Journal of Environmental Radioactivity 146 (2015) 119e124
Contents lists available at ScienceDirect
Journal of Environmental Radioactivity journal homepage: www.elsevier.com/locate/jenvrad
Review
Monte Carlo calculations of the HPGe detector efficiency for radioactivity measurement of large volume environmental samples Ahmed Azbouche a, Mohamed Belgaid b, *, Hakim Mazrou a a b
Centre de Recherche Nucl eaire d'Alger, 02, Bd. Frantz Fanon, B.P. 399, 16000, Alger-Gare, Algiers, Algeria USTHB, Facult e de Physique, Laboratoire SNIRM, B.P. 32, El-Alia, 16111, Bab Ezzouar, Algiers, Algeria
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 October 2014 Received in revised form 13 April 2015 Accepted 17 April 2015 Available online
A fully detailed Monte Carlo geometrical model of a High Purity Germanium detector with a 152Eu source, packed in Marinelli beaker, was developed for routine analysis of large volume environmental samples. Then, the model parameters, in particular, the dead layer thickness were adjusted thanks to a specific irradiation configuration together with a fine-tuning procedure. Thereafter, the calculated efficiencies were compared to the measured ones for standard samples containing 152Eu source filled in both grass and resin matrices packed in Marinelli beaker. From this comparison, a good agreement between experiment and Monte Carlo calculation results was obtained highlighting thereby the consistency of the geometrical computational model proposed in this work. Finally, the computational model was applied successfully to determine the 137Cs distribution in soil matrix. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Monte Carlo simulation Detector efficiency Germanium dead layer 152 Eu Marinelli source Gamma-ray spectrometry 137 Cs distribution in soil
1. Introduction Gamma-ray spectrometry is a common technique widely used for identification and quantification of radionuclides in samples of different matrices and geometries. This technique offers an advantage of being rapid and non-destructive and does not require any special sample treatment. Moreover, the use of high purity germanium (HPGe) detectors with high energy resolution allows identification and activity measurement of natural and artificial radionuclides in biological, geological and environmental samples, with the highest possible sensitivity. However, for large volume samples, the use of multi-gamma radionuclide for calibration procedure of the activity measurements fails in determining the activity of different radionuclides with a sufficient accuracy due mainly to an under estimation of the detector efficiency. In reality, the lack of standard sources with different geometries and matrices makes the experimental determination of the detector efficiency, an arduous task (Abbas et al., 2002; Mostajaboddavati et al., 2006; Chirosca et al., 2013).
* Corresponding author. Fax: þ213 21 247344. E-mail address: [email protected] (M. Belgaid). http://dx.doi.org/10.1016/j.jenvrad.2015.04.015 0265-931X/© 2015 Elsevier Ltd. All rights reserved.
Nowadays and in order to overcome the above cited difficulty encountered in such cases, most of the small and existing environmental radioactivity laboratories have developed and validated their own counting procedures for routine analysis of large volume samples using gamma-ray spectrometry. To reach this purpose, an attempt was made to develop locally a reliable computational rrez-Villanueva model useful for environmental applications (Gutie et al., 2008; Dababneh et al., 2014). The Monte Carlo (MC) method is well appropriate to perform the calibration and to reproduce the detector response for a variety of matrices and for different ge denas ometries with sufficient accuracy (Bochud et al., 2006; Ro et al., 2007; Sima and Arnold, 2009; Chirosca et al., 2013). In this work, the Monte Carlo computer code MCNP5 (X-5 Monte Carlo Team, 2003) is used to develop a detailed geometrical model to a HPGe detector together with an 152Eu multigamma source, in a Marinelli beaker geometry, to evaluate accurately the detector efficiency for large volume sources. The choice of 152Eu as a multi-gamma ray source for the calibration of the detector efficiency is justified by its availability and cheapness, its relatively long life-time and the wide energy range (120e1600 keV). Unfortunately, this source emits gamma rays in cascade, which, at distances close to the detector, cause, coincidence summing that one should carefully take into account since it's one of the main effect that can modify substantially the detector
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efficiency value (Laborie et al., 2000; Garcia-Talavera et al., 2001; Agarwal et al., 2011). The nominal dimensions of the detector of interest as specified by the manufacturer were first taken to develop the initial geometrical model. Then, by means of a specific measurement configuration using two reference point sources (241Am, 137Cs) located at five positions in front and around the detector, a finetuning procedure was applied to adjust the model parameters, in particular, the dead layer thickness. Thereafter, the proposed Monte-Carlo geometrical model was validated against measurements obtained using two standard sources, provided and certified by LEA (Laboratoire Etalons d’Activit e, Division de CERCA, France). Finally, the proposed MC model was applied for the same measurement configuration, using the same geometry (Marinelli beaker), to determine the detection efficiency curve for a 152Eu source filled in matrix soil. The obtained value was used to estimate accurately the activity of 137Cs on a soil sample in order to evaluate the degree of soil erosion.
A p-type HPGe detector model, GX-3519, with a carbon-epoxy entrance window manufactured by CANBERRA (Canberra Industries), is used for routine gamma spectrometric analysis in the environmental laboratory. The detector has the following specifications: 35% relative efficiency at 1.33 MeV gerays relative to a 00 00 3 3 NaI(Tl) crystal, 1.85 keV resolution (FWHM) at 1332.5 keV and 0.86 keV at 122 keV, with an amplifier shaping time constant of 4 ms, the detector had a 68.2 peak-to-Compton ratio for 60Co. The Desktop Spectrum Analyzer DSA 1000 was used in this work. The detector was surrounded with 114 mm-thick graded lead shield (Canberra 747 Series Lead Shield), with liners of 3 mm of tin and 1.5 mm of copper to reduce the contribution to the spectrum of the lead X-rays, achieving a low background needed in environmental applications. Two 152Eu sources where considered: a source with 4.17 kBq activity (relative uncertainty 5% with a coverage factor k ¼ 2), with a gamma impurity of about 0.49% of 154Eu, at the time of measurement, imbedded in a resin matrix (C18H20O3) having 1.15 g cm3 in density and a 5.39 kBq source (relative uncertainty 5% for k ¼ 3), with a 0.33% gamma impurity at the time of measurement, mixed in grass (C6H12O6) with a density of 0.6 g cm3. The spectra sources were collected over 7000 s, to obtain good counting statistics, with dead time less than 2%; all spectra were treated using Genie 2000 (Canberra Industry). The experimental detector efficiency is given by:
N APtc
N εPtc
(2)
N εCSCPtc
(3)
Auncor labo ðEÞ ¼
AIAEA ¼
The coincidence summing correction factors deduced are listed herein in Table 1.
