CN116739224A - Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source - Google Patents
Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source Download PDFInfo
- Publication number
- CN116739224A CN116739224A CN202311020008.XA CN202311020008A CN116739224A CN 116739224 A CN116739224 A CN 116739224A CN 202311020008 A CN202311020008 A CN 202311020008A CN 116739224 A CN116739224 A CN 116739224A
- Authority
- CN
- China
- Prior art keywords
- source
- sub
- list
- target
- concentration
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000004088 simulation Methods 0.000 claims abstract description 125
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 94
- 231100000719 pollutant Toxicity 0.000 claims abstract description 94
- 238000012544 monitoring process Methods 0.000 claims abstract description 37
- 238000011109 contamination Methods 0.000 claims description 32
- 239000000356 contaminant Substances 0.000 claims description 12
- 238000004590 computer program Methods 0.000 claims description 6
- 238000012216 screening Methods 0.000 claims description 4
- 230000008878 coupling Effects 0.000 claims description 3
- 238000010168 coupling process Methods 0.000 claims description 3
- 238000005859 coupling reaction Methods 0.000 claims description 3
- 238000005067 remediation Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 238000006243 chemical reaction Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 2
- 238000003915 air pollution Methods 0.000 description 1
- 238000013475 authorization Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001311 chemical methods and process Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C10/00—Computational theoretical chemistry, i.e. ICT specially adapted for theoretical aspects of quantum chemistry, molecular mechanics, molecular dynamics or the like
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/20—Identification of molecular entities, parts thereof or of chemical compositions
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/90—Programming languages; Computing architectures; Database systems; Data warehousing
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Computing Systems (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Bioinformatics & Computational Biology (AREA)
- Economics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Strategic Management (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Chemical & Material Sciences (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Crystallography & Structural Chemistry (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Primary Health Care (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present disclosure relates to a method, an apparatus and a storage medium for determining a contribution concentration of a heavy point pollution source, and relates to the technical field of atmospheric remediation, including: dividing the sub-source list into a plurality of sub-source lists under the condition that the number of target pollution sources in the simulation grids of the sub-source list is a plurality of sub-source lists, wherein the sub-source list is a list formed by the target pollution sources, and one simulation grid in the sub-source list is used for indicating the pollutant discharge amount of one target pollution source; inputting the multiple sub-source lists, the source mark files and the receptor files into an air quality model to obtain the contribution concentration of the target pollution source corresponding to the simulation grid to the site pollutant concentration of the monitoring site; the source marking file is used for marking the target pollution source corresponding to the simulation grid. The method for determining the contribution concentration of the heavy point pollution source can be used for obtaining the contribution concentration more accurately and faster.
Description
Technical Field
The present disclosure relates to the field of air pollution control technology, and in particular, to a method, an apparatus, and a storage medium for determining a concentration of a heavy point pollution source.
Background
At present, with the development of technology, in the process of simulating the contribution concentration of a pollution source to the concentration of site pollutants, a second generation air quality model and a third generation air quality model are generated.
In the related technology, the third generation air quality is adopted to simulate the contribution concentration of a pollution source to the site pollutant concentration, and the simulation efficiency is low; the contribution concentration of the pollution source to the site pollutant concentration is simulated by combining the second-generation air quality model and the third-generation air quality model, and the accuracy of the contribution concentration obtained by simulation is low.
Disclosure of Invention
To overcome the problems in the related art, the present disclosure provides a method, apparatus, and storage medium for determining a contribution concentration of a heavy point contamination source.
According to a first aspect of embodiments of the present disclosure, there is provided a method of determining a contribution concentration of a heavy point contamination source, comprising:
dividing a sub-source list into a plurality of sub-source sub-lists under the condition that the number of target pollution sources in a simulation grid of the sub-source list is a plurality of, wherein the sub-source list is a list formed by the target pollution sources, and one simulation grid in the sub-source sub-list is used for indicating the pollutant discharge amount of one target pollution source;
Inputting the multiple sub-source lists, the source mark files and the receptor files into an air quality model to obtain the contribution concentration of the target pollution source corresponding to the simulation grid to the site pollutant concentration of the monitoring site; the source marking file is used for marking a target pollution source corresponding to the simulation grid, the receptor file comprises a position of a monitoring station in the sub-source list, and the air quality model comprises a third-generation air quality model.
Optionally, inputting the multiple sub-lists of molecular sources, the source tag file and the receptor file into an air quality model to obtain a pollution source corresponding to the simulation grid, and contributing the concentration of the site pollutant of the monitoring site, including:
and inputting the plurality of sub-lists of the molecular sources, the source mark file, the receptor file and the background list into an air quality model to obtain the contribution concentration, wherein the background list is a list formed by non-target pollution sources.
Optionally, the method further comprises:
coupling the plurality of sub-source sub-lists with the background list to obtain a total emission list;
and inputting the total emission list into the air quality model to obtain the pollutant concentration of the pollution source corresponding to each grid in the total emission list.
Optionally, the method further comprises:
and under the condition that the number of target pollution sources in the simulation grid of the sub-source list is one, inputting the sub-source list, the source mark file and the receptor file into an air quality model to obtain the contribution concentration.
Optionally, the method further comprises:
acquiring the position information of the target pollution source;
intersecting the position information of the target pollution source with the simulation grid to obtain a map file;
and marking grids with the target pollution source in the map file by adopting different identifiers to obtain the source marking file.
Optionally, the method further comprises:
acquiring the position information of the monitoring station;
intersecting the position information of the monitoring station with the simulation grid to obtain the position of the monitoring station in the simulation grid;
and obtaining the receptor file according to the position of the monitoring station point in the simulation grid.
