A method and system for early warning of carbon emission data quality based on big data

Abstract

This invention discloses a carbon emission data quality early warning method and system based on big data. The early warning method includes the following steps: collecting and preprocessing carbon emission data from enterprises and actual emissions; calculating the theoretical total carbon emissions of a single enterprise based on the enterprise carbon emission data; calculating the theoretical specific content of carbon emission types at each stage based on the theoretical total carbon emissions of a single enterprise, and issuing an early warning if the specific content of a certain type exceeds the industry standard; detecting the actual carbon emission type content and total carbon emissions of a single enterprise at each stage, comparing them with the industry standard, and issuing an early warning if they exceed the standard; calculating the difference between the actual monitored carbon emissions in the control area and the area's carbon emission standard, and the difference between the carbon emission type content and the type standard, and issuing an early warning if they exceed the standard; providing an early warning record for the area based on the early warning information; calculating a carbon emission reduction potential index to assess the degree of carbon emission reduction after the early warning enterprise takes measures. This invention provides early warning information from multiple aspects of carbon emissions, making carbon emission early warning more accurate.

Description

Technical Field

[0001] This invention relates to the field of data processing, and in particular to a method and system for early warning of carbon emission data quality based on big data. Background Technology

[0002] As the global climate change problem becomes increasingly severe, global temperatures continue to rise, and extreme weather events occur more frequently, in order to avoid more serious consequences from climate change, it is necessary to significantly reduce greenhouse gas emissions and achieve carbon neutrality, which has become a key strategy for addressing climate change.

[0003] To address this, the present invention proposes a carbon emission data quality early warning method based on big data. This method can ensure the authenticity and reliability of carbon emission data, thereby providing solid data support for global emission reduction efforts. It can also help regulatory authorities detect data anomalies in a timely manner and prevent companies from falsely reporting or concealing carbon emission data. Summary of the Invention

[0004] This invention provides a carbon emission data quality early warning method based on big data, comprising: S10. Collect carbon emission data from both enterprise and actual monitoring perspectives, and perform data preprocessing; S20. Calculate the theoretical total carbon emissions of a single enterprise based on the enterprise's carbon emission data; S30. Calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise. If the specific content of a certain type exceeds the industry standard, an early warning will be issued. S40. Detect the actual carbon emission types and total carbon emissions of each stage of a single enterprise, and compare them with industry standards. If the standards are exceeded, an early warning will be issued. S50. Calculate the difference between the actual monitored carbon emissions in the control area and the carbon emission standard of the area, and calculate the difference between the content of carbon emission types in the control area and the standard for each type. If the standard is exceeded, an early warning will be issued. S60. Provide area warning records based on warning information; S70. Calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises that have taken certain emission reduction measures.

[0005] The carbon emission data quality early warning method based on big data, as described above, requires the collection of carbon emission data from both enterprise and actual monitoring perspectives. Enterprise data includes enterprise production data, energy consumption data, waste management data, types of carbon emissions, and other data that can generate carbon emissions. Actual monitoring data includes the types and contents of carbon emission gases in the controlled area and the total amount of carbon emissions in the area.

[0006] As described above, a big data-based carbon emission data quality early warning method requires calculating the carbon emissions from coal combustion separately for each individual enterprise. Coal combustion is the main cause of carbon emissions. Ideally, coal combustion produces carbon dioxide, but in actual combustion, coal often undergoes incomplete combustion, producing carbon dioxide and other greenhouse gases. Calculating the carbon emissions from coal combustion separately makes the calculation results more accurate.

[0007] The carbon emission data quality early warning method based on big data, as described above, includes the carbon emissions of a single enterprise, the carbon emissions generated by energy, the carbon emissions generated by factors such as chemical reactions and physical changes caused by production processes, the carbon emissions generated by chemical reactions of raw materials during production, and the carbon emissions generated during waste treatment.

[0008] The carbon emission data quality early warning method based on big data, as described above, requires the use of a gas analyzer to detect the actual carbon emission types and total carbon emissions of each stage of a single enterprise. Depending on the carbon emission gas being detected, two types are used: infrared absorption gas analyzer and gas chromatography-mass spectrometry.

