2615 results about "Ammoniacal nitrogen" patented technology

The invention relates to the technical field of process control, in particular to an intelligent environment monitoring and adjusting system for lip fish culture, which comprises an environment parameter monitoring module, a multivariable linkage calculation module, a self-adaptive adjusting module, a fuzzy logic control module and an abnormity emergency response module. According to the method, the trend value is formed through time-phased grouping analysis and relevance calculation of the water quality parameters, dynamic prediction of the breeding environment change is achieved, the cooperative adjustment capacity among the dissolved oxygen, the water temperature and the ammonia nitrogen concentration is optimized through analysis of the multi-parameter linkage relation, the accuracy of environment control is improved, and the method is suitable for large-scale popularization and application. The cooperation efficiency of oxygen pump frequency and temperature control equipment response is improved through real-time matching calculation of equipment operation parameters, the rapid adaptive capacity to water quality changes is enhanced, abnormal fluctuation monitoring is combined with equipment linkage adjustment, rapid response during water quality sudden change is ensured, and the adverse effect of environment fluctuation on fish growth is reduced.

The invention provides a sewage treatment aeration control system and method based on multi-parameter collaborative optimization. The method comprises the following steps: acquiring multi-sensor data of COD (Chemical Oxygen Demand), BOD5 (Biochemical Oxygen Demand), DO (Dissolved Oxygen Demand), ammonia nitrogen, ORP (Oxidation Reduction Potential), pH (Potential of Hydrogen), water inlet flow and sludge concentration of wastewater in an aeration tank by utilizing a multi-parameter sensor module; according to the dynamic correction oxygen mass transfer coefficient and the feedforward parameter, establishing a relationship between the water inlet load and aeration; calculating the air volume of an air blower and the fine adjustment value of the opening degree of a butterfly valve through a PID control algorithm and feedback parameters, and correcting the aeration quantity to obtain a total air volume target value; and adjusting the opening degree and the rotating speed of a guide vane of the air blower according to the self-adaptive PID control parameters and the corrected total air volume target value by utilizing a self-adaptive PID controller, and adjusting the opening degree of a butterfly valve according to a gradient butterfly valve adjusting strategy. The output of the air blower is optimized by adopting self-adaptive PID, and the opening degree of the butterfly valve of each biological tank is dynamically adjusted through a gradient valve adjusting strategy, so that the accurate control of the aeration rate is realized; the sewage treatment effect is ensured.

The invention discloses an integrated water quality monitoring and processing system for aquaculture, and the system comprises a data collection module which is used for obtaining dissolved oxygen, ammonia nitrogen, pH value, temperature and flow data from a plurality of spatial distributed sensing nodes; the data preprocessing module is used for completing noise removal, correction and time sequence synchronization; the water quality state estimation module is used for outputting real-time multi-point water quality states based on a distributed unscented Kalman filtering algorithm; the space-time fluid modeling module is used for constructing a Lagrange model to extract a flow velocity field and a diffusion coefficient; the scheduling optimization module is used for generating an aeration and dosing scheme by adopting an improved multi-target Pareto optimization algorithm based on a space-time sensitive boundary; the execution module is used for controlling an air blower, an aeration pipe and a dosing pump to complete oxygenation and dosing operations; and the self-adaptive updating module is used for collecting feedback data to adjust filtering gain and optimizing parameters so as to realize closed-loop control of the system.

The invention relates to the technical field of environment assessment, in particular to a coastal zone culture area multi-dimensional environment assessment method and a cloud platform. The method comprises the following steps: continuously recording dissolved oxygen concentration, pH value, centigrade temperature, salinity unit, turbidity scattering unit, chlorophyll fluorescence intensity, ammonia nitrogen milligram per liter and nitrite milligram per liter, synchronously calling multi-source remote sensing images covering a culture area and an adjacent water area, extracting remote sensing reflectivity data through image correction and atmospheric correction, and calculating to obtain water color parameters. According to the method, the water quality sensor array is deployed at the key point of the culture area, continuous multi-parameter environmental data acquisition is carried out, multi-source remote sensing images are synchronously integrated, water color information is extracted in real time, and the timeliness and data accuracy of culture water area environmental monitoring are improved; trend decomposition and dynamic baseline construction are carried out based on the data sequence, so that the environmental fluctuation evaluation of the breeding area is more objective and accurate.

