Analytical Review of Methodological Approaches for Measuring Circularity in Building Renovation


  • Roma Almeida Linnaeus University, Sweden
  • Krushna Mahapatra Linnaeus University, Sweden
  • Brijesh Mainali Linnaeus University, Sweden


system thinking, built-environment, resource efficiency, environment impact assessment, comparative analysis


Circularity in construction industry requires understanding of the complex system dynamics, which are affected by various building layers and societal systems. While the existing building stock offers opportunities to enable re-looping of construction and demolition waste, the assessment of building circularity performance is not straightforward, due to lack of standard database, methods, and tools. This may lead to subjective interpretations by practitioners who rely on lifecycle assessment (LCA) approach complemented with circularity indicators (C-indicators) to know the level of circularity (LOC) of building materials, components, and elements. Thus, these C-indicators requires careful evaluation of the current methodological approaches. The aim of this paper is to map and evaluate the nexus between assessment methodologies highlighting their strengths, limitations, and areas of improvement. In this study, a complementary approach of systematic literature review and design research concept was used to classify seven primary aspects covering 18 key performance indicators, that impact the system thinking approach of the renovation project. The critical analysis of ten distinguished C-indicators show conditional, beneficial and trade-off relationships between various indicators. At the same time, the dynamic aspect of re-looping the resources is missing in these indicators and sustainability is accounted by complementing lifecycle impacts rather than coupling them. Results of this review highlight substantial gaps in C-indicators applicability for renovation projects with emphasis to formulate a practical guidance to assess recirculation of materials throughout the value chain.


Metrics Loading ...