Complex environment aerosol pollutant diffusion simulation method and device

Abstract

The invention provides a complex environment aerosol pollutant diffusion simulation method and device. The method comprises the following steps: constructing a WRF-CFD data pipeline; the configuration and the data setting of the WRF-CFD data pipeline are initialized; the WRF. Conf configuration information is analyzed and filled, and a WRF calculation result is generated; uniformly calculating content field and wind field data of condensed moisture in the air based on a WRF calculation result; a WRF calculation result is converted to a CFD calculation grid through a cubic spline interpolation method, and a CFD case is obtained; and initializing a CFD case, and submitting the CFD case to a computing node to obtain an aerosol pollutant diffusion simulation result. According to the method, the content field of the condensed moisture in the air is uniformly calculated, and the cleaning source item is introduced into the aerosol diffusion control equation, so that the influence of different meteorological conditions on aerosol diffusion is quantitatively represented, and the application range and the application scene are remarkably widened.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of fluid mechanics simulation, in particular to a complex environment aerosol pollutant diffusion simulation method and device. BACKGROUND

[0002] Fine aerosol diffusion state simulation under complex environment has important application value in many fields such as environmental protection and emergency response, which can provide accurate aerosol pollutant diffusion prediction for decision makers, so as to better assess and manage potential risks. Traditional methods include trapezoidal method, Bernoulli curve function, Lagrangian model and Gaussian plume model, etc. However, it is difficult to capture the influence of building groups and complex terrain on wind field and pollutant concentration distribution.

[0003] In the prior art, CN105403664B proposes a point source evaluation method based on WRF-CHEM. The method uses a 4-layer nested grid, and the innermost grid resolution is only 3km. Buildings are not explicitly modeled (represented by urban canopy parameterization), which cannot effectively evaluate the diffusion range of pollutants in urban environment. CN119294280A proposes a pollutant diffusion simulation method based on CFD, which can use a three-dimensional city model to analyze the influence of urban buildings on pollutant aerosol diffusion. However, this method only uses CFD method for calculation, without considering the climate background field, which makes it difficult to truly fit the actual situation.

[0004] At the same time, the existing technology does not pay enough attention to the complex weather conditions, and the coupling method is too single, only supporting the input of single wind field data, which cannot effectively reflect the complex weather conditions. Moreover, the precision of simulating aerosol diffusion in the prior art has significant limitations, and various meteorological factors cannot be fully considered to affect the diffusion and deposition of pollutant aerosols.

[0005] On the other hand, since meteorological model (WRF) is mainly used for mesoscale simulation, and fluid mechanics calculation (CFD) is applied to local flow simulation of smaller scale, there is a significant difference between the two, which requires measures to effectively bridge this difference in data processing to ensure the accuracy and operability of the simulation results. However, the existing technology does not fully consider the difference in simulation time scale between WRF and CFD, which may lead to low calculation efficiency, and may also affect the accuracy and real-time performance of the simulation results, especially in application scenarios that require rapid response, the efficiency problem is particularly prominent. SUMMARY

[0006] In view of the defects in the prior art, the present application provides a complex environment aerosol pollutant diffusion simulation method and device.

[0007] To achieve the above purpose, the technical scheme adopted by the present application is as follows: In one aspect, the present application provides a complex environment aerosol pollutant diffusion simulation method, comprising the following steps: Building a WRF-CFD data pipeline; Initializing the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf; Parsing WRF.conf configuration information and filling, generating data and configuration files required for WRF calculation, generating WRF calculation results, and converting the calculation results into netCDF4 format; Based on the WRF calculation results, the content field of the condensed water in the air and the wind field data are uniformly calculated; and the content field of the condensed water in the air is taken as the parameter of the removal coefficient in the aerosol diffusion control equation in CFD, the wind field data is taken as the boundary condition of the velocity field in CFD, and the WRF calculation results are converted to the calculation grid of CFD through the cubic spline interpolation method to obtain the CFD case; the aerosol diffusion control equation includes a cleaning source term for representing the influence of different meteorological conditions on aerosol diffusion; Initializing the CFD case and submitting it to the calculation node to obtain the aerosol pollutant diffusion simulation results.

