Detection Of Pollutants In Water Research Articles

A fluorescent test paper fabricated by in situ growth of a functional Zn-MOG for fast and effective detection of Cr(VI) and Fe(III)

Heavy metals, like iron and chromium(Cr), have been proved to be a serious pollutant to environmental and biological systems. Long-term exposure to Cr(VI) ions through drinking water is harmful to human and will cause some serious diseases. Therefore, exploring new method for selective and rapid detection of such specific pollutants in water is crucial for environmental protection and human health. Herein, a novel functional metal organic gel(MOG) was successfully fabricated. Its detection limit of Cr(VI) was 2.4 × 10−8 mol·L−1 in aqueous solution, and 1.2 × 10−6 mol·L−1 for Fe(III) Based on the excellent deformability of MOG materials, a fluorescent test paper which could realize visible detection of Cr(VI) was fabricated by the in situ growth of Zn-MOGs onto the filter paper. To the best of our knowledge, it is the first sample of Zn-MOGs Based Test Paper (Zn-MOGs-FP) fabricated by in situ growth.

Biomass valorization of walnut shell into biochar as a resource for electrochemical simultaneous detection of heavy metal ions in water and soil samples: Preparation, characterization, and applications

Lately, due to its accessibility and eco-friendliness, walnut shell biochar (WS-BC) is gaining attention as an electrode material component in the electrochemical detection of water pollutants. The overall performance of WS-BC is reliant on the nature of raw biomass and the production methods as well. In our concept, biochar, prepared from raw walnut shell (WS) by pyrolysis, was added to a carbon paste electrode (CPE), and poly-tyrosine (p-Tyr) was electrodeposited on the surface of the BC-doped electrode. The conditions of the elaboration of the electrode, such as pH, potential, and the number of deposition cycles, pH were optimized. The obtained p-Tyr-BC-CPE platform was tested for the determination of cadmium, lead, copper, and mercury ions in water and soil samples, using square wave voltammetry (SWV). The raw WS biomass and its BC were examined by thermal analysis (TG-DSC), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM/EDX) techniques. The synergistic effects of the coexistence of the WS-BC and the thin film of p-Tyr, for the detection of traces of heavy metal ions were investigated by electrochemical tests. The electrochemical characterization of the unmodified and modified electrodes was performed using the cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) methods, while the Cd2+, Pb2+, Cu2+, and Hg2+ detection experiments were studied using the CV and SWV techniques. The optimized experimental conditions for the p-Tyr-BC-CPE platform were evaluated. The obtained electrochemical results showed that the p-Tyr-BC-CPE platform produced excellent sensitivity toward the heavy metal ions: LOD of 0.086, 0.175, 0.246, and 0.383 nM for Cd(II), Pb(II), Cu(II) and Hg(II), respectively. The modified electrode platform displayed high selectivity, stability, and good reproducibility.

Identifying Water Pollution Sources Using Real-Time Monitoring and IoT

Water is a natural resource essential for basic human life; however, water pollution is deteriorating in major water sources, such as rivers, seas, and lakes. This study evaluated and identified specific pollution sources owing to numerous industrial and other potential sources of pollution along the enormous length of a Siak river. A water pollution detection system was installed and deployed at river measurement stations having the potential to pollute, particularly near industrial sites releasing chemicals and wastewater. Data obtained from the system was analyzed using an algorithm to detect and assess any abnormal behavior change in the data over time. Six detection systems were deployed around the river, primarily in residential and industrial areas. As the studied river is one of the deepest in Indonesia, this research focused only on analyzing and identifying the sources of polluted water around Pekanbaru where many people, including water supply companies, utilize the river water. Water pollution sources were identified at sensor nodes two and four, which indicated through abnormal data that various types of material were present in the river and were detected using the sensors system. Several processes are required to improve the location data accuracy, e.g., improving the algorithm using training data, performing several iterations, increasing data from the sensor, and repeating the process many times to establish the source coordinate, as shown in the results.

Fast Detection of Different Water Contaminants by Raman Spectroscopy and Surface-Enhanced Raman Spectroscopy.

