Detection and quantification of CH4 plumes using the WFM-DOAS retrieval on AVIRIS-NG hyperspectral data

Methane is the second most important anthropogenic greenhouse gas in the Earth's atmosphere. To effectively reduce these emissions, a good knowledge of source locations and strengths is required. Airborne remote sensing instruments such as the Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) with meter-scale imaging capabilities are able to yield information about the locations and magnitudes of methane sources. In this study, we successfully applied the weighting function modified differential optical absorption spectroscopy (WFM-DOAS) algorithm to AVIRIS-NG data measured in Canada and the Four Corners region. The WFM-DOAS retrieval is conceptually located between the statistical matched filter (MF) and the optimal-estimation-based iterative maximum a posteriori DOAS (IMAP-DOAS) retrieval algorithm, both of which were already applied successfully to AVIRIS-NG data. The WFM-DOAS algorithm is based on a first order Taylor series approximation of the Lambert-Beer law using only one precalculated radiative transfer calculation per scene. This yields the fast quantitative processing of large data sets. We detected several methane plumes in the AVIRIS-NG images recorded during the Arctic-Boreal Vulnerability Experiment (ABoVE) Airborne Campaign and successfully retrieved a coal mine ventilation shaft plume observed during the Four Corners measurement campaign. The comparison between IMAP-DOAS, MF, and WFM-DOAS showed good agreement for the coal mine ventilation shaft plume. An additional comparison between MF and WFM-DOAS for a subset of plumes showed good agreement for one plume and some differences for the others. For five plumes, the emissions were estimated using a simple cross-sectional flux method. The retrieved fluxes originated from well pads, cold vents, and a coal mine ventilation shaft and ranged between (155 +/- 71) kg (CH4) h(-1) and (1220 +/- 450) kg (CH4) h(-1). The wind velocity was a significant source of uncertainty in all plumes, followed by the single pixel retrieval noise and the uncertainty due to atmospheric variability. The noise of the retrieved CH4 imagery over bright surfaces (>1 mu W cm(-2) nm(-1) sr(-1) at 2140 nm) was typically +/- 2.3 % of the background total column of CH4 when fitting strong absorption lines around 2300 nm but could reach over +/- 5 % for darker surfaces (< 0.3 W mu cm(-2) nm(-1) sr(-1) at 2140 nm). Additionally, a worst case large-scale bias due to the assumptions made in the WFM-DOAS retrieval was estimated to be +/- 5.4 %. Radiance and fit quality filters were implemented to exclude the most uncertain results from further analysis mostly due to either dark surfaces or surfaces where the surface spectral reflection structures are similar to CH4 absorption features at the spectral resolution of the AVIRIS-NG instrument.