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<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2024.1524585</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Mapping microplastic pathways and accumulation zones in the Gulf of Finland, Baltic Sea &#x2013; insights from modeling</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Mishra</surname>
<given-names>Arun</given-names>
</name>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Siht</surname>
<given-names>Enriko</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>V&#xe4;li</surname>
<given-names>Germo</given-names>
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<contrib contrib-type="author">
<name>
<surname>Liblik</surname>
<given-names>Taavi</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>Buhhalko</surname>
<given-names>Natalja</given-names>
</name>
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<contrib contrib-type="author">
<name>
<surname>Lips</surname>
<given-names>Urmas</given-names>
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</contrib-group>    <aff id="aff1">
<institution>Department of Marine Systems, Tallinn University of Technology</institution>,
<addr-line>Tallinn</addr-line>, <country>Estonia</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Meilin Wu, Chinese Academy of Sciences (CAS), China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Marcos D. Mateus, Instituto Superior T&#xe9;cnico - Universidade de Lisboa, Portugal</p>
<p>Meng Chuan Ong, University of Malaysia Terengganu, Malaysia</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Arun Mishra, <email xlink:href="mailto:arun.mishra@taltech.ee">arun.mishra@taltech.ee</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>20</day>
<month>01</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>11</volume>
<elocation-id>1524585</elocation-id>
<history>
<date date-type="received">
<day>07</day>
<month>11</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>23</day>
<month>12</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Mishra, Siht, V&#xe4;li, Liblik, Buhhalko and Lips</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Mishra, Siht, V&#xe4;li, Liblik, Buhhalko and Lips</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>A hydrodynamic model coupled with a particle tracking model was used to identify the pathways and accumulation areas of microplastics (MP) in the Gulf of Finland (GoF) over a three-year period (2018-2020). Two key sources, wastewater treatment plants (WWTPs) and rivers, were considered, focusing on polypropylene (PP)/polyethylene (PE) and polyethylene terephthalate (PET) particles sized 20-500 &#x3bc;m. Rivers contribute 76% of total MP entering the gulf, while WWTPs account for the remaining 24%. Most of the MP accumulates inside the gulf and does not drift to the Baltic Proper. The eastern part of the gulf exhibits the highest surface concentrations of particles influenced by the Neva River. In the water column, MP concentrations were notably high in shallow coastal areas, decreasing gradually offshore. Potential MP accumulation zones were identified primarily between longitudes 28&#xb0;E and 30&#xb0;E, particularly near the major rivers Narva and Kymi and in the easternmost gulf related to the Neva River discharge. The MP concentrations in the surface layer and water column were higher in winter while settling was more intense in summer. Short-term variability in the surface layer was caused by (sub)mesoscale advection and divergence/convergence, while in the near-bottom layer, strong bottom currents and consequent resuspension elevated the concentrations.</p>
</abstract>
<kwd-group>
<kwd>microplastic</kwd>
<kwd>microplastic pathways</kwd>
<kwd>hydrodynamic modeling</kwd>
<kwd>Lagrangian particles</kwd>
<kwd>GETM</kwd>
<kwd>ERGOM</kwd>
<kwd>Gulf of Finland</kwd>
<kwd>Baltic Sea</kwd>
</kwd-group>
<counts>
<fig-count count="11"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="108"/>
<page-count count="17"/>
<word-count count="7627"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Coastal Ocean Processes</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Microplastics (MP), which are particles smaller than 5 mm, can be found in various aquatic environments, including the oceans, seas, estuaries and rivers (<xref ref-type="bibr" rid="B14">Cole et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B34">Jambeck et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B84">Set&#xe4;l&#xe4; et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B64">Matja&#x161;i&#x10d; et&#xa0;al., 2023</xref>). The significant increase in plastic production since the early 1970s has raised numerous concerns about plastic pollution in aquatic systems. It has been estimated that over 170 trillion plastic particles are floating in the world&#x2019;s oceans (<xref ref-type="bibr" rid="B21">Eriksen et&#xa0;al., 2023</xref>), and their presence is also increasing in the seabed, coastlines, and marine biota (<xref ref-type="bibr" rid="B7">Barnes et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B89">Suaria and Aliani, 2014</xref>; <xref ref-type="bibr" rid="B58">Llorca et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B64">Matja&#x161;i&#x10d; et&#xa0;al., 2023</xref>). Despite substantial efforts and initiatives to reduce plastic usage, global annual plastic waste production is projected to continue rising in the coming years. By 2025, the United Nations Sustainable Development Goal 14.1 aims to reduce marine pollution, including plastics.</p>
<p>In Europe, The Marine Strategy Framework Directive (2008/56/EC, European Commission, 2008) (MFSD) identified anthropogenic litter as a dominant pressure and a main source of impact on coastal habitats. The MSFD establishes requirements for the EU (European Union) member states to achieve and maintain a good environmental status in their marine environments, as well as to prevent any future deterioration including the MSFD descriptor D10. In addition, the European Chemical Agency (EGCHA) has proposed restriction of MP in many products within the EU/EEA (European Economic Area) region, with the goal of preventing or minimizing their discharge into the environment (<xref ref-type="bibr" rid="B22">European Chemicals Agency, 2019</xref>). In 2021, the European Union also banned single-use plastics within its member states (<xref ref-type="bibr" rid="B29">Harvey and Watts, 2018</xref>).</p>
<p>According to <xref ref-type="bibr" rid="B24">GESAMP (2019)</xref>, the marine environment can be infiltrated by plastic through multiple entry points, including riverine systems, shoreline activities, shipping, and atmospheric deposition. Various studies (<xref ref-type="bibr" rid="B108">Ziajahromi et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B66">Mintenig et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B37">Kay et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B75">Prata, 2018</xref>; <xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>) have highlighted the significant influence of human activities on MP deposition. Among these activities, Wastewater Treatment Plants (WWTPs) are recognized as a significant emission pathway. For example, Municipal WWTPs have shown high efficiency in removing MP (<xref ref-type="bibr" rid="B13">Carr et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B93">Talvitie et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B26">Gies et&#xa0;al., 2018</xref>); however, untreated WWTP effluents exhibit elevated MP concentrations (<xref ref-type="bibr" rid="B91">Sun et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>). <xref ref-type="bibr" rid="B6">Baresel and Olshammar (2019)</xref> proposed that MP retention in WWTPs based on their respective treatment stages ranges from 85% to 98% in the Baltic Sea region. Despite this relatively high overall removal efficiency, WWTPs are still considered a significant MP emission pathway in the Baltic Sea region due to the substantial volumes of wastewater they process (<xref ref-type="bibr" rid="B6">Baresel and Olshammar, 2019</xref>). In the Baltic Sea, wastewater and stormwater plants are typically separated (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>). Sewer overflows, comprising stormwater and untreated wastewater can substantially contribute to the MP load in the environment (<xref ref-type="bibr" rid="B60">Magnusson, 2016</xref>; <xref ref-type="bibr" rid="B20">Dris et&#xa0;al., 2018</xref>). During periods of heavy precipitation, stormwater serves as a critical entry point for MP into the aquatic environment. <xref ref-type="bibr" rid="B6">Baresel and Olshammar (2019)</xref> suggest that the yearly discharge from sewer overflows is comparable in magnitude to that of treated wastewater.</p>