Fast monitoring of water quality is a fundamental part of environmental management and protection, in particular, the possibility of qualitatively and quantitatively determining its contamination at levels that are dangerous for human health, fauna and flora. Among the techniques currently available, Raman spectroscopy and its variant, Surface-Enhanced Raman Spectroscopy (SERS), have several advantages, including no need for sample preparation, quick and easy operation and the ability to operate on the field. This article describes the application of the Raman and SERS technique to liquid samples contaminated with different classes of substances, including nitrates, phosphates, pesticides and their metabolites. The technique was also used for the detection of the air pollutant polycyclic aromatic hydrocarbons and, in particular, benzo(a)pyrene, considered as a reference for the carcinogenicity of the whole class of these compounds. To pre-concentrate the analytes, we applied a methodology based on the well-known coffee-ring effect, which ensures preconcentration of the analytes without any pretreatment of the sample, providing a versatile approach for fast and in-situ detection of water pollutants. The obtained results allowed us to reveal these analytes at low concentrations, close to or lower than their regulatory limits.

Microwave-assisted green synthesis of carbon dots derived from wild lemon (Citrus pennivesiculata) leaves as a fluorescent probe for tetracycline sensing in water

Herein, we report an eco-friendly biomass based completely greener microwave assisted synthesis of carbon dots from wild lemon leaves having superior photo-luminescent properties with moderately good quantum yield. The carbon dots synthesized (LLCDs) were characterized by high resolution transmission electron microscopy, fluorescent, UV–vis absorption, Fourier transform infrared and Raman spectroscopic techniques. The quenching of native fluorescence of LLCDs observed with tetracycline antibiotic was made use to make it as a fluorescent probe. Tetracycline is widely used as a drug to treat various bacterial infections and as a growth promoter in variety of farming fields like aquaculture and feedstock’s. The excessive usage of this antibiotic in farming fields caused severe water pollution and micro level detection of tetracycline in water system is highly demanded for the protection of health and environment. Based on the selective interaction of tetracycline with LLCDs, a simple and cost effective analytical method was proposed to detect tetracycline in water with satisfactory parameters. The limit of detection is 0.42 µM with a linear range of 0 to 27. 27 µM. The mechanism of quenching was investigated through various experiments and finally accredited to static quenching. Furthermore, the same method has been practically applied for tetracycline detection in natural water resources with acceptable recoveries ranging from 95.56 % to 101.93 %.

A Deep Learning Approach to Organic Pollutants Classification Using Voltammetry.

This paper proposes a deep leaning technique for accurate detection and reliable classification of organic pollutants in water. The pollutants are detected by means of cyclic voltammetry characterizations made by using low-cost disposable screen-printed electrodes. The paper demonstrates the possibility of strongly improving the detection of such platforms by modifying them with nanomaterials. The classification is addressed by using a deep learning approach with convolutional neural networks. To this end, the results of the voltammetry analysis are transformed into equivalent RGB images by means of Gramian angular field transformations. The proposed technique is applied to the detection and classification of hydroquinone and benzoquinone, which are particularly challenging since these two pollutants have a similar electroactivity and thus the voltammetry curves exhibit overlapping peaks. The modification of electrodes by carbon nanotubes improves the sensitivity of a factor of about ×25, whereas the convolution neural network after Gramian transformation correctly classifies 100% of the experiments.

The Use of Bryophytes, Lichens and Bromeliads for Evaluating Air and Water Pollution in an Andean City

Air and water pollution are global environmental problems; thus, bioindicators have become important tools for monitoring various pollutants, including metals and metalloids. Parmotrema arnoldii (Du Rietz) Hale and Tillandsia usneoides L. were evaluated as indicators of heavy metals in the air and Platyhypnidium aquaticum A. Jaeger and Marchantia polymorpha L. as indicators of heavy metals and a metalloid in water. The concentrations of cadmium (Cd), lead (Pb), copper (Cu), manganese (Mn) and zinc (Zn) as air pollutants and aluminum (Al), cadmium (Cd), iron (Fe), manganese (Mn), lead (Pb), zinc (Zn) and arsenic (As) as water pollutants were analyzed within four different zones (control, northern, central and southern) in an Andean city of Ecuador. The level of metal concentrations in the air for P. arnoldii and T. usneoides had the following order of concentration: Zn > Mn > Pb > Cd > Cu. In the case of water, P. aquaticum pointed out a concentration of Al > Mn > Fe > Zn > As > Pb > Cd and proved to be more effective in detecting water pollution than the species M. polymorpha, which had a concentration of Al >Zn > Fe > Cd >As > Mn > Pb. P. aquaticum showed a higher capacity to accumulate heavy metals than M. polymorpha; therefore, it can be used as a model species for passive water quality monitoring. However, P. arnoldii and T. usneoides showed similar heavy metal accumulation related to air quality. The passive monitoring of air quality using bromeliads and lichens as well as bryophytes for water quality proved their effectiveness and applicability in tropical regions such as Ecuador.

