A carbon footprint traceability and verification method based on distributed ledger

Abstract

The application discloses a carbon footprint traceability and verification method based on a distributed ledger. First, the trusted hardware is used to generate a first verification voucher for the original operation data at the source. Then, the proof server runs a zero-knowledge proof circuit to generate a calculation validity proof without exposing the original data as private input. Finally, the smart contract binds digital assets to greenhouse gas emission reductions after verifying the above-mentioned voucher and proof. The method solves the contradiction between transparency and data privacy in carbon accounting, and realizes trusted, efficient and privacy-protected carbon footprint traceability.

Description

Technical Field

[0001] This application relates to the fields of data processing and information security, and in particular to a method for carbon footprint tracing and verification based on distributed ledger. Background Technology

[0002] Against the backdrop of global efforts to address climate change, new energy industries, represented by wind and solar power, are experiencing rapid development. However, the expansion of this industry faces a core challenge: how to quantify and verify its real 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 statements 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 commercially sensitive data during their daily production and operation, such as real-time power generation, equipment operating efficiency, operation and maintenance plans, and terms in power purchase agreements (PPAs). This data is an integral part of the company's core competitiveness, and its leakage would pose a significant business risk.

[0004] Current carbon asset registration and accounting systems are mostly centralized, and their inherent limitations are becoming increasingly apparent. The main shortcomings of existing systems include:

[0005] (1) High cost and delay

[0006] Existing systems typically rely on periodic manual audits to verify data, resulting in data update delays and high accounting costs.

[0007] (2) Lack of real-time traceability

[0008] Traditional auditing methods struggle to achieve real-time tracing and verification of the carbon emission reduction generation process;

[0009] (3) Data security risks

[0010] Centralized databases are susceptible to single points of failure and data tampering, which, if they occur, will severely impact the credibility of the system.

[0011] (4) Market fragmentation and double calculation

[0012] Inconsistent standards and fragmented systems among different countries, regions, and platforms result in poor liquidity of carbon assets. Moreover, this increases the risk of double counting, where the same carbon emission reduction is counted or declared twice, thereby undermining the efficiency and credibility of the global carbon market.

[0013] Therefore, existing technologies present an irreconcilable contradiction between meeting the carbon market's requirements for transparency and traceability and protecting the privacy of core corporate data. The market urgently needs a novel technological solution that can achieve real-time, reliable, transparent, and traceable carbon footprint data while ensuring corporate data privacy. Summary of the Invention

[0014] This application proposes a carbon footprint tracing method that can balance data privacy protection and credible verification, in order to resolve the fundamental contradiction between the need for transparency and verifiability and the need to protect the privacy of core business data of enterprises in carbon footprint tracing.

[0015] According to one embodiment of this application, a carbon footprint tracing and verification method based on distributed ledger is proposed, the method comprising:

[0016] Raw operational data is acquired by data acquisition equipment deployed at the site of a new energy power generation project. The data acquisition equipment uses a built-in trusted hardware module and a corresponding private key to generate a first verification credential containing a timestamp and the data source for the raw operational data.

[0017] The certifying server receives the original operating data and uses it as private input, while simultaneously obtaining the project parameters and the final declared greenhouse gas emission reductions as public input.

[0018] The proof server runs a preset carbon accounting zero-knowledge proof circuit to calculate the private and public inputs to generate a calculation validity proof to prove the validity of the greenhouse gas emission reduction calculation process.

[0019] A smart contract deployed on a distributed ledger receives a casting request containing the greenhouse gas emission reduction, the computational validity proof, and the first verification credential, and executes verification logic. The verification logic includes casting an immutable digital asset bound to the greenhouse gas emission reduction on the distributed ledger if and only if the computational validity proof is valid and the first verification credential is valid.

[0020] In some implementations, 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 operational data to generate the first verification credential.

[0021] In some embodiments, the method further includes:

[0022] The smart contract also receives one or more second verification credentials generated by an independent verification authority, each of which indicates that the corresponding authority has performed off-chain verification of the original operational data within a specified reporting period;

[0023] The verification logic executed by the smart contract further includes the condition that the second verification credential reaches a preset quantity threshold.

[0024] In some implementations, the zero-knowledge proof circuit for carbon accounting enforces the following mathematical constraints:

[0025] An aggregation operation is performed on the grid-connected net power generation sequence in the private input to obtain a sum value;

[0026] The summation, multiplied by the baseline emission factor in the public input, is equal to the greenhouse gas emission reduction in the public input.

