Authors : Hazel A. Kissi Dankwah

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/2srjye9u

Scribd : https://tinyurl.com/2wpuzkpf

DOI : https://doi.org/10.38124/ijisrt/26feb1119

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : This paper introduces CarbonLedgerProof (CLP), a novel cryptographic traceability algorithm designed to connect asset-level emissions data with financial statement estimates for enhanced Environmental, Social, and Governance (ESG) assurance and impairment testing. The proposed CLP algorithm bridges the gap between carbon emissions reporting and the financial implications of environmental risks, ensuring transparency and traceability across asset portfolios. By integrating blockchain technology and zero-knowledge proofs (ZKPs), CLP offers a secure and efficient way to validate emissions data against financial estimates, addressing challenges in ESG data integrity and providing an automated framework for impairment testing in the context of sustainability. In comparison to existing algorithms such as GreenLedger, CarbonProof, ESG-Chain, and a Traditional Audit (TradAudit) baseline. CLP demonstrates superior performance in terms of scalability, data integrity, and computational efficiency. Through an extensive experimental evaluation, we showcase CLP's ability to significantly reduce verification time and enhance the accuracy of ESG assurance processes. The results indicate that CLP outperforms traditional methods in integrating emissions data into financial systems, offering an innovative approach for real-time emissions monitoring and risk assessment. This paper concludes by proposing CLP as a transformative tool for corporate ESG reporting, with practical implications for financial institutions, auditors, and regulators seeking to streamline the integration of carbon data into decision-making frameworks.

Keywords : CarbonLedgerProof (CLP), Cryptographic Traceability, ESG Assurance, Impairment Testing, Blockchain.

References :

