Developing a Robust Calibration Framework for Concentration and Size Distributions from Low-Cost Particulate Matter Sensors in the Greater Toronto Area

The Toronto Atmospheric Monitoring of Emissions (TAME) Project aims to quantify greenhouse gas and air pollutant emissions on the path to net-zero using a variety of instruments. The Quant-AQ MODULAIR is one such low-cost instrument that collects in-situ concentrations of four gas species and particulate matter. Lower cost in-situ sensors provide the opportunity to greatly increase the spatial density of measurements across the Greater Toronto Area. One key drawback associated with employing relatively low-cost instruments compared to higher grade reference instruments is the trade-off between increasing the number of sensors deployed and maintaining data accuracy.
We found the performance of our particulate matter (PM) sensors was largely affected by inherent design constraints chosen to minimize both size and cost. While factory calibration provides reasonable accuracy under ideal conditions, a more robust calibration of the sensor data is required to ensure the accuracy of PM measurements across all atmospheric conditions found within the Greater Toronto Area.
To this extent, our calibration framework is designed to address the physical response of the sensors to varying particulate matter concentrations and associated meteorological conditions, specifically ambient temperature and relative humidity. Three Quant-AQ units co-located with a reference grade instrument since April 2025 provided sufficient testing datasets for performance comparisons in all seasons. Sensor performance for PM2.5 and PM10 (Particulate matter less than 2.5μm and 10μm, respectively) greatly exceeds standards set by the U.S Environmental Protection Agency for all three co-located units, indicating reliable measurements throughout the year.
Conducting additional analyses of the accuracy in particle number size distribution will enable more precise insights into the variability of particle concentrations and allow for potential source appointment of PM throughout the Greater Toronto Area. Enhanced dataset accuracy will allow for better quantification of changes in PM concentrations and size distribution as we transition towards a low-carbon economy.