Detection Of Pollutants In Water Research Articles

A “2-in-1” Bioanalytical System Based on Nanocomposite Conductive Polymers for Early Detection of Surface Water Pollution

A “2-in-1” Bioanalytical System Based on Nanocomposite Conductive Polymers for Early Detection of Surface Water Pollution

Design of magnetic photonic crystal microdroplet for sensitive detection of cationic organic pollutants by the coupled resonance effect

Photonic crystals (PCs), periodically arranged nanoparticles, have emerged with extraordinary optical properties for light manipulation owing to their photonic band gaps (PBGs). Here, a novel strategy and method was developed for efficient enrichment and sensitive detection of cationic organic pollutants in water. Size-controlled Fe3O4@poly (4-styrenesulfonic acid-co-maleic acid) (Fe3O4@PSSMA) was prepared, and high surface charge were formed with the coating of PSSMA layer on the surface of Fe3O4, which could be used for adsorption and removal of cationic organic pollutants. The Fe3O4@PSSMA after adsorbing cationic organic pollutant were assembled to magnetic photonic crystal microdroplet (MPCM) structure in an external magnetic field, which was used as surface-enhanced Raman scattering (SERS) substrate. By coupling the magnetically tuned PBGs with Raman laser wavelength, the light utilization efficiency can be improved and the coupled resonance effect was greatly enhanced. The enhancement factor (EF) of MB was more than 800 attributing to the dual function of enrichment and coupled resonance effect of MPCM. The developed analytical strategy is the first time to use MPCM as a SERS substrate to realize the sensitive detection of 10 nmol L−1 MB in real water, which greatly improves the application of MPCM in the field of contaminant analysis and detection in water.

SISTEM CERDAS PENGURAS AIR AKUARIUM SECARA OTOMATIS BERBASIS INTERNET oF THINGS (IoT) MENGGUNAKAN ALGORITMA C4.5 pada PLATFORM BLYNK

In general, fishkeeping has been a widely cherished activity among communities since ancient times, owing to its ease of maintenance and care, which encourages many individuals to engage in it. However, due to busy schedules or unforeseen circumstances, checking the water conditions in aquariums often poses a challenge. Therefore, there is a need for a tool capable of automatically controlling and draining aquarium water based on IoT technology using the C4.5 algorithm on the Blynk platform. This system can drain water if the aquarium water becomes cloudy, raise the temperature if it drops below optimal levels, and limit water filling. The ESP8266 and ESP32-S modules are utilized to receive, process, and transmit data to the aquarium owner via Wi-Fi. Relays serve as electrical power distributors for supporting components such as water pumps, water heaters, and solenoid valves. Testing results indicate that the water condition control component effectively operates in line with the system's functions and objectives. The existence of this tool can assist fishkeepers in maintaining real-time aquarium water quality, detecting water pollution, and monitoring the health of fish within the aquarium.

Detection of metallic pollutants in waste water using bio sensors and its remediation

AbstractWater pollution has emerged as the biggest threat to the sustenance of human civilization and the environment. With the increase in rapid industrialization and urbanization, there is a considerable increase in the influx of complex and diverse pollutants in water bodies. Hence continuous and efficient monitoring is required to detect the pollutants in the aquatic environment. Either preventing or detecting and subsequent elimination of these pollutants is of utmost importance for the health of the aquatic ecosystem. Biosensors have proved to be efficient in detecting these pollutants in a better way as compared to other conventional methods. Sensors are devices that have the ability to detect changes in the physical, chemical, or biological domains and produce a signal that can be measured. The distinguisher element in it minimizes noise caused by other components in the analyte mixture by being able to detect a specific analyte or set of analytes. This current review is focused on the role of biosensors in detecting metallic pollutants in water bodies. It also discusses the process of remediation of metallic pollutants in the aquatic environment.

Package-Less Liquid Phase Sensing Using Surface Acoustic Waves on Lithium Tantalate Oxide.

