4.7 Article

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

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 748, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.141396

Keywords

Airborne particulate matter; Fine particles; Low-cost sensors; Calibration; South Europe

Funding

  1. project PANhellenic infrastructure for Atmospheric Composition and climatE change - Operational Programme Competitiveness, Entrepreneurship and Innovation (NSRF 2014-2020) [MIS 5021516]
  2. European Union (European Regional Development Fund)

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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 PM2.5 measurements using the original sensor values were reasonably well correlated (R-2 = 0.82 for PM1 and R-2 = 0.56 for PM2.5) 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 PM1-2.5 (particles with diameters between 1 and 2.5 mu m), PM2.5-10 (diameters between 2.5 and 10 mu m) and PM10, the performance of the low-cost sensors was poor in this area with R-2 < 0.37 in all cases. The response of the PAir sensor for PM1 and PM2.5 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 mu g m(-3)) and for PM2.5 to 18% (1.1 mu g m(-3)). The corresponding root mean square errors are 25% (1.4 mu g m(-3)) for hourly PM1 and 25% (1.6 mu g m(-3)) for PM2.5. 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. (C) 2020 Elsevier B.V. All rights reserved.

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