Institut de Radioprotection et de Sûreté Nucléaire

Manganese (Mn) removal in passive mine water treatment remains a challenge due to its slow oxidation kinetics, requiring specific biogeochemical conditions. Constructed wetlands are often the key functional units enabling Mn removal in full-scale passive treatment plants. This study examines the key biogeochemical factors influencing Mn removal in a full-scale passive mine water treatment plant located in Alès (South-East France). Over one year, monitoring of physicochemical parameters, microbial communities, and Mn speciation in solid phases was conducted every two months. Results highlight temporal variations in Mn removal efficiency, with two main mechanisms identified: (1) Mn carbonate (MnCO₃) precipitation, likely influenced by high carbonate concentrations in mine water, and (2) Mn oxide (δ-MnO₂) formation, mainly associated with reed rhizosphere, where it accumulates as mineral plaque. In mine water, Mn removal correlates with Fe particle concentrations, suggesting a catalytic effect, as well as with alkalinity and the abundance of microorganisms affiliated to Alteromonadaceae, suggesting a microbial influence. Mn removal appears to be primarily abiotic, driven by favourable pH and alkaline conditions that promote Mn carbonate precipitation, by autocatalytic oxidation reactions occurring on rhizosphere surfaces and by plant's design including surface area and hydrological conditions. Microbial communities may facilitate certain Mn removal processes depending on environmental conditions.

The Management and Uncertainties of Severe Accident (MUSA) project aimed to establish a harmonised approach for applying BEPU methods in severe accident analyses, with particular focus on the source term. The second work package “ Identification & Quantification of Uncertainty Sources” addressed one of the most crucial steps in BEPU analysis applying forward uncertainty propagation. Its main outcome is a knowledge-based matrix compiling over 600 uncertain input parameters related to source term assessment, including their associated models, phenomena, and (partial) quantifications. It was utilised and continuously updated in subsequent calculation work packages (Phebus FPT1, reactor and SFP case). First a consistent set of Figure of Merits, such as iodine and caesium release, was established. A systematic backward selection and characterisation approach of the associated uncertain input parameters was established, considering among others influencing phenomena, modelling choices, code capabilities, etc. While some parameters, such as shape factors, were common across codes - though different characterisations depending on code/user were provided - others were code-specific, appearing in only one or few codes. Establishing physically justifiable distributions proved challenging largely due to the scarcity of data and consequently heavy reliance on expert judgement and code-specific knowledge. Nevertheless, each parameter's characterisation had to be defendable on scientific grounds. In the absence of direct evidence, the characterisation was justified based on physical behaviour, while where direct association was not possible due to system complexity, on reasonable indirect evidence. This paper presents an overview of the work, main findings and conclusions, including the data base, and highlights key challenges and future research needs identified during the project. • Identification and quantification of uncertainty sources related to source term. • Systematic backward approach to select and quantify uncertain input parameters associated with the source term. • Comprehensive data base consisting of over 600 uncertain input parameters, including their quantification. • Scientifically defendable characterisation including justification. • Identification of future needs: further harmonisation, cross comparison as well as extension of the data base.

Abstract. We describe an improved method and the associated package for estimating the statistics of temperature extremes in a Bayesian framework. Building on previous work, this method uses a range of climate model simulations to provide a prior of the real-world changes, and then considers observations to derive a posterior estimate of past and future changes. The new version described in this study makes it possible to process several scenarios simultaneously, while keeping one single counterfactual world (i.e., the world without human influence). We offer a free licensed, easy-to-use command-line tool called ANKIALE (ANalysis of Klimate with bayesian Inference: AppLication to extreme Events), which can be used to reproduce the analyses presented here, as well as to process user-defined events. ANKIALE is based on a python code, but is designed to be used from the command line interface. ANKIALE is natively parallel, enabling it to be used on a personal computer as well as on a supercomputer. To derive the posterior, ANKIALE uses state of art MCMC-methods to sample the posterior distribution. The potential of this method and tool is illustrated via an application to maximum temperature over Europe between 1850 and 2100 (the posterior is derived from ERA5, covering the period from 1940 to 2024), at a 0.25° resolution, for a range of four emission scenarios, including a particular focus on the city of Paris (France).

