Ian Hamilton is an Associate Professor at the UCL Energy Institute, University College London, UK. Ian’s research is focused on the nexus between energy supply-demand in buildings, indoor and urban environmental conditions, and health and climate change. Ian is the Principle Investigator for the IEA’s ‘Annex 70: Building energy epidemiology’ on energy and building stock data and modelling, drawing together researchers from 25 institutions across 12 countries. Ian is a co-investigator on the UK’s ‘Centre on Research for Energy Demand Solutions’, the UK-China Centre for Total Building Performance and the UK’s Health Protection Research Unit on ‘Healthy and Sustainable Cities under Climate Change’.
IAN HAMILTON
What does the transition towards lowcarbon building stock mean for Europe?
European building stock is responsible for around a third of CO2 emissions, and the EU has set a target of 20 % reduction by 2020 and 60 % by 2030, from a 1990 baseline. Meeting these targets means focusing on decarbonising the power supply and making concerted efforts to reduce energy demand through retrofits of existing stock.
Building energy epidemiology is the study of energy demands to improve our understanding of variations in the energy-consuming population, and their causes
Under the Energy performance of buildings Directive[1], Member States must outline specific actions to deliver these reductions across their building stock. For many, this means devising programmes that provide support and financial incentives to carry out energy performance audits and refurbishments. The question that must be addressed is: what policies and actions will deliver these results?
Policies are developed in a complex environment of crosscutting multi-objective and interacting issues, including the climate crisis, energy markets, development and building controls, and socioeconomic pressures. European building stock is not simple: a heterogeneous population of buildings in terms of design, construction, uses and users across a diverse political and climatic geography. The tools and systems necessary for such a large-scale assessment are lacking, as is a general understanding of the characteristics which affect energy performance.
What is energy building epidemiology and how can it help the energy efficiency of building stock?
To achieve such large-scale change, it makes sense to use existing methods, tools and practices for targeting and testing interventions among populations. One such field is epidemiology. Building energy epidemiology is the study of energy demands to improve our understanding of variations in the energy-consuming population, and their causes. It considers the complex interactions between physical and engineered systems, socio-economic and environmental conditions, and the individual practices of occupants.
Energy epidemiology provides an over-arching approach, where findings from large-scale studies inform energy policy, and provide the context for conventional smallscale studies and information for predictive models.
Building energy epidemiology is being taken up by many European researchers through Annex 70: Building energy epidemiology[2] under the International Energy Agency’s (IEA) technology collaboration partnership within Energy in buildings and communities. Annex 70 is an international collaboration of researchers, industry and government from across the globe who are working to develop methods to improve empirical evidence on energy demand in building stock
How can analyses of building stocks at scale help policymaking?
Being able to identify the spread and level of energy demand and performance across building stock reveals the scale of the challenge and offers a general ‘health check’. Being able to further determine the factors that influence energy performance, and devise and test retrofit treatment strategies based on a working knowledge of their real performance, is fundamental to meeting the targets.
In the UK, the use of a National energy efficiency data-framework has yielded considerable benefit for policymakers in evaluating the impact of retrofit programmes on energy use’
Developing a system for consistent data collection and review will help policymakers understand how building characteristics, and people’s behaviours and needs, drive energy use. This will help to improve the energy performance gap – the difference between models used to plan retrofits, and subsequent real-world measurements.
Such a system of information collection and analysis will also allow policymakers to better understand the intended and unintended consequences of their programmes. For example, a retrofit package will impact differently on households living with fuel poverty than those which are not.
Are there best practices in national building stock monitoring and how can we apply them more widely?
Routine data collection on energy efficiency retrofits is lacking across Europe. Many authorities report processes for changes made to buildings – e.g. land valuation and taxation, building controls, and energy performance certificates (EPCs) – but few have the data for population level, epidemiological studies. EPCs are helpful but there are issues with how these certificates are designed and implemented.
However, some initiatives are beginning to yield improved empirical analysis, helping to target and evaluate energy performance investments. EPC data are publicly available in some countries (UK, Ireland, Netherlands, Denmark, Sweden, Norway), providing a degree of transparency and a detection mechanism, though they still need to be improved in terms of quality. In Ireland, the approach to information collection for the EPC[3] is highly focused on quality of information and the assessor’s ability to provide advice for future investment in energy performance
What policy initiatives have produced positive results in the UK?
In the UK, the practice of using of large, federated databases, such as the National Energy Efficiency Data-Framework[4], has improved the understanding of the real-world (i.e. empirically measured) impacts of large-scale retrofit programmes. Analysis of energy supplier obligations found that some retrofits were not achieving what the models had estimated (Hamilton et al, 2013[5] ; Hamilton et al 2017[6] ).
In the UK, the use of NEED has yielded considerable benefit for policymakers in evaluating the impact of retrofit programmes on energy use7 , helping to target energy poverty programmes such as the Energy Company Obligation and the Warm Homes Discount.