An airport atmospheric environment prediction method, device, equipment and storage medium

Abstract

This application discloses a method, apparatus, device, and storage medium for predicting airport atmospheric environment, comprising: acquiring output data related to airport atmospheric environment parameters generated by an airport model; processing a specified file in the output data in a batch processing manner and starting a first atmospheric diffusion model to perform parallel calculations on the output data to obtain a result file corresponding to the output data; converting the result file into a data format supported by a second atmospheric diffusion model, and using the second atmospheric diffusion model to perform superposition and post-processing on the converted result file to obtain result data that meets preset requirements. Based on the output data related to airport atmospheric environment parameters generated by the airport model, this application utilizes the first and second atmospheric diffusion models for parallel processing and superposition, and finally obtains the required result data through post-processing, thereby improving the data processing efficiency in airport atmospheric environment prediction scenarios.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a method, apparatus, equipment, and storage medium for predicting the atmospheric environment of an airport. Background Technology

[0002] After the implementation of the Technical Guidelines for Environmental Impact Assessment (Atmospheric Environment) (HJ2.2-2018), atmospheric environmental impact prediction and assessment must be carried out for new, relocated, and expanded hub and trunk airport projects.

[0003] Existing airport models used for aviation energy conservation, emission reduction, and environmental impact assessment cannot meet the guidelines for daily average mass concentrations of basic pollutants and secondary PM2.5 levels during simulation and prediction in environmental impact assessment work. 2.5 The calculation requirements for the concentration contribution value of newly added pollution sources under normal emission conditions in airport expansion and renovation projects are addressed by some environmental impact assessment (EIA) professionals who modify model scripts through programming and directly perform secondary data processing on the model output files to meet the calculation requirements of the guidelines. However, the prediction scenarios for atmospheric environmental impact assessment generally include the contribution value of newly added pollution sources, regional superposition value, and K-value of regional environmental quality improvement. Among these, the contribution value of newly added pollution sources in expansion and renovation projects needs to be obtained by subtracting the atmospheric environmental impact prediction results of the planning year and the current year (C). 改扩建 =C 规划年 -C 现状年 The prediction scenarios typically include four scenarios, and the predictor factors are typically seven. Therefore, airport models involve a large amount of computation, and single-threaded calculations are time-consuming and inefficient, failing to meet the computational needs of practical working models. It is necessary to study feasible methods to improve computational efficiency in order to enhance the computational efficiency and capabilities of airport models.

[0004] Therefore, the aforementioned technical problems urgently need to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, apparatus, device, and storage medium for predicting airport atmospheric environment, which can improve data processing efficiency in airport atmospheric environment prediction scenarios. The specific solution is as follows:

[0006] The first aspect of this application provides a method for predicting the atmospheric environment of an airport, including:

[0007] Obtain output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment;

[0008] The specified file in the output data is processed in batch mode, and the first atmospheric diffusion model is started to perform parallel calculations on the output data to obtain the result file corresponding to the output data.

[0009] The result file is converted into a data format supported by the second atmospheric diffusion model, and the converted result file is overlaid and post-processed using the second atmospheric diffusion model to obtain result data that meets the preset requirements.

[0010] Optionally, acquiring the output data related to airport atmospheric environmental parameters generated by the airport model includes:

[0011] Obtain the output data generated by the EDMS model or AEDT model, which includes meteorological documents, pollution source lists, and related control documents.

[0012] Optionally, the step of processing a specified file in the output data in a batch manner and starting the first atmospheric diffusion model to perform parallel calculations on the output data to obtain a result file corresponding to the output data includes:

[0013] The control file in the output data is modified by a batch processing script to add time variable parameters and set the file output format of the AERMOD model;

[0014] The AERMOD model is started in parallel by a batch script, so that the AERMOD model outputs the result file in units of the time variable parameter.

[0015] Optionally, the second atmospheric diffusion model is the CALPUFF model;

[0016] Accordingly, converting the result file into a data format supported by the second atmospheric diffusion model includes:

[0017] The result file is converted into a data format supported by the CALPUFF model using the AER2CAL tool; wherein the result file is output by the AERMOD model and has a corresponding file output format.

[0018] Optionally, the airport atmospheric environment prediction method further includes:

[0019] Determine whether the sum of the emissions of sulfur dioxide and nitrogen oxides in the pollution source list in the output data is less than a preset threshold. If so, do not calculate the emissions of secondary pollutants, and directly execute the step of superimposing the converted result file using the second atmospheric diffusion model.

