Creating a 3D map of the plastic litter polluting our oceans

Microplastic debris ending up at the sea surface has become a known major environmental issue. However, how microplastic particles move and when they sink in the ocean remains largely unknown. Here, we model microplastic subject to biofouling (algal growth on a substrate) to estimate sinking timescales and the time to reach the depth where particles stop sinking. We combine NEMO‐MEDUSA 2.0 output, that represents hydrodynamic and biological properties of seawater, with a particle‐tracking framework. Different sizes and densities of particles (for different types of plastic) are simulated, showing that the global distribution of sinking timescales is largely size‐dependent as opposed to density‐dependent. The smallest particles we simulate (0.1 μm) start sinking almost immediately around the globe and their trajectories take the longest time to reach their first sinking depth (relative to larger particles). In oligotrophic subtropical gyres with low algal concentrations, particles between 1 mm and 10 μm do not sink within the 90‐day simulation time. This suggests that in addition to the comparatively well‐known physical processes, biological processes might also contribute to the accumulation of floating plastic (of 1 mm–10 μm) in subtropical gyres. Particles of 1 μm in the gyres start sinking largely due to vertical advection, whereas in the equatorial Pacific they are more dependent on biofouling. The qualitative impacts of seasonality on sinking timescales are small, however, localised sooner sinking due to spring algal blooms is seen. This study maps processes that affect the sinking of virtual microplastic globally, which could ultimately impact the ocean plastic budget.

Global coastlines potentially contain significant amounts of plastic debris, with harmful implications for marine and coastal ecosystems, fisheries and tourism. However, the global amount, distribution and origin of plastic debris on beaches and in coastal waters is currently unknown. Here we analyse beaching and resuspension scenarios using a Lagrangian particle transport model. Throughout the first 5 years after entering the ocean, the model indicates that at least 77% of positively buoyant marine plastic debris (PBMPD) released from land-based sources is either beached or floating in coastal waters, assuming no further plastic removal from beaches or the ocean surface. The highest concentrations of beached PBMPD are found in Southeast Asia, caused by high plastic inputs from land and limited off-shore transport, although the absolute concentrations are generally overestimates compared to field measurements. The modelled distribution on a global scale is only weakly influenced by local variations in resuspension rates due to coastal geomorphology. Furthermore, there are striking differences regarding the origin of the beached plastic debris. In some Exclusive Economic Zones (EEZ), such as the Indonesian Archipelago, plastic originates almost entirely from within the EEZ while in other EEZs, particularly remote islands, almost all beached plastic debris arrives from remote sources. Our results highlight coastlines and coastal waters as important reservoirs of marine plastic debris and limited transport of PBMPD between the coastal zone and the open ocean.

Field studies in the global ocean have shown that plastic fragments make up the majority of plastic pollution in terms of abundance. It is not well understood how quickly plastics in the marine environmental fragment, however. Here, we study the fragmentation process in the oceanic environment by considering a model which captures continuous fragmentation of particles over time in a cascading fashion. With this cascading fragmentation model we simulate particle size distributions (PSDs), specifying the abundance or mass of particles for different size classes. The fragmentation model is coupled to an environmental box model, simulating the distributions of plastic particles in the ocean, coastal waters, and on the beach. We demonstrate the capabilities of the model by calibrating it to estimated plastic transport in the Mediterranean Sea, and compare the modelled PSDs to available observations in this region. Results are used to illustrate the effect of size-selective processes such as vertical mixing in the water column and resuspension of particles from the beach into coastal waters. The model quantifies the role of fragmentation on the marine plastic mass budget: while fragmentation is a major source of secondary plastic particles in terms of abundance, it seems to have a minor effect on the total mass of particles larger than 0.1 mm. Future comparison to observed PSD data allow us to understand size-selective plastic transport in the environment, and potentially inform us on plastic longevity.

We study the vertical dispersion and distribution of negatively buoyant rigid microplastics within a realistic circulation model of the Mediterranean sea. We first propose an equation describing their idealized dynamics. In that framework, we evaluate the importance of some relevant physical effects: inertia, Coriolis force, small-scale turbulence and variable seawater density, and bound the relative error of simplifying the dynamics to a constant sinking velocity added to a large-scale velocity field. We then calculate the amount and vertical distribution of microplastic particles on the water column of the open ocean if their release from the sea surface is continuous at rates compatible with observations in the Mediterranean. The vertical distribution is found to be almost uniform with depth for the majority of our parameter range. Transient distributions from flash releases reveal a non-Gaussian character of the dispersion and various diffusion laws, both normal and anomalous. The origin of these behaviors is explored in terms of horizontal and vertical flow organization.

