296 results about "Water pollutants" patented technology

The invention discloses an intelligent monitoring and early warning system and method for agricultural non-point source pollution, and relates to the technical field of environmental monitoring, accurate prediction of water pollutant concentration is realized through multi-source heterogeneous data acquisition and fusion, a dynamic attention mechanism and a PINN-Transformer coupling model, the system extracts data spatial and temporal characteristics by using an optimized Transformer model, and the method is applied to the intelligent monitoring and early warning of agricultural non-point source pollution. A water pollution diffusion physical constraint is embedded, it is ensured that a prediction result conforms to an actual hydrodynamic law, and based on high-precision spatial-temporal distribution data, an intelligent algorithm is adopted to track a pollution diffusion path and rapidly lock a pollution source; meanwhile, the cellular automaton model simulates pollution risk dynamic diffusion and assists regional risk assessment, the system also combines a block chain technology to carry out credible evidence storage on key monitoring data, and real-time data processing and early warning pushing are realized through a cloud edge collaborative architecture. And an efficient and reliable technical solution is provided for agricultural water environment management and pollution prevention and control.

The invention relates to the technical field of water quality detection, and discloses a water quality pollutant detection method, system and equipment based on spectral analysis, and the method comprises the following steps: carrying out real-time spectral data acquisition on a water body sample in a vehicle driving process through a multispectral sensor array in a vehicle-mounted water quality detection device; obtaining a water body spectrum three-dimensional data cube; carrying out anti-vibration wavelength calibration and ambient light source interference elimination processing to obtain a preprocessed spectrum data set; performing standard multivariate decomposition processing and horizontal local constraint optimization of a pollutant target wave band on the preprocessed spectrum data set to obtain enhanced feature fingerprint spectrums for different types of water quality pollutants; and inputting the enhanced feature fingerprint spectrum into a deep belief network model to perform pollutant feature matching analysis to obtain various pollutant types and corresponding concentration values in the water body sample, thereby effectively eliminating ambient light changes and other background interferences, not only determining the pollutant types, but also accurately quantifying the concentration values.

The invention provides an underground water pollutant concentration prediction method and system based on machine learning, and relates to the technical field of underground water pollutant concentration prediction.The method comprises the steps that historical data, hydrogeological parameters, meteorological data, human activity data and geochemical parameters of underground water pollutant concentration of a target area are preprocessed; dividing a training set, a verification set and a test set; constructing a preset resolution feature set based on a geochemical mechanism; selecting an adaptive machine learning model according to data characteristics and coupling a physical mechanism; performing hyper-parameter tuning by adopting Bayesian optimization, and supplementing small sample data in combination with transfer learning to complete model training; predicting the underground water pollutant concentration of the target area by using the trained model, and outputting a pollutant concentration prediction result with an uncertainty interval; the invention provides a technical scheme for predicting the concentration of underground water pollutants, which is efficient, accurate and high in adaptability.

The invention relates to the technical field of water quality detection, and discloses a water quality detection method and device based on an electrochemical sensor. The method comprises the following steps: deploying a multi-depth electrochemical sensor array in a target water body according to different water depth positions and carrying out real-time monitoring to obtain electrochemical response signal data; performing electrochemical fingerprint feature recognition on the electrochemical response signal data to obtain electrochemical feature vectors of water sample pollutants at different water depth positions; carrying out pollutant analysis through a hierarchical electrochemical transfer-attention network model to obtain types and concentrations of heavy metal ions and organic pollutants in water samples at different water depth positions; and executing Kriging space interpolation and environmental factor correction to generate a three-dimensional pollutant distribution dynamic map of the target water body. According to the method, high-precision identification of low-concentration multi-component coexisting pollutants is realized, and visual analysis of spatial distribution characteristics and migration rules of water pollutants is realized.

