Carbon emission data acquisition method, device, system, equipment and medium
By acquiring and analyzing the data to be analyzed for carbon emission sources, calculating coefficients, analyzing and evaluating carbon emissions, and using mixed models for data analysis, the problems of cumbersome carbon emission data collection methods and poor monitoring effects in the existing technology are solved, and more accurate and real-time monitoring of carbon emission data is achieved.
Patent Information
- Application Number
- CN202510269755.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-07
- Publication Date
- 2025-06-06
AI Technical Summary
The existing carbon emission data collection methods are cumbersome and are susceptible to human factors. It is difficult to monitor the trend of carbon emissions in real time, and the monitoring effect is relatively average.
By obtaining the data to be analyzed for the target carbon emission source, including activity data and production process data, calculating coefficient carbon emissions, analyzing carbon emissions and evaluating carbon emissions, data analysis is performed using a hybrid model, and finally calculating the target carbon emissions to obtain the target collected data.
It improves the accuracy and real-timeness of carbon emission data monitoring, can evaluate carbon emissions from different angles, effectively improve monitoring effect, and is suitable for analysis on different time scales.
Smart Images
Figure CN120106392A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of carbon emission data processing, and in particular to a carbon emission data collection method, device, system, equipment and medium. Background Art
[0002] At present, the carbon emission data collection method mainly relies on manual sampling, and carries out steps such as sample preparation, sample storage and analysis. The entire collection and analysis process is relatively cumbersome and easily affected by human factors. In addition, this collection method analyzes the entire carbon emission process as a whole. Therefore, this method can usually only obtain the average carbon emissions over a longer period of time. It is difficult to monitor the changing trend of carbon emissions in real time, and the monitoring effect is relatively general. Summary of the invention
[0003] The present invention application provides a carbon emission data collection method, device, system, equipment and medium to solve the technical problem of how to improve the monitoring effect.
[0004] In order to solve the above technical problems, the present invention provides a carbon emission data collection method, comprising:
[0005] Acquire data to be analyzed of a target carbon emission source, wherein the data to be analyzed includes activity data and production process data;
[0006] Calculate the coefficient carbon emissions according to the carbon emission coefficient corresponding to the activity data; analyze the production process of the target carbon emission source and calculate the carbon emissions; when the target carbon emission source is an installation type emission source, use the life cycle assessment method to obtain the assessed carbon emissions;
[0007] The target carbon emissions are calculated according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions.
[0008] As a preferred solution, the target carbon emissions are calculated according to the coefficient carbon emissions, the analyzed carbon emissions and the assessed carbon emissions, specifically:
[0009] The target carbon emissions are calculated according to the following formula:
[0010] E = (E1 + E2 + E3) / 3;
[0011] Among them, E is the target carbon emissions, E1 is the coefficient carbon emissions, E2 is the analyzed carbon emissions, and E3 is the assessed carbon emissions.
[0012] As a preferred solution, the step of obtaining the target collection data of the target carbon emission source according to the target carbon emission includes:
[0013] Obtaining sample data, and dividing the sample data into a training set, a validation set, and a test set;
[0014] The preset hybrid model is trained using the training set, and during the training process, the model parameters of the preset hybrid model are adjusted using the validation set, and the performance of the preset hybrid model is evaluated using the test set;
[0015] When the performance of the preset hybrid model meets the preset conditions, a target model is obtained;
[0016] The target carbon emission is input into the target model, and target collection data is obtained based on the output of the target model.
[0017] As a preferred solution, the preset hybrid model includes at least two of a linear regression model, a decision tree, a support vector machine and a neural network.
[0018] As a preferred solution, after obtaining the target collection data of the target carbon emission source according to the target carbon emission amount, the carbon emission data collection method further includes:
[0019] The carbon dioxide concentration data of the target carbon emission source is read from at least one of a preset ground carbon dioxide monitoring network, a remote sensing sensor, a hyperspectral remote sensor, a laser absorption spectrometer and an unmanned aerial vehicle sensor; and the carbon dioxide data of multiple target carbon emission sources are combined for analysis to obtain carbon dioxide concentration distribution information.
[0020] As a preferred solution, the carbon emission data collection method further includes:
[0021] The carbon dioxide concentration distribution information is analyzed by using numerical simulation and inversion technology to construct a three-dimensional distribution model of carbon dioxide data concentration.