To identify barriers to transport in a fluid domain, community detection algorithms from network science have been used to divide the domain into clusters that are sparsely connected with each other. In a previous application to the closed domain of the Mediterranean Sea, communities detected by the Infomap algorithm have barriers that often coincide with well‐known oceanographic features. We apply this clustering method to the surface of the Arctic and subarctic oceans and thereby show that it can also be applied to open domains. First, we construct a Lagrangian flow network by simulating the exchange of Lagrangian particles between different bins in an icosahedral‐hexagonal grid. Then, Infomap is applied to identify groups of well‐connected bins. The resolved transport barriers include naturally occurring structures, such as the major currents. As expected, clusters in the Arctic are affected by seasonal and annual variations in sea‐ice concentration. An important caveat of community detection algorithms is that many different divisions into clusters may qualify as good solutions. Moreover, while certain cluster boundaries lie consistently at the same location between different good solutions, other boundary locations vary significantly, making it difficult to assess the physical meaning of a single solution. We therefore consider an ensemble of solutions to find persistent boundaries, trends and correlations with surface velocities and sea‐ice cover.

The detection of finite-time coherent particle sets in Lagrangian trajectory data using data clustering techniques is an active research field at the moment. Yet, the clustering methods mostly employed so far have been based on graph partitioning, which assigns each trajectory to a cluster, i.e. there is no concept of noisy, incoherent trajectories. This is problematic for applications to the ocean, where many small coherent eddies are present in a large fluid domain. In addition, to our knowledge none of the existing methods to detect finite-time coherent sets has an intrinsic notion of coherence hierarchy, i.e. the detection of finite-time coherent sets at different spatial scales. Such coherence hierarchies are present in the ocean, where basin scale coherence coexists with smaller coherent structures such as jets and mesoscale eddies. Here, for the first time in this context, we use the density-based clustering algorithm OPTICS (Ankerst et al., 1999) to detect finite-time coherent particle sets in Lagrangian trajectory data. Different from partition based clustering methods, OPTICS does not require to fix the number of clusters beforehand. Derived clustering results contain a concept of noise, such that not every trajectory needs to be part of a cluster. OPTICS also has a major advantage compared to the previously used DBSCAN method, as it can detect clusters of varying density. Further, clusters can also be detected based on density changes instead of absolute density. Finally, OPTICS based clusters have an intrinsically hierarchical structure, which allows to detect coherent trajectory sets at different spatial scales at once. We apply OPTICS directly to Lagrangian trajectory data in the Bickley jet model flow and successfully detect the expected vortices and the jet. The resulting clustering separates the vortices and the jet from background noise, with an imprint of the hierarchical clustering structure of coherent, small scale vortices in a coherent, large-scale, background flow. We then apply our method to a set of virtual trajectories released in the eastern South Atlantic Ocean in an eddying ocean model and successfully detect Agulhas rings. At larger scale, our method also separates the eastward and westward moving parts of the subtropical gyre. We illustrate the difference between our approach and partition based k-Means clustering using a 2-dimensional embedding of the trajectories derived from classical multidimensional scaling. We also show how OPTICS can be applied to the spectral embedding of a trajectory based network to overcome the problems of k-Means spectral clustering in detecting Agulhas rings.

The transport of plastic particles from inland sources to the oceans garbage patches occurs trough coastal regions where the transport processes depend highly on wave--induced motions. In this study, experimental measurements of the plastic particles wave--induced Lagrangian drift in intermediate water depth are presented investigating the influence of the wave conditions, particle size and density on the motion of relatively large plastic particles. A large influence of the particle density is observed causing particles to float or sink for relative densities lower and larger than water respectively. The measured net drift of the floating particles correlates well with theoretical solutions for particle Stokes drift, where the net drift is proportional to the square of the wave steepness. Floating particles remain at the free water surface because of buoyancy and no evidence of any other influence of particle inertia on the net drift is observed. Non--floating particles move close to the bed with lower velocity magnitudes than the floating particles' motion at the free surface. The drift of non--floating particles reduces with decreasing wave number, and therefore wave steepness.

The seafloor covers some 70% of the Earth’s surface and has been recognized as a major sink for marine litter. Still, litter on the seafloor is the least investigated fraction of marine litter, which is not surprising as most of it lies in the deep-sea, i.e. the least explored ecosystem. Although marine litter is considered a major threat for the oceans, monitoring frameworks are still being set-up. This paper reviews current knowledge and methods, identifies existing needs, and points to future developments that are required to address the estimation of seafloor macrolitter. It provides background knowledge and conveys the views and thoughts of scientific experts on seafloor marine litter and offers a review of monitoring and ocean modeling techniques. Knowledge gaps that need to be tackled, data needs for modeling, and data comparability and harmonization are also discussed in the paper. In addition, it shows how research on seafloor macrolitter can inform international protection and conservation frameworks to prioritize efforts and measures against marine litter and its deleterious impacts.

