Floating marine macro litter in the Black Sea: Toward baselines for large scale assessment

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Environmental Pollution 309 (2022) 119816

Available online 21 July 2022

Floating marine macro litter in the Black Sea: Toward baselines for large scale assessment

^☆

D. Gonz´alez-Fern´andez

^a^,^*

, G. Hanke

^b

, M. Pogojeva

^c^,^d

, N. Machitadze

^e

, Y. Kotelnikova

^f

, I. Tretiak

^f

, O. Savenko

^f^,^g

, K. Bilashvili

^e

, N. Gelashvili

^e

, A. Fedorov

^d

, D. Kulagin

^d

, A. Terentiev

^c

, J. Slobodnik

^h

aDepartment of Biology, University Marine Research Institute INMAR, University of C´adiz and European University of the Seas, Puerto Real, Spain

bEC Joint Research Centre, Ispra, Italy

cN. N. Zubov’s State Oceanographic Institute, Roshydromet, Moscow, Russia

dShirshov Institute of Oceanology, Russian Academy of Sciences, Moscow, Russia

eIv. Javakhishvili Tbilisi State University, Tbilisi, Georgia

fUkrainian Center of Ecology of the Sea, Odessa, Ukraine

gNational Antarctic Scientific Center of Ukraine, Kiev, Ukraine

hEnvironmental Institute, Kos, Slovak Republic

A R T I C L E I N F O Keywords:

Marine pollution Marine litter Plastic litter

Floating marine macro litter Monitoring

Black sea

A B S T R A C T

The Black Sea is a semi-enclosed basin subject to major anthropogenic pressures, including marine litter and plastic pollution. Due to numerous large rivers draining into the basin and a population settled along the coast, the region could accumulate significant amounts of floating litter over time. Until now, only limited field data were available, and litter quantities and distribution remained unknown. In this study, floating marine macro litter (FMML) was assessed at the regional Black Sea scale for the first time, showing relatively high litter densities across the basin that reached a weighted mean of 81.5 items/km². Monitoring data revealed an accumulation of floating items offshore in the eastern part of the basin, resembling on a small scale a ‘garbage patch’, where litter items were trapped, showing elevated densities in comparison to their surrounding areas.

Most of these items were made of plastic materials (ca. 96%) and included large numbers of plastic and polystyrene fragments of small size ranges (2.5–10 cm). Harmonised field data collection through consistent and regular monitoring programmes across the region is essential to establish baselines and thresholds for large scale assessment at international level.

1. Introduction

Marine litter has been recognized as a threat to marine wildlife by the European Marine Strategy Framework Directive (MSFD) (European Commission, 2008), the Regional Sea Conventions (UNEP, 2006), and by international provisions such as the United Nations Sustainable Development Goal 14 (UN, 2015). Recently, the United Nations has signed the first global resolution to combat plastic pollution, defining and guiding the elaboration of a legally binding treaty by 2024 (UNEP, 2022). Marine litter and plastic pollution influence a wide spectrum of other environmental, economic, safety, health, and cultural aspects.

Marine litter is mainly composed of plastics with slow degradation rates,

which together with a continuous rise in plastic production, waste generation, and inefficient waste disposal, can lead to a dramatic increase in the quantity of plastics in our oceans and shorelines in the coming decades (Geyer et al., 2017; Jambeck et al., 2015; Lebreton and Andrady, 2019).

The Black Sea is a semi-enclosed basin of ca. 423,000 km²and a total coastline length of approximately 4000 km, connected to the Mediter- ranean Sea through the Bosphorus Strait, and therefore mostly isolated from the World Ocean (Bakan and Büyükgüng¨or, 2000; BSC, 2019).

River basins draining into the Black Sea include some of the largest European rivers such as Danube, Dnieper, Dniester, Don, Kuban and Southern Bug, along with a large number of smaller rivers and coastal

☆This paper has been recommended for acceptance by Eddy Y. Zeng.

* Corresponding author.

E-mail address: daniel.gonzalez@uca.es (D. Gonz´alez-Fern´andez).

Contents lists available at ScienceDirect

Environmental Pollution

journal homepage: www.elsevier.com/locate/envpol

https://doi.org/10.1016/j.envpol.2022.119816

Received 26 February 2022; Received in revised form 30 June 2022; Accepted 17 July 2022

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Environmental Pollution 309 (2022) 119816 drainage basins running through populated areas (Jaoshvili, 2002). The

Black Sea receives the drainage from an extensive catchment area, up to 2.5 million km², covering partially or entirely the territories of 23 Eu- ropean and Asian countries (BSC, 2007; Rouholahnejad et al., 2014), and hosting a population of approximately 174 million (estimated for 2015 following the methodology described in Gonz´alez-Fern´andez et al.

