CN115965510A - Pollutant real-time tracing method and device and electronic equipment - Google Patents
Pollutant real-time tracing method and device and electronic equipment Download PDFInfo
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Abstract
The disclosure provides a real-time tracing method and device for pollutants and electronic equipment, which can be applied to the technical field of pollution prevention and tracing. The method comprises the following steps: determining n first target grids and m second target grids from preset grids according to monitoring values of preset monitoring sites and a preset meteorological model; determining I third target grids from preset grids according to the n first target grids and the m second target grids; correspondingly obtaining I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model; correspondingly obtaining I monitoring concentrations of the target pollutants according to the I third target grids and monitoring values of preset monitoring sites; obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and determining a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
Description
Technical Field
The present disclosure relates to the field of pollution prevention and traceability technologies, and in particular, to a method and an apparatus for tracing a pollutant in real time, and an electronic device.
Background
With the development of urbanization and industrialization, pollution sources are concentrated in urban clusters and industrial parks, and pollutants generated by the pollution sources are transmitted in the urban clusters and the industrial parks through the atmosphere. The transported contaminants adversely affect the health of people in urban communities and industrial parks, as well as the surrounding environment. How to quickly and accurately determine the position of a pollution source so as to monitor the pollution source and treat the pollution is more and more concerned.
According to pollutant emission data, a meteorological numerical model and a particle diffusion model are combined to obtain backward traceability data of pollutants, and the pollutants can be traced. However, the common meteorological numerical model is generally a mesoscale meteorological numerical model, and the analysis scale of the pollution tracing method based on the mesoscale meteorological numerical model is relatively large, and is not suitable for tracing the pollution source under the condition of small microscale.
Disclosure of Invention
In view of the above, a primary objective of the present disclosure is to provide a method, an apparatus and an electronic device for tracing a source of a pollutant in real time, so as to solve at least one of the above mentioned technical problems.
In order to achieve the above object, an aspect of the present disclosure provides a real-time tracing method for pollutants. The real-time tracing method for pollutants comprises the following steps:
determining n first target grids from preset grids according to monitoring values of preset monitoring sites and a preset meteorological model, wherein n is a positive integer; determining m second target grids from the preset grids according to the monitoring values of the preset monitoring stations, wherein m is a positive integer; determining I third target grids from the preset grids according to the n first target grids and the m second target grids, wherein I is a positive integer; correspondingly obtaining I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model; correspondingly obtaining I monitoring concentrations of the target pollutants according to the I third target grids and the monitoring values of the preset monitoring sites; obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and determining a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
According to an embodiment of the present disclosure, the determining n first target grids from the preset grid according to the monitoring value of the preset monitoring station and the preset meteorological model includes:
obtaining the real-time position of the target pollutant according to the monitoring value of the preset monitoring station; determining a backward propagation time period and a backward propagation range of the target pollutant through the particle diffusion model according to the real-time position of the target pollutant and the preset meteorological model; and determining the n first target grids from preset grids according to the backward propagation range of the target pollutants and the first precision grid.
According to an embodiment of the present disclosure, the determining m second target grids from the preset grids according to the monitoring values of the preset monitoring stations includes:
obtaining target monitoring data according to the monitoring value of the preset monitoring station, wherein the target monitoring data comprises the monitoring data of the target pollutant of the preset monitoring station in the backward propagation time period of the target pollutant; and determining the m second target grids from the preset grids according to the target monitoring data.
According to an embodiment of the present disclosure, the determining I third target grids from the preset grids according to the n first target grids and the m second target grids includes:
and determining an overlapped area in the preset grid as the third target grid under the condition that the n first target grids and the m second target grids are overlapped on the preset grid correspondingly.
According to an embodiment of the present disclosure, the obtaining an ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitored concentration includes:
obtaining an ith contribution value according to the ith staying time period and the ith monitoring concentration; obtaining a total contribution value according to the ith contribution value; and obtaining the ith contribution ratio according to the ith contribution value and the total contribution value.
