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Minerals 2017, 7(1), 15; doi:10.3390/min7010015

A Computer-Controlled SEM-EDX Routine for Characterizing Respirable Coal Mine Dust

Department of Mining and Minerals Engineering, Virginia Tech, Blacksburg, VA 24061, USA
Author to whom correspondence should be addressed.
Academic Editor: David Cliff
Received: 18 November 2016 / Revised: 4 January 2017 / Accepted: 16 January 2017 / Published: 23 January 2017
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A recent resurgence in coal workers’ pneumoconiosis (or “black lung”) and concerns over other related respiratory illnesses have highlighted the need to elucidate characteristics of airborne particulates in occupational environments. A better understanding of particle size, aspect ratio, or chemical composition may offer new insights regarding causal factors of such illnesses. Scanning electron microscopy analysis using energy dispersive X-ray (SEM-EDX) can be used to estimate these particle characteristics. If conducted manually, such work can be very time intensive, limiting the number of particles that can be analyzed. Moreover, potential exists for user bias in interpretation of EDX spectra. A computer-controlled (CC) routine, on the other hand, can allow similar analysis at a much faster rate, increasing total particle counts and reproducibility of results. This paper describes a CCSEM-EDX routine specifically developed for analysis of respirable dust samples from coal mines. The routine is verified based on reliability of results obtained on samples of known materials, and reproducibility of results obtained on a set of 10 dust samples collected in the field. The characteristics of the field samples are also discussed with respect to mine occupational environments. View Full-Text
Keywords: CCSEM-EDX; respirable coal mine dust; dust characteristics; occupational health; black lung CCSEM-EDX; respirable coal mine dust; dust characteristics; occupational health; black lung

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Johann-Essex, V.; Keles, C.; Sarver, E. A Computer-Controlled SEM-EDX Routine for Characterizing Respirable Coal Mine Dust. Minerals 2017, 7, 15.

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