38 results about "Ozone pollution" patented technology

The invention provides an ozone pollution tracing method and device, computer equipment and a storage medium, and belongs to the field of environment monitoring, and the method comprises the steps: obtaining the concentration data of volatile organic pollutants in a target area; performing positive definite matrix factorization on the concentration data to obtain a component spectrum matrix and a contribution matrix of each pollution source, and matching the component spectrum matrix and the contribution matrix based on a preset pollution source; respectively carrying out one-by-one reduction simulation on each pollution source, calculating the ozone net generation rate after reduction of different pollution sources, and calculating the relative increment reaction activity coefficient of ozone after reduction of a single pollution source; according to the pollutant concentration and the relative increment reaction activity coefficient corresponding to different pollution sources, calculating the contribution rate of each pollution source to ozone generation, and taking the pollution source with the maximum contribution rate as the main source of ozone. Therefore, by analyzing and simulating the components of the volatile organic pollutants and controlling the variables to reduce the pollution sources one by one, the ozone can be automatically traced.

The invention relates to the technical field of environmental monitoring and atmospheric pollution early warning, in particular to a Yangtze River Delta composite extreme weather ozone pollution early warning model construction method, which comprises the following steps of S1, acquiring high-resolution meteorological data and pollutant concentration data of a Yangtze River Delta region to form an original data set; and S2, carrying out missing value interpolation and abnormal value elimination on the meteorological data and the pollutant data, and carrying out grid alignment according to time and space to generate a unified spatial-temporal characteristic matrix. According to the method, by collecting Yangtze Delta high-resolution weather and pollutant data, performing data cleaning, bimodal feature coding and joint representation modeling, predicting the ozone concentration and generating regional early warning through multi-layer Transform self-adaptive attention, the problems that traditional ozone early warning mostly depends on a single-modal prediction model, and the reliability of the ozone early warning is greatly improved are solved. And due to the lack of multi-modal space-time dependent capture, the problem of early warning information lag is caused.

The invention relates to the technical field of atmospheric environment intelligent treatment, and discloses an ozone pollution dynamic prediction and control area discrimination method and system based on mixed symbol-numerical reasoning. The method comprises the following steps: constructing a knowledge graph oriented to the atmospheric photochemical reaction field, wherein the knowledge graph comprises chemical species nodes and edges with temperature-irradiance dependent reaction rates; taking the knowledge graph as a chemical kinetics constraint, taking real-time monitoring data as input, guiding the large model to carry out end-to-end prediction on the ozone peak concentration, and introducing a chemical kinetics consistency penalty term; reversely updating the reaction rate weight in the knowledge graph based on the prediction error and the residual error of the observation value to form a closed-loop optimization mechanism; and judging whether the current atmospheric environment belongs to a VOC control region, a NOx control region or a transition region by combining the uncertainty of large model prediction and the VOC dominant reaction path confidence of the knowledge graph. According to the invention, credible discrimination of ozone generation dominant factors on the principle level is realized.

This invention discloses a method for predicting mixed PM2.5 and ozone pollution at high spatiotemporal resolution, comprising the following steps: first, using historical air quality data as the dependent variable and the driving factor data corresponding to the historical air quality data as the independent variable, to obtain the optimal PM2.5 concentration. 2.5 A model for predicting ozone concentration was developed, and then significantly correlated driving factors were extracted using a hexagonal grid as the prediction unit, which were then input into the PM2.5 concentration prediction system. 2.5 In ozone concentration prediction models, PM2.5 concentrations are obtained at high spatiotemporal resolution. 2.5 The ozone concentration spatial distribution prediction map and the ozone concentration spatial distribution prediction map are then intersected spatially to obtain the PM2.5 concentration. 2.5 A prediction map of mixed pollution with ozone. The prediction method of this invention has advantages such as good applicability and high reliability, and can accurately predict PM2.5. 2.5 When mixed with ozone, the concentration of PM2.5 in the atmosphere... 2.5 It has important guiding significance for the prevention and control of ozone, has high application value, and has good application prospects.

