Visualization method and system for unorganized carbon dioxide diffusion in industrial park

Abstract

The invention discloses a visualization method and system for unorganized carbon dioxide diffusion in an industrial park. The method comprises the following steps: acquiring real-time meteorological data in an industrial park; according to the meteorological data and the actual emission condition of the emission source, diffusion parameter coefficients are determined, and an unorganized carbon dioxide diffusion model of the industrial park is constructed; superposing the carbon dioxide concentrations of the plurality of point sources, and establishing an industrial park unorganized multi-point source Gaussian diffusion model based on the industrial park unorganized carbon dioxide diffusion model; and optimizing a Gaussian diffusion model, and converting the coordinate system and the longitude and latitude to realize carbon dioxide concentration diffusion visualization. According to the method, the accuracy and comprehensiveness of carbon dioxide diffusion simulation are improved, the spatial distribution of the carbon dioxide concentration is more intuitive, and monitoring and management are facilitated, so that the scientificity and effectiveness of carbon dioxide emission monitoring and management in the industrial park are remarkably improved, and effective technical support is provided for environmental protection.

Description

Technical Field

[0001] The invention relates to the technical field of underground positioning of subway trains, and in particular to a visualization method and system for unorganized carbon dioxide diffusion in an industrial park. Background Art

[0002] At present, the energy industry is developing rapidly, carbon dioxide emissions are increasing, and the carbon dioxide content in the air has increased significantly, leading to climate warming and a prominent greenhouse effect. Carbon emission reduction is imminent, and carbon emission reduction depends on the data obtained by the carbon dioxide monitoring system. In actual projects, some industrial parks do not have centralized emission sources and source strength values, making it difficult to visualize the carbon dioxide concentration of the entire industrial park; moreover, most of the current models only consider carbon emissions from a single gas source, ignoring carbon emissions from multiple gas sources, and cannot effectively provide a scientific basis for environmental protection and pollution control in industrial parks.

[0003] Therefore, how to realize the visualization of the diffusion of unorganized carbon dioxide concentration in industrial parks and improve the scientificity and effectiveness of carbon dioxide emission monitoring and management in industrial parks is a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0004] In view of this, the present invention provides a method and system for visualizing the diffusion of unorganized carbon dioxide in an industrial park that can solve the above technical problems. By collecting real-time meteorological data of the industrial park, combining the actual emission conditions of each emission source, determining the diffusion parameters, and converting the coordinate system and longitude and latitude, the diffusion concentration of unorganized carbon dioxide emissions in the industrial park is obtained. The present invention not only improves the accuracy and comprehensiveness of carbon dioxide diffusion simulation, but also makes the spatial distribution of carbon dioxide concentration more intuitive and convenient for monitoring and management, thereby significantly improving the scientificity and effectiveness of carbon dioxide emission monitoring and management in industrial parks, and providing effective technical support for environmental protection.

[0005] To achieve the above object, the technical solution adopted by the present invention is:

[0006] In a first aspect, an embodiment of the present invention provides a method for visualizing unorganized carbon dioxide diffusion in an industrial park, the method comprising the following steps:

[0007] S1. Obtain real-time meteorological data in the industrial park;

[0008] S2. Determine the diffusion parameter coefficient based on meteorological data and the actual emission conditions of emission sources, and construct an unorganized carbon dioxide diffusion model for industrial parks;

[0009] S3. Superimpose the carbon dioxide concentrations of multiple point sources and establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks;

[0010] S4. Optimize the Gaussian diffusion model, transform the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

[0011] Furthermore, in S1, the real-time meteorological data includes data on wind speed, wind direction, atmospheric stability, temperature and humidity.

[0012] Furthermore, the atmospheric stability is divided into six categories, A to F, according to the Pasquier classification, wherein: A, B, and C stability represent unstable atmospheric states, D stability represents neutral atmospheric states, and E and F stability represent stable atmospheric states.

