A multi-channel comprehensive monitoring method for carbon emissions

Abstract

The present invention discloses a multi-channel comprehensive monitoring method for carbon emissions. The method includes: obtaining global-scale atmospheric carbon dioxide concentration and distribution, gas column concentration, and concentration data at preset fixed points; inputting them into the software platform of the carbon emissions monitoring system for visual monitoring; determining whether they are within their respective preset ranges, adding additional fixed points in areas exceeding the preset range, arranging carbon dioxide emission detectors, and using electric drones to fly to obtain atmospheric carbon dioxide concentration and total emissions data; the software platform of the carbon emissions monitoring system conducts real-time monitoring to realize the monitoring of the distribution and change trend of atmospheric carbon dioxide in a three-dimensional environment. The present invention improves the defects of low accuracy and low spatio-temporal resolution of existing carbon emissions monitoring means, realizes a multi-channel carbon emissions data assimilation scheme, provides an effective means for accurately estimating regional and point-source carbon emissions, and improves the reliability of greenhouse gas emission accounting.

Description

Technical Field

[0001] The present invention relates to a comprehensive monitoring method for carbon emissions, belonging to the technical field of atmospheric environment monitoring, and specifically relates to a multi-channel comprehensive monitoring method for carbon emissions. Background Art

[0002] The global climate change caused by carbon emissions has brought severe challenges to the development of human economy and society. At present, in the process of moving towards carbon neutrality, more accurate and rapid monitoring of the carbon dioxide content in the environment is an important way to control carbon emissions.

[0003] At present, a series of technologies for carbon emissions monitoring have been developed internationally. The current mainstream carbon emissions monitoring methods can be roughly divided into two types: one is "bottom-up", that is, carbon emissions are decomposed into several components, then statistically analyzed according to their respective characteristics, and finally the total carbon emissions are obtained by summation; the other is "top-down", that is, based on the observation of atmospheric carbon concentration, the surface carbon emissions are inverted.

[0004] Traditional carbon emissions monitoring mainly relies on ground monitoring networks. Although the method of ground-based monitoring of carbon emissions has the advantages of high accuracy and strong reliability, as a single-point measurement, it cannot conduct large-scale monitoring; while satellite observations have the characteristics of global coverage and high sampling frequency, and can carry out wide-range and long-term continuous monitoring of atmospheric carbon concentration on a global scale, but there are many environmental parameter deviations that will lead to large errors in the inversion results of surface carbon emissions. All in all, there is still a lack of carbon emissions monitoring means with high accuracy and high spatio-temporal resolution. Summary of the Invention

[0005] In order to solve the problems in the background art, the present invention provides a multi-channel comprehensive monitoring method for carbon emissions, which can combine the advantages of "bottom-up" and "top-down" and has high accuracy and high spatio-temporal resolution to solve the deficiencies in the existing carbon emissions monitoring methods.

[0006] The technical solution adopted by the present invention is as follows:

[0007] The comprehensive monitoring method for carbon emissions of the present invention includes the following steps:

[0008] Step 1: Use a carbon satellite equipped with a carbon dioxide data collector to obtain global-scale atmospheric carbon dioxide concentration and distribution data within a preset time range.

[0009] Step 2: Use ground-based carbon dioxide observation stations distributed globally to obtain continuous and accurate global-scale atmospheric carbon dioxide gas column concentration data in real time within a preset time range. The ground-based carbon dioxide observation stations are specifically the Total Carbon Column Observing Network (TCCON) stations.

[0010] Step 3: Obtain the atmospheric carbon dioxide concentration data at each preset fixed point within a preset time range by using carbon dioxide emission detectors distributed at several preset fixed points on a global scale; the carbon dioxide emission detectors can obtain more detailed and accurate atmospheric carbon dioxide concentration data at the preset fixed points to supplement the global-scale atmospheric carbon dioxide concentration obtained by the carbon satellite.

[0011] Step 4: Input all the data obtained in Steps 1-3 into an external carbon emission monitoring system software platform, and use data assimilation methods to perform structured processing and unstructured processing on each data to obtain their respective structured data and unstructured data. The carbon emission monitoring system software platform visualizes all the above data, facilitating the monitoring of the global-scale atmospheric carbon dioxide concentration and distribution, the atmospheric carbon dioxide gas column concentration, and the atmospheric carbon dioxide concentration at each preset fixed point by the carbon emission monitoring system software platform.

