The impact of modeling assumptions on retrofit decision-making for low-carbon buildings

Abstract

To reach decarbonization goals, effective and robust building retrofit decisions are critical. Environmental retrofit assessments rely on full or partial life cycle assessments, which require several modeling assumptions. However, the currently typical ‘status quo’ modeling assumptions for assessing building retrofits need to be questioned with an increasing state of climate emergency. We identify and study the impact of five relevant modeling assumptions that potentially influence the effectiveness of building retrofit: (i) the environmental allocation of photovoltaic electricity, (ii) the effect of global warming, (iii) decarbonization pathways, (iv) choice of the analysis period, and (v) the allocation of biogenic carbon stored in building materials. To investigate the impact of modeling assumptions on the environmental performance and the robustness of retrofit decisions, we establish a framework to compare calculated GHG emissions under different modeling assumptions. The framework is applied to a typical Swiss building. The results show that the choice of modeling assumptions can indeed affect retrofit decision-making based on GHG emissions. In particular, grid decarbonization assumptions strongly impact the choice of renovation strategies. Similarly, the allocation method of locally produced renewable electricity can be decisive when investigating the installation of photovoltaic systems. Aligning the analysis period with the urgency of global warming mitigation shifts the focus towards the embodied emissions, favoring low-emission materials. In contrast, assumptions on global warming do not majorly affect the retrofit decision for the example building. Overall, the introduced approach leads to a more comprehensive view on building retrofit robustness, allowing decision-makers to make better-informed retrofit decisions.