BIM- and GIS-Based Life-Cycle-Assessment Framework for Enhancing Eco Efficiency and Sustainability in the Construction Sector

Abstract

The world is progressing towards sustainable, eco-friendly, recyclable materials to enhance the circular economy and mitigate the issues of carbon footprint, overburdened landfills, and waste of natural resources. As increasing greenhouse gas (GHG) emissions are a major contributor towards climate change and given that the construction industry is one of the major producers of GHG emissions, it is crucial to meticulously quantify and lower its emissions, especially in the context of developing countries. This research presents a novel framework by combining advanced tools i.e., building information modeling (BIM), life-cycle assessment (LCA), geographic information systems (GISs), and quantification of embodied emissions to optimize construction’s design, material-selection, operations, maintenance, and waste-management processes. The effectiveness of the proposed approach has been demonstrated with the help of a real-world case study in Islamabad, Pakistan. A building model has been generated using BIM, and a comprehensive LCA has been conducted. Additionally, GIS tools have been utilized to identify the locations and accessibility of available-waste-management facilities. Based on this data, embodied emissions related to handling and transportation of waste material to disposal facilities have been computed using mathematical analyses. Furthermore, targeted mitigation strategies have been proposed and an optimized route has been designed using GIS-based route-optimization tools along the suggested facility centers in the Islamabad region. The case study has been reassessed with alleviation strategies, and the results show that 29.35% of the materialization stage, 16.04% of the operational stage, and 21.14% of the end-of-life-phase GHG emissions can be effectively reduced. Hence, pre-evaluating the environmental degradation caused by construction projects throughout their life cycle might offer an opportunity to comprehend and reduce prospective environmental impacts.

1. Introduction

The construction sector is one of the paramount sources of environmental depredation owing to the manufacturing of construction materials and direct or indirect energy use throughout the construction, operation, and end-of-life phases. Over 39% of annual worldwide carbon emissions are caused by the construction industry [1,2]. European Union-member countries account for 50% of global-warming emissions [3]. Annual production on the European continent is close to 890 million tons [4], while China alone almost produces 1.13 billion tons of construction waste [5]. Furthermore, Pakistan’s extensive construction projects have an impact on 34% of the country’s natural energy resources and 67.5% of the ecology [6]. There is a lack of a holistic approach that promotes a circular economy and lowers energy consumption, greenhouse gas (GHG) emissions, and waste production, particularly in developing nations [7]. It is apparent, from global policy initiatives and the increasing number of publications on the subject of reducing waste generation and ecological effects, that the world is moving towards sustainable, recyclable, economical, and environmentally friendly approaches to strengthen the circular economy and to alleviate the issues of surging waste generation, GHG emissions, overburdened landfills, and degradation of natural resources [8,9,10,11]. Therefore, a sustainable and ecologically sound framework should be adopted to utilize and integrate innovative construction materials, advanced methods, modern designs, and digital technologies that will revamp the environment.

Rising environmental degradation poses a critical threat and has gained significant attention around the globe. Approaches available in the literature, i.e., utilizing the life-cycle assessment (LCA), a procedure that is used to systematically evaluate a project or product’s inputs, outputs, and potential environmental effect [12], has been used often to evaluate the impact of buildings on the environment. LCA has provided promising results for formulating mitigation strategies. Kamari et al. assessed phases of the life cycle of buildings to identify the phase with the highest environmental impact at the design stage [13]. Norman et al. studied the energy use and greenhouse gas emissions of highly and low-populated buildings to demonstrate the effects of urban density [14]. Schenk et al. compared the ecological impacts of wooden buildings versus concrete and steel-framed buildings utilizing the LCA [15]. Furthermore, various other types of buildings were also analyzed using LCA [16]. In addition to LCA, modern tools have emerged with advancements in technology that promise to enhance and optimize the sustainability of the construction industry. Building information modeling (BIM) has been systematically explored in recent years for sustainability assessments [17,18]. BIM is a digital representation of an actual structure that works as an integrated database platform for diverse data acquired from various disciplines. Additionally, it has the innate ability to generate and manage the data necessary for a variety of building assessments [19,20,21].

In recent studies, there has been a significant amount of research on the integration of BIM and LCA of buildings. The limitations of the traditional LCA methods, which include time consumption, expenses, and manual-data-entry requirements, can be minimized using BIM-based LCA [11,21,22]. Moreover, mathematical analyses that take a variety of GHG emission parameters into account, can be utilized in order to accurately quantify construction and demolition’s (CDW) GHG emissions [23]. The proposed integration of mathematical equations with a BIM-based LCA approach can aid in precise identification of the GHG emissions and can offer crucial strategies for minimizing the major damage to the ecosystem caused by the disposal of CDW. Meanwhile, the embedded impacts of buildings can also be significantly reduced by optimizing transportation and end-of-life-phase approaches [24]. Geographic information systems (GISs) can be employed to use geographic data for identifying the locations of waste-treatment facilities and landfills. This data can further be used to develop optimized waste-transportation routes [25]. Therefore, there is still space to integrate and implement the above-mentioned advanced tools and develop an approach to enhance the eco efficiency and sustainability of the construction sector, specifically in the context of developing countries.

