Current Issues of Pharmacy and Medical Sciences

Monte Carlo simulation implementation to investigate uncertainty in exposure modeling

Annales UMCS, Sectio DDD, Pharmacia, Vol. XXIV, N 4, 25


1 Occupational Hygiene and Ergonomics Dept., Lublin University of Technology, Lublin, Poland

2 Department of Clinical Pathomorphology, Medical University of Lublin, Poland

3 Department od Chemotherapy, St John’s Cancer  Center, Lublin, Poland

4 Radio-Diagnostic Dept., St John’s Cancer Center, Lublin, Poland


This study used Monte Carlo (MC) simulation to examine the influence of uncertainty on an exposure model and to determine whether a difference exists between workers groups in asbestos wastes transportation and decontamination process. Data on work practices and conditions were gathered in interviews with long-serving employees and pilot monitoring process at the asbestos contaminated sites. With the use of previously developed deterministic modeling techniques and likely distributions for model parameters, MC simulations generated exposure profiles for the two monitored job conditions. The exposure profiles overlapped considerably, although the average estimated exposure for one job site was approximately double that of the other. However, when the correlation between the model parameters in the two sites was considered, it was concluded that there was a significant difference in the estimates. Models are increasingly being used to estimate exposure. Different work situations inevitably result in different exposure estimates. However, it is difficult to determine whether such differences in estimated exposure between worker groups are simply the result of uncertainty with respect to the model parameters or whether they reflect realdifferences between occupational groups. This study demonstrates the value of MC simulation in helping define the uncertainty in deterministic model estimates.

Files to download


exposure assessment, modeling


April 2021

Mon Tue Wed Thu Fri Sat Sun
      01 02 03 04
05 06 07 08 09 10 11
12 13 14 15 16 17 18
19 20 21 22 23 24 25
26 27 28 29 30