How mathematical models might predict desertification from global warming and dust pollutants
Global warming and dust pollutants endanger humans and the ecosystem. One very efficient way to reduce emissions of greenhouse gases and dust is to use plant biomass in a greenbelt. This study provides a mathematical model for how dust pollutants and climate change affect plant biomass dynamics. The...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | MethodsX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2215016125001050 |
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| Summary: | Global warming and dust pollutants endanger humans and the ecosystem. One very efficient way to reduce emissions of greenhouse gases and dust is to use plant biomass in a greenbelt. This study provides a mathematical model for how dust pollutants and climate change affect plant biomass dynamics. The proposed model is thoroughly described. The model's analysis is centered on identifying prospective equilibrium positions. The study indicates that it is feasible to establish two steady states. The stability analysis illustrates that both steady states are consistently stable under the specified conditions. The local bifurcations at each steady state are derived; specifically, transcritical bifurcation may occur if a plant's growth rate is selected as a bifurcation point. The theoretical study is validated through numerical simulations. Desertification may arise if the intrinsic growth rate of plant biomass, the dust pollutants-induced plant biomass depletion coefficient, and the coefficient of natural depletion of dust contaminants are not effectively managed, according to the numerical simulation result. • This research describes how to make a nonlinear model and sets its parameters to simulate the risk of desertification caused by global warming and dust pollutants. • The proposed model's behaviour is described using stability analysis theory as a methodology. • Numerical simulations confirm the performance of the proposed methodology. |
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| ISSN: | 2215-0161 |