Circularity Tools and Frameworks for New Buildings

Chapter 16 Circularity Tools and Frameworks for New Buildings Bengü Güngör , Akmaral Agibayeva , Ferhat Karaca , Rand Askar , Christina Giarma, Leonardo Rosado , Rocío Pineda-Martos , Philip Griffiths , and Luís Bragança Abstract The assessment of circularity in new building projects necessitates consideration of diverse factors such as material choice, design strategies, construction methods, operational efficiency, and end-of-life practices. Various tools and methodologies have been developed to aid stakeholders in the construction industry in evaluatingtheseaspectsandmakinginformeddecisions.Withthedynamicevolutionofthe circular economy, understanding current circular practices is crucial for identifying areas needing enhancement. However, the absence of a tandardized approach poses a challenge, with existing methods often either too broad or narrowly focused on specific circular elements. This limits the comprehensive evaluation of system performance. Addressing these challenges requires practical tools, particularly for early B. Güngör Department of Industrial Engineering, Izmir Demokrasi University, Engineering Faculty, Izmir, Türkiye A. Agibayeva ·F. Karaca (B ) Department of Civil and Environmental Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan e-mail: [email protected] R. Askar ·L. Bragança ISISE, ARISE, Department of Civil Engineering, University of Minho, 4804-533 Guimarães, Portugal C. Giarma Laboratory of Building Construction and Building Physics, Department of Civil Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece L. Rosado Chalmers University of Technology, Civil and Environmental Engineering, Göteborg, Sweden R. Pineda-Martos Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos, Escuela Técnica Superior de Ingeniería Agronómica, Universidad de Sevilla, Ctra. de Utrera, Km. 1, 41005 Seville, Spain P. Griffiths School of Architecture and the Built Environment, Ulster University, Belfast, UK © The Author(s) 2025 L. Bragança et al. (eds.), Circular Economy Design and Management in the Built Environment, Springer Tracts in Civil Engineering, https://doi.org/10.1007/978-3-031-73490-8_16 431 432 B. Güngör et al. design stages, that integrate quantitative methods to ensure circularity and environmentalperformancegoalsaremetefficiently.Thischapterreviewsexistingcircularity assessment parameters, discusses aggregation methods for criteria and indicators, and evaluates available tools to guide researchers, practitioners, and policymakers in advancing circular practices in construction. Keywords Building circularity ·Circularity assessment ·Circular economy · Construction industry 16.1 Introduction The efficient circularity assessment of new buildings requires a multitude of factors that must be considered, including material selection, design strategies, construction techniques, operational efficiency, and end-of-life management. Consequently, a range of tools and methodologies have been developed to evaluate these aspects and support decision-making processes for stakeholders involved in the construction industry (CI). With the dynamic evolution of the circular economy (CE) within the sector, it is imperative to acquire a comprehensive understanding of the circular practices that have been introduced. This understanding is crucial for distinguishing the current state of implementation and identifying areas that require further application or improvement.Numerousreviewarticlesareavailablethatidentifiedexistingtoolsand methods for circularity assessment in CI [10,12,18,27,30,60,70]. The current challengeofcircularityassessment isthelackofa standardisedapproach.Previousassessmentmethods eitherfocusedon circularityasa generaltermor prioritisedonespecific circular element. A limited scope of circularity indicators restricts the comprehensive evaluation of the system’s performance. Consequently, using individual indicators as the only means to assess the circular building design and disassembly potential remains challenging, along with quantitative support being the primary method. While the theoretical foundations of circularity are well-established, which was also handled in various sections in this book, the CI requires more practical tools for assessing circularity. Particularly in the early design phase, there is a demand for quantitative methods and tools that facilitate circular designs, mitigating the risk of rework in later phases due to issues related to circularity and environmental performance. However, the main challenge remains in the availability of information for circular assessments within the current design workflow, where uncertainty and incompleteness prevail, especially in the BIM approach. To effectively guide the design workflow, there is a need for more automated circularity assessment tools capable of directly evaluating circularity aspects. Despite the development of frameworks, there is a perceived lack of supportive policies to improve the reuse and recycling in CI. This chapter addresses the challenges and needs of circular assessment methods for new building projects. Readers may find other relevant details about the criteria, 16 Circularity Tools and Frameworks for New Buildings 433 indicators, and implementation practices of such tools in the different chapters of the report. However, this chapter comprehensively reviews the circularity assessment parameters and their possible variations on indicators and factors, and then presents quantitative and qualitative aggregation methods for the criteria and indicators to develop guidelines, indexes, and rating methods. Finally, the available circularity assessment tools are evaluated as complete assessment methods. By examining the existing literature and drawing insights from case studies, this study intends to shed light on the diverse approaches researchers, practitioners, and policymakers employ in this rapidly evolving field. 