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

Zubair, Muhammad Umer; Ali, Mubashir; Khan, Muhammad Arsalan; Khan, Adil; Hassan, Muhammad Usman; Tanoli, Waqas Arshad

doi:10.3390/buildings14020360

Cited by 7 publications

(3 citation statements)

References 54 publications

(57 reference statements)

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“…The approach for predicting the CECI based on physical models involves the establishment of a physical model of the building system [20]. This entails an analysis of the roles and interactions of various factors within the building system to predict the CECI.…”

Section: Literature Reviewmentioning

confidence: 99%

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

Hou,

Liu

2024

Sustainability

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The extensive carbon emissions produced throughout the life cycle of buildings have significant impacts on environmental sustainability. Addressing the Carbon Emissions from China’s Construction Industry (CECI), this study uses panel data from seven coastal areas (2005–2020) and the Bayesian Optimization Extreme Gradient Boosting (BO-XGBoost) model to accurately predict carbon emissions. Initially, the carbon emission coefficient method is utilized to calculate the CECI. Subsequently, adopting the concept of a fixed-effects model to transform provincial differences into influencing factors, we employ a method combining Spearman rank correlation coefficients to filter out these influencing factors. Finally, the performance of the prediction model is validated using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R2) and Mean Absolute Percentage Error (MAPE). The results indicate that the total CECI for the seven provinces and cities increased from 3.1 billion tons in 2005 to 17.2 billion tons in 2020, with Shandong Province having the highest CECI and Hainan Province having the lowest. The total population, Gross Domestic Product (GDP) and floor space of the buildings completed passed the significance test, among a total of eight factors. These factors can be considered explanatory variables for the CECI prediction model. The BO-XGBoost algorithm demonstrates outstanding predictive performance, achieving an R2 of 0.91. The proposed model enables potential decisions to quantitatively target the prominent factors contributing to the CECI. Its application can guide policymakers and decision makers toward implementing effective strategies for reducing carbon emissions, thereby fostering sustainable development in the construction industry.

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Section: Literature Reviewmentioning

confidence: 99%

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

Hou,

Liu

2024

Sustainability

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“…Benefiting from the rapid development of information and digital technology in the construction industry, the data and information of the whole lifecycle of engineering projects can not only be effectively organized but also realize the visualized presentation of the construction digital models [14][15][16][17]. More fortunately, the digital information completely reflects all the real situation of the project and can be continuously updated as the construction progresses.…”

Section: Introductionmentioning

confidence: 99%

Construction Safety Risk Assessment of High-Pile Wharf: A Case Study in China

Wang,

Yuan

2024

Buildings

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The complexity of the wharf components and the harshness of the offshore construction environment increase the safety risk of hazards, which has highlighted the importance and urgency of safety risk management in high-pile wharf constructions. This paper established a visualized digital construction safety risk model for high-pile wharf based on a so-called FAHP method (the combination of fuzzy comprehensive evaluation (FCE) and analytic hierarchy process (AHP) methods). The construction safety risk indicators were constructed as the target layer, the principle layer and the scheme layer, and then the corresponding safety risk assessment algorithm was established. The physical, functional and safety risk assessment parameters of the component in the BIM model were employed to the safety risk assessment algorithm, and the risk assessment level of each sub-process was subsequently classified. The case study indicated that the high-pile wharf construction project included five elements in principle layer and 15 risk indicators in the scheme layer. Moreover, it was demonstrated that the sub-processes with the highest construction risk level were steel pipe pile sinking in wharf construction and steel pipe pile, steel sheath-immersed pile sinking and embedded rock pile construction in approaches to bridge construction with a risk level of III. In this way, the quantitative visualization of the construction safety risk was effectively realized, which facilitates the safety risk management of construction sites and timely warning and response to unexpected safety accidents.

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“…In terms of waste management, the Madaster platform registers buildings and establishes material passports for them, facilitating the exchange and reuse of materials through data management [17]. Additionally, assessments of building material stocks and waste disposal methods in larger areas using BIM (building information modeling) and GIS (geographic information system) technologies are beneficial for preparing for future waste and carbon emissions [18,19]. Zhu H. et al developed a more precise method for building a framework for reusing building materials [20].…”

Section: Introductionmentioning

confidence: 99%

Carbon Emissions Reduction of a Circular Architectural Practice: A Study on a Reversible Design Pavilion Using Recycled Materials

Zhu,

Liou,

Chen

et al. 2024

Sustainability

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The construction industry, as a major consumer of resources and energy, accounts for about 40% of global carbon emissions. The concept of a circular economy (CE) is one effective means to address this issue. The entire lifecycle of a building includes: material production, construction, operation, and demolition. The production of building materials emits the largest proportion of carbon dioxide, followed by the operational phase, while construction (including demolition) has the smallest proportion. However, it is crucial to note the waste phase after demolition, where building materials are typically disposed of through incineration or landfill, leading to significant carbon emissions and environmental degradation. Therefore, carbon emissions generated during both the production and waste phases of the construction industry cannot be overlooked. This article employs a combined approach of practice and research, using the Circular Pavilion as a case study. From the design stage, reducing resource usage and carbon emissions are considered crucial factors. Reversible design, modularity, and the use of recycled materials are employed to reduce the emissions of “embodied carbon” and enhance material reuse. To validate the effectiveness of recycled materials in reducing greenhouse gas (GHG) emissions, this study calculates the material usage and carbon emissions during the production, transportation, and waste phases of the Circular Pavilion, Concrete Pavilion, and Steel Pavilion. The Circular Pavilion accounts for 34% and 3.5% of the total carbon emissions of the Concrete Pavilion and Steel Pavilion, respectively. In conclusion, the practical implementation of reversible design and recycled materials based on the concept of a circular economy is key to transitioning the construction industry from environmentally harmful impacts to eco-friendly practices. This establishes an effective method for resource reuse and carbon dioxide reduction in the construction sector, allowing waste resources to re-enter production and manufacturing processes, thereby reducing natural extraction, waste disposal, and energy consumption. Future applications of this method in the construction field involve establishing multidimensional composite design models and conducting feasibility assessments with upstream and downstream supply chains to support the realization of circular cities.

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

Cited by 7 publications

References 54 publications

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

Construction Safety Risk Assessment of High-Pile Wharf: A Case Study in China

Carbon Emissions Reduction of a Circular Architectural Practice: A Study on a Reversible Design Pavilion Using Recycled Materials

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