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Versailles Saint-Quentin-en-Yvelines University
Country: France
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43 Projects, page 1 of 9
  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 101053033
    Overall Budget: 2,412,600 EURFunder Contribution: 2,412,600 EUR
    Partners: UVSQ

    Among the thousands of extrasolar planets discovered, Earth-like objects focus our attention to seek new habitable worlds. Eleven Earth-sized planets have already been discovered in the Habitable Zone (HZ) of their host-star, including three in the TRAPPIST-1 planetary system. Deciphering their atmospheres is the challenge of the next decade in exoplanetary science, stressing out urgent needs in fundamental data for these objects. My aim is to investigate how the atmospheric organic reservoir forms and evolves in the frame of humid exoplanetary atmospheres in Habitable Zone. I will also quantify the impact of theses processes on the climate and on the potential for prebiotic chemistry on these planets. I propose to consider the role of organic aerosols as prebio-signature: those are nanoparticles chemically produced in the atmosphere. I will address the capacity of exo-Earths atmospheres to produce organic aerosols in various oxidative conditions, and their further physical and chemical interactions with atmospheric water. To tackle these questions, I will combine experiments and models to discover the reactivity that occurs in atmospheres within an extensive range of oxidation conditions. I will experimentally determine the physical properties of the aerosols, and then model their radiative impact and their propensity to generate clouds in the atmosphere. I will also experimentally identify the prebiotic molecules composing the aerosols that dissolve into clouds. This transfer from the dry organic reservoir towards liquid water is indeed critical for the emergence of life. The ERC-AdG Oxyplanets project will contribute to interpret and suggest observations for the future NASA-JWST and ESA-ARIEL space missions. Furthermore, it will reinforce our knowledge of the habitability of Earth-like exo-worlds, potentially reappraising the conditions for life to appear on the early-Earth.

  • Funder: EC Project Code: 628735
    Partners: UVSQ
  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 834169
    Overall Budget: 184,708 EURFunder Contribution: 184,708 EUR
    Partners: UVSQ

    Soil organic matter is the largest land carbon (C) pool, vulnerable to land-use change and climate change. Soil C models are used to assess current organic C stocks and make predictions under future conditions. These models are typically developed to make predictions over centennial timescales. Given the ‘4 per mil’ initiative, there is now a critical need for annual-to-decadal soil C stock predictions to evaluate land management decisions and hold participants accountable to stated goals. The project proposes a new soil model framework to make predictions at annual-to-decadal timescales by developing a Bayesian forecasting model from a deterministic soil carbon model with the capacity to ingest multiple data types, propagate uncertainty from data and parameters into predictions, and update predictions when new data become available. The main focus is probabilistic prediction of soil C changes under land use and climate change for the next two decades. Specifically, the project plans build a forecasting model version of the Millennial model, recently developed by the researcher with University colleagues. The Millennial model is an evolution of the commonly used soil C model Century – also incorporated in the global land surface model (ORCHIDEE) of the host institution (LSCE) - but in contrast to Century, Millennial includes soil pools that correspond directly to measurements. First, we will develop the Bayesian calibration of modeled temperature response against warming experiment data, using the Millennial model to integrate measurements from the multi-national, collaborative whole-soil warming experiments FORHOT and BBSFA. Then, we will develop the Bayesian calibration of the modeled land management response against field data with different amounts and quality of added litter. We will then incorporate this new model into ORCHIDEE to predict soil C storage for near term land-based mitigation objectives of the Paris Climate Agreement.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 891576
    Overall Budget: 257,620 EURFunder Contribution: 257,620 EUR
    Partners: UVSQ

    Soil is both the largest sink and source of organic carbon (C) exchanged with the atmosphere. These exchanges result from biological processes, the primary source being the decomposition of soil organic matter (SOM), which is controlled by physical factors such as climate. As such, soil C emissions are very vulnerable to climate change but can also be reduced with new land management practices if we can predict the outcomes of soil carbon-climate feedbacks. However, predictions from the existing large-scale soil C models strongly diverge, and reveal large uncertainties in the processes and controls at play. One of these uncertainties is the effect of change in precipitation regimes on SOM decomposition mediated by soil microorganisms. Functions describing the decomposition response of soil carbon to soil moisture are static in current large-scale models, yet recent empirical studies show that decay responses under new soil moisture conditions can change due to shifts in microbial communities. Recent evidence suggests that evolution is a key processes driving these shifts in microbial communities. This project proposes to integrate variable decomposition-moisture functions into a large-scale soil C model to reflect precipitation history and carbon substrate influence on microbial responses to changing soil moisture. These functions will be calculated from a mechanistic microbial model that accounts for both ecological and evolutionary processes. The mechanistic model will be an updated version of the trait-based model DEMENT developed by the fellow’s supervisor at the partner institution (UC Irvine). The moisture response functions will be integrated into a commonly used soil carbon model, RothC, that has been incorporated into the global land surface model (ORCHIDEE) of the host institution (LSCE).

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 101055305
    Overall Budget: 2,485,310 EURFunder Contribution: 2,485,310 EUR
    Partners: UVSQ

    The main objective of the PREFER project is to open the scientific debate on existential risk to empirical enquiry. The PREFER team will identify how lay ethics (the ethics of ordinary people) manifest themselves in non-Western communities faced with extreme threat. Local terminal risks due to the collapse of regional ecosystems will serve as proxies for existential risks. Thus, this pioneering project will obtain, for the first time, empirical evidence on how ordinary humans evaluate and cope with real-life terminal situations. Existential risks concern humanity as a whole: it is essential to add to the variety and number of voices heard in scientific deliberations. A broader discourse on existential risk will contribute to better governance and decision-making around existential risks. The PREFER team will conduct field work in two diverse geographical areas whose inhabitants are experiencing the collapse of life-sustaining ecosystems: the Arctic and the Mekong Delta. Three communities in each area will serve as case studies. Preparatory fieldwork has revealed that members are aware of the terminal threat and have expressed fears that they are facing the end of the life they know. Community transdisciplinary research (the co-production of knowledge with and for local communities) will be accompanied by ethnographic work. Data will be collected in the form of narratives which will be analyzed as sources of information on how local communities appraise the multiple dimensions of local terminal risk, including descriptions, the meanings drawn from these and involvement in impact mitigation actions. These results will then be applied to existential risks, all the while analyzing the appositeness of the PREFER proxy-based approach. Finally, although the main focus is on widening the discourse on existential risks, PREFER will also contribute to the urgent empirical analysis of terminality in the face of collapsing regional ecosystems.