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Abstract This study exclusively focused on the potential application of an inexpensive and sustainable waste macro-algal biomass as an adsorbent for biosorption of copper ions from aqueous medium. After extraction of agar from brown macro-marine algae Gelidiella acerosa, the residual biomass without any further treatment was used as an adsorbent for the expulsion of copper from wastewater. Physicochemical parameters of biosorption like initial pH, initial concentration of Cu(II) solution and biosorbent dosage were optimized using response surface methodology. The maximum copper biosorption potential of 96.36% was observed at optimum conditions of pH of 5.31, initial concentration of 23.87 mg/l and biosorbent dosage of 0.41 g/l. Adopting FTIR and SEM techniques, the surface morphological features of biosorbent were studied. The pseudo-second-order kinetic model was found to be a proper approach to describe biosorption kinetics. All these results confirmed that spent G. acerosa could be considered as an efficient, eco-friendly and economic alternative for Cu(II) removal from aqueous solution.

Cadmium biosorption capacity of the biosorbent prepared from Gelidiella acerosa (brown algae) from synthetic cadmium solutions at optimum process conditions was investigated. The surface functional groups of the biosorbent responsible for biosorption were identified using FTIR analysis and the surface texture and porosity of the biosorbent was analyzed by SEM analysis. Response surface methodology (RSM) and artificial neural network (ANN) combined with central composite design (CCD) were used for modeling and optimization of biosorption and to study interaction effects of the three effective process variables such as solution pH, initial cadmium ion concentration and biosorbent dosage. Prediction capacities of RSM and ANN were compared and found that RSM showed better prediction performance than ANN. Kinetic data were well fitted to second order rate equation showing maximum biosorption capacity of 21.73 mg/g for 100 mg/l metal solution concentration. It was further confirmed by fitting the data to Elovich model. Biosorption mechanism was investigated using Intra-particle diffusion and Boyd models. The optimum cadmium removal efficiency of the biosorbent was found as 90.25%. [ABSTRACT FROM AUTHOR]