occurrences, (eco)toxicity and relevance for water quality in
Europe Chemical Mixtures Thomas Backhaus University of Gothenburg
[email protected]
Slide 2
Chemical Mixtures Mixtures of toxic chemicals Aquatic
Ecosystems Ecotoxicology Focus
Slide 3
PREDICT BEAM ACE EDEN CONTAMED Inspired from work in the
following EU projects
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Monitoring Data Sweden Stina Adielsson, Sarah Graaf, Melle
Andersson & Jenny Kreuger (2009) Resultat frn miljvervakningen
av bekmpningsmedel (vxtskyddsmedel). ISSN 0347-9307. Swedish
University of Agricultural Sciences, Uppsala.
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Mixture effect is higher than the effect of each individual
component Individual quality targets not necessarily sufficient The
ecotoxicology of chemical mixtures
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Walter, H., et al. (2002) Mixture toxicity of priority
pollutants at No Observed Effect Concentrations (NOECs).
Ecotoxicology 11:299-310. Mixture of priority pollutants
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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
Slide 8
Mixture toxicity concepts E Mix = Effect of the mixture of n
compounds E i = Effect of substance i, when applied singly c i =
Concentration of component i in the mixture (i = 1...n) ECx i =
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 Similarly acting substances:
Concentration Addition Dissimilarly acting substances: Independent
Action
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Mixture toxicity concepts E Mix = Effect of the mixture of n
compounds E i = Effect of substance i, when applied singly
Dissimilarly acting substances: Independent Action Assumes that
components affect the same endpoint, but do that completely
independent of each other
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Biochemical networks
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Ecological networks
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Mixture toxicity concepts E Mix = Effect of the mixture of n
compounds E i = Effect of substance i, when applied singly
Dissimilarly acting substances: Independent Action Assumes that
components affect the same endpoint, but do that completely
independent of each other In contradiction to A.The physiological
and ecological networking of life B.The notion of a narcotic mode
of action, common to all organic chemicals.
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Mixture toxicity concepts E Mix = Effect of the mixture of n
compounds E i = Effect of substance i, when applied singly c i =
Concentration of component i in the mixture (i = 1...n) ECx i =
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 Similarly acting substances:
Concentration Addition Dissimilarly acting substances: Independent
Action
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How? Nonylphenol River basin modeling of the expected
consequences of chemical mixtures Sumpter, J., et al. (2006)
Modeling Effects of Mixtures of Endocrine Disrupting Chemicals at
the River Catchment ScaleE, Env. Sci. Techn. 40:5478-5489
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Nonylphenol Natural estrogens (E1, E3), Pharmaceutical (EE2)
River basin modeling of the expected consequences of chemical
mixtures Sumpter, J., et al. (2006) Modeling Effects of Mixtures of
Endocrine Disrupting Chemicals at the River Catchment ScaleE, Env.
Sci. Techn. 40:5478-5489
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It is the opinion of the SCHER that the CA approach may be
assumed as a temporary interim method for deriving EQs for
mixtures. SCHER, Opinion on the Chemicals and the Water Framework
Directive: Technical Guidance for Deriving Environmental Quality
Standards (2010) How?
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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 Properties of
Concentration Addition
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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 Mode of Action
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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
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Contribution of low, individually non-toxic concentrations
Backhaus, Blanck, Sumpter, On the ecotoxicology of pharmaceutical
mixtures, 2008
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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
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The maximum possible difference between IA- and CA- predicted
toxicities 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. TU: Toxic Unit, ratio
between conc and EC50 Junghans, et al. (2006) Application and
validation of approaches for the predictive hazard assessment of
realistic pesticide mixtures. Aquatic Toxicology 76, 2006
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Assumes similar mode of action of all mixture components
Differences to the toxicities predicted by the competing concept of
IA are small and negligible Properties of Concentration
Addition
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Assumes similar mode of action of all mixture components
Extrapolates from single substance to mixture toxicity Assumes no
interaction between the components in the mixture Properties of
Concentration Addition
Slide 25
Single Components Laboratory EQS (PNEC) Single Components Field
Mixture Field
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Vighi et al (2003) Water quality objectives for mixtures of
toxic chemicals: problems and perspectives, Ecotox. Env. Safety,
54, 139-150 Applying 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 Properties of Concentration
Addition
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Assumes similar mode of action of all mixture components
Extrapolates from single substance to mixture toxicity Assumes no
interaction between the components in the mixture Properties of
Concentration Addition
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A synergistic mixture Laetz et al., EHP, 2008 S ynergistic
effects of binary mixtures of carbamate (CB) and organophospate
(OP) pesticides DZN: Diazinon; MLN: Malathion; CRL: Carbaryl CBN:
Carbofuran; CFS: Clopyrifos
Slide 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.
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TU Distribution for a 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 Sum of TUs = 0.98
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What happens if a compound is synergized? SynFactor = 2
SynFactor = 10 Rank of synergised compound Sum of Toxic Units
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Average Synergy Factor What happens if n compounds are
synergized?
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Rare Limited to mixtures with few compounds Multi-component
mixtures dampen quantitative consequences Interactions, Synergisms,
Antagonisms
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Assumes similar mode of action of all mixture components
Extrapolates from single substance to mixture toxicity Assumes no
interaction between the components in the mixture Properties of
Concentration Addition
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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
Options for overcoming the limitations of CA/IA
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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) Options for overcoming the limitations of
CA/IA
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Interactions Need for a case-by-case consideration
Multi-component mixtures are comparatively robust Options for
overcoming the limitations of CA/IA
Slide 43
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) Summary and
Conclusions
Slide 44
occurrences, (eco)toxicity and relevance for water quality in
Europe Chemical Mixtures Thomas Backhaus University of Gothenburg
[email protected]