This paper proposes an innovative approach to integrate BIM, LCA, reduce GHG emissions through quantification with mathematical analyses, and using GIS to develop an estimation and evaluation approach containing all life-cycle phases, i.e., construction phase, operation phase, and end-of-life phase. The aim is to identify all the critical parameters and processes that cause the deterioration of the environment and propose appropriate strategies to ameliorate the critical materials and processes for reducing ecological degradation. The effectiveness and efficiency of the developed approach is illustrated through a real-world case study from Pakistan. Mitigation strategies including optimized design, use of sustainable materials, waste-management facilities, etc., to reduce environmental depredations have been proposed and implemented in the case study to validate the approach. A re-evaluation of all phases with improved materials and processes has been conducted to compare the impacts. Moreover, the proposed approach also paves the way for designers and construction managers to conduct a pre-evaluation of environmental damage caused by materials, processes, and waste that enables the construction of sustainable and eco-friendly structures.

2. Literature Review

LCA focuses primarily on social and environmental impacts [26], and it is frequently used in sectors like automotive design, production of equipment, and designing consumer goods [27]. LCA has been implemented in the construction industry since the 1980s [28], and in the 1990s it was further standardized with multiple workshops and research and handbook publications [29,30] often to assess the environmental effects of a specific building over the course of its lifetime, which generally contains the extraction of raw materials, industrial production, construction, execution, maintenance, restoration, substitution, and demolition [31]. Architects and designers can also gather information on which approach is optimal by comparing the environmental impact of numerous choices and making the changes in designs accordingly. For instance, structural designers can choose more sustainable materials with lower carbon footprints rather than selecting materials that produce high carbon emissions [32,33]. Each LCA database is specific to a particular area of study [34]. Despite the outcome being less reliable and significantly subjective, it is simpler to make conclusions from. Hence, LCA has been rapidly growing in the construction sector around the globe [35,36,37,38].

GHG emissions of buildings can be broken down into two main categories: embodied GHG emissions and operating GHG emissions. The primary sources of embodied GHG emissions are the extraction of raw materials, production and transportation of building materials and components, on-site construction activities, demolition, and landfill emissions [39]. Daily energy use ultimately produces the operating GHG emissions, i.e., heating, lighting, air conditioning, and water supply [40]. The evaluation of building GHG emissions in the past mostly focused on energy consumption in operation [41], and embodied GHG emissions were seldom taken into account [42].

Building information modelling (BIM) is defined as a set of frameworks, procedures, and technological advancements that create a systematic way to preserve critical project data and structure design information in digital form throughout the life cycle of a building [43]. Environmental-performance assessments and sustainability-improving activities can be carried out precisely and successfully using BIM, since it enables multidisciplinary information to be integrated inside a single model. Over the past few years, the concept of “green BIM” has gained enormous popularity in the architecture and construction industry. Green BIM is the use of BIM tools to accomplish sustainability or enhanced building performance [44]. Regardless of increasing knowledge and understanding of BIM, and its ability for environmental sustainability, the rate of adoption of BIM in green construction projects is still quite low, and its full potential has not yet been explored [45].

BIM has the capability to streamline the implementation of comprehensive LCA for various categories of buildings [40]. Using BIM, Shadram et al. developed an approach for assessing the embodied energy of materials [46]. Similarly, Han et al. developed a methodology for optimizing building systems with the goal of reducing life-cycle costs while taking into account energy consumption analyses only [47]. BIM-enabled LCA offers a great opportunity to accelerate the process of collecting life-cycle inventory data while also enhancing the simulation accuracy of the LCA research for the particular building. However, there is still a need for improvement and harmonization of the current BIM and LCA technologies [48].

GIS is used in numerous sectors, including urban planning, transportation, resource management, forestry, managing natural disasters, ecological modeling, and engineering. Developing nations are becoming increasingly concerned with inadequate waste management. Hence, the development of essential infrastructure and instruments on the basis of an effective management framework is necessary for proper waste management [49]. Various GIS-based tools such as ArcGIS network analysis have been developed that are being used in the solid-waste-management sector and provide network-based-analyses capabilities encompassing routes, travel directions, nearby facilities, and service-area analyses [50]. These tools allow users to model a variety of realistic network circumstances, such as turn limitations, speed restrictions, height constraints, and traffic patterns at various times of the day.

3. Methodology

In order to evaluate and optimize the environmental impact caused by a building or any structure during different phases of its life cycle, a comprehensive framework that incorporates various tools and methods including BIM, LCA, disposal of GHG quantification, and GIS-based route optimization has been proposed in this research. The framework is then validated in the following sections with the help of a real-time case study that primarily focuses on operationalizing the framework and reducing the GHG’ emissions contributed to by the construction sector. The integration of different tools, technologies and methods not only streamlines the evaluation process but also promotes the timely adoption of sustainable strategies and methodologies. The framework of the proposed model is illustrated in Figure 1.

Making a BIM model with functional and physical features is the basic requirement for evaluating the overall efficiency performance of a building. Therefore, the foremost step in the proposed framework is to obtain data for developing an accurate 3D BIM model of the building. Additionally, the availability and accessibility of waste-management facilities in the vicinity is also identified. The developed BIM model and all the related information serves as a base for the impact assessment, analysis, and amelioration stages of the proposed framework.

