Ontology-based product carbon footprint assessment method and related device

Abstract

Disclosed in the present invention are an ontology-based product carbon footprint assessment method and a related device. The method comprises: on the basis of a published input-output table, calculating full lifecycle carbon emissions generated by means of the industry's average output value; then, by means of Taylor series expansion, calculating carbon emissions at different stages of the full industrial chain of a product, and identifying the stages with the highest carbon emissions; and finally performing accurate data replacement for the stages with high carbon emissions. The present invention provides a foundational database capable of being associated with an industrial activity relationship, provides a standardized ontology-based product carbon footprint assessment model based on the industry average, and embeds an inference algorithm to achieve automatic completion of an enterprise carbon footprint model, such that the standardization of carbon emission calculation and the transparency of carbon emissions at each production stage of a product are achieved, thereby helping enterprises to quickly assess their own product carbon footprints and benchmark against the industry carbon footprint.

Description

A product carbon footprint assessment method based on ontology and related equipment Technical Field

[0001] The present invention relates to the technical field of ontology-based product carbon footprint assessment, and in particular to an ontology-based product carbon footprint assessment method, system, terminal and computer-readable storage medium. Background Art

[0002] As the global "carbon neutrality" process accelerates, my country is fully committed to promoting low-carbon development in various industrial chains. Currently, most companies are unable to quickly and accurately assess their own carbon emissions. There is an urgent need to develop a standardized, intelligent, and efficient carbon footprint basic database and assessment method to enable companies to quickly and accurately assess their own carbon emissions.

[0003] Existing databases only provide data on carbon emission factors for different production activities and lack models for the interrelationships between different production activities along the industrial chain. Even ontology-based product carbon footprint assessments by different companies in the same industry require first analyzing the carbon emission processes throughout the lifecycle and then collecting data for calculation, resulting in a significant amount of duplication. Furthermore, the lack of standardized process modeling methods often results in a large number of processes being missing from the model, processes and relationships between them being collapsed, and modeling results from different teams differing significantly with the sources of these differences hidden, resulting in inaccurate, inconsistent, difficult to compare, difficult to trace, and difficult to reuse.

[0004] Most existing carbon footprint databases use a process-based lifecycle carbon footprint modeling approach, sequentially identifying all processes of a product, from raw material acquisition to transportation to production. For example, concrete production requires identifying all processes in its entire industry chain, including the fact that the concrete production process requires cement, water, and electricity, and generates direct carbon emissions; the cement production process requires limestone, water, and electricity, the production of water requires electricity, and the production of electricity requires coal; and coal production requires raw coal mining, etc. This process requires a large amount of cross-industry expertise, and often due to a lack of knowledge about the production process or missing data, a large number of processes are overlooked, resulting in an incomplete modeling framework. Omitted processes are generally not disclosed, making it difficult to form a standardized carbon footprint model in the industry, and it is also difficult to reuse and improve existing models among different teams, making it difficult to directly compare the carbon footprints of peer products.

[0005] Existing databases only provide data on carbon emission factors for different production activities (data from the professional field of carbon footprint assessment), but lack models for the interrelationships between different production activities along the industrial chain (data from the professional field of product-related assessment). Even when assessing the carbon footprint of products from different companies in the same industry, the process of identifying and analyzing the carbon emissions process throughout the product's life cycle must be preceded by data collection and calculation, resulting in a significant amount of duplication.

[0006] Therefore, the existing technology still needs to be improved and developed. Technical issues

[0007] The main purpose of the present invention is to provide an ontology-based product carbon footprint assessment method, system, terminal and computer-readable storage medium, aiming to solve the problem in the existing technology that it is impossible to obtain a standardized ontology-based product carbon footprint assessment model, thereby making it impossible for enterprises to quickly and accurately assess their own carbon emissions and obtain accurate ontology-based product carbon footprint assessment results. Technical Solutions

[0008] To achieve the above objectives, the present invention provides an ontology-based product carbon footprint assessment method, which comprises the following steps:

[0009] Determine the target product that requires ontology-based product carbon footprint assessment, determine the industry to which the target product belongs based on the target product and the industry basic database, obtain a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establish an environmental input-output life cycle assessment model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle assessment model;

[0010] Using Taylor series expansion, the carbon emission paths along the entire industrial chain of the target product are extracted, the carbon emissions along each carbon emission path are calculated, target points where carbon emissions exceed a preset threshold on all carbon emission paths are identified, and high-carbon emission processes are determined based on the target points to determine the industrial chain link and corresponding industry where the high-carbon emission processes are located;

[0011] The high-carbon emission process is classified and the attribute parameters of the high-carbon emission process are obtained. An ontology precise model is established for the target product according to the attribute parameters. The original data of the target point is replaced with process data based on the ontology precise model, and an ontology-based product carbon footprint assessment result is output.

[0012] Optionally, the ontology-based product carbon footprint assessment method, wherein the steps of obtaining a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establishing an environmental input-output life cycle assessment model, and calculating the total carbon footprint of the target product based on the environmental input-output life cycle assessment model, specifically include:

[0013] According to the industry to which the target product belongs, obtain the public inter-industry economic input-output relationship table and establish an environmental input-output life cycle assessment model; X-DX=F; (1) E=RX=R(ID) -1 F; (2)

[0014] Among them, vector X represents the total output of each economic sector classified by the country; D refers to the direct consumption coefficient matrix, which represents the output of other economic sectors required for each economic sector to produce one unit of product; vector F represents the total economic output value of the target economic sector; vector E represents the total amount of greenhouse gas emissions of different types; matrix R represents the different types of greenhouse gas emissions caused by each unit of output of each economic sector; matrix I represents a unit matrix;

[0015] The environmental input-output life cycle assessment model calculates the total carbon footprint of the target product based on the different types of greenhouse gas emissions caused by each unit output of each economic sector, the unit matrix, the direct consumption coefficient matrix and the overall economic output value of the target economic sector.

[0016] Optionally, in the ontology-based product carbon footprint assessment method, the Taylor series expansion is performed as follows:

[0017] Where k represents a series of integers from zero to positive infinity, each integer represents a production stage in the entire industrial chain;

[0018] Through Taylor series expansion, carbon emissions from different stages and processes are extracted to form a carbon emission path.

[0019] Optionally, in the ontology-based product carbon footprint assessment method, the classification of the high-carbon emission processes is specifically as follows:

[0020] The high-carbon emission process is classified according to stage entity objects, process entity objects, material flow objects or relationship objects.

[0021] Optionally, in the ontology-based product carbon footprint assessment method, the stage entity objects include the raw material acquisition stage and the product production stage; the process entity objects include the production process and the transportation process; the material flow objects include material flow and product flow; and the relationship objects include upstream and downstream relationships.

[0022] Optionally, the ontology-based product carbon footprint assessment method further comprises:

[0023] For all process-related material flows involved in product carbon footprint assessment, ontology categories and hierarchies are established through term aggregation.

[0024] Optionally, in the ontology-based product carbon footprint assessment method, establishing ontology categories and hierarchies by term aggregation for all process-related material flows involved in the product carbon footprint assessment specifically includes:

[0025] Establish categories and category hierarchies for each object. During user use, the background can quickly retrieve related processes based on the precise ontology model of each process.

[0026] In addition, to achieve the above-mentioned purpose, the present invention further provides an ontology-based product carbon footprint assessment system, wherein the ontology-based product carbon footprint assessment system includes:

[0027] An evaluation model establishment and carbon footprint total amount determination module is used to determine the target product that requires ontology-based product carbon footprint assessment, determine the industry to which the target product belongs based on the target product and the industry basic database, obtain a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establish an environmental input-output life cycle assessment model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle assessment model;

[0028] A mathematical expansion and high-carbon emission process identification module is used to extract the carbon emission path of the target product along the entire industrial chain using Taylor series expansion, calculate the carbon emissions along each carbon emission path, identify target points on all carbon emission paths where carbon emissions exceed a preset threshold, and determine the high-carbon emission process based on the target points to determine the industrial chain link and corresponding industry in which the high-carbon emission process is located;

[0029] The ontology precise model establishment and data replacement module is used to classify the high-carbon emission process and obtain the attribute parameters of the high-carbon emission process, establish an ontology precise model for the target product based on the attribute parameters, replace the original data of the target point with process data based on the ontology precise model, and output the product carbon footprint assessment result based on the ontology.