(2021)). Large quantities of silt, nutrients, organic matter, chemical pollutants, and unknown amounts of litter and plastics are carried by rivers into the region (BSC, 2007; 2019). The countries surrounding the Black Sea (Bulgaria, Romania, Ukraine, Russia, Georgia, and Turkey) have a permanent coastal population of 17.5 million. Moreover, 6–8 million tourists visit the region every year (Vespremeanu and Golum- beanu, 2018), implying a dense population along the coastline, associated to relevant waste generation and probability of inadequate disposal in close proximity to the marine environment (BSC, 2007; Todorova et al., 2018). In the European context, the estimated waste management rates of the countries bordering the Black Sea have been described as medium (80–90%) for Russia and Turkey, and low (<80%) for Bulgaria, Romania, Ukraine and Georgia; modelled results predict an annual input of 98 million floating macrolitter items to the region, where Ukraine and Turkey are the largest contributors (Gonz´alez-Fern´andez et al., 2021).

Industry, agriculture and port activities are important in the region, particularly related to refineries, metallurgic, textile, and food pro- cessing and shipping (BSC, 2019). Although gradually improving, limited access to sewage treatment plants is a common issue in coastal areas of the region (BSC, 2019). At the same time, the Black Sea is one of the major fishing areas in the world with relevant maritime, recreational and industrial uses of the sea that can act as additional sources of plastic waste (Bakan and Büyükgüng¨or, 2000; FAO, 2018). All these facts make the Black Sea particularly exposed to marine litter accumulation, as has been described by the Black Sea Commission (BSC, 2019, 2007) and other recent studies (Aytan et al., 2020).

Floating marine macro litter (FMML) is the fraction of marine litter

>2.5 cm, primarily plastics that can travel long distances and be present in large quantities, becoming a risk for marine wildlife directly exposed at sea through ingestion and entanglement (Kühn et al., 2015). Further, macro litter is subject to degradation and fragmentation processes, resulting in a source for secondary microplastics (Lebreton et al., 2019).

In the Black Sea, data on FMML densities (e.g., items/km²) have only been reported a few times and mostly at small scale in coastal areas of Ukraine and the Kerch Strait (BSC, 2007), Romania (Suaria et al., 2015), Bulgaria (Berov and Klayn, 2020) and Georgia (Aytan et al., 2020), hindering the possibility to provide a large-scale assessment in the region.

In this study, we focused on the assessment of FMML in the Black Sea.

Visual observations were used to obtain information in a European regional sea where existing data were very limited and restricted to coastal areas. Field data collection was aimed at bridging knowledge gaps on abundance, composition, and distribution of FMML across the Black Sea, testing a harmonised monitoring approach developed by the DG Joint Research Centre (JRC) of the European Commission (EC) to allow assessment of comparable results across regions. This is the most comprehensive database on FMML ever collected in the Black Sea. The results generated in this study are of relevant interest for future defini- tion of floating litter baselines and thresholds in the region. Such baselines and thresholds are needed for the assessment of Good Environmental Status (GES) under Descriptor 10 (Marine Litter) during the implementation of the MSFD for European Union (EU) Member States (i.e., Bulgaria and Romania), and can also be integrated in activities of the Black Sea Commission, fostering collaboration between EU, EU associated countries, and non-EU countries.

2. Methods

2.1. Visual observations

Field data collection took place in the framework of the EMBLAS-II (Improving Environmental Monitoring in the Black Sea – Phase II, ENPI/2013/313-169) and EMBLAS-Plus (Improving Environmental Monitoring in the Black Sea – Selected Measures, ENI/2017/389-859) projects (Slobodnik et al., 2022, 2020a; 2020b), and in collaboration with the JRC. EMBLAS projects aimed to improve environmental monitoring in the Black Sea, supporting the partner countries (Georgia, Russia, and Ukraine) to perform environmental monitoring and assessment following the principles of the MSFD. The database included in this study consisted of a compilation of data from different surveys collected in 2017 and 2019, reporting a total of 302 monitoring sessions. The observers performed 269.4 h of visual observations along transects, covering total length and surface area of 4761 km and 93.9 km², respectively (Table 1). Valid surveys took place from May to November 2017 and from June to October 2019, covering different zones of the Black Sea (Table 1 and Fig. 1). Monitoring in the western basin was mostly limited to the northern part; the route between Odessa and Istanbul was surveyed only sporadically from ferry ships in May–June and November 2017, and particularly at a speed range 10–16 knots and elevated observation height (24 m). Survey metadata and monitoring setup parameters are detailed in Supplementary Tables S1 and S2.

The monitoring method was based on visual observations from ves- sels, following a harmonised approach. The observers were trained, through several workshops organized by the JRC, to follow the methodology described in the ‘Guidance on Monitoring of Marine Litter in European Seas’ of the EC (Galgani et al., 2013) and use the JRC Floating Litter Monitoring app (Android operating system, version 2.0) for data registering and reporting (Gonz´alez-Fern´andez and Hanke, 2017). In brief, visual observations were made from the bow or deck of the ship applying a fixed-width strip transect methodology to scan for floating items during navigation (Campanale et al., 2019; Chambault et al., 2018; Thiel et al., 2003). The strip width varied depending on the observation platform height and vessel speed (Supplementary Table S2).

