Library Dissertation Showcase

Comparison of Bioremediation Methods using Sulfate- Reducing Bacteria for Cobalt, Copper, and Nickel

  • Year of Publication:
  • 2020

Breakthroughs in new and improved bioremediation methods paired with sulfate-reducing bacteria (SRB) have great potential in the clean-up of heavy metal pollution from Cobalt, Copper, and Nickel. These metals are all required at increasing levels worldwide in order to support the modern lifestyle. While they are released into the ecosystem naturally at small amounts, large scale mining operations have resulted in much higher levels. Even at small concentrations these heavy metals are detrimental to health and the environment, requiring remediation solutions. SRB prove useful for bioremediation due to their metabolic flexibility and variety across species, allowing them to thrive in many situations.

Database searches using Web of Science and Google Scholar yielded 15 relevant papers to compare methods against one another. Copper had the greatest number of results compared to Cobalt and Nickel. A regular culture method was set as a baseline for comparison, as it is a well-tested standard to determine if a new method is effective and useful. Alternate methods were then described and examined, with tables and figures utilised for visual representation. Comparisons showed which methods were most effective at heavy metal removal, while detailing specific parameters. To be appropriate for real world applications, certain factors must be considered when selecting the most effective method such as cost effectiveness, heavy metal removal efficiency, pH, temperature, and duration of experiment. An additional comparison using a pollutant donor with these metals for simultaneous bioremediation was prepared and included, but with limited resources available.

Bioremediation methods paired with SRB are being developed, and used, as the threat of environmental pollution continues to grow. Comparative analyses are critical for identifying process efficiencies and knowledge gaps. This area is developing quickly, with great potential for future research and optimisation.

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