The basinwide surface transport of tracers such as heat, nutrients and plastic in the North Atlantic Ocean is organized into large scale flow structures such as the Western Boundary Current and the Subtropical and Subpolar Gyres. Being able to identify these features from drifter data is important for studying tracer dispersal, but also to detect changes in the large scale surface flow due to climate change. We propose a new and conceptually simple method to detect groups of trajectories with similar dynamical behaviour from drifter data using network theory and normalized cut spectral clustering. Our network is constructed from conditional bin-drifter probability distributions and naturally handles drifter trajectories with data gaps and different lifetimes. The eigenvalue problem of the respective Laplacian can be replaced by a singular value decomposition of a related sparse data matrix. The construction of this matrix scales with O(NM + Nτ), where N is the number of particles, M the number of bins and τ the number of time steps. The concept behind our network construction is rooted in a particle's symbolic itinerary derived from its trajectory and a state space partition, which we incorporate in its most basic form by replacing a particle's itinerary by a probability distribution over symbols. We represent these distributions as the links of a bipartite graph, connecting particles and symbols. We apply our method to the periodically driven double-gyre flow and successfully identify well-known features. Exploiting the duality between particles and symbols defined by the bipartite graph, we demonstrate how a direct low-dimensional coarse definition of the clustering problem can still lead to relatively accurate results for the most dominant structures, and resolve features down to scales much below the coarse graining scale. Our method also performs well in detecting structures with incomplete trajectory data, which we demonstrate for the double-gyre flow by randomly removing data points. We finally apply our method to a set of ocean drifter trajectories and present the first network-based clustering of the North Atlantic surface transport based on surface drifters, successfully detecting well-known regions such as the Subpolar and Subtropical Gyres, the Western Boundary Current region and the Carribean Sea.

A large percentage of global ocean plastic waste enters the northern hemisphere Indian Ocean (NIO). Despite this, it is unclear what happens to buoyant plastics in the NIO. Because the subtropics in the NIO is blocked by landmass, there is no subtropical gyre and no associated subtropical garbage patch in this region. We therefore hypothesise that plastics "beach" and end up on coastlines along the Indian Ocean rim. In this paper, we determine the influence of beaching plastics by applying different beaching conditions to Lagrangian particle tracking simulation results. Our results show that a large amount of plastic likely ends up on coastlines in the NIO, while some crosses the equator into the southern hemisphere Indian Ocean (SIO). In the NIO, the transport of plastics is dominated by seasonally reversing monsoonal currents, which transport plastics back and forth between the Arabian Sea and the Bay of Bengal. All buoyant plastic material in this region beaches within a few years in our simulations. Countries bordering the Bay of Bengal are particularly heavily affected by plastics beaching on coastlines. This is a result of both the large sources of plastic waste in the region, as well as ocean dynamics which concentrate plastics in the Bay of Bengal. During the intermonsoon period following the southwest monsoon season (September, October, November), plastics can cross the equator on the eastern side of the NIO basin into the SIO. Plastics that escape from the NIO into the SIO beach on eastern African coastlines and islands in the SIO or enter the subtropical SIO garbage patch.

Estimates of plastic inputs into the ocean are orders of magnitude larger than what is found in the surface waters. This can be due to discrepancies in the sources of plastic released into the ocean, but can also be explained due to the fact that it is not well known what the most dominant sinks of marine plastics are, and on what time scales these operate. To get a better understanding on possible sources and sinks, an inverse modelling methodology is presented here for a Lagrangian ocean model, estimating floating plastic quantities in the Mediterranean Sea. Field measurements of plastic concentrations in the Mediterranean are used to inform parametrizations defining various sources of marine plastics, and removal of plastic particles due to beaching and sinking. The parameters of the model are found using inverse modelling, by comparison of model results and measurements of floating plastic concentrations. Time scales for the sinks are found, and likely sources of plastics can be ranked in importance. A new mass balance is made for floating plastics in the Mediterranean: for 2015 there is an estimated input of 2,100-3,400 tonnes, and of plastics released since 2006, about 170-420 tonnes remain afloat in the surface waters, 49-63% ended up on coastlines, and 37-51% have sunk down.

Despite the ubiquitous and persistent presence of microplastic (MP) in marine ecosystems, knowledge of its potential harmful ecological effects is low. In this work, we assessed the risk of floating MP (1 μm – 5 mm) to marine ecosystems by comparing ambient concentrations in the global ocean with available ecotoxicity data. The integration of twenty-three species-specific effect threshold concentration data in a species sensitivity distribution yielded a median unacceptable level of 1.21 * 105 MP m-3 (95% CI: 7.99 * 103 – 1.49 * 106 MP m-3). We found that in 2010 for 0.17% of the surface layer (0 – 5 m) of the global ocean a threatening risk would occur. By 2050 and 2100, this fraction increases to 0.52% and 1.62%, respectively, according to the worst-case predicted future plastic discharge into the ocean. Our results reveal a spatial and multidecadal variability of MP-related risk at the global ocean surface. For example, we have identified the Mediterranean Sea and the Yellow Sea as hotspots of marine microplastic risks already now and even more pronounced in future decades.

