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Optimizing Carbon Emission Reduction Pathways in Prefabricated Building Materialization Stages: A Cloud Entropy and NK Model Approach

プレハブ建築の材料化段階における炭素排出削減経路の最適化：クラウドエントロピーおよびNKモデルアプローチ (AI 翻訳)

Daopeng Wang, Huan Liu, Jiaming Xu, Ping Liu, Yu Fang

Applied Sciences📚 査読済 / ジャーナル2026-04-04#炭素会計Origin: CN
DOI: 10.3390/app16073539
原典: https://doi.org/10.3390/app16073539

🤖 gxceed AI 要約

日本語

本研究は、プレハブ建築の材料化段階における炭素排出の影響因子と最適化経路を調査。中国西部の大規模プレキャスト工場での縦断的フィールド調査に基づき、32因子の排出ウェイトをクラウドエントロピーモデルで定量化。その結果、低ウェイト因子でも連鎖効果によりシステム全体の炭素削減に大きな影響を与える「レバレッジ効果」が存在することを発見。NKモデルシミュレーション（1万回）で各因子の削減ポテンシャルを予測し、最もレバレッジ効果の高い4指標を特定。直接的排出制御と間接的連鎖最適化を統合した戦略的提言を行う。

English

This study investigates influencing factors and optimization pathways for embodied carbon emissions in prefabricated building materialization. Using field data from a large precast factory in western China, it develops a cloud entropy model to weigh 32 factors, revealing 'leveraging effects' where low-weight factors can disproportionately influence systemic carbon reduction via cascading impacts. NK model simulations (10,000 iterations) identify four key leverage indicators. Strategic recommendations emphasize a synergistic approach combining direct emission control and indirect cascading optimization, offering actionable insights for systemic carbon reduction in prefabricated construction.

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

中国のプレハブ建築を対象とした研究だが、クラウドエントロピーやNKモデルを用いた排出因子の特定と最適化手法は、日本の建設業界における炭素削減戦略にも応用可能。特に、材料調達段階での間接的な排出削減に示唆を与える。

In the global GX context

This study provides a novel method using cloud entropy and NK models to identify key factors for carbon reduction in prefabricated construction, relevant globally for the construction sector's decarbonization. The 'leveraging effect' concept can inform policy design and corporate strategy in other countries by highlighting indirect cascading impacts.

👥 読者別の含意

🔬研究者:GX researchers can learn the application of cloud entropy and NK modeling for systemic carbon reduction in construction supply chains, particularly the identification of leveraging factors.

🏢実務担当者:Corporate sustainability teams in construction can use the factor identification method to prioritize emission reduction efforts and design more effective interventions.

🏛政策担当者:Policymakers can consider leveraging factors with cascading impacts for more efficient building sector decarbonization policies, focusing on both direct and indirect emission pathways.

📄 Abstract（原文）

In response to escalating global environmental challenges, mitigating carbon emissions in the construction sector has emerged as a critical strategy for addressing climate change. As reported by the United Nations Environment Programme (UNEP) and the International Energy Agency (IEA), the construction industry remains a major contributor to global greenhouse gas emissions. This study investigates the influencing factors and optimization pathways for embodied carbon emissions during the materialization phase of prefabricated buildings. Through longitudinal field research at a large-scale precast component factory in western China, key carbon emission factors were identified using Min–Max normalization and Principal-Components Analysis (PCA). A cloud entropy–based evaluation model was further developed to quantify the emission weights of 32 factors. The results reveal the existence of ‘leveraging effects’ among emission factors, wherein certain low-weight factors exert disproportionate influence on systemic carbon reduction because of their cascading impacts on other variables. Prioritizing factors with greater leveraging potential is imperative for the formulation of effective emission reduction policies. This study leverages NK model simulations (10,000 iterations), to predict the reduction potential of each factor and identifies four indicators with the most significant leveraging effects. Strategic recommendations are proposed that emphasize a synergistic approach that integrates direct emission control and indirect cascading optimization. These findings provide actionable insights for achieving systemic carbon reduction in prefabricated building systems.

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