The invention provides a method for rapidly detecting wastewater pollutants by atomic fluorescence spectrometry, and belongs to the technical field of wastewater treatment.The method comprises the steps that atomic fluorescence spectrum data of a wastewater sample are collected to establish a spectrum interference matrix to characterize the spectral line overlapping condition between elements; abnormal values are recognized through statistical analysis, a spectrum outlier matrix is built, abnormal fluorescence intensity distribution is recorded, sample matrix non-characteristic fluorescence signals are measured, a background fluorescence interference matrix is built, background interference intensity is quantized, system signal change rules are continuously monitored and detected, and a signal drift tendency matrix is built to predict the signal drift tendency. A spectrum interference matrix and a background fluorescence interference matrix are processed through a spectrum analytic function, compensation factors are calculated, spectrum overlapping and background interference influences are corrected, system drift is corrected in real time, and a final wastewater pollutant concentration detection result is output, so that the technical problem of unstable detection precision caused by coupling of multiple interference factors is solved.

The invention relates to an electric flocculation reactor and an electric flocculation treatment method. The electric flocculation reactor is provided with a biochemical treatment unit and a pretreatment unit located in the front of the biochemical treatment unit, and an electrode assembly with adjustable electrode spacing is arranged in the pretreatment unit. According to the electric flocculation treatment method, the electric flocculation reactor is adopted for removing pollutants in water, the distance between electrode plates in the electrode assembly is set or adjusted according to the water flow of inlet water or the pollutant flow, the biochemical treatment unit comprises an aerobic tank, the electrode assembly is arranged in the aerobic tank, iron ions are released through the electrode assembly, and the water quality is improved. And an iron ion environment beneficial to growth and metabolism of aerobic microorganisms is formed. According to the invention, the electrode spacing of the electric flocculation reaction can be adjusted, and the electric flocculation reaction device can better adapt to actual requirements.

The invention provides a sewage treatment multi-objective optimization method and device and a storage medium, and relates to the field of sewage data analysis and processing.The method comprises the steps that firstly, multiple types of sewage data are collected in a time sequence mode at a specified sewage data station and preprocessed to form a data set, then a sewage prediction model is constructed based on a deep learning model, and a sewage prediction result is obtained; and inputting the data set for training, and predicting the energy consumption of the sewage treatment equipment and the effluent pollutant concentration. Then, a multi-objective optimization function is constructed, so that the total energy consumption is minimized, and the effluent pollutant concentration reaches the standard; and finally, solving the function by using a multi-objective particle swarm optimization algorithm to obtain an optimal solution set, and screening out an optimal operation parameter from the optimal solution set. According to the method, two important targets of energy consumption minimization and effluent pollutant concentration standard reaching can be considered at the same time, the relation between energy consumption and water quality can be balanced, the optimal operation parameters are screened out from the optimal solution set, and the overall performance of sewage treatment equipment is improved.

The invention discloses a high-valued graded utilization method of marine shells, and belongs to the technical field of comprehensive utilization of biological resources and preparation of functional materials. The method comprises the following steps: cleaning, air-drying and superfine grinding marine shell wastes such as abalone shells, and extracting water-soluble organic components in the marine shell wastes by adopting mild water extraction, so that the obtained extract is rich in protein, polysaccharide or small molecule peptide, has good biological activity, and can be used for preparing functional materials such as biomimetic mineralization, tissue repair and the like; extracted shell powder residues are subjected to heat treatment or chemical activation treatment and then compounded with natural polymer materials such as chitosan and sodium alginate, and the composite adsorbent which is loose in structure and large in specific surface area is prepared and can be used for removing dye, heavy metal, antibiotics and other water pollutants. According to the invention, separate utilization of organic components and inorganic framework materials in the marine shells is realized, and the method has the characteristics of environmental protection, efficient resource conversion and multifunctional application, and has a good industrial popularization prospect.

The invention relates to the technical field of water pollutant concentration detection, and discloses a water pollutant concentration detection system and method based on big data analysis, and the water pollutant concentration detection method based on big data analysis comprises the following steps: constructing a multi-level sensing network, the multi-layer sensing network comprises a fixed monitoring station layer, a water surface unmanned ship layer and an underwater robot layer; carrying out multi-modal data fusion by utilizing a knowledge constraint data assimilation algorithm to generate consistent water quality parameter estimation; a double-layer cognitive structure combining a knowledge graph and a causal model is constructed, and water pollutant propagation understanding and tracing are achieved; continuous optimization of system configuration is realized through a multi-objective reinforcement learning framework; through collaborative optimization of a multi-layer sensing network, the system realizes three-dimensional monitoring of a water body, the monitoring coverage range is expanded, and meanwhile, the high-precision detection capability is kept.

