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Analysis of the Impact of the COVID-19 Pandemic on the Value of CO 2 Emissions from Electricity Generation

Author

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  • Agata Jaroń

    (Faculty of Security, Logistics and Management, Military University of Technology, 00-908 Warsaw, Poland)

  • Anna Borucka

    (Faculty of Security, Logistics and Management, Military University of Technology, 00-908 Warsaw, Poland)

  • Rafał Parczewski

    (Faculty of Security, Logistics and Management, Military University of Technology, 00-908 Warsaw, Poland)

Abstract

The study analyzed the impact of the COVID-19 pandemic on the carbon dioxide emissions from electricity generation. Additionally, monthly seasonality was taken into account. It was assumed (research hypothesis) that both the COVID-19 pandemic (expressed in individual waves of infection cases) and the month have a significant impact on CO 2 emissions. Analysis of variance (ANOVA) and non-parametric Kruskal–Wallis tests were used to evaluate the significance of the influence of individual explanatory variables on the CO 2 emission. The identification of the studied series (CO 2 emission) was first made by means of a linear regression model with binary variables and then by the ARMAX model. The analysis shows that in the consecutive months and periods of the COVID-19 pandemic, CO 2 emissions differ significantly. The highest increase in emissions was recorded for the second wave of the pandemic, as well as in January and February. This is due to the overlapping of both the increase in infections (favoring stays at home) and the winter season. It can be concluded that working plants, schools and factories had the same demand for electricity, but sources of increased consumption were people staying at home and in hospitals as a result of deteriorated health, isolation or quarantine.

Suggested Citation

  • Agata Jaroń & Anna Borucka & Rafał Parczewski, 2022. "Analysis of the Impact of the COVID-19 Pandemic on the Value of CO 2 Emissions from Electricity Generation," Energies, MDPI, vol. 15(13), pages 1-15, June.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4514-:d:844226
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    References listed on IDEAS

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    Cited by:

    1. Anna Borucka, 2023. "Seasonal Methods of Demand Forecasting in the Supply Chain as Support for the Company’s Sustainable Growth," Sustainability, MDPI, vol. 15(9), pages 1-21, April.

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