石炭火災から発生する典型汚染物質の特性調査：中国新疆スラブラクの事例研究
Investigation on Characteristics of Typical Pollutants Generated from Coal Fires: A Case Study of Sulabulak, Xinjiang, China (原題)
Xinrong Du, Zhicheng Yang, Qiang Zeng
🤖 gxceed AI 要約
日本語
本研究は、中国新疆スラブラクの地下石炭火災地域を対象に、実験室シミュレーション、リモートセンシング、現地観測を統合し、燃焼段階ごとのガス生成特性と重金属の移行メカニズムを解明した。また、炭素排出係数とリモートセンシング面積を組み合わせた石炭損失モデルを構築し、年間GHG排出量を約0.65万トンCO2換算と推定した。この手法は乾燥地域の石炭火災の炭素インベントリ開発に貢献する。
English
This study integrates laboratory simulation, remote sensing, and field monitoring to characterize pollutant emissions from the Sulabulak underground coal fire in Xinjiang, China. It identifies combustion stages, heavy metal partitioning, and estimates annual GHG emissions at approximately 0.65 × 10^4 t CO2 equivalent using a coupled coal loss model. The approach supports carbon accounting for coal fires in arid regions.
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
日本では石炭火災は主要課題ではないが、炭素会計の方法論（実験・リモセン・実測の統合）は、SSBJ対応の排出量算定やサプライチェーン排出量の精緻化に応用可能。特に、非定常排出源の算定手法は、日本の廃棄物処理やバイオマス燃焼などの排出量評価に示唆を与える。
In the global GX context
Globally, coal fires are an under-reported source of GHG emissions. This study's integrated accounting approach (micro-experiment, remote sensing, field measurement) offers a replicable methodology for carbon inventories in hard-to-measure emission sources, relevant to TCFD/ISSB disclosure where accurate Scope 1 accounting is critical.
👥 読者別の含意
🔬研究者:Provides a novel integrated methodology for carbon accounting of coal fires, combining experimental, remote sensing, and field data.
🏢実務担当者:Offers a framework for quantifying emissions from unconventional sources, useful for companies with mining or waste operations.
🏛政策担当者:Highlights the need to include coal fires in national GHG inventories and provides a method for doing so.
📄 Abstract（原文）
Coal fires are a significant source of greenhouse gas emissions and ecological pollutants, yet their emission characteristics and carbon accounting remain poorly constrained. To reveal the pollutant generation characteristics and carbon emission levels of the typical underground coal fire area in Sulabulak, Xinjiang, this study integrated laboratory simulation, multi-source remote sensing inversion, and in situ field monitoring. Thermogravimetric analysis, a high-temperature tube furnace, HSC thermodynamic simulation, and multi-source remote sensing data from Landsat-8/9 and Sentinel-1A were employed to investigate the gaseous products and heavy metal migration mechanisms at different combustion stages, and to delineate the spatial extent of different combustion states in the fire area. A coal loss model was then constructed by coupling experimentally determined carbon emission factors with remote sensing-derived areas and was compared with an emission flux model based on field measurements. The results show that the coal oxidation process proceeds through three distinct stages, with indicator gas ratios (CO2/CO and C2H4/C2H6) serving as effective indicators for combustion state identification. Heavy metal partitioning is governed by elemental volatility and redox conditions: As and Se partition predominantly into the gas phase, while Zn becomes enriched in fly ash. Remote sensing time series analysis documents continuous fire expansion accompanied by progressive surface subsidence. By cross-validating the indirect coal loss model (constrained by remote sensing area) against the direct emission flux model (constrained by field measurements), we estimate the current annual GHG emission of the Sulabulak fire area at approximately 0.65 × 104 t CO2 equivalent. This study proposes a coupled “micro-experiment–macro-remote sensing–field measurement” approach for carbon emission accounting, providing reliable data support for environmental pollution control and the development of carbon inventories for coal fires in arid regions.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/fire9080360first seen 2026-08-27 05:37:30 · last seen 2026-09-22 05:09:41
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