Carbon footprint traceability and verification method based on distributed account book

Abstract

The invention discloses a carbon footprint traceability and verification method based on a distributed account book. The method comprises the following steps: firstly, generating a first verification voucher for original operation data at a source by using trusted hardware; then, the prover server runs a zero-knowledge proving circuit, and generates a calculation validity proving under the condition that the original data serving as private input is not exposed; and finally, after the intelligent contract verifies that the voucher and the proof are valid, casting digital assets bound with the greenhouse gas emission reduction on a distributed account book. According to the method, the contradiction between transparency and data privacy in carbon accounting is solved, and credible, efficient and privacy-protecting carbon footprint traceability is realized.

Description

Technical Field

[0001] The present application relates to the fields of data processing and information security, and in particular to a carbon footprint traceability and verification method based on a distributed ledger. Background Art

[0002] Against the backdrop of global climate change, new energy industries, represented by wind and solar power, are experiencing rapid growth. However, this expansion faces a core challenge: how to quantify and verify their true environmental benefits in a credible, transparent, and efficient manner.

[0003] On the one hand, market regulators, investors, and environmental organizations urgently need verifiable and transparent carbon reduction declarations to effectively combat "greenwashing" and ensure the credibility of the carbon credit market and the true value of green financial products. On the other hand, renewable energy power generation companies generate a large amount of highly commercially sensitive data during their daily operations, such as real-time power generation, equipment operating efficiency, operation and maintenance plans, and terms and conditions in power purchase agreements (PPAs). This data is integral to a company's core competitiveness, and its disclosure poses significant commercial risks.

[0004] The currently used carbon asset registration and accounting systems are mostly centralized systems, and their inherent limitations are becoming increasingly prominent. The main flaws of the existing systems include: (1) High cost and delay Existing systems often rely on periodic manual audits to verify data, resulting in delayed data updates and high accounting costs; (2) Lack of real-time traceability Traditional auditing methods make it difficult to trace and verify the carbon emission reduction process in real time; (3) Data security risks Centralized databases have the risk of single point failure and data tampering, which, if it occurs, will seriously affect the credibility of the system; (4) Market fragmentation and double counting Inconsistent standards and fragmented systems across countries, regions, and platforms have led to poor liquidity in carbon assets. This has also increased the risk of double counting, where the same carbon emission reductions are counted or claimed repeatedly, thereby weakening the efficiency and credibility of the global carbon market.

[0005] Therefore, existing technologies face an irreconcilable conflict between meeting the carbon market's requirements for transparency and traceability while protecting the privacy of core corporate data. The market urgently needs a new technical solution that can achieve real-time, reliable, transparent, and traceable carbon footprinting while ensuring corporate data privacy. Summary of the Invention

[0006] This application proposes a carbon footprint traceability method that can balance data privacy protection and trusted verification, in order to resolve the fundamental contradiction between the need for transparency and verifiability in carbon footprint traceability and the need for privacy protection of the company's core business data.

[0007] According to one embodiment of the present application, a carbon footprint traceability and verification method based on a distributed ledger is proposed, the method comprising: The data acquisition device deployed at the new energy power generation project site acquires the original operation data, and the data acquisition device uses a built-in trusted hardware module and a corresponding private key to generate a first verification certificate containing a timestamp and a data source for the original operation data; The proving party server receives the raw operation data and uses the raw operation data as private input, and simultaneously obtains the project parameters and the final declared greenhouse gas emission reduction as public input; The proving server runs a preset carbon accounting zero-knowledge proof circuit to calculate the private input and the public input to generate a calculation validity proof for proving the validity of the greenhouse gas emission reduction calculation process; A smart contract deployed on a distributed ledger receives a minting request including the greenhouse gas emission reduction amount, the computational validity proof, and the first verification certificate, and executes verification logic, wherein the verification logic includes minting an unalterable digital asset bound to the greenhouse gas emission reduction amount on the distributed ledger if and only if the computational validity proof is valid and the first verification certificate is valid.

[0008] In some embodiments, the trusted hardware module is a trusted execution environment (TEE) or a secure element (SE), which generates and stores the private key in an environment isolated from the main operating system, and performs a signing operation on the original operation data to generate the first verification credential.

