Although rivers contribute to the flux of litter to the marine environment,
estimates of riverine litter amounts and detailed studies on floating
riverine litter behaviour once it has reached the sea are still scarce. This
paper provides an analysis of the seasonal behaviour of floating marine
litter released by rivers within the south-eastern Bay of Biscay based on
riverine litter characterizations, drifters, and high-frequency radar observations and Lagrangian simulations. Virtual particles were released in
the coastal area as a proxy of the floating fraction of riverine litter
entering from rivers and reaching the open waters. Particles were
parameterized with a wind drag coefficient (Cd) to represent their
trajectories and fate according to the buoyancy of the litter items. They
were forced with numerical winds and measured currents provided by
high-frequency radars covering selected seasonal week-long periods between
2009 and 2021. To gain a better insight into the type and buoyancy of the
items, samples collected from a barrier placed at the Deba River (Spain) were
characterized at the laboratory. Items were grouped into two categories: low-buoyancy items (objects not exposed to wind forcing, e.g. plastic bags) and
highly buoyant items (objects highly exposed to wind forcing, e.g. bottles). Overall, low-buoyancy items encompassed almost 90 % by number and
68 % by weight. Weakly buoyant items were parameterized with Cd= 0 % and
highly buoyant items with Cd= 4 %; this latter value is the result of the
joint analysis of modelled and observed trajectories of four satellite
drifting buoys released at the Adour (France), Deba (Spain), and Oria (Spain)
river mouths. Particles parameterized with Cd= 4 % drifted faster towards
the coast through the wind, notably during the first 24 h. In summer, over 97 % of particles beached after 1 week of simulation. In autumn this
value fell to 54 %. In contrast, low-buoyancy items took longer to arrive at the shoreline, particularly during spring with fewer than 25 % of
particles beached by the end of the simulations. The highest concentrations
(>200 particles km-1) were recorded during summer for Cd= 4 %
in the French region of Pyrénées-Atlantiques. Results showed that
the regions in the study area were highly affected by rivers within or
nearby the region itself. These results couple observations and a
river-by-river modelling approach and can assist decision-makers on setting
emergency responses to high fluxes of floating riverine litter and on
defining future monitoring strategies for heavily polluted regions within the
south-eastern Bay of Biscay.
Introduction
Rivers act as key vectors bringing improperly disposed and mismanaged litter
from land into the marine environment. Riverine litter poses a large threat
to freshwater systems by degrading aquatic life, impacting freshwater
quality, and increasing economic losses linked with human activities
(van Emmerik and Schwarz, 2020;
Al-Zawaidah et al., 2021). However, most of the litter research conducted to
date has focused on marine environments (87 %) when compared to
freshwaters systems (13 %) (Blettler et al., 2018). Indeed,
riverine litter contributions to oceans are still uncertain, and results
vary depending on the input data and the model applied
(Lebreton et al., 2017; Schmidt et al.,
2017; Mai et al., 2020). Recent findings derived from extensive modelling
efforts suggest that about 1600 rivers worldwide account for 80 % of
plastic inputs to the ocean, with small urban rivers among the most polluting
(Meijer et al., 2021). Models require comprehensive field
data and consistent and harmonized protocols to validate the amounts, type,
and size of riverine inputs (González-Fernández and Hanke,
2017; Wendt-Potthoff et al., 2020; Margenat et al., 2021). Such
comprehensive data were obtained in Europe thanks to the RIMMEL project
(González-Fernández and Hanke, 2017).
This research concluded that between 307 and 925 million floating riverine
litter items are annually transferred into the ocean mainly through small
rivers, streams, and coastal run-off (González-Fernández et al., 2021).
Once it has reached the sea, floating riverine litter can accumulate close
to the shoreline or it can be transported to open waters, reaching even
remote areas far from the coast. Indeed, the distribution and fate of
floating litter in the marine environment is affected by the metocean
conditions (currents, turbulence, wind) but also by the buoyancy of the
objects (Ryan, 2015; Lebreton et
al., 2019; Maclean et al., 2021). Objects with low buoyancy are mainly
driven by currents, by contrast with highly buoyant items, which are driven along
the water surface partially by winds. This wind effect (“windage”) on
floating marine litter behaviour has been further investigated by Lagrangian
modelling studies in the open ocean (Allshouse et al., 2017; Maximenko
et al., 2018; Lebreton et al., 2019; Abascal et al., 2009) when compared to
the coastal area (Critchell and Lambrechts,
2016; van Utenhove, 2019; Tong et al., 2021). The lack of observational data is
one of the key limitations for parameterizing the windage effect and
accurately predict floating marine litter behaviour. However, observations
derived from drifting buoys, such as those provided for decades by the
Global Drifter programme, have been used to fill this gap. They have allowed
simulating more realistic floating marine litter pathways from origin to
fate by integrating experimental windage parameterizations and the
corresponding comparison between observed and modelled trajectories
(Duhec et al., 2015;
Pereiro et al., 2018; Rizal et al., 2021). Nowadays, more affordable and
environmentally friendly solutions are gaining force among researchers, as
drifters are built using biopolymers (Novelli et al.,
2017; D'Asaro et al., 2020) or have compact and lightweight designs with a
GPS-tracking component for easy deployment (Meyerjürgens et al., 2019;
van Sebille et al., 2021).
At the coastal scale, windage parameterization combined with realistic knowledge
on coastal circulation becomes crucial to reduce the uncertainties of
modelled trajectories (Van Sebille et al., 2020). Land-based
high-frequency radar systems (hereafter HF radars,
Rubio et al., 2017) offer the opportunity to
monitor surface currents in coastal areas, where the transport processes are
significantly more complex than in open-ocean waters due to the effect of the
coast, the bathymetry, and other local forcings (e.g. river discharges or
coastal upwellings). In the south-eastern Bay of Biscay (hereafter SE Bay of
Biscay), as part of the operational oceanography system
EuskOOS, an HF radar provides near-real-time surface currents fields. The system has already been used to study surface coastal transport processes in the area in combination
with multisource data (Manso-Narvarte
et al., 2018, 2021; Rubio et al., 2011, 2013, 2018, 2020; Solabarrieta et
al., 2014, 2015, 2016). The HF radar is also a good example of effective
monitoring of surface currents with strong potential for floating marine
litter management. Research conducted by Declerck et al. (2019) in the SE Bay of Biscay provided the first assessment of floating
marine litter transport and distribution in the region, coupling surface
current observations from the EuskOOS system, Lagrangian modelling, and riverine
inputs. Nowadays, these observations are used by local authorities both in
real time and in hindcast in the framework of the operational service
FML-TRACK to collect floating marine litter in the area. However, the
accurate modelling of the transport and fate of floating marine litter needs to
consider the variety of floating objects and sources and additional physical
parameterization, such as windage.
