Global calibration models match ad-hoc calibrations field performances in low cost particulate matter sensors

Abstract

Field calibration is recognized as the best performing approach for operational deployment of low cost air quality sensors. In this approach, each individual sensors node is co-located with reference analyzers to derive ad-hoc calibration algorithms parameters. This strongly limits scalability, and thus mass deployment of these devices for improved air quality phenomena knowledge and management. Global calibration, aiming to derive a single calibration function to be used for all multisensors in a batch, is a promising approach recently tackled in artificial olfaction field. In this work, this approach is firstly applied to low cost PM sensors. Results show comparable performances with conventional, ad-hoc (individual) approaches paving the way for a more scalable approach to calibration of AQ multisensors devices.