Probabilistic Fault Displacement Hazard Analysis (PFDHA) quantifies the probability and the expected amount of coseismic displacement associated with the activity of Active and Capable Faults (ACFs) at a given site. Common PFDHA approaches distinguish between primary on-fault displacement and distributed off-fault ruptures occurring on secondary faults or fractures and typically rely on empirical scaling relationships calibrated for specific earthquake magnitudes. However, these methods are often calibrated for specific tectonic or kinematic settings and lack readily available computational tools. Moreover, available PFDHA approaches do not commonly include the possibility to investigate the floating rupture mechanism, i.e., the possibility that surface ruptures involve only portions of the full fault trace.To overcome these limitations, we developed FaulTED, a new user-friendly MATLAB-based code for PFDHA that integrates a comprehensive set of published models, including magnitude–frequency distributions, fault scaling relationships, and surface rupture probability functions. The toolkit comprises two main modules: (i) a site-specific hazard curve calculator and (ii) a fault-specific hazard map generator for user-defined return periods. Both modules explicitly account for on-fault and distributed off-fault ruptures and incorporate the floating rupture approach commonly adopted in probabilistic seismic hazard analysis.The modular architecture of FaulTED allows users to flexibly select and compare alternative models through a structured input file, enabling sensitivity analyses and systematic exploration of epistemic uncertainties. FaulTED is designed as a user-oriented platform to support infrastructure planning in regions affected by ACFs.

The Western Alps have been the focus of detailed seismological investigations based on instrumental records, revealing diffuse seismicity predominantly expressed as earthquake swarms (M < 3.5), mainly concentrated along major inherited shear zones. Geological evidence indicates that these structures are compatible with a main cumulated strike-slip motion, whereas GPS data and instrumental seismicity suggest predominantly vertical deformation. Historical archives further document several moderate earthquakes (M > 5), particularly in the Ubaye–Mercantour region. The Durance–Sérenne–Bersezio fault system is identified as the main active structure in this area and is therefore the focus of a multidisciplinary study aimed at detecting and characterizing co-seismic surface ruptures.At the Lombarde Pass (Mercantour), a 2 km-long fault scarp displays geomorphological markers indicative of right-lateral strike-slip motion along the Bersezio fault. Several ERT profiles across the fault highlight a very localized low-resistivity zone in the bedrock beneath the morphological scarp. Paleoseismological trenches excavated across the fault scarp reveal a clear, single co-seismic rupture, with a maximum vertical apparent offset of ~1 m at the bedrock–Quaternary deposits interface. Radiocarbon dating (¹⁴C) of bulk sediment samples from three trenches constrains this event to 7–6 ka cal BP, consistent with post–Younger Dryas deglaciation.These results suggest the occurrence of large-magnitude earthquakes (M > 6) in a region currently dominated by swarm seismicity and provide new constraints on fault kinematics and deformation localization at the boundary between the internal and external Alpine domains.This study sheds new light on discussions held during the PATA Days 2022 field trip, where this unusual tectonic structure in the Western Alps raised passionate questions about its Holocene activity and seismic potential.

This review comprehensively examines the variability and uncertainty associated with test guideline (TG)-conform genotoxicity data and explores the respective implications for the integration of non-animal-methods (NAMs) into regulatory frameworks. Historical amendments to OECD TGs are mapped to reveal the method's evolution that improves the scientific quality of the data but also explains data heterogeneity within available databases. An analysis of the major genotoxicity databases ECVAM, ISSMIC, and OASIS demonstrates substantial variability in genotoxicity calls. Using the EFSA genotoxicity database, which currently harbours the best-curated (meta-) data, we estimate that 22-77% of compounds exhibit similarity of replicate results below 85%, depending on the assay. The potentially most important variables statistically explaining variability and sensitivity were analysed. The practical limitations to identify them with high reliability and to define their optimum needs to be accepted as a qualitative baseline uncertainty. These findings underscore the necessity of contextualizing NAM performance evaluations within the intrinsic variability and uncertainty of animal and in vitro reference data. We propose that this variability is explicitly considered in the development and validation of NAM-based Integrated Approaches for Testing and Assessment. This review provides a critical foundation for regulators and scientists aiming to enhance the acceptance and utility of NAMs in genotoxicity assessment.