[0012] The structured data and unstructured data are presented together through four-dimensional spatio-temporal data to visualize the atmospheric carbon dioxide conditions at each spatio-temporal point; the carbon emission monitoring system software platform can display the four-dimensional spatio-temporal data according to time and space, or can freely choose to display each of the original data in Steps 1-3.

[0013] Step 5: The carbon emission monitoring system software platform determines whether the global-scale atmospheric carbon dioxide concentration, gas column concentration, and the atmospheric carbon dioxide concentration at each preset fixed point are within their respective preset ranges within the preset time range based on all the data obtained in Steps 1-3. If all are within their respective preset ranges, use an electric drone device to fly above each preset fixed point to obtain the total carbon dioxide emissions data above each preset fixed point; if there are several regions within the global scale where the atmospheric carbon dioxide concentration or gas column concentration exceeds their respective preset ranges, add several additional fixed points in each region where the atmospheric carbon dioxide concentration or gas column concentration exceeds their respective preset ranges. Arrange a carbon dioxide emission detector at each additional fixed point to obtain the atmospheric carbon dioxide concentration data at the additional fixed points, and use the electric drone device to fly above each preset fixed point and each additional fixed point to obtain the atmospheric carbon dioxide concentration and total emissions data above each preset fixed point and each additional fixed point.

[0014] Step 6: Input all the data obtained in Step 5 into the carbon emission monitoring system software platform. Use the data assimilation method to perform structured processing and unstructured processing on each data obtained in Step 5 to obtain their respective structured data and unstructured data. The carbon emission monitoring system software platform visualizes each data obtained in Step 5 and their respective structured data and unstructured data, facilitating the carbon emission monitoring system software platform to monitor the concentration and total emissions of atmospheric carbon dioxide at the continuous preset carbon measurement points in the vertical three-dimensional space above each preset fixed point and each additional fixed point, so as to realize the monitoring of the distribution and change trend of atmospheric carbon dioxide in the three-dimensional environment.

[0015] In the said Step 1, the carbon dioxide data collector carried by the carbon satellite is a greenhouse gas detector GMI or a hyperspectral greenhouse gas detector.

[0016] In the said Step 4, the atmospheric carbon dioxide emission data at each preset fixed point are all processed to obtain their own structured data and unstructured data.

[0017] In the said Step 5, a carbon dioxide emission detector, a pitot tube flowmeter and a single-chip microcomputer device are carried on the electric unmanned aerial vehicle device. The carbon dioxide emission detector, the pitot tube flowmeter and the single-chip microcomputer device are all electrically connected. The electric unmanned aerial vehicle device sails above each preset fixed point and each additional fixed point, and monitors at a number of continuous preset carbon measurement points in the vertical three-dimensional space above each preset fixed point and each additional fixed point. The carbon dioxide emission detector obtains the concentration data of atmospheric carbon dioxide at each preset carbon measurement point, and the pitot tube flowmeter obtains the total gas emission data at each preset carbon measurement point, and transmits them to the single-chip microcomputer device together. The single-chip microcomputer device calculates and obtains the total emissions data of atmospheric carbon dioxide by using the pressure difference sensing method through the concentration data of atmospheric carbon dioxide and the total gas emission data. The electric unmanned aerial vehicle device carrying the carbon dioxide emission detector and the pitot tube flowmeter can obtain more detailed and accurate atmospheric carbon dioxide data in the three-dimensional space above the fixed point, and can, by establishing a three-dimensional GIS space, combine the flight track of the unmanned aerial vehicle and the carbon dioxide emission data, and draw the distribution change situation of the carbon emission data of the environmental three-dimensional monitoring on the three-dimensional GIS platform for display.

[0018] The described carbon dioxide emission detector is integrated with a satellite GPS positioning device and a wireless communication device. The carbon dioxide emission detector and the satellite GPS positioning device are both electrically connected to the wireless communication device, and the wireless communication device on the electric drone device is also electrically connected to the single-chip microcomputer device. The satellite GPS positioning device is used to obtain positioning data through positioning, including position coordinates and altitude data, and transmit the positioning data to the wireless communication device. The single-chip microcomputer device transmits the atmospheric carbon dioxide concentration and total emission data to the wireless communication device, and the wireless communication device transmits the time data, positioning data, atmospheric carbon dioxide concentration data, and total emission data to the carbon emission monitoring system software platform in real time.

[0019] The described carbon dioxide emission detector is an NDIR carbon dioxide sensor.