[0020] If not, use the POSTUTIL tool to calculate the emissions of secondary pollutants.

[0021] Optionally, the superposition and post-processing of the transformed result file using the second atmospheric diffusion model includes:

[0022] The CALSUM overlay tool in the CALPUFF model is used to overlay the converted result file to obtain the overlay result file, and then post-processing is performed on the overlay result file.

[0023] Optionally, the post-processing of the result file after overlay processing includes:

[0024] The CALPOST tool in the CALPUFF model is used to extract the data results from the overlay process results file to obtain the results data that meet the relevant guidelines.

[0025] A second aspect of this application provides an airport atmospheric environment prediction device, comprising:

[0026] The output data acquisition module is used to acquire output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment.

[0027] The parallel processing module is used to process a specified file in the output data in a batch processing manner and start the first atmospheric diffusion model to perform parallel calculations on the output data to obtain a result file corresponding to the output data.

[0028] The format conversion and overlay processing module is used to convert the result file into a data format supported by the second atmospheric diffusion model, and to use the second atmospheric diffusion model to perform overlay processing and post-processing on the converted result file to obtain result data that meets preset requirements.

[0029] A third aspect of this application provides an electronic device comprising a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the aforementioned airport atmospheric environment prediction method.

[0030] A fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the aforementioned airport atmospheric environment prediction method.

[0031] In this application, output data related to airport atmospheric environmental parameters generated by an airport model is first obtained; wherein the airport model is used for aviation energy conservation, emission reduction, and environmental impact assessment; then, a specified file in the output data is processed in batch processing, and a first atmospheric diffusion model is started to perform parallel calculations on the output data to obtain a result file corresponding to the output data; finally, the result file is converted into a data format supported by a second atmospheric diffusion model, and the converted result file is overlaid and post-processed using the second atmospheric diffusion model to obtain result data that meets preset requirements. It can be seen that this application, based on the output data related to airport atmospheric environmental parameters generated by the airport model, utilizes the first and second atmospheric diffusion models for parallel and overlay processing, and finally obtains the required result data through post-processing, thereby improving the data processing efficiency under airport atmospheric environmental prediction scenarios. Attached Figure Description

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0033] Figure 1 A flowchart of an airport atmospheric environment prediction method provided in this application;

[0034] Figure 2 A schematic diagram illustrating a specific airport atmospheric environment prediction method provided in this application;

[0035] Figure 3 This application provides a schematic diagram of the structure of an airport atmospheric environment prediction device.

[0036] Figure 4 This application provides a structural diagram of an electronic device for predicting the atmospheric environment at an airport. Detailed Implementation

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Existing airport models cannot meet the prediction requirements of the "Technical Guidelines for Environmental Impact Assessment - Atmospheric Environment" (HJ169-2018) (hereinafter referred to as the "Guidelines"), including the daily average mass concentration of basic pollutants at the guarantee rate and secondary PM2.5. 2.5 The calculation requirements include subtracting the planned year and current year for airport expansion and renovation projects to obtain the concentration contribution value of newly added pollution sources under normal emissions. Some environmental impact assessment personnel directly perform secondary data processing on the model output files through programming. However, they may encounter single-factor hourly concentration result files exceeding 20GB, resulting in extremely low efficiency for addition or subtraction processing due to the large data volume, and may even lead to computer memory overflow and inability to process the data. If secondary PM calculation is required... 2.5 At the same time, SO2 and NO also need to be controlled. X and PM 2.5 The current method of processing three result files by overlaying them daily results in low efficiency. To address these technical shortcomings, this application provides an airport atmospheric environment prediction scheme. Based on the output data related to airport atmospheric environment parameters generated by the airport model, parallel processing and overlay processing are performed using a first atmospheric diffusion model and a second atmospheric diffusion model. Finally, the desired result data is obtained through post-processing. This improves data processing efficiency in airport atmospheric environment prediction scenarios.

[0039] Figure 1 A flowchart illustrating an airport atmospheric environment prediction method provided in this application embodiment. See also... Figure 1 As shown, the atmospheric environment prediction method for this airport includes:

[0040] S11: Obtain the output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment.

