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Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems

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

Deadline for manuscript submissions: 19 July 2024 | Viewed by 8041

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Special Issue Editors

Dr. Habib Ullah

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Guest Editor

1. Innovation Center of the Yangtze River Delta, Zhejiang University, Hangzhou 311400, China
2. College of Environmental and Resource Science, Zhejiang University, Hangzhou, China
Interests: toxic elements; wastewater treatment; emission-reduction; energy; combustion analysis; energy conversion; biomass conversion; pyrolysis; biomass burning; hydrothermal treatment

Dr. Asfandyar Shahab

E-Mail Website
Guest Editor

College of Environmental Science and Engineering, Guilin University of Technology, Guilin, China
Interests: ground and surface water contamination; wastewater treatment; heavy metals; organic and inorganic contaminants removal; adsorption studies; nanomaterials; biochar and activated carbon; metal organic frameworks (MOFs); emerging contaminants

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore the application of SMART (Sustainable, Monitoring, Analysis, Remediation and Treatment) water systems for the integrated management of aquatic contaminant sources, pollution assessment and remediation. The use of advanced technologies and innovative approaches in SMART water systems enables real-time monitoring, the accurate detection of contaminants, and targeted remediation strategies. By linking these components, this Special Issue seeks to bridge the gap between scientific research and practical applications, fostering the development of sustainable solutions for addressing aquatic contamination challenges.

Potential topics for submission include, but are not limited to:

The development and optimization of SMART water systems:

-The design and implementation of sensor networks for the real-time monitoring of aquatic contaminants;
-The integration of data analysis algorithms for the accurate detection and identification of pollution sources;
-Automation and control systems for efficient remediation and treatment processes;
-The optimization of the layout of monitoring points in the water supply network;
-Decision support systems for guiding management actions based on real-time data.

Innovative Approaches for Pollution Assessment:

-Advances in biomonitoring and bioindicators for evaluating contamination levels and ecological impacts;
-The integration of remote sensing and geospatial analysis techniques for mapping and monitoring pollution sources;
-The development of novel analytical methods for the rapid and sensitive detection of emerging contaminants;
-Risk assessment methodologies for quantifying the impacts of aquatic contamination on human and ecological health;

Remediation Technologies and Strategies:

-The application of advanced oxidation processes, membrane filtration, and nanotechnology in SMART water systems;
-Bioremediation approaches for the removal and degradation of specific contaminants;
-Passive treatment systems for the long-term management of contaminated aquatic environments;
-The evaluation of the effectiveness and sustainability of different remediation technologies.

Case Studies and Field Applications:

-The successful implementation of SMART water systems in diverse aquatic environments;
-Demonstration projects showcasing the integration of SMART technologies for contaminant management;
-Lessons learned and challenges encountered in deploying and operating SMART water systems;
-Economic and environmental evaluations of SMART water system implementations.

Policy Frameworks and Regulatory Considerations:

-The integration of SMART water system data into policy development and decision-making processes;
-The assessment of policy gaps and the identification of strategies for improving regulatory frameworks;
-Case studies highlighting the role of SMART water systems in achieving compliance with environmental regulations;
-Socio-economic considerations and stakeholder engagement in the context of SMART water system implementation;

Submission Guidelines: Contributors are invited to submit original research articles, reviews or case studies that address the intersection of SMART water systems with aquatic contaminant sources, pollution assessment and remediation. Manuscripts should adhere to the journal's guidelines for submission. All submissions will undergo rigorous peer review to ensure high scientific quality and relevance to the Special Issue’s theme.

We believe that this Special Issue will provide a platform for researchers, practitioners and policymakers to share their knowledge, experiences and innovative solutions for managing the sources of aquatic contaminants and pollutants and their remediation using SMART water systems. Together, we can advance the understanding and application of SMART technologies in safeguarding and restoring the health of our aquatic ecosystems.

Dr. Habib Ullah
Dr. Asfandyar Shahab
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 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

SMART water systems
aquatic contaminant sources
pollution assessment
remediation technologies
monitoring and detection
decision support
risk assessment
water age
machine-learning-based optimization
hydrological modeling
cost-effective management
optimization policy
regulatory frameworks

Published Papers (5 papers)

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Research

15 pages, 1998 KiB

Open AccessArticle

Tap Water Quality: Challenges and Psychological Consequences

by Warda Khalid, Chen Shiyi, Mbega Ramadhani Ngata, Asmat Ali, Abdulwahed Fahad Alrefaei, Mikhlid H. Almutairi, Isma Kulsoom, Wakeel Hussain and Muhammad Yousuf Jat Baloch