Green synthesis of carbon dots from elm seeds via hydrothermal method for Fe3+ detection and cell imaging

• Carbon dots were synthesized by hydrothermal method using elm seed as carbon source. • The CDs were selectively quenched by Fe 3+ and can be used as sensitive Fe 3+ sensor. • The CDs were good biocompatible and could label HepG2 cells with blue fluorescence. Hydrothermal method to prepare biomass-based carbon dots (CDs) is environmentally-friendly and it can convert useless waste into valuable materials. In this work, we aimed to use natural siberian elm ( Ulmus pumila L.) seeds as carbon source to synthesize CDs by hydrothermal method. The obtained CDs were characterized by TEM, FTIR and XPS methods, founding they were near-spherical in shape with an average diameter of 3.83 nm. The CDs were mainly composed by carbon, nitrogen and oxygen, which formed the various hydrophilic functional carboxyl, hydroxyl, amino and amide groups on the surface. In addition, the CDs could emit bright blue fluorescence under ultraviolet illumination with excellent pH stability and photostability. Among various metal ions, the CDs could be selectively quenched by Fe 3+ . The degree of quenching was linearly related to the concentration of Fe 3+ , indicating they could be used for Fe 3+ detection. Finally, the CDs were proven to be good biocompatible by MTT assay and they could effectively label HepG2 cells with bright blue fluorescence. In summary, the CDs could be potentially applied as Fe 3+ sensors for water pollution detection and agents for cell imaging.

A novel water pollution detection method based on acoustic signals and long short-term neural network

A novel water pollution detection method based on acoustic signals and long short-term neural network

UV-Cured Green Polymers for Biosensorics: Correlation of Operational Parameters of Highly Sensitive Biosensors with Nano-Volumes and Adsorption Properties.

The investigated polymeric matrixes consisted of epoxidized linseed oil (ELO), acrylated epoxidized soybean oil (AESO), trimethylolpropane triglycidyl ether (RD1), vanillin dimethacrylate (VDM), triarylsulfonium hexafluorophosphate salts (PI), and 2,2-dimethoxy-2-phenylacetophenone (DMPA). Linseed oil-based (ELO/PI, ELO/10RD1/PI) and soybean oil-based (AESO/VDM, AESO/VDM/DMPA) polymers were obtained by cationic and radical photopolymerization reactions, respectively. In order to improve the cross-linking density of the resulting polymers, 10 mol.% of RD1 was used as a reactive diluent in the cationic photopolymerization of ELO. In parallel, VDM was used as a plasticizer in AESO radical photopolymerization reactions. Positron annihilation lifetime spectroscopy (PALS) was used to characterize vegetable oil-based UV-cured polymers regarding their structural stability in a wide range of temperatures (120–320 K) and humidity. The polymers were used as laccase immobilization matrixes for the construction of amperometric biosensors. A direct dependence of the main operational parameters of the biosensors and microscopical characteristics of polymer matrixes (mostly on the size of free volumes and water content) was established. The biosensors are intended for the detection of trace water pollution with xenobiotics, carcinogenic substances with a very negative impact on human health. These findings will allow better predictions for novel polymers as immobilization matrixes for biosensing or biotechnology applications.

