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Newly Sensors and Biosensors for Water Quality Monitoring
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Newly Sensors and Biosensors for Water Quality Monitoring

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 17999

Special Issue Editors

Dr. Lorena Parra

E-Mail Website
Guest Editor
Research Institute for Integrated Management of Coastal Areas (IGIC), Universitat Politècnica de València, 46730 Grau de Gandia, Spain
Interests: environmental monitoring; precision agriculture; image processing; crop management; smart cities; physical sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Sandra Sendra

E-Mail Website
Guest Editor
Instituto de Investigación para la Gestión Integrada de Zonas Costeras, Universitat Politècnica de València, Gandía C/Paranimf, 1, 46730 Grao de Gandia, Spain
Interests: wireless sensor networks; electronic design; underwater communications; environmental monitoring; sensors
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues

The measurement of water quality is crucial in different areas, from agriculture to industry and even for utilities or for environmental surveillance. In recent decades, continuous pollution has changed the quality of most of the water sources, including freshwater and the seas. Each of the aforementioned fields requires the monitorization of the water quality. Nonetheless, each field entails specific needs and parameters. For some applications, the simple measuring of temperature or conductivity, using physical sensors, is enough. Meanwhile, in other cases, chemical sensors are necessary to measure the presence of specific substances, such as dissolved oxygen or the pH.

Nevertheless, the most accurate studies might even require more sophisticated sensors to detect the presence of certain compounds, which cannot be detected by physicochemical sensors. The biosensors have proved useful in achieving those measurements and monitoring options to have new systems for comprehensive water quality monitoring.

Traditionally, for water quality studies, there are several parameters which must be measured in the laboratory. Further, with the development of new technologies, most of the parameters can be measured on-site and have real-time monitorization. Therefore, there are still parameters which cannot be measured by the existing sensors.

The purpose of this Special Issue is to publish the lasts sensors and biosensors for water quality monitoring and their applications in different fields. The design and development of new physicochemical sensors and biosensors, integration of these new sensors in sensor networks, verification and validation of systems based on biosensors, and data fusion proposals to improve the water quality indicators based on sensor networks are welcomed.

Dr. Lorena Parra
Prof. Sandra Sendra
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. Applied Sciences 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 2400 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

  • Lab-on-a-chip technology
  • Biosensor development
  • Physicochemical sensor
  • Optical sensors
  • Membranes
  • Ion-selective electrode
  • Sensor network
  • Environmental surveillance
  • Pollution monitoring
  • Farming systems
  • Industrial process

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Published Papers (5 papers)

