Accurate traceability method and system for atmospheric pollution source

Abstract

The invention relates to the technical field of air pollution tracing, and particularly discloses an air pollution source accurate tracing method and system, and the system comprises a multi-source data monitoring module, a multi-source data analysis module, a pollution tracing comprehensive analysis module, a pollution diffusion model verification optimization module, and a pollution tracing analysis module. By comprehensively considering various factors, setting a proportionality coefficient to calculate a pollution traceability comprehensive index and comparing the pollution traceability comprehensive index with a threshold value, a pollution traceability area and a potential area can be effectively marked, simulation concentration is calculated according to actual parameters in combination with the verification and optimization process of a pollution diffusion model, a root-mean-square error is reduced by adjusting a source intensity value, and a pollution source diffusion coefficient is increased. According to the method, the model is continuously optimized, so that the model better fits the actual situation, finally, the real pollution source is determined according to the acceptable threshold value, scientific and accurate basis and method are provided for air pollution control, and improvement of the control efficiency and effect and improvement of the atmospheric environment quality are facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of atmospheric pollution source tracing, and specifically refers to a method and system for accurately tracing atmospheric pollution sources. Background Art

[0002] In the field of atmospheric pollution source tracing, traditional methods often have many limitations. On the one hand, most rely only on a single type of data for analysis. For example, they only focus on pollutant concentration monitoring data, while ignoring the comprehensive influence of meteorological conditions, source emission characteristics, and geographical environment on the diffusion and distribution of atmospheric pollution. This leads to one-sided analysis results and low tracing accuracy. On the other hand, in terms of model application, existing models lack effective verification and optimization mechanisms, with fixed model parameters and being unable to well adapt to the actual complex and changeable atmospheric environment. As a result, the simulation results deviate greatly from the actual situation, making it difficult to accurately lock in the real pollution source, thus affecting the pertinence and effectiveness of atmospheric pollution control.

[0003] Most current tracing methods are limited to a certain type of data and cannot comprehensively reflect the causes and propagation processes of atmospheric pollution. Relying only on pollutant concentration data, it is difficult to explain the deep-seated reasons for changes in pollutant concentration, such as the influence of meteorological condition changes (wind speed, wind direction, atmospheric stability, etc.) on pollutant diffusion, and the role of different pollution source emission intensities and geographical locations on the surrounding pollution distribution. This analysis method with a single data source is prone to missing key information, resulting in misjudgment or missed judgment of pollution sources. Summary of the Invention

[0004] In view of the above situation, to overcome the defects of the prior art, the present invention provides a method and system for accurately tracing atmospheric pollution sources to solve the above-mentioned technical defects.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A method for accurately tracing atmospheric pollution sources includes the following steps:

[0006] Step 1: Multi-source data monitoring and acquisition: Set distributed monitoring points in the atmospheric pollution area, and monitor and acquire the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area for each monitoring period through various data monitoring instruments set in each distributed monitoring point. Then, identify and remove outliers that significantly deviate from the normal range from the acquired tracing analysis data through statistical methods. For data with different dimensions, standardize them to have the same scale.

[0007] Step 2: Meteorological data analysis: Extract wind speed, solar radiation intensity and cloud cover data from the meteorological data in the source analysis data, use the Pasquier stability classification method to determine the atmospheric stability level, and assign corresponding parameter values ​​to different levels to obtain the atmospheric stability parameters of each distributed monitoring point in the atmospheric pollution area corresponding to each monitoring period. The atmospheric stability value is calculated by dividing the atmospheric stability parameters of each distributed monitoring point in the atmospheric pollution area corresponding to each monitoring period by the wind speed.

[0008] Step 3: Source emission data analysis: Extract the pollutant emissions per unit time of industrial pollution sources from the source emission data in the source tracing analysis data, and obtain the distance between the emission source and each monitoring point through the geographic information system. By dividing the emission value by the distance, the source shadow value corresponding to each distributed monitoring point in the air pollution area in each monitoring period is obtained.

[0009] Step 4: Geographic information data analysis: Extract terrain complexity parameters from the geographic information data in the source analysis data, and use remote sensing image data to calculate the proportion of vegetation coverage to the total area of ​​the study area through image processing and analysis technology to obtain the vegetation coverage rate. Divide the terrain complexity parameter by the vegetation coverage rate to obtain the ground cover value corresponding to each distributed monitoring point in the air pollution area in each monitoring period.