Surface acoustic wave (SAW) transducers propagating shear waves are compatible with sensing chemical compounds in a liquid phase. However, if the liquid surrounding the sensor possesses a higher permittivity than the piezoelectric substrate, then the interdigitated electrodes for converting the incoming electromagnetic wave to acoustic waves are susceptible to capacitive short-circuiting, leading to excessive insertion losses. By using high-permittivity lithium tantalate oxide (LTO), we demonstrate chemical sensing in water without the need for dedicated microfluidic packaging. Nevertheless, the gravimetric sensitivity of these package-less transmission Love-mode delay lines remains comparable to that of low-permittivity quartz when appropriately tuning the guiding layer of thin film to confine energy to the surface in a Love mode. We extend the transmission line gravimetric sensitivity measurement to a reflective delay line geometry for passive transducers that can be wirelessly probed. For instance, ground-penetrating radar (GPR) can be used for subsurface sensing, here targeting water pollution detection, operating in the 100-500-MHz range. This center frequency was selected as a tradeoff between penetration depth (lower frequency) and antenna size (smaller at higher frequency). Nonspecific binding of proteins detection is shown in the context of biosensing applications.

Fluorescence response of metalo-hydrogen-bonded organic framework (MHOF) with room temperature phosphorescence to organic pollutants

For health, environmental and safety reasons, it is necessary to conduct highly sensitive detection of organic contaminant antibiotics (sulfathiazole) and nitro explosive drugs (o-nitroaniline) in water. In this work, metal-hydrogen bonded organic framework (MHOF), {[Co(Ad)2(H2O)4]·(H2L)·2.5H2O}n (1), was synthesized by a one-pot hydrothermal method with 2,6-bis(3,5-dicarboxyphenoxy) pyridine (H4L) and adenine (Ad). This MHOF shows a 4-fold interpenetrated three-dimensional (3D) network structure. Importantly, 1 has excellent fluorescence properties and can be used as fluorescent chemical sensor to detect sulfathiazole (STZ) and 2-nitroanilin (2-NA) with limit of detection (LOD) 203 ppb and 6.8 ppb, respectively. By UV-vis absorption/emission spectroscopic measurements and DFT calculations, it is found that photoinduced electron transfer (PET) and fluorescence resonance energy transfer (FRET) are two potential quenching processes. This is the first report of metal-hydrogen bond organic frameworks (MHOFs) as a promising new fluorescent chemical sensor for the detection of organic pollutants in water.

Advantages of the low-temperature secondary emission mass spectrometry in analysis of metal ions in water samples revisited

A problem of necessity of concentrating trace admixtures of metal ions required for ecological water analysis can be overcome by harnessing a physical phenomenon of phase separation in aqueous solutions during their freezing. It is shown that the accumulation of metal-containing solutes in the channels between ice crystallites in the frozen solids is sufficient for their successful detection by means of low-temperature secondary emission mass spectrometry. Sufficiency of microliters volumes of water is an advantage of such an approach. Observation of various types of metal ions in frozen water samples is demonstrated on the examples of tap water, sea water, snow and a medicinal preparation. Revisiting and summation of physical basics of mass spectrometric examining of frozen water-inorganic salt solutions and estimates of advancement of mass spectrometric instrumentation permit us to propose a workflow for accelerated and simplified mass spectrometric detection of metal pollutants in water.

Comprehensive Analysis of Phylogenetic Relationship and Optimal Codons in Mitochondrial Genomes of the Genus Pseudogastromyzon

As indicator organisms for water pollution detection, Pseudogasteromyzon species play a vital role in aquatic environment monitoring. We have successfully sequenced the mitogenomes of P. fasciatus jiulongjiangensis and P. myersi and downloaded the mitogenomes of nine other Pseudogastromyzon fish on GenBank to conduct a detailed comparative analysis of their phylogenetic relationships and evolutionary history. The findings revealed a conservation in both gene composition and gene order. Except for the trnS1 gene lacking dihydrouracil arms, the other 21 tRNAs showed the typical clover-leaf secondary structure. According to the ΔRSCU method, we identified the seven most abundant optimal codons: CUA, GUA, CCA, CAA, GAA, AGC, and GGC. The construction of maximum parsimony, maximum likelihood, and Bayes trees yielded congruent topologies, and the 11 Pseudogastromyzon species were clustered into two major clusters. Among them, one of which was composed of P. fangi, P. changtingensis changtingensis, and P. changtingensis tungpeiensis, while the remaining eight species formed another cluster, further subdivided into five smaller clusters. Distinct clusters formed between P. fasciatus jiulongjiangensis and P. meihuashanensis, P. cheni and P. peristictus, and P. laticeps and P. lianjiangensis, and the remaining two species were clustered separately, thereby enhancing our understanding of them. Furthermore, our analysis results of divergence times revealed that these 11 Pseudogasteromyzon species underwent rapid differentiation in the Pleistocene epochs. Overall, our study sheds light on the phylogenetic relationship and evolutionary history of Pseudogasteromyzon species, providing a necessary knowledge foundation for further understanding the intricacies of an ecosystem health assessment.

