Method and device for simulating diffusion of aerosol pollutants in complex environment

Abstract

The application provides a complex environment aerosol pollutant diffusion simulation method and device, comprising constructing a WRF-CFD data pipeline; initializing configuration and data setting of the WRF-CFD data pipeline; analyzing WRF.conf configuration information and filling, generating WRF calculation results; uniformly calculating content field and wind field data of condensed water in air based on the WRF calculation results; converting the WRF calculation results to the calculation grid of CFD through a cubic spline interpolation method, obtaining a CFD case; initializing the CFD case and submitting to a calculation node, obtaining aerosol pollutant diffusion simulation results. The application quantitatively characterizes the influence of different meteorological conditions on aerosol diffusion by uniformly calculating the content field of condensed water in air and introducing a cleaning source term in the aerosol diffusion control equation, thereby significantly widening the application range and application scenarios.

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:

[0008] In one aspect, the present application provides a complex environment aerosol pollutant diffusion simulation method, comprising the following steps:

[0009] Building a WRF-CFD data pipeline;

[0010] Initializing the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf;

[0011] 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 to netCDF4 format;

[0012] 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;

[0013] Initializing the CFD case and submitting it to the calculation node to obtain the aerosol pollutant diffusion simulation results.

[0014] Further, initializing the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf, comprising:

[0015] Downloading and storing the underlying surface and meteorological data to the predefined directory to complete the data setting initialization of the WRF-CFD data pipeline;

[0016] Completing the WRF controllable parameter configuration and the WRF fixed parameter configuration through WRF.conf;

[0017] Completing the CFD controllable parameter configuration and the CFD fixed parameter and solver configuration through CFD.conf.

[0018] Further, the CFD fixed parameters include high-precision urban three-dimensional geometric models, solver control parameters, and grid parameters.

[0019] Further, the solver is a transient scalar solver using a large eddy simulation model.

[0020] 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 to netCDF4 format, comprising:

[0021] Parsing the WRF.conf configuration, filling the nested grid settings, simulation time in the corresponding namelist in the WRF.conf configuration;

[0022] Based on the filled WRF.conf configuration, the program generates the data and configuration files required for WRF calculation, and pre-processes the data through conversion and interpolation;

[0023] 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;

[0024] The WRF calculation result is losslessly converted into netCFD4 format.

[0025] Further, the content field of the condensed water in the air is calculated according to the following formula:

[0026] ;

[0027] ;

[0028] ;

[0029] 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.

[0030] Further, the wind field data includes wind speed and wind direction;

[0031] The wind speed is calculated according to the following formula:

[0032] ;

[0033] The wind direction is calculated according to the following formula:

[0034] ;

[0035] 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.

[0036] Further, the aerosol diffusion control equation is:

[0037] ;

[0038] 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.

[0039] Further, it further comprises:

[0040] After the configuration and data setting initialization of the WRF-CFD data pipeline, parameterization parallel configuration is carried out;

[0041] A plurality of CFD case folders are generated through the parameterization parallel configuration to realize parallel simulation of the CFD case.

[0042] In another aspect, the present application provides a complex environment aerosol pollutant diffusion simulation device, comprising:

[0043] The first module is used for constructing a WRF-CFD data pipeline;

[0044] The second module is used for initializing the configuration and data setting of the WRF-CFD data pipeline through WRF.conf and CFD.conf;

[0045] The third module is used for parsing the WRF.conf configuration information and filling, generating the data and configuration file required for WRF calculation, generating the WRF calculation result, and converting the calculation result into the netCDF4 format;

[0046] The fourth module is used for uniformly calculating the content field of the condensed water in the air and the wind field data based on the WRF calculation result; taking the content field of the condensed water in the air as the parameter of the removal coefficient in the aerosol diffusion control equation in the CFD, taking the wind field data as the boundary condition of the velocity field in the CFD, converting the WRF calculation result to the calculation grid of the CFD through the cubic spline interpolation method, and obtaining the CFD case; the aerosol diffusion control equation contains the cleaning source term, which is used for representing the influence of different meteorological conditions on the aerosol diffusion;

[0047] The fifth module is used for initializing the CFD case and submitting it to the calculation node to obtain the aerosol pollutant diffusion simulation result.

