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Development of a single biofilm extraction method for non-target analysis and bioassays to monitor wastewater micropollutants
No full textInternational audiencePassive samplers (PS) are strong tools to monitor micropollutants due to their ability to accumulate andconcentrate the pollutants present in water. Among existing PS, those using biofilms as a receiving phasehave gained interest for environmental monitoring, notably in waste water, for which conventional PS arelimited by biofouling. Extraction and (bio)analysis of contaminants adsorbed in biofilms still needoptimisation in monitoring context. Non-target analysis has been increasingly used during the last decadeto detect a large range of water micropollutants, including emerging contaminants, which positions it as agreat tool for environmental monitoring. However, this method does not account for the biologicalactivities of the compounds, and the impact of mixture effects on their activity. Hence, as acomplementary approach, in vitro bioassays provide a global bioactivity profile of the water sampleswhile considering all the bio-active micropollutants and their potential mixture effect. The combination ofPS with bioassays and chemical analysis has already shown its effectiveness in characterizing water.This work aims to develop an approach based on the coupling of an innovative biofilm -based PS withnon-target screening and in vitro bioassays to characterize wastewater. This presentation will mainly focuson the development a single biofilm extraction method for both non -target analysis and bioassays,allowing us to have a robust correlation between the compounds analysed and the activity measured.Several solvents, extraction methods, and clean-up strategies were implemented and compared for biofilmextraction. The extracts were then subjected to chemical analysis and in vitro bioassays. For the chemicalanalysis performed on a liquid chromatography coupled to a high-resolution mass spectrometry, theextraction efficiency was evaluated based on characteristics such as standard recoveries, number ofcommon and specific compounds detected with suspect screening, number of common and specificunknown features detected, and range of molecular weight or polarity. For bioassays, the evaluations wereassessed on the response of four nuclear receptors (estrogenic, androgenic, pregnane X, and arylhydrocarbon receptors).Based on the outcome of the results obtained for these tests, a single extraction protocol offering the bestefficiency compromise for both chemical analysis and in vitro bioassays will be presente
An Ensemble Machine Learning Approach for Predicting Sources of Organic Aerosols Measured by Aerosol Mass Spectrometry
No full textInternational audienceLong-term source apportionment of atmospheric organic aerosols (OA) is essential for supporting air pollution management strategies. While aerosol mass spectrometry (AMS) combined with traditional source apportionment tools can accurately identify various OA sources, they face efficiency challenges when processing large volumes of long-term data. This study proposes an ensemble machine learning approach to efficiently apportion OA sources from long-term AMS measurements. Using six-year observation of a simplified version of AMS (i.e., ACSM) in the Paris region along with OA factor data derived from positive matrix factorization analysis, we developed an ensemble machine learning source apportionment model. Compared to individual machine learning algorithms, the ensemble model substantially reduced the root-mean-square error (RMSE) and increased the correlation coefficient in predicting OA sources by approximately 30% and 5%, respectively. Sensitivity analysis with five years of baseline data revealed that model performance relatively stabilizes when the training data exceeds two years, with RMSE values for primary and secondary OA factors at 0.31–0.45 μg/m3 and 0.69–0.84 μg/m3, respectively. This ensemble model not only enhances the efficiency of long-term OA source apportionment but also holds potential for near-real-time online applications
Oxidative potential of atmospheric particles in Europe and exposure scenarios
