Prediction of remained pyrite fraction within a coal waste pile with using of multivariate regression method

Subject Areas : environmental management

Behshad Jodeiri Shokri ¹ , Faramarz Doulati Ardejani ² , Sadegh Karimpouli ³

1 - Assistant Professor, Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran *(Corresponding Author).
2 - Professor, School of Mining, College of Engineering, University of Tehran, Tehran, Iran
3 - Assistant Professor, Department of Engineering, University of Zanjan, Zanjan, Iran.

Received: 2014-01-15 Accepted : 2014-02-20 Published : 2016-09-22

Keywords: Coal Waste Pile, Remained Pyrite Fraction, multivariate regression, Alborz- Sharghi Coal Washing P,

Abstract :

Background and Objective: Acid mine drainage (AMD) is one of the most environmental problems which is caused by mining activities. It may be generated from oxidation of sulfide minerals (specifically pyrite) in mining wastes, ore and mineral processing. As a result, prediction and measurement of pyrite can play a key role in investigation of AMD process. In this paper, a relationship based on multivariate regression is suggested for predicting of remained pyrite fraction within a coal waste pile located nearby Alborz- Sharghi coal washing plant. Method: For this purpose, the model uses the most important factors (independent variables) including depth, mole fraction of oxygen, local temperature and cumulative annual precipitation (from the initial deposition of the wastes within the pile) as input parameters and returns the remaining pyrite fraction (dependent variable) in the related depth of the pile as its output. Findings: The results of the laboratory experiments reveal that the fraction of pyrite remaining gradually increased at the lower depth where the oxygen diffuses from the surface to 2 m of the pile. A comprehensive statistical analysis was conducted after obtaining and collecting of the required data which caused all the possible relationships among the target and independent variables to be suggested and presented. Then, the best model (relationship) according to Efroymson’s the step wise regression method was presented to predict of the remained pyrite fraction within the pile. Discussion and discussions: The relatively high confidence level of the suggested model (87%) reveals its appropriate reliability. A strong correlation (R2=90%) between validation data and suggested model also confirms the desirable reliability of the model. The proposed model is recommended to be applied in similar coal waste piles and will economize time and cost in investigation of AMD process on the environmental management issue of mining wastes.  

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