A new FSA approach for in situ γ ray spectroscopy

Determination, Separation and Application of 137Cs: A Review

In the context of the rapid development of the world's nuclear power industry, it is necessary to establish background data on radionuclides of different samples from different regions, and the premise of obtaining such basic data is to have a series of good sample processing and detection methods. The radiochemical analysis methods of low-level radionuclides ¹³⁷Cs (Cesium) in environmental and biological samples are introduced and reviewed in detail. The latest research progress is reviewed from the five aspects of sample pretreatment, determination, separation, calculation, application of radioactive cesium and the future is proposed.

In-situ γ-ray analysis of ground surface radioactivity using portable HPGe γ spectrometer

As essential high-end equipment for nuclear emergency monitoring, the portable HPGe γ spectrometer currently lacks supporting in-situ measurement methods, limiting its role and value in emergency missions. For this practical problem, this paper studies the measurement of ground surface radioactivity by portable HPGe γ spectrometer in nuclear emergency monitoring in view of the particularity of nuclear emergency source items. Firstly, the detection efficiency of point sources at different horizontal distances when the spectrometer is installed at the height of 1 m from the center of the detector to the ground is calculated. Secondly, the concept of effective contribution distance is defined and analyzed. Thirdly, the point source detection efficiency is obtained using the numerical integration method of calculation. Integrate to calculate the detection efficiency of the surface source, and then calculate the radioactive surface activity of the surface. Finally, the effectiveness of the method is verified through experiments.

Dependence of photon registration efficiency on LaBr3(Ce) detector orientation for in situ radionuclide monitoring

Knowledge of a radiation detector's numerical characteristics allows its energy efficiency to be calibrated theoretically for any measurement geometry. Here, energy efficiency calibration is discussed for oriented LaBr₃(Ce) detectors used for in situ radiation monitoring. Vertical and horizontal detector orientations relative to the ground surface are compared using efficiency calibrations based on the detector's numerical characteristics and are equally effective. Quantitative assessment of the different measurement geometries was performed using a new analytical approach: integrated absolute full energy peak efficiency.

An Easily Integrable Industrial System for Gamma Spectroscopic Analysis and Traceability of Stones and Building Materials

In the building material and stones market, lots of restrictions are coming in different world zones. In Europe, a recent regulatory set up the maximum level of radiological emissions for materials intended for use in public and private building structures. For this reason, companies need to have a very efficient radiological measurements system in their production chain, in order to respect all the rules and to be competitive in the world market. This article describes CORSAIR, a Cloud-Oriented Measurement System for Radiological Investigation and Traceability of Stones. Our cyber-physical system consists of sensing nodes network connected to a data collection gateway through LoRaWAN protocol, and interfaces with a centralized cloud application. CORSAIR introduces a fast, repeatable, real-time and non-destructive method to measure radiological emissions and other parameters of each single building material item, uniquely identified by an applied RFID tag. The validity of this system is confirmed by in-situ measurement campaign compared with high-precision laboratory analysis. The results demonstrate the accuracy of the CORSAIR sensor and the possibility to easily integrate it in the company production chain without any change.

Near real-time soil erosion mapping through mobile gamma-ray spectroscopy

Soil erosion has been associated with various negative environmental impacts foremost of which is the potential pressure it could impose on global food security. The poor conditions of our agricultural soil can be attributed to years of unsustainable farming practices occurring throughout history that has placed significant pressure on the environment. Moreover, climate change scenarios indicate further intensification which is likely making prediction and assessment of erosion processes critical for long term agricultural sustainability. This study demonstrates the potential of mobile gamma-ray spectrometry with large volume NaI(Tl) detectors to identify, at high spatial resolution, changes in ¹³⁷Cs soil concentration within the ploughed layer of soil and enabling the soil erosion processes to be quantified. This technique represents a significant advantage over conventional spatially-isolated point measurements such as soil sampling as it offers real time mapping at the field scale. However, spectral signal derived from measurements in the field are highly dependent on the calibration procedure used and are particularly sensitive to source-detector changes such as the presence of a vehicle, ground curvature and soil moisture content. Conventional calibration procedures tend to not consider these potential sources of uncertainty potentially leaving the system vulnerable to systematic uncertainties, especially when 137Cs concentrations are low. This study used Monte Carlo simulations to investigate such changes utilising additional information including a high-resolution digital terrain model. The method was demonstrated on a ploughed site in Scotland, revealing a mixture of tillage and water erosion patterns supported by soil core data. Findings showed that the sites topography had relatively little effect (<10%) on calculated erosion rates, but moisture content could be the determining factor, albeit very difficult to measure reliably throughout a survey.

Advances in detection algorithms for radiation monitoring

This paper presents a review of up-to-date advancements in detection algorithms employed in radiation monitoring for generating radiation maps of ground contamination and tracking radioactive release into the atmosphere. Detection algorithms for true count processing, spectroscopy processing, and plume tracking are discussed in chronological order of development. Process steps of detection include height correction, solid-angle correction, background radioactivity correction, Compton continuum elimination, de-noising of gamma-radiation spectra, and recording of plume passage events.

