Gas pollution leakage tracing method, device and equipment under complex diffusion condition

Abstract

The invention relates to the field of gas leakage monitoring. The embodiment of the invention provides a gas pollution leakage tracing method and device under a complex diffusion condition and electronic equipment. The gas pollution leakage tracing method under the complex diffusion condition comprises the following steps: establishing a fingerprint spectrum of a surrounding pollution source, and setting a typical factor of each pollution source; the typical factors are used for representing typical pollution components of the pollution source; obtaining receptor pollution data of the polluted area; calculating an analysis error between a tracing result based on a chemical mass balance model and the receptor pollution data, and determining a pollution component as an error factor according to a contribution degree to the analysis error; and determining a variable weight chemical mass balance model according to the typical factor and the error factor, wherein the variable weight chemical mass balance model is used for determining a pollution source. According to the embodiment of the invention, accurate traceability of pollutants commonly existing in a field environment under a complex diffusion condition is realized.

Description

Technical Field

[0001] The present invention relates to the field of gas leakage monitoring, and in particular to a method for tracing the source of gas pollution leakage under complex diffusion conditions, a device for tracing the source of gas pollution leakage under complex diffusion conditions, an electronic device and a computer-readable storage medium. Background Art

[0002] With the rapid development of industrial construction and urbanization, resources and energy are being consumed rapidly, and the atmospheric environment will face unprecedented pressure. Understanding the emission characteristics of atmospheric pollutants in key areas and qualitatively and quantitatively explaining the sources and contributions of characteristic pollutants are important conditions for fully achieving the "Ten Measures for Air Pollution Control" and scientifically and rationally establishing a long-term mechanism for air pollution prevention and control.

[0003] At present, the chemical mass balance model analysis method is one of the important source analysis technologies. Without considering the detection error of the analytical instrument, the traceability error of this analysis method mainly comes from the following three aspects. First, interference from unknown sources; interference from unknown sources will cause the receptor data to not match the established pollution source fingerprint map, resulting in analysis errors. In response to this problem, the patented pollutant source analysis method provides a solution; second, changes in pollution source emission characteristics. It does not match the pollution source fingerprint map established in the early stage; third, complex on-site conditions affect the diffusion and transmission path of the pollution source. There is a significant difference between the pollution source fingerprint map constructed in the early stage and the pollution characteristics that actually diffused to the receptor area. There is currently a lack of effective solutions for the second and third sources of errors mentioned above.

[0004] The chemical mass balance model (CMB) is one of several receptor models used in atmospheric pollution source management. The model was first proposed in 1972 and officially named the chemical mass balance method in 1980. The CMB model established by this method is currently the most studied and widely used receptor model in the actual work of atmospheric particulate matter source analysis. Summary of the invention

[0005] The purpose of the embodiments of the present invention is to provide a method, device and electronic equipment for tracing the source of gas pollution leakage under complex diffusion conditions to solve some problems in the prior art.

[0006] In order to achieve the above-mentioned objectives, the first aspect of the present invention provides a method for tracing the source of gas pollution leakage under complex diffusion conditions, including: establishing a fingerprint map of surrounding pollution sources and setting typical factors for each pollution source; the typical factors are used to characterize the typical pollution components of the pollution sources; obtaining receptor pollution data of the polluted area; calculating the analytical error between the tracing results based on the chemical mass balance model and the receptor pollution data, and determining the pollution component as the error factor according to the contribution to the analytical error; determining a variable weight chemical mass balance model according to the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine the pollution source.

[0007] Preferably, a fingerprint map of surrounding pollution sources is established, including: taking the pollution emission sources that have a pollution impact on the receptor area as the surrounding pollution sources; constructing a fingerprint map with the main pollutant components diffused from the pollution sources to the receptor area and their volume concentration ratios, or constructing a fingerprint map with the main pollutant components emitted by the pollution source and their volume concentration ratios.

[0008] Preferably, a typical factor of each pollution source is set, including: if the pollutant component in the fingerprint of the pollution source meets the following conditions, then the pollutant component is the typical factor of the pollution source: the volume concentration percentage of the pollutant component in the fingerprint of the pollution source exceeds a preset threshold; exceeds a preset multiple of the average volume concentration of the pollutant component; and the contribution rate of the pollutant volume concentration percentage of the pollution source to the receptor point under a specific wind direction exceeds a preset contribution rate threshold.

[0009] Preferably, obtaining receptor pollution data of a polluted area includes: obtaining an ambient air sample of the receptor area; and using a pollutant component qualitative and quantitative analysis device to analyze the ambient air sample to obtain pollutant components and volume concentration ratios.

[0010] Preferably, calculating the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data comprises: obtaining the analytical error SSE by the following steps:

[0011]

[0012] Where N is the number of surrounding pollution sources, M is the number of polluting components; p ij is the volume concentration of the jth pollution component contributed by the i-th pollution source to the receptor area in the analysis result; c j The volume concentration of the jth pollutant component in the receptor pollution data.

[0013] Preferably, the p ij Obtained through the following steps: ij =F ij ·S i Among them, F ijis the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; S i is the total volume concentration of the pollution components contributed by the ith pollution source to the receptor area, which is the source tracing result based on the chemical mass balance model.

[0014] Preferably, the pollutant component is determined as the error factor according to its contribution to the analytical error, including: when the analytical error is greater than K times the baseline error, the analytical sub-error of each pollutant component is calculated; if the proportion of the analytical sub-error of any pollutant component in the analytical error exceeds a preset proportion threshold, and exceeds a preset multiple of the mean of the analytical sub-errors of each pollutant component, then the pollutant component is set as the error factor.