All macro litter items (>2.5 cm in the longest dimension) were regis- tered during the monitoring sessions running the app on a tablet com- puter. Binoculars were occasionally used to confirm the identity of items. The identification and documentation of litter items was based on a harmonised list of floating litter item categories extracted from the MSFD Master List of Litter Categories, and size ranges (2.5–5 cm, 5–10 Table 1

Monitoring effort during the EMBLAS Joint Black Sea Surveys. Distribution of transects (monitoring sessions), duration, linear distance, surveyed area, and number of observed items are grouped per year, basin zone, and total effort.

Basin zones classified according to two criteria: western vs. eastern basin, and territorial sea (TS) vs. open sea (OS).

No. of

transects Duration

(hours) Linear

distance (km) Area

(km²) No. of items

2017 132 152.4 2729 64.0 4941

2019 170 117.0 2032 30.0 2714

Western 126 123.7 2222 44.9 1739

Eastern 176 145.7 2538 49.0 5916

TS 136 119.6 1669 28.5 1425

OS 166 149.8 3091 65.4 6230

Western-

TS 52 55.9 793 12.3 432

Western-

OS 74 67.8 1430 32.6 1307

Eastern-

TS 84 63.6 877 16.2 993

Eastern-

OS 92 82.0 1661 32.8 4923

Total

effort 302 269.4 4761 93.9 7655

D. Gonz´alez-Fern´andez et al.

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cm, 10–20 cm, 20–30 cm, 30–50 cm, and >50 cm), according to Galgani et al. (2013). In order to improve item size estimation, the observers trained with known size targets to get familiarized with the sizes at different distances from the observation platform. Performance of visual monitoring was restricted to good sea state Beaufort ≤3, except in 15 monitoring sessions (Beaufort 4, wind speed 11-16 knots). Those 15 monitoring sessions did not show statistically significant differences with the rest of the transects (Mann-Whitney Rank Sum Test, p > 0.05).

Furthermore, litter density did not show a decreasing trend towards higher Beaufort values (analysis not included).

2.2. Floating litter abundance and distribution

Floating litter density was estimated for each monitoring session as a simple abundance index:

D = N/(L x W)

where D is litter density in items per square kilometre (items/km²), N is the total number of litter items observed, L is the transect length and W is the fixed-width strip. For spatial visualization and classification of individual transects, midpoints and distance to the coast were calculated for each monitoring session. Transect midpoints were adopted as representative geographical locations to plot litter density results in QGIS 3.4 Software. Monitoring sessions were classified into western and eastern basin zones selecting Longitude 34.2 E as division limit; 12 NM distance from the coast divided the data into territorial sea (TS) and open sea (OS) zones. The combination of these two criteria allowed a further classification into four zones: western-TS, western-OS, eastern- TS, and eastern-OS.

2.3. Statistical analysis

In addition to common descriptive statistics, area-weighted means and medians were calculated to balance differences in survey effort per monitoring session. Due to non-normal distribution of data, non- parametric tests were selected to study differences in floating litter densities. Mann-Whitney Rank Sum tests were run to evaluate differences between years (2017 vs. 2019), basin zones (western vs. eastern), and distance to the coast zones (TS vs. OS). Additionally, monitoring sessions were grouped into four distance ranges defined by descriptive statistics (Q1, Median and Q3) of their distance to the coast: D1 (<2.14

NM, n = 76), D2 (2.14–17.15 NM, n = 75), D3 (17.15–59.22 NM, n = 76), D4 (>59.22 NM, n = 75). Kruskal-Wallis analysis of variance on ranks test and Dunn’s pairwise multiple comparison test were used to assess differences among distance ranges.

In the approximation to FMML quantification, the percentile boot- strapping method was used (Davison and Hinkley, 1997) (10,000 rep- licates, random sampling with replacement) to calculate the 95%

confidence interval of the weighted mean.

3. Results

3.1. FMML abundance and distribution

Fig. 2 includes the spatial distribution of FMML densities across the Black Sea. The mean FMML density was 93.6 ± 128.3 items/km²(median 38.6 items/km²), ranging from 0 to 810.2 items/km². The area- weighted mean was 81.5 ± 89.4 items/km²(weighted median 35.7 items/km²). The datasets included 40 monitoring sessions with zero litter counts (0 items/km²), which were mostly, i.e. 33 out 40, located in the TS (<12 NM from the coastline) around the city areas of Odessa (Ukraine) and Sochi (Russian Federation), and along the coast from Gelendzhik-Novorossiysk to the Kerch Strait. At the same time, high litter densities >200 items/km²(84th percentile of all data) were observed only occasionally in TS, and particularly in proximity (<12 NM radius) to the city areas of Odessa (weighted mean ~29 items/km²and max. ~580 items/km²), Novorossiysk (weighted mean ~51 items/km² and max. ~660 items/km²), and Batumi (weighted mean ~92 items/

km²and max. ~400 items/km²). In contrast, most of the high-density values detected in the study, i.e. 39 out of 48, were in the OS (>12 NM from the coastline), and particularly in the eastern Black Sea basin.

