Constraining CO2 fluxes over Europe using FLEXINVERT and in-situ measurements

Atmospheric carbon dioxide (CO2) is a significant greenhouse gas, and its concentration has increased by 51% compared to the pre-industrial value. Concerning its impact on the earths climate system, there is an urge to reduce CO2 emissions, hence mitigating global warming and climate change. This requires adequate knowledge of its source-sink distribution and quantification of the CO2 budget. Inverse modeling has emerged as an effective tool to constrain greenhouse gas (GHG) fluxes using the spatiotemporal pattern of atmospheric concentration measurements. In this regard, this study focuses on estimating CO2 fluxes over Europe using the Bayesian inverse modelling framework FLEXINVERT during the year 2021. In-situ CO2 concentrations were taken from various locations across Europe (World Data Centre for Greenhouse Gases, WDCGG) and data were averaged every 3 hours. The Lagrangian Particle Dispersion Model FLEXPART (FLEXible PARTicle) is employed to calculate the source-receptor relationship (SRR). The FLEXPART model has been run backward in time to trace back the particles (released from the locations of observation sites) for 10 days. Background CO2 concentrations are calculated using the sensitivity of concentration at the termination points from FLEXPART and the global 3D concentration from the FLEXible PARTicle-chemical transport model (FLEXPART-CTM). The uncertainty reduction, calculated from posterior and prior flux uncertainties, indicates how well the prior fluxes are optimized. In addition, longer backward simulations can be carried out to assess the impact of transport on background CO2 concentrations and the uncertainty reduction.