CN115204759A - Local list gridding manufacturing method and device based on multi-source data - Google Patents
Local list gridding manufacturing method and device based on multi-source data Download PDFInfo
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Abstract
The invention provides a local list gridding manufacturing method and device based on multi-source data, relating to the technical field of environmental protection and comprising the following steps: acquiring a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area; calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list; constructing high-resolution spatial grid information data of a target area based on the first target data; based on the mode configuration file and the high-resolution spatial grid information data, the spatial distribution, the time distribution and the species distribution are sequentially carried out on the total emission amount to obtain spatial distribution local emission source list gridding data, time distribution local emission source list gridding data and species distribution local emission source list gridding data, and the technical problem that the accuracy of the existing local emission source list gridding data is low is solved.
Description
Technical Field
The invention relates to the technical field of environmental protection, in particular to a local list gridding manufacturing method and device based on multi-source data.
Background
The air quality numerical model has become an important scientific tool for researching air quality at present. The mode gridding emission source is used as an important component of the air quality numerical mode, and influences the simulation effect of the air quality numerical mode. Therefore, the high-resolution mode gridding emission source is indispensable, and the local high-resolution mode gridding emission source can be generated by local grid emission source list gridding, so that accurate prediction and early warning are carried out on the local air quality, and a scientific basis is provided for making an air quality decision.
However, the local grid data of the emission source list, which is manufactured by the existing high-resolution mode grid data manufacturing method of the emission source, has the problems of low accuracy and quality, poor universality and the like.
No effective solution has been proposed to the above problems.
Disclosure of Invention
In view of this, the present invention provides a local inventory gridding production method and device based on multi-source data, so as to alleviate the technical problem that the accuracy of the existing local discharge source inventory gridding data is low.
In a first aspect, an embodiment of the present invention provides a local manifest gridding manufacturing method based on multi-source data, including: acquiring a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, wherein the local emission source lists corresponding to different emission source list templates comprise different emission source data types, and the first target data comprises: geographic information data and satellite data; calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, wherein the second target data comprises: an emissions manifest factor and a pattern profile, wherein the pattern profile comprises: the method comprises the following steps of (1) selecting a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes; constructing high-resolution spatial grid information data of the target region based on the first target data; and sequentially performing space distribution, time distribution and species distribution on the emission total amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list gridding data, time distribution local emission source list gridding data and species distribution local emission source list gridding data.
Further, the geographic information data includes: administrative division longitude and latitude data and population distribution data; the satellite data includes: land use type data and night light data.
Further, the total emission amount is calculated by the formula
Wherein, in the process,
is a species of
Industry
The corresponding total amount of emissions is,
for the trade
Corresponding to the total amount of the discharged gas,
is a species of
Industry
The corresponding discharge factor is used to determine the discharge rate,
for the trade
The corresponding level of activity is determined by the activity level,
to remove efficiency.
Further, constructing high resolution spatial grid information data of the target region based on the first target data, comprising: based on a preset resolution, carrying out grid division on the satellite data to obtain satellite space grid information; and carrying out normalization processing on the satellite space grid information and the population distribution data to obtain the high-resolution space grid information data.
Further, based on the mode configuration file and the high-resolution spatial grid information data, sequentially performing spatial distribution, time distribution and species distribution on the total emission amount to obtain spatial distribution local emission source list gridding data, time distribution local emission source list gridding data and species distribution local emission source list gridding data, and the method comprises the following steps of: performing space distribution on the total emission amount based on the mode configuration file to obtain a space distribution result; adding the space distribution result to the high-resolution space grid information data to obtain grid data of the space distribution local emission source list; time distribution is carried out on the grid data of the space distribution local emission source list, and the grid data of the time distribution local emission source list is obtained; and carrying out species distribution on the time distribution local emission source list gridding data to obtain the species distribution local emission source list gridding data.
