Suspended Particles In Water Research Articles

Polarization optical properties of suspended particles measurement in water by a polarized Scheimpflug lidar system

The polarization optical properties of suspended particles in water play a pivotal role in numerical simulation or real water medium detection. Polarized multi-wavelength oceanic lidar provides an effective method for characterizing the size, shape, and concentration of suspended particles. In this paper, we present a concise and effective optical approach to measure the information in the polarization of the lidar signal with 0°, 45°, 90°, and 135° polarization angles of suspended particles by laboratory experiments based on polarized Scheimpflug lidar system. This work uses typical suspended particles with different sizes and shapes as tracer particles to analyze particulate polarization information. Experiments with spherical or irregular silicon dioxide particles show that these particles can be effectively distinguished by analyzing the polarization optical properties of the backward scattering light. The laboratory system can classify suspended particles and may serve as a shipborne oceanic lidar or be used with submersibles.

Validation of the method for determining priority phthalates by GC-MS at trace concentrations in surface water with a background pollution level

A methodology for determining priority phthalates (PP) at trace concentrations in surface waters with a background pollution level has been validated. Lake Baikal, the largest natural reservoir that retains up to 20% of the world’s fresh surface waters, was chosen as a natural model for the study. Baikal is characterized by a minimal content of suspended organic matter, a low degree of mineralization and a background level of organic pollutants. Four priority phthalates were found in Baikal water: dimethyl phthalate, diethyl phthalate di-n-butyl phthalate and di-(2-ethylhexyl) phthalate present in the concentration range from 0.01 to 0.66 μg/liter. The method for phthalate determination includes a single liquid-liquid extraction of phthalates (Vsample = 1 liter) and direct analysis of the extracts by GC-MS. Considering the minimum content of suspended particles in water and the use of high sensitivity of the mass spectrometry, the stages of sample filtration and concentration of extracts are excluded from the procedure. Deuterated phthalates are used as surrogate internal standards for the quantitative determination of priority phthalates. The laboratory background of phthalates was assessed using reagent-blank methods, exhaustive multiple extraction and subsequent exclusion of the resulting value from the determination result as a systematic error. The limits of phthalate determination (0.01 – 0.17 μg/liter) and the error of determination (±δ from 12 to 38%) were assessed in the concentration range from 0.01 to 0.66 μg/liter. The method was validated during monitoring of persistent organic pollutants in water of Lake Baikal for the period 2015 – 2023.

A comparative study for ferro particles cloaking and wetting characteristics

Ferro hydrophobic particles possess essential properties for controlling the behavior of suspended substances in water. By adjusting the concentration of these particles, the magnetic force within the fluid carrier can be modified, leading to the emergence of distinct flow structures and patterns on the water's surface. This study examines the cloaking phenomenon exhibited by different ferroparticle conditions, employing both experimental and numerical approaches. Under the magnetic influence, hydrophilic particles can attain cloaking velocities of up to 35 mm/s, while hydrophobic particles remain unaffected by the magnetic force, remaining suspended on the water's surface. Hydrophobization of ferroparticles not only decreases their water-cloaking ability but also alters their magnetic properties. The inherent hydrophobic nature of these particles enhances water surface stability, rendering them valuable in various applications, including biomedical and self-cleaning technologies. This research holds particular significance for manipulating suspended particles in water, particularly in biomedical applications like drug delivery and tissue engineering, as well as for advancing self-cleaning technologies.

Investigation of the Effect of Pumping Depth and Frequency of Flapping Hydrofoil on Suspended Matter Discharge Characteristics