[0020] The beneficial effects of the present invention are:

[0021] A multi-channel comprehensive carbon emission monitoring method of the present invention adopts carbon satellite technology, ground-based carbon dioxide observation technology, distributed carbon dioxide emission detection technology, and carbon dioxide emission detection technology based on electric drones, establishes a multi-channel carbon emission database, and realizes the extraction of high-value carbon emission information that is expandable, identifiable, and interactive.

[0022] The present invention improves the defects of low accuracy and low spatio-temporal resolution of the existing carbon emission monitoring means, realizes a multi-channel carbon emission data assimilation scheme, provides an effective means for accurately estimating regional and point-source carbon emissions, and improves the reliability of greenhouse gas emission accounting. Description of the Drawings

[0023] Figure 1 It is a schematic flow chart of the method of the present invention;

[0024] Figure 2 It is a schematic diagram of the two-dimensional distribution of carbon dioxide concentration in a certain area in an embodiment of the present invention;

[0025] Figure 3 It is a schematic diagram of the three-dimensional distribution of the 4D co-presentation of structured and unstructured data of carbon dioxide concentration in a certain area in an embodiment of the present invention; Detailed Embodiment

[0026] The following further describes the present invention in detail with reference to the drawings and specific embodiments.

[0027] As Figure 1 shown, the comprehensive carbon emission monitoring method of the present invention includes the following steps:

[0028] Step 1: Use a carbon satellite equipped with a carbon dioxide data collector to obtain global-scale atmospheric carbon dioxide concentration and distribution data within a preset time range.

[0029] In Step 1, the carbon dioxide data collector carried by the carbon satellite is a greenhouse gas detector GMI or a hyperspectral greenhouse gas detector.

[0030] Step 2: Use the ground-based carbon dioxide observation stations distributed globally to obtain continuously accurate atmospheric carbon dioxide column concentration data on a global scale within a preset time range. The ground-based carbon dioxide observation stations are specifically the Total Carbon Column Observing Network (TCCON) stations.

[0031] Step 3: Use carbon dioxide emission detectors at several preset fixed points on a global scale to obtain atmospheric carbon dioxide concentration data at each preset fixed point within a preset time range; the carbon dioxide emission detectors can obtain more detailed and accurate atmospheric carbon dioxide concentration data at the preset fixed points to supplement the global-scale atmospheric carbon dioxide concentration obtained by the carbon satellite.

[0032] Step 4: Input all the data obtained in Steps 1 - 3 into an external carbon emissions monitoring system software platform, and use data assimilation methods to perform structured and unstructured processing on each data to obtain their respective structured data and unstructured data. The carbon emissions monitoring system software platform visualizes all the above data to facilitate the monitoring of the global-scale atmospheric carbon dioxide concentration and distribution, atmospheric carbon dioxide column concentration, and atmospheric carbon dioxide concentration at each preset fixed point by the carbon emissions monitoring system software platform.

[0033] In Step 4, the atmospheric carbon dioxide emission data at each preset fixed point is processed to obtain its own structured data and unstructured data.

[0034] The structured data and unstructured data are presented together through four-dimensional spatio-temporal data to visualize the atmospheric carbon dioxide conditions at each spatio-temporal point; the carbon emissions monitoring system software platform can display the four-dimensional spatio-temporal data according to time and space, or can freely choose to display each original data in Steps 1 - 3.

[0035] Step 5: The software platform of the carbon emission monitoring system determines whether the global-scale atmospheric carbon dioxide concentration and column concentration, as well as the atmospheric carbon dioxide concentration at each preset fixed point, are within their respective preset ranges within a preset time range based on all the data obtained in Steps 1-3. If all are within their respective preset ranges, the electric drone device is navigated to above each preset fixed point to obtain the total carbon dioxide emission data above each preset fixed point; if there are several regions within the global scale where the atmospheric carbon dioxide concentration or column concentration exceeds their respective preset ranges, several additional fixed points are added in each region where the atmospheric carbon dioxide concentration or column concentration exceeds their respective preset ranges. A carbon dioxide emission detector is arranged at each additional fixed point to obtain the atmospheric carbon dioxide concentration data at the additional fixed point, and the electric drone device is navigated to above each preset fixed point and above each additional fixed point to obtain the atmospheric carbon dioxide concentration and total emission data above each preset fixed point and above each additional fixed point.

