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Predicting global atmospheric carbon dioxide concetration dynamics: A time-integrated mathematical modelling approach

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dc.contributor.author MUNEZERO, Jean de Dieu
dc.date.accessioned 2025-09-12T13:09:30Z
dc.date.available 2025-09-12T13:09:30Z
dc.date.issued 2024-02
dc.identifier.uri http://dr.ur.ac.rw/handle/123456789/2487
dc.description Master's Dissertation en_US
dc.description.abstract The rise in the concentration of carbon dioxide (CO2) in the atmosphere is a serious problem that has an impact on the environment and the world’s climate. Effective mitigation measures require accurate future CO2 level predictions and an understanding of the processes causing this increase. Our thesis introduces an enhanced mathematical model of the average global concentration of atmospheric carbon dioxide, based on human emissions. We accomplish so by measuring the behavior of carbon dioxide released into and withdrawn from the atmosphere using a straightforward ordinary differential equation. Wecalculatebest-fitcurvestoestimatetheamountofanthropogenic CO2 emissionsintheatmosphere. In order to determine a model approximation, we estimate the model parameters using the least squares method. We evaluate the model’s solution and talk about how fit the model is. The model shows that the constant rise in anthropogenic emissions is what is responsible for the boundary-less increase in atmospheric carbon dioxide concentration. The concentration of CO2 in the atmosphere will steadily rise if CO2 emission is not controlled, with increasingly dire consequences en_US
dc.language.iso en en_US
dc.subject Model parameters using multiple data sources en_US
dc.subject Numerical solutions of the enhanced model en_US
dc.subject Numerical solutions en_US
dc.title Predicting global atmospheric carbon dioxide concetration dynamics: A time-integrated mathematical modelling approach en_US
dc.type Dissertation en_US


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