Abstract

Selecting a proper respirator requires determining the ratio of an employee's maximum use concentration (MUC) divided by the occupational exposure limit of a chemical. Current industrial hygiene practice often is to obtain a percentile estimate (e.g. 95th) of the measured exposure distribution to apply as the MUC. However, practitioners who are not yet familiar with statistical or mathematical approaches may choose the highest exposure data point as the MUC, a method that is still considered appropriate by the Occupational Safety and Health Administration. Nonetheless, choosing a respirator using the highest exposure data point when only limited data are available may result in not always providing the most adequate respirator. Because some practitioners are not familiar with exposure assessment tools, our primary goal in this study was to demonstrate the best process when selecting respiratory protection by using a combination of exposure data and assessment tools. Three user-friendly tools, IHDataAnalyst, Advanced REACH Tool, and IHSTAT, were selected to demonstrate how to use different types of tool outputs when choosing a respirator. A decision logic was developed to help users navigate the combining of different data inputs. Personal full-shift exposure data collected in four different workplaces were used to describe four different outcomes generated when the maximum exposure data point and the tool's output are compared with the exposure limit of the chemical. Outcomes varied, from determinations of 'high confidence' (or final decision) to 'low confidence' (or indicating more data are needed) in the selection of a respirator recommendation. In conclusion, systematically adopting the combination of exposure data and assessment tools could increase practitioners' confidence in decision-making when choosing respirators from a limited exposure data set. These suggested guidelines will lead practitioners toward good industrial hygiene practices.

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