No full textInternational audienceAtmospheric particulate matter (PM), a public health concern worldwide, is at present regulated according to its mass concentration1. However, it is increasingly thought that mass concentration may not fully capture the physicochemical properties of PM linked to its health impact2. Consequently, it has been suggested to further investigate the adequacy of this metric as an unequivocal indicator of PM health effects3, 4-5. The new European regulation on air quality introduced oxidative potential (OP) as a recommended parameter to be monitored at supersites1, to explore further deciphering information about PM reactivity and health impacts6,7. Here we use a database of almost 11,500 OP measurements from 43 locations across parts of Europe that were analysed with the two most commonly used OP assays8, OPAA and OPDTT, with a standardized protocol9,10. We find high spatial variability of OP across Europe, strongly influenced by site type, such as urban or rural. Accounting for OP alongside PM mass suggests that further improvements in urban air quality may require consideration, particularly near roads, where volumetric OP of PM10 exceeds background levels by a factor of 2.4 to 3.1, depending on the assay used. Analysis of mitigation strategies shows that traffic is a key source to target for effectively reducing OP in cities, whereas comprehensive reductions in PM from both traffic and biomass burning are required to also meet World Health Organization mass guidelines. Although the epidemiological evidence for OP health impacts is still evolving2,8, our findings may help inform the interpretation of future work
Nontarget and Suspect Screening of Fluorinated Ionic Liquids and PFAS in European Wastewaters Using Supercritical Fluid Chromatography
No full textInternational audiencePer- and polyfluoroalkyl substances (PFAS) and fluorinatedionic liquids were investigated in municipal effluents from 30 wastewatertreatment plants (WWTPs) across 15 European countries using supercriticalfluid chromatography−high-resolution mass spectrometry (SFC-HRMS) fornontarget screening. Bis-perfluoroalkyl sulfonimide (bis-FASI) ionic liquidswere detected as bis(trifluoromethanesulfonyl)imide (NTf2−), two rarelyreported homologues (±2 CF2, namely FSI− and BETI−), and two previouslyunreported homologues (±1 CF2, namely FTFSI− and FTNTf2−). Bis-FASIswere present in 85% of samples and were more abundant in effluents fromlarger WWTPs. The fluorinated anion PF6−, commonly used in ionic liquids,was found in all samples (≤3 μg/L). Hexafluoroarsenate (AsF6−), reportedhere for the first time in municipal wastewater, was detected in 32% of samplesin eight countries. PF6− and AsF6− concentrations exceeded those of traditionalPFSAs and PFCAs in 97% of the samples. No removal was detected for perfluorinated compounds, inorganic anions, and lowfluorinatedpharmaceuticals and pesticides. Low-fluorinated substances were detected in 90% of samples (>100 ng/L), yet PF6−alone surpassed the combined concentration of all low-fluorinated substances in 27 out of 30 samples. These results reveal thesignificance of unconventional fluorinated substances for the overall fluorine load in wastewater, highlighting the need to extendmonitoring strategies beyond legacy PFAS
Amélioration de la connaissance des mécanismes d'instabilité et de l'impact du changement climatique sur les cavités souterraines
No full textInternational audienc
Automatic Classification of Acoustic Signals for Rockfall Detection in an Abandoned Chalk Mine Using Machine Learning
No full textInternational audienceThis study investigates the use of machine learning for the automatic classification of acoustic signals in an abandoned chalk mine to detect rockfall events, which can indicate potential structural collapse. Acoustic data from the Royer mine in Château-Landon, France, were used and classified into three categories: rockfall events, non-rockfall noises, and autotests. We employed a comprehensive approach that included data preprocessing, feature extraction, data augmentation, and hyperparameter tuning to optimize model performance. Additionally, we tested two input handling approaches: one where each event is treated as a combination of four signals, and another where each signal is considered individually. The models tested include Logistic Regression, Random Forest, Support Vector Classifier (SVC), and XGBoost. After applying these techniques, we achieved an overall accuracy exceeding 92%, with rockfall detection showing particularly high performance, reaching a recall close to 0.98. These results demonstrate the effectiveness of machine learning in distinguishing rockfall events from other acoustic signals. Extending this method to other monitoring mines with diverse geological conditions could help validate and generalize the approach. The developed AI-based monitoring system offers a promising solution for real-time mine safety management, significantly reducing manual analysis efforts and enhancing risk assessment capabilities
