Pollutant concentration contribution identification method and system driven by multi-point network tracing

Abstract

The present invention proposes a multi-point networked source tracing-driven pollutant concentration contribution identification method and system. This method obtains the location of high-concentration pollutant sites and the corresponding high-concentration time period; obtains meteorological data and underlying surface characteristics in the high-concentration site area to perform meteorological simulation; performs backward trajectory tracing based on the meteorological simulation results; and performs multi-site networked source tracing based on the tracing results to obtain backward trajectories and pollution sources for different sites. The backward trajectories of different sites are combined with the spatial three-dimensional concentration distribution data of air quality in the area of ​​the high-concentration pollutant site area to obtain the hourly time node concentration of different backward trajectories, and quantitatively analyze regional pollution and the change process of pollutant concentration within the pollution source between different sites. The present invention utilizes spatial three-dimensional concentration distribution data and backward trajectory technology to quantify the exogenous contribution of pollutants in different regions, reducing the uncertainty of the results of calculating regional contribution and local contribution, and reducing the computational complexity.

Description

Technical Field

[0001] The present invention relates to the field of environmental monitoring technology, and in particular to a pollutant concentration contribution identification method and system driven by multi-point networking and source tracing. Background Art

[0002] Pollutants not only originate from local emissions but can also be affected by pollution sources in external areas. The impact of these external pollution sources, especially cross-border pollution, has become a problem that many cities and regions cannot ignore. Accurately identifying and quantifying the contribution of external pollution is crucial for improving air quality, formulating environmental policies, and implementing pollution prevention and control. Current methods have the following shortcomings:

[0003] 1. Existing pollutant source analysis mainly relies on fixed monitoring stations and ground-based meteorological data. These methods have large spatial and temporal limitations, making it difficult to fully understand the diffusion patterns of pollutants and the contribution of external pollution sources.

[0004] 2. Traditional backward trajectory analysis methods are often based on point data and lack a detailed description of pollution distribution in a large area.

[0005] 3. Traditional methods for calculating regional and local contributions typically rely on extensive computation or statistical model decomposition to obtain the corresponding results, such as PCA and CTM numerical simulation. However, these methods often require the integration of extensive historical data, resulting in both high computational complexity and relatively long computation time. Calculating a city's regional and local contributions requires integrating data from all stations within the city. Furthermore, since the calculations are unilateral, they can lead to significant uncertainty.

[0006] 4. Traditional backward trajectories typically only calculate geographic locations, making it impossible to assess contributions. They also often treat the trajectory between two points as a single source, failing to fully account for the differences in pollution sources across different land use types. For example, emissions from industrial areas primarily come from industrial sources, while emissions from urban residential areas primarily come from residential sources. This crude zoning approach ignores the differences in emission characteristics across different land use types. Summary of the Invention

[0007] Given that existing pollutant source tracing methods have certain limitations in determining the proportion of external sources of regional pollution, especially under dynamic meteorological conditions and complex geographical environments, traditional methods often cannot accurately reflect the transport paths and distribution of different pollutants in the air. The main purpose of this invention is to propose a multi-point network tracing driven pollutant concentration contribution identification method and system, which combines spatial three-dimensional concentration distribution data and backward trajectory technology to more accurately estimate the proportion of external sources of regional pollution, targeting , ozone and long-life greenhouse gases (e.g. , methane, etc.) to adapt to their different propagation characteristics and life cycles, thereby providing more accurate data support for air quality management.

[0008] The present invention proposes a method for identifying pollutant concentration contributions driven by multi-point network tracing, the method comprising the following steps:

[0009] Step 1: Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration;

[0010] Step 2: Acquire meteorological data of the high-value station area, and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field;

[0011] Step 3: The station conducts backward trajectory tracing based on the three-dimensional meteorological field to determine the backward trajectory several hours before the time of high pollutant concentration;

[0012] Step 4: Conduct multi-site network linkage tracing based on the backward trajectory of the pollutant concentration several hours before the high value period to determine the backward trajectory and pollution source of different sites;

[0013] Step 5: Combine the backward trajectories of different stations with the three-dimensional concentration distribution data of air quality in the area of ​​high pollutant concentration stations to calculate the hourly time node concentration of different backward trajectories;

[0014] Step 6: Based on the hourly time node concentrations of different backward trajectories, quantitatively analyze regional pollution to determine the regional transmission contribution, the emission flux of pollutants within pollution sources of different land use types, and the change process of pollutant concentration within pollution sources.

