Methane Detection of Super-Emitters by Remote Sensing and Investigation of Wind-Driven Bias in Complex Terrain: A Multi-Instrument Analysis

Metallurgical coal operations are a significant but poorly constrained source of methane (CH4) in Canada. We present a multi-instrument analysis of 63 methane plume detections at Fording River Operations, British Columbia (January 2022–March 2026), using the Airborne Visible/Infrared Imaging Spectrometer—Next Generation (AVIRIS-NG; n = 39), the Earth Surface Mineral Dust Source Investigation (EMIT; n = 4) and Tanager-1 (n = 20). Of these, 41 plumes (65%) were quantified, with retrieved emission rates of 34–3622 kg CH4 h−1; 54% exceeded the 500 kg h−1 super-emitter threshold. Because 73% of detections fall in September and no detections are available for 2023, results characterize the late-summer overpass window and should not be extrapolated seasonally without further coverage. The central finding is a systematic, asymmetric wind-speed disagreement between two numerical weather prediction (NWP) products that maps onto the Integrated Mass Enhancement (IME) quantification outcome. A univariate logistic regression identifies HRRR wind speed as a significant predictor of quantification success (OR = 0.29 per m s−1, 95% CI [0.15, 0.56], p < 0.001; AUC = 0.80; 5-fold cross-validated AUC = 0.79 ± 0.20, fold range 0.45–1.00). Cross-validation against ERA5-Land shows that HRRR exceeds ERA5 by a mean of +0.86 m s−1 (+43%) for unquantified events but shows near-zero disagreement for quantified events (–0.09 m s−1, –6%). A sensitivity analysis restricted to HRRR-forced retrievals (EMIT + Tanager-1, n = 24) confirms the finding is not an artefact of mixed wind data sources (OR = 0.28, AUC = 0.83, p = 0.018).

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Journal
Mining
Published
2026-05-22
DOI
https://doi.org/10.3390/mining6020035
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
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article

Methane Detection of Super-Emitters by Remote Sensing and Investigation of Wind-Driven Bias in Complex Terrain: A Multi-Instrument Analysis

Yutong Chai, Ke Li, Soheil Asgarpour, Shunde Yin et al.
Mining
Atmospheric and Environmental Gas Dynamics
article

Methane Detection of Super-Emitters by Remote Sensing and Investigation of Wind-Driven Bias in Complex Terrain: A Multi-Instrument Analysis

Yutong Chai, Ke Li, Soheil Asgarpour, Shunde Yin, Richard Boudreault, Kristie Jingyi Hu
article en

Abstract

Metallurgical coal operations are a significant but poorly constrained source of methane (CH4) in Canada. We present a multi-instrument analysis of 63 methane plume detections at Fording River Operations, British Columbia (January 2022–March 2026), using the Airborne Visible/Infrared Imaging Spectrometer—Next Generation (AVIRIS-NG; n = 39), the Earth Surface Mineral Dust Source Investigation (EMIT; n = 4) and Tanager-1 (n = 20). Of these, 41 plumes (65%) were quantified, with retrieved emission rates of 34–3622 kg CH4 h−1; 54% exceeded the 500 kg h−1 super-emitter threshold. Because 73% of detections fall in September and no detections are available for 2023, results characterize the late-summer overpass window and should not be extrapolated seasonally without further coverage. The central finding is a systematic, asymmetric wind-speed disagreement between two numerical weather prediction (NWP) products that maps onto the Integrated Mass Enhancement (IME) quantification outcome. A univariate logistic regression identifies HRRR wind speed as a significant predictor of quantification success (OR = 0.29 per m s−1, 95% CI [0.15, 0.56], p < 0.001; AUC = 0.80; 5-fold cross-validated AUC = 0.79 ± 0.20, fold range 0.45–1.00). Cross-validation against ERA5-Land shows that HRRR exceeds ERA5 by a mean of +0.86 m s−1 (+43%) for unquantified events but shows near-zero disagreement for quantified events (–0.09 m s−1, –6%). A sensitivity analysis restricted to HRRR-forced retrievals (EMIT + Tanager-1, n = 24) confirms the finding is not an artefact of mixed wind data sources (OR = 0.28, AUC = 0.83, p = 0.018).

MiningVol. 6(2)
Council of Canadian Academies (CA), University of Waterloo (CA)
Openalex Percentile: Top 6%
Atmospheric and Environmental Gas Dynamics
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Methane Detection of Super-Emitters by Remote Sensing and Investigation of Wind-Driven Bias in Complex Terrain: A Multi-Instrument Analysis — Yutong Chai, Ke Li, et al. · Mining (2026) | TGRS Research Map | TGRS