A 10-month experiment comparing three Airbeam, three Dylos 1100 Pro, and one Met One BAM FEM instrument(s), with parallel meteorological data, was conducted in the Houston area. While neither the Dylos instrument nor the Airbeam data had a strong correlation with the reference data for the entire measurement period, correlation was moderate and most pollution events were captured with each instrument. Good agreement within instruments of the same brand were found, which means that qualitative information about pollution (at different times and in different places), can be gained at lower cost. Performance over time was seen to change and thus agreement between instruments and the FEM data was not steady, as seen in different R~2 values for linear fits between the calculated Dylos mass concentration and FEM mass concentration in monthly bins. Meteorological parameters, such as relative humidity and temperature, were found to affect this agreement. This makes the applicability of calibration with short colocation experiments uncertain. Neither the Dylos nor the Airbeam outperformed the other, but those developing a network should choose the same type of sensor for the best data comparability.
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机译：在休斯敦地区进行了一个为期10个月的实验，将三架Airbeam，三架Dylos 1100 Pro和一台Met One BAM FEM仪器与并行气象数据进行了比较。虽然Dylos仪器和Airbeam数据在整个测量期间均与参考数据没有强相关性，但相关性中等，并且每种仪器都捕获了大多数污染事件。人们发现同一品牌的仪器之间具有良好的一致性，这意味着可以以较低的成本获得有关污染（在不同时间和不同地点）的定性信息。随着时间的推移，性能会发生变化，因此仪器与FEM数据之间的一致性不稳定，如在计算的Dylos质量浓度和月仓中FEM质量浓度之间的线性拟合的不同R〜2值中所见。已发现气象参数（例如相对湿度和温度）会影响该协议。这使得在短时共置实验中校准的适用性不确定。 Dylos和Airbeam都没有优于其他，但是开发网络的人应该选择相同类型的传感器，以实现最佳的数据可比性。
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