E3S Web Conf.
Volume 352, 20227th International Conference on Energy Science and Applied Technology (ESAT 2022)
|Number of page(s)||7|
|Section||Clean Energy Technologies|
|Published online||27 June 2022|
Forest management plan based on carbon sequestration model
School of ocean and environment, Tianjin University of science and technology, Tianjin 300457, China
With the increase of carbon dioxide emissions in various countries, greenhouse gases surge, posing a threat to life systems. In this context, how to balance the multifaceted value of forests and improve the relationship between climate change through carbon sequestration of forests and forest products, so as to achieve the sustainable development of forests, is an urgent problem to be solved. The forest management decision-making model established in this paper includes comprehensive considerations such as carbon sequestration, biodiversity, socio-economic and cultural entertainment. The forest carbon sequestration model consists of direct absorption by vegetation and indirect sequestration of carbon dioxide by forest products. We use Cara model to comprehensively estimate forest net primary productivity and establish a model of carbon dioxide storage of forest products based on analytic hierarchy process. In order to realize the sustainable development of forest, we also applied fuzzy comprehensive evaluation and entropy weight method to establish a forest management plan model integrating biodiversity, social economy, culture and entertainment. Finally, we applied the model to Saihanba National Forest Park in China and got positive feedback. The forest management model established in this paper provides theoretical basis and technical support for forest sustainable development.
Key words: Forest management planning model / Forest carbon sequestration model / Analytic hierarchy process / Fuzzy comprehensive evaluation / Entropy weight method
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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