The western-OS hardly ever exhibited high litter densities above 200 items/km².

A comparison between litter densities observed in 2017 and 2019 did not show statistically significant differences (Mann-Whitney Rank Sum Test, p > 0.05). In relation to geographical zones, differences between the western (median 26.5) and eastern (median 62.3 items/km²) basin were statistically significant (Mann-Whitney Rank Sum Test, p < 0.01).

Similarly, litter densities were significantly higher in the OS (median 66.9 items/km²) compared to those in the TS (median 18.7 items/km²) (Mann-Whitney Rank Sum Test, p < 0.01). The latter was further investigated grouping the data by year and basin zone (Fig. 3). Most Fig. 1. Monitoring sessions across the Black Sea, represented by transect midpoints for 2017 (green dots) and 2019 (red dots) surveys. Dashed area corresponded to the Black Sea basin considered in the study, divided into western vs. eastern zones by a vertical line at Longitude 36.2 E. The light blue coastal strip (12 NM distance from the coastline) delimited territorial sea vs. open sea zones. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

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Environmental Pollution 309 (2022) 119816

cases indicated higher median litter densities in the OS compared to the TS, except for the western basin in 2017, where the opposite was noticed at statistically significant level (Mann-Whitney Rank Sum Test, p <

0.01). In 2019, significant differences were observed between the TS and the OS both in the western (Mann-Whitney Rank Sum Test, p < 0.01) and eastern (Mann-Whitney Rank Sum Test, p < 0.01) basin. A final test consisted of grouping all the data (n = 302) into four distance ranges (according to distance to the coast) to perform a Kruskal-Wallis analysis of variance on ranks. The Kruskal-Wallis test showed statistically sig- nificant differences (p < 0.01) among the median litter densities. In detail, a Dunn’s pairwise multiple comparison test indicated significant differences between the groups D1 vs. D4, D2 vs. D3 and D2 vs. D4. The median litter densities in ascending order were D2 (13.4 items/km²) <

D1 (24.3 items/km²) < D3 (47.4 items/km²) < D4 (84.0 items/km²).

3.2. FMML composition and item size distribution

In this study, the observers identified 7655 FMML items diversified into 35 litter categories (Supplementary Table S3). Plastic items made up to 95.8% of total items, followed by Paper/Cardboard items (1.7%), while the rest of litter materials were present in proportions lower than 1% (Fig. 4). The top 10 items showed exclusively plastic litter categories, and accounted for 94.9% of total items, while the top 20 items were more diverse in terms of litter materials and added up to 99.2% of total items (Fig. 4). ‘G79 - Plastic pieces 2.5 cm > < 50 cm’ was by far the most abundant litter item. These top item results were largely consistent between the western and eastern basin, with some variations (Supple- mentary Table S3). Some of the most frequent items, ‘G38 - Cover/

packaging’ and ‘G124 - Other plastic/polystyrene items’, interchanged ranking positions in these two basin zones, contrasting a higher proportion (ca. + 9%) of cover/packaging items (e.g., food wrappers) in the western basin and higher proportions of plastic pieces and other plastic/

Fig. 2. Floating marine macro litter densities (items/km²) in the Black Sea. Monitoring sessions (n = 302) performed in the years 2017 and 2019.

Fig. 3. Floating marine macro litter densities (item/km²) per year and basin zones. Box-Whiskers represented percentiles 50th (median), 25th-75th (box) and 10th- 90th (whiskers). Basin zones classified according to two criteria: western vs. eastern basin, and territorial sea (TS) vs. open sea (OS).

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polystyrene items in the eastern basin. Also, two Paper/Cardboard items ranked in the top 10 list in the western basin. Regarding proportions of top items in the TS and the OS, a relative increase of plastic pieces and decrease of single-use plastics (SUP) such as cover/packaging, bags and bottles were observed in the OS (Supplementary Table S3).

The overall item size distribution (total items) showed an exponential-type increasing frequency toward small sized items (Fig. 5).

This was dominated by a high percentage of fragments in the total items, classified under ‘G79 - Plastic pieces 2.5 cm > < 50 cm’ (45.6%) and

‘G82 - Polystyrene pieces 2.5 cm > < 50 cm’ (10.3%). This distribution pattern was consistent for 2017 vs. 2019, western vs. eastern basin, and TS vs. OS items (Fig. 5). However, there was a noticeable relative decrease of ca. 12% for the smallest size range (2.5–5 cm) in the TS compared to the OS.