[0030] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and an ontology-based product carbon footprint assessment program stored in the memory and executable on the processor, wherein the ontology-based product carbon footprint assessment program, when executed by the processor, implements the steps of the ontology-based product carbon footprint assessment method described above.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an ontology-based product carbon footprint assessment program, and when the ontology-based product carbon footprint assessment program is executed by a processor, it implements the steps of the ontology-based product carbon footprint assessment method described above. Beneficial effects

[0032] In the present invention, a target product that needs to undergo an ontology-based product carbon footprint assessment is determined, the industry to which the target product belongs is determined based on the target product and an industry basic database, a public inter-industry economic input-output relationship table is obtained based on the industry to which the target product belongs, an environmental input-output life cycle assessment model is established, and the total carbon footprint of the target product is calculated based on the environmental input-output life cycle assessment model; the carbon emission path of the target product on the entire industrial chain is extracted by using a Taylor series expansion method, the carbon emissions on each carbon emission path are calculated, the target points whose carbon emissions on all carbon emission paths exceed a preset threshold are identified, and the high-carbon emission process is determined based on the target point to determine the industrial chain link and the corresponding industry in which the high-carbon emission process is located; the high-carbon emission process is classified, and the attribute parameters of the high-carbon emission process are obtained, an ontology-based precise model is established for the target product based on the attribute parameters, the original data of the target point is replaced with the process data based on the ontology-based precise model, and the ontology-based product carbon footprint assessment result is output. The present invention provides a basic database that can associate industrial activity relationships, provides a standardized ontology-based product carbon footprint assessment model based on the industry average level, and embeds an inference algorithm to automatically complete the enterprise carbon footprint model, realizing the standardization of carbon emission calculations and the transparency of carbon emissions in all links of product production, helping enterprises to quickly assess the carbon footprint of their own products and benchmark the industry carbon footprint. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] FIG1 is a flow chart of a preferred embodiment of the ontology-based product carbon footprint assessment method of the present invention;

[0034] FIG2 is a schematic diagram of the process and principle of implementing the product carbon footprint assessment method based on ontology in a preferred embodiment of the present invention;

[0035] FIG3 is a schematic diagram of an example of carbon emission extraction results of a road construction life cycle in a preferred embodiment of the ontology-based product carbon footprint assessment method of the present invention;

[0036] FIG4 is a schematic diagram showing the principle of a preferred embodiment of the ontology-based product carbon footprint assessment system of the present invention;

[0037] FIG5 is a schematic diagram of an operating environment of a preferred embodiment of the terminal of the present invention. Best Mode for Carrying Out the Invention

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clear and distinct, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0039] The ontology-based product carbon footprint assessment method according to a preferred embodiment of the present invention is shown in FIG1 and FIG2 . The ontology-based product carbon footprint assessment method comprises the following steps:

[0040] Step S10: Determine the target product that needs to undergo ontology-based product carbon footprint assessment, determine the industry to which the target product belongs based on the target product and the industry basic database, obtain a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establish an environmental input-output life cycle assessment model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle assessment model.

[0041] Specifically, according to the industry to which the target product belongs, an environmental input-output life cycle assessment model can be established based on the inter-industry economic input-output relationship table published by the state (i.e., the public inter-industry economic input-output relationship table. Basically, each industry can find the corresponding category in the economic input-output table, and all the items in the table can be calculated): X-DX=F; (1) E=RX=R(ID) -1 F; (2)

[0042] Among them, vector X represents the total output of each economic sector classified by the national statistics; D refers to the direct consumption coefficient matrix, which represents the output of other economic sectors required for each economic sector to produce one unit (such as 10,000 yuan) of product (for example, how much electricity and transportation costs are required to produce 10,000 yuan of steel), and is published uniformly by the National Bureau of Statistics; vector F represents the overall economic output value of the target economic sector (for example, the steel production sector), that is, the overall economic output value of the sector in that year; vector E represents the total amount of greenhouse gas emissions of different types, including carbon dioxide, methane, nitrous oxide, etc.; matrix R represents the different types of greenhouse gas emissions caused by each unit of output of each economic sector; matrix I represents a unit matrix.

