International challenge to predict the impact of radioxenon releases from medical isotope production on a comprehensive nuclear test ban treaty sampling station

Impacts of future nuclear power generation on the international monitoring system

Many countries are considering nuclear power as a means of reducing greenhouse gas emissions, and the IAEA (IAEA, 2022) has forecasted nuclear power growth rates up to 224% of the 2021 level by 2050. Nuclear power plants release trace quantities of radioxenon, an inert gas that is also monitored because it is released during nuclear explosive tests. To better understand how nuclear energy growth (and resulting Xe emissions) could affect a global nonproliferation architecture, we modeled daily releases of radioxenon isotopes used for nuclear explosion detection in the International Monitoring System (IMS) that is part of the Comprehensive Nuclear Test-Ban Treaty: 131mXe, 133Xe, 133mXe, and 135Xe to examine the change in the number of potential radioxenon detections as compared to the 2021 detection levels. If a 40-station IMS network is used, the potential detections of 133Xe in 2050 would range from 82% for the low-power scenario to 195% for the high-power scenario, compared to the detections in 2021. If an 80-station IMS network is used, the potential detections of 133Xe in 2050 would range from 83% of the 2021 detection rate for the low-power scenario to 209% for the high-power scenario. Essentially no detections of 131mXe and 133mXe are expected. The high growth scenario could lead to a 2.5-fold increase in 135Xe detections, but the total number of detections is still small (on the order of 1 detection per day in the entire network). The higher releases do not pose a health issue, but better automated methods to discriminate between radioactive xenon released from industrial sources and nuclear explosions will be needed to offset the higher workload for people who perform the monitoring.

Addressing the quantification of meteorological uncertainties in the atmospheric transport simulations of the 133Xe industrial background

The French National Data Center (NDC) uses an automated simulation of the 133Xe worldwide atmospheric background as one of the means to categorize the radionuclide measurements of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS). These simulations take into account 133Xe releases from the known or assumed major industrial emitters in the world and global-scale meteorological data. However, a quantification of the simulation uncertainties in this operational set up is yet to be addressed. This work discusses the benefits of meteorological ensemble data as available from National Centers for Environmental Prediction (NCEP) for that purpose. For this study, the daily dispersion of releases from the Institute for Radio Elements (IRE), a medical isotope production facility located in Fleurus (Belgium), was calculated over one year with emissions measured in-site and ensemble meteorological data. The ensemble contains 31 members, which resulted in as many predictions of activity concentration for any given time and place. The resulting distribution statistics (mean, median and spread), and the control run, were confronted to the deterministic run and to measurements at one IMS-like station near Paris (France) and one IMS station in Freiburg (Germany). Overall, the ensemble results have decreased the simulation performance, as expected given the use of meteorological analyses only. However, contrasting patterns were found with a detailed analysis of daily activity concentration over two one-month-and-a-half periods. Noticeably, outlier results were found to carry the best forecast in some significant detections, proving their relevance for the measurement categorization, despite their isolated character. Importantly, the ensemble has allowed the quantification of meteorological uncertainties, which was beneficial in all cases. It either has improved the confidence of IMS data categorization or has pointed to low confidence predictions. A criterion to identify the latter is suggested, based on information provided by the ensemble distributions. In addition, maps of probability of detections and of relative spread are suggested to show additional benefits of ensemble meteorology.

Impact of industrial nuclear emissions on nuclear explosion monitoring

In 1995, the development of a global radioactive xenon monitoring network was discussed in the Conference on Disarmament as part of a nuclear explosion verification regime. Discussions considered different network densities and different possible source magnitudes. The Comprehensive Nuclear Test Ban Treaty was subsequently written to initially include 40 locations for noble gas (radioxenon) samplers, and to consider using a total of 80 locations for noble gas samplers in its International Monitoring System (IMS) after the treaty enters into force. Since 2000, a global network of noble gas monitoring locations has been built as part of the IMS. This network, currently with 31 locations, is of sufficient sensitivity to discover that the Earth's atmosphere contains a complex anthropogenic radioactive xenon background. In this work, the impact of calculated xenon backgrounds on IMS radionuclide stations is determined by atmospheric transport modeling over a period of two years using global average values. The network coverage for potential nuclear explosions is based on a proposed method for finding anomalies among frequent background signals. Even with the addition of background radioxenon sources and using a conservative anomaly-based approach, this work shows that various network configurations have higher xenon coverage than the estimates developed when the IMS network was designed in 1995. While these global xenon coverage figures are better than expected when the network was designed in 1995, the regional impact of background radioxenon sources is large, especially for smaller source magnitudes from potential nuclear explosions, and in some cases the xenon background vastly reduces the coverage value of individual sampling locations. The results show the detection capability and presents an optimal installation order of noble gas sampling locations, e.g. from 40 to 80, after the treaty enters into force.