3.3. Approximation to FMML quantification

Based on the data collected over a total surveyed area of 93.9 km² (2017 and 2019), and the differences observed in the western vs. eastern basin and the TS vs. OS, we estimated that 35.5 million macro litter items (>2.5 cm) could be floating in the Black Sea surface waters, ranging from 24.3 to 49.5 million (95% confidence interval), based on weighted mean densities (items/km²) calculated in four zones of the Black Sea (Table 2). These estimates assumed homogeneous litter densities within each zone for the extrapolation of results.

Although our methodology did not allow us to measure the weight of the observed litter, a rough estimate of the FMML mass was made considering published data (Lebreton et al., 2018). The numerical litter loads presented in Table 2 were approximated to mass loads considering the averaged weight per litter item in different size ranges, calculated from plastic items data collected in the Pacific Ocean (Lebreton and Reisser, 2018) (Supplementary Table S4). We estimated that 535 tonnes of FMML could be present in the Black Sea, ranging from 366 to 745 tonnes (95% confidence interval).

4. Discussion

This is the first time FMML has been monitored at large scale in the Black Sea, including the OS (>12 NM distance from the coast) across the basin from north-west (Odessa) to south-east (Batumi), revealing relatively high litter densities away from coastal waters. Our results suggest a long-term accumulation of floating items offshore in the eastern basin.

This accumulation could resemble at small scale a ‘garbage patch’ like in the subtropical ocean gyres (C´ozar et al., 2014; Eriksen et al., 2014;

Lebreton et al., 2018), where litter items are trapped showing elevated densities in comparison to the surrounding areas. It was not possible to assess the existence of a similar accumulation in the western basin due to limited data collection in the OS.

4.1. FMML pollution levels

Previous comparable macro litter data (i.e. vessel-based Fig. 4. Top floating marine macro litter items in the Black Sea. Litter item categories and codes extracted from the MSFD Master List (Galgani et al., 2013).

Fig. 5. Floating marine macro litter items size distribution. Percentage per litter size range in different zones, years and total (n is number of items).

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Environmental Pollution 309 (2022) 119816

observations) were scarce and mostly focused on coastal waters in the northern and western Black Sea: mean densities of 6.6 and 65.7 items/

km²were estimated in Ukraine and the Kerch Strait, respectively (BSC, 2007); in Romania, a mean density of 30.9 ± 7.4 items/km²(max. 135.9 items/km²) was found in the area between Constanta and the mouth of the Danube River (Suaria et al., 2015); and Bulgarian waters presented a mean density of 41.5 ± 30 items/km²(max. 93.8 items/km²) (Berov and Klayn, 2020). Most of these values fitted in the interquartile range observed in our study for the western basin (Fig. 3). However, previous studies did not register such high peaks as those found in that zone during 2017 and 2019, e.g., in the vicinity of Odessa (max. ~580 items/km²). The detection of these high peaks may have been condi- tioned by differences in the geographical zones surveyed, and inter-seasonal and inter-annual variability in the Black Sea (Miladinova et al., 2020; Stanev and Ricker, 2019), but not necessarily by increasing temporal trends. Nonetheless, the data collected in 2003 in Ukrainian coastal waters (mean density 6.6 items/km²) (BSC, 2007) seemed to be one order of magnitude below the results obtained herein for the western-TS (weighted mean 35.0 items/km²), corresponding mostly to Ukrainian and Romanian waters, and very similar to mean densities detected previously in Romania (Suaria et al., 2015) and Bulgaria (Berov and Klayn, 2020). Such hypothetical increasing temporal FMML trends in the Black Sea, approximately five-fold over 15 years, would be slower than the 17-fold increase over 25 years suggested for the Mediterranean Sea by Suaria and Aliani (2014). In any case, data on temporal changes remain limited for the purpose of assessing whether such increasing rates are taking place or not. Harmonised data collection and consistent monitoring programmes should be implemented to produce comparable data in order to help establish baseline levels and sound trend assessments in the coming years (Galgani et al., 2013; Schulz et al., 2019). The database included in this study is of great value for the implementation of such baseline levels.

In the Mediterranean Sea, another European semi-enclosed sea basin, litter abundance varied regionally and seasonally (Arcangeli et al., 2020; Campana et al., 2018; Suaria and Aliani, 2014), reaching mean densities of 16–19 items/km²(max. 200 items/km²) in the north-western part (Garcia-Garin et al., 2020), 232 ± 325 items/km² (max. 1593 items/km²) in the eastern Mediterranean Sea (south Cyprus area) (Constantino et al., 2019), and 492 items/km²(max. 9205 items/km²) around Italy (Campanale et al., 2019). These references suggest that, in certain areas of the Mediterranean Sea, FMML pollution could be more intense than in the Black Sea. However, a larger scale assessment in the Mediterranean Sea lowered the mean FMML density to 24.9 ± 2.4 items/km²(Suaria and Aliani, 2014), which is in the same order of magnitude but ca. three times lower than the overall weighted mean of 81.5 ± 89.4 items/km²estimated for the Black Sea in this study.

