Evidence map›Paper›PMID 36679731›Full record

ArticleSensors (Basel, Switzerland)2023

Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach.

Silvia Merlino, Marina Locritani, Antonio Guarnieri, Damiano Delrosso, Marco Bianucci, Marco Paterni

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Silvia MerlinoCNR-ISMAR (Istituto di Scienze Marine-Sede di La Spezia), 19032 La Spezia, Italy.ORCID 0000-0002-4537-2903
Marina LocritaniIstituto Nazionale di Geofisica e Vulcanologia, Sezione di Roma 2, 00143 Roma, Italy.ORCID 0000-0003-2827-5631
Antonio GuarnieriIstituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, 40127 Bologna, Italy.ORCID 0000-0001-8162-6571
Damiano DelrossoIstituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, 40127 Bologna, Italy.
Marco BianucciCNR-ISMAR (Istituto di Scienze Marine-Sede di La Spezia), 19032 La Spezia, Italy.ORCID 0000-0002-0276-2813
Marco PaterniCNR-IFC (Istituto di Fisiologia Clinica-Pisa), 56124 Pisa, Italy.

Funding

European Union's Horizon 2020 research and innovation programme No. 101000825INGV "ML-DAR Project, ricerca libera 9999.521 RL2019
6 · The paper itself

Abstract

It is well established that most of the plastic pollution found in the oceans is transported via rivers. Unfortunately, the main processes contributing to plastic and debris displacement through riparian systems is still poorly understood. The Marine Litter Drifter project from the Arno River aims at using modern consumer software and hardware technologies to track the movements of real anthropogenic marine debris (AMD) from rivers. The innovative "Marine Litter Trackers" (MLT) were utilized as they are reliable, robust, self-powered and they present almost no maintenance costs. Furthermore, they can be built not only by those trained in the field but also by those with no specific expertise, including high school students, simply by following the instructions. Five dispersion experiments were successfully conducted from April 2021 to December 2021, using different types of trackers in different seasons and weather conditions. The maximum distance tracked was 2845 km for a period of 94 days. The activity at sea was integrated by use of Lagrangian numerical models that also assisted in planning the deployments and the recovery of drifters. The observed tracking data in turn were used for calibration and validation, recursively improving their quality. The dynamics of marine litter (ML) dispersion in the Tyrrhenian Sea is also discussed, along with the potential for open-source approaches including the "citizen science" perspective for both improving big data collection and educating/awareness-raising on AMD issues.

Indexed as

citizen sciencedriftersIoT technologyLagrangian dispersal modelsmarine littersmart tracking devices

Identifiers

PMID36679731
PMCPMC9863889

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.