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Link to original content: http://pubmed.ncbi.nlm.nih.gov/34614030/
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. 2021 Oct 6;16(10):e0258281.
doi: 10.1371/journal.pone.0258281. eCollection 2021.

Visualising household air pollution: Colorimetric sensor arrays for monitoring volatile organic compounds indoors

Affiliations

Visualising household air pollution: Colorimetric sensor arrays for monitoring volatile organic compounds indoors

Emer Duffy et al. PLoS One. .

Abstract

Indoor air quality monitoring as it relates to the domestic setting is an integral part of human exposure monitoring and health risk assessment. Hence there is a great need for easy to use, fast and economical indoor air quality sensors to monitor the volatile organic compound composition of the air which is known to be significantly perturbed by the various source emissions from activities in the home. To meet this need, paper-based colorimetric sensor arrays were deployed as volatile organic compound detectors in a field study aiming to understand which activities elicit responses from these sensor arrays in household settings. The sensor array itself is composed of pH indicators and aniline dyes that enable molecular recognition of carboxylic acids, amines and carbonyl-containing compounds. The sensor arrays were initially deployed in different rooms in a single household having different occupant activity types and levels. Sensor responses were shown to differ for different room settings on the basis of occupancy levels and the nature of the room emission sources. Sensor responses relating to specific activities such as cooking, cleaning, office work, etc were noted in the temporal response. Subsequently, the colorimetric sensor arrays were deployed in a broader study across 9 different households and, using multivariate analysis, the sensor responses were shown to correlate strongly with household occupant activity and year of house build. Overall, this study demonstrates the significant potential for this type of simple approach to indoor air pollution monitoring in residential environments.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1
Scanned images of sensor array taken before and after exposure to (A) pentanal vapour and (B) acetic acid vapour; (C) graph shows ΔE (Euclidean distance) for carbonyl sensors to increasing amounts of pentanal and pH sensors to increasing amounts of acetic acid. Error bars represent the standard deviation of triplicates.
Fig 2
Fig 2. Scores plot from PCA on sensor array responses after 48 h deployment in different rooms within a single home.
Fig 3
Fig 3
(A) Cumulative response of sensor array during 48 h deployment in open-plan living room/kitchen and office; (B), (C) first derivative of sensor response shows the impact of different types of activities on VOC levels indoors.
Fig 4
Fig 4. Scores plot from PCA on sensor array responses after 48 h deployment in 9 households.
Two sensors were deployed in each household (labelled (a) and (b)) and are linked by the blue ovals overlaid on the plot.
Fig 5
Fig 5. Biplot from PCA on sensor array responses after 48 h deployment in 9 households.
The arrows show the variables (acid sensors, carbonyl sensors, cleaning, use of personal care products, smoking, year built). The length of the arrows represent the contribution of each variable to PC 1 and 2. Two sensors were deployed in each household (labelled (a) and (b)).

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E.D. was supported by funding from the European Union’s Horizon 2020 Research and Innovation Programme (https://ec.europa.eu/programmes/horizon2020/) under the Marie Skłodowska-Curie and by funding from Science Foundation Ireland (SFI) (https://www.sfi.ie/) under Grant Number: SFI/12/RC/2289_P2, co-funded by the European Regional Development Fund. K.H. and R.L. were supported by the Academy of Finland (REMEDIAL consortium, grant no: 296724) and University of Eastern Finland (UEF). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.