Building data models for scalable high-definition life cycle assessment

The built environment is a major contributor to the climate and ecosystem emergency with building construction and operation responsible for almost 40% of energy-related greenhouse gas (GHG) emissions globally. Increasing energy efficiency of buildings and adopting sustainable construction practices are crucial for achieving decarbonization goals. Furthermore, addressing the entire life cycle of buildings, including operational and embodied GHG emissions, has been identified as a key area for action by scientific bodies such as the Intergovernmental Panel on Climate Change (IPCC) and is at the heart of a new wave of climate policies within the European Union.

This thesis aims to overcome prevailing limitations in building life cycle assessment (LCA) to inform policy making and regulation for reducing the climate impacts of individual buildings and building stocks. The lack of understanding regarding the significance of GHG emissions at different stages of a building life cycle remains a challenge. Additionally, standardized documentation requirements, data collection protocols, and data processing tools need further development. The availability of open and accessible data for benchmarking the environmental impact of buildings and setting decarbonization targets is thus far limited. At the macro scale, modelling building stocks faces challenges due to limited information on impacts related to the full building life cycle and a narrow representation of building types. Existing approaches tend to focus on energy and GHG emissions associated with building operation, overlooking other life cycle stages and lacking a comprehensive LCA indicator perspective. This thesis addresses these gaps through research questions related to embodied carbon in building life cycles, metrics and methods supporting European climate policy, and the integration of comprehensive LCA for building and building stock analysis.

The research utilizes evidence synthesis, environmental LCA, building information modelling (BIM), and building stock modelling. The thesis is comprised of eight chapters: Chapter 1, the introduction, provides an overview of the relevance and urgency of reducing whole life GHG emissions in buildings, highlighting the limitations in current approaches and the research objectives; Chapter 2 presents a systematic review and global meta-analysis which unravel the role of embodied GHG emissions in the life cycle of new buildings, emphasizing the importance of mitigating these emissions to address the climate crisis; Chapter 3 offers an analysis of embodied carbon data from new buildings across Europe and investigates benchmarking whole life embodied carbon, considering different building typologies, construction types, and carbon intensities. It includes and examination of the contribution of various life cycle stages and building parts and addresses methodological inconsistencies and data limitations; The dataset established thus far is presented in chapter 4 via a detailed data descriptor for an open database on whole life carbon of buildings. It describes the collection, processing, and harmonization of data underlying the previous chapters, providing an overview of the resulting database and attribute distributions; In chapter 5 the step towards building stock level is made via an integrated review of assessment models for environmental analysis of building stocks mapped with the objectives of specific EU policy initiatives related to the Green Transformation of the Built Environment. The chapter identifies strengths and weaknesses of existing models, providing insights for robust decision making; Chapter 6 introduces the Scalable Life Cycle Engineering (SLiCE) data model. It also proposes the space-time-indicator (STI) framework to conceptualize data requirements for comprehensive LCA for building and building stock analysis. The SLiCE building data model is presented as an open data logic designed to handle large amounts of high granularity building life cycle information. The chapter also showcases the implementation of SLiCE within a prototypical hotspot analysis tool as well as for dynamic climate impact assessment; Chapter 7 presents an implementation of the SLiCE logic to address the trade-off between model resolution and scale of assessment. SLiCE is implemented with KU Leuven's building LCA model, establishing a novel building LCA ecosystem. The chapter demonstrates the application of SLiCE in various research contexts, from micro-scale to macro-scale analysis and elaborates on the use of SLiCE for prospective analysis of the European building stock; Finally, chapter 8 synthesizes the findings from the previous chapters, discusses insights from applying the SLiCE model, and offers an outlook for the use of SLiCE in supporting decision making, policy development, and real estate management.

By addressing these research questions and providing the insights and novel methods outlined above, this thesis contributes to advancing environmental engineering research with a particular focus on sustainable construction and the reduction of whole life carbon in buildings. The metrics, methods and models presented support sustainable building practices and policies at the European level and beyond.