[0013] Furthermore, in S2, an unorganized carbon dioxide diffusion model for industrial parks is constructed, and the specific process includes:

[0014] 1) According to the atmospheric stability level and source distance, based on the Pasqukll-Gifford diffusion parameter curve, the horizontal diffusion coefficient σ is calculated using the empirical curve method. y and the vertical diffusion coefficient σ z Calculate, the calculation formula is:

[0015] σ y =a y X 0.9031

[0016]

[0017] In the formula, a y 、a z 、b z 、c z is the constant value of the diffusion coefficient calculated based on the empirical curve, and its value is related to the atmospheric stability and the distance from the release point; X represents the distance from the release point;

[0018] 2) Define the directions of the x, y and z axes in the Cartesian coordinate system. The concentration value detected by the carbon dioxide monitoring device at a certain point (x0, y0, z0) is C0. Based on the Gaussian diffusion model, the diffusion model of unorganized carbon dioxide emissions is obtained as follows:

[0019] ①Under ideal conditions of no wind or light wind:

[0020] The concentration value of a point in the industrial park space is:

[0021]

[0022] In the formula, C(x,y,z) is the concentration value at the position (x,y,z) of the industrial park, C0 is the initial concentration value, x0, y0, z0 are the coordinate positions of a certain point in the coordinate system of the monitoring device in space, σ xis the diffusion coefficient of the wind direction on the x-axis, σ y is the diffusion coefficient of the wind direction on the y axis, σ z is the diffusion coefficient of the wind direction along the z axis;

[0023] ② In windy conditions:

[0024] The model is modified by considering the wind speed, and the diffusion model expression is:

[0025]

[0026] Where u, v, and w are the components of wind speed on the x, y, and z axes, respectively, and σ is the standard deviation of wind speed;

[0027] The calculation formula for wind speed standard deviation is:

[0028]

[0029] Where v is each wind speed observation value, is the average wind speed, and n is the number of observations.

[0030] Furthermore, in S3, the establishment process of the unorganized multi-point source Gaussian diffusion model in the industrial park includes:

[0031] The pollutant concentration in the entire area is calculated by linear superposition of the single point source diffusion model: For a single unorganized source, the Gaussian diffusion model expression is:

[0032]

[0033] In the formula, C i (x, y, z) is the concentration value of the i-th point source in the industrial park; C i is the initial concentration value of the i-th point source; u i 、v i 、w i is the wind speed component of the ith point source on the x, y, and z axes; i ,y i 、z i represents the position of the i-th point source;

[0034] For multiple point sources in the area, the total concentration C at any point is calculated by summing the contributions of all point sources:

[0035]

[0036] C total(x,y,z) =C1(x,y,z)+C2(x,y,z)+...+C n (x,y,z)

[0037] In the formula, C total(x,y,z)represents the total concentration value of discrete points in the industrial park, C n (x, y, z) is the concentration contribution value of the nth point source at the discrete point.

[0038] Furthermore, in S4, the coordinate system of the unorganized carbon dioxide diffusion model is determined, and the longitude and latitude conversion is performed based on the coordinate system. The unorganized emissions are simulated using the converted model to obtain the concentration distribution and realize the visualization of the carbon dioxide concentration in the industrial park. The specific process includes:

[0039] a. Perform coordinate system transformation on the unorganized carbon dioxide diffusion model. The coordinate system of the unorganized carbon dioxide diffusion model is constructed based on the Cartesian coordinate system. The X-axis direction is the horizontal direction, from left to right; the Y-axis is the vertical direction, from bottom to top; and the Z-axis is the third direction perpendicular to the horizontal plane, from back to front;

[0040] b. To convert the longitude and latitude of the unorganized carbon dioxide diffusion model, it is necessary to determine the origin conversion from the local coordinate system to the global coordinate system and determine the longitude and latitude corresponding to the origin of the local coordinate system; the conversion formula is:

[0041] Lat=lat Origin +Y local / m lat

[0042] Lon=lon Origin +X local / m lon

[0043] In the formula, Lat and Lon represent the longitude and latitude coordinates respectively; lat Origin is the latitude of the local coordinate origin; lon Origin is the longitude of the local coordinate origin; Y local is the ordinate in the local plane coordinate system; X local is the horizontal coordinate in the local plane coordinate system; m lat is the distance corresponding to each degree of latitude; m lon is the distance corresponding to each degree of longitude;

[0044] c. Use the coordinate system and longitude and latitude as the simulation input conditions to simulate the unorganized emissions, obtain the concentration distribution of unorganized single point sources and multi-point sources, and realize the visualization of carbon dioxide concentration in industrial parks.