[0036] In Step 5, a carbon dioxide emission detector, a Pitot tube flowmeter, and a single-chip microcomputer device are carried on the electric drone device. The carbon dioxide emission detector, the Pitot tube flowmeter, and the single-chip microcomputer device are all electrically connected. The electric drone device is navigated to above each preset fixed point and above each additional fixed point, and monitoring is carried out at several preset carbon measurement points continuously in the vertical three-dimensional space above each preset fixed point and above each additional fixed point. The carbon dioxide emission detector obtains the atmospheric carbon dioxide concentration data at each preset carbon measurement point, the Pitot tube flowmeter obtains the total gas emission data at each preset carbon measurement point, and they are jointly transmitted to the single-chip microcomputer device. The single-chip microcomputer device calculates and obtains the total carbon dioxide emission data using the differential pressure sensing method based on the atmospheric carbon dioxide concentration data and the gas total emission data. The electric drone device carrying the carbon dioxide emission detector and the Pitot tube flowmeter can obtain more detailed and accurate atmospheric carbon dioxide data in the three-dimensional space above the fixed point, and by establishing a three-dimensional GIS space, combining the flight track of the drone and the carbon dioxide emission data, the distribution change of the carbon emission data of the environmental three-dimensional monitoring can be plotted and displayed on the three-dimensional GIS platform.

[0037] The carbon dioxide emission detector is integrated with a satellite GPS positioning device and a wireless communication device. Both the carbon dioxide emission detector and the satellite GPS positioning device are electrically connected to the wireless communication device, and the wireless communication device on the electric unmanned aerial vehicle device is also electrically connected to the single-chip microcomputer device. The satellite GPS positioning device is used to obtain positioning data through positioning, including position coordinates and altitude data, and transmit the positioning data to the wireless communication device. The single-chip microcomputer device transmits the atmospheric carbon dioxide concentration and total emission data to the wireless communication device, and the wireless communication device transmits the time data, positioning data, atmospheric carbon dioxide concentration data, and total emission data to the carbon emission monitoring system software platform in real time. The carbon dioxide emission detector is an NDIR carbon dioxide sensor.

[0038] Step 6: Input all the data obtained in Step 5 into the carbon emission monitoring system software platform, and use the data assimilation method to perform structured processing and unstructured processing on each data obtained in Step 5 to obtain their respective structured data and unstructured data. The carbon emission monitoring system software platform visualizes each data obtained in Step 5 and their respective structured data and unstructured data, which is convenient for the carbon emission monitoring system software platform to monitor the concentration of atmospheric carbon dioxide and the total emission of atmospheric carbon dioxide at continuous preset carbon measurement points in the vertical three-dimensional space above each preset fixed point and each additional fixed point, so as to realize the monitoring of the distribution and change trend of atmospheric carbon dioxide in the three-dimensional environment, such as Figure 2 and Figure 3 shown, which is a 4D three-dimensional space distribution map presented jointly by the two-dimensional distribution map of the carbon dioxide concentration in a certain area collected during the specific implementation of the present invention and its structured data and unstructured data.

[0039] Based on the carbon dioxide data obtained by the existing carbon satellite technology, ground-based carbon dioxide observation technology, and distributed carbon dioxide emission detection technology, the carbon dioxide emission data at the specified points in the airspace of the unmanned aerial vehicle, as a data supplement with higher accuracy and stronger timeliness, together form a massive comprehensive carbon emission monitoring database; the carbon dioxide data in the spatial three-dimensional environment collected are formed into a three-dimensional distribution and change trend according to regions, airspaces, and time domains, providing accurate data and a scientific basis for the carbon emission system.

[0040] The above detailed description is considered illustrative rather than restrictive, and it should be understood that the above embodiments should be understood as only used to illustrate the present invention and not used to limit the protection scope of the present invention. After reading the content recorded in the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent changes and modifications also fall within the scope defined by the claims of the present invention.

