CN114841437A - Method and device for pre-evaluating contribution of emission source to air quality and electronic equipment - Google Patents
Method and device for pre-evaluating contribution of emission source to air quality and electronic equipment Download PDFInfo
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Abstract
The invention provides a method, a device and electronic equipment for pre-evaluating the contribution of an emission source to air quality, wherein the method comprises the following steps: acquiring a first gridding emission list based on a known emission list in a simulation area containing a target area; inputting the first gridding discharge list into a preset air quality model to simulate and iteratively adjust the air quality, and obtaining a second gridding discharge list in a simulation area; converting the second gridding discharge list into discharge source data, wherein the discharge source data comprises a discharge source, a discharge source position and discharge parameters, and the discharge parameters are obtained based on discharge amount corresponding to grids; the emission source data and data of one or more emission sources to be evaluated of the target area are input into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality. By the method and the device, when the emission list is incomplete, the influence of the emission source on the air quality can be accurately pre-evaluated by less computing resources, and secondary conversion is also considered.
Description
Technical Field
The invention relates to the technical field of air quality monitoring, in particular to a method and a device for pre-evaluating contribution of an emission source to air quality and electronic equipment.
Background
Construction projects can have a profound impact on ecology and environment, for example, in the operation of some large plants, the exhaust gas can have a large impact on air quality. In order to protect ecology and environment while a project is being constructed, environmental impact evaluation is generally performed on a construction project. In addition, in the atmospheric pollution treatment, the influence of key pollution sources on the air quality of a city or a station is quantitatively simulated and forecasted, so that the control is accurate and fine.
Su 29130, \29130andZhao Jinyang invent a method for evaluating the influence of a WRF-CHEM model on the atmospheric environment of a large-scale point pollution source, but the method needs a large amount of pollution source data and general investigation on the pollution source data to obtain accurate and complete atmospheric pollution source emission data. If the emission data of the atmospheric pollution source in a certain city or region is incomplete or the base year of the list is earlier, the method cannot be used. In actual simulation prediction, a complete atmospheric pollution source emission list cannot be obtained frequently, meanwhile, the method can only perform simulation prediction on one key source at a time, if the number of key sources is large, multiple times of simulation prediction are needed, the number of required computing resources is large, and timeliness is difficult to guarantee. Therefore, this method has limited application in actual environmental evaluation and simulation prediction.
For the above reasons, the CALPUFF model or the AERMOD model is generally used for the environmental evaluation and simulation prediction of the gravity source at present. The AERMOD model only considers the diffusion of pollutants and does not relate to secondary conversion, PM 2.5 Generally, the predicted value of (c) is low. The CALPUFF model may consider second order transformations, butThe CALPUFF simulation result is greatly influenced by the integrity of an input heavy point source, and if the input pollution source is complete, the simulation effect is good; if a complete list of emissions from atmospheric pollution sources is not available, simulation evaluations may still be performed, but are generally less effective. And in actual simulation evaluation, a complete emission list of the atmospheric pollution source cannot be obtained frequently.
In summary, in the related art, no effective solution has been proposed yet how to accurately pre-evaluate the influence of the emission source on the air quality with less computing resources under the condition of incomplete emission list.
Disclosure of Invention
According to an aspect of the invention, there is provided a method of pre-assessing the contribution of an emission source to air quality, comprising:
acquiring a first gridding emission list based on a known emission list in a simulation area containing a target area;
inputting the first gridding discharge list into a preset air quality model for simulating air quality, adjusting the first gridding discharge list based on an error between a simulation result and a corresponding monitoring result, and repeatedly simulating and adjusting until the error between the simulation result and the monitoring result is smaller than a preset value to obtain a second gridding discharge list in a simulation area, wherein the second gridding discharge list comprises grids and discharge amounts corresponding to the grids;
converting the second gridding discharge list into discharge source data, wherein the discharge source data comprise a discharge source, a position of the discharge source and discharge parameters, and the discharge parameters are obtained based on discharge amount corresponding to grids;
the emission source data and data of one or more emission sources to be evaluated of the target area are input into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality.
