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Wastewater discharge from wastewater treatment plants continuously pumps microplastics into rivers, yet their transport distances within these waterways remain unknown. Herein, we developed a conceptual framework by synthesizing the microplastic data from the Yangtze River Basin to evaluate its transport distances, quantifying a significant spatial dependence between large-scale wastewater discharge and riverine microplastics (p < 0.05). The presence of microplastics at a specific sampling site could be attributed to wastewater discharge within a large-scale range spanning >1000 km upstream, encompassing a substantial portion equivalent to one-third of the Yangtze River Basin. The dominance analysis indicated that the contribution of wastewater discharge in rivers with higher discharge (>100 m3/s) to riverine microplastic pollution exceeded 65% within the Yangtze River Basin. The spatial dependence framework of riverine microplastics on wastewater discharge advances our prior understanding of the prevention and control of riverine microplastics by demonstrating that such pollution is not limited to nearby environmental factors.
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Plastic entering the environment is a growing threat for ecosystems. We estimate the annual mass of known Dutch plastic waste generated and littered and where it ends up. We use two methods: (1) a material flow analysis of plastic waste separately collected from 13 economic sectors (including households, industry and imports) and estimate the amount sent to processing plants or exported and (2) a mismanagement model from observations of litter (on Dutch beaches and riverbanks) plus estimates of inadequately managed exported plastic scraps entering the environment abroad. In 2017 (the most recent complete data set available), an estimate of 1990 (±111) kilotonnes [kt] of plastic waste was separately collected. The top three plastic waste generating sectors (74% of the total) were households, clothing and textiles, and importation. Our mismanagement model estimates that 4.3-21.2 kt enters the environment annually; almost all of which occurs in foreign countries after inadequate management of imported Dutch waste. We highlight unknowns, including the source and/or destination of imported (623 kt) and exported (514 kt) plastics, plastics in non-household mixed waste streams and the plastic fraction of some separately collected waste, for example, e-waste. Our results stress the need for improved monitoring and reporting of plastic waste. Beyond the Netherlands, our recommendations could also help other high-income countries' decision-makers reach their circular economy goals.
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Ecossistema , Gerenciamento de Resíduos , Países Baixos , Plásticos , Têxteis , Indústrias , ReciclagemRESUMO
Anthropogenic macrolitter (>0.5 cm) in rivers is of increasing concern. It has been found to have an adverse effect on riverine ecosystem health, and the livelihoods of the communities depending on and living next to these ecosystems. Yet, little is known on how macrolitter reaches and propagates through these ecosystems. A better understanding of macrolitter transport dynamics is key in developing effective reduction, preventive, and cleanup measures. In this study, we analyzed a novel dataset of citizen science riverbank macrolitter observations in the Dutch Rhine-Meuse delta, spanning two years of observations on over 200 unique locations, with the litter categorized into 111 item categories according to the river-OSPAR protocol. With the use of regression models, we analyzed how much of the variation in the observations can be explained by hydrometeorology, observer bias, and location, and how much can instead be explained by temporal trends and seasonality. The results show that observation bias is very low, with only a few exceptions, in contrast with the total variance in the observations. Additionally, the models show that precipitation, wind speed, and river flow are all important explanatory variables in litter abundance variability. However, the total number of items that can significantly be explained by the regression models is 19% and only six item categories display an R2 above 0.4. This suggests that a very substantial part of the variability in macrolitter abundance is a product of chance, caused by unaccounted (and often fundamentally unknowable) stochastic processes, rather than being driven by the deterministic processes studied in our analyses. The implications of these findings are that for modeling macrolitter movement through rivers effectively, a probabilistic approach and a strong uncertainty analysis are fundamental. In turn, point observations of macrolitter need to be planned to capture short-term variability.
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Ecossistema , Monitoramento Ambiental , Rios , Processos EstocásticosRESUMO
Trees play a crucial role in the water, carbon and nitrogen cycle on local, regional and global scales. Understanding the exchange of momentum, heat, water, and CO 2 between trees and the atmosphere is important to assess the impact of drought, deforestation and climate change. Unfortunately, ground measurements of tree properties such as mass and canopy interception of precipitation are often expensive or difficult due to challenging environments. This paper aims to demonstrate the concept of using robust and affordable accelerometers to measure tree properties and responses. Tree sway is dependent on mass, canopy structure, drag coefficient, and wind forcing. By measuring tree acceleration, we can relate the tree motion to external forcing (e.g., wind, precipitation and related canopy interception) and tree physical properties (e.g., mass, elasticity). Using five months of acceleration data of 19 trees in the Brazilian Amazon, we show that the frequency spectrum of tree sway is related to mass, canopy interception of precipitation, and canopy-atmosphere turbulent exchange.