[0027] In some implementations, the method further includes generating the baseline emission factor via a subsystem based on secure multi-party computation (SMPC), which performs the following steps:

[0028] Multiple data providers within the power grid participating in the calculation input their respective confidential operational data, including fuel consumption and power generation, into the SMPC protocol in encrypted form.

[0029] The SMPC protocol collaboratively completes the calculation of emission factors for the entire power grid without decrypting any party's data share.

[0030] Only the baseline emission factor result, which is finally aggregated and calculated and made public 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.

[0031] In some implementations, the digital asset is implemented as a full-chain non-fungible token (ONFT) based on a common messaging protocol for transfer between multiple heterogeneous distributed ledger networks.

[0032] In some implementations, the method also includes configuring cross-chain security through the following steps:

[0033] The contract owner of the digital asset sets security parameters for the specified cross-chain transfer path by invoking the configuration function provided by the general messaging protocol.

[0034] In some implementations, setting security parameters includes:

[0035] Select a combination of one or more decentralized validator networks (DVNs) from the open market to verify the legitimacy of cross-chain messages; and

[0036] Set a verification threshold, which represents the minimum number of decentralized validator networks that can submit valid verifications.

[0037] In some implementations, the method further includes the following asset write-off operations:

[0038] When a holder of a digital asset initiates a write-off transaction, the write-off transaction will trigger the smart contract to permanently destroy or lock the digital asset.

[0039] Simultaneously, corresponding public and tamper-proof write-off event records are generated on the distributed ledger. These write-off event records serve as final proof that the corresponding greenhouse gas emission reductions have been declared and cannot be traded or used again.

[0040] In some implementations, 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 assessment, monitoring and quantification, and transparency and reporting.

[0041] This application proposes a distributed ledger-based carbon footprint tracing and verification method. By combining trusted hardware signatures at the source with an independent third-party verification network, it constructs a complete trust chain from the physical world to the digital world, fundamentally ensuring the authenticity and credibility of the original data. Based on this trust, the scheme utilizes zero-knowledge proofs to perform verifiable calculations of carbon emission reductions, ensuring that the verification process does not involve any commercially sensitive data, thus resolving the conflict between transparency requirements and commercial privacy protection.

[0042] Furthermore, by automating the verification and digital asset minting processes through smart contracts, this solution further improves the accounting efficiency of carbon assets, reduces auditing costs, and eliminates the risk of double-counting by relying on the immutability of distributed ledgers. Going further, this solution realizes verified carbon assets as a type of full-chain token (ONFT) that can seamlessly circulate across multiple blockchain networks, breaking down the fragmentation of traditional markets and greatly enhancing the liquidity and financial composability of carbon assets, laying the foundation for their integration into a wider range of digital economic applications. Attached Figure Description

[0043] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this specification and, together with the description, serve to explain the principles of this specification.

[0044] Figure 1This is a flowchart illustrating a carbon footprint tracing and verification method based on distributed ledger provided in an embodiment of this application;

[0045] Figure 2 This is a schematic diagram of the system architecture and data flow of an exemplary embodiment of this application. Detailed Implementation

[0046] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0047] The core concept of this application is to provide an end-to-end carbon footprint tracing and verification method to overcome the challenges of data credibility, computational privacy, and asset interoperability. This solution first utilizes trusted hardware deployed in a physical environment to cryptographically sign the data at its source, establishing an undeniable chain of trust from the physical to the digital world. Building upon this, the solution employs zero-knowledge proof technology to perform privacy-preserving, verifiable computations on raw operational data containing corporate trade secrets, generating a cryptographic proof of the validity of the carbon emission reduction calculation process without disclosing any sensitive information. Finally, this proof, along with other verification credentials, is submitted to a smart contract on a distributed ledger for automated verification. Once successful, a unique, immutable digital asset with cross-chain transfer capabilities is forged, uniquely linked to the verified emission reduction. This achieves highly transparent, trustworthy, and efficient circulation of carbon assets throughout their entire lifecycle while ensuring data privacy and security.

[0048] The following will refer to the appendix. Figure 1 This application provides a detailed description of the carbon footprint tracing and verification method based on distributed ledger provided in the embodiments of this application.