2. Experiment
ε¼
Laboratory) of IAEA Laboratories in Seibersdorf (Austria). The sample was a water solution containing g-emitting radionuclide, including 60Co, 152Eu and 241Am. The activity concentration of 152 Eu certified by IAEA was 49.9 ± 0.41 Bq kg1 (IAEA, evaluation Report, 2014). The method consists to pack an amount 400 cm3 of volume of spiked water in the Marinelli beaker and measure during 30,000 s. The coincidence summing correction factors (CSC) were obtained by dividing the activity Auncor ðEÞ of 152Eu measured in the labo laboratory for each gamma energy without correction, by the reference activity AIAEA, according to the following equations:
(1)
where N is the net area at the interest peak energy, corrected for background counts, A is the source activity in Becquerel with decay time correction; tcis the collection time in second and P is the gamma ray emission probability. In this work, the effect of the coincidence summing on the efficiency calibration has been taken into account in order to improve the experimental efficiency results (Boshkova, 2014). The measured efficiencies were corrected by the coincidence summing correction factors by using the results issued from our participation in the proficiency test carried out in 2013, under the auspice of the International Atomic Energy Agency (IAEA-TEL2013-01 TEL/SWMCN proficiency test). The analyzed sample was a spiked water given by SWMCN (Soil and Water & Crop Nutrition Laboratory) in cooperation with TEL (Terrestrial Environment
3. Monte Carlo calculation 3.1. Monte Carlo detector model The experimental setup was modeled using the Monte Carlo NParticle Transport Code (MCNP5) developed by Los Alamos National Laboratory. A detailed physical treatment, including the photoelectric effect with the resulting X-ray fluorescence, the incoherent scattering with form factors and pair production, were considered in the energy range between 1 and 1500 keV. The F8 tally and GEB (Gaussian Energy Broadening) card options of the MCNP5 code was used. This tally calculates the absolute fullenergy peak efficiency of the detector with energies lying in the interval [1e1500 keV]. The GEB option allows the incorporation of the detector's resolution (energy broadening) at various photon energies. For this purpose, the Full Width at Half Maximum (FWHM) of the experimental data was fitted by the following function:
FWHMðMeVÞ ¼ a þ b
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi E þ cE2
(4)
where E is the energy of the incident particle in MeV, and for the detector used in this work a ¼ 0.707 103 MeV, b ¼ 0.946 103 MeV1/2 and c ¼ 0. The simulated spectrum was binned with an energy window of 0.5 keV/channel, to reproduce the experimental conditions. The MC model used for the HPGe detector in Marinelli beaker geometry is shown in Fig. 1. In Fig. 1, the Marinelli beaker sits directly on top of the detector to provide relatively a high-efficiency. The description of the detector-Marinelli source geometry was given in detail in the cell and surface cards of the MCNP input file. It is described with 14 cells and 21 surfaces. In Fig. 2, both measured and simulated spectra can be seen. The qualitative spectrum obtained in Fig. 2 was simulated with PE mode, 31 gammas energies of the 152Eu were introduced in MCNP input file, which were emitted according to its two modes of decay. The Samarium and Gadolinium characteristics X-ray region, from the energy range 40 keVe50 keV produced during the 152Eu decay are not used in the simulation and consequently did not appear in this figure.
A. Azbouche et al. / Journal of Environmental Radioactivity 146 (2015) 119e124 Table 1 Correction factors of coincidence effects for
152
Eu source in 400 ml Marinelli beaker.
Nuclide
Energy (keV)
Activity measured Uncorrected (Bq/kg)
152
121.78 244.66 344.31 443.98 778.72 867.38 964.01 1085.79 1112.04 1408.02
45.6 44.7 45.7 45.5 44.2 43.0 46.5 51.4 47.8 47.5
Eu
121
± ± ± ± ± ± ± ± ± ±
1.02 1.01 1.02 1.01 1.00 0.92 1.02 1.06 1.05 1.04
Activity reference IAEA (Bq/kg) 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9
± ± ± ± ± ± ± ± ± ±
0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41
Fig. 1. 2D view of Marinelli beaker and HPGe detector modeled with MCNP5.
Fig. 2.
152
Eu spectrum source in resin matrix obtained experimentally and with MCNP5.