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Árvores , Acelerometria , Brasil , Mudança Climática , Folhas de PlantaRESUMO
Wind and rain are considered main drivers for mobilization and transport of macroplastics on land, yet there is a lack of empirical data that quantifies this. We present lab experiment results on land-based macroplastic mobilization and transport. We placed four types of macroplastics on terrains with varying surface roughness and slope angles, and exposed them to changing wind speeds and rain intensities. In general, we find that the mobilization probability and transport velocity of macroplastics strongly depend on the combination of the terrain characteristics and material properties. At Beaufort 3, 100% of the plastic bags were mobilized, whereas for the other plastic types less than 50% were mobilized. We found 1.4 (grass) to 5 times (paved surface) higher mobilization probabilities on land than assumed by existing plastic transport models. Macroplastic transport velocities were positively correlated with wind speed, but not with rain intensity. This suggests that macroplastics are not transported on land by rain unless surface runoff develops that can bring the macroplastics afloat. Macroplastic transport velocities were, driven by wind, 1.9 and, driven by rain, 4.9 times faster on paved surfaces than on grass. This study enhances our understanding of land-based macroplastic transport and provides an empirical basis for models.
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Marine plastic pollution poses significant ecological, economic, and social challenges, necessitating innovative detection, management, and mitigation solutions. Spectral imaging and optical remote sensing have proven valuable tools in detecting and characterizing macroplastics in aquatic environments. Despite numerous studies focusing on bands of interest in the shortwave infrared spectrum, the high cost of sensors in this range makes it difficult to mass-produce them for long-term and large-scale applications. Therefore, we present the assessment and transfer of various machine learning models across four datasets to identify the key bands for detecting and classifying the most prevalent plastics in the marine environment within the visible and near-infrared (VNIR) range. Our study uses four different databases ranging from virgin plastics under laboratory conditions to weather plastics under field conditions. We used Sequential Feature Selection (SFS) and Random Forest (RF) models for the optimal band selection. The significance of homogeneous backgrounds for accurate detection is highlighted by a 97 % accuracy, and successful band transfers between datasets (87 %-91 %) suggest the feasibility of a sensor applicable across various scenarios. However, the model transfer requires further training for each specific dataset to achieve optimal accuracy. The results underscore the potential for broader application with continued refinement and expanded training datasets. Our findings provide valuable information for developing compelling and affordable detection sensors to address plastic pollution in coastal areas. This work paves the way towards enhancing the accuracy of marine litter detection and reduction globally, contributing to a sustainable future for our oceans.
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Monitoramento Ambiental , Aprendizado de Máquina , Plásticos , Plásticos/análise , Monitoramento Ambiental/métodos , Poluentes Químicos da Água/análise , Tecnologia de Sensoriamento RemotoRESUMO
Researchers and practitioners have extensively utilized supervised Deep Learning methods to quantify floating litter in rivers and canals. These methods require the availability of large amount of labeled data for training. The labeling work is expensive and laborious, resulting in small open datasets available in the field compared to the comprehensive datasets for computer vision, e.g., ImageNet. Fine-tuning models pre-trained on these larger datasets helps improve litter detection performances and reduces data requirements. Yet, the effectiveness of using features learned from generic datasets is limited in large-scale monitoring, where automated detection must adapt across different locations, environmental conditions, and sensor settings. To address this issue, we propose a two-stage semi-supervised learning method to detect floating litter based on the Swapping Assignments between multiple Views of the same image (SwAV). SwAV is a self-supervised learning approach that learns the underlying feature representation from unlabeled data. In the first stage, we used SwAV to pre-train a ResNet50 backbone architecture on about 100k unlabeled images. In the second stage, we added new layers to the pre-trained ResNet50 to create a Faster R-CNN architecture, and fine-tuned it with a limited number of labeled images (≈1.8k images with 2.6k annotated litter items). We developed and validated our semi-supervised floating litter detection methodology for images collected in canals and waterways of Delft (the Netherlands) and Jakarta (Indonesia). We tested for out-of-domain generalization performances in a zero-shot fashion using additional data from Ho Chi Minh City (Vietnam), Amsterdam and Groningen (the Netherlands). We benchmarked our results against the same Faster R-CNN architecture trained via supervised learning alone by fine-tuning ImageNet pre-trained weights. The findings indicate that the semi-supervised learning method matches or surpasses the supervised learning benchmark when tested on new images from the same training locations. We measured better performances when little data (≈200 images with about 300 annotated litter items) is available for fine-tuning and with respect to reducing false positive predictions. More importantly, the proposed approach demonstrates clear superiority for generalization on the unseen locations, with improvements in average precision of up to 12.7%. We attribute this superior performance to the more effective high-level feature extraction from SwAV pre-training from relevant unlabeled images. Our findings highlight a promising direction to leverage semi-supervised learning for developing foundational models, which have revolutionized artificial intelligence applications in most fields. By scaling our proposed approach with more data and compute, we can make significant strides in monitoring to address the global challenge of litter pollution in water bodies.
