The goal of this study was to identify drivers of environmental impact and quantify their influence on the environmental performance of wooden and massive residential and office buildings. We performed a life cycle assessment and used thermal simulation to quantify operational energy demand and to account for differences in thermal inertia of building mass. Twenty-eight input parameters, affecting operation, design, material, and exogenic building properties were sampled in a Monte Carlo analysis. To determine sensitivity, we calculated the correlation between each parameter and the resulting life cycle inventory and impact assessment scores. Parameters affecting operational energy demand and energy conversion are the most influential for the building's total environmental performance. For climate change, electricity mix, ventilation rate, heating system, and construction material rank the highest. Thermal inertia results in an average 2-6% difference in heat demand. Nonrenewable cumulative energy demand of wooden buildings is 18% lower, compared to a massive variant. Total cumulative energy demand is comparable. The median climate change impact is 25% lower, including end-of-life material credits and 22% lower, when credits are excluded. The findings are valid for small offices and residential buildings in Switzerland and regions with similar building culture, construction material production, and climate.
Purpose This paper addresses the application and potential of LCSA in the built environment with a focus on refurbishments of residential buildings. It specifically addresses the phenomenon of interchange of building technologies efficiencies under different life time assessments from economy, ecology and social fields. An approach of optimization rather than hard target numbers is proposed as win-win-win situations are unlikely. Methods A multidimensional Pareto optimization methodology, using LCC, LCA combined with first stages of a social assessment in a feasibility study but potentially later full SLCA, is proposed, which site-specifically visualizes the interchange between different options in building design or modification, and evaluates optimal overall concepts. LCA and LCC are used to analyze a case study from an EU project named BEEM-UP in which solutions for largescale uptake of refurbishment strategies are developed. Social frame conditions are taken into account by identifying the driving technologies and feeding the consequences of their implementation for the residents into the tenant involvement part of the project. Results and discussion The calculations prove that the general assumptions leading to the methodology hold true at least for this case study. A clear Pareto-optimal curve is visible when assessing LCC and LCA. The example buildings results show certain systems to be dominating clusters on the figures while others clearly can be identified as not relevant. Several of the driving technologies however fail to be applicable because of social frame conditions, e.g., clear requests by the tenants. Based on the conclusions, the potential for including SLCA as a third dimension in the methodology and possible visualization options are discussed. Conclusions The development in the field of social indicators in the building sector has to be strengthened in order to come up with a holistic picture and respectively with appropriate responses to current challenges. While some solutions identified in the LCC/LCA assessment also have good social characteristics, several others have not and solutions identified as lacking might have social advantages that are currently left out of consideration The upcoming Standards EN 15643-5 and ISO 15686-x are a promising step in this direction as is the work to create a conceptual framework for impact assessment within SLCA by the scientific community.
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