<p>Several studies have indicated that rivers are a primary source of MP and play a crucial role in transporting plastic waste into oceans (<xref ref-type="bibr" rid="B34">Jambeck et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B86">Siegfried et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B83">Schrank et&#xa0;al., 2022</xref>). Rivers flowing through highly populated cities with significant industrial activity along their banks may serve as an important source of MP in the estuarine bays such as the Gulf of Finland (GoF) in the Baltic Sea (<xref ref-type="bibr" rid="B62">Martyanov et&#xa0;al., 2021</xref>). It has been estimated that between 1.15 and 2.41 million tons or more of plastics are deposited annually into oceans via rivers (<xref ref-type="bibr" rid="B46">Lebreton et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B82">Schmidt et&#xa0;al., 2017</xref>). Numerous studies have discussed the pollution patterns of large rivers and provided insights into the regional and global factors responsible for MP pollution in the water column and sediments (<xref ref-type="bibr" rid="B64">Matja&#x161;i&#x10d; et&#xa0;al., 2023</xref>). High variability in MP concentration can be seen in both the water column and sediments depending on factors such as sampling methodology, anthropogenic activities and the size of the catchment area (<xref ref-type="bibr" rid="B85">She et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B64">Matja&#x161;i&#x10d; et&#xa0;al., 2023</xref>). Additionally, a significant proportion of marine beach litter is attributed to the input of plastic waste into rivers (<xref ref-type="bibr" rid="B103">Veerasingam et&#xa0;al., 2016</xref>). However, it is important to note that this study does not consider river retention in its analysis.</p>
<p>The Baltic Sea, located in northern Europe, is known as one of the largest brackish water bodies in the world (<xref ref-type="bibr" rid="B30">HELCOM, 2023</xref>). With a catchment area four time larger than its surface area (372,858 km<sup>2</sup>) (<xref ref-type="bibr" rid="B61">Marko and Urs, 2013</xref>) and an average depth of 55m, the Baltic Sea faces significant challenges related to marine litter (<xref ref-type="bibr" rid="B30">HELCOM, 2023</xref>). Coastal areas along the Baltic Sea exhibit significant concentration of beach litter (<xref ref-type="bibr" rid="B30">HELCOM, 2023</xref>). Plastic materials make up the most frequently encountered marine litter in the Baltic Sea (<xref ref-type="bibr" rid="B30">HELCOM, 2023</xref>). As of 2023, HELCOM&#x2019;s aim to substantially decrease plastic waste and mitigate its harmful effects on coastal and marine ecosystems remains unfulfilled (<xref ref-type="bibr" rid="B30">HELCOM, 2023</xref>). The Baltic Sea receives a substantial volume of water from various rivers, with an average combined flow rate of approximately 14,085 m<sup>3</sup>/s (<xref ref-type="bibr" rid="B65">Meier and Kauker, 2003</xref>). Due to the extended residence time of pollutants in the Baltic Sea during the water renewal period, which can last up to 30 years (<xref ref-type="bibr" rid="B47">Lepp&#xe4;ranta and Myrberg, 2009</xref>), the pollutants present in the Baltic Sea have a significant impact on the aquatic environment. Consequently, it is reasonable to assume that the Baltic Sea serves as a major hotspot for plastics, primarily through river discharge. Large impacts of riverine inputs as critical pathways for plastics into marine environments has also been identified in other parts of the world (<xref ref-type="bibr" rid="B105">Vianello et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B95">Uaciquete et&#xa0;al., 2024</xref>).</p>
<p>The GoF is an elongated estuarine basin situated in the northeastern region of the Baltic Sea with an average depth of 37 m and a maximum depth of 123 m (<xref ref-type="bibr" rid="B47">Lepp&#xe4;ranta and Myrberg, 2009</xref>). The gulf stretches approximately 400 km in length, with a width that varies between 48 and 135 km (<xref ref-type="bibr" rid="B2">Alenius et&#xa0;al., 1998</xref>). There is a free water exchange between the GoF and BP at the western border, and fresh water is discharged mostly to the eastern part of the GoF. Several studies have reported the presence of MP in the GoF (<xref ref-type="bibr" rid="B55">Lips et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B84">Set&#xe4;l&#xe4; et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B97">Uurasj&#xe4;rvi et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>). However, the knowledge about the spatial and temporal variation of MPs in the Baltic Sea is limited (<xref ref-type="bibr" rid="B1">Aigars et&#xa0;al., 2021</xref>). In addition, the methodology for acquiring information about MPs can vary based on the instruments utilized, mesh size, sampling depth, and the extent of the sampling area (<xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B85">She et&#xa0;al., 2022</xref>).</p>
<p>Modeling the movement and fate of MP is particularly relevant in semi-enclosed systems like the Gof, where limited exchange and localized inputs contribute to accumulation of marine debris (<xref ref-type="bibr" rid="B94">Tsiaras et&#xa0;al., 2021</xref>). Eulerian and Lagrangian models are commonly used in such simulations (<xref ref-type="bibr" rid="B8">Bigdeli et&#xa0;al., 2022</xref>). Lagrangian modeling, also known as particle tracking modeling, tracks individual particles (<xref ref-type="bibr" rid="B87">Siht et&#xa0;al., 2025</xref>, in press), while an Eulerian approach considers advection and diffusion at specific locations (<xref ref-type="bibr" rid="B8">Bigdeli et&#xa0;al., 2022</xref>). <xref ref-type="bibr" rid="B73">P&#xe4;rn et&#xa0;al. (2023)</xref> employed a combination of a hydrodynamic model and a particle tracking model to understand the transport and fate of marine litter including accumulation areas in the Baltic Sea. <xref ref-type="bibr" rid="B63">Martyanov et&#xa0;al. (2023)</xref> considered different initial fall velocities of suspended MP to study their distribution in the eastern GoF. <xref ref-type="bibr" rid="B80">Schernewski et&#xa0;al. (2021)</xref> incorporated emission scenarios from WWTPs and combined sewerage plants into their model to estimate the fate of plastics in the Baltic Sea environment. The GETM (General Estuarine Transport Model) ocean circulation model has been utilized in several studies, including those conducted by <xref ref-type="bibr" rid="B80">Schernewski et&#xa0;al. (2021)</xref> and <xref ref-type="bibr" rid="B72">Osinski et&#xa0;al. (2020)</xref>, to analyze the transportation of MP in the Baltic Sea. However, these studies did not include the impact of biofouling on the buoyancy of floating MP and their removal process through sinking and sedimentation (<xref ref-type="bibr" rid="B72">Osinski et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B80">Schernewski et&#xa0;al., 2021</xref>). Modeling studies in the Baltic Sea (<xref ref-type="bibr" rid="B62">Martyanov et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B23">Frishfelds et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B68">Murawski et&#xa0;al., 2022</xref>), North Sea (<xref ref-type="bibr" rid="B16">Cuttat, 2018</xref>), and Mediterranean Sea (<xref ref-type="bibr" rid="B94">Tsiaras et&#xa0;al., 2021</xref>) have incorporated biofouling of MP particles that is important to simulate their fate in the marine environment accurately (<xref ref-type="bibr" rid="B68">Murawski et&#xa0;al., 2022</xref>).</p>