[0015] The present invention also proposes a pollutant concentration contribution identification system driven by multi-point network tracing, wherein the system applies the above-mentioned multi-point network tracing driven pollutant concentration contribution identification method, and the system includes:

[0016] Data observation module, used for:

[0017] Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration;

[0018] Weather simulation module for:

[0019] Obtain meteorological data of the high-value station area and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field;

[0020] Network tracing module, used for:

[0021] The station conducts backward trajectory tracing based on the three-dimensional meteorological field to determine the backward trajectory several hours before the time of high pollutant concentration;

[0022] Based on the backward trajectory of pollutant concentrations in the hours before the peak, multi-site network linkage tracing is carried out to determine the backward trajectory and pollution source of different sites;

[0023] Quantitative Analysis Module for:

[0024] The backward trajectories of different stations are combined with the three-dimensional concentration distribution data of air quality in the area of ​​high pollutant concentration stations to calculate the hourly time node concentration of different backward trajectories;

[0025] Based on the hourly time node concentrations of different backward trajectories, regional pollution is quantitatively analyzed to determine the regional transmission contribution, the emission flux of pollutants within pollution sources of different land use types, and the change process of pollutant concentrations within pollution sources.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. Traditional pollution source analysis methods usually rely on ground monitoring station data, which has limited spatial distribution and is prone to data deviation. In order to overcome this shortcoming, it is necessary to combine spatial three-dimensional concentration distribution data. Spatial three-dimensional concentration distribution data includes different types of data such as lidar data, spatial interpolation data of monitoring points, satellite three-dimensional remote sensing data, and numerical simulation. The present invention uses spatial three-dimensional concentration distribution data and backward trajectory technology to provide a wider spatial coverage, quantify the exogenous contribution of pollutants in different regions, and enhance the accuracy of quantitative analysis of external regional transmission contributions. This is of great significance for cross-regional pollution source identification and control.

[0028] 2. Traditional backward trajectory models can exhibit significant errors in complex terrain (such as mountainous areas and coastal regions) and meteorological conditions (such as inversion layers and poor atmospheric stability). By combining the backward trajectory model with spatial three-dimensional concentration distribution data, this method can more effectively trace the source of pollutants in complex environments. It also considers the combined impact of both local and remote pollution sources, particularly for pollutants transported across regions. This overcomes the limitations of traditional methods and is particularly important when assessing the contribution of external regional transport.

[0029] 3. In the traditional method of calculating regional contribution and local contribution, a large number of calculations or decomposition through statistical models are mainly used to obtain the corresponding results, such as the PCA method and the CTM numerical simulation method. However, this calculation method often needs to be combined with a large amount of historical data for calculation, which not only requires a large amount of calculation but also takes a relatively long time. When calculating the regional contribution and local contribution of a city, it is necessary to collect all the site data in the city together for calculation, and since it is only a unilateral calculation of the numerical value, it may lead to greater uncertainty. The present invention improves the algorithm by introducing backward trajectory technology, reduces the uncertainty of the results of calculating regional contribution and local contribution, and reduces the amount of calculation.

[0030] 4. Since traditional backward trajectories generally only calculate geographic locations, it is impossible to evaluate the contribution, and the trajectory between two points of the backward trajectory is often regarded as a unified source, which fails to fully combine the differences in pollution sources due to different land use types. For example, emissions in industrial areas mainly come from industrial sources, and emissions in urban residential areas mainly come from residential sources. This rough zoning method ignores the differences in emission characteristics between different land types. The present invention combines backward trajectory technology, spatial three-dimensional concentration distribution data, and land use types to more accurately capture the contributions of different sources in a local area and improve the accuracy of the calculation results.

