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.

While the mean age-of-air, the time from entry into the stratosphere to any interior point, can be derived from trace gas observations, the mean residence time, the time from an interior point to its exit, is constrained only through rare events such as volcanic eruptions. Here we show that age-of-air and residence time are not independent but obey a compensation rule: their opposing latitudinal gradients cancel to produce near-uniform mean total transit times at each altitude. This uniformity reveals a previously unrecognised constraint within the Brewer-Dobson circulation, where rapid tropical ascent is necessarily balanced by prolonged interior residence, and vice versa. Exploiting this constraint, we infer global residence time fields directly from age-of-air observations and reproduce the observed residence time of the 2022 Hunga Tonga water vapour plume within published uncertainty ranges. Our framework transforms age-of-air, routinely measured by existing satellite networks, into a continuous observational constraint on stratospheric residence time. This opens a path to monitor whether the acceleration of stratospheric circulation under climate change shortens or prolongs the persistence of high-altitude emissions.

Emissions from land-based transport, aviation, and shipping contribute significantly to climate change. Besides CO2, these emissions include short-lived compounds that affect air quality but are also climatically relevant. We use a global chemistry-climate model to show that the climate effects of these non-CO2 emissions are substantial across all transport sectors both now and in the future. In sum, the non-CO2 impacts result in a cooling, which offsets the positive climate forcing from transport-induced CO2 by around 80% at present and between 25 and 60% in different scenarios for 2050. The trade-off that air pollutants mitigate global warming is strongly reduced in a future scenario with low anthropogenic emissions, where even small remaining amounts of non-CO2 compounds cause significant cooling as they are released in a very clean atmosphere. Our findings emphasize the need to take non-CO2 effects into account when assessing climate protection strategies for the transport sectors.

Abstract. Contrail-avoidance is a widely studied measure to reduce the non-CO2 climate effect of aviation. However, some mitigation gain is likely to be compromised through increased emissions (CO2, NOx, and H2O) and their climate effect. Here, we analyse the impact of contrail-optimised flights on the overall net climate benefit. We evaluate more than 4,000 flights with large contrail impact traversing Northern Europe in 2023, each with two trajectory options: the filed trajectory submitted to the network manager and a contrail-optimised trajectory, allowing only vertical deviations and a maximum fuel penalty of 2%. Our model setup is based on the European Unions's non-CO2 monitoring, reporting and verification (MRV) framework, modelling contrails with the contrail cirrus prediction model (CoCiP) and employing the algorithmic climate change functions (aCCFs) for NOx and H2O effects. This paper highlights three points: First, while 93% of contrail-optimised flights emit more NOx (on average +2.5%), they emit it at lower, less climate-sensitive altitudes, so only 65% of flights exhibit an increased NOx climate effect (+1.1%, measured in efficacy-weighted global warming potential over 100 years, EGWP100), with considerable spatial and daily variability. Second, we find a risk of only 2% that the net climate benefit is not achieved when optimising for contrails alone, whereas using forecast weather data poses a far greater risk, causing optimisation to fail in ~15% of cases. The net climate benefit, however, is reduced from −16.5% to −11.1%, measured in EGWP100, when including NOx and H2O effects in the evaluation. Third, we find that the results are consistent to the choice of climate metric, with net climate benefit rates of −11.1%, −12.4%, and −16.2% obtained for EGWP100, the average temperature response over 100 years (ATR100), and EGWP20, respectively. We conclude that savings attributed to contrail-avoidance under a hard constraint on extra fuel and considering flights with large contrail impact only, exceed the NOx and H2O penalties. We do, however, recommend further research that accounts for model uncertainties, in order to determine whether the clear dominance of contrail over NOx (and H2O) effects identified here for contrail-optimised trajectories remains robust.

