Improved strategies for oil-spill remediation will follow a better understanding of the nature, activities and regulating parameters of petroleum hydrocarbon-degrading microbial communities in temperate marine environments. The addition of crude oil to estuarine water resulted in an immediate change in bacterial community structure, increased abundance of hydrocarbon-degrading microorganisms and a rapid rate of oil degradation, suggesting the presence of a pre-adapted oil-degrading microbial community and sufficient supply of nutrients. Relatively rapid degradation was found at 4 degrees C, the lowest temperature tested; and it was temperature rather than nutrient addition that most influenced the community structure. A detailed phylogenetic analysis of oil-degrading microcosms showed that known hydrocarbonoclastic organisms like Thalassolituus and Cycloclasticus, as well as proposed oil degraders like Roseobacter, were present at both 4 degrees C and 20 degrees C, demonstrating the thermo-versatility of such organisms. Clones related to Oleispira antarctica (98% 16S rRNA similarity), a psychrophilic alkane degrader, were dominant in the 4 degrees C oil-degrading community, whereas other clones constituting a different clade and showing 94% similarity 16S rRNA with O. antarctica were found in situ. These findings demonstrate the potential for intrinsic bioremediation throughout the course of the year in temperate estuarine waters, and highlight the importance of both versatile psychrotolerant and specialized psychrophilic hydrocarbon-degrading microbes in effecting this process at low temperatures.

Crude oil is a complex mixture of different hydrocarbons. While diverse bacterial communities can degrade oil, the specific roles of individual members within such communities remain unclear. To identify the key bacterial taxa involved in aerobic degradation of specific hydrocarbons, microcosm experiments were established using seawater from Stanford le Hope, Thames estuary, UK, adjacent to a major oil refinery. In all microcosms, hydrocarbon degradation was significant within 10 weeks, ranging from > 99% of low-molecular-weight alkanes (C(10)-C(18)), 41-84% of high-molecular-weight alkanes (C(20)-C(32)) and pristane, and 32-88% of polycyclic aromatic hydrocarbons (PAHs). Analysis of 16S rRNA sequences from clone libraries and denaturing gradient gel electrophoresis (DGGE) indicated that, except when incubated with fluorene, PAH-degrading communities were dominated by Cycloclasticus. Moreover, PAH-degrading communities were distinct from those in microcosms containing alkanes. Degradation of the branched alkane, pristane, was carried out almost exclusively by Alcanivorax. Bacteria related to Thalassolituus oleivorans (99-100% identity) were the dominant known alkane degraders in n-alkane (C(12)-C(32)) microcosms, while Roseobacter-related bacteria were also consistently found in these microcosms. However, in contrast to previous studies, Thalassolituus, rather than Alcanivorax, was dominant in crude oil-enriched microcosms. The communities in n-decane microcosms differed from those in microcosms supplemented with less volatile alkanes, with a phylogenetically distinct species of Thalassolituus out-competing T. oleivorans. These data suggest that the diversity and importance of the genus Thalassolituus is greater than previously established. Overall, these experiments demonstrate how degradation of different petroleum hydrocarbons is partitioned between different bacterial taxa, which together as a community can remediate petroleum hydrocarbon-impacted estuarine environments.

There is little information on how different strategies for the bioremediation of marine oil spills influence the key indigenous hydrocarbon-degrading bacteria (hydrocarbonoclastic bacteria, HCB), and hence their remediation efficacy. Therefore, we have used quantitative polymerase chain reaction to analyse changes in concentrations of HCB in response to intervention strategies applied to experimental microcosms. Biostimulation with nutrients (N and P) produced no measurable increase in either biodegradation or concentration of HCB within the first 5 days, but after 15 days there was a significant increase (29%; P < 0.05) in degradation of n-alkanes, and an increase of one order of magnitude in concentration of Thalassolituus (to 10(7) cells ml(-1)). Rhamnolipid bioemulsifier additions alone had little effect on biodegradation, but, in combination with nutrient additions, provoked a significant increase: 59% (P < 0.05) more n-alkane degradation by 5 days than was achieved with nutrient additions alone. The very low Alcanivorax cell concentrations in the microcosms were hardly influenced by addition of nutrients or bioemulsifier, but strongly increased after their combined addition, reflecting the synergistic action of the two types of biostimulatory agents. Bioaugmentation with Thalassolituus positively influenced hydrocarbon degradation only during the initial 5 days and only of the n-alkane fraction. Bioaugmentation with Alcanivorax was clearly much more effective, resulting in 73% greater degradation of n-alkanes, 59% of branched alkanes, and 28% of polynuclear aromatic hydrocarbons, in the first 5 days than that obtained through nutrient addition alone (P < 0.01). Enhanced degradation due to augmentation with Alcanivorax continued throughout the 30-day period of the experiment. In addition to providing insight into the factors limiting oil biodegradation over time, and the competition and synergism between HCB, these results add weight to the use of bioaugmentation in oil pollution mitigation strategies.

