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The Impact of the COVID-19 Pandemic on the Volume of Fuel Supplies to EU Countries

Author

Listed:
  • Izabela Dembińska

    (Faculty of Economics and Engineering of Transport, Maritime University of Szczecin, 70-507 Szczecin, Poland)

  • Agnieszka Barczak

    (Faculty of Economics, West Pomeranian University of Technology, 71-270 Szczecin, Poland)

  • Katarzyna Szopik-Depczyńska

    (Institute of Management, University of Szczecin, 71-004 Szczecin, Poland)

  • Irena Dul

    (SEC (Szczecińska Energetyka Cieplna), 70-653 Szczecin, Poland)

  • Adam Koliński

    (Poznan School of Logistics, 61-755 Poznań, Poland)

  • Giuseppe Ioppolo

    (Department of Economics, University of Messina, 98122 Messina, Italy)

Abstract

The COVID-19 pandemic is undoubtedly a destructive factor, strongly affecting the economic fields. From the perspective of the countries affected by the pandemic, almost all sectors of the economy saw declines in economic indicators. First, the lockdown and its social consequences contributed to this. The increasing time perspective since the outbreak of the COVID-19 pandemic implies increasingly more studies analyzing its impact on various economic spheres. The aim of the research is to determine the difference in the level of fuel supplies between a pandemic situation and a situation where a pandemic would not occur. We assumed that the pandemic is a determinant of the decline in fuel supplies. The subjects of the analysis were the following fuels: kerosene-type jet fuel, gas oil and diesel oil, motor gasoline, and oil products. The countries of the European Union were analyzed. Monthly data from 2015–2021 provided by Eurostat were used for the analyses. The forecasts for 2020–2021 were determined using the exponential smoothing method. The assumption was shown to be accurate in the case of kerosene-type jet fuel, gas oil, and diesel oil. In this case, there was a clear drop in the level of supplies. The analysis of forecasts shows that if it were not for the COVID-19 pandemic, in the years 2020–2021, in accordance with the forecasts obtained, approximately 31,495 thousand tons of kerosene-type jet fuel and 11,396 thousand tons of gas oil and diesel oil would have been additionally supplied to the EU countries. For oil products, supply volumes also decreased, but unlike previously mentioned fuels, supply levels had not recovered to pre-pandemic levels by the end of 2021. On the other hand, the forecast of deliveries indicates the volume of 95,683 thousand tons of oil products.

Suggested Citation

  • Izabela Dembińska & Agnieszka Barczak & Katarzyna Szopik-Depczyńska & Irena Dul & Adam Koliński & Giuseppe Ioppolo, 2022. "The Impact of the COVID-19 Pandemic on the Volume of Fuel Supplies to EU Countries," Energies, MDPI, vol. 15(22), pages 1-18, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8439-:d:969813
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    References listed on IDEAS

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    1. Robert G. Brown & Richard F. Meyer, 1961. "The Fundamental Theorem of Exponential Smoothing," Operations Research, INFORMS, vol. 9(5), pages 673-685, October.
    2. Dariusz Tloczynski & Malgorzata Wach-Kloskowska & Sebastian Susmarski, 2021. "The Impact of COVID 19 on the Aviation Fuel Supply Chain in the Face of Changes in Air Traffic Service: Case Study of one of the Polish Airports," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 623-633.
    3. Richard S Gray & Mohammad Torshizi, 2021. "Update to agriculture, transportation, and the COVID‐19 crisis," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(2), pages 281-289, June.
    4. Smith, L. Vanessa & Tarui, Nori & Yamagata, Takashi, 2021. "Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions," Energy Economics, Elsevier, vol. 97(C).
    5. Agnieszka Barczak & Izabela Dembinska & Lukasz Marzantowicz & Katarzyna Nowicka & Katarzyna Szopik-Depczynska & Tomasz Rostkowski, 2020. "The Impact of Unpredictable Factors on the Uncertainty’s Structure in the Management of Logistics Processes," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 186-200.
    6. Billah, Baki & King, Maxwell L. & Snyder, Ralph D. & Koehler, Anne B., 2006. "Exponential smoothing model selection for forecasting," International Journal of Forecasting, Elsevier, vol. 22(2), pages 239-247.
    7. Wan, Daoxia & Xue, Rui & Linnenluecke, Martina & Tian, Jinfang & Shan, Yuli, 2021. "The impact of investor attention during COVID-19 on investment in clean energy versus fossil fuel firms," Finance Research Letters, Elsevier, vol. 43(C).
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