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-on-filter 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.Graphical

Highlights

  • Published in the topical collection Advances in Direct Optical Detection with guest editors Antje J

  • Due to the abundance of primarily aluminosilicates or iron within the natural dust samples and not listed by X-ray diffraction (XRD), the data was corrected by derived elemental composition using energy-dispersive X-ray spectroscopy (EDX) mapping (Table 3)

  • Calcite Dolomite Quartz Others approach applied in the present study reduces the data to the main directions of variance across the entire spectrum by transformation into the space spanned by the partial least squares (PLS) loadings, called latent variables (LVs) [28,29,30]

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Summary

Introduction

Published in the topical collection Advances in Direct Optical Detection with guest editors Antje J. The exposure of mine workers to crystalline particles in the respirable size regime is a global problem in occupational health and safety at surface and underground mining operations [1,2,3,4,5]. The focus of recent studies is especially targeted to respirable crystalline silica (alpha quartz), which is known to cause a variety of lung diseases including chronic obstructive pulmonary disease (COPD) and silicosis. For occupational safety and health, the hazardous effects during the exposure of mine workers to dust containing respirable crystalline silica particles was unambiguously proven during past studies [4, 10,11,12]. A permissible exposure limit (PEL) of 100 μg/m3 respirable dust present in metal/non-metal mines was prescribed by the U.S Mine Safety and Health Administration (MSHA).

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