Modeling submerged biofouled microplastics and their vertical trajectories

Abstract

Abstract. The fate of (micro)plastic particles in the open ocean is controlled by physical and biological processes. Here, we model the effects of biofouling on the subsurface vertical distribution of spherical, virtual plastic particles with radii of 0.01–1 mm. For the physics, four vertical velocity terms are included: advection, wind-driven mixing, tidally induced mixing, and the sinking velocity of the biofouled particle. For the biology, we simulate the attachment, growth and loss of algae on particles. We track 10,000 particles for one year in three different regions with distinct biological and physical properties: the low productivity region of the North Pacific Subtropical Gyre, the high productivity region of the Equatorial Pacific and the high mixing region of the Southern Ocean. The growth of biofilm mass in the euphotic zone and loss of mass below the euphotic zone result in the oscillatory behaviour of particles, where the larger (0.1–1.0 mm) particles have much shorter average oscillation lengths (< 10 days; 90th percentile) than the smaller (0.01–0.1 mm) particles (up to 130 days; 90th percentile). A subsurface maximum concentration occurs just below the mixed layer depth (around 30 m) in the Equatorial Pacific, which is most pronounced for larger particles (0.1–1.0 mm). This occurs since particles become neutrally buoyant when the processes affecting the settling velocity of the particle and the motion of the ocean are in equilibrium. Seasonal effects in the subtropical gyre result in particles sinking below the mixed layer depth only during spring blooms, but otherwise remaining within the mixed layer. The strong winds and deepest average mixed layer depth in the Southern Ocean (400 m) result in the deepest redistribution of particles (> 5000 m). Our results show that the vertical movement of particles is mainly affected by physical (wind-induced mixing) processes within the mixed layer and biological (biofilm) dynamics below the mixed layer. Furthermore, positively buoyant particles with radii of 0.01–1.0 mm can sink far below the euphotic zone and mixed layer in regions with high near-surface mixing or high biological activity. This work can easily be coupled to other models to simulate open-ocean biofouling dynamics, in order to reach a better understanding of where ocean (micro)plastic ends up.

Three-Dimensional Dispersion of Neutral “Plastic” Particles in a Global Ocean Model

“…For the particles transport in the Lagrangian framework, we have only taken into account the influence of currents resolved by the ocean model, because of its limited spatial resolution in the horizontal and vertical, and its temporal resolution. There are several other processes that should be estimated to validate our results, the ones that come readily to mind being the vertical eddy diffusion due to energetic surface turbulence (Kukulka et al, 2012;Fischer et al, 2021;Onink et al, 2022), and tidally-driven mixing whose impact is not confined to the bottom but reaches the thermocline (Tuerena et al, 2019;Portela et al, 2020). These processes as well as submesoscale processes with large vertical velocities in the upper layer are not resolved within our NEMO simulation at 1/12 ° (Klein and Lapeyre, 2009).…”

The streaming of plastic in the Mediterranean Sea

“…To achieve rigorous validation of surface sinking and net beaching rates, future empirical studies should provide time series of washed-up and bottom-deposited plastic volumes. The description of surface sinking rates could benefit from considering spatial variation in biofouling rates 34 , 43 . Furthermore, three-dimensional modeling is required to investigate the fate of plastics from surface to seafloor.…”

Empirical Lagrangian parametrization for wind-driven mixing of buoyant particles at the ocean surface

“…The parametrizations presented in this study are intended for use in 3D Lagrangian experiments using OGCM data and therefore should yield numerically stable results for the relatively large integration time steps used in large-scale Lagrangian vertical transport modeling (Lobelle et al, 2021). While there are more stable schemes available than the EM scheme used in this study (Gräwe et al, 2012), the EM scheme is computationally the cheapest and yields concentration profiles that match reasonably well with observations.…”

“…The drift term assures that the well-mixed condition is met, which states that an initially uniform particle distribution must remain uniform even with inhomogeneous turbulence (Brickman and Smith, 2002;Ross and Sharples, 2004). This approach, termed a Markov-0 (M-0) or random walk model, assumes that turbulent fluctuations exhibit no autocorrelation on timescales t, which for global-scale Lagrangian simulations can range from 30 s (Lobelle et al, 2021) to 30 min (Onink et al, 2019). However, measurements from Lagrangian ocean floats show this is an oversimplification, as coherent oceanic flow structures can induce velocity autocorrelations that can persist for significantly longer timescales (Denman and Gargett, 1983;Brickman and Smith, 2002).…”

“…All Lagrangian simulations are run using Parcels v2.2.1 (Delandmeter and Sebille, 2019), which has been used for 1D, 2D and 3D particle oceanographic simulations (Fischer et al, 2021;Lobelle et al, 2021). The simulations start with 100 000 particles released at Z(0) = 0 and run for 12 h. The model is one dimensional with horizontal velocities set to zero.…”