1. Adewale, L.D. (2025). Applying Supply Chain 4.0 to Vertical Supply Chain Integration: A key to revitalizing US automotive manufacturing sector. International Journal of Research Publication and Reviews. https://doi.org/10.55248/gengpi.6.0225.0940
2. Adewale, L.D. (2025). Lifecycle Assessment and Circular Economy Strategies for Sustainable Automotive Materials: Optimizing Recycling, Waste Reduction, and Cost Efficiency. International Journal of Research Publication and Reviews. https://doi.org/10.55248/gengpi.6.0225.0953
3. Adewale, L.D. (2025). Sustainable and high-performance materials in automotive manufacturing: enhancing durability, lightweighting, and lifecycle optimization through data-driven material science. International Research Journal of Modernization in Engineering Technology and Science, 7(2). https://www.doi.org/10.56726/IRJMETS67497
4. Ajayi, A. A., Igba, E., Soyele, A. D., & Enyejo, J. O. (2024). Enhancing Digital Identity and Financial Security in Decentralized Finance (Defi) through Zero-Knowledge Proofs (ZKPs) and Blockchain Solutions for Regulatory Compliance and Privacy. IRE Journals, Volume 8, Issue 4, ISSN: 2456-8880.
5. Ajayi, A. A., Igba, E., Soyele, A. D., & Enyejo, J. O. (2024). Quantum Cryptography and Blockchain-Based Social Media Platforms as a Dual Approach to Securing Financial Transactions in CBDCs and Combating Misinformation in U.S. Elections. International Journal of Innovative Science and Research Technology, Volume 9, Issue 10, Oct. 2024, ISSN No:-2456-2165. https://doi.org/10.38124/ijisrt/IJISRT24OCT1697.
6. Akande, O. A., Ijiga, O. M., Bamigwojo, O. V., & Ogboji, A. J. (2026). Assessment of memorization, prompt inference, and retrieval risks in healthcare large language models. International Journal of Innovative Science and Research Technology, 11(1), 2887–2916. https://doi.org/10.38124/ijisrt/26jan1453
7. Aluso, L. & Enyejo, J. O. (2025). Enhancing Financial Risk Assessment through Hybrid Simulation Models Using Oracle Crystal Ball and Python Monte Carlo Engines. International Journal of Scientific Research in Science, Engineering and Technology, 509-537. https://doi.org/10.32628/IJSRSET261337
8. Aluso, L. (2021). Forecasting Marketing ROI Through Cross-Platform Data Integration Between HubSpot CRM and Power BI. International Journal of Scientific Research in Science, Engineering and Technology, 8(6), 356–378. https://doi.org/10.32628/IJSRSET214420
9. Aluso, L., Kpogli, S. A., & Enyejo, J. O. (2026). Predictive analytics for educational equity: A machine learning approach to identifying learning gaps in low-resource schools. International Journal of Recent Research in Interdisciplinary Sciences, 13(1), 12–26. https://doi.org/10.5281/zenodo.18390393
10. Animasaun, J.B., Ijiga, O.M., Ayoola, V.B., & Enyejo, L.A. (2024). Evaluating the Stability of Cannabinoid Extracts Following Different Solvent Evaporation Conditions: A GC-MS/LC-MS Degradation Profiling Study. International Journal of Scientific Research and Modern Technology.
11. Animasaun, J.B., Ijiga, O.M., Ayoola, V.B., & Enyejo, L.A. (2024). Impact of Solvent Polarity on Volatile and Non-Volatile Cannabinoid Recovery: A Multivariate GC-MS/LC-MS Extraction Optimization Study. International Journal of Scientific Research and Modern Technology.
12. Awolola, O. J., Azonuche, T. I., Enyejo, J. O., Ononiwu, M. & Ayoola, V. B. (2025). Innovation-Focused Business Models for Scaling Small and Medium-Sized Engineering Firms Through Technology  Adoption and Process Standardization International Journal of Scientific Research in Science, Engineering and Technology  Volume 12, Issue 5, PG 497-519  doi : https://doi.org/10.32628/IJSRSET25125416
13. Awolola, O. J., Azonuche, T. I., Enyejo, J. O., Ononiwu, M. & Ayoola, V, B. (2026). “Integrating Digital Project Controls and Risk Mitigation Frameworks to Improve Decision-Making in Complex Civil Engineering Projects". Volume. 11 Issue.1, January 2026 International Journal of Innovative Science and Research Technology (IJISRT) 2869-2886 https://doi.org/10.38124/ijisrt/26jan1455
14. Awolola, O. J., Azonuche, T. I., Enyejo, J. O., Ononiwu, M. & Ayoola, V. B. (2026). “Innovation-Led Construction Management Strategies for Improving Procurement, Contractor Coordination, and Regulatory Compliance in Emerging Economics". Volume. 11 Issue.1, January 2026 International Journal of Innovative Science and Research Technology (IJISRT) 2853-2868 https://doi.org/10.38124/ijisrt/26jan1454
15. Ballou, B., Chen, P. C., Grenier, J. H., & Heitger, D. L. (2018). Corporate social responsibility assurance and reporting quality: Evidence from restatements. Journal of Accounting and Public Policy, 37(2), 167-188.
