The vertical distribution of plutonium 241Pu in marine sediments can assist in determining the deposition history and sedimentation process of analyzed regions. In addition, 241Pu/239+240Pu activity ratio could be used as a sensitive fingerprint for radioactive source identification. The present preliminary studies on vertical distribution of 241Pu in sediments from four regions of the southern Baltic Sea are presented. The distribution of 241Pu was not uniform and depended on sediment geomorphology and depth as well as location. The highest concentrations of plutonium were found in the surface layers of all analyzed sediments and originated from the Chernobyl accident.

A flexible 2D/3D oil spill modeling system addressing the distinct nature of the surface and water column fluids, major oil weathering and improved retention/reposition processes in coastal zones is presented. The system integrates hydrodynamic, transport and oil weathering modules, which can be combined to offer different-complexity descriptions as required by applications across the river-to-ocean continuum. Features include accounting for different composition and reology in the surface and water column mixtures, as well as spreading, evaporation, water-in-oil emulsification, shoreline retention, dispersion and dissolution. The use of unstructured grids provides flexibility and efficiency in handling spills in complex geometries and across scales. The use of high-order Eulerian–Lagrangian methods allows for computational efficiency and for handling key processes in ways consistent with their distinct mathematical nature and time scales. The modeling system is tested through a suite of synthetic, laboratory and realistic-domain benchmarks, which demonstrate robust handling of key processes and of 2D/3D couplings. The application of the modeling system to a spill scenario at the entrance of a port in a coastal lagoon illustrates the power of the approach to represent spills that occur in coastal regions with complex boundaries and bathymetry.

Genome resources have advantages for understanding diverse areas such as biological patterns and functioning of organisms. Omics platforms are useful approaches for the study of organs and organisms. These approaches can be powerful screening tools for whole genome, proteome, and metabolome profiling, and can be used to understand molecular changes in response to internal and external stimuli. This methodology has been applied successfully in freshwater model fish such as the zebrafish Danio rerio and the Japanese medaka Oryzias latipes in research areas such as basic physiology, developmental biology, genetics, and environmental biology. However, information is still scarce about model fish that inhabit brackish water or seawater. To develop the self-fertilizing killifish Kryptolebias marmoratus as a potential model species with unique characteristics and research merits, we obtained genomic information about K. marmoratus. We address ways to use these data for genome-based molecular mechanistic studies. We review the current state of genome information on K. marmoratus to initiate omics approaches. We evaluate the potential applications of integrated omics platforms for future studies in environmental science, developmental biology, and biomedical research. We conclude that information about the K. marmoratus genome will provide a better understanding of the molecular functions of genes, proteins, and metabolites that are involved in the biological functions of this species. Omics platforms, particularly combined technologies that make effective use of bioinformatics, will provide powerful tools for hypothesis-driven investigations and discovery-driven discussions on diverse aspects of this species and on fish and vertebrates in general.

We assessed the effects of 17α-ethinylestradiol (EE2) on spawning and reproductive behavior of the brackish medaka Oryzias melastigma at environmental concentrations. Breeding pairs were exposed to EE2 at either lower concentrations (0, 1, and 10ng/L) or higher concentrations (0, 50, and 100ng/L) for 14days. Swimming performance and reproductive behavior (following, dancing, and copulation) of the males were analyzed at the end of exposure. Additionally, gonad histology was conducted in the males in the higher EE2 experiment. We found that spawning was significantly inhibited in the 50–100ng/L EE2 groups. Swimming performance was not affected in all groups. Dancing and copulation were significantly suppressed in the 50–100ng/L groups. No effect was observed in testis histology in the 50–100ng/L groups. Our data suggests that reproductive behavior of O. melastigma can be utilized as a behavioral endpoint for ecotoxicology studies of endocrine disruptors in estuarine/marine environments.

Concentrations of heavy metals in river water and sediment were investigated in nine estuaries along the coast of Bohai Bay, Northern China. Multivariate statistical techniques such as principal component analysis and cluster analysis, in combination with metal concentration analysis and correlation analysis, were used to identify the possible sources of the metals and the pollution pattern in nine estuaries along the coast of Bohai Bay. The environmental risks of metals, evaluated by sediment quality guidelines and background values, revealed Hg contamination in the estuaries. However, levels of Cd in estuarine sediments were low, and they were less than those levels in river sediments, partly due to the high mobility and dilution of river or seawater. Cd did not contribute to sediment deposits in estuaries. High organic matter from effluents from large municipal sewage treatment plants was predominantly responsible for restricting Hg mobility from the river to Bohai Bay.

