High Resolution CO2 Simulation for Detecting Emission Hotspots Signal in GOSAT XCO2 Data

Thursday, 18 December 2014
Rajesh Janardanan Achari1, Johannes W Kaiser2, Shamil S Maksyutov1, Akihiko Ito1, Alexander Ganshin3,4, Ruslan Zhuravlev3,4 and Yukio Yoshida1, (1)CGER-NIES, Tsukuba, Japan, (2)Max Planck Institute for Chemistry, Mainz, Germany, (3)Tomsk State University, Tomsk, Russia, (4)Central Aerological Observatory, Moscow, Russia
Emissions due to combustion of fossil fuel and biomass are two major sources of atmospheric carbon dioxide. The trace gases emitted by biomass burning have a significant influence on the atmosphere which currently accounts for ~25% of the annual anthropogenic emission of CO2into the atmosphere. Also some of the world's most carbon-dense ecosystems like South America and Africa are increasingly susceptible to fire.

Though observing atmospheric greenhouse gas dry air mole fractions from space is an approach in practice, the problem of delineating the contribution from the flux arising from different sources has always been a matter of interest. Here we demonstrate the capability of a space-borne CO2 observational platform (Greenhouse gas Observing SATellite, GOSAT) to detect emissions of CO2 due to biomass burning. We made an attempt to detect fire emission signal of CO2 in GOSAT observed total column dry air mole fractions of CO2 (XCO2) for a period June 2009 through December 2012. We performed Lagrangian time inverted simulation (trajectory between 2-3 days) of CO2 transport using FLEXPART for GOSAT observation locations using high resolution (0.1 degree) biomass burning (GFAS V1.1) fluxes. The resulting total column mixing ratios of CO2 (ΔXCO2,model) were grouped into 0.2 ppm bins over spatial regions of 10x10 degree. The result was compared to anomalies of GOSAT XCO2, calculated as ΔXCO2,obs=XCO2,obs-local background (omitting influence from other regimes of emission), collectively for the analysis period and for large continental regions where these detected signals predominate. GOSAT data showed good agreement with modeled ΔXCO2 till about 0.9 ppm (for example regression slope of 0.989 for African continent up to 0.7 ppm) , beyond this, the number of observations with higher ΔXCO2drops and hence poor correspondence to model values.

Our analysis points towards the potential of dedicated greenhouse gas observing satellites providing larger number observations like the OCO-2 which can better observe narrow plumes downwind of CO2 emission hotspots, resulting in larger number of high concentration observations.