Hamilton, IG; (2015) Energy Epidemiology: an epidemiological approach to empirically-based population-level energy demand research. Doctoral thesis , UCL (University College London).

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Abstract

The shift to a low carbon economy and the need to address energy demand priorities will involve the retrofit of millions of buildings resulting in changes in energy demand services at the national and international scale. Studying energy demand in buildings at a population level is different than in individual or small samples because of population heterogeneity. Evaluating policies and determining the effect of technologies in situ in millions of buildings means using techniques that support that level of analysis and use empirically derived data that can represent complex real-world conditions. Health epidemiology, which studies the distribution and determinants of population health outcomes, offers a compelling framework for studying population level energy demand. The aim of this thesis is to determine whether the adaption of the conceptual and methodological framework of epidemiology can support the study of energy, people and buildings. This thesis tests this hypothesis by examining relevant epidemiological concepts and its methodological framework along with three studies that adapt and apply epidemiological methods to energy demand and energy efficiency retrofits in UK houses. The method studies use a database of over 13 million dwellings to study energy efficiency retrofit uptake and their impact on energy demand. The method study findings support the case that an epidemiological approach to energy demand provides an appropriate and plausible conceptual and methodological framework for determining population-level evidence to inform modelling and policy development and evaluation. Adapting the epidemiological approach is not a panacea to dealing with the challenges facing the field of research in energy demand in buildings. However, it does provide a set of concepts, methods and analysis tools that are capable of supporting an empirically-based population-level research approach, identified as a necessary step towards to developing a robust foundation of evidence.

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