Air pollution benefit-cost analyses depend on dispersion models to predict population exposures to pollutants, but it is difficult to determine the reasonableness of the model estimates. This is in part because validation with field measurements is not feasible for marginal concentration changes and because few models can capture the necessary spatial and temporal domains with adequate sophistication. In this study, we use the concept of an intake fraction (the fraction of a pollutant or its precursor emitted that is eventually inhaled) to provide insight about population exposures and model performance. We apply CALPUFF, a regional-scale dispersion model common in health benefits assessments, to seven power plants in northern Georgia, considering both direct emissions of fine particulate matter (PM2.5) and secondarily formed ammonium sulfate and ammonium nitrate particles over a domain within 500 km of Atlanta. We estimate emission-weighted average intake fractions of 6 x 10(-7) for primary PM2.5, 2 x 10(-7) for ammonium sulfate from SO2, and 6 x 10(-8) for ammonium nitrate from NOx, with no effect of SO2 on ammonium nitrate. To provide insight about model strengths and limitations, we compare our findings with those from a frequently applied source-receptor (S-R) matrix. Using S-R matrix over an identical domain, the corresponding intake fractions are 5 x 10(-7), 2 x 10(-7), 3 x 10(-8), and -2 x 10(-8), respectively, with the values approximately doubling if the domain is expanded to cover the continental United States. Evaluation of model assumptions and comparison of past intake fraction estimates using these two models illustrates the importance of assumptions about the relative concentrations of ammonia, sulfate, and nitrate, which significantly influences ammonium nitrate intake fractions. These findings provide a framework for improved understanding of the factors that influence population exposures to particulate matter.