[0008] Further, initializing the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf, comprising: Download and store the underlying surface and meteorological data to the predefined directory to complete the data setting initialization of the WRF-CFD data pipeline; Complete the WRF controllable parameter configuration and WRF fixed parameter configuration through WRF.conf; Complete the CFD controllable parameter configuration and CFD fixed parameter and solver configuration through CFD.conf.

[0009] Further, the CFD fixed parameters include high-precision urban three-dimensional geometric models, solver control parameters, and grid parameters.

[0010] Further, the solver is a transient scalar solver using large eddy simulation model.

[0011] Further, parsing WRF.conf configuration information and filling, generating data and configuration files required for WRF calculation, generating WRF calculation results, and converting the calculation results into netCDF4 format, comprising: Parsing WRF.conf configuration, filling the nested grid settings and simulation time in WRF.conf configuration in the corresponding namelist; Based on the filled WRF.conf configuration, the program calls the data and configuration files required for WRF calculation, and pre-processes the data through conversion and interpolation; Based on the WRF calculation configuration file, the pre-processed data is submitted to the computing node for operation to generate the WRF calculation result; The WRF calculation result is losslessly converted into the netCFD4 format.

[0012] Further, the content field of the condensed water in the air is calculated according to the following formula: ; ; ; Wherein, is the content field of the condensed water in the air; is the cloud and fog related variable; is the precipitation related variable; is the snow related variable; is the air density; is the total condensed water mixing ratio at each grid point; is the air pressure; is the temperature.

[0013] Further, the wind field data includes wind speed and wind direction; The wind speed is calculated according to the following formula: ; The wind direction is calculated according to the following formula: ; Wherein, is the wind speed; is the wind direction; is the component of the wind speed in the east-west direction; is the component of the wind speed in the north-south direction.

[0014] Further, the aerosol diffusion control equation is: ; Wherein, is the aerosol concentration; is the time; is the gradient operator; is the wind speed vector; is the diffusion coefficient; is the source term of the aerosol; is the aerosol removal coefficient.

[0015] Further, it also includes: After the configuration and data setting initialization of the WRF-CFD data pipeline, parameterization parallel configuration is carried out; A plurality of CFD case folders are generated through the parameterization parallel configuration to realize parallel simulation of the CFD case.

[0016] In one aspect, the present application provides a complex environment aerosol pollutant diffusion simulation device, comprising: The first module is configured to build a WRF-CFD data pipeline; The second module is configured to initialize the configuration and data setting of the WRF-CFD data pipeline through WRF.conf and CFD.conf; The third module is configured to parse the WRF.conf configuration information and fill it in, generate the data and configuration file required for WRF calculation, generate the WRF calculation result, and convert the calculation result into a netCDF4 format; The fourth module is configured to uniformly calculate the content field of the condensed water in the air and the wind field data based on the WRF calculation result; take the content field of the condensed water in the air as a parameter of the removal coefficient in the aerosol diffusion control equation in the CFD, take the wind field data as a boundary condition of the velocity field in the CFD, convert the WRF calculation result to the calculation grid of the CFD through a cubic spline interpolation method, and obtain a CFD case; the aerosol diffusion control equation contains a cleaning source term for representing the influence of different meteorological conditions on the aerosol diffusion; The fifth module is configured to initialize the CFD case and submit it to a calculation node to obtain an aerosol pollutant diffusion simulation result.

[0017] Compared with the prior art, the present application has the beneficial technical effects that: The present application provides a complex environment aerosol pollutant diffusion simulation method and device, which uniformly calculates the content field of the condensed water in the air, introduces a cleaning source term into the aerosol diffusion control equation, and quantitatively represents the influence of different meteorological conditions on the aerosol diffusion, thereby significantly widening the application range and application scenarios of the present application; at the same time, the present application realizes high-quality data transfer from the mesoscale WRF calculation result to the microscale CFD model through a cubic spline interpolation method.

[0018] The WRF-CFD data pipeline built by the present application eliminates a large amount of manual intervention environment in the traditional method through a standardized configuration file management and a template-based case generation mechanism, and greatly improves the simulation calculation efficiency and repeatability. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only represent some of the embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on the drawings shown.