[0015] Preferably, calculating the analytical sub-error of each pollution component includes:

[0016] Among them, SSE j is the analytical sub-error corresponding to the jth pollution component; N is the number of surrounding pollution sources; p ij is the volume concentration of the contribution of the i-th pollution source to the j-th pollution component in the receptor pollution data in the analysis result; c j Volume concentration of the jth component in the receptor contamination data.

[0017] Preferably, determining the variable weight chemical mass balance model according to the typical factor and the error factor comprises obtaining the variable weight chemical mass balance model according to the following relationship:

[0018]

[0019] Among them, k ij is the weight coefficient to be optimized for the jth pollution component of the i-th pollution source. If the jth pollution component is an error factor and is a typical factor of the i-th pollution source, then set k ij is the weight coefficient to be optimized, otherwise k ij is a fixed value of 1; E j is the analytical concentration error of the jth pollutant component.

[0020] Preferably, the method further comprises: using the error factor to correct the fingerprint spectrum of the surrounding pollution sources.

[0021] Preferably, the variable weight chemical mass balance model is used to determine the pollution source, including: based on the principle of minimizing the analytical error SSE of the variable weight chemical mass balance model, calculating the weight coefficient k to be optimized ij , and further analyze to obtain the total volume concentration S of the pollution components contributed by the i-th pollution source to the receptor area i , and then determine the source of pollution.

[0022] Preferably, based on the calculation results of the variable weight chemical mass balance model, the contribution concentration P′ of the i-th pollution source to the j-th pollution component in the receptor area is obtained. ij , the steps are as follows:

[0023] P' ij =k ij ·F ij ·S i ;

[0024] Among them, F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; k ij is the weight coefficient to be optimized for the jth pollution component of the ith pollution source; S i is the total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area; the above k ij , S i This is the traceability result based on the variable weight chemical mass balance model.

[0025] The present invention also provides a gas pollution leakage tracing device under complex diffusion conditions, which includes: a typical factor determination module, which establishes a fingerprint map of surrounding pollution sources and sets typical factors for each pollution source; the typical factors are used to characterize the typical pollution components of the pollution sources; a data acquisition module, which is used to obtain receptor pollution data of the polluted area; an error factor determination module, which is used to calculate the analytical error between the tracing result based on the chemical mass balance model and the receptor pollution data, and determine the pollution component as the error factor according to the contribution to the analytical error; and a model construction module, which is used to determine a variable weight chemical mass balance model according to the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine the pollution source.

[0026] The present invention also provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the aforementioned gas pollution leakage tracing method under complex diffusion conditions.

[0027] The present invention also provides a non-transitory computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable the computer to execute the aforementioned gas pollution leakage tracing method under complex diffusion conditions.

[0028] In a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein instructions are stored in the storage medium, and when the instructions are executed on a computer, the computer executes the steps of the aforementioned method for tracing the source of gas pollution leakage under complex diffusion conditions.

[0029] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the aforementioned gas pollution leakage tracing method under complex diffusion conditions.

[0030] The above technical solution has at least the following beneficial effects:

[0031] The embodiment of the present invention establishes a variable weight chemical mass balance model based on typical factors and error factors, and provides an overall technical route for the correction of chemical mass balance models under complex conditions. It solves the problem of low accuracy and large analysis error of existing source tracing analysis methods when complex conditions affect the diffusion and transmission characteristics of pollution sources and the emission characteristics of current pollution sources do not match the established fingerprint spectrum, and improves the accuracy and identification efficiency of gas pollution leakage tracing under complex diffusion conditions that are commonly present in field environments.

[0032] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0034] Figure 1 Schematically showing a schematic diagram of the steps of a method for tracing the source of gas pollution leakage under complex diffusion conditions according to an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of an implementation of a method for tracing the source of gas pollution leakage under complex diffusion conditions according to an embodiment of the present invention is shown;

[0036] Figure 3 A schematic diagram showing the relationship between the surrounding pollution sources and the receptor area according to an embodiment of the present invention is shown;

[0037] Figure 4 A schematic diagram of environment distribution according to an embodiment of the present invention is shown schematically;

[0038] Figure 5 A schematic diagram of the structure of a gas pollution leakage tracing device under complex diffusion conditions according to an embodiment of the present invention is shown;

[0039] Figure 6The first half of the schematic diagram of the CMB and variable weight CMB source tracing analysis results in an embodiment of the present invention is schematically shown;

[0040] Figure 7 The second half of the schematic diagram of the CMB and variable-weight CMB provenance analysis results in an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0041] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0042] Example 1

[0043] Figure 1 The following schematically shows the steps of a method for tracing the source of gas pollution leakage under complex diffusion conditions according to an embodiment of the present invention. Figure 1 As shown, a method for tracing the source of gas pollution leakage under complex diffusion conditions includes:

[0044] S01. Establish a fingerprint map of the surrounding pollution sources and set the typical factors of each pollution source; the typical factors are used to characterize the typical pollutant components of the pollution sources; specifically, the surrounding pollution sources in this embodiment are pollution emission sources that have a pollution impact on the receptor area; since the polluted gas generated by the pollution source is easily affected by the complex conditions on site during the diffusion and transmission process, causing certain substances to change the diffusion path, so that the pollution characteristics emitted by the pollution source are different from the pollution characteristics that actually affect the receptor area, in order to accurately analyze the source of pollution, it is recommended to construct a fingerprint map based on the main pollutant components and their volume concentration ratios that diffuse from the pollution source to the receptor area. However, considering the complexity of the on-site environment, the receptor area is generally affected by the cross-influence of multiple pollution sources at the same time, and it is difficult to clearly define the main pollutant components and their proportions that diffuse from each single emission source to the receptor area. At this time, the main pollutant components and their volume concentration ratios emitted by the pollution source can be used to construct a fingerprint map. Similarly, in the process of diffusion and transmission, a reasonable position is selected to analyze the main pollutant components and their volume concentration ratios, and a fingerprint map can also be established.

