Airborne and spaceborne remote sensing (RS) collecting hyperspectral imagery provides unprecedented opportunities for the detection and monitoring of floating riverine and marine plastic debris. However, a major challenge in the application of RS techniques is the lack of a fundamental understanding of spectral signatures of water-borne plastic debris. Recent work has emphasised the case for open-access hyperspectral reflectance reference libraries of commonly used polymer items. In this paper, we present and analyse a high-resolution hyperspectral image database of a unique mix of 40 virgin macroplastic items and vegetation. Our double camera setup covered the visible to shortwave infrared (VIS-SWIR) range from 400 to 1700 nm in a darkroom experiment with controlled illumination. The cameras scanned the samples floating in water and captured high-resolution images in 336 spectral bands. Using the resulting reflectance spectra of 1.89 million pixels in linear discriminant analyses (LDA), we determined the importance of each spectral band for discriminating between water and mixed floating debris, and vegetation and plastics. The absorption peaks of plastics (1215 nm, 1410 nm) and vegetation (710 nm, 1450 nm) are associated with high LDA weights. We then compared Sentinel-2 and Worldview-3 satellite bands with these outcomes and identified 12 satellite bands to overlap with important wavelengths for discrimination between the classes. Lastly, the Normalised Vegetation Difference Index (NDVI) and Floating Debris Index (FDI) were calculated to determine why they work, and how they could potentially be improved. These findings could be used to enhance existing efforts in monitoring macroplastic pollution, as well as form a baseline for the design of future multispectral RS systems.

Plastic pollution in aquatic ecosystems is a growing threat to ecosystem health and human livelihood. Recent studies show that the majority of environmental plastics accumulate within river systems for years, decades and potentially even longer. Long‐term and system‐scale observations are key to improve the understanding of transport and retention dynamics, to identify sources and sinks, and to assess potential risks. The goal of this study was to quantify and explain the variation in floating plastic transport in the Rhine‐Meuse delta, using a novel 1‐year observational data set. We found a strong positive correlations between floating plastic transport and discharge. During peak discharge events, plastic transport was found up to six times higher than under normal conditions. Plastic transport varied up to a factor four along the Rhine and Meuse rivers, which is hypothesized to be related to the complex river network, locations of urban areas, and tidal dynamics. Altogether, our findings demonstrate the important role of hydrology as driving force of plastic transport dynamics. Our study emphasizes the need for exploring other factors that may explain the spatiotemporal variation in floating plastic transport. The world's most polluted rivers are connected to the ocean through complex deltas. Providing reliable observations and data‐driven insights in the transport and dynamics are key to optimize plastic pollution prevention and reduction strategies. With our paper we aim to contribute to both advancing the fundamental understanding of plastic transport dynamics, and the establishment of long‐term and harmonized data collection at the river basin scale.

Reducing plastic pollution in rivers, lakes, and oceans is beneficial to aquatic animals and human livelihood. To achieve this, reliable observations of the abundance, spatiotemporal variation, and composition of plastics in aquatic ecosystems are crucial. Current efforts mainly focus on collecting data on the open ocean, on beaches and coastlines, and in river systems. Urban areas are the main source of plastic leakage into the natural environment, yet data on plastic pollution in urban water systems are scarce. In this paper, we present a simple method for plastic hotspot mapping in urban water systems. Through visual observations, macroplastic abundance and polymer categories are determined. Due to its simplicity, this method is suitable for citizen science data collection. A first application in the Dutch cities of Leiden and Wageningen showed similar mean plastic densities (111–133 items/km canal) and composition (75–80% soft plastics), but different spatial distributions. These observations emphasize the importance of long-term data collection to further understand and quantify spatiotemporal variations of plastics in urban water systems. In turn, this will support improved estimates of the contribution of urban areas to the plastic pollution of rivers and oceans.

Airborne and spaceborne remote sensing (RS) collecting hyperspectral imagery provides unprecedented opportunities for the detection and monitoring of floating riverine and marine plastic debris.However, a major challenge in the application of RS techniques is the lack of fundamental understanding of spectral signatures of water-borne plastic debris. Recent work has emphasised the case for open-access hyperspectral reflectance reference libraries of commonly used polymer items. In this paper, we present and analyse a high-resolution hyperspectral image databaseof a unique mix of 40 virgin macroplastic items and vegetation. Our double camera setup covered the visual to shortwave infrared (VIS-SWIR) range from 400-1700 nm in a dark room experiment with controlled illumination. The cameras scanned the samples floating in water and captured high-resolution images in 336 spectral bands. Using these resulting reflectance spectra as a baseline, a linear discriminant analysis was done to determine which wavelengths are more useful for discriminating between water and mixed floating debris, and vegetation and plastics. We then examined current Sentinel-2 and Worldview-3 satellite techniques, and the Normalised Vegetation Difference Index (NDVI) and Floating Debris Index (FDI) to determine why they work, and how they could potentially be improved. These findings could be used to enhance existing efforts in monitoring macroplastic pollution, as well as form a baseline for the design of future multispectral RS systems.

