Comparison of electromagnetic wave sensors with optical and low-frequency spectroscopy methods for real-time monitoring of lead concentrations in mine water

The feasibility of using novel electromagnetic wave sensors for real-time monitoring of metal pollution in water was assessed. Five solutions with different concentrations of lead (0, 1, 10, 50, 100 mg/L) were measured using several sensing methods: UV-Vis spectroscopy, low frequency capacitance and resistance measurements, and two sensing systems based on microwave technology. With this last approach, two sensing devices were used: a resonant cavity and a planar sensor with gold interdigitated electrode design printed on a PTFE substrate with a protective PCB lacquer coating. Results confirmed the ability of these systems to quantify the lead concentration as changes in spectrum signal at specific frequencies of the electromagnetic spectrum. Spectra were unique, with clearly observed shifts in the resonant frequencies of the sensors when placed in direct contact with different lead solutions, demonstrating the possibility of continuous monitoring with great sensitivity, selectivity, and high spatial and temporal resolution. Consequently, determination of trace and toxic metals using microwave spectroscopy is a promising alternative to traditional grab-sampling and laboratory based analyses. On-line and continuous monitoring of real-time metal concentrations offers the potential for a more effective emergency response and the platform for better scientific understanding and remediation of contaminated mine drainage

Microwave Technology: The Missing Piece of the Puzzle

At present, water quality control is still dominated by laboratory analysis of grab samples. Sensors are only available for a very limited number of parameters and frequently do not entirely meet the needs of the users. Even a brief overview of the state-of-the-art in the real time water monitoring reveals that it is not possible to achieve adequate detection of water parameters by using only one type of sensor. Accordingly, the solution is to merge various technologies into a single system that would employ the best available methods for the detection of specific water contaminants, so as to provide overall superior sensitivity, selectivity and long-term stability, while enabling real-time wireless data collection for enhanced cost-effectiveness. Namely, multi-sensor platforms that utilise the best available methods combined into a single monitoring process are seen as the only way to achieve the holistic monitoring capabilities. It is suggested that a special role in this development is reserved for microwave technology based sensors a missing piece in the puzzle to potentially solve the issue of real-time water quality control. This paper reviews the capabilities of microwave sensors for real-time water quality monitoring as compared to other alternative methods, namely standard UV-VIS optical methods; fibre optic sensors; amperometric sensors, biosensors, specifically-sensitive microelectrodes and lab-on-chip sensing systems

Detection of pathogenic bacteria in aqueous media: Assessing the potential of real-time electromagnetic wave sensing

This paper reports on the capabilities of a novel electromagnetic wave sensing method to detect and identify the presence of various pathogenic bacteria in aqueous media. In particular, the change in the electromagnetic wave signal in microwave frequency range is used as an indicator of bacteria presence. The assessment was conducted by recording reflected signal spectra when the sensor was in contact with deionised water, Escherichia coli, sterile nutrient broth and Pseudomonas aeruginosa solutions. The distinct feature of the proposed system is that the detection is performed in real time, without the need for additional sample processing or chemicals. This bacteria detection method would be of benefit in a broad range of applications, ranging from water quality monitoring in wastewater treatment facilities to safety assurance in healthcare and food industry

Flexible Approach to Sensors Arrays Nanopatterning for Real-Time Water Contaminants Monitoring Platform

This paper reports on the development of a flexible nanopatterning approach using the NanoeNablerTM to manufacture miniaturised sensor arrays platform for real-time water quality assessment. Traditionally biosensors are fabricated by lithography, screen printing, inkjet printing, spin-or deep-coating methods to immobilize the sensing element onto substrate pre-patterned with electrodes. NanoeNablerTM patterning method is benchmarked against other currently adapted approaches for cost-effective sensors arrays manufacture. Sensors measuring ~1 µm diameter or more can be patterned for further employment in molecularly imprinted polymer structures. Notably, the dimensions of the sensor depend on the fluid being patterned and on the interaction forces between the substrate and the patterning tool. Thus, careful selecting of patterning parameters is vital for repeatable and controlled manufacture of sensors to guarantee superior sensitivity. The reported nanopatterning method is capable of accurately placing attoliter to femtoliter volumes of liquids, including proteins and DNAs, onto any substrate, thus making it an ideal technology for biomedical sensors. A custom-made 1 cm2 silicon wafer with 48 interdigited electrodes sensor heads was used as a platform for the multi-sensor array with potential use in a wide range of real-time monitoring applications

Biomedical Sensing with Hydroxyapatite Ceramics in GHz Frequency Range

Hydroxyapatite (HA) is a leading biocompatible material extensively used for bone implants as a porous ceramic graft and as a bioactive coating. Electrical characteristics of HA can be employed in implantable devices for real-time in vivo pressure sensor applications such as in knee or hip prosthesis. In particular, high piezo and pyroelectricity of HA, its polarisation by electron beam and selective adsorption of proteins on polarised domains indicate the potential for real-time biosensing applications of HA. For this purpose, a comprehensive understanding of the dielectric behaviour of different forms of HA over a frequency range relevant for biomedical sensing is critical. Such information for HA, especially its frequency dependent dielectric behaviour over the GHz range, is rare. To this end, we report on novel investigations of properties of HA in powder and film forms in the GHz frequency range

