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TitlePotential useFilterResponsible scientistsFilterRelated to deliverable
AttachmentUncertainty and variability tool
The tool consists of a set of equations and calculation rules that can be used to separately quantify uncertainty (i.e. lack of knowledge) and variability (e.g. interindividual variability in intake or sensitivity) in measurement data. Once quantified, uncertainty and variability can be propagated separately in model calculations by means of nested Monte Carlo simulation. This enables model predictions that distinguish between variability (e.g. the population fraction at risk) and uncertainty in input data (e.g. the probability that the predicted population fraction at risk is correct).
Ad M.J. Ragas, Department of Environmental Science, Radboud University Nijmegen, the Netherlands, a.ragas@science.ru.nl
D.4.1.1
AttachmentVulnerability index for surface water ecosystems
Vulnerability index for surface water ecosystems
Marco Vighi, University of Milano Bicocca, marco.vighi@unimib.it
Alessio Ippolito, University of Milano Bicocca, a.ippolito4@campus.unimib.it>
WP 2.2
AttachmentWorst Case Definition (WCD) Model
The model can help optimize risk assessment planning by initial screening level analyses and guiding quantitative assessment in relation to knowledge needs for better decision support concerning environmental and human health protection or risk reduction. The WCD model facilitates the evaluation of fundamental uncertainty using knowledge mapping principles and techniques in a way that can improve a complete uncertainty analysis. Ultimately, the WCD is applicable for describing risk contributing factors in relation to many different types of risk management problems since it transparently and effectively handles assumptions and definitions and allows the integration of different forms of knowledge, thereby supporting the inclusion of multifaceted risk components in cumulative risk management.
Peter B. Sørensen, Department of Terrestrial Ecology
National Environmental Research Institute
Aarhus University
Vejlsøvej 25, P.O.Box 314
DK-8600 Silkeborg
Denmark
Email: pbs@dmu.dk
D.1.2.7
AttachmentALPaCA” (Analysis of Landscape and Climate Parameters for Continental scale Assessment of the fate of pollutants)
A compilation of GIS layers for multimedia assessment of pollutants in air, soil and water at the European continental scale.
Alberto Pistocchi, JRC-IES, alberto.pistocchi@jrc.europa.eu for scientific issues.
Giovanni Bidoglio, JRC-IES, Giovanni.bidoglio@jrc.ec.europa.eu for conditions of use.
D.1.1.4
AttachmentEco-SpaCE (Ecological and Spatially explicit Cumulative Exposure model)
A receptor-oriented, ecology-based individual-based model to predict exposure and risk of terrestrial vertebrates to environmental stressors (chemical and natural). It can be used to assess the exposure and risk at the population level and to explore the relative contribution of chemical stress in a multiple stressor situation.
Mark Loos, Department of Environmental Science, Radboud University Nijmegen, the Netherlands, m.loos@science.ru.nl
Ad M.J. Ragas, Department of Environmental Science, Radboud University Nijmegen, the Netherlands, a.ragas@science.ru.nl
D.4.2.13
AttachmentEcological Vulnerability Analysis
Ecological Vulnerability Analysis
H.J. De Lange, Alterra, marieke.delange@wur.nl
J.H. Faber, Alterra, jack.faber@wur.nl
J. Lahr, Alterra, joost.lahr@wur.nl
D.4.2.6 and D.4.2.11
AttachmentFocus groups and group work techniques for exploring the social and communicative aspects of risks
Focus groups and group work techniques for exploring the social and communicative aspects of risks
Christina Benighaus;  Dialogik, Lerchenstraße 22, 70716 Stuttgart, benighaus@dialogik-expert.de
D.4.3.6
AttachmentSurvey on risks for risk management and risk policy development
Survey on risks for risk management and risk policy development
Jari Lyytimäki, Finnish Environment institute, jari.lyytimaki@ymparisto.fi
 
D.4.3.5
AttachmentSimulation of Risks to the respiratory health of a mobile person
A receptor-oriented and individual-based model to simulate and assess the human exposure to single and combined environmental stressors (chemicals, climate, etc.). It comprises the movement pattern of the individual and can explore the effectiveness of abatement strategies as well as the relative contribution of individual stressors.
Uwe Schlink, Helmholtz Centre for Environmental Research, Leipzig, Germany (uwe.schlink@ufz.de)
D.4.2.14-2.
AttachmentNovel probabilistic assessment factors
Assessment factors (a.k.a. extrapolation factors, safety factors or uncertainty factors) are used to derive environmental quality standards (EQSs) when there is a small number of chronic NOEC data available (n < 10). Assessment factors decrease when more NOECs become available, e.g., for aquatic ecosystems an AF of 100 is used when only one NOEC is available, an AF of 50 when two NOECs are available and an AF of ten when three to nine NOECs are available. We developed an alternative system of probabilistic assessment factors which (1) provide an explicit level of protection, (2) have the tendency to become less strict when more information becomes available, and (3) allow specification of a statistical confidence level.
Ad M.J. Ragas, Department of Environmental Science, Radboud University Nijmegen, the Netherlands, a.ragas@science.ru.nl
D.4.1.15