Uncertainty Analysis of Embedded Energy and Greenhouse Gas Emissions Using BIM in Early Design Stages

Abstract

With current efforts to increase energy efficiency and reduce greenhouse gas (GHG) emissions of buildings in the operational phase, the share of embedded energy (EE) and embedded GHG emissions is increasing. In early design stages, chances to influence these factors in a positive way are greatest, but very little and vague information about the future building is available. Therefore, this study introduces a building information modeling (BIM)-based method to analyze the contribution of the main functional parts of buildings to find embedded energy demand and GHG emission reduction potentials. At the same time, a sensitivity analysis shows the variance in results due to the uncertainties inherent in early design to avoid misleadingly precise results. The sensitivity analysis provides guidance to the design team as to where to strategically reduce uncertainties in order to increase precision of the overall results. A case study shows that the variability and sensitivity of the results differ between environmental indicators and construction types (wood or concrete). The case study contribution analysis reveals that the building’s structure is the main contributor of roughly half of total GHG emissions if the main structural material is reinforced concrete. Exchanging reinforced concrete for a wood structure reduces total GHG emissions by 25%, with GHG emissions of the structure contributing 33% and windows 30%. Variability can be reduced systematically by first reducing vagueness in geometrical and technical specifications and subsequently in the amount of interior walls. The study shows how a simplified and fast BIM-based calculation provides valuable guidance in early design stages.

Applying Deep Learning and Databases for Energy-efficient Architectural Design - Abstract

“…4. Lifecycle energy assessment -Most of the research works focus on either operational or embodied energy; thus the trade-off is not considered which exists between these two types of energy consumption (Dixit, 2017;Harter et al, 2020).…”

“…Design-embedded sensitivity analysis serves to determine parameter influence on energy performance and allows for the prioritisation of decisions (Harter et al, 2020;Singh and Geyer, 2020). The methods have been implemented prototypically and are shown in the digital modelling environment Revit.…”

Integrated data-driven and knowledge-based performance evaluation for machine assistance in building design decision support

“…In most current design processes embodied emissions are evaluated at a later phase when most construction and material decisions have already been made. The prediction of embodied emissions in early design phases is subject to significant uncertainties due to a lack of detailed information (Schneider-Marin, Harter, Tkachuk & Lang, 2020;Harter, Singh, Schneider-Marin, Lang & Geyer, 2020). Bridging the gap between the lack of information in early design phases and the LCA methodology to predict embodied emissions has been identified as a significant research gap (Theißen, Höper, Wimmer, Zibell, Meins-Becker, Rössig, Goitowski & Lambertz, 2020).…”

Recommendations for Developing a BIM for the Purpose of LCA in Green Building Certifications

“…[18]. However, integrating a full life cycle assessment (LCA) process into this workflow entails significant expertise and a high degree of uncertainty [19,20]. Implementable workflows have been already developed for the early stages of the design process [21].…”