An atmospheric traceability system based on an aerosol radar

Abstract

The present invention discloses an atmospheric traceability system based on an aerosol radar, which relates to the technical field of atmospheric pollution prevention and control services. This technical solution significantly improves the ability to identify aerosol components and solves the problem of insufficient identification of aerosol components. The optical property analysis module accurately calculates the aerosol component coefficient Rcf and evaluates it through a preset threshold, optimizing the accuracy of component identification. In addition, the meteorological condition adjustment module obtains and processes meteorological data in real time, dynamically adjusts detection parameters, reduces the impact of meteorological conditions on data, and enhances the stability of the system under different meteorological conditions. These improvements overall enhance the accuracy of air pollution monitoring and the adaptability of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of air pollution prevention and control services, and particularly to an atmospheric traceability system based on an aerosol radar. Background Art

[0002] The atmospheric traceability system is the product of the integration of multidisciplinary technologies and is widely used in fields such as environmental protection, emergency response, industrial monitoring, and climate research; the atmospheric traceability system based on an aerosol radar is a technical means that uses radar technology to monitor and track the dynamics of aerosol particles (such as dust, smoke, pollen, industrial pollutants, etc.) in the atmosphere. The aerosol radar can provide high-precision aerosol vertical distribution information and has unique advantages in the monitoring and traceability of air pollution. And it has a wide range of application fields, including air pollution prevention and control services;

[0003] However, in practical applications, there are also many technical drawbacks in the existing technologies, including:

[0004] 1. Insufficient ability to identify aerosol components: The aerosol radar has limited ability to identify the specific components of aerosols. It can usually only detect the concentration and distribution of aerosols, but it is difficult to distinguish specific pollutant types, such as different organic substances, sulfates, nitrates, etc. This lack of identification ability may limit the application of the system in pollution source tracing and cause analysis.

[0005] 2. Difficulty in integrating with other monitoring systems: Integrating the data of the aerosol radar system with the data of other monitoring means (such as satellite remote sensing, ground monitoring stations, etc.) poses technical challenges, including incompatible data formats and differences in communication protocols between different systems. This may lead to the inability to fully utilize the data and affect the accurate tracing of pollution sources;

[0006] 3. Sensitivity to meteorological conditions: The detection effect of the aerosol radar is easily affected by meteorological conditions, such as strong winds, rainfall, haze, etc. These conditions may cause the scattering, attenuation, or increased noise of the radar signal, thereby reducing the accuracy and reliability of the data and affecting the effectiveness of pollution tracing and prevention measures. Summary of the Invention

[0007] The purpose of the present invention is to provide an atmospheric traceability system based on an aerosol radar to solve the above problems.

[0008] The present invention is achieved through the following technical solutions:

[0009] An atmospheric traceability system based on an aerosol radar includes an air pollution monitoring module, an optical property analysis module, a meteorological condition adjustment module, a path identification module, a pollution source positioning module, and a comprehensive evaluation module;

[0010] The air pollution monitoring module is used to collect vertical distribution data of aerosols in the atmosphere through an aerosol radar. Meanwhile, based on the obtained vertical distribution data, it preliminarily processes the real-time monitoring data, then generates an aerosol concentration data set. Finally, it extracts relevant parameters therefrom, calculates and obtains the optical property index Opt, and transmits it to the optical property analysis module;

[0011] The optical property analysis module is used to identify different types of polluted particulate matters in the atmosphere according to the optical property index Opt and in combination with the scanning law of aerosols, calculate the aerosol composition coefficient Rcf based on these types and conduct an evaluation and analysis. Finally, it transmits the evaluation and analysis results to the path recognition module;

[0012] The meteorological condition adjustment module is used to receive real-time meteorological related data, and based on a preset meteorological model, adjust the detection parameters of the aerosol radar. After adjustment, it generates a parameter detection data set, and then transmits the adjusted data to the path recognition module;

[0013] The path recognition module, based on the data of the aerosol radar and the adjusted detection parameter set, identifies the transmission path of the aerosol, calculates the propagation path coefficient Ptc, and transmits the result to the pollution source location module;

[0014] The pollution source location module is used to establish a pollution source location model, and at the same time correlate and fit the propagation path coefficient Ptc, the aerosol composition coefficient Rcf and the relevant data of the pollution source location model. Finally, it generates a pollution source location index Psp, locates the position of the pollution source, and transmits it to the comprehensive evaluation module;

[0015] The comprehensive evaluation module is used to compare the pollution source location index Psp with the relevant data of historical pollution sources, comprehensively evaluate the severity of the current air pollution, generate an air pollution prevention and control suggestion report, and assist in decision-making at the same time.

