36 results about "Industrial emission" patented technology

The invention relates to the technical field of carbon emission prediction, and discloses a combined carbon emission prediction method based on multi-source heterogeneous tensor data. The method comprises the steps that multi-source carbon emission data streams such as industrial emission, traffic flow and energy consumption in a target area are collected, and a carbon emission tensor sequence with the unified space-time dimension is generated through heterogeneous tensor conversion; multi-scale space-time correlation features in the sequence are extracted through a dynamic feature fusion algorithm, and a combined prediction model containing a long-period trend prediction branch and a short-period fluctuation prediction branch is constructed. And iteratively training the model by using a historical tensor sequence until convergence, and inputting a real-time multi-source data stream to output a combined prediction result. According to the method, effective integration and deep feature mining of multi-source heterogeneous data are realized, different change rules of carbon emission are accurately captured through branching model design, the comprehensiveness and reliability of prediction are improved, and scientific reference is provided for carbon emission management and control.

The invention relates to the technical field of data integration, and particularly discloses a perfluoro / polyfluoroalkyl substance multi-source exposure data integration risk assessment system, which is characterized in that environmental exposure data of perfluoro / polyfluoroalkyl substances is acquired through a multi-source environmental sensor array, and a PFAS multi-mode exposure feature database is established; carrying out pollution source isotope fingerprint analysis, and obtaining source contribution rate distribution maps of three pollution sources of industrial emission, surface runoff and atmospheric settlement through a nonlinear source analysis algorithm; constructing a three-dimensional geographic information dynamic migration model according to the source contribution rate distribution map, and generating a multi-medium dynamic migration flux matrix; a composite risk assessment model is established based on the multi-medium dynamic migration flux matrix, probability risk assessment is executed in combination with an ecological toxicity threshold database, and a space gridding risk grade map is output; the method not only fills the blank of the prior art in the aspects of multi-medium dynamic modeling and nonlinear source analysis, but also provides powerful technical support for environmental pollution control and ecological risk prevention and control.

The invention provides a remote sensing-based land utilization carbon emission evaluation method, device and equipment and a medium, and the method comprises the steps: carrying out the radiometric calibration and spatial registration of obtained multi-source remote sensing data, and obtaining a standardized raster data set; generating a land utilization classification grid map based on the standardized grid data set; generating a land change vector layer through a continuous multi-stage land utilization classification grid map; generating a dynamic evaluation unit vector boundary according to the land utilization classification grid map and the land change vector layer; correcting a vegetation carbon absorption coefficient and an industrial emission coefficient in real time based on remote sensing inversion data, and constructing a spatial carbon transfer model; and inputting the land utilization classification grid map, the dynamic evaluation unit vector boundary and the spatial carbon transfer model into a layered mixed carbon emission evaluation model to obtain a carbon emission intensity distribution map. By adopting the scheme, the carbon emission under different land utilization modes can be accurately evaluated, and the scientificity and policy applicability of regional carbon balance evaluation are improved.

The invention provides an atmospheric pollutant traceability analysis method and system. According to the method, a form classification standard is established through particle shape features, and atmospheric particles are divided into naturally raised dust and industrial emission particle swarms. A dual-wavelength laser technology is adopted for natural flying dust, specifically, the first wavelength is matched with the inherent frequency of mineral crystals, amorphous scattering interference is blocked through polarization beam splitting, and a reflection signal sequence is extracted to generate a mineral migration path; and the second wavelength screens heavy metal scattering signals of the industrial particles, and a heavy metal diffusion track is constructed by utilizing spatial intensity gradient. And superposing the two paths and aerosol three-dimensional distribution data to generate a thermal distribution diagram, and when the space density exceeds a threshold value, calculating a migration path deviation value and a trajectory offset, dynamically distributing pollution source contribution weights, and outputting a pollution source analysis result. According to the invention, dynamic and accurate analysis of natural and industrial pollution sources is realized, and the regional pollution traceability and management and control strategy targeting are improved.

The invention discloses an industrial emission carbon and emission reduction real-time monitoring device and a use method thereof, and belongs to the technical field of industrial emission monitoring. An industrial emission carbon reduction and emission reduction real-time monitoring device comprises a detection device shell, a detection plate is installed outside the detection device shell, and a second fan is installed at the lower end of the detection device shell; and three upper-layer filter plates and three lower-layer filter plates are mounted in the detection device shell. The problems that an existing emission monitoring device cannot treat monitored carbon emission gas, and long-term work of the monitoring device is affected are solved, a servo motor is adjusted through a PLC module, an upper-layer filter plate and a lower-layer filter plate are driven to move, the upper-layer filter plate and the lower-layer filter plate are arranged in a targeted mode, and under the condition that the carbon emission reaches the standard, the carbon emission can be effectively controlled. The upper-layer filter plate and the lower-layer filter plate can be rotated to a vertical position, so that filter elements in the filter plates are prevented from being consumed, and the service life of equipment is prolonged.

