Towards More Reliable Aircraft Emission Inventories for Local Air Quality Assessment

Accurate quantification of aircraft emissions and their uncertainties is essential for well-informed policy-making, air quality management, and the development of sustainable airport strategies. This study addresses uncertainties in aircraft emission estimates implemented for local air pollutants with hourly resolution at six European airports. Publicly available flight-tracking data were used to determine aircraft movements and types, but they typically lack detailed information on aircraft engine models, thus contributing to uncertainties in emission factors. Times-in-mode for take-off, climb-out, and approach modes followed International Civil Aviation Organization (ICAO) recommendations, while taxi times, known to vary between airports, were modeled using statistical distributions derived from Eurocontrol, and the contribution of taxi time to overall uncertainty in emission estimates was investigated. Monte Carlo simulation combined with Sobol sensitivity analysis identified the relative contribution of each uncertainty source. On average, the results indicate an uncertainty of 23% for CO, 34% for HC, 7% for NOx, and 21% for PM across the airports analyzed. Overall, the proposed methodology introduces a novel framework utilizing publicly available, hourly resolved flight-tracking data with robust uncertainty analysis to estimate airport-level emissions with enhanced reliability, providing crucial information for local air quality assessment and policy development.