Rocznik Ochrona Środowiska 2026, vol. 28, pp. 649-657
Çağdaş Civelek 
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Niğde Ömer Halisdemir University, Türkiye |
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https://doi.org/10.54740/ros.2026.043 |
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Greenhouse gas (GHG) emissions in Türkiye have shown a continuous increase over the past 35 years, with a total rise of 155.3%. In comparison, agricultural greenhouse gas emissions have increased by 41.8% and currently account for approximately 12% of total GHG emissions, highlighting the sector's significant contribution. Accurately determining and planning future emission levels is crucial for implementing effective mitigation strategies and aligning with European Union regulations. This study presents a comparative analysis of Türkiye's agricultural greenhouse gas emissions with those of the 27 European Union countries for the period 2015–2023 and provides forecasts for the years 2025–2030. The findings indicate that, although Türkiye ranks as the second-highest country in terms of total agricultural greenhouse gas emissions, it ranks ninth lowest in terms of emission intensity. Among the three prediction models evaluated, the Random Forest Regression model demonstrated the best performance, achieving a coefficient of determination (R²) of 0.503, compared to 0.482 for Ridge Regression and −2.048 for Linear Regression.
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greenhouse gas emission, machine learning, agricultural greenhouse
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AMA Style
Civelek Ç. Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting. Rocznik Ochrona Środowiska. 2026; 28. https://doi.org/10.54740/ros.2026.043
ACM Style
Civelek Ç. 2026. Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting. Rocznik Ochrona Środowiska. 28. DOI:https://doi.org/10.54740/ros.2026.043
ACS Style
Civelek Ç. Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting. Rocznik Ochrona Środowiska 2026, 28, 649-657. https://doi.org/10.54740/ros.2026.043
APA Style
Civelek Ç. (2026). Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting. Rocznik Ochrona Środowiska, 28, 649-657. https://doi.org/10.54740/ros.2026.043
ABNT Style
CIVELEK Ç. Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting. Rocznik Ochrona Środowiska, v. 28, p. 649-657, 2026. https://doi.org/10.54740/ros.2026.043
Chicago Style
Çağdaş Civelek. 2026. "Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting". Rocznik Ochrona Środowiska 28, 649-657. https://doi.org/10.54740/ros.2026.043
Harvard Style
Civelek Ç. (2026) "Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting", Rocznik Ochrona Środowiska, 28, pp. 649-657. doi:https://doi.org/10.54740/ros.2026.043
IEEE Style
Ç. Civelek, "Agricultural Greenhouse Gas Emissions in Türkiye: A Comparison with EU-27 Countries and Machine Learning–Based Forecasting", RoczOchrSrod, vol. 28, pp. 649-657. https://doi.org/10.54740/ros.2026.043