[0043] The environmental input-output life cycle assessment model calculates the total carbon footprint of the target product based on the different types of greenhouse gas emissions caused by each unit output of each economic sector, the unit matrix, the direct consumption coefficient matrix and the overall economic output value of the target economic sector.

[0044] Step S20: Using the Taylor series expansion method, extract the carbon emission path of the target product in the entire industrial chain, calculate the carbon emissions on each carbon emission path, identify the target points on all carbon emission paths where the carbon emissions exceed the preset threshold, and determine the high-carbon emission process based on the target points to determine the industrial chain link and corresponding industry where the high-carbon emission process is located.

[0045] Specifically, through mathematical expansion (i.e., Formula 3), the carbon emission path along the entire product chain is extracted. Each point on the carbon emission path is a default carbon emission value. On this basis, points with high carbon emissions on all paths are identified (i.e., target points exceeding a preset threshold, for example, the carbon emissions of this process are greater than 5% of the total carbon emissions. Different products may need to adjust this value according to actual conditions. For example, the direct carbon emissions of concrete production, the carbon emissions generated by the cement production process required for concrete production, the carbon emissions generated by electricity production, and even the production of electricity consumed by the cement production process will all be points with high emissions on the carbon emission path). Based on the relative position of the high-carbon emission process on the carbon emission path, the industrial chain link and industry in which it is located are determined, and in step S30, the process is further refined and modeled to obtain more accurate process data. For example, the previous stage of concrete production is cement production, water resource production, electricity production, etc., while the previous stage of cement production is limestone production, and the previous stage of electricity production is coal production, etc. The production relationships between these industries are already reflected in the input-output table. The total carbon footprint is calculated in step S10, while in step S20, the carbon emissions of different stages and processes are extracted through mathematical expansion to form the carbon emission path in example Figure 2, and a series of processes with the highest carbon emissions can be identified.

[0046] Among them, k represents a series of integers from zero to positive infinity, each integer represents a production stage in the entire industrial chain; k=0 represents the direct carbon emission process, such as the direct carbon emissions generated by the concrete production process; k=1 represents tracing back one stage, such as the carbon emissions generated by the cement, water and electricity production process required for concrete production; k=2 represents tracing back one stage, such as the carbon emissions generated by the coal production process required for electricity production; and so on...; through the Taylor series expansion method, the carbon emissions of different stages and processes are extracted to form a carbon emission path.

[0047] Let's use concrete production as an example to explain this using a tracing method. Figure 3 illustrates road construction, but the principle remains the same. The concrete production process generates direct carbon emissions, which are equal to R*(D^0)*F. For k = 0, this corresponds to the case where only concrete production occurs, with no other industries involved, resulting in a single value. Furthermore, concrete production consumes materials (cement, water) and energy (electricity), which also generate carbon emissions during the production process. Tracing back one stage, to k = 1, the carbon emissions from the cement, water, and electricity production processes are equal to R*(D^1)*F. This matrix operation decomposes the carbon emissions from industries related to concrete production. The cement, water, and electricity production processes themselves involve material and energy consumption, such as limestone, water, and electricity. Therefore, we need to trace back one more stage, to k = 2. The carbon emissions from this stage are equal to R*(D^2)*F. This matrix operation decomposes the carbon emissions from industries related to cement, water, and electricity production. For details, see example Figure 3. Each dot represents an industry, and connected dots represent directly related industries. Each industry is connected to many other industries, effectively expanding exponentially. However, the further you expand, the smaller the values ​​become. However, this method only requires those points with large values. Because these points are calculated using national data and represent industry averages, if you want to analyze specific products, you need to replace them with more accurate data from the company itself to improve calculation accuracy. This is why the mathematical expansion in step S20 and the precise substitution in step S30 are required. Generally, when expanding to k = 5 or k = 6, the values ​​are very small, so further expansion is unnecessary. Only the large values ​​need to be precisely substituted. The entire method is a hybrid carbon footprint assessment based on the environmental input-output model framework (combining the environmental input-output method with a process-based assessment method). Its advantage is that the environmental input-output assessment in step S10 encompasses all economic processes, ensuring the integrity of the calculation framework, while step S30 improves calculation accuracy through precise process-based substitution.

