Harmonizing Low-Cost Air Quality Sensors for a Hybrid Monitoring Network

Air quality monitoring is crucial for assessing environmental health and supporting mitigation strategies. This research focuses on the co-location of various low-cost particulate matter (PM) sensors—uRADMonitor, AirGradient, PurpleAir, Clarity, and sensors from community initiatives—alongside a mobile laboratory equipped with a reference-grade GRIM EDM 180 analyzer. The primary goal is to identify and quantify bias among these low-cost sensors for PM2.5 and PM10 measurements at the same location.

By systematically analyzing the measurement discrepancies, a generalized correction formula is derived, enabling the harmonization of readings across different sensor types. The corrected data will form the basis of a hybrid air quality monitoring network, which standardizes PM2.5 and PM10 concentrations regardless of the sensor manufacturer. This approach leverages the affordability and scalability of low-cost sensors while ensuring data quality comparable to reference instruments.

The results aim to address limitations in the current low-cost sensor ecosystem, enhance interoperability, and provide communities and policymakers with reliable, high-resolution air quality data. Ultimately, this study supports the development of inclusive and sustainable monitoring frameworks that empower both urban and rural regions with actionable environmental insights, using all kinds of sensors.