Monte carlo simulation implementationto investigate uncertainty in exposure modeling
DOI:
https://doi.org/10.12923/Keywords:
exposure assessment, modelingAbstract
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 real differences between occupational groups. This study demonstrates the value of MC simulation in helping define the uncertainty in deterministic model estimates.
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