Numerical Methods in Civil Engineering

Numerical Methods in Civil Engineering

Modeling Fenton Treatment for Landfill Leachate with the Focus on Initial COD and Sludge Generation

Document Type : Research

Authors
1 Assistant Professor, Department of Civil Engineering, Semnan University, Semnan, Iran
2 Assistant Professor, Department of Civil Engineering, Faculty of Civil Engineering, Semnan University, Semnan, Iran.
3 Department of Environmental Engineering, Faculty of Civil Engineering, K.N.Toosi University of Technology, Tehran, Iran
Abstract
There are different methods to treat landfill leachates among which Fenton process as a pretreatment physiochemical method is used in this paper to improve the BOD to COD ratio. While the center of attention of most previous studies has been the removal of organic pollutants, the amount of generated sludge is normally neglected which is an important element. Therefore, in this study, two other factors (SIR and ORSR) in addition to COD removal rate, are evaluated to consider the sludge generation factor as well. Meanwhile, the initial COD concentration of the leachate is a changeable factor depending on the site, region, climate and internal reactions that is examined in this research. For the design of the experiment, central composite design was used to minimize the required tests and see the interaction between variables. Therefore, input variables were pH, (H2O2)⁄(Fe2+), Fe2+ dosage and initial COD concentration while COD removal, SIR and ORSR were seen as output targets. The interesting result is that the initial concentration of COD was not a determining factor for COD removal rate, SIR and ORSR. Although low pH values were favorable for COD removal rate, high pH value led to better SIR and ORSR quantities which indicate the lower usage of chemical for pH adjustments. For favorable SIR, the amount of Fe dosage must be restricted to generate lower sludge. For higher ORSR values, high pH and (H2O2)⁄(Fe2+) quantities were suggested. The formulas for each target could pave the way for more accurate predictions of the results.
Keywords

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Volume 9, Issue 3
Winter 2025
Pages 39-46

  • Receive Date 10 November 2024
  • Revise Date 08 December 2024
  • Accept Date 14 March 2025