The building design process plays a central role in efforts to implement energy-efficient practices. However, unilateral design choices based solely on reducing operational energy use can significantly increase a building’s embodied energy and life cycle energy use as there is a trade-off between embodied and operational energy. To support such trade-off problems, multi-objective optimization represents a useful approach that produces a set of optimal solutions from where a solution can then be selected and progressed within the design process. Selecting one solution from the set of optimal solutions can however be a challenging task as each solution has the potential to be chosen as the optimum. Therefore, the purpose of this study was to explore how solutions from a multi-objective optimization approach can be analyzed further to provide information to decision-makers when selecting the optimal design solution. An approach is proposed where the integration of post-optimization sensitivity analysis into a multi-objective optimization approach aims to support decision-makers in analyzing the optimal solutions provided by the optimization process. The applicability of approach is demonstrated using a case of a multifamily apartment building located in Sweden, where the aforementioned trade-off is explored for a set of energy efficiency measures. Thereby, a diverse range of optimal solutions that could result in up to 4520 GJ life cycle energy (LCE) savings relative to the case building’s initial design was initially identified using the multi-objective optimization. These solutions were then subjected to a sensitivity analysis where the results indicated that in general the lowest and highest sensitivity in terms of LCE use belonged to the insulation thicknesses in roof and walls, respectively. Furthermore, the thickness of exterior floor insulation yielded the greatest variation in the sensitivity. The findings of case study indicate that the post-optimization sensitivity analysis can add valuable information that complements the results obtained using a multi-objective optimization approach. Consequently, it can support decision-making on how to progress with the design in terms of what design parameters have a negligible or significant impact on the objectives when they are varied, thus facilitating prioritization.

A bottom-up dynamic modeling framework aiming to incorporate realities of the decision-making process when implementing energy-saving building renovations is proposed and applied to a case study of all multifamily buildings in Gothenburg, Sweden. The developed model is based on real conditions of existing buildings, from the national Energy Performance Certificate database, building and property registers, and cadastral maps from the city planning office. Although explorative, the framework accounts for the reaction capacity in terms of (i) investments by all property owners and (ii) total workmanship capacity in the city. Two scenarios were considered to account for renovations driven solely by technical renovation needs (end-of-life of building components) and by cost efficiency; further, both scenarios were investigated at different levels of reaction capacity. The developed framework is easily replicable to other regions and cities. The retrofitting includes, as individual measures as well as in packages, increased insulation levels, increased efficiency of lighting and appliances, and the installation of heat recovery systems and photovoltaic panels.

Whereas implementation of energy-efficient measures dictated solely by technical renovation needs led to a very low energy demand, with some buildings becoming energy producers by 2050, implementation strictly driven by cost-efficiency (from the perspective of the property owners) only reduced the energy demand by 5% during this time and would not fully utilize the investment capacity of the property owners. Furthermore, the current limitations of reaction capacity for the market shares allowed for a reduction of the energy demand by only 15% during the same period. Workmanship capacity was more constraining than investment capacity and is thus identified as a local imperative need and suggests co-benefits related to job creation within the construction sector.

Building retrofit is considered as a vital step to achieve energy and climate goals in both Europe and Sweden. Nevertheless, retrofitting solutions based merely on reducing operational energy use can increase embodied energy use, mainly due to altering the existing trade-off between the two. Considering this trade-off is vitally important, especially for retrofitting buildings located in cold climate regions, as reduction of operational energy use to meet standards of energy-efficient buildings may require a deep retrofitting that can considerably increase the embodied energy and thus be unfavorable from a Life Cycle Energy (LCE) perspective. This article presents a case study in which multi-objective optimization was used to explore the impact of a wide range of retrofitting measures on the aforementioned trade-off for a building in Sweden located in a subarctic climatic zone. The studied building was a typical 1980s multi-family residence. The goal was to explore and compare the optimal retrofitting solution(s) for the building, aiming to achieve Swedish energy-efficient building standards (i.e. new-build and near-zero energy standards). The results of the optimization indicated that (1) use of additional insulation in walls and roof, (2) replacement of existing windows with more energy-efficient ones, and (3) change of traditional mechanical extract ventilation to heat recovery ventilation are the primary and optimal retrofitting measures to fulfill the new-build Swedish energy standard and achieve highest LCE savings. However, to fulfill more far-reaching operational energy savings, application of additional retrofitting measures was required, increasing the embodied energy use considerably and resulting in lower LCE savings compared to the optimal retrofitting solution that only reached the Swedish new-build energy standard. The LCE difference between the optimal retrofitting solutions that fulfilled the new-build standard and the strictest near-zero (passive house) standard was 1862 GJ, which is equivalent to almost four years of operational energy use for the original building. This indicates that there is a limit to the reduction of operational energy use when retrofitting existing buildings, beyond which additional reductions can considerably increase the embodied energy and thus be unfavorable in terms of LCE use.

