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Article

Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM

by
Bernardette Soust-Verdaguer
*,
José Antonio Gutiérrez Moreno
and
Carmen Llatas
Instituto Universitario de Arquitectura y Ciencias de la Construcción, Escuela Técnica Superior de Arquitectura, Universidad de Sevilla. Reina Mercedes Avenue 2, 41012 Seville, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2274; https://doi.org/10.3390/su15032274
Submission received: 29 November 2022 / Revised: 18 January 2023 / Accepted: 19 January 2023 / Published: 26 January 2023
(This article belongs to the Special Issue BIM-Based Life Cycle Sustainability Assessment for Buildings, Volume II)
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Abstract

:
Recent international scientific studies have described the current situation regarding CO2 emissions and have provided evidence of its catastrophic short- and medium-term consequences. The implementation of solutions of a more sustainable nature to reduce and mitigate this situation is becoming increasingly urgent. To this end, the integration of multi-dimension and life cycle assessment into the design process of buildings can help and support decision making. Life Cycle Sustainability Assessment (LCSA) is one of the scientific community’s most widely recognized methodologies for this purpose, combining the evaluation of the social, economic, and social dimensions (Triple Bottom Line). One of the main obstacles to implementing this methodology lies in the difficulties in automatically comparing alternative design options for the selection of different materials. To overcome this limitation, the authors developed the BIM3LCA (Building Information Modelling Three Life Cycle Assessment) tool conceived to guide the decision-making process during the early design steps. This study introduces a Building Information Modelling (BIM) plug-in development and validates its application in a case study to support the multi-criteria building material selection based on the LCSA implementation at the early design stage. Three building material alternatives for the structural system of a multi-family residential building are employed to validate this plug-in. The results show the viability of using this tool during the early design stages and demonstrates the consistency of the results regarding the use of the BIM model to conduct the LCSA. The study discusses the benefits and limitations of the BIM3LCA tool. This research contributes towards the integration of multi-dimension real-time assessment in the building design process by using semantically rich BIM models.

