Abstract
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.
Highlights
The impact of climate change in the Arctic poses great environmental concern since temperature inPolar Regions is rising faster than in lower latitude areas [1,2,3,4], with increasing occurrence of warming events [5]
Air temperature measured by the AIRQino showed a very good agreement with the CCT reference sensor (r2 = 0.97, root mean square errors (RMSEs) = 1.17 ◦ C, Figure 3a)
Seasonal temperature trends were closely followed by AIRQino and Gruvebadet Atmospheric Laboratory (GAL) PM10 trends were in agreement (r2 = 0.78, RMSE = 3.06 μg m-3, Figure 3e), but AIRQino was generally underestimating PM10 concentrations (Figure 4e, bias of −2.40 μg m-3 and normalized bias of −73.42%)
Summary
The impact of climate change in the Arctic poses great environmental concern since temperature inPolar Regions is rising faster than in lower latitude areas [1,2,3,4], with increasing occurrence of warming events [5]. The faster warming at the poles is primarily due to the ice-albedo positive feedback, where a temperature increase induces melting of ice caps, glaciers, and sea ice, reducing surface albedo and increasing surface temperature of the region [3,6,7]. Another important positive feedback due to warming is the permafrost reduction and melting, with associated greenhouse gas (GHG) emissions to the atmosphere [8]. Year-round measurements extended to the winter season have been demonstrated to be important to fill knowledge gaps [9,10] and specific instrumental setup have been developed and assessed for Polar Regions winter measurements [11]
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