Uncertainty Analysis of Embedded Energy and Greenhouse Gas Emissions Using BIM in Early Design Stages
| Autor: | Patricia Schneider-Marin, Werner Lang, Hannes Harter, Konstantin Tkachuk |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
020209 energy
Geography Planning and Development lcsh:TJ807-830 lcsh:Renewable energy sources 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law 01 natural sciences 0202 electrical engineering electronic engineering information engineering Sensitivity (control systems) life cycle energy assessment Uncertainty analysis lcsh:Environmental sciences 0105 earth and related environmental sciences lcsh:GE1-350 Renewable Energy Sustainability and the Environment business.industry lcsh:Environmental effects of industries and plants Variance (accounting) Environmental economics Design team embedded greenhouse gas emissions embedded global warming potential design assessment embedded primary energy building information modeling (BIM) lcsh:TD194-195 Building information modeling Greenhouse gas life cycle assessment (LCA) early building design Environmental science business Embodied energy life cycle energy analysis Efficient energy use |
| Zdroj: | Sustainability Volume 12 Issue 7 Sustainability, Vol 12, Iss 7, p 2633 (2020) |
| ISSN: | 2071-1050 |
| DOI: | 10.3390/su12072633 |
| Popis: | 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&rsquo 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. |
| Databáze: | OpenAIRE |
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