A deep learning-based biomonitoring system for detecting water pollution using Caenorhabditis elegans swimming behaviors

Caenorhabditis elegans is a representative organism whose DNA structure has been fully elucidated. It has been used as a model organism for various analyses, including genetic functional analysis, individual behavioral analysis, and group behavioral analysis. Recently, it has also been studied as an important bioindicator of water pollution. In previous studies, traditional machine learning methods, such as the Hidden Markov Model (HMM), were used to determine water pollution and identify pollutants based on the differences in the swimming behavior of C. elegans before and after exposure to chemicals. However, these traditional machine learning models have low accuracy and a relatively high false-negative rate. This study proposes a method for detecting water pollution and identifying the types of pollutants using the Long Short-Term Memory (LSTM) model, a deep learning model suitable for time-series data analysis. The swimming activities of C. elegans in each of the image frames are characterized by the Branch Length Similarity (BLS) entropy profile. These BLS entropy profiles are converted into input vectors through additional preprocessing using two clustering methods. We conduct experiments using formaldehyde and benzene at 0.1 mg/L each, with observation time intervals varying from 30 to 180 s. The performance of the proposed method is compared with that of the previously proposed HMM approach and variants of LSTM models, such as Gated Recurrent Unit (GRU) and Bidirectional LSTM (BiLSTM).

Ultrasensitive detection of aromatic water pollutants through protein immobilization driven organic electrochemical transistors.

Xenobiotic aromatic water pollutants pose an extreme threat to environmental sustainability. Due to the lack of detectable functional groups in these compounds and scarcity of selective bio-recognition scaffolds, easy-to-use sensing strategies capable of on-site detection remain unavailable. Herein, to address this lacune, we entail a strategy that combines biosensor scaffolds with organic electronics to create a compact device for environmental aromatic pollution monitoring. As proof of principle, a sensor module capable of rapid, economic, reliable, and ultrasensitive detection of phenol down to 2 ppb (0.02 μM) was designed wherein biosensing protein MopR was coupled with an organic electrochemical transistor (OECT). For effective interfacing of the sensing scaffold MopR, graphene oxide (GO) nanosheets were optimized as a host immobilization matrix. The MopR-GO immobilized sensor module was subsequently substituted as the gate electrode with PEDOT:PSS serving as an organic semiconductor material. The resulting OECT sensor provided a favourable microenvironment for protein activity, maintaining high specificity. Exclusive phenol detection with minimal loss of sensitivity (<5% error) could be achieved in both complex pollutant mixtures and real environmental samples. This fabrication strategy that amalgamates biological biosensors with organic electronics harnesses the potential to achieve detection of a host of emerging pollutants.

Carbohydrate polymer-supported metal and metal oxide nanoparticles for constructing electrochemical sensors

Metal- and metal oxide-carbohydrate polymers are considered a promising tool for electrochemical detection of biological analytes and water pollutants.

Magnetic Persimmon Leaf Composite: Preparation and Application in Magnetic Solid-Phase Extraction of Pesticides in Water Samples.

