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DSD-INT 2023 3D hydrodynamic modelling of microplastic transport in lakes - Jagau

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Presentation by Lisa Jagau (University of Bayreuth, Germany) at the Delft3D User Days, during the Delft Software Days - Edition 2023 (DSD-INT 2023). Thursday, 16 November 2023, Delft.

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Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 1 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
3D Hydrodynamic Modeling of Microplastic
Transport in Lakes
Lisa Jagau, Vadym Aizinger
Chair of Scientific Computing
CRC1357 Microplastics | University of Bayreuth
lisa.jagau@uni-bayreuth.de
Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 2 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
Objective
1
Image source: Plastics Europe, 2022
Motivation
▪ Increased usage of plastic products has led to
(micro)plastics pollution in all environmental
compartments
▪ Microplastics (MP) potentially harmful,
many organisms exposed directly in
hydrosphere
▪ Many studies have focused on marine
MP, limnic systems less researched
Approach
▪ Use case study: Großer Brombachsee,
Germany
− Part 1: Set up hydrodynamic model
− Part 2: Add MP transport
Global plastic use by application:
Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 3 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
Study Area
Großer Brombachsee
▪ Surface area 9.1 km2
▪ Average depth 15.9 m
▪ Deepest point 35 m
▪ Main inflow in west, main outflow in
east
▪ Water led from River Danube to River
Main watershed
▪ Main function: supply (dry) Franconia
with water from south of Germany +
buffer flooding of River Altmühl
▪ Strongly varying water level due to
different forms of usage + climatic
conditions
2
Image source: Fischereiverband Mittelfranken, 2022
Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 4 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
Part 1: Hydrodynamic Model
Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 5 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
Density Function for Mesh Generation
4
Scatter set 2
~ 𝑏𝑒𝑑 𝑙𝑒𝑣𝑒𝑙 𝑠𝑙𝑜𝑝𝑒−1
𝑟𝑒𝑓𝑖𝑛𝑒 𝑎𝑙𝑙 𝑎𝑟𝑒𝑎𝑠 𝑤𝑖𝑡ℎ 𝑤𝑎𝑡𝑒𝑟 𝑑𝑒𝑝𝑡ℎ < 15𝑚,
𝑏𝑦 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑦𝑖𝑛𝑔 𝑤𝑖𝑡ℎ 𝑓𝑎𝑐𝑡𝑜𝑟 0.8
Scatter set 1
~ 𝑤𝑎𝑡𝑒𝑟 𝑑𝑒𝑝𝑡ℎ
𝑡𝑎𝑘𝑒 𝑚𝑖𝑛𝑖𝑚𝑢𝑚 𝑣𝑎𝑙𝑢𝑒 𝑎𝑡 𝑒𝑎𝑐ℎ 𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛
Resulting Scatter Set for Mesh Density
Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation
Folie 6 | <Titel des Vortrags> | <Name der/des Bearbeiter/s>
Computational Mesh with Bed Level
5
Computational Mesh
▪ 8718 mesh elements
ranging from 30-120m
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DSD-INT 2023 3D hydrodynamic modelling of microplastic transport in lakes - Jagau

  • 1. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 1 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> 3D Hydrodynamic Modeling of Microplastic Transport in Lakes Lisa Jagau, Vadym Aizinger Chair of Scientific Computing CRC1357 Microplastics | University of Bayreuth lisa.jagau@uni-bayreuth.de
  • 2. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 2 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Objective 1 Image source: Plastics Europe, 2022 Motivation ▪ Increased usage of plastic products has led to (micro)plastics pollution in all environmental compartments ▪ Microplastics (MP) potentially harmful, many organisms exposed directly in hydrosphere ▪ Many studies have focused on marine MP, limnic systems less researched Approach ▪ Use case study: Großer Brombachsee, Germany − Part 1: Set up hydrodynamic model − Part 2: Add MP transport Global plastic use by application:
