A method and system for tracing and authenticating carbon footprint of green alcohol fuel

Abstract

The present invention relates to a method and system for tracing and authenticating the carbon footprint of green alcohol fuel, and belongs to the field of tracing and authenticating technology. The method includes: obtaining fuel raw materials, collecting raw material equipment energy consumption, raw material conversion energy consumption, storage equipment energy consumption, and filling equipment energy consumption; obtaining the complex carbon emissions of the fuel throughout its life cycle through a carbon emission model based on the collected raw material equipment energy consumption, raw material conversion energy consumption, storage equipment energy consumption, and filling equipment energy consumption; storing the fuel raw materials and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain an authentication blockchain; and obtaining the fuel authentication result through an authentication model based on the authentication blockchain. The traceability authentication based on the carbon footprint of green alcohol fuel is realized, and the security and reliability of the traceability authentication are guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of traceability authentication, and in particular relates to a method and system for traceability authentication based on carbon footprint of green alcohol fuel. Background Art

[0002] With the International Maritime Organization's adoption of the "2023 Ship Greenhouse Gas Emissions Reduction Strategy" and the release of a series of international policies such as the EU's inclusion of the shipping industry in the carbon emissions trading system, green methanol, as a clean energy produced from biomass, industrial waste gas and other renewable resources, has become the core choice for the shipping industry to decarbonize. However, with the promotion of green alcohol fuel, how to prove that ship fuel is green alcohol fuel has become a pain point in the industry. Accurately tracing and certifying the carbon footprint of ship fuel throughout its life cycle has become a good solution. Carbon footprint traceability is a process of tracking and calculating carbon emission data during energy production, transportation, and use to comprehensively assess its environmental impact. It can not only certify that ship fuel is green alcohol fuel, but also provide transparent and reliable carbon emission reduction information to enterprises, governments and consumers, and contribute to the green and low-carbon economy.

[0003] At present, the traceability system is applied in the food, medicine, construction and other industries, including China Traceability Cloud Public Service Platform, Food Safety Anti-counterfeiting Traceability System Platform, China Food Safety Traceability Platform, China Bird's Nest Traceability Management Service Platform, and traceability system based on RFID technology and electronic tag anti-counterfeiting technology. However, there is still a lack of a unified traceability certification system in the shipping industry. At the same time, most of the existing traceability systems use centralized databases to store privacy data, which is prone to single point failures and information leakage. Blockchain technology can ensure that the data recorded on the chain cannot be tampered with and is traceable throughout the process through encryption algorithms and consensus technologies, providing guarantees for carbon footprint traceability certification. Therefore, how to effectively combine blockchain with green alcohol fuel carbon footprint traceability certification can ensure the authenticity, timeliness and reliability of carbon footprint traceability certification while ensuring data security. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention provides a method and system for carbon footprint traceability authentication of green alcohol fuel.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A carbon footprint traceability authentication method based on green alcohol fuel, comprising:

[0007] Energy consumption of obtaining fuel raw materials, collecting raw material equipment, converting raw materials, storing equipment, and refueling equipment;

[0008] The complex carbon emissions of the fuel throughout its life cycle are obtained through a carbon emission model according to the energy consumption of the raw material collection equipment, the energy consumption of the raw material conversion, the energy consumption of the storage equipment, and the energy consumption of the filling equipment;

[0009] Storing the fuel raw materials and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain;

[0010] The fuel authentication result is obtained through the authentication model according to the authentication blockchain.

[0011] Preferably, the complex carbon emissions of the fuel throughout its life cycle are obtained through a carbon emission model based on the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption, including:

[0012] According to the energy consumption of the raw material collection equipment, the energy consumption of the raw material conversion, the energy consumption of the storage equipment, and the energy consumption of the filling equipment, the carbon emission quantification data of the fuel throughout its life cycle is obtained through a carbon emission quantification model;

[0013] Preset process causal relationships, and obtain a shipping fuel carbon emission knowledge graph through ontology knowledge modeling based on the process causal relationships and the quantitative data of carbon emission of the fuel throughout its life cycle;

[0014] The complex carbon emissions of the fuel throughout its life cycle are obtained through a similarity model based on the shipping fuel carbon emission knowledge graph and the quantitative data on the carbon emissions of the fuel throughout its life cycle.

