A method for tracing air pollution sources and related devices

Abstract

The present application provides a method for tracing the source of atmospheric pollution and related devices, relating to the technical field of atmospheric pollution prevention and control, including: obtaining the site identification of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period; based on the site identification, screening out multiple emission sources that have a spatial position relationship with the air quality monitoring site from a preset association table and obtaining the emission data of each emission source; using the meteorological data and emission data, calculating the prior probability that the emission source causes air quality abnormality and the likelihood probability that the emission source causes air quality abnormality; calculating the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source; and determining the emission source to be traced from all emission sources based on the posterior probability of each emission source, wherein the emission source to be traced is the emission source that is most likely to cause air quality abnormality among all emission sources, thereby realizing rapid tracing of the pollution source.

Description

Technical Field

[0001] The present application relates to the technical field of air pollution prevention and control, and in particular to an air pollution source tracing method and related devices. Background Art

[0002] Atmospheric pollution source tracing is to trace the source of pollutants when abnormal air quality is detected at air quality monitoring stations. In the current atmospheric pollution source tracing method, the chimney parameter data and meteorological data of the emission source are used as input data, and the physical diffusion simulation method is used to trace the pollution source.

[0003] Taking the commonly used environmental impact assessment model CALPUFF as an example, the model takes chimney parameter data and meteorological data as input. It uses a non-steady-state Lagrangian puff diffusion model to numerically simulate the entire process of pollutant emission, transport, and diffusion. The model characterizes pollutant concentration distribution by tracking the spatiotemporal evolution of discrete "puffs" in the simulation. Specifically, the model first inputs meteorological data (such as wind speed, temperature, turbulence, and wind direction) to reflect the characteristics of realistic atmospheric stratification and local circulation. Then, using chimney parameter data (such as emission rate, emission height, and exit velocity) from emission sources during air quality anomalies, the model calculates the trajectory of each puff as it is advected along the airflow. This model also accounts for puff expansion caused by turbulent diffusion, dry and wet deposition effects, and chemical reactions between pollutants. By superimposing the contributions of all puffs to the pollutant concentrations measured at air quality monitoring stations at different times, a spatiotemporally continuous pollutant distribution field is generated.

[0004] Because the model needs to perform physical diffusion simulation on the transmission process of pollutants emitted by each puff, the simulation calculation amount is large and the response time is long, making it difficult to quickly trace the source of pollution. Summary of the Invention

[0005] In view of the above problems, this application provides a method and related device for tracing the source of air pollution to achieve the purpose of rapid tracing. The specific solution is as follows:

[0006] The first aspect of the present application provides a method for tracing the source of air pollution, comprising:

[0007] Obtaining the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period, where the pollutant type refers to at least one pollutant, and the abnormally high value period is the period when the abnormal emission of the pollutant causes the air quality monitoring site to monitor abnormal air quality;

[0008] Based on the site identifier, a plurality of emission sources having a spatial position relationship with the air quality monitoring site are screened from a preset association relationship table, and emission data of each emission source is obtained from the preset association relationship table, wherein the plurality of emission sources having a spatial position relationship are emission sources that may affect the air quality monitored by the air quality monitoring site;

[0009] For any emission source, using the meteorological data and the emission data, calculate the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality;

[0010] Calculating a posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source, wherein the posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the combined effect of the abnormal emission of the pollutant and the meteorological conditions corresponding to the meteorological data;

[0011] According to the posterior probability of each emission source, an emission source to be traced is determined from all emission sources, and the emission source to be traced is the emission source that is most likely to cause the abnormal air quality among all emission sources.

[0012] In a possible implementation, the calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes:

[0013] Calculating a priori probability that the emission source causes abnormal air quality using the permitted emission amount of the pollutant recorded in the emission data, wherein the priori probability represents a probability that the abnormal emission of the pollutant by the emission source causes the abnormal air quality;

[0014] Calculating a wind speed correction factor, a distance attenuation factor, a wind direction weight, and an atmospheric stability correction factor using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring station;

[0015] Calculating the likelihood probability that the emission source causes abnormal air quality using the wind speed correction factor, the distance attenuation factor, the wind direction weight, the atmospheric stability correction factor, and the prior probability, wherein the likelihood probability represents the probability that the abnormal air quality is caused by the abnormal emission of the pollutants by the emission source under the meteorological conditions;

[0016] or,

[0017] The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes:

[0018] Calculating a wind speed correction factor, a distance attenuation factor, a wind direction weight, and an atmospheric stability correction factor using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring station;

[0019] Calculating a priori probability that the emission source causes air quality anomaly using the wind speed correction factor, the distance attenuation factor, the wind direction weight, and the atmospheric stability correction factor, wherein the priori probability represents the impact of the meteorological conditions on the transmission of the pollutant;

[0020] The likelihood probability that the emission source causes abnormal air quality is calculated using the emission allowable amount of the pollutant recorded in the emission data and the prior probability.

[0021] In one possible implementation, calculating the wind speed correction factor, the distance attenuation factor, the wind direction weight, and the atmospheric stability correction factor by using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring site includes:

[0022] Calculate the wind speed correction factor according to the formula f_w=exp(-1 / v), where f_w is the wind speed correction factor and v is the wind speed in the meteorological data;

[0023] Calculate the distance attenuation factor according to the formula f_r=exp(-d / d_c), where f_r is the distance attenuation factor, d is the distance from the emission source to the air quality monitoring site in the spatial position relationship, d_c is the characteristic distance, and d_c=v×a preset first constant;

[0024] The wind direction weight is calculated according to the formula f_d=(1-cos(θ_w-θ_s)) / 2, where f_d is the wind direction weight, θ_w is the wind direction angle in the meteorological data, and θ_s is the azimuth of the emission source relative to the air quality monitoring station;

[0025] According to the atmospheric stability level in the meteorological data, the atmospheric stability correction factor matching the atmospheric stability level is obtained from a preset correction relationship table.

[0026] In a possible implementation, the calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes:

[0027] Obtaining chimney parameter data and the emission permit of the pollutant from the emission data, calculating the ground concentration of the emission source using the chimney parameter data, the meteorological data, and the emission permit, and calculating a priori probability that the emission source causes air quality anomaly using the ground concentration of the emission source, the priori probability representing the impact of the meteorological conditions on pollutant transmission;

[0028] Calculating the likelihood probability that the emission source causes abnormal air quality using the emission allowance, wherein the likelihood probability represents the probability that the abnormal emission of the pollutants by the emission source causes the abnormal air quality;

[0029] or,

[0030] The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes:

[0031] Obtaining chimney parameter data and emission allowances of the pollutants from the emission data;

[0032] Calculating, using the permitted emission amount of the pollutant, a priori probability that the emission source causes abnormal air quality, wherein the priori probability represents the probability that the abnormal emission of the pollutant by the emission source causes the abnormal air quality;

[0033] The chimney parameter data, the meteorological data and the emission permit are used to calculate the ground concentration of the emission source, and the ground concentration of the emission source is used to calculate the likelihood probability that the emission source causes air quality abnormality, and the likelihood probability represents the impact of the meteorological conditions on pollutant transmission.

[0034] In one possible implementation, the method further includes:

[0035] Obtaining chimney parameter data and the emission allowance of the pollutant from the emission data of the emission source to be traced;

[0036] Calculating the ground concentration of the emission source using the chimney parameter data, the meteorological data, and the emission permit;

[0037] The ground concentration of the emission source is visually displayed in a preset manner.

[0038] In a possible implementation, the calculating the ground concentration of the emission source using the chimney parameter data, the meteorological data, and the emission permit includes:

[0039] Calculate the effective chimney height of the emission source to be traced according to the formula H=h+Δh, where H is the effective chimney height, h is the actual chimney height in the chimney parameter data, Δh is the lifting height, and Δh=d_s×v_s×(1-T_a / T_s) / v, d_s is the chimney outlet inner diameter in the chimney parameter data, v_s is the outlet velocity in the chimney parameter data, T_s is the exhaust temperature in the chimney parameter data, T_a is the ambient temperature in the meteorological data, and v is the wind speed in the meteorological data;

[0040] Calculate the lateral diffusion parameter according to the formula σ_y=a_y×x / (1+b_y×x)^c_y, where σ_y is the lateral diffusion parameter, x is the downwind distance in the meteorological data, and a_y, b_y, and c_y are preset atmospheric stability coefficients, where a_y, b_y, and c_y are determined according to the atmospheric stability level in the meteorological data;

[0041] Calculate the vertical diffusion parameter according to the formula σ_z=a_z×x / (1+b_z×x)^c_z, where σ_z is the vertical diffusion parameter, and a_z, b_z, and c_z are preset atmospheric stability coefficients, which are determined according to the atmospheric stability level in the meteorological data;

[0042] Using Gaussian ground model

[0043] C(x,y,0)=(Q / (2π×v×σ_y×σ_z))×exp(-y² / (2σ_y²))×exp(-H² / (2σ_z²)) calculates the ground concentration of the emission source to be traced, C(x,y,0) is the ground concentration, Q is the emission rate, Q=the preset multiple of the emission permit ÷ 365 days ÷ 24 hours ÷ 3600 seconds, v is the wind speed, y is the lateral distance, and H is the effective chimney height.

