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

Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 9777

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Special Issue Editor

Prof. Dr. Guocheng Zhu

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Guest Editor

Department of Civil Engineering, Hunan University of Science and Technology, Xiangtan 411201, China
Interests: water treatment; environmental monitoring; machine leaning; water source management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Today, we are more active than ever on the Earth, and the damage to ecology is greater than ever. Water ecology needs to be protected better, and people's health should also receive more attention. At present, the safety of drinking water supply faces problems, such as pollution of drinking water sources, insufficient water quality, backward treatment technology of existing water supply plants, and pollution of the water supply pipe network system. However, at the same time, the demand for high-quality drinking water is increasing. This contradiction inevitably poses a huge risk to the quality of drinking water. These threats include organic matter, heavy metals, nutrients, emerging pollutants, and more. The main objective of this topic is to collect new monitoring, assessment, and treatment techniques related to drinking water quality. We welcome the use of successful risk assessment models to assess the quality of water affected by the environment, including disinfection by-products, nutrients, heavy metals, organics, microplastics, metal nanoparticles, and more. It also includes an assessment of water quality caused by human actions, such as human mining, industrial wastewater discharge, and agricultural activities. New water treatment technologies are also very welcome. The main purpose of this special is to promote people's attention to drinking water and raise awareness of people’s health. The topics of this special issue are as follows, but are not limited to:

Environmental impact assessment on source water;
pollutant monitoring and evaluation and its new technologies;
new technologies for drinking water treatment;
the migration and transformation processes of pollutants;
monitoring, treatment, and protection technology of drinking water in pipe networks;
new model for assessment of water quality using artificial intelligence.

Prof. Dr. Guocheng Zhu
Guest Editor

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Keywords

water
monitoring
health
treatment
assessment
model

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Published Papers (5 papers)

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Research

15 pages, 9475 KiB

Open AccessArticle

Adsorption of Sb(III) from Solution by Immobilized Microcystis aeruginosa Microspheres Loaded with Magnetic Nano-Fe₃O₄

by Saijun Zhou, Yong Jiao, Jiarong Zou, Zhijie Zheng, Guocheng Zhu, Renjian Deng, Chuang Wang, Yazhou Peng and Jianqun Wang

Water 2024, 16(5), 681; https://doi.org/10.3390/w16050681 - 26 Feb 2024

Cited by 2 | Viewed by 1293

Abstract

In this study, a renewable and reusable immobilized Microcystis aeruginosa microsphere loaded with magnetic Nano-Fe₃O₄ composite adsorbent material is designed to study the treatment of wastewater containing heavy metal Sb(III). Through static absorption experiments combined with various characterization methods, this article studies the absorption process and mechanism of Sb(III), and investigates the optimal preparation conditions and environmental influencing factors. The results show that the optimal preparation conditions for immobilized Microcystis aeruginosa microspheres loaded with magnetic Nano-Fe₃O₄ adsorbent materials are 50.0% mass fraction of Microcystis suspension, 1.5% mass fraction of Nano-Fe₃O₄, and 2.5% mass fraction of sodium alginate. When the pH of the solution is 4, the reaction temperature is 25 °C, and the adsorbent dosage is 8.5 g/L, the removal rate of Sb(III) is the highest, reaching 83.62% within 120 min. The adsorption process conforms to the pseudo-second order kinetic model and Langmuir adsorption isotherm model, mainly characterized by chemical adsorption and surface complexation. Therefore, the composite material has been proven to be an efficient Sb (III) adsorption material. Full article

(This article belongs to the Special Issue Drinking Water Quality and Health Risk Assessment)

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23 pages, 8767 KiB

Open AccessArticle

The Degradation of Sulfamethoxazole via the Fe²⁺/Ultraviolet/Sodium Percarbonate Advanced Oxidation Process: Performance, Mechanism, and Back-Propagate–Artificial Neural Network Prediction Model

by Juxiang Chen, Chong Ruan, Wanying Xie, Caiqiong Dai, Yuqiong Gao, Zhenliang Liao and Naiyun Gao

Water 2024, 16(4), 532; https://doi.org/10.3390/w16040532 - 7 Feb 2024

Viewed by 1754

Abstract

The degradation of sulfamethoxazole (SMX) via the Fe²⁺/Ultraviolet (UV)/sodium percarbonate (SPC) system was comprehensively investigated in this study, including the performance optimization, degradation mechanism, and predicting models. The degradation condition of SMX was optimized, and it was found that appropriate amounts [...] Read more.

C_{{Fe}^{2 +}}

(10~30 μM) and C_SPC (10 μM) under an acidic condition (pH = 4~6) were in favor of a higher degradation rate. According to probe compound experiments, it was considerable that

∙ OH

and

∙ {CO}_{3}^{-}

was the primary and subordinate free radical in SMX degradation, and

k_{∙ OH, SMX}

maintained two times more than that of

k_{{∙ CO}_{3}^{-}, SMX}

, especially under acidic conditions. The UV direct photolysis and other active intermediates were also responsible for the SMX degradation. These active intermediates were produced via the Fe²⁺/UV/SPC system, involving

{∙ HO}_{2}

{HCO}_{4}^{-}

∙ O_{2}^{-}

, or ¹O₂. Furthermore, when typical anions co-existed, the degradation of SMX was negatively influenced, owing to

{HCO}_{3}^{-}

and

{CO}_{3}^{2 -}

possibly consuming

∙ OH

or H₂O₂ to compete with SMX. In addition, the prediction model was successfully established via the back-propagate artificial neural network (BP-ANN) method. The degradation rate of SMX was well forecasted via the Back-Propagate–Artificial Neural Network (BP-ANN) model, which was expressed as

