Monitoring urban atmospheric CO2 plumes from space: sensitivity to urban physics and scale effects over Paris

Quantifying urban CO₂ emissions from space can be approached using different methodologies, including direct plume-based analyses, but combining satellite observations with atmospheric transport models requires the ability to realistically reproduce fine-scale spatial gradients over cities. Using the Grand Paris area as a testbed, we investigate the sensitivity of simulated near-surface CO₂ concentrations to urban physics parameterization and horizontal resolution within the WRF-Chem modeling framework coupled to a high-resolution fossil fuel emission inventory. At mesoscale resolution (900 m), a hierarchy of urban representations ranging from simulations without urban physics to multi-layer urban canopy models is evaluated, showing that the Building Energy Model (BEM) provides the most physically consistent simulation of surface energy fluxes, boundary-layer development, and near-surface CO₂ variability. Building on this configuration, we compare mesoscale simulations with Large-Eddy Simulation (LES) runs at 300 m and 100 m resolution. Model results are evaluated against dense urban CO₂ observations from the high-precision Picarro network, a complementary mid-cost sensor network from ICOS-Cities, and surface sensible and latent heat flux observations from the ICOS ETC Level-2 fluxes data product. An extensive urban observation network including wind lidars and ceilometers from Urbisphere project provides an exceptional constraint for the evaluation of boundary-layer structure and vertical mixing at fine scales. The LES simulations substantially enhance the representation of spatial heterogeneity and localized CO₂ enhancements associated with major emission sources, which are smoothed or underestimated at mesoscale resolution. However, increased resolution also amplifies sensitivity to local wind fields and emission inventory uncertainties. These results highlight that both urban physics and model resolution critically shape the ability of transport models to reproduce observed urban CO₂ gradients.