[0045] S02. Obtain receptor pollution data of the polluted area. The receptor pollution data here refers to the pollution analysis results obtained by instrumental analysis of pollutants collected from the receptor area.

[0046] S03. Calculate the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data, and determine the pollutant component as the error factor according to the contribution to the analytical error; according to the principle of the chemical mass balance model, if the pollutant components and proportions diffused to the receptor area by each pollution source are the same as its fingerprint spectrum, the qualitative and quantitative analysis equipment has no detection error, and is not interfered by other unknown sources, then the receptor pollution data analysis result based on the chemical mass balance will have no analytical error. Ignore the detection error of the qualitative and quantitative analysis equipment and the interference of unknown sources. If the analytical error is small, it is considered that the on-site environment has no impact on the diffusion and propagation of the pollution source, and the source analysis result can be directly output at this time. If the analytical error is large, further precise source analysis is required.

[0047] S04. Determine a variable weight chemical mass balance model based on the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine the pollution source. In this step, the variable weight chemical mass balance model is obtained by setting the weight coefficient to be optimized in the original chemical mass balance model and solving the weight coefficient. Pollutant source tracing is performed based on the variable weight chemical mass balance model.

[0048] Through the above implementation methods, the problems of low accuracy and large analysis errors of existing tracing and analysis methods under complex conditions that affect the diffusion and transmission characteristics of pollution sources and when the emission characteristics of current pollution sources do not match the established fingerprint map are solved, thereby achieving accurate tracing of pollutants under complex diffusion conditions that are commonly found in on-site environments.

[0049] Figure 2 The following is a schematic diagram showing the implementation of a method for tracing the source of gas pollution leakage under complex diffusion conditions according to an embodiment of the present invention. Figure 2 As shown, the main steps include: establishing a fingerprint map of surrounding pollution sources and setting typical factors for each pollution source; obtaining receptor pollution data in the receptor area; calculating the analytical error based on the chemical mass balance model and clarifying the error factor; establishing a variable weight chemical mass balance model based on typical factors and error factors, and calculating the pollution source.

[0050] Figure 3 The schematic diagram shows the relationship between the surrounding pollution sources and the receptor area according to the embodiment of the present invention. Figure 3As shown, in this optional embodiment, the fingerprint of the surrounding pollution sources is established, including: the pollution emission sources that have a pollution impact on the receptor area are the surrounding pollution sources; the fingerprint is constructed based on the main polluting components and their proportions that are diffused from the pollution source to the receptor area, or the fingerprint is constructed based on the main polluting components and their proportions that are emitted by the pollution source. The pollution source fingerprint in this embodiment is composed of the main polluting components and their proportions emitted by the pollution source. If conditions permit, the fingerprint is constructed based on the main polluting components and their proportions that are diffused from the pollution source to the receptor area, otherwise the fingerprint is constructed based on the main polluting components and their proportions that are emitted by the pollution source. Generally, the number of polluting components contained in the fingerprint should not be less than 8.

[0051] In some optional embodiments, the typical factors of each pollution source are set, including: if the pollutant component in the fingerprint of the pollution source meets the following conditions, then the pollutant component is the typical factor of the pollution source: the volume concentration percentage of the pollutant component in the fingerprint of the pollution source exceeds the preset threshold value; exceeds the preset multiple of the average volume concentration of the pollutant component; and the percentage contribution rate of the pollutant volume concentration of the pollution source to the receptor point under a specific wind direction exceeds the preset contribution rate threshold. The typical factor of the pollution source belongs to the pollutant component recorded in the fingerprint of the pollution source, and the volume concentration percentage of the pollutant component in the fingerprint of the pollution source exceeds the preset threshold value, such as 15%. And it exceeds 2 times 1 / M (i.e., the average volume concentration percentage of the pollutant component), M is the number of pollutants, and 2 is the preset multiple for example. And the percentage contribution rate of the pollutant volume concentration of the pollution source to the receptor point under a specific wind direction exceeds the preset contribution rate threshold value, such as 30%; the annual wind frequency of the specific wind direction is not less than 5%. Through the above setting method, the pollution source and its pollution factor that have the characteristics of significantly affecting the pollutant concentration in the receptor area are clearly defined and set as the typical factor of the pollution source. The setting of typical factors is mainly used to solve the problem mentioned above that complex conditions affect the diffusion and transmission characteristics of pollution sources. Since any pollutant component may change during the diffusion and transmission process, even if the pollutant component with a small proportion changes, it is not enough to fully affect the source tracing calculation results. Therefore, it is necessary to screen out pollution sources and their pollution factors that have the characteristics of significantly affecting the pollutant concentration in the receptor area.

