ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Economics and Management
Evaluation of the Effectiveness of China's Forest Carbon Trading Market Policy
Dawei Wang
Limin Geng
Wenxing Shen
Nanjing Forestry University, Nanjing, China
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Abstract
Forest carbon sinks play a crucial role in mitigating climate change, and their development is supported by various policy measures in China. This paper evaluates the effectiveness of China's forest carbon sink policies from 2014 to 2024, focusing on three key performance dimensions: economic, social, and environmental. While applying the Analytic Hierarchy Process (AHP) and Gray Correlation Analysis, this study constructs a comprehensive performance evaluation framework and quantitatively assesses the impacts of forest carbon sequestration policies on these dimensions. The findings indicate significant improvements in all three areas, with economic performance, including four secondary indicator variables, showing consistent growth. Social performance, reflected in three main secondary indicator variables, also demonstrated steady progress, although at a slower rate compared to environmental gains. Environmental performance saw the most notable improvements, with four secondary indicator variables increasing substantially by 2024. Furthermore, Gray Correlation Analysis revealed that economic performance indicators, particularly forestry industry investment and the contribution rate of the forestry sector's total output to GDP, had the most significant impact on policy effectiveness. The study concludes that while substantial progress has been made, continued policy optimization, increased investment, and enhanced environmental governance are essential to furthering China's carbon neutrality and sustainable development goals.
Summary
Keywords
Analytic hierarchy process, Carbon trading, Economic performance, environmental performance, Forest carbon sinks, Gray correlation analysis, Policy evaluation, Social performance
Received
05 November 2025
Accepted
17 February 2026
Copyright
© 2026 Wang, Geng and Shen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dawei Wang
Disclaimer
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