Abstract
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 PM2.5 sensor output correlates strongly with reference measurements (R2 = 0.87 against a beta attenuation monitor and R2 = 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.
Highlights
Exposure to airborne particulate matter (PM) has been documented, over the last three decades, as being related to a wide range of human health impacts, including respiratory and cardiovascular disease [1,2], increased mortality, and loss of life expectancy [3,4]
Low-cost PM monitors, which are based on optical particle counting technology, have emerged as a cost-efficient solution where indicative yet dense monitoring is required in order to provide real-time information to citizens and stakeholders
We propose a novel approach using external size fractionation data, that can be applied in urban PA-II networks, especially in cases of regional dust events, which are frequent in Southern European countries
Summary
Exposure to airborne particulate matter (PM) has been documented, over the last three decades, as being related to a wide range of human health impacts, including respiratory and cardiovascular disease [1,2], increased mortality, and loss of life expectancy [3,4]. While measurements from low-cost PM devices cannot be used for the assessment of regulatory compliance with air quality standards, it has been demonstrated that they can track reasonably well the variability of concentrations (on various time-scales) and can be subject to calibration based on reference-monitor data, in order to provide realistic ambient concentration levels [21] In this respect, low-cost PM sensors have been recently evaluated by laboratory and field studies [22,23], and are proposed as tools for both long-term as well as event-based monitoring—for instance when dealing with forest fires [24]. The utility and operational capabilities of the network were evaluated during large urban air pollution episodes that were caused by intense residential wood burning and forest fires
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