency calibrationof the detector was made using the standard volumetric sources which are contained
109 Cd, 57 Co, 139 Ce, 51 Cr, 85 Sr, 137 Cs, 54 Mn, 88 Y, and 60 Co supplied by Japan Radioisotope
Association. The detector was enclosed in a shielding made out of compacted lead of 10 cmof thickness. Each soil sample was enclosed in a cylindrical polypropylene container (U8type container, 100 cm3 ) after drying for 24 h at 110 ◦ C. The prepared soil sample was thenenclosed in an air-tight container for 40 days to allow radioactive equilibrium between
226 Ra and 222 Rn to be reached. The measurement time was set as 80,000 s. In this study,
the weighted average concentration of 214 Pb and 214 Bi were used as the 226 Ra concentrationin the soil samples by counting photons in the photoelectric peak channels of 352 keV for
214 Pb and 609 keV for 214 Bi. 228 Ra was measured by counting photons in the photoelectricpeak channel of 911 keV for 228 Ac. The uncertainty for the activity concentration was
evaluated taking into account the uncertainties of the counts for the sample and background.
Coincidence summing, self-attenuation and decay corrections were applied using software(Gamma Studio, SEIKO EG&G, Tokyo, Japan).
2.4. Comparison of the Exhalation Rates with the Other Methods
2.4.1. Accumulation Chamber with Scintillation Cell
The stainless-steel accumulation chamber was set on the ground surface. Radongas exhaled from the ground was accumulated for 1.5 to 3 h. Then, the radon gas inside
the accumulation chamber was collected into a scintillation cell (Pylon 300A, Pylon Electrics,
Inc., Toronto, Ontario Canada) at a sampling ﬂow rate of 0.5 L min−1 and a samplingtime of 5 min. After 3.5 h, the alpha counts from radon gas in the scintillation cell were38

IJERPH 2021, 18, 1489

measured using a portable radiation monitor (AB-5, Pylon Electrics, Inc., Toronto, Ontario
Canada) [29]. The radon exhalation rate by grab sampling can be calculated by applying
Equation (5).
( N − Nb ) · CF · V · λRn
ERn =
(5)
S · [1 − exp(−λRn · t)]Here, N and Nb are the count rates of the sample and background (cpm), CF isthe conversion factor from count rate to radon concentration (27.0 Bq m−3 cpm−1 ) [30],
V is the volume of the accumulation chamber (1.4 × 10−2 m3 ), λRn is the decay constantof radon (2.1 × 10−6 s−1 ), S is the area under the accumulation chamber (9.9 × 10−2 m2 ),and T is the accumulation time (s).
2.4.2. In Situ Radon and Thoron Exhalation Rate Monitor
Radon and thoron exhalation rates from the ground was also measured with an in-situ
radon and thoron exhalation rate monitor (MSZ). The details of the method have been
described by Saegusa et al. [31]. The monitor was composed of an accumulation chamber(volume, 13 L), a ZnS(Ag) scintillation detector with an aluminized mylar sheet, a lightguide, a photomultiplier tube, a pulse counting part and scaler, and a timer. The area ofan acrylic board coated with ZnS(Ag) scintillator was 0.12 m2 . Count rates were recorded
over consecutive 30-s intervals during a total recording period of 30 min after the monitor
was set up on the ground. The conversion factors from count rates of 10 min and 30 min toexhalation rates of radon and thoron were 0.521 ± 0.040 mBq m−2 s−1 cpm−1 and 18.1 ±3.2 mBq m−2 s−1 cpm−1 , respectively. The measurement uncertainties for radon and thoron
exhalation rates using the MSZ have been reported as ~20% and ~6%, respectively [11].
3. Results and Discussion
3.1. Physical Parameters of Soil and 226 Ra and 228 Ra Activity Concentrations at the Study Site
The percentages of sand, silt and clay for each soil sample collected at the study sitewere evaluated as 63 ± 4%, 16 ± 2%, and 21 ± 3%, respectively. As a result, the texturalclass of all soil samples was decided as sandy clay loam (SCL) based on a soil texture
triangle. In general, the characteristics of SCL are reported to be high water retention
and low air permeability [32]. Dry bulk density, soil particle density and porosity were
evaluated as 1340 ± 19 kg m−3 , 2657 ± 27 kg m−3 , and 0.50 ± 0.07, respectively. Theseobtained values were not signiﬁcantly different from the typical values of 1300−1350 kg
m−3 for dry bulk density, 2600−2700 kg m−3 for soil particle density, and 0.3−0.6 forporosity [33]. Activity concentrations of 226 Ra and 228 Ra were evaluated to be 24.1 ± 0.4 Bq
kg−1 and 34.0 ± 0.9 Bq kg−1 , respectively. According to the UNSCEAR [1], the Japanesemean activity concentrations of 226 Ra and 228 Ra (assuming radioactive equilibrium with
232 Th) are reported as 33 Bq kg−1 and 28 Bq kg−1 , respectively. Thus, radium activity
concentrations in soil at the study site were found to be slightly lower than those of
the national mean.
3.2. Radon and Thoron Concentration in the Ventilated-Type Accumulation Chamber
An example of the vertical distribution of thoron concentration inside the ventilated
type accumulation chamber is shown in Figure 2. Thoron concentration decreased exponentially with the height above the ground surface. On the other hand, radon concentrations
inside the accumulation chamber did not depend on the height above the ground. These observations were similar to the previously reported ﬁndings [16,17,19]. The results obtainedat the 10 cm and above height from the ground were not considered in the calculationof thoron exhalation rate because the thoron concentrations at these heights were below
the lower limit of detection. Additionally, the air exchange rate of the accumulationchamber was evaluated as 0.30 h−1 which was similar to the literature [9].

39

IJERPH 2021, 18, 1489

Figure 2. Example of the vertical distribution of thoron concentration inside the ventilated type
accumulation chamber. The thoron concentration at ground level (z = 0 cm) was determined to be
416 ± 42 Bq m−3 .

3.3. Comparison of Radon and Thoron Exhalation Rates Obtained by the Present System to Those
Obtained by the Other Methods
Comparison of radon and thoron exhalation rates obtained by the ventilated-type
accumulation chamber, accumulation chamber with scintillation cell and in situ monitor are
shown in Table 1. Radon exhalation rates obtained by the passive method were in relatively
good agreement with the results measured by the accumulation chamber with scintillation
cell and in situ monitor (MSZ) taking into account the measurement uncertainty. Statisticalanalyses were conducted using the “EZR software” (Easy R) [34]. The difference was considered signiﬁcant for p < 0.05. A one-way ANOVA test was performed for the comparisonof radon exhalation rates obtained by each technique. Consequently, the radon exhalation
rate measured by the present system and those obtained by the other methods are notsigniﬁcantly different (p = 0.128). Furthermore, the thoron exhalation rate obtained by
the ventilated-type accumulation chamber in the ﬁrst measurements was also in agreementwith the result obtained by the in situ monitor (p = 0.156). However, in the second measurements, thoron exhalation rate obtained by the ventilated-type accumulation chamber
was approximately half that of the value obtained by the in situ monitor. Theoretically,
the diffusion length of thoron is reported as a few centimeters which is much shorter
than that of radon due to the short half-life of thoron. Therefore, thoron exhalation rateis considered to be more strongly affected by the soil surface condition compared withthe radon exhalation rate. Thus, it is necessary to make intercomparison experiments
repeatedly to ensure the quality of the data obtained by the present ventilated-type accumulation chamber. However, the present method can offer an easy and low-cost system forthe measurements of both radon and thoron exhalation rates, as no electric power supply
is needed and operation and maintenance are easy.

40

IJERPH 2021, 18, 1489

Table 1. Comparison of radon and thoron exhalation rates obtained by the ventilated-type accumulation chamber, accumulation chamber with scintillation cell, and in situ monitor (MSZ) method.
Intercomparison

1st measurement

2nd measurement

Methods

Radon Exhalation
Rate (mBq m−2 s−1 )Thoron Exhalation
Rate (mBq m−2 s−1 )Ventilated-type
accumulation chamber

3.6 ± 0.5797 ± 336

Accumulation chamberwith scintillation cell

4.6 ± 2.9–

In situ monitor (MSZ)
method

1.1 ± 0.1

584 ± 103

Ventilated type
accumulation chamber

4.3 ± 0.51120 ± 321

Accumulation chamberwith scintillation cell

8.8 ± 5.3–

In situ monitor (MSZ)
method

5.1 ± 1.8474 ± 177

3.4. Seasonal Variations of the Radon and Thoron Exhalation Rates
Seasonal variations of radon and thoron exhalation rates are shown in Figure 3.
The median values (range) of radon exhalation rate in spring, summer, autumn and winterwere estimated to be 3.5 ± 0.5 (2.4−5.8), 5.4 ± 1.1 (4.0−6.4), 5.6 ± 0.3 (4.0−7.1), and 3.5 ±
0.3 (2.1−4.8) mBq m−2 s−1 , respectively. The median values (range) of thoron exhalation
rates were evaluated as 614 ± 126 (159−848), 555 ± 110 (295−1110), 563 ± 395 (61−1524),
and 593 ± 138 (318−797) mBq m−2 s−1 for spring, summer, autumn and winter, respectively. Annual means of the radon and thoron exhalation rates were evaluated to be 4.5± 0.3 mBq m−2 s−1 and 581 ± 113 mBq m−2 s−1 , respectively. According to the resultsof a large-scale survey in Japan [12,35], average radon and thoron exhalation rates fromthe ground were 8.6 mBq m−2 s−1 (N = 111) and 790 mBq m−2 s−1 (N = 405), respectively.
Therefore, radon and thoron exhalation rates at the present measurement site were 52%
and 74% of the Japanese averages. Furthermore, average radon exhalation rates in summer
and autumn were higher than the annual mean. The ratio of the radon exhalation rate insummer to the radon exhalation rate in winter (or spring) is 1.5 and the ratio of the radon
exhalation rate in autumn to the radon exhalation rate in winter (or spring) is 1.6. A oneway ANOVA was performed to determine whether there are any statistically signiﬁcantdifferences between the means of each season. Consequently, it showed no statisticallysigniﬁcant difference in the average radon exhalation rate between the seasons in thisstudy (p = 0.103). However, the median values of radon exhalation rate tend to be higher
from summer to autumn and lower from winter to spring (Figure 3a). Zhuo et al. [36]reported a similar seasonal variation of radon exhalation rate from the ground in China.
Zhuo et al. [9] have also reported a negative correlation between radon exhalation rate
and precipitation. On the other hand, Hosoda et al. [12] reported that when the variation ofmoisture saturation was small, the soil temperature appeared to induce a strong effect on
the exhalation rate. However, when the variation of moisture saturation was large, the inﬂuence of moisture saturation appears to be larger than the soil surface temperature [12].
Furthermore, it has been also reported that an increase in the soil temperature markedly decreased the amount of adsorption of gases which contributed to the increase of emanationand diffusion coefﬁcients [37,38]. Precipitation data from a location near the monitoringsite were reported by the Japan Meteorological Agency [39], and cumulative precipitationsin spring, summer, autumn, and winter during the measurement period were 424, 586, 441,
and 177 mm, respectively. Additionally, their respective mean temperatures were 14.1, 25.2,
17.9, and 4.2 ◦ C. Therefore, the radon exhalation rate in winter at the measurement site
might be affected by low precipitation and temperature. On the other hand, in summer
the high temperature might affect the radon exhalation rate.
41

IJERPH 2021, 18, 1489

Figure 3. Seasonal variations of radon (a) and thoron (b) exhalation rates. The lines from top tobottom of the box-plot from top to bottom are deﬁned as maximum, third quartile (75th percentile),
median (50th percentile), ﬁrst quartile (25th percentile), and minimum values.

The statistical analysis using the one-way ANOVA test showed that there was no
signiﬁcant difference between the averages of thoron exhalation rate for the different
seasons (p = 0.982) (Figure 3b). According to the report by Prasad et al. [40], radon
and thoron exhalation rates in summer and autumn were higher than those in spring
and winter. However, the reported diffusion length of radon and thoron were a few
meters and a few centimeters, respectively [11,26]. That is, thoron exhalation rate fromthe ground would be affected by such environmental parameters as moisture saturationand temperature around the surface soil. Therefore, the soil temperature and moisturesaturation were measured continuously for three months in summer at 10 cm depth fromthe surface inside and outside of the accumulation chamber. The average surface soil
temperature inside and outside the accumulation chamber were 22.3 ± 3.5 (RSD: 18%)
and 22.2 ± 3.9 ◦ C (RSD: 16%), respectively. The results suggested that the accumulationchamber setup was not affected by the surface soil temperature as same with the previous
42

IJERPH 2021, 18, 1489

report [10]. On the other hand, the average moisture saturation (convert from volumetricwater content using porosity) inside and outside the accumulation chamber were evaluatedto be 0.364 ± 0.172 (RSD: 47%) and 0.114 ± 0.028 (RSD: 24%), respectively. As we mentioned
above, Zhuo et al. reported that the water potential inside and outside of the stainless-steel
box shown nearly the same throughout the year [10]. It is well known that the water
potential is related parameter to volumetric water content which is inﬂuential parameter of
exhalation rate. However, both the average moisture saturation and its variation inside
the accumulation chamber were smaller than those outside the chamber. Additionally,
the accumulation chamber was embedded 15 cm into the soil. That is, it is considered that
this measurement condition was not easy for water due to rainfall to move from outside
the chamber to under the chamber by passing through pore spaces in the surface soil.
However, the thoron exhalation rates obtained in this study may be considered as baseline
level at the measurement site. Thus, we will develop the correction method of thoron
exhalation rates with the variation of the environmental factors. Additionally, it might
be possible to evaluate the seasonal variations of thoron exhalation rate if a passive typeradon and thoron discriminative monitor was set in a small size accumulation chamber.
4. Conclusions
In this study, radon and thoron exhalation rates from the ground were simultaneously
evaluated for four years by applying the naturally ventilated accumulation chamber ofa previous report. The results were compared to the data obtained by the accumulationchamber with scintillation cell and in situ radon and thoron exhalation rate monitor.
The results of the present method had relatively good agreement with results of the othermethods. Relationships between radon exhalation rates with environmental parameters
were also observed and their variations with seasons were determined. The baseline level ofthoron exhalation rate at the measurement site was evaluated. However, thoron exhalation
rates did not show clear seasonal variations, most likely due to limitations of the present
methodology. Therefore, the methodology will be modiﬁed based on the present results toallow the season variation of thoron exhalation rate from the ground to be obtained.
Author Contributions: Conceptualization, M.H. and S.T.; methodology, W.Z., N.A., M.H., and S.T.;
validation, C.K., K.I., N.A., and M.H.; formal analysis, Y.T., T.S., and R.Y.; investigation, Y.T., T.S., R.Y.,
K.I., N.A., M.H., and S.T.; resources, N.A., M.H., and S.T.; data curation, T.S. and M.H.; writing—original draft preparation, O.B.M.; writing—review and editing, Y.T., T.S., R.Y., W.Z., C.K., K.I.,
N.A., M.H., and S.T.; visualization, T.S. and M.H.; supervision, C.K., N.A., M.H., and S.T.; project
administration, N.A., M.H., and S.T.; funding acquisition, M.H. and S.T. All authors have readand agreed to the published version of the manuscript.
Funding: This work has been partially supported by the Research Foundation for the Electrotechnology of Chubu, the NIFS Collaboration Research Program (NIFS17KLEA034), the Radiation Effects
Association, the JSPS KAKENHI (Grant Number 16H02667, 16K15358, and 18K10023), and the Hirosaki University Institutional Research Grant.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleA New Methodology for Deﬁning Radon Priority Areasin Spain
Alicia Fernández, Carlos Sainz, Santiago Celaya *, Luis Quindós, Daniel Rábago and Ismael Fuente
Environmental Radioactivity Laboratory of the University of Cantabria (LaRUC), University of Cantabria,
Santander, 39011 Cantabria, Spain; alicia.fernandezv@unican.es (A.F.); sainzc@unican.es (C.S.);
luis.quindos@unican.es (L.Q.); daniel.rabago@unican.es (D.R.); fuentei@unican.es (I.F.)* Correspondence: santiago.celaya@unican.es

Abstract: One of the requirements of EU-BSS (European Basic Safety Standards) is the design andimplementation of a National Radon Action Plan in the member states. This should deﬁne, as
accurately as possible, areas of risk for the presence of radon gas (222 Rn) in homes and workplaces.
The concept used by the Spanish Nuclear Safety Council (CSN), the body responsible for nuclear
safety and radiation protection in Spain, to identify “radon priority areas” is that of radon potential.
This paper establishes a different methodology from that used by the CSN, using the same study
variables (indoor radon measurements, gamma radiation exposure data, and geological information)
to prepare a radon potential map that improves the deﬁnition of the areas potentially exposed toradon in Spain. The main advantage of this methodology is that by using simple data processing thedeﬁnition of these areas is improved. In addition, the application of this methodology can improvethe delimitation of radon priority areas and can be applied within the cartographic system usedby the European Commission-Joint Research Center (EC-JRC) in the representation of different
environmental parameters.
Citation: Fernández, A.; Sainz, C.;
Celaya, S.; Quindós, L.; Rábago, D.;

Keywords: radon potential map; geography information systems; geology; risk

Fuente, I. A New Methodology forDeﬁning Radon Priority Areas inSpain. IJERPH 2021, 18, 1352.
https://

1. Introduction

doi.org/10.3390/ijerph18031352

Numerous studies have shown that there is a clear correlation between indoor radon
exposure and the risk of developing lung cancer [1,2]. Radon gas is considered to be thesecond leading cause of lung cancer after tobacco, and is responsible for between 3 and
14% of deaths caused by this disease in the ﬁrst world [3,4] and the main source of ionizing
radiation for the population [5–8].
The World Health Organization (WHO) recommended a reference level of 100 Bq/m3
annual average radon concentration to initiate action plans to minimize health hazards
due to indoor radon exposure. However, if this level cannot be reached under the countryspeciﬁc conditions, the chosen reference level should not exceed 300 Bq/m3 , which represents approximately 10 mSv per year [4].
The interest in radon exposure maps is because the concentration of radon in buildings
varies according to their geographical location. This variability is due to a large number offactors that affect the presence of radon indoors. These maps will be a useful instrument
for applying the requirements of European legislation [5], which must be implemented
in member states at all administrative levels: national, regional and local, to the radon
problem. An overview of indoor radon mapping in Europe [9,10] showed the heterogeneityof the data: each country used different sampling strategies, measurement techniques, andrepresentations of the data obtained.
In 2013, the EU-BSS (European Basic Safety Standards) required the design andimplementation of National Radon Action Plans in the member states to identify areas ofrisk for the presence of radon gas in homes and workplaces. It establishes that the indoor
radon concentration level in homes and workplaces be set at 300 Bq/m3 , and requires the

Academic Editors: Shinji Tokonami
and Ikuo Kashiwakura
Received: 17 December 2020
Accepted: 28 January 2021
Published: 2 February 2021

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with regard to jurisdictional claims inpublished maps and institutional afﬁliations.

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
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distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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https://www.mdpi.com/journal/ijerph

IJERPH 2021, 18, 1352

radon priority areas (RPA) to be delimited. The BSS deﬁnes the RPA as an area where it isexpected that in a signiﬁcant number of houses the average annual radon concentration
exceeds the national reference level [5].
The problem was that different interpretations of RPA were introduced in eachcountry [11–17]. In Europe, both mapping methodologies and the deﬁnitions of RPAs
are diverse [18–26].
The concept of radon potential, soil radon potential, or geogenic radon potential isused by the different member states to deﬁne and delineate the Radon Priority Areas.
Projects currently under development, such as the EURAMET MetroRADON [27–29], orthe European Atlas of Natural Radiation [30–35], try to homogenize concepts, mapping
methodologies that permit a clear deﬁnition of these areas.
The Spanish Nuclear Safety Council (CSN) published a radon potential map in2017 [36,37]. The concept used in Spain, and deﬁned by the CSN to identify “radon priority
areas”, is that of radon potential. The CSN deﬁnes these areas using the 90th percentile togenerate a cartography of the radon potential map of Spain. The variables used by CSN are
the national 222 Rn concentration database measurements in homes, geological information(lithostratigraphies), and exposure rates to terrestrial gamma radiation.
The CSN generated the radon potential map by combining these three variables:
Radon measurements in homes were grouped by lithostratigraphic unit and level of
exposure to gamma radiation, and units with homogeneous radon levels were obtained
from these data groups. For these units, the 90th percentile (P90) of the radon concentration
distribution was considered to be a limit with higher than 90% conﬁdence, and the units
were represented by rank in 5 categories based on radon levels from the use of the 90th
percentile: P90 > 400 Bq/m3 ; P90 301–400 Bq/m3 ; P90 201–300 Bq/m3 ; P90 101–200 Bq/m3
and P90 < 100 Bq/m3 . A radon concentration value is calculated using the 90th percentile,
meaning that 90% of the values in an area are below that value, and 10% are above it. The
CSN identiﬁed the areas of Spain where there are a signiﬁcant percentage of homes withradon concentrations with a given probability of exceeding 300 Bq/m3 [36,37].
This paper sets out a mapping methodology that improves the deﬁnition of radonpriority areas in Spain using the same variables used by the CSN (222 Rn concentration
measurements in homes, lithostratigraphies, and gamma radiation exposure data), but witha different approach. In addition, following the steps taken by the European CommissionJoint Research Centre (EC-JRC) in the production of the European Atlas of Natural Radiation and the European Radon Map [30–35], their reference coordinate system (theGISCO-LAEA projection) will be used and the 10 km × 10 km cell system to represent thedata obtained. This cell system ensures the conﬁdentiality of the radon samples taken in
private homes and harmonizes the maps from the different countries.
2. Materials and Methods
2.1. Input Data
In order to produce a Spanish radon potential map with this new methodology, weused the following data sources:
2.1.1. Concentration of 222 Rn in Homes
There were 11,500 data points on radon concentration measurements throughout Spain
used in the preparation of this study. These measurements are taken from the national
222 Rn concentration database in homes carried out in sampling campaigns between 1991
and 2016 grouped by municipalities [38]. The samples were taken inside houses, on the
ground ﬂoor, and the measurements were made with track detectors (CR39) exposed for aperiod of three to six months.
The bulk of these 9500 measurements were collected by the University of Cantabria
through different projects sponsored by CSN according to the internal location protocolof the Environmental Radioactivity Laboratory of the University of Cantabria (LaRUC),
created using the indications of the CSN Safety Guide 11.01 [39]. The LaRUC Laboratory has
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IJERPH 2021, 18, 1352

been validated by Public Health England (PHE) since 2002 [40] and accredited since 2016
through UNE-EN ISO/IEC 17025, ENAC [41], to carry out this type of radon measurementon air. This will be the dependent variable (variable 0) in this study.
2.1.2. Gamma Radiation Exposure Data
The gamma radiation exposure data were obtained from the Natural Gamma Radiation Map (MARNA) [42]. This map assesses the rate of exposure to terrestrial gamma
radiation at a height of 1 meter above the ground. It was produced by taking aerial and terrestrial measurements with a variety of analysis techniques, and these were later correlated
through the MARNA project [43].
Terrestrial gamma radiation rates in Spain range from 44 to 287 nGy/h. This information is identiﬁed in 22 individualized rates. The information about the 22 terrestrial
gamma radiation rates (rates of 44 at 287 nGy/h) in Spain was extracted after downloading
the map image in high quality (.tiff) offered by the CSN website [42]. This will be the ﬁrst
independent variable (variable 1) analyzed.
2.1.3. Lithostratigraphies
The Lithostratigraphic, Permeability and Hydrogeological Map of Spain at a scaleof 1:200,000 [44] produced by the Geological and Mining Institute of Spain (IGME) wasused, and 329 lithostratigraphic units were analyzed. This map includes the permeabilityof the lithological units, homogeneously representing the lithostratigraphies and grouping
them by similar permeability values. This cartography is used because numerous studies show the importance of soil permeability in determining the radon potential insidebuildings [45,46]. The digital cartography was downloaded in a compatible format (.shp)
with the use of Geographic Information System (GIS) programs. This will be the second
independent variable (variable 2) analyzed.
2.1.4. Radon Potential
Information about radon potential in Spain was obtained after downloading the map
image from the CSN website [11,36]. The 5 units shown were analyzed with homogeneousradon levels based on radon levels from the use of the 90th percentile: Unit 1 (>400 Bq/m3 ),Unit 2 (301–400 Bq/m3 ), Unit 3 (201–300 Bq/m3 ), Unit 4 (101–200 Bq/m3 ), and Unit 5(<100 Bq/m3 ). This will be the variable (variable 3) used to perform the comparison of thedata obtained in this work.
2.2. General Procedure
2.2.1. Framework
A Geographical Information System program (ESRI ArcGis v. 10.0, Environmental
Systems Research Institute: Redlands, CA, USA) [47] was used to produce the cartography
for this paper. The KaleidaGraph v. 4.1 (Synergy Software: PA, USA) [48] program wasused to analyze the data obtained and to make graphs.
To follow a similar scheme to other EU member countries, we began working with acontinental level projection system (GISCO-LAEA), and deﬁned the European working
area with a 10 km × 10 km grid with established limits (coordinates) as suggested by the
Joint Research Centre of the European Commission EC-JRC [30,33]. To deﬁne the Spanish
working area, we used the administrative boundaries provided by the National Geographic
Institute [49], generating a total of 5478 cells of 10 km × 10 km. For each cell, an identifying
code was created and its centroid in meters (“x” and “y” coordinates) was calculated.

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IJERPH 2021, 18, 1352

2.2.2. Harmonization of Input Data
The formats in which the source information for these variables appears are different,
and so it was necessary to harmonize this information to later process the data:
Concentration of 222 Rn in Homes
The radon concentration variable was analyzed using the 11,500 data points obtainedin the various measurement campaigns mentioned above. This information was stored in
the GIS database and transferred to the 10 km × 10 km cell system: the transposition of thevalues into the cell system was performed by calculating the arithmetic mean of the radon
concentration points data (in Bq/m3 ) contained in each 10 km × 10 km cell. This variable
therefore contains information on 5478 ﬁelds in its attribute table, corresponding to theaverage radon concentration (in Bq/m3 ) for each of the 5478 Spanish cells. The decision to
use the arithmetic mean was taken because the EC-JRC suggested it in the European Radon
Atlas [30–35] as the most appropriate parameter in the representation of this variable, due
to the great variability of the concentrations obtained per 10 km × 10 km cell and because
it is used in most epidemiological studies.
Exposure Rate to Terrestrial Gamma Radiation, Lithostratigraphy and Radon Potential
The information about the Spanish lithostratigraphic units was downloaded in a shapeformat, and so we worked with geological data of the 329 polygons and the attribute table oflithostratigraphic units provided by IGME. The data for the rates of exposure to terrestrial
gamma radiation and radon potential in Spain were downloaded in a high-quality image
format. These images were georeferenced to the Spanish administrative boundaries, andits polygons were later digitized in as much detail as possible (at an approximate scale ofbetween 1:3000 and 1:5000): the 5 units with homogeneous radon level were digitized as
5 polygons, assigning them their value in Bq/m3 . There were 22 terrestrial gamma radiation
rates digitized as 22 polygons, assigning them their value in nGy/h. A noteworthy fact isthat there are no data on exposure to terrestrial gamma radiation for the Balearic Islands or
the Canary Islands, so this variable could not be taken into account when conducting thestudy in these areas.
As mentioned above, each of these variables in shape format contains the graphicalunit/polygon (ﬁeld) information stored in its attribute table, with each ﬁeld being a record
with information about the typology of the element or surface coverage to be analyzed (it isa homogeneous category of information). For the subsequent data analysis, it was necessary
to calculate, for each variable, which was the unit or ﬁeld (polygon) with the largest surface
area contained in each 10 km × 10 km cell. To do this, the cell system was intersected withthe variables gamma radiation, lithostratigraphies and radon potential, and the surfaceof the majority ﬁeld was calculated in each one. In this way, each 10 km × 10 km cell was
assigned the value of the ﬁeld with the highest probability of occurrence in those 100 km2 .
2.2.3. Data Processing
The data processing was different for the input data depending on the origin of thesource information: for the dependent variable (concentration of 222 Rn in homes) thearithmetic mean data of the radon concentration points (in Bq/m3 ) contained in each
10 km × 10 km cell was transferred to the cell system. The data for the independent
variables (exposure rate to terrestrial gamma radiation and lithostratigraphy), and the datafor performing the comparison of the data and validating the study results (CSN radon
potential) were transferred to the cell system by the generation of density maps.
The methodology of the density map creation process is shown in Figure 1 andis as follows:

50

IJERPH 2021, 18, 1352

Figure 1. Diagram of the methodology for creating the density maps.

The ﬁrst step was to create a 2500 m × 2500 m dot mesh on each side, ﬁtted to the limitsof the 10 km × 10 km cells in Spain. This meant that each cell was covered homogeneously
by a total of 16 points. This dot mesh allowed the extraction, for each 10 km × 10 km cell,of the points contained in each ﬁeld of the study variables. The process was carried out byintersecting the dot mesh with each of the previously selected ﬁelds; in this way a seriesof layers were created that indicated the density of points per 10 km × 10 km cell: theminimum value (0) corresponded to the absence of that ﬁeld in that cell, and the maximum
value (16) was related to the total presence of that ﬁeld in that cell. Thus, 22-point layers
related to variable 1 (exposure rate to terrestrial gamma radiation), 329-point layers wereassociated with variable 2 (lithostratigraphies), and 5-point layers were created for variable
3 (CSN radon potential). Density maps were generated with each of these point layers, andﬁtted the limits of the 10 km × 10 km cells from the point density tool [50].
Once the density maps of each variable were generated, the relationship between
the dependent variable (concentration of 222 Rn in homes) and the independent variables(exposure rate to terrestrial gamma radiation and lithostratigraphy) was analyzed. In
previous steps, the centroid (“x” and “y” coordinates) of the 5478 cells 10 km × 10 km
had been calculated, and an identiﬁcation code added to each of them. Using the extractby-points tool, the radon concentration value transferred to the cell system (dependent
variable) was extracted. In the same way, with this tool, the value of the gamma rate
information was extracted for each of the cells of the 22 density maps related to the ﬁelds ofvariable 1. The same procedure was carried out with the 329 ﬁelds of variable 2, extracting
the information from the lithostratigraphic typology.
Using the data extracted, a simple linear correlation analysis was performed to checkthe positive or negative relationship between the two parameters for each cell. For example,
in a cell with code 1 the Pearson correlation coefﬁcient (R) of the average radon concentration is calculated, and so is the exposure rate to terrestrial gamma radiation with the ﬁeld 44
nGy/h, for that same cell, the ﬁeld 88 nGy/h and so on for each ﬁeld of each variable. The
degree of adjustment was quantiﬁed through the Pearson correlation coefﬁcient (R), giving
for each of the correlations, a value between −1 and +1. The data of these correlations werenormalized into 9 categories: value 1 R > +0.75, value 2 (R +0.74 to +0.5), value 3 (R +0.49 to+0.25), value 4 (R +0.24 to +0.1), value 5 (R = 0), value 6 (R −0.1 to −0.24), value 7 (R −0.25
to −0.49), value 8 (R −0.50 to −0.74), and value 9 (R < −0.75). This grouping into ranges of51

IJERPH 2021, 18, 1352

values facilitated the process of representing the correlations obtained between the radon
concentration with respect to exposure to gamma radiation and lithostratigraphy.
2.3. Development of the Relationship Maps between Independent Variables and the 222 Rn
Concentration in Homes and the New Radon Potential Map
For the variable terrestrial gamma radiation exposure rate, the data were represented
graphically using the cell system, which gathers the 22 ﬁelds into 5 categories, deﬁned
by their radon concentrations: 44 nGy/h correspond to 100 Bq/m3 and 89 nGy/h with
300 Bq/m3 [51]. The correlations obtained between the radon concentrations with respect toexposure to gamma radiation were represented graphically in 9 categories according to theranges mentioned above. Similarly, the lithostratigraphy variable was represented graphically in the cell system, bringing together the 329 lithostratigraphic ﬁelds of the Iberian
Peninsula, the Balearic Islands, and the Canary Islands. The correlations obtained between
the radon concentrations with respect to the lithostratigraphies were also represented
graphically in 9 categories.
From these two correlation maps, a new radon potential map (Radon Potential Map
Calculated) was generated. The sum of the categories of both maps was represented on thiscalculated map, and so the numerical range of each cell was between 1 and 18: Values from13 to 18 indicate a positive linear relationship with radon and therefore a high probabilityof ﬁnding high concentrations. Values from 8 to 12 indicate the absence of a relationshipand therefore an average probability of ﬁnding high concentrations. Values from 1 to 7
indicate a negative linear relationship with radon and therefore a low probability of ﬁnding
high concentrations.
To facilitate the interpretation of the results, and to represent the data according totheir possible radon concentration range, the values were reclassiﬁed into 5 categories:
Category 1 (>400 Bq/m3 ), Category 2 (301–400 Bq/m3 ), Category 3 (201–300 Bq/m3 ),Category 4 (101–200 Bq/m3 ), and Category 5 (<100 Bq/m3 ). The equivalences applied tothe entire process are shown in Table 1 below:
Table 1. Equivalences and data grouping by ranges of values.

(Bq/m3 )Calculated Potential Radon Map(Value)Pearson’s Correlation Coefﬁcient(R)

Lithostratigraphies andTerrestrial Gamma Radiation
Rates Intersections Value(Value)>400
301–400
201–300
101–200<100

18 to 14
13 to 109 to 7
6 to 43 to 1>+0.75+0.74 to +0.26+0.25 to −0.25−0.26 to −0.74<−0.759
7 to 86 to 43 to 2
1

222 Rn Concentration

The methodology used to evaluate the results was as follows: the success or failure
capacity per 10 km × 10 km cell was compared for each of the variables analyzed (222 Rnconcentration measurements in homes, exposure rate to terrestrial gamma radiation andlithostratigraphies), from both the CSN P90 Radon Potential Map and the Radon Potential
Calculated Map. It was considered a success if a cell was in the same concentration or
range of values (see Table 1 equivalences) and it was considered a failure if the cell was nota match.
3. Results
3.1. Analysis of Variables
3.1.1. Concentration of 222 Rn in Homes
Regarding the concentration of 222 Rn in homes, the 11,500 data points on the concentration of 222 Rn in air were analyzed using as a starting point the central trend measures and52

IJERPH 2021, 18, 1352

dispersion, and according to the shape of the distribution sample. Table 2 offers the updated
data regarding previous publications [52,53] showing the main parameters obtained:
Table 2. Statistics on radon concentration data for Spain.

Spain

Number of
Measurements

Arithmetic Mean
(Bq/m3 )Arithmetic
Standard
Deviation

Geometric Mean
(Bq/m3 )Geometric
Standard
Deviation

1-st Quartile(Bq/m3 )Median(Bq/m3 )3-rd Quartile(Bq/m3 )Range(Bq/m3 )Skewness

Kurtosis

11,500

101

260.6

58

2.6

30

56

110

10–15,400

31.5

1497

The central trend measures show that the data do not follow a normal distribution,
since the arithmetic mean (101 Bq/m3 ) is far from the median (56 Bq/m3 ). Furthermore, thestandard deviation of the arithmetic mean is 260.6 Bq/m3 , which shows a high dispersionof the data.
Analysis of the shape of the sample distribution shows a high coefﬁcient of kutorsis (K = 1497), indicating a leptokurtic distribution, whereas the asymmetry coefﬁcient(CS = 31.5) indicates a positive asymmetry: The distribution of measurements is log-normal.
The distribution of measurements is log-normal, as shown in the histogram (Figure 2). This
distribution is usual for radon concentration measurements since most of the measurements obtained are in low concentrations, whereas only a few measurements appear in thehigh concentration range.

Figure 2. Histogram of the radon concentration data.

Analyzing these 11,500 data points, it is seen that 27% of the samples exceed the levelof 100 Bq/m3 to initiate action plans (5% of the measurements exceed 300 Bq/m3 and 22%
are in the range of between 100 and 300 Bq/m3 ).
On transposing these data to the cell system, it is seen (Table 3) that the majority (76%)
are in the range of low concentrations (<100 Bq/m3 ), 22% between 100–300 Bq/m3 , andthat the percentage of cells in high concentrations (>300 Bq/m3 ) is reduced to 2%.
53

IJERPH 2021, 18, 1352

Table 3. Mean concentration of 222 Rn and number of measurements per 10 × 10 cell.
222 Rn Concentration

Arithmetic Mean (A.M)(Bq/m3 )>400
301–400
201–300
101–200<100

No of
10 km × 10 km
Cells
(%)

No of
Measurements
per Cell(Average)

1 Measurements(%)

2 to 6
Measurements(%)>6
Measurements
(%)

1
1
4
18
76

3.9
4.2
5.2
4.9
2.8

32
34
37
37
50

52
45
40
42
41

16
21
23
21
9

It is also clear that the sampling in Spain is not heterogeneous, since there are areas
where the measurement density is much higher than others; this is because the samplingin Spain was deﬁned based on a series of criteria that concentrated the number of measurements in areas with potentially high radon concentrations. The decision of how manymeasurements to be carried out in each 10 km × 10 km cell was made by the CSN, taking
into account the general objectives established by the EC-JRC in the creation of the European Radon Map, considering superﬁcial, population and lithostratigraphic criteria, andaccording to the rate of exposure to terrestrial gamma radiation [51,52].
Despite efforts to try to cover the entire country with at least one measurement per
10 km × 10 km cell, it can be seen that a large part of its surface does not have any
measurements (40%). Of the cells for which measurements are available, it is representativethat a large percentage of Spain is covered with only one measurement (47%) or withtwo measurements (19%), whereas cells with more than 6 measurements represent 15%of the total.
Analyzing cell percentage according to concentration category and measurements,
it is seen that 68% of cells with concentrations greater than 400 Bq/m3 have more than
two measurements (in 52% of cases from 2 to 6 measurements, and in 16% more than
6 measurements), and that in the concentration range between 301 and 400 Bq/m3 thispercentage of cells is also high (66%). The percentage is slightly lower for the intermediateconcentrations (101–300 Bq/m3 ) where 63% of cells have more than 2 measurements. Low
concentrations (<100 Bq/m3 ), despite being the most numerous category, is the one withthe fewest measurements. Half of its cells have a single measurement, reducing the numberof cells with more than 6 measurements to 9%.
It is clear that as the number of measurements per cell increases, the concentration
ranges are better deﬁned.
3.1.2. Exposure Rate to Terrestrial Gamma Radiation
From the analysis of the rates of exposure to terrestrial gamma radiation (Figure 3a),
95% of the peninsula is found to have medium and low rates: 2% of the country is below
44 nGy/h, and 93% between 45 and 122 nGy/h. The areas with rates higher than 122 nGy/hare few (5%), and are mainly in the northwest area of the peninsula and in the Central
System. In these areas, there is a clear correspondence between the presence of high radon
concentrations and high rates of gamma exposure [43,54].
Analyzing the data of this variable with respect to radon concentrations (Figure 3b), a
positive linear relationship is observed between the two parameters starting at 78 nGy/h,the relationship becoming clearer in the case of the identiﬁed areas of high rates. These
areas correspond once again to those previously mentioned, along with areas of the Catalan
Coastal Cordillera and the Pyrenees, corroborating the correspondence of high radon
concentrations and high rates of gamma exposure.

54

IJERPH 2021, 18, 1352

(a)

(b)

Figure 3. (a) Figure Terrestrial gamma radiation rates (nGy/h) and (b) Relationship between terrestrial gamma radiation
rates and radon concentration.

3.1.3. Lithostratigraphies
Regarding the lithostratigraphy variable, it is known that the main indicator in determining a higher or lower probability of high concentrations of radon in an area is thepresence of uranium in soils and rocks, for which reason the lithological formations witha high proportion of uranium will generate a high proportion of radium and therefore ahigher proportion of radon. In general, the highest uranium values (>2.88 ppm) [55], areassociated with acidic intrusive plutonic rocks such as granites.
The analysis of lithostratigraphies (Figure 4a) in Spain suggests that the geologies mostcommonly found in Spain are acidic plutonic rocks such as granites, granodiorites, andquartz diorites (8% of the territory). Due to the large number of lithostratigraphies present
in Spain, the legend of this ﬁgure only shows the most numerous (more than 2% of theterritory), the complete legend is available in the IGME [56]. It is also noteworthy that 4% of
the territory is made up of slates and greywacke. Both shales (metamorphic rocks producedby silt-clay sedimentary rocks) and greywacke (detrital sedimentary rocks derived fromthe dismantling of acidic plutonic rocks) generally also have high uranium content [43].
In the areas where these two formations are present, there may be a high probability ofﬁnding high radon concentrations, which was conﬁrmed after performing the correlation
analyses of the two variables.
The results of the relation between lithostratigraphies and radon concentrations(Figure 4b) show that 100 lithostratigraphies show a positive relationship. The clearest relation (>+0.75) appears in a single case, in the geologies corresponding to acidic, Hercynian
plutonic rocks (granites, granodiorites, quartz diorites). It has been conﬁrmed that thisgeology is associated with a high presence of radon.
55

IJERPH 2021, 18, 1352

In addition, six other lithostratigraphies show a marked relationship with the presenceof high radon concentrations (between +0.51 and +0.75), representing another 8% of thepeninsular surface. They mainly correspond to metamorphic rocks such as shales, gneiss,
schists, or quartzites (these are rocks with high concentrations of uranium) [43] and detrital
sedimentary rocks such as greywacke derived from acidic plutonic rocks.
On analyzing the geographical distribution of these areas, it is seen that they correspond to the northwest area of the peninsula and the area of the Central System. A close
relationship is also observed with the geological formations in the west of the peninsula
and their extension towards Sierra Morena, speciﬁc areas of the Pyrenean Range, and in
the area of the Catalan Coastal Cordilleras.

(a)

(b)

Figure 4. (a) Figure Lithostratigraphies 1:200,000 and (b) Figure Relationship lithostratigraphies and radon concentration.

3.2. Comparison of Radon Potential Maps Generated
As shown in Figure 5, where the P90 Radon Potential Map generated by the CSN(hereafter P90 Potential Map) and the Radon Potential Map Calculated in the present
study are compared, both maps show a similar percentage of cells in the range of radon
concentrations greater than 400 Bq/m3 (17% in the case of the Calculated Map and 16%
in the P90 Potential Map). In both maps, the areas deﬁned in this range correspond once
again to the northwest of the peninsula, the Central System area, the west of the peninsula
extending towards Sierra Morena, south of the Pyrenees, and in the area of the Catalan
Coastal Cordilleras.
The increase in the weight of the cells with concentrations between 301 Bq/m3 and400 Bq/m3 is signiﬁcant: it goes from 2% in the P90 Potential Map to 19% in the case of the
Calculated Map. As will be seen later, the calculation of this new zoning ﬁts possible radon
concentrations more reliably. It is mainly seen in the west of the peninsula surrounding thehighest concentrations. The area of Sierra Morena up to the border with Portugal is also56

IJERPH 2021, 18, 1352

clearly deﬁned in this range, and in some areas to the north of the peninsula, areas of thePenibaetic System or areas to the west of the Ebro valley.
Both maps have a similar percentage of cells in the concentration range between
201–300 Bq/m3 (20% in the case of the Calculated Map and 21% in the P90 Potential Map).
However, analyzing Figure 4 shows changes in zoning: in the CSN P90 Potential Map theseareas were deﬁned as mainly bordering the areas of greater concentrations in the west of
the peninsula and certain areas in the south of the Ebro valley, while with the Calculated
Map these areas are mainly found in the south of the Iberian System and the south of theEbro valley.

(a)

(b)

Figure 5. Potential Radon Map. (a) Calculated Map and (b) Map based on Spanish Nuclear Safety Council (CSN) data.

The most signiﬁcant change occurs in the cells between 101 and 200 Bq/m3 , where it
drops from 59% in the case of the P90 Potential Map to 35% in the Calculated Map. The
reduction is this percentage is accompanied by a large group of the cells located in thiscategory switching, on the Calculated Map, to the range between 301–400 Bq/m3 and cellsof less than 100 Bq/m3 .
Regarding the range of cells with concentrations below 100 Bq/m3 , an increase in
the number of cells is observed, going from 2% on the P90 Potential Map to 7% on the
Calculated Map. This increase in cells is due to a large number of the cells identiﬁedin the CSN map as in the range between 101–200 Bq/m3 having moved to this range oflower concentrations. The area in this category lies mainly in the south of Spain in the
Guadalquivir Valley and the Levante.
3.3. Assessment of the Degree of Identiﬁcation of the Maps
To quantify the degree of identiﬁcation of the Radon Potential Calculated Map withrespect to radon concentrations, the cells are analyzed, identifying for each variable thepercentage of failures or successes in each of the ranges. Table 4 reﬂects the degree ofidentiﬁcation of each of the study variables.
57

IJERPH 2021, 18, 1352

Table 4. Degree of identiﬁcation between the variables of the maps Potential Radon Map Calculated and P90 CSN.
Radon Potential Calculated Map
222 RnConcentration
A.M(Bq/m3 )Success(%)

Failure(%)>400
301–400
201–300
101–200
<100

68
20
15
15
11
12

32
80
85
85
89
86

Gamma Radiation
Rate(nGy/h)>167
123–167
89–12245–88<48

Success(%)

Failure
(%)

90
8
3
41
0
32

10
92
97
59
100
68

Lithostratigraphies
Success
1:200,000(%)(Class)98, 76, 5, 4
3, 2
1

96
36
27
65
80
47

Failure
(%)
4
64
73
35
20
53

Radon Potential Map P90 CSN
222 RnConcentration
A.M(Bq/m3 )Success(%)

Failure(%)>400
301–400
201–300
101–200
<100

64
3
30
37
2
10

36
97
70
63
98
90

Gamma Radiation
Rate(nGy/h)>167
123–167
89–12245–88<48

Success(%)

Failure
(%)

53
2
31
72
0
57

47
98
69
28
100
38

Lithostratigraphies
Success
1:200,000(%)(Class)98, 76, 5, 4
3, 2
1

89
0
31
91
0
47

Failure
(%)
11
100
69
9
100
53

3.3.1. Degree of Identiﬁcation Regarding Radon Concentrations
Regarding radon concentrations, both maps show a high capacity to identify cells withconcentrations greater than 400 Bq/m3 , but the Calculated Potential Map improves thedata obtained with respect to the P90 Potential Map: it returns 68% correct identiﬁcation ofthese areas compared to 64%.
The increase in the identiﬁcation capacity of the Calculated Potential Map in areas
with concentrations between 301–400 Bq/m3 is of special interest, from 20% to 3% reported
by potential radon map CSN, Directive 2013/59/Euratom sets the ﬁrst value as a reference
level to be considered when devising National Action Plans against radon gas in order todeﬁne Radon Priority Areas that, with the proposed method, becomes easier to deﬁne.
In the intermediate concentration ranges, the identiﬁcation capacity of the P90 Potential Map is superior to that of the Calculated Potential Map: In the range 201–300 Bq/m3
and 101–200 Bq/m3 it identiﬁes appropriately 30% and 37% of the cells. The Calculated
Potential Map correctly identiﬁes 15% of cases.
The greater capacity of identiﬁcation of the P90 Potential Map in these ranges of mean
concentrations is mainly due to the scarcity of measurements made in these areas. As previously shown, a higher sampling density per cell more precisely deﬁnes the concentrations,and many of the cells identiﬁed as having average concentrations would move to anotherrange of concentrations as the number of measurements in them increases. This greater
identiﬁcation capacity is also due to the fact that the CSN map assigned a high weightto the gamma radiation variable, while when creating the Calculated Potential Map, theweight of the variables was homogenized.
In the lower concentration ranges, the identiﬁcation capacity of the Calculated Potential Map improves to 12% as against 3% of the P90 Potential Map.
3.3.2. Degree of Identiﬁcation Regarding the Rates of Exposure to Terrestrial
Gamma Radiation
Regarding the rates of exposure to terrestrial gamma radiation, the P90 Potential Map
has a greater capacity of identiﬁcation (57%) as compared to the Calculated Potential Map(32%). However, when analyzing the different ranges in detail, it is found that this reduction
58

IJERPH 2021, 18, 1352

in global accuracy is mainly due to low identiﬁcation in the cells corresponding to theaverage rates (between 45 nGy/h and 122 nGy/h), because the data on radon concentrationin this grid is limited. On the other hand, the increase in the identiﬁcation of cells withhigher rates is notable: in cells with more than 167 nGy/h the level of identiﬁcation
increases to 90%, and in cells between 123 nGy/h and 167 nGy/h it rises to 8%.
3.3.3. Degree of Identiﬁcation Regarding the Lithostratigraphies
With respect to lithostratigraphies, both maps correctly identify 47% of the cells. The
differences emerge when analyzing the different classes associated with concentrations.
In the cells corresponding to lithostratigraphies associated with concentrations ofmore than 400 Bq/m3 (Class 9), the Calculated Potential Map increases identiﬁcation to
96% as against 89% of the P90 Potential Map.
It is of particular interest that the Calculated Potential Map correctly identiﬁes 36% of
the cells associated with Classes 7 and 8 (lithostratigraphies linked to radon concentrations
between 301 Bq/m3 and 400 Bq/m3 ), since the CSN map does not have the capacity toidentify these areas. Again, Directive 2013/59/Euratom sets the value 300 Bq/m3 as thereference level for producing National Action Plans against radon gas.
The identiﬁcation of cells associated with concentrations between 201 Bq/m3 and300 Bq/m3 (Classes 4, 5 and 6) is similar in both maps: 27% in the case of the Calculated
Potential Map and 31% of the P90 Potential Map.
The identiﬁcation capacity of the Calculated Potential Map drops to 65% comparedto 91% of the P90 Potential Map in Class 2 and 3 cells (lithostratigraphies associated withconcentrations between 101 Bq/m3 and 200 Bq/m3 ). This is due to the existence of lithostratigraphies that were previously identiﬁed with intermediate concentrations, but now
have come to be placed in the category of low concentrations: in Class 1 (lithostratigraphies
associated with radon concentrations of less than 100 Bq/m3 ) the Calculated Potential Map
has an accuracy of 80% as opposed to the null capacity of the P90 Potential Map.
4. Conclusions
In conclusion, it has been shown that:

•
•

•

•

The Calculated Potential Map correctly identiﬁes 12% of the cells in terms of theprobability of ﬁnding a radon concentration in a given area, improving the percentageof the P90 Potential Map (which correctly identiﬁes 10% of the cells).
Regarding the probability of ﬁnding an exposure rate to terrestrial gamma radiation associated with a radon concentration, the P90 Potential Map properly identiﬁes 57% of
the cells, while the Calculated Potential Map identiﬁes 32% of the cells. This is because
when making the map, the CSN gave great weight to this variable, whereas when making the Calculated Potential Map, the weight of the study variables was homogenized.
Regarding the probability of ﬁnding lithostratigraphies related to the greater or lesser
presence of radon, both maps correctly identify 47% of the cells. In general, it isseen that the Calculated Radon Potential Map improves the identiﬁcation of cells
in terms of the probability of ﬁnding a radon concentration associated with a typeof lithostratigraphy, since it homogenizes the ability to place a type correctly in allconcentration ranges. Its identiﬁcation capacity is markedly better in the ranges ofhigher concentrations (>300 Bq/m3 ) and lower concentrations (<100 Bq/m3 ).
The Calculated Radon Potential Map in this study prepared from joining together thecorrelation maps shows that in 36% of the country there is a probability of ﬁnding
radon concentrations higher than 300 Bq/m3 (17% above 400 Bq/m3 and 19% between
301 Bq/m3 and 400 Bq/m3 ). With this map, the areas of Spain with probable highradon concentrations (more than 300 Bq/m3 ) are precisely deﬁned.

The map also identiﬁes the areas with a probability of ﬁnding radon concentrationsof between 100 Bq/m3 and 300 Bq/m3 more reliably, by homogenizing the weights of thevariables. This range of concentrations is also of particular interest, as the WHO designates
100 Bq/m3 as the recommended reference level to start action plans against radon gas.
59

IJERPH 2021, 18, 1352

Author Contributions: Conceptualization, A.F., C.S., and L.Q.; methodology, A.F., C.S., S.C., L.Q.,
D.R., and I.F.; software, A.F.; validation, A.F.; formal analysis, A.F., C.S., and L.Q.; investigation,
A.F., C.S., S.C., L.Q., D.R., and I.F.; writing—original draft preparation, A.F., C.S., and L.Q.; writing—review and editing, A.F., C.S., and L.Q.; visualization, A.F. All authors have read and agreed to the
published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The data presented in this study are available in article.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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ratigrafia_A0.pdf (accessed on 30 June 2020).

62International Journal ofEnvironmental Researchand Public Health
ArticleMeasurement of Indoor Thoron Gas Concentrations Using a
Radon-Thoron Discriminative Passive Type Monitor:
Nationwide Survey in Japan
Tetsuya Sanada
Department of Radiological Technology, Faculty of Health Sciences, Hokkaido University of Science, Sapporo,
Hokkaido 006-8585, Japan; sanada-t@hus.ac.jp

Abstract: As part of a nationwide survey of thoron (220 Rn) in Japan, the indoor 220 Rn gas concentrations in 940 dwellings were measured throughout one year, from 1993 to 1996, using a passive
type 222 Rn-220 Rn discriminative monitor. The monitor was placed in a bedroom or a living room ineach house for four successive three-month periods. The mean annual indoor 220 Rn concentration
was estimated from the four measurements in each house. The arithmetic mean, the median and thegeometric mean for indoor 220 Rn concentrations in 899 dwellings were 20.1, 9.6 and 10.0 Bq m−3 ,respectively. The 220 Rn concentrations exhibited a log-normal distribution. It was found that the
220 Rn concentrations were dependent on the nature of the materials used for wall construction andalso on the distance of measurement from the wall. Signiﬁcant seasonal variations in the 220 Rnconcentration were not observed. It would seem that the nature of the wall material contributed tothe increased indoor 220 Rn concentrations.
Keywords: thoron; radon; indoor; radioactivity; environment; nationwide survey; SSNTD
Citation: Sanada, T. Measurement of
Indoor Thoron Gas Concentrations
Using a Radon-Thoron Discriminative
Passive Type Monitor: Nationwide
Survey in Japan. IJERPH 2021, 18,1299.
https://doi.org/10.3390/ijerph18031299
Academic Editor: Paul B. Tchounwou
Received: 31 December 2020
Accepted: 29 January 2021
Published: 1 February 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional afﬁliations.

Copyright: © 2021 by the author.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Radon (222 Rn), thoron (220 Rn) and their progeny species are large contributors to theannual exposure of an effective dose to the general population. 222 Rn and its progeny
species contribute about half of the annual effective dose due to natural radiation basedon the world mean dose. According to the United Nations Scientiﬁc Committee on the
Effects of Atomic Radiation [1], the annual effective dose from natural radiation sources
has been calculated to be 2.4 mSv as the worldwide average, whereas 222 Rn and 220 Rn
contribute 1.2 and 0.1 mSv, respectively. 222 Rn and 220 Rn are products of the decay chainsof natural radionuclides, such as the 238 U and 232 Th series, and have half-lives of 3.825 days
and 55 s, respectively. The 220 Rn half-life is very short compared with 222 Rn. Thus, only
a very small amount of 220 Rn can enter a room from the outside. It is considered that a
220 Rn concentration gradient exists near the mud-based walls and ﬂoors in low ventilatedhouses [2]. Therefore, if a mud mortar wall is present in housing materials which havehigh concentrations of thorium, 220 Rn and its decay products may enter houses and cause
potential health problems. In particular, traditional wooden houses with mud mortar walls
are a common house type in Japan.
The International Commission on Radiological Protection (ICRP) [3] have issued
new dose conversion factors for 222 Rn and 220 Rn progeny species based on a dosimetricapproach in Publication 137. The values speciﬁed are 16.8 and 107 nSv (Bq m−3 h)−1 ,respectively. This means that even small amounts of 220 Rn progeny species will cause
higher radiation exposure compared to 222 Rn [4]. Therefore, interest in 220 Rn exposure is
growing among the health sciences communities. Recently, a number of 220 Rn surveys
have been carried out in local regions and nationwide, and the results have been publishedenabling an evaluation of exposures from 220 Rn [5–21]. Also, the need to adopt reliable
220 Rn measurement techniques has been argued in several papers [22].
63

IJERPH 2021, 18, 1299. https://doi.org/10.3390/ijerph18031299

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IJERPH 2021, 18, 1299

An indoor 222 Rn survey was conducted on 940 houses nationwide in Japan from 1993
to 1996 using 222 Rn–220 Rn discriminative passive type monitors [23]. The passive monitor,
developed by Doi and Kobayashi [2], was placed in either a bedroom or a living room
where residents spent most of their time. Indoor 222 Rn concentrations were determined at
20 dwellings in each prefecture for four successive three-month periods to cover an entire
year. In the survey, to eliminate the inﬂuence of 220 Rn on 222 Rn measurement, the 220 Rnconcentration was performed at the same time for referencing purposes. The 222 Rn and
220 Rn calibration experiments were performed in a standard radon chamber at the National
Radiological Protection Board (Didcot, UK) and using the 222 Rn–220 Rn mixed chamber ofWaseda University (Tokyo, Japan), respectively. This study is concerned with the results
for the indoor 220 Rn concentrations using the reference data from the nationwide survey
which was conducted to determine the 222 Rn concentrations in Japan [23]. Furthermore,
the seasonal and regional variations were investigated, and the inﬂuence of the type ofhouse structure was examined as mentioned previously. However, this study does notinclude a dose assessment of 220 Rn because the 220 Rn concentration varies widely in rooms
and it is not easy to measure the activity concentration given the short half-life of theradioisotope [22].
2. Materials and Methods
2.1. 220 Rn Monitor and Measurement Periods
The solid-state nuclear track detector (SSNTD) was developed at the National Instituteof Radiological Sciences (Chiba, Japan) as a 222 Rn and 220 Rn discriminative monitor [2]. The
monitor consists of two electroconductive hemispheres and there are two polycarbonateﬁlms installed in the center of the two hemispheres. To isolate and separate the progeny
species of 222 Rn and 220 Rn, a glass ﬁber ﬁlter is located in the ﬁrst hemisphere. Therefore,
only gaseous 222 Rn and 220 Rn can pass through the ﬁlter and enter the ﬁrst hemisphere.
This monitor has two different diffusion chambers which have relatively large and small
ventilation rates. This system has been developed based on the large difference in half-livesof 222 Rn and 220 Rn. After being exposed, the ﬁlm was ﬁrst subjected to chemical etchingwith a mixed solution of 8 mol L−1 KOH and 20% C2 H5 OH at 30 ◦ C for 30 min [23]. Thenthe ﬁlms were electrochemically etched at 800 V and 2000 Hz for 2 h. A control ﬁlm, which
was exposed to particles from an 241 Am source and which had been etched simultaneouslywith the sample ﬁlms, was also prepared to assure the stability of the etching condition.
The track density was converted to the average 220 Rn concentration by the calibration
factor after subtraction of the background track density, i.e., 3.5 ± 1.8 tracks cm−2 . In thecase of the three month long exposure period, the detection limit (DL) for the concentrationof 220 Rn was estimated to be 7.4 Bq m−3 (k = 1.65), the deﬁnition of DL being based on thedeﬁnition of Currie [24]. Four monitors were used in the survey to determine the meanannual 220 Rn concentration. Consequently, the DL for the mean annual 220 Rn concentration
was estimated to be about 1/2 of DL value speciﬁed above. The measurements were carriedout for four successive three-month periods to cover a whole year (i.e., January–March,
April–June, July–September and October–December) for estimation of the mean annual
indoor 220 Rn concentration. The survey was carried out for four years (January 1993–June1996) and conducted in the same manner as reported previously [23].
2.2. 220 Rn Calibration Experiments
The 222 Rn and 220 Rn calibration experiments were performed in a standard radon
chamber at the National Radiological Protection Board in the UK and at the 222 Rn–220 Rn
mixed chamber of Waseda University, Tokyo, respectively [25]. 220 Rn conversion factor
was evaluated to be 0.0098 ± 0.0016 (tracks cm−2 per Bq m−3 d).