The invention discloses an improved gas flow control method, which relates to the technical field of gas flow detection, and comprises the following steps: a gas flow detection system based on a honeycomb phase array technology monitors the gas flow in a large pipeline in real time; analyzing airflow distribution in the large pipeline based on fluid dynamics simulation; establishing an associated mathematical model, and correcting a flow value; various errors are compensated; connecting measured data with a carbon emission monitoring system, and transmitting the measured data to a data center in real time; the invention further discloses an improved gas flow control system which comprises a gas flow detection module, a calculation processing module and a remote data transmission module. By combining the honeycomb phase array technology, the multi-sensor fusion technology and the fluid dynamics simulation analysis technology, the precise, reliable and intelligent gas flow control method and system are provided, the accuracy and stability of flow measurement can be improved, and industrial emission can be monitored and controlled in real time.

The invention discloses an environmental protection data monitoring method and system, and relates to the technical field of environmental protection data monitoring, and the method comprises the steps: constructing a monitoring network in which a fixed monitoring station and a mobile monitoring unit cooperatively work, and achieving the comprehensive collection of real-time data of air quality; multi-source data is transmitted to a cloud platform by using a high-speed data transmission network formed by low-power wireless communication LPWAN and a 5G network, and a high-resolution thermodynamic diagram is generated through a data puzzle algorithm, so that the defects of insufficient space coverage and data updating lagging of traditional monitoring are effectively overcome. According to the method, a pollutant component quantitative model is further constructed by adopting a big data analysis and stoichiometric method, real-time data of PM2.5, VOC and sulfur dioxide are mapped to each pollution source, and accurate quantification of contribution rates of pollution sources such as industrial emission, traffic tail gas and building dust is realized through automatic normalization of a soft maximization function.

The invention discloses a conductivity pollution intelligent diagnosis method based on multi-modal feature fusion and adaptive density clustering. The method comprises the following steps: (1) carrying out data processing through an intelligent data preprocessing module; (2) detecting the conductivity data through a multi-scale anomaly detection engine; (3) carrying out system extraction through a multi-modal feature extraction system; (4) optimizing the data through an adaptive density clustering algorithm; and (5) performing diagnosis through an intelligent diagnosis decision-making system. The invention provides a conductivity pollution intelligent diagnosis method based on multi-modal feature fusion and adaptive density clustering. The conductivity pollution intelligent diagnosis method is suitable for application scenes of intelligent water affairs, drainage basin water quality monitoring, industrial emission supervision and the like.

The invention discloses a sea-land interaction zone underground water pollution source tracing method based on multi-pollutant fingerprints, and the method comprises the steps: constructing a fingerprint feature library of eight key pollutants including cadmium, arsenic, nitrate nitrogen, ammonium nitrogen, phosphate, total petroleum hydrocarbon, sulfamethoxazole, pH value and the like; statistical characteristic models of four pollution sources of industrial emission, agricultural non-point sources, oil exploitation and aquaculture are established, Z-Score standardization and a similarity calculation method based on a standard normal distribution probability density function are adopted, comprehensive similarity evaluation is performed in combination with a risk weight distribution mechanism, a similarity threshold value of 0.7 is set to perform pollution source identification and sorting, and the pollution sources are identified and sorted according to the similarity threshold value. And correction is performed by considering environmental factors such as tide, season and geology of a sea-land interaction zone. The method can quickly and accurately recognize the groundwater pollution source of the sea-land interaction zone, the traceability accuracy rate reaches 80% or above, and scientific and technical support is provided for prevention and control of groundwater pollution of the sea-land interaction zone and formulation of an environmental protection policy.

The invention belongs to the technical field of carbon emission, and particularly relates to an industrial emission carbon reduction and emission reduction real-time monitoring device which comprises a base, a monitor body is fixedly connected to one side of the upper end face of the base, an air inlet pipe is arranged on one side of the monitor body, and a filter screen is fixedly connected to one side of an inner cavity of the air inlet pipe. The monitor body is further provided with a foreign matter removing assembly for preventing the end of the air inlet pipe from being covered. By means of the foreign matter removing assembly, the plastic bag covering the air inlet of the air inlet pipe can be removed regularly. Gas circulation blocking caused by the fact that a plastic bag covers the gas inlet is avoided, and normal operation of monitoring work is guaranteed.

