Online Water Quality Monitoring Research Articles

Multi-level information fusion for spatiotemporal monitoring in water distribution networks

This paper deals with online water quality monitoring in distribution networks based on surrogate water quality parameters (WQPs). The present strategy is based on multi-level information fusion using hierarchical belief rule-based (BRB) systems. Networked fuzzy belief rule-based (NF-BRB) and high-level BRB systems are introduced for information fusion at the feature level. Primary and secondary features are extracted from online WQP signals. Primary features are analyzed using the NF-BRB system that is built through knowledge elicitation from experts. Secondary features are interpreted through the high-level BRB system that employs a fuzzy partitioning on the feature sets and a hybrid learning strategy for its rule base construction. Finally, the dynamic fuzzy evidential fusion is introduced to aggregate the local and spatial assessments in each analysis window. As an important contribution of this paper, we propose a new validation method for event detection in the water distribution network (WDN) based on adaptive projection of the signal patterns attributed to anomaly events, obtained through contamination experiments in a pilot facility, to the real WQP signals measured across the WDN. Single and composite contamination events based on several biological and chemical contaminants are simulated to evaluate the performance of the proposed framework in event detection. The proposed multi-level information fusion framework obtains a high detection rate and a reduced number of false negative and positive results.

Design and Implementation of Water Quality On-Line Monitoring System Based on Combination of Multiple Data Transmission

Water quality on-line monitoring is the necessary means to control water environment pollution and provide effective data for the research of water ecological restoration. Using free wireless communicating module of ZigBee we realized transmitting data from sensors on the river bank to the data storage center. Based on serial ports of micro-controller a protocol converter circuit was designed. With program the Modbus RTU protocol data packet on RS-485 bus was converted into ZigBee communication protocol and then transmitted to the Internet. Supplemented by GSM the reliability of data was enhanced. Water quality online monitoring system based on multiple data communication provides browse of real-time river water quality through the Internet network, which is fast and convenient to be exported for research.

A miniature porous aluminum oxide-based flow-cell for online water quality monitoring using bacterial sensor cells

The use of live bacterial reporters as sensing entities in whole-cell biosensors allows the investigation of the biological effects of a tested sample, as well as the bioavailability of its components. Here we present a proof of concept for a new design for online continuous water monitoring flow-cell biosensor, incorporating recombinant reporter bacteria, engineered to generate an optical signal (fluorescent or bioluminescent) in the presence of the target compound(s). At the heart of the flow-cell is a disposable chip made of porous aluminum oxide (PAO), which retains the sensor microorganisms on its rigid planar surface, while its high porosity allows an undisturbed access both to the sample and to essential nutrients. The ability of the bacterial reporters to detect model toxic chemicals was first demonstrated using a “naked” PAO chip placed on solid agar, and later in a chip encased in a specially designed flow-through configuration which enables continuous on-line monitoring. The applicability of the PAO chip to simultaneous online detection of diverse groups of chemicals was demonstrated by the incorporation of a 6-member sensor array into the flow-through chip. The selective response of the array was also confirmed in spiked municipal wastewater effluents. Sensing activity was retained by the bacteria after 12-weeks storage of freeze-dried biochips, demonstrating the biochip potential as a simple minimal maintenance “plug-in” cartridge. This low-cost and easy to handle PAO-based flow-cell biosensor may serve as a basis for a future platform for water quality monitoring.

