Wastewater Assessment and Biochemical Oxygen Demand Value Prediction from Mining Operations: A Case Study

Abstract

Wastewater is a byproduct of industrial or household waste processes, and its contamination level must be determined before treatment. Discharges of liquid effluents generated by mining operations, one of the most prevalent forms of industrial waste water, pose a risk to human health and the environment. This study evaluates the physicochemical quality of industrial liquid effluent discharges from the Boukhadra mine (Algeria). Samples were collected from the washing water to identify the level of contamination of these liquid discharges and to measure physicochemical parameters such as temperature (T), hydrogen potential (pH), Electrical Conductivity (EC), Suspended Solids (SS), Chemical Oxygen Demand (COD), Biological Oxygen Demand for 5 days (BOD5), Oils and Greases (O&G), iron (Fe+2) and Kjeldahl Nitrogen (NTK). It was found that the concentration values of those effluents exceeded the maximum contamination limits specified by international industrial waste standards. A simple and reliable prediction model was developed to estimate DBO5, based on MES, COD, and O&G, by using classical regression analysis and fitting Design of Experiments (DOE) methodology. When comparing the analytical results, it was found that the quadratic model provided a better estimation, with a high correlation coefficient (R2) of 0.9976. The parameters determined in this study will enable engineers to quickly estimate the degree of wastewater contamination and choose adequate treatment strategies.