NIR Spectroscopy for Non-Destructive Prediction of Greenhouse Gas Emissions and Global Warming Potential by Biomass Combustion
バイオマス燃焼による温室効果ガス排出と地球温暖化ポテンシャルの非破壊予測のためのNIR分光法 (AI 翻訳)
Panmanas Sirisomboon, Prakash Gyawali, Jetsada Posom, Ravipat Lapcharoensuk, Bim Prasad Shrestha, Axel Funke
🤖 gxceed AI 要約
日本語
本レビューは、バイオマス燃焼による温室効果ガス（GHG）排出と地球温暖化ポテンシャル（GWP）の予測に近赤外分光法（NIR）が利用可能かを検討する。GHG排出測定の従来法と比較し、NIR分光法は非破壊で迅速な評価を可能にする。サトウキビバガスなどの例を用いて、NIR分光法の利点と限界を示し、気候変動対策への応用可能性を確認した。
English
This review examines the feasibility of using near-infrared (NIR) spectroscopy for non-destructive prediction of greenhouse gas (GHG) emissions and global warming potential (GWP) from biomass combustion. It compares NIR spectroscopy to conventional methods and demonstrates its advantages for rapid assessment. Case studies on sugarcane bagasse confirm its potential as an alternative to IPCC estimation methods for climate change mitigation.
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
この研究は、バイオマス燃焼に伴うGHG排出の迅速評価手法を提案しており、日本のバイオマス発電所や廃棄物処理施設での排出管理に応用できる可能性がある。ただし、日本のGHG排出報告制度（省エネ法・温対法）との直接の関連は薄いが、測定技術の効率化に貢献できる。
In the global GX context
This paper presents a novel method for predicting GHG emissions from biomass combustion using NIR spectroscopy, which could support monitoring and reporting in global climate frameworks like the IPCC guidelines. It offers a practical tool for biomass-based energy systems, aligning with the need for accurate emission factors under disclosure regimes such as the EU's CSRD. However, it is not directly tied to corporate disclosure standards.
👥 読者別の含意
🔬研究者:Researchers working on biomass combustion emission modeling may find NIR spectroscopy a promising non-destructive technique for rapid GHG prediction.
🏢実務担当者:Sustainability teams in biomass power plants could use this method for real-time emission monitoring to improve reporting accuracy.
🏛政策担当者:Policymakers concerned with biomass energy's climate impact might consider integrating such measurement techniques into national GHG inventory methodologies.
📄 Abstract（原文）
Greenhouse gas (GHG) emissions from biomass combustion include carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), which cause climate change and global warming. By measuring GHG emissions by biomass combustion, a potent protocol for the calculation of global warming potential (GWP), which is how much the global temperature has risen due to combustion processes, can be achieved, contributing to determining the mean reduction in global temperature rise and fostering a transition towards more sustainable energy systems. Additionally, warning can be given of the GHG and GWP risks associated with different species of biomass. This review includes the GHG emissions and GWP of biomass combustion and their measurement and estimation directly through biomass sample combustion, using unmanned aerial vehicles (UAVs) and satellite measurements of radiation interacting with atmospheric gases, or satellite-derived data and calculations according to IPCC guidelines. In addition, the relationship of lignocellulosic compounds and elements in biomass to HHV and GHG emissions is described. The key mechanism of molecular vibration of hydrogen bonds in biomass caused by NIR radiation related to GHG emissions is revealed and recorded regarding the possibility of using NIR spectroscopy for the prediction of GHG emissions and GWP. Calculation examples for sugarcane bagasse and other biomass species are shown. The comparative advantages and limitations of NIR spectroscopy with respect to other methods are included. These factors lead to elucidation of the possibility of using NIR spectroscopy for non-destructive prediction of GHG emissions. In this review, the feasibility of using NIR spectroscopy to evaluate GHG emissions, GWP and emission factors (EFs) as an alternative to IPCC estimation methods related to climate change by biomass combustion is confirmed. NIR spectroscopy is a novel methodology for predicting GHG emissions and GWP directly from intact chip or powder biomass spectral data without explicit gas measurement. This article records the essential spectroscopic knowledge of biomass polymer valorization that is of value in polymer science.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.3390/polym18091142first seen 2026-05-14 22:43:09
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