CN115203879A - Carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology - Google Patents
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Abstract
The invention relates to the technical field of environmental monitoring, in particular to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, which has accurate source identification and provides scientific and feasible identification, tracking and judgment basis for finding out carbon emission sources; the method comprises the steps of (1) extracting and counting high-concentration pixel points of satellite remote sensing products, (2) obtaining ground observation data, (3) performing reverse simulation analysis and calculation, (4) performing atmosphere backward trajectory model cluster analysis, (5) establishing an electronic pollution map, and (6) identifying carbon emission sources and emission units.
Description
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to a carbon neutralization greenhouse gas emission identification method based on a big data correlation analysis technology.
Background
Since the industrial revolution, greenhouse gases such as carbon dioxide and methane emitted by human beings are important factors causing global warming, wherein the carbon dioxide and the methane are the most important greenhouse gases, and therefore, the control of artificial carbon emission is the most core means for slowing down global warming.
Disclosure of Invention
In order to solve the technical problems, the invention provides the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, which has accurate source identification and provides scientific and feasible identification, tracking and judgment basis for finding out the carbon emission source.
The invention discloses a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, which comprises the steps of (1) extracting and counting high-concentration pixel points of satellite remote sensing products, (2) obtaining ground observation data, (3) performing reverse simulation analysis and calculation, (4) performing atmospheric backward trajectory model cluster analysis, (5) establishing an electronic pollution map, and (6) identifying carbon emission sources and emission units.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the high-concentration pixel points of the satellite remote sensing products are extracted and counted based on the satellite remote sensing products, the concentrations of main greenhouse gases, namely methane and carbon dioxide, are inverted, compared with the inverted data values of the data products in the same period and in the same region, the main greenhouse gases, namely the methane and the carbon dioxide, are verified mutually and verified mutually, the reliability and the accuracy of the near-ground atmospheric methane and carbon dioxide concentration products are ensured, and the greenhouse gas space-time distribution characteristics are obtained on a large scale.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the obtained ground observation data are compared with the inversion result of the satellite remote sensing product based on the ground observation station, the space-time distribution characteristics are analyzed, and the satellite product precision is further corrected.
The invention discloses a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the atmosphere backward trajectory model clustering analysis is based on near-ground greenhouse gas observation data, the atmosphere backward trajectory model is used for identifying the movement trajectories of greenhouse gas agglomerates and particles in the atmosphere, and the emission source is further verified.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology.
The carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology is characterized in that a carbon emission source and an emission unit are identified, the carbon emission source is identified and verified by utilizing reverse simulation calculation and atmosphere backward trajectory model cluster analysis based on satellite remote sensing data and ground observation data of multiple verification and inversion, the gas emission unit is further accurately identified by combining an enterprise electronic pollution map, and a specific emission source is locked.
The invention discloses a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, and the detection data of satellite remote sensing products are mutually verified.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, wherein the electronic pollution map is established by compiling a source list result by using an IPCC method, verifying the reliability through transverse and longitudinal comparison, and leading into a Geographic Information System (GIS) after no error so as to form a dynamic electronic pollution map.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, disclosed by the invention, the atmosphere chemical transmission reverse simulation based on the satellite remote sensing and ground observation data assimilation technology is analyzed and calculated through reverse simulation, so that the uncertainty of greenhouse gas emission estimation is reduced.
The invention discloses a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, which is used for identifying a carbon emission source and an emission unit by comprehensively utilizing satellite remote sensing data, ground monitoring data and an enterprise electronic map, combining reverse simulation calculation and atmosphere backward trajectory model clustering analysis, and accurately identifying the carbon emission source from a large scale to a small scale to a micro scale and finally to the emission unit.
Compared with the prior art, the invention has the beneficial effects that: the system utilizes comprehensive utilization of satellite remote sensing data, ground monitoring data and an enterprise electronic pollution map, adopts reverse simulation calculation and atmospheric backward trajectory model clustering analysis, accurately identifies high-emission areas and emission units, adopts mutual evidence of identification technology, is accurate in source identification, can finely arrive at specific units, and provides scientific and feasible identification, tracking, judgment basis and working tongs for finding out carbon emission sources.