[0009] As described above, the carbon emission data quality early warning method based on big data is affected by uncertainties in the content detected by the infrared absorption gas analyzer, including uncertainties in the accuracy of the measuring equipment, uncertainties in the limitations of the measuring method, uncertainties in environmental conditions, and uncertainties in the inhomogeneity of the sample.

[0010] As described above, in a big data-based carbon emission data quality early warning method, the content detected by gas chromatography-mass spectrometry is affected by uncertainties, including the uncertainty of the concentration of standard substances, the uncertainty of instrument response, the uncertainty of environmental conditions, and the uncertainty of the sample injection process.

[0011] This invention also provides a carbon emission data quality early warning system based on big data, comprising: Data Acquisition Module: Used to collect carbon emission data from both enterprise and actual monitoring sources, and to perform data preprocessing; Enterprise Calculation Module: Used to calculate the theoretical total carbon emissions of a single enterprise based on its carbon emission data; Enterprise Theoretical Carbon Emission Type Content Assessment Module: This module is used to calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise. If the specific content of a certain type exceeds the industry standard, an early warning will be issued. Enterprise Actual Carbon Emission Assessment Module: This module is used to detect the actual carbon emission types and total carbon emissions of a single enterprise at each stage, and compare them with industry standards. If the standards are exceeded, an early warning will be issued. Control Area Assessment Module: Used to calculate the difference between the actual monitored carbon emissions in the control area and the carbon emission standard of the area, and to calculate the difference between the content of different types of carbon emissions in the control area and the standard for each type. If the standard is exceeded, an early warning will be issued. Early warning recording module: used to generate early warning records for a given area based on early warning information; Carbon emission reduction calculation module: used to calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises after taking certain emission reduction measures.

[0012] The beneficial effects achieved by this invention are as follows: This invention provides early warning information from multiple aspects of carbon emissions, making carbon emission early warning more accurate. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0014] Figure 1 This is a flowchart of a carbon emission data quality early warning method based on big data, provided in Embodiment 1 of this application.

[0015] Figure 2 This is a schematic diagram of a carbon emission data quality early warning system based on big data, provided in Embodiment 2 of this application. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Example 1

[0018] like Figure 1 As shown, Embodiment 1 of this application provides a carbon emission data quality early warning method based on big data, including: S10. Collect carbon emission data from both enterprise and actual monitoring perspectives, and perform data preprocessing.

[0019] Raw carbon emission data of enterprises within the control area were collected from enterprise reports and on-site visits. The raw carbon emission data of enterprises includes enterprise production data, energy consumption data, waste management data, types of carbon emissions, and other data that can generate carbon emissions.

[0020] Carbon emission data for the controlled area is collected through environmental monitoring stations and data acquisition terminals. This includes the types and amounts of carbon emission gases, as well as the total carbon emissions within the area. The types of carbon emission gases include carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorinated carbon, sulfur hexafluoride, and nitrogen trifluoride.

[0021] The collected data should be initially sorted and classified. Classification can be based on factors such as the source of the data, including enterprise type, energy type, time attribute of the data, annual, quarterly, and monthly data, specific carbon emission links reflected by the data, combustion emissions in the production process, and process emissions.

[0022] The collected data undergoes data cleaning to remove outliers and missing values. Missing data is filled using interpolation, while outliers are identified and processed using box plots. Based on industry experience, a normal fluctuation range for energy consumption of a certain type of enterprise is established. By setting reasonable data range thresholds, data exceeding this range is marked as suspicious and further verified or directly removed.

[0023] Data formatting was performed to standardize the time format and units, ensuring all data could be correctly parsed and compared. All carbon emission data was converted to tons per year and stored according to the year, month, and day time format. Through data cleaning and formatting, the accuracy and consistency of the data were ensured, providing a high-quality data foundation for subsequent calculations.

[0024] S20. Calculate the theoretical total carbon emissions of a single enterprise based on the enterprise's carbon emission data.

