Technology Prioritisation and Collaborative Retrofit Pathways for Public Building Decarbonisation: Evidence from a Sample of 218 Real-World Retrofit Projects
公共建築物の脱炭素化のための技術優先順位付けと協調的改修経路：218件の実改修プロジェクトからのエビデンス (AI 翻訳)
Zhenwei Guo, Yan Qu, Chan Xia, Stephen Siu Yu Lau, Zhidong Zhang, Yijia Miao, Qingqin Wang
🤖 gxceed AI 要約
日本語
中国の夏暑冬冷地域の公共建築物218件の改修データを分析し、炭素削減率を指標にXGBoost-SHAPとApriori分析を適用。屋根断熱、外壁断熱、換気改修が中核技術と特定され、受動的エンベロープ、日射制御・再エネ統合、運用管理改善の3つの共採用パターンを発見した。
English
Using 218 real-world retrofit projects in China's Hot Summer and Cold Winter region, this study applies XGBoost-SHAP and Apriori analysis to identify core technologies (roof insulation, external wall insulation, ventilation) and three co-adoption patterns (passive-envelope, solar-renewable integration, operational improvement).
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
日本のGX政策でも公共建築物の改修は重要である。本論文のデータ駆動型フレームワークは中国の事例だが、断熱・換気を中核とする技術優先順位や共採用パターンは、日本の建築改修計画やSBJ評価に応用可能な示唆を提供する。
In the global GX context
This paper offers an evidence-based, interpretable framework for prioritizing building retrofit technologies. The core technologies and co-adoption patterns identified are relevant for global building decarbonization, especially in similar climates, and the methodology is transferable to other regions.
👥 読者別の含意
🔬研究者:Demonstrates a robust combination of XGBoost and association rule mining for retrofit technology prioritization with interpretability.
🏢実務担当者:Identifies high-impact technologies (roof/wall insulation, ventilation) and co-adoption patterns to guide retrofit planning.
🏛政策担当者:Provides a data-driven basis for designing subsidy programs or regulatory standards for public building retrofits.
📄 Abstract（原文）
Public building retrofit is an important pathway for reducing operational carbon emissions, but evidence-based technology prioritisation remains limited under real-world multi-technology retrofit conditions. This study develops an interpretable data-driven framework to identify priority technologies and technology co-adoption patterns for public buildings in China’s Hot Summer and Cold Winter (HSCW) region. Based on 218 completed retrofit projects, the carbon reduction rate (CRR) was used as the performance indicator, and 15 retrofit technologies were analysed using FDR-adjusted Mann–Whitney U tests, repeated-validation XGBoost–SHAP analysis, and Apriori association-rule mining. The projects showed substantial variation in CRR, with a mean of 24.98% and a median of 21.70%. Across five repeated 5-fold cross-validations, the predictive XGBoost model achieved a mean R2 of 0.417 and a mean RMSE of 0.127. Roof insulation, external wall insulation, and ventilation system retrofit showed the strongest combined evidence and were classified as core technologies. Apriori analysis further revealed three empirical co-adoption patterns: integrated passive-envelope retrofit, solar-control and renewable-energy integration, and operational-management improvement. The findings suggest that retrofit planning in the HSCW region should prioritise envelope insulation and ventilation performance, while selecting shading, system, renewable-energy, and operational-control measures according to project-specific conditions.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.3390/buildings16152941first seen 2026-07-25 06:24:10
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