13358results about "Air quality improvement" patented technology

The invention provides a particulate matter and ozone source monitoring method and system based on a distributed sensor, and relates to the technical field of pollution treatment. According to the invention, sensor nodes with geographic perception capability are deployed in a monitoring area in a high-density manner, pollutant concentration and meteorological parameters are collected in real time, and data are uploaded to a cloud platform for preprocessing and dynamic calibration; a machine learning model is constructed based on the combined features of the pollutants and the meteorological factors, a driving relation is mined, and pollutant influence factors are extracted; further performing joint modeling on the influence factors and regional emission source data, identifying the coupling strength between pollutants and emission sources by adopting a classification or clustering method, and judging the categories of main sources; backward trajectory simulation, source fingerprint analysis and multi-source regression decomposition are combined to realize pollution path inversion and source contribution rate quantification; and finally, constructing a geographic information visualization platform, displaying a pollution thermodynamic diagram, a contribution change diagram and an evolution path diagram, and providing support for multi-source pollution traceability and scientific management and control.

The invention discloses an electronic nose system for monitoring indoor air quality. The electronic nose system comprises a vacuum pump assembly, a flowmeter assembly, a two-position three-way valve assembly, a two-position two-way valve assembly, a reaction chamber, an air inlet and an air outlet. The system can be switched into different channels by adjusting the vacuum pump assembly, the flow meter assembly, the two-position three-way valve assembly and the two-position two-way valve assembly, then the flow direction and the flow speed of standard gas and sampling gas are controlled, a reaction chamber with a sensing chamber array is connected into the channels, and calibration of the system and detection of the gas are achieved.

The invention provides a medical waste whole-process supervision method based on an intelligent medical waste monitoring platform, and the method comprises the steps: enabling collected smell data to be matched with pre-established medical waste smell component data, judging the type of medical waste to which a smell source belongs, and determining whether the smell concentration exceeds a preset threshold value or not; if the odor concentration exceeds the standard, microorganism information is obtained according to the relevance between the odor component information and microorganisms, and the microorganism breeding risk is evaluated in combination with temperature and humidity control parameters of the air conditioner; simulating airflow distribution of an air conditioning system, predicting diffusion paths and influence ranges of odor in different areas of a hospital by combining with position layout of an air outlet of the air conditioner, and generating an odor diffusion thermodynamic diagram; and according to the optimized disinfection scheme, the air conditioning system is controlled to enter a disinfection mode, the fresh air introduction proportion and the filtering efficiency grade are adjusted, a disinfectant is sprayed in the key area, and the disinfection effect is monitored in real time.

The invention discloses a natural gas odorant concentration intelligent detection device suitable for remote monitoring, and belongs to the field of natural gas safety monitoring, and the natural gas odorant concentration intelligent detection device comprises an odorant concentration sensor array used for detecting original concentration data of a natural gas odorant; the cross validation module is used for carrying out fusion processing on the original concentration data corresponding to the various sensors respectively to obtain calibrated odorant concentration detection data; the pipeline monitoring module is used for obtaining pipeline operation data; the communication module is connected with the cross validation module, the pipeline monitoring module and the remote monitoring module; the remote monitoring module is used for determining an odorant concentration predicted value based on integrated multiple models according to the original concentration data and the pipeline operation data corresponding to the multiple sensors respectively; and obtaining a final odorant concentration confirmation result according to the calibrated odorant concentration detection data and the odorant concentration predicted value. According to the invention, high-precision, real-time and reliable remote intelligent monitoring of the concentration of the natural gas odorant is realized.