In some embodiments, converting the second meshed emissions manifest into emissions source data comprises:
and taking each grid in the second gridding discharge list as a discharge source to obtain discharge source data, wherein each grid is taken as a source, a point source or a surface source, the position of the point source is the central point of the three-dimensional space corresponding to the grid, the position of the source is the three-dimensional space corresponding to the grid, and the position of the surface source is the plane corresponding to the grid.
In some embodiments, further comprising:
generating a meteorological background field of a target forecast time interval of a target area;
inputting the emission source data and data of one or more emission sources to be evaluated of a target area into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality, wherein the method comprises the following steps:
the meteorological background field, the emission source data, and the data of one or more emission sources to be evaluated of the target area are input into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality of the target forecast period.
In some embodiments, converting the second meshed emissions manifest into emissions source data comprises: and converting the part corresponding to the target area in the second gridding emission list into emission source data.
In some embodiments, adjusting the first gridded emissions manifest based on an error between the simulation results and the corresponding monitoring results includes:
for each region within the simulation region:
in the case that the simulation result of the area is higher than the corresponding monitoring result, reducing the discharge amount of each grid in the area in the first gridded discharge list based on the error between the simulation result and the corresponding monitoring result;
and in the case that the simulation result of the area is lower than the monitoring result, increasing the discharge amount of each grid in the area in the first gridded discharge list based on the error between the simulation result and the corresponding monitoring result.
In some embodiments, reducing or increasing the emissions of the respective grid within each region in the first gridded emissions manifest includes:
and reducing or increasing the emission amount of each grid in each area in the first gridded emission list in an equal proportion, wherein the reduced or increased proportion is positively correlated with the error.
In some embodiments, the simulation result of each area is an average value of grids corresponding to each monitored station in the area, and the corresponding monitoring result is an average value of each monitored station in the area.
According to another aspect of the present invention, there is provided an apparatus for pre-evaluating the contribution of an emission source to air quality, comprising:
the acquisition module is used for acquiring a first gridding emission list based on a known emission list in a simulation area containing a target area;
the adjusting module is used for inputting the first gridding discharge list into a preset air quality model to simulate the air quality, adjusting the first gridding discharge list based on the error between the simulation result and the corresponding monitoring result, and repeatedly simulating and adjusting until the error between the simulation result and the monitoring result is smaller than a preset value to obtain a second gridding discharge list in the simulation area, wherein the second gridding discharge list comprises grids and discharge amounts corresponding to the grids;
the conversion module is used for converting the second gridding emission list into emission source data, wherein the emission source data comprises an emission source, the position of the emission source and an emission parameter, and the emission parameter is obtained based on the emission amount corresponding to the gridding;
and the evaluation module is used for inputting the emission source data and the data of one or more emission sources to be evaluated of the target area into the CALPUFF model together so as to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality.
According to still another aspect of the present invention, there is provided an electronic apparatus including:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program comprises instructions which, when executed by a processor, cause the processor to carry out the method of the invention.
According to yet another aspect of the present invention, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of the present invention.
According to one or more technical schemes provided by the embodiment of the invention, based on a first gridding discharge list based on a known discharge list in a simulation area containing a target area, a preset air quality model is used for carrying out simulation iteration of air quality to obtain a second gridding discharge list in the simulation area, so that a more complete and accurate discharge list of the target area is obtained, and the discharge list of the target area can be free from being compiled; the second gridding emission list is converted into emission source data, so that the emission source data with relatively complete and accurate target regions can be obtained, and the complete emission source data can be avoided being investigated; the emission source data and the data of one or more emission sources to be evaluated of a target area are input into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality, so that the contribution of the one or more emission sources to be evaluated to the air quality is pre-evaluated by taking the emission source data as a background emission source, the problem of inaccurate evaluation result caused by incomplete emission source data can be solved, the influence of a plurality of emission sources on the air quality can be simulated at one time by using the CALPUFF model, and the problem of large calculation amount and poor timeliness in one emission source evaluation at one time by using a WRF-CHEM-based method can be solved. Meanwhile, the CALPUFF model also considers secondary conversion, so that the evaluation result is more accurate.