[0022] Correspondingly, the present invention application also provides a carbon emission data collection device, including a collection device body, a data processing module, a data collection module, a power supply module and a mounting bracket, wherein the data collection module is used to execute the carbon emission data collection method.
[0023] Accordingly, the present invention application also provides a carbon emission data collection system, including an acquisition module, an analysis module and a collection module;
[0024] The acquisition module is used to acquire the data to be analyzed of the target carbon emission source, wherein the data to be analyzed includes activity data and production process data;
[0025] The analysis module is used to calculate the coefficient carbon emission according to the carbon emission coefficient corresponding to the activity data; analyze the production process of the target carbon emission source and calculate the carbon emission; when the target carbon emission source is an equipment type emission source, the life cycle assessment method is used to obtain the assessed carbon emission;
[0026] The collection module is used to calculate the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions.
[0027] As a preferred solution, the acquisition module calculates the target carbon emissions according to the coefficient carbon emissions, the analysis carbon emissions and the evaluation carbon emissions, specifically:
[0028] The acquisition module calculates the target carbon emissions according to the following formula:
[0029] E = (E1 + E2 + E3) / 3;
[0030] Among them, E is the target carbon emissions, E1 is the coefficient carbon emissions, E2 is the analyzed carbon emissions, and E3 is the assessed carbon emissions.
[0031] As a preferred solution, the acquisition module obtains the target acquisition data of the target carbon emission source according to the target carbon emission amount, including:
[0032] The acquisition module acquires sample data and divides the sample data into a training set, a validation set and a test set;
[0033] The preset hybrid model is trained using the training set, and during the training process, the model parameters of the preset hybrid model are adjusted using the validation set, and the performance of the preset hybrid model is evaluated using the test set;
[0034] When the performance of the preset hybrid model meets the preset conditions, a target model is obtained;
[0035] The target carbon emission is input into the target model, and target collection data is obtained based on the output of the target model.
[0036] As a preferred solution, the preset hybrid model includes at least two of a linear regression model, a decision tree, a support vector machine and a neural network.
[0037] As a preferred solution, the carbon emission data collection system further includes a concentration analysis module. After the collection module obtains the target collection data of the target carbon emission source according to the target carbon emission amount, the concentration analysis module is used to:
[0038] The carbon dioxide concentration data of the target carbon emission source is read from at least one of a preset ground carbon dioxide monitoring network, a remote sensing sensor, a hyperspectral remote sensor, a laser absorption spectrometer and an unmanned aerial vehicle sensor; and the carbon dioxide data of multiple target carbon emission sources are combined for analysis to obtain carbon dioxide concentration distribution information.
[0039] As a preferred solution, the carbon emission data collection system further includes a construction module, and the construction module is used to:
[0040] The carbon dioxide concentration distribution information is analyzed by using numerical simulation and inversion technology to construct a three-dimensional distribution model of carbon dioxide data concentration.
[0041] Correspondingly, the present application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the carbon emission data collection method when executing the computer program.
[0042] Correspondingly, the present application also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the carbon emission data collection method.
[0043] Compared with the prior art, the present invention has the following beneficial effects:
[0044] The present invention application provides a carbon emission data collection method, device, system, equipment and medium, the carbon emission data collection method comprising: obtaining data to be analyzed of a target carbon emission source, the data to be analyzed comprising activity data and production process data; calculating coefficient carbon emissions according to a carbon emission coefficient corresponding to the activity data; analyzing the production process of the target carbon emission source, and calculating and analyzing carbon emissions; when the target carbon emission source is a device-type emission source, obtaining assessed carbon emissions using a life cycle assessment method; calculating the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the assessed carbon emissions, thereby obtaining the target collection data of the target carbon emission source according to the target carbon emissions. The present invention application analyzes activity data, production process and adopts life cycle assessment method when the target carbon emission source is an equipment-type emission source, and obtains coefficient carbon emissions, analysis carbon emissions and evaluation carbon emissions respectively, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions. Compared with the prior art that analyzes the entire carbon emission process as a whole, it can accurately evaluate the emissions of the target carbon emission source from the perspectives of the activity status, production process and evaluation results of the target carbon emission source, and effectively improve the monitoring effect. In addition, the carbon emission data collection method of the present application is suitable for analysis of longer and shorter time periods, can realize monitoring of different time scales, and can provide a certain reference for monitoring changes in carbon emission data. BRIEF DESCRIPTION OF THE DRAWINGS
[0045] Figure 1 : A flow chart of an embodiment of the carbon emission data collection method provided in the present application.
