Effects of suspended particles and dispersants on marine oil snow formation of crude oil/diesel oil.

Marine oil snow (MOS) potentially forms after an oil spill. To fully understand the mechanism of its formation, we investigated the effects of suspended particles (SP) and dispersants on MOS formation of crude oil and diesel oil by laboratory experiments. In the crude oil experiment, the SP concentration of 0.2 g L-1 was more suitable for crude oil MOS formation. The addition of dispersants significantly stimulated N and TV during MS/MOS formation of SP at 0.4 g L-1 and 0.8 g L-1 concentration (p < 0.05). Without SP, the dispersants also stimulated crude oil MOS formation. Furthermore, the concentration of SP had a significantly positive effect on the reduction of the total amount of N-alkanes (p < 0.05). In the diesel oil experiment, after adding dispersants to diesel oil, the maximum N, Dm, and TV values at a SP concentration of 0.2 g L-1 were significantly higher than those at 0.4 g L-1 and 0.8 g L-1 (p < 0.05). Besides, we found that dispersants stimulated MOS formation in diesel oil at a SP concentration of 0.2 g L-1. However, the dispersants had an inhibitory effect on diesel oil MOS formation without SP. Notably, the MOS formed by diesel oil appeared white, unlike the black MOS associated with crude oil. These findings are important for the environmental impact of oil spills and elevated SP concentrations.

Chemometric techniques in oil spill identification: A case study in Dalian 7.16 oil spill accident of China.

Chemometric methods have unique advantages regarding comprehensive consideration of multiple parameters and the classification of samples or variables. Classification of oil spill sources was carried out by using chemometric techniques, such as Repeatability Limit, hierarchical cluster analysis (HCA), Student's t-test and Principal component analysis (PCA) Biplot. In addition, this paper takes the fingerprint identification of a Dalian "7.16″ oil spill accident as an example to illustrate the effectiveness of chemometric techniques in oil identification. PCA scores plot (explaining 82.77% of variance accounted for three PCs) showed that samples belong to four clusters and result of HCA method further confirmed that. The residual oil in Jinshatan Beach and Haibei Square may be caused by the explosion of Dalian "7-16" oil pipeline accident. The use of chemometric techniques is significant in providing independent validation for classifying the types of spilled oil in the investigation of oil spill pollution. The results will be of great significance to improve the accuracy and efficiency of oil spill identification based on oil fingerprint.

Sparse robust graph-regularized non-negative matrix factorization based on correntropy.

Non-negative Matrix Factorization (NMF) is a popular data dimension reduction method in recent years. The traditional NMF method has high sensitivity to data noise. In the paper, we propose a model called Sparse Robust Graph-regularized Non-negative Matrix Factorization based on Correntropy (SGNMFC). The maximized correntropy replaces the traditional minimized Euclidean distance to improve the robustness of the algorithm. Through the kernel function, correntropy can give less weight to outliers and noise in data but give greater weight to meaningful data. Meanwhile, the geometry structure of the high-dimensional data is completely preserved in the low-dimensional manifold through the graph regularization. Feature selection and sample clustering are commonly used methods for analyzing genes. Sparse constraints are applied to the loss function to reduce matrix complexity and analysis difficulty. Comparing the other five similar methods, the effectiveness of the SGNMFC model is proved by selection of differentially expressed genes and sample clustering experiments in three The Cancer Genome Atlas (TCGA) datasets.

Dual Hyper-Graph Regularized Supervised NMF for Selecting Differentially Expressed Genes and Tumor Classification.

Non-negative matrix factorization (NMF) is a dimensionality reduction technique based on high-dimensional mapping. It can learn part-based representations effectively. In this paper, we propose a method called Dual Hyper-graph Regularized Supervised Non-negative Matrix Factorization (HSNMF). To encode the geometric information of the data, the hyper-graph is introduced into the model as a regularization term. The advantage of hyper-graph learning is to find higher order data relationship to enhance data relevance. This method constructs the data hyper-graph and the feature hyper-graph to find the data manifold and the feature manifold simultaneously. The application of hyper-graph theory in cancer datasets can effectively find pathogenic genes. The discrimination information is further introduced into the objective function to obtain more information about the data. Supervised learning with label information greatly improves the classification effect. Furthermore, the real datasets of cancer usually contain sparse noise, so the L2,1-norm is applied to enhance the robustness of HSNMF algorithm. Experiments under The Cancer Genome Atlas (TCGA) datasets verify the feasibility of the HSNMF method.