[0049] like Figure 1 As shown, the first step of this method is to acquire raw operational data using data acquisition equipment deployed at the site of the new energy power generation project. The data acquisition equipment uses a built-in trusted hardware module and a 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 part is the starting point of the entire trust chain, ensuring the authenticity and non-repudiation of the data from the physical source.

[0050] The raw operational data typically refers to key performance indicators that directly reflect the environmental benefits of new energy projects, such as net grid-connected power generation. The data acquisition equipment can be smart meters or Supervisory Control and Data Acquisition (SCADA) systems installed at power plants (such as wind farms and photovoltaic power plants). To ensure the trustworthiness of these devices, according to a preferred embodiment of this application, the trusted hardware module is a Trusted Execution Environment (TEE) or a 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 executing code and storing keys, effectively preventing attacks and data tampering from the software layer. Within this secure area, the device can generate and hold a pair of asymmetric keys (public and private keys), where the public key is registered in the project identity contract on the blockchain. The device collects operational data at preset time intervals (e.g., hourly) and uses its private key to digitally sign data packets containing key information such as timestamps and cumulative net power generation. This signature serves as the first verification credential, providing irrefutable cryptographic evidence from the physical source for each piece of data.

[0051] Next, the proving server receives the original operational data and uses it as private input, while simultaneously acquiring the project parameters and the final declared greenhouse gas emission reductions as public input. The proving server runs a pre-set carbon accounting zero-knowledge proof circuit to calculate the private and public inputs to generate a computational validity proof (steps S103 and S104) to demonstrate the validity of the greenhouse gas emission reduction calculation process. This part is the core of achieving verifiable calculations under privacy protection.

[0052] The proving server is typically an off-chain server controlled by the new energy power generation company. The private inputs are the company's commercially sensitive information, which, 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, including the project identifier, the baseline methodology used, publicly authoritative grid emission factors, and the greenhouse gas emission reduction figures ultimately claimed by the proving party. Zero-knowledge proofs (ZKPs) are cryptographic protocols that allow one party (the prover) to prove a statement to another party (the verifier) ​​as true without revealing any additional information beyond "the statement is true." The computational validity proof in this scheme uses zero-knowledge proofs, which can prove to any third party that the proving party did indeed use real, compliant private data and correctly executed the carbon accounting method agreed upon by both parties, thereby arriving at its claimed emission reduction results, without revealing any private inputs throughout the verification process.

[0053] To standardize and ensure the reliability of the calculation process, according to a specific embodiment of this 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; 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.

[0054] According to this implementation, the circuit does not employ 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 Guidelines for Grid-Connected Power Generation Projects) using a series of mathematical constraints. The circuit first accumulates the private input (i.e., the net grid-connected power generation sequence) as a time-series array to obtain the total power generation during the reporting period (i.e., the sum). Then, it forcibly verifies that the following core formula must hold true:

[0055] Total electricity generation × baseline emission factor = greenhouse gas emission reduction.

[0056] Only if the equation holds true 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.

[0057] In this calculation, the baseline emission factor serves as a crucial public input, and its calculation itself may involve sensitive data from multiple grid participants. Therefore, according to a preferred embodiment of this application, the method further includes generating the baseline emission factor through a subsystem based on Secure Multi-Party Computation (SMPC). This subsystem performs the following steps: multiple grid-based data providers participating in the calculation input their respective confidential operational 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 baseline emission factor result, which is publicly disclosed to all participants, and uses the baseline emission factor result as the public input to the carbon accounting zero-knowledge proof circuit.

[0058] The Secure Multi-Party Computation (SMPC) employed in this embodiment is a technology that allows multiple untrusted parties to collaboratively compute a function without exposing their private inputs to each other. Through this subsystem, data entities such as power plants can break down their confidential operational data (such as fuel consumption and generating hours) into encrypted shares and input them into a protocol. The protocol, through the interactive computation of these shares among the parties, ultimately derives an authoritative grid emission factor that is publicly available to all, while in this process, no single party can access the raw data of any other party.

[0059] 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, the computational validity proof, and the first verification credential, and executes verification logic. This verification logic includes minting an immutable digital asset bound to the greenhouse gas emission reduction on the distributed ledger if and only if the computational validity proof is valid and the first verification credential is valid (steps S105, S106, S107).