[0025] Coal combustion is a major cause of carbon emissions. Ideally, complete coal combustion produces carbon dioxide, but in actual combustion processes, incomplete combustion produces carbon dioxide and other greenhouse gases. The carbon emissions from coal combustion over a period of time *t* are... ,in This represents the amount of carbon dioxide emissions that could theoretically be produced by the complete combustion of carbon in coal within time t. The percentage of carbon content in the coal used can be found in coal quality testing reports or relevant coal resource data. This represents the amount of coal consumed over a period of time t. Based on the fixed stoichiometric relationship between carbon and carbon dioxide, the complete combustion of 12 parts by mass of carbon produces 44 parts by mass of carbon dioxide. The theoretical carbon dioxide emissions are then converted into the actual carbon dioxide emissions produced during combustion. This represents the amount of carbon dioxide emitted during the actual combustion process within time t. This indicates the efficiency of coal combustion. Indicates the methane emission factor. This represents the methane content produced during the actual combustion of coal within time t. Indicates the nitrous oxide emission factor. This represents the nitrous oxide content produced during the actual combustion of coal within time t. Incomplete combustion of coal produces other gases; this calculation only considers the carbon emissions from coal combustion.

[0026] Based on the company's production data, energy consumption data, and waste management data, calculate the total carbon emissions generated at each stage of the company's operations. ,in, This represents the carbon emissions generated by using coal energy within time t; if coal energy is not used, then... It is 0. This represents the carbon emissions generated by energy sources other than coal used by the company within time t, where n represents the number of energy sources used by the company. This represents the amount of the i-th type of energy consumed by the enterprise within time t. Let represent the carbon emission coefficient corresponding to the i-th energy source. This represents the carbon emissions generated within time t due to chemical reactions, physical changes, and other factors caused by the production process, where m represents the number of stages in the enterprise's production process. This represents the amount of relevant activity in the j-th stage of the enterprise's production process within time t. This represents the carbon emission factor corresponding to the j-th stage. This represents the carbon emissions generated by chemical reactions of raw materials during the production process within time t, where p is the number of types of raw materials used by the company. This indicates the amount of the z-th raw material used by the company. This represents the carbon emission factor corresponding to the z-th raw material. q represents the carbon emissions generated during the waste disposal process of the enterprise within time t, where q is the number of types of waste generated by the enterprise. This represents the amount of type l waste generated by the enterprise within time t. This represents the carbon emission coefficient of the l-th type of waste.

[0027] Based on the above calculation formula, calculate the carbon emissions of each enterprise within the controlled area.

[0028] S30. Calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise. If the specific content of a certain type exceeds the industry standard, an early warning will be issued.

[0029] For the calculated carbon emissions at each stage, let the carbon emissions from energy generation be E, the carbon emissions from production processes be A, the carbon emissions from raw materials during production be R, and the carbon emissions from waste treatment be W. Further analysis is conducted on the specific content of different types of carbon emissions, including carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulfur hexafluoride, and nitrogen trifluoride.

[0030] The proportion of different types of carbon emissions in total carbon emissions varies depending on a company's production activities and its use of energy and raw materials. Let the proportion of the s-th type of carbon emission in the energy-generated carbon emissions E be... , The specific content of the s-th type of carbon emission can be obtained through relevant industry research, experimental data, or enterprise-specific monitoring data. It can be calculated using the following formula, Use the above formulas to calculate the theoretical specific content of each type of carbon emission in each stage.

[0031] Based on industry standards and policy requirements, a comparative analysis is conducted to determine whether the specific content of different carbon emission types at each stage exceeds the limits. Different industries may have different limit standards for each carbon emission type at different production stages; therefore, the specific limit standards are not fixed. Let the limit standard for the s-th carbon emission type in the energy stage be... The calculated specific content of this type of carbon emission in this stage is: .if If this is the case, it indicates a problem with the company's production process design or production machinery, and an early warning will be issued. The above methods are used to compare whether the specific content of different carbon emission types in each stage exceeds the standard, and the stages exceeding the standard, the types of carbon emissions, and the specific content are recorded.

