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Processes
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Innovative Strategies and Emerging Technologies in Wastewater Treatment
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Innovative Strategies and Emerging Technologies in Wastewater Treatment

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Environmental and Green Processes".

Deadline for manuscript submissions: 25 October 2025 | Viewed by 1350

Special Issue Editor

Dr. Abdelali El Gaidoumi

E-Mail Website
Guest Editor
Laboratory of Biotechnology, Bioresources and Bioinformatics (3 Bio), Higher School of Technology of Khenifra, Sultan Moulay Slimane University, Beni Mellal, Morocco
Interests: materials synthesis; photocatalysis; wastewater treatment; response surface methodology; zeolites, clays
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wastewater treatment plays a vital role in environmental protection and water sustainability, addressing challenges such as industrial discharge, emerging contaminants, and increasing global water demand. Traditional treatment methods are being enhanced with advanced and integrated approaches, incorporating physical, chemical, and biological techniques. Recent developments focus on cost-effective, energy-efficient, and environmentally friendly solutions to improve pollutant removal and resource recovery.

This Special Issue on “Innovative Strategies and Emerging Technologies in Wastewater Treatment” invites high-quality contributions on cutting-edge research and technological advancements in wastewater management. Topics of interest include, but are not limited to, the following:

  • Advanced oxidation processes (AOPs);
  • Nanomaterials and hybrid materials for water purification;
  • Membrane-based separation technologies;
  • Bioremediation and microbial treatment processes;
  • Electrochemical and photocatalytic methods;
  • Resource recovery (nutrients, metals, energy);
  • Process modeling, optimization, and AI-driven treatment solutions;
  • Sustainable and decentralized wastewater treatment systems.

We welcome original research, reviews, and case studies highlighting novel approaches and practical implementations for improved wastewater management.

Dr. Abdelali El Gaidoumi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • wastewater treatment
  • advanced oxidation processes (AOPs)
  • nanomaterials for water purification
  • membrane separation technologies
  • bioremediation and microbial treatment
  • electrochemical water treatment
  • photocatalysis for wastewater remediation
  • resource recovery and circular economy
  • process modeling and optimization
  • sustainable and decentralized treatment systems

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

23 pages, 2150 KB  
Article
Visible-Light-Driven Ferrioxalate Activation for Dye Degradation in a Recirculating Photoreactor: LED vs. Fluorescent Light Sources
by Slimane Merouani, Amina Kadri and Halima Chouib
Processes 2025, 13(9), 2716; https://doi.org/10.3390/pr13092716 - 26 Aug 2025
Viewed by 375
Abstract
This study explores the visible-light-driven photolysis of Ferrioxalate complexes for the degradation of Toluidine Blue (TB), a persistent phenothiazine dye, using a 1 L recirculating batch-loop photoreactor. The reactor system incorporated two tubular photochemical units (35 cm × 3 cm each) in series: [...] Read more.
This study explores the visible-light-driven photolysis of Ferrioxalate complexes for the degradation of Toluidine Blue (TB), a persistent phenothiazine dye, using a 1 L recirculating batch-loop photoreactor. The reactor system incorporated two tubular photochemical units (35 cm × 3 cm each) in series: the first equipped with an immersed blue fluorescent lamp (12 W, 30 cm-tube), and the second with dual external blue LED lamps (18 W total, 30 cm) encasing a double-walled glass cell. Continuous flow between the units was maintained via a peristaltic pump. Experimental investigations were used to evaluate the effects of key parameters such as Fe(III) and oxalate concentrations, initial TB load, pH, light source, flow rate, ligand type, dissolved gas type, external H2O2 addition, and the presence of various inorganic ions. The results demonstrate efficient dye degradation, with ~75% TB removal within 1 h under combined fluorescent and LED irradiation, where each reactor contributing comparably. The optimal performance was achieved at pH 4, with a 10 oxalate-to-Fe(III) molar ratio (1 mM:0.1 mM) and a flow rate of 25 mL s−1. Among various ligands tested (oxalate, acetate, citrate, EDTA), oxalate proved to be the most effective. The presence and type of anions significantly influenced degradation efficiency due to their potential scavenging effects. Although the process achieved high dye removal, TOC analysis indicated only moderate mineralization, suggesting the accumulation of non-colored intermediates. External H2O2 addition moderately improved TOC removal, likely due to enhanced hydroxyl radical generation via the Fenton mechanism. These findings highlight the promise of Ferrioxalate-based photochemical systems under visible light for dye removal, while also emphasizing the need for further research into by-product identification, mineralization enhancement, and toxicity reduction to ensure safe effluent discharge. Full article
(This article belongs to the Special Issue Innovative Strategies and Emerging Technologies in Wastewater Treatment)
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17 pages, 2729 KB  
Article
Intelligent Effluent Management: AI-Based Soft Sensors for Organic and Nutrient Quality Monitoring
by Fathima Reneeth, Tabassum-Abbasi, Tasneem Abbasi and S. A. Abbasi
Processes 2025, 13(6), 1664; https://doi.org/10.3390/pr13061664 - 26 May 2025
Viewed by 683
Abstract
Modular wastewater treatment units in large residential complexes in India’s crowded cities often lack stringent monitoring due to cost constraints and limited technical manpower. Although these plants must meet effluent standards, testing often requires sending samples to external labs, causing delays and added [...] Read more.
Modular wastewater treatment units in large residential complexes in India’s crowded cities often lack stringent monitoring due to cost constraints and limited technical manpower. Although these plants must meet effluent standards, testing often requires sending samples to external labs, causing delays and added costs. As a result, they are rarely monitored, risking improper effluent discharge. Quick, cost-effective assessments of effluent quality could significantly improve plant operation and maintenance. Addressing the special challenges faced by such wastewater treatment systems, artificial intelligence (AI)-based soft sensors and virtual instruments have been developed to forecast effluent quality with the help of a water quality parameter that is inexpensively, easily, and immediately measurable with a hand-held device. In this study, advanced artificial neural network (ANN)-based soft sensors were developed to enhance the monitoring and management of effluent quality in five modular wastewater treatment plants in Bangalore. The models serve as virtual instruments for the measurement of total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP), using the wastewater turbidity as the input parameter. By using these AI models, operators can better anticipate and manage water quality, ultimately contributing to more efficient and effective wastewater treatment operations. This innovative approach represents a significant advancement in wastewater treatment technology providing a practical and efficient solution to streamline monitoring and enhance overall plant performance. Full article
(This article belongs to the Special Issue Innovative Strategies and Emerging Technologies in Wastewater Treatment)
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