Water Pollution Monitoring Research Articles

Fractional order interval optimization method based on perturbation bound and gamma function of a non-equidistant ROGM

PurposeThe purpose of this paper is to propose a fractional order optimization method based on perturbation bound and gamma function of a DGM(r,1).Design/methodology/approachBy analyzing and minimizing perturbation bound, the sub-optimal solution on fractional order interval is obtained through offline solving without iterative calculation. By this method, an optimized fractional order non-equidistant ROGM (OFONEROGM) is applied in fitting and prediction water quality parameters for a surface water pollution monitoring system.FindingsThis method can narrow fractional order interval in this work. In a surface water pollution monitoring system, the fitting and prediction performances of OFONEROGM are demonstrated comparing with integer order non-equidistant ROGM (IONEROGM).Originality/valueA method of offline solving the sub-optimal solution on fractional order interval is proposed. It can narrow the optimized fractional order range of NEROGM without iterative calculation. A large number of calculations are eliminated. Besides that, optimized fractional order interval is only related to the number of original data, and convenient for practical application. In this work, an OFONEROGM is modeled for predicting water quality trend for preventing water pollution or stealing sewage discharge. It will provide guiding significance in water quality parameter fitting and predicting for water environment management.

Retrieval Algorithm of Water Pollutant Concentration Based on UAV Remote Sensing Technology

With the development of the society and economy, traditional water pollution monitoring methods can no longer meet the normal needs of work. Unmanned aerial vehicle remote sensing technology has gradually emerged, and it has shown a development trend of multimodel and multifunction. However, the application of UAV remote sensing technology in water pollution monitoring is in its infancy and has not formed a unified method and standard. This paper introduces the disadvantages of UAV Remote Sensing Technology in water pollution monitoring and provides a way to improve the application level of UAV Remote Sensing Technology in water pollution monitoring. In order to make full use of the advantages of remote sensing monitoring technology in water ecological environment monitoring, including wide coverage, fast analysis speed, accurate and reliable monitoring results, and large amount of information, according to the spectral effect of polluted water, a remote sensing inversion model of river and lake parameters is established to determine the water quality of rivers and lakes. Concentrations of pollutants in the body are inverted and analyzed. The analysis results show that the fitting effect of the inversion model is accurate and the accuracy errors reflected by the degree of dispersion and deviation are also acceptable. The inversion results of the concentration of river and lake characteristic parameters based on the Gaofen-1 remote sensing image data are in line with the actual situation. The research results can greatly strengthen the monitoring capacity of the sewage outlet and provide reference for related research on water pollution caused by the sewage outlet.

Characterization of the laser-induced breakdown spectroscopy near the gas-liquid two-phase interface.

The characterization of laser-induced breakdown spectroscopy (LIBS) near the gas-liquid two-phase interface was investigated with the laser acting on the sample along the horizontal direction. Simulation of the laser beam focusing process and observation of laser beam spot images show that difference in focusing positions in the air and the solution results from refraction of the laser beam entering the solution from the air and the change of propagation direction on the container lateral. The peak power and mean irradiance of the focused laser beam spot increase with the distance away from the interface, which is attributed to the fact that the loss of laser energy due to the refraction and reflection of light at the interface decreases with the focusing position moving away from the interface. This variation trend of laser irradiance allows for the growth of the spectral line intensity and lifetime with increasing the distance from the interface. The plasma electron density and temperature decrease with the delay time but increase with the distance away from the interface at the same delay time. Our findings help us to gain more insight into the characteristics and evolution mechanisms of LIBS produced near the gas-liquid two-phase interface, which provides theoretical guidance for the correction of LIBS spectra especially in water pollution monitoring.

River Water Pollution Prevention and Monitoring System Based on Internet of Things Cloud Platform

River Water Pollution Prevention and Monitoring System Based on Internet of Things Cloud Platform

Harnessing the Potential of Biological Recognition Elements for Water Pollution Monitoring.

Environmental monitoring of pollutants is an imperative first step to remove the genotoxic, embryotoxic, and carcinogenic toxins. Various biological sensing elements such as proteins, aptamers, whole cells, etc., have been used to track down major pollutants, including heavy metals, aromatic pollutants, pathogenic microorganisms, and pesticides in both environmental samples and drinking water, demonstrating their potential in a true sense. The intermixed use of nanomaterials, electronics, and microfluidic systems has further improved the design and enabled robust on-site detection with enhanced sensitivity. Through this perspective, we shed light on the advances in the field and entail recent efforts to optimize these systems for real-time, online sensing and on-site field monitoring.