[0052] In some optional embodiments, obtaining receptor pollution data of the polluted area includes: obtaining ambient air samples of the receptor area; using pollutant component qualitative and quantitative analysis equipment to analyze the ambient air samples to obtain pollutant components and volume concentration ratios. The receptor area is the area to be analyzed to clarify the source of pollution. Obtaining receptor pollution data is a necessary condition for conducting source tracing and analysis calculations. The specific method is as follows: obtaining ambient air samples of the receptor area, using pollutant component qualitative and quantitative analysis equipment to clarify the pollutant components and volume concentration ratios; to avoid differences in analysis capabilities between different types of equipment, it is recommended to obtain receptor pollution data and establish a pollution source fingerprint map, using the same type of qualitative and quantitative analysis equipment; when the receptor area is a point, it is necessary to continuously collect multiple air samples at different times at the location; when the receptor area is a body, surface, or line, it is necessary to continuously collect multiple air samples at different locations in the area at the same time / or different times. Increasing the sample size of receptor pollution data can improve the accuracy of source tracing and analysis results, while avoiding accidental situations that may be caused by a single sample. To this end, it is recommended to continuously collect multiple air samples at different times. For receptor areas such as body, surface, line (such as factory boundary), different spatial locations have different pollution characteristics, and multiple air samples need to be collected at different spatial locations, such as five-point sampling or uniform sampling. Considering the different concentrations of pollutants at different spatial locations and the different importance or sensitivity of different locations in reality, the number of samples can be increased in heavily polluted areas, key areas, and sensitive areas.

[0053] In some optional embodiments, calculating the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data includes: obtaining the analytical error SSE by the following steps:

[0054] Where N is the number of surrounding pollution sources, M is the number of polluting components; p ij is the volume concentration of the jth pollution component contributed by the i-th pollution source to the receptor area in the analysis result; c j The volume concentration of the jth pollutant component in the receptor pollution data.

[0055] According to the chemical mass balance model, the p ij Obtained through the following steps: ij =F ij ·S i Among them, F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; S i is the total volume concentration of the pollution components contributed by the ith pollution source to the receptor area, which is the source tracing result based on the chemical mass balance model.

[0056] In some optional embodiments, the pollutant component is determined as an error factor based on its contribution to the analytical error, including: when the analytical error is greater than K times the benchmark error, the analytical sub-error of each pollutant component is calculated; if the proportion of the analytical sub-error of any pollutant component in the analytical error exceeds a preset proportion threshold, and exceeds a preset multiple of the mean of the analytical sub-errors of each pollutant component, then the pollutant component is set as the error factor. After the analytical error calculation is completed, the following method is given to determine whether the analytical error is small enough to characterize that the calculation result is accurate enough: set the benchmark error, if the SSE is less than K times the benchmark error BSSE, it means that the analytical result is good and can be directly output; otherwise, the SSE is greater than K times the benchmark error BSSE, that is, the analytical result is poor, and the error factor needs to be further clarified, a variable weight CMB model is established, and the analytical result is calculated; the K is recommended to be 5%-20%; the benchmark error calculation formula is as follows:

[0057] In some optional embodiments, the method further comprises: calculating an analytical sub-error of each pollution component, comprising:

[0058]

[0059] Among them, SSE j is the analytical sub-error corresponding to the jth pollution component; N is the number of surrounding pollution sources; p ij is the volume concentration of the contribution of the i-th pollution source to the j-th pollution component in the receptor pollution data in the analysis result; c j Volume concentration of the jth component in the receptor contamination data.

[0060] In some optional embodiments, determining the variable weight chemical mass balance model according to the typical factor and the error factor includes obtaining the variable weight chemical mass balance model according to the following relationship:

[0061]

[0062] Among them, k ij is the weight coefficient to be optimized for the jth pollution component of the i-th pollution source. If the jth pollution component is an error factor and is a typical factor of the i-th pollution source, then set k ij is the weight coefficient to be optimized, otherwise k ij The value is fixed at 1. j is the analytical concentration error of the jth pollutant component.

[0063] The variable weight chemical mass balance model is used to determine the pollution source, including: based on the principle of minimizing the analytical error SSE of the variable weight chemical mass balance model, calculating the weight coefficient k to be optimized ij, and further analyze to obtain the total volume concentration S of the pollution components contributed by the i-th pollution source to the receptor area i , and then determine the source of pollution.

[0064] Based on the calculation results of the variable weight chemical mass balance model, the contribution concentration p of the i-th pollution source to the j-th pollution component in the receptor area is obtained. i ' j , the method is as follows:

[0065] p i ' j =k ij ·F ij ·S i ;

[0066] Among them, F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; k ij is the weight coefficient to be optimized for the jth pollution component of the ith pollution source; S i is the total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area; the above k ij , S i This is the traceability result based on the variable weight chemical mass balance model.

[0067] In some optional embodiments, the method further includes: using the error factor to correct the fingerprint of the surrounding pollution source. ij If k is less than 1, it means that the jth pollutant component actually emitted by the i-th pollution source is reduced compared with the proportion set in the fingerprint map, or the jth pollutant component is severely attenuated during the diffusion of polluted gas; ij If it is greater than 1, it means that the jth pollutant component of the ith pollution source or other pollution sources has an increased emission compared with the proportion set in the fingerprint spectrum; when the above conclusions are reached in multiple analysis results, it is recommended to optimize the construction of the fingerprint spectrum according to the current latest emission characteristics, and it is recommended to adjust the volume concentration proportion of the jth pollutant component (which is repeatedly determined as an error factor) in the fingerprint spectrum of the ith pollution source to F ij ×k ij .

[0068] In some optional embodiments, the variable weight chemical mass balance model is used to determine the pollution source, including: based on the principle of minimizing the analytical error of the variable weight chemical mass balance model, calculating the weight coefficient k to be optimized ij , and further analysis shows that S i (The total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area) is used to determine the pollution source. A simple variable weight chemical mass balance model is also provided in this embodiment as follows:

[0069]

[0070] Among them, k j is the weight coefficient of the jth pollution component; if the jth pollution component is an error factor and is a typical factor of any pollution source, k is directly set j is a positive number less than 1, usually set to 1 / 6 to 1 / 3, otherwise k j =1; on this basis, the analytical calculation is carried out based on the principle of minimizing the analytical error SSE, and s i (The total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area) E j is the analytical concentration error of the jth pollutant component.

