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23 October 2018 Optical system of high-precision greenhouse gas imaging spectrometer
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The increase of atmospheric concentration of anthropogenic greenhouse gases(GHGs), primarily carbon dioxide(CO2) and methane(CH4), is concerned as a main cause of the global climate change. From the previous experiences in GHG detecting, satellite imaging spectral remote sensing provides the unique potentials in accuracy, precision, coverage, temporal sampling and spectral resolution, having been developing as an effective and efficient means for monitoring GHGs’ accumulation and emission in the atmosphere. This paper reports a promising optical design of very high spectral resolution imaging spectrometer on LEO satellite with a swath of over 100 km and a spatial resolution of less than 3 km. Its specification satisfies with the requirement of high column concentration retrieval precision of 1ppm for CO2 and 9ppb for CH4 within four absorption bands (755-765nm, 1595-1625nm, 2040-2080nm and 2275-2325nm). Above all, up to 23000 spectral resolving power hints us the superiorities of immersed grating in increasing resolution but decreasing volume. A holographic flat plane grating is directly etched on a wedge prism, operating in reflective near-Littrow condition, having optimized diffraction efficiency of over 85%. Additional prisms are introduced to correct the smile distortion of the slit image produced by the grism. This method is crucial for the fidelity of the instrument spectral response function (ISRF) and data processing. Moreover, to desensitize the instrument to the polarization state of the income radiation, four polarization scramblers are adopted after the shared fore-optics, specially designed for each bands. Thanks to the scramblers, the predicted polarization sensitivity is lower than 1% at worst.
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Qiao Pan and Weimin Shen "Optical system of high-precision greenhouse gas imaging spectrometer", Proc. SPIE 10781, Earth Observing Missions and Sensors: Development, Implementation, and Characterization V, 107810D (23 October 2018);

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