1. Introduction

Recent international scientific studies have described the current situation with regard to CO2 emissions, and have provided evidence of its catastrophic short- and medium-term consequences [1]. In this respect, the built environment plays a crucial role, since it is responsible for 40% of greenhouse gas emissions [1] and constitutes one of the largest consumers of natural resources [2]. Given the environmental, economic, and social impact [3] that buildings produce throughout their life cycle, society demands an increase in the sustainability of buildings [4,5,6]. In order to overcome this situation, current international sustainability strategies such as the United Nations Sustainable Development Goals [7] and European strategies such as Green Deal [8] and Circular Economy Action Plan [9] propose radical changes in our development model, such as decarbonization. Moreover, the predictions and scientific evidence regarding the effects of climate change [1,10] necessitate the implementation of measures of a more effective and innovative nature to produce drastic changes. Indeed, the scenario for the improvement of energy efficiency in the building sector terminates when, for example, near-zero energy consumption standards are reached [11], or when the use of renewable sources for energy supply in the operational phase are fully achieved. However, the embodied impacts related to materials and products included in buildings have yet to be reduced. Hence, due to the complexity of existing problems, potential solutions demand that the sustainability of buildings is addressed from a holistic perspective that integrates the three fundamental dimensions (environmental, economic, and social) for their whole life cycle [11,12].
The Building Information Modelling methodology is the “construction of a model that contains the information about a building from all phases of the building life cycle” [13]. Currently, an increasing number of studies demonstrate the potential of the use of BIM methodology in supporting sustainable construction [14] and in the integration of tools based on LCA [15,16]. Furthermore, the use of BIM in current practice in AECO (Architecture, Engineering, Construction, and Operation) has been mandatory for the tendering of public buildings in the EU since the end of 2018 [14]. Indeed, the use of BIM constitutes a digital revolution in the construction sector, and the scientific community has highlighted its potential in improving the sustainability of buildings [17,18,19,20]. However, its effective implementation in the building sector, which requires tools adapted to each context and integrated into the design workflow, remains insufficiently mature [15].
The design process is crucial for the reduction of the impact of the building during its life cycle [11,12]. Consequently, Life Cycle Assessment (LCA) constitutes the most objective and widely employed method [13,14] for the assessment of the environmental impact of building projects, and it plays a crucial role in achieving decarbonization objectives [21]. In recent decades, the use of the LCA method has been largely focused on scientific research by the academia sector [22,23]. The results from a survey of 500 practitioners in the construction sector point out the lack of quantitative life cycle assessment in the early design stages [23], and provide evidence of its limited implementation in practice. However, recent developments are helping to turn this situation around. Indeed, the sustainability assessment in the design process is moving from qualitative to quantitative metrics [24]. The use of LCA-based methods in sustainability assessment and sustainability certification has increased in recent years. For example, the Level(s) [25] (European Commission) framework for the assessment of building sustainability, and the DGNB (German Sustainable Building Council) [26] and Verde (Spain) [27] Green Building Rating System (GBRS), use simplified LCA and LCC methods in the evaluation process. Moreover, they have integrated both methods into their evaluation requirements [26,28]. Nevertheless, the reduction of the environmental impact of the built environment goes beyond traditional unidimensional approaches [29]. Life Cycle Sustainability Assessment (LCSA) provides a more comprehensive approach than do the LCA and LCC techniques. The methodology combines three methods based on the quantification of the life cycle impacts: (environmental) LCA, Life Cycle Costing (LCC), and Social-Life Cycle Assessment (S-LCA) [18]. It, therefore, conducts the so-called Triple Bottom Line (TBL) sustainability assessment. Nonetheless, the integration of the Social-Life Cycle Assessment (S-LCA) is not yet specifically required in this certification or assessment framework [30], since it is only starting to be considered as a relevant method for its integration into future developments of the sustainability certifications [21], in order to provide a more quantitative assessment of sustainability. One of the main obstacles therein involves the limited data availability and the limited development of indicators adapted to the BIM workflow and design process [30]. The potential of using the LCSA to assess the embodied impacts (environmental, economic, and social) of those directly related to the materials that compose the building from a life cycle perspective is demonstrated in the literature [31].
