Sensitivity to the sources of uncertainties in the modeling of atmospheric CO 2 concentration within and in the vicinity of Paris

Lian, Jinghui; Bréon, François-Marie; Broquet, Grégoire; Lauvaux, Thomas; Zheng, Bo; Ramonet, Michel; Xueref-Remy, Irène; Kotthaus, Simone; Haeffelin, Martial; Ciais, Philippe

page10708The top-down atmospheric inversion method that couples atmospheric COinline-formula2 observations with an atmospheric transport model has been used extensively to quantify COinline-formula2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled COinline-formula2 that are of different origins than the targeted COinline-formula2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of 1-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations, and COinline-formula2 boundary conditions. The simulated COinline-formula2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime model–data misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the COinline-formula2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the COinline-formula2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated COinline-formula2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Nevertheless, our results demonstrate the potential of our optimal COinline-formula2 atmospheric modeling system to be utilized in atmospheric inversions of COinline-formula2 emissions over the Paris metropolitan area. We evaluated the model performances in terms of wind, vertical mixing, and COinline-formula2 model–data mismatches, and we developed a filtering algorithm for outliers due to local contamination and unfavorable meteorological conditions. Analysis of model–data misfit indicates that future inversions at the mesoscale should only use afternoon urban COinline-formula2 measurements in winter and suburban measurements in summer. Finally, we determined that errors related to COinline-formula2 boundary conditions can be overcome by including distant background observations to constrain the boundary inflow or by assimilating COinline-formula2 gradients of upwind–downwind stations rather than by assimilating absolute COinline-formula2 concentrations.

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Lian, Jinghui / Bréon, François-Marie / Broquet, Grégoire / et al: Sensitivity to the sources of uncertainties in the modeling of atmospheric CO2 concentration within and in the vicinity of Paris. 2021. Copernicus Publications.

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