Assessing the prospective environmental impacts and circularity potentials of building stocks: An open‐source model from Austria (PULSE‐AT)

Abstract

Building stock models can provide information on the current and future environmental impacts of buildings. Therefore, these models are useful tools for identifying trajectories that are compatible with the objectives of the Paris Agreement. However, the models often lack detail, which can lead to underestimations of the actual impacts of national building stocks, resulting in misinformed decision‐making. This study presents the steps needed to create an archetype‐based bottom‐up building stock model that uses Python and Brightway2. Prospective environmental assessments, including circularity assessments, can be performed by combining life cycle assessment (LCA) with material flow analysis (MFA). An important facet of this model is that it supports the development of a practical and easily reproducible method for the high‐precision modeling of a building stock. This model is open source, is readily adaptable to other countries, and does not require programming knowledge. This combined LCA‐MFA method can be used to assess the potential to reduce greenhouse gas (GHG) emissions from the Austrian building stock in five future scenarios involving sufficiency, energy, material, and design‐related measures. The results show different reduction potentials for embodied and operational GHG emissions depending on the set of measures taken. In all scenarios, mineral and synthetic materials contribute the most to embodied GHG emissions. Finally, the issue of validating building stock models is addressed, and numerous cross‐evaluations are proposed to ensure the reliability of results.

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