The invention discloses low-temperature-resistant and high-salt-resistant aerobic pseudomonas kirschner kirschner K2 as well as a preparation method and application thereof. The preparation method comprises the following steps: carrying out low-temperature and high-salt enrichment culture; screening and domesticating, and monitoring the concentration of ammonia nitrogen; and after 3-5 times of enrichment culture, diluting the enrichment culture, further culturing until a macroscopic bacterial colony is obtained, and then picking and carrying out plate streaking to separate a pure strain. The invention also relates to application of the strain in preparation or prevention of nitrification and denitrification nitrogen removal drugs in treatment of high-salt nitrogen-containing wastewater. The strain is low-temperature-resistant and high-salt-resistant heterotrophic-aerobic denitrifying bacteria, has the characteristic of low temperature resistance, grows well at low temperature and high salt salinity, has higher heterotrophic nitrification-aerobic denitrification nitrogen removal capacity, is suitable for nitrogen removal treatment of high-salt wastewater such as food processing wastewater and landfill leachate, and has wide application prospects. The superiority is particularly obvious under a low-temperature condition.

The invention relates to the technical field of water environment treatment, in particular to a water environment ecological treatment method and system based on a constructed wetland, and the method comprises the following steps: measuring the dissolved oxygen concentration, ammonia nitrogen concentration, total phosphorus concentration, water temperature and pH value of a root zone in the constructed wetland, and calculating the pollutant concentration distribution value and plant root system distribution density of each monitoring point; and obtaining a water quality root distribution characterization value. In an artificial wetland environment, the concentration of dissolved oxygen, the concentration of ammonia nitrogen, the concentration of total phosphorus, the water temperature and the pH value of a root zone are measured, the concentration distribution of pollutants is calculated, numerical calculation is carried out in combination with the distribution density of plant root systems, water quality root system distribution characterization is constructed, spatial heterogeneity analysis of wetland water quality is enhanced, and the targeting of pollutant degradation is optimized. Based on water quality root system distribution characterization, plant growth cycle parameters are calculated in combination with water quality parameters, association between water quality dynamic changes and plant growth states is constructed, and the adaptability of wetland ecological regulation and control is improved.

The invention discloses a shallow lake water quality pollution treatment system and method, and relates to the technical field of water pollution, and the method comprises the steps: S1, building a disturbance intensity index DIX and ammonia nitrogen concentration change curve, achieving the quantitative recognition of bottom mud disturbance and pollution release behaviors, training a rebound risk prediction model according to the quantitative recognition, and outputting a rebound risk prediction coefficient Ft; and the capability of pre-judging the rebound trend of the ammonia nitrogen pollution is effectively improved. In the step S2, the adjusted aeration response frequency BAF is dynamically generated based on the rebound risk prediction coefficient Ft value, so that the aeration behavior is converted into a risk-driven system from a traditional timing system, the energy consumption and disturbance intensity are further reduced, and the treatment efficiency is improved. And S3, further introducing a governance residual coefficient GRC, constructing a complete feedback closed loop, and realizing accurate evaluation and secondary strategy optimization of the governance effect of each round, thereby avoiding the problem of effect back-off or excessive disturbance after governance.

The invention provides an intelligent aeration system and a control method, and the system comprises a multi-parameter monitoring module which collects parameters such as water depth, pressure, temperature, dissolved oxygen, inlet water ammonia nitrogen, chemical oxygen demand, and mixed liquid suspended solid concentration in real time; the data analysis and preprocessing module adopts a sliding window algorithm to carry out data cleaning and anomaly detection; the oxygen supply demand prediction module establishes an oxygen demand prediction model based on machine learning, and combines theoretical calculation and deep learning prediction; the multi-target intelligent control module adopts a reinforcement learning algorithm, establishes a Markov decision process model, and optimizes the processing effect and energy consumption at the same time; the execution control module is used for accurately adjusting the rotating speed of a fan, the opening degree of a valve and the running state of an aerator; and the system collaborative optimization module realizes linkage control of the aeration system and the carbon source adding system. The system has the functions of self-adaptive parameter adjustment, fault diagnosis and self-recovery, the DO control precision reaches 95% or above, the daily average electricity is saved by 9.7%, the NH4-N of effluent is reduced by 25%, and the annual comprehensive benefit exceeds 500,000 yuan.

