493 research outputs found

    Hypoxia does not influence the response of fish to a mixture of estrogenic chemicals

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    The official published version can be obtained from the link below - Copyright @ 2009 American Chemical SocietyChemical risk assessment procedures assign a major role to standardized toxicity tests, in which the response of a particular organism to a single test substance is determined under otherwise constant and favorable conditions in the laboratory. This approach fails to consider the potential for chemical interactions, as well as failing to consider how the toxicological response varies, depending on the conditions of exposure. As yet, the issue of confounding factors on chemically mediated effects in wildlife has received little attention, despite the fact that a range of physicochemical parameters, including temperature, water quality, and pH, are known to modify chemical toxicity. Here, we consider how the estrogenic response of fish varies with regard to hypoxia. Fathead minnows (Pimephales promelas) were exposed to a mixture of estrogenic chemicals under hypoxic or normoxic conditions. Their estrogenic response was characterized using an in vivo assay, involving the analysis of the egg yolk protein, vitellogenin (VTG). The results revealed that there was no effect of hypoxia on the VTG response in either treatment group at the end of the exposure period. This suggests that this end point is robust and relatively insensitive to the effects of any physiological changes that arise as a result of hypoxia. The implications of these negative findings are discussed in terms of their relevance with regard to the development of risk assessment policy.This work was funded by a grant from the Natural Environment Research Council(NE/D00389X/1)

    The influence of a surfactant, linear alkylbenzene sulfonate, on the estrogenic response to a mixture of (xeno)estrogens in vitro and in vivo

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    This is the post-print version of the final paper published in Aquatic Toxicology. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright © 2008 Elsevier B.V. All rights reserved.The effect of the presence of a surfactant on the activity of a mixture of environmental estrogens was assessed. In their natural habitat, fish are subject not only to exposure to mixtures of estrogenic compounds, as has been addressed in previous publications, but also to other confounding factors (chemical, physical and biological), which may, in theory, affect their responses to such compounds. To assess the potential for such interference, the commonly occurring surfactant, linear alkylbenzene sulfonate (LAS), was applied to the yeast estrogen screen at various concentrations, independently and together with a mixture of estrogens at constant concentrations. LAS enhanced the estrogenic activity of the mixture, an effect which became less pronounced over the course of time. This information was used to design an in vivo study to assess induction of vitellogenin in fathead minnows exposed to the same mixture of estrogens plus LAS. A similar trend was observed, that is, the response was enhanced, but the effect became less pronounced as the study progressed. However, the enhanced response in vivo occurred only at the highest concentration of LAS tested (362 Όg/L), and was transient because it was no longer apparent by the end of the study. Although LAS is a significant contaminant in terms of both concentration and frequency of detection in the aquatic environment, these data do not suggest that it will have a significant impact on the response of fish to environmental estrogens

    A multi-risk methodology for the assessment of climate change impacts in coastal zones

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    Climate change threatens coastal areas, posing significant risks to natural and human systems, including coastal erosion and inundation. This paper presents a multi-risk approach integrating multiple climate-related hazards and exposure and vulnerability factors across different spatial units and temporal scales. The multi-hazard assessment employs an influence matrix to analyze the relationships among hazards (sea-level rise, coastal erosion, and storm surge) and their disjoint probability. The multi-vulnerability considers the susceptibility of the exposed receptors (wetlands, beaches, and urban areas) to different hazards based on multiple indicators (dunes, shoreline evolution, and urbanization rate). The methodology was applied in the North Adriatic coast, producing a ranking of multi-hazard risks by means of GIS maps and statistics. The results highlight that the higher multi-hazard score (meaning presence of all investigated hazards) is near the coastline while multi-vulnerability is relatively high in the whole case study, especially for beaches, wetlands, protected areas, and river mouths. The overall multi-risk score presents a trend similar to multi-hazard and shows that beaches is the receptor most affected by multiple risks (60% of surface in the higher multi-risk classes). Risk statistics were developed for coastal municipalities and local stakeholders to support the setting of adaptation priorities and coastal zone management plans

    Inventory of GIS-Based Decision Support Systems Addressing Climate Change Impacts on Coastal Waters and Related Inland Watersheds

