Fluid injection related to underground resources has become widespread, causing numerous cases of induced seismicity. If felt, induced seismicity has a negative effect on public perception and may jeopardise wellbore stability, which has led to the cancellation of several projects. Forecasting injection-induced earthquakes is a big challenge that must be overcome to deploy geo-energies to significantly reduce CO2 emissions and thus mitigate climate change and reduce related health issues. The basic conjecture is that, while initial (micro)seisms are caused by well-known mechanisms that could be predicted, subsequent activity is caused by harder to understand and, at present, unpredictable coupled thermo-hydro-mechanical-seismic (THMS) processes, which is the reason why available models fail to forecast induced seismicity. The objective of this project is to develop a novel methodology to predict and mitigate induced seismicity. We propose an interdisciplinary approach that integrates the THMS processes that occur in the subsurface as a result of fluid injection. The methodology, based on new analytical and numerical solutions, will concentrate on (1) understanding the processes that lead to induced seismicity by model testing of specific conjectures, (2) improving and extending subsurface characterization by using industrial fluid injection operations as a long-term continuous characterization methodology, so as to reduce prediction uncertainty, and (3) using the resulting understanding and site specific knowledge to predict and mitigate induced seismicity. Project developments will be tested and verified against fluid-induced seismicity at field sites that present diverse characteristics. Arguably, the successful development of this project will provide operators with concepts and tools to perform pressure management to reduce the risk of inducing seismicity to acceptable levels and thus, improve safety and reverse public perception on fluid injection activities.

Anthropogenic emissions of the toxic heavy metal mercury (Hg) threaten human health and ecosystems. The elemental form of emitted gaseous mercury, Hg(0), can be transported globally in the atmosphere due to its long lifetime of 4–6 months, but upon oxidation it forms soluble divalent mercury, Hg(II), which is rained out within days. However, there are many uncertainties associated with atmospheric Hg chemistry, leading to uncertain predictions of its fate and ecosystem impacts. Additionally, it is unknown how Hg cycling has been affected by recent, global change-induced trends in atmospheric oxidants (e.g., ozone and halogens). To address these knowledge gaps, the interdisciplinary SUMAC project will train the experienced researcher (ER) to integrate the latest knowledge from laboratory kinetics, computational and isotope chemistry, and field measurements into a global atmospheric Hg model, GEOS-Chem. By applying statistical methods from the field of global sensitivity analysis, the ER will identify the key chemical reaction rates that contribute the most to the uncertainty in the atmospheric Hg lifetime. Using Bayesian inference methods, the ER will develop constraints from field measurements for these reaction rates, establishing a new chemical mechanism for atmospheric Hg models. With the refined Hg chemical mechanism, the ER will conduct historical and future simulations to evaluate temporal trends in the Hg chemical lifetime and resultant impacts on Hg dispersion and deposition. By being the first study to quantify the influence of atmospheric chemistry on observed Hg trends, SUMAC will support the effectiveness evaluation of the Minamata Convention on Mercury, an international treaty aimed at reducing Hg emissions. Aside from the breakthrough research outcomes, SUMAC will strengthen the capacity of Hg modelling within Europe through the ER’s training activities, knowledge transfer to host institutions, open-access model development, and outreach.

Global biodiversity loss is disproportionately rapid on islands, which despite being hotspots of biodiversity, comprise ~ 80% of world’s species extinctions. The vulnerability of insular ecosystems to global change has been historically related to the introduction of invasive species. Yet, we still lack a quantitative understanding of how other major threats such as climate change will jeopardise, not only species, but pivotal ecosystem functions derived from trophic interactions such as animal-mediated seed dispersal. To date, the scarce data and methodological limitations have entailed a lack of studies on the effect of climate change on seed dispersal in entire island communities. ECORISC implies a major step ahead previous work with its integration of a new global dataset on ~65 insular seed-dispersal networks, alongside methodological approaches from the fields of interaction networks, ecological niche modelling and future climate change projections. The combination of empirical knowledge on the structure and vulnerability of current insular communities with future climate, species extinctions and interaction rewiring simulations will provide an integrated understanding of the resilience of seed dispersal in insular systems to climate change. The main outcome of ECORISC (i.e. the quantification of structural and functional consequences derived from climate-driven biodiversity loss) will provide essential knowledge needed to restore Europe’s ecosystems and biodiversity, one of the main issue mainstreamed in the first Horizon Europe strategic plan. During the course of this project, I will receive essential training by world leading experts of the fields of island ecology, niche modelling and complex systems at three outstanding institutes from the disciplines of Ecology and Physics, thus paving my way towards establishing an independent and distinct research profile in the fields of global change and community ecology.