<p>The objective of this study is to provide an overview of the pathways and accumulation areas of MP in the GoF using a multi-year high-resolution model simulation and realistic loads from the rivers and WWTPs. We chose Lagrangian particle tracking model approach, describing MP as Super-Individuals (SI; (<xref ref-type="bibr" rid="B79">Scheffer et&#xa0;al., 1995</xref>) to improve computational efficiency, with each SI representing a group of particles. We have also conducted a series of sensitivity experiments aimed at gaining a deeper insight into the impact of various processes, such as mixing, beaching, resuspension, and biofouling (<xref ref-type="bibr" rid="B87">Siht et&#xa0;al., 2025</xref>, in press). In the present study, a 3-year model simulation was conducted to identify potential MP accumulation patterns in the surface layer, water column and sediments.</p>
<p>The paper is organized as follows: it begins with a description of the hydrodynamic model, biogeochemistry model, and Lagrangian particle tracking model, along with MP input data sets. It is followed by an analysis of the model results, aiming to uncover the MP pathways and accumulation areas in the GoF. Finally, the results are discussed, and conclusions are derived.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Hydrodynamic model and setup</title>
<p>General Estuarine Transport Model (GETM) (<xref ref-type="bibr" rid="B11">Burchard and Bolding, 2002</xref>) has been used to simulate the circulation and density fields of the Baltic Sea and GoF in this study. GETM is a hydrostatic, three-dimensional primitive equation model that has embedded adaptive vertical coordinates (<xref ref-type="bibr" rid="B33">Hofmeister et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B38">Klingbeil et&#xa0;al., 2018</xref>), which significantly reduces the numerical mixing in the simulations (<xref ref-type="bibr" rid="B27">Gr&#xe4;we et&#xa0;al., 2015</xref>). The vertical mixing (viscosity and diffusion) in the GETM is calculated with two equation <italic>k-&#x3b5;</italic> model via coupling with General Ocean Turbulence Model (GOTM) (<xref ref-type="bibr" rid="B10">Burchard, 2001</xref>; <xref ref-type="bibr" rid="B12">Canuto et&#xa0;al., 2001</xref>) and the sub-grid horizontal mixing with Smagorinsky parameterization (<xref ref-type="bibr" rid="B88">Smagorinsky, 1963</xref>).</p>
<p>The biogeochemistry model ERGOM (<xref ref-type="bibr" rid="B69">Neumann et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B71">Neumann and Schernewski, 2008</xref>) is coupled with the hydrodynamic model via Framework Aquatic Biogeochemical Models (FABM; <xref ref-type="bibr" rid="B9">Bruggeman and Bolding, 2014</xref>) and has been used to calculate the chlorophyll-a concentration for biofouling of MP in the Gulf of Finland. In short, ERGOM has 12 state variables and describes a nitrogen and phosphorus cycle, although part of the phosphorus is considered with the N:P ratio (<xref ref-type="bibr" rid="B78">Redfield, 1934</xref>). More details about the ERGOM model can be found from in (<xref ref-type="bibr" rid="B76">Radtke et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B70">Neumann et&#xa0;al., 2022</xref>) and references therein.</p>
<p>We are using a three-level nested modelling system. The whole Baltic Sea has been simulated with a horizontal grid step of 1 nautical mile (approximately 1852 m) and 50 adaptive vertical layers (<xref ref-type="bibr" rid="B27">Gr&#xe4;we et&#xa0;al., 2015</xref>). Medium-resolution model based on the settings described in <xref ref-type="bibr" rid="B107">Zhurbas et&#xa0;al. (2018)</xref> and <xref ref-type="bibr" rid="B51">Liblik et&#xa0;al. (2020</xref>, <xref ref-type="bibr" rid="B52">2022)</xref> has a horizontal grid spacing of 0.5 nautical miles and covers the central Baltic Proper along with the Gulf of Finland and the Gulf of Riga. The high-resolution model covers the Gulf of Finland and has a horizontal grid spacing of 0.125 nautical miles. The number of adaptive layers in medium- and high-resolution runs is 60. Spatially interpolated results with hourly resolution from the coarse-resolution model are used for the boundary conditions in the medium-resolution model and from the medium-resolution model are used for the boundary conditions in the high-resolution model.</p>
<p>Atmospheric forcing at the sea surface (wind stress and heat flux) is calculated offline from the ERA5 re-analysis (<xref ref-type="bibr" rid="B31">Hersbach et&#xa0;al., 2020</xref>). Freshwater input to the models is based on the runoff data compiled for the Baltic Model Intercomparison Project (<xref ref-type="bibr" rid="B28">Gr&#xf6;ger et&#xa0;al., 2022</xref>) by <xref ref-type="bibr" rid="B99">V&#xe4;li et&#xa0;al. (2019)</xref> and Estonian rivers have been corrected by the input estimates from EstModel (<ext-link ext-link-type="uri" xlink:href="https://estmodel.app/en/#/estimates">https://estmodel.app/en/#/estimates</ext-link>, last access 10.09.2023).</p>
<p>The simulation period for the high-resolution model was from 2018 to mid-2021. The runs were initially started from a motionless state, i.e. current velocity components and sea surface height were set to zero. Previous studies have shown that the adjustment of the wind-driven circulation in the Baltic Sea takes only a few days (e.g. <xref ref-type="bibr" rid="B40">Krauss and Br&#xfc;gge, 1991</xref>; <xref ref-type="bibr" rid="B56">Lips et&#xa0;al., 2016</xref>).</p>
<p>For more details of the model setup and validation, the reader is referred to (<xref
ref-type="bibr" rid="B87">Siht et&#xa0;al 2025,</xref> in press).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Lagrangian particle model</title>
<p>We employed the Lagrangian particle tracking model described by (<xref ref-type="bibr" rid="B87">Siht et&#xa0;al 2025,</xref> in review) to track virtual MP particles. The particle tracking model used the 12-hour 3-dimensional output of the high-resolution GETM setup for particle transport. Beyond advection, our model accounted for several additional processes: 1) dispersion, 2) beaching, 3) biofouling, and 4) resuspension.</p>
<p>Our model computed the horizontal diffusion coefficient for particle dispersion based on the current shear velocity, following the Smagorinsky method (<xref ref-type="bibr" rid="B88">Smagorinsky, 1963</xref>). Here, we set the Smagorinsky coefficient C<sub>s</sub> to 0.2.</p>
<p>Beaching was implemented through a timer-based approach, where particles became beached after a specified duration in the beach zone. In our simulations, all particle types shared a uniform beaching time of 10 days. The beaching zone was defined as the sea cell nearest to the shoreline (i.e., 250m). Resuspension from beaches was not implemented, i.e., once beached, the particle remained still and was effectively removed from the simulation.</p>
<p>Following <xref ref-type="bibr" rid="B68">Murawski et&#xa0;al. (2022)</xref>, biofouling is described as a saturated growth process that depends on the maximum biofilm thickness and the growth time scale. The biofouling process was initiated when chlorophyll-a concentration exceeded 1.1 mg m<sup>-3</sup>. In the current simulations, the maximum biofilm thickness was set to 6.7% of the initial particle radius, and the growth time scale was set to 20 days.</p>
<p>Negatively buoyant particles could settle and be resuspended when the critical shear velocity was exceeded. The vertical velocity gained from resuspension was proportional to the local bottom friction velocity.</p>
<p>The simulation period for the particle tracking model was from 2018-02-05 to 2021-01-01. New particle coordinates were calculated with a time step of 600 seconds. At each time step, the current velocity components (and other hydrological parameters) were interpolated in time and space to the exact particle locations. The particle coordinates were saved at 12-hour intervals. A total of approximately 146 million particles were released during the simulation.</p>
<sec id="s2_2_1">
<label>2.2.1</label>
<title>Calculations</title>
<p>The concentrations of MP particles in the surface layer were defined for the water layer from the sea surface to the geopotential height of -1 m. The water column was defined as extending from the sea surface to the uppermost layer of the seabed, and the concentrations were integrated over the entire column. The meridionally integrated values refer to the temporal average of integrated values from south to north, which essentially describes the cross-sectional profile of the entire model domain. All mean concentration fields were spatially smoothed with a 2.5 km window to reduce the high-frequency variability. The size of the window aligns with the local baroclinic Rossby radius of approximately 2-4 km (<xref ref-type="bibr" rid="B3">Alenius et&#xa0;al., 2003</xref>). The results presented in the current study are based on two model years (2019-2020) after a spin-up period of one year.</p>
