Swiss economy; Sustainability assessment; Environmental and social hot-spots; Open science; Externalities; Global value chains; Resource scarcity; Life Cycle Assessment
Shinde Rhythima, Froemelt Andreas, Kim Aleksandra, Hellweg Stefanie (2022), A novel machine-learning approach for evaluating rebounds-associated environmental footprint of households and application to cooperative housing, in Journal of Environmental Management
, 304, 114205-114205.
Kim Aleksandra, Mutel Christopher, Froemelt Andreas (2022), Robust high-dimensional screening, in Environmental Modelling and Software
, 148, 105270.
Paulillo Andrea, Kim Aleksandra, Mutel Christopher, Striolo Alberto, Bauer Christian, Lettieri Paola (2021), Influential parameters for estimating the environmental impacts of geothermal power: A global sensitivity analysis study, in Cleaner Environmental Systems
, 3, 100054-100054.
Jakobs Arthur, Schulte Simon, Pauliuk Stefan (2021), Price Variance in Hybrid-LCA Leads to Significant Uncertainty in Carbon Footprints, in Frontiers in Sustainability
, 2, 1.
Stucki Matthias, Jattke Marleen, Berr Marcus, Desing Harald, Green Ashley, Hellweg Stefanie, Laurenti Rafael, Meglin Ronny, Muir Karen, Pedolin Dario, Shinde Rhythima, Welz Tobias, Keller Regula Lisa (2021), How life cycle–based science and practice support the transition towards a sustainable economy, in The International Journal of Life Cycle Assessment
, 26(5), 1062-1069.
This project will quantify the global environmental and social burdens associated with current Swiss production and consumption from a life-cycle perspective. It will substantially improve on the current state of knowledge by adaptively coupling detailed process-specific inventory data from the ecoinvent database with multi-regional industry-sector specific input-output (MRIO) data from the EXIOBASE database. Special attention will be dedicated to the scientifically sound combination of data from different sources, aggregation levels, and physical/economic layers. We will also integrate quantitative social indicators from the Social Hotspots Database into the ecoinvent database. Based on this global, consistent, and comprehensive dataset, we will identify location-dependent hot spots and leverage points for the environmental and social impacts of Swiss production and consumption, and determine areas where improvements carry the smallest economic burdens or even provide economic benefits. We will also consider and quantify resource dependencies, criticalities, and risks of key Swiss industries. During the project, we will create or update inventory data shown to be particularly important, uncertain, or outdated.