[0015] Preferably, the carbon emission quantitative data of the fuel life cycle is obtained through a carbon emission quantification model based on the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption, including:

[0016] The quantitative data of carbon emissions throughout the fuel life cycle includes carbon emissions at collection points, carbon emissions at processing points, carbon emissions at warehouses, and carbon emissions at filling stations;

[0017] The carbon emission at the collection point is obtained by calculating the carbon emission at the collection point according to the energy consumption of the raw material collection equipment;

[0018] Obtain the carbon emission of waste by-products and the fuel consumption, and calculate the carbon emission of the processing point through processing carbon emission according to the raw material conversion energy consumption, the carbon emission of waste by-products and the fuel consumption;

[0019] The carbon emissions of the warehouse are calculated by using the carbon emissions of the storage equipment according to the energy consumption of the storage equipment;

[0020] The carbon emissions of the filling station are calculated based on the energy consumption of the filling equipment through the carbon emissions of the filling equipment.

[0021] Preferably, obtaining the complex carbon emissions of the fuel throughout its life cycle through a similarity model based on the shipping fuel carbon emissions knowledge graph and the fuel life cycle carbon emissions quantification data includes:

[0022] Presetting an initial similar shipping fuel carbon emission knowledge graph, and obtaining a similar shipping fuel carbon emission knowledge graph by calculating the cosine similarity based on the initial similar shipping fuel carbon emission knowledge graph and the shipping fuel carbon emission knowledge graph;

[0023] According to the shipping fuel carbon emission knowledge graph and the similar shipping fuel carbon emission knowledge graph, an entity node embedding vector and a similar entity node embedding vector are obtained by conversion through the TransE method;

[0024] Obtaining a matching value by multi-view cosine matching calculation according to the entity node embedding vector and the similar entity node embedding vector;

[0025] A Top-k similar shipping fuel carbon emission knowledge graph is obtained by sorting according to the matching values;

[0026] Obtaining a graph matching value by adding and calculating the matching values;

[0027] A similarity score is obtained by calculating the cosine similarity based on the Top-k similar shipping fuel carbon emission knowledge graph, the shipping fuel carbon emission knowledge graph, and the graph matching value;

[0028] The complex carbon emissions of the fuel throughout its life cycle are calculated by using the carbon emission value based on the similarity score and the quantitative data on the carbon emissions of the fuel throughout its life cycle.

[0029] Preferably, the step of storing the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain comprises:

[0030] Obtaining encrypted authentication data through an elliptic curve encryption algorithm based on the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle;

[0031] The encrypted authentication data is stored through IPFS, and a unique identifier is added to obtain the authentication blockchain.

[0032] Preferably, obtaining the fuel authentication result through the authentication model according to the authentication blockchain includes:

[0033] Obtaining a fuel ID and a fuel attribute value, and triggering a smart contract by matching the fuel ID and the unique identifier;

[0034] Obtaining an attribute hash value by using a hash function to calculate the attribute value of the fuel;

[0035] Obtain a traceability information file by accessing IPFS and matching the fuel attribute value;

[0036] Obtaining a corrected hash value by calculating a hash function according to the traceability information file;

[0037] The fuel authentication result is obtained by comparing and judging the attribute hash value and the correction hash value.

[0038] Preferably, the comparison judgment includes judging whether the attribute hash value and the correction hash value are the same, if yes, the fuel authentication result is that the fuel is green alcohol fuel; if no, the fuel authentication result is that the fuel is non-green alcohol fuel.

[0039] A carbon footprint traceability authentication system based on green alcohol fuel includes a data acquisition module, a carbon emission calculation module, a blockchain storage module, and a traceability authentication module, including:

[0040] The data acquisition module is used to acquire fuel raw materials, collect raw material equipment energy consumption, raw material conversion energy consumption, storage equipment energy consumption, and filling equipment energy consumption;

[0041] The carbon emission calculation module is used to obtain the complex carbon emissions of the fuel throughout its life cycle through a carbon emission model according to the energy consumption of the raw material collection equipment, the energy consumption of the raw material conversion, the energy consumption of the storage equipment, and the energy consumption of the filling equipment;

[0042] The blockchain storage module is used to store the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle into a blockchain to obtain a certified blockchain;

[0043] The traceability authentication module is used to obtain the fuel authentication result through the authentication model according to the authentication blockchain.

[0044] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned carbon footprint traceability authentication method based on green alcohol fuel when executing the program.

