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Methodology for Evaluating the Uncertainty of Embodied Carbon Assessments in Construction Projects across Project Phases.

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Titel: Methodology for Evaluating the Uncertainty of Embodied Carbon Assessments in Construction Projects across Project Phases.
Autoren: Pozzer, Alberto E.1 (AUTHOR) emmanuelpozzer@utexas.edu, Rausch, Christopher2 (AUTHOR), Leite, Fernanda3 (AUTHOR)
Quelle: Journal of Construction Engineering & Management. Oct2025, Vol. 151 Issue 10, p1-15. 15p.
Schlagwörter: *UNCERTAINTY (Information theory), *ENVIRONMENTAL impact analysis, *PROJECT management, *MONTE Carlo method, CONSTRUCTION projects, DATA quality, GREENHOUSE gases
Abstract: There is increasing attention toward reducing greenhouse gas emissions on construction projects in light of their significant contribution to global warming. One of the scrutinized aspects is the measurement and reduction of embodied carbon (EC), including the materials and activities involved in the project execution. However, the assessment of this environmental impact generally involves uncertainty due to the lack of precision in emission factors and the inherent unpredictability in prospective project parameters. Since data quality and accuracy for embodied carbon assessments vary significantly across project phases, it is crucial to evaluate how the uncertainty in the results changes when the assessments are performed at different times of the project development. This study presents a new framework using Monte Carlo (MC) simulation to systematically evaluate and compare uncertainty in carbon assessments across project phases. Three case studies are used to validate this framework and statistically model how the uncertainty varies from one phase to the other. The individual assessment of the case studies reveals that the change in uncertainty for different project phases can range up to 20%–31% based on the differences in the coefficient of variation (COV). Similarly, the mean value reported can vary from 6% to 14%. The uncertainty tends to be reduced for later project phases showing confidence intervals for the coefficient of variation of 0.33–0.39, 0.12–0.28, and 0.04–0.20 for concept, engineering, and construction stages, respectively. However, the specific values depend also on the particularities of the project and the data that each project has available. This work demonstrates that an uncertainty analysis should be included with all embodied carbon assessments to increase the transparency of the emissions reported and the comparison of alternatives. By increasing the reliability of assessments, this study supports the reduction of the net contribution of the construction industry to global carbon dioxide emissions. Practical Applications: There is an increasing interest in the construction industry in quantifying and reducing its carbon emissions. However, the methods to estimate the carbon emitted during the construction of projects are generally imprecise and contain uncertainty. Moreover, the information available to perform the analysis varies depending on the project phase when the assessment is performed. This study proposes a methodology to quantify uncertainty in carbon assessments for the construction of projects and to analyze its variation based on the information available. The approach was tested in the evaluation of three case studies. The results show that mean values in carbon assessments performed in early project phases can differ from 6% to 14% from those in later phases. In addition, the expected coefficient of variation (COV) for the concept, engineering, and construction phases ranges between 0.33–0.39, 0.12–0.28, and 0.04–0.20, respectively. These values can be employed to contrast with those obtained for the project. These references combined with the sensitivity analysis can contribute to improving decision making. For example, project managers may anticipate when additional information is required for a particular variable, and consultants may identify if the assessments are reliable enough to be communicated. Furthermore, this framework can be replicated by industry practitioners to obtain informed decisions when comparing different projects or project alternatives. [ABSTRACT FROM AUTHOR]
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Beschreibung
Abstract:There is increasing attention toward reducing greenhouse gas emissions on construction projects in light of their significant contribution to global warming. One of the scrutinized aspects is the measurement and reduction of embodied carbon (EC), including the materials and activities involved in the project execution. However, the assessment of this environmental impact generally involves uncertainty due to the lack of precision in emission factors and the inherent unpredictability in prospective project parameters. Since data quality and accuracy for embodied carbon assessments vary significantly across project phases, it is crucial to evaluate how the uncertainty in the results changes when the assessments are performed at different times of the project development. This study presents a new framework using Monte Carlo (MC) simulation to systematically evaluate and compare uncertainty in carbon assessments across project phases. Three case studies are used to validate this framework and statistically model how the uncertainty varies from one phase to the other. The individual assessment of the case studies reveals that the change in uncertainty for different project phases can range up to 20%–31% based on the differences in the coefficient of variation (COV). Similarly, the mean value reported can vary from 6% to 14%. The uncertainty tends to be reduced for later project phases showing confidence intervals for the coefficient of variation of 0.33–0.39, 0.12–0.28, and 0.04–0.20 for concept, engineering, and construction stages, respectively. However, the specific values depend also on the particularities of the project and the data that each project has available. This work demonstrates that an uncertainty analysis should be included with all embodied carbon assessments to increase the transparency of the emissions reported and the comparison of alternatives. By increasing the reliability of assessments, this study supports the reduction of the net contribution of the construction industry to global carbon dioxide emissions. Practical Applications: There is an increasing interest in the construction industry in quantifying and reducing its carbon emissions. However, the methods to estimate the carbon emitted during the construction of projects are generally imprecise and contain uncertainty. Moreover, the information available to perform the analysis varies depending on the project phase when the assessment is performed. This study proposes a methodology to quantify uncertainty in carbon assessments for the construction of projects and to analyze its variation based on the information available. The approach was tested in the evaluation of three case studies. The results show that mean values in carbon assessments performed in early project phases can differ from 6% to 14% from those in later phases. In addition, the expected coefficient of variation (COV) for the concept, engineering, and construction phases ranges between 0.33–0.39, 0.12–0.28, and 0.04–0.20, respectively. These values can be employed to contrast with those obtained for the project. These references combined with the sensitivity analysis can contribute to improving decision making. For example, project managers may anticipate when additional information is required for a particular variable, and consultants may identify if the assessments are reliable enough to be communicated. Furthermore, this framework can be replicated by industry practitioners to obtain informed decisions when comparing different projects or project alternatives. [ABSTRACT FROM AUTHOR]
ISSN:07339364
DOI:10.1061/JCEMD4.COENG-15802