Managing the EU energy crisis and greenhouse gas emissions: Seasonal ARIMA forecast

  • 398 Views
  • 177 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Changes in the logistics of energy resources and their potential shortage are causing a review of the EU energy policy. The energy sector significantly affects the progress toward achieving climate policy goals due to significt greenhouse gas emissions. The REPowerEU plan, implemented in the EU27 to overcome the energy crisis, requires new forecasts of greenhouse gas emissions due to a change in European energy policy.
This paper aims to examine the consequences of the management of the energy crisis caused by Russia’s invasion of Ukraine on EU climate policy. This study focuses on forecasting greenhouse gas emissions in the EU until 2030 and uses the Seasonal ARIMA model based on quarterly time series in the EU27.
Depending on energy management and changes in energy policy to overcome the energy crisis, a positive or negative scenario for greenhouse gas emissions may occur. An important parameter that should be considered when determining the scenario of the EU energy development according to climate policy was defined by correlation analysis.
According to the negative scenario and under the influence of the effects of the Russian invasion of Ukraine, the value of greenhouse gas emissions in the EU at the beginning of 2030 will be 0.752911 tons per capita. The positive scenario shows greenhouse gas emissions can be reduced to 0.235225 tons per capita.
The study results proved two extreme scenarios of greenhouse gas emissions, depending on how to overcome the energy crisis.

Acknowledgment
The authors appreciate the copyright holder: © European Union, 1995–2022, as well as the source of the extracted data, which is the European Commission website, Eurostat http://ec.europa.eu/eurostat (accessed on 16 October 2022).
This study was funded by the European Union (the project No. 101048079 – EU4SmartED – ERASMUS-JMO-2021-HEI-TCH-RSCH); by the Ministry of Education and Science of Ukraine (projects No. 0122U000788, 0122U000769, 0121U109553, 0120U102001, 0122U000777).
This research was funded by Faculty of Organization and Management of the Silesian University of Technology (grant number: 13/990/BK_23/0178).

view full abstract hide full abstract
    • Figure 1. Cumulative greenhouse gas emissions by economic activity (in tons per capita), EU27, 2010-Q1 – 2022-Q1
    • Figure 2. Greenhouse gas emissions by economic activity (tons per capita), EU27, 2010-Q1 – 2022-Q1
    • Figure 3. Greenhouse gas emissions by electricity, gas, steam, and air conditioning supply activity (top) and its three additive components (tons per capita), EU27, 2010-Q1 – 2022-Q1
    • Figure 4. Greenhouse gas emissions by electricity, gas, steam, and air conditioning supply activity (tons per capita), EU27, 2010-Q1 – 2022-Q1: the rolling mean (red), the rolling standard deviation (black), and the decomposed data (blue)
    • Figure 5. Seasonal ARIMA model diagnostics
    • Figure 6. Forecast of greenhouse gas emissions by electricity, gas, steam, and air conditioning supply activity (tons per capita) by 2030, EU27
    • Table 1. Summary of recent research on sustainable development pathways
    • Table 2. Sectors responsible for greenhouse gas emissions (by economic activity)
    • Table 3. Augmented Dickey-Fuller test of the decomposed data (Greenhouse gas emissions by electricity, gas, steam, and air conditioning supply activity (tons per capita), EU27, 2010-Q1 – 2022-Q1)
    • Table 4. Results of building the Seasonal ARIMA model
    • Table 5. Relationship between energy consumption and CO2 and greenhouse gas emissions
    • Conceptualization
      Aleksandra Kuzior, Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Funding acquisition
      Aleksandra Kuzior, Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Methodology
      Aleksandra Kuzior, Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Project administration
      Aleksandra Kuzior, Liudmyla Saher
    • Supervision
      Aleksandra Kuzior, Ihor Vakulenko, Liudmyla Saher
    • Writing – original draft
      Aleksandra Kuzior, Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Writing – review & editing
      Aleksandra Kuzior, Ihor Vakulenko
    • Data curation
      Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Formal Analysis
      Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Investigation
      Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov
    • Resources
      Ihor Vakulenko, Liudmyla Saher, Serhiy Lyeonov
    • Software
      Ihor Vakulenko, Svitlana Kolosok, Serhiy Lyeonov
    • Validation
      Ihor Vakulenko, Liudmyla Saher, Serhiy Lyeonov
    • Visualization
      Ihor Vakulenko, Svitlana Kolosok, Liudmyla Saher, Serhiy Lyeonov