Forest optimal management model for carbon sequestration

This paper evaluates forest carbon sequestration capacity as well as its ecological and cultural value using multiple models. Through calculating and forecasting the carbon sequestration trends of various tree species, the optimal time for tree cutting can be identified to maximize carbon sequestration benefits. Based on the analysis, China is predicted to achieve carbon neutrality by 2064—slightly later than its 2060 target. Then, a linear programming model for forest product carbon sequestration suggests increasing solid wood production and extending product lifespans. Finally, applying the established model to the Changbai Mountain Forest reveals that prioritizing cultural values maximizes overall forest value.

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Publication Details

Journal
Journal of Computational Methods in Sciences and Engineering
Published
2025-06-17
DOI
https://doi.org/10.1177/14727978251352140
Primary Topic
Forest Management and Policy
Type
article
Field-Weighted Citation Impact
0.00
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article

Forest optimal management model for carbon sequestration

Quandong Feng, Ruocheng Dong, Yanfang Zhang
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Journal of Computational Methods in Sciences and Engineering
Forest Management and Policy
article

Forest optimal management model for carbon sequestration

Quandong Feng, Ruocheng Dong, Yanfang Zhang
article en

Abstract

This paper evaluates forest carbon sequestration capacity as well as its ecological and cultural value using multiple models. Through calculating and forecasting the carbon sequestration trends of various tree species, the optimal time for tree cutting can be identified to maximize carbon sequestration benefits. Based on the analysis, China is predicted to achieve carbon neutrality by 2064—slightly later than its 2060 target. Then, a linear programming model for forest product carbon sequestration suggests increasing solid wood production and extending product lifespans. Finally, applying the established model to the Changbai Mountain Forest reveals that prioritizing cultural values maximizes overall forest value.

Journal of Computational Methods in Sciences and Engineering
Beijing Forestry University (CN)
Openalex Percentile: Top 86%
Forest Management and Policy
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