Single-blind test of airplane-based hyperspectral methane detection via controlled releases

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Abstract

Methane leakage from point sources in the oil and gas industry is a major contributor to global greenhouse gas emissions. The majority of such emissions come from a small fraction of “super-emitting” sources. We evaluate the emission detection and quantification capabilities of Kairos Aerospace’s airplane-based hyperspectral imaging methane emission detection system for methane fluxes of 18–1,025 kg per hour of methane (kgh(CH4)). In blinded controlled releases of methane conducted over 4 days in San Joaquin County, CA, Kairos detected 182 of 200 valid nonzero releases, including all 173 over 15 kgh(CH4) per meter per second (mps) of wind and none of the 12 nonzero releases below 8.3 kgh(CH4)/mps. Nine of the 26 releases in the partial detection range of 5–15 kgh(CH4)/mps were detected. There were no false positives: Kairos did not detect methane during any of the 21 negative controls. Plume quantification accuracy depends on the wind measurement technique, with a parity slope of 1.15 (σ = 0.037, R2 = 0.84, N = 185) using a cup-based wind meter and 1.45 (σ = 0.059, R2 = 0.80, N = 157) using an ultrasonic anemometer. Performance is comparable even with only modeled wind data. For emissions above 15 kgh/mps, quantification error scales as roughly 30%–40% of emission size, even when using wind reanalysis data instead of ground-based measurements. This reflects both uncertainty in wind measurements and in Kairos’ estimates. These findings suggest that at 2 mps winds under favorable environmental conditions in the United States, Kairos could detect and quantify over 50% of total emissions by identifying super-emitting sources.

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