122 results about "Atmospheric pollution" patented technology

This utility model relates to the field of detection equipment technology, specifically an air pollution detection device, including a connecting plate. Three sets of triangular legs are hinged to the outer surface of the connecting plate. A fixing plate is fixedly mounted on the upper end face of the connecting plate. A groove is formed on the upper end face of the fixing plate. A detection device base is provided on the upper side of the fixing plate. An inner cavity is formed inside the fixing plate, and a threaded rod is rotatably connected inside the inner cavity. The end of the threaded rod is helically connected to a threaded tube. This utility model, through its quick-installation structure, allows the detection device to be quickly and easily installed on a support device, effectively simplifying the traditional installation process, saving operation time, and significantly improving installation efficiency. Simultaneously, this structure enhances the connection stability between the device and the support, reducing data errors caused by loosening, thereby improving the accuracy and reliability of the detection work. It is suitable for air monitoring needs in various environments.

This invention relates to the field of air pollution monitoring technology and discloses an air pollution discrimination method and device based on machine learning. The method comprises the following steps: inputting pollution source attribute information and monitoring data from the first and second time periods into a pollution feature model to obtain pollution feature vectors; determining candidate pollution sources similar to the baseline pollution source type based on vector correlation; inputting the feature vectors of the candidate pollution sources and historical periodic monitoring data into a discrimination model trained with the baseline pollution source as a positive sample to obtain the pollution type discrimination result. The pollution feature model extracts multi-dimensional spatial distribution vectors from a spatiotemporal feature model to initialize the network layer and updates parameters dimensionally. The discrimination model combines dynamic monitoring data and feature vectors to achieve discrimination. The device includes units for feature generation, correlation analysis, and type discrimination. This solution improves the accuracy and efficiency of air pollution discrimination through multi-dimensional data fusion and model optimization.

This application discloses a method and system for determining pollution causes based on the correlation between atmospheric diffusion conditions and emission contributions, relating to the field of atmospheric pollution cause identification. The method includes: aligning meteorological, emission, and receptor observations to a unified spatiotemporal reference to obtain multi-source baseline data; calculating a diffusion stability index characterizing vertical mixing and horizontal transport using meteorological monitoring, generating time-varying diffusion condition weights; generating a time-response diffusion kernel from the emission source to the receptor point using a diffusion model under unit emission conditions, and constructing diffusion-contribution correlation information with observed concentrations to characterize the temporal coupling strength; establishing a diffusion-contribution dynamic optimization model, using diffusion condition weights to constrain the coupling relationship, and iteratively solving for time-varying contribution coefficients based on the convergence target of simulated and observed concentrations, outputting the dynamic contribution of each source and the pollution cause. Thus, time-varying diffusion conditions are explicitly introduced into the source contribution inversion framework, achieving stable separation and reliable attribution of source contributions.

This invention relates to the field of air pollution control technology, and in particular provides a microbial treatment system for high-concentration malodorous air pollution, including a purification tower. The purification tower has an inlet pipe at its bottom and an outlet pipe at its top. Inside the purification tower, from top to bottom, are arranged a microbial filling chamber, a filter plate, and a spray device. The bottom end of a rotating shaft extends to the bottom of the purification tower and is connected to a power unit. A gas collection cylinder is installed at the top of the rotating shaft. The gas collection cylinder passes upward through the filter plate and extends into the microbial filling chamber, and is fixedly connected to a rotating hood. An air inlet is provided along the axial direction of the section of the gas collection cylinder outside the bottom of the microbial filling chamber. Microbial material can fall evenly and continuously into the waste gas cavity, fully contacting the high-concentration malodorous waste gas, improving mass transfer efficiency and microbial degradation efficiency, and meeting the treatment needs of high-concentration malodorous pollution.

The present application relates to the field of environmental science and air pollution control technology, and discloses a method and device for dynamically estimating and quantifying the emission of volatile organic compounds of gas stations, which is based on the data of volatile organic compound emissions of gas stations and multi-source environmental data to construct data sets, input each data set into the corresponding initial prediction model to train the target prediction model, and calculate the single station emission prediction value through the target model; then, based on all single station prediction values, the input data error and model structure uncertainty are integrated and quantified, and finally the total emission of all gas stations and the corresponding uncertainty interval are calculated to realize the accurate prediction of the emission and the systematic quantification of the uncertainty, wherein through the multi-model training and uncertainty quantification, the present application not only realizes the accurate prediction of the emission of volatile organic compounds of gas stations and the calculation of the total emission, but also outputs the total emission uncertainty interval with reliable confidence level and quantifies the fluctuation risk of the prediction result.