[0016] Preferably, the air pollution monitoring module includes an aerosol radar data collection unit and a data preprocessing and feature extraction unit;

[0017] The aerosol radar data collection unit is used to obtain the vertical distribution data of aerosols in the atmosphere in real time; through the aerosol radar device, it scans different altitude layers in the atmosphere, obtains the aerosol concentration data at different times, and records the change information of aerosols with time and altitude. Among them, the data collected by the aerosol radar device is stored in a vertical profile form and preprocessed, and finally an aerosol concentration vertical distribution data set in the atmosphere is generated;

[0018] Preferably, the data preprocessing and feature extraction unit is used to extract the vertical distribution dataset of aerosol concentration. After dimensionless processing, the extinction coefficient Xxs and scattering coefficient Sxs of the aerosol are obtained through calculation. Subsequently, the extinction coefficient Xxs and scattering coefficient Sxs are fitted to obtain the optical property index Opt. The specific calculation formula is as follows:

[0019] Xxs = ∫N(D)·Qext(D,λ)·πD 2 dD;

[0020] Sxs = ∫N(D)·Qsca(D,λ)·πD 2 dD;

[0021]

[0022] In the formula, D represents the diameter of the aerosol particles, with the unit of micrometer. N(D) represents the aerosol particle size distribution function, which uses the form of lognormal distribution to describe the number of aerosol particles with diameter D per unit volume;

[0023] Qext(D,λ) represents the extinction efficiency factor, indicating the light extinction ability of the aerosol particles at a specific particle size D and wavelength λ; Qsca(D,λ) represents the scattering efficiency factor, indicating the light scattering ability of the aerosol particles at a specific particle size D and wavelength λ; πD 2 represents the cross-sectional area of the aerosol particles;

[0024] Xxs(h) represents the extinction coefficient of the aerosol in units of m-1, indicating the attenuation degree of the light when passing through a certain height. m represents the meter in the length unit, used to represent the scattering degree of light per unit length; Sxs(h) represents the scattering coefficient of the aerosol in units of m-1·sr-1, indicating the intensity of the light scattered by the aerosol at this height. sr represents the steradian in the solid angle unit, used to represent the angular distribution of the light scattering direction.

[0025] Preferably, the optical property analysis module includes an optical property calculation unit and a component analysis and evaluation unit;

[0026] The optical property calculation unit calculates and obtains the aerosol component coefficient Rcf by fitting the optical property index Opt. The specific formula is as follows:

[0027]

[0028] In the formula, Opt i represents the optical property index of the i-th aerosol particulate matter, which depends on the scattering and extinction characteristics of the particulate matter; Qpt z represents the total optical property index of all types of aerosol particulate matters, W iRepresents the weight of the i-th type of particulate matter, which is specifically set by the user according to the optical property responses of different pollutants.

[0029] Preferably, the component analysis and evaluation unit evaluates the aerosol component coefficient Rcf through a preset pollutant safety threshold T1 and a pollutant warning threshold T2, where the pollutant safety threshold T1 < the pollutant warning threshold T. The specific evaluation content is as follows:

[0030] If the aerosol component coefficient Rcf ≤ the pollutant safety threshold T1, a first component result is generated at this time, indicating that the pollution level is in a safe state;

[0031] If the pollutant safety threshold T1 < the aerosol component coefficient Rcf ≤ the pollutant warning threshold T2, a second component result is generated at this time, indicating that the pollutant concentration exceeds the safety standard but has not reached the warning level. At the same time, monitoring is strengthened and meteorological adjustment and further analysis are carried out;

[0032] If the aerosol component coefficient Rcf > the pollutant warning threshold T2, a third component result is generated at this time, indicating that the pollutant concentration has exceeded the warning threshold, and measures are taken and pollution control is carried out.

[0033] Preferably, the meteorological condition adjustment module includes a meteorological data reception and processing unit and a detection parameter adjustment unit;

[0034] The meteorological data reception and processing unit obtains the atmospheric conditions in real time through a weather station and other meteorological monitoring devices, including temperature, humidity, wind speed, wind direction, and air pressure; secondly, the received data is preprocessed, and the preprocessed meteorological data will be used for subsequent model adjustment.

[0035] The detection parameter adjustment unit adjusts the detection parameters of the aerosol radar based on a preset meteorological model and combines the meteorological data, and finally generates a new detection data set.

[0036] Preferably, the path recognition module includes a data analysis unit and a path coefficient calculation unit;

[0037] The data analysis unit is used to receive the vertical distribution data from the aerosol radar and the adjusted new detection parameter set, and at the same time, preliminarily analyze the spatio-temporal distribution of the aerosol; and determine the movement trajectory and distribution trend of the pollutant through the concentration change and scan data of the aerosol;

[0038] The path coefficient calculation unit quantitatively analyzes the transmission path of the aerosol, extracts the vertical distribution data of the aerosol radar, including after dimensionless processing, and calculates the propagation path coefficient Ptc:

[0039] Ptc = ∫ V∫C(x,y,z)·V(x,y,z)·A(x,y,z)dv;

[0040] In the formula, C(x, y, z) represents the concentration distribution of the aerosol, with the unit of μg / m 3 ;

[0041] V(x, y, z) represents the spatial distribution of the wind speed on the aerosol path, with the unit of m / s;

[0042] A(x, y, z) represents the diffusion cross-sectional area of the aerosol, with the unit of m 2 ;

[0043] dv is the integral symbol, integrating over the spatial volume V, with the unit of m 3 .