A distributed robust opportunity constraint-based steel park micro-grid low-carbon optimization operation method belongs to the technical field of electric power systems, constructs a DRCC-based steel park micro-grid material-energy consumption-carbon emission model, performs low-carbon optimization operation, facilitates comprehensive mining of industrial emission reduction potential, optimizes and upgrades a production mode, and improves production efficiency. Decision reference considering reliability and economical efficiency is provided for production and operation of the micro-grid in the steel park, risk preferences and actual demands in production, operation and transaction are accurately balanced, an optimal implementation scheme is formulated, then the economic benefit and operation reliability of the micro-grid in the steel park are improved, and a low-carbon and efficient economic operation mode is achieved.

The invention provides an industrial emission pollutant concentration identification method, system and device based on a multi-mode video, and the method comprises the steps: obtaining a visible light / infrared video which is subjected to time-space alignment, positioning a pollution feather flu region of interest, extracting image and time sequence features in the region of interest (ROI), and carrying out the regression, thereby obtaining an initial concentration estimation value yhat; based on the scale proportion of the ROI in the image, a plurality of calibration curves are adaptively selected or weighted by using a preset function to calibrate the initial concentration yhat, and the calibrated concentration ycal is output; meanwhile, uncertainty is given in a quantile interval mode, and coverage rate calibration is achieved through monotone mapping. And finally, binding the concentration, the uncertainty and the intermediate process data with the unique traceability identifier to generate a reviewable evidence packet. According to the method, end-to-end quantitative identification from common video to concentration is realized, and accuracy, robustness and traceability are improved.

The invention discloses an industrial waste heat recycling system based on the Internet of Things. According to the system, the ultra-high temperature heat pump unit plays a crucial role in an industrial waste heat recycling system based on the Internet of Things. The method has the advantages that the temperature of waste heat is increased efficiently, low-temperature waste heat is converted into high-quality heat energy, and therefore the recycling value of energy is greatly increased. By adopting an advanced compression technology and an environment-friendly refrigerant, the unit can stably operate under a high-temperature working condition, and continuous and reliable supply of heat energy is ensured. In addition, the intelligent control system of the ultra-high-temperature heat pump unit can automatically adjust operation parameters according to real-time data, energy efficiency optimization is achieved, and the energy consumption cost is reduced. The heat exchange efficiency is further improved through the efficient heat exchanger design, and heat losses are reduced. Therefore, the ultrahigh-temperature heat pump unit not only improves the waste heat recovery efficiency and economical efficiency, but also contributes to reducing industrial emission and promoting green and sustainable development.

The present application relates to the technical field of carbon emission prediction, and discloses a combined carbon emission prediction method based on multi-source heterogeneous tensor data.The method comprises collecting multi-source carbon emission data streams such as industrial emissions, traffic flow and energy consumption in a target area, and generating a unified spatio-temporal dimension carbon emission tensor sequence through heterogeneous tensor conversion.Through a dynamic feature fusion algorithm, multi-scale spatio-temporal correlation features in the sequence are extracted, and a combined prediction model containing a long-period trend prediction branch and a short-period fluctuation prediction branch is constructed.After the model is iteratively trained to convergence using historical tensor sequences, real-time multi-source data streams can be input to output the combined prediction results.The method realizes effective integration and deep feature mining of multi-source heterogeneous data, accurately captures different change laws of carbon emissions through branched model design, improves the comprehensiveness and reliability of the prediction, and provides a scientific reference for carbon emission control.

The invention discloses a novel method for predicting potential AQI based on a causal framework, and the method comprises the steps: processing an industrial emission characteristic p (X, Xnei), a pollutant concentration prediction result p (MX, Xnei, W) and an industrial emission influence parameter p (YX, Xnei, M, W) through a potential AQI prediction model, and obtaining an air quality index prediction result # imgabs0 # # imgabs1 # of t {pred} time steps in the future. The causal relationship between the industrial emission intervention and the AQI can be effectively identified, so that the model can more accurately predict the actual influence of the industrial emission intervention measures under different environment and climate conditions.