Recent studies highlight that the integration of LCSA-based sustainability assessment in the building sector is scarce [32,33], as its implementation in BIM [33]. The authors’ recent development [31] constitutes one of the first to propose an interoperable framework. This study develops an Autodesk Revit Dynamo Script [34] and defines the main steps for real-time LCSA calculations to be conducted in BIM. It is based on the enrichment of the parameters of the BIM model, that was previously implemented by Santos et al. [35,36,37] to conduct LCA and LCC. Similar principles are implemented in Röck et al. [38], Bueno et al. [39], Giaveno et al. [40], and Santos et al. [37,41] that insert new parameters in the BIM objects (environmental impact categories), which have previously been defined in an Excel file. Zhaon et al. [42] propose a plug-in implemented in BIM to low-carbon building design optimization, which focuses on operational aspects such as energy consumption and daylighting performance, but embodied impacts are not included in the assessment. Filho et al. [43] conducted the LCSA based on a BIM model integrating a multi-criteria decision-making technique (Fuzzy Analytical Hierarchy Process (AHP)), nevertheless the work proposes a manual workflow, which lacks in the automation of the LCSA implementation in BIM using a single plug-in. In this vein, the existing literature [37,38,39,40,41] provides evidence of limitations in the use of the data sources along the design stages. It means that for the early design, step generic data from ecoinvent [44] is mainly used, and for the detailed design steps, specific data from EPDs (Environmental Product Declaration) are used. One of the limitations of this approach involves the risk of data inconsistency in the simultaneous implementation of the LCA techniques, which include various inventories (and data structures for the economic and environmental dimensions) and data sources depending on the dimension (e.g., ecoinvent [44] for the environmental dimension and CYPE for the economic dimension). This gap was recently explored in this research [45], which demonstrates the potential of the method and its consistency throughout the design process. The study uses a Triple Bottom Line (TBL) database to integrate the environmental, economic, and social dimension, which means a sustainability assessment based on a triple dimension. The TBL database is developed to fill the information gaps in the early design steps [45] and to provide and harmonize the data structure for the triple-dimension assessment. Another limitation detected in the existing studies [31] involves the automatic comparison of various design options, modelled in different BIM folders, and also the difficulties in detecting model errors and the user interface limitations of the prototype developments [31]. The lack of a stable and user-friendly interface is a limitation in this existing development [31]. Using the plug-in requires a basic knowledge of Dynamo Autodesk Revit and the plug-in mainly depends on pre-developed packages for Dynamo Autodesk Revit to complete several functions (such as data visualization). In addition, there are limitations on the results of the data visualization, which depend on a predefined layout and existing functionalities. Moreover, the use of the outputs is limited to the format and visualization charts that the packages are including. Hence, knowledge gaps are detected so that these shortcomings are addressed in this present study.
Given that the authors′ previous studies are based on the development of a prototype tool [31] and on the demonstration of the data consistency of the LCSA framework throughout the design process [45], this present study proceeds with the improvement of the latter’s development, and explores its potential for the selection of building material based on multi-criteria decision-making techniques, which are discussed for the first time in this work.
Therefore, unlike the previous three articles [31,33,45] and in order to fill the detected knowledge gaps, this present paper aims to answer the following research questions (RQ):
  • RQ1: Is it possible to conduct an automatic calculation of the environmental, economic, and social impacts based on the LCSA method in real time using specific (improving the usability and data visualization) software integrated into the BIM environment?
  • RQ2: Is it possible to implement an automatic multi-model assessment to support the building material selection within the BIM environment?
To this end, the BIM3LCA tool has been developed: a BIM-based Sustainability Life Cycle Assessment plug-in to support the integration of environmental, economic, and social information into the BIM objects, as described in Section 2. Section 3 includes the tool validation with a case study application to evaluate three alternative building materials for a multi-family residential building located in Seville. Section 4 discusses the advantages and limitations of the developed tool, while Section 5 focuses on the conclusions of the research.