Water 2023, 15(22), 3987; https://doi.org/10.3390/w15223987 - 16 Nov 2023

Viewed by 1499

Abstract

Investigating drinking water quality is crucial for public health, as clean water access is a fundamental requirement for a healthy life. To comprehensively assess Karachi’s drinking water quality, 152 water samples were systematically collected from five districts: Malir, Karachi West, Karachi East, Karachi South, and Karachi Central. The investigation involved analyzing various physicochemical and microbiological parameters in comparison to WHO 2011 guidelines. Additionally, integrated techniques like principal component analysis and water quality index computation offer insights into both potable and non-potable water aspects, with a focus on health-related well-being. Elevated levels of turbidity and chloride were identified across all five districts, with the residual chloride surpassing permissible limits in Karachi West and Karachi Central. Coliform and E. coli levels exhibited significant variations, with the highest mean values recorded in Karachi Central and the lowest in Karachi East. The overall analysis revealed that only 16.67%, 38.71%, 50%, 43.33%, and 58.06% of the water supply is suitable for drinking in Malir, Karachi West, Karachi East, Karachi South, and Karachi Central, respectively, while 83.33%, 61.29%, 50%, 56.67%, and 41.94% are unsuitable for drinking, posing substantial health risks. Urgent interventions in water quality management and public health are imperative to mitigate these risks associated with substandard drinking water. Full article

(This article belongs to the Special Issue Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems)

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16 pages, 3181 KiB

Open AccessArticle

Machine Learning Algorithms for Predicting the Water Quality Index

by Enas E. Hussein, Muhammad Yousuf Jat Baloch, Anam Nigar, Hussain F. Abualkhair, Faisal Khaled Aldawood and Elsayed Tageldin

Water 2023, 15(20), 3540; https://doi.org/10.3390/w15203540 - 11 Oct 2023

Cited by 3 | Viewed by 2547

Abstract

Groundwater is one of the water resources used to preserve natural water sources for drinking, irrigation, and several other purposes, especially in industrial applications. Human activities related to industry and agriculture result in groundwater contamination. Therefore, investigating water quality is essential for drinking and irrigation purposes. In this work, the water quality index (WQI) was used to identify the suitability of water for drinking and irrigation. However, generating an accurate WQI requires much time, as errors may be made during the sub-index calculations. Hence, an artificial intelligence (AI) prediction model was built to reduce both time and errors. Eighty data samples were collected from Sakrand, a city in the province of Sindh, to investigate the area’s WQI. The classification learners were used with raw data samples and the normalized data to select the best classifier among the following decision trees: support vector machine (SVM), k-nearest neighbors (K-NN), ensemble tree (ET), and discrimination analysis (DA). These were included in the classification learner tool in MATLAB. The results revealed that SVM was the best raw and normalized data classifier. The prediction accuracy levels for the training data were 90.8% and 89.2% for the raw and normalized data, respectively. Meanwhile, the prediction accuracy levels for the testing data were 86.67 and 93.33% for the raw and normalized data, respectively. Full article

(This article belongs to the Special Issue Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems)

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14 pages, 3322 KiB

Open AccessArticle

Cleansing Water: Harnessing Trimetallic Nanoparticles in Sunlight to Degrade Methylene Blue Dye, Aiding Aquatic Contaminant Cleanup

by Zaheer Ahmad, Reena Tahir, Nazli Sajjad, Farah Batool, Noor Zada and Habib Ullah

Water 2023, 15(19), 3404; https://doi.org/10.3390/w15193404 - 28 Sep 2023

Cited by 1 | Viewed by 1026

Abstract

The contamination of industrial water sources with synthetic dyes, such as methylene blue (MB), remains a persistent environmental concern, demanding effective remediation techniques. In response, this research centers on the utilization of trimetallic nanoparticles (TMNPs) composed of Fe-Ni-Cr, Fe-Ni-Cd and Fe-Ni-Cu as a promising solution to address color-related pollution in aquatic ecosystems. These nanoparticles were synthesized using the wet chemical precipitation method and rigorously characterized using Fourier transform infrared (FT-IR), energy-dispersive X-rays (EDX), and scanning electron microscopy (SEM). Armed with these trimetallic nanoparticles, our primary objective was to harness their photocatalytic prowess when exposed to direct sunlight in aqueous environments for the degradation of MB. The progress of photodegradation was meticulously monitored using a reliable visible spectrophotometer, providing insights into the degradation kinetics. Remarkably, within just six hours of solar irradiation, the TMNPs exhibited a remarkable capacity to degrade MB, achieving an impressive degradation rate ranging from 77.5% to 79.4%. In our relentless pursuit of optimization, we conducted a comprehensive examination of various parameters including catalyst dosage, dye dosage, and pH levels, focusing specifically on the Fe-Ni-Cr TMNPs. Through systematic experimentation, a trifecta of optimal conditions emerged: a pH level of 10 (resulting in a 79.35% degradation after 1.5 h), a catalyst amount of 0.005 g (yielding 43.5% degradation after 1.5 h), and a dye concentration of 40.0 ppm (culminating in a 42.54% degradation after 1.5 h). The study also extended its scope to explore the regeneration potential of the catalyst, shedding light on its sustainability in long-term applications. Amidst the vibrant interplay of color and water, TMNPs emerged as a symbol of optimism, offering a promising avenue for the removal of synthetic dyes from the water system. With each experiment and investigation, we inch closer to realizing clearer waters and brighter environmental horizons. Full article

