Monitoring and apportioning sources of indoor air quality using low-cost particulate matter sensors

• Published in: Environment international Vol. 174; p. 107907
• Main Authors: Bousiotis, Dimitrios, Alconcel, Leah-Nani S., Beddows, David C.S., Harrison, Roy M., Pope, Francis D.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Ltd 01.04.2023; Elsevier
• Subjects: Air Pollutants - analysis; Air Pollution; Air Pollution, Indoor - analysis; Environmental Monitoring - methods; Exposure; Indoor air quality; Infiltration; Particle Size; Particulate matter; Particulate Matter - analysis; PM2.5; Source apportionment; Exposure; Infiltration; Source apportionment; Particulate matter; PM2.5; Indoor air quality
• ISSN: 0160-4120; 1873-6750
• DOI: 10.1016/j.envint.2023.107907

•A new methodology is provided for low cost source apportionment of household PM.•The characteristics of different rooms are assessed on their air quality impact.•The key role of outdoor air infiltration into the household is quantified.•Daily PM exposure estimates are provided with reference to the WHO guidelines.•Methodology is easily translatable and scalable to different indoor environments. Air quality is one of the most important factors in public health. While outdoor air quality is widely studied, the indoor environment has been less scrutinised, even though time spent indoors is typically much greater than outdoors. The emergence of low-cost sensors can help assess indoor air quality. This study provides a new methodology, utilizing low-cost sensors and source apportionment techniques, to understand the relative importance of indoor and outdoor air pollution sources upon indoor air quality. The methodology is tested with three sensors placed in different rooms inside an exemplar house (bedroom, kitchen and office) and one outdoors. When the family was present, the bedroom had the highest average concentrations for PM2.5 and PM10 (3.9 ± 6.8 ug/m3 and 9.6 ± 12.7 μg/m3 respectively), due to the activities undertaken there and the presence of softer furniture and carpeting. The kitchen, while presenting the lowest PM concentrations for both size ranges (2.8 ± 5.9 ug/m3 and 4.2 ± 6.9 μg/m3 respectively), presented the highest PM spikes, especially during cooking times. Increased ventilation in the office resulted in the highest PM1 concentration (1.6 ± 1.9 μg/m3), highlighting the strong effect of infiltration of outdoor air for the smallest particles. Source apportionment, via positive matrix factorisation (PMF), showed that up to 95 % of the PM1 was found to be of outdoor sources in all the rooms. This effect was reduced as particle size increased, with outdoor sources contributing >65 % of the PM2.5, and up to 50 % of the PM10, depending on the room studied. The new approach to elucidate the contributions of different sources to total indoor air pollution exposure, described in this paper, is easily scalable and translatable to different indoor locations.