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    A Decision Support System (DSS) is a computer-based software that can assist decision makers in their decision process, supporting rather than replacing their judgment and, at length, improving effectiveness over efficiency. Environmental DSS are models based tools that cope with environmental issues and support decision makers in the sustainable management of natural resources and in the definition of possible adaptation and mitigation measures [2]. DSS have been developed and used to address complex decision-based problems in varying fields of research. For instance, in environmental resource management, DSS are generally classified into two main categories: Spatial Decision Support Systems (SDSS) and Environmental Decision Supports Systems (EDSS) [3-5]. SDSS provide the necessary platform for decision makers to analyse geographical information in a flexible manner, while EDSS integrate the relevant environmental models, database and assessment tools – coupled within a Graphic User Interface (GUI) – for functionality within a Geographical Information System (GIS) [1,4-6]. In some detail, GIS is a set of computer tools that can capture, manipulate, process and display spatial or geo-referenced data in which the enhancement of spatial data integration, analysis and visualization can be conducted [8-9]. These functionalities make GIS-tools useful for efficient development and effective implementation of DSS within the management process. For this purpose they are used either as data managers (i.e. as a spatial geo-database tool) or as an end in itself (i.e. media to communicate information to decision makers)

    On the Application of GIS-based Decision Support Systems to study climate change impacts on coastal systems and associated ecosystems

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    One of the most remarkable achievements by scientists in the field of global change in recent years is the improvedunderstanding of climate change issues. Its effects on human environments, particularly coastal zones and associated watersystems, are now a huge challenge to environmental resource managers and decision makers. International and regionalregulatory frameworks have been established to guide the implementation of interdisciplinary methodologies, useful toanalyse water-related systems issues and support the definition of management strategies against the effects of climatechange. As a response to these concerns, several decision support systems (DSS) have been developed and applied toaddress climate change through geographical information systems (GIS) and multi-criteria decision analysis (MCDA)techniques; linking the DSS objectives with specific functionalities leading to key outcomes, and aspects of the decisionmaking process involving coastal and waters resources. An analysis of existing DSS focusing on climate change impacts oncoastal and related ecosystems was conducted by surveying the open literature. Consequently, twenty DSS were identifiedand are comparatively discussed according to their specific objectives and functionalities, including a set of criteria (generaltechnical, specific technical and applicability) in order to better inform potential users and concerned stakeholders throughthe evaluation of a DSS’ actual application.Key words: Climate change, Decision support, GIS, regulations, Environmen

    Water-Assisted Concerted Proton-Electron Transfer at Co(II)-Aquo Sites in Polyoxotungstates With Photogenerated RuIII(bpy)33+ Oxidant

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    The cobalt substituted polyoxotungstate [Co6(H2O)2(α-B-PW9O34)2(PW6O26)]17− (Co6) displays fast electron transfer (ET) kinetics to photogenerated RuIII(bpy)33+, 4 to 5 orders of magnitude faster than the corresponding ET observed for cobalt oxide nanoparticles. Mechanistic evidence has been acquired indicating that: (i) the one-electron oxidation of Co6 involves Co(II) aquo or Co(II) hydroxo groups (abbreviated as Co6(II)−OH2 and Co6(II)−OH, respectively, whose speciation in aqueous solution is associated to a pKa of 7.6), and generates a Co(III)−OH moiety (Co6(III)−OH), as proven by transient absorption spectroscopy; (ii) at pH>pKa, the Co6(II)−OH→RuIII(bpy)33+ ET occurs via bimolecular kinetics, with a rate constant k close to the diffusion limit and dependent on the ionic strength of the medium, consistent with reaction between charged species; (iii) at p

    The KULTURisk Regional Risk Assessment methodology for water-related natural hazards – Part 1: Physical–environmental assessment