[0031] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of the pollutant concentration contribution identification method driven by multi-point network tracing proposed in the present invention;

[0033] Figure 2 It is a display diagram of the backward trajectory combined with spatial three-dimensional concentration distribution data;

[0034] Figure 3 This is a framework diagram of the pollutant concentration contribution identification system driven by multi-point networking and source tracing proposed in this invention. DETAILED DESCRIPTION

[0035] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0036] These and other aspects of the embodiments of the present invention will become clear with reference to the following description and accompanying drawings. In these descriptions and accompanying drawings, some specific implementations of the embodiments of the present invention are specifically disclosed to illustrate some ways of implementing the principles of the embodiments of the present invention, but it should be understood that the scope of the embodiments of the present invention is not limited thereto.

[0037] See also Figure 1 This embodiment provides a method for identifying pollutant concentration contributions driven by multi-point network tracing, the method comprising the following steps:

[0038] Step 1: Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration;

[0039] Step 2: Obtain meteorological data of the high-value station area, and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field;

[0040] Step 3: The station performs backward trajectory tracing based on the three-dimensional meteorological field to obtain the backward trajectory of the pollutant concentration several hours before the time of high value;

[0041] Step 4: Based on the backward trajectory of the pollutant concentration several hours before the high value time, multi-site network linkage tracing is carried out to obtain the backward trajectory of different sites and the pollution source;

[0042] See also Figure 2 In this step, the atmospheric pollutant diffusion model and three-dimensional meteorological field are used to reconstruct the air mass flow trajectory several hours before the station's peak value, displaying the source location information and concentration data of the polluted air mass at that station during that time period. Combined with the hourly three-dimensional spatial concentration distribution data, the hourly time node concentration of the backward trajectory is obtained. Different stations are networked and linked for source tracing. The difference in pollutant concentrations between linked stations is used to determine the source and generation area of ​​the pollutants along the transmission path.

[0043] The specific steps for networking and linking different sites for source tracing and using the pollutant concentration differences between linked sites to determine the source and generation area of ​​pollutants along the transmission path are as follows:

[0044] The first station conducts backward trajectory tracing prediction to obtain the source trajectory of the air mass;

[0045] According to the air mass source trajectory, the backward trajectory tracing result of the second station adjacent to the air mass source trajectory is obtained, and the pollutant concentration value of the second station at the past time is displayed at the same time. This is repeated until the backward trajectory tracing result of the Nth station and the pollutant concentration value of the Nth station at the past time are obtained;

[0046] Calculate the pollutant concentration values ​​at past moments in the air mass source trajectory, and determine whether there are new pollution sources or new pollutants in the path of the air mass source trajectory based on the difference in pollutant concentration values ​​between two adjacent stations, and determine the overall movement path and time-series change process of pollution within the target range;

[0047] Determine the location of the source of pollutants based on the overall movement path and temporal change process of pollution within the target range.

[0048] like Figure 2 As shown, taking the triggering linkage traceability of observation equipment at point A as an example, the pollutant concentration value at point A at coordinates (x, y, z) at 22 hours is 50μg / m 3 The pollutant concentration at point B at coordinates (x', y', z') at 21 hours is 41 μg / m 3 The calculated concentration difference between point A and point B is 9 μg / m 3 , it is judged that there is a new pollution source added or new pollutants generated on the path from the polluted air mass passing through point B at 21 hours to the point A at 22 hours.

[0049] Step 5: Combine the backward trajectories of different stations with the three-dimensional concentration distribution data of air quality in the area of ​​high-pollutant concentration stations to obtain the hourly time node concentrations of different backward trajectories;

[0050] Step 6: Quantitatively analyze regional pollution based on hourly time node concentrations for different backward trajectories to obtain regional transmission contributions, pollutant emission fluxes within pollution sources of different land use types, and the changing process of pollutant concentrations within pollution sources.

[0051] As a preferred embodiment of the present invention, quantitatively analyzing regional pollution based on hourly time node concentrations of different backward trajectories and obtaining regional transmission contributions specifically include the following steps:

[0052] Identify high-value area sites and sites that are linked to high-value area sites for traceability;

[0053] Obtain the pollutant concentration of the local site within the current area at the current moment, and obtain the pollutant concentration of the nearest neighboring site in the area outside the local boundary at the previous moment;

[0054] Excluding the impact of rainfall on atmospheric pollutants, the regional transmission contribution is calculated based on the pollutant concentrations at the local site in the current region at the current moment and the pollutant concentrations at the nearest neighboring site in the region outside the local boundary at the previous moment.

