Keywords

1 Introduction

The built environment is known as a significant contributor to both sustainability problems and solutions [1]. In such a context, the growing consensus about three facts is of paramount importance leading to progressive efforts in providing comprehensive standards and guidelines for the Life Cycle Sustainability Assessment (LCSA) in the building sector. First is the perception of sustainability as a multidimensional, interdisciplinary, and dynamic science. It requires continuous research to deliver a balanced understanding among various dimensions, including environment, economy, and social dimensions [2, 3]. The dynamism among sustainability pillars and their inherent intricacies demands providing up-to-date standards and guidelines as an indispensable requirement of the assessment works and continuous methodological development and improvement [3,4,5].

Second is the fact that the expansion of the building sector in response to the growing needs of housing and urbanization trends shows that the building sector is a key role player to achieve the sustainability targets in the present and the future [6, 7]. In the same context, the large share of existing buildings discloses the significant potential of building refurbishment strategies to reach sustainability in this sector [8].

Last but not least is that the building sector can no longer be considered as lineated life products. The building sector’s life span is now being studied in the cradle to grave circular scheme by which its sustainability must be evaluated with a whole life cycle perspective [1].

However, various building sustainability assessment frameworks and standards have been released worldwide, a survey on their implementation level in the recent scientific publications is worthy of investigation. This research aims to review and discuss recent scientific publications in LCSA on building energy retrofitting. The goal is to enlighten the extent to which the current standards have been employed in the reviewed publications, the missing aspects (not developed in the standards), and propose scenarios for development and methodological implementation.

To achieve the purpose mentioned above, the published research papers in the field of LCSA in building energy retrofitting are critically reviewed and discussed with a focus on the scope and indicators coverage, the adopted assessment methodologies, weighting, and aggregation methods among LCSA pillars and the final decision-making procedures. The papers are reviewed in four categories containing LCA, LCC, SLCA, and multidimensional LCSA studies where the limitations and advances are critically discussed.

The initial results of the present review highlight that the main challenges in the published research papers could be attributed to (1) lack of required databases, (2) quantification and measurement problems in LCSA impact categories, (3) lack of including impact categories and indicators suggested by standards, and consequently (4) an unbalanced level of development in LCSA pillars evaluation. Also, the level of information provided in each study, both as the input data and the final results, do not match the standards recommendations. Moreover, the development of SLCA assessment methodologies and the synthesis among LCSA pillars through weighting and aggregation are found as vivid obstacles of LCSA application in the literature. These findings along with more issues found in this review, enlighten and explain the critical challenges of LCSA standards implementation in building energy retrofit studies. The data and information management, alongside the considerable computational time required for the in-depth assessment, are the main obstacles in applying LCSA in building energy retrofitting.

In this chapter, the root and evolution of the concept of sustainability over the last decade are studied. Later on, the advent of life cycle sustainability assessment in the building sector and its integration into decision-making methods in building design is reviewed and analyzed. Afterward, The application of LCSA in building energy retrofitting is critically discussed to highlight the main challenges and emerging opportunities in this field of study. The chapter continues with a detailed classification of the main observed challenges of LCSA implementation in building and energy retrofit design. In the end, after an in-depth review, the development of integrated frameworks coupled with optimization models and the integration of Building Information Modeling (BIM) is discussed as promising solutions for implementing LCSA into building and energy retrofit design.

2 Sustainability and Development; The Roots and Evolution

Although the term sustainability is widely used, there are still ambiguities and complexities in the concept of sustainability and sustainable development [9, 10]. This vagueness has been discussed over the years, and it is still being addressed in the academic environment. One possible reason that leads to these complexities is the fact that both sustainability and development are not static and have been evolving in response to the existing dynamism between society and nature [3,4,5]. The concept of sustainable development is initially driven from economic discipline in [11], where the concerns were about the capacity of limited natural resources to support the increasing human population. According to the Scopus database, the term sustainability was found in 70th, when it first emerged in the scientific literature of economic studies [11], however, some previous studies indicate that the use of this term dates back to a monograph published in 1713 to address the sustainable use of forest resources [2, 12].

As described in dictionaries, development refers to the gradual growth to become more advanced [13]. To clarify this general definition, several theories and interpretations have been proposed by scholars in different fields. One of the definitions collected by [5] elaborates development as a multidimensional process in which major changes in social structures, attitudes, and institutions as well as economic growth, inequality reduction, and poverty eradication are involved. Regarding the historical definitions, the term sustainability primarily addresses the economic-environmental aspects, while development is more oriented to socio-economic issues. Therefore, sustainable development could be interpreted as a concept addressing social, economic, and environmental issues. A similar interpretation is now widely accepted and used.

It is possible to track the efforts to interpret and standardize the term sustainability or sustainable development in the twentieth century. The United Nations conference on the human environment held in Stockholm, Sweden, in 1972, is known as the first international conference to deal with the concept of sustainability [14]. In the declaration of the Stockholm conference, 26 principals were agreed concerning human rights and responsibilities with respect to the social, environmental, and economic aspects. These principles demand an internationally collaborative action plan to achieve sustainable development principles worldwide. In this conference, 109 recommendations were provided to determine how the international participant should effectively regulate their actions to protect the human environment [15].

