Remediation Of Crude Oil Polluted Soil Research Articles

Modelling and Optimizing the Effect of pH on Remediation of Crude Oil Polluted Soil with Biochar Blend: RSM Approach

This research modelled the effect of pH on the remediation of crude oil-polluted soil using biochar blend. The biochar blends, PL-500, pW-500, and RS-400, were made by pyrolyzing poultry litter, pine wood, and rice straw at varied temperatures and times. The pH of the crude oil polluted soil was 4.72. Response surface experimental design mixed biochar to remediate total petroleum hydrocarbons (TPH). Following 30 days of bioremediation, 15g PL-500, 3g PW-500 and 6g RS-400, removed a maximum of 46% TPH. The experimental data were statistically modelled and optimized using design expert software and response surface methods. Analysis of variance (ANOVA) was used to determine the significance of each regression coefficient. Biochar blend improved soil pH to 6.9 following remediation. ANOVA indicated that PL-500 was significant for predicting TPH % degradation at p =0.0290, suggesting that its high pH, nutrient, and soil water conservation values made it more effective in remediating TPH. The quadratic model predicts with R2 =0.8567. A model fit statistics were used to examine soil pH influence on TPH remediation. RSM study indicated a good positive association between statistical model and experiment with R2 = 0.7612. The model fits experimental data and predicts that . Remediation requires soil pH and biochar's alkalinity raised soil pH to 6.9, which promoted hydrocarbon-utilizing bacteria.

Remediation of Crude Oil-Polluted Soil by the Bacterial Rhizosphere Community of Suaeda salsa Revealed by 16S rRNA Genes.

Crude oil pollution of soil is a serious environmental issue, and bioremediation using plants and microorganisms is a natural and sustainable method for its restoration. Pot incubation of a two-factor randomized block (plants with two levels, and crude oil with three levels) was designed to investigate the rhizosphere bacterial community of Suaeda salsa (L.) Pall. Crude oil contamination of soil was studied at different levels: 2 g/kg (low), 4 g/kg (medium), and 6 g/kg (high) levels. In this study, the physicochemical properties of the collected rhizosphere soil were analyzed. Moreover, the soil bacteria were further identified using the 16S rRNA gene. The effects of S. salsa and crude oil and their interaction on the physiochemical properties of the soil and crude oil degradation were found to be significant. Crude oil significantly influenced the diversity and evenness of bacteria, while the effects of S. salsa and interaction with crude oil were not significant. Proteobacteria were found to be dominant at the phylum level. Meanwhile, at the genera level, Saccharibacteria and Alcanivorax increased significantly in the low and medium contamination treatment groups with S. salsa, whereas Saccharibacteria and Desulfuromonas were prevalent in the high contamination treatment group. High crude oil contamination led to a significant decrease in the bacterial diversity in soil, while the effects of S. salsa and its interaction were not significant. Despite the highest abundance of crude oil degradation bacteria, S. salsa reduced crude oil degradation bacteria and increased bacteria related to sulfur, phosphorus, and nitrogen cycling in the low and high contamination group, whereas the opposite effect was observed for the medium contamination treatment group. The abundance of most crude oil degradation bacteria is negatively correlated with crude oil content. Nitrogen cycling bacteria are sensitive to the total nitrogen, total phosphorus, ammonia nitrogen, and nitrate nitrogen, and pH of the soil. Sulfur cycling bacteria are sensitive to aromatic hydrocarbons, saturated hydrocarbons, and asphaltene in soil. This research is helpful for further studying the mechanism of synergistic degradation by S. salsa and bacteria.

Optimization of reed-specific degrading bacteria by response surfaces for remediation of crude oil-polluted soil in Xinjiang, China

This paper discussed the optimization of conditions for remediation of crude oil-polluted soil based on pot experiment by applying reed-specific degrading bacteria, and using response surfaces methodology. We took the initial crude oil concentration, the amount of inoculation, the ratio of nitrogen and phosphorus, and the use of surfactant (Tween-80) as independent variables (factors), and the degrading ratio of crude oil as the dependent variable (response) after a 90-day experiment. The experiment explored the impacts of each independent variable and their interactions on the bioremediation of crude oil-polluted soil using the Box-Behnken design. Working with a simulated forecasting model the study obtained optimization values for the treatment parameters of 200 g/kg of the reed+specific degrading bacteria, a nitrogen to phosphorus ratio of about 6.0, and 0.2% surfactant. Under experimental conditions, for crude oil concentrations of 10, 30 and 50 g/kg, the optimal effects of the treatments achieved 71.87%, 66.61% and 54.52% degradation of the crude oil, respectively. The results can provide a basis for the technical development of plant-microorganism combined bioremediation of crude oil-polluted soil.