Quantitative evaluation of in-situ bioremediation of compound pollution of oil and heavy metal in sediments from the Bohai Sea, China.

Owing to the semi-enclosed environment of the Bohai Sea, the ecological effects caused by an oil spill would be significant. A typical in- situ bioremediation engineering project for of oil-spilled marine sediments was performed in the Bohai Sea and a quantitative assessment of the ecological restoration was performed. The bioremediation efficiencies of n-alkane and PAHs in the sediment are 32.84 ± 21.66% and 50.42 ± 17.49% after 70 days of bioremediation, and 60.99 ± 10.14% and 68.01 ± 18.60% after 210 days, respectively. After 210 days of bioremediation, the degradation rates of two- to three ring PAHs and four-ring PAHs are 84.44 ± 23.03% and 26.62 ± 43.76%, respectively. In addition, the concentrations of the heavy metals first increased by 6.00% due to oil spill degradation and release, and then decreased by 72.60% with the degradation of oil caused by bioremediation or vertical migration. According to the continuous tracking monitoring, the composition of the microbial community in the restored area was similar to that in the control area and the clean area in Bohai Sea after 210 days of bioremediation. These results may provide some theoretical and scientific data to understand the degradation mechanism and assessing the ecological remediation efficiency for oil spills in open sea areas.

Sparse Graph Regularization Non-Negative Matrix Factorization Based on Huber Loss Model for Cancer Data Analysis.

Non-negative matrix factorization (NMF) is a matrix decomposition method based on the square loss function. To exploit cancer information, cancer gene expression data often uses the NMF method to reduce dimensionality. Gene expression data usually have some noise and outliers, while the original NMF loss function is very sensitive to non-Gaussian noise. To improve the robustness and clustering performance of the algorithm, we propose a sparse graph regularization NMF based on Huber loss model for cancer data analysis (Huber-SGNMF). Huber loss is a function between L 1-norm and L 2-norm that can effectively handle non-Gaussian noise and outliers. Taking into account the sparsity matrix and data geometry information, sparse penalty and graph regularization terms are introduced into the model to enhance matrix sparsity and capture data manifold structure. Before the experiment, we first analyzed the robustness of Huber-SGNMF and other models. Experiments on The Cancer Genome Atlas (TCGA) data have shown that Huber-SGNMF performs better than other most advanced methods in sample clustering and differentially expressed gene selection.

Effects of diesel oil spill on macrobenthic assemblages at the intertidal zone: A mesocosm experiment in situ.

The oil spill accidents may drastically impact the environment and ecosystem at intertidal zones. The spilled oil will penetrate the sediments and accumulate to cause lethal or sublethal effects on the benthic invertebrates. An M-BACI experiment was manipulated in situ to assess the ecological responses of benthic macrofauna to different degrees of diesel oil spill. Both biotic and abiotic parameters were studied for 126 days, subjected to both "pulse" and "press" oil contaminations. The content of aliphatic hydrocarbons (displayed as ratios of n-C17/Pr and n-C18/Ph) slightly dropped then continuously existed in the sediment during the experiment time. The macrofaunal assemblage structures were dramatically altered in species number, abundance and biomass. In general, it takes longer time for the macrofauna assemblages to recover under high concentration oil spill than that under low concentration. Our results highlight the diversified strategies for survival and recolonization among dominant species, which distinguish themselves between: i) tolerant species, ii) opportunistic species, and iii) equilibrium species.

Biodegradation of marine oil spill residues using aboriginal bacterial consortium based on Penglai 19-3 oil spill accident, China.

