This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and °P'"' ons °f authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.CRAC2 is a computer code for estimating the health effects and economic costs that night result from a release of radioactivity from a nuclear reactor to the environment. This paper describes tests of sensitivity of the predicted health effects to uncertainties in parameters associated with inhalation of the released radionuclides. These parameters are the particle size of the carrier aerosol and, for each element in the release, the clearance parameters for the lung model en which the code's dose conversion factors for inhalation are based. CRAC2 uses hourly meteorological data and a straight-line Gaussian plume model to predict the transport of airborne radioactivity; it includes models for plume depletion and population evacuation, and data for the distributions of population and land use. The code can compute results for single weather sequences, or it can perform random sampling of weather sequences from the meteorological data file rmd compute results for each weather sequence in the sample. For the work described in this paper, we concentrated on three fixed weather sequences that represent a range of conditions. For each fixed weather sequence, we applied random sampling to joint distributions of the inhalation parameters in order to estimate the sensitivity of the predicted health effects. All sampling runs produced coefficients of variation that were less than 50%, but some differences of means between weather sequences were substantial, as werv> some differences between means and the corresponding CRAC2 results without random sampling. Early injuries showed differences of as much as 1-2 orders of magnitude, while the differences in early fatalities were less than a factor of 2. Latent cancer fatalities varied by less than 10%.