[0044] In one possible implementation, the method further includes:

[0045] Obtaining emission data of each emission source in a preset area to be monitored, the emission data of the emission source including the pollutants that can be emitted by the emission source, the emission permit amount of the pollutants that can be emitted, the geographical location data of the emission source, and the chimney parameter data of the emission source, the chimney parameter data including the actual chimney height, the inner diameter of the chimney outlet, the outlet velocity, and the exhaust temperature;

[0046] Classifying pollutants that can be emitted by the emission source to obtain a pollutant mapping relationship, wherein the pollutant mapping relationship records pollutants belonging to the same pollutant type;

[0047] Obtaining site data of each of the air quality monitoring sites in the preset monitored area, the site data including geographic location data of the air quality monitoring site and a site identifier of the air quality monitoring site, the site identifier being used to point to a unique air quality monitoring site;

[0048] Performing cleaning and preprocessing operations on the site data of each of the air quality monitoring sites to obtain the site data of the air quality monitoring sites available in the preset area to be monitored;

[0049] Calculating the distance from the emission source to the available air quality monitoring site using the geographic location data of the emission source and the geographic location data of the available air quality monitoring site, wherein the distance from the emission source to the available air quality monitoring site is recorded in the spatial position relationship between the emission source and the available air quality monitoring site;

[0050] Determine the emission sources whose distance from the available air quality monitoring sites is within a preset distance range, and record the emission data of the emission sources within the preset distance range, the pollutant mapping relationship of the emission sources, the site data of the available air quality monitoring sites, and the spatial position relationship between the emission sources and the available air quality monitoring sites in the preset association relationship table. The available air quality monitoring sites can be used as the air quality monitoring sites to be traced.

[0051] A second aspect of the present application provides an atmospheric pollution source tracing device, comprising:

[0052] A first acquisition module is configured to obtain a site identifier of an air quality monitoring site to be traced, a type of pollutant to be traced, and meteorological data during an abnormally high-value period, wherein the pollutant type refers to at least one pollutant, and the abnormally high-value period is a period during which abnormal emissions of the pollutant cause the air quality monitoring site to detect abnormal air quality;

[0053] a screening module, configured to screen, based on the site identifier, a plurality of emission sources that have a spatial position relationship with the air quality monitoring site from a preset association relationship table, and obtain emission data of each of the emission sources from the preset association relationship table, wherein the plurality of emission sources that have a spatial position relationship are emission sources that may affect the air quality monitored by the air quality monitoring site;

[0054] A first calculation module is configured to calculate, for any emission source, a priori probability that the emission source causes abnormal air quality and a likelihood probability that the emission source causes abnormal air quality using the meteorological data and the emission data;

[0055] a second calculation module, configured to calculate a posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source, wherein the posterior probability of the emission source indicates a probability that the abnormal air quality is caused by the combined effect of the abnormal emission of the pollutants and the meteorological conditions corresponding to the meteorological data;

[0056] A determination module is used to determine the emission source to be traced from all emission sources based on the posterior probability of each emission source, and the emission source to be traced is the emission source that is most likely to cause the abnormal air quality among all emission sources.

[0057] A third aspect of the present application provides an electronic device, comprising at least one processor and a memory connected to the processor, wherein:

[0058] The memory is used to store computer programs;

[0059] The processor is used to execute the computer program so that the electronic device can implement the method for tracing the source of atmospheric pollution of the first aspect or any implementation manner of the first aspect.

[0060] The fourth aspect of the present application provides a computer storage medium, which carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement the method for tracing the source of atmospheric pollution according to the first aspect or any implementation of the first aspect.

[0061] The fifth aspect of the present application provides a computer program product, including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements the method for tracing the source of atmospheric pollution according to the first aspect or any implementation of the first aspect.

[0062] By means of the above-mentioned technical scheme, a method for tracing the source of atmospheric pollution provided by the present application can utilize the emission data of the emission source and the meteorological data during the abnormally high value period to calculate the prior probability and the likelihood probability of the emission source causing the air quality abnormality, and then calculate the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source. The posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the abnormal emission of pollutants and meteorological conditions. Then, based on the posterior probability of each emission source, the emission source to be traced is determined from all emission sources, thereby realizing the use of probability to trace the pollution source that causes the air quality abnormality. Therefore, without the need for physical diffusion simulation of the pollutant transmission process, the contribution probability of each emission source to the current air quality abnormality (i.e., the posterior probability) is quantified, thereby reducing the computational cost, improving the response speed, and thus realizing the rapid tracing of the pollution source.

[0063] Furthermore, the emission source to be traced is the one most likely to cause abnormal air quality, determined from among multiple emission sources that have a spatial relationship with the air quality monitoring station. These multiple emission sources with a spatial relationship are emission sources that may affect the air quality monitored by the air quality monitoring station. These emission sources are pre-stored in a preset association table, thereby narrowing the scope of sources to be traced in advance and improving traceability efficiency. Furthermore, the probability calculation uses the emission data pre-stored in the preset association table, eliminating the need for real-time data on pollutant emissions from the emission source, saving data collection time and relying less on data accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The above and other features, advantages, and aspects of the various embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the originals and elements are not necessarily drawn to scale.

[0065] Figure 1 A flow chart of a method for tracing the source of air pollution provided in this application;

[0066] Figure 2 Another flow chart of an air pollution source tracing method provided in this application;

[0067] Figure 3 Another flow chart of an air pollution source tracing method provided in this application;

[0068] Figure 4 A schematic diagram of a method for tracing the source of air pollution provided in this application;

[0069] Figure 5 Another schematic diagram of an air pollution source tracing method provided in this application;

[0070] Figure 6 A schematic structural diagram of an atmospheric pollution source tracing device provided in this application;

[0071] Figure 7 This is another structural schematic diagram of an air pollution source tracing device provided by this application;

[0072] Figure 8 This is a schematic diagram of the structure of the electronic device provided in this application. DETAILED DESCRIPTION

[0073] The following describes the embodiments of the present application in conjunction with the accompanying drawings. The terms used in the implementation methods of the present application are only used to explain the specific embodiments of the present application and are not intended to limit the present application.

[0074] The embodiments of the present application are described below in conjunction with the accompanying drawings. Those skilled in the art will appreciate that, with the development of technology and the emergence of new scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0075] The terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable under appropriate circumstances, and this is merely a way of distinguishing the objects of the same attributes when describing them in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0076] See Figure 1 , which shows a flow chart of an air pollution source tracing method provided by an embodiment of the present application, which may include the following steps:

[0077] S101. Obtain the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period. The pollutant type refers to at least one pollutant. For example, sulfur pollutants may include sulfur dioxide, sulfur trioxide, and sulfuric acid mist, and nitrogen oxides may include nitrogen monoxide and nitrogen dioxide.

[0078] Abnormally high-value periods are periods when abnormal pollutant emissions cause air quality monitoring stations to detect abnormal air quality. In this embodiment, abnormal air quality can mean that the air quality monitoring station detects abnormal emissions of a certain type of pollutant. When abnormal emissions of a certain type of pollutant are detected, rapid tracing of the emission of that type of pollutant is triggered. The type of pollutant to which the abnormal emissions belong is the type of pollutant to be traced, and the air quality monitoring station that detected the abnormality is the air quality monitoring station to be traced.

[0079] One feasible way to determine whether pollutant emissions are abnormal is to compare monitoring data from multiple air quality monitoring stations. If the concentration of a pollutant detected by one air quality monitoring station is greater than the concentration of the same pollutant detected by other air quality monitoring stations, then the emission of that pollutant is considered abnormal. If the concentration of a pollutant detected by an air quality monitoring station is N times the average concentration of the same pollutant detected by other air quality monitoring stations, then the emission of that pollutant is considered abnormal, where N is a natural number greater than 1.

[0080] For example, air quality monitoring site A can monitor sulfur dioxide concentration, which is related to sulfur emissions. When air quality monitoring site A monitors a sulfur dioxide concentration that is three times the average sulfur concentration monitored by other nearby air quality monitoring sites, air quality monitoring site A can determine that there are abnormal sulfur emissions from surrounding pollution sources, sulfur-type pollutants are the type of pollutants to be traced, and air quality monitoring site A is the air quality monitoring site to be traced.

