Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS.

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Airborne atmospheric carbon dioxide measurement using 1.5 µm laser double-pulse IPDA lidar over a desert area.

An integrated path differential absorption (IPDA) lidar can accurately measure regional C O 2 weighted column average concentrations (X C O 2), which are crucial for understanding the carbon cycle in climate change studies. To verify the performance and data inversion methods of space-borne IPDA lidar, in July 2021, we conducted an airborne lidar validation experiment in Dunhuang, Gansu Province, China. An aircraft was equipped with a lidar system developed to measure X C O 2 and an in situ greenhouse gas analyzer (GGA). To minimize measurement errors, energy monitoring was optimized. The system bias error of the DAOD was determined by changing the laser output mode from the off/on to the on/on mode. The X C O 2 inversion results obtained through comparing the schemes of averaging signals before "log (logarithm)" and averaging after "log" indicate that the former performs better. The IPDA lidar measured X C O 2 over the validation site at 405.57 ppm, and both the IPDA lidar and GGA measured sudden changes in the C O 2 concentration. The assimilation data showed a similar trend according to the altitude to the data measured by the in situ instrument. A comparison of the mean X C O 2 derived from the GGA results and assimilation data with the IPDA lidar measurements showed biases of 0.80 and 1.12 ppm, respectively.