İçeriğe geç
akaturk Akademik ölçüm

Makale detayı · 2023 · article

European Union 2030 Carbon Emission Target: The Case of Turkey

Dergi Sustainability ISSN kaydı başka bir dergiye işaret ediyor; ad YÖKSİS kaydından.
ISSN2071-1050
YÖKSİS OpenAlex Açık erişim · gold Üst %10
Yıl2023
Atıf32OpenAlex
Atıf31Semantic Scholar · 2 etkili
Yüzdelik%97,7
FWCI9,761,00 = dünya ortalaması
Scopus (SJR)Q1
WoS (JCR)Q2

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıSustainability
  • Katalog eşleşmesi (ISSN)Sustainability (Switzerland)
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

Climate awareness caused by the threat of global warming is the number one agenda item for developed and developing economies. Plans developed in this context, environmentally friendly trends in economic activities, and countries’ efforts to adapt to sustainable development have enabled new road maps. The most important of these efforts is the Paris Climate Agreement signed in 2015 and the Green Deal implemented by the European Union (EU) within the framework of this agreement. In this study, the carbon emissions of Turkey, which has important trade relations with the EU, were estimated using machine learning techniques, and a prediction was made for 2030 based on the results obtained. These results were evaluated in line with the targets of the Green Deal. The R2 of support vector regression (SVR), which was applied in the model as one of the machine learning techniques, was found to be 98.4%, and it was found to have the highest predictive power. This technique was followed by multiple linear regression (MLR) with a 97.6% success rate and artificial neural networks (ANN) with a 95.8% success rate, respectively. According to the estimates achieved with the most successful model, SVR, Turkey’s carbon emissions are expected to be 723.97 million metric tons (mt) of carbon dioxide (CO2) in 2030, the target year set by the EU. This level is 42% higher than the target that needs to be achieved given the data existing in 2019. According to these results, Turkey will not be able to reach the targets set by the EU unless it increases its coal-based energy consumption and provides incentives for renewable energy sources.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

32atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yerel katalogda bu makaleye atıf yapan 30 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).

  1. 2024 Estimation Of Turkeys Carbon Dioxide Emission with Machine LearningAtıf 16 · OpenAlex
  2. 2024 Development of a Forecasting Framework Based on Advanced Machine Learning Algorithms for Greenhouse Gas EmissionsAtıf 13 · OpenAlex
  3. 2024 Yeni Medyanın Sürdürülebilirlik Bakış Açısına Göre İncelenmesi: Bibliyometrik AnalizAtıf 13 · OpenAlex
  4. 2024 Yeni Medyanın Sürdürülebilirlik Bakış Açısına Göre İncelenmesi: Bibliyometrik AnalizAtıf 13 · OpenAlex
  5. 2025 Estimation of CO2 Emissions in Transportation Systems Using Artificial Neural Networks, Machine Learning, and Deep Learning: A Comprehensive ApproachAtıf 9 · OpenAlex
  6. 2025 Analysing Social Media Discourse on Electric Vehicles with Machine LearningAtıf 8 · OpenAlex
  7. 2025 Analysing Social Media Discourse on Electric Vehicles with Machine LearningAtıf 8 · OpenAlex
  8. 2025 Analysing Social Media Discourse on Electric Vehicles with Machine LearningAtıf 8 · OpenAlex
  9. 2025 Analysing Social Media Discourse on Electric Vehicles with Machine LearningAtıf 8 · OpenAlex
  10. 2025 Analysing Social Media Discourse on Electric Vehicles with Machine LearningAtıf 7 · OpenAlex

Yazarlar

6
  1. MEHMET KAYAKUŞ AKDENİZ ÜNİVERSİTESİ 1
  2. MUSTAFA TERZİOĞLU 2
  3. DİLŞAD ERDOĞAN 3
  4. SELİN AYGEN ZETTER AKDENİZ ÜNİVERSİTESİ 4
  5. ÖNDER KABAŞ 5
  6. Georgiana Moiceanu 6