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Real-Time Exposure Measurement​ (IOHA 2018 OnDemand)

Recorded at IOHA 2018

Earn 1 Contact Hour

NIOSH strives to publish new and improved sampling and analytical methods covering emerging chemical hazards. NIOSH Draft Method 3706, VOCs by Portable Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS) using Passive Sampling, is being developed to address onsite monitoring of toxic industrial chemicals for protection of workers and emergency responders. The method will allow onsite testing on the day of release to determine exposure levels. There have been some challenges in intra-instrument variability. Discussion of these results and possible internal standard addition schemes that may improve resultant measurement variability in the NIOSH method will be discussed.

Routine health risk assessments at AF Combat Arms firing ranges involve periodic monitoring of instructor exposure to total metals and chemicals. Advances in direct reading instruments provide the opportunity for real-time monitoring, which could be used to reduce cost, time, and provide immediate feedback to mitigate exposures. Immediate feedback of exposure levels can help individuals understand activities that lead to hazardous exposure levels. However, real-time monitors produce large data sets that can be cumbersome to analyze. Video monitoring technology is a tool that can enhance exposure assessments by facilitating the correlations between activities and real-time data.

Mental fatigue represents a decrease in brain activity and performance. Fatigue is the result of a lack of rest and/or high mental workload. Because it can lead to production error, reduced production, accidents, degraded situational awareness, and reduced physical and cognitive ability, fatigue is a costly industrial issue. Notable industrial accidents due, at least in part, to operator fatigue include the Exxon Valdez, Three Mile Island, and the Chernobyl accidents. Research has demonstrated that fatigue can be measured by changes in the power of the alpha, theta, gamma, and delta bands of an electroencephalogram (EEG). Real-time measurements of fatigue could be used to predict and prevent fatigue events before they happen. While mobile, real-time measurement of fatigue is possible, current monitoring methods tend to be inconvenient, expensive, and/or suffer from false positives.

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