Survey Paper on Development of Water Pollution Monitoring System

Water pollution is one of the biggest threats to our surroundings. To supply good quality of water it is important to monitor the quality of water. So, we are designing a cheap and time consuming water pollution monitoring system. The system comprises of different sensors which is used to measure the physical and chemical parameters of the water. The parameters such as temperature, pH, turbidity, TDS sensor of the water can be measured. The measured values from the sensors are provided to Arduino, it reads the data and provide the results. Finally, the sensor data gets appended in the file and can also be viewed on Arduino serial monitor.

Advancement of Environmental Monitoring System Using IoT and Sensor: A Comprehensive Analysis

<abstract> <p>The emergence of the Internet of Things (IoT) has brought a revolution in global communication network technology. It has acquired many day-to-day applications in healthcare, education, agriculture, etc. In addition, IoT has also had a significant impact in the field of environmental monitoring.The significant factors in a healthy environment are air quality, water pollution, and waste management, where the world's population can live securely. Monitoring is necessary for us to achieve global sustainability. As monitoring technology has advanced in recent years, environmental monitoring systems have evolved from essential remote monitoring to an advanced environment monitoring (AEM) system, incorporating Internet of Things (IoT) technology and sophisticated sensor modules.The present manuscript aims to accomplish a critical review of noteworthy contributions and research studies about environmental monitoring systems, which involve monitoring air quality, water quality, and waste management.The rapid growth of the world's population and the exhaustion of natural resources, coupled with the increasing unpredictability of environmental conditions, lead to significant concerns about worldwide food security, global warming, water pollution, and waste overflowing. Automating tasks in the building environment, based on the Internet of Things (IoT) application, is meant to eliminate problems with the traditional approach. This study aims to examine and evaluate numerous studies involving monitoring air, water, waste, and overall environmental pollution, as well as their effect on the environment. This article categorizes studies based on their research purposes, techniques, and findings. This paper examines advanced environmental monitoring systems through sensor technology, IoT, and machine learning.</p> </abstract>

State-of-the art and perspectives of underwater optical wireless communications

In scientific, military, and industrial sectors, the development of robust and efficient submarine wireless communication links is of enormous interest. Underwater wireless communications can be carried out through acoustic, radio frequency (RF), and optical waves. Underwater optical communication is not a new idea, but it has recently been considered because seawater exhibits a window of reduced absorption both in the visible spectrum and long-wavelength UV light (UV-A). Compared to its bandwidth limited acoustic counterpart, underwater optical wireless communications (UOWCs) can support higher data rates at low latency levels. Underwater wireless communication networks are important in ocean exploration, military tactical operations, environmental and water pollution monitoring. Anyway, given the rapid development of UOWC technology, documents are still needed showing the state of the art and the progress made by the most current research. This paper aims to examine current technologies, and those potentially available soon, for Underwater Optical Wireless Communication and to propose a new perspective using UV-A radiation.

Designing of Microwave Metamaterial Biosensor for Water Pollution Monitoring

This paper focuses on developing a microwave metamaterial-based Microstrip Ring Resonator for water quality monitoring. Water pollution is increasing at an alarming rate, worsening pollution and destroying natural habitats. This paper aims to design a metamaterial-based resonator, analyse its performance with various biosamples, and then fabricate the designed product to validate the sensing performance. For this purpose, Computer Simulation Technology (CST) is used to design and simulate the proposed biosensor, with Rogers-RO3003 as the substrate material. In addition, for the proof of concept, different types of liquid materials under test were used in simulation and measurement. The procedures begin with the design and simulation of the MRR using CST, followed by the fabrication stage when the simulation produced the desired results, and finally, laboratory measurements for data collection. The sensing area of the microstrip ring resonator was observed through electric field distribution, where a gap was introduced in the ring structure. The results show that proposed structure of the resonator was able to distinguish different types of liquid that were placed in the sensing gap, by shifting the resonance frequency based on their dielectric constant. In summary, a new metamaterial-based microstrip ring resonator is produced to monitor liquid quality. The concept behind the paper was proven through simulations and experiments where it is suitable to be used as a sensing algorithm. In future work, this product could be used to monitor residue in our clean water, such as river, to minimise the polluted drinking water risk.

Construction of River Water Pollution Monitoring Information System Based on Contamination Detection Technologies

Construction of River Water Pollution Monitoring Information System Based on Contamination Detection Technologies

Development of spectrophotometric method for analysis of mercaptopurine and dimercaprol for use in quality control and monitoring water pollution

In the present work, spectrophotometric method was developed for analysis of mercaptopurine and dimercaprol to be applied in quality control and monitoring water pollution. These drugs are used for the treatment of cancer and heavy metal poisoning respectively. Both mercaptopurine and dimercaprol react with colourless anhydrous manganese (II) acetate in DMSO to form soluble brown coloured complexes which showed λmax at 350 nm and 360nm during spectrophotometric analysis. This newly developed method was successfully applied for analysis of commercial drugs and spiked water. The recovery of these drugs from commercial formulations and spiked water samples was in the range between 98.0-99.7% with RSDs in the range 0.56-1.50% that indicated high degree of accuracy and precision of the method.