64

IJERPH 2021, 18, 1299

3. Results and Discussion
3.1. Distribution of 220 Rn Concentration
The mean annual 220 Rn concentrations were obtained for 899 houses, the number ofhouses monitored being reduced from the original 940 houses as was the case for 222 Rn [23].
The annual arithmetic mean, and the median were calculated and values less than the DL(<4 Bq m−3 ) were included in each quarter value. In addition, if a negative value wasobtained due to statistical variation as a result of background subtraction, this value was
assigned as a zero. The histogram for the mean annual indoor 220 Rn concentrations ispresented in Figure 1. The mean annual 220 Rn concentration was found to vary from <4
to 383 Bq m−3 . The arithmetic mean, the median, the geometric mean and the geometricstandard deviation were 20.1 ± 36.8, 9.6, 10.0 Bq m−3 and 3.2, respectively. The 222 Rnconcentrations varied from 3.1 to 208 Bq m−3 . The arithmetic mean, the median, thegeometric mean and the geometric standard deviation were 15.5 ± 13.5, 11.7, 12.7 Bq m−3
and 1.78, respectively [23]. As a comparison, Kim et al. reported that the geometricmean for 220 Rn concentrations in Korea was 10.7 Bq m−3 . The log-normal cumulative
frequency distribution for the indoor 220 Rn concentrations is shown in Figure 2. The 220 Rnconcentration distribution would appear to be close to a log-normal distribution. The
distribution of the mean annual indoor 220 Rn concentrations was accepted as a log-normal
distribution based on the Kolmogorov–Smirnov test at a signiﬁcance level of 95%.

Number of houses: 899
Arithmetic mean: 20.1 Bq mƺ3Median: 9.6 Bq mƺ3
Geometric mean: 10.0 Bq mƺ3

Maximum: 383 Bq mƺ3

Rn concentration (Bq mƺ3)

220

Figure 1. Histogram for indoor 220 Rn concentrations.

3.2. Seasonal Variation
The indoor 220 Rn concentration data for each season are presented in Table 1. Negativevalues in this dataset were eliminated for calculation of the geometric mean. A signiﬁcantseasonal variation in the 220 Rn concentrations for the four seasons was not found. According to Kim et al. [15] and Stjanovska et al. [16], a temporal pattern in the 220 Rn concentration
data was observed with values in the winter and spring seasons being higher than thosein the summer and autumn. Martinez et al. [17] found that the highest concentrations for
Mexico City were in the autumn season and the lowest concentrations were in summer.
In the present study, slight differences were noted in the 220 Rn concentrations depending on the periods of exposure. The lowest 220 Rn concentrations for all types of houses
were observed in the winter season (October–December). However, a different relationshipwas noted for the 222 Rn concentrations, namely, that the 222 Rn concentrations tended tobe higher in winter compared to the other seasons [23]. This was probably because theresidents used domestic heaters to maintain a comfortable room temperature in winter, and65

IJERPH 2021, 18, 1299

Rn concentration (Bq mƺ3)consequently there would have been increased ventilation rates due to the contribution of
convection and/or stack effect in the rooms.

220

Q 

Figure 2. Cumulative frequency distribution for indoor 220 Rn concentrations. This ﬁgure has been
prepared using the mean annual 220 Rn concentrations in excess of zero Bq m−3 .
Table 1. 220 Rn concentrations measured in the different seasons.

Measurement Period

Number ofHousesJanuary–March
April–June
July–September
October–December

899

220 Rn (Bq m−3 )

AM

SD

GM
(Number of Houses)

18.9
22.8
21.9
16.6

40.0
39.2
42.3
41.0

14.6 (576)
14.4 (733)14.0 (713)13.0 (492)

GSD

3.5
3.5
3.3
3.9

AM: Arithmetic mean; SD: Standard deviation; GM: Geometric mean; GSD: Geometric standard deviation(dimensionless).

The variation of the 220 Rn concentration in the rooms was slightly different from thatof 222 Rn, which may reﬂect the differences in the half-lives and sources of 220 Rn, despite thefact that there were large ﬂuctuations in the standard deviations for the seasonal variationsof 220 Rn concentrations. The reason why the indoor 220 Rn concentrations did not display avariation similar to 222 Rn is unclear at this time.
3.3. Nature of Housing
Indoor 220 Rn concentrations were categorized in terms of the structural features of the
housing. The annual mean, the standard deviation, and the geometric mean for the indoor
220 Rn concentrations together with number of houses monitored are given in Table 2. The
arithmetic and geometric mean concentrations for wooden and concrete-based houses
have higher values than those of other structures, although there were large ﬂuctuationsin the data. The maximum value was found for a wooden house with a mud wall, thehighest 220 Rn concentration being 383 Bq m−3 . The cause of the high 220 Rn concentrationof wooden houses is that they have relatively high ratio of the mud wall in comparison toother house structure types. Table 3 lists the ratio of the mud wall in each housing type.
Accordingly, the 220 Rn concentrations in wooden houses are higher than those for otherhousing types.

66

IJERPH 2021, 18, 1299

Table 2. The mean annual 220 Rn concentration for each type of house.
Structure

220 Rn (Bq m−3 )Number ofHouses

AM

SD

GM

597
182
90
16
6

23.1
16.3
8.6
21.8
3.4

40.7
32.5
8.9
25.6
2.6

10.8
9.6
6.1
13.8
2.7

WoodenConcrete
Steel frame
Concrete blockPrefabricated

AM: Arithmetic mean; SD: Standard deviation; GM: Geometric mean.

Table 3. Ratio of mud wall in each structure type.
Structure Type

Total Number ofHousesNumber of Mud
Wall Houses

Ratio of Mud Wallin the House (%)

WoodenConcrete
Steel frame
Concrete blockPrefabricated

597
182
90
16
6

190
3
0
1
0

31.8
1.6
0
6.3
0

With respect to the 220 Rn concentrations by region, the overall ratios for wooden
houses with mud walls in the Hokkaido—Tohoku, Kanto and Kyushu—Okinawa areas arelower than for those in other areas of Japan. Therefore, the 220 Rn concentrations in theseformer areas also tends to be lower than the values found in the other areas.
3.4. Dependency of 220 Rn Concentration on Wall Structure and Distance from Wall

Q 

Q 
Q 

Q 

220

Rn concentration (Bq mƺ3)

The present survey on 220 Rn concentrations considered four categories of material
which were used for wall construction in the houses. The mean annual 220 Rn concentrations obtained by passive measurement for the different wall materials in the houses
are presented in Figure 3. Inspection of the results (Figure 3) reveals that high 220 Rnconcentrations occurred for houses with mud walls, and the values decreased graduallywith distance from the surface of the wall as shown in Figure 4. Yonehara et al. reported
similar behavior for 220 Rn concentrations at locations near the wall surfaces in Japanesedwellings [26].

Figure 3. 220 Rn concentrations for various wall materials.

67Q 
Q 
Q Q  Q 
Q 
Q 
Q 
Q 

Q 

220

Rn concentration (Bq mƺ3)

IJERPH 2021, 18, 1299

Figure 4. 220 Rn concentrations at different distances from the wall surface for all wall materials.

3.5. 220 Rn and 222 Rn Correlation

Annual mean 222Rn concentration (Bq mƺ3)

The correlation between the indoor 220 Rn and 222 Rn concentrations was investigated.
The relationship between the 220 Rn and the 222 Rn concentrations is illustrated in Figure 5.
The concentration distributions for both radioisotopes follow approximately a log-normal
distribution. Consequently, both datasets were calculated after taking the logarithmsof the respective data. The linear regression analysis shows a weak positive correlation(R = 0.25). The ratio for the concentrations of 220 Rn/222 Rn ranged from 0.007 to 40.3 andreveal a log-normal plot. The arithmetic mean for 220 Rn/222 Rn was 1.64 and geometricmean was 0.78.

Figure 5. Correlation between the mean annual concentrations of 220 Rn and 222 Rn.

4. Conclusions
The mean annual indoor 220 Rn concentrations were measured in 899 houses usinga passive 222 Rn–220 Rn discriminative monitor. The arithmetic mean, the median and thegeometric mean were 20.1, 9.6 and 10.0 Bq m−3 , respectively. The 220 Rn concentration
plot exhibited a log-normal distribution. The maximum 220 Rn concentration found in
the present survey was 383 Bq m−3 for a wooden house with mud walls. The survey
68

IJERPH 2021, 18, 1299

data for the indoor 220 Rn concentrations in Japan did not exhibit a signiﬁcant seasonalvariation. There was a marked difference in the 220 Rn concentration depending on thenature of the house structure. Relatively higher concentrations of 220 Rn were found inwooden and concrete block houses compared to other housing types. In general, the 220 Rnconcentrations in traditional wooden houses with mud walls tended to be higher thanthose for houses with different wall types. Further, it was demonstrated that the 220 Rnconcentrations decreased with distance of measurement from the wall.
Funding: This research was carried out in collaboration with 47 prefectural institutes under the
auspices of the former Science and Technology Agency of Japan.
Institutional Review Board Statement: Not applicable for studies not involving humans or animals.
Informed Consent Statement: Not applicable for studies not involving humans.
Data Availability Statement: The data presented in this study are available on request from thecorresponding author.
Conﬂicts of Interest: The author declares no conﬂict of interest.

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70International Journal ofEnvironmental Researchand Public Health
ArticleTemporal and Spatial Variation of Radon Concentrations inEnvironmental Water from Okinawa Island, Southwestern Partof JapanShunya Nakasone 1, *, Akinobu Ishimine 2 , Shuhei Shiroma 3 , Natsumi Masuda 3 , Kaori Nakamura 1 ,Yoshitaka Shiroma 4 , Sohei Ooka 5 , Masahiro Tanaka 6,7 , Akemi Kato 8 , Masahiro Hosoda 9 , Naofumi Akata 10 ,Yumi Yasuoka 11 and Masahide Furukawa 1
1

2

3

4

5
6

7

8

Citation: Nakasone, S.; Ishimine, A.;
Shiroma, S.; Masuda, N.; Nakamura,

9K.; Shiroma, Y.; Ooka, S.; Tanaka, M.;
Kato, A.; Hosoda, M.; et al. Temporal

10

and Spatial Variation of Radon
Concentrations in Environmental

11

Water from Okinawa Island,Southwestern Part of Japan. IJERPH*

Graduate School of Engineering and Science, University of the Ryukyus, Nishihara,
Okinawa 903–0213, Japan; k198345@eve.u-ryukyu.ac.jp (K.N.); m_furu@sci.u-ryukyu.ac.jp (M.F.)
Department of Radioecology, Institute for Environmental Sciences, Rokkasho, Aomori 039–3212, Japan;
aki_ishi@ies.or.jp
Faculty of Science, University of the Ryukyus, Nishihara, Okinawa 903–0213, Japan;
shiromashuhei1101@gmail.com (S.S.); 83ka.ha.ho@gmail.com (N.M.)
Faculty of Education, University of the Ryukyus, Nishihara, Okinawa 903–0213, Japan;
y_shiro@cs.u-ryukyu.ac.jp
Nanto Co., Ltd., Naha, Okinawa 900–0013, Japan; oooka@gyokusendo.co.jp
Department of Helical Plasma Research, National Institute for Fusion Science, National Institutes of Natural
Sciences, Toki, Gifu 509–5292, Japan; tanaka.masahiro@nifs.ac.jp
School of Physical Sciences, The Graduate University for Advanced Studies, SOKENDAI, Toki,
Gifu 509–5292, Japan
Department of Engineering and Technical Services, National Institute for Fusion Science, National Institutesof Natural Sciences, Toki, Gifu 509–5292, Japan; kakemi@nifs.ac.jp
Department of Radiation Science, Hirosaki University Graduate School of Health Sciences, Hirosaki,
Aomori 036–8564, Japan; m_hosoda@hirosaki-u.ac.jp
Department of Radiation Chemistry, Institute of Radiation Emergency Medicine, Hirosaki University,
Hirosaki, Aomori 036–8564, Japan; akata@hirosaki-u.ac.jp
Radioisotope Research Center, Kobe Pharmaceutical University, Kobe, Hyogo 658–8558, Japan;
yasuoka@kobepharma-u.ac.jp
Correspondence: k198602@eve.u-ryukyu.ac.jp; Tel.: +81–3998-1029

2021, 18, 998.
https://doi.org/10.3390/
ijerph18030998
Academic Editor: Paul B. Tchounwou
Received: 28 December 2020
Accepted: 20 January 2021
Published: 23 January 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional afﬁliations.

Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.

Abstract: In this study, to get a better understanding in characterizing groundwater and ensure its
effective management, the radon concentrations in water samples were measured through Ryukyu
limestone in southern Okinawa Island, Japan. Water samples were collected from a limestone cave
(Gyokusendo cave, dropping water) and two springs (Ukinju and Komesu, spring water), and theradon concentrations were measured by liquid scintillation counters. The radon concentrations inthe samples from the Gyokusendo cave, and Ukinju and Komesu springs were 10 ± 1.3 Bq L−1 ,3.2 ± 1.0 Bq L−1 , and 3.1 ± 1.1 Bq L−1 , respectively. The radon concentrations showed a gradually
increasing trend from summer to autumn and decreased during winter. The variation of radon
concentrations in the dripping water sample from the Gyokusendo cave showed a lagged response
to precipitation changes by approximately 2–3 months. The estimated radon concentrations in thedripping water sample were calculated with the measured radon concentrations from the dripping
water obtained during the study period. Based on our results, groundwater in the Gyokusendo cavesystem was estimated to percolate through the Ryukyu limestone in 7–10 days, and the residence timeof groundwater in the soil above Gyokusendo cave was estimated to be approximately 50–80 days.
This work makes a valuable contribution to the understanding of groundwater processes in limestone
aquifers, which is essential for ensuring groundwater sustainability.

This article is an open access article
distributed under the terms andKeywords: radon concentration; groundwater; residence time; limestone aquifer; Okinawa Island

conditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

71

IJERPH 2021, 18, 998. https://doi.org/10.3390/ijerph18030998

https://www.mdpi.com/journal/ijerph

IJERPH 2021, 18, 998

1. Introduction
Radon is a radioactive noble gas with an atomic number of 86. Although there aremany isotopes of radon, only three occur in the natural environment: 222 Rn, 220 Rn (Thoron),and 219 Rn (Actinon), with half-lives of 3.8 d, 55.6 s, and 3.9 s, respectively. 222 Rn is the mostfrequently used radon isotope due to its relatively long half-life compared to thoron andactinon. Hereinafter, “radon” refers to 222 Rn. Radon is a natural radionuclide belonging to
the uranium (238 U) decay series, with radium (226 Ra) as a parent nuclide. The 238 U decay
series ends with 206 Pb, a stable isotope of lead. Inhalation of radon and its decay products isbelieved to increase the risk of lung cancer [1]. Most radon in the environment is producedby the alpha decay of radium in the soil and rocks. Since radon is extremely soluble inwater (e.g., 0.295 cm3 kg−1 at 15 ◦ C), there may be an exchange and equilibrium between
pore-water and pore-gas when the soil is unsaturated [2]. In addition, radon is chemicallyinert. Therefore, if it is dissipated from soil grains into pore water or voids, it can migrate
relatively far from where it is produced by advection or diffusion [2]. Eventually, some of
the radon dissipated in the pore water migrates to the groundwater and is dissolved inspring or hot spring water. Radon, which is widely distributed in the natural environment,
is commonly used to study atmospheric transport processes and groundwater ﬂow systems
such as groundwater recharge, ﬂow, and discharge [3,4].
Radon can be used as a hydrological tracer for estimating the residence time of groundwater under very special boundary conditions (e.g., in limestone areas or for submarine
groundwater discharge in the coastal zone) [5–7]. In karst aquifers, researchers have analyzed radon concentrations to understand the recharge dynamics of water passing throughthe soil layer to the saturated zone [8]. Additionally, groundwater and soil radon concentrations are measured during irrigated and non-irrigated periods in paddy ﬁelds, and thedifference in the concentration values between groundwater and surface water is used toevaluate surface water inﬁltration into the aquifer [9]. Radon can also be used for estimating
the probability of geophysical risk events such as volcanic activity and earthquakes [10–12].
Pre-earthquake radon anomalies have been found in soil gases, groundwater, and springwater [13,14]. Radon serves as a useful geochemical tracer for studying the short-term
environmental characteristics of cave systems, such as the ﬂow of the atmospheric circulation. Variations in the air density and atmospheric radon concentrations inside and outside
caves have been reported for the seasonal natural ventilation in the cave [15–17].
The storage capacity of a limestone layer alone is low due to it being highly permeable
and porous. However, when a limestone layer overlies an impermeable layer in a nonconformant way, as is the case on Okinawa Island, the limestone serves as an aquifer.
Limestones can serve as excellent natural aquifers and provide drinking water to 25% of
the world’s population [18]. Moreover, water in limestone aquifers is the only available
drinking water in some regions and serves as a valuable water source for agriculture [18].
Okinawa Island, a Japanese island in the East China Sea, is characterized by shortand steep river channels. Moreover, because its watershed area is small, the rainfall isdischarged directly into the ocean. Okinawa Island experienced a relatively high annual
precipitation of 2040 mm during the 1981–2010 period [19]. However, due to signiﬁcantseasonal and interannual changes, the ﬂow of rivers on the island is unstable and theamount of water available is limited. Therefore, it is difﬁcult to secure stable water resourcesin Okinawa Island from river water alone and part of the water for agriculture and domestic
use is provided by groundwater. To establish a stable supply and ensure the sustainable useof groundwater in the future, it is necessary to determine the groundwater characteristics,
such as availability and residence time, in limestone aquifers. However, because of theheterogeneous permeability and complex hydrogeological structure of limestone, it is
difﬁcult to understand the behavior of groundwater from existing numerical models. For
example, groundwater inﬁltration and residence time in limestone aquifers vary with eachprecipitation event.
Characteristics of local groundwater processes can be inferred from radon measurements. Shiroma et al. (2016) intermittently measured the radon concentration in dripping
72

IJERPH 2021, 18, 998

water exuding from the ceiling of a cave and reported that it is a potential source of radonin the cave atmosphere [20]. Although other factors may be involved, by comparing radon
concentrations and monthly precipitation, changes in radon concentrations were shown tocorrespond to precipitation changes after a delay of 60–90 days. Furthermore, groundwater was calculated to percolate through the Ryukyu limestone in 9 to 10 days. However,
the radon concentration data were collected intermittently for only one year and only at
one site.
The main objective of this study is as attempt to calculate the residence time ofgroundwater in limestone areas. The study area comprised a limestone cave and two
springs in the southern part of Okinawa Island. The residence time of groundwaterfrom the soil to the cave was calculated based on the relationship between the radon
concentration of the dripping water from the cave ceiling and the monthly precipitation.
Moreover, we sampled two springs in the study area to understand the spatial distributionof radon concentrations in the groundwater.
2. Materials and Methods
2.1. Overview of the Study Site
Okinawa Prefecture, located in southwestern Japan, is the only prefecture in the country with a subtropical climate (Figure 1A). Ryukyu limestone, which originates from coral
reef sediments, formed approximately one million to 500,000 years ago [21]. Limestone is
widely distributed, and there are numerous limestone caves in Okinawa. The southern partof Okinawa Island consists of the Neogene-Quaternary Shimajiri Group and the Ryukyu
Group, with low-lying terrain below 200 m in elevation. The Shimajiri Group of the Neogene Pliocene is predominantly composed of mudstone and is prone to erosion, while
the limestone Quaternary Pleistocene Ryukyu Group, which is predominantly composedof limestone, is more resistant to erosion and forms a ﬂat-surfaced topography [22]. The
Ryukyu limestone overlies the Shimajiri Group in a non-conformant way. The Ryukyu
limestone is permeable, while the Shimajiri Group is impermeable [23]. Therefore, Ryukyu
limestones serve as aquifers in Okinawa Island (i.e., Ryukyu aquifer).

Figure 1. Locations of the study area (A) and sampling sites (B). The white square shows the Automated Meteorological
Data Acquisition System (AMeDAS) situated at Itokazu.

Okinawa Island has three major soil types: Shimajiri Mahji, Kunigami Mahji, andJahgaru. Shimajiri Mahji is a dark red soil, which is widely distributed in the Ryukyu
limestone distribution area [24], with a reddish brown to dark brown color that is neutral73

IJERPH 2021, 18, 998

to slightly alkaline [25]. Dark red soil is derived from the weathering products of limestone
and/or a high-background radiation area, mainly the southeastern part of China [25].
2.2. Sample Collection
Water samples were collected from Gyokusendo cave (26◦ 08 25 N, 127◦ 44 57 W, 46 m
altitude, dripping water), Ukinju spring (26◦ 08 15 N, 127◦ 47 35 W, 6.5 m altitude, spring),
and Komesu spring (26◦ 05 18 N, 127◦ 42 04 W, 3.2 m altitude, coastal spring), all locatedin the southern portion of Okinawa Island (Figure 1B). Water samples were collected from
October 2016 to October 2020. Sample collection at Ukinju and Komesu started in April
2018 and May 2018, respectively. The collection period in the springs was delayed because
it took time to ﬁnd a location with a high ﬂow rate in the coastal area. However, data for
April to June 2020 are missing for each location due to the COVID-19 pandemic.
Gyokusendo cave is a limestone cave situated in a 120-m-thick body of Ryukyu
limestone. Shimajiri Mahji soil is distributed on the surrounding ground surface. The
total length of Gyokusendo cave reaches 5000 m, and approximately 800 m are open
for tourism [26]. A concrete staircase with a height of approximately 30 m serves as an
entrance to the main cave. A branch cave in an undisclosed area about 30 m away from thestalagmite named “Shoryu no Kane” was selected as the water sampling point (Figure 2).
There are soda-straw stalactites (straws) at this site with a signiﬁcantly high drip rate.
Therefore, it was possible to collect 10 mL of dripping water in approximately 10 min. The
Ryukyu limestone is exposed at Ukinju spring and Komesu spring, and Shimajiri Mahji
is distributed in the surrounding ground surface at both sites. The Ukinju and Komesu
springs are located near the coast, 170 m and 12 m from the coastline, respectively.

Figure 2. Location of the sampling point in Gyokusendo cave (map from, Shiroma et al. 2016 [20]).

For sample collection, 20 mL high-performance glass vials (PerkinElmer, USA) containing 10 mL of high efﬁciency mineral oil scintillator (PerkinElmer, USA) were prepared.
For each site, 5 samples were collected. The water samples were collected using a syringewith the needle removed. Water samples (12 mL) were collected directly from the straw
formed in the cave ceiling in Gyokusendo cave. At the Ukinju and Komesu sites, the same
sample amounts were collected near the spring outlets. The syringe was pointed upward,
and the plunger was pressed carefully to remove air from the inside. A needle was thenattached, and the tip of the needle was positioned just over the bottom of the glass vial,
and 10 mL of sample was injected. The time elapsed from water sample injection to theclosing of the lid of the glass vial was set as the water sampling time. After water sampling,
the samples were shaken for 60 s and left in the dark for 4 h until radiative equilibrium
was achieved to extract the radon from the sample water into the mineral oil scintillator.
Temperature and humidity data in the cave were measured using HOBO Pro v2
Loggers (U23–001, ONSET, USA). However, data for December 2016 and February 2017
were missing due equipment failure. Precipitation data outside the cave were obtained fromthe Automated Meteorological Data Acquisition System (AMeDAS) situated at Itokazu
74

IJERPH 2021, 18, 998(Figure 1B). The pH and electrical conductivity (EC) of the water samples were measured
using a pH meter (AS-712pH, HORIBA) and an EC meter (B-771COND, HORIBA). To
verify the existence of saltwater inﬂow, the salinity (PSU; Practical Salinity Unit) was alsomeasured at Ukinju and Komesu spring located in the coastal area using a digital salinity
meter (HI96822, HANNA instruments).
2.3. Analysis of Radon Concentration in Water
The radon concentrations in water were measured for 60 min per sample using aliquid scintillation counter. The measurements were performed using a Quantulus 1220
(PerkinElmer, USA), at the National Institute for Fusion Science, from October 2016 to
February 2019 and a Tri-Carb 2019TR (PerkinElmer, USA), at the University of the Ryukyus
Center for Research Advancement and Collaboration, from March 2019 to October 2020.
The radon concentration CR (Bq L−1 ) was calculated using the following equation:( A0 − B0 ) exp λTp(1)
CR =f Rn V
where A0 is the counting rate (cps) of the water sample, B0 is the counting rate (cps) of the
background sample, λ is the radon decay constant (day−1 ), Tp is the elapsed period (day),which was corrected for radioactive decay to between the sampling time and the middle
measurement time, f Rn is the radon conversion factor of 3.24 cps Bq L−1 for the Quantulus
1220 and 4.5 cps Bq−1 for the Tri-Carb2019TR, and V is the sample volume (0.01 L) [27].
For measurements using the Quantulus 1220, A0 and B0 were calculated using thecounting rate cps for 600–910 ch. Additionally, for measurements using the Tri-Carb2019TR,
A0 and B0 were calculated using the counting rate cps for 0–1024 ch using the integral
counting method [27–29]. The minimum detected radon concentration MDC (Bq L−1 ) was
calculated using the following equation [30]:
ND = 4.65
MDC =

B0
2.71
+
t
t

(2)

ND
f Rn V(3)

where ND is the minimum value of net count rate (cps), t is the counting time of the sample
and the background (sec). The minimum detected radon concentrations by this method
were 1.0 Bq L−1 for the Quantulus1220 and 0.9 Bq L−1 for the Tri-Carb2019TR [30].
Uncertainties were estimated for the following components: the counting rate (cps) of
the water sample and background sample, the measurement time (s) of the water sample
and background sample, the radon decay constant (s−1 ), the elapsed period (s), the radon
conversion factor (cps Bq L−1 ), and the sample volume (L). Estimates were also made foreach of these components, which were combined to give the expanded uncertainty [31]. By
applying a coverage factor of k = 2, the expanded uncertainty was evaluated as 10%. In thisstudy, radon concentrations are expressed as the arithmetic mean ± standard deviation of
5 samples.
3. Results and Discussion
3.1. Physical Parameters and Meteorological Data
The pH and EC of the water samples and the monthly precipitation data are shown in
Figure 3. The pH and EC range of the samples from the Gyokusendo cave were 6.8–7.9,
0.76–1.52 mS cm−1 . For the Ukinju spring, the pH and EC ranged from 6.7–8.2 and 0.64
and 0.99 mS cm−1 . For the Komesu spring, the pH ranged between 6.5–8.1 and the EC
measured between 0.55 and 0.96 mS cm−1 .

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IJERPH 2021, 18, 998

Figure 3. Monthly variations for the October 2016–October 2020 period of pH (A), electrical conductivity (B), and precipitation (C) in the water samples, and temperature (D) in the Gyokusendo cave.

The results reveal no significant seasonal variation in pH and EC. The monthly precipitation ranged from 11.50–669.50 mm. The monthly precipitation tended to be higher
during the rainy season (May-June) and the typhoon season (August-October) and lower
in winter (December–February). The salinity of Ukinju spring and Komesu spring, locatednear the coast, was in the range of 0–1 PSU, and seawater contamination was not observed.
The temperature inside the Gyokusendo cave is shown in Figure 3D. The temperature
outside the cave showed a marked seasonal variation (high in summer, low in winter) of
15–27 ◦ C [19], while inside the cave, the temperature varied marginally, ranging from
23–27 ◦ C. The humidity in the cave was generally 100% throughout the measurement period.
3.2. Temporal Variation of Radon Concentrations for the Water Samples
Radon concentrations for the dripping water collected at the Gyokusendo cave ranged
from 7.1–13 Bq L−1 (Figure 4), with an average of 10 ± 1.3 Bq L−1 . The radon concentration
for the dripping water collected at the same site between May 2013 and March 2014 wasrelatively consistent and ranged between 6.4 to 15 Bq L−1 [20]. The radon concentration for the dripping water increased gradually from summer (June–August) to autumn(September–November) and then decreased in winter (December–February).

Figure 4. Radon concentration variation for the Gyokusendo cave, Ukinju spring and Komesu springwater samples collected during the October 2016–October 2020 sampling period.

76

IJERPH 2021, 18, 998

The monthly average radon concentrations of the dripping water for the entire sampling period were the highest (11 ± 0.8 Bq L−1 ) in October and the lowest (8.8 ± 1.2 Bq L−1 )in February (Figure 5). These variations were similar to the seasonal variations in atmospheric radon concentrations in the Gyokusendo cave sample (high in summer and low
in winter) observed between July 1990 and January 1993 [15–17]. The radon concentrations for the water collected at Ukinju spring and Komesu spring were 3.2 ± 1.0 Bq L−1(1.1–6.1 Bq L−1 ) and 3.1 ± 1.1 Bq L−1 (1.1–5.8 Bq L−1 ) (Figure 4). There was a gradualincrease in radon concentrations from summer to autumn. However, no clear seasonalvariation was apparent (Figure 4).

Figure 5. Variation of radon concentrations for the dripping water sample from the Gyokusendo cave compared to themonthly precipitation obtained from AMeDAS (Itokazu) for the study period.

3.3. Relationship between Radon Concentration for Dripping Water and Monthly Precipitation
The temporal variation in the radon concentrations of the dripping water from the
Gyokusendo cave and the precipitation recorded for the study period are shown in Figure 5.
The monthly precipitation was approximately 500 mm during the rainy season, increased
during the typhoon season, and decreased to approximately 100–150 mm during winter.
In May 2017, an anomalously high precipitation amount of 579 mm (equivalent
to approximately 30% of the 2017 annual precipitation) was recorded, and the radon
concentration of the dripping water in July of that year was 12 Bq L−1 , the highest recorded
in 2017. The precipitation from May to June 2018 was lower than usual, averaging a monthly
amount of 300 mm. However, in September 2018, the radon concentration in the dripping
water from the cave was exceptionally high, reaching 12 Bq L−1 . In 2019, the highest
amount of precipitation for the year (597 mm) was recorded in June, and the maximum
radon concentration for the year was recorded in September (12 Bq L−1 ). More than
600 mm of precipitation was observed in June 2020, and maximum radon concentrations of
12 Bq L−1 and 13 Bq L−1 were recorded in July and October 2020. Conversely, a decreasing
precipitation trend corresponded to a decrease in the radon concentration. Additionally,time series analysis (moving average) of the radon concentrations in dripping water andprecipitation showed a correlation between the 2-month moving average (R = 0.50) andthe 3-month moving average (R = 0.50) [32]. Therefore, variations in radon concentrationsof the dripping water samples indicated that the radon concentration increased during
77

IJERPH 2021, 18, 998

periods of heavy rainfall, although a delay of around two to three months after a monthly
precipitation change was observed. This suggests that precipitation percolates at a rate of
60 to 90 d from the soil to the Ryukyu limestone situated above the Gyokusendo cave andreaches the cave as dripping water.
Radon concentrations in groundwater reﬂect the inherent 226 Ra contents of the hostrock or formation [33]. In areas where karst aquifers are distributed, estimated radon
concentrations in the soil are higher than the radon concentrations in the groundwater.
Therefore, the main source of radon in groundwater has been reported to be soil [8].
Furthermore, the concentrations of the 238 U series in the Ryukyu limestone (8.6 Bq kg−1 )were reported to be lower than those in Shimajiri red soil (86.0 Bq kg−1 ) [34], suggestingthat the main source of radon in groundwater is the soil deposited in the upper part of
the Gyokusendo cave. Additionally, the amount of soil water inﬁltrating into the aquifer
increases with heavy precipitation [7]. In limestone areas, the residence time of soil water
was noted to reﬂect the residence time in the limestone bodies [8]. The ﬂow velocity is
proportional to the ﬂow rate and inversely proportional to the cross-sectional area of thechannel. The ﬂow velocity is the distance an object moves per unit time, the ﬂow rate is thevolume of ﬂuid per unit time ﬂowing past a point through the cross-sectional area. The
channel is referring to solution openings through the limestone. The following equations
was used to calculate the ﬂow velocity:
ν=

Q
A

(4)

where ν is the ﬂow velocity (m s−1 ), Q is the ﬂow rate (m3 s−1 ), and A is the cross-sectional
area of the channel (m2 ). It is assumed that the main source of radon in groundwater isthe soil deposited in the upper part of the Gyokusendo cave and that the cross-sectional
area of the channel does not change signiﬁcantly. Therefore, radon in the dripping water
is derived from radon in the soil pore water, which is governed by the soil 226 Ra content
and the residence time of groundwater in the Ryukyu limestone. Moreover, the amountof groundwater in the Ryukyu limestone depends on precipitation. High precipitation
rates shorten the residence time of groundwater in the Ryukyu limestone by increasing
inﬁltration into the soil, which accelerates the groundwater ﬂow velocity. Low precipitation
rates reduce inﬁltration into the soil, thus, decreasing the groundwater ﬂow velocity andincreasing the residence time of groundwater. Attenuation is constant (the half-life, 3.8 day)over time. Therefore, the longer the residence time, the lower the radon concentration andvice versa. In this study, the radon concentration trends correlated with the precipitation
trends, suggesting that the soil may be the source of radon in the groundwater. Moreover,the variation in the radon concentration of the dripping water sample may have been due
to the residence time of groundwater in the Ryukyu limestone.
3.4. Estimation of Residence Time Using Radon Decay in the Dripping Water
A schematic of a vertical section of the Gyokusendo cave is shown in Figure 6. In
the ﬁgure, A shows the boundary between the soil and the Ryukyu limestone, and B isa straw stalactite on the cave ceiling where the dripping water is collected. Precipitation
percolates through the soil and limestone bodies above the cave and seeps into the cavefrom the ceiling as dripping water. Since radon is rarely present in precipitation, radonin groundwater is mainly supplied by the soil. The concentration of radon in waterinﬁltrated into the ground increases with time due to the supply of radon produced by soil
particles. However, as the concentration increases, the number of decaying radon atoms
increases, and eventually, an equilibrium state is reached where supply and decay are
equal. Therefore, radon in the soil water and 226 Ra in the solid phase are in permanentequilibrium. Additionally, if radon remains in the soil long enough, the concentration ofradon in the gas and liquid phases will reach the equilibrium state speciﬁc to each soil

78

IJERPH 2021, 18, 998

species. The following equations were used to quantify the radon concentration in soil
water and the gas phase at gas-liquid equilibrium:
Ew = KT Ea(5)where Ew is the radon concentration in soil water (kBq m−3 ), KT is the radon partition
coefﬁcient, and Ea is the radon concentration in the gas phase (kBq m−3 ). The radon
partition coefﬁcient was calculated using the following equation [35]:
KT =

9.12
17.0 + T(6)

where T is the temperature (◦ C), and the mean value of the temperature in the cave, 24.9 ◦ C,
was used.

Figure 6. Schematic of the Gyokusendo cave proﬁle, where A is the boundary between the soil and the limestone, and B is
the target straw stalactite.

According to the UNSCEAR 2000 (United Nation Scientiﬁc Committee on the Effectsof Atomic Radiation 2000), the concentration of radon in soil pore gas Ea (Bq m−3 ) can becalculated using the following equation [36]:Ea = CRa f ρs ε−1 (1 − ε) [m(KT − 1) + 1]−1(7)

is the concentration of 226 Ra in the soil (Bq kg−1 ), f is the radon emanation

where CRa
coefﬁcient, ρs is the density of solid particles (kg m−3 ), ε is the porosity, and m is the water
saturation. In this study, based on a previous report [37], the radon emanation coefﬁcientfor typical soil on Okinawa Island was set to 0.40, the concentration of 226 Ra in soil was
set to 106 Bq kg−1 dry, the solid particle density was set to 2697 kg m−3 , and the porosity
was set to 0.67. The water saturation was 0.95, which is representative of the UNSCEAR
2000 [36]. The radon partition coefﬁcient KT was calculated using Equation (6) [35]. Since
we could not directly measure the soil temperature, we used the temperature in the cave
(24.9 ◦ C) as approximation of the soil temperature. Radon concentrations (Bq m−3 ) in soil
water were calculated using Equation (5). The above values were deﬁned as the radon
concentration in the groundwater at point A (Figure 6).
Because radon was not supplied from the Ryukyu limestone, we assumed that theradon concentration in the groundwater was attenuated by the residence time of thegroundwater in the Ryukyu limestone. The estimated radon concentration in the dripping
79

IJERPH 2021, 18, 998

water sample Ed , exuding from point B (Figure 6), was calculated using the estimatedradon concentration in soil water from Equation (5) and the following equation.
Ed = Ew exp(−λt)(8)

where t is the residence time (days) of groundwater in the Ryukyu limestone.
The estimated radon concentrations in the dripping water sample calculated from
Equation (8) were compared with the measured radon concentrations in the dripping waterobtained during the study period. The radon concentration in the soil pore gas calculated
from Equation (7) was 215 kBq m−3 . The radon concentration in the soil pore water
calculated from Equation (5) was 46.8 kBq m−3 . Radon concentrations for the dripping
water sample obtained during the study period ranged from 7.1–13 kBq m−3 as shown in
Figure 4. Based on the decay of radon (half-life: 3.8 d) from point A (estimated values) topoint B (measured values) and the assumption that the residence time of soil and Ryukyu
limestone is 60 to 90 d, the residence time of groundwater in the Ryukyu limestone wasestimated to be 7 to 10 d. These results are generally consistent with previously reported
values (9–10 d) [20]. Moreover, the residence time of groundwater in the soil deposited in
the upper part of the Gyokusendo cave was estimated to be approximately 50 to 80 d.
The residence time of groundwater in the Ryukyu limestone at the Ukinju spring
and Komesu spring sites was also calculated from Equation (8). For this calculation, we
assumed that no radon was supplied from the Ryukyu limestone, the soil was uniformly
deposited, and the radon concentration in the soil was in radiative equilibrium. The radon
concentrations for the water samples from the Ukinju spring and Komesu spring sites
ranged from 3.1–6.1 Bq L−1 and 1.1–5.8 Bq L−1 , respectively. Based on the radon attenuation
between the measured radon concentrations in the water samples and the estimated radon
concentrations in the pore water, the residence times in the Ryukyu limestone at Ukinju
spring and Komesu spring were estimated to be 12 to 21 d and 12 to 19 d, respectively.
Nakaya et al. (2018) reported an average residence time in the Ryukyu limestone aquiferof 14–34 years based on the results of SF6 concentrations in the spring and well wateraround the Komesu spring site [38]. The residence time estimated in this study is very
limited because it was calculated based on observations at only one point in the catchment.
Although we were able to calculate the residence time, our results signiﬁcantly differ fromthose of previous studies. In the future, it will be necessary to discuss the residence timeafter considering additional factors such as the frequency of collection, and number of sites,and depth of sampling sites.
4. Conclusions
Radon concentrations for dripping water and spring water samples were collected in
the southern part of Okinawa Island from October 2016 to October 2020. The estimatedradon concentrations in the dripping water sample were calculated with the measuredradon concentrations from the dripping water obtained during the study period. Based on
our results, we determined the following:
(1)

(2)

The radon concentrations in the water samples from the Gyokusendo cave, Ukinju spring, and Komesu spring were 10 ± 1.3 Bq L−1 , 3.2 ± 1.0 Bq L−1 , and
3.1 ± 1.1 Bq L−1 , respectively. Radon concentrations for the water samples showed agradually increasing trend from summer to autumn and decreased in the winter. Thiswas particularly noticeable in the radon concentrations measured in the dripping
water sample from the Gyokusendo cave.
From the variation in the radon concentrations for the dripping water and precipitation, we estimated that the radon concentration changes in the dripping waterlags precipitation changes by approximately 2–3 months. These results indicate thatprecipitation takes 60 to 90 d to percolate into the soil and accumulate in the Ryukyu
limestone overlying the Gyokusendo cave. The water then enters the cave as dripping
water from the cave ceiling.
80

IJERPH 2021, 18, 998

(3)

(4)

From a simple radon behavior model, groundwater in the Gyokusendo cave system
was estimated to percolate through the Ryukyu limestone in 7 to 10 d, and theresidence time of groundwater in the soil above the Gyokusendo cave was estimatedat approximately 50 to 80 d.
The residence times of groundwater in the Ryukyu limestone at the Ukinju spring
and Komesu spring sites were calculated to be 12 to 21 d and 12 to 19 d, respectively.
However, this estimation was lower than that of previous studies (14–34 years).
Therefore, it will be necessary for future studies to discuss the residence time after
understanding factors such as the frequency of collection, and the number of sites,and depth of sampling sites. Additionally, to verify the residence time and mixing ofgroundwater in the area, radioactive isotopes with longer half-lives, such as tritium(half-life: 12.3 y) should be analyzed in the future.

Author Contributions: Conceived and designed the survey: S.N., Y.S., N.A., M.F. Performed experiments: S.N., A.I., S.S., N.M., S.O., K.N., A.K. Analyzed the data: S.N., A.I., S.S., N.M. Wrote the paper:
S.N. Acquired the funding: S.N., M.T., N.A., M.H., Y.S. Contributed to discussions: S.N., Y.S., N.A.,
Y.Y., M.F. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by JSPS KAKENHI Grant Number JP20J12397 and 18K14543, the
NIFS budget NIFS20KLEA046 and NIFS18KNWA002.
Acknowledgments: The radon concentration analyses were performed at the National Institute for
Fusion Science, University of the Ryukyus Center of Research Advancement and Collaboration.
Conﬂicts of Interest: The authors declare that they have no conﬂict of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleDiscriminative Measurement of Absorbed Dose Rates in Air
from Natural and Artiﬁcial Radionuclides in Namie Town,
Fukushima Prefecture
Koya Ogura 1 , Masahiro Hosoda 1,2 , Yuki Tamakuma 1,2 , Takahito Suzuki 1,† , Ryohei Yamada 1,‡ , Ryoju Negami 1 ,Takakiyo Tsujiguchi 1 , Masaru Yamaguchi 1 , Yoshitaka Shiroma 3 , Kazuki Iwaoka 4 , Naofumi Akata 2 ,Mayumi Shimizu 2 , Ikuo Kashiwakura 1 and Shinji Tokonami 2, *
1

2

3

4

*
†
‡

Graduate School of Health Sciences, Hirosaki University, 66-1 Hon-cho, Hirosaki, Aomori 036-8564, Japan;
kogura@hirosaki-u.ac.jp (K.O.); m_hosoda@hirosaki-u.ac.jp (M.H.); tamakuma@hirosaki-u.ac.jp (Y.T.);
suzuki-takahito@fujielectric.com (T.S.); yamada.ryohei@jaea.go.jp (R.Y.); h20gg204@hirosaki-u.ac.jp (R.N.);
r.tsuji@hirosaki-u.ac.jp (T.T.); masarun@hirosaki-u.ac.jp (M.Y.); ikashi@hirosaki-u.ac.jp (I.K.)
Institute of Radiation Emergency Medicine, Hirosaki University, 66-1 Hon-cho, Hirosaki,
Aomori 036-8564, Japan; akata@hirosaki-u.ac.jp (N.A.); mshimizu@hirosaki-u.ac.jp (M.S.)
Faculty of Education, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Okinawa 903-0213, Japan;
y_shiro@cs.u-ryukyu.ac.jp
National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage,
Chiba 263-0024, Japan; iwaoka.kazuki@qst.go.jp
Correspondence: tokonami@hirosaki-u.ac.jp
Present address: Fuji Electric Co., Ltd., 1 Fujimachi, Hino, Tokyo 191-8502, Japan.
Present address: Radiation Protection Department, Nuclear Fuel Cycle Engineering Laboratories, Japan
Atomic Energy Agency, 4-33 Muramatsu, Tokai, Ibaraki 319-1194, Japan.

Citation: Ogura, K.; Hosoda, M.;
Tamakuma, Y.; Suzuki, T.; Yamada, R.;
Negami, R.; Tsujiguchi, T.;
Yamaguchi, M.; Shiroma, Y.; Iwaoka,
K.; et al. Discriminative Measurementof Absorbed Dose Rates in Air fromNatural and Artiﬁcial Radionuclides
in Namie Town, Fukushima
Prefecture. IJERPH 2021, 18, 978.
https://
doi.org/10.3390/ijerph18030978
Academic Editor: Paul B. Tchounwou
Received: 28 December 2020
Accepted: 18 January 2021
Published: 22 January 2021

Publisher’s Note: MDPI stays neutral
with regard to jurisdictional claims inpublished maps and institutional afﬁl-

Abstract: Ten years have elapsed since the accident at the Fukushima Daiichi Nuclear Power Plant
in 2011, and the relative contribution of natural radiation is increasing in Fukushima Prefecture
due to the reduced dose of artiﬁcial radiation. In order to accurately determine the effective doseof exposure to artiﬁcial radiation, it is necessary to evaluate the effective dose of natural as well as
artiﬁcial components. In this study, we measured the gamma-ray pulse-height distribution over
the accessible area of Namie Town, Fukushima Prefecture, and evaluated the annual effective doseof external exposure by distinguishing between natural and artiﬁcial radionuclides. The estimatedmedian (range) of absorbed dose rates in air from artiﬁcial radionuclides as of 1 April 2020, is 133(67–511) nGy h−1 in the evacuation order cancellation zone, and 1306 (892–2081) nGy h−1 in the
difﬁcult-to-return zone. The median annual effective doses of external exposures from natural andartiﬁcial radionuclides were found to be 0.19 and 0.40 mSv in the evacuation order cancellation zone,
and 0.25 and 3.9 mSv in the difﬁcult-to-return zone. The latest annual effective dose of external
exposure discriminated into natural and artiﬁcial radionuclides is expected to be utilized for radiation
risk communication.
Keywords: Fukushima Daiichi Nuclear Power Plant; Namie Town; natural radionuclides; artiﬁcial
radionuclides; cesium-134; cesium-137; external exposure dose evaluation

iations.

1. Introduction
Copyright: © 2021 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms andconditions of the Creative Commons
Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

On 11 March 2011, a magnitude 9.0 earthquake struck the Tohoku region along theeastern coast of Japan. The earthquake caused a tsunami with a height of more than 15 m,
and affected the Fukushima Daiichi Nuclear Power Plant (FDNPP). The FDNPP lost power
and the cores of Units 1 to 3 became heated and melted. This caused a hydrogen gas
explosion [1]. As a result of the FDNPP accident, 132 Te, 131 I, 134 Cs, 137 Cs, and rare gases
such as 133 Xe, etc., were released into Fukushima Prefecture and other eastern regions ofJapan [2]. The radioactivity of radionuclides released into the atmosphere is shown in the
UNSCEAR 2013 report (Table 1) [3]. On the day of the accident, the Japanese government83

IJERPH 2021, 18, 978. https://doi.org/10.3390/ijerph18030978

https://www.mdpi.com/journal/ijerph

IJERPH 2021, 18, 978issued an indoor evacuation order to residents within 10 km of the FDNPP, and issued anevacuation order to residents within 20 km the next day [4]. Thereafter, the area where
the annual cumulative dose may have exceeded 20 mSv, outside the 20 km area from the
FDNPP was designated as a “planned evacuation zone”. In addition, regardless of theannual cumulative dose, the area within 20 to 30 km of the FDNPP was designated as
an “emergency evacuation preparation zone” and the area within 20 km was designatedas a “warning zone” [5]. Namie Town, Fukushima Prefecture (The location map that isshown in Figure 1a was made by original maps from d-maps.com), is also one of the areas
signiﬁcantly contaminated by radionuclides due to the FDNPP accident, and because it
was a planned evacuation zone, the townspeople living there were forced to evacuate.
In 2012, the area where the annual cumulative dose was conﬁrmed to be 20 mSv or less was
designated as an “evacuation order cancellation preparation zone”. This is the area where
temporary return homes, restricted businesses such as shops, hospitals, and farming are
permitted. Areas where the annual cumulative dose may exceed 20 mSv but are conﬁrmed
to be 50 mSv or less have been designated as a “restricted residence zone” and it has
become possible to temporarily return home or enter for road restoration. Areas where
the annual cumulative dose exceeds 50 mSv and the annual cumulative dose may not fall
below 20 mSv, ﬁve years from 2012, has been designated as a “difﬁcult-to-return zone”.
Figure 1b indicates each area division, and taken from the ofﬁcial website of Fukushima
Prefecture [5]. Subsequently, the artiﬁcial decontamination of radionuclides was actively
promoted, and in 2017, six years after the earthquake, evacuation orders were lifted in someareas of Namie Town [6]. Currently, the return of evacuees is progressing, and by the endof November 2020, more than 1500 people were living in Namie Town [7]. Before the Great
East Japan Earthquake, the registered population of Namie Town was 21,434 [8]. Years after
the FDNPP accident, the returning residents continue to have a signiﬁcant amount ofradiation anxiety [9]. Experts in radiation science and psychology at each Japanese support
organization, including the university of the current authors, have communicated radiation
risk, and interacted with residents to reduce anxiety about radiation. In consideration ofthis, Kudo et al. conducted a questionnaire survey on the basic knowledge of radiation
among those who returned to Namie Town. It was found that many Namie townspeople
recognize that natural and artiﬁcial radiation have different effects on the human body,even if the effective dose is the same [10].
Since the FDNPP accident, national staff and researchers at universities and research
institutions have been evaluating artiﬁcial radioactive contamination and investigating the
distribution of ambient dose equivalent rates [11–13]. In addition, internal and external
exposures from artiﬁcial radionuclides are being evaluated [14–19], and monitoring posts
are installed in various locations to continuously measure the ambient dose equivalent
rate [20]. In 2017, Shiroma et al. conducted a car-borne su rvey in Namie Town, Fukushima
Prefecture, and reported that the absorbed dose rate in air was 0.041–11 μGy h−1 [21].
More than nine years have passed since the FDNPP accident, and the relative contributionof natural radiation to ambient dose equivalent rates is increasing because the dose ofartiﬁcial radiation is decreasing. This means that it is not possible to estimate the effects on
the human body due to artiﬁcial radionuclides, without correctly evaluating the dose fromnatural radionuclides. People with a high risk of internal exposure, such as agricultural
workers, need information on internal exposure due to inhalation of dust. However, clarifying the actual conditions of external exposure from natural and artiﬁcial radionuclides isuseful for radiation risk communication for general population, which has a low risk ofinternal exposure. In this study, the gamma-ray pulse-height distribution was measured
and analyzed in Namie Town, which was divided into 1 km × 1 km meshes. An absorbed
dose rate map that discriminated between natural and artiﬁcial radionuclides was createdfrom the absorbed dose rate in the air, and the annual effective dose to external exposure
was calculated.

84

IJERPH 2021, 18, 978

Table 1. The estimated value of the quantity of typical radionuclides released into the atmosphere by the Fukushima Daiichi
Nuclear Power Plant (FDNPP) accident.
The Estimated Value of the Quantity of Radionuclides Released into the Atmosphere (Bq)
132 Te

131 I

132 I

133 I

133 Xe134 Cs136 Cs137 Cs

2.9 × 1016

1.2 × 1017

2.9 × 1016

9.6 × 1015

7.3 × 1018

9.0 × 1015

1.8 × 1015

8.8 × 1015

(a)

(b)

Figure 1. (a) Location of Namie Town, Fukushima Prefecture, Japan, and (b) ofﬁcially designed evacuation zones asof 1 April 2017. (a) is created by d-maps.com (https://d-maps.com/carte.php?num_car=29487, https://d-maps.com/
carte.php?num_car=11273). (b) is taken from the ofﬁcial website with permission from the administrative ofﬁcer inFukushima Prefecture [5].