The invention discloses in-situ polymerization low-temperature curing ink-jet ink which comprises ink A and ink B. The ink A at least comprises an initiator and deionized water, and the ink B at least comprises a sensitizer, a carbon-carbon double-bond water-soluble monomer, a carbon-carbon double-bond resin water-based dispersion and deionized water. The persulfate initiator in the ink A generates free radicals under the action of the ferrous sulfate sensitizer in the ink B, the free radicals initiate in-situ polymerization reaction to form a polymer network structure, pigment is firmly fixed to the surface of fiber, it is ensured that the initiator and the sensitizer start to react only when making contact, and the color fastness of the pigment is improved. The problem that the ink is unstable in the storage process is solved, and the curing speed is high. According to the invention, the use of an ultraviolet lamp is avoided, and light pollution and ozone pollution generated by the ultraviolet lamp in the environment are reduced. And compared with a UV photoinitiator with aromatic groups, a product obtained by reacting the applied persulfate is safer to a human body, and the method is a more environment-friendly printing scheme.

The invention discloses a park scale air quality mode chemical mechanism improvement method for improving ozone simulation capability, and belongs to the technical field of ozone pollution treatment. The method comprises the following steps: by introducing a VOCs related reaction path, enriching a kinetic equation of ozone generation, so that the model can describe a more complex atmospheric chemical process. Theoretically, the reaction items of the model are more comprehensive, and the ozone simulation requirements under different pollution scenes can be met. Through introduction of VOCs, key links in a NOx-O3 reaction chain can be supplemented, and the adaptability and predictive ability of the model to the actual atmospheric environment are improved. And the model structure is improved, so that the simulation result has a more scientific basis. Due to the fact that emission characteristics of VOCs in different regions and time periods are greatly different, the applicability of a traditional model is limited. According to the model, the reaction rate can be dynamically adjusted according to the actual emission condition of VOCs, and the model is suitable for various atmospheric environments and has a wider application prospect.

The invention discloses an ozone concentration daily value prediction method fusing radiation quantity and multiple meteorological factors, and the method comprises the steps: constructing a photochemical activity index representing an ozone photochemical generation process, and introducing a time lag characteristic and a radiation-driven dynamic weight adjustment mechanism; therefore, the model can effectively describe the nonlinear response relation to solar radiation in the ozone generation process and the synergistic effect of meteorological factors. Compared with a traditional prediction method based on a single meteorological factor, the method has higher accuracy and stability in the aspects of ozone concentration change trend, peak value identification and high value interval prediction; meanwhile, prediction errors under different radiation conditions are further reduced through a segmented correction mechanism, so that the generalization ability and engineering applicability of the model are integrally improved, and reliable technical support can be provided for ozone pollution early warning and atmospheric environment management.

This invention discloses an ozone forecasting method based on multi-model fusion, which consists of the following steps: data preprocessing, feature engineering, model training, model evaluation, model prediction, and model correction. This process ultimately yields reliable ozone prediction results. This method is easy to operate, data acquisition is readily available, and it does not require the collection of large amounts of precursor pollutant emission data. It can predict most ozone pollution conditions using only meteorological data, significantly improving prediction accuracy and compensating for the large biases in predictions based on a single model.

The invention provides a method and system for quantifying the influence of lake surface reflection on ozone generation, and relates to the technical field of atmospheric environment monitoring and evaluation.The method comprises the steps that measuring equipment is synchronously arranged at a lake body and a land contrast point, and reflected radiation and meteorological chemical parameters are collected; carrying out calibration, interpolation and abnormal value processing on the data; calculating the albedo of the lake surface and the additional radiation flux relative to the standard underlying surface; calculating a nitrogen dioxide photolysis frequency increment based on the additional radiation flux; a photochemical box model is used for simulating an atmospheric chemical reaction, the species concentration is updated through a time stepping method, and finally the ozone generation increment caused by lake surface reflection is obtained. A unit albedo contribution coefficient is further defined, and quantitative evaluation of the influence of lake surface reflection on ozone generation is achieved. The method overcomes the defect that in the prior art, the lake surface specular reflection enhancement effect is ignored, the contribution of lake surface reflection to ozone generation can be accurately quantified, and a scientific basis is provided for accurate prediction and prevention and treatment of ozone pollution.