In contrast, a study in the Baltic Sea found very low FMML densities

<0.5 items/km²(Roth¨ausler et al., 2019). The North Sea (North East Atlantic Ocean) showed mean densities around 30 items/km²(max. 300 items/km²) (Gutow et al., 2018; Thiel et al., 2011), fitting in the lower range of mean densities estimated at large scale in the Mediterranean Sea (Suaria and Aliani, 2014) and the Black Sea (this study). Data reported in open Atlantic oceanic waters presented mean densities between 0.8 and 3 items/km²around the continental shelf of Portugal and

the Autonomous Region of the Azores (Chambault et al., 2018; S´a et al., 2016), showing low litter densities compared to the Black Sea. Overall, the FMML densities (items >2.5 cm) found in the Black Sea can be considered as relatively high in the European context.

In the North Pacific Ocean, an estimate of the accumulation of floating litter in the Great Pacific Garbage Patch provided a mean density of ca. 700 macro plastic items/km²(max. ca. 2400 items/km²) (Lebreton et al., 2018). The accumulation of floating litter in semi-enclosed sea basins such as the Black Sea and the Mediterranean Sea, although highly exposed to litter input from rivers and large coastal populations (González-Fernández et al., 2021), does not seem to reach such elevated mean FMML densities, possibly subject to removal processes leading to sinking (Cózar et al., 2015), and particularly to the importance of beaching processes due to the limited dimension of these basins combined with atmospheric and hydrodynamic circulation patterns, as pointed out in recent modelling studies for the Black Sea (Miladinova et al., 2020; Stanev and Ricker, 2019) and the Mediterra- nean Sea (Kaandorp et al., 2020; Macias et al., 2019).

4.2. Spatial distribution: field data vs. modelled patterns

In this study, the differences between the western and eastern Black Sea identified significantly higher densities of floating litter in the latter.

Our data collection took place from May to November, covering mainly summer and autumn periods in both 2017 and 2019. A Black Sea modelling study anticipated that floating litter distribution should mainly be controlled by basin circulation, and accumulation zones along the south-eastern and eastern coast were expected to be abundant in summer along with continuous retention of litter in the eastern coast section, drawing similarities with our results (Miladinova et al., 2020).

The authors also identified a “big retention zone in the centre of the western gyre in summer”, expected to shift towards the east in winter, which in the long term would also contribute to the litter accumulation observed in the eastern basin. However, unlike these model simulations, the monitoring of floating litter in the western basin did not reflect such high litter densities.

In the data collected sporadically from ferry ships at 24 m high platforms (348 items), 26% of the items were in the size range 2.5–5 cm, lower than the 44% obtained for monitoring platforms <12 m height (7307 items) (analysis not included). This potential bias could result in an underestimation of litter densities in the western-OS (route Odessa- Istanbul). Inconsistencies in the comparison of data from different monitoring platforms (e.g., different observation height) have previously been raised by Arcangeli et al. (2020), who suggested a compar- ison of data for items >20 cm. An additional analysis of litter densities for items >20 cm in the Black Sea showed statistically significant dif- ferences between the western (median 3.74 items/km²) and eastern (median 15.97 items/km²) basin in the OS (Mann-Whitney Rank Sum Test, p < 0.01) (data not included). Regardless of the possible under- estimation in counting small items (2.5–5 cm) introduced by monitoring from 24 m high platforms, the latter reinforced the idea of different accumulation levels in the western and eastern basin, i.e., for items >20 cm, the median was one order of magnitude higher in the eastern-OS.

In contrast, a second modelling study in the Black Sea claimed that, Table 2

Floating marine macro litter numerical load estimate in the Black Sea. Litter density (items/km²) corresponded to area-weighted mean values per basin zone. Litter load indicated number of items for the mid estimate (area-weighted mean density), and low and high estimates (95% confidence interval). Basin zones classified according to two criteria: western vs. eastern basin, and territorial sea (TS) vs. open sea (OS).