2. Materials and Methods
2.1. Measurement Location and Method of γ-Ray Pulse-Height Distribution
From 15 September 2016 to 13 December 2019, gamma-ray pulse-height distributions
were obtained at the 130 accessible points that divided the entire area of Namie Town
into a mesh of 1 km × 1 km. A 3 × 3-inch NaI(Tl) scintillation spectrometer (EMF-211,
EMF Japan Co., Himeji, Japan [22]) was used to obtain the measurements. The detector was
installed 1 m above the ground and connected to a control laptop PC. The measurement
time was 900 s. Latitude and longitude coordinate data were obtained using a Global Positioning System to create an absorbed dose rate map. Gamma-ray pulse-height distributionsat 2–5 points were additionally acquired in six of the 130 meshes, and the ﬂuctuation of theabsorbed dose rate in air in the mesh was evaluated.
2.2. Analysis of Gamma-Ray Pulse-Height Distribution and Correction of Absorbed Dose Ratein Air
The gamma-ray pulse-height distributions obtained by the NaI(Tl) scintillation spectrometer is different from the distributions of the gamma-ray energy spectrum. The pulseheight distributions of gamma-ray are unfolded into the energy spectrum by a response
matrix of 49 rows × 49 columns, and then the dose contributions for each radionuclide arecalculated according to the previous reports to discriminate between natural and artiﬁcial
radionuclides [23–25]. The absorbed dose rate in air obtained by the analysis needs to be
85

IJERPH 2021, 18, 978corrected to consider the number of days elapsed from the measured date. Factors that
reduce radioactivity in the environment include the physical half-life of radionuclides,
diffusion by wind, rain, and inﬁltration into soil, and the implementation of artiﬁcial decontamination of radioactive substances. In order to comprehensively evaluate the factors that
affect the attenuation of radioactivity, the apparent half-life was calculated using the dataof the air dose rate that is regularly observed at the monitoring posts widely installed in
Namie Town. There are 103 monitoring posts in Namie Town, and the measurement data
are published on the website [20]. Some of these datasets have long-term data loss within
the period in which we measured the gamma-ray pulse-height distribution, and signiﬁcantdose increases and decreases in a short period of time that are not due to artiﬁcial decontamination. It is probable that the data loss could not be measured due to maintenance ofthe monitoring posts. The short-term signiﬁcant ﬂuctuation of the ambient dose equivalent
rate may be due to a device malfunction, but the speciﬁc cause is unknown. These data
may affect the appropriate time decay correction of absorbed dose rates in air. Therefore,
the apparent half-life was calculated using the data of 55 monitoring posts, and excluding
the lossy dataset and coefﬁcient of determination R2 of less than 0.7 (not due to artiﬁcial
decontamination) in the exponential approximation of the ambient dose equivalent rate.
Equation (1) was used to calculate the apparent half-life (Ta ).
Ta = t ×

0.693
ln

D1
D0

(1)

where D0 and D1 are the ambient dose equivalent rates (μSv h−1 ) as of 1 April 2016,
and 1 April 2020, respectively, and t is the elapsed time, which was taken as used four
years. The FDNPP accident released short half-life radionuclides such as 131 I and 133 Xeand long half-life radionuclides such as 134 Cs and 137 Cs. Originally, it was necessary to
calculate the apparent half-life for each of the short-half-life and long-half-life radionuclides,
but now that nine years have elapsed since the accident, the contribution from the shorthalf-life radionuclides can be ignored [26,27]. The apparent half-life was calculated using
the simple formula in Equation (1), considering only the contribution from radionuclides
with a long half-life. The calculated apparent half-life was divided into an evacuation
order cancellation zone and a difﬁcult-to-return zone, and the ﬂuctuation was evaluated to
examine the application to the correction of the absorbed dose rate in air.
2.3. Estimating the Effective Dose of External Exposure
The annual effective dose of external exposure in Namie Town was estimated using
Equation (2), and the time-corrected absorbed dose rate in air.
E = D × DCF × T × (Qin × R + Qout )(2)

where D is the time-corrected absorbed dose rate in air (nGy h−1 ) and DCF is a doseconversion factor (Sv Gy−1 ) from the absorbed dose rate in air to the effective dose toexternal exposure. The natural radionuclide component DCF uses 0.748, as reported by
Moriuchi et al., and the artiﬁcial radionuclide uses 0.73, as reported by Omori et al. [28,29].
T is the number of hours per year, which is 8766 h (24 h × 365.25 d). Qin is the indoor occupancy factor, Qout is the outdoor occupancy factor, and they are 0.83 and 0.17, respectively,
as reported by Ploykrathok et al. [30]. R is a reduction factor, the natural radionuclide is 1,
and the artiﬁcial radionuclide is 0.43, as reported by Yoshida et al. [31].
3. Results and Discussion
3.1. Absorbed Dose Rate in Air and Dose Rate Map
The gamma-ray pulse-height distribution was measured over the entire accessiblearea of Namie Town and was developed using a response matrix to determine the absorbed
dose rate in air. The absorbed dose rates in air of the natural radionuclides, artiﬁcial ra86

IJERPH 2021, 18, 978

dionuclides, and their totals are 15–68, 14–11,861, and 47–11,900 nGy h−1 , respectively.
The total absorbed dose rate in air obtained in this study is almost in agreement with
the 0.041–11 μGy h−1 measured by Shiroma et al. [21]. The absorbed dose rates in airof natural radionuclides, artiﬁcial radionuclides, and their totals in the evacuation ordercancellation zone are 19–51, 14–2010, and 47–2040 nGy h−1 , respectively. The natural,
artiﬁcial, and their total absorbed dose rates in air in the difﬁcult-to-return zone are 15–
68, 140–11,861, and 186–11,900 nGy h−1 , respectively. The radioactivity ratios of cesium(134 Cs/137 Cs) released from Units 1, 2, and 3 of the FDNPP were reported to be 0.941,
1.082, and 1.046, respectively [32]. This radioactivity ratio is evaluated as the value as of
11 March 2011. As a result of estimating 134 Cs/137 Cs as of March 2011 for the measured
data, the median (range) was 1.07 (1.04–1.09), and it was conﬁrmed that 134 Cs and 137 Cs
were released from FDNPP. The apparent half-life was calculated by analyzing the datasetsof 55 monitoring posts installed in Namie Townin order to time-correct the measured
absorbed dose rate in air. A total of 32 of them were located in areas exceeding 1.0 μGy h−1
as of April 2016. 10 of them were located in areas exceeding 1.0 μGy h−1 as of April 2020.
The mean ± standard deviation, coefﬁcient of variation, and median (range) of apparent
half-lives in the difﬁcult-to-return zone are 4.2 ± 1.4 y, 33%, and 4.7 (4.0–4.8) y, respectively(Appendix A Table A1). Considering that the half-life of 137 Cs is approximately 30 years,
the reason why the apparent half-life is shortened is seemingly strongly inﬂuenced bydiffusion due to environmental factors. The mean ± standard deviation, coefﬁcient ofvariation, and median (range) of the apparent half-life in the evacuation order cancellation
zone are 4.8 ± 2.7 y, 56%, and 4.7 (2.3–6.7) y, respectively. It was found that there arevariations in the areas where residence is allowed. The apparent half-life was calculatedusing the data from 1 April 2016 to 1 April 2020. A detailed review of the data for eachmonitoring post revealed that some areas were decontaminated after April 2016, and somewere decontaminated prior to that date [33]. The implementation of artiﬁcial decontamination contributes to rapid dose reduction and signiﬁcantly shortens the apparent half-life.
Therefore, the evacuation order cancellation zone was further divided into areas where
decontamination was conducted before, and on and after, April 2016, and the apparent
half-life was analyzed. Figure 2 indicates the difﬁcult-to-return zone, evacuation order cancellation zone decontaminated before April 2016, and evacuation order cancellation zone
decontaminated on, and after, April 2016 areas. The mean ± standard deviation, coefﬁcientof variation, and median (range) of the apparent half-life in the evacuation order cancellation zone are 6.4 ± 2.0 y, 31%, and 6.1 (5.0–7.5) y, respectively (Appendix A Table A2).
Conversely, the mean value ± standard deviation, coefﬁcient of variation, and median(range) of the apparent half-life limited to the zones where decontamination was completed
after 1 April 2016, are 2.0 ± 0.6 y, 30%, 1.8. (1.6–2.3) y, respectively (Appendix A Table A3).
A signiﬁcant difference test was performed using the Mann–Whitney U test for the apparent half-life of the evacuation order cancellation zone decontaminated before, and on
and after, April 2016. It was conﬁrmed there was a signiﬁcant difference between thetwo groups (p-value < 3.8 × 10–7 ). This result demonstrates that the implementation of
decontamination signiﬁcantly contributes to the reduction of the ambient dose equivalent
rates from artiﬁcial radionuclides. In addition, it was found that the evacuation ordercancellation zone can be evaluated with a ﬂuctuation of approximately 30%, by dividing
it into two areas for the calculations. This coefﬁcient of variation is signiﬁcantly lower
than when the evacuation order cancellation zone was not divided into two. In addition,a signiﬁcant difference in apparent half-life was determined using the Mann–Whitney U
test for the difﬁcult-to-return zone and evacuation order cancellation zone decontaminatedbefore April 2016, for the difﬁcult-to-return zone and the evacuation order cancellation
zone decontaminated on and after April 2016. The p-values are 6.9 × 10−4 and 9.5 × 10−4 ,respectively, conﬁrming that there is a signiﬁcant difference in distribution. Hayes et al.
reported that the effective half-life of radiocesium in the environment was 7.8 years as atheoretical value and 3.2 years as a measured value [34]. Table 2 shows a comparison of87

IJERPH 2021, 18, 978

the apparent half-life calculated in this study, the previously reported effective half-life,
and the theoretical half-life.

Figure 2. Area classiﬁcation for which the apparent half-life was calculated, and the location of themonitoring posts. The red circles indicate the location of the monitoring posts used for the analysis,
the blue mesh is the difﬁcult-to-return zone, the pink mesh is the evacuation order cancellation zone
where the radionuclides decontamination work was carried out before April 2016, and the green
mesh is the evacuation order cancellation zone where the radionuclides decontamination work was
carried out after April 2016. This map was drawn using a map created by Generic Mapping Tools [35].
Table 2. Comparison of the half-life of radiocesium in the environment.
Apparent Half-Life of Radiocesium in the Environment (y)Evacuation Order Cancellation Zone
Decontaminatedbefore April 2016

Decontaminated on
and after April 2016

6.4

2.0

Difﬁcult-to-Return
Zone

Previously
Reported Value [34]

Theoretical Value [34]

4.2

3.2

7.8

The measured data of absorbed dose rates in air from artiﬁcial radionuclides werecorrected to the values as of 1 April 2020 using different apparent half-lives for each of thethree areas (Appendix B). The median (range) is shown in Table 3, and the distribution of
the absorbed dose rate in air of the artiﬁcial radionuclides collected as of 1 April 2020 isshown in Figure 3.
Table 3. Median (range) estimated absorbed dose rate in air as of 1 April 2020.
Absorbed Dose Rate in air as of 1 April 2020 (nGy h−1 )Natural radionuclides
Artiﬁcial radionuclides
Total

88

Evacuation Order
Cancellation Zone

Difﬁcult-to-Return Zone

28 (25–35)
133 (67–511)
161 (995–81)

37 (30–45)
1306 (892–2081)
1340 (921–2124)

IJERPH 2021, 18, 978

Figure 3. Histogram of absorbed dose rate in air of artiﬁcial radionuclides corrected as of 1 April 2020.

A signiﬁcant difference test was performed using the Mann–Whitney U test on the absorbed dose rates in the air from artiﬁcial radionuclides in the evacuation order cancellation
zone and the difﬁcult-to-return zone. It was conﬁrmed that the two groups are signiﬁcantly
different (p-value = 6.0 × 10−14 ). The evacuation order cancellation zone is an area that
the Japanese government has determined people can live in because it has been conﬁrmedthat the ambient dose equivalent rate has decreased [6]. In contrast, the difﬁcult-to-returnzone is an area where the annual cumulative dose exceeds 50 mSv as of April 2012, and theannual cumulative dose may not fall below 20 mSv after ﬁve years have elapsed [5]. It was
found that the absorbed dose rate in air remained high in the difﬁcult-to-return zone nine
years after the FDNPP accident. The mean ± standard deviation and median (range) ofabsorbed dose rates in air by natural radionuclides throughout Namie Town are 35 ± 10
and 34 (28–42) nGy h−1 , respectively. The national average in Japan is reported to be
50 nGy h−1 [36]. It was found that the average value of Namie Town was 70% of thenational average value. These data can be used for radiation risk communication. The absorbed dose rate maps (Figure 4a,b) were developed so that the absorbed dose rate in air
could be visually understood by dividing it into natural and artiﬁcial radionuclides.
The activity concentrations of 40 K, 232 Th, and 238 U are shown in Appendix B. When examining the absorbed dose rate in air from natural radionuclides (Figure 4a), it can be seenthat the eastern coastal area of Namie Town is less than 40 nGy h−1 in most areas. The rangeof activity concentrations of 40 K, 232 Th, and 238 U in the evacuation order cancellation zone
were 109–444, 9–32, and 9–34 Bq kg−1 , respectively. Conversely, in the mountainous areas on the west side, there are many areas of 40 nGy h−1 or more. The range of activity
concentrations of 40 K, 232 Th, and 238 U in the difﬁcult-to-return zone were 99–1830, 9–46,
and 10–161 Bq kg−1 , respectively. On the west side of Namie Town, where granite is widelydistributed, the activity concentrations of 40 K, 232 Th, and 238 U tended to be high [37].
When examining the absorbed dose rate in air from artiﬁcial radionuclides (Figure 4b),
it can be seen that there is a clear difference between the coastal areas on the east sideand the mountainous areas on the west side. This is a clear result of the evacuation ordercancellation zone and the difﬁcult-to-return zone. In the coastal area, decontamination was
actively conducted in order to realize the return of evacuees, and the evacuation order was
lifted in March 2017 [6]. In contrast, the mountainous area on the west side has many areas
89

IJERPH 2021, 18, 978exceeding 1.0 μGy h−1 , and is remains designated as a difﬁcult-to-return zone. This result
indicates that artiﬁcial decontamination activities contribute signiﬁcantly to dose reduction.
However, there were two meshes in the evacuation order cancellation area that exceeded
1.0 μGy h−1 . Factors that increased the absorbed dose rate in air in this area include thepresence of slopes composed of soil and the presence of localized forest areas in the city,such as bamboo groves. Slopes composed of soil have not been actively decontaminatedbecause they may loosen the ground and cause sediment-related disasters. Local forest
areas in the city, such as bamboo groves, are difﬁcult to decontaminate by removing theupper part of the soil without cutting, which is a factor that increases the absorbed dose rate
in air. However, local forests and slopes composed of soil do not always exist uniformly
within a 1 km × 1 km mesh. In order to examine the variation of the measurement data inthe mesh, the absorbed dose rate in air was additionally measured at 2–5 points in six outof the 130 meshes (Table 4). Although there are some ﬂuctuations depending on the mesh,it was found that it is possible to evaluate with a volatility of approximately 50% or less.
It was also determined that the volatility is not dose-dependent.

(a)

(b)

Figure 4. (a) Map of absorbed dose rate in air derived from natural radionuclides and (b) map ofabsorbed dose rate in air derived from artiﬁcial radionuclides. This map was drawn using a map
created by Generic Mapping Tools [35].

90

IJERPH 2021, 18, 978

Table 4. Evaluation of variation of measurements data in a 1 km × 1 km mesh.
Absorbed Dose Rate in Air
Mesh Code

Number of
Measurements

Average ± Standard
Deviation (nGy h−1 )Standard Error(nGy h−1 )Coefﬁcient of
Variation

F5
L22
L23
M22
M24
N23

4
3
6
5
4
3

1118 ± 84
126 ± 33
312 ± 147
227 ± 83
156 ± 14147 ± 44

42
19
60
37
7
25

8%
26%
47%
37%
9%
30%

3.2. Estimating External Exposure DoseTable 5 indicates the median (range) of the annual effective dose of external exposure
calculated from the absorbed dose rate in the air. The annual effective doses of naturalradionuclides in the evacuation order cancellation zone, difﬁcult-to-return zone, and Namie
Town as a whole are 0.12–0.33, 0.10–0.45, and 0.10–0.45 mSv, respectively, and their geometric mean (mean ± standard deviation) is 0.20 (0.20 ± 0.05), 0.24 (0.24 ± 0.06), and 0.22
(0.23 ± 0.06), respectively. The national average effective annual dose of ground gammarays in Japan is 0.33 mSv. It was found that the average value for the town of Namie is
70% of the national average [38,39]. The annual effective doses of external exposure to
artiﬁcial radionuclides in the evacuation order cancellation zone, difﬁcult-to-return zone,
and entire Namie Town are 0.03–4.6, 0.23–19.6, and 0.03–19.6 mSv, respectively. The medianannual external exposure effective dose from artiﬁcial radionuclides in the evacuation ordercancellation zone (0.40 mSv) is 0.21 mSv, which differs from the median natural radionuclides (0.19 mSv). In contrast, the median annual external exposure effective dose from
artiﬁcial radionuclides in the difﬁcult-to-return zone (3.9 mSv) is 15.6 times higher than the
median from natural radionuclides (0.25 mSv). A signiﬁcant difference test was performed
using the Mann–Whitney U test on the annual effective dose of external exposure from
artiﬁcial radionuclides in the evacuation order cancellation zone and the difﬁcult-to-returnzone. The two groups have a statistically signiﬁcant difference (p-value < 6.0 × 10− 14 ).
This difﬁcult-to-return zone is an area where access to people is restricted. Cars are allowed
on some sections, but the general public is still not allowed to stay for a long time [40].
Currently, in difﬁcult-to-return zone, active decontamination is being carried out so thatpeople can live. In the future, this artiﬁcial decontamination is expected to reduce theabsorbed dose rate in air.
Table 5. Estimated annual external exposure effective dose.
Median (Range) Annual External Exposure Effective Dose (mSv)
Evacuation Order Cancellation
Zone

Difﬁcult-to-Return Zone

0.19 (0.16–0.23)
0.40 (0.20–1.5)
0.55 (0.39–1.7)

0.25 (0.20–0.29)
3.9 (2.7–6.2)
4.1 (2.9–6.5)

Natural radionuclides
Artiﬁcial radionuclides
Total

4. Conclusions
The absorbed dose rate in air was measured by discriminating between natural andartiﬁcial radionuclides in the entire area of Namie Town, an area affected by the FDNPP
accident. The following results were obtained from this study:
1.

2.

From the measurements of 134 Cs and 137 Cs concentrations, it was conﬁrmed that
Namie Town was radioactively contaminated by artiﬁcial radionuclides from the
FDNPP accident.
From the data of the monitoring posts installed in Namie Town, the median (range)of the apparent half-life of artiﬁcial radionuclides in the evacuation order cancellation
91

IJERPH 2021, 18, 9783.

4.

zone decontaminated before April 2016, the evacuation order cancellation zone decontaminated after April 2016, and the difﬁcult-to-return zone, is 6.4 ± 2.0, 2.0 ± 0.6,
and 4.2 ± 1.4 y, respectively.
The median (range) of absorbed dose rates in the air from artiﬁcial radionuclides
time-corrected as of 1 April 2020, using the apparent half-life are 133 (67–511) and
1306 (892–2081) nGy h−1 in the evacuation order cancellation zone and the difﬁcultto-return zone, respectively.
The median annual effective doses of external exposures from natural and artiﬁcial
radionuclides are 0.19 and 0.40 mSv in the evacuation order cancellation zone and0.25 and 3.9 mSv in the difﬁcult-to-return zone.

Examination of the absorbed dose rate in the air from artiﬁcial radionuclides revealeda clear difference between the eastern coastal area and the western mountainous area.
This result suggests that artiﬁcial decontamination activities contribute signiﬁcantly todose reduction. The distribution map of the absorbed dose rate in air measured in thisstudy, and the information on the annual external exposure effective dose calculated bydiscriminating between natural and artiﬁcial radionuclides, are expected to be utilized forradiation risk communication.
Author Contributions: Conceptualization, M.H. and S.T.; Formal analysis, Y.T., T.S., R.Y., and R.N.;
Funding acquisition, S.T.; Investigation, K.O., M.H., Y.T., T.S., T.T., M.Y., Y.S., K.I., and M.S.; Methodology, M.H. and S.T.; Project administration, S.T.; Supervision, M.H. and S.T.; Validation, K.O., M.H.
and N.A.; Visualization, K.O.; Writing—original draft, K.O.; Writing—review and editing, M.H., T.T.,
M.Y., Y.S., I.K., and S.T. All authors have read and agreed to the published version of the manuscript.
Funding: This research was supported by Research on the Health Effects of Radiation, organized by
the Ministry of the Environment, Japan.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

Appendix A
Table A1. Calculation table of apparent half-life in the difﬁcult-to-return zone.
Mesh Code
B5
D8
F4
F5
F5
F5
F8
G6
G8
H13
J14
L16
M18
Q19
Q19
Q20

Ambient Dose Equivalent Rate (μSv h−1 )As of 1 April 2016

As of 1 April 2020

4.2
2.4
1.2
0.96
4.9
2.1
3.6
2.3
1.7
5.4
6.4
1.0
3.6
2.2
11.8
4.7

2.4
1.3
0.64
0.60
0.70
0.44
2.0
1.3
0.88
3.2
3.2
0.62
2.0
1.2
5.7
0.69

92

Apparent Half-Life (y)
4.7
4.5
4.7
5.8
1.4
1.8
4.6
5.1
4.2
5.2
4.0
5.6
4.8
4.7
3.9
1.4

IJERPH 2021, 18, 978

Table A2. Calculation table of apparent half-life in the evacuation order cancellation zone where
decontamination was conducted before 1 April 2016.
Mesh Code
L18
L19
L22
M19
M20
M21
M21
M22
M23
M23
N22
N24
N24
N24
N25
N25
N25
N26
N26
N26
O23
O24
P21
P23
P25

Ambient Dose Equivalent Rate (μSv h−1 )As of 1 April 2016

As of 1 April 2020

1.5
3.2
0.40
2.2
0.59
1.1
0.38
0.41
0.25
0.16
0.88
0.22
0.19
0.12
0.25
0.08
0.10
0.21
0.13
0.09
0.46
0.23
0.64
1.6
0.16

0.76
1.9
0.28
1.2
0.41
0.60
0.24
0.32
0.18
0.11
0.38
0.14
0.14
0.07
0.15
0.06
0.07
0.13
0.09
0.06
0.24
0.17
0.30
0.97
0.11

Apparent Half-Life (y)
3.9
5.0
8.2
4.7
7.5
4.4
6.1
10.5
8.8
8.1
3.3
5.9
10.1
5.9
5.5
7.4
6.2
6.1
6.4
7.0
4.2
9.2
3.6
5.7
7.1

Table A3. Calculation table of apparent half-life in the evacuation order cancellation zone where
decontamination was conducted on, and after, 1 April 2016.
Mesh Code
L19
N21
N22
N23
O20
O20
O21
O21
O21
O22
O22
P24
Q21

Ambient Dose Equivalent Rate (μSv h−1 )As of 1 April 2016

As of 1 April 2020

1.2
3.2
2.5
1.0
2.1
2.7
1.2
1.7
1.2
1.3
0.58
1.6
1.3

0.36
0.39
0.26
0.25
0.47
0.55
0.26
0.36
0.34
0.19
0.27
0.28
0.38

93

Apparent Half-Life (y)
2.3
1.3
1.2
1.9
1.8
1.7
1.8
1.8
2.3
1.4
3.6
1.6
2.3

IJERPH 2021, 18, 978Appendix B
Table A4. Measured absorbed dose rate in air from natural and artiﬁcial radionuclides, estimated absorbed dose rate in air
from artiﬁcial radionuclide as of 1 April 2020, and activity concentrations of natural radionuclides.
Absorbed Dose Rate in Air (nGy h−1 )Mesh Code

Measuring
Date

A3
A4
A5
B3
B4
B5
B6
B7
C4
C5
C6
C7
C8
D2
D3
D4
D5
D6
D7
D8
E1
E3
E4
E5
E6
E7
E8
F1
F2
F4
F5
F6
F7
F8
F9
F10
F11
G2
G3
G4
G5
G6
G7
G8
G9
G11
G12
H3
H4

2017/8/23
2018/9/10
2018/9/10
2017/8/23
2017/8/23
2017/11/1
2017/8/23
2017/11/1
2017/8/23
2017/8/23
2017/11/1
2017/11/3
2017/11/1
2017/8/24
2017/8/24
2017/11/1
2017/8/23
2017/11/1
2017/11/1
2017/11/1
2017/8/24
2017/8/24
2017/8/24
2017/8/23
2017/11/1
2017/11/1
2017/11/1
2017/8/24
2017/8/25
2017/8/24
2016/9/15
2016/9/15
2017/11/3
2017/11/3
2017/11/3
2017/11/3
2017/11/3
2017/8/24
2017/8/24
2017/8/24
2017/8/25
2017/8/25
2017/11/2
2017/11/2
2017/11/2
2017/11/3
2018/5/16
2017/8/24
2017/8/24

Artiﬁcial Radionuclides

Artiﬁcial Radionuclides
as of
1 April 2020

Natural Radionuclides

1620
1320
1600
2230
1370
3578
2990
1760
1850
3280
3020
1960
1360
1230
1240
2840
1520
3741
2160
1950
239
811
954
2300
2670
3120
2200
305
246
1200
140
1980
3010
1770
1060
5335
5412
255
376
891
1230
2380
1930
2080
913
3100
5890
315
151

1048
1017
1233
1442
886
2390
1934
1175
1196
2121
2017
1310
908
796
802
1897
983
2498
1442
1302
155
525
617
1487
1783
2083
1469
197
159
776
77
1095
2012
1183
709
3566
3618
165
243
576
796
1541
1289
1390
610
2072
4303
204
98

50
54
28
51
26
22
33
22
23
47
37
38
28
49
37
44
39
29
32
30
36
41
41
45
35
43
50
30
29
53
46
44
48
23
48
45
38
17
31
45
30
28
36
37
68
47
40
45
36

94

40 K
(Bq kg−1 )232 Th(Bq kg−1 )238 U(Bq kg−1 )

419
428
244
477
248
273
262
178
139
431
354
286
244
400
382
382
363
317
311
288
314
351
367
391
300
407
502
302
252
419
400
391
484
213
428
545
530
143
216
407
263
242
326
323
628
477
545
407
388

32
39
21
27
15
18
22
12
16
22
22
22
15
28
17
23
18
22
17
13
18
25
22
22
16
25
27
16
17
29
19
20
22
13
22
42
37
10
19
22
15
17
17
17
26
27
42
26
20

28
29
13
28
14
11
19
14
15
28
19
25
17
30
21
26
23
15
17
18
22
23
24
28
23
22
25
15
17
34
31
28
27
13
30
25
21
10
20
27
18
16
22
23
46
22
22
24
17

IJERPH 2021, 18, 978

Table A4. Cont.
Absorbed Dose Rate in Air (nGy h−1 )Mesh Code

Measuring
Date

H6
H7
H8
H9
H10
H12
H13
I4
I6
I7
I8
I9
I10
I12
I13
I14
J13
J14
J15
J19
K13
K16
K19
K20
K22
L16
L17
L18
L19
L20
L21
L22
L23
L25
M17
M18
M19
M20
M21
M22
M23
M24
M25
M26
N20
N21
N22
N23
N24
N25
N26
N27
O20

2018/9/10
2017/8/25
2017/11/2
2017/11/2
2017/11/2
2018/5/16
2016/9/16
2017/8/24
2018/9/10
2017/8/25
2017/11/2
2017/11/2
2017/11/2
2018/5/16
2018/9/11
2018/5/16
2018/5/16
2018/5/16
2018/5/16
2017/12/22
2018/5/16
2018/9/10
2017/12/22
2017/12/22
2019/11/14
2018/5/16
2018/5/16
2018/9/11
2017/12/22
2017/12/22
2017/12/22
2017/12/22
2018/12/26
2018/12/26
2018/5/16
2018/5/16
2016/9/16
2017/12/22
2017/12/22
2016/9/16
2017/12/23
2018/12/26
2018/12/26
2017/12/23
2017/12/22
2017/12/22
2018/5/16
2017/12/22
2016/9/16
2016/9/15
2018/12/26
2017/12/23
2017/12/22

Artiﬁcial Radionuclides

Artiﬁcial Radionuclides
as of
1 April 2020

Natural Radionuclides

1310
1430
1690
2090
2360
6466
5306
207
1130
1220
1560
1640
3190
4278
2470
3788
3799
4369
3898
925
5721
1570
595
1120
179
2490
2090
1510
231
1100
1950
147
285
89
1720
2120
1510
1260
343
423
242
105
35
33
854
174
141
1460
14
67
76
27
135

1010
926
1129
1396
1577
4723
2935
134
871
790
1042
1096
2131
3125
1904
2767
2775
3192
2847
724
4179
1210
466
876
172
1819
1527
1277
104
861
1526
115
249
78
1256
1549
1031
986
268
289
189
92
31
26
668
136
73
654
9
46
67
21
60

42
15
45
43
32
44
54
28
45
37
38
37
34
52
41
52
31
41
42
23
39
40
21
30
26
37
40
46
28
24
19
28
30
22
24
33
26
27
44
23
35
32
51
39
24
32
47
38
39
28
31
39
26

95

40 K
(Bq kg−1 )232 Th(Bq kg−1 )238 U(Bq kg−1 )

339
99
437
348
304
659
678
251
323
330
348
333
407
582
354
447
336
459
394
208
502
308
199
311
205
367
373
382
290
189
109
258
265
169
220
281
181
137
311
222
360
258
339
388
197
305
444
413
336
298
244
379
260

28
11
16
22
18
45
45
15
35
18
15
15
15
36
31
35
24
28
22
15
39
33
13
16
18
20
23
32
14
13
13
16
20
14
16
21
16
21
28
12
17
18
34
17
14
19
20
15
20
12
16
18
15

23
9
30
28
16
25
31
16
24
23
24
24
15
30
19
30
16
23
24
12
22
19
10
15
14
19
21
24
14
15
13
15
15
13
11
18
16
18
27
13
18
20
32
23
14
15
29
21
24
16
20
22
12

IJERPH 2021, 18, 978

Table A4. Cont.
Absorbed Dose Rate in Air (nGy h−1 )Mesh Code

Measuring
Date

O21
O22
O23
O24
O25
O26
O27
P20
P21
P22
P23
P24
P25
P26
P27
Q19
Q20
Q21
Q22
Q23
Q27
R18
R19
R20
R21
R27
S20
T20

2017/12/22
2017/12/22
2017/12/23
2017/12/23
2017/12/23
2018/12/26
2018/12/26
2017/8/26
2017/12/22
2017/12/22
2018/12/26
2016/9/17
2017/12/23
2018/12/26
2018/12/26
2016/9/17
2018/9/10
2017/8/26
2018/9/11
2018/9/11
2018/12/26
2018/9/10
2016/9/17
2017/8/26
2017/8/26
2018/12/26
2017/8/26
2017/8/26

Artiﬁcial Radionuclides

Artiﬁcial Radionuclides
as of
1 April 2020

Natural Radionuclides

120
306
398
231
1690
182
19
2010
100
53
149
563
39
76
20
9604
1480
1620
206
98
61
5560
11861
1650
2390
101
5342
4269

94
137
312
181
1323
159
17
1519
78
41
130
162
30
66
18
5316
1141
648
119
83
53
4285
6565
1069
1548
88
3460
2764

27
23
34
36
34
44
32
25
24
34
21
28
46
40
27
26
30
27
28
20
22
30
39
30
21
30
28
21

40 K
(Bq kg−1 )232 Th(Bq kg−1 )238 U(Bq kg−1 )

272
230
298
388
257
416
285
184
242
357
224
236
407
360
254
1260
257
260
257
181
225
416
1830
280
202
266
360
342

15
12
19
18
20
22
20
15
14
19
10
20
31
22
14
91
18
15
15
14
9
44
161
18
15
16
30
24

14
13
19
18
22
25
17
16
11
16
11
13
23
22
15
13
16
15
15
9
13
16
22
15
9
18
15
11

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ArticleRadon Activity Concentrations in Natural Hot Spring Water:
Dose Assessment and Health Perspective
Eka Djatnika Nugraha 1,2 , Masahiro Hosoda 2,3 , June Mellawati 1 , Untara Untara 1 , Ilsa Rosianna 4 ,Yuki Tamakuma 2,3 , Oumar Bobbo Modibo 2 , Chutima Kranrod 3 , Kusdiana Kusdiana 1 and Shinji Tokonami 3, *
1

2

3

4

*

Citation: Nugraha, E.D.; Hosoda, M.;
Mellawati, J.; Untara, U.; Rosianna, I.;
Tamakuma, Y.; Modibo, O.B.;
Kranrod, C.; Kusdiana, K.; Tokonami,
S. Radon Activity Concentrations in
Natural Hot Spring Water: Dose
Assessment and Health Perspective.
IJERPH 2021, 18, 920.
https://doi.org/10.3390/

Centre for Technology of Radiation Safety and Metrology, National Nuclear Energy Agency ofIndonesia (BATAN), Jakarta 12440, Indonesia; eka.dj.n@batan.go.id (E.D.N.);
june_mellawati@batan.go.id (J.M.); tara@batan.go.id (U.U.); kusdiana@batan.go.id (K.K.)
Department of Radiation Science, Graduate School of Health Sciences, Hirosaki University,
Hirosaki 036-8504, Japan; m_hosoda@hirosaki-u.ac.jp (M.H.); tamakuma@hirosaki-u.ac.jp (Y.T.);
h19gg701@hirosaki-u.ac.jp (O.B.M.)
Institute of Radiation Emergency Medicine, Hirosaki University, Hirosaki 036-8504, Japan;
kranrodc@hirosaki-u.ac.jp
Centre for Nuclear Minerals Technology, National Nuclear Energy Agency of Indonesia (BATAN),
Jakarta 12440, Indonesia; ilsa.r@batan.go.id
Correspondence: tokonami@hirosaki-u.ac.jp; Tel.: +81-172-39-5404

Abstract: The world community has long used natural hot springs for tourist and medicinal purposes.
In Indonesia, the province of West Java, which is naturally surrounded by volcanoes, is the main
destination for hot spring tourism. This paper is the ﬁrst report on radon measurements in tourism
natural hot spring water in Indonesia as part of radiation protection for public health. The purposeof this paper is to study the contribution of radon doses from natural hot spring water and thereby
facilitate radiation protection for public health. A total of 18 water samples were measured with
an electrostatic collection type radon monitor (RAD7, Durridge Co., USA). The concentration ofradon in natural hot spring water samples in the West Java region, Indonesia ranges from 0.26 to
31 Bq L−1 . An estimate of the annual effective dose in the natural hot spring water area ranges from
0.51 to 0.71 mSv with a mean of 0.60 mSv for workers. Meanwhile, the annual effective dose for the
public ranges from 0.10 to 0.14 mSv with an average of 0.12 mSv. This value is within the range ofthe average committed effective dose from inhalation and terrestrial radiation for the general public,
1.7 mSv annually.

ijerph18030920

Keywords: radon; hot spring; dose assessment; public healthAcademic Editor: Paul B. Tchounwou
Received: 25 December 2020
Accepted: 20 January 2021
Published: 21 January 2021

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1. Introduction
Odourless and originating from radium-226 (226 Ra) decay that naturally occurs in theearth’s crust, radon is a radioactive noble gas. According to the United Nations Scientiﬁc
Committee on the Effects of Atomic Radiation (UNSCEAR), half of the world’s mean valueof annual effective dose by natural radiation sources is attributed to 222 Rn, thoron (220 Rn)
and their progenies [1]. Radon (222 Rn) has been recognised as a carcinogenic gas and iswell-known as the second leading health risk factor for lung cancer [1–3]. Radon fromwater contributes to the total inhalation risk associated with radon in indoor air. In addition
to this, drinking water contains dissolved radon and the radiation emitted by radon andits radioactive decay products exposes sensitive cells in the stomach as well as otherorgans once it is absorbed into the bloodstream. Noting this danger, the United States
Environmental Protection Agency (EPA) proposed a maximum contaminant level (MCL)
for radon in the water around 11 Bq L−1 [4].
Radon dissolves in water that passes through soil and rock containing the naturalradioactive substance [5,6]. As a result, water moving deeper through the earth’s crust
gathers increasing concentrations of radon and other natural radioactive materials. When,99

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IJERPH 2021, 18, 920

during the geothermal process, temperatures and pressures increase enough, some of thiswater is expelled through faults and cracks, reaching the earth’s surface as hot springs.
Hot spring water produced under these circumstances usually contains high concentrationsof 222 Rn. This is due to at least one of two natural processes: 226 Ra dissolving in the water
after interacting with rock and soil in the earth or 222 Rn entering the water from rocks
containing 226 Ra [6–8].
The world community has long used natural hot springs for tourist and medicinal
purposes. In Indonesia, the province of West Java, which is naturally surrounded byvolcanoes, is a prime hot spring tourist destination. Approximately 1.8 million tourists
visit natural hot springs in the West Java province each year [9–11].
It is, therefore, necessary to study the contribution of 222 Rn doses from natural hot
spring water as part of radiation protection for public health. This paper is the ﬁrst
report on 222 Rn measurements in tourism natural hot spring water in Indonesia. Previous
studies related to radon measurements in Indonesia included measurements of air atdwellings [12–15], 222 Rn in water samples [15], 222 Rn in geothermal and geosciences [16]2. Materials and Methods
2.1. Study Area
This research was conducted in several districts in West Java, including the Ciater
Hot Springs area in Subang; the Ciwidey and Pangalengan Hot Springs areas in Bandung;
and the Cipanas and Darajat Hot Springs areas in Garut. Each of these hot springs is amajor tourist destination, as shown in Figure 1. Visited by approximately 300,000 tourists
each year, the Ciwidey and Pangalengan areas are tourist destinations located on the
Patuha volcano. The Ciater Hot Spring, located on the Tangkuban Perahu volcano, is themost popular area for hot spring tourism with approximately 1.3 million visitors annually.
Finally, as many as 50,000 tourists visit the Cipanas and Darajat areas every year [9–11].
The Cipanas area is located on the Guntur volcano, and the Darajat area is on the Kamojang
volcano, which also has a geothermal power plant.

Figure 1. The study area, covering three cities: Bandung, Subang, and Garut. The black dots represent cities, and red
asterisks indicate sampling locations.

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IJERPH 2021, 18, 920

2.2. Radon Measurement in Water Samples
A total of 18 water samples of 250 mL each were collected using radon-tight reagent
bottles as part of the water analysis accessory (RAD-H2O, Durridge Co., USA). This study
was conducted in September 2019, which includes the dry season. The samples included
17 natural hot springs water samples and one mineral water sample. The samples were
measured for temperature, pH, and electroconductivity (E.C.) (Laquatwin, Horiba, Japan).
In addition, the ambient dose equivalent rates (PDR-111, Hitachi, Japan) around thesampling area were measured. An electrostatic collection type 222 Rn monitor (RAD7,
Durridge Co., USA) connected to a water analysis accessory was used to measure thesamples and detect alpha activity. The RAD7 detector connected the monitor with abubbling kit for degassing of 222 Rn in a water sample into the air in a closed circuit, asshown in Figure 2. Before the 222 Rn arrived at the detector, it also needed to be dried witha desiccant (CaSO4 , Drierite, W A Hammond, USA) to absorb the moisture.

Figure 2. Schematic of experimental setup for measuring dissolved 222 Rn measurement

We used the WAT250 protocol in ﬁve-minute cycles and ﬁve recycles to generate
data. In this measurement protocol for grab samples analysis, the pump ran for ﬁve
minutes, ﬂushing the measurement chamber, and then stopping. The RAD7 waited for ﬁve
additional minutes at the end of the run before printing a summary. Since the analysis wasmade more than an hour after the sample was taken, a correction was applied to accountfor 222 Rn decay [17]. The amount of radon loss was calculated using the decay formula, or
Equation (1):(1)Ct = C0 Ae−λt /60
where Ct (Bq m−3 ) is the 222 Rn activity concentration at time t (min); C0 is the 222 Rn
activity concentration at time t = 0; and λ is the 222 Rn decay constant (7.542 × 10−3 h−1 ).
2.3. Radon Measurement in the Air
We measured the 222 Rn activity concentration in the air 1 m above the hot spring poolwith RAD7 for 8 h. An ‘auto’ mode was used to obtain this measurement in 60 min cycles,
and eight recycles were allowed. 222 Rn measurements began with the sniff mode beforechanging automatically to the normal mode after 3 h 45 min. The results obtained werethen averaged. We also measured the 222 Rn activity concentration in the dwelling aroundeach natural hot spring area as the background for estimating the transfer coefﬁcient from
222 Rn in the water to 222 Rn in the air.

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IJERPH 2021, 18, 920

2.4. Estimation of Annual Effective Dose
We used Equation (2) to calculate the contribution of 222 Rn in the water to 222 Rn in theatmosphere. Meanwhile, the internal annual effective dose from 222 Rn through inhalation,
the annual effective dose from external radiation, and the annual effective dose are shownin Equations (3)–(5), respectively.
DRn−w = CRn−w × TFRn−w− a ,(2)Ein( Rn) = CRn × F × DCFRnP × T,

(3)∗

Eext = H × CF × DCFH − D × T,

(4)

AED = Eext + Ein− Rn .

(5)

is the 222 Rn activity concentration contributed from water

In Equation (2), DRn−w
to the atmosphere (Bq m−3 ); CRn−w is the 222 Rn activity concentration in the water samples (Bq L−1 ); and TFRn−w− a is the transfer coefﬁcient from water to air, which equals
1 × 10−4 [18,19]. In Equation (3), Ein( Rn) is the internal annual effective dose from 222 Rn
through inhalation (mSv); CRn is the 222 Rn activity concentration in the air (Bq m−3 ); F isthe equilibrium factor of 222 Rn and radon progeny, which equals 0.4; DCFRnP is the doseconversion factor for 222 Rn, which equals 1.7 × 10−5 mSv (Bq h m−3 )−1 [3,20]; and T is
the time, which is 2000 h for the worker and 8 h a week, or 384 h annually, for the public.
In Equation (4), Eext is the annual effective dose from external radiation; H ∗ is the ambient
dose equivalent rates (nSv h−1 ); CF is the conversion factor from ambient dose equivalent
rates to the absorbed dose in the air, which equals 0.652 (Gy Sv−1 ) [21]; and DCFH − D is theconversion factor from the absorbed dose in the air to the external effective dose, whichequals 0.7 [1]. Finally, AED is the annual effective dose (mSv).
3. Results and Discussion
Natural hot springs are a popular tourist attraction in West Java. Since at least 1980,
tourists have enjoyed the natural atmosphere of the area while participating in activities
such as swimming, soaking, photographing the scenery, and walking in the park. Manyeven stay overnight [9–11]. Despite its diverse other uses, natural hot spring water inWest Java is not used for drinking. Therefore, we performed dose assessments throughinhalation and external dose radiation only.
From a total of 17 natural hot spring water samples and one mineral bottled water
sample, the value of electroconductivity ranged from 0.164 to 1.925 mS cm−1 with anaverage value of 1.541 mS cm−1 . Meanwhile, the pH ranged from 5 to 7 with an averagevalue of 6. Finally, water temperature, as shown in Table 1, ranged from 36 to 42 ◦ C withan average of 39 ◦ C. According to the regulations of the Indonesian Ministry of Health [22],and the World Health Organisation [23], the E.C. and pH values in natural hot spring water
samples in West Java fall above recommended values, which must be below 1.5 mS cm−1
and 6.5–8.5 for E.C. and pH, respectively. E.C. is closely related to the content of dissolved
solids in the water. Thus, if water with a high E.C. value and pH level is used for drinking,gastrointestinal upset and kidney disease can result. Unlike the natural hot spring water
samples, the mineral bottled water is suitable for drinking.

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IJERPH 2021, 18, 920

Table 1. The location, physical and chemical properties of the water samples.
Samples

Area

A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
B1
B2
B3
B4
C1
C2
C3
M

CipanasCipanasCipanasCipanasDarajatDarajatDarajatDarajatDarajatDarajat
Ciwidey
Ciwidey
Ciwidey
Pangalengan
Ciater
Ciater
CiaterBottled waterLongitude

LatitudeElevation

Temperature

Electroconductivity at 25 ◦ C

(E)

(S)

(m)

(◦ C)

(mS cm−1 )107.8716
107.8816
107.7016
107.5016
107.7415
107.7414
107.7416
107.7287
107.7287
107.7287
107.3843
107.3901
107.3853
107.6148
107.6544
107.6544
107.6544-−7.17643−7.18884−7.19645−7.19646−7.21833−7.21914−7.22191−7.22935−7.22906−7.22851−7.14416−7.14710−7.14429−7.23211−6.80861−6.80861−6.80862
-

1678
1675
1668
1671
1672
1670
1672
1973
1976
1985
1779
1781
1724
1450
873
885
897
-

38
38
39
39
37
38
37
42
42
42
37
39
36
39
36
38
39
25

1.511
1.459
1.485
1.458
1.442
1.538
1.586
1.682
1.628
1.677
1.425
1.590
1.385
1.925
1.401
1.415
1.598
0.164

6
6
6
6
6
6
6
5
5
5
6
6
6
5
6
6
5
7

36
42
39

0.164
1.925
1.541

5
7
6

min
max
averagepH

The dissolved 222 Rn in water samples in the natural hot spring area shown in Figure 3
have a range of 1 to 31 Bq L−1 . With the exceptions of water samples A1, B4, and C3, thesevalues were all below the maximum concentration limit (MCL), 11 Bq L−1 , suggested by
the EPA. Water samples from this natural hot spring area contained dissolved 222 Rn activity
concentrations higher than the MCL but within the limit of the alternative maximum
concentration level (AMCL) of 148 Bq L−1 , also suggested by the EPA [4]. Based on the
UNSCEAR 2000 report, the AMCL of 148 Bq L−1 is the limit determining the concentrationof 222 Rn in the water that will produce an indoor 222 Rn increment equal to an outdoor
222 Rn activity concentration of 15 Bq m−3 with the transfer coefﬁcient from water to indoor
air applied as 1 × 10−4 [18]. The 222 Rn activity concentration in natural hot spring water in
the West Java province will contribute to an 222 Rn activity concentration in the air equal to
0.1–3.1 Bq m−3 concurrent to the 222 Rn activity concentration in air measured in this study
as shown in Table 2.

Figure 3. Radon activity concentration in water samples. MCL = maximum contaminant level.

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IJERPH 2021, 18, 920

Table 2. Details of measuring result: Dissolved 222 Rn in water, 222 Rn in air, and calculation of annual effective dose.

Samples

Dissolved
Radon
in WaterRadon
in Air

Ambient
Dose
Equivalent
Rate

Radon
Transfer
Coefﬁcient from
Water toAir

Contributed
Dissolved
Radon inWater toRadon in Air

Annual Effective
Dose due toIngestion (mSv)

Annual Effective
Dose due toExternal Exposure(mSv)

Total Annual
Effective Dose(mSv)

Bq L−1

Bq m−3nSv h−1

Bq m−3

WorkerPublicWorkerPublicBq L−1

Bq m−3

A1
A2
A3
A4
A5
A6
A7
A8
A9
A10
B1
B2
B3
B4
C1
C2
C3
M

31 ± 3.4
9 ± 1.0
7 ± 0.7
9 ± 1.0
8 ± 0.9
8 ± 0.99 ± 1.0
2 ± 0.3
4 ± 0.4
4 ± 0.5
5 ± 0.6
2 ± 0.2
1 ± 0.1
31 ± 3.5
8 ± 0.9
8 ± 0.918 ± 2.0
0.3 ± 0.1

48 ± 749 ± 742 ± 638 ± 639 ± 639 ± 640 ± 638 ± 638 ± 638 ± 638 ± 637 ± 635 ± 642 ± 748 ± 749 ± 850 ± 8-43 ± 241 ± 243 ± 241 ± 238 ± 237 ± 236 ± 240 ± 241 ± 240 ± 236 ± 238 ± 235 ± 244 ± 238 ± 237 ± 238 ± 2-

5.9 × 10−4
2.1 × 10−3
1.8 × 10−3
9.3 × 10−4
1.1 × 10−3
1.1 × 10−3
1.1 × 10−3
3.4 × 10−3
2.0 × 10−3
1.9 × 10−3
2.0 × 10−3
5.4 × 10−3
5.5 × 10−3
3.2 × 10−4
1.7 × 10−3
1.6 × 10−3
2.0 × 10−3
-

3.1
0.9
0.7
0.9
0.8
0.8
0.9
0.3
0.4
0.4
0.5
0.2
0.1
3.1
0.8
0.9
1.8
0.1

0.65
0.67
0.57
0.52
0.53
0.53
0.54
0.52
0.52
0.52
0.52
0.50
0.48
0.57
0.65
0.67
0.68
-

0.13
0.13
0.11
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.09
0.11
0.13
0.13
0.13

0.04
0.04
0.04
0.04
0.03
0.03
0.03
0.04
0.04
0.04
0.03
0.03
0.03
0.04
0.03
0.03
0.03

0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01

0.69
0.70
0.61
0.55
0.57
0.56
0.58
0.55
0.55
0.55
0.55
0.54
0.51
0.61
0.69
0.70
0.71

0.13
0.14
0.12
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.11
0.10
0.10
0.12
0.13
0.13
0.14

Averageminmax

9 ± 1.0
1 ± 0.1
31 ± 3.542 ± 635 ± 550 ± 839 ± 235 ± 244 ± 22.0 × 10−3
3.2 × 10−4
5.5 × 10−3

0.9
0.1
3.1

0.53
0.48
0.68

0.11
0.09
0.13

0.04
0.03
0.04

0.01
0.01
0.01

0.60
0.51
0.71

0.12
0.10
0.14

Comparing the values of 222 Rn levels in West Java to 222 Rn activity concentrations
elsewhere reveal that Indonesian levels are rather low. Studies in Slovenia [24], the U.S. [25],Spain [26], Taiwan [27], Hungary [28], Poland [29], Venezuela [30], Germany [31], Croatia [32], Iran [33], and Thailand [6] report 222 Rn activity concentrations in hot spring water
ranging from 0.2 to 600 Bq L−1 . The radon concentration in an area is closely related
to geological rock types, which in West Java have andesitic rock types that contain low
uranium and radium content [34–36].
The radon activity concentration in the air in the hot spring area of the West Java
province ranges from 35 to 50 Bq m−3 with an average of 42 Bq m−3 . Equation (6) compares
the activity value of the 222 Rn activity concentration dissolved in water and the 222 Rn in
the air.
ΔCa,(6)Transfer coefﬁcient =Cwhere, ΔCa is the average increment of 222 Rn activity concentration in the air (Bq m−3 ).
This result is a subtraction of the 222 Rn activity concentration in the air around the natural
hot spring pool from the 222 Rn activity concentration outside of dwellings around the hotspring area. The 222 Rn activity concentration outside of dwellings around the hot springarea for Cipanas, Darajat, Ciwidey, Pangalengan and Ciater were 30, 30, 28, 32, and 35 Bq
m−3 , respectively. Cw is the dissolved 222 Rn activity concentration in the water (Bq m−3 ).
The value of 222 Rn coefﬁcient transfer from water to air in this study was an average of
2.0 × 10−03 . This value is higher than the value UNSCEAR [18] and Hopke et al. [19] found,possibly due to the effect of water mixing, since tourists were active in the pool while we
conducted measurements. Others, including Radolic et al. [32] and Song et al. [37], havereported average transfer coefﬁcients around 4.9 × 10−3 and 1.5 × 10−3 , respectively.
The annual effective dose in the natural hot spring water area ranges from 0.51 to
0.71 mSv with a mean of 0.60 mSv for workers. Meanwhile, the public dose ranges from
0.10 to 0.14 mSv with an average of 0.12 mSv. This value falls within the average committed

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IJERPH 2021, 18, 920

effective dose from inhalation and terrestrial radiation for the general public, 1.7 mSv
annually, determined by UNSCEAR [1].
4. Conclusions
The concentration of 222 Rn in natural hot spring water samples in the West Java regionof Indonesia has a range of 1 to 31 Bq L−1 . An estimate of the annual effective dose in thenatural hot spring water area ranges from 0.51 to 0.71 mSv with a mean of 0.60 mSv forworkers. Meanwhile, the public is exposed to a range of 0.10 to 0.14 mSv with an averageof 0.12 mSv. This value falls within the range of the averaged committed effective dosefrom inhalation and terrestrial radiation for the general public, 1.7 mSv annually.
Author Contributions: Conceptualisation, E.D.N., M.H. and S.T.; methodology, E.D.N., Y.T., K.K.,
M.H. and S.T.; validation, E.D.N., M.H, and U.U.; formal analysis, E.D.N., and M.H.; investigation,
E.D.N., I.R.; resources, K.K., U.U., M.H. and S.T.; data curation, E.D.N.; writing—original draft
preparation, E.D.N.; writing—review and editing, E.D.N., M.H., K.K., U.U., I.R., Y.T., O.B.M., C.K.,
J.M., and S.T.; visualisation, E.D.N.; supervision, M.H., J.M and S.T.; funding acquisition, M.H. and
S.T. All authors have read and agreed to the published version of the manuscript.
Funding: This research was partially funded by the Indonesian Government, Japan Society for the
Promotion of Science KAKENHI [20H00556, 18KK0261, 16K15368, 16H02667, JP18K10023], andHirosaki University institutional research grant.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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106International Journal ofEnvironmental Researchand Public Health
ArticleRadiological Assessment of Indoor Radon and Thoron
Concentrations and Indoor Radon Map of Dwellings in
Mashhad, Iran
Mohammademad Adelikhah 1 , Amin Shahrokhi 1 , Morteza Imani 2 , Stanislaw Chalupnik 3 and Tibor Kovács 1, *
1

2

3

*

Citation: Adelikhah, M.; Shahrokhi,
A.; Imani, M.; Chalupnik, S.; Kovács,
T. Radiological Assessment of Indoor
Radon and Thoron Concentrations
and Indoor Radon Map of Dwellingsin Mashhad, Iran. IJERPH 2020, 18,141. https://

Institute of Radiochemistry and Radioecology, University of Pannonia, 8200 Veszprém, Hungary;
emad@mk.uni-pannon.hu (M.A.); ashahrokhi@almos.uni-pannon.hu (A.S.)
Materials and Nuclear Fuel Research School, Nuclear Science and Technology Research Institute,
Tehran 11365-8486, Iran; imani.mrt@gmail.com
Silesian Centre for Environmental Radioactivity, Central Mining Institute, plac Gwarków 1,
40-166 Katowice, Poland; schalupnik@gig.eu
Correspondence: kt@almos.uni-pannon.hu; Tel.: +36-88-624-178

Abstract: A comprehensive study was carried out to measure indoor radon/thoron concentrationsin 78 dwellings and soil-gas radon in the city of Mashhad, Iran during two seasons, using two
common radon monitoring devices (NRPB and RADUET). In the winter, indoor radon concentrations measured between 75 ± 11 to 376 ± 24 Bq·m−3 (mean: 150 ± 19 Bq m−3 ), whereas indoor
thoron concentrations ranged from below the Lower Limit of Detection (LLD) to 166 ± 10 Bq·m−3(mean: 66 ± 8 Bq m−3 ), while radon and thoron concentrations in summer fell between 50 ± 11
and 305 ± 24 Bq·m−3 (mean 115 ± 18 Bq m−3 ) and from below the LLD to 122 ± 10 Bq m−3(mean 48 ± 6 Bq·m−3 ), respectively. The annual average effective dose was estimated to be
3.7 ± 0.5 mSv yr−1 . The soil-gas radon concentrations fell within the range from 1.07 ± 0.28 to
8.02 ± 0.65 kBq·m−3 (mean 3.07 ± 1.09 kBq·m−3 ). Finally, indoor radon maps were generated by
ArcGIS software over a grid of 1 × 1 km2 using three different interpolation techniques. In gridcells where no data was observed, the arithmetic mean was used to predict a mean indoor radon
concentration. Accordingly, inverse distance weighting (IDW) was proven to be more suitable forpredicting mean indoor radon concentrations due to the lower mean absolute error (MAE) and root
mean square error (RMSE). Meanwhile, the radiation health risk due to the residential exposure toradon and indoor gamma radiation exposure was also assessed.
Keywords: residential exposure; dose; gamma radiation; health risk; radon mapping; CR-39

dx.doi.org/10.3390/ijerph18010141
Received: 8 December 2020
Accepted: 23 December 2020
Published: 28 December 2020
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claimsin published maps and institutional
afﬁliations.

Copyright: © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This
article is an open access article distributed
under the terms and conditions of theCreative Commons Attribution (CC BY)
license (https://creativecommons.org/
licenses/by/4.0/).

1. Introduction
In general, people are exposed to ionizing radiation from various natural and artiﬁcial
sources. Radon (222 Rn), thoron (220 Rn), and the progeny of both can be regarded as thelargest contributor to the annual effective dose for the public in the world (50% of thetotal public dose) [1,2]; however, public exposure to ionizing radiation can be higher due
to a new dose conversion factor [3]. Exposure to radon and its decay products is thesecond most common cause of lung cancer after tobacco smoking [4]. The health risks
related to radon exposure primarily arise in indoor environments, while outdoor radonlevels are generally low. The most important source of indoor radon is soil gas inﬁltration,and the intensity of this source relies on the composition of the ground, i.e., granite, tile,clay, etc. Soil gas inﬁltration is produced in mineral grains by the radioactive decay of
226 Ra, emanated into the void spaces between the grains, transported by diffusion andadvection/convection, and eventually exhaled from the soil into boreholes where it isdetected. Moreover, cracks in concrete ﬂoors and walls, drainage pipes, connecting parts ofbuildings, heating, ventilation, and air conditioning ducts are the possible routes throughwhich radon can enter into indoor environments [5].
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IJERPH 2020, 18, 141

Measuring indoor radon and thoron concentrations and radon mapping was considered for years and several papers were published on the topic around the world [6–17],
including in many Iranian cities [18–27] to increase public awareness of environmental
radioactivity and to predict radon-prone areas, which would help authorities with regard to
the development of an appropriate strategy to reduce public exposure to radon and thoron.
This reduced exposure would increase the quality of life and improve public long-term
health. Due to the lack of data concerning indoor radon and thoron concentrations inhouses in the city of Mashhad, an attempt was made to measure indoor radon and thoron
concentrations in 78 houses to calculate the annual committed effective dose caused by
the inhalation of radon and thoron. The measurements were taken during two seasons,summer (July–September 2019) and winter (December 2019–February 2020). The annual
average radon and thoron concentrations were estimated by averaging measured concentrations during these periods. Subsequently, a radon map was produced using ArcGIS
software and three different interpolation techniques, within a grid with the dimensionsof 1 km × 1km. Meanwhile, the soil gas radon concentrations (as the major source ofindoor radon) in different districts of Mashhad were also measured using a passive method
based on CR-39 detectors during the summer when soil moisture and precipitation islow. Moreover, external exposure rates for terrestrial gamma radiation in Iran from 36 to
130 nGy h−1 with an average of 71 nGy h−1 have been reported [1,2]. In 2015, Sohrabi
et al. also measured the indoors and outdoors gamma dose rates for about 1000 houses
in 36 cities in Iran and the national mean background outdoor gamma dose rates werereported as being 70.2 nGy h−1 [28]. Therefore, to assess the radiation health risk, the publicindoor doses from radon gas and indoor gamma radiation were compared and assessed.
2. Materials and Methods
2.1. Study Area
Mashhad is the second largest metropolis in Iran and is the capital of Razavi Khorasan
Province in northeastern Iran. It has an area of 351 km2 and its population is more than
3 million people according to the last census (Statistical Centre of Iran, 2016). It has
witnessed rapid growth over the last two decades, mostly as a result of its economic, social,
and religious attractions. The city is 985 m above sea level with the geographic coordinatesof 36◦ 17 45 N, 59◦ 36 43 E. Geologically, the Kalaj mountains, which consist of granitic
hills covered by silty deposits, are situated to the south of Mashhad, towards the northwest
is Kale Ghaemabad that is comprised of more sandy soil, and in all other directions is
a plateau with a mix of clay loam and soft sandy soils. Figure 1 shows the location of
Mashhad in Iran.

Figure 1. Location of the city of Mashhad in Razavi Khorasan Province, Iran.

