Estimation of soil radioactivity-depth profiles using Bayesian inversion of borehole gamma spectrometry data.

Inversion of in situ borehole gamma spectrometry data is a faster and relatively less laborious method for calculating the vertical distribution of radioactivity in soil than conventional soil sampling method. However, the efficiency calculation of a detector for such measurements is a challenging task due to spatial and temporal variation of the soil properties and other measurement parameters. In this study, the sensitivity of different soil characteristics and measurement parameters on simulated efficiencies for a 662 keV photon peak were investigated. In addition, a Bayesian data inversion with a Gaussian process model was used to calculate the activity concentration of 137Cs and its uncertainty considering the sources of uncertainty identified during the sensitivity analysis, including soil density, borehole radius, and the uncertainty in detector position in the borehole. Several soil samples were also collected from the borehole and surrounding area, and 137Cs activity concentration was measured to compare with the inversion results. The calculated 137Cs activity concentrations agree well with those obtained from soil samples. Therefore, it can be concluded that the vertical radioactivity distribution can be calculated using the probabilistic method using in situ gamma spectrometric measurements.

2D inversion of in situ gamma-ray spectrometric measurements of 137Cs for site characterization.

Environmental contamination by radioactive materials can be characterized by in situ gamma surface measurements. During such measurements, the field of view of a gamma detector can be tens of meters wide, resulting in a count rate that integrates the signal over a large measurement support volume/area. The contribution of a specific point to the signal depends on various parameters, such as the height of the detector above the ground surface, the gamma energy and the detector properties, etc. To improve the spatial resolution of the activity concentration, contributions of a radionuclide from nearby areas to the count rate of a single measurement should be disentangled. The experiments described in this paper, deployed 2D inversion of in situ gamma spectrometric measurements using a non-negative least squares-based Tikhonov regularization method. Data were acquired using a portable LaBr3 gamma detector. The detector response as a function of the distance of the radioactive source, required for the inversion process, was simulated using the Monte Carlo N-Particle (MCNP) transport code. The uncertainty on activity concentration was calculated using the Monte Carlo error propagation method. The 2D inversion methodology was first satisfactorily assessed for 133Ba and 137Cs source activity distributions using reference pads. Secondly, this method was applied on a 137Cs contaminated site, making use of above-ground in-situ gamma spectrometry measurements, conducted on a regular grid. The inversion process results were compared with the results from in-situ borehole measurements and laboratory analyses of soil samples. The calculated 137Cs activity concentration levels were compared against the activity concentration value for exemption or clearance of materials which can be applied by default to any amount and any type of solid material. Using the 2D inversion and the Monte Carlo error propagation method, a high spatial resolution classification of the site, in terms of exceeding the exemption limit, could be made. The 137Cs activity concentrations obtained using the inversion process agreed well with the results from the in-situ borehole measurements and those from the soil samples, showing that the 2D inversion is a convenient approach to deconvolute the contribution of radioactive sources from nearby areas within a detector's field of view, and increases the resolution of spatial contamination mapping.

Minimum detectable activity concentration of radio-cesium by a LaBr3(Ce) detector for in situ measurements on the ground-surface and in boreholes.

A 3.81 × 3.81 cm LaBr3(Ce) detector based portable measurement setup has been developed for in situ gamma spectrometric survey of a contaminated site. This system is suitable for above- and below ground surface gamma spectrometric measurements of 137Cs. However, the minimum detectable activity concentration (MDAC), an important parameter of a measurement system, should be estimated for planning purposes of the gamma spectrometric survey. In this study, the MDAC of 137Cs for the measurement setup was investigated. The efficiency of the measurement setups was calculated from Monte Carlo simulations using MCNP code. The numerical model of the different studied set-ups, used in MCNP, performed well for the known cases. The results show that the MDAC varies with the position of the detector with respect to ground surface. A 5-20 min acquisition time, depending on the detector position, can be sufficient to get a MDAC of about 10% of the exemption limit of 137Cs (100 Bq/kg).

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.

Europe-Wide Atmospheric Radionuclide Dispersion by Unprecedented Wildfires in the Chernobyl Exclusion Zone, April 2020.