[0045] In a second aspect, an embodiment of the present invention further provides a visualization system for unorganized carbon dioxide diffusion in an industrial park, which uses the above-mentioned visualization method for unorganized carbon dioxide diffusion in an industrial park to realize the visualization of unorganized carbon dioxide diffusion in an industrial park, and the system includes:

[0046] Data acquisition module, used to obtain real-time meteorological data in the industrial park;

[0047] The model building module is used to determine the diffusion parameter coefficient based on meteorological data and the actual emission conditions of the emission sources, and to build an unorganized carbon dioxide diffusion model for industrial parks; and to superimpose the carbon dioxide concentrations of multiple point sources, and to establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks;

[0048] The visualization module is used to optimize and analyze the Gaussian diffusion model, convert the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

[0049] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement the above-mentioned method for visualizing the diffusion of unorganized carbon dioxide in an industrial park.

[0050] Compared with the prior art, the present invention has at least the following beneficial effects:

[0051] The present invention proposes a visualization method and system for the diffusion of unorganized carbon dioxide in industrial parks. By collecting real-time meteorological data of industrial parks, combined with the actual emission conditions of each emission source, the diffusion parameters are determined, and the coordinate system and longitude and latitude are converted to obtain the diffusion concentration of unorganized carbon dioxide emissions in industrial parks, and visualize them. The present invention not only improves the accuracy and comprehensiveness of carbon dioxide diffusion simulation, but also makes the spatial distribution of carbon dioxide concentration more intuitive and convenient for monitoring and management, thereby significantly improving the scientificity and effectiveness of carbon dioxide emission monitoring and management in industrial parks, and providing effective technical support for environmental protection.

[0052] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0053] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0055] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0056] Figure 1 A schematic flow chart of a method for visualizing unorganized carbon dioxide diffusion in an industrial park provided in an embodiment of the present invention.

[0057] Figure 2 A schematic diagram of coordinate transformation provided by an embodiment of the present invention.

[0058] Figure 3 A schematic diagram of a single-source unorganized carbon dioxide diffusion simulation provided in an embodiment of the present invention.

[0059] Figure 4 A schematic diagram of multi-source unorganized carbon dioxide diffusion simulation provided by an embodiment of the present invention.

[0060] Figure 5 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0062] In the description of the present invention, it should be noted that: in some processes described in the specification and drawings of this application, multiple operations appearing in a specific order are included, but it should be clearly understood that these operations may not be performed in the order in which they appear in this document or may be performed in parallel. In addition, various serial numbers are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0063] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] See also Figure 1 As shown, the present invention provides a method for visualizing unorganized carbon dioxide diffusion in an industrial park, and the method mainly includes the following steps:

[0065] 1. Obtain real-time meteorological data in the industrial park;

[0066] 2. According to the meteorological data and the actual emission situation of the emission source, the diffusion parameter coefficient is determined, and the unorganized carbon dioxide diffusion model (single point source diffusion model) of the industrial park is constructed;

[0067] 3. Superimpose the carbon dioxide concentrations of multiple point sources and establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks;

[0068] 4. Optimize and analyze the Gaussian diffusion model, convert the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

[0069] The specific implementation mode and working principle of the method of the present invention are described in detail below:

[0070] Step 1: Obtain real-time meteorological data within the industrial park, including wind speed, wind direction, atmospheric stability, temperature and humidity data.

[0071] In this embodiment, the specific implementation method for the above step 1 is:

[0072] ① Install sensors at appropriate locations in the industrial park to collect real-time meteorological data such as wind speed, wind direction, temperature and humidity in the area.

