ERC FUNDED PROJECTS

The global marine ecosystem is being deeply altered by human activity. On the one hand, rising concentrations of atmospheric greenhouse gases are changing the physical and chemical state of the ocean, exerting pressure from the bottom up. Meanwhile, the global fishery has provided large economic benefits, but in so doing has restructured ecosystems by removing most of the large animal biomass, a major top-down change. Although there has been a tremendous amount of research into isolated aspects of these impacts, the development of a holistic understanding of the full interactions between physics, chemistry, ecology and economic activity might appear impossible, given the myriad complexities. This proposal lays out a strategy to assemble a team of trans-disciplinary expertise, that will develop a unified, data-constrained, grid-based modeling framework to represent the most important interactions of the global human-ocean system. Building this framework requires solving a series of fundamental problems that currently hinder the development of the full model. If these problems can be solved, the resulting model will reveal novel emergent properties and open the doors to a range of previously unexplored questions of high impact across a range of disciplines. Key questions include the ways in which animals interact with oxygen minimum zones with implications for fisheries, the impacts fish harvesting may have on nutrient recycling, spatio-temporal interactions between managed and unmanaged fisheries, and fundamental questions about the relationships between fish price, fishing cost, and multiple markets in a changing world. Just as the first coupled ocean-atmosphere models revealed a wealth of new behaviours, the coupled human-ocean model proposed here has the potential to launch multiple new fields of enquiry. It is hoped that the novel approach will contribute to a paradigm shift that treats human activity as one component within the framework of the Earth System.

1 600 000 €

Start date: 2016-07-01, End date: 2021-06-30

This project aims at making a breakthrough contribution in the broad area of Control of Partial Differential Equations (PDE) and their numerical approximation methods by addressing key unsolved issues appearing systematically in real-life applications. To this end, we pursue three objectives: 1) to contribute with new key theoretical methods and results, 2) to develop the corresponding numerical tools, and 3) to build up new computational software, the DYCON-COMP computational platform, thereby bridging the gap to applications. The field of PDEs, together with numerical approximation and simulation methods and control theory, have evolved significantly in the last decades in a cross-fertilization process, to address the challenging demands of industrial and cross-disciplinary applications such as, for instance, the management of natural resources, meteorology, aeronautics, oil industry, biomedicine, human and animal collective behaviour, etc. Despite these efforts, some of the key issues still remain unsolved, either because of a lack of analytical understanding, of the absence of efficient numerical solvers, or of a combination of both. This project identifies and focuses on six key topics that play a central role in most of the processes arising in applications, but which are still poorly understood: control of parameter dependent problems; long time horizon control; control under constraints; inverse design of time-irreversible models; memory models and hybrid PDE/ODE models, and finite versus infinite-dimensional dynamical systems. These topics cannot be handled by superposing the state of the art in the various disciplines, due to the unexpected interactive phenomena that may emerge, for instance, in the fine numerical approximation of control problems. The coordinated and focused effort that we aim at developing is timely and much needed in order to solve these issues and bridge the gap from modelling to control, computer simulations and applications.

2 065 125 €

Start date: 2016-10-01, End date: 2021-09-30

The fight against climate change is among Europe’s top policy priorities. In this research agenda, I propose to push out the frontier in the area of Energy and Environmental Economics by carrying out policy-relevant research on a pressing issue: how to design optimal regulatory and market-based solutions to achieve a least cost transition towards a low-carbon economy. The European experience provides unique natural experiments with which to test some of the most contentious issues that arise in the context of electricity markets, including the potential to change households’ demand patterns through dynamic pricing, the scope of renewables to mitigate market power and depress wholesale market prices, and the design and performance of the auctions for renewable support. While there is a body of policy work on these issues, it generally does not meet the required research standards. In this research, I will rely on cutting-edge theoretical, empirical, and simulation tools to disentangle these topics, while providing key economic insights that are relevant beyond electricity markets. On the theory front, I propose to develop new models that incorporate the intermittency of renewables to characterize optimal bidding as a key, broadly omitted ingredient in previous analysis. In turn, these models will provide a rigorous structure for the empirical and simulation analysis, which will rely both on traditional econometrics for casual inference as well as on state-of-the-art machine learning methods to construct counterfactual scenarios for policy analysis. While my focus is on energy and environmental issues, my research will also provide methodological contributions for other areas - particularly those related to policy design and policy evaluation. The conclusions of this research should prove valuable for academics, as well as to policy makers to assess the impact of environmental and energy policies and redefine them where necessary.

1 422 375 €

Start date: 2018-09-01, End date: 2023-08-31

Soil dust aerosols are mixtures of different minerals, whose relative abundances, particle size distribution (PSD), shape, surface topography and mixing state influence their effect upon climate. However, Earth System Models typically assume that dust aerosols have a globally uniform composition, neglecting the known regional variations in the mineralogy of the sources. The goal of FRAGMENT is to understand and constrain the global mineralogical composition of dust along with its effects upon climate. The representation of the global dust mineralogy is hindered by our limited knowledge of the global soil mineral content and our incomplete understanding of the emitted dust PSD in terms of its constituent minerals that results from the fragmentation of soil aggregates during wind erosion. The emitted PSD affects the duration of particle transport and thus each mineral’s global distribution, along with its specific effect upon climate. Coincident observations of the emitted dust and soil PSD are scarce and do not characterize the mineralogy. In addition, the existing theoretical paradigms disagree fundamentally on multiple aspects. We will contribute new fundamental understanding of the size-resolved mineralogy of dust at emission and its relationship with the parent soil, based on an unprecedented ensemble of measurement campaigns that have been designed to thoroughly test our theoretical hypotheses. To improve knowledge of the global soil mineral content, we will evaluate and use available remote hyperspectral imaging, which is unprecedented in the context of dust modelling. Our new methods will anticipate the coming innovation of retrieving soil mineralogy through high-quality spaceborne hyperspectral measurements. Finally, we will generate integrated and quantitative knowledge of the role of dust mineralogy in dust-radiation, dust-chemistry and dust-cloud interactions based on modeling experiments constrained with our theoretical innovations and field measurements.

2 000 000 €

Start date: 2018-10-01, End date: 2023-09-30