Framework for parametric assessment of operational and embodied energy impacts utilising BIM

ABSTRACT In recent years advances in digital tools have been leading the way in the construction of cleaner, more energy-efficient buildings. Furthermore, improvements in Building Information Modelling (BIM) have resulted in various tools being used to assess building performance and overall Life Cycle Analysis (LCA). This work offers a unique insight into the development of a parametric LCA BIM tool, focusing on both operational and embodied energy perspectives through case study analysis of a commercial and a domestic building in the UK. A mixed research method was employed combining a literature review, qualitative and quantitative LCA case study analysis, and parametric modelling. The results indicate that embodied energy is much more critical in the early stages of the building’s life, then is quickly overtaken by operational energy. In addition, many variations exist in energy outputs between domestic and commercial buildings. Operational energy takes a significant share in domestic buildings compared to commercial buildings. These variations are attributed to different design methods, construction materials, occupancy patterns and energy demands. The study proposes an LCA-BIM interactive user-led method of addressing energy hotspots for both operational and embodied elements, which can provide more instant identification of energy critical areas. Such an approach can offer real alternative BIM-based analysis tools during the design stages, compared to those currently being used, which focus mainly on either LCA of operational or embodied energy.


Framework for parametric assessment of operational and embodied energy impacts utilising BIM
Zaid Alwan* a , Amalka Nawarathna a ; Rana Ayman a , Mingyu Zhu b Yomna Elghazi

Introduction
The architecture, engineering, and construction (AEC) sector is recognised to be a major consumer of non-renewable energy and source of carbon emissions. It is responsible for 35% of global energy consumption and 38% of energy related global carbon emissions [1]. Of this 35%, 30% comes from the operational energy (OE) [1] that buildings use in operational activities such as heating, cooling, lighting, and building appliances [2]. Significant advances in both legislative measures and technologies have resulted in building mechanical systems becoming more efficient in terms of OE consumption [3], but this has caused the embodied energy (EE) share of whole life cycle energy, i.e.
the energy required by all the processes associated with building production, to increase [2], [4]. Until recently, the EE share of buildings was not always fully accounted for due to the complexity and timeconsuming nature of its assessment, compared to operational energy use. However, in recent years it has become the focus of both policymakers and researchers wishing to optimise the total energy consumption of buildings throughout the life cycle [2], [5]. To enable the AEC sector to meet the 2015 Paris Agreement goals [6] and United Nations (UN) sustainable development goals, equal attention to both operational and embodied energy impacts is required.
Life cycle assessment (LCA) approaches are widely used to estimate the environmental impacts of J o u r n a l P r e -p r o o f buildings during their whole life cycle, from raw materials extraction to the end of life [8], [9]. However, the depth and breadth of LCA analysis has been a source of confusion and frustration for researchers as well as professionals in the AEC sector, due to the variables of material harmonisation [10] and boundary conditions [11]. Accordingly, the current research discussed in this paper follows international standards, using the methodological framework which has been described in ISO 14040 [12] for estimating and evaluating environmental impact throughout a product or service system life cycle, from cradle to gate. According to this, LCA comprises four phases: goal and scope definition, life cycle inventory (LCI), life cycle impact assessment (LCIA), and interpretation (ISO 14040, 2006).
Firstly, the goal and scope definition phase establishes the goal, system boundaries and level of detail of the LCA. The second phase, life cycle inventory (LCI), involves collecting and synthesising input/output data relating to the building being studied. The third phase, life cycle impact assessment (LCIA), involves evaluating the significance of potential environmental impacts using the LCI results.
Typically, LCI and LCIA are merged and simplified in building analysis [13], [14]. The last phase, interpretation, deals with the demonstration of results from both LCI and LCIA. It includes summarising, drawing conclusions and recommendations, and decision-making in compliance with the goal and scope of the study.
With regard to EE assessment, generally, the bill of quantities (BOQ) is required: the quantity of individual materials or components is multiplied by the energy coefficient extracted from a specific LCA database. Numerous LCA databases are available from which to extract coefficients of materials and components, for instance: Inventory of Carbon and Energy (ICE) [15]; ecoinvent 3.3 [16]; ÖKOBAUDAT [17]; and Athena Life Cycle Inventory Product Databases [18]. However, this manual estimation approach is very time-consuming; much effort is needed to establish the BOQ and find the correct coefficients of building materials from LCA databases, which are mostly either country-specific or region-specific [19], [20].
A complete LCA of whole energy consumption will normally be considered when complete architectural construction and mechanical details for a project are identified. By then, it is often too late to consider potential substitutions of materials, components or systems to make the building more energy efficient. Early analysis in the architectural design process could be highly beneficial in enabling the minimisation of environmental impact [21]. In addition, LCA analysis needs to feature in J o u r n a l P r e -p r o o f the current digitalisation drive of buildings, as opposed to current manual calculations [22]. BIM, with its many benefits, has been a transformative tool within the AEC sector [23]. In addition, in the last few years BIM maturity within projects has been assessed with reference to LCA from associated cost [24] to Global Warming Potential (GWP) assessment [25] and sustainable project delivery. Accordingly, there are opportunities available to optimise energy consumption by further improving design and construction using BIM.
While many academic publications have focused mainly on impacts of operational and embodied energy and their associated carbon in isolation, the critical focus in this research is in terms of the challenges of a whole cycle approach for both EE and OE, and the most effective way to obtain meaningful answers within the AEC sector utilising BIM. No academic studies exist that link both operational and embodied aspects of energy in one tool for the AEC sector from a UK perspective.