Although any modelling software capable of BIM integration can be used for modelling purposes, however, in this research, Autodesk Revit-2023 has been preferred owing to its in-built capabilities for developing an efficient estimating model and resolving interface issues. For reliable LCA findings, consistent modeling with standard naming practices in the material database is also crucial. Revit platform serves the purpose as it incorporates complete building data, including walls, floors, roofs, structures, windows, doors, etc., and also provides vast modification options using 3D objects referred to as “families.” Furthermore, the procedure has been illustrated in Figure 2.

Considering all life-cycle stages, i.e., from the creation of materials through to the end-of-life phase of a building’s lifespan, the LCA strives to thoroughly analyze the environmental impact of a building structure. During the design process, special emphasis must be attributed to reducing the embodied impacts, including structural, architectural, mechanical, and electrical components. The stages incorporated in LCA are shown in Figure 3 below.

In the 3D BIM model of a building, the building components are categorized and ranked in accordance with suggested levels. Figure 2 provides details on data integration and processing inside the BIM environment. Moreover, the environmental effects are evaluated during the impact-assessment stage of the proposed framework while taking into account all construction phases and materials, with an emphasis on carbon emissions. The four fundamental phases of the LCA technique, i.e., aim and scope, inventory, impact assessment, and interpretation, are incorporated to evaluate the environmental impacts. The purpose, audiences, and system limits are first identified for definition of the aim and scope. The second step in assessing the inventory is gathering information on all pertinent energy and mass flow inputs and outputs as well as emissions to the air, water, and land for each stage of the operation. Calculating a building system’s material and energy intake and output is a part of this step. Third, based on the inventory analysis, the impact assessment assesses possible environmental effects, and then impacts are arranged in an orderly manner in their respective phases. For this purpose, the life-cycle impact-assessment (LCIA) method included in the Eco-invent database, which is a life-cycle inventory repository based on various types of sustainability-assessment methodologies [51], has been employed. The existing life-cycle-assessment studies have been mainly focused on operational-phase impacts, neglecting the significant impact of embodied GHG emissions, particularly CO₂ emissions. However, in this study, the carbon emissions have been assessed in terms of tonsCO₂, considering all materials and phases in the overall lifespan of the building. Lastly, the interpretation phase includes scenarios and input-data variability to improve construction performance, and it provides clear findings that are in line with the study objectives.

Moreover, in order to incorporate the environmental impact during the end-of-life phase of a building, CO₂ emitted during the transportation of construction and demolition waste (CDW) to appropriate waste facilities was considered in the embodied emissions calculations. Construction materials are usually classified as recyclable and non-recyclable, with recyclable components undergoing recycling and non-recyclable components going to landfills. Proper handling of waste material is ensured by providing various types of waste-management facilities including classification centers, second material store, recycling plants, and landfill sites. Hence, location and accessibility of various waste-management facilities impact the CDW transportation and handling of emissions. In order to measure the disposal emissions of CDW, an efficient approach is required as the majority of current methods utilized to extract CDW information have proven to be time consuming, inaccurate, and difficult [52]. Hence, a method of quantifying the emissions with mathematical formulae based on a number of factors has been used. Factors used for the embodied emissions calculations were sourced from Bok et al. [53] and Turner et al. [54]. The formulas used to calculate the source’s separated CDW’s CO₂ emissions, including transportation emissions and CDW handling emissions at each disposal facility, are provided below.

$${\mathrm{E}}_{{\mathrm{C}\mathrm{O}}_2}={\mathrm{E}}_{\mathrm{T}\mathrm{r}}+{\mathrm{E}}_{\mathrm{H}}$$

(1)

Transportation and handling of emissions are added to determine the overall CO₂ emissions, as seen in the formulae above. Here, E_Tr is the CDW transportation emissions and E_H is the CDW handling emissions. Formula for transportation emissions’ calculation that helps estimate the environmental impact of waste transportation based on distances and transportation modes for various waste types is provided below [55].

$$\begin{gathered} {\mathrm{E}}_{\mathrm{t}\mathrm{r}}={\sum }_{\mathrm{k}=1}^{\mathrm{K}}{\sum }_{\mathrm{j}=1}^{\mathrm{J}}{\mathrm{Q}}_{\mathrm{c}\mathrm{r},\mathrm{k}}\times {\mathrm{e}}_{\mathrm{d},\mathrm{j}}\times {\mathrm{D}}_{\mathrm{c}\mathrm{r}}+{\sum }_{\mathrm{k}=1}^{\mathrm{K}}{\sum }_{\mathrm{j}=1}^{\mathrm{J}}{\mathrm{Q}}_{\mathrm{s}\mathrm{l},\mathrm{k}}\times {\mathrm{e}}_{\mathrm{d},\mathrm{j}}\times {\mathrm{D}}_{\mathrm{s}\mathrm{l}}{\sum }_{\mathrm{k}=1}^{\mathrm{K}}{\sum }_{\mathrm{j}=1}^{\mathrm{J}}{\mathrm{Q}}_{\mathrm{b}\mathrm{s},\mathrm{k}} \\ \times {\mathrm{e}}_{\mathrm{d},\mathrm{j}}\times {\mathrm{D}}_{\mathrm{b}\mathrm{s}}+{\sum }_{\mathrm{k}=1}^{\mathrm{K}}{\sum }_{\mathrm{j}=1}^{\mathrm{J}}{\mathrm{Q}}_{\mathrm{s}\mathrm{c},\mathrm{k}}\times {\mathrm{e}}_{\mathrm{d},\mathrm{j}}\times {\mathrm{D}}_{\mathrm{s}\mathrm{c}} \end{gathered}$$

