Industrial boiler product carbon footprint accounting method and accounting device

Abstract

The present application relates to a kind of industrial boiler product carbon footprint accounting method and accounting device, carbon footprint accounting method includes the following steps: step S100: in the whole life cycle of industrial boiler product, form multistage carbon footprint accounting node, and carbon source data acquisition and input are carried out to the multistage carbon footprint accounting node, obtain multiple-node carbon activity unit and carbon activity data;Step S200: based on the multiple-node carbon activity unit, search carbon activity unit and factor database of carbon footprint accounting platform, obtain carbon activity factor;Step S300: based on the multiple-node carbon activity unit, influence effect analysis is carried out to multiple-node carbon activity unit, obtain the cause and effect independent variable parameter and multiple-dimension dependent variable correction coefficient;Step S400: based on multiple-node carbon activity information, through carbon footprint accounting analysis model, obtain the multiple-node carbon emission result and carbon footprint accounting result of industrial boiler product.

Description

Technical Field

[0001] This invention relates to the field of carbon footprint accounting technology, and in particular to a method and apparatus for calculating the carbon footprint of industrial boiler products. Background Technology

[0002] Industrial boilers are commonly used heat sources in many production and processing processes. However, their manufacturing and use generate greenhouse gases such as carbon dioxide, exacerbating global climate change and environmental pollution. Therefore, measuring the carbon emissions of industrial boilers and accurately calculating their carbon footprint is an important step in reducing greenhouse gas emissions, monitoring environmental impacts, and formulating carbon reduction policies.

[0003] Currently, the calculation of carbon emissions from industrial boilers mainly focuses on the product's usage process and often relies on manual data collection and complex calculations, which is neither comprehensive nor time-consuming and prone to errors. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and apparatus for calculating the carbon footprint of industrial boiler products.

[0005] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows: Firstly, a method for calculating the carbon footprint of industrial boiler products, comprising the following steps: Step S100: During the entire life cycle of industrial boiler products, multi-level carbon footprint accounting nodes are formed, and carbon source data is collected and entered into the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and carbon activity data. Step S200: Based on the multi-node carbon activity unit, search the carbon activity unit and factor database of the carbon footprint accounting platform to obtain carbon activity factors; Step S300: Based on the multi-node carbon active unit, perform an impact effect analysis on the multi-node carbon active unit to obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Step S400: Based on multi-node carbon activity information, obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products through a carbon footprint accounting analysis model; the multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting analysis model refers to the sum of carbon emission accounting models built with the manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide generated by carbon activities at each node based on carbon activity information, and then corrects the calculation results using multidimensional dependent correction coefficients to obtain the carbon emission results for each node.

[0006] Preferably, step S100 includes: Step S110: Perform carbon source analysis based on the multi-level carbon footprint accounting nodes to obtain the carbon activity units and carbon activity data of the node carbon sources; Step S120: Based on the carbon activity units and carbon activity data of the node carbon source, obtain carbon source set weight allocation data; the carbon source set weight allocation data is the proportion of the activity data of each carbon source activity unit of the node to the activity data of the total carbon source activity units of the node. Step S130: Obtain the carbon source analysis weight constraint; the carbon source analysis weight constraint refers to the threshold at which the proportion of carbon activity data of node carbon sources contributes less to the node's greenhouse gas emissions. Step S140: Determine whether the carbon source set weight allocation data meets the carbon source analysis weight constraint conditions, and obtain the carbon activity unit and carbon activity data judgment results of the carbon source; the carbon activity unit and carbon activity data judgment results of the carbon source refer to comparing the activity data of the carbon source activity unit with the threshold to see if it is less than the threshold. Step S150: Based on the judgment results of the carbon activity units and carbon activity data of the carbon source, the carbon activity units and carbon activity data of the carbon source are filtered to obtain multi-node carbon activity units and carbon activity data; if the activity data of the carbon source activity unit is less than the threshold, it is excluded from the node carbon activity unit and carbon activity dataset.

[0007] Preferably, the entire life cycle of the industrial boiler product includes: manufacturing process, transportation process, installation process, use process, and recycling process; The aforementioned multi-node carbon activity unit refers to the tangible material of the production or consumption activities that lead to greenhouse gas emissions; the aforementioned carbon activity data refers to the representation of the production or consumption activities of each node activity unit that lead to greenhouse gas emissions.

[0008] Preferably, step S200 includes: Step S210: Based on the multi-node carbon activity units and carbon activity data of industrial boiler products, obtain the carbon footprint accounting records of related products; Step S220: Based on the carbon footprint accounting records of the associated products, perform clustering and reliability analysis to obtain the standard carbon activity factor; Step S230: Based on the standard carbon activity factor and the multi-node carbon activity unit of the industrial boiler product, the carbon activity factor is obtained through feature correction calculation; the feature correction calculation is to calculate the feature quantity correction coefficient by performing data feature quantity calculation on the carbon activity factor of the industrial boiler product and the standard carbon activity factor; the carbon activity factor refers to the product of the standard carbon activity factor and the feature quantity correction coefficient.

[0009] Preferably, step S300 includes: Step S310: Obtain the associated records of the multi-node carbon activity data; Step S320: Perform carbon causation analysis based on the multi-node carbon activity data association records, determine the causal results of the multi-node carbon activity data association records, and obtain the causal independent variable parameters; Step S330: Based on the causal law of the multi-node carbon activity data association records, perform upgrade correction calculations on the multi-node carbon activity data association records to obtain multidimensional dependent variable correction coefficients; the multidimensional dependent variable correction coefficients include the dependent variable correction coefficients for the influence of multiple independent variables corresponding to the multi-level carbon footprint accounting nodes.

