Assessing Greenhouse Gas Monitoring Capabilities Using SolAtmos End-to-End Simulator: Application to the Uvsq-Sat NG Mission

Author:

Clavier Cannelle12,Meftah Mustapha1ORCID,Sarkissian Alain1ORCID,Romand Frédéric2,Hembise Fanton d’Andon Odile2,Mangin Antoine2,Bekki Slimane1,Dahoo Pierre-Richard1ORCID,Galopeau Patrick1,Lefèvre Franck1ORCID,Hauchecorne Alain1ORCID,Keckhut Philippe1

Affiliation:

1. LATMOS, Université de Versailles Saint-Quentin-en-Yvelines, Université Paris-Saclay, Sorbonne Université, Centre National de la Recherche Scientifique (CNRS), 11 Boulevard d’Alembert, 78280 Guyancourt, France

2. ACRI-ST—CERGA, 10 Avenue Nicolas Copernic, 06130 Grasse, France

Abstract

Monitoring atmospheric concentrations of greenhouse gases (GHGs) like carbon dioxide and methane in near real time and with good spatial resolution is crucial for enhancing our understanding of the sources and sinks of these gases. A novel approach can be proposed using a constellation of small satellites equipped with miniaturized spectrometers having a spectral resolution of a few nanometers. The objective of this study is to describe expected results that can be obtained with a single satellite named Uvsq-Sat NG. The SolAtmos end-to-end simulator and its three tools (IRIS, OptiSpectra, and GHGRetrieval) were developed to evaluate the performance of the spectrometer of the Uvsq-Sat NG mission, which focuses on measuring the main GHGs. The IRIS tool was implemented to provide Top-Of-Atmosphere (TOA) spectral radiances. Four scenes were analyzed (pine forest, deciduous forest, ocean, snow) combined with different aerosol types (continental, desert, maritime, urban). Simulated radiance spectra were calculated based on the wavelength ranges of the Uvsq-Sat NG, which spans from 1200 to 2000 nm. The OptiSpectra tool was used to determine optimal observational settings for the spectrometer, including Signal-to-Noise Ratio (SNR) and integration time. Data derived from IRIS and OptiSpectra served as input for our GHGRetrieval simulation tool, developed to provide greenhouse gas concentrations. The Levenberg–Marquardt algorithm was applied iteratively to fine-tune gas concentrations and model inputs, aligning observed transmittance functions with simulated ones under given environmental conditions. To estimate gas concentrations (CO2, CH4, O2, H2O) and their uncertainties, the Monte Carlo method was used. Based on this analysis, this study demonstrates that a miniaturized spectrometer onboard Uvsq-Sat NG is capable of observing different scenes by adjusting its integration time according to the wavelength. The expected precision for each measurement is of the order of a few ppm for carbon dioxide and less than 25 ppb for methane.

Funder

Université de Versailles Saint-Quentin-en-Yvelines

Académie de Versailles

Communauté d’Agglomération de Saint-Quentin-en-Yvelines

Centre Paris-Saclay des Sciences Spatiales

Publisher

MDPI AG

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