Efficiency calibration and self-attenuation correction in radioxenon measurement using β-γ coincidence method

Measurement of the four radioxenon isotopes, namely 131mXe, 133mXe, 133Xe, and 135Xe, play a key role in underground nuclear test monitoring for ensuring compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT). To improve detection sensitivity, a β-γ coincidence technique is commonly used. Due to the presence of the gas matrix, such as stable xenon, nitrogen, helium, the self-attenuation effects should be taken into account when measuring different types of sample. In order to improve the accuracy of the measurement, the detection efficiencies of X-rays and γ-rays were derived by using a simulation gas calibration source with low density of sponge matrix. The detection efficiencies of β-particles and conversion electrons (CEs) were calibrated by measuring radioxenon sample. The self-attenuation correction factors of X-rays and γ-rays were determined by Geant4 simulation method. The self-attenuation correction factors of β-particles and CEs were provided by measuring the radioxenon samples with different volumes of xenon, nitrogen and helium.

Characterisation of Xe-133 background at the IMS stations in the East Asian region: Insights based on known sources and atmospheric transport modelling

Radioxenon can be produced with a high fission yield during a nuclear explosion, making it an important tracer to demonstrate the nuclear origin of an explosion. For this reason, it is continuously monitored by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) as part of the verification regime. Radioxenon is emitted by civil nuclear facilities, like nuclear power plants (NPPs) or isotope production facilities (IPFs), providing significant but variable contribution to the noble gas background. The discrimination between CTBT-relevant radioxenon detections and the background is then a challenging task. This work aims at estimating the radioxenon background at 8 East Asian noble gas stations of the International Monitoring Systems (IMS) (out of 26 certified and 14 others foreseen) based on known sources and atmospheric transport modelling (ATM). For the purpose of this study, the transportable system in Mutsu, Japan, was also included. The results demonstrate a predominant contribution of NPPs to the radioxenon background at most of the East Asian IMS stations, especially during summertime. In autumn, as a result of large-scale atmospheric circulation, the contribution of remote IPFs starts to dominate. In the summertime, up to 80% of the Xe-133 detections at a station may be explained by contributions from NPPs. The detections even rise to 100% in some specific cases. At some stations under investigation in this study, a transition from NPP to IPF domination is observed in September and continues during the autumn season. It has also been shown that, for some stations, simulated concentrations above the detection limit may include observable contributions from up to 19 different sources per daily sample; at the same time the sample being sensitive to 80 or more possible sources of radioxenon. This indicates that the accumulation of many weak sources can lead to a measurable result in a single air sample. This might also explain observations at very remote stations. Another important conclusion is that, despite limited knowledge about release patterns of NPPs, the agreement between simulated and measured values was good in many cases. Availability of IMS measurements allowed for validation of simulations. This comparison revealed that approximately 76% of simulated values were underestimated. Based on the paired t-test, a 95% confidence interval for the true mean difference between measurements and simulations was constructed. It was estimated that for data dominated by NPPs contribution (i.e. NPPs contribution exceeds 70%), the overall uncertainty of simulated results lies between 0.07 and 0.10 mBq/m3. For data dominated by IPFs contribution (i.e. IPFs contribution exceeds 70%), the uncertainty for the simulations is in the range between 0.03 and 0.12 mBq/m3.

Source Term Analysis of Xenon (STAX): An effort focused on differentiating man-made isotope production from nuclear explosions via stack monitoring

An overview of the hardware and software developed for the Source Term Analysis of Xenon (STAX) project is presented which includes the data collection from two stack monitoring systems installed at medical isotope production facilities, infrastructure to transfer data to a central repository, and methods for sharing data from the repository with users. STAX is an experiment to collect radioxenon emission data from industrial nuclear facilities with the goal of developing a better understanding of the global radioxenon background and the effect industrial radioxenon releases have on nuclear explosion monitoring. A final goal of this work is to utilize collected data along with atmospheric transport modeling to calculate the contribution of a peak or set of peaks detected by the International Monitoring System (IMS) to provide desired discriminating information to the International Data Centre (IDC) and National Data Centers (NDCs). Types of data received from the STAX equipment are shown and collected data was used for a case study to predict radioxenon concentrations at two IMS stations closest to the Institute for RadioElements (IRE) in Belgium. The initial evaluation of results indicate that the data is very valuable to the nuclear explosion monitoring community.