Drawings
Further details, features and advantages of the invention are invented in the following description of exemplary embodiments with reference to the drawings, in which:
FIG. 1 illustrates a flow chart of a method of pre-evaluating the contribution of an emissions source to air quality in accordance with an exemplary embodiment of the present invention;
FIG. 2 shows a schematic block diagram of an apparatus for pre-evaluating the contribution of emissions sources to air quality in accordance with an exemplary embodiment of the present invention;
FIG. 3 illustrates a block diagram of an exemplary electronic device that can be used to implement an embodiment of the invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description. It should be noted that the terms "first", "second", and the like in the present invention are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in the present invention are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present invention are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
In the related art, the AERMOD or CALPUFF model is mainly used for the simulation evaluation of the weight source. The AERMOD model mainly considers diffusion and does not consider secondary conversion, so that the emission source data of gas-involved enterprises are provided based on the forecasting system of the AERMOD model, and the forecasting of the contribution of pollutant concentrations of national control points, provincial control points, small micro-stations and the like can be realized. The CALPUFF model has higher flexibility, can consider secondary conversion, and has higher requirements on the integrity and the accuracy of input pollution source data. If the input pollution source emission data is complete, the simulation effect is good; if the input pollution source data is incomplete, although simulation can be carried out, the simulation effect is generally biased.
According to the embodiment of the invention, through the combined application of the air quality models (any model) such as NAQPMS, CMAQ, WRF-CHEM and CAMx and the CALPUFF model, the air quality models (any model) such as NAQPMS, CMAQ, WRF-CHEM and CAMx are used, a gridded atmospheric pollution source emission list is obtained based on a list gridding technology and a list reverse correction technology, the emission of each grid is processed to obtain the emission of each grid in a three-dimensional space, and each grid is used as an emission source and the emission source to be simulated and predicted to be simultaneously input into the CALPUFF model for simulation evaluation, so that the influence value of the key source to be evaluated on a city or a site is obtained.
According to the embodiment of the invention, the forecast of the contribution of pollutant concentrations of national control stations, provincial control stations, small and miniature stations and the like can be realized by providing the discharge data of the gas-related heavy point sources, and the simulation effect is good. The embodiment of the invention can carry out simulation evaluation without complete pollution source emission data by processing the gridding emission list, and has small calculated amount and high timeliness.
The embodiment of the invention uses the air quality model to quantitatively predict the key pollution source to the SO of the city or the station 2 、NO 2 、PM 2.5 、PM 10 、CO、CO 2 And the influence of the pollutant concentration can be used for the environmental influence evaluation of construction projects, and meanwhile, the reference can be provided for the atmospheric environment evaluation and the urban atmospheric pollution source treatment through the simulation forecast of the gravity pollution source. The method has great practical significance for improving the atmospheric quality, coordinating the environment and realizing sustainable development of social economy.
The following describes aspects of embodiments of the present invention with reference to the drawings.
Fig. 1 shows a flowchart of a method of pre-evaluating the contribution of an emission source to air quality according to an exemplary embodiment of the present invention, which includes steps S101 to S104, as shown in fig. 1.
Step S101, a first grid emission list based on a known emission list in a simulation area containing a target area is obtained.
In the present embodiment, the target area may include a geographical range divided by administrative districts, such as a county (district), a city, or a province (direct prefecture city, autonomous district), and the like. It should be understood that in the present embodiment, the target area may also include a geographical area divided in other manners.
As an embodiment, the simulation area may include only the target area. For example, the target area is a city, or a province, etc. As another embodiment, the simulation region may include the target region and a peripheral region of the target region, thereby allowing for transmission of the peripheral region to the target region. As an example, the target area may be a city, and the surrounding area may include one or more cities in the vicinity of the target area. As another example, the simulated area includes the target area and a geographic area within a preset distance of the perimeter of the target area.