Aim and objectives
The aim of this research was to develop a single parametric BIM and whole LCA-based tool that can be used to estimate both operational and embodied energy of buildings in the UK context. The research aim was delivered through the following objectives: 1) Identification and critique of existing BIM has made significant impacts in transforming day-to-day operations within the AEC industry through promoting collaborative culture and project delivery [26] and enhancing performance across the building and infrastructure life cycle [27]. Incorporating energy analysis into BIM during the design stage would provide many benefits, including giving more consideration to alternative options which would optimise the whole building life cycle energy consumption [28]. A number of innovative methods have been used recently, integrating LCA [19] and operational energy assessment within BIM processes [29], but the literature contains few research contributions on integrating whole building life cycle energy analysis and utilising BIM to optimise total energy consumption. This systematic analysis explores the challenges faced in using existing tools for whole building life cycle energy analysis in BIM-based projects. The current BIM-based sustainability and LCA processes are summarised in Figure 1 and Figure 2, which show standalone energy simulation systems and semiintegrated BIM approaches, respectively.  The complexity of using both of the above methods for material and energy properties leads to possible data loss. When it comes to analysing a model, designers and others have to do additional work to make sure the information is accurate. This process is time-consuming and requires IT skills which are not always available to the sector. In addition, very few studies have focused on linking workflow obstacles of green projects to potential improvements using current BIM capabilities [30].
Fully integrated LCA analysis systems do not exist; this area is often overlooked in favour of software used for design and construction planning.

Challenges in using existing BIM tools for whole life cycle energy analysis
Many researchers in the AEC sector have highlighted that estimating total energy within design projects is challenging [31], [32]. LCA BIM-based energy analysis is increasing [33], and many off-theshelf systems exist [19]. However, their uptake has been limited due to economic and technical issues J o u r n a l P r e -p r o o f (see Table 1). Many challenges remain, as will be highlighted in this section. While tools exist, their application is limited in terms of accounting whole LCA impacts, and there are numerous issues with interoperability and BIM access to databases [34], [35]. Reluctance within the AEC sector to adopt LCA BIM is a big challenge. A recent national UK BIM adoption survey [36] indicated that the use of BIM to meet sustainability targets is a low priority when it comes to applying BIM to a project. While the sector is under pressure to adopt global sustainability measures and meet sustainable development goals (SDG), it appears the BIM agenda still revolves around improving design quality, increasing productivity, and enabling collaboration. In reality, BIM also needs to be adopted as a framework for sustainability analysis energy reduction targets, and can be applied to different stages of projects. It has been demonstrated that the use of innovative applications in the construction industry, such as modern methods of construction and offsite manufacture, utilised within BIM [37], can help with addressing current environmental pressures; the Framework of Sustainable Strategic Development (FSSD) [38], is one example which may help the sector become more accepting of sustainability challenges.  [46], which uses a series of dynamo scripts to build a material library with the required inventory database and the quantities modelled in Revit, with visualisation options. In summary, many researchers at present are striving to provide a dynamic, flexible tool using programming languages to deal directly with the BIM model, and this trend is likely to continue with increased digitalisation and automation of the process.