Optionally, in a case that the number of target pollution sources in the simulation grid of the sub-source list is a plurality, dividing the sub-source list into a plurality of sub-source sub-lists includes:
under the condition that the number of target pollution sources in the simulation grids of the sub-source list is a plurality of, determining target grids with the largest number of target pollution sources in the simulation grids;
And dividing the sub-source list into sub-source sub-lists of the target number according to the target number of the target pollution sources in the target grid.
Optionally, the method further comprises:
determining, for each of a plurality of weather patterns, a concentration of contribution of a plurality of target pollution sources to the site pollutant concentration during the pollution of said each weather pattern;
screening a pollution source to be controlled corresponding to a target contribution concentration greater than a preset contribution concentration from the contribution concentrations;
and establishing an association relation between the pollution source to be managed and controlled and the weather type.
According to a second aspect of embodiments of the present disclosure, there is provided an apparatus for determining a concentration of a contribution of a heavy point contamination source, comprising:
a dividing module configured to divide a sub-source list into a plurality of sub-source lists in a case that the number of target pollution sources is a plurality of in-model grids of the sub-source list, wherein the sub-source list is a list formed by the target pollution sources, and one of the sub-source lists is used for indicating pollutant discharge amount of one target pollution source;
the simulation module is configured to input the multiple sub-lists of the sub-sources, the source mark files and the receptor files into an air quality model to obtain contribution concentration of a target pollution source corresponding to the simulation grid to site pollutant concentration of a monitoring site; the source marking file is used for marking a target pollution source corresponding to the simulation grid, and the receptor file comprises the position of the monitoring site in the simulation grid.
According to a third aspect of embodiments of the present disclosure, there is provided an apparatus for determining a concentration of a contribution of a heavy point contamination source, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
the steps of the method of determining the contribution concentration of the heavy point contamination source provided by the first aspect of the present disclosure are performed.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method of determining the concentration of contribution of a heavy point contamination source provided by the first aspect of the present disclosure.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
the air quality model is a third-generation air quality model, and the third-generation air quality model can fully consider the secondary conversion of pollutants, and can accurately quantitatively evaluate the contribution concentration of different types of pollutants to the concentration of the pollutants at the site, so that the third-generation air quality model can accurately obtain the contribution concentration of the target pollution source; in the process of obtaining the contribution concentration, each simulation grid in the sub-file of the sub-source only has one target pollution source, but not a plurality of pollution sources, so that the air quality model only needs to perform synchronous simulation once, the contribution concentration corresponding to each target pollution source in the sub-list of the sub-sources can be obtained, and the mode of multiple simulation like a third generation model is not needed, and the multiple target pollution sources in one simulation grid in the sub-list of the sub-sources are respectively simulated for multiple times, so that the contribution concentration of the multiple target pollution sources is obtained, the calculation time is saved, and the calculation efficiency is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a flow chart illustrating a method of determining a contribution concentration of a heavy point contamination source according to an example embodiment;
FIG. 2 is a schematic diagram of a split source inventory, according to an example embodiment;
FIG. 3 is a schematic diagram of a plurality of sub-lists of molecular sources, shown in accordance with an exemplary embodiment;
FIG. 4 is a schematic diagram of a source markup file, shown according to an example embodiment;
FIG. 5 is a schematic diagram illustrating a total emissions inventory, according to an exemplary embodiment;
FIG. 6 is a schematic diagram of a background manifest shown according to an example embodiment;
FIG. 7 is a schematic diagram of a source markup file, shown according to an example embodiment;
FIG. 8 is a block diagram illustrating an apparatus for determining the concentration of contributions of a heavy point contamination source, according to an example embodiment;
FIG. 9 is a block diagram illustrating an apparatus for determining the concentration of contributions of a heavy point contamination source, according to an example embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
It should be noted that, all actions for acquiring signals, information or data in the present disclosure are performed under the condition of conforming to the corresponding data protection rule policy of the country of the location and obtaining the authorization given by the owner of the corresponding device.
In the related art, referring to the sub-source list shown in fig. 2, there may be a plurality of pollution sources in one simulation grid in the sub-source list (the pollution sources are represented by five-pointed star in fig. 2), and three pollution sources in one simulation grid in the fifth column of the fifth row in the lower right corner of fig. 2 are exemplified. In the prior art, after the sub-source list is input into the air quality model, only the sum of the contribution concentrations of three pollution sources in one simulation grid to the site pollutant concentration, namely the total pollutant concentration of the three pollution sources, can be obtained, and the contribution concentration of a single pollution source in one simulation grid to the site pollutant concentration can not be obtained.
Based on the method, a second-generation air quality model can be used for carrying out simulation evaluation on the contribution concentration of a single pollution source to the concentration of the station pollutant, however, the second-generation air quality model cannot consider sufficient secondary conversion, the simulation error of particulate matters is large, and ozone cannot be simulated.
Based on the method, the contribution concentration of a single pollution source to the site pollutant concentration can be obtained by adopting a technical scheme of combining a second generation air quality model and a third generation air quality model, and the scheme is as follows: the third generation air quality model is utilized to obtain the total pollutant concentration of three pollutant sources in a simulation grid, the weight of each pollutant source is determined through the second generation air quality model, the total pollutant concentration is multiplied by the weight of each pollutant source, and the contribution concentration of each pollutant source to the pollutant concentration of a site is obtained. However, the simulation error of the second-generation air quality model is larger, so that the weight error of each pollution source obtained by determination is larger, and the accuracy of the contribution concentration of each pollution source to the site pollutant concentration obtained based on the weight with larger error is lower.