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IJERPH 2020, 18, 141

2.2. Measuring Techniques
Indoor radon and thoron concentrations are measured in the living rooms of houses
at ground level. Regarding the recruited of participants, the priority was given to theolder houses by selecting 3 to 5 dwellings from each district randomly depending on thesize of the residential area. The majority of the houses examined were built 15 to 45 years
ago using bricks composed of sand and cement along with cemented ﬂoors. The indoor
measurements were conducted over a period of 90 days in total during the summer (July–
September 2019) and winter (December 2019–February 2020). To determine the indoor
radon and thoron concentrations, RADUET, a commercially available passive integrated
radon–thoron discriminative detector, was used. These detectors consist of two diffusion
chambers with different ventilation rates, and each chamber contains a CR-39 chip with thedimensions of 10 × 10 mm2 (RADUET, Radosys Ltd., Budapest, Hungary) for detecting
the alpha particles emitted from radon and thoron as well as their progenies [29,30]. All
detectors were hung at a height of 1–2 m above the ground using hard wire and positioned
at least 20 cm away from any of the wall surfaces in the living rooms of the houses.
In addition, a solid-state nuclear track detector (SSNTD), CR-39, was used to measureradon concentrations in soil gas. In this regard, a hole was dug in the soil of about 11 cm indiameter and 50–60 cm in depth. Then, a long PVC tube was ﬁxed into the hole with thecovered top end of the tube protruding from the ground by about 5 cm. At the bottom ofeach tube, a NRBP radon dosimeter [31] was placed for a period of 45 days between Julyand September 2019.
After exposure, all detectors were wrapped in protective aluminum foil and returnedfor processing at the Institute. In the laboratory, they washed with distilled water and dried
and then chemically etched. The etching condition for CR-39 was as follows: Solution:
6.0 M NaOH; Temperature: 90 ◦ C; Time: 3 h. The track densities were counted using an
optical transmission microscope and image analysis software. The calibration factors were
determined as a result of exposure tests using radon and thoron calibration chambers at
the Institute of Radiochemistry and Radioecology of the University of Pannonia, Hungary,and is comprehensively described in [30–32].
2.3. Annual Effective Dose, Excess Lifetime Cancer Risk (ELCR) and Lung Cancer Cases (LCC)
Associated with Radon/Thoron Exposure
The annual committed effective doses originating from the inhalation of indoor radonor thoron were calculated using the following equation provided by [1]:E(Rn/Tn) = C(Rn/Tn) × F(Rn/Tn) × t × K(Rn/Tn)(1)where ERn/Tn denotes the annual committed effective dose from exposure to radon or
thoron (mSv yr−1 ); CRn/Tn stands for the annual average radon or thoron concentrations inhouses (Bq m−3 ); F(Rn/Tn) represents the indoor equilibrium factors for radon or thoron andtheir respective progenies. The following values were provided by United Nations Scientiﬁc
Committee on the Effects of Atomic Radiation (UNSCEAR) in 2000 [1]: F = 0.40 and
F = 0.02 for radon and thoron, respectively; t is the number of hours spent inside annually(7000 h). Also, K(Rn/Tn) denotes the following dose conversion factors recommended by
UNSCEAR in 2000 [1]: KRn = 9 nSv and KTn = 40 nSv per unit of integrated radon andthoron concentrations (Bq h m−3 ), respectively.
In this survey, the average of the radon concentrations in the summer and winterrepresents the annual radon concentration. Furthermore, between December and February
is regarded as the winter season when people tend to close windows because of thecold weather. The total exposure time was 90 days over the two seasons assessed. The
Excess Lifetime Cancer Risk (ELCR) per 100,000 people was calculated using the following
equation [33]:
ELCR = E(Rn/Tn) × DL × RF
(2)

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IJERPH 2020, 18, 141

where DL represents the life expectancy, estimated to be 70 years; and RF stands for the riskof fatal cancer per Sievert of 5.5 × 10−2 Sv−1 as recommended by International Commission
on Radiological Protection (ICRP) Publication 103. Finally, the Lung Cancer Cases per year
per million people (LCC) was estimated by using the risk factor lung cancer induction
18 × 10−6 mSv−1 and calculated by the following equation [34]:
LCC = E(Rn/Tn) × 18 × 10−6 .

(3)

2.4. Statistical Analysis
The statistical analysis was carried out using IBM SPSS Statistics 21 (Armonk, NY, USA).
The Kolmogorov-Smirnov test was applied to test the null hypothesis for the homogeneous
distribution of the datasets. The Kruskal–Wallis non-parametric test with the Dunn’s
post-hoc analysis was also used to test whether the samples originated from the same
distribution based on the comparison of medians.
2.5. Radon Mapping and Cross-Validation
Radon mapping has great economic and social consequences; moreover, a highresolution, accurate, and statistically powerful radon map is necessary to increase publicawareness of environmental radioactivity and inﬂuence government policy with the purpose of reducing radon exposure in the general population. Depending on the datasets
applied, two types of maps can be used: 1. Indoor Radon Maps which are based on indoor
radon measurements (as applied in this study); and 2. Geogenic Radon Maps which are
based on geological information [35]. The major merit of indoor radon maps is that radon
concentrations are directly measured at the exposure point.
In this study, an indoor radon map was generated by using ArcGIS software version
10.7 (GDi Esri Hungary Ltd., Budapest, Hungary) over a grid with the dimensions of
1 km × 1 km; moreover, three interpolation methods were tested: inverse distance weighting (IDW), ordinary kriging (OK), and Empirical Bayesian kriging (EBK). The arithmetic
mean (AM) was used over grid cells with the dimensions of 1 km × 1 km to predict themean indoor radon concentration on the ground ﬂoor of buildings in the grid cells where
no data was available. It is important to keep in mind that radon maps are only a probabilistic tool to make policy decisions such as prioritization; they cannot be used to deriveradon concentrations for an individual dwelling. By using some indexes, namely the mean
absolute error (MAE), root mean square error (RMSE), root mean squared logarithmic error(RMSLE), percentage bias (PB), and coefﬁcient of determination (R2 ), the accuracy of thedifferent techniques was also examined, as presented in Equations (4)–(8):
MAE =

1 n
| Zi − Xi |
n i∑
=1



1 n
( Zi − Xi )2
n i∑
=1

(5)

1 n
(log( Zi +1) − log( Xi +1))2
n i∑
=1

(6)

∑in=1 ( Zi − Xi )∑in=1 Xi

(7)

RMSE =RMSLE =

(4)

PB = 100
R2 = 1 −2∑in=1 ( Zi − Xi )2
∑in=1 Xi − X(8)where Xi and Zi denote the measured and predicted values in the location, n stands forthe number of points in the validation group, and X represents the mean of Xi . MAE and
RMSE are often applied to assess the performance of models. The model ﬁts properly if
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IJERPH 2020, 18, 141

the aforementioned indicators approach zero when calculated. PB (%) is the mean of thetendency in larger/smaller predicted values than those observed [36]. R2 is the ﬁt line
explaining to which degree the model is going to ﬁt to the dataset [37].
3. Results and Discussion
3.1. Activity Measurements
Within this study, the radon and thoron concentrations in 78 houses were surveyedover a total exposure time of 90 days (45 days in both the summer and the winter) byusing a RADUET detector. The frequency distribution of the indoor radon and thoron
for the 78 houses assessed in Mashhad over the two seasons are shown in Figure 2. In
addition, a comparison among normal distribution and log-normal distribution of data isalso illustrated in Figure 3. The indoor 222 Rn and 220 Rn concentrations in the winter ranged
from 75 ± 11 to 376 ± 24 Bq·m−3 with a mean value of 150 ± 19 Bq·m−3 and from below theLower Limit of Detection (LLD) to 166 ± 10 Bq·m−3 with a mean value of 66 ± 8 Bq m−3 ,respectively. In the case of the summer, the indoor 222 Rn and 220 Rn concentrations ranged
from 50 ± 11 to 305 ± 24 Bq·m−3 with a mean value of 114 ± 18 Bq·m−3 and frombelow the LLD to 122 ± 10 Bq·m−3 with a mean value of 48 ± 6 Bq m−3 , respectively. In
addition, the annual average indoor 222 Rn and 220 Rn concentrations in the studied areas
were 132 ± 19 Bq·m−3 and 58 ± 7 Bq m−3 , respectively. The main source of indoor 222 Rn
originates from soil gas inﬁltration, building materials, and ventilation [4]. Meanwhile,during cold winters, residents use natural gas and close all vents, causing the radon
accumulation found in houses.

Figure 2. Normal Distribution of indoor (A) radon and (B) thoron concentrations (Bq m−3 ) over the two seasons at the
ground level of dwellings examined in Mashhad.

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IJERPH 2020, 18, 141

Figure 3. Log-Normal Distribution of indoor (A) radon and (B) thoron concentrations (Bq m−3 ) over the two seasons at the
ground level of dwellings examined in Mashhad.

World organizations such as ICRP, WHO, and U.S. Environmental Protection Agency(EPA) have recommended various guidelines for radon exposure [1,4,33,38,39]. The annual
average indoor radon concentration is below the recommendation values (300 Bq m−3 )provided by the ICRP in 2010. The results concerning the annual average radon concentration exceed the action level (100 Bq m−3 ) recommended by the WHO in 2009. When
compared to the worldwide geometric mean (GM) of 37 Bq·m−3 (geometric standard
deviation (GSD) = 2.2) reported by UNSCEAR in 2000, the indoor radon in the city of
Mashhad is almost 4 times (139.68 Bq m−3 ) and approximately 3 times (105.8 Bq m−3 )higher than the world average in the winter and summer, respectively. It was also foundthat during the winter and summer, the indoor radon concentrations in 31% and 20% of
the dwellings were higher than the reference level of 148 Bq·m−3 recommended by the US
EPA in 2003.
The graph in Figure 4 shows the correlation between indoor 222 Rn and 220 Rn concentrations for the dwellings examined in Mashhad. Regarding the relationship between radon
and thoron concentrations, no clear and strong correlation between was observed andthoron concentrations could not be predicted from widely available information concerningradon. However, indoor radon and thoron concentration might directly depend on theactivity of 226 Ra and 232 Th (228 Th) in building materials, ground is the main entry path ofradon at dwellings; therefore, it could say that the content of both 222 Rn and 220 Rn depends
on the building materials and soil composition.
As previously discussed, the main source of indoor 222 Rn originates from soil gas
inﬁltration, 222 Rn concentrations in the soil gas of different districts in Mashhad were
measured by using a passive method based on CR-39 detectors in the summer when soil
moisture and precipitation are low. In order to determine soil gas radon concentrations,only 36 NRPB dosimeters were retrieved from where they were set up, while the remaining
6 dosimeters were considered lost. Figure 5 shows a histogram of soil gas radon concentrations in Mashhad during the summer. The soil gas radon concentrations recorded in the112

IJERPH 2020, 18, 141

studied area fell within the range of 1.07 ± 0.28 to 8.02 ± 0.65 kBq·m−3 with a mean value of
3.07 ± 1.09 kBq m−3 . As is shown in Figure 4, the activity concentrations of 222 Rn vary fromlocation to location, possibly because of the physic geological properties of the types of soil
studied, topographic differences, as well as geomorphology and meteorological conditionsof the region. The average radon concentrations in both soil gas and indoor environments
are approximately the minimum and maximum values in the same region, respectively.
Moreover, the correlation between indoor radon and soil gas radon concentrations for the
districts studied is shown in Figure 6. The correlation analysis yielded a positive correlation(R2 = 0.361) between average indoor radon and soil-gas radon concentrations.

Figure 4. Correlation between the indoor radon and thoron concentrations of the 78 houses examinedin Mashhad over two seasons.

The normality distribution of data was checked using the Kolmogorov–Smirnov test.
Considering the normality assumption in the null hypothesis of the Kolmogorov–Smirnov
test, the probability value (p-value) in all tests was less than 1%; therefore, the normality
distribution of radon and thoron concentrations in any of the following subfactors was
rejected. In this study, by applying the Kruskal–Wallis nonparametric test with Dunn’s post
hoc analysis, the null hypothesis, due to the absence of a statistically signiﬁcant differencein the average gas concentration, was rejected; therefore, the season and type of gas affect
the gas concentration (p-value < 0.05). The difference in radon concentrations between
well-ventilated and poorly ventilated dwellings was statistically signiﬁcant (p < 0.05). It
was assumed that houses with natural ventilation are poorly ventilated and houses mechanical ventilation systems are well-ventilated houses. The ﬁnding indicates that the radon
concentration is lower for well-ventilated dwellings compared to poorly ventilated ones.
The results of this study are consistent with others that have been conducted concerning
this topic [40–42]. Because the level of indoor radon concentration depends on the degreeof indoor ventilation, moreover, in well-ventilated dwellings, radon can easily escape
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IJERPH 2020, 18, 141

and does not accumulate inside, meaning indoor radon concentrations are less high inwell-ventilated dwellings compared to in poorly ventilated ones [40].

Figure 5. The soil-gas radon concentrations (kBq m−3 ) in the studied area.

Figure 6. The correlation between indoor radon and soil-gas radon concentrations.

Table 1 shows descriptive statistics that resulted from the measurement of the indoor
radon and thoron concentrations in the 78 houses studied in Mashhad during the two
seasons considered. Furthermore, the results reveal a seasonal variation in indoor radon
and thoron concentrations, which were higher in the winter than in the summer. This isbecause the doors and windows of dwellings remain closed most of the time in the wintercompared to in the summer, hence ventilation is poorer in the winter. The ratio of winter tosummer concerning indoor radon and thoron concentrations was also established for all 78
dwellings studied. This ratio of indoor radon concentrations ranged from 1.23 to 1.48 withan average value of 1.31. With regard to the indoor thoron concentration, the average ofthis ratio was similar, at 1.36. The reason of heterogeneous behavior of seasonal variationsin 222 Rn and 220 Rn concentrations might be that the source of 220 Rn is mainly limited
to the concentration of 232 Th (228 Th) in building materials, while in case of radon, theground’s concentration is additionally considered. Therefore, in summer due to a high air
exchange rate, e.g., using a ventilator or opening windows, the concentration of both 220 Rn
and 222 Rn goes down, while in winter since the air exchange rate is lower than summer,
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IJERPH 2020, 18, 141

the concentration of 220 Rn and 222 Rn build up but as the source of indoor 222 Rn is both
ground and building material rather than the only source of 220 Rn as building materials,
the seasonal change of indoor thoron concentration is less than that of indoor radon.
Table 1. Basic Statistics of indoor and soil gas 222 Rn and 220 Rn concentrations in samples from
Mashhad.

A.M 1

SeasonParameter

SummerIndoor air radon(Bq m−3 )Indoor air thoron(Bq m−3 )Soil-gas radon(kBq m−3 )Winter

G.M 2

S.D 3

Min

Max

115.02

105.8

50.64

50.8

305.2

48.73

37.4

27.95

<LLD

122.5

3.07

2.71

1.621

1.078

8.021

150.3

139.68

62.74

75.3

376.6

66.17

49.41

34.24

<LLD

166.3

Indoor air radon(Bq m−3 )Indoor air thoron(Bq m−3 )Winter/Summer
Ratio (Mean)
222 Rn220 Rn1.31

1.36

1 A.M = Arithmetical mean, 2 G.M = Geometrical mean, 3 S.D = Standard deviation.

A comparison of radon concentration in the soil gas under investigation with thosereported in other countries is also given in Table 2. It can clearly be seen that the radon
concentration in soil samples from the Sri Ganganagar district and the northern state ofRajasthan in India, the city of Najaf in Iraq, and Yemen are in close agreement with thepresent work. It can be concluded that the soil in Mashhad is suitable for construction
without posing any health hazards.
Table 2. Comparison of soil-gas radon concentrations under investigation with those in othercountries using different methods and sampling depths.

RegionRadon in
Soil-Gas(KBq m−3 )Measurement
MethodSampling
Depth (cm)ReferenceBǎita-Stei, Romania
Bolsena, Italy
Bulgaria
Hungary
Najaf, Iraq
Rajasthan, India
Sharr-Korabi, Kosovo
Slovenia
Sri Ganganagar, India
Yemen
Mashhad, Iran

5.5–512
7–176
3–97
1–47.10.009–9.29
0.94–10.05
0.295–32
0.9–32.9
0.9–10.10
0.15–13.56
1.07–8.02

Lucas Cell
RAD 7
AlphaGuard
RAD 7
RAD 7
RAD 7
SSNTDs (CR-39)
AlphaGuard
RAD 7
SSNTDs (CR-39)
SSNTDs (CR-39)

40–80
60–70
100
80
5–60
100
80
100
10–100
0–150
50–60

[43]
[14]
[44]
[45]
[46]
[47]
[48]
[49]
[50]
[51]
Present study

3.2. Radiation Dose and Risk Assessment
In this study, the average of the radon concentrations in the summer and winter was
assumed to be the annual average radon concentration. The corresponding annual effective
dose from the inhalation of radon and thoron was calculated as 3.7 ± 0.5 mSv yr−1 . The
committed effective dose from indoor radon and thoron was found to vary from 2.11 to
9.73 mSv yr−1 with a mean value of 4.22 mSv yr−1 for the winter, and 1.51 to 7.92 mSv yr−1
with a mean value of 3.14 mSv yr−1 for the summer. It can be seen that the committed
effective doses were higher in the winter compared to the summer. The excess lifetime
cancer risk and lung cancer cases per year per million people were also calculated to be
14.1 and 65.4, respectively.
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IJERPH 2020, 18, 141

According to the WHO in 2009, the risk of lung cancer increases by 16% per a
100 Bq·m−3 increase in radon concentration (long-time average) [4]. Therefore, the doseresponse relation is linear, i.e., the risk of lung cancer is proportional to radon exposure [4].
Nevertheless, based on a report produced by the Ministry of Health’s Center for Disease
Management in Iran, cancer is the third most signiﬁcant cause of death after road trafﬁc accidents and cardiovascular mortality. In 2019, Roshandel et al. reported that theage-standardized rates (ASR) of lung cancer were 127 and 52.1 per 100,000 Iranian males
and females, respectively [52]. In the case of Razavi Khorasan Province, the ASR was
121.2 and 54.0 per 100,000 Iranian males and females, respectively. Therefore, the annual
average excess risk due to radon inhalation in Mashhad is 14/100,000, i.e., less than theage-standardized death rate from cancer in Mashhad. Hence, indoor radon exposure is
responsible for approximately 12% of lung cancer deaths in this city, which is close to
the estimates by WHO in 2009 of the worldwide proportion of lung cancer due to radon(3–14%).
Given the annual average excess risk values by comparing local radiological risks withnational cancer incidence data, it can be concluded that the local risks are raised but are notnecessarily representative of the city as a whole. This radiation risk assessment should beconsidered with caution as the radon measurements are not sufﬁciently representative of
the investigated area; moreover, calculations made using ICRP data only provide a broad
overview of the risk and comparison with the national cancer incidence rate. Therefore,
extensive measurements are needed for a reliable comparison.
It is also essential to measure the amount of natural radiation in each area as this candetermine the suitability of the environment for a healthy lifestyle. The indoor and outdoor
gamma exposure rates in the air 1 m above the ground from terrestrial radionuclides
and cosmic rays in Mashhad are 155.73 ± 13.92 nGy h−1 and 126.15 ± 15.66 nGy h−1 ,respectively [28]. Using a determined conversion factor as 0.7 Sv Gy−1 , converting theabsorbed doses to effective doses [1], the annual indoor and outdoor effective dose rates ofthe public from gamma exposure were found to be 0.95 ± 0.08 and 0.77 ± 0.09 mSv yr−1 .
Therefore, by comparing these values with the corresponding annual effective doses fromthe inhalation of radon and thoron (3.7 ± 0.5 mSv yr−1 ), it could be concluded that most of
the doses received indoors in the dwellings studied in Mashhad city are from the inhalationof radon and thoron (about 79 % of the total dose). A comparison of the indoor radon
concentration and radiation risk assessment under investigation, with those reported inother Iranian cities also provided in Table 3.

116

84

78

Yazd

Mashhad161.11216

3.44 × 10−2
26.1
47.16
62.28
(56.7)(74.1)

5.6 × 10−3
1 × 10−2
1.3 × 10−2
(12.3 × 10−3 )(15.9 × 10−3 )4.6 × 10−2

43.38

9.2 × 10−3

61.74

1.3 × 10−2
-

12.96

2.7 × 10−1-

LCC 3 ×10−6

ELCR 2[22]

Summer: 20% > 148 Bq m−3
Winter: 31% > 148 Bq m−3

30% of basements> 148 Bq m−3

38% > 100 Bq m−3

5.4% > 100 Bq m−3-

Current study

[21]

[25]

[24]

[18]

[23]

[19]

5.3% of apartments > 100 Bq
m−3
24.3% > 100 Bq m−3[26]

In most dwellings > 100 Bq m−3

Reference

4% > 100 Bq m−3

Excessive Rate (%)

1 SD= Standard deviation, 2 ELCR= Excess Lifetime Cancer Risk, 3 LCC= Lung Cancer Cases.

3.46
Summer: 3.1
Winter: 4.2

137.4 (149.5)

Summer: 115(51)Winter: 150 (62)

2.62

1.45

30

104

57.6 (33.06)

185

ShirazTehranRamsar

(0.25–3.78)

Autumn: 8.95
Winter: 12

123

Qom

31.9

3.43

Autumn: 355
Winter: 476

148

Mashhad163 (57)

0.72

500

400

Lahijan

28.57 (39.38)

Mean Effective
Dose (mSv yr−1 )

2.41

51

IsfahanMean Radon
Concentration (SD 1 )95.83

Number of Dwelling

RegionTable 3. Studies on indoor radon concentration (Bq m−3 ) and radiation health risk in various Iranian cities.
IJERPH 2020, 18, 141

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IJERPH 2020, 18, 141

3.3. Spatial Distribution Map of Indoor Radon Concentrations
The Distance Weighting (IDW) and Ordinary Kriging (OK) techniques, known as
Kriging techniques, depend on the distance between two points, namely those of observation and estimation in the interpolation. IDW weighted the contribution of the observed
points on the estimated interpolation with regard to this distance alone. On the other hand,
OK also considers the correlation between the points and forms an initial function, i.e.,
covariance or variogram, which can iteratively be updated.
The spatial distribution map of indoor radon concentrations in Mashhad dwellings
were plotted in Figure 7 by various interpolation techniques, e.g., IDW, OK, and Empirical
Bayesian Kriging (EBK) over a grid with the dimensions of 1 km × 1 km using ArcGIS
software version 10.7. Accordingly, radon concentrations were lower than standard values
in eastern residential areas and were higher in central as well as southern districts. Nevertheless, when the spatial autocorrelation between cells was considered, predictions aboutradon concentrations using different methods range from 65 to 260 Bq m−3 . These values
may be more realistic and similar to average values found in some dwellings in the region.

Figure 7. Predicted Indoor Radon Map of Mashhad dwellings over a grid with the dimensions of 1 km × 1 km using the(A) Inverse distance weighting, (B) Empirical Bayesian Kriging, and (C) Ordinary Kriging interpolation techniques.

Moreover, the accuracies of the various techniques applied according to ﬁve indicators are given in Table 4. IDW, which predicts unknown values using known values
concerning their distance, was proven to be more suitable for predicting mean indoor
radon concentrations over grids with the dimensions of 1 km × 1 km (i.e., arithmetic mean,
ground ﬂoor), due to the lower MAE and RMSLE values of 28.159 and 0.01210, respectively,in addition to a lower bias, 20.069 to be exact. However, all mentioned models have atendency to overestimate bias (PB > 0). In addition, the model with the higher R2 is IDW,
which indicates that this model ﬁts the data better.

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IJERPH 2020, 18, 141

Table 4. Summary of the cross-validation results.
Method

MAE 1

RMSE 2RMSLE 3PB 4

R2Inverse distance weighting
Empirical Bayesian Kriging
Ordinary Kriging

28.15928.23528.42434.93135.14836.3640.012100.012180.01346

20.06920.12320.268

0.234
0.224
0.169

1 MAE = mean absolute error, 2 RMSE = root mean square error, 3 RMSLE = root mean squared

logarithmic error, 4 PB= percentage bias.

4. Conclusions
To estimate the impact of indoor radon and thoron on residentials as well as develop
and implement the most economical method to reduce radon exposure using a radon map,
this paper presents the measured indoor radon and thoron concentrations in 78 dwellings
as well as soil gas radon concentrations in different districts of Mashhad, Iran during
summer and winter. As the average of the radon concentrations in the summer and winterwere assumed to be the annual average radon concentration in this study, the annual
average indoor radon and thoron concentrations were calculated as being 132 ± 19 and
58 ± 7 Bq m−3 , respectively. Soil gas radon concentrations also ranged from 1.07 ± 0.28 to
8.02 ± 0.65 kBq·m−3 with a mean value of 3.07 ± 1.09 kBq·m−3 during the summer.
The corresponding annual effective dose from the inhalation of radon and thoron was
calculated as being 3.7 ± 0.5 mSv yr−1 . Subsequently, the excess lifetime cancer risk was
calculated as 14.13. Hence, exposure to indoor radon is responsible for approximately 12%of lung cancer deaths in Mashhad, which is close to the WHO estimates of the worldwide
proportion of lung cancer due to radon (3–14%). By comparing the annual indoor effective
dose rate from gamma exposure with the annual effective dose from the inhalation of radon
and thoron, it was concluded that most of the dose received inside the dwellings studiedin Mashhad, approximately 79% of the total dose, originates from the inhalation of radon
and thoron.
Since high-risk areas can be recognized on radon maps, which are useful for targeting
landlords and the building industry, an indoor radon map was generated by using ArcGIS
software over a grid with the dimensions of 1 km × 1 km using three interpolation
techniques. The arithmetic mean was used over the grid cells to predict a mean indoor
radon concentration on the ground-ﬂoor level of buildings in the grid cells where no data
was available. The IDW technique was proven to be most suitable one for predicting meanindoor radon concentrations over grids with the dimensions of 1 km × 1 km.
In addition to the results and given the signiﬁcant health impacts of radon and thoron,
it is hoped that both radon and thorn gases will be studied more seriously in Iran andthat these techniques as well as complementary procedures will be used to minimize its
concentration. It is recommended that radon gas concentrations should be measured in all
regions of the country by numerous devices supplied by the Atomic Energy Organizationof Iran (AEOI). As a result, it would be possible to compile a radon map of Iran to estimate
the concentration and number of radon-induced incidences of cancer, as well as decide
how to distribute the population. This would aid to reduce the number of cases of lungcancer and other radon-induced human health problems.
Author Contributions: Conceptualization, M.A., A.S., and T.K.; methodology, M.A., A.S., andT.K.; software, M.A. and M.I.; validation, M.A., A.S., T.K., and S.C.; formal analysis, M.A., A.S.;
investigation, M.A., A.S., and T.K.; resources, T.K.; data curation, T.K. and S.C.; writing—originaldraft preparation, M.A.; writing—review and editing, M.A., A.S., S.C., and T.K.; visualization, M.A.
and A.S.; supervision, T.K.; project administration, T.K.; funding acquisition, T.K. All authors haveread and agreed to the published version of the manuscript.
Funding: This work was supported by the TKP2020-IKA-07 project ﬁnanced under the 2020-4.1.1TKP2020 Thematic Excellence Programme by the National Research, Development and Innovation
Fund of Hungary and by the Hungarian National Research OKTA grant No. K128805 and K128818.
Institutional Review Board Statement: Not applicable for studies not involving humans or animals.
119

IJERPH 2020, 18, 141

Informed Consent Statement: Not applicable for studies not involving humans.
Data Availability Statement: The data presented in this study are available on request from thecorresponding author.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleAn Improved Passive CR-39-Based Direct 222Rn/220Rn
Progeny Detector
Jun Hu 1 , Guosheng Yang 2 , Chutima Kranrod 1 , Kazuki Iwaoka 2 , Masahiro Hosoda 1,3
and Shinji Tokonami 1, *
1
2
3

*

Institute of Radiation Emergency Medicine, Hirosaki University, 66-1 Hon-cho, Hirosaki 036-8564, Japan;
hujun@hirosaki-u.ac.jp (J.H.); kranrodc@hirosaki-u.ac.jp (C.K.); m_hosoda@hirosaki-u.ac.jp (M.H.)
National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage,
Chiba 263-8555, Japan; yang.guosheng@qst.go.jp (G.Y.); iwaoka.kazuki@qst.go.jp (K.I.)
Graduate School of Health Sciences, Hirosaki University, 66-1 Hon-cho, Hirosaki 036-8564, Japan
Correspondence: tokonami@hirosaki-u.ac.jp; Tel.: +81-172-39-5404

Received: 23 October 2020; Accepted: 16 November 2020; Published: 18 November 2020

Abstract: An improved passive CR-39-based direct 222 Rn/220 Rn progeny detector with 3 detection
channels was designed and tested in this study to measure and calculate equilibrium equivalentconcentration (EEC) of both 222 Rn and 220 Rn without the equilibrium factor. A theoretical model
was established to calculate the EEC with optimization. Subsequently, an exposure experiment
was carried out to test the performance of this detector, and we compared the chamber experimentand the theoretical model by estimating and measuring various parameters. The deposition ﬂux ofprogeny derived from the prediction agreed well with the value measured in the exposure chamber.
The energy-weighted net track density (NTD) measured by this detector is much more reliable toreﬂect the linear relation between NTD and time-integrated EEC. Since the detector is sensitive to the
exposure environmental condition, it is recommended to apply the detector to measure the EEC after
its calibration in a typical indoor environment.
Keywords: 222Rn progeny; 220Rn progeny; CR-39; equilibrium equivalent concentration; deposition velocity

1. Introduction
In the conventional integrating measurements for 222 Rn and 220 Rn activity concentrations in alarge-scale survey, the solid-state nuclear track detector (SSNTD) technique is usually used. Several
designs of measuring devices using SSNTD have been used for indoor 222 Rn and 220 Rn surveys, such as
RADUET [1], Pin-hole dosimeter [2–4], and so on. In the two diﬀerent diﬀusion rate chambers of thesemeasuring devices, because there is a diﬀusion barrier against 220 Rn based on its quite short half-life,
the low diﬀusion rate chamber detects mainly 222 Rn and the high diﬀusion rate chamber detects both
222 Rn and 220 Rn. However, evaluation of the internal exposure to 222 Rn and 220 Rn does not directly use
the activity concentration of 222 Rn and 220 Rn gas instead of the equilibrium equivalent concentration(EEC). It should be noted that the equilibrium factor depends on various parameters, such as theradioactive decay, ventilation, and reactions with the structure and the surface of furnishing. Becauseof the short half-life of 220 Rn (55.6 s), the indoor 220 Rn concentration distributes heterogeneously,
decreasing with distance from the source [5,6]. Therefore, it is not feasible to use the 220 Rn concentration
directly measured by the integrating detectors to evaluate its internal exposure. Otherwise, study of the
behavior of 222 Rn and 220 Rn decay products indoors is important for assessing the natural backgroundradiation exposures on the public through the inhalation route. Therefore, the direct measurement
technique of 222 Rn and 220 Rn progeny is desirable and necessary for the evaluation of internal indoor
222 Rn and 220 Rn exposure.

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IJERPH 2020, 17, 8569

In the recent 20 years, a direct 220 Rn progeny measurement technique based on CR-39 detector for
EEC of 220 Rn was developed and used by Zhuo and Iida [7], Tokonami et al. [8], Zhuo and Tokonami [9],Tokonami [10], Sorimach et al. [11], and Hu et al. [12]. Mishra and Mayya [13] were the ﬁrst to develop
the direct 222 Rn and 220 Rn progeny measurement techniques using LR-115 detector. CR-39 is the mostsensitive and popular detector for recording α-particles [14] and performs stable results; no direct 222 Rn
and 220 Rn progeny detector using CR-39 was developed and applied because its energy windows forrecording α-particles is quite wide, and it is unable to distinguish alpha energy directly, although someresearchers make great eﬀorts to develop dedicated tools based on the track geometrical characteristics
to measure alpha particles. Moreover, the application of the direct measurement technique fordetermining their progeny concentrations depends on estimation of the eﬀective deposition velocities
of combinations of 222 Rn and 220 Rn progenies in a typical indoor environment. Some researchers [11,15]
used the experimental method to estimate the geometric mean deposition velocity and applied thedata to actual measurement in an indoor environment. However, the experimental conditions had a
lot of limitations on environmental parameters for estimating the deposition velocity. In this study,
we developed a passive CR-39-based direct 222 Rn/220 Rn progeny detector. The 222 Rn and 220 Rn
behavior model and particle deposition model were used to estimate the concentration of each 222 Rn
and 220 Rn progeny as well as the EEC.
2. Materials and Methods
2.1. The Passive CR-39-Based Direct 222 Rn/220 Rn Progeny Detector
The structure of the detector is shown in Figure 1. The piece of commercially available ally diglycol
carbonate (CR-39) (the BARYOTRAK, produced by Fukuvi Chemical Industry Co., Ltd., Fukui, Japan)
was used as a detecting material to measure alpha particles emitted from 222 Rn and 220 Rn progeny.
Each detection channel was mounted with a diﬀerent thickness of aluminum-vaporized polyethylene
ﬁlms (Mylar ﬁlms), which can only detect the alpha particles emitted from corresponding progeny
radionuclides and ensure that lower energy alpha emissions (from the gases and other airborne alphaemitters) do not pass through the absorber. In the conventional passive direct 222 Rn/220 Rn progeny
detector, there are only 2 detecting channels: the 220 Rn progeny (TnP) channel and the 222 Rn progeny(RnPII) channel. The TnP channel can only detect the 8.78 MeV alpha particles emitted from 212 Po
atoms, which are formed from the decay of 212 Pb and 212 Bi atoms deposited on the ﬁlm surface without
any interference from other alpha emissions of natural radioactivity decay series. The RnPII channel
selectively detects 212 Po and 214 Po (7.69 MeV) from the decay of surface deposited 222 Rn and 220 Rnprogeny. In the improved passive detector, we added one more detecting channel RnPI to detect thealpha emission energy higher than that of 218 Po (6.0 MeV). The design information is present in Table 1.
Since the RnPI and RnPII cthannels are in a mixed 222 Rn and 220 Rn progeny environment, there areinterferences from the high energy alpha particles, which could be subtracted using the tracks on the
TnP channel. Therefore, 4 slices of CR-39 detector are used on the TnP channel instead of 2 slices on
the other channels to decrease the error.
Table 1. The design information of each detector channel.

ChannelMembraneThickness(mg cm−2 )NuclideTnP

7.10

212 Po

RnPII

5.05

RnPI

3.25

212 Po214 Po212 Po and 212 Bi
214 Po218 PoEnergy of
α-Particle
(MeV)

Track
Registration
Eﬃciency, η

8.785
8.785
7.687
8.785 and 6.051
7.687
6.003

0.063
0.212
0.182
0.152
0.249
0.135

124

Deposited Atoms
212 Pb, 212 Bi
212 Pb, 212 Bi
218 Po, 214 Pb, 214 Bi
212 Pb, 212 Bi
218 Po, 214 Pb, 214 Bi
218 PoIJERPH 2020, 17, 8569

Figure 1. The passive CR-39-based direct 222 Rn/220 Rn progeny detector: (a) a schematic diagram of theprogeny detector showing the detectable radionuclides of each channel and (b) a photo of the actual
setup of the progeny detector.

2.2. The Theoretical Model and Parameters2.2.1. Theoretical Model
Among the several aspects of indoor behaviors of 222 Rn and 220 Rn, apart from the decay losses,
deposition and ventilation are two major mechanisms to remove the decay products from indoor air.
Unlike the removal process by ventilation which depends essentially on the air exchange rate in agiven room environment, the removal by deposition depends on the activity size distribution and thestructure of turbulence at the air–surface interface. Since this detector is designed using the depositionmode, it is necessary to avoid uncontrolled static charges from aﬀecting the deposition rates. Hence,
the aluminized side of the Mylar is chosen to act as the deposition surface.
To describe the behavior of 222 Rn and 220 Rn progeny, the relationship between the attached
222 Rn and 220 Rn progeny deposition ﬂux, J (atom cm−2 s−1 ), and track density, N (tracks cm−2 ) can be
expressed as follows:
N
(1)
J=
ηt
where η is the track registration eﬃciency, which is the multiplier of the branching ratio of its progeny,
the geometric eﬃciency, and etching eﬃciency. For each channel, the geometric eﬃciency depends
on the energies of incident α-particle, incident angles against the absorbers, and the thickness of
the absorbers. The track registration eﬃciency measured in this study is present in Table 1, whichcorresponds to the etching condition using 6 N NaOH solutions at 60 ◦ C for 24 h without stirring. t is
the exposure period (s).
The eﬀective deposition velocity of the progeny, Ve (cm s−1 ), is deﬁned as follows:
Ve =

J
C

(2)

where C is the atom concentration of the progeny (atom cm−3 ).
To determine the deposited progeny atoms from the alpha tracks registered in CR-39, we needto check the progeny atoms’ ultimate decay on the surface of the detector, which causes the alphatrack to the CR-39. In the case of 222 Rn progeny, a fraction of all the alpha particles emitted from theatoms of 218 Po, 214 Pb, and 214 Bi deposited on the absorber can form tracks on the CR-39. Therefore,
the tracks counted at the end can be directly proportional to the sum of the 218 Po, 214 Pb, and 214 Bi
atoms deposited. Similarly, the total tracks registered by the 220 Rn progeny will be proportional to thesum of the 212 Pb and 212 Bi atoms deposited. Accordingly, we can deﬁne the following:
NTn = ηTn,Po212 · Ve,Tn · (CPb212 + CBi212 ) · t
125

(3)

IJERPH 2020, 17, 8569

NRn2 = ηRn2,Po212 · Ve,Tn · (CPb212 + CBi212 ) · t + ηRn2,Po214 · Ve,Rn · (CPo218 + CPb214 + CBi214 ) · t(4)

NRn1 = ηRn1,Po212 · Ve,Tn · (CPb212 + CBi212 ) · t + ηRn1,Po214 · Ve,Rn · (CPo218 + CPb214 + CBi214 ) · t+ηRn1,Bi212 · Ve,Tn · (CPb212 + CBi212 ) · t + ηRn1,Po218 · Ve,Rn,Po218 · CPo218 · t(5)where the subscripts of Tn, Rn1, and Rn2 mean the parameters of the TnP channel, RnPI channel,
and RnPII channel, respectively, and the subscript of each radionuclide means the corresponding
parameter. Some of the parameters used in this study are shown in Table 1. Ve,Tn is the eﬀective
deposition velocity of 220 Rn progeny, which is a combination of deposition velocities of 212 Pb and 212 Bi.
Ve,Rn is a combination of deposition velocities of 218 Po, 214 Pb, and 214 Bi. Ve,Rn,Po218 is the only eﬀective
deposition velocity of 218 Po.
In the mixed 222 Rn and 220 Rn environment, we can easily count the registered tracks on the TnPchannel from 212 Po decay, which come from the decay of the deposition ﬂux of 212 Pb and 212 Bi, as shownin Equation (6). Accordingly, from Equations (3)–(5), we can also calculate the counts of registered
tracks from 214 Po on the RnPII channel and 218 Po on the RnPI channel as in Equations (7) and (8).
TnP
= ηTn,Po212 · Ve,Tn · (CPb212 + CBi212 ) · t = NTn
NPo212(6)

RnP2 = η
NPo214
Rn2,Po214 · Ve,Rn · (CPo218 + CPb214 + CBi214 ) · tη= NRn2 − ηRn2,Po212
NTn
Tn,Po212(7)

RnP1 = η
NPo218Rn1,Po218 · Ve,Rn,Po218 · CPo218 · t= NRn1 −(8)(ηRn1,Po212 +ηRn1,Bi212 )η
RnP2
NTn − ηRn1,Po214
NPo214
ηTn,Po212
Rn2,Po214

In the atmosphere, a large fraction of 218 Po and 212 Pb can react with the ions in the air and form
clusters in a short time by the neutralization process. Due to the larger diﬀusion coeﬃcient of thesecluster particles, 222 Rn and 220 Rn progenies can attach themselves to various surfaces, such as thesurfaces of aerosol particles and droplets in the atmosphere, thereby giving rise to a consecutive activity
size distribution. This distribution is broadly classiﬁed into two groups: the unattached fraction
and the attached fraction. The eﬀective deposition velocities combine the contribution from both theunattached and attached fractions of each progeny species. Considering the contributions of these two
fractions, the deposition velocity of each radionuclide can be demonstrated as follows:
Vi = pi · Vdu + (1 − pi ) · Vda(9)where pi denotes the unattached fraction of radionuclide i, and Vdu and Vda denote the deposition
velocities of the unattached and attached fraction of airborne particles, respectively, which are dependent
on the aerodynamic factors instead of the radionuclides themselves.
Since the registered tracks from 212 Po decay come from the decay of the deposition ﬂux of 212 Pb
and 212 Bi, according to the concept of the eﬀective deposition velocity, the deposition velocity of TnPchannel could be written as follows:
Ve,Tn =

VPb212 · CPb212 + VBi212 · CBi212
CPb212 + CBi212(10)

Similarly, the deposition velocity of the RnPII and RnPI channels could be written as follows:
Ve,Rn =

VPo218 · CPo218 + VPb214 · CPb214 + VBi214 · CBi214
CPo218 + CPb214 + CBi214
Ve,Rn,Po218 = VPo218

126

(11)
(12)

IJERPH 2020, 17, 8569

The atom concentrations in these equations could also be reexpressed in terms of the activity
concentrations (Ai , Bq m−3 ) by using the decay constant λi , s−1 . Subsequently, Equations (6)–(8) could
be modiﬁed as follows:V·λ+ VBi212 · λPb212 · r3r
1
TnP
NPo212· APb212 · t= ηTn,Po212 · Pb212 Bi212
·
+ 3
(13)
λBi212 + λPb212
λPb212λBi212where r3 = ABi212 /APb212 .
RnP2 = η
NPo214
Rn2,Po214 ·VPo218 · λPb214 · λBi214 +VPb214 · λPo218 · λBi214 · r1 +VBi214 · λPo218 · λPb214 · r2
λPb214 · λBi214 +λPo218· λBi214 · r1 +λPo218 · λPb214 · r2
rr
· λ 1 + λ 1 + λ 2 · APo218 · t
Po218
Bi214
Pb214

(14)

where r1 = APb214 /APo218 and r2 = ABi214 /APo218 .
RnP1
NPo218= ηRn1,Po218 · VPo218 ·APo218·t
λPo218(15)

To solve these equations above, we introduced the Jacobi room model [16] for both 222 Rn and
220 Rn. Because the steady-state Jacobi room model is a system of linear equations, the number of

unknowns, such as the unattached fractions of each progeny radionuclide and the ratios of the progeny
concentration, is less than the number of equations. The solutions of the unknowns could be deducedby the parameters in the Jacobi room model, which are the attachment rate constant, λa (s−1 ); the rate
constant for deposition of unattached progeny, λd u (s−1 ); the rate constant for deposition of attachedprogeny, λd a (s−1 ); and the ventilation rate constant, λv (s−1 ). The details of the equations of the Jacobi
room model for both 222 Rn and 220 Rn behaviors could be found elsewhere [6]. Finally, the APb212 canbe solved by the data of the TnP channel and APo218 can be solved by both the RnPI channel and RnPII
channel in the equations.
2.2.2. Parameters Estimation
Deposition Velocity
In the theoretical model, Lai and Nazaroﬀ’s [17] three-layer model was adopted to simulate
the particle deposition. Compared to the other existing formulations of such models based on thepioneering work of Corner and Pendlebury [18], lacking a thorough physical foundation, the proposedmodel involves three mechanisms of particle transport: Brownian diﬀusion, turbulent diﬀusion,and gravitational settling. It predicts deposition to smooth surfaces as a function of particle size anddensity. Therefore, the only required input parameters are enclosure geometry and friction velocity.
This deposition velocity estimation method has already been applied for deposition particles in a roomand experimentally veriﬁed by Mishra et al. [15].
Parameters in the Jacobi Room Model
In practice, the indoor rooms can be regarded as a rectangular cavity. The rate constant for
deposition in the Jacobi room model is estimated by using the deposition velocity calculated by Lai
and Nazaroﬀ’s three-layer model [17]. For the rectangular cavity, the rate constant for deposition canbe written as follows:
vid,u Su + vid,v Sv + vid,d Sd(16)
λid = nc ·Vwhere the superscript i, with the allowed values a and u, allows us to distinguish the two important statesof 222 Rn and 220 Rn progeny: attached and unattached. Su , Sv , and Sd are the areas of upward-facing
surfaces, vertical surfaces, and downward-facing surfaces, respectively; and nc is the correction
coeﬃcient of the surface area [19], which can be used to correct the changes of ratio caused by the127

IJERPH 2020, 17, 8569

increased furnishing surface area in practical application. The deposition velocity of the unattachedfraction was interpolated by the result of the numerical integration for ﬁne particles in the reference [17].
The rate constant for attachment in the Jacobi room model reﬂects the attachment velocity of
the unattached 222 Rn and 220 Rn progeny to the ambient aerosol. The charging process depends onthe electric charge distribution of an aerosol in steady state. In most used theories, attachment is
diﬀusion-controlled as a result of electrostatic attraction and follows the gas kinetic laws [20–22].
The expression of the rate constant for attachment can be written as follows:
λa = β · Noβ=∞0

   β dp Z dp ddp

(17)
(18)

where No is the aerosol concentration, reﬂecting the concentration of condensation nuclei and whereZ(dp ) is the number size distribution of aerosol for unit aerosols concentration and can be described as afrequency function of the lognormal distribution with the count median diameter (CMD) and geometricstandard deviation (GSD, σg ). β(dp ) is the attachment coeﬃcient. The rate constant for attachment wasestimated by the compound trapezoid formula with the Latin-hypercube sampling method.
3. Results and Discussion
3.1. The Comparison of Chamber Test with a Theoretical Model
To verify the feasibility of measuring the EEC, a veriﬁcation experiment was conducted in 222 Rn
and 220 Rn exposure chambers located in Hirosaki University, Japan. The chamber veriﬁcation system
includes 4 function cells, as shown in Figure 2. (1) The source generation cell is a 222 Rn gas and
220 Rn gas generation system, which employs the natural uranium rock and commercially available
lantern mantles as the 222 Rn and 220 Rn sources, respectively, to generate and import 222 Rn and 220 Rn to
the mix chamber. The humidiﬁer in this cell is responsible for maintaining the stability of the inlet
gas concentration. (2) The aerosol generation cell contains 3 components, a compressor, a constant
output atomizer (TSI, Inc., Aerosol Generator Model 3076), and a diﬀusion dryer ﬁlled with silica gel.
The 5000 μg mL−1 NaCl solution is employed to generate droplets with the median diameter of 0.3 μm(GSD < 2.0) to mix with 222 Rn gas or 220 Rn gas in the mix chamber. (3) The exposure cell includes twochambers: a mix chamber and an exposure chamber. The volumes of the mix chamber and exposure
chamber are 150 L and 3.24 m3 (dimensions of 2.25 × 1.2 × 1.2 m3 , L × W × H), respectively. The mix
chamber provides a buﬀer to create more chances for the aerosol particles and gas to form a stableprogeny ﬂux to the exposure chamber. To maintain stable concentration in the exposure chamber,the experiment adopted a circulating connection that applies the outlet of the exposure chamber as
the inlet of the source generation cell with an airﬂow rate of 3 L min−1 . (4) The measurement cell is
responsible for measuring progeny concentrations and environmental parameters in the veriﬁcation
experiment. The portable Si-photodiode detector with a sampling ﬂow rate of 0.5 L min−1 and an EMD
Millipore MF-Millipore AAWG02500 Mixed Cellulose Ester Filter Membrane were used to measure
the EEC of 222 Rn in real-time. The details of the Si-photodiode detector can be found elsewhere [23,24].
The periodic grab sampling method was carried out to replace the portable Si-photodiode detector
to measure the EEC of 220 Rn. The Model 3034 SMPSTM Scanning Mobility Particle Sizer producedby TSI® was adopted to measure the concentration of condensation nuclei, CMD, and its GSD (σg ).
The concentration of condensation nuclei in the exposure chamber ranged from 2.05 × 104 to 4.32 × 104
particles per cm3 . The CMD of the aerosol in the exposure chamber ranged from 0.187 to 0.218 μm.
The friction velocity was calculated using a fan-turbulence model [11,25], as follows:u∗ =Ns d2t
V1/3

128

(19)

IJERPH 2020, 17, 8569

where Ns is the rotation speed of the fan (2300 rotation min−1 ), dt is the blade length for rotation (5 cm),and V is the volume of the exposure chamber. In this exposure chamber, we set two fans in opposite
directions; as a result, we obtained u* as 23.53 cm s−1 . In the veriﬁcation experiment, each channel
had 4 slices of CR-39 in the vertical and upward orientations as one group. For the total veriﬁcation
experiment, each exposure period had 3 groups of progeny detectors in the front, middle, and backof the bottom of the exposure chamber. In the theoretical model, the genetic algorithm is adopted to
optimize the parameters in the calculation process. The measured values of the concentration of nuclei
condensation number, CMD and its GSD, estimated friction velocity, and ventilation rate are the input
parameters. Since the friction velocity, ventilation rate, and particle distribution ﬂuctuate and change
all the time, the equilibrium value of each parameter during the exposure period should be optimized
depending on the diﬀerent circumstances for each survey.

Figure 2. A schematic diagram of the chamber veriﬁcation system.

A genetic algorithm with an improved goodness-of-ﬁt objective function was adopted to optimize
the results of the theoretical method [26]. The improved genetic algorithm was used to maximize thegoodness-of-ﬁt objective function f (x) as follows:
f (x) =ni = 1 ωixn | 1,i −x2,i |
· ωi
i=1
xi

(20)

where n is the number of objects of the model; x1,i, and x2,i are the measured data from actual
measurement of EEC; and ωi is the weight. The measured ranges of the concentration of nuclei
condensation number, CMD, and its GSD are the optimized parameters, and the goodness-of-ﬁtfunction is carried out to decrease the error of the average EEC of 222 Rn calculated by the calibrated
portable Si-photodiode detector and the CR-39-based progeny detector. The average track density ofdetectors deployed in the upward and vertical orientations was used to calculate the EEC of 222 Rn by
the progeny detector, which is in the same orientation as that placed in use. The same veriﬁcation
experiment was also conducted for 220 Rn progeny except for the measurement method for the EEC of
220 Rn, which used the periodic grab sampling method to replace the portable Si-photodiode detector.
The comparison results of the progeny detector and experiment are shown in Tables 2 and 3. In thecalculation, we estimated the deposition velocity of total condensation nuclei in the vertical andupward orientations, which were in the same orientation as the setting in the experiment, and thetotal deposition velocity and deposition ﬂux of each channel. As shown in Table 2, for the 220 Rn

129

IJERPH 2020, 17, 8569

progeny with an exposure time of 36.9 h, the average experimentally estimated deposition velocities
in the upward and vertical orientations were 0.193 ± 0.067 and 0.217 ± 0.045 m h−1 , respectively.
Additionally, the model-simulated deposition velocities were 0.243 and 0.238 m h−1 , respectively, whichwere located in the ranges of the experimental data. In the experiment, the deposition velocity in the
upward orientation presented insigniﬁcant variation with that of the vertical orientation. The exposure
time also presented an insigniﬁcant inﬂuence on the deposition velocity between 25.5 and 36.9 h.
For deposition ﬂux, the variation of deposition ﬂux on the TnP channel estimated by the model showed
excellent agreement with experimental values. As shown in Table 3, for the 222 Rn progeny, among
distinct exposure times of 30, 70, and 102 h, the calibrated deposition velocities varied narrowly in the
upward and vertical orientations, with the ranges of 0.123–0.136 and 0.117–0.131 m h−1 , respectively.
The average deposition ﬂuxes in the theoretical model of 222 Rn progeny on the RnPII channel andof 218 Po on the RnPI channel were located in the ranges of the experimental values in most cases.
The deposition ﬂux was calculated by the net track density (NTD). The calculation process of NTD
itself has uncertainty, especially caused by the sensitivity of the CR-39 detector, read-out of the tracks,
counting statistics, and assumed background of the CR-39 detectors [11], except for the exposure
environment. Additionally, from Equations (6)–(8), the calculation of the tracks registered by lower
alpha-energy progeny should exclude the tracks registered by higher alpha- energy progeny on thechannel. Therefore, with a thinner absorber ﬁlter, a higher uncertainty of the measured deposition ﬂux
is present due to propagations of the uncertainty during the calculation of the NTD.
Table 2. The comparison results of the progeny detector and experiment in a 220 Rn chamber
veriﬁcation system.
Model

Experiment

Model

Experiment

Exposure time (h)

25.5

36.9

The number concentration (N cm−3 )27,29730,417

GSD, σg

1.506

1.613

0.203

0.203

CMD (μm)
Track density(tr mm−2 )Upward3.9

2.9

Vertical

4.3

4.8

Upward0.185

0.143 ± 0.029

0.243

0.193 ± 0.067

Vertical

0.169

0.158 ± 0.040

0.238

0.217 ± 0.045

212 Pb

0.185

——

0.219

——

212 Bi

0.132

——

0.183

——

Deposition ﬂux(atoms cm−2 s−1 )Upward

0.081

0.081

0.055

0.069

Vertical

0.090

0.090

0.042

0.042

EEC of 220 Rn

Upward237 ± 88

Vertical

263 ± 88

Deposition velocity(m h−1 )(Bq m−3 )244 ± 108 1

148 ± 38
188 ± 50155 ± 67 1

1 The value was calculated by the average equilibrium equivalent concentration (EEC) of 220 Rn over the whole

exposure period by grab sampling method.

130

131

0.101

214 Bi

1214 ± 322
267 ± 187

0.014

VerticalVerticalUpwardUpward214 Bi to RnPII

218 Po, 214 Pb,

0.041

0.155

214 Pb

Vertical

0.290

218 Po218 Po to RnPI

0.131

VerticalUpward

0.136

——

0.123

0.005 ± 0.004

740 ± 27 1

0.023 ± 0.006

603 ±312

730 ±290

0.011

0.022

0.051 ± 0.010
0.043 ± 0.009

0.091

0.135

0.248

0.117

——

——

——

——

——

——

——

——

——

693 ±16 1

0.016 ± 0.009

0.014 ± 0.008

0.040 ± 0.014

0.048 ± 0.017

7.1 ± 1.8

Upward

13.6 ± 2.1

7.4 ± 1.5
1.1 ± 0.8

RnPI
RnPII

1.768
0.191

630 ± 375

——

——

——

——

——

686 ± 31 1

0.009 ± 0.007

0.007 ± 0.006

0.035 ± 0.019

0.030 ± 0.016

5.9 ± 1.3

17.2 ± 2.7

4.9 ± 1.1

758 ± 370

0.008

0.018

0.092

0.112

0.230

0.119

0.125

Experiment33,278102

14.9 ± 2.3

Model

1 The value was calculated by the average EEC of 222 Rn over the whole exposure period by the continuous portable Si-photodiode detector.

EEC of 222 Rn(Bq m−3 )Deposition ﬂux(atoms cm−2 s−1 )Deposition velocity(m h−1 )Vertical

6.2 ± 1.6

4.5 ± 1.2

RnPII

RnPI

16.4 ± 2.5

Upward6.3 ± 1.3

Track density(tr mm−2 )

0.200

0.233

CMD (μm)

1.761

33,833

1.714

Experiment34,52870

GSD, σgModel

Concentration of nuclei number (N cm−3 )Experiment30

Exposure time (h)ModelTable 3. The comparison results of the progeny detector and experiment in a 222 Rn chamber veriﬁcation system.

