Boreal forest fires are a significant contributor to atmospheric composition in the high northern hemisphere, and are highly variable both spatially and temporally. This study uses a new emissions model [Kasischke et al., 2005] to generate input to the University of Maryland Chemical Transport Model [Allen et al., 1996], with the goal of examining and constraining the key uncertainties in current understanding of boreal forest fire behavior. Model outputs are compared with data from the MOPITT instrument as well as in situ measurements of CO. A case study of CO transport during the summer of 2000 is used to examine several key uncertainties in the emissions estimates, describing how current levels of uncertainty affect atmospheric composition and applying atmospheric measurements can be applied to constrain uncertainty. Source magnitudes determined by inverse methods were shown to be highly sensitive to the assumed injection properties. For the boreal forest in 2000, the best agreement with observations was obtained with a pressure-weighted profile of injection throughout the tropospheric column, but detailed examination of the results makes clear that any uniform parameterization of injection will be a significant source of error when applied globally. Comparison of simulated CO distributions from daily, weekly, and monthly aggregate emissions sources demonstrated that while model data sources produced a valid representation of emissions at weekly resolution, the atmospheric distribution outside the source region has very little sensitivity to temporal variability at scales finer than 30 days. Different estimates of burned area produced large differences in simulated patterns of atmospheric CO. The GBA-2000 global product and the data sources used by Kasischke et al. [2005] gave better agreement with atmospheric observations compared to the GLOBSCAR product. Comparison of different estimates of fuel consumption indicated that atmospheric measurements of CO have limited sensitivity to spatial variability in fuels, but that current fuels maps can improve agreement with atmospheric measurements. These results provide a clear indication of how atmospheric measurements can be used to test hypotheses generated by emissions models.