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Environ Sci Pollut Res Int ; 18(9): 1487-96, 2011 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-21538227

RESUMO

PURPOSE: Bioaugmentation and biostimulation have been widely applied in the remediation of oil contamination. However, ambiguous results have been reported. It is important to reveal the controlling factors on the field for optimal selection of remediation strategy. In this study, an integrated field landfarming technique was carried out to assess the relative effectiveness of five biological approaches on diesel degradation. The limiting factors during the degradation process were discussed. METHOD: A total of five treatments were tested, including conventional landfarming, nutrient enhancement (NE), biosurfactant addition (BS), bioaugmentation (BA), and combination of bioaugmentation and biosurfactant addition (BAS). The consortium consisted of four diesel-degrading bacteria strains. Rhamnolipid was used as the biosurfactant. The diesel concentration, bacterial population, evolution of CO(2), and bacterial community in the soil were periodically measured. RESULTS: The best overall degradation efficiency was achieved by BAS treatment (90 ± 2%), followed by BA (86 ± 2%), NE (84 ± 3%), BS (78 ± 3%), and conventional landfarming (68 ± 3%). In the early stage, the total petroleum hydrocarbon was degraded 10 times faster than the degradation rates measured during the period from day 30 to 100. At the later stage, the degradation rates were similar among treatments. In the conventional landfarming, contaminated soil contained bacteria ready for diesel degradation. CONCLUSION: The availability of hydrocarbon was likely the limiting factor in the beginning of the degradation process. At the later stage, the degradation was likely limited by desorption and mass transfer of hydrocarbon in the soil matrix.


Assuntos
Gasolina/análise , Microbiologia do Solo , Poluentes do Solo/metabolismo , Biodegradação Ambiental , Bioensaio , Biomassa , Monitoramento Ambiental/métodos , Poluição Ambiental , Glicolipídeos/metabolismo , Cinética , Modelos Lineares , Consórcios Microbianos , Análise Serial de Proteínas/métodos
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