Aviation emissions are responsible for climate impacts through both carbon dioxide emissions and other emissions, in particular, of nitrogen oxides, water vapour, particulates, and contrail formation. In December 2022, the European Commission, Parliament and Council agreed to revise the European Union Emission Trading System for aviation. As such, from January 1, 2025, aircraft operators must monitor non-carbon dioxide climate effects, but suitable metrics for climate impact, handling of uncertainties and practical implementation are still under discussion or at least heavily debated. In this perspective, we propose a procedure for how to include non-carbon dioxide aviation effects into political frameworks. The main goal must be to create incentives for climate change mitigation for the aviation industry. Uncertainties in atmospheric processes need to be appropriately incorporated to minimise risk, and pilot projects are required to test implementation capabilities. Analysing risk, employing consistent monitoring, and determining economic effects will provide scientific grounds for including non-carbon dioxide effects in the European Union Emission Trading System. For the inclusion of aviation non-carbon dioxide climate effects in the European Union Emission Trading System, uncertainties in atmospheric processes can be addressed through careful calculation and risk assessment.

Quantitative assessments of CO2 and non-CO2 climate effects of aviation emissions require the choice of a physical climate metric. In consequence estimating mitigation potentials or integrating non-CO2 effects in legislation or cost-benefit analyses require the choice of a metric. However, since various metrics are currently in use and estimates and numbers vary over different climate metrics, it is desirable and necessary to have conversion factors available which allow to convert from one physical climate metric to another. Hence, we introduce an approach how such climate metric conversion factors can be calculated and present an initial set based on the climate response model AirClim. These conversion factors can be used for various applications. These include, for example, converting results from models that only calculate radiative forcing into a climate metric and scaling model results calculated with different metrics to the same one for one-to-one comparisons.In addition, the conversion factors can be used for convenient analyses of the influence of metric choice on the results of a climate assessment. To this end, it is shown here how the ratio of non-CO2 to CO2 differs depending on the choice of metric. The metrics GWP, EGWP, GTP and ATR are analysed, each with a time horizon of 20, 50, 100 and 500 years. The choice of the temporal emission curve is also analysed and it is shown exemplarily why a sequence of pulse emissions does not provide the same climate metric result as constant emissions.

Aviation emissions at typical cruise altitude (~9-13 km) consists of a blend of chemical components including aerosols and their precursor gases, affecting the Earth's radiation budget via both direct and indirect aerosol effects, resulting in a significant climate effect. Current estimates of aviation-induced climate effects are based on coarse-resolution global aerosol-climate models, which are not able to resolve the microphysical processes at the aircraft plume scale. This results in large uncertainties in the aviation-induced impact on aerosol number and size, which are key quantities for estimating the aerosol indirect effect, especially for low-level liquid-phase clouds. A double-box aircraft exhaust plume model is developed to explicitly simulate the aerosol microphysics inside the dispersing aircraft exhaust plume, together with a simplified representation of the vortex regime (which begins ∼ 10 s after emission and captures the dynamics of aerosol particle interactions with contrail ice particles). This study focuses specifically on sulfate (SO4) and soot aerosols, as well as the total number concentration of aviation-induced aerosol particles. The plume model is used to quantify aviation-induced aerosol number concentrations at the end of the dispersion regime where the exhaust has dispersed on scales resolved by global models (~46 h), and the results are compared with those from the instantaneous dispersion approach commonly used in global models. The difference between the two approaches is defined as the plume correction. For typical North Atlantic cruise conditions, the plume correction ranges from −15% (with contrail ice in the vortex regime) to −4.2% (without contrail ice). A tendency-based process analysis shows that the negative value of the plume correction is due to the higher efficiency of coagulation process in the plume approach, leading to lower total particle number concentrations compared to the instantaneous dispersion approach. Sensitivity studies performed for different world regions highlight the role of background conditions for the plume-scale processes, with the plume correction varying between −12 % for Europe and −42 % for China. Parametric studies performed on various aviation emission parameters used to initialise the plume model demonstrate the strong influence of contrail ice in the vortex regime, which substantially reduces aerosol number concentrations in the plume approach. They also show a large sensitivity towards aviation fuel sulfur content, as SO2 emissions and subsequent H2SO4 formation are key drivers of nucleation. The plume model can be directly implemented in coarse-resolution global aerosol–climate models or used as offline parametrisation to constrain quantifications of the climate effects of aviation-induced aerosol particles.

