Evaluating the effects of surface properties on methane retrievals using a synthetic airborne visible/infrared imaging spectrometer next generation (AVIRIS-NG) image

Abstract

Atmospheric methane has been increasing since the beginning of the industrial era due to anthropogenic emissions. Methane has many sources, both natural and anthropogenic, and there continues to be considerable uncertainty regarding the contribution of each source to the total methane budget. Thus, remote sensing techniques for monitoring and measuring methane emissions are of increasing interest. Recently, the Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) has proven to be a valuable instrument for quantitative mapping of methane plumes. Despite this success, uncertainties remain regarding the sensitivity of the retrieval algorithms, including the influence of albedo and the impact of surfaces that may cause spurious signals. To explore these sensitivities, we applied the Iterative Maximum a Posterior Differential Optical Absorption Spectroscopy (IMAP-DOAS) methane retrieval algorithm to synthetic reflected radiances with variable methane concentrations, albedo, surface cover, and aerosols. This allowed for characterizing retrieval performance, including potential sensitivity to variable surfaces, low albedo surfaces, and surfaces known to cause spurious signals. We found that dark surfaces (below 0.10 μWcm−2nm−1sr−1 at 2139 nm), such as water and green vegetation, and materials with absorption features in the 2200–2400 nm range caused higher errors in retrieval results. We also found that aerosols have little influence on retrievals in the SWIR. Results from the synthetic scene are consistent with those observed in IMAP-DOAS retrievals for real AVIRIS-NG scenes containing methane plumes from a waste dairy lagoon and coal mine ventilation shafts. Understanding the effect of surface properties on methane retrievals is important given the increased use of AVIRIS-NG to map gas plumes from a diversity of sources over variable landscapes.