Statistical Analysis of the Elemental Characteristics of Airborne Coal Mine Dust

"This paper outlines some of the work associated with a research study into the relationship between the characteristics of coal mine dust and the incidence of coal workers' pneumoconiosis (CWP). The project involves study of the chemical, mineralogical, and morphological characteristics of the dust. Early stages of the study have dealt primarily with the size analysis and elemental composition of airborne dust in continuous miner sections. This paper outlines the procedures and findings of the elemental analysis portion of the study.Most of the previous elemental analyses of coal were made available in the quest for information on the combustibility of coal dust or on causal agents and prevalence of CWP. However, no extensive studies have been performed to date, primarily due to the limitations of the analytical methods. A review of the analytical methods for elemental characterization of coal and coal dust particles is presented. TI1e comparisons are made based on the sample mass required, the sample preparation required, the destructivity of the test, and the capability of providing an easy multi-element analysis. The reasons for selecting the proton-induced x-ray emission spectroscopy (PIXE) method are outlined.The PIXE method was applied to both the airborne coal mine dust and channel samples collected from seven continuous miner sections in six different mines. Channel samples of the coal, roof and floor were collected and analyzed. Airborne dust sampling was performed using multi-stage cascade impactors and permissible 2.0 I/min pumps. Sampler locations were fixed in the sections with respect to the continuous miner and roof bolter or with respect to the intake and return airways. Sampling times varied from 45 minutes to 6 hours, depending on the dust concentration.The statistical analysis of the resulting elemental data is presented. Of particular importance are the analyses of the variation of elemental composition with size and the variation in elemental composition over the working section. One interesting finding is outlined showing the multivariate statistical analysis of the trace elements and its implications in the identification of the dust sources. The paper concludes with an analysis of the ramifications of the elemental data to related medical studies."