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Macroplastic fate and transport in the freshwater environment are of great concern due to the potentially harmful effects of macroplastic on plants, animals, and humans. Here, we present a modeling approach to simulate macroplastic fate and transport at the country scale based on an existing plastic release model. The fate model was parametrized through available monitoring data and results from field experiments and applied to Swiss rivers and lakes. We found that almost all (98%) macroplastic emissions into freshwater remain within Switzerland. After exploring the influences of weirs, retention in rivers, and retention in lakes through a sensitivity analysis, we found a high retention variability across different catchments and within rivers. In all 22 analyzed scenarios for continuous retention along each river bank (i.e., beaching), we found that at least 70% of input emissions into the water bodies would be retained long-term in the catchments (about 200 g per river km and year). Across all catchments, we found a dominance of "continuous retention" through beaching along the entire river length compared with "point retention" at weirs or lakes. Thus, by modeling macroplastic fate and transport on a country level for the first time, we were able to confirm the concept of "rivers as plastic reservoirs" through modeling.
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Hydrometeorological processes are often assumed to be key drivers of plastic transport. However, the predominant focus on these factors overlooks the impact of anthropogenic factors, such as mismanaged plastic waste (MPW) on plastic transport variability. Here, we investigate the roles of both anthropogenic and hydrometeorological factors on plastic pollution in the Odaw catchment, Ghana. Data on macroplastic transport and density were collected at ten locations between December 2021 and December 2022. We tested for differences between the wet and dry seasons and applied a multiple regression analysis to examine the separate and combined impact of hydrometeorological variables (rainfall, discharge, and windspeed) on macroplastic transport. Additionally, we analyzed the spatial correlation in macroplastic transport/density with MPW and population density. Data collection involved visual counting of floating macroplastics at 10 river locations and counting litter at 9 riverbanks and land locations. Rainfall data was sourced from TAHMO (Trans-African Hydrometeorological Observatory), discharge was measured during field campaigns, and windspeed data sourced from a global climate data provider. We used globally modelled MPW estimates to represent anthropogenic factors. Contrary to previous studies, we found no seasonal differences in macroplastic pollution and only weak correlations were observed between the hydrometeorological variables and macroplastic transport. However, a strong correlation was observed between MPW and macroplastic pollution. We hypothesize that, the influence of hydrometeorological factors on macroplastic transport depend on the relative impact of anthropogenic factors. Our research highlights the limited role of hydrometeorology, showing the significant role of mismanaged plastic waste to field monitored macroplastic pollution variability in the catchment. This insight is essential for future research as it highlights the importance of holistically investigating both anthropogenic and hydrometeorological factors in explaining plastic transport and retention dynamics. This insight is essential for developing interventions that effectively address plastic pollution in catchments.
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Catchment-scale plastic pollution assessments provide insights in its sources, sinks, and pathways. We present an approach to quantify macroplastic transport and density across the Odaw catchment, Ghana. We divided the catchment into the non-urban riverine, urban riverine, and urban tidal zones. Macroplastic transport and density on riverbanks and land were monitored at ten locations in December 2021. The urban riverine zone had the highest transport, and the urban tidal zone had the highest riverbank and land macroplastic density. Water sachets, soft fragments, and foam fragments were the most abundant items. Our approach aims to be transferable to other catchments globally.