[0048] Step S30: classify the high-carbon emission process and obtain the attribute parameters of the high-carbon emission process, establish an ontology precise model for the target product according to the attribute parameters, replace the original data of the target point with process data based on the ontology precise model, and output the product carbon footprint assessment result based on the ontology.

[0049] Specifically, based on the identified high-carbon emission processes, they are classified according to stage entity objects (such as raw material acquisition stage, product production stage), process entity objects (such as production process, transportation process), material flow objects (such as material flow, product flow), and relationship objects (such as upstream and downstream relationships).

[0050] For high-carbon emission processes, mathematical expansion only reveals their specific layer—that is, how many layers back from concrete production (based on the value of k)—and the industry they belong to. Therefore, we first need to identify the product or process they represent in reality. For example, whether they belong to the material production stage or the product production stage, the production process (e.g., k = 1 for cement production, or k = 2 for electricity consumption for cement production) or the transportation process (e.g., cement transportation), as well as the material flows involved and their connections to other processes. Based on these attributes, we then model the actual production process of this product, determining, for example, the specific cement grade used, the specific amount used, whether carbon reduction measures were employed, and the carbon emissions generated. Finally, this specific model replaces the original, simple industry-average carbon emission data (this is a case of replacing one data point with another). If detailed data is available for the entire electricity production chain, then, when k = 2, we can package the electricity production required for concrete production and all values ​​back to it and replace them entirely with the detailed data (see the third large circle in the third column of the precise model replacement section in Figure 2).

[0051] For all processes involved in the carbon footprint assessment of products and their related material flows, ontology categories and hierarchies are established through term aggregation, such as establishing categories (classes) and category hierarchies (parent classes, child classes) for each object. During user use, the backend implements rapid retrieval of related processes based on the ontology models of each process. For example, if they are all process entity objects, you can add relationship attributes such as "need... (such as materials, energy consumption)"; if they are all relationship objects, you can add basic logical relationships such as "what relationship, who has a relationship with whom" and so on. Through the definition of basic logical relationships, on the one hand, it can automatically prompt which attributes are needed during use, and on the other hand, it is also conducive to the use of the nesting of these logical relationships, that is, the embedding of high-order reasoning logic, to perform some subsequent automatic deductions.

[0052] In addition, the present invention identifies the relationships between different categories and defines their attributes, such as the attributes of the relationship between processes, the attributes of the relationship between processes and material flows, etc. On this basis, the various types of processes, attributes, relationships and other objects mentioned above are enhanced with ontology semantics and embedded with high-order reasoning logic (ontology semantic enhancement is equivalent to explaining to the computer what different objects are and how they can be used in a language that the computer can understand, and then through high-order reasoning logic embedding, it can achieve automatic reasoning and completion). For example, if "A is a component of B" and "C is a component of B", then it can be deduced that "A and C together constitute B". When the material usage data of A is missing, it can be inferred and completed through the material usage data of B and C.

[0053] The present invention first calculates the total carbon footprint through step S10, and expands the key carbon emission paths in step S20 to find the points with high carbon emissions. Then, in step S30, more accurate data is used for the data of these points (these more accurate data need to be obtained based on process modeling, that is, the ontology precise model in step S30).

