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

被引:35
|
作者
Schneider-Marin, Patricia [1 ]
Harter, Hannes [1 ]
Tkachuk, Konstantin [1 ]
Lang, Werner [1 ]
机构
[1] Tech Univ Munich, TUM, Inst Energy Efficient & Sustainable Design & Bldg, D-80333 Munich, Germany
关键词
early building design; life cycle assessment (LCA); building information modeling (BIM); embedded greenhouse gas emissions; embedded global warming potential; life cycle energy analysis; life cycle energy assessment; design assessment; embedded primary energy; LIFE-CYCLE ASSESSMENT; SENSITIVITY-ANALYSIS; EMBODIED ENERGY; BUILDINGS; LCA; VISUALIZATION; INTEGRATION; MANAGEMENT;
D O I
10.3390/su12072633
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
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页数:19
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