Statistical sampling applied to the radiological characterization of historical waste

International audienceThe evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like g-emitters and high-energy X-rays, can be measured via non-destructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM) from outside a package because they are a-or b-emitters. The present article discusses the application of linear regression, scaling factors (SF) and the so-called "mean activity method" to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN). Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given

Uncertainty quantification applied to the radiological characterization of radioactive waste

This paper describes the process adopted at the European Organization for Nuclear Research (CERN) to quantify uncertainties affecting the characterization of very-low-level radioactive waste. Radioactive waste is a by-product of the operation of high-energy particle accelerators. Radioactive waste must be characterized to ensure its safe disposal in final repositories. Characterizing radioactive waste means establishing the list of radionuclides together with their activities. The estimated activity levels are compared to the limits given by the national authority of the waste disposal. The quantification of the uncertainty affecting the concentration of the radionuclides is therefore essential to estimate the acceptability of the waste in the final repository but also to control the sorting, volume reduction and packaging phases of the characterization process. The characterization method consists of estimating the activity of produced radionuclides either by experimental methods or statistical approaches. The uncertainties are estimated using classical statistical methods and uncertainty propagation. A mixed multivariate random vector is built to generate random input parameters for the activity calculations. The random vector is a robust tool to account for the unknown radiological history of legacy waste. This analytical technique is also particularly useful to generate random chemical compositions of materials when the trace element concentrations are not available or cannot be measured. The methodology was validated using a waste population of legacy copper activated at CERN. The methodology introduced here represents a first approach for the uncertainty quantification (UQ) of the characterization process of waste produced at particle accelerators

Assessing real-world vaccine effectiveness against severe forms of SARS-CoV-2 infection: an observational study from routine surveillance data in Switzerland.

BACKGROUND In Switzerland, SARS-CoV-2 vaccination campaigns started in early 2021. Vaccine coverage reached 65% of the population in December 2021, mostly with mRNA vaccines from Moderna and Pfizer-BioNtech. Simultaneously, the proportion of vaccinated among COVID-19-related hospitalisations and deaths rose, creating some confusion in the general population. We aimed to assess vaccine effectiveness against severe forms of SARS-CoV-2 infection using routine surveillance data on the vaccination status of COVID-19-related hospitalisations and deaths, and data on vaccine coverage in Switzerland. METHODS We considered all routine surveillance data on COVID-19-related hospitalisations and deaths received at the Swiss Federal Office of Public Health from 1 July to 1 December 2021. We estimated the relative risk of COVID-19-related hospitalisation or death for not fully vaccinated compared with fully vaccinated individuals, adjusted for the dynamics of vaccine coverage over time, by age and location. We stratified the analysis by age group and by calendar month. We assessed variations in the relative risk of hospitalisation associated with the time since vaccination. RESULTS We included a total of 5948 COVID-19-related hospitalisations of which 1245 (21%) were fully vaccinated patients, and a total of 739 deaths of which 259 (35%) were fully vaccinated. We found that the relative risk of COVID-19 related hospitalisation was 12.5 (95% confidence interval [CI] 11.7-13.4) times higher for not fully vaccinated than for fully vaccinated individuals. This translates into a vaccine effectiveness against hospitalisation of 92.0% (95% CI 91.4-92.5%). Vaccine effectiveness against death was estimated to be 90.3% (95% CI 88.6-91.8%). Effectiveness appeared to be comparatively lower in age groups over 70 and during the months of October and November 2021. We also found evidence of a decrease in vaccine effectiveness against hospitalisation for individuals vaccinated for 25 weeks or more, but this decrease appeared only in age groups below 70. CONCLUSIONS The observed proportions of vaccinated among COVD-19-related hospitalisations and deaths in Switzerland were compatible with a high effectiveness of mRNA vaccines from Moderna and Pfizer-BioNtech against hospitalisation and death in all age groups. Effectiveness appears comparatively lower in older age groups, suggesting the importance of booster vaccinations. We found inconclusive evidence that vaccine effectiveness wanes over time. Repeated analyses will be able to better assess waning and the effect of boosters

A new approach to characterize very-low-level radioactive waste produced at hadron accelerators

