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Electrocoagulation with aluminum electrodes for sago industry wastewater: Process optimization and performance evaluation through response surface methodology

Environmental Progress & Sustainable Energy 2026 Score: 40 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Subramaniapillai Niju, Vijayananth Shruthi, K. Priyadharshini

Summary

This paper is not primarily about microplastics — it evaluates electrocoagulation as a wastewater treatment method for sago (tapioca starch) industry effluent, optimizing conditions to achieve strong removal of organic load, suspended solids, and nutrients.

Study Type Environmental

Abstract The discharge of untreated sago wastewater, characterized by a high organic load, leads to severe contamination of receiving water bodies. This study investigates the application of electrocoagulation (EC) using aluminum electrodes as a treatment method and employs response surface methodology (RSM) for process optimization. A central composite design was used to evaluate the influence of three key operating parameters—pH, electrolysis time, and applied voltage—on pollutant removal and energy consumption. The optimized conditions were identified as pH 7, electrolysis time of 25 min, and applied voltage of 10 V. Under these conditions, the process achieved 61.7% chemical oxygen demand removal with a relatively low specific energy consumption of 11.25 kWh/m 3 . Additional reductions included 93.3% for total suspended solids, 34.3% for nitrate, and 75.5% for phosphate, indicating the suitability of EC for multi‐pollutant removal. Characterization of the sludge and scum confirmed the formation of amorphous aluminum hydroxides along with associated organic and inorganic compounds, validating the underlying pollutant removal mechanisms. Overall, the findings demonstrate that electrocoagulation is a promising and feasible pre‐treatment approach for treating high‐strength sago wastewater. Optimization through RSM provides a reliable framework for identifying efficient operating conditions, making the process viable for large‐scale industrial application.

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