Integrating BIM-LCA to Enhance Sustainability Assessments of Constructions

Author:

Lima Mayara S. Siverio1ORCID,Duarte Susana2,Exenberger Hans1ORCID,Fröch Georg1,Flora Matthias1

Affiliation:

1. Department of Structural Engineering and Material Sciences, University of Innsbruck, 6020 Innsbruck, Austria

2. Quadrante Engenharia, Alfrapark, Estrada do Seminário 4, Edifício C, Piso 1 Sul, Alfragide, 2614-523 Amadora, Portugal

Abstract

The need for sustainable practices in the construction sector has never been more pressing, as the sector seeks to mitigate its carbon footprint, water consumption, and waste generation. The integration of building information modeling (BIM) and life-cycle assessment (LCA) emerges as a promising solution for rapidly and accurately evaluating the environmental impact of construction. This integration has the potential to empower stakeholders to make informed decisions, paving the way for a more environmentally conscious future in the construction sector. However, there are still challenges to overcome before this is a standard procedure. Data interoperability and standardized classifications necessitate ongoing research. To understand the potential of BIM–LCA integration in minimizing carbon emissions in constructions, this study focuses on a hypothetical renovation project, unraveling the mechanics of BIM–LCA integration and exploring its challenges and opportunities. While the existing literature acknowledges the potential benefits of BIM–LCA integration, few research efforts delve into the specific issues that practitioners may face. Our approach seeks to fill this gap by presenting a holistic view of the integration process, highlighting the practical steps and addressing the intricacies involved. The results show that the most relevant information when performing a BIM–LCA integration using Revit® (v 2022) and OneClick LCA (OCL) is the name-property given to the materials within Revit®. Despite the advances made by this semi-automated approach, interoperability and data accessibility challenges remain. The results show that automated material identification relies on Revit® classifications and necessitates careful modeling practices to prevent impact-calculation redundancy.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

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