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Adsorption, Optimization, and Kinetic modeling of Methyl Red Removal from Textile-Polluted Water Using Brewery waste as an adsorbent.
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1  Laboratory of Process Engineering, Materials and Environment, Faculty of Technology, University of Djillali Liabes, PO Box 89, Sidi Bel Abbes 22000, Algeria.
Academic Editor: Juan Francisco García Martín


Environmental pollution, driven largely by industrial emissions, especially from the textile sector, is a pressing concern today. Inadequate treatment of global colored industrial effluents poses a significant environmental threat, leading to water pollution and potential risks to aquatic ecosystems and human health, further amplified by the mutagenic and carcinogenic effects of specific persistent dyes. In response, efforts have been directed towards investigating low-cost, easily accessible, and efficient bio-adsorbents to tackle the removal of dyes from wastewater. This study specifically aims to assess the efficacy of a particular industrial waste, namely Brewery waste, as an adsorbent for the elimination of methyl red dye. The results of the dye adsorption onto Brewery waste were analyzed using first- and second-order kinetics models. Various operational parameters, including the dye concentration, the pH of the dye solution, the mass of the adsorbent, and the reaction time, were scrutinized to optimize the operational aspects of the adsorption process. The kinetic results indicate the involvement of both internal and external diffusion processes in the adsorption mechanism. Brewery waste exhibited optimal performance in a weakly acidic medium with a pH of 4, and the Langmuir isotherm effectively characterizes the adsorption of the dye onto Brewery waste, with a coefficient of determination (R²) of 1 and a maximal adsorption capacity (qemax) of 64.1 mg/g.

Brewery waste proves to be an effective and economical adsorbent with a substantial capacity for removing methyl red dye from aqueous solutions.

Keywords: Brewery waste, Adsorption, Kinetic modeling, Operational parameters, Optimization.