analysis of the efficacy of the MSHA respirable dust sampling program in surface metal/nonmetal mining industry

Open Access
Author:
Lashgari, Ali
Graduate Program:
Energy and Mineral Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
July 07, 2017
Committee Members:
  • Jeffery Kohler, Dissertation Advisor
  • Jeffery Kohler, Committee Chair
  • Jeremy M. Gernand, Committee Member
  • Shimin Liu, Committee Member
  • Dennis Murphy, Outside Member
Keywords:
  • Surface Mining
  • Occupational Health and Safety
  • Respirable Dust
  • Silica
  • Compliance Sampling
  • Classification and Regression Tree
  • Metal/Nonmetal Mining
  • Fugitive Dust
  • Dust Exposure
  • Quartz
Abstract:
The mining industry continues to be an important contributor to the American economy. However, there are a variety of health concerns associated with mining. Exposure to respirable silica dust is one of the sources of health risks in surface mines. A variety of respiratory diseases and other ailments, including silicosis and other non-malignant respiratory diseases, may be caused by exposure to respirable silica dust. The Mine Act of 1977 requires the Mine Safety and Health Administration (MSHA) to inspect mines every year. While one goal of these inspections is to ensure compliance with occupational health and safety regulations, Congress’s overall intent was to improve the safety and health of America’s mine workers. MSHA conducts a vigorous respirable dust sampling program to ensure compliance with its regulations as part of its deterrence and compliance mandate. MSHA inspections are resource intensive and consume a significant percentage of the agency’s annual appropriation. The question of whether MSHA’s compliance-sampling program is accomplishing the intended outcome is one of continued interest to the Government Accountability Office, taxpayers, organized labor, industry, and mine workers. The goal of this research is to determine the efficacy of the MSHA compliance-sampling program for respirable silica dust in surface metal and nonmetal mining operations. It is difficult to evaluate the efficacy of the program in reducing silicosis among mine workers because of the incomplete knowledge of health outcomes among miners and many confounding variables. The consequences of excess silica exposure can take years to develop. It is often impossible to accurately determine where and when exposures occurred, and whether exposures are fully attributable to occupational sources. Therefore, other surrogate metrics are required to assess the extent to which MSHA’s sampling program and enforcement activity is contributing to the intended outcome. Two surrogate measures, including deterrence effect and exposure reduction, can be used to inform this assessment. The objectives of this research include: (i) to determine the deterrence effect associated with the sampling program, (ii) to determine the extent to which mine worker exposure has changed, and (iii) to examine the MSHA compliance-sampling database for opportunities for improving the health of mine workers through the use of this database. These objectives will be achieved through analysis of the compliance-sampling database for the following specific aims: (i) to quantify the change in compliance over the period of the program, (ii) to determine the relationship, if any, between the number of samples taken in any inspection year (annual sampling load) and noncompliance frequency, (iii) to quantify the change in worker exposure over the period of the program, (iv) to explore evidence that the current sampling strategy could be changed to better identify overexposed occupations, and (v) to find evidence of gaps in knowledge, practices, or technologies that could reduce overexposure. The MSHA Compliance-sampling database for surface metal and nonmetal mining operations during the 19-year period from 1997 to 2015 was used in this study. Characteristics and limitations of the MSHA compliance-sampling database were considered in selecting the methods to analyze the database. Descriptive statistics of the database were used to determine if deterrence and exposure reduction effects exist. This method was also employed to determine relationships between annual sampling load and noncompliance frequency. As a part of the fourth specific aim, the database was examined for signs of unusual overexposures. Commodities and occupations with the highest and lowest noncompliance record were identified through Classification and Regression Tree analysis. A field study was planned to assess the potential value of the database to improve the health of mine workers by testing to determine whether the knowledge gained from the MSHA database analysis could be useful to identify gap areas knowledge, practices, or control technologies that could reduce overexposure. Personal and area samples were collected from several dimension stone cutting shops during the field trip, using Helmet-CAM tool, gravimetric samplers, and passive dust monitors. This research has determined that the MSHA compliance-sampling program fails to meet in many cases its intended purpose of improving health of mineworkers by insuring compliance and reducing exposure. In recent years, the noncompliance frequency percent (percentage of overall samples that are noncompliant) and average exposure level fluctuate from year to year with no strong downward trend. Therefore, deterrence and exposure reduction effects do not exist throughout the years. Deterrence and reduction in exposure exist only for some occupations and commodities, during short periods of time. Many other occupations showed a fairly constant level of noncompliance and exposure over the past years. There are also a few occupations and commodities that exhibited upward trends for noncompliance and exposure levels. For many occupations, the annual sampling load did not correlate to the annual noncompliance frequency. There are low-risk occupations (occupations that demonstrate relatively lower rate of overexposure) that are very frequently sampled by MSHA inspectors. The increase in the annual sampling load for low-risk occupations did not result in capturing more noncompliant samples. In addition, there are high-risk occupations that are less frequently inspected. The increase of sampling load in the case of high-risk occupations resulted in capturing more noncompliant samples. This indicates a lack of efficient sampling resource allocation, and also indicates that opportunities exist to improve MSHA sampling resource allocation based on knowledge generated using the database. The results of this study indicated that occupations such as stone cutter/polisher, bagging operator, and cleanup man are among high-risk occupations. On the other hand, there are occupations with very low probability of over-exposure that are very frequently sampled. Front-end loader operator, truck driver and backhoe operator are among those low-risk occupations. This study shows that data-driven methods could be useful tools to suggest improved sampling strategies that more effectively target high-risk occupations and commodities. This field study showed that the MSHA database could be used to determine occupations and commodities that are more often overexposed. Then, detailed exposure assessment methods can be used to determine areas and tasks that contribute to elevated exposure rates. Finally, the offending areas/tasks can be investigated to determine potential gaps – including a gap in proper practice of existing control technologies, lack of effective control technology, or a gap in knowledge regarding sources of elevated exposure. It can also help in determining modifications that could be made to improve the health of mine workers through reducing their exposure level. The results of this study can help make certain inferences about the utility of the MSHA database for the purposes of: improving MSHA’s sampling resource allocation; identifying gap areas (including gaps in knowledge, technology, or proper practice of existing interventions); and developing interventions that effectively target the true sources of exposure.