[0081] In some examples, the site identifier of the air quality monitoring site to be traced and the type of pollutant to be traced can be manually input by the user. For example, when the user finds that the air quality monitoring site A monitors an abnormal sulfur concentration or the air quality monitoring site A monitors an abnormal sulfur concentration alarm, the user manually inputs the site identifier of the air quality monitoring site A and the type of pollutant to be traced is sulfur type. In some examples, the air quality monitoring site can automatically input the site identifier when the air quality abnormality is monitored, and automatically determine the type of pollutant to be traced based on the abnormal air quality. For example, the air quality monitoring site A monitors abnormal air quality, and the abnormal air quality is abnormal sulfur concentration. Generally, the abnormal sulfur concentration is caused by abnormal sulfur-type pollutants discharged into the air. The air quality monitoring site needs to trace the sulfur-type pollutants. Therefore, the air quality monitoring site can determine that the type of pollutant to be traced is sulfur type and automatically obtain the site identifier of the air quality monitoring site A.

[0082] In this embodiment, the site identifier of the air quality monitoring site can point to a unique air quality monitoring site, such as the site identifier can be but not limited to a site name or a site identification code. Air quality monitoring sites in different areas may use the same site name, and the air quality monitoring sites are distinguished by the site identification code. The site identification code can be obtained by encoding the site name and the area to which the air quality monitoring site belongs. Meteorological data is used to indicate the meteorological conditions during abnormally high value periods. Meteorological conditions affect the transmission of pollutants, thereby affecting the monitoring of air quality monitoring sites. Therefore, when tracing the source of pollution, the impact of meteorological data should be considered to evaluate the impact of pollutant emissions on air quality under specific meteorological conditions, and to conduct rapid tracing based on multiple factors. Among them, meteorological data can be obtained by the air quality monitoring site from a server that provides meteorological data. The specific acquisition method is not limited in this embodiment. Meteorological data can include data used for probability calculations, such as meteorological data can include wind speed, wind direction angle, downwind distance and ambient temperature, etc. This embodiment does not limit meteorological data.

[0083] S102. Based on the site identifier, multiple emission sources that have a spatial location relationship with the air quality monitoring site are screened out from the preset association relationship table, and emission data of each emission source is obtained from the preset association relationship table. The multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site.

[0084] In this embodiment, the spatial position relationship is used to indicate the geographical location relationship between the emission source and the air quality monitoring site, such as indicating the distance from the emission source to the air quality monitoring site, and further indicating the orientation of the emission source relative to the air quality monitoring site (which can be expressed as an azimuth), etc. The air quality monitoring site can use the site identifier in a preset association table to identify multiple emission sources that have a spatial position relationship with it and store the spatial position relationship between the emission source and the air quality monitoring site in the preset association table. During the tracing process, the site identifier can be used to complete the screening of emission sources, so as to screen out the emission sources that cause abnormal air quality from the multiple emission sources that have a spatial position relationship with the air quality monitoring site, thereby narrowing the emission scope to a certain extent and laying the foundation for rapid tracing.

[0085] The preset association table can also store emission data of the emission source. The emission data can be the emission parameters set for the emission source when the emission source is planned. The emission of the emission source is limited by the emission data. For example, the emission data can specify the pollutants that the emission source can emit and the emission permit amount of each pollutant that can be emitted. The emission permit amount specifies the maximum emission amount of the pollutant that the emission source can emit.

[0086] In the actual tracing process, it is difficult for air quality monitoring stations to collect accurate real-time data on pollutant emissions from emission sources when enterprises secretly discharge. Therefore, in this embodiment, the air quality monitoring station uses emission data, which saves data collection time and is less dependent on data accuracy. And usually, when enterprises secretly discharge pollutants, the amount of pollutants emitted is greater than the amount of emissions recorded in the emission data (such as the emission permit amount). If the air quality monitoring station uses emission data to monitor that the emission source is the source of pollution that caused the abnormal air quality, the enterprise's secret discharge will also cause abnormal air quality. Of course, if the actual emission amount of the emission source is less than the emission amount recorded in the emission data, the air quality monitoring station's monitoring this time is incorrect. Therefore, the air quality monitoring station sacrifices the accuracy of monitoring to a certain extent when using emission data for tracing.

[0087] S103. For any emission source, using meteorological data and emission data, calculate the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality.

[0088] One feasible approach is: using the permitted emission amounts of pollutants recorded in the emission data to calculate the prior probability that the emission source causes abnormal air quality, the prior probability indicates the probability that the abnormal emission of pollutants from the emission source causes abnormal air quality, and the permitted emission amount of pollutants is the maximum emission of pollutants pointed to by the type of pollutant to be traced; using the spatial position relationship between meteorological data, emission sources and air quality monitoring stations to calculate the wind speed correction factor, distance attenuation factor, wind direction weight and atmospheric stability correction factor; using the wind speed correction factor, distance attenuation factor, wind direction weight, atmospheric stability correction factor and prior probability, calculate the likelihood probability that the emission source causes abnormal air quality, the likelihood probability indicates the probability that the abnormal emission of pollutants from the emission source causes abnormal air quality under the meteorological conditions corresponding to the meteorological data. By introducing the prior probability into the likelihood probability, the impact of abnormal pollutant emissions on air quality is transmitted, thereby improving accuracy.

[0089] Among them, one possible implementation method for calculating prior probability and likelihood probability is as follows:

[0090] The prior probability of the i-th emission source is calculated according to the formula P(θ_i)=Q_i / ΣQ_i, where P(θ_i) is the prior probability of the i-th emission source, Q_i is the permitted emission amount of the pollutant recorded in the emission data of the i-th emission source, in t / a (tons / year), and ΣQ_i is the total permitted emission amount of the pollutant from all emission sources, in t / a. It should be noted here that a pollutant type may correspond to multiple pollutants. In the process of calculating the prior probability, the permitted emission amounts of multiple pollutants belonging to the same pollutant type are added together to obtain the prior probability that an emission source will emit multiple pollutants simultaneously.

[0091] The wind speed correction factor is calculated according to the formula f_w=exp(-1 / v), where f_w is the wind speed correction factor and v is the wind speed in the meteorological data. Specifically, the air quality monitoring station can obtain multiple meteorological data during abnormally high periods. When calculating the wind speed correction factor, the wind speed v can be the average wind speed in multiple meteorological data, in units of m / s (meters per second).

[0092] The distance attenuation factor is calculated according to the formula f_r=exp(-d / d_c), where f_r is the distance attenuation factor, d is the distance from the emission source to the air quality monitoring site in the spatial position relationship, in m (meters), d_c is the characteristic distance, and d_c=v×preset first constant. The value of the preset first constant can be, but is not limited to, 3600.

[0093] Calculate the wind direction weight using the formula f_d=(1-cos(θ_w-θ_s)) / 2, where f_d is the wind direction weight, θ_w is the wind direction angle from the meteorological data (in degrees), and θ_s is the azimuth of the emission source relative to the air quality monitoring station (in degrees). The wind direction angle can be the average of wind direction angles from multiple pieces of meteorological data collected by the air quality monitoring station during periods of abnormally high values.

[0094] Based on the atmospheric stability level in the meteorological data, an atmospheric stability correction factor matching the atmospheric stability level is retrieved from a preset correction relationship table. The preset correction relationship table records the correspondence between atmospheric stability levels and atmospheric stability correction factors. After obtaining the atmospheric stability level, the corresponding atmospheric stability correction factor is retrieved from the preset correction relationship table. For example, the atmospheric stability levels are A, B, C, D, E, and F. The atmospheric stability correction factor for Class A is 1.2, the atmospheric stability correction factor for Class B is 1.0, the atmospheric stability correction factor for Class C is 0.8, the atmospheric stability correction factor for Class D is 0.6, the atmospheric stability correction factor for Class E is 0.4, and the atmospheric stability correction factor for Class F is 0.2. If the atmospheric stability level is Class A, the atmospheric stability correction factor retrieved is 1.2. The same atmospheric stability level can be the average atmospheric stability level of multiple meteorological data points obtained by the air quality monitoring station during the period of abnormally high values, or it can be the atmospheric stability level that occurs most frequently, which is not limited in this embodiment.

[0095] After obtaining the above factors, the likelihood probability of the i-th emission source is calculated according to the formula L(θ_i|D)=P(θ_i)×f_w×f_s×f_d×f_r, where L(θ_i|D) is the likelihood probability of the i-th emission source and f_s is the atmospheric stability correction factor. The i-th emission source is one of the multiple emission sources selected in step S102 above. For each of these multiple emission sources, the prior probability and likelihood probability must be calculated according to the above formula.

[0096] Through actual tracing, the inventors discovered that during the pollutant diffusion process, the rule that affects the diffusion of pollutants is: the greater the distance between the emission source and the air quality monitoring station, the smaller the probability that the air quality monitoring station will detect abnormal air quality, and the wind speed and wind direction will also attenuate. The calculation formulas for the above-mentioned correction factors follow this rule. Therefore, the air quality monitoring station can trace the source by vectorizing the probability calculation, which reduces the calculation cost and speeds up the response.

