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Träfflista för sökning "WFRF:(Marcomini Antonio) "

Sökning: WFRF:(Marcomini Antonio)

  • Resultat 1-5 av 5
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1.
  • Badetti, Elena, et al. (författare)
  • Novel multimethod approach for the determination of the colloidal stability of nanomaterials in complex environmental mixtures using a global stability index: TiO2 as case study
  • 2021
  • Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 801
  • Tidskriftsartikel (refereegranskat)abstract
    • A systematic study on the colloidal behavior of uncoated and polyvinylpyrrolidone (PVP) coated TiO2 engineered nanomaterials (ENMs) in simulated aqueous media is herein reported, in which conditions representative for natural waters (pH, presence of divalent electrolytes (i.e. Ca2+/Mg2+ and SO42−), of natural organic matter (NOM) and of suspended particulate matter (SPM)) were systematically varied. The colloidal stability of the different dispersions was investigated by means of Dynamic and Electrophoretic Light Scattering (DLS and ELS) and Centrifugal Separation Analysis (CSA), and a global stability index based on these three techniques was developed. The index allows to quantitatively classify the nano-based dispersions according to their colloidal stability affected by the different parameters studied. This multimethod approach clearly identifies inorganic SPM followed by divalent electrolytes as the main natural components destabilizing TiO2 ENMs upon entering in simulated natural waters, while it highlights a moderate stabilization induced by NOM, depending mainly on pH. Moreover, the PVP coating was found to attenuate the influence of these parameters on the colloidal stability. The obtained results show how the global stability index developed is influenced by the complexity of the system, suggesting the importance of combining the information gathered from all the techniques employed to better elucidate the fate and behavior of ENMs in natural surface waters.
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2.
  • Brian, Jayne V, et al. (författare)
  • Accurate prediction of the response of freshwater fish to a mixture of estrogenic chemicals.
  • 2005
  • Ingår i: Environmental health perspectives. - 0091-6765. ; 113:6, s. 721-8
  • Tidskriftsartikel (refereegranskat)abstract
    • Existing environmental risk assessment procedures are limited in their ability to evaluate the combined effects of chemical mixtures. We investigated the implications of this by analyzing the combined effects of a multicomponent mixture of five estrogenic chemicals using vitellogenin induction in male fathead minnows as an end point. The mixture consisted of estradiol, ethynylestradiol, nonylphenol, octylphenol, and bisphenol A. We determined concentration-response curves for each of the chemicals individually. The chemicals were then combined at equipotent concentrations and the mixture tested using fixed-ratio design. The effects of the mixture were compared with those predicted by the model of concentration addition using biomathematical methods, which revealed that there was no deviation between the observed and predicted effects of the mixture. These findings demonstrate that estrogenic chemicals have the capacity to act together in an additive manner and that their combined effects can be accurately predicted by concentration addition. We also explored the potential for mixture effects at low concentrations by exposing the fish to each chemical at one-fifth of its median effective concentration (EC50). Individually, the chemicals did not induce a significant response, although their combined effects were consistent with the predictions of concentration addition. This demonstrates the potential for estrogenic chemicals to act additively at environmentally relevant concentrations. These findings highlight the potential for existing environmental risk assessment procedures to underestimate the hazard posed by mixtures of chemicals that act via a similar mode of action, thereby leading to erroneous conclusions of absence of risk.
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4.
  • Lamon, Lara, et al. (författare)
  • Modeling the influence of climate change on the mass balance of polychlorinated biphenyls in the Adriatic Sea
  • 2012
  • Ingår i: Chemosphere. - : Elsevier BV. - 0045-6535 .- 1879-1298. ; 87:9, s. 1045-1051
  • Tidskriftsartikel (refereegranskat)abstract
    • Climate forcing is forecasted to influence the Adriatic Sea region in a variety of ways, including increasing temperature, and affecting wind speeds, marine currents, precipitation and water salinity. The Adriatic Sea is intensively developed with agriculture, industry, and port activities that introduce pollutants to the environment. Here, we developed and applied a Level Ill fugacity model for the Adriatic Sea to estimate the current mass balance of polychlorinated biphenyls in the Sea, and to examine the effects of a climate change scenario on the distribution of these pollutants. The model's performance was evaluated for three PCB congeners against measured concentrations in the region using environmental parameters estimated from the 20th century climate scenario described in the Special Report on Emission Scenarios (SRES) by the IPCC, and using Monte Carlo uncertainty analysis. We find that modeled fugacities of PCBs in air, water and sediment of the Adriatic are in good agreement with observations. The model indicates that PCBs in the Adriatic Sea are closely coupled with the atmosphere, which acts as a net source to the water column. We used model experiments to assess the influence of changes in temperature, wind speed, precipitation, marine currents, particulate organic carbon and air inflow concentrations forecast in the IPCC A1B climate change scenario on the mass balance of PCBs in the Sea. Assuming an identical PCBs' emission profile (e.g. use pattern, treatment/disposal of stockpiles, mode of entry), modeled fugacities of PCBs in the Adriatic Sea under the A1B climate scenario are higher because higher temperatures reduce the fugacity capacity of air, water and sediments, and because diffusive sources to the air are stronger.
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5.
  • Simeoni, Christian, et al. (författare)
  • Evaluating the combined effect of climate and anthropogenic stressors on marine coastal ecosystems : Insights from a systematic review of cumulative impact assessment approaches
  • 2023
  • Ingår i: Science of the Total Environment. - : Elsevier BV. - 0048-9697. ; 861
  • Forskningsöversikt (refereegranskat)abstract
    • Cumulative impacts increasingly threaten marine and coastal ecosystems. To address this issue, the research community has invested efforts on designing and testing different methodological approaches and tools that apply cumulative impact appraisal schemes for a sound evaluation of the complex interactions and dynamics among multiple pressures affecting marine and coastal ecosystems. Through an iterative scientometric and systematic literature review, this paper provides the state of the art of cumulative impact assessment approaches and applications. It gives a specific attention to cutting-edge approaches that explore and model inter-relations among climatic and anthropogenic pressures, vulnerability and resilience of marine and coastal ecosystems to these pressures, and the resulting changes in ecosystem services flow. Despite recent advances in computer sciences and the rising availability of big data for environmental monitoring and management, this literature review evidenced that the implementation of advanced complex system methods for cumulative risk assessment remains limited. Moreover, experts have only recently started integrating ecosystem services flow into cumulative impact appraisal frameworks, but more as a general assessment endpoint within the overall evaluation process (e.g. changes in the bundle of ecosystem services against cumulative impacts). The review also highlights a lack of integrated approaches and complex tools able to frame, explain, and model spatio-temporal dynamics of marine and coastal ecosystems' response to multiple pressures, as required under relevant EU legislation (e.g., Water Framework and Marine Strategy Framework Directives). Progress in understanding cumulative impacts, exploiting the functionalities of more sophisticated machine learning-based approaches (e.g., big data integration), will support decision-makers in the achievement of environmental and sustainability objectives.
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