From early April 2020, wildfires raged in the highly contaminated areas around the Chernobyl nuclear power plant (CNPP), Ukraine. For about 4 weeks, the fires spread around and into the Chernobyl exclusion zone (CEZ) and came within a few kilometers of both the CNPP and radioactive waste storage facilities. Wildfires occurred on several occasions throughout the month of April. They were extinguished, but weather conditions and the spread of fires by airborne embers and smoldering fires led to new fires starting at different locations of the CEZ. The forest fires were only completely under control at the beginning of May, thanks to the tireless and incessant work of the firefighters and a period of sustained precipitation. In total, 0.7-1.2 TBq 137Cs were released into the atmosphere. Smoke plumes partly spread south and west and contributed to the detection of airborne 137Cs over the Ukrainian territory and as far away as Western Europe. The increase in airborne 137Cs ranged from several hundred µBq·m-3 in northern Ukraine to trace levels of a few µBq·m-3 or even within the usual background level in other European countries. Dispersion modeling determined the plume arrival time and was helpful in the assessment of the possible increase in airborne 137Cs concentrations in Europe. Detections of airborne 90Sr (emission estimate 345-612 GBq) and Pu (up to 75 GBq, mostly 241Pu) were reported from the CEZ. Americium-241 represented only 1.4% of the total source term corresponding to the studied anthropogenic radionuclides but would have contributed up to 80% of the inhalation dose.

The assessment of the April 2020 chernobyl wildfires and their impact on Cs-137 levels in Belgium and The Netherlands.

In April 2020, several wildfires took place in and around the Chernobyl exclusion zone. These fires reintroduced radioactive particles deposited during the 1986 Chernobyl disaster into the atmosphere, causing concern about a possible radiation hazard. Several countries and several stations of the International Monitoring System measured increased Cs137 levels. This study presents the analyses made by RIVM and SCK CEN/RMI during the April 2020 wildfires. Furthermore, more in-depth research was performed after the wildfires. A statistical analysis of Cs137 detections is presented, comparing the April 2020 detections with historical detections. Inverse atmospheric transport modelling is applied to infer the total released Cs137 during the wildfires. Finally, it is assessed whether the Cs137 detections in Belgium and the Netherlands can be attributed to the wildfires.

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).

Parametrization of homogeneous forested areas and effect on simulated dose rates near a nuclear research reactor.

One of the major uncertainties in dispersion-based simulations at the local scale is the representation of terrain effects. The aim of the current study is to quantify this type of uncertainty for dose-rate predictions over a homogeneous forest cover. At the Belgian reactor BR1, situated in a forested environment, ambient gamma-dose-rate data from routine Ar-41 releases are available in the first 300 m from the release point. We develop a forest parameterization that meets the site-specific needs, and integrate it in different dispersion models. Using different terrain-roughness parameterizations, we compare three types of models: a dispersion model driven by a Langevin equation, an advection-diffusion model, and a Gaussian plume model as a special case of the latter one. We find that all models are biased up to a factor of four, partly due to an uncertain source strength. The dose-rate uncertainty due to the model choice is a factor of 2.2 for a stack release and a factor of 14 for a ground release.

Source localisation and its uncertainty quantification after the third DPRK nuclear test.

The International Monitoring System is being set up aiming to detect violations of the Comprehensive Nuclear-Test-Ban Treaty. Suspicious radioxenon detections were made by the International Monitoring System after the third announced nuclear test conducted by the Democratic People's Republic of Korea (DPRK). In this paper, inverse atmospheric transport and dispersion modelling was applied to these detections, to determine the source location, the release term and its associated uncertainties. The DPRK nuclear test site was found to be a likely source location, though a second likely source region in East Asia was found by the inverse modelling, partly due to the radioxenon background from civilian sources. Therefore, techniques to indirectly assess the influence of the radioxenon background are suggested. In case of suspicious radioxenon detections after a man-made explosion, atmospheric transport and dispersion modelling is a powerful tool for assessing whether the explosion could have been nuclear or not.

Time resolution requirements for civilian radioxenon emission data for the CTBT verification regime.

The capability of the noble gas component of the International Monitoring System as a verification tool for the Comprehensive Nuclear-Test-Ban Treaty is deteriorated by a background of radioxenon emitted by civilian sources. One of the possible approaches to deal with this issue, is to simulate the daily radioxenon concentrations from these civilian sources at noble gas stations by using atmospheric transport models. In order to accurately quantify the contribution from these civilian sources, knowledge on the releases is required. However, such data are often not available and furthermore it is not clear what temporal resolution such data should have. In this paper, we assess which temporal resolution is required to best model the 133Xe contribution from civilian sources at noble gas stations in an operational context. We consider different sampling times of the noble gas stations and discriminate between nearby and distant sources. We find that for atmospheric transport and dispersion problems on a scale of 1000 km or more, emission data with subdaily temporal resolution is generally not necessary. However, when the source-receptor distance decreases, time-resolved emission data become more important. The required temporal resolution of emission data thus depends on the transport scale of the problem. In the context of the Comprehensive Nuclear-Test-Ban Treaty, where forty noble gas stations will monitor the whole globe, daily emission data are generally sufficient, but for certain meteorological conditions, better temporally resolved emission data are required.