A high-temperature environment ultraviolet flue gas analyzer, comprising a detection housing (1), wherein a moving assembly (2) is arranged below the detection housing (1), and a detection and analysis assembly (3) is arranged in the detection housing (1). An annular gas storage cavity (421) is divided into a plurality of gas storage spaces by means of a plurality of gas distribution partition plates (43), thereby implementing storage of multiple gas samples, achieving independent detection of gas samples, and implementing comparison of detection results. By means of opening / closing of electromagnetic valves on internal pipes, internal gas purification is realized, thereby improving detection accuracy, and preventing contamination of a gas to be detected caused by gas mixing. The gas is heated by means of a heating assembly (55) to evaporate moisture in the gas, thereby preventing condensation of water during storage or detection, and also avoiding detection result distortion caused by moisture exposure to internal detection devices. Angle adjustment of an air extraction pipe (53) is implemented by means of an angle adjustment assembly (57), such that the extraction angle can be adjusted at multiple angles according to requirements, thereby improving the extraction efficiency.

The invention discloses an atmospheric particle early warning device for air pollution concentration monitoring, and belongs to the technical field of air particle pollutant monitoring, the atmospheric particle early warning device comprises an equipment main body fixedly mounted in a monitoring area, an alarm is fixedly mounted on the outer side of the upper part of the equipment main body, and a fixed pipe is fixedly mounted at the upper end of the equipment main body; a movable pipe is arranged on the inner side of the fixed pipe in a lifting mode, a sampling head is fixedly connected to the top of the movable pipe, a cleaning assembly driven through air pressure change is arranged on the inner side of the sampling head, a base is fixedly arranged on the outer side of the fixed pipe, and a movable plate is arranged on the inner side of the base in a lifting mode; and a backflushing cleaning assembly is connected between the movable plate and the base. The atmospheric particle early warning device for monitoring the air pollution concentration can collect gas samples at different height positions, and can automatically clean impurities attached to the outside of the filter screen and residual gas in a pipeline after sampling is finished, so that long-term and accurate monitoring of equipment is effectively ensured.

The invention relates to the technical field of atmosphere volatile organic compound source analysis, in particular to a source analysis method and system for one-time manually discharged VOCs based on a receptor model. Comprising the following steps: constructing a photochemical age parameterized model by using [OH] exposure, initial isoprene emission concentration, [OVOCs] observation concentration, tracer observation concentration, actual [OVOCs] reaction rate constant and tracer reaction rate constant, calculating [OVOCs] primary artificial emission theoretical concentration according to the photochemical age parameterized model, and observing [NMHCs] artificial emission observation concentration, the method comprises the following steps of: obtaining a full-spectrum [VOCs] primary artificial emission observation concentration, carrying out photochemical loss correction and atmospheric diffusion correction on the full-spectrum [VOCs] primary artificial emission observation concentration to obtain a [VOCs] primary artificial emission initial concentration, and carrying out VOCs source analysis by utilizing the [VOCs] primary artificial emission initial concentration according to a PMF receptor model. According to the method, the analysis precision of the PMF receptor model on the VOCs source in the actual atmosphere can be improved.

The invention relates to the field of pollution source analysis, and discloses a formaldehyde pollution source analysis and ozone influence quantification method and system for coupling a receptor model and a box-type model, and the method comprises the steps: collecting the concentration of formaldehyde and other pollutants in urban atmosphere in real time through online monitoring equipment, and carrying out abnormal value marking and data standardization processing; performing source analysis on the processed data based on a positive definite factor matrix method to generate a pollution source contribution matrix; converting the source contribution matrix into a molecular concentration input file which can be recognized by the box-type model; embedding a free radical circulation mechanism into the box-type model, and executing photochemical simulation under different pollution source scenes; and generating a pollution source contribution heat map based on a simulation result, and outputting management and control suggestions through a deep learning model. The method has the following effects: by coupling the receptor model and the box type model, not only can different pollution sources of formaldehyde be determined, but also the influence of each pollution source on ozone generation through photochemical reaction can be analyzed.