Based on the method, a third generation air quality model can be adopted to obtain the contribution concentration of a single pollution source to the site pollutant concentration, and the scheme is as follows: the third generation air quality model firstly uses a background list to simulate once to obtain the first pollutant concentration of the simulation grid; superposing the first pollution sources on the basis of the first pollutant concentration (namely, simulating that the number of the pollution sources in the grid is changed from 0 to 1) to obtain a second pollutant concentration, wherein the value of the second pollutant concentration increased compared with the first pollutant concentration is the contribution concentration of the first pollution sources; then, the second pollution sources are overlapped on the basis of the second pollutant concentration (namely, the number of the pollution sources in the simulation grid is changed from 1 to 2), so that third pollutant concentration is obtained, and the value of the third pollutant concentration increased compared with the second pollutant concentration is the contribution concentration of the second pollution sources; and then, the third pollution source is overlapped on the basis of the third pollutant concentration (namely, the number of the pollution sources in the simulation grid is changed from 2 to 3), so that the fourth pollutant concentration is obtained, and the value of the fourth pollutant concentration increased compared with the third pollutant concentration is the contribution concentration of the third pollution source. Therefore, when the third generation air quality model obtains the contribution concentration of each pollution source, one simulation is needed, if the contribution concentration of three pollution sources in one simulation grid is needed to be simulated, four simulation calculations are needed, the number of grids in the source dividing list is huge, the number of pollution sources contained in each grid is also larger, the number of contribution concentrations needed to be calculated finally is larger, and finally the efficiency of outputting the contribution concentration of each pollution source is slower. It can be appreciated that the third generation air quality model only needs to obtain a total emission list, wherein the total emission list comprises a background list and an emission list, and the multiple cycle simulation can be performed to output the contribution concentration of each pollution source.
Based on this, the present disclosure proposes a method of determining a contribution concentration of a heavy point contamination source, the method comprising the following steps.
In step S11, in the case where the number of target pollution sources is plural in the simulation grid of the sub-source list, the sub-source list is divided into plural sub-source sub-lists.
In some embodiments, in the case that the number of target pollution sources in the simulation grids of the source division list is a plurality, determining a target grid in which the most number of target pollution sources exist in the plurality of simulation grids; and dividing the sub-source list into sub-source sub-lists of the target number according to the target number of the target pollution sources in the target grid.
Optionally, the number of target pollution sources present in the target grid having the largest number of target pollution sources in the plurality of simulated grids of the sub-source list corresponds to the number of sub-source lists.
For example, referring to the sub-source list shown in fig. 2, there are a plurality of simulation grids in the sub-source list, six simulation grids in fig. 2 have target pollution sources, wherein the target grid having the largest number of target pollution sources is the target grid of the fifth row and the fifth column in the lower right corner, and the target grid has the target pollution sources having the 3 target number, so the sub-source list may be divided into three sub-source sub-lists, such as the sub-source sub-list a, the sub-source sub-list B and the sub-source sub-list C shown in fig. 3, so that each simulation grid having target pollution sources only includes one target pollution source in each simulation grid having target pollution sources, and three target pollution sources in the simulation grid of the fifth row and the fifth column in the sub-source list are divided into three different sub-source sub-lists, and two target pollution sources in the simulation grid of the first row and the simulation grid of the fourth column in the sub-source list and two target pollution sources in the simulation grid of the second row and the second column in the sub-source sub-list are also divided into two different sub-source sub-lists.
Optionally, the sub-source list is a list formed by the target pollution sources, the simulation grid in the sub-source list may include one target pollution source or may include a plurality of target pollution sources, in the case that the simulation grid in the sub-source list includes one target pollution source, the simulation grid is used for indicating the pollutant emission amount of one target pollution source, and in the case that the simulation grid in the sub-source list includes a plurality of target pollution sources, the simulation grid is used for indicating the total pollutant emission amount of a plurality of target pollution sources; a simulated grid in the sub-list of sub-sources is used to indicate the pollutant emissions of a target pollutant source.
Alternatively, the target pollution source may be a pollution source of interest to a user among a plurality of pollution sources, and the pollution source may be a point source such as an industrial source, a restaurant source, or the like. Industrial sources may be referred to as pollution sources because factories emit pollutants during operation, and restaurant stores emit pollutants during operation, so restaurant sources may also be referred to as pollution sources. It will be appreciated that the heavy point contamination source proposed by embodiments of the present disclosure may be a target contamination source of interest to the user.
For example, if a user wants to pay attention to the contribution concentration of plant a to the site contaminant concentration among the contamination sources such as plant a, plant B, and plant C, then plant a is the target contamination source, and the remaining plants B and C are non-target contamination sources. The embodiment of the disclosure is used for researching the contribution concentration of the target pollution source focused by a user to the site pollutant concentration.
Alternatively, the simulated grid is a hypothetical grid, and embodiments of the present disclosure may assume that the area of the simulated grid is large and the target pollution source is a factory or mobile source that is small, so there will typically be multiple target pollution sources in the simulated grid and one target pollution source cannot occupy multiple simulated grids.
In step S12, the multiple sub-source lists, the source tag file and the receptor file are input into an air quality model, so as to obtain a contribution concentration of the target pollution source corresponding to the simulation grid to the site pollutant concentration of the monitoring site.
In some embodiments, the plurality of sub-lists of molecular sources, source signature files, receptor files, and background lists are input to an air quality model to obtain the contribution concentration.
Alternatively, the air quality model may be a third generation air quality model, such as CAMx (Comprehensive Air Quality Model with Extensions) model, CMAQ (Community Multiscale Air Quality Model) model, WRF-chem (Weather Research and Forecasting model coupled to Chemistry) model, NAQPMS (Nested Air Quality Prediction Model System) model, and the like; the third-generation air quality model can fully consider the secondary conversion of pollutants, namely the physical and chemical processes of the pollutants in the atmosphere, so that the contribution concentration of different secondary pollutants such as ozone and the like to the concentration of the pollutants at the site can be accurately and quantitatively estimated.
Optionally, the source marking file is used for marking the target pollution sources corresponding to the simulation grid, and the air quality model can track each target pollution source in the sub-list of the sub-sources according to the source marking file, so as to obtain the contribution concentration of each target pollution source to the site pollutant concentration.
