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Climate Finance, Carbon Accounting, and Green-Bond Readiness: Building Financial Analytics Frameworks for Sustainable Project Evaluation
Subject area: Science,Engineering and Technology · Area of research: Internal Controls
DOI: https://doi.org/10.64388/IREV10I1-1719494
Abstract
Climate risk disclosure requirements, burgeoning green capital markets, and shifting carbon accounting frameworks have presented a clear need for entities to develop strong financial analytics systems for assessing sustainable project value. There is a pressing need to develop robust financial analytics systems for evaluating sustainable projects, driven by convergence in climate risk disclosure, rising green capital markets, and evolving carbon accounting frameworks. We propose an integrated framework that links the principles of structuring green bonds with the carbon accounting frameworks, climate-scenario modelling, and investment appraisal methods in a way that is coherent and easily applicable to practice. The paper builds on the key elements of the Green Bond Principles (GBP), the Task Force on Climate-related Financial Disclosures (TCFD), the Science Based Targets initiative (SBTi), and the GHG Protocol Corporate Accounting and Reporting Standard to construct a five-pillar analytical architecture. This architecture supports organisations from their initial carbon inventory phase to project-level financial modelling, impact-metric documentation, stakeholder reporting, and readiness for issuing green bonds or sustainability-linked bonds. The framework is illustrated through case applications in renewable energy, green buildings, and NbS, while a scenario-driven section discusses emerging issues such as biodiversity credits, Article 6 carbon markets, and AI-enhanced ESG analytics.
Keywords
Climate Finance · Green Bonds · Carbon Accounting · GHG Protocol · TCFD · SBTi · ESG Analytics · Sustainable Investment · Impact Metrics · Net Zero
How to cite this paper
@article{1719494,
author = {Pascal Gbang Yelduora, Evans Chingezi, Munashe Naphtali Mupa},
title = {Climate Finance, Carbon Accounting, and Green-Bond Readiness: Building Financial Analytics Frameworks for Sustainable Project Evaluation},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {1},
pages = {365-376},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719494.pdf},
abstract = {Climate risk disclosure requirements, burgeoning green capital markets, and shifting carbon accounting frameworks have presented a clear need for entities to develop strong financial analytics systems for assessing sustainable project value. There is a pressing need to develop robust financial analytics systems for evaluating sustainable projects, driven by convergence in climate risk disclosure, rising green capital markets, and evolving carbon accounting frameworks. We propose an integrated framework that links the principles of structuring green bonds with the carbon accounting frameworks, climate-scenario modelling, and investment appraisal methods in a way that is coherent and easily applicable to practice. The paper builds on the key elements of the Green Bond Principles (GBP), the Task Force on Climate-related Financial Disclosures (TCFD), the Science Based Targets initiative (SBTi), and the GHG Protocol Corporate Accounting and Reporting Standard to construct a five-pillar analytical architecture. This architecture supports organisations from their initial carbon inventory phase to project-level financial modelling, impact-metric documentation, stakeholder reporting, and readiness for issuing green bonds or sustainability-linked bonds. The framework is illustrated through case applications in renewable energy, green buildings, and NbS, while a scenario-driven section discusses emerging issues such as biodiversity credits, Article 6 carbon markets, and AI-enhanced ESG analytics.},
keywords = {Climate Finance · Green Bonds · Carbon Accounting · GHG Protocol · TCFD · SBTi · ESG Analytics · Sustainable Investment · Impact Metrics · Net Zero},
month = {July},
doi = {https://doi.org/10.64388/IREV10I1-1719494}
}