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Sensors for Water Quality Monitoring and Assessment
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Sensors for Water Quality Monitoring and Assessment

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Environmental Sensing".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 4044

Special Issue Editors

Prof. Dr. Joaquín Ángel Ortuño

E-Mail Website
Guest Editor
Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, 30100-Murcia, Spain
Interests: chemical sensors; ion-selective electrodes; electrochemistry at the interface between two immiscible electrolyte solutions (ITIESs)
Special Issues, Collections and Topics in MDPI journals
Dr. José M. Olmos

E-Mail Website
Guest Editor
Department of Analytical Chemistry, Faculty of Chemistry, University of Murcia, 30100 Murcia, Spain
Interests: ion-selective electrodes; voltametric techniques at solid/liquid and liquid/liquid interfaces; modelling chemical systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue covers all topics related to the use of sensors in general, and chemical sensors in particular, to assess an aspect or aspects of water quality, including waters of any origin or use.

Water quality monitoring is crucial across a wide variety of cases. Water quality is related to a number of physical, chemical and biological parameters that are determined by the use or origin of the water. Water’s uses include drinking, irrigation, aquaculture and industry. The origins of water include groundwater, rivers, lakes, reservoirs, seawater, wastewater and waters from aquaculture. The water’s quality is indicative of environmental pollution.

Chemical sensors are a very useful tool for water quality monitoring. This is due to the wide variety of chemical sensors available and their continuous innovation, which allows many different chemical species to be monitored. Additionally, these sensors have suitable performance characteristics for real-time, in situ measurements.

Prof. Dr. Joaquín Ángel Ortuño
Dr. José M. Olmos
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. Sensors 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

  • sensors
  • water quality
  • chemical sensors
  • water monitoring
  • real-time monitoring
  • drinking water
  • seawater
  • aquaculture
  • environmental pollution
  • wastewater
  • groundwater

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

Published Papers (4 papers)

