Time series analysis of coal mine accident experience

This study investigates several forecasting techniques that can be useful to mine safety managers for studying mine accident rate behavior. Three time series models were studied for extrapolation of accident rates. These models are applied to historical accident incidence data from a coal mine. Further, a method is presented for evaluating the three models for the selection of an appropriate model. For this particular mine application, it is concluded that the more complex Box-Jenkins ARMA model as well as first order autoregressive model do not give better results than the simple exponential smoothing model. However, when the random variations or autocorrelations in the accident experience rates between periods are different, the models may predict differently. As such, specific models must be developed for each mine on the basis of statistical analysis of the mine accident experience data over time. Moreover, the importance of incorporating human judgement to interpret the results of statistical forecasting cannot be overemphasized. Integration of policy or operating changes, which may impact mine safety performance, with statistical forecasting techniques is essential to arrive at a realistic prediction of future performance.     

Riverine pollution in some northern and north eastern states of india

Water samples from 30 rivers in northern and north-eastern hilly states of India were analysed for bacteriological and physicochemical parameters along with metals and pesticide residues. It was found that 34% of samples had >50 coliforms/100 ml, while 24% of samples demonstrated >50 thermotolerant (faecal) coliforms/100 ml. Among the metals, iron was found to be above maximum permissible limits in the rivers of all the states, while manganese was found to be above the maximum permissible limit in the rivers of Tripura and some northern states. Zinc, lead, nickel, chromium, copper, cobalt and cadmium plus physicochemical parameters and residual pesticides, however, were within their maximum permissible limits.     

Risk assessment: an approach to control hazards in mines

Accidents and injuries related to work are major occupational health problems in most of the industrialized countries.Traditional approaches to manage workplace safety in mines have mainly focused on job redesign and technical aspects of engineering systems.It is being realized that compliance to rules and regulations of mines is a prerequisite;however,it is not sufficient to achieve further reduction in accident and injury rates in mines.Proactive approaches are necessary to further improve the safety standards in mines.Unsafe conditions and practices in mines lead to a number of accidents,which in turn may cause loss and injury to human lives,damages to property,and loss of production.Hazard identification and risk assessment is an important task for the mining industry which needs to consider all the risk factors at workplaces.Applications of risk management approaches in mines are necessary to identify and quantify potential hazards and to suggest effective solutions.In this paper,the following risk estimation techniques were discussed:(i)DGMS(Directorate General of Mines Safety,India)risk rating criterion,and(ii)a matrix based approach.The proposed tools were demonstrated through an application in an opencast coal mine in India.It was inferred that the risk assessment approach can be used as an effective tool to indentify and control hazards in mines.     

Evaluation of the presence-absence (P-A) test: A simplified bacteriological test for detecting coliforms in rural drinking water of India

One thousand three-hundred and ninety-four drinking water sources comprising ground water, surface water and piped supplies were tested in order to compare the presence-absence (P-A) test with standard MPN method to detect coliforms as indicators of water quality. Out of 1394 samples, 1074 (77.04%) and 1030 (74.88%) were positive by the MPN and P-A test, respectively. The P-A test detected 96% of the positives detected by the MPN test. The P-A test may be effectively used as a rapid screening method to detect coliform contamination in less polluted sources such as ground water and piped supplies.     

Potability of water sources in relation to metal and bacterial contamination in some northern and north-eastern districts of India

A total of 1094 water samples from 326 springs, 207 streams, 183 dug wells, 151 piped supplies, 90 tube wells, 75 hand pumps, 60 rivers and 2 lakes were collected from eight northern and six north-eastern districts of India. Samples were analysed to assess their potability by estimating the level of heavy metals and bacterial (coliform and faecal coliform) contaminations. Iron was found in a maximum number (53%) of water samples from hand pumps, followed by lead in 43% of the tube wells, chromium in 16% of dug wells, cadmium in 13% of streams and manganese in 7% of hand pumps above their maximum admissible concentrations (MACs). Maximum metal pollution has been observed in a considerable number of water samples from Doda, followed by Almora, Mirzapur and Bankura. Hand pump water samples exhibited maximum metal pollution followed by dug well, spring, stream and river water samples. Contamination of coliform and/or faecal coliform bacteria ranged between 41% and 67% of water samples from open water sources but it was also less, i.e. 6–15% of water samples from tube wells and hand pumps. In general, 42–85% of water samples from districts surveyed, except from Jammu (18%) and Mirzapur (27%), were found to be bacteriologically unsatisfactory. Since toxic metals and pathogenic bacteria pose a risk to public health, monitoring of drinking water sources is required.