- Title
- Multiwall carbon nanotubes increase the microbial community in crude oil contaminated fresh water sediments
- Creator
- Abbasian, Firouz; Lockington, Robin; Palanisami, Thavamani; Megharaj, Mallavarapu; Naidu, Ravi
- Relation
- Science of the Total Environment Vol. 539, Issue January 2016, p. 370-380
- Publisher Link
- http://dx.doi.org/10.1016/j.scitotenv.2015.09.031
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2016
- Description
- Since crude oil contamination is one of the biggest environmental concerns, its removal from contaminated sites is of interest for both researchers and industries. In situ bioremediation is a promising technique for decreasing or even eliminating crude oil and hydrocarbon contamination. However, since these compounds are potentially toxic for many microorganisms, high loads of contamination can inhibit the microbial community and therefore reduce the removal rate. Therefore, any strategy with the ability to increase the microbial population in such circumstances can be of promise in improving the remediation process. In this study, multiwall carbon nanotubes were employed to support microbial growth in sediments contaminated with crude oil. Following spiking of fresh water sediments with different concentrations of crude oil alone and in a mixture with carbon nanotubes for 30. days, the microbial profiles in these sediments were obtained using FLX-pyrosequencing. Next, the ratios of each member of the microbial population in these sediments were compared with those values in the untreated control sediment. This study showed that combination of crude oil and carbon nanotubes can increase the diversity of the total microbial population. Furthermore, these treatments could increase the ratios of several microorganisms that are known to be effective in the degradation of hydrocarbons.
- Subject
- bioremediation; multiwall carbon nanotubes; crude oil; pyrosequencing
- Identifier
- http://hdl.handle.net/1959.13/1319912
- Identifier
- uon:24007
- Identifier
- ISSN:0048-9697
- Language
- eng
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