[0045] A storage medium containing computer executable instructions, which are used to execute the above-mentioned green alcohol fuel carbon footprint traceability authentication method when executed by a computer processor.

[0046] The beneficial effects of the present invention are:

[0047] (1) Through carbon emission models and full life cycle analysis, quantitative data on carbon emissions throughout the fuel life cycle are obtained. At the same time, ontology knowledge modeling is used to convert the quantitative data on carbon emissions throughout the fuel life cycle into a carbon emission knowledge graph. Through similarity models, data relationships are deeply mined, which can calculate carbon emissions for complex fuel supply chains and improve the accuracy of carbon emission calculations.

[0048] (2) Through blockchain technology, with the help of elliptic curve encryption algorithm and IPFS distributed storage system, fuel raw materials and carbon emission data are stored in the authentication blockchain to ensure the security, immutability and traceability of the data. Through smart contracts, authentication is quickly matched to improve the credibility of the authentication process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0050] Figure 1 The present invention is a flow chart of a method for tracing and authenticating the carbon footprint of green alcohol fuel. DETAILED DESCRIPTION

[0051] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0052] See also Figure 1 , a carbon footprint traceability certification method based on green alcohol fuel, including:

[0053] S1: Energy consumption of obtaining fuel raw materials, collecting raw material equipment, raw material conversion, storage equipment, and filling equipment;

[0054] S2: Obtaining the complex carbon emissions of the fuel throughout its life cycle through a carbon emission model according to the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption;

[0055] S3: storing the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain;

[0056] S4: Obtain the fuel authentication result through the authentication model according to the authentication blockchain.

[0057] In step S2, the carbon emission model includes:

[0058] S201: Obtaining carbon emission quantification data of the fuel throughout its life cycle through a carbon emission quantification model according to the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption;

[0059] S202: Preset process causal relationships, and obtain a shipping fuel carbon emission knowledge graph through ontology knowledge modeling based on the process causal relationships and the quantitative data of carbon emission throughout the fuel life cycle;

[0060] S203: Obtaining the complex carbon emissions of the fuel throughout its life cycle through a similarity model according to the shipping fuel carbon emission knowledge graph and the quantitative data of carbon emissions of the fuel throughout its life cycle.

[0061] Specifically, the carbon emission quantification model includes:

[0062] S201-1: The quantitative data of carbon emissions throughout the fuel life cycle includes carbon emissions at the collection point, carbon emissions at the processing point, carbon emissions at the warehouse, and carbon emissions at the filling station;

[0063] S201-2: Calculating the carbon emissions at the collection point based on the energy consumption of the raw material collection equipment;

[0064] The calculation expression of carbon emission at the collection point is:

[0065] ,

[0066] in, E 1 Carbon emissions for the collection point, P is the device power, H Indicates the equipment running time. EF ene is the carbon emission factor;

[0067] S201-3: Obtain carbon emissions from waste byproducts and fuel consumption, and calculate the carbon emissions of the processing point through processing carbon emissions according to the raw material conversion energy consumption, the carbon emissions from waste byproducts and the fuel consumption;

[0068] The processing carbon emission calculation expression is:

[0069] ,

[0070] in, E 2 is the carbon emission of the processing point, E elec Represents carbon emissions from electricity consumption, E fuel represents carbon emissions from fuel consumption, E out represents the carbon emission of waste by-products of the treatment, P elec Indicates the energy consumption of raw material conversion, in kw / h, T For the duration of electricity use, EF elec represents the electricity emission factor, F fuel is the fuel consumption, EF fuel is the fuel emission factor;

[0071] S201-4: Calculating the carbon emissions of the warehouse based on the energy consumption of the storage equipment through the carbon emissions of the storage equipment;

[0072] The carbon emission calculation expression of the storage equipment is:

[0073] ,

[0074] in, E 3 is the carbon emission of the warehouse, P equ is the energy consumption of the storage device, T is the warehouse running time, EF hfuel is the carbon emission factor;

[0075] S201-5: Calculating the carbon emissions of the filling station based on the energy consumption of the filling equipment and the carbon emissions of the filling equipment;

[0076] The carbon emission calculation expression of the filling equipment is:

[0077] ,

[0078] in, E 4 is the carbon emission of the filling station, P fill is the energy consumption of the filling equipment, T is the operation time of the filling station, EF felec is the carbon emission factor.

