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A global network of monitoring stations is set up that can measure tiny concentrations of airborne radioactivity as part of the verification regime of the Comprehensive Nuclear-Test-Ban Treaty. If Treaty-relevant detections are made, inverse atmospheric transport modelling is one of the methods that can be used to determine the source of the radioactivity. In order to facilitate the testing of novel developments in inverse modelling, two sets of test cases are constructed using real-world 133Xe detections associated with routine releases from a medical isotope production facility. One set consists of 24 cases with 5 days of observations in each case, and another set consists of 8 cases with 15 days of observations in each case. A series of inverse modelling techniques and several sensitivity experiments are applied to determine the (known) location of the medical isotope production facility. Metrics are proposed to quantify the quality of the source localisation. Finally, it is illustrated how the sets of test cases can be used to test novel developments in inverse modelling algorithms.

In June 2020, observations of anthropogenic radionuclides in Estonia, Finland, and Sweden that were not related to any acknowledged environmental release led to a comprehensive investigation on the source and cause of the unusual emissions. Several of the observed radionuclides were on the list of Comprehensive Nuclear-Test-Ban Treaty (CTBT) relevant radionuclides as an indicator of a potential nuclear test, and warranted detailed investigation. While analysis of aerosol samples coupled with Atmospheric Transport and Dispersion Modelling (ATDM) is a standard approach for environmental particulate releases, several new techniques were employed to better characterize the samples that allowed for useful inferences to be made. These inferences were crucial in forming the ultimate hypothesis for determining the facility type and location of the release.

Traces of radionuclides have been frequently detected in the European atmosphere for several years. The measured concentrations are usually very low, ranging from 0.1 to 10 & mu;Bq m- 3, and do not pose any health or environmental problems.This study aims to diagnose the origin of small undeclared radionuclide releases into the atmosphere. An inverse modelling approach that combines environmental measurements and atmospheric transport modelling is first used to assess the source location of the release. In addition, the type and process of the nuclear facility from which the release could originate are investigated by identifying the isotope production pathways and comparing them with known typical inventories. These two parts of the proposed method are complementary and allow us to extract as much information as possible from a set of radionuclide measurement data.In a previous study, the origins of detections of various radionuclides (60Co, 134Cs, 137Cs, 103Ru, 106Ru, 141Ce, 95Nb, 95Zr) in Finland, Sweden and Estonia in June 2020 have been investigated. In this paper, the previous investigation is extended by analysing two additional events that occurred in northern Europe in July 2019 and May 2022, as well an overview of other unknown releases detected in Finland over the last decade. A more detailed analysis of the 2020 event is also provided by analysing new available environmental measurements. The calculations indicate that the source location of the three events appears to be in the same region, in Russian Federation. The most probable origin of the June 2020 release seems to be a primary ion exchange resin, after 2 to 5 months of decay, of a pressurized water reactor with fuel cladding failure, and dispersion of fissile material in the primary.The July 2019 and May 2022 events are of particularly noteworthy due to the simultaneous presence of 46Sc, which is neither produced nor in the fuel, nor in the primary loop of PWR or RBMK nuclear power plants, and typical corrosion-activated products from power plants (60Co). Two hypotheses are proposed to explain this source term: a mixture of various solid wastes or recently irradiated graphite from a RBMK reactor.The reliability of the methodology is demonstrated, in particular in the section dedicated to atmospheric transport modelling, and the successful association with source term analysis provides a valuable tool for future studies and assessments of both minor and major radionuclide releases.

The International Monitoring System (IMS) is a unique global network of sensors, tuned to measure various phenomenology, with the common goal of detecting a nuclear explosion anywhere in the world. One component of this network collects measurements of radioactive particulates and gases (collectively known as radionuclides) present in the atmosphere; through this, compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) can be verified. The radionuclide sub-network consists of 120 sensors across 80 locations, supported by 16 measurement laboratories. All radionuclide stations make use of a form of γ-ray spectroscopy to measure radionuclides from samples; this remains largely unchanged since the network was first established 25 years ago. Advances in sampling and spectroscopy systems can yield improvements to the sensitivity of the network to detect a nuclear explosion. This paper summarises the status of the IMS radionuclide network, the current suite of technology used and reviews new technology that could enhance future iterations, potentially improving the verification power of the IMS.

Environmental air sampling is one of the principal monitoring technologies employed for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT). By combining the analysis of environmental samples with Atmospheric Transport and Dispersion Modelling (ATDM), and using a Bayesian source reconstruction algorithm, an estimate of the release location, duration, and quantity can be computed. Bayesian source reconstruction uses an uncertainty distribution of the input parameters, or priors, in a statistical framework to produce posterior probability estimates of the event parameters. The quality of the event reconstruction directly depends on the accuracy of the prior uncertainty distribution. With many of the input parameters, the selection of the uncertainty distribution is not difficult. However, with environmental samples, there is one component of the uncertainty at the interface between sample measurements and the ATDM that has been overlooked. Typically, a much smaller volume or quantity of material is sampled from the much larger domain represented in the ATDM. By examining the response of a dense network of radionuclide detectors on the West Coast of Canada during the passage of the Fukushima debris plume, an initial estimate of this uncertainty was determined to be between 20% and 30% depending on sample integration time.