The World Commission on Environment and Development (WCED) provided the first definition of sustainable development in 1987. In the draft published by WCED, Sustainable development was defined as a development that meets the needs of the pursuant without compromising the ability of the future generations to meet their needs. This definition considers the limited ability of the environment to provide the present and future needs of humanity while highlighting that the economic and social requirements in all countries must also be defined in terms of sustainability [16].

An important UN Conference on Environment and Development (UNCED) was held in Rio de Janeiro, Brazil, in 1992 [17]. It is known as the first attempt to implement sustainable development from concept to an international action plan [12]. In the 4th principle of the Rio declaration, environmental protection is emphasized as an integral part of development. The 5th principle refers to eradicating poverty and standard of living as indispensable social requirements of sustainable development. The 12th principle promotes a supportive and open international economic system leading to economic growth for better addressing the problems of environmental degradation [18]. An overall review of the Rio declaration principles shows that environmental issues are the main concerns and the core of this declaration since most of the principles have aimed to promote practical environmental protection actions. Later in 2002, in the World Summit on Sustainable Development held in Johannesburg, South Africa, the balance between economic development, social development, and environmental development as interdependent and mutually reinforcing pillars of sustainability were reaffirmed [19].

Regarding the conflicts among three sustainability pillars and the unequal or insufficient progress in the three dimensions of sustainability, the United Nations Conference on Sustainable Development, Rio + 20 was held in Rio de Janeiro, Brazil, in 2012 [20], emphasizing the balance among sustainability pillars. In the report of this conference entitled “The future we want”, poverty eradication is recognized as the greatest global challenge facing the world and an indispensable requirement for sustainable development [21]. In this report, the concept of the green economy is recognized as an essential tool that is available for achieving all pillars of sustainable development. A particular focus on the social aspect highlighted in this conference was also among the Millennium Development Goals, where six goals out of all eight proposed sustainable development goals were oriented to the social dimension of sustainability [22].

The following United Nations Sustainable Development Summit was held in New York in 2015. The resolution adopted by the General Assembly in UN on 25 September 2015 entitled “Transforming our world: the 2030 agenda for sustainable development, changed the traditional concept of sustainable development fundamentally [12] and set out 17 areas of sustainable development goals [23]. These areas are known as the last versions of Sustainable Development Goals (SDGs) declared by United Nations. The year 2015 was a distinguished historical point when the UN set out the 17 SDGs. Not only this step forward for better understanding SDGs and providing the bases of intergovernmental collaboration, but also the Paris Agreement on international effort to increase the abilities of countries in controlling the impacts of climate change [24], have been considered as the historical human efforts to build a more sustainable future.

As elaborated in this section, the definitions of sustainability and development have been subjected to several changes in their meaning and priorities over the last decades. The dynamism and evolving interaction between human society and the natural resources as a complex system could be recognized as the main reason for changing interpretation to define meanings and priorities in sustainability and development.

3 Sustainability Assessment of Buildings—A Life Cycle Approach

The concept of sustainable development targets all human activities and aspects of life and is expected to be adopted by public policy makers to regulate the socio-economic aspect of worldwide activities. It is particularly promoted and applied to address the issues related to the design of the built environment in the last decade [25].

The increasing need for housing in human societies resulting from population growth has led to a rapid expansion of the built environment [26]. The share of the building sector in final energy consumption and GHG emission are increasing worldwide. According to the statistics, the building sector is accounted for 36 and 39% of the final energy consumption and CO2 emission globally [27]. These values have been estimated at 40 and 32% in European Union (EU), respectively [28].

Given the noticeable contribution of the built environment expansion to the environmental impacts [6, 7], economy, and societies [29] as three pillars of sustainable development [30], growing attention to this issue is now emerging in academies, industries, and policy programs. The increasing awareness about the building sector's considerable impacts on sustainability targets resulted in establishing standards and guidelines to reduce the environmental impacts in this sector. In this context, both the economic and social performance of the building sector has been pursued by emerging studies, as well as the environmental performance, to provide harmony and balance among three life cycle sustainability pillars [1]. However, the social dimension is the least addressed aspect of building sustainability in the literature [31], mainly due to simplifying the sustainability concept in buildings and reducing it to merely environmental sustainability. The terms sustainability and green buildings have been in use interchangeably in building science literature [31]. Consequently, the initial understanding of the term “green” as “building design strategies that are less environmentally and ecologically damaging than typical practices” [32], as well as the fact that environmental performance has been better surveyed and standardized [33], could be recognized as the main reasons explaining why all three sustainability dimensions are not equally developed and investigated in the building science literature.

Like the general concept of sustainability, the definition of sustainability in buildings has experienced various interpretations and evolution over the last decade. However, at least three sustainability pillars, such as environment, economy, and society, are now recognized as the widely accepted interpretation; the value judgment among these three pillars is still controversial. Looking at Green Building Rating Systems (GBRSs) such as LEED and BREEAM, the dominancy of a tendency to the environmental interpretation of green or sustainable building is observable [32].