[0010] Step 5: Comprehensive analysis of pollution source tracing: Extract the sum of the concentrations of various pollutants from the pollutant concentration data in the source tracing analysis data and record it as the pollution concentration value According to a large amount of historical data analysis and verification, the gas stability value is set Source Shadow Value and ground cover value The proportionality coefficients are denoted as k 1 , k 2 , k 3 , according to the formula Calculate the pollution source comprehensive index for each distributed monitoring point in the air pollution area corresponding to each monitoring period By calculating the pollution source comprehensive index of each distributed monitoring point in the air pollution area corresponding to each monitoring period The pollution source tracing comprehensive index threshold is compared with the threshold set by humans based on historical data analysis. Monitoring points with a pollution source tracing comprehensive index greater than the threshold are marked as pollution source tracing areas, and vice versa, they are marked as pollution potential areas;

[0011] Step 6. Verification of pollution diffusion model: Divide the pollution emission amount per unit time by the unit time to obtain the source strength value YQ. At the same time, measure the height of the pollution source emission port from the ground, denoted as the source height value YH. Calculate the average wind speed FU by calculating the average wind speed in each monitoring period. Determine the horizontal diffusion parameter SK and the vertical diffusion parameter CK according to the atmospheric stability grade and the downwind distance. Based on the above parameters, establish a pollution diffusion model to simulate the concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point

[0012] Step 7. Optimization of pollution diffusion model: Extract the monitoring concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point from the pollutant concentration data in the traceability analysis data The simulated concentration of pollutants at a certain point (x, y, z) in the space and the monitoring concentration are comprehensively calculated to obtain the root mean square error WJ and the pollution source diffusion coefficient WR. By adjusting the source strength value, the root mean square error WJ is reduced and the pollution source diffusion coefficient WR is increased to optimize the pollution diffusion model in Step 6;

[0013] Step 8. Determine the pollution traceability area: Conduct statistical analysis based on a large amount of actual monitoring data collected, set an acceptable threshold ΔCE, and calculate the simulated concentration CE of pollutants at a certain point (x, y, z) in the space (x,y,z) and the monitoring concentration the absolute value of the difference. If the above calculation result is greater than the acceptable threshold ΔCE, adjust the source strength value until the simulation result of the model satisfies and this monitoring point is marked as the pollution traceability area, then it is determined that this monitoring point area is the real pollution source.

[0014] Furthermore, the traceability analysis data includes pollutant concentration data, meteorological data, source emission data, and geographic information data.

[0015] Furthermore, when determining the atmospheric stability grade by the Pasquill stability classification method, the atmospheric stability can be divided into six levels: A (extremely unstable), B (unstable), C (weakly unstable), D (neutral), E (weakly stable), F (stable), corresponding to different parameter values respectively.

[0016] Furthermore, the terrain complexity parameter quantifies the terrain complexity through digital elevation model geographic information data, calculates indicators such as the slope, aspect change, and terrain undulation degree of a certain area's terrain, and then synthesizes these indicators into a terrain complexity parameter according to the corresponding set rules.

[0017] Furthermore, the simulated concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point According to the formula

[0018] the simulated concentration of pollutants at a certain point (x, y, z) in space is calculated

[0019] Furthermore, the root mean square error WJ is calculated according to the formula and the pollution source diffusion coefficient WR is calculated according to the formula where respectively represent the average values of the simulated concentration and the monitored concentration

[0020] Furthermore, the root mean square error WJ reflects the average deviation degree between the simulated value and the monitored value. The smaller WJ is, the smaller the overall deviation between the simulated value and the monitored value is, and the higher the accuracy of the model is; the pollution source diffusion coefficient WR measures the linear correlation degree between the simulated value and the monitored value. The closer WR is to 1, the stronger the linear correlation between the simulated value and the monitored value is, and the better the fitting effect of the model to the actual situation is.