[0009] In some embodiments, the method further comprises: The smart contract further receives one or more second verification certificates generated by an independent verification agency, each of which indicates that the corresponding agency has conducted off-chain verification of the raw operational data within a specified reporting period; The verification logic executed by the smart contract further includes a condition that the second verification credential reaches a preset quantity threshold.

[0010] In some embodiments, the carbon accounting zero-knowledge proof circuit enforces the following mathematical constraints: performing an aggregation operation on the grid-connected net power generation sequence in the private input to obtain a sum value; The result of multiplying the sum by the baseline emission factor in the public input is equal to the greenhouse gas emission reduction in the public input.

[0011] In some embodiments, the method further comprises generating the baseline emission factor by a secure multi-party computation (SMPC)-based subsystem, the subsystem performing the following steps: Multiple data providing entities within the power grid participating in the calculation input their respective confidential operating data into the SMPC protocol in the form of encrypted shares, wherein the confidential operating data includes fuel consumption and power generation; The SMPC protocol collaboratively calculates the emission factor for the entire power grid without decrypting any party's data share. Only the baseline emission factor result obtained through the final aggregate calculation and disclosed to all participants is output, and the baseline emission factor result is used as the public input of the carbon accounting zero-knowledge proof circuit.

[0012] In some embodiments, the digital asset is implemented as an on-chain non-fungible token (ONFT) based on a universal messaging protocol for transfer between multiple heterogeneous distributed ledger networks.

[0013] In some embodiments, the method further includes performing cross-chain security configuration by: The contract owner of the digital asset sets security parameters for the specified cross-chain transfer path by calling the configuration function provided by the universal messaging protocol.

[0014] In some embodiments, setting security parameters includes: Select a combination of one or more decentralized validator networks (DVNs) from the open market to verify the legitimacy of cross-chain messages; and Set a validation threshold, which represents the minimum number of decentralized validators in the network that must submit valid validations.

[0015] In some embodiments, the method further includes the following asset write-off operations: The holder of a digital asset initiates a write-off transaction, which triggers the smart contract to permanently destroy or lock the digital asset; At the same time, a corresponding public, tamper-proof cancellation event record is generated on the distributed ledger, which serves as the final proof that the corresponding greenhouse gas emission reduction has been claimed and cannot be traded or used again.

[0016] In some embodiments, the fields of the on-chain data structure of the digital asset directly map to the requirements of the ISO 14064-2 standard and the GHG Protocol project accounting guidelines regarding project boundary definition, baseline scenario establishment, additionality demonstration, monitoring and quantification, and transparency and reporting.

[0017] This application proposes a distributed ledger-based carbon footprint traceability and verification method. By combining trusted hardware signatures at the source with an independent third-party verification network, it establishes a complete chain of trust from the physical to the digital world, fundamentally ensuring the authenticity and credibility of the original data. Based on this trustworthy foundation, this solution utilizes zero-knowledge proofs to perform verifiable calculations of carbon emission reductions, eliminating the need for access to any commercially sensitive data during the verification process, thereby resolving the conflict between transparency requirements and commercial privacy protection.

[0018] Furthermore, by automating the verification and digital asset minting processes through smart contracts, this solution further improves carbon asset accounting efficiency, reduces audit costs, and eliminates the risk of double counting by leveraging the immutability of distributed ledgers. Furthermore, this solution transforms verified carbon assets into an open-chain token (ONFT) that can flow seamlessly across multiple blockchain networks, breaking the fragmentation of traditional markets, significantly enhancing the liquidity and financial composability of carbon assets, and laying the foundation for their integration into a wider range of digital economy applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the specification and, together with the description, serve to explain the principles of the specification.

[0020] Figure 1 This is a flow chart of a carbon footprint traceability and verification method based on a distributed ledger provided in an embodiment of the present application; Figure 2 It is a system architecture and data flow diagram of an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0021] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0022] The core concept of this application is to provide an end-to-end carbon footprint traceability and verification method to overcome the challenges of data credibility, computational privacy, and asset interoperability. This solution first utilizes trusted hardware deployed at the physical site to cryptographically sign data at its source, establishing an undeniable chain of trust from the physical world to the digital world. Furthermore, this solution leverages the key technology of zero-knowledge proofs to perform privacy-protected verifiable calculations on raw operational data containing corporate trade secrets, generating cryptographic proof of the validity of the carbon emission reduction calculation process without leaking any sensitive information. Ultimately, this proof, along with other verification credentials, is submitted to a smart contract on a distributed ledger for automated verification. Once verified, a digital asset uniquely tied to the verified emission reduction is minted, immutable, and capable of cross-chain transfer. This ensures data privacy and security while achieving highly transparent, trustworthy, and efficient carbon asset transfer throughout its lifecycle.

