The application of human physiologically based pharmacokinetic (PBPK) modeling combined with measured biomonitoring data, has a great potential to backtrack external exposure to chemicals during chemical incidents. So far, an important shortcoming of 'reversed dosimetry' is that uncertainty and variability in the model predictions are often neglected. The aim of this paper is to characterize the variation in predicted environmental air concentrations by means of reversed dosimetry as a result of uncertainty in chemical-specific input data and variability in physiological parameters. Human biomonitoring data (N-2-cyanoethylvaline in blood) from a chemical incident with acrylonitrile (ACN) combined with the BioNormtox PBPK model are used as a case to reconstruct the air concentration and uncertainty thereof at the time of the incident. The influence of uncertainty in chemical-specific properties and exposure duration, and interindividual variability in physiological parameters on the reconstructed air exposure concentrations were quantified via nested Monte Carlo simulation. The range in the reconstructed air concentrations of ACN during the incident was within a factor of 3. Uncertainty in the exact exposure duration directly after the chemical accident was found to have a dominant influence on the model outcomes. It was also shown that uncertainty can be further reduced by collecting human biomonitoring data as soon as possible after the incident. Finally, the collection of specific information about individual physiological parameters from the victims, such as body weight, may further reduce the variation by 5 to 20% in our case study. Future research should include the comparison of reversed dosimetry model outcomes with measured air and biological concentrations to further increase the confidence in the model approach and its implementation in practice.