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Research

15 pages, 3217 KiB  
Article
Advances in the Monitoring of Algal Blooms by Remote Sensing: A Bibliometric Analysis
by Maria-Teresa Sebastiá-Frasquet, Jesús-A Aguilar-Maldonado, Iván Herrero-Durá, Eduardo Santamaría-del-Ángel, Sergio Morell-Monzó and Javier Estornell
Appl. Sci. 2020, 10(21), 7877; https://doi.org/10.3390/app10217877 - 6 Nov 2020
Cited by 10 | Viewed by 4485
Abstract
Since remote sensing of ocean colour began in 1978, several ocean-colour sensors have been launched to measure ocean properties. These measures have been applied to study water quality, and they specifically can be used to study algal blooms. Blooms are a natural phenomenon [...] Read more.
Since remote sensing of ocean colour began in 1978, several ocean-colour sensors have been launched to measure ocean properties. These measures have been applied to study water quality, and they specifically can be used to study algal blooms. Blooms are a natural phenomenon that, due to anthropogenic activities, appear to have increased in frequency, intensity, and geographic distribution. This paper aims to provide a systematic analysis of research on remote sensing of algal blooms during 1999–2019 via bibliometric technique. This study aims to reveal the limitations of current studies to analyse climatic variability effect. A total of 1292 peer-reviewed articles published between January 1999 and December 2019 were collected. We read all the literature individually to build a database. The number of publications increased since 2004 and reached the maximum value of 128 in 2014. The publications originated from 47 countries, but the number of papers published from the top 10 countries accounted for 77% of the total publications. To be able to distinguish between climate variability and changes of anthropogenic origin for a specific variable is necessary to define the baseline. However, long-term monitoring programs of phytoplankton are very scarce; only 1% of the articles included in this study analysed at least three decades and most of the existing algal blooms studies are based on sporadic sampling and short-term research programs. Full article
(This article belongs to the Special Issue Newly Sensors and Biosensors for Water Quality Monitoring)
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12 pages, 1509 KiB  
Article
Development of Heavy Metal Potentiostat for Batik Industry
by Siti Nur Hanisah Umar, Mohammad Nishat Akhtar, Elmi Abu Bakar, Noorfazreena M. Kamaruddin and Abdul Rahim Othman
Appl. Sci. 2020, 10(21), 7804; https://doi.org/10.3390/app10217804 - 4 Nov 2020
Cited by 6 | Viewed by 3477
Abstract
The consumption of reactive dyes in the batik industry has led to a severe concern in monitoring the heavy metal level in wastewater. Due to the necessity of implementing a wastewater monitoring system in the batik factory, a Heavy Metal potentiostat (HMstat) was [...] Read more.
The consumption of reactive dyes in the batik industry has led to a severe concern in monitoring the heavy metal level in wastewater. Due to the necessity of implementing a wastewater monitoring system in the batik factory, a Heavy Metal potentiostat (HMstat) was designed. The main goal of this study is to understand the optimal design concept of the potentiostat function in order to investigate the losses of accuracy in measurement using off-the-shelf devices. Through lab-scale design, the HMstat comprises of an analog potentiostat read-out circuit component (PRCC) and a digital control signal component (CSC). The PRCC is based on easy to use components integrated with a NI-myRIO controller in a CSC. Here, the myRIO was equipped with built-in analog to digital converter (ADC) and digital to analog converter (DAC) components. In this paper, the accuracy test and detection of cadmium(II) (Cd2+) and lead(II) (Pb2+) were conducted using the HMstat. The results were compared with the Rodeostat (an open source potentiostat available on the online market). The accuracy of the HMStat was higher than 95% and within the precision rate of the components used. The HMstat was able to detect Cd2+ and Pb2+ at −0.25 and −0.3 V, respectively. Similar potential peaks were obtained using Rodeostat (Cd2+ at −0.25 V and Pb2+ at −0.3 V). Full article
(This article belongs to the Special Issue Newly Sensors and Biosensors for Water Quality Monitoring)
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26 pages, 5878 KiB  
Article
New Sensor Based on Magnetic Fields for Monitoring the Concentration of Organic Fertilisers in Fertigation Systems
by Daniel A. Basterrechea, Lorena Parra, Marta Botella-Campos, Jaime Lloret and Pedro V. Mauri
Appl. Sci. 2020, 10(20), 7222; https://doi.org/10.3390/app10207222 - 16 Oct 2020
Cited by 4 | Viewed by 2722
Abstract
In this paper, we test three prototypes with different characteristics for controlling the quantity of organic fertiliser in the agricultural irrigation system. We use 0.4 mm of copper diameter, distributing in different layers, maintaining the relation of 40 spires for powered coil and [...] Read more.