(This article belongs to the Special Issue Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems)

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17 pages, 916 KiB

Open AccessArticle

Heavy Metals and Microbial Diversity: A Comparative Analysis of Rivers Swat and Kabul

by Basharat Ali, Anwarzeb Khan, Syed Shujait Ali, Haji Khan, Mehboob Alam, Asmat Ali, Abdulwahed Fahad Alrefaei, Mikhlid H. Almutairi and Ki In Kim

Water 2023, 15(18), 3297; https://doi.org/10.3390/w15183297 - 19 Sep 2023

Cited by 2 | Viewed by 1213

Abstract

Water contamination with heavy metals seriously affects water and sediment quality and may affect the aquatic biota. This study assessed the impact of heavy metals on the morphological characteristics of aquatic microorganisms in potentially contaminated water. Different physicochemical parameters and heavy metals contents were analyzed for toxicological assessment along with microbial diversity in the rivers Swat and Kabul. The pH of River Swat water was neutral to slightly alkaline, while River Kabul was neutral to slightly acidic. The results showed substantial variations in heavy metal concentration across different sampling points. In both River Swat and River Kabul water samples, Cu and Zn concentrations were below the permissible limits for surface and drinking water qualities while the rest of the heavy metals exceeded the permissible limit with Cd being the most abundant heavy metal. Similarly, in sediment samples all the heavy metals were below the permissible limits except for Cd that exceeded the Environment Canada (EC) limits in River Swat and EC and NOVA limits in River Kabul. The rest of the heavy metals concentrations were within the permissible limits, with few exceptions. The results showed that in River Swat, most of the contamination was of geogenic origin, while the main source of contamination in River Kabul was anthropogenic. Results of microbial analysis showed that River Swat has more diversity than River Kabul, which may be due to the low contamination profile of River Swat. It was further observed that high heavy metal concentrations negatively impact the morphological characteristics of microorganisms. The heavy metals concentration and microbial diversity were closely related to each other. Full article

(This article belongs to the Special Issue Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems)

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14 pages, 2778 KiB

Open AccessArticle

Groundwater Contamination and Risk Assessment in Greater Palm Springs

by Warda Khalid, Muhammad Yousuf Jat Baloch, Asmat Ali, Mbega Ramadhani Ngata, Abdulwahed Fahad Alrefaei, Abdur Rashid, Predrag Ilić, Mikhlid H. Almutairi and Jamil Siddique

Water 2023, 15(17), 3099; https://doi.org/10.3390/w15173099 - 29 Aug 2023

Cited by 2 | Viewed by 1143

Abstract

Groundwater is an essential resource for drinking water, but its contamination with potentially toxic elements and arsenic (As) is a global issue. To evaluate As and its levels in the Coachella Valley, the US Geological Survey (USGS) collected 17 groundwater samples. This study looked into the arsenic distribution, enrichment, hydrogeochemical behavior, and health risks associated with the samples. The comparative analysis between groundwater contamination in Greater Palm Springs and similar regions, could provide valuable insights into regional differences and common challenges. The hydrogeochemical facies showed the dominance of calcium and magnesium-bicarbonate-carbonate, indicating permanent hardness and salt deposits of residual carbonate. The Gibbs plot demonstrated that chemical weathering of rock-forming minerals and evaporation are the primary forces impacting groundwater chemistry. Geochemical modeling revealed saturation for calcite and dolomite, and under-saturation for halite. Principal component analysis identified the potential contributory sources for contamination of groundwater. The carcinogenic and non-carcinogenic potentials of the toxic elements arsenic, cadmium, chromium (VI), and lead were calculated using a human health risk assessment model. For both adults and children, the highest non-carcinogenic mean value was observed for arsenic (8.52 × 10⁻¹), with the lowest for cadmium (1.32 × 10⁻³). Children had the highest cumulative non-carcinogenic risk from potentially toxic elements. Our research offers crucial baseline data for assessing arsenic in groundwater at the regional level, which is important for health risk reduction and remediation programs. The data show that preventative action must be taken to reduce the potential health risks in the study area from drinking groundwater, particularly for children. Full article

(This article belongs to the Special Issue Sources and Pollutants of Aquatic Contaminants, and Their Remediation Using SMART Water Systems)

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