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Dynamics of Functional Genes and Bacterial Community during Bioremediation of Diesel-Contaminated Soil Amended with Compost

  • Hyoju Yang (Department of Environmental Science and Engineering, Ewha Womans University) ;
  • Jiho Lee (Department of Environmental Science and Engineering, Ewha Womans University) ;
  • Kyung-Suk Cho (Department of Environmental Science and Engineering, Ewha Womans University)
  • Received : 2022.10.24
  • Accepted : 2023.01.31
  • Published : 2023.04.28

Abstract

Compost is widely used as an organic additive to improve the bioremediation of diesel-contaminated soil. In this study, the effects of compost amendment on the remediation performance, functional genes, and bacterial community are evaluated during the bioremediation of diesel-contaminated soils with various ratios of compost (0-20%, w/w). The study reveals that the diesel removal efficiency, soil enzyme (dehydrogenase and urease) activity, soil CH4 oxidation potential, and soil N2O reduction potential have a positive correlation with the compost amendment (p < 0.05). The ratios of denitrifying genes (nosZI, cnorB and qnorB) to 16S rRNA genes each show a positive correlation with compost amendment, whereas the ratio of the CH4-oxidizing gene (pmoA) to the 16S rRNA genes shows a negative correlation. Interestingly, the genera Acidibacter, Blastochloris, Erythrobacter, Hyphomicrobium, Marinobacter, Parvibaculum, Pseudoxanthomonas, and Terrimonas are strongly associated with diesel degradation, and have a strong positive correlation with soil CH4 oxidation potential. Meanwhile, the genera Atopostipes, Bacillus, Halomonas, Oblitimonas, Pusillimonas, Truepera, and Wenahouziangella are found to be strongly associated with soil N2O reduction potential. These results provide useful data for developing technologies that improve diesel removal efficiency while minimizing greenhouse gas emissions in the bioremediation process of diesel-contaminated soil.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government through the Ministry of Science and ICT (MSIT) (2019R1A2C2006701 & 2022R1A2C2006615).

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