Abstract
Respiratory health effects such as mesothelioma, silicosis, and lung cancer have been shown to be associated with working in the taconite mining industry. Taconite workers may also have elevated risks from cardiovascular disease (CVD), although the relationship of CVD to dust exposures at these mines has not been well-studied. Motivated by evidence from environmental epidemiological studies and occupational cohorts that have implicated the effects of fine particulates with increased risk of cardiovascular diseases, we conducted an air monitoring campaign to characterize fine aerosol concentrations at 91 locations across six taconite mines using an array of direct-reading instruments to obtain measurements of mass concentrations (PM2.5 or particles with aerodynamic diameter less than 2.5 μm, and respirable particulate matter or RPM), alveolar-deposited surface area concentrations (ADSA), particle number concentrations (PN), and particle size distributions. To analyze these data, we fit a Bayesian hierarchical model with an AR(1) correlation structure to estimate exposure while accounting for temporal correlation. The highest estimated geometric means (GMs) were observed in the pelletizing and concentrating departments (pelletizing maintenance, balling drum operator, and concentrator operator) for PM2.5 and RPM. ADSA and PN generally had highest GMs in the pelletizing department, which processed large amounts of powder-like particles into iron pellets. The within-location variability (GSD_WL) generally ranged from 1 to 3 for all exposure metrics, except for a few locations which indicated changes of activities that caused the exposures to change. Between-location variability (GSD_BL) estimates were generally higher than GSD_WL, indicating larger differences in exposure levels at different locations between mines than at individual locations over the course of several hours. Ranking between PM2.5 and RPM generally agree with each other, whereas ADSA and PN were more consistent with each other, with some overlap with PM2.5 and RPM. Differences in ranking these groups may have potential implication for occupational epidemiological studies that rely on exposure information to detect an exposure-response relationship for various job groups. Future epidemiological studies investigating fine aerosol exposures and health risks in occupational settings are encouraged to use multiple metrics to see how they influence health outcomes risk.