It is important for the Government to be able to predict the future energy needs of UK industries, homes and transport to ensure sufficient supply. At the same time, the UK needs to plan to reduce energy use in order to meet climate change reduction targets. At the moment the UK Government uses an Energy Demand Model which makes future energy predictions based on estimates of economic growth, the price of fuel and the number of households there will be in the future. This technique for predicting future energy needs is deficient, because it fails to take account of the fact that household demand for goods and services is the major driver of the economic performance of industry, and that the way households spend today is likely to be very different in the future. My fellowship takes a 'whole systems' approach to understanding the UK's demand for energy. The link between household spends and industrial energy use can be determined by quantifying the total energy required in the supply chain of producing a product. It is also possible to capture the energy that is embedded in goods exported abroad and goods imported to the UK from other countries with very different energy efficiency standards in their factories. I will develop a new indicator of energy demand: 'the UK's Energy Footprint' which shows the full amount of energy associated with products bought by UK consumers between 2005 and 2015. I have met with the Department for Business, Energy and Industrial Strategy (BEIS) to ensure that this new indicator will be reported alongside the Carbon Footprint. Instead of simply looking at the changing goods and services bought by an average household, this fellowship will consider the differing expenditure profile of up to 60 different household types between 2005 and 2015. For this, I will use geodemographic expenditure profiles developed by CallCredit, a credit reference company. The main user of geodemographic data is the business sector understanding their consumers, so it is important that the data is current and constantly kept up-to-date. Producers of this type of data do not keep previous years' profiles as a readily available product. This means that their data has never been used to understand the changing geodemographic profile in the UK or elsewhere. I have made an agreement with CallCredit to exclusively acquire a decade's worth of expenditure data from their archive. This means that it will be possible for the first time to determine whether the energy needs of the UK have altered due to households buying different types of products or whether the change is due to the mix of households in the UK changing. I will use mathematical analyses to calculate the drivers of the change in UK energy demand. The research will be able to determine what effect the recession had on the energy demand of different households. I will then focus on using predictions of the changing household types and predictions on how lifestyles may change in the future to estimate what the UK's demand for energy will be in 2030. There is uncertainty as to how the UK's infrastructure might have to change in order to cope with an aging population or the trend for homeworking. This fellowship will address this by determining the energy requirements of these futures by forming scenarios which calculate the UK's energy needs when there are greater proportions of these types of household present in the UK's demography. Outputs from this research will also be used to verify the BEIS's future energy demand scenarios and provide new inputs to their Energy Demand Model. This work therefore has great importance in ensuring the UK can meet the energy needs of its businesses and people, and become more sustainable, now and in the future.

If the significant numbers of dwellings with solid masonry walls (SMWs) are to be insulated, there will have to be a paradigm shift in the way that moisture risk is assessed. Methods must be developed to clearly demonstrate that insulation solutions are effective, robust and resilient to moisture even when considering the vagaries of our future climate and the way that people choose to live in their homes. This research will result in new methods and metrics, backed by rigorous scientific evidence, that enable moisture risk assessment of SMWs to be carried out routinely, new insulation materials to be developed and more homes to be insulated. Insulating the UKs existing housing stock will be an essential step in achieving greenhouse gas reduction targets and alleviating fuel poverty. The highest levels of heat loss occur in the c30% (8 million) homes that have SMWs. Insulating these walls offers significant potential for fuel savings but may cause moisture problems. Water accumulates within SMWs when it is raining outside or humid inside and diminishes with drier conditions. This water can pass from one face of the wall to the other as there is no cavity to act as a capillary break. Applying insulation to either the inside or outside face of the wall changes the temperature of the masonry, the rate of wetting and drying at each face and the locations where water vapour might condense and accumulate. This moisture can lead to mould growth, interstitial condensation and freeze thaw damage. These problems can cause severe damage, are expensive to repair and can affect the health of occupants. Current guidance in the UK Building Regulations (approved document C) and related standards is not adequate for assessing moisture risk when insulating SMWs. The simplified steady-state vapour diffusion model is not appropriate because dynamic liquid moisture conduction is the dominant moisture transport mechanism when SMWs are exposed to rainfall. There is a distinct lack of guidance on how to use more advanced transient heat and moisture simulation software, what inputs should be used for the boundary conditions and how the results translate into moisture risk. Straightforward design principles, based on many years of practical experience and research, have led to contradictory advice e.g. there is no clear consensus on how permeable the insulation material should be to water vapour. Thus only a small handful of hygrothermal experts might ever attempt a quantitative risk assessment for insulating SMWs and fewer SMWs are being insulated as a result. This research project will address these problems. Firstly, a framework will be developed for using advanced heat and moisture simulation software to carry out moisture risk assessment. This will include guidance on the boundary conditions to be used at the inside of the wall, and outside especially for wind driven rain exposure. It will also identify appropriate criteria to minimise risk from moisture accumulation within the wall, mould growth at the indoor surface and freeze/thaw at the outside surface. A number of insulation materials will be compared to understand which can best reduce the risk of moisture damage when insulating SMWs. Secondly, probabilistic modelling methods will be used to understand how robust different insulation solutions are to moisture damage given that there is considerable uncertainty in boundary conditions and material properties. Thirdly, new approaches to moisture risk assessment will be explored. A 'moisture safety factor' might describe how resilient an insulated SMW is to extreme events such as flooding. It may be possible to develop a completely new laboratory test for assessing insulation solutions. The underlying strength of this research comes from the collection high quality primary data, in the new state-of-the-art Hygrothermal Test Facility, for validating the results from the models.