An early-stage embodied carbon assessment method for the Global South: Sri Lankan case study
グローバルサウスのための初期設計段階におけるエンボディドカーボン評価手法：スリランカのケーススタディ (AI 翻訳)
A. Nawarathna, Zaid Alwan, Barry J. Gledson, N. Fernando
🤖 gxceed AI 要約
日本語
スリランカのオフィスビル25棟のデータを用いて、初期設計段階でエンボディドカーボン（EC）を推定する回帰モデルを開発。グロス内部床面積と外壁面積が主要な変数であり、データ制約下でも実用的なEC推定を可能にする。
English
This study develops a multiple linear regression model for early-stage embodied carbon (EC) estimation using data from 25 office buildings in Sri Lanka. Gross internal floor area (GIFA) and external wall area (EWA) are the most influential parameters. The model provides a practical, data-efficient tool for EC assessment in Global South contexts.
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
日本ではSSBJや有報でのカーボン開示が進むが、データが豊富な先進国と異なり、本論文が提示するデータ制約下での簡易EC推定手法は、日本の中小企業や途上国サプライチェーンの管理にも示唆を与える。
In the global GX context
This paper addresses a critical gap for embodied carbon quantification in data-scarce Global South contexts, aligning with the need for accessible tools under growing carbon disclosure mandates (e.g., ISSB, CSRD). Its regression-based approach could be adapted for other developing countries.
👥 読者別の含意
🔬研究者:Researchers in carbon accounting and building sustainability can use this model as a basis for adapting to other data-scarce contexts.
🏢実務担当者:Built environment professionals in the Global South can apply this early-stage tool to estimate embodied carbon without extensive data.
🏛政策担当者:Policymakers in developing countries can leverage this method to set benchmarks and incentivize low-carbon design.
📄 Abstract（原文）
Quantifying embodied carbon (EC) is essential for mitigating climate change impacts and reducing excessive use of natural and non-renewable materials. Yet, many Global South countries face several challenges such as data limitations, technical capacity gaps and limited use of EC assessment tools, particularly at early design stage where the greatest reduction potential exists. This study therefore aims to develop an accessible early design stage EC assessment model to support more effective EC management. This study employs a mono-method quantitative approach using secondary data from 25 office building projects in Sri Lanka. Data for model development were extracted from architectural drawings and bills of quantities (BOQs) to determine material quantities, while EC coefficients were obtained from Inventory of carbon and energy (ICE) v3.0. Model development integrated multiple linear regression (MLR) technique with life cycle assessment (LCA) principle. The findings indicate that the developed model provides accurate and reliable EC estimates using a limited set of early design parameters. Gross internal floor area (GIFA) and external wall area (EWA) were found to be the most influential in determining EC estimations. The model provides built environment professionals with a practical and time-efficient tool for estimating EC at the early design stage, supporting informed design decisions, wider adoption in data-scarce contexts, and improved carbon management in the Global South. This study is distinctive in providing an accessible EC assessment model specifically tailored to the constraints of Global South contexts, where limited data and technical capacity often hinder effective carbon management.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1108/bepam-11-2025-0394first seen 2026-06-29 06:32:20
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