Coincidence factor 0.914 0.896 0.915 0.912 0.885 0.862 0.932 1.031 0.958 0.951
± ± ± ± ± ± ± ± ± ±
0.024 0.024 0.024 0.024 0.024 0.024 0.023 0.025 0.023 0.023
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Table 2 Germanium detector crystal details given by manufacturer and adjusted by simulation. Germanium detector details
Nominal value (mm) Adjusted value (mm)
Germanium crystal diameter Crystal length Core hole diameter Core hole depth Dead layer thickness (front) Side dead layer (side) Germanium front to inside of end cap distance Carbon epoxy window thickness End cap material Al thickness
60.5 61 12 51 0.004 0.004 5
59.5 60.5 12 51 0.05 0.05 5
0.5 1.5
0.5 1.5
3.2. Dead layer estimation The dead layer thickness of a given germanium detector is an important parameter that can affect drastically its response. Many authors have highlighted the dead layer influence on the response of germanium detectors for medium and high gamma-ray energy denas et al., 2003; Boson et al., 2008; Courtine et al., 2008; range (Ro Aline et al., 2012; Andreotti et al., 2014). In fact, they reported that the dead layer thickness is often greater than the nominal value given by the manufacturers. Consequently, this parameter is always subject to a continuous evaluation. In this work, the dead layer thickness of a newly acquired HPGe detector was estimated using a specific irradiation geometrical configuration together with a fine-tuning procedure. For this purpose, the experimental set-up consisted mainly in collimating two reference point sources: 241Am (59.5 keV) and 137Cs (661.6 keV), positioned successively at five different locations; the first one was located in front of the detector and the remaining four positions were situated around the detector. Due to their small energy, the 241Am gamma-rays has been used to adjust the estimation of the external thickness of the dead layer due to the low penetration of the photon in the crystal. The 137Cs gamma-rays were used to adjust the internal dead layer since their energy (661.6 keV) has a large penetration (mean free path is 26.5 mm) in the germanium crystal (Courtine et al., 2008). The adjustment procedure used herein to estimate the dead layer thickness of the germanium detector is based on a gradual increase of the dead layer thickness i.e. in a stepwise process from its initial value (given by the manufacturer) till to its final value. At each step where a new value of the dead layer thickness is suggested, a series of comparison between experimental intrinsic efficiencies with the MC results, obtained at five chosen locations, is performed. The calculation procedure stops when the mean difference between experimental and calculated intrinsic
Table 3 Comparison of experimental and simulated efficiencies for Nuclide
152
Eu
Mean ± SD
efficiencies at these five locations is below 5%. This corresponds to the average uncertainty of our experimental measurements. The final results achieved following this adjustment procedure are given in Table 2. In Table 2, one can see that the nominal value of the dead layer provided by the manufacturer was 4 mm, whether the calculated one was increased by a factor of 12. However, this value remains reasonable comparatively to those found in the literature. 4. Validations of Monte Carlo results For the detector-Marinelli source model in both resin and grass matrices, the main gamma ray energies of 152Eu are used,108 incident photons were simulated, to achieve a relative statistical uncertainty of less than 1% for the considered peaks. The results of the experimental and calculated efficiencies, for the 152Eu source mixed with grass and resin in a Marinelli beaker are listed in Table 3. The MC calculated efficiencies were found to be slightly higher than the experimental efficiencies. The relative uncertainty associated to simulated values of efficiency with MCNP5 code is less than 1% and the maximum uncertainty associated to experimental value is about 3%. The MCNP5-to-experimental efficiency ratios are also given in Table 3 with an average uncertainty less than 5%. The agreement achieved between calculated and experimental efficiencies is considered as good enough to validate the MC geometrical model proposed in this work. 5. Application for environmental samples analysis 5.1. Detector efficiency calculation in soil matrix In this section, the developed MC detector-Marinelli source model was applied to calculate the full peak energy efficiency for a 152 Eu source in soil matrix. The physical characteristics of the soil used in the simulation were determined experimentally: the soil sample was dried in air, and then it was sieved at 2 mm to remove the larger particles. After homogenization, a quantity about 550 mg (z400 ml) of soil was conditioned in the same Marinelli beaker used in the calibration. The measured bulk density of soil sample is about 1.35 g cm3. The detailed elemental composition of the soil needed by the MCNP5 code input file was obtained by analyzing small quantities of soil using the Wavelength Dispersive X-Ray Fluorescence (WDXRF) method. The WDXRF spectrometer Model used in this work is a MagixPro (Panalytical ex Philips) equipped with an X-ray tube with a Rhodium anode, and a series of eight crystal analyzers covering the analytical range of elements from Bore to Uranium. It is also
152
Eu Marinelli source mixed in resin and grass matrix.
Resin matrix
Grass matrix
Energy (keV)
Exp efficiency 102
121.78 244.66 344.31 443.98 778.72 867.38 964.01 1085.79 1112.04 1408.02
6.60 4.62 3.88 2.99 1.99 1.83 1.69 1.60 1.55 1.31
± ± ± ± ± ± ± ± ± ±
0.19 0.12 0.09 0.06 0.04 0.03 0.03 0.04 0.03 0.02
MCNP efficiency 102
MCNP/Exp ratio
Exp efficiency 102
7.17 5.10 4.07 3.12 2.05 1.92 1.71 1.69 1.58 1.32
1.09 1.10 1.05 1.04 1.03 1.05 1.01 1.06 1.02 1.01 1.05 ± 0.03
7.59 5.56 4.52 3.58 2.34 2.07 1.92 1.78 1.70 1.42
± ± ± ± ± ± ± ± ± ±
0.20 0.18 0.12 0.11 0.08 0.07 0.06 0.06 0.05 0.04
MCNP efficiency 102
MCNP/Exp ratio
8.13 6.01 4.79 3.65 2.45 2.13 1.98 1.89 1.75 1.46
1.07 1.08 1.06 1.02 1.05 1.03 1.03 1.06 1.03 1.02 1.04 ± 0.02
A. Azbouche et al. / Journal of Environmental Radioactivity 146 (2015) 119e124 Table 4 Mass fraction of soil composition used in Monte Carlo simulations. Element
Formula
Mass fraction (%)
Mg Al Si P K Ca Fe Ti
MgO Al2O3 SiO2 P2O5 K2O CaO Fe2O3 TiO2
1.72 15.01 54.81 0.12 2.70 16.84 7.33 0.97
± ± ± ± ± ± ± ±
0.05 0.50 0.80 0.03 0.08 0.90 0.30 0.16
The mass fraction of the elemental composition of the soil, as used in MCNP5 code, is reported in Table 4. The developed MC detector-Marinelli source model was used consequently to simulate the efficiency calibration in a soil matrix. The full peak energy efficiency curve for 152Eu source energies calculated by the MCNP5 code is shown in Fig. 3. These results allow determining the detector efficiency in the energy interval between 120 and 1500 keV commonly used for several applications in a terrestrial environmental laboratory. According to the simulation results obtained, the efficiency of detector increases as the density of the matrix decreases, this is due to the associated decrease in photon attenuation within the sample. The efficiency detector value at 661.6 keV for Marinelli source in soil matrix deduced from the efficiency curve is found to be ε ¼ 0.0219. 5.2.
