Ying-Fang Wang1, Shih-Min Wang2, Yu-Chieh Kuo3, Chungsik Yoon4, Ya-Fen Wang5, Perng-Jy Tsai 3

  • 1 Department of Occupational Safety and Health, Chung Shan Medical University, Taichung City 40201, Taiwan
  • 2 Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, New Taipei City 24301, Taiwan
  • 3 Department of Environmental and Occupational Health, College of Medicine, National Cheng Kung University, Tainan City 70403, Taiwan
  • 4 Department of Environmental Health and Institute of Health and Environment, School of Public Health, Seoul National University, Seoul 151-742, Korea
  • 5 Department of Bioenvironmental Engineering, Chung Yuan Christian University, Taoyuan City 32023, Taiwan

Received: August 31, 2017
Revised: October 14, 2017
Accepted: October 16, 2017
Download Citation: ||https://doi.org/10.4209/aaqr.2017.08.0299  

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Cite this article:
Wang, Y.F., Wang, S.M., Kuo, Y.C., Yoon, C., Wang, Y.F. and Tsai, P.J. (2017). Long-term Multiple Chemical Exposure Assessment for a Thin Film Transistor Liquid Crystal Display (TFT-LCD) Industry. Aerosol Air Qual. Res. 17: 2891-2900. https://doi.org/10.4209/aaqr.2017.08.0299


  • Long-term multiple chemical exposure assessment in high-tech industries.
  • Using exposure surrogates for conducting exposure assessment.
  • Predicting models for establishing long-term exposure databanks.
  • Establishing acceptable surrogate levels for the routine checks.



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 (CT-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 (CVOCi) of 107 VOCs. Predictive models were established by relating the CT-VOCs to CVOCi of each individual compound via simple regression analysis. The established predictive models were employed to construct a year-long CVOCi databank based on the measured year-long CT-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 CVOCi were much lower than their permissible exposure limits. Predictive models obtained from simple linear regression analyses were found with an R2 > 0.453 indicating that CT-VOCs were adequate for predicting CVOCi. The predicted year-long CVOCi 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 CT-VOCs as a surrogate for the routine checking purpose, the present study yielded allowable CT-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.

Keywords: Multiple chemical exposures; Risk assessment; Clean room; Long-term exposure assessment

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