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Published December 15, 2020 | Published
Journal Article Open

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

Abstract

As a greenhouse gas with strong global warming potential, atmospheric methane (CH₄) emissions have attracted a great deal of attention. Although remote sensing measurements can provide information about CH₄ sources and emissions, accurate retrieval is challenging due to the influence of atmospheric aerosol scattering. In this study, imaging spectroscopic measurements from the Airborne Visible/Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG) in the shortwave infrared are used to compare two retrieval techniques – the traditional matched filter (MF) method and the optimal estimation (OE) method, which is a popular approach for trace gas retrievals. Using a numerically efficient radiative transfer model with an exact single-scattering component and a two-stream multiple-scattering component, we also simulate AVIRIS-NG measurements for different scenarios and quantify the impact of aerosol scattering in the two retrieval schemes by including aerosols in the simulations but not in the retrievals. The presence of aerosols causes an underestimation of CH₄ in both the MF and OE retrievals; the biases increase with increasing surface albedo and aerosol optical depth (AOD). Aerosol types with high single-scattering albedo and low asymmetry parameter (such as water-soluble aerosols) induce large biases in the retrieval. When scattering effects are neglected, the MF method exhibits lower fractional retrieval bias compared to the OE method at high CH₄ concentrations (2–5 times typical background values) and is suitable for detecting strong CH₄ emissions. For an AOD value of 0.3, the fractional biases of the MF retrievals are between 1.3 % and 4.5 %, while the corresponding values for OE retrievals are in the 2.8 %–5.6 % range. On the other hand, the OE method is an optimal technique for diffuse sources (<1.5 times typical background values), showing up to 5 times smaller fractional retrieval bias (8.6 %) than the MF method (42.6 %) for the same AOD scenario. However, when aerosol scattering is significant, the OE method is superior since it provides a means to reduce biases by simultaneously retrieving AOD, surface albedo, and CH₄. The results indicate that, while the MF method is good for plume detection, the OE method should be employed to quantify CH₄ concentrations, especially in the presence of aerosol scattering.

Additional Information

© Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 20 Feb 2020 – Discussion started: 12 May 2020 – Revised: 14 Oct 2020 – Accepted: 16 Oct 2020 – Published: 15 Dec 2020. A portion of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). The authors gratefully acknowledge the insightful and constructive comments from the two anonymous reviewers, which improved the clarity and quality of the manuscript and elevated the significance of the work beyond the original expectation. Data availability: The code and data are available from the authors upon request. Author contributions: VN conceived the work, provided the radiative transfer and aerosol models, supervised YH, and assisted with manuscript preparation. YH designed and performed the retrievals, analyzed the results, and prepared the original manuscript. ZCZ contributed to retrieval setup and assisted with analysis of the results. PK provided valuable inputs into the science of CH4 remote sensing. YLY supervised YH and participated in the evaluation of the retrieval results and intercomparison. All listed authors contributed to the review and editing of this paper. The authors declare that there is no conflict of interest. This research has been supported by the NASA "Utilization of Airborne Visible/Infrared Imaging Spectrometer Next Generation Data from an Airborne Campaign in India" program (grant no. NNH16ZDA001N-AVRSNG) and the Jet Propulsion Laboratory Research and Technology Development program. PK was funded by the Japan Society for the Promotion of Science International Research Fellow Program. Review statement: This paper was edited by Jun Wang and reviewed by two anonymous referees.

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