[0023] The following will refer to the attached Figure 1 , a detailed description of the carbon footprint traceability and verification method based on distributed ledger provided in the embodiment of the present application is given.

[0024] like Figure 1 As shown, the first step of this method is to obtain raw operational data from data acquisition equipment deployed at the renewable energy power generation project site. The data acquisition equipment uses a built-in trusted hardware module and its corresponding private key to generate a first verification credential containing a timestamp and data source for the raw operational data (steps S101 and S102). This step is the starting point of the entire trust chain, ensuring the authenticity and non-repudiation of the data from the physical source.

[0025] Raw operational data typically refers to key performance indicators such as grid-connected net power generation that directly reflect the environmental benefits of new energy projects. The data collection device can be a smart meter or supervisory control and data acquisition (SCADA) system installed at a power generation site (such as a wind farm or photovoltaic power plant). To ensure the trustworthiness of these devices, according to a preferred embodiment of the present application, the trusted hardware module is a trusted execution environment (TEE) or secure element (SE). This trusted hardware module generates and stores the private key in an environment isolated from the main operating system and performs a signing operation on the raw operational data to generate the first verification credential. The trusted execution environment (TEE) or secure element (SE) provides a secure area isolated from the main operating system for code execution and key storage, effectively preventing software-level attacks and data tampering. Within this secure area, the device generates and maintains a pair of asymmetric keys (public and private), with the public key being registered with the project identity contract on the blockchain. The device collects operational data at preset intervals (e.g., every hour) and uses its private key to digitally sign data packets containing key information such as timestamps and accumulated net power generation. This signature can serve as the first verification credential, providing non-repudiable cryptographic evidence that each piece of data comes from a physical source.

[0026] Next, the proving server receives the raw operational data as private input, along with the project parameters and the final declared greenhouse gas emission reductions as public input. The proving server then runs a pre-defined carbon accounting zero-knowledge proof circuit, calculating the private and public inputs to generate a computational validity proof that verifies the validity of the greenhouse gas emission reduction calculation process (steps S103 and S104). This process is the core of verifiable computation under privacy protection.

[0027] The proving server is typically an off-chain server controlled by a renewable energy power generation company. The private inputs are the company's commercially sensitive information and, in addition to the aforementioned raw operational data, may also include project-specific efficiency or loss factors. The public inputs are data visible to all participants and include the project identifier, the baseline methodology employed, publicly available and authoritative grid emission factors, and the greenhouse gas emissions reductions ultimately claimed by the proving party. A zero-knowledge proof (ZKP) is a cryptographic protocol that allows one party (the prover) to prove the truth of a claim to another party (the verifier) ​​without revealing any additional information beyond the fact that the claim is true. The computational validity proof in this scheme utilizes a zero-knowledge proof, which can prove to any third party that the proving party used authentic, compliant private data and correctly executed the agreed-upon carbon accounting method to arrive at the claimed emissions reductions. All private inputs are not disclosed during the verification process.

[0028] In order to make the calculation process standardized and trustworthy, according to a specific embodiment of the present application, the carbon accounting zero-knowledge proof circuit enforces the following mathematical constraints: performing an aggregation operation on the grid-connected net power generation sequence in the private input to obtain a sum value; the result of multiplying the sum value by the baseline emission factor in the public input is equal to the greenhouse gas emission reduction in the public input.

[0029] In this implementation, the circuit does not use general-purpose calculation tools. Instead, it precisely encodes and solidifies the core calculation formulas from internationally recognized carbon accounting standards (such as the GHG Protocol Grid-Connected Power Generation Project Guidelines) within a series of mathematical constraints. The circuit first accumulates the private input (i.e., the grid-connected net power generation sequence) as a time series array to obtain the total power generation (i.e., the sum) for the reporting period. It then enforces the following core formula: Total electricity generation × baseline emission factor = greenhouse gas emission reduction.