[0032] S40. Detect the actual carbon emission types and total carbon emissions of each stage of a single enterprise, and compare them with industry standards. If the standards are exceeded, an early warning will be issued.

[0033] Infrared absorption gas analyzer is used to detect the composition and content of carbon emissions from coal combustion and other processes, including carbon dioxide, methane, and nitrous oxide. Let the actual carbon emissions from a certain process be... In the analysis, the specific content of the e-th type of carbon emission in the total carbon emissions was determined as follows: The content detected by instruments is affected by uncertainty. Uncertainty is a parameter that describes the reliability of measurement and reflects the range of difference between the measured value and the true value.

[0034] Corrected detection value The meeting will be located in and Between, among them, The uncertainty in the accuracy of a measuring device. Uncertainty represents the limitations of a measurement method. Indicates the uncertainty of environmental conditions. The uncertainty represents the non-uniformity of the sample. This indicates the industry standard limit for the e-th type of carbon emission at this stage. If the actual emissions of the e-th type of carbon emission exceed the standard, an early warning will be issued.

[0035] The contents of hydrofluorocarbons, perfluorinated carbon, sulfur hexafluoride, and nitrogen trifluoride at each stage were detected using gas chromatography-mass spectrometry (GC-MS). Let the actual carbon emissions from a certain stage be L, and the specific content of the b-th carbon emission type within the actual carbon emissions be determined as follows: The content detected using a coupled instrument is affected by uncertainty, and the corrected detection value The meeting will be located in and Between, among them, The uncertainty in the concentration of a standard substance. This represents the uncertainty in the instrument's response. Indicates the uncertainty of environmental conditions. This indicates the uncertainty in the sample injection process. This indicates the industry standard limit for carbon emission type b at this stage. If the actual emissions of carbon emission type b exceed the standard, an early warning will be issued.

[0036] The above formula is used to calculate the actual carbon emission types and content in each stage. If the content of more than one type exceeds the standard, an early warning will be issued, and the warning stage and the type of carbon emission exceeding the standard will be recorded.

[0037] The actual carbon emissions of a single enterprise are aggregated from the measured emissions at each stage of its operations to obtain the total actual carbon emissions of that enterprise. Compared with theoretical total carbon emissions In comparison, if the actual total carbon emissions exceed the limit, an early warning will be issued. The actual total carbon emissions of each enterprise will be compared with the theoretical total carbon emissions, and a list of enterprises exceeding the limit will be compiled.

[0038] S50. Calculate the difference between the actual monitored carbon emissions in the control area and the carbon emission standard of the area, and calculate the difference between the content of carbon emission types in the control area and the standard for each type. If the standard is exceeded, an early warning will be issued.

[0039] set up This represents the total carbon emissions detected by monitoring stations within the controlled area during time period t. Indicates the carbon emission standards for the area. It represents the total amount of carbon dioxide. This indicates the total amount of methane. This represents the total amount of nitrous oxide. This indicates the total amount of hydrofluorocarbons. This indicates the total amount of perfluorocarbons. This indicates the total amount of sulfur hexafluoride. This indicates the total amount of nitrogen trifluoride.

[0040] like , If the carbon emission data quality within the controlled area is problematic, an early warning will be triggered. This indicates a single carbon emission gas within the controlled area. This indicates the corresponding emission standards. .

[0041] S60. Provide area warning records based on warning information.

[0042] The area's early warning records include: early warnings for individual carbon emissions exceeding standards within the control area; early warnings for total carbon emissions exceeding the area's carbon emission standards; early warnings for the specific content and total amount of carbon emissions in the theoretically planned production processes of enterprises within the control area exceeding standards; early warnings for the actual content of carbon emission types in each production process of enterprises within the control area exceeding the standard for any single type; and early warnings for the actual total carbon emissions of enterprises exceeding the theoretical total carbon emissions.

[0043] S70. Calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises that have taken certain emission reduction measures.