Plastic debris and other anthropogenic litter has negative impacts on ecosystem health and human livelihood (van Emmerik & Schwarz, 2020). Despite several global initiatives to tackle this emerging environmental challenge, plastic production and leakage into the environment is expected to further grow in the coming decades (Borrelle et al., 2020). Rivers have been assumed to be the main conveyors of land-based plastic waste into the ocean (Meijer et al., 2021;Schmidt et al., 2017). However, recent work has suggested that plastic pollution can be retained within river systems for years to decades, and potentially even longer . Plastics accumulate on riverbanks, in vegetation, around hydraulic structures, and within estuaries, where they are exposed to environmental weathering leading to degradation and fragmentation (Delorme et al., 2021). The secondary micro-and nanoplastics that arise from this may lead to additional environmental risks, and may eventually be exported into the ocean (Koelmans et al., 2022). Understanding transport and retention dynamics

Rivers are pathways and storage zones for plastic pollution. Land-based plastic waste enters river systems through anthropogenic and hydrometeorological processes, after which they are transported and retained. Only a small fraction (<2%) is assumed to make it into the ocean. Understanding and quantifying river plastic transport are important to optimize prevention and reduction strategies and to evaluate the efficacy of new regulations and interventions. To achieve this, consistent and reliable data are crucial. River plastic pollution monitoring is still an emerging field, especially since river-scale plastic pollution assessments are limited to date. Here, we present an estimate of floating plastic transport and polymer characterization along the Rhine, from Switzerland to the river mouth in Netherlands. We show plastic transport is highly variable along the river, but with a significant increase towards the river mouth. High plastic transport was observed close to urban areas, and confluences with tributaries, suggesting both are likely entry points of plastic pollution. The largest plastic transport was measured in the estuary, which is explained by the tidal dynamics, limiting the transport of plastic into the sea. Our results can be used as a baseline to compare with future assessments. Furthermore, the plastic transport and composition estimates can be directly compared to other rivers that applied the same approach, which may reduce the uncertainty in global river plastic emission simulations. With our study, we aim to contribute to the development of a simple harmonized plastic monitoring approach to quantify plastic pollution at the river basin scale.

Anthropogenic litter is omnipresent in terrestrial and freshwater systems, and can have major economic and ecological impacts. Monitoring and modeling of anthropogenic litter comes with large uncertainties due to the wide variety of litter characteristics, including size, mass, and item type. It is unclear as to what the effect of sample set size is on the reliability and representativeness of litter item statistics. Reliable item statistics are needed to (1) improve monitoring strategies, (2) parameterize litter in transport models, and (3) convert litter counts to mass for stock and flux calculations. In this paper, we quantify sample set size requirement for riverbank litter characterization, using a database of more than 14,000 macrolitter items (&gt;0.5 cm), sampled for 1 year at eight riverbank locations along the Dutch Rhine, IJssel, and Meuse rivers. We use this database to perform a Monte Carlo based bootstrap analysis on the item statistics, to determine the relation between sample size and variability in the mean and median values. Based on this, we present sample set size requirements, corresponding to selected uncertainty and confidence levels. Optima between sampling effort and information gain is suggested (depending on the acceptable uncertainty level), which is a function of litter type heterogeneity. We found that the heterogeneity of the characteristics of litter items varies between different litter categories, and demonstrate that the minimum required sample set size depends on the heterogeneity of the litter category. This implies that more items of heterogeneous litter categories need to be sampled than of heterogeneous item categories to reach the same uncertainty level in item statistics. For example, to describe the mean mass the heterogeneous category soft fragments (&gt;2.5 cm) with 90% confidence, 990 items were needed, while only 39 items were needed for the uniform category metal bottle caps. Finally, we use the heterogeneity within litter categories to assess the sample size requirements for each river system. All data collected for this study are freely available, and may form the basis of an open access global database which can be used by scientists, practitioners, and policymakers to improve future monitoring strategies and modeling efforts.

&lt;p&gt;Accumulation of plastic in aquatic environments negatively impacts ecosystems and human livelihood. Urban areas are assumed to the main source of plastic pollution in these environments, because of high anthropogenic activity. Yet, the drivers of plastic emissions, abundance and retention within these systems and subsequent transport to river systems is poorly understood. In this study, we demonstrate that urban water systems function as major contributors to river plastic pollution, and explore the potential driving factors contributing to the transport dynamics. Monthly visual counting of floating litter at six outlets of the Amsterdam water system results in an estimated 2.7 million items to enter the closely connected IJ river annually, ranking it among the most polluting systems measured in the Netherlands and Europe. Subsequent analyses of environmental drivers (including rainfall, sunlight, wind speed and tidal regimes) and litter flux showed no strong correlations (r = -0.19 - 0.16), implying additional investigation of potential drivers is required. High frequency observations at various locations within the urban water system and advanced monitoring using novel technologies could be explored to harmonize and automate monitoring. Once litter type and abundance are well-defined with a clear origin, communication of the results with local communities and stakeholders could help co-develop solutions and stimulate behavioural change geared to reduce plastic pollution in urban environments.&lt;/p&gt;