[0097] One point that needs to be explained here is that the pollutants that can be emitted by multiple emission sources that have a spatial relationship with the air quality monitoring station may be different. Among these multiple emission sources, there may be emission sources that do not emit pollutants of the type of pollutants to be traced (referred to as pollutants to be traced). This means that the emission data of the emission source does not record the emission permit of the pollutants to be traced or the emission permit of the pollutants to be traced is zero. The air quality monitoring station can perform any of the following processing on the emission source: 1. Do not calculate the prior probability of the emission source; 2. Use the pollutants to be traced to screen the emission sources before calculating the prior probability to exclude emission sources that do not emit pollutants to be traced; 3. Directly assign the prior probability of the emission source to 0. In addition, the air quality monitoring station can use the azimuth of the emission source relative to the air quality monitoring station to screen the emission source, such as screening out emission sources with an azimuth greater than 0, and only trace the source from these emission sources.

[0098] In this embodiment, the air quality monitoring station may also first use meteorological data to calculate the prior probability that the emission source causes air quality anomalies, and then use the emission allowances and prior probabilities recorded in the emission data to calculate the likelihood probability that the emission source causes air quality anomalies. For example, one possible implementation method is to use the spatial relationship between meteorological data, emission sources, and air quality monitoring stations to calculate the wind speed correction factor, distance attenuation factor, wind direction weight, and atmospheric stability correction factor; use the wind speed correction factor, distance attenuation factor, wind direction weight, and atmospheric stability correction factor to calculate the prior probability that the emission source causes air quality anomalies, where the prior probability represents the impact of meteorological conditions on pollutant transmission; and use the emission allowances and prior probabilities of pollutants recorded in the emission data to calculate the likelihood probability that the emission source causes air quality anomalies.

[0099] The calculation formulas for the wind speed correction factor, distance attenuation factor, wind direction weight, and atmospheric stability correction factor are described above. The prior probability of the i-th emission source is calculated according to the formula P(θ_i) = f_w × f_s × f_d × f_r, where f_w is the wind speed correction factor, f_r is the distance attenuation factor, f_d is the wind direction weight, and f_s is the atmospheric stability correction factor. The likelihood probability of the i-th emission source is calculated according to the formula L(θ_i|D) = P(θ_i) × (Q_i / ΣQ_i), where Q_i is the permitted emission amount of the pollutant recorded in the emission data of the i-th emission source, in tons / year, and ΣQ_i is the total permitted emission amount of pollutants emitted by all emission sources. The specific process is not further elaborated in this embodiment.

[0100] S104. Calculate the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source. The posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the combined effects of abnormal emissions from the pollution source and meteorological conditions.

[0101] One possible approach is to use the Bayesian formula to calculate the posterior probability of the emission source, for example, according to the formula

[0102] P(θ_i|D)=(P(θ_i)×L(θ_i|D)) / Σ(P(θ_i)×L(θ_i|D)) calculates the posterior probability of the i-th emission source, where P(θ_i|D) is the posterior probability of the i-th emission source, P(θ_i) is the prior probability of the i-th emission source, L(θ_i|D) is the likelihood probability of the i-th emission source, and Σ(P(θ_i)×L(θ_i|D)) is the sum of the posterior probabilities of all emission sources.

[0103] S105. Determine the emission source to be traced from all emission sources based on the posterior probability of each emission source. The emission source to be traced is the emission source that is most likely to cause abnormal air quality among all emission sources.

[0104] One feasible approach is: the air quality monitoring site screens out all emission sources with a posterior probability greater than a preset probability, such as all emission sources with a posterior probability greater than 0. These emission sources can be used as emission sources to be traced. Furthermore, all emission sources to be traced can be sorted from large to small according to the posterior probability, and the sorted results are recorded in a contribution probability table. The contribution probability table can record but is not limited to recording the identification of the emission source to be traced, the geographical location data of the emission source to be traced, the posterior probability of the emission source to be traced, etc. The contribution probability table can be used as a clue to the source of pollution and applied to the ecological environment department to conduct on-site tracing and investigation of abnormal air quality events. The posterior probability of the emission source to be traced can also be called the contribution probability. Through this embodiment, the contribution degree of each emission source to the air quality monitoring site can be quantified.

[0105] By using the above technical solution, air quality monitoring stations can use the emission data of emission sources and meteorological data during abnormally high value periods to calculate the prior probability and likelihood probability of the emission source causing air quality anomaly. Then, based on the prior probability and likelihood probability of the same emission source, the posterior probability of the emission source is calculated. The posterior probability of the emission source indicates the probability that the abnormal emission of pollutants and meteorological conditions jointly cause air quality anomaly. Then, based on the posterior probability of each emission source, the emission source to be traced is determined from all emission sources, realizing the use of probability to trace the pollution source that causes air quality anomaly. Thus, without the need for physical diffusion simulation of the pollutant transmission process, the contribution probability of each emission source to the current air quality anomaly (i.e., the posterior probability) is quantified, reducing the computational cost and improving the response speed, thereby realizing the rapid tracing of pollution sources. As the inventors have found through testing, when the technical solution provided by this application is implemented on a desktop computer for tracing, the desktop computer can determine the emission source to be traced within 1 second.

[0106] Furthermore, the emission source to be traced is the one most likely to cause abnormal air quality, determined from among multiple emission sources that have a spatial relationship with the air quality monitoring station. These multiple emission sources with a spatial relationship are emission sources that may affect the air quality monitored by the air quality monitoring station. These emission sources are pre-stored in a preset association table, thereby narrowing the scope of sources to be traced in advance and improving traceability efficiency. Furthermore, the probability calculation uses the emission data pre-stored in the preset association table, eliminating the need for real-time data on pollutant emissions from the emission source, saving data collection time and relying less on data accuracy.

[0107] After determining the emission source to be traced, the air quality monitoring station can also calculate the ground concentration of the emission source to be traced, so as to visually display the spatial distribution characteristics of pollutant diffusion through the ground concentration, and provide a scientific basis for environmental management and pollution source management. Figure 2 As shown, it shows another flow chart of an atmospheric pollution source tracing method provided in an embodiment of the present application, which may include the following steps:

[0108] S101. Obtain the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period. The pollutant type refers to at least one pollutant, and the abnormally high value period is the period when abnormal pollutant emissions cause the air quality monitoring site to detect abnormal air quality.

[0109] S102. Based on the site identifier, multiple emission sources that have a spatial location relationship with the air quality monitoring site are screened out from the preset association relationship table, and emission data of each emission source is obtained from the preset association relationship table. The multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site.

[0110] S103. For any emission source, using meteorological data and emission data, calculate the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality.

[0111] S104. Calculate the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source. The posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the combined effects of abnormal emissions from the pollution source and meteorological conditions.

[0112] S105. According to the posterior probability of each emission source, determine the emission source to be traced from all emission sources. The emission source to be traced is the emission source that is most likely to cause abnormal air quality among all emission sources.

[0113] S106. Obtain chimney parameter data and permitted emission amounts of pollutants from the emission data of the emission source to be traced.

[0114] S107. Calculate the ground concentration of the emission source to be traced using chimney parameter data, meteorological data, and emission permits.

[0115] In this embodiment, air quality monitoring stations can calculate the ground concentration in order according to the ranking of the emission sources to be traced in the contribution probability table. Corresponding air quality monitoring stations can then obtain chimney parameter data for each emission source to be traced in this ranking. Chimney parameter data includes actual chimney height, chimney outlet inner diameter, outlet velocity, and exhaust temperature. Ground concentration is calculated based on these parameters, meteorological data, and emission permits.

[0116] One method for calculating the ground concentration can be to calculate the effective chimney height of the emission source to be traced according to the formula H = h + Δh, where H is the effective chimney height (in meters), h is the actual chimney height (in meters) from the chimney parameter data, Δh is the lift height (in meters), and Δh = d_s × v_s × (1-T_a / T_s) / v, where d_s is the chimney outlet inner diameter (in meters) from the chimney parameter data, v_s is the outlet velocity (in meters per second) from the chimney parameter data, T_s is the exhaust temperature (in Kelvin) from the chimney parameter data, T_a is the ambient temperature (in K) from the meteorological data, and v is the wind speed (in meters per second) from the meteorological data. The effective chimney height is calculated using chimney parameter data and meteorological data from periods of abnormally high values. During these periods, air quality monitoring stations can obtain multiple outlet velocities, exhaust temperatures, ambient temperatures, and wind speeds. In this embodiment, the average of these parameters can be used to calculate the effective chimney height.