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FIG. 1 is a technical roadmap for the present invention;
Detailed Description
The following detailed description of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
As shown in fig. 1, the method for identifying carbon-neutral greenhouse gas emission based on big data correlation analysis technology of the present invention comprises (1) extracting and counting high concentration pixel points of satellite remote sensing products, (2) obtaining ground observation data, (3) performing reverse simulation analysis and calculation, (4) performing atmospheric backward trajectory model clustering analysis, (5) establishing an electronic pollution map, and (6) identifying carbon emission sources and emission units; the system utilizes comprehensive utilization of satellite remote sensing data, ground monitoring data and an enterprise electronic pollution map, adopts reverse simulation calculation and atmospheric backward trajectory model clustering analysis, can accurately identify high-emission areas and emission units, has mutual evidence of identification technology, is accurate in source identification, can be more precise to specific units, and provides scientific and feasible identification, tracking, judgment basis and working hand grips for finding carbon emission sources.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the high-concentration pixel points of the satellite remote sensing products are extracted and counted based on the satellite remote sensing products, the concentrations of main greenhouse gases, namely methane and carbon dioxide, are inverted, compared with the inverted data values of the data products in the same period and in the same region, the main greenhouse gases, namely the methane and the carbon dioxide, are verified mutually and verified mutually, the reliability and the accuracy of the near-ground atmospheric methane and carbon dioxide concentration products are ensured, and the greenhouse gas space-time distribution characteristics are obtained on a large scale.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the obtained ground observation data are compared with the inversion result of the satellite remote sensing product based on the ground observation station, the space-time distribution characteristics are analyzed, and the satellite product precision is further corrected.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, the atmosphere backward trajectory model clustering analysis is based on near-ground greenhouse gas observation data, the atmosphere backward trajectory model is used for identifying the movement trajectories of greenhouse gas agglomerates and particles in the atmosphere, and the emission source is further verified.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, which comprises the steps of establishing an electronic pollution map, establishing an enterprise database based on literature data and actual investigation, comprehensively understanding carbon emission characteristics of an enterprise, and establishing a dynamic electronic pollution map including but not limited to enterprise names, addresses, longitudes and latitudes, responsible persons, contact ways, greenhouse gas emission sources, emission amount and the like by combining a Geographic Information System (GIS).
The carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology is characterized in that a carbon emission source and an emission unit are identified, the carbon emission source is identified and verified by utilizing reverse simulation calculation and atmosphere backward trajectory model cluster analysis based on satellite remote sensing data and ground observation data of multiple verification and inversion, the gas emission unit is further accurately identified by combining an enterprise electronic pollution map, and a specific emission source is locked.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, wherein the detection data of a satellite remote sensing product are mutually verified, and the detection data comprise but are not limited to Japanese greenhouse gas observation satellites, atmospheric infrared detectors AIRS carried on American satellites Aqua and carbon satellites in China.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, wherein electronic pollution map establishment is realized by compiling a source list result by using an IPCC method, verifying reliability through transverse and longitudinal comparison and leading in a Geographic Information System (GIS) after no error, so that a dynamic electronic pollution map is formed.
According to the carbon neutralization greenhouse gas emission identification method based on the big data correlation analysis technology, disclosed by the invention, the atmosphere chemical transmission reverse simulation based on the satellite remote sensing and ground observation data assimilation technology is analyzed and calculated through reverse simulation, so that the uncertainty of greenhouse gas emission estimation is reduced.
The invention discloses a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, which is characterized in that a carbon emission source and an emission unit are identified by comprehensively utilizing satellite remote sensing data, ground monitoring data and an enterprise electronic map, combining reverse simulation calculation and atmosphere backward trajectory model clustering analysis, and accurately identifying the carbon emission source from a large scale to a small scale to a micro scale and finally accurately identifying the emission unit.
