Modelling Childhood Exposure to Indoor Air Pollution Across Socio-economic Groups
Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in many developed countries, around 80% of modern life is spent indoors, meaning indoor environments may be a better proxy for personal exposure. Building characteristics - such as volume, airtightness, additional ventilation – and occupant behaviour mean indoor air pollution exposure may vary across socio-economic groups, leading to health inequalities. Children are particularly susceptible to the health effects induced by exposure to air pollutants because of their immature immune and lung systems. Thus, children of low socio-economic status (SES) may be a subgroup of the population disproportionately affected by exposure to indoor air pollution.
The UK building stock is expected to undergo a series of modifications in order to meet national carbon targets, as it has only seen modest declines in carbon emissions since the Climate Change Act was established in 2008. Policy-mediated modifications to the built environment can be associated with compromised health, comfort and wellbeing through the emerging dichotomy that arises between increased building airtightness and the maintenance of optimal indoor air quality. Given their limited resources to adapt to changing conditions, vulnerable populations within society, such as those of low socio-economic status (SES), may be disproportionately affected by the unanticipated effects of policies which are implemented without consideration of the wider socio-economic processes governing the space.
Indoor environment modelling (IEM) is a growing area of research offering a methodology through which evidence regarding adaptions to the built environment can be robustly examined before implementation, reducing exposure inequalities. In this research, building physics models will be used to simulate indoor air pollution in a range of representative dwellings. The project will incorporate qualitative information, such as household SES, into a quantitative model in order to estimate exposure disparities across income groups. The calculated indoor exposures will be applied to a parametrised stock model to calculate exposures for a representative population.