Third international challenge to model the medium- to long-range transport of radioxenon to four Comprehensive Nuclear-Test-Ban Treaty monitoring stations

In 2015 and 2016, atmospheric transport modeling challenges were conducted in the context of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) verification, however, with a more limited scope with respect to emission inventories, simulation period and number of relevant samples (i.e., those above the Minimum Detectable Concentration (MDC)) involved. Therefore, a more comprehensive atmospheric transport modeling challenge was organized in 2019. Stack release data of Xe-133 were provided by the Institut National des Radioéléments/IRE (Belgium) and the Canadian Nuclear Laboratories/CNL (Canada) and accounted for in the simulations over a three (mandatory) or six (optional) months period. Best estimate emissions of additional facilities (radiopharmaceutical production and nuclear research facilities, commercial reactors or relevant research reactors) of the Northern Hemisphere were included as well. Model results were compared with observed atmospheric activity concentrations at four International Monitoring System (IMS) stations located in Europe and North America with overall considerable influence of IRE and/or CNL emissions for evaluation of the participants' runs. Participants were prompted to work with controlled and harmonized model set-ups to make runs more comparable, but also to increase diversity. It was found that using the stack emissions of IRE and CNL with daily resolution does not lead to better results than disaggregating annual emissions of these two facilities taken from the literature if an overall score for all stations covering all valid observed samples is considered. A moderate benefit of roughly 10% is visible in statistical scores for samples influenced by IRE and/or CNL to at least 50% and there can be considerable benefit for individual samples. Effects of transport errors, not properly characterized remaining emitters and long IMS sampling times (12-24 h) undoubtedly are in contrast to and reduce the benefit of high-quality IRE and CNL stack data. Complementary best estimates for remaining emitters push the scores up by 18% compared to just considering IRE and CNL emissions alone. Despite the efforts undertaken the full multi-model ensemble built is highly redundant. An ensemble based on a few arbitrary runs is sufficient to model the Xe-133 background at the stations investigated. The effective ensemble size is below five. An optimized ensemble at each station has on average slightly higher skill compared to the full ensemble. However, the improvement (maximum of 20% and minimum of 3% in RMSE) in skill is likely being too small for being exploited for an independent period.

Use of STAX data in global-scale simulation of 133Xe atmospheric background

A global-scale simulation of the ¹³³Xe atmospheric background is automated at the French National Data Center (NDC) for the purpose of categorizing the radionuclide measurements of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) International Monitoring System (IMS). These simulations take into account ¹³³Xe releases from all known major industrial emitters in the world, compiled from the literature and described as constant values. Emission data measured directly at the stack of the Institute for Radio Elements (IRE), a medical isotope production facility located in Fleurus (Belgium), were implemented in the simulations with a time resolution of 15 minutes. This work discusses the contribution of real (measured) emissions to the prediction of the ¹³³Xe atmospheric background at IMS noble gas stations and at a location near Paris, for which IMS-like ¹³³Xe measurements were available. For the purpose of this study, simulations initiated with the IRE measured emissions were run in parallel to those with the a priori emissions used to date. The benefits of including actual emissions in the simulations were found as a function of the distance between the station and the source of the release. At the closest stations, i.e., near Paris (France) and at Schauinsland, Freiburg (Germany), respectively 250 and 400 km from Fleurus, the simulated activity concentrations differed by a factor greater than 2 more than one third of the time, and by a factor of more than 5 about 10% of the time. No significant or detectable differences were found beyond 1500-2000 km. Furthermore, at the Paris station, the timing of the measured peaks was better reproduced with the actual emission data. However, not all peak amplitudes were correctly reproduced even though the real emissions were used, highlighting the remaining uncertainties, primarily in the meteorological data and transport modeling.

Using STAX data to predict IMS radioxenon concentrations

The noble gas collection and measurement stations in the International Monitoring System (IMS) are heavily influenced by releases from medical isotope production facilities. The ability to reliably model the movement of radioxenon from the points of release to these IMS samplers has improved enough that a routine aspect of the analysis of IMS radioxenon data should be the prediction of the effect of releases from industrial nuclear facilities on the sample concentrations. Predicted concentrations at IMS noble gas systems in Germany and Sweden based on measured releases from Institute for Radioelements (IRE) in Belgium and atmospheric transport modeling for a four-month period are presented and discussed.

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.