The invention belongs to the technical field of river and lake water quality monitoring, and discloses a river and lake water quality intelligent traceability monitoring system and method.Dissolved organic matter fluorescent fingerprints are analyzed in real time through a three-dimensional fluorescent monitoring unit, pollution markers are detected, and parameters such as COD, ammonia nitrogen and total phosphorus are synchronously detected through a full-spectrum monitoring unit; the video monitoring unit is used for collecting section images / videos of rivers and lakes, other sensors are used for collecting real-time values of chlorophyll, pH, conductivity, turbidity and dissolved oxygen in a water body, then the data processing module is used for carrying out normalization processing on multi-source data, and the analysis and early warning module is used for analyzing water quality early warning scores, spectrum early warning scores and video early warning scores. All scores are synthesized to obtain a comprehensive early warning score, traceability is started when comprehensive early warning is larger than or equal to the grade II, pollution sources are recognized based on three-dimensional fluorescence spectrum comparison and upstream patrol, and a river and lake water body monitoring-early warning-traceability-verification closed loop is achieved.

The invention provides an intelligent management method and system for reducing pollution and carbon of rural domestic sewage. According to the method, sewage flow velocity, COD concentration, ammonia nitrogen content data, user water use time and detergent use amount are collected, and a database is constructed. And weighting the flow velocity and COD to generate a pollution load evaluation value, and calculating an organic matter pollution influence value in combination with ammonia nitrogen and detergent data. A porous ceramic medium is arranged in the biological treatment device, and the dissolved oxygen concentration is adjusted according to the pollution load. A correlation curve of a COD concentration peak value and water consumption time is established, a prediction model is constructed in combination with dissolved oxygen parameters, the gas injection and reflux ratio is adjusted through graded pressure instructions, and the critical value of dissolved oxygen is maintained. The day and night temperature difference is fused to correct the degradation rate, and the optical detection data is combined to optimize the critical range and the instruction priority, so that the cooperative control of sewage treatment and carbon emission reduction is realized. According to the invention, self-adaptive adjustment of dissolved oxygen in sewage treatment is realized, and the sewage reduction and carbon reduction management efficiency of domestic sewage is improved.

The invention provides a treatment method of ammonia-nitrogen-containing wastewater, and belongs to the technical field of wastewater treatment. The preparation process comprises the following steps: preparing the wastewater treatment agent; preparing an immobilized microbial compound; and treating the ammonia-nitrogen-containing wastewater. According to the immobilized microbial carrier prepared by the invention, a stable dual-network structure and proper pore channels are formed through the synergistic effect of the polyvinyl alcohol, the carboxymethyl chitosan and the polyurethane; secondary cross-linking significantly enhances the stability of the carrier, optimizes internal pore channels, and is beneficial to attachment and proliferation of microorganisms; after the corn straw biochar is modified by Ca / Al, the specific surface area and functional groups are increased, and the physicochemical adsorption of ammonia nitrogen is enhanced. The three are combined, and ammonia nitrogen in wastewater is efficiently removed through synergism of carrier adsorption and microbial metabolism.

The invention belongs to the technical field of sewage treatment and artificial intelligence, and particularly relates to an effluent ammonia nitrogen concentration measurement method based on a neural network and Bayesian optimization, which comprises the following steps: step 1, constructing a basic model, collecting a characteristic variable x, preprocessing x, and normalizing x; 2, inputting x into a basic model for feature extraction and reinforcement; 3, extracting long-term time sequence features of a feature sequence from the x after feature extraction and enhancement through a bidirectional long-short-term memory neural network, dynamically adjusting an input step length, capturing a bidirectional time dependency relationship in the sequence, and outputting a predicted value; and step 4, performing parallel Bayesian optimization algorithm, dynamically adjusting the acquisition function, simultaneously evaluating a plurality of candidate points, performing parallel adaptive acquisition function, and outputting a measurement value. According to the scheme, the acquisition function can be dynamically adjusted according to different stages of the optimization process, the parameter space coverage rate is improved, multiple candidate points are evaluated at the same time, the exploration speed of the parameter space is increased, and the generalization ability of the model is enhanced.