Claims

1. A multi-channel comprehensive monitoring method for carbon emissions, characterized in that: Including the following steps: Step 1: Using a carbon satellite equipped with a carbon dioxide data collector to obtain global-scale atmospheric carbon dioxide concentration and distribution data within a preset time range; Step 2: Using ground-based carbon dioxide observation stations distributed globally to obtain real-time global-scale continuous atmospheric carbon dioxide column concentration data within a preset time range; Step 3: Using carbon dioxide emission detectors at several preset fixed points on a global scale to obtain atmospheric carbon dioxide concentration data at each preset fixed point within a preset time range; Step 4: Inputting all the data obtained in Steps 1 - 3 into an external carbon emission monitoring system software platform, and using data assimilation methods to perform structured and unstructured processing on each data to obtain their respective structured and unstructured data. The carbon emission monitoring system software platform visualizes all the above data, and the carbon emission monitoring system software platform monitors the global-scale atmospheric carbon dioxide concentration and distribution, atmospheric carbon dioxide column concentration, and atmospheric carbon dioxide concentration at each preset fixed point; Step 5: The carbon emission monitoring system software platform determines whether the global-scale atmospheric carbon dioxide concentration, gas column concentration, and atmospheric carbon dioxide concentration at each preset fixed point are within their respective preset ranges based on all the data obtained in Steps 1 - 3. If they are all within their respective preset ranges, then use an electric drone device to fly above each preset fixed point to obtain the total carbon dioxide emissions data above each preset fixed point; If there are several regions within the global scale where the atmospheric carbon dioxide concentration or gas column concentration exceeds their respective preset ranges, then add several additional fixed points in each region where the atmospheric carbon dioxide concentration or gas column concentration exceeds their respective preset ranges. Arrange a carbon dioxide emission detector at each additional fixed point to obtain the atmospheric carbon dioxide concentration data at the additional fixed point, and use an electric drone device to fly above each preset fixed point and each additional fixed point to obtain the atmospheric carbon dioxide concentration and total emissions data above each preset fixed point and each additional fixed point; Step 6: Inputting all the data obtained in Step 5 into the carbon emission monitoring system software platform, using data assimilation methods to perform structured and unstructured processing on each data obtained in Step 5 to obtain their respective structured and unstructured data. The carbon emission monitoring system software platform visualizes each data obtained in Step 5 and their respective structured and unstructured data. The carbon emission monitoring system software platform monitors the atmospheric carbon dioxide concentration and total carbon dioxide emissions at continuous preset carbon measurement points in the vertical three-dimensional space above each preset fixed point and each additional fixed point to achieve monitoring of the distribution and change trend of atmospheric carbon dioxide in a three-dimensional environment; In the aforesaid step 5, a carbon dioxide emission detector, a Pitot tube flowmeter and a single-chip microcomputer device are carried on the electric unmanned aerial vehicle device. The carbon dioxide emission detector, the Pitot tube flowmeter and the single-chip microcomputer device are all electrically connected. The electric unmanned aerial vehicle device sails above each preset fixed point and each additional fixed point, and monitors at a number of preset carbon measurement points continuously in the vertical three-dimensional space above each preset fixed point and each additional fixed point. The carbon dioxide emission detector acquires the concentration data of atmospheric carbon dioxide at each preset carbon measurement point, and the Pitot tube flowmeter acquires the total gas emission data at each preset carbon measurement point, and they are jointly transmitted to the single-chip microcomputer device. The single-chip microcomputer device calculates and obtains the total emission data of atmospheric carbon dioxide by using the differential pressure sensing method through the concentration data of atmospheric carbon dioxide and the total gas emission data; By establishing a three-dimensional GIS space, combining the flight track of the unmanned aerial vehicle and the carbon dioxide emission data, the distribution change of the carbon emission data of the environmental three-dimensional monitoring is plotted and displayed on the three-dimensional GIS platform.

2. The multi-channel comprehensive carbon emission monitoring method according to claim 1, characterized in that: In the aforesaid step 1, the carbon dioxide data collector carried by the carbon satellite is a greenhouse gas detector GMI or a hyperspectral greenhouse gas detector.

3. A multi-channel comprehensive monitoring method for carbon emissions according to claim 1, characterized in that: In the aforesaid step 4, the atmospheric carbon dioxide emission data at each preset fixed point are all processed to obtain its own structured data and unstructured data.

4. A multi-channel comprehensive monitoring method for carbon emissions according to claim 1, characterized in that: The carbon dioxide emission detector is integrated with a satellite GPS positioning device and a wireless communication device. The carbon dioxide emission detector and the satellite GPS positioning device are both electrically connected to the wireless communication device. The wireless communication device on the electric unmanned aerial vehicle device is also electrically connected to the single-chip microcomputer device; the satellite GPS positioning device is used to locate and acquire positioning data, including position coordinates and altitude data, and transmit the positioning data to the wireless communication device. The single-chip microcomputer device transmits the atmospheric carbon dioxide concentration and total emission data to the wireless communication device, and the wireless communication device transmits the time data, positioning data, atmospheric carbon dioxide concentration data and total emission data to the carbon emission monitoring system software platform in real time.

5. A multi-channel comprehensive carbon emission monitoring method according to claim 1, characterized in that: The carbon dioxide emission detector is an NDIR carbon dioxide sensor.

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