Poor air quality has become one of the main controllable public health problems in many areas, both in developing countries and industrial societies. Epidemiological studies suggest that the larger parts of air pollution chronic effects are likely to stem from Particulate Matter (PM). Most of these studies use PM mass concentration as the exposure metric and current regulation actions are also based on PM mass. However, much of the ambient particle mass consists of low toxicity components, whereas reactive trace species can be major contributors to PM toxicity. Mass may thus not be the best marker of the health impact of PM. However, there is currently no consensus regarding a possible alternative metric that would provide relevant information for health, and could be standardized and used in routine measurements. One key parameter that drives the PM toxicity is their carrying or inducing reactive oxygen species (ROS) in the lung, at the origin of biological effects by disrupting the lung natural redox balance. This new health metric is defined as the Oxidative Potential (OP) of PM. Since OP integrates processes related to particles size and surface properties together with their chemical composition, it is believed to give a “simple” integrative metric more representative of PM potential interactions with specific targets in the human body. GET OP, STAND OP overarching aim is to make significant progresses to validate or invalidate oxidative potential of PM as a relevant indicator of health impacts of PM exposure, as a step towards proposing it as metric for air quality regulation. To achieve this overall objective, the following program is being implemented. WP1: Towards a CTM-based source apportionment of OP over Europe. WP1 methodology relies first on extended time series of OP measurements including three complementary assays. PM10/2.5 samples will come from contrasted environments from many past and ongoing programs that include extensive chemical characterization (~ 4 500 samples). We will apply an OP apportionment method for all sites, combining positive matrix factorization and multi-dimensional analysis of OP. Then, we perform the implementation of OP as a prognostic variable in chemical transport model LOTOS-EUROS with the overall goal to get daily OP maps over Europe. WP1 will lead to a comprehensive “climatology” of OP for various environments, assessing quantitative links with PM chemistry and sources. Ranking sources of PM emissions as OP contributors is a key parameter for policy initiatives, as is the demonstration of the capability of a large scale chemical-transport model to predict OP. WP2: OP exposure in a medium-size town. WP2 will rely on a field campaign with both indoor and outdoor sampling for about 40 sites in the Grenoble area, in cold and warm seasons. We aim at recalculating a realistic average OP exposure for the whole population derived from personal OP and outdoor/indoor OP and to assess further spatial and temporal variations of OP in Grenoble. It is based on the Land-Use-Regression interpretation of OP measurements from indoor/outdoor campaigns and from the extended time-series of OP measurements from one background outdoor site of Grenoble. WP3: OP relevance for cohort’s health. OP is usually assessed on filters from ambient samples which are not representative of personal exposure. In the context of the SEPAGES mother-child cohort in Grenoble, women and their newborns have carried for 8 days in several occasions a personal active PM sampler to monitor their exposure. We will characterize the association between personal OP (from cohort’s filter) and the health of pregnant women adjusting for the relevant confounders using regression models. WP3 will give a proper evaluation of the hypothesis that OP’s could be better predictor than the mass for each of the health endpoint.

The future evolution of mountain glaciers is of major concern to the world scientific community and civil society. However, our knowledge on the evolution of glaciers is limited by the huge uncertainty affecting the future of high mountain precipitation and by the oversimplified representation of snow/ice albedo feedbacks in current glaciological modelling. The iFROG project aims at refining the glacier evolution scenario by addressing these bottlenecks. The project will be implemented following three specific actions (or work packages): - Action 1: To enhance observation of precipitation rates and the rain/snow transition at local and regional scales using remote sensing techniques at different time scales.This will offer a comprehensive dataset of observation data that will serve as a base in action 2. - Action 2: To better constrain atmospheric reanalyses (ERA5) using outputs of action 1 and to bias-correct and downscale Global Circulation Models outputs. These data sets will be used in action 3. - Action 3: To provide more realistic future glaciological projections including feedbacks of precipitation phase on albedo and accumulation variability, and impacts of future rain/snow transition height using physical surface mass balance models. The project focuses on three well-documented glaciers located in contrasting climatic zones. The iFROG project is highly multidisciplinary and will foster rich exchanges within IGE (Institut des Géosciences de l’environnement) and with Météo France researchers. The iFROG project will be highly beneficial for the international visibility of the PI (Fanny Brun). It will also have large impacts in the fields of glaciology, as refined surface mass balance models have not yet been used to simulate future glacier evolution.

