An integrated approach was developed to assess exposure and health-risk from polycyclic aromatic hydrocarbons (PAHs) contained in oil mists in a fastener manufacturing industry. One previously developed model and one new model were adopted for predicting oil mist exposure concentrations emitted from metal work fluid (MWF) and PAHs contained in MWF by using the fastener production rate (Pr) and cumulative fastener production rate (CPr) as predictors, respectively. By applying the annual Pr and CPr records to the above two models, long-term workplace PAH exposure concentrations were predicted. In addition, true exposure data was also collected from the field. The predicted and measured concentrations respectively served as the prior and likelihood distributions in the Bayesian decision analysis (BDA), and the resultant posterior distributions were used to determine the long-term exposure and health-risks posed on workers. Results show that long term exposures to PAHs would result in a 3.1%, 96.7%, and 73.4% chance of exceeding the PEL-TWA (0.2 mg/m3), action level (0.1 mg/m3), and acceptable health risk (10−3), respectively. In conclusion, preventive measures should be taken immediately to reduce workers’ PAH exposures.

Collecting multiple and long-term samples is necessary to accurately describe the exposure profile of a similar exposure group (SEG), but only a few industries can afford to do this because of the costs and manpower needed. In the present study, measured oil mist concentrations (C m , n = 11) were randomly collected on eleven days during one year (serving as the likelihood distribution in Bayesian decision analysis (BDA)), and daily fastener production rates (Pr, n = 250) were used as a surrogate for predicting the yearlong oil mist exposure concentrations (C p ) (serving as the prior distribution in BDA). The resulting BDA posterior distributions were used to assess the long-term oil mist exposures to threading workers in a fastener manufacturing industry. The feasibility of the proposed methodology was finally examined with reference to the effects of the sample size of the C m . The results show that threading workers experienced more severe thoracic and respirable oil mist exposure than exposure to the inhalable fraction. Using Pr as a surrogate was adequate to explain ~92% of the variations in C m . By combining C p and C m , our results suggest that the BDA technique adopted in this work was effective in predicting workers' long-term exposure. By judging the consistency of the resulting posterior exposure ratings, this study suggests that the proposed methodology could be feasible, even when the sample size of C m is set as low as 3.

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