This document describes SimpleBox4nano, a multimedia fate model for modeling the environmental exposure of nanomaterials. The model is an adaptation of the SimpleBox4 multimedia fate model to account for processes relevant to particles and engineered nanoparticles. It models the fate of nanoparticles in air, water, soil and sediment compartments and processes such as dry and wet deposition, sedimentation, resuspension, heteroagglomeration and dissolution. The model requires parameters like attachment efficiency, dissolution rates, nanoparticle size and properties, and emission rates. Guidance and standard test guidelines are still needed for measuring some input parameters. The model output can be used for screening level exposure assessment and life cycle assessment. It may take less than 30 days to reach

1. SimpleBox4nano
SimpleBox approach to exposure
modelling of nanomaterials
Joris Quik
ECHA NMEG-10, 7th November 2017

2. Contents
1. Background
2. SimpleBox4.01-nano
3. Input
4. Output
5. Guidance and next steps

3. Modelling exposure to nanomaterials
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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
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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
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air
soilwater
sediment
Meesters 2014 ES&T

6. Multimedia fate model – SimpleBox4nano
● Transformation of ENPs
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*
*
**
**
**
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
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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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*
*
* *
* *
**

11. Inputs explaining variation output SUMENP&ENP-PM
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air
soilwater
sediment
ENP size
Attachment Efficiency (+soil) Attachment Efficiency
Natural PM size and density (+soil) Natural PM size
ENP size
Dissolution rate (Ag only)Dissolution rate (Ag only)
Aerosol size

12. Input sensitivity SimpleBox4nano
Sediment concentration plotted against
the attachment efficiency and dissolution rate
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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
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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
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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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