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The environmental impacts of face-to-face and remote university classes during the COVID-19 pandemic
Diogo A Lopes Silva1, Gabriela Giusti1, Izabela S Rampasso2
1Research Group on Sustainability Engineering, Department of Production Engineering, Federal University of São Carlos (UFSCar), Sorocaba, Brazil.
Abstract:
The face-to-face university classes were abruptly transferred to virtual environments during the pandemic of COVID-19, which generated changes in teaching routine and environmental impacts associated with them. Considering this reality, studies comparing the environmental impacts of face-to-face and remote classes can be of great value. In this sense, this study performed a Life Cycle Assessment (LCA) of face-to-face and remote university classes in a Higher Education institution in the context of COVID-19. Inputs of energy and materials (food, office materials), outputs (air and water emissions, and solid waste) were gathered in situ for the functional unit of 2 hours of face-to-face or virtual class per week for 60 engineering students. Thirteen midpoint impact categories were selected by using the recent Impact World+ midpoint method for Continental Latin America, version 1.251. In the literature, most papers about the environmental management of educational activities focus on the energy efficiency of buildings and electronic equipment during their use. But this study revealed other environmental hotspots primarily associated with meal consumption followed by ethanol fuel use. Meal consumption patterns can be explained by the fact that people usually eat more often during home-office activities. Otherwise, the transportation impacts due to ethanol use are related mainly to face-to-face classes, as much transport is required such as for food supply and student transportation. Finally, an uncertainty and a sensitivity analysis were designed for the LCA conclusions. We concluded that remote classes during the COVID-19 pandemic tend to minimize the overall evaluated impacts to ten of the thirteen impact categories. An optimal scenario was also proposed showing an overall minimization of the impacts by up to 57%, if a hybrid class model were to be adopted.
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