CN112988940A - Pollution tracing method and device - Google Patents
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Abstract
The invention discloses a pollution tracing method and a pollution tracing device. The method comprises the following steps: inputting air quality forecast data into an air mass track tracing model, and calculating to obtain backward diffusion tracks of the selected point location at different heights at a preset moment after a preset duration; extracting longitude and latitude data sets of all heights on the backward diffusion track, and drawing a trajectory line according to all the heights and the corresponding longitude and latitude data sets; and screening out the pollution sources of which the distance between the distance and the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, and obtaining the emission information of the pollution sources around the track. The device comprises a diffusion track calculating unit, a track line drawing unit and a pollution source screening unit. The method and the device combine the respective advantages of the backward trajectory method and the pollution source information method to link the results, further scientifically focus the pollution source tracing result, and provide guidance and direction for subsequent pollution prevention and control work.
Description
Technical Field
The invention relates to the technical field of atmospheric pollution tracing and control, in particular to a pollution tracing method and a pollution tracing device.
Background
In recent years, the air quality in China is obviously improved, pollution control work gradually develops towards refinement and differentiation along with the reduction of the concentration of pollutants, and higher requirements are placed on the tracing mode and accuracy of pollution sources.
Currently, the common tracing methods for pollution sources mainly include: the method comprises a pollution source emission inventory method, a numerical model simulation method, a receptor model analysis method and the like, wherein the numerical model simulation method takes a second-generation atmospheric diffusion model and a third-generation air quality numerical model as common modes, and in addition, the numerical model simulation method is an air mass diffusion model method which is simplified by neglecting a physical and chemical conversion process in pollution transmission.
The atmospheric diffusion model is one of important tools for atmospheric pollution control, and aims to research the rules of diffusion, conversion, migration and removal of air pollutants discharged into the atmosphere, and the modes for describing the atmospheric diffusion rules at present are mainly classified into 3 types, including: a modified gaussian plume diffusion model, an euler diffusion model, and a lagrange diffusion model.
Although the existing tracing methods for the pollution sources are various, the various methods respectively occupy one place, and the analysis results have different indications on the areas, industries and the like of the pollution sources. At present, the practice of tracing the pollution source by combining a plurality of types of methods is lacked, so the advantages of the methods cannot be well combined, and the development of fine tracing cannot be rapidly advanced.
Disclosure of Invention
The invention innovatively provides a pollution tracing method and device, which combines a backward track result and pollution source information to realize more refined and accurate pollution tracing.
In order to achieve the above technical object, in one aspect, the present invention discloses a pollution tracing method, including: inputting air quality forecast data into an air mass track tracing model, and calculating to obtain backward diffusion tracks of the selected point positions at different heights at preset time through preset duration; extracting longitude and latitude data sets of all altitudes on the backward diffusion track, and drawing a trajectory line according to all altitudes and the corresponding longitude and latitude data sets; and screening out the pollution sources of which the distance from the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, so as to obtain the emission information of the pollution sources around the track.
Further, after the pollution source whose distance from the drawn trajectory line is smaller than the preset length is screened out, the pollution source tracing method further includes: and sequencing the screened pollution sources according to the discharge amount from large to small.
Further, for the pollution tracing method, the air quality forecast data comprises an output result of a weather forecast mode and/or forecast data of a global forecast system.
Further, for the pollution tracing method, the air mass trajectory tracing model may include a gaussian plume diffusion model, an euler diffusion model, a lagrangian diffusion model, or a derivative model based on the gaussian plume diffusion model, the euler diffusion model and/or the lagrangian diffusion model.
Further, for the pollution tracing method, the derivative model of the lagrangian diffusion model comprises a mixed particle lagrangian integral trajectory model.
In another aspect, the present invention discloses a pollution tracing apparatus, which includes: the diffusion track calculation unit is used for inputting the air quality forecast data into the air mass track tracing model and calculating to obtain backward diffusion tracks of the selected point positions at different heights at the preset moment through the preset duration; the trajectory drawing unit is used for extracting longitude and latitude data sets of all the heights on the backward diffusion trajectory and drawing a trajectory according to all the heights and the corresponding longitude and latitude data sets; and the pollution source screening unit is used for screening the pollution sources of which the distance from the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, so that the emission information of the pollution sources around the track is obtained.
Further, the pollution tracing apparatus further comprises: and the sorting unit is used for sorting the screened pollution sources according to the discharge amount from large to small.
Further, for the pollution tracing apparatus, the air mass trajectory tracing model may include a gaussian plume diffusion model, an euler diffusion model, a lagrangian diffusion model, or a derivative model based on the gaussian plume diffusion model, the euler diffusion model and/or the lagrangian diffusion model.