[0046] Figure 2 : A structural schematic diagram of an embodiment of a carbon emission data collection device provided in the present application.
[0047] Figure 3 : A structural schematic diagram of an embodiment of a carbon emission data collection system provided in the present application. DETAILED DESCRIPTION
[0048] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0049] Embodiment 1
[0050] Please refer to Figure 1 , Figure 1A carbon emission data collection method provided for the present invention includes steps S101 to S103; wherein each step is described in detail as follows:
[0051] Step S101, obtaining data to be analyzed of a target carbon emission source.
[0052] In this embodiment, the carbon emission data collection method can be applied to a carbon emission data collection device (eg Figure 2 In the embodiment shown), the carbon emission data collection device can be a computer device, which includes but is not limited to a smart phone, a laptop, a tablet computer, a desktop computer, and a physical server and a cloud server connected to a display unit. The display unit ( Figure 2 Not shown) can be used to display carbon emissions, such as the distribution and time trend of carbon emissions.
[0053] The target carbon emission sources are mainly various types of carbon emission equipment. For example, while power generation equipment provides electricity, it will release a large amount of carbon dioxide as it burns coal, natural gas, etc.; or, in some heavy industries, such as steel, cement and chemical production processes, the production process or equipment requires the use of a large amount of fossil fuels, and the use of these fuels will emit a large amount of carbon dioxide; or, in the transportation process, vehicles such as cars, airplanes and ships often burn gasoline and diesel and produce exhaust emissions (including carbon dioxide) during driving, and the transportation sector is also a major contributor to carbon emissions.
[0054] For different types of carbon emission sources, the specific scope of data collection can be defined based on factors such as their geographical location, industry classification and time span, thereby determining the parameters of data collection, such as collection frequency and sampling point setting.
[0055] The present application obtains the above-mentioned data to be analyzed by reading the equipment data of the carbon emission source, namely the carbon emission equipment, and the data to be analyzed includes the activity data and production process data of the equipment.
[0056] In this embodiment, the activity data includes energy consumption, raw material consumption, etc., and the production process data includes data on the conversion of electricity, heat, water, and other energy sources during the production process, specifically including multiple production links or processes. The activity data and production process data can be obtained by reading the historical data of the device, and after obtaining, the abnormal data can be processed and corrected.
[0057] Step S102, calculate the coefficient carbon emissions according to the carbon emission coefficient corresponding to the activity data; analyze the production process of the target carbon emission source and calculate and analyze the carbon emissions; when the target carbon emission source is an equipment-type emission source, use the life cycle assessment method to obtain the assessed carbon emissions.
[0058] In this step, the corresponding carbon emission coefficient (or carbon emission factor) and carbon emission calculation formula are determined according to the energy type, energy consumption, and activity type involved in the activity data, and the coefficient carbon emission E1 is calculated using the carbon emission coefficient and carbon emission calculation formula.
[0059] On the other hand, the production process can be analyzed in detail, the analytical carbon emissions of this indicator can be calculated and expressed as E2.
[0060] Furthermore, when the target carbon emission source is an equipment-type emission source, the life cycle assessment method is used to evaluate the carbon emissions of the equipment-type carbon emission source throughout its life cycle to obtain the assessed carbon emissions. Exemplarily, the overall process flow range of the equipment-type carbon emission source (such as the range of one or more combinations of pre-plant processing flow, transportation flow, waste treatment flow, in-plant physical treatment flow, in-plant chemical treatment flow, product shaping flow, and distribution and use flow) can be determined, and combined with the evaluation requirements corresponding to the carbon emission accounting, the corresponding carbon emission accounting boundary is generated, thereby realizing the assessment of carbon emissions throughout the life cycle, obtaining the assessed carbon emissions and expressing them in E3.
[0061] Step S103, calculating the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, thereby obtaining the target collection data of the target carbon emission source according to the target carbon emissions.
[0062] In a preferred embodiment, the target carbon emission can be calculated according to the following formula:
[0063] E = (E1 + E2 + E3) / 3;
[0064] Among them, E is the target carbon emissions, E1 is the coefficient carbon emissions, E2 is the analyzed carbon emissions, and E3 is the assessed carbon emissions.
[0065] The calculated target carbon emissions data can then be cleaned, such as removing outliers and filling missing data, as well as correcting it and adjusting the units and standards of the data to ensure consistency and accuracy of the data.