IJERPH 2020, 17, 8569

IJERPH 2020, 17, 8569

3.2. Comparison of the Estimated Deposition Velocities with Previous Studies
Compared with the deposition velocities of the total 222 Rn and 220 Rn progeny of the otherresearchers [7,11,15,27], as shown in Table 4, these values varied widely from 0.117 to 8.64 m h−1 and
0.072 to 19.08 m h−1 , respectively. To analyze the impact factors of the deposition velocity of 222 Rn and
220 Rn progenies, except the deposition velocities measured by Bigu [25], other deposition velocities
measured in small-size chambers are much higher than that measured in the test rooms, dwellings, orlarge-size chambers. This can be explained by the turbulence, caused by the surface roughness, friction
velocity, and airﬂow rate on the surface in a small-size chamber, being much more intense than that ina large room. Similarly, in Bigu’s research, the mixing fan was operated to investigate the eﬀect ofstrong airﬂow and turbulence on the deposition velocity [24]. When the fan is on, the surface airﬂow
and turbulence would be more intense, accompanying the increasing deposition velocity of the 222 Rn
and 220 Rn progenies.
Table 4. Summary of the deposition velocities of 222 Rn and 220 Rn progenies in previous studies.
Reference[27]

Deposition Velocity (m h−1 )TnP Detector

8.64

19.08

Fan on, 26 m3 test facility

3.24

2.16

Fan oﬀ, 26 m3 test facility

0.19 ± 0.04

Dwelling, the same structure of TnP detector as this study

0.075 ± 0.0072

22.5 m3 test room[7]0.132 ± 0.0036[15]

2.37 ± 0.785
0.117

[11]
This study

RemarkRnP Detector

0.125 ± 0.007

0.5 m3 chamber
0.072

Dwelling

0.828 ±0.072

150 L chamber, same TnP detector as this study

0.178 ± 0.045

3.24 m3 chamber

The design of TnP detectors from Zhuo and Iida [7] and Sorimachi et al. [11] are the same as thatin the present study, and only the measuring environmental conditions are diﬀerent. The deposition
velocity measured in the small-size chamber [11] is signiﬁcantly higher than that measured indwellings [7] and the present study. It should be noted that the deposition velocity measured in thisstudy agreed well with that measured in dwellings. Besides, the deposition velocities of the RnP
detector measured by Marsh et al. [15] in the test room and dwelling were also comparable to that ofthe present study. Therefore, the deposition velocities estimated by both experiments and theoreticalmodels are acceptable in this study. Furthermore, the calibration results from this study are suitable toassess the 222 Rn and 220 Rn progeny exposure in test rooms and dwellings.
3.3. The Relationship between NTD and Time-Integrated EEC
The relationship between the NTD and the time-integrated EEC of 222 Rn and 220 Rn is shown in
Figure 3. Based on the concept of the potential alpha energy concentration of 222 Rn and 220 Rn progeny,
the NTD caused by 212 Po on the TnP channel can be used to estimate the total potential alpha energy of
212 Po emitted by the deposited 212 Pb and 212 Bi. The detectors were exposed to a total of 220 Rn progeny
concentration of 83 ± 20 Bq m−3 during the exposure period from 0.2 to 2.5 d. The time-integrated EECof 220 Rn ranged from approximately 16 to 168 Bq m−3 d, which corresponded to the time-integrated
EEC of 220 Rn in an exposure period between 1 week to 3 months with the average EEC of ca. 2 Bq
m−3 per day indoors [5]. The result demonstrated that the values of NTD increased linearly with anincrease of time-integrated EEC of 220 Rn. Accordingly, the NTD caused by 218 Po on channel RnPI canbe used to estimate the atom number of the deposited 218 Po on the detector ﬁrstly decaying to 214 Pb.
Furthermore, the NTD of 214 Po can be used to calculate the total potential alpha energy of 214 Po emitted

132

IJERPH 2020, 17, 8569

by the deposited 218 Po, 214 Pb, and 214 Bi during the decay. Therefore, in Figure 3a, the energy-weighted
NTD was calculated as follows:




 
ε 218 Po · NTD of 218 Po + ε 214 Po · NTD of 214 Po
Energy weighted NTD =(21)( ε(218 Po) + ε(214 Po))
where ε (i) is the alpha energy of the radionuclide i emitted during the decay. ε(218 Po) is 6.0 MeV, and ε(214 Po) is 7.7 MeV. The progeny detectors were exposed to an average EEC of 222 Rn of 685 ± 6 Bq m−3
during the exposure period. The time-integrated EEC of 222 Rn ranged from approximately 863 to 2839
Bq m−3 d, which corresponds to the time-integrated EEC of 222 Rn in an exposure period from 1 monthto 3 months with an average EEC of 222 Rn of ca. 30 Bq m−3 per day. As a result, the values of the three
NTDs increased linearly with the increase of the time-integrated EEC of 222 Rn. Thus, it is possible toestimate the EEC of 222 Rn indoors during a certain period. To compare the three NTDs as a function of
the time-integrated EEC of 222 Rn, the R2 of NTD of 218 Po, energy-weighted NTD, and NTD of 214 Pb
were successively decreased from 0.9861 to 0.5625. Therefore, compared to the other deposition-based
passive 222 Rn progeny detectors which only measure the NTD contributed by 214 Po, the detector withtwo channels is much more reliable. Besides, the progeny detector with 4 slices of CR-39 for the TnPchannel designed rather than the same slices of CR-39 for each channel is recommended to decrease
the error in calculation.
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1HWWUDFNGHQVLW\ 7UPP\ [
5 






3RRQ7Q3






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
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7LPHLQWHJUDWHG((&RI5Q %TPGE

Figure 3. The net track density (NTD) as a function of time-integrated equilibrium equivalentconcentration (EEC): (a) the NTD as a function of time-integrated EEC of 222 Rn, where the NTD has
excluded the contribution of other radionuclides on the CR-39, and (b) the NTD as a function oftime-integrated EEC of 220 Rn.
133

IJERPH 2020, 17, 8569

4. Conclusions
In this study, a 3-channel passive CR-39-based direct 222 Rn/220 Rn progeny detector was developed
and tested to measure and calculate the EEC of both 222 Rn and 220 Rn without the equilibrium factor.
In the veriﬁcation chamber experiment, the genetic algorithm was implemented to optimize theestimation result of the theoretical model. The optimized deposition ﬂuxes of 220 Rn progeny on
the TnP channel, the 222 Rn progeny on the RnPII channel, and 218 Po on the RnPI channel agreed
well with the experimental measurements. The EEC of 220 Rn and 222 Rn measured by the calibrated
devices are comparable to the estimated value of the detector. Compared with the two channels’
detectors, the energy-weighted NTD is much more reliable to estimate the EEC of 222 Rn rather than
only measuring the NTD contributed by 214 Po. Moreover, because the exposure conditions, especiallythe airﬂow and turbulence in the room, are smaller than that in the small-size chamber, the deposition
velocity measured in this study is close to the value measured in the room. Therefore, a detector
calibrated in a similar size to the chamber test as in this study is more reliable for assessment of 220 Rn
and 222 Rn progeny exposure. At last, since the detector is sensitive to the exposure environmental
condition, in the site survey, it is recommended to use the improved passive CR-39-based directprogeny detector after its calibration in a typical indoor environment.
Author Contributions: Conceptualization, J.H. and S.T.; data curation, J.H. and G.Y.; formal analysis, J.H. andG.Y.; funding acquisition, J.H. and S.T.; investigation, J.H.; methodology, J.H., C.K., and K.I.; project administration,
S.T.; resources, M.H.; supervision, S.T.; writing—original draft, J.H.; writing—review and editing, G.Y. and S.T.
All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by JSPS KAKENHI, grant numbers 16K15368, 18KK0261, 19J14291,
and 20H00556.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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135

International Journal ofEnvironmental Researchand Public Health
ArticleTotal Diet Study to Assess Radioactive Cs and 40K
Levels in the Japanese Population before and after the
Fukushima Daiichi Nuclear Power Plant Accident
Hiroshi Terada 1, *, Ikuyo Iijima 2 , Sadaaki Miyake 3 , Kimio Isomura 4 and Hideo Sugiyama 1
1
2
3
4

*

Department of Environmental Health, National Institute of Public Health, Saitama 351-0197, Japan;sugiyama.h.aa@niph.go.jp
Chemistry Division, Kanagawa Prefectural Institute of Public Health (Retired), Kanagawa 253-0087, Japan;
ikijima@icloud.com
Biological Eﬀect Research Group, Saitama Prefectural Institute of Public Health, Saitama 355-0133, Japan;
miyake.sadaaki@pref.saitama.lg.jp
Hyogo Prefectural Institute of Public Health and Environmental Sciences (Retired), Kobe 652-0032, Japan;
zaihuriboku@gmail.com
Correspondence: terada.h.aa@niph.go.jp; Tel.: +81-48-458-6263

Received: 10 October 2020; Accepted: 31 October 2020; Published: 3 November 2020

Abstract: We conducted a total diet study (TDS) of 137 Cs, 134 Cs, and 40 K to assess their average
dietary exposure levels in a Japanese adult population before and after the Fukushima Daiichi nuclear
power plant (FDNPP) accident. Nineteen market baskets were evaluated in 2006–2011. In eachbasket, a TDS sample comprising tap water and 160–170 food items, which were combined into
13 groups, were collected for analysis by gamma-ray spectrometry. From 2006 to 2010, the 137 Cs
activity concentration in the “ﬁsh and shellﬁsh” group was 0.099 Bq/kg, representing the highest value
obtained, whereas the total committed eﬀective dose (CED) of radiocesium isotopes (137 Cs + 134 Cs)
was 0.69 μSv. In 2011, “milk and dairy products” from Sendai City had a Cs activity concentration of
12 Bq/kg, representing the highest values among all food groups studied. However, the annual CEDof radioactive Cs in Fukushima City was 17 μSv after the FDNPP accident, which is 60-fold lower
than the maximum permissible dose of 1 mSv/year. The mean CED obtained for 40 K was 180 μSv,
which is comparable to the global average. Our results reveal the average dietary exposure of 137 Cs,
134 Cs, and 40 K, which can aid in estimating the radiological safety of foods.
Keywords: total diet study; radioactive cesium; potassium-40; dietary intake; dose assessment;
Fukushima accident

1. Introduction
To ensure food safety, it is essential to assess the exposure levels to toxic substances in food.
Currently, there are three approaches for estimating the dietary intake of such substances: total dietstudy (TDS), duplicate portion study (DPS), and selective study of individual foodstuﬀs. A TDS,
also referred to as a market basket study, has an advantage over the two alternatives in terms of
its accuracy. Furthermore, TDS takes into account the eﬀect of kitchen preparation on the levels of
toxic substances in food, and provides information on which food groups are the main sources ofcontamination [1]. Therefore, TDSs have been supported and endorsed by the Food and Agriculture
Organization of the United Nations (FAO) and the World Health Organization (WHO) since the1970s. According to a survey carried out in 2015 by Health Canada, in cooperation with the WHO,
approximately 53 countries around the world perform TDS analyses [2].
The ﬁrst TDS was conducted in response to public concerns about a radioactive fallout fromatmospheric nuclear testing [3,4]. Fallouts contain hundreds of diﬀerent radionuclides. Among these,
IJERPH 2020, 17, 8131; doi:10.3390/ijerph17218131

137

www.mdpi.com/journal/ijerph

IJERPH 2020, 17, 8131

137 Cs and 90 Sr are the most signiﬁcant sources of internal exposure to radiation, owing to their long

half-lives of 30.17 years and 28.8 years, respectively, as well as to their chemical similarities to essential
elements (137 Cs resembles potassium and 90 Sr resembles calcium). Therefore, the U.S. Food and Drug
Administration (FDA) has been carrying out TDSs focusing on these two radionuclides since 1961 [5].
In Japan, TDSs have been performed annually by the Ministry of Health, Labour and Welfare(MHLW) since 1977 [6,7]. Initially, pesticides and their metabolites, seven metals (Pb, Cd, total Hg,
total As, Cu, Mn, and Zn), and total polychlorinated biphenyl (PCB) were analyzed in these studies [6,8].
Similarly, radioactivity monitoring has been conducted by the Nuclear Regulation Authority (NRA)
since the 1950s. Radionuclide levels in airborne dust, rainwater, river water, seawater, soil, and foodhave been analyzed in this monitoring [9]. Until 2008, the NRA also conducted DPSs to evaluate
the daily dietary intake of radionuclides [10–12]. Subsequently, TDSs of radionuclides began in2003 by the MHLW to assess total exposure levels of radionuclides in the average Japanese diet,as well as the contribution of each food group to this total. Between 2003 and 2011, we carried out
a TDS, which was supported by a Health and Labour Sciences Research Grant (HLSRG) from the
MHLW [13–19]. From 2003 to 2005, the dietary exposure to man-made radionuclides (137 Cs, 134 Cs,
and 90 Sr) and natural radionuclides (40 K, 214 Pb, 214 Bi, 228 Ac, 212 Pb, 208 Tl, and U) were determined.
Sugiyama et al. [13] revealed that only trace amounts of 137 Cs were found in TDS samples, and that“ﬁsh and shellﬁsh” contained 0.145 Bq/kg, representing the highest activity concentration measured.
They also found that the daily dietary intake and the committed eﬀective dose (CED) of 137 Cs were,at the very most, 0.080 Bq/person/day and 0.38 μSv, respectively, with the main sources of the exposure
being from the “ﬁsh and shellﬁsh”, “meat and eggs”, and “other vegetables, mushrooms and seaweeds”
food groups.
The present study aimed to assess trends in dietary exposure levels to γ-emitting radionuclides,
namely 137 Cs, 134 Cs, and 40 K, from typical Japanese diets via TDS. The concentrations, dietary intake,and CEDs of these radionuclides from 2006 to 2011 have been presented. The results from before andafter the Fukushima Daiichi nuclear power plant (FDNPP) accident that occurred in March 2011 havebeen compared. We also attempted to summarize the results of the TDS performed between 2012 and2019 by other institutions in Japan, because almost 10 years have passed since the FDNPP accident.
2. Materials and Methods
2.1. Sampling and Preparation
Each year, TDS samples have been collected from three or four cities in diﬀerent regional blocksof Japan, except for the year 2010. Each sample collection is referred to as a market basket (MB).
We collected as many locally produced food items as possible. The most preferred production
areas in descending order were same prefecture, same regional block, and other regional blocks inJapan. As shown in Figure 1, 19 MBs were collected from all regional blocks of Japan, other thanMinami-Kyushu, from 2006 to 2011. In each MB, 160 to 170 food items were purchased from local
retailers. These items were classiﬁed into 13 food groups as follows: rice and rice products (Group I);
cereals, seeds, nuts, and potatoes (Group II); sugars and confectionaries (Group III); fats and oils (GroupIV); pulses and their products (Group V); fruits (Group VI); green and yellow vegetables (Group VII);other vegetables, mushrooms, and seaweeds (Group VIII); beverages (Group IX); ﬁsh and shellﬁsh(Group X); meat and eggs (Group XI); milk and dairy products (Group XII); and seasonings (GroupXIII). The relative proportion of each food item within a group was based on average regional foodconsumption data for individuals 20 years and over, which were obtained from the National Healthand Nutrition Survey (NHNS) performed by the MHLW between 2002 and 2004. Individual food items
were cooked, if necessary, and then combined for analysis into 13 food groups. In addition, tap water
was collected in each MB for drinking water (Group XIV). Thus, in total 19 × 14 = 266 TDS samples
were obtained. The sample weights of individual food groups were approximately 5 kg, with the
exception of 12 kg for “rice and rice products” and 100 kg for “drinking water”.

138

IJERPH 2020, 17, 8131

Regional blocks of Japan*
1.
2.
3.
4.
5.
6.

Hokkaido
TohokuKanto I
Kanto II
Hokuriku
Tokai

7.
8.
9.
10.
11.
12.

Kinki I
Kinki II
Chugoku
Shikoku
Kita-Kyushu
Minami-Kyushu*classified according to National Health andNutrition Survey in Japan

Figure 1. Sampling sites of included in the total diet study conducted from 2006 to 2011. Sampling
year of each site is denoted in parenthesis.

TDS samples, other than “fats and oils” and “drinking water”, were freeze-dried or heat-dried andthen incinerated at 450 ◦ C for 24 h into ash. The ash samples were placed in separate plastic containers
with a capacity of 100 mL. The “drinking water” samples were condensed by heating and evaporated
to dryness, and the residues were stored in the plastic containers, as described above. The “fats andoil” samples were stored in 1 L Marinelli beakers in their raw state.
2.2. Determination of 137 Cs, 134 Cs, and 40 K
Cs-137, Cs-134, and K-40 in the TDS samples were detected for a minimum of 80,000 s using
high-purity Ge semiconductor detectors (2519 and GC2018 of CANBERRA Co., Meriden, CT, USA;EGPC 20-190-R of EURYSIS Co., Lingolsheim, Cedex-France; CNVD30-35195 of OXFORD Co., Oxon,
Oxford, UK; and IGC40200 and IGC25190SD of PGT Co., Princeton, NJ, USA). Activity concentrationsof the three radionuclides were corrected as of the end of the sampling period and expressed in
Bq/kg of fresh weight. Energy and eﬃciency calibrations were performed using γ-ray volume sources(MX033U8PP and MX033MR, Japan Radioisotope Association, Tokyo, Japan). The limits of detection(LODs) for 137 Cs and 134 Cs were approximately 0.05 Bq/kg for all food groups, except for “fats andoils” and “seasonings”.
2.3. Calculation of Dietary Intake and the Committed Eﬀective Dose (CED) Values
The daily dietary intake of radioactive Cs and 40 K for adults was calculated from the activity
concentrations of the three radionuclides in the samples, as described above. The radionuclide139

IJERPH 2020, 17, 8131

activity concentration was multiplied by the average food consumption value for the adult population,
as determined by the NHNS, in each regional block to provide the radionuclide intake for eachradionuclide and food group. Next, the calculated intake for each food group was summed to estimate
the total dietary intake of a given radionuclide in each MB. The dietary intake of radioactive Cs was
obtained by summation of 137 Cs and 134 Cs intake values. If a target radionuclide was not detected in asample, the activity concentration of the non-detected (ND) radionuclide was assumed to be zero or
the LOD value. The lower and upper limits of the total radionuclide intake values were estimated byassuming the ND value as zero and the LOD, respectively.
The CED values associated with Cs and 40 K for adults were estimated under the assumptionof a one-year intake of the TDS samples, and were obtained by applying the dietary radionuclide
intake values and dose coeﬃcients for ingestion of each radionuclide, given by the International
Commission on Radiological Protection (ICRP), to be 1.3 × 10−8 Sv/Bq for 137 Cs, 1.9 × 10−8 Sv/Bq for
134 Cs, and 4.6 × 10−9 Sv/Bq for 40 K [20]. The CED of radioactive Cs was calculated by summing thoseof 137 Cs and 134 Cs. The ND radionuclides were given a value of zero and the LOD for estimating thelower and upper limits of the CED values, respectively.
3. Results and Discussion
3.1. Levels of 137 Cs, 134 Cs, and 40 K
3.1.1. 137 Cs Levels before the FDNPP Accident
We collected 16 MBs from 13 cities between 2006 and 2010, resulting in a total of 224 TDS samples.
Cesium-137 was the only anthropogenic radionuclide observed in these samples, as 134 Cs, which
was released from the Chernobyl disaster, was not detected at all. Table 1 summarizes the 137 Cs
activity concentrations in TDS samples from 2006 to 2010. The activity concentrations of 137 Cs in TDS
samples were all below 0.1 Bq/kg during this period. The food group “ﬁsh and shellﬁsh” had a 137 Cs
activity concentration of 0.099 Bq/kg, representing the highest value measured, followed by “othervegetables, mushrooms and seaweeds” (0.092 Bq/kg), “meat and eggs” (0.083 Bq/kg), and “milk anddairy products” (0.057 Bq/kg). The highest mean 137 Cs activity concentrations were found in “ﬁshand shellﬁsh” (0.072 Bq/kg) followed by “other vegetables, mushrooms and seaweeds” (0.024 Bq/kg),“meat and eggs” (0.024 Bq/kg), and “milk and dairy products” (0.022 Bq/kg). These results are similar
to the TDS carried out between 2003 and 2005 [13]. Cesium-137 was detected in all “ﬁsh and shellﬁsh”
samples, whereas it was not found in any samples of “fats and oils”, “seasonings”, and “drinking
water”. The detection rate of 137 Cs was about 30%, and was the highest in “ﬁsh and shellﬁsh” (100%),
followed by “milk and dairy products” (68.8%), “meat and eggs” (62.5%), and “other vegetables,
mushrooms and seaweeds” (50.0%).
3.1.2. 137 Cs and 134 Cs Levels after the FDNPP Accident
We obtained 42 TDS samples from Sendai City, Fukushima City, and Tokyo in October andNovember of 2011, approximately six months after the FDNPP accident. According to the United
Nations Scientiﬁc Committee on the Eﬀects of Atomic Radiation (UNSCEAR) [21], the total release of
137 Cs, 134 Cs, and 131 I in the atmosphere resulting from the FDNPP incident was estimated to be 8.8 PBq,
9.0 PBq, and 124 PBq, respectively. Immediately after the FDNPP accident, some foodstuﬀs, such as
spinach and milk, were highly contaminated with 131 I, which accumulates in the thyroid gland andmay increase the risk of thyroid cancer [22–24]. However, 131 I levels decreased rapidly and became
undetectable [25–27], owing to its short half-life of 8.02 days. Therefore, 131 I was not observed in thepresent study.

140

141

Beverages

Fish and shellﬁshMeat and eggs
Milk and dairy products
Seasonings
Drinking water

VIII

IX *5

X
XI
XII
XIII *6
XIV

0.092<0.024<0.016<0.018
0.099
0.041
0.057
<0.140<0.0004

0.004<0.0250.035<0.056<0.058<0.0240.015<0.003<0.010<0.018<0.032<0.040<0.010<0.0220.067<0.023<0.021<0.012<0.0002

Max.
*2

Min.
*1

2006 (n = 4)0.078
<0.018<0.025<0.075<0.0001<0.004<0.029<0.005<0.015<0.012<0.024<0.024<0.010<0.016

Min.
*1

0.093
0.032
0.018
<0.155<0.0004<0.0150.069

0.00450.016<0.052<0.049
0.016
0.027
0.018

Max.
*2

2007 (n = 3)0.029
<0.020<0.027<0.054<0.0001<0.007<0.015<0.004<0.014<0.015<0.014<0.024<0.011<0.009

Min.
*1

0.071
0.083
0.033
<0.14
<0.0005

0.00730.031

0.00610.034
0.019<0.0650.019<0.037<0.039Max.
*22008 (n = 4)

0.062
<0.025<0.042<0.028<0.0001<0.004<0.022<0.008<0.009<0.022<0.022<0.014<0.010<0.024

Min.
*1

0.093
0.054
0.051
<0.087<0.0003

0.0049

0.024

0.013
0.033
<0.038<0.0780.032
0.038<0.029Max.
*2

2009 (n = 4)

0.048
0.028
0.035
<0.089<0.0002<0.006<0.0180.020<0.010<0.150<0.220<0.076<0.026<0.0242010(n = 1)0.00077 ±0.002100.0720 ± 0.0205
0.024 ± 0.024
0.022 ± 0.012
000.024 ± 0.031

0.0036 ± 0.0059
0.0058 ± 0.012
0.0049 ± 0.011
00.0042 ± 0.010
0.0041 ± 0.011
0.0021 ± 0.0057

Mean ± SD *3

100.0
62.5
68.8
0
0

12.5

50

37.5
25.0
18.8
0
18.8
12.5
12.5

Percentage ofDetection (%) *4n = number of the market basket(s) performed in each year. *1 Minimum 137 Cs activity concentration in each year. *2 Maximum 137 Cs activity concentration in each year. *3 Mean andstandard deviation values of 137 Cs activity concentrations, which were calculated under the assumption that the concentrations of the non-detected were zero. *4 Detection rate of 137 Cs
for each food group. *5 This food group was categorized as “Seasonings and beverages” in 2006. *6 This food group was categorized as “Others” in 2006.

Rice and rice products
Cereals, nuts, and potatoes
Sugars and confectionaries
Fats and oils
Pulses and their products
FruitsGreen and yellow vegetables
Other vegetables,
mushrooms, and seaweeds

I
II
III
IV
V
VI
VII

Food Group

Activity Concentrations of 137 Cs (Bq/kg)

Table 1. Activity concentrations of 137 Cs in Japanese total diet study samples from 2006 to 2010.

IJERPH 2020, 17, 8131

IJERPH 2020, 17, 8131

Cesium-134 was not detected in any of the TDS samples between 2006 and 2010, but was observedin all food groups, with the exception of “fats and oils”, in 2011 as a consequence of the FDNPP accident.
Table 2 shows the 137 Cs and 134 Cs activity concentration of the TDS samples after the FDNPP accident.
The detection rates of 137 Cs and 134 Cs were 88% and 69%, respectively. No sample exceeded the 137 Cslevel of 0.1 Bq/kg during 2006 to 2010, whereas 19 samples exceeded this level in 2011. The activity
concentrations of 137 Cs (Bq/kg) were in the range of <0.041–6.400 in Sendai City, <0.089–4.100 in
Fukushima City, and <0.045–2.100 in Tokyo; while those of 134 Cs (Bq/kg) were <0.011–5.400 in Sendai
City, <0.040–3.500 in Fukushima City, and <0.025–1.700 in Tokyo. The activity concentration ratios of
134 Cs to 137 Cs in the TDS samples were ranged from 0.38 to 0.94, and the mean and standard deviation
values were calculated to be 0.73 and 0.14, respectively.
The highest activity concentration of radioactive Cs (137 Cs + 134 Cs) among the 42 TDS samples
was 12 Bq/kg, and found in the “milk and dairy products” group from Sendai City. This food groupalso showed the highest Cs activity concentration in Tokyo (3.8 Bq/kg), while fruits carried the highest
activity concentration in Fukushima City (7.6 Bq/kg). Cs activity concentrations in the fruits ofFukushima City were characteristically higher than those in Sendai City (0.093 Bq/kg) and Tokyo(0.17 Bq/kg). Although “green and yellow vegetables”, such as spinach, showed extremely highCs activity concentrations, with values exceeding 10,000 Bq/kg immediately following the FDNPP
accident, their levels declined rapidly [26–28]. Thus, Cs activity concentrations in “green and yellow
vegetables” were at most 0.58 Bq/kg in our TDS samples. The “meat and eggs” group was found tohave higher Cs activity concentration before the FDNPP accident, while the relatively low activity
concentration after the accident is due to the import of animal feed from foreign countries. Interestingly,
137 Cs and 134 Cs were not found in any “fats and oil” samples before or after the accident. This may be
due to their poor solubility in lipids.
After the FDNPP accident, regulation of the levels of radionuclides in food was establishedby the MHLW. On 17 March 2011, the provisional regulation value (RPV) for radioactive Cs wasestablished to be 200 Bq/kg for “drinking water” and “milk and dairy products”, and 500 Bq/kg forvegetables, grain, meat, eggs, and ﬁsh [28,29]. Presently, the standard limits, which were put into placeon 1 April 2012, are 100 Bq/kg for general foods, 50 Bq/kg for milk and infant foods, and 10 Bq/kg for
drinking water [30,31]. In the present study, although Cs activity concentrations of the TDS samples
increased signiﬁcantly after the FDNPP accident, the concentrations were well below the regulatorylevels. The highest radioactive Cs value of 12 Bq/kg in this TDS was 17 times lower than the RPV for“milk and dairy products”, and four times lower than the standard limit for milk.
3.1.3. 40 K Levels
Potassium is an essential element in food products and humans. Potassium-40, whose naturalabundance is 0.0117%, is the only naturally occurring radionuclide of potassium, and has a very long
half-life of 1.248 billion years. Accordingly, 40 K in foods contributes considerably to internal exposurein the general public. The activity concentration values of 40 K in the TDS samples are listed in Table 3.
In contrast to 137 Cs and 134 Cs, 40 K was detected in all food groups, and the levels were in the range of
10–100 Bq/kg in most of the TDS samples analyzed. The mean 40 K level values between 2006 and 2011
measured for individual food groups were the highest in “green and yellow vegetables”, at 90 Bq/kg,
followed by “pulses and their products” (84 Bq/kg), and “ﬁsh and shellﬁsh” (83 Bq/kg). In contrast,
mean 40 K values were relatively low in “fats and oils”, “drinking water”, “rice and rice products”,
and “beverages”. The 40 K activity concentration was not signiﬁcantly diﬀerent before and after the
FDNPP accident.

142

IX *1X
XI
XII
XIII *2
XIV

VIII

I
II
III
IV
V
VI
VII

0.015
0.300
0.063
2.000
0.052
0.017

0.710

0.017
2.200
0.074
6.400
<0.2300.0087

0.150
0.018
0.300
0.056
2.100
0.140
0.0048

0.044

0.079
0.058
0.053
<0.045
0.130
0.093
0.059

Tokyo

0.580
0.011
0.210
<0.0401.600<0.088
0.015

0.084

1.200
0.320
0.130
<0.100<0.0403.500
0.270

Fukushima<0.011
1.800
0.047
5.400
<0.1600.0071

0.210
0.140
0.054
<0.072<0.025<0.0360.160
0.230<0.0284.000
0.120
12.000<0.3900.016<0.028
0.012
0.210
0.021
1.70
<0.1100.0038

0.480
0.310
0.170
<0.160<0.066<0.093
0.360

Sendai

0.057
0.035<0.025<0.048
0.098
0.074
0.025

Tokyo

Sendai

1.500
0.340
0.180
<0.089
0.041
4.100
0.310

0.270
0.170
0.120
<0.087<0.0410.05700.200

Fukushima

Sendai

0.026
0.510
0.063
3.500
0.052
0.032

1.300

2.600
0.660
0.320
<0.190
0.041
7.600
0.580

Fukushima

0.030
0.510
0.077
3.800
0.140
0.0086

0.044

0.140
0.093
0.053
<0.093
0.230
0.170
0.084

Tokyo

Activity Concentrations of 137 Cs +134 Cs (Bq/kg)*1 This food group was categorized as “Seasonings and beverages” in 2006. *2 This food group was categorized as “Others” in 2006.

Rice and rice products
Cereals, nuts, and potatoes
Sugars and confectionaries
Fats and oils
Pulses and their products
FruitsGreen and yellow vegetables
Other vegetables, mushrooms, andseaweeds
Beverages
Fish and shellﬁshMeat and eggs
Milk and dairy products
Seasonings
Drinking water

Food Group

Activity Concentrations of 134 Cs(Bq/kg)

Activity Concentrations of 137 Cs(Bq/kg)Table 2. Activity concentrations of 137 Cs and 134 Cs in Japanese total diet study samples in 2011.

IJERPH 2020, 17, 8131

143

144

Rice and rice products
Cereals, nuts, and potatoes
Sugars and confectionaries
Fats and oils
Pulses and their products
FruitsGreen and yellow vegetables
Other vegetables, mushrooms,
and seaweeds
Beverages
Fish and shellﬁshMeat and eggs
Milk and dairy products
Seasonings
Drinking water
28.0
95.0
89.0
51.0
74.0
0.061

106.0

47.0

23.0
74.0
64.0
45.0
11.0
0.019

7.1
53.0
44.0
4.3
104.0
54.0
99.0

Max. *3

5.1
42.0
23.0
<1.2
94.0
41.0
76.0

Min. *2

7.9
81.0
68.0
41.0
66.0
0.015

93.0

5.7
44.0
54.0
<0.81
70.0
46.0
63.0

Min. *2

9.0
88.0
85.0
50.0
88.0
0.05

136.0

9.7
63.0
64.0
0.9
103.0
57.0
106.0

Max. *2

2007 (n = 3)

7.4
70.0
61.0
37.0
64.0
0.017

47.0

7.1
48.0
65.0
<0.90
72.0
48.0
85.0

11.0
87.0
80.0
43.0
71.0
0.087

105.0

7.9
55.0
71.0
1.6
98.0
55.0
104.0

3.2
75.0
60.0
44.0
28.0
0.021

39.0

5.7
50.0
51.0
<0.22
68.0
44.0
78.0

9.3
99.0
82.0
105.0
69.0
0.040

103.0

11.0
57.0
64.0
1.2
96.0
61.0
99.0

Max.
*3

Min.
*2

Min.
*2

Max.
*3

2009 (n = 4)2008 (n = 4)

8.1
77.0
77.0
43.0
79.0
0.039

55.0

3.5
48.0
67.0
<2.7
59.0
61.0
95.0

2010
(n = 1)
31.0
52.0
65.0
<1.2
78.0
50.0
95.0
48.0
8.6
96.0
73.0
48.0
76.0
0.012

81.0 ± 29
12.0 ± 8.2
82.0 ± 7.9
73.0 ± 9.8
49.0 ± 1564.0 ± 19
0.041 ± 0.020

Fukushima

7.8
79.0
74.0
46.0
82.0
0.018

58.0

8.3
62.0
67.0
<1.2
80.0
51.0
79.0

Sendai

6.3
96.0
47.0
51.0
81.0
0.053

59.0

5.4
54.0
49.0
<1.1
76.0
48.0
103.0

Tokyo

Activity Concentrations of 40 K
(Bq/kg) in 2011 *5

7.1 ± 1.7
51.0 ± 5.1
56.0 ± 14
1.0 ± 1.3 *6
85.0 ± 1552.0 ± 5.8
89.0 ± 11

Mean ± SD *4(Bq/kg)n = number of the market basket(s) performed in each year. *1 Before the Fukushima Daiichi nuclear power plant accident. *2 Minimum 40 K activity concentration in each year.
*3 Maximum 40 K activity concentration in each year. *4 Mean and standard deviation values of 40 K activity concentration before the Fukushima Daiichi nuclear power plant accident. *5
After the Fukushima Daiichi nuclear power plant accident. *6 Calculated under the assumption that the 40 K activity concentrations of the non-detected were zero. *7 This food group was
categorized as “Seasonings and beverages” in 2006. *8 This food group was categorized as “Others” in 2006.

IX *7
X
XI
XII
XIII *8
XIV

VIII

I
II
III
IV
V
VI
VII

Food Group

2006 (n = 4)

Activity Concentrations of 40 K (Bq/kg) *1

Table 3. Activity concentrations of 40 K in Japanese total diet study samples from 2006 to 2011.

IJERPH 2020, 17, 8131

IJERPH 2020, 17, 8131

3.2. Dietary Intake and CED Values of Radioactive Cs
3.2.1. Before the FDNPP Accident
Table 4 presents the total daily dietary intake values and CEDs of radioactive Cs and 40 K for
adults in each MB. Between 2006 and 2010, the lower and upper limits of radioactive Cs intake varied
from 0.0047 to 0.0320 Bq/person/day and from 0.060 to 0.122 Bq/person/day, respectively. The meanvalues obtained for the lower and upper limits during the same period were 0.020 Bq/person/day(SD = 0.0082) and 0.085 Bq/person/day (SD = 0.019), respectively. Similar results were obtained in aprevious study [13]. The lower and upper limits in each MB were signiﬁcantly diﬀerent because of the
low detection rates of 137 Cs and 134 Cs before the FDNPP accident (30% and 0%, respectively).
Table 4. Total daily dietary intake values and committed eﬀective doses of radioactive Cs (137 Cs + 134 Cs)
for adults in Japan, estimated via total diet studies from 2006 to 2011.
RegionDaily Intake(Bq/Person·Day)

City

Year

Before the
FDNPP *3
accident

Lower
Limit *1

Upper
Limit *2

Lower
Limit *1

Upper
Limit *2

2006

Kanto I
Kanto II
Hokuriku
Kinki IITokyo
NaganoKanazawa
Nara

0.03200.02700.01900.0210

0.079
0.081
0.061
0.065

0.150
0.150
0.130
0.089

0.40
0.40
0.45
0.34

2007

Kanto I
Hokuriku
Shikoku

Yokohama
Niigata
Kochi

0.02800.01600.0100

0.120
0.064
0.100

0.099
0.130
0.074

0.37
0.69
0.37

2008

Hokkaido
TohokuKinki I
Kita-Kyushu

SapporoSendaiOsaka
Fukuoka

0.02200.00470.03100.0079

0.087
0.097
0.060
0.086

0.049
0.100
0.022
0.140

0.58
0.58
0.55
0.33

2009

Kanto I
Hokuriku
Chugoku
ShikokuTokyo
Kanazawa
Hiroshima
Kochi

0.02900.02300.01400.0160

0.071
0.100
0.098
0.072

0.037
0.140
0.110
0.064

0.51
0.40
0.63
0.55

2010

Tokai

NagoyaMean ± SD *4
After the
FDNPP *3
accident

Committed Eﬀective
Dose (μSv)

2011

TohokuTohokuKanto I

Sendai
FukushimaTokyo

0.0220

0.120

0.077

0.41

0.0200 ±0.00830.085 ±
0.019

0.098 ±
0.041

0.47 ±
0.11

2.20
2.90
0.67

2.20
2.90
0.69

12.0
17.0
3.8

13.0
17.0
3.9

*1 Assuming that the activity concentrations of the non-detected radionuclides were zero. *2 Assuming that theactivity concentrations of non-detected radionuclides were equal to the limits of detection. *3 FDNPP: Fukushima
Daiichi nuclear power plant. *4 Mean and standard deviation values before the Fukushima Daiichi nuclear power
plant accident.

As previously described, the NRA conducted DPS studies of radionuclides until 2008, and compiled
the results from 47 prefectures in Japan into a database [32]. According to the database, the daily intake
of 137 Cs for adults between 2003 and 2008 ranged from below the detection limit to 0.56 Bq/person/day,and the mean was calculated to be 0.018 Bq/person/day (SD = 0.031), assuming that the activity
concentration value of ND radionuclides was zero. Although a larger variation was observed,
this ﬁnding is similar to the mean lower limit of radioactive Cs intake obtained in the present study.
The lower and upper limits of the CEDs of radioactive Cs were in the range of 0.022–0.150 μSv
and 0.33–0.69 μSv, with mean values of 0.098 μSv (SD = 0.041) and 0.47 μSv (SD = 0.11), respectively.
The current standard limits for radionuclides in food in Japan were established on the basis of anannual CED of 1 mSv, representing the maximum permissible dose due to food consumption [27,31].
145

IJERPH 2020, 17, 8131

Although the upper limit of the CEDs obtained were overestimated, due to the low detection rate of
137 Cs and 134 Cs, the highest CED of 0.69 μSv is approximately 1400 times lower than the maximum
permissible dose, and thus would seem to pose no health risk.
3.2.2. After the FDNPP Accident
Since 137 Cs and 134 Cs were detected in most of the food groups after the FDNPP accident, the lower
and upper limits of radioactive Cs intakes were calculated using actual activity concentrations ofthese radionuclides, rather than zero or LODs. Thus, the lower and upper limits were almost thesame in each MB after the FDNPP accident, while they were signiﬁcantly diﬀerent before the accident.
The lower limits of total radioactive Cs intake were estimated to be 2.9 Bq/person/day in Fukushima
City, 2.2 Bq/person/day in Sendai City, and 0.67 Bq/person/day in Tokyo, after the FDNPP accident(Table 4).
The lower limits of the total CED of radioactive Cs in 2011 were 12 μSv in Sendai City, 17 μSv
in Fukushima City, and 3.8 μSv in Tokyo. The high value obtained for Fukushima City is expected,
as it is located the closest to the FDNPP incident. Figure 2 displays the lower limits of CED values ofradioactive Cs from 2003 to 2011, and shows that values obtained after the FDNPP accident were about
two orders of magnitude higher than before the accident. Nevertheless, the highest CED of radioactive
Cs (17 μSv), which was the exposure level in half a year after the FDNPP accident, is approximately
60 times lower than the maximum permissible dose.

Figure 2. Committed eﬀective doses of radioactive Cs (137 Cs + 134 Cs) obtained from each market basket(2003–2011). The closed circles show the results of each market basket. The doses were estimated withthe assumptions of one-year intake values of the total diet samples, and the activity concentration
values of non-detected radionuclides to be zero.

Figure 3 summarizes the CED values of radioactive Cs, organized by food group, in 2011. The threefood groups with the highest contributions to the CEDs were “milk and dairy products” (66%), “ﬁsh andshellﬁsh” (17%), and “rice and rice products” (8.2%) in Sendai City; “rice and rice products” (33%),
fruits (32%), and “milk and dairy products” (15%) in Fukushima City; and “milk and dairy products”(69%), “rice and rice products” (7.6%), and “ﬁsh and shellﬁsh” (7.0%) in Tokyo.

146

IJERPH 2020, 17, 8131

Figure 3. Committed eﬀective doses of radioactive cesium (137 Cs + 134 Cs) by food groups in 2011.
Distance from the Fukushima Daiichi nuclear power plant to each city is denoted in parentheses.
This ﬁgure was modiﬁed from [19].

In 2011, TDSs of radioactive Cs and 40 K were also carried out by Tsutsumi et al. [33] andMiyazaki et al. [34]. Tsutsumi et al. analyzed MBs from Sendai City, Fukushima City, and Tokyo in
September and November 2011, and revealed that the lower limits of total CED values of radioactive
Cs were 17 μSv in Sendai City, 19 μSv in Fukushima City, and 2.1 μSv in Tokyo. They also found that“ﬁsh and shellﬁsh”, “fruits”, “green and yellow vegetables”, and “milk and dairy products” were themain contributors to the CED values obtained. Although the contributing food groups varied to someextent, their ﬁndings are similar to the total CED values of radioactive Cs obtained in the present study.
Miyazaki et al. collected an MB from Nagoya City in August 2011, and measured CED values forradioactive Cs of 1.5 μSv, which was lower than that obtained in both our study and that of Tsutsumi
et al. This might be because of the distance between the FDNPP accident site and Nagoya City, which at
446 km, is much larger than that to Sendai City (95 km), Fukushima City (62 km), or Tokyo (227 km).
After 2011, the TDSs have been performed by other institutions in Japan. The National Institute of
Health Sciences have been conducting the TDS, which was targeting 15 areas, including Fukushima
Prefecture, Miyagi Prefecture, and Tokyo, twice a year since 2011. Uekusa et al. [35] revealed that the
maximum CEDs due to radioactive Cs decreased to 9.4 μSv (March 2012), 3.8 μSv (September 2012),
and 7.1 μSv (March 2013) from 19 μSv in 2011 [33]. In the past two years, the results were as follows:
1.1 μSv (February–March 2018) [36], 1.1 μSv (September–October 2018) [37], 1.0 μSv (February–March2019) [38], and 1.0 μSv (September–October 2019) [39]. The Tokyo Metropolitan Institute of Public
Health also have been carrying out the TDS in Tokyo once a year. Their results between 2012 and2019 showed that the CEDs due to radioactive Cs in Tokyo ranged from 0.20 μSv (2017) to 1.3 μSv(2012) [40]. All the results mentioned above indicated that the CEDs due to radioactive Cs clearlydecreased from those in 2011, as expected. In 2019, the maximum CED of 1.0 μSv was 17 times lower
than that from the present study, and was one-thousandth of the maximum permissible level. However,
the maximum CED between 2012 and 2019 was still higher than the maximum upper limit of the CED,
due to radioactive Cs before the FDNPP accident (0.69 μSv).
3.3. Dietary Intake and CED Values of 40 K
The minimum and maximum total dietary intake values of 40 K between 2006 and 2011 were
65 Bq/person/day and 94 Bq/person/day, respectively (Table 5), and the mean was calculated to be
79 Bq/person/day (SD = 7.0). Since 40 K was found in almost all TDS samples, the upper limit was inaccordance with the lower limit in each MB. The intake values of 40 K showed smaller variation thanthose obtained for Cs, and no signiﬁcant diﬀerence was observed before or after the FDNPP accident.

147

IJERPH 2020, 17, 8131

Table 5. Total daily dietary intake values and committed eﬀective doses of 40 K for adults in Japan,
estimated via total diet studies from 2006 to 2011.
Year

Before the
FDNPP *1
accident

RegionCity

2006

Kanto I
Kanto II
Hokuriku
Kinki IITokyo
NaganoKanazawa
Nara

76
78
77
65

170
180
180
150

2007

Kanto I
Hokuriku
Shikoku

Yokohama
Niigata
Kochi

91
94
79

210
210
180

2008

Hokkaido
TohokuKinki I
Kita-Kyushu

SapporoSendaiOsaka
Fukuoka

81
78
80
69

180
180
180
160

2009

Kanto I
Hokuriku
Chugoku
ShikokuTokyo
Kanazawa
Hiroshima
Kochi

76
72
85
79

170
160
190
180

2010

Tokai

NagoyaMean ± SD *2
After the
FDNPP *1
accident

Daily Intake
Committed(Bq/Person·Day) Eﬀective Dose (μSv)

2011

TohokuTohokuKanto I

Sendai
Fukushima
Tokyo

75

170

78.0 ± 7.3

178 ± 16

88
81
78

200
180
180

*1 FDNPP: Fukushima Daiichi nuclear power plant. *2 Mean and standard deviation value before the Fukushima
Daiichi nuclear power plant accident.

The present study was based on food consumption data derived from the NHNS between
2002 and 2004, as previously described. According to the NHNS, the daily K intake for adults was
2.452 g/person/day in 2002 [41], 2.426 g/person/day in 2003 [42], and 2.372 g/person/day in 2004 [43].
Since 1 g of K corresponds to 30.3 Bq of 40 K, the intake of this radionuclide can be estimated to be
74 Bq/person/day in 2002, 74 Bq/person/day in 2003, and 72 Bq/person/day in 2004; this is in close
agreement with the mean 40 K intake value obtained in the present study. On the other hand, 40 K intake
between 2003 and 2008 varied from 5 to 150 Bq/person/day, according to a DPS conducted by the
NRA [32]. The mean 40 K intake was calculated to be 57 Bq/person/day (SD = 16), and was clearly
diﬀerent from our ﬁnding. The DPS was performed on ﬁve consecutive days from June to January,
whereas the NHNS was conducted for only a single day in November, to ensure the participationof a suﬃcient number of households. Thus, it should be noted that seasonal changes in food item
availability and individual daily variations in food intake cannot be assessed using the NHNS and thisTDS [7,44].
The minimum, maximum, and mean total CED values of natural occurring radionuclide 40 K
between 2006 and 2011 were 150 μSv, 210 μSv, and 180 μSv (SD = 16), respectively, which are inclose agreement with a previous TDS [13]. The mean value obtained was approximately ten times
higher than the maximum CED obtained for artiﬁcial radioactive Cs in the present study, and wascomparable to the worldwide average of 170 μSv [45]. Figure 4 shows the percent contributions of
the contributing food groups to the CED values of 40 K in 2011. The food group “other vegetables,
mushrooms, and seaweeds” had the greatest contribution to the CED values in Sendai City (31%),
Fukushima City (26%), and Tokyo (32%). These results were similar to those of Tsutsumi et al. [33] andMiyazaki et al. [34].

148

IJERPH 2020, 17, 8131

Figure 4. Percentage contributions of food groups to the committed eﬀective doses of 40 K in 2011.
Distance from the Fukushima Daiichi nuclear power plant to each city is denoted in parentheses.
This ﬁgure was modiﬁed from [19].

3.4. TDS of Radionuclides Conducted by Other Countries
The second International Workshop on Total Diet Studies compiled a list of core (screening),
intermediate, and comprehensive (reﬁned assessment) priority chemicals that should be considered
for inclusion in a TDS [46]. Radionuclides are categorized into the intermediate list, and there are three
countries that routinely conduct TDSs, including Japan [2].
The United States has been performing TDSs continuously since 1961, as mentioned previously.
The FDA routinely analyzes the following radionuclides in their TDS analysis: 137 Cs, 90 Sr, 106 Ru, 131 I,
and 40 K. According to the FDA’s report [47], the following three of 2984 samples were above thereporting limit of 5 Bq/kg for 137 Cs between 2006 and 2014: “baby foods, squash” in 2007 (93.3 Bq/kg),“raisin bran cereal” in 2009 (10.8 Bq/kg), and “salad dressing, creamy/buttermilk type, low calorie” in2014 (40.5 Bq/kg).
Canada also continuously carries out TDSs of radionuclides. Health Canada has been monitoring
natural (40 K and 210 Pb) and artiﬁcial (137 Cs, 134 Cs, 131 I, 241 Am, 57 Co, and 60 Co) radionuclides in foods
since 2000. Their results between 2015 and 2017 showed that all 480 samples tested contained 137 Cs
and 134 Cs levels below the minimum detection limit, showing a value of approximately 1.3 Bq/kg [48].
The result obtained from the American study was comparable to our ﬁnding, in that only
one of the 266 TDS samples exceeded 137 Cs levels of 5 Bq/kg. Similarly, the Canadian study wasconsistent with respect to 137 Cs levels, speciﬁcally for those observed before the FDNPP accident in
the present study. However, such a comparison should be interpreted with caution, since the numberof composite samples analyzed in each MB diﬀered between the three countries (approximately 280
for the United States, approximately 160 for Canada, and 14 for the present study) [5,49]. In thepresent study, individual food items with high levels of 137 Cs may be underrepresented, due to thegrouping of a greater number of food items within each category, which could have lower levels of theradionuclide [1,50]. This dilution eﬀect might have caused the 137 Cs levels after the FDNPP accident in
the present study to be lower than those of “baby foods, squash”, etc., as mentioned above. Meanwhile,the detection rate of 137 Cs in the present study was much higher than that in the United States andCanada, owing to the lower LOD values of 137 Cs. The present study evaluated the exposure level to
137 Cs as previously described, whereas the United States and Canada did not, because 137 Cs was notdetected in nearly any samples.
China [51] and Lebanon [52] also conducted TDSs of radionuclides in 1990 and 2004, respectively.
For each MB, both countries collected 12 composite samples, similar to the approach used in the present
study. Cs-137 activity concentration in their TDS was found to be below 0.1 Bq/kg for most of the food149

IJERPH 2020, 17, 8131

groups, with the exception of potatoes, which had a value of 10.21 Bq/kg in China; that is consistent
with our ﬁndings prior to the FDNPP accident.
4. Conclusions
The present study provides an estimate of the average dietary exposure of 137 Cs, 134 Cs, and 40 K for
adults in Japan. Before the FDNPP accident, activity concentrations of 137 Cs were in the range of thosereported in other countries, and dietary intake values and CEDs were consistent with our previous TDS.
Similarly, after the FDNPP accident, the activity concentration and exposure levels of radioactive Cs
were well below the regulatory levels, despite an increase in two orders of magnitude being measured.
The exposure levels of 40 K did not diﬀer before and after the FDNPP accident. The mean CED of
40 K was comparable to the international average, and was 10 times higher than the highest CED ofradioactive Cs obtained in the present study.
On an international level, TDSs of radionuclides are scarce, and currently, only Japan evaluates
trends in exposure levels to these contaminants. Thus, our ﬁndings provide invaluable information
with regard to the radiological safety of foods. However, the present study has some limitations. First,
the exposure levels immediately after the FDNPP accident could not be estimated, because the TDS in2011 was performed approximately six months after the accident. Second, seasonal variation cannot be
assessed, as the NHNS and this TDS were performed in only one season each year. Finally, the present
study did not examine the exposure of children, or exposure to other radionuclides, such as 90 Sr, Pu,
and 106 Ru, which are targets of standard limit regulations in foods. Therefore, further studies are
required to determine the dietary exposure levels of these radionuclides for both adults and children.
Author Contributions: Conceptualization, H.T., I.I., S.M., K.I. and H.S.; methodology, H.T., I.I., S.M., K.I. and
H.S.; formal analysis, H.T. and H.S.; investigation, H.T., I.I., S.M., K.I. and H.S.; resources, I.I., S.M., K.I. and H.S.;
data curation, H.T. and H.S.; writing—original draft preparation, H.T.; writing—review and editing, H.T., H.S.;
visualization, H.T.; supervision, H.S.; project administration, H.S.; funding acquisition, H.S. All authors have readand agreed to the published version of the manuscript.
Funding: This research was funded by the MHLW HLSRG (Research on Food Safety) (grant nos.
H16-Shokuhin-Ippan-015, H19-Shokuhin-Ippan-003, and H22-Shokuhin-Ippan-017).
Acknowledgments:
sample preparation.

The authors would like to thank Michiko Koyano for her technical support inConﬂicts of Interest: The authors declare no conﬂict of interest.

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153

International Journal ofEnvironmental Researchand Public Health
ArticlePassive-Type Radon Monitor Constructed Using a
Small Container for Personal Dosimetry
Yuki Tamakuma 1,2 , Chutima Kranrod 1 , Takahito Suzuki 2,† , Yuki Watanabe 3,‡ ,Thamaborn Ploykrathok 1,§ , Ryoju Negami 2 , Eka Djatnika Nugraha 2 , Kazuki Iwaoka 4 ,Mirosław Janik 4 , Masahiro Hosoda 1,2 and Shinji Tokonami 1, *
1

2

3
4

*
†
‡
§

Institute of Radiation Emergency Medicine, Hirosaki University, 66-1 Honcho, Hirosaki,
Aomori 036-8564, Japan; tamakuma@hirosaki-u.ac.jp (Y.T.); kranrodc@hirosaki-u.ac.jp (C.K.);
thamaborn.p@outlook.com (T.P.); m_hosoda@hirosaki-u.ac.jp (M.H.)
Graduate School of Health Sciences, Hirosaki University, 66-1 Honcho, Hirosaki, Aomori 036-8564, Japan;
suzuki-takahito@fujielectric.com (T.S.); h20gg204@hirosaki-u.ac.jp (R.N.);
h20gg701@hirosaki-u.ac.jp (E.D.N.)
School of Health Sciences, Hirosaki University, 66-1 Honcho, Hirosaki, Aomori 036-8564, Japan;
watanabe.yuki@jaea.go.jp
National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage,
Chiba 263-0024, Japan; iwaoka.kazuki@qst.go.jp (K.I.); janik.miroslaw@qst.go.jp (M.J.)
Correspondence: tokonami@hirosaki-u.ac.jp; Tel.: +81-172-39-5404
Present address: Fuji Electric Co., Ltd., 1 Fujimachi, Hino, Tokyo 191-8502, Japan.
Present address: Radiation Protection Department, Nuclear Fuel Cycle Engineering Laboratories,
Japan Atomic Energy Agency, 4-33 Muramatsu, Tokai, Ibaraki 319-1194, Japan.
Present address: Department of Nuclear Engineering, Faculty of Engineering, Chulalongkorn University,
Bangkok 10330, Thailand.

Received: 14 July 2020; Accepted: 2 August 2020; Published: 5 August 2020

Abstract: The International Commission on Radiological Protection (ICRP) recently recommended
a new dose conversion factor for radon based on the latest epidemiological studies and dosimetricmodel. It is important to evaluate an inhalation dose from radon and its progeny. In the present study,a passive radon personal monitor was designed using a small container for storing contact lenses
and its performance was evaluated. The conversion factor for radon (222 Rn), the eﬀect of thoron(220 Rn) concentration and the air exchange rate were evaluated using the calibration chamber at
Hirosaki University. The minimum and maximum detectable radon concentrations were calculated.
The conversion factor was evaluated as 2.0 ± 0.3 tracks cm−2 per kBq h m−3 ; statistical analysesof results showed no signiﬁcant eﬀect from thoron concentration. The minimum and maximum
detectable radon concentrations were 92 Bq m−3 and 231 kBq m−3 for a measurement period of threemonths, respectively. The air exchange rate was estimated to be 0.26 ± 0.16 h−1 , whose eﬀect on themeasured time-integrated radon concentration was small. These results indicate that the monitor
could be used as a wearable monitor for radon measurements, especially in places where radon
concentrations may be relatively high, such as mines and caves.
Keywords: passive radon monitor; development; sensitivity; detection limit; air-exchange rate

1. Introduction
Radon is one of the naturally occurring radionuclides, which is well known as the second leadingrisk factor for lung cancer after tobacco smoking [1]. According to the United Nations Scientiﬁc
Committee on the Eﬀects of Atomic Radiation (UNSCEAR) 2008 report on the sources and eﬀects ofionizing radiation [2], the world mean value of annual eﬀective dose by natural radiation sources
is 2.4 mSv, and half of this dose is attributed to radon (222 Rn), thoron (220 Rn), and their progenies.
IJERPH 2020, 17, 5660; doi:10.3390/ijerph17165660

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IJERPH 2020, 17, 5660

Radon and thoron, which are radioactive noble gases, are normally generated by radioactive decay
from radium (226 Ra and 224 Ra) in soil, rocks, and building materials. Indoor radon concentrations tend
to be higher than outdoor concentrations due to the ventilation rate. Many indoor radon concentration
surveys have been carried out in various countries [3–7]. The world mean indoor radon concentration
was reported to be 40 Bq m−3 [8]. However, radon concentrations in mines and caves are higher
than indoor concentrations because radon generated from surrounding rocks and soil can be easily
accumulated due to the low ventilation. Recently, it has been reported that mean radon concentrationsat several mines and caves were over ~1000 Bq m−3 [9–12].
In 2017, the International Commission on Radiological Protection (ICRP) recommended a newdose conversion factor of 3 mSv per mJ h m−3 for radon in buildings and underground mines basedon current epidemiological studies and dosimetric model [13,14]. This value corresponds to 17 nSv
per Bq h m−3 , which is almost twice the dose conversion factor of 9 nSv per Bq h m−3 given by the
UNSCEAR 2006 report on the sources and eﬀects of ionizing radiation [15]. Many countries willapprove the new dose conversion factor of ICRP for the occupational environment under the existing
situation [16]. Therefore, it is important to evaluate an inhalation dose from radon and its progeny,
especially for workers in mines and caves.
Generally, radon concentration is measured using passive-type monitors recording long-term
measurements [17]. However, passive-type monitors have an upper limit of detection. The overlapsof tracks made by alpha particles in the measurement at a high radon concentration area lead to theunderestimation of radon concentration. Thus, the sensitivity to radon should be lower than that ofprevious monitors to measure radon concentrations in the prone area. These monitors are large andinconvenient to carry and they are not designed to be carried by workers. Therefore, a passive radon
monitor with low sensitivity to radon for measurement in radon-prone areas that is small enough to be
carried during the work period is needed for evaluation of inhalation dose. In the present study, sucha passive radon personal monitor was designed and its performance was evaluated.
2. Materials and Methods
2.1. Overview of the Passive Radon Rersonal Monitor
A passive radon personal monitor is shown in Figure 1a. A small container for storing contactlenses was adapted because it is cheap, and easy to obtain and handle. Each container volume was~3.2 cm3 . A solid-state track detector (CR-39; BARYOTRAK, Nagase Landauer, Ltd., Tsukuba, Japan),
1.0 × 1.0 cm, was used as the detecting material and one piece of CR-39 was held in place at the topof each container with sticky clay (Figure 1b). Electroconductive materials have been used for thecontainer of previous passive radon monitors to avoid electrostatic phenomena, which may cause a
non-uniform deposition of radon progeny [18,19]. Thus, an electroconductive coating material (D-362,
Fujikura Kasei Co., Ltd., Tokyo, Japan) was used on the container’s inner wall. Each container was
closed by an attached lid; this makes an invisible air gap that prevents thoron from passing into themonitor. The radon concentration (XRn ) was calculated using the following Equation (1):XRn =N − N0
CFRn ·T(1)

where XRn is the mean concentration of radon during the exposure period in kBq m−3 ; N and N0(tracks cm−2 ) are the track density in the measurement and the background, respectively; CFRn (tracks
cm−2 per kBq h m−3 ) is the conversion factor to radon concentration, which is obtained by a calibration
experiment; and T is the exposure time in hours.

156

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(b)

(a)

Figure 1. External view of the passive radon personal monitor constructed using a small container forstoring contact lenses (a) and a schematic representation of the monitor (b).