[0060] 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 can automatically execute preset terms. In this step, the smart contract acts as an automated, trustless verifier. The smart contract can automatically verify whether a computational validity proof is valid for a given public input and verify the legality of the digital signature of the first verification credential. Only when all verifications pass will the smart contract perform a minting operation, generating a digital asset representing the verified carbon emission reduction. If any verification fails, the request will be rejected (step S108).

[0061] To further enhance the system's credibility and introduce social consensus, according to another embodiment of this application, the method further includes: the smart contract also receives one or more second verification credentials generated by independent verification institutions, each second verification credential representing that the corresponding institution has performed off-chain verification of the original operational data within a specified reporting period; the verification logic executed by the smart contract further includes a condition that the number of second verification credentials reaches a preset threshold. This step can introduce a network of validators composed of independent third-party auditing institutions with professional qualifications (such as ISO 14064-3 auditing qualifications). These institutions will conduct independent off-chain audits of the project's operational data within a certain reporting period (e.g., cross-checking the settlement statements of the power grid company). After the audit is passed, the institution will use its official private key to sign a verification statement, i.e., a second verification credential, and submit it to the blockchain. The verification logic of the smart contract is enhanced, and in addition to the aforementioned cryptographic verification, it will also check whether the number of received second verification credentials has reached a preset threshold (e.g., in a setting that requires verification by 3 institutions, the threshold can be set to 2). Only when this quantity threshold condition is also met can the minting of digital assets be finally triggered. This embodiment employs a hybrid model that combines hardware cryptographic proofs with the socioeconomic consensus of professional human auditors, forming a powerful check and balance mechanism that greatly increases the difficulty and cost of data forgery.

[0062] In some embodiments, the design of the final generated digital asset itself has also been optimized. In a preferred embodiment, the digital asset may be implemented as a full-chain non-fungible token (ONFT) based on a common messaging protocol for transfer between multiple heterogeneous distributed ledger networks.

[0063] Non-fungible tokens (NFTs) are digital assets with unique identifiers that are not interchangeable. Full-chain non-fungible tokens (ONFTs), on the other hand, are a special type of NFT based on cross-chain interoperability protocols (such as LayerZero). They are not locked onto a single blockchain but can be securely and seamlessly transferred between multiple different blockchain networks (such as Ethereum and Polygon), thus solving the fragmentation problem of the digital asset ecosystem and greatly improving asset liquidity and application potential.

[0064] To ensure the security of such cross-chain transfers, this application also provides a risk-adjustable security mechanism. In some embodiments, the method further includes configuring cross-chain security through the following steps: the contract owner of the digital asset sets security parameters for a specified cross-chain transfer path by invoking the configuration function provided by the general messaging protocol. Furthermore, setting the security parameters includes: selecting a combination of one or more decentralized validator networks (DVNs) from the open market to verify the legitimacy of the cross-chain message; and setting a verification threshold, which represents the minimum number of decentralized validator networks that submit valid verifications. This means that the asset owner can dynamically configure the security level of their cross-chain transfers based on the economic value of the asset. For example, for a high-value asset transfer, the owner can configure a security combination of 5 reputable DVNs and set the verification threshold to 5, meaning that at least 4 of the selected 5 DVNs must confirm the legitimacy of the cross-chain transaction before the transaction can be finally executed on the target chain, thereby significantly reducing security risks.

[0065] The digital asset may also include a write-off step in the final stage of its lifecycle. In one specific embodiment, the method further includes the following asset write-off operation: the holder of the digital asset initiates a write-off transaction, which triggers the smart contract to permanently destroy or lock the digital asset; simultaneously, a corresponding public and immutable write-off event record is generated on the distributed ledger, which serves as final proof that the corresponding greenhouse gas emission reduction has been declared and cannot be traded or used again.

[0066] According to this embodiment, when a company or individual purchases the digital asset to offset its own carbon emissions, it can perform a "write-off" or "retire" operation. This operation permanently removes the asset from circulation and leaves a publicly verifiable record on the blockchain. The company can declare this emissions reduction in its Environmental, Social, and Governance (ESG) report and provide a link to the on-chain write-off record as highly credible public evidence of its emissions reduction claim.

[0067] 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 to the important 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.

[0068] According to this embodiment, each minted digital asset is itself a miniature, machine-readable, internationally standardized compliance report summary. Its metadata structure includes fields such as project ID, reporting period, baseline methodology used, emission factor used in calculation, final emission reduction value, and URI pointing to the off-chain public report, giving each asset inherent compliance and market credibility.

