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Spatiotemporal Analysis of PM10 and PM2.5 with EBK3D and Space-Time Cube in the City of Lisbon, Portugal
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Resumo(s)
This thesis conducts a spatiotemporal analysis of particulate matter (PM10 and PM2.5) in Lisbon, Portugal, through 2022, utilizing Empirical Bayesian Kriging 3D (EBK3D) and Space-Time Cube analysis to explore pollution dynamics. Focused on how Particulate Matter (PM) levels vary across Lisbon and identifying distinct patterns during different traffic periods on weekdays and weekends. It employs geostatistical methods to analyze pollution levels, offering insights into the spatial and temporal distribution of PM concentrations. Key findings highlight areas with persistent high pollution and temporal fluctuations throughout the city. This research helps in the understanding of Lisbon's PM related air pollution.
Descrição
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
Palavras-chave
Urban Air Quality PM10 PM2.5 Empirical Bayesian Kriging 3D Space-Time Cube Emerging Hot Spot Analysis Local Outlier Analysis SDG 3 - Good health and well-being SDG 11 - Sustainable cities and communities