[0071] Since the simple variable weight chemical mass balance model reduces the analytical error weight of the error factor, it will lead to the calculated S i There is a deviation from the actual total contribution concentration of the i-th pollution source to the pollution components in the receptor area. Therefore, it is recommended that the contribution concentration of the i-th pollution source to the j-th pollution component in the receptor area be calculated as follows:

[0072]

[0073] Furthermore, the total contribution concentration of the pollution components of the i-th pollution source to the receptor area is:

[0074] Example 2

[0075] This embodiment mainly provides a method for determining the typical factors of pollution sources. The typical factors of pollution sources belong to the pollutant components recorded in the fingerprint of the pollution source, the volume percentage of the pollutant components in the fingerprint of the pollution source exceeds 10%, and exceeds 2 times 1 / M, where M is the number of pollutants, and the volume percentage contribution rate of the pollution source to the pollutant of the receptor point under a specific wind direction exceeds 30%; the annual wind frequency of the specific wind direction is not less than 5%.

[0076] Figure 4 The following schematic diagram shows the environment distribution according to an embodiment of the present invention. Figure 4 As shown, a certain refinery has four pollution emission sources, namely residual oil, wax oil, reforming, and tank area. A receptor area is arranged in the reserved land on the south side, and the source of pollutants in the receptor area is analyzed.

[0077] Fingerprints of the above four pollution sources were established. Combined with the pollution emission characteristics of each device, a total of 17 pollution components were included. The following table shows example fingerprints of two pollution sources: residual oil and tank area.

[0078]

[0079]

[0080] First, it is required that the typical factors of the pollution source belong to the pollutant components recorded in the fingerprint of the pollution source, and the volume percentage of the pollutant components in the fingerprint of the pollution source exceeds 10%, and exceeds 1 / 17 of 2 times, that is, the pollutant components that meet the conditions for the residual oil hydrogenation pollution source include isobutane, 1-butene, n-butane, and isopentane, and the pollutant components that meet the conditions for the tank area pollution source include propylene, n-butane, isopentane, and octane.

[0081] Secondly, the relevant results of the previous source tracing analysis based on the chemical mass balance model were obtained, and it was found that under winter conditions (especially under northwest wind conditions), the residual oil hydrotreating unit would have a greater pollution impact on the receptor area, and the maximum pollution contribution rate of the 32 source tracing results under this wind direction condition was 37%, and the average contribution rate was 12%. From the statistical results of annual meteorological conditions, it can be seen that the northwest wind is the dominant wind direction in the area in winter, and the annual wind frequency is 11%. In summary, the requirements that the volume percentage contribution rate of pollutants from the pollution source to the receptor point under a specific wind direction exceeds 30% and the annual wind frequency of the specific wind direction is not less than 5% are met.

[0082] Therefore, the typical factors of residue hydrogenation pollution sources are set as isobutane, 1-butene, n-butane and isopentane.

[0083] Example 3

[0084] This embodiment mainly shows the calculation and identification method of analytical error, benchmark error, and error factor based on the chemical mass balance model. A certain refining enterprise has four pollution emission sources, namely, residual oil, wax oil, reforming, and tank area, and a receptor area is arranged in the reserved land on the south side. Establish fingerprint maps of four pollution emission sources to identify the typical factors of each emission source. For example, the typical factors of residual oil hydrogenation pollution source are isobutane, 1-butene, n-butane, and isopentane.

[0085] The receptor pollution data was obtained, and the sources of pollutants in the receptor area were used and analyzed to obtain the concentration values ​​of each pollutant component contributed by each pollution source. The results are as follows.

[0086]

[0087] The analytical error is the error between the receptor contamination fitting result obtained by analysis and the actual receptor contamination data, and the calculation formula is as follows:

[0088]

[0089] The analytical error of any j-th contamination component is calculated as follows:

[0090]

[0091] The reference error is calculated as follows:

[0092] Among them, N is the number of pollution sources, which is 4, and M is the number of pollution components, which is 17.

[0093] Among them, p ij It is the volume concentration of the contribution of the i-th pollution source in the analysis result to the j-th pollutant in the receptor pollution data; for example, the volume concentration of the contribution of the first pollution source, residual oil hydrogenation, to the fifth pollutant, isobutane, in the receptor pollution data is 147 ppb.

[0094] Among them, c j is the volume concentration of the jth component in the receptor pollution data; for example, the volume concentration of the fifth pollution component, isobutane, is 214 ppb. Calculate the analytical error SSE of each pollution component j And the overall analytical error SSE, the results are as follows:

[0095]

[0096] After the calculation is completed, the identification process based on the error factor is as follows:

[0097] 1) If the SSE is less than K times the benchmark error BSSE, it means that the analytical result is good and can be directly output; otherwise, if the SSE is greater than K times the benchmark error BSSE, the analytical result is poor and it is necessary to further clarify the error factor, establish a variable weight CMB model, and calculate the analytical result;

[0098] 2) If the analytical error SSE of any contaminant component j If the proportion of the analytical error SSE exceeds r and exceeds 2 times 1 / M, where M is the number of pollutants, the pollutant is set as the error factor. Here, K is 5%; r is 20%.