The invention belongs to the technical field of water pollutant identification, and particularly relates to a water pollutant distinguishing method and system based on multi-source spectrum fusion. According to the method, ultraviolet visible spectrum data and three-dimensional fluorescence spectrum data are effectively integrated in a multi-source spectrum data fusion mode, so that the characteristic information of water pollutants is captured, stably appearing characteristic absorption wavebands can be positioned by utilizing the ultraviolet visible spectrum data, and the water pollutants can be accurately detected. The method comprises the following steps: identifying a characteristic sub-region capable of representing the fluorescence response characteristic of a pollutant through three-dimensional fluorescence spectrum data, in a characteristic extraction stage, performing first-order derivative operation on an ultraviolet visible spectrum to position an absorption peak position, calculating curvature distribution of a three-dimensional fluorescence spectrum to identify the characteristic sub-region, and when a fusion characteristic is generated, performing first-order derivative operation on the three-dimensional fluorescence spectrum to identify the characteristic sub-region; according to the method, the key operation parameters are subjected to grid search optimization, and the optimal key operation parameter combination is screened out by performing multiple rounds of iterative training and evaluation on a preset training set and a verification set, so that the recognition performance of the real-time collected water sample is improved.

The invention provides a rapid detection method for water pollutants, which comprises the following steps: removing large-particle impurities and suspended solids in a water sample to be detected to obtain a target water sample; the method comprises the following steps: synchronously detecting multiple pollutant indexes of a target water sample through a multi-source sensor array to generate an initial detection data set; performing noise filtering and baseline correction on the initial detection data set to generate a target detection data set; performing space-time dimension dynamic fusion and feature decoupling on the target detection data set to generate water quality pollutant data and dynamic risk assessment indexes; and constructing a multi-dimensional risk assessment report by adopting the water quality pollutant data and the dynamic risk assessment indexes. By adopting a dynamic gradient filtering technology, impurity interference is effectively removed, dynamic risk assessment of a time dimension is realized, the accuracy and reliability of detection in a complex water quality environment are remarkably improved, and rapid and accurate water quality pollutant detection and risk assessment are realized.

The invention relates to the technical field of water pollutant removal, in particular to a UiO-66 / sodium carboxymethyl cellulose / polyvinyl alcohol / melamine sponge composite material and a preparation method and application thereof.The preparation method comprises the steps that zirconium chloride and terephthalic acid are dissolved in an organic solvent to obtain a mixed solution, the mixed solution is transferred into a reaction kettle, and through solvothermal reaction, the UiO-66 / sodium carboxymethyl cellulose / polyvinyl alcohol / melamine sponge composite material is obtained; the preparation method comprises the following steps: preparing UiO-66 powder; putting UiO-66 powder into the sodium carboxymethyl cellulose solution, and uniformly stirring the UiO-66 powder and the sodium carboxymethyl cellulose solution to obtain a UiO-66 / CMC mixed solution; placing the UiO-66 / CMC mixed solution in a polyvinyl alcohol solution, and uniformly stirring the UiO-66 / CMC / PVA mixed solution to obtain a UiO-66 / CMC / PVA mixed solution; the preparation method comprises the following steps: dipping a melamine sponge in a UiO-66 / CMC / PVA mixed solution to obtain an adsorption saturated melamine sponge; the UiO-66 / CMC / PVA / coated MS composite material is obtained by repeatedly freezing and thawing the adsorption saturated melamine sponge for multiple times and then freeze-drying, the composite material can be used for rapidly, efficiently and selectively removing phosphate or fluorine ions and the like in water and is convenient to separate and recycle, and a new thought is provided for development of efficient water treatment adsorbent materials.

