Research on and Application of a Low-Carbon Assessment Model for Railway Bridges During the Construction Phase Based on the ANP-Fuzzy Method

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🔬研究者:Provides a validated integrated methodology (ANP-Fuzzy) for factor weighting and fuzzy evaluation in carbon assessment, useful for advancing construction carbon accounting research.

🏢実務担当者:Bridge designers and construction managers can use the proposed index system and model to identify major carbon sources and optimize low-carbon design during planning.

🏛政策担当者:Offers a systematic tool for setting carbon reduction targets and benchmarks in infrastructure projects, supporting national decarbonization policies.

Against the backdrop of global climate change and China’s “dual-carbon” goals, carbon emissions from the construction phase of transportation infrastructure, particularly the rapidly expanding railway network, have garnered significant attention. However, systematic research and general evaluation models targeting the factors influencing carbon emissions during the railway bridge construction phase remain insufficient. To address this gap, this study presents a novel low-carbon evaluation model that integrates the analytic network process (ANP) and the fuzzy comprehensive evaluation (FCE) method. First, a carbon accounting model covering four stages—material production, transportation, construction, and maintenance—is established based on life cycle assessment (LCA) theory, providing a data foundation. Second, an innovative low-carbon evaluation index system for railway bridges, comprising 5 criterion layers and 23 indicator layers, is constructed. The ANP method is employed to calculate weights, effectively capturing the interdependencies among indicators, while the FCE method handles assessment ambiguities, forming a comprehensive evaluation framework. A case study of the bridge demonstrates the model’s effectiveness, yielding an evaluation score of 82.38 (“excellent” grade), which is consistent with expert judgement. The ranking of indicator weights from the model is highly consistent with the actual carbon emission inventory ranking (Spearman coefficient of 0.714). Key indicators—C21 (use of high-performance materials), C22 (concrete consumption), and C25 (transportation energy consumption)—collectively account for approximately 60% of the total impact, accurately identifying the major emission sources. This research not only verifies the model’s efficacy in pinpointing critical carbon sources but also provides a scientific theoretical basis and practical tool for low-carbon decision-making and optimization in the planning and design stages of railway bridge projects.

• semanticscholar https://doi.org/10.3390/infrastructures11010032first seen 2026-05-06 00:48:42