Direct-on-Filter α-Quartz Estimation in Respirable Coal Mine Dust Using Transmission Fourier Transform Infrared Spectrometry and Partial Least Squares Regression

Abstract

In order to help reduce silicosis in miners, the National Institute for Occupational Health and Safety (NIOSH) is developing field-portable methods for measuring airborne respirable crystalline silica (RCS), specifically the polymorph α-quartz, in mine dusts. In this study we demonstrate the feasibility of end-of-shift measurement of α-quartz using a direct-on-filter (DoF) method to analyze coal mine dust samples deposited onto polyvinyl chloride filters. The DoF method is potentially amenable for on-site analyses, but deviates from the current regulatory determination of RCS for coal mines by eliminating two sample preparation steps: ashing the sampling filter and redepositing the ash prior to quantification by Fourier transform infrared (FT-IR) spectrometry. In this study, the FT-IR spectra of 66 coal dust samples from active mines were used, and the RCS was quantified by using: (1) an ordinary least squares (OLS) calibration approach that utilizes standard silica material as done in the Mine Safety and Health Administration's P7 method; and (2) a partial least squares (PLS) regression approach. Both were capable of accounting for kaolinite, which can confound the IR analysis of silica. The OLS method utilized analytical standards for silica calibration and kaolin correction, resulting in a good linear correlation with P7 results and minimal bias but with the accuracy limited by the presence of kaolinite. The PLS approach also produced predictions well-correlated to the P7 method, as well as better accuracy in RCS prediction, and no bias due to variable kaolinite mass. Besides decreased sensitivity to mineral or substrate confounders, PLS has the advantage that the analyst is not required to correct for the presence of kaolinite or background interferences related to the substrate, making the method potentially viable for automated RCS prediction in the field. This study demonstrated the efficacy of FT-IR transmission spectrometry for silica determination in coal mine dusts, using both OLS and PLS analyses, when kaolinite was present.

Atomic Spectrometry Update – a review of advances in environmental analysis

“…Although a feasibility study demonstrated 58 m to be packaged within a compact size. The LOD was <1 ppb.…”

Direct infrared spectroscopy for the size-independent identification and quantification of respirable particles relative mass in mine dusts

“…The first successful results on the in-field quantification via the NIOSH direct-on-filter (DoF) method combined with portable FTIR spectrometers have proven to be of comparable quality to the NIOSH 7500 method [21]. In that study, mine dust particles were directly collected onto PVC filters by the respirable samplers [2,22]. The DoF method combined with the FTIR technique is included in ISO 19087:2018 by the International Organization for Standardization [23].…”

“…The DoF method combined with the FTIR technique is included in ISO 19087:2018 by the International Organization for Standardization [23]. However, analytical confounders such as variable background and effects of mixed mineral components in the analyzed dust sample matrix have been shown to negatively influence the reliability of the data analysis [1,22,24]. Those effects are most effectively addressed by single variable data evaluation strategies, as shown via a direct calibration approach for coal and non-coal mine dust using partial least squares regression (PLSR) [1,22].…”

“…However, analytical confounders such as variable background and effects of mixed mineral components in the analyzed dust sample matrix have been shown to negatively influence the reliability of the data analysis [1,22,24]. Those effects are most effectively addressed by single variable data evaluation strategies, as shown via a direct calibration approach for coal and non-coal mine dust using partial least squares regression (PLSR) [1,22]. Most recent studies by Cauda et al [2] confronted the problem of confounding variables with a sector-specific and a mine-specific approach.…”

Evaluating the use of a field-based silica monitoring approach with dust from copper mines

“…While the field-based estimation of RCS with portable FTIR can provide results comparable to the standard analysis—i.e., XRD analysis with NIOSH 7500—when no analytical confounders are present, [18] the negative effect of other minerals has been recognized as a necessary consideration. [27–29] Laboratory methods for RCS quantification uses the experience of analysts and, if needed, pre-treatment of the samples to address the presence of analytical cofounders. These tools will not be available if a portable FTIR is used by industrial hygienists in the field.…”