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Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology

Journal

ENVIRONMENT INTERNATIONAL
Volume 143, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2020.105748

Keywords

Indoor air quality; Household air pollution; Socio-economic status; Environmental justice; Indoor environment modelling; Preferred reporting items for systematic reviews meta-analyses (PRISMA)

Funding

  1. EPSRC Centre for Doctoral Training in Energy Demand (LoLo) grant [EP/L01517X/1]
  2. Public Health England (UCL award) [551610/178423]
  3. Wellcome Trust [205207/Z/16/Z, 209387/Z/17/Z]
  4. Wellcome Trust [205207/Z/16/Z] Funding Source: Wellcome Trust

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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 developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics such as build quality, volume and ventilation and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and preand posthousing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

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