The invention provides a bioreactor aeration self-adaptive control method and system based on machine learning, and the method comprises the steps: collecting the water inlet flow, ammonia nitrogen concentration, dissolved oxygen concentration, water temperature and chemical oxygen demand data of a bioreactor in real time through a sensor, and carrying out the water balance verification and the Kalman filtering pretreatment containing a water temperature compensation item; generating an aeration instruction by adopting multi-model collaboration; outputting a reference aeration rate by a deep reinforcement learning DRL model; the self-adaptive PID controller dynamically adjusts the proportionality coefficient according to the dissolved oxygen deviation and calculates the correction amount; and the LSTM network generates a fusion weight, and combines the seasonal compensation factor and the safety coefficient to synthesize the final aeration rate. The system passes mutation rate constraint and nitrification efficiency verification, an ASM1 model is triggered to recheck when the deviation exceeds the standard, and after passing, an air blower with the precision of + / -2% executes an instruction and performs closed-loop feedback in a period smaller than or equal to 10 seconds. After the method is implemented, the aeration energy consumption is reduced to 0.38 kWh / m, the effluent ammonia nitrogen standard reaching rate is improved to 98.5%, the dissolved oxygen fluctuation range is reduced to + / -0.3 mg / L, and the impact load response time is shortened to be within 15 minutes.

The invention relates to an intelligent breeding method for crayfish offspring seeds in a winter fallow field, and belongs to the technical field of aquaculture. In order to solve the problems of dissolved oxygen management lag, high ammonia nitrogen accumulation risk and overlarge energy consumption caused by low utilization rate of winter fallow fields and dependence of water quality regulation and control on artificial experience in the prior art, the method comprises the following steps: deploying a water quality dynamic monitoring system based on the Internet of Things to collect data of water temperature, dissolved oxygen, pH value, ammonia nitrogen and nitrite in real time; the power and the water level of the oxygenation equipment are dynamically adjusted after analysis of the edge calculation module; graded regulation and control are achieved by combining a three-level response mechanism, when the dissolved oxygen content is lower than 6 mg / L or the pH value is abnormal, the power of the nanometer oxygenation device is started to 50%, and when the dissolved oxygen content continuously deteriorates, the irrigation system is linked to inject the water body with the temperature being adjusted in advance. According to the method, through intelligent multi-parameter cooperative control and ecological bait design, the resource utilization rate of the winter fallow field is increased, the survival rate of the young crayfish is increased to 85% or above, and the method is suitable for large-scale and green efficient breeding of the young crayfish in a rice-shrimp rotation mode.

The invention relates to a continuous flow AOA whole-course anaerobic ammonia oxidation self-enrichment enhanced denitrification system and method, and the system comprises a front anoxic tank, an aerobic tank and a rear anoxic tank which are connected in series, and is filled with a biological filler; the monitoring aeration device comprises an ammonia nitrogen detector and an aeration unit which are connected with the aerobic tank; the reflux device is used for communicating a reflux outlet of the rear anoxic tank with water distribution of the front anoxic tank; and the PID control unit is connected with the monitoring aeration device, the backwashing control valve and the reflux device. The method comprises the following steps: sewage flows into the front anoxic tank, the aerobic tank and the rear anoxic tank; regulating and controlling the reflux ratio to domesticate the biological membrane of the aerobic tank; the ammonia nitrogen concentration of effluent of the aerobic tank is detected in real time through an ammonia nitrogen detector, and the PI D control unit dynamically adjusts the aeration rate of the aerobic tank according to the ammonia nitrogen concentration value and a preset target value, so that the aerobic tank and the rear anoxic tank form an anaerobic ammonium oxidation bacteria self-enrichment environment; the backflow device is used for enabling effluent of the rear anoxic tank to flow back to the front anoxic tank according to a preset proportion, so as to form a whole-process anaerobic ammonia oxidation self-enrichment environment.

The invention relates to the technical field of microorganisms, and discloses a sewage aquatic microbe with ammoxidation capacity, a microbial agent and application of the microbial agent. The strain name of the sewage aquatic microbe is B1, and the preservation number of the sewage aquatic microbe is CCTCC No: M 2025640. The sewage aquatic microbacterium B1 provided by the invention can convert ammonia nitrogen into nitrite nitrogen, so that short-cut nitrification is realized in wastewater treatment, and the strain can tolerate and effectively treat ammonia nitrogen with relatively high concentration, and has relatively good adaptive capacity to environments with different pH values, salinity and temperatures.

