Türkiye’deki Farklı Sektörlere Ait Sera Gazı Emisyon Değerlerinin Çok Katmanlı Algılayıcılar ile Tahmin Edilmesi

Yıl 2020, Cilt: 12 Sayı: 2, 464 - 478, 30.06.2020

Okan Oral , Sinan Uğuz

https://doi.org/10.29137/umagd.646038

Öz

Küresel ısınmaya neden olan karbondioksit (CO₂), Nitröz oksit (N₂O) ve Metan (CH₄) çeşitli sektörler tarafından oluşturulan sera gazlarıdır. Birleşmiş milletler iklim değişikliği çerçeve sözleşmesi (UNFCCC) kuralları gereğince Türkiye’nin de içinde olduğu ülkelerin çeşitli sektörleri tarafından oluşturulan sera gazı emisyon değerleri kayıt altına alınarak takip edilmektedir. Ülkelerin oluşturdukları sera gazı emisyon değerleri zaman içinde bir çok etkene göre farklılık oluşturabilir. Bu yüzden bu değerin tahmin edilmesi ülkeler açısından önemlidir. Bu çalışmada kullanılan ve Avrupa Çevre Ajansından elde edilen veriler, Türkiye’deki üretim, enerji endüstrisi, yerleşim ve ulaşım sektörlerine ait 1990-2014 yılları arasındaki sera gazı emisyon değerlerini içermektedir. Veri seti, bir makine öğrenmesi tekniği olan Çok Katmanlı Algılayıcılar (ÇKA) ile eğitilmiştir. Üç farklı sera gazı için kurulan modeller incelendiğinde elde edilen en yüksek  değeri üretim, enerji endüstrisi, yerleşim ve ulaşım sektörleri için sırasıyla 0.86, 0.93, 0.91 ve 0.95 olarak bulunmuştur. Çalışmada ayrıca 2020 yılında doğaya salınımını gerçekleştirmesi öngörülen üç farklı sera gazına ait emisyon değerleri tahmin edilmiş ve sonuçlar 14 yıllık geçmiş dönem verilerinin ortalaması ile kıyaslanmıştır. Buna göre üretim, enerji endüstrisi ve ulaşım sektörlerinde %64’lere varan oranda artışlar gözlenirken yerleşim sektöründe bazı gazlarda ortalama %15 oranında bir düşüş olacağı tahmin edilmiştir.

Anahtar Kelimeler

Sera gazı emisyon, Makine öğrenmesi, Çok katmanlı algılayıcılar, Yapay sinir ağları

Prediction with Multi-layer Perceptrons of Greenhouse Gas Emission Belonging to Different Sectors in Turkey

Öz

Carbon dioxide CO₂ Nitrous oxide N₂O and Methane CH₄ which cause global warming are greenhouse gases generated by various sectors. Greenhouse gas emissions generated by various sectors of the countries, including Turkey are followed and recorded in accordance with The United Nations Framework Convention on Climate Change (UNFCCC) rules. The greenhouse gas emissions generated by countries may change over time depending on many factors. Therefore, it is important for countries to estimate this value. The data used in this study and obtained from the European Environment Agency include greenhouse gas emissions between the years 1990-2014, belonging to Turkey's production, energy industry, residential and transport sectors.  The data set was trained with Multi Layer Perceptrons (MLP), a machine learning technique. When the models established for three different greenhouse gases were examined, the highest  values obtained were 0.86, 0.93, 0.91 and 0.95 for the production, energy industry, residential and transportation sectors, respectively. In addition, the emission values of three different greenhouse gases, which are foreseen to be released to nature in 2020, were estimated and the results were compared with the average of the data of the last 14 years. Accordingly, production, energy industry and transportation sectors have increased by up to 64%, while it is estimated that there will be an average decrease of 15% in some gases in the residential sector.

Anahtar Kelimeler

Greenhouse gas, Machine learning, Multi-layer perceptron, Artificial neural networks

Kaynakça

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