[0020] Figure 1 The flow chart of the complex environment aerosol pollutant diffusion simulation method provided by an embodiment; Figure 2 The schematic diagram of the three-dimensional simulated terrain provided by an embodiment; Figure 3 The schematic diagram of the aerosol pollutant diffusion concentration simulation result provided by an embodiment, wherein, Figure 3 (a) is the schematic diagram of the aerosol pollutant diffusion concentration simulation result at 600s of diffusion, Figure 3 (b) is the schematic diagram of the aerosol pollutant diffusion concentration simulation result at 1600s of diffusion. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only represent some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort fall within the protection scope of the present application.

[0022] Reference Figure 1 The complex environment aerosol pollutant diffusion simulation method provided by an embodiment comprises the following steps: Constructing a WRF-CFD data pipeline; Initializing the configuration and data setting of the WRF-CFD data pipeline through WRF.conf and CFD.conf; Parses the WRF.conf configuration information and fills it, generates the data and configuration files required for WRF calculation, generates the WRF calculation result, and converts the calculation result into netCDF4 format; Based on the WRF calculation result, the content field of the condensed water in the air and the wind field data are uniformly calculated; the content field of the condensed water in the air is taken as the parameter of the removal coefficient in the aerosol diffusion control equation in CFD, the wind field data are taken as the boundary condition of the velocity field in CFD, the WRF calculation result is converted to the calculation grid of CFD through the cubic spline interpolation method, and the CFD case is obtained; the aerosol diffusion control equation contains a cleaning source term, which is used to represent the influence of different meteorological conditions on the aerosol diffusion; The CFD case is initialized and submitted to the computing node to obtain the simulation result of the aerosol pollutant diffusion.

[0023] The WRF.conf and the CFD.conf are a configuration file of the WRF model and a configuration file of the CFD model, respectively.

[0024] By uniformly calculating the content field of the condensed water in the air and introducing a cleaning source term into the aerosol diffusion control equation, the influence of different meteorological conditions on the aerosol diffusion is quantitatively characterized, the application range and application scenarios of the present application are significantly widened, and meanwhile, the high-quality data transmission from the mesoscale WRF calculation result to the microscale CFD model is realized through the cubic spline interpolation method.

[0025] In an embodiment, the configuration and data setting of the WRF-CFD data pipeline are initialized through the WRF.conf and the CFD.conf, including: The underlying surface and meteorological data are downloaded and stored in a predefined directory to complete the data setting initialization of the WRF-CFD data pipeline; The WRF controllable parameter configuration and the WRF fixed parameter configuration are completed through the WRF.conf; The CFD controllable parameter configuration and the CFD fixed parameter and solver configuration are completed through the CFD.conf.

[0026] Specifically, the WRF controllable parameters include a simulation time period, a simulation time step, simulation geographic location information and a nested network setting. The WRF fixed parameters adopt a fixed parameterization scheme, including a New Thompson cloud microphysics scheme, a Kain-Fritsch set operation parameterization scheme, an RRTM long-wave radiation scheme, a Dudhia short-wave radiation scheme, a Revised MM5 Monin-Obukhov Scheme near-surface layer scheme, a Noah land surface scheme, a YSU planetary boundary layer scheme and a MYNN turbulence closure scheme. The CFD controllable parameters include an aerosol source position, a release rate, a parallel region setting, a simulation time length and a simulation step.

[0027] The CFD fixed parameters include a high-precision urban three-dimensional geometric model, solver control parameters (including a time step, a convergence criterion and a relaxation factor) and grid parameters (including a grid type, a size and a boundary layer encryption strategy). By keeping the high-precision urban three-dimensional geometric model, the solver control parameters and the grid parameters unchanged, the repeatability and the result consistency of the WRF calculation result bridging coupled to the CFD calculation grid are ensured.

[0028] The solver is a transient scalar solver using a large eddy simulation model. This solver can read hourly WRF calculation results and map them in real time. Because it uses a large eddy simulation model, it retains the adaptive external iteration mechanism of the transient cyclic solver, enabling efficient calculation of the spatiotemporal evolution of aerosol concentrations under varying meteorological and precipitation conditions in complex terrain environments.

