Building information modelling (BIM) in Life Cycle Assesment: literature review and comparative study

• Autor(a) principal: Barros, Natalia Nakamura
• Data de Publicação: 2016
• Outros Autores: Silva, Vanessa Gomes da
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: PARC (Campinas)
• Texto Completo: https://periodicos.sbu.unicamp.br/ojs/index.php/parc/article/view/8645401
• topic: BIM. Energia incorporada. Emissão de GHG. Avaliação do ciclo de vida.; BIM. Embodied Energy. GHG Emission. Life cycle assessment.

The need to reduce energy consumption and emissions of greenhouse gases (GHG) has come to the forefront of international discussion and efforts. In this sense, combining Life Cycle Assessment (LCA) with Building Information Modeling (BIM) constitutes a field full of potential that however remains underexplored. A literature review showed that most papers published on the intersection between BIM and LCA, have focused on the development and improvement of computational tools to assist LCA in building design and construction. Few contributions are available on the workflow. This paper, in addition to presenting the review of the literature conducted, investigates the potential impact brought by the adoption of BIM in LCA emphasizing the process, the associated technology and information exchanged. The method encompasses a systematic literature review, followed by a comparative analysis of traditional manual information input versus BIM-aided lifecycle assessment. This paper provides a theoretical contribution on BIM and lifecycle assessment integration. The systematic literature review identified recent research trends and gaps, and launched the base for developing the workflows examined. The analysis showed that adoption of BIM-aided lifecycle LCee / LCeghg have a variable impact in design process and a high impact in data collection phase. The most distinctive advantage of BIM-aided LCA is its capacity for process optimization, the possibility to iteratively support design decision-making instigating convergence to an optimal solution.