To achieve the above technical object, in yet another aspect, the present invention discloses a computing device. The computing device includes: one or more processors, and a memory coupled with the one or more processors, the memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the above-described method.
To achieve the above technical objects, in yet another aspect, the present invention discloses a machine-readable storage medium. The machine-readable storage medium stores executable instructions that, when executed, cause the machine to perform the above-described method.
The invention has the beneficial effects that:
in the existing common pollution tracing method, the Hysplit backward trajectory method can only provide a source path of a polluted air mass, and the control measure can only determine a rough control direction according to the result, but does not achieve the purpose of precise control. Information obtained through the pollution source discharge list and/or the pollution source census data can only be collated to obtain the key large-discharge pollution source results of the whole area, but the pollution sources do not influence pollution of a certain time, so that the purpose of scientific pollution control cannot be achieved only through the pollution source discharge list and/or the pollution source census data. The pollution tracing method and the device provided by the embodiment of the invention combine the respective advantages of the backward trajectory method and the pollution source information method, link the results, further refine and scientifically focus the pollution tracing result, and further provide guidance and direction for subsequent pollution prevention and control work.
Drawings
In the figure, the position of the upper end of the main shaft,
FIG. 1 is a flowchart of a pollution tracing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of a pollution tracing method according to an exemplary embodiment of the present invention;
fig. 3 is a schematic structural diagram of a pollution tracing apparatus according to another embodiment of the present invention;
FIG. 4 is a block diagram of a computing device for pollution tracing according to an embodiment of the present invention.
Detailed Description
The pollution tracing method and the device provided by the invention are explained and explained in detail below with reference to the drawings of the specification.
Fig. 1 is a flowchart of a pollution tracing method according to an embodiment of the present invention. FIG. 2 is a flow chart of a pollution tracing method according to an embodiment of the present invention.
As shown in fig. 1 and 2, in step S110, the air quality prediction data is input into the air mass trajectory tracing model, and a backward diffusion trajectory of the selected point location at the preset time at different heights through the preset duration is calculated. The height and the preset duration of the air mass at the selected point position can be configured in the model input parameters at will.
The air quality Forecast data may include output results of a Weather Forecast mode (WRF), and/or Forecast data of a Global Forecast System (GFS).
The air mass trajectory tracing model can comprise a Gaussian plume diffusion model, an Euler diffusion model and a Lagrange diffusion model, or various derivative models based on the Gaussian plume diffusion model, the Euler diffusion model and/or the Lagrange diffusion model. The input data may vary depending on the model selected. The derivative Model of the Lagrangian diffusion Model may include a Hybrid Particle Lagrangian integration Trajectory Model (Hysplit, Hybrid Single-Particle Lagrangian integration Trajectory Model). The HYSPLIT model is also called a backward trajectory model, can calculate not only the deposition of pollutant concentration diffusion, but also the motion trajectory of single pollutant particles, and is one of the most widely used atmospheric transmission and diffusion models in the current atmospheric science community. The HYSPLIT model can be used for calculating the source and destination track results of the air mass with different heights at a specific point, and the method has a considerable guiding effect on pollution tracing.
In step S120, longitude and latitude data sets of the respective altitudes on the backward diffusion trajectory are extracted, and trajectory lines are drawn according to the respective altitudes and the corresponding longitude and latitude data sets.
In step S130, according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source census, the pollution source whose distance from the drawn trajectory line is smaller than the preset length is screened out, so as to obtain the emission information of the pollution source around the trajectory. Wherein the distance between the pollution source and the plotted trajectory line is the minimum distance between the pollution source and the plotted trajectory line. The information can be stored in a database according to a certain format through various pollution source data obtained by sorting a pollution source emission list and/or pollution source general survey. The preset length can be set by a user.
The emission list of pollution sources is the emission of one or more pollutant emission sources in a certain areaThe amount is estimated, and a complete set of the atmospheric pollutant emission list should cover the emission sources of fossil fuel fixed burning, process, mobile source, solvent use, open raise dust, biomass burning, agriculture and the like, and the emission sources comprise sulfur dioxide (SO)2) Nitrogen oxides (NOx), carbon monoxide (CO), Volatile Organic Compounds (VOCs), and ammonia (NH)3) Primary Particulate Matter (PM)2.5And PM10) And ozone (O)3) And the like, and is provided with a dynamic updating mechanism. A large amount of preliminary investigation work is needed to compile a pollution source emission list, the preliminary investigation work comprises basic information of various pollution sources in a compiled area, production activity modes/environments, production activity yield and other data, so that the emission of different pollutants by the pollution sources is obtained through calculation, and the investigation can be further developed on the basis of pollution source general survey results. And a pollution source discharge basic database can be established by combining basic survey data of point sources, line sources and surface sources when a discharge list is compiled.
