To minimize the risk of dangerous climate change associated with increasing concentrations of atmospheric greenhouse gases (GHG), as part of ongoing international efforts, the 2008 Climate Change Act requires that the UK reduces its GHG emissions by at least 80% by 2050, compared to 1990 levels. To support such legislation, methods must be developed to reduce uncertainty on existing national GHG emissions estimates and monitor the efficacy of emissions reduction strategies. In 2010, CO2 represented about 85% of total UK GHG emissions, with the remainder largely from methane (CH4) and nitrous oxide (N2O). In 2010, the main UK sources of CO2 were energy supply, road transport, business, and residential; the main sources of CH4 were agriculture and landfill with small sources from gas leakage and coal mines; and the main sources of N2O were agriculture, industrial process, and road transport. There are substantial associated uncertainties with sectoral estimates of these emissions, particularly for N2O. The main focus of Greenhouse gAs Uk and Global Emissions (GAUGE) is to quantify UK budgets of CO2, CH4, and N2O from different sectors, and to improve global GHG budgets. The UK study will focus on fossil fuels and agriculture, the two largest sources of the three GHGs. We will achieve this by combining atmospheric measurements with computer models of the atmosphere, which describe the movement of GHGs after emission. We already have a reasonable idea of where GHGs are emitted but the size of the emissions typically has a large associated error. Depending on the emission type it may also have a substantial seasonal cycle (e.g., agriculture). It is therefore important we make regular GHG measurements at different times of the year and in different places. The UK research aircraft will provide the broad-scale 3-D perspective on the inflow and outflow of UK GHG budgets, complementing information from existing tall towers. The network of tall towers measure GHGs at 100-200m above the surface to ensure that the sampled air is representative of larger areas, and the towers are intentionally sited to provide estimates of GHG emissions in the Devolved Administrations. As part of GAUGE we will add to this network with a tower in the Scottish borders that provides substantially more information about the north of England, Scotland, and the North Sea; a tower over SE England, downwind of London; and we will support existing instruments on the BT tower in central London. The SE London tower and the BT tower together will allow us to provide the first multi-year record of urban emissions from a megacity. We will use GHG isotopes to improve understanding of the fossil fuel sources. A detailed study of agricultural GHG emissions will be conducted over East Anglia, allowing us to quantify the importance of this sector in the UK GHG budget. Weekly measurements aboard a North Sea ferry will provide constraints on UK GHG fluxes by regularly sampling transects of UK outflow. Satellite observations of GHGs offer a unique global perspective, linking UK emissions to the rest of the world, and we will work with NASA to develop and apply new observations to quantify global GHG budgets on a sub-UK spatial scale. Embedded in this long-term measurement strategy will be a measurement intensive to quantify London GHG emissions, where we will use the UK research aircraft to sample profiles of upwind/downwind air, validate dedicated satellite observations, and link urban measurements with downwind in situ and tall tower measurements. In GAUGE we bring together computer models of the atmosphere, and a team of world-leading modellers, in order to relate observed variations of GHGs to estimates of the underlying emissions. Statistical approaches will be used to find emissions that best agree with the measurements, taking account of model and data uncertainties. The main outcome from GAUGE will be robust GHG emission estimates from the UK and from the world.

The UK is planning to make massive investments in offshore wind farms which will result in several fleets of similar wind turbines being installed around the UK coastline. The economic case for these wind turbines assumes a very high technical availability, which means simply that the turbines have to be working and ready to generate electricity for nearly all of the time. Not achieving this availability could well result in large economic losses. Unfortunately there is relatively little operational experience of offshore systems on which to base the estimates used. The systems may turn out to behave in unexpected ways by failing earlier than expected, or by proving more difficult to maintain. Even well-known systems can behave differently when used in new environments, which is why reliability databases often indicate ranges of failure behaviour rather than single number estimates. Availability is difficult to model because, in addition to the unknown impact of different environments, there is often a period of adjustment in which operators and manufacturers adapt their processes and systems to the new situation, leading to the potential for availability growth. However, with a new fleet of turbines there is also an aging process as they all grow older together which could lead to lower availability. The economic case for offshore systems depends a lot on whether high enough availability can be achieved, particularly in the early years of operation which are important for paying back the investment costs. This project looks at the degree of uncertainty there is in availability estimates for offshore wind turbines. This uncertainty is not one that averages out when there are a large number of turbines, because it has a systematic affect across all the turbines in a wind farm and therefore leads to corresponding uncertainty in the overall availability across the wind farm. This type of uncertainty is often called state-of-knowledge uncertainty and only gets reduced by collecting data over the longer term. Even if we are not yet able to collect operational data, we can still gain an understanding of the sources of state-of-knowledge uncertainty. Mathematical models can help us understand how different sources of uncertainty affect the uncertainty about availability, and to find out which ones we should be most concerned about. That, in turn, will help researchers to focus their energies on resolving the issues that ultimately have the biggest impact.In this project, operations researchers will work together with engineers and other researchers in the renewables sector, in order to build credible mathematical models to help answer these questions. Doing that requires the development of new mathematics, particularly in the way we represent how uncertainties are affected by different environmental and engineering aspects. It requires us to find better ways of getting information from experts into a form that we can use in the mathematical models, and it also requires us to find new ways of running the models on a computer.

