06-12, 17:15–17:30 (Europe/London), Sala Biblioteca @ PoliBa
In late February 2022, the invasion of Russia in the Ukrainian territory started. As is known, air is one of the most affected components of the environment during such exceptional circumstances. The changes in the pattern of civilian and industrial activities may cause the variation of air quality in terms of different pollutants. Hence, conducting proper air quality assessment can be of great importance in the war-affected areas. The pivotal objective of this research is to present an overview of air quality monitoring and air pollution prediction carried out for Ukrainian territory. Utilizing the Copernicus Sentinel-5P TROPOMI observations, the emissions of ozone (O3), nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO) in Kiev, Kharkiv, Donetsk, Kherson, and Lviv are monitored during 2022. The relevant records are compared to the same business-as-usual (BAU) periods in 2019 and 2021 to detect significant changes. Visual interpretations supported by statistical analysis proved that the ongoing war has significant impacts on the concentration of pollutants throughout Ukraine. Following this, a hybrid machine learning model is developed to predict the concentration of a well-known air quality indicator called particulate matter 2.5 (PM2.5). The prediction results indicated a reliable accuracy of the proposed methodology, as well as its superiority over benchmark models. In short, this research shows promising application of state-of-the-art technologies inducing remote sensing and artificial intelligence for solving air quality problems in during exceptional events.
Marco Scaioni, Civil Engineering MSc Degree (Politecnico Milano, Italy, 1995), PhD on Geodetic and Mapping Sciences (Politecnico Milano, 1999).
Full Professor of Geomatics at Politecnico Milano, Dept. of Architecture, Built Environment and Construction Engineering (ABC). Head of ABC-PhD programme.
Formerly, Full Professor in the College of Surveying and Geo-Informatics at Tongji University, Shanghai (2011-2014).
Main research interests: Photogrammetry and Laser scanning from multiple platforms, Integration GIS/BIM for buildings and infrastructures, Geomatics for Geosciences (Glaciology and Geology) and Cultural Heritage, Geodatabases for urban planning, Deep Learning classification of point clouds.
Associate Editor of Applied Geomatics (Springer) and the ISPRS Journal of Photogrammetry and Remote Sensing (Elsevier).
He published more than 310 scientific papers, including 65 papers on WoS-indexed journals (H-index: 22), 171 Scopus-indexed papers (H-index: 30) and two edited books.