In order to study the effect of the pumping depth and pumping frequency of the flapping hydrofoil device on suspended solids in the waters, this paper takes raceway aquaculture as an example, and introduces a flapping hydrofoil device to improve the discharge of suspended solids in the raceway, in response to the problem of the deposition of suspended solids from fish faeces and bait residues in water. The CFD method was used to compare and analyze the discharge of suspended solids at different pumping depths, and the combined effect of the two was studied according to different combinations of pumping frequency and pumping depth. The results proved that the flapping hydrofoil motion can improve the bottom hydrodynamic insufficiency in ecological waters and thus enhance the discharge effect of suspended particles in water. In addition, the pumping depth of the flapping hydrofoil is too deep for the movement to be disturbed by the bottom surface, while the thrust generated by the flapping hydrofoil is weakened if the depth is too shallow. When the pump water depth is 1.1 H, the reversed Kármán vortex street is more stable under the balancing effect of the bottom surface and gravity, and the rate curve of the flapping hydrofoil acting on the discharge of suspended particles is better. From our comprehensive consideration of the joint effect of the pumping depth and pumping frequency, we recommend the use of a 1.1 H of pumping depth and 2.0 Hz pumping frequency in combination to achieve the best effect of discharging suspended particles. This study provides valuable insights into the actual engineering applications of flapping hydrofoil devices for improving water quality and ecological sustainability in raceway aquaculture.

Improved boosting and self-attention RBF networks for COD prediction based on UV-vis.

Chemical Oxygen Demand (COD) is crucial for assessing water quality. Compared to traditional chemical detection methods, UV-vis spectroscopy for measuring COD offers advantages such as speed, reduced consumption of materials, and no secondary pollution. Considering the impact of suspended particles in water, this paper proposes an optimized boosting model based on a combination strategy for turbidity compensation, using absorption spectra obtained from reservoir water samples via UV-vis. A self-attention mechanism is introduced into the radial basis function (RBF) network, resulting in a COD detection model based on the saRBF framework. This model facilitates comprehensive optimization of the entire process, from turbidity compensation of the original absorption spectrum to the subsequent COD prediction. Experimental results show that the proposed COD measurement model achieves a coefficient of determination of 0.9267, a root mean square error of 1.2669, and a mean absolute error of 1.0097, outperforming other COD measurement models. This work provides a new approach for turbidity compensation and COD detection research.

Enrichment of Water Bodies with Phenolic Compounds Released from Betula and Pinus Pollen in Surface Water.

Betula and Pinus pollen, which are dispersed in natural surface waters, release biologically active compounds into the water bodies. This study aims to evaluate variations in the distribution and composition of phenolic compounds in suspended particles in natural water bodies during pollen spreading. Samples taken from water bodies of different trophic levels were analyzed by microscopy, UV/VIS spectroscopy, HPTLC, and HPLC/DAD. The study revealed that the total phenolic content in water-suspended particles varied from 3.0 mg/g to 11.0 mg/g during Betula and Pinus pollen spreading. It was also observed that the surface water of dystrophic natural lakes had a higher content of phenolic compounds than the eutrophic, hypereutrophic, and mesotrophic water bodies. Chlorogenic, trans-ferulic, vanillin, and 3,4-dihydroxybenzoic acids were frequently detected in the surface water samples. Experimental measurements have shown variations in the release of phenolic compounds from Betula pollen into water (p < 0.05). After the exhibition of pollen, the distilled water predominantly contained bioactive chlorogenic acid. Further in situ investigations are necessary to gain a more comprehensive understanding of the function of phenolic compounds in aquatic ecosystems. The exploration of the release of bioactive compounds from pollen could provide valuable insights into the potential nutritional value of pollen as a nutrient source for aquaculture.

Study on Motion Mechanism of Suspended Particles in Water Under Ultrasound

Particles in the ultrasonic field by the influence of acoustic radiation force, its motion characteristics will be changed. Based on the simplified ultrasonic cleaning assumption, numerical simulation is used to construct a simulation model of suspended particles in the ultrasonic field in liquid water environment, and to study the law of ultrasonic waves on the motion characteristics of suspended particles in water. The research results show that the ultrasonic arrangement of the array makes the ultrasonic waves produce ultrasonic focusing on the propagation path. The alternating fluctuations of ultrasonic positive and negative sound pressure are in the horizontal line parallel to the bottom, and the vibration amplitude of suspended particles in the middle region is the largest. For the vertical position perpendicular to the bottom, the region with larger vibration amplitude of suspended particles is at 1/5 from the bottom. The particles in the high sound pressure area are pushed to the gathering area, and the particle vibration amplitude in the low sound pressure area is small, which proves that the gathering area of the particles is often the low sound pressure area. The research results will contribute to the study of particle motion in the ultrasonic field.