[0054] The present invention provides a basic database that can be associated with industrial activity relationships, provides a standardized carbon footprint assessment model based on the industry average level, and embeds an inference algorithm to realize the automatic completion of the enterprise carbon footprint model, helping enterprises to quickly evaluate the carbon footprint of their own products and benchmark the industry carbon footprint. The final product can be widely used in various industries such as energy, energy storage batteries, electric vehicles, and building materials. The present invention adopts a hybrid life cycle assessment method based on the environmental input-output model framework. First, based on the input-output table published by the state, the full life cycle carbon emissions generated by the average output value of the industry are calculated. Then, the Taylor series expansion is used to calculate the carbon emissions of different links in the entire industrial chain of the product, clarify which links have higher carbon emissions, and finally replace the links with high carbon emissions with accurate data. This method can achieve the standardization of carbon emission calculations, the transparency of carbon emissions in each link of product production, and clarify which processes have undergone accurate data replacement, which is conducive to the reuse of models and the comparison of different products. Users only need to select the industry to which the product belongs to obtain the average carbon footprint of the product industry and the carbon emission distribution of different links in the entire industrial chain. In the process of using process data for precise data replacement, ontology-based modeling is used to establish the interrelationships between different production activities in the industrial chain, and data deduction and automatic completion are realized based on the interrelationships between different production activities, which can greatly reduce the user's data collection and entry work.

[0055] Beneficial effects:

[0056] (1) Standardization: This helps the government monitor and compare the carbon emissions of products from different companies, and prevents companies from artificially eliminating high-energy consumption and high-carbon emission processes.

[0057] (2) Lowering the technical threshold and carbon footprint assessment costs: Product carbon footprint assessment often requires professionals with cross-disciplinary knowledge, requiring both industry expertise and carbon footprint assessment expertise, making carbon footprint assessment more difficult. This invention consolidates this knowledge into a centrally updated and continuously iterative database of specialized domain knowledge, and provides users with detailed instructions and usage steps, significantly lowering the technical threshold and carbon footprint assessment costs for enterprises.

[0058] (3) Reducing repetitive work: By using the industry-standardized carbon footprint assessment model established in steps S10 and S20, the large amount of process identification, data collection and modeling work required for traditional modeling can be significantly reduced; the refined model replacement established in step S30 can reduce a large amount of data collection work through model reuse and ontology-based intelligent inference.

[0059] Furthermore, as shown in FIG4 , based on the ontology-based product carbon footprint assessment method, the present invention also provides an ontology-based product carbon footprint assessment system, wherein the ontology-based product carbon footprint assessment system includes:

[0060] Evaluation model establishment and carbon footprint total amount determination module 51 is used to determine the target product that needs to undergo ontology-based product carbon footprint assessment, determine the industry to which the target product belongs based on the target product and the industry basic database, obtain a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establish an environmental input-output life cycle assessment model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle assessment model;

[0061] The mathematical expansion and high-carbon emission process determination module 52 is used to extract the carbon emission paths of the target product along the entire industrial chain using a Taylor series expansion method, calculate the carbon emissions along each carbon emission path, identify target points on all carbon emission paths where carbon emissions exceed a preset threshold, and determine the high-carbon emission process based on the target points to determine the industrial chain link and corresponding industry in which the high-carbon emission process is located;

[0062] The ontology precise model establishment and data replacement module 53 is used to classify the high-carbon emission process and obtain the attribute parameters of the high-carbon emission process, establish an ontology precise model for the target product according to the attribute parameters, replace the original data of the target point with process data based on the ontology precise model, and output the product carbon footprint assessment result based on the ontology.

[0063] Furthermore, as shown in FIG5 , based on the ontology-based product carbon footprint assessment method and system, the present invention also provides a terminal, which includes a processor 10, a memory 20, and a display 30. FIG5 only shows some components of the terminal, but it should be understood that implementation of all shown components is not required, and more or fewer components may be implemented instead.

[0064] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Furthermore, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 may also be used to temporarily store data that has been output or is to be output. In one embodiment, a product carbon footprint assessment program 40 based on the ontology is stored on the memory 20, and the product carbon footprint assessment program 40 based on the ontology can be executed by the processor 10, thereby realizing the product carbon footprint assessment method based on the ontology in this application.

