Publication Date:
2023-01-23
Description:
first_pagesettingsOrder Article Reprints
Open AccessArticle
Marine Litter Tracking System: A Case Study with Open-Source Technology and a Citizen Science-Based Approach
by Silvia Merlino 1,*ORCID,Marina Locritani 2ORCID,Antonio Guarnieri 3ORCID,Damiano Delrosso 3,Marco Bianucci 1ORCID andMarco Paterni 4
1
CNR-ISMAR (Istituto di Scienze Marine-Sede di La Spezia), 19032 La Spezia, Italy
2
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Roma 2, 00143 Roma, Italy
3
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Bologna, 40127 Bologna, Italy
4
CNR-IFC (Istituto di Fisiologia Clinica-Pisa), 56124 Pisa, Italy
*
Author to whom correspondence should be addressed.
Sensors 2023, 23(2), 935; https://doi.org/10.3390/s23020935
Received: 28 November 2022 / Revised: 9 January 2023 / Accepted: 10 January 2023 / Published: 13 January 2023
(This article belongs to the Special Issue Enabling Citizen Science in Communal Smart Environments with IoT Technology)
Download Browse Figures Review Reports Versions Notes
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.
Description:
This research was funded by the INGV “ML-DAR Project, ricerca libera—9999.521 RL2019”; moreover, this paper is part of the NAUTILOS project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 101000825.
Description:
Published
Description:
935
Description:
7TM.Sviluppo e Trasferimento Tecnologico
Description:
JCR Journal
Keywords:
IoT technology
;
citizen science
;
marine litter
;
smart tracking devices
;
Lagrangian dispersal models
;
drifters
;
03.02. Hydrology
Repository Name:
Istituto Nazionale di Geofisica e Vulcanologia (INGV)
Type:
article
Permalink
