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Leachate Treatment via TiO2/UV Heterogeneous Photocatalysis: A Multiple Polynomial Regression Model
Tratamiento de lixiviados mediante fotocatálisis heterogénea TiO2/UV: un modelo de regresión polinomial múltiple
DOI:
https://doi.org/10.15446/ing.investig.101497Keywords:
leachates, TiO2, heterogeneous photocatalysis, model, polynomial regression (en)lixiviado, TiO2, fotocatálisis heterogénea, modelo, regresión polinómica (es)
Advanced oxidation processes such as TiO2/UV heterogeneous photocatalysis are suitable treatment methods for wastewater with high pollutant loads such as landfill leachates. Optimizing the variables that influence the process is a fundamental aspect. However, in this regard, experimental conditions are limited in terms of resources and time, which is why modeling allows obtaining a general understanding of the phenomenon from a set of experimental data. This work sought to model the photocatalytic process via multivariate polynomial regression, considering variables such as the catalyst concentration, the pH level, and the accumulated energy concerning the percentage of degradation in terms of dissolved organic carbon (DOC). The implemented fitting method resulted in a third-degree polynomial with an R2 of 0,8652, concluding that the model and its conclusions are valid. Moreover, with greater degrees, the model curve overfitted, even with better R2. DOC abatement showed a negative correlation with pH and the catalyst dose, while an opposite trend was observed for the accumulated energy. The model predictions allow inferring that, at low catalyst doses and medium and high pH levels, it is possible to find maximum degradations at low cumulative energies.
Los procesos de oxidación avanzada como la fotocatálisis heterogénea TiO2/UV son métodos de tratamiento adecuados para aguas residuales con altas cargas contaminantes como los lixiviados de rellenos sanitarios. La optimización de las variables que influyen en el proceso es un aspecto fundamental. Sin embargo, en este aspecto, las condiciones experimentales son limitadas en términos de recursos y tiempo, por lo que el modelado permite obtener una comprensión general del fenómeno a partir de un conjunto de datos experimentales. Este trabajo pretendió modelar el proceso fotocatalítico mediante regresión polinómica multivariada, teniendo en cuenta variables como la concentración del catalizador, el nivel de pH y la energía acumulada en relación con el porcentaje de degradación en términos de carbón orgánico disuelto (DOC). El método de ajuste implementado dio como resultado un polinomio de grado 3 con un R2 de 0,8652, concluyendo que el modelo y sus conclusiones son válidos. Además, a mayor grado, la curva del modelo se sobreajustó, incluso con mejor R2. La remoción de DOC mostró una correlación negativa con el pH y la dosis de catalizador, y se observó una tendencia opuesta para la energía acumulada. Finalmente, las predicciones del modelo permiten inferir que, a dosis bajas del catalizador y niveles medios y altos de pH, es posible encontrar degradaciones máximas con bajas energías acumuladas
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Copyright (c) 2023 Dorance Becerra Moreno, Fiderman Machuca-Martínez, Aymer Maturana, Salvador Enrique Villamizar Mosquera, Joseph Wbeimar Soto Verjel, Ángelo Joseph Soto Vergel
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