Lagrangian and Eulerian modelling of 106Ru atmospheric transport in 2017 over northern hemisphere.

In September 2017, numerous measurement stations recorded large surface concentrations of Ru106 in Europe. This event was well recorded by various monitoring stations worldwide and offer a valuable framework to compare the modelling strategies deployed to quickly evaluate where the plume goes and with what concentrations. In general, the source and its intensity are not known and hypotheses have to be done. Models have to be fast and accurate: Lagrangian and Eulerian are often used but rarely compared. In this study, the FLEXPART Lagrangian model and the WRF-CHIMERE Eulerian models are used to simulate the emissions, transport and deposition of this source of Ru106. First, it is shown that the hypothesis of location, timing and intensity of the source is realistic, by comparison to surface measurements. Second, sensitivity analysis performed with the Eulerian model and several transport scheme showed that this model may provide better results than the Lagrangian one. It opens the door to further development, including chemistry and mixing with other pollutants during these specific events.

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.

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.

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.

6 months of radioxenon detection in western Europe with the SPALAX-New generation system - Part1: Metrological capabilities.

The SPALAX-NG is a new-generation system that is designed to detect radioactive xenon at trace levels in the atmosphere following a nuclear explosion or civilian source release. This new system formed part of a validation program led by the Provisional Technical Secretary of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) Organization. In this study, the first SPALAX-NG unit was tested for six months between October 2018 and April 2019 at the CEA/DIF premises near Paris, France. This test period provided an outstanding opportunity to illustrate the high level of detectability and reliability of the system. The data availability obtained over this period was approximately 99%, which was well above the CTBT Data Availability criteria of 95%. The data reliability was demonstrated by a comparison with a collocated SPALAX-1 unit (former version of SPALAX) and by re-measuring several samples at the CTBT-certified French laboratory FRL08. The high sensitivity to the detection of the four relevant radioxenon isotopes was fully demonstrated and enabled the recording of a major dataset for western Europe. A large set of isotopic ratios was measured, which enabled the discrimination criteria between civilian sources and nuclear test signatures to be refined.

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.

How to improve parameter estimates in GLM-based fMRI data analysis: cross-validated Bayesian model averaging.

In functional magnetic resonance imaging (fMRI), model quality of general linear models (GLMs) for first-level analysis is rarely assessed. In recent work (Soch et al., 2016: "How to avoid mismodelling in GLM-based fMRI data analysis: cross-validated Bayesian model selection", NeuroImage, vol. 141, pp. 469-489; http://dx.doi.org/10.1016/j.neuroimage.2016.07.047), we have introduced cross-validated Bayesian model selection (cvBMS) to infer the best model for a group of subjects and use it to guide second-level analysis. While this is the optimal approach given that the same GLM has to be used for all subjects, there is a much more efficient procedure when model selection only addresses nuisance variables and regressors of interest are included in all candidate models. In this work, we propose cross-validated Bayesian model averaging (cvBMA) to improve parameter estimates for these regressors of interest by combining information from all models using their posterior probabilities. This is particularly useful as different models can lead to different conclusions regarding experimental effects and the most complex model is not necessarily the best choice. We find that cvBMS can prevent not detecting established effects and that cvBMA can be more sensitive to experimental effects than just using even the best model in each subject or the model which is best in a group of subjects.

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

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.