Amsterdam urban water system as entry point of river plastic pollution

Tasseron, Paolo; Begemann, Finn; Joosse, Nonna; Ploeg, Martine van der; Driel, Joppe van; Emmerik, Tim van

doi:10.1007/s11356-023-26566-5

Cited by 13 publications

(11 citation statements)

References 45 publications

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“…Research on such travel dynamics in urban areas remains scarce. A recent study on Amsterdam found no significant correlations between rainfall and floating plastic transport in either of the six measured canals (Tasseron et al, 2023). For the Huveaune River in Marseille, Tramoy et al (2022) found that 36% of the annual macroplastic transport occurred during heavy rainfall events.…”

Section: Pluvial Floodsmentioning

confidence: 86%

“…Another complicating factor is that plastic pollution comes in countless different polymer types, shapes, rigidity, and sizes, which all influence the way they move through in the environment (van Emmerik & Schwarz, 2020). It is clear that plastic is a purely anthropogenic pollutant, and increased concentrations are generally observed close to densely populated areas (Kuizenga et al, 2023;Tasseron et al, 2023). However, large accumulations are found around the world in parallel.…”

Section: Introductionmentioning

confidence: 99%

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The impact of floods on plastic pollution

van Emmerik

2024

Glob. Sustain.

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Non-Technical Summary. Plastic harms ecosystem health and human livelihood on land, in rivers, and in the sea. To prevent and reduce plastic pollution, we must know how plastics move through the environment. Extreme events, such as floods, bring large amounts of plastic into rivers around the world. This article summarizes how different flood types (excessive rainfall, high river flow, or floods from the sea) flush or deposit plastic pollution, and how this impacts the environment. Furthermore, this paper also discusses how improved resilience to floods is important to prevent and reduce plastic pollution. Technical Summary. Plastic pollution is ubiquitous in the environment and threatens terrestrial, freshwater, and marine ecosystems. Reducing plastic pollution requires a thorough understanding of its sources, sinks, abundance, and impact. The transport and retention dynamics of plastics are however complex, and assumed to be driven by natural factors, anthropogenic factors, and plastic item characteristics. Current literature shows diverging correlations between river discharge, wind speed, rainfall, and plastic transport. However, floods have been consistently demonstrated to impact plastic transport and dispersal. This paper presents a synthesis of the impact of floods on plastic pollution in the environment. For each specific flood type (fluvial, pluvial, coastal, and flash floods), we identified the driving transport mechanisms from the available literature. This paper introduces the plastic-flood nexus concept, which is the negative feedback loop between floods (mobilizing plastics), and plastic pollution (increasing flood risk through blockages). Moreover, the impact of flood-driven plastic transport was assessed, and it was argued that increasing flood resilience also reduces the impact of floods on plastic pollution. This paper provides a perspective on the importance of floods on global plastic pollution. Increasing flood resilience and breaking the plastic-flood nexus are crucial steps toward reducing environmental plastic pollution. Social Media Summary. Floods have a large impact on plastic pollution transport, which can be reduced through improved flood resilience

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Section: Pluvial Floodsmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

The impact of floods on plastic pollution

van Emmerik

2024

Glob. Sustain.

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“…It was also experimentally documented that microparticles formed via EPS and PS polymer fragmentation have smaller sizes than those released from PP and PET, with the largest formed from HDPE plastic (Boersma et al, 2023). Numerous riverine macroplastic waste items (e.g., cups, meat trays, plastic cutlery and straws, building insulation) are built from these fragmentation prone polymers (EPS, PS) (Plastic Europe 2021; Gonzalez-Fernandez et al, 2021;Tasseron et al, 2023). Gaining field-based information on their fragmentation rates seems to be especially important for our further understanding of the risks resulting from riverine macroplastic pollution.…”

