Carbon footprint evaluation for waste management of fluorinated anaesthetics in the UK using mathematical modelling
英国におけるフッ素化麻酔薬の廃棄物管理の炭素フットプリント評価：数理モデルを用いて (AI 翻訳)
Quinn Stein, Ali Özel, A. Chakera, Marc P. Y. Desmulliez, Humphrey H. P. Yiu, Martin R. S. McCoustra
🤖 gxceed AI 要約
日本語
英国NHSのフッ素化麻酔薬（特にデスフルラン）の廃棄処理経路に伴う炭素排出を推定する数理モデルとPython APIを開発。高温焼却が最も一般的な経路で、大気放出と比較して70%以上の排出削減が可能。プラズマ破壊は不完全燃焼生成物を減らし、排出を5%未満に抑える可能性があるが、実証と実装可能性の検証が必要。
English
This study develops a mathematical model and open-source Python API to estimate carbon emissions from disposal pathways of fluorinated anaesthetics in the UK NHS. High-temperature incineration in clinical waste streams is the most likely route, reducing emissions by over 70% compared to release. Plasma destruction shows the highest potential, cutting emissions to less than 5% by reducing incomplete combustion products, though validation and feasibility studies are needed.
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
日本の医療機関でも麻酔薬の温室効果ガス排出が課題となっており、脱炭素経営が求められる中、廃棄物処理経路の選択による排出削減の定量評価手法は参考になる。SSBJ開示やサステナビリティ報告において、医療分野のスコープ1・2排出削減に寄与する可能性がある。
In the global GX context
This paper provides a quantitative framework for assessing disposal pathways of high-GWP anaesthetic gases, relevant to global healthcare decarbonization efforts. It aligns with TCFD/ISSB climate disclosure requirements by offering a method to account for Scope 1 emissions from anaesthetic use and disposal, and supports transition planning in the healthcare sector.
👥 読者別の含意
🔬研究者:Provides a replicable modelling approach for estimating emissions from medical waste disposal, useful for healthcare carbon footprint research.
🏢実務担当者:Offers a tool (Python API) for hospitals to model and reduce emissions from anaesthetic waste, aiding sustainability reporting.
🏛政策担当者:Highlights the need for policy on anaesthetic waste disposal routes to achieve healthcare emission reduction targets.
📄 Abstract（原文）
The UK NHS faces increasing pressure to diminish its carbon footprint, with fluorinated anaesthetic agents representing a significant source of direct greenhouse gas emissions. Several NHS trusts retain substantial quantities of unused stock and waste volatile anaesthetics (VAs), particularly desflurane, requiring appropriate disposal. However, a crucial unquantified aspect is the endpoint destruction routes and associated emissions for accumulated desflurane stock and waste anaesthetics. We developed a mathematical model accompanied by an open-source Python-based application programming interface (API) to estimate equivalent carbon emissions and their climate impacts across disposal pathways. Stochastic modelling also estimates uncertainties of input parameters and their effects on model predictions. User-defined input parameters in the API allow practitioners to model specific destruction pathways. We identified high-temperature incineration in clinical waste streams as the most likely route, which, compared with release, shows reductions of more than 70% in equivalent emissions. Model predictions suggest that plasma destruction has the highest potential for reducing equivalent carbon emissions, to less than 5% from all waste fluorinated VAs by reducing the formation of products of incomplete combustion, with an associated reduction in climate impact. Crucial work still needs to be done to validate theoretical estimates, accurately assess the formation of products of incomplete combustion from fluorinated VAs under varying destruction conditions, and evaluate the feasibility of implementing the assessed waste streams.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.bja.2026.05.051first seen 2026-08-03 04:54:26
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。