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Coastal accumulation of microplastic particles emitted from the Po River, Northern Italy: Comparing remote sensing and hydrodynamic modelling with in situ sample collections


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Microplastic research has mainly concentrated on open seas, while riverine plumes remain largely unexplored despite their hypothesized importance as a microplastic source to coastal waters. This work aimed to model coastal accumulation of microplastic particles (1–5 mm) emitted by the Po River over 1.5 years. We posit that river-induced microplastic accumulation on adjacent coasts can be predicted using (1) hydrodynamic-based and (2) remote sensing-based modelling. Model accumulation maps were validated against sampling at nine beaches, with sediment microplastic concentrations up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed that discharged particle amount is only semi-coupled to beaching rates, which are strongly mouth dependent and occur within the first ten days. Remote sensing modelling was found to better capture river mouth relative strength, and accumulation patterns were found consistent with hydrodynamic modelling. This methodology lays groundwork for developing an operational monitoring system to assess microplastic pollution emitted by a major river.
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Marine Pollution Bulletin
journal homepage:
Coastal accumulation of microplastic particles emitted from the Po River,
Northern Italy: Comparing remote sensing and hydrodynamic modelling
with in situ sample collections
Elizabeth C. Atwood
, Francesco M. Falcieri
, Sarah Piehl
, Mathias Bochow
Michael Matthies
, Jonas Franke
, Sandro Carniel
, Mauro Sclavo
, Christian Laforsch
Florian Siegert
RSS Remote Sensing Solutions GmbH, Isarstr. 3, 82065 Baierbrunn, Germany
Ludwig-Maximilians-Universität Munich, GeoBio-Center, Großhadernerstr. 2, 82152 Martinsried, Planegg, Germany
Consiglio Nazionale delle Ricerche – Istituto di Scienze Marine (CNR-ISMAR), Arsenale-Tesa 104, Castello 2737/F, 30122 Venezia, Italy
University Bayreuth, Dept. Animal Ecology I, Universitätsstr. 30, 95440 Bayreuth, Germany
Helmholtz Centre Potsdam - GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
University of Osnabrück, Institute of Environmental Systems Research, Barbarastr. 12, 49069 Osnabrück, Germany
Beach sediment
River plume
Microplastic research has mainly concentrated on open seas, while riverine plumes remain largely unexplored
despite their hypothesized importance as a microplastic source to coastal waters. This work aimed to model
coastal accumulation of microplastic particles (1–5 mm) emitted by the Po River over 1.5 years. We posit that
river-induced microplastic accumulation on adjacent coasts can be predicted using (1) hydrodynamic-based and
(2) remote sensing-based modelling. Model accumulation maps were validated against sampling at nine beaches,
with sediment microplastic concentrations up to 78 particles/kg (dry weight). Hydrodynamic modelling revealed
that discharged particle amount is only semi-coupled to beaching rates, which are strongly mouth dependent and
occur within the first ten days. Remote sensing modelling was found to better capture river mouth relative
strength, and accumulation patterns were found consistent with hydrodynamic modelling. This methodology
lays groundwork for developing an operational monitoring system to assess microplastic pollution emitted by a
major river.
1. Introduction
Marine plastic litter has long been recognized as an environmental
problem (Azzarello and van Vleet, 1987;Law and Thompson, 2014;
Sheavly and Register, 2007) but only recently has begun to receive
international attention at a level adequate to the potential severity of
the threat (G7 Germany, 2015;GESAMP, 2016;UNEP, 2016). Micro-
plastics, commonly defined as particles < 5 mm in diameter (Galgani
et al., 2013), are increasingly proving to be ubiquitous in all water
systems. Roughly 70 to 80% of marine debris comes primarily from
land-based sources (Wagner et al., 2014), much being passively col-
lected in waterways which eventually flow to the sea. Mani et al. (2015)
found river water concentrations up to 3.9 million particles/km
metropolitan areas along the Rhine River. Annual input of plastic par-
ticles to the Great Laurentian Lakes is estimated at 9.8 thousand tonnes
(Hoffman and Hittinger, 2017). Despite the fact that freshwater systems
are at least as severely contaminated as the oceans (Dris et al., 2015),
large rivers have to date received relatively little attention (Mani et al.,
2015;Wagner et al., 2014). An estimated 1.15 and 2.41 million tonnes
enter the oceans each year from rivers alone (Lebreton et al., 2017),
representing up to 50% of land based plastic emissions estimate, which
ranges from 4.8 to 12.7 million tonnes (Jambeck et al., 2015). Once
microplastics reach coastal waters, their dispersion and transportation
pathways are governed by ocean and atmosphere dynamics; our un-
derstanding of these physical processes is still limited. Some authors
suggest that how these processes influence microplastic transport may,
to some extent, be comparable to well-studied suspended sediment
transportation systems (Zhang, 2017), which could offer a more es-
tablished framework for modelling suspended microplastic transporta-
Received 24 July 2018; Received in revised form 21 September 2018; Accepted 19 November 2018
Corresponding author at: RSS Remote Sensing Solutions GmbH, Isarstr. 3, 82065 Baierbrunn, Germany.
E-mail address: (E.C. Atwood).
Marine Pollution Bulletin 138 (2019) 561–574
0025-326X/ © 2018 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
Microplastic transportation pathways are characterized by complex
dynamics due to processes such as movement mechanisms (windage
and sinking velocities) as well as changes in physical and chemical
characteristics (loss of structural integrity, fragmentation and ag-
gregation, see review Andrady, 2017) as well as interactions with biota
(Law and Thompson, 2014). A combined hydrodynamic-Lagrangian
transportation model effort would therefore be surely dependent upon
necessary simplifying assumptions, as well as the quality of the hy-
drodynamic forcing data. Such models, with different degrees of rea-
lism, have been recently utilized to hindcast potential sources of
stranded plastic litter in the Indian Ocean (Bouwman et al., 2016;
Duhec et al., 2015), Aegean Sea (Politikos et al., 2017) and Adriatic Sea
(Carlson et al., 2017). To date, little attention has been placed on local-
scale river plume microplastic transport modelling in coastal seas
(Browne et al., 2010;Carlson et al., 2017;Zhang, 2017). It is important
to bear in mind that, due to the intrinsic model simplifications, dis-
persion pathways computed based on modelling results can accumulate
errors over longer distances and times. Generally, modelling results
should be considered qualitative rather than quantitative until vali-
dated against an independent dataset. A different type of model based
on remote sensing acquisitions offers multiple depictions of the river
plume that inherently include actual environmental conditions. While
such an image displays the complex coastal ocean environment of the
surface layer, it nevertheless offers restricted information for below the
water surface and only represents the snapshot time period when the
image was acquired.
In this paper, we implement and compare these two different types
of models to assess how microplastics from a major river are spreading
into a semi-enclosed sea and accumulate along its coastline. The ob-
jective is to create a coastal microplastic exposure map, which depicts
accumulation of particles emitted from the Po River along the outer
delta and covering southward the coastal area still under strong influ-
ence from the main Po River plume. Model (1) is a Lagrangian particle
transportation model forced by a state-of-the-art hydrodynamic model,
while model (2) is based on satellite remote sensing of river plume form
and intensity along the coastline. We hypothesize that both models are
able to capture coastal patterns in river plume emitted microplastic
accumulation. Model results are validated against sediment sampling
for microplastics from beaches with varying river plume exposure
gradients. Development of a system to model coastal accumulation of
microplastic debris from rivers would represent a very useful tool for
agencies responsible for monitoring and reporting this pollution, as well
as organization of clean-up activities and remediation strategies.
2. Materials and methods
2.1. Study area
The Adriatic Sea separates the Italian peninsula and Balkan coast,
extending 800 km from the connection with the Ionian Sea over the
Strait of Otranto northwest toward the Venice Lagoon (Fig. 1). The
prevailing currents flow counterclockwise from the Strait of Otranto
along the Balkan coastline and return southward with the Western
Adriatic Current (WAC) along the Italian coastline (Artegiani et al.,
1997a, 1997b;Carniel et al., 2016). The North Adriatic sub-basin is
defined as the shallow area north of the 100 m isobath (Fig. 1).
The Po River provides the largest riverine influx to the Adriatic Sea,
averaging daily 1500 m
/s with streamflow ranging between 100 m
and 11,550 m
/s (Falcieri et al., 2014). Being the longest river in Italy,
the Po River drainage area (74,000 km
) encompasses much of the
northern region of the country, with > 20 million inhabitants, and in-
cludes many large cities as well as areas of intensive industrial and
agricultural activities (lower left inset Fig. 1). The river splits into many
sub-rivers before flowing into the Adriatic Sea, the main recognized
arms of which are the Po di Maistra, della Pila, delle Tolle, di Gnocca
(or della Donzella) and di Goro (upper right inset Fig. 1). Additionally,
there exist many side channels and lagoons, which also carry a portion
of the river water to the sea. Notable among these side channels are the
Busa di Scirocco and di Tramontana. The delta is an actively changing
system with shifting sandbars that can obstruct outflow from a parti-
cular mouth (Simeoni and Corbau, 2009) and thus increase the outflow
elsewhere. The highest river discharge occurs in the spring, associated
with high precipitation and snow-melt runoff, and the lowest in autumn
(Falcieri et al., 2014).
Both wind regime and freshwater influx play a deciding role in
North Adriatic circulation patterns (Bignami et al., 2007;Bolaños et al.,
2014;Falcieri et al., 2014). There are three main recognized wind re-
gimes: Bora, Scirocco and Mistral. Bora events consist of strong, dry,
northeasterly winds that tend to occur more often during the winter
months, which together with low river discharge results in a small Po
River plume that remains close to the coastline (Boldrin et al., 2009;
Falcieri et al., 2014). As mentioned above, a Scirocco event comprises
warm, humid, east-southeasterly winds that tend to occur more often
during the spring to fall. This wind regime together with high river
discharge results in a wider plume that can extend far across the
Adriatic Basin. Mistral events are the least powerful of the wind regimes
and are defined based on winds coming from the northwest, which have
been found to minorly enhance WAC flow into the Ionian Sea (Bignami
et al., 2007).
2.2. Sample design
The Po Delta field campaign was conducted from 4 to 25 June 2016,
during which both water and sediment samples were taken. Water
sample locations were selected to cover the main Po River, recognized
river mouths and important subsidiary river mouths as well as the
plume, ranging from near-coast waters to the plume outer edge (in-
dicated by surface waters with salinity > 30 PSU). At each station,
water samples used to estimate microplastic concentrations were col-
lected from a small boat using a specially designed mini-manta trawl
(300 μm mesh, further details available in S1 of the Supplementary
material). A total of 24 water stations were sampled, the locations of
which are indicated in Fig. 2 of the Results. The trawl net was rinsed
before each sample collection by running the net without the cod end
through the water for 5 min at the sampling location. One trawl pass per
location was conducted alongside the boat for an average of 20 min and
only when wind conditions were below Beaufort 2 (light breeze,
6–11 km/h). Samples were stored in glass jars until further processing
in the lab. During trawling, in situ measurements were collected for sea
surface temperature (°C) and salinity (PSU). Water clarity measure-
ments (visibility depth with a Hydrobios secchi disk) were conducted
both before and after each trawl. Additionally, 2 L water samples were
concurrently collected from the water surface (top 40 cm) for later
determination of the water parameters chlorophyll-A(Chl-A) and sus-
pended particulate matter (SPM). Water samples were also processed
for measurement of colored dissolved organic matter (CDOM, or
Gelbstoff), but due to very low detected CDOM levels, these data were
determined not useful for building a regionally calibrated remote sen-
sing algorithm. Samples were kept dark while being stored in a cooler
with ice until filtering later that the same day.