[0029] In one embodiment, the WRF.conf configuration information is parsed and filled, the data and configuration files required for WRF calculation are generated, the WRF calculation results are generated, and the calculation results are converted into the netCDF4 format, including: Parse the WRF.conf configuration and fill the nested grid settings and simulation time in the corresponding namelist; Based on the filled WRF.conf configuration, the program is called to generate the data and configuration files required for WRF calculation, and the data is preprocessed by transformation and interpolation. Based on the WRF calculation configuration file, the preprocessed data is submitted to the computing node for operation to generate the WRF calculation results; Convert WRF calculation results to netCFD4 format without loss.

[0030] In this example, the WPS program is called to generate the data and configuration files required for WRF calculations. Ungrib.exe, geogrid.exe, and metgrid.exe are then run sequentially to perform data conversion and interpolation, completing data preprocessing to match the WRF model input requirements. Real.exe is called to generate the WRF calculation configuration file, submitting the preprocessed data to the compute nodes for computation and generating WRF calculation results. The ARWpost program is called to losslessly convert the WRF calculation results to the netCFD4 format and save them in the Results folder, facilitating the subsequent process of bridging the WRF calculation results to the CFD computational grid.

[0031] Before bridging the WRF calculation results to the CFD computational grid, the WRF calculation results are read from the Results folder through the netCFD4 interface. Since the temporal and spatial scales of WRF are significantly larger than those of CFD, only a single WRF run is required to meet the needs of subsequent aerosol pollutant dispersion simulations.

[0032] In one embodiment, the content field of condensable water in the air and the wind field data are uniformly calculated based on the WRF calculation results; the WRF calculation results include the horizontal wind speed component ( ), cloud-related variables ( ), precipitation-related variables ( ), snowfall-related variables ( , vertical wind speed component ( ), temperature and air pressure.

[0033] The content field of condensed water in the air is calculated according to the following formula: ; ; ; wherein, is the content field of condensed water in the air; is a cloud and fog related variable; is a precipitation related variable; is a snowfall related variable; is air density; is the total condensed water mixing ratio at each grid point; is air pressure; is temperature.

[0034] The content field of condensed water in the air reflects the important influence of different meteorological conditions (rain, snow, ice crystals, graupel, clouds and fog) in aerosol diffusion simulation.

[0035] The wind field data includes wind speed and wind direction; The wind speed is calculated according to the following formula: ; The wind direction is calculated according to the following formula: ; wherein, is the wind speed; is the wind direction; is the component of the wind speed in the east-west direction; is the component of the wind speed in the north-south direction. Since the vertical wind speed component ( ) is small, it has little effect on the overall aerosol diffusion level, and therefore is not considered.

[0036] The aerosol diffusion control equation is: ; wherein, is the aerosol concentration; is time; is the gradient operator; is the wind speed vector; is the diffusion coefficient; is the source term of the aerosol; is the aerosol removal coefficient.

[0037] By introducing the cleaning source term in the aerosol diffusion control equation , so as to characterize the influence of different meteorological conditions on the diffusion of aerosols. The WRF-CFD data pipeline configures different simulation conditions according to different meteorological conditions.

[0038] The CFD case is initialized and submitted to the computing node to obtain the simulation result of the diffusion of aerosol pollutants. The initialization of the CFD case specifically includes sequentially performing grid feature extraction, basic grid generation, parallel decomposition, adaptive grid refinement, grid reconstruction, and topology setting on the CFD case.

[0039] In a preferred embodiment, the complex environmental aerosol pollutant diffusion simulation method further comprises: After the configuration and data setting initialization of the WRF-CFD data pipeline, parameterized parallel configuration is performed. A plurality of CFD case folders are generated through parameterized parallel configuration to realize parallel simulation of the CFD cases.

[0040] In this embodiment, the parameterized parallel configuration includes Cluster.conf and Parametric.conf. The Cluster.conf defines the parameters of the computing cluster, including the computing task submission mode of the cluster, the maximum number of allocated computing nodes for a single computing task, and the maximum number of available nodes. The Parametric.conf is a parameter configuration for large-scale task parallel conditions for parameter traversal. The definable parameters are determined by WRF.conf and CFD.conf, and the parameters that need to be arranged and combined for traversal are separated by a semicolon.