Section: Polymer Typementioning

confidence: 99%

Macroplastic fragmentation in rivers

Liro¹,

Zielonka²,

Emmerik³

2023

Preprint

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The process of macroplastic (>0.5 cm) fragmentation results in the production of smaller plastic particles (micro- and nanoplastics), which threaten biota and human health and are difficult to remove from the environment. The global coverage and long retention times of macroplastic waste in fluvial systems (ranging from years to centuries) create long-lasting and widespread potential for its fragmentation and the production of secondary micro- and nanoplastics. However, the pathways and rates of this process are unknown, which constitutes a fundamental knowledge gap in our understanding of macroplastic fate in rivers and the transfer of produced microparticles throughout the environment. To set the stage for future research aiming to fill this gap, we present a conceptual framework which identifies two types of riverine macroplastic fragmentation controls: intrinsic (resulting from plastic item properties) and extrinsic (resulting from river characteristics and climate) processes. First, based on the existing literature, we identify the intrinsic properties of macroplastic items that make them particularly prone to fragmentation (e.g., the film shape, low polymer resistance, previous weathering). Second, we propose a conceptual model showing how extrinsic controls can modulate the intensity of macroplastic fragmentation in perennial and intermittent rivers. Using this model, we hypothesize that the inundated parts of perennial river channels—as specific zones exposed to the constant transfer of water and sediments—provide particular conditions that accelerate the physical fragmentation of macroplastics resulting from their mechanical interactions with water, sediments, and riverbeds. The non-inundated parts of perennial river channels provide conditions for biochemical fragmentation via photo-oxidation. In intermittent rivers, the whole channel zone is hypothesized to favor both the physical and biochemical fragmentation of riverine macroplastics, with the dominance of the mechanical type during the wet season. Our conceptualization aims to support future experimental works quantifying macroplastic fragmentation rates in different types of rivers.

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“…Regardless of the type of waste and its destination in the environment, urban areas are the main source of litter pollution in water bodies. For instance, recent estimates for the city of Amsterdam suggest that around 2.7 million items enter the closely connected IJ river annually (Tasseron et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Advancing deep learning-based detection of floating litter using a novel open dataset

Jia,

Vallendar,

de Vries

et al. 2023

Front. Water

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Supervised Deep Learning (DL) methods have shown promise in monitoring the floating litter in rivers and urban canals but further advancements are hard to obtain due to the limited availability of relevant labeled data. To address this challenge, researchers often utilize techniques such as transfer learning (TL) and data augmentation (DA). However, there is no study currently reporting a rigorous evaluation of the effectiveness of these approaches for floating litter detection and their effects on the models' generalization capability. To overcome the problem of limited data availability, this work introduces the “TU Delft—Green Village” dataset, a novel labeled dataset of 9,473 camera and phone images of floating macroplastic litter and other litter items, captured using experiments in a drainage canal of TU Delft. We use the new dataset to conduct a thorough evaluation of the detection performance of five DL architectures for multi-class image classification. We focus the analysis on a systematic evaluation of the benefits of TL and DA on model performances. Moreover, we evaluate the generalization capability of these models for unseen litter items and new device settings, such as increasing the cameras' height and tilting them to 45°. The results obtained show that, for the specific problem of floating litter detection, fine-tuning all layers is more effective than the common approach of fine-tuning the classifier alone. Among the tested DA techniques, we find that simple image flipping boosts model accuracy the most, while other methods have little impact on the performance. The SqueezeNet and DenseNet121 architectures perform the best, achieving an overall accuracy of 89.6 and 91.7%, respectively. We also observe that both models retain good generalization capability which drops significantly only for the most complex scenario tested, but the overall accuracy raises significantly to around 75% when adding a limited amount of images to training data, combined with flipping augmentation. The detailed analyses conducted here and the released open source dataset offer valuable insights and serve as a precious resource for future research.

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Amsterdam urban water system as entry point of river plastic pollution

Cited by 13 publications

References 45 publications

The impact of floods on plastic pollution

The impact of floods on plastic pollution

Macroplastic fragmentation in rivers

Advancing deep learning-based detection of floating litter using a novel open dataset

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