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Measurement and Monte Carlo simulation of γ-ray dose rate in high exposure building materials

NUCLEAR CHEMISTRY, RADIOCHEMISTRY, RADIOPHARMACEUTICALS AND NUCLEAR MEDICINE

Measurement and Monte Carlo simulation of γ-ray dose rate in high exposure building materials

A. Abbasi
M. Hassanzadeh
Nuclear Science and TechniquesVol.28, No.2Article number 20Published in print 01 Feb 2017Available online 26 Dec 2016
33601

Natural radioactivity radionuclides in building materials, such as 226Ra, 232Th and 40K, cause indoor exposure due to their gamma rays. In this research, in a standard dwelling room (5.0 m×4.0 m×2.8 m), with the floor covered by various granite stones, was set up to simulate the dose rates from the radionuclides using MCNP4C code. Using samples of granite building products in Iran, activities of the 226Ra, 232Th and 40K were measured at 3.8–94.2, 6.5–172.2 and 556.9–1529.2 Bq·kg−1, respectively. The simulated dose rates were 26.31–184.36 nGy·h−1, while the measured dose rates were 27.70–204.17 nGy·h−1. With the results in good agreement, the simulation is suitable for any kind of dwelling places.

RadioactivityBuilding MaterialsAbsorbed doseExperimentalMCNP4C.

1. Introduction

Indoor exposure to gamma-rays from natural radionuclides in building materials is inherently greater than outdoor exposure [1]. To determine radiological hazards to human health, the natural radioactivity from building materials must be under control. Some researchers measured radioactivity in concrete, granites and sand [2]. Terrestrial origin building materials, such as concrete, cement, brick, sand, aggregate, marble, gypsum and granite, [3] usually contain the uranium and thorium decay series radionuclides, so the radiation exposure arises mainly from 238U, 232Th series and 40K [4]. When the duration of occupancy is taken into account, indoor exposure becomes even more significant [5].

The distribution and concentrations of the parent radium radionuclides in bedrocks of various types vary greatly from type to type. In general, granites have relatively high radium content. Therefore, it is not only important but also feasible to assess the radiological hazard by calculating indoor external dose based on radioactivity measured for building materials [6]. Radium-226, as an alpha emitter with a half-life of 1622 years, is a natural decay product of 238U series. The other gamma-emitting radionuclides from 226Ra decay are 214Pb and 214Bi.

The specific absorbed dose rate in air is mainly affected by parameters of position concerned in room, thickness and density of building materials [7-8]. The Monte Carlo code MCNP4C has been used to evaluate the absorbed doses in air. Developed for simulating transports of electrons, neutrons, photons etc., the code gives an arbitrary three-dimensional configuration of materials in geometric cells. The model has been presented in term of an input file in this code. It encloses the geometry, material, source information and the type of output needed in the form of standard tallies already supplied [9].

In this paper, in a living room geometry, dose rates of 226Ra, 232Th and 40K in high exposure building materials in Iran are measured and simulated using the MCNP4C code. The simulation and measurement results are compared.

2. Materials and Methods

2.1 Experimental procedure

The collected samples were pulverized, sieved through a 0.2 mm mesh, sealed in standard 1 L Marinelli beakers, dry-weighed and stored for 4 weeks before counting in order to allow the attainment of equilibrium between 226Ra and 222Rn and its decay products. In equilibrium, the activity of each daughter is equal to that of the initial isotope of the series [8]. The gamma-ray spectra of the prepared samples were measured using a typical high-resolution gamma spectrometer based on a coaxial P-type shielded high-purity germanium (HPGe) detector, with a relative photo peak efficiency of 80% and energy resolution of 1.80 keV (FWHM) at 1332 keV, coupled to a high count-rate Multi-Task 16 k MCA card. Commercial software Gamma Genie-2000 was used for data analysis [6].

The 226Ra activities were calculated from the short-lived daughters 214Pb (295.2 and 351.9 keV) and 214Bi (609.3 keV). Similarly, 232Th activities were measured by taking the mean activity of photo peaks of the daughter nuclides 228Ac (338.40, 911.07 and 968.90 keV) and 212Pb (238.63 keV). Activities of 40K were determined directly from its 1460.83 keV gamma-ray. Quality assurance of the measurements was determined by using of Standard Reference Material IAEA Soil-375 [10].

