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Adsorption behavior and mechanism of heavy metals onto microplastics: A meta-analysis assisted by machine learning.

Environmental pollution (Barking, Essex : 1987)
Microplastics (MPs) have the potential to adsorb heavy metals (HMs), resulting in a combined pollution threat in aquatic and terrestrial environments. However, due to the complexity of MP/HM properties and experimental conditions, research on the ads...

Machine learning for the adsorptive removal of ciprofloxacin using sugarcane bagasse as a low-cost biosorbent: comparison of analytic, mechanistic, and neural network modeling.

Environmental science and pollution research international
Contamination with traces of pharmaceutical compounds, such as ciprofloxacin, has prompted interest in their removal via low-cost, efficient biomass-based adsorption. In this study, classical models, a mechanistic model, and a neural network model we...

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures.

Environmental pollution (Barking, Essex : 1987)
Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mix...

Groundwater health risk assessment and its temporal and spatial evolution based on trapezoidal fuzzy number-Monte Carlo stochastic simulation: A case study in western Jilin province.

Ecotoxicology and environmental safety
The United States Environmental Protection Agency (USEPA) Four-step-Method (FSM) is a straightforward and extensively utilized tool for evaluating regional health risks, However, the complex and heterogeneous groundwater environment system causes gre...

Collaboration of bacterial consortia for biodegradation of high concentration phenol and potential application of machine learning.

Chemico-biological interactions
Mixed culture of microorganisms is an effective method to remove high concentration of phenol in wastewater. At present, it is still a challenge for microorganisms to remove high-concentration phenol from wastewater. In this study, a phenol-degrading...

Artificial neural network modeling for the prediction, estimation, and treatment of diverse wastewaters: A comprehensive review and future perspective.

Chemosphere
The application of artificial neural networks (ANNs) in the treatment of wastewater has achieved increasing attention, as it enhances the efficiency and sustainability of wastewater treatment plants (WWTPs). This paper explores the application of ANN...

Predicting bioavailability of potentially toxic elements (PTEs) in sediment using various machine learning (ML) models: A case study in Mahabad Dam and River-Iran.

Journal of environmental management
Considering the significant impact of potentially toxic elements (PTEs) on the ecosystem and human health, this paper, investigated the contamination level of four PTEs (Zn, Cu, Mo and Pb) and their mobility in sediments of Mahabad dam and river. Cho...

Sustainable utilization of FeO-modified activated lignite for aqueous phosphate removal and ANN modeling.

Environmental research
Lignites are widely available and cost-effective in many countries. Sustainable methods for their utilization drive innovation, potentially advancing environmental sustainability and resource efficiency. In the present study, FeO (∼25.1 nm) supported...

Discovering transformation products of pharmaceuticals in domestic wastewaters and receiving rivers by using non-target screening and machine learning approaches.

The Science of the total environment
Wastewater treatment plants (WWTPs) are an important source of pharmaceuticals in surface water, but information about their transformation products (TPs) is very limited. Here, we investigated occurrence and transformation of pharmaceuticals and TPs...

Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye.

Environmental science and pollution research international
Groundwater resources in Bitlis province and its surroundings in Türkiye's Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region's volcanic rock structure. To ...