In recent years, the utilization of biomass materials for the removal and detection of water pollutants has garnered considerable attention. This study introduces, for the first time, the preparation of Fe3O4/persimmon leaf magnetic biomass composites. The magnetic composites were employed in a magnetic solid-phase extraction method, coupled with gas chromatography-electron capture detection (GC-ECD), for the analysis of four pesticides (trifluralin, triadimefon, permethrin, and fenvalerate) in environmental water samples. The innovative magnetic persimmon leaf composites were synthesized by in situ generation of Fe3O4 nanoparticles through coprecipitation and loaded onto persimmon leaves. These composites exhibit superparamagnetism with a saturation magnetization of 12.8 emu g-1, facilitating rapid phase separation using a magnetic field and reducing the extraction time to 10 min. Desorption can be achieved within 30 s by aspirating 20 times, eliminating the need for time-consuming and labor-intensive experimental steps like filtration and centrifugation. The specific surface area of the magnetic composite adsorbent increased from 1.3279 m2 g-1 for the original persimmon leaf to 5.4688 m2 g-1. The abundant hydroxyl and carboxyl groups on the composites provide ample adsorption sites, resulting in adsorption capacities ranging from 55.056 mg g-1 to 73.095 mg g-1 for the studied pesticides. The composites exhibited extraction recoveries ranging from 80% to 90% for the studied pesticides. Compared to certain previously reported MSPE methods, this approach achieves equivalent or higher extraction recoveries in a shorter operation time, demonstrating enhanced efficiency and convenience. Good linearity of the target analytes was obtained within the range of 0.75-1500 μg L-1, with a determination of coefficient (R2) greater than 0.999. These findings contribute to the use of magnetic persimmon leaf biomass materials as effective and environmentally friendly adsorbents for pollutant determination in water samples.

Dosage-sensitive and simultaneous detection of multiple small-molecule pollutants in environmental water and agriproducts using portable SERS-based lateral flow immunosensor

The co-contamination of pesticide residues and mycotoxins in agricultural products is a global concern, with the potential for cumulative and synergistic damaging effects, imposing substantial health and economic burdens to the public. The dosage-sensitive and simultaneous detection of multiple pollutants, with a heightened sensitivity in real samples, poses a significant demand and challenge. Herein, we propose a portable detection method integrating surface-enhanced Raman scattering (SERS)-with lateral flow immunoassay (LFIA), offering high sensitivity and multiplex analysis capabilities. This approach enables the simultaneous detection of imidacloprid (IMI), pyraclostrobin (PYR) and aflatoxin B1 (AFB1) through a single test strip. Utilizing the immune-specific binding between antigen and antibodies, we immobilised antibody- conjugated SERS nanotags on three test lines of the strips to generate Raman signal amplification in the proposed biosensor. Accurate quantitative analysis was performed by measuring the SERS signal intensity on the test lines. The limits of detection were 8.6 pg/mL for IMI, 97.4 pg/mL for PYR and 8.9 pg/mL for AFB1, exhibiting sensitivities 12-fold, 102-fold and11-fold higher than the colorimetric signals, respectively. Importantly, the SERS-LFIA immunosensor demonstrated robust performance when applied to real samples, yielding recoveries ranging from 86.16 % to 115.0 %, with relative standard deviation values below 8.67 %. These results underscore the excellent stability, high selectivity and reliability the proposed SERS-LFIA immunosensor. Consequently, it holds promise for the detection of multiple pesticides and mycotoxins in both environmental and agricultural samples.

Assessing the Role of Information and Communication Technology (ICT) in Safeguarding the Environment through the Application of the MOORA Method

Information and Communication Technology (ICT) plays a vital role in bolstering endeavors aimed at safeguarding the environment, and the MOORA method offers a structured approach. ICT involves the use of digital tools and technologies to manage and transmit information, enabling real-time data collection, analysis, and communication. In environmental protection, ICT aids in various ways, such as monitoring air and water quality, tracking wildlife patterns, and managing waste disposal. The MOORA method is a decision-making technique that helps prioritize alternatives based on multiple conflicting criteria. In the context of environmental protection, the MOORA method assists in selecting the most effective ICT solutions. It evaluates various ICT options by considering multiple objectives, such as efficiency, cost-effectiveness, ecological impact, and scalability. MOORA computes ratios to compare alternatives against each criterion, enabling a comprehensive assessment. By assigning weights to the criteria, stakeholders can emphasize specific factors according to their importance. For instance, when choosing between different ICT systems for waste management, the MOORA method can quantify the ecological benefits of reduced emissions, energy savings, and waste reduction against factors like implementation costs and technological feasibility. This systematic evaluation ensures that the chosen ICT solution aligns with the overall goal of environmental protection while considering practical constraints. ICT leverages advanced technologies to bolster environmental protection, and the MOORA method provides a structured approach to assess and prioritize ICT solutions. This combined approach facilitates informed decision-making, leading to the adoption of efficient and sustainable technologies that contribute to a healthier planet. The Smart Grid System (A1), E-waste Recycling Program (A2), Air Quality Monitoring Network (A3), Water Pollution Detection Sensors (A4), Green Supply Chain Management Software (A5), and Virtual Environmental Education Platform (A6) are employed as alternative solutions. These alternatives are assessed based on their ability to achieve Reduction in Environmental Impact (C1), Enhancement of Efficiency (C2), Cost Efficiency (C3), and User-Friendliness (C4).The environmental production of E-waste Recycling Program is got first rank and Smart Grid System is got lowest rank.

