1. Method for the Analysis of Respirable Airborne Particulates on Filter Using the Mineral Liberation Analyser.
- Author
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LaBranche, Nikky, Wightman, Elaine, Teale, Kellie, Johnstone, Kelly, and Cliff, David
- Subjects
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AIR filters , *MINERALS , *DUST diseases , *X-ray spectra , *COAL mining , *INDUSTRIAL hygiene - Abstract
In recent years, the Mineral Liberation Analyser (MLA) has played a pivotal role in analysing respirable and inhalable ambient air samples collected on filters from both underground coal and metalliferous mines. Leveraging backscattered electron (BSE) image analysis and X-ray mineral identification, the MLA offers automated quantitative mineral characterization. The escalating prevalence and severity of mine dust lung diseases, particularly among young miners, have reignited interest in comprehensively understanding the dust's characterization, encompassing mineralogy, particle size, and shape. Merely measuring total respirable dust exposure and its duration based on gravimetrically determined weight is no longer deemed sufficient in addressing the evolving landscape of occupational health challenges in mining environments. Since the publication of previous studies, efforts have been dedicated to refining the Mineral Liberation Analyser (MLA) methodology for respirable dust sampling. This refinement, discussed in detail in this paper, encompasses various enhancements, such as the implementation of data checks to identify carbon contamination, backscattered electron (BSE) drift, and the misclassification of X-ray spectra. Additionally, an examination of sampling efficiency led to the exploration of using smaller samples as an alternative to the time-intensive analysis of entire filters. Furthermore, this paper presents a reanalysis of paired filter sample sets previously reported using the Sarver Group Methodology. These samples are subjected to analysis using the Mineral Liberation Analyser, providing a more detailed illustration of the outputs derived from the updated methodology and compared to previously published MLA data. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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