Microplastic and tar pollution on three Canary Islands beaches: An annual study

Herrera, Alicia; Asensio, Maite; Martínez, Ico; Santana, Ángel Rodríguez; Packard, Theodore T.

doi:10.1016/j.marpolbul.2017.10.020

Cited by 102 publications

(44 citation statements)

References 47 publications

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“…According to the studies performed in our geographical context, namely Canary Islands, five types of relevant particles are present in coastal areas [44], which are briefly described:…”

Section: A Methodology For Sample Extraction and Preparationmentioning

confidence: 99%

SMACC: A System for Microplastics Automatic Counting and Classification

et al. 2020

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The management of plastic debris is a serious issue due to its durability. Unfortunately, million tons of plastic end up in the sea becoming one of the biggest current environmental problems. One way to monitor the amount of plastic in beaches is to collect samples and visually count and sort the plastic particles present in them. This is a very time-consuming task. In this work, we present a Computer Vision-based system which is able to automatically count and classify microplastic particles (1-5 mm) into five different visual classes. After cleaning a collected sample in the lab, the proposed system makes use of a pair of its images with different characteristics. The procedure includes a segmentation step, which is based on the Sauvola thresholding method, followed by a feature extraction and classification step. Different features and classifiers are evaluated as well as a deep learning approach. The system is tested on 12 different beach samples with a total of 2507 microplastic particles. The particles of each sample were manually counted and sorted by an expert. This data represents the ground truth, which is compared later with the results of the automatic processing proposals to evaluate their accuracy. The difference in the number of particles is 34 (1.4%) and the error in their classification is less than 4% for all types except for the line shapes particles. These results are obtained in less than half of the time needed by the human expert doing the same task manually. This implies that it is possible to process more than twice as many samples using the same time, allowing the biologists to monitor wider areas and more frequently than doing the process manually. INDEX TERMS Computer vision, deep learning, microplastics classification.

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“…According to the studies performed in our geographical context, namely Canary Islands, five types of relevant particles are present in coastal areas [44], which are briefly described:…”

Section: A Methodology For Sample Extraction and Preparationmentioning

confidence: 99%

SMACC: A System for Microplastics Automatic Counting and Classification

et al. 2020

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“…MPs are dispersed into the ocean all over the world. Often detected in beaches (Herrera et al 2017;Imhof et al 2018;Naji et al 2017), seabed sediments (Karlsson et al 2017;Van Cauwenberghe et al 2013), wastewater effluents (Magnusson and Norén 2014;Murphy et al 2016;Ziajahromi et al 2016), surface waters (Eriksen et al 2013;La Daana et al 2017), freshwater systems (Horton et al 2017b) and even sea ice in the Arctic (Lusher et al 2015;Obbard et al 2014;Waller et al 2017), and the Antarctic (Waller et al 2017) transported by ocean and wind. MPs also have been observed in the atmosphere, as well as in indoor and outdoor environments (Dris et al 2017;Gasperi et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Occurrence, sources, human health impacts and mitigation of microplastic pollution

Karbalaei

Hanachi

Walker

et al. 2018

Environ Sci Pollut Res

407

168

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The presence and accumulation of plastic and microplastic (MP) debris in the natural environment is of increasing concern and has become the focus of attention for many researchers. Plastic debris is a prolific, long-lived pollutant, that is highly resistant to environmental degradation, readily adheres hydrophobic persistent organic pollutants and is linked to morbidity and mortality in numerous aquatic organisms. The prevalence of MPs within the natural environment are a symptom of continuous and rapid growth in synthetic plastic production and mismanagement of plastic waste. Many terrestrial and marine-based processes, including domestic and industrial drainage, maritime activities agricultural runoff and wastewater treatment plants (WWTPs) effluent, contribute to MP pollution in aquatic environments. MPs have been identified in food consumed by human and in air samples, and exposure to MPs via ingestion or inhalation could lead to adverse human health effects. Regulations in many countries have already been established or will soon be implemented to reduce MPs in aquatic environments. This review focuses on the occurrence, sources, and transport of MPs in terrestrial and aquatic environments to highlight potential human health effects, and applicable regulations to mitigate impacts of MPs. This study also highlights the importance of personality traits and cognitive ability in reducing the entry of MPs into the environment.

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“…The Canary Islands, located in the subtropical Northeastern Atlantic Ocean, 62 nautical miles west of Morocco at the closest point, are known for their high marine and terrestrial biodiversity. Microplastic studies in the area have been conducted in beaches [63,64] and, more recently, in fish [30]. However, with regard to seawater samples, this is the first study to report pelagic microplastics in the subsurface waters of the region.…”

Section: Comparison Of Reported Datamentioning

confidence: 99%

Pump-underway ship intake: An unexploited opportunity for Marine Strategy Framework Directive (MSFD) microplastic monitoring needs on coastal and oceanic waters

2020

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Broad scale sampling methods for microplastic monitoring in the open ocean waters remain a challenge in oceanography. A large number of samples is required to understand the distribution, abundance and fate of microplastic particles in the environment. Despite more than a decade of widespread study, there is currently no established time series of microplastic measurements and the research community is yet to establish a standardised set of methods that will allow data to be collected in a quick, affordable and interoperable way. We present a sampling technique involving the connection of a custom-built microplastic sampling device to the pump-underway ship intake system of a research vessel (RV) as an unexploited opportunity for oceanic monitoring needs concerning microplastic abundance and distribution. The method is cost effective, highly versatile and accurate, and is able to sample particles down to 50μm from opportunity platforms, thus contributing to an emerging area of study, and in particular helping to increase the monitoring reporting of data, and thereby serving as a valuable aid for the implementation of the Marine Strategy Framework Directive (MSFD). Sampling was performed during three consecutive oceanographic cruises in the subtropical NE Atlantic over a year, sampling subsurface waters (4 m depth) during navigation and while on coastal and oceanic stations. Microplastic particles were found in all stations and transects sampled. Fibres (64.42%) were predominant over fragments (35.58%), with the concentration values falling within the ranges of data reported for other areas of the Atlantic.

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Microplastic and tar pollution on three Canary Islands beaches: An annual study

Cited by 102 publications

References 47 publications

SMACC: A System for Microplastics Automatic Counting and Classification

SMACC: A System for Microplastics Automatic Counting and Classification

Occurrence, sources, human health impacts and mitigation of microplastic pollution

Pump-underway ship intake: An unexploited opportunity for Marine Strategy Framework Directive (MSFD) microplastic monitoring needs on coastal and oceanic waters

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