Hybrid Model for Assessing the Carbon Footprint in Pilot Training

The research aimed to create a hybrid model for assessing the carbon footprint of pilots’ education at a flight school, taking into account the level of implementation of green infrastructure by the educational institution, while excluding indirect emissions from the model. The study implemented an approach that combines fuzzy set theory with expert evaluation methods, utilizing membership functions and convolution mechanisms to incorporate subjective expert assessments into formalized numerical measures. The research was focused on two research questions: Does the proposed hybrid model allow for a practical assessment of a pilot’s carbon footprint during his training? Does the hybrid model provide the ability to automatically determine the level of carbon footprint of an aviation educational institution and generate substantiated recommendations for the strategic management of sustainable development of the educational process? The resulting model enables a quantitative assessment of individual CO2 emissions during pilot training and provides collective insights into the overall carbon footprint, accounting for the green infrastructure’s level of implementation. The hybrid model was tested and validated using real data from the Technical University of Košice (Slovakia) within the “PILOT” study program (2022–2025). The experimental calculations are based on the Viper SD4, a homogeneous aircraft type. The model is designed to account for multiple aircraft types through weighted aggregation, a feature that can be used in future institutional implementations. These recommendations are practical for managers and specialists at aviation educational institutions, environmental analysts, curriculum developers, and policymakers focused on sustainable development. At the current stage, the model primarily captures direct training-related and institution-level operational emissions, while indirect emissions were included only to a limited extent because of insufficiently available and non-systematically recorded data. Therefore, the proposed framework should be interpreted as an operational decision-support model rather than a full greenhouse gas inventory covering all indirect emission sources.