[0044] Preferably, the pollution source positioning module includes a model construction unit and a positioning analysis unit;

[0045] In the pollution source positioning model constructed by the model construction unit, the distribution of different pollution sources in the geographical space is preset; by collecting relevant data and meteorological data in the pollution source positioning model, and combining with the propagation path coefficient Ptc and the component identification coefficient Rcf, the potential pollution source locations are identified through a fitting algorithm to generate the pollution source positioning index Psp. The specific formula in the fitting process is:

[0046]

[0047] In the formula, N represents the normalization factor, Ppl represents the emission frequency, Pst represents the emission duration, Ksx represents the diffusion coefficient, Wd represents the temperature, Sd represents the humidity, Fs represents the wind speed, Fx represents the wind direction, and Qy represents the air pressure;

[0048] The positioning analysis unit is used to perform spatial analysis by combining the pollution source positioning index Psp with geographical data; at the same time, by comparing with the on-site monitoring data, the location accuracy of the pollution source is further verified.

[0049] Preferably, the comprehensive evaluation module includes a pollution source comparison unit and a pollution prevention and control suggestion generation unit;

[0050] The pollution source comparison unit extracts historical data related to the current atmospheric pollution source from the historical database, including historical pollution events, pollution source locations, pollution diffusion patterns, and pollution intensities, and fits the historical data related to the atmospheric pollution source to obtain the historical pollution positioning index Lpsp; the pollution source similarity Wrxs is calculated through the following formula;

[0051]

[0052] Preferably, the pollution prevention and control recommendation generation unit evaluates the similarity Wrxs with the pollution source through a preset first similarity threshold P1 and a second similarity threshold P2, where the first similarity threshold P1 is greater than the second similarity threshold P2, and the evaluation content is as follows:

[0053] When the pollution source similarity Wrxs ≥ similarity threshold P1, a first similarity result is generated at this time;

[0054] When the first similarity threshold P1 < pollution source similarity Wrxs < second similarity threshold P2, a second similarity result is generated at this time;

[0055] When the pollution source similarity Wrxs ≤ similarity threshold P2, a third similarity result is generated at this time;

[0056] According to the evaluation and analysis results, an air pollution prevention and control recommendation report is automatically generated, specifically:

[0057] When the first similarity result is generated, successful historical prevention and control strategies should be adopted, including implementing strict emission controls, increasing pollution control facilities, and conducting large-scale environmental clean-ups; at the same time, restricting operating hours, adjusting control facilities, and implementing emergency response measures;

[0058] When the second similarity result is generated, take some specific adjustment measures and adjust them in combination with general prevention and control strategies, including adjusting production processes, adjusting daily monitoring, and implementing local controls;

[0059] When the third similarity result is generated, take basic pollution control measures to prevent potential problems, including conducting regular maintenance, adjusting production management, and carrying out regular inspections.

[0060] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0061] 1. The present invention improves the ability to identify aerosol components; through system components such as an air pollution monitoring module and an optical property analysis module, the vertical distribution data and optical property index of an aerosol radar are used to identify aerosol components; specifically, the optical property calculation unit and the component analysis and evaluation unit in the optical property analysis module can accurately calculate the aerosol component coefficient Rcf and evaluate pollutants according to a preset threshold; this method effectively solves the problem of insufficient aerosol component identification through dimensionless processing and optical property fitting, improves the system's accurate identification ability of aerosol types and concentrations, and thus provides more accurate pollution source information;

[0062] 2. The present invention simplifies the integration with other monitoring systems; the design of each module in the solution includes functional units such as data acquisition, preprocessing, analysis, and evaluation. These modules achieve effective integration between systems through standardized data transmission interfaces and consistent data formats; the data transmission interfaces of the meteorological condition adjustment module and the path recognition module enable seamless docking of real-time adjustment of meteorological data and identification of aerosol transmission paths, avoiding information loss and errors during data transmission; in addition, through optimized interfaces between modules and preset model parameters, the system can be easily integrated with other atmospheric monitoring systems, improving the compatibility and cooperation efficiency of the overall system;

[0063] 3. The present invention addresses the sensitivity to meteorological conditions; the impact of meteorological conditions on aerosol radar detection cannot be ignored. Therefore, a meteorological condition adjustment module is specifically designed in the technical solution; the meteorological condition adjustment module includes a meteorological data reception and processing unit and a detection parameter adjustment unit, which acquires and processes meteorological data in real time, adjusts detection parameters according to a preset model, and generates a new detection data set; in this way, the system can dynamically adjust detection parameters according to real-time meteorological changes, ensuring the accuracy and stability of aerosol data; through this dynamic adjustment of meteorological conditions, the technical solution effectively reduces the impact of meteorological conditions on aerosol monitoring data, improving the adaptability and reliability of the system under different meteorological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of this application, and do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0065] Figure 1 is a schematic diagram of the framework structure of an atmospheric traceability system based on an aerosol radar according to the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0066] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with the embodiments and the drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and do not constitute a limitation to the present invention. It should be noted that the present invention is already in the actual R & D and use stage.