[0048] Compared with the prior art, the beneficial technical effects of the present application are:

[0049] The application provides a complex environment aerosol pollutant diffusion simulation method and device, which quantitatively characterizes the influence of different meteorological conditions on aerosol diffusion by uniformly calculating the content field of condensed water in air and introducing a cleaning source term in an aerosol diffusion control equation, thereby significantly widening the application range and application scenarios of the application. Meanwhile, the high-quality data transfer from the mesoscale WRF calculation result to the microscale CFD model is realized through the cubic spline interpolation method.

[0050] The WRF-CFD data pipeline constructed by the application eliminates the large amount of manual intervention environment in the traditional method through the standardized configuration file management and the template case generation mechanism, and realizes the whole-process unattended operation, thereby greatly improving the simulation calculation efficiency and repeatability. BRIEF DESCRIPTION OF DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description only constitute some embodiments of the application, and for those skilled in the art, other drawings can also be obtained from the structures shown in the drawings without creative labor.

[0052] Figure 1 The complex environment aerosol pollutant diffusion simulation method flowchart provided for an embodiment;

[0053] Figure 2 The three-dimensional simulated terrain schematic diagram provided for an embodiment;

[0054] Figure 3 The aerosol pollutant diffusion concentration simulation result schematic diagram provided for an embodiment, wherein, Figure 3 (a) is the aerosol pollutant diffusion concentration simulation result schematic diagram at 600s of diffusion, Figure 3 (b) is the aerosol pollutant diffusion concentration simulation result schematic diagram at 1600s of diffusion. DETAILED DESCRIPTION

[0055] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments only constitute some of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the application.

[0056] REFERENCE Figure 1 The complex environment aerosol pollutant diffusion simulation method provided for an embodiment comprises the following steps:

[0057] Constructing a WRF-CFD data pipeline;

[0058] Initializing the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf;

[0059] Parsing the WRF.conf configuration information and filling, generating the data and configuration files required for WRF calculation, generating the WRF calculation results, and converting the calculation results into netCDF4 format;

[0060] Based on the WRF calculation results, 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 is taken as the boundary condition of the velocity field in CFD, the WRF calculation results are converted to the calculation grid of CFD through the cubic spline interpolation method, and the CFD case is obtained; the aerosol diffusion control equation includes a cleaning source term for representing the influence of different meteorological conditions on aerosol diffusion;

[0061] Initializing the CFD case and submitting it to the calculation node to obtain the simulation results of aerosol pollutant diffusion.

[0062] WRF.conf and CFD.conf are the configuration files of the WRF model and the configuration files of the CFD model, respectively.

[0063] By uniformly calculating the content field of the condensed water in the air and introducing the cleaning source term in the aerosol diffusion control equation, the influence of different meteorological conditions on aerosol diffusion is quantitatively represented, which significantly broadens the application range and application scenarios of the present application; at the same time, the high-quality data transfer from the mesoscale WRF calculation results to the microscale CFD model is realized through the cubic spline interpolation method.

[0064] In an embodiment, the configuration and data settings of the WRF-CFD data pipeline are initialized through WRF.conf and CFD.conf, including:

[0065] Downloading and storing the underlying surface and meteorological data to the predefined directory to complete the data setting initialization of the WRF-CFD data pipeline;

[0066] Completing the WRF controllable parameter configuration and the WRF fixed parameter configuration through WRF.conf;

[0067] Completing the CFD controllable parameter configuration and the CFD fixed parameter and solver configuration through CFD.conf.

[0068] Specifically, the controllable parameters of WRF include simulation time period, simulation time step, simulation geographical location information and nested network settings. The fixed parameters of WRF adopt a fixed parameterization scheme, including New Thompson cloud microphysical scheme, Kain-Fritsch set operation parameterization scheme, RRTM long-wave radiation scheme, Dudhia short-wave radiation scheme, Revised MM5 Monin-Obukhov Scheme near-surface scheme, Noah land surface scheme, YSU planetary boundary layer scheme and MYNN turbulence closure scheme. The controllable parameters of CFD include aerosol source location, release rate, parallel region setting, simulation time and simulation step.