There are known emission lists in the related art, which may include regional, national, continent, global emission lists on a regional scale of interest. By way of example, known emissions manifests may include, but are not limited to: china Multi-resolution Emission Inventory for China, MEIC, Asian regional Emission Inventory (MIX), Global atmosphere Research Emission Database (EDGAR), etc. And emission lists in cities and provinces are compiled in partial cities, provinces and other areas.
In the present embodiment, performing a gridding process on the emission list may obtain a gridded emission list (simply referred to as a gridded emission list). The gridding emission list is an emission list formed by distributing the emission quantity in a geographical grid on the basis of the established emission list. Taking the MEIC as an example, corresponding emission lists can be provided according to different years, model simulation areas, industries and space-time resolutions, and the emission lists comprise a multi-layer nested high space-time resolution emission list for air quality models such as NAQPMS, CMAQ, WRF-Chem or CAMx.
Generally, the accuracy of an emission list having a large area scale is not as high as that of an emission list having a small area scale. As an example, the state-level emission list covers a plurality of cities, but a large error exists between the part of the state-level emission list corresponding to each city and the actual emission list of the city, and further, the update cycle of the state-level emission list is long, so that data is old, and therefore, the emission list of the city is prepared. The emission list is large relative to the area size, wherein the emission list of the local area is also called local emission list. Some areas (e.g., cities) do not compile localized emissions lists. In step S101, a grid emission list (referred to as a first grid emission list) based on a known emission list in a simulation area including a target area is obtained, and in a subsequent step, the emission list of the target area is adjusted based on the first grid emission list. The list of known emissions within the simulation area may be from one or more data sources. When the known emission list in the simulation area comes from a plurality of data sources, the emission lists of the plurality of data sources are coupled to obtain the known emission list in the simulation area. As an example, a grid emission list of city A and cities surrounding city A is obtained from the MEIC. As another example, if the target area and the perimeter area of the target area are comprised of at least two data sources, the emission manifest for the simulation area is a coupling of the at least two data sources.
Step S102, inputting the first gridding discharge list into a preset air quality model for simulating air quality, adjusting the first gridding discharge list based on an error between a simulation result and a corresponding monitoring result, and repeating the simulation and adjustment until the error between the simulation result and the monitoring result is smaller than a preset value to obtain a second gridding discharge list in a simulation area, wherein the second gridding discharge list comprises grids and discharge amounts corresponding to the grids.
The air quality model may simulate air quality based on the gridded emissions manifest. In step S102, the predetermined air quality model may be NAQPMS, CMAQ, WRF-CHEM, CAMx, or the like. In steps S101 and S102, the first gridded emissions manifest is in a data format recognizable by the preset air quality model. This embodiment is not limited to this. As an example, CMAQ relies on external programs to estimate the amount of pollution sources' emissions, location, and time variations when processing the emissions source information. The inputs in the first gridded emissions list are on the same horizontal and vertical spatial scales and cover the same time period as used in the air quality model simulation.
Typically, the air quality model simulates air quality using a gridded emissions manifest and an meteorological model. In step S102, the meteorological background field corresponding to the first grid emission list is also input into a preset air quality model. In step S102, the weather pattern is a historical weather ambient field. As an example, the historical weather ambient field may be obtained based on known techniques. As an example, topographic data of the target area and meteorological data during a preset historical period (e.g., three years of history) are acquired, and a meteorological background field for the year during the preset historical period is generated using a meteorological model (e.g., WRF).
In step S102, the monitoring result may be an actual measurement value of the monitored site. Based on the comparison between the monitoring results and the simulation results, the difference between the first gridded emissions list and the actual or localized emissions list may be evaluated, the error between the monitoring results and the simulation results may be used to adjust the first gridded emissions list, and the above process may be repeated to obtain new simulation results based on the adjusted first gridded emissions list until the error between the monitoring results and the simulation results is less than or equal to a predetermined value (e.g., 5%). When the error between the monitoring result and the simulation result is less than or equal to the preset value, the adjusted first gridded emission list can be regarded as a localized emission list of the simulation area, and is referred to as a second gridded emission list in the invention.