The application discloses an ozone pollution hierarchical cause analysis method and system based on double-index joint threshold division, wherein the ozone pollution hierarchical cause analysis method based on double-index joint threshold division comprises the following steps: data acquisition and preprocessing; according to the preprocessed data, double-index joint threshold division is performed; according to the result of double-index joint threshold division, a hierarchical cause analysis model is established; and according to the output result of the hierarchical cause analysis model, early warning mapping is performed. Through double-index joint threshold division, the application solves the limitation of single-index determination, realizes accurate subdivision of over-standard types, and realizes full-process automatic operation, shortens response time, and greatly improves decision-making efficiency. The application reduces the decision threshold through visual design, effectively reduces the number of ozone pollution days through early warning mapping, optimizes the allocation of governance resources, and has significant practical value and popularization significance.

The present application belongs to the technical field of ecological environment protection, and provides a method for purifying ozone in air by phyllosphere microorganism and plant in cooperation. The method comprises the following steps: preparing a culture medium by taking plant leaf extract and potato starch wastewater as main raw materials, culturing phyllosphere plant growth promoting bacteria, preparing a plant growth promoting bacteria inoculum, inoculating the plant growth promoting bacteria on plant leaves, and uniformly placing the potted plants inoculated with the plant growth promoting bacteria in an ozone-polluted room. The method can achieve the effect of purifying air by phyllosphere microorganism and plant in cooperation. The method utilizes the synergistic effect of phyllosphere microorganism and plant, has high ozone purification efficiency in air, is simple to operate, environment-friendly, low in cost, and has wide application prospect.

The invention relates to a normal-temperature high-water-resistance ozonolysis catalyst and a preparation method and application thereof, the catalyst is of a composite oxide-heterojunction structure of Ni < 1-x > CexO-CeO2, and 0 lt; xlt; and 0.1. Dissolving soluble Ce salt and Ni salt in water to obtain a mixed solution, dropwise adding the obtained mixed solution and a precipitant into a reactor together, maintaining the constant pH value to be 9-11, and aging at a constant temperature to obtain a mixed precipitate; and filtering, washing and drying the obtained mixed precipitate, and then calcining in an air atmosphere to obtain the Ni < 1-x > CexO-CeO2 catalyst. Compared with the prior art, the catalyst is simple to prepare, high in water resistance, good in stability, good in ozone purification effect and suitable for large-scale industrial production. The catalyst can be applied to the fields of near-surface low-concentration ozone pollution purification or ozone decomposition in a closed space and the like.

The invention provides an ozone pollution assessment method based on SHAP-IPSO-CNN. The ozone pollution assessment method is used for assessing high accuracy and high interpretability of ozone pollution in a chemical industrial park. The method comprises the following steps: firstly, predicting the distribution concentration of volatile organic compounds discharged by enterprises in a park in a target monitoring station by using an atmospheric diffusion model, and forming model input characteristics by the distribution concentration, the concentration of other pollutants in the target monitoring station and meteorological factors; then, three different machine learning models are considered for deep comparison and preferential SHAP analysis, and a feature importance queue is established by using an SHAP analysis result. Then, an improved particle swarm optimization algorithm is combined with the feature importance of SHAP analysis, and training features are dynamically adjusted to optimize the performance of the CNN model. According to the integrated model, by combining the efficient feature extraction capability of a convolutional neural network (CNN), the global search optimization characteristic of an improved particle swarm optimization (IPSO) algorithm and the explanation capability of SHAP analysis, the influence evaluation on ozone formation is realized. The method provided by the invention has high reliability and application prospect under complex conditions.

