An innovative approach for microplastic sampling in all surface water bodies using an aquatic drone

Pasquier, Gabriel; Doyen, Périne; Carlesi, Nicolas; Amara, Rachid

doi:10.1016/j.heliyon.2022.e11662

Cited by 14 publications

(4 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The type of material, size, and shape of floating plastic litter was determined according to the findings of an initial field campaign along certain rivers and canals in Scotland (including segments of rivers Kelvin and Clyde and the Forth and Clyde Canal, e.g., see Figure 1), during which the plastic litter captured in the riparian zone were sampled. There has been an increasing number of recently published studies on the methods of sampling floating macro-and meso-plastics, which range from passive to active, also using bespoke and elaborate or expensive equipment or just sourcing information via citizen science participation projects [36][37][38][39][40][41][42]. Given the plethora of sampling procedures, the optimal sampling may depend on the location and flow conditions that are characteristic of a specific river system.…”

Section: Experimental Matrixmentioning

confidence: 99%

Transport of Floating Plastics through the Fluvial Vector: The Impact of Riparian Zones

Valyrakis,

Gilja,

Liu

et al. 2024

Water

View full text Add to dashboard Cite

This study presents results from an experimental campaign to explore how different riparian zone characteristics may facilitate the transport or capturing of plastics floating through the fluvial system. Specifically, following field observations for the transport of plastics through fluvial vectors, a substantial number of flume experiments has been designed to assess the effect of floating macro-plastics and riparian zone characteristics. The results from flume experiments were analyzed using particle tracking velocimetry techniques to derive transport metrics (such as transport velocities) of macro-plastics of different sizes and shapes, released at five locations across a wide channel with distinct distance from the vegetated riverbank. The findings are discussed while considering the trapping mechanisms along the vegetated riverbank, which include a range of vegetation densities and arrangements, aiming to identify and quantify the degree of impact of each of the control parameters on the transport of floating plastics. The flow velocimetry records obtained at locations near and within the riverbank correlate well with the transport velocities of the floating plastics. Macro-plastic litter carried downstream away from the riverbank can have up to nine times the transport velocity, compared to those found within the riverbank. The change from a low to a high average density can result in about three times decrease in the transport velocity of floating macro-plastic litter within the riparian zone. These outcomes can help inform better practices for the management of riparian vegetation to maximize the trapping efficiency of macro-plastics, adapted to different flow conditions and river morphologies.

show abstract

Section: Experimental Matrixmentioning

confidence: 99%

Transport of Floating Plastics through the Fluvial Vector: The Impact of Riparian Zones

Valyrakis,

Gilja,

Liu

et al. 2024

Water

View full text Add to dashboard Cite

show abstract

“…The UAD is an aquatic surface drone, named Jellyfishbot, specifically designed for removing floating debris [25]. It is equipped with two propulsions, which are located under the two floating parts, and a remote control and communication system.…”

Section: The Rov-ulco Systemmentioning

confidence: 99%

“…It is equipped with two propulsions, which are located under the two floating parts, and a remote control and communication system. The aquatic drone can reach a top speed of 2 knots and can have autonomy in terms of power that is greater than 2 h. The UAD was tailored at the University of Littoral (ULCO) to enable plastic material sampling in different water bodies, even in confined and hard-to-reach areas such as small waterways, estuaries, or rivers [25]. The UAD is an aquatic surface drone, named Jellyfishbot, specifically designed for removing floating debris [25].…”

Section: The Rov-ulco Systemmentioning

confidence: 99%

“…The aquatic drone can reach a top speed of 2 knots and can have autonomy in terms of power that is greater than 2 h. The UAD was tailored at the University of Littoral (ULCO) to enable plastic material sampling in different water bodies, even in confined and hard-to-reach areas such as small waterways, estuaries, or rivers [25]. The UAD is an aquatic surface drone, named Jellyfishbot, specifically designed for removing floating debris [25]. It is equipped with two propulsions, which are located under the two floating parts, and a remote control and communication system.…”

Section: The Rov-ulco Systemmentioning

confidence: 99%

See 1 more Smart Citation

A New Remote Hyperspectral Imaging System Embedded on an Unmanned Aquatic Drone for the Detection and Identification of Floating Plastic Litter Using Machine Learning

et al. 2023

Self Cite

View full text Add to dashboard Cite

This paper presents a new Remote Hyperspectral Imaging System (RHIS) embedded on an Unmanned Aquatic Drone (UAD) for plastic detection and identification in coastal and freshwater environments. This original system, namely the Remotely Operated Vehicle of the University of Littoral Côte d’Opale (ROV-ULCO), works in a near-field of view, where the distance between the hyperspectral camera and the water surface is about 45 cm. In this paper, the new ROV-ULCO system with all its components is firstly presented. Then, a hyperspectral image database of plastic litter acquired with this system is described. This database contains hyperspectral data cubes of different plastic types and polymers corresponding to the most-common plastic litter items found in aquatic environments. An in situ spectral analysis was conducted from this benchmark database to characterize the hyperspectral reflectance of these items in order to identify the absorption feature wavelengths for each type of plastic. Finally, the ability of our original system RHIS to automatically recognize different types of plastic litter was assessed by applying different supervised machine learning methods on a set of representative image patches of marine litter. The obtained results highlighted the plastic litter classification capability with an overall accuracy close to 90%. This paper showed that the newly presented RHIS coupled with the UAD is a promising approach to identify plastic waste in aquatic environments.

show abstract

Capillary Skimming of Floating Microplastics via a Water‐Bridged Ratchet

Cho,

Park,

Lee

et al. 2024

Advanced Science

View full text Add to dashboard Cite

Floating microplastics (MPs) have recently become a major concern in marine pollution; however, current filter‐based technology is hardly effective for directly removing such MPs from the water surface because of specific mesh size and clogging issues. This paper introduces a new skimming concept for removing floating MPs utilizing capillary force mediated by the elevation of a hydrophilic ratchet at the air−water interface. MPs floating near the ratchet surface are spontaneously forced toward the ratchet with a concave water meniscus, driven by the Cheerios effect. The MPs can then be skimmed and temporarily held by the deforming concave water meniscus as the ratchet rises. Here, it is found that the stability of the water bridge plays a crucial role in skimming success because it provides capillary adhesion between the MP and the ratchet. The proposed capillary skimming method is observed to be effective across nearly all types of floating MPs, ranging in size from 1 to 4 mm, and with densities varying from 0.02 to 0.97 g cm−3, which is also demonstrated by a prototype of marine robot cleaner.

show abstract

An innovative approach for microplastic sampling in all surface water bodies using an aquatic drone

Cited by 14 publications

References 44 publications

Transport of Floating Plastics through the Fluvial Vector: The Impact of Riparian Zones

Transport of Floating Plastics through the Fluvial Vector: The Impact of Riparian Zones

A New Remote Hyperspectral Imaging System Embedded on an Unmanned Aquatic Drone for the Detection and Identification of Floating Plastic Litter Using Machine Learning

Capillary Skimming of Floating Microplastics via a Water‐Bridged Ratchet

Contact Info

Product

Resources

About