This paper aims at estimating the seasonal behaviour of the floating marine
litter fraction released by rivers within the SE Bay of Biscay reaching open
waters. To do so, a Lagrangian model was forced by real observations from the
EuskOOS HF radar and particles were parameterized to represent floating
marine litter trajectories of two groups of items according to their
buoyancy. Riverine litter collected from a local barrier was characterized
at the laboratory to explore the fraction of high- and low-buoyancy items.
Since most of the items were low-buoyancy, simulations considering only
surface currents were performed as the reference. Complementary Lagrangian
simulations for highly buoyant items (and less abundant in the area) were
also performed. In this case, four low-cost buoys with a similar buoyancy to certain highly buoyant items were built and released in three different rivers.
Drifter data were used to parameterize the wind effect on this type of item and consequently achieve more accurate results.
Study area
The study was conducted in the SE Bay of Biscay, between north-eastern Spain
(Basque Country) and south-western France (Landes). The study area extends
from 43.27 to 44.58∘ N and from 3.18 to
1.27∘ W, falling within the coverage area of the HF radar station
of the operational oceanography system EuskOOS (Fig. 1). The study area
comprises two Basque regions (Bizkaia (Spain) and Gipuzkoa (Spain)), two
French departments (Pyrénées-Atlantiques and Landes), and eight rivers (Deba (Spain), Urola (Spain), Oria (Spain),
Urumea (Spain), Oiartzun (Spain), Bidasoa (Spain), Nivelle (France), and
Adour (France)). The mean annual river discharge varies widely between
rivers from 3.71 m3 s-1 (Oiartzun) to 350 m3 s-1 (Adour) (Sheppard, 2018), and the population density differs between the
Spanish and French border: 44.8 inhabitants km-2 (Landes) to 303.7 inhabitants km-2 (Basque Country) (Eurostat, 2019). The
bathymetry in the SE Bay of Biscay is characterized by the presence of a
narrow continental shelf ranging 7 and 24 km wide in the Basque
area, gradually increasing along the French coast up to about 70 km
(Bourillet et al., 2006;
Rodríguez et al., 2021). The continental shelf in the SE Bay of Biscay
comprises two main areas: the Aquitaine shelf with a N–S orientation and
the Cantabrian shelf with an E–W orientation. The continental slope is very
pronounced, with a slope of the order of 10 %–12 %
(Sheppard, 2018). Over the continental shelf, the ocean
circulation is marked by seasonal variability. At shorter temporal scales,
circulation in the study area is mostly modulated by the bathymetry and the
coastal orientation, the density-driven currents, and winds (Le Boyer et al., 2013;
Solabarrieta et al., 2014). Tidal currents are quite weakly constrained by the
topography and the width of the continental shelf
(Lavin et al., 2006; González et al., 2007;
Karagiorgos et al., 2020). Along-shelf currents are more intense and
persistent during winter and autumn (about 10–15 cm s-1), contrary to
the other seasons, especially in summer (about 2.5 cm s-1)
(Charria et al., 2013). In
winter, the prevailing SW winds causes an E to N flow from the Spanish
coasts towards the French coasts. The moderate to strong NW winds occurring
in spring and summer induce a S and SW surface current circulation
accompanied by a greater variability (Solabarrieta
et al., 2015). In winter, westerly winds in the Basque coast reinforce the
slope current (named the Iberian Poleward Current (IPC)), a warm and saline intrusion trapped within 50 km of the shelf edge, reaching its greatest velocities (up to 70 cm s-1) during this season. The IPC favours the along-slope transport of water
masses (Solabarrieta et al.,
2014; Porter et al., 2016). The exchange between shelf and deep-sea waters
in winter is associated with the generation of eddies, from the interaction of
currents with the topography (Lavin et al.,
2006; Rubio et al., 2018; Teles-Machado et al., 2016). Maximum run-offs
combined with SW winds also allow river plumes to spread northwards and along
the French shore during winter. However, this path changes in spring, when
river discharges are reduced and winds blow from the north-west (Lavin et al., 2006; Puillat et al., 2006).
First global modelling studies coupling ocean circulation and Lagrangian
particle-tracking models reported that the SE Bay of Biscay is a hotspot for
floating marine litter (Lebreton et al., 2012; van Sebille et al., 2012).
Recent Lagrangian modelling studies combining measured and predicted surface
currents by the HF radar and the Iberian Biscay Irish System (IBI) Copernicus model revealed that floating
marine litter circulation in the SE Bay of Biscay is marked by a high
seasonal variability. Results showed a higher retention during spring and
summer and a northward dispersion along the French coast during autumn and
winter (Declerck et al., 2019; Rubio et
al., 2020). Surface currents derived from the Regional Ocean Modelling System
(ROMS) and a particle-tracking model were combined by
Pereiro et al. (2019) to track the numerical
drifters representing floating marine litter in the Bay of Biscay. In this
study, longer residence times and higher concentrations were observed in the
SE Bay of Biscay when compared to north-western Iberian coastal waters,
particularly in winter. From numerical simulations run using the HYCOM model, Rodríguez-Díaz
et al. (2020) showed that
floating marine litter items with high windage (Cd= 3 %–5 %) tend to
accumulate in nearshore areas of the Bay of Biscay or end up beached. This
trend is consistent with recent numerical simulations combining surface
currents from the operational IBI and the
numerical model TESEO that also revealed that the highly buoyant items
(Cd= 4 %) rapidly beach in the SE Bay of Biscay, mainly in spring and
summer (Ruiz et al., 2022a). Since June
2020, innovative detection and tracking solutions combining ocean modelling
and remote observation systems have been operating in the SE Bay of Biscay to support floating marine litter reduction strategies both downstream
(interception at the sea with collection vessels and on beaches with cleaning
facilities) and upstream (source identification and reduction)
(Delpey et al., 2021). However, research on floating marine
litter behaviour in the SE Bay of Biscay is still in its early stage.
Further experiments are needed to fully understand the role of windage,
waves, and tides in the complex 3D circulation patterns governing coastal
accumulation.