[0117] The lateral diffusion parameter is calculated using the formula σ_y = a_y × x / (1 + b_y × x) ^ c_y, where σ_y is the lateral diffusion parameter and is expressed in meters. x is the downwind distance in meters from the meteorological data (an average value can also be used for the downwind distance). a_y, b_y, and c_y are preset atmospheric stability coefficients, determined based on the atmospheric stability level from the meteorological data. The vertical diffusion parameter is calculated using the formula σ_z = a_z × x / (1 + b_z × x) ^ c_z, in meters. σ_z is the vertical diffusion parameter and a_z, b_z, and c_z are preset atmospheric stability coefficients, determined based on the atmospheric stability level from the meteorological data. For example, if an air quality monitoring station has a pre-set relationship table that records the correspondence between atmospheric stability levels and preset atmospheric stability coefficients, the corresponding preset atmospheric stability coefficient can be found from this relationship table using the atmospheric stability level.

[0118] Using Gaussian ground model

[0119] C(x,y,0)=(Q / (2π×v×σ_y×σ_z))×exp(-y² / (2σ_y²))×exp(-H² / (2σ_z²)) calculates the ground concentration of the emission source to be traced. C(x,y,0) is the ground concentration in g / m³ (grams per cubic meter), Q is the emission rate in g / s (grams per second), Q = the preset multiple of the emission allowance ÷ 365 days ÷ 24 hours ÷ 3600 seconds. The preset multiple can be, but is not limited to, 100 times. v is the wind speed, y is the lateral distance in meters, and H is the effective chimney height. The lateral distance y is used to simulate the diffusion range of the pollutant and can range from 0 to the preset analysis upper limit.

[0120] In this embodiment, the ground concentration uses a preset multiple of the emission allowance, and the emission allowance is magnified to simulate the maximum impact of pollutants under abnormal air quality conditions.

[0121] S108. Visualize the ground concentration of the emission source to be traced according to a preset display method, and intuitively display the spatial distribution characteristics of pollutant diffusion through the visualization. The preset display method can display the ground concentration of multiple points in the pollutant diffusion path, such as using longitude as the horizontal coordinate and latitude as the vertical coordinate, representing a point on the diffusion path by longitude and latitude, and marking the ground concentration at that point. This embodiment does not limit the preset display method.

[0122] See Figure 3 , which shows another flow chart of an air pollution source tracing method provided in an embodiment of the present application, which may include the following steps:

[0123] S201. Obtain emission data of each emission source in a preset monitored area. The emission data of the emission source includes pollutants that can be emitted by the emission source, the emission permit amount of pollutants that can be emitted, the geographical location data of the emission source, and the chimney parameter data of the emission source. The chimney parameter data includes the actual chimney height, the inner diameter of the chimney outlet, the outlet velocity, and the exhaust temperature.

[0124] S202: Classify the pollutants that can be emitted by the emission source to obtain a pollutant mapping relationship. The pollutant mapping relationship records all pollutants belonging to the same pollutant type. After obtaining the emission data of the emission source and the pollutant mapping relationship, missing value filling can also be performed to ensure data integrity.

[0125] S203: Acquire site data of each air quality monitoring site in a preset area to be monitored. The site data includes geographic location data of the air quality monitoring site and a site identifier of the air quality monitoring site. The site identifier is used to point to a unique air quality monitoring site.

[0126] S204: Clean and preprocess the site data for each air quality monitoring site to obtain site data for available air quality monitoring sites in the preset monitored area. The cleaning and preprocessing operations primarily involve deduplication and deletion of deactivated air quality monitoring sites. Deactivated air quality monitoring sites are marked with the word "deactivated" and are deleted accordingly.

[0127] S205. Calculate the distance from the emission source to the available air quality monitoring site using the geographic location data of the emission source and the geographic location data of the available air quality monitoring site. The distance from the emission source to the available air quality monitoring site is recorded in the spatial location relationship between the emission source and the available air quality monitoring site.

[0128] One possible way to calculate the distance from an emission source to an available air quality monitoring station is to use the formula

[0129] d=2r×arcsin((sin²(Δφ / 2)+cos(φ1)cos(φ2)sin²(Δλ / 2)) 1 / 2 ) Calculate the distance from the emission source to the available air quality monitoring site; d is the distance in meters, r is the radius of the earth, which is 6371000 meters, φ1 is the latitude in the geographic location data of the available air quality monitoring site, φ2 is the latitude in the geographic location data of the emission source, Δφ is the latitude difference, and Δλ is the longitude difference.

[0130] S206. Identify emission sources whose distances from available air quality monitoring stations are within a preset distance range. The preset distance range may be a distance within the monitoring range of an air quality monitoring station that affects the monitored air quality. For example, the preset distance range may be 10 km to 25 km (kilometers).

[0131] S207. Record the emission data of the emission sources within the preset distance range, the pollutant mapping relationship of the emission sources, the site data of the available air quality monitoring sites, and the spatial location relationship between the emission sources and the available air quality monitoring sites into a preset association relationship table. The available air quality monitoring sites in the preset association relationship table are the air quality monitoring sites to be traced when the air quality is abnormal, wherein the preset association relationship table can be stored as a database file. When tracing the source at the air quality monitoring site, the pre-built-in emission data is obtained from the database file. Each time the source is traced, it is only necessary to provide the site identification of the air quality monitoring site to be traced, the type of pollutant to be traced, and the meteorological data, which is easy to operate.

[0132] S208: Obtain the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period. The pollutant type refers to at least one pollutant, and the abnormally high value period is the period when abnormal pollutant emissions cause the air quality monitoring site to detect abnormal air quality.

[0133] S209. Based on the site identifier, multiple emission sources that have a spatial location relationship with the air quality monitoring site are screened out from the preset association relationship table, and emission data of each emission source is obtained from the preset association relationship table. The multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site.

[0134] S210. For any emission source, using meteorological data and emission data, calculate the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality.

[0135] S211. Based on the prior probability and likelihood probability of the same emission source, calculate the posterior probability of the emission source. The posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the combined effects of abnormal emissions from the pollution source and meteorological conditions.

[0136] S212. Determine the emission source to be traced from all emission sources based on the posterior probability of each emission source.

[0137] In this embodiment, steps S208 to S212 are the same as steps S101 to S105 described above and are not repeated here. In this embodiment, the air quality monitoring site can record the emission data of the emission source, the pollutant mapping relationship of the emission source, the site data of the available air quality monitoring sites (which can be used as air quality monitoring sites to be traced when the air quality is abnormal), and the spatial position relationship between the emission source and the available air quality monitoring sites in a preset association table in advance. When tracing the source at the air quality monitoring site, the pre-built-in data is obtained from the preset association table. Each time the source is traced, only the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and the meteorological data need to be provided, which is easy to operate.

[0138] The above describes the process of calculating the prior probability using the emission permit and then calculating the likelihood probability using meteorological data and the prior probability. This embodiment can also use other methods to calculate the prior probability and likelihood probability. One feasible method is to obtain chimney parameter data and the emission permit of the pollutant from the emission data, calculate the ground concentration of the emission source using the chimney parameter data, meteorological data, and the emission permit, and use the ground concentration of the emission source to calculate the prior probability that the emission source causes abnormal air quality. The prior probability represents the impact of meteorological conditions on pollutant transmission; and use the emission permit to calculate the likelihood probability that the emission source causes abnormal air quality. The likelihood probability represents the probability that the abnormal emission of pollutants by the emission source causes abnormal air quality.

[0139] Another feasible approach is to obtain chimney parameter data and pollutant emission permits from emission data; use the pollutant emission permits to calculate the prior probability that the emission source causes abnormal air quality, and the prior probability represents the probability that the abnormal emission of pollutants from the emission source causes abnormal air quality; use the chimney parameter data, meteorological data and emission permits to calculate the ground concentration of the emission source, and use the ground concentration of the emission source to calculate the likelihood probability that the emission source causes abnormal air quality, and the likelihood probability represents the impact of meteorological conditions on pollutant transmission.

[0140] For the calculation formula of the ground concentration, please refer to the relevant description in step S107 above. After calculating the ground concentration of all emission sources, the probability is calculated according to the formula P_i = C(monitor_i) / C(max). This probability can be used as the prior probability or likelihood probability of the i-th emission source calculated using the ground concentration of the i-th emission source, where C(monitor_i) is the ground concentration of the i-th emission source and C(max) is the maximum ground concentration among all emission sources.

[0141] The following combination Figure 4 The atmospheric pollution source tracing method provided in the embodiment of the present application is described. The site data of the air quality monitoring site includes: longitude and latitude (a representation of geographic location data) and site name. The site name can be used as the site identifier of the air quality monitoring site. If the air quality monitoring sites in different regions use the same site name, the site identifier can be obtained by encoding the site name and the area to which the air quality monitoring site belongs, such as Figure 4 The emission data of the emission source include emission permit amount, longitude and latitude, and chimney parameter data.

