Simulation and Management Research of Forest Carbon Sequestration

DOI: https://doi.org/10.62517/jlsa.202407101

Author(s)

Cheng Wang*

Affiliation(s)

College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China *Corresponding Author

Abstract

With the rapid development of the petroleum industry, the total amount of carbon dioxide emissions continues to increase. Forests are the main way to absorb carbon dioxide, while the absorption efficiency of mature trees is gradually decreasing. This study established a queuing theory model, which is based on the analytic hierarchy process, determines the index weight of the factors and the gray correlation degree analysis method to establish a decision matrix. Through the decision matrix, the best way to use the forest can be obtained, and the forest resources can be used to the maximum extent, reduce carbon dioxide concentration and improve self-economy. Carbon sequestration models use forests and their derivatives to minimize carbon dioxide concentrations and increase the economic benefits of forests.

Keywords

Queuing Theory Model; Simulation; Analytic Hierarchy Process; Optimization Decision Model

References

[1] B. Han, Z. Ming, Y. Zhao, T. Wen and M. Xie, "Comprehensive risk assessment of transmission lines affected by multi-meteorological disasters based on fuzzy analytic hierarchy process", Int. J. Electr. Power Energy Syst ., Volume 133, Page 107190, December 2021, doi: 10.1016/j.ijepes.2021.107190. [2] H. Jiang and B. Q. Hu, "A novel three-way group investment decision model under intuitionistic fuzzy multi-attribute group decision-making environment", Inf. Sci., Vol. 569, Pages 557–581, August 2021, doi: 10.1016 /j.ins.2021.05.026. [3] A. J. Dugan, J. W. Lichstein, A. Steele, J. M. Metsaranta, S. Bick and D. Y. Hollinger, Opportunities for forest sector emissions reductions: a state-level analysis, Ecol. Appl., Vol. 31, Issue 5, pp. e02327, 7 March 2021, doi: 10.1002/eap.2327. [4] S. Sarangi, A. Chakraborty and K. P. Triantis, "Multimarket competition effects on product line decisions-A multi-objective decision model in fast moving consumer goods industry", J. Bus. Res., Vol. 133, pp. 388–398, 9 March 2021, doi: 10.1016/j.jbusres.2021.05.019. [5] S.-L. Hsueh, B. Zhou, Y.-L. Chen and M.-R. Yan, "Supporting technology-enabled design education and practices by DFuzzy decision model: applications of cultural and creative product design", Int. J. Technol. Des. Educ., Volume 32, Issue 4, Pages 2239–2256, September 2022, doi: 10.1007/s10798-021-09681-7. [6] X. Pinjie, T. Zhongfu, W. Mianbin and H. Jianchao, "Spot Market Optimal Decision-Making Model of Purchase Electricity for Power-Supplying Company Based on CVaR Model", Trans. China Electrotech. Soc., Volume 24, Issue 4, pp. 186–192, 2009. [7] M. Salgado, M. Negrete-Pincetic, A. Lorca and D. Olivares, "A low-complexity decision model for home energy management systems", Appl. Energy, volume 294, page 116985, July 2021, doi : 10.1016/j.apenergy.2021.116985. [8] D. Zhao, F. Lin, R. Gu, H. Peng and T. Yan, "Bank Credit Decision Analysis Based on Fuzzy Analytic Hierarchy Process", Proc. 33rd Chin. Control Decis. Conf. Ccdc 2021, pp. 3853–3858 , 2021, doi: 10.1109/CCDC52312.2021.9601946. [9] Makovskis, K., Popluga, D., Colmorgen, F., Gerdes, H., Lazdina, D.. Evaluation of fast-growing plantations using AHP-AHP (case study situation in Latvia). Proceedings of the 29th European Biomass Energy Conference and Exhibition, 2021:205.DOI:10.26914/c.cnkihy.2021.049639. [10] P. Zhang, Q. Liu and B. Kang, "An improved OWA-Fuzzy AHP decision model for multi-attribute decision making problem", J. Intell. Fuzzy Syst., Volume 40, Issue 5, Pages 9655–9668, 2021 , doi: 10.3233/JIFS-202168. [11] L. Yao, X. Yan, M. Xu, M. Wu, Z. Yu and M. Li, "Study on Herders' Willingness to Protect Grassland Based on the IAD Extended Decision Model", Land, Volume 10, Issue 4, Page 424, April 2021, doi: 10.3390/land10040424. [12] S. Lipovetsky, "Understanding the Analytic Hierarchy Process", Technometrics, Volume 63, Issue 2, Pages 278–279, April 2021, doi: 10.1080/00401706.2021.1904744. [13] M. A. Njana, E. Zahabu and R. E. Malimbwi, Carbon stocks and productivity of mangrove forests in Tanzania, South. For.- J. For. Sci., Vol. 80, Issue 3, pp. 217–232, 2018, doi: 10.2989/20702620.2017.1334314. [14] T. Saaty and K. Kułakowski, Axioms of the Analytic Hierarchy Process (AHP) and its Generalization to Dependence and Feedback: The Analytic Network Process (ANP), Arxiv, june 2016, doi: arXiv:1605.05777. [15] L. Jiang and X. Wang, "Optimization of Online Teaching Quality Evaluation Model Based on Hierarchical PSO-BP Neural Network", Complexity, Volume 2020, Page 6647683, November 2020, doi:10.1155/2020/6647683. [16] Gou Ruikun, Li Wei, Yang Yanzheng, Bai Jiankun, Meng Yuchen, Wu Jun, Ding Yali, Dai Zheng, Shi Qi, Song Shanshan, Lin Guanghui. Changes in Water Retention and Carbon Sequestration in the Huangshan UNESCO Global Geopark (China) from 2000 to 2015. Forests, 2020, 11(11): 1152-1159