Reporting Silica Dust Exposure Measurements in South African Gold and Coal Mines: 2005 to 2016

Abstract

Background: Arising from the Mine Health and Safety Act 29 of 1996 (MHSA), one of the measures to protect mine workers is monitoring exposure to airborne pollutants. Mines are statutorily required to report airborne pollutant concentrations to the Department of Mineral Resources and Energy (DMRE) on a regular basis. Based on the DMRE's 2013 report, it was determined that 76% of workers were exposed to airborne pollutants at concentrations less than 10% of their respective occupational exposure limits (OELs). Using the same exposure data from the DMRE, the Chamber of Mines of South Africa reported a 14% improvement in the exposure to the airborne pollutants from 2005 to 2013. However, these reported reduced exposures to airborne pollutants are based on the summation of all airborne pollutant exposures by the DMRE. The annual reports refer to the percentage of employees exposed to the combined airborne pollutants, rather than to specific pollutants, such as silica dust – a hazard that is high on the occupational health agenda of the mining industry. From these reports, broad (and perhaps incorrect) conclusions are reached with regard to trends in silica dust and other exposures. The limitations of the SAMI include inaccurate data, self-regulation, incomplete employment and exposure records, and historical biases, which hinder its ability to effectively handle occupational health risks. This emphasizes the immediate need for clear and consistent regulations, accurate data collection, and impartial research approaches to protect the health of mine workers. Objectives: The objectives of this study were to describe trends in combined airborne pollutant and silica dust concentrations from 2005 to 2016, and to evaluate the DMRE Mandatory Code of Practice (MCoP) and the EN 689 methods (for testing exposure levels in the workplace against the OEL of 0.1 mg/m3) as published by the European Committee for Standardization (CEN), using reported silica dust concentrations from 2015 and 2016. Methods: This was a cross-sectional study in which secondary airborne pollutants exposure data, reported to the DMRE by coal and gold mining members of the Minerals Council, were analysed. The 282 870 data points were pooled together to describe trends in airborne pollutant exposures as they comprised 69 airborne pollutants reported by different mines with various mining methods, activities, and occupations. The exposure data was categorized into coal and gold mines, and further into four three-yearly periods (i.e. period 1: 2005-2007, period 2: 2008-2010, period 3: 2011-2013, and period 4: 2014-2016). This was conducted in order to have a consistent metric to allow for uniform assessment across different pollutants with varying OELs. Dividing the exposure concentration by its OEL provided a ratio, similarly to the way that an Air Quality Index is calculated. As a result, the data was normalized by dividing each pollutant exposure concentration by its occupational exposure limit (OEL) to obtain a ratio, termed Q. The arithmetic mean, standard deviation, geometric mean, and geometric standard deviation of the Qs were calculated for each of the three groups i.e. coal and gold mines combined, b) coal mines, and c) gold mines, for each period. Jeffreys’s Amazing Statistics Program was used to analyse the Qs and silica dust concentrations. The Kruskal–Wallis test was used to identify statistically significant differences among the four time periods for each commodity group. Additionally, Scheffe’s post-hoc test in JASP was conducted for further analysis and comparison of differences across all observed periods. Two methods, namely the EN 689 and the method required by the DMRE MCoP, were used to assess compliance. EXPOSTATS Tool 1 was used to calculate the arithmetic mean (AM), median, standard deviation (SD), geometric mean (GM), geometric standard deviation (GSD), and 90th and 95th percentiles of the exposure data derived from EN 689. Microsoft Excel was used to calculate the 90th and 95th percentiles of the exposure data based on MCoP method. A total of 127 014 silica dust data points from 2005 to 2016 out of the 282 870 were utilized to describe silica dust exposure trends, and 44 990 data points from the 127 014 were used to assess compliance for the years 2015 and 2016. Results: A total of 282 870 personal airborne pollutant concentrations from 2005 to 2016, obtained from DMRE, were included the analysis. Analysis of the pooled airborne pollutant exposure concentrations indicated that there was a high variability (data points were far apart and also far from the GM) as the GSDs ranged from 6.37 to 7.53, 7.8 to 8.43, and 5.7 to 6.16 for the coal and gold mines combined, coal mines alone, and gold mines alone, respectively. The variabilities of the silica dust concentrations were less than that of the pooled airborne pollutant data. The GSDs of the silica dust concentrations were < 3.5 for all three groups compared to the GSDs calculated from the pooled airborne pollutants concentrations, where the lowest GSD was 5.7. The trends in the pooled airborne pollutant exposure