Nitrogen compounds are essential for life. They are needed to make many biological compounds including proteins, amino acids, DNA and ATP (the 'fuel source' of cells), without which no living organism could survive. Nitrogen is particularly important because it often limits food production, while high levels of N compounds in the environment lead to serious pollution problems. By supplying N fertilizers, farmers greatly improve their yields. This has been essential to feed the growing world population over the last century, with N fertilizers estimated to sustain ~3.5 billion people, almost half of humanity. While the increased manufacture and mobilization of reactive N sources can be seen as a great feat of 'geoengineering', there have been many unintended consequences. A growing human population needs more food, so more fertilizers, especially as we now eat more animal products per person. The result is a complex web of pollution issues, threatening water, air and soil quality, altering climate balance and impacting on ecosystems and human health. In addition to the loss of N from farms, other sources cannot be forgotten. These include air emissions from burning, and losses to water from sewage systems. Overall, human alteration of the global N cycle makes for a multi-issue problem that ranks alongside climate change as one of the great challenges of the 21st century. The European Nitrogen Assessment has estimated that N pollution alone causes 70-320 billion Euro per year of damage across the EU (Nature, 14 April 2011,472,159). Given the wide diversity of nitrogen loss pathways into the environment, there are many potential solutions. In a recent report 'Our Nutrient World' led by CEH for the United Nations Environment Programme (UNEP, launched Feb 2013), 10 key actions were identified which would contribute to better nutrient management, simultaneously helping to meet food security goals while reducing the pollution of air, land and water, with multiple benefits for ecosystems, climate and human health. However, 'Our Nutrient World' also identified that there is currently no global international agreement that links the many benefits and threats of nitrogen. As a result, there is also no coordinated scientific assessment and support process to quantify and demonstrate these linkages. This gap is now being addressed by the International Opportunities Fund (IOF) of the NERC through its support for a new endeavour "Pump priming to towards the International Nitrogen Management System" - or 'INMSpp' for short. The central idea is that a scientific support system is needed that can provide the evidence needed to show how joined-up management of the global nitrogen cycle will deliver multiple benefits, and to be able to evaluate options that policy makers may wish to consider. Already there is a developing ambition for INMS as reflected by the invitation from the UN Global Environment Facility (GEF) for the NERC Centre for Ecology and Hydrology (CEH) to work with UNEP to develop a concept to establish a future INMS approach. Ultimately this would be a major endeavour, linking indicators, models and datasets to allow evaluation of possible international agreements. The INMS pump priming project provides a key step towards this eventual goal. As one of the key challenges to establish model chains from source to impact to mitigation and adaptation the INMSpp project has taken on the task of working out how integrated global modelling of the nitrogen cycle should be developed. The project will bring together a global consortium to examine how models can be joined up to demonstrate the net benefits of better nitrogen management. This will be a key resource as the INMS approach is developed. The outcome is the prospect to show how linking up different international environmental agreements can build common ground, simultaneously supporting food and energy security and a cleaner environment.

The importance and urgency of reducing carbon dioxide emissions has received much publicity. Electricity generation is responsible for 38% of carbon emissions world wide. Of all sources of global warming electricity generation is probably, technologically, the most easily replaced by carbon free sources. Electricity from sunlight using the photo-voltaic effect, which we will refer to as solar PV, was very much a niche application as little as 15 years ago. However in the last decade silicon solar PV technology has developed with astonishing speed so that today it is the cheapest form of electricity generation in most countries within 45 degrees of the equator. Equally importantly the cost of manufacture is decreasing by 24% for each doubling of production volume, much faster than most products. At the moment Solar PV provides only 2.6% of the world's electricity (in kWh) although a higher percentage in some countries (eg 7.9% in Germany, 5.4% in India). There are a number of factors which delay the take up of this technology. The biggest difficulty is intermittency in countries like the UK where peak load does not match peak solar output necessitating pumped storage hydro or other rapid start up generation which adds to the cost. In tropical and sub-tropical countries solar generation matches the load much better and it is these countries in which electricity demand is increasing most rapidly. However in general there is a reluctance to invest in Solar which in part is due to Solar being regarded as an unproven technology and questions regarding long term reliability of a capital intensive system with a costing based on a projected life of >25 years. It is well known that silicon solar cells degrade. There are two commercially important mechanisms. One is due to a reaction involving boron and oxygen which happens very quickly reducing the efficiency by ~2% in the first 24 hours of operation. This is well enough understood for specialists to be on the way to developing ways of minimising the effect and demonstrating stability. The other mechanism is called "light and elevated temperature degradation" (LeTID). It takes months or sometimes years to produce a degradation of between 2 and 5%. The higher the light intensity and the higher the temperature the faster the degradation although there are large variations between different materials and solar cell designs which are not at all understood despite much behavioural data. The aims of this project are to develop a fundamental understanding of the degradation mechanism, to test proposed methodologies for reducing or eliminating LeTID and to use our understanding of the degradation mechanisms involved to develop meaningful accelerated life tests. Experimental work will be done in Manchester using test devices fabricated by us in Manchester and by the University of New South Wales (Australia). The prime techniques used will be optical, chemical and electrical measurements in Manchester and the Australian National University (Canberra) supported by modelling work at the University of Aveiro (Portugal). These will include lifetime spectroscopy, Deep Level Transient Spectroscopy and variants, admittance spectroscopy, low temperature photo-luminescence, time resolved photo-luminescence, Raman spectroscopy, hydrogen measurements and Secondary Ion Mass Spectroscopy. Materials and devices samples will be supplied by two manufactures active in the silicon solar field.