Prediction of Optimal Coagulant Injection Dosages and pH in Wastewater Using Visual MINTEQ Model

Abstract

The secondary wastewater treatment effluents without further advanced sewage treatment were used as raw water, and the changes in pH, electric conductivity (EC), total dissolved solids (TDS), and turbidity according to dosages of coagulant injection were investigated through both Jar-test and Visual MINTEQ model. Then, the changes in water quality between Jar-test measurement and Visual MINTEQ prediction were evaluated. From the measurement results from Jar-test, the residual turbidity decreased, and reached lower values around 1.63 NTU with the increase in the coagulant dosages. Regardless of the type of coagulant, the pH decreased as the dosage of coagulant injection increased. From the prediction results of Visual MINTEQ model, the optimal dosages of coagulant injection for both Al2(SO4)3 and FeCl3 were estimated to be less than 0.1 mM. The optimal dosages of coagulant injection displayed slight differences between measured values through Jar-test and predicted value through Visual MINTEQ modeling, and this difference is mainly due to the complex functions of solubility differences between Al2(SO4)3 and FeCl3 at pH 6~7 and the ignorance of reactions of organic matters and other ions with Al2(SO4)3 and FeCl3 in the Visual MINTEQ model. Measured pH values gradually decreased with the increase in the dosage of coagulant injection whereas predicted pH values sharply decreased with the increase in the dosage of coagulant injection. From the results, Visual MINTEQ model can predict the similar values of composition and concentration in ions and pH in treated water up to some critical dosage of coagulant injection (i.e., 0.7 mM). However, Visual MINTEQ model can not predict the detail water chemistry in effluents with various compounds at trace levels and with high dosages of coagulation injection.