The invention provides a photocatalysis and biological reaction mixed efficient air purification system, and relates to the technical field of biological air purification, the system comprises a photocatalysis reaction module, a biological reaction module, an intelligent control module, a sensor monitoring module, a data analysis and optimization module, and a modularization and self-maintenance module; the system is combined with a photocatalytic reaction module and a biological reaction module, a multi-stage degradation and efficient decomposition treatment mode is adopted, the photocatalytic reaction module firstly degrades pollutants in air into intermediate products, then the biological reaction module further degrades the intermediate products through microorganisms, and finally thorough purification is achieved. According to the multi-stage synergistic reaction, the air purification efficiency is remarkably improved, thorough removal of pollutants in the treatment process is ensured, the environmental risk is reduced, various indexes in the degradation process are dynamically adjusted through a multi-target optimization algorithm, it is ensured that each stage achieves the optimal effect, and the performance and stability of the whole system are further improved.

The invention relates to the technical field of environmental pollutant detection, in particular to a straw open-air incineration pollutant emission quantitative method based on multi-source data fusion, which comprises the following steps: based on air pollutant monitoring data, calling a sensor network to obtain PM2.5, CO and NOX concentrations, analyzing fire point heat radiation intensity, collecting meteorological data, and calculating the concentration of PM2.5, CO and NOX; and obtaining a pollution source data set by combining the time sequence change of the fire points and the meteorological parameters. By integrating an environment monitoring sensor, satellite remote sensing and ground meteorological data, the comprehensiveness and accuracy of pollution source monitoring are improved, the combination of fire point intensity and pollutant concentration time sequence data is optimized, the evaluation of fire point and pollution hot spot areas and the comprehensive analysis of wind directions and meteorological conditions are optimized, the accuracy of a pollutant diffusion model is improved, and the pollution source diffusion efficiency is improved. The pollutant release amount is dynamically adjusted, and the diffusion model is corrected by using a geographic information system, so that the scientificity of pollution prediction and emission intensity evaluation is enhanced, and more accurate pollution prevention and control decision support is provided.

The invention relates to the technical field of mining area pollution monitoring, and discloses an atmospheric pollution monitoring system based on a mining area and a monitoring method thereof.The atmospheric pollution monitoring system based on the mining area comprises the steps that firstly, geographic environment data, outdoor environment data and well area environment data are obtained through a network deployment module and stored; the real-time transmission module is used for preprocessing the acquired data and transmitting the preprocessed data to the comprehensive analysis module, and the comprehensive analysis module is used for analyzing the atmospheric pollution index, judging whether to send out pollution early warning or not according to the calculation result of the atmospheric pollution index, and sending out a pollution alarm signal under the condition that the pollution early warning needs to be sent out; the mining area air pollution monitoring system can comprehensively monitor the mining area air pollution in a multi-dimensional manner, accurately identify the main pollution source and the dynamic change of the main pollution source, break through the limitation of traditional fixed site monitoring, flexibly capture the spatial and temporal change of the mining area pollution, accurately identify the pollution source, improve the monitoring accuracy and improve the monitoring efficiency. And an alarm signal is sent timely.

The invention relates to the technical field of data processing, in particular to an abnormal data processing system for atmospheric pollution monitoring, which comprises the following steps: acquiring a concentration sequential sequence and a standard sequential sequence of gas; performing preliminary evaluation on the concentration time sequence to obtain a preliminary abnormal degree; sequentially carrying out segmentation and fitting on the concentration time sequence to determine subsequences and a target curve; dividing a segmentation sequence based on the target curve, and segmenting a matching sequence; based on the change of the correlation between the segmentation sequence and the standard time sequence along with time, analyzing the offset characteristic of the gas concentration change trend to determine the trend time sequence offset degree, and combining the normal distribution fitting result of the concentration time sequence to determine the detection influence weight; and acquiring abnormal data in the concentration data of each gas at the monitoring point according to the detection influence weight and the initial abnormal degree. According to the method, the decision weight of the isolated tree is adaptively determined, so that the detection accuracy of the abnormal data in the concentration data is improved.