The invention relates to the technical field of pollution treatment of livestock and poultry breeding, in particular to a pollutant emission prediction and management system for a livestock and poultry farm, which comprises a data acquisition and storage unit, a data processing unit, a data processing unit and a data processing unit, and is characterized in that the data acquisition and storage unit is used for acquiring multi-source data of the farm in real time; the influence factor calculation unit obtains key influence factors influencing water quality change and malodorous gas based on production data and facility operation data of the farm; the model prediction analysis unit generates a predicted value of pollutant emission by using a dynamic multi-dimensional pollutant emission prediction model, and key influence factors are introduced in the prediction process for correction; and the management decision-making unit judges the early warning level and generates a control instruction according to the early warning level. According to the system, accurate prediction of emission of malodorous gas and water pollutants is realized by constructing a dynamic multi-dimensional pollutant emission prediction model, and meanwhile, the system not only prevents excessive emission of pollutants in advance, but also is deeply integrated with aquaculture production management to guide actual aquaculture operation.

The invention discloses a pollution risk assessment method, a pollution risk assessment device, pollution risk assessment equipment and a computer readable storage medium for an underground water environment, and the method can accurately simulate the migration and diffusion of pollutants in underground water through a constructed underground water pollutant migration model. And calculating exposure by combining sensitive receptor distribution, calculating risk indexes and probabilities according to toxicological parameters, and finally determining risk levels. Through application of the series of models, the accuracy and scientificity of risk assessment are greatly improved, a reliable basis is provided for groundwater pollution prevention, control and treatment, and potential environmental risks are effectively reduced.

The invention discloses a method for preparing a porous carbon material by recycling coal gasification slag and semi-coke wastewater, which comprises the following steps: by taking coal gasification fine slag as a carrier and semi-coke wastewater as a phenol source, carrying out flotation-acid leaching modification on the fine slag to purify a carbon-rich component and optimize the surface adsorption activity of the carbon-rich component; then fully adsorbing phenolic substances in the wastewater by utilizing the modified slag body; introducing a composite aldehyde cross-linking agent, and initiating an in-situ phenolic aldehyde polymerization reaction to generate a composite precursor; the precursor is subjected to high-temperature carbonization and alkali activation pore forming, and finally the porous carbon material with the characteristics of high specific surface area, rich graded pores and low ash content is prepared. According to the process, full-amount collaborative recycling of the two wastes is achieved, and the process is green and free of secondary pollution. The obtained material is high in carbon content and rich in defect structure and surface functional groups, shows excellent adsorption capacity and catalytic carrier performance, can be widely applied to the fields of deep purification of water pollutants, adsorption of volatile organic compounds, energy catalysis and the like, and has remarkable environmental protection benefits and resource economic values.

The invention discloses a water pollutant adsorbent. The water pollutant adsorbent is characterized by comprising a chelate prepared by reacting manganese dioxide with an EDTA-2Na (Ethylene Diamine Tetraacetic Acid-2Na) solution. The invention also discloses a preparation method and a production system of the water pollutant adsorbent. The preparation method of the water pollutant adsorbent comprises the following steps: 1, crushing and grinding electrolytic manganese anode mud; 2, removing impurities in the electrolytic manganese anode slime to obtain filter residues; 3, cleaning the filter residues, and carrying out solid-liquid separation to obtain an intermediate product; and 4, chelating modification. The water pollutant adsorbent production system comprises a reaction kettle. According to the technical scheme, the manganese dioxide raw material can be effectively utilized to prepare the pollutant adsorption and treatment material, and high-valued treatment of the electrolytic manganese anode mud solid waste is effectively achieved.

The invention relates to the technical field of water body pollution monitoring, in particular to a multispectral image fused water body pollutant accurate recognition system, which comprises a data acquisition module, a cloud processing module, a boundary processing module, a pollution recognition module, a diffusion prediction module and a visualization module, the system constructs sub-pixel representation of a water pollutant boundary by using a differential geometry manifold theory, and realizes high-precision pollutant boundary description through a multi-scale analysis and curvature flow optimization technology; enhancing pollutant characteristic expression by adopting multispectral image fusion and an optimal wave band selection technology; using a support vector machine model to accurately identify various pollutant types such as oil films, oil spots, algae blooms and the like; based on a boundary fine description result and a pollutant type identification result, the diffusion trend of pollutants is accurately predicted in combination with historical flow, wind direction and wind speed data, and the system improves the water pollutant boundary identification precision and enhances the identification capability of complex boundary forms and low-contrast regions.