[0010] Preferably, after step S400, the method further includes: Step S500: Obtain the basic information of the industrial boiler product; Step S600: Based on the carbon footprint accounting results and basic information of the industrial boiler product, perform carbon footprint analysis to obtain an industrial boiler product carbon footprint report; Step S700: Based on the carbon footprint report of the industrial boiler product, conduct a feasibility analysis through a carbon footprint simulation and optimization model to obtain a carbon reduction plan for the industrial boiler product. The carbon footprint simulation and optimization model obtains multi-node carbon footprint ratio characteristic coefficients based on the industrial boiler product carbon footprint report. It then labels multi-level carbon footprint accounting nodes according to the multi-node carbon emissions and carbon footprint ratio characteristic coefficients to obtain the multi-level carbon footprint node optimization value. The greater the multi-level carbon footprint node optimization value, the better the carbon reduction effect of that node.

[0011] Preferably, multiple basic carbon reduction schemes for products are obtained by optimizing the value of multi-level carbon footprint nodes; the carbon footprint simulation optimization model is used to predict the effects of multiple basic carbon reduction schemes for products, and multiple predicted characteristic values ​​of industrial boiler cost and carbon footprint of industrial boiler are obtained; the better the predictive performance of the basic carbon reduction scheme for products, the larger the corresponding predicted characteristic value of industrial boiler product cost; the smaller the predicted carbon footprint accounting result of the basic carbon reduction scheme for products, the larger the corresponding predicted characteristic value of industrial boiler product carbon footprint.

[0012] Preferably, based on the basic carbon reduction schemes of multiple products, a low-carbon technology database is used for screening and matching to obtain multiple historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values; these multiple historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values ​​are ranked by similarity with multiple industrial boiler cost prediction feature values ​​and multiple industrial boiler carbon footprint prediction feature values; the multiple historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values ​​with the highest similarity are the multiple industrial boiler cost prediction feature values ​​and multiple industrial boiler carbon footprint prediction feature values. The carbon footprint prediction feature values ​​of multiple industrial boiler products are compared with the corresponding cost prediction feature values ​​of multiple industrial boiler products to obtain multiple basic carbon reduction scheme evaluation feature values ​​for the products. The maximum value of these multiple basic carbon reduction scheme evaluation feature values ​​is selected to determine the optimal carbon reduction scheme evaluation feature value. The multiple basic carbon reduction schemes for the products are matched based on the optimal carbon reduction scheme evaluation feature value to obtain the product carbon reduction scheme. The multiple basic carbon reduction scheme evaluation feature values ​​include multiple ratios between the carbon footprint prediction feature values ​​of multiple industrial boiler products and the corresponding cost prediction feature values ​​of multiple industrial boiler products. The optimal carbon reduction scheme evaluation feature value refers to the maximum value among the multiple carbon reduction scheme evaluation feature values. The product carbon reduction scheme refers to the basic carbon reduction scheme for the product corresponding to the optimal carbon reduction scheme evaluation feature value.

[0013] Secondly, an accounting device is provided, which performs carbon footprint accounting using the aforementioned industrial boiler product carbon footprint accounting method; the accounting device includes: Carbon data acquisition and input module: used to form multi-level carbon footprint accounting nodes throughout the entire life cycle of industrial boiler products, and to collect and input carbon source data for the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and carbon activity data. Carbon activity factor acquisition module: used to search the carbon activity unit and factor database of the carbon footprint accounting platform based on the multi-node carbon activity units to obtain carbon activity factors. Carbon data processing module: used to perform impact effect analysis on the multi-node carbon activity unit based on the multi-node carbon activity unit, and obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Carbon footprint accounting module: Based on multi-node carbon activity information, it uses a carbon footprint accounting analysis model to obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products; The multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting and analysis model refers to the sum of the carbon emission accounting models built with the production and manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide generated by carbon activities at each node based on carbon activity information, and then corrects the calculation results using multidimensional dependent correction coefficients to obtain the carbon emission results for each node.

[0014] Preferably, the accounting device further includes: Basic information acquisition module: used to acquire basic information about the industrial boiler product; Carbon footprint analysis module: used to perform carbon footprint analysis based on the carbon footprint accounting results and basic information of the industrial boiler product, and obtain a carbon footprint report of the industrial boiler product; Carbon reduction optimization module: Based on the carbon footprint report of the industrial boiler product, it performs feasibility analysis through a carbon footprint simulation optimization model to obtain carbon reduction solutions for the industrial boiler product. The carbon footprint simulation and optimization model calculates the ratio of the multi-node carbon footprint accounting results of industrial boiler products to obtain the multi-node carbon footprint ratio characteristic coefficient. Based on the multi-node carbon emissions and the carbon footprint ratio characteristic coefficient, the multi-level carbon footprint accounting nodes are labeled to obtain the multi-level carbon footprint node optimization value. The higher the multi-level carbon footprint node optimization value, the better the carbon reduction effect of that node.

[0015] The beneficial effects of this invention are as follows: This invention provides a method and apparatus for calculating the carbon footprint of industrial boiler products, solving the problems of incomplete scope and inaccurate results in existing carbon footprint calculation methods for industrial boiler products. Through carbon data acquisition and input, carbon activity factor acquisition, and carbon data processing, based on multi-node carbon activity information and a carbon footprint calculation analysis model, multi-node carbon emission results and carbon footprint calculation results for industrial boiler products are obtained; thus achieving efficient, stable, and accurate technical effects for carbon footprint calculation of industrial boiler products. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Obviously, the drawings described below only relate to some embodiments of this disclosure, and are not intended to limit this disclosure.