Study area with the release locations of the satellite drifting buoys
and the riverine barrier. Dots in light yellow represent the nodes of the HF
radar grid. Dots in orange represent the trajectories of the buoys. Numbers
with stars in pink correspond to the particle releasing location for
floating marine litter simulations: (1) Deba, (2) Urola, (3) Oria, (4) Urumea, (5) Oiartzun, (6) Bidasoa, (7) Nivelle, and (8) Adour rivers.
Methods and dataRiverine litter sampling
In spring 2018, a riverine barrier was placed in the Deba River (Gipuzkoa) to
retain and collect floating riverine litter during low to moderate flows.
This barrier enabled a passive sampling to characterize litter items in the lab. The barrier, which consisted of a nylon artisanal net supported by hard
floats (buoys), was 40 m long and 0.6 m high with a 60 mm mesh size (see
photos in Appendix A). The sampling was conducted weekly from April to
June 2018. In total eight riverine litter samples were collected. Litter
items were quantified, weighed, and categorized in the lab according to the
master list included in the Guidance on Monitoring of Marine Litter in European Seas (Joint Research Centre, 2014). Items were grouped into
seven types of material (artificial polymer materials, rubber, cloth/textile,
processed/worked wood, paper/cardboard, metal, and glass/ceramics) and
further classified into 44 categories (see the classification in Appendix B). Riverine litter items were also categorized into two groups (low- and
high-buoyancy items) considering their exposure to wind based on Ruiz et al. (2022a).
Drifter observations
Four satellite drifting buoys (herein after “low-cost buoys”) were built by
the authors and deployed one by one in the river mouths of the Deba (Buoy A),
Oria (Buoy B), and Adour (buoys C and D) between April 2018 and November 2018
(Fig. 1, Table 1). The low-cost buoys provided positioning every 5 min
using satellite technology. Low-cost buoys were 9 cm in height and 9.5 cm in
float diameter and weighed approximately 200 g (Fig. 2). A GPS (SPOT Trace
device) powered by four AAA cells was placed in the bottom of a high-density
polyethylene (HDPE) plastic container sealed to guarantee water tightness.
They were chosen because of their capability to ensure a reasonable balance
between an accurate signal emission and their purchase and communication
fees. SPOT Trace devices have been used over the past few years in coastal
and open-ocean applications in a wide range of studies. Studies range from calibrating HF radars (Martínez Fernández et al.,
2021) and tracking drifting objects such as icebergs (Carlson et al.,
2020), pelagic Sargassum (Putman et al., 2020;
van Sebille et al., 2021), or fishing vessels (Widyatmoko et al.,
2021; Hoenner et al., 2022) to search and rescue training
(Russell, 2017) and oil spill and litter monitoring
(Novelli et al., 2018; Meyerjürgens et
al., 2019). Almost two-thirds of the buoy floated above the water surface, thus
preventing any satellite signal losses. Buoys A and D and transmitted their
positions on an ongoing basis until their landing. Buoys B and C stopped
emitting while they were drifting. In all cases, battery lifetime was enough
for an adequate performance of the buoys. Once on land, citizens collected
the buoys and reported their corresponding location.
Main components of the low-cost buoy. The structure: (a) HDPE
container and SPOT Trace device powered by four AAA cells. Assembly process:
(b) final appearance once the buoy is sealed; the buoy is labelled with
contact information both within and outside; (c) the SPOT Trace was fixed at
the base of the container with adhesive tape to avoid twists and turns of
the buoy.
Locations, periods, and distances covered by the drifting buoys.
Buoy IDRiverInitial date (UTC+1)Final dateDistance covered (km)ADeba16 September 2018 08:004 October 2018 07:00116.1BOria12 April 2018 16:0018 April 2018 12:00118.72CAdour29 July 2018 20:002 August 2018 20:0071.21DAdour28 November 2018 09:0030 November 2018 11:0064.41HF radar current observations and wind data
Surface velocity current fields were obtained from the EuskOOS HF radar
station composed by two antennas located at Matxitxako and Cape Higer and
covering the SE Bay of Biscay since 2009, a range up to 150 km from the
coast. The EuskOOS HF radar is part of JERICO-RI and it is operated
following JERICO-S3 project best practices, standards, and recommendations
(see Solabarrieta et al., 2016; Rubio
et al., 2018, for details). Data consist of hourly current fields with a 5 km spatial resolution obtained from using the gap-filling OMA methodology
(Kaplan and Lekien, 2007;
Solabarrieta et al., 2021). In total, 85 OMA modes, built setting a minimum spatial
scale of 20 km and applied to periods with data from the two antennas, were
used to provide maximum spatiotemporal continuity in the HF radar current
fields, which is a prerequisite of performing accurate Lagrangian
simulations. The application of the OMA methodology has been validated for the
Lagrangian assessment of coastal ocean dynamics in the study area by
Hernández-Carrasco et al. (2018). HF
radar velocities were quality controlled using procedures based on velocity
and variance thresholds, signal-to-noise ratios, and radial and total
coverage, following standard recommendations (Mantovani et al., 2020). Data subsets
were built for the Lagrangian simulations avoiding periods with temporal
gaps (still present in the case of the failure of one or two antennas) of more
than a few hours. Hourly ERA5-U10-wind fields were obtained from the
atmospheric reanalysis computed using the IFS model of the European Center
for Medium-Range Weather Forecast (ECMWF) (see C3S, 2019 for
details). The ERA5 atmospheric database covers the Earth on a 30 km horizontal
grid using 137 vertical levels from the surface up to a height of 80 km and
provides estimates of a large number of atmospheric, land, and oceanic
climate variables, currently from 1979 to within 3 months of real time. Both
HF radar current observations and wind data cover the drifter's emission
periods and the selected week-long periods between 2009 and 2021 for
riverine litter simulations (see Appendix C for the selected periods).
Particle transport model
The application of the transport module of the TESEO particle-tracking model
(Abascal et
al., 2007, 2017a, b; Chiri et al., 2020) was two-fold: (1) to simulate the
transport and fate of floating marine litter entering from rivers and
reaching the open waters of the SE Bay of Biscay and (2) to estimate a windage
coefficient by calibrating the model according to the low-cost buoy trajectories. This module allows for simulating passive particles driven by
surface currents, wind, and turbulent diffusion. Particle trajectories were
calculated using the following equation:
dxidt=ua(xi,t)+ud(xi,t),
where ua and ud are the advective velocity and
diffusive velocity, respectively, for the xi point and t time.
