Monte Carlo simulation by GEANT 4 and GESPECOR of in situ gamma-ray spectrometry measurements

Soil radioactivity-depth profiles from regularized inversion of borehole gamma spectrometry data

An in situ borehole gamma logging method using a LaBr₃ gamma detector has been developed to characterize a¹³⁷Cs contaminated site. The activity-depth distribution of ¹³⁷Cs was derived by inversion of the in situ measurement data using two different least squares methods, (i) Least squares optimization (LSO) and (ii) Tikhonov regularization. The regularization parameter (λ) of the Tikhonov regularization method was estimated using three different methods i.e. the L-curve, Generalized Cross Validation (GCV) and a prior information based method (PIBM). The considered inversion method variants were first validated for a¹³⁷Cs contaminated pipe, and in most of the cases, the calculated activity of ¹³⁷Cs was found to be within the acceptable range. The calculated ¹³⁷Cs activity-depth profiles from in situ measurements were also in good agreement with the ones obtained from soil sample analysis, with an R² ranging from 0.76 to 0.82. The GCV method for estimating λ appeared to perform better than the two other methods in terms of R² and root mean squared error (RMSE). The L-curve method resulted in higher RMSE than the other Tikhonov regularization methods. Instability was observed in the activity concentration depth profile obtained from the LSO method. Therefore, we recommend the Tikhonov regularization with GCV for estimating λ for estimating the activity concentration-depth profile. The site studied showed ¹³⁷Cs activity concentrations above the exemption limit down to depths of 0.50-0.90 m.

Study of coincidence summing effect using Monte Carlo simulation to improve large samples measurement for environmental applications

A new measurement model composed of High Purity Germanium detector HPGe including Lead Shield with a mixed source of Am-241, Cd-109, …in a soil matrix packed in a cylindrical container was developed by Monte Carlo N-Particles code MCNP5. The Monte Carlo models being largely used for efficiencies calculations in routine environmental radioactivity measurements of high volume soil samples. In order to validate the simulation, a multi-radionuclides soil matrix source in a cylindrical container is prepared. Comparing the simulated results to the experimental ones, allows us to correct coincidence summing in the soil standard and study its effect in activity measurements where a good agreement is found between corrected activities and results found by another geometry and show how uncorrected efficiency curves lead to erroneous activity calculation. Finally, the developed model is applied to study the distribution of natural and artificial radioactivity in a forest site in Bainem, northern of Algeria, these results are invested for radiological impact and soil erosion studies in the study Area.

Optimization and validation of a LaBr3(Ce) detector model for use in Monte Carlo simulations

A reliable detector model is needed for Monte Carlo efficiency calibration. A LaBr₃(Ce) detector model was optimized and verified using different radioactive sources (²⁴¹Am,¹³³Ba,¹³⁷Cs,⁶⁰Co and¹⁵²Eu) and geometries (point, extended and surface). PENELOPE and MCNP were used for Monte Carlo simulations. A good agreement was observed between simulated and experimental full energy peak efficiencies (FEPE) as their mean relative difference was 2.84% ± 1.93% and 2.79% ± 1.99% for PENELOPE and MCNP simulation, respectively. The differences between simulated FEPEs of two Monte Carlo codes were negligible except for low energies (< 100 keV).

A benchmark for Monte Carlo simulation in gamma-ray spectrometry

Monte Carlo (MC) simulation is widely used in gamma-ray spectrometry, however, its implementation is not always easy and can provide erroneous results. The present action provides a benchmark for several MC software for selected cases. The examples are based on simple geometries, two types of germanium detectors and four kinds of sources, to mimic eight typical measurement conditions. The action outputs (input files and efficiency calculation results, including practical recommendations for new users) are made available on a dedicated webpage.

Investigating the potentialities of Monte Carlo simulation for assessing soil water content via proximal gamma-ray spectroscopy

Proximal gamma-ray spectroscopy recently emerged as a promising technique for non-stop monitoring of soil water content with possible applications in the field of precision farming. The potentialities of the method are investigated by means of Monte Carlo simulations applied to the reconstruction of gamma-ray spectra collected by a NaI scintillation detector permanently installed at an agricultural experimental site. A two steps simulation strategy based on a geometrical translational invariance is developed. The strengths of this approach are the reduction of computational time with respect to a direct source-detector simulation, the reconstruction of ⁴⁰K, ²³²Th and ²³⁸U fundamental spectra, the customization in relation to different experimental scenarios and the investigation of effects due to individual variables for sensitivity studies. The reliability of the simulation is effectively validated against an experimental measurement with known soil water content and radionuclides abundances. The relation between soil water content and gamma signal is theoretically derived and applied to a Monte Carlo synthetic calibration performed with the specific soil composition of the experimental site. Ready to use general formulae and simulated coefficients for the estimation of soil water content are also provided adopting standard soil compositions. Linear regressions between input and output soil water contents, inferred from simulated ⁴⁰K and ²⁰⁸Tl gamma signals, provide excellent results demonstrating the capability of the proposed method in estimating soil water content with an average uncertainty <1%.

Measurements of 106Ru in Sweden during the autumn 2017: Gamma-ray spectrometric measurements of air filters, precipitation and soil samples, and in situ gamma-ray spectrometry measurement

During the last days of September to the first days of October in 2017, a unique detection of ¹⁰⁶Ru was observed in air filters sampled at different locations in Sweden via the national air monitoring network. Furthermore, measurements of precipitation also showed the presence of ¹⁰⁶Ru. This initiated soil sampling and in situ gamma-ray spectrometry at one of the locations.

Monte Carlo calculations of the HPGe detector efficiency for radioactivity measurement of large volume environmental samples

A fully detailed Monte Carlo geometrical model of a High Purity Germanium detector with a (152)Eu 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 (152)Eu 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 (137)Cs distribution in soil matrix. From this application, instructive results were achieved highlighting, in particular, the erosion and accumulation zone of the studied site.