The present application relates to the technical field of waste heat recycling, in particular to a method for converting industrial waste heat into low-pressure steam to drive ammonia adsorption refrigeration, comprising the following steps: Step 1: industrial waste heat collection and pretreatment, S1.1 waste heat classification collection: for different types of waste heat (slag waste heat, high-temperature flue gas, low-pressure steam, engine exhaust gas) in industrial production, special heat exchange devices are used for classification collection, wherein slag waste heat is recovered through indirect heat exchange devices; the present application efficiently recovers industrial low-grade waste heat and converts it into stable low-pressure steam of 0.3 MPa and above, and the waste heat utilization rate is increased to more than 85%; the refrigeration process does not consume high-grade energy, the main machine operates at zero cost, the comprehensive energy-saving rate is more than 77.8%, the annual electricity saving can reach 140,000 degrees per set, natural working substance ammonia is used as refrigerant, ammonia can be cyclically decomposed and compounded under natural conditions, and there is no greenhouse gas emission; fluorine-containing refrigerants such as freon are abandoned, atmospheric pollution is avoided from the source, and the green and low-carbon development trend is met.

This invention relates to the technical field of special equipment for air pollution environmental protection, and proposes an environmentally friendly petrochemical tail gas separation and treatment device. The device includes a shell, with a cyclone pre-separation chamber, a composite filtration chamber, and a fine filtration discharge chamber sequentially arranged from bottom to top along the airflow direction via partitions. A tail gas inlet pipe is fixedly connected to the bottom side wall of the shell, and a clean gas discharge pipe is fixedly connected to the top side wall. A cyclone guiding mechanism is installed in the cyclone pre-separation chamber; a condensation mechanism is fixed on the outer wall of the shell corresponding to the cyclone pre-separation chamber; a cylindrical filter element assembly is installed in the composite filtration chamber; and a pulse backflushing assembly is fixed on the top cover, with an electric heating mechanism fixed on the top cover to cooperate with the pulse backflushing assembly. This technical solution solves the problems of existing petrochemical tail gas treatment equipment having a single separation and purification stage, easy filter element clogging, and inconvenient maintenance and replacement, especially the backflushing structure easily interfering with filter element disassembly and assembly, affecting the continuous and stable operation of the equipment.

The application discloses a method for accurately evaluating the contribution of meteorological bias based on multi-technology integration of atmospheric pollutants simulation bias, which solves the technical problems of insufficient correlation and quantification of meteorological bias and pollution simulation bias, insufficient depth of bias analysis, and missing spatiotemporal contribution rule representation in the prior art. The WRF-CMAQ coupling mode is used to obtain meteorological and pollutant concentration simulation data, and combined with the observation data of the national control site, a standardized bias feature variable data set containing meteorological bias and pollutant concentration bias is constructed. The VIF factor is used to screen and eliminate parameter collinearity, and an XGBoost bias model is constructed to quantify the nonlinear correlation between meteorological bias and pollutant concentration bias. The SHAP model is introduced to analyze the contribution weight of each meteorological bias parameter. Combined with the spatiotemporal information of the site, the Kriging interpolation is used to generate the global spatiotemporal distribution atlas of the contribution of each meteorological bias parameter. The application provides a precise quantitative basis for the targeted optimization of the WRF meteorological field and the improvement of the simulation accuracy of atmospheric pollution.

The application provides a method for evaluating the risk of tuberculosis under the combined exposure of extreme weather and air pollution, comprising the steps of: obtaining meteorological data, air pollution data and tuberculosis incidence data of a target area within a target period; identifying extreme weather events based on the meteorological data, identifying air pollution events based on the air pollution data, and identifying combined exposure events based on the meteorological data and the air pollution data, wherein the combined exposure events are combinations of the extreme weather events and the air pollution events that occur within a time interval less than a preset threshold and are spatially co-located; based on the spatial co-location, constructing a regression model with the number of cases in the tuberculosis incidence data as the dependent variable and whether the combined exposure event occurs as the binary explanatory variable, and evaluating the influence of the combined exposure event on the risk of tuberculosis. The application realizes high-precision quantitative evaluation of the risk of tuberculosis under the combined exposure of extreme weather and air pollution, and provides a scientific basis for early warning and precise prevention and control.