16.2 Circularity Assessment Parameters: The Variation of Criteria and Indicators The identification and use of criteria and indicators are key activities in circularity assessment. These activities have been the focus of much research in the field, and they are essential for developing effective circularity assessment methods. This subsection briefly overviews the criteria and indicators, typically the focal point of all the tools used in circularity assessment methods. It highlights the thematic and conceptual similarities and differences between the different criteria and indicators, which will help readers understand their relationships and key roles in the circularity assessment paradigm. For more detailed information, please refer to the dedicated chapters on the criteria and indicators of this book. Circularity assessment is performed through the use of various circularity indicators or a specific metric that utilises single or aggregated scores [26]. However, the lack of consensus on the definition creates confusion in distinguishing a circularity indicator from other circularity metrics (e.g., index, framework). The lack of standardisation yielded the interchangeable use of multiple circular terminology, often hindering the result interpretation. The definition given by the Organisation for Economic Co-operation and Development (OECD) describes an indicator as “a quantitative or qualitative factor or variable that provides a simple and reliable means to measure achievement, to reflect changes connected to an intervention, or to help assess the performance of a development actor” [74]. The use of generic circularity indicators is restricted by the unique attributes of CI. Unlike most products in the manufacturing industry, buildings have longer service lives, incorporate diverse materials, engage multiple stakeholders, and are highly customised and context dependent. These distinctive characteristics complicate the straightforward implementation of standardised circularity indicators in the construction sector [61]. A set of reliable indicators is vital when assessing the progress towards the CE [34]. This section reviews only those circularity metrics focusing on a single circularity aspect to be classified as a circularity indicator. Numerous studies have reviewed existing circularity indicators [85]. reviewed a set of 55 circularity indicators and classified them into ten different categories, 434 B. Güngör et al. including CE implementation level (e.g., micro, meso, macro), loops (e.g., maintain, reuse/remain, recycle), performance (e.g., intrinsic, impacts), prospective (e.g., actual, potential), usages (e.g., improvement, benchmarking, communication), transversely (e.g., generic, sector-specific), dimension (e.g., single, multiple), units (e.g., quantitative, qualitative), format (e.g., web-based tool, Excel), and sources (e.g., academic,companies, agencies)categories.However,mostofthereviewed indicators were adapted from existing methods in other sectors, specifically for the construction sector, with the exception of the Building Circularity Index (BCI). Khadim [60] analysed another set of 24 specific circularity indicators with 35 variations with a wide scale of application (e.g., new and existing buildings, type of buildings, and scale of measurement). [77] reviewed common building construction and demolition waste (BCDW) indicators and classified them into four categories: process, government initiatives, market, investment, and platforms,industrial symbiosis; and sharing economy. Likewise, [55] discussed existing trends, challenges, and perspectives of CE in CI by reviewing existing indicators and their dimensions (e.g., environmental, economic, management/behaviour, technological, social, innovation, and policy). The existing circularity indicators reviewed in the literature are presented in Table 16.1. It is worth mentioning that not all indicators are thoroughly reviewed in the text. 16.3 Development and Design of Circularity Indicators The majority of existing circularity indicators employ quantitative measures, given the fundamental purpose of a circularity indicator, which lies in the objective assessment of critical aspects and dimensions of CE in built environments. However, there are instances of adopting qualitative and semi-qualitative approaches in indicator development. For example, the measurement scale developed by [73] is a qualitative assessment scale that adopts selected indicators for the construction industry. Other examples of a semi-qualitative approach include C2C by Antwi-Afari et al. (2022) and the methodology described by [1]. Development of a new indicator