The PRIMOFOOD project aims to innovate in modelling the effect of food prices on household purchasing behaviour. It is in line with axis 1.5 of the AAPG2019 "Food and Food Systems". The proposed innovations will allow for a better assessment of the effectiveness and distributive effects of nutritional taxation policies. The identification of price effects can be based either on the econometric analysis of existing market data or on the analysis of experimental data generated in lab. Econometric methods may have limited internal validity, while experimental methods have questionable external validity. Our project therefore proposes to address the respective weaknesses of these two methods and, beyond that, to exploit their complementarities. WP1 will develop innovative experimental analyses of price effects. First, using innovative protocols, we will analyze the effect of large price changes, similar to the levels used in micro-simulations of pricing policies, but much larger than the changes observed in market data. The objective is to identify possible salience and reference price effects, which can induce non-linearities and discontinuities in consumer reactions to prices. We will also test the potential complementarities between pricing policies and nutritional labelling of the NutriScore type. We will also study the effects of social norm, cognitive load, and the existence of opportunity costs. WP2 will develop a structural econometric model of quality and quantity demand under multiple constraints. Beyond the usual budget constraint, the model will include a nutritional intake constraint, with possible extension to multiple linear constraints. The objective is to reflect that the choices of some households are constrained by the need to ensure a minimum of energy intake, or for some potentially addictive goods (alcohol and sugar). This econometric modelling work poses various theoretical and practical challenges. The empirical work will use Kantar WorldPanel scanner data on the consumption of non-alcoholic drinks by French households, and will aim in particular to identify the existence of effects of sugar habituation. WP3 will aim to show the possibility of evaluating the ex-ante evaluation of pricing policies by a micro-simulation of taxation policies based on a model that integrates the outcomes of the two work packages. We will first cross-validate the experimental and econometric methods, comparing the econometric approach with the data generated in the experiments. This will allow us to identify opportunities to improve the specifications of the econometric model, an improvement that will be implemented by a Bayesian method. Finally, we will carry out micro-simulations based on the case of the taxation of sweetened drinks, which has been in place in France since 2012. This will allow us to better characterize the effectiveness of this tax, as well as its distributive and welfare impacts on the various socio-economic segments of the population. PRIMOFOOD provides methodological contributions to the scientific communities and to important public policy issues. The team includes researchers covering the spectrum of issues addressed, from fundamental methodological issues to public policy expertise. The project proposes an international approach, with the ambition of replicating part of the work on American data, with a view to comparing food systems. Finally, the project will produce tools to better understand the links between the long-term dynamics of price changes and the sustainability of food systems.

The question of sea-level upraise in relationship to East Antarctica Ice Sheet (EAIS) dynamics is a major question in the context of climate change. The presumed stability of the EAIS and thus of little impact from this zone for the Sea Level Rise (SLR) actually stands on little data on the coast, and on under-constrained numerical models. For now, these models, for the coming centuries, take little account of the long-term evolution of the ice sheet in the coastal domain, since the LGM (Last Glacial Maximum, 20 ka). These models are mainly based on satellital and on distal glacial (EPICA), or marine, data. However, the critical scale of processes acting on the ice sheet evolution (like the evolution of the grounding line or the isostatic rebound) stand on much longer temporal scales (from multi-centennial to multi-millennial scales), and are essentially acting along the coast. In this project, we propose to document the post-LGM deglaciation dynamics of Terre Adélie (TA), with both data from Solid Earth and marine compartments to bring stronger constraints and validations into numerical models of the EAIS on the last 20 ka. The validated models will be used in a forward mode to investigate the future behaviour of the the EAIS until 2300. -In the 'Solid Earth' investigation, we will apply a multi-geochronological investigation of moraine records (based on Cosmogenic Radionuclide dating of Be, Al, C and OSL (Optically Simulated Luminescence) of moraine boulders along the Terre Adélie coast to document the EAIS retreat following the LGM. OSL dating of marine sediments will allow to date former grounding lines that have been uplifted, which will allow quantify the (still undefined) isostatic rebound. - The new marine data will comprise the acquisition of new geochemical data on available sediment cores off the TA coast, at high resolution until 11.5 ka. These data will allow to recalculate the paleo-temperatures both at the sea surface and around -500 m (that is at the level of the grounding line of the EAIS in TA). These data will notably allow for the first time to document the MWP-1B warming phase, which will be used as a proxi of current climate change. - These Solid Earth and marine data will be combined with the other, more distal, ice sheet and marine records to provide a precise frame for glacial fluctuations and IAES thickness since 20 ka. These data will be used to further constrain and validate interactive 3D numerical modellings of the EAIS in TA to evaluate the regression of the glaciers in relation to the various forcings on a 20 ka scale. The best-fit models will be used in forward mode for evaluating the future response of EAIS until 2300.