The invention discloses a pre-training model and multi-source coding feature fusion-based water pollutant molecular property prediction method and system, and relates to the technical field of environmental science and artificial intelligence crossing. Comprising the steps of collecting pollutant data; the collected pollutant data is preprocessed; taking SMILES as a molecular input basis, and extracting molecular features; according to the molecular features, feature vectors are obtained from an encoder and then input to a vector interaction module for feature fusion; and embedding the comprehensive molecules obtained after feature fusion into an expert mixed structure module to obtain comprehensive representation of an expert mechanism, inputting the comprehensive representation of the expert mechanism into a preset prediction head, and completing prediction of molecular properties through the prediction head. According to the method, the molecular language model features, the molecular graph neural network features and the molecular descriptor features are integrated, and feature fusion is carried out by utilizing an attention mechanism and residual connection, so that high-precision prediction of the molecular properties of pollutants is realized.

The invention relates to a water pollutant collection technology, and aims to provide a device for filtering and screening micro-plastics in a water body in a multi-stage manner. Comprising an inlet water pre-separation unit, a multi-stage filtering and screening unit, an automatic membrane changing unit and a control unit, the multi-stage filtering and screening unit comprises a plurality of filtering and screening assemblies which are connected in sequence and are of the same structure, an elastic corrugated pipe and a second water suction pump. The automatic film changing unit comprises a plurality of film changing assemblies which are the same in structure and are sequentially connected through a central rotating shaft, and a second stepping motor is arranged at the tail end of the central rotating shaft; and the membrane exchange assemblies and the filtering and screening assemblies are arranged in a one-to-one correspondence manner. According to the invention, the functions of automatic film changing control, multi-stage screening and self-cleaning are integrated, and the problem of filter screen blockage can be effectively solved; while the collection efficiency is improved, precise separation and continuous treatment of micro-plastics with different particle sizes are realized; through the control unit, mutual cooperation of the rotary membrane replacing assembly and the telescopic filtering and screening assembly is achieved, and automatic replacement of the filter membrane assembly is achieved.

A water pollutant detection method based on absorption-electrochemical characteristic fusion belongs to the technical field of environmental monitoring, and comprises the following steps: respectively acquiring absorption spectrum data and current-potential data through a spectrometer and an electrochemical workstation, highlighting key peak position characteristics by using an attention mechanism, and inhibiting redundancy and noise interference; extracting local and global features of the two types of signals by using a convolutional neural network, and splicing the local and global features to obtain joint representation; and cross-modal feature fusion is realized through a dynamic routing mechanism of the capsule network, and a spatial relationship and a hierarchical structure between features are captured. And finally, constructing a classification and regression double-branch output structure to realize pollutant type identification and concentration prediction. Compared with an existing single detection technology, the detection sensitivity of the low-concentration pollutants can be remarkably improved, the distinguishing problem of peak value overlapping is effectively solved, the selectivity and robustness of the system are enhanced, and therefore high-precision integrated detection of the water pollutants is achieved.

The present invention discloses a magnetic yak hair-based biomass activated carbon, as well as its preparation method and application. The magnetic yak hair-based activated carbon is prepared by a two-step process of mixing Fenton iron mud with yak hair activated carbon, based on the carbonization and activation of yak hair. The activated carbon has a maximum specific surface area of ​​2632 m² / g and can be separated from a solution using magnetism. It can be used for the efficient adsorption of water pollutants such as organic dyes and antibiotics.