</sec>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Emission scenarios</title>
<sec id="s2_3_1">
<label>2.3.1</label>
<title>Microplastics sources and emission calculations</title>
<p>The fate of MP in the marine environment relies heavily on the density of plastics. Density serves as a determining factor in classifying plastics into two main categories: floating and sinking types. Floating plastics consist of high- and low-density polyethylene (PE) with a density range of 915&#x2013;970 kg/m<sup>3</sup>, as well as polypropylene (PP) with a density range of 890&#x2013;920 kg/m<sup>3</sup> (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>). Sinking plastics include rigid polyvinyl chloride (PVC) with a density range of 1300&#x2013;1450 kg/m<sup>3</sup> and polyethylene terephthalate (PET) with a density of 1380 kg/m<sup>3</sup> (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>). PP, PE, and PET are the most prevalent plastics observed in aquatic environments (<xref ref-type="bibr" rid="B39">Kooi and Koelmans, 2019</xref>). In this study, two main sources of plastics were considered:</p>
<list>
<list-item>
<p>a. MP inputs from WWTPs were estimated based on the study by <xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al. (2020)</xref>. The MP load into the GoF catchment (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A, B</bold>
</xref>) was calculated using treated wastewater discharge data and particle concentrations in raw water. The average minimum and maximum MP concentrations in raw wastewater were based on literature (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>), and we considered maximum MP concentrations (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>), and river retention was not taken into consideration.</p>
</list-item>
<list-item>
<p>b. MP inputs from rivers were selected as another major source of marine plastic pollution because they are responsible for a high level of land-based sources, such as mismanaged waste (<xref ref-type="bibr" rid="B34">Jambeck et&#xa0;al., 2015</xref>). The variability in observed MP concentrations in rivers is notable (<xref ref-type="bibr" rid="B15">Constant et&#xa0;al., 2020</xref>) partly caused by the choice of sampling method, the type of instrument used, the lower size limit of MPs being sampled, the season during which sampling takes place, and the specific processing and analysis methods employed. According to <xref ref-type="bibr" rid="B83">Schrank et&#xa0;al. (2022)</xref>, surface water samples from the Danube River had an average concentration of 48.7 particles/m<sup>3</sup>. The average concentration of plastic in the T&#xea;t River was 42 particles/m<sup>3</sup> (<xref ref-type="bibr" rid="B15">Constant et&#xa0;al., 2020</xref>), while the Narva River had an average of 47 particles/m<sup>3</sup> (<xref ref-type="bibr" rid="B57">Lips et&#xa0;al., 2020</xref>). Based on the above literature and assuming that only a quarter comes from WWTPs (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>), in this study, we considered the MP amount in the rivers (without contribution of WWTPs) to be 35 particles/m<sup>3</sup>. We calculated the daily load of MP from river sources (particles/day) by multiplying the concentration of 35 particles/m<sup>3</sup> by the river discharge in the GoF (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1D</bold>
</xref>).</p>
</list-item>
</list>
<p>The floating and sinking behavior of MP is not only determined by their density but is also influenced by their size and shape. In our study, we focused on MP with a size range of 20&#x2013;500 &#x3bc;m, which we divided into two classes: 20-200 and 200-500 &#x3bc;m. Based on <xref ref-type="bibr" rid="B80">Schernewski et&#xa0;al. (2021)</xref> and <xref ref-type="bibr" rid="B41">Kuddithamby et&#xa0;al. (2024)</xref>, we assumed that 90% of the MP would fall into the 20-200 &#x3bc;m size class. Additionally, we assumed that the MP had a spherical shape.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Panel <bold>(A, B)</bold> represent a map of the Baltic Sea and a map of the WWTPs (blue dots) and river (red dots) emissions points at the coast of the GoF. Yellow dots represent the cities mentioned in the study. The red line indicates the thalweg along the GoF; panels <bold>(C, D)</bold> display the emissions of PET and PP/PE MP particles (20-500 um) from WWTPs and riverine sources entering the GoF. The diamond markers in panel (1C) represent emissions from inland WWTPs.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g001.tif"/>
</fig>
</sec>
<sec id="s2_3_2">
<label>2.3.2</label>
<title>Emission scenarios for PP/PE and PET</title>
<p>Calculated emissions from WWTPs and rivers serve as the inputs for the two main scenario runs.</p>
<p>In Scenario 1, the focus was on evaluating the loads of PET and PP/PE from WWTP sources, specifically considering the 20-500 &#x3bc;m MP size fraction. To gain a deeper understanding, this size fraction was further divided into two sub-ranges: small particles (20-200 &#x3bc;m) and large particles (200-500 &#x3bc;m) for both PET and PP/PE.</p>
<p>In Scenario 2, the analysis encompassed PET and PP/PE loads from riverine sources, taking into account the 20-500 &#x3bc;m MP size fractions. Like Scenario 1, this size fraction was divided into two sub-ranges: small particles (20-200 &#x3bc;m) and large particles (200-500 &#x3bc;m) for both PET and PP/PE.</p>
<p>Thus, eight scenario runs were simulated in total, representing two types of MP, two size fractions, and two emission pathways. It is important to note that all scenarios assume a constant daily MP emission throughout the entire simulation period (<xref ref-type="table" rid="T1">
<bold>Table 1</bold>
</xref>), facilitating a thorough evaluation of MP pollution. Thus, eight scenario runs were simulated in total, representing two types of MP, two size fractions, and two emission pathways.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Distribution of total emissions of PET and PP/PE particles from WWTPs and rivers per day.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" colspan="5" align="left">Emissions to the GoF catchment</th>
</tr>
<tr>
<th valign="top" align="left">Sources</th>
<th valign="top" align="left">20-500 &#x3bc;m</th>
<th valign="top" align="left">20-200 &#x3bc;m</th>
<th valign="top" align="left">200-500 &#x3bc;m</th>
<th valign="top" align="left">% share</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">WWTP - (PET)</td>
<td valign="top" align="left">1.55E+09</td>
<td valign="top" align="left">1.40E+09</td>
<td valign="top" align="left">1.55E+08</td>
<td valign="top" rowspan="2" align="left">24.3</td>
</tr>
<tr>
<td valign="top" align="left">WWTP - (PP/PE)</td>
<td valign="top" align="left">1.95E+09</td>
<td valign="top" align="left">1.76E+09</td>
<td valign="top" align="left">1.95E+08</td>
</tr>
<tr>
<td valign="top" align="left">River - (PET + PP/PE)</td>
<td valign="top" align="left">1.09E+10</td>
<td valign="top" align="left">9.86E+09</td>
<td valign="top" align="left">1.09E+09</td>
<td valign="top" align="left">75.7</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Overall variability of microplastic distribution</title>
<p>The time series of the share of particles in different states is shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>. The overall spin-up of the model was relatively fast &#x2013; after initialization, the share of particles in the water column dropped quickly to approximately 15%, while the share of sedimented particles stabilized between 75 &#x2013; 80%. Meanwhile, the share of particles at the boundary reached approximately 1%, and the share of beached particles reached 10% during the spin-up period. The small light particles were the most abundant in the water column, and the large heavy particles were the least common (see <xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2A, B</bold>