[0021] Furthermore, a tracing system for an accurate tracing method of atmospheric pollution sources includes:

[0022] A multi-source data monitoring module, which is used to monitor and obtain the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period through various data monitoring instruments set in each distributed monitoring point;

[0023] A multi-source data analysis module, which is used to calculate and analyze the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period one by one;

[0024] A pollution tracing comprehensive analysis module, which is used to comprehensively calculate and analyze the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area after calculation and analysis to obtain the pollution tracing comprehensive index corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period

[0025] A pollution diffusion model verification and optimization module, which is used to establish a calculation model for the simulated concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point, and optimize the model in combination with the root mean square error WJ and the pollution source diffusion coefficient WR;

[0026] A pollution tracing analysis module, based on the simulated concentration CE of pollutants at a certain point (x, y, z) in space (x,y,z) and the monitored concentration ​And the comprehensive pollution source tracing index corresponding to each distributed monitoring point in the air pollution area during each monitoring period Determine the pollution source area.

[0027] Advantages of the present invention:

[0028] In the present invention, through the setting of distributed monitoring points and the acquisition of multi-source data monitoring, data such as pollutant concentration, meteorology, source emissions, and geographical information are covered, and outlier removal and standardization processing are performed, avoiding the errors of single data analysis, improving the accuracy of source tracing. The Pasquill stability classification method is used to determine the atmospheric stability level and calculate the atmospheric stability value, the source shadow value is obtained by combining source emission data analysis, and the ground cover value is obtained by geographical information data analysis. Considering various factors comprehensively makes the source tracing analysis more comprehensive. At the same time, by setting a proportional coefficient to calculate the comprehensive pollution source tracing index and comparing it with the threshold, the pollution source tracing area and potential area can be effectively marked. Combining the verification and optimization process of the pollution diffusion model, the simulated concentration is calculated based on actual parameters, and the root mean square error is reduced and the pollution source diffusion coefficient is increased by adjusting the source strength value, continuously optimizing the model to make it more in line with the actual situation. Finally, the real pollution source is determined based on the acceptable threshold, providing a scientific and accurate basis and method for air pollution control, helping to improve the control efficiency and effect, and improving the air quality. Description of the drawings

[0029] The present invention will be further described below with reference to the drawings.

[0030] Figure 1 It is a flowchart of a method for accurately tracing air pollution sources according to an embodiment of the present invention;

[0031] Figure 2 It is a principle block diagram of a system for accurately tracing air pollution sources according to an embodiment of the present invention. Specific implementation manners

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall also fall within the protection scope of the present invention.

[0033] As shown in the present invention and the claims, unless the context clearly indicates otherwise, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0034] Although the present invention makes various references to certain modules in the system according to embodiments of the present invention, any number of different modules may be used and run on a user terminal and / or a server. The modules are merely illustrative, and different aspects of the system and method may use different modules.

[0035] Flowcharts are used in the present invention to illustrate the operations performed by the system according to embodiments of the present invention. It should be understood that the operations before or below do not necessarily have to be performed precisely in order. Instead, various steps may be performed in reverse order or simultaneously as needed. Also, other operations may be added to these processes, or one or several steps may be removed from these processes.

[0036] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein.

[0037] Embodiment 1:

[0038] Please refer to Figure 1 As shown, an accurate tracing method for atmospheric pollution sources includes the following steps:

[0039] Step 1: Multi-source data monitoring and acquisition: Set distributed monitoring points in the atmospheric pollution area, and monitor and acquire the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period through various data monitoring instruments set in each distributed monitoring point. Identify and remove outliers that significantly deviate from the normal range from the acquired tracing analysis data through statistical methods, and for data with different dimensions, make them have the same scale through standardization processing;

[0040] It should be noted that the tracing analysis data includes pollutant concentration data, meteorological data, source emission data, and geographical information data. Through comprehensive analysis after monitoring and acquiring multi-source data, the error of the single-data analysis result can be avoided, and the accuracy of tracing atmospheric pollution sources can be improved.

[0041] Step 2: Meteorological data analysis: Extract wind speed, solar radiation intensity, and cloud cover data from the meteorological data in the tracing analysis data, determine the atmospheric stability grade using the Pasquill stability classification method, and assign corresponding parameter values to different grades to obtain the atmospheric stability parameters corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period. Calculate the gas stability value by dividing the atmospheric stability parameters corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period by the wind speed

[0042] It should be noted that when determining the atmospheric stability level through the Pasquill stability classification method, the atmospheric stability can be divided into six levels: A (extremely unstable), B (unstable), C (weakly unstable), D (neutral), E (weakly stable), and F (stable), corresponding to different parameter values. Assuming that the parameter values corresponding to levels A - F are 6, 4, 3, 2, 1, and 0.5 in sequence (the specific parameter values can be determined according to actual research and experience), if the atmospheric stability at a certain moment is determined to be level C through meteorological conditions, then the value of the atmospheric stability parameter is 3.

