Completed PhD Thesis at LIPID

Life Cycle Assessment (LCA) is widely recognized as an appropriate method to measure carbon emissions. However, LCA methods, both time-consuming and requiring a high resolution of detail, are too rarely used by practitioners today, specifically at the early design stage of buildings. This thesis aims to tackle this issue by proposing a novel approach combining parametric assessment, sensitivity analysis, target cascading and data visualization. The method proposes a knowledge-database of design alternatives generated with a parametric approach that applies a combination of user-defined design options, using the Saltelli sampling technique, to a project-specific massing scheme. Later, the carbon emissions of each of these design alternatives are calculated. It is thus possible to explore thousands of alternatives, the influence of the design parameters, carbon budget at the building component scale and understands the consequences of architectural choices on the carbon emissions by using data visualization techniques. Finally, the usability of the method has been assessed thanks to a real-life case study: the architectural competition for the Smart Living Lab in Fribourg, Switzerland.