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Assessing the formation of new volatile Particulate Matter in an atmospheric chamber depending on fuel composition: a step toward understanding nucleation mechanisms in aircraft engine emissions
No full textInternational audienceAviation emissions adversely affect air quality in and around airports, contributing to public health concerns for airport workers and within neighbouring communities (Neu, 2020). In addition to greenhouse gases like CO2, we need to consider volatile and nonvolatile Particulate Matter (vPM and nvPM, respectively – IATA, 2021). The nvPM are defined essentially as soot particles from the incomplete combustion of the fuel and present in the engine exhaust over 350 °C. The vPM are formed by nucleation from gaseous precursors in the cooling exhaust gas downstream of the engine. Sulfuric acid formed in the engine exhaust, completed by chemi-ions and organic compounds, seems to be linked to the formation of vPM (Vancassel et al. 2004; Sorokin et al. 2001). However, the molecular mechanisms behind this phenomenon are still unknown. The UNREAL project aims at studying at the molecular level the different mechanisms of new particle formation from the exhausts of aircraft engines fed by different fuel composition from the standard Jet A-1 to 100 % SAF (Alcohol to Jet, AtJ) (Ortega, 2020). Diluted fuel emissions produced from a liquid CAST burner (Jing 2003) were simultaneously injected, after particle filtration, into the CESAM atmospheric chamber (LISA, Créteil) and a Potential Aerosol Mass Oxidation Flow Reactor (PAM-OFR), for aging. A particular attention was given to the formation of new particles and notably organic matter. In addition to on-line characterization techniques (particle size distribution, number concentration and chemical composition), different filter samples were collected to study the particle chemical composition in laboratory by Two Step Laser Mass Spectrometry and Secondary Ion Mass Spectrometry techniques (Ngo et al., 2020). We compared the amount of vPM produced by Jet A-1 kerosene, AtJ synthetic kerosene and a blend of both. We found that AtJ was able to produce much more particles than both other fuels (Fig. 1). A new campaign, planned in April 2022, focusing on the first steps of nucleation will take advantage of an Atmospheric Pressure Interface Time of Flight Mass Spectrometer (API-ToF-MS) to characterize the clusters formed during the first steps of nucleation, determine key compounds and investigate their links with the fuel used
Construction de VGAI mélange : Étude de cas pour un mélange de substances irritantes: Avis de l’AnsesRapport d’expertise collective
No full textCitation suggérée :Anses. (2022). Construction de VGAI mélange : Etude de cas pour un mélange de substancesirritantes. (autosaisine n°2016-SA-0101). Maisons-Alfort : Anses, 183 p.La question de l’exposition de l’humain à des mélanges et du risque associé potentiel pour la santé se pose depuis de nombreuses années. Des documents et recommandations institutionnels sont notamment publiés depuis les années 2000 pour la prise en compte des mélanges, principalement dans le cadre d’évaluation des risques sur la santé (US EPA, 2000 ; 2002 ; 2006 ; ILSI, 1999; ATSDR, 2001 ; 2004; Health Council of the Netherlands, 2002; IGHRC, 2008; EFSA, 2008 ; 2009 ; 2013; WHO-IPCS, 2009; Kortenkamp et al., 2009; SCHER, 2011).Dans le domaine des substances chimiques, le nombre de composés enregistrés par le ChemicalAbstract Service (CAS) était de 34 millions en 2008 (Stewart and Carter, 2009). En 2018, plus de17 000 substances individuelles avaient été enregistrées dans le cadre de la réglementationeuropéenne REACh (Registration, Evaluation and Authorisation of Chemicals) (règlementn°1907/2006). Le nombre exact de substances chimiques sur le marché de l’Union européenne n’est pas connu précisément mais l’agence européenne des substances chimiques (ECHA) l’estimait en 2017 à près de 140 000 substances (https://echa.europa.eu/fr/registration-statistics-infograph#).Les contaminations environnementales (air, eau, sols etc.) par les substances chimiques peuventrésulter notamment : (i) des procédés de fabrication conduisant à des émissions potentielles dans l’air, l’eau et/ou les sols ; (ii) de l’utilisation de produits de consommation contenant des substances chimiques dans la vie quotidienne ; (iii) des émissions issues non intentionnellement de la combustion ; (iv) de la persistance dans l’environnement de substances qui peuvent être interdites à présent par la réglementation, etc.La