[0067] Embodiment 1

[0068] As Figure 1 shown, the present invention provides an atmospheric traceability system based on an aerosol radar, including an air pollution monitoring module, an optical property analysis module, a meteorological condition adjustment module, a path recognition module, a pollution source positioning module, and a comprehensive evaluation module;

[0069] The air pollution monitoring module is used to collect the vertical distribution data of aerosols in the atmosphere through an aerosol radar. At the same time, based on the obtained vertical distribution data, the real-time monitoring data is preliminarily processed, and then an aerosol concentration data set is generated. Finally, relevant parameters are extracted from it, the optical property index Opt is calculated and obtained, and it is transmitted to the optical property analysis module;

[0070] The optical property analysis module is used to identify different types of polluted particulate matters in the atmosphere according to the optical property index Opt and in combination with the scanning law of aerosols, calculate the aerosol composition coefficient Rcf based on these types and conduct an evaluation and analysis, and finally transmit the evaluation and analysis results to the path recognition module;

[0071] The meteorological condition adjustment module is used to receive real-time meteorological related data, and based on a preset meteorological model, adjust the detection parameters of the aerosol radar. After adjustment, a parameter detection data set is generated, and then the adjusted data is transmitted to the path recognition module;

[0072] The path recognition module identifies the transmission path of aerosols based on the data of the aerosol radar and the adjusted detection parameter set, calculates the propagation path coefficient Ptc, and transmits the result to the pollution source location module;

[0073] The pollution source location module is used to establish a pollution source location model, and at the same time associate and fit the propagation path coefficient Ptc, the aerosol composition coefficient Rcf and the relevant data of the pollution source location model, and finally generate a pollution source location index Psp, locate the position of the pollution source, and transmit it to the comprehensive evaluation module;

[0074] The comprehensive evaluation module is used to compare the pollution source location index Psp with the relevant data of historical pollution sources, comprehensively evaluate the severity of the current air pollution, generate an air pollution prevention and control suggestion report, and assist in decision-making at the same time.

[0075] In this embodiment, the system collects the vertical distribution data of aerosols in real time through an aerosol radar and generates an aerosol concentration data set, ensuring the comprehensiveness and real-time nature of the data; secondly, the optical property analysis module accurately calculates the optical property index and the aerosol composition coefficient, thereby improving the ability to identify different types of polluted particulate matters; the meteorological condition adjustment module adjusts the detection parameters in real time, overcomes the interference of meteorological factors on the data, and enhances the stability of the system; the path recognition module further analyzes the transmission path of aerosols, calculates the propagation path coefficient, and improves the accuracy of pollution source location; finally, the comprehensive evaluation module provides targeted pollution prevention and control suggestions by comparing historical data, assists in decision-making, and effectively addresses technical challenges such as insufficient aerosol composition identification, high system integration difficulty, and meteorological condition influence; these improvements overall enhance the comprehensive performance and practical value of the system.

[0076] Example 2

[0077] The air pollution monitoring module includes an aerosol radar data acquisition unit and a data preprocessing and feature extraction unit;

[0078] The aerosol radar data acquisition unit is used to obtain the vertical distribution data of aerosols in the atmosphere in real time; by means of an aerosol radar device, different altitude layers in the atmosphere are scanned to obtain aerosol concentration data at different times, and the variation information of aerosols with time and altitude is recorded; among them, the data collected by the aerosol radar device is stored in the form of a vertical profile and preprocessed, and finally a vertical distribution dataset of aerosol concentration in the atmosphere is generated;

[0079] The data preprocessing and feature extraction unit is used to extract the vertical distribution dataset of aerosol concentration, and after dimensionless processing, the extinction coefficient Xxs and scattering coefficient Sxs of aerosols are obtained through calculation. Subsequently, the extinction coefficient Xxs and scattering coefficient Sxs are fitted to obtain the optical property index Opt. The specific calculation formula is:

[0080] Xxs = ∫N(D)·Qext(D,λ)·πD 2 dD;

[0081] Sxs = ∫N(D)·Qsca(D,λ)·πD 2 dD;

[0082]

[0083] In the formula, D represents the diameter of aerosol particles, with the unit of micrometer, N(D) represents the aerosol particle size distribution function, and the logarithmic normal distribution form is used to describe the number of aerosol particles with a diameter of D per unit volume;

[0084] Qext(D,λ) represents the extinction efficiency factor, indicating the light extinction ability of aerosol particles at a specific particle size D and wavelength λ; Qsca(D,λ) represents the scattering efficiency factor, indicating the light scattering ability of aerosol particles at a specific particle size D and wavelength λ; πD 2 represents the cross-sectional area of aerosol particles;

[0085] Xxs(h) represents the extinction coefficient of aerosols with the unit of m-1, indicating the attenuation degree of light when passing through a certain height. m represents the meter in the length unit, used to represent the scattering degree of light per unit length; Sxs(h) represents the scattering coefficient of aerosols with the unit of m-1·sr-1, indicating the intensity of light scattered by aerosols at this height. sr represents the steradian in the solid angle unit, used to represent the angular distribution of the light scattering direction.

[0086] In this embodiment, significant improvements have been achieved in aerosol monitoring by refining the aerosol radar data acquisition and processing procedures. The aerosol radar data acquisition unit obtains the vertical distribution data of aerosols in real time, accurately records the concentration changes of aerosols at different altitude layers and time points, thus providing a comprehensive dataset of the vertical distribution of aerosol concentrations. The data preprocessing and feature extraction unit performs dimensionless processing on these data, calculates the extinction coefficient Xxs and scattering coefficient Sxs of aerosols, and obtains the optical property index Opt through fitting. In this process, the extinction coefficient Xxs measures the attenuation degree of light passing through the aerosol layer, and the scattering coefficient Sxs measures the scattering intensity of light in the aerosol layer. These parameters help accurately evaluate the optical properties of aerosols and identify different types of polluting particulate matters, thereby improving the accuracy and reliability of pollution monitoring. These improvements not only enhance the system's response ability to aerosol concentration changes, but also optimize the process of obtaining optical property data, improving the monitoring and analysis capabilities of air pollution.