A transition toward a circular building sector, in which built-in construction products with remaining technical life are reused, would decrease the amount of waste generated, improve resource utilization and reduce greenhouse gas emissions related to the built environment. Based on this premise, this study (1) identifies key barriers to the increased reuse of high-quality construction products in the Swedish building sector and, based on these barriers (2) presents a set of new working practices that enable reuse in building and deconstruction projects. The study uses an explorative research approach based on data from ten case studies of Swedish building and deconstruction projects, semi-structured interviews and a survey conducted with key building-sector stakeholders. The results identify a lack of knowledge and an immature market as key barriers that must be removed in order to enable increased reuse in the Swedish building sector. Key working practices identified as solutions for increased reuse are (1) materials inventories, (2) targets for reuse, (3) circular building design, (4) planning for reuse, (5) incentives for reuse in procurement and (6) long-term documentation strategies enabling future reuse. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd.

The building design process is crucial in efforts to implement energy-efficient practices by adopting Energy Efficiency Measures (EEMs). However, design choices based solely on reducing operational energy use can significantly increase a building's embodied energy and Life Cycle Energy (LCE) use, because there is a trade-off between embodied and operational energy. This article presents a case study in which multi-objective optimization was used to explore the effects of various EEMs on the aforementioned trade-off. Optimal solution(s) for six different building shapes (rectangular, H-, U-, l-, T- and cross-shaped) based on two sets of EEMs were investigated and compared. The first set of EEMs consisted of EEMs that can be implemented or modified during the early design phase, such as the building's shape, orientation, Window to Wall Ratio (WWR), and constituent materials. The second set comprised EEMs that can be implemented later in the design phase (i.e. EEMs relating to the constituent materials). The LCE reductions achieved by finding optimal solutions for EEMs in the first set (ranged from 2175.2 to 3803.8 GJ) were significantly (over 5 times) higher than those achieved for the second set (ranged from 418.6 to 625.6 GJ) for all building shapes. Moreover, LCE use for pre-optimization building designs varied significantly with building shape. However, after optimization, the differences in LCE use between the optimal solutions of different building shapes were modest. This means that designers and construction companies can select building shapes based on customer requirements, but also highlights the importance of using multi-objective optimization during early design process to identify optimal combinations of EEMs that minimize LCE use.

Virtual design tools and methods can aid in creating decision bases, but it is a challenge to balance all the trade-offs between different disciplines in building design. Optimization methods are at hand, but the question is how to connect and coordinate the updating of the domain models of each discipline and centralize the product definition into one source instead of having several unconnected product definitions. Building information modelling (BIM) features the idea of centralizing the product definition to a BIM-model and creating interoperability between models from different domains and previous research reports on different applications in a number of fields within construction. Recent research features BIM-based optimization, but there is still a question of knowing how to design a BIM-based process using neutral file formats to enable multidisciplinary optimization of life-cycle energy and cost. This paper proposes a framework for neutral BIM-based multidisciplinary optimization. The framework consists of (1) a centralized master model, from which different discipline-specific domain models are generated and evaluated; and (2) an optimization algorithm controlling the optimization loop. Based on the proposed framework, a prototype was developed and used in a case study of a Swedish multifamily residential building to test the framework’s applicability in generating and optimizing multiple models based on the BIM-model. The prototype was developed to enhance the building’s sustainability performance by optimizing the trade-off between the building’s life-cycle energy (LCE) and life-cycle cost (LCC) when choosing material for the envelope. The results of the case study demonstrated the applicability of the framework and prototype in optimizing the trade-off between conflicting objectives, such as LCE and LCC, during the design process.