  • 3. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 3 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Study Area Großer Brombachsee ▪ Surface area 9.1 km2 ▪ Average depth 15.9 m ▪ Deepest point 35 m ▪ Main inflow in west, main outflow in east ▪ Water led from River Danube to River Main watershed ▪ Main function: supply (dry) Franconia with water from south of Germany + buffer flooding of River Altmühl ▪ Strongly varying water level due to different forms of usage + climatic conditions 2 Image source: Fischereiverband Mittelfranken, 2022
  • 4. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 4 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Part 1: Hydrodynamic Model
  • 5. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 5 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Density Function for Mesh Generation 4 Scatter set 2 ~ 𝑏𝑒𝑑 𝑙𝑒𝑣𝑒𝑙 𝑠𝑙𝑜𝑝𝑒−1 𝑟𝑒𝑓𝑖𝑛𝑒 𝑎𝑙𝑙 𝑎𝑟𝑒𝑎𝑠 𝑤𝑖𝑡ℎ 𝑤𝑎𝑡𝑒𝑟 𝑑𝑒𝑝𝑡ℎ < 15𝑚, 𝑏𝑦 𝑚𝑢𝑙𝑡𝑖𝑝𝑙𝑦𝑖𝑛𝑔 𝑤𝑖𝑡ℎ 𝑓𝑎𝑐𝑡𝑜𝑟 0.8 Scatter set 1 ~ 𝑤𝑎𝑡𝑒𝑟 𝑑𝑒𝑝𝑡ℎ 𝑡𝑎𝑘𝑒 𝑚𝑖𝑛𝑖𝑚𝑢𝑚 𝑣𝑎𝑙𝑢𝑒 𝑎𝑡 𝑒𝑎𝑐ℎ 𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 Resulting Scatter Set for Mesh Density
  • 6. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 6 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Computational Mesh with Bed Level 5 Computational Mesh ▪ 8718 mesh elements ranging from 30-120m
  • 7. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 7 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Outflow Boundary ▪ Measured water discharge Schematic Model 6 Inflow Boundary ▪ Measured water discharge ▪ Measured water temperature Wall/ Lake Bed Behavior ▪ No normal flow ▪ Wall: Free-slip ▪ Lake Bed: Constant Manning friction 0.0023 s/m1/3 Free Surface Boundary ▪ 10m wind speed and direction ▪ 2m air temperature ▪ Relative humidity ▪ Cloud cover ▪ Precipitation
  • 8. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 8 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Temperature Measurements 2012 7 -30 -25 -20 -15 -10 -5 0 6 8 10 12 14 16 18 20 22 Depth [m] Temperature [°C] May, 21st July, 16th September, 10th December, 03rd
  • 9. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 9 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> May, 21st July, 16th September, 10th December, 03rd Vertical Mesh Sensitivity Analysis 8 Temperature Profiles, 30 sigma-layers Temperature Profiles, 30 z-layers Temperature [°C] Depth [m] May, 21st July, 16th September, 10th December, 03rd Temperature [°C] Depth [m] • z-layer model shows more realistic stratification
  • 10. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 10 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Vertical Mesh Sensitivity Analysis 9 • Vertical grid converges at 60 equidistant z-layers Temperature [°C] Depth [m] Temperature [°C] Depth [m] May, 21st July, 16th September, 10th December, 03rd Temperature Profiles, 30 z- / 60 z-layers Temperature Profiles, 60 z- /80 z-layers 30 layers 60 layers 60 layers 80 layers
  • 11. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 11 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Model Calibration 10 Temperature Profiles, September, Varying horizontal diffusivity • Realistic profiles, but 1-2°C too cold • Ice formation not included in model → Repeat simulations with start date in spring Temperature Profiles, September, Varying vertical diffusivity Temperature [°C] Depth [m] 1 m2/s measurements 3 m2/s 5 m2/s hor. diffusivity: vert. diff.: 5e-7 m2/s hor. vis.: 10 m2/s vert. vis.: 5e-5 m2/s Temperature [°C] Depth [m] measurements 5e-7 m2/s 1e-6 m2/s 3e-6 m2/s vert. diffusivity: hor. diff.: 5 m2/s hor. vis.: 10 m2/s vert. vis.: 5e-5 m2/s
  • 12. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 12 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> 11 May, 21st July, 16th September, 10th December, 03rd Temperature [°C] Depth [m] Temperature Profiles, Simulation Start in March Best Calibration Parameters Horizontal diffusivity: 1 m2/s Vertical diffusivity: 5e-7 m2/s horizontal viscosity: 0 m2/s Vertical viscosity: 5e-6 m2/s Model Calibration