[0087] Among them, the specific formula of N(D) is:

[0088] In the formula, N0 represents the total number concentration of aerosol particles, with the unit of particles / cm 3 , which reflects the total number of aerosol particles of all particle sizes per unit volume;

[0089] D represents the diameter of aerosol particles, with the unit of micrometers. This is a variable of the particle size distribution, representing aerosol particles of different sizes;

[0090] D g represents the geometric mean diameter of the aerosol particle size, with the unit of micrometers. This parameter represents the central value of the aerosol particle size in the distribution, and most of the aerosol particles are concentrated near this range;

[0091] σ g represents the geometric standard deviation of the aerosol particle size (unitless). It describes the width of the particle size distribution. The larger the value, the more dispersed the particle size distribution of aerosol particles. Conversely, the smaller the value, the more concentrated the particle size is in a certain range;

[0092] In D and InDg respectively represent the natural logarithms of the particle size D and the geometric mean diameter Dg. By taking the logarithm, the particle size distribution is transformed into a log-normal distribution, making the distribution shape more reasonable in different particle size ranges.

[0093] Example 3

[0094] The optical property analysis module includes an optical property calculation unit and a composition analysis and evaluation unit;

[0095] The optical property calculation unit calculates and obtains the aerosol composition coefficient Rcf by fitting the optical property index Opt. The specific formula is as follows:

[0096]

[0097] In the formula, Opt i represents the optical property index of the i-th type of aerosol particle, which depends on the scattering and extinction characteristics of the particle; Qpt z represents the total optical property index of all types of aerosol particles, and W i represents the weight of the i-th type of particle, which is specifically set by the user according to the optical property response of different pollutants.

[0098] The component analysis and evaluation unit evaluates the aerosol composition coefficient Rcf by presetting the pollutant safety threshold T1 and the pollutant warning threshold T2, where the pollutant safety threshold T1 < the pollutant warning threshold T. The specific evaluation content is as follows:

[0099] If the aerosol composition coefficient Rcf ≤ the pollutant safety threshold T1, a first component result is generated at this time, indicating that the pollution level is in a safe state;

[0100] If the pollutant safety threshold T1 < the aerosol composition coefficient Rcf ≤ the pollutant warning threshold T2, a second component result is generated at this time, indicating that the pollutant concentration exceeds the safety standard but has not reached the warning level. At the same time, monitoring is strengthened and meteorological adjustment and further analysis are carried out;

[0101] If the aerosol composition coefficient Rcf > the pollutant warning threshold T2, a third component result is generated at this time, indicating that the pollutant concentration has exceeded the warning threshold, and measures are taken and pollution control is carried out.

[0102] In this embodiment, the accuracy of aerosol composition analysis is significantly improved through the optical property calculation unit and the component analysis and evaluation unit; the optical property calculation unit calculates the aerosol composition coefficient Rcf by fitting the optical property index Opt, where the optical property index Opt comprehensively considers the scattering and extinction characteristics of aerosol particles, and the aerosol composition coefficient Rcf reflects the optical property weights of different aerosol particles. These parameters provide a more accurate data basis for aerosol composition analysis; the component analysis and evaluation unit grades and evaluates the aerosol composition coefficient Rcf according to the preset pollutant safety threshold T1 and pollutant warning threshold T2, improves the system's response ability to different pollution levels, and helps to implement targeted pollution control and prevention measures.

[0103] Embodiment 4

[0104] The meteorological condition adjustment module includes a meteorological data reception and processing unit and a detection parameter adjustment unit;

[0105] The meteorological data receiving and processing unit obtains atmospheric conditions in real time through weather stations and other meteorological monitoring devices, including temperature, humidity, wind speed, wind direction, and air pressure; secondly, preprocesses the received data, and the preprocessed meteorological data will be used for subsequent model adjustment.

[0106] The detection parameter adjustment unit adjusts the detection parameters of the aerosol radar based on a preset meteorological model and combined with meteorological data, and finally generates a new detection data set.

[0107] In this embodiment, the detection accuracy and adaptability of the aerosol radar are significantly improved through the meteorological data receiving and processing unit and the detection parameter adjustment unit; the meteorological data receiving and processing unit obtains atmospheric conditions such as temperature, humidity, wind speed, wind direction, and air pressure in real time, and preprocesses the data to provide an accurate basis for model adjustment; the detection parameter adjustment unit dynamically adjusts the detection parameters of the aerosol radar, such as radar wavelength, scanning angle, and pulse frequency, based on the preprocessed meteorological data, thereby generating a new detection data set; this improvement enhances the system's response ability to changing meteorological conditions, enabling the aerosol radar to more accurately detect and analyze the aerosol distribution in the atmosphere, and improving the overall monitoring effect and data quality.

