Urban Physics, Sustainability and Health

Friday 29.4 at 10.00–11.30

The impact of heat waves on three different inhabited buildings – a micrometorological perspective

Achim Drebs & Kirsti Jylhä, Finnish Meteorological Institute, Climate Change and Future Cities

In our study, we simulate the thermal conditions at the time of the prolonged heat wave in 2018 (cut-off date: 17.7.2018) in three different buildings: a single-family house, a multi-storey house and a multi-storey house in a street canyon. All three houses have normal insulation. The simulations are divided into three phases: 1) all houses have neither wall nor roof greening; 2) the houses have roof greening (Sedum with mixed substrate); 3) all houses have wall greening (Hedea Helix) in addition to roof greening.

In our study, special attention is paid to the air temperature and humidity distribution close to the buildings as well as to the radiation conditions of the building surfaces and the greened roofs and walls. The influence of the thermal conditions on the near-ground to human thermal conditions (at a height of 1.5 m) is described by the analysis.

As an example of the diverse simulation results, the reduction of the surface temperatures of the roof of a stand-alone, moderately insulated, multi-storey building is described. Here, the installation of the green roof with sedum achieves a reduction of the surface temperatures by up to 20 K at times of highest sun elevation. At the same time, the reduction in wall surface temperatures on the south wall will be about 10 K.

COVID-19 and individual home energy-use and travel habits: understanding long-term environmental implications

Raul Castaño-Rosa, CNESS seed funding project

Globally, COVID-19 restrictions have affected all of us at all levels, regardless of the educational level, cultural background, and country of residence. However, not all people have been equally affected due to their different backgrounds, contexts, coping mechanisms, strategies, and resources. For instance, from a representative survey in Finland, we know that energy behaviours shifted among Finnish households, and some even struggled to pay for their bills; 8% of all households reported using more energy than usual for that time of year and 5% of households worried that their energy supply might be affected. Moreover, having a car and access to use it has played an important role in mobility choices and, consequently, citizens wellbeing. Air quality has considerably improved in Finland over the past 30 years, but this shift in behaviour may have an impact on the significant fuel use. This project aims to provide a better understanding of potential long-term impacts of COVID-19 on energy use in the home and mobility behaviour and how this may impact both outdoor and indoor air quality. To address this question, a postal survey will be undertaken, collecting data about household composition; housing type; geographic region; wellbeing aspects; energy and travel habits now and in the future within the region of Helsinki. Descriptive and inferential statistics will be used to anylyse the associations between the different variables. Results will provide insights into shifts in people’s energy use and transport habits that could (positively or negatively) influence and impact on air quality and, consequently, wellbeing.

Understanding and mitigating the drivers of urban air pollution inequalities

Lauren Ferguson, University College London; Jonathon Taylor, Tampere University; Michael Davies, University College London & Phil Symonds University College London

Deprived communities in many cities are exposed to higher levels of outdoor air pollution, and there is increasing evidence of similar disparities for indoor air pollution exposure. There is a need to understand and incorporate the drivers of these disparities in population exposure models, so that changes to which can be understood in terms of their contribution to inequalities. However, existing models which quantify exposure across different subgroups of the urban population typically rely on the outdoor element only, despite individuals in the developed world spending up to 80% of their time indoors. To get a complete picture of urban inequalities, indoor environments must be considered. With a focus on London, UK, this work explores the drivers of urban air pollution inequalities in both indoor and outdoor environments, using national building and time-use surveys, geographical data and socio-demographic information. In particular, five factors are explored, namely: the quality of the outdoor environment and ambient levels of pollution; housing characteristics, including ventilation properties and internal sources of pollution; occupant behaviours; population time-activity patterns; and underlying health conditions. A modelling framework is then proposed combining the data inputs to assess how urban air pollution exposure varies for populations of different socio-economic status. Adapting the tool to model the effects of different policy scenarios and applying the framework to other cities is discussed. 

Building Physics modelling of Indoor Environments at Population-Scale

Jonathon Taylor, Tampere University & Phil Symonds, University College London

Globally, buildings account for a large proportion of energy use, and in the United Kingdom this is driven primarily by heating. Here, housing is energy inefficient relative to other locations in Western Europe, with high energy consumption and fuel poverty risks. To meet legally-binding greenhouse gas emission targets and reduce wintertime cold exposure, there is an urgent need to renovate the housing stock; however doing so can lead to unintended negative consequences for indoor environmental conditions and health.

This presentation describes a tool used to assess the energy consumption, indoor environmental quality, and health consequences in the English and Welsh housing stock. By running a large number of building physics simulations, we estimate heating energy, summertime heat, wintertime cold, indoor air pollution, and mould growth risk for representative dwellings types. A neural network metamodel (or a model derived from the building physics models) is then used to estimate building performance for dwellings in housing stock models of England and Wales under current and potential retrofit scenarios, while health impact models convert indoor environmental exposures to estimates of health outcomes. The tool enables the rapid calculation of how changes such as energy efficient retrofit, climate change, climate adaptation, and population changes may impact on health and energy consumption at the population-level.