Optimizing the Coagulation Dose Considering Multi Factors: A Design of Experiment Approach
DOI:
https://doi.org/10.33736/jaspe.11048.2025Keywords:
COD, Design of Experiments, Optimization, Residual Coagulant, TurbidityAbstract
Optimizing coagulant dosage for drinking water treatment is essential for enhancing water quality. It also improves operational efficiency and cost-effectiveness. Traditionally, treatment plants focus on removing turbidity, often neglecting other critical factors such as co-pollutant removal, residual coagulant levels, and sludge production. This study addresses these limitations by optimizing coagulant dosage to simultaneously maximize turbidity and chemical oxygen demand (COD) removal, minimize residual Al concentrations, and reduce sludge generation. It employs a multi–parameter approach to improve the water treatment process, targeting low (10 NTU), medium (50 NTU), and high (400 NTU) turbidity synthetic water samples, representative of Mahaweli River water quality. The methodology includes preparing synthetic water, conducting jar tests to evaluate coagulation performance, and using design of experiments with Response Surface Methodology to identify optimal coagulant dosages and mixing speeds. Poly-aluminum chloride (PAC) was found to be the most effective coagulant for low- and medium-turbidity waters, with optimal dosages of 7 mg/l and 7.8 mg/l, and mixing speeds of 220 rpm and 216 rpm. Under these conditions, the final turbidity of water was 0.1648 NTU and 0.6890 NTU, with sludge weights of 0.0047 g and 0.0382 g, respectively. For high turbidity water, alum was optimal at 27 mg/l, with a mixing speed of 226 rpm, resulting in a turbidity of 2.3904 NTU and a sludge weight of 0.2203 g. COD removal percentages for low, medium, and high turbidity samples were 49.12%, 53.45%, and 49.57%. Residual aluminum levels remained below 10 ppm across all samples, measured via titration and Atomic Absorption Spectroscopy (AAS). These findings show that optimized coagulant dosage improves water quality, reduces sludge, and minimizes chemical residuals, providing cost-effective and sustainable improvements in water treatment. The study recommends multi–parameter optimization strategies and mechanical mixing methods in conventional water treatment plants to enhance efficiency and ensure high-quality drinking water.
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