Low-cost sensors for measuring airborne particulate matter: Field evaluation and calibration at a South-Eastern...

Low-cost sensors are useful tools for the collection of air quality data, augmenting the existing regulatory monitoring networks and providing an unprecedented opportunity to increase their spatial coverage. This study presents a calibration process of a low-cost PM sensor (PurpleAir PA-II, PAir) in ambient conditions in the city of Patras, Greece, during 18 months of 2017-2018. The hourly PM₁ and PM_2.5 measurements using the original sensor values were reasonably well correlated (R² = 0.82 for PM₁ and R² = 0.56 for PM_2.5) with the reference instrument, but with a high mean bias and root mean square error. There was a small improvement of around 10% for the daily averages. For PM_1-2.5 (particles with diameters between 1 and 2.5 μm), PM_2.5-10 (diameters between 2.5 and 10 μm) and PM₁₀, the performance of the low-cost sensors was poor in this area with R² < 0.37 in all cases. The response of the PAir sensor for PM₁ and PM_2.5 changed significantly compared to the reference instrument during periods with high dust (or other coarse particle) concentrations. These periods were excluded and a simple linear calibration was then developed for the rest of the fine PM measurements. A method for the identification of these high dust periods based on regional model predictions is proposed. This calibration reduces the relative mean error for hourly PM₁ to 19% (1.1 μg m^-3) and for PM_2.5 to 18% (1.1 μg m^-3). The corresponding root mean square errors are 25% (1.4 μg m^-3) for hourly PM₁ and 25% (1.6 μg m^-3) for PM_2.5. The biases of the corrected values are, as expected, practically zero. Surprisingly, the relative humidity had a negligible effect on fine PM measurements of the PAir in this location and for the conditions of the study.