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Water Purification

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An open-source deep learning model for predicting effluent concentration in capacitive deionization.

The Science of the total environment
To effectively evaluate the performance of capacitive deionization (CDI), an electrochemical ion separation technology, it is necessary to accurately estimate the number of ions removed (effluent concentration) according to energy consumption. Herein...

A novel fuzzy framework for technology selection of sustainable wastewater treatment plants based on TODIM methodology in developing urban areas.

Scientific reports
Optimal technology selection of wastewater treatment plants (WWTPs) necessitates the adoption of data-driven scientific approaches that satisfy the sustainability requirements of the urban ecosystem. Such approaches should be able to provide actionab...

Deep learning model based on urban multi-source data for predicting heavy metals (Cu, Zn, Ni, Cr) in industrial sewer networks.

Journal of hazardous materials
The high concentrations of heavy metals in municipal industrial sewer networks will seriously impact the microorganisms of the activated sludge in the wastewater treatment plant (WWTP), thus deteriorating the effluent quality and destroying the stabi...

Investigation of intra - event variations of total, dissolved and truly dissolved metal concentrations in highway runoff and a gross pollutant trap - bioretention stormwater treatment train.

Water research
Metals in stormwater can be toxic to organisms, particularly when occurring in truly dissolved form (fraction <3 kDa). Here, using 153 samples collected during six rains, we investigated intra-events variations of total, dissolved and truly dissolved...

Water quality prediction model using Gaussian process regression based on deep learning for carbon neutrality in papermaking wastewater treatment system.

Environmental research
Wastewater recycling is the measure with enormous potentiality to achieve carbon neutrality in wastewater treatment plants. High-precision online monitoring can improve the stability of wastewater treatment system and help wastewater recycling. A new...

An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants.

Environmental science & technology
Mathematical modeling plays a critical role toward the mitigation of nitrous oxide (NO) emissions from wastewater treatment plants (WWTPs). In this work, we proposed a novel hybrid modeling approach by integrating the first principal model with deep ...

Water Quality Indicator Interval Prediction in Wastewater Treatment Process Based on the Improved BES-LSSVM Algorithm.

Sensors (Basel, Switzerland)
This paper proposes a novel interval prediction method for effluent water quality indicators (including biochemical oxygen demand (BOD) and ammonia nitrogen (NH3-N)), which are key performance indices in the water quality monitoring and control of a ...

Occurrence and concentration of 20-100 μm sized microplastic in highway runoff and its removal in a gross pollutant trap - Bioretention and sand filter stormwater treatment train.

The Science of the total environment
Microplastic pollution of stormwater can be a serious threat to the environment. Gross pollutant trap (GPT) - bioretention treatment trains have been shown previously to treat (inter alia) particulate stormwater pollutants including microplastic part...

Towards better process management in wastewater treatment plants: Process analytics based on SHAP values for tree-based machine learning methods.

Journal of environmental management
Understanding the mechanisms of pollutant removal in Wastewater Treatment Plants (WWTPs) is crucial for controlling effluent quality efficiently. However, the numerous treatment units, operational factors, and the underlying interactions between thes...

A novel artificial intelligent model for predicting water treatment efficiency of various biochar systems based on artificial neural network and queuing search algorithm.

Chemosphere
This study aims at providing a robust artificial intelligent model for predicting the efficiency of heavy metal removal from aqueous solutions of biochar systems with high accuracy and reliability. Not only is it environmentally significant, but it i...