HAL-BRGM, les publications scientifiques en libre accès du BRGM
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Etude scientifique et participative sur la qualité du sol et de l’air et sur la perception des pollutions par les habitants dans la zone Sebikotane-Diamniadio, Sénégal - Résultats du projet AirGeo (2021 – 2024)
No full textLow δ<sup>30</sup>Si values in olivine-hosted melt inclusions trace sediment contributions to subduction zone melts
No full textInternational audienceThis study reports the first high-precision silicon isotope (δ30Si) measurements of olivine-hosted melt inclusions (OHMIs) and their host olivine crystals using laser ablation multi-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS). We analyzed samples from two contrasting tectonic settings: three mid-ocean ridge basalts (MORB) and four island arc volcanic rocks. Our results reveal systematic differences in silicon isotope compositions between these two environments. MORB samples show internally consistent δ30Si values in both melt inclusions and host olivine crystals, with isotopic fractionation between phases suggesting equilibrium crystallization processes in MORB magmas. In contrast, arc samples display greater heterogeneity and systematically lower δ30Si values that deviate from equilibrium fractionation factors between olivine and melt. The absence of a correlation with the degree of polymerization of the silicate melt (NBO/T) indicates that these isotopic signatures are not controlled by melt structure. The coupling of low δ30Si and high δ18O values suggests significant contributions from subducted sedimentary materials, particularly siliceous components, to the arc magma source. Our results demonstrate that OHMIs preserve small-scale Si isotope heterogeneities which are invisible at the bulk rock scale. This work highlights the potential of in situ silicon isotope analysis of melt inclusions and their host crystals to trace magmatic processes and source contributions in different tectonic environments, hence providing new insights into the geochemical evolution of arc magmas and the role of subducted materials in mantle heterogeneity
Kinematic segmentation of a DSGSD on the flank of the exhumed Leo Pargil Dome (northwestern Himalaya) using InSAR
No full textInternational audienceDeep-seated landslides in high mountain terrain typically deform slowly over years to decades, making their internal kinematics difficult to characterise from field observations alone. Here we investigate the Leo Pargil landslide on the southwestern flank of the exhumed Leo Pargil gneiss dome in the northwestern Indian Himalaya, a large active deep-seated gravitational slope deformation (DSGSD) in the region. Multi-temporal persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis of Sentinel-1 data is combined with geological and structural information to characterise the landslide's present-day kinematics and internal segmentation. Ascending and descending Sentinel-1 data from 2018 to 2023 are combined to decompose InSAR-derived displacement into vertical and horizontal components, allowing spatial variations in displacement magnitude and direction to be resolved across the landslide body. The displacement field is strongly segmented, with faster-moving sections separated by sharp displacement gradients and relatively stable zones, indicating the presence of distinct internal sectors within the landslide. The upper part of the slope shows displacement patterns consistent with a rotational component near the headscarp, whereas the lower part is characterised by predominantly slope-parallel motion. Spatial variations in motion broadly follow mapped structural and lithological boundaries, indicating that inherited structures and slope geometry may influence the present-day deformation pattern. The results show that the Leo Pargil landslide is a segmented deepseated gravitational slope deformation on the flank of an exhumed gneiss dome, with its present-day kinematics consistent with inherited structural heterogeneity and ongoing geomorphic processes
Combining Mineral Liberation Analysis and Falcon gravity separation testing for reprocessing an ultrafine scheelite tailings
No full textInternational audienceHistorical mine tailings constitute both an environmental concern and a potential source of secondary raw materials. Indeed, these tailings can contain valuable metals and minerals due to less efficient beneficiation technologies in the past and to the fact that the original process did not seek out elements that are currently in high demand. Therefore, reprocessing mine tailings represents an opportunity to combine site remediation with the production of valuable elements. Although mine tailings do not require intensive regrinding, the fineness of the material poses a formidable separation challenge. Technological advances could overcome these difficulties, achieving higher separation efficiencies attained during production.This study investigates the feasibility of reprocessing scheelite tailings produced in the 1980s in order to mitigate their environmental impact and recover residual valuable metals. The tailings of interest comprises a one-metre-high oxidised layer, resulting from weathering, overlying a reduced layer with a thickness of several meters.The first part of the study is focused on comprehensive tailings’ mineralogical characterization by Mineral Liberation Analysis (MLA). The results showed that the unoxidized part of the tailings is rich in silicates, pyrrhotite and calcite, with arsenopyrite being the sole As-bearing mineral. Regarding the oxidised layer, the concentration of pyrrhotite, calcite and arsenopyrite are depleted and it contains a number of neoformed minerals, including gypsum and hydrous ferric oxides (HFO). Elemental deportment calculations show that HFO and arsenopyrite host 92.8% and 7.2% of the arsenic, respectively. Scheelite, however, remains the only W-bearing mineral in both sections of the tailings. Particle size analysis confirms the fineness of the tailings, with a P80 of less than 60 µm. Additionally, over 80% of the minerals of interest (scheelite and