Uncertainty Propagation in Bridge Construction Carbon Emission Quantification

Hafiz Muhammad Hazib (), Imran Shabbir (), Weizong Lai (), Yue Pan () and Jianjun Qin ()
Additional contact information
Hafiz Muhammad Hazib: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Ocean and Civil Engineering
Imran Shabbir: Prime Engineering & Testing Consultants
Weizong Lai: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Ocean and Civil Engineering
Yue Pan: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Ocean and Civil Engineering
Jianjun Qin: Shanghai Jiao Tong University, State Key Laboratory of Ocean Engineering, Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, School of Ocean and Civil Engineering

A chapter in Data-Driven Methods for Reliability and Safety Engineering: Applications in Industrial Systems, 2026, pp 439-452 from Springer

Abstract: Abstract Given the rapid expansion of infrastructure such as large-scale bridges in developing countries, their environmental impacts, particularly during the construction phase from the perspective of carbon emissions, have attracted have become a subject of increasing scholarly and policy interest. This study presents a probabilistic life cycle assessment for a large-scale bridge in Pakistan to illustrate uncertainty propagation in carbon emission quantification during construction, beginning with the explicit identification of uncertainties in emission factors. Monte Carlo simulation is employed to estimate the embodied carbon footprint associated with material production, transportation, and on-site construction activities, resulting in an average of $$72.5{ } \times { }10^{6} { }\;{\text{kg CO}}_{2} - {\text{eq }}\left( {{ sigma }{ } = { }11.6{ } \times { }10^{6} {\text{ kg CO}}_{2} - {\text{eq}}} \right).$$ 72.5 × 10 6 kg CO 2 - eq sigma = 11.6 × 10 6 kg CO 2 - eq . The uncertainty propagation indicates substantial variability $$\left( {{\text{CV }} = { }16{\text{\% }}} \right)$$ CV = 16 \% with $$\pm 20{-}30\%$$ ± 20 - 30 % confidence intervals, driven by probabilistic characteristics of material, transportation, and energy emission factors. From the expected value perspective, material extraction accounts for 55% of total emissions, transportation for 43%, and construction activities for 3%. At the component-level, the superstructure ( $$23.38{ } \times { }10^{6} { }\;{\text{kg CO}}_{{2}} - {\text{eq}}$$ 23.38 × 10 6 kg CO 2 - eq ) and deck ( $$23.27 \times 10^{6} \;{\text{ kg CO}}_{{2}} - {\text{eq}}$$ 23.27 × 10 6 kg CO 2 - eq ) represent the primary sources. To reduce life-cycle emissions and associated uncertainties, technical measures such as low-clinker binders, optimized logistics, and BIM-integrated stochastic carbon modules are recommended, complemented by policy interventions including performance-based carbon caps, geospatial emission factors, and blockchain-based supplier disclosures. This framework advances traditional LCA methodologies, enabling more informed low-carbon decision-making in resource-constrained contexts.

Keywords: Probabilistic LCA; Monte Carlo simulation; Embodied carbon; Bridge construction (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ssrchp:978-3-032-22873-4_32

Ordering information: This item can be ordered from
http://www.springer.com/9783032228734

DOI: 10.1007/978-3-032-22873-4_32

Access Statistics for this chapter

More chapters in Springer Series in Reliability Engineering from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().