Compendium of Sensors and Monitors and Their Use in the Global Water Industry

Online monitoring of water quality is an powerful enabler in the water industry. It is a crucial component in the pro-active management of processes and assets, and helps improve performance and cost efficiency. Instrumentation for the monitoring of most water quality parameters is commercially available. Implementation of such equipment, however, remains largely limited to a small number of basic parameters and is still confined to key nodes in collection, treatment and distribution systems. A primary hurdle to further realization of the potential of online monitoring is the lack of publicly available information on system performance, key drivers and barriers (technical, economic and social) to successful implementation. A study was performed to identify and document information on commercially available instrument types, associated costs (capital and operating), and real-world experiences with the use of sensors in the global water / wastewater industry. This information was compiled in an online compendium, to facilitate sharing of information and learning from experience.The study has shown that the current generation of technology is suitable for routine operation. However, there is no one-size-fits-all solution to monitoring questions. Furthermore, successful application of on-line water quality monitoring requires commitment of considerable resources, which need to be accompanied by a solid QA/QC plan. Furthermore, the understanding and appreciation of monitoring and the efforts required to make it a success need to be embedded and supported at all levels within an organization.Deciding whether on-line monitoring is the best solution to a need for information has to be done in careful process. Defining needs and requirements, building a business case around this and then carefully working out the specifications and all organizational aspects of the monitoring program are prerequisites for effective implementation and to prevent surprises and disappointmentThis title belongs to WERF Research Report Series.ISBN: 9781780406695 (eBook)

Hexacyanoferrate-adapted biofilm enables the development of a microbial fuel cell biosensor to detect trace levels of assimilable organic carbon (AOC) in oxygenated seawater.

A marine microbial fuel cell (MFC) type biosensor was developed for the detection of assimilable organic carbon (AOC) in ocean water for the purpose of online water quality monitoring for seawater desalination plants prone to biofouling of reverse osmosis (RO) membranes. The anodophilic biofilm that developed on the graphite tissue anode could detect acetate as the model AOC to concentrations as low as 5 µM (120 µg/L of AOC), which is sufficiently sensitive as an online biofouling risk sensor. Although the sensor was operated at a higher (+200 ± 10 mV) than the usual (-300 mV) anodic potential, the presence of oxygen completely suppressed the electrical signal. In order to overcome this outcompeting effect of oxygen over the anode as electron acceptor by the bacteria, hexacyanoferrate (HCF(III)) was found to enable the development of an adapted biofilm that transferred electrons to HCF(III) rather than oxygen. As the resultant of the reduced HCF(II) could readily transfer electrons to the anode while being re-oxidised to HCF(III), the marine MFC biosensor developed could be demonstrated to work in the presence of oxygen unlike traditional MFC. The possibility of operating the marine MFC in batch or continuous (in-line) mode has been explored by using coulombic or potentiometric interpretation of the signal.

Absorption and fluorescence properties of chromophoric dissolved organic matter: implications for the monitoring of water quality in a large subtropical reservoir.

The development of techniques for real-time monitoring of water quality is of great importance for effectively managing inland water resources. In this study, we first analyzed the absorption and fluorescence properties in a large subtropical reservoir and then used a chromophoric dissolved organic matter (CDOM) fluorescence monitoring sensor to predict several water quality parameters including the total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), dissolved organic carbon (DOC), and CDOM fluorescence parallel factor analysis (PARAFAC) components in the reservoir. The CDOM absorption coefficient at 254 nm (a(254)), the humic-like component (C1), and the tryptophan-like component (C3) decreased significantly along a gradient from the northwest to the lake center, northeast, southwest, and southeast region in the reservoir. However, no significant spatial difference was found for the tyrosine-like component (C2), which contributed only four marked peaks. A highly significant linear correlation was found between the a(254) and CDOM concentration measured using the CDOM fluorescence sensor (r(2) = 0.865, n = 76, p < 0.001), indicating that CDOM concentrations could act as a proxy for the CDOM absorption coefficient measured in the laboratory. Significant correlations were also found between the CDOM concentration and TN, TP, COD, DOC, and the maximum fluorescence intensity of C1, suggesting that the real-time monitoring of CDOM concentrations could be used to predict these water quality parameters and trace the humic-like fluorescence substance in clear aquatic ecosystems with DOC <2 mg/L and total suspended matter (TSM) concentrations <15 mg/L. These results demonstrate that the CDOM fluorescence sensor is a useful tool for on-line water quality monitoring if the empirical relationship between the CDOM concentration measured using the CDOM fluorescence sensor and the water quality parameters is calibrated and validated.

