@article{Neves_Aquino_Santana_Nascimento Júnior_Barbosa_Carvalho_Silva_Benachour_Rocha_2022, title={Biosorption textile wastewater employing lemon peel derivatives: data analysis and kinetic modeling}, volume={26}, url={https://periodicos.ufsm.br/reget/article/view/65265}, DOI={10.5902/2236117065265}, abstractNote={<p>The present work aimed to evaluate the efficiency of an agro-industrial waste biosorbent in the removal of real textile wastewater. A model sample with methylene blue and remazol golden yellow at equimolar proportions was prepared to be treated with in natura, carbonized, and activated lemon peel beads. Activated biosorbent demonstrated superior capacity and removal rates. Characterization analyses investigated the morphology and physico-chemical properties of the biomaterial. The pH (2.0) and dosage (1.6 g.L<sup>-1</sup>) studies were carried out to select parameters for further studies. In kinetic assays, methylene blue equilibrium was reached faster than remazol golden yellow RNL. The analyses of fitting parameters indicated Elovich kinetic model to describe biosorption of the yellow dye while pseudo-first-order fit best to the blue dye biosorption data. The intraparticle diffusion model indicated that more than one step may limit biosorption kinetics. In the treatment of real textile wastewater, 94.22% of dyes removal was attained after 360 minutes of operation at the selected operational conditions. Kinetics of adsorption of real wastewater presented considerable fitting to the models with R² greater than 0.93. An artificial neural network model was developed to describe the removal of dyes in real wastewater with satisfactory fitting (R<sup>2</sup> = 0.990).</p><p><em> </em></p>}, journal={Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental}, author={Neves, Naiana Santos da Cruz Santana and Aquino, Ramon Vinícius Santos de and Santana, Ingrid Larissa da Silva and Nascimento Júnior, Welenilton José do and Barbosa, Ada Azevedo and Carvalho, Rafaela Ferreira and Silva, Josivan Pedro and Benachour, Mohand and Rocha, Otidene Rossiter Sá da}, year={2022}, month={Dec.}, pages={e2} }