The invention provides an industrial source VOCs emission component spectrum construction method based on headspace analysis and a material balance algorithm. The method comprises the following steps: (1) raw material sample collection and pretreatment; (2) analysis of VOCs components in raw materials; (3) establishment of a material balance model; and (4) establishment of an enterprise overall emission component spectrum. According to the method, through coupling of experimental determination and material balance simulation, cross-scale connection from solvent physicochemical characteristics to enterprise emission spectrums is achieved, the accuracy, representativeness and operability of the industrial VOCs emission source component spectrums are remarkably improved, and a scientific and systematic novel method is provided for industry emission reduction decision making and pollution source analysis.

The application provides a kind of industrial source VOCs emission component spectrum construction method based on headspace analysis and material balance algorithm.The method comprises the following steps: (1) raw material sample collection and pretreatment (2) VOCs component analysis in raw material (3) material balance model establishment (4) enterprise overall emission component spectrum establishment.The application realizes the cross-scale connection from the physical and chemical properties of solvent to enterprise emission spectrum through the coupling of experimental determination and material balance simulation, significantly improves the accuracy, representativeness and operability of industrial VOCs emission source component spectrum, and provides a scientific, systematic new method for industry emission reduction decision and pollution source analysis.

The low-energy-consumption CO2 trapping device comprises a bin body, a gas inlet pipe and a discharging pipe are arranged on the bin body, a first liquefying box and a second liquefying box are symmetrically arranged in the bin body, the gas inlet pipe is connected with the two liquefying boxes through a first gas distributing pipe and a second gas distributing pipe, and the first gas distributing pipe and the second gas distributing pipe are provided with electromagnetic valves. The bottom end of the liquefying box is connected with a discharging pipe through a first discharging pipe and a second discharging pipe which are provided with one-way valves; the gas distribution pipe penetrates through the filter box, a detachable filter layer is arranged in the filter box, a plate heat exchanger is arranged on one side of the liquefaction box, and a jacket type low-temperature rectifying column is mounted in the liquefaction box. The trapping method comprises the steps of pretreatment, split-flow gas inlet, liquefaction trapping, discharge backflow prevention, dynamic adjustment and maintenance, and a single / double-box operation mode can be switched according to the CO2 emission load. The device realizes continuous and stable capturing process, dynamic and controllable energy consumption, high CO2 capturing purity and recovery rate, is convenient to maintain, is suitable for industrial emission sources of power plants, chemical plants and the like, and has remarkable energy-saving effect and industrial application value.

The invention discloses a method and a system for determining heavy metal pollution characteristics of water sediment, and relates to the technical field of environment monitoring and water environment governance, the system is characterized in that surface sediment samples are regularly collected at different positions of water in a mine area and an industrial gathering area, and a metal element data set and a reference data set are established; calculating a single-factor pollution index, and judging whether single metal exceeds the standard or not; integrating the single-factor pollution indexes to obtain a comprehensive pollution index, and determining the overall pollution level; whether manual input pollution exists or not is judged by calculating the geocumulative index; according to the method, correlation analysis, principal component analysis, factor analysis and GIS space statistics are combined, multi-dimensional indexes are extracted, pollution source analysis coefficients are calculated, agricultural non-point source or industrial emission dominant pollution types are determined, and corresponding prevention and control strategies are generated. According to the method, multilevel feature recognition and source analysis of sediment heavy metal pollution can be realized, and a scientific basis is provided for water area pollution treatment and risk management and control.

The invention discloses a liquid carbon dioxide offshore jacket type injection and storage method. The liquid carbon dioxide offshore jacket type injection and storage method comprises the steps that S1, carbon dioxide captured by an industrial emission source is purified; s2, pressurizing and cooling the purified carbon dioxide to convert the carbon dioxide into liquid carbon dioxide; s3, the liquid carbon dioxide is conveyed to the offshore jacket platform through a transport ship, and the liquid carbon dioxide is stored in the offshore jacket platform; s4, pressurizing the liquid carbon dioxide to enable the pressure of the liquid carbon dioxide to be increased to 30-100 MPa; s5, the pressurized liquid carbon dioxide is stably injected into the seabed deep reservoir, so that the carbon dioxide is sealed and stored in the seabed deep reservoir; and S6, full-period monitoring is carried out on the sealed and stored products, and the leakage risk is early warned in advance. The liquid carbon dioxide offshore jacket type injection and storage method has the advantages of being simple in step, high in transportation efficiency and the like.