[0017] Figure 1 This is a flowchart illustrating a method for calculating the carbon footprint of an industrial boiler product according to the present invention. Figure 2 This is a schematic diagram of the structure of the accounting device of the present invention; The module includes: 11. Carbon data acquisition and input module; 12. Carbon activity factor acquisition module; 13. Carbon data processing module; 14. Carbon footprint accounting module; 15. Basic information acquisition module; 16. Carbon footprint analysis module; and 17. Carbon reduction optimization module. Detailed Implementation

[0018] The technical solutions in the embodiments of the present invention have been clearly and completely described. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0019] First aspect: Please see the appendix Figure 1 A method for calculating the carbon footprint of industrial boiler products includes the following steps: Step S100: During the entire life cycle of industrial boiler products, multi-level carbon footprint accounting nodes are formed, and carbon source data is collected and entered into the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and carbon activity data. Step S200: Based on the multi-node carbon activity unit, search the carbon activity unit and factor database of the carbon footprint accounting platform to obtain carbon activity factors; Step S300: Based on the multi-node carbon active unit, perform an impact effect analysis on the multi-node carbon active unit to obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Step S400: Based on multi-node carbon activity information, obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products through a carbon footprint accounting analysis model; the multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting analysis model refers to the sum of carbon emission accounting models built with the manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide emissions generated by carbon activities at each node (specifically, the carbon activities at each node in the production, transportation, installation, use, and recycling processes) based on carbon activity information. The calculation results are then corrected using a multidimensional dependent variable correction coefficient to obtain the carbon emission results for each node. Finally, based on database queries, data sets are constructed from the multi-node carbon emission results of multiple industrial boilers in the database.

[0020] By collecting and inputting carbon data, obtaining carbon activity factors, and processing carbon data, and based on multi-node carbon activity information, a carbon footprint accounting analysis model is used to obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products; thus achieving efficient, stable, and accurate technical results for carbon footprint accounting of industrial boiler products.

[0021] The carbon footprint accounting analysis model is formula (1), and the carbon footprint accounting result (CFP) is expressed as follows: (1); In the formula: The unit is ton carbon dioxide equivalent (tCO2e). The amount of carbon dioxide emitted during the production and manufacturing process of the accounting entity is expressed in tons of carbon dioxide equivalent (tCO2e). The amount of carbon dioxide emitted during the transportation process of the main body is calculated in tons of carbon dioxide equivalent (tCO2e). The amount of carbon dioxide emitted during the installation process of the main body is calculated in tons of carbon dioxide equivalent (tCO2e). The amount of carbon dioxide emitted during the use of the main body is calculated in tons of carbon dioxide equivalent (tCO2e). The amount of carbon dioxide emitted during the main body's recycling and treatment process is expressed in tons of carbon dioxide equivalent (tCO2e).

[0022] Specifically, the entire life cycle process refers to the entire life cycle of an industrial boiler product, from its initial material stage back to its final material stage, including: manufacturing, transportation, installation, use, and recycling. The manufacturing process begins when all resources and materials enter the factory and ends when the industrial boiler product is ready for shipment. The transportation process begins after the industrial boiler product leaves the factory and ends when it reaches its final destination. The installation process begins when the industrial boiler product is assembled at its final destination and ends when it is ready for operation. The use process begins when the industrial boiler product starts operating and outputs heat and ends when it reaches its designed service life. The recycling process begins when the industrial boiler product reaches the end of its designed service life and ends when the industrial boiler is recycled, dismantled, and sorted. This entire life cycle process corresponds to multi-level carbon footprint accounting nodes. These multi-level carbon footprint accounting nodes include the manufacturing, transportation, installation, use, and recycling nodes of the industrial boiler product. The multi-node carbon activity units refer to the tangible materials of production or consumption activities that contribute to greenhouse gas emissions. Examples include fossil fuels, metallic materials, non-metallic materials, electricity, steam, and hot water. Carbon activity data refers to the amount of production or consumption activities at each node that contribute to greenhouse gas emissions. Examples include: the amount of fossil fuels burned, the amount of metallic and non-metallic materials used, the amount of electricity purchased, and the amount of steam and hot water consumed.

[0023] In step S400, each data group contains multi-node carbon activity units, carbon activity data, carbon activity factors, multidimensional dependent correction coefficients, and carbon emission result information for multiple industrial boiler products.

[0024] Furthermore, 80% of the data from multiple datasets is randomly selected as a debug dataset, and 20% is randomly selected as a training dataset. The debug dataset is continuously trained and learned until convergence, resulting in a carbon footprint accounting analysis model. The debug dataset is then used as input to the model, allowing for gradual algorithm updates and iterative performance optimization. This carbon footprint accounting analysis model has the function of calculating the carbon footprint of multi-node carbon activity information from input industrial boiler products.

[0025] By using a carbon footprint accounting analysis model to calculate the carbon footprint of carbon activities at multiple nodes, a complete and adaptive carbon footprint accounting result for industrial boiler products was obtained, thereby improving the efficiency, stability, and accuracy of carbon footprint accounting for industrial boiler products.

[0026] Specifically, in one optional implementation, the method for calculating the carbon footprint of an industrial boiler product... Step S100 includes: Step S110: Perform carbon source analysis based on the multi-level carbon footprint accounting nodes to obtain the carbon activity units and carbon activity data of the node carbon sources; Step S120: Based on the carbon activity units and carbon activity data of the node carbon source, obtain carbon source set weight allocation data; the carbon source set weight allocation data is the proportion of the activity data of each carbon source activity unit of the node to the activity data of the total carbon source activity units of the node. Step S130: Obtain the carbon source analysis weight constraint; the carbon source analysis weight constraint refers to the threshold at which the proportion of carbon activity data of node carbon sources contributes less to the node's greenhouse gas emissions. Step S140: Determine whether the carbon source set weight allocation data meets the carbon source analysis weight constraint conditions, and obtain the carbon activity unit and carbon activity data judgment results of the carbon source; the carbon activity unit and carbon activity data judgment results of the carbon source refer to comparing the activity data of the carbon source activity unit with the threshold to see if it is less than the threshold. Step S150: Based on the judgment results of the carbon activity units and carbon activity data of the carbon source, the carbon activity units and carbon activity data of the carbon source are filtered to obtain multi-node carbon activity units and carbon activity data; if the activity data of the carbon source activity unit is less than the threshold, it is excluded from the node carbon activity unit and carbon activity dataset.

