[Microbial community structure and distribution characteristics in oil contaminated soil].

Molecular biology methods such as PCR-DGGE combined with phylogenetic analysis were used for the soil microbial community structure and distribution profiling. Relationship of microbial community structure and distribution differed in a typical oil contaminated field was studied. Results showed that soil oil content was the main factor to the difference of microbial community structure similarity. The similarity index of microbial community structure and oil content had a significantly negative correlation. The contaminated soil microorganism genus had an uneven distribution. Thus, soil pollution had obvious stress and differentiation for microbial community structure and species relationship. Dominant species in oil contaminated soil were identified as Gulosibacter, Halomonas, Petrobacter, Methylocystis, and Pseudoalteromonas. The findings provide a basis for understanding the microbial characteristics of oil contaminated soil.

[Compositions and diagnostic ratios of heavily degraded crude oil residues in contaminated soil in oilfields].

The aims of this study were to determine the rate of degradation of crude oil in soil, to reveal the fingerprints of residual oil after long-term biodegradation, and to screen parameters for evaluation of the biodegradability residual oil. A total of 18 contaminated soil samples containing heavily degraded crude oil residuals from Daqing, Shengli and Baise oilfields were analyzed. More than 100 individual target compounds including straight-and branched-chain alkanes (n-alkanes, pristane and phytane), polycyclic aromatic hydrocarbons (PAHs), terpanes, steranes and triaromatic steranes (TAS) in residual oil were determined by gas chromatography-mass spectrometry (GC-MS). For all the soil samples, less than 10% and 30% of alkanes and PAHs remained in the residual oils relative to crude oils. Terpanes, steranes and TAS were found to be less biodegradable. Depletions decreased with increasing carbon number of n-alkanes. However, average depletions > 80% were found in n-alkanes with carbon numbers < 37. Average depletions were > 70% for 2-4 ring PAHs, while 5-6 ring PAHs were more resistant. Increase in alkylation level decreased depletion within homologues of naphthalene, phenanthrene, chrysene and Benzo[e] pyrene. GC-MS could only reveal less than 3% of the compounds of residual oils, which were mainly comprised of n-alkanes with carbon number > 20, alkylated naphthalenes and phenanthrenes, terpanes, steranes and TAS. Based on compositional characteristics of alkanes and PAHs in residual oils, 6 diagnostic ratios, which were ratios of susceptible compounds to resistant compounds or to the amounts residual oil, were proposed as the parameters for characterization of residual oils and determining the biodegradability of oils contaminated soils.

[Microbial community constitute and phylogenetic analysis on oil polluted soils in oilfields of China].

The microbial communities in oil polluted soils from oilfields of China were analyzed using a modern molecular biological approach. The crude total DNA from soils were directly extracted, 16S rDNA fraction were amplified by PCR, the bands were separated using denaturing gradient gel electrophoresis (DGGE), and some of the typical bands were sequenced and compared with the records of NCBI to classify the germs. Comparison of the DNA extraction indicated that the yields were 1.4-2.2 times as much as the existing technique, and the DNA purity reached 1.8-2.0. With higher similarity and correlation in CQ and DQ oilfields but lower in that of SL and YM oilfields, the influence factors to microbial communities consisted in the elementary properties of soil samples such as oil contents, water ratio, etc. Extraction and sequencing analysis of selected 16S rDNA bands demonstrated a range of similarity of 89%-100% to reference bacteria. The Shannon-Weiner index of the oil contaminated soils was 0.5-1.2, and which was increased slightly along with the enhancement of microbial amounts and FDA activities. According to this research, it has possibility in developing a reliable tool for researching oil contaminated soil bacteria diversity, and in applying a credible foundation for adjusting the microbial ecosystem and determining the dominant community in contaminated soils in oilfields.

Sensitivity of key factors and uncertainties in health risk assessment of benzene pollutant.

Predicting long-term potential human health risks from contaminants in the multimedia environment requires the use of models. However, there is uncertainty associated with these predictions of many parameters which can be represented by ranges or probability distributions rather than single value. Based on a case study with information from an actual site contaminated with benzene, this study describes the application of MMSOILS model to predict health risk and distributions of those predictions generated using Monte Carlo techniques. A sensitivity analysis was performed to evaluate which of the random variables are most important in producing the predicted distributions of health risks. The sensitivity analysis shows that the predicted distributions can be accurately reproduced using a small subset of the random variables. The practical implication of this analysis is the ability to distinguish between important versus unimportant random variables in terms of their sensitivity to selected endpoints. This directly translates into a reduction in data collection and modeling effort. It was demonstrated that how correlation coefficient could be used to evaluate contributions to overall uncertainty from each parameter. The integrated uncertainty analysis shows that although drinking groundwater risk is similar with inhalation air risk, uncertainties of total risk come dominantly from drinking groundwater route. Most percent of the variance of total risk comes from four random variables.