[0142] The spatial position relationship between the two is obtained through the longitude and latitude of the air quality monitoring station and the emission source, and is identified by the station name. When the air quality is abnormal, the air quality monitoring station obtains event data, which includes: station identification, pollutant type and meteorological data. When tracing the source, the pollutant type is used to determine the pollutant to obtain the emission permit of the pollutant, and the spatial position relationship is used to determine the emission source to be traced. The emission permit is then used to calculate the prior probability. Meteorological data and prior probability are introduced to calculate the likelihood probability, and the posterior probability is calculated using the prior probability and posterior probability. After sorting, the emission source to be traced is obtained and the posterior probability of the emission source is used as the contribution probability. The ground concentration of each emission source to be traced is calculated in turn using the sorting of the posterior probability. The ground concentration can be calculated using the Gaussian ground model and chimney parameter data, and the ground concentration is visualized.

[0143] Figure 4 The air pollution source tracing method shown has the following advantages:

[0144] 1) Comprehensively considers factors such as emission permits, meteorological data, and spatial location relationships, without the need for physical diffusion simulation of pollution transmission. By using probability to assess pollution sources during air quality anomalies, rapid source tracing is achieved. 2) It can quantify the probability of each emission source's contribution to air quality monitoring stations. 3) It can intuitively display the spatial distribution characteristics of pollutant diffusion (such as ground concentration). 4) It provides a scientific basis for environmental management and pollution source control. 5) It does not require accurate real-time emission data and relies less on the accuracy of input data. 6) It has low computational cost and fast response speed. For example, a single source tracing calculation takes no more than 1 second on a desktop computer. 7) Emission data is pre-built in, and each source tracing only requires providing site identification, meteorological data, and pollutant type, making it easy to operate.

[0145] Another schematic diagram of the atmospheric pollution source tracing method is as follows: Figure 5 As shown, Figure 4 The difference lies in the way the prior probability and likelihood probability are calculated. Figure 5 As shown, the emission permit, meteorological data and chimney parameter data are combined, and a Gaussian ground model is introduced. Specifically, the emission permit is used to calculate the prior probability, the emission permit, meteorological data, chimney parameter data and Gaussian ground model are used to calculate the ground concentration of the emission source, and the ground concentration of the emission source is used to calculate the likelihood probability. Other processes are not repeated here.

[0146] The above introduces a method for tracing the source of air pollution provided by an embodiment of the present application. The following will introduce a device for executing the above-mentioned method for tracing the source of air pollution.

[0147] See also Figure 6 , Figure 6This is a schematic diagram of the structure of an atmospheric pollution source tracing device provided in an embodiment of the present application. Figure 6 As shown, the air pollution source tracing device may include: a first acquisition module 10, a screening module 20, a first calculation module 30, a second calculation module 40 and a determination module 50.

[0148] The first acquisition module 10 is used to obtain the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and the meteorological data during the abnormally high value period. The pollutant type points to at least one pollutant. The abnormally high value period is the period when the air quality monitoring site monitors abnormal air quality due to abnormal pollutant emissions. For details, please refer to the above step S101.

[0149] The screening module 20 is used to screen out multiple emission sources that have a spatial location relationship with the air quality monitoring site from the preset association table based on the site identifier, and to obtain the emission data of each emission source from the preset association table. The multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site. For specific instructions, please refer to the above step S102.

[0150] The first calculation module 30 is used to calculate, for any emission source, the prior probability and the likelihood probability of the emission source causing air quality anomaly using meteorological data and emission data.

[0151] In one possible implementation, the first calculation module 30 may include: a first calculation unit, a second calculation unit, and a third calculation unit. The first calculation unit is used to calculate the prior probability that the emission source causes abnormal air quality by using the emission allowance of pollutants recorded in the emission data. The prior probability represents the probability that the abnormal emission of pollutants by the emission source causes abnormal air quality. The second calculation unit is used to calculate the wind speed correction factor, distance attenuation factor, wind direction weight, and atmospheric stability correction factor by using the spatial position relationship between meteorological data, emission sources, and air quality monitoring stations. The third calculation unit is used to calculate the likelihood probability that the emission source causes abnormal air quality by using the wind speed correction factor, distance attenuation factor, wind direction weight, atmospheric stability correction factor, and prior probability. The likelihood probability represents the probability that the abnormal emission of pollutants by the emission source causes abnormal air quality under meteorological conditions.

[0152] or,

[0153] The first calculation unit is used to calculate the wind speed correction factor, distance attenuation factor, wind direction weight and atmospheric stability correction factor by using the spatial position relationship between meteorological data, emission sources and air quality monitoring stations. The second calculation unit is used to calculate the prior probability that the emission source causes air quality anomaly by using the wind speed correction factor, distance attenuation factor, wind direction weight and atmospheric stability correction factor. The prior probability represents the impact of meteorological conditions on pollutant transmission. The third calculation unit is used to calculate the likelihood probability that the emission source causes air quality anomaly by using the emission permit amount and prior probability of the pollutant recorded in the emission data.

[0154] In one possible implementation, the first calculation module 30 is used to obtain chimney parameter data and pollutant emission permits from emission data, calculate the ground concentration of the emission source using the chimney parameter data, meteorological data and emission permits, and use the ground concentration of the emission source to calculate the prior probability that the emission source causes abnormal air quality, and the prior probability represents the impact of meteorological conditions on pollutant transmission; and use the emission permit to calculate the likelihood probability that the emission source causes abnormal air quality, and the likelihood probability represents the probability that abnormal air quality is caused by abnormal emission of pollutants from the emission source.

[0155] or,

[0156] The first calculation module 30 is used to obtain chimney parameter data and pollutant emission permits from emission data; use the pollutant emission permits to calculate the prior probability that the emission source causes abnormal air quality, and the prior probability represents the probability that the abnormal emission of pollutants from the emission source causes abnormal air quality; use the chimney parameter data, meteorological data and emission permits to calculate the ground concentration of the emission source, and use the ground concentration of the emission source to calculate the likelihood probability that the emission source causes abnormal air quality, and the likelihood probability represents the impact of meteorological conditions on pollutant transmission.

[0157] The specific process of the first calculation module 30 calculating the prior probability and the likelihood probability can be found in the above method embodiment part, which will not be repeated here.

[0158] The second calculation module 40 is used to calculate the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source. The posterior probability of the emission source indicates the probability that the abnormal emission of pollutants and meteorological conditions will cause abnormal air quality. One feasible way is to use the Bayesian formula to calculate the posterior probability of the emission source, for example, according to the formula

[0159] P(θ_i|D)=(P(θ_i)×L(θ_i|D)) / Σ(P(θ_i)×L(θ_i|D)) calculates the posterior probability of the i-th emission source, where P(θ_i|D) is the posterior probability of the i-th emission source, P(θ_i) is the prior probability of the i-th emission source, L(θ_i|D) is the likelihood probability of the i-th emission source, and Σ(P(θ_i)×L(θ_i|D)) is the sum of the posterior probabilities of all emission sources.

[0160] The determination module 50 is used to determine the emission source to be traced from all emission sources based on the posterior probability of each emission source. The emission source to be traced is the emission source that is most likely to cause abnormal air quality among all emission sources. For details, please refer to the above step S105.

[0161] By means of the above technical solution, the atmospheric pollution source tracing device can use the emission data of the emission source and the meteorological data during the abnormally high value period to calculate the prior probability and likelihood probability of the emission source causing the air quality abnormality, and then calculate the posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source. The posterior probability of the emission source indicates the probability that the abnormal emission of pollutants and meteorological conditions jointly cause the air quality abnormality. Then, based on the posterior probability of each emission source, the emission source to be traced is determined from all emission sources, realizing the use of probability to trace the pollution source that causes the air quality abnormality. Thus, without the need for physical diffusion simulation of the pollutant transmission process, the contribution probability of each emission source to the current air quality abnormality (i.e., the posterior probability) is quantified, reducing the computational cost and improving the response speed, thereby realizing the rapid tracing of the pollution source. As the inventors have found through testing, when the technical solution provided by this application is implemented on a desktop computer for tracing, the desktop computer can determine the emission source to be traced within 1 second.

[0162] Furthermore, the emission source to be traced is the one most likely to cause abnormal air quality, determined from among multiple emission sources that have a spatial relationship with the air quality monitoring station. These multiple emission sources with a spatial relationship are emission sources that may affect the air quality monitored by the air quality monitoring station. These emission sources are pre-stored in a preset association table, thereby narrowing the scope of sources to be traced in advance and improving traceability efficiency. Furthermore, the probability calculation uses the emission data pre-stored in the preset association table, eliminating the need for real-time data on pollutant emissions from the emission source, saving data collection time and relying less on data accuracy.

