Evaluation of occupational exposures to respirable dust in underground coal mines

Using categorical data analyses in determination of dust-related occupational diseases in mining

Dust-related occupational diseases are common in the mining sector. It is important to identify employees who have high potential for these diseases and to investigate the factors affecting disease formation. For this reason, dust and dust-related occupational diseases should be carefully investigated in mining operations. In this study, dust-related occupational diseases in an open-pit lignite mine were investigated. Firstly, dust measurements were performed and then a health check of all employees was implemented. The obtained data set was categorized by taking into account the occupation, age, experience and level of dust exposure of the employees. While the logistic regression analysis was performed to determine the probability of the diseases, a hierarchical loglinear model was established to investigate the factors in the occurrence of these diseases for those employees with the diseases. Therefore, the most important factors for the development of the diseases were determined by the hierarchical loglinear model.

Waveband selection within 400-4000 cm-1 of optical identification of airborne dust in coal mine tunneling face

Aimed at the optical evaluation of pollution levels caused by rock dust in an underground coal mine tunneling face, the optimal detection line and optical channel were investigated. The spatial distribution of airborne rock dust under local mining and ventilation conditions was simulated by the computational fluid dynamics method; thus, combined with the scattering and absorption properties of dust particles and gas molecules, the spectral transmission characteristics of a polluted atmosphere, including dust aerosols within 400-4000  cm^-1, were obtained. By eliminating the optical background of mine gases, the pure infrared signals of rock dust were further analyzed. Based on the comparison results, the detection line, which is 1.5 m high and 0.3 m away from the right wall, was determined to be the best observation position, and a waveband of 1505-1525  cm^-1 was selected to estimate the dust concentration. In addition, a dual-band detection method was presented, which can simultaneously identify the dust distribution and dispersion.

Experimental investigation on the infrared refraction and extinction properties of rock dust in tunneling face of coal mine

Comprehensive experimental research on the fundamental optical properties of dust pollution in a coal mine is presented. Rock dust generated in a tunneling roadway was sampled and the spectral complex refractive index within an infrared range of 2.5-25 μm was obtained by Fourier transform infrared spectroscopy measurement and Kramers-Kronig relation. Experimental results were validated to be consistent with equivalent optical constants simulated by effective medium theory based on component analysis of x-ray fluorescence, which illustrates that the top three mineral components are SiO2 (62.06%), Al2O3 (21.26%), and Fe2O3 (4.27%). The complex refractive index and the spatial distribution tested by a filter dust and particle size analyzer were involved in the simulation of extinction properties of rock dust along the tunneling roadway solved by the discrete ordinates method and Mie scattering model. The compared results illustrate that transmission is obviously enhanced with the increase of height from the floor but weakened with increasing horizontal distance from the air duct.

Comparison of the Cumulative Incidence Rates of Coal Workers' Pneumoconiosis between 1970 and 2013 among Four State-Owned Colliery Groups in China

The purpose of this study was to identify differences in the incidence characteristics of coal workers’ pneumoconiosis (CWP) based on data from four large state-owned colliery groups of China, by comparing the cumulative incidence rates of CWP. We investigated 87,904 coal workers from the Datong, Kailuan, Fuxin, and Tiefa Colliery Groups, who were exposed to dust for at least 1 year. The cumulative incidence rate of CWP was calculated with the life-table method and stratified analysis among coal workers with different occupational categories during different years of first dust exposure. Our results showed the cumulative incidence rate of Datong was higher than that of any other colliery group among workers with different occupational categories during different years of first dust exposure. For Datong workers who started their dust exposure in the 1970s, the cumulative incidence rates of CWP among tunneling, mining, combining, and helping workers were 34.77%, 10.20%, 34.59%, and 4.91% during the observed time of 34 years, respectively. For those in the 1980s, the cumulative incidence rates were 32.29%, 13.51%, 2.98%, and 0.47%, respectively. The cumulative incidence rates of Fuxin and Tiefa were the lowest. In conclusion, the Datong colliery has the highest cumulative incidence rate of CWP among the four studied collieries, followed by Kailuan. The cumulative incidence rates of Fuxin and Tiefa were the lowest. Additional dust-proofing measures for decreasing dust concentrations are still necessary.

Alterations of serum biomarkers associated with lung ventilation function impairment in coal workers: a cross-sectional study

BACKGROUND

Previous studies have demonstrated that alterations in certain circulating biomarkers may be correlated with Coal workers' pneumoconiosis (CWP). This study investigated the relationship between changes of serum biomarkers and pulmonary function during the development of CWP.

METHODS

Lung function parameters and specific serum indices were measured in 69 non-smoking coal workers, including 34 miners with CWP, 24 asymptomatic miners and 11 miners with minimal symptoms. The associations between changes in pulmonary function and serum indices were tested with Pearson's correlation coefficients. Multivariable analysis was used to estimate the predictive power of potential determinant variables for lung function.

RESULTS

Compared to healthy miners, lung function (FVC, FEV1, FEF50, FEF75, FEF25-75 % of predicted values) was decreased in miners with CWP (p < 0.05). Increased serum matrix metalloproteinase-9 (MMP-9) was associated with decreased FVC% of predicted values in the asymptomatic miners (r = -0.503, p = 0.014).

CONCLUSIONS

In coal mine workers, alterations of lung function parameters are associated with the development of CWP and with changes in circulating MMP-9, TIMP-9, IL-13 and IL-18R. These serum biomarkers may likely reflect the pathogenesis and progression of CWP in coal workers, and may provide for the importance of serum indicators in the early diagnosis of lung function injury in coal miners.

Identification and classification of high risk groups for Coal Workers' Pneumoconiosis using an artificial neural network based on occupational histories: a retrospective cohort study

Background

Coal workers' pneumoconiosis (CWP) is a preventable, but not fully curable occupational lung disease. More and more coal miners are likely to be at risk of developing CWP owing to an increase in coal production and utilization, especially in developing countries. Coal miners with different occupational categories and durations of dust exposure may be at different levels of risk for CWP. It is necessary to identify and classify different levels of risk for CWP in coal miners with different work histories. In this way, we can recommend different intervals for medical examinations according to different levels of risk for CWP. Our findings may provide a basis for further emending the measures of CWP prevention and control.

Methods

The study was performed using longitudinal retrospective data in the Tiefa Colliery in China. A three-layer artificial neural network with 6 input variables, 15 neurons in the hidden layer, and 1 output neuron was developed in conjunction with coal miners' occupational exposure data. Sensitivity and ROC analyses were adapted to explain the importance of input variables and the performance of the neural network. The occupational characteristics and the probability values predicted were used to categorize coal miners for their levels of risk for CWP.

Results

The sensitivity analysis showed that influence of the duration of dust exposure and occupational category on CWP was 65% and 67%, respectively. The area under the ROC in 3 sets was 0.981, 0.969, and 0.992. There were 7959 coal miners with a probability value < 0.001. The average duration of dust exposure was 15.35 years. The average duration of ex-dust exposure was 0.69 years. Of the coal miners, 79.27% worked in helping and mining. Most of the coal miners were born after 1950 and were first exposed to dust after 1970. One hundred forty-four coal miners had a probability value ≥0.1. The average durations of dust exposure and ex-dust exposure were 25.70 and 16.30 years, respectively. Most of the coal miners were born before 1950 and began to be exposed to dust before 1980. Of the coal miners, 90.28% worked in tunneling.

Conclusion

The duration of dust exposure and occupational category were the two most important factors for CWP. Coal miners at different levels of risk for CWP could be classified by the three-layer neural network analysis based on occupational history.