Abstract. Methane is the second most important anthropogenic greenhouse gas in the Earth's atmosphere. Reducing methane emissions is consequently an important element in limiting the global temperature increase below 2 °C compared to preindustrial times. Therefore, a good knowledge of source strengths and source locations is required. Anthropogenic methane emissions often originate from point sources or small areal sources, such as fugitive emissions at oil and gas production sites or landfills. 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, especially in areas with many potential emission sources.To extract methane column enhancement information from spectra recorded with the AVIRIS-NG instrument, different retrieval algorithms have been used, e.g. the matched filter (MF) or the Iterative Maximum A Posteriori DOAS (IMAP-DOAS) retrieval. The WFM-DOAS algorithm, successfully applied to AVIRIS-NG data in this study, fills a gap between those retrieval approaches by being a fast, non-iterative algorithm based on a first order approximation of the Lambert-Beer law, which calculates the change in gas concentrations from deviations from one background radiative transfer calculation using precalculated weighting functions specific to the state of the atmosphere during the overflight. This allows the fast quantitative processing of large data sets. Although developed for high spectral resolution measurements from satellite instruments such as SCIAMACHY, TROPOMI and the MAMAP airborne sensor, the algorithm can be applied well to lower spectral resolution AVIRIS-NG measurements. The data set examined here was recorded in Canada over different gas and coal extraction sites as part of the larger Arctic Boreal Vulnerability Experiment (ABoVE) Airborne Campaign in 2017.The noise of the retrieved CH₄ imagery over bright surfaces (> 1 μW 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 (−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.We detected several methane plumes in the AVIRIS-NG images recorded during the ABoVE Airborne Campaign. For four of those plumes, the emissions were estimated using a simple cross sectional flux method. The retrieved fluxes originated from well pads and cold vents and ranged between (89 ± 46) kg (CH₄) h⁻¹ and (141 ± 87) kg (CH₄) h⁻¹. The wind uncertainty was a significant source of uncertainty for all plumes, followed by the single pixel retrieval noise and the uncertainty due to atmospheric variability. For one plume the wind was too low to estimate a trustworthy emission rate, although a plume was visible.

中文翻译：

---

使用WFM-DOAS检索AVIRIS-NG高光谱数据对CH ₄羽流进行检测和定量

摘要。甲烷是地球大气中第二重要的人为温室气体。因此，与工业化前相比，减少甲烷排放量是限制全球温度升高低于2°C的重要因素。因此，需要对源的强度和源的位置有充分的了解。人为甲烷排放通常来自点源或小型区域源，例如油气生产基地或垃圾填埋场的逃逸排放。机载遥感仪器，例如具有仪表级成像功能的下一代机载可见红外成像光谱仪（AVIRIS-NG），能够产生有关甲烷源的位置和大小的信息，尤其是在具有许多潜在排放源的地区。为了从用AVIRIS-NG仪器记录的光谱中提取甲烷柱增强信息，已使用了不同的检索算法，例如，匹配过滤器（MF）或迭代最大后验DOAS（IMAP-DOAS）检索。WFM-DOAS算法已成功应用于本研究中的AVIRIS-NG数据，它是一种快速的非迭代算法，该算法基于Lambert-Beer律的一阶近似值填补了这些检索方法之间的空白，该算法可计算变化通过使用特定于飞越过程中大气状态的预先计算的加权函数，从一个背景辐射传输计算得出的偏差中计算气体浓度。这样可以对大型数据集进行快速定量处理。尽管针对SCIAMACHY，TROPOMI和MAMAP机载传感器等卫星仪器的高光谱分辨率测量而开发，但该算法可以很好地应用于较低光谱分辨率的AVIRIS-NG测量。作为2017年更大的北极北方脆弱性试验（ABoVE）机载战役的一部分，此处检查的数据集在加拿大的不同天然气和煤炭开采地点进行了记录。当在2300 nm附近安装强吸收线时，在明亮表面上（在2140 nm处> 1μWcm ^-2  nm ^-1  sr ^-1）上的_4张图像通常占CH ₄背景总色谱柱的±2.3％，但可能超过±5对于较暗的表面（在2140 nm处为-2 nm ^-1  sr ^-1），％。此外，由于WFM-DOAS检索中的假设，最坏情况下的大规模偏差估计为±5.4％。实施辐射和拟合质量滤镜以排除进一步分析中最不确定的结果，这主要是由于深色表面或表面光谱反射结构类似于CH ₄的表面在AVIRIS-NG仪器的光谱分辨率下具有吸收特性。我们在ABoVE空降战役期间记录的AVIRIS-NG图像中检测到了几个甲烷羽流。对于这些羽流中的四个，使用简单的截面通量方法估算了排放量。回收的通量来自井垫和通风口，范围在（89±46）kg（CH ₄）h ^-1和（141±87）kg（CH ₄）h ^-1之间。风的不确定性是所有羽流不确定性的重要来源，其次是单个像素检索噪声以及由于大气变化而引起的不确定性。尽管可见烟羽，但对于一根烟羽而言，风太低，无法估计可信赖的排放率。