</xref>). Most particles that left the GoF (reached the boundary) also belonged to the small light class (3%), whereas the large light particles beached the most (28%). Approximately 65% of the small light and large light particles and 92% and 95% of the small heavy and large heavy particles, respectively, settled after 3 years of simulation.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Time series of the particle budget in different classes for the Gulf of Finland. <bold>(A)</bold> water column, <bold>(B)</bold> bottom, <bold>(C)</bold> boundary, and <bold>(D)</bold> beached. All time series have been smoothed using a 7-day moving window.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g002.tif"/>
</fig>
<sec id="s3_1_1">
<label>3.1.1</label>
<title>Variability of surface concentrations</title>
<p>The average concentration of MP particles in the surface layer is shown in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>. The concentrations were larger for the light particles (PP/PE) compared to heavy particles (PET) but high for both types near major coastal sources (<xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3E, F</bold>
</xref>). Since the riverine input to the Russian part was six-fold greater than the combined input to the Estonian and Finland parts, the highest concentrations of riverine-origin MP were in the eastern part of the gulf (<xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3A, B</bold>
</xref>). The WWTP-origin particle concentrations were high in the vicinity of larger cities (St. Petersburg, Helsinki and Tallinn, <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3C, D</bold>
</xref>). The overall mean riverine origin particle concentrations for PP/PE within the model domain were about 3.8 particles/m<sup>2</sup>, but the maximum values exceeded 50 particles/m<sup>2</sup> in the eastern part of the gulf (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). The PET particles did not disperse as extensively as PP/PE particles from the eastern part of the gulf towards the west. PET particles from WWTPs were primarily gathered near Helsinki and in the eastern part of the gulf (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). PP/PE particles from WWTPs had a similar distribution to the PET, but dispersion was higher, and the impact of Tallinn was more pronounced. On average, the PET and PP/PE particles released from WWTPs had concentrations of 0.1 and 1.0 particles/m<sup>2</sup> within the model domain, respectively. When considering particles from both rivers and WWTPs, the average surface concentrations for PET and PP/PE particles were 1.4 particles/m<sup>2</sup> and 4.8 particles/m<sup>2</sup>, respectively. The findings indicate that most of the MP particles in the central gulf are predominantly retained near their source areas, with limited long-distance transport.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Mean concentrations of PET and PP/PE MP particles (20 - 500 &#x3bc;m) in the surface layer of the GoF in 2019-2020. Panels <bold>(A, B)</bold> represent the riverine origin PET and PP/PE particles; panels <bold>(C, D)</bold> WWTP origin PET and PP/PE particles; panels <bold>(E, F)</bold> display composite maps of different origin PET and PP/PE particles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g003.tif"/>
</fig>
</sec>
<sec id="s3_1_2">
<label>3.1.2</label>
<title>Water column</title>
<p>
<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref> provides an overview of the mean spatial distributions of vertically integrated MP amounts in the water column during 2019 and 2020. The occurrence of particles in the water column was larger in the eastern part than in the western part of the gulf, where concentrations were much smaller for both the riverine and WWTP-origin particles. Heavy particles tended to remain closer to sources (rivers and WWTPs) in the eastern part, but high integrated concentrations can also be seen along the thalweg of the gulf in the western part.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Mean spatial distribution of vertically integrated concentrations of PET and PP/PE (20-500 mm) in the GoF in 2019-2020. Panels <bold>(A, B)</bold> represent the riverine origin PET and PP/PE particles; panels <bold>(C, D)</bold> WWTP origin PET and PP/PE particles; panels <bold>(E, F)</bold> display composite maps of different origin PET and PP/PE particles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g004.tif"/>
</fig>
<p>The model data suggests that a gradual decrease in MP concentration was likely influenced by both the configuration of the gulf and the distance from the main sources (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). Particularly in shallower areas, to the east from 28&#xb0;E, there was an elevated presence of riverine PET and PP/PE particles (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, B</bold>
</xref>). Conversely, in the region to the west from 28&#xb0;E, where the Neva River has less influence, lower concentrations of riverine-origin PET and PP/PE particles were observed. The mean concentrations of WWTP-origin particles were higher in both the eastern and western regions, with lower concentrations between 26&#xb0;E and 28&#xb0;E (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4C, D</bold>
</xref>). This variation in WWTP-origin PET and PP/PE particles is likely due to the locations of the main input sources. The region between 26&#xb0;E and 28&#xb0;E receives less pollution from WWTPs, resulting in lower concentrations of WWTP-origin particles in this area.</p>
<p>
<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref> represents the meridionally integrated concentrations from south to north in the water column during 2019 and 2020. From the surface to the seabed, PET particles had lower concentrations, while PP/PE particles were more prevalent, likely due to the higher density of PET particles, causing them to sink more quickly (<xref ref-type="fig" rid="f5">
<bold>Figures&#xa0;5A&#x2013;D</bold>
</xref>). A characteristic vertical distribution of particles with high concentrations near the sea surface and the seabed and a minimum in the intermediate water layer is revealed for both particle types in the deeper areas of the gulf.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Mean meridionally integrated concentration of PET and PP/PE MP particles (20 - 500 &#x3bc;m) in the water column of the GoF in 2019-2020. Panels <bold>(A, B)</bold> represent the riverine origin PET and PP/PE particles; panels <bold>(C, D)</bold> WWTP origin PET and PP/PE particles; panels <bold>(E, F)</bold> display composite maps of different origin PET and PP/PE particles. The bathymetry data along the latitude axis is represented as the maximum depth values for each longitude coordinate.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g005.tif"/>
</fig>
</sec>
<sec id="s3_1_3">
<label>3.1.3</label>
<title>Accumulation of particles</title>
<p>Sedimentation of particles of different origins and classes is shown in <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>. Sedimentation of the MP has occurred almost on the whole seabed of the gulf. The largest concentrations in the seabed are in the eastern part of the gulf, similar to those in the water column. The heavy particles (PET) tend to sink quickly and accumulate in the coastal areas, with notable amounts observed in Neva Bay, Narva Bay and near Kotka on the northern coast. Relatively high values were also in deeper areas of the central part of the gulf (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>). WWTP-origin PET particles had the highest values in the western and eastern parts of the gulf, while lower accumulation rates were revealed between 26.5 and 28&#xb0;E (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6C</bold>
</xref>).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Mean spatial concentrations of PET and PP/PE MP particles (20 - 500 &#x3bc;m) on the seabed of the GoF in 2019-2020. Panels <bold>(A, B)</bold> represent the riverine origin PET and PP/PE particles; panels <bold>(C, D)</bold> WWTP origin PET and PP/PE particles; panels <bold>(E, F)</bold> display composite maps of different origin PET and PP/PE particles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g006.tif"/>