The invention discloses a method for preparing a bismuth ferrite composite catalytic material by using red mud as well as a product and application of the bismuth ferrite composite catalytic material. The method comprises the following steps: mixing chlorine salt and red mud, uniformly stirring, adding a hydrochloric acid solution, uniformly stirring, roasting, recovering flue gas generated in the roasting process, and obtaining roasting residues and roasting dust generated by recovering the flue gas after roasting is finished; and mixing the roasted dust and bismuth nitrate, uniformly stirring, adding the calcined residue, uniformly grinding, adding water, stirring, drying the material, and calcining to obtain the bismuth ferrite composite catalytic material. The preparation process is simple, the red mud is used as a main raw material, and full-amount resource utilization of the red mud can be achieved. The prepared composite catalytic material can be used for efficiently purifying landfill leachate, and COD, ammonia nitrogen, total phosphorus and heavy metal pollution are efficiently removed through a photocatalysis mechanism.

The invention provides a digital twinborn monitoring, regulating and controlling method for a copepod bait biological domestication process. The method comprises the following steps: establishing a micro-ecology and population dynamics coupled twinborn model, and defining a monitoring parameter and control object unified term system; collecting multi-source sensing data at an edge end, and performing clock synchronization, signal denoising and state estimation to obtain a micro-ecology, group and water body state joint estimation result; executing parameter online identification based on state estimation, and constructing a safety constraint set of ammonia nitrogen, dissolved oxygen, death rate, environment change rate and the like; the breeding efficiency improvement and the system stability balance are realized through a multi-objective optimization function; and generating a micro-ecological pulse and environment gradual change cooperative control action set according to a solving result, and when a set condition is met, outputting a domestication prescription and terminating the process. Intelligent, low-stress and high-stability regulation and control of a copepod domestication process are realized through digital twin modeling, rolling predictive control and a self-evolution updating mechanism.

The invention discloses a regulation and control method and system for gradient resource utilization of rural domestic tail water, and the requirements of reuse water in different seasons are met through regulation and control, that is, the quality of outlet water in the irrigation season meets the farmland water quality standard, and the quality standard of miscellaneous use of tail water or ecological water supplement is met in the non-irrigation season. According to the method, the state of tail water is monitored in real time through a sensor matrix, meanwhile, organic matter (or chemical oxygen demand) and ammonia nitrogen, total nitrogen, total phosphorus and microorganism effluent quality requirements input by a user are obtained, and time sequence semantic features of the state of the tail water are mined by adopting a neural network technology based on deep learning; and carrying out conjoint analysis on organic matters, ammonia nitrogen, total nitrogen and total phosphorus effluent to obtain associated characterization of multi-aspect tail water treatment requirements.

The invention relates to the technical field of sewage treatment, in particular to a dynamic control method applied to a culture tail water circulation treatment system. The method comprises the following steps: continuously detecting aquaculture tail water on a water inlet pipeline, calculating the ratio of chemical oxygen demand to five-day biochemical oxygen demand as a first degradation index, and calculating the ratio of ultraviolet absorbance to total organic carbon concentration as a second degradation index; according to the first degradation index and the second degradation index, identifying aging complementary and range complementary organic load degradation characteristics, and determining a process treatment path based on the organic load degradation characteristics; performing primary pretreatment on the aquaculture tail water in different process treatment paths to obtain intermediate water quality data; detecting the ammonia nitrogen concentration of the intermediate water quality data, and extracting the time change rate of the ammonia nitrogen concentration as an ammonia nitrogen conversion parameter. According to the invention, the oxygen utilization efficiency and the removal rate of organic matters and nitrogen are improved through regional dissolved oxygen and function configuration optimization.

The invention discloses a high-activity short-cut nitrification quick-start long-term stable operation process, which relates to the technical field of biological sewage treatment, and comprises the following steps: inoculating sludge, carrying out anaerobic fermentation pretreatment, and removing expanded sludge and sludge foam in combination with quick sludge discharge and manual removal; controlling the number of days of sludge age, reproliferating the sludge, enriching ammonia oxidizing bacteria, and inhibiting and elutriating nitrite oxidizing bacteria; long-term operation is carried out under the condition of no sludge discharge, the abundance and activity of ammonia oxidizing bacteria are maintained, and meanwhile, the abundance of nitrite oxidizing bacteria is controlled; the proliferation of nitrite oxidizing bacteria is controlled by using the predation effect of protozoa and metazoan, and the accumulation rate of nitrite in the reactor is controlled; monitoring the dissolved oxygen, the pH value and the concentrations of ammonia nitrogen, nitrite nitrogen and nitrate nitrogen in the reactor in real time, and regulating and controlling the influent ammonia nitrogen load and the free ammonia concentration; dissolved oxygen distribution is adjusted in an intermittent aeration or microporous aeration mode, and the operation conditions of the short-cut nitrification reactor are optimized. The method is simple to operate, economical and effective.

