Two methods for estimating the performance characteristics of aerosol samplers were discussed. The methods were the polygonal approximation (PA) method and the curve fitting (CF) method. The PA method estimated the mean concentration of a sampled aerosol by approximating the integral of the sampling efficiency curve and the normalized distribution of the aerosol particles by a series of polygons. The variance of the estimated mean concentrations was expressed in terms of intersample and residual variations of the measured efficiency values. The CF method estimated a mean concentration for each sampled aerosol by fitting a curve to the efficiency values for that specimen using linear or nonlinear least square regression techniques. The methods were evaluated by applying them to published data on fluorescent tagged monodisperse aerosols obtained using MRE 113A static samplers and PM-10 ambient aerosol samplers. Estimates of sampler efficiency, sampler bias, and imprecision were obtained using each method and compared. The two methods generally produced comparable results when applied to the data obtained with the PM-10 sampler. The PA method gave poorer results for aerosol size distributions than the CF method when assessed by the magnitude of the geometric standard deviation of the mean. The data obtained with the MRE 113A sampler were generally not amenable to analysis by the CF method due to a small number of data points, which led to large uncertainties in the estimates of sampler efficiency, sampler bias, and precision. The authors conclude that when the PA and CF methods are applied to aerosol sampling data, they generally produce similar results when analyzing monodisperse aerosols.