The invention relates to an air quality prediction management method and system for air pollution prevention and control, and relates to the technical field of environment monitoring. The method mainly comprises the following steps: respectively calculating air quality prediction data of a target city and adjacent cities according to industrial emission data, traffic emission data and real-time pollutant concentration monitoring data of the target city and the adjacent cities; updating the air quality prediction data of the target city through the meteorological prediction data and geographic information data of the target city and the adjacent cities thereof and the air quality prediction data of the adjacent cities to obtain final air quality prediction data of the target city; determining whether the final air quality prediction data of the target city is greater than a preset abnormal value; if the air quality is larger than the preset abnormal value, industrial emission and traffic emission of the target city or adjacent cities are managed and controlled according to the generation reason of the final air quality prediction data.

The invention relates to the technical field of industrial emission treatment, in particular to a dust waste gas treatment method. According to the invention, a wet electrostatic precipitation (WESP) deep pretreatment heat energy cascade recycling humidifying hydrophobic zeolite rotating wheel concentration heat storage type oxidation cooperative treatment chain is constructed. Submicron particles and aerosol are efficiently removed under a high-voltage electric field through the WESP unit, and the risk of physical blockage to the rotating wheel is eliminated; afterheat of high-temperature purified flue gas generated by a heat accumulating type oxidation system is utilized, the temperature of saturated wet flue gas at an outlet of the WESP is increased by 5-15 DEG C through gas-gas heat exchange, the relative humidity is reduced to 60% or below, and an environment suitable for zeolite adsorption is created; and the concentrated organic oxide is oxidized and decomposed in the heat accumulating type oxidizing furnace to release heat energy, so that the heat balance of the system is maintained. According to the method, the comprehensive operation energy consumption of the system is remarkably reduced while dual up-to-standard emission of the particulate matters and the organic oxides is guaranteed.

The invention discloses an industrial VOCS emission quality evaluation method and system based on big data, and the method comprises the steps: calculating the emission amount in unit time based on the VOCS concentration and flow, obtaining the emission intensity characteristics, calculating the treatment efficiency characteristics through comparing the VOCS concentration before and after treatment, and simulating the concentration distribution under a complex terrain through an ADMS, and obtaining the environmental influence characteristics; fusing the emission intensity feature, the treatment efficiency feature and the environmental influence feature through a cross-modal attention mechanism; an LSTM neural network is utilized to predict the VOCS emission trend in a future time period, and the operation efficiency of treatment equipment is quantified through a random forest algorithm; and inputting the fusion feature vector into the dynamic evaluation model, and outputting an industrial VOCS emission quality evaluation report. The limitation of traditional single index evaluation is avoided, and the evaluation result is more comprehensive.

The utility model discloses a heavy punch fixing and adjusting device, which relates to the technical field of industrial emission and comprises a heavy punch shell, a top cover, a locking and connecting component and a fixing and guiding component. The top cover is fixedly arranged at the top of the heavy hammer shell, and the top of the top cover is fixedly connected with a mounting block; the locking connecting assembly is arranged on the inner surface of the heavy hammer shell and used for rapidly installing the heavy hammer. The fixed guide assembly is arranged at the top of the mounting block and used for fixing the polar line to the top of the heavy punch. According to the utility model, the cathode wire penetrates into the polar wire hole of the mounting block, the fixing belt is laid along the guide groove, and the bolt penetrates through the fixing belt and the connecting plug-in and is fixed on the mounting block. The adjusting holes are formed in the fixing belts, the positions of the fixing belts can be adjusted conveniently, it is ensured that the center of the counter weight is aligned with the center of the cathode wire, the bolts are locked through the fastening nuts, and the plug-in and the fixing belts are stably connected. According to the design, the cathode wires are accurately positioned, eccentric discharge is avoided, and the gas purification efficiency and stability are improved.

The application discloses a carbon mineralization plate production system coupled with flue gas and waste heat and a carbon cycle method, relates to the technical field of carbon mineralization plate production, and the production system comprises an industrial emission source module, a flue gas pretreatment and buffer module, a waste heat recovery and distribution module, a carbon mineralization plate production line adaptation module and an intelligent coupling control module, the industrial emission source module is used for monitoring flue gas data and performing prediction and data processing; the flue gas pretreatment and buffer module is used for purifying, dynamically conditioning and online detecting flue gas; the waste heat recovery and distribution module is used for waste heat graded recovery, phase change heat storage buffering and intelligent heat distribution network distribution; the carbon mineralization plate production line adaptation module is used for production line equipment modification adaptation, carbonization maintenance and plate conveying control; and the intelligent coupling control module is used for edge control and cloud analysis. The production system provided by the application can realize efficient utilization of industrial flue gas and waste heat resources.