The invention belongs to the technical field of wastewater treatment, and provides a wastewater treatment equipment remote control system based on the Internet of Things, which aims at solving the problems that the traditional fixed DO concentration control cannot adapt to water inlet load fluctuation, the effluent is easy to be substandard or the aeration energy consumption is high, the monitoring data noise is large, and the time sequence is misplaced. According to the scheme, a multi-dimensional real-time sensing network is constructed, flow, COD, BOD, ammonia nitrogen, water temperature, distributed DO and sludge activity sensors are deployed, discrete wavelet transform is adopted for noise reduction, and a data time sequence is aligned; a three-layer load-DO-energy consumption dynamic correlation model is designed, a basic layer predicts a load trend through LSTM, a middle layer quantifies a DO demand through a microbial metabolism model, and an optimization layer outputs an optimal DO set value through a PPO algorithm; and developing a dynamic decision-making system, adaptively generating a DO interval according to a load state, and adjusting fan parameters and number in a linkage manner. According to the invention, load dynamic adaptation is realized, effluent ammonia nitrogen is guaranteed to reach the standard, aeration energy consumption is reduced, and remote control precision and equipment operation efficiency are improved.

The invention discloses a method for preparing a catalyst by using red mud and titanium dioxide acidolysis waste residues as well as a product and application thereof. The method comprises the following steps: calcining red mud, adding titanium dioxide acidolysis waste residues and an auxiliary agent, uniformly stirring, adding a desulfurization waste liquid, uniformly stirring, carrying out a hydrothermal reaction, carrying out solid-liquid separation, and calcining to obtain the catalyst material. The preparation process is simple, and efficient resource utilization of the red mud and the titanium dioxide acidolysis waste residues can be achieved. The catalyst prepared through a hydrothermal reaction and a secondary calcination process realizes efficient removal of COD, ammonia nitrogen, total phosphorus and heavy metal pollutants in waste liquid through a photocatalytic function.

The invention discloses a method for preparing a composite catalyst by synergistically utilizing red mud and arsenic alkali residues as well as a product and application thereof, and belongs to the field of resource utilization of industrial wastes. The method disclosed by the invention is simple in preparation process, wide in preparation raw material source and capable of realizing full-amount utilization of the red mud and the arsenic alkali residues. Compared with a traditional titanium dioxide and iron arsenate catalyst, the composite catalyst prepared by the method is more excellent in performance, the landfill leachate treatment efficiency can be remarkably improved, and the catalytic removal effect of 2145 mg / g COD, 162 mg / g total phosphorus, 356 mg / g ammonia nitrogen and 122 mg / g mercury can be achieved at most.

The invention belongs to the technical field of sewage treatment, and particularly relates to an anaerobic ammonia oxidation-photoelectric denitrification deep nitrogen removal method. The method comprises the following steps: firstly, adopting a double-chamber reactor; introducing part of sewage into the cathode chamber, carrying out Anammox reaction under a dark state condition to remove ammonia nitrogen and part of nitrite nitrogen, and synchronously generating nitrate nitrogen; turning on a light source to irradiate the anode chamber, exciting photo-induced electrons by a photosensitizer, transmitting the photo-induced electrons to the cathode chamber through an external circuit, and driving the sulfur autotrophic denitrification sludge to reduce residual nitrite nitrogen and nitrate nitrogen generated by Anammox; the total nitrogen removal rate is close to 100%. According to the invention, photo-induced electrons are used as the only denitrification electron donor, so that the addition of a carbon source / sulfide is thoroughly avoided, and the risk of secondary pollution is eliminated. The method is suitable for green low-carbon deep treatment of sludge digestion liquid and pharmaceutical wastewater high-ammonia-nitrogen low-carbon-nitrogen-ratio sewage.

The invention discloses a system and a method for classified sewage treatment, and belongs to the technical field of environmental engineering and water treatment. The system comprises the following components: an intelligent water quality detection module, which is used for real-time and accurate monitoring of COD, BOD, ammonia nitrogen, total phosphorus, suspended matter concentration and heavy metal content; the sectional bioreactor realizes deep removal of nitrogen and phosphorus and efficient biological treatment by flexibly adjusting reaction conditions of each section; the intelligent flocculation control module is used for automatically and accurately adjusting the adding amount of a flocculating agent, and is combined with integrated operation of efficient inclined tube precipitation and sludge concentration, so that the water quality of discharged water is stable, and the medicament consumption is reduced; the ultrafiltration membrane bioreactor effectively removes residual suspended matters and colloids, and ensures that the effluent stably reaches the standard for a long time through the synergistic effect of catalytic ozonation; and the sludge treatment module is used for realizing collaborative optimization management of sludge reduction, recycling and energy recycling.