concentrations over the 12-year period, for all three groups, showed that there was a reduction in reported exposures to combined airborne pollutants. The AMs of the ratios (Q) indicated that the reduction in exposures for coal and gold mines combined, gold mining alone and coal mining alone, were 57%, 55% and 26%, respectively. The corresponding GMs of the ratios (Q) for gold mining alone, coal and gold mines combined, and coal mining alone, reduced by 64%, 45% and 15%, respectively, from 2005 to 2016. The distribution of the airborne pollutant data was skewed, which affected AM more than GM, and resulted in differences between the two measures. This was evident in the gold mining data, where the AM decreased by 55% but the GM decreased by 64%. Data for the period 2005-2007 had the highest AM (1.54) and standard deviation (2.75), suggesting that there were outliers. In this period, ratios (Q) ranged from 0.003 to 7.7, impacting the AM and creating a gap between median and AM values. From 2008 to 2010, the AM (1.26) and SD (2.04) decreased, showing reduced variability. A similar trend was observed from 2011 to 2013, with increased numbers of observations and further reduced variability. In 2014-2016, the AM decreased to 0.67 and SD to 1, indicating stability. The GMs for the coal and gold mines combined, coal mines alone and gold mines alone ranged from 0.17 to 0.31, from 0.22 to 0.28, and from 0.16 to 0.45, respectively. The trends in reported silica dust concentrations in all three groups showed a reduction over the 12-year period. The AMs indicated that the reductions for coal and gold mines combined, gold mining alone and coal mining alone, were 61%, 38% and 34%, respectively. The GMs of the silica dust concentrations indicated that the reductions in exposures for coal and gold mines combined, coal mining alone, and gold mining alone, were 54%, 35% and 31%, respectively. The AMs of the silica dust concentrations for coal and gold mines combined ranged from 0.17 to 0.44 mg/m3, while the coal mines ranged from 0.67 to 1.02 mg/m3 from 2005 to 2016. For gold mines, the AMs ranged from 0.13 to 0.23 mg/m3. Similarly, the GMs of the silica dust concentrations for the coal and gold mines combined ranged from 0.11 to 0.24 mg/m3, whereas coal mines ranged from 0.41 to 0.63 mg/m3, and gold mines ranged from 0.09 to 0.13 mg/m3. The 90th percentiles for the silica dust concentrations almost correlated with the AMs as they reduced by 67%, 40% and 34% for coal and gold mining combined, gold mining alone, and coal mining alone, respectively. The 90th percentiles for silica dust concentrations for the coal and gold mines ranged from 1.64 to 2.48 mg/m3, and 0.29 to 0.51 mg/m3, respectively. Although the trends indicated a reduction in exposure to silica dust concentrations, the AM, GM, 90th and 95th percentiles exceeded the OEL of 0.1 mg/m3 for the entire study period for the three groups, except for the gold mines alone in 2016. In that year, the GM was 0.09 mg/m3 (rounded to 0.1 mg/m3). For coal mining only, the 90th percentiles ranged from 1.64 to 2.48 mg/m3, whereas the 95th percentiles ranged from 2.16 to 3.16 mg/m3. For gold mining only, the 90th percentiles ranged from 0.29 to 0.51 mg/m3, and the 95th percentiles ranged from 0.35 - 0.63 mg/m3. A total of 44 990 silica dust concentrations were used from 2015 to 2016 to compare the 95th percentiles according to EN 689, and the 90th percentiles according to the MCoP. The DMRE MCoP method was shown to underestimate the exceedance of the occupational exposure limit by 5-26%, when compared with the EN 689 method. Conclusion: Despite the variabilities and challenges associated with pooling the airborne pollutants concentrations in the coal and gold mining industries, exposures to the airborne pollutants in the three commodity groups decreased from 2005 to 2016. However, reporting employee exposure as pooled airborne pollutants concentrations is flawed and obscures exposures to individual pollutants such as silica dust. The three commodity groups showed a decrease in silica dust exposure measurements from 2005 to 2016. However, there was still overexposure to silica dust in the three groups (greater than the OEL of 0.1 mg/m3). Inhalation of particles containing silica was higher in the coal than the gold mines, which is contradictory to what is known about the silica content of the ores in which the two commodities are found. The DMRE MCoP approach to compliance with silica dust levels underestimated the exceedance of the OEL in comparison to the EN 689’s approach. The current DMRE reporting methodology, i.e. the pooling of all data, does not allow accurate reporting of silica dust exposures and as a result, it does not provide direction or support for carrying out measures to decrease exposure to silica dust. The MCoP method for compliance testing revealed higher 90th-percentiles for coal mining compared to the 90th-percentile estimated for the population (EN 689). For gold mining it was the opposite. The EN 689 method is a more precise means of estimating OEL compliance, which is crucial for managing silica dust and specific pollutant health hazards and should be used in favour of the method in the MCoP.