Dust monitoring equipment in lab

By Nikky La Branche, Research Fellow and OHS in Mining, Dust and Respiratory Health Program Lead – Sustainable Minerals Institute | The University of Queensland

The last decade has seen an increased focus on the escalating prevalence of mine dust lung disease in both the mining and engineered stone industries. A new dust testing methodology has been developed by the Minerals Industry Safety and Health Centre (MISHC) at The University of Queensland (UQ) to provide insight into dust exposure to better protect workers from mine dust lung diseases such as black lung and silicosis.

The alarming rate of silicosis diagnoses in the mining and engineered stone industries has resulted in Australian governments unanimously agreeing to implement a prohibition on the use, supply, and manufacture of engineered stone from 1 July 2024.

The ruling comes after a significant number of new cases have been diagnosed – including young workers with less than a decade of experience in the industry. In Queensland alone, there have been 885 reported cases of Queensland workers being diagnosed with dust-related lung diseases since 2019, mostly in the mining and quarrying, construction and manufacturing industries.

Worker exposure to particulates is currently monitored on a total mass basis via gravimetric analysis. Digging deeper into the details, it’s evident that the story goes beyond just mass.

Measuring beyond mass

The new methodology developed by MISHC is able to take an in-depth look at particle characteristics such as size, shape, and mineral makeup. The method also found interesting patterns in the way particles agglomerate – or group together – which wasn’t a factor that was even considered a few years ago.

We can no longer sweep the dust under the rug; it is evident that the size and shape of the particulate matter can affect its potential impact on human health.

In mining, the prevalence rates of disease can vary widely between regions, even with the same exposure standards. This was evident in British Coal, and is still an issue in Central Appalachia, in the US, where one in five miners are diagnosed with a mine dust lung disease. These regional variations have led researchers to look at the specifics of what in the dust is causing high rates of diseases in some areas, but not others.

Researchers within MISHC and the Mineral Characterisation Research Facility – which are both part of UQ’s Sustainable Minerals Institute (SMI) – developed the methodology for characterising respirable and inhalable dust samples using scanning electron microscopy with energy dispersive spectra on the Mineral Liberation Analyser (MLA).

The MLA was also originally developed at SMI, specifically in its Julius Kruttschnitt Mineral Research Centre, for the analysis of samples for minerals processing. Instead of analysing core samples or bulk samples, the MLA is now able to analyse respirable dust collected on a filter paper by a respirable cyclone – similar to the way dust exposure samples are taken.

Diving into dust data

The MLA provides detailed information on each particle measured on the filter – including the size and shape of the particle – and produces a mineral map of the particle showing the shape and relative contributions of the different mineralogies present in the particle.

Understanding what is in the mine environment is an important precursor to understanding the actual health hazard posed by the dust in different locations.

Lung tissue studies have shown that the size of dust particles can change how much reactivity the dust produces in the lung tissue, particularly for respirable crystalline silica. It’s also become evident that certain contaminants within the dust can produce much more reactivity. Understanding the characterisation of dust can also serve as an input to methods to mitigate exposure.

Multiple dust samples from numerous mining operations have already been analysed using the MLA.

The refined MLA Method was recently published in the Journal Minerals in a paper entitled Method for the Analysis of Respirable Airborne Particulates on Filter Using the Mineral Liberation Analyser.(1) The method has been successful in showing the variety of mineralogical components and particle size distributions present in various areas of the mines.

Analysing the findings

The research found a range of mineralogies present in tested coal samples and for some mines, surprisingly little of the ‘coal dust’ was found to actually be coal.

The MLA can detect up to 42 different mineralogies present, with the 12 most abundant mineralogies shown in Figure 2.

Figure 2. Image credit: University of Queensland

Particle size variation

The research has found that for underground coal mines the average size of particles can vary substantially between mines and, to a lesser extent, there are even variations within the mine.

The overall size distributions of the dust can be calculated by the MLA based on the measurements of the individual particles, which are of the actual particle diameter, not aerodynamic equivalent diameter.

For the coal mines, the overall particle size distributions seem to follow a pattern as shown in Figure 3 with the midface of the longwall (MF – long dashed lines) being the finest dust, while the maingate (MG – solid lines) is somewhat coarser and the continuous miner section is the coarsest dust (CM – short dashed lines).

Figure 3. Image credit: University of Queensland

These findings mean it may be possible for a worker to be exposed to a significant number of sub 1 micron particles that do not add up to enough mass to exceed the eight-hour time-weighted average exposure limit, but can still pose a significant hazard. While in other mines, workers may be exposed to larger particles where far fewer are penetrating into the lungs, but account for a significant portion of the mass in compliance sampling.

The differences in particle size may also affect the behaviour of the dust particles in current dust control methodologies. Mine sites with in depth knowledge on particle sizes and mineralogy can help tailor more effective dust control systems. With the level of detail available, it is possible to see how effective dust control measures are on the various sizes of silica particles present.

Particle agglomeration

The MLA characterisation data also shows that respirable particles are more mineralogically complex than initially thought. The particles look to be agglomerating at this small size producing multiple mineralogies in one particle – not just particles of single mineralogies as was initially thought.

This figure (Figure 4) shows false colour images of silica particles showing different agglomeration patterns from three different mines. The agglomeration patterns can vary between mines with the following patterns showing:

  • Agglomeration with aluminosilicates such as orthoclaseand muscovite
  • Agglomeration with carbon particles, either coal or diesel particulate matter
  • Mostly free silica

Figure 4a. Image credit: University of Queensland

Figure 4b. Image credit: University of Queensland

Figure 4c. Image credit: University of Queensland

When these particles are inhaled, the variations in chemical composition can affect how the body reacts with them.

There can be several sources of dust in a mine besides the cutting of the coal seam and these can be attributed to causes including vehicle traffic though the mine, the mining of roof or floor rock or rider seams, stone dusting activities and other activities in the mine such as shovelling.

Performing sampling in actual mining conditions picks up the contributions from all these sources, which in some instances can be significant. As well as this, the samples conducted in the study were taken in a variety of underground locations including at the maingate and midface of the longwall, around the continuous miners, on the shuttle car, in belt roadways and during secondary recovery activities.

Nikky La Branche. Image credit: University of Queensland

In-depth dust data application

Within MISHC, there is ongoing work to characterise the dust present in different mining environments to better understand how the chemical components, particle sizes and shape contribute to the health effects.

A range of underground coal and metal mines have been sampled to date, with recruitment currently in surface coal mines and engineered stone. One of the goals of the research is to build a database of dust exposures so industry can start to understand the detail of these exposures for a range of workers, and provide more details into the actual exposures of these similar exposure groups.

To address the escalating rates of mine dust lung diseases, MISHC has pioneered a groundbreaking dust testing methodology. Traditional mass-based monitoring is no longer sufficient, and MISHC’s approach – utilising the MLA – examines particle characteristics, revealing patterns in agglomeration previously overlooked. The research not only identifies variations in particle sizes within and between mines but also emphasises the potential health risks posed by submicron particles.

The ultimate goal in establishing a dust database is to provide detailed insights into the specific dust exposures faced by different worker groups, in order to make more informed decisions on exposure and control.

It is crucial for stakeholders, industry leaders, and policymakers to support and engage with these initiatives to ensure a safer and healthier future for mining communities. Uniting in the pursuit of knowledge, awareness and actionable measures to protect miners from mine dust lung diseases can enable industry to prioritise the well-being of those contributing to the mining industry and safeguard their health against the rise of dust-related diseases.

Footnotes:

  1. https://www.mdpi.com/2075-163X/13/12/1526
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