Using satellite multi-angle polarization measurements to characterize atmospheric aerosol above Bohai Bay

The paper analyzes data from the PARASOL optical multi-angle polarization radiometer over the waters of Bohai Bay under various atmospheric conditions and different seawater optical types. The study considered cases of clear atmosphere, haze, dust aerosol, and cloud coverage. The waters of Bohai Bay were categorized into areas heavily influenced by river inflows and relatively clear waters. By utilizing PARASOL data, the degree of polarization (DoP) values of optical radiation at scattering angles of about 90° between incident solar radiation and recorded radiation were determined. Appropriate scatterplots were created using measurements from the 490, 670, and 865 nm bands. Polarimetric pseudo-color maps were presented to classify various atmospheric states. The scatterplots successfully identified atmospheric dust, dust in clouds, haze, and water areas with high levels of suspended particles. The results obtained are consistent with the experience of using the Umov effect to study dust aerosol, which consists in the negative correlation between the maximum polarization of radiation and geometric albedo. The presence of suspended particles in water led to decrease in correlation coefficients between analyzed DoP at different wavelengths within the investigated sea area. The strong influence of river inflows on Bohai Bay in polarimetric data was observed only under clean atmospheric conditions.

Finding an eco-friendly and effective flocculation method to remove algal blooms from water

Algal blooms are rapid growth of microscopic algae in the water that are harmful to the environment because they block sunlight from reaching plants under the surface, deplete the water of useful nutrients, and release carbon emissions. Flocculation is a method that is used to remove algae and it works by binding and agglomerating suspended particles in water to form large particles to assist in their settling. However, most flocculants are chemical flocculants and may harm water quality. Bio-flocculation based on natural flocculants has been studied in drinking water treatment plants (DWTPs) as an eco-friendly alternative technology to conventional flocculants for both turbidity and HABs removal. The total solids assay, sedimentation kinetics assay, and pH testing will be used to measure the effectiveness of flocculants and water quality. These assays were tested with three types of algae: Chlorella vulgaris, Spirulina, Scenedesmus obliquus, and five types of flocculants: Aluminium Sulfate, Copper Sulfate, Chitosan, Moringa oleifera, and Strychnos potatorum Linn. The data collected so far in the study show that the chemical flocculants and bio-flocculants have a similar effectivity at flocculating algae from the water. The findings suggest that there is no significant difference between the bio-flocculants and the chemical flocculant. and that all of the flocculants will be effective. pH testing results have shown that Chitosan, Moringa oleifera, and Strychnos potatorum Linn affect the water quality the least which makes them the more environmentally friendly flocculants.

Self-Supervised Pre-Training Joint Framework: Assisting Lightweight Detection Network for Underwater Object Detection

In the computer vision field, underwater object detection has been a challenging task. Due to the attenuation of light in a medium and the scattering of light by suspended particles in water, underwater optical images often face the problems of color distortion and target feature blurring, which greatly affect the detection accuracy of underwater object detection. Although deep learning-based algorithms have achieved state-of-the-art results in the field of object detection, most of them cannot be applied to practice because of the limited computing capacity of a low-power processor embedded in unmanned underwater vehicles. This paper proposes a lightweight underwater object detection network based on the YOLOX model called LUO-YOLOX. A novel weighted ghost-CSPDarknet and simplified PANet were used in LUO-YOLOX to reduce the parameters of the whole model. Moreover, aiming to solve the problems of color distortion and unclear features of targets in underwater images, this paper proposes an efficient self-supervised pre-training joint framework based on underwater auto-encoder transformation (UAET). After the end-to-end pre-training process with the self-supervised pre-training joint framework, the backbone of the object detection network can extract more essential and robust features from degradation images when retrained on underwater datasets. Numerous experiments on the URPC2021 and detecting underwater objects (DUO) datasets verify the performance of our proposed method. Our work can assist unmanned underwater vehicles to perform underwater object detection tasks more accurately.