Sensitivity study to select the wet deposition scheme in an operational atmospheric transport model

The ability of operational atmospheric transport models to simulate the soil contamination caused by deposition processes is important in the response to a nuclear crisis. The Fukushima accident was characterized by wet deposition of Cs-137, which is difficult to simulate accurately based on observations. A sensitivity study investigated seven wet deposition schemes integrated into operational atmospheric transport models. Deposition maps produced from the multiple simulations are compared with each other and with the observed deposition. Similarities and discrepancies in average behavior are presented for a number of modeling cases on the basis of criteria representing soil contamination crisis management needs. This study confirms the importance of the wet deposition scheme in a crisis management context. None of the schemes used in the study are the best option to satisfy all the comparison criteria. This study suggests that crisis managers must not exclusively trust a single model for selecting responses. At the current time, it is preferable to use several wet deposition schemes in the modelling tools for emergency responses.

6 months of radioxenon detection in western Europe with the SPALAX-New generation system - Part 2: Atmospheric transport modelling

Atmospheric transport modeling has been used to interpret the unprecedented number of multi-isotope detections of radioxenons observed during the six months of the qualification process by the Comprehensive Nuclear-Test-Ban Treaty Organization of the new SPALAX-NG system (Système de Prélèvement Automatique en Ligne avec l'Analyse du Xénon - Nouvelle Génération). Highest ¹³³Xe activity concentrations were found to be systematically associated with the concomitant measurement of several other radioxenons at the prevailing wind direction of north/northeast pointing to the Institute for Radio Elements (IRE), a medical isotope production facility located in Fleurus (Belgium). The lowest ¹³³Xe activity concentrations were not associated with a prevailing wind direction or other radioxenons, indicating the contribution of distant sources (global background). The IRE's average source terms for ^133mXe and to a lesser extent for ¹³³Xe (slightly overestimated by a factor of 1.7) showed good agreement with the literature values, while corrections by a factor of ~23 and ~53 were proposed for ^131mXe and ¹³⁵Xe since the initial values were underestimated. However, detections of ^131mXe alone and some low-activity concentrations of ¹³³Xe associated with only one of the other radioxenons could not be linked to the IRE releases. Analysis of these cases suggests the contribution of local source releases that have been difficult to identify to date. In addition to the global background, releases from such local sources, if not identified, could affect the analysis of the isotopic ratios measured following a nuclear test. The characterization of these local contributions is now possible owing to the capacity of the SPALAX-NG and other new generation measurements systems.

Source type estimation using noble gas samples

A Bayesian source-term algorithm recently published by Eslinger et al. (2019) extended previous models by including the ability to discriminate between classes of releases such as nuclear explosions, nuclear power plants, or medical isotope production facilities when multiple isotopes are measured. Using 20 release cases from a synthetic data set previously published by Haas et al. (2017), algorithm performance was demonstrated on the transport scale (400-1000 km) associated with the radionuclide samplers in the International Monitoring System. Inclusion of multiple isotopes improves release location and release time estimates over analyses using only a single isotope. The ability to discriminate between classes of releases does not depend on the accuracy of the location or time of release estimates. For some combinations of isotopes, the ability to confidently discriminate between classes of releases requires only a few samples.

Non-linear source term and scenario for an operational oil spill model

This study presents time-varying oil spill discharge functions and scenarios for operational oil spill models. This study prescribes non-linear models based on experimental measurements (Tavakoli et al. in Ocean Eng 38(17–18):1894–1907, 2011) and then upscaled to the spill duration and discharge quantity for actual oil spill incidents. Scenarios consist in collision and grounding incidents for the instantaneous spill mode; light, medium, and severe incidents for the continuous spill mode; spilt, containment, and retention practices for the spill management mode. A performance analysis of deterministic simulations indicates that the non-linear source terms and scenarios present realistic and reasonable results, showing the detailed spill patterns on the surface ocean, tail-off oil sheens along the areas swept by the dispersion and significantly different results when oil spill management and mitigation practices are activated. For oil spill modelling in support of field operations, responders and decision makers should be made aware of the variability of oil sheen spatial patterns induced by the oil spill source term to better interpret simulation results and assess the impact of source uncertainty on the clean-up, mitigation, ecological and socio-economic risk.

Source term estimation using multiple xenon isotopes in atmospheric samples

Algorithms that estimate the location and magnitude of an atmospheric release using remotely sampled air concentrations typically involve a single chemical or radioactive isotope. A new Bayesian algorithm is presented that makes discrimination between possible types of releases (e.g., nuclear explosion, nuclear power plant, or medical isotope production facility) an integral part of the analysis for samples that contain multiple isotopes. Algorithm performance is demonstrated using synthetic data and correctly discriminated between most release-type hypotheses, with higher accuracy when data are available on three or more isotopes.

