Multivariate modeling of the Fenton process for enhanced COD removal and low sludge generation in landfill leachate treatment

Biglarijoo, Nader; Shams, Amin

doi:10.22126/arww.2025.11294.1346

Document Type : Research Paper

Authors

Nader Biglarijoo ¹
Amin Shams ²

¹ Department of Civil Engineering, School of Civil Engineering, Semnan University, Semnan, Iran.

² Civil Engineering Department, School of Civil Engineering, Semnan University, Semnan, Iran.

https://doi.org/10.22126/arww.2025.11294.1346

Abstract

Biological treatment methods are not practical when it comes to landfill leachate treatment. Fenton as a physiochemical pretreatment technique is used in this research to increase the BOD/COD ratio. Conventionally, the main purpose of Fenton reaction has been the removal of organic pollutants, but in this paper, two other factors including sludge to iron ratio (SIR) and organic removal to sludge ratio (ORSR) are examined to generate low amounts of sludge as well. For the design of the experimental procedure, central composite design was used to not only minimize the required tests, but also observe the interactions between factors. Therefore, pH, , dosage and reaction time were considered as critical parameters while COD removal rate, SIR, and ORSR were introduced as targets. In order to have a clearer understanding of the process, multivariate modeling was applied to three targets to provide better predictions of the reaction. According to the statistical results, models can acceptably predict the target responses with R² above 0.95 and standard error and F-values were within suitable ranges. To reach high COD removal rates, the critical factors were and while for lower SIR and higher ORSR, the role of pH and were more significant. The reaction time was not a determining factor based on our observations for all three targets.

Keywords

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Multivariate modeling of the Fenton process for enhanced COD removal and low sludge generation in landfill leachate treatment

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Volume 11, Issue 2 - Serial Number 22December 2024Pages 110-115

Volume 11, Issue 2 - Serial Number 22
December 2024
Pages 110-115