For example, referring to fig. 4, the analog grids in the source list of fig. 2 having the target pollution source may be identified by numerals 2 to 7, and the analog grids in the source list having no target pollution source may be identified by numeral 1 to obtain the source markup file, where the source markup file is as follows:
TABLE 1
Table 1 shows the correspondence between the identifier and the simulation grids in the sub-source list, the identifier 2 corresponds to the simulation grid in the first row and the fourth column in the sub-source list, the identifier 3 corresponds to the simulation grid in the second row and the second column in the sub-source list, and the simulation grids corresponding to the identifiers 3 to 7 are not repeated.
It will be appreciated that for an air quality model, which is a machine model, it is not possible to directly distinguish between different target pollution sources in the molecular inventory, and thus the identification in the source signature file may be used to distinguish between target pollution sources in different simulation grids. Because the mark corresponding to each simulation grid in the sub-source list is arranged in the source mark file, namely the mark corresponding to the row-column coordinates of each simulation grid, the air quality model can identify the mark in the source mark file to determine the simulation grid corresponding to the mark in the sub-source list, and further track and obtain the target pollution source in the target grid of the sub-source list.
It will be appreciated that since the sub-list of sub-sources is a sub-list divided from the sub-list of sub-sources, there is naturally also an identification corresponding to each simulated grid in the sub-list of sub-sources in the case of having an identification corresponding to each simulated grid in the sub-list of sub-sources in the source markup file.
Optionally, the receptor file includes a position of the monitoring site in the source-division list, that is, the receptor file includes a simulation grid where the monitoring site is located in the source-division list; the air quality model may be used to derive site contaminant concentrations for the monitoring site based on the receptor file.
Optionally, the background list is a list formed by non-target pollution sources, and the sub-source list and the background list are coupled to obtain a total emission list, that is, the total emission list of the target area is composed of the sub-source list focused by the user and the background list not focused by the user. The background list is input into the air quality model, so that the air quality model can obtain the contribution concentration under the condition that non-target pollution sources are considered, and the obtained contribution concentration is more fit with the actual situation.
For example, referring to the total emissions list shown in fig. 5, in a 5X5 simulation grid, the list formed by the target pollution sources (pentagram in fig. 5 represents the target pollution sources) occupying a plurality of simulation grids is a sub-source list; the list formed after non-target pollution sources (circles in fig. 5 represent non-target pollution sources) excluding target pollution sources occupy a plurality of simulation grids is a background list.
In some embodiments, a plurality of sub-source sub-lists and a background list can be coupled to obtain a total emission list, and the total emission list, the plurality of sub-source sub-lists and the background list are coupled to form a grid emission list; and inputting the source mark file, the grid emission list and the receptor file into an air quality model, wherein the air quality model adopts the marks in the source mark file to track the contribution concentrations of the target pollution sources corresponding to the marks in the sub-lists of the multiple sub-sources to the site pollutant concentration.
The air quality model can simulate and obtain the pollutant concentration corresponding to the pollution source according to the pollutant discharge amount of the pollution source, so after the air quality model obtains the receptor file, the site pollutant concentration of the monitoring site can be obtained because the receptor file is provided with the position of the monitoring site in the simulation grid and the pollutant discharge amount of the monitoring site; after the air quality model acquires the sub-list of the molecular source, the pollutant concentration of the target pollution source can be obtained because the sub-list of the molecular source has the position of the target pollution source in the simulation grid and the emission quantity of the target pollution source; the contribution concentration contributed by the contaminant concentration of the target contaminant source in the site contaminant concentration is ultimately determined. For example, the site contaminant concentration is 10ug/L, then the contaminant concentration of plant A contributes 5ug/L and the contaminant concentration of plant B contributes 5ug/L.
The air quality model can distinguish different sub-lists of the sub-sources according to the identification.
For example, referring to fig. 3 in conjunction with table 1, three target pollution sources in the fifth row of the sub-source list are exemplified by a plant a, a plant B and a plant C, respectively, after the sub-source list is divided into a sub-source sub-list a, a sub-source sub-list B and a sub-source sub-list C, the plant a is divided into a sub-source sub-list a, the plant B is divided into a sub-source sub-list B, and the plant C is divided into a sub-source sub-list C. The air quality model can track the contribution concentration of the plant A in the sub-source list A to the site pollutant concentration according to the identification 7 corresponding to the plant A; tracking the contribution concentration of the plant B of the sub-source list B to the site pollutant concentration according to the identifier 7 corresponding to the plant B; and finally tracking the contribution concentration of the plant C of the sub-source list C to the site pollutant concentration according to the identification 7 corresponding to the plant C.
Optionally, in the case that the number of sub-lists of the sub-sources received by the air quality model is only one, the air quality model may track the target pollution sources directly according to the sequence of the identifiers, so as to obtain the contribution concentration of the target pollution source corresponding to each identifier.
Optionally, in the case that the number of the sub-lists of the sub-sources received by the air quality is plural, the air quality model may distinguish different sub-lists of the sub-sources according to the identification of the sub-list of the sub-sources; and tracking different target pollution sources in the same sub-list of the target pollution sources according to the marks of the target pollution sources to obtain the contribution concentration of the target pollution sources corresponding to each mark.
For example, referring to fig. 2 and fig. 4, if the target pollution sources in the fourth column of the first row share the identifier 2 in the sub-source list; the target pollution sources of the second row and the second column share the mark 3; the target pollution source of the third row and the third column occupies the mark 4; the target pollution source of the fourth row and the second column occupies the mark 5; the target pollution source of the fourth column of the fifth row occupies the mark 6; the target pollution sources of the fifth row and the fifth column share the identifier 7.