Utility of atmospheric transport runs done backwards in time for source term estimation

One of the difficulties encountered in source-term analyses for airborne contaminants is the large computational effort required to predict air concentrations for all possible release scenarios. In some cases, analysts use atmospheric ATM runs with complex models done in the reverse-time direction because one ATM run done backwards in time for each sample can yield as much information as potentially hundreds or thousands of ATM runs done forwards in time. Unfortunately, the effective atmospheric dilution between the source and sampling locations differ depending on the time direction of the ATM run, with runs in the forward time direction being more realistic. No general studies have been published comparing the agreement between runs in the two time directions. Over 18000 ATM runs at 14 release locations were used to explore the agreement between dilution factors for the forward and reversed time directions at distances up to 1000 km from the release point. Ten of the release locations have a correlation below 0.9, with the lowest correlations occurring over mountainous terrain. The release locations were estimated using the time-reversed ATM runs, with 26% of the estimated release points being within 10 km of the modeled release point, 61% within 25 km, and 80% within 50 km. Most of the location differences greater than 50 km occur for two release locations in mountainous terrain. Good time-reversibility cannot be guaranteed for a new analysis, so we recommend any source-term solution using time-reversed ATM runs should include comparisons based on forward time ATM runs.

Source term estimation in the presence of nuisance signals

Many source-term estimation algorithms for atmospheric releases assume the measured concentration data are influenced only by the releases of interest. However, there are situations where identifying a short-term release from an unknown location in the presence of long-term releases from a different location is of interest. One such example is determining if part or all of a typical magnitude concentration of a radioactive isotope in a sampler came from a nuclear explosion, such as the explosion announced by DPRK in 2013, while medical isotope facilities and nuclear power plants were also operating in the region. An estimation algorithm has been developed for the case where a short-duration release is confounded by a long-term nuisance signal associated with an additional release location. The technique is demonstrated using synthetic release data for a hypothetical medical isotope production facility and a hypothetical puff release from a different location. The algorithm successfully determines the location (within 30 km) and time-varying release rate (within a factor of 2) for the medical isotope production facility and the location (within 60 km), time (within 6 h), and release magnitude (within a factor of 4) of the puff 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.

Simulating the mesoscale transport of krypton-85

Due to its half-life, chemical inertness and low solubility in water, radioactive ⁸⁵Kr is a valuable tracer for testing the performance of atmospheric dispersion models in simulating long-range transport of pollutants. This paper evaluates the capability of simulating the dispersion of radiokrypton emitted by a nuclear fuel reprocessing plant in north-west France. Three time periods during which elevated activity concentrations of ⁸⁵Kr in ground level air were detected in south-west Germany are chosen. Simulations have been performed using the HYSPLIT code and the European Centre for Median-Range Weather Forecasts (ECMWF) data base. Although their results show a slight trend of underestimating the measured ⁸⁵Kr concentrations, there is a significant correlation and moderate scatter between observations and simulations with about 50% of the results being within a factor of two of the measured concentrations. The simulated travel time distributions provided a valuable tool for providing additional insight into the dispersion of the tracer radionuclides and for identifying potential causes of deviations between measured and calculated concentrations.

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.

Present and future potential of krypton-85 for the detection of clandestine reprocessing plants for treaty verification

Burnup calculations are applied to determine the amount of krypton-85 that is produced during the irradiation of nuclear fuel. Since krypton-85 is most likely released into the atmosphere during reprocessing to separate plutonium, atmospheric transport modeling is used to calculate the worldwide distribution of krypton-85 concentrations stemming from emissions from declared reprocessing plants. The results are the basis for scenarios in which emissions from clandestine reprocessing facilities have to be detected against various background levels. It is concluded that today's background imposes heavily on the ability to detect small and medium plutonium separation rates; only high separation rates of 1 SQ per week and higher have a chance to be detected with feasible outlay. A fixed network of monitoring stations seems too costly; instead the high number of samples that are required rather calls for mobile sampling procedures, where air samples are collected at random locations over the world and are analyzed in regional laboratories for their krypton-85 concentration. Further, it is argued that krypton-85 emissions from declared reprocessing activities have to be significantly lowered to enable a worldwide verification of the absence of even smaller clandestine reprocessing. For each scenario the number of samples that have to be taken for probable detection is calculated.