The invention relates to a microbial agent prepared based on a new strain of bacillus velezensis, which has the function of broad-spectrum antagonism of common pathogenic bacteria of aquatic products and can effectively prevent and / or treat bacterial diseases and / or fungal diseases of aquatic organisms including crustaceans and fishes. Meanwhile, the content of nitrite and ammonia nitrogen in aquaculture water can be effectively reduced, and the usage amount and residual quantity of antibiotics and chemical drugs in aquaculture are reduced.

The invention discloses a method for preparing a catalytic material by synergistically utilizing red mud and electrolytic manganese residues as well as a product and application thereof. The method comprises the following steps: mixing electrolytic manganese residues and red mud, uniformly stirring, adding ammonium chloride, stirring, adding a hydrochloric acid solution, stirring, roasting and grinding. And adding an auxiliary agent, uniformly stirring, adding water, granulating, standing, carrying out hydrothermal reaction, and roasting to obtain the catalytic material. The preparation process is simple, the technological process is brief, the needed core raw materials are only the red mud and the electrolytic manganese residues, and resource utilization of the red mud and the electrolytic manganese residues is efficiently achieved. The prepared catalytic material can quickly adsorb pollutants in waste liquid under the condition of no photocatalysis, and the removal effect on COD (Chemical Oxygen Demand), ammonia nitrogen, total phosphorus and heavy metal mercury can be further remarkably improved under the photocatalysis condition.

According to the plasma aquaculture water purification method and system, a cold plasma directional screening technology is used as a core to construct a cold plasma water treatment module, a nanosecond pulse plasma generator is used for exciting a gas medium to form cold plasma, active particles are screened in situ through a directional screening assembly, and the cold plasma water treatment module is used for purifying aquaculture water. The method comprises the following steps: introducing ammonia nitrogen into a water body, guiding < 1 > O2 to be quickly injected into the water body, instantaneously completing a primary purification reaction in a gas-liquid intersection chamber, further, in order to fully utilize residual active particles, directionally converting a reaction precursor O3 of < 1 > O2 into < 1 > O2 through a catalytic dissociation module, and completing a secondary purification reaction between the < 1 > O2 and the ammonia nitrogen. Ammonia nitrogen is directionally converted into nitrogen by utilizing a 1O2-dominated non-free radical reaction path, the content of ammonia nitrogen and total inorganic nitrogen in a water body is reduced, and after purification is completed, oxidizing components in the water body and tail gas are respectively removed by adopting a by-product removal assembly, so that the use safety is guaranteed.

The invention discloses a nitrifying bacterium agent suitable for aquarium, fishpond and other aquatic industries, the strain of the nitrifying bacterium agent is Glutamicacter nicotianae TJ-X, the nitrifying bacterium agent is preserved in Guangdong Microbial Culture Collection Center on February 12, 2025, and the preservation number is GDMCC NO.65877. The invention further discloses a preparation method of the nitrifying bacterium agent. The nitrifying bacteria TJ-X strain suitable for the aquarium industry can perform heterotrophic nitrification and aerobic denitrification under the condition that the salt content is 5wt%, under the condition of laboratory pure culture, within 8 hours, the removal rate of ammonia nitrogen, nitrite nitrogen and nitrate nitrogen is 99% or above, the COD degradation rate is 81%, the nitrifying bacteria TJ-X strain is suitable for the environment where organic matter, ammonia nitrogen, nitrite and nitrate coexist, and the nitrifying bacteria TJ-X strain can be applied to the aquarium industry. The microbial agent has the functions of degrading organic matters such as excrement of ornamental fish and fish food, converting organic nitrogen into inorganic nitrogen, and simultaneously degrading inorganic nitrogen such as ammonia nitrogen, nitrite nitrogen and nitrate nitrogen into nitrogen. And the strain is high in biological safety, high in environmental adaptability and high in growth density, can be applied to water industries with high organic matter content and inorganic nitrogen, such as the aquarium industry and aquaculture, and has a wide application prospect.