Browsing by Author "Salamida, Daudi"

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Modeling and control of global warming driven by transportation-induced carbon dioxide emissions through green economy investments
(lsevier, 2025-04-22) Donald, Pita; Salamida, Daudi; Panga, Paul; Mayengo, Maranya
Global warming poses a significant threat to the environment and human well-being, necessitating urgent mitigation measures. This study develops a mathematical model to analyze the impact of fossil-fueled vehicle emissions on atmospheric carbon dioxide (𝐶𝑂2) concentrations and global warming. The model assumes that global warming is driven by rising atmospheric 𝐶𝑂2 levels, which are influenced by vehicle population growth. System parameters are calibrated using global datasets on atmospheric 𝐶𝑂2 concentration, human population, vehicle production, global temperature, and Gross Domestic Product (GDP). Model validation against global data demonstrates excellent predictive performance, as confirmed by statistical metrics. Sensitivity analysis reveals that vehicle growth rate, 𝐶𝑂2-induced global warming, and population-driven temperature increases are key contributors to rising global temperatures. To stabilize the system, investment in the green economy, transitioning from fossil-fueled to clean energy vehicles, and implementing economic policies to curb temperature rise are essential, as confirmed by the numerical simulation of an optimal control problem. Numerical simulations further validate the analytical findings and explore the impact of parameter variations on system behavior. This article integrates an optimal control framework into a dynamic system to formulate data-driven strategies for minimizing global warming while ensuring sustainable economic growth.
Parameters estimation, global sensitivity analysis and model fitting for the dynamics of Plutella xylostella infestations in a cabbage biomass
(Elsevier, 2024-01-24) Mayengo, Maranya; Daniel, Paul; Salamida, Daudi
Plutella xylostella, commonly called Diamondback moth (DBM), a highly destructive and rapidly spreading agricultural pest originally from Europe. This pest poses a significant threat to global food security, with estimates suggesting that periodic outbreaks of Diamondback moth lead to annual crop losses of up to $US 4 − 5 billion worldwide. Given the potential for such substantial losses, it is crucial to employ various methods and techniques to understand the factors affecting the interaction between Diamondback moths and cabbage plants, which, in turn, impact cabbage biomass. In this paper, we propose a deterministic ecological model to capture the dynamics of Plutella xylostella infestations in cabbage biomass. The model is designed based on the life cycle stages of the pest, aiming at targeting the specific stage effectively. The synthetic data is generated using Least Square Algorithm through addition of Gaussian noise into numerically obtained values from existing literature to simulate real-world data. Global sensitivity analysis was done through Latin Hypercube sampling, highlights the significance of parameters such as 𝜓, 𝛼𝐸 and 𝛿 positively influence the growth of the diamondback moth in a cabbage biomass. In light of these findings, the study proposes that control strategies should be specifically directed towards these sensitive parameters. By doing so, we mitigate the pest population and enhance cabbage production.