The project INFRA-ATMO-2 is a follow-up of INFRA-ATMO with the aim of structuring a national consortia to successfully respond to INFRAIA-3-2020 call for Pilot for a new model of Integrating Activities to explore new ways to support the opening of national/regional/ European RIs and the provision of integrated RI services at EU level. National communities in several European countries are organized to respond to research requirements for access to information data for predicting the complex Earth system and it’s functioning. National Atmospheric Research infrastructures ACTRIS-FR (Aerosol, Clouds and Trace Gases Research Infrastructure, end of preparatory phase), ICOS-FR (Integrated Carbon Observing System), IAGOS-FR (In-service Aircraft for a Global Observing System), and the AERIS Data Center are key pillars of the European components of the corresponding RIs. They propose a coordinated response to INFRAIA-3-2020 addressing the need for cross-topic integration and aims at coordinating a joint European atmospheric monitoring infrastructure in response to the increasing complexity of required research on climate change and air quality.

Sea level rise has become a challenge facing society due particularly to the ice sheets that are contributing more significantly than previously anticipated. The mass loss of the ice sheets is due to increased surface melt runoff and outflow of ice associated with current climate warming. Here, we propose to improve our understanding of the dynamic component. Indeed, the ice discharge modulated by changes in ice velocity and thickness changes remains the largest uncertainty in the current and future contribution of the ice sheets to sea level rise. Quantifying and understanding the past/present/future contribution of the ice sheets to sea level rise under the current warming climate requires answering fundamental questions as: How has the ice velocity, thickness and so discharge of outlet glaciers changed on sub-annual to decadal time scales? What are the main and most important external forcing that are controlling changes in glacier ice discharge into the ocean? How can we use ice dynamic observations of the recent past to teach numerical ice flow model and get more precise projection of sea level rise? Until recently the answers to those questions were limited, mainly because the ice sheet observations were spatially incomplete and temporarily sparse, resulting in averaged products to maximize spatial coverage at the expense of temporal information. However, in the last few years, we entered a new era of spaceborne ice sheet observations with the launch of the ESA’s CryoSat-2 in 2010, USGS’ Landsat-8 in 2013 and ESA’s four Sentinel-1 & 2 between 2014 & 2016. Used in the synergistic manner, these satellites offer the first chance for sustained, continuous data acquisition over the ice sheets to map ice motion and elevation. Taking the opportunity offered by these new satellites, the SOSIce project will reconstruct at high temporal and spatial resolution the ice flow for the largest glaciers of Greenland and Antarctica to refine mass balance estimates and improve the forecasting skills of the numerical ice flow models. We have envisioned this work in 3 successive steps: derive time series of the (1) dynamical and geometrical structure of the glaciers from these new sensors, (2) assimilate them into the state-of-the-art ice flow model Elmer/Ice, and (3) disseminate our results using public data archive for the scientific community. By taking advantage of the continuous observations and by assimilating them in an model, we will follow the ice sheet evolution in a fundamentally new way compared to current approaches. Significant technical and scientific issues would be solved from the results of this project, including securing the capacity to process large quantities of data for ice sheet studies, better understanding of the underlying physical processes causing increased in glacier ice discharge, improving ice-sheet model initialization before computing projections, and precisely reassessing the sea-level budget. This project will set very good grounds to initiate an international, scientific collaborative effort to facilitate the growth and establishment of the novel and rapidly growing field of remote sensing of the cryosphere over large datasets.

The isotopic composition of seawater represents an important fingerprint of water masses, containing information about conditions during their formation and evolution. Following at high resolution its 3D spatial and temporal variability in the ocean would provide a direct link to the freshwater cycle, allowing to discriminate between different water sources, such as the one coming from glacier and sea ice melting, riverine freshwater and precipitations. Current knowledge of water isotopes in the ocean remains very poor due to scarcity of measurements obtained from discrete sampling. This project proposes to design and construct a new instrument relying on our recent patent able to provide water isotope mapping at very fine spatial and temporal resolution in the ocean. After validation, the instrument will further be employed for, e.g., field campaigns in the Austral Ocean, helping to better constrain ocean/ice-shelf interactions and ice melting processes, both so far poorly constrain.