[0030] Only when the equality holds can the prover successfully generate a valid proof of computational validity; if the data does not satisfy this constraint, the proof generation algorithm will fail directly.

[0031] In this calculation, the baseline emission factor serves as an important public input, and its calculation itself may also involve sensitive data from multiple grid participants. To this end, according to a preferred embodiment of the present application, the method further includes generating the baseline emission factor via a subsystem based on secure multi-party computation (SMPC). The subsystem performs the following steps: multiple data-providing entities within the grid participating in the calculation input their respective confidential operating data, including fuel consumption and power generation, into the SMPC protocol in the form of encrypted shares; the SMPC protocol collaboratively completes the emission factor calculation for the entire grid without decrypting any party's data share; and only outputs the final aggregated calculated baseline emission factor result, which is public to all participants, and uses the baseline emission factor result as the public input to the carbon accounting zero-knowledge proof circuit.

[0032] Secure Multi-Party Computation (SMPC), a technology used in this embodiment, allows multiple, mutually untrusted parties to collaboratively compute a function without exposing their private inputs. Through this subsystem, data entities, such as power plants, can split confidential operational data (such as fuel consumption and generating hours) into encrypted shares and input them into the protocol. The protocol then interactively calculates these shares, ultimately deriving an authoritative, publicly available grid emission factor. During this process, no single party can access any other party's raw data.

[0033] After obtaining all necessary credentials and proofs, the on-chain verification and asset generation phase begins. A smart contract deployed on the distributed ledger receives a minting request containing the greenhouse gas emission reduction amount, the computational validity proof, and the first verification certificate, and executes verification logic. This verification logic involves minting an immutable digital asset tied to the greenhouse gas emission reduction amount on the distributed ledger only if the computational validity proof and the first verification certificate are valid (steps S105, S106, and S107).

[0034] A distributed ledger (such as a blockchain) is a decentralized, immutable database. A smart contract is a computer program deployed on a distributed ledger that automatically executes pre-defined terms. In this step, the smart contract acts as an automated, trustless verifier. The smart contract automatically verifies that the computational validity proof is valid for the given public input and that the digital signature of the first verification credential is legitimate. Only if all verifications pass will the smart contract execute the minting operation, generating a digital asset representing the verified carbon emission reduction. If any verification fails, the request will be rejected (step S108).

[0035] To further enhance the system's credibility and foster social consensus, according to another embodiment of the present application, the method further comprises: the smart contract also receiving one or more secondary verification certificates generated by independent verification organizations, each of which indicates that the corresponding organization has conducted off-chain verification of the raw operational data within a specified reporting period; and the verification logic executed by the smart contract further includes a condition that the number of secondary verification certificates reaches a preset threshold. This step can involve a verifier network composed of independent third-party auditing organizations with professional qualifications (such as ISO 14064-3 audit qualifications). These organizations will conduct independent off-chain audits of the project's operational data within a specific reporting period (for example, cross-checking the settlement statements of power grid companies). Upon successful audit, the organization will use its official private key to sign a verification statement, known as the secondary verification certificate, and submit it to the blockchain. The smart contract's verification logic has been enhanced. In addition to the aforementioned cryptographic verification, it also checks whether the number of secondary verification certificates received reaches a preset threshold (for example, in a setup requiring verification by three organizations, the threshold can be set to 2). Only when this threshold is met can the minting of the digital asset be finally triggered. This embodiment adopts a hybrid model that combines hardware cryptographic proof with the socioeconomic consensus of professional human auditors, forming a powerful check and balance mechanism, which greatly increases the difficulty and cost of data falsification.

[0036] In some embodiments, the design of the final generated digital asset itself is also optimized. In a preferred embodiment, the digital asset can be implemented as a fully chained non-fungible token (ONFT) based on a universal messaging protocol to be transferred between multiple heterogeneous distributed ledger networks.

[0037] A non-fungible token (NFT) is a uniquely identified, non-interchangeable digital asset. An on-chain non-fungible token (ONFT) is a specialized NFT based on cross-chain interoperability protocols (such as LayerZero). Instead of being locked to a single blockchain, ONFT can be transferred securely and seamlessly across multiple blockchain networks (such as Ethereum and Polygon), addressing the fragmentation of the digital asset ecosystem and significantly enhancing its liquidity and potential for application.