Complexity of mapping life cycle input data and level of details in building BIM models
The complexity and time-consuming nature of mapping life cycle input data with building material quantities are the main challenges of using existing tools [33]. The multiple manual inputs required to J o u r n a l P r e -p r o o f match the sustainability data with the material properties database is impractical because it takes a long time and means high susceptibility to errors during transfer, as highlighted in section 2.1. A critical aspect of BIM is the level of details or developments (LOD) of the model, which is typically LOD 100 for concept design, rising to LOD500 as built. Typically, studies have looked at high LODs of 300 and above, but for LCA to be effective, the analysis needs to cover the early stages of design as well [19], [47]. However, not all projects consist of elements that are accurate or fully coordinated at LOD 300. Alwan and Gledson (2015) [48] provide a concept for a theoretical framework, linking LOD levels to building performance utilising green buildings certification and retrofitting.
The current approach of using both manual (by professionals within the AEC sector) and commercial calculation tools is often based on BOQ and presented as a solution to energy and carbon accounting for a project's LCA carbon impact. It is anticipated that the framework presented will address the current gaps of the LCA-BIM one platform approach and identify crucial elements for such a platform, rethinking or mitigating the impact within LCA-BIM for both EE and OE, rather than relying on lastminute accounting.
LOD is related to the inventory database of building elements, that are refined in the design process, and can be used in material calculations [19]. There are three levels of detail building level: element level, component level and materials level. For example, the Swiss Buildings Database gives an estimate which can be used at the concept stage . For LOD 100, European Bauteilkatalog element library average values can be used, for LOD 200, 300 component level such as "gypsum board twin metal frame wall" or a "brick cavity insulated wall" are classified as one element. The last level is LOD 300 and 400 with a specific coefficient value provided to a material such as brick and rockwool insulation gypsum board for example. In the UK , the ICE database used in this study can be applied at later LOD stages only. There are limited database options that can be used at different LOD stages, therefore LOD 300, or above LOD3 as defined in NBS BIM toolkit [49], is adopted in this case study. It can be concluded that for predictive BIM analysis to work, there needs to be synergy between global databases and LOD levels. It should also be highlighted that there is more than one way of expressing LOD. The NBS definition of LOD is LOD 1, 2, 3, 4, rather than LOD 200, 300, 350, 400, which is the North American standard, and which is widely used worldwide.

Methodology
In order to achieve the research aim and present in one unified approach a whole life parametric J o u r n a l P r e -p r o o f energy estimation tool, both qualitative and quantitative methods using BIM were employed. In the first part, current BIM concepts of digitalisation workflows were applied to two case studies, one commercial and one domestic (see Figure 3 and 4), focusing on both operational and embodied energy perspectives in order to identify the major energy critical elements. The second part involved the development of a parametric user-led LCA-BIM whole system platform within BIM. The outputs from the case studies were key in enabling the identification of the parametric framework to analyse key operational and embodied components. It is expected that this approach will form a combined analysis of both EE and OE, which could be adopted and used within the AEC sector.

Boundary for construction elements in BIM
The part of the method that involves identifying construction elements is essential, as the selection of J o u r n a l P r e -p r o o f the correct co-efficient for EE and OE will be limited to certain stages of the building analysis. Whole impact assessment of every single component is almost impossible, as a building might comprise 1000+ items or types of material, therefore a focus on EE of major building materials' impacts has been adopted. As described in the introduction, LCA begins with goal and scope definition.
Accordingly, systematic mapping was carried out with the aid of BS EN 15978:2011, Building Cost Information Service (BCIS) elements classification, and Royal Institute of British Architects (RIBA) building development stages, as presented in Figure 5, which explains the boundary of the study for both EE and OE.

