Microplastic predictive modelling with the integration of Artificial Neural Networks and Hidden Markov Models (ANN-HMM) DOI

R. Isaac Sajan,

M. Manchu,

C Felsy

и другие.

Journal of Environmental Health Science and Engineering, Год журнала: 2024, Номер 22(2), С. 579 - 592

Опубликована: Сен. 23, 2024

Язык: Английский

Microplastics monitoring in freshwater systems: A review of global efforts, knowledge gaps, and research priorities DOI
Bu Zhao,

Ruth E Richardson,

Fengqi You

и другие.

Journal of Hazardous Materials, Год журнала: 2024, Номер 477, С. 135329 - 135329

Опубликована: Июль 27, 2024

Язык: Английский

Процитировано

27

Recent advances in microplastic removal from drinking water by coagulation: Removal mechanisms and influencing factors DOI
Yufeng Mao, Zheng-Feng Hu, Hong Li

и другие.

Environmental Pollution, Год журнала: 2024, Номер 349, С. 123863 - 123863

Опубликована: Март 31, 2024

Язык: Английский

Процитировано

22

Advanced detection tools in food fraud: A systematic review for holistic and rational detection method based on research and patents DOI Creative Commons

Annadurai Vinothkanna,

Owias Iqbal Dar,

Zhu Liu

и другие.

Food Chemistry, Год журнала: 2024, Номер 446, С. 138893 - 138893

Опубликована: Март 1, 2024

Modern food chain supply management necessitates the dire need for mitigating fraud and adulterations. This holistic review addresses different advanced detection technologies coupled with chemometrics to identify various types of adulterated foods. The data on research, patent systematic analyses (2018-2023) revealed both destructive non-destructive methods demarcate a rational approach in countries. These intricate hygiene standards AI-based technology are also summarized further prospective research. Chemometrics or techniques extensive demanded. A assessment reveals that detect involving multiple substances be simple, expeditious, precise, cost-effective, eco-friendly non-intrusive. scrutiny resulted 39 relevant experimental sets answering key questions. However, additional research is necessitated an affirmative conclusion system modern AI machine learning approaches.

Язык: Английский

Процитировано

17

Connecting the Dots: Livestock Animals as Missing Links in the Chain of Microplastic Contamination and Human Health DOI Creative Commons
Francesca Corte Pause,

Susy Urli,

Martina Crociati

и другие.

Animals, Год журнала: 2024, Номер 14(2), С. 350 - 350

Опубликована: Янв. 22, 2024

Plastic pollution is a global diffuse threat, especially considering its fragmentation into microplastics (MPs) and nanoplastics (NPs). Since the contamination of aquatic environment already well studied, most studies have now focused on soil. Moreover, number exposure routes toxic effects MNPs in humans continuously increasing. Although can cause inflammation, cytotoxicity, genotoxicity immune toxicity livestock animals, which accumulate ingested/inhaled plastic particles transfer them to through food chain, research this topic still lacking. In farm animals as missing link between soil/plant human health effects, paper aims describe their importance carriers vectors MNP contamination. As early stages, there no standard method quantify amount characteristics different matrices. Therefore, creation common database where researchers report data quantification methods could be helpful for both standardization future training an AI tool predicting abundant/dangerous polymer(s), thus supporting policy decisions reduce perfectly fitting with One Health principles.

Язык: Английский

Процитировано

15

Microplastic prevalence and human exposure in the bottled drinking water in the west Godavari region of Andhra Pradesh, India DOI

Vijaykumar Sekar,

Sheha Shaji,

Baranidharan Sundaram

и другие.

Journal of Contaminant Hydrology, Год журнала: 2024, Номер 264, С. 104346 - 104346

Опубликована: Апрель 21, 2024

Язык: Английский

Процитировано

15

Artificial intelligence in microplastic detection and pollution control DOI
Jin Hui,

Fanhao Kong,

Xiangyu Li

и другие.

Environmental Research, Год журнала: 2024, Номер 262, С. 119812 - 119812

Опубликована: Авг. 16, 2024

Язык: Английский

Процитировано

15

Advancements and challenges in microplastic detection and risk assessment: Integrating AI and standardized methods DOI
Hailong Zhang, Qiannan Duan,

Pengwei Yan

и другие.

Marine Pollution Bulletin, Год журнала: 2025, Номер 212, С. 117529 - 117529

Опубликована: Янв. 4, 2025

Язык: Английский

Процитировано

1

Microplastics, microfibers and associated microbiota biofilm analysis in seawater, a case study from the Vesuvian Coast, southern Italy DOI Creative Commons
Manuela Rossi, Alessandro Vergara, Romualdo Troisi

и другие.

Journal of Hazardous Materials, Год журнала: 2025, Номер 488, С. 137468 - 137468

Опубликована: Фев. 4, 2025

The growing concerns regarding pollution from microplastics (MPs) and microfibers (MFs) have driven the scientific community to develop new solutions for monitoring ecosystems. However, many of proposed technologies still include protocols treating environmental samples that may alter plastic materials, leading inaccurate results both in observation counting. For this reason, we are refining a protocol, based on optical microscopy without use pretreatments, applicable different matrices, which allows not only counting but also complete morphological characterization MPs MFs. Previously, protocol has successfully been tested marine sediments Vesuvian area Gulf Naples (Italy) with good results. In present study, MFs seawater collected same geographical provide comprehensive overview their distribution environments. enabled collection information colonies microorganisms microparticles. Next Generation Sequencing (NGS) metagenomic us characterize microbiota composition sampled MPs, so-called Plastisphere. analytical approach allowed several potentially pathogenic bacteria, represent potential threat environment human health. fact, they exploit ability form biofilms plastics proliferate

Язык: Английский

Процитировано

1

Artificial Intelligence-Based Microfluidic Platform for Detecting Contaminants in Water: A Review DOI Creative Commons
Yihao Zhang, Jiaxuan Li, Zhou Yu

и другие.

Sensors, Год журнала: 2024, Номер 24(13), С. 4350 - 4350

Опубликована: Июль 4, 2024

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing is detect contaminants the water. Various methods proposed for water quality testing, such as spectroscopy, chromatography, electrochemical techniques. However, traditional testing require utilization laboratory equipment, which large not suitable real-time field. Microfluidic devices can overcome limitations instruments become an efficient convenient tool analysis. At same time, artificial intelligence ideal means recognizing, classifying, predicting data obtained from microfluidic systems. based on machine learning are being developed with great significance next generation monitoring This review begins brief introduction algorithms involved materials used fabrication detection techniques platforms. Then, latest research development combining two pollutant bodies, including heavy metals, pesticides, micro- nanoplastics, microalgae, mainly introduced. Finally, challenges encountered future directions industrial chips discussed.

Язык: Английский

Процитировано

9

Optical detection probes and sensors for micro-/nano-plastics DOI

Ug. Praveena,

V. Raja,

K.V. Ragavan

и другие.

Reviews in Environmental Science and Bio/Technology, Год журнала: 2024, Номер 23(3), С. 569 - 599

Опубликована: Авг. 15, 2024

Язык: Английский

Процитировано

5