Electrocoagulation-Based Treatment of Tannery Wastewater: Integrated Process Optimization, Predictive Modeling, Cost Analysis, and Sludge Characterization

Tannery wastewater poses significant environmental risks due to its high organic load and toxic constituents, which often render conventional biological treatment methods ineffective. The study evaluates electrocoagulation (EC) for the treatment of synthetic tannery wastewater, specifically targeting the removal of Total Organic Carbon (TOC) and Chemical Oxygen Demand (COD). Box–Behnken Design (BBD) based Response Surface Methodology (RSM) was applied to optimize the main operating variables-pH, current, and reaction time-with the aim of enhancing COD removal while reducing energy usage. Optimal conditions resulted in 83.1% COD removal, 40.2% TOC reduction, and an energy consumption of 14.2 kWh m −3 . Kinetic analyses indicated that COD and TOC removal followed pseudo-first-order kinetics. An Artificial Neural Network (ANN)-based predictive model was developed for forecasting COD removal performance and energy usage. Scavenger analysis revealed that reactive oxygen species play a crucial role in COD removal during the EC process, with ·OH, SO 4 ·–, and O 2 ·– identified as the dominant contributors. In addition, the sludge produced during EC was analyzed by Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD), confirming its composition and suggesting suitability for safe disposal. The integration of EC with predictive modelling tools such as ANN enhances process optimization and performance forecasting.