Chl-Asamples were hand-pump filtered using Whatman GF/F glass
microfiber filters (0.7 μm pore size), following the IOC and SCOR
(1994) protocol. Filters were then wrapped in aluminum and stored at
−20 °C for the duration of the field campaign, after which they were
stored at −80 °C until further processing. Chl-Awas extracted with
96% ethanol and analyzed with a JASCO FP-8600 fluorometer at an
excitation wavelength of 435 nm and an emission wavelength of
670 nm. The fluorometer was calibrated using a photometer (JASCO V-
670) and a Chl-Astandard (C6144-1MG, Sigma-Aldrich). After the first
measurements, samples were acidified with HCl and again measured to
subtract phaeopigments from the chlorophylls to get concentration of
Chl-Ain mg/L following the JGOFS protocol (UNESCO, 1994).
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
SPM samples were hand-pump filtered using pre-weighed cellulose
acetate filters with 0.45 μm pore size, air dried and stored in aluminum
foil (Lindell et al., 1999). Filters were further dried in a 60–80 °C oven
for 2 h and allowed to cool in a desiccator before weighting on a Sar-
torius R 200 D.
Surface reflectance measurements concurrent to each trawl were
taken following the measurement methodology from Mobley (1999)
and Fargion and Mueller (2000). An ASD FieldSpec 3 Hi-Res spectro-
meter was fitted with an 8° optic lens and set to measure raw digital
numbers over an averaging of 50 rapid measurements. For each sam-
pling location, a minimum of five measurement cycles were taken with
the goal to collect as many cycles as possible during trawling. Each
cycle consisted of a downwelling irradiance measurement over a white
reference (nadir angle), an upwelling plus a sky radiance measurement
both made following Mobley geometry (135° azimuth angle from sun,
40° off nadir for water and 40° off zenith for sky; Mobley, 1999), and
lastly a repeated downwelling irradiance measurement to control for
potential changes in lighting intensity conditions over the measurement
cycle. All spectral measurement angles were estimated by hand and
controlled by a second observer with a preset adjustable triangle.
Measurement integration times were optimized for each measurement
cycle in order to maximize signal. Downwelling irradiance was mea-
sured over a 90% Spectralon®white reference panel. Processing of raw
digital numbers into remote sensing reflectance is discussed further in
Section 2.5.
Sediment samples were collected from nine beaches in order to serve
as a validation dataset for the hydrodynamic and remote sensing models
(sample locations are indicated in the Results). Beach sample locations
were selected so that three each of low, medium and high river plume
impact areas would be represented. Estimates of river impact were based
on the hydrodynamic modelling accumulation map (more details below
in Section 2.4). At each location, samples were taken along the extreme
high tide line, following protocols from Moreira et al. (2016) and Turra
et al. (2014), and were only conducted between high tide cycles. The
extreme tide line was defined visually as the area with the largest ac-
cumulation of drift material, which was found to always be a clearly
separate line to the last high tide line. Samples were taken at equal in-
tervals along a 100 m transect line, where the first 10 m were walked
along the straight transect line and then turned at 90° for placement
along the meandering drift line. Samples were taken with a 25 × 25cm
stainless steel quadrat and sampled to a depth of 5 cm. Wet weight of the
samples were recorded and then sieved over 1 mm stainless steel mesh
(matching model assumptions from the hydrodynamic model, more de-
tails below). Additionally, two 1 L bottles where filled with unsieved
sand from the same transect line for later processing in the lab to convert
the wet weight to dry weight.
Fig. 1. Adriatic Sea overview map, showing bathymetry (contour lines follow 50 m depth intervals) along with large coastal cities and bordering countries: AL -
Albania, ME - Montenegro, BIH - Bosnia and Herzegovina, HR - Croatia, SI - Slovenia, IT - Italy. Lower left inset shows Po River watershed (yellow dashed line) with
large inland cities, as well as the Brenta (dark green line) and Adige (light green line) rivers. The Po Delta is displayed in the upper right inset, showing all five major
river mouths (Maistra, Pila, Tolle, Gnocca and Goro) as well as important side channels (Tramontana and Scirocco) and dense aquaculture areas. (For interpretation
of the references to color in this figure legend, the reader is referred to the web version of this article.)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
2.3. Microplastic sample processing
Water samples were first fractionated into two size classes:
5 mm–500 μm and 500–300 μm. To remove organic matter (which
would disturb spectroscopic analysis) from the microplastic water
samples, samples of the size class 500–300 μm were treated with en-
zymatic purification (Löder et al., 2017) and wet peroxide oxidation
(Masura et al., 2015). For the latter class (size 5 mm–500 μm), samples
with high organic content were treated solely with wet peroxide oxi-
dation. All potential microplastic particles > 500μm were visually pre-
sorted, photographed and stored for further analysis with Attenuated
Total Reflectance (ATR) Fourier Transform Infrared (FT-IR) spectro-
scopy. For a full quantitative analysis of the fraction < 500 μm, samples
were split. One subsample was filtered onto aluminum oxide mem-
branes (Whatman Anodisc filters) and analyzed with Focal Plane Array
(FPA) based Micro-FT-IR spectroscopy. The rest of the subsamples were
filtered onto glass fiber filters (grade MN 85/90 BF) and analyzed with
a newly developed shortwave infrared (SWIR) close-range imaging
spectroscopy methodology called PlaMAPP (Schmidt et al., 2018) using
a HySpex SWIR-320 m-e sensor (Norsk Elektro Optikk AS). This method
allows counting microplastic particles, classifying the plastic type and
determining particle size in a semi-automated way. Determination of
plastic type is done by comparing the wavelength positions of the
spectral absorption bands (local minima in the spectral signatures) of
the recorded image spectra to those of plastic spectra from a reference
spectral library.
Sediment samples along the 100 m transect were pooled, then pro-
cessed by drying at 55 °C and separated from inorganic material using a
zinc chloride solution (density 1.6–1.8 g/cm
). The supernatant, which
included both organic material and potential polymer particles, was
collected using a self-made mote spoon (stainless steel, mesh size < 1
mm), rinsed with 98% ethanol and transferred into glass petri dishes.
All potential microplastic particles were visually separated from or-
ganic material under a stereomicroscope (Leica M50 with cold light
source Leica KL 300 LED, Leica Microsystems), photographed (attached
Olympus DP26 camera, 5 Megapixel, Olympus Corp.) and identified to
polymer type using ATR FT-IR spectroscopy.
Spectra of all potential microplastic particles > 500 μm, from both
water and sediment samples, were recorded with a Tensor 27 FT-IR
spectrometer (Bruker Optik GmbH) from 8 co-added scans within a
spectral range from 4000 to 400 cm
and a spectral resolution of
8 cm
. Background scans were performed after every 10th measure-
ment. Spectra were identified using the OPUS v7.5 software, correlating
measured spectra against reference spectra from a custom in-house li-
brary (containing polymer spectra as well as spectra from both natural
and lab materials used during sampling and processing, see Löder et al.,
2015). Spectra of all potential microplastic particles < 500 μm were
collected using the Tensor 27 FT-IR spectrometer further equipped with
Fig. 2. Overview of water microplastic samples (diamonds, blue scale) and sediment microplastic samples (circles, pink scale) collected during the June 2016 field
campaign. A total of 24 water locations and 9 beach locations were sampled, only beach locations are labeled (black text). Water samples are reported as particles/m
while sediment samples are reported as particles per dry weight kg (DW kg). River mouths are labeled in dark blue and dense aquaculture areas within lagoons are
indicated. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
a Hyperion 3000 FT-IR microscope that had a 15× cassegrain objective
and a 64 × 64 FPA detector mounted. Spectra were obtained in trans-
mission mode and measurement settings were as published by Löder
and Gerdts (2015). Obtained chemical images were analyzed with the
ImageLab v2.26 software and the BayreuthParticleFinder tool (devel-
oped during the project together with Epina Software Lab GmbH),
which automatically highlights potential polymer particles on the
chemical image obtained from the FT-IR measurements of the filter.
Given that polymer spectra can diverge, dependent on factors such as
particle size, thickness, color, polymer additives or adsorbed chemicals,
all automatically detected particles were further manually controlled
2.4. Hydrodynamic model
Simulations for microplastic dispersal from the Po River were per-
formed from 1 January 2015 to 15 June 2016, to coincide with the field
sampling campaign. A 3D Individual Based Lagrangian tracking model
(ICHTHYOP; Lett et al., 2008) was implemented to simulate the dis-
persion of virtual microplastic particles (VMP) due to 3D currents and
water column thermohaline structure. In the model, VMP behave as a
Lagrangian drifter under the effect of horizontal/vertical advection and
dispersion as well as buoyancy force due to the difference between the
particle and surrounding water density. Particles were assigned a
spherical shape (diameter of 1 mm) and density of 0.91 g/mL. Density
was chosen to correspond with the averaged density of virgin poly-
ethylene (both high and low density) and polypropylene, which to-
gether account for over 48% of EU demand (PlasticsEurope, 2014) and
represent the majority of sampled microplastic debris (Imhof et al.,
2013;Zbyszewski and Corcoran, 2011). Horizontal dispersion was in-
cluded with a turbulent dissipation rate of є = 10
, in agree-
ment with turbulent kinetic energy observations in the Adriatic Sea.
VMP were tracked for a total of 60 days, in excess of Adriatic particle
half-life model estimates (Liubartseva et al., 2016) and drifter mean
half-life observations (Poulain, 2001) of circa 40 days.
Simulations were based on the simplifying assumption of a constant
concentration of 10 microplastic particles/m
in river waters, as re-
ported in previous observations from the Po River (van der Wal et al.,
2015;Vianello et al., 2015). Given that the river is represented as a
point source inside the hydrodynamical model, VMP were released at
the surface along straight 500 m transects located 250 m in front of each
river mouth, with the goal being to mimic a direct discharge from the
river itself. Po River mouths included Maistra, Pila, Tolle, Gnocca and
Goro plus the Busa di Scirocco (given its presence in the hydrodynamic
model). VMP were released over the entire simulation period at hourly
intervals from all six locations, and the total number of VMP released at
each mouth was determined based on the water discharge distribution
among the main branches of the Po River.
Once released, a VMP was considered beached if it passed closer
than 250 m from the coastline. This fixed distance was set based on the
model spatial resolution (half the horizontal grid size) and in con-
sideration that the model has difficulty representing complex nearshore
processes. VMP were tagged with release date and river mouth, so that
relative contribution from each river mouth could later be assessed.
Once identified as beached, the VMP was removed from the dataset.
VMP resuspension after beaching was not accounted for in the model,
given the still existing amount of uncertainty surrounding this process
(Hardesty et al., 2017;Zhang et al., 2017). This approach could lead to
a small overestimation of beaching rates, but it was decided that a
simplifying approach was preferable to setting an arbitrary factor
meant to represent resuspension and similar nearshore processes.
