Comparing methods for estimating scope 3 waste emissions: a university case study
スコープ3廃棄物排出量推定手法の比較：大学事例研究 (AI 翻訳)
Sofia Abad, Travis Blomberg, Andrea Hicks
🤖 gxceed AI 要約
日本語
この研究は、大学の固形廃棄物データを用いて、スコープ3の廃棄物排出量を推定する4つのモデル（WARM、EIO-LCA、IPCC Waste Tool、SIMAP）を比較した。モデル間で推定値に大きなばらつきがあり、総排出量は約-6474トンから8642トンのCO2換算に及んだ。この結果は、モデルの選択が環境影響評価に大きな影響を与えることを示し、企業や大学の排出量比較における注意を促す。
English
This case study compares four models (WARM, EIO-LCA, IPCC Waste Tool, SIMAP) for estimating scope 3 waste emissions using solid waste data from a university. Results show large variability across models, with total emissions ranging from approximately -6,474 to 8,642 metric tons CO2e. Findings highlight the importance of model assumptions and system boundaries in carbon accounting, relevant for corporate and institutional scope 3 reporting.
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SSBJ基準に基づくスコープ3報告が求められており、本論文のようなモデル選択による差異の理解は、正確な排出量算定と投資家対応に不可欠である。日本の大学や企業が同様の課題に直面しているため、この比較研究は実践的な示唆を提供する。
In the global GX context
With global scope 3 disclosure mandates under ISSB and CSRD, understanding model-driven variability is critical for reliable reporting. This study provides empirical evidence of how different standard tools yield divergent results, informing practitioners about the need for transparency in methodology selection.
👥 読者別の含意
🔬研究者:Provides a systematic comparison of scope 3 waste models, identifying key assumptions driving variability.
🏢実務担当者:Highlights the impact of model choice on reported emissions, useful for selecting tools and interpreting peer comparisons.
🏛政策担当者:Underscores the need for standardized guidelines to reduce reporting inconsistency across organizations.
📄 Abstract（原文）
Abstract With climate change intensifying and growing concerns over greenhouse gas (GHG) emissions, accurate accounting of emissions has become crucial towards identifying hotspots and opportunities for reduction. Higher Education Institutions have taken a large initiative in carbon accounting by reporting scope 1, 2, and 3 emissions. However, scope 3 emissions remain particularly challenging due to its large scope and the diversity of available models and methodologies for calculating. This case study compares several commonly used models (WARM, EIO-LCA, IPCC Waste Tool, and SIMAP) for scope 3 GHG emissions accounting, focusing on GHG protocol category 5: waste generated in operations subcategory. Using a consistent dataset of solid waste metrics from the University of Wisconsin–Madison, differences in results are evaluated to assess the variability across models. Utilizing multiple models and scenarios within those models across a single multi-year data set enables identification of key assumptions and system boundaries that drive variability. The analysis revealed variation in scope 3 estimates across models, with total emissions ranging from approximately metric tons of −6474 to 8642 metric tons of CO 2 equivalents across the 2023 analysis year and models. These findings highlight the need to understand the different implications on projections of environmental impact generated by utilizing different available models with the same dataset and different settings within those models. And highlight the need to understand the different tradeoffs with respect to model assumptions and calculations alongside the effort needed to generate results with each model. This is relevant for considering the comparison among universities’ impacts as well, as these may change significantly based on their choice of model. This is relevant for universities as well when they are comparing their emissions to those of their peers.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/2515-7620/ae807cfirst seen 2026-07-05 04:57:33
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