Structured Under‐Specification of Life Cycle Impact Assessment Data for Building Assemblies

• Published in: Journal of industrial ecology 2019-04, Vol.23 (2), p.319-334
• Main Authors: Tecchio, Paolo, Gregory, Jeremy, Ghattas, Randa, Kirchain, Randolph
• Format: Article
• Language: English
• Subjects: Assemblies; Assembly; Building design; buildings; Classification; Construction materials; Data structures; design process; Environmental impact; Environmental impact assessment; Fidelity; industrial ecology; Information systems; Life cycle analysis; Life cycle assessment; Life cycles; Product design; Residential buildings; Specification; Specifications; streamlined life cycle assessment; structured under‐specification; Uncertainty; uncertainty analysis
• ISSN: 1088-1980; 1530-9290
• DOI: 10.1111/jiec.12746

Summary The existence of uncertainties and variations in data represents a remaining challenge for life cycle assessment (LCA). Moreover, a full analysis may be complex, time‐consuming, and implemented mainly when a product design is already defined. Structured under‐specification, a method developed to streamline LCA, is here proposed to support the residential building design process, by quantifying environmental impact when specific information on the system under analysis cannot be available. By means of structured classifications of materials and building assemblies, it is possible to use surrogate data during the life cycle inventory phase and thus to obtain environmental impact and associated uncertainty. The bill of materials of a building assembly can be specified using minimal detail during the design process. The low‐fidelity characterization of a building assembly and the uncertainty associated with these low levels of fidelity are systematically quantified through structured under‐specification using a structured classification of materials. The analyst is able to use this classification to quantify uncertainty in results at each level of specificity. Concerning building assemblies, an average decrease of uncertainty of 25% is observed at each additional level of specificity within the data structure. This approach was used to compare different exterior wall options during the early design process. Almost 50% of the comparisons can be statistically differentiated at even the lowest level of specificity. This data structure is the foundation of a streamlined approach that can be applied not only when a complete bill of materials is available, but also when fewer details are known.