Abstract
Building construction and operation are responsible for around 40 % of global energy-related greenhouse gas emissions. To identify emissions reduction and removal potentials as well as wider environmental impacts, researchers, policy, and decision makers need comprehensive life cycle sustainability assessment (LCSA) insights on individual buildings and building stocks at large. This article proposes an open building data model for Scalable, high-definition Life Cycle Engineering (SLiCE) as a promising solution to overcome the limitations identified for existing models. The article departs from conceptualizing the problem within the Space-Time-Indicator Nexus; presents the proposed SLiCE data structure; and showcases practical uses of SLiCE data for environmental hotspot analysis as well as for dynamic assessment of climate change impact. The open SLiCE building data model and SLiCE hotspot analysis tool are henceforth available for implementation within life cycle assessment (LCA) of building and building stocks, enabling comprehensive insights on buildings’ environmental impacts across spatiotemporal scales.
Abstract as published.
Cite this article
Röck M, Passer A, Allacker K (2024). SLiCE: an open building data model for scalable high-definition life cycle engineering, environmental hotspot analysis and dynamic impact assessment. Sustainable Production and Consumption. https://doi.org/10.1016/j.spc.2024.01.005
RISE authors
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