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Article

Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

1
Institute of BioEconomy, National Research Council of Italy (CNR IBE), 50019 Sesto Fiorentino (FI), Italy
2
Institute of Polar Sciences, National Research Council of Italy (CNR ISP), 40129 Bologna (BO), Italy
3
Chemistry Department, University of Florence, 50019 Sesto Fiorentino (FI), Italy
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(7), 1919; https://doi.org/10.3390/s20071919
Received: 12 March 2020 / Revised: 27 March 2020 / Accepted: 28 March 2020 / Published: 30 March 2020
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Italy 2019-2020)
The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment. View Full-Text
Keywords: low-cost sensors; Arctic environment; atmospheric composition low-cost sensors; Arctic environment; atmospheric composition
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MDPI and ACS Style

Carotenuto, F.; Brilli, L.; Gioli, B.; Gualtieri, G.; Vagnoli, C.; Mazzola, M.; Viola, A.P.; Vitale, V.; Severi, M.; Traversi, R.; Zaldei, A. Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment. Sensors 2020, 20, 1919. https://doi.org/10.3390/s20071919

AMA Style

Carotenuto F, Brilli L, Gioli B, Gualtieri G, Vagnoli C, Mazzola M, Viola AP, Vitale V, Severi M, Traversi R, Zaldei A. Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment. Sensors. 2020; 20(7):1919. https://doi.org/10.3390/s20071919

Chicago/Turabian Style

Carotenuto, Federico, Lorenzo Brilli, Beniamino Gioli, Giovanni Gualtieri, Carolina Vagnoli, Mauro Mazzola, Angelo P. Viola, Vito Vitale, Mirko Severi, Rita Traversi, and Alessandro Zaldei. 2020. "Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment" Sensors 20, no. 7: 1919. https://doi.org/10.3390/s20071919

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