In a second aspect, an embodiment of the present invention further provides a device for making a local manifest grid based on multi-source data, including: the system comprises an acquisition unit, a calculation unit, a construction unit and a distribution unit, wherein the acquisition unit is used for acquiring a local emission source list filled by a user through an emission source list template in a target area and first target data of the target area, the local emission source lists corresponding to different emission source list templates comprise different emission source data types, and the first target data comprises: geographic information data and satellite data; the calculation unit is configured to calculate, based on the local emission source list and second target data corresponding to the local emission source list, an emission total amount corresponding to the local emission source list, where the second target data includes: an emissions manifest factor and a pattern profile, wherein the pattern profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes; the construction unit is used for constructing high-resolution spatial grid information data of the target area based on the first target data; and the distribution unit is used for sequentially performing space distribution, time distribution and species distribution on the total emission amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data.
Further, the geographic information data includes: administrative division longitude and latitude data and population distribution data; the satellite data includes: land use type data and night light data.
Further, the total emission amount is calculated by the formula
Wherein, in the step (A),
is a species of
Industry
The corresponding total amount of emissions is,
for the trade
Corresponding to the total amount of the discharged gas,
is a species of
Industry
The corresponding discharge factor is used to determine the discharge rate,
for the trade
The corresponding level of activity is determined by the activity level,
to remove efficiency.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory and a processor, where the memory is used to store a program that supports the processor to execute the method in the first aspect, and the processor is configured to execute the program stored in the memory.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored.
In the embodiment of the present invention, by obtaining a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, where local emission source lists corresponding to different emission source list templates include different emission source data types, the first target data includes: geographic information data and satellite data; calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, wherein the second target data comprises: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes; constructing high-resolution spatial grid information data of the target area based on the first target data; and sequentially performing space distribution, time distribution and species distribution on the emission total amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data, so that the aim of manufacturing the local emission source list grid data with higher accuracy is fulfilled, the technical problem of lower accuracy of the conventional local emission source list grid data is solved, and the technical effect of providing scientific basis for accurate air quality prediction and air quality decision is realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a local inventory gridding manufacturing method based on multi-source data according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a local inventory gridding manufacturing apparatus based on multi-source data according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
in accordance with an embodiment of the present invention, there is provided an embodiment of a method for local inventory grid-based production of multi-source data, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer-executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flowchart of a local inventory gridding manufacturing method based on multi-source data according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area are obtained, wherein the local emission source lists corresponding to different emission source list templates comprise different emission source data types, and the first target data comprise: geographic information data and satellite data;
in an embodiment of the present invention, the emission source manifest template includes the following three: the emission source list template 1 mainly comprises data information such as time, industry, species and region; the emission source list template 2 mainly comprises data information of industry, species, regions, points and the like; the emission source list template 3 mainly comprises data information such as regions, point locations, industry factors and the like, wherein the different industries and the different industry factors are different
For example, fossil fuels are fixed combustion sources, with industry factors consisting of sector industry, fuels, fuel technology, unit and annual total consumption. The differences between the different emission source inventory templates are detailed in the following table.
The geographic information data includes: administrative division longitude and latitude data and population distribution data; the satellite data includes: land use type data and night light data.
In addition, it is also noted that different emissions source manifest templates correspond to different libraries of emissions manifest factors. The more detailed the inventory template, the slower the rate of loading the emissions inventory factor library.
Step S104, calculating a total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, where the second target data includes: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes;
it should be noted that, in the embodiment of the present invention, there are a plurality of international mainstream air quality value patterns such as air quality value patterns CMAQ, CAMx, and WRFChem.
The total emission is calculated by the formula
Wherein, in the step (A),
is a species of
Industry
The corresponding total amount of emissions is,
for the trade
Corresponding to the total amount of the discharged gas,
is a species of
Industry
The corresponding emission factor is set to be,
for the trade
The corresponding level of activity is determined by the activity level,
to remove efficiency.
Step S106, based on the first target data, constructing high-resolution space grid information data of the target area;
and S108, sequentially performing space distribution, time distribution and species distribution on the total emission amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data.
In the embodiment of the present invention, by obtaining a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, where local emission source lists corresponding to different emission source list templates include different emission source data types, the first target data includes: geographic information data and satellite data; calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, wherein the second target data comprises: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes; constructing high-resolution spatial grid information data of the target region based on the first target data; and sequentially performing space distribution, time distribution and species distribution on the emission total amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data, so that the aim of manufacturing the local emission source list grid data with higher accuracy is fulfilled, the technical problem of lower accuracy of the conventional local emission source list grid data is solved, and the technical effect of providing scientific basis for accurate air quality prediction and air quality decision is realized.