Multimodal image and spectral feature learning for efficient analysis of water-suspended particles.

We have developed a method to combine morphological and chemical information for the accurate identification of different particle types using optical measurement techniques that require no sample preparation. A combined holographic imaging and Raman spectroscopy setup is used to gather data from six different types of marine particles suspended in a large volume of seawater. Unsupervised feature learning is performed on the images and the spectral data using convolutional and single-layer autoencoders. The learned features are combined, where we demonstrate that non-linear dimensional reduction of the combined multimodal features can achieve a high clustering macro F1 score of 0.88, compared to a maximum of 0.61 when only image or spectral features are used. The method can be applied to long-term monitoring of particles in the ocean without the need for sample collection. In addition, it can be applied to data from different types of sensor measurements without significant modifications.

Relationship Between Pigment Concentration and Dry Weight in Determining Microalgae Abundance in Artificial Water Samples

Microalgae are aquatic organisms that can function as bioindicators of surface water quality. The concentration of chlorophyll a can be measured to determine the level of microalgae abundance in a body of water. Measurement of the dry weight of microalgae biomass is another method that can be used to determine the abundance of microalgae in a body of water. Both methods have their advantages and disadvantages. In measuring chlorophyll concentration, the presence of other compounds besides chlorophyll which can absorb light spectrum at certain wavelengths (wavelengths of 665 nm, 645 nm, and 630 nm) causes the measured absorbance value to be greater than it should be. The level of turbidity due to the content of suspended particles in water is a problem in the dry weight measurement method. Determination of the dry weight of biomass based on the chlorophyll concentration approach is the subject of this study. The results of simple linear regression analysis showed that the concentration of chlorophyll a and the dry weight of microalgae biomass in treatment A had a fairly strong positive correlation (Ra = 0.870), the tendency of which was to follow the linear regression equation Y = 302.35x + 17.121. Determination of dry weight based on the chlorophyll concentration measurement approach can be applied to water samples with suspended solids content that tends to be constant and inert (does not produce substances that can react with organic solvents during the chlorophyll extraction process). In addition, based on the results of data processing it can be concluded that the effect of the content of other suspended particles in the water samples did not show a statistically significant effect.

Field prototype for rapid classification of suspended particles in water based on polarized light scattering and fluorescence measurement

Field prototype for rapid classification of suspended particles in water based on polarized light scattering and fluorescence measurement

Coagulation properties of magnetic magnesium hydroxide for removal of microplastics in the presence of kaolin and humic acid

ABSTRACT Microplastics (MPs) is one of the most concerned emerging pollutants in recent years. Its widespread distribution has been shown to have potentially adverse effects on human health and ecosystems. Therefore, in this study, magnetic magnesium hydroxide coagulant (MMHC) was prepared by adding Fe3O4 magnetic micron particles in the Mg(OH)2 generation process, and it was used with PAM, a polymer flocculant, to remove polyethylene microplastics (≤270 μm) from water by coagulation. The removal efficiency of microplastics by MMHC reached 87.1%, which was 14.7% higher than that of traditional magnesium hydroxide coagulant (MHC). However, the Zeta potential of MMHC was lower than that of MHC, only 17.3 mV. In addition, the surface morphology of MMHC showed bubble-like clusters. The effect of PAM adding time on the microplastic removal efficiency was investigated. The best adding time of non-ionic PAM was 15s before the slow mixing started. The removal efficiency of organic matter and suspended particles in water by MMHC was determined by turbidity, ultraviolet spectrophotometry and three-dimensional fluorescence. The maximum removal efficiency was 98.5% and 93.3%, respectively. With the increase of the concentration of humic acid and kaolin in water, the removal efficiency of microplastics was basically not affected. MMHC can be reused after recycle, but it was found that the electrical neutralization mechanism was affected due to the transformation of its Zeta potential, and the adsorption effect of humic acid and kaolin particles in water became worse, the removal efficiency of microplastics, turbidity and UV254 decreased to 20.2%, 17.5% and 30%, respectively.

