Size and the City: The potential of downsizing in reducing energy demand and increasing quality of life

Recent decades have seen a tremendous growth in the population, particularly in cities. London, for example, has increased from about 6.8 million to 8.2 million over 20 years from 1991 to 2011. Additionally, we have seen substantial demographic change, with an increasing life expectancy and other factors resulting in a larger number of households with only one or two people. One consequence of this is that older people can end up living in inappropriate housing being too large for their needs, with high heating bills and stairs restricting mobility. In addition, this also contributes to the decreasing availability of housing for the growing population. Ultimately, this can lead to unnecessary use of energy and carbon emissions. One potential approach would be to promote downsizing amongst those who live in larger-than-needed properties (defined in relationship to a standard). Some people might choose to live in large properties – for those the question might be for whom could downsizing be rendered an attractive option. For those keen on downsizing, the question is more how it can be realized, i.e. what barriers need to be removed and what help given. In any case, for those who downsize, this could result in significant release of equity (for home owners) or reduced rent, in addition to lower bills and potentially more suitable accommodation in terms of access and mobility. Potential benefits for the wider population would be greater availability of housing stock. This paper will address this issue in different ways. Firstly, empirical data will be presented on the effect of housing size on energy consumption. A sample of N = 991 households, approximately representative for the English population, is analysed with regard to the impact of housing size and housing type on energy consumption. Results show that those two predictors are of greatest importance, and together explain about 29% of the variability in the log-transformed annual energy consumption, surpassing all other variables. In addition, the analysis calculates the amount of under- and overpopulation of housing to give an estimate of the distribution of living space. Secondly, the paper will discuss the benefits of downsizing for the population. A detailed literature review is performed. The results address the benefits of downsizing and highlight which factors would promote downsizing. One issue that has been shown previously, was that those who could downsize felt that little adequate alternative housing was available. Also, general potential effects are discussed, such as freed up living space, and issues of intergenerational justice. Thirdly, the paper will look beyond downsizing at other options such as co-housing, creating multiple-generation homes, or taking a lodger. The prevalence of these schemes will be discussed, and their potential highlighted

A panel model for predicting the diversity of internal temperatures from English dwellings

Using panel methods, a model for predicting daily mean internal temperature demand across a heterogeneous domestic building stock is developed. The model offers an important link that connects building stock models to human behaviour. It represents the first time a panel model has been used to estimate the dynamics of internal temperature demand from the natural daily fluctuations of external temperature combined with important behavioural, socio-demographic and building efficiency variables. The model is able to predict internal temperatures across a heterogeneous building stock to within ~0.71°C at 95% confidence and explain 45% of the variance of internal temperature between dwellings. The model confirms hypothesis from sociology and psychology that habitual behaviours are important drivers of home energy consumption. In addition, the model offers the possibility to quantify take-back (direct rebound effect) owing to increased internal temperatures from the installation of energy efficiency measures. The presence of thermostats or thermostatic radiator valves (TRV) are shown to reduce average internal temperatures, however, the use of an automatic timer is statistically insignificant. The number of occupants, household income and occupant age are all important factors that explain a proportion of internal temperature demand. Households with children or retired occupants are shown to have higher average internal temperatures than households who do not. As expected, building typology, building age, roof insulation thickness, wall U-value and the proportion of double glazing all have positive and statistically significant effects on daily mean internal temperature. In summary, the model can be used as a tool to predict internal temperatures or for making statistical inferences. However, its primary contribution offers the ability to calibrate existing building stock models to account for behaviour and socio-demographic effects making it possible to back-out more accurate predictions of domestic energy demand