According to an embodiment of the present disclosure, the determining the fourth target grid according to the ith contribution ratio includes:
and determining the third target grid corresponding to the ith contribution ratio meeting the preset condition as the fourth target grid.
According to an embodiment of the present disclosure, further comprising:
and dividing preset areas according to the preset monitoring stations to obtain the preset grids.
According to an embodiment of the present disclosure, further comprising:
and determining the preset meteorological model according to the meteorological numerical model and the preset grid.
Another aspect of the present disclosure provides a real-time tracing apparatus for pollutants, including:
the system comprises a first determining module, a second determining module and a monitoring module, wherein the first determining module is used for determining n first target grids from preset grids according to monitoring values of preset monitoring sites and a preset meteorological model, and n is a positive integer; a second determining module, configured to determine m second target grids from the preset grids according to the monitoring values of the preset monitoring stations, where m is a positive integer; a third determining module, configured to determine I third target grids from the preset grids according to the n first target grids and the m second target grids, where I is a positive integer; the first acquisition module is used for correspondingly acquiring I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model; a second obtaining module, configured to correspondingly obtain I monitoring concentrations of the target pollutants according to the I third target grids and the monitoring values of the preset monitoring stations; the calculation module is used for obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and a fourth determining module, configured to determine a fourth target grid from the preset grids according to the ith contribution ratio, where the fourth target grid represents a source location corresponding to the target pollutant.
Yet another aspect of the present disclosure provides an electronic device. The electronic device includes:
one or more processors; a storage device for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform any of the above-described methods.
Based on the technical scheme, compared with the prior art, the embodiment of the disclosure has the following beneficial effects:
and predicting a first range corresponding to the target pollutant in the preset grid according to the preset grid and the preset meteorological model and the monitoring value of the preset monitoring station, and determining the first range as a first target grid. And determining a second range corresponding to the actually measured target pollutant in the preset grid according to the monitoring value of the preset monitoring station, and determining the second range as a second target grid. And determining a third target grid according to the first target grid and the second target grid, wherein the third target grid can more accurately represent a third range corresponding to the pollutant. And acquiring the contribution ratio of the target pollutant in the area corresponding to the third target grid according to the monitoring value of the preset monitoring station, the preset meteorological model and the particle diffusion model, quantifying the influence of the target pollutant in the third target grid, and determining the fourth target grid according to the contribution ratio of the target pollutant. The fourth target grid represents the source position corresponding to the target pollutant, and the rapid and accurate tracing of the target pollutant can be realized through a real-time tracing method of the pollutant.
Drawings
Fig. 1 schematically shows a system architecture diagram of a real-time contaminant tracing method according to an embodiment of the present disclosure.
Fig. 2 schematically shows a flowchart of a real-time tracing method of pollutants according to an embodiment of the present disclosure.
Fig. 3 schematically illustrates a block diagram of a real-time contaminant tracing apparatus according to an embodiment of the present disclosure.
Fig. 4 schematically illustrates a block diagram of an electronic device suitable for implementing a real-time contaminant tracing method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction should be interpreted in the sense one having ordinary skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B, a and C, B and C, and/or A, B, C, etc.).
In the course of implementing the disclosed concept, it was found that at least the following problems exist:
the meteorological numerical model is a mesoscale meteorological numerical model, and the pollutant tracing method based on the mesoscale meteorological numerical model has relatively large analysis scale and is not suitable for tracing the pollution source under the condition of small microscale. In addition, the traceability method based on the emission source inventory data, the mesoscale meteorological numerical model and the particle diffusion model cannot realize the quantitative traceability analysis of the emission data combined with the local area.
