PhD research: Towards a structured consequential modelling approach for the construction sector: the Belgian case.
A fairy tale on methodological choices in LCA


Considering its substantial contribution to the total global energy consumption and its use of raw materials, the construction sector is a clear target for improvement on the way to a more sustainable society. In the last decades, the focus of research and policy broadened from the initial objective of reducing energy consumption of a building in use to a more comprehensive approach that accounts for a building’s entire life cycle, for example by performing a life cycle assessment (LCA). Yet, despite the existence of general frameworks, still many assumptions and methodological choices have to be made throughout an LCA study. In this research, the focus is on consequential LCA, an approach which aims to describe how environmentally relevant flows will change in response to possible decisions. For example to opt for a timber frame instead of a traditional masonry structure.

Despite its relevance is generally acknowledged, there is a lack of studies targeting the construction sector following a consequential modelling approach. In addition, its application is often done in a non-systematic and inconsistent way. So in this context, the goal of this work is to assess how consequential LCA can assist in improving the environmental profile of the construction sector, from materials to entire buildings. In other words, how can consequential LCA be applied on a consistent and transparent way across different products and product systems relevant for the construction sector, while maintaining consistent modelling choices?

Building on the theoretical framework of Weidema et al. a practical method was developed that facilitates the transition from theory to practice and that is specific and detailed but ensures general applicability and practical feasibility. The central concept of this method is to identify the suppliers that are likely to be affected by a change in demand, i.e. the marginal suppliers. The method describes procedures to identify geographical market boundaries and subsequently the suppliers the most sensitive to a change in demand, based on their production trends. Also different perspectives on development can be included, reflecting past trends or expected future developments.

Finally, the proposed method was applied and tested on three cases. In the first case the Belgian electricity grid mix is assessed. The possibilities of the proposed method were explored and used to further optimise the method. The second case focuses on the validation of the method and quantifying the effect of making modelling choices, by analysing a selection of six building products supplied to the Belgian market. While in the last case, demountable and reusable wall designs were evaluated on their environmental performance and compared with conventional designs.

This work demonstrates that it is not only relevant to include a consequential modelling approach in LCA to improve the environmental profile of residential buildings, but also practically feasible to do it in a consistent and structured way. Even though making specific modelling assumptions can affect the results to a great extent, by explicitly accounting for this model uncertainty, more robust results can be obtained to support decisions.

Final manuscript PhD

PhD Thesis

Digital Appendices

Appendix D1 Conference paper: The application of survival analysis for service life prediction of building materials: a proof of concept

Appendix D2 Literature review - 30 consequential case studies

Appendix D3 Explorative Case 2. the Belgian electricity mix – Life cycle inventory, calculation files & impact assessment

Appendix D4 Case 1. Generic building products – Statistical analysis (full details)

Appendix D5 Case 1. Generic building products – Calculation files

Appendix D6 part 1 & part 2 Case 1. Generic building products – Output files

Appendix D7 part 1 & part 2 Case 2. Internal walls designed for change – Calculation and output files

Additional information

R-scripts (under construction)