Suchergebnisse

The building industry is responsible for approximately 40% of energy consumption and 36% of greenhouse gas emissions in the European Union (EU). The most efficient way of reducing a building&rsquo ; s environmental impact is addressing it in the design stage. Here, design freedom is the greatest, but uncertainty is high and there is a nearly limitless number of design options. Based on experiences with zero emission buildings (ZEB) and zero emission neighbourhoods (ZEN), a mapping review has been conducted to analyse how parametric life cycle assessment (LCA) and algorithms have been used to address neighbourhoods, buildings, and construction materials. Results have identified a general gap of knowledge regarding the use of parametric LCA models for decision-support purposes, demonstrated by the substantial focus on analytical methods compared to procedural methods. Implications for the evolution from ZEB to ZEN are twofold: (i) an integrated approach with multiple tools and methods is required, and (ii) further development of algorithms in the tool are needed to address complexity, sensitivity, and uncertainty. This study is expected to foster the development of algorithmic approaches to improve the ZEB tool as a decision-support tool. Further research should address the key questions of when and how.

The building industry is responsible for approximately 40% of energy consumption and 36% of greenhouse gas emissions in the European Union (EU). The most efficient way of reducing a building's environmental impact is addressing it in the design stage. Here, design freedom is the greatest, but uncertainty is high and there is a nearly limitless number of design options. Based on experiences with zero emission buildings (ZEB) and zero emission neighbourhoods (ZEN), a mapping review has been conducted to analyse how parametric life cycle assessment (LCA) and algorithms have been used to address neighbourhoods, buildings, and construction materials. Results have identified a general gap of knowledge regarding the use of parametric LCA models for decision-support purposes, demonstrated by the substantial focus on analytical methods compared to procedural methods. Implications for the evolution from ZEB to ZEN are twofold: (i) an integrated approach with multiple tools and methods is required, and (ii) further development of algorithms in the tool are needed to address complexity, sensitivity, and uncertainty. This study is expected to foster the development of algorithmic approaches to improve the ZEB tool as a decision-support tool. Further research should address the key questions of when and how. ; publishedVersion