Studies On The Sources, Toxicity And Rapid Detection Of The Soil Pollutants In The Oil Exploitation

The significance of petroleum and natural gas to modern civilization is well known. However, it is inevitable for the oilfield to be contaminated during oil exploitation. These activities of oil industries have led to release of various organic and inorganic pollutants into the soil, air, and water, including trace elements, total petroleum hydrocarbons and polycyclic aromatic hydrocarbons. Numerous studies on the organic pollutants released into the water environment by oil and gas industries have been reported and a few researches focus on the contamination in soils generated by oil exploration and exploitation. The situation is worsening and already represents a threat to the environment, to food safety and to sustainable agriculture. In some areas of China, soil already suffers from varying degrees of pollution. Soil contamination has become one of the most pressing problems in our society.In this study, a terrestrial oilfield was selected for the study of soil pollution. The contents of the typical soil pollutants were detected; the distribution of the typical soil pollutants were studied; grade division for soil pollutions were evaluated; the relationship between soil biotoxicity and contents of the typical soil pollutants were modeled; the source of the typical soil pollutants were identified and apportioned; and the rapid detection methods of the typical soil pollutants were developed.A method for extraction and separation of petroleum hydrocarbons (PHs) and polycyclic aromatic hydrocarbons (PAHs) from heavy oil-polluted soil was established. Effects of several factors such as ultrasonic power, temperature, and elution solvents on the extraction were investigated. The experimental results indicated the optimal experimental conditions were obtained as follows:300watt of ultrasonic power,0℃of extraction solvents, n-hexane and dichloromethane/n hexane (1:1, v/v) used as elution solvents. Then12heavy metals (Pb, Cd, Cu, Zn, Ni, Cr, Co, Sb, Fe, Mn, Ag, and Ba) and16PAHs and PHs were tested, and all of them were detected except the silver and barium.The distribution of the typical soil pollutants from the terrestrial petroleum exploitation in horizonal, longitudinal, severce years, mining types, and individual oil wells were investgated by statistical analysis and geographic information systems (GIS). The distributions of the typical soil pollutants (heavy metals, PHs, PAHs) were not significant different in longitudinal (the level of significance is0.05in0-50cm). In horizontal (0-30m), the PAHs contents in soils decrease with increasing distance from the well, the heavy metals increase with increasing distance from0to6m and then decrease with the increase in distance, but the difference was not significant in the95%confidence interval. The distributions of all the typical soil pollutants were significantly different in various oil wells (the level of significance is0.05), the PAHs contents in soils of polymer flooding wells were significantly higher than the water flooding wells, on the contrary, the heavy metals contents in soils of water flooding wells were significantly higher than the polymer flooding wells, and the contents of heavy metals and PAHs were significantly increased with the increase in severe years.The linear regression model and logarithmic fitting model were developed to simulate the concentrations of PHs and the contents of Total Organic Carbon (TOC) in the soil by comparing the different regression models. The determination coefficients (R2) for linear regression model and logarithmic fitting model were0.715and0.874, respectively. The relative average deviations for the predictive values were9.2%and3.3%in a validation data set of14, with the Nash-Sutcliffe simulation efficiency coefficients (NSC) of0.957for the linear regression model and0.959for the logarithmic fitting model. The established models could also provide some information for the application of spectroscopy and remote-sensing technology in the monitoring of petroleum hydrocarbons.The relationship between soil biotoxicity and ten heavy metals (Pb, Cd, Cu, Zn, Ni, Cr, Co, Sb, Fe, and Mn) in an oilfield from China was investigated through multivariable analysis. Multiple regression analysis was conducted to predict the toxicity of the ten heavy metals after mitigated the multicollinearity among the metals by principal component analysis. A multiple regression model was developed to reveal the relationship between the biotoxicity and the contents of ten heavy metals. It was found that the biotoxicity positive correlated with contents of Zn, Ni, Cr, Sb, Fe, and Mn, and negative correlated with contents of Cd, Co, Pb, and Cu. According to the multiple regression model, the contribution to the biotoxicity of the heavy metals in soils was in the order of Cr>Ni>Mn>Sb>Zn>Fe, and a negative influence on the biotoxicity was caused by other four heavy metals, following the order of Cd, Co, Pb, and Cu.The potential interactions of ten heavy metals (Pb, Cd, Cu, Zn, Ni, Cr, Co, Sb, Fe and Mn) on soil biotoxicity were also investigated using a modified principal component regression (MPCR) model in an oilfield in China. Principal component analysis (PCA) was used to mitigate the multicollinearity, and an Expectation-Maximisation (EM) algorithm was applied as a missing value treatment to make the principal components readily interpretable. It was found that the MPCR can be used to model the interaction between heavy metals in the biotoxicity analysis of the oilfield soil. According to the modified PCR model, the Cu acts as a micronutrient in the soil for the activities of luminescent marine bacteria (Photobacterium phosphoreum), and the other nine metals have a toxic effect on the bacteria. Additionally, the interactions of metals between Co-Zn, Co-Cu, Co-Cd, Cu-Pb, Cd-Sb, Pb-Zn and Pb-Cd can be described as antagonistic, while the interactions between Co-Ni, Co-Cr, Co-Sb, Co-Pb, Cu-Sb, Cu-Cd, Cd-Ni, Cd-Fe, Pb-Cr and Pb-Sb can be described as synergistic.Sources of the heavy metals and PAHs in soil from the terrestrial petroleum exploitation were identified by isotope ratios, correlation analysis and multivariate statistical analysis (factor analysis and cluster analysis), and the contribution rate of the main source of the typical soil pollutants were calculated by factor regression analysis. The result showed that the main sources for heavy metals in soil from the terrestrial petroleum exploitation were natural source, traffic source, mixed source, coal-fired source, petroleum source and agricultural source, and their relative contributions were37%,19%,18%,16%,5%and5%; while the major PAHs source was petroleum source with the relative contribution of35%, followed by biological source which account for20%, coal-fired source for17%, and traffic source for16%.Preliminary study found that the test based on the Raman spectra of polycyclic aromatic hydrocarbons can be applied to the identification of pure polycyclic aromatic hydrocarbons in solid, but not suitable for the direct detection of polycyclic aromatic hydrocarbons used in the soil samples.The condition of the ultrasound-assisted dispersive liquid-liquid, micro-extraction method based on solidification of floating organic drop (UAE/DLLME/SFO) technique for PAHs in soils were designed by central composite design, and optimized by the response surface plot. The ideal conditions were extractant (dodecanol) volume52.4μL, emulsifier (methanol) volume1.08mL, weight of the soil0.54g, salt effect (contain of NaCl)3.1%, ultrasonic time3.1min, ultrasonic power59kw. The optimized results of the recoveries were9.12-94.91%, with the relative standard deviation (RSD) of1.07-7.87%. Under the selected conditions, the linear range of PAHs was0.02-0.5, with the limits of detection of0.17-29.13μg/L and the correlation coefficient ranged from0.9950to0.9999.The author hopes this paper would provide the basis for the establishment of the HSE (Health, Safety and Environment) management system in China's petroleum mining industry, and improve management level of the modern oil companies, as well as the cleaner production and sustainable development.