2.2. Conversion Factor to Radon Concentration
To obtain the conversion factor (CF) to radon concentration, this monitor was placed in the radon
calibration chamber [20] at the Institute of Radiation Emergency Medicine (IREM) at Hirosaki University.
The radon concentrations in the chamber were continuously monitored by a scintillation cell (300A,
Pylon Electronics Inc., Ottawa, ON, Canada) with a portable radon monitor (AB-5, Pylon Electronics Inc.,
Ottawa, ON, Canada). Three diﬀerent exposure tests were carried out. Five monitors, totaling 10 CR-39
pieces, were exposed for each exposure condition. After exposure tests, CR-39 pieces were takenfrom the containers and were chemically etched with a 6.0 M NaOH solution at 60 ◦ C for 24 h.
The alpha tracks were counted using ImageJ software (National Institutes of Health, Bethesda, MD,USA) with photos of etched CR-39 pieces. Ten reading areas of 0.01 cm2 , which corresponds to 0.1 cm2 ,were randomly selected to count the number of the tracks. The CFs for each CR-39 were calculatedusing Equation (1), and then the arithmetic mean of the CF value was evaluated.
2.3. Eﬀect of Thoron Interference
To evaluate the eﬀect of thoron concentration, this monitor was placed in the thoron chamber at
IREM. Thoron concentrations were continuously monitored with an electrostatic collection radon-thoron
monitor (RAD7, Durridge. Co. Inc., Billerica, MA, USA). A grab sampling technique using a scintillation
cell with a portable radiation monitor was used for the correction of values measured by the RAD7 [21].
Temperature and relative humidity in the thoron chamber were simultaneously monitored with anenvironmental monitor (TR-73U, T&D Co., Matsumoto, Japan). After exposure, the alpha tracks werecounted in the same way as for radon exposure. The tracks of the exposed group and background werecompared using two-sided Student’s t-tests. The diﬀerence was considered signiﬁcant for p < 0.05.
Excel 2016 software (Microsoft, Washington WA, USA) and R version 3.5.2 were used to perform thestatistical analyses.
2.4. Minimum and Maximum Detectable Radon Concentrations
The minimum detectable radon concentration was evaluated using the method of the International
Organization for Standardization (ISO 11929) [22]. The following equation was used for the calculationof the minimum detectable radon concentration:
√
k 2n0
(2)
y∗ =
S·CF·T
2

y# =



k
2y∗ + S·CF·T

1 − k2 u2rel (S) + u2rel (CF)

157



(3)

IJERPH 2020, 17, 5660

where y∗ and y# are the decision threshold and the minimum detectable radon concentration (kBq m−3 ),respectively; k is the quantile of the standardized normal distribution for probabilities of 0.95
(i.e., k = 1.65); n0 is the number of background tracks (tracks); S is the total reading area (cm2 ); CF is theconversion factor for radon concentration (tracks cm−2 per kBq h m−3 ); T is the exposure time (h); andurel (x) is the standard relative uncertainty for the parameter x. The standard relative uncertainty forthe total reading area urel (S) was assumed to be zero.
In addition, the maximum detectable radon concentration can be calculated using Equation (1)and the maximum track density estimated by an average track diameter measured using an optical
microscopy (Model LVS, Kenis Ltd., Japan). The maximum alpha track density Nmax (tracks cm−2 ) can
be calculated by:1(4)
Nmax = 2dt
where dt is the average alpha track diameter (cm). Then, the maximum detectable concentration
XRn, max in kBq m−3 is expressed as:
XRn, max =Nmax − N0.
CFRn ·T(5)

2.5. Air Exchange Rate
The air exchange rate was evaluated using an exposure–degassing–enclosure method reported by
Omori et al. [23]. The 20 monitors with CR-39s were exposed in the radon chamber at IREM, where theradon concentration was stabilized. The radon concentrations were monitored every hour by thepulse-type ionizing chamber (AlphaGUARD, PQ2000PRO, Genitron Instruments GmbH, Frankfurt,
Germany), which was calibrated by Physilalish Technische Bundesanstalt (Braunschweig, Germany).
After the 48 h exposure, the monitors were taken out of the radon chamber and degassed by leaving
them in an experimental room where the radon concentration was low. The degassing time was set tobe 0, 1, 2, 3, 4, 6, 8, 10, 12 and 16 h, and the radon gas in the monitor rapidly goes out through theinvisible air gap to the experimental room in this period. The monitors were enclosed in a radon-proof
bag made from polyethylene for 288 h when each degassing time passed. Table 1 shows the averageradon concentration, the environmental parameters in the radon chamber, and the experimental room
during the experiment. The average radon concentration observed in the environmental room wasquite low compared to that measured in the radon chamber, which indicated the existence of radon in
the experimental room during the degassing time would be negligible. After the enclosure, the CR-39s
were etched in the same way. For the analysis, 40 reading areas in each CR-39 were taken to avoid
increasing the deviation of the track density in this study because the expected diﬀerence in the track
density for each degassing condition was small.
Table 1. Radon concentration and environmental parameters in the radon chamber and an experimentalroom.
Parameter
Radon concentration (Bq m−3 )Temperature (◦ C)
Relative humidity (%)
Air pressure (hPa)Radon Chamber

Experimental Room

AverageStandard Deviation

AverageStandard Deviation

13,300
27.7
50.1
1002

1603
0.4
2.5
2

7.7
26.3
34.7
1003

3.0
1.5
6.1
7

158

IJERPH 2020, 17, 5660

3. Results
3.1. Conversion Factor to Radon Concentration
Three diﬀerent exposures were controlled as 132 ± 1, 309 ± 3, and 564 ± 5 kBq h m−3 . Using these
data, Figure 2 shows the relationship between the time-integrated radon concentration and the alphatrack density. The CF to radon concentration was found to be 2.0 ± 0.3 tracks cm−2 per kBq h m−3 .

㼀㼞㼍 㼏㼗㻌㼐 㼑㼚 㼟㼕㼠㼥㻌㻔 㼠㼞㼍 㼏㼗㼟㻌㼏㼙 㻙㻞 㻕

㻝㻡

㻝㻜

㻡

㻜
㻜

㻝㻜㻜

㻞 㻜㻜

㻟 㻜㻜

㻠㻜㻜

㻡 㻜㻜

㻢㻜㻜

㼀㼕㼙 㼑㻙㼕㼚 㼠㼑㼓 㼞㼍 㼠㼑㼐 㻌㼞㼍 㼐㼛㼚 㻌㼏㼛㼚 㼏㼑㼚㼠㼞㼍 㼠㼕㼛㼚 㻌㻔 㼗㻮㼝 㻌㼔 㻌㼙 㻙㻟 㻕

Figure 2. The relationship between the time-integrated radon concentration and alpha track density.
Ten CR-39 pieces were exposed for each condition.

3.2. Eﬀect of Thoron Interference
The mean thoron concentration, temperature, and relative humidity were 6785 ± 2122 Bq m−3 ,25.5 ± 0.2 ◦ C, and 9 ± 4%, respectively. Time-integrated thoron concentration was controlled as 329 ± 6
kBq h m−3 . As shown in Figure 3, the track densities for background and exposed CR-39 were 43 ± 17
and 47 ± 27 tracks cm−2 , respectively. As a result of the statistical analysis, no signiﬁcant diﬀerence inthe track density was observed between the background and exposed group (p = 0.76).








%DFNJURXQG

7KRURQ H[SRVHGJURXS❟❟

7UDFNGHQVLW\ WUDFNVFP Figure 3. Track densities for the background and thoron-exposed group in unit of tracks cm−2 .
Bottom and top whiskers are the 25th and 75th percentiles, respectively. The lines across the boxes andthe cross marks represent the median and the arithmetic mean value, respectively.
159

IJERPH 2020, 17, 5660

3.3. Minimum and Maximum Detectable Radon Concentrations
Parameters used for the calculation of the minimum detectable radon concentration aresummarized in Table 2. Notably, the working time of 8 h per day was considered for the calculation;
thus, the measurement times were set to be 720 and 1440 h for three and six months, respectively.
The minimum detectable concentrations with a measurement interval of three and six months were
evaluated as 92 and 46 Bq m−3 , respectively.
Table 2. Parameters used for the calculation of the minimum detectable radon concentration.
Item

SymbolValue

Remarks

Quantiles of the standardized
normal distribution

k

1.65

For probabilities of 0.95

Number of background trackn0

4.3 tracks

Derived from the backgroundtrack density of 43 tracks cm−2

Total reading areaS

0.1 cm2

Ten reading areas of 0.01 cm2

2.0 tracks cm−2 perConversion factor for radon
concentration

CF

Measurement time

T

720 h
1440 hRelative standard uncertainty
for the total reading area

urel (S)0Relative standard uncertainty
For the conversion factor

urel (CF)0.15

kBq h m−3

3 months
6 months

The average alpha track diameter was estimated as 10 μm. Thus, the maximum detectable radon
concentrations with three- and six-month measurements were evaluated as 231 and 116 kBq m−3 , respectively.
3.4. Air Exchange Rate
Figure 4 illustrates the alpha track density with a standard deviation against the degassing time.
The track density slowly decreased with a degassing time of 0–8 h. Theoretically, the decreasing trend
can be ﬁtted by a single exponential function. As a result, the air exchange rate was estimated to be
0.26 ± 0.16 h−1 . The result indicates that the air in the monitor is almost exchanged after 8 h from theend of exposure.
㻞㻜㻜㻜

㻙㻞

㼀㼞㼍 㼏㼗㻌㼐 㼑㼚 㼟㼕㼠㼥㻌㻔 㼠㼞㼍 㼏㼗㼟㻌㼏㼙 㻕㼀㼞㼍 㼏㼗㻌㼐 㼑㼟㼚 㼕㼠㼥㻺 㻌㻩 㻌㻔 㻠 㻠 㻟 㻌㼼㻌㻝 㻜 㻟 㻕 㻌㽢㻌㼑㼤㼜 㻔 㻙㻔 㻜 㻚 㻞 㻢 㻌㼼㻌㻜 㻚 㻝 㻢 㻕 㽢㼠 㻕㻌㻌㻌㻌㻌㻌㻌㻌㻌㻗 㻌㻔 㻤 㻤 㻤 㻌㼼㻌㻤 㻠 㻕㻝㻡㻜㻜㻾 㻞 㻌㻩 㻌㻜 㻚 㻣 㻟

㻝㻜㻜㻜

㻡㻜㻜

㻜
㻜

㻡

㻝㻜

㻝㻡

㻰 㼑㼓 㼍 㼟㼟㼕㼚 㼓 㻌㼠㼕㼙 㼑㻌㻔 㼔 㻕Figure 4. The alpha track density against the degassing time.
160

㻞㻜IJERPH 2020, 17, 5660

4. Discussion
4.1. Conversion Factor to Radon Concentration
The CFs of various passive integrated radon monitors are summarized in Table 3. Many kinds ofpassive integrated radon monitors have been developed by diﬀerent groups, and the CFs are diﬀerent
for each one [18,24–27]. The CF for the present monitor was almost same or lower compared with thefactors for other monitors. This might be due to the diﬀerence in the type of solid-state nuclear track
detector (SSNTD) used in the monitors. The CFs shown in previous papers might have been evaluatedusing a diﬀerent type of SSNTD that has a lower sensitivity than the CR-39 used in the present study.
Thus, the CF for RADUET, widely used for a large-scale radon survey, was also evaluated by the same
method using two types of CR-39s at the same time to check the diﬀerence in sensitivity attributed to
the SSNTD. One was provided by Nagase Landauer Ltd., which was used in the present study, and theother was provided by RadoSys Ltd., which was used by Tokonami et al. [18]. The CFs for RADUET
evaluated in the present study and the previous paper are summarized in Table 4. The CFs of the
CR-39 by Nagase Landauer Ltd. and RadoSys Ltd. were estimated to be 4.4 ± 0.1 and 2.8 ± 0.1 tracks
cm−2 per kBq h m−3 , respectively. This result suggested that the sensitivity of SSNTD signiﬁcantly
aﬀects the CF of a passive radon monitor. Notably, the image analysis system and the chemical etchingcondition might also be signiﬁcant factors aﬀecting the CF.
Table 3. Conversion factors of various passive radon monitors.
Measuring Device

Conversion Factor(Tracks cm−2 per kBq h m−3 )Present radon monitor
RADUET 1
KfK monitor 2
Radtrak
NRPB/SSI 3
Radon-thoron discriminative dosimeter 1

2.0
2.3
0.9
2.8
2.2
1.2

Reference

[18]
[24]
[25]
[26]
[27]

1 The CFs of these monitors were evaluated for those with a low air ventilation rate. 2 KfK: Kernforschungszentrum

Karlsruhe 3 NRPB/SSI: National Radiological Protection Board/Statens strålskyddsinstitut.

Table 4. The conversion factors of RADUET evaluated by two types of CR-39s in the present study andin a previous study. RADUETs, which contain both CR-39s, were simultaneously exposed to radon
atmosphere for evaluation of the diﬀerence in CFs.

Item
Present study
Previous report 2

Conversion Factor(Tracks cm−2 per kBq h m−3 )Nagase Landauer

RadoSys 1

4.4
-

2.8
2.3

1 CR-39s were chemically etched using a 6.25M NaOH solution at 90 ◦ C for 6 h. 2 . The data were cited from
Tokonami et al. [18].

McLaughlin and Fitzgerald developed a model to calculate a CF for a cylindrically-shaped passiveradon monitor [28]. According to the model, the CFs of the monitors, which have radii of 1.0 and
2.0 cm, corresponding to the present monitor and RADUET, respectively, were estimated to be 1.8 and3.7 tracks cm−2 per kBq h m−3 , respectively. Compared with the empirical values, the diﬀerences in
the present monitor and RADUET were 12% and 16%, respectively. Notably, these values calculatedby the model include an uncertainty because the model made assumptions that do not reﬂect theexact geometry and shape of a detector for simpliﬁcation. The ratio of the two values by the model
was calculated as 2.1, whereas that of experimentally evaluated in this study was 2.2. We found areasonably good agreement between the ratios regardless of the simpliﬁed model, indicating that the161

IJERPH 2020, 17, 5660

sensitivity was lower compared with the previous monitor, and the diﬀerence in the CFs between thepresent monitor and RADUET was attributed to the shape of the monitor.
We found that the air gap between the lid and the container prevented thoron from entering
the monitor. This result suggested that the eﬀect of thoron concentration is small enough for radonmeasurements that it could be ignored.
4.2. Minimum and Maximum Detectable Radon Concentrations
The results suggested that the present monitor would be useful for radon measurements in places
where radon concentrations might be relatively high, such as mines and caves. According to a previous
report, radon concentrations in mines and tourist caves have daily and seasonal variations, and its
mean annual concentration was around 3500 Bq m−3 with a standard deviation of 1833 Bq m−3 [12].
There are very few underground mines in Japan so far, but there are some tourist caves; a wearable
monitor may be useful as a simple radiation protection instrument for workers.
The long-term indoor radon concentrations are measured using a passive radon monitor, which isput on a shelf or hung on a wall and roof for three or six months. In this case, the minimum
detectable radon concentrations are evaluated to be 31 and 15 Bq m−3 for three- and six-monthmeasurements, respectively. It has been reported in several foreign countries that their mean indoor
radon concentrations are relatively higher than these values [29–34]. Therefore, the passive radon
monitor developed in this study will be useful not only as a wearable monitor for personal dosimetry
due to radon inhalation but also for indoor radon measurements in many countries.
4.3. Air Exchange Rate
The trend in the alpha track density against the degassing time in Figure 4 was found to be similar
to that reported by Omori et al. [23]. Omori et al. [23] reported that the experimental value was in good
agreement with the theoretically calculated value. The air exchange rate of RADUET was previously
reported as 0.71 h−1 , which is higher than that of the present monitor of 0.26 h−1 [23]. This indicatedthat the present monitor has a higher diﬀusion barrier than RADUET. The monitor is closed by thecontainer’s lid with a screw, which could make the high diﬀusion barrier, whereas RADUET was
designed to be easy to dismantle. As shown in Figure 4, it takes approximately 8 h to completely
exchange the air in the monitor, which is why the eﬀect of thoron could be neglected.
To evaluate the eﬀect of air exchange rate on the measurement result when being used as awearable monitor, the theoretical time-integrated radon concentration in the monitor was calculated
considering the working period. It was assumed that workers wear the monitor for a working period ofeight hours, and do not wear it at other times. If the radon concentration is 1000 Bq m−3 , the theoretical
time-integrated radon concentration in the monitor is estimated to be 7.6 kBq h m−3 , whereas the actual
value is 8.0 kBq h m−3 . We found that the diﬀerence was estimated to be 5%, which is low comparedwith other uncertainties such as a counting error. Therefore, the present monitor can be useful as awearable monitor to evaluate occupational exposure to radon.
5. Conclusions
A passive radon personal monitor was designed using a small container for storing contact lenses
and its performance was tested. The conversion factor to radon concentration and the eﬀect of thoron
concentration on the measurement result were evaluated using the calibration chamber at Hirosaki
University. The conversion factor for radon was evaluated as 2.0 ± 0.3 tracks cm−2 per kBq h m−3 andcould be smaller than those with the previous monitors. No signiﬁcant eﬀect of thoron was observedin the two-sided Student’s t-test. The minimum and maximum detectable radon concentrations were
estimated as 92 Bq m−3 and 231 kBq m−3 for a measurement period of three months, respectively.
The air exchange rate was evaluated to be 0.26 h−1 , and the eﬀect could be ignored even if it is used only
during the working period. These results indicated that this monitor would be useful as a wearable

162

IJERPH 2020, 17, 5660

monitor for radon measurements, especially in caves and mines, and for indoor radon measurements
where relatively high radon concentrations are present.
Author Contributions: Conceptualization, Y.T., M.H., and S.T.; methodology, Y.T., C.K., M.H., and S.T.; validation,
Y.T., M.H., and S.T.; formal analysis, T.S., Y.W., T.P., R.N., and E.D.N.; investigation, T.S., Y.W., T.P., R.N., E.D.N.,
K.I., and M.J.; resources, K.I., M.J., M.H., and S.T.; data curation, Y.T.; writing—original draft preparation, Y.T.;
writing—review and editing, Y.T., C.K., E.D.N., M.J., M.H., and S.T.; visualization, Y.T.; supervision, M.H. and S.T.;
project administration, Y.T., M.H., and S.T.; funding acquisition, M.H. and S.T. All authors have read and agreed tothe published version of the manuscript.
Funding: This research was partially funded by the Japan Society for the Promotion of Science KAKENHI(18K10023, 18KK0261, and 20H00556), the Environmental Radioactivity Research Network Center (E-20-10) andHirosaki University Institutional Research Grant.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleAssessment of Radiation Dose from the Consumptionof Bottled Drinking Water in Japan
Aoife Kinahan 1, *, Masahiro Hosoda 2 , Kevin Kelleher 1 , Takakiyo Tsujiguchi 2 , Naofumi Akata 3 ,Shinji Tokonami 3 , Lorraine Currivan 1 and Luis León Vintró 4
1
2
3
4

*

Environmental Protection Agency, Clonskeagh Square, Clonskeagh, D14 H424 Dublin 14, Ireland;
K.Kelleher@epa.ie (K.K.); L.Currivan@epa.ie (L.C.)
Graduate School of Health Science, Hirosaki University, 66-1 Hon-cho, Hirosaki, Aomori 036-8564, Japan;m_hosoda@hirosaki-u.ac.jp (M.H.); r.tsuji@hirosaki-u.ac.jp (T.T.)
Institute of Radiation Emergency Medicine, Hirosaki University, 66-1 Hon-cho, Hirosaki, Aomori 036-8564,
Japan; akata@hirosaki-u.ac.jp (N.A.); tokonami@hirosaki-u.ac.jp (S.T.)
School of Physics, University College Dublin, Dublin 4, Ireland; luis.leon@ucd.ie
Correspondence: A.Kinahan@epa.ie; Tel.: +353-01-268-0100

Received: 23 June 2020; Accepted: 8 July 2020; Published: 11 July 2020

Abstract: Activity concentrations of 234 U, 235 U, 238 U, 226 Ra, 228 Ra, 222 Rn, 210 Po, 210 Pb, 40 K, 3 H, 14 C,
134 Cs and 137 Cs were determined in 20 diﬀerent Japanese bottled drinking water commerciallyavailable in Japan. The origins of the mineral water samples were geographically distributed acrossdiﬀerent regions of Japan. Activity concentrations above detection limits were measured for theradionuclides 234 U, 235 U, 238 U, 226 Ra, 228 Ra and 210 Po. An average total annual eﬀective dose due toingestion was estimated for adults, based on the average annual volume of bottled water consumed
in Japan in 2019, reported to be 31.7 L/y per capita. The estimated dose was found to be below therecommended World Health Organisation (WHO) guidance level of 0.1 mSv/y for drinking water
quality. The most signiﬁcant contributor to the estimated dose was 228 Ra.
Keywords: dose assessment; Japan; bottled water; guidance level; WHO; natural radionuclides;
artiﬁcial radionuclides; eﬀective dose; ingestion

1. Introduction
People are continuously exposed, both externally and internally, to ionising radiation fromnaturally occurring sources, such as cosmic rays and terrestrial radioactivity, as well as artiﬁcial
sources, such as weapons fallout and authorized and accidental releases from the nuclear industry.
The main pathways for internal exposure to radiation are inhalation and the ingestion of food andwater. On average, people typically receive an estimated dose of 0.3 mSv/y due to the ingestion ofnaturally occurring radionuclides such as 238 U, 232 Th, their daughter products and 40 K in their diet [1].
Drinking water contributes to approximately 0.01 mSv of this dose [2]. While this is a small fraction of
the overall ingested dose, drinking water needs to be monitored, as there can be large variations in
the radioactivity content in water as a result of the underlying geology of the water source. Higher
radioactivity concentrations in drinking water can result in a higher contribution to the overall ingested
dose. The World Health Organisation (WHO) has issued guidelines for drinking water quality. If theradioactivity dose from drinking water is below the WHO recommended guidance level of 0.1 mSv/y,water is deemed safe for human consumption from a radiological perspective [3].
The volume of bottled water being consumed has increased steadily worldwide for the past
14 years, and this trend is also reﬂected in the consumption of bottled water in Japan. According to
the report by the Mineral Water Association of Japan, the annual intake of bottled water consumed inJapan in 2019 was reported to be 31.7 L/y per capita [4]. As shown in Figure 1, this is still signiﬁcantly
IJERPH 2020, 17, 4992; doi:10.3390/ijerph17144992

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IJERPH 2020, 17, 4992

lower than bottled water consumption in many EU countries and the USA. However, a signiﬁcant
increase in the consumption of bottled water has occurred in Japan since 2011 [4], which has been
attributed to consumer behavior after the Fukushima Dai-ichi Nuclear Power Plant (FDNPP) accident.

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Figure 1. Trend graph for the consumption of bottled water in 10 diﬀerent countries, including Japan [4].

In this study, an estimation is made of the radioactivity dose ingested from the consumption ofbottled water in Japan, based on the measurement of activity concentrations for a range of radiologicallysigniﬁcant natural and artiﬁcial radionuclides in a selection of 20 diﬀerent bottled waters collected
throughout the country. The inclusion of artiﬁcial radionuclides such as 3 H, 14 C (also naturally
occurring), 134 Cs and 137 Cs is considered particularly important from a radiation risk communication
perspective, particularly after the FDNPP accident in 2011. Currently, 33 nuclear reactors remain
operable in Japan, of which 9, located in 5 separate power plants, are in operation [5].
A review of the scientiﬁc literature shows that a number of previous studies were carried out todetermine the radioactivity levels in bottled water consumed in Japan. For example, Shiraishi et al.
investigated the eﬀective dose due to 232 Th and 238 U in imported mineral waters [6], and Shozugawa
analysed four Japanese bottled waters for 134 Cs and 137 Cs following the FDNPP accident in 2011 [7].
However, no single study has attempted to analyse Japanese bottled waters for a comprehensive suiteof radionuclides, although similar studies have been conducted in other countries for estimating theactivity concentration and ingestion doses arising from the consumption of natural radionuclides inbottled water [8–22].
The annual eﬀective dose arising from the consumption of bottled water is estimated in this study,
which represents the ﬁrst comprehensive study of this kind to be undertaken in relation to Japanesebottled water. The results presented are based on the analysis of 20 Japanese bottled water samples fornatural and artiﬁcial radionuclides.
2. Materials and Methods
2.1. Sampling and Chemical Characteristics of Bottled Water
Drinking water samples from 20 diﬀerent bottled water companies were purchased from Japanesesupermarkets. The water sources were distributed across the country of Japan (Figure 2), which gives awider geographical distribution to capture any potential eﬀects of variability of the underlying geologyof the regions. To increase representativeness, multiple bottles were purchased for each bottled watercompany and combined into a single sample. All water samples originated from natural mineralwater sources.

166

IJERPH 2020, 17, 4992

Figure 2. Locations of 20 bottle water samples.

To determine the chemical characteristics of the bottled water, pH and water hardness were
evaluated using a pH meter (Eutech pH 700, Thermo Fisher Scientiﬁc, Waltham, MA, USA) and bydetermining the contents of magnesium (Mg) and calcium (Ca) by ICP–MS (ELAN 9000, Perkin Elmer,
Germany), respectively. The water hardness (CaCO3 content) was calculated using Equation (1).
Total Hardness (mg/L as CaCO3 ) = 2.5Ca + 4.1Mg(1)

According to WHO guidelines [23], waters are classiﬁed on the basis of their hardness into
soft (CaCO3 < 60), moderately hard (60 < CaCO3 < 120), hard (120 < CaCO3 < 180) and very hard
(CaCO3 > 180).
2.2. Radionuclide Determination
All samples were analysed for radioactivity in the Environmental Protection Agency, Ireland’sradiation monitoring laboratory, which is accredited to ISO 17025 [24]. Table 1 gives a summary of theradionuclides analysed and the analytical techniques used for their determination. The methods andassociated references are discussed in more detail below.
Table 1. Summary of the methods used for the analysis. HPGe, high-purity germanium.
Radionuclide
3 H, 14 C
222 Rn40 K, 134 Cs, 137 Cs
40 K
210 Po210 Pb226 Ra, 228 Ra
234 U, 235 U, 238 U

Preparation

Analytical Techniques

8:12 mL water:/Ultima Gold ™ LLT
7:1:12 mL water/spike/Ultima Gold ™ LLT
8:12 mL water/organic scintillation cocktail
500 mL Marinelli
Acidiﬁed
500 mL water, acidiﬁed, spontaneous deposition
500 mL water, acidiﬁed, spontaneous deposition(after 6 months)
1 to 4 L water, barium co-precipitation method,stored for one month prior to measurement
Acidiﬁed

Liquid scintillation counting
Liquid scintillation counting
Direct counting on HPGe
ICP–MS (evaluated from stable potassium to 40 K)
Alpha spectrometry
Alpha spectrometry
Gamma spectrometry (HPGe)
ICP–MS (evaluated from total uranium)

2.2.1. Tritium and Carbon-14 Determination
For the determination of 3 H and 14 C, the spiked duplicate method was employed. Eight (8) mLof each water sample was taken for each radionuclide and mixed with 12 mL of Ultima Gold™ LLT167

IJERPH 2020, 17, 4992

(Perkin Elmer, Groningen, The Netherlands) liquid scintillation cocktail. A duplicate sample was madewith 7 mL of water sample and 1 mL of a calibrated 3 H or 14 C standard and mixed with 12 mL of Ultima
Gold™ LLT. These samples were analysed for 720 min using a Tri-Carb® 3170TR/SL (Perkin Elmer,
Waltham, MA, USA) low-level liquid scintillation counter. Analysis of the sample and the spiked
duplicate sample was used to account for chemical and colour quenching in each sample. Optimised
counting parameters were used with energy windows of 0.0–18.6 keV for 3 H and 0.0–156.0 keV for 14 C.
2.2.2. Radon Determination
For the determination of 222 Rn, 8 mL of sample was poured into a 20 mL scintillation vial
containing Perkin Elmer, Ultima Gold™ F liquid scintillation cocktail. The vial was shaken for 60 s
and counted on a Perkin Elmer Tri-Carb® 3170TR/SL low-level liquid scintillation counter for 60 min,after 4 h of dark equilibration and to allow for the short-lived daughter products to reach secularequilibrium. These short-lived daughter products were measured to assess radon activity. The alphaenergy window was optimised to 300–1000 keV. The principle of this method is based on the ISO
standard, ISO 13164–Part 4 [25].
2.2.3. Potassium and Caesium Determination
40 K and 134,137 Cs were analysed by direct counting on a gamma spectrometry system using

in-house analytical methods accredited to the ISO 17025 standard [24]. The samples were measured
with a high-purity germanium (HPGe) p-type co-axial detector (GC7520/S Mirion Technologies Inc.,San Ramon, CA, USA). Radiocaesium concentrations in the water samples were determined by counting
photons in the full-energy peak channels of 605 keV for 134 Cs, 662 keV for 137 Cs and 1461 keV for 40 K.
The measurement time was 86,400 s. The uncertainty for the activity concentration was evaluated taking
into account the uncertainties of the counts for the sample and background. Coincidence summing,
self-attenuation and decay corrections were applied using Canberra ApexGamma software (Mirion
Technologies Inc., San Ramon, CA, USA) in conjunction with GESPECOR Monte-Carlo software (CIDMedia GmbH, Hasselroth, Germany).
The stable potassium content was also determined by ICP–MS (ELAN 9000, Perkin Elmer, Waltham,
MA, USA). Fifty (50) mL of water sample was preserved in 0.5%v/v nitric acid. The principle of thismethod is based on the ISO standard, ISO 17294-2:2016 [26]. The isotopic abundance of 40 K in natural
potassium is 0.0117%, where 40 K has a speciﬁc activity concentration of 3.1 × 10−2 Bq/kg. The amountof K-40 present in the sample was calculated by multiplying the amount of potassium measured (mg/L)by the activity concentration (Bq/kg) and isotopic abundance.
2.2.4. Uranium Determination
The activity concentrations of 234,235,238 U were determined by ICP–MS (ELAN 9000, Perkin
Elmer, Waltham, MA, USA). Fifty (50) mL of water sample was preserved in 0.5% v/v nitric acid.
The total uranium content was assessed. The principle of this method is based on the ISO standard,
ISO 17294-2:2016 [26] Assuming that the uranium isotopes are present in their natural isotopic
abundances in the environment (234 U = 0.0055%, 235 U = 0.72%, 238 U > 99%), the activity concentrationof 234 U, 235 U and 238 U were determined [21].
2.2.5. Radium Determination
For the determination of 226 Ra and 228 Ra, between 1.5 and 4 L was taken for the analysis.
Each sample was acidiﬁed with nitric acid to a pH between 0 and 1. Thirty (30) mL of concentratedhydrochloric acid and 50 mg barium carrier solution were added to the sample in the beaker. The sample
solution was boiled for 10 min. Thirty (30) mL of 9 M sulphuric acid was added and further boiledfor 30 min to form a precipitate. The solution was left to cool overnight to allow the precipitationand settling of barium sulphate. The solution was then ﬁltered through a pre-weighed ﬁlter paper(Whatman GF/C, 47 mm) (Whatman plc., Maidstone, United Kingdom). The ﬁlter was washed with168

IJERPH 2020, 17, 4992

10 mL of ethanol and 10 mL of diethyl ether. The ﬁlter paper was allowed to dry overnight in a
desiccator. The ﬁlter paper was prepared in a tightly sealed container, and the daughter products
214 Pb, 214 Bi (226 Ra) and 228 Ac (228 Ra) were ingrown for more than 30 days to reach secular equilibriumwith Ra. The measurements were made via HPGe gamma spectrometry. GESPECOR Monte-Carlosoftware (CID Media GmbH, Hasselroth, Germany) is typically used for correction for true coincidence
summing and self-attenuation of the samples; however, these were not required in this instance [27].
2.2.6. Polonium and Lead Determination
For the determination of 210 Po and 210 Pb, samples were prepared for spontaneous deposition ona silver (Ag) disc. An aliquot of 500 mL of water sample was placed in a jar and acidiﬁed with 2 M
HCl (pH of 1–2) followed by the addition of 0.5 g of ascorbic acid and 0.25 Bq of 209 Po tracer. A silver
disc was ﬁxed to a holder attached to the lid of the jar, which allowed the disc to be immersed in thesolution. The solution was heated to 80 ◦ C with stirring for 8 h. The disc was rinsed with water andmethanol and dried at room temperature. The 210 Po activities were determined by counting the disks
for 345,600 s using PIPS detectors in the Canberra Alpha Analyst (Mirion Technologies Inc., San Ramon,
California, USA) integrated spectrometry system in conjunction with the Apex Alpha spectrometry
software (Mirion Technologies Inc., San Ramon, California, USA) [28]. The water samples were stored
for 6 months, to allow the ingrowth of the 210 Pb daughter product, 210 Po. The spontaneous deposition
process was repeated with a new aliquot of 209 Po tracer. After analysing the measurements by alpha
spectrometry, the 210 Pb activity concentrations were determined from the polonium activities using
Bateman’s equations [29].
2.3. Determination of the Annual Eﬀective Ingestion Doses
The annual eﬀective dose for each radionuclide was estimated using the following equation:
Ed = Ac × Ca × Dcoeﬀ(2)

where Ed is the annual eﬀective dose due to ingestion (nSv); Ac is the radionuclide activity concentration
measured in the water sample (Bq/L); Ca is the annual consumption of 31.7 L (per capita) reported by theJapanese Mineral Association [4]; and Dcoeﬀ is the dose coeﬃcient provided by the ICRP (nSv/Bq) [30],whose values are given in Table 2. To get the total eﬀective dose for a given sample, the eﬀective doses
for each radionuclide were added. The eﬀective dose was estimated for each sample based on theactivities of the radionuclides analysed. For measurements below the minimum detectable activity
concentration (MDC), the MDC value was used for the dose estimation, which gave a maximum
annual eﬀective dose for each sample.
Table 2. Dose coeﬃcient values used for this study (nSv/Bq).
Isotope

Dose Coeﬃcient (nSv/Bq)

222 Rn [31] 1

3.5 × 100
1.8 × 10−2
5.8 × 10−1
1.9 × 101
1.3 × 101
1.2× 103
6.9 × 102
2.8 × 102
6.9 × 102
4.9 × 101
4.7 × 101
4.5 × 101

3H
14 C
134 Cs137 Cs210 Po210 Pb226 Ra228 Ra
234 U
235 U
238 U

1 Speciﬁc to 222 Rn in drinking water, the value is the sum of weighted equivalent doses.

169

IJERPH 2020, 17, 4992

3. Results and Discussion
3.1. pH and Water Hardness
The pH of the 20 bottled water samples ranged from 6.2 to 8.3. The water hardness, which was
equivalent to the CaCO3 content, ranged from below the detection limit (<4 mg/L) to 147 mg/L. Only one
sample (No. 18) was classiﬁed as hard water. Samples 1, 3 and 17 were classiﬁed as moderately hardwater, and the remaining Japanese bottled water samples were classiﬁed as soft water. No apparent
diﬀerences were observed between soft and hard water samples.
3.2. Radionuclide Activity Concentrations
The activity concentrations measured in the bottled water samples, referenced to the date ofreceipt at the EPA laboratory, are given in Table 3. 222 Rn was not expected to be present in bottled water,as during the bottling process radon gas is released from the product. The analysis was conducted
to rule out any ingrowth from its parent radionuclide, 226 Ra. Elevated levels of 3 H and 14 C were notexpected either, as sources of these radionuclides discharged into the catchments of the bottled water
sources are not signiﬁcant or present in the environment at levels above the limits of detection forthese radionuclides. This was conﬁrmed by our measurements, which showed 3 H and 14 C activity
concentrations below the detection limits in all cases. There were no detectable quantities of 134 Cs
and 137 Cs in the water samples either. This indicates that the bottled water is not aﬀected by fallout
originating from the FDNPP accident. The MDC of 222 Rn, 3 H, 14 C, 134 Cs and 137 Cs were determined
as 60, 210, 160, 10 and 9 mBq/L, respectively. 40 K determined by gamma analysis had an MDC of
160 mBq/. Therefore, the quoted 40 K activity concentrations are based on the determination of stable K
by ICP–MS and were calculated based on its natural abundance in the environment.

170

210 Pb(5.7 ± 0.5) × 100(1.8 ± 0.2) × 100(2.0 ± 0.2) × 100(7.4 ± 0.7) × 100< 1.7 × 100(5.3 ± 0.5) × 100(3.8 ± 0.3) × 100(5.3 ± 0.5) × 10−1
(3.7 ± 0.3) × 100(8.1 ± 0.7) × 10−1
(2.0 ± 0.2) × 100(4.4 ± 0.4) × 100(1.9 ± 0.2) × 101(4.3 ± 0.4) × 100(3.0 ± 0.3) × 100(4.5 ± 0.4) × 100(2.4 ± 0.2) × 100(2.6 ± 0.2) ×100
(6.9 ± 0.6) × 100(5.9 ± 0.5) × 100<9.4 × 10−1
<7.4 × 10−1
<1.3 × 100(2.6 ± 0.4) × 100<1.2 × 100<1.3 × 100<8.9 × 10−1
<1.2 × 100<1.1 × 100<1.1 × 100<5.7 × 10−1
(1.0 ± 0.3) × 100(4.9 ± 0.4) × 100(1.5 ± 0.6) × 100<1.4 × 100<9.7 × 10−1
<8.3 × 10−1
<1.4 × 100(1.9 ± 1.5) × 100(1.7 ± 1.5) × 100

Sample

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

<1.9 × 102<1.1 × 102<1.8 × 102<2.0 × 102<1.7 × 102(8.5 ± 3.9) × 100<2.3 × 102<1.7 × 102<6.0 × 102<1.1 × 102<1.5 × 102<2.4 × 102(1.2 ± 0.5) × 101<2.3 × 102<1.9 × 102<1.9 × 102(1.3 ± 0.6) × 101<1.6 × 102(1.2 ± 0.4) × 101<7.1 × 102

226 Ra(2.6 ± 1.5) × 101<3.7 × 101<3.6 × 102<3.9 × 102<3.4 × 102(2.5 ± 1.1) × 101<4.2 × 101<3.4 × 101<1.1 × 102<3.9 × 102<2.9 × 102<4.3 × 101<3.3 × 102(4.9 ± 1.8) × 101<3.9 × 102(1.9 ± 1.0) × 101<3.2 × 102<3.2 × 102<2.5 × 101(1.6 ± 0.8) × 101

228 Ra(2.6 ± 0.5) × 101<1.3 × 10−1
(2.4 ± 0.5) × 100(2.6 ± 0.5) × 10−1
(1.3 ± 0.3) × 10−1
(7.9 ± 0.2) × 10−1
(5.2 ± 1.1) × 10−1
(2.6 ± 0.5) × 10−1
(1.3 ± 0.3) × 10−1
(1.3 ± 0.3) × 10−1
(3.9 ± 0.8) × 10−1
(5.2 ± 0.1) × 10−1
(1.6 ± 0.3) × 100<1.3 × 10−1
(3.0 ± 0.6) × 100(1.4 ± 0.3) × 10−1
(2.6 ± 0.5) × 10−1
(2.8 ± 0.6) × 100(1.7 ± 0.4) × 10−1
(1.3 ± 0.3) × 10−1

234 U

(1.2 ± 0.2) × 100<5.8 × 10−3
(1.0 ± 0.2) × 10−1
(1.2 ± 0.2) × 10−2
(5.8 ± 0.1) × 10−3
(3.5 ± 0.7) × 10−2
(2.3 ± 0.5) × 10−2
(1.2 ± 0.2) × 10−2
(5.8 ± 1.2) × 10−3
(5.8 ± 1.2) × 10−3
(1.7 ± 0.4) × 10−2
(2.3 ± 0.5) × 10−2
(6.9 ± 0.1) × 10−2
<5.8 × 10−3
(1.3 ± 0.3) × 10−1
(6.3 ± 1.3) × 10−2
(1.2 ± 0.2) × 10−2
(1.2 ± 0.2) × 10−1
(7.5 ± 1.5) × 10−2
(5.8 ± 1.2) × 10−3

235 U

(2.4 ± 0.5) × 101<1.2 × 10−1
(2.2 ± 0.5) × 100(2.4 ± 0.5) × 10−1
(1.2 ± 0.3) × 10−1
(7.3 ± 0.2) × 10−1
(4.8 ± 1.0) × 10−1
(2.4 ± 0.5) × 10−1
(1.2 ± 0.3) × 10−1
(1.2 ± 0.3) × 10−1
(3.6 ± 0.8) × 10−1
(4.8 ± 1.0) × 10−1
(1.5 ± 0.3) × 100<1.2 × 10−1
(2.8 ± 0.6) × 100(1.3 ± 0.3) × 100(2.4 ± 0.5) × 10−1
(2.5 ± 0.5) × 100(1.6 ± 0.3) × 100(1.2 ± 0.3) × 10−1

238 U

Table 3. Radionuclide activity concentration and standard uncertainty (k = 1) values in bottled water (mBq/L).

210 Po(1.3 ± 0.3) × 10−1
<7.7 × 10−3
(1.5 ± 0.3) × 10−2
(1.9 ± 0.4) × 10−2
(3.8 ± 0.8) × 10−2
(6.2 ± 1.3) ± × 10−2
(3.5 ± 0.7) × 10−2
(4.9 ± 1.0) × 10−2
(2.5 ± 0.5) × 10−2
(2.5 ± 0.5) × 10−2
(2.4 ± 0.5) × 10−2
(3.2 ± 0.7) × 10−2
(5.1 ± 1.1) × 10−2
(2.9 ± 0.6) × 10−2
(2.5 ± 0.5) × 10−1
(8.4 ± 1.7) × 10−2
(1.4 ± 0.3) × 10−1
(2.4 ± 0.5) × 10−1
(7.2 ± 1.5) × 10−2
(2.5 ± 0.5) × 10−2

40 K

IJERPH 2020, 17, 4992

171

IJERPH 2020, 17, 4992

3.2.1. Polonium and Lead activity Concentrations
In Table 4, the minimum, maximum and median activity concentrations of 210 Po and 210 Pb of
the detected (above MDC) concentrations are shown. The maximum estimated annual eﬀective dose,
determined using Equation (2), is also included, which is based on the maximum measured activities
for each nuclide. Seven bottled water samples showed 210 Po concentrations above the MDC. For 210 Pb,
19 samples were above the MDC.
Table 4. Activity concentrations for polonium and lead measured in bottled water (mBq/L).
IsotopeMin

Max

MedianMaximum Annual Eﬀective Dose 1 (nSv)

210 Po 2

1.0 ± 0.26
0.53 ± 0.050

4.9 ± 0.39
19 ± 1.8

1.7 ± 0.34
3.8 ± 0.34

186
421

210 Pb 3

1 Based on measured activities; 2 minimum detectable activity concentrations (MDC) = 0.06 mBq/L; 3 MDC = 0.12 mBq/L.

3.2.2. Radium Isotope Activity Concentrations
In Table 5, the minimum, maximum and median values of the radium isotopes of the detectedconcentrations are shown. The maximum estimated annual eﬀective dose using Equation (2) is also
included, which is based on the measured activities. Four and ﬁve bottled water samples showed
concentrations of 226 Ra and 228 Ra above the MDC, respectively.
Table 5. Activity concentrations for radium measured in bottled water (mBq/L).
IsotopeMin

Max

MedianMaximum Annual Eﬀective Dose 1 (nSv)

226 Ra 20.85 ± 0.39
16 ± 8.2

13 ± 5.549 ± 18

12 ± 4.3
25 ± 11100
589

228 Ra 3

1 Based on measured activities; 2 MDC = 112 mBq/L; 3 MDC = 25 mBq/L.

3.2.3. Uranium Isotope Activity Concentrations
In Table 6, the minimum, maximum and median values of the uranium isotopes of the detectedconcentrations are shown. The maximum estimated annual eﬀective dose, determined using Equation(2), is also included, which is based on the measured activities. Eighteen bottled water samples
contained detectable amounts of total uranium, and two were below the limits of detection. The total
uranium content of the bottled water was measured, and the activity concentrations were calculated
based on their natural abundance in the environment.
Table 6. Activity concentrations for uranium analysed in bottled water (mBq/L).
IsotopeMin

Max

MedianMaximum Annual Eﬀective Dose 1 (nSv)

234 U 20.13 ± 0.030
0.005 ± 0.002
0.24 ± 0.050

26 ± 5.4
1.2 ± 0.24
24 ± 5.0

0.52 ± 0.11
0.023 ± 0.005
0.48 ± 0.099

3.3
0.14
2.8

235 U 3238 U 4

1 Based on measured activities; 2 MDC = 0.13 mBq/L; 3 MDC = 0.005 mBq/L; 4 MDC = 0.12 mBq/L.

3.2.4. Comparison of Activity Concentrations in Bottled Mineral Waters for Sale in Other Countries
The activity concentrations found in the bottled water samples in this study were compared to thosedetermined in previous studies in diﬀerent countries. Most studies included the analysis of radium
and uranium. In general, most studies reported radium as the largest contributor to the ingestion dose,apart from Rozmaric et al. [20] who reported uranium isotopes as the main contributor in Croatianmineral waters. The activity concentrations measured in this work for 210 Po were 1.0–4.9 mBq/L.
These values are comparable with results found in Croatia [20] but are lower than those reported
in Italy [14,15] and Austria [10,19]. Activity concentrations for 210 Pb were 0.53–19 mBq/L, whereas
172

IJERPH 2020, 17, 4992

studies in Austria [10,19] showed a broader range for these values but reported a similar geometricmean for 210 Pb activities. In contrast, values reported for Croatian waters [20] showed a lower range ofactivities. The activity concentrations for 226 Ra and 228 Ra ranged between 0.85 and 13 mBq/L and 16
and 49 mBq/L, respectively, which are comparable to the values found in Greece [12] and Pakistan [13].
Studies in Algeria [9], Croatia [20], Italy [14,15] and Poland [16] reported a much broader range of 226 Ra
and 228 Ra activity concentrations in bottled water, but all geometric mean values are in agreementwith the values reported in this study, with the exception of those for Algeria [9]. Algeria reported
a mean value of 26 mBq/L. Studies in Austria [10,19] reported a broader range in radium activity
concentrations and a higher mean value than this study. Studies in Malaysia [22] and Hungary [11]reported a very large range for 226 Ra, with some values reported above 3000 mBq/L. For uranium
isotopes, the ranges of activities reported in Japanese bottled water in this study were 0.24–24 mBq/L
and 0.13–26 mBq/L for 238 U and 234 U, respectively. Studies in Poland [16] reported a lower range
in uranium activity concentrations, whereas Croatia [20] and Tunisia [18] reported similar activities.
Studies in Italy [14,15] and Austria reported a broader range in their results. In both Italian studies, thegeometric mean values for 234 U, 235 U and 238 U were much higher than the reported geometric meanvalues in this study [14,15].
It has been reported that the absorbed dose rates in air due to terrestrial radiation in western partsof Japan are higher than those in eastern parts of Japan [32]. This diﬀerence in dose rate distribution
has been attributed to the presence in western Japan of areas with higher natural uranium andactinium series radionuclides, corresponding to granitic regions with enhanced natural radionuclide
concentrations, relative to other areas characterised by andesite or andosol soils. To investigate apossible similar eﬀect on the uranium content between waters sourced in western and eastern Japan,
the median activity concentrations were statistically compared. The median values of 234 U, 235 U and238 U in western parts of Japan (Nos. 14, 15, 16, 17, 18, 19 and 20) were evaluated as 0.17 mBq/L,
0.063 mBq/L and 1.3 mBq/L, respectively. The corresponding values in eastern parts of Japan were
evaluated as 0.39 mBq/L, 0.017 mBq/L and 0.36 mBq/L, respectively. A Mann–Whitney U Test (with acritical value of U at p < 0.05) showed that the values for each radionuclide from western and easternJapan were not signiﬁcantly diﬀerent from each other.
3.3. Dose Assessment of the Maximum Annual Eﬀective Ingestion Doses from Bottled Water
According to the WHO, 40 K levels do not need to be measured when assessing the dose fromdrinking water. The potassium level in a healthy individual is kept constant by a range of physiologicalprocesses in order to regulate the functions of the body [2]. Therefore, the levels of 40 K were notincluded in the calculation of the annual eﬀective ingestion dose.
Figure 3 presents an overview of the estimated maximum annual eﬀective dose for each sample
dose received from the radionuclides analysed in the bottled water samples. The highest dose value
calculated was 10% of the guidance level recommended by the WHO. The average annual eﬀective
dose estimated for all samples was 5.6 μSv. There was little correlation between doses and locations
across Japan. There were two bottled water products from the same location, i.e., 9 and 10 and 7 and 8,
and these reported similar dose values. In contrast, samples 12 and 13 were not similar, though they
were from the same location.

173ĨĨĞĐƚŝǀĞĚŽƐĞ;μ^ǀͿ

IJERPH 2020, 17, 4992

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ZĞĨĞƌĞŶĐĞůĞǀĞůсϭϬϬμ^ǀϭϬͲϭϭ Ϯ ϯ ϰ ϱ ϲ ϳ ϴ ϵ ϭϬϭϭϭϮϭϯϭϰϭϱϭϲϭϳϭϴϭϵϮϬ
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Figure 3. The maximum annual eﬀective dose in each bottled water sample compared to theguidance level.

4. Conclusions
The activity concentrations of natural and artiﬁcial radionuclides in a wide range of bottled
water produced in Japan were determined. The results showed that the highest activities were due
to naturally occurring radionuclides, i.e., Ra and Pb isotopes. The results are comparable to resultsfrom other studies around the world. The total annual eﬀective ingestion dose was assessed from theactivity concentrations measured in this study and the average rate of consumption of bottled mineralwater in Japan per capita. In all cases, the estimated doses were at least an order of magnitude below
the WHO recommended guidance level of 0.1 mSv for the consumption of drinking water.
Author Contributions: Conceptualization, M.H. and K.K.; Methodology, M.H., K.K. and A.K.; Formal Analysis,
A.K., M.H. and K.K.; Investigation, A.K., M.H. and K.K., Data Curation, A.K., K.K. and M.H.; Writing—originaldraft preparation, A.K.; Writing—review and editing, M.H., K.K., T.T., N.A., S.T., L.C. and L.L.V.; Funding
acquisition, M.H. All authors have read and agreed to the published version of the manuscript.
Funding: This work was partially supported by the Hirosaki University Institutional Research Grant.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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176

International Journal ofEnvironmental Researchand Public Health
ArticleObservation of Dispersion in the Japanese Coastal
Area of Released 90Sr, 134Cs, and 137Cs from the
Fukushima Daiichi Nuclear Power Plant to the Sea
in 2013
Hirofumi Tazoe 1, *, Takeyasu Yamagata 2 , Kazuki Tsujita 3 , Hisao Nagai 2 , Hajime Obata 4 ,Daisuke Tsumune 5 , Jota Kanda 6 and Masatoshi Yamada 1,7
1
2
3
4
5
6
7

*

Department of Radiation Chemistry, Institute of Radiation Emergency Mediation, Hirosaki University,
Hirosaki 036-8652, Japan; myamada@hirosaki-u.ac.jp
College of Humanities and Sciences, Nihon University, Tokyo 156-8550, Japan;
yamagata@chs.nihon-u.ac.jp (T.Y.); hnagai@chs.nihon-u.ac.jp (H.N.)
Graduate School of Basic Integrated Sciences, Nihon University, Tokyo 156-8550, Japan;
kaz.tsujita.chs@gmail.com
Atmosphere and Ocean Research Institute, University of Tokyo 277-8564, Japan; obata@aori.u-tokyo.ac.jp
Environmental Science Research Laboratory, Central Research Institute of Electric Power Industry,
Tokyo 270-1194, Japan; tsumune@criepi.denken.or.jp
Department of Ocean Sciences, Graduate Faculty of Marine Science, Tokyo University of Marine Science andTechnology, Tokyo 108-8477, Japan; jkanda@kaiyodai.ac.jp
Marine Ecology Research Institute, Chiba 299-5105, Japan
Correspondence: tazoe@hirosaki-u.ac.jp; Tel.: +81-172-39-5503

Received: 30 September 2019; Accepted: 22 October 2019; Published: 24 October 2019

Abstract: The March 2011 earthquake and tsunami resulted in signiﬁcant damage to the Fukushima
Daiichi Nuclear Power Plant (FDNPP) and the subsequent release of radionuclides into the ocean.
Here, we investigated the spatial distribution of strontium-90 (90 Sr) and cesium-134/cesium-137(134, 137 Cs) in surface seawater of the coastal region near the FDNPP. In the coastal region, 90 Sr activity
was high, from 0.89 to 29.13 mBq L−1 , with detectable FDNPP site-derived 134 Cs. This indicated that
release of 90 Sr from the power plant was ongoing even in May 2013, as was that of 134 Cs and 137 Cs.
90 Sr activities measured at open ocean sites corresponded to background derived from atmosphericnuclear weapons testing fallout. The FDNPP site-derived 90 Sr/137 Cs activity ratios in seawater weremuch higher than those in the direct discharge event in March 2011, in river input, and in seabedsediment; those ratios showed large variability, ranging from 0.16 to 0.64 despite a short sampling
period. This FDNPP site-derived 90 Sr/137 Cs activity ratio suggests that these radionuclides weremainly derived from stagnant water in the reactor and turbine buildings of the FDNPP, while adiﬀerent source with a low 90 Sr/137 Cs ratio could contribute to and produce the temporal variabilityof the 90 Sr/137 Cs ratio in coastal water. We estimated the release rate of 90 Sr from the power plantas 9.6 ± 6.1 GBq day−1 in May 2013 on the basis of the relationship between 90 Sr and 137 Cs activity(90 Sr/137 Cs = 0.66 ± 0.05) and 137 Cs release rate.
Keywords: Fukushima Daiichi Nuclear Power Plant; strontium-90; cesium-137; seawater monitoring;
contaminated water

1. Introduction
Large amounts of radionuclides, such as cesium-134 (134 Cs), cesium-137 (137 Cs), and iodine-131(131 I), were dispersed into the terrestrial and aquatic environments as a result of an accident at the
Fukushima Daiichi Nuclear Power Plant (FDNPP) of the Tokyo Electric Power Company (TEPCO)IJERPH 2019, 16, 4094; doi:10.3390/ijerph16214094

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in March 2011. Atmospheric release of strontium-90 (90 Sr) in March 2011 was two to four orders ofmagnitude lower than that of 137 Cs on the basis of an analysis of highly contaminated soils (<1.1 Bq
g−1 ) and vegetation (0.026–1.1 Bq g−1 ) collected from a contaminated area in Japan [1]. These 90 Sr/137 Cs
activity ratios were much lower than the ratio for the estimated nuclear fuel compositions (90 Sr/137 Cs =0.74) found in the reactor obtained by the ORIGEN2 code [2]. Atmospheric 90 Sr release (0.01–0.14 PBq [3])was estimated at less than 0.027% of the total amount in the nuclear fuel (5.2 × 102 PBq [2]) at FDNPP
reactor units 1, 2, and 3. Most of the 90 Sr remained in the reactor, although some of it had dissolvedin stagnant water in the reactor and turbine buildings. Observed 90 Sr and 137 Cs concentrations inthe stagnant water were 140 MBq L−1 and 2.8 GBq L−1 , respectively, on 27 March 2011 [4]. Hence,
137 Cs concentrations were 20 times higher than 90 Sr concentrations, and 1.6% of the 90 Sr core inventory
was dissolved into stagnant water [2], which was the most likely candidate for pollution to the ocean.
90 Sr in seawater could be a useful tracer speciﬁc to the radionuclide contaminants directly released
from the FDNPP into the ocean.
Analytical results of the stagnant water sampled from a turbine building in February 2012 indicatedthat 137 Cs activity decreased to 240 MBq L−1 , while 90 Sr concentration remained high (170 MBq L−1 ) [5].
Highly contaminated stagnant water was decontaminated and stored in storage tanks on the FDNPP
site. Some decontaminated water was transferred into reactors for cooling purposes after distillation
or reverse osmosis processes. Before 2015, the decontamination system was optimized to remove
Cs; hence, the treated water had signiﬁcantly higher 90 Sr activity (150 MBq L−1 ) than 137 Cs activity(3.9 kBq L−1 ) [5]. This treated water in the storage tanks was a potential source for 90 Sr contaminationin the environment.
In observation wells between the reactor buildings and the harbor, groundwater was also
monitored by TEPCO after a leakage event of contaminated water in December 2012 [4]. In particular,
90 Sr activity in groundwater in the wells near the seawater intake for reactor units 1 and 2 weresigniﬁcantly higher than the 137 Cs activity (e.g., 90 Sr: 5 × 106 Bq L−1 ; 137 Cs: 2.1 × 102 Bq L−1 at the no.
1–2 wells on 5 July 2013 [6]). The 90 Sr-enriched groundwater might have resulted from leakage of thedecontamination system or from stagnant water. Due to these existing contamination sources, it isnecessary to observe the 90 Sr behavior in the aquatic environment near the FDNPP.
Kanda [7] indicated that continuous release of 137 Cs from the FDNPP harbor to the ocean was
occurring in 2012 based on time series seawater monitoring data. Due to the high 90 Sr/137 Cs activity
ratio in the stagnant water, 90 Sr release from the FDNPP should also be evaluated. TEPCO has
continued seawater monitoring for 90 Sr, 134,137 Cs, and other radionuclides near the FDNPP [3,6].
However, only a few 90 Sr data were obtained within small areas, particularly after 2012 (Figure 1).
This limited monitoring cannot evaluate how much 90 Sr was released or its impact on the coastal
environment and open ocean.
Time series seawater monitoring by TEPCO of 90 Sr near the FDNPP was infrequent comparedto that for radiocesium [3,6]. Povinec et al. [3] showed that the 90 Sr/137 Cs ratio in seawater at amonitoring point near FDNPP increased gradually from 0.01 to 1 between April 2011 and February
2012 (Figure 1), which clearly related with decontamination of stagnant water. The transient increase of
90 Sr in seawater at the T2 site observed in December 2011 could reﬂect the leakage event from the 137 Cs
decontamination system [4]. After 2012, the 90 Sr/137 Cs ratio remained at a constant value around 0.5 at
the T2 site with large variability. 90 Sr/137 Cs activity ratios in stagnant water have varied depending on
the decontamination of 134, 137 Cs. The agreement between the temporal variation of 90 Sr/137 Cs activity
ratio and decontamination of the stagnant water supported the idea that the most probable candidate
was the continuous release from reactor buildings of the FDNPP.
The behavior of 137 Cs in seawater and biota after the accident has been well documented [7–11].
High-density sampling of surface seawater to determine radiocesium activity [12] has been carriedout. Kumamoto et al. [13] reported detailed vertical distributions of Fukushima-derived radiocesium
along the 149 ◦ E meridian in the western North Paciﬁc. However, distributions of 90 Sr derived fromthe FDNPP in the sea have been studied to a signiﬁcantly lesser extent [3,6,14–17]. Castrillejo et al. [17]178

IJERPH 2019, 16, 4094

suggested that continuous release of 90 Sr from the FDNPP was occurring in September 2013 based on
simultaneous observations of 90 Sr and 137 Cs. The estimated release rate of 90 Sr was 2.3–8.5 GBq day−1 ,which was 2–3 orders of magnitude larger than river inputs.