In this paper, we test three prototypes with different characteristics for controlling the quantity of organic fertiliser in the agricultural irrigation system. We use 0.4 mm of copper diameter, distributing in different layers, maintaining the relation of 40 spires for powered coil and 80 for the induced coil. Moreover, we develop sensors with 8, 4, and 2 layers of copper. The coils are powered by a sine wave of 3.3 V peak to peak, and the other part is induced. To verify the functioning of this sensor, we perform several simulations with COMSOL Multiphysics to verify the magnetic field created around the powered coil, as well as the electric field, followed by a series of tests, using six samples between the 0 g/L and 20 g/L of organic fertiliser, and measure their conductivity. First, we find the working frequency doing a sweep for each prototype and four configurations. In this case, for all samples, making a sweep between 10 kHz and 300 kHz. We obtained that in prototype 1 (P1) (coil with 8 layers) the working frequency is around 100 kHz, in P2 (coil with 4 layers) around 110 kHz, and for P3 (coil with 2 layers) around 140 kHz. Then, we calibrate the prototypes measuring the six samples at four different configurations for each sensor to evaluate the possible variances. Likewise, the measures were taken in triplicate to reduce the possible errors. The obtained results show that the maximum difference of induced voltage between the lowest and the highest concentration is for the P2/configuration 4 with 1.84 V. Likewise, we have obtained an optimum correlation of 0.997. Then, we use the other three samples to verify the optimum functioning of the obtained calibrates. Moreover, the ANOVA simple procedure is applied to the data of all prototypes, in the working frequency of each configuration, to verify the significant difference between the values. The obtained results indicate that there is a significate difference between the average of concentration (g/L) and the induced voltage, and another with a level of 5% of significance. Finally, we compare all of the tested prototypes and configurations, and have determined that prototype three with configuration 1 is the best device to be used as a fertiliser sensor in water. Full article
(This article belongs to the Special Issue Newly Sensors and Biosensors for Water Quality Monitoring)
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14 pages, 4810 KiB  
Article
Dissolved Oxygen Forecasting in Aquaculture: A Hybrid Model Approach
by Elias Eze and Tahmina Ajmal
Appl. Sci. 2020, 10(20), 7079; https://doi.org/10.3390/app10207079 - 12 Oct 2020
Cited by 22 | Viewed by 4111
Abstract
Dissolved oxygen (DO) concentration is a vital parameter that indicates water quality. We present here DO short term forecasting using time series analysis on data collected from an aquaculture pond. This can provide the basis of data support for an early warning system, [...] Read more.
Dissolved oxygen (DO) concentration is a vital parameter that indicates water quality. We present here DO short term forecasting using time series analysis on data collected from an aquaculture pond. This can provide the basis of data support for an early warning system, for an improved management of the aquaculture farm. The conventional forecasting approaches are commonly characterized by low accuracy and poor generalization problems. In this article, we present a novel hybrid DO concentration forecasting method with ensemble empirical mode decomposition (EEMD)-based LSTM (long short-term memory) neural network (NN). With this method, first, the sensor data integrity is improved through linear interpolation and moving average filtering methods of data preprocessing. Next, the EEMD algorithm is applied to decompose the original sensor data into multiple intrinsic mode functions (IMFs). Finally, the feature selection is used to carefully select IMFs that strongly correlate with the original sensor data, and integrate into both inputs for the NN. The hybrid EEMD-based LSTM forecasting model is then constructed. The performance of this proposed model in training and validation sets was compared with the observed real sensor data. To obtain the exact evaluation accuracy of the forecasted results of the hybrid EEMD-based LSTM forecasting model, four statistical performance indices were adopted: mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). Results are presented for the short term (12-h) and the long term (1-month) that are encouraging, indicating suitability of this technique for forecasting DO values. Full article
(This article belongs to the Special Issue Newly Sensors and Biosensors for Water Quality Monitoring)
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13 pages, 4075 KiB  
Article
Fabrication and Characterization of Seawater Temperature Sensor with Self-Calibration Based on Optical Microfiber Coupler Interferometer
by Lingjun Zhou, Yang Yu, Liang Cao, Huimin Huang, Yuyu Tao, Zhenfu Zhang, Jianfei Wang, Junbo Yang and Zhenrong Zhang
Appl. Sci. 2020, 10(17), 6018; https://doi.org/10.3390/app10176018 - 31 Aug 2020
Cited by 11 | Viewed by 2440
Abstract
In this paper, a novel high-sensitivity temperature sensor with two sensing regions based on optical microfiber coupler interferometer (OMCI) for ocean application is proposed. The OMCI sensor is constructed by connecting Faraday mirrors to the two ports of the microfiber coupler respectively. Its [...] Read more.
In this paper, a novel high-sensitivity temperature sensor with two sensing regions based on optical microfiber coupler interferometer (OMCI) for ocean application is proposed. The OMCI sensor is constructed by connecting Faraday mirrors to the two ports of the microfiber coupler respectively. Its sensing characteristics analysis and experimental test are conducted. Using a broad-spectrum light source as input light, temperature sensor demodulation can be implemented by tracking the drift of the characteristic wavelength (dip wavelength or peak wavelength) of the reflection spectrum. Experimental results show that the temperature sensitivity of the OMCI sensor can reach 1007.4 pm/°C and the detection dynamic range up to 17.6 °C. Besides, due to the two sensing regions in OMCI, self-calibration of seawater temperature sensing and optimization of multi-parameter cross-sensitive demodulation are performed by affecting the non-equal-arm interferometer through a specific package design of the external environment. The sensor has the advantages of high sensitivity, large dynamic range, small size, easy to manufacture, which will play an important role in the practical application of marine environment monitoring. Full article
(This article belongs to the Special Issue Newly Sensors and Biosensors for Water Quality Monitoring)
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