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Monitoramento Ambiental , Rios , Gana , Poluição Ambiental/análiseRESUMO
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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Rivers represent one of the main conduits for the delivery of plastics to the sea, while also functioning as reservoirs for plastic retention. In tropical regions, rivers are exposed to both high levels of plastic pollution and invasion of water hyacinths. This aquatic plant forms dense patches at the river surface that drift due to winds and currents. Recent work suggests that water hyacinths play a crucial role in influencing plastic transport, by efficiently trapping the majority of surface plastic within their patches. However, a comprehensive understanding of the interaction between water hyacinths and plastics is still lacking. We hypothesize that the properties relevant to plastic transport change due to their trapping in water hyacinth patches. In particular, the length scale, defined as the characteristic size of the transported material, is a key property in understanding how materials move within rivers. Here, we show that water hyacinth patches trap on average 54%-77% of all observed surface plastics at the measurement site (Saigon river, Vietnam). Both temporally and spatially, we found that plastic and water hyacinth presence co-occur. The formation of plastic-plant aggregates carries significant implications for both clean-up and monitoring purposes, as these aggregates can be detected from space and need to be jointly removed. In addition, the length scale of trapped plastics (â¼4.0 m) was found to be forty times larger than that of open water plastics (â¼0.1 m). The implications of this increased length scale for plastic transport dynamics are yet to be fully understood, calling for further investigation into travel distances and trajectories. The effects of plastic trapping likely extend to other key properties of plastic-plant aggregates, such as effective buoyancy and mass. Given the prevalence of plant invasion and plastic pollution in rivers worldwide, this research offers valuable insights into the complex environmental challenges faced by numerous rivers.
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Monitoramento Ambiental , Plásticos , Rios , Poluentes Químicos da Água , Rios/química , Poluentes Químicos da Água/análise , VietnãRESUMO
Research on riverine microplastics has gradually increased, highlighting an area for further exploration: the lack of extensive, large-scale regional variations analysis due to methodological and spatiotemporal limitations. Herein, we constructed and applied a comprehensive framework for synthesizing and analyzing literature data on riverine microplastics to enable comparative research on the regional variations on a large scale. Research results showed that in 76 rivers primarily located in Asia, Europe, and North America, the microplastic abundance of surface water in Asian rivers was three times higher than that in Euro-America rivers, while sediment in Euro-American rivers was five times more microplastics than Asia rivers, indicating significant regional variations (p < 0.001). Additionally, based on the income levels of countries, rivers in lower-middle and upper-middle income countries had significantly (p < 0.001) higher abundance of microplastics in surface water compared to high-income countries, while the opposite was true for sediment. This phenomenon was preliminarily attributed to varying levels of urbanization across countries. Our proposed framework for synthesizing and analyzing microplastic literature data provides a holistic understanding of microplastic disparities in the environment, and can facilitate broader discussions on management and mitigation strategies.
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The transport of floating macroplastics (>2.5 cm) can be impacted by variations in hydrometeorological forcing. Several studies have demonstrated that river discharge, wind, and tides can either accelerate or impede the downstream travel path of plastic. However, there remains a substantial gap in our understanding of the impact of river geomorphological complexity on this process. In this context, the role that river bifurcations play in driving plastic dynamics under different hydrometeorological conditions is largely unexplored. Here, we show that specific plastic item categories react differently to the transport drivers, and bifurcation areas can function both as a retention and release site of plastic litter. We found that hard polyolefin appears to be the most responsive plastic to changes in flow discharge (ρ≈0.40, p≈0.01). Absolute wind velocity magnitude does not correlate to plastic transport. We explored correlations of the various plastic items types with wind vector components in all directions. Multilayer plastics correlated highest to the wind vector component that is most effective in driving plastics from an urban area to the river (ρ≈0.57, p≈0.0001). On a monthly scale, the bifurcation area retained up to 50% of the incoming upstream plastic flux. At other times, an additional 30% was released in the same area. Our results demonstrate how bifurcations distribute different plastic items types downstream under varied hydrometeorological conditions. These yields underscore the importance of assessing floating plastic transport in specific plastic item categories and taking river geomorphological complexity into account.
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Monitoramento Ambiental , Plásticos , Plásticos/análise , Monitoramento Ambiental/métodos , Rios , Vento , Resíduos/análiseRESUMO
Rivers are one of the main conduits that deliver plastic from land into the sea, and also act as reservoirs for plastic retention. Yet, our understanding of the extent of river exposure to plastic pollution remains limited. In particular, there has been no comprehensive quantification of the contributions from different river compartments, such as the water surface, water column, riverbank and floodplain to the overall river plastic transport and storage. This study aims to provide an initial quantification of these contributions. We first identified the main relevant transport processes for each river compartment considered. We then estimated the transport and storage terms, by harmonizing available observations on surface, suspended and floodplain plastic. We applied our approach to two river sections in The Netherlands, with a focus on macroplastics (≥2.5 cm). Our analysis revealed that for the studied river sections, suspended plastics account for over 96% of item transport within the river channel, while their relative contribution to mass transport is only 30%-37% (depending on the river section considered). Surface plastics predominantly consisted of heavier items (mean mass: 7.1 g/#), whereas suspended plastics were dominated by lighter fragments (mean mass: 0.1 g/#). Additionally, the majority (98%) of plastic mass was stored within the floodplains, with the river channel accounting for only 2% of the total storage. Our study developed a harmonized approach for quantifying plastic transport and storage across different river compartments, providing a replicable methodology applicable to different regions. Our findings emphasize the importance of systematic monitoring programs across river compartments for comprehensive insights into riverine plastic pollution.