Green production of self-assembled silver nanoarrays on flexible substrate for direct detection and catalytic degradation of organic water pollutants

Facile eco-friendly green chemistry assisted (hybrid tea rose petals extract) self- assembled plasmonic silver nano structure arrays (AgNS) were fabricated on a flexible substrate. In-situ self-assembly during the reduction process lead to organize arrays like AgNS with smaller size Ag nanocubes. Synthetic mechanisms detailed with optimizations were deliberately projected with UV–visible absorption spectroscopic studies. Structural studies indicated the cubic system of silver with an average crystalline size of 20 nm. Electron microscopic images elucidate the array like self-assembled Ag cubes; outstand for high phase purity with 95.6% of Ag. As well, UV–vis absorption results confirmed the shape confinement of self-assembled Ag nanocubes with the SPR band located around 450–490 nm. Feasibility of AgNS array in catalytic degradation of Rhodamine B dye tests was assessed with efficient degradation of 97% within 8 min. Ever since AgNS were forthright in field of calorimetry detection, H2O2 calorimetry studies were portrayed. Further on, fabrication of flexible, cost-effective plastic SERS support as sensor was developed with AgNS array (GAFPS) is yet another milestone achieved in SERS sensor platform. Raman probe molecule (Rhodamine 6G (R6G)) was exploited in optimization experiments for SERS detection. The optimized GAFPS SERS sensor involved in detection of Methylene blue (MB) and Rhodamine B (RhB) dyes; Sensor sensitivity studies succeeded with its sensitivity limit down to nano-molar range for RhB whereas close to pico-molar range for MB. In nutshell, multifaceted features of self-assembled plasmonic AgNS brings in state of art in the detection and degradation of industrial waste water management systems.

A series of new luminescent lanthanide naphthalates: The discovery of rare multi−responsive sensor for acetone, Fe3+, CrO42− and Cr2O72−

Long−term exposure to hazardous Fe3+, CrO42−, Cr2O72− and acetone may cause serious effects on the human body, so the exploration of new luminescent sensors for quickly and selectively monitoring these hazardous pollutants is very important. Herein, 1,10−phenanthroline (phen) as chromophore was used in combination with 2−naphthalenecarboxylic acid (2−Hnca) bridging ligand to construct a series of new lanthanide naphthalates [Ln2(phen)2(2−nca)6]·nH2O {n = 2, Ln = Sm (1), Eu (2), Gd (3); n = 0, Ln = Dy (4), Tm (5)}, which display binuclear [Ln2(phen)2(μ−2−nca)4(2−nca)2] or [Ln2(phen)2(μ−2−nca)2(2−nca)4] moieties with a center of inversion. Luminescent and sensing experiments illustrate that 2 can not only exhibit a remarkable red light emission with high quantum yield of 52.19 %, but also show a quickly and effectively sensing properties toward different pollutants (Fe3+, CrO42−, Cr2O72− and acetone) in aqueous solution with the lower detecting limits of 1.18–6.63 ppm. So far, a few luminescent lanthanide naphthalates have been emerged, but no lanthanide naphthalates incorporating phen chromophores can be served as the multi−responsive luminescent sensors for monitoring various pollutants. Hence, 2 offers the sole example of lanthanide naphthalates as the multi−responsive sensor for the quick and effective detection of different pollutants in water.

Droplet Microfluidic Device for Chemoenzymatic Sensing.

The rapid detection of pollutants in water can be performed with enzymatic probes, the catalytic light-emitting activity of which decreases in the presence of many types of pollutants. Herein, we present a microfluidic system for continuous chemoenzymatic biosensing that generates emulsion droplets containing two enzymes of the bacterial bioluminescent system (luciferase and NAD(P)H:FMN–oxidoreductase) with substrates required for the reaction. The developed chip generates “water-in-oil” emulsion droplets with a volume of 0.1 L and a frequency of up to 12 drops per minute as well as provides the efficient mixing of reagents in droplets and their distancing. The bioluminescent signal from each individual droplet was measured by a photomultiplier tube with a signal-to-noise ratio of up to 3000/1. The intensity of the luminescence depended on the concentration of the copper sulfate with the limit of its detection of 5 M. It was shown that bioluminescent enzymatic reactions could be carried out in droplet reactors in dispersed streams. The parameters and limitations required for the bioluminescent reaction to proceed were also studied. Hereby, chemoenzymatic sensing capabilities powered by a droplet microfluidics manipulation technique may serve as the basis for early-warning online water pollution systems.