Zone Basin area (km²) Litter density (items/km²) Litter load (mid estimate) Litter load (low estimate) Litter load (upper estimate)

Western-TS 42,298 10.0% 35.0 1.48 × 10⁶ 4.2% 1.05 × 10⁶ 4.3% 1.97 × 10⁶ 4.0%

Western-OS 179,505 42.6% 40.1 7.20 × 10⁶ 20.3% 4.44 × 10⁶ 18.3% 10.78 × 10⁶ 21.8%

Eastern-TS 35,349 8.4% 61.2 2.16 × 10⁶ 6.1% 1.24 × 10⁶ 5.1% 3.27 × 10⁶ 6.6%

Eastern-OS 164,050 38.9% 150.3 24.66 × 10⁶ 69.5% 17.56 × 10⁶ 72.3% 33.44 × 10⁶ 67.6%

Total 421,203 35.50 × 10⁶ 24.30 × 10⁶ 49.46 × 10⁶

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in the long term, no pronounced litter accumulations were expected in the OS (‘interior basin’), and litter densities may be higher along the western and southern parts compared to the eastern and northern ones (Stanev and Ricker, 2019). The Turkish coastline, which is highly populated and subject to elevated quantities of mismanaged waste, could act as a major contributor of floating litter to the Black Sea (González-Fernández et al., 2021; Jambeck et al., 2015). Therefore, it is feasible that, despite the elevated litter densities identified in the northern parts of the basin, litter quantities in the south-western and southern parts could be higher, e.g., influenced by riverine inputs (González-Fernández et al., 2021). Further harmonised and consistent field monitoring would be needed to assess the validity of these hypotheses.

4.3. The Black Sea ‘garbage patch’

Regarding the possible accumulation of litter off the coastal areas, we identified consistently higher litter densities in the OS compared to the TS for the eastern basin, which contrasts with the expected decreasing pattern from sources towards open waters (Arcangeli et al., 2020; Ryan, 2015). In general, the higher densities found in the OS could be related to a large spatial and temporal variability in the litter inputs from rivers and coastal populations, which may have not been fully accounted for during the monitoring in the TS. Our data were collected mostly during summer and autumn, leaving out winter and early spring seasons, periods when maximum rainfall and related riverine plastic input could be expected (Lebreton et al., 2017). Another factor could be the existence of fast transport mechanisms leading to litter removal from the TS through beaching (Stanev and Ricker, 2019) and migration of litter from the TS to the OS, and from the western to the eastern basin (Miladinova et al., 2020), contributing to a long term accumulation offshore.

Furthermore, the Dunn’s multiple comparison test reinforced the idea of an initial minor decrease of litter densities from the coastal sources in the first nautical miles, followed by a consistent increase of litter densities towards the inner basin. Overall, given the limited dimension and semi-enclosed nature of the Black Sea, it is plausible that a variable input of litter from land-based sources may lead to an accumulation of floating items in hydrodynamic structures such as gyres, intensified by the summer stratification causing transport of coastal waters into the inner basin (Guneroglu, 2010).

4.4. Prevalence of plastic litter

The lack of harmonised/standardized data collection and use of different litter classification criteria hinder direct comparisons with the most frequent litter items observed in other regions of the world (Gal- gani et al., 2015; Morales-Caselles et al., 2021). Nonetheless, the top items list in the Black Sea (Fig. 4) revealed similarities with global FMML rankings (Morales-Caselles et al., 2021) and European riverine litter inputs (Gonz´alez-Fern´andez et al., 2018). It presented very high proportions of plastic items (ca. 96% in this study), and dominance of fragments classified under litter categories such as plastic pieces, polystyrene pieces and foam, along with usual single-use plastics such as cover/packaging (e.g., packets and wrappers), bags and bottles. The exponential-type distribution of item frequencies increasing toward small sized items (Fig. 5) has also been described in other regions of the world (Campanale et al., 2019; Lebreton et al., 2018; Ryan, 2015). The prevalence of plastic items in marine litter has not only been observed on the sea surface but also in every marine environmental compartment (Morales-Caselles et al., 2021), highlighting the need for a legally binding global treaty to combat plastic pollution, as expressed in the recently signed United Nations resolution (UNEP, 2022).

4.5. Amount of FMML in the Black Sea

We provided a first approximation to the order of magnitude of total FMML items in the Black Sea. Our estimates used the weighted mean calculated in four different zones, after considering the differences observed between the western vs. the eastern basin, and the TS vs. OS data. Surveys covered areas from north-west to south-east that had never been monitored before. However, this is just a first estimate and additional data should be collected in order to cover unexplored areas and study temporal variability. Seasonal changes are expected in litter inputs along the coast (rivers and coastal populations) and in their spatial distribution at sea, affected by environmental and hydrodynamic conditions. Additional monitoring during winter and spring could reveal a different situation over the basin, e.g., higher litter densities along the TS due to elevated riverine inputs (Lebreton et al., 2017). In contrast, the coastal population increases during summer due to the inflow of tourists, generating a larger amount of waste that may increase the presence of floating litter in proximity to large coastal cities, and therefore be un- equally distributed along the coastline. The latter has already been exposed by our data around the cities of Odessa, Novorossiysk, Gelendzhik and Batumi. Furthermore, data collected in the western basin were geographically limited and did not detect the possible accumulation of litter in the western gyre, as described in model simulations (Miladinova et al., 2020). Similarly, our database missed monitoring data along the southern basin and the Turkish coastal areas, where litter densities could be elevated compared to the eastern and northern parts (Stanev and Ricker, 2019). In summary, following the descriptions of the existing hydrodynamic models, our estimate of 35.5 million FMML items (24.3–49.5 million for the 95% confidence interval) may be a conservative value since litter densities are expected to be higher in the western and southern parts of the Black Sea. Improvements in spatial and temporal coverage during data collection across the whole Black Sea region would be essential to facilitate the establishment of baselines and thresholds for large scale assessment at international level.