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Research

28 pages, 13302 KiB  
Article
Feasibility of Oil Spill Detection in Port Environments Based on UV Imagery
by Marian-Daniel Iordache, Françoise Viallefont-Robinet, Gert Strackx, Lisa Landuyt, Robrecht Moelans, Dirk Nuyts, Joeri Vandeperre and Els Knaeps
Sensors 2025, 25(6), 1927; https://doi.org/10.3390/s25061927 - 20 Mar 2025
Viewed by 288
Abstract
Oil spills in ports are particular cases of oil pollution in water environments that call for specific monitoring measures. Apart from the ecological threats that they pose, their proximity to human activities and the financial losses induced by disturbed port activities add to [...] Read more.
Oil spills in ports are particular cases of oil pollution in water environments that call for specific monitoring measures. Apart from the ecological threats that they pose, their proximity to human activities and the financial losses induced by disturbed port activities add to the need for immediate action. However, in ports, established methods based on short-wave infrared sensors might not be applicable due to the relatively low thickness of the oil layer, and satellite images suffer from insufficient spatial resolution, given the agglomeration of objects in ports. In this study, a lightweight ultraviolet (UV) camera was exploited in both controlled experiments and a real port environment to estimate the potential and limitations of UV imagery in detecting oil spills, in comparison to RGB images. Specifically, motivated by the scarce research literature on this topic, we set up experiments simulating oil spills with various oil types, different viewing angles, and under different weather conditions, such that the separability between oil and background (water) could be better understood and objectively assessed. The UV camera was also used to detect real-world oil spills in a port environment after installing it on a vessel for continuous monitoring. Various separability metrics between water and oil, computed in both scenarios (controlled experiments and port environment), show that the UV cameras have better potential than RGB in detecting oil spills in port environments. Full article
(This article belongs to the Special Issue Sensors for Water Quality Monitoring and Assessment)
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17 pages, 3603 KiB  
Article
pH Sensing Properties of Co3O4-RuO2-Based Electrodes and Their Application in Baltic Sea Water Quality Monitoring
by Kiranmai Uppuluri, Dorota Szwagierczak, Krzysztof Zaraska, Piotr Zachariasz, Marcin Stokowski, Beata Synkiewicz-Musialska and Paweł Krzyściak
Sensors 2025, 25(4), 1065; https://doi.org/10.3390/s25041065 - 11 Feb 2025
Viewed by 552
Abstract
Water is critical for the sustenance of life and pH is an important parameter in monitoring its quality. Solid-state pH sensors provide a worthy alternative to glass-based electrodes due to many advantages such as low cost, longer shelf life, simpler manufacturing, easier operation, [...] Read more.
Water is critical for the sustenance of life and pH is an important parameter in monitoring its quality. Solid-state pH sensors provide a worthy alternative to glass-based electrodes due to many advantages such as low cost, longer shelf life, simpler manufacturing, easier operation, miniaturization, and integration into electronic systems. Cobalt oxides are relatively cheaper and more abundantly available than ruthenium oxide. This work aims to reduce the environmental impact of screen-printed pH sensors by mixing Co3O4 and RuO2 in five molar proportions (30%, 40%, 50%, 60%, and 70%) and investigating the influence of oxide proportions on the pH-sensing properties of the resulting composition using potentiometric characterization, scanning electron microscopy, X-ray diffraction, surface profilometry, and electron dispersive spectroscopy. Although all the developed compositions showed super- or near-Nernstian sensitivity with good linearity, the sensors based on 50 mol% Co3O4-50 mol% RuO2 were the best due to superior sensitivity, selectivity, and stability. Fabricated sensors were applied in real-life environmental, municipal, and commercial water samples, including those from various depths in the Baltic Sea, and were found to be accurate in comparison to a glass electrode. Full article
(This article belongs to the Special Issue Sensors for Water Quality Monitoring and Assessment)
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19 pages, 8885 KiB  
Article
Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning
by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan and Yuhong Li
Sensors 2024, 24(22), 7345; https://doi.org/10.3390/s24227345 - 18 Nov 2024
Cited by 2 | Viewed by 1069
Abstract
The colorimetric method, due to its rapid and low-cost characteristics, demonstrates a wide range of application prospects in on-site water quality testing. Current research on colorimetric detection using deep learning algorithms predominantly focuses on single-target classification. To address this limitation, we propose a [...] Read more.
The colorimetric method, due to its rapid and low-cost characteristics, demonstrates a wide range of application prospects in on-site water quality testing. Current research on colorimetric detection using deep learning algorithms predominantly focuses on single-target classification. To address this limitation, we propose a multi-task water quality colorimetric detection method based on YOLOv8n, leveraging deep learning techniques to achieve a fully automated process of “image input and result output”. Initially, we constructed a dataset that encompasses colorimetric sensor data under varying lighting conditions to enhance model generalization. Subsequently, to effectively improve detection accuracy while reducing model parameters and computational load, we implemented several improvements to the deep learning algorithm, including the MGFF (Multi-Scale Grouped Feature Fusion) module, the LSKA-SPPF (Large Separable Kernel Attention-Spatial Pyramid Pooling-Fast) module, and the GNDCDH (Group Norm Detail Convolution Detection Head). Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. Furthermore, compared to YOLOv8n, the parameter count and computational load were reduced by 25.8% and 25.6%, respectively. Additionally, precision improved by 2.8%, recall increased by 3.5%, mAP50 enhanced by 2%, and mAP95 rose by 1.9%. These results affirm the substantial potential of our proposed method for rapid on-site water quality detection, offering new technological insights for future water quality monitoring. Full article
(This article belongs to the Special Issue Sensors for Water Quality Monitoring and Assessment)
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20 pages, 16413 KiB  
Article
A Wireless Network for Monitoring Pesticides in Groundwater: An Inclusive Approach for a Vulnerable Kenyan Population
by Titus Mutunga, Sinan Sinanovic and Colin Harrison
Sensors 2024, 24(14), 4665; https://doi.org/10.3390/s24144665 - 18 Jul 2024
Cited by 1 | Viewed by 1464
Abstract
Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a [...] Read more.
Safe drinking water is essential to a healthy lifestyle and has been recognised as a human right by numerous countries. However, the realisation of this right remains largely aspirational, particularly in impoverished nations that lack adequate resources for water quality testing. Kenya, a Sub-Saharan country, bears the brunt of this challenge. Pesticide imports in Kenya increased by 144% from 2015 to 2018, with sales data indicating that 76% of these pesticides are classified as highly hazardous. This trend continues to rise. Over 70% of Kenya’s population resides in rural areas, with 75% of the rural population engaged in agriculture and using pesticides. Agriculture is the country’s main economic activity, contributing over 30% of its gross domestic product (GDP). The situation is further exacerbated by the lack of monitoring for pesticide residues in surface water and groundwater, coupled with the absence of piped water infrastructure in rural areas. Consequently, contamination levels are high, as agricultural runoff is a major contaminant of surface water and groundwater. The increased use of pesticides to enhance agricultural productivity exacerbates environmental degradation and harms water ecosystems, adversely affecting public health. This study proposes the development of a wireless sensor system that utilizes radio-frequency identification (RFID), Long-range (LoRa) protocol and a global system for mobile communications (GSM) for monitoring pesticide prevalence in groundwater sources. From the system design, individuals with limited literacy skills, advanced age, or non-expert users can utilize it with ease. The reliability of the LoRa protocol in transmitting data packets is thoroughly investigated to ensure effective communication. The system features a user-friendly interface for straightforward data input and facilitates broader access to information by employing various remote wireless sensing methods. Full article
(This article belongs to the Special Issue Sensors for Water Quality Monitoring and Assessment)
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