Assessment of operational and embodied energy within the design process
The building elements that were chosen for the EE estimation were termed critical embodied and operational "energy hotspots", due to their larger volume and energy consumption. This was a unique feature of this research and was used in order to give a true reflection of the critical elements when considering whole energy LCA within BIM. This numerical operational modelling was developed to J o u r n a l P r e -p r o o f give a realistic measure of current energy consumption for the case studies, based on typical energy consumption in the UK context. This will most likely differ between commercial and domestic buildings due to their differing patterns of use. One commercial and one domestic case study were selected in order to explore where energy was consumed in both operations and materials LCA, thus providing valuable input for the parametric LCA framework regarding what should be included in terms of energy input ratios.
The LOD used to extract the BOQ of both building typesthe domestic and commercial case studies -was categorised as graphical model elements in terms of quantity, size, shape, and location. This information also covers non-graphical data on materials, such as construction block types, windows, and glazing units' thermal performance, as different construction approaches may result in different OE demand, for example.
The commercial case study was a virtual project developed by a BIM-specific training firm, White Frog (2020) [50] in conjunction with the BIM Academy (see Figure 3). This virtual project was selected because it was specifically developed to replicate an actual office, and it has been widely used for training purposes by the BIM Academy [51]. It is anticipated that the findings of this research will be used in future training programmes involving AEC sector professionals. BDN Limited, an architecture firm, provided the domestic case study, which is located in the North of England. The project is exemplary in utilising Modern Methods of Construction (MMC) through 3D BIM offsite cleaner fabrication and addressing many low carbon considerations (see Figure 4). Both case studies were representative of the UK construction sector; however, the methodology of this research can be applied to other construction types, and is not exclusive to the UK.
The characteristics and materials of the case studies were as follows: the commercial office consisted of a steel frame, glazing and precast concrete slabs as a construction option and mixed mode ventilation system. Using a steel frame means more rapid construction time and lower construction costs. A mixed mode or hybrid ventilation system has the advantage of allowing users to maximise passive cooling and utilisation of mechanical systems in extreme hot or cold conditions.
The domestic building was of lightweight insulated concrete block construction, with external expanded polystyrene EPS insulation board and render finish. The house was serviced by an air J o u r n a l P r e -p r o o f source heat pump and underfloor heating in the main living areas, which is typical in the UK environment where summer cooling is seldom required, but winter heating is necessary.

Establishment of embodied energy building profile within BIM through case study analysis
In this study LOD 300 was used, which is equivalent to LOD 3 as defined in the NBS digital toolkit [49] definition of deliverables. BOQs were extracted and automated using a BIM-based approach at LOD 300 and within the boundary set in Figure 5. 3D models of the case studies were analysed, and volumes were extracted and linked to material information for different Revit files, populating the model with appropriate data taken from the ICE 2.0 database [15], a UK-based database which details the embodied energy and carbon of over 120 materials; it is free to use and not countryspecific. The developed model was used to extract BOQ materials, estimates of missing information were documented and applied and then mapped to material-specific values in the ICE database using an Excel sheet. In this quantitative method, using correct building models generated within BIM frameworks, both the quantities and density of the major building elements were established using the EE factors from the ICE database. Areas outside the research boundary (such as secondary materials and furnishing) were not included in the analysis. Finally, a parametric script on Rhino was developed to enable a dynamic iterative approach in order to eliminate the manual work required to map materials on Excel, which will be explained further in section 5.2. (GWP)), and OE data in kW/m 2 generated (representing use). The most commonly used unit for energy in the AEC sector is kWh/m2, so all of the data was converted into kWh for use in the next stage of the process, which concerned which elements can be controlled in a parametric design and altered within the early stages of design.

Synthesis of energy critical OE and EE elements in BIM parametric lens
A parametric script was developed and adapted for UK conditions using modelling software Grasshopper (GH), generating suitable matrices for total energy intensity. The parametric design is useful as it can be used to study the impact of geometric and material variables on environmental aspects, namely embodied energy and operational costs. Parametric tools can also be used to increase awareness in the AEC sector of the potential effects of design and material decisions, due to their interactivity. In this case, a specific LCA plug-in was designed for GH. The script is free and available at Food4Rhino 2 . This has been used and optimised for the first time for complete energy analysis in the UK context. The tool can be used to perform functions similar to the calculation of BOQs, and linked to a database library based on UK environmental conditions and outputs from the case studies. Crucially, it includes the ability to carry out dashboarding of the elements to limit its impact, and can be controlled by the user.

