This exploration focuses on the removal of chromium from actual tannery wastewater, collected from the HARBY TANNERY factory in Rubiki (Badr City), using an economical sorbent made from activated carbon derived from rice straw (CRS). The CRS sorbent is activated using H3PO4. The experiment aims to assess the impact of various parameters, including chromium initial concentration, sorbent dosage, treatment time, agitation velocity (rpm), sorbent particle size, and solution pH, on chromium removal from tannery wastewater. Structural, morphological, and electronic distinctive of raw and treated CRS, as well as carbonized CRS, were analyzed using FTIR, SEM, and TEM techniques. XRF analysis was conducted to investigate the chemical elemental composition of carbonized CRS before and after sorption. Zeta potential measurement was performed to assess the electrical charges of particles present in a suspension. The adsorption data was tested for both Langmuir and Freundlich adsorption isotherms, and most of the factors suggested that it follows the Langmuir adsorption isotherm with an R2 value of 99.67%. Additionally, adsorption kinetics were performed to identify the reaction order, which exhibited that sorption pursued pseudo-second-order kinetics with a rate constant (k) of 0.0658 g/mg g/min, a high correlation factor (R2) of 99.76%, and an estimated equilibrium chromium ion adsorption capacity (qe) of 1.597 mg/g, which closely matched the experimental data (1.4835 mg/g). The improved surface morphology and increased surface area of CRS resulted in approximately 98.9% chromium removal. Mechanism studies confirmed that intraparticle diffusion is not the sole rate-controlling step, and Boyd’s model demonstrated that film diffusion limited the rate of chromium adsorption. The desorption of chromium from the carbonized rice straw surface could be achieved by up to 96.4% of the sorbed amount by raising the solution pH to 10, indicating the potential reusability of carbonized rice straw for additional adsorption cycles. Finally, a statistical regression analysis and least square multivariate analysis were used to establish a correlation for predicting efficiency, yielding an R2 value of 97.54%.
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