</fig>
<p>The composite maps indicate the overall accumulation (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6E, F</bold>
</xref>). In principle, the highest concentrations of both heavy and light particles were in the easternmost part of the gulf and Narva Bay. There is a tendency for higher concentrations near the coastline along the southern coast, while in the northern part, the sedimentation is more homogenous (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6F</bold>
</xref>).</p>
</sec>
<sec id="s3_1_4">
<label>3.1.4</label>
<title>Beaching of particles</title>
<p>The accumulation of particles on beaches around the GoF is shown in <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>. The whole coastline of the gulf has been impacted by the MP, although the load varied in space. Overall, more light particles beached compared to the heavy particles &#x2013; the average number of beached particles was nearly 20 times higher for the light particles. Nevertheless, a relatively high number of heavy particles from rivers (&gt; 10<sup>5</sup> particles/m) have beached on the southern shore of Neva Bay. A high number of light particles from rivers have beached in Neva Bay and Narva Bay, and along the Finnish coastline; particles from WWTPs are also numerous around Neva Bay, inside Tallinn Bay, in the vicinity of Helsinki, and at some spots along the northern coast.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Distribution of particle accumulation on beaches over the period 2019&#x2013;2020. Panels <bold>(A, B)</bold> represent the PET and PP/PE particles, respectively, from rivers; panels <bold>(C, D)</bold> focus on PET and PP/PE particles sourced from WWTPs; panels <bold>(E, F)</bold> display PET and PP/PE particles sourced from both rivers and WWTPs. The values have been spatially smoothed with a window length of 10 km.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g007.tif"/>
</fig>
</sec>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Seasonal variability</title>
<sec id="s3_2_1">
<label>3.2.1</label>
<title>Seasonal dynamics</title>
<p>
<xref ref-type="fig" rid="f8">
<bold>Figures&#xa0;8</bold>
</xref> and <xref ref-type="fig" rid="f9">
<bold>9</bold>
</xref> illustrate the seasonal variations of PET and PP/PE particles in the surface layer, water column and sediments during the summer and winter months in the GoF.</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Mean spatial concentration of PET MP particles (20 - 500 &#x3bc;m) sourced from both rivers and WWTPs in different layers of the GoF during the summer months JJA (June, July, and August, panels <bold>(A, C, E)</bold> and winter months DJF (December, January, and February, panels <bold>(B, D, F)</bold>. Panels <bold>(A, B)</bold> illustrate the concentration in the surface layer; panels <bold>(C, D)</bold> focus on concentration in the water column; panels <bold>(E, F)</bold> showcase the concentration in the bottom layer.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g008.tif"/>
</fig>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Mean spatial concentration of PP/PE MP particles (20 - 500 &#x3bc;m) sourced from both rivers and WWTPs in different layers of the GoF during the summer months JJA (June, July, and August) and winter months DJF (December, January, and February). Panels <bold>(A, B)</bold> illustrate the concentration in the surface layer; panels <bold>(C, D)</bold> focus on concentration in the water column; panels <bold>(E, F)</bold> showcase the concentration in the bottom layer.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g009.tif"/>
</fig>
<p>During the summer months (JJA, June-August), PET MP concentrations near the surface were elevated along the northern and southern coasts, with the highest concentrations near St. Petersburg (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8A</bold>
</xref>). Despite lower river runoff and MP loads in winter (DJF, December-February), surface PET concentrations were higher in winter compared to summer (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8B</bold>
</xref>). A similar tendency was observed in the water column, where vertically integrated PET concentrations were higher in winter, likely due to reduced sedimentation and stronger resuspension driven by winter currents. In contrast, the settled particle concentrations were higher in summer, driven by enhanced biofilm formation and stratification (<xref ref-type="fig" rid="f8">
<bold>Figures&#xa0;8E, F</bold>
</xref>).</p>
<p>The mean surface concentration of PP/PE particles was higher in summer than in winter (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9A, B</bold>
</xref>), with higher levels observed in Narva Bay and along the Tallinn and Helsinki coasts. This winter increase likely reflects reduced sedimentation due to weaker biofilm growth. In contrast, summer concentrations were lower near the surface but higher on the seabed, primarily driven by enhanced biofilm formation and stratification, which promote particle settling (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9C&#x2013;F</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Short-term variability</title>
<p>The impact of an upwelling event along the northern coast is shown in <xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10</bold>
</xref>. There was already a small upwelling visible along the northern coast on 18 July (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10A</bold>
</xref>), the surface concentrations (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10D</bold>
</xref>) were strongly inhomogeneous, with the highest values in the easternmost areas of the gulf and patches also appearing along the northern coast and central part of the gulf. As the upwelling intensified on 22 July (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10B</bold>
</xref>), particles began to advert offshore, forming significant surface patches of MP concentrations in the central gulf (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10E</bold>
</xref>). During the upwelling peak (24<sup>th</sup> of July), a large patch of particles was advected southwards, particularly in the areas with colder temperatures, i.e. in the upwelling zone (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10F</bold>
</xref>).</p>
<fig id="f10" position="float">
<label>Figure&#xa0;10</label>
<caption>
<p>Sea Surface Temperature (SST) maps <bold>(A&#x2013;C)</bold> and surface layers <bold>(D&#x2013;F)</bold> during Upwelling conditions along the Finnish coast in the GoF.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g010.tif"/>
</fig>
<p>The impact of near-bottom currents on particle concentrations in the 5 m thick layer above the seabed is shown in <xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11</bold>
</xref>. Stronger near-bottom currents observed on December 6 (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11B</bold>
</xref>) caused increased resuspension of particles from the seabed, as evidenced by higher concentrations in the near-bottom layer (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11E</bold>
</xref>). On December 7, as the bottom currents relaxed (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11C</bold>
</xref>), resuspension levels decreased moderately (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11F</bold>
</xref>). This suggests that while stronger currents lead to particle resuspension, the eventual relaxation of currents allows particles to settle back onto the seabed over time.</p>
<fig id="f11" position="float">
<label>Figure&#xa0;11</label>
<caption>
<p>Snapshots of bottom currents <bold>(A&#x2013;C)</bold>, and water column particles integrated within 5 meters above the seabed <bold>(D&#x2013;F)</bold> in the GoF.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1524585-g011.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>In this study, results from a multi-year (2018-2020) high-resolution model experiment were employed. This model system incorporated hydrodynamic, biogeochemical and Lagrangian particle tracking models to identify the MP pollution&#x2019;s pathways and accumulation zones within the GoF in the surface layer, water column, coastline and bottom layer. Our research utilized the existing datasets for MP distribution estimates and employed advanced modeling techniques.</p>
