Valuing Carbon Assets for Sustainability: A Dual-Approach Assessment of China’s Certified Emission Reductions

As China’s voluntary greenhouse gas emission reduction mechanism undergoes institutional revitalization, the accurate valuation of carbon assets such as China Certified Emission Reductions (CCERs) becomes increasingly critical for effective climate finance and sustainability-oriented investment. This study proposes an integrated value assessment model for CCERs that combines Long Short-Term Memory (LSTM) neural network-based carbon price forecasting with both the discounted net cash flow method and the Black–Scholes option pricing framework. Applying this model to a wind power project, the study found that the practical value of CCERs, derived from verified emission reductions, significantly exceeds their market option value, underscoring the economic and environmental viability of such projects. By distinguishing between the realized and potential values of carbon credits, this research offers a comprehensive tool for carbon asset valuation that supports corporate carbon management and policy development. The framework contributes to the growing literature on sustainable finance by aligning carbon asset pricing with long-term climate goals and enhancing transparency in carbon markets.

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Publication Details

Journal
Sustainability
Published
2025-05-22
DOI
https://doi.org/10.3390/su17114777
Citations
1
Primary Topic
Climate Change Policy and Economics
Type
article
Field-Weighted Citation Impact
3.13
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Valuing Carbon Assets for Sustainability: A Dual-Approach Assessment of China’s Certified Emission Reductions

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article

Valuing Carbon Assets for Sustainability: A Dual-Approach Assessment of China’s Certified Emission Reductions

Jiawen Liu, Jiayi Wang, Yue Liu, Xinyue Chen, Liyuan Deng
article en
1 citations

Abstract

As China’s voluntary greenhouse gas emission reduction mechanism undergoes institutional revitalization, the accurate valuation of carbon assets such as China Certified Emission Reductions (CCERs) becomes increasingly critical for effective climate finance and sustainability-oriented investment. This study proposes an integrated value assessment model for CCERs that combines Long Short-Term Memory (LSTM) neural network-based carbon price forecasting with both the discounted net cash flow method and the Black–Scholes option pricing framework. Applying this model to a wind power project, the study found that the practical value of CCERs, derived from verified emission reductions, significantly exceeds their market option value, underscoring the economic and environmental viability of such projects. By distinguishing between the realized and potential values of carbon credits, this research offers a comprehensive tool for carbon asset valuation that supports corporate carbon management and policy development. The framework contributes to the growing literature on sustainable finance by aligning carbon asset pricing with long-term climate goals and enhancing transparency in carbon markets.

SustainabilityVol. 17(11)
Jiangsu University (CN)
Openalex Percentile: Top 8%
Climate Change Policy and Economics
3.13
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