16. Bui, T. D., Tsai, F. M., Tseng, M. L., Wu, K. J., & Chiu, A. S. (2020). Effective municipal solid waste management capability under uncertainty in Vietnam: Utilizing economic efficiency and technology to foster social mobilization and environmental integrity. Journal of Cleaner Production, 259, 120981.
17. Cao, X., Kostka, G., & Xu, X. (2019). Environmental political business cycles: the case of PM2. 5 air pollution in Chinese prefectures. Environmental science & policy, 93, 92-100.
18. Christensen, D. M., Serafeim, G., & Sikochi, A. (2022). Why is corporate virtue in the eye of the beholder? The case of ESG ratings. The Accounting Review, 97(1), 147–175. https://doi.org/10.2308/TAR-2019-0506
19. Dey, K., & Shekhawat, U. (2021). Blockchain for sustainable e-agriculture: Literature review, architecture for data management, and implications. Journal of Cleaner Production, 316, 128254.
20. Enyejo, J. O., Adeyemi, A. F., Olola, T. M., Igba, E & Obani, O. Q. (2024). Resilience in supply chains: How technology is helping USA companies navigate disruptions. Magna Scientia Advanced Research and Reviews, 2024, 11(02), 261–277. https://doi.org/10.30574/msarr.2024.11.2.0129
21. Ghosh, P., Jha, A., & Sharma, R. R. K. (2020). Managing carbon footprint for a sustainable supply chain: a systematic literature review. modern supply chain research and applications, 2(3), 123-141.
22. Glasenapp, S., Fonseca, M., Weimar, H., Döring, P., & Aguilar, F. X. (2021). Conversion factors for residential wood energy in the European Union: an introduction to harmonizing units of measurement. Renewable and Sustainable Energy Reviews, 138, 110491.
23. Igba, E., Abiodun, K., & Ali, E. O. (2025). Building the Backbone of the Digital Economy and Financial Innovation through Strategic Investments in Data Centers. International Journal of Innovative Science and Research Technology, ISSN No:-2456-2165. https://doi.org/10.5281/zenodo.14651210
24. Igba, E., Ihimoyan, M. K., Awotinwo, B., & Apampa, A. K. (2024). Integrating BERT, GPT, Prophet Algorithm, and Finance Investment Strategies for Enhanced Predictive Modeling and Trend Analysis in Blockchain Technology. International Journal of Scientific Research in Computer Science, Engineering, and Information Technology, 10(6), 1620-1645. https://doi.org/10.32628/CSEIT241061214
25. Igba, E., Olarinoye, H. S., Ezeh, N. V., Sehemba, D. B., Oluhaiyero, Y. S., & Okika, N. (2025). Synthetic Data Generation Using Generative AI to Combat Identity Fraud and Enhance Global Financial Cybersecurity Frameworks. International Journal of Scientific Research and Modern Technology, Volume 4, Issue 2, 2025. DOI: https://doi.org/10.5281/zenodo.14928919
26. Ijiga, O. M., Okika, N., Balogun, S. A., Agbo, O. J., & Enyejo, L. A. (2025). Recent Advances in Privacy-Preserving Query Processing Techniques for Encrypted Relational Databases in Cloud Infrastructure. International Journal of Computer Science and Information Technology Research, Vol. 13, Issue 3. https://doi.org/10.5281/zenodo.15834617
27. Jiang, F., Jiang, Z., & Kim, K. A. (2020). Capital markets, financial institutions, and corporate finance in China. Journal of Corporate Finance, 63, 101309.
28. Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial intelligence review, 42(1), 21-57.
29. Kotsantonis, S., Pinney, C., & Serafeim, G. (2016). ESG integration in investment management: Myths and realities. Journal of Applied Corporate Finance, 28(2), 10–16. https://doi.org/10.1111/jacf.12169
30. Kpogli, S. A., Onwuzurike, M. A., & Enyejo, J. O. (2024). Integrating Artificial Intelligence and Learning Sciences to Reduce Cognitive Load and Achievement Gaps in Data-Driven K-12 Instructional Systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Volume 10, Issue 6, 2569-2589. https://doi.org/10.32628/CSEIT25113575
31. Onyekaonwu, C. B., Peter-Anyebe, A. C., Ijiga, O. M., Amebleh, J., & Balogun, S. A. (2022). Securing the Digital Vault: Enterprise Data Loss Prevention (DLP) in the Age of GDPR and NDPR. International Journal of Scientific Research and Modern Technology, 1(6), 14–28. https://doi.org/10.38124/ijsrmt.v1i6.1159
32. Sharevault, (n.d). Unlocking Virtual Data Room Potential with Blockchain Integration https://sharevault.com/blog/virtual-data-room/unlocking-virtual-data-room-potential-with-blockchain-integration/
33. Throop, W., & Mayberry, M. (2017). Leadership for the sustainability transition. Business and Society Review, 122(2), 221-250.
34. Tom-Ayegunle, K., Jamil, Y., Echouffo-Tcheugui, J., et al. (2025). Cumulative Burden of Geriatric Conditions and Cardiovascular Outcomes in Older Adults: Analysis From ARIC. JACC Adv., 4(12_Part_1). https://doi.org/10.1016/j.jacadv.2025.102308
35. Zhang, Q., & Huang, X. (2020). A review of carbon footprint verification techniques and technologies in the supply chain. Journal of Cleaner Production, 257, 120430. https://doi.org/10.1016/j.jclepro.2020.120430