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Methods for Predicting the Future Evolution of GHG Emissions by Domains

In: Contemporary Issues in Social Science

Author

Listed:
  • Anca Băndoi
  • Claudiu George Bocean
  • Aurelia Florea
  • Lucian Mandache
  • Cătălina Soriana Sitnikov
  • Anca Antoaneta Vărzaru

Abstract

Global warming is a process that takes place 11,500 years after the end of the last Ice Age. The main identified reason is the increased emissions of greenhouse gases (GHGs). Since the nineteenth century, GHG evolution has recorded a quantum leap from the previous linear development. Human is the main factor behind this evolution, through industrialization and the exponential increase of population. Based on these, the chapter’s primary goal was to highlight an original method of predicting the future evolution of GHG emissions in the domains ofEnergy(includingTransportation),Industry Processes and Product Use,Agriculture,andWaste Management. The novelty of the research consisted of testing several variants of functions (power, exponential, inverse trigonometric) to identify, from a group of variants. This optimal function would generate those predictions, which are closest to the real values. The causes that create GHG emissions in each of the four domains were the foundation for the analysis. This chapter focuses on two main subjects: first, the identification of a smooth function to predict the evolution of GHG emissions, and second, the function’s use to estimate the projections of GHG emissions in the coming years for the four domains:Energy(includingTransportation),Industry Processes and Product Use,Agriculture, andWaste Management. An observation was that the weights of these four domains remain relatively the same despite the reductions in the total GHG emissions.

Suggested Citation

  • Anca Băndoi & Claudiu George Bocean & Aurelia Florea & Lucian Mandache & Cătălina Soriana Sitnikov & Anca Antoaneta Vărzaru, 2021. "Methods for Predicting the Future Evolution of GHG Emissions by Domains," Contemporary Studies in Economic and Financial Analysis, in: Contemporary Issues in Social Science, volume 106, pages 281-306, Emerald Group Publishing Limited.
  • Handle: RePEc:eme:csefzz:s1569-375920210000106018
    DOI: 10.1108/S1569-375920210000106018
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