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

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  • Maximilian Schildt

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    Current address: Mathieustrasse 30, 52074 Aachen, Germany.
    These authors contributed equally to this work.)

  • Johannes Linus Cuypers

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

  • Maxim Shamovich

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

  • Sonja Tamara Herzogenrath

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

  • Avichal Malhotra

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

  • Christoph Alban van Treeck

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

  • Jérôme Frisch

    (Institute of Energy Efficiency and Sustainable Building E3D, RWTH Aachen University, 52074 Aachen, Germany
    These authors contributed equally to this work.)

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.

Suggested Citation

  • Maximilian Schildt & Johannes Linus Cuypers & Maxim Shamovich & Sonja Tamara Herzogenrath & Avichal Malhotra & Christoph Alban van Treeck & Jérôme Frisch, 2023. "On the Potential of District-Scale Life Cycle Assessments of Buildings," Energies, MDPI, vol. 16(15), pages 1-33, July.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:15:p:5639-:d:1203385
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    References listed on IDEAS

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