The advective velocity is calculated as the lineal combination of the wind
and currents according to
ua=uc+Cduw,
where uc is the surface current velocity, uw is the
wind velocity at 10 m over the sea surface, and Cd is the wind drag
coefficient. The turbulent diffusive velocity is obtained using Monte Carlo
sampling in the range of velocities [-ud, ud], which are assumed to be proportional to the diffusion coefficients (Hunter et al., 1993; Maier-Reimer and
Sündermann, 1982). For each time step Δt, the velocity
fluctuation is defined as
ud=6DΔt,
where D is the diffusion coefficient, whose value is 1 m2 s-1 in
accordance with previously modelling work for floating marine litter (Pereiro et al.,
2019; Ruiz et al., 2022a). Simulations were forced by HF radar surface
current velocity and wind data and interpolated at the particle's position
for integrating the trajectories. Beaching along the coast was implemented
by a simple approach: if the particle reaches the shoreline, it is
identified as beached, and it is removed from the computational
process. TESEO has been calibrated and validated by comparing
virtual particle trajectories to observed surface drifter trajectories at
regional and local scale (Abascal
et al., 2009, 2017a, b; Chiri et al., 2019). TESEO is a 3D numerical model
conceived to simulate the transport and degradation of hydrocarbons, but it
has also been successfully applied to the study of transport and accumulation of
marine litter in estuaries (Mazarrasa et al., 2019;
Núñez et al., 2019) and in open waters (Ruiz et al., 2022a).
Wind drag estimation
Two simulation strategies were combined for (1) estimating the wind drag
coefficient and (2) studying the seasonal behaviour of floating items in the
area (Sect. 3.5.2) The wind drag coefficient (Cd) was determined by
comparing the observed trajectories provided by the low-cost buoys and the
modelled trajectories performed with TESEO. The test was done through
different parameterizations of the wind drag coefficient ranging from 0 %
to 7 % (Table 2). This range was chosen based on previously floating
marine litter studies coupling Lagrangian modelling and observations from
satellite drifting buoys (Carson et al.,
2013; Stanev et al., 2019; Van Der Mheen et al., 2019). The coefficient
providing the lowest error was considered the best coefficient to simulate
highly buoyant litter. Due to the grid limitations of the surface currents
and wind data in the coastal area, the comparison was not initialized at the
launching position of the low-cost buoys (river mouths), but instead it was
initialized at the closest grid element that contained valid currents and
wind data (Table 1). Observed positions were interpolated into a uniform
1 h time, fitting the metocean temporal resolution. A release of 1000
virtual particles was performed every 4 h at the corresponding observed
position (Table 2). Particles were tracked over a 24 h period and the
trajectory of the centre of mass of all the particles was computed at every
time step to represent the track of the particle cloud. Observations were
compared to modelled trajectories using the simple separation distance, which
is the difference between the observed and the computed position of the
centre of mass at a time step t. The mean separation distance
D(tmod)‾ was calculated for every modelled position based on the
simple separation distance following Eq. (4):
D(tmod)‾=1N∑i=1NXmodtmod-Xobs(tobs),
where Xmodtmod and
Xobs(tobs) are the modelled and observed trajectories for the
simulation period i of a total of N periods. A mean separation distance
curve was computed for every wind drag coefficient derived from the mean
separation distance curves of the four buoys. The area beneath the mean
separation distance curve was calculated to select the more suitable wind
drag coefficient. The area D̃ was calculated as a numerical
integration over the forecast period via the trapezoidal method following
Eq. (4). This method approximates the integration over an interval by
breaking the area down into trapezoids with more easily computable areas:
D̃≈∫tmod=1tmod=24D(tmod)‾dt.
Lagrangian seasonal simulation of riverine litter items
Seasonal simulations were run for low- and high-buoyancy items to assess the
seasonal differences in the transport and fate of floating riverine litter
once it has reached the open waters of the SE Bay of Biscay. Particles were
released around 2.5 nautical miles off the shoreline due to the complexity
in resolving small-scale processes of floating riverine and marine litter
behaviour in and close to the river mouths. As parameterizations concerning
wind effect linked to the object characteristics are scarce, the optimal
wind drag coefficient estimated for the buoys (see Sect. 3.5.1) was
accounted for by simulating the behaviour of the objects highly exposed to wind.
No wind drag parameterization (Cd= 0 %) was applied for low-buoyancy
objects not subjected to the wind effect. A total of 10 periods per season
uniformly distributed within the study period (2009–2021) were considered
for running the simulations based on the availability of HF radar surface
current datasets (Appendix C). In total, 80 simulations (40 for Cd= 0 %
and 40 for Cd= 4 %) were run for 7 d. For each simulation, 4000 particles were released in eight rivers (500 per river) assuming that river
discharges are equal despite the seasonal variations and the morphological
differences between rivers (Table 2). The total number of particles modelled
for Cd= 0 % was the same as Cd= 4 %. Post-processing was carried out
to compute by river (1) the particles' evolution over the time from their
release until their arrival at the shoreline and (2) the particles'
distribution on the shoreline, counting the number of beached particles per
kilometre of shoreline and indicating the spatial concentration per region.
Simulation, release, and physical parameter values for wind drag
estimation and floating riverine litter simulations.
Simulation parameters Release parameters Physical parameters Number of particlesIntegration timeTime stepRelease locationsRelease timeTurbulent diffusion coefficientWind drag coefficient (Cd)Simulations for wind drag estimation1000 per location24 h60 sAt the observed locations of the buoyOver the emitting period of the buoy at spaced intervals of 4 h1 m2 s-10 %, 2 %, 3 %, 4 %, 5 %, 6 %, 7 %Seasonal riverine litter simulations500 per river1 week60 sAt a distance of 2.5 nautical miles from the river mouthAt the beginning of the selected time period (10 periods per season)1 m2 s-10 %, 4 %ResultsRiverine litter characterization
In total 1576 items and 11.597 kg of floating riverine litter were sampled
and characterized (Fig. 3). Plastic was the most common type of riverine litter in
terms of the number of items (95.1 %) and in weight (67.9 %); they were also
frequent glass/ceramics (16.1 %) and cloth/textile items (6.9 %) when counted by weight. The top
10 litter items accounted for 93.3 % by number and 72.6 % by weight of
the total riverine litter (Table 3). Plastic/polystyrene pieces between 2.5 and 50 cm and other plastic/polystyrene identifiable items (e.g. food labelling) were the most
abundant in terms of number (71.2 %) and weight (16.9 %). Weakly buoyant items encompassed
almost 91 % by number and 68 % by weight of litter items (Fig. 4).