ICHTHYOP simulations were run offline using as physical forcing an
elaboration of the UNIVPM-Regione Marche operational hydrodynamic
model that covers the northern Adriatic Sea (horizontal resolution of
500 m; 12 vertical sigma layers). The model (ROMS, Regional Ocean
Modelling System; Haidvogel et al., 2008; was
implemented in a coupled version with a surface wave model (SWAN,
Simulating WAves Nearshore model; Booij et al., 1999;http://swan. through the COAWST (Coupled-Ocean-Atmosphere-Wave-
Sediment Transport Modelling System; Warner et al., 2010;Warner
et al., 2008). Surface forcings were derived from COSMO-I7, a local
implementation of the Lokal Model (Steppeler et al., 2003) developed
in the framework of the COSMO Consortium (
and run by the Agenzia Regionale per la Prevenzione, l'Ambiente e
l'Energia dell'Emilia Romagna - Servizio Idro-Meteo-Clima (ARPA ER-
SIMC). The UNIVPM-Regione Marche model implementation was
chosen because it was the only freely available and operationally run-
ning forecast model with a high horizontal resolution for the Adriatic
A coastal reference grid was developed for displaying the distribu-
tion of beached particles along the Po Delta shore. To avoid artificial
“shadowing” effects from corners of the hydrodynamic model grid cells
located along the coastline, a smoothed grid was established based
rather on the coastline. This grid was created with ArcGIS v9.31 soft-
ware by projecting the coastline 250 m offshore, separating this into
500 m segments and buffering each segment with 250 m, producing
grid cells variable in both shape and surface but without sharp angles or
abrupt changes in direction. After post processing, distribution maps of
estimated accumulation could be defined for each day up to the entire
simulation period. Beach sediment sampling transect locations were
placed as close as possible to the middle of the modelled accumulation
2.5. Near-range spectral measurements and remote sensing model
The remote sensing model for quantifying coastal exposure to riv-
erine-based microplastic particles was based on the assumption that
suspended microplastic particles are transported by the same mechan-
isms as other passive, suspended water constituents for which well-es-
tablished remote sensing methodologies exist. With the goal being to
optimally capture river plume water reflectance characteristics, near-
range spectral measurements were used to build regionally calibrated
remote sensing spectral reflectance water parameter algorithms for
different satellite platforms.
First, raw digital number measurements from the spectroradiometer
of downwelling irradiance plus upwelling and sky radiance were con-
verted to irradiance, E(z, λ) in units of W/(m
nm), and radiance, L
(z,θ,φ,λ) in units of W/(m
sr nm), using the software package RS
version 6.4.0 from ASD Inc. Radiance measurements were visually
checked for abnormal behavior (such as saturation or detector jumps)
before being converted to remote sensing reflectance (R
) following
the methodology described by Heim (2005):
+ =
RL r xL
Esr(0 , ) (0 , ) ( )
(0 , ) [ ]
total wa sky
where R
(0+,λ) is the remote sensing reflectance directly above the
water surface (0+) for a given wavelength (λ), L
is the above water
(upwelling) radiance measurement, r
is the proportion of directly
back-reflected skylight at the air-water interface (taken here to be
0.021, following Heim, 2005), L
the sky radiance, and E
downwelling irradiance measurement.
dataset from the field campaign together with the in
situ SPM measurements were used to calibrate various candidate algo-
rithms to the Po River region and for a given satellite sensor, the best of
which was then selected as the optimal regionally calibrated empirical
algorithm for the time series analysis. Four separate algorithms for
spectral detection of SPM were considered: (i) Jørgensen (1999) based
on the CZCS band 3 detecting in the range 540–560 nm, (ii) Dekker
(1993) based on in situ spectrometer measurements at 706 nm, and two
different SPOT-3 ratio-based algorithms from Doxaran et al. (2002)
based on (iii) band 3 (780–890 nm) divided by band 1 (500–590 nm)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
and (iv) band 3 divided by band 2 (610–680 nm). All calibrated models
were assessed for quality via Root Mean Square Error (RMSE) as well as
goodness of fit statistics following the methods of the Ocean Color
Group (Campbell and O'Reilly, 2005). This allowed determination of
the best-calibrated SPM algorithm for Po River water with a particular
satellite. Both the “Baseline” and “Calibrated” fits were also assessed for
data overfitting using a leave-one-out cross-validation (LOOCV) tech-
nique (Michaelsen, 1987). Further details regarding the calibration and
validation process are available in S2 of the Supplementary material.
Landsat 8 (L8), a joint mission of the U.S. Geological Survey (USGS)
and National Aeronautics and Space Administration (NASA), is
equipped with two push-broom sensors, the Operational Land Imager
(OLI) and the Thermal Infrared Sensor (TIRS), which provide multi-
spectral images with 30 m spatial resolution. The Po Delta study area is
located in the overlap region between two Landsat flight paths, thus
reducing the revisit time for this particular study to 7 days. The
European Space Agency (ESA) Sentinel-2 (S-2) mission is a constellation
of two identical satellites that are equipped with a push-broom
MultiSpectral Instrument (MSI) sensor. S-2 provides multispectral
images with 10, 20 and 60 m spatial resolution depending on the
spectral band. S-2 has a revisit time of up to 2–3 days at midlatitudes.
Usable images from L8 and S-2 acquired between 1 January 2015 and
30 June 2016 were compiled. Other platforms with coarser image
spatial resolution (≥300 m) but proving daily (MODIS) to 2-day
(Sentinel-3) acquisitions with much greater Signal-to-Noise Ratio (SNR)
were considered but not implemented given that our goal was to cap-
ture the fine river plume structure as close to the coastline as possible.
Different atmospheric correction algorithms were tested to mini-
mize the introduction of artifacts to the bands needed for detection of
various water parameters, which was accomplished through compar-
ison with concurrent in situ R
spectrometer measurements (further
details in S3 and S4 of the Supplementary material).
The L8 and S-2 acquisitions were processed with a hierarchical
object-based image analysis (OBIA) developed with eCognition soft-
ware (Trimble Navigation Ltd.) to remove land, cloud, boats, white caps
and breaking waves. The masked images were then used to create SPM
concentration maps, which showed how the river plume was spreading
into the surface coastal waters over the examined time period.
For each acquisition date, non-coastline pixels were masked and the
remaining utilized as the basis for creating the coastline riverine mi-
croplastic exposure map. This was accomplished by converting pixel
values to a similarity ratio using the average SPM concentration from
all five river mouths for that acquisition date. The goal was to display
how similar a given coastline pixel was to a pure river water pixel,
which was then used to indicate influence from river plume waters
along the coastline. Data were binned into hexagons to allow for
combination of images with differing footprints as well as spatial re-
solution, at diameters of both 30 m and 100 m. This was accomplished
using the “hexbin” package within the R software package (R Core
Team, 2016). The first diameter represents the minimum allowable
resolution and the second to match the sediment sampling scheme as
well as easier visualization of the entire Po Delta coastline. Gaps in the
dataset, produced through masking areas such as cloud cover or
breaking waves, were filled in the time series using a combination of
Nearest Neighbor Filtering and temporal linear interpolation. This was
done again in R using the packages “raster”, “rgdal”, “rgeos”, “sp” and
“spacetime”. SPM values between L8 and S-2 images were compared
using standardized differences to check for any inherent bias between
the different sensors. The time series was then summed to create a
composite image of river plume influence along the Po Delta coastline
for the entire modelled time period.
Po River gauge measurements were obtained for the modelling
period from ARPA ER, taken at Pontelagoscuro. Wind regime in front of
the Po Delta was estimated by extracting the zonal and meridional wind
components from the COSMO I7 dataset (forcing field used in the hy-
drodynamic model) for eight points located 20 km in front of the
coastline. For each point, the daily average magnitude and heading
were first computed, and then all eight points averaged to obtain a
single value representative of the whole area. Significant wind regime
events were identified as days with an average wind speed over 5 m/s
and consistently blowing from northeast (Bora), southeast (Scirocco) or
northwest (Mistral).
2.6. Validation of the modelled microplastic exposure maps
Modelled microplastic accumulation values from both the remote
sensing time series as well as the hydrodynamic particle tracking were
compared to in situ beach sediment microplastic concentrations to as-
sess model validity as well as identify weaknesses and strengths of each
modelling method. Comparisons were made using both Pearson's
Correlation r as well as Spearman's Rank Coefficient ρ. All calculations
were carried out using R software. Model maps were also compared to
one another by unit-base normalizing (also known as feature scaling)
each map and then comparing difference values at regular latitudinal
intervals along the coastline.
3. Results and discussion
3.1. Water parameter sampling
Water parameter field measurements are presented in Table 1. Chl-
Ameasurements fell within 0.005–0.043 mg/L, and SPM values covered
a moderate range as compared with ARPA ER monitoring measure-
ments of SPM from Pontelagoscuro (for the time period January 2015
to June 2016, these ranged from 12 to 372 mg/L). Secchi depth mea-
surements only reached a maximum of 163 cm, all located along the
outer edge of the river plume.
3.2. Microplastic sampling
Water microplastic samples analyzed by ATR FT-IR and SWIR
spectroscopy ranged from 1 to 84 particles/m
(Fig. 2), with the highest
concentrations being found along the outer river plume edge, within
the main arm of the river (Po della Pila) and the side channel Busa di
Tramontana. The Maistra and central Tolle river mouths both had very
low concentrations, < 6 particles/m
. Repeated measures from a par-
ticular river section, such as where Po delle Tolle separates from Pila or
where Tolle splits into three channels before entering the Adriatic, in-
dicated large variability from one sampling time to another.
Some of the highest in situ water microplastic measurements were
found along the outer edge of the Po River plume, which suggests that
either microplastic concentrations in the open Adriatic are at least
comparable with those from the river, or that there are local accumu-
lation processes occurring along the front between fresh river water and
much higher salinity ocean water. Given that rivers are considered one
of the main sources of plastic debris to the ocean (Jambeck et al., 2015;
Lebreton et al., 2017) together with evidence that the Adriatic Sea is a
highly dissipative system (Horvat, 2015), the latter hypothesis is more
likely. Furthermore, concentrations found in this study are an order of
magnitude higher than values measured by Suaria et al. (2016) in the
open Adriatic Sea. Using the median in situ measured microplastic
Table 1
Measured water parameters during the field campaign. Chlorophyll-A(Chl-A)
and suspended particulate matter (SPM) reported in mg/L, Secchi depth
average from before and after trawl in cm.
Chl-A(mg/L) SPM (mg/L) Secchi (cm)
Mean/Median 0.011/0.009 30.2/21.1 67/51
Standard deviation 0.008 29.4 36
Maximum 0.043 127.9 163
Minimum 0.005 7.7 29
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
concentration from this study together with average Po River discharge
(1500 m
/s) and estimates of microplastic particle count to weight in
the Adriatic (1.68 to 3.00 mg/particle; Suaria et al., 2016;van der Wal
et al., 2015;Vianello et al., 2015), a rough estimate of floating micro-
plastic released by the Po River ranges between 2.2 and 3.8 t per day.
This translates to between 785 and 1402 t/yr, coming close to the es-
timates of 1349 t/yr by Liubartseva et al. (2016), although it should be
noted the latter estimate is based on vertical water column integrated
estimates of all plastic debris (both macro and microplastics). Our es-
timate should be taken with care given that the microplastic sampling
method utilized in this study only sampled microplastics floating at the
water surface, which has been shown to often underestimate total
floating microplastic concentrations (Brunner et al., 2015;Kooi et al.,
The beach sediment microplastic samples (Fig. 2) ranged from 0 to
78 particles per dry weight (DW) kg. The highest measurement by far
was on the northernmost beach, Caleri, where a total of 3080 micro-
plastic particles were identified for the entire transect (Table 2). Poly-
styrene (PS), acrylonitrile butadiene styrene (ABS) and styrene acrylo-
nitrile (SAN) were found to have similar spectral signatures, thus were
pooled into a group called styrene-based polymers to avoid potential
confusion between these types. The same was true for the polymer types
ethylene vinyl alcohol (EVOH) and ethylene vinyl acetate (EVA).
