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Framework evaluation demonstrates automated anomaly detection with perfect F1-scores in transit network data, highlighting a scalable foundation for continuous carbon auditing.
Accurate carbon footprint accounting is fundamental for urban environmental governance. However, multi-stakeholder transit networks struggle with data manipulation, privacy risks, and labor-intensive manual auditing. To resolve these trust and scalability bottlenecks, this paper introduces a tri-layer hybrid blockchain framework based on an “off-chain storage, on-chain evidence” paradigm. The architecture synergizes a relational database (MySQL) for high-throughput structured data, the InterPlanetary File System (IPFS) for decentralized raw evidence, and Hyperledger Fabric to immutably anchor dual-layer cryptographic hashes. We engineer a smart contract auditing pipeline that autonomously executes deterministic verification of hash consistency, emission thresholds, and physical logic integrity. Empirical evaluations utilizing a large-scale urban transit dataset injected with adversarial mutations demonstrate high robustness, achieving F1-scores of 1.000 across multidimensional anomalies. This replaces manual testing with statistically significant verification. Ultimately, this framework provides environmental regulators and transit authorities with a highly scalable, privacy-preserving, and trust-minimized infrastructure for continuous carbon footprint traceability.
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Cheng et al. (2026) studied this question.
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