In order to at least partially solve the existing technical problems, the disclosure provides a method and a device for tracing the source of pollutants in real time and electronic equipment, which can be applied to the technical field of pollution prevention and tracing. The real-time tracing method for pollutants comprises the following steps: determining n first target grids from preset grids according to monitoring values of preset monitoring sites and a preset meteorological model, wherein n is a positive integer; determining m second target grids from preset grids according to the monitoring values of preset monitoring stations, wherein m is a positive integer; determining I third target grids from preset grids according to the n first target grids and the m second target grids, wherein I is a positive integer; correspondingly obtaining I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model; correspondingly obtaining I monitoring concentrations of the target pollutants according to the I third target grids and monitoring values of preset monitoring sites; obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and determining a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
Fig. 1 schematically shows a system architecture diagram of a real-time contaminant tracing method according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in FIG. 1, a system architecture 100 according to this embodiment may include; monitoring devices 101, 102, 103, network 104, server 105. The network 104 is used to provide a medium for communication links between the monitoring devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.
The monitoring devices 101, 102, 103 may be a variety of monitoring devices that acquire pre-set regional pollutant emission data.
The server 105 may be a server providing various services, such as a background server (for example only) providing data processing support for the pre-set area pollutant emission data acquired by the monitoring devices 101, 102, 103. The background server can analyze and the like the received pollutant emission data to obtain a pollutant real-time tracing result, and feeds back the pollutant real-time tracing result to other equipment through the network 104, so that the pollutant real-time tracing result can be displayed through the other equipment.
Fig. 2 schematically shows a flowchart of a real-time tracing method of pollutants according to an embodiment of the present disclosure.
As shown in fig. 2, the method for tracing the source of the pollutant in real time includes operations S210 to S270.
In operation S210, n first target grids are determined from the preset grids according to the monitoring values of the preset monitoring stations and the preset meteorological model, where n is a positive integer.
In operation S220, m second target grids are determined from the preset grids according to the monitoring values of the preset monitoring stations, where m is a positive integer.
In operation S230, I third target grids are determined from the preset grids according to the n first target grids and the m second target grids, where I is a positive integer.
In operation S240, I residence time periods of the target pollutant are correspondingly obtained according to I third target grids and the particle diffusion model.
In operation S250, I monitoring concentrations of the target pollutants are correspondingly obtained according to the I third target grids and the monitoring values of the preset monitoring sites.
In operation S260, an ith contribution ratio of the target pollutant is obtained according to the ith staying time period and the ith monitored concentration, wherein i is an integer belonging to [1,I ].
In operation S270, a fourth target mesh is determined from the preset meshes according to the ith contribution ratio, where the fourth target mesh represents a source location corresponding to the target pollutant.
According to the embodiment of the invention, the monitoring value of the target pollutant can be obtained based on the preset monitoring station. The target pollutant may be monitored based on any type of monitoring station in the related art, for example, the target pollutant may be monitored based on an atmospheric pollution fixed monitoring station, a mini station or a micro station, but is not limited thereto, and the target pollutant may also be monitored by using other types of monitoring stations to obtain a monitoring value of the target pollutant. The embodiment of the present disclosure does not limit the specific manner of monitoring the target pollutant, and those skilled in the art can design the monitoring mode according to actual needs.
According to the embodiment of the invention, the preset area can be subjected to grid division based on the size of the preset area and the position of the preset monitoring station, so that the preset grid is obtained. For example, a city cluster or an industrial park may be used as a preset area, and the preset area is divided into preset grids according to the scale accuracy required by actual monitoring. The embodiment of the present disclosure does not limit the specific manner of dividing the preset area into the preset grids, and those skilled in the art can design the preset area according to actual requirements.
According to the embodiment of the invention, the preset meteorological model can be obtained based on the meteorological numerical model. The meteorological numerical model may comprise a mesoscale meteorological numerical model for simulating or forecasting mesoscale regional atmospheric circulation. The mesoscale region is the region scale within the horizontal scale of 20-200 km on the earth surface and the scale of 2-20 km vertical to the earth surface. The scale of the mesoscale meteorological numerical model can be refined to obtain the preset meteorological model.