[0108] Embodiment 5

[0109] The path recognition module includes a data analysis unit and a path coefficient calculation unit;

[0110] The data analysis unit is used to receive the vertical distribution data from the aerosol radar and the adjusted new detection parameter set, and at the same time, preliminarily analyze the spatio-temporal distribution of aerosols; and determine the movement trajectory and distribution trend of pollutants through the concentration change and scanning data of aerosols;

[0111] The path coefficient calculation unit quantitatively analyzes the transmission path of aerosols, extracts the vertical distribution data of the aerosol radar, and after dimensionless processing, calculates the propagation path coefficient Ptc:

[0112] Ptc = ∫ V C(x,y,z)·V(x,y,z)·A(x,y,z)dv;

[0113] In the formula, C(x, y, z) represents the concentration distribution of aerosols, with the unit of μg / m 3 ;

[0114] V(x, y, z) represents the spatial distribution of wind speed on the aerosol path, with the unit of m / s;

[0115] A(x, y, z) represents the diffusion cross-sectional area of aerosols, with the unit of m2 ;

[0116] dv is the integral symbol, integrating over the spatial volume V, with the unit of m 3 。

[0117] In this embodiment, significant improvements are introduced in the aerosol transmission path identification through the data analysis unit and the path coefficient calculation unit; the data analysis unit conducts a preliminary analysis of the spatio-temporal distribution of aerosols by receiving the vertical distribution data of the aerosol radar and the adjusted new detection parameter set, and can accurately identify the movement trajectory and distribution trend of pollutants; the path coefficient calculation unit then conducts a quantitative analysis of the aerosol transmission path, and calculates the propagation path coefficient Ptc by extracting and dimensionless processing the concentration distribution, wind speed distribution, diffusion cross-sectional area and integral range of the spatial dimension of the aerosol; these improvements enhance the system's accurate identification ability of aerosol transmission in complex environments, contribute to more accurately predicting and evaluating the scope and impact of pollutant diffusion, and thus enhance the effectiveness of pollution source location and control.

[0118] Example 6

[0119] The pollution source location module includes a model construction unit and a location analysis unit;

[0120] In the pollution source location model constructed by the model construction unit, the distribution of different pollution sources in the geographical space is preset; by collecting relevant data and meteorological data in the pollution source location model, and combining them with the propagation path coefficient Ptc and the component identification coefficient Rcf, the potential pollution source locations are identified through a fitting algorithm to generate the pollution source location index Psp. The specific formula in the fitting process is:

[0121]

[0122] In the formula, N represents the normalization factor, Ppl represents the emission frequency, Pst represents the emission duration, Ksx represents the diffusion coefficient, Wd represents the temperature, Sd represents the humidity, Fs represents the wind speed, Fx represents the wind direction, and Qy represents the air pressure;

[0123] The location analysis unit is used to conduct spatial analysis by combining the pollution source location index Psp with geographical data; at the same time, by comparing with on-site monitoring data, the location accuracy of the pollution source is further verified.

[0124] In this embodiment, through the cooperation of the model construction unit and the positioning analysis unit, the positioning accuracy of the pollution source is significantly improved; the model construction unit presets the distribution of pollution sources in the geographical space, and by combining meteorological data, the propagation path coefficient Ptc and the component identification coefficient Rcf, uses the fitting algorithm to generate the pollution source positioning index Psp, where the emission frequency Ppl, the emission duration Pst, the diffusion coefficient Ksx, the temperature Wd, the humidity Sd, the wind speed Fs, the wind direction Fx and the air pressure Qy comprehensively consider various factors affecting the pollution source positioning; the positioning analysis unit then conducts spatial analysis by combining with geographical data and compares with the field monitoring data to further verify the position accuracy of the pollution source. This improvement enhances the positioning ability of the system in complex environments and improves the accuracy and response efficiency of pollution control.

[0125] Embodiment 7

[0126] The comprehensive evaluation module includes a pollution source comparison unit and a pollution prevention and control suggestion generation unit;

[0127] The pollution source comparison unit extracts historical data related to the current atmospheric pollution source from the historical database, including historical pollution events, pollution source locations, pollution diffusion patterns and pollution intensities, and fits the historical data related to the atmospheric pollution source to obtain the historical pollution positioning index Lpsp; the pollution source similarity Wrxs is calculated through the following formula;

[0128]

[0129] The pollution prevention and control suggestion generation unit evaluates with the pollution source similarity Wrxs by presetting a first similarity threshold P1 and a second similarity threshold P2, where the first similarity threshold P1 is greater than the second similarity threshold P2, and the evaluation content is:

[0130] When the pollution source similarity Wrxs ≥ similarity threshold P1, a first similarity result is generated at this time;

[0131] When the first similarity threshold P1 < the pollution source similarity Wrxs < the second similarity threshold P2, a second similarity result is generated at this time;

[0132] When the pollution source similarity Wrxs ≤ similarity threshold P2, a third similarity result is generated at this time;

[0133] According to the evaluation and analysis results, an atmospheric pollution prevention and control suggestion report is automatically generated, specifically:

[0134] When the first similarity result is generated, the successful prevention and control strategies in history should be adopted, and these strategies include implementing strict emission controls, increasing pollution control facilities, and conducting large-scale environmental clean-ups; at the same time, restricting operating hours, adjusting control facilities, and implementing emergency response measures;

[0135] When the second similar result is generated, some specific adjustment measures are taken and adjusted in combination with general prevention and control strategies, including adjusting the production process, adjusting daily monitoring and implementing local control;

[0136] When the third similar result is generated, basic pollution control measures are taken to prevent potential problems, including carrying out routine maintenance, adjusting production management and conducting routine inspections.