[0069] To more vividly illustrate the technical solution of this application from the perspectives of system interaction and end-to-end application, the following will refer to... Figure 2 And then provide a detailed description with a specific example.

[0070] In this exemplary embodiment, a new energy company M wants to connect its newly built photovoltaic power plant to this system in order to convert the carbon emission reductions it generates into trusted digital assets.

[0071] First of all, Figure 2 In the leftmost physical world and data acquisition layer, Company M's photovoltaic power plant has deployed compliant data acquisition equipment, namely a smart meter with a built-in Trusted Execution Environment (TEE). After the project goes live, this smart meter continuously collects raw operational data such as net grid-connected power generation in each reporting period (e.g., the first quarter). Figure 2 In step 1, the meter uses its private key, stored within its TEE secure area, to digitally sign the data packet containing the timestamp and reading, generating a first verification credential. This credential is then securely transmitted to a proof-party server controlled by Company M (step 2), which acts as a data aggregation center in the off-chain privacy computation and multi-party verification layer.

[0072] Meanwhile, in the off-chain privacy computation and multi-party verification layer, two other trust mechanisms proposed in this application also began to operate. On the one hand, in order to calculate a reliable baseline emission factor, the grid operator and other power generation entities in the region jointly participated in an SMPC subsystem. Each entity input its confidential operational data, such as fuel consumption and power generation, into the SMPC protocol in the form of encrypted shares. The protocol collaboratively calculated without decrypting any party's original data, and finally output an authoritative grid emission factor (e.g., 0.65 tCO2e / MWh) that was publicly available to all participants, and made public (step 4). On the other hand, Company M selected three independent, professionally qualified auditing firms to form an independent validator network for its project. After the first quarter, these three validating firms each conducted an independent off-chain audit of Company M's power generation data for that quarter. After the audit was passed, each firm used its official private key to sign a verification statement, i.e., a second verification credential, and directly submitted it as a transaction to the on-chain smart contract (step 3). The smart contract automatically recorded these credentials.

[0073] At this point, Company M's proof server, acting as the data aggregation center, has gathered 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 agency. Based on its private raw operating data, the server calculates the total net electricity generation for the first quarter as 10,000 MWh, and accordingly declares its greenhouse gas emission reduction as 10,000 MWh × 0.65 tCO2e / MWh = 6,500 tCO2e. Next, the server invokes the pre-defined carbon accounting ZKP circuit (step 5), using the total net electricity generation time series as private input, and the baseline emission factor and the finally declared 6,500 tCO2e emission reduction as public input, successfully generating a computational validity proof (zkpProof), which is returned to the server in step 6. The server assembles this proof, along with the reference to the first verification credential and the declared emission reduction and other public information, into a complete minting request (step 7).

[0074] In step 8, the server submits the casting request to Figure 2The distributed ledger and smart contract layer in this example use a smart contract. As a neutral, automated validator, 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 whether zkpProof is valid for the given public input; second, it verifies the validity of the hardware signature of the first verification credential; and finally, it checks whether the number of second verification credentials submitted by an independent verification authority and recorded on-chain reaches a preset "2-of-3" threshold. In this example, since all conditions are met, the verification passes, and the smart contract successfully mints a full-chain non-fungible token (ONFT) named Carbon Trace, representing 6,500 tCO2e emission reductions, and sends it to M Company's digital wallet. This ONFT initially exists on a low-cost blockchain network, such as Polygon.

[0075] Finally, enter Figure 2 The bottom layer is the cross-chain interoperability layer. Company M wants to sell this carbon asset on a mainstream carbon trading market located 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 general messaging protocol and its configured DVN network begin to work, verifying the transaction according to a relatively strict risk-adjustable security policy set for this high-value asset. After successful verification, in step 11, an ONFT representing the same asset is minted in Company M's Ethereum wallet address, while the original asset on Polygon is securely locked, ensuring the constant total amount of assets. Finally, in step 12, a large multinational corporation purchases this carbon asset for its ESG report and performs a write-off. The ONFT is permanently destroyed, leaving a publicly verifiable write-off record on Ethereum as irrefutable final proof that the company has achieved its net-zero emissions target.

