Barometric Pressure as a correction factor for low-cost particulate matter sensors

Concentration of particulate matter constitutes a major, environmental problem affecting human health especially in urban areas. Although research centers and government agencies have air quality monitoring systems installed, their limited number prevents the spatiotemporal analysis in urban areas. EU funds research projects to engage citizens for air quality issues. The aim is to involve citizens to install low-cost air quality measuring stations to develop a wider network and to retrieve accurate information about air quality. The use of low-cost sensors arise questions about the reliability of the measurements. It is known, that particles concentration measurement are affected by humidity and temperature. Several models have been proposed to remove the impact of the temperature and humidity on the particle’s measurements but the impact of barometric pressure is under investigation. In this work, an extensive study is performed on the barometric pressure aftermath and corrective factors are proposed in relation to it. The pilot stations were installed next to high cost official stations for a month to calibrate the low-cost sensors. Herein, a model of multiple linear regression is presented to confirm the importance of barometric pressure correction, with the ultimate goal being the optimization of the low-cost particle sensors measured values.