[0038] To ensure the security of this cross-chain transfer, this application also provides a risk-adjustable security mechanism. In some embodiments, the method further includes performing cross-chain security configuration by invoking the configuration function provided by the universal messaging protocol to set security parameters for the specified cross-chain transfer path. Furthermore, setting security parameters includes selecting a combination of one or more decentralized validator networks (DVNs) from the open market to verify the legitimacy of cross-chain messages; and setting a verification threshold, which represents the minimum number of DVNs required to submit valid verifications. This allows asset owners to dynamically configure the security level of their cross-chain transfers based on the economic value of their assets. For example, for a high-value asset transfer, the owner can configure a security combination of five reputable DVNs and set a verification threshold of five. This means that at least four of the five selected DVNs must confirm the legitimacy of the cross-chain transaction for it to be executed on the target chain, significantly reducing security risks.

[0039] The digital asset may also include a write-off step at the end of its lifecycle. In one embodiment, the method further includes the following asset write-off operation: the digital asset holder initiates a write-off transaction, which triggers the smart contract to permanently destroy or lock the digital asset; simultaneously, a corresponding public, immutable write-off event record is generated on the distributed ledger. The write-off event record serves as final proof that the corresponding greenhouse gas emission reduction has been claimed and cannot be traded or used again.

[0040] According to this embodiment, when a company or individual purchases this digital asset to offset their own carbon emissions, they can perform a "write-off" or "retirement" operation. This operation permanently removes the asset from circulation and leaves a publicly traceable record on the blockchain. The company can then claim these emissions reductions in its environmental, social, and governance (ESG) report and provide a link to the on-chain write-off record, providing highly credible public evidence of its emissions reduction claim.

[0041] Finally, based on the concept of compliance-by-design, in some embodiments, the fields of the on-chain data structure of the digital asset directly map important requirements in the ISO 14064-2 standard and the GHG Protocol project accounting guidelines regarding project boundary definition, baseline scenario establishment, additionality demonstration, monitoring and quantification, and transparency and reporting.

[0042] According to this embodiment, each minted digital asset is itself a miniature, machine-readable summary of a compliance report that complies with international standards. Its metadata structure includes fields such as the project ID, reporting period, baseline methodology used, emission factors used in calculations, final emission reduction values, and a URI pointing to the off-chain public report, ensuring that each asset inherently demonstrates compliance and market credibility.

[0043] In order to more vividly illustrate the technical solution of this application from the perspective of system interaction and end-to-end application, the following will refer to Figure 2 , and describes it in detail with a specific example.

[0044] In this exemplary embodiment, new energy enterprise M hopes to connect its newly built photovoltaic power station to this system to convert the carbon emission reductions it generates into trusted digital assets.

[0045] First, in Figure 2 In the physical world and data collection layer on the far left, Company M's photovoltaic power plant deployed a data collection device that meets the requirements, namely a smart meter with a built-in trusted execution environment (TEE). After the project went online, the smart meter continuously collected raw operational data such as the net power generation connected to the grid during each reporting period (for example, the first quarter). Figure 2 In step 1 of the example, the meter uses its private key, stored within the secure enclave of its TEE, to digitally sign a data packet containing a timestamp and reading, generating a first verification credential. This credential is then securely transmitted to the prover server controlled by Company M (step 2), which acts as the data aggregation center for off-chain privacy computation and multi-party verification.

[0046] At the same time, within the off-chain privacy-preserving computation and multi-party verification layers, the two other trust mechanisms proposed in this application also began to operate. To calculate a reliable baseline emissions factor, the region's grid operators and other power generation entities participated in a SMPC subsystem. Each entity inputted confidential operational data, such as fuel consumption and power generation, into the SMPC protocol in the form of encrypted shares. The protocol, without decrypting any party's original data, collaboratively computed the data and ultimately output an authoritative grid emissions factor (e.g., 0.65 tCO2e / MWh) that was publicly available to all participants (Step 4). Company M, on the other hand, selected three independent, professionally qualified auditing firms to form its project's independent verifier network. After the end of the first quarter, each of the three verifiers conducted an independent off-chain audit of Company M's power generation data for that quarter. Upon successful audit, each firm signed a verification statement, known as a secondary verification certificate, using its official private key and submitted it directly as a transaction to the on-chain smart contract (Step 3), which automatically recorded these certificates.

