Inversions of anthropogenic CO2 emissions using CTDAS-WRF over Greece in the East Mediterranean.

The Eastern Mediterranean experiences a rapid acceleration of climate warming mainly due to the continuous growth of greenhouse gases (GHG) in the atmosphere. Carbon dioxide (CO₂) is a key contributor to the human-induced greenhouse effect due to its long lifetime and high atmospheric concentrations. With its levels continuing to rise, the need to mitigate its emissions is of utmost importance. Towards this direction, atmospheric models are used to assess the influence of emissions on atmospheric composition. Emission fields used in models, called bottom-up emission inventories, provide information on the amounts and the distribution of the emitted pollutants. However, these emissions are coupled with large uncertainties at small spatiotemporal scales. Therefore, optimization of these emission estimates is needed to increase accuracy and thus support the identification of targets for emission reduction. In this study, we are optimizing the anthropogenic emissions of CO₂ over Greece by using the data assimilation system CTDAS-WRF (Carbon Tracker Data Assimilation Shell) that uses an Ensemble Kalman filter data assimilation method. As a forward model, we use WRF-CHEM with the GHG mechanism that allows passive tracer transport of CO₂. The sum of emissions from all different anthropogenic sectors from the CAMS anthropogenic emission inventory (CAMS-GLOB-ANT 5.3) is used as input to the model, in addition to biogenic (VPRM) and biomass burning emissions (FINN 2.5). The simulations are then compared to in-situ, FTIR and satellite observations of CO₂ that have been assimilated by CTDAS. The differences between the observations and the simulations are assumed to be only due to the uncertainty of the anthropogenic emissions. Therefore, our system is optimizing only these emissions. Preliminary results show the largest underestimates by the bottom-up inventories over the city of Athens.