(2)

where Q_bs,k: quantity of mixed-waste k from building site to collection center (tons), Q_sc,k: quantity of source-separated waste k from collection center to SMS (tons), Q_cr,k: quantity of source-separated waste k from SMS to recycling plant (tons), Q_sl,k: quantity of source-separated waste k from collection center to landfill (tons), e_d,j: CO₂ emissions for transportation mode j per unit (tons/tons-km), D_bs: distance from building site to collection center (km), D_sc: distance from collection center to SMS (km), D_cr: distance from SMS to recycling plant (km), D_sl: distance from collection center to landfill site (km).

Similarly, the formula used to calculate the handling emissions is as below [56].

$${\mathrm{E}}_{\mathrm{h}}={\sum }_{\mathrm{k}=1}^{\mathrm{k}}{\mathrm{Q}}_{\mathrm{s}\mathrm{l},\mathrm{k}}\times {\mathrm{P}}_{\mathrm{l},\mathrm{k}}$$

(3)

where Q_sl,k is source–waste quantity transported to landfill, and P_l,k is landfill-emission factor. This focuses on physical emissions from disposal rather than chemical biogenic CO₂.

The impact-assessment stage in the proposed framework is followed by the analysis and amelioration stages. In the analysis stage, the phases and factors with the highest environmental impact are identified. These factors are then marginalized by incorporating various alternatives and emission-reduction strategies in the amelioration stage. Thereafter, a re-evaluation of environmental impact is conducted considering all phases of a building’s lifespan again. Finally, GIS technology is utilized to create an optimized route for efficient CDW transportation to primary waste facilities, i.e., the classification center, second material store, recycling plant, and landfill site. The spatial geodatabase for this study has been developed using the commercial GIS platform ArcGIS, enabling advanced modeling and analysis options for waste collection. Furthermore, an ArcGIS network analyst modelling package has been used to perform vehicle routing, as shown in Figure 4.

4. Case Study: BIM-Based Life-Cycle Analysis of Faculty Apartments at NUST, Islamabad

In order to demonstrate the practicality and operability of the proposed framework, a detailed case study has been formulated and presented in this section. The faculty apartment building, with four floors with two apartments on each floor, and a total area of 540 m², located in National University of Sciences and Technology (NUST), Islamabad, has been taken as a case-study building.

4.1. BIM Model of Building

Using the Autodesk Revit application, a detailed 3D model of the building was created as a case study. The elements of the building model were grouped into families that enable systematic and precise estimations. Furthermore, each element of the building was specified after conducting an in-depth analysis of available 2D drawing plans and applicable codes and specifications. All the physical and functional characteristics of the building were included in the database according to the specifications of the building. The nomenclature was set in such a way that life-cycle assessment could easily be conducted. The 3D BIM model is illustrated in Figure 5.

4.2. Impact Assessment of Building

After the development of a functional 3D BIM model of a building, the next step was to perform life-cycle assessment of the building in order to determine the environmental impact during different phases of a building’s lifespan. The data was extracted directly from the BIM and then normalized for further usage in the cloud version of One Click LCA. The created database included all the elements of the building along with their critical information. The automation in database formation significantly reduced the effort and time by quantifying the materials digitally.

Moreover, the database of all materials, like cement, concrete, bricks, wood, steel, glass, and ceramics, was utilized to conduct material mapping from the inventory. For this purpose, Ecoinvent and Gabi databases were effectively utilized. Each material in the database was employed according to the specifications of the case-study building. The prevalent construction practices in Pakistan include vast utilization of cement, concrete, steel, bricks, etc., for grey structures while wood, glass, paints, ceramics, etc., are widely used for interior- and exterior-preparation purposes. Overall, the traditional materials and building specifications are not energy efficient during materialization as well as operational phases [57]. In addition to the material database, other essential data such as water usage, electrical appliances, etc., were inserted in the model to evaluate the impact of the overall operational phase of the building. After the incorporation of all relevant data in the model, the results were obtained in detail for each of the materials during different phases of the lifecycle and were further classified into their respective categories. Life-cycle assessment provided results in terms of mass classifications of each component of the building along with their family-based classification.

Table 1. Classification of building components according to mass.

Item	Value	Unit	Percentage %
Standard slabs	2,400,000	kg	77.21%
Beam	160,000	kg	5.14%
Column	71,000	kg	2.3%
Stairs	14,000	kg	0.47%
Exterior walls	360,000	kg	11.74%
Exterior windows	52,000	kg	1.69%
Exterior doors and grilles	45,000	kg	1.44%

shows that the standard slabs, beams, exterior walls, and columns contribute highest in terms of their mass in the building. Emissions of various resource types have been illustrated in

Table 2. Emissions of various resource types.