[0066] Furthermore, before or after cleaning and correction, the target carbon emissions can be integrated to form a complete carbon emission data set, so that the data set is used to analyze and obtain the spatial and temporal distribution patterns of carbon emissions.
[0067] In a preferred embodiment, the target carbon emission data can be input into a preset artificial intelligence model (target model), and the target collection data can be obtained based on the output of the target model.
[0068] Exemplarily, the target collection data of the target carbon emission source is obtained according to the target carbon emission, including: obtaining sample data, and dividing the sample data into a training set, a validation set, and a test set; using the training set to train a preset hybrid model, and using the validation set to adjust the model parameters of the preset hybrid model during the training process, and using the test set to evaluate the performance of the preset hybrid model; when the performance of the preset hybrid model meets the preset conditions, obtaining the target model;
[0069] The target carbon emission is input into the target model, and target collection data is obtained based on the output of the target model.
[0070] In this embodiment, the preset hybrid model includes at least two of a linear regression model, a decision tree, a support vector machine, and a neural network. For example, it may be a combination of at least two of linear regression + decision tree, support vector machine + neural network, etc. Through training, the preset hybrid model learns the pattern and relationship of carbon emissions, and evaluates the performance of the model through a test set, such as obtaining its prediction accuracy, accuracy and / or recall and other indicators, so as to adjust the structure and parameters of the model according to the performance evaluation results, and realize iterative optimization of its performance until the model meets the preset convergence conditions (when the performance of the preset hybrid model meets the preset conditions), obtain the target model, and deploy the target model to a server or a specific application system for calling. In this way, this embodiment inputs the target carbon emissions into the target model, and obtains the target collection data based on the output of the target model.
[0071] After obtaining the target collection data of the target carbon emission source according to the target carbon emission amount, the carbon emission data collection method further includes:
[0072] The carbon dioxide concentration data of the target carbon emission source is read from at least one of a preset ground carbon dioxide monitoring network, a remote sensing sensor, a hyperspectral remote sensor, a laser absorption spectrometer and an unmanned aerial vehicle sensor; and the carbon dioxide data of multiple target carbon emission sources are combined for analysis to obtain carbon dioxide concentration distribution information.
[0073] Exemplarily, a ground carbon dioxide monitoring network can be established in advance, and ground monitoring stations can be set up at key points such as different regions, cities, industrial areas, and transportation hubs to obtain carbon dioxide concentration data of target carbon emission sources, and record information such as time, location, temperature, and humidity; obtain carbon dioxide concentration distribution information in the atmosphere through sensors carried by equipment such as aircraft, drones, and satellites (satellite remote sensing can cover larger areas, while aircraft / drones are more flexible and can be used for detailed monitoring of specific areas); obtain atmospheric spectral data through hyperspectral remote sensors, and obtain carbon dioxide concentration distribution information by analyzing the absorption characteristics of carbon dioxide (different concentrations of carbon dioxide will produce different absorption characteristics for the spectrum); perform high-precision measurement of carbon dioxide in the air through a laser absorption spectrometer carried by the ground or drones, directly measure the carbon dioxide concentration in the air, and trace it back to carbon dioxide from different sources; or obtain the above-mentioned carbon dioxide concentration distribution information through a combination of one or more of the above methods, thereby ensuring accurate acquisition of carbon dioxide concentration distribution.
[0074] The carbon dioxide concentration distribution information obtained above is calibrated, filtered, interpolated, etc. to eliminate noise and errors. Then, numerical simulation and inversion techniques are used to analyze the carbon dioxide concentration distribution information to construct a three-dimensional distribution model of carbon dioxide data concentration.
[0075] By implementing the above-mentioned preferred implementation mode, the carbon dioxide data of multiple target carbon emission sources are analyzed to obtain the carbon dioxide concentration distribution information, and a three-dimensional distribution model of the carbon dioxide data concentration is constructed. This model can be combined with meteorological models, carbon cycle models and other data for analysis, thereby providing a reference for carbon emission accounting in other different regions, so as to further improve the accuracy of carbon emission monitoring or collection in the above-mentioned other different regions.
[0076] Correspondingly, such as Figure 2 As shown, the present application also provides a carbon emission data collection device, comprising a collection device body (1), a data processing module (2), a data collection module (3), a power supply module (4) and a mounting bracket (5), wherein the data collection module (3) is used to execute the carbon emission data collection method described in any one of the above-mentioned embodiments.
