The document discusses uncertainties in modeling human and ecological risks from chemicals, nanomaterials, and microplastics in the environment. Current risk management is reactive, substance-by-substance, and resource intensive. Modeling risks considers sources, emission, fate, exposure, and effects, but faces many uncertainties. For chemicals, better use and spatially explicit emissions data is needed. Fate modeling requires improved degradation data, especially for ionizing compounds. Effect modeling needs more data on mixtures, genomics, and untested substances. For nanomaterials and microplastics, long-term fate and effects are particularly uncertain due to degradation questions and lack of data.
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Modelling risks of chemicals, nanomaterials and microplastics
1. Uncertainties in modelling human and
ecological risks of chemicals, nanomaterials
and (micro)plastics
Ad M.J. Ragas
Department of Environmental Science, Radboud University, Nijmegen, The Netherlands
Department of Science, Open Universiteit, Heerlen, The Netherlands
OECD Workshop on
Managing Contaminants of Emerging Concern in Surface Waters: Scientific developments and cost-effective policy responses
Paris, 5 February 2018
2. Risks of chemicals, nanomaterials and (micro)plastics
Current management:
• Reactive
• Substance-per-substance
• Resource intensive
• New substances
3. Modelling aquatic risks of chemicals, nanomaterials and
(micro)plastics
SOURCES
• Consumers
• Agriculture
• Industry
• Etc.
EMISSION
• Point source
• Diffuse
FATE
• Partitioning
• Degradation
• Bioaccumu-
lation
EXPOSURE
• Spatial
variation
• Behaviour
EFFECTS
• Human
• Ecosystems
• Economy
4. Example: modelling pharmaceuticals in the environment
National
Consumption Data
Substance
Properties
Water & Sediment
Concentrations
MODEL
5. Uncertainties in modelling aquatic risks of chemicals
SOURCES
• New
substances
• Product
composition
• Spatially
explicit use
data
EMISSION
• Linking use to
emission
FATE
• Ionising
compounds
• Biodegradation
• Secondary
effects (e.g.
Antibiotic
Resistance)
EXPOSURE
• Exotic
exposure
routes (e.g.,
vultures &
bees)
EFFECTS
• Untested
substances =>
(eco)toxico-
genomics?
• Mixture effects
• Interaction
with other
stressors
6. Uncertainties in modelling aquatic risks of chemicals
SOURCES
• New
substances
• Product
composition
• Spatially
explicit use
data
EMISSION
• Linking use to
emission
FATE
• Ionising
compounds
• Biodegradation
• Secondary
effects (e.g.
Antibiotic
Resistance)
EXPOSURE
• Exotic
exposure
routes (e.g.,
vultures &
bees)
EFFECTS
• Untested
substances =>
(eco)toxico-
genomics?
• Mixture effects
• Interaction
with other
stressors
7. Uncertainties in modelling aquatic risks of nanomaterials
SOURCES
• New materials
• Specification of
products and
materials
• (Spatially
explicit) use
data
EMISSION
• Linking use to
emission
FATE
• Partitioning
(colloid
chemistry)
• Dissolution
• Aggregation
• Detection
• Long-term fate
EFFECTS
• Toxicity testing
protocols
• Physical effects
• Long-term
effects
• Detection
SimpleBox4Nano
EXPOSURE
• Exposure
metric: weight,
surface area,
other?
8. Uncertainties in modelling aquatic risks of nanomaterials
SOURCES
• New materials
• Specification of
products and
materials
• (Spatially
explicit) use
data
EMISSION
• Linking use to
emission
FATE
• Partitioning
(colloid
chemistry)
• Dissolution
• Aggregation
• Detection
• Long-term fate
EFFECTS
• Toxicity testing
protocols
• Physical effects
• Long-term
effects
• Detection
SimpleBox4Nano
EXPOSURE
• Exposure
metric: weight,
surface area,
other?
9. Uncertainties in modelling aquatic risks of (micro)plastics
SOURCES
• Macroplastics
• Cosmetics
• Tyres
• Synthetic
textiles
• ????
EMISSION
• Linking use to
emission
FATE
• Degradation
macro to micro
• Dispersal
behaviour in
relation to
specific weight
• Vehicle?
• Long-term fate
• Deep seas
• Detection
EFFECTS
• Physical effects
• Indirect effects
• Long-term
effects
• Detection
EXPOSURE
• Spatial
variation
10. Uncertainties in modelling aquatic risks of (micro)plastics
SOURCES
• Macroplastics
• Cosmetics
• Tyres
• Synthetic
textiles
• ????
EMISSION
• Linking use to
emission
FATE
• Degradation
macro to micro
• Dispersal
behaviour in
relation to
specific weight
• Vehicle?
• Long-term fate
• Deep seas
• Detection
EFFECTS
• Physical effects
• Indirect effects
• Long-term
effects
• Detection
EXPOSURE
• Spatial
variation
11. Key messages
• We need to get more grip on product composition and (spatially
explicit) use data in order to produce reliable emission estimates
• In order to improve the prediction of the fate of chemicals in the
environment we need to focus on degradation data and the
behaviour of ionizing compounds
• In order to improve the prediction of effects of chemicals we need to
focus on Quantitative Structure Activity Relationships (QSARs),
(eco)toxicogenomics and mixture effects
• The two most important questions for (micro)plastics and
nanomaterials are long-term fate (degradation) and effects