Rainfall environment pollutant diffusion analysis method and system based on Gaussian diffusion model

Abstract

The invention belongs to the technical field of pollutant diffusion simulation, and particularly relates to a rainfall environment pollutant diffusion analysis method and system based on a Gaussian diffusion model, and the method specifically comprises the steps: 1, obtaining and preprocessing meteorological data; step 2, based on the Gaussian diffusion model of the continuous point source, obtaining a three-dimensional Gaussian diffusion model changing along with time; step 3, calculating precipitation factors based on the meteorological data, and adding the precipitation factors into a three-dimensional Gaussian diffusion model to obtain a precipitation environmental pollutant diffusion model; and step 4, performing diffusion simulation and result visualization processing by using the rainfall environment pollutant diffusion model, and obtaining an atmospheric pollutant diffusion distribution diagram over time in a rainfall environment. According to the method, the condition of the rainfall environment can be considered, so that the established model can better reflect the real pollutant diffusion condition in the rainfall environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of pollutant diffusion simulation, and in particular relates to a precipitation environment pollutant diffusion analysis method and system based on a Gaussian diffusion model. Background Art

[0002] The Gaussian diffusion model is a classic mathematical model widely used in simulating the diffusion of atmospheric pollutants. The model is based on the Gaussian probability distribution theory and is used to predict the concentration distribution of pollutants released from point sources in the atmosphere. Its basic assumptions include that atmospheric turbulence is isotropic, pollutants follow a normal distribution in the horizontal and vertical directions, and meteorological conditions (such as wind speed, wind direction, etc.) are stable and unchanged.

[0003] However, the existing technology is mainly applicable to the situation where the meteorological conditions are stable and uniform, which makes it difficult to deal with complex meteorological changes. In addition, the traditional Gaussian diffusion model does not consider the impact of precipitation factors on the diffusion effect of pollutants, and its simulation results have certain limitations. Summary of the invention

[0004] In view of this, the present invention provides a precipitation environment pollutant diffusion analysis method and system based on a Gaussian diffusion model, which can take into account the precipitation environment so that the constructed model can better reflect the actual pollutant diffusion situation in the precipitation environment.

[0005] The technical solution for implementing the present invention is as follows:

[0006] In the first aspect, the embodiment of the present application provides a method for analyzing the diffusion of pollutants in a precipitation environment based on a Gaussian diffusion model, and the specific process is as follows:

[0007] Step 1: Meteorological data collection and preprocessing;

[0008] Step 2: Based on the Gaussian diffusion model of continuous point sources, a three-dimensional Gaussian diffusion model that changes with time is obtained;

[0009] Step 3: Calculate the precipitation factor based on the meteorological data, and add the precipitation factor to the three-dimensional Gaussian diffusion model to obtain a precipitation environmental pollutant diffusion model;

[0010] Step 4: Use the precipitation environment pollutant diffusion model to perform diffusion simulation and visualize the results, and then generate a diffusion distribution map of atmospheric pollutants over time in a precipitation environment.

[0011] Furthermore, the three-dimensional Gaussian diffusion model of the present invention that varies with time:

[0012]

[0013] Where C is the concentration of pollutants at any point in space (x, y, z); σ x, σ y , σ z are the diffusion parameters in the x, y, and z directions; u is the average wind speed; x is the distance from the spatial point to the source along the downwind direction; y is the distance from the spatial point to the source along the direction perpendicular to the wind direction; z is the height of the spatial point; H is the pollutant release height, and q is the source strength.

[0014] Furthermore, the precipitation factor of the present invention is:

[0015]

[0016] β=1.2×10 -5 I 0.5

[0017] Among them, I is the rainfall intensity, β is the adsorption coefficient, u refers to the average wind speed of the environment, and x is the distance from the spatial point to the source along the downwind direction.

[0018] Furthermore, the precipitation environmental pollutant diffusion model of the present invention is:

[0019]

[0020] Among them, Q(x)=q*R(x).

[0021] Furthermore, in step four of the present invention: determine the simulation area, set the grid resolution to perform grid division and initialize the grid data; set the time step, use the precipitation environment pollutant diffusion model to calculate the concentration, and organize the pollutant concentration data at each time step calculated by the Gaussian diffusion model into a unified format, and use contour maps to display the spatial distribution of pollutant concentrations.

