Reliability of Low-Cost, Sensor-Based Fine Dust Measurement Devices for Monitoring Atmospheric Particulate Matter Concentrations
Currently, low-cost, sensor-based fine dust measurement devices are commercially available in South Korea. This study evaluated the reliability of three such devices-Yi Shan A4, Plantower PMS7003, and Plantower PMS7003-in comparison to long-term consecutive monitoring systems for discharge and preve...
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Veröffentlicht in: | International journal of environmental research and public health 2019-04, Vol.16 (8), p.1430 |
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Zusammenfassung: | Currently, low-cost, sensor-based fine dust measurement devices are commercially available in South Korea. This study evaluated the reliability of three such devices-Yi Shan A4, Plantower PMS7003, and Plantower PMS7003-in comparison to long-term consecutive monitoring systems for discharge and prevention facilities regarding fine dust control. The performance of these devices for concentration intervals over time was examined through real-time comparison using a GRIMM (Model: 11-A, dust spectrometer from Grimm Technologies) as a reference; this included a correction factor (C-Factor), calculated by a gravimetric method and an equivalence test. For comparison, the reference and target devices were installed in a chamber with fine dust concentrations of 2 µg/m
, with temperature and humidity maintained at 20 °C and 40%, respectively. The fine particulate matter (PM)
concentrations were classified into five intervals: ≤40 µg/m
, 40⁻80 µg/m
, 80⁻120 µg/m
, 120⁻160 µg/m
, and 200⁻230 µg/m
. Statistical analysis was performed using data obtained from national stations for monitoring and controlling fine dust released from facilities under high fine dust loading conditions. The results showed that the measurements of all target devices, which were corrected according to the reference device, provided accurate values at PM
concentrations of ≥40 µg/m
. The statistical analysis results suggest that the evaluated devices are more reliable than the conventional numerical-analysis-based monitoring system. |
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ISSN: | 1660-4601 1661-7827 1660-4601 |
DOI: | 10.3390/ijerph16081430 |