[0163] See Figure 7 , which shows another structural schematic diagram of an atmospheric pollution source tracing device provided by an embodiment of the present application, Figure 6 On this basis, it may further include: a second acquisition module 60 , a third calculation module 70 and a display module 80 .

[0164] The second acquisition module 60 is used to obtain chimney parameter data and permitted emission amounts of pollutants from the emission data of the emission source to be traced.

[0165] The third calculation module 70 is used to calculate the ground concentration of the emission source using the chimney parameter data, meteorological data and emission permit.

[0166] In one possible implementation, the third calculation module 70 is used to calculate the effective chimney height of the emission source to be traced according to the formula H=h+Δh, where H is the effective chimney height, h is the actual chimney height in the chimney parameter data, Δh is the lifting height, and Δh=d_s×v_s×(1-T_a / T_s) / v, d_s is the chimney outlet inner diameter in the chimney parameter data, v_s is the outlet velocity in the chimney parameter data, T_s is the exhaust temperature in the chimney parameter data, T_a is the ambient temperature in the meteorological data, and v is the wind speed in the meteorological data;

[0167] The lateral diffusion parameter is calculated using the formula σ_y = a_y × x / (1 + b_y × x) ^ c_y, where σ_y is the lateral diffusion parameter, x is the downwind distance from the meteorological data, and a_y, b_y, and c_y are preset atmospheric stability coefficients. a_y, b_y, and c_y are determined based on the atmospheric stability level from the meteorological data.

[0168] The vertical diffusion parameter is calculated according to the formula σ_z=a_z×x / (1+b_z×x)^c_z, where σ_z is the vertical diffusion parameter and a_z, b_z, and c_z are preset atmospheric stability coefficients. a_z, b_z, and c_z are determined based on the atmospheric stability level in meteorological data.

[0169] Using Gaussian ground model

[0170] C(x,y,0)=(Q / (2π×v×σ_y×σ_z))×exp(-y² / (2σ_y²))×exp(-H² / (2σ_z²)) calculates the ground concentration of the emission source to be traced, C(x,y,0) is the ground concentration, Q is the emission rate, Q=the preset multiple of the emission permit ÷ 365 days ÷ 24 hours ÷ 3600 seconds, v is the wind speed, y is the lateral distance, and H is the effective chimney height.

[0171] The display module 80 is used to visualize the ground concentration of the emission source in a preset display method, so as to intuitively display the spatial distribution characteristics of pollutant diffusion through the ground concentration, and provide a scientific basis for environmental management and pollution source management.

[0172] In addition, the atmospheric pollution source tracing device provided in the embodiment of the present application may also include: a third acquisition module, a classification module, a fourth acquisition module, a processing module, a fourth calculation module and a recording module.

[0173] The third acquisition module is used to obtain the emission data of each emission source in the preset monitored area. The emission data of the emission source includes the pollutants that the emission source can emit, the emission permit amount of the pollutants that can be emitted, the geographical location data of the emission source and the chimney parameter data of the emission source. The chimney parameter data includes the actual chimney height, the inner diameter of the chimney outlet, the outlet velocity and the exhaust temperature.

[0174] The classification module is used to classify pollutants that can be emitted by emission sources and obtain pollutant mapping relationships. The pollutant mapping relationships record pollutants belonging to the same pollutant type.

[0175] The fourth acquisition module is used to obtain the site data of each air quality monitoring site in the preset monitored area. The site data includes the geographical location data of the air quality monitoring site and the site identifier of the air quality monitoring site. The site identifier is used to point to a unique air quality monitoring site.

[0176] The processing module is used to clean and pre-process the site data of each air quality monitoring site to obtain the site data of the air quality monitoring sites available in the preset monitored area.

[0177] The fourth calculation module is used to calculate the distance from the emission source to the available air quality monitoring site by using the geographic location data of the emission source and the geographic location data of the available air quality monitoring site. The distance from the emission source to the available air quality monitoring site is recorded in the spatial location relationship between the emission source and the available air quality monitoring site.

[0178] The recording module is used to determine the emission sources whose distance from the available air quality monitoring sites is within a preset distance range, and record the emission data of the emission sources within the preset distance range, the pollutant mapping relationship of the emission sources, the site data of the available air quality monitoring sites, and the spatial location relationship between the emission sources and the available air quality monitoring sites in a preset association relationship table. The available air quality monitoring sites can be used as air quality monitoring sites to be traced.

[0179] For the description of the above modules, please refer to the method embodiment section, which will not be repeated here. In this embodiment, the atmospheric pollution source tracing device can pre-record the emission data of the emission source, the pollutant mapping relationship of the emission source, the site data of the available air quality monitoring sites (which can be used as air quality monitoring sites to be traced when the air quality is abnormal), and the spatial position relationship between the emission source and the available air quality monitoring sites into a preset association relationship table. When tracing the source at the air quality monitoring site, the pre-built-in data is obtained from the preset association relationship table. Each time the source is traced, only the site identification of the air quality monitoring site to be traced, the type of pollutant to be traced and the meteorological data need to be provided, which is easy to operate.

[0180] An electronic device is also provided in an embodiment of the present application. Figure 8 , which shows a schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present application. The electronic device in the embodiments of the present application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (personal digital assistants), PADs (tablet computers), desktop computers, etc. Figure 8 The electronic device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0181] like Figure 8 As shown, the electronic device may include a processor (such as a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 802 or the program loaded from the storage device 808 to the random access memory (RAM) 803. When the electronic device is powered on, the RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802 and RAM 803 are connected to each other through a bus 804. The input / output (I / O) interface 805 is also connected to the bus 804. The ROM 802, RAM 803 and the storage device 808 are memories of the electronic device, which are connected to the processor via a bus, wherein the memory is used to store computer programs; the processor is used to execute computer programs so that the electronic device can implement any one of the atmospheric pollution source tracing methods provided in the embodiments of the present application.

[0182] Typically, the following devices may be connected to the I / O interface 805: an input device 806 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 808 including, for example, a memory card, a hard disk, etc.; and a communication device 809. The communication device 809 may allow the electronic device to communicate with other devices wirelessly or by wire to exchange data. Figure 8The electronic device is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead.

[0183] An embodiment of the present application also provides a computer program product including computer-readable instructions. When the computer-readable instructions are executed on an electronic device, the electronic device implements any one of the atmospheric pollution source tracing methods provided in the embodiments of the present application.

[0184] A computer-readable storage medium is also provided in an embodiment of the present application. The storage medium carries one or more computer programs. When one or more computer programs are executed by an electronic device, the electronic device can implement any one of the atmospheric pollution source tracing methods provided in the embodiment of the present application.

[0185] It should also be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed across multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. In addition, in the drawings of the device embodiments provided in this application, the connection relationship between the modules indicates that there is a communication connection between them, which can be specifically implemented as one or more communication buses or signal lines.

[0186] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware, and of course can also be implemented by special hardware including application-specific integrated circuits, special CPUs, special memories, special components, etc. In general, all functions performed by computer programs can be easily implemented with corresponding hardware, and the specific hardware structures used to implement the same function can also be diverse, such as analog circuits, digital circuits or special circuits, etc. However, for the present application, software program implementation is a better implementation method in most cases. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a readable storage medium, such as a computer's floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk or optical disk, etc., and includes a number of instructions to enable a computer device (which can be a personal computer, training equipment, or network equipment, etc.) to execute the methods described in each embodiment of the present application.

[0187] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product.

[0188] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, a computer, a training device or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website, a computer, a training device or a data center. The computer-readable storage medium can be any available medium that a computer can store or a data storage device such as a training device, a data center, etc. that includes one or more available media integrations. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

Claims

1. A method for tracing the source of air pollution, characterized in that: include: Obtaining the site identifier of the air quality monitoring site to be traced, the type of pollutant to be traced, and meteorological data during the abnormally high value period, where the pollutant type refers to at least one pollutant, and the abnormally high value period is the period when the abnormal emission of the pollutant causes the air quality monitoring site to monitor abnormal air quality; Based on the site identifier, multiple emission sources that have a spatial location relationship with the air quality monitoring site are screened from a preset association relationship table, and emission data of each emission source is obtained from the preset association relationship table, wherein the multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site, and the emission data of the emission source are emission parameters set for the emission source when the emission source is planned; For any emission source, using the meteorological data and the emission data, calculate the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality; Calculating a posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source, wherein the posterior probability of the emission source indicates the probability that the abnormal air quality is caused by the combined effect of the abnormal emission of the pollutant and the meteorological conditions corresponding to the meteorological data; According to the posterior probability of each emission source, an emission source to be traced is determined from all emission sources, and the emission source to be traced is the emission source that is most likely to cause the abnormal air quality among all emission sources.

