Luca Catalano
A Transformer-based approach to air quality prediction in Milan through satellite imagery combined with meteorological and morphological data.
Rel. Giuseppe Rizzo, Giacomo Blanco. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2024
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Abstract
Air pollution is one of the most pressing problems of our time, causing serious issues for human health and the environment. It is a key factor in the development of respiratory ailments, ranging from mild conditions like asthma to more severe complications such as decreased lung function, cardiovascular diseases, and premature mortality. Additionally, it has serious environmental repercussions, such as ecosystem degradation, biodiversity loss, and adverse effects on plant growth and agricultural productivity. To better understand and mitigate this problem, remote sensing technologies have been adopted to monitor large areas, facilitating comprehensive air quality assessments. For example, satellite data from the Copernicus Sentinel-5p mission provide valuable information and are useful for forecasting pollutants.
In this study, Copernicus Sentinel-3 and Sentinel-5p data combined with other meteorological and morphological data were used to predict the air quality in the city of Milan, focusing on five pollutants: ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter with a diameter of less than 10 micrometers (PM10), and less than 2.5 micrometers (PM2.5)
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