[0079] Specifically, the process causal relationship represents a direct causal relationship between process knowledge attributes and process nodes.

[0080] In this embodiment, taking the processing process as an example, the ontology knowledge modeling includes taking attributes as nodes of the knowledge graph, causal relationships as edges, and the processing point carbon emissions as scalars to construct a processing point carbon emission knowledge graph; the attributes include the fuel raw materials, processing equipment, processing process flow, processing steps, and process resources; the causal relationship includes the subordinate characteristic relationship of carbon emissions, the time relationship of carbon emissions, and the sequential relationship of the process flow; the shipping fuel carbon emission knowledge graph includes the collection point carbon emission knowledge graph, the processing point carbon emission knowledge graph, the warehouse carbon emission knowledge graph, and the filling station carbon emission knowledge graph.

[0081] Specifically, the similarity model includes:

[0082] S203-1: Preset an initial similar shipping fuel carbon emission knowledge graph, and obtain a similar shipping fuel carbon emission knowledge graph by calculating the cosine similarity based on the initial similar shipping fuel carbon emission knowledge graph and the shipping fuel carbon emission knowledge graph;

[0083] S203-2: converting the shipping fuel carbon emission knowledge graph and the similar shipping fuel carbon emission knowledge graph by using the TransE method to obtain an entity node embedding vector and a similar entity node embedding vector;

[0084] S203-3: Obtaining a matching value by multi-view cosine matching calculation according to the entity node embedding vector and the similar entity node embedding vector;

[0085] The multi-view cosine matching calculation expression is:

[0086] ,

[0087] in, is the matching value, f m is the multi-view cosine matching function, represents the entity node embedding vector, represents the attention vector value of similar entity nodes on the knowledge graph of similar shipping fuel carbon emissions, is the learnable weight vector, is the number of similar entity nodes, represents the similarity score between an entity node and similar entity nodes, j represents the jth similar entity node, i represents the i-th entity node, Embedding vectors for the similar entity nodes, cos Calculate for cosine;

[0088] S203-4: Obtaining a Top-k similar shipping fuel carbon emission knowledge graph by sorting according to the matching values;

[0089] S203-5: Obtaining a graph matching value by adding and calculating the matching values;

[0090] S203-6: Calculating a similarity score by using cosine similarity based on the Top-k similar shipping fuel carbon emission knowledge graph, the shipping fuel carbon emission knowledge graph, and the graph matching value;

[0091] The cosine similarity calculation expression is:

[0092] ,

[0093] in, score(G 0,G 1 ) is the similarity score, G 0 For the shipping fuel carbon emission knowledge graph, G 1 is the Top-k similar shipping fuel carbon emission knowledge graph, is the shipping fuel carbon emission knowledge graph matching value, is the Top-k similar shipping fuel carbon emission knowledge graph matching value, , represents norm calculation;

[0094] S203-7: Calculate the complex carbon emissions of the fuel throughout its life cycle through the carbon emission value according to the similarity score and the quantitative data of the carbon emissions of the fuel throughout its life cycle;

[0095] The carbon emission value calculation expression is:

[0096] ,

[0097] in, Indicates the complex carbon emissions of the fuel throughout its life cycle, n is the number of Top-k similar shipping fuel carbon emission knowledge graph nodes, t represents the tth process, k represents the kth Top-k similar shipping fuel carbon emission knowledge graph node, is the similarity score, i represents the i-th processing process, j represents the jth processing step, Represents the quantitative data of carbon emissions over the entire life cycle of the fuel, m k Represents weight.

[0098] In step S3, storing the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain includes:

[0099] S301: obtaining encrypted authentication data through an elliptic curve encryption algorithm according to the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle;

[0100] S302: Store the encrypted authentication data through IPFS and add a unique identifier to obtain the authentication blockchain.

[0101] In step S4, the authentication model includes:

[0102] S401: Obtain a fuel ID and a fuel attribute value, and trigger a smart contract by matching the fuel ID and the unique identifier;

[0103] S402: Obtaining an attribute hash value by using a hash function calculation according to the fuel attribute value;

[0104] S403: Obtain a traceability information file by accessing IPFS and matching the fuel attribute value;

[0105] S404: Obtaining a corrected hash value by using a hash function calculation according to the traceability information file;

[0106] S405: Obtain the fuel authentication result by comparing and judging the attribute hash value and the correction hash value;

[0107] The comparison judgment includes judging whether the attribute hash value and the correction hash value are the same. If yes, the fuel authentication result is that the fuel is green alcohol fuel; if no, the fuel authentication result is that the fuel is non-green alcohol fuel.