This invention relates to the field of environmental monitoring and intelligent source tracing technology, and discloses a method and system for precise source tracing of small-scale atmospheric pollution sources based on complex mountainous terrain. The method includes: acquiring elevation data and monitoring coordinates; preprocessing the elevation data and performing particle displacement calculations to obtain diffusion path data; performing vector fusion calculations combining the slope characteristics of the elevation data and the diffusion path data to obtain path correction coefficients; constructing a backpropagation model based on the monitoring coordinates and the path correction coefficients to obtain a set of candidate routes; performing probability estimation and calculations on the candidate route set to obtain the theoretical contribution ratio; acquiring the actual monitored concentration; constructing a deviation objective function based on the theoretical contribution ratio; performing numerical partial derivative solutions and iterative position updates to obtain the final source location and confidence level. This method can achieve high-precision targeted source tracing of pollution sources in complex terrain.

This invention discloses a device for treating air pollution, relating to the field of air pollution technology. It includes a fixed mounting base plate, with a filtration box mounted on top of the base plate. The front end of the filtration box is equipped with a drain plug, an exhaust pipe, and an air inlet hood. The upper interior of the filtration box contains a particulate filter plate and a gaseous pollutant adsorption plate for air filtration. A storage tank is installed at the rear end of the filtration box. Movable liquid collection plates connected to the storage tank are located at both ends of the filtration box, and atomizing nozzles are installed inside the movable liquid collection plates. This invention addresses the problem that conventional treatment devices mostly only adsorb and then filter gases, which, while effective for most pollutants, increases the consumption of filter material. Furthermore, existing treatment devices are limited by their single-technology limitations and lack the ability to synergistically control pollutants.

This invention discloses an integrated desulfurization, denitrification, and dust removal device for air pollution control, belonging to the field of environmental protection equipment. The device has a tower-type structure, including a tower base, an integrated tower reaction chamber, and a dust removal operation box. The integrated tower reaction chamber, from bottom to top, is equipped with a high-temperature raw flue gas inlet, a flue gas lifting section, a primary reaction section, and a secondary reaction section. The flue gas lifting section is externally connected to a spray liquid inlet, whose supply end is respectively introduced into the secondary spray sections within the primary and secondary reaction sections, forming a double-layer spray structure. The top of the secondary reaction section has a dust-gas separation section that splits the airflow into filtered airflow and intercepted airflow. The filtered airflow is introduced into the secondary adsorption cylinder via a side-wing outlet component, while the intercepted airflow, after being treated in the dust removal operation box, also converges into the cylinder and is finally discharged through the exhaust pipe. This invention significantly improves removal efficiency, reduces operating energy consumption, enhances adaptability to operating conditions, and achieves ultra-low emissions of flue gas.

This invention relates to a method and system for measuring nitrogen oxide emissions from soil in the field using an extraction-absorption method, belonging to the field of environmental monitoring technology. A soil sampling unit is sealed and placed on the surface of the soil to be tested. Gas is extracted from the soil sampling unit by a power unit, causing outside air to replace the gas inside the soil sampling unit, forming an airflow flowing across the surface of the soil. The airflow is sequentially guided to a first absorption bottle, an oxidation bottle, and a second absorption bottle connected in series. The concentration of nitrite ions in the first and second absorption solutions is measured respectively. Based on the measured nitrite ion concentration, sampling flow rate, sampling time, and the area of ​​the soil covered by the soil sampling unit, the nitrogen oxide emission flux is calculated. This invention achieves stable, efficient, and low-cost offline quantitative measurement of nitrogen oxide emissions from soil in the field, providing reliable technical support for research on land-atmosphere exchange, soil nitrogen cycle, and atmospheric pollution source tracing.