The invention belongs to the technical field of electronic components, and discloses an ammonia gas sensor based on layered MoTe2 and TiO2 heterojunction, and a preparation process and application thereof. The ammonia gas sensor comprises a gas sensitive material and an interdigital electrode plate, wherein the surface of the interdigital electrode plate is coated with the gas sensitive material by adopting a dispensing method. The gas sensitive material is a nano composite material formed by molybdenum ditelluride and titanium dioxide. The method is simple in production process and low in cost, and the obtained gas-sensitive material has relatively high sensitivity, selectivity and rapid recovery to ammonia gas at room temperature and a detection lower limit as low as ppb level. According to the present invention, the excellent ammonia gas detection performance at the room temperature is provided so as to hopefully provide good prospects in the application of the new generation portable low-power-consumption room temperature ammonia gas sensor.

The invention discloses an NO and SO2 mixed gas concentration detection method based on deep learning, and the method comprises the steps: obtaining a to-be-detected NO and SO2 mixed gas, inputting the to-be-detected NO and SO2 mixed gas into a trained mixed gas concentration detection model, and obtaining the concentration detection results of the respective single gases of NO and SO2; according to the model, mixed gas spectrum separation and reconstruction are carried out through a separation and reconstruction model based on a bidirectional long-short-term memory network, so that differential absorption spectrums of two single gases NO and SO2, which are output by the separation and reconstruction model, are obtained at one time; and carrying out feature extraction and concentration prediction on the input sequence data through a concentration detection model based on TCN + RNN network so as to obtain concentration detection results of respective single gases of NO and SO2 as outputs. The method provided by the invention can realize spectral separation of the mixed gas and accurate detection of the concentration of NO and SO2, thereby overcoming the problems of cross sensitivity of SO2 and NO and differential optics of incapability of accurately separating SO2 and NO by a traditional treatment method.

The invention relates to the technical field of ozone precursor traceability, in particular to an ozone precursor collaborative traceability method and system based on a knowledge graph, and the method comprises the following steps: obtaining precursor concentration change, recognizing an abnormal path, extracting path characteristics, carrying out standardized scoring, adjusting graph connection strength, and analyzing sequence offset to obtain collaborative nodes. And screening origin nodes in combination with time sequence meteorology to generate an origin node list. According to the method, pollution response channels are identified through precursor node concentration changes and path connection relations, focusing of key paths is enhanced, paths are scored based on multi-dimensional indexes, connection attributes are dynamically adjusted in combination with monitoring period ozone response intensity, map structure updating is achieved, and concentration response sequence offset is analyzed; according to the method, nodes with co-evolution characteristics are screened, the stable relation identification capability is improved, the path reasonability is evaluated by combining a release time sequence and meteorological conditions, the initial source positioning accuracy is improved, and the response speed and the identification precision of precursor tracing are integrally enhanced.

The invention discloses a VOC gas leakage intelligent inspection system and method based on gas cloud imaging, and belongs to the technical field of VOC gas leakage detection. The inspection system comprises a moving track and an inspection point which are arranged along a monitored object, an intelligent sliding rail type robot which moves along the moving track, and a data processing system. The intelligent sliding rail type robot is provided with a gas cloud imaging host, and the gas cloud imaging host is provided with a medium wave infrared machine core, a visible light machine core and a wireless communication module. The intelligent slide rail type robot moves to each inspection point along the moving track, and the gas cloud imaging host shoots infrared images and visible light images of each inspection point and transmits the infrared images and the visible light images to the data processing system through the wireless communication module. According to the invention, a specific leakage point can be timely and accurately locked, the VOC leakage concentration can be determined, and full-process intelligent inspection from inspection, leakage detection processing, leakage accident archiving, leakage early warning, leakage accident processing to processing result feedback can be realized.