Item	Value	Unit	Percentage %
Electricity	1,400,000	kg CO2e	56.56%
Water	630,000	kg CO2e	24.77%
Ready-mix concrete for structures (beams, columns)	96,000	kg CO2e	3.78%
Paints, coatings, and lacquers	85,000	kg CO2e	3.34%
Regular glass panes	79,000	kg CO2e	3.12%
Concrete masonry units (CMU)	62,000	kg CO2e	2.46%
Refrigerant fluids	61,000	kg CO2e	2.4%
Aluminium-framed glass doors	50,000	kg CO2e	1.99%
Aluminium-frame windows	30,000	kg CO2e	1.18%
Other resource types	9900	kg CO2e	0.39%
Total	2,502,900

, which reveals that electricity and water usage, being part of the operational and materialization stages, contribute the most towards CO₂ emissions compared to other materials used in the building.

After assigning the materials along with the necessary datasets, the impact of the apartment building was assessed over the span of 50 years. According to the LCA results presented in

Table 3. Emissions during materialization and operational stages.

Life-Cycle Stage	Result Category	Carbon Emission (tonCO2e)
Materialization stage	Materials usage	402
Operational stage	Energy usage	2101
Total carbon emissions		2503

, the case-study building generates 2503 tonCO₂ during the construction and operational stages of the building lifecycle. These results were broken down into the materials used during the construction or materialization stages and the energy usage throughout the building’s operational stage. It is evident that the use of less-eco-friendly materials and appliances have a major share in the overall emissions of the building.

The location of waste-management facilities and the transportation route is critical in determining the disposal emissions. The case-study building is located in Islamabad which currently does not have all the facilities for waste management, i.e., a classification center, second material store, and recycling plant. Therefore, the non-availability of these facilities leads to the dumping of all construction–demolition waste into the landfill site. Hence, for this case study, the Rawalpindi waste-management-company (RWMC) landfill was taken into account. The distance between the construction site and the landfill is around 36.3 km as depicted below in Figure 6.

The disposal of GHG emissions also has a crucial impact on the environmental degradation. For the quantification of disposal transportation and handling emissions, mathematical formulae based on a number of factors was used, as mentioned in Section 3. Eleven types of CDWs were considered for assessing the impacts. Firstly, relevant information from the developed 3D BIM model was extracted and the respective quantities of different types of CDWs were estimated after applying the respective change factors, as shown in

Table 4. Quantities of waste materials.

S.No	Material Resource	Data (1)	Units	Density (ton/m3) (2)	Change Factor (3)	Calculated Quantities (ton) (1) × (2) × (3)
1	Concrete	864	m3	2.42	1.1	2299.968
2	Brick	986	m3	1.9	1.2	2248.080
3	Cement	404.25	m3	2	1.2	970.200
4	Lime	1.25	m3	3.3	1.2	4.950
5	Steel	1138.23	T	-	1.1	1252.053
6	Ceramic tile	328.2	m3	2.7	1.1	974.754
7	Paint	291.18	kg	-	1.1	0.320
8	Plastic	12.5	m3	1.6	1.1	22
9	Wood	15.43	T	-	1.15	17.744
10	Paper	244	kg	-	1.15	0.280
11	Plaster	64.1	m3	0.9	1.2	69.228

. It is evident from Table 4 that concrete, bricks, steel, cement, and ceramic tiles contribute most of the waste material after demolition.

After the quantification of different categories of CDW, the next step was to determine the environmental impact during the end-of-life phase of the case-study building.

Table 5. CO₂ disposal emissions from transportation.

S.No	Material Resource	Calculated Quantities (ton) (1)	Emission Factor (ton/ton-km) (2)	Distance (km) (3)	Transportation Emission (tonCO2e) (1) × (2) × (3)
1	Concrete	2299.968	0.000168	36.3	14.026
2	Brick	2248.08	0.000168	36.3	13.709
3	Cement	970.2	0.000168	36.3	5.916
4	Lime	4.95	0.000168	36.3	0.031
5	Steel	1252.053	0.000168	36.3	7.635
6	Ceramic tile	974.754	0.000168	36.3	5.944
7	Paint	0.3201	0.000168	36.3	0.0019
8	Plastic	22	0.000168	36.3	0.1341
9	Wood	17.7445	0.000168	36.3	0.1082
10	Paper	0.2806	0.000168	36.3	0.0017
11	Plaster	69.228	0.000168	36.3	0.4222
				Total	47.9308

shows the results of disposal emissions, which are produced due to the transportation of waste quantities from the building’s location to a landfill site situated 36.3 km away. Based on the observations in the study area, it was determined that diesel freight trucks are generally used for the transportation of material. Hence, the emission factor for transportation-emissions calculations in Table 5 were selected accordingly. It is evident from the table that major contributors of transportation emissions are the principal construction materials including concrete, bricks, cement, steel, and tiles, thereby emphasizing the need for optimal design and use of sustainable materials in the construction industry. Similarly,

Table 6. CO₂ landfill emission from handling waste.