[0077] In this embodiment, the data processing module (2) is arranged on the top surface of the acquisition device body (1), the data acquisition module (3) is arranged on the outside of the data processing module (2), and there are multiple groups of data acquisition modules (3), the energy supply module (4) is arranged inside the data processing module (2), and the mounting bracket (5) is arranged on the bottom surface of the acquisition device body (1).
[0078] When in use, the data processing module (2) is used to process and calculate the output signal of the data acquisition module (3), and calculate the carbon emissions through a preset algorithm. The data acquisition module (3) is used to collect and detect parameters such as the carbon dioxide concentration, air temperature and humidity in the environment in real time. The energy supply module (4) continuously supplies energy to the carbon emission data acquisition device, thereby ensuring its continuous use.
[0079] Correspondingly, such as Figure 3 As shown, the present invention also provides a carbon emission data collection system 300, including an acquisition module 301, an analysis module 302 and a collection module 303;
[0080] The acquisition module 301 is used to acquire the data to be analyzed of the target carbon emission source, wherein the data to be analyzed includes activity data and production process data;
[0081] The analysis module 302 is used to calculate the coefficient carbon emission according to the carbon emission coefficient corresponding to the activity data; analyze the production process of the target carbon emission source and calculate the carbon emission; when the target carbon emission source is an equipment type emission source, the life cycle assessment method is used to obtain the assessed carbon emission;
[0082] The acquisition module 303 is used to calculate the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, so as to obtain the target acquisition data of the target carbon emission source according to the target carbon emissions.
[0083] As a preferred solution, the acquisition module 303 calculates the target carbon emissions according to the coefficient carbon emissions, the analysis carbon emissions and the evaluation carbon emissions, specifically:
[0084] The acquisition module 303 calculates the target carbon emissions according to the following formula:
[0085] E = (E1 + E2 + E3) / 3;
[0086] Among them, E is the target carbon emissions, E1 is the coefficient carbon emissions, E2 is the analyzed carbon emissions, and E3 is the assessed carbon emissions.
[0087] As a preferred solution, the acquisition module 303 obtains the target acquisition data of the target carbon emission source according to the target carbon emission, including:
[0088] The acquisition module 303 acquires sample data and divides the sample data into a training set, a validation set and a test set;
[0089] The preset hybrid model is trained using the training set, and during the training process, the model parameters of the preset hybrid model are adjusted using the validation set, and the performance of the preset hybrid model is evaluated using the test set;
[0090] When the performance of the preset hybrid model meets the preset conditions, a target model is obtained;
[0091] The target carbon emission is input into the target model, and target collection data is obtained based on the output of the target model.
[0092] As a preferred solution, the preset hybrid model includes at least two of a linear regression model, a decision tree, a support vector machine and a neural network.
[0093] As a preferred solution, the carbon emission data collection system 300 further includes a concentration analysis module 302. After the collection module 303 obtains the target collection data of the target carbon emission source according to the target carbon emission, the concentration analysis module 302 is used to:
[0094] The carbon dioxide concentration data of the target carbon emission source is read from at least one of a preset ground carbon dioxide monitoring network, a remote sensing sensor, a hyperspectral remote sensor, a laser absorption spectrometer and an unmanned aerial vehicle sensor; and the carbon dioxide data of multiple target carbon emission sources are combined for analysis to obtain carbon dioxide concentration distribution information.
[0095] As a preferred solution, the carbon emission data collection system 300 further includes a construction module, and the construction module is used to:
[0096] The carbon dioxide concentration distribution information is analyzed by using numerical simulation and inversion technology to construct a three-dimensional distribution model of carbon dioxide data concentration.
[0097] Correspondingly, the present application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the carbon emission data collection method when executing the computer program.
[0098] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the terminal, and various interfaces and lines are used to connect various parts of the entire terminal.
[0099] The memory can be used to store the computer program, and the processor realizes various functions of the terminal by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (SmartMedia Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.
[0100] Correspondingly, the present application also provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the carbon emission data collection method.
[0101] Wherein, if the module of the carbon emission data collection device / terminal / system integration is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.
