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BIM技術に基づく教育建築物の多段階炭素排出ホットスポット特定と低炭素最適化

Multi-Level Carbon Emission Hotspot Identification and Low-Carbon Optimization of Teaching Buildings Based on BIM Technology (原題)

Ming Lei, Hui Chen, Aojun Lei, Mengke Huang, 赵子健, 陈海丰

Buildings📚 査読済 / ジャーナル2026-10-25#炭素会計Origin: CN経営インパクト: 調達リスク対象セクター: construction
DOI: 10.3390/buildings16214244
原典: https://doi.org/10.3390/buildings16214244

🤖 gxceed AI 要約

日本語

中国の大学の鉄筋コンクリート造教育棟を対象に、BIM数量から炭素排出量を算定する枠組みを構築し、段階・材料・部材の各レベルでホットスポットを特定した。A1〜A5の総排出量は16,812.69 tCO2e、原単位442.51 kgCO2e/m2で、A1〜A3が94.40%を占めた。コンクリート・鉄筋・ALCブロックでA1〜A3の88.1%を占め、モンテカルロ不確実性分析と低炭素シナリオ評価により統合最適化で7.72%削減可能と示した。

English

Using BIM-derived quantities, the study builds a carbon accounting framework for a reinforced-concrete university teaching building in China and identifies hotspots at stage, material, and component levels. Total A1–A5 emissions were 16,812.69 tCO2e (442.51 kgCO2e/m2), with A1–A3 accounting for 94.40%; concrete, rebar, and AAC blocks drove 88.1% of A1–A3. Monte Carlo uncertainty and low-carbon scenario analysis show an integrated optimization scenario cuts A1–A5 emissions by 7.72%.

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

建設業のScope 3（カテゴリ1・2）算定や建材由来排出の可視化に関心を持つ日本企業にとって、BIM連携の算定手法はSSBJ開示やサプライチェーン排出管理の実務設計に参考となる。

In the global GX context

Adds a building-level, BIM-integrated embodied-carbon accounting method relevant to Scope 3 Category 1/2 reporting under GHG Protocol and CSRD/ISSB building-sector disclosure, with uncertainty quantification that strengthens disclosure credibility.

👥 読者別の含意

🔬研究者:BIM連携の建築物LCA算定と不確実性分析の手法設計の参考になる。

🏢実務担当者:建材選択や部材レベルの排出ホットスポット管理をScope 3算定に組み込む際の実務例として有用。

🏛政策担当者:建築物の炭素原単位規制や低炭素建材調達基準の設計に定量的根拠を提供する。

📄 Abstract（原文）

Taking a reinforced-concrete frame teaching building at a university as a case study, this study established a carbon emission accounting framework based on BIM-derived quantities, identified carbon emission hotspots at the stage, material, and component levels, and comprehensively evaluated the accounting results and emission reduction potential through sensitivity analysis, Monte Carlo uncertainty analysis, and low-carbon scenario assessment. The results showed that the total A1–A5 carbon emissions of the case-study building were 16,812.69 tCO2e, corresponding to a carbon emission intensity of 442.51 kgCO2e/m2, of which modules A1–A3 accounted for 94.40%. C35 concrete, reinforcing steel, and autoclaved aerated concrete blocks collectively contributed 88.1% of A1–A3 emissions, while reinforcing steel, infill walls, and floor slabs constituted the major component-level hotspots. Monte Carlo simulation showed that the baseline accounting result fell within the main probability distribution range, while the integrated optimization scenario reduced total A1–A5 carbon emissions by 7.72%. This study quantified carbon emissions from the building material production, transportation, and construction stages (A1–A5) of a teaching building and identified priority targets for emission reduction. The results provide a quantitative basis for low-carbon material selection, key component control, and construction-stage optimization of teaching buildings in China.

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