The density of all the granite samples was estimated at 2580 kg·m−3 in average. The granite stones in markets are usually sized at 30 cm × 50 cm× 3 cm [11]. The granites differ from one type to another in their compositions. Table 1 shows the composition of a typical granite stone.

Table 1
Compositions (in %) of a typical granite sample.
Fe2O3 FeO CaO Na2O K2O Al2O3 SiO2
1.22 1.68 1.82 3.69 4.12 14.42 72.04
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Calculation of the dose rate conversion factors was done based on the point kernel integration method for floors covered with 3.0 cm thick granite. The free-in-air absorbed dose rate (nGy·h−1) in the room center can be expressed as Eq. (1) [4]:

dD/dt=0.04AK+0.46ARa+0.60ATh, (1)

where AK, ARa and ATh are the activity concentrations (Bq·kg−1) of 40K, 226Ra and 232Th, respectively.

To calculation the effective annual dose rate (mSv), we consider the conversion factor 0.7 Sv·Gy−1 for adult categories. The indoor occupancy factor is 0.8 given by UNSCEAR report and the allowed indoor dose is 1 mSv·y−1 [5]. The effective annual dose rate is by Eq. (2):

dE/dt=(dD/dt)×0,7(Sv·Gy-1)×24×365×0.8 (h·y-1). (2)
2.2 Theoretical procedure
2.2.1 Room geometry

According to the standard living room, a room with dimensions of 4.0 m × 5.0 m × 2.8 m is defined for the MC simulation. Its floor is covered with granite stones of 3.0 cm thick, with the compositions listed in Table 1. The detector is at the room center.

2.2.2 Monte Carlo Simulation

By defining necessary parameters of high exposure building materials and room geometry, we can simulate the indoor external gamma-ray exposure and the dose distribution. The interaction of photons with walls and the air is simulated by MCNP4C code.

To improve the calculation accuracy, 10–2000 keV gamma-rays of over 1% emission intensity from 226Ra, 232Th and 40K, as summarized in Table 2, are used in the simulation.

Table 2
Gamma energies emission from 226Ra, 232Th series and 40K with intensity higher than 1%
232Th E (keV) 39 57.7 63.7 84.4 99.5 129 154 209 238 241 277 338 510 583 727 860 911 969 2614
  Intensity (%) 1.9 4.8 3.8 1.2 1.2 2.4 6.2 3.9 2.9 4.1 6.8 11.4 21.6 84.2 11.8 12.5 27.7 16.6 100
226Ra E (keV) 46 63 92 295 352 609 1120 1238 1764 2204           40K E (keV) 1461
  Intensity (%) 3.9 3.8 5.4 19.2 37.2 46.3 15.1 5.9 15.8 5.0           Intensity (%) 10.7
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The photon flux and energy deposition in the room center are calculated by using F4 and F6 tallies, respectively. This code reads the input file such as the geometry, materials, neutron source etc. Results of interest can be scored by using tallies. A tally is a specification of what should be included in the output. For example, the photons flux (F4) through a certain area or the number of photons in a particular energy interval can be calculated by [9]:

F4=CΦ(E)dE, (3)

where C is an arbitrary scalar quantity for normalization, Φ(E) is the photon flux (F4) in cm−2, and E is incident photon energy.

The energy deposition or heating tally (F6) is the following track length estimates and can be calculated by:

F6=ρa/ρgH(E)Φ(E)dE, (4)

where, ρa is the atom density (atoms·barn−1·cm−1); ρg is the mass density (g·cm−3); and H(E) is the heating response, having different meanings, depending upon context as follows:

H(E)=σT(E)Havg(E), (5)

where σT is total photon cross section, and Havg(E) is average energy of exiting gamma-rays for each reaction and for all energies is assumed to be deposited locally. The energy deposition tally (F6) is in MeV·g−1.

3. Results and Discussion

3.1 Experimental and Simulation Results

The measured activities of 232Th, 226Ra and 40K in the granite samples are 6.5–172.2, 3.8–94.2 and 556.9–1529.2 Bq·kg−1, respectively. They are shown in Table 3, together with measurement and simulation results of the absorbed dose rate (dD/dt) and effective annual dose rate (dE/dt) due to 226Ra, 232Th and 40K in air.