can be challenging; therefore, adopting them from existing building assessment tools (e.g., BREEM, LEVEL(s), LCA, LCCA, MCI, BCI) remains a more popular approach rather than creating new indicators from scratch [57,60]. The design of circular indicators can be reviewed on the examples of the most commonly used indicators. Indicators can be quantified or qualified based on observations, measurements, calculations, or a combination of complex methods. For example, the rate of virgin materials over reused materials in secondary materials used to construct new buildings is a simple or less complex indicator,it is simply a ratio. The Material Circularity Indicator (MCI) is another example of a more complex indicator developed by the [37] to quantify the level of circularity for construction materials. It assesses the degree to which a product minimises linear resource consumption and maximises materials restoration within its components. Moreover, it evaluates the product’s duration and intensity of use in comparison to an average 16 Circularity Tools and Frameworks for New Buildings 435 Table 16.1 Summary of the circularity metrics of the reviewed literature The existing circularity indicators References Building Circularity Indicator (BCI) [98] Building Circularity Indicator (Disassembly Reconsidered) (BCIDR) [96] BIM-Based Building Circularity Assessment (BBCA) [103] Modified Alba Concept (For Foundations) (MAC) [95] Alba Concept BCI (ACBCI) [8] Modified Building Circularity Indicator (MBCI) [19] Predictive Building Circularity Indicator (PBCI) [27] Circularity Indicator for Pedestrian Bridges (CIPB) [9] ARCH Circular Environmental Indicator Framework (ARCHCEIF) [42] MADASTER Circularity Indicator (MAD-CI) [67] FLEX 4.0 [46] Material Circularity Indicator (MCI) [37] Circular Economy Measurement Scale (CEMS) [73] Circular Economy Scale (CES) [73]) Circular Business Model (CBM) Based Circularity Indicator (CBMCI) [31] Integrated Energy Performance and Circularity (IEPC) [89] BIM-based Whole-life Performance Estimator (BBWPE) [6] Bridge Circularity Assessment Framework (BCAF) [25] Synthetic Economic Environmental Indicator (SEEI) [44] Gypsum End of Life Measurement Indicator (GEOLMI) [59] RIPAT 1.0 [93] Framework for Circular Buildings (FCB) [63] Platform CB’ 23 (PCB) [21] Circularity Calculator (CC) [57] Circular Building Assessment Prototype (CBAP) [16] C-CALC [22] Circulytics [38] Circular Assessment Criteria for Envelope (CACE) [40] Circular Construction Evaluation Framework (CCEF) [29] Material Reutilization Part (C2C) [66] Circle Assessment (CA) [24] Circularity Assessment Tool (CAT) [80] Circular Benefits Tool (CBT) [4] Circular Economy Company Assessment Criteria (CECAC) [97] Circular Economy Index (CEI) [3] (continued) 436 B. Güngör et al. Table 16.1 (continued) The existing circularity indicators References Circular Economy Indicators for India (CEII) [90] Circular Economy Indicator Prototype (CEIP) [100] Circular Economy Monitoring Framework (CEMF) [36] Circular Economy Performance Indicator (CEPI) [56] Circular Economy Toolkit (CET) [3] Circular Economy Toolbox US (CETUS) [92] Circular Economic Value (CEV) [41] Circularity Index (CI) [56] Circular Impacts Project EU (CIPEU) [36] Circularity Material Cycles (CIRC) [79] Closed Loop Calculator (CLC) [43] Circularity Pathfinder (CP) [84] Circularity Potential Indicator (CPI) [3] Super-efficiency Data Envelopment Analysis Model (DEA) [103] Evaluation of CE Development in Cities (ECEDC) [17] Evaluation Indicator System of Circular Economy (EISCE) [3] Indicators for Material input for CE in Europe (IMCEE) [35] End-of-Life Recycling Rates (EoL-RRs) [37] Environmental Protection Indicators (EPICE) in a context of CE [75] Evaluation of Regional Circular Economy (ERCE) [22] Eco-efficient Value Ratio (EVR) [56] Economy-Wide Material Flow Analysis (EWMFA) [53] Five Category Index Method (FCIM) [65] Hybrid LCA Model (HLCAM) [45] Indicators for Consumption for CE in Europe (ICCEE) [35] Circularity Indicator Project (ICT) [99] Indicators for Eco-design for CE in Europe (IECEE) [35] Indicators of Economic Circularity in France (IECF) [68] Integrative Evaluation on the Development of CE (IEDCE) [83] Input–Output Balance Sheet (IOBS) [3] Indicators for Production for CE in Europe (IPCEE) [35] Industrial Park Circular Economy Indicator System (IPCEIS) Geng (2012) Measuring Regional CE–Eco-Innovation (MRCEEI) Smol (2017) National Circular Economy Indicator System (NCEIS) Geng (2012) Product-Level Circularity Metric (PCM) [3] Regional Circular Economy Development Index (RCEDI) [51] (continued) 16 Circularity Tools and Frameworks for New Buildings 437 Table 16.1 (continued) The existing circularity indicators References Resource Duration Indicator (RDI) [3] EU Resource Efficiency Scoreboard (RES) [34] Recycling Indices (RIs) for the CE [37] Resource Productivity (RP) Wen and Meng (2015) Reuse Potential Indicator (RPI) [3] Recycling Rates (RRs) [37] Sustainable Circular Index (SCI) [15] Value-based Resource Efficiency (VRE) [100] Zero Waste Index (ZWI) [15] Whole building circularity indicator (WBCI) [61] Product Circularity Index (PCI), [94] Element Circularity Index (ECI) [94] Critical Success Factors (CSFs) [76] [62] Reuse Potential Indicator (RPI) [10,78] Whole-Life Performance Estimator (WLPE) [6] Circular