1. BEAM Bridging Effect Assessment of Mixtures to ecosystem situations and regulation University of Bremen, Germany University of Göteborg, Sweden University of Milano Bicocca, Italy University of Insubria, Italy UFZ Centre for Environmental Research, Germany BEAM follows a previous project on mixtures PREDICT Prediction and Assessment of the Aquatic Toxicity of Mixtures of Chemicals

2. BEAM Workpackages and objectives (Scientific bases) WP1: TIE (Toxicity Identification and Evaluation) Identification of complex site-specific exposure situations WP2: Exposure assessment Development of predictive approaches for exposure assessment of mixtures WP3: Effect assessment (single species) Determining concentration- response relationships of combined effects Evaluating the predictive power of prognostic concepts WP4: Effect assessment (communities) Development of a bioassay for assessing mixture effects on natural communities Evaluation of predictive power of prognostic concepts on natural communities. WP5: Chemometric approaches Extension of tools for grouping chemicals and for predicting effects by QSAR WP6: Biometrical demand Relationships between quality and quantity of data and the statistical accuracy and precision of mixture toxicity prediction. Determining minimum biometrical demand for the design of experiments.

3. BEAM Workpackages and objectives (Practical applications) WP7: Fundamental Options for Regulation Exploring the quantitative relations between predictions of mixture toxicity by Concentration Addition and Independent Action WP8: Risk Assessment of mixtures Analysing the significance of the risk from the pollution of surface waters with mixtures of pollutants. Characterising the risk that may arise from the pollution of aquatic ecosystems with mixtures of pollutants WP9: Protocols for Ecological Water Quality Target To evaluate how the chemical characteristics of a surface water body, in terms of presence of mixtures of potentially dangerous chemicals may affect the characteristics of an aquatic ecosystem, in relation to the definitions of “High”, “Good” and “Fair” status according to the EU Water Framework Directive. WP10: Consultation of Stakeholders for Implementation Strategies Dissemination of scientific evidence for the significance of combined effects for mixtures of pollutants. Participation of stakeholders in the discussion process on the development of implementation strategies

4. List of toxic substances Biotest (Extract) Biotest of ident. comp. Chemical Analysis Contaminated sample Fractionation Biotest Fractions Stop not toxictoxic toxic? Bioassay directed fractionation and identification Approach WP1

5. WP2 Predictive exposure assessment General procedure 1. Assessment of major chemical emission scenarios from different point and non point sources o Agriculture o Urban sewage o Industrial emissions § Industrial effluents § Chemicals used as technical mixtures 2. Quantification of chemical amount and composition of mixtures reaching surface water 3. Exposure assessment of mixtures by means of suitable environmental fate models

6. Composition of four relevant maize mixtures in function of NPEC/NPNEC

7. Concepts to predict the toxicity of chemical mixtures Assumption: Formula: Assumption: Formula: Concentration Addition (CA) similar sites of action similar modes of action c1c1 Ec x,1 += 1 c2c2 Ec x,2 Independent Action (IA) dissimilar sites of action dissimilar modes of action E(c 1,2 ) = E(c 1 ) + E(c 2 ) - E(c 1 ) E(c 2 ) BEAM - WP3

8. Mixture Toxicity of Priority Pollutants at NOEC’s Effects of the mixture 120 Estimated effects of single substances 9.3 6.26.4 8.5 3.7 6.9 5.2 13.3 3.4 11.9 10.0 86.8 58.0 100.0 0 20 40 60 80 100 Inhibition of algal reproduction [%] Atrazine Biphenyl Chloral hydrate 2,4,5-Trichlorophenole Fluoranthene Lindane Naphthalene Parathion Phoxim Tributyltin chloride Triphenyltin chloride Observation Prediction IA Prediction CA Walter, H, et al. (2002). Ecotoxicology: 299-310. BEAM - WP3

9. SWIFT periphyton community test Periphyton is precolonised in situ (7-8 d) Periphyton is incubated with toxicants (4 d) Species shifts indirectly estimated as change in pigment profiles with HPLC Pigment profiles summarised as Bray-Curtis similarity indices Mixture toxicity predicted with CA and IA Mixture toxicity determined experimentally

