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Water
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Water Pollution Monitoring, Modelling and Management
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Water Pollution Monitoring, Modelling and Management

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

Deadline for manuscript submissions: 20 May 2025 | Viewed by 2789

Special Issue Editors

Prof. Dr. Rongkui Su

E-Mail Website
Guest Editor
College of Environmental Science and Engineering, Central South University of Forestry and Technology, Changsha, China
Interests: water pollution control; emerging organic pollutants; adsorption; catalysis; resource utilization
Special Issues, Collections and Topics in MDPI journals
Dr. Yiting Luo

E-Mail Website
Guest Editor Assistant
Business College, Hunan First Normal University, Changsha, China
Interests: resource; environmental waste; high value utilization; environmental management; life cycle; water pollution control; emerging organic pollutants; environmental assessment; ecological restoration; adsorption; catalysis; water pollution; heavy metal

Special Issue Information

Dear Colleagues,

The frequency of water pollution incidents and their accompanying hazards have generated new requirements for the emergency capacity construction of governments. Therefore, management departments and environmental experts are committed to developing novel water pollution monitoring and early warning response technologies to ensure water quality safety. With the development of big data, artificial intelligence, and environmental monitoring technology, the current water monitoring infrastructure is becoming increasingly sound, and the accumulation of monitoring data is becoming increasingly rich. The conditions for achieving intelligent monitoring and early warning supported by big data are mature. Under the monitoring of the sudden pollution monitoring–early warning–tracing technology system, conducting key technology research such as sudden pollution abnormal warning, optimizing the layout of emergency monitoring sections, and initiating the identification and risk analysis of emergency response projects is a hot issue and an urgent direction for intelligent monitoring and warning regarding water pollution. This Special Issue aims to evaluate and analyze the latest research progress in water pollution monitoring and early warning, modeling and management, and prevention and control, particularly water pollution monitoring, modeling and management based on big data and artificial intelligence.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Water pollution monitoring technology;
  • Water quality prediction model;
  • Water resource management;
  • Water pollution prevention and control.

Dr. Rongkui Su
Guest Editor

Dr. Yiting Luo
Guest Editor Assistant

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. 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

  • water pollution
  • monitoring technology
  • intelligent warning
  • water quality model
  • artificial intelligence
  • pollution prevention and control
  • water resource management
  • wastewater resource utilization

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

Published Papers (3 papers)

