What question did this study set out to answer?

The research aims to evaluate the CO2 efficiency of airlines at Istanbul Airport using machine learning techniques.

January 16, 2026Discover Environment0 citationsOpen Access

Machine Learning Evaluation of Airline CO2 Efficiency at Istanbul Airport

Machine learning based evaluation of airline CO2 efficiency at Istanbul airport

View Full Paper

Ask AI

Bookmark

Authors

Assesses CO2 efficiency in airlines, highlighting the importance of data-informed scheduling for sustainability.

The research aims to evaluate the CO2 efficiency of airlines at Istanbul Airport using machine learning techniques.
Integrated operational flight data with the Atmosfair Airline Index using machine learning.
Developed a multiple linear regression model with total payload and landing frequency as predictors.
Collected flight data from FlightRadar24 for a specific date.
Assessed model performance through adjusted R2, MAE, and RMSE.
Model demonstrated a strong explanatory ability (Adjusted R2 ≈ 0.73).
Found that larger payloads and higher landing frequency significantly improve CO2 efficiency scores.
Model exhibited acceptable predictive accuracy with MAE of 3.82 and RMSE of 4.45.
Contributed a transparent framework aligning with ICAO's net-zero carbon target for 2050.

Cumhur Dülger (2026) studied this question.

View Full Paper

Ask AI

Bookmark

January 16, 2026Discover Environment0 citationsOpen Access

Machine learning based evaluation of airline CO2 efficiency at Istanbul airport

View Full Paper

Ask AI

Bookmark

Authors

Assesses CO2 efficiency in airlines, highlighting the importance of data-informed scheduling for sustainability.

The research aims to evaluate the CO2 efficiency of airlines at Istanbul Airport using machine learning techniques.
Integrated operational flight data with the Atmosfair Airline Index using machine learning.
Developed a multiple linear regression model with total payload and landing frequency as predictors.
Collected flight data from FlightRadar24 for a specific date.
Assessed model performance through adjusted R2, MAE, and RMSE.
Model demonstrated a strong explanatory ability (Adjusted R2 ≈ 0.73).
Found that larger payloads and higher landing frequency significantly improve CO2 efficiency scores.
Model exhibited acceptable predictive accuracy with MAE of 3.82 and RMSE of 4.45.
Contributed a transparent framework aligning with ICAO's net-zero carbon target for 2050.

Cumhur Dülger (2026) studied this question.

View Full Paper

Ask AI

Bookmark