Economy Performance Indicator (CPI) [56] Global Resource Indicator (GRI) [2] Deconstruction, and Resilience (3DR) [75] System Circularity Indicator (SCI) [11] The Circular Construction Evaluation Framework (CCEF) [29] The Disassembly and Deconstruction Analytics System (D-DAS) [5] product within the same industry. The MCI is primarily composed of three key product characteristics: the amount (V) of used virgin raw materials, the amount (W) of unrecoverable waste attributed to the product, and the utility factor (X) that accounts for the lifetime of the product. MCI is determined by considering the proportion of material input (virgin or non-virgin), the material output (either energy recovery or landfill disposal), and the technical lifecycle of a product. These factors collectively represent the theoretical circular capacity of each product. To calculate the MCI for each product, a Bill of Materials (BoM) is utilised as input. The MCI represents 50% of the circular potential of products [11]. From this perspective, the MCI is not just a simple indicator but a more complex assessment method for measuringmaterialcircularity.Inthefourth section, the focusisdrivento thespecifics of the MCI and its integration with other components to form the Building Circularity Indicator (BCI), providing a complete methodology for circularity assessment. 438 B. Güngör et al. 16.4 Development of Circularity Indices: Aggregation of Indicators Generally, criteria and indicators are quantitative or qualitative measures created from a collection of observed facts that might reflect relative positions in a certain area [23]. They can show the change in direction across time and between various units when it is reviewed regularly. They can also be useful in establishing policy priorities, benchmarking, and performance monitoring. When separate indicators are combined into a single index (sometimes called ranking, method, or tool) based on an underlying model, the resulting indicator is generally referred to as an “index” or aggregated indicator [86]. Ideally, the index should measure multidimensional aspects such as competitiveness, industrialisation, sustainability, single market integration, and knowledge-based society, which a single indicator cannot adequately represent. Table 16.2 presents a list of pros and cons of indices, which was originally evaluated by the Joint Research Centre-European Commission in 2008. An index quality and the validity of the information it delivers largely depend on the framework and data used rather than only the methodology employed in its creation [52]. Despite the employment of cutting-edge methodology in its creation, an index built on a weak theoretical foundation or soft data with significant measurement errors may produce policy statements that are open to debate. The experience demonstrates that disagreements regarding the best way to create weights are difficult to settle. Science may considerably contribute to ensuring that the processes of aggregation are as sound and transparent as feasible, although it cannot give an objective approach for creating the only true index to summarise a complex system. Therefore, in this part, a generic index generation framework is given to guide aggregators like a checklist for constructing an index (See Fig. 16.1). Building an index begins with a strong theoretical framework step. The framework should explicitly identify the phenomenon to be assessed and its constituent parts, choosing distinct indicators and weights (see the previous section) that reflect the Table 16.2 Pros and Cons of Aggregated Indicators (Indices) (Adapted from [86], OECD 2008) Pros Cons Indices can be used to summarise complicated or multifaceted problems Indices that are poorly constructed or evaluated may lead to false or incomplete understandings They can simplify classification based on challenging criteria The judgement required to form indices can introduce subjectivity They facilitate the interpretation of trends across a variety of distinct metrics Indicators necessitate data, which is sometimes unavailable or inaccessible, making its acquisition time-consuming or resulting in inaccurate calculations They help fit more data into the allotted space or streamline a list of indicators If the construction process is not transparent, it may obscure serious flaws in some dimensions and make it more difficult to identify appropriate corrective action 16 Circularity Tools and Frameworks for New Buildings 439 Fig. 16.1 A generic framework for index generation steps (Source own elaboration) relative weights of these components and the dimensions of the final composite. The ideal approach would be to base this procedure on what is desirable to measure rather than on which indicators are readily available. Within the data selection step, the quality of the underlying variables significantly impacts both the indices’ strengths and flaws. Variables should ideally be chosen based on their applicability, analytical quality, timeliness, and accessibility. With advancements in data selection and indicator development, aggregated indicators’ quality and accuracy should also advance. Missing data frequently hampers the creation of reliable indices. Both random and non-random data loss is possible. In this situation, a