[0065] In some embodiments, the processor 10 may be a central processing unit (CPU), a microprocessor, or other data processing chip, configured to execute program codes or process data stored in the memory 20, such as executing the ontology-based product carbon footprint assessment method.

[0066] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0067] In one embodiment, when the processor 10 executes the ontology-based product carbon footprint assessment program 40 in the memory 20 , the steps of the ontology-based product carbon footprint assessment method described above are implemented.

[0068] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores an ontology-based product carbon footprint assessment program, and when the ontology-based product carbon footprint assessment program is executed by a processor, the steps of the ontology-based product carbon footprint assessment method described above are implemented.

[0069] In summary, the present invention provides an ontology-based product carbon footprint assessment method and related equipment, the method comprising: determining a target product that requires ontology-based product carbon footprint assessment, determining the industry to which the target product belongs based on the target product and an industry basic database, obtaining a public inter-industry economic input-output relationship table based on the industry to which the target product belongs, establishing an environmental input-output life cycle assessment model, and calculating the total carbon footprint of the target product based on the environmental input-output life cycle assessment model; extracting the carbon emission path of the target product on the entire industrial chain by using a Taylor series expansion method, calculating the carbon emissions on each carbon emission path, identifying target points on all carbon emission paths whose carbon emissions exceed a preset threshold, and determining high-carbon emission processes based on the target points to determine the industrial chain link and corresponding industry in which the high-carbon emission processes are located; classifying the high-carbon emission processes and obtaining attribute parameters of the high-carbon emission processes, establishing an ontology-based precise model for the target product based on the attribute parameters, replacing the original data of the target points with process data based on the ontology-based precise model, and outputting the ontology-based product carbon footprint assessment results. The present invention provides a basic database that can associate industrial activity relationships, provides a standardized ontology-based product carbon footprint assessment model based on the industry average level, and embeds an inference algorithm to automatically complete the enterprise carbon footprint model, realizing the standardization of carbon emission calculations and the transparency of carbon emissions in all links of product production, helping enterprises to quickly assess the carbon footprint of their own products and benchmark the industry carbon footprint.

[0070] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or terminal comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or terminal comprising the element.

[0071] Of course, those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing related hardware (such as a processor, controller, etc.) through a computer program. The program can be stored in a computer-readable storage medium that can be read by a computer. When the program is executed, it can include the processes in the above-described method embodiments. The computer-readable storage medium can be a memory, a magnetic disk, an optical disk, etc.

[0072] It should be understood that the application of the present invention is not limited to the above examples. For those skilled in the art, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. An ontology-based product carbon footprint assessment method, characterized in that, the ontology-based product carbon footprint assessment method includes: Determine the target product for which an ontology-based product carbon footprint assessment is to be conducted, determine the industry to which the target product belongs according to the target product and the industry basic database, obtain the publicly available inter-industry economic input-output relationship table according to the industry to which the target product belongs, establish an environmental input-output life cycle assessment model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle assessment model; Extract the carbon emission paths on the entire industrial chain of the target product by means of Taylor series expansion, calculate the carbon emissions on each carbon emission path, identify the target points where the carbon emissions on all carbon emission paths exceed the preset threshold, and determine the high-carbon emission processes according to the target points, so as to determine the industrial chain links and corresponding industries where the high-carbon emission processes are located; Classify the high-carbon emission processes, obtain the attribute parameters of the high-carbon emission processes, establish an ontology precise model for the target product according to the attribute parameters, replace the original data of the target points with process data based on the ontology precise model, and output the ontology-based product carbon footprint assessment result.