  • 13. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 13 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Fine Tuning of Computational Mesh 12 Temperature [°C] Depth [m] measurements refined metalimnion equidistant layers Temperature Profiles, September, Adjusted Vertical Layers • Refinement of metalimnion results in better temperature profiles 20 z-layers, 1m 30 z-layers, 0.33m 5 z-layers, 0.7m 5 sigma-layers -15 / -35m 20 x 2.7% (54%) -5 / -15m 30 x 0.9% (27%) 2 / -5m 10 x 1.9% (19%)
  • 14. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 14 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Fine Tuning of Computational Mesh 13 8718 elements 34872 elements Temperature Profiles, September, Increased Horizontal Resolution Depth [m] Temperature [°C] measurements 34872 elements 8718 elements • Difference not large enough to justify additional computing ressources
  • 15. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 15 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Summary of Part 1 14 Hydrodynamic Model ▪ Unstructured mesh with 8718 elements ▪ 60 vertical z- layers: refined metalimnion + sigma layers near free surface ▪ Ignore lake freezing effects Best Calibration Parameters Horizontal diffusivity: 1 m2/s Vertical diffusivity: 5e-7 m2/s horizontal viscosity: 0 m2/s Vertical viscosity: 5e-6 m2/s Image source: Fischereiverband Mittelfranken, 2022
  • 16. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 16 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Part 2: MP Transport
  • 17. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 17 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Motivation 16 Eulerian vs Lagrangian Particle Tracking Approach ▪ Eulerian approach more efficient for large concentrations ▪ More flexible for future applications (aging, interactions, heteroaggregation, …) ➢ For first impression of how MP distributes in the model use existing sediments routine of Delft3D FM (non-cohesive particles) Image source: Hüffer et al. 2017
  • 18. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 18 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Outflow Boundary ▪ Measured water discharge Schematic Model 17 Inflow Boundary ▪ Measured water discharge ▪ Measured water temperature Wall/ Lake Bed Behavior ▪ No normal flow ▪ Wall: Free-slip ▪ Lake Bed: Constant Manning friction 0.0023 s/m1/3 Free Surface Boundary ▪ 10m wind speed and direction ▪ 2m air temperature ▪ Relative humidity ▪ Cloud cover ▪ Precipitation 0.1 kg/m3
  • 19. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 19 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Example Results – PS Concentration 18 0.1 mm Polystyrene particles (1030 kg/m3)
  • 20. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 20 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Example Results – MP on Lake Bed 19 0.1 mm Polystyrene particles (1030 kg/m3) 0.5 mm Polystyrene particles (1030 kg/m3) 0.1 mm Polycaprolactone particles (1140 kg/m3)
  • 21. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 21 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Challenges and Limitations 20 • Simulating bouyant particles • Simulating fast-sinking particles • Computationally expensive to simulate all different types and sizes of MP particles separately • Limited options in existing sediments routine of Delft3D FM
  • 22. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 22 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Outlook 21 ▪ More MP simulations with existing sediments routine − Different types of particles − Different input scenarios ▪ Develop MP module within Delft3D FM based on existing sediments routine − Account for MP properties, apart from size and density − Include aging, interaction and heteroaggregation of MP particles − Calibrate and validate with experimental MP data ▪ Validate for different types of lakes 21