[0027] Furthermore, carbon source analysis is performed based on the multi-level carbon footprint accounting nodes to obtain the carbon activity units and carbon activity data of the node carbon sources. The carbon activity units of the node carbon sources refer to quantifiable basic substances that lead to the production or consumption of greenhouse gas emissions, including coal, diesel, natural gas, seamless steel pipes, and steel plates. The carbon activity data of the node carbon sources refers to the representation of the production or consumption of greenhouse gas emissions caused by the carbon activity units of the node carbon sources. Examples include: coal consumption, diesel consumption, natural gas consumption, and the use of seamless steel pipes and plates.

[0028] Furthermore, based on the carbon activity units and carbon activity data of the node carbon sources, carbon source set weight allocation data is obtained. The carbon source set weight allocation data represents the proportion of activity data of each carbon source activity unit in the total activity data of all carbon source activity units in the node. The larger this proportion, the greater the carbon footprint contribution and the greater the contribution to the greenhouse effect of that carbon source activity unit; conversely, the smaller this proportion, the smaller the carbon footprint contribution and the smaller the contribution to the greenhouse effect. For example, for a carbon activity unit like natural gas, the proportions of carbon source activity units and activity data are as follows: methane 96.76%, nitrogen 1.86%, propane 0.18%, ethane 0.885%, hydrogen 0.105%, carbon monoxide 0.1%, carbon dioxide 0.06%, and ethylene 0.05%.

[0029] Furthermore, the carbon source analysis weighting constraints are obtained. These constraints refer to the threshold threshold at which the proportion of carbon activity data from a node's carbon source contributes minimally to the node's greenhouse gas emissions. For example, the threshold could be 1%.

[0030] Furthermore, it is determined whether the weighted allocation data of the carbon source set satisfies the weighted constraints of the carbon source analysis, thereby obtaining the judgment results of the carbon activity units and carbon activity data of the carbon source. The judgment results of the carbon activity units and carbon activity data refer to comparing the activity data of the carbon source activity units with a threshold to see if it is less than the threshold.

[0031] Furthermore, based on the judgment results of the carbon activity units and carbon activity data of the carbon source, the carbon activity units and carbon activity data of the carbon source are filtered to obtain multi-node carbon activity units and carbon activity data. If the activity data of a carbon source activity unit is less than a threshold, it is excluded from the node carbon activity unit and carbon activity dataset. For example, propane 0.18% is less than the threshold of 1%, so it is excluded from the node carbon activity unit and carbon activity dataset.

[0032] By obtaining multi-level carbon footprint accounting nodes and collecting and inputting carbon source data for these nodes, reliable and comprehensive multi-node carbon activity units and carbon activity data can be obtained, thereby improving the technical effect of accurately calculating the carbon footprint of industrial boiler products.

[0033] Specifically, in one optional implementation, step S200 includes: Step S210: Based on the multi-node carbon activity units and carbon activity data of industrial boiler products, obtain the carbon footprint accounting records of related products; Step S220: Based on the carbon footprint accounting records of the associated products, perform clustering and reliability analysis to obtain the standard carbon activity factor; Step S230: Based on the standard carbon activity factor and the multi-node carbon activity unit of the industrial boiler product, the carbon activity factor is obtained through feature correction calculation; the feature correction calculation is to calculate the feature quantity correction coefficient by performing data feature quantity calculation on the carbon activity factor of the industrial boiler product and the standard carbon activity factor; the carbon activity factor refers to the product of the standard carbon activity factor and the feature quantity correction coefficient.

[0034] Specifically, based on the multi-node carbon activity units, the carbon activity unit & factor database of the carbon footprint accounting platform is searched to obtain carbon activity factors. The carbon activity unit & factor database of the carbon footprint accounting platform first includes data collected from enterprises and institutions, such as actual carbon emissions, energy consumption, and product lifecycle data. Secondly, it includes relevant standard service data collected from publicly available channels such as authoritative literature, government documents, academic papers, and research reports. Finally, it includes, but is not limited to, energy consumption data, carbon emission data, and environmental impact data obtained through commercial cooperation with data providers. The carbon activity factor refers to a coefficient characterizing greenhouse gas emissions per unit of production or consumption activity; for example, the carbon activity factor for each ton of seamless steel pipe is 3150 kgCO2 / t.

[0035] Furthermore, based on the correlation analysis of multi-node carbon activity units and carbon activity data of industrial boiler products, carbon footprint accounting records of related products are obtained. The correlation analysis of multi-node carbon activity units and carbon activity data of industrial boiler products refers to multiple carbon footprint correlation parameters corresponding to multiple data types of information in multi-node data items. The larger the carbon footprint correlation parameters, the stronger the correlation between the corresponding correlation data types and the carbon footprint of the industrial product. For example, by querying the carbon footprint accounting records of internal combustion engine products, multiple data types of information for the node carbon activity unit: diesel, and multiple data types, such as usage nodes, fossil fuels, combustion, etc., corresponding to carbon footprint correlation parameters, are obtained. These carbon footprint correlation parameters have a strong correlation with the carbon footprint of industrial boiler products. The carbon footprint accounting records of related products refer to carbon accounting records of products with strong carbon footprint correlation, such as the carbon accounting records of internal combustion engine products.