[0073] ② Calculate atmospheric stability. Atmospheric stability is one of the main reasons affecting the diffusion of carbon dioxide. Atmospheric stability can be divided into six categories of AF according to the Pasquier classification method. It can quickly evaluate atmospheric stability and provide a more intuitive stability classification. Combining it with the Gaussian diffusion model can improve the accuracy of model prediction. Among them, A, B, and C stability are unstable atmospheric states, D stability is a neutral atmospheric state, and E and F stability are stable atmospheric states. The selection of atmospheric stability is related to factors such as wind speed, solar radiation, and total cloud.

[0074] Step 2: Determine the diffusion parameter coefficient based on meteorological data and the actual emissions from emission sources, and construct an unorganized carbon dioxide diffusion model for the industrial park.

[0075] In this embodiment, the specific implementation method for the above step 2 is:

[0076] ①. Determine the atmospheric diffusion parameters according to the real-time meteorological conditions obtained in step 1. According to the atmospheric stability level and the source distance, the horizontal diffusion coefficient σ is calculated using the empirical curve method based on the Pasqukll-Gifford diffusion parameter curve. y and the vertical diffusion coefficient σ z Make an estimate as follows:

[0077] σ y =a y X 0.9031

[0078]

[0079] Where: a y 、a z 、b z 、c z It is the empirical value estimated for the corresponding curve, and its value is related to the atmospheric stability and the distance from the release point.

[0080] ② Define the directions of the x, y, and z axes in the Cartesian coordinate system. It is known that the concentration value detected by the carbon dioxide monitoring device at a certain point (x0, y0, z0) is C0. Based on the Gaussian diffusion model, the diffusion model of unorganized carbon dioxide emissions is obtained:

[0081] (1) Under ideal conditions of no wind or light wind:

[0082] The concentration value of a point in the industrial park space is:

[0083]

[0084] Where: C(x,y,z) is the concentration value (g / m 3 ), C0 is the initial concentration value, that is, the concentration collected by the monitoring device (g / m 3 ), x0, y0, z0 are the coordinate positions of the monitoring device in the coordinate system in space, σ x is the diffusion coefficient of the wind direction on the x-axis (m), σ y is the diffusion coefficient of the wind direction on the y axis (m), σ z is the diffusion coefficient of the wind direction along the z axis (m).

[0085] (2) In windy conditions:

[0086] Under actual meteorological conditions, the model is modified by considering the wind speed. The diffusion model expression is as follows:

[0087]

[0088] Where: u, v, w are the components of wind speed on the x, y, and z axes (m / s), and σ is the standard deviation of wind speed.

[0089] The standard deviation of wind speed is:

[0090]

[0091] Where: v is each wind speed observation value (m / s), is the average wind speed (m / s), n is the number of observations, generally not less than 30 times.

[0092] Step 3: Based on the carbon monitoring device, the carbon dioxide concentrations of multiple point sources are superimposed to obtain the Gaussian diffusion model expression of unorganized multi-point sources in the industrial park.

[0093] In this embodiment, the specific implementation method for the above step 3 is:

[0094] The pollutant concentration in the entire area is approximately calculated by linear superposition of the single-point source diffusion model, that is, at each location, the concentration value corresponding to each source is added to obtain the total concentration field.

[0095] For a single unorganized source, the Gaussian diffusion model expression is:

[0096]

[0097] Where: C i (x,y,z) is the concentration value of the i-th point source in the industrial park (g / m 3 );C i is the initial concentration value of the ith point source, i.e., the concentration collected by the monitoring device (g / m 3 );u i 、v i 、w i is the wind speed at the location of the ith point source (m / s); x i ,y i 、z i represents the position of the i-th point source.

[0098] For multiple point sources in an area, the total concentration C at any point can be calculated by adding up the contributions of all point sources:

[0099]

[0100] C total(x,y,z) =C1(x,y,z)+C2(x,y,z)+...+C n (x,y,z)

[0101] Where: C total(x,y,z) is the total concentration value of discrete points in the industrial park (g / m 3 ), C1(x,y,z), C2(x,y,z), C n (x, y, z) is the concentration contribution of each point source at a discrete point (g / m 3 ).

[0102] For the actual superposition and summation of multiple point sources, different sources are in different atmospheric conditions, and the diffusion coefficient of each source needs to be calculated, see step 2.

