Coal workers’ pneumoconiosis (CWP), commonly referred to as black lung, is a chronic lung disease that results from the inhalation and deposition of coal dust in the lungs. While this disease continues to afflict coal miners, its prevalence has steadily declined over three decades since 1970. Based on a voluntary X-ray surveillance program, conducted by the National Institute for Occupational Safety and Health (NIOSH), this downward trend, however, ended in 2000 and has actually begun to rise. The Mine Safety and Health Administration (MSHA) instituted a Comprehensive Initiative to “End Black Lung” to combat the reported upturn in black lung disease. Rulemaking, with the intent of strengthening respirable dust regulations, is a major part of this initiative. This thesis addresses a controversial aspect of the newly proposed rules – single-shift compliance sampling.
Establishing new requirements for respirable dust compliance requires an understanding of both the accuracy and variability of measurements. Measurement variability is especially important in underground mining where the workplace is constantly moving and ventilation controls are continually changing. The results of a ventilation study performed in three underground coal mines are presented in this thesis. A total of 600 dust-concentration measurements were obtained in this study using Continuous Personal Dust Monitors (CPDMs). The data was analyzed to determine the variability associated with taking dust measurements in the mining workplace. The Johnson transformation was found to produce the best-fit distribution model for the data. This thesis summarizes the results of this study and presents a statistical procedure for establishing an exposure limit.
| Identifer | oai:union.ndltd.org:uky.edu/oai:uknowledge.uky.edu:mng_etds-1004 |
| Date | 01 January 2013 |
| Creators | Khan, Al I. |
| Publisher | UKnowledge |
| Source Sets | University of Kentucky |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Theses and Dissertations--Mining Engineering |
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