Drinking water shortage has become worse in recent decades. A new capacitive deionization (CDI) method for increasing water supplies through the effective desalination of seawater has been developed. Silver as nano Ag and Ag@C which was prepared by carbonization of the Ag+-β-cyclodextrin complex at 573K for 30min can add the antimicrobial function into the CDI process. The Ag@C and Ag nanoparticles dispersed on reduced graphene oxide (Ag@C/rGO and nano Ag/rGO) were used as the CDI electrodes. The nano Ag/rGO and Ag@C/rGO electrodes can reduce the charging resistant, and enhance the electrosorption capability. Better CDI efficiencies with the nano Ag/rGO and Ag@C/rGO electrodes can therefore be obtained. When reversed the voltage, the electrodes can be recovered up to 90% within 5min. This work presents the feasibility for the nano Ag and Ag@C on rGO electrodes applied in CDI process to produce drinking water from seawater or saline water.

Little attention is given to applying the artificial neural network (ANN) modeling technique to understand site–specific air pollution dispersion mechanisms, the order of importance of meteorological variables in determining concentrations as well as the important time scales that influence emission patterns. In this paper, we propose a methodology for extracting the key information from routinely–available meteorological parameters and the emission pattern of sources present throughout the year (e.g. traffic emissions) to build a reliable and physically–based ANN air pollution forecasting tool. The methodology is tested by modeling NO2 concentrations at a site near a major highway in Auckland, New Zealand. The basic model consists of an ANN model for predicting NO2 concentrations using eight predictor variables: wind speed, wind direction, solar radiation, temperature, relative humidity, as well as “hour of the day”, “day of the week” and “month of the year” representing the time variations in emissions according to their corresponding time scales. Of the three input optimization techniques explored in this study, namely a genetic algorithm, forward selection, and backward elimination, the genetic algorithm technique gave predictions resulting in the smallest mean absolute error. The nature of the internal nonlinear function of the trained genetically–optimized neural network model was then extracted based on the response of the model to perturbations to individual predictor variables through sensitivity analyses. A simplified model, based on the successive removal of the least significant meteorological predictor variables, was then developed until subsequent removal resulted in a significant decrease in model performance. The developed ANN model was found to outperform a linear regression model based on the same input parameters. The proposed approach illustrates how the ANN modeling technique can be used to identify the key meteorological variables required to adequately capture the temporal variability in air pollution concentrations for a specific scenario.

In this study we present an analysis of spatio–temporal variability of monthly averaged Vertical Tropospheric Columns (VTCs) of NO2 over Pakistan using OMI (ozone monitoring instrument) dataset from December 2004 to November 2008. The results have shown significant spatial and temporal variability of NO2 column values over the study region. Four NO2 hotspots and a high density corridor were identified within the study region. The main sources of NO2 emissions in these areas were also investigated. During the study period, an average value of NO2 was observed to be 1.102±0.081×1015 molecules/cm2, with an increasing trend of 3.29% per year. Twin cities of Islamabad/Rawalpindi, Lahore, Dera Ghazi Khan and Karachi have shown positive trends of 44.10%, 23.48%, 31.40%, and 32.32% per year respectively. Karachi has shown the highest and the lowest mean monthly average values of 11.33×1015 molecules/cm2 and 0.98×1015 molecules/cm2 respectively. Air mass trajectories for hotspot regions have been used to track possible long–range transport of NO2.

A laboratory study was performed to investigate the composition of products formed from OH–initiated oxidation of aromatic hydrocarbon 1,3,5–trimethylbenzene. The experiments were conducted by irradiating 1,3,5–trimethylbenzene/CH3ONO/NO/air mixtures in smog chamber. The chemical composition of gas and particle–phase products have been investigated with gas chromatography/mass spectrometry (GC/MS) and the aerosol laser time–of–flight mass spectrometer (ALTOFMS), respectively. Experimental results showed that 3,5–dimethyl benzaldehyde, 2,4,6–trimethylphenol, 2–methyl–4–oxo–2–pentenal and 3,5–dimethyl–2–furanone were the predominant products in both the gas and particle–phases. However, there were some differences between detected gas–phase products and those of particle–phase, for example, oxalic acid, 2–methyl–2–hydroxy–3,4–dioxo–pentanal, and 2,3,5–trimethyl–3–nitro–phenol were only existing in the particle–phase. The possible reaction mechanisms leading to these products are also proposed. Compared to offline methods such as GC–MS measurement, the ALTOFMS detection can analyze real–time the secondary organic aerosol (SOA) successfully and provide more information on the products. Thus, ALTOFMS is a useful tool to reveal the formation and transformation processes of SOA particles in smog chambers.

Global in its distribution and pervading all levels of the water column, marine debris poses a serious threat to marine habitats and wildlife. For cetaceans, ingestion or entanglement in debris can cause chronic and acute injuries and increase pollutant loads, resulting in morbidity and mortality. However, knowledge of the severity of effects lags behind that for other species groups. This literature review examines the impacts of marine debris on cetaceans reported to date. It finds that ingestion of debris has been documented in 48 (56% of) cetacean species, with rates of ingestion as high as 31% in some populations. Debris-induced mortality rates of 0–22% of stranded animals were documented, suggesting that debris could be a significant conservation threat to some populations. We identify key data that need to be collected and published to improve understanding of the threat that marine debris poses to cetaceans.