Highly sensitive and selective detection of Pb2+ ions using a novel and simple DNAzyme-based quartz crystal microbalance with dissipation biosensor.

A novel, label-free DNAzyme-based quartz crystal microbalance with dissipation monitoring (QCM-D) biosensor was developed for the highly sensitive and specific detection of Pb(2+) ions. To enhance the performance of the sensor, oligonucleotide-functionalized gold nanoparticles were used for both frequency and dissipation amplification. This sensor was developed by immobilizing Pb(2+)-specific DNAzymes onto the QCM-D sensor surface and allowing them to hybridize with substrate-functionalized AuNPs. The DNAzyme catalyzed the cleavage of the substrate in the presence of Pb(2+) ions, causing the cleaved substrate-functionalized AuNPs to be removed from the sensor surface. Thus, Pb(2+) ions can be determined on-line by monitoring the change in frequency and dissipation signals. The results revealed that the sensor showed a sensitive response to Pb(2+) ions with detection limits of 14 nM and 20 nM for frequency and dissipation, respectively. This QCM-D biosensor also exhibited excellent selectivity toward Pb(2+) ions in the presence of other divalent metal ions. In addition, the approach was able to detect Pb(2+) in tap water, demonstrating its great potential for monitoring drinking water quality. The proposed sensor system described here represents a new class of lead ion sensor. Its simple detection strategy makes it feasible for 'pollution-free' detection; thus, the approach could have applications in on-line water quality monitoring.

A small-scale air-cathode microbial fuel cell for on-line monitoring of water quality

The heavy use of chemicals for agricultural, industrial and domestic purposes has increased the risk of freshwater contamination worldwide. Consequently, the demand for efficient new analytical tools for on-line and on-site water quality monitoring has become particularly urgent.In this study, a small-scale single chamber air-cathode microbial fuel cell (SCMFC), fabricated by rapid prototyping layer-by-layer 3D printing, was tested as a biosensor for continuous water quality monitoring.When acetate was fed as the rate-limiting substrate, the SCMFC acted as a sensor for chemical oxygen demand (COD) in water. The linear detection range was 3–164ppm, with a sensitivity of 0.05μAmM−1cm−2 with respect to the anode total surface area. The response time was as fast as 2.8min.At saturating acetate concentrations (COD>164 ppm), the miniature SCMFC could rapidly detect the presence of cadmium in water with high sensitivity (0.2μgl−1cm−2) and a lower detection limit of only 1μgl−1. The biosensor dynamic range was 1–25μgl−1. Within this range of concentrations, cadmium affected only temporarily the electroactive biofilm at the anode. When the SCMFCs were again fed with fresh wastewater and no pollutant, the initial steady-state current was recovered within 12min.

An On-Line Water Quality Monitoring System for the Reservoirs Based on Android

According to the demand of water quality automatic monitoring in many large or medium reservoirs, we proposed an on-line water quality monitoring system. It is composed of wireless sensor networks and an embedded monitoring platform. We built a novel early-warning model to well adapt to the regular pattern of water quality change in the reservoirs. As a result, an Android application with outstanding control experience is achieved for real-time monitoring, water pollution early warning and water quality comprehensive assessment. Experimental results show that the system can work stably for a long time and provide accurate monitoring information continuously. It can also detect the abnormal signals of water quality in time and alarm. The system efficiently satisfies the requirement of water quality on-line automatic monitoring.