Fig. 3. Efficiency curve of 152Eu source for Marinelli geometry in soil matrix calculated by simulation.
equipped with three detectors used for X-ray measurements: the first one is a gas flow counter, the second one is a proportional counter sealed Xenon and the third one is a scintillation detector used for high energy X-ray measurements.
Fig. 4.
137
123
137
Cs distribution in soil
After calibrating the gamma rays spectrometry technique with the Monte Carlo method, the efficiency results can be used in the determination of the specific activities of radionuclides in soil for many applications. In this work, an application example of the model results is given to determine the 137Cs concentration in soil to assess the degree of soil erosion. Soil samples from an eroded land in North West of Algeria were examined. Samples from small watershed area and a forest which, a 1 km away, was considered as a reference site, since such soil has not been disturbed by erosion. Four separate profiles were collected at four points (P1, P3, P4, P5), including one profile, P5, collected at the reference site (Fig. 4). For each sampling point, pedological pits (dimensions 30 30 30 cm) were dug and six samples at the depths 0e5, 5e10. 10e15, 15e20, 20e25 and 25e30 cm were taken (Mabit et al., 2007). One point was sampled at the surface (P2). A total of 25 samples were stored in plastic bags labeled according to the depth, and were transported in the laboratory. After the preparation and conditioning in Marinelli beaker, the samples were measured during 86,400 s to obtain a good counting statistics. The 137Cs was identified in the spectrum by the 661.6 keV gamma-ray energy.
Cs distribution in the soil profile along the watershed and at the reference site.
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The activity concentration, As (Bq/kg), of the 137Cs in the soil was determined as:
As ¼
N εPtc m
(5)
where, ε is the detector efficiency at 661.6 keV, obtained from exponential fitted curve shown in Fig. 3, m is the sample weight in kg and Ig, P, tc, were defined in the Eq. (1). The vertical distributions of the 137Cs in the soil profile along the watershed caused by the erosion and accumulation phenomena and at the reference site are given in Fig. 4. The Fig. 4 shows the distribution of 137Cs from point P1 to P5. Compared with the reference site (P5), the half of 137Cs was lost from the surface of uncultivated soil at the points 1 and 2. At the point 3, the loss of 137Cs is about 14%, these points are considered erosion zone. In the last point (P4), we can see a redistribution of the 137Cs profile, therefore it can be considered as an accumulation zone.
6. Conclusions In this work, an attempt was made to develop locally a reliable computational procedure tailored for routine gamma-ray spectrometry analysis of large volume samples usually encountered in environmental applications. This procedure was based mainly on the use of a Monte Carlo method. Hence, the detailed MC geometrical model developed to evaluate the HPGe detector efficiency for large volume samples was duly validated. Through the performed calculations, it has been observed that the obtained MC efficiencies were slightly higher than the experimental ones, for different gamma ray energies of 152 Eu, by means of an average ratio of about 1.05. The agreement achieved between calculated and experimental efficiencies was considered as good to validate the MC geometrical model proposed in this work. Thereafter, the above-cited MC model was applied for a specific environmental application to assess the degree of soil erosion. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site. Thus, thanks to the developed MC model, the application of gamma spectrometry is very useful and practical for the analysis of a large volume samples in view to estimate accurately the movement and soil loss in agricultural sites or in the forest areas. Overall, following the encouraging results achieved through this study one can conclude that the proposed computational methodology is very attractive and powerful since it liberates the spectrometry measurement from its reliance on reference sources which might be, in some cases, very constraining for small laboratories. Finally, we intend in a near future to propose further calibration MC models representing large volume samples within different
matrices and geometries, in order, to cover the various environmental application of interest. References Abbas, K., Simonelli, F., D'Alberti, F., Forte, M., Stroosnijder, M.F., 2002. Reliability of two calculation codes for efficiency calibrations of HPGe detectors. Appl. Radiat. Isot. 56, 703e709. Agarwal, C., Chaudhury, S., Goswami, A., Gathibandhe, M., 2011. Full energy peak efficiency calibration of HPGe detector for point and extended sources using Monte Carlo code. J. Radioanal. Nucl. Chem. 287, 701e708. Aline, S.E. Santo, Francis, G. Wasserman, Claudio, C. Conti, 2012. HPGe well detector calibration procedure by MCNP5 Monte Carlo computer code. Ann. Nucl. Energy 46, 213e217. Andreotti, E., Hult, M., Marissens, G., Lutter, G., Garfagnini, A., Hemmer, S., vonSturm, K., 2014. Determination of dead-layer variation in HPGe detectors. Appl. Radiat. Isot. 87, 331e335. Bochud, F., Bailat, J.C., Buchillier, T., Byrde, F., Schmid, E., Laedermann, J.P., 2006. Simple Monte-Carlo method to calibrate well-type HPGe detectors. Nucl. Instrum. Methods A569, 790e795. Boshkova, T., 2014. Experimental assessment of the coincidence summing corrections in gamma-ray spectrometry of bulk samples. Appl. Radiat. Isot. 83, 1e7. Boson, J., Agren, G., Johansson, L., 2008. A detailed investigation of HPGe detector response for improved Monte Carlo efficiency calculations. Nucl. Instrum Methods A 587, 304e314. Canberra Industries, Solid-State Photon Detector, Operators Manual, GMX Series, HPGe (High-Purity Germanium). Chirosca, A., Suvaila, R., Sima, O., 2013. Monte Carlo simulation by GEANT 4 and GESPECOR of in situ gamma-ray spectrometry measurements. Appl. Radiat. Isot. 81, 87e91. Courtine, F., Pilleyre, T., Sanzelle, S., Miallier, D., 2008. Ge well detector calibration by means of a trial and error procedure using the dead layers as a unique parameter in a Monte Carlo simulation. Nucl. Instrum Methods A596, 229e234. Dababneh, S., Al-Nemri, E., Sharaf, J., 2014. Application of Geant4 in routine close geometry gamma spectroscopy for environmental samples. J. Environ. Radioact. 