This analysis demonstrates improved decolorization efficiency in landfill leachate using the heterogeneous Fenton process, indicating effective nanocatalyst application.
Landfill leachates are highly complex and recalcitrant effluents, exhibiting high pollution potential when not subjected to proper treatment. The heterogeneous Fenton process with Ni0.5Zn0.5Fe2O4 nanocatalyst was applied to optimize the decolorization of stabilized raw landfill leachate, considering the color number in terms of the spectral absorption coefficient. For this, the central composite design (CCD) and the response surface methodology (RSM) were used to optimize the operating parameters: pH, catalyst concentration, and H2O2 factor. Ni0.5Zn0.5Fe2O4 catalyst was characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), textural analysis using the Brunauer–Emmett–Teller and the Barrett–Joyner–Halenda (BET-BJH) method, scanning electron microscopy (SEM), and dynamic light scattering (DLS). According to the analysis of variance (ANOVA), the model generated by experimental data regression was statistically significant, with a coefficient of determination (R2) of 0.96. The optimal point defined by the response surfaces corresponded to the values of H2O2 factor 1.14, pH 8.02, and catalyst concentration 0.66 g L-1, whose combination of values resulted in a theoretical response of 89.70% decolorization of the leachate. The validation tests revealed an excellent fit between the value predicted by the model and the values obtained experimentally. The reproducibility of the optimized condition is limited to stabilized leachates. Under the optimized condition, the heterogeneous Fenton process, when compared to the isolated H2O2 and Ni0.5Zn0.5Fe2O4 processes, provided higher absorbance removals of simple and conjugated aromatic compounds, as well as the integrated spectral area from 200 to 800 nm, thus revealing its effectiveness in the treatment of landfill leachate, considering the parameters analyzed, and its contribution to achieving the Sustainable Development Goals (SDGs).
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Quirino et al. (2025) studied this question.
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