Issue |
EPJ Web Conf.
Volume 237, 2020
The 29th International Laser Radar Conference (ILRC 29)
|
|
---|---|---|
Article Number | 01004 | |
Number of page(s) | 4 | |
Section | Space Lidars | |
DOI | https://doi.org/10.1051/epjconf/202023701004 | |
Published online | 07 July 2020 |
https://doi.org/10.1051/epjconf/202023701004
CO2 Profiling by Space-Borne Raman Lidar
1 Scuola di Ingegneria, Università della Basilicata, Potenza, Italy
2 Institut fuer Physik und Meteorologie, Universitaet Hohenheim, Stuttgart, Germany
3 ISMAR,CNR, Roma, Italy
* Email: paolo.digirolamo@unibas.it
Published online: 7 July 2020
As clearly reported in the IPCC fifth Assessment Report, CO2 emissions are already producing destructive effects to the plant ecosystem through the alteration of soil-atmosphere interaction mechanisms.
Although the space and ground network for CO2 monitoring has regularly expanded over the past 50 years, it does not guarantee the necessary spatial and temporal resolution needed for a quantitative analysis of sources and sinks. For the purpose of estimating forests’ carbon capturing capabilities, accurate measurements of CO2 gradients between the forest floor and the top of the canopy, which ultimately translates into the capability to measure CO2 concentration profiles. Space sensors provide CO2 measurements above forest canopies, which do not allow to properly estimate Gross Primary Production (GPP).
These observational gaps could be addressed with an active remote sensing system in space based on the vibrational Raman lidar technique. CO2 profile measurements are possible, together with simultaneous measurements of the temperature and water vapour mixing ratio profile and a variety of additional variables (aerosol backscatter profile, aerosol extinction profile, PBL depth, cloud top and base heights, cloud optical depth). An assessment of the expected performance of the system has been performed based on the application of an analytical simulation model developed at University of Basilicata.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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