Impact of anthropogenic activity on antibiotic behaviors in coastal waters

The overuse of antibiotics and the pollution of the ecological environment caused by their emissions had attracted widespread attention. There was little information on the detection and distribution characteristics of antibiotics in coastal environments with complex water-suspended particles interactions and significant salinity changes. In this study, the occurrence, source, and ecological risk of 26 antibiotics, as well as their response mechanisms to anthropogenic activities were studied. Water samples along a typical silty mud coastal area were collected. The total concentration of antibiotics in the coastal water ranged from 8.5 to 132 ng/L. Spatially, the total concentration showed a downward trend along the canal. The results of offshore samples showed that the highest concentrations occurred near the small estuaries and the northwestern sampling sites. This indicated that the small canals provided a large source of pollutants and the antibiotic distribution were also dominated by local hydrodynamic conditions. Based on the results of principal component analysis-multiple linear regression, the domestic sewage and livestock and poultry farming were identified as the predominant sources of antibiotics. The results of the ecological risk assessment showed that 56.8 % sampling sites were in low-risk. The effect of intensity of anthropogenic disturbance on the distribution of antibiotics was represented by the distance between the sampling site and the city center, and the distance value showed a significant negative correlation with the total concentration of antibiotics. However, different kinds of antibiotics showed different patterns: concentrations of tetracyclines and fluoroquinolones had no significant relationship with distance values; sulfonamides, lincosamides, and macrolides decreased with the intensity of anthropogenic disturbance. This study presented a method to quantify the effect of anthropogenic activities, thus provided a new insight of adjust measures to local conditions for the pollution prevention and ecological risk assessment of antibiotics in coastal areas.

Profile probing of suspended particles in water by Stokes vector polarimetry.

Suspended particles are the important components of natural water. In this paper, a method based on polarized light scattering is proposed for profile probing of the particulate components in water. The profile probing is achieved by a polarized light sheet illuminating the suspension and the Stokes vector imaging system at a 120° backscattering angle, receiving the scattered light of the particles in the scattering volume. Each Stokes vector image (SVI) includes hundreds of star-studded particles whose Stokes vectors are used to retrieve the numbers of each particulate component in water. Experiments of typical particles are conducted. The classifications of these particles powered by the convolutional neural network (CNN) are demonstrated. The particulate components in mixed samples are successfully recognized and quantitatively compared. Considering at least 10 SVIs every second, the concentrations of each particulate component in water are effectively evaluated. The concept of profile probing the particulate components in water is proved to be powerful, by which we can measure up to almost 8000 particles per second. These results encourage the development of in-situ tools with this concept for particle profiling in future field surveying.

Underwater Image Enhancement Using Improved CNN Based Defogging

Due to refraction, absorption, and scattering of light by suspended particles in water, underwater images are characterized by low contrast, blurred details, and color distortion. In this paper, a fusion algorithm to restore and enhance underwater images is proposed. It consists of a color restoration module, an end-to-end defogging module and a brightness equalization module. In the color restoration module, a color balance algorithm based on CIE Lab color model is proposed to alleviate the effect of color deviation in underwater images. In the end-to-end defogging module, one end is the input image and the other end is the output image. A CNN network is proposed to connect these two ends and to improve the contrast of the underwater images. In the CNN network, a sub-network is used to reduce the depth of the network that needs to be designed to obtain the same features. Several depth separable convolutions are used to reduce the amount of calculation parameters required during network training. The basic attention module is introduced to highlight some important areas in the image. In order to improve the defogging network’s ability to extract overall information, a cross-layer connection and pooling pyramid module are added. In the brightness equalization module, a contrast limited adaptive histogram equalization method is used to coordinate the overall brightness. The proposed fusion algorithm for underwater image restoration and enhancement is verified by experiments and comparison with previous deep learning models and traditional methods. Comparison results show that the color correction and detail enhancement by the proposed method are superior.