Detection and Treatment of Persistent Pollutants in Water: General Review of Pharmaceutical Products

AbstractEnvironmental problems of great complexity arise from the enormous number of toxic substances that are generated by anthropogenic activities. Seemingly, society encounters new issues every day thus these problems seem to be endless. Now in the face of the COVID‐19 pandemic and the SARS‐CoV‐2 crisis, a large number of emerging treatment compounds generated by pharmaceutical companies worldwide makes future issues even more treacherous. For this reason, there is an increasing need to detect and treat emerging compounds to prevent them from becoming persistent pollutants. This review describes the advances in the use of electrochemical sensors with modified carbon‐based electrodes among other issues, to determine antibiotics, anti‐inflammatories and antidepressants levels in the environment. It further explores technologies suggested for cleaning wastewater polluted by pharmaceutical products using biological or advanced oxidation processes including photolysis, photocatalysis, microwave heating, ultrasound, Fenton, electro‐Fenton, photoelectro‐Fenton and various combined treatments.

Novel natural exudate as a stabilizing agent for fabrication of copper nanoparticles as a colourimetric sensor to detect trace pollutant

Detection of trace pollutants in water has become one of the most interesting issues due to its direct relation to human health. This work exploits a simple, novel, cost-effective, and environmentally friendly method to fabricate optical copper nanoparticles (Cu NPs) as an efficient colourimetric sensor using tree gum as a stabilising and capping agent. The localised surface plasmon resonance (LSPR) band of almond gum Cu NPs (ACuNPs) is monitored using ultraviolet-visible (UV-vis) spectroscopy. With an average size of 33 nm, the ACuNPs, which were uniformly spherical, are assessed using high resolution-transmission electron microscopy (HR-TEM). The formation of pure metallic-phase crystalline ACuNPs is illustrated using x-ray diffractometry. The Cu nanostructure determines the thiocyanate (SCN−) ions in an aqueous medium as a colourimetric sensor. The ACuNPs demonstrated sensitive and selective colourimetric detection of SCN− ions based on the decrease in LSPR intensity, as monitored by a UV-vis spectrophotometer. The developed sensor is simple, rapid, and inexpensive compared to those based on precious noble metal nanoparticles and is sensitive to SCN− ions with a detection limit of 0.226 mg/l. This work presents the development of a highly effective and rapid sensor to detect SCN− ions without complex apparatuses.

Smartphone-based Surface Plasmon Resonance Sensors: a Review.

The surface plasmon resonance (SPR) is a phenomenon based on the combination of quantum mechanics and electromagnetism, which leads to the creation of charge oscillations on a metal–dielectric interface. The SPR phenomenon creates a signal which measures refractive index change at the metal–dielectric interface. SPR-based sensors are being developed for real-time and label-free detection of water pollutants, toxins, disease biomarkers, etc., which are highly sensitive and selective. Smartphones provide hardware and software capability which can be incorporated into SPR sensors, enabling the possibility of economical and accurate on-site portable sensing. The camera, screen, and LED flashlight of the smartphone can be employed as components of the sensor. The current article explores the recent advances in smartphone-based SPR sensors by studying their principle, components, application, and signal processing. Furthermore, the general theoretical and practical aspects of SPR sensors are discussed.

Polarimetry-inspired feature fusion spectroscopy (PIFFS) for ammonia sensing in water.

The sustainable use of water resources is inseparable from water pollution detection. The sensing of toxic ammonia nitrogen in water currently requires auxiliary reagents, which may cause secondary pollution. Benefiting from the ability of substances to change light characteristics, this work proposes polarimetry-inspired feature fusion spectroscopy (PIFFS) to detect ammonia. The PIFFS system mainly includes a light source, a quarter-wave plate (QWP), a linear polarizer (LP) and a fiber spectrometer. The target light containing substance information is polarization modulated by adjusting the QWP and LP angles. Then, the Stokes parameters of target light can be calculated by appropriate modulations. The feasibility of PIFFS method to detect ammonia nitrogen is verified by experiments on both standard water samples and environmental water samples. Experimental results show that inspired by the first Stokes parameter, the fused features provide superiority in classifying ammonia concentration. The results also demonstrate the effectiveness of support vector machine-based concentration classification and random forests-based spectral selection. The interaction between light and substances ensures that the proposed PIFFS method has the potential to detect other pollutants.