Bio-Electrochemical Sensor for Fast Analysis of Assimilable Organic Carbon in Seawater

A Microbial Fuel Cell (MFC) based biosensor for the determination of Assimilable Organic Carbon (AOC) in seawater was developed by establishing an anodophilic marine biofilm on the surface of an electrode poised at +250 mV (vs Ag/AgCl) rather than the traditionally used potentials of about -300 mV. A linear correlation (R2>0.99) between electrochemical signals (peak current) and acetate concentration ranging 10 to 55 μM was achieved.Using the positive anodic potential enabled the rapid establishment of the electrochemically active anodophilic biomass within a period of less than 8 days, a higher sensitivity (0.017 mA/μM acetate added) and a lower detection limit (2.5 μM acetate, 0.16 mg O2/L of Biological Oxygen Demand (BOD)) compared to the negative anodic potential. Further, it was shown that this bio-electrochemical AOC sensor could tolerate the presence of low concentrations of dissolved oxygen. The established potentiostat controlled MFC biosensor could be used for the purpose of online water quality monitoring for seawater desalination plants prone to biofouling of RO membranes.

Use of On-line Water Quality Monitoring Data to Predict Bacteriological Failures

Variations in continuously monitored on-line water quality data were investigated to establish whether they could be linked to coliform detections at regulatory monitoring points. We focussed on chlorine residual, turbidity and flow rate at water treatment works (WTW)-A. Archived on-line monitoring data from WTW-A were analysed using cross-correlation and self-organising maps in MATLAB® to identify trends in the data running up to coliform detections. The results show that these tools could be developed to help manage WTWs to reduce the number of bacteriological failures. A fingerprint of WTW conditions relating to coliform failures was identified for this case study.

Use of online water quality monitoring for assessing the effects of WWTP overflows in rivers.

The effects on river water quality of sewer overflows are not well known. Since the duration of the overflow is in the order of magnitude of minutes to hours, continuous measurements of water quality are needed and traditional grab sampling is unable to quantify the pollution loads. The objective of this paper was to demonstrate the applicability of high frequency measurements for assessing the impacts of waste water treatment plants on the water quality of the receiving surface water. In our in situ water quality monitoring setup, two types of multiparameter sensors mounted on a floating fixed platform were used to determine the dynamics of dissolved oxygen, specific conductivity, ammonium-N, nitrate-N and dissolved organic carbon downstream of a waste water treatment plant (WWTP), in combination with data on rainfall, river discharge and WWTP overflow discharge. The monitoring data for water quantity and water quality were used to estimate the pollution load from waste water overflow events and to assess the impact of waste water overflows on the river water quality. The effect of sewer overflow on a small river in terms of N load was shown to be significant. The WWTP overflow events accounted for about 1/3 of the river discharge. The NH4-N loads during overflow events contributed 29% and 21% to the August 2010 and June 2011 load, respectively, in only 8% and 3% of the monthly time span. The results indicate that continuous monitoring is needed to accurately represent the effects of sewer overflows in river systems.

Development of variable pathlength UV–vis spectroscopy combined with partial-least-squares regression for wastewater chemical oxygen demand (COD) monitoring

To overcome the challenging task to select an appropriate pathlength for wastewater chemical oxygen demand (COD) monitoring with high accuracy by UV-vis spectroscopy in wastewater treatment process, a variable pathlength approach combined with partial-least squares regression (PLSR) was developed in this study. Two new strategies were proposed to extract relevant information of UV-vis spectral data from variable pathlength measurements. The first strategy was by data fusion with two data fusion levels: low-level data fusion (LLDF) and mid-level data fusion (MLDF). Predictive accuracy was found to improve, indicated by the lower root-mean-square errors of prediction (RMSEP) compared with those obtained for single pathlength measurements. Both fusion levels were found to deliver very robust PLSR models with residual predictive deviations (RPD) greater than 3 (i.e. 3.22 and 3.29, respectively). The second strategy involved calculating the slopes of absorbance against pathlength at each wavelength to generate slope-derived spectra. Without the requirement to select the optimal pathlength, the predictive accuracy (RMSEP) was improved by 20-43% as compared to single pathlength spectroscopy. Comparing to nine-factor models from fusion strategy, the PLSR model from slope-derived spectroscopy was found to be more parsimonious with only five factors and more robust with residual predictive deviation (RPD) of 3.72. It also offered excellent correlation of predicted and measured COD values with R(2) of 0.936. In sum, variable pathlength spectroscopy with the two proposed data analysis strategies proved to be successful in enhancing prediction performance of COD in wastewater and showed high potential to be applied in on-line water quality monitoring.