Referring to fig. 3, when dividing the sub-source list, two target pollution sources corresponding to the identifier 2 are respectively divided into a sub-source list a and a sub-source list B; dividing two target pollution sources corresponding to the mark 3 into a sub-source list A and a sub-source list B respectively; dividing target pollution sources corresponding to the identifiers 4, 5 and 6 into a sub-list A of the sub-sources; and dividing the three target pollution sources corresponding to the mark 7 into a sub-list A of the sub-sources and a sub-list C of the sub-sources respectively.
After three sub-lists of the sub-sources are simultaneously input into the air quality model, the air quality model can distinguish the sub-lists of the sub-sources A to C according to the marks of the sub-lists of the sub-sources A to C; when tracking the target pollution sources in the molecular source sub-list A, tracking the target pollution sources corresponding to the marks 2, 3, 4, 5, 6 and 7 in sequence according to the sequence from small marks to large marks; the principle of tracking the target pollution sources in the molecular source sub-list B and the molecular source sub-list C is similar, and the description is omitted.
In some embodiments, the plurality of sub-listings of sub-sources may be coupled to the background listing to obtain a total emissions listing; and inputting the total emission list into the air quality model to obtain the pollutant concentration of the pollution source corresponding to each grid in the total emission list.
The sum of the contribution concentrations of the target pollution sources corresponding to the same identifier in the sub-lists of the multiple sub-sources is the pollutant concentration of the simulation grids corresponding to the identifier in the sub-list of the sub-sources, so that the pollutant concentration of each simulation grid in the sub-list of the sub-sources can be obtained after the sub-lists of the multiple sub-sources are coupled; and then the pollutant concentration of each simulation grid in the sub-source list and the pollutant concentration of each simulation grid in the background list are mutually compensated to obtain a total emission list, for example, after the sub-source list in fig. 2 is coupled with the background list in fig. 6, the total emission list shown in fig. 5 can be obtained.
The total emission list contains the corresponding pollutant concentration of each grid, and the pollutant concentration can be the sum of the contribution concentrations of a plurality of target pollution sources or the sum of the contribution concentrations of a plurality of non-target pollution sources.
For example, referring to the total emissions list shown in FIG. 5, the pollutant concentration of the simulated grid occupied by the target pollutant source (five-pointed star in FIG. 5) is the sum of the contribution concentrations of the plurality of target pollutant sources; the contaminant concentration of the simulated grid occupied by the non-target contaminant sources (circles in fig. 5) may be the sum of the contribution concentrations of the plurality of non-target contaminant sources.
In some embodiments, in a case that the number of target pollution sources in the simulation grid of the split source list is one, the split source list, the source mark file and the receptor file are input into an air quality model, so as to obtain the contribution concentration.
Optionally, under the condition that the number of target pollutants in each simulation grid in the split source list is one, the air quality model can directly track the target pollutants in each simulation grid in the split source list, the split source list is not required to be divided, and the split source list, the source mark file and the receptor file can be directly input into the air quality model to obtain the contribution concentration.
Through the technical scheme, the sub-source list is divided into the plurality of sub-source sub-lists, so that after the simulation grids in each sub-source list only contain one target pollution source, the air quality model can track one target pollution source contained in each simulation grid in the sub-source list according to the source mark file, and further the contribution concentration of the target pollution source to the site pollutant concentration is determined.
In the process, the air quality model is a third-generation air quality model, and the third-generation air quality model can fully consider the secondary conversion of pollutants, and can accurately quantitatively evaluate the contribution concentration of different types of pollutants to the concentration of the pollutants at the site, so that the third-generation air quality model can accurately obtain the contribution concentration of the target pollution source; in the process of obtaining the contribution concentration, each simulation grid in the sub-files of the sub-sources only has one target pollution source, but does not have a plurality of pollution sources, so that the air quality model only needs to synchronously simulate the sub-lists of the sub-sources once at the same time, the contribution concentration corresponding to each target pollution source in the sub-lists of the sub-sources can be obtained, and the mode of multiple simulation like a third generation model is not needed, and the multiple target pollution sources in one simulation grid in the sub-lists of the sub-sources are respectively simulated for multiple times to obtain the contribution concentration of the target pollution sources, thereby saving the calculation time and improving the calculation efficiency.
In one possible implementation, the source tag file and the recipient file may be obtained by the following steps.
In some embodiments, determining the source markup file includes the steps of:
(1) And acquiring the position information of the target pollution source.
Optionally, the location information of the target pollution source includes geographic information of the target pollution source, such as longitude and latitude.
Alternatively, the pollutant emissions of the target pollutant source may also be obtained.
(2) Intersecting the position information of the target pollution source with the simulation grid to obtain a map file.
Optionally, the location information of the target pollution source may be overlaid on the blank simulation grids to obtain a map file, where the map file may obtain which simulation grids have the target pollution source and which simulation grids do not have the target pollution source.
(3) And marking grids with the target pollution source in the map file by adopting different identifiers to obtain the source marking file.
Optionally, the grids in the map file, where the target pollution source exists, may be marked with the number 2, and the grids in the map file, where the target pollution source does not exist, i.e. the grids occupied by the non-target pollution source, may be marked with the number 1, so as to obtain the source mark file.
For example, referring to FIG. 7, numerals 3, 5, 6, 7, 8, 9, 10, 12 in FIG. 7 are respectively the identifications of the grids occupied by the different target pollution sources; numeral 1 is an identification of the grid occupied by the non-target pollution source.
In some embodiments, determining the recipient file includes the steps of:
(4) And acquiring the position information of the monitoring site.
(5) Intersecting the position information of the monitoring station with the simulation grid to obtain the position of the monitoring station in the simulation grid.
(6) And obtaining the receptor file according to the position of the monitoring station point in the simulation grid.
Optionally, the manner of obtaining the acceptor file is similar to that of obtaining the source tag file, and will not be described in detail herein. The position of the monitoring station in the simulation grid can be called a receptor grid, and row and column coordinates of the receptor grid form a receptor file.