[0044] Let P be the carbon emission reduction potential index. Specifically, the calculation formula is as follows: ,in, This represents a technology coefficient set based on the company's technological level, reflecting the company's potential to achieve emission reductions through technological improvements. This indicates the amount of renewable energy consumed by the company. This represents a company's total energy consumption. The higher the proportion of renewable energy, the greater the potential for emission reduction. This represents a management coefficient set based on the company's management efficiency. This indicates a company's carbon emission intensity, reflecting its current carbon emission status. Y represents the company's total carbon emissions, and Y represents the company's economic output. Companies issuing warnings should take measures to reduce carbon emissions by improving technology, utilizing renewable energy, and enhancing corporate management efficiency.

[0045] Example 2

[0046] like Figure 2 As shown, Embodiment 2 of this application provides a carbon emission data quality early warning system based on big data, including: Data Acquisition Module: Used to collect carbon emission data from both enterprise and actual monitoring sources, and to perform data preprocessing.

[0047] Raw carbon emission data of enterprises within the control area were collected from enterprise reports and on-site visits. The raw carbon emission data of enterprises includes enterprise production data, energy consumption data, waste management data, types of carbon emissions, and other data that can generate carbon emissions.

[0048] Carbon emission data for the controlled area is collected through environmental monitoring stations and data acquisition terminals. This includes the types and amounts of carbon emission gases, as well as the total carbon emissions within the area. The types of carbon emission gases include carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorinated carbon, sulfur hexafluoride, and nitrogen trifluoride.

[0049] The collected data should be initially sorted and classified. Classification can be based on factors such as the source of the data, including enterprise type, energy type, time attribute of the data, annual, quarterly, and monthly data, specific carbon emission links reflected by the data, combustion emissions in the production process, and process emissions.

[0050] The collected data undergoes data cleaning to remove outliers and missing values. Missing data is filled using interpolation, while outliers are identified and processed using box plots. Based on industry experience, a normal fluctuation range for energy consumption of a certain type of enterprise is established. By setting reasonable data range thresholds, data exceeding this range is marked as suspicious and further verified or directly removed.

[0051] Data formatting was performed to standardize the time format and units, ensuring all data could be correctly parsed and compared. All carbon emission data was converted to tons per year and stored according to the year, month, and day time format. Through data cleaning and formatting, the accuracy and consistency of the data were ensured, providing a high-quality data foundation for subsequent calculations.

[0052] Enterprise Calculation Module: Used to calculate the theoretical total carbon emissions of a single enterprise based on its carbon emission data.

[0053] Coal combustion is a major cause of carbon emissions. Ideally, complete coal combustion produces carbon dioxide, but in actual combustion processes, incomplete combustion produces carbon dioxide and other greenhouse gases. The carbon emissions from coal combustion over a period of time *t* are... ,in This represents the amount of carbon dioxide emissions that could theoretically be produced by the complete combustion of carbon in coal within time t. The percentage of carbon content in the coal used can be found in coal quality testing reports or relevant coal resource data. This represents the amount of coal consumed over a period of time t. Based on the fixed stoichiometric relationship between carbon and carbon dioxide, the complete combustion of 12 parts by mass of carbon produces 44 parts by mass of carbon dioxide. The theoretical carbon dioxide emissions are then converted into the actual carbon dioxide emissions produced during combustion. This represents the amount of carbon dioxide emitted during the actual combustion process within time t. This indicates the efficiency of coal combustion. Indicates the methane emission factor. This represents the methane content produced during the actual combustion of coal within time t. Indicates the nitrous oxide emission factor. This represents the nitrous oxide content produced during the actual combustion of coal within time t. Incomplete combustion of coal produces other gases; this calculation only considers the carbon emissions from coal combustion.