[0043] Step 3: Analysis of source emission data: Extract the emissions of pollutants per unit time from industrial pollution sources from the source emission data in the traceability analysis data. At the same time, obtain the distances between emission sources and each monitoring point through a geographic information system. By dividing the emission amount value by the distance, the source shadow value corresponding to each distributed monitoring point in the air pollution area for each monitoring period is obtained.

[0044] It should be noted that in addition to industrial pollution sources, the emission intensity of traffic pollution sources can also be obtained. According to information such as traffic flow, vehicle types, and fuel types, the emission intensity is calculated in combination with the corresponding emission model; use GPS positioning devices to obtain the coordinates of emission sources (such as factory chimneys, traffic arteries, etc.) and monitoring points respectively, and then calculate the distance between the two through a distance calculation formula (such as the distance formula between two points in a plane rectangular coordinate system).

[0045] Step 4: Analysis of geographic information data: Extract the terrain complexity parameter from the geographic information data in the traceability analysis data. At the same time, use remote sensing image data, and through image processing and analysis techniques, calculate the proportion of the area covered by vegetation in the total area of the study area to obtain the vegetation coverage rate. Divide the terrain complexity parameter by the vegetation coverage rate to obtain the ground cover value corresponding to each distributed monitoring point in the air pollution area for each monitoring period.

[0046] It should be noted that the terrain complexity parameter quantifies the terrain complexity through digital elevation model geographic information data, calculates indicators such as the slope, aspect change, and terrain undulation of a certain area's terrain, and then synthesizes these indicators into a terrain complexity parameter according to the corresponding set rules. The corresponding rules are artificially set according to industry standard requirements.

[0047] Step 5: Comprehensive analysis of pollution traceability: Extract the sum of the concentrations of various pollutants from the pollutant concentration data in the traceability analysis data, denoted as the pollution concentration value. Based on the analysis and verification of a large amount of historical data, set the atmospheric stability value Source shadow value And the ground cover value The proportionality coefficients of are respectively denoted as k 1 、k2 、k 3 , according to the formula calculate the pollution source tracing comprehensive index for each distributed monitoring point in the air pollution area corresponding to each monitoring period By comparing the pollution source tracing comprehensive index for each distributed monitoring point in the air pollution area corresponding to each monitoring period with the pollution source tracing comprehensive index threshold set artificially according to historical data analysis, mark the monitoring points with a pollution source tracing comprehensive index greater than the pollution source tracing comprehensive index threshold as pollution source tracing areas, and vice versa, mark them as potential pollution areas;

[0048] Step 6: Pollution diffusion model verification: Divide the pollution emission amount per unit time by the unit time to obtain the source strength value YQ. At the same time, measure the height of the pollution source emission port from the ground, denoted as the source height value YH. Calculate the average wind speed FU by calculating the average wind speed in each monitoring period. Determine the horizontal diffusion parameter SK and the vertical diffusion parameter CK according to the atmospheric stability level and the downwind distance. Based on the above parameters, establish a pollution diffusion model to simulate the concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point for calculation. According to the formula

[0049] calculate the simulated concentration of pollutants at a certain point (x, y, z) in the space where e represents the natural constant.

[0050] It should be noted that for the determination of the horizontal diffusion parameter SK, specifically: find the corresponding diffusion curve according to the downwind distance. Assume the downwind distance is 1000m. For Class B atmosphere, according to the empirical formula SK = a*(downwind distance)^b, where a and b are constants related to the atmospheric stability level (for Class B, a may be 0.16 and b may be 0.85), then SK = 0.16*(1000)^0.85 ≈ 120m; for the determination of the vertical diffusion parameter CK, although it is also determined according to the atmospheric stability level and the downwind distance, the formula and coefficients are different. Specifically: find the corresponding formula or curve according to the downwind distance. Assume the downwind distance is 500m. For Class D atmosphere, according to the empirical formula CK = c*(downwind distance)^d (c and d are constants, for Class D, c may be 0.12 and d may be 0.90), then CK = 0.12*(500)^0.90 ≈ 40m.

