QEMSCAN® automated mineralogical analysis of PM2.5 and PM4: A preliminary study of underground coal mine dust from Poland and Slovenia

Determining the physical and chemical properties of airborne dusts in occupational settings is essential for assessing their potential toxicity as well as the effectiveness of respiratory protective equipment and dust mitigation measures. Here, we report the first successful QEMSCAN® automated mineralogical analysis of potentially toxic PM4 and PM2.5 dust from deep coal mines in Poland and Slovenia. QEMSCAN® was setup to automatically delimit 100,000 ‘particles’ per sample, based on average atomic number contrast, subject these to X-ray elemental analysis at points in a grid pattern (0.5 µm spacing), assign a mineral name to each point and then output the results as particle size, shape, mineralogy and mineral associations data and as mineral maps. The dusts were prepared as dispersions on a polyethylene sheet so that coal particles, with a slightly higher BSE signal, could be recognized from their substrate. Samples were analyzed repeatedly and in different orientations to determine the effects of sample geometry and topography. QEMSCAN® mineral identifications were manually checked using standard SEM X-ray elemental analysis. From a pilot study of Polish and Slovenian coal dust samples, PM4 and PM2.5 contain varying proportions of coal, quartz and other silicates, sulphides, sulphates, carbonates, oxides and other minerals, and notable concentrations of fly-ash particles. That some of these components may be toxic when inhaled, particularly the quartz and fly-ash, highlights the need for larger scale and wider ranging studies. The further potential of the newly developed QEMSCAN® methodology is discussed.

Bibliographic Details

Main Authors:	Johnson, Diane, Rollinson, Gavyn K., Arif, Ali Talib, Moreno, Teresa, Trechera, Pedro, Lah, Robert, Lubosik, Zbigniew, Pindel, Thomas, Gminsk, Richard, Williamson, Ben J.
Format:	artículo biblioteca
Language:	English
Published:	Frontiers Media 2022-09-21
Subjects:	QEMSCAN ®, Automated mineralogy, Coal mining, Dust, PM 2.5, PM 4,
Online Access:	http://hdl.handle.net/10261/282588 https://api.elsevier.com/content/abstract/scopus_id/85140586078
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