[0022] In a second aspect, an embodiment of the present application provides a precipitation environment pollutant diffusion analysis system based on a Gaussian diffusion model, the system comprising: a data acquisition module, a Gaussian diffusion model storage module, a pollutant diffusion model calculation module, and a pollutant diffusion simulation analysis model;

[0023] Data acquisition module: used to acquire meteorological data and perform preprocessing;

[0024] Gaussian diffusion model storage module: based on the Gaussian diffusion model of continuous point sources, obtain the three-dimensional Gaussian diffusion model that changes with time;

[0025] Pollutant diffusion model calculation module: calculates precipitation factors based on the meteorological data, and adds the precipitation factors to the three-dimensional Gaussian diffusion model to obtain a precipitation environment pollutant diffusion model;

[0026] Pollutant diffusion simulation analysis model: Using the precipitation environment pollutant diffusion model, diffusion simulation and result visualization are performed to generate the atmospheric pollutant diffusion distribution map over time in a precipitation environment.

[0027] Furthermore, the three-dimensional Gaussian diffusion model of the present invention that varies with time:

[0028]

[0029] Where C is the concentration of pollutants at any point in space (x, y, z); σ x , σ y , σ z are the diffusion parameters in the x, y, and z directions; u is the average wind speed; x is the distance from the spatial point to the source along the downwind direction; y is the distance from the spatial point to the source along the direction perpendicular to the wind direction; z is the height of the spatial point; H is the pollutant release height, and q is the source strength.

[0030] Furthermore, the precipitation factor of the present invention is:

[0031]

[0032] β=1.2×10 -5 I 0.5

[0033] Among them, I is the rainfall intensity, β is the adsorption coefficient, u refers to the average wind speed of the environment, and x is the distance from the spatial point to the source along the downwind direction.

[0034] Furthermore, the precipitation environmental pollutant diffusion model of the present invention is:

[0035]

[0036] Among them, Q(x)=q*R(x).

[0037] Furthermore, the data acquisition module of the present invention is used to determine the simulation area, set the grid resolution for grid division and initialize the grid data; set the time step, use the precipitation environment pollutant diffusion model to calculate the concentration, organize the pollutant concentration data at each time step calculated by the Gaussian diffusion model into a unified format, and use contour maps to display the spatial distribution of pollutant concentrations.

[0038] Beneficial effects:

[0039] The present invention first processes the meteorological data, then performs multi-step calculations by improving the Gaussian diffusion model, and then visualizes the diffusion simulation result data, and finally obtains the atmospheric pollutant diffusion distribution map over time under the influence of precipitation elements. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 It is the pollutant diffusion simulation algorithm flow based on real-time meteorological data in the present invention;

[0042] Figure 2 is the three-dimensional coordinate system of the Gaussian diffusion model;

[0043] Figure 3 It is a calculation flow chart of Gaussian diffusion model in the present invention;

[0044] Figure 4 It is a flow chart of algorithm design for improving Gaussian diffusion model in the present invention;

[0045] Figure 5 It is a schematic diagram of the results of the development of pollutant concentration over time in the present invention;

[0046] Figure 6 It is a schematic diagram of the results of the pollutant concentration being affected by different precipitation levels in the present invention. DETAILED DESCRIPTION

[0047] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0048] It should be noted that the following embodiments and features in the embodiments may be combined with each other in the absence of conflict; and, based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making any creative work are within the scope of protection of the present disclosure.

[0049] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0050] The present application embodiment provides a pollutant diffusion modeling method based on meteorological data, such as Figure 1As shown, it includes the following steps:

[0051] Step 1: Meteorological data collection and preprocessing;

[0052] Acquire meteorological model data and preprocess it. In this embodiment, meteorological data can be acquired through WRF model or ERA5 data set.

[0053] (1) Obtaining meteorological data using the WRF model

[0054] The WRF (Weather Research and Forecasting) model is used to simulate and provide atmospheric environmental parameters. The WRF model can simulate and predict a variety of physical and chemical processes in the atmosphere, including temperature, humidity, wind speed, wind direction, air pressure, and precipitation. Its unique cross-scale simulation capability can accurately capture weather phenomena from the mesoscale to the global scale.

[0055] (2) Obtaining meteorological data from the ERA5 dataset

[0056] ERA5 is the fifth generation of ECMWF (European Centre for Medium-Range Weather Forecasts) atmospheric reanalysis datasets of global climate from 1940 to the present. ERA5 provides hourly estimates of a large number of atmospheric, land and ocean climate variables. ERA5 combines model data with observational data from around the world, using data assimilation techniques to form a globally complete and consistent dataset.