gestion des risques liés aux substances chimiques est encadrée, d’une part par le règlementREACh, et d’autre part, par des réglementations par milieux (eau, air, etc.) et sectorielles(médicaments, cosmétiques, biocides, etc.), d’où découlent des analyses de risques séparées(Evans et al., 2016). Concernant les mélanges de substances chimiques, il existe dans certaines de ces réglementations des référentiels de gestion des risques cumulés proposant une approcheprogressive par étape. C’est le cas pour l’exposition via l’alimentation (résidus de pesticides et eaux destinées à la consommation humaine) et pour l’étude de l’impact d’installations industrielles sur l’environnement et le voisinage.La question des mélanges, si elle reste complexe, peut donc aujourd’hui être prise en compte dans les démarches d’expertise, compte tenu de l’existence de savoir-faire et de développement de modèles simplifiés faisant relativement consensus. Des recommandations d’organismesinstitutionnels (United States Environment Protection Agency (US-EPA), Agency for ToxicSubstances and Disease Registry (ATSDR), European Food Safety Authority (EFSA), ScientificCommittee on Health and Environmental Risks (SCHER)) soulignent l’importance de leur mise enapplication et formalisent des approches méthodologiques prenant en compte ou non lesinteractions entre les contaminants
Semi-explicit Monoterpene-SOA chemical mechanisms for regional-scale modeling
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Evaluation des risques des substances à effets sans seuil pour les enfants
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Sécuriser le déploiement des installations à hydrogène dans les territoires
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Biomarker toxicodynamics linked to BPA toxicokinetics in three-spined stickleback: a PBPK-TD model
No full textInternational audienceBisphenol A (BPA) is considered a substance of very serious concern due toits endocrine disruptor function, high production volume, and persistence in the aquaticenvironment. In this context, physiologically-based toxicokinetic models coupled withtoxicodynamics (PBTK-TD) have proven to be valuable tools. They allow proposingmore actual exposure scenarios as the exposure may vary over time and they alsoenable linking internal concentrations to various effects that are often decorrelated toexternal dose. Recently, a PBTK has been developed and adapted to BPA ADME(Absorption, Distribution, Metabolization, and Excretion) processes in the three-spinedstickleback. Thus, this work aimed to develop a PBTK-TD model that would permit tobetter understand the impact of BPA on the different functions of the fish, includingdefense capacities and reproduction. In particular, a precise knowledge of the internaldoses in the target organs would allow to i) clearly identify whether the transientbiomarker responses are linked to toxicokinetics, ii) identify the compounds (parentand/or metabolites) responsible for the biomarker responses, and iii) to identifynon-monotonic dose dependencies of biological responses to external exposures thatwould be non-monotonic. In detail, the PBTK was extended to include thetoxicodynamics of various biomarkers measured during two exposures to BPA, one ofseven-day exposure and seven-day depuration, and one of 21-day exposure.Biomarkers including non-specific cellular immunity, metabolic detoxification, oxidativestress, and reproductive parameters were analyzed to select a set of parametersvarying when exposed to BPA. Since it was supposed that the biomarker responseswere produced by indirect mechanisms, indirect toxicodynamic models were chosen todescribe the response. Consequently, mechanism-based equations describing theresponses of biomarkers over time were implemented in the existing PBTK specific toBPA. Then, TD data were divided into two sets, one to allow calibration of parametersrelated to biomarker toxicodynamics and the other to enable evaluation on an unusedcollection of TD data. This study demonstrates the relevance of the three-spinedstickleback as EDC sentinel species and the approach using a PBTK-TD to explore thedynamics of the EDC effects
Quantitative method of mass assessment using tem grids for airborne micrometric particle exposure characterization
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Quantification du risque de fuite sur des organes hydrogène haute pression
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CFD modelling of vented explosions for chambers of two different scales
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