2. Materials and Methods

This research aims to develop a BIM-based application to support both an automatic LCSA and the multi-dimension material assessment within the BIM environment. This study is supported by previous studies in this field [31,33,45] that propose the methodological framework to conduct the LCSA in BIM [33]. Hence, the initial prototype tool (LCSA Dynamo Autodesk Revit Script) described in Llatas et al. [31,45], has been further explored (upgraded) in this article, employed to develop the BIM3LCA tool, and then validated on a case study application (see Figure 1). To address the research questions, the methodology applied in this study focuses on the operative implementation of the approach of previous studies towards validating the tool developed. Therefore, the in-depth analysis of the LCSA results lies outside of the scope of this study.
The selected BIM-based environment software is that of Autodesk Revit, one of the most widely used, both for BIM tools in the international market and for sustainability-related simulations [46] through the Revit Application Programming Interface (API) based on the Microsoft.NET environment. The programming language C# was selected to develop the BIM3LCA tool (including BIM model data management, LCSA calculation, and visualization of the LCSA results), mainly since the most readily available Revit API user′s guide information is based on this language [34]. Furthermore, Windows Form (WinForms) classes were needed to generate the Graphic User Interface (GUI) which acts as a connection between the database and the user.

2.1. LCSA Implementation in BIM

The LCSA implementation was based on the ISO 21931-1 [47] standard. It proposed the organization of the information according to the modularity principle. Table 1 shows a possible organization of the embodied (E) and operational (O) aspects involved in the LCSA based on [31,47], and indicates the information modules included (marked with X) in this study. The incorporation of information modules was based on the data availability and the scope of the study, with the aim of covering as many modules as possible. However, several omissions were assumed and justified in [31]. The scope of the LCSA was focused on the building structure system. Hence, the study only included the building elements that compose the structure (including beam, column, foundation, slab, wall). The service life of those building elements was 50 years (the same as the building life span), which was based on Spanish regulations [48] about the building structure life span.
The LCSA data input (Table 2) refers to the type of information that should be prepared before the plug-in is run. Considering the geometric information about the building elements that composed the building, the BIM model was modeled in a 200 LOD (Level of Development). At that LOD, the “model element is graphically represented within the Model as a generic system, object, or assembly with approximate quantities, size, shape, location, and orientation” [48].
The LCSA data output (Table 2) refers to the type of information that will be calculated with the plug-in. This study includes the following impact categories and indicators: Global Warming Potential (GWP) in kg. CO2 eq. (environmental); costs in Euros (economic); and labor in working hours (social). The selection of the impact categories and indicators: GWP in kg. CO2 eq. (LCA) was based on its relevance in achieving the decarbonization objectives [8]. The selection of the inventory indicators of costs (LCC) and working hours (S-LCA) was based on the existing systematic data sources such as BCCA [49]. The “Working hours” inventory indicator [50] is referenced in the UNEP S-LCA guidelines [50] as the most frequently used activity variable, and it has previously been used in other S-LCA studies [31,45,51,52].

2.2. Case Study Description

The case study is the La María multi-family residential building located in Seville, Spain. The building was promoted by EMVISESA, a public enterprise dedicated to the construction of public housing. The building total area is 2119.24 square meters, distributed across 5 levels (including the ground floor), and 16 apartments. Even though the structure is mainly composed of reinforced concrete and the foundations are composed of slab concrete, this study compares three alternative materials for the structure: timber (CLT), reinforced concrete, and steel (see Figure 2 and Table 3). The complete list of materials is included in the Supplementary Data.

2.3. Tool Development

The tool assumes that the BIM model and the objects contained in the BIM model include insufficient environmental, economic, and social data to conduct an automatic LCSA. To this end, it is necessary to enrich the BIM model. The tool integrates a predefined library of BIM objects (TBL database [31,45]) that are linked to the objects included in the model (Figure 3).
In this study, only the main structural elements are considered in the contribution to the environmental, economic, and social impacts of the project: mechanical, electrical, and MEP elements are excluded from the assessment. The LCSA calculation procedure consists of the multiplication of the bill of material quantities of each building element (from the BIM model) and the impact factor extracted from the TBL database. This procedure and the methodology assumed to conduct the LCSA has been described in previous studies [31,45]. Following the main steps to conduct the LCSA in BIM previously defined in Llatas et al. [31], (parameters assignment, material code assignment, LCSA calculation, and results visualization), this study focuses on developing a more stable and reproducible workflow to conduct reliable LCSA. Thus, it focuses on improving the user interface and the detection of errors in the BIM model, the usability and the materials assignment to the BIM model, the visualization of the LCSA results, and adding more flexibility to the values obtained (different formats). To improve the user interface, the BIM3LCA software creates a single shared parameter (BIM3LCA code) which is automatically assigned to the project’s general information together with elements from the BIM Model: foundations, columns, beams, floors, and walls. The user interface subsequently appears, thereby allowing us to find useful information regarding the BIM model: the different categories, element names, material, and volume information, and the BIM3LCA code to each element can be easily assigned.
The upgrade and optimization of previous developments [31] focuses on increasing the interaction between the model and the plug-in, to support the selection of the building elements.
To this end, and to improve in the detection of errors, the tool enables several verifications to be conducted to detect erratic elements (i.e., due to wrong imports from external models into Autodesk Revit) and to allow for the deletion of these elements and the correction of the imported BIM Model (Figure 4 and Figure 5) before the main user interface appears.
To improve the usability and the materials assignment to the BIM model, the user interface contained the items from the BIM3LCA TBL database which contained all the information required for the LCA, LCC, and S-LCA implementation (see Figure 6). This task can be performed in a single step using the box menu, which enabled automatic filters to detect the category of the elements selected (e.g., on selecting columns, all the items related to the element ‘Structural Columns’ were shown). To facilitate the assignment, the process of a table with all the filtered elements from the BIM Model were shown, displaying the name, BIM object code assigned, material names, and volumes of those elements.
To facilitate the LCSA implementation of the BIM Model, the BIM code from the dropdown list was used. This code related the name of the possible materials from the TBL database with the environmental, economic, and social values for the functional unit (1 cubic meter) of the different materials of the building elements. The window displayed the existing building elements of the selected type (e.g., column, slab, beam, foundation, and wall). Thus, once the code was selected, the ‘Assign Item to Revit Element’ button was used to confirm it. As a result, this information was saved into the selected elements of the BIM model.
To confirm the information added into the corresponding building elements, it was possible to verify whether the information has been successfully saved in the BIM model, which allows them to check the element’s properties in the Revit GUI (Figure 7).
Once the items were assigned with a BIM object code, the calculate button was pressed (Figure 6), the BIM3LCA plugin performed the LCSA calculation automatically and displayed the result in a pop-up window (Figure 8). This window displayed the triple dimension assessment based on the LCA, the LCC, and the S-LCA, of the different building life cycle stages (product, construction, and deconstruction) and life cycle information module (e.g., A1–A3, A5, C1, C2, C4), grouped into building element type (e.g., beam, column, foundation, slab, wall), and the global impact of those stages per dimension on the studied BIM model. This enhancement enables us to visualize the impacts of each of the building elements, life cycle stages, and total results per dimension, in order to implement measures for their potential reduction.
To add more flexibility to the values obtained and to enable their use in other formats, the plug-in not only enables us to visualize the charts (Figure 8), but also the Environmental, Economic and Social tabs can be exported to Microsoft Excel files, in order to extract new customized information (Figure 9).

