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Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach
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 a...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863889/ https://www.ncbi.nlm.nih.gov/pubmed/36679731 http://dx.doi.org/10.3390/s23020935 |
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author | Merlino, Silvia Locritani, Marina Guarnieri, Antonio Delrosso, Damiano Bianucci, Marco Paterni, Marco |
author_facet | Merlino, Silvia Locritani, Marina Guarnieri, Antonio Delrosso, Damiano Bianucci, Marco Paterni, Marco |
author_sort | Merlino, Silvia |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9863889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-98638892023-01-22 Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach Merlino, Silvia Locritani, Marina Guarnieri, Antonio Delrosso, Damiano Bianucci, Marco Paterni, Marco Sensors (Basel) Article 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. MDPI 2023-01-13 /pmc/articles/PMC9863889/ /pubmed/36679731 http://dx.doi.org/10.3390/s23020935 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Merlino, Silvia Locritani, Marina Guarnieri, Antonio Delrosso, Damiano Bianucci, Marco Paterni, Marco Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title | Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title_full | Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title_fullStr | Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title_full_unstemmed | Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title_short | Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach |
title_sort | marine litter tracking system: a case study with open-source technology and a citizen science-based approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863889/ https://www.ncbi.nlm.nih.gov/pubmed/36679731 http://dx.doi.org/10.3390/s23020935 |
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