Occupational Exposures to Engineered Nanomaterials: a Review of Workplace Exposure Assessment Methods

Purpose of Review The purpose of this review is to consolidate exposure assessment methods for occupational research on engineered nanomaterials (ENMs) published within the past 5 years (2015-2020). Recent Findings The three ENMs that generated the highest volume of new research include titanium dioxide, graphene, and aluminum oxide. A multi-metric approach, using both online and offline instruments and analyses, has been found to be a useful method to characterize ENM workplace exposures and was commonly used in the recently published literature. Particle number concentration was the most common online exposure metric used, followed by the metrics of mass and surface area. There are currently no consensus methods for offline analyses of most ENMs. Researchers generally used gravimetric or elemental analyses for carbonaceous nanomaterials, titanium dioxide, and other nanometals, but there was little overlap between other ENM materials reviewed. Using biological markers of exposure, such as urinary oxidative stress biomarkers, as an indication of chronic exposure may also be useful for some ENMs and should be further researched. Generally, similar online instrumentation and offline electron microscopy methods were used for all ENMs. However, this consistency was not observed for offline mass analysis methods within specific ENMs. Consolidation of the most recent methods and results of exposure assessments within this broad material category can guide researchers toward future areas of study. Establishing consensus methods of exposure assessment for each individual ENM is crucial to characterizing workplace exposures, pooling data to fully understand their associated risks, and developing useful occupational exposure limits.

Automated summary

This review consolidates exposure assessment methods for occupational research on engineered nanomaterials (ENMs) within the past 5 years, highlighting the most commonly used materials and methods, emphasizing the importance of combining online and offline instruments and analyses, and pointing out the lack of consensus methods for offline analyses of most ENMs.