3. Results

The tool validation was conducted on a case study where three building material alternatives were evaluated. To that end, three different BIM models that include different material (steel, concrete, and wood) for the structure were compared. The plug-in was executed in a few seconds and the results were displayed, and this enabled us to obtain a global perspective of the applied options, and to view which categories and stages have the most critical impact, which led us to decide which alternative is the optimal material for the BIM model.

Validation of the Tool in the Case Study Application

After the tool application to the case study alternative materials, the results for the LCSA were obtained. Figure 10, Figure 11 and Figure 12 show the screenshots of the values obtained considering the building elements, the LCSA stages, and the total value for each dimension.
It can be inferred from the evaluation of the different design solutions (Table 4), whereas Design Option 1 (timber) had the lowest in CO2 emissions, it had, on the other hand, the highest economic costs. However, Design Option 3 (steel) presented the lowest LCC and S-LCA with an intermediate environmental impact. This fact will be further discussed in Point 4.

4. Discussion

4.1. Lessons Learnt from the Tool Development

The results provide evidence that it is possible to conduct environmental, economic, and social impact calculations based on the LCSA method in real time within the BIM environment (RQ1) using a plug-in. The BIM3LCA structure development enables the simultaneous assessment of different BIM models (and files) and the visualization of the results within the BIM environment (native software where the building was modelled). This enables the designer to speed up the implementation of changes and modifications in real time without any other further steps (such as for the material quantities take-off process in the BIM model). This implies an improvement in aspects such as usability and data visualization compared to previous studies [31]. This study also provides evidence that the BIM3LCA structure tool enables an automatic multi-model assessment to be conducted to support the building material selection within the BIM environment (RQ2). In this vein, the use of the TBL database reduced the effort in the environmental, economic, and social data preparation and BIM workflow adaptation, compared to previous works in this field [43,53]. The authors demonstrate that the plug-in can develop automatic LCSA calculations and support designers in the decision-making process, thereby integrating a straightforward user interface and methods to simplify the detection of the modelling errors.
The selection of the best option was conducted using the real-time calculation of the LCSA to obtain the embodied carbon footprint, economic costs, and the working hours (for the assessment of the social impact).
This development demonstrates that the tool can identify the best option in the three assessed categories and dimensions and shows the greatest building elements (Ifc Building Element Class) contributors (such as IfcBeam, IfcColumn, IfcFoundation, IfcSlab, IfcWall), and LCA stages (such as Product and Construction, Use and End-of-Life).
Due to the relevance of the Life Cycle Inventory (LCI) [45] and the material quantity take-off in the LCSA implementation in BIM [54], the results for the manual and automatic material quantity were compared. Thus, to validate the consistency of the BIM3LCA results, a manual material quantity take-off is compared with that conducted by the plug-in of the existing materials in the BIM model. Table 3 shows that the material quantities extracted from the manual quantity take-off and the plug-in are very similar and that the variation is related to the digits considered after the decimal point. Given that the only possible variations are related to the material quantity take-off values, the results shown in Table 3 demonstrate the validation of the plug-in development using the LCSA-based method.
It is, therefore, demonstrated that by manually extracting the material quantities of the BIM objects and the material quantities used by the plug-in, similar values are obtained and those values are subsequently multiplied with the data from the TBL database (see Table 5). The timber option produces the least CO2 eq. emissions, the steel option is the cheapest, and the concrete option is the best in terms of its contribution to local employment in the construction sector. The results obtained are also aligned with other studies in this field [54,55] that compare the steel, concrete, and timber of the environmental impacts produced by building structure materials.