10. Chromatogram values sq. root transformed

11. Validation of prognostic concepts in environmentally realistic scenarios Emission oriented modelling approaches have been developed in order to identify mixtures of chemicals likely to occur in freshwater and marine waters. Two specific scenarios have been modelled: –emissions from agricultural activities –emissions from petrochemical industry

12. Agricultural Scenario Mixture components: 25 agricultural pesticides.Mainly herbicides Experimental analysis of the mixture in an algal bioassay Results: –Mixture Toxicity can be precisely predicted by CA –Predictions by IA and CA differ only marginally (a factor of 1.1 between the two predicted EC50-values). CA predicts the higher mixture toxicity. –Sum of PEC‘s lead to a severe mixture effect (40% inhibition of reproduction) Petrochemical Scenario Mixture components: 26 organic chemicals Bioassay: Microtox (marine bacterium) Results: –Mixture toxicity is precisely predictable by CA –Predictions by IA and CA differ only marginally. Predicted EC50 values are virtually identical. –Sum of PEC‘s lead to a clear mixture effect (20% inhbition)

13. Biometrical properties of IA and CA CA-Predictions are robust against uncertainties in the single substance data Standard regulatory data sets can be used for calculating CA-predictions IA-Prections become more and more sensitive to uncertainties in the single substance data with increasing number of mixture components Knowledge of low-effect concentrations (EC1 and lower) are needed for the application of IA to multi-component mixtures.

14. Options for a Predictive Hazard Assessment of Chemical Mixtures

15. Quantitative Differences between Predictions of Effect Concentrations for Mixtures

16. Conclusions 1. All available evidence indicates that quantitative differences between predictions of effect concentrations for multi-component mixtures derived from the competing concepts of Independent Action and Concentration Addition usually are relatively small (< or ≈ 1 order of magnitude). 2. Thus, our current status of knowledge may justify the general use of Concentration Addition as a pragmatic default approach to the predictive hazard assessment of chemical mixtures.

17. Application of CA in a regulatory context CA might be applied in two different ways to regulatory data sets (e.g. ecotoxicological data from the “base set“): (1)Calculation of PNEC values for every mixture component; Calculating the PEC/PNEC ratio for every component; Calculating the sum of PEC/PNEC‘s for the mixture (2)CA-based prediction of the mixture toxicity for every considered trophic level (Toxic Unit summation); Application of an Assessment Factor to the most sensitive trophic level.

18. Application of CA in a regulatory context Approach (1) can be directly applied to regulatory data sets Approach (2) is more scientifically sound, but specific Assessment Factors for the different considered trophic levels have to be developed. Approach (1) never predicts a lower mixture toxicity, than approach (2). The maximum factor between both approaches is 3, if the standard three trophic levels (algae, daphnids and fish) are considered.

19. WP9 Methods for the classification of ecological water quality in relation to mixture fate and effects There is a need for developing suitable tools useful to classify water bodies according to the definitions of “High”, “Good” and “Moderate” ecological status of the WFD, in function of the site-specific characteristics of the biological community. At present, water quality for individual chemicals is usually defined, on a chemical and ecotoxicological basis, using the procedures for calculating a PEC/PNEC ratio as described in the TGD. These procedures fulfil the requirements for the assessment of the “Chemical status” of a water body, but are not adequate for the “Ecological status” classification. Being aware that is not the objective of the BEAM project to give answers to these general and complex problems, the only possibility, at present, is to propose a “chemically-based” WQO for mixture supported by the outcomes of the BEAM and PREDICT projects.

20. A preliminary proposal for a Water Quality Objective for mixtures RQ<1 where: RQ can be calculated from the available ecotoxicological information on individual chemicals usually represented by the results of acute or long-term tests on the standard organisms (algae, Daphnia and fish) representative of the aquatic community. This concept for a Water Quality Objective for mixtures represents a preliminary, interim proposal that can be realistically developed taking into account the scarcity of ecotoxicological information usually available for most potentially dangerous chemicals (including many priority pollutants) as well as the lack for a more ecologically–based procedure for defining “Ecological status” of surface waters in agreement with the requirements of the WFD.

21. WP10 Consultation of Stakeholders for Implementation Strategies Four meetings were organised to discuss BEAM results with external experts from regulatory organisations, industry, public research structures and NGOs A joint report is planned to develop proposals for the implementation of BEAM outcomes in a regulatory framework