According to the embodiment of the invention, a Weather forecast model (Weather Research and Forecasting model, WRF) can be selected as a mesoscale meteorological numerical model in practical use. The embodiment of the disclosure does not limit the model type of the mesoscale meteorological numerical model, and a person skilled in the art can select the mesoscale meteorological numerical model according to actual needs.
According to the embodiment of the invention, the particle diffusion model is a simulation model for realizing the transportation and diffusion process of the atmospheric substance according to the motion trail of the gas block group. An air mass may refer to an infinitely small air mass. The particle diffusion model may include two lagrangian particle diffusion modes, FLEXPART and HYSPLIT. The long-time period and the mesoscale transportation, diffusion, dry-wet sedimentation and radiation attenuation processes of the target pollutants can be simulated based on the particle diffusion model. The forward trajectory simulation of the particle diffusion model in time can be used to simulate the trajectory of the pollution source corresponding to the target pollutant, i.e. the diffusion process of the target pollutant. The time backward trajectory of the particle diffusion model can simulate the influence area of the pollution source corresponding to the target pollutant. The embodiment of the present disclosure does not limit the model type of the particle diffusion model, and a person skilled in the art can select the model type according to actual needs.
According to the embodiment of the invention, the backward propagation range of the target pollutant can be simulated and obtained through the particle diffusion model based on the monitoring value of the target pollutant and the preset meteorological model. And determining the backward propagation range of the target pollutant as n first target grids at the corresponding position of the preset grid.
According to the embodiment of the invention, the backward propagation time period of the target pollutant can be obtained in the process of the backward propagation range of the target pollutant. The m second target grids can be determined according to monitoring values of preset monitoring stations corresponding to the time period of backward propagation of the target pollutants.
According to the embodiment of the invention, after I third target grids are determined, I staying time periods and I monitoring concentrations of target pollutants can be obtained through a preset meteorological model and a particle diffusion model according to the monitoring values of preset monitoring sites.
According to the embodiment of the invention, the first target grid corresponding to the target pollutant is determined by presetting the monitoring value of the monitoring station. And determining a second target grid corresponding to the actually measured target pollutant in the preset grid through presetting the monitoring value of the monitoring station. And determining a third target grid according to the first target grid and the second target grid, wherein the third target grid can more accurately represent a third range corresponding to the pollutant. And acquiring the contribution ratio of the target pollutant in the area corresponding to the third target grid according to the monitoring value of the preset monitoring station, the preset meteorological model and the particle diffusion model, quantifying the influence of the target pollutant in the third target grid, and further determining the fourth target grid according to the contribution ratio of the target pollutant. The fourth target grid represents the source position corresponding to the target pollutant, and the rapid and accurate tracing of the target pollutant can be realized through a real-time tracing method of the pollutant.
According to the embodiment of the invention, the tracing method further comprises the following operations:
and dividing the preset area according to the preset monitoring station to obtain the preset grid.
According to the embodiment of the invention, the preset area can be divided into the preset grids according to the position of the preset monitoring station actually existing in the urban cluster or the industrial park and the scale precision required by actual monitoring.
As shown in fig. 1, for the preset grid on the left side of fig. 1, the warps and the wefts may be used as side lines for dividing the preset grid, and the preset monitoring sites may be unevenly distributed at the intersections of the warps and the wefts.
According to the embodiment of the invention, for example, the preset monitoring stations arranged in the area where the discharged pollutants are concentrated can be set in a city cluster or an industrial park, and the density of the preset monitoring stations arranged in the area where the discharged pollutants are dispersed can be higher than that of the preset monitoring stations.
According to an embodiment of the invention, for example, the lengths of the warp and weft threads of a preset grid with a side length of 0.2 to 0.6 ° may be set. The embodiment of the present disclosure does not limit the side length of the preset grid, that is, the size of the preset grid, and those skilled in the art can select the side length according to actual needs.
According to an embodiment of the present invention, the tracing method further includes:
and determining a preset meteorological model according to the weather forecast model and the preset grid.
