Probabilistic Prediction of Acid Mine Drainage Generation Risk Based on Pyrite Oxidation Process in Coal Washery Rejects - A Case Study

In this paper, we investigate a probabilistic approach in order to predict how acid mine drainage is generated within coal waste particles in NE Iran. For this, a database is built based on the previous studies that have investigated the pyrite oxidation process within the oldest abandoned pile during the last decade. According to the available data, the remaining pyrite fraction is considered as the output data, while the depth of the waste, concentration of bicarbonate, and oxygen fraction are the input parameters. Then the best probability distribution functions are determined on each one of the input parameters based on a Monte Carlo simulation. Also the best relationships between the input data and the output data are presented regarding the statistical regression analyses. Afterward, the best probability distribution functions of the input parameters are inserted into the linear statistical relationships to find the probability distribution function of the output data. The results obtained reveal that the values of the remaining pyrite fraction are between 0.764% and 1.811% at a probability level of 90%. Moreover, the sensitivity analysis carried out by applying the tornado diagram shows that the pile depth has, by far, the most critical factors affecting the pyrite remaining

Probabilistic Prediction of Acid Mine Drainage Generation Risk Based on Pyrite Oxidation Process in Coal Washery Rejects - A Case Study Keywords:

Acid Mine Drainage , Monte Carlo Simulation , Statistical analyses , Coal waste