(Towards) anthropogenic CO2 emissions through inverse modelling Frédéric Chevallier LSCE, France The PIs of the TCCON, as listed on https://tccon-wiki.caltech.edu/

(Towards) anthropogenic CO2 emissions through inverse modelling Frédéric Chevallier LSCE, France The PIs of the TCCON, as listed on https://tccon-wiki.caltech.edu/

Outline On the maturity of CO2 inverse modeling Development of CO2 observation systems about the anthropogenic emissions

CO2 observations Surface air-sample measurements Retrievals of CO2 partial column Satellites: AIRS, IASI, TES, … [not demonstrated with real data] Retrievals of CO2 total column Satellites: SCIAMACHY, GOSAT Surface: TCCON Aircrafts

Atmospheric inverse modeling Infer carbon surface fluxes from their measured impact on carbon concentrations CO2 surface fluxes Observations

Atmospheric inverse modeling Infer carbon surface fluxes from their measured impact on carbon concentrations Technology borrowed from Numerical Weather Prediction data assimilation systems CO2 surface fluxes Observations

Atmospheric inversions Pros Directly provides uncertainty estimates Exhaustive, effective and not-intrusive approach NRT possible Refines prior inventories – ultimate estimation Cons Heavy, sophisticated numerical technology Potentially expensive network deployment Shall involve prior information Involves chemistry-transport models Sectorization not straightforward

Are inversion statistics reliable? In its most rigorous form, the inversion problem is expressed by Bayes’ theorem The output of an inversion is not a deterministic field but a multidimensional probability density function How reliable are the second order moments of the pdf (variances and covariances)?

TCCON inversion vs. air-sample inversion Aggregation of weekly/3.75ox2.5o results at the annual sub-continental scale WDCGG, NOAA, RAMCES, CarboEurope databases Chevallier et al., submitted to GRL

Evaluating inversion error statistics at local scale Use air-sample inversion Compare with y = TCCON measurements at 14 stations E[ ( Hxb – y ) ( Hxb – y )T ] = HBHT+R E[ ( Hxa – y ) ( Hxa – y )T ] = HAHT+R

Zooming CO2 inversion is a mature field, even though all scientific questions have not been answered Increase the resolution of the inverse systems of the observation systems

Mesoscale inverse modelling Europe at 50km resolution using the CHIMERE model Summer 2006 15 CO2 stations of the CarboEurope-Integrated Project Comparison with spatial averages of gap-filled CarboEurope flux measurements L4 product Broquet et al. 2011 Obs. Inversion Prior

Towards the inversion of the anthropogenic component (1/2) Development of regional networks in Paris, Los Angeles, Indianapolis, … Indianapolis-Flux CO2-MegaParis Davis et al., 2010

Towards the inversion of the anthropogenic component (2/2) Development of regional networks in Paris, Los Angeles, Indianapolis, … Strategies Add expert knowledge: prescribe some of the space-time pattern of the anthropogenic emissions and adjust a few degrees of freedom only Aggregation errors to be taken into account Add measurements: tracers of anthropogenic emissions (CO, NOx, 14CO2, …) together with CO2 Model errors (chemistry) to be taken into account

Imaging the anthropogenic plumes from space (1/2) CarbonSat is a satellite project which is being developed by ESA, as a candidate for the Earth Explorer Opportunity Mission to be launched in 2018 earliest Measures the atmospheric concentrations of CO2 and CH4 with high spatial resolution (2 x 2 km2) and good spatial coverage (500 km swath width) Focus on hot-spot sources, like power plants Could be operated as a constellation

Imaging the anthropogenic plumes from space (2/2) Accurate wind knowledge is key to the success of the mission

Towards anthropogenic CO2 emissions through inverse modelling What EO/GMES techniques have been used to verify emissions inventories? CO2 inverse modelling systems are being developed for this purpose What key data is needed for this verification? Dense observations around the target regions, of CO2 and of tracers of anthropogenic activity What are the levels of uncertainty in datasets? Depends on observation density - can be properly estimated What future developments/enhancements are possible? The main developments expected are on the observation side Can EO/GMES techniques replace traditional emissions inventory estimates (which use statistical data)? Inverse modelling refines prior inventories but do not replace them

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