[0036] Furthermore, based on the carbon footprint accounting records of the associated industrial boiler products, clustering and reliability analysis are performed to obtain a standard carbon activity factor. The clustering and reliability analysis group multiple carbon footprint related data corresponding to the same data type into one category, and verify the accuracy, authority, and reliability of the data source, confirming that the data is objective data obtained through calibration, verification, and certification. The standard carbon activity factor refers to the carbon data factor of the associated industrial boiler product carbon footprint, used as the benchmark factor for the industrial boiler product carbon data factor through clustering and reliability analysis.

[0037] Furthermore, based on the standard carbon activity factor and the multi-node carbon activity unit of the industrial boiler product, a carbon activity factor is obtained through feature correction calculation. The feature correction calculation involves calculating data feature quantities such as elemental composition, density, kinematic viscosity, and flash point by comparing the industrial boiler product carbon activity factor with the standard carbon activity factor, and obtaining feature quantity correction coefficients. The carbon activity factor is the product of the standard carbon activity factor and the feature quantity correction coefficient.

[0038] By clustering and reliability analysis of the carbon footprint accounting records of related industrial boiler products, reliable and comprehensive carbon activity factors were obtained, thereby improving the technical effectiveness of carbon footprint accounting for industrial boiler products.

[0039] Specifically, in one optional implementation, step S300 includes: Step S310: Obtain the associated records of the multi-node carbon activity data; Step S320: Perform carbon causation analysis based on the multi-node carbon activity data association records, determine the causal results of the multi-node carbon activity data association records, and obtain the causal independent variable parameters; Step S330: Based on the causal law of the multi-node carbon activity data association records, perform upgrade correction calculations on the multi-node carbon activity data association records to obtain multidimensional dependent variable correction coefficients; the multidimensional dependent variable correction coefficients include the dependent variable correction coefficients for the influence of multiple independent variables corresponding to the multi-level carbon footprint accounting nodes.

[0040] Specifically, based on the multi-node carbon activity unit, an impact effect analysis is performed on the multi-node carbon activity data of industrial boilers to obtain multi-dimensional dependent variable correction coefficients. These multi-dimensional dependent variable correction coefficients include the dependent variable correction coefficients for the influence of multiple independent variables corresponding to the multi-level carbon footprint accounting nodes. The larger the multi-dimensional dependent variable correction coefficient, the greater the impact of that multi-dimensional dependent variable correction coefficient on the carbon emissions and carbon footprint accounting results of the industrial boiler product at that node, and the greater the value of carbon footprint optimization for the carbon emissions at that node. For example, the impact of the multi-dimensional independent parameters of the industrial boiler product, such as fuel carbon content and net calorific value, on the dependent variable, the node carbon emissions and carbon footprint accounting results of the industrial boiler product, is illustrated. This achieves the goal of improving the accuracy of the node carbon emissions and carbon footprint accounting results of industrial boiler products by obtaining the multi-dimensional dependent variable correction coefficients corresponding to the multi-dimensional independent parameters, making them more consistent with actual conditions.

[0041] Furthermore, the multi-node carbon activity data correlation records are obtained. These multi-node carbon activity data correlation records refer to information with strong correlation to the multi-node carbon emissions and carbon footprint accounting results of industrial boiler products. For example, test data information on how heat energy is converted, transferred, stored, and utilized internally in the boiler, as well as boiler efficiency and carbon oxidation rate.

[0042] Furthermore, carbon causation analysis is performed based on the multi-node carbon activity data association records to determine the causal law results of the multi-node carbon activity data association records and obtain the causal independent variable parameter. The carbon causation analysis of multi-node carbon activity data association records refers to a method of pursuing the causes of known results. First, the results of the multi-node carbon activity data association records are confirmed; second, possible causes for these results are hypothesized; third, the impact of different results on the multi-node carbon activity data is compared; and finally, the causal law results are repeatedly verified. When the causal law result is positive, the results of the multi-node carbon activity data association records have a positive effect on the multi-node carbon activity data; conversely, when the causal law result is negative, the results of the multi-node carbon activity data association records have a negative effect on the multi-node carbon activity data; and when the causal law is zero, the results of the multi-node carbon activity data association records have no effect on the multi-node carbon activity data. The causal independent variable parameter refers to the assumed cause of the result when the causal law result is positive or negative (i.e., non-zero). For example: boiler oxygen content, flue gas temperature, fly ash carbon content, and ash residue carbon content.

[0043] Furthermore, based on the causal laws of the multi-node carbon activity data association records, an upsizing correction calculation is performed on these records to obtain multidimensional dependent variable correction coefficients. This upsizing correction calculation involves performing dimensional expansion calculations on the causal independent variable parameters corresponding to the multi-node carbon activity data association records, mapping the low-dimensional causal independent variable parameters to a high-dimensional space. The aim is to obtain projection information in the projected multidimensional space, thereby achieving the function of correcting, improving, and optimizing low-dimensional data. The multidimensional dependent variable correction coefficients refer to the quantitative values ​​used to correct, improve, and optimize low-dimensional data from high-dimensional data.

[0044] By analyzing the carbon causation of multi-node carbon activity data, reliable and comprehensive multidimensional causal correction coefficients were obtained, thereby improving the technical effectiveness of carbon footprint accounting for industrial boiler products.

[0045] Specifically, in one optional implementation, step S400 is followed by: Step S500: Obtain the basic information of the industrial boiler product; Step S600: Based on the carbon footprint accounting results and basic information of the industrial boiler product, perform carbon footprint analysis to obtain an industrial boiler product carbon footprint report; Step S700: Based on the carbon footprint report of the industrial boiler product, conduct a feasibility analysis through a carbon footprint simulation and optimization model to obtain a carbon reduction plan for the industrial boiler product. The carbon footprint simulation and optimization model obtains multi-node carbon footprint ratio characteristic coefficients based on the industrial boiler product carbon footprint report. It then labels multi-level carbon footprint accounting nodes according to the multi-node carbon emissions and carbon footprint ratio characteristic coefficients to obtain the multi-level carbon footprint node optimization value. The greater the multi-level carbon footprint node optimization value, the better the carbon reduction effect of that node.