Towards a miniaturized on-site nano-high performance liquid chromatography electrospray ionization ion mobility spectrometer with online enrichment

Safeguarding water quality is resource-intensive and costly. Especially in cases of accidents or disasters, compact devices that allow quick assessment of the current situation are lacking. The objective of this work is the development of a portable measuring device for on-site detection of pollutants in water based on nano-high performance liquid chromatography (nano-HPLC) and electrospray ionization (ESI) ion mobility spectrometry (IMS). Integrated online enrichment by means of solid phase extraction (SPE) further improves sensitivity. In this work, an SPE cartridge exchange unit is presented, which was developed by additive manufacturing in a cost-effective and resource-efficient way. Prerequisites are an easy adaptation to commercially available SPE cartridges and pressure stability of up to 50 bar. In addition, a compact ESI-IMS with 75 mm drift tube length and a resolving power of R = 100 is presented that enables ionization, separation based on ion mobility and detection of analytes at a flow rate of 0.6 – 1.8 µL/min from the liquid phase. This approach also allows miniaturization of the overall system leading to a reduction in energy requirements and the amount of solvents used. For future environmentally benign systems, complete elimination of toxic solvents would be ideal. Therefore, acetonitrile and the nontoxic ethanol are compared as organic mobile phase in terms of elution and ionization efficiency. For characterization, a test mixture containing relevant target analytes, such as chlortoluron, isoproturon, pyrimethanil, mepanipyrim, cyprodinil and carbamazepine, is analyzed. In addition, the analytical greenness metric approach tool is used to evaluate the overall system in terms of its green credentials. It was shown that ethanol can be well used as an organic solvent for the mobile phase and even exhibits better ionization than acetonitrile for the selected model analytes. Furthermore, a relatively high orthogonality of O=0.53 and an effective 2D peak capacity of 2Dneff=174 are reached. Due to the overall miniaturization and splitless coupling, the aims of green chemistry can be met, and ideally a value of 0.92 can be achieved using the AGREE tool for the presented system.

CONTAMINANT IDENTIFICATION IN WATER BY MICROBIAL BIOSENSORS –


 The various micro-organisms are used to identify contaminated water. By the help of biosensors,
 drinking water pollution can be estimated. Rising environmental pollution is badly affecting water.
 Drinking contaminated water causes serious diseases in human beings as well as in animals.
 Microorganism in contaminated water can spread serious diseases. Biosensors are genetically
 modified to identify the occurrence of heavy metals, chemicals and toxins in contaminated water.
 Different microbes are used as biosensors such as Escherichia coli, Algae, Fungi and Clostridium 
 etc. All these biosensors help to detect water pollution by different ways. For example, algae can
 detect water contamination by fluorescence during photosynthesis. Most rural areas are being
 affected by contaminated water. Most of the people living in rural areas are being affected by the
 polluted water as clean water is not available in these areas. People living in rural areas use water
 that looks clear but contains micro-pathogens that can cause dangerous diseases. Biosensors are
 important for identifying contamination, Due biosensor, can easily deduct pollution. Water is very
 important for the survival. Drinking contaminated water can cause serious illness. Therefore, clean
 water is very important.
 Keywords: Microbial Biosensors; Water Pollution

Reproducible Flexible SERS Substrates Inspired by Bionic Micro‐Nano Hierarchical Structures of Rose Petals

AbstractSurface‐enhancement Raman scattering (SERS) is widely applied in environmental protection, biomedicine, origin traceability, food safety, and other fields as a crucial analysis and detection method. The construction strategy of excellent SERS substrates has always been a research hotspot. In this article, a 3D micro‐lens array/wrinkle structures/silver nanoparticles SERS substrate (MLA/WS/AgNPs 3D‐SERS) is prepared, which is enlightened by rose petals with ordered micro‐nano hierarchical structures. Using Rhodamine 6G to measure SERS performance, the minimum detection limit is 10−10 m and the minimum value of relative standard deviation is 6.12%. Moreover, MLA/WS/AgNPs 3D‐SERS substrate can be stored for ≈20 days under natural conditions with almost no performance loss. Finally, the malachite green (MG) detection in the water of Daming Lake is carried out and the characteristic peaks of MG are accurately detected, proving that the substrate has practical application potential in drug detection, food safety, and water pollution detection. This research gives the biomimetic construction of the SERS substrates, which enriches the construction strategy.