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

Marine litter is a significant and growing pollutant in the oceans. In recent years, the number of studies and initiatives trying to assess and tackle the global threat of marine litter has grown exponentially. Most of these studies, when considering macro-litter, focus on floating or stranded litter, whereas there is less information available about marine litter on the seabed. The aim of this paper is to give an overview of the current state-of-the-art methods to address the issue of seafloor macro-litter pollution. The overview includes the following topics: the monitoring of macro-litter on the seafloor; the identification of possible litter accumulation hot spots on the seafloor through numerical models; seafloor litter management approaches (from removal protocols to recycling processes). The paper briefly analyzes the different approaches to involve stakeholders, since the marine litter topic is strongly related to the societal engagement. Finally, attempting to answer to all the critical aspects highlighted in the overview, the paper highlights the need of innovative multi-level solutions to induce a change towards sustainable practices, transforming a problem into a real circular economy opportunity.

Large-area, artificial floating marine litter (FML) targets were deployed during a controlled field experiment and data acquisition campaign: the Plastic Litter Project 2021. A set of 22 Sentinel-2 images, along with UAS data and ancillary measurements were acquired. Spectral analysis of the FML and natural debris (wooden planks) targets was performed, along with spectral comparison and separability analysis between FML and other floating materials such as marine mucilage and pollen. The effects of biofouling and submersion on the spectral signal of FML were also investigated under realistic field conditions. Detection of FML is performed through a partial unmixing methodology. Floating substances such as pollen exhibit similar spectral characteristics to FML, and are difficult to differentiate. Biofouling is shown to affect the magnitude and shape of the FML signal mainly in the RGB bands, with less significant effect on the infrared part of the spectrum. Submersion affects the FML signal throughout the range of the Sentinel-2 satellite, with the most significant effect in the NIR part of the spectrum. Sentinel-2 detection of FML can be successfully performed through a partial unmixing methodology for FML concentrations with abundance fractions of 20%, under reasonable conditions.

Marine litter (ML) accumulation in the coastal zone has been recognized as a major problem in our time, as it can dramatically affect the environment, marine ecosystems, and coastal communities. Existing monitoring methods fail to respond to the spatiotemporal changes and dynamics of ML concentrations. Recent works showed that unmanned aerial systems (UAS), along with computer vision methods, provide a feasible alternative for ML monitoring. In this context, we proposed a citizen science UAS data acquisition and annotation protocol combined with deep learning techniques for the automatic detection and mapping of ML concentrations in the coastal zone. Five convolutional neural networks (CNNs) were trained to classify UAS image tiles into two classes: (a) litter and (b) no litter. Testing the CCNs’ generalization ability to an unseen dataset, we found that the VVG19 CNN returned an overall accuracy of 77.6% and an f-score of 77.42%. ML density maps were created using the automated classification results. They were compared with those produced by a manual screening classification proving our approach’s geographical transferability to new and unknown beaches. Although ML recognition is still a challenging task, this study provides evidence about the feasibility of using a citizen science UAS-based monitoring method in combination with deep learning techniques for the quantification of the ML load in the coastal zone using density maps.

Marine litter density, distribution and potential sources, and the impact on canyon seafloor habitats were investigated in the Motril, Carchuna and Calahonda canyons, located along the northern margin of the Alboran Sea. During the ALSSOMAR-S2S oceanographic survey carried out in 2019, canyon floor imagery was collected by a Remotely Operated Vehicle along 5 km in Motril Canyon, 10 km in Carchuna Canyon, and 3 km in Calahonda Canyon, together with 41 surficial sediment samples. Additionally, coastal uses, maritime traffic and fishing activity data were analysed. A 50 m resolution multibeam bathymetry served as base map. In Motril and Calahonda canyons, the density of marine litter was low and the material is dispersed, very degraded and partially buried. In contrast, the Carchuna Canyon contained a greater amount and variety of litter. The Carchuna Canyon thalweg exhibited a density of marine litter up to 8.66 items·100 m-1, and litter hotspots with a density up to 42 items·m2 are found along the upper reaches of canyon thalweg. Low litter abundances found in the studied canyons most likely reflect low population densities and the absence of direct connections with streams in the nearby coasts. The high shelf incision of Carchuna Canyon and its proximity to the coastline favour littoral sediment remobilization and capture as well as the formation of gravity flows that transport the marine litter along the thalweg toward the distal termination of the channel. Litter hotspots are favoured by the canyon morphology and the occurrence of rocky outcrops. Most debris is of coastal origin, and related to beach occupation and agricultural practices in the adjacent coastal plain. A third origin was represented by fishing gear in the study area. Fishing activity may be producing an impact through physical damage to the skeletons of the colonial scleractinians located in the walls of Carchuna Canyon. In contrast, Motril and Calahonda canyons can be considered passive systems that have mainly acted as depositional sinks in the recent past, as evidenced by buried marine litter.

Marine litter has had a huge impact on the marine environment and the socio-economic activities that depend on healthy oceans. All members of the community must play their part to address marine litter. Teachers are agents of change that are capable of encouraging pro-environmental practices among the community that will reduce environmental issues, including marine litter. However, teachers were found to have limited knowledge regarding ocean literacy and marine pollution. A scoping review was conducted to identify various aspects of content knowledge related to marine litter education that has been recently conducted for school teachers and students. Web of Science, Scopus and ERIC databases were searched for articles published in English between 2015 and 8 July 2021. Fourteen peer-reviewed articles were selected for this study and were subjected to content analysis. Topics related to marine litter were frequently addressed. Meanwhile, topics related to teaching Environmental Education/Education for Sustainable Development (EE/ESD) were the least addressed. Benthic marine litter, solutions to marine litter and the introduction of new types of marine litter were identified as topics that need to be addressed in future marine litter education. This study lists content knowledge based on previous literature and identified the gaps, which will be useful for teachers to improve their knowledge and implement effective marine litter education in school.

