ERC FUNDED PROJECTS

Droughts cause agricultural loss, forest mortality and drinking water scarcity. Their predicted increase in recurrence and intensity poses serious threats to future global food security. Several historically unprecedented droughts have already occurred over the last decade in Europe, Australia and the USA. The cost of the ongoing Californian drought is estimated to be about US$3 billion. Still today, the knowledge of how droughts start and evolve remains limited, and so does the understanding of how climate change may affect them. Positive feedbacks from land have been suggested as critical for the occurrence of recent droughts: as rainfall deficits dry out soil and vegetation, the evaporation of land water is reduced, then the local air becomes too dry to yield rainfall, which further enhances drought conditions. Importantly, this is not just a 'local' feedback, as remote regions may rely on evaporated water transported by winds from the drought-affected region. Following this rationale, droughts self-propagate and self-intensify. However, a global capacity to observe these processes is lacking. Furthermore, climate and forecast models are immature when it comes to representing the influences of land on rainfall. Do climate models underestimate this land feedback? If so, future drought aggravation will be greater than currently expected. At the moment, this remains largely speculative, given the limited number of studies of these processes. I propose to use novel in situ and satellite records of soil moisture, evaporation and precipitation, in combination with new mechanistic models that can map water vapour trajectories and explore multi-dimensional feedbacks. DRY-2-DRY will not only advance our fundamental knowledge of the mechanisms triggering droughts, it will also provide independent evidence of the extent to which managing land cover can help 'dampen' drought events, and enable progress towards more accurate short-term and long-term drought forecasts.

1 465 000 €

Start date: 2017-02-01, End date: 2022-01-31

The future consolidation or erosion of western democracies depends on the political perceptions, experiences and participation of ordinary citizens. Even when they disagree on the implications of their findings, previous studies stress that both attitudinal and behavioural forms of democratic linkages – political trust, political support, loyalty, formal and informal participation – have come under considerable pressure in recent decades. The QUALIDEM project offers a qualitative (re)appraisal of citizens’ (dis-)affection towards politics by relying on the core argument of the policy feedback literature: attitudes and behaviours are outcomes of past policy. It aims to explain the evolutions of democratic linkages as being shaped by public policy, and specifically by the turn to neoliberalism and supranationalisation. It aims to systematically analyse the domestic and socially differentiated effects of both of these major macro transformations to citizens’ representations and experiences of politics, as an addition to the existing emphasis on individual determinants and the existing contextual explanations of disengagement and disaffection towards politics. On the theoretical level, this project therefore aims to build bridges between scholars of public policy and students of mass politics. On the empirical level, QUALIDEM relies on the reanalysis of qualitative data – interviews and focus groups – from a diachronic and comparative perspective focusing on four Western European countries (Belgium, France, Germany and the UK) with the US serving as a counterpoint. It will renew the methodological approach to the question of ordinary citizens’ disengagement and disaffection by providing a detailed and empirically-grounded understanding of the mechanisms of production and change in democratic linkages. It will develop an innovative methodological infrastructure for the storage of and access to twenty years of qualitative European comparative surveys.

1 491 659 €

Start date: 2017-04-01, End date: 2022-03-31

Due to the presence of a rigid cell wall, plant cells are fixed within their tissue context and cannot move relative to each other during development. Plants thus need to rely on directed cell elongation and cell division to generate a full three-dimensional (3D) structure. Controlling cell division orientations relative to the tissue axis is therefore the fundamental basis for 3D growth. In the root, plant cells are organised in cell files and undergo two main types of cell division to allow directional growth: anticlinal cell divisions (AD, adding cells within a cell file) and periclinal cell divisions (PD, creating new cell files, organs and tissues). Understanding the mechanisms that control cell division orientation is a key question in developmental biology and the main focus of this application. PDs are challenging to study as they only occur sporadically and typically in the most inner tissues of the root. I recently constructed a powerful system to induce strong, fast and homogenous PDs in any tissue type. I therefore now have the perfect tool at hands to tackle the fundamental question of how plants control the orientation of its cell divisions by: 1. Understanding the cellular events that occur prior to PD using a set of complementary techniques. 2. Identifying novel downstream components that translate the known genetic triggers for PD into changes in cell division orientation by performing an unbiased genetic screen. 3. Determining the developmental specificity and convergence of the known genetic pathways capable of inducing PD through studying their transcriptional targets in an ectopic tissue context. 4. Establishing a cell-culture based system for genetic and high throughput chemical perturbation studies of cell division orientation. I thus aim to perform a global and comprehensive study of cell division orientation, a process crucial for 3D growth in general and vascular development in specific.