[0054] Based on the company's production data, energy consumption data, and waste management data, calculate the total carbon emissions generated at each stage of the company's operations. ,in, This represents the carbon emissions generated by using coal energy within time t; if coal energy is not used, then... It is 0. This represents the carbon emissions generated by energy sources other than coal used by the company within time t, where n represents the number of energy sources used by the company. This represents the amount of the i-th type of energy consumed by the enterprise within time t. Let represent the carbon emission coefficient corresponding to the i-th energy source. This represents the carbon emissions generated within time t due to chemical reactions, physical changes, and other factors caused by the production process, where m represents the number of stages in the enterprise's production process. This represents the amount of relevant activity in the j-th stage of the enterprise's production process within time t. This represents the carbon emission factor corresponding to the j-th stage. This represents the carbon emissions generated by chemical reactions of raw materials during the production process within time t, where p is the number of types of raw materials used by the company. This indicates the amount of the z-th raw material used by the company. This represents the carbon emission factor corresponding to the z-th raw material. q represents the carbon emissions generated during the waste disposal process of the enterprise within time t, where q is the number of types of waste generated by the enterprise. This represents the amount of type l waste generated by the enterprise within time t. This represents the carbon emission coefficient of the l-th type of waste.

[0055] Based on the above calculation formula, calculate the carbon emissions of each enterprise within the controlled area.

[0056] The module for assessing the types and content of theoretical carbon emissions of enterprises includes a calculation submodule and an early warning submodule.

[0057] The calculation submodule is used to calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise.

[0058] For the calculated carbon emissions at each stage, let the carbon emissions from energy generation be E, the carbon emissions from production processes be A, the carbon emissions from raw materials during production be R, and the carbon emissions from waste treatment be W. Further analysis is conducted on the specific content of different types of carbon emissions, including carbon dioxide, methane, nitrous oxide, hydrofluorocarbons, perfluorocarbons, sulfur hexafluoride, and nitrogen trifluoride.

[0059] The proportion of different types of carbon emissions in total carbon emissions varies depending on a company's production activities and its use of energy and raw materials. Let the proportion of the s-th type of carbon emission in the energy-generated carbon emissions E be... , The specific content of the s-th type of carbon emission can be obtained through relevant industry research, experimental data, or enterprise-specific monitoring data. It can be calculated using the following formula, Use the above formulas to calculate the theoretical specific content of each type of carbon emission in each stage.

[0060] Early warning submodule: If the content of a certain type of product exceeds the industry standard, an early warning will be issued.

[0061] Based on industry standards and policy requirements, a comparative analysis is conducted to determine whether the specific content of different carbon emission types at each stage exceeds the limits. Different industries may have different limit standards for each carbon emission type at different production stages; therefore, the specific limit standards are not fixed. Let the limit standard for the s-th carbon emission type in the energy stage be... The calculated specific content of this type of carbon emission in this stage is: .if If this is the case, it indicates a problem with the company's production process design or production machinery, and an early warning will be issued. The above methods are used to compare whether the specific content of different carbon emission types in each stage exceeds the standard, and the stages exceeding the standard, the types of carbon emissions, and the specific content are recorded.

[0062] The enterprise's actual carbon emissions assessment module includes an infrared absorption gas analyzer submodule, a gas chromatography-mass spectrometry (GC-MS) submodule, and a comparison submodule.

[0063] Infrared absorption gas analyzer submodule: Uses an infrared absorption gas analyzer to detect carbon emissions from coal combustion and other processes, and compares whether the gas content exceeds the standard.

[0064] Infrared absorption gas analyzer is used to detect the composition and content of carbon emissions from coal combustion and other processes, including carbon dioxide, methane, and nitrous oxide. Let the actual carbon emissions from a certain process be... In the analysis, the specific content of the e-th type of carbon emission in the total carbon emissions was determined as follows: The content detected by instruments is affected by uncertainty. Uncertainty is a parameter that describes the reliability of measurement and reflects the range of difference between the measured value and the true value.

[0065] Corrected detection value The meeting will be located in and Between, among them, The uncertainty in the accuracy of a measuring device. Uncertainty represents the limitations of a measurement method. Indicates the uncertainty of environmental conditions. The uncertainty represents the non-uniformity of the sample. This indicates the industry standard limit for the e-th type of carbon emission at this stage. If the actual emissions of the e-th type of carbon emission exceed the standard, an early warning will be issued.

[0066] Gas Chromatography-Mass Spectrometry (GC-MS) Submodule: Uses GC-MS to detect the content of carbon emission gases and compares whether the gas content exceeds the standard.