4.2. Limitations and Future Developments

From the current development, several limitations and future improvements have been detected. This present study identifies and focuses on the sustainability assessment in real-time, automatic assessment of different alternatives and materials, and using the plug-in to visualize the best option. However, what if a set of guidance quantitative values, such as the results for unit impacts (e.g., a cubic meter of a column or a square meter of a wall) for environmental, economic, and social impacts of different materials and building elements, are shown to the designer before deciding which material to use? Indeed, this type of information can help reduce the effort and time required in the modelling process, as well as raise awareness regarding the impacts and consequences of design decisions. Hence, user-centered decision tools not only focus on the assessment process and LCSA results, but also integrate quick and short paths towards identifying the best material (regarding diverse environmental, economic, and social dimensions) so that the required function can be considered for implementation in the future. Furthermore, feedback from designers, policy makers, and various stakeholders can use the tool to test the development and utility of this information in current practice [56].
The present study demonstrates the utility of the tool to conduct a Triple Bottom Line (TBL) sustainability assessment and to compare different materials in real time using a BIM model. However, the results obtained provide evidence of the discrepancy of the values for each of the dimensions and of the existing limitation in the weighting and multi-dimension decision making in the LCSA implementation [57]. The automatic integration of multi-criteria assessment using methods such as TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) [58,59,60] and AHP (Analytic Hierarchy Process) [61,62,63] can help the designer to select the most sustainable option by integrating a variety of categories.
Given the limitation of this development in conducting a whole life cycle building assessment, specifically in the modelling of the distances of transport, future research can focus on modelling transport distances from product manufacturer to site and from site to final disposal points (modules A4 and C2) using GIS (Geographic Information System) and automatic geolocation, such as in [64]. For the integration of other building systems to conduct a whole building LCSA, the main obstacle is the data availability, which means that the development of regionally representative data (environmental, economic, and social) needs to be increased. This plug-in uses manually created BIM objects (data collection and systematization); hence, future developments can focus on improving the automatic and semi-automatic BIM-object creation to enrich the existing database (BIM-TBL).
To increase the tool maturity level, this plug-in should be tested under a variety of case studies, thereby enriching the TBL database and testing different contexts (e.g., adjusting the tool development to different file format exchanges and building elements). This type of test can also help to define the most accurate material quantity take-off unit (e.g., volume and area) for each building element, whereby the lowest number of possible changes in the BIM model are included in the assessment of different material solutions. Moreover, different approaches to the quantity take-off variability can be verified that depend on the building elements, the functional units (for environmental, economic, and social data), and the possible variation of the design parameters (e.g., volume, thickness, and area).

5. Conclusions

There is a relatively new approach to the evaluation of building sustainability through the integration of environmental, economic, and social dimensions using a life cycle perspective (LCSA) and a quantitative assessment. This study aims to contribute to this field by developing the BIM3LCA structure tool to support the material selection during the design process. The case study validation demonstrates the consistency of the tool concerning the material quantity take-off and the building material assessment. The tool is developed in native BIM software to enable real-time LCSA calculations.
The main contribution of this approach involves the development and validation of the BIM3LCA plug-in, an automatic tool to conduct building LCSA in the early design stages and support the selection of the building materials. Given that most of the existing LCSA-based tools are focused on detailed design stages, this tool can help designers increase the consistency of LCSA results throughout the design process. Future research should be focused on improving the development of the tool in order to increase the decision-making potential in the early design steps. Moreover, the verification of further case studies should consider different technical solutions, typologies, and contexts.