The application relates to a SO4 based on deep cross network (DCN V2) feature enhancement and integrated learning 2‑ The concentration driving factor analysis method comprises the following steps: collecting time series data of atmospheric pollutant concentration and meteorological parameters in a target area, and performing pretreatment and quality control; a DCN V2 model integrating a linear cross network, an exponential cross network and a deep neural network is constructed to realize nonlinear high-order cross feature enhancement of original features; a two-layer Stacking integrated learning model taking XGBoost, LightGBM and CatBoost as heterogeneous base models and linear regression as a meta model is constructed, and global optimization is performed through Bayesian optimization; and the SHAP method is applied to quantify the marginal contribution and direction of each feature, and identify the key driving factors of SO4 2‑ concentration. The application integrates optimization strategies such as GPU acceleration, early stopping mechanism, automatic task detection, parallel training and backup training, realizes the automation, high efficiency and reproducibility of the analysis process, and guarantees the physical interpretability of the driving factor analysis, thereby providing scientific and technological support for atmospheric pollution prevention and decision-making.

The application discloses a filter bag replacement structure for a carbon black bag filter and a use method thereof, and belongs to the technical field of air pollution control. The technical key points of the application include a filter bag frame assembly and a quick release assembly. When treating flue gas generated in the production of carbon black, the flue gas can be introduced from the middle box first, then the flue gas can be filtered through the filter bag sleeved on the filter bag frame assembly, the filtered clean gas can be introduced into the upper box through the filter bag frame assembly, and then discharged from the device. When a large amount of carbon black particles are attached to the surface of the filter bag, the carbon black particles can be shaken off through the cooperation of the vibrating assembly and the pulse jet dust cleaning assembly. Before and after the filter bag needs to be replaced, the filter bag frame assembly can be stably arranged through the quick release assembly, and when the filter bag needs to be taken out, the filter bag can be conveniently replaced.

This invention relates to the field of atmospheric environment monitoring technology and discloses a high-precision method for predicting atmospheric pollutant concentrations based on machine learning. The key technical points are: multi-source data acquisition and correlation preprocessing, correlation feature engineering, adaptive data transformation, hybrid machine learning model construction, model optimization, and concentration prediction. A closed-loop technical solution is adopted, employing multi-source data correlation preprocessing, dynamic feature engineering, improved RBF kernel SVR-ELM hybrid model construction, and adaptive PSO optimization, to achieve high-precision prediction of hourly concentrations of different types of atmospheric pollutants, providing reliable data support for atmospheric pollution prevention and control and public health protection.

A carbon coordination-based air quality improvement optimization target determination method and device, medium and product, the method comprising: obtaining a carbon coordination-based air quality comprehensive index corresponding to each subordinate administrative unit; the carbon coordination-based air quality comprehensive index is related to the following parameters: carbon emission total amount control index, baseline year population weighted PM 2.5 concentration, PM 2.5 concentration reduction rate caused by atmospheric pollution end treatment; based on the carbon coordination-based air quality comprehensive index corresponding to each subordinate administrative unit, determine the air quality improvement optimization target corresponding to each subordinate administrative unit. The above scheme can realize the coordination of air quality improvement and carbon emission control target.

The present application relates to a kind of molecular sieve composite metal oxide catalyst and its preparation method and application in air pollution control.The catalyst is with surface aluminum-rich molecular sieve as carrier, in the carrier in situ growth two or more metal oxides and loading capacity and metal ratio can be adjusted;Wherein, the surface aluminum-rich molecular sieve surface aluminum element concentration adjustable and higher than the bulk phase aluminum element concentration, to induce electron from surface aluminum-rich molecular sieve to metal oxide transfer at the interface of surface aluminum-rich molecular sieve and in situ growth metal oxide, form electron-rich metal-oxygen-metal (M-O-M) active site.Compared with prior art, the present application provides a kind of preparation method of molecular sieve composite metal oxide catalyst based on interface electronic structure regulation, the catalyst prepared by the method can effectively improve the catalytic purification efficiency of NO x And VOCs etc. Pollutants at low temperature in air pollution control.