Results
The aim of this research was to adapt existing BIM concepts of digitalisation of design and  Table 2 (see Appendix 1 for the full analysis of both sets of building results). The results indicate that the density of the material rather than its volume plays a significant role in its overall energy impact. MJ, which is an indication of GWP, is the obvious choice for measuring EE as a functional unit within an ICE database. A full breakdown of the major construction elements is provided in Figure 6 and Figure 7, showing the EE for both the commercial and domestic case studies, extracted from the BIM model. It can be seen that the substructure was by far the biggest contributor in the domestic case study, while the roof (followed closely by the substructure) was the greatest contributor in the commercial setting.
Elements near the end of the design process were unlikely to show more variation as the design J o u r n a l P r e -p r o o f process was near end of LOD 300; in both cases, concrete constituted more than 60%, which is hugely significant. OE analyses for the domestic case study revealed that space heating in the winter months, followed by appliances, was by far the highest contributor (see Figure 8). On the other hand, in the commercial setting, the greatest OE impact arose from mechanical systems and heating and cooling, with different zones of the building having markedly different contributions (see Figure 9). Once a building is occupied, another phase of accounting for both OE and EE impact starts and continues over its lifetime. By aggregating the results for all the building elements and performing analyses at the building level over a ten-year future horizon (see Figure 10 and 11) for both of the case studies, interesting variations emerged relating to the impact of operational and embodied elements. It was assumed that a building's operational energy impact will be the same every year to J o u r n a l P r e -p r o o f maintain lighting, heating etc., so that it will increase over 10 years, while the embodied impact locked into the material will remain static for 10 years, unless major renovations are carried out to the building's fabric. This appears to be a straightforward modelling assumption. However, and more crucially, there were significant differences in the elements accounting of building materials for commercial and domestic buildings. When considering LCA and overall energy use of buildings, it is important to take a longerterm view of both EE and OE.

Discussion
This section discusses the findings of the case study analysis and the challenges facing not only researchers but also AEC practitioners in accounting for overall energy and LCA processes. The case study analysis showed different hot spots for total energy use, and the results were used to develop a parametric framework within LCA-BIM. Parametric modelling is suggested as a future approach for interactive BIM energy analysis for the AEC sector.

Different characteristics of benchmarks for domestic and commercial buildings
One of the objectives of the research was to get more accurate LCA data by evaluating the impact of both operational and embodied energy of buildings in the UK context within an LCA-BIM tool.
Previous research, which looked at the embodied aspects of materials alone, and did not account for operational energy use, only gave half the picture of true LCA. Without accounting for operational energy, we cannot reflect on the full impacts in terms of buildings' total LCA.
The work has demonstrated that this can be done from a BIM perspective in a 3D environment through operational and embodied analysis with different geometries and different building types.  Figure 12 in the development of key aspects of the resulting parametric framework.
Clear differences exist between profiles of EE and OE, as can be demonstrated in Table 3, showing an attempt at benchmarking in kWh and MJ units, which can be entered into a BIM parametric platform as indicators of use and LCA for buildings from a UK perspective. The results clearly indicate that the commercial case study had a more significant EE impact than the domestic one, suggesting that EE is more significant in commercial buildings; meanwhile, OE makes up a larger share of overall impact for domestic buildings. This suggests that it is vital to assess operational impacts at the design stage, a process that is often currently overlooked.  is safe to assume that information about total energy and associated carbon kgCO 2 of MJ/kg can have much greater environmental value if captured early at the design stage, rather than five or ten years after the building has been built.

BIM as an iterative unified parametric design tool for effective LCA of whole energy and feedback
While the development of parametric modelling for environmental assessment has been addressed by previous research in terms of its challenges [55], its application within BIM has been relatively underutilised and, more importantly, does not exist within commercial software packages used in BIM.
The unique framework (see Figure 12) was developed based on the outputs from EE and OE analysis of key energy outputs and hotspots of GWP in MJ and kWh in the commercial and domestic case studies. It allows users to carry out quick and timely analysis so they can use the feedback immediately for real-time design decisions affecting current and later stages of the design LOD 300 within BIM, incorporating the assessment of operational energy. The system allows users to integrate different kinds of material libraries from different countries or regions. It can also be linked back to ranges of operational energy consumption patterns and benchmarks. In addition, the calculated operational cost considers variations of the impact of day/night temperature , and especially changes in the weather over the year, by using the weather data files. J o u r n a l P r e -p r o o f The key geometrical elements of the model were linked to the materials and simulated using parametric script linking seven key elements, as shown in Figure 12. The results for heating, cooling, lighting, and electrical appliances were collected, and the results were aggregated together to represent the total annual operational energy consumption (OE). For calculating EE, different areas were linked to their materials, along with their mass and EE factor, to measure the layer's impact, followed by the component's impact and total EE values. This unique approach of linking most of the critical OE and EE aspects in one approach is key from a building analysis point of view.
The proposed framework is suitable for further development, with the potential to add more layers of data; for instance, to profile the differential impacts of building occupancy, use type, lifetime of building, and any future refurbishments. The results have indicated that domestic buildings' operational energy impact becomes more significant and rapidly overtakes the impact of materials over a ten-year period. Within a parametric model, operational energy use (e.g. heating and lighting) can be adjusted using a dashboarding system, and advance modelling of how design affects operational energy use (e.g. height of walls) is possible. This is likely to be highly useful to AEC professionals, who want rapid results and instant feedback without the additional effort of accessing a separate database outside the BIM domain.

