Modelling

Modelling

Understanding the Journey of Microplastics through Science and Simulation

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Introduction

Computer simulations

1. How serious is the plastic litter pollution in EU waters?
2. What do the numbers say?
3. How many are there in the aquatic environment?
4. Where do they come from?
5. Where do they go?
6. Where are the accumulation hotspots?
7. Do they release harmful chemicals?

This question remain guesswork as long as we have to rely on the highly heterogeneous and scattered field data, which requires a lot of effort and processing time.

Physics-based models

Environmental fate and exposure of plastic associated chemicals

Conclusions

Mathematical models, which solve the fundamental equations of physics for the motion of particles in water, provide a complementary tool to fill in the gaps in space and time, not covered by the field sampling. However, these models do not yield exact solutions. We have to limit the number of points, located in space and time, where we solve the equations, as limited by computer memory and computing time.

Eventually, even the most detailed models are not more reliable than weather forecasting models (which solve the same physics).

Computer simulations

Physics-based models

Sediment plume © ESA

Within LABPLAS a choice was made to build physics-based models which simulate the dispersal of clouds of particles in terms of mass concentration, similar as is done for sediment transport in hydraulic engineering.

Settling velocity of microplastic particles

Reduced complexity models

Detailed multidimensional models

Physics-based models

Results for the 2DH Elbe estuary model

The physics-based models developed in LABPLAS:

• Fill the gaps in space and time of mass (and number) concentrations from the field sampling (WP2) and thus complements these data, helping to better interpret the field data.
• Help to understand the pathways, fate and concentrations of microplastics in different compartments (surface, water column, bottom) of riverine, coastal and offshore environments.

Using the model results

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Similar as for fine sediment, microplastic particles continuously settle and resuspend over each tidal cycle.

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RESULTS

Reduced complexity models

In order to reduce computational time, the complexity of the 3D reality can be reduced to a depth-averaged (2DH) model, as applied to the Elbe, or even a 1D model for rivers upstream of their estuary.The ePLAS 1D river basin model, developed by Radboud University, allows fast calculations, by solving only a mass balance for the microplastics (considering discrete size classes and various processes) and assuming local equilibrium, using river discharge data from external sources.

Concept of ePLAS model

Results of ePLAS model

Reduced complexity models

Concept of ePLAS model

• Integration with ePiE: ePLAS expands the ePiE model to include microplastic fate processes across multiple environmental compartments.
• Multimedia Box Model: Each river stretch between two nodes is divided into three boxes – water layer, bed load layer, and sediment layer – to represent interactions and transport of microplastics.
• Steady-State Assumption: Initially assumes dynamic equilibrium (level 3 model) where inputs and outputs are balanced; used for a first approximation despite real-world variability.

• Sedimentation and resuspension
• Burial and dissipation from sediment
• Future Potential: May evolve into a dynamic model if sufficient temporal data and computational resources become available.

• Key Processes Modelled:
• Advective transport (e.g., water flow, bed load movement)
• Heteroaggregation (microplastics binding to suspended particles)

Concept of ePLAS model

Results of ePLAS model

Water layer:

• Smaller-sized tyre wear particles (TWP) exhibit higher mass concentrations retained within both the main river channel and tributaries;
• TWP mass concentrations generally decrease along the main river channel from upstream to downstream;
• Tributaries consistently display higher TWP mass concentrations compared to the main river channel.

Results of ePLAS model

Settling velocity of microplastic particles

It can change over time by biofouling or breakup due to degradation

Concept of Population Balance Equations

Settling velocity of microplastic particlesSettling velocity of microplastic particles

Environmental fate and exposure of plastic associated chemicals

• Chemicals used in plastic will leach from plastic particles into the surrounding environment at all stages of use – from manufacture to use and at end-of-life.
• Evaluating the contribution and human health risks that leaching of chemicals from microplastic particles represents as a vector of exposure, relative to all other exposure pathways, can be best explored using multimedia environmental fate and bioaccumulation models.

Estimating human health risks

Microplastic in marine sediments

Environmental fate and exposure of plastic associated chemicals

• Microplastic particles can sink to the seafloor when they are denser than seawater or when they aggregate with particles with higher density.
• Suspended sediment from the water column can settle on top of the microplastic and bury it.
• Animals mix the sediment with their burrowing movements and distribute the microplastic within the bioactive surface layer of the seabed.
• Microplastic particles can leach chemicals into their environment.
• In seafloor sediments, leached chemicals accumulate in the vicinity of the particle.