Marine plastic debris floating on the ocean surface is a major environmental problem. However, its distribution in the ocean is poorly mapped, and most of the plastic waste estimated to have entered the ocean from land is unaccounted for. Better understanding of how plastic debris is transported from coastal and marine sources is crucial to quantify and close the global inventory of marine plastics, which in turn represents critical information for mitigation or policy strategies. At the same time, plastic is a unique tracer that provides an opportunity to learn more about the physics and dynamics of our ocean across multiple scales, from the Ekman convergence in basin-scale gyres to individual waves in the surfzone. In this review, we comprehensively discuss what is known about the different processes that govern the transport of floating marine plastic debris in both the open ocean and the coastal zones, based on the published literature and referring to insights from neighbouring fields such as oil spill dispersion, marine safety recovery, plankton connectivity, and others. We discuss how measurements of marine plastics (both in situ and in the laboratory), remote sensing, and numerical simulations can elucidate these processes and their interactions across spatio-temporal scales.

We present a new method for chemical characterisation of micro- and nanoplastics based on thermal desorption - proton transfer reaction - mass spectrometry. The detection limit for polystyrene (PS) obtained is <1 ng of the compound present in a sample, which results in 100 times better sensitivity than previously reported by other methods. This allows us to use small volumes of samples (1 mL) and to carry out experiments without a preconcentration step. Unique features in the high-resolution mass spectrum of different plastic polymers make this approach suitable for fingerprinting, even when the samples contain mixtures of other organic compounds. Accordingly, we got a positive fingerprint of PS when just 10 ng of the polymer was present within dissolved organic matter of snow. Multiple types of microplastics (PET, PVC, and PPC), were identified in a snow-pit from the Austrian Alps, however, only PET was detected in the nanometer range for both snow-pit and surface-snow samples. This is in accordance with other publications showing that the dominant form of airborne microplastics are PET fibres. The presence of nanoplastics in high-altitude snow indicate airborne transport of plastic pollution with environmental and health consequences yet to be understood.

Floating plastic debris is an increasing source of pollution in the world's oceans. Numerical simulations using models of ocean currents give insight into the transport and distribution of microplastics in the oceans, but most simulations do not account for the oscillating flow caused by global barotropic tides. Here, we investigate the influence of barotropic tidal currents on the transport and accumulation of floating microplastics, by numerically simulating the advection of virtual plastic particles released all over the world's oceans and tracking these for 13 years. We use geostrophic and surface Ekman currents from GlobCurrent and the currents caused by the four main tidal constituents (M2, S2, K1, and O1) from the FES model. We analyze the differences between the simulations with and without the barotropic tidal currents included, focusing on the open ocean. In each of the simulations, we see that microplastic accumulates in regions in the subtropical gyres, which is in agreement with observations. The formation and location of these accumulation regions remain unaffected by the barotropic tidal currents. However, there are a number of coastal regions where we see differences when the barotropic tidal currents are included. Due to uncertainties of the model in coastal regions, further investigation is required in order to draw conclusions in these areas. Our results suggest that, in the global open ocean, barotropic tidal currents have little impact on the transport and accumulation of floating microplastic and can thus be neglected in simulations aimed at studying microplastic transport in the open ocean.

The tracking of virtual particles is one of the main numerical tools to understand the global dispersion of marine plastic debris and has been successful in explaining the global-scale accumulation patterns of surface microplastic, often called `garbage patches'. Yet, the inherent inaccuracies in plastic input scenarios and ocean circulation model results produce uncertainties in particle trajectories, which amplify due to the chaotic property of the surface ocean flow. Within this chaotic system, the subtropical `garbage patches' correspond to the attractor. These facts make the large scale surface ocean circulation a mixing dynamical system, which means that the information of a particle's initial location is lost over time. We use mixing entropy and Markov chain mixing of the transfer operator associated with surface ocean transport to quantify the time scales of mixing for the global surface ocean in each subtropical basin. In the largest parts of all basins we find mixing times in the order of or below 10 years, which is lower than typical simulation times for surface plastic transport simulations. Maximum mixing times of more than 10 years are found in some parts of the North and South Pacific. Our results have important implications for global dispersion modelling of floating materials on the basin scale: precise initial information has little relevance for long term simulations, and there is a temporal limit after which the backtracking of particles is not meaningful any more.