Radioactive waste is produced as a consequence of preventive and corrective maintenance during the operation of high-energy particle accelerators or associated dismantling campaigns. Their radiological characterization must be performed to ensure an appropriate disposal in the disposal facilities. The radiological characterization of waste includes the establishment of the list of produced radionuclides, called “radionuclide inventory”, and the estimation of their activity. The present paper describes the process adopted at CERN to characterize very-low-level radioactive waste with a focus on activated metals. The characterization method consists of measuring and estimating the activity of produced radionuclides either by experimental methods or statistical and numerical approaches. We adapted the so-called Scaling Factor (SF) and Correlation Factor (CF) techniques to the needs of hadron accelerators, and applied them to very-low-level metallic waste produced at CERN. For each type of metal we calculated the radionuclide inventory and identified the radionuclides that most contribute to hazard factors. The methodology proposed is of general validity, can be extended to other activated materials and can be used for the characterization of waste produced in particle accelerators and research centres, where the activation mechanisms are comparable to the ones occurring at CERN

Analyse statistique pour la caractérisation radiologique des déchets radioactifs au sein des accélérateurs de particules

This thesis introduces a new method to characterize metallic very-low-level radioactive waste produced at the European Organization for Nuclear Research (CERN). The method is based on: 1. the calculation of a preliminary radionuclide inventory, which is the list of the radionuclides that can be produced when particles interact with a surrounding medium, 2. the direct measurement of gamma emitters and, 3. the quantification of pure-alpha, pure-beta and low-energy X-ray emitters, called difficult-to-measure (DTM) radionuclides, using the so-called scaling factor (SF), correlation factor (CF) and mean activity (MA) techniques. The first stage of the characterization process is the calculation of the radionuclide inventory via either analytical or Monte Carlo codes. Once the preliminary radionuclide inventory is obtained, the gamma-emitting radionuclides are measured via gamma-ray spectrometry on each package of the waste population. The major gamma-emitter, called key nuclide (KN), is also identified. The scaling factor method estimates the activity of DTM radionuclides by checking for a consistent and repeated relationship between the key nuclide and the activity of the difficult to measure radionuclides from samples. If a correlation exists the activity of DTM radiodionuclides can be evaluated using the scaling factor otherwise the mean activity from the samples collected is applied to the entire waste population. Finally, the correlation factor is used when the activity of pure-alpha, pure-beta and low-energy X-ray emitters is so low that cannot be quantified using experimental values. In this case a theoretical correlation factor is obtained from the calculations to link the activity of the radionuclides we want to quantify and the activity of the key nuclide. The thesis describes in detail the characterization method, shows a complete case study and describes the industrial-scale application of the characterization method on over 1’000 m3 of radioactive waste, which was carried out at CERN between 2015 and 2017.Ce travail de thèse introduit une nouvelle méthode pour la caractérisation radiologique des déchets très faiblement radioactifs produits au sein de l’Organisation Européenne pour la Recherche Nucléaire (CERN). La méthode se base sur : 1. le calcul des radionucléides en présence, i.e. les radionucléides qui peuvent être produits lors de l’interaction des particules avec la matière et les structures environnantes les accélérateurs, 2. la mesure directe des émetteurs gamma et, 3. la quantification des émetteurs alpha et beta purs et de rayons X de faible énergie, appelés radionucléides difficile-a-mesurer (DTM), en utilisant les méthodes dites des «scaling factor» (SF), «correlation factor» (CF) et activité moyenne (MA). La première phase du processus de caractérisation est le calcul des radionucléides en présence à l’aide de codes de calcul analytiques ou Monte Carlo. Après le calcul de l’inventaire radiologique, les radionucléides émetteurs gamma sont mesurés par spectrométrie gamma dans chaque colis de la population. L’émetteur gamma dominant, appelé « key nuclide » (KN), est identifié. La méthode dite des «scaling factors» permet d’estimer l’activité des radionucléides DTM après évaluation de la corrélation entre l’activité des DTM et l’activité de l’émetteur gamma dominant obtenue à partir d’échantillons. Si une corrélation existe, l’activité des radionucléides DTM peut être évaluée grâce à des facteurs de corrélation expérimentaux appelés « scaling factors », sinon l’activité moyenne obtenue à partir d’échantillons prélevés dans la population est attribuée à chaque colis. Lorsque les activités des émetteurs alpha et beta purs et des émetteurs X de faible énergie ne peuvent pas être estimées par mesure la méthode des « correlation factors » s’applique. La méthode des « correlation factors » se base sur le calcul de corrélations théoriques entre l’émetteur gamma dominant et les radionucléides de très faible activité. Cette thèse décrit en détail la nouvelle technique de caractérisation radiologique, montre un cas d’application complet et présente les résultats de l’industrialisation de la méthode ayant permis la caractérisation radiologique de plus de 1000 m3 de déchets radioactifs au CERN entre 2015 et 2017