134, 27e34. Garcia-Talavera, M., Laedermann, J.P., Decoma, M., Dazaa, M.J., Quintana, B., 2001. Coincidence summing corrections for the natural decay series in gamma-ray spectrometry. Appl. Radiat. Isot. 54, 765e769. rrez-Villanueva, J.L., Martín-Martín, A., Pen a, V., Iniguez, M.P., de Celis, B., Gutie 2008. Calibration of a portable HPGe detector using MCNP code for thede137 termination of Cs in soils. J. Environ. Radioact. 99, 1520e1524. IAEA, 27 May 2014. Individual Evaluation Report. Laborie, J.M., Le Petit, G.L., Abt, D., Girard, M., 2000. Monte Carlo calculation of the efficiency calibration curve and coincidence-summing correction in low-level gamma-ray spectrometry using well-type HPGe detectors. Appl. Radiat. Isot. 53, 57e62. re, M.R., 2007. Assessment of erosion in the Boyer Mabit, L., Bernard, C., Laverdie River watershed (Canada) using a GIS oriented sampling strategy and 137Cs measurements. Catena 71, 242e249. Mostajaboddavati, M., Hassanzadeh, S., Faghihian, H., Abdi, M.R., Kamali, M., 2006. Efficiency calibration and measurement of absorption correction for environmental gamma-spectroscopy of soil samples using Marinelli beaker. J. Radioanal. Nucl. Chem. 268, 539e544. denas, J., Pascual, A., Zarzaa, I., Serradell, V., Ortiz, J., Ballesteros, L., 2003. Analysis Ro of the influence of germanium dead layer on detector calibration simulation for environmental radioactive samples using the Monte Carlo method. Nucl. Instrum. Methods A496, 390e399. denas, J., Gallardo, S., Ballester, S., Primault, V., Ortiz, J., 2007. Application of the Ro Monte Carlo method to the analysis of measurement geometries for the calibration of an HPGe detector in an environmental radioactivity laboratory. Nucl. Instrum. Methods B263, 144e148. Sima, O., Arnold, D., 2009. On the Monte Carlo simulation of HPGe gamma spectrometry systems. Appl. Radiat. Isot. 67, 701e705. X-5 Monte Carlo Team, 2003. MCNP e a General Monte Carlo N Particle Transport Code, Version 5. LA-UR-03-1987. In: Overview and Theory, vol. II. Los Alamos National Laboratory.
Contents lists available at ScienceDirect
Journal of Environmental Radioactivity journal homepage: www.elsevier.com/locate/jenvrad
Review
Monte Carlo calculations of the HPGe detector efficiency for radioactivity measurement of large volume environmental samples Ahmed Azbouche a, Mohamed Belgaid b, *, Hakim Mazrou a a b
Centre de Recherche Nucl eaire d'Alger, 02, Bd. Frantz Fanon, B.P. 399, 16000, Alger-Gare, Algiers, Algeria USTHB, Facult e de Physique, Laboratoire SNIRM, B.P. 32, El-Alia, 16111, Bab Ezzouar, Algiers, Algeria
a r t i c l e i n f o
a b s t r a c t
Article history: Received 1 October 2014 Received in revised form 13 April 2015 Accepted 17 April 2015 Available online
A fully detailed Monte Carlo geometrical model of a High Purity Germanium detector with a 152Eu source, packed in Marinelli beaker, was developed for routine analysis of large volume environmental samples. Then, the model parameters, in particular, the dead layer thickness were adjusted thanks to a specific irradiation configuration together with a fine-tuning procedure. Thereafter, the calculated efficiencies were compared to the measured ones for standard samples containing 152Eu source filled in both grass and resin matrices packed in Marinelli beaker. From this comparison, a good agreement between experiment and Monte Carlo calculation results was obtained highlighting thereby the consistency of the geometrical computational model proposed in this work. Finally, the computational model was applied successfully to determine the 137Cs distribution in soil matrix. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site. © 2015 Elsevier Ltd. All rights reserved.
Keywords: Monte Carlo simulation Detector efficiency Germanium dead layer 152 Eu Marinelli source Gamma-ray spectrometry 137 Cs distribution in soil
1. Introduction Gamma-ray spectrometry is a common technique widely used for identification and quantification of radionuclides in samples of different matrices and geometries. This technique offers an advantage of being rapid and non-destructive and does not require any special sample treatment. Moreover, the use of high purity germanium (HPGe) detectors with high energy resolution allows identification and activity measurement of natural and artificial radionuclides in biological, geological and environmental samples, with the highest possible sensitivity. However, for large volume samples, the use of multi-gamma radionuclide for calibration procedure of the activity measurements fails in determining the activity of different radionuclides with a sufficient accuracy due mainly to an under estimation of the detector efficiency. In reality, the lack of standard sources with different geometries and matrices makes the experimental determination of the detector efficiency, an arduous task (Abbas et al., 2002; Mostajaboddavati et al., 2006; Chirosca et al., 2013).
* Corresponding author. Fax: þ213 21 247344. E-mail address: [email protected] (M. Belgaid). http://dx.doi.org/10.1016/j.jenvrad.2015.04.015 0265-931X/© 2015 Elsevier Ltd. All rights reserved.