Sustained observations are required to determine the marine plastic debris mass balance and to support effective policy for planning remedial action. However, observations currently remain scarce at the global scale. A satellite remote sensing system could make a substantial contribution to tackling this problem. Here, we make initial steps towards the potential design of such a remote sensing system by: (1) identifying the properties of marine plastic debris amenable to remote sensing methods and (2) highlighting the oceanic processes relevant to scientific questions about marine plastic debris. Remote sensing approaches are reviewed and matched to the optical properties of marine plastic debris and the relevant spatio-temporal scales of observation to identify challenges and opportunities in the field. Finally, steps needed to develop marine plastic debris detection by remote sensing platforms are proposed in terms of fundamental science as well as linkages to ongoing planning for satellite systems with similar observation requirements.

The Galápagos Archipelago and Galápagos Marine Reserve lie 1000 km off the coast of Ecuador and are among the world's most iconic wildlife refuges. However, plastic litter is now found even in this remote island archipelago. Prior to this study, the sources of this plastic litter on Galápagos coastlines were unidentified. Local sources are widely expected to be small, given the limited population and environmentally conscious tourism industry. Here, we show that remote sources of plastic pollution are also fairly localised and limited to nearby fishing regions and South American and Central American coastlines, in particular northern Peru and southern Ecuador. Using virtual floating plastic particles transported in high-resolution ocean surface currents, we analysed the plastic origin and fate using pathways and connectivity between the Galápagos region and the coastlines as well as known fishery locations around the east Pacific Ocean. We also analysed how incorporation of wave-driven currents (Stokes drift) affects these pathways and connectivity. We found that only virtual particles that enter the ocean from Peru, Ecuador, and (when waves are not taken into account) Colombia can reach the Galápagos region. It takes these particles a few months to travel from their coastal sources on the American continent to the Galápagos region. The connectivity does not seem to vary substantially between El Niño and La Niña years. Identifying these sources and the timing and patterns of the transport can be useful for identifying integrated management opportunities to reduce plastic pollution from reaching the Galápagos Archipelago.

Buoyant microplastic in the ocean can be submerged to deeper layers through biofouling and the consequent loss of buoyancy or by wind induced turbulent mixing at the ocean surface. Yet the fact that particles in deeper layers are transported by currents that are different from those at the surface has not been explored so far. We compute 10‐year trajectories of 1 million virtual particles with the Parcels framework for different particle advection scenarios to investigate the effect of near‐surface currents on global particle dispersal. We simulate the global‐scale transport of passive microplastic for (i) particles constrained to different depths from the surface to 120 m depth, (ii) particles that are randomly displaced in the vertical with uniform distribution, (iii) particles subject to surface mixing and (iv) for a 3D passive advection model. Our results show that the so called 'garbage patches' become more 'leaky' in deeper layers, and completely disappear at about 60 m depth. At the same time, subsurface currents can transport significant amounts of microplastic from subtropical and subpolar regions to polar regions, providing a possible mechanism to explain why plastic is found in these remote areas. Finally, we show that the final distribution in the surface turbulent mixing scenario with particle rise speed wr=0.003 m/s is very similar to the distribution of plastic at the surface. This demonstrates that it is not necessary to incorporate surface mixing for global long‐term simulations, although this might change on more local scales and for particles with lower rise speeds.

Plastics and other artificial materials pose new risks to health of the ocean. Anthropogenic debris travels across large distances and is ubiquitous in the water and on the shorelines, yet, observations of its sources, composition, pathways and distributions in the ocean are very sparse and inaccurate. Total amounts of plastics and other man-made debris in the ocean and on the shore, temporal trends in these amounts under exponentially increasing production, as well as degradation processes, vertical fluxes and time scales are largely unknown. Present ocean circulation models are not able to accurately simulate drift of debris because of its complex hydrodynamics. In this paper we discuss the structure of the future integrated marine debris observing system (IMDOS) that is required to provide long-term monitoring of the state of the anthropogenic pollution and support operational activities to mitigate impacts on the ecosystem and safety of maritime activity. The proposed observing system integrates remote sensing and in situ observations. Also, models are used to optimize the design of the system and, in turn, they will be gradually improved using the products of the system. Remote sensing technologies will provide spatially coherent coverage and consistent surveying time series at local to global scale. Optical sensors, including high-resolution imaging, multi- and hyperspectral, fluorescence, and Raman technologies, as well as SAR will be used to measure different types of debris. They will be implemented in a variety of platforms, from hand-held tools to ship-, buoy-, aircraft-, and satellite-based sensors. A network of in situ observations, including reports from volunteers, citizen scientists and ships of opportunity, will be developed to provide data for calibration/validation of remote sensors and to monitor the spread of plastic pollution and other marine debris. IMDOS will interact with other observing systems monitoring physical, chemical, and biological processes in the ocean and on shorelines as well as state of the ecosystem, maritime activities and safety, drift of sea ice, etc. The synthesized data will support innovative multi-disciplinary research and serve diverse community of users.

