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Ambient Fine Aerosol Concentrations in Multiple Metrics in Taconite Mining Operations.

A new interesting article has been published in Ann Work Expo Health. 2018 Oct 23. doi: 10.1093/annweh/wxy086. [Epub ahead of print] and titled:

Ambient Fine Aerosol Concentrations in Multiple Metrics in Taconite Mining Operations.

Authors of this article are:

Huynh T, Ramachandran G, Quick H, Hwang J, Raynor PC, Alexander BH, Mandel JH.

A summary of the article is shown below:

Studies in environmental epidemiology and of occupational cohorts have implicated the effects of fine particulates with increased risk of cardiovascular diseases. Motivated by this evidence, we conducted an ambient air monitoring campaign to characterize fine aerosol concentrations around various taconite ore processes in six taconite mines in northeastern Minnesota. The ore processes were first categorized into 16 broad work areas/buildings. We then took air samples at 91 fixed locations using an array of direct-reading instruments to obtain measurements of mass (PM2.5 or particles with aerodynamic diameter <2.5 µm, and respirable particulate matter or RPM), alveolar-deposited surface area (ADSA), and particle number (PN) concentrations. At each location, a respirable gravimetric pump (which was used for calibration purposes) and the instruments measured the ambient dust level for 4 h producing ~240 1-min averaging real-time measurements. To analyze these data, we fit a Bayesian hierarchical model with an autoregressive order 1 correlation structure to estimate pooled concentrations for the 16 work areas/buildings while accounting for temporal correlation. PM2.5 and RPM average ambient concentrations were highly correlated to each other (Pearson's correlation = 0.98), followed by ADSA and PN correlation (R = 0.77). Office and control room areas were found to have the lowest concentrations in all four metrics when compared to other groups. Distinguishing between concentration levels among the remaining groups was more difficult due to the high uncertainty associated with the geometric mean estimates. The geometric standard deviation within location (GSDWL) generally ranged from 1 to 3 for all exposure metrics, except for a few locations that may have had changes in the work activities that generated the observed peaks and variability during the sampling duration. The geometric standard deviation between locations estimates were generally higher than GSDWL, which may indicate larger variability in the processes/activities between locations within each broad work area/building. Future work may look into whether it is feasible to use area measurements for epidemiological investigation and use personal measurements (if available) to validate such approach.
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