This study aimed to develop a novel framework for risk assessment of nitrate groundwater contamination by integrating chemical and statistical analysis for an arid region. A standard method was applied for assessing the vulnerability of groundwater to nitrate pollution in Lenjanat plain, Iran. Nitrate concentration were collected from 102 wells of the plain and used to provide pollution occurrence and probability maps. Three machine learning models including boosted regression trees (BRT), multivariate discriminant analysis (MDA), and support vector machine (SVM) were used for the probability of groundwater pollution occurrence. Afterwards, an ensemble modeling approach was applied for production of the groundwater pollution occurrence probability map. Validation of the models was carried out using area under the receiver operating characteristic curve method (AUC); values above 80 percent were selected to contribute in ensembling process. Results indicated that accuracy for the three models ranged from 0.81 to 0.87, therefore all models were considered for ensemble modeling process. The resultant groundwater pollution risk (produced by vulnerability, pollution, and probability maps) indicated that the central regions of the plain have high and very high risk of nitrate pollution further confirmed by the exiting landuse map. The findings may provide very helpful information in decision making for groundwater pollution risk management especially in semi-arid regions.

The bacterial diversity of a chronically oil-polluted retention basin sediment located in the Berre lagoon (Etang-de-Berre, France) was investigated. This study combines chemical and molecular approaches in order to define how the in situ petroleum hydrocarbon contamination level affects the bacterial community structure of a subsurface sediment. Hydrocarbon content analysis clearly revealed a gradient of hydrocarbon contamination in both the water and the sediment following the basin periphery from the pollution input to the lagoon water. The nC17 and pristane concentrations suggested alkane biodegradation in the sediments. These results, combined with those of terminal-restriction fragment length polymorphism analysis of the 16S rRNA genes, indicated that bacterial community structure was obviously associated with the gradient of oil contamination. The analysis of bacterial community composition revealed dominance of bacteria related to the Proteobacteria phylum (Gamma-, Delta-, Alpha-, Epsilon- and Betaproteobacteria), Bacteroidetes and Verrucomicrobium groups and Spirochaetes, Actinobacteria and Cyanobacteria phyla. The adaptation of the bacterial community to oil contamination was not characterized by dominance of known oil-degrading bacteria, because a predominance of populations associated to the sulphur cycle was observed. The input station presented particular bacterial community composition associated with a low oil concentration in the sediment, indicating the adaptation of this community to the oil contamination.

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Visible and near infrared spectrometry (vis-NIRS) coupled with data mining techniques can offer fast and cost-effective quantitative measurement of total petroleum hydrocarbons (TPH) in contaminated soils. Literature showed however significant differences in the performance on the vis-NIRS between linear and non-linear calibration methods. This study compared the performance of linear partial least squares regression (PLSR) with a nonlinear random forest (RF) regression for the calibration of vis-NIRS when analysing TPH in soils. 88 soil samples (3 uncontaminated and 85 contaminated) collected from three sites located in the Niger Delta were scanned using an analytical spectral device (ASD) spectrophotometer (350-2500nm) in diffuse reflectance mode. Sequential ultrasonic solvent extraction-gas chromatography (SUSE-GC) was used as reference quantification method for TPH which equal to the sum of aliphatic and aromatic fractions ranging between C and C. Prior to model development, spectra were subjected to pre-processing including noise cut, maximum normalization, first derivative and smoothing. Then 65 samples were selected as calibration set and the remaining 20 samples as validation set. Both vis-NIR spectrometry and gas chromatography profiles of the 85 soil samples were subjected to RF and PLSR with leave-one-out cross-validation (LOOCV) for the calibration models. Results showed that RF calibration model with a coefficient of determination (R) of 0.85, a root means square error of prediction (RMSEP) 68.43mgkg, and a residual prediction deviation (RPD) of 2.61 outperformed PLSR (R=0.63, RMSEP=107.54mgkg and RDP=2.55) in cross-validation. These results indicate that RF modelling approach is accounting for the nonlinearity of the soil spectral responses hence, providing significantly higher prediction accuracy compared to the linear PLSR. It is recommended to adopt the vis-NIRS coupled with RF modelling approach as a portable and cost effective method for the rapid quantification of TPH in soils.

Human exposure to lead (Pb) is a growing global public health concern. Elevated blood lead is thought to cause the mental retardation of >0.6 million children globally each year, and has recently been attributed to ~18% of all-cause mortality in the US. Due to the severe health risk, the international community, led by the United Nations Environment Programme (UNEP) and the World Health Organization (WHO), is actively supporting the global phase-out of lead-based paint by 2020. However, there are many significant hurdles on the way to achieving this goal. In light of the importance of the lead-based paint issue, and the urgency of achieving the 2020 phase-out goal, this review provides critical insights from the existing scientific literature on lead-based paint, and offers a comprehensive perspective on the overall issue. The global production and international trade of lead-based paints across Asia, Africa, Latin America, and Europe are critically discussed - revealing that lead-based paints are still widely used in many low and middle-income developing countries, and that the production and trade of lead-based paint is still wide-spread globally. In India, as well as many south-east Asian, African, Latin American and European countries, lead concentrations in paints often exceed 10,000 mg/kg. This will certainly pose a serious global threat to public health from surfaces painted with these products for many decades to come. The sources and pathways of exposure are further described to shed light on the associated health risk and socioeconomic costs. Finally, the review offers an overview of the potential intervention and abatement strategies for lead-based paints. In particular, it was found that there is a general lack of consensus on the definition of lead based paint; and, strengthening regulatory oversight, public awareness, and industry acceptance are vital in combating the global issue of lead based paint.