On the other side, several guidelines have been published to standardize the assessment method of the sustainability in buildings with a life cycle approach such as BEES models [34] or the EN standards, including the framework of building sustainability assessment [35], the framework of environmental [36], social [37], and economic performance assessment [38]. However, these methods provided useful methods to measure the building performance regarding the sustainability pillars, but do not address how to make decisions systematically among alternatives with different environmental, economic, and social performances. For instance, BEES models propose a weighted-sum approach to assign a final index to each alternative based on its environmental and economic performance but stay silent about the weighting methods between economy and environment. Likewise, the EN standards have standardized the calculation methods to measure the environmental [39], economic [40], and social performance [41]; they do not clarify how the decision maker should compare different alternatives having conflicting results for each sustainability pillar.

The sustainability pillars in buildings are still being developed and discussed. For instance, looking at GBRSs, there are various aspects and credits, such as the integrative process in LEED or technical quality and process quality in DGNB, that cannot be attributed to the three traditional sustainability pillars. Likewise, recently a fourth dimension has drawn researchers’ attention in the literature as institutional dimension [42, 43] that is defined as “the results of interpersonal processes, such as communication and co-operation, resulting in information and systems of rules governing the interaction of members of a society” [32].

The various interpretations of sustainability and the lack of accurate definition and calculation methods to quantifiably measure the sustainability pillars show that the sustainability assessment and life cycle sustainability assessment [44] in buildings are still open challenges that need to be more surveyed in the future studies.

4 Life Cycle Sustainability Assessment in the Decision Context—Challenges and Opportunities of Decision-Making Models in Building LCSA

The term Decision-Making (DM) model first emerged in the scientific publication of political science in 1959 [45, 46]. The application of this concept then got increasing attention in other fields as well. As a piece of evidence, the number of scientific publications referred to decision-making models/methods has increased from 2 to more than 15,500 between 1952 to 2020, with a significant growth rate over the recent years. As much as more complicated criteria entered human life, the higher necessity of comprehensive methods to make intelligent decisions is perceived. As a result, the application of DM methods is now widely accepted and is spreading to all fields from very early practice in politics [45] to recent implementation in advanced technologies [47].

Decision-making models are known as the most important application of mathematics in various human activity fields [48]. The necessity of advanced decision-making models arises when at least two assessment criteria exist, and these criteria are contradictory, or the solutions need a value judgment by stakeholders who might have conflicting interests [49].

Facing the global questions that encompass conflicting criteria, multiple diverse goals, contradictory interests, and targets with several different perspectives, Multi-Criteria Decision-Making Models (MCDMs) have been widely implemented to find the appropriate answers to contradictory questions [50]. Sustainability is of those areas that MCDMs models are applied to find comprehensive optimal solutions [51]. As already mentioned, sustainability appeared in the scientific literature in the 70th decade, while the first implementation of a DM model into the sustainability studies dated back to 1997, where it was applied to address the sustainability of future perspective of Swedish urban water systems [52].

Decision-making models in building life cycle sustainability assessment is a very new field of study compared to the comparatively short history of building LCSA. It also shows that building sustainability and life cycle sustainability of buildings were initially developed without taking all the benefits delivered by DM models. However, as LCSA and sustainability assessment include a higher level of complexity and a broader definition over the preceding years, more attention to implementing DM models emerges in the literature.

Amon all MCDM methods, several reviews concluded that AHP is the most popular and applied method in the literature [53, 54]. A study performed by [55] on MCDMs in sustainable energy development issues highlighted that AHP followed by TOPSIS is the most popular multi-criteria decision-making method in the literature. This fact is also confirmed in our review of few papers published in the field of MCDMs in building life cycle sustainability assessment between 2010 to 2020. Table 1 summarizes the features of recent publications that have applied DM models in building life cycle sustainability starting from 2010 to 2020. In this review, those publications that applied decision-making models in building LCSA were reviewed to highlight the coverage level of LCSA pillars and find the most utilized decision-making methods. As shown in Table 1, most reviewed papers included all three sustainability pillars to evaluate the performance of different types of building design solutions such as structural systems and materials, HVAC systems, and building technologies.

Table 1 The features of the recent application of DM models in building LCSA studies
Full size table

Analytical Hierarchy Process (AHP) is found as the most applied MCDM method within the reviewed papers, while some authors have proposed hybrid DM methods to overcome the drawbacks of the single techniques in their studies [56, 57]. AHP was firstly developed by [58]. According to its developer, AHP is defined as “a theory of measurement through pairwise comparisons and relies on the judgments of experts to derive priority scales. Saaty [59] proposed to decompose the decision process into four steps by which it would be possible to apply AHP in making decisions. These steps are [59]: (1) Definition of the problems and determine the kind of knowledge, (2) Structuring the decision hierarchy, (3) Constructing the pairwise comparison matrices, and then (4) Using the obtained weights to define the overall priority. AHP is known as a widely accepted and effective method to support decisions in the complex decision-making process by reducing the problems’ complexity through transforming complicated problems into a set of simple comparisons and rankings [57], and increases the transparency and objectivity of decision-making as well as facilitating the detection of controversial items and providing data for establishing agreements [49].