The invention belongs to the technical field of environmental protection, and discloses a single-tower multi-stage biological deodorization tower capable of spraying in different areas and a deodorization control method thereof.The biological deodorization tower comprises a tower body, a circulating water tank is arranged at the bottom of the inner side of the tower body, the upper space of the circulating water tank is communicated with a main air inlet pipe, and the top of the tower body is communicated with a main air outlet pipe; the N stages of biological spraying deodorization modules are arranged in the tower body at intervals in pairs from bottom to top, so that (N-1) spacer regions are formed between the N stages of biological spraying deodorization modules, and N is an integer greater than or equal to 2; the (N-1) stages of water-gas two-phase separation modules are respectively arranged in the (N-1) spacing areas from bottom to top; spraying liquid of the first-stage biological spraying deodorization module located on the upper portion of the main air inlet pipe is supplied by the circulating water tank, and spraying liquid of the second-stage biological spraying deodorization module to the Nth-stage biological spraying deodorization module is supplied by the water-gas two-phase separation modules arranged in the lower interval areas adjacent to the second-stage biological spraying deodorization module and the Nth-stage biological spraying deodorization module respectively. According to the invention, two stink with different properties can be efficiently removed at the same time.

The present invention relates to the technical field of waste gas component monitoring, specifically a waste gas component monitoring method for organic waste treatment, comprising the following steps: by continuously sampling waste gas, capturing waste gas samples within a target time period, analyzing the compound components in the samples, obtaining preliminary analysis results of waste gas compounds, setting a baseline of compound concentration and identifying a floating interval according to the preliminary analysis results of waste gas compounds, and obtaining waste gas compound baseline data. In the present invention, dynamic monitoring of waste gas samples is achieved through continuous waste gas sampling and analysis, and a compound concentration baseline is set to identify abnormal compounds. This monitoring method can deeply analyze the cause of the abnormality, quickly locate the problem, and adjust parameters such as the amount of input materials and the processing temperature to achieve rebalancing of waste gas components, continuously monitor changes in compound concentration to verify the adjustment effect, greatly improve waste gas treatment efficiency and reliability, effectively meet environmental protection standards, and reduce pollution risks.

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 waste gas treatment, in particular to an organic waste gas treatment device for a circulating spraying production line, and the organic waste gas treatment device comprises a treatment tower, a grating plate, filler, a rotating shaft, a rotating driver, a stirring assembly and a spraying mechanism. For the filler with large accumulation amount, the composite motion can realize omnibearing and deep stirring of the filler, and when the organic waste gas is treated and the filler is accumulated thicker, the waste gas can fully penetrate through each layer of the filler and fully contact with the surface of the filler under the action of the material stirring roller group, so that the filler is fully stirred. The filler can perform adsorption, chemical reaction and the like on harmful substances in the waste gas by virtue of self characteristics, so that pollutants in the waste gas can be more efficiently removed, the purification effect of the organic waste gas is remarkably improved, the exhausted gas is ensured to reach a more strict environmental protection standard, and the surrounding atmospheric environment is powerfully protected.

The invention relates to the technical field of carbon monoxide oxidation catalysts, and discloses a sulfur-tolerant noble metal-based CO oxidation catalyst as well as a preparation method and application thereof. The preparation method of the catalyst comprises the following steps: dipping a carrier in an aqueous solution containing a noble metal precursor and an auxiliary agent precursor, and then drying and roasting to obtain a catalyst matrix; carrying out pre-reduction treatment on the catalyst matrix in a hydrogen-containing atmosphere to obtain a catalyst intermediate; carrying out induced activation on the catalyst intermediate in an atmosphere containing CO and H2S; wherein the carrier is at least one of titanium dioxide, cerium dioxide, aluminum oxide and zirconium dioxide, and the metal element in the auxiliary agent precursor is at least one of Fe, Co and Ni. The catalyst prepared by the method provided by the invention can realize the high-selectivity oxidation process of H2S species, inhibits the adsorption of S species and the formation process of sulfate, and realizes the high-conversion-rate oxidation reaction of carbon monoxide in the presence of H2S.

