Urban atmospheric CO ₂ plumes from space – Part 2: Representation of fine-scale structures

<jats:p>Abstract. Quantifying urban CO2 emissions using spaceborne total column observations requires atmospheric transport models capable of resolving fine-scale spatial and temporal variability across metropolitan areas. Using the Grand Paris region as a testbed, we evaluated the sensitivity of simulated CO2 fields to spatial resolution and model physics within the Weather Research and Forecasting model coupled to a high-resolution fossil fuel emissions inventory. Simulations were conducted at mesoscale (900 m) and Large-Eddy Simulation (LES) resolutions (300 m and 100 m), and evaluated against dense urban CO2 observations from the Paris Picarro and rooftop mid-cost sensors network. Horizontal resolution strongly affects plume morphology: high-resolution simulations produce sharper gradients, higher peak mixing ratios and more realistic temporal variability. LES simulations capture localized enhancements and intra-urban variability more accurately than the 900 m mesoscale run, which systematically underestimates spatial contrasts by a factor of 2–3. Aggregation experiments indicate that averaging LES simulations to 900 m significantly modifies plume magnitudes and spatial gradients. Domain-mean relative errors for near-surface CO2 reach 29–34 % in winter and 59–61 % in summer, while column-integrated XCO2 shows 21–22 % errors in winter and 58–59 % in summer, with maxima exceeding 70 %. While LES improves the representation of urban CO2 variability, it increases sensitivity to local wind and inventory uncertainties, meaning misplaced point sources can cause large local biases. These findings emphasize the need for inversion frameworks able to incorporate scale-dependent transport and inventory uncertainties to ensure unbiased top-down emission estimates and accurate spatial attribution within city domains.</jats:p>