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.

中文翻译：

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植树造林对控制大气中二氧化碳的影响：模拟研究

大气中二氧化碳（CO ₂）气体浓度的增加是造成全球变暖威胁的主要原因。森林是主要的CO ₂汇之一。由于人类活动而导致的全球森林覆盖率的下降，极大地促进了CO ₂ 含量的增加。植树造林是控制大气中CO ₂ 含量的途径。但是，大型人工林存在一些人口，生态和经济方面的限制。在这种情况下，从大气中吸收更多CO ₂的转基因树木的种植可能有助于获得CO ₂ 缓解目标。在这项研究中，提出了一个数学模型来研究转基因树木的种植对控制大气中CO ₂水平的影响。对模型进行了全面的定性分析。对该模型进行校准以适合全球CO ₂ 浓度，人口和森林面积的实际数据。进行了数值模拟，以显示关键参数对森林覆盖和大气CO ₂ 气体动力学的影响。 通过提出最佳控制问题，还研究了在降低人工林计划实施成本的同时减少CO ₂浓度的最佳策略。