[0041] In this embodiment, the output data related to airport atmospheric environmental parameters generated by the airport model is first acquired. The airport model is used for aviation energy conservation, emission reduction, and environmental impact assessment. Airport models include EDMS models or AEDT models, etc. Correspondingly, the output data related to airport atmospheric environmental parameters generated by these models includes meteorological files, pollution source inventories, and related control documents. The above step involves acquiring the output data containing meteorological files, pollution source inventories, and related control documents generated by the EDMS or AEDT model. Specifically, the meteorological files are "*.SFC" and "*.PFL" files, the pollution source inventories are "*.HRE" files, and the control documents are "*.INP" files.

[0042] It is understandable that the EDMS and AEDT models, jointly developed by the Federal Aviation Administration (FAA) and the U.S. Air Force (USAF), are recommended models in the "Technical Guidelines for Environmental Impact Assessment: Atmospheric Environment" (HJ2.1-2018). These models include emission and diffusion models, primarily used to establish air pollutant emission inventories for civil airports and calculate pollutant diffusion. The diffusion model's kernel is the AERMOD model. However, using only the EDMS and AEDT models for simulation and prediction cannot meet the guidelines' requirements for basic pollutant guarantee rates, daily average mass concentrations, and secondary PM2.5 concentrations in environmental impact assessments. 2.5 The calculation requirements for the concentration contribution value of newly added pollution sources under normal emission conditions in airport expansion and renovation projects are addressed in this embodiment, which aims to overcome this technical drawback.

[0043] S12: Process the specified file in the output data in batch processing and start the first atmospheric diffusion model to perform parallel calculations on the output data to obtain the result file corresponding to the output data.

[0044] In this embodiment, to address the issues of airport models failing to meet the guidelines and having low computational efficiency, a batch processing method is used to process specified files in the output data and initiate a first atmospheric diffusion model to perform parallel computation on the output data, obtaining a result file corresponding to the output data. The first atmospheric diffusion model is the AERMOD model. This embodiment modifies the script data generated by the airport diffusion model in batches, alters the output format of the result file, and compresses the result file size. The result file size is approximately 1 / 20th the size of a text file, facilitating subsequent post-processing.

[0045] In this embodiment, the batch processing of a specified file in the output data includes modifying the specified file and starting the parallel computation of the first atmospheric diffusion model. The modification mainly involves adding time variable parameters and setting the file output format of the AERMOD model. Specifically, the specified file is the control file in the output data. That is, the specific process of processing the specified file in the output data and starting the parallel computation of the first atmospheric diffusion model using batch processing includes: modifying the control file in the output data using a batch processing script to add time variable parameters and set the file output format of the AERMOD model; starting the parallel computation of the AERMOD model using a batch processing script, so that the AERMOD model outputs the result file in units of the time variable parameters. The time variable parameters can represent the whole year, a certain season, or even a certain day. The set file output format is an hourly average result file, resulting in an hourly result file corresponding to the output data. The reason for setting the file output format of the AERMOD model is to enable efficient conversion of the result file later.

[0046] S13: Convert the result file into a data format supported by the second atmospheric diffusion model, and use the second atmospheric diffusion model to perform superposition and post-processing on the converted result file to obtain result data that meets the preset requirements.

[0047] In this embodiment, the result file is converted into a data format supported by the second atmospheric diffusion model, and the converted result file is then overlaid and post-processed using the second atmospheric diffusion model to obtain result data that meets preset requirements. The second atmospheric diffusion model is the CALPUFF model. Accordingly, in the format conversion, the AER2CAL tool can be used to convert the result file into a data format supported by the CALPUFF model, which supports the data format "CONC.DAT". That is, the AER2CAL tool performs parallel computation to convert the POSTFILE result file (*.bin) generated by the atmospheric diffusion AERMOD module into the CONC.DAT format of the CALPUFF model's result file. Correspondingly, in step S12, the process of modifying the control file in the output data using a batch script to set the AERMOD model's file output format involves setting the AERMOD model's file output format to a format that the AER2CAL tool can convert. *.bin files are the output format supported by the AERRMOD model and are also a format that the AER2CAL tool can convert. Therefore, step S12 mainly involves modifying the control file in the output data using a batch processing script to set the AERRMOD model's file output format to *.bin file format. The compressed file size of this data format is approximately 1 / 20th the size of a text file, saving computer hard drive resources and reducing the computer performance requirements of the processing process. At the same time, parallel computing further improves processing efficiency.

