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Related Experiment Video

Updated: Jan 19, 2026

Preparation of Rat Skeletal Muscle Homogenates for Nitrate and Nitrite Measurements
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Simultaneous removal of nitrate and nitrite using electrocoagulation/floatation (ECF): A new multi-response

Ebrahim Nazlabadi1, Mohammad Reza Alavi Moghaddam1, Elnaz Karamati-Niaragh1

  • 1Department of Civil & Environmental Engineering, Amirkabir University of Technology (Tehran Polytechnic), Iran.

Journal of Environmental Management
|September 11, 2019
PubMed
Summary

This study optimized electrocoagulation/floatation (ECF) to remove nitrate and nitrite from wastewater. The process was modeled and optimized for residual contaminants and operating costs, achieving significant reductions.

Keywords:
Electrocoagulation/floatationModelingNitrate/ nitrite removalOptimizationResponse surface methodology

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Area of Science:

  • Environmental Engineering
  • Water Treatment Technologies
  • Chemical Engineering

Background:

  • Nitrate and nitrite contamination in wastewater poses significant environmental and health risks.
  • Conventional wastewater treatment methods often struggle with efficient removal of both nitrate and nitrite simultaneously.
  • The electrocoagulation/floatation (ECF) process offers a promising electrochemical approach for water purification.

Purpose of the Study:

  • To model and optimize the electrocoagulation/floatation (ECF) process for simultaneous removal of nitrate and nitrite from wastewater.
  • To achieve target residual concentrations of nitrate (<50 mg/L) and nitrite (<10 mg/L) while minimizing operating costs.
  • To develop a multi-response optimization strategy using computational tools for wastewater treatment.

Main Methods:

  • Utilized response surface methodology (RSM) to design 57 experiments for process evaluation.
  • Investigated the impact of key variables: initial pH, current intensity, initial nitrate concentration, number of electrodes, and reaction time.
  • Employed Analysis of Variance (ANOVA) to validate the predictive capability of the developed models.
  • Developed a custom MATLAB code for multi-response optimization of the ECF process.

Main Results:

  • ANOVA confirmed the reliability of the RSM-generated predictive equations for nitrate, nitrite, and operating costs.
  • Identified eight optimized conditions that met the stringent removal targets for both nitrate and nitrite.
  • Achieved residual nitrate levels below 50 mg/L and nitrite levels below 10 mg/L.
  • Maintained operating costs within the target range of $10 ± 0.05 US$/(kg NO3- removed).

Conclusions:

  • The study successfully demonstrated the efficacy of a modeled and optimized ECF process for simultaneous nitrate and nitrite removal from wastewater.
  • The developed multi-response optimization approach using MATLAB provides a robust framework for efficient wastewater treatment.
  • The findings offer a viable and cost-effective solution for managing nitrogenous pollutants in industrial and municipal effluents.