Abstract

Surface water contains clay, bacteria, dissolved metals, organic matter, color, other suspended solids. The purpose of coagulation and flocculation is to remove these suspended particles which ensure proper operation in treatment plant. Improper use of coagulant dosage affects water quality after treatment, cause operation problems and production costs. A study is being conducted at a surface water treatment plant at Dong Nai River with the capacity of 300,000 m3/day. The treatment process uses iron alum for coagulation and flocculation. Due to the high corrosion property of iron alum and the residue effects of the quality of treated water, it requires strict control in the treatment process as well as the chemical dosage. The main aim of this study is to determine appropriate amount of alum used for the coagulation-flocculation process. Research method is data collection including: turbidity, pH, flow rate of raw water, dosage of iron alum, lime, polymer used in current treatment process. Then, find the model using iron alum by linear regression analysis and BMA methods on R tool platform. Next, verify the appropriate linear regression model of iron alum by Jar test experiment. Results revealed that the BMA model is not suitable for the application because one Jar test results has a mean turbidity value greater than 4 NTU, which does not meet the water quality requirements after sedimentation tank according to the water treatment regulation. The linear regression analysis showed that raw water turbidity and season are two independent factors related to the alum dosage, of which these two factors explain about 78% of the differences that affect the coagulation-flocculation process. This study was successful in determining the appropriate iron alum dosage for the water treatment plant, which can be applied similarly to build appropriate chemical model for water surface water plants and raw water resources.

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