Composition of riverine litter by type of material in terms of the number
of items and weight. Items were collected by the barrier placed in the Deba
River (Gipuzkoa) between April and June 2018.
Top 10 (X) riverine litter items collected from the barrier
located in the Deba River (Gipuzkoa) between April and June 2018. Items have
been ranked by abundance (left) and weight (right) according to the master list categories of beach litter items and classified based on their
exposure to the wind effect.
Riverine litter classification based on the exposure to the wind effect.
Items were collected from the barrier located in the Deba River (Gipuzkoa)
between April and June 2018.
Wind drag coefficient for drifting buoys
Total distances covered by drifting buoys ranged from 62 to 118 km (Table 1), and they all scattered over the HF radar coverage area. Buoys provided
their position data over 385 h before beaching on the Landes and Gipuzkoa
shorelines. When compared with numerical trajectories obtained using
different Cd parameterizations, the mean separation distance
(D(tmod)‾ increased nearly linearly with time for all the
parameterizations, achieving a maximum separation of almost 14 km at 24 h
for Cd= 0 % (Fig. 5). Overall, using no windage parameterization provided
the largest D̃‾. Simulations parameterized with Cd= 4 %
provided the best results with an average ± standard deviation (SD) of
3.2 ± 1.25 km and a maximum value of 4.85 km at 24 h. When assessing
the mean separation distance for all the modelled positions at every observed
position of the buoys, the most common range separation distance for
Cd= 4 % was 2–4 km (Fig. 6). Hence, a wind drag coefficient of 4 % was
applied in the remaining analysis to estimate the behaviour of highly
buoyant items.
Mean separation distance between modelled and observed
trajectories for each wind drag coefficient. The dark line is the mean curve
used for the trapezoidal integration.
Spatial mean distance between modelled and observed trajectories of
buoy A, B, C, and D with a drag coefficient Cd= 4 %. Particle trajectories
were simulated during 24 h, with a re-initialization period every 4 h.
The modelled trajectories are shown in solid lines. Circles represent the mean separation distance at the
observed position for all the modelled positions.
Seasonal trends in floating riverine litter transport and fate
Particle concentration on the shoreline varied between 0 and 258.46 particles km-1 (Fig. 7). Particles parameterized with Cd= 4 % drifted faster
towards the coast, notably during the first 24 h. The highest
concentrations (>200 particles km-1) were recorded during summer
in Pyrénées-Atlantiques for Cd= 4 %, probably due to the seasonal
retention patterns within the study area (Appendix D). Although less
intensely, Cd= 4 % also led to a high particle concentration in
Pyrénées-Atlantiques (106.86 particles km-1) and Gipuzkoa (166.1 particles km-1) during winter. The lowest concentrations (0–20 particles km-1)
were recorded for Cd= 0 % after the first 24 h of simulation,
particularly during autumn. Overall, Bizkaia was the less impacted region
for both windage coefficients (<40 particles km-1). During summer,
over 97 % of particles parameterized with Cd= 4 % beached after 1 week of simulation (Fig. 8). In autumn this value fell to 54 %. In
contrast, beached particles parameterized with Cd= 0 % were less abundant
by the end of the simulations, particularly during spring with less than
25 % of particles trapped in the shoreline.
Overall, the average of particles parameterized with Cd= 0 % was higher
when comparing to Cd= 4 % (Fig. 9). Particles released in French rivers
and parameterized with Cd= 0 % were less abundant during summer, though
this trend was reversed in autumn. For Cd= 0 %, the number of particles
released in the Bidasoa River during summer were the least abundant after 1 week of simulation (<200 particles on average). The vast majority
of particles released in the Urumea River during winter were floating in the
study area by the end of the simulations (479 particles on average).
Particles parameterized with Cd= 4 % beached faster during the first 48 h, mainly in summer and for those particles released in the French
rivers. During this season, the average number of particles floating in the
study area by the end of the simulation ranged between 0 and 250. Similar
trends were observed within the same season between rivers, probably
influenced by the vicinity of rivers and the spatiotemporal resolution of
forcings. Over 40 % of the total particles parameterized with Cd= 4 %
and almost 12 % parameterized with Cd= 0 % beached in Gipuzkoa (Fig. 10). During spring, almost 60 % of beached particles parameterized with
Cd= 0 % were located Bizkaia. For Cd= 0 %, particles released during
summer in the rivers located in the western area of Gipuzkoa drifted longer
distances and reached the Landes shoreline. This trend changed during winter,
when the vast majority of particles released in Gipuzkoa rivers beached
mainly in Gipuzkoa and Bizkaia. Beached particles parameterized with
Cd= 0 % experienced more seasonal variations derived from the surface
current circulation patterns within the SE Bay of Biscay. For Cd= 4 %,
particles beached in Gipuzkoa ranged between 51 % in spring and 38 % in
winter, and Bizkaia was the less affected region despite the season. Overall,
all regions were highly affected by rivers within or nearby the region
itself.
Particle concentration on the Bizkaia, Gipuzkoa, Pyrénées-Atlantiques, and Landes shoreline. The seasonal distribution is shown for Cd= 0 % and Cd= 4 % after 24 and 168 h of simulation.
Seasonal numbers of beached particles parameterized with Cd= 0 %
and Cd= 4 % after 168 h of simulation.
Temporal evolution of the particles parameterized with Cd= 0 %
and Cd= 4 % throughout the different seasons. The curves represent the
average number of particles floating in the water surface by river and for
every time step.
Seasonal analysis of the beached particles parameterized with Cd= 0 % and Cd= 4 % per region and river by the end of the simulation period. The nodes of the region correspond to the number of beached particles. The country to which each river belongs – France (Pyrénées-Atlantiques) and Spain (Gipuzkoa) – is shown on the left side of each figure. The width of the node depicts the sum of the beached particles, and the links represent the number of particles beached per river.
DiscussionRiverine litter composition
An artisanal net placed at the mouth of the Deba River enabled sampling riverine
litter in the study area during spring 2018. Short and narrow rivers prevail
in the SE Bay of Biscay, affected by a strong tidal regime and very
intense, stationary and persistent storms (Ocio et
al., 2015). Studies aiming at reporting the abundance and composition of
floating riverine litter in European rivers date back less than 10 years, and
they were performed in larger and more abundant rivers than the Deba River.