Microplastic in marine sediments

Biogeochemical processes in the seafloor sediment

Microplastic in marine sediments

Biogeochemical processes in the seafloor sediment

The transport of microplastic particles into seafloor sediments and the release of additive chemicals has been implemented into an existing benthic biogeochemical transport reaction model.

Biogeochemical processes in the seafloor sediment

Realease of chemicals from microplastic

Exemplary results for the concentration of flame retardant BDE153 leaching from a polyamid microparticle as function of the depth below the seafloor at three sites. The model includes the transport of the microplastic particle within the sediment over time and the release and transport of the leachate in the pore water over time.

Realease of chemicals from microplastic

Estimating human health risks

• Given the multimedia partitioning behaviour of organic chemicals used as plastic additives, holistic modelling considering all exposure pathways is needed to estimate human exposure.
• When considering the available toxicological data for four well-studied plastic additives, microplastics represent a concerning health risk when the ingestion rate reaches 10 mg/day of 1 micron size plastic particles at maximum contamination levels.

Estimating human health risks

Estimating human health risks

• Holistic exposure models that consider the release of chemicals from all life-cycle stages of plastics (incl. manufacture, use and end-of-life) are needed to evaluate environmental and human health exposure to chemicals.

• Exposure to chemicals via the ingestion of microplastic (one of the possible exposure pathways) has been included as part of a bioaccumulation food web model.

• More data are needed to better characterize and quantify the ingestion of microplastic by organisms at all food web levels, including humans. Data quantifying the concentrations of chemicals in the microplastic are also needed.

• Adopting realistic worst-case scenarios, the relative contribution that microplastic represents as a significant source of exposure is observed to be relatively small in comparison to other exposure pathways, such as the diet for hydrophobic organic..

Estimating human health risks

Conclusions

• Numerical simulation models can be used as tool to study the whereabouts of plastics in rivers, coastal waters and seas and their sediment bottoms. They complement field data by filling in missing data for the entire model domain.
• Unfortunately, field sampling and their processing is time and resources consuming, resulting in a large scarcity of field data, insufficient for accurate calibration and validation of the models.
• More research is needed to further improve the models to incorporate additional processes (in particular the exchange with the bed and the shorelines).
• Human risks for exposure to chemical leachates from plastics can be estimated with a foodweb model along with expert opinion to critically evaluate all the models used, taking into account the many sources of uncertainty.
• Based on current estimated exposure to microplastic (600 ng/d), ingestion of contaminated microplastics does not rise human health concerns.

Conclusions

Follow us!

The particle transport model is coupled to simultaneous computation of the driving forces of water motion (currents and waves), which is driven by atmospheric forcing (wind and pressure) and tides, as well as sediment transport of both sand and mud, allowing to take into account hetero-aggregation of microplastic particles with mud flocs and energy partitioning over both plastics and sediments.Eventually (after a transient initiation period), the motion of the mass concentration patterns over time can be visualized over the model domain.

PROBLEM: Which particle properties to take when no particle is identical?PROPOSED SOLUTIONS using statical distributions of selected parameter:

1. Size-based population balance equations (PBE) for a chosen polymer type.
2. Fall velocity-based PBE for two populations: buoyant and non-buoyant particles (assuming to cover the diversity of all parameters).

WARNING

Do not blindly believe what the model results show! The results of the model cannot be better than the input it uses. The major problems are: The very low resolution in time and space of field data, besides the high variability in results. The lack of information and knowledge of the exact sources of the plastic litter: where, when and how much effectively enters the aquatic environment? * *Mass Flow Analysis, often used to estimate these influxes (without location specification!), show a large gap between the estimated loss in the environment and which fraction of this effectively reaches water.

The settling (or rising) velocity in still water, i.e., the fall velocity, is the key parameter in the model which characterizes the particle motion. The fall velocity depends on: (1) the size and shape of the particle, (2) the difference between the particle density and the water density, (3) the molecular viscosity of the water (which varies with temperature and salinity).

How to use the detailed physics-based model results as input for other models?

• Provide data on plastic and sediment accumulation on the sediment bed, necessary as input for the biogeochemical model, developed by GEOMAR, which aims to quantify the burial of MP and the remobilization of leachates from the bed to the water column.
• Provide data to the foodweb model, developed by Environmental Research, which aims at estimating the risk for humans by consumption of fish living in plastic polluted waters.
• Provide complementary, high-resolution data for the calibration and validation of a reduced complexity model for EU rivers, like ePLAS, developed by Radboud University.