Y_{pre} = \tanh (\tanh (x_{i} W^{ih}) W^{ho})

. The BP-ANN model reflected the relative importance of influence factors well, which was pH > t >

C_{{Fe}^{2 +}} \approx C_{SPC}

. Compared to the response surface method Box–Behnken design (RSM-BBD) model (R² = 0.9765, relative error = 3.08%), the BP-ANN model showed higher prediction accuracy (R² = 0.9971) and lower error (1.17%) in SMX degradation via the Fe²⁺/UV/SPC system. These findings help us to understand, in-depth, the degradation mechanism of SMX; meanwhile, they are conducive to promoting the development of the Fe²⁺/UV/SPC system in SMX degradation, especially in some practical engineering cases. Full article

(This article belongs to the Special Issue Drinking Water Quality and Health Risk Assessment)

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Graphical abstract

13 pages, 2234 KiB

Open AccessArticle

Public Water Service Disruptions: A Descriptive Analysis of Boil Water Advisories

by Fahad Alzahrani and Rady Tawfik

Water 2024, 16(3), 443; https://doi.org/10.3390/w16030443 - 29 Jan 2024

Cited by 1 | Viewed by 1653

Abstract

Water is the essence of life. It possesses profound spiritual and cultural importance, and serving as an indispensable requirement for the achievement of sustainable development. Access to safe, sufficient, affordable, and reliable drinking water is a human right. Water advisories can be used as an indicator of the reliability of access to safe drinking water. The objective of this article is to explore the trends and characteristics of boil water advisories (BWAs) and the reasons behind them. Visual and statistical tools were employed to describe the drinking water advisory data in Kentucky (USA). The dataset covers all counties in Kentucky for 17 years from 2004 to 2020 and contains 378 water systems and 36,673 BWAs. The average duration of BWAs was 5 days. The number of BWAs issued increased, while the average duration decreased during the study period. More BWAs occurred in the summer months (29%), in surface water (92%), and in large systems (54%). The leading factor for issuing a BWA was because of a line break or a leak (87%). It is imperative for governments, organizations, and communities to collaborate to address these issues effectively. Investing in sustainable and resilient water infrastructure is crucial to ensure access to safe water. Full article

(This article belongs to the Special Issue Drinking Water Quality and Health Risk Assessment)

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16 pages, 4432 KiB

Open AccessArticle

Application of EfficientNet and YOLOv5 Model in Submarine Pipeline Inspection and a New Decision-Making System

by Xuecheng Li, Xiaobin Li, Biao Han, Shang Wang and Kairun Chen

Water 2023, 15(19), 3386; https://doi.org/10.3390/w15193386 - 27 Sep 2023

Cited by 3 | Viewed by 2080

Abstract

Submarine pipelines are the main means of transporting oil and gas produced offshore. The present work proposed a deep learning technology to identify damage caused by characteristic events and abnormal events using pipeline images collected by remotely operated vehicles (ROVs). The EfficientNet and You Only Look Once (YOLO) models were used in this study to classify images and detect events. The results show that the EfficentNet model achieved the highest classification accuracy at 93.57 percent, along with a recall rate of 88.57 percent. The combining of the EfficentNet and YOLOv5 models achieved a higher accuracy of detecting submarine pipeline events and outperformed any other methods. A new decision-making system that integrates the operation and maintenance of the model is proposed and a convenient operation is realized, which provides a new construction method for the rapid inspection of submarine pipelines. Overall, the results of this study show that images acquired via ROVs can be applied to deep learning models to examine submarine pipeline events. The deep learning model is at the core of establishing an effective decision support system for submarine pipeline inspection and the overall application framework lays the foundation for practical application. Full article

(This article belongs to the Special Issue Drinking Water Quality and Health Risk Assessment)

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14 pages, 11003 KiB

Open AccessArticle

Luminescence Toxicological Analysis of Water Supply Systems in Dispersed Rural Areas: A Case Study in Boyacá, Colombia

by Yadi Johaira Ramos-Parra, Jaime Díaz-Gómez, Mónica Viviana Mesa-Torres, Sergio David Torres-Piraquive, Nohora Yaneth Zipa-Casas, Sandra Suescún-Carrero and Mabel Medina-Alfonso

Water 2023, 15(13), 2474; https://doi.org/10.3390/w15132474 - 5 Jul 2023

Viewed by 1799

Abstract

The quality of water supply systems is still a major problem in developing countries, especially in rural areas. The acute bioluminescence V. fischeri inhibition assay is widely recognized as a toxicological method that can be used to detect the acute effects of different contaminants. In this study, the physicochemical characteristics and toxicology of 72 water samples collected in 18 rural aqueducts located in Boyacá (Colombia) were evaluated. The primary economic activities identified as potential influencers of water quality in the water supply basins were agriculture (n = 3), livestock (n = 2), and domestic sewage discharge (n = 1). The average luminescence inhibition rate was 66%, with a minimum of 29%, and a maximum of 97%. A total of 85% of the tested samples (n = 61) had “moderate acute hazard”, while 15% (n = 15) had “acute hazard”. A total of 95% of the aqueducts distributed water with high risk. There was a weak positive correlation between the apparent color and the V. fischeri inhibition rate (p < 0.05). The water treatments, including disinfection, and the economic activities had no correlation with the inhibition rate of luminescent bacteria. The results of this investigation can be used by sanitary authorities to incorporate future toxicological monitoring of chemical contaminants, such as humic substances and metals, into water-quality monitoring in rural areas. Full article

(This article belongs to the Special Issue Drinking Water Quality and Health Risk Assessment)

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