2. The ontology-based product carbon footprint assessment method according to claim 1, characterized in that, the step of obtaining the publicly available inter-industry economic input-output relationship table according to the industry to which the target product belongs, establishing an environmental input-output life cycle assessment model, and calculating the total carbon footprint of the target product based on the environmental input-output life cycle assessment model specifically includes: Obtain the publicly available inter-industry economic input-output relationship table according to the industry to which the target product belongs, and establish an environmental input-output life cycle assessment model; X - DX = F; (1) E = RX = R(I - D) -1 F; (2) Wherein, the vector X represents the total output of each economic sector classified and statistically by the country; D refers to the direct consumption coefficient matrix, which represents the output of other economic sectors consumed by each economic sector for producing one unit of product; the vector F represents the total economic output value of the target economic sector; the vector E represents the total amount of different types of greenhouse gas emissions; the matrix R represents the amount of different types of greenhouse gas emissions caused by each unit output of each economic sector; the matrix I represents a unit matrix; The environmental input-output life cycle assessment model calculates the total carbon footprint of the target product based on the amount of different types of greenhouse gas emissions caused by each unit output of each economic sector, the unit matrix, the direct consumption coefficient matrix, and the total economic output value of the target economic sector.

3. The ontology-based product carbon footprint assessment method according to claim 2, characterized in that, The way of the Taylor series expansion is as follows: where k represents a series of integers from zero to positive infinity, and each integer represents a production stage on the entire industrial chain; Extract the carbon emissions of different processes at different stages by means of Taylor series expansion to form carbon emission paths.

4. The ontology-based product carbon footprint assessment method according to claim 1, characterized in that, the classification of the high-carbon emission processes specifically is: Classify the high-carbon emission process according to stage entity objects, process entity objects, material flow objects or relationship objects.

5. The ontology-based product carbon footprint assessment method according to claim 4, wherein, the stage entity objects include the raw material acquisition stage and the product production stage; the process entity objects include the production process and the transportation process; the material flow objects include material flow and product flow; the relationship objects include upstream and downstream relationships.

6. The ontology-based product carbon footprint assessment method according to claim 5, wherein, the ontology-based product carbon footprint assessment method further includes: establishing ontology categories and hierarchies for the material flows related to all processes involved in product carbon footprint assessment through term aggregation.

7. The ontology-based product carbon footprint assessment method according to claim 6, wherein, the establishment of ontology categories and hierarchies for the material flows related to all processes involved in product carbon footprint assessment through term aggregation specifically includes: establishing the categories and category hierarchies of each object, and during the user's use process, the background realizes the rapid retrieval of associated processes based on the precise ontology models of each process.

8. An ontology-based product carbon footprint assessment system, wherein, the ontology-based product carbon footprint assessment system includes: An evaluation model establishment and total carbon footprint determination module, which is used to determine the target product for which ontology-based product carbon footprint assessment is required, determine the industry to which the target product belongs according to the target product and the industry basic database, obtain the publicly available inter-industry economic input-output relationship table according to the industry to which the target product belongs, establish an environmental input-output life cycle evaluation model, and calculate the total carbon footprint of the target product based on the environmental input-output life cycle evaluation model; A mathematical expansion and high-carbon emission process determination module, which is used to extract the carbon emission paths on the entire industrial chain of the target product by means of Taylor series expansion, calculate the carbon emissions on each carbon emission path, identify the target points where the carbon emissions on all carbon emission paths exceed a preset threshold, and determine the high-carbon emission process according to the target points, so as to determine the industrial chain links and corresponding industries where the high-carbon emission process is located; An ontology precise model establishment and data replacement module, which is used to classify the high-carbon emission process, obtain the attribute parameters of the high-carbon emission process, establish an ontology precise model for the target product according to the attribute parameters, replace the original data of the target point with process data based on the ontology precise model, and output the ontology-based product carbon footprint assessment result.

9. A terminal, wherein, the terminal includes: a memory, a processor, and an ontology-based product carbon footprint assessment program stored on the memory and executable on the processor. When the ontology-based product carbon footprint assessment program is executed by the processor, the steps of the ontology-based product carbon footprint assessment method according to any one of claims 1-7 are implemented.

10. A computer-readable storage medium, wherein, The computer-readable storage medium stores an ontology-based product carbon footprint assessment program. When the ontology-based product carbon footprint assessment program is executed by a processor, it implements the steps of the ontology-based product carbon footprint assessment method according to any one of claims 1-7.

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