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Identification, Treatment and Risk Assessment of Emerging Contaminants in Water...
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Identification, Treatment and Risk Assessment of Emerging Contaminants in Water Ecosystems

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: closed (20 March 2026) | Viewed by 2294

Special Issue Editors

Dr. Sai Xu

E-Mail Website
Guest Editor
School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Nanjing, China
Interests: antibiotic resistance; methane oxidation; microbial community; water ecology; photocatalysis; pathogen; wastewater treatment
Special Issues, Collections and Topics in MDPI journals
Dr. Yuxiang Zhu

E-Mail Website
Guest Editor
College of Chemical Engineering, Nanjing Forestry University, Nanjing 210037, China
Interests: environmental behaviors; health risk; photocatalysis; emerging contaminants; contamination control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The identification, control and treatment of emerging contaminants in water are critical for maintaining the safety and quality of our water resources. Emerging contaminants refer to a wide range of chemicals and substances that are not routinely monitored or regulated but may pose risks to human health and the environment. These include pharmaceuticals, personal care products, pesticides, industrial chemicals, and other substances such as antibiotic-resistant genes. Given the harmful effects of these contaminants on water ecosystems, it is increasingly important to understand their ecological and health risks and to develop environmentally sustainable remediation strategies.

This Special Issue welcomes critical reviews and research articles focused on the rapid, cost-effective identification and eco-friendly treatment of emerging contaminants in water ecosystems. Studies on model-based risk assessments of these contaminants are also encouraged. Contributions may explore laboratory- and field-scale solutions, integrating physical, chemical, and microbiological approaches.

Dr. Sai Xu
Dr. Yuxiang Zhu
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Water is an international peer-reviewed open access semimonthly 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 2600 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

  • emerging contaminants
  • contamination control and treatment
  • water ecosystems
  • remediation
  • risk assessment

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Published Papers (2 papers)

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Research

27 pages, 6968 KB  
Article
An Efficient Real-Time Anomaly Detection Scheme for Water Quality Monitoring
by Wenjie Guo, Leijun Huang, Yang Li and Wenxian Luo
Water 2026, 18(6), 726; https://doi.org/10.3390/w18060726 - 19 Mar 2026
Viewed by 651
Abstract
Maintaining high quality of water resources is essential to the physical health of mankind and sustainable development of society. Accordingly, it is necessary to detect anomalies in water quality variations, which may be caused by pollution. However, prompt anomaly detection is a challenging [...] Read more.
Maintaining high quality of water resources is essential to the physical health of mankind and sustainable development of society. Accordingly, it is necessary to detect anomalies in water quality variations, which may be caused by pollution. However, prompt anomaly detection is a challenging task, either demanding a lot of human effort or yielding low accuracy, due to the nonlinear and non-stationary characteristics of water quality data. In this paper, we present an efficient real-time anomaly detection scheme which boosts detection accuracy while mitigating human effort. The scheme takes a prediction–detection–verification approach in which a deep learning prediction model is built from historical data and is used to predict future values. The predicted values are compared with the actual measurements, and the residuals are inspected by a detection model. An alarm is sent to field engineers for verification for each anomaly detected by the detection model, and the verification result is analyzed by the scheme to maintain high prediction and detection accuracy. Experiments on multiple water quality datasets show that the proposed scheme achieves significantly higher recall rates and lower false alarm rates in almost all test scenarios, compared with schemes that do not utilize verification. Full article
(This article belongs to the Special Issue Identification, Treatment and Risk Assessment of Emerging Contaminants in Water Ecosystems)
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22 pages, 4115 KB  
Article
Novel Chitosan-Based Materials to Promote Water Disinfection and Degradation of Contaminants
by Giulio Farinelli, Héloïse Baldo, Laurence Soussan, Flora Lefèbvre, Katell Sénéchal-David, Jean-Noël Rebilly, Frédéric Banse and Damien Quemener
Water 2025, 17(21), 3077; https://doi.org/10.3390/w17213077 - 28 Oct 2025
Viewed by 1240
Abstract
This study explores chitosan (CS)-based materials for water purification, assessing their disinfection and contaminant degradation capabilities. A reproducible protocol was developed to fabricate homogeneous, stable CS films, validated through permeability testing and characterized using thermal (TGA), mechanical (tensile strength, elongation), and physico-chemical (FTIR-ATR, [...] Read more.
This study explores chitosan (CS)-based materials for water purification, assessing their disinfection and contaminant degradation capabilities. A reproducible protocol was developed to fabricate homogeneous, stable CS films, validated through permeability testing and characterized using thermal (TGA), mechanical (tensile strength, elongation), and physico-chemical (FTIR-ATR, water contact angle, SEM-EDX) analyses. A catalyst was employed to complex iron ions and crosslink CS chains via acrylamide functions, stabilizing the CS structure and reducing washout in water. Disinfection tests showed that pure CS exhibited strong antimicrobial activity under varying contamination levels, attributed to direct contact and slight dissolution. Functionalized CS materials acted as catalytic surfaces, requiring hydrogen peroxide (H2O2) to generate reactive oxygen species (ROS). This ROS-mediated process effectively disinfected high bacteria loads and degraded phenol. Electron paramagnetic resonance (EPR) confirmed hydroxyl radicals as the primary active species when H2O2 was present. Under lower contamination levels, residual CS within the functionalized material contributed to direct antimicrobial effects, demonstrating a synergistic action between CS and ROS. These findings highlight CS as a reliable disinfectant and functionalized CS as a versatile material for ROS-driven antimicrobial action and contaminant degradation. The results suggest potential for scalable, sustainable water treatment applications. Future work will focus on optimizing the catalyst structure to enhance ROS production and improve contaminant removal efficiency. Full article
(This article belongs to the Special Issue Identification, Treatment and Risk Assessment of Emerging Contaminants in Water Ecosystems)
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