[0041] A plurality of CFD case folders are generated through parameterized parallel configuration. Specifically, the values in WRF.conf and CFD.conf are replaced according to the traversal parameters, and a plurality of CFD case folders are generated to isolate the computing data, thereby realizing parallel simulation of the CFD cases.

[0042] By introducing the parameterized large-scale parallel computing function, combined with the computing power of the high-performance supercomputing cluster, the system supports automatic scanning calculation of multiple parameter combinations and parallel submission and execution of a large number of computing tasks. Hundreds of simulation cases with different parameter configurations can be run simultaneously at a time, quickly generating massive high-quality CFD simulation data to provide a rich data set for machine learning model training. At the same time, the multi-case parallel computing capability enables the system to quickly generate multiple simulation results for emergency environmental events, providing strong support for the rapid response and scientific decision-making of decision-makers in emergency situations.

[0043] To verify the effect of the present application, a simulation experiment was conducted on the diffusion of point source aerosol pollutants in a certain area of a certain city on a certain day.

[0044] Download the required meteorological and underlying surface data from an open-source website. Set the start_date in WRF.conf to 2021-01-01_00:00:00, the end_date to 2021-01-02_00:00:00, the interval_seconds to 21600, the dx to 11117.748, the dy to 11117.748, the ref_lat to 39.75, the ref_lon to 116.5, the max_dom to 1, the e_we to 36, and the e_sn to 46.

[0045] Configure the CFD.conf file, set the aerosol source position to (0 0 200), the aerosol release rate to 0.1, the number of parallel subdomains to 96, the simulation end time to 2700 s, and the time step to 0.1 s.

[0046] Urban 3D geometric model Figure 2 As shown, process it into an STL file. In the CFD configuration file, set the solution domain to -6200 to 6200 in the X direction, -6200 to 6200 in the Y direction, and 45.1 to 1000 in the Z direction. Set the refined grid box range from the minimum (-6000 -6000 0) to the maximum (6000 6000 400).

[0047] After the settings are completed, proceed to the next steps to obtain the aerosol pollutant diffusion simulation results, such as Figure 3 shown. Figure 3 Two time sections of the horizontal profile at the same height are shown. The plume in the figure expands in the southeast direction as a whole, which is completely consistent with the northwest wind direction predicted by WRF. As the diffusion time increases, several dark blue square-shaped low-concentration areas appear around the source point, corresponding to the locations blocked by buildings; the plume is deflected and forms local entrainment when passing through the gaps between blocks, indicating that the building flow and tail vortex have a significant impact on the near-field dilution. The above phenomenon fully proves that the method of the present invention can accurately reproduce the transport and dilution process of aerosol plumes under complex urban terrain, and can clearly capture details such as deflection and vortex. It can be seen that the method of the present invention is accurate and effective.

[0048] In one embodiment, a device for simulating the diffusion of aerosol pollutants in a complex environment is provided, comprising: The first module is used to build the WRF-CFD data pipeline; The second module is used to initialize the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf; The third module is used to parse and fill in the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate WRF calculation results, and convert the calculation results into netCDF4 format; The fourth module is configured to uniformly calculate the content field of the condensed water in the air and the wind field data based on the WRF calculation result, take the content field of the condensed water in the air as a parameter of the removal coefficient in an aerosol diffusion control equation in the CFD, take the wind field data as a boundary condition of a velocity field in the CFD, convert the WRF calculation result to the calculation grid of the CFD by a cubic spline interpolation method, and obtain a CFD case; the aerosol diffusion control equation contains a cleaning source term, and is used to represent the influence of different meteorological conditions on the aerosol diffusion. The fifth module is configured to initialize the CFD case, submit the CFD case to a calculation node, and obtain a simulation result of the aerosol pollutant diffusion.

[0049] The remaining details of the present application are known in the art.

[0050] The technical features of the above embodiments can be combined in any manner, and for the sake of brevity, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not contradict, they should be considered within the scope of the present application.

[0051] The above embodiments only express several implementation manners of the present application, and the description is relatively specific and detailed, but it should not be understood as a limitation on the scope of the present application. It should be pointed out that, for ordinary skilled persons in the art, without departing from the concept of the present application, several modifications and improvements can be made, which are within the protection scope of the present application.

