Embodied GHG emissions of buildings - Critical reflection of benchmark comparison and in-depth analysis of drivers

Martin Röck*, Maria Balouktsi, Marcella Ruschi Mendes Saade, Freja Nygaard Rasmussen, Endrit Hoxha, Harpa Birgisdottir, Rolf Frischknecht, Guillaume Habert, Alexander Passer, Thomas Lützkendorf

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

10 Citations (Scopus)
56 Downloads (Pure)

Abstract

In the face of the unfolding climate crisis, the role and importance of reducing Greenhouse gas (GHG) emissions from the building sector is increasing. This study investigates the global trends of GHG emissions occurring across the life cycle of buildings by systematically compiling life cycle assessment (LCA) studies and analysing more than 650 building cases. Based on the data extracted from these LCA studies, the influence of features related to LCA methodology and building design is analysed. Results show that embodied GHG emissions, which mainly arise from manufacturing and processing of building materials, are dominating life cycle emissions of new, advanced buildings. Analysis of GHG emissions at the time of occurrence, shows the upfront ‘carbon spike’ and emphasises the need to address and reduce the GHG ‘investment’ for new buildings. Comparing the results with existing life cycle-related benchmarks, we find only a small number of cases meeting the benchmark. Critically reflecting on the benchmark comparison, an in-depth analysis reveals different reasons for cases achieving the benchmark. While one would expect that different building design strategies and material choices lead to high or low embodied GHG emissions, the results mainly correlate with decisions related to LCA methodology, i.e. the scope of the assessments. The results emphasize the strong need for transparency in the reporting of LCA studies as well as need for consistency when applying environmental benchmarks. Furthermore, the paper opens up the discussion on the potential of utilizing big data and machine learning for analysis and prediction of environmental performance of buildings.
Original languageEnglish
Title of host publicationConference Proceedings : World Sustainable Built Environment online conference BEYOND 2020 : 2- 4 November 2020
EditorsHolger Wallbaum, Alexander Hollberg, Liane Thuvander, Paula Femenias, Izabela Kurkowska, Kristina Mjörnell, Colin Fudge
Number of pages8
PublisherIOP Publishing
Publication date20 Nov 2020
Pages1-8
Article number032048
DOIs
Publication statusPublished - 20 Nov 2020
EventWorld Sustainable Built Environment - Beyond 2020, WSBE 2020 - Gothenburg, Sweden
Duration: 2 Nov 20204 Nov 2020

Conference

ConferenceWorld Sustainable Built Environment - Beyond 2020, WSBE 2020
Country/TerritorySweden
CityGothenburg
Period02/11/202004/11/2020
SponsorAutodesk Construction Cloud, Bona, Construction Industry Council, et al., HKGBC, Skanska
SeriesIOP Conference Series: Earth and Environmental Science
Number3 (1.06 – 1.10)
Volume588
ISSN1755-1307

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