S.No	Material Resource	Calculated Quantities (ton) (1)	Handling Emission Factors (ton/ton) (2)	Landfill Emissions (tonCO2e) (1) × (2)
1	Concrete	2299.968	0.13	298.996
2	Brick	2248.08	0.03	67.442
3	Cement	970.2	0.02	19.404
4	Lime	4.95	0.02	0.099
5	Steel	1252.053	0.03	37.562
6	Ceramic tile	974.754	0.018	17.545
7	Paint	0.320	2.25	0.720
8	Plastic	22	0.02	0.44
9	Wood	17.744	0.05	0.887
10	Paper	0.280	2.25	0.63135
11	Plaster	69.228	0.02	1.384
			Total	445.113

displays the quantity of emissions at landfill resulting from the handling of waste.

The overall end-of-life-phase emissions which are the sum of transportation emissions in Table 5, and handling emissions at landfill site in Table 6, are equal to 493.043 tonCO₂. The overall results of the LCA and embodied emission quantification are summarized in

Table 7. Total emissions for the case-study building.

Life-Cycle Stage	Result Category	Carbon Emission (tonCO2e)
Materialization stage	Materials usage	402
Operational stage	Energy usage	2101
End-of-life stage	CDW transportation and disposal	493
Total carbon emissions		2996

, indicating total emissions of 2996 tonCO₂ throughout the lifespan of the case-study building.

4.3. Analyses of Results

As evident from Table 7 above, the results of the life-cycle assessment show the impact of each element on the environment and elaborate that the operational phase was the most critical in the degradation of ecology by contributing about 2101 tonsCO₂. The results implicate that the design as well as the materials utilized in the case-study building were not optimally sustainable in terms of environmental impacts. The estimated carbon-emission values for different stages of a building provide an opportunity to engineers and architects to mitigate the environmental impacts by improving the design and material efficiency. The results also indicate that a number of materials including steel, concrete, cement, bricks, and ceramic tiles, were the most critical materials influencing CO₂ emissions and were barriers to sustainable buildings. Inefficient design and utilization of inefficient materials also led to high energy consumption during operational stage and were paramount factors in intensifying emissions. The primary energy-use functions during building operation included air conditioning, space heating, water heating, and other household electrical appliances. In addition to this, the disposal emission levels produced were also high due to the non-availability of major waste-management facilities in the surrounding region. The three phases, i.e., construction, operation, and end-of-life phase, collectively had a high carbon footprint that not only damages the environment but also abates the sustainability of the construction sector. The total amount of CO₂ emissions from the construction and operation phase was 2503 tonsCO₂, and the total amount of CO₂ emissions from the end-of-life phase, including primarily transportation and disposal of CDW, was 493.043 tonsCO₂.

In order to lessen the environmental effect of building structures, optimization should be completed in the direction of a carefully selected material class, which lowers the number of structural elements. Along with the examination of their suppliers, additional focus should be placed on the kinds of materials which are linked to transportation routes and unit indicators of the environmental effect of materials [58]. The country’s engineering and construction industry is experiencing a smart transition, driven by the rising use of green and sustainable materials to promote low-carbon building design. Therefore, employment of sustainable construction practices and materials with a lower carbon footprint should be prioritized [57,59]. Moreover, the disposal-process emissions are also high owing to the dearth of waste facilities in the study area. Since there has already been a large rise in CDW due to growing urbanization and industrialization, the availability of waste-management facilities, including a classification center, second material store, and recycling plant, is the current necessity. Comprehensive waste facilities in Islamabad will particularly be beneficial for the construction industry by directly reducing the burden on landfills and also enabling the recycling of CDW. For the establishment of these facility centers, the most feasible sites with optimized access would be required to limit the transportation and handling of emissions. In order to resolve this issue, the optimized location and route of waste facilities should be planned using an advanced GIS platform containing all the existing essential information of the region. Implementation of the above mitigation strategies would lessen the overall CO₂ emissions and stimulate the eco efficiency and sustainability of the construction sector.

4.4. Re-Evaluation of the Improved Model including Route Optimization

As mentioned above, a number of mitigation strategies including optimization of building design, utilization of eco-friendly materials and optimal disposal of CDW, can be employed to cut-down the carbon footprint of the case-study building in particular and the overall construction sector in general.

For the case study, the optimal path for effectively disposing of the construction and demolition waste was determined using the network analyst tool provided in ArcGIS, while taking into account all necessary factors. These factors included the locations of sites, the road system, slope, water bodies, built area, and boundaries of administrative areas. In order to achieve reduced disposal route CO₂ emissions, the two key criteria used to evaluate the route-optimization model were economic costs along with environmental safety and sustainability. The financial and ecological impacts associated with the design of the waste facilities in the Islamabad region were considered as the foundation parameters for the optimal-route model. Fuel consumption and placement of centers at a safe distance from residential areas made the model a more efficient, sustainable, and cost-effective system. The most important requirement for lowering fuel usage was for the shortest distance with the least degradation of the environment. Moreover, the built-area analysis of Islamabad and Rawalpindi region, as illustrated in Figure 7a, helped to identify the most suitable locations for proposed waste-management facilities. Based on density data, Figure 7a shows the most suitable sites in green color and the least suitable locations in red color, whereas Figure 7b highlights the optimized route from case study building to various waste-management facility centers proposed in Islamabad Capital Territory (ICT) region. The distances between the facility centers are presented in

Table 8. Distance between different waste-management-facility centers.