[0046] Furthermore, multiple basic carbon reduction schemes for products are obtained based on the value of multi-level carbon footprint node optimization. The carbon footprint simulation optimization model is used to predict the effects of multiple basic carbon reduction schemes for products, and multiple industrial boiler cost prediction feature values ​​and multiple industrial boiler carbon footprint prediction feature values ​​are obtained. The better the prediction performance of the basic carbon reduction scheme, the larger the corresponding industrial boiler product cost prediction feature value. The smaller the predicted carbon footprint accounting result of the basic carbon reduction scheme, the larger the corresponding industrial boiler product carbon footprint prediction feature value.

[0047] Furthermore, based on the basic carbon reduction solutions of multiple products, a low-carbon technology database is used for screening and matching to obtain multiple historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values. These feature values ​​are then ranked by similarity with other historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values. The feature values ​​with the highest similarity are the actual industrial boiler cost prediction feature values ​​and multiple industrial boiler carbon footprint prediction feature values. The carbon footprint prediction feature values ​​of multiple industrial boiler products are compared with the corresponding cost prediction feature values ​​of multiple industrial boiler products to obtain multiple basic carbon reduction scheme evaluation feature values ​​for the products. The maximum value of these multiple basic carbon reduction scheme evaluation feature values ​​is selected to determine the optimal carbon reduction scheme evaluation feature value. The multiple basic carbon reduction schemes for the products are matched based on the optimal carbon reduction scheme evaluation feature value to obtain the product carbon reduction scheme. The multiple basic carbon reduction scheme evaluation feature values ​​include multiple ratios between the carbon footprint prediction feature values ​​of multiple industrial boiler products and the corresponding cost prediction feature values ​​of multiple industrial boiler products. The optimal carbon reduction scheme evaluation feature value refers to the maximum value among the multiple carbon reduction scheme evaluation feature values. The product carbon reduction scheme refers to the basic carbon reduction scheme for the product corresponding to the optimal carbon reduction scheme evaluation feature value.

[0048] Specifically, the basic information of the industrial boiler products includes product name, product function, usage method, form, configuration, brand, and other product characteristic information. Examples include the industrial boiler's application, boiler structure, water circulation method, outlet working fluid pressure classification, combustion method, and manufacturer.

[0049] Specifically, the industrial boiler product carbon footprint report organizes basic information about industrial boiler products, compiles carbon footprint calculation results and corresponding multi-node carbon emission results, and presents and compares data through charts and graphs. It uses an intuitive and digital approach to represent the differences in various values ​​and characteristics, and provides preliminary analysis and explanation of these differences. For example, based on the industrial boiler product carbon footprint calculation results and corresponding multi-node carbon emission results, it compares the carbon emission data of the production, transportation, installation, and recycling nodes through both cyclical and linear data characteristic comparisons. The cyclical data characteristic comparison compares the numerical values ​​of carbon emission results at each node to determine the magnitude and degree of differences between them. The linear data characteristic comparison compares the proportional values ​​of the activity data weights of the carbon activity units corresponding to the carbon emission results at each node to determine the magnitude and degree of differences between them.

[0050] Secondly, such as Figure 2 As shown, an accounting device is used to perform carbon footprint accounting for industrial boiler products using the aforementioned carbon footprint accounting method; the accounting device includes: Carbon data acquisition and input module 11: used to form multi-level carbon footprint accounting nodes throughout the entire life cycle of industrial boiler products, and to collect and input carbon source data for the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and carbon activity data. Carbon activity factor acquisition module 12: used to search the carbon activity unit and factor database of the carbon footprint accounting platform based on the multi-node carbon activity unit to obtain carbon activity factors. Carbon data processing module 13: used to perform impact effect analysis on the multi-node carbon activity unit based on the multi-node carbon activity unit, and obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Carbon footprint accounting module 14: Based on multi-node carbon activity information, it uses a carbon footprint accounting analysis model to obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products. The multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting and analysis model refers to the sum of the carbon emission accounting models built with the production and manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide generated by carbon activities at each node based on carbon activity information, and then corrects the calculation results using multidimensional dependent correction coefficients to obtain the carbon emission results for each node.

[0051] Specifically, in one optional embodiment, the accounting device further includes: Basic information acquisition module 15: used to acquire basic information about the industrial boiler product; Carbon footprint analysis module 16: used to perform carbon footprint analysis based on the carbon footprint accounting results and basic information of the industrial boiler product, and obtain a carbon footprint report of the industrial boiler product; Carbon reduction optimization module 17: Based on the carbon footprint report of the industrial boiler product, it performs a feasibility analysis through a carbon footprint simulation optimization model to obtain a carbon reduction solution for the industrial boiler product. The carbon footprint simulation and optimization model calculates the ratio of multi-node carbon footprint accounting results to the total carbon footprint accounting results for industrial boiler products, obtaining a multi-node carbon footprint ratio characteristic coefficient. Based on the multi-node carbon emissions and the carbon footprint ratio characteristic coefficient, multi-level carbon footprint accounting nodes are labeled to obtain the optimization value of each multi-level carbon footprint node. The higher the optimization value of a multi-level carbon footprint node, the better the carbon reduction effect at that node. Based on the basic information of industrial boiler products and the optimization value of multi-level carbon footprint nodes, carbon reduction solutions for multiple products are obtained.

