Water Treatment Modeling and Nutrient Recovery Processes

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Wastewater Treatment and Reuse".

Deadline for manuscript submissions: closed (10 June 2024) | Viewed by 1866

Special Issue Editors


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Guest Editor
Department of Environmental Engineering, Università della Calabria, Cosenza, Italy
Interests: wastewater treatment; nutrients removal and recovery; anaerobic digestion; soil remediation; waste disposal
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Environmental Engineering, University of Calabria, 87036 Rende, Italy
Interests: wastewater treatment; nutrients removal and recovery; anaerobic digestion; soil remediation; waste disposal
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Proper and effective wastewater management is one of the most critical environmental issues. Uncontrolled wastewater discharge can lead to soil and water bodies deterioration. In particular, high concentrations of nutrients (nitrogen and phosphorus) in wastewater can generate: eutrophication phenomena, compromising the quality of surface water bodies and, at the same time, reducing their biodiversity. In receiving water bodies, nutrient accumulation is mainly attributable to the exploitation of chemical fertilisers in agricultural activities, livestock manure and digestates as soil improvers, and urban and industrial wastewater discharge. Moreover, with the growth of urban centres and industrial development, the amount of contaminants that reach wastewater treatment plants daily is dramatically growing. Therefore, wastewater treatment plants must reach higher treatment capacities to cope with this condition. In this regard, it is necessary to develop innovative water treatments to ensure high-quality standards of effluents. Moreover, the definition of processes for the recovery of nutrients from treated wastewater is of great relevance, given reducing the consumption of natural resources.

The Special Issue welcomes research articles or reviews focusing on the latest knowledge and innovations in contaminant removal and nutrient recovery from water and wastewater. We are interested in contributions that report the results of studies conducted on a laboratory scale or on existing real plants. Contributions should show originality and significantly contribute to the scope of the Special Issue.

Dr. Carlo Limonti
Dr. Maria Curcio
Prof. Dr. Alessio Siciliano
Guest Editors

Manuscript Submission Information

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Keywords

  • agricoltural wastewater
  • biological process
  • chemical–physical treatment
  • industrial wastewater
  • nutrient recovery
  • urban wastewater
  • wastewater process modelling
  • wastewater recovery and reuse
  • wastewater treatment

Published Papers (1 paper)

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Research

17 pages, 4010 KiB  
Article
Advancing Water Quality Research: K-Nearest Neighbor Coupled with the Improved Grey Wolf Optimizer Algorithm Model Unveils New Possibilities for Dry Residue Prediction
by Hichem Tahraoui, Selma Toumi, Amel Hind Hassein-Bey, Abla Bousselma, Asma Nour El Houda Sid, Abd-Elmouneïm Belhadj, Zakaria Triki, Mohammed Kebir, Abdeltif Amrane, Jie Zhang, Amin Aymen Assadi, Derradji Chebli, Abdallah Bouguettoucha and Lotfi Mouni
Water 2023, 15(14), 2631; https://doi.org/10.3390/w15142631 - 20 Jul 2023
Cited by 9 | Viewed by 1493
Abstract
Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in limited datasets and hindering water management research. This study focuses [...] Read more.
Monitoring stations have been established to combat water pollution, improve the ecosystem, promote human health, and facilitate drinking water production. However, continuous and extensive monitoring of water is costly and time-consuming, resulting in limited datasets and hindering water management research. This study focuses on developing an optimized K-nearest neighbor (KNN) model using the improved grey wolf optimization (I-GWO) algorithm to predict dry residue quantities. The model incorporates 20 physical and chemical parameters derived from a dataset of 400 samples. Cross-validation is employed to assess model performance, optimize parameters, and mitigate the risk of overfitting. Four folds are created, and each fold is optimized using 11 distance metrics and their corresponding weighting functions to determine the best model configuration. Among the evaluated models, the Jaccard distance metric with inverse squared weighting function consistently demonstrates the best performance in terms of statistical errors and coefficients for each fold. By averaging predictions from the models in the four folds, an estimation of the overall model performance is obtained. The resulting model exhibits high efficiency, with remarkably low errors reflected in the values of R, R2, R2ADJ, RMSE, and EPM, which are reported as 0.9979, 0.9958, 0.9956, 41.2639, and 3.1061, respectively. This study reveals a compelling non-linear correlation between physico-chemical water attributes and the content of dry tailings, indicating the ability to accurately predict dry tailing quantities. By employing the proposed methodology to enhance water quality models, it becomes possible to overcome limitations in water quality management and significantly improve the precision of predictions regarding critical water parameters. Full article
(This article belongs to the Special Issue Water Treatment Modeling and Nutrient Recovery Processes)
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