Application of Response Surface Methodology to Optimize Coagulation Treatment Process of Urban Drinking Water Using Polyaluminium Chloride

Abstract

Many coagulants such as aluminium sulfate, ferric sulfate, and ferrous sulfate have been investigated in the past, but there is a lack of data on their effectiveness to some specific water quality parameters. This study aimed at investigating the efficiency of the coagulation water treatment process to remove pollutants such as total organic carbon (TOC), total nitrogen (TN), and total suspended solids (TSS) from urban drinking water. The polyaluminium chloride (PAC) coagulant was applied to determine the impact of the treatment process on the structure and diversity of these pollutants in urban drinking water. All water samples were collected from the Yangtze River, Baoshan district, Shanghai, China, over a period of three months which coincided with the late summer and early winter periods. Specific to different coagulant characterizations, a preliminary test was performed with three other coagulants, namely, aluminium sulfate, polyaluminium, silicate sulfate, and ferric sulfate to determine their optimal conditions for floc characterization and removal efficiencies. In summary, the overall performance of the PAC coagulant was better than that of the other three coagulants used in the pre-treatment of the sampled water. The obtained results revealed that under the optimum operating conditions, the doses of the PAC were as follows: 20, 35, 50, 65, and 80 mgL−1, respectively. The water temperature and pH were determined by using a pH meter, the TOC and TN determined by using a TOC analyzer, and the TSS by following the ASTM D2540 method. Furthermore, the response surface methodology by the Box–Behnken optimization analysis was applied to coagulant dosage, temperature, pH, and three corresponding dependent factors (TSS, TOC, and TN) to determine the best optimal conditions for the PAC performance. To determine whether or not the quadratic model adequately explained and predicted the response during the coagulation process, an analysis of variance was performed. Multiple optimal factors were identified for the urban drinking water treatment, including a pH value of 6.9, water temperature of 20.1 °C, and a coagulant dosage of 9.7 mgL−1.

Use of Plackett–Burman and Box–Behnken Designs to Optimize Bioelectricity Production from Winery Residues

“…In this model, data are classified into two types: variables and responses. The model was fit to a quadratic model (Equation ( 1)), as we wanted to obtain a response surface and it was suspected that it has a curvature since the relationship between the variables and data did not vary linearly [20,21].…”