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Monitoramento Ambiental , Plásticos , Rios , Rios/química , Países Baixos , Monitoramento Ambiental/métodos , Poluentes Químicos da Água/análiseRESUMO
The process of macroplastic (>0.5 cm) fragmentation results in the production of smaller plastic particles, 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 mostly unknown and existing experimental data not fully informative, which constitutes a fundamental knowledge gap in our understanding of macroplastic fate in rivers and the transfer of produced microparticles throughout the environment. Here 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). First, based on the existing literature, we identify the intrinsic properties of macroplastic items that make them particularly prone to fragmentation (e.g., film shape, low polymer resistance, previous weathering). Second, we formulate 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 unvegetated areas in 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 macroplastics, with the dominance of the mechanical type during the periods with water flow. Our conceptualization aims to support future experimental and modelling works quantifying plastic footprint of different macroplastic waste in different types of rivers.
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Mountain rivers are typically seen as relatively pristine ecosystems, supporting numerous goods (e.g., water resources) for human populations living not only in the mountain regions but also downstream from them. However recent evidence suggests that mountain river valleys in populated areas can be substantially polluted by macroplastic (plastic item >25 mm). It is unknown how distinct characteristics of mountain rivers modulate macroplastic routes through them, which makes planning effective mitigation strategies difficult. To stimulate future works on this gap, we present a conceptual model of macroplastic transport pathways through mountain river. Based on this model, we formulate four hypotheses on macroplastic input, transport and mechanical degradation in mountain rivers. Then, we propose designs of field experiments that allow each hypothesis to be tested. We hypothesize that some natural characteristics of mountain river catchments can accelerate the input of improperly disposed macroplastic waste from the slope to the river. Further, we hypothesize that specific hydromorphological characteristics of mountain rivers (e.g., high flow velocity) accelerate the downstream transport rate of macroplastic and together with the presence of shallow water and coarse bed sediments it can accelerate mechanical degradation of macroplastic in river channels, accelerating secondary microplastic production. The above suggests that mountain rivers in populated areas can act as microplastic factories, which are able to produce more microplastic from the same amount of macroplastic waste inputted into them (in comparison to lowland rivers that have a different hydromorphology). The produced risks can not only affect mountain rivers but can also be transported downstream. The challenge for the future is how to manage the hypothesized risks, especially in mountain areas particularly exposed to plastic pollution due to waste management deficiencies, high tourism pressure, poor ecological awareness of the population and lack of uniform regional and global regulations for the problem.
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Seas are polluted with macro- (>5 mm) and microplastics (<5 mm). However, few studies account for both types when modeling water quality, thus limiting our understanding of the origin (e.g., basins) and sources of plastics. In this work, we model riverine macro- and microplastic exports to seas to identify their main sources in over ten thousand basins. We estimate that rivers export approximately 0.5 million tons of plastics per year worldwide. Microplastics are dominant in almost 40% of the basins in Europe, North America and Oceania, because of sewage effluents. Approximately 80% of the global population live in river basins where macroplastics are dominant because of mismanaged solid waste. These basins include many African and Asian rivers. In 10% of the basins, macro- and microplastics in seas (as mass) are equally important because of high sewage effluents and mismanaged solid waste production. Our results could be useful to prioritize reduction policies for plastics.
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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 = [Formula: see text]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.
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Plásticos , Rios , Humanos , Água , Ecossistema , Monitoramento Ambiental/métodos , Resíduos/análiseRESUMO
Plastics in rivers and lakes have direct local impact, and may also reach the world's oceans. Monitoring river plastic pollution is therefore key to quantify, understand and reduce plastics in all aquatic ecosystems. The lack of harmonization between ongoing monitoring efforts compromises the direct comparison and combination of available data. The United Nations Environment Programme (UNEP) launched guidelines on freshwater plastic monitoring, to provide a starting point for practitioners and scientists towards harmonized data collection, analysis, and reporting. We developed a five-step workflow to support to design effective plastic monitoring strategies. The workflow was applied to three rivers (Rhine, Mekong and Odaw) across relevant gradients, including geography, hydrology, and plastic pollution levels. We show that despite the simplicity of the selected methods and the limited duration of the data collection, our harmonized approach provides crucial insights in the state of plastic pollution in very different river basins globally.