Author Contributions

Conceptualization. B.S.-V., C.L.; methodology. B.S.-V., C.L.; software. J.A.G.M.; validation. B.S.-V., J.A.G.M. and C.L.; formal analysis. B.S.-V., J.A.G.M. investigation. B.S.-V., J.A.G.M. and C.L.; resources. B.S.-V., J.A.G.M.; data curation. B.S.-V., J.A.G.M. and C.L.; writing—original draft preparation. B.S.-V., J.A.G.M.; writing—review and editing. B.S.-V., C.L.; visualization. B.S.-V., J.A.G.M., supervision. C.L.; project administration. C.L.; funding acquisition. C.L. All authors have read and agreed to the published version of the manuscript.

Funding

The authors thank the Spanish Ministry of Science, Innovation and Universities, which supported the project Grant BIA2017-84830-R funded by MCIN/AEI/10.13039/501100011033 by ERDF A way of making Europe, the Spanish Ministry of Ecological Transition and the Demographic Challenge, which supported the project Grant TED2021-129542B-I00, the Junta de Andalucía and the ERDF A way of making Europe, for supporting the research project Grant P20_00541, and the Junta de Andalucía, Consejería de Fomento, Infraestructuras y Ordenación del Territorio for sup-porting the research, Grant US.20-03.

Data Availability Statement

Not applicable.

Acknowledgments

The authors thank Gabriel Verd Arquitectos and EMVISESA for providing the information about the building case study. The author thanks the participants in the research project Grant BIA2017-84830-R, the research project Grant P20_00541, the research project Grant US.20-03, and the research project Grant TED2021-129542B-I00 for their direct and indirect inputs to the study.

Conflicts of Interest

The authors declare there to be no conflict of interest.

Abbreviations

AHPAnalytic Hierarchy Process
APIApplication Programming Interface
BIMBuilding Information Modelling
DGNB German Sustainable Building Council
EMVISESA Empresa Municipal de Vivienda, Suelo y Equipamiento de Sevilla, S.A.
EPDEnvironmental Product Declaration
IFCIndustry Foundation Classes
GBRS Green Building Rating System
LCA Life Cycle Assessment
LCILife Cycle Inventory
LCSALife Cycle Sustainability Assessment
LCCLife Cycle Costing
LOD Level Of Development
GIS Geographic Information System
GUIGraphic User Interface
GWPGlobal Warming Potential
S-LCASocial Life Cycle Assessment
TBLTriple Bottom Line
TOPSISTechnique for Order of Preference by Similarity to Ideal Solution
WinForms Windows Form

