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Leveraging the trend analysis for modeling of the greenhouse gas emissions associated with coal combustion.
Karakurt, Izzet; Avci, Busra Demir; Aydin, Gokhan.
Afiliação
  • Karakurt I; Mining&Energy Research Group, Mining Engineering Department, Karadeniz Technical University, Ortahisar, 61080, Trabzon, Turkey. karakurt@ktu.edu.tr.
  • Avci BD; Mining&Energy Research Group, Mining Engineering Department, Karadeniz Technical University, Ortahisar, 61080, Trabzon, Turkey.
  • Aydin G; Mining&Energy Research Group, Mining Engineering Department, Karadeniz Technical University, Ortahisar, 61080, Trabzon, Turkey.
Article em En | MEDLINE | ID: mdl-39150668
ABSTRACT
In this paper, it is aimed, for the first time, at deriving simple models, leveraging the trend analysis in order to estimate the future greenhouse gas emissions associated with coal combustion. Due to the expectations of becoming the center of global economic development in the future, BRICS-T (Brazil, the Russian Federation, India, China, South Africa, and Turkiye) countries are adopted as cases in the study. Following the models' derivation, their statistical validations and estimating accuracies are also tested through various metrics. In addition, the future greenhouse gas emissions associated with coal combustion are estimated by the derived models. The results demonstrate that the derived models can be successfully used as a tool for estimating the greenhouse gas emissions associated with coal combustions with accuracy ranges from at least 90% to almost 98%. Moreover, the estimating results show that the total amount of greenhouse gas emissions associated with coal combustions in the relevant countries and in the world will increase to 14 BtCO2eq and 19 BtCO2eq by 2035, with an annual growth of 2.39% and 1.71%, respectively. In summary, the current study's findings affirm the usefulness of trend analysis in deriving models to estimate greenhouse gas emissions associated with coal combustion.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article