Effect of plantation of genetically modified trees on the control of atmospheric carbon dioxide: A modeling study

IF 1.8 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES
Maitri Verma, A. Verma
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引用次数: 10

Abstract

The increase in carbon dioxide (CO2) gas concentration in the atmosphere is primarily responsible for the threat of global warming. Forest is one of the prime sinks of CO2. The reduction in the global forest cover due to human activities has contributed significantly to the increase in CO2 levels. Reforestation and afforestation are avenues to control the atmospheric CO2 level; however, several demographic, ecological, and economic constraints exist in the large‐scale plantations. In this scenario, the plantation of genetically modified trees, which absorb more CO2 from the atmosphere, may aid in attaining the CO2 mitigation target. In this study, a mathematical model is proposed to investigate the effect of the plantation of genetically modified trees on the control of the atmospheric CO2 level. A comprehensive qualitative analysis of the model is carried out. The model is calibrated to fit the actual data of global CO2 concentration, population, and forest area. Numerical simulations are carried out to show the effect of key parameters on the dynamics of forest cover and atmospheric CO2 gas. The optimal strategies for the reduction in CO2 concentration while minimizing the implementation cost of plantation programs are also investigated by proposing the optimal control problem.
种植转基因树木对大气二氧化碳控制作用的模拟研究
大气中二氧化碳(CO2)浓度的增加是全球变暖威胁的主要原因。森林是二氧化碳的主要汇点之一。由于人类活动,全球森林覆盖率的减少对二氧化碳水平的上升起到了重要作用。重新造林和植树造林是控制大气二氧化碳水平的途径;然而,在大规模种植园中存在一些人口、生态和经济方面的制约因素。在这种情况下,种植从大气中吸收更多二氧化碳的转基因树木可能有助于实现二氧化碳减排目标。在本研究中,提出了一个数学模型来研究转基因树木种植对控制大气CO2水平的影响。对该模型进行了全面的定性分析。该模型经过校准,以适应全球二氧化碳浓度、人口和森林面积的实际数据。数值模拟显示了关键参数对森林覆盖和大气CO2气体动力学的影响。通过提出最优控制问题,研究了在最小化种植计划实施成本的同时降低CO2浓度的最优策略。
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来源期刊
Natural Resource Modeling
Natural Resource Modeling 环境科学-环境科学
CiteScore
3.50
自引率
6.20%
发文量
28
审稿时长
>36 weeks
期刊介绍: Natural Resource Modeling is an international journal devoted to mathematical modeling of natural resource systems. It reflects the conceptual and methodological core that is common to model building throughout disciplines including such fields as forestry, fisheries, economics and ecology. This core draws upon the analytical and methodological apparatus of mathematics, statistics, and scientific computing.
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