The invention belongs to the technical field of volatile organic compound treatment, and relates to a VOCs catalyst, in particular to a nitric acid modified red mud-based VOCs catalyst as well as a preparation method and application thereof. The method comprises the following steps: carrying out modification treatment on Bayer process red mud by using 2.5-3.5 mol / L nitric acid, uniformly mixing the modified red mud and manganese salt in a solution to obtain a modified red mud and manganese composite precursor, and calcining the precursor at 500-600 DEG C to obtain the red mud-manganese composite material. According to the invention, the Bayer process red mud is modified by nitric acid, and the modified red mud is used as a carrier to load the transition metal Mn, so that the catalytic efficiency on toluene is obviously improved, and the catalytic treatment on VOCs is expected to be realized.

The invention discloses a mixed gas concentration detection method based on a temperature modulation technology, and relates to the field of semiconductor gas sensing. The problem that the concentration of the mixed gas is difficult to analyze more accurately in the prior art is solved. According to the method, the characteristics of the gas sensitive response data are expanded under the scale of the spatial domain through the temperature modulation technology, the time sequence data are processed by adopting the LSTM neural network model, the characteristic information contained in the sequence data is fully mined, and the recognition precision of the concentration of the mixed gas is remarkably improved through the combination of the temperature modulation technology and the LSTM neural network model. The device and the method are mainly used for detecting the concentration of H2 and CO gas released from the transformer oil in case of failure.

The invention discloses a medical oxygen generator with sterilization and dust removal functions, and relates to the technical field of oxygen generators, the medical oxygen generator comprises an oxygen generator shell, a handle, a touch screen, an oxygen generator bottom plate, an air inlet pipe, a dust removal and sterilization device, an air compression device, a heat dissipation pipe, an adsorption tower, a heat dissipation device, a cleaning device and a humidification cup, the air compression device can suck air and compress air, the dust and bacteria removal device can remove pollutants such as dust and bacteria in the air and prevent the pollutants from entering the air compressor to affect the quality of oxygen inhaled by a patient, the heat dissipation device rapidly dissipates heat of the air in the heat dissipation pipe, the adsorption effect of the adsorption tower is improved, and the service life of the adsorption tower is prolonged. The cooled air enters the adsorption tower, the adsorption tower adsorbs nitrogen in the air, the separated oxygen is decompressed and then conveyed into the humidifying cup, and the oxygen humidified by the humidifying cup is conveyed into an oxygen catheter of a patient.

The invention relates to the technical field of ozone monitoring, in particular to an atmospheric ozone monitoring system and method. Comprising a monitoring box and a box door hinged to the monitoring box, a monitoring box is arranged in the monitoring box, the side wall of the monitoring box is communicated with an exhaust pipe, an ozone sensor is embedded in the top wall of the interior of the monitoring box, and during dynamic monitoring, an airflow conveying mechanism for conveying air into the monitoring box is arranged outside the monitoring box; air is discharged from the exhaust pipe through the ozone sensor. The device not only can carry out dynamic monitoring, but also can carry out static monitoring, the monitoring comprehensiveness is improved, when air in the air bag is released, the partition plate is burst open through airflow, the exhaust pipe, the air conveying box and the air bag are communicated, negative pressure is formed in the exhaust pipe, air in the monitoring box is sucked, and the monitoring accuracy is improved. And residual air in the air delivery pipe enters the monitoring box and is pumped away, so that the influence of the residual air in the air delivery pipe on static monitoring is reduced, and the monitoring accuracy is improved.

The invention relates to the field of environmental remediation, and discloses a remediation method for high-concentration organic pollutants in soil, which comprises the following steps: firstly, injecting a nano zero-valent iron (nZVI) suspension into the contaminated soil for chemical reduction treatment, then adding sodium persulfate for oxidation treatment, and then adding a nano zero-valent iron (nZVI) suspension into the contaminated soil; the complex organic pollutants are converted into biodegradable intermediate products; then, two-stage microbial communities are introduced in sequence, the first-stage microbial community is used for degrading alcohol and ketone intermediate products, the second-stage microbial community is used for degrading organic acid intermediate products, and thorough mineralization of pollutants is achieved. According to the method, the pollutant degradation rate and the final removal effect can be remarkably improved, and the method is suitable for treatment scenes of various high-concentration organic pollutants and has high adaptability and economic benefits.

