MicroAsOx - Microbial system for arsenic removal from contaminated waters
Łukasz Drewniak , Klaudia Dębiec , Jan Krzysztoforski , Grzegorz Rzepa , Tomasz Bajda
AbstractThe MicroAsOx is a proposition of novel low-input, pro-environmental biotechnology for removal of arsenic from contaminated waters, which may be applicable in every region of the world. The technology is based on two stage, biological and chemical–method to remove arsenic from contaminated waters. As the biological catalyst, an arsenite-oxidizing strains carrying the pSinA plasmid, which gives its hosts the ability to oxidize As(III) into As(V) and resistance to heavy metals, are used. In the second part of the technology, the sorption of arsenates phenomenon is used. Bog iron ores, commonly found in the environment and easily accessible for exploitation, are used as the sorbent. The aim of this study was the experimental verification of the technology in a laboratory scale for a variety of environmental conditions, as well as in a pilot installation operating on arsenic contaminated mine waters. The laboratory part of the study allowed to answer the following questions: (i) what factors have influence on the kinetics of the arsenite oxidation process when the selected strains are used, (ii) what type of bog ores are most suitable (form effective and stable bonding with the removed arsenic) for the proposed technology, (iii) what technical solutions (types of bioreactors as well as the types of deposits and adsorbers) should be used, so as to fully exploit the potential of the studied strains and bog iron ores. In turn, the pilot installation allowed to estimate the real potential and limitations of the technology in a real environmental conditions.
|Journal series||New Biotechnology, ISSN 1871-6784, e-ISSN 1876-4347|
|Publication size in sheets||0.3|
|Conference||17th European Congress on Biotechnology (ECB2016), 03-07-2016 - 06-07-2016, Kraków, Polska|
|ASJC Classification||; ; ;|
|Publication indicators||= 0; : 2016 = 1.269; : 2016 = 3.813 (2) - 2016=3.24 (5)|
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