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While the operational energy use of buildings is often regulated in current energy saving policies, their embodied greenhouse gas emissions still have a considerable mitigation potential. The study aims at developing a multi-objective optimization method for design and renovation of buildings incorporating the operational and embodied energy demands, global warming potential, and costs as objective functions. The optimization method was tested on the renovation of an apartment building in Denmark, mainly focusing envelope improvements as roof and exterior wall insulation and windows. Cellulose insulation has been the predominant result, together with fiber cement or aluminum-based cladding and 2-layered glazing. The annual energy demand has been reduced from 166.4 to a range between 76.5 and 83.7 kWh/(m2 y) in the optimal solutions. The fact that the legal requirements of 70 kWh/(m2 y) are nearly met without building service improvements indicates that energy requirements can be fulfilled without compromising greenhouse gas emissions and cost. Since the method relies on standard national performance reporting tools, the authors believe that this study is a preliminary step towards more cost-efficient and low-carbon building renovations by utilizing multi-optimization techniques.

Energy is engaged in the supply chain of many economic sectors; therefore, the environmental impacts of the energy sector are indirectly linked to those of other sectors. Consequential life cycle assessment (CLCA) is an appropriate methodology to examine the direct and indirect environmental impacts of a product due to technological, economic or social changes. To date, different methodological approaches are proposed, combining economic and environmental models. This paper reviews the basic concept of CLCA and the coupling of economic and environmental models for performing CLCA in the energy sector during the period 2006–2020, with the aim to provide a description of the different tools, highlighting their strengths and limitations. From the review, it emerges that economic modelling tools are frequently used in combination with environmental data for CLCA in the energy sector, including equilibrium, input-output, and dynamic models. Out of these, the equilibrium model is the most widely used, showing some strengths in availability of data and energy system modelling tools. The input-output model allows for describing both direct and indirect effects due to changes in the energy sector, by using publicly available data. The dynamic model is less frequently applied due to its limitation in availability of data and modelling tools, but has recently attracted more attention due to the ability in modelling quantitative and qualitative indicators of sustainability.

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