The invention provides a compound microbial agent and application thereof in regulating aquaculture water quality, and the compound microbial agent is prepared by the following steps: firstly, embedding a bacterial liquid composed of alcaligenes faecalis, pseudomonas, ochrobactrum and sphingosine box bacteria through self-assembly by adopting gallic acyl quinic acid, and then modifying lignin by using ferrocene for composite loading. And immersing into a bacterial liquid consisting of photosynthetic bacteria, bacillus and nitrifying bacteria, and drying. According to the invention, ferrocene modified lignin and galloylquinic acid construct a multi-layer load structure to fix microorganisms in a layered manner, so that the microorganisms can stably survive in a complex water body environment, and meanwhile, a plurality of florae act synergistically to degrade organic matters, nitrogen, phosphorus, antibiotics and the like in aquaculture water, so that the degradation efficiency of water pollutants can be remarkably improved; effective adjustment of aquaculture water quality is facilitated, and good data support and theoretical basis are provided for water body improvement in the field of aquatic products.

The invention relates to the field of underground water in-situ remediation, and discloses an underground water circulation well primary battery remediation device and method based on a biochar electrode, and the device comprises a circulation well body which comprises a first screen section and a second screen section; the water pumping and injecting part is used for pumping the polluted underground water into the second screen section from the first screen section and recharging the polluted underground water into the aquifer from the second screen section after treatment to form an underground water circulating flow field; the primary battery assembly comprises a liquid storage part, a cathode assembly, an anode assembly and a proton exchange membrane, is arranged on the second screen section and is used for degrading pollutants in underground water. An oxidizing agent is injected into the liquid storage part and reacts with underground water pollutants collected in the second screen section, electrons are transmitted through the cathode assembly and the anode assembly, the oxidizing agent is prevented from making direct contact with the pollutants, and pollutant degradation and removal are achieved; in the whole process, the generation of high-toxicity intermediate products and the toxic action on primary microorganisms can be reduced, so that the secondary pollution risk of the underground water environment is reduced, and the purpose of green low-carbon remediation is achieved.

The utility model provides a sewage pollutant treatment device. The sewage pollutant treatment device comprises an anode chamber, a cathode chamber, a cation exchange membrane, an aeration structure and a data acquisition system, the anode chamber contains electrogenesis bacteria liquid containing electrogenesis bacteria; an anode carbon rod is inserted into the anode chamber and is filled with an anode graphite carbon felt; a cathode carbon rod is inserted into the cathode chamber, and a cathode graphite carbon felt is arranged on the cathode carbon rod; the cation exchange membrane is arranged between the anode chamber and the cathode chamber, and the cation exchange membrane is a proton exchange membrane; the conventional pollutants in the sewage are decomposed by utilizing electrogenesis bacteria in an anode solution in the anode chamber, chemical energy is converted into electric energy, and electrons and protons are generated; electrons reach the cathode through an external circuit, and protons are transmitted to the cathode chamber through the cation exchange membrane; the aeration structure is communicated with the cathode chamber, oxygen dissolved in the cathode chamber is combined with electrons and protons to generate H2O2, then the H2O2 and Fe < 2 + > are subjected to a Fenton reaction to generate hydroxyl radical.OH, and the hydroxyl radical.OH mineralizes novel pollutants in a cathode solution.

The invention provides a navigation mark monitoring data processing method and a navigation mark monitoring data processing system for ship water pollutant discharge, which are applied to the technical field of sewage discharge, and are used for obtaining readings of various types of water quality sensors on navigation marks in real time and calculating the change rate of the readings in a preset monitoring time period. And intelligent judgment is carried out according to a combination mode of reading change rates of different sensors. The method can intelligently distinguish the fault of the sensor from the actual water pollution, and significantly improves the accuracy of the monitoring data and the reliability of pollution event identification, thereby avoiding the wrong attribution of the pollution responsibility, and providing a more accurate and more reliable monitoring means for the water environment protection.

