Retrieval Method for Carbon Dioxide Using Infrared Laser Occultation from Low-Earth Orbit Satellites

As the dominant greenhouse gas, the spatiotemporal distribution of carbon dioxide (CO₂) concentration is a key parameter in global climate change research. Satellite remote sensing has become a crucial means for detecting CO₂ on a global scale. The infrared laser occultation technology employed by Low-Earth Orbit (LEO) satellites offers a novel technical approach for obtaining vertical profiles of atmospheric CO₂, capitalizing on its advantages of high vertical resolution, high precision, and strong global coverage capability. This paper systematically investigates the CO₂ retrieval method for this technology. The core principle involves a transmission-reception mode based on a LEO-LEO dual-satellite constellation. An infrared laser source onboard the transmitting satellite emits laser pulses at specific wavenumbers, which traverse the atmosphere and are captured by the receiving satellite. Leveraging the selective absorption characteristics of CO₂ in specific infrared bands and the principle of differential absorption, concentration retrieval is achieved. Firstly, an infrared laser occultation signal link model is constructed to optimize the selection of detection wavenumbers. Through simulation analysis of the sensitivity of CO₂ detection precision at different wavenumbers, an optimal wavenumber pair is determined. This wavenumber pair effectively mitigates interference from other atmospheric components, ensuring the specificity of the CO₂ absorption signal. Secondly, a complete retrieval calculation procedure is established. The dual-wavelength transmittance is calculated from the ratio of transmitted power to received signal strength, subsequently enabling the solution of the differential optical depth along the entire optical path. Utilizing the Abel integral transform, the differential optical depth is converted into the CO₂ differential absorption coefficient at the atmospheric path tangent point. Combined with the ideal gas law and the atmospheric quasi-static equation, concentration conversion is performed, ultimately yielding the vertical CO₂ concentration profile. The retrieval method proposed in this study effectively addresses the issues of low vertical resolution and uneven regional coverage inherent in traditional satellite remote sensing for CO₂ profile detection. It provides core algorithmic support for the engineering implementation of spaceborne infrared laser occultation CO₂ detection systems. The high-precision global CO₂ concentration data obtained can offer significant scientific data support for carbon source/sink assessment, climate change prediction, and related policy formulation.