[0052] Specifically, in one optional implementation, the carbon data acquisition and input module 11 includes: Carbon source analysis module: The carbon source analysis module is used to perform carbon source analysis based on the multi-level carbon footprint accounting nodes to obtain the carbon activity units and carbon activity data of the node carbon sources; Carbon source set weight allocation module: The carbon source set weight allocation module is used to obtain carbon source set weight allocation data based on the carbon activity units and carbon activity data of the node carbon source; the carbon source set weight allocation data is the proportion of the activity data of each carbon source activity unit of the node to the activity data of the total carbon source activity units of the node; First execution module: The first execution module is used to obtain the carbon source analysis weight constraint condition; the carbon source analysis weight constraint condition refers to the threshold at which the proportion of carbon activity data of node carbon sources contributes less to the node's greenhouse gas emissions; Judgment Module: The judgment module is used to determine whether the carbon source set weight allocation data meets the carbon source analysis weight constraint conditions, and to obtain the judgment results of the carbon activity unit and carbon activity data of the carbon source; the judgment results of the carbon activity unit and carbon activity data of the carbon source refer to comparing the activity data of the carbon source activity unit with a threshold to see if it is less than the threshold. Data filtering module: The data filtering module is used to filter the carbon activity units and carbon activity data of the carbon source based on the judgment results of the carbon activity units and carbon activity data of the carbon source, and obtain multi-node carbon activity units and carbon activity data; if the activity data of the carbon source activity unit is less than the threshold, it is excluded from the node carbon activity unit and carbon activity dataset.

[0053] Specifically, in one optional implementation, the carbon activity factor obtaining module 12 includes: Second execution module: The second execution module is used to obtain carbon footprint accounting records of related products based on multi-node carbon activity units and carbon activity data of industrial boiler products; Clustering reliability analysis module: The clustering reliability analysis module is used to perform clustering and reliability analysis based on the carbon footprint accounting records of the associated products to obtain the standard carbon activity factor; Feature Correction Calculation Module: The feature correction calculation module is used to obtain the carbon activity factor based on the standard carbon activity factor and the multi-node carbon activity unit of the industrial boiler product through feature correction calculation; the feature correction calculation is to calculate the feature quantity correction coefficient by performing data feature quantity calculation on the carbon activity factor of the industrial boiler product and the standard carbon activity factor; the carbon activity factor refers to the product of the standard carbon activity factor and the feature quantity correction coefficient.

[0054] Specifically, in one optional implementation, the carbon data processing module 13 includes: Third execution module: The third execution module is used to obtain the multi-node carbon activity data association records; Carbon causation analysis module: The carbon causation analysis module is used to perform carbon causation analysis based on the multi-node carbon activity data association records, determine the causal results of the multi-node carbon activity data association records, and obtain causation independent parameters; Upgraded correction calculation module: The upgraded correction calculation module is used to perform upgraded correction calculation on the multi-node carbon activity data association records based on the causal law of the multi-node carbon activity data association records to obtain multidimensional dependent variable correction coefficients; the multidimensional dependent variable correction coefficients include the dependent variable correction coefficients of the influence of multiple independent variables corresponding to the multi-level carbon footprint accounting nodes.

[0055] The above description is only a specific embodiment of the present invention. Various examples and illustrations do not constitute a limitation on the substantive content of the present invention. Those skilled in the art can make modifications or variations to the above-described specific embodiments after reading the specification without departing from the substance and scope of the invention.

Claims

1. A method for calculating the carbon footprint of industrial boiler products, characterized in that: The steps include the following: Step S100: During the entire life cycle of industrial boiler products, multi-level carbon footprint accounting nodes are formed, and carbon source data is collected and entered into the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and multi-node carbon activity data; the multi-node carbon activity data refers to the representation of the amount of production or consumption activities that lead to greenhouse gas emissions by each node activity unit. Step S200: Based on the multi-node carbon activity unit, search the carbon activity unit and factor database of the carbon footprint accounting platform to obtain carbon activity factors; Step S300: Based on the multi-node carbon active unit, perform an impact effect analysis on the multi-node carbon active unit to obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Step S400: Based on multi-node carbon activity information, obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products through a carbon footprint accounting analysis model; the multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting analysis model refers to the sum of carbon emission accounting models built with the manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide generated by the carbon activities of each node based on carbon activity information, and then corrects the calculation results through multidimensional dependent variable correction coefficients to obtain the carbon emission results of each node. Step S200 includes: Step S210: Based on the multi-node carbon activity units and multi-node carbon activity data of industrial boiler products, obtain the carbon footprint accounting records of related products; Step S220: Based on the carbon footprint accounting records of the associated products, perform clustering and reliability analysis to obtain the standard carbon activity factor; Step S230: Based on the standard carbon activity factor and the multi-node carbon activity unit of the industrial boiler product, the carbon activity factor is obtained through feature correction calculation; the feature correction calculation is to calculate the feature quantity correction coefficient by performing data feature quantity calculation on the carbon activity factor of the industrial boiler product and the standard carbon activity factor; the carbon activity factor refers to the product of the standard carbon activity factor and the feature quantity correction coefficient. Step S300 includes: Step S310: Obtain the associated records of the multi-node carbon activity data; Step S320: Perform carbon causation analysis based on the multi-node carbon activity data association records, determine the causal results of the multi-node carbon activity data association records, and obtain the causal independent variable parameters; Step S330: Based on the causal law of the multi-node carbon activity data association records, perform upgrade correction calculations on the multi-node carbon activity data association records to obtain multidimensional dependent variable correction coefficients; the multidimensional dependent variable correction coefficients include the dependent variable correction coefficients for the influence of multiple independent variables corresponding to the multi-level carbon footprint accounting nodes.

2. The method for calculating the carbon footprint of industrial boiler products according to claim 1, characterized in that: The entire life cycle of the industrial boiler product includes: manufacturing process, transportation process, installation process, usage process, and recycling process; The aforementioned multi-node carbon activity unit refers to the tangible material of production or consumption activities that result in greenhouse gas emissions.