Nowadays and in order to overcome the above cited difficulty encountered in such cases, most of the small and existing environmental radioactivity laboratories have developed and validated their own counting procedures for routine analysis of large volume samples using gamma-ray spectrometry. To reach this purpose, an attempt was made to develop locally a reliable computational rrez-Villanueva model useful for environmental applications (Gutie et al., 2008; Dababneh et al., 2014). The Monte Carlo (MC) method is well appropriate to perform the calibration and to reproduce the detector response for a variety of matrices and for different ge denas ometries with sufficient accuracy (Bochud et al., 2006; Ro et al., 2007; Sima and Arnold, 2009; Chirosca et al., 2013). In this work, the Monte Carlo computer code MCNP5 (X-5 Monte Carlo Team, 2003) is used to develop a detailed geometrical model to a HPGe detector together with an 152Eu multigamma source, in a Marinelli beaker geometry, to evaluate accurately the detector efficiency for large volume sources. The choice of 152Eu as a multi-gamma ray source for the calibration of the detector efficiency is justified by its availability and cheapness, its relatively long life-time and the wide energy range (120e1600 keV). Unfortunately, this source emits gamma rays in cascade, which, at distances close to the detector, cause, coincidence summing that one should carefully take into account since it's one of the main effect that can modify substantially the detector
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efficiency value (Laborie et al., 2000; Garcia-Talavera et al., 2001; Agarwal et al., 2011). The nominal dimensions of the detector of interest as specified by the manufacturer were first taken to develop the initial geometrical model. Then, by means of a specific measurement configuration using two reference point sources (241Am, 137Cs) located at five positions in front and around the detector, a finetuning procedure was applied to adjust the model parameters, in particular, the dead layer thickness. Thereafter, the proposed Monte-Carlo geometrical model was validated against measurements obtained using two standard sources, provided and certified by LEA (Laboratoire Etalons d’Activit e, Division de CERCA, France). Finally, the proposed MC model was applied for the same measurement configuration, using the same geometry (Marinelli beaker), to determine the detection efficiency curve for a 152Eu source filled in matrix soil. The obtained value was used to estimate accurately the activity of 137Cs on a soil sample in order to evaluate the degree of soil erosion.
A p-type HPGe detector model, GX-3519, with a carbon-epoxy entrance window manufactured by CANBERRA (Canberra Industries), is used for routine gamma spectrometric analysis in the environmental laboratory. The detector has the following specifications: 35% relative efficiency at 1.33 MeV gerays relative to a 00 00 3 3 NaI(Tl) crystal, 1.85 keV resolution (FWHM) at 1332.5 keV and 0.86 keV at 122 keV, with an amplifier shaping time constant of 4 ms, the detector had a 68.2 peak-to-Compton ratio for 60Co. The Desktop Spectrum Analyzer DSA 1000 was used in this work. The detector was surrounded with 114 mm-thick graded lead shield (Canberra 747 Series Lead Shield), with liners of 3 mm of tin and 1.5 mm of copper to reduce the contribution to the spectrum of the lead X-rays, achieving a low background needed in environmental applications. Two 152Eu sources where considered: a source with 4.17 kBq activity (relative uncertainty 5% with a coverage factor k ¼ 2), with a gamma impurity of about 0.49% of 154Eu, at the time of measurement, imbedded in a resin matrix (C18H20O3) having 1.15 g cm3 in density and a 5.39 kBq source (relative uncertainty 5% for k ¼ 3), with a 0.33% gamma impurity at the time of measurement, mixed in grass (C6H12O6) with a density of 0.6 g cm3. The spectra sources were collected over 7000 s, to obtain good counting statistics, with dead time less than 2%; all spectra were treated using Genie 2000 (Canberra Industry). The experimental detector efficiency is given by:
N APtc
N εPtc
(2)
N εCSCPtc
(3)
Auncor labo ðEÞ ¼
AIAEA ¼
The coincidence summing correction factors deduced are listed herein in Table 1.
2. Experiment
ε¼
Laboratory) of IAEA Laboratories in Seibersdorf (Austria). The sample was a water solution containing g-emitting radionuclide, including 60Co, 152Eu and 241Am. The activity concentration of 152 Eu certified by IAEA was 49.9 ± 0.41 Bq kg1 (IAEA, evaluation Report, 2014). The method consists to pack an amount 400 cm3 of volume of spiked water in the Marinelli beaker and measure during 30,000 s. The coincidence summing correction factors (CSC) were obtained by dividing the activity Auncor ðEÞ of 152Eu measured in the labo laboratory for each gamma energy without correction, by the reference activity AIAEA, according to the following equations:
(1)
where N is the net area at the interest peak energy, corrected for background counts, A is the source activity in Becquerel with decay time correction; tcis the collection time in second and P is the gamma ray emission probability. In this work, the effect of the coincidence summing on the efficiency calibration has been taken into account in order to improve the experimental efficiency results (Boshkova, 2014). The measured efficiencies were corrected by the coincidence summing correction factors by using the results issued from our participation in the proficiency test carried out in 2013, under the auspice of the International Atomic Energy Agency (IAEA-TEL2013-01 TEL/SWMCN proficiency test). The analyzed sample was a spiked water given by SWMCN (Soil and Water & Crop Nutrition Laboratory) in cooperation with TEL (Terrestrial Environment
3. Monte Carlo calculation 3.1. Monte Carlo detector model The experimental setup was modeled using the Monte Carlo NParticle Transport Code (MCNP5) developed by Los Alamos National Laboratory. A detailed physical treatment, including the photoelectric effect with the resulting X-ray fluorescence, the incoherent scattering with form factors and pair production, were considered in the energy range between 1 and 1500 keV. The F8 tally and GEB (Gaussian Energy Broadening) card options of the MCNP5 code was used. This tally calculates the absolute fullenergy peak efficiency of the detector with energies lying in the interval [1e1500 keV]. The GEB option allows the incorporation of the detector's resolution (energy broadening) at various photon energies. For this purpose, the Full Width at Half Maximum (FWHM) of the experimental data was fitted by the following function:
FWHMðMeVÞ ¼ a þ b
pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi E þ cE2
(4)
where E is the energy of the incident particle in MeV, and for the detector used in this work a ¼ 0.707 103 MeV, b ¼ 0.946 103 MeV1/2 and c ¼ 0. The simulated spectrum was binned with an energy window of 0.5 keV/channel, to reproduce the experimental conditions. The MC model used for the HPGe detector in Marinelli beaker geometry is shown in Fig. 1. In Fig. 1, the Marinelli beaker sits directly on top of the detector to provide relatively a high-efficiency. The description of the detector-Marinelli source geometry was given in detail in the cell and surface cards of the MCNP input file. It is described with 14 cells and 21 surfaces. In Fig. 2, both measured and simulated spectra can be seen. The qualitative spectrum obtained in Fig. 2 was simulated with PE mode, 31 gammas energies of the 152Eu were introduced in MCNP input file, which were emitted according to its two modes of decay. The Samarium and Gadolinium characteristics X-ray region, from the energy range 40 keVe50 keV produced during the 152Eu decay are not used in the simulation and consequently did not appear in this figure.