[0099] According to the calculation results of SSE and BSSE, SSE = 58420, BSSE = 115131, that is, SSE is greater than 5% of the reference error BSSE, that is, the analytical result is poor, and the error factor needs to be further clarified; according to SSE j The calculation results show that the SSE of the sixth pollutant 1-butene j It is 56169, accounting for 96.1% of the analytical error SSE, which is more than 20%, that is, 1-butene is the error factor.

[0100] Example 4

[0101] This embodiment mainly provides a specific implementation method for establishing a variable weight chemical mass balance model based on typical factors and error factors.

[0102] The variable weight chemical mass balance model is known as follows:

[0103]

[0104] Among them, k ij is the weight coefficient to be optimized for the jth pollution component of the i-th pollution source. If the jth pollution component is an error factor and is a typical factor of the i-th pollution source, then set k ij is the weight coefficient to be optimized, otherwise k ij The value is fixed at 1. j is the analytical concentration error of the jth pollution component. Among them, the contribution concentration of the i-th pollution source to the j-th pollution component in the receptor area is: p ij =k ij ·F ij ·S i ; where k ij is the weight coefficient to be optimized for the jth pollution component of the ith pollution source; F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; s i is the total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area, where k ij , S i It is the calculation result based on the variable weight chemical mass balance model.

[0105] For example, a certain refinery has four pollution emission sources, namely, residual oil, wax oil, reforming, and tank area. The receptor area is arranged in the reserved land on the south side, and four pollution emission source fingerprints are established; the typical factors of each emission source are identified, such as the typical factors of the residual oil hydrogenation pollution source are isobutane, 1-butene, n-butane, and isopentane; the error factor is identified, because the SSE of the sixth pollutant 1-butene in the chemical mass balance model analysis result is j It accounts for 96.1% of the analytical error SSE, which is the error factor.

[0106] Since the sixth pollutant 1-butene is an error factor and 1-butene is a typical factor of the first (residue oil hydrogenation) and second (tank farm) pollution sources, k is set 1,6 and k 2,6 is the weight coefficient to be optimized, and the remaining k ij The value is fixed at 1.

[0107] At this time, the variable weight chemical mass balance model is established based on typical factors and error factors:

[0108]

[0109] Based on the principle of minimizing the analytical error SSE, the k 1,6 and k 2,6Value and S i , usually set k ij ∈[1 / 3,3], then according to the variable weight chemical mass balance model, the contribution concentration of the i-th pollution source to the j-th pollution component in the receptor area is:

[0110] P'ij=k ij ·F ij ·S i .

[0111] Example 5

[0112] Based on the same inventive concept, the present invention also provides a gas pollution leakage tracing device under complex diffusion conditions. Figure 5 The schematic diagram of the structure of the gas pollution leakage tracing device under complex diffusion conditions according to an embodiment of the present invention is shown. Figure 5 As shown, the device includes: a typical factor determination module, which establishes a fingerprint map of surrounding pollution sources and sets typical factors for each pollution source; the typical factors are used to characterize the typical pollution components of the pollution sources; a data acquisition module, which is used to obtain receptor pollution data of the polluted area; an error factor determination module, which is used to calculate the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data, and determine the pollution component as the error factor according to the contribution to the analytical error; and a model construction module, which is used to determine a variable weight chemical mass balance model according to the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine the pollution source.

[0113] In some optional embodiments, a fingerprint map of surrounding pollution sources is established, including: taking the pollution emission sources that have a pollution impact on the receptor area as the surrounding pollution sources; constructing a fingerprint map based on the main pollutant components diffused from the pollution sources to the receptor area and their volume concentration ratios, or constructing a fingerprint map based on the main pollutant components emitted by the pollution source and their volume concentration ratios.

[0114] In some optional embodiments, a typical factor of each pollution source is set, including: if the pollutant component in the fingerprint of the pollution source meets the following conditions, then the pollutant component is the typical factor of the pollution source: the volume concentration percentage of the pollutant component in the fingerprint of the pollution source exceeds a preset threshold; exceeds a preset multiple of the average volume concentration of the pollutant component; and the contribution rate of the pollutant volume concentration percentage of the pollution source to the receptor point at a specific wind direction exceeds a preset contribution rate threshold.

[0115] In some optional embodiments, obtaining receptor pollution data of a polluted area includes: obtaining an ambient air sample of the receptor area; and using a pollutant component qualitative and quantitative analysis device to analyze the ambient air sample to obtain the pollutant components and volume concentration ratios.

[0116] In some optional embodiments, calculating the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data includes: obtaining the analytical error SSE by the following steps:

[0117] Where N is the number of surrounding pollution sources, M is the number of polluting components; p ij is the volume concentration of the jth pollution component contributed by the i-th pollution source to the receptor area in the analysis result; c j The volume concentration of the jth pollutant component in the receptor pollution data.

[0118] In some optional embodiments, the p ij Obtained through the following steps: ij =F ij ·S i ;

[0119] Among them, F ij is the volume concentration percentage of the jth pollutant in the i-th pollution source obtained based on the fingerprint spectrum; S i is the total volume concentration of the pollution components contributed by the ith pollution source to the receptor area, which is the source tracing result based on the chemical mass balance model.

[0120] In some optional embodiments, the contamination component is determined as an error factor based on its contribution to the analytical error, including: when the analytical error is greater than K times the baseline error, calculating the analytical sub-error of each contamination component; if the proportion of the analytical sub-error of any contamination component in the analytical error exceeds a preset proportion threshold and exceeds a preset multiple of the volume mean, then the contamination component is set as an error factor.

