Using low-cost sensors to assess common air pollution sources across multiple residences
Abstract The rapid development of low-cost sensors provides the opportunity to greatly advance the scope and extent of monitoring of indoor air pollution. In this study, calibrated particle matter (PM) sensors and a non-negative matrix factorisation (NMF) source apportionment technique are used to i...
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Nature Portfolio
2025-01-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-85985-1 |
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| author | Catrin J. Rathbone Dimitrios Bousiotis Owain G. Rose Francis D. Pope |
| author_facet | Catrin J. Rathbone Dimitrios Bousiotis Owain G. Rose Francis D. Pope |
| author_sort | Catrin J. Rathbone |
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| description | Abstract The rapid development of low-cost sensors provides the opportunity to greatly advance the scope and extent of monitoring of indoor air pollution. In this study, calibrated particle matter (PM) sensors and a non-negative matrix factorisation (NMF) source apportionment technique are used to investigate PM concentrations and source contributions across three households in an urban residential area. The NMF is applied to combined data from all houses to generate source profiles that can be used to understand how PM source characteristics are similar or differ between different households in the same urban area. PM2.5 and PM10 concentrations in all three houses were greater, more variable, and significantly different to ambient concentrations recorded at a nearby ambient monitoring site. Concentrations were also significantly different between houses, with the World Health Organisation 24-h guideline limits for PM2.5 breached in one household. The applied methodology was highly successful at modelling concentrations for all the houses (R2 $$\ge$$ ≥ 0.983), finding that across the houses the I/O (indoor to outdoor sources ratio) was the lowest for PM1 (down to 0.08), and greatest for PM10 (up to 4.93). Whilst the sources could not be clearly distinguished further than being outdoors or indoors, the methodology provides clear insights to source variability within and between the monitored houses. These results highlight the importance of monitoring indoor air pollution to improve pollution exposure estimates, as whilst people may live in areas with acceptable ambient air quality, they can be exposed to unhealthy concentrations in their own homes. This method may be applied in future studies for extended periods to investigate the influence of source seasonality on PM concentrations or scaled up to investigate source variability across larger geographical areas. |
| format | Article |
| id | doaj-art-fe117f8ffa3e45f7813ac2beb24643fc |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
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| spelling | doaj-art-fe117f8ffa3e45f7813ac2beb24643fc2025-01-19T12:20:20ZengNature PortfolioScientific Reports2045-23222025-01-0115111410.1038/s41598-025-85985-1Using low-cost sensors to assess common air pollution sources across multiple residencesCatrin J. Rathbone0Dimitrios Bousiotis1Owain G. Rose2Francis D. Pope3School of Geography, Earth and Environmental Sciences, University of BirminghamSchool of Geography, Earth and Environmental Sciences, University of BirminghamSchool of Geography, Earth and Environmental Sciences, University of BirminghamSchool of Geography, Earth and Environmental Sciences, University of BirminghamAbstract The rapid development of low-cost sensors provides the opportunity to greatly advance the scope and extent of monitoring of indoor air pollution. In this study, calibrated particle matter (PM) sensors and a non-negative matrix factorisation (NMF) source apportionment technique are used to investigate PM concentrations and source contributions across three households in an urban residential area. The NMF is applied to combined data from all houses to generate source profiles that can be used to understand how PM source characteristics are similar or differ between different households in the same urban area. PM2.5 and PM10 concentrations in all three houses were greater, more variable, and significantly different to ambient concentrations recorded at a nearby ambient monitoring site. Concentrations were also significantly different between houses, with the World Health Organisation 24-h guideline limits for PM2.5 breached in one household. The applied methodology was highly successful at modelling concentrations for all the houses (R2 $$\ge$$ ≥ 0.983), finding that across the houses the I/O (indoor to outdoor sources ratio) was the lowest for PM1 (down to 0.08), and greatest for PM10 (up to 4.93). Whilst the sources could not be clearly distinguished further than being outdoors or indoors, the methodology provides clear insights to source variability within and between the monitored houses. These results highlight the importance of monitoring indoor air pollution to improve pollution exposure estimates, as whilst people may live in areas with acceptable ambient air quality, they can be exposed to unhealthy concentrations in their own homes. This method may be applied in future studies for extended periods to investigate the influence of source seasonality on PM concentrations or scaled up to investigate source variability across larger geographical areas.https://doi.org/10.1038/s41598-025-85985-1 |
| spellingShingle | Catrin J. Rathbone Dimitrios Bousiotis Owain G. Rose Francis D. Pope Using low-cost sensors to assess common air pollution sources across multiple residences Scientific Reports |
| title | Using low-cost sensors to assess common air pollution sources across multiple residences |
| title_full | Using low-cost sensors to assess common air pollution sources across multiple residences |
| title_fullStr | Using low-cost sensors to assess common air pollution sources across multiple residences |
| title_full_unstemmed | Using low-cost sensors to assess common air pollution sources across multiple residences |
| title_short | Using low-cost sensors to assess common air pollution sources across multiple residences |
| title_sort | using low cost sensors to assess common air pollution sources across multiple residences |
| url | https://doi.org/10.1038/s41598-025-85985-1 |
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