Abstract. We use observations of active fire area and fire radiative power (FRP) from the NASA Moderate Resolution Imaging Spectroradiometers (MODIS), together with a parameterized plume rise model, to estimate biomass burning injection heights during 2006. We use these injection heights in the GEOS-Chem (Goddard Earth Observing System Chemistry) atmospheric chemistry transport model to vertically distribute biomass burning emissions of carbon monoxide (CO) and to study the resulting atmospheric distribution. For 2006, we use over half a million FRP and fire area observations as input to the plume rise model. We find that convective heat fluxes and active fire area typically lie in the range of 1-100 kW m −2 and 0.001-100 ha, respectively, although in rare circumstances the convective heat flux can exceed 500 kW m −2 . The resulting injection heights have a skewed probability distribution with approximately 80 % of the injections remaining within the local boundary layer (BL), with occasional injection height exceeding 8 km. We do not find a strong correlation between the FRPinferred surface convective heat flux and the resulting injection height, with environmental conditions often acting as a barrier to rapid vertical mixing even where the convective heat flux and active fire area are large. We also do not find a robust relationship between the underlying burnt vegetation type and the injection height. We find that CO columns calculated using the MODIS-inferred injection height (MODIS-INJ) are typically −9 to +6 % different to the control calculation in which emissions are emitted into the BL, with differences typically largest over the point of emission. After applying MOPITT (Measurement of Pollution in the Troposphere) v5 scene-dependent averaging kernels we find that we are much less sensitive to our choice of injection height profile. The differences between the MOPITT and the model CO columns (max bias ≈ 50 %), due largely to uncertainties in emission inventories, are much larger than those introduced by the injection heights. We show that including a realistic diurnal variation in FRP (peaking in the afternoon) or accounting for subgrid-scale emission errors does not alter our main conclusions. Finally, we use a Bayesian maximum a posteriori approach constrained by MOPITT CO profiles to estimate the CO emissions but because of the inherent bias between model and MOPITT we find little impact on the resulting emission estimates. Studying the role of pyroconvection in the distribution of gases and particles in the atmosphere using global MOPITT CO observations (or any current spaceborne measurement of the atmosphere) is still associated with large errors, with the exception of a small subset of large fires and favourable environmental conditions, which will consequently lead to a bias in any analysis on a global scale.