[0076] This application, through the specific embodiments described above, elaborates in detail an innovative method for carbon footprint tracing and verification. It should be understood that the above descriptions are merely preferred embodiments of this application and are not intended to limit the scope of protection of this application. (Refer to...) Figure 1 Process description and Figure 2As can be clearly understood by those skilled in the art, the core of this application lies in the creative integration of various technologies such as trusted hardware, zero-knowledge proofs, secure multi-party computation, distributed ledgers, and cross-chain communication protocols, thereby systematically solving the technical challenges of data source credibility, computational process privacy, and final digital asset liquidity. For those skilled in the art, without departing from the innovative ideas of this application, various equivalent substitutions or adaptive modifications can be made to the specific implementation details of this solution, such as the specific cryptographic algorithms used, the type of blockchain network, and the threshold number of validator networks. All such changes should fall within the scope of protection defined in this application.

[0077] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any invention or the scope of the claims, but rather are primarily intended to describe features of specific embodiments of a particular invention. Certain features described in the various embodiments herein may also be implemented in combination in a single embodiment. Conversely, various features described in a single embodiment may also be implemented separately in various embodiments or in any suitable sub-combination. Furthermore, while features may function in certain combinations as described above and even initially claimed in this way, one or more features from a claimed combination may be removed from that combination in some cases, and a claimed combination may refer to a sub-combination or a variation thereof.

[0078] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or requiring all illustrated operations to be performed to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of various system modules and components in the above embodiments should not be construed 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.

[0079] The above description is merely a preferred embodiment of one or more embodiments of this specification and is not intended to limit the scope of 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 should be included within the protection scope of one or more embodiments of this specification.

Claims

1. A carbon footprint tracing and verification method based on distributed ledger, characterized in that, The method includes: Raw operational data is acquired by data acquisition equipment deployed at the site of a new energy power generation project. The data acquisition equipment uses a built-in trusted hardware module and a corresponding private key to generate a first verification credential containing a timestamp and the data source for the raw operational data. The certifying server receives the original operating data and uses it as private input, while simultaneously obtaining the project parameters and the final declared greenhouse gas emission reductions as public input. The proof server runs a pre-defined zero-knowledge proof circuit for carbon accounting, performing calculations on the private and public inputs to generate a computational validity proof that demonstrates the validity of the greenhouse gas emission reduction calculation process. The zero-knowledge proof circuit for carbon accounting enforces the following mathematical constraints: An aggregation operation is performed on the grid-connected net power generation sequence in the private input to obtain a sum value; The summation, multiplied by the baseline emission factor in the public input, is equal to the greenhouse gas emission reduction in the public input. A smart contract deployed on a distributed ledger receives a casting request containing the greenhouse gas emission reduction, the computational validity proof, and the first verification credential, and executes verification logic, which includes casting an immutable digital asset bound to the greenhouse gas emission reduction on the distributed ledger if and only if the computational validity proof is valid and the first verification credential is valid. The method further includes generating the baseline emission factor through a subsystem based on the Secure Multi-Party Computation (SMPC) protocol, which performs the following steps: Multiple data providers within the power grid participating in the calculation input their respective confidential operational data, including fuel consumption and power generation, into the SMPC protocol in encrypted form. The SMPC protocol collaboratively completes the calculation of emission factors for the entire power grid without decrypting any party's data share. Only the baseline emission factor result, which is finally aggregated and calculated and made public 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.

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 operational data to generate the first verification credential.

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

4. 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 common messaging protocol to facilitate transfer between multiple heterogeneous distributed ledger networks.

5. The method according to claim 4, characterized in that, The method also includes configuring cross-chain security through the following steps: The contract owner of the digital asset sets security parameters for the specified cross-chain transfer path by invoking the configuration function provided by the general messaging protocol.

6. The method according to claim 5, 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 verification threshold, which represents the minimum number of decentralized validator networks that can submit valid verifications.

7. The method according to claim 1, characterized in that, The method also includes the following asset write-off operations: When a holder of a digital asset initiates a write-off transaction, the write-off transaction will trigger the smart contract to permanently destroy or lock the digital asset. Simultaneously, corresponding public and tamper-proof write-off event records are generated on the distributed ledger. These write-off event records serve as final proof that the corresponding greenhouse gas emission reductions have been declared and cannot be traded or used again.

8. The method according to claim 1, characterized in that, The fields of the on-chain data structure of the digital assets 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 assessment, monitoring and quantification, and transparency and reporting.

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