Evaluating the detectability of methane point sources from satellite observing systems using microscale modeling

This study evaluates the efficacy of current satellite observing systems to detect methane point sources from typical oil and gas production (O&G) facilities using a novel very high-resolution methane concentration dataset generated using a microscale model. Transport and dispersion of typical methane emissions from seven well pads were simulated and the column enhancements for pseudo satellite pixel sizes of 3, 1, and 0.05 km were examined every second of the 2-h simulations (7200 realizations). The detectability of plumes increased with a pixel resolution, but two orders of magnitude change in emission rates at the surface results only in about 0.4%, 1.6%, and 47.8% enhancement in the pseudo-satellite retrieved methane column at 3, 1, and 0.05 km, respectively. Average methane emission rates estimated by employing the integrated mass enhancement (IME) method to column enhancements at 0.05 km showed an underestimation of the mean emissions by 0.2–6.4%. We show that IME derived satellite-based inversions of methane emissions work well for large persistent emission sources (e.g., super emitters), however, the method is ill-suited to resolve short-term emission fluctuations (< 20 min) in typical well site emissions due to the limitations in satellite detection limits, precision, overpass timing, and pixel resolution.

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Author Bhardwaj, Piyush
Kumar, Rajesh
Mitchell, Douglas A.
Randles, Cynthia A.
Downey, Nicole
Blewitt, Doug
Kosovic, Branko
Publisher UCAR/NCAR - Library
Publication Date 2022-10-19T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2023-08-18T18:41:34.784430
Metadata Record Identifier edu.ucar.opensky::articles:25825
Metadata Language eng; USA
Suggested Citation Bhardwaj, Piyush, Kumar, Rajesh, Mitchell, Douglas A., Randles, Cynthia A., Downey, Nicole, Blewitt, Doug, Kosovic, Branko. (2022). Evaluating the detectability of methane point sources from satellite observing systems using microscale modeling. UCAR/NCAR - Library. http://n2t.net/ark:/85065/d7v69pck. Accessed 24 April 2025.

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