step for imputation of missing data should be managed. Variance estimations should consider the uncertainty in the imputed data. Because of this, the analysis can now account for the impacts of imputation. Single imputation, however, is notorious for underestimating variance because it only fully accounts for imputation uncertainty. The multiple imputation approach, which offers numerous values for each missing value, can better capture the uncertainty brought on by imputed data. More decision-makers need to create aggregated indicators than ever before. In most cases, the choice of a single indicator is made randomly, with little thought given to how that signal may interact with other indicators. Therefore, the data set’s applicability may be evaluated by applying multivariate analysis (MVA), which also helps to understand how the methodological decisions will impact the results. The most common MVA methods are Multiple Linear Regression Analysis, Principal Componentsand FactorAnalysis,CronbachCoefficient Alpha, and Cluster Analysis, which are briefly explained in Table 16.3. 446 B. Güngör et al. compare systems with each other and the different lifetimes of each system. Finally, at a building level, the BCI assesses the separate systems as a whole with a factor for the level of importance of each system. The overall aspects considered in the circularity calculation methodology, technically, only consist of two components: (1) the material specifications and (2) the design for disassembly (functional, technical, and physical). The BCI by Verberne formed the first circularity assessment tool for a whole building level and introduced an important base for later building circularity models, which built upon it and addressed some of its limitations. For example, [96] refined the BCI by addressing certain limitations related to design for disassembly (DfD) and the weighting of factors. [95] expanded the BCI by introducing circularity criteria for foundations. [103] proposed an automated framework using BIM that further developed Verberne’s original BCI. [61] enhanced the model by incorporating adaptability factors. Cradle to Cradle Certified is among the prevalent models for assessing circularity in building projects, evaluating products based on criteria such as material health, reutilisation, renewable energy, water stewardship, and social equity [28]. BREEAM, primarily focused on environmental assessment, incorporates principles of the circular economy related to materials use and life cycle impacts (Building Research Establishment (BRE), n.d.). LEED, developed by the U.S. Green Building Council, promotes sustainable practices in design, construction, and operation, emphasising materials and resources aligned with circular economy principles [91]. The Ellen MacArthur Foundation’s Circulytics measures circular economy performance across business dimensions [39]. Malaysia’s Green Building Index (GBI) rates buildings based on sustainable material use and life cycle impacts, aligning with circular economy principles (Green Building Index Malaysia, n.d.). Despite their importance in advancing sustainability in construction, these models face significant challenges. They often require substantial resources for data collection, analysis, and verification, which can be daunting for smaller organisations or projects with limited capabilities. Moreover, their focus tends to be on inputs like material selection and energy efficiency, rather than on assessing outputs such as actual circularity achieved or the effectiveness of recycling and reuse processes [71]. This gap between input-focused assessments and real-world circular outcomes can hinder their ability to comprehensively achieve sustainability goals. Furthermore, while these models address lifecycle impacts to some extent, they may not fully encompass critical stages such as end-of-life scenarios or the management of materials post-demolition or renovation [14]. Certification costs also pose barriers, as the expenses associated with assessments and audits can be prohibitive, especially for projects in developing regions [101]. Additionally, the adaptability of these models to diverse regional contexts and regulatory frameworks varies, potentially limiting their global applicability. Balancing complexity with practical application remains an ongoing challenge, requiring continuous refinement to ensure these models effectively support sustainable and circular practices across different scales and contexts within the building sector. 16 Circularity Tools and Frameworks for New Buildings 447 In contrast, modern BCI-based tools offer robust features that distinguish them from traditional building circularity models. These tools integrate comprehensive circulareconomy principlesthroughoutthebuildinglifecycle,encompassingnot only material health and energy efficiency but also critical aspects like end-of-life recycling and reuse. They adopt a holistic assessment approach that balances inputs such as material selection with outputs like actual circularity achieved and the recyclability of materials post-use, providing a more accurate measure of sustainable practices [88].Utilisingadvanceddataanalyticsanddigitaltechnologies, thesetools streamline data collection, analysis, and reporting, making sustainability assessments more efficient and accessible across diverse projects. Customisable criteria tailored to regional contexts enhance their global relevance and applicability, fostering transparency and stakeholder engagement. Furthermore, modern tools emphasise performance-based metrics, enabling continuous improvement and benchmarking against sustainability goals. Innovations such as digital twin simulations optimise building performance and resource efficiency. These advancements collectively enhance the capacity of modern building circularity indicator-based tools to drive sustainable and resilient building practices in today’s dynamic environment. 