Laboratoire Interuniversitaire des Systèmes Atmosphériques
Présentation
Le LISA, Laboratoire Interuniversitaire des Systèmes Atmosphériques est une unité de recherche de structure originale dépendant des Universités Paris Est Créteil et Paris Diderot, et du CNRS (UMR CNRS 7583).
Le LISA compte environ 130 personnes, dont 50 enseignants-chercheurs et chercheurs (CNRS & IRD), 36 ITA-IATOS et environ 45 post-doctorants, doctorants et étudiants de Master.
Il dispose d'un important potentiel technique et expérimental réparti sur 3.600m2 de locaux à Créteil et d'une antenne opérationnelle sur le site Paris Rive Gauche, incluant aussi des équipements lourds. Les recherches y sont développées autour d’un thème générale : l’Atmosphère (comme le nom du laboratoire l’indique), Ses principaux thèmes de recherche portent ainsi sur la compréhension du fonctionnement des atmosphères terrestres et planétaires, et des impacts liés à la modification de la composition de l'atmosphère par les activités humaines. Les méthodes utilisées sont fondées sur des observations en atmosphère réelle, sur de la simulation expérimentale en laboratoire et de la modélisation numérique.
Pour mener à bien ces recherches, le LISA regroupe des scientifiques de plusieurs disciplines : physiciens, géochimistes, environnementalistes et une majorité de chimistes. Ce dernier aspect est une de ses caractéristiques importantes par rapport aux autres laboratoires du domaine. Un département technique (doté de 4 pôles : chimie, instrumentation, terrain et informatique) et un département administratif sont en soutien des activités de recherche.
Thèmes de recherche
- Pollution atmosphérique Oxydante et Particulaire
- Devenir du Carbone Organique
- Cycle de l’Aérosol Désertique
- Spectroscopie et Atmosphères
- Exobiologie et Astrochimie
[insu-00357990] Comparison of two major sources of uncertainty in Titan ionospheric chemistry: neutral densities and ion-molecule reactions
Date: 2 Feb 2009 - 15:18
Desc: Discrepancies between the outputs of different models and available data are difficult to assess in the absence of quantified uncertainties. In particular, modelling the chemistry of planetary ionospheres involves numerous physical and chemical parameters, which values are known from laboratory measurements with experimental uncertainty factors. These uncertainty sources should be accounted for in the modelling. In a previous study about Titan ionospheric chemistry 1 we reported the first detailed uncertainty analysis concerning the kinetics parameters of the ion-molecule reactions. We showed that uncertainties on branching ratios contribute significantly to the estimated uncertainties on ion densities. Neutral species were considered as a fixed bath in Titan's ionosphere. Considering that ion densities closely depend on the neutral atmosphere 2 , we expect an important impact of densities of neutral species 3 on the uncertainties of ion densities. In this work, we take into account both uncertainty sources, quantifying their respective contribution to the ion density uncertainties. Uncertainty propagation is performed by Monte Carlo sampling. In addition, we assess the sensitivity to three turbulent diffusion profiles for the neutral species, corresponding to the extreme profiles at high altitudes described in the literature.
[hal-00264480] Uncertainty Analysis in Titan Ionospheric Chemistry Model
Date: 17 Mar 2008 - 13:26
Desc: The Ion Neutral Mass Spectrometer (INMS) of Cassini revealed a rich ion-neutral chemistry in the ionosphere, producing heavy hydrocarbons and nitriles ions. The modelling of such a complex chemistry is challenging, as it involves hundreds of ion-molecule reactions, in addition to an even more complex photochemical-transport model for the neutral atmosphere. The reactions are parametrized by rate constants and branching ratios of products, which have been measured with often sizeable uncertainties. Validation of the ionospheric chemistry model presently relies on the comparison of simulated ion mass spectra (MS) with INMS data, and thus on the estimation of prediction uncertainty. An error budget has been undertaken for the pertinent sources of uncertainty (chemical parameters, neutral densities...). By uncertainty propagation (Monte Carlo sampling) we identified neutral densities as a major source of uncertainty, in comparison to the chemical parameters [1]. Large uncertainties actually characterise the simulated mass spectra, in particular at the higher masses (m/z > 50 amu). In order to identify the parameters responsible for these large uncertainties, a global sensitivity analysis was started. Based on ionospheric and stratospheric chemistry models, we identified a small set of ion-molecule and neutral-neutral reactions, responsible for the large uncertainties on the model predictions. We point out key reactions in need of more accurate laboratory measurements.
[hal-01427727] Décrypthon Grid - Grid Resources Dedicated to Neuromuscular Disorders
Date: 6 Ene 2017 - 00:24
Desc: Thanks to the availability of computational grids and their middleware, a seamless access to computation and storage resources is provided to application developers and scientists. The Décrypthon project is one example of such a high performance platform. In this paper, we present the architecture of the platform, the middleware developed to facilitate access to several servers deployed in France, and the data center for integrating large biological datasets over multiple sites, supported by a new query language and integration of various tools. The SM2PH project represents an example of a biological application that exploits the capacities of the Décrypthon grid. The goal of SM2PH is a better understanding of mutations involved in human monogenic diseases, their impact on the 3D structure of the protein and the subsequent consequences for the pathological phenotypes.
[hal-02171283] MiSynPat: An integrated knowledge base linking clinical, genetic, and structural data for disease-causing mutations in human mitochondrial aminoacyl-tRNA synthetases
Date: 2 Jul 2019 - 18:38
Desc: [...]
[hal-01250910] Detection and Characterisation of Mutations Responsible for Allele-Specific Protein Thermostabilities at the Mn-Superoxide Dismutase Gene in the Deep-Sea Hydrothermal Vent Polychaete Alvinella pompejana
Date: 5 Ene 2016 - 14:27
Desc: Alvinella pompejana (Polychaeta, Alvinellidae) is one of the most thermotolerant marine eukaryotes known to date. It inhabits chimney walls of deep-sea hydrothermal vents along the East Pacific Rise (EPR) and is exposed to various challenging conditions (e.g. high temperature, hypoxia and the presence of sulphides, heavy metals and radiations), which increase the production of dangerous reactive oxygen species (ROS). Two different allelic forms of a manganese-superoxide dismutase involved in ROS detoxification, ApMnSOD1 and ApMnSOD2, and differing only by two substitutions (M110L and A138G) were identified in an A. pompejana cDNA library. RFLP screening of 60 individuals from different localities along the EPR showed that ApMnSOD2 was rare (2 %) and only found in the heterozygous state. Dynamic light scattering measurements and residual enzymatic activity experiments showed that the most frequent form (ApMnSOD1) was the most resistant to temperature. Their half-lives were similarly long at 65 A degrees C (> 110 min) but exhibited a twofold difference at 80 A degrees C (20.8 vs 9.8 min). Those properties are likely to be explained by the occurrence of an additional sulphur-containing hydrogen bond involving the M110 residue and the effect of the A138 residue on the backbone entropy. Our results confirm the thermophily of A. pompejana and suggest that this locus is a good model to study how the extreme thermal heterogeneity of the vent conditions may help to maintain old rare variants in those populations.
Autres contacts
Direction du LISA
Maison des Sciences de l’Environnement 4ème étage
UPEC Campus Centre
61, avenue du Général de Gaulle
94010 CRETEIL CEDEX
contact@lisa.u-pec.fr / 01.45.17.15.60