As aviation's contribution to anthropogenic climate change is increasing, the sector aims at reducing its climate effect in accordance with international agreements. The strong and variable non-CO2 effects are complex, making reliable climate effect quantification a necessary first step. To support this, we develop the easy-To-use first-order climate effect estimator for single flights FlightClim v1.0. The tool estimates the flight-specific climate effect with a simplified calculation model, without requiring detailed information on exact routing, amount of fuel burn, or weather conditions. For this purpose, we first analyze a global flight dataset containing detailed trajectories, associated flight emissions, and climate responses. Similar flights are grouped into clusters, and regression formulas are derived to estimate the Average Temperature Response over 100 years (ATR100) for CO2 and non-CO2 effects. To prevent abrupt changes at cluster boundaries, we apply linear smoothing as postprocessing. Second, we compare a Multiple and a Symbolic Regression approach, where choice of method depends on the specific application as they differ in effort and complexity. The two approaches offer similar estimation quality, which shows that the errors are based on the database, the regression parameters as well as the regression error metric and the physical processes rather than on too easy regression models. Both methods are designed for climate footprint assessments due to their simplicity though not suitable for policy measures. Emission trading or monitoring and reporting systems instead require detailed weather and route data to incentivize operational non-CO2 mitigation. Compared to previous studies, our approach relies on a globally representative and considerably larger dataset covering more aircraft types, including most commercial airliners. In addition it improves precision through smoothed clustering and a dedicated parameterization of aircraft size influence on the contrail effects. The resulting climate effect functions are embedded into the Excel-based tool FlightClim v1.0, which implements the formulas of the Multiple Regression approach due to slight qualitative advantages. Requiring only aircraft size and origin-destination airports as input, FlightClim estimates climate effect for CO2, H2O, NOx emissions and contrail-induced cloudiness. It includes per seat allocation and supports different climate metrics.

Commercial supersonic aircraft may return in the near future, offering reduced travel time while flying higher in the atmosphere than subsonic aircraft, thus displacing part of the passenger traffic and associated emissions to higher altitudes. For the first time since 2007, we present a comprehensive multi-model assessment of the atmospheric and radiative effect of this displacement. We use four models (EMAC, GEOS-Chem, LMDz–INCA, and MOZART-3) to evaluate three scenarios in which subsonic aviation is partially replaced with supersonic aircraft. Replacing 4 % of subsonic traffic with Mach 2 aircraft that have a NOx emissions index of 13.8 g (NO2) kg−1 leads to ozone column loss of −0.3 % (−0.9 DU; model range from −0.4 % to −0.1 %), and it increases radiative forcing by 19.1 mW m−2 (model range from 16.7 to 28.1). This forcing is driven by water vapor (18.2 mW m−2), ozone (11.4 mW m−2), and aerosol emissions (−10.5 mW m−2). The use of a Mach 2 concept with low-NOx emissions (4.6 g (NO2) kg−1) reduces the effect on forcing and ozone to 13.4 mW m−2 (model range from 2.4 to 23.4) and −0.1 % (−0.3 DU; model range from −0.2 % to +0.0 %), respectively. If a Mach 1.6 aircraft with a lower cruise altitude and NOx emissions of 4.6 g (NO2) kg−1 is used instead, we find a near-net-zero effect on the ozone column and an increase in the radiative forcing of 3.7 mW m−2 (model range from 0.5 to 7.1). The supersonic concepts have up to 185 % greater radiative effect per passenger kilometer from non-CO2 emissions compared to subsonic aviation (excluding contrail impacts).

We report on an inconsistency in the latitudinal distribution of aviation emissions between the data products of phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP). Emissions in the CMIP6 data occur at higher latitudes than in the CMIP5 data for all scenarios, years, and emitted species. A comparative simulation with the chemistry-climate model ECHAM/MESSy Atmospheric Chemistry (EMAC) reveals that the difference in nitrogen oxide emission distribution leads to reduced overall ozone changes due to aviation in the CMIP6 scenarios because in those scenarios the distribution of emissions is partly shifted towards the chemically less active higher latitudes. The radiative forcing associated with aviation ozone is 7.6% higher, and the decrease in methane lifetime is 5.7% larger for the year 2015 when using the CMIP5 latitudinal distribution of emissions compared to when using the CMIP6 distribution. We do not find a statistically significant difference in the radiative forcing associated with aviation aerosol emissions. In total, future studies investigating the effects of aviation emissions on ozone and climate should consider the inconsistency reported here.