[0121] In some optional embodiments, the device further comprises: calculating the analytical sub-error of each pollution component, comprising:

[0122]

[0123] Among them, SSE j is the analytical sub-error corresponding to the jth pollution component; N is the number of surrounding pollution sources; p ij is the volume concentration of the contribution of the i-th pollution source to the j-th pollution component in the receptor pollution data in the analysis result; c j Volume concentration of the jth component in the receptor contamination data.

[0124] In some optional embodiments, determining the variable weight chemical mass balance model according to the typical factor and the error factor includes obtaining the variable weight chemical mass balance model according to the following relationship:

[0125]

[0126] Among them, k ij is the weight coefficient to be optimized for the jth pollution component of the i-th pollution source. If the jth pollution component is an error factor and is a typical factor of the i-th pollution source, then set k ij is the weight coefficient to be optimized, otherwise k ij is a fixed value of 1; E j is the analytical concentration error of the jth pollutant component.

[0127] In some optional embodiments, the device further comprises: using the error factor to correct the fingerprint map of the surrounding pollution sources.

[0128] In some optional embodiments, the variable weight chemical mass balance model is used to determine the pollution source, including: determining the pollution source based on the principle of minimizing the analytical error SSE of the variable weight chemical mass balance model.

[0129] In some optional embodiments, based on the calculation results of the variable weight chemical mass balance model, the contribution concentration P of the i-th pollution source to the j-th pollution component in the receptor area is obtained. i ' j , the method is as follows:

[0130] P' ij =k ij ·F ij ·S i ;

[0131] Among them, F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; k ij is the weight coefficient to be optimized for the jth pollution component of the ith pollution source; S i is the total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area; the above k ij , S i This is the traceability result based on the variable weight chemical mass balance model.

[0132] The specific definition of each functional module in the above-mentioned gas pollution leakage tracing device under complex diffusion conditions can be found in the above-mentioned definition of the gas pollution leakage tracing method under complex diffusion conditions, which will not be repeated here. Each module in the above-mentioned device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0133] Example 6

[0134] In order to verify the compatibility of the CMB model and the variable-weight chemical mass balance model with random changes in receptor data, mainly involving interference errors in the detection process and mutation errors in the diffusion process, a test experiment was carried out. The experimental plan and process are described as follows.

[0135] Taking the fingerprint maps of five types of emission sources of a certain refinery, including the reforming unit (source B), wax oil residue unit (source C), gas separation unit (source D), catalytic unit (source E), atmospheric and vacuum unit (source F) and external enterprise emission source (source A) as the data basis, the receptor data based on the fingerprint maps of the above emission sources were simulated and synthesized, and the CMB model and variable weight CMB were used to analyze and calculate the receptor data respectively.

[0136] The specific process is as follows:

[0137] (1) Generate initial receptor data. The initial receptor data is synthesized by superimposing the fingerprint maps of 6 types of emission sources in a certain proportion, that is, the receptor area under the theoretical state is only affected by the 6 types of emission sources, without interference from other emission sources, without the influence of material changes in the diffusion process, and the emission characteristics of the emission sources are completely consistent with the fingerprint map. During the synthesis process, the contribution rate of external enterprises is independently set to 70%, and the contribution rates of the other 5 types of emission sources are randomly assigned, and 200 sets of initial receptor data are obtained, that is, the actual value of the contribution rate of source A of the 200 sets of receptor data is 70%.

[0138] (2) Generate receptor data. For each pollutant in the initial receptor data, a (0-20)% error interference is randomly added, and three substances are randomly selected to significantly reduce their concentration values, with the reduction rate randomly set to (60-100)%, to represent the phenomenon that some pollutants fail to diffuse normally to the traceability area due to complex environmental influences such as meteorology during the pollution diffusion process, and the impact of certain changes in the emission patterns of various emission sources on the receptor area data.

[0139] (3) CMB model analysis and calculation. Based on the fingerprints of six types of emission sources, the CMB model is used to analyze and calculate the receptor data to obtain the contribution rate of external enterprise emission sources (source A).

[0140] (4) Analytical calculation of variable weight CMB model. Based on the fingerprints of six types of emission sources, the variable weight CMB model is used to analyze and calculate the receptor data to obtain the contribution rate of external enterprise emission sources (source A). Figure 6 The first half of the schematic diagram of the CMB and variable weight CMB source tracing analysis results in an embodiment of the present invention is schematically shown; Figure 7 The second half of the schematic diagram of the CMB and variable-weight CMB provenance analysis results in an embodiment of the present invention is schematically shown.

[0141] As can be seen from the figure, the true contribution rate of source A is 70%. The number of traceability experiments in which the relative error of source A in 200 experiments is greater than 10% is statistically analyzed by the CMB model, that is, the contribution rate of source A is less than 63% or greater than 77%. The number of experiments in which the relative error of CMB model analysis is greater than 10% is statistically 23 times, while the number of experiments in which the relative error of analysis obtained by the variable weight CMB model is greater than 10% is only 5 times. At the same time, the maximum error of the CMB model is 47%, while the maximum error of the variable weight CMB model is 59%. That is, the variable weight CMB model has a good analytical effect on the changes in receptor data interference caused by complex environments.

[0142] Example 7

[0143] This embodiment provides a non-volatile computer storage medium, which stores computer executable instructions. The computer executable instructions can execute the method in any of the above method embodiments and achieve the same technical effects.

[0144] A computer program product is also provided in this embodiment, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the methods described in the above aspects and achieves the same technical effects.

