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Updated: May 15, 2026

Design and Use of a Full Flow Sampling System (FFS) for the Quantification of Methane Emissions
Published on: June 12, 2016
Methane Emissions from Underground Coal Mines
Marcelo I Guzman1,2, Thomas M Parris3, Stephen F Greb3
1Department of Chemistry, University of Kentucky, Lexington, Kentucky 40506, United States.
Abstract:
Methane emissions from Kentucky underground coal mines were measured using near-infrared spectrometers deployed on a vehicle, an airplane, and a small uncrewed aerial system (sUAS), offering insights into the effectiveness of these methods under real-world conditions. From 2021-2022, surveys covered 14 active, 4 inactive, and 4 abandoned mines across Kentucky's coal-producing basins. Vehicle-based surveys at 13 active mines detected methane anomalies at 9 sites with anomaly lengths spanning tens to hundreds of meters and peak emissions of 665 ± 229 kg h-1 from two Cardinal mine fans. Airborne GHGSat surveys identified anomalies at 3 sites, including a peak of 1062 ± 386 kg h-1 at Cardinal, consistent with the EPA's Greenhouse Gas Reporting Program (GHGRP) ranges. sUAS emissions measured at Straight Creek were 65 ± 22 kg h-1 (below the GHGRP reporting threshold). Aeris vehicle-based estimates more closely matched GHGRP values than GHGSat estimates and exhibited smaller uncertainties. For example, at Cardinal Nebo, Aeris reported 228 ± 142 kg h-1 versus GHGRP's 360 kg h-1, while GHGSat reported 716 ± 355 kg h-1. These results have important implications, where terrain and road access permit, vehicle-based methods can yield emissions estimates comparable to aircraft- and satellite-based approaches. Additionally, the higher detection rate of vehicle-based surveys suggests superior performance in identifying methane anomalies. This study highlights the spatial and temporal variability of methane emissions from underground coal mines and emphasizes the importance of integrating multiple observational strategies to improve monitoring in underrepresented regions. It also provides a transferable framework for areas where limited data availability has hindered effective methane tracking and mitigation planning.
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