[0048] This embodiment fully leverages the computational advantages of both the AERMOD and CALPUFF models. It eliminates the need to rewrite code for secondary processing of the result files, allowing for the processing of airport model results using existing mature programs. This improves computational efficiency and meets the demands for computational efficiency and results in practical work.

[0049] In this embodiment, before performing overlay processing and post-processing on the transformed result file using the second atmospheric diffusion model, it is necessary to determine whether to use the second atmospheric diffusion model to calculate secondary pollutants in the transformed result file. Specifically, it is necessary to determine whether the sum of the emissions of sulfur dioxide and nitrogen oxides in the pollution source inventory of the result file is less than a preset threshold. If so, the emissions of secondary pollutants are not calculated, and the step of overlay processing on the transformed result file using the second atmospheric diffusion model is directly executed. If not, the emissions of secondary pollutants are calculated using the POSTUTIL tool. For example, sulfur dioxide (SO2) and nitrogen oxides (NO) are calculated using the airport model pollution source emission inventory. XIf the sum of the emissions is greater than or equal to 500 tons / year, then a secondary PM2.5 concentration needs to be calculated. 2.5 Conversely, no calculation is required, and the calculation time is on the order of seconds. This embodiment mainly uses the POSTUTIL tool to perform parallel calculations of the secondary PM. 2.5 .

[0050] Based on this, the CALSUM overlay tool in the CALPUFF model is used to overlay the transformed result files, resulting in the overlay-processed result file. Multiple generated result files (CONC.DAT) are batch overlaid using the CALSUM overlay tool in parallel, with computation time in the order of seconds. Furthermore, to ensure the final calculation results are directly readable and meet relevant guidelines, the CALPOST post-processing module is used. Specifically, the CALPOST tool in the CALPUFF model is used to extract data from the overlay-processed result files, obtaining result data that meets the relevant guidelines. The CALPOST post-processing module is a component of the CALPUFF model, primarily used for batch data extraction from the final CONC.DAT file, outputting the results required by the guidelines, with computation time in the order of seconds.

[0051] Figure 2 The flowchart above shows the complete steps. As can be seen from the diagram, this embodiment overcomes the limitations of the airport diffusion model AERMOD itself, fully leveraging the computational advantages of both AERMOD and CALPUFF models. The AER2CAL tool converts the AERMOD result file into the CALPUFF diffusion module result format. The CALSUM overlay tool quickly calculates the contribution value of new pollution sources in the airport expansion and renovation project. The POSTUTIL tool quickly calculates secondary pollutants. Finally, CALPOST post-processing extracts the result file. This embodiment utilizes existing mature public programs to convert the AERMOD calculation result file into a CALPUFF result file. On the one hand, this compresses the model result file size and improves processing efficiency; on the other hand, it allows the use of CALPUFF model-related tools to handle calculations such as overlay reduction and result post-processing, fully leveraging the computational advantages of both models. This addresses the current inability of airport models to meet the prediction requirements of the "Technical Guidelines for Environmental Impact Assessment - Atmospheric Environment" (HJ169-2018) (hereinafter referred to as the "Guidelines"), including the daily average mass concentration of basic pollutants at the guarantee rate and secondary PM2.5. 2.5 The calculation requirements, such as subtracting the current year from the planning year to obtain the contribution value of newly added pollution source concentrations for airport expansion and renovation projects, reduce the difficulty of atmospheric environmental impact assessment and prediction simulation work for airport projects, and provide practitioners with scientific and effective simulation tools.

[0052] As can be seen, this embodiment first obtains output data related to airport atmospheric environmental parameters generated by an airport model; wherein, the airport model is used for aviation energy conservation, emission reduction, and environmental impact assessment; then, a specified file in the output data is processed in batch processing, and a first atmospheric diffusion model is started to perform parallel calculations on the output data to obtain a result file corresponding to the output data; finally, the result file is converted into a data format supported by a second atmospheric diffusion model, and the converted result file is superimposed and post-processed using the second atmospheric diffusion model to obtain result data that meets preset requirements. Based on the output data related to airport atmospheric environmental parameters generated by the airport model, this embodiment utilizes the first and second atmospheric diffusion models for parallel and superimposed processing, and finally obtains the required result data through post-processing, thereby improving the data processing efficiency under airport atmospheric environmental prediction scenarios.

[0053] See Figure 3 As shown in the illustration, this application also discloses an airport atmospheric environment prediction device, comprising:

[0054] The output data acquisition module 11 is used to acquire output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment.