2. The method according to claim 1, characterized in that The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes: Calculating a priori probability that the emission source causes abnormal air quality using the permitted emission amount of the pollutant recorded in the emission data, wherein the priori probability represents a probability that the abnormal emission of the pollutant by the emission source causes the abnormal air quality; Calculating a wind speed correction factor, a distance attenuation factor, a wind direction weight, and an atmospheric stability correction factor using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring station; Calculating the likelihood probability that the emission source causes abnormal air quality using the wind speed correction factor, the distance attenuation factor, the wind direction weight, the atmospheric stability correction factor, and the prior probability, wherein the likelihood probability represents the probability that the abnormal air quality is caused by the abnormal emission of the pollutants by the emission source under the meteorological conditions; or, The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes: Calculating a wind speed correction factor, a distance attenuation factor, a wind direction weight, and an atmospheric stability correction factor using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring station; Calculating a priori probability that the emission source causes air quality anomaly using the wind speed correction factor, the distance attenuation factor, the wind direction weight, and the atmospheric stability correction factor, wherein the priori probability represents the impact of the meteorological conditions on the transmission of the pollutant; The likelihood probability that the emission source causes abnormal air quality is calculated using the emission allowable amount of the pollutant recorded in the emission data and the prior probability.

3. The method according to claim 2, characterized in that The calculating of the wind speed correction factor, the distance attenuation factor, the wind direction weight, and the atmospheric stability correction factor by using the meteorological data, the spatial position relationship between the emission source, and the air quality monitoring station comprises: Calculate the wind speed correction factor according to the formula f_w=exp(-1 / v), where f_w is the wind speed correction factor and v is the wind speed in the meteorological data; Calculate the distance attenuation factor according to the formula f_r=exp(-d / d_c), where f_r is the distance attenuation factor, d is the distance from the emission source to the air quality monitoring site in the spatial position relationship, d_c is the characteristic distance, and d_c=v×a preset first constant; The wind direction weight is calculated according to the formula f_d=(1-cos(θ_w-θ_s)) / 2, where f_d is the wind direction weight, θ_w is the wind direction angle in the meteorological data, and θ_s is the azimuth of the emission source relative to the air quality monitoring station; According to the atmospheric stability level in the meteorological data, the atmospheric stability correction factor matching the atmospheric stability level is obtained from a preset correction relationship table.

4. The method according to claim 1, wherein The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes: Obtaining chimney parameter data and the emission permit of the pollutant from the emission data, calculating the ground concentration of the emission source using the chimney parameter data, the meteorological data, and the emission permit, and calculating a priori probability that the emission source causes air quality anomaly using the ground concentration of the emission source, the priori probability representing the impact of the meteorological conditions on pollutant transmission; Calculating the likelihood probability that the emission source causes abnormal air quality using the emission allowance, wherein the likelihood probability represents the probability that the abnormal emission of the pollutants by the emission source causes the abnormal air quality; or, The calculating, using the meteorological data and the emission data, the prior probability that the emission source causes abnormal air quality and the likelihood probability that the emission source causes abnormal air quality includes: Obtaining chimney parameter data and emission allowances of the pollutants from the emission data; Calculating, using the permitted emission amount of the pollutant, a priori probability that the emission source causes abnormal air quality, wherein the priori probability represents the probability that the abnormal emission of the pollutant by the emission source causes the abnormal air quality; The chimney parameter data, the meteorological data and the emission permit are used to calculate the ground concentration of the emission source, and the ground concentration of the emission source is used to calculate the likelihood probability that the emission source causes air quality abnormality, and the likelihood probability represents the impact of the meteorological conditions on pollutant transmission.

5. The method according to claim 1, wherein The method further comprises: Obtaining chimney parameter data and the emission allowance of the pollutant from the emission data of the emission source to be traced; Calculating the ground concentration of the emission source using the chimney parameter data, the meteorological data, and the emission permit; The ground concentration of the emission source is visually displayed in a preset manner.

6. The method according to claim 4 or 5, characterized in that The calculating the ground concentration of the emission source by using the chimney parameter data, the meteorological data and the emission allowance includes: Calculate the effective chimney height of the emission source to be traced according to the formula H=h+Δh, where H is the effective chimney height, h is the actual chimney height in the chimney parameter data, Δh is the lifting height, and Δh=d_s×v_s×(1-T_a / T_s) / v, d_s is the chimney outlet inner diameter in the chimney parameter data, v_s is the outlet velocity in the chimney parameter data, T_s is the exhaust temperature in the chimney parameter data, T_a is the ambient temperature in the meteorological data, and v is the wind speed in the meteorological data; Calculate the lateral diffusion parameter according to the formula σ_y=a_y×x / (1+b_y×x)^c_y, where σ_y is the lateral diffusion parameter, x is the downwind distance in the meteorological data, and a_y, b_y, and c_y are preset atmospheric stability coefficients, where a_y, b_y, and c_y are determined according to the atmospheric stability level in the meteorological data; Calculate the vertical diffusion parameter according to the formula σ_z=a_z×x / (1+b_z×x)^c_z, where σ_z is the vertical diffusion parameter, and a_z, b_z, and c_z are preset atmospheric stability coefficients, which are determined according to the atmospheric stability level in the meteorological data; Using Gaussian ground model C(x,y,0)=(Q / (2π×v×σ_y×σ_z))×exp(-y² / (2σ_y²))×exp(-H² / (2σ_z²)) calculates the ground concentration of the emission source to be traced, C(x,y,0) is the ground concentration, Q is the emission rate, Q=the preset multiple of the emission permit ÷ 365 days ÷ 24 hours ÷ 3600 seconds, v is the wind speed, y is the lateral distance, and H is the effective chimney height.

7. The method according to any one of claims 1 to 5, characterized in that The method further comprises: Obtaining emission data of each emission source in a preset area to be monitored, the emission data of the emission source including the pollutants that can be emitted by the emission source, the emission permit amount of the pollutants that can be emitted, the geographical location data of the emission source, and the chimney parameter data of the emission source, the chimney parameter data including the actual chimney height, the inner diameter of the chimney outlet, the outlet velocity, and the exhaust temperature; Classifying pollutants that can be emitted by the emission source to obtain a pollutant mapping relationship, wherein the pollutant mapping relationship records pollutants belonging to the same pollutant type; Obtaining site data of each of the air quality monitoring sites in the preset monitored area, the site data including geographic location data of the air quality monitoring site and a site identifier of the air quality monitoring site, the site identifier being used to point to a unique air quality monitoring site; Performing cleaning and preprocessing operations on the site data of each of the air quality monitoring sites to obtain the site data of the air quality monitoring sites available in the preset area to be monitored; Calculating the distance from the emission source to the available air quality monitoring site using the geographic location data of the emission source and the geographic location data of the available air quality monitoring site, wherein the distance from the emission source to the available air quality monitoring site is recorded in the spatial position relationship between the emission source and the available air quality monitoring site; Determine the emission sources whose distance from the available air quality monitoring sites is within a preset distance range, and record the emission data of the emission sources within the preset distance range, the pollutant mapping relationship of the emission sources, the site data of the available air quality monitoring sites, and the spatial position relationship between the emission sources and the available air quality monitoring sites in the preset association relationship table. The available air quality monitoring sites can be used as the air quality monitoring sites to be traced.

8. An atmospheric pollution source tracing device, characterized in that: include: A first acquisition module is configured to obtain a site identifier of an air quality monitoring site to be traced, a type of pollutant to be traced, and meteorological data during an abnormally high-value period, wherein the pollutant type refers to at least one pollutant, and the abnormally high-value period is a period during which abnormal emissions of the pollutant cause the air quality monitoring site to detect abnormal air quality; a screening module for screening, based on the site identifier, multiple emission sources that have a spatial location relationship with the air quality monitoring site from a preset association relationship table, and obtaining emission data of each emission source from the preset association relationship table, wherein the multiple emission sources that have a spatial location relationship are emission sources that may affect the air quality monitored by the air quality monitoring site, and the emission data of the emission source are emission parameters set for the emission source when the emission source is planned; A first calculation module is configured to calculate, for any emission source, a priori probability that the emission source causes abnormal air quality and a likelihood probability that the emission source causes abnormal air quality using the meteorological data and the emission data; a second calculation module, configured to calculate a posterior probability of the emission source based on the prior probability and likelihood probability of the same emission source, wherein the posterior probability of the emission source indicates a probability that the abnormal air quality is caused by the combined effect of the abnormal emission of the pollutants and the meteorological conditions corresponding to the meteorological data; A determination module is used to determine the emission source to be traced from all emission sources based on the posterior probability of each emission source, and the emission source to be traced is the emission source that is most likely to cause the abnormal air quality among all emission sources.

9. An electronic device, characterized in that: comprising at least one processor and a memory connected to the processor, wherein: The memory is used to store computer programs; The processor is used to execute the computer program so that the electronic device can implement the air pollution source tracing method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that The storage medium carries one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the method for tracing the source of atmospheric pollution as described in any one of claims 1 to 7.

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