Angular surface plasmon resonance-based sensor with a silver nanocomposite layer for effective water pollution detection

For sensing various samples of polluted water and various sodium chloride concentrations using an angular surface plasmon resonance (ASPR), we have introduced a conventional structure and a hybrid heterostructure in the current research. The suggested structures are composed of silver metal, dielectric layers, silver nanocomposite, and a sensing medium. The reflectance spectra of all structures in the visible region were obtained through the utilization of the transfer matrix method by using the angular interrogation method depending on the Kretschmann configuration. Through our findings, five substrate parameters have been optimized to attain the utmost level of sensitivity across all structures: the thickness of Ag-metal, the type and thickness of dielectric materials, the host material type and the volume fraction of nanoparticles for the nanocomposite layer. In this regard, the suggested sensor provides excellent performance with a sensitivity of 448.1°/RIU\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$/\ ext{RIU}$$\\end{document}, signal-to-noise ratio of 0.787, sensor resolution of 0.284°, and figure of merit of 78.766 RIU−1. Therefore, we believe that the introduced design of our ASPR sensor presents a good candidate for an accurate and efficient detection of low concentrations of contaminated water and sodium chloride as well.

Luminescent Metal–Organic Frameworks for Electrochemiluminescent Detection of Water Pollutants

The modern lifestyle has increased our utilization of pollutants such as heavy metals, aromatic compounds, and contaminants that are of rising concern, involving pharmaceutical and personal products and other materials that may have an important environmental impact. In particular, the ultimate results of the intense use of highly stable materials, such as heavy metals and chemical restudies, are that they turn into waste materials, which, when discharged, accumulate in environmental water bodies. In this context, the present review presents the application of metal–organic frameworks (MOFs) in electrochemiluminescent (ECL) sensing for water pollutant detection. MOF composites applied as innovative luminophore or luminophore carriers, materials for electrode modification, and the enhancement of co-reaction in ECL sensors have enabled the sensitive monitoring of some of the most common contaminants of emerging concern such as heavy metals, volatile organic compounds, pharmaceuticals, industrial chemicals, and cyanotoxins. Moreover, we provide future trends and prospects associated with ECL MOF composites for environmental sensing.

Fabrication of nanofibrous membranes decorated with metal-organic frameworks for detection of pollutants in water

The environmental pollution caused by antibiotics, Fe3+ and MnO4− pollutants is becoming increasingly serious. Polyacrylonitrile (PAN) and polymethyl methacrylate (PMMA) were used and decorated with metal-organic frameworks (MOFs) to fabricated three kinds of nanofibrous membranes (NFMs) with different shapes and sizes were prepared by electrospinning technology using in situ growth method and mixed spinning method. The structures and properties of the above three kinds of NFMs were characterized. Among them, PAN@Co/Mn-MOF-74 NFM prepared by in-situ growth method based on PAN was a kind of nano-fluorescent NFM sensor with uniform structure and good fluorescence performance. It showed unique specificity and excellent sensitivity in the detection of ORN, Fe3+ and MnO4−. Compared with previously reported functionalized MOFs, PAN@Co/Mn-MOF-74 NFM has a lower limit of detection (LOD). This study provides a feasible technical route for the preparation of nano-fluorescent NFMs and the targeted detection of trace metal ions and antibiotics.