Despite the morphology and hydrological differences, plastic was the
predominant material in the Deba River, as in the Siene
(Gasperi et al., 2014), Danube (Lechner et al., 2014) or
Rhine River (van der Wal et al., 2015). Similarities were
also found when comparing the top 10 list of riverine litter items to
rivers located in the north-east Atlantic region. Plastic/polystyrene pieces between 2.5 and 50 cm (71.2 %) top the list in
terms of the number of items, and their abundance was slightly higher when
compared to north-east Atlantic rivers (54.53 %)
(Bruge et al., 2018;
González-Fernández et al., 2018). Lower abundances were observed in the
Mediterranean (25.01 %) and the Black Sea (13.74 %). Riverine litter
items trapped on vegetation or deposited on the riverbank can be degraded by
weather conditions (rain, wind, etc.) favouring the fragmentation in plastic
pieces before their arrival in the coastal and marine environment (Chamas
et al., 2020). The fragmentation can be also influenced by the material and
the shape of the litter items (Woods et al., 2021).
Differences in plastic/polystyrene pieces between 2.5 and 50 cm abundances can be attributed to a faster fragmentation due
to the variations in weather conditions between river basins. However, more
detailed analyses on the physical characteristics of litter items (i.e. polymer type) are necessary to fully assess their impact on the occurrence
of fragmented plastic pieces. Results are also in line with the ranking list
of the top 10 beach litter items across the north-east Atlantic region
revealing that single-use plastics (i.e. food containers, bottles, and other
packaging) are among the most abundant riverine litter items together with
plastic fragments (European Commission, 2018). These results differed
from the analysis performed in sea small-scale convergence areas of floating
marine litter (“litter windrows”) on the coastal waters of the SE Bay of Biscay, where
fishing-related items were the second most abundant sub-category in terms of
number after plastic/polystyrene pieces between 2.5 and 50 cm (Ruiz et al., 2020). Substantial differences also exist between
riverine litter sampled in the Deba River and floating marine litter assessed by
visual observation from research vessels in open waters of the Bay of Biscay
(Ruiz et al., 2022a). Differences might be
related to the monitoring method and, also, to the size of the items, since
small items, such as plastic pieces, can be overlooked by the observer when
the visual counting method is applied, contrary to riverine litter samplings for
later analysis in the lab. Overall, riverine litter data acquisition is mainly
focused on the floating fraction, and the litter loads under the surface
water are often ignored. Increasing the quantity of rivers sampled, the
frequency, and the riverine water compartments is necessary to establish the
composition and trends of riverine litter in the SE Bay of Biscay.
Wind drag estimation
One of the largest uncertainties for predicting floating riverine and marine
litter behaviour is the proper quantification of a wind drag coefficient.
Wind drag estimations conducted so far for floating marine litter items
range between 0 % and 6 % (Ko et al., 2020;
Critchell and Lambrechts, 2016; Neumann et al., 2014) with an upper limit of
10 % (Yoon et al., 2010). However, only a few of them
have been validated using observational data
(Maximenko et al., 2018; Callies et al., 2017). In
this study, data provided by low-cost buoys combined with surface
current measurements by HF radar were used as a proxy for modelling the
drift of floating litter objects with similar buoy characteristics (density,
size, and shape). Results demonstrated that Cd= 4 % was the optimal wind
drag coefficient for accurately represent the pathways of the low-cost
buoys in the study area. This value can be consistent with the estimations
of the partially emerged Physalia physalis for the Bay of Biscay
(Ferrer and
Pastor, 2017), but it is almost 3 times higher than the maximum wind drag
coefficient reported in the area by Pereiro et al. (2018). This can be
explained by the fact that buoys used in the experiment remained submerged
beneath the sea surface and were less exposed to the wind effect. The estimated
wind drag coefficient was also greater than Cd= 3 % observed for the
Prestige oil spill accident (Abascal et al., 2009;
Marta-Almeida et al., 2013). Indeed, oil spill studies refer to a range of
wind drag coefficient between 2.5 % to 4.4 % of the wind speed, with a mean
value of 3 %–3.5 % (e.g. ASCE,
1996; Reed et al., 1994). Object characteristics may change over time
due to the exposure to wind, waves, UV radiation, seawater, and the
attachment of organic material (Kooi et al., 2017;
Min et al., 2020). Objects become breakable, and biofouling increases their
density, overcoming the positive buoyancy and impacting their trajectory.
Investigations so far pinpointed longer timescales (weeks to months and longer) than considered in this study (days) for a significant change on the
behaviour of floating objects (Ryan,
2015; Fazey and Ryan, 2016). Consequently, physical variations in the buoy
properties were not accounted for the wind drag estimation. The separation
distance between observed and modelled trajectories has been commonly used to
evaluate the skill of particle-tracking models (Callies
et al., 2017; Haza et al., 2019; Aksamit et al., 2020; Abascal et al.,
2012). In this study, the purpose was not to evaluate the model accuracy but to estimate the wind drag coefficient for the low-cost buoys. However, the
novel approach proposed by Révelard et al. (2021) may
be of particular interest for future experiments oriented towards assessing the wind
drag coefficient of highly buoyant items drifting for short time periods
in the coastal area.
Seasonal riverine litter distribution by region
It is broadly accepted that the SE Bay of Biscay is polluted with floating
marine litter discarded or lost in the marine and coastal area but also with
litter originating inland and transported via rivers and run-off. However,
detailed studies on riverine litter contribution are still scarce, and
modelling efforts combining observations and physical parameterizations of
floating litter properties are non-existent. This study shows that the
exposure to the wind effect largely controls the transport and coastal
accumulation of floating marine litter in the SE Bay of Biscay, with
concentrations varying between regions and over time. Concentrations in
Pyrénées-Atlantiques and Gipuzkoa differed widely from the other
studied regions. Indeed, the highest concentrations occurred in both regions
during summer for low- (100–120 particle km-1) and high-buoyancy items
(> 200 particles km-1). A higher number of particles beached in
Gipuzkoa during summer when compared to Pyrénées-Atlantiques, but
concentrations were lower since the Basque shoreline is longer. The pathways
and fate of low-buoyancy items reflect the seasonal surface water circulation
patterns in the SE Bay of Biscay. Results are in line with findings provided
by Declerck et al. (2019) who pinpointed a higher coastal
retention in the area during spring and summer. Weakly buoyant objects remained
floating at the coastal waters and highly buoyant objects tended to beach
remarkably faster as reported in literature by
Rodríguez-Díaz et al. (2020). However,
long-term data collected by in situ observations of beached litter across
the different regions are necessary to validate the large seasonal
variations and to assess the reliability of concentration levels for
addressing riverine litter issue in priority regions with heavily polluted
coastlines.