Figure 1. Temporal variations of strontium-90/cesium-137 (90 Sr/137 Cs) activity ratio in seawater frommonitoring sites T1 and T2 (T2-1) in the Fukushima Daiichi Nuclear Power Plant (FDNPP) site [6].
T1 and T2 (T2-1) sites are located north and south of the discharge channel of the FDNPP, respectively.

It is still necessary to investigate the amount of released 90 Sr, including its subsequent dispersion
from the FDNPP site to the ocean. Simultaneous determinations of 90 Sr and 137 Cs in seawater areimportant for monitoring the release of radionuclides from the reactor buildings and contaminatedwater from the storage tanks. By comparing 90 Sr behavior with that of 137 Cs in the ocean, we studied
the input source to the sea and the environmental migration processes of both radionuclides, such as
ﬂuvial input, desorption from sediment, and atmospheric deposition. Accumulating environmental
data and understanding the dispersion to the coastal and open oceans are necessary to respond to any
accidental release during decommissioning of the FDNPP—work that will require more than 30 years.
Our aim in this study is to determine the distributions of 90 Sr, 134 Cs, and 137 Cs in 2013 and evaluate
the continuous release of radionuclides from the FDNPP to the ocean based on the comprehensive
analysis of seawater.
2. Surface Current System oﬀ Fukushima Coast
The Kuroshio and Oyashio currents are generated in the mixed region around 36 ◦ N oﬀ the Ibaraki
Prefecture coast in the subject area (Figure 2a,b). The warm (16.5–22.0 ◦ C) and saline (34.4–34.8 psu)
Kuroshio ﬂows northeastward oﬀ the Boso Peninsula. The Oyashio current, oﬀ the Fukushima
Prefecture coast, intrudes southward into the mixing region. The southward intrusion (9.5–10.5 ◦ C,
salinity 33.4–33.8 psu) reaches 36.5 ◦ N, 141.3 ◦ E, and is called the First Branch of the Oyashio [18].
The coastal currents near Fukushima Prefecture are variable on a time scale diﬀerent from those of theKuroshio and Oyashio currents. Coastal water is at a higher temperature (10.8–12.7 ◦ C) and lower
salinity (33.2–33.4 psu) relative to the ﬁrst branch of the Oyashio current. Current meter observations
made between 1971 and 1981 [19] indicated that the along-shore (north–south component) currents
were dominant in this coastal area. The direction of the currents varied approximately every 3−4 days
because of changes in the synoptic-scale wind ﬁelds [19]. The spread of radionuclides from thedirect-release event in April 2011 depended on the coastal current system. Model simulation of directly
released Cs employed the Regional Ocean Modeling System (ROMS), which indicated that the plume
was southwardly advected to the coastal region [20].

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IJERPH 2019, 16, 4094

Figure 2. Maps showing sampling locations. (a) Surface temperature and (b) salinity had two boundary
currents (dashed arrows), the warm northeastwardly Kuroshio current south of the Boso Peninsula andthe cold southerly ﬁrst branch of the Oyashio current oﬀ the Fukushima coast. (c,d) Sampling locations
are marked by red circles and located near the coast of Fukushima Prefecture.

3. Materials and Methods
Seawater samples for the analysis of 90 Sr, 134 Cs, and 137 Cs were obtained during the UM13-5
cruise from 14 to 23 May 2013 undertaken by the RTV Umitaka−Maru of the Tokyo University ofFisheries, Japan. Seawater sampling sites were located in the oﬀshore region in the ﬁrst branch of the
Oyashio current and the coastal region near Fukushima Prefecture (Figure 2c,d). Most of the coastal
sites were south of the FDNPP and close to Iwaki city. The closest observation site to the FDNPP was
NP-2, located approximately 6 km east of it. During the sampling period, most of the inﬂuence fromthe FDNPP could be detected in the region associated with the southerly coastal current.
During the cruise, surface seawater samples were collected by an underway sampling system,
whose inlet was located on the bottom of the ship, at a depth 5 m below the surface. Collected samples
were ﬁltered through a 0.5 μm pore polypropylene cartridge ﬁlter (TCW-05N-PPS, Advantec, Tokyo,
Japan). Filtered water samples were stored in 20 L polyethylene bags and 90 Sr and radiocesium
analyses were carried out separately on land.

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IJERPH 2019, 16, 4094

We conducted 134 Cs and 137 Cs analyses based on Aoyama et al. [21]. First, 20 L of a ﬁlteredseawater sample was acidiﬁed to pH 1.6 with HNO3 . Next, 0.26 g of CsCl was added and thesolution was adsorbed on ammonium phosphomolybdate (AMP) [21]. Then, AMP was collected byﬁltering through a 0.45 μm pore mixed cellulose esters membrane (A045A047A, Advantec, Tokyo,
Japan). After drying the AMP/Cs compound, gamma rays were counted for 80,000–200,000 s with alead-shielded HPGe detector (EGPC 250-P 15, EURISYS MEASURES, NV, USA), 604.7 keV for 134 Cs and661.7 keV for 137 Cs, at the Nihon University in Tokyo. Since the detector was slightly contaminated byatmospherically released 134 Cs and 137 Cs at the time of the accident of the FDNPP, the background wasdetermined before and after this counting period and subtracted from the detected signals for seawater
samples. Cs yield was determined gravimetrically based on AMP weight. The typical minimum
detectable concentrations (MDCs) of 134 Cs and 137 Cs were 0.5 mBq L−1 and 0.4 mBq L−1 , respectively.
For 90 Sr analysis, we added 150 g of (NH4 )2 C2 O4 H2 O to 20 L of ﬁltered seawater and shook
the solution vigorously. Sr was precipitated with Ca oxalate. Oxalate precipitate was decomposed
to carbonate at 550 ◦ C in a muﬄe oven. Then, the precipitate was dissolved in HCl and diluted toabout 200 mL with Milli-Q water. A small portion of sample solution was used for determinationof stable Sr yield by ICP-OES (SPECTROBLUE TI, SPECTRO Analytical Instruments GmbH, Kleve,
Germany). After secular equilibrium between 90 Sr and yttrium-90 (90 Y) (>2 weeks), 90 Y with stable Y
carrier (0.1 mg) was “milked” from the 90 Sr by precipitating the Fe hydroxide and puriﬁed by solid
phase extraction using DGA Resin (DN1ML-R50-S) purchased from Eichrom Technologies, LLC. (IL,USA). Detailed chemical separation and beta counting procedures are described elsewhere [22,23].
Beta particles were counted by a low background 2π gas ﬂow proportional counter (LB−4200, Canberra,
NV, USA) during 120 min intervals for more than 20 h. Typical Sr and Y yields were 82 ± 9 % and 95 ±5 %, respectively.
4. Results
Activities of 90 Sr, 134 Cs, and 137 Cs in surface seawater samples collected in May 2013 aresummarized in Table 1. Mean 90 Sr activity of 0.80 ± 0.11 mBq L−1 at oﬀshore sites (S1, S2, S3, and N01)
was slightly lower than the estimated value (1.0 ± 0.1 mBq L−1 [3]) based on long-term monitoring forsurface water of the western North Paciﬁc. Around sites S2, S3, and N01, cool surface water (9.4–10.4◦ C) from the southerly ﬁrst branch of the Oyashio current was present. 134 Cs activities were lower thanthe MDC (<0.5 mBq L−1 ) at the oﬀshore sites. In this study, we used values obtained at the oﬀshoresites as the background level originating from atmospheric nuclear weapons testing. Compared to
137 Cs and 90 Sr, 134 Cs has a relatively short half-life (2.06 years compared to 30.17 years for 137 Cs and28.8 years for 90 Sr).
High 90 Sr activities were observed along the coastal region with higher temperatures (10.86–12.89◦ C) and higher salinity (33.23–33.35 psu). The highest 90 Sr activity (29.13 ± 0.35 mBq L−1 ) was foundat AN7, approximately 16 km south of the FDNPP, with 22.4 ± 0.6 mBq L−1 for 134 Cs activity and44.7 ± 0.4 mBq L−1 for 137 Cs activity. At the NP-2 site closest to the FDNPP (5 km oﬀshore) in thissampling campaign, we also found high 90 Sr activity (21.81 ± 0.28 mBq L−1 ). Furthermore, at S12oﬀ Iwaki City, 57 km south of the FDNPP, relatively high 90 Sr activity (9.86 ± 0.22 mBq L−1 ) was
found. Distributions of radiocesium activities in surface seawater showed similar trends to those of
90 Sr. The maximum radiocesium activities were obtained at AN7; in particular, 137 Cs activities ranged
from 1.4 mBq L−1 at S2 to 44.7 mBq L−1 there. In the coastal region, 134 Cs activities were in agreementwith 137 Cs activities corrected to 11 March 2011, which indicated that this radiocesium was derived
from the Fukushima accident (134 Cs/137 Cs = 0.99 ± 0.03 [11]).

181

Sampling Date and Time
(year/month/day)

2013/5/14 16:41
2013/5/14 18:39
2013/5/14 19:54
2013/5/14 20:47
2013/5/14 23:12
2013/5/15 5:39
2013/5/15 7:53
2013/5/16 2:28
2013/5/16 8:05
2013/5/16 6:36
2013/5/16 6:08
2013/5/16 22:05
2013/5/17 3:48
2013/5/17 11:27
2013/5/17 12:08
2013/5/17 12:40
2013/5/17 14:05
2013/5/17 15:11
2013/5/17 16:15
2013/5/19 0:57
2013/5/19 5:09
2013/5/20 8:45
2013/5/20 23:05

ID

S1
S2
S3
S4
N01
R01
AN6
M01
NP3
S5
S6
NP2
NP1
S7
S8
S9
S10
S11
S12
S13
S14
AN7
S16

Latitude141◦ 15.60 E
141◦ 21.48 E
141◦ 23.88 E
141◦ 17.46 E
141◦ 14.75 E
141◦ 8.26 E
141◦ 7.80 E
141◦ 6.40 E
141◦ 5.94 E
141◦ 4.02 E
141◦ 2.16 E
140◦ 57.36 E
141◦ 0.06 E
141◦ 5.35 E
141◦ 5.14 E
141◦ 13.80 E
141◦ 20.85 E
141◦ 10.41 E
141◦ 17.99 E
141◦ 7.56 E
141◦ 10.68 E
141◦ 5.88 E
141◦ 30.00 E

Latitude36◦ 33.15 N
36◦ 55.62 N
37◦ 10.50 N
37◦ 26.13 N
37◦ 29.33 N
37◦ 25.20 N
37◦ 21.09 N
37◦ 15.42 N
37◦ 13.11 N
37◦ 6.60 N
36◦ 59.97 N
36◦ 54.93 N
36◦ 54.87 N
36◦ 55.05 N
37◦ 16.94 N
37◦ 14.00 N
37◦ 32.91 N
37◦ 33.03 N
37◦ 24.99 N
37◦ 33.03 N
37◦ 24.99 N
37◦ 24.99 N
37◦ 30.00 N
11.41
9.43
10.37
9.88
9.72
11.02
10.86
10.37
11.90
11.22
11.09
12.41
11.08
11.98
12.10
11.95
12.04
11.74
12.36
12.32
12.69
12.20
12.16

Temperature
(o C)
33.16
33.21
33.51
33.64
33.46
33.31
33.24
33.24
33.35
33.17
33.26
33.26
33.21
33.28
33.26
33.24
33.21
33.24
33.26
33.23
33.30
33.33
33.26

Salinity (psu)0.87 ± 0.06
0.66 ± 0.05
0.75 ± 0.06
1.03 ± 0.06
0.90 ± 0.07
3.09 ± 0.07
2.94 ± 0.13
0.92 ± 0.07
6.25 ± 0.08
0.89 ± 0.06
3.46 ± 0.08
21.81 ± 0.28
0.99 ± 0.07
14.17 ± 0.23
10.63 ± 0.27
21.74 ± 0.38
3.84 ± 0.12
3.68 ± 0.08
9.86 ± 0.22
8.92 ± 0.25
4.56 ± 0.08
29.13 ± 0.35
2.10 ± 0.06

90 Sr Activity (mBq L−1 )

<0.4
<0.4
<0.4
<0.4
<0.4
4.1 ± 0.4
6.9 ± 0.4
1.0 ± 0.3
7.2 ± 0.5
1.4 ± 0.3
8.6 ± 0.5
17.5 ± 1.2
1.4 ± 0.2
7.9 ± 0.4
14.4 ± 0.5
20.2 ± 0.5
7.2 ± 0.4
5.9 ± 0.4
11.9 ± 0.5
7.7 ± 0.4
6.0 ± 0.4
22.4 ± 0.6
2.6 ± 0.3

(mBq L−1 )134 Cs Activity

1.9 ± 0.1
1.4 ± 0.1
1.8 ± 0.1
1.5 ± 0.1
2.0 ± 0.2
7.7 ± 0.3
6.9 ± 0.2
3.8 ± 0.2
14.5 ± 0.3
3.5 ± 0.2
18.2 ± 0.3
39.0 ± 1.2
3.8 ± 0.1
16.5 ± 0.3
29.8 ± 0.4
39.8 ± 0.4
15.7 ± 0.3
12.5 ± 0.3
24.0 ± 0.3
16.1 ± 0.3
13.3 ± 0.3
44.7 ± 0.4
5.7 ± 0.2

(mBq L−1 )137 Cs Activity

Table 1. 90 Sr, 134 Cd, and 137 Cs activities and hydrographic data in seawater collected on the Fukushima Prefecture coast in May 2013. Uncertainties represent
1σ error.

IJERPH 2019, 16, 4094

182

IJERPH 2019, 16, 4094

5. Discussion
5.1. Dispersion of High 90 Sr and 134, 137 Cs Activity PlumeThe high activities of 90 Sr and 137 Cs in the coastal region (Figure 3) can be explained by therelease at the time of the FDNPP accident and the physical processes that later occurred in the ocean.
In the coastal region, high 90 Sr activity seawater samples with high 134 Cs and 137 Cs activities weremainly collected from south of the FDNPP (NP2, and AN7) to oﬀ Iwaki (S12 and S6), which reﬂects thesouthward transport of seawater along the Fukushima coast by the coastal currents. Higher 90 Sr activity
in seawater (>8 mBq L−1 ) was found where the salinity was 33.23–33.33 psu and 11.95–12.41 psu. In
the coastal region, no clear correlation between 90 Sr and salinity or 90 Sr and temperature was observed.

Figure 3. Distribution of 90 Sr and 137 Cs activities in surface seawater collected in May 2013.

The distributions of 90 Sr and 137 Cs activities in May 2013 observed in this study correspondto those of a model simulation of the direct-release event between 26 March and 6 April 2011 [20].
The 137 Cs released from the FDNPP from 26 March was initially advected southward, then transported
to the Ibaraki coast. This simulation suggested that the 137 Cs concentration decreased in May due
to advection and diﬀusion in the open ocean. The coastal currents are variable in this region andsometimes ﬂow northward. Oikawa et al. [16] compiled monitoring data for seawater in the coastal
region by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) andsuggested that the activities of 90 Sr in surface water decreased slowly over time in 2011 and reached
the background level by the end of December 2011. However, because of a lack of sampling sites
for 90 Sr, the 90 Sr plume could have been missed in previous observations. The distribution of ourresults indicates that the released 90 Sr plume from the FDNPP site (leakage of contaminated waterfrom storage tanks) could move to the coastal region south of the FDNPP, carried by the southward
coastal current.
Both activities decreased rapidly from NP2 toward the eastern sites (S6, NP1, and NP3),
which indicate that the eastward dispersion was limited because of the eﬀect of the southern coastal
current during this sampling period. Compared with the pre-Fukushima accident, oﬀshore 90 Sr
activities in the north Paciﬁc Ocean (1.0 ± 0.1) [3] and the activities measured in May 2013 indicatethat the inﬂuences of the Fukushima-derived 90 Sr on open ocean sites in the mixed region between
the Oyashio and Kuroshio currents were negligibly small, as were those of 134 Cs and 137 Cs. However,183

IJERPH 2019, 16, 4094

if any accidental releases from the FDNPP site were to occur during the decommissioning of thereactors, coastal areas could be exposed to a high activity plume.
In September 2017, low 90 Sr (1.0−1.8 mBq L−1 ) and high 137 Cs (9−43 mBq L−1 ) activities wereobtained at low salinity (4–28 psu) in groundwater and beach seawater samples from Sendai Bay,located north of the FDNPP [17]. 90 Sr/137 Cs ratios ranged from 0.036 to 0.19. The 137 Cs activity in low
salinity samples was aﬀected by atmospheric fallout from the FDNPP accident that was deposited onland, while 90 Sr activity was not sensitive to terrestrial input. Therefore, the relationship between 90 Srand 137 Cs can be a useful indicator for river input.
The mouth of the Ukedo River is located between collection sites NP2 and AN6. 137 Cs activity at
NP2 (39.0 mBq L−1 ) was more than ﬁve times higher than that at AN6 (6.9 mBq L−1 ), though theirsalinities were comparable (33.24 and 33.26 psu). Dissolved 137 Cs activity in the Ukedo River,which drains a highly contaminated area, ranged from 200 to 1100 Bq L−1 in August and November
2012 [6]. 90 Sr activity in the Ukedo River was not available but the reported 90 Sr/137 Cs ratio for riverwater in the Fukushima Prefecture [6] was less than 0.04. The contribution to 90 Sr activity in seawaterby input from the Ukedo River should be minor.
5.2. 90 Sr/137 Cs Activity Ratios Derived from the FDNPP Accident
The 90 Sr/137 Cs activity ratios in seawater are diﬀerent according to timing of any release or leakage
event (e.g., direct discharge event from late March to early April 2011 [3,15]). Since Sr and Cs are highly
soluble in seawater, the 90 Sr/137 Cs activity ratio depends on the source, which could be a useful tracer
for the source. The most possible source of 90 Sr and 137 Cs is stagnant water in the reactor building ofunit 2. The 90 Sr/137 Cs ratio of open ocean seawater [3], seawater monitoring data near the FDNPP [6],stagnant water [4], atmospheric input [1], seabed sediment [24], and river water [6] are summarizedwith our data in Figure 4.
The 90 Sr activity of 0.80 ± 0.11 mBq L−1 was obtained at the oﬀshore sites, S1, S2, S3, and N01(Table 2). To evaluate FDNPP site-derived 90 Sr, measured 90 Sr activity was subtracted from this value as
the background value for North Paciﬁc seawater. The measured 134 Cs was a pure FDNPP site-derived
component because of its short half-life (T1/2 = 2.06 yr). The FDNPP site-derived 134 Cs/137 Cs ratio wasreported to be 0.99 ± 0.03 [11] in March 2011. FDNPP site-derived 137 Cs was calculated on the basis ofmeasured 134 Cs activity and the FDNPP site-derived 134 Cs/137 Cs ratio.
Table 2. FDNPP site-derived 90Sr (90Srcorr.) and 137Cs (137Cscorr.) activities and 90Srcorr./137Cscorr. activity ratios.
ID

90 Sr
−1
corr. Activity (mBq L )137 Cs−1
corr. Activity (mBq L )90 Sr
137 Cscorr. /
corr.

S6
S7
S8
S9
S10
S11
S12
S13
S14
AN7
S16
R01
NP3
AN6
NP2

2.66 ± 0.13
9.83 ± 0.28
13.37 ± 0.25
20.94 ± 0.39
3.04 ± 0.16
2.88 ± 0.13
9.07 ± 0.24
8.12 ± 0.27
3.76 ± 0.13
28.33 ± 0.37
1.30 ± 0.12
2.30 ± 0.12
5.46 ± 0.13
2.15 ± 0.16
21.02 ± 0.30

17.0 ± 1.0
15.6 ± 0.8
28.5 ± 1.0
40.0 ± 1.0
14.2 ± 0.8
11.7 ± 0.8
23.5 ± 1.0
15.2 ± 0.8
11.9 ± 0.8
44.3 ± 1.2
5.1 ± 0.6
8.1 ± 0.8
14.2 ± 1.0
5.9 ± 0.6
34.6 ± 2.4

0.16 ± 0.01
0.63 ± 0.04
0.47 ± 0.02
0.52 ± 0.02
0.21 ± 0.02
0.25 ± 0.02
0.39 ± 0.02
0.53 ± 0.03
0.32 ± 0.02
0.64 ± 0.02
0.25 ± 0.04
0.28 ± 0.03
0.38 ± 0.03
0.36 ± 0.05
0.61 ± 0.04

The 90 Srcorr /137 Cscorr ratio estimated from the slope of a linear regression ﬁtting was 0.66 ± 0.05
in Figure 5. 90 Srcorr activities strongly correlated with those of 137 Cscorr (R2 = 0.919), as describedin similar contour maps of 90 Sr and 137 Cs (Figure 3). The high correlation between 90 Sr and 137 Cs
184

IJERPH 2019, 16, 4094

indicates that 90 Sr and 137 Cs were derived from a common source. However, the low 90 Sr activity
samples (<10 mBq L−1 ) showed larger variability in 90 Sr/137 Cs activity ratio (0.34 ± 0.14) relative tothose for high 90 Sr activity samples (>10 mBq L−1 : ratio of 0.56 ± 0.08). If multiple sources to seawater
exist, such as stagnant water, storage water, and groundwater, contributions from each source could
yield temporal and spatial variations. To distinguish these components, detailed 134,137 Cs and 90 Sr
distributions should be investigated. Castrillejo et al. [17] found a short-term transition of 90 Sr/137 Cs
ratio from 0.14 to 0.36 and an abrupt increase in 137 Cs activity in the vicinity of the FDNPP (observationsite St. 1 (or NP0)) in September 2013. 90 Sr and 137 Cs release from the FDNPP could be related to thetidal cycle and weather conditions, which caused a temporal variation of the released 90 Sr/137 Cs ratio
from the FDNPP site.

Figure 4. The 90 Sr/137 Cs activity ratios in the environment and the FDNPP site. The 90 Sr/137 Cs activity
ratio in seawater near the FDNPP was consistent with those from the monitoring points, T1 and T2 [12].
Soil [4] and sediment [24] samples had extremely low 90 Sr/137 Cs activity ratios.

The slope of a linear regression ﬁtting (0.66) was similar to the reported 90 Sr/137 Cs activity ratios
in stagnant water of 0.78 and 0.88, respectively, in July and August of 2013 [5]. The stagnant water
samples were collected from the sampling line behind the mixing point of water from each reactor
building [4,5] (Figure 5). These radionuclides were thought to mainly be derived from the reactor
building of unit 2 on the basis of the initial data for stagnant water in the unit 2 turbine building [2],which was severely damaged. The 90 Sr/137 Cs activity ratio in stagnant water varied depending on
the decontamination of 134, 137 Cs, and gradually increased from the direct-release event in March 2011(0.0256 ± 0.0006 [15]). The 90 Sr/137 Cs activity ratio of seawater in this study is slightly lower than thatof stagnant water, although the most possible source candidate is the continuous release of stagnant
water from the FDNPP.
The discrepancy between our data and monitoring data at T1 (1.25 ± 0.71) implies multiple
sources exist at the FDNPP site. The higher 90 Sr/137 Cs at the T1 site could reﬂect a contribution from185

IJERPH 2019, 16, 4094

90 Sr-rich groundwater. Groundwater around the reactor buildings had a 90 Sr/137 Cs activity ratio(2.4 × 104 [5]) that was 5 orders of magnitude higher than the seawater value observed in this study.
The decontaminated water in storage tanks in the FDNPP was also observed to have high 90 Sr/137 Cs
activity ratios.

Figure 5. FDNPP site-derived 90 Sr and 137 Cs activities in surface seawater with 90 Sr/137 Cs ratio forpossible sources. The lower and upper red solid lines show 90 Sr/137 Cs ratios for stagnant water in thereactor building in July 2013 (0.78) and August 2013 (0.88), respectively [6]. Core inventory (0.74) was
estimated by the ORIGEN2 code [2]. Shaded areas were averaged monitoring data at T1 (1.25 ± 0.71)
and T2-1 (0.31 ± 0.14) sites from January 2013 to October 2013.

The ﬁtted regression line had an x-intercept of 5.8 mBq L−1 . A very low 90 Sr/137 Cs ratio (0.16) was
observed at S6 without a change in salinity. These results indicate that there is a missing source forthe site with a low 90 Sr/137 Cs ratio. In the coastal region, salinities ranged from 33.2 to 33.3 psu andshowed no correlation with activities of 90 Sr and 134, 137 Cs. Atmospherically deposited 90 Sr on landsoil in March 2011 was at a lower level (<1.1 Bq g−1 ) than 137 Cs, where the 90 Sr/137 Cs activity ratio wasconsidered to be 0.00008−0.017 [1] (Figure 5). Higher mobility of 90 Sr has been recognized, but 90 Sr
activity in water of the Fukushima River was less than 4 mBq L−1 in 2012 [6]. 137 Cs activity ranged
from 12 to 190 mBq L−1 , which yielded a low 90 Sr/137 Cs activity ratio of 0.01–0.04 [6]. Considering the
90 Sr/137 Cs activity ratio in seawater, riverine input from the land to the ocean was minor for 90 Sr,
though dissolved 90 Sr activity in the Ukedo River was never reported.
A possible supply process for 137 Cs is the release from seabed sediments. Some amount of Cs could
be scavenged by seabed sediments through adsorption onto particles, such as clay minerals [25–27]
during the direct discharge event. The sedimentary 137 Cs inventory of 100–200 TBq represents only
1%–3% of the total discharge from the FDNPP to the Paciﬁc Ocean in 2011 [28,29]. Approximately 80%of the total 137 Cs sedimentary inventory was found in coastal sediments at less than 150 m water
depth [29]. The highest 90 Sr activity of 63 Bq kg-dry−1 in seabed sediments was observed near the south
discharge gate of the FDNPP site (T2 monitoring point) in September 2011 [6]. Sedimentary 90 Sr/137 Cs
activity ratios observed after the accident ranged from 0.001 to 0.08, which were lower than thosein seawater. 137 Cs could be attributed to the direct discharge event in late March to April 2011 [20].
186

IJERPH 2019, 16, 4094

The extremely low 90 Sr/137 Cs ratio indicates that the contribution of 90 Sr in seawater from the soil andseaﬂoor sediments is less than that of 137 Cs, even if there is a higher mobility for Sr than for Cs in thesoil and sediments.
Another possible low 90 Sr/137 Cs source is contaminated water that remained in a tunnel for pipes
and cables, which were connected to the turbine buildings of units 2 and 3. Contaminated waterin the turbine and reactor buildings was released into the ocean via the tunnel and cracks resulting
from the earthquake and tsunami. During this direct release event, the 90 Sr/137 Cs ratio was very low
0.0256 ± 0.0006 [15] (Figure 5). 137 Cs activity at T1 reached 68 kBq L−1 [20]. After the direct release wasstopped in early April 2011 by sealing cracks and the tunnel entrance, contaminated water could havebeen left in the tunnel until July 2015. Such highly contaminated water could be the source of the low
90 Sr/137 Cs ratio.
The 90 Sr/137 Cs activity ratio of 0.66 ± 0.05 observed in this study was higher than data at themonitoring point, T2-1, near the south discharge gate (0.31 ± 0.14) [6] from January to December
2013, but was lower than that at T1 near the north discharge gate (1.25 ± 0.71) [6] (Figure 5). A large
variation of 90 Sr/137 Cs at T1 was observed, which might reﬂect the local input processes of 90 Sr and
137 Cs. A much higher 90 Sr/137 Cs activity ratio (e.g., 90 Sr activity of 7.5 Bq L−1 and 90 Sr/137 Cs activity
ratio of 3.2 on 26 June 2013) was observed by TEPCO in the harbor [6] than the coastal region as
observed in this study. The variation in 90 Sr/137 Cs activity ratios might reﬂect the spatial and temporal
heterogeneities of released water.
As mentioned above, the similarity of the 90 Sr/137 Cs activity ratio between seawater and thestagnant water supported the idea that the most likely candidate was the continuous release fromthe reactor buildings of the FDNPP. Both high 90 Sr activity and 90 Sr/137 Cs activity ratio in the coastal
region reﬂect the input of the stagnant water. Variability of 90 Sr/137 Cs activity ratios in seawater is an
important indicator to understand the status of the release of contaminated water from the FDNPP.
Unfortunately, the contribution of underground water near the reactor buildings, and released fromsediments to the harbor water, could not be distinguished from the release of the reactor buildings on
the basis of seawater obtained from outside of the harbor. More detailed temporal and spatial data in
the harbor and for other radionuclides such as tritium (3 H) and iodine-129 (129 I) are necessary.
5.3. Estimation of 90 Sr Input to the Ocean from the FDNPPThe continuous release from the FDNPP was the main source to the Fukushima coast. The amountof 137 Cs released daily to the ocean was estimated to be from 8.1 GBq day−1 [7] to 30 GBq day−1 [8]in 2012 on the basis of simulation of the 137 Cs activities of seawater in the harbor and at the northdischarge gate, respectively. We examined the amount of released 90 Sr based on that of 137 Cs in 2013by using Equation (1):
NSr−90 = NCs−137 ×


CSr−90CSr−90= CCs−137 × F ×
CCs−137 SW
CCs−137 SW(1)where N, C, and F represent release rate, activity, and conversion factor from activity to daily release
rate of 137 Cs, respectively. For the estimation of daily released 137 Cs, the activities of 137 Cs at T2-1
300 m south of the south discharge gate were used (Table 3) [6]. Most of the 137 Cs activities were lower
than the MDA (1.2–1.5 Bq L−1 ). To avoid overestimation of the averaged 137 Cs activity, we used only
precise analysis data. The 137 Cs activity at the T2-1 site ranged from 0.14 to 0.98 Bq L−1 and showed
considerable variation (mean value = 0.60 ± 0.35 Bq L−1 ). The conversion factors, F, from activity todaily release rate of 137 Cs were obtained on the basis of the amount of released 137 Cs in the direct
release event of March 2011 and 137 Cs activities at the T2-1 site [7,20]. The conversion factor applied
was 25.5 × 109 [20] for the T2-1 site.

187

IJERPH 2019, 16, 4094

Table 3. Estimation of the release rates for 90 Sr and 137 Cs into the ocean from the FDNPP site in May
2013. C: activity; F: conversion factor; N: release rate.
Monitoring Point

CCs−137 (Bq L−1 )(Jan. to Oct. 2013)

F(×109 L day−1 )NCs−137(GBq day−1 )( CCSr−90 )NSr−90(GBq day−1 )T2-1

0.60 ± 0.35 [6]25.5 [20]15.3 ± 8.9

0.63 ± 0.05

9.6 ± 6.1

Cs−137SW

The resulting daily released amount of 90 Sr was 9.1 ± 6.1 GBq day−1 during our sampling campaign
in May 2013. The observed 90 Sr activity in the coastal region was too low to disturb the ecologicalsystem and aﬀect the background radiation dose, as mentioned above. Continuous release could
increase the inventory of 90 Sr in the Paciﬁc Ocean. If the constant release (9.1 GBq day−1 ) continued
over the year, the annual release rate would be estimated at 3.3 TBq yr−1 , which is small relative tothe inventory of 105 PBq in the ocean [3]. However, 90 Sr in seawater should be closely observed todetect any unexpected release from the nuclear reactor buildings and the contaminated water storage
tanks. This estimation needs to assume a stable release rate from the single source. As discussed
above, the low 90 Sr/137 Cs source contributed to seawater around the FDNPP. Therefore, this result
could be overestimated.
In this study, the 90 Sr/137 Cs activity ratio of 0.66 ± 0.05, which was inﬂuenced by continuous releasefrom the FDNPP, was distinguished based on precise 90 Sr analysis. Buesseler et al. [11,30] suggested
that the possible source of 137 Cs was not only continuous release from the FDNPP but also the input
from subsurface groundwater [31], river water [32], and desorption from the marine sediments in the
coastal region [29,30,33]. The environmental migration of 137 Cs through particulate and dissolved
ﬂuvial inputs, and remineralization from the sediments contaminated by direct discharge of stagnant
water from 26 March to 6 April 2011, must also be taken into consideration. 90 Sr/137 Cs activity ratios
could ﬂuctuate according to the source in the FDNPP area and remobilization of 137 Cs in coastal
water. In addition to monitoring for ongoing release from the reactor buildings and possible leakage ofstored contaminated water in tanks, continuous measurement of 90 Sr is necessary for investigation of
the migration of 137 Cs in the marine environment. A combination of other ﬁssion product nuclides,
129 I and 3 H activity, will provide precise information for the current status of leakages from stagnant
water, groundwater, and stored water in tanks.
5.4. Estimation of Eﬀective Dose Rate by Ingestion from Marine Products
90 Sr dispersion to the coastal area is the most serious issue for ﬁsheries due to its radiotoxicity.

We estimated the dose impact to human health from marine products. The highest 90 Sr activity(29.13 mBq L−1 at AN7; Table 1) was comparable to typical levels for North Paciﬁc surface seawaterin the early 1960s during nuclear weapons testing [34]. Taking into consideration the processes in
the food chain and the highest activity in the coastal water observed in this study (29.13 mBq L−1 atAN−7), we obtained Equation (2):(2)
D = C × CF × IR × F
where D is representative of the annual dose rate. C, CF, IR, and F are representative of the 90 Sr activity
in seawater, the concentration factor from seawater to marine products (5–10 [35]), the intake rate ofmarine products (28.4 kg yr−1 [36]), and dose coeﬃcient (2.8 × 10−8 Sv/Bq [37]), respectively. It should
be noted that these concentrations are quite small (0.23 μSv yr−1 ) compared with the International
Commission on Radiological Protection (ICRP) limit of 1 mSv yr−1 for a member of the general public.
Much higher 90 Sr activities were observed at monitoring points near the south (150−670 mBq L−1 ) andnorth (260−5800 mBq L−1 ) discharge gates [6]. Even this anomalously high 90 Sr activity (5800 mBq L−1 )close to the FDNPP would contribute 46 μSv yr−1 to the annual eﬀective dose rate by marine products.

188

IJERPH 2019, 16, 4094

6. Conclusions
90 Sr is useful as a tracer for continuous releases from the FDNPP site. We reported 90 Sr data inseawater along with 134 Cs and 137 Cs in samples collected in the coastal area oﬀ Fukushima Prefecture.
Released 90 Sr was dispersed along the Fukushima coast, and the highest 90 Sr activity was 29.13 mBq L−1
at a sampling site 16 km south of the FDNPP. FDNPP site-derived 90 Sr/137 Cs ranged from 0.16 to
0.64 and the slope of a linear regression ﬁtting of the relationship of Fukushima site-derived 90 Sr and
137 Cs was 0.66 ± 0.05, which was similar to the ratio of contaminated water in the FDNPP reactor
and turbine buildings. These results suggest that the major contamination source is contaminatedwater in the FDNPP buildings. On the other hand, the l37 Cs-rich source could also aﬀect seawater andcause temporal and spatial variations. The estimated release rate of 90 Sr (9.6 ± 6.1 GBq day−1 ) was
small relative to the inventory of 90 Sr in the Paciﬁc Ocean. Release of 90 Sr has been controlled by thewater shielding wall between the reactor buildings and the harbor since 2015. However, our results
imply that if any accidental release of radionuclides, including 90 Sr from the FDNPP, occurs duringdecommissioning of the reactors, the coastal area can be exposed to a high activity plume.

Author Contributions: Conceptualization, H.T. and M.Y.; methodology, H.T. and H.O.; investigation, H.T;
data curation, H.T., T.Y., K.T., and H.N.; writing—original draft preparation, H.T.; writing—review and editing,
H.O, D.T., and J.K.; visualization, H.T.; supervision, M.Y.; project administration, H.T.; funding acquisition, H.T. All
authors interpreted the data. All authors provided ﬁnal approval of the version of the manuscript for publication
and agreed to be accountable for all aspects of the work.
Funding: This work was supported by JSPS KAKENHI (grant numbers: 24110004 and 26340019).
Acknowledgments: We would like to thank the captain, crew, and scientiﬁc party of the UM-13-5 cruise by the
RTV Umitaka-Maru for their collaboration in sampling.
Conﬂicts of Interest: The authors declare no conﬂicts of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleIsotope Composition and Chemical Species ofMonthly Precipitation Collected at the Site of a
Fusion Test Facility in Japan
Naofumi Akata 1, *, Masahiro Tanaka 2 , Chie Iwata 3 , Akemi Kato 3 , Miki Nakada 3 ,Tibor Kovács 4 and Hideki Kakiuchi 5
1
2
3

4
5

*

Department of Radiation Chemistry, Institute of Radiation Emergency Medicine, Hirosaki University,
Hirosaki 036-8564, Japan
Department of Helical Plasma Research, National Institute for Fusion Science, National Institutes of Natural
Sciences, Toki 509-5292, Gifu, Japan; tanaka.masahiro@nifs.ac.jp
Department of Engineering and Technical Services, National Institute for Fusion Science, National Institutesof Natural Sciences, Toki 509-5292, Gifu, Japan; iwata.chie@nifs.ac.jp (C.I.); kakemi@nifs.ac.jp (A.K.);
nakada.miki@nifs.ac.jp (M.N.)
Institute of Radiochemistry and Radioecology, University of Pannonia,
H-820010 Egyetem Str, Veszprém, Hungary; kt@almos.uni-pannon.hu
Department of Radioecology, Institute for Environmental Sciences, Aomori 039-3212, Japan; ckhsd@ies.or.jp
Correspondence: akata@hirosaki-u.ac.jp; Tel.: +81-173-39-5405

Received: 6 September 2019; Accepted: 9 October 2019; Published: 14 October 2019

Abstract: The deuterium plasma experiment was started using the Large Helical Device (LHD)at the National Institute for Fusion Science (NIFS) in March 2017 to investigate high-temperatureplasma physics and the hydrogen isotope eﬀects towards the realization of fusion energy. In orderto clarify any experimental impacts on precipitation, precipitation has been collected at the NIFS
site since November 2013 as a means to assess the relationship between isotope composition andchemical species in precipitation containing tritium. The tritium concentration ranged from 0.10 to
0.61 Bq L−1 and was high in spring and low in summer. The stable isotope composition and thechemical species were unchanged before and after the deuterium plasma experiment. Additionally,
the tritium concentration after starting the deuterium plasma experiment was within three sigma of
the average tritium concentration before the deuterium plasma experiment. These results suggested
that there was no impact by tritium on the environment surrounding the fusion test facility.
Keywords: tritium monitoring; fusion test facility; deuterium plasma experiment; monthly
precipitation; chemical composition

1. Introduction
The sources of environmental tritium (3 H), a radioisotope of hydrogen that decays to 3 He with ahalf-life of 12.3 years, have been summarized by researchers [1–3]. Most naturally sourced tritium
is produced by the interaction of cosmic rays with nitrogen (14 N) and oxygen (16 O) atoms in theupper atmosphere. The tritium production rate by cosmic rays is estimated as 0.25 atoms cm−2 s−1 [2].
The global production rate of natural tritium is 72 × 1015 Bq y−1 if it is assumed that surface areaof the earth is 5.1 × 1014 m2 . On the other hand, anthropogenic 3 H arises from several sources.
Atmospheric nuclear weapon testing from the 1950s to the early 1960s released signiﬁcant amounts oftritium into the environment [2], and approximately 1.86 × 1020 Bq (650 kg) of tritium was released
during 1945 to 1985 [4]. Tritium concentrations in precipitation were rapidly increased by these
events, and many researchers found high tritium concentrations in precipitation [5,6]. Even now,
residual artiﬁcial tritium is estimated to be approximately 1018 Bq. Nuclear facilities such as nuclear
IJERPH 2019, 16, 3883; doi:10.3390/ijerph16203883

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IJERPH 2019, 16, 3883

power reactors and nuclear fuel reprocessing plants also release tritium to the environment, and they
have become the dominant anthropogenic source. Annual average amounts of released tritium from
nuclear facilities worldwide to the atmosphere were estimated to be 11.7 × 1015 Bq during the period
from 1998 to 2002 [4]. This amount corresponds to approximately 15 to 20% of the annual tritium
production rate by cosmic rays. The amount of tritium on the earth was estimated at approximately
1.0–1.3 × 1018 Bq and is dependent on the balance between production rate and radioactive decay rate.
Accident-released tritium is also important for the natural environment. After the Chernobyl Nuclear
Power Plant accident and the Fukushima Dai-ichi Nuclear Power Plant accident, elevated tritium inenvironmental samples was observed [7,8]. In the case of Japan, Nakasone et al. [9] concluded that
tritium concentrations in monthly precipitation were increased by nuclear weapon testing and the
Fukushima Dai-ichi Nuclear Power Plant accident. In the future, nuclear fusion reactors will have alarge inventory of tritium as fuel. The fuel of nuclear fusion reactors would be the hydrogen isotopes,
deuterium (D) and tritium (T). In the 1990s, the Tokamak Fusion Test Reactor (TFTR) in New Jersey, USA
and the Joint European Torus (JET) in Oxfordshire, UK were used to carry out D–T plasma experiments.
Although the inventory of tritium in these facilities was less than 10 g and tritium in the facilities
was conﬁned using a safety system, tritium concentrations in their surrounding environments wereslightly increased [10]. The International Thermonuclear Experimental Reactor (ITER) is anotherinternational nuclear fusion research and engineering project, and a large experimental tokamak
nuclear fusion device designed to study fusion plasmas of D–T reaction is now under construction inSaint-Paul-lès-Durance, France [11]. It is envisioned to be the next major step in the world’s fusion
programs. Within the ITER, a total inventory of about 2 to 3 kg (1018 Bq) will be necessary to implement
the D–T reaction [12]. Therefore, it is important to understand the tritium level in a surrounding
environment before and after facility operation starts [13].
The Large Helical Device (LHD) was constructed by the National Institute for Fusion Science(NIFS) at Toki City, Gifu Prefecture, and it is one of the world’s largest magnetically conﬁned helicaltype fusion experimental devices [14]. The deuterium plasma experiment using LHD was started there
in March 2017 to investigate high-temperature plasma physics and the hydrogen isotope eﬀects [14].
A small amount of tritium was produced by a fusion reaction in the deuterium plasma experiment.
Although the deuterium and the tritium gases were exhausted from the vacuum vessel of the LHD
and recovered by the exhaust detritiation system (EDS) [15], a part of the tritium was released into
the environment through the main stack. In the ﬁrst year of the deuterium plasma experiment, theannual tritium yield was permitted up to 3.7 × 1010 Bq for commissioning of the deuterium plasma
experiment. The amount of tritium released from the stack was monitored, and the total amountof tritium released during the ﬁrst year of the deuterium plasma experiment (from 6 March 2017 to
31 March 2018) was approximately 0.13 × 109 Bq [16]. This value was negligibly small comparedwith the permitted annual tritium yield (3.7 × 1010 Bq). The tritium concentrations in environmental
samples (environmental water, air, vegetation, etc.) were monitored before and after the deuterium
plasma experiment to assess the impact of released tritium [17–21]. The tritium concentration levels
were within the background range of the environmental variation. As part of the environmental tritium
monitoring, tritium concentration and chemical composition in monthly precipitation and radioactive
materials in monthly total deposition samples were monitored.
In order to clarify the experimental impact on precipitation, precipitation has been collected at the
NIFS site in Toki, Japan since November 2013 as a means to assess the relationship between isotope
composition and chemical species in precipitation with tritium concentration. Partial data of tritium
concentration and stable isotope ratio in precipitation before the deuterium plasma experiment havealready been reported [21]. This paper reports isotope composition and chemical characteristics ofmonthly precipitation collected at Toki and discusses the impact of the ﬁrst year of the deuterium
plasma experiment in the LHD on the surrounding environment.

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IJERPH 2019, 16, 3883

2. Materials and Methods
2.1. Overview of Study Site
The study sampling site was on the roof of a building at the NIFS at Toki City, Gifu Prefecture(35◦ 19 N, 137◦ 10 E). Figure 1 shows the sampling location. Toki City is located approximately
30 km northeast of Nagoya City in the central region of Japan. Toki is located in a small-scale basin,
approximately 10 km in diameter, and it is surrounded by low elevation mountains. The Meteorological
Agency has reported average weather conditions for 30 years (1981–2010) observed at the Tajimi
AMeDAS (Automated Meteorological Data Acquisition System) site, which is located 6 km northwestof NIFS [22]. The average monthly precipitation was high in summer and low in winter, while theaverage wind speed was lower than 1.0 m s−1 in that time period. Average monthly temperature
ranged from 2.9 to 27.4 ◦ C [23].

Figure 1. Maps showing location of the sampling site.

2.2. Sample Collection and Analysis
Monthly precipitation was collected at NIFS. Precipitation samples were collected from
November 2013 to the end of 2017 using a precipitation sampler (ST-1F, Suntechno, Tokyo, Japan) witha 10 L polyethylene container that had been washed with pure water. After measuring sample weight,
pH (B-211, Horiba, Kyoto, Japan) and electrical conductivity (EC) (E-771, Horiba) were measured.
Approximately 1 L of sample water was distilled, and 800 mL of distilled sample water was electrolyzed
to a volume of 65 mL to enrich its tritium content using an electrolytic enrichment system with asolid polymer electrolyte membrane (XZ001, De Nora Permelec Ltd. Fujisawa, Japan). After distilling
the tritium-enriched sample water, 50 mL of sample water was mixed with the same volume of aliquid scintillation cocktail (Ultima Gold LLT, PerkinElmer, Waltham, MA, USA) in a 145 mL low
diﬀusion polyethylene vial with an inner Teﬂon coating. Tritium radioactivity was measured with a
low background liquid scintillation counter (LSC: LSC-LB5 or LSC-LB7, Hitachi, Tokyo, Japan) for1500 min. Counting eﬃciencies were determined using standard tritium solution (SRM 4361C, NIST,
Gaithersburg, MD, USA). The minimum detection level (MDL) of LSC-LB5 and LSC-LB7 with theelectrolytic enrichment system was approximately 0.04 Bq L−1 . Measured values were corrected forradioactive decay to the middle of the sampling period [21].
A part of each sample was ﬁltered using a 0.45 μm membrane ﬁlter (DISMIC 25CS045AS,ADVANTEC, Tokyo, Japan). The ionic species (Cl− , NO3 − , SO4 2− , Na+ , Mg2+ , K+ , Ca2+ , NH4 + ) in theﬁltered samples were determined by ion chromatography (ICS-2100, Dionex, Sunnyvale, CA, USA).
The Gard column and the Separation column produced by Dionex Inc. were used Ion Pac AG17
4 × 50 mm and Ion Pac AS19 4 × 250 mm for anion analysis and Ion Pac CG16 5 × 50 mm and Ion Pac
CS16 5 × 250 mm for cation analysis. We used anion mixed standard solution and cation mixed standard
solution (Kanto Chemical Co. Inc. Tokyo, Japan) for quality control. Stable isotope analysis was
performed using both an isotope ratio mass spectrometer (Delta V Advantage, Thermo Fisher Scientiﬁc,Waltham, MA, USA) with a water equilibrium device (Nakano Electric Inc. Kyoto, Japan) and a cavity
ring-down spectroscopy isotopic water analyzer (model L1102-i, Picarro Inc. Sunnyvale, CA, USA)195

IJERPH 2019, 16, 3883

with a CTC analytics autosampler (HTC-PAL, Leap Technologies, Carrboro, NC, USA). Measurement
precision was better than ± 1.5‰ for δD and ± 0.15‰ for δ18 O.
3. Results and Discussion
3.1. Tritium Concentration in Precipitation

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Figure 2 shows the monthly variations of precipitation data collected at Toki during the sampling
period; they are precipitation amount (A), pH (B), EC (C), and tritium concentration (D). Monthly
precipitation amount ranged from 26 to 363 mm and was high in summer and low in winter. Annual
precipitation amounts in 2014, 2015, 2016, and 2017 were 1515, 1435, 1550, and 1626 mm with thearithmetic mean value of 1532 mm. Average annual precipitation amount for 30 years (1981–2010)
was 1626.7 mm [22], and the value in 2017 was comparable to the reported value, while those of 2014,2015, and 2016 were slightly lower than the reported values. The pH data ranged from 4.3 to 6.9, andabout 56% of the samples were in the range of acid rain with the pH < 5.0. The EC ranged from 5 to28 μS cm−1 . There was no clear seasonal trend for either pH or EC.

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Figure 2. Monthly variations of precipitation amount (A), pH (B), electrical conductivity (EC) (C), andtritium concentration (D) in precipitation collected at Toki, Japan before (2013–2016) and after (2017)
the ﬁrst campaign of the deuterium plasma experiment.

The tritium concentration in the monthly precipitation ranged from 0.10 to 0.61 Bq L−1 andwas high in spring and low in summer. Annual tritium concentrations (arithmetic mean ± standard
deviation) in 2014, 2015, 2016, and 2017 were 0.35 ± 0.14, 0.30 ± 0.08, 0.30 ± 0.13, and 0.32 ± 0.13 Bq L−1 .
Recent data for tritium concentration in monthly precipitation in Japan have been summarized [9,24,25].
It is known that the concentration of environmental tritium depends on the latitude of the sampling
location; it is high at northern latitudes and low at southern latitudes [26,27]. For example, tritium
concentration in monthly precipitation in Sapporo (northern Japan) during July 2015 to December
2017 ranged from 0.24 to 1.27 Bq L−1 [9], that of Rokkasho during April 2001 to March 2006 ranged
from 0.16 to 1.23 Bq L−1 [28], that of Chiba during November 2013 to December 2017 ranged from
0.12 to 0.53 Bq L−1 [24], and that of Okinawa (southern Japan) during June 2014 to December 2017
ranged from 0.05 to 0.27 Bq L−1 [9]. The results of the present study were similar to those of Chiba,
which is at a similar latitude. The seasonal trend for tritium concentration in precipitation was
similar to the general background pattern observed in Japan, which is high in spring and low insummer [27]. The northwestern monsoon from the Asian continent blows into Japan during winter tospring. A relatively higher tritium concentration in precipitation was observed in inland continental
areas due to recycling of tritium by evaporation and precipitation, the so-called continental eﬀect [29].
On the other hand, high-pressure systems develop in the Paciﬁc Ocean in summer and bring air masses
to Japan from the ocean, which have slightly lower tritium concentration [28]. Tritium concentration inprecipitation at Toki changed with meteorological conditions depending on the air-mass transportation

196

IJERPH 2019, 16, 3883

course. The transfer of cosmogenic tritium from the upper atmosphere to the troposphere in springalso seemed to contribute to the seasonal pattern observed.
3.2. Stable hydrogen and Oxygen Isotope Composition in Precipitation
The seasonal variations of δD and δ18 O in monthly precipitation at Toki are shown in Figure 3A
with the monthly precipitation amount, and the reported monthly average temperature at Tajimi
AMeDas site [22] is shown in Figure 3B. δD and δ18 O in monthly precipitation ranged from −103.62 to−20.77‰ and −15.14 to −3.92‰, respectively. Although precipitation amount and average temperature
had a clear seasonal trend, which was high in summer and low in winter, there was no clear seasonalchange in δD and δ18 O. A weak seasonal change of δD and δ18 O in precipitation was reported to havebeen observed in the East Asian region [30]. The present results had a similar seasonal trend to thisreported one.

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Figure 3. Variations of δD and δ18 O in monthly precipitation collected at Toki, Japan with monthly
precipitation amount (A) and the reported monthly average temperature at the Tajimi AMeDas site (B).

In general, δD and δ18 O in global precipitation are well-related by the following equation.
dD = 8.0 × δ18 O + 10

(1)

This equation, called the global meteoric water line (GMWL), is based on precipitation datacollected worldwide [31]. Figure 4 shows the relationship between δD and δ18 O in monthly precipitationcollected at Toki, Japan. The slope of the regression line (δD = 7.5 × δ18 O + 10.6) of precipitation at
Toki was similar to the slope of the GMWL. Additionally, the reported equation based on observationsin the Kanto area of Japan (Kumagaya, Saitama: δD = 7.4 × δ18 O + 9.6, r2 = 0.868) [32] was also similar
to our equation. Here, the intercept of GMWL is known as the deuterium excess (d-excess), and its
equation is as follows [33].
d − excess = δD − 8 × d18 O(2)

The d-excess value is used as a convenient tool for describing conditions aﬀecting evaporationin oceanic moisture source regions. There have been some reports about seasonality of d-excess inprecipitation in Japan [34,35]. In general, high d-excess indicates lower relative humidity in the maritime
air-mass source region [36]. Figure 5A shows the variation of d-excess in monthly precipitation collectedat Toki with precipitation rate, and Figure 5B shows the reported monthly average temperature at theTajimi AMeDas site [22]. The d-excess had clear seasonal variation and was high in winter and low insummer; d-excess and average temperature were negatively correlated (r2 = 0.647). As mentioned
before, the northwestern monsoon from the Asian continent blows onto the Japanese islands during
winter to early spring and carries a dry air-mass with water vapor evaporated rapidly from the Japan197

IJERPH 2019, 16, 3883

Sea. On the other hand, high-pressure systems develop in the Paciﬁc Ocean in summer and bringair-masses from the southern maritime area. This seasonal variation is a general trend seen in Japan,
and the present d-excess value was comparable to the reported value [35]. No impact was found fromthe deuterium plasma experiment on the environment.
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Figure 4. Relationship between δD and δ18 O in monthly precipitation collected at Toki, Japan and aplot of the global meteoric water line.

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Figure 5. Variation of deuterium excess (d-excess) in monthly precipitation collected at Toki, Japan
with monthly precipitation amount (A) and the reported monthly average temperature at the Tajimi
Automated Meteorological Data Acquisition System (AMeDas) site (B).

3.3. Ion Concentrations in Precipitation
Concentrations of anions and cations in precipitation collected at Toki are shown in Figure 6.
Concentration ranges of the anions were Cl− , 0.19 to 1.06 mg L−1 ; NO3 − , 0.35 to 3.06 mg L−1 ; andSO4 2− , 0.41 to 2.35 mg L−1 . The ranges of cations were Na+ , 0.08 to 0.66 mg L−1 ; NH4 + , 0.03 to
0.68 mg L−1 ; K+ , <0.05 to 0.20 mg L−1 ; Mg2+ , <0.05 to 0.10 mg L−1 ; and Ca2+ , 0.11 to 0.62 mg L−1 .
Seasonal variations of Cl− , Na+ , and Mg2+ were a high concentration in winter and a low one insummer. Those of NO3 − , SO4 2− , and NH4 + were a high concentration in spring and a low one inother seasons. The correlation coeﬃcients of ion concentrations in monthly precipitation at Toki, Japanare shown in Table 1. The relationship between Na+ and Cl− concentrations was found to have astrong correlation (r = 0.97, p < 0.01), and the Na+ /Cl− concentration ratio was similar to their ratio
in seawater, and Mg2+ and Cl− also showed a good correlation (r = 0.81, p < 0.01). It was suggested
that Na+ , Cl− and Mg2+ originated from seawater. A good correlation was found between NO3 − ,SO4 2− , and NH4 + (r > 0.80, p < 0.01). It was reported that main anthropogenic sources of NH4 NO3 arebiomass burning, fossil fuel combustion, and gas to particle conversion, and those of (NH4 )2 SO4 are198

IJERPH 2019, 16, 3883

biomass burning, fossil fuel combustion, vehicle exhaust, and gas to particle conversion [37]. In spring,the continental air-mass is coming to Japan. The present species concentration results indicated that
NO3 − , SO4 2− , and NH4 + were transported from the Asian continent to Japan as long-range transported
pollutants. In May 2017, NO3 − , SO4 2− , NH4 + , and Ca2+ were seen to rapidly increase. The Japan
Meteorological Agency reported that a large-scale Asian dust event known as kosa was observed on the
7th and the 8th of May 2017 near the sampling site [38]. From these results, NO3 − , SO4 2− , and NH4 +were thought to have been transported by the kosa in the chemical forms of NH4 NO3 and (NH4 )2 SO4 .
It seemed that there was no impact from the deuterium plasma experiment on the chemical species in
the precipitation.
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Figure 6. Variation of anion and cation concentrations in monthly precipitation collected at Toki, Japan.
Table 1. Correlation coeﬃcients of ion species in monthly precipitation collected at Toki, Japan.

