Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 21
Articles | Volume 19, issue 21
https://doi.org/10.5194/amt-19-7359-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-7359-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 21
Research article
 | 
12 Nov 2026
Research article |  | 12 Nov 2026

A tuneable framework for outlier detection in PM2.5 air sensor networks during wildland fire smoke events

Stuart J. Illson and Karoline K. Barkjohn

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Short summary
During wildland fire smoke events, a sensor reporting unusual values may be broken, or simply the first to detect real smoke. Smoke is patchy, transient, and hard to predict from past events. We developed a generalizable, adjustable method that compares each sensor with its neighbours to flag unreliable data without discarding real smoke impacts. Tested on over 19,000 devices across 9 months, it rarely mistook smoke for a fault and separated brief local events from true sensor malfunctions.
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