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Chemical Mixtures

Chemical Mixtures. occurrences, (eco)toxicity and relevance for water quality in Europe. Thomas Backhaus University of Gothenburg thomas.backhaus@dpes.gu.se. Focus. Chemical Mixtures Mixtures of toxic chemicals Aquatic Ecosystems Ecotoxicology.

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Chemical Mixtures

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  1. Chemical Mixtures occurrences, (eco)toxicity and relevance for water quality in Europe Thomas Backhaus University of Gothenburg thomas.backhaus@dpes.gu.se

  2. Focus • Chemical Mixtures • Mixtures of toxic chemicals • Aquatic Ecosystems • Ecotoxicology

  3. Inspired from work in the following EU projects • PREDICT • BEAM • ACE • EDEN • CONTAMED

  4. Monitoring Data Sweden • StinaAdielsson, Sarah Graaf, Melle Andersson & Jenny Kreuger (2009) Resultat från miljöövervakningen av • bekämpningsmedel (växtskyddsmedel). ISSN 0347-9307. Swedish University of Agricultural Sciences, Uppsala.

  5. The ecotoxicology of chemical mixtures • Mixture effect is higher than the effect of each individual component • Individual quality targets not necessarily sufficient

  6. Mixture of priority pollutants • Walter, H., et al. (2002) Mixture toxicity of priority pollutants at No Observed Effect Concentrations (NOECs). Ecotoxicology 11:299-310.

  7. Realistic pesticide mixture Junghans , et al. (2006) Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aquatic Toxicology 76, 2006

  8. Mixture toxicity concepts Dissimilarly acting substances: Independent Action EMix = Effect of the mixture of n compounds Ei = Effect of substance i, when applied singly Similarly acting substances: Concentration Addition ci = Concentration of component i in the mixture (i = 1...n) ECxi = Concentration of substance i provoking a certain effect x when applied alone ECx(Mix) = Predicted total concentration of the mixture, that provokes x% effect. pi = relative fraction of component i in the mixture

  9. Mixture toxicity concepts Dissimilarly acting substances: Independent Action EMix = Effect of the mixture of n compounds Ei = Effect of substance i, when applied singly • Assumes that components affect the same endpoint, • but do that completely independent of each other

  10. Biochemical networks

  11. Ecological networks

  12. Mixture toxicity concepts Dissimilarly acting substances: Independent Action EMix = Effect of the mixture of n compounds Ei = Effect of substance i, when applied singly • Assumes that components affect the same endpoint, but do that completely independent of each other • In contradiction to • The physiological and ecological networking of life • The notion of a “narcotic” mode of action, common to all organic chemicals.

  13. Mixture toxicity concepts Dissimilarly acting substances: Independent Action EMix = Effect of the mixture of n compounds Ei = Effect of substance i, when applied singly Similarly acting substances: Concentration Addition ci = Concentration of component i in the mixture (i = 1...n) ECxi = Concentration of substance i provoking a certain effect x when applied alone ECx(Mix) = Predicted total concentration of the mixture, that provokes x% effect. pi = relative fraction of component i in the mixture

  14. River basin modeling of the expected consequences of chemical mixtures • Nonylphenol How? • Sumpter, J., et al. (2006) Modeling Effects of Mixtures of Endocrine Disrupting Chemicals at the River Catchment ScaleE, Env. Sci. Techn. 40:5478-5489

  15. River basin modeling of the expected consequences of chemical mixtures • Nonylphenol • Natural estrogens (E1, E3), • Pharmaceutical (EE2) • Sumpter, J., et al. (2006) Modeling Effects of Mixtures of Endocrine Disrupting Chemicals at the River Catchment ScaleE, Env. Sci. Techn. 40:5478-5489

  16. “It is the opinion of the SCHER that the CA approach may be assumed as a temporary interim method for deriving EQs for mixtures.“ How? • SCHER, Opinion on the Chemicals and the Water Framework Directive: Technical Guidance for Deriving Environmental Quality Standards (2010)

  17. Properties of Concentration Addition • Assumes similar mode of action of all mixture components • Only extrapolates from single substance to mixture toxicity • Assumes no interaction between the components in the mixture

  18. Mode of Action • CA and IA are based on mutually exclusive assumptions of the similarity, resp. dissimilarity • Differences between CA- and IA-predicted toxicities depend on • Effect level • Number of components • Mixture ratio

  19. Mixture toxicity of 14 pharmaceuticals Mixture: 14 pharmaceuticals with dissimilar mechanisms of action Organism: Vibrio fischeri (marine bacterium) Red: CA Blue: IA • Backhaus et al., (2000) Predictability of the toxicity of a mixture of dissimilarly acting chemicals to Vibrio fischeri, Env. Tox. Chemistry, 19(9): 2348-2356