Tackling water pollution: real-time monitoring of residual Antimicrobials concentration in aquaculture with microwave spectroscopy

To prevent the improper use of antimicrobials in aquaculture and to assist the food safety law enforcement, this paper reports on a bespoke electromagnetic (EM) wave sensing method for real-time in situ monitoring of residual antimicrobials concentrations in water samples. The antimicrobials solutions were tested in bespoke microwave cavity. Transmitted and reflected power signals were analysed in GHz frequency range and these were dependent on both: the type of antimicrobials present in water and on their concentration

Detecting the presence and concentration of nitrate in water using microwave spectroscopy

Nitrate is a common pollutant in surface waters which water companies must monitor for regulatory and safety reasons. The presence of nitrate in deionised water is detected and concentration estimated from microwave spectroscopy measurements in the range 9kHz-6GHz. Experimental results were obtained for 19 solutions (18 salt solutions in deionised water and 1 deionised water), each measured 10 times with 4001 points (total N=190). The resulting data was randomly assigned into equal parts training and test data (N=95 each). Both regression (for the estimation of nitrate concentration) and classification (for detecting the presence of nitrate) methods were considered, with a rigorous feature selection procedure used to identify two frequencies for each of the classification and regression problems. For detection classification models were applied with nitrate levels binned using 30mg/l as the threshold. A logistic regression model achieved AUROC of 0.9875 on test data and a multi-layer perceptron achieved AUROC of 0.9871. In each case the positive predictive value of the model could be optimised at 100% with sensitivity of 90% and specificity of 100%. For the concentration estimates, a linear regression model was able to explain 42% of the variance in the training data and 45% of the variance in the test data and an MLP model delivered similar performance, explaining 43% of variance in the training data and 47% of variance in the test data. A sensor based on this model would be appropriate for detecting the presence of nitrate above a given threshold but poor at estimating concentration

Milk Urea Content and δ13C as Potential Tool for Differentiation of Milk from Organic and Conventional Low- and High-Input Farming Systems

The influence of farming type (conventional or organic) and production system (low-and high-input) on various quality characteristics of milk have been in the focus of studies over the last decade. The aim of this work was to evaluate the impact of different dairy management and production systems on carbon stable isotopes ratio (δ13C) and milk urea content. The samples of raw milk were collected each two weeks at certified organic high-input and low-input farms, conventional high-input and low-input farms in late indoor period and outdoor period. Data analysis showed clear difference between milk from organic high- and low-input farms with non-overlapping range between -22.90 ‰ and -24.70‰ for δ13С in protein fraction (equal 1.80‰) and between -25.90‰ and -28.20‰ (equal 2.30‰) for δ13С in fat fraction independently from season factor, as for Δδ13С (protein-fat) values in milk from high-input (1.50-3.00‰) and low-input (3.20-6.30‰) organic farms. Analysis of correlation between δ13С in protein fraction and milk urea content values showed that during late indoor period the most significant difference was detected between milk from organic low-input and conventional high-input farms (5.85‰ for δ13С in protein fraction and 4.65 mg/100 g of milk urea content). During outdoor period, the non-overlapping range was established for low-input and high-input organic farms (3.40‰ for δ13С in protein fraction and 10.77 mg/100 g of milk urea content). Results of δ13С values in fat and protein milk fractions, as combination of δ13С in protein fraction and milk urea content could be a potential tool for the distinguish of milk from different farming types, based on different feed composition

Monitoring Use Of Antibiotics In Aquaculture

In the aquaculture industry around the world antibiotics are used for fish disease prevention and treatment. High residual levels of those antibiotics may contaminate natural water resources as well as soil, aquatic animals and plants. Their overuse in human and animal populations can lead to the development of resistant microbial strains, posing a dire threat to global health. Use of antibiotics in aquaculture and its impact on the environment is a growing concern amongst scientists, yet quantifying the amount of use and how much is being disseminated into the environment is very difficult. As with the use of antibiotics in food production more generally, there is a need for better data. To prevent the improper use of antibiotics in aquaculture and to assist the food safety law enforcement, this paper reports on assessing the feasibility of a bespoke electromagnetic wave sensing method for real-time in situ monitoring of residual antibiotic concentrations in water samples. For the first time the antibiotics solutions were tested in contact with planar sensor with interdigitated electrode pattern on a number of substrates, including Rogers®, FR4 and flexible polyimide substrates. Specifically, this paper communicates the experimental results of using bespoke microwave planar type sensors for the determination of Quinolones, in particular Enrofloxacin (ENR) and Norfloxacin (NOR) antibiotic concentrations. Reflected power signals were analysed in GHz frequency range and these were dependent on both: the type of antibiotic present in water and on its concentration