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.

This world-leading Centre for Doctoral Training in Bioenergy will focus on delivering the people to realise the potential of biomass to provide secure, affordable and sustainable low carbon energy in the UK and internationally. Sustainably-sourced bioenergy has the potential to make a major contribution to low carbon pathways in the UK and globally, contributing to the UK's goal of reducing its greenhouse gas emissions by 80% by 2050 and the international mitigation target of a maximum 2 degrees Celsius temperature rise. Bioenergy can make a significant contribution to all three energy sectors: electricity, heat and transport, but faces challenges concerning technical performance, cost effectiveness, ensuring that it is sustainably produced and does not adversely impact food security and biodiversity. Bioenergy can also contribute to social and economic development in developing countries, by providing access to modern energy services and creating job opportunities both directly and in the broader economy. Many of the challenges associated with realising the potential of bioenergy have engineering and physical sciences at their core, but transcend traditional discipline boundaries within and beyond engineering. This requires an effective whole systems research training response and given the depth and breadth of the bioenergy challenge, only a CDT will deliver the necessary level of integration. Thus, the graduates from the CDT in Bioenergy will be equipped with the tools and skills to make intelligent and informed, responsible choices about the implementation of bioenergy, and the growing range of social and economic concerns. There is projected to be a large absorptive capacity for trained individuals in bioenergy, far exceeding current supply. A recent report concerning UK job creation in bioenergy sectors concluded that there "may be somewhere in the region of 35-50,000 UK jobs in bioenergy by 2020" (NNFCC report for DECC, 2012). This concerned job creation in electricity production, heat, and anaerobic digestion (AD) applications of biomass. The majority of jobs are expected to be technical, primarily in the engineering and construction sectors during the building and operation of new bioenergy facilities. To help develop and realise the potential of this sector, the CDT will build strategically on our research foundation to deliver world-class doctoral training, based around key areas: [1] Feedstocks, pre-processing and safety; [2] Conversion; [3] Utilisation, emissions and impact; [4] Sustainability and Whole systems. Theme 1 will link feedstocks to conversion options, and Themes 2 and 3 include the core underpinning science and engineering research, together with innovation and application. Theme 4 will underpin this with a thorough understanding of the whole energy system including sustainability, social, economic public and political issues, drawing on world-leading research centres at Leeds. The unique training provision proposed, together with the multidisciplinary supervisory team will ensure that students are equipped to become future leaders, and responsible innovators in the bioenergy sector.

Solar power is by far the most abundant renewable energy source. However, at present its use is limited by the high cost of solar cells, so that we continue to obtain most of our power from fossil fuels. Polymer (plastic) solar cells are an exciting research field that aims to address this problem, as polymer solar cells could be made by simple manufacturing processes such as roll to roll coating. The result would be much lower cost solar cells, with much lower energy of production. Most research to date has focussed on the efficiency of such solar cells, and good progress has been made, leading to efficiencies approximately two thirds of commercial amorphous silicon solar cells.In this proposal we address the most important remaining issue, namely understanding and enhancing the lifetime of polymer solar cells. To do this we will combine advanced photophysical, morphological and chemical analysis of solar cells before, during and after operation to gain new insight into the factors controlling degradation of such cells. This will provide a solid foundation for developing strategies for extending the solar cell lifetime in the later part of the project.The operation of polymer solar cells depends critically on the nanometre scale arrangement of the materials, so we will use sophisticated electron tomography techniques to study the nanoscale morphology and how it changes with device operation. This will be complemented by optical and electronic measurements performed in-situ on operating solar cells. A further innovation will be to make nanoscale perforation of an encapsulation layer and combine it with electron beam techniques to study local degradation with nanometre resolution. This challenging programme requires collaboration between world-leading research groups in St Andrews, Changchun, and Glasgow to access the range of expertise and facilities to make major progress, and will lead to a new UK-China collaboration.

In order to mitigate the effects of climate change, governments, private companies and individual citizens are taking action to reduce emissions of greenhouse gases (GHGs). Our project will provide new information that can be used to better evaluate the change in emissions that result from these actions. We will help the UK government track the effectiveness of emissions reductions policies that have been implemented to meet the targets laid out in the Climate Change Act (2008), which mandates that GHG emissions are reduced by 80% below 1990 levels by 2050. The UK has played a major part in recent scientific and technological advances in emissions reporting and evaluation. Its GHG emission inventory, which is compiled based on data relating to human activities and rates of emission from each activity, is world-leading. Furthermore, the UK is one of only two countries that regularly submits a second estimate of emissions, those derived from atmospheric measurements, as part of its annual United Nations Framework Convention on Climate Change (UNFCCC) submission. This second "top-down" estimate can be used to assess where uncertainties lie in the inventory and where further development is needed. However, limitations exist in our scientific knowledge and in our technical capabilities that prevent the UK, or any other country, from further improving its emissions reports through the incorporation of atmospheric data. Through the NERC Greenhouse Gas & Emissions Feedback programme, which ended in 2017, we demonstrated the ability to quantify the UK's net national GHG fluxes using atmospheric observations. However, we have not yet been able to separately estimate fossil fuel and biospheric carbon dioxide sources and sinks, or determine the major sectors driving changes in the UK's methane emissions. This proposal will develop new science to address these needs, and pave the way towards the next generation of GHG evaluation methodologies. Our work will span four key areas: 1) Improving models of emissions from individual source and sink sectors to determine when and where GHG emissions to the atmosphere occur from both natural and anthropogenic systems. 2) Utilising new surface and satellite atmospheric GHG observations, such as isotopic measurements of methane and carbon dioxide, and measurements of co-emitted or exchanged gases (oxygen, carbon monoxide, nitrogen dioxide and ethane) to provide information on emissions from different sectors. 3) Utilising enhanced model-data fusion methods for making use of these new observations and for better quantifying uncertainties. 4) Integrating data streams to determine the highest level of confidence in the UK's emissions estimate. To improve the transparency of national reports, scientists and policy makers have been strongly advocating for the combination of such methods in the reporting process. The UNFCCC, at its 2017 Conference of Parties, acknowledged the important role that emissions quantified through atmospheric observations could have in supporting inventory evaluation (SBSTA/2017/L.21). Through our close links to the inventory communities in the UK and around the world, the IPCC and to UK policy makers, we can ensure that our work will be used to update and improve the UK's GHG submission to the UNFCCC and will showcase methods of best-practice.