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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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Sachchida Tripathi on behalf of the Authors (04 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (06 Oct 2020) by Pierre Herckes
RR by Anonymous Referee #1 (28 Oct 2020)
ED: Publish subject to technical corrections (01 Nov 2020) by Pierre Herckes
AR by Sachchida Tripathi on behalf of the Authors (08 Nov 2020)  Author's response    Manuscript
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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.