In a possible implementation manner, the contribution concentration of the target pollution source to the site pollutant concentration at each moment obtained in the steps S11 to S12 may further obtain the pollution sources to be managed and controlled associated with different weather types, which specifically includes the following steps:
(1) For each of a plurality of weather patterns, determining a concentration of contribution of a plurality of target pollution sources to the site pollutant concentration during the pollution of said each weather pattern.
In some embodiments, the weather patterns are atmospheric circulation patterns repeatedly appearing in a certain target area, which are generalized from a wide range of weather patterns, and the weather patterns of the target area can be typed by using a parting model to obtain different weather patterns. The parting factors of parting areas selected from meteorological data can be used as data to be clustered, and the data to be clustered are clustered, so that a parting model is built.
In some embodiments, after the contribution concentration of the target pollution source at each moment is obtained, the contribution concentrations of the target pollution sources at each moment may be clustered to obtain the contribution concentrations of the plurality of target pollution sources in the pollution process of different weather types.
(2) And screening the pollution sources to be controlled corresponding to the target contribution concentration greater than the preset contribution concentration from the contribution concentrations.
In some embodiments, the pollution source to be regulated is one that requires major management under the current weather pattern.
(3) And establishing an association relation between the pollution source to be managed and controlled and the weather type.
In some embodiments, establishing the association between the pollution source to be managed and the weather type may include storing the pollution source to be managed in a database corresponding to the weather type.
For example, among the four target pollution sources of the target area, namely, the target pollution source a, the target pollution source B, the target pollution source C and the target pollution source D, the contribution concentration of the target pollution source a and the target pollution source B under the weather type 1 reaches the preset contribution concentration, the contribution concentration of the target pollution source C and the target pollution source D under the weather type 2 reaches the preset contribution concentration, and the contribution concentration of the target pollution source D under the weather type 3 reaches the preset contribution concentration, the target pollution source a and the target pollution source B may be classified into a state corresponding to the weather type 1, the target pollution source C and the target pollution source D may be classified into a state corresponding to the weather type 2, and the target pollution source D may be classified into a state corresponding to the weather type 3.
In this way, in the case that the same weather type appears at a certain time in the future, a management suggestion can be provided for the pollution process that is about to occur in the weather type, for example, if weather type 1 appears in the future, management of the target pollution source a and the target pollution source B can be suggested, and so on.
FIG. 8 is a block diagram illustrating an apparatus for determining the concentration of contribution of a heavy point contamination source, according to an example embodiment. Referring to fig. 8, the apparatus 800 for determining a contribution concentration of a heavy point contamination source includes a dividing module 810 and a simulation module 820.
A partitioning module 810 configured to partition a sub-list of sub-sources into a plurality of sub-lists of sub-sources, where the sub-list of sub-sources is a list of sub-sources formed by the sub-sources, where one of the sub-lists of sub-sources is used to indicate a pollutant emission amount of one of the sub-sources;
the simulation module 820 is configured to input the multiple sub-lists of molecular sources, the source tag file and the receptor file into an air quality model to obtain a contribution concentration of a target pollution source corresponding to the simulation grid to a site pollutant concentration of a monitoring site; the source marking file is used for marking a target pollution source corresponding to the simulation grid, and the receptor file comprises the position of the monitoring site in the simulation grid.
Optionally, the simulation module 820 includes:
the first simulation sub-module is configured to input the plurality of sub-lists of molecular sources, the source mark file, the receptor file and the background list into an air quality model to obtain the contribution concentration, wherein the background list is a list formed by non-target pollution sources.
Optionally, the apparatus 800 for determining the contribution concentration of the heavy point contamination source comprises:
the coupling module is configured to couple the plurality of sub-source lists with the background list to obtain a total emission list;
and the second simulation sub-module is configured to input the total emission list into the air quality model to obtain the pollutant concentration of the pollution source corresponding to each grid in the total emission list.
Optionally, the simulation module 820 is further configured to input the sub-source list, the source signature file and the acceptor file into an air quality model to obtain the contribution concentration, in case the number of target pollution sources in the simulation grid of the sub-source list is one.
Optionally, the apparatus 800 for determining the contribution concentration of the heavy point contamination source comprises:
a first acquisition module configured to acquire position information of the target pollution source;
the first intersecting module is configured to intersect the position information of the target pollution source with the simulation grid to obtain a map file;
and the marking module is configured to mark different grids by adopting different identifications for grids with the target pollution source in the map file, so as to obtain the source marking file.
Optionally, the apparatus 800 for determining the contribution concentration of the heavy point contamination source comprises:
a second acquisition module configured to acquire position information of the monitoring site;
a second intersecting module configured to intersect the position information of the monitoring site with the simulation grid to obtain a position of the monitoring site in the simulation grid;
and the receptor file determining module is configured to obtain the receptor file according to the position of the monitoring station point in the simulation grid.
Optionally, the apparatus 800 for determining the contribution concentration of the heavy point contamination source comprises:
a weather-type contribution concentration determination module configured to determine, for each of a plurality of weather types, a contribution concentration of a plurality of target pollution sources to the site pollutant concentration during a pollution process of the each weather type;
the screening module is configured to screen pollution sources to be controlled corresponding to target contribution concentration larger than preset contribution concentration from a plurality of contribution concentrations;
the establishing module is configured to establish an association relationship between the pollution source to be managed and the weather type.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
The present disclosure also provides a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the steps of the method of determining the concentration of contribution of a heavy point contamination source provided by the present disclosure.
