Batch and continuous removal of heavy metals from industrial effluents using microbial consortia View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-06

AUTHORS

F. Migahed, A. Abdelrazak, G. Fawzy

ABSTRACT

Bio-removal of heavy metals, using microbial biomass, increasingly attracting scientific attention due to their significant role in purification of different types of wastewaters making it reusable. Heavy metals were reported to have a significant hazardous effect on human health, and while the conventional methods of removal were found to be insufficient; microbial biosorption was found to be the most suitable alternative. In this work, an immobilized microbial consortium was generated using Statistical Design of Experiment (DOE) as a robust method to screen the efficiency of the microbial isolates in heavy metal removal process. This is the first report of applying Statistical DOE to screen the efficacy of microbial isolates to remove heavy metals instead of screening normal variables. A mixture of bacterial biomass and fungal spores was used both in batch and continuous modes to remove Chromium and Iron ions from industrial effluents. Bakery yeast was applied as a positive control, and all the obtained biosorbent isolates showed more significant efficiency in heavy metal removal. In batch mode, the immobilized biomass was enclosed in a hanged tea bag-like cellulose membrane to facilitate the separation of the biosorbent from the treated solutions, which is one of the main challenges in applying microbial biosorption at large scale. The continuous flow removal was performed using fixed bed mini-bioreactor, and the process was optimized in terms of pH (6) and flow rates (1 ml/min) using Response Surface Methodology. The most potential biosorbent microbes were identified and characterized. The generated microbial consortia and process succeeded in the total removal of Chromium ions and more than half of Iron ions both from standard solutions and industrial effluents. More... »

PAGES

1169-1180

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13762-016-1229-3

DOI

http://dx.doi.org/10.1007/s13762-016-1229-3

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https://app.dimensions.ai/details/publication/pub.1031116306


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