[0051] Step 7: Pollution diffusion model optimization: Extract the monitoring concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point from the pollutant concentration data in the traceability analysis data The simulated concentration of pollutants at a certain point (x, y, z) in the space and the monitored concentration Perform comprehensive calculations to obtain the root mean square error WJ and the pollution source diffusion coefficient WR. By adjusting the source strength value, reduce the root mean square error WJ and increase the pollution source diffusion coefficient WR, and continuously optimize the pollution diffusion model in step six;

[0052] Among them, the root mean square error WJ is calculated according to the formula The pollution source diffusion coefficient WR is calculated according to the formula Calculate, where Respectively represent the simulated concentration and the monitored concentration The average value of.

[0053] It should be noted that the root mean square error WJ reflects the average deviation degree between the simulated value and the monitored value. The smaller the WJ, the smaller the overall deviation between the simulated value and the monitored value, and the higher the accuracy of the model; the pollution source diffusion coefficient WR measures the linear correlation degree between the simulated value and the monitored value. The closer WR is to 1, the stronger the linear correlation between the simulated value and the monitored value, and the better the fitting effect of the model to the actual situation.

[0054] Step eight: Determine the pollution source tracing area: Conduct statistical analysis based on a large amount of actual monitoring data collected, set an acceptable threshold ΔCE, and calculate the simulated concentration CE of the pollutant at a certain point (x, y, z) in space (x,y,z) and the monitored concentration The absolute value of the difference. If the above calculation result is greater than the acceptable threshold ΔCE, adjust the source strength value until the simulation result of the model satisfies And this monitoring point is marked as the pollution source tracing area, then it is determined that the area of this monitoring point is the real pollution source.

[0055] It should be noted that the acceptable threshold ΔCE is calculated by calculating the average value and standard deviation of the absolute value of the difference between the simulated concentration and the monitored concentration at each monitoring point, and the result of adding twice the standard deviation to the average value is used as the acceptable threshold.

[0056] Example 2:

[0057] Specifically, this embodiment discloses a system applied to the method for accurately tracing atmospheric pollution sources in the above-mentioned embodiment 1, including:

[0058] A multi-source data monitoring module for monitoring and obtaining the tracing analysis data corresponding to each distributed monitoring point in the atmospheric pollution area during each monitoring period through various data monitoring instruments set in each distributed monitoring point;

[0059] A multi-source data analysis module for calculating and analyzing the source tracing analysis data corresponding to each distributed monitoring point in the air pollution area for each monitoring period one by one;

[0060] A comprehensive pollution source tracing analysis module for comprehensively calculating and analyzing the source tracing analysis data corresponding to each distributed monitoring point in the air pollution area after calculation and analysis to obtain the comprehensive pollution source tracing index corresponding to each distributed monitoring point in the air pollution area for each monitoring period

[0061] A pollution diffusion model verification and optimization module for establishing a calculation model for the simulated concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point and optimizing the model by combining the root mean square error WJ and the pollution source diffusion coefficient WR;

[0062] A pollution source tracing analysis module based on the simulated concentration CE of pollutants at a certain point (x, y, z) in space (x,y,z) and the monitoring concentration as well as the comprehensive pollution source tracing index corresponding to each distributed monitoring point in the air pollution area for each monitoring period to determine the pollution source area.

[0063] In summary, in the present invention, through the setting of distributed monitoring points and the acquisition of multi-source data monitoring, data such as pollutant concentration, meteorology, source emission, and geographical information are covered, and outlier removal and standardization processing are performed, avoiding the errors of single data analysis, improving the accuracy of source tracing, using the Pasquill stability classification method to determine the atmospheric stability level and calculate the gas stability value, obtaining the source shadow value by combining source emission data analysis, and obtaining the ground cover value by geographical information data analysis, comprehensively considering various factors, making the source tracing analysis more comprehensive. At the same time, by setting a proportional coefficient to calculate the comprehensive pollution source tracing index and comparing it with the threshold, the pollution source tracing area and potential area can be effectively marked. Combining the verification and optimization process of the pollution diffusion model, calculating the simulated concentration according to the actual parameters, reducing the root mean square error and increasing the pollution source diffusion coefficient by adjusting the source strength value, continuously optimizing the model to make it more in line with the actual situation, and finally determining the real pollution source according to the acceptable threshold, providing a scientific and accurate basis and method for air pollution control, helping to improve the treatment efficiency and effect, and improving the air environmental quality.