Plastic pollution is an increasing global concern, with estuaries being especially vulnerable as transition zones between freshwater and marine systems. These ecosystems often accumulate large amounts of waste, affecting wildlife and water quality. This study focuses on analysing the circulation patterns of the Ave Estuary, a small, shallow system on Portugal’s north-western coast, and their influence on litter transport and distribution. This site was selected for installing an aquatic litter removal technology under the EU-funded MAELSTROM project. A 2DH hydrodynamic model using Delft3D FM, coupled with the Wflow hydrological model, was implemented and validated. Various scenarios were simulated to assess estuarine dynamics and pinpoint zones prone to litter accumulation and flood risk. The results show that tidal action and river discharge mainly drive the estuary’s behaviour. Under low discharge, floating litter should be mostly transported toward the ocean, while high discharge conditions should result in litter movement at all depths due to stronger currents. High water levels and flooding occur mainly upstream and in specific low-lying areas near the mouth. Low-velocity zones, which can favour litter accumulation, were found around the main channel and on the western margin near the estuary’s mouth, even during high flows. These findings highlight persistent accumulation zones, even under extreme event conditions.

Most advances in the remote sensing of floating marine plastic litter have been made using passive remote-sensing techniques in the visible (VIS) to short-wave-infrared (SWIR) parts of the electromagnetic spectrum based on the spectral absorption features of plastic surfaces. In this paper, we present developments of new and emerging remote-sensing technologies of marine plastic litter such as passive techniques: fluid lensing, multi-angle polarimetry, and thermal infrared sensing (TIS); and active techniques: light detection and ranging (LiDAR), multispectral imaging detection and active reflectance (MiDAR), and radio detection and ranging (RADAR). Our review of the detection capabilities and limitations of the different sensing technologies shows that each has their own weaknesses and strengths, and that there is not one single sensing technique that applies to all kinds of marine litter under every different condition in the aquatic environment. Rather, we should focus on the synergy between different technologies to detect marine plastic litter and potentially the use of proxies to estimate its presence. Therefore, in addition to further developing remote-sensing techniques, more research is needed in the composition of marine litter and the relationships between marine plastic litter and their proxies. In this paper, we propose a common vocabulary to help the community to translate concepts among different disciplines and techniques.

Litter cleanup and disposal management in the marine environment are increasingly subject to public scrutiny, government regulation and stakeholder initiatives. In practice, ongoing efforts and new investment decisions, for example in new cleanup technologies, are constrained by financial and economic resources. Given budgetary restrictions, it is important to optimize decision-making using a scientific framework that takes into account the various effects of investments by combining multiple scientific perspectives and integrating these in a consistent and coherent way. Identifying optimal levels of marine litter cleanup is a challenge, because of its cross-disciplinary nature, involving physics, environmental engineering, science, and economics. In this paper, we propose a bridge-building, spatial cost-benefit optimization framework that allows prioritizing where to apply limited cleanup efforts within a regional spatial network of marine litter sources, using input from the maturing field of marine litter transport modeling. The framework also includes ecosystem functioning in relation to variable litter concentrations, as well as the potentially non-linear cost-efficiency of cleanup technologies. From these three components (transport modeling, ecosystem functioning, cleanup-effectiveness), along with litter source mapping, we outline the optimal cleanup solution at any given ecological target or economic constraint, as well as determine the cleanup feasibility. We illustrate our framework in a Baltic and Mediterranean Sea case study, using real data for litter transport and cleanup technology. Our study shows that including pollution Green's functions is essential to assess the feasibility of cleanup and determine optimal deployment of cleanup investments, where the presented framework combines physical, economical, technological and biological data consistently to compare and rank alternatives.

Most marine litter monitoring methods used on beaches focus on macro-litter (>25 mm) only and show shortcomings regarding smaller litter classes (<25 mm), especially at Baltic Sea beaches. Therefore, we used a sand rake method developed for large micro- (2–5 mm), and meso- (5–25 mm) litter to quantify the overall pollution status of Baltic Sea beaches and to test if the method is useful in terms of the requirements of the Marine Strategy Framework Directive (MSFD). Between July 2017 and October 2019, 197 sand rake method surveys were carried out at 35 regions around the Baltic Sea. In total, 9345 litter pieces were found on an area of 10,271 m 2 of which 69.9% were 2–25 mm in size. Artificial polymers (4921 litter pieces) were predominant (mean 52.7% ± 13.3). Abundance of litter was 0.91 pieces/m 2 ± 1.50 (median 0.40 pieces/m 2 ). The most common litter were industrial pellets (19.8%), non-identifiable plastic pieces 2–25 mm (17.3%), cigarette butts (15.3%), and paraffin (11.9%). At 15 surveys at the German North Sea island of Sylt the litter abundance ranged from 0.45 pieces/m 2 (median) to 0.59 pieces/m 2 ± 0.37 (mean). Here, 69.2% of the litter was 2–25 mm in size and paraffin was predominant (69.2%). Beaches show a high pollution level with large micro- and meso-litter (2–25 mm) and our data can serve as a Baltic-wide pollution baseline. In contrast to the naked eye OSPAR method for macro-litter, the sand rake method is generally applicable on all sandy beaches, both urban and remote. This method also allows for the provision of a full spatial pollution pattern and can serve for assessing the effectiveness of marine litter mitigation measures.