08/12/2024
Understanding microplastics - with high-speed cameras
Microplastics are a global problem: they end up in rivers and oceans, they accumulate in living organisms and disrupt entire ecosystems. How tiny particles behave in a current is difficult to describe scientifically, especially in the case of thin fibres, which make up more than half of microplastic contamination in marine life-forms. In turbulent currents, it is almost impossible to predict their movement.
Scientists at TU Wien (Vienna) have now succeeded in characterising the behaviour of such microplastic fibres in experiments in a channel flow with the help of high-speed cameras. This should now form the basis for new models that can be used to predict the spread of microplastics globally. The results have been published in the journal "Physical Review Letters".
Small, curved fibers
"How microplastic particles move, disperse, and settle depends on their rotational dynamics," explains Vlad Giurgiu, first author of the current publication and doctoral student in Prof Alfredo Soldati's team at TU Wien. "This is easy to analyse in the case of almost spherical particles. But usually, microplastics are elongated, curved fibers." In this case, complicated effects occur: The fibres can rotate in all three spatial directions, and this rotation also influences their interaction with the surrounding flow.
"In a perfectly uniform, laminar flow we would be able to predict theoretically the behaviour of simple objects, like spheres or ellipsoids," says Marco De Paoli, who collaborates with the team at the Institute of Fluid Mechanics and Heat Transfer at TU Wien. "But in the real world, you're neither dealing with perfectly laminar flows nor with perfectly symmetric particles. Instead, turbulence and complex shapes are present, which significantly influence the transport of the particles. This makes theoretical predictions impossible."
What exactly happens is difficult to calculate. "There have already been various computer simulations, but they rely on simplified models to describe the fibers behaviour," says Vlad Giurgiu. "You therefore need experimental data with which you can compare and improve these theoretical models".
Precisely this kind of data can be obtained in the TU Wien Turbulent Water Channel, located at the Arsenal Science Center (Vienna). Controlled flows can be generated over a path length of 8.5 metres. Small, curved microplastic fibres with a length of 1.2 millimetres were introduced into the water and exposed to a turbulent flow.
Six cameras see more than two
The team installed six special cameras just above the surface of the water: at a frequency of 2000 images per second, they collected high-resolution images of the microplastic particles in the current. The three-dimensional position and orientation of each individual microplastic particle can then be computed analyzing these images. "Theoretically, this would also work with just two cameras, but with six cameras, the data is even more reliable and accurate, especially when the concentration of particles is high" explains Giuseppe Carlo Alp Caridi, coauthor of the study and Head of Optical Reconstruction at the Institute of Fluid Mechanics and Heat Transfer at TU Wien.
In this way, a large amount of data can be extracted about the motion of hundreds of thousands of microplastic particles and then analysed statistically. "For example, it turned out that the fibers show a completely different behaviour near a wall than in the middle of the water flow, far away from the walls," explains Vlad Giurgiu.
This means that reliable data is now available for the first time to validate theoretical calculation models on the behaviour of such particles. In future, it should also be possible to predict the propagation of microplastic fibers on a large scale. "Imagine you have a ship that can filter microplastics from seawater," says Marco De Paoli. "Then you need to know where best to send this ship - after all, the ocean is really big. If you understand the behaviour of the particles precisely, then the answer can be calculated with great reliability."
Source: TU Wien