1. USES guia del USES 4.0. http://www.rivm.nl/bibliotheek/rapporten/601450012.html EUSES (European Union System for the Evaluation of Substances) Multimedia Transport and Transformation Model According to the supporting Technical Guidance Documents (TGD) for European risk assessment Euses: http://ecb.jrc.it/Euses/

2. EUSES Aim: To harmonise risk assessment in a systematic and transparent approach Include : Emission, exposure, bio-effects and risk estimation for the environment and humans

3. Compartments in Euses

4. –EUSES –Stand-alone application – Multimedia models for: - emissions - transport & transformation - exposure of man and environment – Effects assessment for man and environment – Risk characterisation for man and environment – Conservative results as ‘reasonable worst-cases’ – 3 spatial scales (personal, local, regional) – 2 time scales: - long-term, sub-/chronic - short-term, acute – Uses equations of the Technical Guidance Documents (TGD) of the EU

5. RELEASE ESTIMATION Production Formulation Processing Private Use Recovery

6. The local scale of EUSES generic world. The local point source emitting directly ore indirectly into the different compartments [EUSES 1.00]

8. Structure of the regional distribution model Simple Box of EUSES

9. Complexity of EUSES [Berding et al. (1999)]

10. O verview over the EUSES software structure

11. PEC:The Predicted Environmental Concentration Is the concentration in the environment or food which is predicted by a model. PNEC: The Predicted No Effect Concentration Is a concentration level in the environment or food below which adverse effects are most likely not to occur.

12. Predicted environmental concentration and Predicted no effect concentration [Boeije (1999)]

13. RCR (EUSES): Risk Characterisation Ratio RCR is the ratio of the Predicted Environmental Concentration and the Predicted No-Effect Concentration (RCR = PEC/PNEC) and expresses the likelihood of adverse effects to occur. Margin of Safety (MOS) (EUSES): Is the ratio ‘effect level’/’exposure level’=MOS and describes the degree of risk.

14. A significant influence on all PECs have :  the melting point,  emissions to regional air,  the wind speed,  the atmospheric mixing height..

15. The soil-PECs are strongly affected by:  the degradation rate in soil,  the vapour pressure,  the aerosol collection efficiency,  the specific mixing depth,  the constant of Junge equation,  the volume fraction of solids in soil,  the density of solid phase,  the surface area of aerosol particles,  partially by the average daily precipitation  the octanol-water partition coefficient

16. The water/sediment-PECs depend on:  the volume fraction of water in sediment,  the fraction connected to STP,  partially on the octanol-water partition coefficient,  partially on the average daily precipitation,  partially on the weight fraction of organic carbon in suspended matter,  partially on the density of water phase.

17. Comparison -Outputs – on site / off site concentrations in air, water, sediment, plants and soil – concentrations in breast milk, fish, milk, meat, eggs, tap/swimming water – daily human doses by inhalation, ingestion (breast milk, water, milk, meat, fish, soil) and dermal uptake – individual human lifetime risk attributable to exposures over a certain period – soil clean-up goals (depending on a target risk) EUSESCalTOX – estimates for releases to air, water and soil, life cycle step-wise and spatial scale – predicted environmental concentrations (PEC) in surface water, air, soils and sediment – concentrations in fish, plants, drinking water, milk, meat – exposure of consumers via products – workplace exposure of humans – daily human doses by inhalation, ingestion (water, milk, meat, fish, crops), dermal contact – Predicted No-Effect Concentrations (PNEC) in the environment – Risk Characterisation Ratio for the environment (RCR=PEC/PNEC) = likelihood of adverse effects occurring – Margin Of Safety for humans (MOS= ‘effect’/’exposure’) = degree of risk

18. Comparison - Applicability – non-ionic organic chemicals, radionuclides, fully dissociating in-/ organic chemicals, solid-phase metal species, partially dissociated in-/ organic species – site specific – very low concentrations (not exceeding the solubility limit in any phase) – long time scales (preferably one year to decades) – areas greater than 1000 m 2 with a water fraction of max. 10 % of the surface area EUSESCalTOX – unacceptable errors may occur assessing: poorly soluble, inorganic or ionisable substances – petroleum can only be assessed using the Hydrocarbon Block Method (HBM) – not site specific without proper data adjustments – several hazards are not considered: global warming, ozone depletion, acidification, eutrophication, etc. – short and long time scales – all spatial scales smaller than continental areas

19. Comparison - Benefits – easy export/import of data/results for visualisation – possibility of Dynamic Data Exchange (DDE) to other applications from within Excel – applicability of sensibility/uncertainty analysis – relatively well structured input/output sections – easy to understand and use EUSESCalTOX – assessment for the environment and humans – implemented step by step input of the necessary data – control of the range of the data introduced by the user – possibility of introducing the data in different units – great amount of different output data – estimation routines for a lot of the necessary data (emissions, effects, etc.) – great amount of European default data – wide range of time and spatial scales – implemented life cycle steps

20. ComparisonDisadvantages – only risk assessments for humans – the implemented macros do not run very well – no control of the range of the values introduced by the user – fixed units – default data are valid for California (and therefore not applicable for European risk assessment) – limited applicability for short term exposure and small areas/sites – limited output of risk values (only non/cancer risk for humans) EUSESCalTOX – very complex and difficult to understand – data exchange/export is very difficult if not impossible and does not work automatically – sensitivity/uncertainty analysis are not applicable – graphical visualisation of the results is not implemented