<p>We considered two distinct particle types: (1) PET particles with density greater than sea water and (2) PP/PE particles with density less than sea water. In addition, particles within a size range of 20 to 500 um were considered and further categorized into small (20 - 200) and large (200 - 500) particles. Generally, this is well supported by literature. PP, PE, PET, PVC, and PS are the most common polymers found worldwide (<xref ref-type="bibr" rid="B104">Vermeiren et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B25">Geyer et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B39">Kooi and Koelmans, 2019</xref>). In China, <xref ref-type="bibr" rid="B59">Lv et&#xa0;al. (2019)</xref> found the following polymer shares: PP (15%), PE (18%), PET (47%) and PS (20%) in the raw wastewater. In the Mediterranean, out of the total MP observed, <xref ref-type="bibr" rid="B74">Pedrotti et&#xa0;al. (2016)</xref> reported that around 86-97% share accounted for the following polymers: PP, PE and polyamides. In our study, we used PP, PE and PET due to their abundance in the environment and as they cover a wide range of densities from 900 to 1300 kg/m<sup>3</sup>. We used the previous load estimates from <xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al. (2020)</xref>, which included WWTP locations and emissions exclusively used within the GoF catchment area. Based on the available literature (<xref ref-type="bibr" rid="B83">Schrank et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B15">Constant et&#xa0;al., 2020</xref>), we have considered mean MP particles found in the rivers. Nevertheless, substantial uncertainties still exist regarding emissions from the WWTPs and MP presence in rivers.</p>
<p>The Baltic Sea receives land-based MPs from rivers and coastal catchment areas (<xref ref-type="bibr" rid="B68">Murawski et&#xa0;al., 2022</xref>). The GoF is under considerable anthropogenic pressure, and as a result, the levels of pollutants, including the MP in water and biota are higher compared to the neighboring basins such as the Gulf of Riga or Baltic Proper (<xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B42">Kuprijanov et&#xa0;al., 2024</xref>). In addition, our results indicate that most of the MP particles entering the GoF do not spread to the Baltic Proper, but instead accumulate within the GoF.</p>
<p>Due to prevailing cyclonic surface circulation in the GoF, floating litter tends, in general, to drift towards the Baltic Proper in higher abundances along the northern coast (<xref ref-type="bibr" rid="B73">P&#xe4;rn et&#xa0;al., 2023</xref>). Our study reveals that the easternmost part of the GoF exhibits the highest levels of MP pollution in the surface layer. Similar tendencies for the GoF have been shown by other modelling studies (e.g. <xref ref-type="bibr" rid="B68">Murawski et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B73">P&#xe4;rn et&#xa0;al., 2023</xref>) due to the large freshwater input from the Neva River. Pollution levels were notably reduced in the central gulf, with concentrations at least an order of magnitude smaller. Rivers discharge freshwater and substances in amounts not typically found in seawater (e.g. <xref ref-type="bibr" rid="B32">Hetland and Hsu, 2013</xref>) and, as a result, river plumes, small or large, with high concentrations of tracers and plume fronts in the vicinity of sources are formed. Five river plume fronts were noticeable in the study area associated with the Neva River, Luga River, Narva River and Kymi River (<xref ref-type="bibr" rid="B92">Suursaar et&#xa0;al., 2021</xref>). Nevertheless, none of these fronts are stationary as they undergo spatial excursions and other dynamic transformations (<xref ref-type="bibr" rid="B92">Suursaar et&#xa0;al., 2021</xref>), and consequently, we could not detect regions with persistently high MP concentrations at these frontal regions. However, such convergent density fronts are characterized by relatively large vertical velocities (<xref ref-type="bibr" rid="B17">D&#x2019;Asaro et&#xa0;al., 2020</xref>) that likely restrict MP transport over long horizontal distances. Additionally, quasi-persistent eddy activity may contribute to such a high number of plastics near the emission areas (<xref ref-type="bibr" rid="B5">Andrejev et&#xa0;al., 2004</xref>; <xref ref-type="bibr" rid="B73">P&#xe4;rn et&#xa0;al., 2023</xref>).</p>
<p>Our simulations revealed that both the PET and PP/PE particles predominantly accumulated in the seabed in close proximity to coastal regions and emission points. The accumulation areas of lighter PP/PE particles extended further offshore. Due to their negative buoyancy, PET particles consistently descend into the water column, ultimately settling on the seabed, particularly near coastal areas. Recent research, using an Eulerian modeling approach, also reported the accumulation of PET particles in shallow coastal waters of the Baltic Sea (<xref ref-type="bibr" rid="B81">Schernewski et&#xa0;al., 2020</xref>). In contrast, PP/PE particles, initially buoyant, remained suspended longer before sinking. This coastal accumulation was particularly evident near riverine sources such as the Neva River estuary and the Narva Bay. The shallow nature of the GoF, with an average depth of 37 m (<xref ref-type="bibr" rid="B47">Lepp&#xe4;ranta and Myrberg, 2009</xref>), contributes to higher deposition rates in these areas. <xref ref-type="bibr" rid="B43">Kuprijanov et&#xa0;al. (2021)</xref> reported similar patterns of hazardous substance accumulation in shallow areas, such as Neva Bay and Finnish coastal inlets, though MP accumulation may persist longer in deeper areas.</p>
<p>Resuspension events, driven by near-bottom currents &gt; 30 cm s<sup>-1</sup>, occasionally &gt; 50 cm s<sup>-1</sup> (<xref ref-type="bibr" rid="B48">Liblik et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B77">Rasmus et&#xa0;al., 2015</xref>; <xref ref-type="bibr" rid="B90">Suhhova et&#xa0;al., 2018</xref>), or wave-induced shear stress (<xref ref-type="bibr" rid="B35">J&#xf6;nsson et&#xa0;al., 2005</xref>), can remobilize MPs from sediments back into the water column gulf. This dynamic interplay of deposition and resuspension highlights the importance of hydrodynamic forces in redistributing MPs in the current study.</p>
<p>The beaching of particles occurred almost throughout the entire GoF. The hotspots were mostly in bays with limited access to the open sea, e.g. Neva Bay, Tallinn Bay, and multiple locations on the northern coast. Previous studies have highlighted similar trends, with higher particle accumulation near the major rivers and urban areas, such as St. Petersburg and the Gulf of Riga (<xref ref-type="bibr" rid="B80">Schernewski et&#xa0;al., 2021</xref>). Our results show that light particles had substantially higher beaching rates compared to heavy particles, likely due to differences in their buoyancy and settling dynamics. Likely, a lot of the heavy PET particles settled in the shallow areas quicker than in 10 days required for a particle to be considered beached as defined in the simulations in the present study. Therefore, a significantly smaller amount of PET was found on beaches compared to light particles. These findings underline the importance of focused monitoring and sampling near key pollution sources, such as the Bay of Tallinn, to validate the simulation results and improve understanding of beaching dynamics.</p>
<p>The model effectively replicates the seasonal variability of MP concentrations observed in the GoF. Spring and summer are periods of heightened biological activity in the Baltic Sea (e.g. <xref ref-type="bibr" rid="B54">Lips et&#xa0;al., 2014</xref>). MP concentrations in the surface layer are lower in summer than winter were consistent with observations in the northern Baltic Proper and the GoF (<xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>). Furthermore, a recent modeling study conducted in Neva Bay, which used a different modeling approach compared to our study, reported a 10-fold decrease in the surface concentration during the summer months compared to the winter (<xref ref-type="bibr" rid="B62">Martyanov et&#xa0;al., 2021</xref>). This seasonal pattern reflects the combined influence of biofouling, hydrodynamics and stratification. In summer, phytoplankton blooms promote biofouling, enhancing the sinking rates of MPs and further leading to their accumulation on the seabed. Vertical stratification, while necessary for biofouling, also acts as a barrier, potentially trapping MPs withing the thermocline (<xref ref-type="bibr" rid="B97">Uurasj&#xe4;rvi et&#xa0;al., 2021</xref>). By late summer, the decay of thermocline and reduced primary production lead to less biofilm formation and reduced organic matter (<xref ref-type="bibr" rid="B4">Almroth-Rosell et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B49">Liblik and Lips, 2011</xref>) which may slow MP sinking.</p>