[0069] The fixed parameters of CFD include high-precision urban three-dimensional geometric model, solver control parameters (including time step, convergence criterion and relaxation factor) and grid parameters (including grid type, size and boundary layer encryption strategy). By keeping the high-precision urban three-dimensional geometric model, solver control parameters and grid parameters unchanged, the repeatability and result consistency of the WRF calculation results bridging coupled to the CFD calculation grid are ensured.

[0070] The solver is a transient scalar solver using large eddy simulation model. Through the solver, the hourly WRF calculation results can be read and mapped in real time. Since the solver uses large eddy simulation model, the adaptive outer iteration mechanism of transient cycle solution is retained, so that the spatio-temporal evolution of aerosol concentration under different meteorological and precipitation conditions in complex environmental terrain can be efficiently solved.

[0071] In an 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 netCDF4 format, including:

[0072] The WRF.conf configuration is parsed, and the nested grid settings and simulation time in the WRF.conf configuration are filled in the corresponding namelist;

[0073] Based on the filled WRF.conf configuration, the program generates the data and configuration files required for WRF calculation, and the data is preprocessed by conversion and interpolation processing;

[0074] Based on the WRF calculation configuration file, the preprocessed data is submitted to the computing node for operation to generate the WRF calculation results;

[0075] The WRF calculation results are losslessly converted into netCFD4 format.

[0076] In the present embodiment, the data and configuration files required for calling the WPS program for WRF calculation are sequentially run ungrib.exe, geogrid.exe and metgrid.exe to complete the conversion and interpolation of data, thereby completing the preprocessing of data to match the input requirements of the WRF model. The real.exe is called to generate the WRF calculation configuration file, and the preprocessed data is submitted to the computing node for operation to generate the WRF calculation result. The ARWpost program is called to convert the WRF calculation result into netCFD4 format without loss, and save it under the Results folder, thereby facilitating the subsequent process of bridging and coupling the WRF calculation result to the CFD calculation grid.

[0077] Before the process of bridging and coupling the WRF calculation result to the CFD calculation grid, the WRF calculation result is read from the Results folder through the netCFD4 interface; and since the space-time scale of WRF is significantly larger than CFD, only a single run of WRF is required to meet the needs of subsequent aerosol pollutant diffusion simulation.

[0078] In an embodiment, the content field of condensed water in the air and the wind field data are uniformly calculated based on the WRF calculation result; the WRF calculation result includes horizontal wind speed component (u, ), cloud and fog related variables (q ), precipitation related variables (q ), snow related variables (q ), vertical wind speed component (w ), temperature (T) and air pressure (P).

[0079] The content field of condensed water in the air is calculated according to the following formula:

[0080] ;

[0081] ;

[0082] ;

[0083] wherein, is the content field of 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.

[0084] The content field of the condensed state water in the air reflects the important influence of different meteorological conditions (rain, snow, ice crystal, graupel, cloud and fog, etc.) in the aerosol diffusion simulation.

[0085] The wind field data includes wind speed and wind direction;

[0086] The wind speed is calculated according to the following formula:

[0087] ;

[0088] The wind direction is calculated according to the following formula:

[0089] ;

[0090] 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 (vz) has little effect on the overall aerosol diffusion level, it is not considered.

[0091] The aerosol diffusion control equation is:

[0092] ;

[0093] 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.

[0094] By introducing the cleaning source term in the aerosol diffusion control equation, the influence of different meteorological conditions on aerosol diffusion is represented. The WRF-CFD data pipeline configures different simulation conditions according to different meteorological conditions.

[0095] Initialize the CFD case and submit it to the computing node to obtain the aerosol pollutant diffusion simulation result. 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.

[0096] In a preferred embodiment, the complex environment aerosol pollutant diffusion simulation method further comprises:

[0097] After the configuration and data setting initialization of the WRF-CFD data pipeline, parameterization parallel configuration is performed;

[0098] A plurality of CFD case folders are generated through the parameterization parallel configuration to realize parallel simulation of the CFD cases.

