Aircraft contrails form through ice crystal nucleation initiated primarily by engine-emitted particles. These ice crystals can lead to persistent contrails, contributing to climate warming, thus making understanding their activation a key target for mitigation strategies. This study presents large eddy simulations (LES) coupled with a refined soot activation model. The microphysical scheme incorporates solute effects through the hygroscopicity parameter (κ), enabling a more realistic representation of water activity during soot particle activation. These numerical simulations utilized a LEAP-1A engine under realistic cruise conditions, examining three scenarios: (i) varying κ (0.0005, 0.005, 0.0142), corresponding to an equivalent fuel sulfur content (FSC) of 50, 410, and 1270 ppm, respectively; (ii) varying initial soot emission indices ( – #/kg-fuel), and (iii) varying initial soot core radii (10–30 nm). The results indicated that reducing κ from 0.0142 to 0.0005 slightly reduced ice particle radii, yet increased the activation fraction by ∼20% due to enhanced water vapor availability. Reducing the initial soot number in two successive steps, from to #/kg-fuel, increased the mean ice particle radius from ∼0.3 μm to 2.4 μm in 1 s and elevated the activated fraction by ∼66%. Larger initial soot core radii enhanced activation by ∼20%, with mean ice particle radius differences reaching ∼80% in around 0.4 s and narrowing to ∼10% by 1s. Additionally, the results highlighted the importance of 3D LES with online-coupled microphysics, whereas the 0D offline box model overpredicted activation more than 50% and misrepresented the κ sensitivity. • Online-coupled 3D LES with hygroscopicity (κ)-based soot activation captures near-field contrail microphysics. • Higher κ / FSC (fuel sulfur content) yields larger ice radii but lower activation due to vapor competition (non-linear effects). • Lower produces larger mean radius, higher activation, and narrower size distributions. • Larger soot core radius increases activation and final radius; smaller cores resist activation via the Kelvin effect. • 0D offline box models overpredict activation and misrepresent κ sensitivity; 3D online coupling is required.
Afkari et al. (Sun,) studied this question.
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