Bayesian source reconstruction is a powerful tool for determining atmospheric releases. It can be used, amongst other applications, to identify a point source releasing radioactive particles into the atmosphere. This is relevant for applications such as emergency response in case of a nuclear accident or Comprehensive Nuclear-Test-Ban treaty verification. The method involves solving an inverse problem using environmental radioactivity observations and atmospheric transport models. The Bayesian approach has the advantage of providing an uncertainty quantification on the inferred source parameters. However, it requires the specification of the inference input errors, such as the observation error and model error. The latter is particularly hard to provide as there is no straightforward way to determine the atmospheric transport and dispersion model error. Here, the importance of model error is illustrated for Bayesian source reconstruction using a recent and unique case where radionuclides were detected on several continents. A numerical weather prediction ensemble is used to create an ensemble of atmospheric transport and dispersion simulations, and a method is proposed to determine the model error.

The 2011 Fukushima Daiichi Reactor accident generated a large data set of global radionuclide observations. Frequent observations of xenon, caesium and iodine radioisotopes provided an opportunity to examine the performance of inter-continental scale meteorological models, in particular, the important mechanisms of in-cloud scavenging, precipitation, and deposition. Previous studies investigated these phenomena over short range, but this is the first time a global, coordinated surveillance system and in particular, a non-scavenged noble gas data set was available for use in such a study. Since particle size distributions are very different at long range, the parametrization of the deposition is important for accurate atmospheric modelling. The accuracy of these models are crucial in the Comprehensive Nuclear-Test-Ban Treaty (CTBT) context where discrimination of local and distant civilian sources from a potential nuclear test is a challenging problem. Beyond the CTBT context, accurate prediction of deposition is important for emergency and consequence management of nuclear emergencies, allowing a small set of data, combined with an appropriate model to represent a much larger domain, even up to continental scales. The modelling results for ground deposition and airborne activity of radiocaesium and radioiodine are presented and validated against the actual measurements.

Atmospheric transport and dispersion models are important tools in radiation protection as they help to estimate the impact of radionuclides released into the atmosphere. In particular, such models can be used in combination with radionuclide observations to estimate unknown source term parameters, or to improve source term estimates obtained through other methods. In this paper, a Bayesian inference system was used to determine the source term parameters and their corresponding credible intervals of a real-world anomalous 75Se release at a nuclear facility in Belgium. Furthermore, a formulation is proposed that not only takes into account true detections, but also true instrumental non-detections, false alarms and real misses. The Bayesian inference system is able to correctly determine the known source location. The Bayesian inference is then refined by fixing the release location and by making stronger assumptions about the release period.

In October 2017, most European countries reported unique atmospheric detections of aerosol-bound radioruthenium (106Ru). The range of concentrations varied from some tenths of µBq·m-3 to more than 150 mBq·m-3 The widespread detection at such considerable (yet innocuous) levels suggested a considerable release. To compare activity reports of airborne 106Ru with different sampling periods, concentrations were reconstructed based on the most probable plume presence duration at each location. Based on airborne concentration spreading and chemical considerations, it is possible to assume that the release occurred in the Southern Urals region (Russian Federation). The 106Ru age was estimated to be about 2 years. It exhibited highly soluble and less soluble fractions in aqueous media, high radiopurity (lack of concomitant radionuclides), and volatility between 700 and 1,000 °C, thus suggesting a release at an advanced stage in the reprocessing of nuclear fuel. The amount and isotopic characteristics of the radioruthenium release may indicate a context with the production of a large 144Ce source for a neutrino experiment.

The Comprehensive Nuclear-Test-Ban Treaty (CTBT) bans the testing of nuclear explosive devices underground, in the atmosphere and underwater. Two main technologies, radionuclide and seismo-acoustic monitoring, are deployed in the International Monitoring System used for the verification of the CTBT. Medical isotope production from fission-based processes is the dominant contributor to a worldwide background of radioxenon. This background can make the discrimination of nuclear tests from legitimate nuclear activities very challenging. Even if emissions from medical isotope producers experienced a large reduction, there remain other important sources of radioxenon that contribute to the global background such as research reactors and nuclear power plants. Until recently, the largest producer of medical isotopes was located in Canada, at the Canadian Nuclear Laboratories (CNL) facility. The characterization of CNL emissions and its research reactor can provide valuable information for effective verification of the CTBT.

Using a recently published global data set of 22Na and 7Be from the global monitoring network of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), atmospheric circulation and stratosphere-troposphere interactions are examined. Cosmogenic 22Na has a half-life well-suited to environmental processes with durations from several months to a decade. Combined with corresponding 7Be observations, these two cosmogenic isotopes form a useful environmental tracer and new radiochronometer to study physical interactions of air masses in the stratosphere and troposphere.

