Published in Scientific Papers. Series E. Land Reclamation, Earth Observation & Surveying, Environmental Engineering, Vol. XIII
Written by Stefan-Mihai PETREA, Ira-Adeline SIMIONOV, Alina ANTACHE, Aurelia NICA, Maxim ARSENI, Adrian ROSU, Dragos CRISTEA, Catalina ITICESCU
The paper aims to develop a comparative and integrated analytical framework (CIAF) that will ensure an in-depth understanding of environmental triggers in Western (W) vs Eastern (E) Great Cities (GC) of the European Union (EU). Parameters corresponding to both environmental (EVD) and economic (ECD) dimensions were selected for each of the first 10 EU WGC and EGC, respectively. The EVD considers the impact of PM2.5. exposure, as well as municipal waste generation and days of strong heat stress, while the ECD considers the GDP, labour productivity, as well as unemployment rate, all connected to the demographical dynamics of the analysed urban areas. A machine-learning methodology, consisting of MLR and XGBoost algorithms, is used for the development of the CIAF. The results indicate significant peculiarities between both WGC and EGC and reveal high accuracy (>85%) in various prediction scenarios. The findings can be used as a basis for the future development of complex decision-support tools, tackling to optimize the environmental management in EU GC.
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