Polyethylene (PE), polypropylene (PP) and the styrene polymer group
made up > 97% of all particles sampled on six beaches (Boccasette, Pila
North 1, Pila South, Allagamento, Barricata and Goro). Beach sediment
particles identified as belonging to the styrene polymer group were
most often found in their foamed form, which is not surprising con-
sidering that the non-foamed polystyrene is less dense than seawater.
The remaining three beaches had either an increased contribution from
EVOH/EVA or, in the case of Pila North 2, elevated contributions for
the polymer types polyamide (PA) and polyethylene terephthalate
The top three contributing polymer types from the beach sediment
microplastic concentrations were PE, styrene-based polymers and PP, in
step with general trends observed in both the Po River (van der Wal
et al., 2015) and the Mediterranean Sea (Suaria et al., 2016) as well as
coastal (Zhang, 2017) and global oceans (Andrady, 2017). PE and PP
make up between 45 and 50% of total global plastic production
(PlasticsEurope, 2016). Higher occurrence of other plastic types, espe-
cially the heavier polymers such as EVOH, PVAL, PET (polyethylene
terephthalate) and PVC (polyvinylchloride), were found at Caleri, Le-
vante and Pila North 2 (Fig. 2 and Table 2). Caleri in particular was
found to have the most extreme microplastic concentration, exceeding
the measurement by Munari et al. (2017) of 21 particles/DW kg at
Volano, just south of the Po Delta. It is important to note that a possible
explanation for this could be different sampling locations, as this study
sampled the extreme high tide line in contrast to the most recent high
tide line. Our measurements were lower than those made in the Venice
Lagoon (672–2175 particles/DW kg; Vianello et al., 2013), although it
should be noted that smaller size classes were under investigation in the
study by Vianello et al. and it is often the case that particle abundances
increase with decreasing size class (Imhof et al., 2018;Lee et al., 2013).
The two northernmost beaches surveyed in this study (Caleri and Le-
vante) were located close to either a public parking lot or a harbor.
Heavier particles are known to be transported more slowly than parti-
cles which are less dense than surrounding seawater (Cable et al.,
2017), which include the plastic types EVOH, PVAL, PET and PVC in
their virgin form. This suggests that the higher concentration rates more
likely result from local sources, rather than longer distance transpor-
tation by the Po River plume or other Adriatic currents.
3.3. Time series data and hydrodynamic model accumulation
River discharge and wind speed, overlain with wind regimes, are
shown in Fig. 3 together with total daily beached VMP and a pictorial
overview of satellite acquisition coverage (discussed in more detail in
the following Section 3.4). The highest observed daily wind speeds
(Fig. 3a) occurred in February, March and November 2015, and March
2016, which all corresponded to northeast winds (Bora events, light
blue bars in Fig. 3). Scirocco events (southeast wind, green bars) were
observed to have less strong wind speeds. Both Mistral and Scirocco
events were found to have occurred less frequently than Bora events.
Comparing Po River average daily outflow with the total daily
beached VMP (Fig. 3b), a loose connection between streamflow and
number of beached VMP was evident. This comes as no great surprised
since Po River streamflow was inherently linked to daily particle release
rate in the model. High beaching rates in February, June and October
2015 were observed to follow high river discharge events, but this
pattern was not always present. Beaching peaks in July 2015 and
January 2016 did not correlate with high river discharge events,
hinting that beaching is not only driven by the amount of released VMP
but also by the surface current field close to the coast and winds.
Of all VMP released, only 18% were found to beach during the si-
mulations. The ratio of released-to-beached VMP for each mouth was
highly variable. Po della Pila, Busa di Scirocco and Po di Gnocca river
mouths were found to beach < 10% of all VMP released, while Po di
Maistra and delle Tolle presented higher rates (26% and 19% respec-
tively). By far the highest rate of beaching was determined for the
southernmost river mouth, Po di Goro, with 94% of all released VMP
being found to have beached. In Fig. 4a, the percentage of beached VMP
from a particular river mouth are compared with the total VMP beached
for each model run day. The other river mouths (Maistra, Pila, Scirocco,
Tolle and Gnocca) display similar behavior in that the majority of
Table 2
Sediment microplastic overview for all 9 beaches sampled, listed north to south. Percent contribution from each plastic type identified is listed: PE polyethylene, PP
polypropylene, PS polystyrene (
also includes ABS acrylonitrile butadiene styrene and SAN styrene acrylonitrile), PA polyamide, EV accounts for EVOH ethylene
vinyl alcohol and EVA ethylene vinyl acetate, PEST polyester, PET polyethylene terephthalate, PVC polyvinyl chloride, PUR polyurethane, PVAL polyvinyl alcohol,
SBR styrene butadiene rubber, C/U accounts for either composite particles or unknown plastic types. Total microplastic particles found as well as particles/DW kg is
indicated for each beach sampled.
Beach % contribution Tot. part. Part./DW kg
Caleri 45.0 8.6 28.0 < 1 18.0 < 1 < 1 < 1 < 1 0 0 < 1 3080 78.8
Levante 62.2 14.6 16.4 < 1 5.7 < 1 < 1 < 1 < 1 < 1 < 1 < 1 2032 59.4
Boccasette 42.9 13.2 42.9 0 < 1 0 0 0 0 0 0 < 1 182 3.9
Pila North 1 27.0 14.8 54.8 0 < 1 0 < 1 0 0 0 0 < 1 115 2.2
Pila North 2 60.2 9.7 20.4 1.9 0 < 1 4.9 0 < 1 0 0 < 1 103 3.6
Pila South 45.7 18.9 34.1 0 1.4 0 0 0 0 0 0 0 440 8.4
Allagamento 10.0 5.0 85.0 0 0 0 0 0 0 0 0 0 20 0.5
Barricata 19.2 13.8 66.3 < 1 < 1 0 0 0 0 0 0 0 652 14.3
Goro 52.0 19.0 27.8 0 < 1 0 0 0 0 0 0 < 1 248 5.2
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
beaching occurs within the first 3 days and was then followed by a
sudden drop to low values, remaining close to zero after about 10 days.
The Po di Goro mouth, on the other hand, also displayed high beaching
rates in the first 5 days but thereafter a more gradual decline, reaching
zero levels after circa 20 days. Thus, VMP released by the Po di Goro
mouth were able to reach the coastline for a longer period of time (up to
30 days after release, as shown in Fig. 4a) and thus had higher prob-
ability to be beached than VMP released from the other mouths. Fig. 4b
depicts the percentage of beached VMP per river mouth as compared to
the total VMP released by the same river mouth. Here the much larger
percentage of VMP to become beached from the total released by the Po
di Goro mouth was quite clear, with over 34% of all VMP released from
the river mouth being beached within the first three days after release.
The elevated beaching rates of the Po di Maistra and delle Tolle were
also more clearly depicted.
The hydrodynamic model beaching accumulation map for the entire
simulation period is shown in Fig. 5. VMP release points in front of river
mouths are indicated by the red arrows. Higher beached VMP accu-
mulation was evident locally around each of the river mouth release
points (Fig. 5a), as well as along the southern coast of the Po Delta and
extending along the southward coast. The highest accumulation areas
were modelled to be just south of the Po della Pila river mouth, and
near to the Po di Gnocca and di Goro river mouths. The individual
distribution from each river mouth is depicted in Fig. 5b, showing that
the VMP beaching rates for all mouths remain quite local except for the
southernmost Po di Goro mouth.
The hydrodynamic modelling results suggest that surface currents
play a more deciding role in determining beaching rates, with the
number of particles being released by the river only semi-coupled to
beach accumulation. Surface currents in the northern Adriatic are de-
termined by wind regime and freshwater influx, the Po River being the
main contributor (Falcieri et al., 2014). VMP tracks from different river
mouths revealed beaching rates of up to 18% for all modelled river
mouths, with the exception of the southernmost mouth Po di Goro. This
is a result of the Goro freshwater plume likely being held closer to the
shoreline by the other plumes, thus allowing plume water to interact
with the coastline for a longer period of time. For the other river
mouths, VMP beaching was found to occur within 10 days following
release, and beaching rate estimates suggests that over 80% of the
microplastic particles being released by the Po River are being dis-
persed to the open Adriatic Sea system.
3.4. Remote sensing model accumulation
Results of all four assessed SPM algorithms are presented in Table 3,
where the algorithm basis is listed along with the fitted algorithm and
model fit statistics (RMSE, LOOCV-RMSE, bias). Model fit statistics
were found to be reduced by an order of magnitude through the cali-
bration/validation for both the Jørgensen and Dekker algorithms, only
slight improvement was achieved for one of the band-ratio Doxaran
algorithms while the other was found to be a non-significant predictor
for the Po River water. Given the observed overlap of the Chl-Are-
flectance peak at 560 nm with the SPM signal saturation between 550
and 700 nm, the Dekker algorithm was selected as preferable to the
Jørgensen algorithm (further details in S5 and S6 of the Supplementary
material). Furthermore, the Dekker algorithm was found to be a sig-
nificant predictor for both L8 as well as S-2 data.
A total of 26 usable images from L8 and S-2 (12 and 14 respectively)
were compiled covering the modelling time period (as shown in Fig. 3
and Table 4). Usable images from two out of the total eighteen months
considered could not be obtained. Of the compiled usable satellite
images, five instances of Bora/low discharge were captured, as well as
three instances of Scirocco/high discharge, only two instances of Bora/
Fig. 3. (a) Average daily wind speed (m/s) in front of the Po Delta. Colored bars highlight wind events: Bora (light blue), Scirocco (green) and Mistral (light gray).
Horizontal dashed line depicts the 5 m/s wind speed threshold. (b) Average daily Po River outflow (m
/s) at Pontelagoscuro (dark blue line, left axis) compared with
the average daily total of beached virtual microplastic particles (VMP, rose line, right axis). VMP were tracked in the model a total of 60 days, with the first day that
satisfied this condition indicated by the vertical dashed black line. Usable satellite acquisitions are depicted by arrows (Landsat 8: L8, red; Sentinel-2: S-2, blue) along
the temporal horizontal axis, ticked below to separate months. Wind events displayed as in (a). (For interpretation of the references to color in this figure legend, the
reader is referred to the web version of this article.)
Fig. 4. Percent beached virtual microplastic particles (VMP) from each river
mouth in comparison to (a) total daily beached VMP and (b) total daily released
VMP. Days after release are depicted along the horizontal axis. Release events
after April 15th, 2016, are not included since these were run for < 60 days.
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
high and Mistral/high, and one instance each of Scirocco/low and
Mistral/low discharge conditions. Images were atmospherically cor-
rected (further details in S3 and S4 of the Supplementary material) and
the optimal calibrated regional empirical algorithm for each sensor was
implemented to create a time series of SPM river plume maps.
Examples from satellite image masking and implementation of the
calibrated SPM algorithm are shown in Fig. 6. High/low river discharge
was classified as daily average river discharge over/below the median
discharge rate for the entire modelling period (1210 m
/s). From the
acquisition with high discharge, the strong effect of a wind event on
river water transportation was quite evident. In the case of high dis-
charge together with southeasterly Scirocco winds (Fig. 6b), plume
water can be observed being pushed northward of the Po della Pila
mouth. With northwesterly Mistral winds (Fig. 6c), the plume shape
appears to be more heavily influenced by river outflow, with high river
discharge producing a plume extending further into the Adriatic. But in
the case of northeasterly Bora winds (Fig. 6a), the high discharge plume
was kept closer to the coastline while primarily spreading high SPM
waters toward the south. A somewhat different pattern was observed
for the acquisitions concurrent to low discharge. The Bora wind event
on January 16, 2016, was observed to again retain the plume close to
the southern coastline (Fig. 6d). Plume form under low discharge and
Scirocco wind was only demonstrated with one acquisition (Fig. 6e).
