A Predictive Model For Solution Composition, Neutralizer Dosage, And Sludge Generation In The Treatment Of Acid Mine Drainage From Abandoned Mines

Acid Mine Drainage (AMD), high acid water containing heavy metals discharged from mines, has been recognized as major cause of mine pollution. In Japan, the government spends billions of yen every year to prevent pollution caused by AMD in about 80 abandoned mines. It is widely recognized that the treatment could continue for long decades or an even century. However, costs and environmental loads are uncertain during the treatment because a predictive model for the quality of AMD, the dosage of neutralizer, and the amount of sludge that is applicable for abandoned mines with limited data has not yet been established. In this study, a two-steps predictive model for solution composition and neutralization chemical requirements of AMD in future was constructed based on the geochemical modeling. Requisite input data of the model was the past historical water quality data from AMD monitoring, such as metal concentration and pH in the solution, instead of the sample rocks as other conventional prediction methods. In the first step, solution composition of AMD in the future was extrapolated from the available historical data using geochemical simulation considering the first order kinetics for the mineral dissolution. In the second step, neutralizer dosage and sludge generation in the future was predicted based on the geochemical simulation supposing the chemical equilibrium and oxidation state for all of elements in the solution. Based on case studies of two abandoned mines in Japan, solution composition, neutralizer dosage and sludge generation were estimated. The results of this study demonstrate the effectiveness of our model for the prediction of AMD quality and chemical requirements of neutralization treatment after mine closing. The model is useful for the estimation of the neutralizer dosage and the sludge volume in abandoned mines with limited data. Keywords: acid mine drainage, predictive model, geochemical modeling, first order kinetics, water monitoring