[Uncertainty analysis of health risk assessment caused by benzene contamination in a contaminated site].

Lots of uncertainties lie in the procedure of environmental risk assessment (ERA) and how to analyze them exactly is studied comprehensively. Based on the investigation of petroleum contamination in a contaminated site, the representative benzene contaminant in soil was selected to analyze uncertainty of environmental risk resulting from drinking and inhalation exposure routes, using the Monte-Carlo simulations. According to the analysis results, the total health risk average value caused by benzene contamination from the alkene factory is 1.18 x 10(-4) for the people living on the district A, which is more than the risk limit of U.S. EPA 10(-6) and means contamination hazard to health. In four different areas of the alkene factory, the main source of risk comes from the cracking equipments with 1.17 x 10(-4). With the impact factors of the uncertainty, the contamination harm to the human health's probability is different referring to the different risk level, which is a criteria value meaning no harm to health issued by different institution. The study results provide an important foundation of effective control and remediation actions of contaminated sites.

[Removal of oil in the lake water in Daqing area using subsurface constructed wetland].

Based on the water quality and climate of the oil contaminated lake in Daqing area, four simulated subsurface wetland systems were constructed in the field to study their removal effect of oil in lake water, including the gravel bed, the gravel-reed bed, the slag-reed bed and the slag bed. The research lasted about 360 d, including five periods: the start up period, the microorganism adding period, the slow-releasing carbon sources adding period, the low temperature period and the normal operation period. During the study, oil removal efficiency of the four units are 24.7%,28.4%, 45.9% and 42.9% respectirely, and the slag unit shows better than gravel unit. The adding of microorganism and slow-releasing carbon sources markedly improves the oil removal. The application of plant in the wetland system also promotes the oil removal. In all the four simulated subsurface wetland systems, 70% of the oil removal attributes to the adsorption effect.

Production of biosurfactant and its role in the biodegradation of oil hydrocarbons.

Based on indigenous bacteria from the oil-contaminated site of Dawu water source area in Zibo city of China, the production of biosurfactant and its role in the biodegradation of oil hydrocarbons have been investigated. Batch experiments were performed with paraffin as the sole substrate under temperature of 30 degrees C and pH of 7. Two high-effective species of bacteria (Z1 and Z2) were isolated. During the growth of both species, biosurfactants were produced, as indicated by the decrease of surface tensions of the enrichment medium from 61 to 45 mN/m. The critical micelle concentration (CMC) of Z1 ferment liquid was 0.4 (volume content). When reaching the CMC, Z1 ferment liquid demonstrated the effect of dissolution enhancement, that is, it could enhance the dissolved concentration of phenanthrene to above 1 mg/L, which was higher than the saturated solubility of phenanthrenene under standard condition. Elementary identification results revealed that both Z1 and Z2 belongs to bacillus. Z1 was 0.5 microm in diameter, 0.5-3 microm in length, and bearing flagellum, while Z2 was 0.2 microm in diameter, 0.5-1 microm in length and no flagellum.

Volatile fatty acids as electron donors for the reductive dechlorination of chloroethenes.

Uses of a mixture of six volatile fatty acids (VFAs) including acetic, propionic, butyric, isobutyric, valeric and isovaleric acids as electron donors for the reductive dechlorination of chloroethenes have been investigated by both microcosm and column studies. The fates of tetrachloroethene (PCE), cis-dichloroethene (cis-DCE) and vinyl chloride (VC) in the presence of VFAs and in the absence of VFAs were respectively documented. The results showed that VFAs stimulated complete reductive dechlorination of chloroethenes, either as direct substrates for the dechlorinating bacteria or via H2 formed during VFAs-degradation. There were sequential utilizations of different VFAs by fermenting bacteria. In the microcosm, propionic acid was the first to be used, followed by acetic, butyric, isobutyric, valeric, and isovaleric acids, and their mean first-order degradation rates obtained were 0.128, 0.048, 0.016, 0.027, 0.025 and 0.003 day(-1), respectively. In the column, propionic acid was the first to be used, followed by butyric and valeric acids, and their calculated first-order degradation rates were 0.833, 0.403 and 0.260 day(-1), respectively.