SPM signal from the river water on this date were quite low, making the
plume difficult to detect, but through utilizing a different stretch the
plume could be observed to extend further into the Adriatic. The Mistral
wind together with low discharge (Fig. 6f) was observed to retain the
river plume close to the coastline, but much smaller than was observed
with high discharge. Standard difference comparison between L8 and S-
2 images revealed a slight sensor bias, in that detected L8 SPM values
tended to be less (< 2 mg/L) than detected S-2 SPM values. This
amount represented < 2% of the SPM range measured in the field
(Table 1) and was thus taken to be negligible.
Results of the remote sensing composite hexagon binning processing
are presented in Fig. 7, with red indicating coastal areas of high river
water influence and green areas with less. Strong river water influence
was detected around all five river mouths (Maistra, Pila, northern and
central Tolle, Gnocca and Goro) as well as the Busa di Tramontana and
di Scirocco. The southern arm of the Po delle Tolle was observed to
have a lesser influence, while the northern section of coastline between
river mouths presented very low rates of river water influence. Coast-
line sections near to the Po della Pila mouth and southward were ob-
served to have higher rates, with the highest influence evidently being
along the coastal section just north of Po della Pila. An area of very high
river water influence (red) was detected between Po della Pila and Busa
di Tramontana, which corresponds to an additional river mouth flowing
out from the lagoon that was first observed during the field campaign.
Coastal exposure modelling using SPM derived from remote sensing
images was able to well capture the signal of sediment heavy river
plume waters spreading along the coastline (Fig. 6 and Fig. 7). Plume
Fig. 5. (a) Distribution map for virtual microplastic particle (VMP) beaching accumulation over the entire 1.5-year simulation period, VMP release locations in front
of river mouths are indicated by the red arrows. Color scale (beige low, red high) indicates total particles beached over entire modelling period. (b) Beached VMP for
each river mouth displayed separately, color scale (blue low, red high) indicates percentage of total VMP beached from that particular river mouth. (For inter-
pretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 3
Calibrated algorithms for suspended particulate matter (SPM). Algorithm spectral basis and publication is indicated in the first column, standard fit algorithm in the
second column together with model fit statistics: root mean square error (RMSE) and bias. Baseline and satellite specific algorithms are listed in the following
columns, with fitted algorithm listed followed by fit statistics (RMSE, leave-one-out cross-validation RMSE, bias) in parentheses. Relationships that were found to be
non-significant (α ≥ 0.05) during fitting are indicated with N/A. The satellite sensor band used is also indicated,e.g. Landsat 8 band 3 centered at 560 nm is indicated
by b3
Algorithm basis Standard fit Baseline fit Landsat 8 Sentinel-2
Band at 555 nm (Jørgensen, 1999) 0.09 + 56.19 b
(154.91; 148.22)
exp(1.47 + 0.60 b
(40.66; 29.98; 27.67)
exp(1.46 + 0.60 b3
(40.64; 29.35; 27.67)
exp(1.45 + 0.60 b3
(40.65; 29.63; 27.67)
Band at 706 nm (Dekker, 1993) 2.69 + 3.31 b
(561.16; 488.92)
exp(1.92 + 0.79 b
(40.45; 21.72; 27.67)
exp(1.82 + 0.66 b4
(40.50; 22.91; 27.67)
exp(1.91 + 0.78 b5
(40.45; 21.65; 27.67)
SPOT bands XS3 (cen. 835 nm) and XS1
(cen. 545 nm) (Doxaran et al., 2002)
exp(3.01 + 3.13 XS3
/ XS1
(27.37; 21.06)
exp(2.37 + 3.25 XS3
/ XS1
(26.29; 29.62; 16.43)
N/A exp(2.39 + 3.57 b8
/ b3
(26.42; 29.79; 16.49)
SPOT bands XS3 (cen. 835 nm) and XS2
(cen. 645 nm) (Doxaran et al., 2002)
exp(2.56 + 5.31 XS3
/ XS2
(83.15; 50.92)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
exposure was found to be highest locally around the five main river
mouths (Maistra, Pila, Tolle, Gnocca and Goro), as well as by side
channels (Scirocco, Tramontana). Different amounts of river plume
exposure were determined for the three arms of the Tolle river mouth,
with the highest signal coming from the middle arm and the lowest
from the southern arm. Evidence of an extra river mouth with strong
outflow between Tramontana and Pila from the remote sensing analysis
follows observations made while collecting the field data. The Po della
Pila mouth is supposed to transport over 60% of the entire river dis-
charge (Correggiari et al., 2005), but based on the SPM exposure map,
this river mouth appears to be on par with the effects from the Po delle
Tolle and Busa di Tramontana. A persistent sand bank was observed at
the opening of this river mouth, both in the remote sensing images and
during sampling in the field. In images taken during high SPM events, it
is clear that flow out of Po della Pila is being split into a northern and
southern portion after encountering this sand bar. If flow is indeed
being slowed out of Po della Pila by the presence of this sand bar, this
would provide a mechanism to explain why the flow is high out of the
Busa di Tramontana and the unnamed outlet just south of Tramontana.
Although this can only be definitively tested with in situ hydrodynamic
measurements, the potential of using remote sensing SPM images for
identifying fine-scale river mouth dynamic patterns is nevertheless well
demonstrated here. The time series was able to capture multiple ac-
quisitions of Bora events with low river discharge and one instance with
high river discharge. In all events, the river plume is observed to stay
closer to the Italian coastline with Bora wind, following results and
model predictions made by Falcieri et al. (2014). This is in stark con-
trast to the situation observed with Scirocco together with high dis-
charge, where the river plume can be observed to extend further east
and north (Fig. 6). River plume dynamics during Mistral events appear
to be controlled more by river discharge than wind regime. The re-
lationship between wind regime and freshwater outflow on northern
Adriatic circulation patterns is complex, but remote sensing images of
the river plume can certainly serve as a useful tool for testing hy-
Very low in situ water microplastic concentrations were found for
the Po di Maistra and delle Tolle mouths, as well as the Busa di
Scirocco. Two of these river mouths, namely Maistra and Scirocco, were
observed to also have low river plume influence from the remote sen-
sing accumulation map. Maistra is expected to have the smallest out-
flow of all river mouths (Correggiari et al., 2005), and was thus also
found to have the smallest impact from the hydrodynamic accumula-
tion modelling (Fig. 5). The low in situ water microplastic concentration
measurement from Po delle Tolle is less easily clarified, as this mouth
was found to have a substantial influence by both the hydrodynamic
and remote sensing accumulation models. There was also a discrepancy
between the measured in situ concentrations from the middle Tolle
mouth and before the Tolle arm divides into three. This suggests that
Table 4
Temporal satellite image coverage from January 2015 to June 2016. Total images from each satellite (Sentinel-2: S-2; Landsat 8: L8) are listed in the table, note that
S-2 images first became available July 2015. Satellite acquisitions also depicted in Fig. 4.
Platform Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Total
L8 1 0 1 2 1 0 0 0 1 1 1 0 1 0 1 1 0 1 12
S-2 – – – – – 1 2 3 1 0 1 1 1 1 0 1 2 24
Fig. 6. Combined effect of different wind regimes (Bora, Scirocco or Mistral) with differing river discharge conditions on river plume transportation along the
Western Adriatic. River discharge is termed “high” (panels a, b, c) or “low” (panels d, e, f) depending on daily discharge relative to the median (1210 m
/s) over the
entire simulation period. Wind events were classified based on wind direction (indicated by wind compass in each column, pointing in the direction that wind is
blowing) and strength (winds in excess of 5 m/s). Suspended Particulate Matter (SPM) values, ranging from low in blue to high in red, depict river plume shape.
Masked pixels are depicted in dark blue, land in light gray (outside of area of interest in dark gray). (For interpretation of the references to color in this figure legend,
the reader is referred to the web version of this article.)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
further accumulation processes may be occurring within the Tolle sub-
arm which have not been captured by the model, and thus warrants
further investigation than was feasible within the scope of this study.
3.5. Model validation results
No significant relationship was found when comparing the in situ
beach sediment microplastic concentrations to the nearest hydro-
dynamic model grid cell (p > 0.10 for Pearson's r and Spearman's ρ).
Removal of beach locations that were under more influence from beach
tourism and nearby aquaculture (namely Caleri, Levante, Boccasette
and Barricata) resulted in a stronger correlation with the hydrodynamic
results: Pearson's r= 0.79 and Spearman's ρ = 0.80 (p < 0.07 in both
cases). Comparison of in situ beach sediment microplastic concentra-
tions with the nearest remote sensing model 30 m hexagon revealed a
moderate negative correlation, with Pearson's r= −0.58 (p = 0.05).
No significant correlation was found at the 100 m hexagon resolution.
Focusing the comparison to beaches with lesser influence from beach
tourism and nearby aquaculture did not reveal an improved correlation.
Removal of the styrene-based polymers from the in situ beach sediment
microplastic concentrations was also considered, given that the ma-
jority of the styrene-based polymer group was composed of foamed
polystyrene. This particular styrene polymer form is highly buoyant and
thus very susceptible to windage during transport as well as potential
higher susceptibility for further particle fractionation during beach
sediment lab processing. Despite these considerations, removal of this
group from in situ beach sediment microplastic concentrations was not
found to provide any further model improvement.
Comparison between the two models is depicted in Fig. 8, where the
normalized remote sensing exposure map is shown next to the hydro-
dynamic model accumulation map (Fig. 8a). General tendencies for
lower normalized values along the coastline north of Pila di Maistra and
south of Lido di Volano were similar between the two model results.
Strong river mouth signal from Pila, the southern Tolle, Gnocca and
Goro were also evident in both maps. Visual dissimilarities were most
evident for the river mouths Maistra, Tramontana and Scirocco, where
a strong signal was registered by the remote sensing model but not by
the hydrodynamic model. In Fig. 8b, the difference of the normalized
values (remote sensing normalized values, RS
, minus hydrodynamic
normalized values, HD
) are displayed as a bar chart aligned along
the latitudinal axis. The comparison was made along the full overlap
extent of both maps and the distribution is indicated in Fig. 8b with one
and two standard deviation gray shaded areas. A slight positive bias is
observed, meaning that the RS
values tend to be higher than the
values, with 95% of all values lying between −0.07 and 0.49.
Areas of exceptional variation, indicated by bars lying outside the
shaded gray area, were notably the coastline located between Pila and
Scirocco and between the northern and central Tolle mouths.
Validation of both accumulation models against all in situ mea-
surements did not produce a significant relationship. This is likely due
to additional microplastic processes (such as biofouling or sinking) and
sources outside of the Po River water which were not included in either
model. Artifacts may also have been introduced to the correlation
through the in situ sediment sampling scheme. In an effort to circum-
vent potential temporal variability, the extreme high tide line was
chosen for the field sampling over the most recent high tide line.