Distances (km)	CS	CC	SMS	RP	LS
CS	-	22.62	-	-	-
CC	22.62	-	1.20	-	-
SMS	-	1.20	-	1.60	-
RP	-	-	1.60	-	-
LS	-	2.00	-	-	-

.

Applying the mitigation strategies discussed above and implementing the distance between the facility centers presented in Table 8, a re-evaluation of the whole framework was conducted. The impact of the case-study building was re-assessed over the span of 50 years after assigning the materials and necessary datasets with mitigation strategies. The design was optimized by employing sustainable design practices such as optimization of building envelop and insulation, having energy-efficient appliances, etc. [57], and replacing materials with a high carbon footprint with sustainable materials to re-assess the impact of building for a 50-year life span. The new sustainable design was compared with the current design to quantify the percentage of reduction in CO₂ during different life phases, i.e., construction, operational, and end of life, of the case-study building. By conducting the re-evaluation, the effectiveness and efficiency of all the proposed mitigation strategies were evaluated. Emissions of various resource types after re-evaluation by implementing the mitigation strategies are mentioned in

Table 9. Emissions from various resource types after re-evaluation.

Item	Value	Unit	Percentage %
Electricity	1,100,000	kg CO2e	53.38%
Water	630,000	kg CO2e	31.19%
Ready-mix concrete for structures (beams, columns)	74,000	kg CO2e	3.68%
Paints, coatings, and lacquers	51,000	kg CO2e	2.54%
Ready-mix concrete for external walls and floors	46,000	kg CO2e	2.27%
Concrete masonry units (CMU)	44,000	kg CO2e	2.2%
Aluminum frame windows	41,000	kg CO2e	2.06%
Refrigerant fluids	34,000	kg CO2e	1.7%
Ready-mix concrete for foundations and internal walls	28,000	kg CO2e	1.4%
Total	2,048,000

below.

After design optimization and replacement of high-carbon-footprint material with the sustainable materials, results of the LCA were re-evaluated, as shown in

Table 10. Emission from materialization and operational stage after re-evaluation in tonCO₂e.

Life-Cycle Stage	Result Category	Carbon Emission (tonCO2e)
Materialization stage	Materials usage	284
Operational stage	Energy usage	1764
Total carbon emissions		2048

. The results show that the apartment building produces construction and operational carbon emissions of 2048 tonsCO₂e, indicating a decrease in the emissions in both the materialization and operational stages of the building. Furthermore, CO₂ emissions occurred due to the transportation of waste from construction sites to various waste facilities, and eventually to the landfill site, are shown in

Table 11. CO₂ transportation emissions after re-evaluation.

Qbs,k	ed,jCO2	Dbs	Qsc;k	Dsc	Qcr;k	Dcr	Qsl;k	Dsl	Transportation Emission
2299.968	0.000168	22.62	459.994	1.2	459.994	1.6	1839.974	2	9.575
2248.08	0.000168	22.62	449.616	1.2	449.616	1.6	1798.464	2	9.359
970.2	0.000168	22.62	194.04	1.2	194.04	1.6	776.16	2	4.039
4.95	0.000168	22.62	0.99	1.2	0.99	1.6	3.96	2	0.021
1252.053	0.000168	22.62	250.411	1.2	250.411	1.6	1001.642	2	5.212
974.754	0.000168	22.62	194.951	1.2	194.951	1.6	779.804	2	4.058
0.3201	0.000168	22.62	0.0641	1.2	0.0641	1.6	0.2561	2	0.002
22	0.000168	22.62	4.4	1.2	4.4	1.6	17.6	2	0.092
17.7445	0.000168	22.62	3.549	1.2	3.549	1.6	14.1956	2	0.074
0.2806	0.000168	22.62	0.0562	1.2	0.0562	1.6	0.225	2	0.001
69.228	0.000168	22.62	13.846	1.2	13.846	1.6	55.383	2	0.288
								Total	32.721

. Finally, the results of handling emissions after re-evaluation are shown in

Table 12. CO₂ Handling emissions after re-evaluation.

Material Resource	Calculated Quantities (ton) (1)	Handling Emission Factors (ton/ton) (2)	Landfill Emissions (ton) (1) × (2)
Concrete	1839.974	0.13	239.197
Brick	1798.464	0.03	53.954
Cement	776.16	0.02	15.523
Lime	3.96	0.02	0.0792
Steel	1001.642	0.03	30.049
Ceramic tile	779.803	0.018	14.036
Paint	0.2561	2.25	0.576
Plastic	17.6	0.02	0.3521
Wood	14.196	0.05	0.7097
Paper	0.225	2.25	0.5051
Plaster	55.383	0.02	1.1075
		Total	356.089

.

According to the re-evaluation results presented above, the materialization- and operational-stage carbon emissions were 284 and 1764 tonCO_2, respectively, whereas the total amount of CDW transportation and handling emissions were 388.81 tonCO₂. The overall re-evaluation results are summarized in

Table 13. Total emissions after re-evaluation for the case-study building.