16.5.3 HOUSEFUL’s Building Circularity Methodology (BCM) TheHorizon2020 HOUSEFULprojecton“Innovativecircularsolutionsandservices for new business opportunities in the EU housing sector” (2018–2022) recently reported a methodology to evaluate circularity degree in the sector of housing to be implemented at the earlier stages (new and retrofitted) of building design, as an originally circularity measure via a global circularity indicator, the BCS, Building CircularityScore[49].TheHOUSEFULapproach,usingacomposedcircularityindicator, is fundamental on the degree of circularity based on six pillars—.e., energy, water, and material balances,social and environmental impacts; and life cycle cost reduction. Being the proposed indicator under a life-cycle-based methodological approach, it is aligned with common and existing methods of building sustainability, such as the CEN Technical Committee 350 (CEN TC 350) and the European Union (EU) LEVEL(s); including potential for improvements regarding water and energy circularity per life cycle stage. The six pillars encompass a set of meaningful Key Performance Indicators (KPIs) and weighting factors (energy and water consumption, materials usage, social added value, and life cycle economic value), which are extensively implemented in the sustainable construction sector to result in a single circularity KPI, the so-called BCS [49]. The methodology was applied in the HOUSEFUL demo buildings and related projects, being tested and validated in practice with real data and in different scenarios by comparing different buildings—i.e., location, use, measures, etc. (González et al., n.d.). 448 B. Güngör et al. The Building Circularity Methodology (BCM) was proposed as a multidimensional model to assess and evaluate the circularity degree in residential and/or tertiary buildings (housing sector), highlighting its implementation in the EU countries under a Circular Economy (CE) perspective. This methodology and the BSC constitute a consistent and reliable output aimed at applying market-usable and innovative solutions accessible to data on current circularity degrees. Thus, it would be useful to inform existing policies and strategies on circularity in the urban built environment and to provide recommendations to the construction sector stakeholders—e.g., designers, manufacturers, promoters, decision-policy, lawmakers, and end-users. Moreover, the HOUSEFUL approach and indicator, which is based on easy and objective metrics, would bring green funding opportunities under the umbrella of administrations and other public bodies and tenders and novel project calls towards the implementation, achievement and promotion of CE principles in the urban built environment. The BSC would be automatically calculated by providing input data on the HOUSEFUL web-based Circularity Tool (CT), as a Software-as-a-Service (SaaS) tool facilitating decision-making and future planning and the design at the construction phase [49]. As highlighted above, the HOUSEFUL’s Building Circularity methodology was developed by considering the CE principles of recyclability, reusability and waste management related to materials and buildings on energy and water life cycles, and economic and social performance, as well as circular solutions feasibility. Moreover, new and existing methodologies on CE pillars were considered—e.g., Life Cycle Assessment (LCA), Life Cycle Cost (LCC), and Social Life Cycle Assessment (S-LCA). Additionally, the HOUSEFUL approach is also well-matched with sustainable building certifications—e.g., LEED, BREAM, WELL [49]. The comprehensive circularity calculation, at building level characterisation and its indicators, complements the BCS by the above-mentioned six-pillar consideration. Thus, circularity degree valuation at the lifecycle stage level would provide and identify solid knowledge on improvements and solutions among different CE aspects (pillars), thus improving and unifying building circularity [47]. 