000253568 001__ 253568
000253568 005__ 20190619220020.0
000253568 0247_ $$2doi$$a10.1016/j.rser.2018.02.036
000253568 037__ $$aARTICLE
000253568 245__ $$aAn integrative approach for embodied energy: Towards an LCA-based data-driven design method
000253568 260__ $$c2018-02-27
000253568 269__ $$a2018-02-27
000253568 336__ $$aJournal Articles
000253568 520__ $$aThe built environment is one of the major contributors of greenhouse gas (GHG) emissions. To tackle climate change, global targets have been set for this sector. Although life-cycle assessment (LCA) methods are typically used to evaluate a building project's embodied energy in its final stages of development, this evaluation would be especially valuable at early design stages, when the opportunity to modify the design is greatest. In this paper, an extensive review of methods to improve the usability of LCA at the early design stage is presented. Three major issues regarding the application of LCA arose from this analysis at this stage: its time consumption, the lack of design details, and the non-reproducibility of results. Moreover, LCA makes it possible to assess environmental performance, but does not provide design alternatives, which are crucial to introduce environmental targets into an iterative design process. To that end, existing techniques that can address the major LCA issues were identified, together with their respective limits. These include some promising tools that provide and explore design alternatives and their respective environmental performances. Among these tools are exploration methods, which have not been applied to LCA insofar as it is not possible to do so in a reasonable computational time. To bridge this gap, the paper outlines the structure of an LCA-based data-driven design method, which uses a combination of LCA, parametric analysis, data visualization, sensitivity analysis, and target cascading techniques.
000253568 6531_ $$aLCA
000253568 6531_ $$aEarly design stage
000253568 6531_ $$aEmbodied energy
000253568 6531_ $$aExploration method
000253568 6531_ $$aParametric
000253568 6531_ $$aSensitivity
000253568 6531_ $$aData visualization
000253568 6531_ $$aTarget cascading
000253568 700__ $$g251357$$aJusselme, Thomas$$0249233
000253568 700__ $$g103324$$aRey, Emmanuel$$0244344
000253568 700__ $$0241777$$aAndersen, Marilyne$$g103938
000253568 773__ $$q123-132$$j88$$tRenewable and Sustainable Energy Reviews
000253568 8560_ $$fjoelle.eaves@epfl.ch
000253568 85641 $$uhttps://www.sciencedirect.com/science/article/pii/S1364032118300662$$yFulltext
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000253568 960__ $$athomas.jusselme@epfl.ch
000253568 961__ $$apierre.devaud@epfl.ch
000253568 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000253568 980__ $$aARTICLE
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