A benchmark study of BIM-based whole-building life-cycle assessment tools and processes. Issue 3 (1st October 2016)

• Record Type: Journal Article
• Authors: Schultz, Joshua; Ku, Kihong; Gindlesparger, Matthew; Doerfler, James
• Is Part Of: International journal of sustainable building technology & urban development. Volume 7:Issue 3/4(2016)
• Page Start: 219
• Page End: 229
• Publication Date: 2016-10-01
• Subjects: BIM -- whole building -- LCA -- Tally -- Athena IE; Sustainable urban development -- Periodicals; Architecture and technology -- Periodicals; City planning -- Periodicals; 720.4705
• DOI: 10.1080/2093761X.2017.1302839
• Languages: English
• ISSNs: 2093-761X

Abstract

Abstract: As comprehensive sustainable design methods advance, whole-building life-cycle assessment (LCA) is becoming an important part of sustainable practices. The goal of this research is to evaluate the LCA tool Tally to establish a baseline process for LCA based on building information modelling (BIM). In order to generate benchmarks for whole-building LCA, the architecture, engineering, and construction industry must agree with the United States (US) government on a standard method of measuring embodied carbon in conjunction with a design tool. This paper involves a literature review and two case studies as a comparative software analysis between two whole-building LCA tools: the Autodesk-Revit-based Tally plugin and the Athena Impact Estimator (IE). The case studies include two different unit spaces – walls only in Case 1 and walls, windows, doors, floors, and roof in Case 2 – that were analysed in Tally and the Athena IE to compare the user input parameters, outputs, life-cycle inventory (LCI) databases, and interfaces. The findings highlight the discrepancies between the two environments' inputs and outputs, and offer best practice guidelines towards a BIM-based LCA process. While the emergence of BIM-based LCA tools offers to help users such as architects, engineers, and contractors who are not LCA practitioners, this research shows that the tools include specific data input biases and methods which impact LCA outcomes. Thus a deeper understanding on the part of the users is needed, along with improvements to the software interfaces.