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Application of Building Information Modelling in Construction and Demolition Waste Management: Systematic Review and Future Trends Supported by a Conceptual Framework

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  • Eduardo José Melo Lins

    (Department of Civil Engineering, Universidade Federal de Pernambuco (UFPE), Avenida Acadêmico Hélio Ramos, s/n, Cidade Universitária, Recife 50740-530, Brazil
    Department of Civil Engineering, Escola Politécnica da Universidade de Pernambuco, R. Benfica, 455-Madalena, Recife 50720-001, Brazil)

  • Rachel Perez Palha

    (Department of Civil Engineering, Universidade Federal de Pernambuco (UFPE), Avenida Acadêmico Hélio Ramos, s/n, Cidade Universitária, Recife 50740-530, Brazil)

  • Maria do Carmo Martins Sobral

    (Department of Civil Engineering, Universidade Federal de Pernambuco (UFPE), Avenida Acadêmico Hélio Ramos, s/n, Cidade Universitária, Recife 50740-530, Brazil)

  • Adolpho Guido de Araújo

    (Department of Civil Engineering, Universidade Federal de Pernambuco (UFPE), Avenida Acadêmico Hélio Ramos, s/n, Cidade Universitária, Recife 50740-530, Brazil
    Department of Civil Engineering, Escola Politécnica da Universidade de Pernambuco, R. Benfica, 455-Madalena, Recife 50720-001, Brazil)

  • Érika Alves Tavares Marques

    (Department of Civil Engineering, Universidade Federal de Pernambuco (UFPE), Avenida Acadêmico Hélio Ramos, s/n, Cidade Universitária, Recife 50740-530, Brazil)

Abstract

The architecture, engineering, construction, and operations industry faces an urgent need to enhance construction and demolition waste management in urban areas, driven by increasing demolition and construction activities and a desire to align with sustainable practices and the circular economy principles. To address this need, a systematic literature review on the building information modelling methodology was conducted, employing a structured protocol and specific tools for the analysis of academic studies, based on PRISMA guidelines and StArt software (version 3.4 BETA). Ninety relevant studies published between 1998 and 2024, were analysed and selected from the Web of Science, Scopus, and Engineering Village databases. Findings indicate that China leads in publications with 34%, followed by Brazil (8%) and the United Kingdom (7%). The analysis emphasises the use of drones and LiDAR scanners for precise spatial data, processed by 3D reconstruction tools like Pix4D and FARO As-Built. Revit excels in 3D modelling, providing a robust platform for visualisation and analysis. Visual programming tools such as Dynamo automate processes and optimise material reuse. The study presents a conceptual framework that integrates these technologies with the principles of the circular economy, clarifying the interactions and practical applications that promote the sustainable management of demolition waste from urban buildings and process efficiency. Although the approach promotes material reuse and sustainability, it still faces barriers such as the need for waste segregation at the source, the adaptation of innovative technologies, like the iPhone 15 Pro LiDAR and thermal cameras, as well as associated costs. These factors may limit its adoption in larger-scale projects, particularly due to the increased complexity of buildings.

Suggested Citation

  • Eduardo José Melo Lins & Rachel Perez Palha & Maria do Carmo Martins Sobral & Adolpho Guido de Araújo & Érika Alves Tavares Marques, 2024. "Application of Building Information Modelling in Construction and Demolition Waste Management: Systematic Review and Future Trends Supported by a Conceptual Framework," Sustainability, MDPI, vol. 16(21), pages 1-55, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:21:p:9425-:d:1510037
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    References listed on IDEAS

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    1. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    2. Adolpho Guido de Araújo & Arnaldo Manoel Pereira Carneiro & Rachel Perez Palha, 2020. "Predictive Methodology for the Quantification of Environmental Aspects in Urban Infrastructures," Sustainability, MDPI, vol. 12(18), pages 1-25, September.
    3. Gi-Wook Cha & Choon-Wook Park & Young-Chan Kim & Hyeun Jun Moon, 2023. "Predicting Generation of Different Demolition Waste Types Using Simple Artificial Neural Networks," Sustainability, MDPI, vol. 15(23), pages 1-22, November.
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    5. Zhijia You & Chen Wu & Lianqiong Zheng & Lingjun Feng, 2020. "An Informatization Scheme for Construction and Demolition Waste Supervision and Management in China," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
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