[0047] At this point, Company M's proving server, acting as a data aggregation center, has assembled all the necessary information: the first verification credential from its own equipment, the public baseline emission factor obtained from the SMPC subsystem, and the second verification credential submitted to the blockchain by the verification authority. Based on its private raw operational data, the server calculated a total net power generation of 10,000 MWh for the first quarter and claimed a greenhouse gas emissions reduction of 10,000 MWh × 0.65 tCO2e / MWh = 6,500 tCO2e. The server then invoked the pre-defined carbon accounting ZKP circuit (step 5), taking the total net power generation time series as private input and the baseline emission factor and the final claimed emission reduction of 6,500 tCO2e as public input. The server successfully generated a proof of computational validity (zkpProof) and returned it to the server in step 6. The server assembled this proof, along with a reference to the first verification credential and public information such as the claimed emissions reduction, into a complete minting request (step 7).

[0048] In step 8, the server submits the casting request to Figure 2The smart contract at the distributed ledger and smart contract layer in [1]. Acting as a neutral, automated verifier, the smart contract receives and parses the request in step 9 and automatically executes its verification logic. The smart contract performs a triple check: first, it verifies that the zkpProof is valid for the given public input; second, it verifies that the hardware signature of the first verification credential is legitimate; and finally, it checks that the number of second verification credential submitted by an independent verification authority, as recorded on-chain, reaches a preset "2 of 3" threshold. In this example, since all conditions are met and verification passes, the smart contract successfully mints a fully chained non-fungible token (ONFT) called Carbon Trace, representing 6,500 tCO2e of emission reductions, and sends it to Company M's digital wallet. This ONFT initially exists on a low-cost blockchain network, such as Polygon.

[0049] Finally, enter Figure 2 At the bottom, the cross-chain interoperability layer. Company M wishes to sell this carbon asset on a mainstream carbon trading market on the Ethereum mainnet. In step 10, the company initiates a cross-chain transfer request from Polygon to Ethereum through a decentralized application. The underlying universal messaging protocol and its associated DVN network begin to validate the transaction according to the stringent, risk-adjustable security policies established for this high-value asset. Once verified, in step 11, an ONFT token representing the same asset is minted at Company M's Ethereum wallet address, while the original asset on Polygon is securely locked, ensuring a constant supply of the asset. Finally, in step 12, a large multinational corporation purchases the carbon asset for its ESG reporting and executes a write-off. The ONFT token is permanently destroyed, leaving a publicly traceable write-off record on Ethereum as irrefutable proof that the company has achieved its net-zero emissions goal.

[0050] This application describes in detail an innovative carbon footprint traceability and verification method through the above specific implementation methods. It should be understood that the above description is only a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Figure 1 Process description and Figure 2Based on the systematic example of this application, those skilled in the art can clearly understand that the core of this application is to creatively integrate multiple technologies such as trusted hardware, zero-knowledge proof, secure multi-party computing, distributed ledgers and cross-chain communication protocols, thereby systematically solving the technical problems of data source credibility, computing process privacy and ultimate digital asset liquidity. For those skilled in the art, without departing from the innovative ideas of this application, various equivalent replacements or adaptive modifications can be made to the specific implementation details of this solution, such as the specific cryptographic algorithm used, the type of blockchain network, the number threshold of the validator network, etc., and these changes should fall within the scope of protection determined by this application.

[0051] Although this specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of protection claimed, but are mainly used to describe the features of specific embodiments of specific inventions. Certain features described in multiple embodiments within this specification may also be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment may also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, although features may work in certain combinations as described above and even initially claimed as such, one or more features from the claimed combination may be removed from the combination in some cases, and the claimed combination may point to a sub-combination or a variation of the sub-combination.

[0052] Similarly, although operations are depicted in a particular order in the accompanying drawings, this should not be understood as requiring that these operations be performed in the particular order shown or performed sequentially, or that all illustrated operations be performed to achieve the desired results. In some cases, multitasking and parallel processing may be advantageous. In addition, the separation of various system modules and components in the above-described embodiments should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product, or packaged into multiple software products.