Green roofs are complex technology systems, adopting a vegetation layer on the outermost surface of the building shell. A proper design implement environmental and energy benefits. Green roof are aimed to reduce roof temperature and thus the summer solar gains, without worsening the winter energy performance. Most studies evaluating green roof performance have been conducted in warmer climates. There are very limited studies of green roofs in cold climate. Some research has investigated the thermal effect of the snow layer on green roof. But no study has so far evaluated the energy performance of green roof in sub-arctic climate. This study evaluates the heat flow and thermal effect on a green roof situated on a passive house building in the sub-arctic town Kiruna, Sweden for a period from 25th of October—4th of January. The ongoing measurements of temperature and heat flux is done on an extensive green roof and compared to the same roof covered solely by a roofing felt layer. The fluctuation in temperature was consistently higher for the roof with the roofing felt layer than for the green roof. But the surface temperature of both roofs was getting more and more align as the roofs are covered by snow during November and December. However during December month the green roof had a higher heat flux out of the building compared to the black roof.

Design choices with a unilateral focus on the reduction of operational energy for developing energy-efficient and near-zero energy building practices can increase the impact of the embodied energy, as there is a trade-off between embodied and operational energy. Multi-objective optimization approaches enable exploration of the trade-off problems to find sustainable design strategies, but there has been limited research in applying it to find optimal design solution(s) considering the embodied versus operational energy trade-off. Additionally, integration of this approach into a Building Information Modeling (BIM) for facilitating set up of the building model toward optimization and utilizing the benefits of BIM for sharing information in an interoperable and reusable manner, has been mostly overlooked. To address these issues, this paper presents a framework that supports the making of appropriate design decisions by solving the trade-off problem between embodied and operational energy through the integration of a multi-objective optimization approach with a BIM-driven design process. The applicability of the framework was tested by developing a prototype and using it in a case study of a low energy dwelling in Sweden, which showed the potential for reducing the building’s Life Cycle Energy (LCE) use by accounting for the embodied versus operational energy trade-off to find optimal design solution(s). In general, the results of the case study demonstrated that in a low energy dwelling, depending on the site location, small reductions in operational energy (i.e. 140 GJ) could result in larger increases in embodied energy (i.e. 340 GJ) and the optimization process could yield up to 108 GJ of LCE savings relative to the initial design. This energy saving was equivalent to up to 8 years of the initial design’s operational energy use for the dwelling, excluding household electricity use.

Buildings account for 40% of all energy use in European countries. The European Union (EU) therefore encourages member states to adopt Energy Efficiency Measures (EEMs) and implement energy-efficient practices during building design to minimize the energy use of buildings. However, recent studies have shown that energy-efficient buildings may not always outperform conventional buildings in terms of Life Cycle Energy (LCE) use. This is mainly due to the trade-off between embodied and operational energy, and a reliance on EEMs that reduce operational energy while sometimes increasing embodied energy and LCE use. To improve buildings’ environmental performance, the impact of different EEMs on buildings’ energy use needs to be assessed from a lifecycle perspective, and methods for identifying optimal combinations of EEMs that minimize LCE use should be developed. Ideally, these methods should be integrated with building information modelling (BIM) to enable seamless data exchange and to help Architecture, Engineering and Construction (AEC) practitioners make optimal design decisions relating to EEMs. The work presented in this thesis had two overall objectives: (1) to explore the scope for developing BIM-supported method(s) for assessing and optimizing the impact of EEMs on buildings’ LCE use during the design process, and (2) use the BIM-supported method(s) for exploring the impact of various EEMs that are implemented and modified during the building design process on the buildings’ LCE use.

