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Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

ABSTRACT: Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and Wales, developed from Energy Performance Certificate (EPC) data and containing information for approximately 11.5 million dwellings. First, we estimate indoor/outdoor (I/O) ratios and total indoor concentrations of outdoor air pollution for PM2.5 and NO2 for all EPC dwellings in London. The potential to estimate concentration from both indoor and outdoor sources is then demonstrated by modelling indoor background CO levels for England and Wales pre- and post-energy efficient adaptation, including heating, cooking, and smoking as internal sources. In London, we predict a median I/O ratio of 0.60 (99% CIs; 0.53-0.73) for outdoor PM2.5 and 0.41 (99%CIs; 0.34-0.59) for outdoor NO2; Pearson correlation analysis indicates a greater spatial modification of PM2.5 exposure by housing (??=?0.81) than NO2 (??=?0.88). For the demonstrative CO model, concentrations ranged from 0.4-9.9?ppm (99%CIs)(median?=?3.0?ppm) in kitchens and 0.3-25.6?ppm (median?=?6.4?ppm) in living rooms. Clusters of elevated indoor concentration are found in urban areas due to higher outdoor concentrations and smaller dwellings with reduced ventilation potential, with an estimated 17.6% increase in the number of living rooms and 63% increase in the number of kitchens exceeding recommended exposure levels following retrofit without additional ventilation. The model has the potential to rapidly calculate indoor pollution exposure across large housing stocks and estimate changes to exposure under different pollution or housing policy scenarios.

SUBMITTER: Taylor J

PROVIDER: S-EPMC6467545 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

Taylor Jonathon J Shrubsole Clive C Symonds Phil P Mackenzie Ian I Davies Mike M

The Science of the total environment 20190225

Estimates of population air pollution exposure typically rely on the outdoor component only, and rarely account for populations spending the majority of their time indoors. Housing is an important modifier of air pollution exposure due to outdoor pollution infiltrating indoors, and the removal of indoor-sourced pollution through active or passive ventilation. Here, we describe the application of an indoor air pollution modelling tool to a spatially distributed housing stock model for England and ...[more]

PMID: 30831373

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Project description:Because most people spend the majority of their time in microenvironments, indoor air pollution (IAP) has gained more attention than outdoor air pollution recently. It is indeed crucial to understand IAP sources and the factors that influence human exposure. We synthesized evidence on IAP levels and contributing factors in Ethiopia from available literature, utilizing findings from 19 studies to retrieve 66 relevant values. Particulate matters (PM2.5, PM4, PM10, and TSP), as well as gaseous pollutants such as carbon monoxide (CO), nitrogen dioxide (NO2), polyaromatic hydrocarbons (PAHs), and total volatile organic compounds (TVOCs), were analyzed. The calculated mean concentrations for PM2.5, PM10, NO2, TVOCs, and CO were 477.47 μg/m3, 228.38 μg/m3, 63.84 μg/m3, 1361.79 μg/m3, and 18.82 ppm, respectively, all of which exceeded the annual WHO exposure guidelines. Geographical location, stove type, and household activities showed a variation in pollutants concentration. The higher levels of pollutants were attributed to emissions from biomass fuel used for baking injera, wot preparation, and conducting a coffee ceremony, as well as poor ventilation, season, cooking time, and tobacco smoke. The health risk assessments for exposure to various domestic activities were found to be acceptable, except for PM10, with the highest correlation with an acute respiratory infection. Although improved cookstove technology has been proposed as a sustainable energy source, investigations in Ethiopia have revealed that there is still room for public health protection. There is a paucity of research on the relationship between indoor and outdoor air pollution. Future research should prioritize these issues, with a focus on the link between IAP exposure and health effects. In conclusion, there is a higher IAP concentration in Ethiopia so the community should be made aware of it as well as related health effects, and immediate mitigation measures are needed to achieve a reduction in exposure.

Dataset Information

Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

Publications

Application of an indoor air pollution metamodel to a spatially-distributed housing stock.

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