The application discloses a kind of high sensitivity optical systems based on optical waveguide, it is related to environmental monitoring field, including: light source module, for emitting middle infrared waveband preset wavelength laser;Coupling air chamber module, for the laser of light source module operation emission is coupled into calcium fluoride-based optical waveguide;Gas sensing modulation module, for after containing pollutant atmosphere sample is sent into air chamber by micro flow pump at constant speed by gas inlet, sense light signal carrying pollutant information;Optical signal processing module, for amplifying and screening processing to light signal carrying pollutant information;Detection module, for obtaining the light signal of optical signal processing module operation processing, light signal is quickly and accurately converted into digital electrical signal;The application can efficiently sense pollutant information by accurately corresponding pollutant characteristic absorption peak, cooperate micro flow pump and gas sensing modulation module, provide intuitive, accurate data support for environmental protection workers, help precise management air pollution, protect ecological environment.

The application discloses a sewage treatment chemical deodorization device, which comprises a sewage treatment tank and a stench treatment cylinder, the sewage treatment tank is sequentially divided into a dosing premixing area, a communicating area, a mixed flow area and a mixing area from top to bottom, the sewage treatment tank is internally provided with a sewage inlet, a dosing barrel for adding chemicals into the dosing premixing area is arranged on the top of the sewage treatment tank, the dosing barrel is communicated with the dosing premixing area through a chemical injection pipe, a chemical injection pump is connected to the chemical injection pipe, a plurality of flow guide pipes are fixedly connected between the bottom edge of the mixed flow area and the mixing area in the circumferential direction, sewage treatment, chemical injection, stench collection and stench chemical purification are integrated, sewage deodorization and tail gas deodorization are simultaneously performed, volatile stench in the tank is collected through a gas collecting hood, negative pressure closed conveying is adopted, unorganized diffusion of the foul gas is avoided in the whole process, atmospheric pollution around is reduced, the working environment is improved, and the environmental protection performance is high.

The present application relates to a kind of dual optical path nitrogen dioxide measurement system and method based on blue laser, using dual-wavelength laser cavity enhanced absorption spectroscopy technology, carries out NO2 absorption measurement under 405nm and 410nm wavelength, and combined with high reflectivity optical resonator, improve detection precision and sensitivity.Through dual-wavelength comparison method, using dual-wavelength absorption spectroscopy analysis, calculate absorbance difference, to effectively eliminate the influence of environmental factors on measurement accuracy, improve measurement reliability.Using more than 99.9% high reflectivity mirror, to realize high reflectivity optical resonator enhancement technology, laser is reflected in resonator multiple times, optical path is extended hundreds of times, improve NO2 absorption signal intensity, realize ppb grade ultra-low concentration measurement.Compared with traditional optical method, the system has lower cost, higher accuracy and stronger environmental adaptability, provides an efficient, stable solution for atmospheric pollution monitoring.

The application provides a data analysis method and device, an electronic device and a storage medium, and belongs to the technical field of atmospheric environment monitoring and data analysis. The method comprises the following steps: acquiring multi-source atmospheric data of a target region in a current preset time period; simulating an atmospheric pollutant concentration field of the target region based on the multi-source atmospheric data and through a pre-trained physical mechanism embedded graph neural network model to obtain a simulated concentration field; when an atmospheric pollutant concentration value of at least one monitoring node in the simulated concentration field is greater than a preset abnormal threshold, determining that there is an atmospheric pollutant concentration abnormality in the target region at the current moment; in response to the determination that there is the atmospheric pollutant concentration abnormality, performing reverse attribution calculation and analysis based on the physical mechanism embedded graph neural network model to determine at least one emission source category causing the atmospheric pollutant concentration abnormality and the contribution degree of the at least one emission source category. The application can improve the accuracy of atmospheric pollution abnormality determination and quantify the contribution degree of an emission source.

The present application relates to the field of environmental protection and air pollution control technology, especially to an energy-saving and environment-friendly type bag type dust collector timing blowback ash removal system and method, the method comprising: establishing aerodynamic reference frame, anchoring clean resistance benchmark; Perform flexible unloading, make softening window by reducing the frequency of induced fan, cooperate with pulse valve to prevent ash removal; Capture the resistance drop trajectory after ash removal and extract the rate characteristics; According to the characteristics, adaptively reconstruct the parameters, dynamically adjust the ash removal span and unloading depth of the next period, and assist the deterioration blocking mechanism to ensure safety. The system includes filter and gas source array, negative pressure and flexible adjustment, resistance high frequency sensing and cooperative decision master control units. The present application solves the problems of high energy consumption, incomplete ash removal and short filter bag life caused by airflow resistance in traditional ash removal, realizes closed-loop adaptive control of pure physical feedback, and provides an energy-saving and environment-friendly type bag type dust collector timing blowback ash removal system and method.

