Transfer dynamics of macroplastics in estuaries – New insights from the Seine estuary: Part 2. Short-term dynamics based on GPS-trackers

Tramoy, Romain; Gaspéri, Johnny; Colasse, Laurent; Silvestre, Marie; Dúbois, Philippe; Noûs, Camille; Tassin, Bruno

doi:10.1016/j.marpolbul.2020.111566

Cited by 80 publications

(106 citation statements)

References 49 publications

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“…Perhaps the most important finding of the study reported here is that travel distances for macroplastic debris in rivers are short and variable. This is consistent with the finding of Tramoy et al (2020) in the Seine and implies that some previous estimates of the terrestrial to marine macroplastic flux may not be accurate. Of course, fluxes are likely to vary with river stage but may not necessarily be higher as discharge increases.…”

Section: Discussionsupporting

confidence: 88%

“…Again, this can be determined with additional tracer experiments, but across longer temporal scales. For practicality, these types of experiment could usefully employ GPS trackers (see Tramoy et al, 2020). These have the added advantage of providing high temporal resolution data on the location of plastic tracers.…”

Section: Discussionmentioning

confidence: 99%

“…In particular, dominant modes of transport, residence times, accumulation processes (temporary and permanent) and storage zones in different reach types and under different flow regimes remain uncertain (see Figure 1, which summarises the main processes affecting macroplastic displacement in rivers). One recent study which contributes to closing these knowledge gaps is that reported by Tramoy et al (2020), who used GPS trackers to understand the transfer dynamics of macroplastic in the River Seine and its estuary. They found that macroplastic debris moved intermittently and its residence time was much longer than the transit time of water.…”

Section: Introductionmentioning

confidence: 99%

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Macroplastic Debris Transfer in Rivers: A Travel Distance Approach

2021

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Plastic accumulation in the marine environment is a major concern given the harmful effects and longevity of plastics at sea. Although rivers are likely to significantly contribute to the flux of plastic to marine systems, the behaviour of plastic debris in fluvial systems remains poorly understood and estimates of riverine plastic flux derived from field measurements and modelling efforts are highly uncertain. This paper presents a new probabilistic model of plastic transport in rivers which describes the main processes controlling plastic displacement and which predicts the statistical distribution of travel distances for individual items of buoyant macroplastic debris. Macroplastic transport is controlled by retention in temporary stores (or traps) created by vegetation, bank roughness elements and other obstacles. The behaviour of these traps is represented in the model via a series of Bernoulli trials conducted in a Monte Carlo simulation framework. The model was applied to a tracer experiment in a small 1.1 km river reach. Three replicates were used for calibration and three for validation. For each replicate, 90 closed air-filled polyethylene terephthalate (PET) bottles were introduced at the upstream end of the reach and the location of each bottle was recorded after 24 h. Bottles were chosen as “model” macroplastic litter items given their high usage and littering rate. Travel distances were low. The average and maximum distances travelled over 24 h were 231 m and 1.1 km, respectively. They were also variable. The coefficient of variation of travel distances was 0.94. Spatial patterns were controlled by the location and characteristics of discrete traps. The model was able to describe the observed travel distance distributions reasonably well, suggesting that modelling plastic behaviour in longer reaches and even whole catchments using a stochastic travel distance approach is feasible. The approach has the potential to improve estimates of river plastic flux, although significant knowledge gaps remain (e.g., the rate and location of plastic supply to river systems, the transport behaviours of different types of plastic debris and trap effectiveness in different types of river system, season, and discharge).

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Section: Discussionsupporting

confidence: 88%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Macroplastic Debris Transfer in Rivers: A Travel Distance Approach

2021

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“…To resolve these transport mechanisms, data during extreme events and on riverbank residence times are needed. 10 , 11 …”

Section: Resultsmentioning

confidence: 99%

Disentangling Variability in Riverbank Macrolitter Observations

Roebroek

Hut

Vriend

et al. 2021

Environ. Sci. Technol.

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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 R 2 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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“…The temporal constancy of particle concentration may favor particle retention in the Bay if, as suggested by some studies (Moore et al, 2011;Watkins et al, 2019;Bailey et al, 2021), riverine concentration increases with stormflow. These high-flow events result in shorter estuarine residence times and hence particles would be preferentially exported during such events, as has been seen for macroplastics in other estuaries like the Seine (Tramoy et al, 2020). Similarly, we assume all rivers have the same particle concentration, but nearby watershed population density is known to impact particle concentrations (Yonkos et al, 2014;Bikker et al, 2020).…”

Section: Model Limitationsmentioning

confidence: 97%

Estuaries as Filters for Riverine Microplastics: Simulations in a Large, Coastal-Plain Estuary

et al. 2021

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Public awareness of microplastics and their widespread presence throughout most bodies of water are increasingly documented. The accumulation of microplastics in the ocean, however, appears to be far less than their riverine inputs, suggesting that there is a “missing sink” of plastics in the ocean. Estuaries have long been recognized as filters for riverine material in marine biogeochemical budgets. Here we use a model of estuarine microplastic transport to test the hypothesis that the Chesapeake Bay, a large coastal-plain estuary in eastern North America, is a potentially large filter, or “sink,” of riverine microplastics. The 1-year composite simulation, which tracks an equal number of buoyant and sinking 5-mm diameter particles, shows that 94% of riverine microplastics are beached, with only 5% exported from the Bay, and 1% remaining in the water column. We evaluate the robustness of this finding by conducting additional simulations in a tributary of the Bay for different years, particle densities, particle sizes, turbulent dissipation rates, and shoreline characteristics. The resulting microplastic transport and fate were sensitive to interannual variability over a decadal (2010–2019) analysis, with greater export out of the Bay during high streamflow years. Particle size was found to be unimportant while particle density – specifically if a particle was buoyant or not – was found to significantly influence overall fate and mean duration in the water column. Positively buoyant microplastics are more mobile due to being in the seaward branch of the residual estuarine circulation while negatively buoyant microplastics are transported a lesser distance due to being in the landward branch, and therefore tend to deposit on coastlines close to their river sources, which may help guide sampling campaigns. Half of all riverine microplastics that beach do so within 7–13 days, while those that leave the bay do so within 26 days. Despite microplastic distributions being sensitive to some modeling choices (e.g., particle density and shoreline hardening), in all scenarios most of riverine plastics do not make it to the ocean, suggesting that estuaries may serve as a filter for riverine microplastics.

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Transfer dynamics of macroplastics in estuaries – New insights from the Seine estuary: Part 2. Short-term dynamics based on GPS-trackers

Cited by 80 publications

References 49 publications

Macroplastic Debris Transfer in Rivers: A Travel Distance Approach

Macroplastic Debris Transfer in Rivers: A Travel Distance Approach

Disentangling Variability in Riverbank Macrolitter Observations

Estuaries as Filters for Riverine Microplastics: Simulations in a Large, Coastal-Plain Estuary

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