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Global Temperature and Carbon Dioxide Nexus: Evidence from a Maximum Entropy Approach

Author

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  • Pedro Macedo

    (CIDMA—Center for Research and Development in Mathematics and Applications, Department of Mathematics, University of Aveiro, 3810-193 Aveiro, Portugal)

  • Mara Madaleno

    (Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
    Departamento de Economia, Gestão, Engenharia Industrial e Turismo (DEGEIT), Universidade de Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal)

Abstract

The connection between Earth’s global temperature and carbon dioxide (CO 2 ) emissions is one of the highest challenges in climate change science since there is some controversy about the real impact of CO 2 emissions on the increase of global temperature. This work contributes to the existing literature by analyzing the relationship between CO 2 emissions and the Earth’s global temperature for 61 years, providing a recent review of the emerging literature as well. Through a statistical approach based on maximum entropy, this study supports the results of other techniques that identify a positive impact of CO 2 in the increase of the Earth’s global temperature. Given the well-known difficulties in the measurement of global temperature and CO 2 emissions with high precision, this statistical approach is particularly appealing around climate change science, as it allows the replication of the original time series with the subsequent construction of confidence intervals for the model parameters. To prevent future risks, besides the present urgent decrease of greenhouse gas emissions, it is necessary to stop using the planet and nature as if resources were infinite.

Suggested Citation

  • Pedro Macedo & Mara Madaleno, 2022. "Global Temperature and Carbon Dioxide Nexus: Evidence from a Maximum Entropy Approach," Energies, MDPI, vol. 16(1), pages 1-13, December.
  • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:277-:d:1016337
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    References listed on IDEAS

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    1. Glen P. Peters & Robbie M. Andrew & Tom Boden & Josep G. Canadell & Philippe Ciais & Corinne Le Quéré & Gregg Marland & Michael R. Raupach & Charlie Wilson, 2013. "The challenge to keep global warming below 2 °C," Nature Climate Change, Nature, vol. 3(1), pages 4-6, January.
    2. Costas Varotsos & Yuri Mazei & Elena Novenko & Andrey N. Tsyganov & Alexander Olchev & Tatiana Pampura & Natalia Mazei & Yulia Fatynina & Damir Saldaev & Maria Efstathiou, 2020. "A New Climate Nowcasting Tool Based on Paleoclimatic Data," Sustainability, MDPI, vol. 12(14), pages 1-14, July.
    3. Vladimir F. Krapivin & Costas A. Varotsos & Vladimir Yu. Soldatov, 2017. "The Earth’s Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability," IJERPH, MDPI, vol. 14(8), pages 1-19, August.
    4. Withey, Patrick & Johnston, Craig & Guo, Jinggang, 2019. "Quantifying the global warming potential of carbon dioxide emissions from bioenergy with carbon capture and storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    5. Vinod, Hrishikesh D. & Lopez-de-Lacalle, Javier, 2009. "Maximum Entropy Bootstrap for Time Series: The meboot R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i05).
    6. G. P. Peters & R. M. Andrew & J. G. Canadell & P. Friedlingstein & R. B. Jackson & J. I. Korsbakken & C. Quéré & A. Peregon, 2020. "Carbon dioxide emissions continue to grow amidst slowly emerging climate policies," Nature Climate Change, Nature, vol. 10(1), pages 3-6, January.
    7. Vinod, Hrishikesh D., 2006. "Maximum entropy ensembles for time series inference in economics," Journal of Asian Economics, Elsevier, vol. 17(6), pages 955-978, December.
    8. Greg H. Rau & Heather D. Willauer & Zhiyong Jason Ren, 2018. "The global potential for converting renewable electricity to negative-CO2-emissions hydrogen," Nature Climate Change, Nature, vol. 8(7), pages 621-625, July.
    9. Myles R. Allen & David J. Frame & Chris Huntingford & Chris D. Jones & Jason A. Lowe & Malte Meinshausen & Nicolai Meinshausen, 2009. "Warming caused by cumulative carbon emissions towards the trillionth tonne," Nature, Nature, vol. 458(7242), pages 1163-1166, April.
    10. Philippe Goulet Coulombe & Maximilian Gobel, 2021. "On Spurious Causality, CO2, and Global Temperature," Papers 2103.10605, arXiv.org.
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