[0055] The impact of rainfall on atmospheric pollutants (such as ) concentrations, the impact of rainfall needs to be considered when calculating regional transport contributions to avoid large errors in the results due to rainfall. The model assumes that the impact of rainfall on pollutants ends when humidity drops below 80% after rainfall. Therefore, eliminating the impact of rainfall on atmospheric pollutants involves the following steps:

[0056] The end of the impact of rainfall on pollutants is defined as when the humidity drops below 80% after rainfall;

[0057] Calculate the time period from the start to the end of rainfall that will affect pollutants and obtain the rainfall impact time period. The corresponding process has the following relationship:

[0058] ;

[0059] in ， Indicates the time of rainfall impact on atmospheric pollutants; Indicates the time when rainfall is likely to occur; Indicates the time after rainfall affects the concentration of atmospheric pollutants.

[0060] The stations within the rainfall-affected period are excluded from participating in regional transmission contributions to reduce the error in the results caused by rainfall.

[0061] As a preferred embodiment of the present invention, the regional transmission contribution is calculated based on the pollutant concentration of the local station in the current area at the current moment and the pollutant concentration of the nearest neighboring station in the area outside the local boundary at the previous moment. The corresponding process has the following relationship:

[0062] ;

[0063] in, express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside p right T Regional transmission contribution ratio of the local site at the moment; express T The altitude at the moment is H Pollutants corresponding to local sites p The concentration (unit: μg / m 3 ); express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside p The concentration (unit: μg / m 3 ).

[0064] As a preferred embodiment of the present invention, the pollution sources passed by the backward trajectory between two stations are divided into different categories based on land use type, such as urban industrial areas (industrial sources), urban residential areas (residential sources), and forest areas (natural sources). The regional pollution is quantitatively analyzed by the hourly time node concentration of different backward trajectories. The process of obtaining the corresponding emission flux of pollutants within pollution sources of different land use types is expressed in the following relationship:

[0065] ;

[0066] in, The backward trajectory between two points passes through i Pollutants in pollution sources p Emission flux (unit: μg / (m 2 s)); The backward trajectory between two points passes through i Pollutants in pollution sources p Emissions (in μg / s); The backward trajectory between two points passes through i The horizontal area of ​​the pollution source (unit: m 2 ).

[0067] As a preferred embodiment of the present invention, the concentration of each hourly time node of different backward trajectories is used to quantitatively analyze regional pollution, and the process corresponding to the change process of pollutant concentration in the pollution source is obtained, which has the following relationship:

[0068] ;

[0069] in, express T The altitude at the moment is H Pollutants corresponding to local sites p The concentration (unit: μg / m 3 ); express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside p The concentration (unit: μg / m 3 ); express T The altitude at the moment is H Local site and T-τ The altitude at the moment is HZ The backward trajectory between the nearest neighbor sites in the local boundary outside the area passes through a height of h No. i Pollutants in pollution sources p Concentration changes (unit: μg / m 3 ); Represents the pollutants in the pollution source that the backward trajectory between two points passes through p The concentration proportional coefficient.

[0070] T The altitude at the moment is H Local site and T-τ The altitude at the moment is HZ The height of the backward trajectory between the nearest neighbor sites in the local boundary outside the area is h No. i Pollutants in pollution sources p The calculation process of the concentration change has the following relationship:

[0071] ;

[0072] in, and They represent the number of points that the backward trajectory between two points passes through. i Pollutants in pollution sources p The emission flux and the pollutants in all pollution sources passed by the backward trajectory between two points p The average emission flux (unit: μg / (m 2 s)); and Represents the pollution sources that the backward trajectory between two points passes through i The distance between the two points and the distance of the backward trajectory between the two points (unit: m); The backward trajectory between two points passes through i The vertical mixing coefficient of each pollution source at height h (unit: m 2 / s); The backward trajectory between two points passes through i The wind speed at the corresponding height h for each pollution source (unit: m / s); The backward trajectory between two points passes through i The contribution ratio of the pollution generated by direct emissions from individual pollution sources, diffusion effects, and physical and chemical processes such as chemical conversion to the concentration change; The backward trajectory between two points passes through i The deviation of the concentration change of each pollution source is expected to be close to 0.

