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A BIM-Driven Dynamic LCA Framework for Net Carbon Accounting of Buildings: A Case Study in Hot-Summer Region of China

BIM駆動型動的LCAフレームワークによる建物の正味炭素会計：中国暑熱地域のケーススタディ (AI 翻訳)

Qinghe Liu, Shushan Li, Zujun Liu, Hongmei Li

Sustainability📚 査読済 / ジャーナル2026-05-08#炭素会計Origin: CN
DOI: 10.3390/su18104682
原典: https://doi.org/10.3390/su18104682

🤖 gxceed AI 要約

日本語

本研究は、BIMとLCAを統合した建物のライフサイクル炭素会計の自動化フレームワークを提案。中国南寧のオフィスビルを対象としたケーススタディでは、運用段階と建材生産段階が主要排出源であり、グリッド排出係数や主要材料係数が炭素排出量に大きな影響を与えることを示した。実用的な低炭素設計ツールとしての価値がある。

English

This study proposes an automated BIM-driven LCA framework for building lifecycle carbon accounting. A case study in Nanning, China, shows that operational and material production stages are major emission sources, and sensitivity analysis identifies grid emission factor and key material factors as critical variables. The framework offers a real-time data feedback tool for low-carbon building design and a transparent methodological reference.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本でも建築物のライフサイクル炭素評価の重要性が高まっており、BIMとLCAの統合手法は、日本の建設業界における効率的な炭素会計の参考になる。ただし、中国固有の排出係数データベースに依存している点に注意。

In the global GX context

This paper contributes to global building carbon accounting literature by demonstrating a practical BIM-LCA integration with localized emission factors. The methodology aligns with lifecycle thinking in disclosure frameworks like TCFD and ISSB, though the data is specific to China. It highlights the potential for automated carbon tracking in building design.

👥 読者別の含意

🔬研究者:Provides a replicable BIM-LCA integration method and sensitivity analysis that can inform building carbon accounting research.

🏢実務担当者:Offers a tool for real-time carbon feedback during building design, aiding low-carbon optimization in engineering practice.

🏛政策担当者:Demonstrates a transparent accounting approach that could support building carbon reporting standards and regulations.

📄 抄録（日本語訳）

针对当前建筑全生命周期碳排放核算中普遍存在的数据来源分散、依赖多软件协同以及建筑信息模型（BIM）与生命周期评价（LCA）集成效率低等问题，本研究旨在构建一种BIM驱动的、数据可追溯的建筑全生命周期碳核算自动化方法。本文提出一种基于Revit二次开发的全生命周期碳核算框架。通过定义统一的数据映射规则并构建可扩展的本地化碳排放因子数据库，该框架实现了从BIM模型信息提取、智能因子匹配到分阶段核算与报告生成的 seamless 工作流程。以南宁某办公楼作为实证案例，结果表明运行阶段和建筑材料生产阶段是主要排放源，分别占总排放量的78.82%和24.13%；运输阶段占1.68%；施工阶段占0.40%；拆除与回收阶段因材料回收效益呈现–3.53%的负排放。所开发插件的核算结果与传统方法相比相对误差为6.67%，并通过不确定性分析验证了核算框架的稳健性。敏感性分析进一步揭示，电网排放因子、关键材料因子和建筑设计使用寿命是影响碳排放的核心变量。本研究的贡献在于提出一种可操作且可扩展的BIM-LCA集成解决方案。其实用价值在于为建筑设计阶段的低碳优化提供实时数据反馈工具，同时为工程实践中的碳核算提供高度透明的方法学参考，从而支持可持续城市发展追求中的数据驱动决策。

AI 翻訳（deepseek-v4-flash）。 正確を期す場合は下の原文を参照してください。

📄 Abstract（原文）

Addressing the prevalent issues of scattered data sources, reliance on multi-software collaboration, and low integration efficiency between Building Information Modeling (BIM) and Life Cycle Assessment (LCA) in current building life cycle carbon emission accounting, this study aims to construct a BIM-driven, data-traceable automated method for building life cycle carbon accounting. This paper proposes a life cycle carbon accounting framework based on Revit secondary development. By defining unified data mapping rules and constructing a scalable localized carbon emission factor database, this framework achieves a seamless workflow from BIM model information extraction and intelligent factor matching to phased accounting and report generation. Taking an office building in Nanning as an empirical case study, the results indicate that the operational stage and the building material production stage are the primary emission sources, accounting for 78.82% and 24.13% of the total emissions, respectively; the transportation stage accounts for 1.68%; the construction stage accounts for 0.40%; and the demolition and recycling stage exhibits negative emissions of –3.53% due to material recovery benefits. The accounting results of the developed plugin exhibit a relative error of 6.67% compared to traditional methods, and the robustness of the accounting framework is verified through uncertainty analysis. Sensitivity analysis further reveals that the grid emission factor, key material factors, and building design service life are the core variables affecting carbon emissions. The contribution of this study lies in proposing an operable and scalable BIM-LCA integrated solution. Its practical value resides in providing a real-time data feedback tool for low-carbon optimization during the building design stage, as well as offering a highly transparent methodological reference for carbon accounting in engineering practice, thereby supporting data-driven decision-making in the pursuit of sustainable urban development.

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