Divergence between eddy covariance fluxes and CO2 emission inventory of Vienna only partly explained by remote-sensed based vegetation predictors

Accurate quantification of urban carbon dioxide (CO 2 ) emissions is essential for evaluating local mitigation strategies. Yet discrepancies can occur when comparing city emission inventories with flux estimates from measurement-based methods such as eddy covariance (EC). This study investigated whether urban vegetation can explain such inventory-flux discrepancies in Vienna, Austria. Residuals between downscaled, temporally resolved inventories and tall tower CO 2 flux measurements generally exhibited a temporal pattern following seasonal and diel dynamics in vegetation CO 2 uptake. To evaluate this potential influence, correlations of inventory-flux residuals with satellite-derived Leaf Area Index (LAI) and Fraction of Absorbed Photosynthetic Active Radiation (FAPAR) within flux footprints, as well as meteorological variables, were tested. Results revealed positive correlations with daytime data ( ρ = 0.74 for LAI vs. relative residual), and negative correlations with nighttime data ( ρ = −0.65 for LAI vs. absolute residual), suggesting a role of biogenic processes in urban CO 2 fluxes, driven by daytime plant net assimilation and nighttime plant and soil respiration. Subsequently, a first estimate of net ecosystem exchange (NEE) was quantified using a semi-empirical urban vegetation flux model and directly compared with the observed residuals. Monte Carlo simulations ( n = 3000) indicate that NEE remains comparatively small, resulting in only a marginally improved agreement between emission inventory and EC observations (R 2 = 0.361 without NEE; R 2 = 0.361–0.390). Although diurnal and seasonal variations in biogenic fluxes are noticeable, they are too small to reconcile the systematic divergence between EC observations and the downscaled inventory, pointing to additional sources of uncertainty.