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A Standard Characterization Methodology for Respirable Coal Mine Dust Using SEM-EDX

Author

Listed:
  • Rachel Sellaro

    (Department of Civil and Environmental Engineering, Virginia Tech, Holden Hall Room 108A, Virginia Tech Blacksburg, VA 24061, USA)

  • Emily Sarver

    (Department of Mining and Minerals Engineering, Virginia Tech, Holden Hall Room 108A, Virginia Tech Blacksburg, VA 24061, USA)

  • Daniel Baxter

    (Environmental Analysis Associates, Inc., 5290 Soledad Road, San Diego, CA 92109, USA)

Abstract

A key consideration for responsible development of mineral and energy resources is the well-being of workers. Respirable dust in mining environments represents a serious concern for occupational health. In particular, coal miners can be exposed to a variety of dust characteristics depending on their work activities, and some exposures may pose risk for lung diseases like CWP and silicosis. As underscored by common regulatory frameworks, respirable dust exposures are generally characterized on the basis of total mass concentration, and also the silica mass fraction. However, relatively little emphasis has been placed on other dust characteristics that may be important in terms of identifying health risks. Comprehensive particle-level analysis to estimate chemistry, size, and shape distributions of particles is possible. This paper describes a standard methodology for characterization of respirable coal mine dust using scanning electron microscopy (SEM) with energy dispersive X-ray (EDX). Preliminary verification of the method is shown based several dust samples collected from an underground mine in Central Appalachia.

Suggested Citation

  • Rachel Sellaro & Emily Sarver & Daniel Baxter, 2015. "A Standard Characterization Methodology for Respirable Coal Mine Dust Using SEM-EDX," Resources, MDPI, vol. 4(4), pages 1-19, December.
  • Handle: RePEc:gam:jresou:v:4:y:2015:i:4:p:939-957:d:60591
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    References listed on IDEAS

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    1. Scott Laney, A. & Attfield, M.D., 2014. "Examination of potential sources of bias in the US Coal Workers' Health Surveillance Program," American Journal of Public Health, American Public Health Association, vol. 104(1), pages 165-170.
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    Cited by:

    1. Conchita Kamanzi & Megan Becker & Johanna Von Holdt & Jennifer Broadhurst, 2022. "Development of a SEM-EDS-XRD Protocol for the Physicochemical and Automated Mineralogical Characterisation of Coal Dust Particles," Resources, MDPI, vol. 11(12), pages 1-24, December.

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