According to the embodiment of the invention, the size precision of the weather forecast model can be correspondingly modified into the size precision of the preset grid, so that the preset meteorological model is obtained.
According to the embodiment of the invention, the preset area is divided into the preset grids with small size precision according to the position of the preset monitoring station which actually exists and the scale precision required by actual monitoring, so that the preset meteorological model with small size precision can be obtained. And performing precision division based on the position of the actually existing preset monitoring station to obtain a preset meteorological model, wherein when the backward propagation range of the target pollutant is predicted based on the monitoring value of the preset monitoring station, the corresponding relation between the preset meteorological model and the actual data is more accurate, and the accuracy of the real-time pollutant tracing method can be improved.
According to the embodiment of the invention, the step of determining n first target grids from the preset grids according to the monitoring values of the preset monitoring stations and the preset meteorological model comprises the following steps:
obtaining the real-time position of the target pollutant according to the monitoring value of a preset monitoring station; and determining the backward propagation time period and the backward propagation range of the target pollutant through the particle diffusion model according to the real-time position of the target pollutant and the preset meteorological model. And determining n first target grids from the preset grids according to the backward propagation range of the target pollutants and the first precision grids.
As shown in fig. 1, a location marked with a pentagon shape may be set as a tracing point with respect to the preset grid on the left side of fig. 1. And (4) presetting a monitoring value obtained by a monitoring station near the source tracing point at the moment t as the monitoring value of the current moment, wherein t is a positive integer.
According to the embodiment of the invention, the air mass range of the backward target pollutant is obtained by predicting the preset meteorological model and combining the particle diffusion model according to the obtained monitoring value at the current moment. And corresponding the air mass range of the backward target pollutant to a preset grid, and determining n first target grids from the preset grid.
According to the embodiment of the invention, the determining m second target grids from the preset grids according to the monitoring values of the preset monitoring stations comprises the following steps:
and obtaining target monitoring data according to the monitoring value of the preset monitoring station, wherein the target monitoring data comprises the monitoring data of the target pollutant of the preset monitoring station in the backward propagation time period of the target pollutant. And determining m second target grids from the preset grids according to the target monitoring data.
According to the embodiment of the invention, under the condition of obtaining the backward propagation time period, the monitoring values of the preset monitoring stations in the backward propagation time period are correspondingly obtained, and the preset grids in which the target pollutants exist in the preset monitoring stations in the backward propagation time period are determined as m second target grids.
According to an embodiment of the present invention, determining I third target grids from the preset grids according to the n first target grids and the m second target grids comprises:
and under the condition that the n first target grids and the m second target grids are correspondingly overlapped on the preset grid, determining an overlapped area in the preset grid as a third target grid.
According to the embodiment of the present invention, it may be further configured that, when the n first target grids and the m second target grids are not overlapped on the preset grid, the independent first target grids or the independent second target grids are screened, and the remaining non-independent first target grids or the remaining non-independent second target grids are determined as the third target grids. Setting an independent first target grid as a first target grid of which 8 peripheral adjacent grids are not the first target grid or the second target grid; the independent second target mesh is set as a second target mesh in which none of the 8 surrounding neighboring meshes is the first target mesh or the second target mesh.
According to an embodiment of the present invention, obtaining an ith contribution ratio of the target pollutant from the ith dwell time period and the ith monitored concentration comprises:
and obtaining an ith contribution value according to the ith staying time period and the ith monitoring concentration. And obtaining a total contribution value according to the ith contribution value. And obtaining the ith contribution ratio according to the ith contribution value and the total contribution value.
According to an embodiment of the present invention, the ith contribution ratio of the target pollutant can be obtained by expression of formula (1):
wherein, P i Is the ith contribution of the target contaminant (unit:%); t is i Is the ith residence time period (unit: s) for the target contaminant; c i For the ith monitored concentration of a target contaminant (unit: μ g/m) 3 ) (ii) a Alpha represents the vertical exchange rate (unit: m) of the air mass in which the near-surface target pollutant is positioned 3 /s), the near-surface target pollutant can be set to be uniform in the preset grid in the vertical exchange velocity field of the air mass.