In the embodiment of the present invention, step S104 includes the following steps:
step S11, based on a preset resolution, carrying out grid division on the satellite data to obtain satellite space grid information;
and S12, carrying out normalization processing on the satellite space grid information and the population distribution data to obtain high-resolution space grid information data.
The above steps will be described below by taking the target region as beijing as an example.
Firstly, downloading corresponding MOIDS high-resolution satellite data according to the MODIS satellite data China regional industry serial number, wherein the high-resolution satellite data comprises: land use type data and night light data;
the land utilization types include urban construction land, agricultural land, forest, grassland, desert and the like, and the grid distribution rationality of the emission list can be increased due to the detailed land utilization types. The data such as night lamp can reflect the economic development degree of the area to a certain extent, and the grid distribution scientificity of the emission list can be increased by combining the data such as population.
Because the satellite data of different area row and column numbers have certain data dislocation, the origin of coordinates can be determined by calculating coordinate drift, and then data splicing is carried out.
Then, the spliced satellite data is re-projected, and high-resolution satellite grid data in a Chinese range are cut out.
And after the high-resolution satellite grid data of the Chinese range is obtained, dividing longitude and latitude data according to the administrative division of Beijing city.
In the high-resolution satellite grid data of the Chinese range, the longitude and latitude data of Beijing city are indexed, and the range of the Beijing city in the satellite grid data is drawn.
Because the data grids of different satellite data have different sizes, the satellite data of different types (such as land utilization type satellite data, night light data, and the like) need to be processed with uniform grid size to obtain satellite space grid information.
And carrying out normalization processing on the satellite space grid information. Dividing each grid by the total population, such as demographic distribution data; for example, in the agricultural land utilization type, the grid value of each representative agricultural land is 1, and the values of other non-agricultural lands are 0.
And obtaining the high-resolution spatial grid information data of Beijing.
In the embodiment of the present invention, step S108 includes the following steps:
step S21, carrying out space distribution on the total emission amount based on the mode configuration file to obtain a space distribution result;
step S22, adding the space distribution result to the high-resolution space grid information data to obtain grid data of the space distribution local emission source list;
step S23, performing time distribution on the grid data of the space distribution local emission source list to obtain the grid data of the time distribution local emission source list;
and S24, carrying out species distribution on the time distribution local emission source list gridding data to obtain the species distribution local emission source list gridding data.
In the embodiment of the invention, firstly, the information such as the pattern mesh in the pattern configuration file is read in and matched with the pattern setting range in the high-resolution mesh information data. When the space distribution processing is carried out, the integrated high-resolution space grid data of different types can be distributed through different weight distribution methods, so that grid data of the list of the space distribution local discharge sources are obtained, for example, for an industrial discharge source, night lamp data and industrial construction land data in a land utilization type occupy a large distribution proportion, and for an agricultural discharge source, agricultural farmland data in the land utilization type occupy a large distribution proportion.
And then, the mode configuration file contains basic mode grid information and time scale distribution scheme information such as emission source days, weeks and months of different industries. And performing data dimension increasing treatment on the gridding data of the spatial distribution local emission source list, reading in daily variation coefficients of different industries in the mode configuration file, and further generating emission source data of each industry with daily emission characteristics. And similarly, data of time scales such as weeks and months can be further obtained, and finally grid data of the time distribution local emission source list are generated.
Finally, due to different chemical mechanisms adopted by different modes (CMAQ, CAMx, WRFChem and the like), corresponding emission source input data are different, and the difference is mainly reflected in that the chemical species of the emission source input data are different. The mode configuration file comprises a chemical mechanism species preset allocation scheme of a common mode, and mode chemical species allocation of each emission species industry by industry is carried out by reading in a local list gridding emission source B.