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Figure 1. Schema of the methodology developed in this work.
Figure 1. Schema of the methodology developed in this work.
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Figure 2. 3D View of the material alternatives BIM model.
Figure 2. 3D View of the material alternatives BIM model.
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Figure 3. BIM3LCA User Interface.
Figure 3. BIM3LCA User Interface.
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Figure 4. BIM3LCA. Null Element Volume Detection.
Figure 4. BIM3LCA. Null Element Volume Detection.
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Figure 5. BIM3LCA. Null Element Material Volume Detection.
Figure 5. BIM3LCA. Null Element Material Volume Detection.
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Figure 6. BIM3LCA. Item category assignment.
Figure 6. BIM3LCA. Item category assignment.
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Figure 7. BIM3LCA. Item assignment verification.
Figure 7. BIM3LCA. Item assignment verification.
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Figure 8. BIM3LCA. Pop-up window of the LCSA results.
Figure 8. BIM3LCA. Pop-up window of the LCSA results.
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Figure 9. BIM3LCA. Pop-up window to export to Excel the LCSA results.
Figure 9. BIM3LCA. Pop-up window to export to Excel the LCSA results.
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Figure 10. Results for Design option 1 (timber and reinforced concrete).
Figure 10. Results for Design option 1 (timber and reinforced concrete).
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Figure 11. Results for Design option 2 (reinforced concrete).
Figure 11. Results for Design option 2 (reinforced concrete).
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Figure 12. Results for Design option 3 (steel and reinforced concrete).
Figure 12. Results for Design option 3 (steel and reinforced concrete).
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Table
Table 1. Information modules according to ISO 21931-1 [47].
Table 1. Information modules according to ISO 21931-1 [47].
Information Modules Building Sustainability Assessment
A0A1-A3A4A5B1B2B3B4B5B6B7B8C1C2C3C4D
Environmental
LCA		E X X XX X
O
Economic
LCC		E X X X
O
Social
S-LCA		E X XX X
O
A0: Land and associated fees/advice; A1: Raw material supply; A2: Transport and all upstream process from cradle to gate; A3: Manufacturing of products; A4: Transportation to the site; A5: Construction of the building, B1: Use; B2: Maintenance; B3: Repair; B4: Replacement; B5: Refurbishment; B6 to B8: Use of energy resources, use of material resources, use of water and building user’s activities not covered in B1-B7, C1: Deconstruction/Demolition; C2: Transport waste processing of disposal; C3: Waste processing; C4: Disposal; D: Potential net benefits from reuse, recycling and or energy recovery, beyond the system boundary. Fuente: ISO 21931-1 (ISO, 2022).
Table
Table 2. Description of the data input and output for the plug-in application.
Table 2. Description of the data input and output for the plug-in application.
Data input
LCALCCS-LCA
BIM modelBuilding elements volumesBuilding elements volumesBuilding elements volumes
TBL database
Data output
LCALCCS-LCA
Impact
category and
indicator		CO2 eq. emissionsEurosWorking hours
Table
Table 3. Description of the main materials included in the design options.
Table 3. Description of the main materials included in the design options.
Design Option 1Design Option 2Design Option 3
FoundationsReinforced Concrete H25Reinforced Concrete H25Reinforced Concrete H25
Retaining wallsReinforced Concrete H25Reinforced Concrete H25Reinforced Concrete H25
BeamsWood M24Reinforced Concrete H25Steel
ColumnsWood M24Reinforced Concrete H25Steel
SlabsWood CLTReinforced Concrete H25Collaborating and
(collaborating) metal sheet
Table
Table 4. Summary of the results for the three material alternatives.
Table 4. Summary of the results for the three material alternatives.
Environmental
(Kg. CO2 eq.)		Economic
(Euros)		Social
(Working Hours)
Timber273,904787,4558003
Concrete474,249569,86710,423
Steel337,087423,2807249
Table
Table 5. Description of the main materials (Material Volume in m3) included in the design options.
Table 5. Description of the main materials (Material Volume in m3) included in the design options.
Design Option 1Design Option 2Design Option 3
Manual
Extraction		Plug-InManual
Extraction		Plug-InManual
Extraction		Plug-In
Foundations191.30191.2970291.14291.1433191.30191.2970
Retaining walls106.63106.6320163.54163.5176106.63106.6320
Beams35.9035.900625.8825.87874.194.1946
Columns38.7738.768452.1452.19911.901.9032
Slabs542.64542.6368633.31633.3076460.49460.4912
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Soust-Verdaguer, B.; Gutiérrez Moreno, J.A.; Llatas, C. Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM. Sustainability 2023, 15, 2274. https://doi.org/10.3390/su15032274

AMA Style

Soust-Verdaguer B, Gutiérrez Moreno JA, Llatas C. Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM. Sustainability. 2023; 15(3):2274. https://doi.org/10.3390/su15032274

Chicago/Turabian Style

Soust-Verdaguer, Bernardette, José Antonio Gutiérrez Moreno, and Carmen Llatas. 2023. "Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM" Sustainability 15, no. 3: 2274. https://doi.org/10.3390/su15032274

APA Style

Soust-Verdaguer, B., Gutiérrez Moreno, J. A., & Llatas, C. (2023). Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM. Sustainability, 15(3), 2274. https://doi.org/10.3390/su15032274

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