Table 3
The dose rate (dD/dt) and effective annual dose rate (dE/dt) due to 226Ra, 232Th and 40K in air in granites in Iran.
Sample code Commercial name Activity (Bq·kg−1) dD/dt (nGy·h−1) dE/dt (mSv·y−1)
    232Th 226Ra 40K Measured* Simulated** Measured Simulated
G 1 Chayan sable 7.2 4.8 561.4 28.7 ± 1.1 33.7±0.4 0.14 0.17
G 2 Tekab 75.9 39.2 1017.8 101.9 ± 2.4 99.6±0.3 0.50 0.50
G 3 Nehbndan birjand 172.2 99.2 1529.2 204.2 ± 2.9 175.2±0.8 1.00 0.88
G 4 Peranshahr 82.1 53.3 964.7 109.2 ± 1.8 81.6±0.6 0.54 0.41
G 5 Torbat hydaryeh 9.1 10.8 647.5 35.7 ± 1.4 38.1±0.2 0.18 0.19
G 6 Natanz 87.1 58.3 1124.7 120.9 ±2.6 131.7±0.7 0.59 0.66
G 7 Morvared mashhad 65.6 39.7 941.6 92.9 ± 4.1 47.3±0.5 0.46 0.24
G 8 Akbatan hamedan 65.8 49.6 1144.3 105.1 ± 2.2 71.6±0.3 0.52 0.36
G 9 Sangeh alamot 79.6 43.2 1101.7 109.1 ± 2.1 68.5±0.6 0.54 0.34
G 10 Garmez yazd 59.2 29.9 1047.2 89.4 ± 1.7 96.7±0.4 0.44 0.48
G 11 Balloch zahedan 84.9 41.8 1121.4 112.5 ± 1.6 121.7±0.3 0.55 0.61
G 12 Morvared sabz 73.1 36.8 1002.3 98.7 ± 3.1 70.4±0.5 0.48 0.35
G 13 khoramdareh 171.3 96.7 1362.7 196.0 ± 5.8 184.4±0.8 0.96 0.92
G 14 Chayan sable 55.9 25.3 811.8 76.1 ± 1.5 86.1±0.4 0.37 0.43
G 15 Tekab 68.1 44.3 1101.4 102.6 ± 2.3 67.6±0.3 0.50 0.34
G 16 Trasheh sfed 148.9 89.3 1341.2 178.7 ± 3.9 160.2±0.6 0.88 0.80
G 17 Morvared sabz 6.5 3.8 556.9 27.7 ± 1.4 26.9±0.2 0.14 0.13
G 18 Hekmtaneh 58.9 39.4 1131.2 96.4 ± 2.6 83.4±0.6 0.47 0.42
G 19 Sangeh lorestan 9.5 5.8 601.8 32.1 ± 1.1 26.3±0.4 0.16 0.13
G 20 Alborz 166.4 79.2 1234.5 180.9 ± 3.6 142.6±0.8 0.89 0.71
Average   77.4 44.5 1017.2 104.9± 2.5 90.7 0.51 0.45
Minimum value   6.5 3.8 556.9 27.7 26.3 0.14 0.13
Maximum value   172.2 99.2 1529.2 204.2 184.4 1.00 0.92
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* Uncertainties are given within 1 standard deviation. ** Calculation error is under 5%.

The absorbed dose rate is calculated by using DFn (Dose Function), DEn (Dose Energy) cards and tally F4 operations. Suppose one wanted to compute a dose rate of some type associated with a flux tally, either total or by energy group. This feature allows one to enter a point-wise response function (such as flux-to-dose conversion factors) as a function of energy to modify a regular tally. The energy points are specified on the DEn card and the corresponding values of the dose function are identified on the DFn card.

The calculated dose rate distributions due to 232Th, 226Ra and 40K in the room floor are shown in Fig 1. As can be seen, the dose rate in the floor center is the maximum. The dose rate decreases with increasing height (the Z direction, not shown).