16.5.4 Circular Construction Evaluation Framework (CCEF) The Circular Construction Evaluation Framework (CCEF), proposed relatively recently by [29], aims at evaluating the degree of a project’s circularity. It addresses both existing and new (proposed) design and construction projects and can be used by a variety of contributors and participants in a project’s development (e.g., clients and other professionals in the sector). Its methodological approach consists of the quantification of the level of the examined project’s circularity with regard to several relevant criteria. The assessment takes place on a whole-building basis and at the level of building elements. The circularity credentials for each one of these levels are quantified by 16 Circularity Tools and Frameworks for New Buildings 449 different criteria organised in broader groups. Specifically, when the whole building is considered, 14 criteria are employed, classified under four groups [29]: •Recorded information design, data, and materials: 1. Disassembly plan included in design drawings and specifications, 2. Disassembly sequencing information, 3. Clarity and transferability of plans and specifications, •Adaptability in design: 4. Versatility (in regular use, cosmetic change), 5. Convertibility (partition/space changes), 6. Expandability (vertical, without major foundation modification), 7. Expandability (horizontal, compatible foundations) •Simplicity in design: 8. Parts per element, 9. Standardisation and modularity of elements (dimensions), 10. Standardisation and modularity of elements (component variation), 11. Standardisation and modularity of elements (connections), 12. Degree of element independence and classification of construction •Health and safety: 13. Toxicity/synthetic chemicals, 14. Ease of access, construction, and disassembly The respective structure at the assessment level of elements comprises 11 criteria thatare classifiedintothreegroupsand threecriterianotbelongingto alargerthematic area [29]: •Durability: 1. Number of previous design lives/uses, 2. Length of previous design lives, 3. Predicted length of current design life •Material inventory: 4. Suppliers and production, 5. Warranties, 6. Donor building(s), 7. Reclaimed and/or recycled content, 8. Involvement of reuse in cleaning or restoration work, 9. Life Cycle Analysis with end-of-life Scenario and Environmental Product Declaration •Finishes/Treatment: 10. Synthetic/chemical/wet resins/adhesives? (yes/no response) 11. Chemical coatings, 12. Reversibility of connections, 13. Reusable (without restoration or modification), 14. Recyclable (no downgrading) The rating in the context of each criterion ranges from 0 to 5, with higher scores indicating a higher degree of circularity. This scoring scale is also used for criteria of a qualitative nature (e.g., yes/no reply), so that quantitative final results are achieved. The evaluations at the elementand at the whole building level take place separately and result in two separate scores. Regarding the objectivity of the results, the authors formulating the framework point out the possibility of “an element of bias” [29], p. 6). The structure of the framework’s computational implementation provides the possibility for weightings’ determination and introduction (however, such development is unavoidably accompanied by a subjectivity factor). As indicated by the aforementioned criteria, circularity aspects heavily considered within this framework are, among others, design for adaptability and disassembly, as well as materials’ reuse. LCA/EPDs related issues, durability and reusability, toxic or synthetic substances creating health risks or preventing direct reuse of components, and several other parameters (simplicity, methods of construction), all seen under the light of a lifecycle approach also considering past and future design lives and uses, are also included in the performed assessments. 450 B. Güngör et al. 16.5.5 Disassembly and Deconstruction Analytics System (D-DAS) The disassembly and deconstruction analytics system (D-DAS) is a framework enabling the integration of end-of-life performance evaluation/consideration into the buildings’ design stage and process [5]. The system’s main target evolves around the selection of materials, already in the building’s design stage, that will contribute not only to efficient materials’ use but also to the reduction of waste at the end-of-life with regard to the built environment. D-DAS uses and builds upon the capabilities of building information modelling (BIM). Allowing the consideration of various alternative solutions for the building design at various levels (materials selection, etc.) and providing the possibility for access to extensive information on the building as well as for complex computational processes, visualisation, and simulation, this system can serve as a decision support tool. Four layers of D-DAS architecture work together as a single system. The data, based on which the calculations are made, are related to building design (parametric building models, materials, etc.), to the building materials’ specification (materials’ properties and status), as well as to deconstruction and demolition information (historical data). The system comprises five functional models and analytics: (i) Building Whole Life Performance Analytics, related to the calculation/ estimation of the building’s performance over time; (ii) Building Element Deconstruction Analytics, resulting in an evaluation of the building design with regard to whether and to which degree design for deconstruction is supported (the applied model is based on Deconstructibility Assessment Score [7], (iii) Deconstruction Arising Analytics, forming the basis for the Pre-Deconstruction Audit generation (iv) Design for Deconstruction Advisor, which identifies possible optimisation points in the design (building componentsand materials wise) regarding the materials reuse and the reduction of waste, and provides alternative solutions; (v) Deconstruction Visualisation, providing the plan of the deconstruction process, as well as its visualisation (along with the disassembly process). Each one of these entities supports a different functionality. According to [5], D-DAS can be implemented either as a plugin for an existing BIM or as a standalone application (visualisation and simulation tools-based). The implementation of D-DAS presented by [5] is a plug-in to Autodesk Revit, including the functional modules (i), (ii), and (iii). It was validated through the examination of three alternative scenarios for a building. However, important assumptions and simplifications were adopted in this process [13], creating the need for further testing and validation of the system. 