As-bearing minerals) occur below 40 µm. This situation can be explained by the brittle nature of scheelite and by the use of shaking tables and flotation steps during the exploitation of the scheelite mine.The second part of the work is dedicated to investigating the performance of several reprocessing flowsheets, in which the core separation step is enhanced gravity separation. The Falcon concentrator was selected based on its ability to recover tungsten-bearing minerals from fine materials. Separation tests were conducted to assess the effects of the feed material properties and operating conditions on the selective recovery of W- and As-bearing minerals, using MLA to better understand the separation mechanisms. A promising concentration performance was obtained on the oxidised tailings for scheelite, with a WO3 recovery of 60% and an enrichment ratio of 3.4 after three successive Falcon concentration steps. However, this performance was achieved for a feed sample that was deslimed at 10 µm, emphasizing the limits of the Falcon concentrator to recover ultrafine scheelite particles. Challenges were also encountered during the selective separation of arsenic. For the unoxidized tailings, this is primarily due to the similar density of arsenopyrite and scheelite, whereas for the oxidised tailings, this is due to the deportment of arsenic in HFO acting as a gangue mineral. These findings highlight the need for complementary downstream processing strategies for arsenic removal
Contributions to the development and simulations of generic, modular and multiphysics greenhouses dynamic models, evaluated with a whole year study case dataset
No full textAlso known as : A greenhouse dynamic model to assess sustainable solutions Contributions to the development and simulations of generic, modular and multiphysics greenhouses dynamic models, evaluated with a whole year study case datasetInternational audienceNorth-Western Europe heated greenhouses need to address their high fossil energy dependency while they start to face with climate change. In this context, physics-based greenhouses dynamic models can be used for prospective assessments of innovative shapes, equipment, control, etc. A prerequisite for such model-based evaluation is a review of existing implementations, the improvement and development of suitable sub-models in a generic and modular approach that do not require calibration, and the evaluation of a use case global model with a solid experimental dataset. First, this paper details contributions to existing models regarding several aspects: solar gain, boundaries effects, airflows and leakages, heat and mass transfer. The second part is dedicated to the evaluation of an experimental tomato greenhouse global model for an 11-month period. Its assessment is multiphysics: indoor climate, utilities consumptions, yield and Leaf Area Index. The resulting 5 min sampling indoor air climate Root Mean Square Error is 1.3 °C (temperature) and 8.1%RH (relative humidity). The tomato yield Mean Absolute Error is 1.1 kg m-2. Mass balances also quantify the losses and potentials for water and CO2. The global model outputs are compared with literature, and it is demonstrated that assessing the accuracy of models based only on statistical indicators is questionable. This approach is compatible with assessments of prospective solutions, it increases the confidence for scaling results from small to large commercial greenhouses, and it constitutes a base from which simpler and black box models can be derived for other applications such as predictive control
An extended kinematic inventory, magnitude-frequency curves, and damage assessment of rock slope failures in the central Spanish Pyrenees
No full textInternational audienceA new inventory of rock slope failures (RSFs) compiled in the central Spanish Pyrenees within the framework of the SPIRAL Project has identified 1232 RSFs, yielding a relatively low spatial density of 0.11 events per km 2 . These RSFs exhibit very slow to extremely slow average displacement rates, ranging from 5 mm to 75 mm per year. Rock slides and earthflows are the most prevalent failure types, accounting for over 93% of the total, whereas rock slope deformations (RSDs), composite failures, and rock avalanches are comparatively rare. This predominance of rock slides and earthflows results in a shallower magnitude-frequency distribution relative to other mountainous regions. Lithology, glacial debuttressing, and slope angle are identified as the most influential conditioning factors. Most RSFs occur on slopes between 20 • and 30 • , especially in deglaciated settings and in bedrock composed of fine-grained, low-strength lithologies, such as turbidites, slates, marls, and evaporitic sequences, where weathering plays a critical role in promoting slope instability. Unfortunately, these relatively moderate slopes, which often correspond to relict landslide deposits, provided favourable conditions for the establishment of at least 25 human settlements in the past. These communities are now under threat and will require multimillion-euro investments to stabilize active movements. Furthermore, 41 RSFs intersect communication and irrigation networks, 138 affect ski resort infrastructures, 94 compromise paved roads, and 29 pose risks to dam safety. The estimated direct costs associated with active RSFs already exceed €152 million, and additional substantial mitigation efforts are anticipated in the near future
Beyond green hydrogen production: Ground transport within Europe, the hidden environmental impacts