Cl−
SO4 2−
NO3 −
Na+
NH4 +
K+
Mg2+

SO4 2−

NO3 −

Na+

NH4 +

K+

Mg2+

Ca2+

0.28

0.21
0.85

0.97
0.30
0.20

0.23
0.80
0.84
0.21

0.10
0.42
0.26
0.10
0.19

0.81
0.30
0.28
0.79
0.11
0.04

0.56
0.56
0.62
0.54
0.60
0.17
0.68

199

IJERPH 2019, 16, 3883

3.4. Environmental Assessment of Impact from the Deuterium Plasma Experiment
After starting the ﬁrst campaign of the deuterium plasma experiment in April 2017, a part ofthe produced tritium was released into the atmosphere through the facility stack [16]. Here, theimpact of the experiment on monthly precipitation is discussed. After starting the deuterium plasma
experiment, tritium concentration in precipitation ranged from 0.17 to 0.47 Bq L−1 , which was similar
to the concentration range before the experiment, and the seasonal variation was similar too (Figure 2).
All data were within three sigma of the average tritium concentration before the deuterium plasma
experiment [21]. From this result, it was suggested that there was no impact by tritium on thesurrounding environment of the fusion test facility.
The survey of deuterium in precipitation is also important to assess the impact from the deuterium
plasma experiment, because deuterium gas is used as fuel gas [21]. The unit of tritium concentration
usually used is the tritium unit (1 TU = 0.118 Bq L−1 ). Figure 7 shows the relationship between tritium
concentration (TU) and δD in precipitation at Toki. The values were in the same area of the graph before
and after the deuterium plasma experiment. This also suggested that there were no impacts by tritiumand deuterium on the surrounding environment of the fusion test facility after the deuterium plasma
experiment. Additionally, these results supported those reported by Tanaka et al [20]. A committed
eﬀective dose equivalent of 6.2 × 10−6 mSv y−1 was estimated for an annual consumption of drinking
water having the highest tritium concentration in precipitation after starting the deuterium plasma
experiment (0.47 Bq L−1 ) by using a dose conversion factor of 1.8 × 10−11 Sv/Bq [39] and a daily water
intake rate of 2.0 L [40]. This value was negligibly small compared with 1 mSv, which is the index of
the annual dose limit for the general public.
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Figure 7. Relationship between tritium concentration (TU) and δD in precipitation at Toki.

4. Conclusions
The deuterium plasma experiment using the LHD was started in March 2017 to investigate
high-temperature plasma physics and the hydrogen isotope eﬀect. Although deuterium and tritium
gas were exhausted from the vacuum vessel of the LHD and recovered by the exhaust detritiation
system, a small amount of hydrogen gas was released into the atmosphere through the main stack.
To assess the impact of released tritium to precipitation, monthly precipitation had been monitored at
the NIFS site from November 2013 to establish background values for tritium, hydrogen, and oxygen
stable isotope compositions and chemical species. The tritium concentration ranged from 0.10 to
0.61 Bq L−1 and was high in spring and low in summer. δD and δ18 O in monthly precipitation ranged
from −103.62 to −20.77‰ and −15.14 to −3.92‰, respectively. There was no clear seasonal change inδD and δ18 O, and the ﬁndings were similar to reported seasonal data. The slope of the line showing
the relationship between δD and δ18 O in monthly precipitation (δD = 7.5 × δ18 O + 10.6) was similar tothe slope of GMWL. The d-excess showed clear seasonal variation, which was high in winter and low
in summer; d-excess and average temperature were negatively correlated (r2 = 0.647). As a result of200

IJERPH 2019, 16, 3883

ion species measurements, NO3 − , SO4 2− , and NH4 + were determined to have been transported fromthe Asian continent to Japan as NH4 NO3 and (NH4 )2 SO4 .
Tritium concentration in precipitation after starting the deuterium plasma experiment was within
three sigma of the average tritium concentration before the deuterium plasma experiment. There wasno clear change in stable isotope composition and chemical species. From this, it seemed that there
was no impact from tritium on the surrounding environment of the fusion test facility. The committed
eﬀective dose equivalent from drinking water to local residents after the deuterium plasma experiment
was calculated to be negligibly small compared with the annual dose limit of 1 mSv. We plan to survey
continuously until shutdown of LHD.
Author Contributions: Conceived and designed the survey: N.A., M.T., T.K., H.K. Performed experiments: N.A.,
C.I., A.K., M.N. Analyzed the data: N.A., C.I., M.N. Wrote the paper: N.A., T.K. Acquired the funding: N.A.
Contributed to discussions: N.A., M.T., T.K., H.K.
Funding: This research was funded by the NIFS budget 10203004ULAA024, JSPS KAKENHI Grant Number
17K00559 and 17KK0015, and Hungarian National Research OTKA Grant No K128805.
Acknowledgments: The authors are grateful to T. Saze, H. Miyake and T Nishimura (National Institute for Fusion
Science) for their important support and discussions.
Conﬂicts of Interest: The authors declare that they have no conﬂicts of interest.

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International Journal ofEnvironmental Researchand Public Health
ArticleEvaluation of Environmental Contamination andEstimated Radiation Exposure Dose Rates among
Residents Immediately after Returning Home to
Tomioka Town, Fukushima Prefecture
Masahiko Matsuo 1 , Yasuyuki Taira 1, *, Makiko Orita 1 , Yumiko Yamada 1 , Juichi Ide 2 ,Shunichi Yamashita 3 and Noboru Takamura 1
1

2
3

*

Department of Global Health, Medicine and Welfare, Atomic Bomb Disease Institute, Nagasaki University
Graduate School of Biomedical Sciences, Nagasaki, Nagasaki Prefecture 852-8523, Japan;
bb55b16008@ms.nagasaki-u.ac.jp (M.M.); orita@nagasaki-u.ac.jp (M.O.); yumiko@nagasaki-u.ac.jp (Y.Y.);takamura@nagasaki-u.ac.jp (N.T.)
Nuclear Safety Research Association, Tokyo 105-0004, Japan; j-ide@fukushima-power.com
Special Advisor to the President, Nagasaki University, Nagasaki, Nagasaki Prefecture 852-8521, Japan;
shun@nagasaki-u.ac.jp
Correspondence: y-taira@nagasaki-u.ac.jp; Tel.: +81-95-819-7171

Received: 2 April 2019; Accepted: 23 April 2019; Published: 26 April 2019

Abstract: On 1 April 2017, six years have passed since the Fukushima Daiichi Nuclear Power Station(FDNPS) accident, and the Japanese government declared that some residents who lived in Tomioka
Town, Fukushima Prefecture could return to their homes. We evaluated environmental contamination
and radiation exposure dose rates due to artiﬁcial radionuclides in the livelihood zone of residents(living space such as housing sites), including a restricted area located within a 10-km radius fromthe FDNPS, immediately after residents had returned home in Tomioka town. In areas where theevacuation orders had been lifted, the median air dose rates were 0.20 μSv/h indoors and 0.26 μSv/h
outdoors, and the radiation exposure dose rate was 1.6 mSv/y. By contrast, in the “diﬃcult-to-returnzone,” the median air dose rate was 2.3 μSv/h (20 mSv/y) outdoors. Moreover, the dose-forming
artiﬁcial radionuclides (radiocesium) in the surface soil were 0.018 μSv/h (0.17 mSv/y) in the evacuation
order-lifted areas and 0.73 μSv/h (6.4 mSv/y) in the diﬃcult-to-return zone. These ﬁndings indicatethat current concentrations of artiﬁcial radionuclides in soil samples have been decreasing in theevacuation order-lifted areas of Tomioka town; however, a signiﬁcant external exposure risk still exists
in the diﬃcult-to-return zone. The case of Tomioka town is expected to be the ﬁrst reconstruction
model including the diﬃcult-to-return zone.
Keywords: air dose rate; diﬃcult-to-return zone; evacuation order-lifted areas; eﬀective dose rate;
external exposure risk; Fukushima Daiichi Nuclear Power Station accident; living space; radiocesium;
surface soil; Tomioka town

1. IntroductionMore than eight years have passed since 11 March 2011, the date of the 9.0-magnitude Great
East Japan Earthquake, subsequent tsunami, and disaster at the Fukushima Daiichi Nuclear Power
Station (FDNPS), which is operated by the Tokyo Electric Power Company. Various radionuclides
were released from the FDNPS into the atmosphere, eventually being deposited on land and at sea
in the surrounding areas [1]. The estimated total amount of iodine-131 (131 I) released ranged fromabout 100–500 petabecquerel (PBq), and that of cesium-137 (137 Cs) was generally in the range of
6–20 PBq [2]. For perspective, the estimated releases of 131 I and 137 Cs from the FDNPS were about
IJERPH 2019, 16, 1481; doi:10.3390/ijerph16091481

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IJERPH 2019, 16, 1481

10% and 20%, respectively, of those estimated for the Chernobyl accident [2]. Although much of thereleased radionuclides was dispersed over the Paciﬁc Ocean, a fraction was dispersed over the eastern
mainland of Japan; these radionuclides were deposited on the ground by dry and/or wet atmosphericdeposition through rain, fog, or snow, depending on the meteorological conditions [2,3]. These two
radionuclides, together with cesium-134 (134 Cs), made the largest contribution by far in terms of public
exposure [2]. Thus, the Japanese government, municipality and private companies have carried out
the environmental and individual radiation monitoring including the external and internal exposure
doses to conﬁrm the radiation level aﬀected areas by the FDNPS accident [4–6]. From these monitoring
results, it is conﬁrmed that artiﬁcial radionuclides with a relatively long half-life such as 134 Cs (half-life:
2.1 y) and 137 Cs (half-life: 30 y) still exist in the environmental samples including soils and plants inareas around the FDNPS [4–6].
During the eight years since the FDNPS accident, the levels of environmental radioactivity
have been decreasing because of the natural decay of the radionuclides, meteorological conditions(weathering), and decontamination by the Japanese government and municipality including Tomioka
Town [7–10]. The eﬀorts of the Japanese government to reduce the estimated annual exposure dose rate
to less than 20 mSv/y in the areas with an estimated annual exposure dose rate greater than 20 mSv/y(the restricted residence and diﬃcult-to-return zones), and to reduce the estimated annual exposure
dose rate closer to 1 mSv/y in the areas with an estimated annual exposure dose rate of less than
20 mSv/y (the evacuation order cancellation preparation zone and the evacuation order-lifted areas)
are still ongoing; this is being done with the cooperation of local authorities and inhabitants throughthe implementation of eﬀective decontamination work, which is being carried out according to therecommendations of the International Commission on Radiological Protection [4,11,12]. However, it isstill necessary to evaluate the long-term behavior and exposure risk of radiocesium in the environmental
samples such as soils by the radiation monitoring.
Tomioka town is located within a 20-km radius of the FDNPS. On 1 April 2017, with the Act on
Special Measures Concerning Nuclear Emergency Preparedness, the Japanese government declaredthat residents who lived in approximately 88% of the gross area of the Tomioka town could returnto their homes because the air dose rates were at low levels (estimated doses were expected to beless than 20 mSv/y) [4,5]. Although 1.5 years have passed since this “declaration of return,” as of
1 October 2018, there were 12,341 evacuees of the Tomioka town, 2627 (21.3%) of whom still currently
live outside of Fukushima Prefecture, 9714 (78.7%) living somewhere in Fukushima Prefecture, and therate of residents who have returned home in Tomioka town is still extremely low, at 791 (6.4%) [6].
The reason for this limited number is thought to be anxiety regarding exposure to radiation derived
from the accident [13,14]. In fact, the “diﬃcult-to-return” zone, where the integrated dose rates areover 50 mSv/y, represents approximately 12% of the gross area of the Tomioka town; therefore, the riskof external and internal exposure while residents perform activities of daily living (ADL) remains aparticular concern, and some means to reassure the public safety are required [4].
Our previous reports showed that the external and internal exposure dose rates among residents
who had returned to Kawauchi village, which is adjacent to Tomioka town, were limited [15] (Figure 1).
Nevertheless, long-term environmental monitoring, as well as eﬀorts such as further decontaminationand food monitoring, should continue around the FDNPS [16–19], including the Tomioka town.
Especially, the external exposure risk on the livelihood zone of residents (returner’s living space) suchas housing sites is not evaluated unlike the data which the municipal government including the nationaland municipality government have reported by literature, database and website. Therefore, in thepresent study, to evaluate the amount of environmental contamination and calculate the contributory
external radiation exposure doses of residents who had already returned or who planned to return inthe future, we measured air dose rates and analyzed the concentrations of artiﬁcial radionuclides in soil
samples collected in the residential areas of the Tomioka town using gamma spectrometry (Figure 1).

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IJERPH 2019, 16, 1481

Tomioka town is located within a 20-km radius from the Fukushima Daiichi Nuclear Power Station in an areathat also includes a ‘‘difficult-to-return zone’’ and ‘‘evacuation order-lifted areas.’’ The gray dotted circles are
the sampling points in the evacuation order-lifted areas, and the red circles are the sampling points in the“difficult-to-return” zone.

Figure 1. Location of Tomioka town, Fukushima Prefecture.

2. Materials and Methods
2.1. Sampling Points
The FDNPS (37◦ 25’ N, 141◦ 02’ E) is located on the east coast of Honshu Island, approximately
200 km northeast of Tokyo. Tomioka town (public oﬃce: 37◦ 20’ N, 141◦ 0’ E) is located 8.5 km southof the FDNPS. In the present study, we measured air dose rates and collected soils from 65 sampling
points in 45 residential areas where residents had returned home and near 20 assembly halls in Tomioka
town between 11 July and 25 October 2017 (Figure 1).
2.2. Measurement of Air Dose Rates and Radionuclides
In the present study, the air dose rates were monitored in air 1 m above the ground at all sampling
points using a NaI(Tl) scintillation survey meter (TCS-172B, Hitachi-Aloka Medical, Ltd., Tokyo,
Japan), which can measure gamma rays (50 keV-3 MeV, ambient dose equivalent rate at 1cm depth:
0.00–30.0 μSv/h). We measured air dose rates with a time constant of 10. In the evacuation order-lifted
areas, an additional radiation dose (radiocesium) including the natural dose was estimated using thefollowing formula:
Aext (mSv/y) = [(Cint − 0.04 μSv/h)·16h + (Cext − 0.04 μSv/h)·8 h]·365 d·0.001(1)where Cint is the indoor air dose rate (μSv/h) and Cext is the outdoor air dose rate (μSv/h). The ﬁxed
number (0.04 μSv/h) in the formula is deﬁned as the natural dose in Japan, and 16 h and 8 h are deﬁned
as representing the indoor and outdoor ADL, respectively. This calculation was based on the method
described by the Ministry of the Environment [8]. According to the monitoring information by thenational and local authorities, the prevalent dose-forming artiﬁcial radionuclides from various samples
have been mainly 134 Cs and/or 137 Cs in oﬀsite areas around the FDNPS. [4,5].
At the same time, to evaluate the vertical distribution and external radiation exposure, 130 samples(65 sites × 2) of surface soil (0–5 and 5–10 cm below the surface) were collected at Tomioka town
from July to October 2017. Soil sampling was carried out at all sampling sites using a core samplingtechnique (two core samples for each point). The size of the soil samples was 18.2 cm2 (diameter of
4.8 cm) and the density of the soil layers (0–10 cm) ranged from 0.31 to 2.3 g/cm3 (dry). The mass

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IJERPH 2019, 16, 1481

of the soil samples collected in each area ranged from 24.5 to 284 g. After collection, all samples
were dried for 24 h in a ﬁxed temperature dryer (105 ◦ C). Next, the samples were sieved for pebbles
and organic materials (>2 mm). After preparation, the samples were placed in plastic containers
made of polypropylene and analyzed using a high purity germanium detector (ORTEC® GMX series,
Ortec International Inc., Oak Ridge, TN, USA) coupled to a multi-channel analyzer (MCA7600, Seiko
EG&G Co., Ltd., Chiba, Japan) for 3600–36,000 s. We set the measuring time to detect objective
radionuclide levels. The target gamma ray peaks used for the measurements were 604.66 keV for 134 Cs(half-life: 2.1 y) and 661.64 keV for 137 Cs (half-life: 30 y). Decay corrections were made based on thesampling date. The detector eﬃciency calibration for diﬀerent measurement geometries including thedensity and thickness of samples was performed using mixed activity standard volume sources (Japan
Radioisotope Association, Tokyo, Japan); the relative detection eﬃciency of this instrument was 33.04%.
Sample collection, processing, and analysis were executed in accordance with standard methods ofthe radioactivity measurement authorized by the Ministry of Education, Culture, Sports, Science, andTechnology, Japan [20]. All measurements were performed at Nagasaki University, Nagasaki, Japan.
The obtained data are expressed as average, range (minimum–maximum) and medians.
2.3. Eﬀective Dose Rate
After the measurements, external eﬀective dose rates (μSv/h and mSv/y) from soil samples were
estimated from artiﬁcial radionuclide concentrations using the following formula:
Hext = C·Dext ·f ·s(2)

where C is the activity concentration (median) of detected artiﬁcial radionuclides (134 Cs and 137 Cs)(kBq/m2 ; estimated from the radiocesium concentration in Bq/kg, including soil particles (<2 mm) andcollected surface soil (0.00182 m2 )), Dext is the dose conversion coeﬃcient reported as the kerma-rate
in air at 1 m above the ground per unit activity per unit area ((μGy/h)/(kBq/m2 )), supposing thatthe air-kerma rate and the absorbed dose rate in air were the same value, for radiocesium with therelaxation mass per unit area (β: g/cm2 ) set to 10 (5-20 y) because more than eight years had passed since
the FDNPS accident (1.95×10-3 (μGy/h)/(kBq/m2 ) for 134 Cs and 7.55×10−4 (μGy/h)/(kBq/m2 ) for 137 Cs,
ICRU 1994) [21], f is the unit conversion coeﬃcient (0.7 Sv/Gy for the eﬀective dose rate in the body perunit absorbed dose rate in air) [22], and s is the decrease in the coeﬃcient by a shielding factor against
exposure to gamma rays from a sample at 1 m above the ground (0.7 under the condition of usualland) [23]. These calculations were based on the method described in our previous study [15,16,24].
2.4. Ethics Statement
The present study was approved by the ethics committee of Nagasaki University Graduate Schoolof Biomedical Sciences (project registration number: 17030212), and written informed consent was
obtained from the owners of the land containing all sampling points.
3. Results
The air dose rates in Tomioka town are shown in Table 1. In the evacuation order-lifted areas,
the median air dose rates inside the homes of the residents who had returned were 0.20 [0.086–0.37] μSv/hindoors, 0.26 [0.088–0.68] μSv/h outdoors (in front of the entrance), and 0.34 [0.14–1.3] μSv/h in the
backyard. The annual estimated doses were 1.7 mSv/y indoors, 2.3 mSv/y outdoors, and 3.0 mSv/y inthe backyard. Therefore, an additional radiation exposure dose of 1.6 mSv/y was estimated by theformula (1). On the other hand, in the diﬃcult-to-return zone, the median air dose rates were 2.3[1.1–2.9] μSv/h outdoors and 2.1 [1.8–2.4] μSv/h in the backyard. The annual estimated doses were
20 mSv/y outdoors and 18 mSv/y in the backyard.

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IJERPH 2019, 16, 1481

Table 1. Air dose rates around residences and assembly halls in Tomioka town, Fukushima Prefecture,
during September to October 2017.
Air Dose Rate in μSv/h

PointsAverage

Range

MedianExternal Eﬀective
Dose Rate in mSv/yShielding
Factor
0.77 g

Evacuation
order-lifted
areas (n = 61) a

Indoors
Outdoors
Backyard

0.20 ± 0.058 c
0.29 ± 0.12
0.40 ± 0.19

0.086–0.37 d
0.088–0.68
0.14–1.34

0.20 (0.28) e
0.26 (0.43)
0.34 (0.63)

1.7 f
2.3
3.0

Diﬃcult-to-returnzone (n = 4) b

Outdoors
Backyard

2.2 ± 0.65
2.1 ± 0.23

1.1–2.9
1.8–2.4

2.3 (2.7)
2.1 (2.4)

20
18

a residences (n = 45) and assembly halls (n = 16). b assembly halls (n = 4). c mean ± S.D. d minimum-maximum.

e parentheses show 90th percentile. f median × 24h × 365d × 0.001. g shielding factor of air dose rates ratio(indoors/outdoors).

The distribution of detected artiﬁcial radionuclides (radiocesium) and external eﬀective dose rates
from the surface soil due to radiocesium and the radionuclide ratios (134 Cs/137 Cs in Bq/kg [dry]) in
Tomioka town are shown in Table 2. The dose-forming artiﬁcial radionuclides 134 Cs and 137 Cs wereprevalent in all samples. In the evacuation order-lifted areas, the radiocesium concentrations inside thehomes of the residents who had returned were 238 (8.0–6063) (0–5 cm) Bq/kg (dry) and 334 (3.7–5803)(5–10 cm) Bq/kg (dry) for 134 Cs, and 1784 (34–45,331) (0–5 cm) Bq/kg (dry) and 2093 (28–48,911)(5–10 cm) Bq/kg (dry) for 137 Cs. The external eﬀective dose rates from the surface soil (0–5 cm)
were estimated as 0.17 mSv/y. On the other hand, in the diﬃcult-to-return zone, the radiocesium
concentrations inside the assembly halls were 8025 (3317–18,552) (0–5 cm) Bq/kg (dry) and 6633
(4654–9034) (5–10 cm) Bq/kg (dry) for 134 Cs, and 62,131 (25,559–141,209) (0–5 cm) Bq/kg-dry and51,840 (36,317–69,377) (5–10 cm) Bq/kg-dry for 137 Cs. The external eﬀective dose rates from the surface
soil (0–5 cm) were estimated as 6.4 mSv/y. In the evacuation order-lifted areas, the radiocesium
concentrations were lower in the surface soil samples (0–5 cm) than in the lower layers (5–10 cm),whereas in the diﬃcult-to-return zone, the radiocesium concentrations were higher in the surface soil
samples (0–5 cm) than in the lower layers (5–10 cm). Therefore, in the diﬃcult-to-return zone, there
was still an accumulation of radiocesium in the surface layer. In the present study, the concentrationsof radiocesium exceeded 8000 Bq/kg (dry), which is the standard value for storing decontamination
waste according to the Japanese guidelines, at some (17) sampling points, and the median radiocesium
values (134 Cs/137 Cs ratios) in the soil samples were 0.13 (0.093–0.18) at the time of sampling, regardlessof whether they were in the diﬃcult-to-return zone [25]. Moreover, the eﬀective dose rates from the air
dose rates in outdoors and soil samples in Tomioka town showed a positive relationship (r = 0.51 and
0.61, Figure 2).
Table 2. Distribution of radiocesium in soil samples in Tomioka town, Fukushima Prefecture.
Radiocesium Concentration in Bq/kg (dry) a

Pointsdepth
Evacuationorder-lifted
areas (n = 61) aDiﬃcultto-return zone(n = 4) b

Average

Range

Median134 Cs (2.1 y)

137 Cs (30 y)

134 Cs (2.1 y)

137 Cs (30 y)

134 Cs (2.1 y)

137 Cs (30 y)

0–5 cm
5–10 cm

694.3 ± 1137 c
750.0 ± 1035

4996 ± 8421
5585 ± 8163

8.0–6063 d
3.7–5803

34–45,331
28–48,911

238 (1950) e
334 (2016)

1784 (12,966)
2093 (15,209)

0–5 cm9480 ± 5708

72,757 ± 43,211

3317–18,552

25,559–141,209

8025 (15,906)

5–10 cm

6739 ± 2067

52,343 ± 15,690

4654–9034

36,317–69,377

6633 (8893)

62,131(121,336)
51,840 (68,551)

External
Eﬀective
Dose Ratein mSv/yRadionuclide
Ratio in
134 Cs/137 Cs

0.17 f0.13 (0.14) g
0.13 (0.14)

6.4

0.13 (0.13)
0.13 (0.14)

a Residences (n = 45) and assembly halls (n = 16). b Assembly halls (n = 4). c mean ± S.D. d minimum-maximum.
e parentheses show 90th percentile. f calculated by the formula (2). g median (90th percentile).

The eﬀective external doses in the living space of residents within housing sites immediately after
the cancellation of the restriction in Tomioka Town (during September to October in 2017) are shownin Figure 3. In the present study, the external exposure doses including radiocesium were mainly
higher in the backyard than outdoors in front of the entrance. Naturally, the external exposure doses

209

IJERPH 2019, 16, 1481

including radiocesium were higher in outdoors than indoors by the shielding eﬀectiveness of theirhouse. Moreover, the external exposure doses due to radiocesium in soil samples were suﬃciently
low level.

Figure 2. Relationship between estimated external eﬀective dose rates from surface soil and air dose
rates in Tomioka town. (a) Air dose rates in outdoor (entrance) vs., (b) air dose rates in outdoors(backyard) vs. and (c) air dose rates in indoor (entrance) vs. eﬀective dose rates of soil samples.
The external eﬀective dose rates from soil samples were estimated using a high purity germanium
detector (only radiocesium). Air dose rates were measured at the sampling points using a NaI (Tl)scintillation survey meter (natural dose rates including radiocesium).

Figure 3. External exposure doses immediately after the cancellation of restriction in Tomioka Town.
The eﬀective external doses in residents living space within housing sites during September to Octoberin 2017. Yellow, blue and green squares show the natural dose rates including radiocesium. Red squareshows the external eﬀective dose rates from soil samples (only radiocesium).

4. Discussion
In the present study, the artiﬁcial radionuclides 134 Cs and 137 Cs were detected in all samples fromTomioka town by gamma spectrometry, and the 134 Cs/137 Cs values of these samples were around
0.13, which is thought to be the consequence of the relatively early decay of 134 Cs (median: 238(8.0−6063) Bq/kg (dry) for 134 Cs and 1784 (34−45,331) Bq/kg (dry) for 137 Cs in the upper layer (0−5 cm);see Table 2). Immediately after the accident, the 134 Cs/137 Cs values were reported as 0.9 in areas to thesouth and southwest of the FDNPS, which were higher than those observed around the Chernobyl
Nuclear Power Plant [26,27]. Eight years have passed since the FDNPS accident, and it was conﬁrmed

210

IJERPH 2019, 16, 1481

that the 134 Cs/137 Cs values have been decreasing because of the natural decay of 134 Cs (half-life: 2.1 y).
Therefore, in the present study, the radiocesium (the 134 Cs/137 Cs values: 0.13 (median)) detected inthese samples was obviously derived from the FDNPS accident.
In the present study, air dose rates were higher in the backyard (where trees and plants such as
cedar were growing) than outdoors in front of the entrance to homes in evacuation order-lifted areas(0.34 (0.14−1.3) μSv/h in the backyard vs. 0.26 (0.088–0.68) μSv/h outdoors and 0.20 (0.086–0.37) μSv/hindoors; Table 1). In the diﬃcult-to-return zone, the outdoor air dose rates (in the backyard and in frontof the entrance) were nearly equivalent, and the samples were still contaminated (2.1 (1.8−2.4) μSv/h in
the backyard vs. 2.3 (1.1–2.9) μSv/h outdoors; Table 1). Also, gaps were observed between air dose rates
and estimated external eﬀective dose rates. The external eﬀective dose rate in the evacuation-order-lifted
areas were estimated at 10 times higher than the external estimated eﬀective dose rates from radiocesiumin soil samples (Tables 1 and 2). However, because a positive relationship (r = 0.61) was observed
between air dose rates in the backyard and estimated eﬀective dose rates from surface soil samples,the ﬁndings of the present study suggest that the environmental radiation dose was mainly derived
from surface soil and areas around vegetation, including fallen leaves (Figure 2). Following the FDNPS
accident, the residential areas, farmlands, forests (the close to residential areas; <20 m), and roads
within the evacuation order areas around the FDNPS were extensively decontaminated by suitable
methods, and decontamination of the entire area, excluding the diﬃcult-to-return zones, was completed
on 19 March 2018 [25]. However, the decontamination eﬀect of areas around vegetation including
fallen leaves may be limited. Some reports have suggested that radiocesium accumulates in various
forest environments through the forest biota [24,28–31]. The detection of high 137 Cs concentrations inevergreen cedar needles after the accident indicated that the canopy interception of atmosphericallydeposited 137 Cs, and the existence of high 137 Cs activity in newly developed foliage during the six
years after the accident, particularly in the leaves of Japanese konara oak (Quercus serrata) seedlingsin an abandoned coppice forest, suggests translocation and eﬃcient recycling of 137 Cs within thetrees [32]. On the other hand, the eﬀective dose rates from the air dose rates in indoors and soil samplesin Tomioka town showed a negative relationship (r = 0.10, Figure 2). The shielding eﬀect by houses
was comparatively high because there were a lot of new houses with high airtightness in areas of
the cancellation of restriction in the Tomioka Town (shielding factor = 0.77, Table 1) [22,23]. Actually,
the additional radiation exposure dose was estimated at low level (1.6 mSv/y) [33].
The Japanese and local government aim to reduce the estimated annual exposure dose rate to
1 mSv/y as early as possible and continue with further reductions in residential areas. In the present
study, the current contamination levels due to radiocesium were extremely diﬀerent in both areas; low(0.17 mSv/y) in the evacuation order-lifted areas and relatively high (6.4 mSv/y) in the diﬃcult-to-returnzone in Tomioka town (Table 2). In the eight years that have passed since the FDNPS accident,
the estimated external exposure levels in the evacuation order-lifted areas have decreased becauseof decontamination and the decay of artiﬁcial radionuclides; however, further remediation of soil
contaminated with artiﬁcial radionuclides in the diﬃcult-to-return zone, which is a crucial social
responsibility in Japan and internationally, is still needed. Based on the current ﬁndings regarding
radiocesium concentrations and eﬀective dose rates, decreases in external exposure doses are theevidence that evacuees from the Tomioka town may return (Figure 3). Especially, the concentrationsof detected radiocesium in surface soils were low during two layers (0–5 cm and 5–10 cm) in theevacuation order-lifted areas of Tomioka town, and the current levels of environmental contamination
around homes in this area of Tomioka town are extremely low. Conversely, in the diﬃcult-to-returnzone, the concentrations of detected radiocesium were higher in surface soil samples (0–5 cm) thanin lower layers (5–10 cm), because in this area, eﬀective decontamination of the strong absorption ofradiocesium by soil particles is not progressing smoothly (Table 2). Most 137 Cs accumulated within
1.5 years after the FDNPS accident and 137 Cs continued to be retained in the upper mineral soil layer(0–5 cm) [34]. Absorption of 137 Cs appears to be the primary process regulating the 137 Cs distribution
in the soil proﬁles (vertical distribution) over ﬁve years of monitoring after contamination [34]. In other211

IJERPH 2019, 16, 1481

words, these ﬁndings suggest that environmental contamination and the eﬀective dose rates on the
ground in the evacuation order-lifted areas will be decreased by decontamination procedures, suchas the removal of surface soil [35] (Figure 3). In addition, the decontamination of residential areas,
farmlands, forests, and roads is being carried out by suitable methods [35]. Reconstruction projects havealready started in the area of the diﬃcult-to-return zone in coordination with relevant ministries andagencies such as the Ministry of the Environment and Reconstruction Agency [36]. In Tomioka town,
the pre-decontamination of the diﬃcult-to-return zone has been carried out [37]. The investigationof the Ministry of the Environment and our research by the car-survey report the eﬀectiveness of the
pre-decontamination in the diﬃcult-to-return zone (data not shown). It is expected that evacuation
orders will be lifted for wider areas in the diﬃcult-to-return zone in the near future.
This study did have several limitations. First, the number of soil sampling points wererelatively limited, especially in the diﬃcult-to-return zone (n = 4), because the size of the sample
collection was small under the serious and emergent conditions of the FDNPS accident. Although
we researched in the residential area as much as possible for the return to home in the future, further
investigation with detailed conditions is needed while conﬁrming the change of radiation doses by thedecontamination work.
Second, other types of evidence such as the internal exposure doses, infrastructure repairs andsupport services also play roles in the decision to return. Especially, agricultural activities and thecountryside (satoyama) cultural practice of ingesting edible wild plants (sansai) and mushrooms arebeing carried out carefully based on the guidelines by the Nuclear Emergency Response Headquartersof the Japanese government, accompanied by the ongoing decontamination of farmlands andradiation monitoring [5,38]. Edible wild plants and mushrooms are well-known as accumulators ofradiocesium [16,18,19,39–42]. Currently, the shipment of agricultural products in Japan is determinedbased on regulations outlined by the Japanese government [43]. In Tomioka town, the monitoring
system for local foods by using the nondestructive equipment for detecting radiocesium such as the
NaI spectrometer is an eﬀective tool to avoid unnecessary radiation exposure since February 2018.
Further investigations on external and internal eﬀective doses, are needed [44,45].
5. Conclusions
In the present study, we evaluated environmental contamination and contributions from theexternal exposure due to radiocesium in Tomioka town near the FDNPS. Based on the current ﬁndings
regarding radiocesium concentrations and eﬀective dose rates, we conﬁrmed that current levels are
decreasing suﬃciently, especially in the evacuation order-lifted areas located within a 20-km radiusfrom the FDNPS and decontaminated rapidly, even though a certain amount of radiocesium derived
from the accident was detected in soil samples in these areas. Thus, decreases in external exposure
doses are the evidence that that evacuees from Tomioka town may return with the long-term follow-up,
as well as environmental monitoring and countermeasures, such as further decontamination andrestrictions on the intake of local foods (edible wild plants and mushrooms) that can cause unnecessary
radiation exposure, and physical and mental support [35–37]. The case of Tomioka town is expected tobe the ﬁrst reconstruction model for evaluating environmental contamination and radiation exposure
dose rates due to artiﬁcial radionuclides, including areas such as the diﬃcult-to-return zone near
the FDNPS.
Author Contributions: M.O. and N.T. conceived and designed the framed study; Y.T., M.O. and Y.Y. designed
the methodology in this investigation; M.M., Y.T., M.O., Y.Y. and J.I. investigated the environmental radiationin Tomioka town; M.M. analyzed the sample data and wrote our manuscript; Y.T. reviewed and edited themanuscript; N.T. and Y.T. reviewed the sample data; Y.T., M.O., Y.Y. and N.T. administered the project; S.Y. and N.T.
supervised the project; N.T. acquired the funding; M.M., Y.T., M.O., Y.Y., J.I. and N.T. contributed to discussing thestatistical method and the interpretation of our ﬁndings.
Funding: This work was supported by Research on the Health Eﬀects of Radiation organized by the Ministry of
the Environment, Japan.

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Acknowledgments: We would also like to thank Yoshiyuki Nitta, Tsuyoshi Wakamatsu, and Shinya Kurosawa(Tomioka Municipal Government, Fukushima, Japan) for assistance with our research plan and sample collection.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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tomioka_tokuteifukkosaiseikyotenkuikifukkosaiseikeikaku.pdf (accessed on 1 April 2019). (In Japanese)
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215

International Journal ofEnvironmental Researchand Public Health
Brief Report

Study of Well Waters from High-Level Natural Radiation Areas
in Northern Vietnam
Van-Hao Duong 1 , Thanh-Duong Nguyen 1 , Miklos Hegedus 2 , Erika Kocsis 2 and Tibor Kovacs 2, *1

2*Geophysics Department, Hanoi University of Mining and Geology, No 18, Vien Street, Bac Tu Liem District,Hanoi 100 000, Vietnam; duongvanhao@humg.edu.vn (V.-H.D.); nguyenthanhduong@humg.edu.vn (T.-D.N.)
Institute of Radiochemistry and Radioecology, University of Pannonia, H-8200 Veszprem, Hungary;hegedusm@almos.uni-pannon.hu (M.H.); kocsiserika@almos.uni-pannon.hu (E.K.)
Correspondence: kt@almos.uni-pannon.hu

Abstract: The determination of natural radionuclide concentrations plays an important role forassuring public health and in the estimation of the radiological hazards. This is especially true forhigh level radiation areas. In this study, 226 Ra, 228 Ra and 238 U concentrations were measured inwell waters surrounding eight of the high-level natural radiation areas in northern Vietnam. The
226 Ra, 228 Ra and 238 U activity concentrations vary from <1.2 × 10−3 –2.7 (0.46), <2.6 × 10−3 –0.43(0.07) and <38 × 10−3 –5.32 Bq/L (0.50 of median), respectively. 226 Ra and 238 U isotopes in most areas
are in equilibrium, except for the DT-Thai Nguyen area. The calculated radiological hazard indices
are generally higher than WHO (World Health Organization) recommendations. Average annual
effective dose and excess lifetime cancer risk values due to drinking well water range from to 130 to540 μSv/year and 7.4 × 10−6 to 3.1 × 10−5 , respectively.
Keywords: 226 Ra; 228 Ra; 238 U; well water; radiological hazards; REE and uranium mines; northern Vietnam

Citation: Duong, V.-H.; Nguyen,
T.-D.; Hegedus, M.; Kocsis, E.;
Kovacs, T. Study of Well Waters from
High-Level Natural Radiation Areas
in Northern Vietnam. IJERPH 2021,
18, 469.
https://doi.org/10.3390/ijerph18020469
Received: 7 December 2020
Accepted: 5 January 2021
Published: 8 January 2021
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional afﬁliations.

Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

1. Introduction
Human beings are always exposed to a wide range of natural radionuclides [1].
Natural radionuclides can be present in the whole environment, including soil, water, air,food and even our bodies. Radionuclides in soil, air and water come from different sources,
such as the weathering of the earth’s crust, mining activities or fertilizer materials [2–7].
The radionuclides in water can enter the food chain, if the water is used for drinking
or irrigation purposes. Determination of natural radionuclide concentrations in all theenvironments plays an important role for public health, because it can be used to assess
the population’s exposure to radiation and estimate the radiological hazard.
Investigations on natural radiation have received particular attention throughout
the world in the last decade, which led to extensive studies in many countries, especiallyin or surrounding the high-level natural radiation areas. Studies regarding the naturalradioactivity in water from different sources were widely conducted [7–15].
Among natural radionuclides, uranium leaches out from the bedrock and is present inwater (surface and underground water) in various dissolved and suspended particulate
forms. Other sources can be from the dry or wet deposition of aerosol from air. 228 Ra
originates from the 232 Th series, and in contrast to the typically not very soluble of Th
element, 228 Ra can be partially mobilized in natural waters, giving information on geochemical conditions and enabling contributions to the potential public exposure. 226 Ra isa long-lived daughter of the 238 U decay series, and it is also found in the water in trace
quantities. The concentrations of 238 U, 228 Ra and 226 Ra in the water depend on the lithology,
geomorphology and other geological conditions [16]. Thus, the concentration of theseradionuclides varies from one site to another. The study concerning 226 Ra, 228 Ra and 238 U
concentrations in drinking water allows understanding their distribution and evaluating
their impact on human health.
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IJERPH 2021, 18, 469

In Northern Vietnam, there are several mines, which contain higher than average
concentrations of radioactive elements such as the rare earth mines in NX (Lai Chau),
DP (Lai Chau), MH (Lao Cai) and YP (Yen Bai); there is also a polymetallic mine (alsocontaining high uranium concentration) in DT (Thai Nguyen); ﬁnally, there is uranium ore
in BY (Son La), TS (Phu Tho) and NB (Cao Bang). These mines were recently reported tohave a high radioactive background by unpublished data from the Geological Division forRadioactive and Rare Minerals, Hanoi, Vietnam. This presents a possible public healthconcern. Therefore, in this study, the natural radionuclide concentrations in well water(226 Ra, 228 Ra 238 U) in the area surrounding these mines are investigated. Based on theactivity concentrations, the radiological health hazards are also evaluated.
2. Materials and Methods
2.1. Study Areas
The eight areas in Northern Vietnam, including NX-Lai Chau, DP-Lai Chau, MH-Lao
Cai, BY-Son La, TS-Phu Tho, YP-Yen Bai, DT-Thai Nguyen and NB-Cao Bang were selected
for this study. The location of these areas is presented in Figure 1. The NX mine is one of
the largest rare earth element (REE) mines in Vietnam, with probable reserves of about
7.7 million tons. DP mine ranks the second, with probable reserves of about 3.7 million tons
and is followed by MH with approximately 400,000 tons and YP with about 5000 tons [17].
BY (Son La), TS (Phu Tho) and NB (Cao Bang) have uranium ore deposits, while DT (Thai
Nguyen) is the largest polymetallic mine in Vietnam.

Figure 1. Location of the study areas (map was modiﬁed from Hung et al., 2016) [18].

2.2. Sample Collection and Preparation
In each study location, 20 water samples were collected from local wells during 2018–2019. These wells were dug manually in the soil to the depth of about 5 to 10 m, andthese wells provide drinking water for the local population. A total of 160 water samples
with 50 L for each sample were collected for this study. Each water sample was stored
218

IJERPH 2021, 18, 469

in a big, 50 L plastic container. Each water sample was co-precipitated as Ba(Ra)SO4 forradium isotopes, then the uranium isotopes were subsequently precipitated as (NH4 )2 U2 O7
together with MnO2 [15,19,20]. The solid precipitate was then ﬁltered. Together with study
samples, a blank sample was prepared using distilled water in order to determine thebackground. The obtained precipitated sample was dried and milled to powder, then they
were pressed into cylindrical plastic containers, weighted and ﬁnally hermetically sealed.
The samples were stored for 4 half-lives in order to reach the secular equilibrium (16 daysfor 226 Ra after sealing, and approximately 100 days for 238 U after precipitation).
2.3. Methods
2.3.1. Measurements of Activity Concentration of 238 U, 228 Ra and 226 Ra in Water
After the samples reached equilibrium, activity concentration measurements were
performed using a high-resolution detector HPGe with a low background made by Ortec™.
The analysis was performed using Gamma Vision software. The detector’s energy resolution was 1.9 keV at the 1.33 MeV 60 Co gamma-ray peak. To reduce the effects of backgroundradiation at the laboratory, the detector was shielded by a 10-cm thick old-lead cylinder
with a 1 mm cadmium and 1 mm copper inner lining. The samples were counted for twodays to minimize the statistical counting error and activity calculation and calibration werecarried out based on standard reference materials (IAEA-375). The level of backgroundradiation present in the laboratory and introduced by the chemical process was determinedusing the blank sample.
The activity concentration of each sample was determined based on its respective
gamma lines. The gamma lines of 609.3 keV, 1120.3 keV and 1764.5 keV of 214 Bi were used
to determine the activity concentration of 226 Ra, the 911.1 keV line of 228 Ac was used for
228 Ra while the 1001 keV line of 234m Pa was used for 238 U (which was veriﬁed by 235 U
measurement using the 186 keV line). The lowest limit detection were 0.0012, 0.0026 and0.038 Bq/L for 226 Ra, 228 Ra and 238 U, respectively (the values were used for a studied
sample volume of 50 L).
The activity concentrations of 226 Ra, 228 Ra and 238 U are calculated based on thefollowing Equation (1) [7]:Nsp Mst Ast Ci Cdi
Asp =
(1)
Nst Mspwhere: Asp and Ast is activity concentration of studied and standard samples; Nsp , Msp
and Nst, Mst are the net measured intensity and mass of the sample and standard sample,
respectively; Ci is the correction factor for the differences between the densities of thesamples and the standard sample for the i isotope; and Cdi is the correction fraction for the
precipitation efﬁciency for the i isotope.
2.3.2. Evaluation of Radiological Hazard Indices•

Annual effective dose (AED)

The annual effective dose (AED) due to the ingestion of the drinking well water was estimated to assess the radiological hazards for the local population by using
Equation (2) [21]:AED (μSv/year) = A (Bq/L) × Cw (L/year) × DCF (μSv/Bq)(2)

where AED is the annual effective dose due to ingestion of radionuclides; A is the activity concentration of radionuclides; Cw is the annual water consumption for a person(730 L/year for adults) [22]. DCF is the ingestion dose conversion factor for the corresponding radionuclides (0.28, 0.69 and 0.045 μSv/Bq for 226 Ra, 228 Ra and 238 U, respectively) [21,23]. We all know that there are some other isotopes, like 210 Po, which cancontribute to a higher annual effective dose caused by drinking well waters, but in thisstudy we only used the 226 Ra, 228 Ra and 238 U values to calculate the AED.
219

IJERPH 2021, 18, 469•

Excess lifetime cancer risk (ELCR)

Based on the values of AED, excess lifetime cancer risks (ELCR) were calculated using
the following Equation (3) [24]:
ELCR = AED × Life Expectancy (LE) × Risk factor (RF)(3)

where LE is life expectancy of Vietnamese people in North Vietnam and mountainous
areas (71 years) (https://www.gso.gov.vn/default_en.aspx?tabid=774); RF the risk factor
associated with radiation, which is equal to 0.057 Sv−1 [24].
3. Results and Discussion
3.1. Activity Concentration
The range and average values of activity concentration of 226 Ra, 228 Ra and 238 U
measured in the well water samples are given in Table 1. It can be seen that the activity
concentration of 226 Ra, 228 Ra and 238 U ranges from <0.0012–2.7, <0.0026–0.43 and <0.038–
5.32 Bq/L, respectively. The highest concentrations of all three isotopes are found in
DT-Thai Nguyen. This table shows only a slight difference in concentration between 226 Ra,
228 Ra and 238 U in most cases, except for the DT-Thai Nguyen sampling site. 226 Ra, 228 Ra
and 238 U ratios near unity indicate recent contact with uranium bearing not yet weatheredminerals [25]. The concentrations of 226 Ra, 228 Ra and 238 U are less than 1 Bq/L in most areas,
except for DT-Thai Nguyen (Table 1). In the case of DT-Thai Nguyen, the concentrations of
226 Ra, 228 Ra and 238 U are comparatively high and are in the ranges of 0.36–2.70, 0.05–0.43
and 0.33–5.32 Bq/L, respectively. There, the 226 Ra concentration can reach levels multiple
times higher than the WHO guideline (1 Bq/L) [26]. The high concentrations of 226 Ra and238 U in DT-Thai Nguyen can be attributed to the polymetallic mine (which contains highuranium concentration) in this area. There are some activities, such as exploitation andthe process of ore sorting going on, which can inﬂuence activity concentrations. It should
be noted that the water samples in this study were taken from wells with depth of lessthan 10 m. These type of wells depend on rainfall and surface water as their source ofwater. Accordingly, they are easily contaminated by surface water and various humanactivities. Thus, the human activities in the polymetallic mine can lead to a relatively highconcentration of 226 Ra, 228 Ra and 238 U in well water.
Table 1. Concentration of natural radionuclides in well water samples in North, Vietnam.
Activity Concentration (Bq/L)
228 Ra238 U

LocationsType of MineValue

226 RaNX-Lai Chau

REE mine

Range (SD)Average

0.26–0.65 (0.09)
0.44

0.04–0.10 (0.01)
0.06

0.15–0.72 (0.15)
0.50

0.64–1.73
0.95

DP-Lai Chau

REE mine

Range (SD)Average

0.35–0.59 (0.08)
0.47

0.05–0.15 (0.03)
0.11

0.31–0.71 (0.10)
0.54

0.60–1.19
0.90

MH-Lao Cai

REE mine

Range (SD)

0.30–0.78 (0.16)

0.31–0.87 (0.18)

0.69–1.52

Average

0.52<0.0026–0.11(0.02)
0.07 *

0.56

0.96

Average<0.0012–0.54(0.07)
0.23 *<0.0026–0.12(0.02)
0.08 *

Range (SD)

0.25–0.74 (0.11)

Average

0.45<0.0026–0.09(0.02)
0.06 *

0.25–0.97 (0.19)
0.48
0.36–2.70 (0.69)
1.15

YP-Yen Bai

BY-Son La

REE mine

Uranium mine

Range (SD)TS-Phu Tho

Uranium mine

Range (SD)Average

DT-Thai Nguyen

Uranium mine

Range (SD)Average

220

226 Ra/238 U<0.038–0.70 (0.12)**

0.31 ***

0.27–0.63 (0.08)

0.76–1.44

0.41

1.08

0.05–0.10 (0.02)
0.07

0.27–0.69 (0.11)
0.48

0.50–1.76
1.01

0.05–0.43 (0.11)
0.18

0.33–5.32 (1.46)
2.06

0.50–1.42
0.79

IJERPH 2021, 18, 469

Table 1. Cont.
LocationsType of MineNB-Cao Bang

Uranium mine

Overall range

Activity Concentration (Bq/L)
228 Ra
238 U

Value

226 RaRange (SD)

0.32–0.97 (0.18)

Average

0.53<0.0026–0.13(0.02)
0.07<0.00122.7<0.0026
0.43

Minimum
Maximum

226 Ra/238 U

0.34–0.80 (0.12)

0.53–1.43

0.55

0.97

<0.038
5.32

0.50
1.76

* during averaging values under the detection limit were taken as the detection limit to give a conservative estimate. ** uncalculable values
were left out of the ratio calculation.

Table 2 compares the 226 Ra, 228 Ra and 238 U concentrations in the well water samples
in this study with that of different water sources in different countries. The concentrationsof 226 Ra, 228 Ra and 238 U in well water in the areas observed in this study are signiﬁcantly
higher than those in Hoa Binh, Vietnam. In addition, the observed concentrations arehigher than those in reported for many other countries [8–12,16], whereas they are lower
than some values reported for tube wells in India. The concentrations observed in well
water signiﬁcantly depend on the type of aquifer rock as well as the chemical and physicalcharacteristics of water [27], thus such differences can be expected. The concentrationof studied radionuclides observed in well water in this study is within the worldwide
range [28].
Table 2. 226 Ra and 238 U concentrations in water samples in different areas.
Countries

Samples

Northern Vietnam
Hoa Binh, Vietnam
Italy
TurkeyJordanErbil, Iraq

Well water
Groundwater
Drinking water
Drinking water
Tap water
Surface water
Tube well
Open well
Groundwater
Surface water

Gogi, India
Ghana
World range

Drinking water

226 RaActivity concentration (Bq/L)
228 Ra<0.0012–2.7
0.005–0.029
0.0050–0.0608<0.027–2.431
0.096
0.274–1.03
0.0195–10.5
0.0366–0.0571
0.09–0.18
0.08–0.17
0.0002–45

238 U

References<0.0026–0.43≤0.0200.00010–0.0257<0.036–0.270
0.170
0.00676–0.244 *0.22–0.99 *0.18–0.74 *<0.038–5.32≤0.0005–0.009
0.000206–0.103
0.033
0.274–1.03 *0.0123–33.2
0.114–0.160
0.09–0.18 *
0.08–0.17 *This study
[15]
[12]
[9]
[8]
[11]

0.0001–7.7

0.000028–150

[28]

[16]
[10]

* Equilibrium was assumed by the original authors.

Regarding the concentration ratio of 226 Ra/238 U in well water samples, as shown in
Table 1, the average value ranges from 0.57 (DT-Thai Nguyen) to 1.09 (BY-Son La). The data
presented in Table 1 also shows that on average there is near equilibrium between 226 Ra
and 238 U, except for DT-Thai Nguyen. Kumar et al. (2016) reported that the concentrationof 226 Ra/238 U in groundwater in southwestern Punjab in India was varied from 0.08
to 0.22 [29]. In groundwater in Finland, Asikainen (1981) also showed that the ratioof 226 Ra/238 U ranged from 0.05 to 1. By contrast, other previous studies reported theenrichment of 226 Ra in groundwater [30]. For examples, Gascoyne (1989) indicated thatthe 226 Ra/238 U ratios in Canadian groundwater varied from 0.026 to 5300; this ratio in
Konnngara Australian groundwater was from 0.02 to 89 [31]. Recently, the research resultsof Almasoud et al. (2020) indicated that the ratios of 226 Ra/238 U in groundwater samples in
Saudi Arabia ranged from 1.25 to 20.4 [32]. The issue is further complicated by the effectsof the recoil from the emission of an alpha particle, which can increase the mobility ofthe daughter nuclide due to the Szilárd–Chalmer effect. On the other hand, the 234 Th or
234 U can be ﬁxed to more weathering resistant mineral phases, resulting in relatively more221

IJERPH 2021, 18, 469

238 U dissolving into groundwater [31]. The depletion of

234 U in groundwater can also be
observed based on the relative abundances of U under various geochemical conditions [30]
The relationship between activity concentrations of 238 U and 226 Ra in well water
samples in this study is shown in Figure 2. A signiﬁcant positive correlation was foundbetween the two radionuclides with a Pearson correlation coefﬁcient, 0.9402 and a p value< 0.00001 for the overall dataset, due to the inﬂuence of the higher values observed at
DT-Thai Nguyen. The high value of correlation between 238 U and 226 Ra shows that theseradionuclides have leached from the similar host rock [16]. Excluding DT-Thai Nguyen,there is moderate positive correlation with a Pearson correlation coefﬁcient of 0.6326, anda p value < 0.00001. Similarly, a strong positive correlation was observed both between
238 U and 228 Ra (Pearson correlation coefﬁcient: 0.8411, with a p value < 0.00001) and
226 Ra and 228 Ra (Pearson correlation coefﬁcient: 0.7834, with a p value < 0.00001) for theoverall dataset, however the effect of the higher values at DT-Thai Nguyen improving thecorrelation are observable here as well.

Figure 2. Relationship between 238 U and 226 Ra concentrations.

3.2. Radiological Hazards
The calculated radiation hazard indices based on the average activity concentrations
for some drinking well water in northern Vietnam are listed in Table 3. As shown in thistable, the annual effective dose (AED) for 226 Ra is signiﬁcantly higher than that for 238 U,
while 228 Ra is in the middle despite having a higher dose conversion coefﬁcient due tothe comparatively low activity concentrations. The average total annual effective dose
for adults due to the consumption of water ranges from 130 to 540 μSv/year with themean value of 240 μSv/year. The average excess life cancer risk (ELCR) due to drinking
the investigated well water is from 7.4 × 10−6 to 3.1 × 10−5 (7 to 31 cases per 1 million
people) with the average of 1.4 × 10−5 (14 cases per 1 million people). Speciﬁc wells canhave higher values; the overall maximum activity concentrations were observed in a wellin YP-Yen Bai translating to a total annual effective dose of 540 μSv/y for adults and an
ELCR of 7.0 × 10−5 (70 cases per 1 million people). As reported by the WHO (2017), thereference values for AED and ELCR due to drinking water are 100 μSv/year and 1.0 × 10−5 ,respectively. It can be seen that the results of AED and ELCR due to consumption of well
water in this study are higher on average for each area from the observed radionuclides
alone than the values suggested by the WHO (2017), with the exception of ELCR for YPYen Bai. This indicates that there is a need for deﬁning local policy regarding the wells
in high-level natural radiation areas, northern Vietnam (in the observed areas), especially
DT-Thai Nguyen.
222

IJERPH 2021, 18, 469

Table 3. Radiation hazard indices for well water samples in northern Vietnam.
LocationsType of Mine

NX-Lai Chau
DP-Lai Chau
MH-Lao Cai
YP-Yen Bai
BY-Son La
TS-Phu Tho
DT-Thai Nguyen
NB-Cao Bang

REE mine
REE mine
REE mine
REE mine
U mineU mineU mineU mineAverage

226 Ra228 RaAED (μSv/Year)
238 U

Total

120
130
150
60
130
140
320
150

40
80
50
50
40
50
120
50

20
20
30
10
20
20
90
20

190
240
220
130
180
210
540
220

1.1 × 10−5
1.3 × 10−5
1.3 × 10−5
7.4 × 10−6
1.0 × 10−5
1.2 × 10−5
3.1 × 10−5
1.3 × 10−5

150

60

30

240

1.4 × 10−5

ELCR

4. Conclusions
The concentrations of 226 Ra, 228 Ra and 238 U in well waters in different locations
surrounding the high-level radiation areas in northern Vietnam were extensively measured
and evaluated. The research results show that the concentrations of 226 Ra, 228 Ra and 238 U
in well water samples in the observed mining areas of northern Vietnam are comparatively
higher than those reported for other areas of Vietnam and other countries. The highest
concentrations of 226 Ra, 228 Ra and 238 U are observed in DT-Thai Nguyen. The research also
shows that the concentration of 226 Ra and 238 U for most locations on average are aroundequilibrium, except for DT-Thai Nguyen. Regarding the radiological hazards assessment,
the calculated results of AED and ELCR due to the consumption of well water are often
higher, and for DT-Thai Nguyen multiple times higher, than the WHO reference values.
The results generated from this study provide important baseline data for the impact
assessment of the mining activities in the region in the future.
Author Contributions: Conceptualization, V.-H.D., T.-D.N., and T.K.; methodology, M.H., V.-H.D.,and T.K.; formal analysis, M.H., T.-D.N.; investigation, V.-H.D., T.-D.N., E.K., and T.K.; resources,
V.-H.D., and T.K.; data curation, T.K. and M.H.; writing—original V.-H.D., and M.H. and T.K. draft
preparation, V.-H.D.; writing—review and editing, M.H., E.K., V.-H.D., and T.K.; visualization, V.H.D. and E.K.; supervision, T.K.; project administration, T.K.; funding acquisition, V.-H.D. and T.K.
All authors have read and agreed to the published version of the manuscript.
Funding: The research work is supported by Grant of The National Foundation for Science andTechnology Development (NAFOSTED), Vietnam, no 105.05-2019.10. and the TKP2020-IKA-07
project ﬁnanced under the 2020-4.1.1-TKP2020 Thematic Excellence Programme by the National
Research, Development and Innovation Fund of Hungary.
Institutional Review Board Statement: Not applicable for studies not involving humans or animals.
Informed Consent Statement: Not applicable for studies not involving humans.
Data Availability Statement: The data presented in this study are available on request from thecorresponding author.
Conﬂicts of Interest: The authors declare no conﬂict of interest.

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