As an alternative implementation, after screening out the pollution source whose distance from the plotted trajectory line is less than the preset length, the pollution tracing method of this embodiment may further include the steps of: and sequencing the screened pollution sources according to the discharge amount from large to small. After the pollution sources are sequenced according to the emission amount, the emission sources to be managed and controlled mainly, such as information of a certain enterprise, a certain construction site and the like, can be obtained according to the emission amount screening, so that the aims of precise management and control and scientific pollution control are fulfilled.
Fig. 3 is a schematic structural diagram of a pollution tracing apparatus according to another embodiment of the present invention. As shown in fig. 3, the pollution tracing apparatus 300 according to this embodiment includes a diffusion trace calculating unit 310, a trace drawing unit 320, and a pollution source screening unit 330.
The diffusion trajectory calculation unit 310 is configured to input the air quality prediction data into the air mass trajectory tracing model, and calculate a backward diffusion trajectory of the selected point location at the preset time at different heights through a preset duration. The air quality forecast data may include the output of the WRF and/or forecast data of the GFS, among others. The air mass trajectory tracing model can comprise a Gaussian plume diffusion model, an Euler diffusion model and a Lagrange diffusion model, or various derivative models based on the Gaussian plume diffusion model, the Euler diffusion model and/or the Lagrange diffusion model. The input data may vary depending on the model selected. The derivative Model of the Lagrangian diffusion Model may include a Hybrid Particle Lagrangian integration Trajectory Model (Hysplit, Hybrid Single-Particle Lagrangian integration Trajectory Model). The operation of the diffusion trace calculating unit 310 may refer to the operation of step S110 described above with reference to fig. 1.
The trajectory line drawing unit 320 is configured to extract longitude and latitude data sets of each altitude on the back diffusion trajectory, and draw a trajectory line according to each altitude and the corresponding longitude and latitude data set. The operation of the diffusion trace line drawing unit 320 may refer to the operation of step S120 described above with reference to fig. 1.
The pollution source screening unit 330 is configured to screen out a pollution source whose distance from the drawn trajectory line is smaller than a preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source census, so as to obtain the emission information of the pollution source around the trajectory. The operation of the pollution source screening unit 330 may refer to the operation of step S130 described above with reference to fig. 1.
As an optional implementation manner, the pollution tracing apparatus 300 of this embodiment may further include a sorting unit configured to sort the screened pollution sources according to the emission amount from large to small. After the pollution sources are sequenced according to the emission amount, the emission sources to be managed and controlled mainly, such as information of a certain enterprise, a certain construction site and the like, can be obtained according to the emission amount screening, so that the aims of precise management and control and scientific pollution control are fulfilled.
In the existing common pollution tracing method, the Hysplit backward trajectory method can only provide a source path of a polluted air mass, and the control measure can only determine a rough control direction according to the result, but does not achieve the purpose of precise control. Information obtained through the pollution source discharge list and/or the pollution source census data can only be collated to obtain the key large-discharge pollution source results of the whole area, but the pollution sources do not influence pollution of a certain time, so that the purpose of scientific pollution control cannot be achieved only through the pollution source discharge list and/or the pollution source census data. The pollution tracing method and the device provided by the embodiment of the invention combine the respective advantages of the backward trajectory method and the pollution source information method, link the results, further refine and scientifically focus the pollution tracing result, and further provide guidance and direction for subsequent pollution prevention and control work.
FIG. 4 is a block diagram of a computing device for pollution tracing according to an embodiment of the present invention.
As shown in fig. 3, computing device 400 may include at least one processor 410, storage 420, memory 430, communication interface 440, and internal bus 450, and at least one processor 410, storage 420, memory 430, and communication interface 440 are connected together via bus 450. The at least one processor 410 executes at least one computer-readable instruction (i.e., an element described above as being implemented in software) stored or encoded in a computer-readable storage medium (i.e., memory 420).
In one embodiment, computer-executable instructions are stored in the memory 420 that, when executed, cause the at least one processor 410 to perform: inputting air quality forecast data into an air mass track tracing model, and calculating to obtain backward diffusion tracks of the selected point positions at different heights at preset time through preset duration; extracting longitude and latitude data sets of all altitudes on the backward diffusion track, and drawing a trajectory line according to all altitudes and the corresponding longitude and latitude data sets; and screening out the pollution sources of which the distance from the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, so as to obtain the emission information of the pollution sources around the track.
It should be understood that the computer-executable instructions stored in the memory 420, when executed, cause the at least one processor 410 to perform the various operations and functions described above in connection with fig. 1-3 in the various embodiments of the present disclosure.
