Atmospheric dispersion modelling in West Africa is crucial to understand, predict, and mitigate the impacts of air pollution on public health, ecosystems, and regional climate in a context of rapid urbanization and industrialization. This study develops a three-dimensional analytical model for carbon monoxide (CO) dispersion, governed by the turbulent scalar flux transport equation within a second-order Eulerian framework. A theoretical analysis of the model establishes the existence and uniqueness of the solution, and derives the associated optimality system using control theory and monotone operator techniques. From this formulation, an analytical solution is obtained that explicitly incorporates diffusion coefficients, turbulence intensities dependent on atmospheric stability (cloud cover and radiation), and three-dimensional wind components
derived from ERA5 reanalysis. The analytical model is then calibrated through four-dimensional variational data assimilation (4D-Var) using satellite-based CO observations from the Copernicus EAC4 reanalysis, to produce fields consistent with observations. An application over the Gulf of Guinea during the dry season demonstrates that the coupled Model-4D-Var system generates CO dispersion maps with finer spatial resolution (0.25？ × 0.25？) than the input satellite products (0.75？ × 0.75？), while maintaining good agreement with observations, as indicated by low RMSE, small negative fractional bias, and FAC2 values between 0.5 and 2 at most pressure levels. These high-resolution maps enable the quantification, identification, and tracking of CO plumes in space and time, including persistent plumes over southern and northern Nigeria, Ghana, and the Central African Republic, linked to gas flaring, biomass burning, and urban/industrial emissions. The results highlight the potential of combining an analytical dispersion model with 4D-Var to improve CO monitoring in data-sparse regions, such as the Gulf of Guinea.
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