Despite the advantages of the AHP method, one challenging issue associated with this method is that different hierarchies of criteria may affect and cause changes in weight allocations [55, 60]. Cinelli et al. [61] have concluded that although AHP is simple to understand and is well-supported by tools, as a drawback, it is cognitively demanding for decision makers’ perspectives.

AHP assumes a full compensation among the criteria that means a low performance in one criterion could be entirely compensated by the high performance of other criteria [61]. While AHP is found as the most applied MCDM method to determine weights of criteria, TOPSIS is known as one of the most popular methods to rank alternatives in a decision-making process, thanks to its straightforward application [55]. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as developed by [67] is based on the concept that the selected alternative must have the shortest distance to the positive ideal solution while keeping the longest distance from the negative ideal solution [57]. Although TOPSIS is highly appreciated due to its easy application in problems with different sizes, some of its disadvantages are also addressed in the literature, such as not considering the correlation of attributes and its difficulty to weight attributes and keep the consistency of judgments [68].

These facts as fundamental critics about the most applied MCDMs in sustainability studies partially show why integrating MCDM methods in this research field could be called an open challenge. It is important to note that this paper does not aim to review all MCDM methods; in fact, the pros and cons of the most popular methods have been briefly discussed to understand the most common challenges of implementing decision-making models in sustainability assessment.

5 Implementing Life Cycle Sustainability Assessment in Buildings—The Case of Building Energy Refurbishment

This section reviews the published papers that addressed at least one dimension of life cycle sustainability assessment in building energy retrofitting to understand the methodological advancement, limitations, and challenges in this topic. Therefore, all the relevant papers published and indexed in Scopus and Elsevier until 2020 were retrieved and initially classified into three rubrics, including LCA, LCC, and SLCA studies. These papers are analyzed to clarify the adopted methodologies in each paper to provide a clear picture of the state of the art.

Figure 1 represents the number of papers published between 1989 to 2019 and their distribution around the world. As it is shown in this figure, the publication in this field is increasing fast during preceding years. The European countries, led by Sweden, Italy, Spain, and Portugal, followed by United States, Canada, and China, have the largest share in the research and publication of this field. The lack of LCSA research in several countries underlines that this research field is still not applied worldwide despite its significance in understanding global sustainability issues.

Fig. 1
figure 1

Cumulative number of publications and their distribution in the world

Full size image

5.1 LCA in Building Energy Retrofitting; A Review on Methods and Assumptions

Different assumptions and limitations in LCA studies make them difficult to be compared and interpreted against each other. A review is needed to be performed to highlight these assumptions, challenges, and new advancements within the research works related to LCA of building energy retrofit. This review provides essential bases to develop a comprehensive methodological framework for the application of LCA in building energy retrofit design.

Those papers that addressed the LCA of building energy retrofitting in the title or abstract were collected. By reviewing methods and materials in each paper, the challenges of LCA in building energy retrofit are discussed in this section. This part focuses on investigating uncertainties, inconsistencies, challenges, and methodological advances in LCA application in energy retrofit projects. These challenges might affect the reliability and comparability of LCA studies. Reviewing the assumptions and solutions in previous studies will provide a better perspective on how each LCA study could be integrated into the decision-making process of an energy retrofit design project.

One reported issue in previous LCA studies is how to standardize functional unit (FU) in LCA [69] of energy retrofitting which will be reviewed and discussed in this section. The different functional unit has been used in the reviewed papers. In the present review paper, four different kinds of functional units are found:

  1. 1.

    The energy demand/ consumption to provide the required level of thermal comfort [70].

  2. 2.

    The quantity of used materials in a system [71].

  3. 3.

    The unit of area or volume of the refurbished building [72].

  4. 4.

    The whole building under LCA [73].

According to the LCA standards, the functional unit must be clarified in the assessment report. In this review, we realized that some authors have not clearly shown the functional unit in their works, making their results impossible to be compared with other studies [39].

It is reported that the most popular system boundaries in LCA studies are cradle to grave [74]; this statement is also concluded and confirmed in the present review. Some researchers have limited the system boundary of the study solely to the overwhelming life cycle phases [75,76,77]. For instance, Mangan and Oral [78] limited their analysis to the production stage and use stage due to the lack of data in demolition and end-of-life stages. The system boundary limitation in the research is justified by the fact that previous studies have proven that these eliminated stages (demolition and end of life) have nearly 1 percent of total energy consumption in a building life cycle.

Some other researchers have included the whole building life cycle following the EN 15,978 standard [73, 79,80,81]. Regarding the reviewed papers in this section, it is found that most researchers have used the whole life cycle phases in their studies, while the lack of databases alongside the negligible impacts are seen as the main reasons and justification for excluding some life cycle phases in the rest of the reviewed papers. An interesting research by Oregi et al. [82] showed a simplified LCA in which only the production and operation phases are covered could provide accurate results in designing energy retrofit scenarios.

