Robust Big-Hit Flight Identification

We define big-hit flights as the smallest subset of daily flights accounting for 80% of the total climate impact, including CO2 and non-CO2 effects. Targeting and optimizing these flights offers the most effective climate impact mitigation with minimal disruption to airspace capacity, operations, and costs. In this study, we present a robust method to identify big-hit flights in the Borealis area, a free route airspace over nine North-Western European countries. Analyzing four months of 2019 with around 10.000 daily flights, we identify big-hit flights and assign days a probability of causing them. Preliminary results show that <15% of all flights are big-hit flights. To ensure robustness, we apply three models with distinct metrics: (1) distance flown through potential contrail regions, (2) a merged algorithmic climate change function (aCCF) accounting for contrails and NOx-induced O3 increase and CH4 depletion, and (3) the contrail cirrus prediction model (CoCiP).