3. Modelling exposure to nanomaterials
| Date_Text3
Nanomaterials in the environment
● Emission
● Fate
● Exposure
● Effects
4. Multimedia fate model – SimpleBox 4
● Fate processes
● Landscape scenario (nested)
– Regional, Continental & Global
(arctic, moderate, tropic)
– 3 soil and water types
4
air
soilwater
sediment
Hollander 2016 Chemosphere
Van de Meent ECHA/2014/253
rivm.nl/SimpleBox
Natural
Agricultural
Urban/Other
Lake
River
Sea
5. Multimedia fate model – SimpleBox4nano
● Adaptation of transport
processes to particles
– Engineered Nanoparticles
(ENP)
– Particulate Matter (PM)
● New algorithms for
– Dry & wet deposition
– Sedimentation & resuspension
● No volatilisation
5
air
soilwater
sediment
Meesters 2014 ES&T
6. Multimedia fate model – SimpleBox4nano
● Transformation of ENPs
6
*
*
**
**
**
Dissolution
Heteroagglomeration
Nanoparticle (1-100 nm)
PM<0.45µm or Natural colloid
PM>0.45µm or Coarse particle
Meesters 2014 ES&T
Degradation
*
Ion or dissolved metal
7. Model Use
● For screening level exposure assessment
– Development (PhD thesis J. Meesters, available upon request)
– Statistical method for probabilistic RA (Jacobs et al. 2016)
– Analysis for modelling microplastics (Kooi et al. 2017)
● Life Cycle Assessment
– deriving fate factors (Ettrup et al. 2017)
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8. Input parameters
● Attachment efficiency [ENP-PM]
– Soil and water type specific
● Dissolution rate (s-1)
– Soil and water type specific
● Radius (nm) & Density (kg m-3)
– Primary ENP
● Emission rate (t/y)
– Primary ENP and/or other forms
8
Natural
Agricultural
Urban/Other
Lake
River
Sea
9. How to find input parameters
● Attachment efficiency (measure or calculate)
– Methods in scientific literature
– Basic approach in OECD dispersion stability TG 318
● Dissolution rate (measure or expert judgement)
– Development of OECD TG
● Size and density primary ENP (manufacturer data)
● Size and density heteroagglomerate (measure and/or calculate)
– Monitoring data
● Emission rates (Calculate from Production Volume)
– Methods and models in scientific literature
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10. Uncertainty of new aspects
● Uniform distributions:
– Size of ENP (1 – 100 nm)
– Attachment efficiency (10-4 – 1)*
– Dissolution rate (s-1)*
› Ag: 10-20 – 10-5
› TiO2: 10-20 – 10-13
› C60: 0
● Size and density PM (realistic)*
*Independent for each compartment and particle type (PM<0.45 PM>0.45)
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*
*
* *
* *
**
12. Input sensitivity SimpleBox4nano
Sediment concentration plotted against
the attachment efficiency and dissolution rate
12
Free ENPs Bioavailable Total particulate
Meesters 2017 thesis
Bioavailability in
current regulation:
< 0.45 µm
▪ Free nanoparticles
▪ Heteroagglomerates
(<0.45 µm)
▪ Heteroagglomerates
(>0.45 µm)
13. Steady state - Output
● Some removal processes are
very slow:
– Burial in sediment or
Soil leaching/erosion
● How long does it take to reach
steady state for ENPs?
● Average values taken from
previous runs
13
air
soilwater
sediment
14. Time to steady state
● Time to steady state depends
on ENP fraction considered
– <30 days for free ENPs
– Not reached in marine
environment, otherwise:
– <100 years for bioavail.
ENPs to reach 90%
– <100.000 years for total,
air much faster <30 days.
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15. Modelling options - output
● Use dynamic simulation to estimate PEC at defined time point
– E.g. 100 year PECs
● Deem current steady state approach acceptable
– At least for regional and continental scale
● Which fraction to consider relevant PEC?
– Free, <0.45 um, >0.45 um
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*
*
* *
* *
**
16. Guidance and guidelines required:
● TG on dissolution
● TG on measuring attachment efficiency
● Guidance/TG on Size distribution
● Current Emission scenarios relevant for NPs?
– SimpleTreat modelling fractions emitted other than free ENPs
● Guidance on defining relevant PECs
– Bioavailable fraction
– Steady state or time dynamic
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17. Next steps in
model development:
● Model refinement in NanoFASE project
– Finding the best algorithms
● Model calibration in caLIBRAte
● Goal:
A regulatory relevant screening level
multimedia fate model for particles
17
rivm.nl/SimpleBox
joris.quik@rivm.nl
18. Acknowledgements
This work is supported by funding from the European Union’s Horizon 2020 research and
innovation programme under grant agreement No 646002 “NanoFASE” and by
NanoNextNL, a micro- and nanotechnology consortium of the Government of The
Netherlands and 130 partners.
References:
Meesters, J.A.J., K. Veltman, A.J. Hendriks, and D. van de Meent. 2013. 'Environmental exposure assessment of engineered nanoparticles:
why REACH needs adjustment', Integr Environ Assess Manag, 9: e15-26.
Meesters, J.A.J., A.A. Koelmans, J.T.K. Quik, A.J. Hendriks, and D. van de Meent. 2014. 'Multimedia Modeling of Engineered Nanoparticles
with SimpleBox4nano: Model Definition and Evaluation', Environ Sci Technol, 48: 5726-36.
Meesters, J.A.J., J.T.K. Quik, A.A. Koelmans, A.J. Hendriks, and D. van de Meent. 2016. 'Multimedia environmental fate and speciation of
engineered nanoparticles: a probabilistic modeling approach', Environ Sci Nano, 3: 715-27.
Jacobs, R., J.A.J. Meesters, C.J. ter Braak, D. van de Meent, and H. van der Voet. 2016. 'Combining exposure and effect modeling into an
integrated probabilistic environmental risk assessment for nanoparticles', Environ Toxicol Chem, 35: 2958-67.
Ettrup, K., A. Kounina, S.F. Hansen, J.A.J. Meesters, E.B. Vea, and A. Laurent. 2017. 'Development of Comparative Toxicity Potentials of TiO2
Nanoparticles for Use in Life Cycle Assessment', Environ Sci Technol, 51: 4027-37.
Hollander, A., M. Schoorl, and D. van de Meent. 2016. 'SimpleBox 4.0: Improving the model while keeping it simple', Chemosphere, 148:
99-107.
Meent, van de, Dik, J. Quik, T. Traas, 2014. Identification and preliminary analysis of update needs for EUSES, ECHA/2014/253
Meesters, J.A.J. 2017. 'Environmental Exposure Modeling of Nanoparticles', PhD thesis, Radboud University Nijmegen.
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