A baseline for source localisation using the inverse modelling tool FREAR.

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.

Uncertainty quantification of atmospheric transport and dispersion modelling using ensembles for CTBT verification applications.

Airborne concentrations of specific radioactive xenon isotopes (referred to as "radioxenon") are monitored globally as part of the verification regime of the Comprehensive Nuclear-Test-Ban Treaty, as these could be the signatures of a nuclear explosion. However, civilian nuclear facilities emit a regulated amount of radioxenon that can interfere with the very sensitive monitoring network. One approach to deal with this civilian background of radioxenon for Treaty verification purposes, is to explicitly simulate the expected radioxenon concentration from civilian sources at monitoring stations using atmospheric transport modelling. However, atmospheric transport modelling is prone to uncertainty, and the absence of an uncertainty quantification can limit its use for detection screening. In this paper, several ensembles are assessed that could provide an atmospheric transport modelling uncertainty quantification. These ensembles are validated with radioxenon observations, and recommendations are given for atmospheric transport modelling uncertainty quantification. Finally, the added value of an ensemble for detection screening is illustrated.

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.

Bayesian source reconstruction of an anomalous Selenium-75 release at a nuclear research institute.

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.

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.

International challenge to model the long-range transport of radioxenon released from medical isotope production to six Comprehensive Nuclear-Test-Ban Treaty monitoring stations.

After performing a first multi-model exercise in 2015 a comprehensive and technically more demanding atmospheric transport modelling challenge was organized in 2016. Release data were provided by the Australian Nuclear Science and Technology Organization radiopharmaceutical facility in Sydney (Australia) for a one month period. Measured samples for the same time frame were gathered from six International Monitoring System stations in the Southern Hemisphere with distances to the source ranging between 680 (Melbourne) and about 17,000 km (Tristan da Cunha). Participants were prompted to work with unit emissions in pre-defined emission intervals (daily, half-daily, 3-hourly and hourly emission segment lengths) and in order to perform a blind test actual emission values were not provided to them. Despite the quite different settings of the two atmospheric transport modelling challenges there is common evidence that for long-range atmospheric transport using temporally highly resolved emissions and highly space-resolved meteorological input fields has no significant advantage compared to using lower resolved ones. As well an uncertainty of up to 20% in the daily stack emission data turns out to be acceptable for the purpose of a study like this. Model performance at individual stations is quite diverse depending largely on successfully capturing boundary layer processes. No single model-meteorology combination performs best for all stations. Moreover, the stations statistics do not depend on the distance between the source and the individual stations. Finally, it became more evident how future exercises need to be designed. Set-up parameters like the meteorological driver or the output grid resolution should be pre-scribed in order to enhance diversity as well as comparability among model runs.

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.

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.