The invention relates to a carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology, the basic basis of data assimilation is Bayesian probability analysis theory, and prior estimation of gas emission parameters is reversely optimized by utilizing atmospheric methane concentration measurement data through transmission simulation of an atmospheric Chemical Transmission Mode (CTM), so that the uncertainty of methane emission estimation is reduced. The atmospheric methane emission inverse simulation employs a linear hypothetical algorithm of "synthetic inverse" and the methane concentration change at any location in the atmosphere is considered to be a linear combination of the concentration contributions of the individual emission source methane transmissions to that location.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (11)
1. A carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology is characterized by comprising the steps of (1) extracting and counting high-concentration pixel points of satellite remote sensing products, (2) obtaining ground observation data, (3) performing reverse simulation analysis and calculation, (4) performing atmospheric backward trajectory model clustering analysis, (5) establishing an electronic pollution map, and (6) identifying carbon emission sources and emission units.
2. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the extraction statistics of high concentration pixel points of satellite remote sensing products is based on satellite remote sensing products, the main greenhouse gas methane and carbon dioxide concentrations are inverted, compared with the inverted data values of the data products in the same period and in the same area, and verified mutually, so that the reliability and accuracy of near-ground atmospheric methane and carbon dioxide concentration products are ensured, and the greenhouse gas space-time distribution characteristics are obtained on a large scale.
3. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the obtained ground observation data is based on a ground observation station, compared with the inversion result of the satellite remote sensing product, the space-time distribution characteristics are analyzed, and the satellite product precision is further corrected.
4. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the reverse simulation analysis calculation is based on near-ground greenhouse gas observation data and satellite remote sensing data, greenhouse gas concentration is simulated by using a reverse simulation method, and emission sources are identified.
5. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the atmosphere backward trajectory model cluster analysis is based on near-ground greenhouse gas observation data, and the atmosphere backward trajectory model is used for identifying the movement trajectories of greenhouse gas agglomerates and particles in the atmosphere and further verifying the emission sources.
6. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the establishment of the electronic pollution map is based on literature and actual survey, the establishment of an enterprise database, the comprehensive understanding of the carbon emission characteristics of enterprises, and the establishment of a dynamic electronic pollution map in combination with a Geographic Information System (GIS).
7. The method for identifying carbon-neutral greenhouse gas emission based on big data correlation analysis technology as claimed in claim 1, wherein the carbon emission source and emission unit are identified and verified by using reverse simulation calculation and atmosphere backward trajectory model cluster analysis based on satellite remote sensing data and ground observation data of multiple verification inversion, and the gas emission unit is further accurately identified by combining with an enterprise electronic pollution map to lock a specific emission source.
8. The carbon neutralization greenhouse gas emission identification method based on big data correlation analysis technology as claimed in claim 1, wherein the probe data of the satellite remote sensing product mutually verify.
9. The method for identifying carbon neutralization greenhouse gas emission based on big data correlation analysis technology as claimed in claim 1, wherein the establishing of the electronic pollution map is to utilize IPCC method to compile source list results, compare and verify reliability transversely and longitudinally, and introduce the results into a Geographic Information System (GIS) after no errors, so as to form a dynamic electronic pollution map.
10. The method for identifying carbon neutral greenhouse gas emission based on big data correlation analysis technology according to claim 1, wherein the reverse simulation analysis calculates the atmosphere chemical transmission reverse simulation based on satellite remote sensing and ground observation data assimilation technology, and the uncertainty of greenhouse gas emission estimation is reduced.
11. The method for identifying carbon neutralization greenhouse gas emission based on big data correlation analysis technology as claimed in claim 1, wherein the identification of carbon emission source and emission unit is performed by comprehensively utilizing satellite remote sensing data, ground monitoring data and enterprise electronic map, combining reverse simulation calculation and atmosphere backward trajectory model cluster analysis, and accurately identifying carbon emission source from big scale to small scale to micro scale and finally to emission unit.
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| CN116596158A (en) * | 2023-06-14 | 2023-08-15 | 深圳市汉宇环境科技有限公司 | Regional pollution source emission total prediction method |
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| CN116596158A (en) * | 2023-06-14 | 2023-08-15 | 深圳市汉宇环境科技有限公司 | Regional pollution source emission total prediction method |
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