As an embodiment, in step S102, adjusting the first gridded emissions list based on an error between the simulation result and the corresponding monitoring result includes: for each region within the simulation region: in the case that the simulation result of the area is higher than the corresponding monitoring result, reducing the discharge amount of each grid in the area in the first grid discharge list based on the error between the simulation result and the corresponding monitoring result; in the case where the simulation result of the area is lower than the monitoring result, the discharge amount of each grid in the area in the first gridded discharge list is increased based on an error between the simulation result and the corresponding monitoring result.
As an embodiment, the reducing or increasing the emission amount of each grid in the area in the first gridded emission list comprises: and reducing or increasing the discharge amount of each grid in the area in the first gridding discharge list in an equal proportion, wherein the reduced or increased proportion is positively correlated with the error. As an example, the simulation results are 15% higher (error) than the monitoring results, reducing the emissions of each grid in the area by 15%. As another example, the simulation results are 10% lower (error) than the monitoring results, increasing the emissions of each grid in the area by 10%. It should be understood that other ways of adjusting the data based on the error are also possible, and the error may also be determined based on different statistical methods, which is not limited by the embodiment.
As an embodiment, the simulation result of each area is an average value of grids corresponding to each monitored station in the area, and the corresponding monitoring result is an average value of each monitored station in the area. The grid is associated with the monitored site based on the geographic range covered by the grid and the geographic location of the monitored site. As an example, a region includes 10 monitored sites, the mean of the monitoring within the region can be an arithmetic average of the monitored values of the 10 monitored sites, and the mean of the simulation within the region can be an arithmetic average of the simulated values of the grid associated with the 10 monitored sites. The monitoring station may include a national control station, a provincial control station, a small mini station, and the like, which is not limited in this embodiment.
In step S102, the simulation result may include the concentration of one or more atmospheric pollutants, and the like. Accordingly, the monitoring results include the concentration of one or more atmospheric pollutants corresponding to the simulation results, and the like. In the case of multiple atmospheric pollutants, the error between the simulation result and the monitoring result corresponding to each pollutant can be determined separately, and the overall error is determined based on multiple errors, but the method is not limited thereto, and the error calculation can be performed by using a known statistical method.
Step S103, converting the second gridding emission list into emission source data, wherein the emission source data comprises an emission source, the position of the emission source and an emission parameter, and the emission parameter is obtained based on the emission amount corresponding to the gridding.
The position of the emission source includes longitude, latitude, altitude, and the like, and the altitude may be a ground clearance or an altitude. The emission parameter includes an emission amount.
The second gridding discharge list is a three-dimensional discharge list, and correspondingly, the discharge source data obtained through conversion is three-dimensional discharge source data. Namely the emission sources distributed in the three-dimensional space, the position of the emission sources in the three-dimensional space and the emission parameters of the emission sources.
As an embodiment, in step S103, converting the second gridded emission list into emission source data includes: and taking each grid in the second gridded emission list as an emission source to obtain emission source data, wherein each grid is taken as a source, a point source or a surface source. The position of the point source is the central point of the three-dimensional space corresponding to the grid, the position of the source is the three-dimensional space corresponding to the grid, and the position of the surface source is the plane corresponding to the grid. Therefore, a relatively complete urban emission source can be provided, and the problem of large simulation error caused by incomplete local emission lists is solved. In addition, each grid is used as an emission source, so that the processing complexity can be reduced, further the computing resources can be saved, the computing speed can be increased, and the processing complexity can be further reduced by using each grid as a point source. It should be understood that a plurality of grids may be used as one emission source, and the embodiment is not limited thereto.
The second gridded discharge list is a three-dimensional gridded discharge list, wherein the second gridded discharge list is divided into grid planes in the horizontal direction and is divided into multiple layers of grid planes in the vertical direction. Two meshes adjacent in the vertical direction may form a three-dimensional space. The position of the point source is the central point of the three-dimensional space corresponding to the grid, and the position of the source is the three-dimensional space corresponding to the grid.
