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

Abstract

Due to the global need for energy and resources, many workers are involved in underground and surface mining operations where they can be exposed to potentially hazardous crystalline dust particles. Besides commonly known alpha quartz, a variety of other materials may be inhaled when a worker is exposed to airborne dust. To date, the challenge of rapid in-field monitoring, identification, differentiation, and quantification of those particles has not been solved satisfactorily, in part because conventional analytical techniques require laboratory environments, complex method handling, and tedious sample preparation procedures and are in part limited by the effects of particle size. Using a set of the three most abundant minerals in limestone mine dust (i.e., calcite, dolomite, and quartz) and real-world dust samples, we demonstrate that Fourier transform infrared (FTIR) spectroscopy in combination with appropriate multivariate data analysis strategies provides a versatile tool for the identification and quantification of the mineral composition in relative complex matrices. An innovative analytical method with the potential of in-field application for quantifying the relative mass of crystalline particles in mine dust has been developed using transmission and diffuse reflection infrared Fourier transform spectroscopy (DRIFTS) within a unified multivariate model. This proof-of-principle study shows how direct on-site quantification of crystalline particles in ambient air may be accomplished based on a direct-onfilter measurement, after mine dust particles are collected directly onto PVC filters by the worker using body-mounted devices. Without any further sample preparation, these loaded filters may be analyzed via transmission infrared (IR) spectroscopy and/or DRIFTS, and the mineral content is immediately quantified via a partial least squares regression (PLSR) algorithm that enables the combining of the spectral data of both methods into a single robust model. Furthermore, it was also demonstrated that the size regime of dust particles may be classified into groups of hazardous and less hazardous size regimes. Thus, this technique may provide additional essential information for controlling air quality in surface and underground mining operations.

A Novel Calibration Method for the Quantification of Respirable Particles in Mining Scenarios Using Fourier Transform Infrared Spectroscopy

“…This global problem poses the challenge of providing sensing technologies and data evaluation methods for rapid on-site reaction and intervention in support of occupational health and safety. [1][2][3][4][5][6][7] Especially respirable dust particles, which may enter unciliated airways have the highest hazard potential, as they are suspected of causing various lung diseases. demanded facilitating on-the-spot intervention strategies.…”

“…demanded facilitating on-the-spot intervention strategies. 1,5,[8][9][10] Most studies related to this field specifically target the quantification of respirable crystalline silica (RCS), i.e., alpha quartz, which is well known to cause lung diseases such as silicosis while also being suspected to be a lung carcinogen. [11][12][13] This hazardous effect relating the exposure of mining workers to dust containing RCS was readily confirmed during past studies, 4,[14][15][16] and resulted in a permissible exposure limit (PEL) of 0.1 mg/m 3 respirable dust present in metal/non-metal mines, as prescribed by the U.S.…”

“…The loaded filters are then sent on to an appropriately equipped laboratory and analyzed in a controlled environment using XRD after proper sample preparation, which includes low temperature ashing or chemical extraction. 1,5,7,10,20 However, conventional laboratory techniques do not enable rapid in-field monitoring of respirable dust components due to the required sample preparation routines, the need for laboratory environments, and complex analysis procedures. Additionally, XRD is limited by particle size effects (e.g., line broadening) especially in the respirable size regime.…”

“…Especially for crystalline matrices, it has been demonstrated during earlier studies that FT-IR spectroscopy provides a versatile tool for the identification and quantification of a wide variety of minerals, including organic matrix components even in most complex scenarios. 5,23,25 Infrared spectroscopy was previously used for analyzing mine dust particles collected onto PVC filters by NIOSH via portable IR spectrometers that may be directly adapted for in-field usage. The obtained results were comparable to the results obtained via NIOSH method 7500.…”

“…However, it was revealed that quantification may be affected by background signatures, spectral matrix complexity (e.g., IR band overlaps), particle size distribution, and especially by matrix effects if unexpected mineral components occur within the analyzed sample; these effects are usually summarized by the term ''analytical confounders". 1,5,6,20,28 Cauda et al 1 faced this challenge via a sector-and a mine-specific approach, which tailors a univariate quantification to a specific deposit with a similar matrix composition. An alternative approach is resorting to advanced multivariate data analysis strategies as shown, e.g., by Bayman et al, directly calibrating natural coal and noncoal mine dust samples for RCS quantification.…”