This thesis investigates the implementation of the “Green Radiology” model in a hospital radiology department, focusing on strategies to reduce energy consumption and environmental impact. Through a three-year analysis of diagnostic equipment and auxiliary systems, combined with targeted interventions—such as automated shutdowns, digital process integration, and space optimization—it achieved notable reductions in energy use and emissions. The results underscore environmental, economic, and organizational benefits, confirming the model’s scalability to other healthcare or corporate settings. The research concludes with practical recommendations and outlines future directions to enhance sustainability through both technological innovation and behavioral change in medical environments.
Questa tesi esplora il concetto di “Green Radiology” applicato a un dipartimento di radiologia ospedaliero, analizzando i consumi energetici di apparecchiature diagnostiche e sistemi ausiliari. Attraverso un monitoraggio triennale e l’introduzione di interventi mirati—come lo spegnimento automatico, la digitalizzazione dei processi e l’ottimizzazione degli spazi—è stato possibile ridurre significativamente i consumi e le emissioni. I risultati evidenziano benefici economici, ambientali e organizzativi, dimostrando la replicabilità del modello in altri contesti sanitari o aziendali. La ricerca si conclude con raccomandazioni per future applicazioni tecnologiche e una visione integrata della sostenibilità in ambito sanitario.
Reduction of Energy Emissions and Prospects for Eco-Sustainable Practices in the Radiology Department: "Green Radiology"
CRAPANZANO, Agata
2025
Abstract
This thesis investigates the implementation of the “Green Radiology” model in a hospital radiology department, focusing on strategies to reduce energy consumption and environmental impact. Through a three-year analysis of diagnostic equipment and auxiliary systems, combined with targeted interventions—such as automated shutdowns, digital process integration, and space optimization—it achieved notable reductions in energy use and emissions. The results underscore environmental, economic, and organizational benefits, confirming the model’s scalability to other healthcare or corporate settings. The research concludes with practical recommendations and outlines future directions to enhance sustainability through both technological innovation and behavioral change in medical environments.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/213144
URN:NBN:IT:UNIPA-213144