17:15 〜 19:15
[ACG41-P07] Preparation for XCO2 Retrieval from High-Resolution Drone and Nano-Satellite Observations
キーワード：XCO2、HISUI (Hyperspectral Imager SUIte)、Retrieval
Carbon dioxide (CO2) is one of the main drivers of global warming, and its reduction is essential for mitigating climate change. Under the Paris Agreement, governments are obligated to measure and report national CO2 emissions. Therefore, many countries have enacted laws requiring companies to disclose their CO2 emissions. However, traditional methods based on fuel consumption and electricity usage may carry the risk of underreporting emissions. Localized satellite-based observations of CO2 column density (XCO2) enable us to perform more accurate and real-time verification of CO2 emissions. Recently, the hyperspectral sensor PRISMA operated by the Italian Space Agency (ASI), has successfully achieved high-spatial-resolution (~30 m) XCO2 observations (Cusworth et al., 2023). Additionally, private companies such as GHGSat also accelerate local-scale XCO2 observations.
Recently, a new demonstration project to develop a high-sensitivity, compact, and multi-wavelength infrared sensor has started under the economic security critical technology development program (K-Program) framework. The target of that project is to realize infrared spectroscopy with a high-wavelength resolution by the Liquid Crystal Fabry-Perot Etalon (LCFP) onboard the drones and micro-satellites for more precise quantification of XCO2 with facility-scale high-resolution. In parallel with the development of the sensor, in this study, we are preparing a retrieval analysis of XCO2 using existing observation data.
We derived XCO2 from CO2 absorption spectra at 2 μm obtained from the HISUI hyperspectral sensor onboard the International Space Station. We employed two approaches for XCO2 retrieval: the CIBR (Continuum Interpolated Band Ratio) technique (Spinetti et al., 2008) and the least-square fitting technique using the LBL (Line-by-Line) radiative transfer calculation. The CIBR indicates the relative depth of CO2 absorption lines. XCO2 is derived from the CIBR values using a predetermined conversion equation, making the analysis setup simple and quick. The latter LBL method often allows for more detailed analysis, including vertically resolving the CO2 abundance profile, but at a higher computational cost.
The CIBR analysis successfully retrieved reasonable XCO2 (~420 ppm) under certain conditions and locations. The CIBR-based approach demonstrated extremely low computational cost and was well-suited for detecting high-concentration CO2 plumes. However, identifying small-scale CO2 plumes and estimating background XCO2 required additional background corrections, particularly for water vapor and surface albedo. We will compare these CIBR-based results with the retrieval results using the LBL radiative transfer calculations. In addition, we will present a quantitative error analysis of water vapor absorption interference.
Recently, a new demonstration project to develop a high-sensitivity, compact, and multi-wavelength infrared sensor has started under the economic security critical technology development program (K-Program) framework. The target of that project is to realize infrared spectroscopy with a high-wavelength resolution by the Liquid Crystal Fabry-Perot Etalon (LCFP) onboard the drones and micro-satellites for more precise quantification of XCO2 with facility-scale high-resolution. In parallel with the development of the sensor, in this study, we are preparing a retrieval analysis of XCO2 using existing observation data.
We derived XCO2 from CO2 absorption spectra at 2 μm obtained from the HISUI hyperspectral sensor onboard the International Space Station. We employed two approaches for XCO2 retrieval: the CIBR (Continuum Interpolated Band Ratio) technique (Spinetti et al., 2008) and the least-square fitting technique using the LBL (Line-by-Line) radiative transfer calculation. The CIBR indicates the relative depth of CO2 absorption lines. XCO2 is derived from the CIBR values using a predetermined conversion equation, making the analysis setup simple and quick. The latter LBL method often allows for more detailed analysis, including vertically resolving the CO2 abundance profile, but at a higher computational cost.
The CIBR analysis successfully retrieved reasonable XCO2 (~420 ppm) under certain conditions and locations. The CIBR-based approach demonstrated extremely low computational cost and was well-suited for detecting high-concentration CO2 plumes. However, identifying small-scale CO2 plumes and estimating background XCO2 required additional background corrections, particularly for water vapor and surface albedo. We will compare these CIBR-based results with the retrieval results using the LBL radiative transfer calculations. In addition, we will present a quantitative error analysis of water vapor absorption interference.