Miniaturized water quality monitoring pH and conductivity sensors

The development of cost-effective, durable and sensitive on-line water quality monitoring sensors that can be installed across water distribution networks has attracted attention to increase the frequency of monitoring and hence reduce the risk of accidental or deliberate contaminations or improve routine control of water quality. This paper presents microsensors fabricated and implemented in a serpentine channel interface for the measurement of pH and conductivity, two important water quality parameters. The performance of these sensors was tested in both still (static) and flowing (dynamic) water. The serpentine channel interface, numerically optimized, provides a constant flow and a constant outlet pressure condition for dynamic experiments. Tests conducted for evaluating the effect of the exposure time on the sensor performance show no change in the sensor response even after one month. Finally, the pH and conductivity sensors were compared against the common commercial sensors used for evaluating water quality. The results show that the pH and conductivity sensors are as precise as the commercial sensors in both static and dynamic conditions. However, the cost of the sensors presented here is significantly lower than that of the commercial sensors.

Analysis and Solution on the Correlation between Dissolved Oxygen Sensor and pH Sensor for Water Quality Monitoring

This paper designs a multi parameter real-time water quality on-line monitoring system for aquaculture water. This system achieves the online monitoring among temperature, turbidity, DO (dissolved oxygen), pH and electrical conductivity. The crosstalk, produced by the simultaneous measurement with DO and pH sensors, will affect accuracy and stability of monitoring results. This paper analyzes the source of crosstalk, describes a circuit model of causing crosstalk, and designs an isolated circuit between powers and signals as well. The experimental results show that, the real-time monitoring of DO and pH has the characteristics of speediness, high precision, small error and low noise.

Real-Time Wireless Water Quality Monitoring System Based on MODBUS Protocol

Recently, the environment problem has been more serious, especially the water-quality problem. In this paper, we develop the portable water-quality monitoring terminal, which can collect and real-time transmit water-quality parameters. The monitoring center received the data based on Modbus protocol by using wireless radio station. System structure and transmitting data frame are discussed here. The paper also introduced the monitoring software function in the monitoring center. The result of system test proved that the water-quality terminal can transfer the data to the remote monitoring center for a long time successfully, the system can achieve real-time and on-line water-quality monitoring functions.

Application of Environmental Internet of Things on water quality management of urban scenic river

An online water quality management system (OWQMS), one of the main components of Environmental Internet of Things (EIoT), comprising online water quality monitoring subsystem, digital data transmission subsystem, and data processing parts, was established to manage an urban scenic river, Xinglin Bay, Xiamen, China. Three operational modes, including supplementing reclaimed domestic wastewater and fresh surface water from the Xinglin Bay to maintain the river water level, and cycling landscape water to stabilize the water quality, were examined. No water deterioration was detected throughout the period, and therefore OWQMS was proved to be effective in managing the scenic river and keeping the quality of landscape water stable in the past four years. Moreover, strong self-purification in the river water on pollutants, including nitrogen and phosphate degradation, was observed. The outcomes showed that OWQMS was useful and effective for the management of scenic waters.

Study on Methods of Water Quality Analysis Based on Conventional Water Quality Monitoring Parameters

Water contamination events of urban water supply often show the characteristics of abruptness and variety, and the on-line water quality monitoring parameters usually are difficult to cover various contaminant parameters. With the help with routine detection and on-line water quality monitoring, it is possible to detect and judge whether a water quality event has happened or not and to identify its type indirectly, and obtain the relevant information of qualitative and quantitative analysis. These will be significant to the decision making by the concerning sectors and units. Taking the events of ammonium iron sulfate in the distribution system for example, the relationship of water between contamination concentration and conventional water quality monitoring parameters is investigated, and the quantitative method based on D-S evidence theory is given.