J o u r n a l P r e -p r o o f
Rhino/Grasshopper as a tool is used by creative designers for free form generation and creative building structures, but the software has greater analytical potential if adopted in the right way. For example, a critical look at the application of parametric methods in the practice of design reveals use is still predominantly based on aesthetic, structural, and fabrication criteria [56] while its applications for building performance and daylighting research are still growing [57].
In the proposed tool ( Figure 12), a unique integration was carried out by linking an EE database (ICE) and an OE database (Energyplus+). The Bombyx plug (energy analysis), developed by ETH in Switzerland, was adapted and used in a UK context [58]. ETH Zurich researchers have expressed interest in further collaboration and development and have made a version of this available online [59].
One positive aspect of this system is that it can be adopted to different regions, depending on local environmental factors and different types of databases. This can be facilitated through the opensource, codes, and plug-ins, which are downloadable through the grasshopper community [60].
These plug-ins cover aspects such as daylight and shading. In addition, energy profiles for occupancy loads, energy consumption, and the script are modified according to the requirements of specific geographical locations and environmental priorities. For example, hot dry regions of the world will adapt the script to have more focus on shading, while a temperate region will focus on material use and heating options. Similarly, the materials library of BIM objects and environmental impact vary depending on the databases and energy intensity associated with material production. Figure 13 shows how the tool allows the user to manipulate elements of the design, such as height, and the impact of such changes on operational energy, within a domestic case study. The software development in this section gives an insight into how LCA analysis can be approached within a UK context, and the results of this work will be added to the community depository for anyone to download.
J o u r n a l P r e -p r o o f It is not common for architecture practices to adopt standalone parametric modelling with no upper or lower material or energy range limit. The current framework offers a dashboarding system based on UK building regulations, which the user can influence for immediate results. A tool such as this one may provide important early level design input regarding which areas have the greatest impact, depending on building type, allowing the user to model, demonstrate and influence change.

A plethora of different LCA datasets and benchmarks
Findings from the literature and the research suggest that while parametric whole LCA for impacts is possible, confusion lies in the range of software and datasets available, and choosing which is the best one to apply. While adaptation to calculation methods for embodied impacts is challenging, issues with material libraries for LCA calculations can be confusing for professionals in the AEC sector. Similar work was done using a European Swiss database (KBOB, 2017), and it was noted that the approach to GWP was very different to that of the UK-based ICE database. Another factor to consider is different BIM-based methodologies for environmental impacts. In the domestic case study, BREDEM energy modelling proved an effective methodology for domestic energy analysis in the UK,

J o u r n a l P r e -p r o o f
In different parts of the world there will be different databases for both OE and EE, and associated carbon counting, as well as different policy procedures for integration of embodied impacts. For example, in the Netherlands it is a legislative requirement to carry out a LCA; while in British Columbia in Canada, embodied carbon assessment is mandatory, all projects are required to report it, and there is a target for a 40% reduction in embodied impacts by 2030 [61]. In the digital world of global collaboration, a unifying global approach is needed to guide AEC practices.