[0055] The parallel processing module 12 is used to process a specified file in the output data in a batch processing manner and start the first atmospheric diffusion model to perform parallel calculations on the output data to obtain a result file corresponding to the output data.

[0056] The format conversion and overlay processing module 13 is used to convert the result file into a data format supported by the second atmospheric diffusion model, and to use the second atmospheric diffusion model to perform overlay processing and post-processing on the converted result file to obtain result data that meets preset requirements.

[0057] As can be seen, this embodiment first obtains output data related to airport atmospheric environmental parameters generated by an airport model; wherein, the airport model is used for aviation energy conservation, emission reduction, and environmental impact assessment; then, a specified file in the output data is processed in batch processing, and a first atmospheric diffusion model is started to perform parallel calculations on the output data to obtain a result file corresponding to the output data; finally, the result file is converted into a data format supported by a second atmospheric diffusion model, and the converted result file is superimposed and post-processed using the second atmospheric diffusion model to obtain result data that meets preset requirements. This embodiment, based on output data related to airport atmospheric environmental parameters generated by any airport model, utilizes the first and second atmospheric diffusion models for parallel and superimposed processing, and finally obtains the required result data through post-processing, thereby improving data processing efficiency under airport atmospheric environmental prediction scenarios.

[0058] In some specific embodiments, the output data acquisition module 11 is specifically used to acquire the output data generated by the EDMS model or AEDT model, which includes meteorological files, pollution source lists and related control files.

[0059] In some specific embodiments, the parallel processing module 12 specifically includes:

[0060] The time variable parameter setting unit is used to modify the control file in the output data through a batch processing script to add time variable parameters;

[0061] The output format setting unit is used to modify the control file in the output data through a batch processing script to set the file output format of the AERMOD model.

[0062] A parallel computing unit is used to initiate parallel computation of the AERMOD model through a batch processing script, so that the AERMOD model outputs the result file in units of the time variable parameter.

[0063] In some specific embodiments, the airport atmospheric environment prediction device further includes:

[0064] The secondary pollutant calculation module is used to determine whether the sum of the emissions of sulfur dioxide and nitrogen oxides in the pollution source list in the output data is less than a preset threshold. If it is, the emissions of secondary pollutants are not calculated, and the step of superimposing the converted result file using the second atmospheric diffusion model is directly executed. If not, the emissions of secondary pollutants are calculated using the POSTUTIL tool.

[0065] In some specific embodiments, the format conversion and overlay processing module 13 specifically includes:

[0066] The format conversion unit is used to convert the result file with the set file output format into a data format supported by the CALPUFF model using the AER2CAL tool;

[0067] The overlay unit is used to overlay the converted result file using the CALSUM overlay tool in the CALPUFF model to obtain the overlay-processed result file.

[0068] The post-processing unit is used to perform post-processing on the result file after the superposition process;

[0069] The extraction module is used to extract the data results from the overlay process of the result file using the CALPOST tool in the CALPUFF model, and obtain the extracted result data that meets the relevant guidelines.

[0070] Furthermore, embodiments of this application also provide an electronic device. Figure 4 This is a structural diagram of an electronic device 20 according to an exemplary embodiment. The content of the diagram should not be construed as limiting the scope of this application.

[0071] Figure 4 This is a schematic diagram of the structure of an electronic device 20 provided in an embodiment of this application. Specifically, the electronic device 20 may include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. The memory 22 stores a computer program, which is loaded and executed by the processor 21 to implement the relevant steps in the airport atmospheric environment prediction method disclosed in any of the foregoing embodiments.

[0072] In this embodiment, the power supply 23 is used to provide operating voltage for each hardware device on the electronic device 20; the communication interface 24 can create a data transmission channel between the electronic device 20 and external devices, and the communication protocol it follows can be any communication protocol applicable to the technical solution of this application, and is not specifically limited here; the input / output interface 25 is used to acquire external input data or output data to the outside world, and its specific interface type can be selected according to specific application needs, and is not specifically limited here.

[0073] In addition, the memory 22, as a carrier for resource storage, can be a read-only memory, random access memory, disk or optical disk, etc. The resources stored thereon can include operating system 221, computer program 222 and data 223, etc., and the storage method can be temporary storage or permanent storage.