16 Circularity Tools and Frameworks for New Buildings 451 16.6 Insights for Future Work and Further Improvements This section offers valuable insights into the challenges faced by the construction industry in developing circularity assessment tools. To promote more sustainable construction practices and advance the field of circularity assessment, we need to identify several areas for future improvements. •Standardisation of Circularity Assessment: The critical review in this section highlights that one of the main challenges is the lack of a standardised approach to circularity assessment. Therefore, future research should focus on developing sector-wide standards and guidelines for assessing circularity in construction projects. This would streamline the evaluation process and make it easier to compare different projects. •Development of Automated Tools: As mentioned, there is a need for more automated circularity assessment tools, especially in the early design phase. Researchers and software developers should work together to create user-friendly software that integrates circularity assessment seamlessly into Building Information Modelling (BIM) workflows. This will help architects and designers make informed decisions from the outset, reducing the risk of rework in later project phases. •Enhanced Data Availability: The circular economy addresses the importance of data sharing and availability within the current design workflow, where uncertainty and incompleteness prevail, and is addressed in this review as a significant challenge. Future research should explore ways to improve data collection and sharing, possibly through collaborative platforms and databases specifically tailored for circularity assessment in construction. •Policy Support: The section also mentions a perceived lack of supportive policies to improve reuse and recycling in the construction industry. Advocacy for and developmentof policies thatincentivise circularconstructionpractices,suchastax incentives or procurement regulations, can significantly accelerate the adoption of circularity principles. •Circularity Indicator Classification and Standardisation: There is a confusion arising from the interchangeable use of circular terminology. Future work should focus on classifying and standardising circularity indicators, indices, and frameworks to provide a clear and consistent language for circularity assessment in the construction sector. •Innovative Circularity Indicators: Researchers should explore and develop new circularity indicators tailored to the construction industry’s unique attributes. These indicators should consider factors such as building service life, diverse materials, stakeholder involvement, and customisation. •Interdisciplinary Collaboration: Circular construction is a complex field that requires expertise in materials science, architecture, engineering, policy, and economics. Encouraging interdisciplinary collaboration among these experts can help foster a holistic approach towards assessing circularity and promoting innovation. 452 B. Güngör et al. •Qualitative and Semi-Qualitative Approaches: While quantitative indicators are essential, it is equally crucial to explore qualitative and semi-qualitative approaches for circularity assessment. These approaches may offer a better understanding of the social and environmental dimensions of circular construction. •Education and Training: To promote the adoption of circularity in the construction industry, it is vital to develop training programmes and educational resources for professionals and stakeholders. Building a skilled workforce that understands the principles and benefits of circularity is essential. •Longitudinal Studies: Longitudinal studies that track the impact of circular construction practices over time can provide valuable insights into their effectiveness. Monitoring the performance and environmental impact of circular buildings throughout their lifecycle and integrating them into existing assessment tools can be a useful strategy. In conclusion, the construction industry is undergoing a transformation towards circular economy principles. However, to further advance this shift, it is essential to address challenges like standardisation, data availability, policy support, and the development of innovative tools and indicators. With these improvements, the construction industry can become a more sustainable and circular sector, contributing to a greener future. References 1. 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