Interpreting atmospheric CO₂ observations over cities from space requires transport models that accurately link concentration patterns to surface fluxes, making realistic urban boundary-layer representation critical. This study examines how urban physics parameterizations influence boundary-layer dynamics and near-surface CO₂ mixing ratios over the Paris metropolitan area under winter and summer conditions. Using the Weather Research and Forecasting (WRF) model, four configurations are evaluated: no-urban representation (No_URB), a single-layer urban canopy model (SLUCM), and two multi-layer schemes (BEP: Building Effect Parameterization and BEM: Building Energy Model). Model outputs are assessed against surface energy flux observations, turbulence measurements, planetary boundary layer height (PBLH), and near-surface CO₂ mixing ratios from dense urban and suburban monitoring networks, alongside wind, temperature and humidity. Urban physics exert strong control on wintertime boundary-layer structure and CO₂ variability, with scheme differences driven primarily by sensible heat flux, friction velocity, and turbulent kinetic energy, producing large contrasts in PBLH and CO₂ accumulation. In summer, PBLH diurnal patterns converge across schemes, with a characteristic plateau during active convection, and CO₂ variability becomes dominated by convective mixing. BEM provides the most physically consistent representation across both seasons. Sensitivity tests with three planetary boundary layer schemes show that Mellor–Yamada–Janjic coupled with BEM best reproduces wintertime CO₂, capturing realistic nighttime accumulation and daytime mixing, while Yonsei University and BouLac exhibit systematic biases. These results demonstrate that realistic urban physics combined with an appropriate turbulence scheme are essential for physically consistent urban CO₂ simulations, particularly in winter.