Another factor to acknowledge is the assumption of beaching occurring
after a particle passes within 250 m of the coastline, representing a
substantial simplification of nearshore currents but which was neces-
sary with the given modelling tools. A slightly significant correlation
was found between the hydrodynamic accumulation map and in situ
samples from beaches which were only accessible by boat and not lo-
cated next to a large harbor. An inverse relationship between amount of
beach litter and distance to nearest parking lot has already been es-
tablished in the Adriatic (Munari et al., 2017), suggesting that beach
tourism poses a significant plastic litter source not included in the
models. The remote sensing river plume exposure model was not found
to have a significant relationship with the in situ samples but was very
useful in identifying which river mouths were significant outflow con-
tributors during the simulation period. This information can be useful
in the set-up of future ocean current models of the Po Delta. A number
of factors not incorporated into either the hydrodynamic or the remote
sensing model may largely explain the missing correlation. Refuse re-
sulting from the major shipping corridors which cross the Adriatic are
posited to account for 20% of all marine plastic litter introduced each
year to the sea and the Po River for only 13.5% thereof (Liubartseva
et al., 2016). Windage of particles was not accounted for in the hy-
drodynamic model, which can provide drift speeds up to 25% larger
than the current speed (Chubarenko et al., 2016). After particles be-
come beached, wind transportation may move particles laterally or
further inland (Munari et al., 2016). Microplastic particle aging within
the marine environment was also not represented, including processes
of biofouling, further fragmentation, flocculation and aggregation, all
which are recognized as important dynamic parameters influencing
residence times and transportation pathways (Zhang, 2017). VMP
density was simplified to 0.91 g/mL, representative of the average of
virgin PE (both high and low density) and PP, which was a necessary
assumption given the scope of the study. It would be quite interesting to
test how differing particle density for each major plastic type would
affect modelled coastal accumulation patterns, especially for the
polymer groups most represented in the sediment samples (PE, PP and
PS). Seasonality was accounted for in the hydrodynamic model through
changing the amount of VMP released dependent upon Po River out-
flow, but the concentration of microplastic particles was held constant
during the entire modelling period. It has been established that river
mouth concentrations of microplastic particles can vary by up to three
orders of magnitude at different times of the year (Lebreton et al., 2017)
and that storm water runoff events can significantly increase river
Fig. 7. Composite hexagon (100 m) map of SPM time series, colored by
summed daily similarity values to river water. High rates of river plume in-
fluence (red) are observed at all five major river mouths and the Busa di
Tramontana and di Scirocco, around Po della Pila. Low river plume influence
(green) can be observed along the northern coast of the delta. (For inter-
pretation of the references to color in this figure legend, the reader is referred to
the web version of this article.)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
mouth microplastic load (Zhang, 2017). Beaching in this study's hy-
drodynamic model follows simplifying assumptions made in other
studies (Lebreton et al., 2012;Politikos et al., 2017), since the me-
chanisms controlling onshore-offshore transport of microplastic parti-
cles remain unclear (Critchell et al., 2015;Hardesty et al., 2017;Hinata
et al., 2017;Moreira et al., 2016). Despite this, these mechanisms likely
play a driving role in determining small-scale and temporal variation in
sediment microplastic deposition rates (Carlson et al., 2017;Hinata
et al., 2017;Schulz et al., 2017;Zhang, 2017).
4. Conclusions and outlook
In situ sampling of both Po River and Adriatic Sea waters revealed
microplastic concentrations up to 84 particles/m
and beach sediment
concentrations up to 78 particles/DW kg. The hydrodynamic modelling
approach was able to identify differing beaching rates between various
river mouths and suggested that particle beaching mostly occurred
within the first 10 days of release. Particles which do not beach within
this initial time period (over 80% of all VMP emitted by the Po River)
were transported away from the Po Delta coastline. Po River emitted
particles that were moved offshore remained offshore, likely due to the
continual freshwater input creating water density boundaries that in-
hibit westward transport. Especially the Po di Goro mouth was identi-
fied as effecting higher beaching rates over a much longer stretch of
coastline. The suspended sediment remote sensing approach was able to
well represent river mouth relative strength, such as the smaller con-
tribution from the southernmost Po delle Tolle river arm or the much
larger contribution of Busa di Tramontana in river outflow.
Microplastic accumulation exposure maps were constructed from both
approaches, which were found to be similar to one another but were not
found to have a significant relationship to in situ beach sampling. This
relationship changed when beaches that were closer to public parking
lots and harbors were removed, suggesting that microplastic sources
which were not accounted for in either modelling approach are also
large contributors to beach microplastic accumulation.
There remain many uncertainties still in our understanding of the
transportation and accumulation mechanisms of microplastics
(Hardesty et al., 2017) and with this study we offer some insight into
these mechanisms within the coastal environment. From the hydro-
dynamic modelling, we see how particles not beached within the first
10 days are transported away from the coastline. The hydrodynamic
model also offers a continual track of VMP transportation and could be
used to study VMP distribution in the open sea. The remote sensing
model presents snapshots of surface river plume form at a finer spatial
resolution over a larger area than computationally feasible with ex-
isting ocean current models. River plume exposure during the model-
ling period could be well captured but this is difficult to translate to
actual microplastic accumulation rates. Model assimilation of remote
sensing data into ocean current simulation models has begun to gain
traction in other oceanographic modelling areas (Miyazawa et al.,
2013;Stroud et al., 2009;Zhang et al., 2014), with up to 40% im-
provements in model forecast root square error. Hardesty et al. (2017)
have already suggested the great improvements possible to our under-
standing of microplastic transportation pathways through integrating
simulation model and empirical observations.
Deeper understanding of microplastic sources, pathways and accu-
mulation areas is intrinsic to our ability to mitigate introduction of this
pollutant to limnic and marine systems as well as organize clean-up
activities. International agreements are already in place forbidding
deposition of litter into the Mediterranean marine environment (Mistri
et al., 2017;Munari et al., 2016), yet despite these steps this enclosed
sea continues to have particularly high concentrations of marine debris
Fig. 8. (a) Remote sensing hexagon-binned (100 m) exposure map (left) next to hydrodynamic model accumulation map (right), both datasets have been unit-based
normalized (green low to red high). (b) Difference normalized remote sensing model (RS
) to normalized hydrodynamic model (HD
), aligned along the
latitudinal axis. Percentage all observations (obs.) at one standard deviation (1-σ, 68%, dark gray) or two (2-σ, 95%, light gray) is indicated, and river mouth position
along bar chart is shown in blue italics. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
E.C. Atwood et al. Marine Pollution Bulletin 138 (2019) 561–574
(Cozar et al., 2015;Suaria et al., 2016). Other modelling efforts within
the Adriatic suggest that land-based sources of marine litter contribute
the majority of marine litter entry into the sea each year (Munari et al.,
2017). National borders are not a component of marine plastic debris
transportation pathway mechanisms and finding middle ground in na-
tional agendas to support concerted legislation efforts are difficult. In
situ microplastic sampling and sample processing is costly, thus mod-
elling offers a methodology for upscaling point measurements to larger
areas than could be feasibly sampled (Hardesty et al., 2017). Fresh-
water systems, in particular rivers, have been slower to receive the
same microplastic research attention as attributed to marine systems
(Wagner et al., 2014). Evidence exists that even low-density tourism
can still create heavy consumer plastic pollution (Free et al., 2014).
Methods for identifying marine debris sources and forecasting accu-
mulation areas have already been put forward as a method to reduce
the cost and optimize the effort of remediation activities (Krelling et al.,
2017;UNEP, 2016). This study demonstrates the strengths and weak-
nesses of two separate modelling approaches, providing further tools
aiming to answer the suggestion of Hardesty et al. (2017) to develop
multipart solutions which can be applied at both local and regional
scales to effect change.
Supplementary data to this article can be found online at https://
The authors would like to thank Sandra Lohberger for providing
advice and input to both the analysis and writing of the paper. This
work was very kindly supported by numerous lab technicians and in-
terns. Sabela Rodríguez Castaño, Sophia Wisböck and Moritz Altenbach
in particular provided much appreciated support in image processing.
Both Veronika Mitterwallner and Lena Löschel played very important
roles in the preparation and analysis of the microplastic samples, and
Heghnar Martirosyan and Annika Heymann are thanked for their help
with ATR measurements. We would like to extend our thanks to our
brave boat captains, Claudio and Sandro, who were willing to take a
trio of crazy scientists repeatedly out into the open ocean. This study
was partly funded by the German Federal Ministry for Economic Affairs
and Energy (Bundesministerium für Wirtschaft und Energie, or BMWi)
via the DLR Space Administration under the grant numbers 50EE1301
and 50EE1269, and by the Italian National Flagship Program RITMARE
of the Italian Ministry of Education, University and Research.
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... Most studies focused on the characteristics and abundance of MPs in individual compartments (biotic or abiotic) (i.e., Vianello et al., 2013;Piarulli et al., 2019Piarulli et al., , 2020Renzi et al., 2020;Sfriso et al., 2021;Mistri et al., 2021;Mudadu et al., 2022;Provenza et al., 2023), with limited integration, which affects our understanding of MP dynamics in these lagoons. Only two studies examined two abiotic compartments (water and sediment) (Atwood et al., 2019;Specchiulli et al., 2023). Most coastal lagoons where MPs were studied were in international or national protected areas such as Ramsar sites, nature reserves, sites of wildlife conservation importance, sites of community or regional importance (SIC or SIR), or special protection areas (ZPS) ( Table 1). ...
... In contrast, algae and kelp were used only in one study . As with the other environmental matrices, in three studies sediment samples were collected at various depths from the surface to a depth of 5 cm (Vianello et al., 2013;Atwood et al., 2019;Mistri et al., 2021). The mass of sediment transported to the laboratory varied, as did the sampling device, which was sometimes not specified. ...
... The mass of sediment transported to the laboratory varied, as did the sampling device, which was sometimes not specified. Only two studies analyzed the abundance of MP in the water using different methods (Atwood et al., 2019;Specchiulli et al., 2023). One study used a mini-manta trawl to sample litter directly at the water surface (Atwood et al., 2019), while the other collected 5 L of water in MP-free container . ...
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Lagoons play an important role in providing a variety of ecological services. They provide important habitats for several plant and animal species, also acting as natural filters that regulate water quality. Microplastic (MP) pollution has become a global environmental problem that warrants in-depth studies to understand its impact on socioeconomically and ecologically important areas such as lagoon systems. However, there is a notable lack of data on the occurrence of MPs in Italian lagoon systems, highlighting the need for monitoring and assessment. In this review, peer-reviewed studies from Google Scholar and Scopus databases were examined (n = 10), reflecting the current knowledge on the occurrence of MPs in Italian lagoon systems. A high degree of methodological heterogeneity was recorded, making difficult a meaningful comparison and draw comprehensive conclusions about the occurrence of MPs. Alarmingly, in Italy, only 9 of more than 100 coastal transition ecosystems have been monitored for MP pollution, leaving a significant number unexplored and inadequately studied. In addition, most studies have focused primarily on organism analysis without simultaneously examining the presence of MPs in water and sediments, making it difficult to establish links between MP pollution in abiotic and biotic compartments. To address these gaps, we extended the literature review to research performed worldwide to identify potential organisms suitable for monitoring MPs in lagoons and nearshore transition ecosystems. As observed in many studies, our results highlight the urgent scientific need to standardize methods, procedures, and sampling designs to facilitate comparability and improve the robustness of future research in this area. Overall, this review sheds light on the MP occurrence in Italian lagoon systems, highlights the limitations of existing studies, and emphasizes the urgency of adopting standardized approaches for consistent monitoring and assessment. By addressing these research gaps, we can improve our understanding of MP pollution in lagoons and develop effective strategies to protect these important ecosystems.
... River plumes represent the region where riverine and marine water are joined (Malli et al. 2022). Floating plastics and microplastics litters can be trapped in these plumes due to different water properties and hydrodynamic processes (Atwood et al. 2019). This part being a boundary layer between rivers and oceans is not considered in this framework. ...
