Examining Determinants of Transport-Related Carbon Dioxide Emissions by Novel Super Learner Algorithm

Kartal M. T., PATA U. K., Depren Ö.

Transportation Research Part D: Transport and Environment, cilt.136, 2024 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 136
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1016/j.trd.2024.104429
  • Dergi Adı: Transportation Research Part D: Transport and Environment
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Applied Science & Technology Source, Aquatic Science & Fisheries Abstracts (ASFA), Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, EconLit, Environment Index, Geobase, INSPEC, Metadex, Pollution Abstracts, Civil Engineering Abstracts
  • Anahtar Kelimeler: Artificial intelligence, Determinants, Super learner algorithm, Top transport-related CO2 emitting countries, Transport-Related CO2 Emissions
  • Hatay Mustafa Kemal Üniversitesi Adresli: Evet

Özet

Combating carbon dioxide (CO2) emissions across sectors becomes inevitable due to negative impacts. The transport sector takes place among the most important sectors. Accordingly, the study examines transport-related CO2 (TCO2) emissions in the top four emitting countries (namely, the United States, Canada, Saudi Arabia, & Australia) by considering six explanatory variables, using data from 1990/Q1 to 2020/Q4, and performing an artificial intelligence approach. The outcomes show fresh insights that (i) super learner (SL) algorithm overwhelms other machine-learning algorithms in terms of model performance; (ii) energy intensity has an increasing impact on TCO2 emissions, whereas others (e.g., financial development, income, globalization, oil use, & urbanization) have a mixed impact across countries; (iii) the influential variables have some critical thresholds, where the power of impacts differentiate across these limits. Hence, the SL algorithm presents robust outcomes for TCO2 emissions. Accordingly, a set of policy endeavors for the countries examined are also discussed.