The invention discloses an OVOC source analysis method, system, medium and equipment in the atmospheric environment, and relates to the technical field of environmental protection, and the method comprises the steps: monitoring the environment, and collecting pollutant concentration data and environmental data during observation; analyzing a plurality of pollution sources of the primary emission part of the OVOC and the concentration of each compound in each pollution source by utilizing a multiple linear regression model and an atmospheric pollutant source analysis receptor model; and inputting into an atmospheric photochemical box-type model to simulate the net generation rate of each oxygen volatile organic compound. The pollution source concentration is quantitatively reduced, the pollution source concentration and other pollution source concentration data which are not reduced are respectively input into an atmospheric photochemical box-type model to simulate the net generation rate and sensitivity of each OVOC, and quantitative analysis of the secondary generation process of the oxygen-containing volatile organic compounds is realized through a relative increment reaction activity coefficient method. Weighted calculation is carried out on the proportion of a primary emission source and a secondary generation source obtained through a multi-line element regression method, and full-process OVOC source quantitative analysis in the atmospheric environment is achieved.

The invention provides an activated carbon fiber capable of efficiently removing formaldehyde and a preparation method thereof, the activated carbon fiber is of a composite material fiber structure of porous TiO2 derived from activated carbon and a metal organic framework (MOF), and the preparation method of the composite material comprises pretreatment of activated carbon, preparation of a Ti-MOF precursor and preparation of TiO2 / activated carbon fiber. According to the invention, the MOF-derived porous TiO2 / activated carbon composite fiber structure is constructed, physical adsorption and photocatalytic degradation functions are cooperated, and the limitation of single adsorption capacity is broken through; the interface bonding problem of the MOF derivative and the activated carbon is solved, and high-dispersion loading and stable and firm compounding of the active components are realized; a process path capable of realizing large-scale preparation is provided, and continuous production of the composite fiber is realized through an electrostatic spinning technology.

The invention provides a method for selecting a high-concentration VOCs adsorbent at different temperatures and application, and belongs to the technical field of waste gas governing. According to the method, through testing pore structure parameters of a model adsorption material with concentrated pore size distribution, a static adsorption isotherm and a dynamic penetration curve for VOCs at different temperatures, a high-concentration VOCs adsorbent is obtained; a linear relation equation of the critical aperture and the critical pressure is established through linear fitting, then a correlation equation of the critical aperture, the temperature and the partial pressure is established, and the appropriate aperture distribution range and the model selection standard of the high-concentration VOCs adsorbent at different temperatures are determined by combining dynamic adsorption results. According to the method, the ternary matching relation equation of the VOCs partial pressure, the temperature and the critical aperture is constructed, accurate type selection of the high-concentration VOCs adsorbent at different temperatures is achieved, the pore volume utilization rate and the adsorption capacity can be improved, meanwhile, desorption energy consumption and the VOCs pyrolysis risk are reduced, and a theoretical basis is provided for adsorbent type selection and technical optimization.

The invention belongs to the technical field of air pollution detection, and particularly relates to an air environment pollution degree detection system and method based on big data. According to the method, detection and early warning of the air environment pollution degree are achieved by mining and analyzing the multi-source environment data, and a dynamic weight distribution strategy is adopted when the pollution comprehensive index in the monitoring area is determined, so that the calculation precision of the pollution comprehensive index is effectively improved, the accuracy and timeliness of air quality monitoring are improved, and the method is suitable for popularization and application. Besides, by constructing the space-time incidence matrix and calculating the correlation strength coefficient, the correlation between abnormal types can be automatically identified, a scientific basis is provided for emergency response, meanwhile, a bimodal early warning mechanism provided by the invention can distinguish instantaneous anomalies and normalized anomalies, and the accuracy of emergency response is improved. The problems of resource waste and untimely emergency response caused by false alarm or missing alarm are avoided, and the continuity and stability of air quality monitoring are ensured.