With the increasing amount of data produced by numerical ocean models, so increases the need for efficient tools to analyse these data. One of these tools is Lagrangian ocean analysis, where a set of virtual particles are released and their dynamics is integrated in time based on fields defining the ocean state, including the hydrodynamics and biogeochemistry if available. This popular methodology needs to adapt to the large variety of models producing these fields at different formats. This is precisely the aim of Parcels, a Lagrangian ocean analysis framework designed to combine (1) a wide flexibility to model particles of different natures and (2) an efficient implementation in accordance with modern computing infrastructure. In the new Parcels v2.0, we implement a set of interpolation schemes to read various types of discretised fields, from rectilinear to curvilinear grids in the horizontal direction, from z- to s- levels in the vertical and different variable distributions such as the Arakawa's A-, B- and C- grids. In particular, we develop a new interpolation scheme for a three-dimensional curvilinear C-grid and analyse its properties. Parcels v2.0 capabilities, including a suite of meta-field objects, are then illustrated in a brief study of the distribution of floating microplastic in the North West European continental shelf and its sensitivity to different physical processes.

Buoyant marine plastic debris has become a serious problem affecting the marine environment. To fully understand the impact of this problem, it is important to understand the dynamics of buoyant debris in the ocean. Buoyant debris accumulates in “garbage patches” in each of the subtropical ocean basins because of Ekman convergence and associated downwelling at subtropical latitudes. However, the precise dynamics of the garbage patches are not well understood. This is especially true in the southern Indian Ocean (SIO), where observations are inconclusive about the existence and numerical models predict inconsistent locations of the SIO garbage patch. In addition, the oceanic and atmospheric dynamics in the SIO are very different to those in the other oceans. The aim of this paper is to determine the dynamics of the SIO garbage patch at different depths and under different transport mechanisms such as ocean surface currents, Stokes drift and direct wind forcing. To achieve this, we use two types of ocean surface drifters as a proxy for buoyant debris. We derive transport matrices from observed drifter locations and simulate the global accumulation of buoyant debris. Our results indicate that the accumulation of buoyant debris in the SIO is much more sensitive to different transport mechanisms than in the other ocean basins. We relate this sensitivity to the unique oceanic and atmospheric dynamics of the SIO.

Plastic pollution in the marine environment is well documented. What remains less recognized and understood are the chemicals associated with it. Plastics enter the ocean with unreacted monomers, oligomers, and additives, which can leach over time. Moreover, plastics sorb organic and inorganic chemicals from surrounding seawater, for example, polychlorinated biphenyls (PCBs) and metals. Thus, interception and cleanup of plastics reduces the amount of chemical contaminants entering or reentering the oceans and removes those already present. Here, we estimate 1) the mass of selected chemical additives entering the global oceans with common plastic debris items, and 2) the mass of sorbed chemicals (using PCBs as a case study) associated with microplastics in selected locations. We estimate the mass of additives that entered the oceans in 2015 as constituents of 7 common plastic debris items (bottles, bottle caps, expanded polystyrene (EPS) containers, cutlery, grocery bags, food wrappers, and straws or stirrers). We calculate that approximately 190 tonnes (t) of 20 chemical additives entered the oceans with these items in 2015. We also estimate the mass of PCBs associated with microplastics in 2 coastal (Hong Kong and Hawaii) and 2 open ocean (North Pacific and South Atlantic gyres) locations, as comparative case studies. We find that the mass of chemicals is related to the mass of plastics in a location, with greater mass of PCBs closer to the source (i.e., land), where there is more plastic per unit area compared to the open ocean. We estimate approximately 85 000 times more PCBs associated with plastics in an average 4.5‐km stretch of beach in Hong Kong than from the same size transect in the North Pacific gyre. In conclusion, continuing efforts for plastic interception and cleanup on shorelines effectively reduces the amount of plastic‐related chemicals entering and/or reentering the marine environment.

Although marine plastic pollution has been the focus of several studies, there are still many gaps in our understanding of the concentrations, characteristics and impacts of plastics in the oceans. This study aimed to quantify and characterize plastic debris in oceanic surface waters of the Antarctic Peninsula. Sampling was done through surface trawls, and mean debris concentration was estimated at 1,794 items.km−2 with an average weight of 27.8 g.km−2. No statistical difference was found between the amount of mesoplastics (46%) and microplastics (54%). We found hard and flexible fragments, spheres and lines, in nine colors, composed mostly of polyurethane, polyamide, and polyethylene. An oceanographic dispersal model showed that, for at least seven years, sampled plastics likely did not originate from latitudes lower than 58°S. Analysis of epiplastic community diversity revealed bacteria, microalgae, and invertebrate groups adhered to debris. Paint fragments were present at all sampling stations and were approximately 30 times more abundant than plastics. Although paint particles were not included in plastic concentration estimates, we highlight that they could have similar impacts as marine plastics. We call for urgent action to avoid and mitigate plastic and paint fragment inputs to the Southern Ocean.