According to an embodiment of the present invention, determining the fourth target mesh according to the ith contribution ratio comprises:
and determining the third target grid corresponding to the ith contribution ratio meeting the preset condition as a fourth target grid.
According to the embodiment of the invention, I contribution ratios of the target pollutants can be arranged to be sorted from large to small, a third target grid corresponding to the first k contribution ratios is determined as a fourth target grid, and k is a positive integer smaller than I.
According to the embodiment of the invention, the method can further refine the type of the target pollutant, perform contribution ratio calculation on different types of target pollutants, and determine the fourth target grids corresponding to different types of target pollutants by the method for determining the fourth target grids.
According to the embodiment of the invention, the position of the pollution source corresponding to the target pollutant can be accurately obtained by combining the pollution source position database of the actual region corresponding to the preset grid according to the actual position corresponding to the fourth target grid.
According to the embodiment of the invention, based on the particle diffusion model and gridding monitoring, a first target grid and a second target grid corresponding to a target pollutant are determined by presetting the monitoring value of a monitoring station. And determining a third target grid according to the first target grid and the second target grid, wherein the third target grid can more accurately represent a third range corresponding to the pollutant. And acquiring the contribution ratio of the target pollutant in the area corresponding to the third target grid according to the monitoring value of the preset monitoring station, the preset meteorological model and the particle diffusion model, quantifying the influence of the target pollutant in the third target grid, and further determining the fourth target grid according to the contribution ratio of the target pollutant. Based on the pollution source location database, the source location corresponding to the target pollutant represented by the fourth target grid can be determined, and the rapid and accurate tracing of the target pollutant under the condition of small microscale can be realized through the real-time tracing method of the pollutant. The small-scale pollutant gridding quantitative traceability analysis and the accurate positioning of the heavy pollution source in the urban cluster or the industrial park are realized.
Fig. 3 schematically illustrates a block diagram of a real-time contaminant tracing apparatus according to an embodiment of the present disclosure.
As shown in fig. 3, the real-time contaminant tracing apparatus 300 includes a first determining module 310, a second determining module 320, a third determining module 330, a first obtaining module 340, a second obtaining module 350, a calculating module 360 and a fourth determining module 370.
The first determining module 310 is configured to determine n first target grids from a preset grid according to a monitoring value of a preset monitoring station and a preset meteorological model, where n is a positive integer.
The second determining module 320 is configured to determine m second target grids from the preset grids according to the monitoring values of the preset monitoring stations, where m is a positive integer.
The third determining module 330 determines I third target grids from the preset grids according to the n first target grids and the m second target grids, where I is a positive integer.
The first obtaining module 340 is configured to correspondingly obtain I staying time periods of the target pollutant according to the I third target grids and the particle diffusion model.
And a second obtaining module 350, configured to correspondingly obtain I monitoring concentrations of the target pollutants according to the I third target grids and the monitoring values of the preset monitoring stations.
And the calculating module 360 is used for obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ].
And the fourth determining module 370 determines a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
According to an embodiment of the present disclosure, the first determining module 310 includes a first obtaining sub-module, a second obtaining sub-module, and a first determining sub-module.
And the first acquisition submodule is used for acquiring the real-time position of the target pollutant according to the monitoring value of the preset monitoring station.
And the second acquisition submodule is used for determining the backward propagation time period and the backward propagation range of the target pollutant through the particle diffusion model according to the real-time position of the target pollutant and the preset meteorological model.
And the first determining submodule is used for determining n first target grids from the preset grids according to the backward propagation range of the target pollutants and the first precision grids.
According to an embodiment of the present disclosure, the second determining module 320 includes a third obtaining sub-module and a second determining sub-module.
And the third acquisition submodule is used for acquiring target monitoring data according to the monitoring value of the preset monitoring station, wherein the target monitoring data comprises the monitoring data of the target pollutant of the preset monitoring station in the backward propagation time period of the target pollutant.