Virtual reality to enhance BIM and digital representation of impacts
For AEC experts and other stakeholders to engage with the impacts of parametric modelling, instant and accessible feedback is needed, and this may be difficult to achieve through the cumbersome task of operating a parametric dashboard, which also needs technical skills. The research team is currently investigating better visualisation of the parametric tool within BIM, so that users and stakeholders can better relate to overall total parametric LCA within Virtual Reality (VR) (see Figure 14). In recent years VR technology has been applied to facilitate design, construction, and management for the built environment [62]. VR programmes' ability to integrate with BIM and the live synchronisation between the BIM and the VR model enables auto-updates in real-time. In reality, terms such as GWP, kgCO 2 , MJ/kg, and kWh might be hard to interpret in architecture offices, and even for many AEC professionals, and their application in an immersive environment may be more convincing. The application of VR in LCA can diminish discrepancies at the source. Furthermore, despite the different technical backgrounds of users, participants have been shown to positively embrace the ideas and aspirations of VR [63].
J o u r n a l P r e -p r o o f Visual programming, if done well, can provide immediate information that can be acted upon straight away, providing an important link between geometry and the data [64], and this novel approach may persuade the sector to consider LCA as a major priority within BIM. The use of computer-generated VR imagery, such as flythrough animations and interactive solutions, is not new to the sector [65] and has been used in marketing and design representations, although not previously as an LCA concept.
Virtual models have the benefit of dynamic information input and output, which can be integrated into a BIM model. As the parametric LCA total analysis is evolving, physical live data such as climate and material and EE can be exported from the GH model in Figure 10 and integrated in the virtual model using VR gaming technology, Unreal gaming engine [66].

BIM as a driver for change and cleaner fabrication
This study has demonstrated that utilising BIM to address areas of the greatest energy impact -"Hotspots" -is possible for the purpose of total energy LCA analysis in building projects. Such results can feed into ISO 14040 or the BIM Execution Plan [67], which facilitates the implementation of energy and other LCA targets in a BIM project. Furthermore, links between parametric LCA and other established BIM procedures can be made, such as the National Building Specifications (NBS) BIM library, which is recognised internationally.
The availability of standardised components for BIM objects such as NBS is becoming more common for design consideration [68], and moves for fabrication and offsite manufacturing can be BIMintegrated [37]. The dynamic framework proposed can allow for material substitution for cleaner standardised components such as walls and other equipment, allowing more opportunities for innovation and collaboration in new production processes for design and construction .

J o u r n a l P r e -p r o o f
Future legislative pressure and targets for BIM frameworks should be integrated within building performance and linked to LCA. The AEC sector is at a crossroads with the new construction revolution 4:0 [69], which requires the industry to transform itself to incorporate more automation and digitalisation. The sector is already lacking in competitiveness, as highlighted by the Construction Leadership Council [70], because of its low levels of research and innovation. It is critical that such challenges are addressed, and LCA accountability which leads to sustainability by innovation could help to achieve this.

Advantages and limitations of BIM-LCA approach
The novel approach outlined in this paper involves combining both OE and EE use and linking the outputs to a range of data benchmarks, or ones set by users. This can in turn be linked to a VR domain to allow users to analyse energy consumption data in a user-friendly fashion. Currently, professionals consider each element of building design in isolation when it comes to building evaluation of construction projects and decision-making on the addition of renewables or low carbon materials. Building parametric intelligence into BIM-LCA models provides a great deal of design power in terms of allowing parametric decisions control for decision-making. For instance, within the BIM model, constraints can be built in for specific materials not to exceed certain benchmarks for EE and OE within a project, meaning low energy alternatives or carbon solutions have to be sought. The benchmarks in Table 3 could act as standards for commercial and domestic scenarios.
It is also worth noting that the framework tool is at an early design stage and is likely to mature and evolve, with more established benchmarks and better material libraries being developed, especially for EE aspects. One potential limitation to consider in terms of wider adoption of such tools is that while design iterations can be quick and link to databases, parametric design and BIM integration can be a steep learning curve for professionals in the AEC sector, almost akin to learning from 3D, and constituting a huge move from the traditional 2D approach. Finally, construction projects and the market have to be ready to adopt such a data-driven approach for it to be successful, if wider adoption is to be realised in the long term. This unique approach, which has not been attempted before, enhances the feasibility of dashboarding and testing of sustainable alternatives, for both operational and embodied aspects. This method of visual scripting potentially provides more flexibility, allowing the designer to focus on the impact of major building elements. The addition of benchmarks could be used to further improve the proposed framework, and additional case studies should be investigated in different national and regional contexts.

Conclusion
Providing a range including upper and lower limits for AEC practitioners, as well as benchmarks, is vital for the tool to be a success. Visualisation of results is key: it is much more important to show a convincing impact of a few major hotspots in, for instance, a VR domain, rather than total energy impact in a hard-to-interpret graphic. There needs to be further integration of LCA in terms of simulation and existing BIM protocols, BIM objects and governmental drivers, otherwise a standalone LCA tool will not be effective in the long term.