LCI is known as one of the most complicated steps of an LCA study because of the vast numbers of inputs and missing data on materials and building components’ environmental performance. In this review, some databases, such as Ecoinvent and EPDs, as well as existing literature or specific data reported by manufacturers, are found as the most common databases (Fig. 2). According to Oregi et al. [80], since different databases may have been prepared using various assumptions, it is essential to pay attention to the possible inconsistency of databases used in research.

Fig. 2
figure 2

Life cycle inventory databases used in the reviewed papers

Full size image

Several environmental impact categories and indicators are proposed by LCA standards [39]; however, most published papers have only evaluated a small number of environmental impacts. It is stated that energy and global warming potential (GWP) is the most surveyed key performance indicator in previous studies; however, it is worthy of focusing and reviewing papers that have taken into account more indicators and study how they have been compared against each other. Most of the reviewed papers have only analyzed less than three environmental impact categories mainly due to simplifying the data acquiring procedure. Global warming potential and energy are the most evaluated impacts, as illustrated in Fig. 3.

Fig. 3
figure 3

Number of research papers that addressed each environmental impact. Note Energy refers to cumulative energy demand, non-renewable primary energy, embodied energy, life cycle energy and gross energy requirement

Full size image

De Larriva et al. [70] included two environmental indicators, Gross Energy Requirement (GER), and Global Warming Potential (GWP). They have stated that since the LCA is increasingly motivated by the climate change debate, they have chosen these two indicators.

The environmental impact categories in the study performed by Garcia-Perez [71] are limited to global warming potential and embodied energy. Ghose et al. [72] selected twelve environmental impacts recommended by EN 15,978 such as global warming potential, ozone depletion potential, photochemical oxidation potential, acidification potential, eutrophication potential, abiotic depletion (resources and fossil fuels) according to the CML impact assessment method. They also used UseTox method to evaluate human toxicity carcinogenic, human toxicity non-carcinogenic and ecotoxicity freshwater and ILCD 2011 + ReCipe method for particulate matter formation and ionizing radiation. The selection of these categories is in line with national recommendations in New Zealand, as they reported. In contrast, Mangan and Oral [78] and Marique and Rossi [79] only focused on life cycle energy and CO2 emission. Oregi et al. [80] included only NonRenewable Primary Energy resources in their life cycle impact category. Valancius et al. [77] also included limited environmental indicators such as nonrenewable primary energy and CO2 emission. Indicators in the study performed by Tadeu et al. [83] are limited to nonrenewable primary energy and greenhouse gas emissions over the building's life cycle.

For simplicity, Oregi et al. [82] considered only one indicator, which is “Use of nonrenewable primary energy sources.” Managn and Koclar Oral [76] only took into account LCE and LCCO2. in their study. In the analysis performed by Valacius, Vilutiene, and Rogoza [77], only CO2 emission and nonrenewable primary energy consumption over the building life cycle are taken into account. The research performed by Nydahl et al. [81] is focused on two environmental impact categories, including life cycle energy use and greenhouse gas emissions. Beccali et al. [73] considered six environmental impact categories at the level of mid-point indicators, including Cumulative Energy Demand (CED), Global Warming Potential (GWP), Ozone Depletion Potential (ODP), Acidification Potential (AP), Eutrophication Potential (EP), Photochemical Ozone Creation Potential (POCP).

The above-mentioned examples also confirm that, although most researchers have followed the LCA standards to calculate environmental impacts, only a few papers have analyzed all proposed environmental impacts by LCA standards. This limitation is mainly due to the lack of databases or with the aim of simplifying the calculation steps, which hopefully will be resolved by developing LCI databases and advancing the LCA software to facilitate the calculation process for non-expert users.

Finally, in some of the reviewed papers, some criteria that are almost neglected in the literature such as the different energy mixes in the future, have also been considered. Ghose et al. [72] have taken into account different energy mixes since, according to national energy programs, the share of fossil fuels is predicted to be reduced by implementing renewable energy sources in New Zealand.

5.2 LCC in Building Energy Retrofitting; Indicators and Economic Parameters

This section concentrates on the application of Life Cycle Cost (LCC) as a well-established method for the analysis of the economic performance of buildings [8, 84, 85]. The main parameters of LCC analysis in selected reviewed papers are discussed in this section, including the LCC indicator and economic parameters such as discount rate and energy price inflation rate in each paper.

Several economic indicators such as Net Present Value (NPV), Payback Period, Net Saving or Net Benefit, Saving to Investment Ratio, and Adjusted Internal Rate of Return are proposed by relevant standards [40]. Our review showed that NPV is the most used economic indicator in the reviewed papers (Fig. 4). Other economic indicators such as Value at Risk, Energy productivity, Net Present Cost, Net Saving, Saving to Investment Ratio, Adjusted Internal Rate of Return, Simply Pay Back Period are also adopted in different papers.

