Articles | Volume 16, issue 20
https://doi.org/10.5194/amt-16-4709-2023
https://doi.org/10.5194/amt-16-4709-2023
Research article
 | 
18 Oct 2023
Research article |  | 18 Oct 2023

Performance evaluation of MOMA (MOment MAtching) – a remote network calibration technique for PM2.5 and PM10 sensors

Lena Francesca Weissert, Geoff Steven Henshaw, David Edward Williams, Brandon Feenstra, Randy Lam, Ashley Collier-Oxandale, Vasileios Papapostolou, and Andrea Polidori

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Latest update: 23 Apr 2024
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Short summary
We apply a previously developed remote calibration framework to a network of particulate matter (PM) sensors deployed in Southern California. Our results show that a remote calibration can improve the accuracy of PM data, which was particularly visible for PM10. We highlight that sensor drift was mostly due to differences in particle composition than monitor operational factors. Thus, PM sensors may require frequent calibration if PM sources vary with different wind conditions or seasons.