No full textInternational audienceAs Europe accelerates its transition to low-carbon energy, renewable hydrogen is expected to play a key role in decarbonizing hard-to-abate industrial sectors. While the environmental impacts of hydrogen production via electrolysis are starting to be well understood, those of its storage and transport remain poorly determined. Yet, they are crucial to overall sustainability. This study presents a comparative Life Cycle Assessment (LCA) of six land-based delivery pathways across Europe for green hydrogen produced via Proton Exchange Membrane (PEM) electrolysis powered by wind energy. The scenarios differ in storage and transport methods-compressed gas (by truck or pipeline), liquefied hydrogen, and three chemical vectors (dibenzyltoluene, ammonia and methanol) transported by truck. While the production phase of green hydrogen shows a low Global Warming (GW) impact, the delivery stages are far from negligible, leading in certain cases to an overall GW impact exceeding that of domestically produced blue or grey hydrogen. These findings are amplified by taking into account hydrogen leaks across the supply chain and their Global Warming Potential. However, results demonstrate that there is no one-size-fits-all hydrogen delivery solution; optimal pathways depend on supply chain parameters, mainly distance and hydrogen demand. Pipeline transport emerges as the most environmentally efficient option for largescale long-distance hydrogen transportation, whereas compressed gas hydrogen by truck is better suited for small-scale local delivery. Alternative delivery options, such as hydrogen liquefaction or conversion into chemical carriers with higher energy density, can lower transport-related emissions. These advantages often come with environmental trade-offs, as additional conversion steps shift part of the burden to other life-cycle stages and to other impact categories beyond GW, such as acidification and eutrophication. This study highlights the importance of integrating delivery considerations into hydrogen deployment strategies and policies. Finally, while the focus is on intra-European exchanges and ground transport, future work must investigate international hydrogen trade and maritime transport, along with their broader environmental and geopolitical implications
Multi-hazard probabilistic safety assessments using Bayesian networks – A framework and demonstration for integrating technical and human risk
No full textInternational audienceDespite the advantages of using Bayesian networks for probabilistic risk assessment, adoption in practice has been limited due to the lack of realistic, facility-scale studies. Scaling up from systems to facility-level safety assessments poses challenges in (i) integrating external hazards and their cascading effects, and (ii) resolving non-homogeneity of various technical and human reliability models. The novelty of the study is in formalising risk integration using Bayesian networks, at facility scale, and demonstrating its effectiveness in addressing associated challenges. A Bayesian network-based multi-hazard risk framework is introduced and demonstrated for a nuclear power plant subject to flooding and earthquake hazards, capturing dependencies among hazards and consequences. Individual reliability modelsconventionally extraneous to facility-wide risk modelsare included as subnetworks by using Bayesian network-based surrogate models for technical systems and a Bayesian networks approach for human reliability modelling. Two approaches are used for subnetwork integrationobject-oriented and unified Bayesian networks. The unified approach allows for prediction, diagnostics and intercausal reasoning since Bayesian inference is bi-directional. Conversely, in the object-oriented approach, diagnostics are limited to within individual subnetworks and as a consequence the model can potentially neglect dependencies between objects. However, the object-oriented model requires only 50 % of the computational memory and consumes less than 25% of the runtime as the unified network, while improving visual clarity of the risk model. The model reveals key insightsfor example, variations in operator stress or available response time during a hazard event can result in up to a 77 % change in top event probabilitydemonstrating its effectiveness in capturing critical relationships in complex, facility-scale risk scenarios. These findings can be used to suitably allocate resources towards risk mitigation and plant safety management
Optimal structures of crop irrigation strategies with state constraints
No full textInternational audienceWe investigate an optimal control problem of crop irrigation with non-autonomous and non-smooth dynamics. Depending on contexts and objectives, several formulations associated to different constraints and criteria can be derived. Our work aims at providing optimal feedback solutions for these problems by deriving and analyzing the optimality necessary conditions. To this end, we assemble the different problems into a common formulation, and we carry out a dedicated way of handling state constraints. We show that all optimal irrigation strategies belong to a family of simple parameterized time-varying feedback controls, independently of the context and objective, and suitable for computational purposes
Introducing the concept of supervised stacking to improve the signal-to-noise ratio: application to airborne electromagnetic data
No full textInternational audienceGeophysics provides useful information of the subsurface for many applications. However, noise generally affects the dataset, which may prevent the acquisition of usable data. Stacking techniques can be used in an attempt to improve the signal-to-noise ratio. However, stacking is generally applied without any control on the raw data taken into account, and can be ineffective given the nature of noise that can affect the dataset. To a lesser extent, arbitrarily increasing the stack size may also be ineffective, especially in anthropized environments.This paper introduces a supervised stacking method that stacks raw data considering different combinations, and then estimates the signal-to-noise ratio of the resulting stacked data. The estimation of the signal-to-noise ratio uses the singular value decomposition filtering, which has proven to be effective in identifying noise affecting AEM data.The stacking method is applied to the raw data of three different AEM datasets acquired in noisy resistive environments. The results show that the method improves the signal-to-noise ratio and can reduce high-amplitude noise. It provides less noisy data for post-processing and offers new processing possibilities