Bioremediation, mainly by indigenous bacteria, has been regarded as an effective way to deal with the petroleum pollution after an oil spill accident. The biodegradation of crude oil by microorganisms co-incubated from sediments collected from the Penglai 19-3 oil platform, Bohai Sea, China, was examined. The relative susceptibility of the isomers of alkylnaphthalenes, alkylphenanthrenes and alkyldibenzothiophene to biodegradation was also discussed. The results showed that the relative degradation values of total petroleum hydrocarbon (TPH) are 43.56% and 51.29% for sediments with untreated microcosms (S-BR1) and surfactant-treated microcosms (S-BR2), respectively. TPH biodegradation results showed an obvious decrease in saturates (biodegradation rate: 67.85-77.29%) and a slight decrease in aromatics (biodegradation rate: 47.13-57.21%), while no significant difference of resins and asphaltenes was detected. The biodegradation efficiency of alkylnaphthalenes, alkylphenanthrenes and alkyldibenzothiophene for S-BR1 and S-BR2 samples reaches 1.28-84.43% and 42.56-86.67%, respectively. The efficiency of crude oil degradation in sediment with surfactant-treated microcosms cultures added Tween 20, was higher than that in sediment with untreated microcosms. The biodegradation and selective depletion is not only controlled by thermodynamics but also related to the stereochemical structure of individual isomer compounds. Information on the biodegradation of oil spill residues by the bacterial community revealed in this study will be useful in developing strategies for bioremediation of crude oil dispersed in the marine ecosystem.

In situ microbial remediation of crude oil-soaked marine sediments using zeolite carrier with a polymer coating.

Marine oil spill pollution is an important environmental problem in the world, especially crude oil-soaked marine sediments, because they are difficult to be remediated. In this study, in situ bioremediation of oil-soaked sediment was performed in the middle of the Bohai Sea. Oil-degrading bacteria were adsorbed on powdery zeolite (PZ)/granular zeolites (GZ) surfaces and then wrapped with poly-γ glutamic acid (γ-PGA). Settling column and wave flume experiments were conducted to model marine conditions and to select appropriate biological reagents. The optimal conditions were as follows: the average diameter of GZ 3 mm, mass ratio of GZ/PZ 2:1, and concentration of γ-PGA 7%. After bioremediation, over 50% of most oil-spilled pollutants n-alkanes (C12 to C27) and polycyclic aromatic hydrocarbons were degraded in 70 days. This work resulted in a successful trial of in situ bioremediation of oil-soaked marine sediments.

Oil mixing behavior after an oil spill: identification conflicts of different fingerprints.

Clearing up whether spilled oil is mixed or not can strengthen the accuracy of oil spill identification. In the present study, the biomarkers in spilled oil samples were detected. The weathering modes of different types of diagnostic ratio and carbon isotope values of individual n-alkanes were also analyzed. The results showed that the diagnostic ratios of steroids, terpenes and aromatics, and weathering characteristics of carbon isotope composition (δ13C) of individual n-alkanes supported the idea that Dalian oil spill emerged from a single oil source. Furthermore, commonly used diagnostic ratios of n-alkanes indicated that the Dalian oil spill had undergone the oil mixing process. The different identifying outcomes indicate that some kinds of n-alkane-rich substance (such as oil dispersants) were mixed in the Dalian spilled oil and interfered with the routine diagnosis ratios of n-alkanes.

Assessing pollution-related effects of oil spills from ships in the Chinese Bohai Sea.

An analysis of the effects of potential oil spills will provide data in support of decisions related to improving the response to oil spills and its emergency management. We selected the Chinese Bohai Sea, especially the Bohai Strait, as our investigation region to provide an assessment of the effects of pollution from ship-related oil spills on adjacent coastal zones. Ship-related accidents are one of the major factors causing potential oil spills in this area. A three dimensional oil transport and transformation model was developed using the Estuary, Coastal, and Ocean Model. This proposed model was run 90 times and each run lasted for 15days to simulate the spread and weathering processes of oil for each of four potential spill sites, which represented potential sites of ship collisions along heavy traffic lanes in the Bohai Sea. Ten neighboring coastal areas were also considered as target zones that potentially could receive pollutants once oil spilled in the study areas. The statistical simulations showed that spills in winter were much worse than those in summer; they resulted in very negative effects on several specific target zones coded Z7, Z8, Z9, and Z10 in this paper. In addition, sites S3 (near the Penglai city) and S4 (near the Yantai city) were the two most at-risk sites with a significantly high probability of pollution if spills occurred nearby during winter. The results thus provided practical guidelines for local oil spill prevention, as well as an emergency preparedness and response program.

Study of weathering effects on the distribution of aromatic steroid hydrocarbons in crude oils and oil residues.