[0103] Step 4: Optimize and analyze the Gaussian diffusion model (convert the coordinate system and longitude and latitude) to visualize the diffusion of carbon dioxide concentration.

[0104] In this embodiment, the specific implementation method for the above step 4 is as follows:

[0105] ①. Convert the coordinate system of the unorganized carbon dioxide diffusion model. The coordinate system of the unorganized carbon dioxide diffusion model is constructed based on the Cartesian coordinate system. The X-axis is horizontal, from left to right; the Y-axis is vertical, from bottom to top; the Z-axis is the third direction perpendicular to the horizontal plane, from back to front (the unorganized carbon dioxide diffusion model here is different from the original Gaussian diffusion coordinate system. The original Gaussian diffusion coordinate system is that X is the downwind direction, the Y-axis is perpendicular to the wind direction and horizontal, and its positive direction points to the left of the X-axis, and the Z-axis is perpendicular to the ground and upward), such as Figure 2 As shown, the coordinate system XOY represents the Gaussian diffusion coordinate system, the coordinate system EDN represents the plane coordinate system, and θ is the angle between the DE axis and the OX axis and is less than 90°.

[0106] ② To convert the longitude and latitude of the unorganized carbon dioxide model, it is necessary to determine the origin conversion from the local coordinate system to the global coordinate system, and determine the longitude and latitude corresponding to the origin of the local coordinate system. Specifically:

[0107] The number of meters per degree in longitude is calculated using the average value of latitude. In general, each degree in latitude is approximately equal to 111.32 kilometers, and the number of meters per degree in longitude varies with latitude, which can be calculated using the cosine function. By dividing the known local coordinate value by the number of meters per degree and adding the longitude and latitude of the origin, the local coordinate can be converted to longitude and latitude coordinates, realizing the mutual conversion between the local coordinate system and the global coordinate system. The conversion formula is as follows:

[0108] Lat=lat Origin +Y local / m lat

[0109] Lon=lon Origin +X local / m lon

[0110] Where: Lat, Lon represent the longitude and latitude coordinates respectively; lat Origin is the latitude of the local coordinate origin; lon Origin is the longitude of the local coordinate origin; Y local is the ordinate in the local plane coordinate system; X local is the horizontal coordinate in the local plane coordinate system; m lat is the distance per degree of latitude, m lat =111320m;m lonis the distance per degree of longitude, m lon =m lat ×cos(lat Origin ).

[0111] Finally, the coordinate system and longitude and latitude are used as the simulation input conditions to simulate the fugitive emissions, see Figure 3 and Figure 4 As shown, the concentration distribution of unorganized single point sources and multiple point sources is obtained, realizing the visualization of carbon dioxide concentration in the industrial park.

[0112] From the description of the above embodiments, those skilled in the art can know that the present invention proposes a method for visualizing the diffusion of unorganized carbon dioxide in industrial parks. It is a method for monitoring the unorganized carbon dioxide emissions in industrial parks using a Gaussian diffusion model based on a carbon dioxide monitoring device, and monitors the concentration diffusion of unorganized carbon dioxide in industrial parks to achieve visualization of the diffusion of unorganized carbon dioxide concentration in industrial parks. The present invention collects real-time meteorological data from industrial parks, combines the actual emissions of each emission source, determines diffusion parameters, and converts the coordinate system and longitude and latitude to obtain the diffusion concentration of unorganized carbon dioxide emissions in industrial parks. This method not only improves the accuracy and comprehensiveness of carbon dioxide diffusion simulation, but also makes the spatial distribution of carbon dioxide concentration more intuitive and easy to monitor and manage, thereby significantly improving the scientificity and effectiveness of carbon dioxide emission monitoring and management in industrial parks, and providing important technical support for environmental protection.

