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

机译:北极环境中低成本大气传感器的长期性能评估

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摘要

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 CO ). 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 (r ≈ 0.8) and small absolute errors for both PM and PM (≈1 µg m for PM and ≈3 µg m for PM ), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO exhibits a satisfying agreement with r around 0.70 and an absolute error of ≈23 mg m . 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.
机译:北极是重要的自然实验室,对气候变化极为敏感,因此对其进行监测非常重要。由于极端的环境,通常很难部署传感器,并且观测值仅限于几个稀疏的观测点,从而限制了北极测量的时空覆盖范围。考虑到这些限制,部署坚固耐用的低成本传感器网络的可能性仍然是一个有趣且方便的选择。本工作首次验证了一种低成本传感器阵列(AIRQino),用于监测北极的基本气象参数和大气成分(气温,相对湿度,颗粒物和CO)。 AIRQino在斯瓦尔巴群岛使用了一年,其输出与参考传感器相比。结果显示与参考气象参数(气温(T)和相对湿度(RH))具有良好的一致性,相关系数高于0.8,绝对误差小(温度≈1°C,RH约6%)。低成本的颗粒物(PM)传感器具有良好的线性度(r≈0.8),并且PM和PM的绝对误差都较小(PM约为1 µg m,PM约为≈3µg m),而总体精度受以下两个因素影响未知的局部气溶胶成分,以及在高湿度条件下可能产生吸湿作用。 CO表现出令人满意的一致性,r约为0.70,绝对误差约为23 mg m。总体而言,这些结果以及出色的数据覆盖范围和稀缺的维护需求使AIRQino或类似设备的集成成为将来在北极环境中扩展传感器网络的有趣工具。

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