On the Potential of District-Scale Life Cycle Assessments of Buildings

Maximilian Schildt, Johannes Linus Cuypers, Maxim Shamovich, Sonja Tamara Herzogenrath, Avichal Malhotra, Christoph Alban van Treeck and Jérôme Frisch ()
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Maximilian Schildt: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Johannes Linus Cuypers: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Maxim Shamovich: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Sonja Tamara Herzogenrath: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Avichal Malhotra: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Christoph Alban van Treeck: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
Jérôme Frisch: Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany

Energies, 2023, vol. 16, issue 15, 1-33

Abstract: Climate neutrality goals in the building sector require a large-scale estimation of environmental impacts for various stakeholders. Life Cycle Assessment (LCA) is a viable method for this purpose. However, its high granularity, and subsequent data requirements and effort, hinder its propagation, and potential employment of Machine Learning (ML) applications on a larger scale. The presented paper outlines the current state of research and practice on district-scale building LCA in terms of standards, software and certifications, and data availability. For this matter, the authors present the development and application of two district-scale LCA tools, Teco and DisteLCA, to determine the Global Warming Potential (GWP) of three different residential districts. Both tools employ data based on (including, but not limited to) CityGML, TABULA, and ÖKOBAUDAT. The results indicate that DisteLCA’s granular approach leads to an overestimation of environmental impacts, which can be derived from the statistical approach to operational energy use and related emissions. While both tools lead to substantial time savings, Teco requires less manual effort. The linkage of the aforementioned data sources has proven laborious and could be alleviated with a common data framework. Furthermore, large-scale data analysis could substantially increase the viability of the presented approach.

Keywords: life cycle assessment (LCA); global warming potential (GWP); CityGML; urban building energy modelling (UBEM); reduced-order modelling (ROM) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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