A. Azbouche et al. / Journal of Environmental Radioactivity 146 (2015) 119e124 Table 1 Correction factors of coincidence effects for
152
Eu source in 400 ml Marinelli beaker.
Nuclide
Energy (keV)
Activity measured Uncorrected (Bq/kg)
152
121.78 244.66 344.31 443.98 778.72 867.38 964.01 1085.79 1112.04 1408.02
45.6 44.7 45.7 45.5 44.2 43.0 46.5 51.4 47.8 47.5
Eu
121
± ± ± ± ± ± ± ± ± ±
1.02 1.01 1.02 1.01 1.00 0.92 1.02 1.06 1.05 1.04
Activity reference IAEA (Bq/kg) 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9 49.9
± ± ± ± ± ± ± ± ± ±
0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41 0.41
Fig. 1. 2D view of Marinelli beaker and HPGe detector modeled with MCNP5.
Fig. 2.
152
Eu spectrum source in resin matrix obtained experimentally and with MCNP5.
Coincidence factor 0.914 0.896 0.915 0.912 0.885 0.862 0.932 1.031 0.958 0.951
± ± ± ± ± ± ± ± ± ±
0.024 0.024 0.024 0.024 0.024 0.024 0.023 0.025 0.023 0.023
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Table 2 Germanium detector crystal details given by manufacturer and adjusted by simulation. Germanium detector details
Nominal value (mm) Adjusted value (mm)
Germanium crystal diameter Crystal length Core hole diameter Core hole depth Dead layer thickness (front) Side dead layer (side) Germanium front to inside of end cap distance Carbon epoxy window thickness End cap material Al thickness
60.5 61 12 51 0.004 0.004 5
59.5 60.5 12 51 0.05 0.05 5
0.5 1.5
0.5 1.5
3.2. Dead layer estimation The dead layer thickness of a given germanium detector is an important parameter that can affect drastically its response. Many authors have highlighted the dead layer influence on the response of germanium detectors for medium and high gamma-ray energy denas et al., 2003; Boson et al., 2008; Courtine et al., 2008; range (Ro Aline et al., 2012; Andreotti et al., 2014). In fact, they reported that the dead layer thickness is often greater than the nominal value given by the manufacturers. Consequently, this parameter is always subject to a continuous evaluation. In this work, the dead layer thickness of a newly acquired HPGe detector was estimated using a specific irradiation geometrical configuration together with a fine-tuning procedure. For this purpose, the experimental set-up consisted mainly in collimating two reference point sources: 241Am (59.5 keV) and 137Cs (661.6 keV), positioned successively at five different locations; the first one was located in front of the detector and the remaining four positions were situated around the detector. Due to their small energy, the 241Am gamma-rays has been used to adjust the estimation of the external thickness of the dead layer due to the low penetration of the photon in the crystal. The 137Cs gamma-rays were used to adjust the internal dead layer since their energy (661.6 keV) has a large penetration (mean free path is 26.5 mm) in the germanium crystal (Courtine et al., 2008). The adjustment procedure used herein to estimate the dead layer thickness of the germanium detector is based on a gradual increase of the dead layer thickness i.e. in a stepwise process from its initial value (given by the manufacturer) till to its final value. At each step where a new value of the dead layer thickness is suggested, a series of comparison between experimental intrinsic efficiencies with the MC results, obtained at five chosen locations, is performed. The calculation procedure stops when the mean difference between experimental and calculated intrinsic
Table 3 Comparison of experimental and simulated efficiencies for Nuclide
152
Eu
Mean ± SD
efficiencies at these five locations is below 5%. This corresponds to the average uncertainty of our experimental measurements. The final results achieved following this adjustment procedure are given in Table 2. In Table 2, one can see that the nominal value of the dead layer provided by the manufacturer was 4 mm, whether the calculated one was increased by a factor of 12. However, this value remains reasonable comparatively to those found in the literature. 4. Validations of Monte Carlo results For the detector-Marinelli source model in both resin and grass matrices, the main gamma ray energies of 152Eu are used,108 incident photons were simulated, to achieve a relative statistical uncertainty of less than 1% for the considered peaks. The results of the experimental and calculated efficiencies, for the 152Eu source mixed with grass and resin in a Marinelli beaker are listed in Table 3. The MC calculated efficiencies were found to be slightly higher than the experimental efficiencies. The relative uncertainty associated to simulated values of efficiency with MCNP5 code is less than 1% and the maximum uncertainty associated to experimental value is about 3%. The MCNP5-to-experimental efficiency ratios are also given in Table 3 with an average uncertainty less than 5%. The agreement achieved between calculated and experimental efficiencies is considered as good enough to validate the MC geometrical model proposed in this work. 5. Application for environmental samples analysis 5.1. Detector efficiency calculation in soil matrix In this section, the developed MC detector-Marinelli source model was applied to calculate the full peak energy efficiency for a 152 Eu source in soil matrix. The physical characteristics of the soil used in the simulation were determined experimentally: the soil sample was dried in air, and then it was sieved at 2 mm to remove the larger particles. After homogenization, a quantity about 550 mg (z400 ml) of soil was conditioned in the same Marinelli beaker used in the calibration. The measured bulk density of soil sample is about 1.35 g cm3. The detailed elemental composition of the soil needed by the MCNP5 code input file was obtained by analyzing small quantities of soil using the Wavelength Dispersive X-Ray Fluorescence (WDXRF) method. The WDXRF spectrometer Model used in this work is a MagixPro (Panalytical ex Philips) equipped with an X-ray tube with a Rhodium anode, and a series of eight crystal analyzers covering the analytical range of elements from Bore to Uranium. It is also
152
Eu Marinelli source mixed in resin and grass matrix.
