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.
Defining plastic pollution hotspots Tasseron, Paolo F.; van Emmerik, Tim H.M.; Vriend, Paul ...
Science of the total environment,
07/2024, Letnik:
934
Journal Article
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Odprti dostop
Plastic pollution in the natural environment poses a growing threat to ecosystems and human health, prompting urgent needs for monitoring, prevention and clean-up measures, and new policies. To ...effectively prioritize resource allocation and mitigation strategies, it is key to identify and define plastic hotspots. UNEP's draft global agreement on plastic pollution mandates prioritizing hotspots, suggesting a potential need for a defined term. Yet, the delineation of hotspots varies considerably across plastic pollution studies, and a definition is often lacking or inconsistent without a clear purpose and boundaries of the term. In this paper, we applied four common definitions of hotspot locations to plastic pollution datasets ranging from urban areas to a global scale. Our findings reveal that these hotspot definitions encompass between 0.8 % to 93.3 % of the total plastic pollution, covering <0.1 % to 50.3 % of the total locations. Given this wide range of results and the possibility of temporal inconsistency in hotspots, we emphasize the need for fit-for-purpose criteria and a unified approach to defining plastic hotspots. Therefore, we designed a step-wise framework to define hotspots by determining the purpose, units, spatial scale, temporal scale, and threshold values. Incorporating these steps in research and policymaking yields a harmonized definition of hotspots, facilitating the development of effective plastic pollution prevention and reduction measures.
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•Plastic pollution in aquatic environments can be extremely concentrated in hotspots.•Hotspots are often not defined, or everyone using the term defines a hotspot differently.•Mitigation strategies, targeted clean-ups, and international policies require effective identification of plastic hotspots.•We introduce a fit-for-purpose framework to identify and define plastic hotspots in a harmonized way.
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.
Plastic pollution in aquatic ecosystems has increased dramatically in the last five decades, with strong impacts on human and aquatic life. Recent studies endorse the need for innovative approaches ...to monitor the presence, abundance, and types of plastic in these ecosystems. One approach gaining rapid traction is the use of multi‐ and hyperspectral cameras. However, most experiments using this approach were in controlled environments, making findings challenging to apply in natural environments. We present a method linking lab‐ and field‐based identification of macroplastics using hyperspectral data (1,150–1,675 nm). Experiments using riverbank‐harvested macroplastics were set up in a laboratory environment, and on the banks of the Rhine River. Representative pixel selections of eleven lab‐based images (n = 786,264 pixels) and two field‐based images (n = 40,289 pixels) were used to analyze the differences between these environments. Next, classifier algorithms such as support vector machines (SVM), spectral angle mapper (SAM) and spectral information divergence (SID) were applied, because of their robustness to varying light conditions and high accuracies in mapping spectral similarities. Our results showed that SAM classifiers are most robust in separating plastic pixels from background elements. By applying lab‐based data for plastic detection in field‐based images, user accuracies for plastics to up to 93.6% (n = 8,370 plastic pixels) were attained. This study provides key fundamental insights in linking lab‐based data to plastic detection in the field. With this paper we aim to contribute to the development of future spectral missions to detect and monitor plastic pollution in aquatic ecosystems.
Key Points
Lab‐based hyperspectral imagery used in classifier algorithms can detect plastics in natural environments with accuracies up to 93.6%
Spectral angle mapper algorithms are most robust for plastic pixel detection in challenging dynamic environmental conditions
The hyperspectral data set we present can be used on multiple scales, supporting the design of new equipment and future satellite missions
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.
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 (>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 (>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.
Accumulation of plastic litter in aquatic environments negatively impacts ecosystems and human livelihood. Urban areas are assumed to be 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 are 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 entering 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 very weak and insignificant 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 behavioral change geared to reduce plastic pollution in urban environments.
This paper shares an early-career perspective on potential themes for the upcoming International Association of Hydrological Sciences (IAHS) Scientific Decade (SD). This opinion paper synthesizes six ...discussion sessions in western Europe identifying three themes that all offer a different perspective on the hydrological threats the world faces and could serve to direct the broader hydrological community: "Tipping points and thresholds in hydrology," "Intensification of the water cycle," and "Water services under pressure." Additionally, four trends were distinguished concerning the way in which hydrological research is conducted: big data, bridging science and practice, open science, and inter- and multidisciplinarity. These themes and trends will provide valuable input for future discussions on the theme for the next IAHS SD. We encourage other early-career scientists to voice their opinion by organizing their own discussion sessions and commenting on this paper to make this initiative grow from a regional initiative to a global movement.
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