The discovery of the mass-independent isotopic fractionations of sulfur and oxygen (S-MIF and O-MIF) has revolutionized the way fundamental geochemical questions are addressed and have produced one of the most iconic figures in geosciences, i.e. the presence of S-MIF in rocks older than 2.3 billion years and its sudden quasi disappearance thereafter. Regarding O-MIF, the majority of the anomalies observed on Earth originate from the ozone anomaly transferred to oxygen-bearing molecules. Although there are still uncertainties pertaining to the mechanisms of O-MIF transfers, they tend to pale into insignificance when compared to those on the exact processes creating S-MIF. There is now no general consensus on the origin of S-MIF in the atmosphere and all the proposed mechanisms are still highly debated in geosciences. Recently NASA has identified the resolution of the origin of S-MIF as one of the top priorities for its astrobiology program, recognizing the importance of MIF in solving the epic question of the origin of life and its interaction with the planetary environment. The identification and quantitative understanding of processes involved in creating and transferring MIF anomalies, a prerequisite for extracting the information embedded in isotopic data, would certainly lead to major advances in our comprehension of the geochemical and environmental evolution of our Earth, from its most primitive existence to the present day. In this project, we propose a multidisciplinary approach to re-examine the sources of MIF in sulfates using an integrated program of novel laboratory experiments, dedicated field studies and innovative multi-scale atmospheric photochemical modeling (including both O- and S-MIF as prognostic variables). First, using the successful isotopic methodology applied to sulfate from polar snow and ice core, we will assess the potential of sulfate leached from volcanic ash as tracers of atmospheric oxidation processes. Second, we plan to carry out a new set of chamber experiments on SO2-related production of S-MIF considering environmental conditions that are as close as possible to those of the stratosphere and of the presupposed Archean atmosphere. Third, for the first time, S-MIF and O-MIF isotope chemistry schemes will be coupled and implemented in models (i.e. a photochemical box/plume model and a global chemistry-transport model). As O-MIF has already largely demonstrated its capacity to probe sulfur oxidation mechanisms in the atmosphere, combining O-MIF and S-MIF analysis should represent a powerful approach to constrain better inferences on the origin of S-MIF. One of the aims is to improve our quantitative understanding of oxidation processes of volcanic and anthropogenic sulfur, and of the resulting production of aerosols. We will also assess the potential of this innovative approach for probing atmospheric chemistry in the distant past. Overall, by providing a much more robust basis for quantitative inferences from S-MIF and O-MIF data, the project will yield new constraints on fundamental questions regarding the late oxygenation of the atmosphere, the shift from an anaerobic to aerobic environment for life, and the reconstruction of the impact of volcanic eruptions and human activities on atmospheric oxidizing capacity and climate.

Understanding, modeling, forecasting and reconstructing fine-scale and large-scale processes and their interactions are among the key scientific challenges in ocean-atmosphere science. Artificial Intelligence (AI) technologies and models open new paradigms to address poorly-resolved or poorly-observed processes in ocean-atmosphere science from the in-depth exploration of available observation and simulation big data. In this context, this proposal aims to bridge the physical model-driven paradigm underlying ocean & atmosphere science and AI paradigms with a view to developing geophysically-sound learning-based and data-driven representations of geophysical flows accounting for their key features (e.g., chaos, extremes, high-dimensionality). We specifically address three key methodological questions: (i) How to learn physically-sound representations of geophysical flows? (ii) Which learning paradigms for the representation of geophysical extremes? (iii) how to learn computationally-efficient representations and algorithms for data assimilation?. Upper ocean dynamics will provide the scientifically-sound sandbox for evaluating and demonstrating the relevance of these learning-based paradigms to address model-to-observation and/or sampling gaps for the modeling, forecasting and reconstruction of imperfectly or unobserved geophysical random flows. To implement these objectives, we gather a transdisciplinary expertise in Numerical Methods (INRIA GRA & Rennes), Applied Statistics (IMT, LSCE), Artificial Intelligence (IMT, LIP6) and Ocean and Atmosphere Science (IGE, INRIA GRA, LOPS), complemented by the participation of two SMEs (Ocean Data Lab and Ocean Next) to anticipate the added value of AI technologies in future earth observation missions and coupled observation-simulation systems.

In the marine environment, macroplastic wastes undergo chemical and physical modifications leading to their fragmentation into microplastics (MPs) and nanoplastics (NPs). Additional MPs and potentially NPs enter the Oceans via rivers and atmospheric deposition. To date, the fate of ocean plastic debris is far to be understood and this is especially true when it comes to small MPs and NPs. Besides, the established presence of MPs in the atmospheric compartment, found in urbanized areas but also in remote locations, and the potential presence of NPs are of growing concern. These plastic particles can influence the Earth’s climate and degrade air quality. A transfer of plastic particles from the oceans to the atmosphere has recently been hypothesized. Literature strongly suggests this sea-to-air transfer of MPs/NPs processes similarly as for the generation of primary marine aerosols (sea spray aerosols) i.e., via the bursting of air bubbles plumes at the ocean’s surface. Nevertheless, the magnitude and significance of this phenomenon for both the marine and atmospheric compartments are still controversial. In this project, we hypothesize these marine MPs and NPs emissions are significant at the global scale and contribute to marine dispersal of MPs and NPs to remote ocean regions, and to terrestrial and cryospheric parts of the Earth system. We propose an innovative and complementary approach to address two objectives: 1. assess the water-to-air transfer of MPs and NPs particles and their co-contaminants via bubble bursting as a function of environmental parameters and plastic particle properties using laboratory experiments, 2. improve ocean and atmosphere models of MPs and NPs, and their coupling, to understand MPs/NPs transport and cycling.