Evidence map›Paper›PMID 42045280›Full record

ArticleScientific reports2026

A semi-autonomous camera-based system for global monitoring of riverine floating macroplastic transport.

S Pinson, A Vollering

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

S PinsonThe Ocean Cleanup, Rotterdam, The Netherlands. stijn.pinson@theoceancleanup.com.
A VolleringThe Ocean Cleanup, Rotterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding, predicting and preventing plastic transport through rivers benefits from monitoring and comprehension of the dynamics of plastic transport from an hourly to multi-annual scale. Existing methodologies for the monitoring of plastic transport are not suited for long, continuous observation periods or lack a rigorous comparability between locations. This paper proposes and tests a methodology for the monitoring and quantification of floating macroplastic transport in rivers that is suitable for multi-year periods and comparable between locations. Camera deployments on bridges that focus on longevity and standardization of data collection in combination with object detection and tracking techniques resulted in high-frequency data of floating macroplastic detections and flux from 11 locations worldwide spanning multiple years. This tracking and detection methodology can be transferred to new locations with low effort in model retraining. Comparison to visual counting measurements shows that we can measure the same dynamics and ranges of flux. We also demonstrate that this technique allows us to measure the surface flow velocity and tidal fluctuations of plastic debris in rivers as well as identify high transport rate events such as floods. This paper offers a comprehensive monitoring method for the transport of floating macroplastics which can be used to improve plastic transport models and measure the effects of policy and mitigation strategies of plastic debris in rivers.

Identifiers

PMID42045280
PMCPMC13319437

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.