[0108] Specifically, the authentication model is carried out under a smart contract, which automatically executes preset rules to ensure the transparency and non-tamperability of the authentication process.

[0109] In this embodiment, the authentication blockchain includes a data layer, a network layer, a consensus layer, a contract layer, and an application layer; the data layer includes block transaction information, hash function, Merkle tree, timestamp, difficulty coefficient, and asymmetric encryption algorithm; the network layer includes information transmission rules, broadcast mechanism, and message verification mechanism between nodes in the chain; the consensus layer includes a consensus mechanism; the contract layer includes smart contracts; and the application layer performs traceability authentication.

[0110] In this embodiment, the entire traceability system includes collection points, processing plants, warehouses, filling stations, ships, information and digital platforms, and blockchain platforms; the green alcohol fuel processing process includes the collection process, processing process, storage process, and filling process.

[0111] A carbon footprint traceability authentication system based on green alcohol fuel includes a data acquisition module, a carbon emission calculation module, a blockchain storage module, and a traceability authentication module, including:

[0112] The data acquisition module is used to acquire fuel raw materials, collect raw material equipment energy consumption, raw material conversion energy consumption, storage equipment energy consumption, and filling equipment energy consumption;

[0113] The carbon emission calculation module is used to obtain the complex carbon emissions of the fuel throughout its life cycle through a carbon emission model according to the energy consumption of the raw material collection equipment, the energy consumption of the raw material conversion, the energy consumption of the storage equipment, and the energy consumption of the filling equipment;

[0114] The blockchain storage module is used to store the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle into a blockchain to obtain a certified blockchain;

[0115] The traceability authentication module is used to obtain the fuel authentication result through the authentication model according to the authentication blockchain.

[0116] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0117] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0118] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0119] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A carbon footprint traceability authentication method based on green alcohol fuel, characterized in that: The following steps are involved: Energy consumption of obtaining fuel raw materials, collecting raw material equipment, converting raw materials, storing equipment, and refueling equipment; According to the energy consumption of the raw material collection equipment, the energy consumption of the raw material conversion, the energy consumption of the storage equipment, and the energy consumption of the filling equipment, the carbon emission quantification data of the fuel throughout its life cycle is obtained through a carbon emission quantification model; Preset process causal relationships, and obtain a shipping fuel carbon emission knowledge graph through ontology knowledge modeling based on the process causal relationships and the quantitative data of carbon emission of the fuel throughout its life cycle; Presetting an initial similar shipping fuel carbon emission knowledge graph, and obtaining a similar shipping fuel carbon emission knowledge graph by calculating the cosine similarity based on the initial similar shipping fuel carbon emission knowledge graph and the shipping fuel carbon emission knowledge graph; According to the shipping fuel carbon emission knowledge graph and the similar shipping fuel carbon emission knowledge graph, an entity node embedding vector and a similar entity node embedding vector are obtained by conversion through the TransE method; Obtaining a matching value by multi-view cosine matching calculation according to the entity node embedding vector and the similar entity node embedding vector; A Top-k similar shipping fuel carbon emission knowledge graph is obtained by sorting according to the matching values; Obtaining a graph matching value by adding and calculating the matching values; A similarity score is obtained by calculating the cosine similarity based on the Top-k similar shipping fuel carbon emission knowledge graph, the shipping fuel carbon emission knowledge graph, and the graph matching value; The complex carbon emissions of the fuel throughout its life cycle are obtained by calculating the carbon emission value according to the similarity score and the quantitative data of the carbon emissions of the fuel throughout its life cycle; Storing the fuel raw materials and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain; The fuel authentication result is obtained through the authentication model according to the authentication blockchain.