1 499 938 €

Start date: 2017-02-01, End date: 2022-01-31

Combustion science will play a major role in the future quest for sustainable, secure and environmentally friendly energy sources. Two thirds of the world energy supply rely on combustion of fossil and alternative fuels, and all scenarios forecast an increasing absolute energy supply through combustion, with an increasing share of renewables. Thus, combustion will remain the major actor in transportation and power generation as well as in manufacturing processes, like steel and glass. Nevertheless, combustion science will need profound innovation to meet future energy challenges, such as energy efficiency and fuel flexibility, and ensure future generations with affordable and sustainable energy and healthy environment. In this context, MILD combustion represents a very attractive solution for its fuel flexibility and capability to deliver very high combustion efficiency with virtually zero pollutant emissions. Such a combustion regime is the result of a very strong interaction between turbulent mixing and chemical kinetics. The fundamental mechanism of this interaction is not fully understood, thus justifying the need for experimental and numerical investigations. The overall objective of the present research proposal is to drive the development of modern and efficient combustion technologies, by means of experimental, theoretical, and numerical simulation approaches. New-generation simulation tools for MILD combustion will be developed, to reduce the dependence on sub-grid models and increase the fidelity of numerical simulations. High-fidelity experimental data will be collected on quasi-industrial systems, to disclose the nature of the interactions between fluid dynamics, chemistry and pollutant formation processes in MILD combustion. Experiment and numerical simulations will be tied together by Validation and Uncertainty Quantification techniques, to allow the ground-breaking application of the developed approaches and promote innovation in the energy sector.

1 499 110 €

Start date: 2017-04-01, End date: 2022-03-31

Physics dictate that a flow device has to leave a wake or the signature of it producing sustentation forces, extracting energy, or simply moving through the medium; these flow structures can then impact negatively or favorably another device downstream. Wake turbulence between aircraft in air traffic and wake losses within wind farms are prime examples of this phenomenon, and incidentally constitute pivotal challenges to their respective fields of transportation and wind energy. These are highly complex and unsteady flows, and distributed control based on affordable wake models has failed to produce robust schemes that can alleviate turbulence effects and achieve efficiency at the scale of the system of devices. This project proposes an Artificial Intelligence and bio-inspired paradigm for the control of flow devices subjected to wake effects. To each flow device, we associate an intelligent agent that pursues given goals of efficiency or turbulence alleviation. Every one of these flow agents now relies on machine-learning tools to learn how to make the right decision when confronted with wake or turbulent flow structures. At a system level, we employ Multi-Agent System and Distributed Learning paradigms. Based on Game Theory, we build a system of interactions that incite the emergence of collaborative behaviors between the agents and achieve global optimized operation among the devices. We claim that the design of a system that learns how to control the flow, is simpler than the design of the control scheme and will yield a more robust scheme. The learning of formation flying among aircraft and of wake alleviation between wind turbines will constitute our study cases. The investigation will essentially be carried by means of large-scale numerical simulations; such simulations will produce the first ever realizations of self-organized systems in a turbulent flow. We will then apply our learning frameworks to a small-scale wind farm.

1 999 591 €

Start date: 2017-09-01, End date: 2022-08-31