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PurposeThe international working group MariLCA has proposed a framework aiming towards integrating the impacts of plastic pollution in life cycle impact assessment (LCIA). Filling one of the identified mechanisms, this paper proposes a harmonized LCIA framework for the development of mechanistic fate factors (FFs) and consequently characterization factors (CFs) for microplastics (MPs) emissions in the marine environment, for the proposed impact category “Physical effects on biota.”Methods Based on a literature review, fate mechanisms and environmental factors influencing MPs in the marine environment are identified. Dominant fate mechanisms are determined, based on which the marine environment is divided into homogeneous sub-compartments. Following on this framework and multimedia fate models adopted in LCIA, rate matrices for different types, shapes, and sizes of MPs are constructed. Fate matrices are obtained by negatively inverting rate matrices. Similar to emission-related impact categories, CF matrices are constructed by multiplying FF matrices with exposure-effect matrices.Results and discussionThe marine environment is divided into marine sub-compartments at two different scales: continental and global. Marine sub-compartments include beach, water surface, water column, and sediments at the continental scale and water surface, water column, and sediments at the global scale. Due to the dependency of MPs fate on their physiology (shape, size, and density), different rate and fate matrices can be obtained. Mechanistic characterization factors for water surface and water column sub-compartments are obtained by multiplying the fate matrix with already existing exposure-effect factors for aquatic ecosystem. However, in order to develop CFs for beach and sediments sub-compartments, this framework suggests the development of new exposure and effect factors specific to these sub-compartments.Conclusion Since LCA is known as a holistic approach, marine litter should be integrated in its impact assessment. This proposed framework fills one of the gaps of MariLCA’s framework that aims towards integrating plastic litter in LCIA by proposing fate and CF matrices for different types of microplastics emitted to the marine environment.
... However, the mechanisms of transporting plastic in an estuary remain largely unknown (Duncan et al., 2020;van Emmerik et al., 2019a). Simulating the transport of plastic due to the tides, wind, river flows and the response to morphological features in an estuary requires validation (Zhang, 2017;Atwood et al., 2019;Ryan and Perold, 2021) but observational data are often insufficient at the local scale (van Emmerik and Schwarz, 2020;Duncan et al., 2020;Vermeiren et al., 2016). The recent development of remote sensing (Martínez-Vicente et al., 2019), GPS drifter trackers (Tramoy et al., 2020a) and beach clean-ups (Andrady, 2017) should provide more observational data in future at the local scale. ...
Estuaries can act as plastic retention hotspots, but the hydrodynamic controls on retention are not well understood. This study investigates the retention of river-sourced buoyant plastics in a well-mixed estuary, the Waitematā Estuary, using validated numerical simulations of floats with different tides, winds, and freshwater discharge. The proportion of floats grounded on the shore in all seven simulations is higher than 60 % and over 90 % in five simulations after ten days. <20 % of the floats leave the estuarine mouth in any of the simulations. An increase of two orders of magnitude in freshwater discharge doubles the likelihood for floats to reach the lower estuary. However, we find increased freshwater discharge doubles the lateral circulation towards the shore and results in similar proportions of grounding (90 %) as the low discharge cases. These findings challenge the conventional view that plastics preferentially enter the open ocean after high river discharge.
... No significant differences were highlighted between the different sampling locations (p > 0.05). subaerial deposits of the Po Delta the maximum concentration found was 23.30 MPs/kg and 78.8 MPs/kg by Piehl et al. (2019) and Atwood et al. (2019), respectively, which point out the need to determine the abundance of MPs in the subaqueous counterpart of the delta. Our results on the Po prodelta sediment reveal a concentration of two orders of magnitude higher than those documented for the subaerial deposit with an average concentration of 139.7 ± 80 MPs/kg d.w., and a pick in MP abundance of up to 625 MPs/kg d.w. ( Table 2). ...
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Deltas are the locus of river-borne sediment accumulation, however, their role in sequestering plastic pollutants is still overlooked. By combining geomorphological, sedimentological, and geochemical analyses, which include time-lapse multibeam bathymetry, sediment provenance, and μFT-IR analyses, we investigate the fate of plastic particles after a river flood event providing an unprecedented documentation of the spatial distribution of sediment as well as of microplastics (MPs), including particles fibers, and phthalates (PAEs) abundances in the subaqueous delta. Overall sediments are characterized by an average of 139.7 ± 80 MPs/kg d.w., but display spatial heterogeneity of sediment and MPs accumulation: MPs are absent within the active sandy delta lobe, reflecting dilution by clastic sediment (ca. 1.3 Mm3) and sediment bypass. The highest MP concentration (625 MPs/kg d.w.) occurs in the distal reaches of the active lobe where flow energy dissipates. In addition to MPs, cellulosic fibers are relevant (of up to 3800 fibers/kg d.w.) in all the analyzed sediment samples, and dominate (94 %) with respect to synthetic polymers. Statistically significant differences in the relative concentration of fiber fragments ≤0.5 mm in size were highlighted between the active delta lobe and the migrating bedforms in the prodelta. Fibers were found to slightly follow a power law size distribution coherent with a one-dimensional fragmentation model and thus indicating the absence of a size dependent selection mechanism during burial. Multivariate statistical analysis suggests traveling distance and bottom-transport regime as the most relevant factors controlling particle distribution. Our findings suggest that subaqueous prodelta should be considered hot spots for the accumulation of MPs and associated pollutants, albeit the strong lateral heterogeneity in their abundances reflects changes in the relative influence of fluvial and marine processes.
Microplastics have recently received high global attention, as their widespread presence can potentially cause physical and toxicological risks to organisms. The west coast of Lombok Island in Indonesia has a high potential for microplastic accumulation; even so, its presence in this area was not well studied. Therefore, this study aimed to describe the distribution and density of microplastics within the sediments on the west coast of Lombok. Microplastic sampling had been carried out in the northern, middle, and southern portions of the west coast of Lombok based on distinct geographical and vegetational characteristics. Sediment samples were taken within the HTL (High Tide Line) zone based on the excavation depths categories, i.e. A (0–2cm), B (2–4 cm), C (4–6 cm), D (6–8 cm), and D (8–10 cm). The sediment samples were filtered using an aluminum sieve with a mesh size of 4.75 mm, targeting microplastic pieces below that size. A total of 16,685 microplastic debris were found distributed horizontally and vertically throughout the station. There was a significant difference in the microplastic density distributed between stations [F(10,22) = 6.96, p < 0.001] and between sediment depths [F(10,44) = 9.07,p < 0.001]. The order of average microplastic concentration was southern > northern > middle stations group. The highest microplastic number recorded in SMP11 (southern station, open bay, high anthropogenic activity, with river and primary mangrove vegetation) was as many as 2,361 (density, D = 125,920.00 ± 204.33 items/m3), whereas SMP01 (northern station, open bay, low anthropogenic activity, and with river and secondary mangrove vegetation) had the lowest microplastic number of 678 (D = 36,160.00 ± 72.82 items/m3). In general, the majority of microplastics (45.76%) were distributed on the sediment surface (A–B), where there was a repeating pattern in the difference of microplastic density fluctuations of about 3% at every 4cm of sediment depth (B–C and D–E), which is thought to be driven by daily tidal fluctuation.There was no clear pattern that indicated whether the specific type of shoreline or the presence of rivers and mangroves had an influence on the level of microplastic accumulation. However,the southern stations group had a considerably higher average of microplastic accumulation.We suspect that the geographical position towards the main ocean current contributes greatly to the microplastic accumulation at the site.
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Over the last century, accumulation of microplastic has emerged as a greater threat to the environment, plants, microorganisms and even human beings. Microplastics can be intentionally produced for industries such as cosmetics, or they may be unintentionally generated from degradation of bulk plastic debris. Furthermore, mismanagement of plastic waste is a major source of microplastics. When ingested, microplastics can alter several physical, chemical and biological processes in living organisms. Thus, their toxicity silently spreads its roots into the biosphere. Unfortunately, current strategies for the elimination of microplastics are not sufficient for their complete removal and degradation. Therefore, the adoption of green innovative technologies is the first step toward a microplastic-free environment. However, advances for its effective degradation and elimination are hindered by our limited understanding. This literature study investigates microplastic comprehensively, covering their sources, fate, ecological impacts and their effects on biological processes. It includes an analysis of microplastics in Indian rivers, explores methods for its eradication and degradation, emphasizes plastic recycling and offers future recommendations to pave way toward achieving a microplastic-free environment. Graphical Abstract
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Microplastics have recently received high global attention, as their widespread presence can potentially cause physical and toxicological risks to organisms. The west coast of Lombok Island in Indonesia has a high potential for microplastic accumulation; even so, its presence in this area was not well studied. Therefore, this study aimed to describe the distribution and density of microplastics within the sediments on the west coast of Lombok. Microplastic sampling had been carried out in the northern, middle, and southern portions of the west coast of Lombok based on distinct geographical and vegetational characteristics. Sediment samples were taken within the HTL (High Tide Line) zone based on the excavation depths categories, i.e. A (0-2 cm), B (2-4 cm), C (4-6 cm), D (6-8 cm), and D (8-10 cm). The sediment samples were filtered using an aluminum sieve with a mesh size of 4.75 mm, targeting microplastic pieces below that size. A total of 16,685 microplastic debris were found distributed horizontally and vertically throughout the station. There was a significant difference in the microplastic density distributed between stations [F(10,22) = 6.96, p < 0.001] and between sediment depths [F(10,44) = 9.07, p < 0.001]. The order of average microplastic concentration was southern > northern > middle stations group. The highest microplastic number recorded in SMP11 (southern station, open bay, high anthropogenic activity, with river and primary mangrove vegetation) was as many as 2,361 (density, D = 125,920.00 ± 204.33 items/m 3), whereas SMP01 (northern station, open bay, low anthropogenic activity, and with river and secondary mangrove vegetation) had the lowest microplastic number of 678 (D = 36,160.00 ± 72.82 items/m 3). In general, the majority of microplastics (45.76%) were distributed on the sediment surface (A-B), where there was a repeating pattern in the difference of microplastic density fluctuations of about 3% at every 4 cm of sediment depth (B-C and D-E), which is thought to be driven by daily tidal fluctuation. There was no clear pattern that indicated whether the specific type of shoreline or the presence of rivers and mangroves had an influence on the level of microplastic accumulation. However, the southern stations group had a considerably higher average of microplastic accumulation. We suspect that the geographical position towards the main ocean current contributes greatly to the microplastic accumulation at the site.
Plastics are ubiquitous in the global marine ecosystem; however, studies on microplastic (MPs) ingestion by fish in the remote Antarctic are extremely limited. We detected MPs in ocellated icefish (Chionodraco rastrospinosus)-a limitedly distributed but ecologically important species-in the northern Antarctic Peninsula. This is the first study reporting MPs distribution in the stomach, intestine, and gill of this species. Of 32 C. rastrospinosus individuals, 10 (31.3 %) individuals ingested MPs. Totally, 157 suspected microplastic particles were detected, and only 10 MPs were finally confirmed from the subsampled 38 highly suspected particles after FTIR detection, with an average of 0.36 particles per individual. The stomach, intestine, and gills of each fish contained 0.06 ± 0.24, 0.16 ± 0.36, and 0.09 ± 0.29 particles, respectively. Fibrous MPs with a diameter of <200 μm were predominant in all tissues, with blue MPs being the most common. Polyester and acrylic acid were the most frequently observed plastic polymers. MPs abundance in C. rastrospinosus was unrelated to biometrics.
Microplastic (MP) pollution is ubiquitous in the oceans and poses serious threats to the marine ecosystems. Nowadays numerical modeling has become one of the widely used tools for monitoring and predicting the transport and fate of MP in marine environments. Despite the growing body of research on numerical modeling of marine MP, the advantages and disadvantages of various modeling methods have not received systematic evaluation in published works. Important aspects such as parameterization schemes for MP behaviors, factors influencing MP transport, and proper configuration in beaching are essential for guiding researchers to choose proper methods in their work. For this purpose, we comprehensively reviewed the current knowledge on factors influencing MP transport, classified modeling approaches according to the governing equations, and summarized up-to-date parameterization schemes for MP behaviors. Critical factors such as vertical velocity, biofouling, degradation, fragmentation, beaching, and washing-off were reviewed in the frame of MP transport processes.