[0099] In this embodiment, the parameterization parallel configuration includes Cluster.conf and Parametric.conf. The Cluster.conf defines parameters of a computing cluster, including a computing task submission mode of the cluster, a maximum number of allocated computing nodes of a single computing task and a maximum number of available nodes. The Parametric.conf is a parameter configuration for a large-scale task parallel condition of parameter traversal, wherein 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.

[0100] A plurality of CFD case folders are generated through the parameterization parallel configuration, specifically, values in WRF.conf and CFD.conf are replaced according to the traversal parameters, and a plurality of CFD case folders are generated to realize computing data isolation, thereby realizing parallel simulation of the CFD cases.

[0101] By introducing the parameterization large-scale parallel computing function, combined with the computing capability of the high-performance supercomputing cluster, the automatic scanning calculation of multiple parameter combinations and the parallel submission and execution of a large number of computing tasks are supported. Hundreds of simulation cases with different parameter configurations can be run simultaneously at a time, a large amount of high-quality CFD simulation data is quickly generated, and a rich data set is provided for machine learning model training. At the same time, the multi-case parallel computing capability enables the system to quickly generate multiple simulation results of emergency plans for sudden emergency environmental events, and provides strong support for the rapid response and scientific decision-making of decision-makers in emergency situations.

[0102] To verify the effect of the present application, a simulation experiment is performed on the diffusion of point source aerosol pollutants in a certain region of a certain city on a certain day.

[0103] The required meteorological data and underlying surface data are downloaded from an open source website. The start_date in WRF.conf is set to 2021-01-01_00:00:00, the end_date is set to 2021-01-02_00:00:00, the interval_seconds is set to 21600, the dx is set to 11117.748, the dy is set to 11117.748, the ref_lat is set to 39.75, the ref_lon is set to 116.5, the max_dom is set to 1, the e_we is set to 36, and the e_sn is set to 46.

[0104] Configure the CFD.conf file, setting the aerosol source location to (0 0 200), the aerosol release rate to 0.1, the number of parallel subdomains to 96, the simulation end time to 2700s, and the time step to 0.1s.

[0105] Urban 3D geometric model such as Figure 2 As shown, process it into an STL file. Set the solution domain in the CFD configuration file: X direction -6200 to 6200, Y direction -6200 to 6200, Z direction 45.1 to 1000. Set the range of the encrypted mesh box from minimum (-6000 -6000 0) to maximum (6000 6000 400).

[0106] After setting up, proceed with subsequent steps to obtain the aerosol pollutant diffusion simulation results, such as... Figure 3 As shown. Figure 3 The figure shows two time sections at the same horizontal elevation. The plume extends generally in a southeast direction, perfectly matching the northwest wind direction predicted by the WRF. As the diffusion time increases, several dark blue square-shaped low-concentration areas appear around the source point, corresponding to the locations of building obstruction. The plume is deflected and forms local entrainment when crossing gaps between blocks, indicating that the flow around buildings and the wake vortex have a significant impact on near-field dilution. These phenomena fully demonstrate that the method described in this 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. Therefore, it can be seen that the method described in this invention possesses accuracy and effectiveness.

[0107] In one embodiment, a device for simulating the diffusion of aerosol pollutants in a complex environment is provided, comprising:

[0108] The first module is used to build the WRF-CFD data pipeline;

[0109] The second module is used to initialize the configuration and data settings of the WRF-CFD data pipeline through WRF.conf and CFD.conf;

[0110] The third module is used to parse and populate the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate the WRF calculation results, and convert the calculation results into netCDF4 format;

[0111] The fourth module is used to uniformly calculate the content field of condensed moisture in the air and wind field data based on the WRF calculation results; and uses the content field of condensed moisture in the air as the parameter of the scavenging coefficient in the aerosol diffusion control equation in CFD, and the wind field data as the boundary condition of the velocity field in CFD. The WRF calculation results are transformed onto the CFD calculation grid by cubic spline interpolation to obtain the CFD case; the aerosol diffusion control equation includes a scavenging source term to characterize the influence of different meteorological conditions on aerosol diffusion;

[0112] The fifth module is used to initialize CFD cases and submit them to the computing nodes to obtain simulation results of aerosol pollutant diffusion.