[0113] Furthermore, the present invention also provides a visualization system for unorganized carbon dioxide diffusion in an industrial park, which is applied to a visualization method for unorganized carbon dioxide diffusion in an industrial park described in the above embodiment to realize visualization of unorganized carbon dioxide diffusion in an industrial park, and the system includes:

[0114] Data acquisition module, used to obtain real-time meteorological data in the industrial park;

[0115] The model building module is used to determine the diffusion parameter coefficient based on meteorological data and the actual emission conditions of the emission sources, and to build an unorganized carbon dioxide diffusion model for industrial parks; and to superimpose the carbon dioxide concentrations of multiple point sources, and to establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks;

[0116] The visualization module is used to optimize and analyze the Gaussian diffusion model, convert the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

[0117] An embodiment of the present invention provides a visualization system for unorganized carbon dioxide diffusion in an industrial park, and its implementation principle and technical effects are the same as those of the aforementioned method embodiment. For the sake of brief description, parts not mentioned in this embodiment can be referred to the corresponding contents in the aforementioned method embodiment, which will not be repeated here.

[0118] Also, see Figure 5 As shown, an embodiment of the present invention further provides an electronic device, which may include a processor 10, a memory 11, a communication bus 12, and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, and the processor executes the computer program to implement a method for visualizing the diffusion of unorganized carbon dioxide in an industrial park in the above method embodiment.

[0119] The processor 10 may be composed of an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits with the same or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and combinations of various control chips. The processor 10 is the control core of the electronic device, and uses various interfaces and lines to connect various components of the entire electronic device, and executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory 11, and calling data stored in the memory 11.

[0120] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, electronic devices or computer program products, etc. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0121] It should be noted that the word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The present invention can be implemented by means of hardware comprising a number of different components and by means of a suitably programmed computer. The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other.

[0122] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for visualizing unorganized carbon dioxide diffusion in an industrial park, characterized in that: The method comprises the following steps: S1. Obtain real-time meteorological data in the industrial park; S2. Determine the diffusion parameter coefficient based on meteorological data and the actual emission conditions of emission sources, and construct an unorganized carbon dioxide diffusion model for industrial parks; S3. Superimpose the carbon dioxide concentrations of multiple point sources and establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks; S4. Optimize the Gaussian diffusion model, transform the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

2. The method for visualizing unorganized carbon dioxide diffusion in an industrial park according to claim 1, characterized in that: In S1, the real-time meteorological data includes data on wind speed, wind direction, atmospheric stability, temperature and humidity.

3. The method for visualizing unorganized carbon dioxide diffusion in an industrial park according to claim 2, characterized in that: The atmospheric stability is divided into six categories, A to F, according to the Pasquier classification system, wherein: A, B, and C stability represent unstable atmospheric states, D stability represents neutral atmospheric states, and E and F stability represent stable atmospheric states.

4. The method for visualizing unorganized carbon dioxide diffusion in an industrial park according to claim 3, characterized in that: In S2, an unorganized carbon dioxide diffusion model for industrial parks is constructed. The specific process includes: 1) According to the atmospheric stability level and source distance, based on the Pasqukll-Gifford diffusion parameter curve, the horizontal diffusion coefficient σ is calculated using the empirical curve method. y and the vertical diffusion coefficient σ z Calculate, the calculation formula is: s y =a y X 0.9031 In the formula, a y 、a z 、b z 、c z is the constant value of the diffusion coefficient calculated based on the empirical curve, and its value is related to the atmospheric stability and the distance from the release point; X represents the distance from the release point; 2) Define the directions of the x, y, and z axes in the Cartesian coordinate system. The concentration value detected by the carbon dioxide monitoring device at a certain point (x0, y0, z0) is C0. Based on the Gaussian diffusion model, the diffusion model of unorganized carbon dioxide emissions is obtained as follows: ①Under ideal conditions of no wind or light wind: The concentration value of a point in the industrial park space is: In the formula, C(x,y,z) is the concentration value at the position (x,y,z) of the industrial park, C0 is the initial concentration value, x0, y0, z0 are the coordinate positions of a certain point in the coordinate system of the monitoring device in space, σ x is the diffusion coefficient of the wind direction on the x-axis, σ y is the diffusion coefficient of the wind direction on the y axis, σ z is the diffusion coefficient of the wind direction along the z axis; ② In windy conditions: The model is modified by considering the wind speed, and the diffusion model expression is: Where u, v, and w are the components of wind speed on the x, y, and z axes, respectively, and σ is the standard deviation of wind speed; The calculation formula for wind speed standard deviation is: Where v is each wind speed observation value, is the average wind speed, and n is the number of observations.