Validation of gamma scanning method for optimizing NaI(Tl) detector model in Monte Carlo simulation

The aim of this study is the validation of gamma scanning method for optimizing NaI(Tl) detector model in Monte Carlo simulation. The experimental procedure involved: scanning on front and lateral surfaces of the detector with collimated low-energy photon beam; calibrating the efficiency with energies between 31-1408 keV for point sources at distances of 0 cm and 30 cm from source to the detector. The Monte Carlo code used for the simulations was MCNP6. The diameter and the length of crystal were determined according to the measured results of gamma scanning with a collimated ²⁴¹Am radioactive source. The distance from window to crystal was estimated using transmission measurement recorded on a second detector. The density of reflector was adjusted to obtain the match between measured and simulated values of efficiency ratio of 81 and 31 keV from a ¹³³Ba radioactive source. The optimized model was applied in Monte Carlo simulations to determine the efficiency and energy spectrum response function of NaI(Tl) detector for point source measurements in two configurations. Good agreement was obtained between measured and simulated results.

Training Future Engineers to Be Ghostbusters: Hunting for the Spectral Environmental Radioactivity

Although environmental radioactivity is all around us, the collective public imagination often associates a negative feeling to this natural phenomenon. To increase the familiarity with this phenomenon we have designed, implemented, and tested an interdisciplinary educational activity for pre-collegiate students in which nuclear engineering and computer science are ancillary to the comprehension of basic physics concepts. Teaching and training experiences are performed by using a 4” × 4” NaI(Tl) detector for in-situ and laboratory γ-ray spectroscopy measurements. Students are asked to directly assemble the experimental setup and to manage the data-taking with a dedicated Android app, which exploits a client-server system that is based on the Bluetooth communication protocol. The acquired γ-ray spectra and the experimental results are analyzed using a multiple-platform software environment and they are finally shared on an open access Web-GIS service. These all-round activities combining theoretical background, hands-on setup operations, data analysis, and critical synthesis of the results were demonstrated to be effective in increasing students’ awareness in quantitatively investigating environmental radioactivity. Supporting information to the basic physics concepts provided in this article can be found at http://www.fe.infn.it/radioactivity/educational.

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%.

Accuracy of Flight Altitude Measured with Low-Cost GNSS, Radar and Barometer Sensors: Implications for Airborne Radiometric Surveys

Flight height is a fundamental parameter for correcting the gamma signal produced by terrestrial radionuclides measured during airborne surveys. The frontiers of radiometric measurements with UAV require light and accurate altimeters flying at some 10 m from the ground. We equipped an aircraft with seven altimetric sensors (three low-cost GNSS receivers, one inertial measurement unit, one radar altimeter and two barometers) and analyzed ~3 h of data collected over the sea in the (35–2194) m altitude range. At low altitudes (H < 70 m) radar and barometric altimeters provide the best performances, while GNSS data are used only for barometer calibration as they are affected by a large noise due to the multipath from the sea. The ~1 m median standard deviation at 50 m altitude affects the estimation of the ground radioisotope abundances with an uncertainty less than 1.3%. The GNSS double-difference post-processing enhanced significantly the data quality for H > 80 m in terms of both altitude median standard deviation and agreement between the reconstructed and measured GPS antennas distances. Flying at 100 m the estimated uncertainty on the ground total activity due to the uncertainty on the flight height is of the order of 2%.

In the Field Feasibility of a Simple Method to Check for Radioactivity in Commodities and in the Environment

INTRODUCTION

Some release of radionuclides into the environment can be expected from the growing number of nuclear plants, either in or out of service. The citizen and the big organization could be both interested in simple and innovative methods for checking the radiological safety of their environment and of commodities, starting from foods.

METHODS

In this work three methods to detect radioactivity are briefly compared  focusing on the most recent, which converts a smartphone into a radiation counter.

RESULTS

The results of a simple sensitivity test are presented showing the measure of the activity of reference sources put at different distances from each sensor.

DISCUSSION

The three methods are discussed in terms of availability, technology, sensitivity, resolution and usefulness. The reported results can be usefully transferred into a radiological emergency scenario and they also offer some interesting implication for our current everyday life, but show that the hardware of the tested smart-phone can detect only high levels of radioactivity. However the technology could be interesting to build a working detection and measurement chain which could start from a diffused and networked first screening before the final high resolution analysis.

CONVERTING SPECIFIC ACTIVITY INTO AMBIENT DOSE EQUIVALENT: UPDATED COEFFICIENTS FOR IN SITU GAMMA SPECTROMETRY

In situ gamma spectrometry is a valuable tool to assess the radionuclides released in the environment and the associated dose. This requires prior establishment of coefficients allowing the conversion of the specific activity into ambient equivalent dose. The aim of this work is to calculate updated conversion factors for monoenergetic photons and for a series of radionuclides of interest. The calculation was performed using the Monte Carlo (MC) method, the GEANT4 MC code, various activity distribution models and up-to-date nuclear decay data. A new set of conversion factors is established in the energy range extending from  <100 keV to 8.5 MeV. The coefficients calculated in this work were compared to the data published in the literature.