Rivers as key vectors of riverine litter
The interpretation of the spatial and temporal riverine litter distribution
by river can be challenging since riverine litter fluxes in the study area
are highly uncertain. In the study area, two major assumptions were made
regarding the river systems: (1) the same river discharge for all rivers and (2) the same river discharge for all seasons. This means that the same amounts of
riverine litter were allocated for every river regardless of the differences in
the width and depth and the seasonal flow variations. Since each river basin
has its own particularities, future modelling approaches should be adapted
to the morphology and hydrological conditions of the catchment area.
Other drivers, such as the land use or population density, can be a determining
factor for the amount of mismanaged litter that could contribute to riverine
litter fluxes (Schmidt et al., 2017;
Schuyler et al., 2021). It is also necessary to further investigate if
higher river flows in the area are directly related to an increased
discharge of riverine litter since analysis already performed in different
river basins shows contradicting relations between the occurrence of riverine
litter and river fluxes (van Emmerik and Schwarz,
2020). Along with the complex nature of qualifying riverine litter fluxes,
litter behaviour in the coastal area of the SE Bay of Biscay is still in its
early stage, and much has yet to be revealed. Particular attention should be
paid to Pyrénées-Atlantiques and Gipuzkoa, as the main impacted regions
in the studied area. Rivers in the study area are mainly located in Gipuzkoa, which favours the accumulation of floating litter in this region regardless of the season. Regional coordination should be reinforced due to the
transboundary movement of floating riverine litter in the study area and
reasonable efforts oriented towards retaining or removing riverine litter as clean-up
measures in the riverbanks should be investigated to avoid litter being
transported to the coastal and marine environment.
Model limitations
The interaction between floating litter and the shoreline is highly complex
and relies on many processes including waves and tides. Indeed, waves and
tides can constrain coastal accumulation since they can resuspend and
transport litter back into the ocean (Brennan et al.,
2018; Compa et al., 2022). The geomorphology can also affect the retention
of litter washing ashore. Sandy beaches tend to be more efficient at
trapping and accumulating litter than rocky areas, which favour litter
fragmentation (Robbe
et al., 2021; Weideman et al., 2020). How these processes contribute to the
actual beaching is unknown, and they cannot be resolved yet at a suitable
resolution (Melvin et al., 2021). In this study, particles
were released in open waters, and once they reached the shoreline, they were
classified as beached. The tidal effect and the wave-induced Stokes drift
were not accounted for to avoid introducing more uncertainties. However, further
field and laboratory experiments to better understand how these processes
influence floating litter behaviour on the coastline are recommend. For future research, it is also important to consider exploring the effect of the
type of shoreline on coastal accumulation. In this study, a constant
diffusion coefficient of 1 m2 s-1 was regarded as a pragmatic choice
based on previous modelling work for floating marine litter. However, more
field measurements are necessary to accurately assess the influence of the
diffusion process on the transport of floating marine litter.
Conclusions
The SE Bay of Biscay has been described by global and regional models as an
accumulation zone for floating marine litter. However, detailed studies on
floating riverine litter behaviour once items arrive in open waters are
still scarce. Based on HF radar current observations and a wind dataset, this
contribution tries to fill this gap by providing insights into how low- and
high-buoyancy litter released by several rivers of the SE Bay of Biscay may
affect the nearby regions seasonally in terms of concentration and beaching.
Analysis of riverine litter samples collected by a barrier placed in the
study area showed that low-buoyancy objects were predominant, although highly
buoyant objects were also relevant in terms of weight. Simulations for
assessing the seasonal trends of floating riverine litter transport and fate
were performed with the Lagrangian model TESEO. To properly integrate the
differences in litter buoyancy, simulations were parameterized with a wind
drag coefficient for low- and high-buoyancy items. The wind drag for highly
buoyant items was estimated by comparing the observed and the modelled
positions of four drifters. The developed low-cost buoys proved to be
suitable to provide real-time trajectories of highly buoyant objects exposed
to wind. However, drifters with different characteristics should be used in
future studies to account for the windage effect on different types of items.
The transport and fate of both high- and low-buoyancy items released by
rivers was calculated by season. Highly buoyant items rapidly beached (in
less than 48 h), particularly in summer and winter; in contrast, despite
the season over two-thirds of low-buoyancy items remained floating after 1 week of being released. This highlights the discrepancy between the behaviour
for low- and high-buoyancy objects and the importance of parameterizing the
windage effect in order to accurately predict riverine litter accumulation
in the coastal area of the SE Bay of Biscay. Beached particles were mainly
found in Gipuzkoa regardless of the season and the wind drag coefficient.
Overall, the less affected region was Bizkaia with the exception of a spring
period for low-buoyancy items. Despite the season, most of the riverine
litter remained in the study area and rivers polluted the regions within the
river basin or surrounding it. Investigating what beaches are most likely to
accumulate large quantities and the contribution per river can provide
relevant input to response operations after storm events in the short to
medium term and can also support the identification of priority rivers for
a monitoring programme, assisting adapted intervention of
riverine pollution regionally in the future.
Floating barrier for riverine litter collection
Floating barrier (a) and installation in the Deba River (Gipuzkoa) (b).
Riverine litter classification based on the exposure to the wind
effect
Data were gathered from surveys carried out during spring 2018 in
the Deba River (Gipuzkoa).
