Using artificial intelligence to rapidly identify microplastics pollution and predict microplastics environmental behaviors

Journal of Hazardous Materials, Год журнала: 2024, Номер 474, С. 134865 - 134865

Опубликована: Июнь 12, 2024

Язык: Английский

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Revealing the Removal Behavior of Five Neglected Microplastics in Coagulation-Ultrafiltration Processes: Insights from Experiments and Predictive Modeling

Journal of Hazardous Materials, Год журнала: 2025, Номер 491, С. 137857 - 137857

Опубликована: Март 6, 2025

Язык: Английский

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Pollution of the aquatic environment by plasticizers leached from microplastics originating from linear sewage systems

Desalination and Water Treatment, Год журнала: 2025, Номер unknown, С. 101122 - 101122

Опубликована: Март 1, 2025

Язык: Английский

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Modeling of microplastics degradation in aquatic environments using an experimental plan

Journal of Hazardous Materials, Год журнала: 2024, Номер 471, С. 134396 - 134396

Опубликована: Апрель 23, 2024

The aim of this article is to apply advanced predictive modeling techniques understand the degradation process microplastics in aquatic environments. Utilizing a Fractional Factorial Central Composite Experimental Plan, study seeks develop precise statistical models that enable forecasting quantity pollutants generated during under various environmental conditions. This tool was applied model changes DOC (dissolved organic carbon) and DEHP (bis(2-ethylhexyl) phthalate) values ecosystems. methods were developed using data derived from laboratory tests conducted GC-MS technique. obtained approximating functions, considering factors such as time, water temperature, particle size, significantly reduced analysis time. A two-stage verification functions conducted, accuracy function form, its adequacy, significance input variables, their correlation with DEHP. employed Plan allowed for simultaneous reduction number experiments prediction influence variables on output values. Precise support understanding microplastic process, facilitating development effective strategies managing pollution.

Язык: Английский

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Long-term Prediction Method for PM2.5 Concentration Using Edge Channel Graph Attention Network and Gating Closed-form Continuous-time Neural Networks

Process Safety and Environmental Protection, Год журнала: 2024, Номер 189, С. 356 - 373

Опубликована: Июнь 20, 2024

Язык: Английский

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Enabling data-driven process dynamic modeling for extractive leaching and chemical precipitation

Process Safety and Environmental Protection, Год журнала: 2024, Номер 211, С. 179 - 183

Опубликована: Окт. 9, 2024

Язык: Английский

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Derivation of marine water quality criteria for copper based on artificial neural network model

Environmental Pollution, Год журнала: 2024, Номер 363, С. 125172 - 125172

Опубликована: Окт. 21, 2024

Язык: Английский

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Novel insights into halogenated carbazoles (HCZs) prediction in tap water: a comparative study of grey relational analysis-based neural networks

Journal of Cleaner Production, Год журнала: 2024, Номер unknown, С. 144482 - 144482

Опубликована: Дек. 1, 2024

Язык: Английский

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