And the second determining submodule is used for determining m second target grids from the preset grids according to the target monitoring data.
According to an embodiment of the present disclosure, the third determination module 330 includes a third determination submodule.
And the third determining submodule is used for determining an overlapped area in the preset grid as a third target grid under the condition that the n first target grids and the m second target grids are correspondingly overlapped on the preset grid.
According to an embodiment of the present invention, the calculation module 360 includes a first calculation submodule, a second calculation submodule, and a third calculation submodule.
And the first calculation submodule is used for obtaining an ith contribution value according to the ith staying time period and the ith monitoring concentration.
And the second calculation submodule is used for obtaining a total contribution value according to the ith contribution value.
And the third calculation submodule is used for obtaining the ith contribution ratio according to the ith contribution value and the total contribution value.
According to an embodiment of the present disclosure, the fourth determination module 370 includes a fourth determination sub-module.
And the fourth determining submodule is used for determining the third target grid corresponding to the ith contribution ratio meeting the preset condition as the fourth target grid.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to the embodiments of the present disclosure may be implemented at least partially as hardware circuits, by hardware or firmware in any other reasonable manner of integrating or packaging circuits, or in any one of or a suitable combination of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be implemented at least partly as a computer program module, which when executed, may perform a corresponding function.
Fig. 4 schematically shows a block diagram of an electronic device suitable for implementing a real-time contaminant tracing method according to an embodiment of the disclosure. The electronic device shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 4, the computer electronic device 400 according to the embodiment of the present disclosure includes a processor 401 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage section 409 into a Random Access Memory (RAM) 403. Processor 401 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 401 may also include onboard memory for caching purposes. Processor 401 may include a single processing unit or multiple processing units for performing the different actions of the method flows in accordance with embodiments of the present disclosure.
In the RAM 403, various programs and data necessary for the operation of the electronic apparatus 400 are stored. The processor 401, ROM 402 and RAM 403 are connected to each other by a bus 404. The processor 401 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 402 and/or the RAM 403. Note that the program may also be stored in one or more memories other than the ROM 402 and the RAM 403. The processor 401 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, electronic device 400 may also include an input/output (I/O) interface 405, input/output (I/O) interface 405 also being connected to bus 404. Electronic device 400 may also include one or more of the following components connected to I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output section 407 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. A drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 410 as necessary, so that a computer program read out therefrom is mounted into the storage section 408 as necessary.
Embodiments of the present disclosure also include a computer-readable storage medium, which may be embodied in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method provided by the embodiments of the present disclosure, when the computer program product runs on an electronic device, the program code is configured to cause the electronic device to implement the task scheduling method and the task processing method provided by the embodiments of the present disclosure.
The computer program, when executed by the processor 401, performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure. The above described systems, devices, modules, units, etc. may be implemented by computer program modules according to embodiments of the present disclosure.
According to embodiments of the present disclosure, the computer program may be supported by a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. The computer program may also be transmitted in the form of a signal, distributed over a network medium, and downloaded and installed through the communication section 409 and/or installed from the removable medium 411. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the disclosure, and these alternatives and modifications are intended to fall within the scope of the disclosure.
Claims (10)
1. A real-time tracing method for pollutants, comprising:
determining n first target grids from a preset grid according to a monitoring value of a preset monitoring station and a preset meteorological model, wherein n is a positive integer;
determining m second target grids from the preset grids according to the monitoring values of the preset monitoring stations, wherein m is a positive integer;
determining I third target grids from the preset grids according to the n first target grids and the m second target grids, wherein I is a positive integer;
correspondingly obtaining I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model;
correspondingly obtaining I monitoring concentrations of the target pollutants according to the I third target grids and the monitoring values of the preset monitoring sites;
obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and
and determining a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
2. The tracing method of claim 1, wherein the determining n first target grids from the preset grids according to the monitoring values of the preset monitoring station and the preset meteorological model comprises:
obtaining the real-time position of the target pollutant according to the monitoring value of the preset monitoring station;
determining a backward propagation time period and a backward propagation range of the target pollutant through the particle diffusion model according to the real-time position of the target pollutant and the preset meteorological model; and
and determining the n first target grids from preset grids according to the backward propagation range of the target pollutants and the first precision grids.