Fig. 4
figure 4

Number of research papers that addressed each LCC indicator, Var: Value at Risk, AIRR: Adjusted Internal Rate of Return, NS: Net Saving, EP: Energy Productivity, PPT: Payback Period Time, CAGR: Compound Annual Growth Rate, SIR: Saving to Investment Ratio, IRR: Internal Rate of Return, NPV: Net Present Value

Full size image

Taking accurate Discount Rate (DR) and Inflation Rate (IR) values is of paramount importance in economic assessments. A wide range of values both for the discount rate and inflation rate is found in the reviewed papers, while the EN 16,627:2015 proposes using the discount rate equal to 3 percent for the sake of comparability of the results of LCC studies. Some researchers have compared the LCC results by taking various values for discount and inflation rates in their studies [86,87,88,89,90]. For instance, Copiello, Gabrielli, and Boniaci [91] reported that the discount rate might affect the results four times as much as the energy price. They also mentioned that the discount rate might also affect the energy retrofit project by encouraging owners for higher initial investment. Our analysis shows that the values taken by researchers are usually higher than the 10-year average values which are reported by the countries.

As shown in Fig. 5, the minimum and maximum values of the discount rate applied in the research papers are higher than the actual average value of the discount rate in each country. Although it is worthy of investigation to analyze the influence of various DR values in research works, it is recommended to adopt the macroeconomic values according to the actual economic situation of the study project. Moreover, in compliance with the EN standards taking similar DR values in LCC studies in the building sector increases the comparability of the results. In case the researchers aim to conduct sensitivity analysis to evaluate the impact of the different economic situations on their project, the economic parameters should also represent the actual values in the projects’ economic contexts and the relevant standards (e.g., Italian studies in Table 2, Figs. 5 and 6).

Table 2 Summarizes the economic parameters applied in selected LCC studies in each country.
Full size table
Fig. 5
figure 5

The minimum, maximum discount rate (%) applied in the LCC studies in each country versus the 10-year average discount rate of the countries

Full size image
Fig. 6
figure 6

The minimum, maximum Energy Price Inflation rate (%) applied in the LCC studies in each country versus the 10-year En-PIR of the countries (the average of gas and electricity price for end-user in residential buildings)

Full size image

Regarding the values of discount rate and energy price inflation rate, Fig. 7 represents important information about the reviewed papers. As it is illustrated, most research works are performed with an energy price inflation rate lower than the average in all papers. However, a variety of discount rate values are considered in papers. Figure 7 shows that the papers published in different countries tend to conduct LCC analysis with a combination of low to a medium value of inflation rate and medium to high value for discount rate.

Fig. 7
figure 7

The average of discount rate versus the average of energy-price inflation rate adopted in selected LCC studies in each country

Full size image

5.3 SLCA in Building Energy Retrofitting; The Implementation Level

Any adverse or beneficial change to the society or the quality of life that could be expressed with quantifiable indicators is defined as SLCA impact with respect to the following categories in EN 15,643-3:2012 [37]: accessibility, adaptability, health and comfort, loading and neighborhood, maintenance, safety/security, sourcing of material and services, and stakeholder involvement.

In the present review, no published research paper is found which directly addresses the social dimension of building energy retrofitting with a life cycle approach in the title, abstract, or keywords. However, few papers are found in which some social indicators such as thermal comfort [117], human live risk [118], and social feasibility [119] are taken into account. Thermal comfort could be considered as a social aspect of building sustainability assessment according to EN 15,643-3:2012 since it affects occupants and users’ satisfaction levels. The studies performed by Assiego de Lavaria et al. [120] and Mostavi et al. [117] are of those few ones that have addressed one of the impact categories of social LCA in their assessment.

6 LCSA Challenges; A Classification of the Open Challenges and a Discussion on Emerging Solutions in the Literature

Several challenges are associated with sustainability assessment as a multidimensional interdisciplinary field of study [121]. However, taking a life cycle approach to sustainability assessment increases the study's comprehensiveness; it might result in a higher level of sophistication since more databases and assessment methods with a higher level of uncertainties and inconsistencies might be included in the analysis. Given the discussions in the previous sections and the research papers that addressed the sustainability assessment challenges within the last five years, the main challenges of measurement in life cycle sustainability assessment are presented and discussed in this section. Such a discussion helps to enlighten what aspects of LCSA need to be investigated and developed by further research works in the future.

The challenges associated with data collection and accessibility are constantly reported as one of the main obstacles in implementing life cycle sustainability assessment [1]. The required databases to conduct life cycle sustainability assessment are not readily available for specific materials, products, or services around the world [122,123,124,125,126,127,128,129] and the data acquisition procedure is not straightforward [126,127,128,129,130,131,132,133,134] due to the complexity of the data preparation and data-sharing challenges [124, 135]. Although databases have been developed during the last decade, the lack of data is still a barrier in this field. Moreover, the uncertainty caused by the missing data of emerging technologies alongside the uncertainties of measuring methods are known as important LCSA challenges [126, 134, 136,137,138,139].

