Variation and Uncertainty of Microplastics in Commercial Table Salts: Critical Review and Validation

Lee, Hee-Jee; Song, Nan-Seon; Kim, Jisu; Kim, Seung-Kyu

doi:10.1016/j.jhazmat.2020.123743

Cited by 48 publications

(13 citation statements)

References 55 publications

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“…The anthropogenic impact on the climate and environment has prompted the analysis and detection of pollutants or contaminants with Fourier transform infrared spectroscopy (FTIR), such as microplastics in waters , and table salts, nitrates from agricultural fertilizers in soil, − and polyaromatic hydrocarbons in the ocean’s surface. , The diversity of the chemical composition of the pollutants and the central fundamental technique of FTIR underscores the importance of a computational method for improved throughput of spectral analysis. The bottleneck is most frequently the assignment of peaks to relevant functional groups. , …”

Section: Introductionmentioning

confidence: 99%

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

et al. 2021

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Fourier Transform Infrared Spectroscopy (FTIR) is a ubiquitous spectroscopic technique. Spectral interpretation is a time-consuming process, but it yields important information about functional groups present in compounds and in complex substances. We develop a generalizable model via a machine learning (ML) algorithm using Convolutional Neural Networks (CNNs) to identify the presence of functional groups in gas phase FTIR spectra. The ML models will reduce the amount of time required to analyze functional groups and facilitate interpretation of FTIR spectra. Through web scraping, we acquire intensity-frequency data from 8728 gas phase organic molecules within the NIST spectral database and transform the data into images. We successfully train models for 15 of the most common organic functional groups, which we then determine via identification from previously untrained spectra. These models serve to expand the application of FTIR measurements for facile analysis of organic samples. Our approach was done such that we have broad functional group models that inference in tandem to provide full interpretation of a spectrum. We present the first implementation of ML using image-based CNNs for predicting functional groups from a spectroscopic method. File list (2) download file view on ChemRxiv ML functional group ID in FTIR spectra.docx (545.84 KiB) download file view on ChemRxiv ML functional group ID in FTIR spectra.pdf (645.08 KiB) Functional group identification for FTIR spectra using image-based machine learning models

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Section: Introductionmentioning

confidence: 99%

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

et al. 2021

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“…In the last few years, several studies regarding the microplastic contamination of salt intended for human consumption [ 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 ] have been published and discussed [ 171 , 172 , 173 , 174 ]. Salts provide essential nutrition elements and, thanks to their chemical characteristics and low cost, are used in food preservation methods (e.g., fruits, cheese, cereals, drinks).…”

Section: Microplastic Transport In the Food Web And Consequent Human Exposurementioning

confidence: 99%

Microplastics in the Environment: Intake through the Food Web, Human Exposure and Toxicological Effects

Pironti

Ricciardi

Motta

et al. 2021

Toxics

156

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Recently, studies on microplastics (MPs) have increased rapidly due to the growing awareness of the potential health risks related to their occurrence. The first part of this review is devoted to MP occurrence, distribution, and quantification. MPs can be transferred from the environment to humans mainly through inhalation, secondly from ingestion, and, to a lesser extent, through dermal contact. As regards food web contamination, we discuss the microplastic presence not only in the most investigated sources, such as seafood, drinking water, and salts, but also in other foods such as honey, sugar, milk, fruit, and meat (chickens, cows, and pigs). All literature data suggest not-negligible human exposure to MPs through the above-mentioned routes. Consequently, several research efforts have been devoted to assessing potential human health risks. Initially, toxicological studies were conducted with aquatic organisms and then with experimental mammal animal models and human cell cultures. In the latter case, toxicological effects were observed at high concentrations of MPs (polystyrene is the most common MP benchmark) for a short time. Further studies must be performed to assess the real consequences of MP contamination at low concentrations and prolonged exposure.

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“…density, specific surface area, and wettability). To that end, scanning electron microscopy (SEM) can be used to evaluate the particle surface, whereas dynamic imaging allows determining distributions according to particle size and shape [70,71].…”

Section: Generation Of Mps 321 Mps Generated From Biodegradable Plasticsmentioning

confidence: 99%

Biodegradable plastics in aquatic ecosystems: latest findings, research gaps, and recommendations

Ribba

Lopretti

Oca-Vásquez³

et al. 2022

Environ. Res. Lett.

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Plastic accumulation's negative impact on aquatic ecosystems is a known and undeniable problem. Much of the scientific community's efforts are focused on the effects of the most common commodity plastics, but the consequences of the so-called biodegradable plastics in these ecosystems have been little discussed. Although their biodegradable characteristic generates the widespread belief that they are harmless to the environment, it has been proven many years ago that this property cannot be taken lightly. The material´s end-of-life fate is critical to classify it as biodegradable or not. In this context, many plastics classified as biodegradable do not meet the requirements of norms and standards to be considered biodegradable in aquatic ecosystems. Furthermore, during the last five years, the scientific community has shown that they can give rise to the formation of bio-microplastics during their degradation, which can have similar effects to those of conventional microplastics or even worse. This review will detail all recent information regarding how biodegradable plastics can influence aquatic ecosystems, causing adverse health effects in living beings or acting as vectors of chemical pollutants. Besides, the key points that must be addressed in greater depth will be identified, including the need to consider a greater variety of biodegradable plastics and develop systematic methods that allow quantifying and identifying the remains of these pollutants in living species. Another aspect to consider is the dynamics of arrival and mobilization of microplastics in the oceans. It should be studied how small animals fed by filterings, such as red crabs and other zooplankton organisms, move the microplastic through the water column and get into food webs. These particles are mistakenly ingested by the number of species at different trophic levels, where bioaccumulation in tissues must be considered a toxicity factor. Finally, a series of recommendations and future perspectives will be listed.

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Variation and Uncertainty of Microplastics in Commercial Table Salts: Critical Review and Validation

Cited by 48 publications

References 55 publications

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

Functional Group Identification for FTIR Spectra Using Image-Based Machine Learning Models

Microplastics in the Environment: Intake through the Food Web, Human Exposure and Toxicological Effects

Biodegradable plastics in aquatic ecosystems: latest findings, research gaps, and recommendations

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