The invention provides a treatment device and a treatment method for formaldehyde-containing wastewater. The treatment device comprises an adjusting unit, a degradation pretreatment unit and an anaerobic membrane biological reaction unit, the anaerobic membrane biological reaction unit comprises an anaerobic digestion sludge reaction zone, a membrane separation zone and a reconnection piece, the anaerobic digestion sludge reaction zone is communicated with the membrane separation zone, one end of the reconnection piece is communicated with the membrane separation zone, and the other end of the reconnection piece is communicated with the anaerobic digestion sludge reaction zone. The method can effectively remove formaldehyde, COD and other pollutants in the polyformaldehyde wastewater, effectively resists to-be-treated wastewater pollutant concentration fluctuation and violent water quantity and water quality impact, and has the advantages of low sludge yield, stable treatment and up-to-standard effluent quality.

The invention discloses a training system and method of a semi-supervised machine learning model for water pollutant detection, and relates to the field of environment detection. The problem that an existing semi-supervised machine learning model is insufficient in universality is solved. The system comprises a water body sampling module used for collecting a water body sample of a monitoring area; the pollutant adding module is used for adding pollutants to the water body sample according to randomly obtained pollutant types and concentration settings of different combinations to obtain the water body sample, and sending the water body sample to the data sampling module; the data sampling module is used for collecting physicochemical properties of the water body samples of the water body sampling module and the pollutant adding module through a sensor; and the data analysis module is used for inputting the physicochemical property data of the water body sample acquired by the water body sampling module into a semi-supervised machine learning model, and constructing and training the semi-supervised machine learning model by taking the physicochemical property data as input. The method is also suitable for the field of real-time training and detection of water pollutants.

Contaminants in a liquid are removed using bubbles containing ozone and / or other gas in a method having steps that include multistage shearing and venturi injection to increase dissolution of gases into the liquid, and the generation of bubbles introduced to the liquid by one or more of cavitation, vortex management, shear degradation, and ultrasonics. The liquid may be water, the contaminants are at least one of organic and inorganic contaminants, and the bubbles preferably have a diameter of 125 nanometers a density ratio of about 2.5 * 108 bubbles / cm3. A system that may be used for this method includes one or more pumps; optionally one or more settling tanks; optionally one or more dosing stations; an injector to introduce a gas to the fluid; an Ultrafine bubble (UFB) generator to produce UFB's; optionally one or more sensors; optionally a safety system; and optionally a controller.

The invention discloses high-flux filter paper for water filtration and a preparation method thereof. The method comprises the following steps: by taking natural silkworm cocoons as a silk fibroin fiber raw material, preparing silk fibroin fibers through a synergistic effect of solvent dissolution and mechanical stripping; the silk fibroin fibers and the polyester long and short fibers form an interwoven network structure through a physical entanglement and electrostatic assembly technology; the silk fibroin fiber / polyester long fiber / polyester short fiber high-flux water filtering filter paper is prepared from polyester long and short fibers serving as a filtering framework and silk fibroin fibers through a wet papermaking process. The silk fibroin fiber / polyester long fiber / polyester short fiber high-flux water filtration filter paper obtained by the invention has high flux and high toughness through bionic cobweb multistage structural design, effectively filters water pollutants such as fine particulate matters and micro-nano plastic particulate matters, and is suitable for high-precision filtration in severe environments such as a cooling water system and radioactive wastewater treatment.

The application discloses a kind of ZnO-MoO3 material of loading oxygen vacancy and its preparation method and the application of activated high ferrate degradation water pollutants, the preparation method of ZnO-MoO3 material of loading oxygen vacancy is as follows: the mass ratio 10:1~80:1 of ZnO and MoO3 is weighed, first using oscillator initial mixing, then be placed in ball mill jar, again put into ball mill and carry out ball milling to depth mixing, again the mixed powder is placed in tube furnace and calcined under inert atmosphere, calcination temperature is 300~900 DEG C, calcination time is 2~10 hours, collect sample after calcination, after cooling to room temperature, the ZnO-MoO3 material of loading oxygen vacancy is prepared.The application uses ZnO-MoO3 material of loading oxygen vacancy and activates high ferrate (Fe (VI)) to strengthen degradation typical drug pollutants, and the material significantly improves the degradation ability of high ferrate to drug pollutants, widens the application scene of high ferrate and realizes the effective removal of water drug pollutants.