TSG_MLGeneral nameNumber of itemsWeight (kg)General codeWeakly buoyant items transported by currents G1Four- or six-pack yokes, six-pack rings13.3G2Bags7170.7G3Shopping bags incl. pieces8292.44G4Small plastic bags, e.g. freezer bags450.9G5What remains from rip-off plastic bags21186.31G20–G24Plastic caps and lids/plastic rings38216.39G26Cigarette lighters19.7G27Cigarette butts and filters10.1G30Crisps packets/sweet wrappers56250.2G31Lolly sticks12.4G32Toys and party poppers297.5G36Fertilizers/animal feed bags111.5G48Synthetic rope26.7G76Plastic/polystyrene pieces 2.5 cm >< 50 cm11221788.32G77Plastic/polystyrene >50 cm13337.34G96Sanitary towels/panty liners/backing strips351099.8G100Medical/pharmaceutical containers/tubes769.4G101Dog faeces bags2106G124Other plastic/polystyrene items (identifiable)581958.5G125Balloons and balloon sticks51.1G134Other rubber pieces11.6G135Clothing (clothes, shoes)3481.7G145Other textiles (incl. rags)7320.5G148Cardboard (boxes and fragments)385.7G156–G157Paper and paper fragments2121.2G158Other paper items469.1G159Corks421.2G173Other (specify)2199.3G177Foil wrappers, aluminium foil17G179Bottle caps, lids, and pull tabs10Total91.12 %67.95 %Highly buoyant items transported by wind and currents G7Drink bottles <=0.5 L5142.6G8Drink bottles >0.5 L391.1G9Cleaner bottles and containers2105.7G10Food containers incl. fast-food containers98723.9G11–G12Cosmetics bottles and other containers (shampoo, shower gel, deodorant)4100.3G17Injection gun containers118.3G33Cups and cup lids632.6G150–G151Cartons/Tetra Pak2121.2G153Cups, food trays, food wrappers, drink containers469.1G174Aerosol/spray can industry2143.2G175–G176Bottle caps, lids, and pull tabs25G177Bottles incl. pieces51832.3G178Light bulbs131.7Total8.88 %32.05 %Selected seasonal week-long periods from the HF radar
(2009–2021)
Periods selected between 2009 and 2021 based on the availability
surface current datasets provided by the HF radar.
Winter Period 1Period 2Period 3Period 4Period 5Period 6Period 7Period 8Period 9Period 10Initial date7 Feb 2013 08:009 Mar 2021 22:0023 Jan 2009 01:002 Jan 2013 11:0018 Jan 2016 17:002 Jan 2014 15:0017 Feb 2017 06:0017 Jan 2012 09:0022 Jan 2017 17:0012 Jan 2021 23:00Final date14 Feb 2013 07:0016 Mar 2021 21:0030 Jan 2009 00:009 Jan 2013 10:0025 Jan 2016 16:009 Jan 2014 14:0024 Feb 2017 05:0024 Jan 2012 08:0029 Jan 2017 16:0019 Jan 2021 22:00Spring Period 1Period 2Period 3Period 4Period 5Period 6Period 7Period 8Period 9Period 10Initial date14 Apr 2015 23:0016 May 2012 00:0016 Apr 2017 14:0021 Apr 2012 08:005 Jun 2014 06:0011 Apr 2021 20:006 May 2012 06:0010 Apr 2015 08:008 May 2018 22:0022 Apr 2016 11:00Final date21 Apr 2015 22:0022 May 2012 23:0023 Apr 2017 13:0028 Apr 2012 07:0012 Jun 2014 05:0018 Apr 2021 19:0013 May 2012 05:0017 Apr 2015 07:0015 May 2018 21:0029 Apr 2016 10:00Summer Period 1Period 2Period 3Period 4Period 5Period 6Period 7Period 8Period 9Period 10Initial date19 Aug 2017 01:004 Jul 2015 16:0015 Aug 2016 18:008 Aug 2012 11:0014 Aug 2015 00:008 Sep 2013 23:0011 Sep 2017 11:0013 Sep 2015 02:008 Jul 2019 04:005 Aug 2014 20:00Final date26 Aug 2017 00:0011 Jul 2015 15:0022 Aug 2016 17:0015 Aug 2012 10:0020 Aug 2015 23:0015 Sep 2013 22:0018 Sep 2017 10:0020 Sep 2015 01:0015 Jul 2019 03:0012 Aug 2014 19:00Autumn Period 1Period 2Period 3Period 4Period 5Period 6Period 7Period 8Period 9Period 10Initial date16 Oct 2014 22:0017 Oct 2011 08:0024 Oct 2015 11:008 Nov 2011 17:0010 Dec 2020 10:006 Nov 2015 01:0023 Nov 2015 21:004 Oct 2017 23:004 Oct 2015 20:0023 Nov 2020 04:00Final date23 Oct 2014 21:0024 Oct 2011 07:0031 Oct 2015 10:0015 Nov 2011 16:0017 Dec 2020 09:0013 Nov 2015 00:0030 Nov 2015 20:0011 Oct 2017 22:0011 Oct 2015 19:0030 Nov 2020 03:00Seasonal mean current and wind fields (2009–2021)
Mean current (a) and wind fields (b) in the study area during each season for the selected periods between 2009 and 2021. The colour bars represent the magnitude of current and wind speed. The arrows indicate the current and wind mean direction and are scaled with currents and wind speed (data sources: HF radar – EuskOOS, https://www.euskoos.eus/en/data/basque-ocean-meteorological-network/high-frequency-coastal-radars/; ERA5, https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5, last access: 11 November 2019).
Code and data availability
Code and data used to conduct this study are available upon request by contacting the corresponding authors.
Video supplement
Animations of the surface currents, winds, and Lagrangian simulations area
available for the study period 2009–2021 (10.5446/s_1355, Ruiz et al., 2022b).
Author contributions
IR performed the investigation, the data analysis, and the visualization assets and wrote the original paper. AJA contributed to the conceptualization of the investigation, provided the software, and reviewed and edited the paper. OCB and AR contributed to the conceptualization of the investigation and supervised, reviewed, and edited the paper. All authors contributed to refining the paper for submission.
Competing interests
The contact author has declared that none of the authors has any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We are grateful to the Emergencies and Meteorology Directorate – Security
department – Basque Government for public data provision from the Basque
Operational Oceanography System EuskOOS. This study
has been conducted using EU Copernicus Marine Service information. We thank
Luis Ferrer for sharing his valuable knowledge on the custom-built drifters.
We thank Cristina Barreau, Antoine Bruge, Igor Granado, Théo Destang,
Alix McDaid, and Jon Andonegi for their support with the release of the drifters. We thank the citizens who collected and reported the drifters' arrival at the Basque and French coasts. This paper is contribution no. 1134 from
AZTI, Marine Research, Basque Research and Technology Alliance (BRTA). This paper is part of the PhD research of Irene Ruiz, supervised by Oihane C. Basurko
and Anna Rubio.
Financial support
This research has been partially funded through the EU's LIFE Program (LIFE
LEMA project, grant agreement no. LIFE15 ENV/ES/000252) and by the EU's H2020 Program (JERICO-S3 project, grant
agreement no. 871153).
Review statement
This paper was edited by Erik van Sebille and reviewed by two anonymous referees.
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