[0057] In this algorithm, the meteorological element data obtained from the WRF simulation or ERA5 dataset are converted into a unified .nc format through the corresponding algorithm, and an interactive interface between the meteorological data and the improved Gaussian diffusion model is established to realize the real-time coupling calculation of the meteorological data module and the pollutant diffusion module, ensuring that the simulation results of the pollutant diffusion effect are updated in real time.

[0058] Step 2: Based on the Gaussian diffusion model of continuous point sources, a three-dimensional Gaussian diffusion model that changes with time is obtained;

[0059] The traditional Gaussian model is applicable to uniform atmospheric conditions and is based on the following assumptions: the wind speed inside the simulation space is uniform and stable; the release of pollutant sources is continuous and uniform; the mass of pollutants remains conserved during the overall diffusion process (without considering material transformations such as nuclide decay); in addition, the theory assumes that the concentration of pollutants during continuous point source diffusion conforms to the law of normal distribution.

[0060] To simulate the diffusion of pollutants under point source release using the above Gaussian model, we first need to establish a three-dimensional coordinate system, taking the vertical projection point of the pollutant release point to the ground as the coordinate origin, taking the z-axis along this point perpendicular to the ground, taking the main wind direction as the x-axis, and obtaining the corresponding direction of the y-axis through the right-hand rule. Establish a three-dimensional coordinate system in Gaussian space, as shown in the attached figure. Figure 2 shown.

[0061] Based on the above assumptions, the pollutant concentration distribution function at any point in the simulation area can be obtained as:

[0062]

[0063] Where: C is the concentration of pollutants at any point (x, y, z) in the target area, kg / m 3 ; A(x) is the function to be determined; σ y , σ z is the diffusion parameter in the y and z directions, m.

[0064] Considering the continuous emission of point sources and the law of mass conservation, on any cross section perpendicular to the x-axis, there exists:

[0065]

[0066] Where: q is the source strength, that is, the rate at which point sources emit pollutants; u is the average ambient wind speed, m / s.

[0067] Further considering the stability and uniformity of the wind field, the undetermined function can be obtained:

[0068] A(x)=q / 2πuσ y σ z (3)

[0069] In summary, the core formula of the Gaussian diffusion model of continuous point sources can be derived:

[0070]

[0071] The specific calculation steps of pollutant concentration are as follows: Figure 3 As shown:

[0072] The Gaussian diffusion model of continuous point sources in the above formula (4) is a traditional Gaussian model that only considers wind speed and wind direction. It is suitable for continuous leakage diffusion and uniform meteorological fields, and can solve the steady-state distribution characteristics of pollutant diffusion in this specific case. However, for the actual diffusion of pollutants in the atmosphere, the background field of meteorological elements will change over time, that is, the time effect should be considered in the Gaussian diffusion model to obtain the nuclear pollutant diffusion results that change over time.

[0073] Generally speaking, the smoke released by a point source starts from the origin o and migrates continuously with the wind direction, and diffuses in the y and z directions at the same time. According to the material balance, the following three-dimensional Gaussian diffusion formula that changes with time can be further derived:

[0074]

[0075] Where C is the concentration of pollutants at any point in space (x, y, z), kg / m 3 ; σ x , σ y , σ z are the diffusion parameters in the x, y, and z directions; u is the average wind speed; x is the distance from the spatial point to the source along the downwind direction; y is the distance from the spatial point to the source along the direction perpendicular to the wind direction; z is the height of the spatial point; and H is the pollutant release height.

[0076] Step 3: Calculate the precipitation factor based on the meteorological data, and add the precipitation factor to the three-dimensional Gaussian diffusion model to obtain a precipitation environmental pollutant diffusion model;

[0077] Precipitation is an atmospheric element that has an important impact on the diffusion of pollutants. During precipitation, raindrops will interact with pollutants in the atmosphere and transfer pollutants from the gas phase to the liquid phase through the wet deposition process. This process will deeply affect the concentration of pollutants in the atmosphere. Considering the impact of rainfall on the concentration of diffused gases, the Gaussian model is further improved. The improved point source Gaussian diffusion model is as follows:

[0078]

[0079] in,

[0080]

[0081] β=1.2×10 -5 I 0.5 (8)

[0082] Where I is the rainfall intensity, in mm·h -1 ; β is the adsorption coefficient; unit is m·s -1 .

[0083] Step 4: Use the precipitation environment pollutant diffusion model to perform diffusion simulation and visualize the results, and then generate a diffusion distribution map of atmospheric pollutants over time in a precipitation environment.