<p>In contrast, during winter, reduced biofouling, weaker stratification and stronger hydrodynamic activity contribute to higher MP concentrations at the surface. Stronger near-bottom currents can also resuspend particles from the seabed, maintaining elevated MP levels in the water column.</p>
<p>A wind-induced coupled coastal upwelling-downwelling event, which is frequent in the GoF (e.g. <xref ref-type="bibr" rid="B53">Lips et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B96">Uiboupin and Laanemets, 2009</xref>; <xref ref-type="bibr" rid="B44">Laanemets et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B100">V&#xe4;li et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B50">Liblik and Lips, 2017</xref>) was selected as a case study. Previous studies have proposed that coastal upwelling may result in relatively low concentrations of MPs in coastal waters (<xref ref-type="bibr" rid="B18">de Lucia et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B19">Desforges et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>) while high concentration patches can form in the convergence zone of coastal downwelling (<xref ref-type="bibr" rid="B67">Mishra et&#xa0;al., 2022</xref>). In contrast, <xref ref-type="bibr" rid="B45">La Daana et&#xa0;al. (2017)</xref> found no significant difference in MP concentrations between Benguela upwelling sites and other non-upwelling sites.</p>
<p>During the upwelling events, the distribution in the surface layers indicated large particle concentrations converged in the sub-mesoscale stripes or small eddy-like features in the upwelling frontal zone, where the Rossby numbers (not shown) and temperature gradients were high (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10</bold>
</xref>). Previously, <xref ref-type="bibr" rid="B102">V&#xe4;li et&#xa0;al. (2017</xref>, <xref ref-type="bibr" rid="B101">2018)</xref> showed the convergence of particles in the GoF at the locations of the high Rossby number and sub-mesoscale activity. A recent modelling study (<xref ref-type="bibr" rid="B98">V&#xe4;li et&#xa0;al., 2024</xref>) indicated the frequent occurrence of sub-mesoscale activity in the GoF. Observations of the temporal changes of MP concentrations are very challenging in such estuarine systems, where, on the one hand, the MP input from land is high, and, on the other hand, strong thermohaline gradients exist.</p>
<p>Previous studies have shown that episodic events, such as storms or wind-driven upwelling, can generate bottom currents, which can disturb bottom sediments, resuspending MPs into the overlying water column (<xref ref-type="bibr" rid="B72">Osinski et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B106">Zhou et&#xa0;al., 2021</xref>). In areas with high sedimentation rates, where MPs accumulate on the seabed, even short-term increases in current velocity have been shown to result in the release of particles back into the water column (<xref ref-type="bibr" rid="B36">Kane and Clare, 2019</xref>). Our results mirror this process, where we observed a marked decrease in sedimented MP concentrations and an increase in water column particles following periods of intensified bottom currents.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusions and summary</title>
<p>We applied a combination of hydrodynamic, biogeochemical, and Lagrangian particle tracking models to trace MP pathways and identify potential accumulation zones in the GOF. This three-year simulation, with sub-mesoscale permitting horizontal resolution, revealed MP concentrations at the surface, within the water column, and accumulation on the seabed. The results provide critical insights into MP distribution pathways, spatial heterogeneity and the influence of hydrodynamics on MP transport and accumulation.</p>
<p>The study revealed that approximately 75% of MP particles settle on the seabed, making it the primary accumulation area in the GoF. Around 10% of particles were beached, with notable accumulation in Neva Bay, Narva Bay, and parts of the Finnish coastline. Only 1% of MP particles exited the gulf through the western boundary, while 14% remained suspended in the water column, influenced by episodic resuspension events. These findings highlight the GoF&#x2019;s role as a significant retention zone for MPs due to its semi-enclosed geography and hydrodynamic conditions.</p>
<p>MP concentrations were highest near major coastal and riverine sources, particularly in the eastern part of the gulf. Surface concentrations of light particles exceeded those of heavy particles, especially in proximity to WWTPs and river mouths. The zonally integrated concentrations demonstrated higher values in the shallower eastern areas and a marked decrease west of 28&#xb0;E. This spatial variability underscores the influence of anthropogenic inputs and local hydrodynamics on MP distribution.</p>
<p>Hydrodynamic processes played a key role in shaping MP transport and redistribution in the GoF. Upwelling and downwelling events, as well as episodic intensification of bottom currents, significantly influenced the redistribution of MPs. Strong bottom currents resuspended settled MPs into the water column, temporarily increasing their concentrations. These dynamic processes emphasize the importance of monitoring MPs across all layers of the marine environment &#x2013; not just the surface layer but also the water column and seabed, to fully understand their transport and fate.</p>
<p>This study provides a scientific basis for policymakers to regulate MP emissions from WWTPs, manage riverine inputs, and address urban coastal pollution. By identifying hotspot areas, such as Neva Bay and Narva Bay, the findings can help prioritize resources for pollution control. Future monitoring efforts in the GoF and Baltic Sea should extend beyond the surface layer to include the water column and seabed, incorporating multipoint sampling at various depths, especially near emission sources. Additionally, mitigation measures should focus on the eastern gulf, where MP concentrations are consistently elevated.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>AM: Conceptualization, Data curation, Investigation, Methodology, Software, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. ES: Conceptualization, Data curation, Investigation, Methodology, Software, Validation, Visualization, Writing &#x2013; original draft, Writing &#x2013; review &amp; editing. GV: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing &#x2013; review &amp; editing. TL: Conceptualization, Data curation, Formal analysis, Funding acquisition, Project administration, Supervision, Validation, Visualization, Writing &#x2013; review &amp; editing. NB: Conceptualization, Resources, Validation, Writing &#x2013; review &amp; editing. UL: Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Validation, Visualization, Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by the Estonian Research Council grant PRG602 and the JPI Oceans project RESPONSE (funded by the Ministry of the Environment of Estonia and the Estonian Research Council).</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>Allocation of computing time from HPC at Tallinn University of Technology is gratefully acknowledged. The GETM community at Leibniz Institute of Baltic Sea research (IOW, Warnem&#xfc;nde) is acknowledged for the code maintenance and support. Prof. Gerald Schernewski (IOW) is acknowledged for providing MP load data for the GoF.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
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