Artificial intelligence in microplastic detection and pollution control

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

Опубликована: Авг. 16, 2024

Язык: Английский

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Advancements and challenges in microplastic detection and risk assessment: Integrating AI and standardized methods

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

Опубликована: Янв. 4, 2025

Язык: Английский

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Machine learning-driven QSAR models for predicting the cytotoxicity of five common microplastics

Toxicology, Год журнала: 2024, Номер 508, С. 153918 - 153918

Опубликована: Авг. 11, 2024

Язык: Английский

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Effect of polypropylene microplastics on the performance of membrane bioreactors in wastewater treatment

Environmental Research, Год журнала: 2025, Номер unknown, С. 120837 - 120837

Опубликована: Янв. 1, 2025

Язык: Английский

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Insight into the Size Markers and Eco-Health Significance of Microplastics and Plasticizers from Typical Sources in Northwest China

Опубликована: Янв. 1, 2025

Язык: Английский

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Microplastic Pollution in Terrestrial Systems: Sources and Implications for Soil Functioning and Plant Performance

Water Air & Soil Pollution, Год журнала: 2025, Номер 236(3)

Опубликована: Фев. 24, 2025

Язык: Английский

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Artificial intelligence: A key fulcrum for addressing complex environmental health issues

Environment International, Год журнала: 2025, Номер unknown, С. 109389 - 109389

Опубликована: Март 1, 2025

Язык: Английский

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Enhanced spectral signatures with Ag nanoarrays in hyperspectral microscopy for CNN-based microplastics classfication

Frontiers in Chemistry, Год журнала: 2025, Номер 13

Опубликована: Март 21, 2025

Microplastics are a pervasive pollutant in aquatic ecosystems, raising critical environmental and public health concerns driving the need for advanced detection technologies. Microscopic hyperspectral imaging (micro-HSI), known its ability to simultaneously capture spatial spectral information, has shown promise microplastic analysis. However, widespread application is hindered by limitations such as low signal-to-noise ratios (SNR) reduced sensitivity smaller particles. To address these challenges, this study investigates use of Ag nanoarrays reflective substrates micro-HSI. The localized surface plasmon resonance (LSPR) effect enhances resolution suppressing background reflections isolating reflection bands from interference. This improvement results significantly increased SNR more distinct features. When analyzed using 3D-2D convolutional neural network (3D-2D CNN), integration improved classification accuracy 90.17% 98.98%. These enhancements were further validated through Support Vector Machine (SVM) analyses, demonstrating robustness reliability proposed approach. demonstrates potential combining with CNN models enhance micro-HSI performance, offering novel effective solution precise microplastics advancing chemical analysis, monitoring, related fields.

Язык: Английский

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Characterization and toxicological effects of microplastics in PM2.5 in background sites of the southern coast of China

Atmospheric Environment, Год журнала: 2024, Номер 337, С. 120779 - 120779

Опубликована: Авг. 24, 2024

Язык: Английский

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