Articles | Volume 18, issue 3
https://doi.org/10.5194/amt-18-817-2025
https://doi.org/10.5194/amt-18-817-2025
Research article
 | 
13 Feb 2025
Research article |  | 13 Feb 2025

Performance evaluation of Atmotube PRO sensors for air quality measurements in an urban location

Aishah I. Shittu, Kirsty J. Pringle, Stephen R. Arnold, Richard J. Pope, Ailish M. Graham, Carly Reddington, Richard Rigby, and James B. McQuaid

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Cited articles

Alfano, B., Barretta, L., Del Giudice, A., De Vito, S., Di Francia, G., Esposito, E., Formisano, F., Massera, E., Miglietta, M. L., and Polichetti, T.: A Review of Low-Cost Particulate Matter Sensors from the Developers' Perspectives, Sensors, 20, 6819, https://doi.org/10.3390/s20236819, 2020. 
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Atmotube: Atmotube Technical Specifications, https://atmotube.com/atmotube-support/atmotube-technical-specification (last access: 24 July 2023), 2023. 
Badura, M., Batog, P., Drzeniecka-Osiadacz, A., and Modzel, P.: Regression methods in the calibration of low-cost sensors for ambient particulate matter measurements, SN (Springer) Appl. Sci., 1, 622, https://doi.org/10.1007/s42452-019-0630-1, 2019. 
Barkjohn, K. K., Gantt, B., and Clements, A. L.: Development and application of a United States-wide correction for PM2.5 data collected with the PurpleAir sensor, Atmos. Meas. Tech., 14, 4617–4637, https://doi.org/10.5194/amt-14-4617-2021, 2021. 
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Short summary
The study highlighted the performance of Atmotube PRO sensor particulate matter (PM) data. The result showed inter-sensor variability among the Atmotube PRO sensor data. This study showed 62.5 % of the sensors used for the study exhibited greater precision in their PM2.5 measurements. The overall performance showed that sensors passed the base testing using 1 h averaged data and that a multiple linear regression model using relative humidity values improved the performance of the PM2.5 data.
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