Optimization of coagulation-flocculation process for colour removal in purification of paint industry effluent using novel seed of Spondias mombin Linn

In response to growing environmental concerns over industrial wastewater, this study investigates the use of a novel plant-based coagulant derived from Spondias Mombin Linn (SML) seeds for treating paint industry effluent. The coagulant’s colour removal efficiency was assessed using a jar test and optimized through a Box-Behnken Design (BBD) matrix. Physicochemical analysis of the raw effluent showed high pollutant levels, including acidity (134 mg/L), hardness (294 mg/L), sulphate (120 mg/L), TSS (156.30 mg/L), BOD (129 mg/L), and dark red colour. Heavy metals such as lead (0.245 mg/L), iron (0.968 mg/L), and chromium (0.07 mg/L) exceeded NIS limits. Characterization of SML before and after treatment using SEM, FTIR, and XRD revealed decreased surface porosity, bonding of functional groups to contaminants, and a shift from crystalline to amorphous structure, respectively. The BBD-generated second-order polynomial model (R² = 0.9688, p < 0.05) confirmed significant interactions among coagulant dosage, pH, and settling time. Optimal conditions 0.4 g/L dosage, pH 10, and 30 minutes settling time—achieved a colour removal efficiency of 82.291% ±2.244. These findings demonstrate that SML seed is a promising, sustainable, and low-cost alternative to conventional coagulants for effective treatment of paint industry wastewater. • It explores the use of ground seeds of Spondias mombin Linn as a novel, eco-friendly bio-coagulant for the purification of paint effluent. • The research aims to improve the purification efficiency of paint effluent by optimizing key process parameters such as coagulant dosage, pH, and settling time using response surface methodology (RSM). • The process achieved high colour removal efficiency, presenting a sustainable alternative to conventional chemical coagulants. • The findings confirm the effectiveness of the treatment process through instrumental analysis.