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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-173
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-173
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 06 May 2019

Submitted as: research article | 06 May 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

Towards accurate methane point-source quantification from high-resolution 2D plume imagery

Siraput Jongaramrungruang1, Christian Frankenberg1,2, Georgios Matheou3, Andrew Thorpe2, David R. Thompson2, Le Kuai4, and Riley Duren2 Siraput Jongaramrungruang et al.
  • 1Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena,CA91125, USA
  • 2NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA91109, USA
  • 3Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA
  • 4Joint Institute for Regional EarthSystem Science and, University of California, Los Angeles, CA 90095, USA

Abstract. Methane is the second most important anthropogenic greenhouse gas in the Earth climate system but emission quantification of localized point sources has been proven challenging, resulting in ambiguous regional budgets and source categories distributions. Although recent advancements in airborne remote sensing instruments enable retrievals of methane enhancements at unprecedented resolution of 1–5 m at regional scales, emission quantification of individual sources can be limited by the lack of knowledge of local wind speed. Here, we developed an algorithm that can estimate flux rates solely from mapped methane plumes, avoiding the need for ancillary information on wind speed. The algorithm was trained on synthetic measurements using Large Eddy Simulation under a range of background wind speeds of 1–10 m/s and source emission rates ranging from 10 to 1000 kg/hr. The surrogate measurements mimic plume mapping performed by the next generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and provide an ensemble of 2-D snapshots of column methane enhancements at 5m spatial resolution. We make use of the integrated total methane enhancement in each plume, denoted as Integrated Methane Enhancement (IME), and investigate how this IME relates to the actual methane flux rate. Our analysis shows that the IME corresponds to the flux rate non-linearly and is strongly dependent on the background wind speed over the plume. We demonstrate that the plume width, defined based on the plume angular distribution around its main axis, provides information on the associated background wind speed. This allows us to invert source flux rate based solely on the IME and the plume-shape itself. On average, the error estimate based on randomly generated plumes is approximately 30 % for an individual estimates and less than 10 % for an aggregation of 30 plumes. A validation against a natural gas controlled release experiment agree to within 32 %, supporting the basis for the applicability of this technique to quantifying point sources over large geographical area in airborne field campaigns and future space-based observations.

Siraput Jongaramrungruang et al.
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Siraput Jongaramrungruang et al.
Siraput Jongaramrungruang et al.
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Latest update: 17 Aug 2019
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Short summary
This paper demonstrates the use of high-resolution 2D plume imagery from airborne remote sensing retrievals to quantify methane point sources emissions. It shows significant improvements on the flux estimates without the need for direct wind speed measurements. This paves the way for enhanced flux estimates in future field campaign and space-based observations to better understand the magnitude and distribution of various point sources of methane.
This paper demonstrates the use of high-resolution 2D plume imagery from airborne remote sensing...
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