The composition and distribution of triaromatic steroid hydrocarbons in oil residues after biodegradation and photo-oxidation processes were detected, and the diagnostic ratios for oil spill identification were developed and evaluated based on the relative standard deviation (RSD) and the repeatability limit. The preferential loss of C27 methyl triaromatic steranes (MTAS) relative to C28 MTAS and C29 MTAS was shown during the photo-oxidation process. In contrast to the photochemical degradation, the MTAS with the original 20R biological configuration was preferentially degraded during the biodegradation process. The RSD of most of the diagnostic ratios of MTAS ranged from 9 to 84% during the photo-oxidation process. However, the RSDs of such ratios derived from MTAS were all <5% even in high biodegradation, and such parameters may also provide new methods on oil spill identification. The parameters of monoaromatic sterane and monoaromatic sterane are not used well for oil spill identification after photo-oxidation. The triaromatic steroid hydrocarbons retained their molecular compositions after biodegradation and photo-oxidation and most of the diagnostic ratios derived from them could be efficiently used in oil spill identification.

Fingerprint and weathering characteristics of crude oils after Dalian oil spill, China.

In an attempt to analyze the chemical characterization of oil residues and examine the suitability of chemical fingerprinting methods in oil spill investigations, multiple parameters sensitive to both sources and degree of weathering were used to characterize oil residues from "7-16" Dalian oil spill, China. Oil residues collected 90 days to 120 days after the spill showed a weathering pattern where significant amounts of light to middle molecular weight normal alkanes were depleted with pristane and phytane as dominant peaks. Diagnostic ratios developed from n-alkane and selected isoprenoids (e.g. Pr/Ph, n-C17/Pr, n-C18/Ph, carbon preference index, LMW/HMW-alkanes ratio), all display obvious changes over weathering time, indicating that these ratios are not valid for oil source identification. Furthermore, the biomarker ratios of hopanes and steranes with relative standard deviations (RSDs) of 0.88-4.08% were useful for source identification even for severely weathered oil residues. In addition, RSD of δ(13)C values of individual n-alkanes in oil residue varied from 0.07% to 0.20%, which suggest that stable carbon isotope profile of n-alkanes can also be a useful tool for tracing the source of an oil spill.

Chemical characterization of naturally weathered oil residues in the sediment from Yellow River Delta, China.

With its close proximity to Shengli Oilfield, China's second largest oilfield, the Yellow River Delta is at high risk for crude oil contamination. The massive oil discharge in oilfield may offer a chance for a natural experiment to investigate compositional changes of oil residues and study the stability of source- and weathering-dependent molecular parameters in oil residues after spills. The results demonstrate that the conventional diagnostic ratios, such as C2920S/(20S+20R), C29/C30H, C30ßα/αß, C3122S/(22S+22R), C2-DBTs/C2-PHENs, C3-DBTs/C3-PHENs, DBT/MCHRY, CHRY/PHENs, are also valid for oil source identification even after extensive weathering of spilled oils in terrestrial environment, although some exceptions were encountered for extensively weathered sample. Moreover, the ratios of selected specific biomarkers (the oleanane index, the gammacerane index) have been developed and assessed as source indicators. Finally, we find that some maturity parameters based on alkyl naphthalenes and methyl phenanthrenes in petroleum geochemistry, such as the methylnaphthalene ratios (TMNr, TeMNr, PMNr), the methylphenanthrene ratios (MPI-1, MPDF), can be applied for the source identification and correlation at their lightly to moderately weathered stage.

[Geochemical characteristics of radon and mercury in soil gas in Lhasa, Tibet, China].

The geochemical characteristics of radon and mercury in soil gas in Lhasa and vicinity are investigated based on the measurements of Rn and Hg concentrations, and environmental quality for Rn and Hg in soil gas was evaluated by means of the index of geoaccumulation. The data of Rn and Hg of 1 579 sampling site indicate that the values of environmental-geochemical background of Rn and Hg are 7 634.9 Bq/m3, 41.5 ng/m3 with standard deviations of 2.7 Bq/m3, 2.2 ng/m3, respectively. The environmental quality for Rn in soil gas is better in the west and east parts of studied area, but becomes moderate pollution (level III) in the north part of the central area. Rn is derived from radioactive elements in granitic sediments in the intermountain basin and granite base, which are the major sources of pollution. The environmental quality for Hg in soil gas becomes gradually polluted from the suburban to the center of urban, and the highest pollution reaches level IV. The background of Hg in soil gas is mainly controlled by compositions of sediments, but the Hg pollution caused by human waste and religionary use of mercury.