[0084] Attached Figure 4To improve the algorithm design flow chart of the Gaussian diffusion model, the pollution source module collects source parameters such as the release rate of pollutants in real time and transmits them to the simulation calculation module. The meteorological parameter module obtains precipitation meteorological parameters in real time and transmits them to the simulation calculation module. The simulation calculation module processes the source data, meteorological data, and custom parameters such as the calculation area size, and substitutes them into the model for concentration distribution calculation. Finally, the concentration distribution cloud map of pollutants in the atmosphere is obtained through visualization. The specific steps are as follows:

[0085] 1. Pollution source setting

[0086] Set the basic information of the pollutant emission source, such as location, release height, and emission speed. These information will be used as input parameters of the model.

[0087] 2. Meteorological element settings

[0088] ① Data source selection: Determine whether to use the WRF model or the ERA5 dataset as the source of meteorological data.

[0089] ②Data acquisition: Obtain the required meteorological data, including precipitation parameters, through WRF model simulation or download from the ERA5 official website.

[0090] ③ Data preprocessing: The acquired data needs to be preprocessed, including format conversion, time alignment, spatial interpolation, etc., to ensure that the meteorological data can match the geographic and time coordinates in the model. During data processing, the appropriate time and spatial resolution can be selected according to research needs.

[0091] 3. Simulate regional settings

[0092] ① Determine the simulation area: clarify the geographical area of ​​the simulation, which is usually determined based on the research objectives, the location of pollution sources, and sensitive areas of concern. The simulation area should be large enough to include all important areas where pollutants may spread, while also taking into account the limitations of computing resources.

[0093] ② Set the grid resolution: The grid resolution refers to the size of each cell in the grid, which determines the spatial accuracy of the algorithm model. The choice of resolution should be based on research needs, data availability, and computing resources.

[0094] ③ Grid division: According to the determined simulation area and grid resolution, the entire area is divided into a series of regular grid cells.

[0095] ④ Initialize grid data: After the grid division is completed, each grid unit needs to be initialized, including setting the initial concentration value (usually 0, indicating no pollutants), recording the grid coordinate information, etc.

[0096] 4. Diffusion formula calculation

[0097] ① Time step setting: Set an appropriate time step (such as every hour) based on research requirements and the temporal resolution of the data.

[0098] ② Concentration calculation: According to Gaussian diffusion theory, the pollutant concentration at any point downwind can be calculated using the improved Gaussian diffusion model formula, which involves the standard deviation in each direction (i.e., diffusion coefficient), and these parameters are related to the location of the grid point. In each time step, the current meteorological data and pollution source data are used to calculate the concentration distribution of pollutants using the Gaussian diffusion formula.

[0099] ③ Iterative calculation: move the time forward one step, repeat the above process until the simulation ends, and superimpose the results.

[0100] 5. Result visualization steps

[0101] ①Solution of simulation results: The pollutant concentration data at each time step calculated by the Gaussian diffusion model are sorted into a unified format, including the spatial coordinates (x, y, z) and the corresponding concentration value C.

[0102] ② Draw a concentration distribution map: Use contour maps to show the spatial distribution of pollutant concentrations. The depth of color or the size of the symbol can indicate the concentration, and the specific value is shown in the legend color scale.

[0103] Combined with the visualization results, the temporal and spatial variation characteristics of pollutant diffusion are analyzed and discussed, and the possible influencing factors and potential risks are analyzed to provide data reference for relevant decision-making.

[0104] Attached Figure 5-6 The above content proves the effectiveness of the modified Gaussian algorithm, that is, the present invention can generate corresponding pollutant diffusion results in combination with the meteorological conditions input in real time.

[0105] The embodiment of the present application is a precipitation environment pollutant diffusion analysis system based on a Gaussian diffusion model, the system comprising: a data acquisition module, a Gaussian diffusion model storage module, a pollutant diffusion model calculation module, and a pollutant diffusion simulation analysis model;

[0106] Data acquisition module: used to acquire meteorological data and perform preprocessing;

[0107] Gaussian diffusion model storage module: used to store the three-dimensional Gaussian diffusion model that changes with time;

[0108] Pollutant diffusion model calculation module: calculates precipitation factors based on the meteorological data, and adds the precipitation factors to the three-dimensional Gaussian diffusion model to obtain a precipitation environment pollutant diffusion model;

[0109] Pollutant diffusion simulation analysis model: Using the precipitation environment pollutant diffusion model, diffusion simulation and result visualization are performed to generate the atmospheric pollutant diffusion distribution map over time in a precipitation environment.