The apparatus may be a stand-alone electronic device or may be part of a stand-alone electronic device, for example, in one embodiment, the apparatus may be an integrated circuit (Integrated Circuit, IC) or a chip, where the integrated circuit may be an IC or may be a collection of ICs; the chip may include, but is not limited to, the following: GPU (Graphics Processing Unit, graphics processor), CPU (Central Processing Unit ), FPGA (Field Programmable Gate Array, programmable logic array), DSP (Digital Signal Processor ), ASIC (Application Specific Integrated Circuit, application specific integrated circuit), SOC (System on Chip, SOC, system on Chip or System on Chip), etc. The integrated circuit or chip described above may be used to execute executable instructions (or code) to implement the method of determining the contribution concentration of the heavy point contamination source described above. The executable instructions may be stored on the integrated circuit or chip or may be retrieved from another device or apparatus, such as the integrated circuit or chip including a processor, memory, and interface for communicating with other devices. The executable instructions may be stored in the memory, which when executed by the processor implement the method of determining the contribution concentration of the heavy point contamination source described above; alternatively, the integrated circuit or chip may receive executable instructions through the interface and transmit them to the processor for execution to implement the method of determining the contribution concentration of the heavy point contamination source described above.
In another exemplary embodiment, a computer program product is also provided, comprising a computer program executable by a programmable apparatus, the computer program having code portions for performing the above-described method of determining a contribution concentration of a heavy point contamination source when executed by the programmable apparatus.
FIG. 9 is a block diagram illustrating an apparatus 900 for determining a concentration of a contribution of a heavy point contamination source, according to an example embodiment. For example, apparatus 900 may be provided as a server. Referring to FIG. 9, apparatus 900 includes a processing component 922 that further includes one or more processors, and memory resources represented by memory 932, for storing instructions, such as applications, executable by processing component 922. The application programs stored in memory 932 may include one or more modules that each correspond to a set of instructions. Further, processing component 922 is configured to execute instructions to perform the method of determining the contribution concentration of the heavy point contamination source described above.
The apparatus 900 may also include a power component 926 configured to perform power management of the apparatus 900, a wired or wireless network interface 950 configured to connect the apparatus 900 to a network, and an input/output interface 958. The apparatus 900 may operate based on an operating system stored in the memory 932.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure. This disclosure is intended to cover any adaptations, uses, or adaptations of the disclosure following the general principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It is to be understood that the present disclosure is not limited to the precise arrangements and instrumentalities shown in the drawings, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (11)
1. A method of determining a concentration of contribution of a heavy point source of contamination, comprising:
dividing a sub-source list into a plurality of sub-source sub-lists under the condition that the number of target pollution sources in a simulation grid of the sub-source list is a plurality of, wherein the sub-source list is a list formed by the target pollution sources, and one simulation grid in the sub-source sub-list is used for indicating the pollutant discharge amount of one target pollution source;
Inputting the multiple sub-source lists, the source mark files and the receptor files into an air quality model to obtain the contribution concentration of the target pollution source corresponding to the simulation grid to the site pollutant concentration of the monitoring site; the source marking file is used for marking a target pollution source corresponding to the simulation grid, the receptor file comprises a position of a monitoring station in the sub-source list, and the air quality model comprises a third-generation air quality model.
2. The method of claim 1, wherein inputting the plurality of sub-lists of sub-sources, the source signature file, and the receptor file into an air quality model to obtain a contribution concentration to a site contaminant concentration of a monitoring site of a contamination source corresponding to the simulation grid, comprises:
and inputting the plurality of sub-lists of the molecular sources, the source mark file, the receptor file and the background list into an air quality model to obtain the contribution concentration, wherein the background list is a list formed by non-target pollution sources.
3. The method according to claim 2, wherein the method further comprises:
coupling the plurality of sub-source sub-lists with the background list to obtain a total emission list;
And inputting the total emission list into the air quality model to obtain the pollutant concentration of the pollution source corresponding to each grid in the total emission list.
4. The method according to claim 1, wherein the method further comprises:
and under the condition that the number of target pollution sources in the simulation grid of the sub-source list is one, inputting the sub-source list, the source mark file and the receptor file into an air quality model to obtain the contribution concentration.
5. The method according to claim 1, wherein the method further comprises:
acquiring the position information of the target pollution source;
intersecting the position information of the target pollution source with the simulation grid to obtain a map file;
and marking grids with the target pollution source in the map file by adopting different identifiers to obtain the source marking file.
6. The method according to claim 1, wherein the method further comprises:
acquiring the position information of the monitoring station;
intersecting the position information of the monitoring station with the simulation grid to obtain the position of the monitoring station in the simulation grid;
And obtaining the receptor file according to the position of the monitoring station point in the simulation grid.
7. The method of claim 1, wherein in the case where the number of target pollution sources in the simulation grid of the split source list is a plurality, dividing the split source list into a plurality of split source sub-lists comprises:
under the condition that the number of target pollution sources in the simulation grids of the sub-source list is a plurality of, determining target grids with the largest number of target pollution sources in the simulation grids;
and dividing the sub-source list into sub-source sub-lists of the target number according to the target number of the target pollution sources in the target grid.
8. The method according to claim 1, wherein the method further comprises:
determining, for each of a plurality of weather patterns, a concentration of contribution of a plurality of target pollution sources to the site pollutant concentration during the pollution of said each weather pattern;
screening a pollution source to be controlled corresponding to a target contribution concentration greater than a preset contribution concentration from the contribution concentrations;
and establishing an association relation between the pollution source to be managed and controlled and the weather type.
9. An apparatus for determining a concentration of a contribution of a heavy point source of contamination, comprising:
A dividing module configured to divide a sub-source list into a plurality of sub-source lists in a case that the number of target pollution sources is a plurality of in-model grids of the sub-source list, wherein the sub-source list is a list formed by the target pollution sources, and one of the sub-source lists is used for indicating pollutant discharge amount of one target pollution source;
the simulation module is configured to input the multiple sub-lists of the sub-sources, the source mark files and the receptor files into an air quality model to obtain contribution concentration of a target pollution source corresponding to the simulation grid to site pollutant concentration of a monitoring site; the source marking file is used for marking a target pollution source corresponding to the simulation grid, and the receptor file comprises the position of the monitoring site in the simulation grid.