3. The method for calculating the carbon footprint of industrial boiler products according to claim 1, characterized in that: The process following step S400 also includes: Step S500: Obtain the basic information of the industrial boiler product; Step S600: Based on the carbon footprint accounting results and basic information of the industrial boiler product, perform carbon footprint analysis to obtain an industrial boiler product carbon footprint report; Step S700: Based on the carbon footprint report of the industrial boiler product, conduct a feasibility analysis through a carbon footprint simulation and optimization model to obtain a carbon reduction plan for the industrial boiler product. The carbon footprint simulation and optimization model obtains multi-node carbon footprint ratio characteristic coefficients based on the industrial boiler product carbon footprint report. It then labels multi-level carbon footprint accounting nodes according to the multi-node carbon emissions and carbon footprint ratio characteristic coefficients to obtain the multi-level carbon footprint node optimization value. The greater the multi-level carbon footprint node optimization value, the better the carbon reduction effect of that node.

4. The method for calculating the carbon footprint of industrial boiler products according to claim 3, characterized in that: Based on the value of multi-level carbon footprint node optimization, multiple basic carbon reduction schemes for products are obtained; the carbon footprint simulation optimization model is used to predict the effects of multiple basic carbon reduction schemes for products, and multiple industrial boiler cost prediction characteristic values ​​and multiple industrial boiler carbon footprint prediction characteristic values ​​are obtained. The better the predictive performance of the product's basic carbon reduction scheme, the larger the corresponding industrial boiler product cost prediction characteristic value; the smaller the predicted carbon footprint accounting result of the product's basic carbon reduction scheme, the larger the corresponding industrial boiler product carbon footprint prediction characteristic value.

5. The method for calculating the carbon footprint of industrial boiler products according to claim 4, characterized in that: Based on the basic carbon reduction solutions of multiple products, a low-carbon technology database is used for screening and matching to obtain multiple historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values. These feature values ​​are then ranked by similarity with other historical industrial boiler cost prediction feature values ​​and multiple historical industrial boiler carbon footprint prediction feature values. The feature values ​​with the highest similarity are the actual industrial boiler cost prediction feature values ​​and multiple industrial boiler carbon footprint prediction feature values. The carbon footprint prediction feature values ​​of multiple industrial boiler products are compared with the corresponding cost prediction feature values ​​of multiple industrial boiler products to obtain multiple basic carbon reduction scheme evaluation feature values ​​for the products. The maximum value of these multiple basic carbon reduction scheme evaluation feature values ​​is selected to determine the optimal carbon reduction scheme evaluation feature value. The multiple basic carbon reduction schemes for the products are matched based on the optimal carbon reduction scheme evaluation feature value to obtain the product carbon reduction scheme. The multiple basic carbon reduction scheme evaluation feature values ​​include multiple ratios between the carbon footprint prediction feature values ​​of multiple industrial boiler products and the corresponding cost prediction feature values ​​of multiple industrial boiler products. The optimal carbon reduction scheme evaluation feature value refers to the maximum value among the multiple carbon reduction scheme evaluation feature values. The product carbon reduction scheme refers to the basic carbon reduction scheme for the product corresponding to the optimal carbon reduction scheme evaluation feature value.

6. An accounting device, characterized in that: The carbon footprint of industrial boiler products shall be calculated using the carbon footprint accounting method described in any one of claims 1-5. The accounting device includes Carbon data acquisition and input module: used to form multi-level carbon footprint accounting nodes throughout the entire life cycle of industrial boiler products, and to collect and input carbon source data for the multi-level carbon footprint accounting nodes to obtain multi-node carbon activity units and multi-node carbon activity data. Carbon activity factor acquisition module: used to search the carbon activity unit and factor database of the carbon footprint accounting platform based on the multi-node carbon activity unit to obtain carbon activity factors; Carbon data processing module: used to perform impact effect analysis on the multi-node carbon activity unit based on the multi-node carbon activity unit, and obtain the causal independent variable parameters and multidimensional dependent variable correction coefficients; Carbon footprint accounting module: Based on multi-node carbon activity information, it uses a carbon footprint accounting analysis model to obtain multi-node carbon emission results and carbon footprint accounting results for industrial boiler products; The multi-node carbon activity information includes carbon activity units, carbon activity data, carbon activity factors, and multidimensional dependent variable correction coefficients; the carbon footprint accounting and analysis model refers to the sum of the carbon emission accounting models built with the production and manufacturing process, transportation process, installation process, use process, and recycling process as nodes; The carbon emission accounting model for each node calculates the carbon dioxide generated by carbon activities at each node based on carbon activity information, and then corrects the calculation results using multidimensional dependent correction coefficients to obtain the carbon emission results for each node.

7. The accounting apparatus according to claim 6, characterized in that: Also includes: Basic information acquisition module: used to acquire basic information about the industrial boiler product; Carbon footprint analysis module: used to perform carbon footprint analysis based on the carbon footprint accounting results and basic information of the industrial boiler product, and obtain a carbon footprint report of the industrial boiler product; Carbon reduction optimization module: Based on the carbon footprint report of the industrial boiler product, it performs feasibility analysis through a carbon footprint simulation optimization model to obtain carbon reduction solutions for the industrial boiler product. The carbon footprint simulation and optimization model calculates the ratio of the multi-node carbon footprint accounting results of industrial boiler products to obtain the multi-node carbon footprint ratio characteristic coefficient. Based on the multi-node carbon emissions and the carbon footprint ratio characteristic coefficient, the multi-level carbon footprint accounting nodes are labeled to obtain the multi-level carbon footprint node optimization value. The higher the multi-level carbon footprint node optimization value, the better the carbon reduction effect of that node.

Images