[0064] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation. The magnitude of the coefficient is a specific value obtained by quantifying each parameter. Regarding the magnitude of the coefficient, as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0065] In addition, those skilled in the art can understand that various aspects of the present invention can be illustrated and described by several patentable types or situations, including any new and useful process, machine, product, or combination of substances, or any new and useful improvement thereof. Accordingly, various aspects of the present invention can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above-mentioned hardware or software can all be referred to as "data blocks", "modules", "engines", "units", "components", or "systems". In addition, various aspects of the present invention may be embodied as a computer product located in one or more computer-readable media, which includes computer-readable program codes.

[0066] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by those of ordinary skill in the art to which this invention belongs. It should also be understood that terms such as those defined in a common dictionary should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0067] The above is the description of the present invention and should not be regarded as a limitation thereof. Although several exemplary embodiments of the present invention have been described, those skilled in the art will readily understand that many modifications can be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined by the claims. It should be understood that the above is the description of the present invention and should not be considered limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A method for accurately tracing the source of air pollution, characterized in that: The following steps are involved: Step 1: Multi-source data monitoring and acquisition: Distributed monitoring points are set up in the air pollution area, and the traceability analysis data of each distributed monitoring point in the air pollution area corresponding to each monitoring period is monitored and acquired through various data monitoring instruments set up in each distributed monitoring point. The acquired traceability analysis data is identified by statistical methods, and outliers that obviously deviate from the normal range are removed. For data of different dimensions, they are standardized to have the same scale; Step 2: Meteorological data analysis: Extract wind speed, solar radiation intensity and cloud cover data from the meteorological data in the source analysis data, use the Pasquier stability classification method to determine the atmospheric stability level, and assign corresponding parameter values ​​to different levels to obtain the atmospheric stability parameters of each distributed monitoring point in the atmospheric pollution area corresponding to each monitoring period. The atmospheric stability value ME is calculated by dividing the atmospheric stability parameters of each distributed monitoring point in the atmospheric pollution area corresponding to each monitoring period by the wind speed. j i ; Step 3: Source emission data analysis: Extract the pollutant emissions per unit time of industrial pollution sources from the source emission data in the source tracing analysis data, and obtain the distance between the emission source and each monitoring point through the geographic information system. By dividing the emission value by the distance, the source shadow value corresponding to each distributed monitoring point in the air pollution area in each monitoring period is obtained. Step 4: Geographic information data analysis: Extract terrain complexity parameters from the geographic information data in the source analysis data, and use remote sensing image data to calculate the proportion of vegetation coverage to the total area of ​​the study area through image processing and analysis technology to obtain the vegetation coverage rate. Divide the terrain complexity parameter by the vegetation coverage rate to obtain the ground cover value corresponding to each distributed monitoring point in the air pollution area in each monitoring period. Step 5: Comprehensive analysis of pollution source tracing: Extract the sum of the concentrations of various pollutants from the pollutant concentration data in the source tracing analysis data and record it as the pollution concentration value According to a large amount of historical data analysis and verification, the gas stability value is set Source Shadow Value and ground cover value The proportional coefficients are denoted as k1, k2, and k3 respectively. According to the formula Calculate the pollution source comprehensive index for each distributed monitoring point in the air pollution area corresponding to each monitoring period By calculating the pollution source comprehensive index of each distributed monitoring point in the air pollution area corresponding to each monitoring period The pollution source tracing comprehensive index threshold is compared with the threshold set by humans based on historical data analysis. Monitoring points with a pollution source tracing comprehensive index greater than the threshold are marked as pollution source tracing areas, and vice versa, they are marked as pollution potential areas; Step 6: Verification of the pollution diffusion model: Divide the pollution emission per unit time by the unit time to obtain the source strength value YQ. At the same time, measure the height of the pollution source emission port from the ground, which is recorded as the source height value YH. Calculate the average wind speed in each monitoring period to obtain the average wind speed FU. Determine the horizontal diffusion parameter SK and the vertical diffusion parameter CK according to the atmospheric stability level and the downwind distance. Based on the above parameters, establish a pollution diffusion model to simulate the concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point. Step 7: Pollution diffusion model optimization: Extract the monitoring concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point from the pollutant concentration data in the source traceability analysis data The simulated concentration of the pollutant at a point (x, y, z) in space and monitoring concentration Perform comprehensive calculations to obtain the root mean square error WJ and the pollution source diffusion coefficient WR. By adjusting the source strength value, the root mean square error WJ is reduced and the pollution source diffusion coefficient WR is increased, and the pollution diffusion model in step six is ​​optimized; Step 8. Determine the pollution source area: Perform statistical analysis based on the large amount of actual monitoring data collected, set an acceptable threshold ΔCE, and calculate the simulated concentration CE of the pollutant at a certain point in space (x, y, z) (x,y,z) and monitoring concentration If the above calculation result is greater than the acceptable threshold ΔCE, the source strength value is adjusted until the simulation result of the model meets If the monitoring point is marked as a pollution source tracing area, the monitoring point area is determined to be the real pollution source.

