Evaluation and control of respirable crystalline silica (RCS) exposures are critical components of an effective mine industrial hygiene program. To provide more timely exposure data in the field, an end-of-shift Fourier transform infrared (FT-IR) spectrometry method has been developed for evaluation of direct-on-filter RCS. The present study aimed to apply this FT-IR method using field samples collected in three Northwestern U.S. metal/nonmetal mines and compare the results to traditional laboratory X-ray diffraction analysis (XRD). Seventy-five dust samples were analyzed using both methods. Samples for each mine were split in half by random assignment, with half used to create a calibration factor for the FT-IR analysis and half used to apply the calibration. Nonparametric correlational and two-sample comparative tests were used to assess the strength of association and the level of agreement between the two methods. Strong, positive correlations were observed between FT-IR and XRD RCS concentrations, with Spearman rank correlation coefficients ranging between 0.84 and 0.97. The mean RCS concentrations determined through FT-IR analysis were lower than through XRD analysis, with mean differences ranging from -4 to -133 ug/m and mean percent errors ranging from 12% to 28%. There was a statistically significant improvement in the level of agreement between log FT-IR and log XRD RCS concentrations following calibration at two of the three mines, with mean differences of -0.03 (p = 0.002) and -0.02 (p = 0.044) in the log scale. The reduction in mean difference following calibration at the other mine was not statistically significant (mean log scale difference = -0.05, p = 0.215), but the differences between FT-IR and XRD were not significantly different without calibration (mean log scale difference = -0.07, p = 0.534). The results indicate that mine-specific calibration factors can improve the level of agreement between RCS concentrations determined via a field-based, end-of-shift FT-IR method in metal/non-metal mines as compared to traditional XRD analysis.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6327839PMC
http://dx.doi.org/10.1080/15459624.2018.1495334DOI Listing

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