Fig. 1
The absorbed dose rate distribution in the room floor, due to 232Th, 226Ra and 40K.
pic

The simulated dose rates are 26.3–184.4 nGy·h−1, averaged at 90.7 nGy·h−1, while the measured dose rates are 27.7–204.2 nGy·h−1, averaged at 104.9 nGy·h−1.The two sets of minimum-maximum range and average value overlap closely. Thus the simulation method is suitable to any kind of dwelling places with the use of granite stones. The uncertainties calculation are calculated within 1σ (standard deviation) and simulation uncertainties calculated fewer than 5% errors by code. The uncertainty is calculated by:

Xmean=(Xi)/N; σX=[(XiXmean)2/N]1/2;X=Xmean±σX (6)

where Xmean is the mean value, N is number of data and Xi is data. (i=1,2,3…,N).

The approximations errors are expressed by:

Rel(XA)=|(XTXA)/XT| XT0, (7)

where, XT is the true value and XA is the approximate value.

The measured 232Th, 226Ra and 40K activities of the samples are used to calculate the effective annual dose rates, which are. 0.14–1.00 mSv·y−1, while the simulated effective annual dose rates are 0.13 – 0.92 mSv·y−1.

4. Conclusion

The amount of radiation from natural radionuclides of 226Ra, 232Th and 40K in building materials are determined with a standard room of 5.0 m×4.0 m×2.8 m with its floor covered by various granite stones produced in Iran. The dose rates are measured by a gamma-ray spectral system with an HPGe detector, and simulated with the MCNP4C code. The two sets of minimum-maximum dose rate range and averaged dose rate show good agreement..

References
1. UNSCEAR,

United Nations Scientific Committee on the Effects of Atomic Radiation

. Sources and effects of ionizing radiation. Report to the General Assembly with annexes. Volume I, United Nations Publications, (2000).
Baidu ScholarGoogle Scholar
2. European Commission,

Radiation Protection 112-Radiological Protection Principles Concerning the Natural Radioactivity of Building Materials

. In: Directorate- General: Environment, Nuclear Safety and Civil Protection. Office for Official Publications of the European Communities, (1999).
Baidu ScholarGoogle Scholar
3. E. Cetin, N. Altinsoy, Y. Örgün,

Natural radioactivity levels of granites used in Turkey

. Radiation protection dosimetry. 151(2):299-305 (2012). doi: 10.1093/rpd/ncs007
Baidu ScholarGoogle Scholar
4. A. Faanu, H. Lawluvi, D.O. Kpeglo et al.,

Assessment of natural and anthropogenic radioactivity levels in soils, rocks and water in the vicinity of Chirano Gold Mine in Ghana

. Radiation protection dosimetry. 158(1):87-99 (2014). doi: 10.1093/rpd/nct197
Baidu ScholarGoogle Scholar
5. S. Dziri, A. Nachab, A. Nourreddine et al.,

Experimental and simulated effective dose for some building materials in France

. World Journal of Nuclear Science and Technology. 30;33(02):41 (2013). doi: 10.4236/wjnst.2013.32007
Baidu ScholarGoogle Scholar
6. A. Abbasi,

Calculation of gamma radiation dose rate and radon concentration due to granites used as building materials in Iran

. Radiation protection dosimetry. 155(3):335-342 (2013). doi: 10.1093/rpd/nct003
Baidu ScholarGoogle Scholar
7. S. Risica, C. Bolzan, C. Nuccetelli,

Radioactivity in building materials: room model analysis and experimental methods

. Science of the total environment. 14;272(1):119-126 (2001). doi: 10.1016/S0048-9697(01)00675-1
Baidu ScholarGoogle Scholar
8. UNSCEAR,

United Nations Scientific Committee on the Effects of Atomic Radiation

. Sources and effects of ionizing radiation, Report to the General Assembly with annexes. Volume I, NY: United Nations, (2010).
Baidu ScholarGoogle Scholar
9. J.F. Briesmeister, MCNP4C: Monte Carlo-N-Particle Transport Code System, LA-13709, (2000).
10. Canberra, Genie-2000 Version 3.2, Canberra Industries, Inc, (2013).
11. N.W El-Dine, A. El-Shershaby, F. Ahmed et al.,

Measurement of radioactivity and radon exhalation rate in different kinds of marbles and granites

. Applied Radiation and Isotopes, 30;55(6):853-60 (2001). doi: 10.1016/S0969-8043(01)00107-5
Baidu ScholarGoogle Scholar