4.5 Article

Field Evaluation of Low-Cost PM Sensors (Purple Air PA-II) Under Variable Urban Air Quality Conditions, in Greece

期刊

ATMOSPHERE
卷 11, 期 9, 页码 -

出版社

MDPI
DOI: 10.3390/atmos11090926

关键词

particulate matter; PM2; 5; air quality; low-cost sensors; optical particle counter

资金

  1. project PANhellenic infrastructure for Atmospheric Composition and climatE change [MIS 5021516]
  2. Operational Program Competitiveness, Entrepreneurship and Innovation (NSRF 2014-2020)
  3. European Union (European Regional Development Fund)

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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.

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