Employ Mathematical Modeling to Summarize, Analyze, And Predict the Relationship Between Carbon Dioxide and Temperature, Location, And Other Factors.

Authors

  • Yuheng Xie
  • Yanxi He
  • Yufei Ye
  • Chenfei Liu

DOI:

https://doi.org/10.54097/y1jm6q63

Keywords:

Carbon dioxide, greenhouse gases, clean energy use, temperature, modeling.

Abstract

Fluctuations in the amount of greenhouse gases (GHGs) are affected by a variety of factors, both natural and artificial. Natural factors, such as volcanic eruptions and changes in the intensity of solar radiation, can cause fluctuations in greenhouse gases. However, in recent years, human activities have surpassed natural factors and have become a major driver of climate change. During the industrial revolution, the widespread use of fossil fuels, large-scale deforestation and emissions from factories caused irreversible damage to ecosystems. Rising global temperatures are destroying natural ecosystems around the world and are a potential threat to human survival. In this paper, we systematically examine and analyze the main sources of greenhouse gas emissions, explore the factors contributing to air pollution, and evaluate the specific impacts of these changes on global warming. We analyze the relationship between global warming and different factors (economic development, clean energy, and CO2 emissions) by using both one-way linear regression models and multiple linear regression models. A quadratic linear regression model shows that solar energy is the most promising renewable energy source. Meanwhile, using the global GDP as a criterion, we have shown that economic growth contributes to CO2 emissions. However, due to the governments having valued economic development more, the upward growth trend of the economic development curve is intensified, while the downward growth trend of the global average temperature is slowed down. Finally, we developed a multivariate linear regression model to evaluate whether using new energy sources could help mitigate global warming. Based on the previous analysis, we focus on the factor of CO2 emission. By using the linear regression model, we obtained the projected values of CO2 emissions, clean energy usage and global GDP in 2050, and the CO2 emissions in 2050 are 36.59439 billion tons, which meet the goal of carbon neutrality.

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References

IPCC climate report 2022 summary: The key findings. (2023, June 19). Climate Consulting. https://climate.selectra.com/en/news/ipcc-report-2022

Carbon dioxide now more than 50% higher than pre-industrial levels. (2022, June 3). National Oceanic and Atmospheric Administration. https://www.noaa.gov/news-release/carbon-dioxide-now-more-than-50-higher-than-pre-industrial-levels

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Wikipedia contributors. (2024, February 22). Dickey–Fuller test. Wikipedia. https://en.wikipedia.org/wiki/Dickey%E2%80%93Fuller_test

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Published

21-05-2024

Issue

Section

Articles

How to Cite

Xie, Y., He, Y., Ye, Y., & Liu, C. (2024). Employ Mathematical Modeling to Summarize, Analyze, And Predict the Relationship Between Carbon Dioxide and Temperature, Location, And Other Factors. Academic Journal of Science and Technology, 11(1), 13-20. https://doi.org/10.54097/y1jm6q63