[0073] The backward trajectory between two points passes through the pollutants in the pollution source p The calculation process of the concentration proportional coefficient has the following relationship:

[0074] .

[0075] Please refer to Figure 3This embodiment further provides a pollutant concentration contribution identification system driven by multi-point network tracing, wherein the system applies the pollutant concentration contribution identification method driven by multi-point network tracing as described above, and the system includes:

[0076] Data observation module, used for:

[0077] Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration;

[0078] Weather simulation module for:

[0079] Obtain meteorological data of the high-value station area and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field;

[0080] Network tracing module, used for:

[0081] The station conducts backward trajectory tracing based on the three-dimensional meteorological field to determine the backward trajectory several hours before the time of high pollutant concentration;

[0082] Based on the backward trajectory of pollutant concentrations in the hours before the peak, multi-site network linkage tracing is carried out to determine the backward trajectory and pollution source of different sites;

[0083] Quantitative Analysis Module for:

[0084] The backward trajectories of different stations are combined with the three-dimensional concentration distribution data of air quality in the area of ​​high pollutant concentration stations to calculate the hourly time node concentration of different backward trajectories;

[0085] Based on the hourly time node concentrations of different backward trajectories, regional pollution is quantitatively analyzed to determine the regional transmission contribution, the emission flux of pollutants within pollution sources of different land use types, and the change process of pollutant concentrations within pollution sources.

[0086] It should be understood that, although the various steps in the flow chart of each embodiment of the present invention are shown in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0087] It should be understood that various components of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0088] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0089] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A multi-point network source tracing driven pollutant concentration contribution identification method, characterized in that: The method comprises the following steps: Step 1: Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration; Step 2: Acquire meteorological data of the high-value station area, and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field; Step 3: The station conducts backward trajectory tracing based on the three-dimensional meteorological field to determine the backward trajectory several hours before the time of high pollutant concentration; Step 4: Conduct multi-site network linkage tracing based on the backward trajectory of the pollutant concentration several hours before the high value period to determine the backward trajectory and pollution source of different sites; Step 5: Combine the backward trajectories of different stations with the three-dimensional concentration distribution data of air quality in the area of ​​high pollutant concentration stations to calculate the hourly time node concentration of different backward trajectories; Step 6: Based on the hourly time node concentrations of different backward trajectories, quantitatively analyze regional pollution to determine the regional transmission contribution, the emission flux of pollutants within pollution sources of different land use types, and the change process of pollutant concentration within pollution sources; In step 6, quantitatively analyzing regional pollution based on hourly time node concentrations of different backward trajectories to obtain regional transmission contributions specifically includes the following steps: Identify high-value area sites and sites that are linked to high-value area sites for traceability; Obtain the pollutant concentration of the local site within the current area at the current moment, and obtain the pollutant concentration of the nearest neighboring site in the area outside the local boundary at the previous moment; Excluding the impact of rainfall on atmospheric pollutants, the regional transport contribution is calculated based on the pollutant concentrations at the local station in the current region at the current moment and the pollutant concentrations at the nearest neighboring station in the region outside the local boundary at the previous moment; The following relationship exists for the process of quantitatively analyzing regional pollution by using the hourly time node concentrations of different backward trajectories to obtain the emission flux of pollutants from pollution sources of different land use types: ； in, represents the emission flux of pollutant p in the i-th pollution source passed by the backward trajectory between two points; represents the emission of pollutant p in the i-th pollution source passed by the backward trajectory between two points; represents the horizontal area of ​​the i-th pollution source passed by the backward trajectory between two points; The concentration of each hourly time node of different backward trajectories is used to quantitatively analyze regional pollution. The following relationship exists for the process corresponding to the change process of pollutant concentration within the pollution source: ； in, express T The altitude at the moment is H Pollutants corresponding to local sites p concentration; express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside the p concentration; express T The altitude at the moment is H Local site and T-τ The altitude at the moment is HZ The backward trajectory between the nearest neighbor sites in the local boundary outside the area passes through a height of h No. i Pollutants in pollution sources p changes in concentration; Represents the pollutants in the pollution source that the backward trajectory between two points passes through p The concentration proportional coefficient; T The altitude at the moment is H Local site and T-τ The altitude at the moment is HZ The height of the backward trajectory between the nearest neighbor sites in the local boundary outside the area is h No. i Pollutants in pollution sources p The calculation process of the concentration change has the following relationship: ； in, and They represent the number of points that the backward trajectory between two points passes through. i Pollutants in pollution sources p The emission flux and the pollutants in all pollution sources passed by the backward trajectory between two points p The average emission flux of and Represents the pollution sources that the backward trajectory between two points passes through i The distance between the two points and the distance of the backward trajectory between the two points; The backward trajectory between two points passes through i The corresponding height of pollution sources h The vertical mixing coefficient of The backward trajectory between two points passes through i The corresponding height of pollution sources h wind speed; The backward trajectory between two points passes through i The contribution ratio of direct emissions from each pollution source, diffusion effects, and pollution formed by chemical conversion processes to concentration changes; The backward trajectory between two points passes through i The deviation of the concentration change of each pollution source.