Floating microplastic in the oceans is known to accumulate in the subtropical ocean gyres, but unclear is still what causes that accumulation. We investigate the role of various physical processes, such as surface Ekman and geostrophic currents, surface Stokes drift and mesoscale eddy activity, on the global surface distribution of floating microplastic with Lagrangian particle tracking using GlobCurrent and WaveWatch III reanalysis products. Globally, the locations of microplastic accumulation (accumulation zones) are largely determined by the Ekman currents. Simulations of the North Pacific and North Atlantic show that the locations of the modeled accumulation zones using GlobCurrent Total (Ekman+Geostrophic) currents generally agree with observed microplastic distributions in the North Pacific, and with the zonal distribution in the North Atlantic. Geostrophic currents and Stokes drift do not contribute to large scale microplastic accumulation in the subtropics, but Stokes drift leads to increased microplastic transport to Arctic regions. Since the WaveWatch III Stokes drift and GlobCurrent Ekman current datasets are not independent, combining Stokes drift with the other current components leads to an overestimation of Stokes drift effects and there is therefore a need for independent measurements of the different ocean circulation components. We investigate whether windage would be appropriate as a proxy for Stokes drift but find discrepancies in the modelled direction and magnitude. In the North Pacific, we find that microplastic tends to accumulate in regions of relatively low eddy kinetic energy, indicating low mesoscale eddy activity, but we do not see similar trends in the North Atlantic.

We sampled 17 nesting sites for loggerhead (Caretta caretta) and green turtles (Chelonia mydas) in Cyprus. Microplastics (<5 mm) were found at all locations and depths, with particularly high abundance in superficial sand. The top 2 cm of sand presented grand mean ± SD particle counts of 45,497 ± 11,456 particles m−3 (range 637–131,939 particles m−3). The most polluted beaches were among the worst thus far recorded, presenting levels approaching those previously recorded in Guangdong, South China. Microplastics decreased with increasing sand depth but were present down to turtle nest depths of 60 cm (mean 5,325 ± 3,663 particles m−3. Composition varied among beaches but hard fragments (46.5 ± 3.5%) and pre-production nurdles (47.8 ± 4.5%) comprised most categorised pieces. Particle drifter analysis hindcast for 365 days indicated that most plastic likely originated from the eastern Mediterranean basin. Worsening microplastic abundance could result in anthropogenically altered life history parameters such as hatching success and sex ratios in marine turtles.

The whereabouts of the overwhelming majority of plastic estimated to enter the environment is unknown. This study’s aim was to combine information about the environmental occurrence and physicochemical properties of widespread polymers to predict the fate of aquatic plastic litter. Polyethylene and polypropylene are common in the surface layer and shorelines; polyester and cellulosic fibres in sewage treatment works, estuarine and deep-sea sediments. Overall, non-buoyant polymers are underrepresented on the ocean surface. Three main explanations are proposed for the missing plastic. The first is accumulation of both buoyant and non-buoyant polymers in sewage treatment works, river and estuarine sediments and along shorelines. The second is settling of non-buoyant polymers into the deep-sea. The third is fragmentation of both buoyant and non-buoyant polymers into particles smaller than captured by existing experimental methods. Some isolation techniques may overrepresent larger, buoyant particles; methodological improvements are needed to capture the full size-range of plastic litter. When microplastics fragment they become neutrally-buoyant, thus nanoplastics are potentially widely dispersed in aquatic systems, both horizontally and vertically. Ultimately, over decades or longer, plastics are potentially solubilized and subsequently biodegraded. The rates at which these processes apply to plastic litter in different environmental compartments remain largely unknown.

Global surface transport in the ocean can be represented by using the observed trajectories of drifters to calculate probability distribution functions. The oceanographic applications of the Markov Chain approach to modelling include tracking of floating debris and water masses, globally and on yearly-to-centennial timescales. Here, we analyse the error inherent with mapping trajectories onto a grid and the consequences for ocean transport modelling and detection of accumulation structures. A sensitivity analysis of Markov Chain parameters is performed in an idealised Stommel gyre and western boundary current as well as with observed ocean drifters, complementing previous studies on widespread floating debris accumulation. Focusing on two key areas of inter-ocean exchange - the Agulhas System and the North Atlantic intergyre transport barrier - we assess the capacity of the Markov Chain methodology to detect surface connectivity and dynamic transport barriers. Finally, we extend the methodology's functionality to separate the geostrophic and non-geostrophic contributions to inter-ocean exchange in these key regions.