[0053] The above description is merely a preferred embodiment of one or more embodiments of this specification and is not intended to limit one or more embodiments of this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of this specification shall be included in the scope of protection of one or more embodiments of this specification.

Claims

1. A carbon footprint traceability and verification method based on distributed ledger, characterized in that: The method comprises: The data acquisition device deployed at the new energy power generation project site acquires the original operation data, and the data acquisition device uses a built-in trusted hardware module and a corresponding private key to generate a first verification certificate including a timestamp and a data source for the original operation data; The proving party server receives the raw operation data and uses the raw operation data as private input, and simultaneously obtains the project parameters and the final declared greenhouse gas emission reduction as public input; The proving server runs a preset carbon accounting zero-knowledge proof circuit to calculate the private input and the public input to generate a calculation validity proof for proving the validity of the greenhouse gas emission reduction calculation process; A smart contract deployed on a distributed ledger receives a minting request including the greenhouse gas emission reduction amount, the computational validity proof, and the first verification certificate, and executes verification logic, wherein the verification logic includes minting an unalterable digital asset bound to the greenhouse gas emission reduction amount on the distributed ledger if and only if the computational validity proof is valid and the first verification certificate is valid.

2. The method according to claim 1, characterized in that The trusted hardware module is a trusted execution environment (TEE) or a secure element (SE). The trusted hardware module generates and stores the private key in an environment isolated from the main operating system, and performs a signing operation on the original operation data to generate the first verification credential.

3. The method according to claim 1, characterized in that The method further comprises: The smart contract further receives one or more second verification certificates generated by an independent verification agency, each of which indicates that the corresponding agency has conducted off-chain verification of the raw operational data within a specified reporting period; The verification logic executed by the smart contract further includes a condition that the second verification credential reaches a preset quantity threshold.

4. The method according to claim 1, wherein The carbon accounting zero-knowledge proof circuit enforces the following mathematical constraints: performing an aggregation operation on the grid-connected net power generation sequence in the private input to obtain a sum value; The result of multiplying the sum by the baseline emission factor in the public input is equal to the greenhouse gas emission reduction in the public input.

5. The method according to claim 4, characterized in that The method further includes generating the baseline emission factor by a subsystem based on a secure multi-party computation (SMPC) protocol, the subsystem performing the following steps: Multiple data providing entities within the power grid participating in the calculation input their respective confidential operating data into the SMPC protocol in the form of encrypted shares, wherein the confidential operating data includes fuel consumption and power generation; The SMPC protocol collaboratively calculates the emission factor for the entire power grid without decrypting any party's data share. Only the baseline emission factor result obtained through the final aggregate calculation and disclosed to all participants is output, and the baseline emission factor result is used as the public input of the carbon accounting zero-knowledge proof circuit.

6. The method according to claim 1, characterized in that The digital asset is implemented as a full-chain non-fungible token (ONFT) based on a universal messaging protocol for transfer between multiple heterogeneous distributed ledger networks.

7. The method according to claim 6, characterized in that The method also includes performing cross-chain security configuration through the following steps: The contract owner of the digital asset sets security parameters for the specified cross-chain transfer path by calling the configuration function provided by the universal messaging protocol.

8. The method according to claim 7, characterized in that Setting security parameters includes: Select a combination of one or more decentralized validator networks (DVNs) from the open market to verify the legitimacy of cross-chain messages; and Set a validation threshold, which represents the minimum number of decentralized validators in the network that must submit valid validations.

9. The method according to claim 1, characterized in that The method further includes the following asset write-off operations: The holder of a digital asset initiates a write-off transaction, which triggers the smart contract to permanently destroy or lock the digital asset; At the same time, a corresponding public, tamper-proof cancellation event record is generated on the distributed ledger, which serves as the final proof that the corresponding greenhouse gas emission reduction has been claimed and cannot be traded or used again.

10. The method according to claim 1, characterized in that The fields of the on-chain data structure of the digital asset directly map to the requirements of the ISO 14064-2 standard and the GHG Protocol project accounting guidelines regarding project boundary definition, baseline scenario establishment, additionality demonstration, monitoring and quantification, and transparency and reporting.

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