2023
DOI: 10.1088/1742-6596/2600/10/102019
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Low-cost carbon dioxide concentration sensors for assessing air quality in the built environment: an on-site evaluation of their measurement performance

F Salamone,
S Sibilio,
M Masullo

Abstract: Carbon dioxide (CO2) concentration is commonly used to determine indoor air quality. However, wearable environmental monitoring devices have not considered CO2 content, because they have mainly focused on the outdoor environment. Our goal is to develop a new wearable monitoring system for indoor research purposes that also incorporates a CO2 concentration sensor. We evaluated the performance of two low-cost CO2 sensors, the Senseair K30 and the Sensirion SCD30, by comparing them with a professional reference s… Show more

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Cited by 1 publication
(2 citation statements)
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“…Second, some air quality sensor systems depend on the ambient diffusion of gasses [ 10 , 11 , 14 , 16 , 17 ]. Hence, future experimental studies could explore reaction kinetics using a diffusion-based experimental setup measuring concentration changes over long periods of time in a closed chamber containing FDM-printed thermoplastics.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Second, some air quality sensor systems depend on the ambient diffusion of gasses [ 10 , 11 , 14 , 16 , 17 ]. Hence, future experimental studies could explore reaction kinetics using a diffusion-based experimental setup measuring concentration changes over long periods of time in a closed chamber containing FDM-printed thermoplastics.…”
Section: Resultsmentioning
confidence: 99%
“…Additionally, low-cost sensors have enabled the creation of large sensor networks that augment established government monitoring sites and increase the spatial distribution of measurements [ 5 , 6 , 7 , 8 ]. Simultaneously, 3D printing, particularly fused deposition modeling (FDM) using thermoplastic filaments, has emerged as an economical means to craft customized structural supports and sensor housings for air quality research applications [ 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ].…”
Section: Introductionmentioning
confidence: 99%