Retrieval of Total Phosphorus Concentration in the Surface Water of Miyun Reservoir Based on Remote Sensing Data and Machine Learning Algorithms

Some essential water conservation areas in China have continuously suffered from various serious problems such as water pollution and water quality deterioration in recent decades and thus called for real-time water pollution monitoring system underwater resources management. On the basis of the remote sensing data and ground monitoring data, this study firstly constructed a more accurate retrieval model for total phosphorus (TP) concentration by comparing 12 machine learning algorithms, including support vector machine (SVM), artificial neural network (ANN), Bayesian ridge regression (BRR), lasso regression (Lasso), elastic net (EN), linear regression (LR), decision tree regressor (DTR), K neighbor regressor (KNR), random forest regressor (RFR), extra trees regressor (ETR), AdaBoost regressor (ABR) and gradient boosting regressor (GBR). Then, this study applied the constructed retrieval model to explore the spatial-temporal evolution of the Miyun Reservoir and finally assessed the water quality. The results showed that the model of TP concentration built by the ETR algorithm had the best accuracy, with the coefficient R2 reaching over 85% and the mean absolute error lower than 0.000433. The TP concentration in Miyun Reservoir was between 0.0380 and 0.1298 mg/L, and there was relatively significant spatial and temporal heterogeneity. It changed remarkably during the periods of the flood season, winter tillage, planting, and regreening, and it was lower in summer than in other seasons. Moreover, the TP in the southwest part of the reservoir was generally lower than in the northeast, as there was less human activities interference. According to the Environmental Quality Standard for the surface water environment, the water quality of Miyun Reservoir was overall safe, except only for an over-standard case occurrence in the spring and September. These conclusions can provide a significant scientific reference for water quality monitoring and management in Miyun Reservoir.

Corrigendum to: Water Pollution Monitoring through Remote Sensing

We apologize for the error that occurred in the online version of the article. Incorrect name of 5th author was published in the article entitled “Water Pollution Monitoring through Remote Sensing” in “Curr. Anal. Chem., 2021, 17(6), 802-814 [1]. The original article can be found online at https://doi.org/10.2174/1573411016666200206095055 Original: Gadug Sudhamsu Corrected: Gurijala Sudhamsu

Preparation of lightweight daisy-like magnetic molecularly imprinted polymers via etching synergized template immobilization for enhanced rapid detection of trace 17β-estradiol

17β-estradiol (E2), as one of the pharmaceutical and personal care product, frequently contaminates environmental water as estrogen pollutant and possesses great risk to human survival as well as the sustainable development of the ecosystem. Herein, to achieve an effective adsorbent system for the selective removal of E2 from the environmental water, Fe3O4 nanoparticles are subjected to chemical etching to reduce the overall mass and then employed as carriers to prepare a novel type of lightweight daisy-like magnetic molecularly imprinted polymers (LD-MMIPs) adopting template immobilization strategy. The LD-MMIPs based etched magnetic nanoparticles not only exhibit light mass but also have plentiful imprinted sites in the etched channels, which significantly increases the adsorption capacity for E2. The daisy-like LD-MMIPs own strong magnetic responsiveness, well crystallinity, fast binding kinetics, high adsorption amount, and excellent selectivity. Moreover, combining with HPLC, the LD-MMIPs as adsorbents have been successfully used to specifically recognize and detect trace E2 in environmental water. Thus, the proposed LD-MMIPs with high adsorption capacity hold great potential in monitoring water pollution. Additionally, this work also provides an alternative strategy for improving the adsorption capacity of magnetic molecularly imprinted polymers through a convenient chemical etching technology.

Real-Time Acid Rain Sensor Based on a Triboelectric Nanogenerator Made of a PTFE–PDMS Composite Film

Self-powered sensors based on triboelectric nanogenerators (TENGs) are increasingly used in real-life applications, especially for monitoring water pollution, rain pH, and the like. Here, we fabric...