[0145] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0146] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0147] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0149] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0150] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0151] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0152] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0153] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for tracing the source of gas pollution leakage under complex diffusion conditions, characterized in that: The method comprises: Establishing fingerprints of surrounding pollution sources and setting typical factors of each pollution source; the typical factors are used to characterize typical pollution components of the pollution sources; Obtain receptor contamination data for contaminated areas; Calculating the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data, and determining the pollution component as the error factor according to the contribution to the analytical error; A variable weight chemical mass balance model is determined according to the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine pollution sources.

2. The method according to claim 1, characterized in that Establish a fingerprint map of surrounding pollution sources, including: The pollution emission sources that have a pollution impact on the receiving area are referred to as the peripheral pollution sources; The fingerprint map is constructed based on the main pollutant components diffused from the pollution source to the receptor area and their volume concentration ratios, or the fingerprint map is constructed based on the main pollutant components emitted by the pollution source and their volume concentration ratios.

3. The method according to claim 1, characterized in that Set typical factors for each pollution source, including: If the pollution component in the fingerprint of the pollution source meets the following conditions, then the pollution component is a typical factor of the pollution source: The volume concentration percentage of the pollutant component in the fingerprint of the pollution source exceeds a preset threshold; Exceeds a preset multiple of the average volume concentration of the pollutant; and The percentage contribution rate of the pollutant volume concentration of the pollution source at the receptor point under a specific wind direction exceeds the preset contribution rate threshold.

4. The method according to claim 1, characterized in that Obtain receptor contamination data for contaminated areas, including: obtaining an ambient air sample in the receptor area; The ambient air sample is analyzed using a pollutant component qualitative and quantitative analysis device to obtain the pollutant components and volume concentration ratios.

5. The method according to claim 1, characterized in that Calculate the analytical error between the traceability results based on the chemical mass balance model and the receptor contamination data, including: The analytical error SSE is obtained by the following steps: Where N is the number of surrounding pollution sources, M is the number of polluting components; p ij is the volume concentration of the jth pollution component contributed by the i-th pollution source to the receptor area in the analysis result; c j The volume concentration of the jth pollutant component in the receptor pollution data.

6. The method according to claim 5, characterized in that The p ik Obtained through the following steps: p ij =F ij ·S i ; Among them, F ik is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; S i is the total volume concentration of the pollution components contributed by the ith pollution source to the receptor area, which is the source tracing result based on the chemical mass balance model.

7. The method according to claim 1, characterized in that Determining the contamination component as an error factor according to the contribution to the analytical error includes: When the analytical error is greater than K times the reference error, the analytical sub-error of each pollution component is calculated; If the proportion of the analytical sub-error of any pollution component in the analytical error exceeds the preset proportion threshold and exceeds the preset multiple of the mean of the analytical sub-errors of each pollution component, the pollution component is set as the error factor.

8. The method according to claim 7, characterized in that Calculate the analytical sub-error for each contamination component, including: Among them, SSE j is the analytical sub-error corresponding to the jth pollution component; N is the number of surrounding pollution sources; p ij is the volume concentration of the contribution of the i-th pollution source to the j-th pollution component in the receptor pollution data in the analysis result; c j Volume concentration of the jth component in the receptor contamination data.

9. The method according to claim 1, characterized in that: Determining a variable weight chemical mass balance model according to the typical factor and the error factor includes obtaining the variable weight chemical mass balance model according to the following relationship: Among them, k ik is the weight coefficient to be optimized for the jth pollution component of the i-th pollution source. If the jth pollution component is an error factor and is a typical factor of the i-th pollution source, then set k ij is the weight coefficient to be optimized, otherwise k ij is a fixed value of 1; E j is the analytical concentration error of the jth pollutant component.

10. The method according to claim 9, characterized in that The method further comprises: using the error factor to correct the fingerprint spectrum of the surrounding pollution sources.

11. The method according to claim 9, characterized in that The variable weight chemical mass balance model is used to determine the pollution source, including: Based on the principle of minimizing the analytical error SSE of the variable weight chemical mass balance model, the weight coefficient k to be optimized is calculated. ij , and further analyze to obtain the total volume concentration S of the pollution components contributed by the i-th pollution source to the receptor area i , and then determine the source of pollution.

12. The method according to claim 11, characterized in that Based on the calculation results of the variable weight chemical mass balance model, the contribution concentration P of the i-th pollution source to the j-th pollution component in the receptor area is obtained. i ' j , the steps are as follows: P'ij=k ij ·F ij ·S i ; Among them, F ij is the volume concentration ratio of the jth pollutant component in the fingerprint of the i-th pollution source; k ij is the weight coefficient to be optimized for the jth pollution component of the ith pollution source; S i is the total volume concentration of the pollution components contributed by the i-th pollution source to the receptor area; the above k ij , S i This is the traceability result based on the variable weight chemical mass balance model.

13. A gas pollution leakage tracing device under complex diffusion conditions, characterized in that: The device comprises: The typical factor determination module establishes a fingerprint map of surrounding pollution sources and sets the typical factors of each pollution source; the typical factors are used to characterize the typical pollution components of the pollution source; Data collection module, used to obtain receptor pollution data in the polluted area; an error factor determination module, for calculating the analytical error between the traceability result based on the chemical mass balance model and the receptor pollution data, and determining the pollutant component as the error factor according to the contribution to the analytical error; and A model building module is used to determine a variable weight chemical mass balance model based on the typical factors and the error factors, and the variable weight chemical mass balance model is used to determine the pollution source.

14. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor executes the gas pollution leakage tracing method under complex diffusion conditions as described in any one of claims 1 to 12.

15. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable the computer to execute the gas pollution leakage tracing method under complex diffusion conditions as described in any one of claims 1 to 12.

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