As an embodiment, the emission source data of the target region is used in the pre-evaluation, and thus, a portion of the second gridded emission list corresponding to the target region is converted into the emission source data. That is, the emission source data is a portion corresponding to the target region. Thus, the data processing amount can be reduced.
Through steps S101 to S103, the list is iteratively adjusted through air quality models (any model) such as NAQPMS, CMAQ, WRF-CHEM, CAMx and the like, a complete and accurate gridding emission list of the target area is obtained, and the emission source data of the target area is further obtained through conversion. Thereafter the pre-evaluation phase is entered.
And step S104, inputting the emission source data and the data of one or more emission sources to be evaluated in the target area into a CALPUFF model together so as to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality.
As one example, the data of the emission source to be evaluated may include a major pollutant (SO) 2 、NO X Particulate matter, VOCs, etc.), emissions, chimney height, chimney diameter, flue gas temperature, flue gas flow rate, etc.
In step S104, when the contribution of the plurality of emission sources to be evaluated to the air quality is pre-evaluated, the emission source data and the data of the plurality of emission sources to be evaluated are input into the CALPUFF model together, and the contribution of the plurality of emission sources to be evaluated to the air quality is output by the CALPUFF model at the same time. And each emission source to be evaluated does not need to be pre-evaluated once respectively, so that the pre-evaluation timeliness is improved.
In atmospheric remediation, the influence of key pollution sources on the air quality of a city or a station is quantitatively simulated and forecasted, and the method further comprises the following steps: and generating a meteorological background field of a target forecast time interval of the target area. In the above step S104, the meteorological background field, the emission source data, and the data of one or more emission sources to be evaluated of the target area are input together into the CALPUFF model to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality of the target forecast period. The CALPUFF model is used for simulation and prediction to obtain the SO of each emission source to be evaluated for the city or the site 2 、NO 2 、PM 2.5 、PM 10 、CO、CO 2 The predicted value of the concentration of the pollutants is obtained; because the CALPUFF simulation has a complete background emission source, the secondary conversion is considered, and the simulation error can be greatly reduced. Meanwhile, only any air model such as NAQPMS, CMAQ, WRF-CHEM, CAMx and the like is needed to provide a background list through simulation, the air quality model is not used in actual simulation evaluation, and only a CALPUFF model is used, so that computing resources can be greatly saved, and timeliness is improved.
Compared with the traditional CALPUFF model simulation, the method and the device can solve the problem that the evaluation result is inaccurate due to incomplete input pollution sources in the environment evaluation. Meanwhile, compared with a WRF-CHEM-based large-scale point pollution source atmospheric environment influence evaluation method, the method provided by the embodiment of the invention can simulate the influence of a plurality of emission sources on the air quality at one time, and solves the problems of large calculation amount and poor timeliness. The discharge source data simulation stage has no timeliness requirement, and a CALPUFF model is used for simulation evaluation in the pre-evaluation stage, so that the calculation resources are greatly saved, and the timeliness is improved; and because a complete background emission source is input during CALPUFF model simulation, secondary conversion is considered during simulation, and the error is relatively small. Compared with the traditional method for simulating and predicting by directly using the CALPUFF model, the method does not need complete atmospheric pollution source general survey data, provides the emission source data of the gas-related heavy point source, can predict the influence of the CALPUFF model on the heavy point source, and can predict SO 2 、NO 2 、PM 2.5 、PM 10 、CO、CO 2 Has better forecasting effect.
Exemplary embodiments of the present invention also provide an apparatus for pre-evaluating the contribution of an emission source to air quality.