IoT based smart water quality monitoring system

Pollution of water is one of the main threats in recent times as drinking water is getting contaminated and polluted. The polluted water can cause various diseases to humans and animals, which in turn affects the life cycle of the ecosystem. If water pollution is detected in an early stage, suitable measures can be taken and critical situations can be avoided. To make certain the supply of pure water, the quality of the water should be examined in real-time. Smart solutions for monitoring of water pollution are getting more and more significant these days with innovation in sensors, communication, and Internet of Things (IoT) technology. In this paper, a detailed review of the latest works that were implemented in the arena of smart water pollution monitoring systems is presented. The paper proposes a cost effective and efficient IoT based smart water quality monitoring system which monitors the quality parameters uninterruptedly. The developed model is tested with three water samples and the parameters are transmitted to the cloud server for further action.

Fabrication, Potentiometric Characterization, and Application of Screen-Printed RuO2 pH Electrodes for Water Quality Testing.

Screen-printed sensing electrodes attract much attention for water pollution monitoring due to their small size, physical and chemical durability, and low cost. This paper presents the fabrication and broad potentiometric characterization of RuO2 pH sensing electrodes deposited by screen printing on alumina substrates and sintered in the 800–900 °C temperature range. All the fabricated electrodes showed close to Nernstian sensitivity, good linearity, fast response, small drift, low hysteresis, and low cross-sensitivity toward various interfering cations and anions. Furthermore, decreasing the sintering temperature led to better adhesion of the RuO2 layer and a negligible response to interfering ions. The measurements in real-life samples from different water sources showed that the fabricated electrodes are on par with conventional glass electrodes with a maximum deviation of 0.11 pH units, thus indicating their potential for application in water quality monitoring.

The Effectiveness of “River Chief System” Policy: An Empirical Study Based on Environmental Monitoring Samples of China

There has been controversy in theory and practice among studies about the governance of the “River Chief System” (RCS) policy and the watershed management issues behind it. This paper uses the regression discontinuity (RD) method and the water pollution monitoring data of 150 state-controlled monitoring points in China from 2007 to 2018 at the China National Environmental Monitoring Station to empirically study the effect of the “River Chief System” on water pollution treatment and the influencing factors behind the effect of the “River Chief System”. The results show that the “River Chief System” policy has a positive impact on river pollution treatment in the observation term. The implementation effectiveness of the “River Chief System” is limited by factors such as the boundaries of the river chief’s jurisdictions, the administrative conflict among river chiefs, local government environmental expenditure capacity, and environmental pressure. It is believed that the key to basin governance is to further improve the synergistic model of basin governance among regions.

A new method for highly efficient separation and determination of arsenic species in natural water using silica modified with polyamines

A simple and highly efficient method for the determination of highly toxic arsenic species using non-covalently aminated silica is proposed. The polyamines including poly(hexamethyleneguanidine), poly(4,9-dioxadodecane-1,12-guanidine), hexadimethrine, and poly(diallyldimethylammonium) were tested as silica modifiers. The prepared adsorbents allow effective preconcentration of anionic species of arsenic from aqueous solutions. It was found that As(V) can be quantitatively extracted from solutions at pH 4.5–7.0 by the anion exchange mechanism in less than 5 min, while neutral at this pH As(III) was not adsorbed at these conditions. A reaction with 2,3-dimercapto-1-propanesulphonic acid, which resulted in the formation of the negatively charged complex of As(III) with adsorbents was used for its quantitative extraction from solutions with a pH of 3.5–6.5. A system of two cartridges filled with poly(diallyldimethylammonium) modified silica and the on-line reaction of As(III) with 2,3-dimercapto-1-propanesulphonic acid proceeding between the cartridges was used for separate preconcentration and determination of As(V) and As(III) at pH 5. The proposed method was used for four-year monitoring of natural water pollution by arsenic in the area of residence of the indigenous peoples of Tyva Republic (Russia).

Reusable System for Phenol Detection in an Aqueous Medium Based on Nanodiamonds and Extracellular Oxidase from Basidiomycete Neonothopanus nambi.

A reusable system for phenol determination in an aqueous medium was obtained by adsorption of extracellular oxidase from fungus Neonothopanus nambi onto modified nanodiamonds (MND) synthesized by detonation. It was found that the enzyme strongly binds to MND and exhibits catalytic activity in the reaction of co-oxidation of phenol with 4-aminoantipyrine without the addition of hydrogen peroxide. In the presence of the MND-oxidase complex, a significantly (by an order of magnitude) higher yield of the reaction product is recorded as compared to the yield in the presence of a free enzyme; the mechanism of the revealed effect is discussed. Model experiments have demonstrated the multiple use of the MND-oxidase complex for testing phenol in aqueous samples. The immobilized enzyme exhibits functional activity during long-term (2 months) storage of the MND-oxidase complex at 4°C. The data obtained create the prerequisites for using the created system in environmental monitoring of water pollution with phenol.