In assistance of radionuclide measurements at Canada’s Comprehensive Nuclear-Test-Ban Treaty (CTBT) laboratory, a Geant4 Monte Carlo application has been developed in simulating a broad-energy germanium detector and calculating detection efficiencies. The detector model was optimized in a reliable and non-biased manner through simultaneous tuning on gap distance and detector dimension, and was validated over various realistic measurement scenarios. All work is based on a series of experiments which covers the typical energy range of gamma radiation in environmental analysis, and considers the variety of the CTBT sample type, dimension and distance-to-detector. In all cases, the predicted efficiencies are consistent with the empirical ones within 5%, with a typical deviation of 3% in majority.

In this paper, a dual high purity germanium (HPGe) gamma spectrometer detection system with an increased solid angle was developed. The detection system consists of a pair of Broad Energy Germanium (BE-5030p) detectors and an XIA LLC digital gamma finder/Pixie-4 data-acquisition system. A data file processor was developed containing five modules that parses Pixie-4 list-mode data output files and classifies detections into anticoincident/coincident events and their specific coincidence types (double/triple/quadruple) for further analysis. A novel cosmic veto system was installed in the detection system. It was designed to be easy to install around an existing system while still providing sufficient cosmic veto shielding comparable to other designs. This paper describes the coverage and efficiency of this cosmic veto and the data processing system. It has been demonstrated that the cosmic veto system can provide a mean background reduction of 66.1%, which results in a mean MDA improvement of 58.3%. The counting time to meet the required MDA for specific radionuclide can be reduced by a factor of 2-3 compared to those using a conventional HPGe system. This paper also provides an initial overview of coincidence timing distributions between an incoming event from a cosmic veto plate and HPGe detector.

Measurement of cosmogenic 22Na in daily aerosol samples is often difficult due to low atmospheric production rates. A new technique based upon spectral summation of sequential high-volume aerosol samples to measure 22Na is described and validated. This summation technique has broad applications to any detection system that produces sequential representative sample measurements in which radioisotopes are just below the detection limit, provided the energy calibration is stable. It is anticipated that a global dataset of this radionuclide will have many important environmental science applications.

The International Monitoring System (IMS) is part of the verification regime for the Comprehensive Nuclear-Test-Ban-Treaty Organization (CTBTO). At entry-into-force, half of the 80 radionuclide stations will be able to measure concentrations of several radioactive xenon isotopes produced in nuclear explosions, and then the full network may be populated with xenon monitoring afterward. An understanding of natural and man-made radionuclide backgrounds can be used in accordance with the provisions of the treaty (such as event screening criteria in Annex 2 to the Protocol of the Treaty) for the effective implementation of the verification regime. Fission-based production of (99)Mo for medical purposes also generates nuisance radioxenon isotopes that are usually vented to the atmosphere. One of the ways to account for the effect emissions from medical isotope production has on radionuclide samples from the IMS is to use stack monitoring data, if they are available, and atmospheric transport modeling. Recently, individuals from seven nations participated in a challenge exercise that used atmospheric transport modeling to predict the time-history of (133)Xe concentration measurements at the IMS radionuclide station in Germany using stack monitoring data from a medical isotope production facility in Belgium. Participants received only stack monitoring data and used the atmospheric transport model and meteorological data of their choice. Some of the models predicted the highest measured concentrations quite well. A model comparison rank and ensemble analysis suggests that combining multiple models may provide more accurate predicted concentrations than any single model. None of the submissions based only on the stack monitoring data predicted the small measured concentrations very well. Modeling of sources by other nuclear facilities with smaller releases than medical isotope production facilities may be important in understanding how to discriminate those releases from releases from a nuclear explosion.

This paper applies a Bayesian probabilistic inferential methodology for the reconstruction of the location and emission rate from an actual contaminant source (emission from the Chalk River Laboratories medical isotope production facility) using a small number of activity concentration measurements of a noble gas (Xenon-133) obtained from three stations that form part of the International Monitoring System radionuclide network. The sampling of the resulting posterior distribution of the source parameters is undertaken using a very efficient Markov chain Monte Carlo technique that utilizes a multiple-try differential evolution adaptive Metropolis algorithm with an archive of past states. It is shown that the principal difficulty in the reconstruction lay in the correct specification of the model errors (both scale and structure) for use in the Bayesian inferential methodology. In this context, two different measurement models for incorporation of the model error of the predicted concentrations are considered. The performance of both of these measurement models with respect to their accuracy and precision in the recovery of the source parameters is compared and contrasted.

Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout across the northern hemisphere resulting from the Fukushima Dai-ichi Nuclear Power Plant accident in March 2011. Sampling data from multiple International Modeling System locations are combined with atmospheric transport modeling to estimate the magnitude and time sequence of releases of Xe-133. Modeled dilution factors at five different detection locations were combined with 57 atmospheric concentration measurements of Xe-133 taken from March 18 to March 23 to estimate the source term. This analysis suggests that 92% of the 1.24 x 10(19) Bq of Xe-133 present in the three operating reactors at the time of the earthquake was released to the atmosphere over a 3 d period. An uncertainty analysis bounds the release estimates to 54-129% of available Xe-133 inventory. (C) 2013 Elsevier Ltd. All rights reserved.