Note d’appui scientifique et technique de l’Anses relative à l’élaboration de concentrations seuils pour les substances chimiques présentes dans les produits de protection intime
No full textCitation suggérée : Anses. (2025). Note d’appui scientifique et technique de l’Anses relative à la présence desubstances chimiques dans les produits de protection intime. (saisine 2024-AST-0115). Maisons-Alfort : Anses, 66 p.L’Anses a été saisie le 26 juillet 2024 par la Direction générale de la santé (DGS) et la Direction générale de la concurrence, de la consommation et de la répression des fraudes (DGCCRF) pour la réalisation de l’appui scientifique et technique suivant : élaboration de concentrations seuils pour les substances chimiques présentes dans les produits de protection intime.CONTEXTE ET OBJET DE LA DEMANDESuite à une saisine de la DGCCRF et de la DGS, l’Anses a publié en 2019 une expertise sur la sécurité des protections intimes (Anses 2019). Celle-ci n’a pas mis en évidence de préoccupation sanitaire liée aux substances chimiques présentes dans ces produits. Le principal risque est lié uniquement au port de protections intimes internes (tampon, coupe menstruelle) : le syndrome de choc toxique menstruel, bien que rare, peut entraîner de graves conséquences sur la santé des femmes qui en sont victimes.Depuis cette expertise, des actions ont été mises en œuvre par le gouvernement afin d’inciter les industriels à mettre en place des autocontrôles périodiques des produits et à améliorer leur processus d’approvisionnement et de fabrication de façon à supprimer ou limiter autant que possible la présence de substances chimiques réoccupantes (HAP, dioxines, furanes, phtalates, pesticides notamment). D’autre part, des contrôles périodiques ont été diligentés sur ces produits par la DGS et la DGCCRF dont les derniers résultats d’enquête sur les nouveaux produits de protection intime (serviettes réutilisables ou culottes menstruelles, tampons à usage unique dits « biologiques » ou réutilisables) ont été publiés en mars 2022 [1].Le 30 décembre 2023 a été publié le décret n°2023-1427 relatif à l’information sur certains produits de protection intime [2]. Celui-ci vise à renforcer la protection et l’information des consommatrices et, en particulier, l’information spécifique sur les produits de protection intime sur les trois points essentiels suivants : la composition de ces produits, les modalités et précautions d’utilisation et les risques sanitaires associés à la composition ou à l’utilisation de ces produits.Dans le but de contrôler l'application du décret cité précédemment, la DGCCRF et la DGS ont saisi l’Anses pour élaborer des concentrations seuils correspondant à la quantité théorique maximale par substance à ne pas dépasser dans une protection intime, par type de produit (serviettes hygiéniques, protège-slips, tampons et coupes menstruelles). Ces valeurs non réglementaires permettront aux autorités de contrôle de décider des suites à donner à l’issue des campagnes de contrôle effectuées par le service commun des laboratoires (SCL) sur les produits de protection intime présents sur le marché français.L’expertise sera réalisée pour les substances détectées et quantifiées dans les essais réalisés par le SCL en 2016, 2019 et 2021 et l’institut français du textile et de l’habillement (IFTH) en 2018 (Anses 2019), ainsi que pour les substances suivantes très susceptibles d’être retrouvées, en quantités diverses, à la fois dans les tampons et les protections externes : tous les HAP, tous les dioxines et furanes, tous les polychlorbiphényle (PCB), le glyphosate et ses métabolites, l’acide aminométhylphosphonique (AMPA) et le N-acétyl glyphosate, ainsi que le dichlorodiphényltrichloroéthane (DDT) et ses 6 métabolites.Il est également demandé à l’Anses de fournir un appui à l'interprétation des données issues des résultats d'analyses des contrôles d'articles à venir, notamment pour d'éventuelles nouvelles substances.L’Anses souligne que les autres types de protection intime (culotte menstruelle, éponge, etc.) ne sont pas inclus dans le champ de cette expertise.[1] https://www.economie.gouv.fr/dgccrf/laction-de-la-dgccrf/les-enquetes/controle-des-nouveaux-produits-dhygiene-feminine, consulté le 20/03/2025[2] https://www.legifrance.gouv.fr/jorf/article_jo/JORFARTI000048737554, consulté le 18/03/2025(Saisine liée n°2016-SA-0108
La fabrique de la prévention des risques industriels majeurs en chimie de spécialité : bilan et perspectives