In the approximation to FMML mass load, a database from the Great Pacific Garbage Patch (Lebreton et al., 2018; Lebreton and Reisser, 2018) was the only available source to calculate average weight per litter item over a wide size spectrum of FMML (Supplementary Table S4). Given the high percentage of plastic items observed in the Black Sea (95.8% of total items), and therefore expected limited influence of other litter materials in the total mass estimates, we approximated plastic item weight to total litter item weight per size range. In addition to the difficulty of comparing heterogeneous data from such different regions of the world, where item categories and size distribution may vary (C´ozar et al., 2015), the use of different monitoring methods and litter item classification lists added uncertainties to our approximation. Furthermore, the average weight for our size range 2.5–5 cm was matched with that available for the size range 1.5–5 cm (Lebreton and Reisser, 2018), which may underestimate the mass in that interval. Also, in the size range >50, the average weight could be very variable because of the extent of size range considered (50–100 cm), implying a large uncertainty in a fraction that is quite relevant in terms of mass (Lebreton and Reisser, 2018). Therefore, our FMML mass estimates must be considered with caution. The conversion from numerical to mass estimates needs further development through appropriate monitoring, providing harmonised data and targeting the collection (e.

g., using trawl nets) of representative samples for a wide litter size spectrum in the region of interest, to minimise uncertainties.

5. Conclusions

A large-scale assessment of the pollution of the Black Sea by FMML was conducted in 2017 and 2019 within the EU/UNDP EMBLAS-II and EMBLAS-Plus projects. More than 4700 km of the sea surface, repre- senting ca. 94 km², were monitored at 302 individual transects using a harmonised methodology. The final estimated mean density of 81.5

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Environmental Pollution 309 (2022) 119816 items/km²(area-weighted) was ca. three times higher compared to the

average values observed in the Mediterranean Sea. These results indi- cate that the Black Sea could be the most polluted European sea region in terms of FMML. The observations also showed relevant spatial differences of FMML due to potential variability in the litter sources and oceanographic pathways with the highest densities recorded in the eastern open sea zone. The large proportion of small litter items (e.g., fragments <10 cm) prevents application of clean-up strategies at sea, resulting in the need to implement measures to mitigate the input at the sources. Furthermore, the identification of single use items can facilitate the assessment of trends in the coming years. This goal can only be achieved through the implementation of a common and harmonised methodology/protocol for monitoring and assessment, as proposed by the MSFD Technical Group on Marine Litter (MSFD TG ML, 2022). In this sense, the EMBLAS projects have provided significant progress in the Black Sea, demonstrating the validity of the used methodology for assessments at international level beyond the EU, which suggests its applicability at the global scale. The use of a harmonised approach and the implementation of consistent/regular monitoring programmes across the entire sea region are essential to derive appropriate baselines and thresholds for the assessment of pollution levels and trends. Such information could be further linked to beach litter studies and modelling to eventually identify the sources and inputs, enabling the development of effective mitigation measures in the region.

Credit author statement

D. Gonz´alez Fern´andez: Conceptualization, Methodology, Valida- tion, Formal analysis, Visualization, Writing - original draft, Writing - review & editing. M. Pogojeva: Conceptualization, Investigation, Data Curation, Writing - review & editing. G. Hanke: Conceptualization, Methodology, Writing - review & editing. N. Machitadze, Y. Kotelni- kova, I. Tretiak, O. Savenko, N. Gelashvili, K. Bilashvili, D. Kulagin, A.

Fedorov, A. Terentiev: Investigation. Jaroslav Slobodnik: Funding acquisition, Project administration, Conceptualization, Writing - review

& editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data will be made available on request.

Acknowledgements

The authors wish to thank the people and institutions involved in the EMBLAS-II (Improving Environmental Monitoring in the Black Sea – Phase II, ENPI/2013/313-169) and EMBLAS-Plus (Improving Environ- mental Monitoring in the Black Sea – Selected Measures, ENI/2017/389- 859) projects. D. Gonz´alez-Fern´andez was supported by the European Union (H2020-MSCA–IF–2018 846843 - LitRivus) and by the 2014-2020 ERDF Operational Programme and the Department of Economy, Knowledge, Business and University of the Regional Government of Andalusia: Project reference FEDER-UCA18-107247.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.

org/10.1016/j.envpol.2022.119816.

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