Life-Cycle Stage	Result Category	Carbon Emission (tonCO2e)
Materialization stage	Materials usage	284
Operational stage	Energy usage	1764
End-of-life stage	CDW transportation and disposal	389
Total carbon emissions		2437

, showing the total emissions of 2437 tonCO₂ in comparison to the current situation’s emissions of 2996 tonCO₂. It is evident that by optimizing the design and utilizing eco-friendly materials, a reduction of emissions by 29.35% and 16.04% can be achieved in the materialization and operational stages, respectively. Moreover, end-of-life-phase emissions can be reduced by up to 21.14% by ensuring availability and optimal accessibility of waste facilities within the boundaries of Islamabad Capital Territory.

5. Conclusions

This study developed an integration of the BIM, LCA, GIS, and mathematical calculation of the embodied disposal-process GHG emissions to optimize the construction design, material-selection, operations, maintenance, and waste-management processes. The proposed framework provided significant advantages, including the development of a 3D BIM model that enables direct generation of material data and reduces the laborious task of manual data processing and the associated possibility for inaccuracies. Through BIM, the features and design aspects of the building were represented digitally, thereby providing more precise and comprehensive information than the conventional estimating techniques. A detailed evaluation of the lifecycle performance of buildings was achieved by incorporating the entire lifecycle assessment into the proposed technique. In-depth analyses and the identification of unsustainable practices and materials were achieved using the automated generation of more comprehensive and comparable LCA data. To ensure the development of targeted emission-reduction strategies, it was also crucial to estimate CDW data precisely and to quantify CDW disposal-process GHG emissions, which were integrated into the framework using mathematical formulae calculations. Furthermore, optimized routes along the facility centers for minimizing CDW’s handling and transportation emissions, enhancing the recycling of waste, and lowering of the burden on the landfills were designed using GIS-based route-optimization tools. The whole framework was critically validated with the help of a case study in order to demonstrate the practicality of the framework.

A four-storey faculty apartment building located in Islamabad, Pakistan, was considered as a case-study building. After the development of a functional 3D BIM model of the building, life-cycle assessment of the building was conducted in order to determine the environmental impact during different phases of the building’s lifespan. The results of the life-cycle assessment showed the impact of each element on the environment and elaborated that the operational phase was the most critical in the degradation of ecology by contributing about 2101 tonsCO₂. The results indicated that the design, as well as the materials utilized in the case-study building, were not optimally sustainable in terms of environmental impacts. Moreover, the results specified that a number of materials, including steel, concrete, cement, bricks, and ceramic tiles, were the most critical materials influencing CO₂ emissions and were barriers to sustainable buildings. Inefficient design and utilization of inefficient materials also led to high energy consumption during the operational stage, and they were paramount factors in intensifying emissions. In addition to this, the disposal-process emissions produced were also high due to the unavailability of major waste-management facilities in the Islamabad region. The total amount of CO₂ emissions from the construction and operation phase was 2503 tonsCO₂, and the total amount of CO₂ emissions from the end-of-life phase, including primarily transportation and disposal of CDW was 493.043 tonsCO₂.

A number of mitigation strategies, including optimization of building design, utilization of eco-friendly materials and optimal disposal of CDW, were evaluated to cut-down the carbon footprint of the case-study building in particular and the overall construction sector in general. The impacts of the case-study apartments were re-assessed over the span of 50 years after assigning the materials and necessary datasets with mitigation strategies. The design was optimized by employing sustainable design practices and replacing materials with a high carbon footprint with sustainable materials. The new sustainable design was compared with the current design to quantify the percentage reduction in CO₂ during different life phases, i.e., construction, operational, and end of life of the case-study building. The results indicated that by optimizing the design and utilizing eco-friendly materials, a 29.35% and 16.04% reduction can be achieved in materialization and operational GHG emissions, respectively. In order to achieve reduced disposal-process CO₂ emissions, the two key criteria used to evaluate the GIS-based route-optimization model were economic costs along with environmental safety and sustainability. The financial and ecological impacts associated with the design of the waste facilities in the Islamabad region were considered as the foundation parameters for the optimal-route model. The optimization results indicated a reduction of 21.14% in the end-of-life-stage emissions. Hence, it is apparent that the proposed framework enhances eco efficiency and sustainability in the construction sector by reducing the GHG emissions of buildings. Furthermore, pre-evaluating the environmental degradation caused by construction projects at the design stage might offer an opportunity to comprehend and reduce prospective environmental impacts.

6. Recommendations

The proposed framework, integrating BIM, LCA, GIS, and the mathematical calculation of disposal-process GHG emissions, provides multiple directions for future research. The framework can be further extended by incorporating other sustainable design methodologies, databases, and software for more improvement in sustainability and environmental safety. Secondly, the proposed framework is more focused on the calculation and reduction of CO₂ emissions; however, in future research, other pollutants can also be evaluated for further enhancement of eco efficiency. Thirdly, this study presented CDW disposal strategies that were environmentally friendly. However, additional handling considerations, such as financial advantages, might also be considered. Thus, future research might focus on a CDW cost–benefit analysis including an evaluation of the trade-offs between the environment and the economy.