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Mathematical Modeling of Vehicle Carbon Dioxide Emissions

Authors: Pita Donald; Maranya Mayengo; Aristide G. Lambura;

Mathematical Modeling of Vehicle Carbon Dioxide Emissions

Abstract

The demand for transportation, driven by an increasing global population, is continuously rising. This has led to a higher number of vehicles on the road and an increased reliance on fossil fuels. Consequently, the rise in atmospheric carbon dioxide (CO2) levels has contributed to global warming. Therefore, it is important to consider sustainable transportation practices to meet climate change mitigation targets. In this research paper, a non-linear mathematical model is developed to study the dynamics of atmospheric CO2 concentration in relation to human population, economic activities, forest biomass, and vehicle population. The developed model is analyzed qualitatively to understand the long-term behavior of the system's dynamics. Model parameters are fitted to actual data of world population, human economic activities, atmospheric CO2, forest biomass, and vehicle population. It is shown that increased vehicular CO2 emissions have a potential contribution to the increase in atmospheric CO2 and the decline of human population. Numerical simulations are carried out to verify the analytical findings and we performed global sensitivity analysis to explore the impacts of different sensitive parameters on the CO2 dynamics.

Country
Tanzania (United Republic of)
Related Organizations
Keywords

Social sciences (General), H1-99, Sustainable transportation, Q1-390, Mathematical model, Science (General), Atmospheric carbon dioxide, Climate change, Vehicular emission, Greenhouse gas, Research Article

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Top 10%
Top 10%
Green
gold
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