  20. Contribution of low, individually non-toxic concentrations Backhaus, Blanck, Sumpter, On the ecotoxicology of pharmaceutical mixtures, 2008

  21. Possible ratios EC50(IA) / EC50(CA) • Faust et al., (2000) Competing Concepts for the Prediction of Mixture Toxicity: Do the Differences Matter for Regulatory Purposes? Public Report of the BEAM Project

  22. The maximum possible difference between IA- and CA-predicted toxicities TU: Toxic Unit, ratio between conc and EC50 • the maximum possible ratio between the CA- and the IA-predicted EC50 is n (the number of mixture components). • the more “imbalanced“ the mixture – in terms of TU contributions to the mixture - the smaller the maximum possible error. Junghans , et al. (2006) Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aquatic Toxicology 76, 2006

  23. Properties of Concentration Addition • Assumes similar mode of action of all mixture components Differences to the toxicities predicted by the competing concept of IA are small and negligible

  24. Properties of Concentration Addition • Assumes similar mode of action of all mixture components • Extrapolates from single substance to mixture toxicity • Assumes no interaction between the componentsin the mixture √

  25. Single Components Laboratory EQS (PNEC) Single Components Mixture Field Field

  26. Applying Concentration Addition • Vighi et al (2003) Water quality objectives for mixtures of toxic chemicals: • problems and perspectives, Ecotox. Env. Safety, 54, 139-150

  27. Compound 1: PEC1=0.4*10-4 EC50Algae: 1.0 EC50Daphnids: 0.1 PNEC = 10-4 EC50Fish: 1.0 Compound 2: PEC2= 0.8*10-4 EC50Algae: 0.1 PNEC = 10-4 EC50Daphnids: 1.0 EC50Fish: 1.0

  28. Compound 1 Compound 2 0.4 0.8 ?

  29. Concentration Addition Single Components Mixture Laboratory Laboratory EQS (PNEC) EQS (PNEC) Single Components Mixture Field Field

  30. EC50’s Algae DaphnidsFish Conc Comp1 1.0 0.1 1.0 0.4*10-4 Comp2 0.1 1.0 1.0 0.8*10-4 Mix 0.150.72 1.0 1.2*10-4 RQ=0.8

  31. Properties of Concentration Addition • Extrapolates from single substance to mixture toxicity Extrapolation Lab->Field can be achieved either by summing up PEC/PNECs or by summing up TUs

  32. Properties of Concentration Addition • Assumes similar mode of action of all mixture components • Extrapolates from single substance to mixture toxicity • Assumes no interaction between the componentsin the mixture √ √

  33. A synergistic mixture Synergistic effects of binary mixtures of carbamate (CB) and organophospate (OP) pesticides DZN: Diazinon; MLN: Malathion; CRL: Carbaryl CBN: Carbofuran; CFS: Clopyrifos Laetz et al., EHP, 2008

  34. Belden, J.B. et al. (2007) How well can we predict the toxicity of pesticide mixtures to aquatic life? Integrated Environmental Assessment and Management. 3:364-372.

  35. TU Distribution for a realistic pesticide mixture Sum of TU’s = 0.98 Junghans , et al. (2006) Application and validation of approaches for the predictive hazard assessment of realistic pesticide mixtures. Aquatic Toxicology 76, 2006

  36. What happens if a compound is synergized? SynFactor = 10 Sum of Toxic Units SynFactor = 2 Rank of synergised compound

  37. What happens if n compounds are synergized? Sum of Toxic Units Average Synergy Factor

  38. Interactions, Synergisms, Antagonisms • Rare • Limited to mixtures with few compounds • Multi-component mixtures dampen quantitative consequences

  39. Properties of Concentration Addition √ • Assumes similar mode of action of all mixture components • Extrapolates from single substance to mixture toxicity • Assumes no interaction between the componentsin the mixture √ √

  40. Options for overcoming the limitations of CA/IA • Mode of Action • Start with CA • Accompany by an error estimations • IA only if (i) indications of risk and (ii) the error estimates indicate that IA may indeed predict a lower mixture toxicity

  41. Options for overcoming the limitations of CA/IA • Extrapolation Lab -> Field • Start with summing up PEC/PNECs (scientifically problematic, but easily applied and cautious) • Analyse sum of toxic units (scientifically sound, potentially problematic to apply)

  42. Options for overcoming the limitations of CA/IA • Interactions • Need for a case-by-case consideration • Multi-component mixtures are comparatively robust

  43. Summary and Conclusions • Mixtures matter. They are there and they are toxic. • Quality standards and risk quotients for individual compounds form the basis, but are insufficient alone. • The science on mixture ecotoxicology provides regulatory tools and options (mainly based on CA, accompanied by error estimations)

  44. Chemical Mixtures occurrences, (eco)toxicity and relevance for water quality in Europe Thomas Backhaus University of Gothenburg thomas.backhaus@dpes.gu.se

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