[0074] The operating system 221 manages and controls the various hardware devices and computer programs 222 on the electronic device 20 to enable the processor 21 to perform calculations and processing on the massive amounts of data 223 in the memory 22. The operating system 221 can be Windows Server, Netware, Unix, Linux, etc. In addition to including computer programs capable of performing the airport atmospheric environment prediction method executed by the electronic device 20 as disclosed in any of the foregoing embodiments, the computer program 222 may further include computer programs capable of performing other specific tasks. The data 223 may include output data collected by the electronic device 20.

[0075] Furthermore, this application also discloses a storage medium storing a computer program. When the computer program is loaded and executed by a processor, it implements the steps of the airport atmospheric environment prediction method disclosed in any of the foregoing embodiments.

[0076] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0077] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0078] The airport atmospheric environment prediction method, apparatus, equipment, and storage medium provided by the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for predicting atmospheric environment at airports, characterized in that, include: Obtain output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment; The output data is processed in batch mode to select a file and the first atmospheric diffusion model is started to perform parallel calculations on the output data to obtain a result file corresponding to the output data. Specifically, this includes: modifying the control file in the output data using a batch processing script to add time variable parameters and set the file output format of the AERMOD model; and starting the parallel calculation of the AERMOD model using a batch processing script so that the AERMOD model outputs the result file in units of the time variable parameters. The result file is converted into a data format supported by the second atmospheric diffusion model, and the converted result file is then overlaid and post-processed using the second atmospheric diffusion model to obtain result data that meets preset requirements. Specifically, this includes: using the AER2CAL tool to convert the result file into a data format supported by the CALPUFF model; wherein the result file is output by the AERMOD model and has a corresponding file output format; using the CALSUM overlay tool in the CALPUFF model to overlay the converted result file to obtain the overlaid result file, and then performing post-processing on the overlaid result file.

2. The airport atmospheric environment prediction method according to claim 1, characterized in that, The acquisition of output data related to airport atmospheric environmental parameters generated by the airport model includes: Obtain the output data generated by the EDMS model or AEDT model, which includes meteorological documents, pollution source lists, and related control documents.

3. The airport atmospheric environment prediction method according to claim 2, characterized in that, Before performing overlay processing and post-processing on the transformed result file using the second atmospheric diffusion model, the process also includes: Determine whether the sum of the emissions of sulfur dioxide and nitrogen oxides in the pollution source list in the output data is less than a preset threshold. If so, do not calculate the emissions of secondary pollutants, and directly execute the step of superimposing the converted result file using the second atmospheric diffusion model. If not, use the POSTUTIL tool to calculate the emissions of secondary pollutants.

4. The airport atmospheric environment prediction method according to claim 1, characterized in that, The post-processing of the result file after overlay processing includes: The CALPOST tool in the CALPUFF model is used to extract the data results from the overlay process results file to obtain the results data that meet the relevant guidelines.

5. An airport atmospheric environment prediction device, characterized in that, include: The output data acquisition module is used to acquire output data related to airport atmospheric environmental parameters generated by the airport model; wherein, the airport model is used for aviation energy conservation, emission reduction and environmental impact assessment. The parallel processing module is used to process a specified file in the output data in a batch processing manner and start the first atmospheric diffusion model to perform parallel calculations on the output data to obtain a result file corresponding to the output data; specifically, it includes: modifying the control file in the output data through a batch processing script to add time variable parameters and set the file output format of the AERMOD model; starting the parallel calculation of the AERMOD model through a batch processing script so that the AERMOD model outputs the result file in units of the time variable parameters; The format conversion and overlay processing module is used to convert the result file into a data format supported by the second atmospheric diffusion model, and to perform overlay processing and post-processing on the converted result file using the second atmospheric diffusion model to obtain result data that meets preset requirements. Specifically, it includes: using the AER2CAL tool to convert the result file into a data format supported by the CALPUFF model; wherein the result file is output by the AERMOD model and has a corresponding file output format; using the CALSUM overlay tool in the CALPUFF model to perform overlay processing on the converted result file to obtain the overlay-processed result file, and performing post-processing on the overlay-processed result file.

6. An electronic device, characterized in that, The electronic device includes a processor and a memory; wherein the memory is used to store a computer program, which is loaded and executed by the processor to implement the airport atmospheric environment prediction method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, Used to store computer-executable instructions, which, when loaded and executed by a processor, implement the airport atmospheric environment prediction method as described in any one of claims 1 to 4.

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