Measuring greenhouse gas emissions from space
Earth orbiting satellites with dedicated GHG-measuring instruments have become a priority for space agencies. By covering the entire globe with frequent revisits, they provide the potential to derive the consistent GHG budgets that are needed to understand the natural cycle of CO2 and CH4. They also provide the potential to monitor the effectiveness of climate policy by quantifying emissions from very intense and local point sources like industrial sites, through more diffuse areas emitting GHG like cities, up to national scales.
TRACE will study the design of a new generation of space-borne instruments concepts, to be launched in the next decade, suited to the global monitoring of GHG emissions. In particular, it will develop an end-to-end performance simulation platform going from instrumental and orbital parameters to the accuracy of GHG emission estimates. This platform will combine advanced radiative transfer inverse modeling (converting the satellite-measured radiances into atmospheric concentrations of GHG) and atmospheric transport inverse modeling (converting atmospheric concentration data into fluxes estimates). It will be used to assess the potential of existing and future satellite missions and constellations to monitor GHG emissions, and the contribution of ground-based networks, supporting the definition of optimal strategies for an operational greenhouse gas-monitoring infrastructure. This assessment will include the analysis of the performances and complementarity of different GHG satellite measurement options such as the chosen wavelength domain (thermal infrared or shortwave infrared), the satellite orbit (heliosynchronous vs. geostationary or tropical), the spatial resolution and the swath of the observations, as well as the more detailed spectrometer and radiometer instrument specifications.
This program will be addressed by integrating the knowledge from engineers and researchers at Thales Alenia Space who are responsible for designing new instruments, from LMD’s experts in radiative transfer inverse modeling and LSCE’s flux inversion experts.