Development of a SEM-EDS-XRD Protocol for the Physicochemical and Automated Mineralogical Characterisation of Coal Dust Particles

Conchita Kamanzi (), Megan Becker, Johanna Von Holdt and Jennifer Broadhurst
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Conchita Kamanzi: Minerals to Metals Initiative, Department of Chemical Engineering, University of Cape Town, Cape Town 7700, South Africa
Megan Becker: Minerals to Metals Initiative, Department of Chemical Engineering, University of Cape Town, Cape Town 7700, South Africa
Johanna Von Holdt: Department of Environmental and Geographical Science, University of Cape Town, Cape Town 7700, South Africa
Jennifer Broadhurst: Minerals to Metals Initiative, Department of Chemical Engineering, University of Cape Town, Cape Town 7700, South Africa

Resources, 2022, vol. 11, issue 12, 1-24

Abstract: Exposure to coal dust from mining-related activities has historically been linked to several preventable but incurable respiratory diseases. Although the findings of numerous biological studies have determined that the physicochemical and mineralogical aspects of dust particles greatly influence both cytotoxic and proinflammatory pathways, robust datasets which quantitatively define these characteristics of coal dust remain limited. This study aims to develop a robust characterisation routine applicable for real-world coal dust, using an auto-SEM-EDS system. In doing so, the study addresses both the validation of the particle mineralogical scans and the quantification of a range of coal particle characteristics relevant to respiratory harm. The findings presented demonstrate the application of auto-SEM-EDS-XRD systems to analyse and report on the physicochemical and mineralogical characteristics of thousands of dust-sized particles. Furthermore, by mineralogically mapping the particles, parameters such as liberation, mineral association and elemental distribution can be computed to understand the relationships between elements and minerals in the particles, which have yet to be quantified by other studies.

Keywords: auto-SEM-EDS; particle characterisation; coal dust related diseases; liberation; element distribution (search for similar items in EconPapers)
JEL-codes: Q1 Q2 Q3 Q4 Q5 (search for similar items in EconPapers)
Date: 2022
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