Simulation of a Sensitive Mid-infrared (MIR) D-Shaped Optical Fiber Water Pollutant Sensor

AbstractIn this work, an efficient optical sensor is proposed for the sensitive detection of various pollutants in water. The suggested optical sensor is based on an indium fluoride (InF3) glass fabricated as a D-shaped optical fiber. The polished surface of the D-shaped fiber is coated with a gold grating to induce the surface plasmon resonance (SPR). The SPR depends on the optical properties of the polluted water analyte in physical contact with the grating. The proposed optical SPR fiber sensor operates within the mid-infrared (MIR) range (3000–4500 nm) to detect any slight change in the water refractive index (RI) due to any pollutants. The full vectorial finite element method (FVFEM) is utilized to calculate the modal properties of the reported sensor. High sensor sensitivity of 17,834 nm/RIU (refractive index units) is achieved for the detection of dissolution of nitric acid (HNO3) in water at a concentration of 14% v/v (volume/volume). Additionally, the reported sensor detects the dissolution of hydrogen peroxide (H2O2) in water investigated at concentrations of 15% v/v and 30% v/v, with sensitivities of 12,308 nm/RIU and 17,143 nm/RIU, respectively. Further, suspending polystyrene beads of diameter 0.1 μm in the water at a concentration of 10% v/v gives a maximum sensitivity of 5333 nm/RIU. Therefore, the proposed sensor provides a promising approach for the detection of water pollutants in the MIR wavelength regime, rather than the weaker response in the near infrared.

Preparation of a recyclable composite aerogel with controllable peroxidase-like activity for on-site and visual analysis of the dihydroxybenzene isomers

Colorimetric detection methods have been attracted and preferred for analytes assessment. Although simple and highly efficient colorimetric strategies based on nanozymes have been developed, there remain inherent problems of intrinsic color interference for accurate analysis and erratic activity to lose controllable, recyclable, and sensitive efficacies. Herein, we have prepared a novel composite aerogel named PACO that is rationally assembled by the poly (vinyl alcohol) aerogel (PVA aerogel) and copper oxide nanoparticles (CuO NPs) to address these challenges. PACO has been proved to exhibit the controllable peroxidase (POD)-like activity through separating the solid PACO from the aqueous solutions. Meanwhile, PACO can avoid intrinsic color interferences and provide more accurate detection performance for naked-eye discrimination. Furthermore, PACO shows the recyclable and long lifetime performances for sensitive detection of water pollutants including hydroquinone (HQ) and catechol (CC) with the LOD of 0.084 μM and 0.101 μM, respectively. Finally, we have constructed a smartphone-based colorimetric detection platform to realize the on-site and visualanalysis of water pollutants in real water samples. Overall, PACO achieves the advanced detection performances to exhibit great potential in nanozymes based sensing method development and colorimetric-related analytical research.

A water-stable Y(III)-MOF as multi-responsive luminescent sensor for high-efficiency detection of Fe3+, Cu2+, and MnO4- ions in aqueous solutions

The effective detection of pollutants in water, such as Fe3+, Cu2+, and MnO4- ions, is critical to human health and environmental protection. Two yttrium-based coordination polymers {[Y(BITA)(H2O)]NO3}n (CP-1) and {[Y(HBTA)(ox)(H2O)]·H2O}n (CP-2) based on a π-conjugated 2,5-di(1H-imidazol-1-yl)terephthalic acid (H2BITA) were successfully prepared and sufficiently characterized. CP-1 exhibits a unique cationic 3D framework with a lvt net, accompanied by the decoration of NO3- anions. Adjacent Y3+ sites are bridged by double syn-syn carboxylate to form [Y2(μ-COO)2]n chains. CP-2 shows a 3D two-fold interpenetrating network with zigzag chains of [Y2(μ-C2O2)]n formed by ancillary oxalate bridging Y3+ ions. The HBTA- linkers propagate the 1D oxalate chains into 3D frameworks. The luminescent properties of CPs were investigated. Both CPs-1 and 2 exhibit purple and green fluorescence in the solid state, respectively. Meanwhile, CP-1 demonstrates excellent luminescent emission together with good chemical stability. Intriguingly, CP-1 exhibits outstanding selective and sensitive detection of cationic Fe3+ and Cu2+ and anionic MnO4- in aqueous solutions through luminescence quenching. In particular, the luminescence intensity could be significantly decreased by existence of MnO4-, which is seldom reported among the Y(III)-based coordination polymers. The quenching mechanism for various ions has been discussed in detail.