5. The method for visualizing unorganized carbon dioxide diffusion in an industrial park according to claim 4, characterized in that: In S3, the process of establishing the Gaussian diffusion model of unorganized multi-point sources in industrial parks includes: The pollutant concentration in the entire area is calculated by linear superposition of the single point source diffusion model: For a single unorganized source, the Gaussian diffusion model expression is: In the formula, C i (x, y, z) is the concentration value of the i-th point source in the industrial park; C i is the initial concentration value of the i-th point source; u i 、v i 、w i is the wind speed component of the ith point source on the x, y, and z axes; i ,y i 、z i represents the position of the i-th point source; For multiple point sources in the area, the total concentration C at any point is calculated by summing the contributions of all point sources: C total(x,y,z) =C1(x,y,z)+C2(x,y,z)+...+C n (x,y,z) In the formula, C total(x,y,z) represents the total concentration value of discrete points in the industrial park, C n (x, y, z) is the concentration contribution value of the nth point source at the discrete point.

6. The method for visualizing unorganized carbon dioxide diffusion in an industrial park according to claim 5, characterized in that: In S4, the coordinate system of the unorganized carbon dioxide diffusion model is determined, and the longitude and latitude conversion is performed based on the coordinate system. The converted model is used to simulate the unorganized emissions to obtain the concentration distribution and realize the visualization of the carbon dioxide concentration in the industrial park. The specific process includes: a. Perform coordinate system transformation on the unorganized carbon dioxide diffusion model. The coordinate system of the unorganized carbon dioxide diffusion model is constructed based on the Cartesian coordinate system. The X-axis direction is the horizontal direction, from left to right; the Y-axis is the vertical direction, from bottom to top; and the Z-axis is the third direction perpendicular to the horizontal plane, from back to front; b. To convert the longitude and latitude of the unorganized carbon dioxide diffusion model, it is necessary to determine the origin conversion from the local coordinate system to the global coordinate system and determine the longitude and latitude corresponding to the origin of the local coordinate system; the conversion formula is: Years=years Origin +Y local / m lat Lon=lon Origin +X local / m lon In the formula, Lat and Lon represent the longitude and latitude coordinates respectively; lat Origin is the latitude of the local coordinate origin; lon Origin is the longitude of the local coordinate origin; Y local is the ordinate in the local plane coordinate system; X local is the horizontal coordinate in the local plane coordinate system; m lat is the distance corresponding to each degree of latitude; m lon is the distance corresponding to each degree of longitude; c. Use the coordinate system and longitude and latitude as the simulation input conditions to simulate the unorganized emissions, obtain the concentration distribution of unorganized single point sources and multi-point sources, and realize the visualization of carbon dioxide concentration in industrial parks.

7. A visualization system for unorganized carbon dioxide diffusion in industrial parks, characterized in that: The method for visualizing the unorganized carbon dioxide diffusion in an industrial park as claimed in any one of claims 1 to 6 is applied to realize the visualization of the unorganized carbon dioxide diffusion in the industrial park, and the system comprises: Data acquisition module, used to obtain real-time meteorological data in the industrial park; The model building module is used to determine the diffusion parameter coefficient based on meteorological data and the actual emission conditions of the emission sources, and to build an unorganized carbon dioxide diffusion model for industrial parks; and to superimpose the carbon dioxide concentrations of multiple point sources, and to establish an unorganized multi-point source Gaussian diffusion model for industrial parks based on the unorganized carbon dioxide diffusion model for industrial parks; The visualization module is used to optimize and analyze the Gaussian diffusion model, convert the coordinate system and longitude and latitude, and realize the visualization of carbon dioxide concentration diffusion.

8. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores machine executable instructions that can be executed by the processor, and the processor executes the machine executable instructions to implement a visualization method for unorganized carbon dioxide diffusion in an industrial park that can be executed as described in any one of claims 1-6.

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