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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/amt-2020-51
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-51
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 12 May 2020

Submitted as: research article | 12 May 2020

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This preprint is currently under review for the journal AMT.

Quantifying the impact of aerosol scattering on the retrieval of methane from airborne remote sensing measurements

Yunxia Huang1,2, Vijay Natraj1, Zhaocheng Zeng2,4, and Yuk L. Yung2,3 Yunxia Huang et al.
  • 1School of Science, Nantong University, Nantong, 226007, China
  • 2Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125, USA
  • 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
  • 4Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095, USA

Abstract. As a greenhouse gas with strong global warming potential, atmospheric methane (CH4) emissions have attracted a great deal of attention. Remote sensing measurements can provide information about CH4 sources and emissions. However, accurate assessment of CH4 emissions is challenging due to the influence of aerosol scattering in the atmosphere. In this study, imaging spectroscopic measurements from the Airborne Visible/Infrared Imaging Spectrometer–Next Generation (AVIRIS-NG) in the short-wave infrared are used to analyze the impact of aerosol scattering on CH4 retrievals. Using a numerically efficient two-stream-exact-single-scattering radiative transfer model, we also simulate AVIRIS-NG measurements for different scenarios and quantify the impact of aerosol scattering using two retrieval techniques – the traditional Matched Filter (MF) method and the Optimal Estimation (OE) method, which is a popular approach for trace gas retrievals. The results show that the MF method exhibits up to 50 % lower fractional retrieval bias compared to the OE method at high CH4 concentrations (> 100 % enhancement over typical background values) and is suitable for detecting strong CH4 emissions, while the OE method is an optimal technique for diffuse sources (< 50 % enhancement), showing up to five times smaller fractional retrieval bias than the MF method. In addition, the impacts of aerosol scattering as a function of different parameters, such as surface albedo, CH4 concentration, aerosol optical depth, single scattering albedo and asymmetry parameter, are also discussed.

Yunxia Huang et al.

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Yunxia Huang et al.

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Short summary
As a greenhouse gas with strong global warming potential, atmospheric methane emissions have attracted a great deal of attention. However, accurate assessment of these emissions is challenging in the presence of atmospheric particulates called aerosols. We quantify the aerosol impact on methane quantification from airborne measurements using two techniques, one that has traditionally been used by the imaging spectroscopy community and the other commonly employed in trace gas remote sensing.
As a greenhouse gas with strong global warming potential, atmospheric methane emissions have...
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