AIMC Topic: Wastewater

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Enhancement of ultrasonic disintegration of sewage sludge by aeration.

Journal of environmental sciences (China)
Sonication is an effective way for sludge disintegration, which can significantly improve the efficiency of anaerobic digestion to reduce and recycle use of sludge. But high energy consumption limits the wide application of sonication. In order to im...

Sequential dynamic artificial neural network modeling of a full-scale coking wastewater treatment plant with fluidized bed reactors.

Environmental science and pollution research international
This study proposed a sequential modeling approach using an artificial neural network (ANN) to develop four independent models which were able to predict biotreatment effluent variables of a full-scale coking wastewater treatment plant (CWWTP). Suita...

Prediction of effluent concentration in a wastewater treatment plant using machine learning models.

Journal of environmental sciences (China)
Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentratio...

Artificial neural network modelling of pharmaceutical residue retention times in wastewater extracts using gradient liquid chromatography-high resolution mass spectrometry data.

Journal of chromatography. A
The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastewater extracts is presented using artificial neural networks for the first time. Radial basis functio...

Spatiotemporal evolution and driver analysis of wastewater greenhouse gas emissions in Chinese mainland: Insights and future trends.

Environmental research
Wastewater greenhouse gas (GHG) emissions represent a complex system characterized by distinct spatial-temporal patterns influenced by various drivers. This study examined the spatiotemporal heterogeneity of wastewater GHG emission intensity and tota...

Combining flow virometry with tree-based machine learning models for rapid virus particle estimation in different wastewater matrices.

Water research
Enumerating virus particles (VPs) at different stages of the wastewater treatment process or along the distribution network is essential for ensuring high performance and reducing public health risks. Herein, we aimed to (i) optimize the flow viromet...

Generative deep learning model assisted multi-objective optimization for wastewater nitrogen to protein conversion by photosynthetic bacteria.

Bioresource technology
For decades, the photosynthetic bacteria (PSB)-based nitrogen treatment and valorization from wastewater have been explored. However, balancing nitrogen removal performance and resource recovery potential in PSB has remained a key unresolved issue fo...

Morphotype-resolved characterization of microalgal communities in a nutrient recovery process with ARTiMiS flow imaging microscopy.

Water research
Microalgae-driven nutrient recovery represents a promising technology for phosphorus removal from wastewater while simultaneously generating biomass that can be valorized to offset treatment costs. As full-scale processes come online, system paramete...

Advances in sulfate-reducing bacteria-driven bioelectrolysis: mechanisms and applications in microbial electrolysis cell technology.

Environmental research
The discharge of sulfate-rich wastewater from chemical and pharmaceutical and food processing industries results in serious environmental problems that impact both the natural environment and human health. The conventional sulfate removal process usi...

Machine Learning-Assisted Discovery of Bimetallic Oxides for Highly Efficient Catalytic Ozonation.

Environmental science & technology
Catalytic ozonation stands out as an effective process in the advanced treatment of industrial wastewater, where heterogeneous catalysts play a pivotal role. Here, by screening 1603 bimetallic oxides via machine learning (ML), a pioneering ZnCuO was ...