A significant challenge of implementing LCSA is the fact that no consensus exists to establish or adopt a clear methodology to link the three dimensions of sustainability [1, 122, 129, 140,141,142,143]. The combination and harmonization among different metrics and measurement techniques [122, 139, 140, 143] alongside the different maturity levels of assessment methods for LCSA pillars [131, 136, 137, 144], specifically the weakness in developing the quantifiable measurement methods of the social dimension [127, 129, 131, 133, 134, 144,145,146] is of the most critical challenges in this field. Aggregating the LCSA pillars is a complex issue [1, 122, 126, 129, 136, 140,141,142] due to the challenges associated with selecting the suitable indicators [3, 122, 125, 127,128,129, 145], weighting [1, 44, 126, 134, 139, 146,147,148], normalization [44, 134, 142, 146, 148], and formulating life cycle sustainability [1, 129, 130, 133, 139, 149, 150].

As illustrated in Fig. 8, the associated challenges of measuring LCSA could be initially classified into six groups, including Data, Measuring methods, Aggregation, Indicator selection, Uncertainties, and Results. Further and future research works need to be conducted to resolve these challenges. Apart from the continuous efforts to standardize the measuring methods, to develop databases and reduce the uncertainty of the evaluations through methodological advancements, new trends in the literature are found to answer the challenges of integrating and facilitating LCSA in the building design process. The advent of developing integrated LCSA models and digitalization-LCSA nexus in the literature are examples of the new research trends aiming at providing solutions to ease the LCSA implementation in building and energy retrofitting design.

Fig. 8
figure 8

Classification of the existing challenges related to measuring life cycle sustainability assessment. The size of each section corresponds with the number of papers addressed each challenge

Full size image

6.1 Integrated LCSA Models—Multi-dimensional LCSA Studies and Application of Optimization Methods

The research works that have addressed more than one LCSA dimension have constantly been increasing over the last few years. Several authors have included LCA and LCC simultaneously in their analysis, such as Krarti and Dubey [151] evaluated the economic and environmental benefits of three levels of energy retrofitting for different building types, including residential, commercial, and governmental buildings. Ruparathna et al. [152] proposed a method to find the best energy retrofit scenarios of buildings by considering energy consumption, life cycle costs, and GHG emission. Some researchers proposed a conceptual framework for an integrated LCSA model using a weighted-sum approach that includes all three LCSA pillars [153, 154]. Implementing LCSA into energy building energy retrofitting is a multi-objective task for which optimization methods and algorithms to find the extremum values of multi-variable functions are used by several authors over the last years to resolve the complexity of this task [1, 155].

Table 3 summarizes the recent research papers that addressed more than one LCSA pillar and represents the indicators and optimization algorithms adopted in each study.

Table 3 Summary of integrated multidimensional LCSA studies
Full size table

Although several research papers have already been published addressing multidimensional life cycle sustainability assessment of buildings, our review showed that there are still challenges to be resolved. For instance, the lack of well-established quantification methods to measure SLCA is still a barrier to implement LCSA. Moreover, the lack of consensus on weighting methods for aggregating LCSA pillars is still an open challenge in this field. These challenges are expected to be resolved through future research on integration methods; however, it requires the development of LCI databases, measurement development, and standardization of LCSA pillars.

6.2 BIM-Based LCSA—A Solution for Data Management and Processing

Digitalization in the built environment and the application Building Information Modeling (BIM) are growing rapidly in the construction industry and can help and support the integrated design process through improving information management and cooperation between designers, producers, and end-users during the whole buildings’ life cycle stages [172,173,174,175].

Buildings consist of various components; this brings a massive amount of information and complexity to the design phase [176]. This is usually reported as the main reason for performing LCSA at the later project phases, where the complexity and uncertainties are reduced [177, 178]. BIM tools are capable of providing and present both graphical, numerical, and descriptive information of buildings in different levels of development (LOD) [179,180,181,182], which is an important requirement for applying an LCA during the design phase. It is also reported that the use of LCA methods in the building sector cannot be developed without developing the level of information in this sector, on the other hand, it is stated that the use of BIM for public buildings will be compulsory in the EU from October 2018 [182] and expected to be extensively used in the near future [173]. All these facts indicate that BIM-based life cycle sustainability assessment is a promising and indispensable solution to resolving data integration and management challenges.

Several researchers have addressed the application of BIM in building life cycle assessment. For instance, Malmqvist et al. [183] proposed BIM tools to overcome data analysis problems during the early stages of the design process. They indicated that in the early stages of design, there are many possible solutions and decisions to take, while the precise data which are required for the LCA calculations are usually available at the later design stages. To overcome this problem, speed up the LCA calculation process, and increase the accuracy and completeness of the evaluations, they suggested using BIM tools in the LCA-design process [183].