10. An apparatus for determining a concentration of a contribution of a heavy point source of contamination, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to:
performing the steps of the method of any one of claims 1 to 8.
11. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the steps of the method of any of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311020008.XA CN116739224B (en) | 2023-08-14 | 2023-08-14 | Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311020008.XA CN116739224B (en) | 2023-08-14 | 2023-08-14 | Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116739224A true CN116739224A (en) | 2023-09-12 |
| CN116739224B CN116739224B (en) | 2023-11-03 |
Family
ID=87911777
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311020008.XA Active CN116739224B (en) | 2023-08-14 | 2023-08-14 | Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116739224B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117610895A (en) * | 2024-01-23 | 2024-02-27 | 中科三清科技有限公司 | Method and device for determining heavy point pollution source management and control time, electronic equipment and medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111523717A (en) * | 2020-04-15 | 2020-08-11 | 北京工业大学 | Inversion estimation method for atmospheric pollutant emission list |
| CN112418609A (en) * | 2020-10-30 | 2021-02-26 | 暨南大学 | Surface-grid-point-based accurate tracing method for secondary atmospheric pollution |
| CN114371260A (en) * | 2022-01-17 | 2022-04-19 | 上海蓝科石化环保科技股份有限公司 | Gridding monitoring, diffusion early warning and tracing method for non-organized VOCs of industrial enterprise |
| CN114757807A (en) * | 2022-06-13 | 2022-07-15 | 江苏省生态环境监测监控有限公司 | Multi-mode fused online accounting method for actual emission of atmospheric pollutants |
| CN116415408A (en) * | 2022-12-07 | 2023-07-11 | 中国气象科学研究院 | VOCs emission source list dynamic inversion method based on four-dimensional variation assimilation |
-
2023
- 2023-08-14 CN CN202311020008.XA patent/CN116739224B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111523717A (en) * | 2020-04-15 | 2020-08-11 | 北京工业大学 | Inversion estimation method for atmospheric pollutant emission list |
| WO2021208393A1 (en) * | 2020-04-15 | 2021-10-21 | 北京工业大学 | Inversion estimation method for air pollutant emission inventory |
| CN112418609A (en) * | 2020-10-30 | 2021-02-26 | 暨南大学 | Surface-grid-point-based accurate tracing method for secondary atmospheric pollution |
| CN114371260A (en) * | 2022-01-17 | 2022-04-19 | 上海蓝科石化环保科技股份有限公司 | Gridding monitoring, diffusion early warning and tracing method for non-organized VOCs of industrial enterprise |
| CN114757807A (en) * | 2022-06-13 | 2022-07-15 | 江苏省生态环境监测监控有限公司 | Multi-mode fused online accounting method for actual emission of atmospheric pollutants |
| CN116415408A (en) * | 2022-12-07 | 2023-07-11 | 中国气象科学研究院 | VOCs emission source list dynamic inversion method based on four-dimensional variation assimilation |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117610895A (en) * | 2024-01-23 | 2024-02-27 | 中科三清科技有限公司 | Method and device for determining heavy point pollution source management and control time, electronic equipment and medium |
| CN117610895B (en) * | 2024-01-23 | 2024-04-16 | 中科三清科技有限公司 | Method and device for determining heavy point pollution source management and control time, electronic equipment and medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116739224B (en) | 2023-11-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101350012B (en) | Method and system for matching address | |
| Openshaw | Learning to live with errors in spatial databases | |
| CN116739224B (en) | Method, apparatus and storage medium for determining contribution concentration of heavy point pollution source | |
| CN101299834B (en) | Method for checking base station position | |
| Nguyen et al. | Development of the typical driving cycle for buses in Hanoi, Vietnam | |
| CN111178786B (en) | Emission source position determining method and system for guaranteeing regional air quality | |
| CN112800165B (en) | Industrial cluster positioning method and device based on clustering algorithm and electronic equipment | |
| CN111753906B (en) | Method and device for clustering pollutant transmission tracks, electronic equipment and storage medium | |
| CN112526639B (en) | Air quality forecasting method and device and storage medium | |
| CN112669190A (en) | Detection method and device for abnormal emission behavior of pollution source and computer equipment | |
| Middleton et al. | Mosaic v1. 1: landscape scenario creation software for simulation of pollen dispersal and deposition | |
| CN114881814A (en) | Natural resource comprehensive investigation technical method | |
| CN116739222B (en) | Method and device for determining pollutant concentration contribution value of road moving source | |
| Nitta et al. | canaper: Categorical analysis of neo‐and paleo‐endemism in R | |
| CN116228501B (en) | Pollution discharge exceeding area industry determining method and device, storage medium and electronic equipment | |
| CN109977190B (en) | Large-scale vector map data-oriented area query processing method and device | |
| CN111815178A (en) | Air quality standard-reaching analysis method and device, electronic equipment and storage medium | |
| CN111666368A (en) | Data processing method and device, storage medium and terminal | |
| CN115094815B (en) | Watering operation control method and device, electronic equipment and storage medium | |
| CN112926029A (en) | Residential area identification and division method for rural domestic sewage treatment | |
| CN112561145A (en) | Ozone pollution control sensitive area forecasting method, storage medium and terminal | |
| Uzhinskiy et al. | Management of environmental monitoring data: UNECE ICP Vegetation case | |
| CN116933349B (en) | Human activity intensity acquisition method and device, storage medium and electronic equipment | |
| Perdana et al. | WebGIS-Based Soil Fertility Information System in Cibodas Botanical Garden | |
| CN116541574B (en) | Intelligent extraction method, device, storage medium and equipment for map sensitive information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |