Identification of microplastics and associated contaminants using ultra high resolution microscopic and spectroscopic techniques

Melo-Agustín, Paola; Kozak, Eva R.; Perea-Flores, María de Jesús; Mendoza-Pérez, Jorge A.

doi:10.1016/j.scitotenv.2022.154434

Cited by 28 publications

(2 citation statements)

References 52 publications

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“…As a high-resolution tool, AFM enables a more detailed examination of the physical properties of microplastics [56]. For instance, Melo-Agustín et al [57] employed AFM for morphological analysis of microplastic surfaces, discovering that polyethylene (PE) microplastic surfaces exhibit higher levels of roughness than polypropylene (PP) microplastic surfaces. This observation suggests that PE is more susceptible to degradation than PP, potentially leading to greater contaminant adsorption.…”

Section: Emerging Contaminantsmentioning

confidence: 99%

Employing Atomic Force Microscopy (AFM) for Microscale Investigation of Interfaces and Interactions in Membrane Fouling Processes: New Perspectives and Prospects

Wei,

Zhang,

Wang

et al. 2024

Membranes

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Membrane fouling presents a significant challenge in the treatment of wastewater. Several detection methods have been used to interpret membrane fouling processes. Compared with other analysis and detection methods, atomic force microscopy (AFM) is widely used because of its advantages in liquid-phase in situ 3D imaging, ability to measure interactive forces, and mild testing conditions. Although AFM has been widely used in the study of membrane fouling, the current literature has not fully explored its potential. This review aims to uncover and provide a new perspective on the application of AFM technology in future studies on membrane fouling. Initially, a rigorous review was conducted on the morphology, roughness, and interaction forces of AFM in situ characterization of membranes and foulants. Then, the application of AFM in the process of changing membrane fouling factors was reviewed based on its in situ measurement capability, and it was found that changes in ionic conditions, pH, voltage, and even time can cause changes in membrane fouling morphology and forces. Existing membrane fouling models are then discussed, and the role of AFM in predicting and testing these models is presented. Finally, the potential of the improved AFM techniques to be applied in the field of membrane fouling has been underestimated. In this paper, we have fully elucidated the potentials of the improved AFM techniques to be applied in the process of membrane fouling, and we have presented the current challenges and the directions for the future development in an attempt to provide new insights into this field.

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Section: Emerging Contaminantsmentioning

confidence: 99%

Employing Atomic Force Microscopy (AFM) for Microscale Investigation of Interfaces and Interactions in Membrane Fouling Processes: New Perspectives and Prospects

Wei,

Zhang,

Wang

et al. 2024

Membranes

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“…For example, to adequately quantify MPs, restrictive procedures to avoid airborne contamination have to be secured [ 37 , 38 ]. Various approaches are commonly used to fulfill the second phase concerning the detection and quantification of MPs in environmental and biological matrices: microscopy [ 39 , 40 ], pyrolysis combined with gas chromatography [ 41 , 42 ], Fourier-transform infrared (FTIR) spectroscopy [ 43 , 44 ], micro-FTIR [ 5 , 45 ], and scanning electron microscopy [ 41 , 46 ]. Both phases require the highest levels of experience since methodological issues challenge data produced by researchers.…”

Section: Introductionmentioning

confidence: 99%

Application of Pattern Recognition and Computer Vision Tools to Improve the Morphological Analysis of Microplastic Items in Biological Samples

Astel,

Piskuła

2023

Toxics

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Since, in many routine analytical laboratories, a stereomicroscope coupled with a digital camera is not equipped with advanced software enabling automatic detection of features of observed objects, in the present study, a procedure of feature detection using open-source software was proposed and validated. Within the framework of applying microscopic expertise coupled with image analysis, a set of digital images of microplastic (MP) items identified in organs of fish was used to determine shape descriptors (such as length, width, item area, etc.). The edge points required to compute shape characteristics were set manually in digital images acquired by the camera coupled with a binocular, and respective values were computed via the use of built-in MotiConnect software. As an alternative, a new approach consisting of digital image thresholding, binarization, the use of connected-component labeling, and the computation of shape descriptors on a pixel level via using the functions available in an OpenCV library or self-written in C++ was proposed. Overall, 74.4% of the images were suitable for thresholding without any additional pretreatment. A significant correlation was obtained between the shape descriptors computed by the software and computed using the proposed approach. The range of correlation coefficients at a very high level of significance, according to the pair of correlated measures, was higher than 0.69. The length of fibers can be satisfactorily approximated using a value of half the length of the outer perimeter (r higher than 0.75). Compactness and circularity significantly differ for particles and fibers.

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Methods for Micro‐ and Nanoplastics Analysis

Slusarski‐Santana,

Panatto,

dos Passos

et al. 2024

Toxic Effects of Micro‐ and Nanoplastics

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Identification of microplastics and associated contaminants using ultra high resolution microscopic and spectroscopic techniques

Cited by 28 publications

References 52 publications

Employing Atomic Force Microscopy (AFM) for Microscale Investigation of Interfaces and Interactions in Membrane Fouling Processes: New Perspectives and Prospects

Employing Atomic Force Microscopy (AFM) for Microscale Investigation of Interfaces and Interactions in Membrane Fouling Processes: New Perspectives and Prospects

Application of Pattern Recognition and Computer Vision Tools to Improve the Morphological Analysis of Microplastic Items in Biological Samples

Methods for Micro‐ and Nanoplastics Analysis

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