Many researchers have elaborated the necessity of BIM application in LCA and have tried to use BIM tools in an LCA process [181, 184,185,186,187]. Although many studies demonstrate the advantages and benefits of BIM-based life cycle assessment and the integration of BIM and LCA [187,188,189], serious challenges such as software integration or data requirements are still the main problems and barriers in this field [182]. The existing BIM tools are not capable of comparing different alternatives, also still suffer from data library limitations [74, 184, 186]. It is understandable that in order to make the BIM-LCA integration useful, the input data, assessment process, result acquisition, and interpretation must be as easily achievable as soon as possible, and the whole integrated assessment system must be user-friendly [182].

The integration between BIM tools and energy simulation software is not still fully developed. Also, data exchange between BIM and LCA tools is another critical issue. In some research works, automated produced bills of materials are imported into the excel sheets for the LCA calculation. Ajayi et al. [187], Basbagill et al. [190], Peng [184], and Houlihan et al. [191], as well as many other researchers, have used a manual process for data exchange between BIM tools and LCA tools or LCA calculation sheet in Excel. However, some plugins on Revit Autodesk make it possible to quantify environmental impacts in the BIM environment based on LCA methods [183, 193]. There is still a gap in software integration between BIM, LCSA, and energy simulation tools.

Another problem stated and confirmed by researchers is that BIM databases are not developed enough for the LCA process. Because of this problem, in most cases, the bill of material quantities and material properties are edited manually by the end-users [182].

Although the BIM concept is not effective in integrating building performance assessment into the sketch design phase due to the excessive required time for modeling [192], if the task is about implementing the LCSA in designing energy retrofit scenarios, BIM can significantly facilitate the assessment process, since many of design parameters have already been defined and the uncertainty is lower in energy retrofit design compared to the sketch and initial design phase.

To start an integrated BIM-LCSA design process, some questions must be answered first:

  1. 1.

    What are the design and assessment goals? The answer will determine what kinds of performance criteria must be assessed.

  2. 2.

    What is the assessment methodology, and what kind of assessment methodologies need to be integrated into BIM?

  3. 3.

    What kind of data and databases need to be integrated into BIM?

  4. 4.

    What is the required detail, accuracy, and completeness level for the performance assessment?

  5. 5.

    How should the result be reported, and in which way should they be processed and used?

As an example to answer one of these questions, Dupuis et al. [193] indicated that to be able to perform an accurate LCA study and achieve sound results, every data element should be at least at the LOD 350 detail level. Each BIM model at a lower level than LOD 350 means that some essential data for LCA calculation will be missed.

Although BIM-based LCSA is a promising solution to overcome the integration challenges of LCSA in building and energy retrofit design, there are still some challenges in applying this framework, such as availability of life cycle inventory (LCI) databases, software integration, and transferring building information between modeling software and LCSA tools. Given the rapid progress in developing design-assessment tools and LCI databases, it is expected that LCSA analyses would be possible to be performed in the BIM environment without using intermediary tools in the near future.

7 Conclusion

This chapter discussed how sustainability assessment has been developed from a single-dimension and environmental-oriented interpretation to a multidimensional interdisciplinary research field by reviewing its roots and evolution path over the last decades. Then we discussed how decision-making models have been integrated into life cycle sustainability assessment of buildings to facilitate the informed decision-making in the multi-objective design-assessment contexts such as building life cycle assessment. Through literature review on the implementation of LCSA in building energy retrofitting, we discussed the existing challenges of the life cycle sustainability assessment. We concluded that different assumptions such as various functional units, system boundaries, and lack of a wide range of standard environmental impacts result in complexities in the comparability of the reviewed research works. Moreover, the lack of LCI databases is known as the main obstacle of LCA application. Also, we showed that the level of documentation of some research works is lower than the recommendation by relevant standards, which need to be considered in future research works to enhance the readability and comparability of the results.

Regarding the LCC studies, we showed that Net Present Value is the most popular economic indicator used by several researchers to evaluate the economic performance of their retrofit design. Macroeconomic parameters such as discount rate and energy price inflation rate adopted in each paper were discussed, and we showed that the assumed values in the research papers are lower than the actual values in the economic context of the study in most cases. However, we highlighted that several papers have taken various values of discount rate and energy price inflation rate to evaluate the impacts of these parameters on the final results.

In this review, the lack of integrating social life cycle assessment into evaluating energy retrofit design is found as one of the main limitations. The SLCA is less developed than LCA and LCC and requires more methodological advancements, especially in developing measurement methods, quantifiable indicators, and databases.

It is also found that the number of multidimensional LCSA studies in building and energy retrofit design is increasing over the preceding years, and several researchers have proposed integrated frameworks to implement LCSA into the building design. In this context, the development of optimization algorithms and available tools are promising solutions to facilitate the LCSA implementation in the multi-objective building design process. Likewise, the BIM-based approach to integrate LCSA into the building design process attracted the researcher’s attention for solving the complexity of data management and processing in building life cycle sustainability assessment. Nevertheless, it is essential to develop measurement methods, standardization, and aggregation methods of LCSA pillars alongside providing more comprehensive databases and developing integrated software and tools by future research works to facilitate the implementation of LCSA in the building and energy retrofit design process.