3. The tracing method of claim 2, wherein said determining m second target grids from said preset grids according to the monitoring values of said preset monitoring stations comprises:
obtaining target monitoring data according to the monitoring value of the preset monitoring station, wherein the target monitoring data comprises the monitoring data of the target pollutant of the preset monitoring station in the backward propagation time period of the target pollutant; and
and determining the m second target grids from the preset grids according to the target monitoring data.
4. The tracing method of claim 1, wherein said determining I third target grids from said preset grids according to said n first target grids and said m second target grids comprises:
in case there is an overlap of the n first target grids and the m second target grids corresponding to the preset grid,
and determining the overlapped area in the preset grid as the third target grid.
5. The tracing method of claim 1, wherein said deriving an ith contribution ratio of the target pollutant from an ith dwell time period and an ith monitored concentration comprises:
obtaining an ith contribution value according to the ith staying time period and the ith monitoring concentration;
obtaining a total contribution value according to the ith contribution value; and
and obtaining the ith contribution ratio according to the ith contribution value and the total contribution value.
6. The tracing method of claim 1, wherein said determining a fourth target mesh according to said ith contribution ratio comprises:
and determining the third target grid corresponding to the ith contribution ratio meeting a preset condition as the fourth target grid.
7. The tracing method of claim 1, further comprising:
and dividing preset areas according to the preset monitoring stations to obtain the preset grids.
8. The tracing method of claim 1, further comprising:
and determining the preset meteorological model according to the meteorological numerical model and the preset grid.
9. A real-time contaminant tracing apparatus, comprising:
the first determining module is used for determining n first target grids from the preset grids according to the monitoring values of the preset monitoring stations and the preset meteorological model, wherein n is a positive integer;
the second determining module is used for determining m second target grids from the preset grids according to the monitoring values of the preset monitoring sites, wherein m is a positive integer;
a third determining module, configured to determine I third target grids from the preset grids according to the n first target grids and the m second target grids, where I is a positive integer;
the first acquisition module is used for correspondingly acquiring I staying time periods of the target pollutants according to the I third target grids and the particle diffusion model;
the second acquisition module is used for correspondingly acquiring I monitored concentrations of the target pollutants according to the I third target grids and the monitoring values of the preset monitoring sites;
the calculation module is used for obtaining the ith contribution ratio of the target pollutant according to the ith staying time period and the ith monitoring concentration, wherein i is an integer belonging to [1,I ]; and
and the fourth determining module is used for determining a fourth target grid from the preset grids according to the ith contribution ratio, wherein the fourth target grid represents the source position corresponding to the target pollutant.
10. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116307258A (en) * | 2023-05-08 | 2023-06-23 | 中科三清科技有限公司 | Pollution source abnormal emission determination method and device, storage medium and electronic equipment |
| CN118195282A (en) * | 2024-05-17 | 2024-06-14 | 浙江省生态环境监测中心(浙江省生态环境信息中心) | Pollution control guiding method and device, storage medium and electronic equipment |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116307258A (en) * | 2023-05-08 | 2023-06-23 | 中科三清科技有限公司 | Pollution source abnormal emission determination method and device, storage medium and electronic equipment |
| CN116307258B (en) * | 2023-05-08 | 2023-08-11 | 中科三清科技有限公司 | Pollution source abnormal emission determination method and device, storage medium and electronic equipment |
| CN118195282A (en) * | 2024-05-17 | 2024-06-14 | 浙江省生态环境监测中心(浙江省生态环境信息中心) | Pollution control guiding method and device, storage medium and electronic equipment |
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