Removal of carbon dioxide from the atmosphere to reduce global warming: a modelling study

Shukla, J.B.; Chauhan, M. S.; Sundar, Shyam; Naresh, Ram

doi:10.1504/ijgw.2015.067754

Cited by 29 publications

(7 citation statements)

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“…In recent decades, several mathematical models are used to study the dynamical relationship of atmospheric

{CO}_{2}

gas with forest, human population, and so on (Caetano et al, 2011; Devi & Gupta, 2018, 2020; Devi & Mishra, 2020; Misra & Verma, 2013, 2015; Misra et al, 2015; Shukla et al, 2015; Verma & Misra, 2018). Shukla et al (2015) studied the effect of using liquid species and planting green belt around the source on the reduction of

{CO}_{2}

emissions. Misra and Verma (2015) proposed a nonlinear delay model to study the effect of delay in reforestation on the mitigation of atmospheric

{CO}_{2}

.…”

Section: Introductionmentioning

confidence: 99%

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

Verma

2021

Natural Resource Modeling

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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. Recommendations for Resource Managers The enhanced concentration of 0.1emCO0.1em2 is primarily responsible for anthropogenic global warming. Declination in global forest cover is contributing to the increase in the 0.1emCO0.1em2 concentration. Plantation of trees is an avenue to combat global warming by reducing the atmospheric 0.1emCO0.1em2 level. However, plantation activities are constrained by land availability and other constraints. In this scenario, the use of genetically modified trees may aid in achieving 0.1emCO0.1em2 mitigation targets. Forest plantation using genetically modified trees brings more reduction in 0.1emCO0.1em2 concentration in comparison to when planted trees are not genetically modified. The forest management policies should focus on the development and plantation of genetically modified trees having more 0.1emCO0.1em2 sequestration capacity, so that the carbon stock per unit forest area can be increased. Such policies are also found to be helpful in attaining the target reduction in 0.1emCO0.1em2 concentration under economic constraints.

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“…In recent decades, several mathematical models are used to study the dynamical relationship of atmospheric

{CO}_{2}

{CO}_{2}

emissions. Misra and Verma (2015) proposed a nonlinear delay model to study the effect of delay in reforestation on the mitigation of atmospheric

{CO}_{2}

.…”

Section: Introductionmentioning

confidence: 99%

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

Verma

2021

Natural Resource Modeling

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“…As this model is non-linear, it is to be analyzed by using the stability theory of differential equations (Shukla et al, 2015;Goyal and Shukla, 2018).…”

Section: Mathematical Modelmentioning

confidence: 99%

Effects of Mitigation Options on the Control of Methane Emissions Caused by Rice Paddies and Livestock Populations to Reduce Global Warming: A Modeling Study and Comparison with Environmental Data

Sundar¹,

Mishra²,

Shukla³

2021

J ENVIRON INFORM

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In this paper, a non-linear mathematical model is proposed and analyzed to study the effects of mitigation options on the control of methane emissions in the atmosphere caused by rice paddies and livestock populations to reduce global warming. In the modeling process, it is assumed that the cumulative biomass density of rice paddies and the density of livestock populations follow logistic models with their respective growth rates and carrying capacities. The growth rate of concentration of methane in the atmosphere is assumed to be directly proportional to the cumulative density of various processes involved in the production of rice paddies as well as the cumulative density of various processes used in the farming of livestock populations. This growth rate is also assumed to increase with natural factors such as wetlands but it decreases with the cumulative density of mitigation options, considered to be proportional to the increased level of methane concentration in the atmosphere. The non-linear model is analyzed by using the stability theory of differential equations and computer simulation. The analysis shows that mitigation options can control the methane emissions in the atmosphere caused by rice paddies and livestock populations considerably. The computer simulation of the model confirms this analytical result. The data from model prediction is compared with actual methane data in the atmosphere and found to be very satisfactory.

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“…It explores the impact of technological options on CO2 reduction, revealing that increasing implementation rates and efficiency effectively lower atmospheric CO2 levels. Shukla et al [11] proposed a nonlinear model to explore removing CO2 from the atmosphere using external species and photosynthesis.…”

Section: Introductionmentioning

confidence: 99%

Optimization Technique on Dynamics of Carbon Dioxide to Controlling Global Warming

Mehmood,

Hassan

2024

Preprint

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Background Carbon dioxide is increasing in the atmosphere day by day due to diverse sources increasing global warming. Meeting the energy demands of the expanding human population, large-scale carbon dioxide (CO2) is produced. Effective reduction of CO2 emissions from the energy sector and others through optimization is required to reduce global warming. Model: This paper presents a mathematical model that captures the dynamic relationship between carbon dioxide levels in the atmosphere, human population dynamics, energy use, and the progression of global warming as distinct sections. Real-time data from these sections are utilized to adjust model parameters. Methodology: Firstly, the stability analysis of the proposed model is examined to determine whether solutions remain bounded or converge to specific states on the equilibrium points. Secondly, sensitivity analysis of the model is investigated and determines the behavior of the dynamic system on changes in parameters. Lastly, the optimization technique is applied to the model to reduce global warming by optimizing the level of CO2 emission from the energy sector. Results Through optimization, results show that global warming is majorly reduced when the CO2 emission from the energy sector is reduced. Novelty: The thorough analysis and validation of the proposed model offer valuable insights for devising effective strategies to mitigate climate change.

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Removal of carbon dioxide from the atmosphere to reduce global warming: a modelling study

Cited by 29 publications

References 0 publications

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

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

Effects of Mitigation Options on the Control of Methane Emissions Caused by Rice Paddies and Livestock Populations to Reduce Global Warming: A Modeling Study and Comparison with Environmental Data

Optimization Technique on Dynamics of Carbon Dioxide to Controlling Global Warming

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