AIS VE TİCARET VERİLERİ KULLANILARAK SERA GAZI EMİSYONU VE EĞİLİM TAHMİNİ

Yıl 2022, Cilt: 9 Sayı: Special Issue 2nd International Symposium of Sustainable Logistics “Circular Economy”, 107 - 121, 09.12.2022

Thuta Kyaw Win , Daisuke Watanabe , Shigeki Torıumı

https://doi.org/10.54709/iisbf.1181251

Öz

Günümüzde karbonsuzlaştırma ve sera gazı (GHG) emisyonlarını azaltma girişimleri nedeniyle sıvılaştırılmış doğal gaz (LNG) alternatif bir denizcilik yakıtı olarak yaygın bir şekilde kullanılmaya başlanmıştır. Japonya en büyük küresel LNG ithalatçısı ve en büyük ham petrol ithalatçılarından biri olduğundan, bu çalışma LNG ve tanker taşımacılığı ile bunların Japonya'daki emisyonlarına ve ithalat hacimlerine odaklanmaktadır. Bu çalışmada, emisyon tahmin modeli Holtrop-Mennen güç tahmin yöntemine dayalı olarak oluşturulmuştur. Otomatik tanımlama sistemi (AIS) verileri kullanılarak yakıt tüketimi ve sera gazı emisyonları tahmin edilmiştir. Daha sonra, Japonya ticaret istatistikleri kullanılarak uzun vadeli sera gazı emisyonu tahmin edilmiştir. Gemi hareket verileri ve ticaret istatistikleri birleştirildiğinde, Japonya'daki sera gazı emisyonunun tankerler için yıllar içinde azalacağı ve LNG taşıyıcıları için sabit kalacağı öngörülmektedir. Sonuçlar çevre ve ticaret politikalarının oluşturulmasında dikkate alınabilir. Çalışmanın Japonya'daki sıfır emisyon projeleri ve uygulamaları için faydalı bilgiler sağlayacağı umulmaktadır.

Anahtar Kelimeler

otomatik tanımlama sistemi, gemi emisyonu, sera gazları, LNG, Japonya

GREENHOUSE GAS EMISSION AND THEIR TREND PREDICTION USING AIS AND TRADE DATA

Öz

Due to decarbonization and greenhouse gas (GHG) emission reduction attempts nowadays, liquefied natural gas (LNG) has become widely used as an alternative marine fuel. As Japan is the top global LNG importer and one of the largest crude oil importers, this study focuses on LNG and tanker shipping and their emissions in Japan, and import volumes. In this study, the emission estimation model is constructed based on the Holtrop-Mennen power prediction method. Using automatic identification system (AIS) data, fuel consumption and GHG emissions are estimated. Next, long term GHG emission is predicted using hthe Japan trade statistics. Combining the vessel movement data and trade statistics, GHG emission in Japan is projected to decline over years for tankers, and to remain stable for LNG carriers. The results could be considered in formulating environmental and trade policy. It is hoped the study will provide useful insights for zero emission projects and implementations in Japan.

Anahtar Kelimeler

automatic identification system, ship emission, greenhouse gases, LNG, Japan.

Kaynakça

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