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Most plastic pollution originates on land. As such, freshwater bodies serve as conduits for the transport of plastic litter to the ocean. Understanding the concentrations and fluxes of plastic litter in freshwater ecosystems is critical to our understanding of the global plastic litter budget and underpins the success of future management strategies. We conducted a replicated field survey of surface plastic concentrations in four lakes in the North American Great Lakes system, the largest contiguous freshwater system on the planet. We then modeled plastic transport to resolve spatial and temporal variability of plastic distribution in one of the Great Lakes, Lake Erie. Triplicate surface samples were collected at 38 stations in mid-summer of 2014. Plastic particles >106 μm in size were quantified. Concentrations were highest near populated urban areas and their water infrastructure. In the highest concentration trawl, nearly 2 million fragments km−2 were found in the Detroit River—dwarfing previous reports of Great Lakes plastic abundances by over 4-fold. Yet, the accuracy of single trawl counts was challenged: within-station plastic abundances varied 0- to 3-fold between replicate trawls. In the smallest size class (106–1,000 μm), false positive rates of 12–24% were determined analytically for plastic vs. non-plastic, while false negative rates averaged ~18%. Though predicted to form in summer by the existing Lake Erie circulation model, our transport model did not predict a permanent surface “Lake Erie Garbage Patch” in its central basin—a trend supported by field survey data. Rather, general eastward transport with recirculation in the major basins was predicted. Further, modeled plastic residence times were drastically influenced by plastic buoyancy. Neutrally buoyant plastics—those with the same density as the ambient water—were flushed several times slower than plastics floating at the water's surface and exceeded the hydraulic residence time of the lake. It is likely that the ecosystem impacts of plastic litter persist in the Great Lakes longer than assumed based on lake flushing rates. This study furthers our understanding of plastic pollution in the Great Lakes, a model freshwater system to study the movement of plastic from anthropogenic sources to environmental sinks.
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The aim of this study is to develop standard statistical methods and software for the analysis of beach litter data. The optimal ensemble of statistical methods comprises the Mann-Kendall trend test, the Theil-Sen slope estimation, the Wilcoxon step trend test and basic descriptive statistics. The application of Litter Analyst, a tailor-made software for analysing the results of beach litter surveys, to OSPAR beach litter data from seven beaches bordering on the south-eastern North Sea, revealed 23 significant trends in the abundances of beach litter types for the period 2009–2014. Litter Analyst revealed a large variation in the abundance of litter types between beaches. To reduce the effects of spatial variation, trend analysis of beach litter data can most effectively be performed at the beach or national level. Spatial aggregation of beach litter data within a region is possible, but resulted in a considerable reduction in the number of significant trends.
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A circulation model is coupled to a Lagrangian particle-tracking model to simulate the transport floating litter particles in the Aegean Sea, Greece (Eastern Mediterranean). Considering different source regions and release dates, simulations were carried out to explore the fate and distribution of floating litter over 1990–2009, taking into account the seasonal and interannual variability of surface circulation. Model results depicted recurrently high concentrations of floating litter particles in the North Aegean plateau, the Saronikos Gulf, and along Evia and Crete islands. Modeled transport pathways of floating litter demonstrated that source regions are interconnected, with Saronikos Gulf being a main receptor of litter from other sources. Notably higher percent of litter exit (∼35%) than enter the model domain (∼7%) signified that Aegean Sea seems to act as a source rather than receptor of floating litter pollution in the Eastern Mediterranean Sea. Beached litter was found around 10%, mostly located in the western part of the Aegean Sea. This is the first modeling study to explore the transport of floating marine litter in Greek waters.
Following the widespread assumption that a majority of ubiquitous marine microplastic particles originate from land-based sources, recent studies identify rivers as important pathways for microplastic particles (MPP) to the oceans. Yet a detailed understanding of the underlying processes and dominant sources is difficult to obtain with the existing accurate but extremely time-consuming methods available for the identification of MPP. Thus in the presented study, a novel approach applying shortwave infrared imaging spectroscopy for the quick and semi-automated identification of MPP is applied in combination with a multitemporal survey concept. Volume-reduced surface water samples were taken from transects at ten points along a major watercourse running through the South of Berlin, Germany, on six dates. After laboratory treatment , the samples were filtered onto glass fiber filters, scanned with an imaging spectrometer and analyzed by image processing. The presented method allows to count MPP, classify the plastic types and determine particle sizes. At the present stage of development particles larger than 450 mm in diameter can be identified and a visual validation showed that the results are reliable after a subsequent visual final check of certain typical error types. Therefore, the method has the potential to accelerate microplastic identification by complementing FTIR and Raman microspectroscopy. Technical advancements (e.g. new lens) will allow lower detection limits and a higher grade of automatization in the near future. The resulting microplastic concentrations in the water samples are discussed in a spatio-temporal context with respect to the influence (i) of urban areas, (ii) of effluents of three major Berlin waste-water treatment plants discharging into the canal and (iii) of precipitation events. Microplastic concentrations were higher downstream of the urban area and after precipitation. An increase in microplastic concentrations was discernible for the wastewater treatment plant located furthest upstream though not for the other two.
Micro-Fourier transform infrared (micro-FTIR) spectroscopy and Raman spectroscopy enable the reliable identification and quantification of microplastics (MPs) in the lower micron range. Since concentrations of MPs in the environment are usually low, the large sample volumes required for these techniques lead to an excess of co-enriched organic or inorganic materials. While inorganic materials can be separated from MPs using density separation, the organic fraction impedes the ability to conduct reliable analyses. Hence, the purification of MPs from organic materials is crucial prior to conducting an identification via spectroscopic techniques. Strong acidic or alkaline treatments bear the danger of degrading sensitive synthetic polymers. We suggest an alternative method, which uses a series of technical grade enzymes for purifying MPs in environmental samples. A basic enzymatic purification protocol (BEPP) proved to be efficient while reducing 98.3 ± 0.1 % of the sample matrix in surface water samples. After showing a high recovery rate (84.5 ± 3.3 %), the BEPP was successfully applied to environmental samples from the North Sea where MPs numbers range from 0.05 to 4.42 items m−³. Experiences with different environmental sample matrices were considered in an improved and universally applicable version of the BEPP, which is suitable for Focal plane array detector (FPA)-based micro-FTIR analyses of water, wastewater, sediment, biota and food samples.
Microplastic pollution of the marine environment has received increasing attention from scientists, the public, and policy makers over the last few years. Marine microplastics predominantly originate near the coast and can remain in the nearshore zone for some time. However, at present, there is little understanding of the fate and transport of microplastics in coastal regions. This paper provides a comprehensive overview of the physical processes involved in the movement of microplastics from estuaries to the continental shelf. The trajectory and speed of microplastics are controlled by their physical characteristics (density, size, and shape) and ocean dynamic conditions (wind, waves, tides, thermohaline gradients, and the influence of benthic sediments). Microplastic particles can be subjected to beaching, surface drifting, vertical mixing, and biofouling, as well as bed-load and suspended load transport processes, until reaching terminal deposition on beaches, in coastal marshes, in benthic sediments or until they are carried by ocean currents to subtropical convergence zones. The dynamic interaction of released microplastics with the shoreline is regulated by onshore/offshore transport, which is impacted by the source location as well as the geometry, vegetation, tidal regime, and wave direction. Wind and wave conditions dominate surface drifting of buoyant particles through Ekman drift, windage, and Stokes drift mechanisms. Neustic microplastic particles travel in the subsurface because of vertical mixing through wind-driven Langmuir circulation and heat cycling. Increasing accumulation of microplastics in benthic sediments needs to be quantitatively explored in terms of biofouling, deposition, entrainment, and transport dynamics. Further studies are required to understand the following: 1) the primary parameters (e.g., windage, terminal velocity, diffusivity, critical shear stress) that determine microplastic transport in different pathways; 2) dynamic distribution of microplastics in various coastal landscapes (e.g., wetlands, beaches, estuaries, lagoons, barrier islands, depocenters) regulated by hydrodynamic conditions; and 3) interactions between the physical transport processes and biochemical reactions (degradation, flocculation, biofouling, ingestions).
Plastic particles in marine and freshwater environments span from macroscopic to microscopic size classes. Each may have a different impact on individuals, populations and ecosystems, but still the wide variety of methods used in beach sediment sampling inhibit comparisons among studies and therefore hampers a risk assessment. A large portion of the uncertainties is due to differing sampling strategies. By quantifying the alongshore distribution of macro- and microplastic particles within five beaches of Lake Garda, we aim to shed light on the accumulation behavior of microplastic particles at an exemplary lake which might give indications for potential sampling zones. The identification of plastic at the single particle level with a spatial resolution down to 1μm was performed by Raman microspectroscopy. Given the time consuming approach we reduced the number of samples in the field but increased the spatial area where a single sample was taken, by utilizing a transect approach in combination with sediment cores (5cm depth). The study revealed that, in comparison to the water line and the high-water line, the drift line of all five beaches always contained plastic particles. Since the drift line accumulate particulate matter on a relatively distinct zone, it will enable a comparable sampling of microplastic particles. The applied sampling approach provided a representative method for quantifying microplastic down to 1μm on a shore consisting of pebbles and sand. Hence, as first step towards a harmonization of beach sediment sampling we suggest to perform sampling at the drift line, although further methodological improvements are still necessary.
The ubiquitous presence and persistency of microplastics in aquatic environments is of particular concern because these pollutants represent an increasing threat to marine organisms and ecosystems. An identification of the patterns of microplastic distribution will help to understand the scale of their potential effect on the environment and on organisms. In this study, the occurrence and distribution of microplastics in the Bohai Sea are reported for the first time. We sampled floating microplastics at 11 stations in the Bohai Sea using a 330 μm trawling net in August 2016. The abundance, composition, size, shape and color of collected debris samples were analyzed after pretreatment. The average microplastic concentration was 0.33 ± 0.34 particles/m(3). Micro-Fourier transform infrared spectroscopy analysis showed that the main types of microplastics were polyethylene, polypropylene, and polystyrene. As the size of the plastics decreased, the percentage of polypropylene increased, whereas the percentages of polyethylene and polystyrene decreased. Plastic fragments, lines, and films accounted for most of the collected samples. Accumulation at some stations could be associated with transport and retention mechanisms that are linked to wind and the dynamics of the rim current, as well as different sources of the plastics.
This is the first survey to investigate the occurrence and extent of microplastic contamination in sediments collected along a coast-open sea 140 km-long transect in the Central Adriatic Sea. Plastic debris extracted from 64 samples of sediments were counted, weighted and identified by Fourier-transform infrared spectroscopy (FT-IR). Several types of plastic particles were observed in 100% of the stations. Plastic particles ranged from 1 to 30 mm in length. The primary shape types by number were filaments (69.3%), followed by fragments (16.4%), and film (14.3%). Microplastics (1–5 mm) accounted for 65.1% of debris, mesoplastics (5–20 mm) made up 30.3% of total amount, while macro debris (> 20 mm) accounted for 4.6% of total plastics collected. Identification through FT-IR spectroscopy evidenced the presence of 6 polymer types: the majority of plastic debris were nylon, polyethylene and ethylene vinyl alcohol copolymer. Our data are a baseline for microplastic research in the Adriatic Sea.