There are fundamental gaps in our understanding of the fates of microplastics in the ocean, which must be overcome if the severity of this pollution is to be fully assessed. The predominant pattern is high accumulation of microplastic in subtropical gyres. Using in situ measurements from the 7th Continent expedition in the North Atlantic subtropical gyre, data from satellite observations and models, we show how microplastic concentrations were up to 9.4 times higher in an anticyclonic eddy explored, compared to the cyclonic eddy. Although our sample size is small, this is the first suggestive evidence that mesoscale eddies might trap, concentrate and potentially transport microplastics. As eddies are known to congregate nutrients and organisms, this phenomenon should be considered with regards to the potential impact of plastic pollution on the ecosystem in the open ocean.

Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.

There is growing global concern over the chemical, biological and ecological impact of plastics in the ocean. Remote sensing has the potential to provide long-term, global monitoring but for marine plastics it is still in its early stages. Some progress has been made in hyperspectral remote sensing of marine macroplastics in the visible (VIS) to short wave infrared (SWIR) spectrum. We present a reflectance model of sunlight interacting with a sea surface littered with macro plastics, based on geometrical optics and the spectral signatures of plastic and seawater. This is a first step towards the development of a remote sensing algorithm for marine plastic using light reflectance measurements in air. Our model takes the colour, transparency, reflectivity and shape of plastic litter into account. This concept model can aid the design of laboratory, field and Earth observation measurements in the VIS-SWIR spectrum and explain the results.

Understanding the global mass inventory is one of the main challenges in present research on plastic marine debris. Especially the fragmentation and vertical transport processes of oceanic plastic are poorly understood. However, whereas fragmentation rates are unknown, information on plastic emissions, concentrations of plastics in the ocean surface layer (OSL) and fragmentation mechanisms is available. Here, we apply a systems engineering analytical approach and propose a tentative 'whole ocean' mass balance model that combines emission data, surface area-normalized plastic fragmentation rates, estimated concentrations in the OSL, and removal from the OSL by sinking. We simulate known plastic abundances in the OSL and calculate an average whole ocean apparent surface area-normalized plastic fragmentation rate constant, given representative radii for macroplastic and microplastic. Simulations show that 99.8% of the plastic that had entered the ocean since 1950 had settled below the OSL by 2016, with an additional 9.4 million tons settling per year. In 2016, the model predicts that of the 0.309 million tons in the OSL, an estimated 83.7% was macroplastic, 13.8% microplastic, and 2.5% was < 0.335 mm 'nanoplastic'. A zero future emission simulation shows that almost all plastic in the OSL would be removed within three years, implying a fast response time of surface plastic abundance to changes in inputs. The model complements current spatially explicit models, points to future experiments that would inform critical model parameters, and allows for further validation when more experimental and field data become available.

As ocean general circulation models (OGCMs) move into the petascale age, where the output of single simulations exceeds petabytes of storage space, tools to analyse the output of these models will need to scale up too. Lagrangian ocean analysis, where virtual particles are tracked through hydrodynamic fields, is an increasingly popular way to analyse OGCM output, by mapping pathways and connectivity of biotic and abiotic particulates. However, the current software stack of Lagrangian ocean analysis codes is not dynamic enough to cope with the increasing complexity, scale and need for customization of use-cases. Furthermore, most community codes are developed for stand-alone use, making it a nontrivial task to integrate virtual particles at runtime of the OGCM. Here, we introduce the new Parcels code, which was designed from the ground up to be sufficiently scalable to cope with petascale computing. We highlight its API design that combines flexibility and customization with the ability to optimize for HPC workflows, following the paradigm of domain-specific languages. Parcels is primarily written in Python, utilizing the wide range of tools available in the scientific Python ecosystem, while generating low-level C code and using just-in-time compilation for performance-critical computation. We show a worked-out example of its API, and validate the accuracy of the code against seven idealized test cases. This version 0.9 of Parcels is focused on laying out the API, with future work concentrating on support for curvilinear grids, optimization, efficiency and at-runtime coupling with OGCMs.

The leakage of large plastic litter (macroplastics) into the ocean is a major environmental problem. A significant fraction of this leakage originates from coastal cities, particularly during extreme rainfall events. As coastal cities continue to grow, finding ways to reduce this macroplastic leakage is extremely pertinent. Here, we explore why and how coastal cities can reduce macroplastic leakages during extreme rainfall events. Using nine global cities as a basis, we establish that while cities actively create policies that reduce plastic leakages, more needs to be done. Nonetheless, these policies are economically, socially and environmentally cobeneficial to the city environment. While the lack of political engagement and economic concerns limit these policies, lacking social motivation and engagement is the largest limitation towards implementing policy. We recommend cities to incentivize citizen and municipal engagement with responsible usage of plastics, cleaning the environment and preparing for future extreme rainfall events.