No full textInternational audienceCe chapitre se nourrit du long travail effectué depuis 2004 conjointement, ou séparément par les deux auteur.e.s pour comprendre la fabrique de laprévention des risques industriels majeurs au sein d’entreprises de la chimie, et en particulier de la chimie de spécialité1, mais aussi d’autres systèmes à risques, tels que des installations nucléaires de base, des stockages de déchets nucléaires, des usines pyrotechniques, de la métallurgie ou le transport de gaz… La recherche commune porte sur cinq grands cas de chimie de spécialité que nous avons observés, décrits et analysés en étant attentifs au travail de la grande pluralité d’acteurs contribuant dans ces entreprises à produire la sécurité industrielle3 par interactions avec des acteurs externes
Technical note: sensitivity of the CAMS regional air quality modelling system to anthropogenic emission temporal variability
No full textInternational audienceAn accurate characterization of the temporal distribution in primary emissions is essential for air quality modeling. This study evaluates the impact of replacing the default temporal profiles in the Copernicus Atmosphere Monitoring Service (CAMS) European air quality multi-model ensemble with an updated dataset (CAMS-REG-TEMPO). The sensitivity of 11 regional models and the ensemble to these changes is assessed by comparing modeled and observed monthly, weekly, and diurnal cycles of nitrogen dioxide (NO2), ozone (O3), coarse particulate matter (PM10), and fine particulate matter (PM2.5) across Europe. NO2 shows the greatest improvement, with weekly cycle correlations increasing up to +0.17 due to better road transport emissions representation. PM10 correlations improve in winter (up to +0.13 weekly and +0.07 diurnal) due to refined residential wood combustion emissions. PM2.5 correlations remain largely unchanged, except for diurnal cycles, which improve in winter (+0.18) but slightly degrade in spring and summer (−0.02). O3 is the least affected, as correlations were already high with default profiles (0.9–0.95). For some species and timescales (e.g., NO2 diurnal cycles), results vary across models, highlighting the complex interactions between emission timing and atmospheric processes. CAMS-REG-TEMPO has little effect on annual RMSE and bias, aside from slight improvements in high PM10 concentrations. Overall, the findings support implementing CAMS-REG-TEMPO in the operational CAMS multi-model ensemble
Addressing the advantages and limitations of using Aethalometer data to determine the optimal Absorption Ångström Exponents (AAEs) values for eBC source apportionment
No full textInternational audienceThe apportionment of equivalent black carbon (eBC) to combustion sources from liquid fuels (mainly fossil; eBCLF) and solid fuels (mainly non-fossil; eBCSF) is commonly performed using data from Aethalometer instruments (AE approach). This study evaluates the feasibility of using AE data to determine the absorption Ångström exponents (AAEs) for liquid fuels (AAELF) and solid fuels (AAESF), which are essential parameters for the AE approach. AAEs were calculated from Aethalometer data as the fit in a log-log space of the six absorption coefficients (470-950 nm) versus the corresponding wavelengths. Our results demonstrate that AAELF can be robustly determined as the 1st percentile (PC1) of AAE values from fits with R2>0.99. This R2-filtering was necessary to remove extremely low and noisy-driven AAE values commonly observed under clean atmospheric conditions (i.e., low absorption coefficients). Conversely, AAESF can be obtained from the 99th percentile (PC99) of unfiltered AAE values. To optimize the signal from solid fuel sources, winter data should be used to calculate PC99, while summer data should be used to calculate PC1 to maximize the signal from liquid fuel sources. The derived PC1 (AAELF) and PC99 (AAESF) values ranged from 0.79 to 1.08, and 1.45 to 1.84, respectively. The AAESF values were further compared with those constrained using the signal at mass-to-charge 60 (m/z 60), a marker for fresh biomass combustion, measured by aerosol chemical speciation monitor (ACSM) and aerosol mass spectrometry (AMS) instruments deployed at 16 sites. Overall, the AAESF values derived from the two methods showed strong agreement, with a coefficient of determination of 0.78. However, the uncertainties in both approaches can vary depending on site-specific sources, and in certain environments, such as at traffic-dominated sites, neither approach may be fully applicable