Assessment of the announced North Korean nuclear test using long-range atmospheric transport and dispersion modelling.

On 6 January 2016, the Democratic People's Republic of Korea announced to have conducted its fourth nuclear test. Analysis of the corresponding seismic waves from the Punggye-ri nuclear test site showed indeed that an underground man-made explosion took place, although the nuclear origin of the explosion needs confirmation. Seven weeks after the announced nuclear test, radioactive xenon was observed in Japan by a noble gas measurement station of the International Monitoring System. In this paper, atmospheric transport modelling is used to show that the measured radioactive xenon is compatible with a delayed release from the Punggye-ri nuclear test site. An uncertainty quantification on the modelling results is given by using the ensemble method. The latter is important for policy makers and helps advance data fusion, where different nuclear Test-Ban-Treaty monitoring techniques are combined.

Nuclear and Radiological Preparedness: The Achievements of the European Research Project PREPARE.

The PREPARE project aimed closing gaps identified in nuclear and radiological preparedness in Europe following the first evaluation of the Fukushima disaster. With 46 partners from Europe and Japan, it collected the key players in the area of emergency management and rehabilitation preparedness. Starting from February 2013, the project ended in January 2016. Among others, the project reviewed existing operational procedures for long-lasting releases, cross-border problems in radiation monitoring and food safety and further developed missing functionalities in decision support systems ranging from improved source term estimation and dispersion modelling to the inclusion of hydrological pathways for European water bodies. In addition, a so-called Analytical Platform has been developed to explore the scientific and operational means to improve information collection, information exchange and the evaluation of such types of disasters. The tools developed within the project will be partly integrated into the decision support systems ARGOS and JRODOS.

On the capability to model the background and its uncertainty of CTBT-relevant radioxenon isotopes in Europe by using ensemble dispersion modeling.

Knowledge on the global radioxenon background is imperative for the Comprehensive Nuclear-Test-Ban Treaty verification. In this paper, the capability to simulate the radioxenon background from regional sources is assessed at two International Monitoring System stations in Europe. An ensemble dispersion modeling approach is used to quantify uncertainty by making use of a subset of the Ensemble Prediction System of the European Centre for Medium-Range Weather Forecasts. Although the uncertainty quantification shows promising results, the ensemble shows a lack of spread that could be attributed to emission uncertainty from nuclear power plants, which is not taken into account. More knowledge on the emissions of nuclear power plants can help improve our understanding of the radioxenon background.

Dynamic dose assessment by Large Eddy Simulation of the near-range atmospheric dispersion.

In order to improve the simulation of the near-range atmospheric dispersion of radionuclides, computational fluid dynamics is becoming increasingly popular. In the current study, Large-Eddy Simulation is used to examine the time-evolution of the turbulent dispersion of radioactive gases in the atmospheric boundary layer, and it is coupled to a gamma dose rate model that is based on the point-kernel method with buildup factors. In this way, the variability of radiological dose rate from cloud shine due to instantaneous turbulent mixing processes can be evaluated. The steady release in an open field of (41)Ar and (133)Xe for 4 different release heights is studied, thus covering radionuclides that decay with a high-energy gamma and a low-energy gamma, respectively. Based on these simulations, the variability of dose rates at ground level for different averaging times in the dose measurements is analyzed. It is observed that turbulent variability in the wind field can lead to dose estimates that are underestimated by up to a factor of four when conventional long-term measurements are used to estimate the dose from short-term exposures.

PREPARE: innovative integrated tools and platforms for radiological emergency preparedness and post-accident response in Europe.

The PREPARE project that started in February 2013 and will end at the beginning of 2016 aims to close gaps that have been identified in nuclear and radiological preparedness in Europe following the first evaluation of the Fukushima disaster. Among others, the project will address the review of existing operational procedures for dealing with long-lasting releases and cross-border problems in radiation monitoring and food safety and further develop missing functionalities in decision support systems (DSS) ranging from improved source-term estimation and dispersion modelling to the inclusion of hydrological pathways for European water bodies. In addition, a so-called Analytical Platform will be developed exploring the scientific and operational means to improve information collection, information exchange and the evaluation of such types of disasters. The tools developed within the project will be partly integrated into the two DSS ARGOS and RODOS.