Analysis of Pm2.5 and Pm10 in City Streets: Environmental Impacts and Strategies for Reduction

Air pollution is one of the most pressing environmental and social challenges of our time. Among the various pollutants, fine particulate matter (PM2.5) and coarse particulate matter (PM10) are considered particularly harmful because of their ability to infiltrate the human respiratory system and to persist in the atmosphere. Long-term exposure to these pollutants has been linked to chronic diseases such as asthma, bronchitis, cardiovascular disorders, and, in severe cases, premature mortality. This research seeks to evaluate the actual levels of PM2.5 and PM10 in representative urban streets, with the dual aim of understanding how their concentrations vary under different environmental and infrastructural conditions and of proposing practical strategies to mitigate their presence. To achieve this, a combination of real-time monitoring systems, statistical data analysis, and urban policy evaluation was employed. The adopted approach allows for a detailed overview of the dynamics of particulate matter pollution within complex city environments. The results obtained underline the main dispersion patterns, their correlation with meteorological conditions such as wind and humidity, and their direct dependence on vehicular traffic. Furthermore, they highlight discrepancies between different monitoring technologies, showing how sensor calibration and accuracy can influence the interpretation of air quality. On this basis, the study suggests a set of integrated actions - ranging from technological innovation to policy measures - aimed at limiting population exposure and guiding the future of sustainable urban planning.

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Publication Details

Published
2025-10-27
DOI
https://doi.org/10.1109/icrera66237.2025.11284016
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
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article

Analysis of Pm2.5 and Pm10 in City Streets: Environmental Impacts and Strategies for Reduction

Fabio Viola, Rosario Miceli, Sonia Leva, Sergio Calabrese et al.
Air Quality Monitoring and Forecasting
article

Analysis of Pm2.5 and Pm10 in City Streets: Environmental Impacts and Strategies for Reduction

Fabio Viola, Rosario Miceli, Sonia Leva, Sergio Calabrese, Filippo Brugnone, Michela Longo
article en

Abstract

Air pollution is one of the most pressing environmental and social challenges of our time. Among the various pollutants, fine particulate matter (PM2.5) and coarse particulate matter (PM10) are considered particularly harmful because of their ability to infiltrate the human respiratory system and to persist in the atmosphere. Long-term exposure to these pollutants has been linked to chronic diseases such as asthma, bronchitis, cardiovascular disorders, and, in severe cases, premature mortality. This research seeks to evaluate the actual levels of PM2.5 and PM10 in representative urban streets, with the dual aim of understanding how their concentrations vary under different environmental and infrastructural conditions and of proposing practical strategies to mitigate their presence. To achieve this, a combination of real-time monitoring systems, statistical data analysis, and urban policy evaluation was employed. The adopted approach allows for a detailed overview of the dynamics of particulate matter pollution within complex city environments. The results obtained underline the main dispersion patterns, their correlation with meteorological conditions such as wind and humidity, and their direct dependence on vehicular traffic. Furthermore, they highlight discrepancies between different monitoring technologies, showing how sensor calibration and accuracy can influence the interpretation of air quality. On this basis, the study suggests a set of integrated actions - ranging from technological innovation to policy measures - aimed at limiting population exposure and guiding the future of sustainable urban planning.

University of Palermo (IT), Politecnico di Milano (IT)
Sustainable cities and communities
Openalex Percentile: Top 44%
Air Quality Monitoring and Forecasting
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