The invention discloses a method for analyzing the influence of low-carbon traffic on ozone pollution by considering public participation. The method comprises the following steps: S1, collecting low-carbon traffic development level data, ozone pollution treatment level data and public participation degree data of a target area; s2, carrying out standardization processing on the collected data, and calculating a comprehensive value of low-carbon traffic, ozone pollution and public participation; s3, constructing an intermediary model by taking the comprehensive value as an input variable; s4, under the framework of the intermediary model, checking the direct effect of low-carbon traffic on ozone pollution, the action effect of public participation on low-carbon traffic and ozone pollution and the intermediary effect of public participation; and S5, quantifying the intermediary effect degree of the public participating in the influence of low-carbon traffic on ozone pollution. The method not only can quantify the relationship between low-carbon traffic development and ozone pollution treatment, but also can reveal the intermediary effect in which the public participates, and provides support for formulating a more scientific and effective environmental strategy.

The invention discloses a GAT-xLSTM-based ozone concentration long-term prediction method, and relates to the technical field of environmental air quality monitoring and prediction. Firstly, air quality data and meteorological data of a monitoring station are collected and preprocessed, and a reference data set is constructed. By constructing the GAT-xLSTM model, medium and long term accurate prediction of the ozone concentration is realized. The method comprises the following steps: constructing a space-time diagram structure of multi-source heterogeneous data, and extracting spatial correlation characteristics between monitoring stations by using GAT; separating a trend item and a seasonal item in the time sequence through a seasonal trend decomposition technology, and carrying out time feature modeling on the seasonal item by adopting xLSTM; and fusing prediction results of the spatial features and the time features, and outputting a final ozone concentration prediction value. According to the method, the problems of insufficient space-time correlation capture and too fast error accumulation in long-term prediction of a traditional model are solved, the medium-and-long-term prediction precision is remarkably improved, and technical support can be provided for ozone pollution prevention and control.

This invention discloses a method and apparatus for precise source tracing and analysis of atmospheric ozone pollution. Based on the concentration data of each VOC species among multiple species monitored at ambient air quality monitoring stations, the ozone generation potential of each species is determined; the ozone generation reactivity of each species is determined; key VOC species for ozone generation are screened based on both ozone generation potential and ozone generation reactivity; mobile VOC monitoring is conducted around the ambient air quality monitoring stations, and automatic offline sampling and laboratory analysis are performed at high-value TVOC sites; key pollution sources for ozone generation at the ambient air quality monitoring stations are identified and subject to control. This invention provides a more comprehensive analysis of atmospheric ozone pollution, accurately identifying specific pollution sources and better providing technical support for environmental management.

The invention relates to the technical field of air purification, in particular to an ozone-free and static-free hydrated negative oxygen ion generating device and method. The device comprises a base, a supporting shell, a fixing shell, a connecting shell and an exhaust cover, a mounting plate and a control box are arranged in the base, a water tank is mounted in the supporting shell, the top of the water tank is in threaded connection with a sealing cover, an exhaust hole is formed in the top of the water tank, and an atomizer is arranged in the water tank; the ultrasonic atomization and induction charge coupling design is adopted, ozone pollution and electrostatic hazards caused by traditional corona discharge are eliminated, and the safety characteristics of zero ozone and no electrostatic leakage are achieved; charge strengthening is carried out on micron-sized water mist through the non-contact induction coil, the technical bottleneck that pure water power negative ion generation concentration is low is effectively broken through, hydrated negative oxygen ions can be stably output, and the device is suitable for various closed space air purification scenes.

This invention provides a quantitative method and system for assessing the impact of lake surface reflection on ozone formation, relating to the field of atmospheric environmental monitoring and assessment technology. The method includes: simultaneously deploying measuring equipment at both the lake surface and a land control point to collect reflected radiation and meteorological chemical parameters; calibrating, interpolating, and processing outliers on the data; calculating the lake surface albedo and the additional radiative flux relative to the standard underlying surface; calculating the nitrogen dioxide photolysis frequency increment based on the additional radiative flux; simulating atmospheric chemical reactions using a photochemical box model and updating species concentrations via a time-stepping method to ultimately obtain the ozone formation increment caused by lake surface reflection; further defining a unit albedo contribution coefficient to achieve a quantitative assessment of the impact of lake surface reflection on ozone formation. This invention overcomes the shortcomings of existing technologies that neglect the enhancement effect of lake surface specular reflection, accurately quantifying the contribution of lake surface reflection to ozone formation, and providing a scientific basis for precise forecasting and prevention of ozone pollution.

