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Abstract
This study evaluates the performance of Smart Citizen Kits (SCKs), a network of low-cost sensors, in monitoring urban air pollution, with a focus on PM2.5, PM10, carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), temperature, and humidity. SCK measurements were compared to reference-grade instruments (ARPAE) during collocation campaigns in Bologna, Italy, during both summer and winter. The results indicate that while SCKs effectively capture the temporal trends of pollutants and environmental parameters, they show discrepancies in absolute concentrations, particularly for PM10 and NO2, due to cross-sensitivity, environmental influences, and sensor-specific biases. Strong correlations were observed between temperature (R² = 0.89) and humidity, confirming the reliability of SCKs for environmental monitoring. However, moderate correlations for PM2.5 (R² = 0.59) and low correlations for PM10 (R² = 0.19) highlight the need for post-data correction methods to improve quantitative accuracy. The study also demonstrated the influence of meteorological factors, such as relative humidity and wind speed, on sensor performance and pollutant dispersion. This study underscores the potential of low-cost sensor networks for tracking urban air quality variability, provided that calibration and correction techniques are applied to enhance their accuracy and reliability for regulatory and scientific applications.
Abstract
This study evaluates the performance of Smart Citizen Kits (SCKs), a network of low-cost sensors, in monitoring urban air pollution, with a focus on PM2.5, PM10, carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), temperature, and humidity. SCK measurements were compared to reference-grade instruments (ARPAE) during collocation campaigns in Bologna, Italy, during both summer and winter. The results indicate that while SCKs effectively capture the temporal trends of pollutants and environmental parameters, they show discrepancies in absolute concentrations, particularly for PM10 and NO2, due to cross-sensitivity, environmental influences, and sensor-specific biases. Strong correlations were observed between temperature (R² = 0.89) and humidity, confirming the reliability of SCKs for environmental monitoring. However, moderate correlations for PM2.5 (R² = 0.59) and low correlations for PM10 (R² = 0.19) highlight the need for post-data correction methods to improve quantitative accuracy. The study also demonstrated the influence of meteorological factors, such as relative humidity and wind speed, on sensor performance and pollutant dispersion. This study underscores the potential of low-cost sensor networks for tracking urban air quality variability, provided that calibration and correction techniques are applied to enhance their accuracy and reliability for regulatory and scientific applications.
Tipologia del documento
Tesi di dottorato
Autore
Sarfraz, Maryam
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
37
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Air Quality, Low-cost sensor, field evaluation, particulate matter, CO2
Data di discussione
26 Giugno 2025
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Sarfraz, Maryam
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
37
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Air Quality, Low-cost sensor, field evaluation, particulate matter, CO2
Data di discussione
26 Giugno 2025
URI
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