The work presented in this thesis is based on an exploratory research design involving iterative cycles of (1) problem identification, (2) method development, (3) method examination, and (4) theory suggestion. In step 1, problems were identified by conducting literature studies and workshops with AEC practitioners, and analyzing archival data. In step 2, prototyping was used to develop methods to overcome the identified problems. In step 3, the applicability of these methods (or prototypes) was tested in case studies on actual and hypothetical building projects. Three case studies were conducted – one dealing with a low energy dwelling located in Kiruna, Sweden; another dealing with a multifamily residential building in Uppsala, Sweden; and a third dealing with a hypothetical multifamily residential building in Stockholm, Sweden. In step 4, the results were compared to existing theories to strengthen existing knowledge and identify previously unrecognized findings.

In relation to the first objective, the results obtained show that the factors and activities required to develop BIM-supported method(s) for assessing and optimizing the impact of EEMs on a building’s LCE use during the design phase are:

• A database that stores external and building project data (e.g. BIM data) and links it to be used for assessment and optimization, providing access to the data whenever needed.

• The development of interfaces using middleware applications to ensure interoperability and seamless automated exchange of information between BIM and other systems.

• Predefined objects (i.e. building part and component recipes) that are stored in a database and linked to inventories and Environmental Product Declarations (EPDs) for the relevant materials, enabling assessment of the buildings’ embodied energy and LCE use.

• The application of multi-objective optimization techniques (e.g. Pareto-based genetic algorithms) to identify optimal solution(s) for EEMs that minimize (optimize) the building’s LCE use.

In relation to the second objective of the thesis, the results obtained indicate that:

• EEMs that are implemented and modified during the detailed design phase have much less influence on the building’s LCE use than those implemented in the early design phase. Highly influential EEMs related to the early design phase which were tested herein were the building’s shape, orientation, Window to Wall Ratio (WWR), and the selection of materials used in the building envelope.

• Generally, thickening roof insulation has a strong beneficial effect on LCE use for buildings in Sweden.

• For buildings using energy sources with high primary energy factors, the most effective way to reduce LCE use may be to implement many EEMs that reduce operational energy use. However, this approach may be less helpful for buildings using greener energy sources because in such cases the embodied energy may have a greater effect on the final LCE use.

• The embodied energies of materials in the same class can vary significantly between suppliers. Such differences in embodied energy can be identified by considering the suppliers’ EPDs, the energetic contributions due to their mode of transportation from the site of production, and the distance between the site of production and the construction site.

• If the developed optimization approach is used to identify optimal combinations of EEMs in the early design phase, designers can freely choose from a wide range of building shapes without greatly affecting LCE use. However, without early phase optimization, designs that use different building shapes may exhibit significantly different LCE use values.

The results provide both theoretical and practical contributions that may be useful to researchers and AEC practitioners seeking to develop BIM-supported design processes and to reduce buildings’ LCE use by adopting appropriate EEMs. The results also show that embodied energy can be a major component of a building’s LCE use if the building’s design relies heavily on EEMs designed solely to reduce operational energy use. Policy makers and governmental bodies are thus advised to update regulations and building codes to reflect the importance of embodied energy so as to minimize the LCE use of new and retrofitting building projects.

Evaluation of carbon impacts during building design has for too long unilaterally focused on the operational carbon impacts through the application of Energy Efficiency Measures (EEMs), e.g. enhancing the thermal resistance of the building envelope by using additional insulations, Window to Wall Ratio (WWR) etc. Research indicates that there is a need to also include the embodied carbon impacts and optimizing the trade-off between embodied and operational carbon impacts. Multi-objective optimization approaches can be a solution for handling this trade-off. Therefore, a previously developed BIM-based multi-objective optimization approach has been extended to also cover the impact of the carbon footprint. The extended optimization approach was then tested in a case study of a multifamily residential building located in Stockholm to find the optimal design solutions of the embodied versus operational carbon impact trade-off. The results of the case study demonstrate the applicability of the extended approach in handling the trade-off problem and aiding in more environmentally friendly decisions during the design process.