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    Abstract. In recent years, the frequency of catastrophes induced by natural hazards has increased, and flood events in particular have been recognized as one of the most threatening water-related disasters. Severe floods have occurred in Europe over the last decade, causing loss of life, displacement of people and heavy economic losses. Flood disasters are growing in frequency as a consequence of many factors, both climatic and non-climatic. Indeed, the current increase of water-related disasters can be mainly attributed to the increase of exposure (elements potentially at risk in flood-prone area) and vulnerability (i.e. economic, social, geographic, cultural and physical/environmental characteristics of the exposure). Besides these factors, the undeniable effect of climate change is projected to strongly modify the usual pattern of the hydrological cycle by intensifying the frequency and severity of flood events at the local, regional and global scale. Within this context, the need for developing effective and pro-active strategies, tools and actions which allow one to assess and (possibly) to reduce the flood risks that threatens different relevant receptors becomes urgent. Several methodologies to assess the risk posed by water-related natural hazards have been proposed so far, but very few of them can be adopted to implement the last European Flood Directive (FD). This paper is intended to introduce and present a state-of-the-art Regional Risk Assessment (RRA) methodology to appraise the risk posed by floods from a physical–environmental perspective. The methodology, developed within the recently completed FP7-KULTURisk Project (Knowledge-based approach to develop a cULTUre of Risk prevention – KR) is flexible and can be adapted to different case studies (i.e. plain rivers, mountain torrents, urban and coastal areas) and spatial scales (i.e. from catchment to the urban scale). The FD compliant KR-RRA methodology is based on the concept of risk being function of hazard, exposure and vulnerability. It integrates the outputs of various hydrodynamic models with site-specific bio-geophysical and socio-economic indicators (e.g. slope, land cover, population density, economic activities etc.) to develop tailored risk indexes and GIS-based maps for each of the selected receptors (i.e. people, buildings, infrastructure, agriculture, natural and semi-natural systems, cultural heritage) in the considered region. It further compares the baseline scenario with alternative scenarios, where different structural and/or non-structural mitigation measures are planned and eventually implemented. As demonstrated in the companion paper (Part 2, Ronco et al., 2014), risk maps, along with related statistics, allow one to identify and classify, on a relative scale, areas at risk which are more likely to be affected by floods and support the development of strategic adaptation and prevention measures to minimizing flood impacts. In addition, the outcomes of the RRA can be eventually used for a further socio-economic assessment, considering the tangible and intangible costs as well as the human dimension of vulnerability

    ChemicalDrift 1.0: an open-source Lagrangian chemical-fate and transport model for organic aquatic pollutants

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    A new model for transport and fate of chemicals in the aquatic environment is presented. The tool, named ChemicalDrift, is integrated into the open-source Lagrangian framework OpenDrift and is hereby presented for organic compounds. The supported chemical processes include the degradation, the volatilization, and the partitioning between the different phases that a target chemical can be associated with in the aquatic environment, e.g. dissolved, bound to suspended particles, or deposited to the seabed sediments. The dependencies of the chemical processes on changes in temperature, salinity, and particle concentration are formulated and implemented. The chemical-fate modelling is combined with wide support for hydrodynamics by the integration within the Lagrangian framework which provides e.g. advection by ocean currents, diffusion, wind-induced turbulent mixing, and Stokes drift generated by waves. A flexible interface compatible with a wide range of available metocean data is made accessible by the integration, making the tool easily adaptable to different spatio-temporal scales and fit for modelling of complex coastal regions. Further inherent capabilities of the Lagrangian approach include the seamless tracking and separation of multiple sources, e.g. pollutants emitted from ships or from rivers or water treatment plants. Specific interfaces to a dataset produced by a model of emissions from shipping and to an unstructured-grid oceanographic model of the Adriatic Sea are provided. The model includes a database of chemical parameters for a set of poly-aromatic hydrocarbons and a database of emission factors for different chemicals found in discharged waters from sulfur emission abatement systems in marine vessels. A post-processing tool for generating mean concentrations of a target chemical, over customizable spatio-temporal grids, is provided. Model development and simulation results demonstrating the functionalities of the model are presented, while tuning of parameters, validation, and reporting of numerical results are planned as future activities. The ChemicalDrift model flexibility, functionalities, and potential are demonstrated through a selection of examples, introducing the model as a freely available and open-source tool for chemical fate and transport that can be applied to assess the risks of contamination by organic pollutants in the aquatic environment
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