The application discloses an ozone concentration long-term prediction method based on GAT-xLSTM, and relates to the technical field of environmental air quality monitoring and prediction. First, air quality data and meteorological data of monitoring stations are collected and preprocessed to construct a benchmark data set. Through the construction of a GAT-xLSTM model, the medium and long-term accurate prediction of ozone concentration is realized. The steps include: constructing a space-time graph structure of multi-source heterogeneous data, using GAT to extract the spatial correlation features between monitoring stations; separating the trend term and the seasonal term in the time series through the seasonal trend decomposition technology, and using xLSTM to model the time characteristics of the seasonal term; fusing the spatial feature and the time feature prediction results to output the final ozone concentration prediction value. The application solves the problems of insufficient capture of space-time correlation and rapid accumulation of errors in the long-term prediction of traditional models, significantly improves the medium and long-term prediction accuracy, and provides technical support for ozone pollution prevention and control.

This application discloses a method, apparatus, equipment, medium, and product for identifying dominant meteorological factors of ozone pollution, relating to the field of ozone pollution analysis. The method comprises preprocessing ozone pollutant concentration data and meteorological factors to obtain daily ozone averages and meteorological factors matching the pollutant concentration data, and performing time series decomposition using a KZ filter to obtain baseline components of ozone and meteorological factors; decomposing the baseline components of ozone and meteorological factors using a first machine learning model and a KZ filter to obtain long-term components related to ozone emissions; determining long-term components related to ozone meteorology based on the long-term components related to ozone emissions; and determining dominant meteorological factors based on the long-term components related to ozone meteorology and meteorological factors using a second machine learning model and a SHAP algorithm. This application can reduce computational costs and improve identification efficiency.

The utility model relates to the technical field of procyanidine processing, in particular to a raw material sterilization device for extracting procyanidine, which comprises a sterilization box, a sealing door is arranged on the side surface of the sterilization box, a visual window is arranged at the center of the side surface of the sealing door, and a handle is fixedly welded on the side surface of the sealing door. Anti-skid supporting legs are fixedly welded to the bottom surface of the sterilization box, an air heater is fixedly connected to the inner wall of the sterilization box, and an ozone generator is fixedly connected to the top surface of the sterilization box. Efficient sterilization and drying treatment of materials is achieved through the synergistic effect of ozone and hot air, ozone generated by an ozone generator is evenly input into the device through multiple stages of pipelines, and the materials make full contact with the ozone in combination with a dynamic turning structure driven by a rotating motor, so that the sterilization rate of the materials is increased, and the drying efficiency is improved. After sterilization, the hot-air blower is used for circularly drying the internal materials, and residual ozone in the device is synchronously decomposed, so that the ozone is prevented from polluting the environment.

The invention relates to a microwave photochemical multiple efficient sterilization and disinfection system, which can simultaneously sterilize and deodorize odor and bacteria-containing water, and can simultaneously generate microwaves, ultraviolet rays, ozone and hot air through a fan, a waveguide tube, a microwave net and a quartz light-emitting tube. The generated ozone amount is 2-3 times that of an ozone generator with the same power; the intensity of microwaves and ultraviolet can be adjusted according to the characteristics of bacteria-containing water, scrap iron serves as a photocatalytic oxidation catalyst and is integrated with microwave, ultraviolet, ozone and hot air, the sterilization and inactivation efficiency is higher, and the cost is lower; according to the drop type spray tower, ozone and hot air are mixed with bacteria-containing water, and the ozone is fully utilized to pre-sterilize the bacteria-containing water and react with the ozone; tail gas containing a small amount of ozone is introduced into the activated carbon box loaded with the catalyst through the fan, so that the sterilization efficiency is improved, no ozone is discharged while activated carbon is regenerated, and no ozone pollution is ensured.

