scholarly journals Design of a Microbial Remediation Inoculation Program for Petroleum Hydrocarbon Contaminated Sites Based on Degradation Pathways

Author(s):  
Xingchun Li ◽  
Wei He ◽  
Meijin Du ◽  
Jin Zheng ◽  
Xianyuan Du ◽  
...  

This paper analyzed the degradation pathways of petroleum hydrocarbon degradation bacteria, screened the main degradation pathways, and found the petroleum hydrocarbon degradation enzymes corresponding to each step of the degradation pathway. Through the Copeland method, the best inoculation program of petroleum hydrocarbon degradation bacteria in a polluted site was selected as follows: single oxygenation path was dominated by Streptomyces avermitilis, hydroxylation path was dominated by Methylosinus trichosporium OB3b, secondary oxygenation path was dominated by Pseudomonas aeruginosa, secondary hydroxylation path was dominated by Methylococcus capsulatus, double oxygenation path was dominated by Acinetobacter baylyi ADP1, hydrolysis path was dominated by Rhodococcus erythropolis, and CoA path was dominated by Geobacter metallireducens GS-15 to repair petroleum hydrocarbon contaminated sites. The Copeland method score for this solution is 22, which is the highest among the 375 solutions designed in this paper, indicating that it has the best degradation effect. Meanwhile, we verified its effect by the Cdocker method, and the Cdocker energy of this solution is −285.811 kcal/mol, which has the highest absolute value. Among the inoculation programs of the top 13 petroleum hydrocarbon degradation bacteria, the effect of the best inoculation program of petroleum hydrocarbon degradation bacteria was 18% higher than that of the 13th group, verifying that this solution has the best overall degradation effect. The inoculation program of petroleum hydrocarbon degradation bacteria designed in this paper considered the main pathways of petroleum hydrocarbon pollutant degradation, especially highlighting the degradability of petroleum hydrocarbon intermediate degradation products, and enriching the theoretical program of microbial remediation of petroleum hydrocarbon contaminated sites.

2000 ◽  
Vol 40 (1) ◽  
pp. 19-31 ◽  
Author(s):  
Yun-Juan Chang ◽  
John R. Stephen ◽  
Amy P. Richter ◽  
Albert D. Venosa ◽  
Julia Brüggemann ◽  
...  

2020 ◽  
Vol 54 (18) ◽  
pp. 11396-11404
Author(s):  
Barbara A. Bekins ◽  
Jennifer C. Brennan ◽  
Donald E. Tillitt ◽  
Isabelle M. Cozzarelli ◽  
Jennifer McGuire Illig ◽  
...  

2014 ◽  
Vol 497-498 ◽  
pp. 250-259 ◽  
Author(s):  
Seungjin Kim ◽  
Rosa Krajmalnik-Brown ◽  
Jong-Oh Kim ◽  
Jinwook Chung

2007 ◽  
Vol 87 (5) ◽  
pp. 551-563
Author(s):  
Carol Luca ◽  
Bing C Si ◽  
Richard E Farrell

Petroleum hydrocarbon (PHC) contamination is one of the most common contaminants in soils and remediation of PHC-contaminated sites requires methods for characterizing the spatial distribution of PHC on a site. Few studies have compared the performance of indicator kriging (IK) and sequential indicator simulation (SIS) in site characterization of petroleum-contaminated sites, or the application of these methods given the fraction based guidelines. The objectives of this study were to determine if IK and SIS indicate similar contaminated areas and to examine how the probability of exceeding thresholds changes when multiple fractions are considered simultaneously. An abandoned refinery near Kamsack, Saskatchewan, characterized by clay-textured soils was sampled and analyzed for PHC fractions (F2 and F3). The probability of a location exceeding a fraction’s remediation criteria was determined using IK and SIS. Based on critical probability thresholds, IK indicated a greater area was contaminated by F2 (6.3%) and F3 (0.8%) than SIS (4.5 and 0.6%, respectively). When the remediation criteria for both F2 and F3 were considered simultaneously, “dependent” and “independent” cases were examined. The dependent case assumed perfect correlation and used the maximum probability of either F2 or F3 as the new estimate. The independent case assumed no correlation and evaluated the probability of F2 > 2500 mg kg–1 or F3 > 6600 mg kg–1. The dependent case resulted in a smaller contaminated area than the independent case in both IK and SIS. On this site the differences between the two methods were small, although IK did smooth the distribution. Key words: Sequential indicator simulation, indicator kriging, geostatics, petroleum hydrocarbon contamination, uncertainty


PLoS ONE ◽  
2016 ◽  
Vol 11 (6) ◽  
pp. e0157201
Author(s):  
Sang-Yeop Lee ◽  
Gun-Hwa Kim ◽  
Sung Ho Yun ◽  
Chi-Won Choi ◽  
Yoon-Sun Yi ◽  
...  

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