Underwater Image Enhancement Method Based on Feature Fusion Neural Network

Aiming at the problems of uneven illumination of underwater image caused by supplementary illumination in deep-sea and night waters, image noise, low contrast and color deviation caused by suspended particles in water, a new underwater image enhancement method under non-uniform illumination is proposed. The heterogeneous feature fusion module is designed to fuse different levels and different levels of features, so as to improve the overall perception ability of the network to detail information and semantic information. Secondly, a new feature attention mechanism is designed to improve the traditional channel attention mechanism, and the improved channel attention and pixel attention mechanism are added to the heterogeneous feature fusion process to strengthen the ability of the network to extract pixel features with different turbidity. Then, the dynamic feature enhancement module is designed to adaptively expand the receptive field to improve the adaptability of the network to the image distortion scene and the ability of model conversion, and strengthen the network’s learning of the region of interest. Finally, the color loss function is designed, and the absolute error loss and structural similarity loss are jointly minimized to correct the color deviation on the basis of maintaining the image texture. A multi-scale feature extraction module is designed to extract different levels of features at the beginning of the network, and the output results are obtained through the convolution layer with jump connection and the attention module. The experimental results on several data sets show that this method can have good results in processing synthetic underwater images and real underwater images, and can better restore the image color and texture details compared with the existing methods. It conforms to the characteristics of human vision, and the visual effect is better than the existing underwater image enhancement algorithms.

Designing wound filters for cleaner water using winding technology: Influence of leading and lagging wind

Wound filters are now an integral part of domestic water purification plants. They are used to achieve micro-filtration, and the extent to which they can remove the suspended particles in water is a function of various aspects of winding technology. It includes the wind type, winding mode, porosities of yarn/filter, and its end-use environment. Earlier works have reported the influence of coil angle on filter performance but not the influence of wind type. The present study aimed to produce wound filters at three different coil angles with leading/lagging winds and compare their filtration performances. Results showed that filters wound with the lowest coil angle (@ 20°) with leading wind and lower porosity developed a pressure drop of 5.57 psi with a nominal rating of 72 μm. Filters wound with the lagging wind, and higher porosity produced a pressure drop of 4.8 psi with a micron rating of 56 μm; for similar winding and yarn porosity conditions. A subsequent increase in coil angle resulted in lower pressure drop and more inadequate micron ratings. However, the filters wound with the leading wind always recorded a higher pressure drop for all coil angles. All wound filters’ porosity was different, as their surface area and yarn content affected their pressure drop and micron ratings.

The influence mechanism of the main suspended particles of Yellow River sand on the emitter clogging − An attempt to improve the irrigation water utilization efficiency in Yellow River basin

The existence of suspended particles in water poses a great challenge to the adaptability of drip irrigation technology. To explore the differences in emitter clogging caused by irrigation water containing various suspended solids, this research used irrigation water containing Yellow River sand, quartz sand, and sodium bentonite as the main suspended particles (designated HW, SW and BW, respectively) to conduct a short-period emitter anti-clogging test and particle settlement test in static water. The results showed that the type of suspended particles had a very significant impact on the relative flow rate (Dra) of the emitter (P < 0.01). Emitter clogging was the most serious in the HW treatment, followed by the SW treatment, and emitters in the BW treatment had the lowest clogging degree. The clogging substance formed in the HW treatment exhibited a compact and stable structure; that in the SW treatment was a loosely structured accumulation of large particles; and that in the BW treatment had a flocculent structure with strong plasticity that flowed easily with water. These three types of suspended particles experienced two stages of sedimentation: short rapid sedimentation followed by slow sedimentation. Grid clogging at the emitter’s water inlet caused emitter clogging. The total mass of sediment in laterals in the HW treatment was the largest, and the Dra was the smallest; the total mass of sediment in laterals in the BW treatment was the smallest, and the Dra was the largest. In the SW treatment, the values of these two indexes were between those in the HW and BW treatments. Single suspended particles, such as quartz sand (powder) or sodium bentonite (clay), had more difficulty forming stable clogging structures, so the Dra was relatively high. Coarse and fine particles were balanced in Yellow River sand; thus, the emitter was easily clogged, and the degree of clogging was the most serious. This study tried to provide a basis for the differences and formation mechanisms of emitter clogging and the anti-clogging strategies of emitters in drip irrigation systems in different reaches of the Yellow River.