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Research

17 pages, 14314 KiB  
Article
Design of a 3D Platform for the Evaluation of Water Quality in Urban Rivers Based on a Digital Twin Model
by Yanan Xu, Ming Hui and Haozhe Qu
Water 2024, 16(24), 3668; https://doi.org/10.3390/w16243668 - 19 Dec 2024
Viewed by 606
Abstract
To improve the informatization construction and intelligent decision-making level of river and lake basin management, the water quality of a digital twin basin was considered as the starting point and a water quality evaluation platform for Chuancheng River and Baihe River in Nanyang [...] Read more.
To improve the informatization construction and intelligent decision-making level of river and lake basin management, the water quality of a digital twin basin was considered as the starting point and a water quality evaluation platform for Chuancheng River and Baihe River in Nanyang City, Henan Province was established. Based on digital twin technology, the platform establishes a virtual space city model, uses the long short-term memory algorithm to establish a water quality prediction model, draws the distribution of water pollution factors in two dimensions based on Kriging interpolation, simulates the pollutant diffusion in three dimensions based on numerical simulation, and finally builds a visual platform for evaluation and analysis. The platform combines digital twin with three models: one-dimensional (1D) water quality data processing, two-dimensional pollutant distribution, and three-dimensional (3D) pollutant diffusion simulation to achieve visual and comprehensive management of water quality assessment. Compared with the traditional 1D water quality data management platform, the proposed digital twin 3D urban river water quality evaluation platform system solves the problems of low visualization degree, single management, and incomplete analysis, as well as provides a new technical guarantee for the management of urban river water quality. Full article
(This article belongs to the Special Issue Water Pollution Monitoring, Modelling and Management)
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14 pages, 3407 KiB  
Article
Synergistic Enhancement of Oxytetracycline Hydrochloride Removal by UV/ZIF-67 (Co)-Activated Peroxymonosulfate
by Yiting Luo, Zhao Liu, Mingqiang Ye, Yihui Zhou, Rongkui Su, Shunhong Huang, Yonghua Chen and Xiangrong Dai
Water 2024, 16(18), 2586; https://doi.org/10.3390/w16182586 - 12 Sep 2024
Cited by 4 | Viewed by 657
Abstract
This study developed a new system for removing antibiotics using UV/ZIF-67 (Co)-activated peroxymonosulfate. The presence of antibiotic organic pollutants in urban sewage presents a substantial challenge for sewage treatment technologies. Due to the persistent chemical stability of antibiotics, their low environmental concentrations, and [...] Read more.
This study developed a new system for removing antibiotics using UV/ZIF-67 (Co)-activated peroxymonosulfate. The presence of antibiotic organic pollutants in urban sewage presents a substantial challenge for sewage treatment technologies. Due to the persistent chemical stability of antibiotics, their low environmental concentrations, and their resistance to degradation, effectively removing residual antibiotics remains a significant issue in urban wastewater treatment. This study introduces an eco-friendly photocatalytic technology designed to enhance the removal of oxytetracycline (OTC) from municipal wastewater using a UV/ZIF-67 (Co)/PMS system. The results showed that compared with UV, UV/PMS, ZIF-67 (Co), ZIF-67 (Co)/PMS, and UV/ZIF-67 (Co) systems, the UV/ZIF-67 (Co)/PMS system had the highest OTC removal rate. When 10 mg ZIF-67 (Co) and 1 mM PMS were applied to 100 mL 30 mg/L OTC solution, the degradation efficiency reached 87.73% under 400 W ultraviolet light. Increasing the dosage of ZIF-67 (Co) and PMS can improve the removal rate of OTC, but the marginal benefit of additional dosage is reduced. The highest degradation efficiency was observed at weakly acidic pH, which may be due to potential damage to the internal structure of the catalyst and reduced performance under extreme pH conditions. The influence of chloride ions and nitrate ions on the reaction system is minimal, while bicarbonate ions exhibit a significant inhibitory effect on the removal of OTC. The UV/ZIF-67 (Co)/PMS system exhibits adaptability to various water sources, including tap water, Guitang River water, and pure water. The results of free radical identification indicate the presence of hydroxyl and sulfate groups in the UV/ZIF-67 (Co)/PMS system, both of which play important roles in the degradation of OTC. This study offers valuable insights and technical support for the green, efficient, and environmentally friendly removal of antibiotics from urban wastewater. Full article
(This article belongs to the Special Issue Water Pollution Monitoring, Modelling and Management)
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18 pages, 1655 KiB  
Article
Analyzing Priority Management for Water Quality Improvement Strategies with Regional Characteristics
by Jimin Lee, Minji Park, Byungwoong Choi, Jinsun Kim and Eun Hye Na
Water 2024, 16(10), 1333; https://doi.org/10.3390/w16101333 - 8 May 2024
Viewed by 1025
Abstract
As the management areas for NPS pollution continue to increase, it is essential to conduct a situation analysis considering the regional characteristics and the scope of pollution reduction. In this study, the focus is on differentiating regional (urban, agricultural) characteristics to enhance water [...] Read more.
As the management areas for NPS pollution continue to increase, it is essential to conduct a situation analysis considering the regional characteristics and the scope of pollution reduction. In this study, the focus is on differentiating regional (urban, agricultural) characteristics to enhance water quality and reduce pollution loads in the increasing management areas for NPSs. Furthermore, priority management areas are identified based on urgency and vulnerability, and management strategies are proposed. The assessment involved evaluating both streamflow and water quality (T-P) using long-term monitoring data and watershed models (SWAT and HSPF) that take into account regional characteristics. The results indicated notable regional improvements, with T-P pollution reductions ranging from 20.7% to 26.8% and T-P concentration reductions ranging from 16.4% to 24.7% compared to baseline conditions in unmanaged areas. Based on these research findings, it is anticipated that the efficient and effective management of NPS pollution can be implemented on a regional basis. Moreover, the results of this study will not only contribute to the establishment of pollution standards, but also significantly impact the evaluation and proposal of management objectives, thereby making a substantial contribution to national water quality policies. Full article
(This article belongs to the Special Issue Water Pollution Monitoring, Modelling and Management)
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