For example, CMAQ may select a CB6AE7 chemistry scheme with emission source input data containing 62 emission source species variables of ACET, ACROLEIN, ALD2, NO2, PMC, PSO4, etc., and then distribute these 62 species variables industry by industry and species by species through the local inventory gridded emission source B obtained in step 8. The distribution method comprises the following steps:
case 1: if the emission source species variable PMC represents coarse particles, only one of the 62 emission source species variables in the mode represents the coarse particles, and the total emission data of the emission source of the industrial industry of the file B, which represents the coarse particles, can be totally divided into the PMC variable to give a distribution coefficient of 1;
case 2: if the emission source species variable ACET represents a volatile substance, the 62 mode emission source species variables include a plurality of volatile species variables, and the different volatile species variables have different weights, the total amount of emission source data representing the volatile substance in the industrial emission source of the document B may be given to the distribution coefficients corresponding to the different volatile species variables such as ACET (different distribution coefficients corresponding to different species are given in the mode configuration file) according to different weights, and the sum of the total distribution coefficients obtained by the volatile species variables should be 1.
Thus, after species distribution of the industrial industry is carried out on 62 species variables, a species emission source C0 of the industrial industry can be generated, and the treatment is carried out in the same way with other industries to obtain C1 and C2 \8230, and if a gridding emission source is obtained by division, the emission source can be obtained through output. Otherwise, continuing to summarize the gridding emission sources of the C0, C1, C2 and other industries, and finally obtaining the local list gridding emission source C.
Similarly, the CB6 chemical mechanism solution of CAMx contains 54 emission source species variables such as ACET, ALD2, SO2, XYL, etc., and the RADM2 chemical mechanism solution of WRFChem contains 31 emission source species variables such as E _ CO, E _ NO, E _ ALD, E _ XYL, etc., and after the species assignment, species assignment local emission source list gridding data can be obtained.
In the embodiment of the invention, data sources required by making the grid data of the local list are multi-sourced, and data such as population, land use types, night lamps and the like are fully considered, so that grid distribution of emission sources is more reasonable, mode emission sources are more credible, and mode simulation effect is more reliable.
Meanwhile, the corresponding mode gridding emission source can be customized and generated according to the emission source list data with different detail degrees provided by the user. The problem that a user cannot make a local gridding emission source with a certain credibility due to insufficient emission source data and the like is avoided.
Example two:
the embodiment of the invention also provides a local list gridding manufacturing method and device based on multi-source data, which are used for executing the local list gridding manufacturing method and device based on the multi-source data provided by the embodiment of the invention.
As shown in fig. 2, fig. 2 is a schematic diagram of the local inventory gridding manufacturing method device based on multi-source data, where the local inventory gridding manufacturing method device based on multi-source data includes: an acquisition unit 10, a calculation unit 20, a construction unit 30 and an allocation unit 40.
The acquiring unit is configured to acquire a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, where local emission source lists corresponding to different emission source list templates include different emission source data types, and the first target data includes: geographic information data and satellite data;
the calculation unit is configured to calculate, based on the local emission source list and second target data corresponding to the local emission source list, an emission total amount corresponding to the local emission source list, where the second target data includes: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes;
the construction unit is used for constructing high-resolution spatial grid information data of the target area based on the first target data;
and the distribution unit is used for sequentially performing space distribution, time distribution and species distribution on the total emission amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data.
In the embodiment of the present invention, by obtaining a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, where local emission source lists corresponding to different emission source list templates include different emission source data types, the first target data includes: geographic information data and satellite data; calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, wherein the second target data comprises: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes; constructing high-resolution spatial grid information data of the target area based on the first target data; and sequentially performing space distribution, time distribution and species distribution on the emission total amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data, so that the aim of manufacturing the local emission source list grid data with higher accuracy is fulfilled, the technical problem of lower accuracy of the conventional local emission source list grid data is solved, and the technical effect of providing scientific basis for accurate air quality prediction and air quality decision is realized.
Example three:
an embodiment of the present invention further provides an electronic device, including a memory and a processor, where the memory is used to store a program that supports the processor to execute the method described in the first embodiment, and the processor is configured to execute the program stored in the memory.
Referring to fig. 3, an embodiment of the present invention further provides an electronic device 100, including: the device comprises a processor 50, a memory 51, a bus 52 and a communication interface 53, wherein the processor 50, the communication interface 53 and the memory 51 are connected through the bus 52; the processor 50 is arranged to execute executable modules, such as computer programs, stored in the memory 51.
The Memory 51 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 53 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used.
The bus 52 may be an ISA bus, a PCI bus, an EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
The memory 51 is used for storing a program, the processor 50 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 50, or implemented by the processor 50.