2. The method for accurately tracing the source of air pollution according to claim 1, characterized in that: The source tracing analysis data includes pollutant concentration data, meteorological data, source emission data and geographic information data.

3. The method for accurately tracing the source of air pollution according to claim 1 is characterized in that: When determining the atmospheric stability level through the Pasquier stability classification method, the atmospheric stability is divided into A extremely unstable, B unstable, C weakly unstable, D neutral, E weakly stable and F stable, corresponding to different parameter values.

4. The method for accurately tracing the source of air pollution according to claim 1 is characterized in that: The terrain complexity parameter quantifies the terrain complexity through the digital elevation model geographic information data, calculates the slope, slope change, and terrain undulation indicators of a certain area, and then combines these indicators into a terrain complexity parameter according to the corresponding set rules.

5. The method for accurately tracing the source of air pollution according to claim 1, characterized in that: The simulated concentration of the pollutant at a certain point (x, y, z) in the space of each monitoring point According to the formula Calculate the simulated concentration of pollutants at a point (x, y, z) in space 6. The method for accurately tracing the source of air pollution according to claim 1, characterized in that: The root mean square error WJ is based on the formula Calculated, the pollution source diffusion coefficient WR is based on the formula Calculated, where Respectively, the simulated concentrations and monitoring concentration The average value of .

7. The method for accurately tracing the source of air pollution according to claim 1, characterized in that: The root mean square error WJ reflects the average deviation between the simulated values ​​and the monitored values. The smaller the WJ, the smaller the overall deviation between the simulated values ​​and the monitored values, and the higher the accuracy of the model. The pollution source diffusion coefficient WR measures the linear correlation between the simulated values ​​and the monitored values. The closer WR is to 1, the stronger the linear correlation between the simulated values ​​and the monitored values.

8. A tracing system applied to the method for accurately tracing the source of air pollution according to any one of claims 1 to 7, characterized in that: include: The multi-source data monitoring module is used to monitor and obtain the traceability analysis data of each distributed monitoring point in the air pollution area corresponding to each monitoring period through various data monitoring instruments set in each distributed monitoring point; The multi-source data analysis module is used to calculate and analyze the traceability analysis data of each distributed monitoring point in the air pollution area corresponding to each monitoring period; The pollution source tracing comprehensive analysis module is used to perform comprehensive calculation and analysis on the tracing analysis data of each distributed monitoring point in the air pollution area corresponding to each monitoring period after calculation and analysis, and obtain the pollution source tracing comprehensive index of each distributed monitoring point in the air pollution area corresponding to each monitoring period The pollution diffusion model verification and optimization module is used to establish the simulated concentration of pollutants at a certain point (x, y, z) in the space of each monitoring point. The calculation model is optimized by combining the root mean square error WJ and the pollution source diffusion coefficient WR; Pollution source analysis module, based on the simulated concentration CE of pollutants at a certain point in space (x, y, z) (x,y,z) and monitoring concentration And the pollution source comprehensive index corresponding to each distributed monitoring point in the air pollution area during each monitoring period Identify the pollution source areas.

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