Use of Low-Cost Sensors to Study Atmospheric Particulate Matter Concentrations: Limitations and Benefits Discussed through the Analysis of Three Case Studies in Palermo, Sicily

The paper discusses the results of the concentrations of atmospheric particulate matter, in the PM<sub>2.5</sub> and PM<sub>10</sub> fractions, acquired by two low-cost sensors. The research was carried out from 1 July 2023 to 30 June 2024, in Palermo, Sicily. The results obtained from two systems equipped with the same sensor model were compared. Excellent linear correlation was observed between the results, with differences in measurements falling within instrumental accuracy. Two instruments equipped with different sensors, models Novasense SDS011 and Plantower PMSA003, were placed at the same site. These were complemented by a weather station to measure meteorological parameters. Upon comparing the atmospheric particulate matter concentrations measured by the two instruments, it was observed that there was a good linear correlation for PM<sub>2.5</sub> and a poor linear correlation for PM<sub>10</sub>. Additionally, the PMSA003 sensor appeared to consistently record higher concentrations than the SDS011 sensor. During periods influenced by natural sources and/or anthropogenic activities at the regional and/or local scale, i.e., the dispersal of Saharan sands, forest fires, and local events using fireworks, abnormal concentrations of atmospheric particulate matter were detected. Despite the inherent limitations in precision and accuracy, both low-cost instruments were able to identify periods with abnormal concentrations of atmospheric particulate matter, regardless of their source or type.

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Publication Details

Journal
Sensors
Published
2024-10-14
DOI
https://doi.org/10.3390/s24206621
Citations
4
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
0.82

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article

Use of Low-Cost Sensors to Study Atmospheric Particulate Matter Concentrations: Limitations and Benefits Discussed through the Analysis of Three Case Studies in Palermo, Sicily

Luciana Randazzo, Sergio Calabrese, Filippo Brugnone
4 citations
Sensors
Air Quality Monitoring and Forecasting
0.82
article

Use of Low-Cost Sensors to Study Atmospheric Particulate Matter Concentrations: Limitations and Benefits Discussed through the Analysis of Three Case Studies in Palermo, Sicily

Luciana Randazzo, Sergio Calabrese, Filippo Brugnone
article en
4 citations

Abstract

The paper discusses the results of the concentrations of atmospheric particulate matter, in the PM<sub>2.5</sub> and PM<sub>10</sub> fractions, acquired by two low-cost sensors. The research was carried out from 1 July 2023 to 30 June 2024, in Palermo, Sicily. The results obtained from two systems equipped with the same sensor model were compared. Excellent linear correlation was observed between the results, with differences in measurements falling within instrumental accuracy. Two instruments equipped with different sensors, models Novasense SDS011 and Plantower PMSA003, were placed at the same site. These were complemented by a weather station to measure meteorological parameters. Upon comparing the atmospheric particulate matter concentrations measured by the two instruments, it was observed that there was a good linear correlation for PM<sub>2.5</sub> and a poor linear correlation for PM<sub>10</sub>. Additionally, the PMSA003 sensor appeared to consistently record higher concentrations than the SDS011 sensor. During periods influenced by natural sources and/or anthropogenic activities at the regional and/or local scale, i.e., the dispersal of Saharan sands, forest fires, and local events using fireworks, abnormal concentrations of atmospheric particulate matter were detected. Despite the inherent limitations in precision and accuracy, both low-cost instruments were able to identify periods with abnormal concentrations of atmospheric particulate matter, regardless of their source or type.

SensorsVol. 24(20)
Istituto Nazionale di Geofisica e Vulcanologia (IT), University of Palermo (IT)
European Commission
Openalex Percentile: Top 30%
Air Quality Monitoring and Forecasting
0.82
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