Varying Performance of Low-Cost Sensors During Seasonal Smog Events in Moravian-Silesian Region

• Published in: Atmosphere 2024-11, Vol.15 (11), p.1326
• Main Authors: Nevrlý, Václav, Dostál, Michal, Bitala, Petr, Klečka, Vít, Sléžka, Jiří, Polách, Pavel, Nevrlá, Katarína, Barabášová, Melánie, Langová, Růžena, Bernatíková, Šárka, Martiníková, Barbora, Vašinek, Michal, Nevrlý, Adam, Lazecký, Milan, Suchánek, Jan, Chaloupecká, Hana, Kiča, David, Wild, Jan
• Format: Article
• Language: English
• Subjects: Accuracy; Air monitoring; Air pollution; Air quality; Air quality monitoring stations; Ambient temperature; Atmospheric aerosols; Atmospheric monitoring; Atmospheric particulates; Bias; Calibration; Carbon monoxide; Complexity; Cost control; Czech Republic; Data analysis; Datasets; Dust storms; Environmental conditions; Environmental monitoring; Heating; Humidity; Industrial areas; Industrial pollution; linear regression; Low cost; low-cost sensors; Nitrogen dioxide; Outdoor air quality; Particle size; Particle size distribution; Particulate emissions; Particulate matter; Poland; Polish smog; Pollutants; Pollution monitoring; Pollution sources; Saharan dust; Saharan dust storm; Sandstorms; Seasonal distribution; Sensors; Size distribution; Smog; Suspended particulate matter; VOCs; Volatile organic compounds; Winter
• ISSN: 2073-4433; 2073-4433
• DOI: 10.3390/atmos15111326

Air pollution monitoring in industrial regions like Moravia-Silesia faces challenges due to complex environmental conditions. Low-cost sensors offer a promising, cost-effective alternative for supplementing data from regulatory-grade air quality monitoring stations. This study evaluates the accuracy and reliability of a prototype node containing low-cost sensors for carbon monoxide (CO) and particulate matter (PM), specifically tailored for the local conditions of the Moravian-Silesian Region during winter and spring periods. An analysis of the reference data observed during the winter evaluation period showed a strong positive correlation between PM, CO, and NO2 concentrations, attributable to common pollution sources under low ambient temperature conditions and increased local heating activity. The Sensirion SPS30 sensor exhibited high linearity during the winter period but showed a systematic positive bias in PM10 readings during Polish smog episodes, likely due to fine particles from domestic heating. Conversely, during Saharan dust storm episodes, the sensor showed a negative bias, underestimating PM10 levels due to the prevalence of coarse particles. Calibration adjustments, based on the PM1/PM10 ratio derived from Alphasense OPC-N3 data, were initially explored to reduce these biases. For the first time, this study quantifies the influence of particle size distribution on the SPS30 sensor’s response during smog episodes of varying origin, under the given local and seasonal conditions. In addition to sensor evaluation, we analyzed the potential use of data from the Copernicus Atmospheric Monitoring Service (CAMS) as an alternative to increasing sensor complexity. Our findings suggest that, with appropriate calibration, selected low-cost sensors can provide reliable data for monitoring air pollution episodes in the Moravian-Silesian Region and may also be used for future adjustments of CAMS model predictions.