Using Machine Learning for the Calibration of Airborne Particulate Sensors

Lakitha O.H. Wijeratne, Daniel R. Kiv, Adam R. Aker, Shawhin Talebi, David J. Lary
2019 Sensors  
Airborne particulates are of particular significance for their human health impacts and their roles in both atmospheric radiative transfer and atmospheric chemistry. Observations of airborne particulates are typically made by environmental agencies using rather expensive instruments. Due to the expense of the instruments usually used by environment agencies, the number of sensors that can be deployed is limited. In this study we show that machine learning can be used to effectively calibrate
more » ... er cost optical particle counters. For this calibration it is critical that measurements of the atmospheric pressure, humidity, and temperature are also made.
doi:10.3390/s20010099 pmid:31877977 pmcid:PMC6982762 fatcat:dbuztyxtfbamrjnl354edhr3s4