A PM2.5 prediction system and method based on dynamic weighting and anomaly correction are proposed, relating to the interdisciplinary fields of air pollution control and intelligent environmental monitoring. The PM2.5 prediction system based on dynamic weighting and anomaly correction includes, from front to back, a data preprocessing module, an adjacency matrix construction module, a spatiotemporal graph construction module, a spatial feature extraction module, a spatiotemporal feature fusion module, and an outlier adaptive correction module, all connected in a data flow. The outlier adaptive correction module and the spatiotemporal graph construction module are connected in a data flow. The PM2.5 prediction method based on dynamic weighting and anomaly correction comprises the following steps: data input and preprocessing; construction of a dynamically weighted adjacency matrix; spatiotemporal graph construction and spatial feature extraction; multimodal spatiotemporal feature fusion; and outlier adaptive correction. This invention dynamically fuses three types of weights using trainable coefficients, enabling the model to automatically learn the importance of spatial proximity, meteorological conditions, and pollutant correlations under different scenarios.

The application provides a catalyst for synergistically removing toluene and NOx, a preparation method and application thereof, and belongs to the technical field of atmospheric pollution control. The catalyst comprises a MnCuTi mixed oxide, has a particle size of 250-380 mu m, a specific surface area of 155.10-164.25 m 2 / g, a pore volume of 0.270-0.281 cm 3 / g, and an average pore size of 6.672-6.951 mm. The preparation method comprises the following steps: mixing copper nitrate, manganese nitrate solution, deionized water and glacial acetic acid with ethanol to obtain solution A; dissolving tetrabutyl titanate in ethanol to obtain solution B; adding solution B into solution A drop by drop under stirring to form a sol and continuing to stir; aging, drying, grinding and calcining; and tabletting and sieving to obtain the catalyst. The catalyst is used for synergistically removing toluene and NOx, has low raw material cost, simple and controllable preparation process, strong repeatability, good catalytic activity and high selectivity.

The application provides an atmospheric pollution treatment device and a method for preparing a lithium battery negative electrode material. The application relates to the field of atmospheric pollution treatment, and the atmospheric pollution treatment device comprises a ground-mounted introduction mechanism. The atmospheric pollution treatment device and the method for preparing the lithium battery negative electrode material can effectively delay the exhaust gas flow rate to stabilize the gas volume through the lower baffle and the upper baffle staggered arranged in the introduction pipe. The solid particle impurities generated in the calcination process are deposited at the bottom of the pipe. The activated carbon box is used for removing peculiar smell and adsorbing tiny particles. The exhaust gas flows through the porous filler balls stacked on the filler tray. The alkali solution is lifted to the water spraying pipe by the circulating pump and is uniformly sprayed downward, so that the alkali solution and the hydrogen fluoride gas in the rising exhaust gas are contacted on the surface of the filler balls and neutralization reaction occurs, the efficient removal of hydrogen fluoride is realized, the alkali solution is recycled to reduce the cost, the hierarchical and collaborative treatment of the solid particles, peculiar smell and hydrogen fluoride in the calcination exhaust gas is realized, and the environmental protection level is significantly improved.

This invention discloses a method and system for locating and analyzing atmospheric pollution sources based on monitoring stations, belonging to the field of environmental monitoring and pollution source apportionment. The method involves acquiring pollutant concentration sequences and spatial coordinates of monitoring stations; extracting the main disturbance characteristic parameters of each station to construct a disturbance time-series vector and a propagation delay matrix; generating a candidate vector set of pollution propagation paths based on the relationship between delay and space, and performing path consistency assessment to select the path with the highest coherence; combining meteorological data to infer the initial location of the pollution source; establishing a local anti-diffusion model based on the estimation results; reconstructing concentration data from neighboring stations; and verifying the effectiveness of source location through error feedback. This invention can achieve high-precision identification of pollution source locations in complex pollution scenarios, possessing technical advantages such as strong timeliness, high adaptability, and verifiable location results.