SLiCE: An open building data model for scalable high-definition life cycle engineering, dynamic impact assessment, and systematic hotspot analysis

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 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 dynamic assessment of climate change impact as well as for systematic environmental hotspot analysis.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.