Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece
Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece
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DOI：
10.3390/atmos11090926
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发表时间：
2020-09-01
期刊：
影响因子：
2.9
通讯作者：
Gerasopoulos, Evangelos
中科院分区：
文献类型：
--
作者：
Stavroulas, Iasonas;Grivas, Georgios;Gerasopoulos, Evangelos
颗粒传感器技术的最新进展导致了低成本、紧凑型颗粒物(PM)监测仪的开发和利用。这些设备可以部署在密集的监测网络中，从而能够更好地表征环境水平和暴露的时空变异性。然而，其测量的可靠性是一个重要的先决条件，与参考级仪器相比，需要进行严格的性能评估和校准。在这项研究中，对Purple Air PA-II设备(低成本PM传感器)在希腊的两个城市环境和三个季节进行了现场评估，并与不同类型的参考仪器进行了比较。在雅典(希腊最大的城市，有近400万居民)进行了为期五个月的测量，时间跨度为2019年夏天和2020年冬春，并在2019年冬春期间在希腊西北部的中等城市约阿尼纳(10万居民)进行了测量。PM(2.5)传感器的输出与参考测量值密切相关(对于Beta衰减监测器，R-2=0.87；对于光学参考级监测器，R-2=0.98)。传感器-参考协议中的偏差被确定为主要与粗颗粒浓度升高和环境相对湿度高有关。简单和多元回归模型被测试来补偿这些偏差，极大地改善了传感器的响应。在实施模型后，观测到传感器误差的大幅下降，导致雅典和Ioannina数据集的平均绝对百分比误差分别为0.18和0.12。总体而言，一个受质量控制和可靠评估的低成本网络可以成为智慧城市空气质量监测的一个不可或缺的组成部分。按照这一思路提供了案例研究，其中使用PA-II设备网络监测影响雅典地区的城市周边森林火灾期间和约阿尼纳冬季极端烟雾事件期间空气质量的恶化情况，这些事件与燃烧木材用于住宅取暖有关。
Recent advances in particle sensor technologies have led to an increased development and utilization of low-cost, compact, particulate matter (PM) monitors. These devices can be deployed in dense monitoring networks, enabling an improved characterization of the spatiotemporal variability in ambient levels and exposure. However, the reliability of their measurements is an important prerequisite, necessitating rigorous performance evaluation and calibration in comparison to reference-grade instrumentation. In this study, field evaluation of Purple Air PA-II devices (low-cost PM sensors) is performed in two urban environments and across three seasons in Greece, in comparison to different types of reference instruments. Measurements were conducted in Athens (the largest city in Greece with nearly four-million inhabitants) for five months spanning over the summer of 2019 and winter/spring of 2020 and in Ioannina, a medium-sized city in northwestern Greece (100,000 inhabitants) during winter/spring 2019-2020. The PM(2.5)sensor output correlates strongly with reference measurements (R-2= 0.87 against a beta attenuation monitor and R-2= 0.98 against an optical reference-grade monitor). Deviations in the sensor-reference agreement are identified as mainly related to elevated coarse particle concentrations and high ambient relative humidity. Simple and multiple regression models are tested to compensate for these biases, drastically improving the sensor's response. Large decreases in sensor error are observed after implementation of models, leading to mean absolute percentage errors of 0.18 and 0.12 for the Athens and Ioannina datasets, respectively. Overall, a quality-controlled and robustly evaluated low-cost network can be an integral component for air quality monitoring in a smart city. Case studies are presented along this line, where a network of PA-II devices is used to monitor the air quality deterioration during a peri-urban forest fire event affecting the area of Athens and during extreme wintertime smog events in Ioannina, related to wood burning for residential heating.