FIG. 2 shows a schematic block diagram of an apparatus for pre-evaluating the contribution of an emission source to air quality, according to an exemplary embodiment of the present invention, as shown in FIG. 2, including:
an obtaining module 210, configured to obtain a first gridded emission list based on a known emission list in a simulation region including a target region;
an adjusting module 220, configured to input the first grid emission list into a preset air quality model to perform air quality simulation, adjust the first grid emission list based on an error between a simulation result and a corresponding monitoring result, and repeat the simulation and the adjustment until the error between the simulation result and the monitoring result is smaller than a preset value, so as to obtain a second grid emission list in a simulation area, where the second grid emission list includes grids and emission amounts corresponding to the grids;
a conversion module 230, configured to convert the second grid emission list into emission source data, where the emission source data includes an emission source, a location of the emission source, and an emission parameter, and the emission parameter is obtained based on an emission amount corresponding to a grid;
an evaluation module 240 is configured to input the emission source data and data of one or more emission sources to be evaluated of the target area together into a CALPUFF model to pre-evaluate a contribution of the one or more emission sources to be evaluated to the air quality.
In some embodiments, further comprising: the meteorological module is used for generating a meteorological background field of a target forecast time interval of a target area; an evaluation module 240 for inputting the meteorological background field, the emission source data, and the data of one or more emission sources to be evaluated of the target area together into the CALPUFF model to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality of the target forecast period.
In some embodiments, the conversion module 230 is configured to convert a portion of the second gridded emissions manifest corresponding to the target area into the emissions source data.
In some embodiments, the adjustment module 220 adjusts the first gridded emissions list based on an error between the simulation results and the corresponding monitoring results, including:
for each region within the simulation region:
in the case that the simulation result of the area is higher than the corresponding monitoring result, reducing the discharge amount of each grid in the area in the first gridded discharge list based on the error between the simulation result and the corresponding monitoring result;
and in the case that the simulation result of the area is lower than the monitoring result, increasing the discharge amount of each grid in the area in the first gridded discharge list based on the error between the simulation result and the corresponding monitoring result.
In some embodiments, the adjusting module 220, for reducing or increasing the emissions of the grids in each area of the first gridded emissions list, includes:
and reducing or increasing the emission amount of each grid in each area in the first gridded emission list in an equal proportion, wherein the reduced or increased proportion is positively correlated with the error.
In some embodiments, the simulation result of each area is an average value of grids corresponding to each monitored station in the area, and the corresponding monitoring result is an average value of each monitored station in the area.
An exemplary embodiment of the present invention also provides an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor, the computer program, when executed by the at least one processor, is for causing the electronic device to perform a method according to an embodiment of the invention.
Exemplary embodiments of the present invention also provide a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor of a computer, is operable to cause the computer to perform a method according to an embodiment of the present invention.
Exemplary embodiments of the present invention also provide a computer program product comprising a computer program, wherein the computer program is operative, when executed by a processor of a computer, to cause the computer to perform a method according to an embodiment of the present invention.
Referring to fig. 3, a block diagram of a structure of an electronic device 300, which may be a server or a client of the present invention, which is an example of a hardware device that may be applied to aspects of the present invention, will now be described. Electronic device is intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 3, the electronic device 300 includes a computing unit 301 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)302 or a computer program loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the device 300 can also be stored. The calculation unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
A number of components in the electronic device 300 are connected to the I/O interface 305, including: an input unit 306, an output unit 307, a storage unit 308, and a communication unit 309. The input unit 306 may be any type of device capable of inputting information to the electronic device 300, and the input unit 306 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. Output unit 307 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, a video/audio output terminal, a vibrator, and/or a printer. The storage unit 308 may include, but is not limited to, a magnetic disk, an optical disk. The communication unit 309 allows the electronic device 300 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth devices, WiFi devices, WiMax devices, cellular communication devices, and/or the like.
The computing unit 301 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 301 performs the various methods and processes described above. For example, in some embodiments, the method of pre-evaluating the contribution of emission sources to air quality may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 300 via the ROM 302 and/or the communication unit 309. In some embodiments, the computing unit 301 may be configured in any other suitable manner (e.g., by way of firmware) to perform a method of pre-evaluating the contribution of emissions sources to air quality.