[0137] In this embodiment, through the pollution source comparison unit and the pollution prevention and control recommendation generation unit, the pertinence and effectiveness of air pollution prevention and control are significantly improved; the pollution source comparison unit extracts relevant historical data from the historical database, including pollution events, source locations, diffusion patterns and intensities, obtains the historical pollution location index Lpsp through fitting, and calculates and evaluates the pollution source similarity Wrxs. The pollution prevention and control recommendation generation unit generates an automated prevention and control report according to the evaluation result of the pollution source similarity Wrxs. When the first similar result is generated, it is recommended to adopt historical successful strategies such as strict emission control and environmental cleaning. When the second similar result is generated, it is recommended to adjust the production process and local control. When the third similar result is generated, implement basic pollution control measures such as routine maintenance and production management adjustment. These improvement points and parameter evaluations greatly enhance the pertinence and predictability of prevention and control measures, and improve the accuracy and response efficiency of pollution management.

[0138] The specific implementation manners described above further elaborate on the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above are only specific implementation manners of the present invention and are not used to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An atmospheric source tracing system based on aerosol radar, characterized by: It includes air pollution monitoring module, optical characteristics analysis module, meteorological condition adjustment module, path identification module, pollution source location module and comprehensive evaluation module; The atmospheric pollution monitoring module is used to collect vertical distribution data of aerosols in the atmosphere through an aerosol radar, and based on the acquired vertical distribution data, preliminarily process the real-time monitoring data, and then generate an aerosol concentration data set; finally, extract the relevant parameters therein, calculate and obtain the optical characteristic index Opt, and transmit it to the optical characteristic analysis module; The optical characteristic analysis module is used to identify different types of pollutant particles in the atmosphere according to the optical characteristic index Opt and the scanning law of the aerosol, and calculate the aerosol composition coefficient Rcf according to these types and evaluate and analyze them, and finally transmit the evaluation and analysis results to the path identification module; The meteorological condition adjustment module is used to receive real-time meteorological related data, and adjust the detection parameters of the aerosol radar based on a preset meteorological model, generate a parameter detection data set after the adjustment, and then transmit the adjusted data to the path identification module; The path identification module identifies the transmission path of the aerosol based on the data of the aerosol radar and the adjusted detection parameter set, calculates the propagation path coefficient Ptc, and transmits the result to the pollution source positioning module; The pollution source positioning module is used to establish a pollution source positioning model, and at the same time associate and fit the propagation path coefficient Ptc, the aerosol composition coefficient Rcf and the pollution source positioning model related data, and finally generate the pollution source positioning index Psp, locate the location of the pollution source, and transmit it to the comprehensive evaluation module; The comprehensive assessment module is used to compare the pollution source location index Psp with historical pollution source related data, comprehensively assess the severity of current air pollution, generate an air pollution prevention and control recommendation report, and assist in decision-making.

2. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The air pollution monitoring module includes an aerosol radar data acquisition unit and a data preprocessing and feature extraction unit; The aerosol radar data acquisition unit is used to obtain the vertical distribution data of aerosols in the atmosphere in real time; through the aerosol radar equipment, different altitude layers in the atmosphere are scanned to obtain aerosol concentration data at different times, and the change information of aerosols with time and altitude is recorded; wherein the data collected by the aerosol radar equipment is stored in the form of vertical profiles and preprocessed, and finally a vertical distribution data set of aerosol concentration in the atmosphere is generated.

3. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The data preprocessing and feature extraction unit is used to extract the vertical distribution data set of aerosol concentration, and after dimensionless processing, the extinction coefficient Xxs and the scattering coefficient Sxs of the aerosol are obtained by calculation. The extinction coefficient Xxs and the scattering coefficient Sxs are then fitted to obtain the optical characteristic index Opt. The specific calculation formula is: In the formula, D represents the diameter of the aerosol particles in micrometers, and N(D) represents the aerosol particle size distribution function, which uses the log-normal distribution to describe the number of aerosol particles with a particle size of D per unit volume; Qext(D,λ) represents the extinction efficiency factor, which indicates the light extinction ability of aerosol particles at a specific particle size D and wavelength λ; Qsca(D,λ) represents the scattering efficiency factor, which indicates the light scattering ability of aerosol particles at a specific particle size D and wavelength λ; represents the cross-sectional area of ​​the particle; Xxs(h) means the unit is m -1 The extinction coefficient of aerosol indicates the attenuation degree of light when it passes through a certain height; m is used to indicate the scattering degree of light per unit length; Sxs(h) is expressed in m -1 and sr -1 The scattering coefficient of aerosols indicates the intensity of light scattered by aerosols at this height; sr represents the steradian in the solid angle unit, which is used to indicate the angular distribution of the light scattering direction; h is used to represent different altitude layers in the vertical profile of the atmosphere.

4. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The optical characteristic analysis module includes an optical characteristic calculation unit and a component analysis evaluation unit; The optical property calculation unit calculates and obtains the aerosol composition coefficient Rcf by fitting the optical property index Opt. The specific formula is: In the formula, Opt i It represents the optical property index of the i-th aerosol particle, which depends on the scattering and extinction characteristics of the particle; Qpt z Represents the total optical property index of all types of aerosol particles, W i Represents the weight of the i-th particle, which is set by the user according to the optical characteristics of different pollutants.

