Tracking plastics: In conversation with Dr. van der Mheen

I have met quite a few people who always knew that they wanted to be ocean scientists, but this was not the case for me. I always loved nature though; I grew up in Zimbabwe and spent a lot of time in nature parks as a kid, which helped me develop huge respect and love for the environment from an early age. I also remember my father telling me about Einstein’s twin paradox, a thought experiment in relativity theory, as a young girl, which made me very curious to keep exploring how the world works.

After finishing school in the Netherlands, I decided to study physics, initially with the idea to specialise in astrophysics. However, when I completed my undergraduate studies, I realised that although astrophysics inspired me, I wanted to study something closer, something that I could see first-hand. This realisation led me to an MSc in physical oceanography.

After completing my Masters, I worked for a Dutch institute that advised the government and other clients on a variety of water-related issues. Although the projects I worked on were interesting and relevant, three years down and I started to miss academic research. Around the same time, a friend told me about the Ocean Cleanup Foundation, which at the time was a small start-up trying to tackle ocean plastic pollution in a new way. I volunteered with them alongside my job and became very interested in the type of research they were doing. Not long after that, I quit my job and moved to Perth to do my own PhD research on ocean plastic pollution. I decided to focus on plastic waste in the Indian Ocean, both because the Indian Ocean is right at my doorstep and because so little research seemed to focus on this ocean basin.

A particle-tracking model is a computer model that tracks the locations of virtual “particles” over time as they drift in the ocean. Essentially, we create a simulation that is as realistic as possible by including current (pun intended) information about currents, wave action, circulation patterns, and anything else that might influence the movement of a particle in the ocean. We then try to mimic the particles in the ocean based on the characteristics we are interested in (for example; how buoyant an object is) and look at how physical variables such as wind and wave conditions on a given day might move the particles around.

Particle tracking simulations are used for a lot of different purposes, and virtual particles can represent almost anything. For example, particle tracking simulations can be used to: determine the exchange of fish larvae between different fisheries; predict the spread of an oil spill; or assist in search and rescue operations at sea. In my research, I use particle tracking models to simulate how plastic waste moves in the ocean and to determine where it might eventually end up.

The basic principle behind particle tracking models is relatively simple: If you know the speed and direction (velocity) that a particle is travelling at, you can determine its location after a certain time (distance travelled = velocity x time travelled). Largely, virtual particles are assumed to drift at the same speed and in the same direction as the ocean surface currents. Imagine, if the currents are moving at 5 km/ph from north to south, we expect that the particles will also move at that speed in that direction. Of course, as you increase the number of variables – things get a bit more complicated, like if the item that you are modelling is very floaty (for example, a plastic bottle filled with air), then the wind and waves can also influence where the item might go and how fast.

Another important consideration for a particle tracking model is when and where to “release” virtual particles into the simulation. For example, for an oil spill, this would be the location and time when oil first started to leak, and for a search and rescue operation, this might be the last known time and location of a person or boat at sea. However, in the case of ocean plastic pollution, the exact time, location, and amount of plastic entering the ocean are often unknown.

Figure 2: Definition of northern Indian Ocean (NIO) and southern Indian Ocean (SIO) extracted from van der Mheen et al., (2020)

In the northern Indian Ocean (Figure 2), the wind and ocean surface currents are heavily influenced by the monsoon system. During the southwest monsoon season (June, July, August), the wind above the northern Indian Ocean mostly blows from the southwest. During the northeast monsoon season (December, January, February), the wind changes direction and blows mostly from the northeast. As the wind changes direction with each monsoon season, the major ocean surface currents in the northern Indian Ocean change direction too. This is unique to this ocean basin: nowhere else in the world do major ocean surface currents change direction like this!

 As you can imagine, this has consequences for the transport of plastic waste in the northern Indian Ocean: depending on the season, plastic moves back and forth between the Arabian Sea and the Bay of Bengal. As it does so, it frequently comes close to coastlines, and so there is a high likelihood of plastics “beaching” or ending up on coastlines. In our particle tracking simulations (van der Mheen et al., 2020), all particles (representing plastic waste) ended up on coastlines throughout the northern Indian Ocean. Because islands like Sri Lanka and the Maldives are in the pathway of the reversing Southwest- and Northeast Monsoon Current, our model shows that it is likely they will be particularly heavily affected by beaching plastic waste.

In our paper about beaching plastics in the Indian Ocean (van der Mheen et al., 2020), we considered plastic waste from rivers based on a previous study by Lebreton et al. (2017). In their paper, they estimated the amount of plastic waste entering the ocean from rivers based on the watershed area of each river, the population density in that area, the percentage of mismanaged plastic waste and any available measurements of plastic in rivers. Based on this estimate, the largest sources of plastic waste in the Indian Ocean were from several rivers surrounding the Bay of Bengal: the Ganges (India, Bangladesh); the Brantas, Solo, Serayu, and Progo (Indonesia); the Irrawaddy (Myanmar); and the Mekong (Thailand, Cambodia, Laos, China, Myanmar, Vietnam).

Meijer et al. (2021) recently published an updated estimate of the amount of plastic waste entering the ocean from rivers. The contribution from Indonesian rivers was much smaller in this estimate than in the previous estimate highlighting the uncertainty about how much plastic waste actually enters the ocean. This is mainly because there are not enough measurements but also because there are so many possible sources of ocean plastic pollution. It is relatively straightforward to measure how much plastic enters the ocean from a river mouth. But it is much more difficult to determine how much plastic waste enters the ocean directly from beaches, coastal cities, or from boats.

Plastic waste washes up on many remote islands. Often this waste comes from distant, non-local sources. Tracking plastics (for example, by using particle tracking simulations) makes it possible to identify these sources. So, if we can, for example, determine that small island community ‘A’ receives a lot of plastic waste from country ‘B’, then ‘A’ and ‘B’ can work together to stop plastic waste from entering the ocean from country B in the first place.