Protecting Water Quality and Public Health Using a Smart Grid

After the attacks on September 11, 2001 and the follow-up risk assessments by utilities across the United States, securing the water distribution system against malevolent attack became a strategic goal for the U.S. Environmental Protection Agency. Following 3 years of development work on a Contamination Warning System (CWS) at the Greater Cincinnati Water Works, four major cities across the United States were selected to enhance the CWS development conducted by the USEPA. One of the major efforts undertaken was to develop a process to seamlessly process “Big Data” sets in real time from different sources (online water quality monitoring, consumer complaints, enhanced security, public health surveillance, and sampling and analysis) and graphically display actionable information for operators to evaluate and respond to appropriately. The most significant finding that arose from the development and implementation of the “dashboard” were the dual benefits observed by all four utilities: the ability to enhance their operations and improve the regulatory compliance of their water distribution systems. Challenge: While most of the utilities had systems in place for SCADA, Work Order Management, Laboratory Management, 311 Call Center Management, Hydraulic Models, Public Health Monitoring, and GIS, these systems were not integrated, resulting in duplicate data entry, which made it difficult to trace back to a “single source of truth.” Each one of these data sources can produce a wealth of raw data. For most utilities, very little of this data is being translated into actionable information as utilities cannot overwhelm their staffs with manually processing the mountains of data generated. Instead, utilities prefer to provide their staffs with actionable information that is easily understood and provides the basis for rapid decision-making. Smart grid systems were developed so utilities can essentially find the actionable needle in the haystack of data. Utilities can then focus on rapidly evaluating the new information, compare it known activities occurring in the system, and identify the correct level of response required. Solution: CH2M HILL was engaged to design, implement, integrate, and deploy a unified spatial dashboard/smart grid system. This system included the processes, technology, automation, and governance necessary to link together the disparate systems in real time and fuse these data streams to the GIS. The overall solution mapped the business process involved with the data collection, the information flow requirements, and the system and application requirements. With these fundamentals defined, system integration was implemented to ensure that the individual systems worked together, eliminating need for duplicate data entry and manual processing. The spatial dashboard was developed on top of the integration platform, allowing the underlying component data streams to be visualized in a spatial setting. Result: With the smart grid system in place, the utilities had a straightforward method to determine the true operating conditions of their systems in real time, quickly identify a potential non-compliance problem in the early stages, and improve system security. The smart grid system has freed staff to focus on improving water quality through the automation of many mundane daily tasks. The system also plays an integral role in monitoring and optimizing the utilities’ daily operations and has been relied on during recovery operations, such as those in response to recent Superstorm Sandy. CH2M HILL is starting to identify the processes needed to expand the application of the smart grid system to include real-time water demands using AMI/AMR and real-time energy loads from pumping facilities. Once the smart grid system has been expanded to include Quality-Quantity-Energy, CH2M HILL can apply optimization engines to provide utility operations staffs with a true optimization tool for their water systems.

Implementation of an innovative sensor technology for effective online water quality monitoring in the distribution network

For safe supply of drinking water, water quality needs to be monitored online in real time. The consequence of inadequate monitoring can result in substantial health risks, and economic and reputational damages. Therefore, Vitens N.V., the largest drinking water company of the Netherlands, set a goal to explore and invest in the development of intelligent water supply. In order to do this Vitens N.V. has set up a demonstration network for online water quality monitoring, the Vitens Innovation Playground (VIP). With the recent innovative developments in the field of online sensoring Vitens kicked off, in 2011, its first major online sensoring program by implementing a sensor grid based on EventLab systems from Optiqua Technologies Pte Ltd in the distribution network. EventLab utilizes bulk refractive index as a generic parameter for continuous real time monitoring of changes in water quality. Key characteristics of this innovative optical sensor technology, high sensitivity generic sensors at low cost, make it ideal for deployment as an early warning system. This paper describes different components of the system, the technological challenges that were overcome, and presents performance data and conclusions from deployment of Optiqua's EventLab systems in the VIP.