Resin matrix
Grass matrix
Energy (keV)
Exp efficiency 102
121.78 244.66 344.31 443.98 778.72 867.38 964.01 1085.79 1112.04 1408.02
6.60 4.62 3.88 2.99 1.99 1.83 1.69 1.60 1.55 1.31
± ± ± ± ± ± ± ± ± ±
0.19 0.12 0.09 0.06 0.04 0.03 0.03 0.04 0.03 0.02
MCNP efficiency 102
MCNP/Exp ratio
Exp efficiency 102
7.17 5.10 4.07 3.12 2.05 1.92 1.71 1.69 1.58 1.32
1.09 1.10 1.05 1.04 1.03 1.05 1.01 1.06 1.02 1.01 1.05 ± 0.03
7.59 5.56 4.52 3.58 2.34 2.07 1.92 1.78 1.70 1.42
± ± ± ± ± ± ± ± ± ±
0.20 0.18 0.12 0.11 0.08 0.07 0.06 0.06 0.05 0.04
MCNP efficiency 102
MCNP/Exp ratio
8.13 6.01 4.79 3.65 2.45 2.13 1.98 1.89 1.75 1.46
1.07 1.08 1.06 1.02 1.05 1.03 1.03 1.06 1.03 1.02 1.04 ± 0.02
A. Azbouche et al. / Journal of Environmental Radioactivity 146 (2015) 119e124 Table 4 Mass fraction of soil composition used in Monte Carlo simulations. Element
Formula
Mass fraction (%)
Mg Al Si P K Ca Fe Ti
MgO Al2O3 SiO2 P2O5 K2O CaO Fe2O3 TiO2
1.72 15.01 54.81 0.12 2.70 16.84 7.33 0.97
± ± ± ± ± ± ± ±
0.05 0.50 0.80 0.03 0.08 0.90 0.30 0.16
The mass fraction of the elemental composition of the soil, as used in MCNP5 code, is reported in Table 4. The developed MC detector-Marinelli source model was used consequently to simulate the efficiency calibration in a soil matrix. The full peak energy efficiency curve for 152Eu source energies calculated by the MCNP5 code is shown in Fig. 3. These results allow determining the detector efficiency in the energy interval between 120 and 1500 keV commonly used for several applications in a terrestrial environmental laboratory. According to the simulation results obtained, the efficiency of detector increases as the density of the matrix decreases, this is due to the associated decrease in photon attenuation within the sample. The efficiency detector value at 661.6 keV for Marinelli source in soil matrix deduced from the efficiency curve is found to be ε ¼ 0.0219. 5.2.
Fig. 3. Efficiency curve of 152Eu source for Marinelli geometry in soil matrix calculated by simulation.
equipped with three detectors used for X-ray measurements: the first one is a gas flow counter, the second one is a proportional counter sealed Xenon and the third one is a scintillation detector used for high energy X-ray measurements.
Fig. 4.
137
123
137
Cs distribution in soil
After calibrating the gamma rays spectrometry technique with the Monte Carlo method, the efficiency results can be used in the determination of the specific activities of radionuclides in soil for many applications. In this work, an application example of the model results is given to determine the 137Cs concentration in soil to assess the degree of soil erosion. Soil samples from an eroded land in North West of Algeria were examined. Samples from small watershed area and a forest which, a 1 km away, was considered as a reference site, since such soil has not been disturbed by erosion. Four separate profiles were collected at four points (P1, P3, P4, P5), including one profile, P5, collected at the reference site (Fig. 4). For each sampling point, pedological pits (dimensions 30 30 30 cm) were dug and six samples at the depths 0e5, 5e10. 10e15, 15e20, 20e25 and 25e30 cm were taken (Mabit et al., 2007). One point was sampled at the surface (P2). A total of 25 samples were stored in plastic bags labeled according to the depth, and were transported in the laboratory. After the preparation and conditioning in Marinelli beaker, the samples were measured during 86,400 s to obtain a good counting statistics. The 137Cs was identified in the spectrum by the 661.6 keV gamma-ray energy.
Cs distribution in the soil profile along the watershed and at the reference site.
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The activity concentration, As (Bq/kg), of the 137Cs in the soil was determined as:
As ¼
N εPtc m
(5)
where, ε is the detector efficiency at 661.6 keV, obtained from exponential fitted curve shown in Fig. 3, m is the sample weight in kg and Ig, P, tc, were defined in the Eq. (1). The vertical distributions of the 137Cs in the soil profile along the watershed caused by the erosion and accumulation phenomena and at the reference site are given in Fig. 4. The Fig. 4 shows the distribution of 137Cs from point P1 to P5. Compared with the reference site (P5), the half of 137Cs was lost from the surface of uncultivated soil at the points 1 and 2. At the point 3, the loss of 137Cs is about 14%, these points are considered erosion zone. In the last point (P4), we can see a redistribution of the 137Cs profile, therefore it can be considered as an accumulation zone.
6. Conclusions In this work, an attempt was made to develop locally a reliable computational procedure tailored for routine gamma-ray spectrometry analysis of large volume samples usually encountered in environmental applications. This procedure was based mainly on the use of a Monte Carlo method. Hence, the detailed MC geometrical model developed to evaluate the HPGe detector efficiency for large volume samples was duly validated. Through the performed calculations, it has been observed that the obtained MC efficiencies were slightly higher than the experimental ones, for different gamma ray energies of 152 Eu, by means of an average ratio of about 1.05. The agreement achieved between calculated and experimental efficiencies was considered as good to validate the MC geometrical model proposed in this work. Thereafter, the above-cited MC model was applied for a specific environmental application to assess the degree of soil erosion. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site. Thus, thanks to the developed MC model, the application of gamma spectrometry is very useful and practical for the analysis of a large volume samples in view to estimate accurately the movement and soil loss in agricultural sites or in the forest areas. Overall, following the encouraging results achieved through this study one can conclude that the proposed computational methodology is very attractive and powerful since it liberates the spectrometry measurement from its reliance on reference sources which might be, in some cases, very constraining for small laboratories. Finally, we intend in a near future to propose further calibration MC models representing large volume samples within different
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