Here, we propose the establishment of a large European and global collaboration to include national surveillance units from both within and outside the European Union. This collaboration will facilitate cooperation between neurologists, epidemiologists and neuropathologists 1) to harmonize the protocols involved in patient documentation, biomaterial sampling/ storage, biomarker testing/assay analysis and data sharing; and 2) to standardise a more precise diagnosis in patients with RPD by analysis of the biochemical markers in the cerebrospinal fluid and blood. We will work on standardisation of tests that are currently available and harmonise their use between centers worldwide. We will define standards for biochemically based diagnosis in most relevant rapid progressive dementia such as CJD and rpAD. As an add-on value, we will define criteria for early differential diagnosis between rapid progressive neurodegenerative or potentially reversible dementia.

Space weather describes the changing properties of near-Earth space, which influences the flow of electrical currents in this region, particularly within the ionosphere and magnetosphere. Space weather results from solar magnetic activity, which waxes and wanes over the Sunspot cycle of 11 years, due to eruptions of electrically charged material from the Sun's outer atmosphere. Particularly severe space weather can affect ground-based, electrically conducting infrastructures such as power transmission systems (National Grid), pipelines and railways. Ground based networks are at risk because rapidly changing electrical currents in space, driven by space weather, cause rapid geomagnetic field changes on the ground. These magnetic changes give rise to electric fields in the Earth that act as a 'battery' across conducting infrastructures. This 'battery' causes geomagnetically induced currents (GIC) to flow to or from the Earth, through conducting networks, instead of in the more resistive ground. These GIC upset the safe operation of transformers, risking damage and blackouts. GIC also cause enhanced corrosion in long metal pipeline networks and interfere with railway signalling systems. Severe space weather in March 1989 damaged power transformers in the UK and caused a long blackout across Quebec, Canada. The most extreme space weather event known - the 'Carrington Event' of 1859 - caused widespread failures and instabilities in telegraph networks, fires in telegraph offices and auroral displays to low latitudes. The likelihood of another such extreme event is estimated to be around 10% per decade. Severe space weather is therefore recognised in the UK government's National Risk Register as a one-in-two to one-in-twenty year event, for which industry and government needs to plan to mitigate the risk. Some studies have estimated the economic consequence of space weather and GIC to run to billions of dollars per day in the major advanced economies, through the prolonged loss of electrical power. There are mathematical models of how GIC are caused by space weather and where in the UK National Grid they may appear (there are no models of GIC flow in UK pipelines or railway networks). However these models are quite limited in what they can do and may therefore not provide a true picture of GIC risk in grounded systems, for example highlighting some locations as being at risk, when in fact any problems lie elsewhere. The electrical model that has been developed to represent GIC at transformer substations in the National Grid misses key features, such as a model of the 132kV transmission system of England and Wales, or any model for Northern Ireland. The conductivity of the subsurface of the UK is known only partly and in some areas not at all well. (We need to know the conductivity in order to compute the electric field that acts as the 'battery' for GIC.) The UK GIC models only 'now-cast', at best, and they have no forecast capability, even though this is a stated need of industry and government. We do not have tried and tested now-cast models, or even forecast models, of magnetic variations on the ground. This is because of our under-developed understanding of how currents flow in the ionosphere and magnetosphere, how these interconnect and how they relate to conditions in the solar wind. In this project we will therefore upgrade existing or create new models that relate GIC in power, pipe and railway networks to ionospheric, magnetospheric and solar wind conditions. These models will address the issues we have identified with the current generation of models and their capabilities and provide accurate data for industry and governments to assess our risk from space weather. In making progress on these issues we will also radically improve on our physical understanding of the way electrical currents and electromagnetic fields interact near and in the Earth and how they affect the important technologies we rely on.

Human activity has led to an increase in pCO2 and methane levels from pre-industrial times to today. While the former increase is primarily due to fossil fuel burning, the increase in methane concentrations is more complex, reflecting not only direct human activity but also feedback mechanisms in the climate system related to temperature and hydrology-induced changes in methane emissions. To unravel these complex relationships, scientists are increasingly interrogating ancient climate systems. Similarly, one of the major challenges in palaeoclimate research is understanding the role of methane biogeochemistry in governing the climate of ice-free, high-pCO2 greenhouse worlds, such as during the early Paleogene (around 50Ma). The lack of proxies for methane concentrations is problematic, as methane emissions from wetlands are governed by precipitation and temperature, such that they could act as important positive or negative feedbacks on climate. In fact, the only estimates for past methane levels (pCH4) arise from our climate-biogeochemistry simulations wherein GCMs have driven the Sheffield dynamic vegetation model, from which methane fluxes have been derived. These suggest that Paleogene pCH4 could have been almost 6x modern pre-industrial levels, and such values would have had a radiative forcing effect nearly equivalent to a doubling of pCO2, an impact that could have been particularly dramatic during time intervals when CO2 levels were already much higher than today's. Thus, an improved understanding of Paleogene pCH4 is crucial to understanding both how biogeochemical processes operate on a warmer Earth and understanding the climate of this important interval in Earth history. We propose to improve, expand and interrogate those model results using improved soil biogeochemistry algorithms, conducting model sensitivity experiments and comparing our results to proxy records for methane cycling in ancient wetlands. The former will provide a better, process-orientated understanding of biogenic trace gas emissions, particularly the emissions of CH4, NOx and N2O. The sensitivity experiments will focus on varying pCO2 levels and manipulation of atmospheric parameters that dictate cloud formation; together, these experiments will constrain the uncertainty in our trace greenhouse gas estimates. To qualitatively test these models, we will quantify lipid biomarkers and determine their carbon isotopic compositions to estimate the size of past methanogenic and methanotrophic populations, and compare them to modern mires and Holocene peat. The final component of our project will be the determination of how these elevated methane (and other trace gas) concentrations served as a positive feedback on global warming. In combination our work will test the hypothesis that elevated pCO2, continental temperatures and precipitation during the Eocene greenhouse caused increased wetland GHG emissions and atmospheric concentrations with a significant feedback on climate, missing from most modelling studies to date. This work is crucial to our understanding of greenhouse climates but such an integrated approach is not being conducted anywhere else in the world; here, it is being led by international experts in organic geochemistry, climate, vegetation and atmospheric modelling, and palaeobotany and coal petrology. It will represent a major step forward in our understanding of ancient biogeochemical cycles as well as their potential response to future global warming.