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

Related authors

ENSO Modulation of PM2.5 air pollution in Central Kalimantan, Indonesia revealed by a dense network of Purple Air sensors
Ailish M. Graham, Dominick V. Spracklen, James B. McQuaid, Richard Rigby, Hanun Nurrahmawati, Devina Ayona, Resti Salmayenti, Kitso Kusin, Adi Jaya, Thomas E. L. Smith, Annisa Alifindira, Shofwan Al Banna Choiruzzad, and Richard Pope
EGUsphere, https://doi.org/10.5194/egusphere-2026-2746,https://doi.org/10.5194/egusphere-2026-2746, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Decomposing pre-industrial to present-day land use change forcing in the UK Earth System Model
Emma Sands, Fiona M. O'Connor, James Weber, Ruth M. Doherty, and Richard J. Pope
Atmos. Chem. Phys., 26, 8553–8573, https://doi.org/10.5194/acp-26-8553-2026,https://doi.org/10.5194/acp-26-8553-2026, 2026
Short summary
Quantifying Drivers of Tropospheric OH and Its Trends: Sensitivity to Atmospheric Processes and Implications for Methane Lifetime
Xuewei Hou, Ryan Hossaini, Oliver Wild, Andrea Mazzeo, Richard J. Pope, Ye Wang, Siyuan Wang, Yuanhong Zhao, James Lee, Bin Zhu, Tianliang Zhao, and Alok K. Pandey
EGUsphere, https://doi.org/10.5194/egusphere-2026-3114,https://doi.org/10.5194/egusphere-2026-3114, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
A modeling study of global distribution and formation pathways of highly oxygenated organic molecules (HOMs) from monoterpenes
Xinyue Shao, Yaman Liu, Xinyi Dong, Minghuai Wang, Ruochong Xu, Joel A. Thornton, Duseong S. Jo, Man Yue, Wenxiang Shen, Manish Shrivastava, Stephen R. Arnold, and Ken S. Carslaw
Atmos. Chem. Phys., 26, 6427–6448, https://doi.org/10.5194/acp-26-6427-2026,https://doi.org/10.5194/acp-26-6427-2026, 2026
Short summary
Challenges in measuring sticky biogenic ice-nucleating macromolecules
Joseph Robinson, Martin I. Daily, Polly B. Foster, Jack P. Macklin, James B. McQuaid, Mark D. Tarn, and Benjamin J. Murray
Aerosol Research Discuss., https://doi.org/10.5194/ar-2026-17,https://doi.org/10.5194/ar-2026-17, 2026
Preprint under review for AR
Short summary

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. 
AQMD: Field Evaluation Atmotube Pro, Air Quality Sensor performance Evaluation Centre, https://www.aqmd.gov/aq-spec (last access: 30 January 2025), 2020. 
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. 
Download
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.
Share