Arsenic removal from solution using nano-magnetic compound: optimization modeling by response surface method

Area of Science:

• Environmental Science
• Materials Science
• Nanotechnology

Background:

• Arsenic contamination in water poses significant health risks.
• Effective removal of arsenic is crucial for public health and environmental safety.
• Nanomaterials offer promising solutions for contaminant remediation.

Purpose of the Study:

• To synthesize and characterize manganese iron oxide nanoparticles (MFO-n) for arsenic removal.
• To investigate and optimize the arsenic adsorption process using response surface methodology.
• To evaluate the efficiency of MFO-n in reducing arsenic mobility and toxicity.

Main Methods:

• Co-precipitation method for synthesizing MFO-n.
• Characterization using FTIR, FE-SEM, XRD, VSM, XRF, and BET.
• Central Composite Design (CCD) for modeling and optimization of arsenic adsorption.
• Investigated variables: pH, arsenic concentration, nanoparticle concentration, and time.

Main Results:

• MFO-n were successfully synthesized and characterized.
• The CCD model accurately predicted arsenic adsorption (R² = 0.97, p < 0.0001).
• Optimal conditions achieved >94% arsenic removal: pH 5, 2 g/L nanoparticles, 60 min, 3250 µg/L initial arsenic.

Conclusions:

• MFO-n demonstrate high efficiency in removing toxic arsenic species from aqueous solutions.
• The optimized adsorption process using CCD provides a reliable method for arsenic remediation.
• Synthesized MFO-n represent a viable solution for mitigating arsenic contamination.