  • 23. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 23 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> Thank You! Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project Number 391977956 – SFB 1357
  • 24. Arbeitsbereich MuSe (Marketing und Services) | LS Marketing & Innovation Folie 24 | <Titel des Vortrags> | <Name der/des Bearbeiter/s> References [1] Z. Akdogan and B. Guven. Microplastics in the environment: A critical review of current understanding and identification of future research needs. Environmental Pollution, 254:113011, 2019. [2] A. Bagaev, A. Mizyuk, L. Khatmullina, I. Isachenko, and I. Chubarenko. Anthropogenic fibres in the Baltic Sea water column: Field data, laboratory and numerical testing of their motion. Science of The Total Environment, 599-600:560–571, 2017. [3] H. Berger, T. Liepold, H. Pfitzinger-Schiele, M. R¨atz, and N. W¨olkl. Wasser f¨ur Franken ”Die Uberleitung Donau-Main”. Bayerisches Staatsministerium f¨ur Umwelt und Verbraucherschutz (StMUV), Rosenkavalierplatz 2, 81925 Munich, Germany, 2018.. [4] J. Derraik. The pollution of the marine environment by plastic debris: A review. Marine Pollution Bulletin, 44(9):842–852, 2002. [5] J. Dusaucy, D. Gateuille, Y. Perrette, and E. Naffrechoux. Microplastic pollution of worldwide lakes. Environmental Pollution, 284:117075, 2021. [6] German Environment Agency (Umweltbundesamt). Kenndaten Ausgew¨ahlter Seen. Available online at: https://www.umweltbundesamt.de/daten/ (accessed December 18th, 2022), 2018. [7] D. He, Y. Luo, S. Lu, M. Liu, Y. Song, and L. Lei. Microplastics in soils: Analytical methods, pollution characteristics and ecological risks. Trends in Analytical Chemistry, 109:163–172, 2018. [8] G. Jimenez-Skrzypek, C. Hernandez-Sanchez, C. Ortega-Zamora, J. Gonzalez-Salamo, M. A. Gonzalez-Curbelo, and J. Hernandez-Borges. Microplastic- adsorbed organic contaminants: Analytical methods and occurrence. Trends in Analytical Chemistry, 136:116186, 2021. [9] X. Li, Q. Mei, L. Chen, H. Zhang, B. Dong, X. Dai, C. He, and J. Zhou. Enhancement in adsorption potential of microplastics in sewage sludge for metalpollutants after the wastewater treatment process. Water Research, 157:228–237, 2019. [10] J. Liao and Q. Chen. Biodegradable plastics in the air and soil environment: Low degradation rate and high microplastics formation. Journal of Hazardous Materials, 418:126329, 2021. [11] R. Nousheen, I. Hashmi, D. Rittschof, and A. Capper. Comprehensive analysis of spatial distribution of microplastics in Rawal Lake, Pakistan using trawl net and sieve sampling methods. Chemosphere, 308(1):136111, 2022. [12] L. M. Rios, C. Moore, and P. R. Jones. Persistent organic pollutants carried by synthetic polymers in the ocean environment. Marine Pollution Bulletin, 54:1230–1237, 2007. [13] Y. K. Song, S. H. Hong, S. Eo, M. Jang, G. M. Han, A. Isobe, and W. J. Shim. Horizontal and Vertical Distribution of Microplastics in Korean Coastal Waters. Environmental Science Technology, 52(21):12188–12197, 2018. [14] L. Su, Y. Xue, L. Li, D. Yang, P. Kolandhasamy, D. Li, and H. Shi. Microplastics in Taihu Lake, China. Environmental Pollution, 216:711–719, 2016. [15] M. Tamminga and E. K. Fischer. Microplastics in a deep, dimictic lake of the North German Plain with special regard to vertical distribution patterns. Environmental Pollution, 267:115507, 2020. [16] L. Yao, L. Hui, Z. Yang, X. Chen, and A. Xiao. Freshwater microplastics pollution: Detecting and visualizing emerging trends based on Citespace II. Chemosphere, 245:125627, 2020. 23