A surrogate approach was deployed for assessing long-term exposures of multiple chemicals at 8 selected working areas of 3 manufacturing processes located at a clean room of a thin film transistor liquid crystal display (TFT-LCD) industry. For each selected area, 6 to 12 portable photoionization detector (PID) were placed uniformly in its workplace to measure its total VOCs concentrations (C T-VOCs ) for 6 randomly selected workshifts. Simultaneously, one canister was placed beside one of these portable PIDs, and the collected air sample was analyzed for individual concentration (C VOCi ) of 107 VOCs. Predictive models were established by relating the C T-VOCs to C VOCi of each individual compound via simple regression analysis. The established predictive models were employed to construct a year-long C VOCi databank based on the measured year-long C T-VOC for each selected area using the same portable PID. The ethanol (381 ppb-2,480 ppb), acetone (123 ppb-624 ppb) and propylene glycol monomethyl ether acetate 29 (PGMEA; 14.4 ppb-2,241 ppb) dominated in all selected areas, and all measured C VOCi were much lower than their permissible exposure limits. Predictive models obtained from simple linear regression analyses were found with an R 2 > 0.453 indicating that C T-VOCs were adequate for predicting C VOCi . The predicted year-long C VOCi reveals that long-term total multiple chemical exposures of all selected areas fall to the range 0.10%-20% of the permissible exposure level. Using the C T-VOCs as a surrogate for the routine checking purpose, the present study yielded allowable C T-VOCs fall to the ranges of 49.1 ppm-577 ppm. Considering the approach used in the present study requires less cost and manpower, it would be applicable to similar industries for conducting long-term multiple chemical exposure assessments in the future.
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