[0052] The above only describes the preferred embodiments of the present application, and is not intended to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for simulating the diffusion of aerosol pollutants in a complex environment, characterized in that: The following steps are involved: Build the WRF-CFD data pipeline; Initialize the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf; Parse the WRF.conf configuration information and fill it in, generate the data and configuration files required for WRF calculation, generate WRF calculation results, and convert the calculation results into netCDF4 format; Based on the WRF calculation results, the condensable water content field and wind field data in the air are uniformly calculated. The condensable water content field in the air is used as the parameter of the purge coefficient in the aerosol diffusion control equation in CFD, and the wind field data is used as the boundary condition of the velocity field in CFD. The WRF calculation results are converted to the CFD calculation grid through the cubic spline interpolation method to obtain a CFD case. The aerosol diffusion control equation includes a purge source term to characterize the impact of different meteorological conditions on aerosol diffusion. Initialize the CFD case and submit it to the computing node to obtain the aerosol pollutant diffusion simulation results.

2. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, characterized in that: Initialize the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf, including: Download and store the underlying surface and meteorological data into a predefined directory to complete the data setup initialization of the WRF-CFD data pipeline; Complete WRF controllable parameter configuration and WRF fixed parameter configuration through WRF.conf; Complete CFD controllable parameter configuration as well as CFD fixed parameters and solver configuration through CFD.conf.

3. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 2, characterized in that: The CFD fixed parameters include a high-precision three-dimensional urban geometric model, solver control parameters, and grid parameters.

4. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 2, wherein: The solver is a transient scalar solver using a large eddy simulation model.

5. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, wherein: Parse and fill in the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate WRF calculation results, and convert the calculation results into netCDF4 format, including: Parse the WRF.conf configuration and fill the nested grid settings and simulation time in the corresponding namelist; Based on the filled WRF.conf configuration, the program is called to generate the data and configuration files required for WRF calculation, and the data is preprocessed by transformation and interpolation. Based on the WRF calculation configuration file, the preprocessed data is submitted to the computing node for operation to generate the WRF calculation results; Convert WRF calculation results to netCFD4 format without loss.

6. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, wherein: The content field of condensed water in the air is calculated according to the following formula: in, is the content field of condensed water in the air; is a cloud-related variable; is a precipitation-related variable; is a snowfall-related variable; is the air density; is the total condensate mixing ratio at each grid point; is the air pressure; For temperature.

7. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, wherein: The wind field data includes wind speed and wind direction; The wind speed is calculated according to the following formula: The wind direction is calculated according to the following formula: in, is the wind speed; For wind direction; is the component of wind speed in the east-west direction; is the north-south component of the wind speed.

8. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, wherein: The aerosol diffusion governing equation is: in, is the aerosol concentration; For time; is the gradient operator; is the wind speed vector; is the diffusion coefficient; is the source term of aerosol; is the aerosol clearance coefficient.

9. The method for simulating the diffusion of aerosol pollutants in a complex environment according to claim 1, wherein: Also includes: After the configuration and data setup of the WRF-CFD data pipeline are initialized, parameterized parallel configuration is performed; Generate multiple CFD case folders through parametric parallel configuration to achieve parallel simulation of CFD cases.

10. A complex environment aerosol pollutant diffusion simulation device, characterized in that: include: The first module is used to build the WRF-CFD data pipeline; The second module is used to initialize the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf; The third module is used to parse and fill in the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate WRF calculation results, and convert the calculation results into netCDF4 format; The fourth module is used to uniformly calculate the condensable water content field and wind field data in the air based on the WRF calculation results. The condensable water content field in the air is used as the parameter of the purge coefficient in the aerosol diffusion control equation in CFD, and the wind field data is used as the boundary condition of the velocity field in CFD. The WRF calculation results are converted to the CFD calculation grid through cubic spline interpolation to obtain CFD cases. The aerosol diffusion control equation includes a purge source term to characterize the impact of different meteorological conditions on aerosol diffusion. The fifth module is used to initialize the CFD case and submit it to the computing node to obtain the aerosol pollutant diffusion simulation results.

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