2. The carbon footprint traceability authentication method based on green alcohol fuel according to claim 1 is characterized in that: The carbon emission quantitative data of the fuel life cycle obtained by using the carbon emission quantitative model according to the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption includes: The quantitative data of carbon emissions throughout the fuel life cycle includes carbon emissions at collection points, carbon emissions at processing points, carbon emissions at warehouses, and carbon emissions at filling stations; The carbon emission at the collection point is obtained by calculating the carbon emission at the collection point according to the energy consumption of the raw material collection equipment; Obtain the carbon emission of waste by-products and the fuel consumption, and calculate the carbon emission of the processing point through processing carbon emission according to the raw material conversion energy consumption, the carbon emission of waste by-products and the fuel consumption; The carbon emissions of the warehouse are calculated by using the carbon emissions of the storage equipment according to the energy consumption of the storage equipment; The carbon emissions of the filling station are calculated based on the energy consumption of the filling equipment through the carbon emissions of the filling equipment.

3. The carbon footprint traceability authentication method based on green alcohol fuel according to claim 1 is characterized in that: The method of storing the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle in a blockchain to obtain a certified blockchain includes: Obtaining encrypted authentication data through an elliptic curve encryption algorithm based on the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle; The encrypted authentication data is stored through IPFS, and a unique identifier is added to obtain the authentication blockchain.

4. The carbon footprint traceability authentication method based on green alcohol fuel according to claim 3 is characterized in that: Obtaining the fuel authentication result through the authentication model according to the authentication blockchain includes: Obtaining a fuel ID and a fuel attribute value, and triggering a smart contract by matching the fuel ID and the unique identifier; Obtaining an attribute hash value by using a hash function to calculate the attribute value of the fuel; Obtain a traceability information file by accessing IPFS and matching the fuel attribute value; Obtaining a corrected hash value by calculating a hash function according to the traceability information file; The fuel authentication result is obtained by comparing and judging the attribute hash value and the correction hash value.

5. The carbon footprint traceability authentication method based on green alcohol fuel according to claim 4 is characterized in that: The comparison judgment includes judging whether the attribute hash value and the correction hash value are the same. If yes, the fuel authentication result is that the fuel is green alcohol fuel; if no, the fuel authentication result is that the fuel is non-green alcohol fuel.

6. A carbon footprint traceability authentication system based on green alcohol fuel, including a data acquisition module, a carbon emission calculation module, a blockchain storage module, and a traceability authentication module, characterized in that: include: The data acquisition module is used to acquire fuel raw materials, collect raw material equipment energy consumption, raw material conversion energy consumption, storage equipment energy consumption, and filling equipment energy consumption; The carbon emission calculation module is used to obtain the carbon emission quantitative data of the fuel's entire life cycle through a carbon emission quantification model according to the energy consumption of the raw material collection equipment, the raw material conversion energy consumption, the storage equipment energy consumption, and the filling equipment energy consumption; Preset process causal relationships, and obtain a shipping fuel carbon emission knowledge graph through ontology knowledge modeling based on the process causal relationships and the quantitative data of carbon emission of the fuel throughout its life cycle; Presetting an initial similar shipping fuel carbon emission knowledge graph, and obtaining a similar shipping fuel carbon emission knowledge graph by calculating the cosine similarity based on the initial similar shipping fuel carbon emission knowledge graph and the shipping fuel carbon emission knowledge graph; According to the shipping fuel carbon emission knowledge graph and the similar shipping fuel carbon emission knowledge graph, an entity node embedding vector and a similar entity node embedding vector are obtained by conversion through the TransE method; Obtaining a matching value by multi-view cosine matching calculation according to the entity node embedding vector and the similar entity node embedding vector; A Top-k similar shipping fuel carbon emission knowledge graph is obtained by sorting according to the matching values; Obtaining a graph matching value by adding and calculating the matching values; A similarity score is obtained by calculating the cosine similarity based on the Top-k similar shipping fuel carbon emission knowledge graph, the shipping fuel carbon emission knowledge graph, and the graph matching value; The complex carbon emissions of the fuel throughout its life cycle are obtained by calculating the carbon emission value according to the similarity score and the quantitative data of the carbon emissions of the fuel throughout its life cycle; The blockchain storage module is used to store the fuel raw material and the complex carbon emissions of the fuel throughout its life cycle into a blockchain to obtain a certified blockchain; The traceability authentication module is used to obtain the fuel authentication result through the authentication model according to the authentication blockchain.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the carbon footprint traceability authentication method based on green alcohol fuel as described in any one of claims 1-5 is implemented.

8. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the carbon footprint traceability authentication method based on green alcohol fuel as described in any one of claims 1-5 when executed by a computer processor.

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