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Methane is a greenhouse gas that has a global warming potential (GWP) of 25 relative to carbon dioxide (CO2). In 2021 an estimated 36 billion-tons of CO2 and 640 million-tons (16 billion-tons GWP equivalent) of methane were emitted. Emission consists of anthropogenic and naturally occurring sources with natural emissions accounting for 35-50% of total emissions. Natural emission caused by decaying organic matter in wetlands and melting tundra, increase as global temperatures rise, thus creating a positive feedback loop increasing their significance and exacerbating global warming. Effective mapping of natural emissions requires high field-of-view (FOV) global satellite coverage. Detection of small weak sources and mapping of larger plume nonuniformity requires a small ground-sample-distance (GSD). Methane has several fine spectral features in the SWIR allowing for effective detection and quantification. In this paper we design an imaging spectrometer for single pixel methane quantification using a tradeoff study between spectral resolution and sensor SNR. Increases in spectral resolution increase spectral separability of methane from other gases, while decreasing SNR. Increases in GSD increase SNR and FOV, while reducing spatial resolution. Environmental factors such as water absorption and ground reflectance further affect performance. Retrieval performance was tested with simulated noisy at-aperture radiance spectra using a dry vegetation surface, atmospheres with varying water and methane concentrations, and the developed sensor model. Gas concentrations were retrieved by finding the atmosphere providing the smoothest retrieved reflectance. Retrieval errors were studied to find the optimal sensor parameters. Several future and current imaging spectrometers were used for comparison.
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