IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i11p3264-d567860.html
   My bibliography  Save this article

The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland

Author

Listed:
  • Aurelia Rybak

    (Department of Electrical Engineering and Industrial Automation, Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Aleksandra Rybak

    (Department of Physical Chemistry and Technology of Polymers, Faculty of Chemistry, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

This article presents the research on the analysis of the impact of social isolation caused by the COVID-19 pandemic on gaseous air pollutant concentrations. For this purpose, the authors presented (thermal maps) and analyzed the concentrations of selected gases such as NO 2 , CO, SO 2 , and PM 2.5 particles during the strict quarantine period in Poland and other EU countries. Statistical analysis of the concentration level of these gases was performed. It was noticed that in Poland, Germany, and France, the concentrations of such gases as CO, NO 2 , and PM 2.5 particles decreased, while in Italy and Spain, the tendency was the opposite. To verify whether the discovered dependencies are not a natural continuation of the trends shaping the given phenomenon, the time series of gas and PM 2.5 particle emissions were analyzed. On this basis, the emission forecast up to 2023 was created, using the ARIMA class models. The obtained results allowed to construct five scenarios for the development of NO 2 , CO, SO 2 , and PM 2.5 emissions until 2023, considering the impact of the COVID-19 pandemic. It was stated that in the optimistic scenario, in 2023, a decrease in CO, NO 2 , and PM 2.5 emissions could be achieved by maximums of 51%, 95%, and 28%, respectively.