2. The multi-point network tracing driven pollutant concentration contribution identification method according to claim 1 is characterized in that: Eliminating the impact of rainfall on air pollutants specifically involves the following steps: The end of the impact of rainfall on pollutants is defined as when the humidity drops below 80% after rainfall; Calculate the time period from the start to the end of rainfall that will affect pollutants and obtain the rainfall impact time period; The stations within the rainfall-affected period are excluded from participating in regional transmission contributions to reduce the error in the results caused by rainfall.

3. The multi-point network source tracing driven pollutant concentration contribution identification method according to claim 2 is characterized in that: In step 6, the regional transmission contribution is calculated based on the pollutant concentration of the local station in the current area at the current moment and the pollutant concentration of the nearest neighboring station in the area outside the local boundary at the previous moment. The corresponding process has the following relationship: ； in, express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside the p right T Regional transmission contribution ratio of the local site at the moment; express T The altitude at the moment is H Pollutants corresponding to local sites p concentration; express T-τ The altitude at the moment is HZ The pollutants corresponding to the nearest neighboring stations in the local boundary area outside the p concentration.

4. The multi-point network tracing driven pollutant concentration contribution identification method according to claim 3 is characterized in that: The process of calculating the time period from the start to the end of rainfall that will affect pollutants corresponds to the following relationship: ； in ， Indicates the time of rainfall impact on atmospheric pollutants; Indicates the time when rainfall is likely to occur; Indicates the time after rainfall affects the concentration of atmospheric pollutants.

5. The pollutant concentration contribution identification method driven by multi-point network tracing according to claim 1 is characterized in that: The backward trajectory between two points passes through the pollutants in the pollution source p The calculation process of the concentration proportional coefficient has the following relationship: 。 6. A multi-point network traceability driven pollutant concentration contribution identification system, characterized by: The system applies the multi-point networking source tracing driven pollutant concentration contribution identification method according to any one of claims 1 to 5, and the system includes: Data observation module, used for: Obtain the location of the site with high pollutant concentration and the time period with corresponding high pollutant concentration; Weather simulation module for: Obtain meteorological data of the high-value station area and perform meteorological simulation on the meteorological data according to the underlying surface characteristics of the high-value station area to obtain a three-dimensional meteorological field; Network tracing module, used for: The station conducts backward trajectory tracing based on the three-dimensional meteorological field to determine the backward trajectory several hours before the time of high pollutant concentration; Based on the backward trajectory of pollutant concentrations in the hours before the peak, multi-site network linkage tracing is carried out to determine the backward trajectory and pollution source of different sites; Quantitative Analysis Module for: The backward trajectories of different stations are combined with the three-dimensional concentration distribution data of air quality in the area of ​​high pollutant concentration stations to calculate the hourly time node concentration of different backward trajectories; Based on the hourly time node concentrations of different backward trajectories, regional pollution is quantitatively analyzed to determine the regional transmission contribution, the emission flux of pollutants within pollution sources of different land use types, and the change process of pollutant concentrations within pollution sources.

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