The invention discloses an ozone concentration forecasting method, which utilizes air quality observation data of 326 cities throughout the country, processes abnormal and missing data, and reanalyzes relative humidity, precipitation, boundary layer height, short-wave radiation, sea level air pressure, wind direction, wind speed and dew point in the data in combination with ERA5. A high-quality database used for supporting deep learning is established, graph structures are established with cities and provinces as nodes respectively, and the spatial dependency relationship between the nodes is adjusted in a self-adaptive mode through a dynamic learnable edge weight mechanism; self-adaptively updating the edge weight according to the input spatio-temporal characteristics, and further quantifying and analyzing the propagation path of ozone among different regions; and key meteorology and precursor factors are dynamically identified through a channel attention mechanism. According to the invention, the accuracy and real-time performance of ozone forecasting are improved, and transmission paths and driving factors thereof between regions can be disclosed; and scientific basis and technical support are provided for ozone pollution prevention and control and regional joint prevention and joint control.

The application discloses an ozone pollution cause path construction method based on causal inference, which comprises the following steps: step 1) taking the conventional influencing factors in ozone pollution cause analysis as explanatory variables of the ozone pollution cause path; step 2) performing significance test on each explanatory variable and defining confounding explanatory variables; step 3) determining key explanatory variables and intermediate variables by using Granger causality test, and initially building an intermediate path; step 4) performing test and correction on the intermediate path; step 5) determining a regulating variable by performing group difference test, and initially building a regulated intermediate path; and step 6) performing statistical test and correction on the regulated intermediate path, and evaluating the regulating effect of the regulating variable on the intermediate path. The ozone pollution cause path construction method provides theoretical guidance for clarifying the ozone pollution formation mechanism under a complex pollution system and proposing effective and feasible ozone pollution prevention and control measures.

The present application relates to a kind of preparation method of ambient temperature high humidity ozone decomposition catalyst and its application, the catalyst is synthesized by simple rheological phase method, mainly using Co and Mn to form double metal oxide.The optimal performance catalyst obtained can realize the removal efficiency of nearly 100% to ozone under ambient temperature high humidity condition, and keep stable and efficient operation at least 100h.The method is not only energy-efficient, short steps, and green pollution-free, except water does not use any surfactant or template and other polluting solvents.The catalyst can be widely used in various low concentration ozone pollution sources, such as air purifier, sterilization cabinet, printer, and ultraviolet photolysis and other end ozone decomposition.

The invention discloses an ozone control area identification and diagnosis method and system based on multi-source satellite data. The method comprises the following steps: constructing a standardized long sequence data set; representing the regional ozone weekend effect by adopting an ozone weekend-weekend absolute difference; establishing a linear regression model of the HCHO / NO2 ratio and the regional ozone weekend effect according to the standardized long sequence data set and the regional ozone weekend effect, and obtaining a regional adaptive HCHO / NO2 key threshold interval through the linear regression model; and according to the standardized long sequence data set, identifying the trend characteristics of the HCHO / NO2 ratio, and according to the trend characteristics of the HCHO / NO2 ratio and the regional HCHO / NO2 key threshold interval, carrying out diagnostic analysis on the evolution type of the ozone control region. By establishing a regional dependent HCHO / NO2 key threshold system and combining with analysis of HCHO / NO2 trend turning points, accurate identification and diagnosis of global 30-year ozone control region space-time evolution conditions can be realized, and a reliable basis is provided for monitoring, prevention and treatment of global ozone pollution.

The invention discloses an ozone pollution real-time traceability analysis platform, and particularly relates to the field of environment monitoring and pollution traceability, and the platform comprises a data collection module which comprises an ozone sensor unit, a meteorological data collection unit and a data preprocessing unit; the ozone sensor unit monitors the ozone concentration in the air in an electrochemical or ultraviolet light or optical sensing mode. By introducing a traceability analysis unit based on the combination of a physical model and a machine learning algorithm, the position of an ozone pollution source can be accurately identified and tracked, and a pollutant diffusion path is simulated; the diffusion trend of pollutants is deduced in real time by using a Gaussian diffusion model and combining meteorological data such as wind speed and temperature parameters; through the dynamic analysis method, the problem of inaccurate traceability caused by lack of dynamic combination of space and time in a traditional monitoring method is solved, and the pertinence of pollution treatment is remarkably improved.