[0110] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A precipitation environmental pollutant diffusion analysis method based on Gaussian diffusion model, characterized in that: The specific process is: Step 1: Acquisition and preprocessing of meteorological data; Step 2: Based on the Gaussian diffusion model of continuous point sources, a three-dimensional Gaussian diffusion model that changes with time is obtained; Step 3: Calculate the precipitation factor based on the meteorological data, and add the precipitation factor to the three-dimensional Gaussian diffusion model to obtain a precipitation environmental pollutant diffusion model; Step 4: Use the precipitation environment pollutant diffusion model to perform diffusion simulation and visualize the results, and then generate a diffusion distribution map of atmospheric pollutants over time in a precipitation environment.

2. The precipitation environmental pollutant diffusion analysis method based on Gaussian diffusion model according to claim 1 is characterized in that: Three-dimensional Gaussian diffusion model with time: Where C is the concentration of pollutants at any point in space (x, y, z); σ x , σ y , σ z are the diffusion parameters in the x, y, and z directions; u is the average wind speed; x is the distance from the spatial point to the source along the downwind direction; y is the distance from the spatial point to the source along the direction perpendicular to the wind direction; z is the height of the spatial point; H is the pollutant release height, and q is the source strength.

3. The precipitation environmental pollutant diffusion analysis method based on Gaussian diffusion model according to claim 2 is characterized in that: The precipitation factor is: β＝1.2×10 -5 I 0.5 Among them, I is the rainfall intensity, β is the adsorption coefficient, u refers to the average wind speed of the environment, and x is the distance from the spatial point to the source along the downwind direction.

4. The precipitation environmental pollutant diffusion analysis method based on Gaussian diffusion model according to claim 3 is characterized in that: The precipitation environmental pollutant diffusion model is: Among them, Q(x)=q*R(x).

5. The precipitation environmental pollutant diffusion analysis method based on Gaussian diffusion model according to claim 1 is characterized in that: In step 4: determine the simulation area, set the grid resolution for grid division and initialize the grid data; set the time step, use the precipitation environment pollutant diffusion model to calculate the concentration, organize the pollutant concentration data at each time step calculated by the Gaussian diffusion model into a unified format, and use contour maps to display the spatial distribution of pollutant concentrations.

6. A precipitation environmental pollutant diffusion analysis system based on Gaussian diffusion model, characterized in that: The system includes: a data acquisition module, a Gaussian diffusion model storage module, a pollutant diffusion model calculation module and a pollutant diffusion simulation analysis model; Data acquisition module: used to acquire meteorological data and perform preprocessing; Gaussian diffusion model storage module: used to store the three-dimensional Gaussian diffusion model that changes with time; Pollutant diffusion model calculation module: calculates precipitation factors based on the meteorological data, and adds the precipitation factors to the three-dimensional Gaussian diffusion model to obtain a precipitation environment pollutant diffusion model; Pollutant diffusion simulation analysis model: Using the precipitation environment pollutant diffusion model, diffusion simulation and result visualization are performed to generate the atmospheric pollutant diffusion distribution map over time in a precipitation environment.

7. The precipitation environment pollutant diffusion analysis system based on Gaussian diffusion model according to claim 6 is characterized in that: Three-dimensional Gaussian diffusion model with time: Where C is the concentration of pollutants at any point in space (x, y, z); σ x , σ y , σ z is the diffusion parameter in the x, y, and z directions; u is the average wind speed; x is the distance from the spatial point to the source along the downwind direction; y is the distance from the spatial point to the source along the direction perpendicular to the wind direction; z is the height of the spatial point; H is the pollutant release height, and q is the source strength.

8. The precipitation environment pollutant diffusion analysis system based on Gaussian diffusion model according to claim 6 is characterized in that: The precipitation factor is: β＝1.2×10 -5 I 0.5 Among them, I is the rainfall intensity, β is the adsorption coefficient, u refers to the average wind speed of the environment, and x is the distance from the spatial point to the source along the downwind direction.

9. The precipitation environment pollutant diffusion analysis system based on Gaussian diffusion model according to claim 7 is characterized in that: The precipitation environmental pollutant diffusion model is: Among them, Q(x)=q*R(x).

10. The precipitation environment pollutant diffusion analysis system based on Gaussian diffusion model according to claim 6 is characterized in that: The data acquisition module is used to determine the simulation area, set the grid resolution for grid division and initialize the grid data; set the time step, use the precipitation environment pollutant diffusion model to calculate the concentration, organize the pollutant concentration data at each time step calculated by the Gaussian diffusion model into a unified format, and use contour maps to display the spatial distribution of pollutant concentrations.

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