The processor 50 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by instructions in the form of hardware integrated logic circuits or software in the processor 50. The Processor 50 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 51, and the processor 50 reads the information in the memory 51 and completes the steps of the method in combination with the hardware.
Example four:
the embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the method in the first embodiment.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplification of description, but do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A local inventory gridding manufacturing method based on multi-source data is characterized by comprising the following steps:
acquiring a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, wherein local emission source lists corresponding to different emission source list templates contain different emission source data types, and the first target data comprises: geographic information data and satellite data;
calculating the total emission amount corresponding to the local emission source list based on the local emission source list and second target data corresponding to the local emission source list, wherein the second target data comprises: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes;
constructing high-resolution spatial grid information data of the target area based on the first target data;
and sequentially performing space distribution, time distribution and species distribution on the emission total amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list gridding data, time distribution local emission source list gridding data and species distribution local emission source list gridding data.
2. The method of claim 1,
the geographic information data includes: administrative division longitude and latitude data and population distribution data;
the satellite data includes: land use type data and night light data.
3. The method of claim 1,
the total emission amount is calculated by the formula
Wherein, in the step (A),
is a species of
Industry
The corresponding total amount of emissions is,
for the trade
Corresponding to the total amount of the discharged gas,
is a species of
Industry
The corresponding emission factor is set to be,
for the trade
The corresponding level of activity is determined by the activity level,
to remove efficiency.
4. The method of claim 2, wherein constructing high resolution spatial grid information data for the target region based on the first target data comprises:
based on a preset resolution, carrying out grid division on the satellite data to obtain satellite space grid information;
and carrying out normalization processing on the satellite space grid information and the population distribution data to obtain the high-resolution space grid information data.
5. The method of claim 1, wherein sequentially performing space allocation, time allocation and species allocation on the total emission amount based on the mode configuration file and the high-resolution spatial grid information data to obtain spatial allocation local emission source list gridding data, time allocation local emission source list gridding data and species allocation local emission source list gridding data comprises:
performing space distribution on the total emission amount based on the mode configuration file to obtain a space distribution result;
adding the space distribution result to the high-resolution space grid information data to obtain grid data of the space distribution local emission source list;
time distribution is carried out on the grid data of the space distribution local emission source list, and the grid data of the time distribution local emission source list is obtained;
and carrying out species distribution on the time distribution local emission source list gridding data to obtain the species distribution local emission source list gridding data.
6. A local inventory gridding production device based on multi-source data is characterized by comprising: an acquisition unit, a calculation unit, a construction unit and an allocation unit, wherein,
the acquiring unit is configured to acquire a local emission source list filled by a user in a target area through an emission source list template and first target data of the target area, where local emission source lists corresponding to different emission source list templates include different emission source data types, and the first target data includes: geographic information data and satellite data;
the calculation unit is configured to calculate, based on the local emission source list and second target data corresponding to the local emission source list, an emission total amount corresponding to the local emission source list, where the second target data includes: an emissions manifest factor and a mode profile, wherein the mode profile comprises: the system comprises a plurality of air quality value modes, emission source classification selection conditions corresponding to the air quality value modes and emission source requirements corresponding to the air quality value modes;
the construction unit is used for constructing high-resolution spatial grid information data of the target area based on the first target data;
and the distribution unit is used for sequentially performing space distribution, time distribution and species distribution on the total emission amount based on the mode configuration file and the high-resolution space grid information data to obtain space distribution local emission source list grid data, time distribution local emission source list grid data and species distribution local emission source list grid data.
7. The apparatus of claim 6,
the geographic information data includes: administrative division longitude and latitude data and population distribution data;
the satellite data includes: land use type data and night light data.
8. The apparatus of claim 6,
the total emission amount is calculated by the formula
Wherein, in the step (A),
is a species of
Industry
The corresponding total amount of emissions is,
for the trade
Corresponding to the total amount of the discharged gas,
is a species of
Industry
The corresponding emission factor is set to be,
for the trade
The corresponding level of activity is determined by the activity level,
to remove efficiency.
9. An electronic device comprising a memory for storing a program that enables a processor to perform the method of any of claims 1 to 5 and a processor configured to execute the program stored in the memory.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of the claims 1 to 5.
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