Treatment of Wastewaters Generated by Surfactant-Enhanced Washing of Soils in an Aerobic Biofilter Inoculated with a Consortium of Hydrocarbon Degraders.
Br Biotechnol J
; 2013 Oct; 3(4): 471-484
Article
in En
| IMSEAR
| ID: sea-162528
Aims: The aims of this work were 1) To evaluate the performance of a submerged biofiltration system for the treatment of a surfactant-enriched wastewater that had been generated by a soil washing process. 2) To evaluate the effect of the flux and organic load over the performance of the system. 3) To determine the microbial evolution as an effect of the flux at different lengths of the biofilter by using a denaturing gradient gel electrophoresis (DGGE) analysis. Study Design: A three factorial design was used to evaluate the effect of different fluxes and organic loads over the performance of a continuously operated submerged aerobic biofilter. The DGGE technique was employed to determine microbial changes in the biofilter. Place and Duration of Study: The study was carried out at the Bioprocess Laboratory, Bioprocesses Department UPIBI-IPN, Mexico. The experimental stage lasted approximately eight months and the DGGE analysis four months more. Methodology: Contaminated soil was physicochemical and microbiologically characterized. A total of 70 kg of contaminated soil was washed using a 1:3 ratio soil/surfactant solution (0.5% Sulfopon 30-SP30). The surfactant-enriched wastewater was then treated in a submerged biofilter. The biofiltration system consisted of a column with a length of 50 cm and diameter of 12 cm. The biofilter was packed with tezontle with an average diameter of 0.2-0.4 cm and 70% void space. The biofilter working volume was 4.5 L. The samples of the packing material for the DGGE analysis were obtained from the ports located along the biofilter: at the wastewater inlet, at the middle of the column and at the outlet. After DNA extraction with a Power Soil DNA Isolation Kit (MO BIO), PCR (polymerase chain reaction) analysis was conducted. The 16S rRNA gene was amplified using universal bacterial primers. The data obtained by DGGE analysis for the microbial population developed in the biofilter were further analyzed by the Jaccard similarity coefficient. Results: The soil contained 14,704 mg/kg TPH. BTEX compounds were not found, and only two different PAHs were found in the soil samples: benzo-fluoranthene and benzopyrene, at concentrations of 0.1280 and 0.0682 mg/kg of soil, respectively. During the surfactant-aided soil washing, the highest removal percentage of the oil removed from the soil was 59% with 0.5% SP30. The wastewater generated after the soil washing process contained, in average 1,329 mg COD/L and 211 mg/L of grease and oil. Higher COD removals were obtained at a flux of 0.4 L/h for both of the COD initial concentrations. While the highest removal was 78.27%, determined at an initial COD concentration of 300 mg/L. When applying fluxes of 0.28 and 0.40 L/h at a higher initial COD concentration, the COD removals were increased; this was not the case for a flux of 0.63 L/h. For a given initial COD concentration, the removal efficiencies were higher for lower fluxes. Analysis of the similarity between the microbial populations for varying fluxes and levels along the length of the biofilter was determined by the Jaccard (JI) index. The results showed that the initial microbial populations (t0) have low similarities with the developed microbial populations at the different conditions tested. Conclusion: Both the flux and the initial COD concentration had an impact on COD removal and the microbial concentration in the column. The COD removal percentages were similar at fluxes of 0.28 and 0.63 L/h. The highest removal percentage of 78.27% was obtained at a flux of 0.4L/h; this finding was in agreement with the highest microbial count and the specialization of microbial populations (less diversity). In general, it was shown that the flux had an effect on changes in microbial population. Greater effects were observed on the microbial population due to the position along the reactor, e.g., the greatest differences were found at the different levels of the biofilter.
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Br Biotechnol J
Year:
2013
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Article