[0113] Matters not covered in this invention are common knowledge.

[0114] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0115] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these modifications and improvements all fall within the protection scope of this application.

[0116] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for simulating the diffusion of aerosol pollutants in complex environments, characterized in that, Includes the following steps: Build a WRF-CFD data pipeline; The configuration and data settings of the WRF-CFD data pipeline are initialized using WRF.conf and CFD.conf; Parse and populate the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate the WRF calculation results, and convert the calculation results into netCDF4 format; Based on the WRF calculation results, the content field of condensed moisture in the air and the wind field data are calculated uniformly. The content field of condensed moisture in the air is used as the parameter of the scavenging 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 transformed onto the CFD calculation grid by cubic spline interpolation to obtain the CFD case. The aerosol diffusion control equation includes a scavenging source term to characterize the influence of different meteorological conditions on aerosol diffusion. Initialize the CFD case and submit it to the compute node to obtain the simulation results of aerosol pollutant diffusion.

2. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, The configuration and data settings of the WRF-CFD data pipeline are initialized using WRF.conf and CFD.conf, including: Download and store the underlying surface and meteorological data to a predefined directory to complete the initialization of data settings for the WRF-CFD data pipeline. Configure controllable parameters and fixed parameters of WRF using WRF.conf; The CFD controllable parameters, fixed parameters, and solver are configured using CFD.conf.

3. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 2, characterized in that, The CFD fixed parameters include a high-precision urban 3D geometric model, solver control parameters, and mesh parameters.

4. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 2, characterized in that, The solver is a transient scalar solver that uses a large eddy simulation model.

5. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, Parse and populate the WRF.conf configuration information, generate the data and configuration files required for WRF computation, generate the WRF computation results, and convert the computation results to netCDF4 format, including: Parse the WRF.conf configuration and populate the nested grid settings and simulation time in the corresponding namelist. Based on the populated 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 computation configuration file, the preprocessed data is submitted to the compute node for computation to generate WRF computation results; The WRF calculation results are converted into netCFD4 format without loss.

6. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, The content field of condensed moisture in the air is calculated according to the following formula: in, This represents the content field of condensed moisture in the air; For variables related to clouds and fog; For precipitation-related variables; For variables related to snowfall; air density; The total condensate mixing ratio at each grid point; It refers to air pressure; For temperature.

7. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, 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, Wind speed; Wind direction; This represents the east-west component of the wind speed; This represents the wind speed component in the north-south direction.

8. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, The aerosol diffusion control equation is as follows: in, This refers to the aerosol concentration. For time; For gradient operators; This is the wind speed vector; The diffusion coefficient is denoted as . For aerosol source terms; This represents the aerosol removal coefficient.

9. The method for simulating the diffusion of aerosol pollutants in complex environments as described in claim 1, characterized in that, Also includes: After the configuration and data settings of the WRF-CFD data pipeline are initialized, parameterized parallel configuration is performed. Multiple CFD case folders are generated through parameterized parallel configuration to achieve parallel simulation of CFD cases.

10. A device for simulating the diffusion of aerosol pollutants in complex environments, 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 populate the WRF.conf configuration information, generate the data and configuration files required for WRF calculation, generate the WRF calculation results, and convert the calculation results into netCDF4 format; The fourth module is used to uniformly calculate the content field of condensed moisture in the air and wind field data based on the WRF calculation results; and uses the content field of condensed moisture in the air as the parameter of the scavenging coefficient in the aerosol diffusion control equation in CFD, and the wind field data as the boundary condition of the velocity field in CFD. The WRF calculation results are transformed onto the CFD calculation grid by cubic spline interpolation to obtain the CFD case; the aerosol diffusion control equation includes a scavenging source term to characterize the influence of different meteorological conditions on aerosol diffusion; The fifth module is used to initialize CFD cases and submit them to the computing nodes to obtain simulation results of aerosol pollutant diffusion.

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