[0067] The contents of hydrofluorocarbons, perfluorinated carbon, sulfur hexafluoride, and nitrogen trifluoride at each stage were detected using gas chromatography-mass spectrometry (GC-MS). Let the actual carbon emissions from a certain stage be L, and the specific content of the b-th carbon emission type within the actual carbon emissions be determined as follows: The content detected using a coupled instrument is affected by uncertainty, and the corrected detection value The meeting will be located in and Between, among them, The uncertainty in the concentration of a standard substance. This represents the uncertainty in the instrument's response. Indicates the uncertainty of environmental conditions. This indicates the uncertainty in the sample injection process. This indicates the industry standard limit for carbon emission type b at this stage. If the actual emissions of carbon emission type b exceed the standard, an early warning will be issued.

[0068] The above formula is used to calculate the actual carbon emission types and content in each stage. If the content of more than one type exceeds the standard, an early warning will be issued, and the warning stage and the type of carbon emission exceeding the standard will be recorded.

[0069] Comparison submodule: Used to compare the actual carbon emissions of a single enterprise with the theoretical total carbon emissions.

[0070] The actual carbon emissions of a single enterprise are aggregated from the measured emissions at each stage of its operations to obtain the total actual carbon emissions of that enterprise. Compared with theoretical total carbon emissions In comparison, if the actual total carbon emissions exceed the limit, an early warning will be issued. The actual total carbon emissions of each enterprise will be compared with the theoretical total carbon emissions, and a list of enterprises exceeding the limit will be compiled.

[0071] The controlled area assessment module is used to calculate the difference between the actual monitored carbon emissions in the controlled area and the carbon emission standards for the area, and to calculate the difference between the content of different types of carbon emissions in the controlled area and the standards for those types. If the standards are exceeded, an early warning will be issued.

[0072] set up This represents the total carbon emissions detected by monitoring stations within the controlled area during time period t. Indicates the carbon emission standards for the area. It represents the total amount of carbon dioxide. This indicates the total amount of methane. This represents the total amount of nitrous oxide. This indicates the total amount of hydrofluorocarbons. This indicates the total amount of perfluorocarbons. This indicates the total amount of sulfur hexafluoride. This indicates the total amount of nitrogen trifluoride.

[0073] like , If the carbon emission data quality within the controlled area is problematic, an early warning will be triggered. This indicates a single carbon emission gas within the controlled area. This indicates the corresponding emission standards. .

[0074] Early warning record module: Used to generate early warning records for a specific area based on early warning information.

[0075] The area's early warning records include: early warnings for individual carbon emissions exceeding standards within the control area; early warnings for total carbon emissions exceeding the area's carbon emission standards; early warnings for the specific content and total amount of carbon emissions in the theoretically planned production processes of enterprises within the control area exceeding standards; early warnings for the actual content of carbon emission types in each production process of enterprises within the control area exceeding the standard for any single type; and early warnings for the actual total carbon emissions of enterprises exceeding the theoretical total carbon emissions.

[0076] Carbon emission reduction calculation module: used to calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises after taking certain emission reduction measures.

[0077] Let P be the carbon emission reduction potential index. Specifically, the calculation formula is as follows: ,in, This represents a technology coefficient set based on the company's technological level, reflecting the company's potential to achieve emission reductions through technological improvements. This indicates the amount of renewable energy consumed by the company. This represents a company's total energy consumption. The higher the proportion of renewable energy, the greater the potential for emission reduction. This represents a management coefficient set based on the company's management efficiency. This indicates a company's carbon emission intensity, reflecting its current carbon emission status. Y represents the company's total carbon emissions, and Y represents the company's economic output. Companies issuing warnings should take measures to reduce carbon emissions by improving technology, utilizing renewable energy, and enhancing corporate management efficiency.

