Eco-Friendly Coagulant versus Industrially Used Coagulants: Identification of Their Coagulation Performance, Mechanism and Optimization in Water Treatment Process

The evaluation of complex organic and inorganic coagulant's performances and their relationships could compromise the surface water treatment process time and its efficiency. In this work, process optimization was investigated by comparing an eco-friendly chitosan with the industrially used coagulants namely aluminum sulfate (alum), polyaluminum chloride (PAC), and aluminum chlorohydrate (ACH) in compliance with national drinking water standards. To treat various water samples from different treatment plants with turbidity and pH ranges from 20-826.3 NTU and 5.21-6.80, respectively, 5-20 mg/L coagulant dosages were varied in the presence of aluminum, ferum, and manganese. Among all, 10 mg/L of the respective ACH and chitosan demonstrated 97% and 99% turbidity removal in addition to the removal of the metals that complies with the referred standard. However, chitosan owes fewer sensitive responses (turbidity and residual metal) with the change in its input factors (dosage and pH), especially in acidic conditions. This finding suggested its beneficial role to be used under the non-critical dosage monitoring. Meanwhile, ACH was found to perform better than chitosan only at pH > 7.4 with half dosage required. In summary, chitosan and ACH could perform equally at a different set of optimum conditions. This optimization study offers precise selections of coagulants for a practical water treatment operation.

Automated summary

The study compared the performances of eco-friendly chitosan with industrial coagulants in treating water samples with turbidity and pH variations. Chitosan showed efficient removal of turbidity and metals with less sensitive responses to changes in dosage and pH, especially in acidic conditions. Meanwhile, ACH performed better at higher pH levels with half the dosage required, suggesting both coagulants can perform equally well under different optimal conditions.