Articles | Volume 14, issue 1
Atmos. Meas. Tech., 14, 37–52, 2021
https://doi.org/10.5194/amt-14-37-2021
Atmos. Meas. Tech., 14, 37–52, 2021
https://doi.org/10.5194/amt-14-37-2021

Research article 04 Jan 2021

Research article | 04 Jan 2021

Robust statistical calibration and characterization of portable low-cost air quality monitoring sensors to quantify real-time O3 and NO2 concentrations in diverse environments

Ravi Sahu et al.

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Cited articles

Akasiadis, C., Pitsilis, V., and Spyropoulos, C. D.: A Multi-Protocol IoT Platform Based on Open-Source Frameworks, Sensors, 19, 4217, 2019. a
Apte, J. S., Messier, K. P., Gani, S., Brauer, M., Kirchstetter, T. W., Lunden, M. M., Marshall, J. D., Portier, C. J., Vermeulen, R. C., and Hamburg, S. P.: High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data, Environ. Sci. Technol., 51, 6999–7008, 2017. a
Arroyo, P., Herrero, J. L., Suárez, J. I., and Lozano, J.: Wireless Sensor Network Combined with Cloud Computing for Air Quality Monitoring, Sensors, 19, 691, 2019. a
Baron, R. and Saffell, J.: Amperometric Gas Sensors as a Low Cost Emerging Technology Platform for Air Quality Monitoring Applications: A Review, ACS Sensors, 2, 1553–1566, 2017. a, b
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain, B., Broday, D., and Bartonova, A.: Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?, Environ. Int., 99, 293–302, 2017. a
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Short summary
A unique feature of our low-cost sensor deployment is a swap-out experiment wherein four of the six sensors were relocated to different sites in the two phases. The swap-out experiment is crucial in investigating the efficacy of calibration models when applied to weather and air quality conditions vastly different from those present during calibration. We developed a novel local calibration algorithm based on metric learning that offers stable and accurate calibration performance.