The present application relates to a kind of resource utilization method of N2O in adipic acid tail gas, under the condition of not using catalyst, still can N2O in adipic acid tail gas is handled, and further production has industrial value nitric acid and will not cause impact to environment nitrogen and oxygen, in reaching to N2O in adipic acid tail gas is handled while generating economic benefits, and process is simple, N2O removal rate is high, stability is high, environment-friendly and resource utilization rate is high, tail gas catalytic treatment can also be substantially reduced the cost of processing.And the method of the present application can be continuously operated, can continuously solve adipic acid industrial tail gas emission problem, so that it reaches industrial emission standard, reduces the cost of enterprise processing tail gas, has important practical significance and engineering application value.

The invention discloses an atmospheric pollution source dynamic point source emission list construction method, system and device, a medium and a product, and relates to the field of environmental protection, and the method comprises the steps: collecting CEMS emission data, a regional grid list and meteorological data; identifying different chemical species in the atmospheric pollution source according to the emission data of the CEMS, and determining the pollutant type; for each pollutant type, calculating an hourly real-time monitoring emission rate according to emission data of the CEMS; the smoke plume lifting height is calculated according to the environment wind speed and CEMS emission data; the point source emission rate in the regional grid list is dynamically updated according to the hour-by-hour real-time monitoring emission rate, the smoke plume lifting height, CEMS emission data and meteorological data are combined, the dynamic point source emission list of the atmospheric pollution source is constructed, the dynamic change characteristics of actual emission along with time can be reflected, and the industrial emission process can be simulated more truly.

The invention provides an industrial emission cloth bag dust removal device based on multi-stage filtration, which belongs to the technical field of flue gas filtration equipment and comprises a filter box, an exhaust pipe and an air inlet pipe. Wherein a shaft pipe is arranged in the filter box, one end of the shaft pipe extends into the air inlet pipe, a plurality of blocking nets distributed in the length direction are arranged in the air inlet pipe, the blocking nets are connected to the shaft pipe, and the outer side of the air inlet pipe is sleeved with a magnet exciting coil capable of being electrified to generate a magnetic field. A plurality of blocking nets are arranged in the air inlet pipe, the outer side of the air inlet pipe is sleeved with the magnet exciting coil, the magnet exciting coil magnetizes the blocking nets in the air inlet pipe, magnetic substances (iron, nickel and cobalt) in gas are adsorbed on the blocking nets under the action of a magnetic field, the magnetic substances can be separated independently, the magnet exciting coil is closed at regular intervals, and therefore the magnetic substances can be separated independently. And magnetic substances on the barrier net are cleaned.

The present invention discloses a VOC room-temperature condensation treatment system and method utilizing the static activity of activated carbon, relating to the technical field of industrial VOCs treatment. The system comprises a VOCs pretreatment system, a desorption condensation system, an auxiliary adsorption bed C, an adsorption bed A, and an adsorption bed B; adsorption beds A and B are connected to an adsorption blower via an adsorption inlet valve; the adsorption blower is connected to the VOCs pretreatment system; adsorption beds A and B are connected to the atmosphere via an adsorption outlet valve; adsorption beds A and B are connected in series via series valves Ab and Ba; and the ends of adsorption bed A, adsorption bed B, and auxiliary adsorption bed C are connected to the ends of the desorption condensation system via desorption condensation valves. The treatment method using the system of the present invention fully utilizes the static activity of activated carbon, reduces the cost of activated carbon, extends its service life, and recovers organic solvents of high purity and high recovery efficiency. The "2+1" model simplifies the control strategy and makes operation more reliable.

This invention provides an industrial emission baghouse dust collector based on multi-stage filtration, belonging to the technical field of flue gas filtration equipment. It includes a filter box, an exhaust pipe, and an inlet pipe. The filter box contains a shaft tube, one end of which extends into the inlet pipe. The inlet pipe contains multiple barrier meshes distributed along its length, connected to the shaft tube. An excitation coil capable of generating a magnetic field is fitted onto the outer side of the inlet pipe. This invention, by setting multiple barrier meshes inside the inlet pipe and fitting an excitation coil on the outer side, magnetizes the barrier meshes. Magnetic materials (iron, nickel, cobalt) in the gas are adsorbed onto the barrier meshes under the influence of the magnetic field, allowing for individual separation of the magnetic materials. The excitation coil is periodically turned off to clean the magnetic materials from the barrier meshes.