[0102] Compared with the prior art, the present invention has the following beneficial effects:
[0103] The present invention application provides a carbon emission data collection method, device, system, equipment and medium, the carbon emission data collection method comprising: obtaining data to be analyzed of a target carbon emission source, the data to be analyzed comprising activity data and production process data; calculating coefficient carbon emissions according to a carbon emission coefficient corresponding to the activity data; analyzing the production process of the target carbon emission source, and calculating and analyzing carbon emissions; when the target carbon emission source is a device-type emission source, obtaining assessed carbon emissions using a life cycle assessment method; calculating the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the assessed carbon emissions, thereby obtaining the target collection data of the target carbon emission source according to the target carbon emissions. The present invention application analyzes activity data, production process and adopts life cycle assessment method when the target carbon emission source is an equipment-type emission source, and obtains coefficient carbon emissions, analysis carbon emissions and evaluation carbon emissions respectively, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions. Compared with the prior art that analyzes the entire carbon emission process as a whole, it can accurately evaluate the emissions of the target carbon emission source from the perspectives of the activity status, production process and evaluation results of the target carbon emission source, and effectively improve the monitoring effect. In addition, the carbon emission data collection method of the present application is suitable for analysis of longer and shorter time periods, can realize monitoring of different time scales, and can provide a certain reference for monitoring changes in carbon emission data.
[0104] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.
Claims
1. A method for collecting carbon emission data, characterized in that: include: Acquire data to be analyzed of a target carbon emission source, wherein the data to be analyzed includes activity data and production process data; Calculate the coefficient carbon emission amount according to the carbon emission coefficient corresponding to the activity data; Analyze the production process of the target carbon emission source and calculate and analyze the carbon emissions; when the target carbon emission source is an equipment-type emission source, use the life cycle assessment method to obtain the assessed carbon emissions; The target carbon emissions are calculated according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions.
2. A carbon emission data collection method as claimed in claim 1, characterized in that: The target carbon emissions are calculated according to the coefficient carbon emissions, the analyzed carbon emissions and the assessed carbon emissions, specifically: The target carbon emissions are calculated according to the following formula: E = (E1 + E2 + E3) / 3; Among them, E is the target carbon emissions, E1 is the coefficient carbon emissions, E2 is the analyzed carbon emissions, and E3 is the assessed carbon emissions.
3. A carbon emission data collection method as claimed in claim 1, characterized in that: The step of obtaining the target collection data of the target carbon emission source according to the target carbon emission includes: Obtaining sample data, and dividing the sample data into a training set, a validation set, and a test set; The preset hybrid model is trained using the training set, and during the training process, the model parameters of the preset hybrid model are adjusted using the validation set, and the performance of the preset hybrid model is evaluated using the test set; When the performance of the preset hybrid model meets the preset conditions, a target model is obtained; The target carbon emission is input into the target model, and target collection data is obtained based on the output of the target model.
4. A carbon emission data collection method as claimed in claim 1, characterized in that: The preset hybrid model includes at least two of a linear regression model, a decision tree, a support vector machine and a neural network.
5. A carbon emission data collection method as claimed in claim 1, characterized in that: After obtaining the target collection data of the target carbon emission source according to the target carbon emission amount, the carbon emission data collection method further includes: The carbon dioxide concentration data of the target carbon emission source is read from at least one of a preset ground carbon dioxide monitoring network, a remote sensing sensor, a hyperspectral remote sensor, a laser absorption spectrometer and an unmanned aerial vehicle sensor; and the carbon dioxide data of multiple target carbon emission sources are combined for analysis to obtain carbon dioxide concentration distribution information.
6. A carbon emission data collection method as claimed in claim 5, characterized in that: The carbon emission data collection method further includes: The carbon dioxide concentration distribution information is analyzed by using numerical simulation and inversion technology to construct a three-dimensional distribution model of carbon dioxide data concentration.
7. A carbon emission data collection device, characterized in that: It includes a collection device body, a data processing module, a data collection module, a power supply module and a mounting bracket, and the data collection module is used to execute a carbon emission data collection method as described in any one of claims 1 to 6.
8. A carbon emission data collection system, characterized in that: It includes an acquisition module, an analysis module and a collection module; The acquisition module is used to acquire the data to be analyzed of the target carbon emission source, wherein the data to be analyzed includes activity data and production process data; The analysis module is used to calculate the coefficient carbon emission amount according to the carbon emission coefficient corresponding to the activity data; Analyze the production process of the target carbon emission source and calculate and analyze the carbon emissions; when the target carbon emission source is an equipment-type emission source, use the life cycle assessment method to obtain the assessed carbon emissions; The collection module is used to calculate the target carbon emissions according to the coefficient carbon emissions, the analyzed carbon emissions and the evaluated carbon emissions, so as to obtain the target collection data of the target carbon emission source according to the target carbon emissions.
9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the carbon emission data collection method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the carbon emission data collection method according to any one of claims 1 to 7.