Efficiency calibration for in situ γ-ray measurements on the seabed using Monte Carlo simulations: Application in two different marine environments

A new approach for calibrating an in situ detection system for measurements in marine sediments has been developed. The efficiency calibration was deduced on full spectral range by Monte Carlo simulations (MCNP5 code) considering a close detector-seabed geometry set-up. Moreover, the influence of the detection efficiency with respect to the variations of the sediment geological characteristics was studied through Monte Carlo simulations. The results of the theoretical approach were compared with experimental calculations in two different real test cases, yielding a satisfactory agreement (up to 10% and 20% for sites 1 and 2 respectively) in the energy range from 351 keV to 2614 keV. For the experimental measurements, the in situ detection system KATERINA was deployed both in the seawater and on the seabed in two different marine environments. The experimental determinations of the detection efficiency were performed by utilizing the acquired data of the deployments, along with additional necessary laboratory measurements. The adopted approach and the obtained results are discussed.

Mapping the spatial distribution and activity of (226)Ra at legacy sites through Machine Learning interpretation of gamma-ray spectrometry data

Radium ((226)Ra) contamination derived from military, industrial, and pharmaceutical products can be found at a number of historical sites across the world posing a risk to human health. The analysis of spectral data derived using gamma-ray spectrometry can offer a powerful tool to rapidly estimate and map the activity, depth, and lateral distribution of (226)Ra contamination covering an extensive area. Subsequently, reliable risk assessments can be developed for individual sites in a fraction of the timeframe compared to traditional labour-intensive sampling techniques: for example soil coring. However, local heterogeneity of the natural background, statistical counting uncertainty, and non-linear source response are confounding problems associated with gamma-ray spectral analysis. This is particularly challenging, when attempting to deal with enhanced concentrations of a naturally occurring radionuclide such as (226)Ra. As a result, conventional surveys tend to attribute the highest activities to the largest total signal received by a detector (Gross counts): an assumption that tends to neglect higher activities at depth. To overcome these limitations, a methodology was developed making use of Monte Carlo simulations, Principal Component Analysis and Machine Learning based algorithms to derive depth and activity estimates for (226)Ra contamination. The approach was applied on spectra taken using two gamma-ray detectors (Lanthanum Bromide and Sodium Iodide), with the aim of identifying an optimised combination of detector and spectral processing routine. It was confirmed that, through a combination of Neural Networks and Lanthanum Bromide, the most accurate depth and activity estimates could be found. The advantage of the method was demonstrated by mapping depth and activity estimates at a case study site in Scotland. There the method identified significantly higher activity (<3 Bq g(-1)) occurring at depth (>0.4m), that conventional gross counting algorithms failed to identify. It was concluded that the method could easily be employed to identify areas of high activity potentially occurring at depth, prior to intrusive investigation using conventional sampling techniques.

Development of a neural network approach to characterise (226)Ra contamination at legacy sites using gamma-ray spectra taken from boreholes

There are a large number of sites across the UK and the rest of the world that are known to be contaminated with (226)Ra owing to historical industrial and military activities. At some sites, where there is a realistic risk of contact with the general public there is a demand for proficient risk assessments to be undertaken. One of the governing factors that influence such assessments is the geometric nature of contamination particularly if hazardous high activity point sources are present. Often this type of radioactive particle is encountered at depths beyond the capabilities of surface gamma-ray techniques and so intrusive borehole methods provide a more suitable approach. However, reliable spectral processing methods to investigate the properties of the waste for this type of measurement have yet to be developed since a number of issues must first be confronted including: representative calibration spectra, variations in background activity and counting uncertainty. Here a novel method is proposed to tackle this issue based upon the interrogation of characteristic Monte Carlo calibration spectra using a combination of Principal Component Analysis and Artificial Neural Networks. The technique demonstrated that it could reliably distinguish spectra that contained contributions from point sources from those of background or dissociated contamination (homogenously distributed). The potential of the method was demonstrated by interpretation of borehole spectra collected at the Dalgety Bay headland, Fife, Scotland. Predictions concurred with intrusive surveys despite the realisation of relatively large uncertainties on activity and depth estimates. To reduce this uncertainty, a larger background sample and better spatial coverage of cores were required, alongside a higher volume better resolution detector.

Full spectrum analysis in environmental monitoring

In environmental radiation monitoring, the time-variable natural gamma radiation background complicates the nuclide identification and analysis of a gamma spectrum. A full spectrum analysis based on the noise adjusted singular value decomposition method for the description of the time-variable background and adjustment calculations is a possible analysis method, which may provide advantages compared with a peak-based analysis, if applied to a time series of gamma spectra. An analysis example is shown and discussed with a measured time series of gamma spectra obtained from a spectroscopic gamma detector with a NaI(Tl) scintillator as it is used in the environmental radiation monitoring.