Development and Implementation of an Automated SEM-EDX Routine for Characterizing Respirable Coal Mine Dust

This thesis describes the development and use of a computer-automated microscopy routine for characterization of respirable dust particles from coal mines. Respirable dust in underground coal mining environments has long been known to pose an occupational health hazard for miners. Typically following years of exposure, coal workers' pneumoconiosis (CWP) and silicosis are the most common disease diagnoses. Although dramatic reductions in CWP and silicosis cases were achieved across the US between about 1970-1999 through a combination of regulatory dust exposure limits, improved ventilation and dust abatement practices, a resurgence in disease incidence has been noted more recently – particularly in parts of Appalachia. To shed light on this alarming trend and allow for better understanding of the role of respirable dust in development of disease, more must be learned about the specific characteristics of dust particles and occupational exposures.

This work first sought to develop an automated routine for the characterization of respirable dust using scanning electron microscopy with energy dispersive x-ray (SEM-EDX). SEM-EDX is a powerful tool that allows determination of the size, shape, and chemistry of individual particles, but manual operation of the instrument is very time consuming and has the potential to introduce user bias. The automated method developed here provides for much more efficient analysis – with a data capture rate that is typically 25 times faster than that of the manual method on which it was based – and also eliminates bias between users. Moreover, due to its efficiency and broader coverage of a dust sample, it allows for characterization of a larger and more representative number of particles per sample. The routine was verified using respirable dust samples generated from known materials commonly observed in underground coal mines in the central Appalachian region, as well as field samples collected in this region. This effort demonstrated that particles between about 1-9μm were accurately classified with respect to defined chemical categories, and suggested that analysis of 500 particles across a large area of a sample filter generally provides representative results.

The automated SEM-EDX routine was then used to characterize a total of 210 respirable dust samples collected in eight Appalachian coal mines. The mines were located in three distinct regions (i.e., northern, mid-central and south-central Appalachia), which differed in terms of primary mining method, coal seam thickness and mining height, and coal and/or rock mineralogy. Results were analyzed to determine whether number distributions of particle size, aspect ratio, and chemistry classification vary between and within distinct mine regions, and by general sampling location categories (i.e., intake, feeder, production, return). Key findings include:

1. Northern Appalachian mines have relatively higher fractions of coal, carbonate, and heavy mineral particles than the two central Appalachian regions, whereas central Appalachian mines have higher fractions of quartz and alumino-silicate particles.
2. Central Appalachian mines tended to have more mine-to-mine variations in size, shape, and chemistry distributions than northern Appalachian mines.
3. With respect to particle size, samples collected in locations in the production and return categories have the highest percentages of very small particles (i.e., 0.94-2.0μm), followed by the feeder and then the intake locations.
4. With respect to particle shape, samples collected in locations in the production and return categories have higher fractions of particles with moderate (i.e., length is 1.5 to 3x width) to relatively high aspect ratios (i.e., length is greater than 3x width) compared to feeder and intake samples.
5. Samples with relatively high fractions of alumino-silicates have higher fractions of particles with moderate aspect ratios than samples with low alumino-silicate fractions.
6. Samples with relatively high fractions of quartz particles have higher fractions of particles with moderate aspect ratios and higher percentages of very small particles than samples with no identified quartz particles.
7. Samples with high fractions of carbonates have higher percentages of particles with relatively low aspect ratios (i.e., length and width are similar) than samples with no identified carbonate particles.