[0078] The specific embodiments described above further illustrate the purpose, technical solution, 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. Any modifications, equivalent substitutions, improvements, etc., made on the basis of the technical solution of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for early warning of carbon emission data quality based on big data, characterized in that, include: S10. Collect carbon emission data from both enterprise and actual monitoring perspectives, and perform data preprocessing; S20. Calculate the theoretical total carbon emissions of a single enterprise based on the enterprise's carbon emission data; S30. Calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise. If the specific content of a certain type exceeds the industry standard, an early warning will be issued. S40. Detect the actual carbon emission types and total carbon emissions of each stage of a single enterprise, and compare them with industry standards. If the standards are exceeded, an early warning will be issued. S50. Calculate the difference between the actual monitored carbon emissions in the control area and the carbon emission standard of the area, and calculate the difference between the content of carbon emission types in the control area and the standard for each type. If the standard is exceeded, an early warning will be issued. S60. Provide area warning records based on warning information; S70. Calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises that have taken certain emission reduction measures.

2. The carbon emission data quality early warning method based on big data as described in claim 1, characterized in that, Carbon emission data collection needs to be done from both enterprise and actual monitoring perspectives. Enterprise data includes enterprise production data, energy consumption data, waste management data, types of carbon emissions, and other data that can generate carbon emissions. Actual monitoring data includes the types and levels of carbon emission gases in the controlled area, and the total amount of carbon emissions in the area.

3. The carbon emission data quality early warning method based on big data as described in claim 1, characterized in that, In theory, calculating the total carbon emissions of a single enterprise requires separately calculating the carbon emissions from coal combustion. Coal combustion is the main cause of carbon emissions. Ideally, complete combustion of coal produces carbon dioxide, but in actual combustion, coal often undergoes incomplete combustion, producing carbon dioxide and other greenhouse gases. Calculating the carbon emissions from coal combustion separately makes the calculation results more accurate.

4. The carbon emission data quality early warning method based on big data as described in claim 1, characterized in that, The total carbon emissions of a single enterprise include carbon emissions from energy generation, carbon emissions from chemical reactions and physical changes caused by production processes, carbon emissions from chemical reactions of raw materials during production, and carbon emissions from waste disposal.

5. The carbon emission data quality early warning method based on big data as described in claim 1, characterized in that, To detect the actual types and amounts of carbon emissions at each stage of a single enterprise's operations, a gas analyzer is required. Depending on the type of carbon emission gas being detected, two types are used: infrared absorption gas analyzer and gas chromatography-mass spectrometry (GC-MS).

6. The carbon emission data quality early warning method based on big data as described in claim 4, characterized in that, The content detected by an infrared absorption gas analyzer is affected by uncertainties, including uncertainties in the accuracy of the measuring equipment, uncertainties in the limitations of the measuring method, uncertainties in environmental conditions, and uncertainties in the inhomogeneity of the sample.

7. The carbon emission data quality early warning method based on big data as described in claim 4, characterized in that, The content detected by gas chromatography-mass spectrometry is affected by uncertainties, including the uncertainty of the concentration of the standard substance, the uncertainty of the instrument response, the uncertainty of environmental conditions, and the uncertainty of the sample injection process.

8. A carbon emission data quality early warning system based on big data, characterized in that, include: Data Acquisition Module: Used to collect carbon emission data from both enterprise and actual monitoring sources, and to perform data preprocessing; Enterprise Calculation Module: Used to calculate the theoretical total carbon emissions of a single enterprise based on its carbon emission data; Enterprise Theoretical Carbon Emission Type Content Assessment Module: This module is used to calculate the theoretical specific content of carbon emission types in each stage of carbon emission based on the theoretical total carbon emission of a single enterprise. If the specific content of a certain type exceeds the industry standard, an early warning will be issued. Enterprise Actual Carbon Emission Assessment Module: This module is used to detect the actual carbon emission types and total carbon emissions of a single enterprise at each stage, and compare them with industry standards. If the standards are exceeded, an early warning will be issued. Control Area Assessment Module: Used to calculate the difference between the actual monitored carbon emissions in the control area and the carbon emission standard of the area, and to calculate the difference between the content of different types of carbon emissions in the control area and the standard for each type. If the standard is exceeded, an early warning will be issued. Early warning recording module: used to generate early warning records for a given area based on early warning information; Carbon emission reduction calculation module: used to calculate the carbon emission reduction potential index and assess the degree of carbon emission reduction achieved by enterprises after taking certain emission reduction measures.

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