Suggested Citation

  • Aurelia Rybak & Aleksandra Rybak, 2021. "The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland," Energies, MDPI, vol. 14(11), pages 1-25, June.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3264-:d:567860
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/11/3264/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/11/3264/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    2. He, Chao & Yang, Lu & Cai, Bofeng & Ruan, Qingyuan & Hong, Song & Wang, Zhen, 2021. "Impacts of the COVID-19 event on the NOx emissions of key polluting enterprises in China," Applied Energy, Elsevier, vol. 281(C).
    3. Dieter Helm, 2020. "The Environmental Impacts of the Coronavirus," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(1), pages 21-38, May.
    4. Yalta, A. Talha & Jenal, Olaf, 2009. "On the importance of verifying forecasting results," International Journal of Forecasting, Elsevier, vol. 25(1), pages 62-73.
    5. Oscar Claveria, 2019. "Forecasting the unemployment rate using the degree of agreement in consumer unemployment expectations," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 53(1), pages 1-10, December.
    6. repec:iab:iabjlr:v:53:i:1:p:art.3 is not listed on IDEAS
    7. B. Lahcen & J. Brusselaers & K. Vrancken & Y. Dams & C. Silva Paes & J. Eyckmans & S. Rousseau, 2020. "Green Recovery Policies for the COVID-19 Crisis: Modelling the Impact on the Economy and Greenhouse Gas Emissions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 731-750, August.
    8. Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olga Pilipczuk, 2021. "Determinants of Managerial Competences Transformation in the Polish Energy Industry," Energies, MDPI, vol. 14(20), pages 1-27, October.
    2. Kadir Diler Alemdar & Ömer Kaya & Antonino Canale & Muhammed Yasin Çodur & Tiziana Campisi, 2021. "Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey," Energies, MDPI, vol. 14(18), pages 1-15, September.
    3. Tomasz Wołowiec & Iuliia Myroshnychenko & Ihor Vakulenko & Sylwester Bogacki & Anna Maria Wiśniewska & Svitlana Kolosok & Vitaliy Yunger, 2022. "International Impact of COVID-19 on Energy Economics and Environmental Pollution: A Scoping Review," Energies, MDPI, vol. 15(22), pages 1-26, November.
    4. Shuhui Yu & Xin Guan & Junfan Zhu & Zeyu Wang & Youting Jian & Weijia Wang & Ya Yang, 2023. "Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China," Sustainability, MDPI, vol. 15(11), pages 1-14, June.
    5. Ankitha Nandipura Prasanna & Priscila Grecov & Angela Dieyu Weng & Christoph Bergmeir, 2022. "Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand," Papers 2209.08885, arXiv.org, revised Oct 2022.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hugo S. Gonçalves & Sérgio Moro, 2023. "On the economic impacts of COVID‐19: A text mining literature analysis," Review of Development Economics, Wiley Blackwell, vol. 27(1), pages 375-394, February.
    2. Lenka Mynaříková & Vít Pošta, 2023. "The Effect of Consumer Confidence and Subjective Well-being on Consumers’ Spending Behavior," Journal of Happiness Studies, Springer, vol. 24(2), pages 429-453, February.
    3. Oscar Claveria & Petar Sorić, 2023. "Labour market uncertainty after the irruption of COVID-19," Empirical Economics, Springer, vol. 64(4), pages 1897-1945, April.
    4. Oscar Claveria & Enric Monte & Salvador Torra, 2020. "“Spectral analysis of business and consumer survey data”," AQR Working Papers 2012002, University of Barcelona, Regional Quantitative Analysis Group, revised May 2020.
    5. Gillmann, Niels & Kim, Alisa, 2021. "Quantification of Economic Uncertainty: a deep learning approach," VfS Annual Conference 2021 (Virtual Conference): Climate Economics 242421, Verein für Socialpolitik / German Economic Association.
    6. Shehabi, Manal, 2022. "Modeling long-term impacts of the COVID-19 pandemic and oil price declines on Gulf oil economies," Economic Modelling, Elsevier, vol. 112(C).
    7. Arturas Kaklauskas & Edmundas Kazimieras Zavadskas & Natalija Lepkova & Saulius Raslanas & Kestutis Dauksys & Ingrida Vetloviene & Ieva Ubarte, 2021. "Sustainable Construction Investment, Real Estate Development, and COVID-19: A Review of Literature in the Field," Sustainability, MDPI, vol. 13(13), pages 1-42, July.
    8. António Bento Caleiro, 2021. "Learning to Classify the Consumer Confidence Indicator (in Portugal)," Economies, MDPI, vol. 9(3), pages 1-12, September.
    9. Adriana AnaMaria Davidescu & Simona-Andreea Apostu & Liviu Adrian Stoica, 2021. "Socioeconomic Effects of COVID-19 Pandemic: Exploring Uncertainty in the Forecast of the Romanian Unemployment Rate for the Period 2020–2023," Sustainability, MDPI, vol. 13(13), pages 1-22, June.
    10. Wooi Chen Khoo & Kim Leng Yeah & Shun Yi Hong, 2022. "Modeling unemployment duration, determinants and insurance premium pricing of Malaysia: insights from an upper middle-income developing country," SN Business & Economics, Springer, vol. 2(8), pages 1-25, August.
    11. Oscar Claveria, 2021. "Forecasting with Business and Consumer Survey Data," Forecasting, MDPI, vol. 3(1), pages 1-22, February.
    12. Mihaela, Simionescu, 2020. "Improving unemployment rate forecasts at regional level in Romania using Google Trends," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    13. Sorić, Petar & Lolić, Ivana & Claveria, Oscar & Monte, Enric & Torra, Salvador, 2019. "Unemployment expectations: A socio-demographic analysis of the effect of news," Labour Economics, Elsevier, vol. 60(C), pages 64-74.
    14. Jia, Zhijie & Wen, Shiyan & Lin, Boqiang, 2021. "The effects and reacts of COVID-19 pandemic and international oil price on energy, economy, and environment in China," Applied Energy, Elsevier, vol. 302(C).
    15. Phi-Hung Nguyen & Jung-Fa Tsai & Ihsan Erdem Kayral & Ming-Hua Lin, 2021. "Unemployment Rates Forecasting with Grey-Based Models in the Post-COVID-19 Period: A Case Study from Vietnam," Sustainability, MDPI, vol. 13(14), pages 1-27, July.
    16. Petar Sorić & Blanka Škrabić Perić & Marina Matošec, 2022. "Breaking new grounds: a fresh insight into the leading properties of business and consumer survey indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4511-4535, December.
    17. Oscar Claveria, 2020. "“Measuring and assessing economic uncertainty”," AQR Working Papers 2012003, University of Barcelona, Regional Quantitative Analysis Group, revised Jul 2020.
    18. Oscar Claveria, 2021. "Uncertainty indicators based on expectations of business and consumer surveys," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 48(2), pages 483-505, May.
    19. Xinyue Lin & Lingli Qi & Haoran Pan & Basil Sharp, 2022. "COVID-19 Pandemic, Technological Progress and Food Security Based on a Dynamic CGE Model," Sustainability, MDPI, vol. 14(3), pages 1-18, February.
    20. Periklis Gogas & Theophilos Papadimitriou & Emmanouil Sofianos, 2022. "Forecasting unemployment in the euro area with machine learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 551-566, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3264-:d:567860. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.