5. The atmospheric source tracing system based on aerosol radar according to claim 4, characterized in that: The component analysis and evaluation unit evaluates the aerosol component coefficient Rcf by presetting the pollutant safety threshold T1 and the pollutant warning threshold T2, wherein the pollutant safety threshold T1 < the pollutant warning threshold T. The specific evaluation content is: If the aerosol component coefficient Rcf ≤ the pollutant safety threshold T1, the first component result is generated, indicating that the pollution level is in a safe state; If the pollutant safety threshold T1 < aerosol component coefficient Rcf ≤ pollutant warning threshold T2, the second component result is generated, indicating that the pollutant concentration exceeds the safety standard but has not reached the warning level. At the same time, monitoring is strengthened and meteorological adjustments and further analysis are carried out; If the aerosol component coefficient Rcf>pollutant warning threshold T2, the third component result is generated, indicating that the pollutant concentration has exceeded the warning threshold, and measures are taken to control pollution.

6. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The meteorological condition adjustment module includes a meteorological data receiving and processing unit and a detection parameter adjustment unit; The meteorological data receiving and processing unit obtains atmospheric conditions in real time, including temperature, humidity, wind speed, wind direction and air pressure, through a meteorological station and other meteorological monitoring equipment; secondly, preprocesses the received data, and uses the preprocessed meteorological data for subsequent model adjustment; The detection parameter adjustment unit adjusts the detection parameters of the aerosol radar based on a preset meteorological model and in combination with meteorological data, including radar wavelength, scanning angle and pulse frequency, and generates a new detection data set with the adjusted parameters.

7. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The path identification module includes a data analysis unit and a path coefficient calculation unit; The data analysis unit is used to receive the vertical distribution data and the adjusted new detection parameter set from the aerosol radar, and to perform a preliminary analysis on the temporal and spatial distribution of the aerosol; and to determine the movement trajectory and distribution trend of the pollutants through the concentration change and scanning data of the aerosol; The path coefficient calculation unit quantitatively analyzes the transmission path of the aerosol, extracts the vertical distribution data of the aerosol radar, performs dimensionless processing, and calculates the propagation path coefficient Ptc: Ptc=∫ V C(x,y,z)·V(x,y,z)·A(x,y,z)dv; Where C(x,y,z,) represents the aerosol concentration distribution in μg / m 3 ; V(x,y,z) represents the spatial distribution of wind speed along the aerosol path, in m / s; A(x,y,z) represents the diffusion cross-sectional area of ​​the aerosol, in m 2 ; dv is the integral symbol, which is the integral of the spatial volume V, and the unit is m 3 .

8. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The pollution source positioning module includes a model building unit and a positioning analysis unit; The pollution source location model constructed by the model building unit presets the distribution of different pollution sources in the geographic space; by collecting relevant data and meteorological data in the pollution source location model, and combining them with the propagation path coefficient Ptc and the component identification coefficient Rcf, the potential pollution source location is identified through the fitting algorithm, and the pollution source location index Psp is generated. The specific formula in the fitting process is: Where N represents the normalization factor, Ppl represents the emission frequency, Pst represents the emission duration, Ksx represents the diffusion coefficient, Wd represents the temperature, Sd represents the humidity, Fs represents the wind speed, Fx represents the wind direction, and Qy represents the air pressure; The positioning analysis unit is used to combine the pollution source positioning index Psp with geographic data for spatial analysis; at the same time, by comparing with field monitoring data, the location accuracy of the pollution source is further verified.

9. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The comprehensive assessment module includes a pollution source comparison unit and a pollution prevention and control suggestion generation unit; The pollution source comparison unit extracts historical data related to the current air pollution source from the historical database, including historical pollution events, pollution source locations, pollution diffusion patterns and pollution intensity, and fits the historical data related to the air pollution source to obtain the historical pollution location index Lpsp; The pollution source similarity Wrxs is calculated by the following formula; 10. The atmospheric source tracing system based on aerosol radar according to claim 1, characterized in that: The pollution prevention suggestion generation unit evaluates the pollution source similarity Wrxs by presetting a first similarity threshold P1 and a second similarity threshold P2, wherein the first similarity threshold P1 is greater than the second similarity threshold P2, and the evaluation content is: When the pollution source similarity Wrxs ≥ similarity threshold P1, the first similarity result is generated; When the first similarity threshold P1>pollution source similarity Wrxs>second similarity threshold P2, a second similarity result is generated; When the pollution source similarity Wrxs ≤ similarity threshold P2, the third similarity result is generated; Based on the evaluation and analysis results, an air pollution prevention and control recommendation report is automatically generated, specifically: When the first similar result is generated, historically successful prevention and control strategies should be adopted, including strict emission control, additional pollution control facilities, large-scale environmental cleanup, as well as limiting operating hours, adjusting control facilities, and implementing emergency response measures; When the second similar result is generated, some specific adjustment measures are taken in combination with the general prevention and control strategy, including adjusting the production process, adjusting daily monitoring and implementing local control; When a third similar result is generated, take basic contamination control measures to prevent potential problems, including performing routine maintenance, adjusting production management, and conducting routine inspections.

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