Statistical analysis for the radiological characterization of radioactive waste in particle accelerators

This thesis introduces a new method to characterize metallic very-low-level radioactive waste produced at the European Organization for Nuclear Research (CERN). The method is based on: 1. the calculation of a preliminary radionuclide inventory, which is the list of the radionuclides that can be produced when particles interact with a surrounding medium, 2. the direct measurement of γ emitters and, 3. the quantification of pure-α, pure-β and low-energy X-ray emitters, called difficult-to-measure (DTM) radionuclides, using the so-called scaling factor (SF), correlation factor (CF) and mean activity (MA) techniques. The first stage of the characterization process is the calculation of the radionuclide inventory via either analytical or Monte Carlo codes. Once the preliminary radionuclide inventory is obtained, the γ-emitting radionuclides are measured via γ-ray spectrometry on each package of the waste population. The major γ-emitter, called key nuclide (KN), is also identified. The scaling factor method estimates the activity of DTM radionuclides by checking for a consistent and repeated relationship between the key nuclide and the activity of the difficult to measure radionuclides from samples. If a correlation exists the activity of DTM radiodionuclides can be evaluated using the scaling factor otherwise the mean activity from the samples collected is applied to the entire waste population. Finally, the correlation factor is used when the activity of pure-α, pure-β and low-energy X-ray emitters is so low that cannot be quantified using experimental values. In this case a theoretical correlation factor (CF) is obtained from the calculations to link the activity of the radionuclides we want to quantify and the activity of the key nuclide. The thesis describes in detail the characterization method, shows a complete case study and describes the industrial-scale application of the characterization method on over 1000 m3 of radioactive waste, which was carried out at CERN between 2015 and 2017

Radiological characterization of printed circuit boards for future elimination

Electronic components like printed circuit boards (PCBs) are commonly used in CERN's accelerator complex. During their lifetime some of these PCBs are exposed to a radiation field of protons, neutrons and pions and are activated. In view of their disposal towards the appropriate final repository, a radiological characterization must be performed. The present work proposes a general characterization procedure based on the definition of a reference chemical composition, on the calculation of the corresponding radionuclide inventory and on the measurement of a tracer radionuclide. This method has been validated with real-life cases of electronic boards which were exposed to the typical radiation fields in CERN's accelerators. The activation studies demonstrate that silver is the key element with respect to the radiological characterization of electronic waste due to the production of Ag-110m and Ag-108m. A sensitivity analysis shows that the waiting time is the main parameter affecting the radionuclide inventory. Results also indicate that, as is the case of other families of radioactive waste, an accurate assessment of the radiological inventory of PCBs would require the precise knowledge of their chemical composition, as well as the radiation field to which they were exposed

A New Approach to Estimate Uncertainty in Waste Characterization

International audienc

Statistical sampling applied to the radiological characterization of historical waste

The evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like γ-emitters and high-energy X-rays, can be measured via non-destructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM) from outside a package because they are α- or β-emitters. The present article discusses the application of linear regression, scaling factors (SF) and the so-called “mean activity method” to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN). Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given

A bayesian framework to update scaling factors for radioactive waste characterization

Nuclear power plants and research facilities commonly employ the so-called scaling factor (SF) method to quantify the activity of difficult-to-measure (DTM) radionuclides within their radioactive waste packages. The method relies on the establishment of a relationship between an easy-to-measure (ETM) radionuclide, called key nuclide (KN), and difficult-to-measure radionuclides, after the collection of a representative sample from the waste population. The distribution of the scaling factors, as well as the parameters defining the distribution, can change over time. Therefore, the accuracy of the calculated activity of the DTM radionuclides depends on the capacity of the scaling factor method to follow the time evolution of the waste population. In practice, waste producers collect periodically new samples from the waste population and check the variation and the validity of the scaling factors. In this article, we present a simple Bayesian framework to update scaling factors when a new data set becomes available. The method is tested and validated for radioactive waste produced at CERN (European Organization for Nuclear Research) and can be easily implemented for waste of different origin