In the present disclosure, computing device 400 may include, but is not limited to: personal computers, server computers, workstations, desktop computers, laptop computers, notebook computers, mobile computing devices, smart phones, tablet computers, cellular phones, Personal Digital Assistants (PDAs), handheld devices, messaging devices, wearable computing devices, consumer electronics, and so forth.
According to one embodiment, a program product, such as a non-transitory machine-readable medium, is provided. A non-transitory machine-readable medium may have instructions (i.e., elements described above as being implemented in software) that, when executed by a machine, cause the machine to perform various operations and functions described above in connection with fig. 1-3 in various embodiments of the present disclosure.
Specifically, a system or apparatus may be provided which is provided with a readable storage medium on which software program code implementing the functions of any of the above embodiments is stored, and causes a computer or processor of the system or apparatus to read out and execute instructions stored in the readable storage medium.
In this case, the program code itself read from the readable medium can realize the functions of any of the above-described embodiments, and thus the machine-readable code and the readable storage medium storing the machine-readable code form part of the present invention.
Examples of the readable storage medium include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-R, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs), magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer or from the cloud via a communications network.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the claims, and all equivalent structures or equivalent processes that are transformed by the content of the specification and the drawings, or directly or indirectly applied to other related technical fields are included in the scope of the claims.
Claims (10)
1. A pollution tracing method, comprising:
inputting air quality forecast data into an air mass track tracing model, and calculating to obtain backward diffusion tracks of the selected point positions at different heights at preset time through preset duration;
extracting longitude and latitude data sets of all altitudes on the backward diffusion track, and drawing a trajectory line according to all altitudes and the corresponding longitude and latitude data sets;
and screening out the pollution sources of which the distance from the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, so as to obtain the emission information of the pollution sources around the track.
2. The pollution tracing method according to claim 1, wherein after screening out the pollution source whose distance from the plotted trajectory is less than a preset length, the method further comprises:
and sequencing the screened pollution sources according to the discharge amount from large to small.
3. The pollution tracing method according to claim 1, wherein the air quality forecast data includes an output result of a weather forecast mode and/or forecast data of a global forecast system.
4. The pollution tracing method according to any one of claims 1-3, wherein the air mass trajectory tracing model may include a Gaussian plume diffusion model, an Euler diffusion model, a Lagrangian diffusion model, or a derivative model based on the Gaussian plume diffusion model, the Euler diffusion model and/or the Lagrangian diffusion model.
5. The pollution tracing method of claim 4, wherein the derivative model of the Lagrangian diffusion model comprises a mixed particle Lagrangian integral trajectory model.
6. A pollution tracing apparatus, comprising:
the diffusion track calculation unit is used for inputting the air quality forecast data into the air mass track tracing model and calculating to obtain backward diffusion tracks of the selected point positions at different heights at the preset moment through the preset duration;
the trajectory drawing unit is used for extracting longitude and latitude data sets of all the heights on the backward diffusion trajectory and drawing a trajectory according to all the heights and the corresponding longitude and latitude data sets;
and the pollution source screening unit is used for screening the pollution sources of which the distance from the drawn track line is less than the preset length according to the emission height and the position information of each pollution source obtained from the pollution source emission list and/or the pollution source general survey, so that the emission information of the pollution sources around the track is obtained.
7. The pollution traceability device of claim 6, further comprising: and the sorting unit is used for sorting the screened pollution sources according to the discharge amount from large to small.
8. The pollution tracing apparatus according to claim 6 or 7, wherein the air mass trajectory tracing model comprises a Gaussian plume diffusion model, an Euler diffusion model, a Lagrangian diffusion model, or a derivative model based on the Gaussian plume diffusion model, the Euler diffusion model and/or the Lagrangian diffusion model.
9. A computing device, comprising:
one or more processors, and
a memory coupled with the one or more processors, the memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-5.
10. A machine-readable storage medium having stored thereon executable instructions that, when executed, cause the machine to perform the method of any one of claims 1 to 5.
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Family Cites Families (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006105805A (en) * | 2004-10-06 | 2006-04-20 | Matsushita Electric Ind Co Ltd | Trajectory data management device and program |
CN106295905A (en) * | 2016-08-22 | 2017-01-04 | 南京大学 | A kind of air quality based on Lagrange conveying model is quickly traced to the source forecasting procedure |
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GB202201846D0 (en) * | 2019-08-14 | 2022-03-30 | Innovation Center For Clean Air Solutions | Method for selecting pollutant treatment measure |
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-
2021
- 2021-04-02 CN CN202110362245.9A patent/CN112988940A/en active Pending
-
2022
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