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Quantification of Heavy Metals and Other Inorganic Contaminants on the Productivity of Microalgae
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Experimental study and parameters optimization of microalgae based heavy metals removal process using a hybrid

N Sultana1, S M Zakir Hossain2, M Ezzudin Mohammed3

  • 1Department of Computer Science, College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.

Scientific Reports
|September 16, 2020
PubMed
Summary

Chlorella kessleri microalgae effectively remove heavy metals from wastewater. Optimized conditions using RSM-DF and RSM-CSA modeling achieved 99.54% lead removal, demonstrating a viable biosorbent for water remediation.

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Area of Science:

  • Environmental Science
  • Biotechnology
  • Materials Science

Background:

  • Wastewater contamination by heavy metals poses significant environmental and health risks.
  • Microalgae offer a sustainable and cost-effective biosorbent solution for heavy metal removal.
  • Characterization of microalgal biomass is crucial for understanding biosorption mechanisms.

Purpose of the Study:

  • To investigate the efficacy of Chlorella kessleri as a biosorbent for heavy metal removal from wastewater.
  • To optimize biosorption process parameters using advanced modeling techniques.
  • To evaluate the simultaneous removal of multiple heavy metals.

Main Methods:

  • Biosorption experiments using Chlorella kessleri on synthetic wastewater.
  • Characterization of microalgal biomass via FTIR and SEM/XRD analyses.
  • Optimization of process parameters (pH, temperature, biomass dose) using Response Surface Methodology (RSM), Desirability Function (DF), and Crow Search Algorithm (CSA).

Main Results:

  • Maximum lead(II) removal efficiency of 99.54% achieved under optimal conditions (pH 6.34, 27.71 °C, 1.5 g L-1 biomass).
  • RSM-DF and hybrid RSM-CSA models accurately predicted biosorption performance, with experimental validation showing <5% error.
  • Pseudo-second order kinetic model best described lead(II) biosorption.
  • Removal efficiency order for mixed heavy metals: Pb(II) > Co(II) > Cu(II) > Cd(II) > Cr(II).

Conclusions:

  • Chlorella kessleri is a highly effective biosorbent for lead(II) and other heavy metals.
  • Integrated RSM-DF and RSM-CSA modeling provides a robust approach for optimizing biosorption processes.
  • Microalgae-based biosorption presents a promising technology for heavy metal remediation in wastewater treatment.