Program code for implementing the methods of the present invention may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
Claims (10)
1. A method of pre-evaluating the contribution of an emissions source to air quality, comprising:
acquiring a first gridding emission list based on a known emission list in a simulation area containing a target area;
inputting the first gridding discharge list into a preset air quality model for simulating air quality, adjusting the first gridding discharge list based on an error between a simulation result and a corresponding monitoring result, and repeating the simulation and adjustment until the error between the simulation result and the monitoring result is smaller than a preset value to obtain a second gridding discharge list in the simulation area, wherein the second gridding discharge list comprises grids and discharge amounts corresponding to the grids;
converting the second gridding emission list into emission source data, wherein the emission source data comprises an emission source, a position of the emission source and an emission parameter, and the emission parameter is obtained based on an emission amount corresponding to a grid;
inputting the emission source data and data of one or more emission sources to be evaluated of the target area into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality.
2. The method of claim 1, wherein converting the second gridded emissions manifest into emissions source data comprises:
and taking each grid in the second gridding discharge list as a discharge source to obtain the discharge source data, wherein each grid is taken as a source, a point source or a surface source, the position of the point source is the central point of the three-dimensional space corresponding to the grid, the position of the source is the three-dimensional space corresponding to the grid, and the position of the surface source is the plane corresponding to the grid.
3. The method of claim 1, further comprising:
generating a meteorological ambient field of the target region target forecast time interval;
inputting the emission source data and data of one or more emission sources to be evaluated of the target area into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality, wherein the method comprises the following steps:
inputting the meteorological background field, the emission source data and data of one or more emission sources to be evaluated of the target area into a CALPUFF model together to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality of the target forecast period.
4. The method of any of claims 1 to 3, wherein converting the second gridded emissions manifest into emissions source data comprises: and converting the part corresponding to the target area in the second gridding emission list into emission source data.
5. The method of claim 1, wherein adjusting the first gridded emissions list based on an error between a simulation result and a corresponding monitoring result comprises:
for each region within the simulation region:
in the case that the simulation result of the area is higher than the corresponding monitoring result, reducing the emission amount of each grid in the area in the first gridded emission list based on the error between the simulation result and the corresponding monitoring result;
and in the case that the simulation result of the area is lower than the monitoring result, increasing the discharge amount of each grid in the area in the first gridded discharge list based on the error between the simulation result and the corresponding monitoring result.
6. The method of claim 5, wherein reducing or increasing the emissions of each grid within the area in the first gridded emissions list comprises:
and reducing or increasing the emission amount of each grid in the area in the first gridded emission list in an equal proportion, wherein the reduced or increased proportion is positively correlated with the error.
7. The method according to claim 5 or 6, wherein the simulation result of each area is an average value of grids corresponding to each monitored site in the area, and the corresponding monitoring result is an average value of each monitored site in the area.
8. An apparatus for pre-evaluating the contribution of an emissions source to air quality, comprising:
the acquisition module is used for acquiring a first gridding emission list based on a known emission list in a simulation area containing a target area;
the adjusting module is used for inputting the first gridding discharge list into a preset air quality model for simulating air quality, adjusting the first gridding discharge list based on an error between a simulation result and a corresponding monitoring result, and repeating the simulation and adjustment until the error between the simulation result and the monitoring result is smaller than a preset value to obtain a second gridding discharge list in the simulation area, wherein the second gridding discharge list comprises grids and discharge amounts corresponding to the grids;
the conversion module is used for converting the second gridding emission list into emission source data, wherein the emission source data comprises an emission source, the position of the emission source and an emission parameter, and the emission parameter is obtained based on the emission amount corresponding to a grid;
and the evaluation module is used for inputting the emission source data and the data of one or more emission sources to be evaluated of the target area into a CALPUFF model together so as to pre-evaluate the contribution of the one or more emission sources to be evaluated to the air quality.
9. An electronic device, comprising:
a processor; and
a memory for storing a program, wherein the program is stored in the memory,
wherein the program comprises instructions which, when executed by the processor, cause the processor to carry out the method according to any one of claims 1-7.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method according to any one of claims 1-7.
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