The climate impact of aviation resulting from both CO_2 emissions and non-CO_2 effects is gaining attention from aviation stakeholders seeking to identify potential mitigation options. There is a need to consolidate the use of assessment methods and climate metrics, which are required to convert aviation non-CO_2 effects into CO_2 -equivalent emissions. We provide an overview of the operational, technological and scenario-based climate impact assessment methods that have been applied in literature as well as considerations and requirements for the choice of climate metric. We propose a four-layer technology climate impact assessment methodology, which includes: (1) the technology parameters, such as entry into service and temporal and spatial network use; (2) the calculation of three-dimensional aircraft trajectories and emission inventories; (3) the calculation of radiative forcing and induced temperature change time series; and (4) the overall climate impact, measured using a climate metric. We recommend two climate metrics that best fulfill the requirements, the Average Temperature Response (ATR100) and the Efficacy-weighted Global Warming Potential (EGWP100), both over 100 years. Additionally, we discuss further steps, such as the understanding of the most sensitive parameters in this approach, how uncertainties can be included to provide robust estimates, aspects of verification and update possibilities for new findings in research.

Aviation-induced aerosols, particularly composed of sulfate (SO4), can interact with liquid clouds by enhancing their reflectivity and lifetime, thereby exerting a cooling effect. The magnitude of these interactions, however, remains highly uncertain and may even offset the combined warming from aviation's other climate forcers depending on spatiotemporal factors such as emission altitude and season. Here, we introduce AIRTRAC v2.0, the latest advancement of the Lagrangian tagging submodel within the Modular Earth Submodel System (MESSy), and the first submodel to provide aviation-specific sulfate tagging in this framework. AIRTRAC contributes to lowering uncertainty by tracking global contributions of aviation-emitted sulfur dioxide (SO2) and sulfuric acid (H2SO4) to SO4 formation. Using a sulfur-species tagging approach for SO2, H2SO4 and SO4, it enables the characterization of transport patterns and highlights atmospheric regions with enhanced potential for aerosol-cloud interactions. In contrast to some of the existing sulfate tagging models, AIRTRAC considers a full range of microphysical processes along trajectories. To investigate sulfate transport from aviation, two global simulations were performed for January-March and July-September 2015, using pulse emissions of SO2 and H2SO4 distributed across a cruise altitude of 240 hPa (similar to 10.6 km) based on the aviation SO2 inventory of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Comparisons of AIRTRAC-derived SO4 distributions with perturbation-based simulations under analogous conditions show reasonable agreement. Using AIRTRAC v2.0, we estimate median SO2 and SO4 lifetimes of 22 d and 2.1 months, respectively, in northern winter, and 14 d and 2.2 months in summer, consistent with volcanic eruption modeling studies and observational benchmarks involving high-altitude SO2 injection. The median SO4 production efficiency during summer was found to be statistically significantly larger by 144 % compared to winter, likely due to a more efficient oxidation of SO2. Large-scale circulation patterns and emission latitude may enhance SO4 lifetimes: tropical emissions can be upwelled into the stratosphere past 100 hPa (similar to 16 km) over time, while high-latitude emissions can persist longer because they may be directly injected above the climatological tropopause. AIRTRAC v2.0 currently excludes SO2 oxidation from aviation nitrogen oxides (NOx) and does not tag other species such as black carbon. Owing to its flexible design, however, the approach can be readily extended to additional aerosols. Overall, AIRTRAC v2.0 offers the novel capability to track the atmospheric transport of aviation-emitted SO2, H2SO4 and SO4, providing critical insights into one of aviation's most uncertain climate impacts.

We use global atmospheric chemistry models (GACMs) to understand the extent to which NOx emissions from ships affect the surface ozone concentration and its seasonal cycle over continental regions. Here we use three different attribution approaches: NOx-tagged, combined-tagged and perturbation; implemented in three different GACMs, for understanding the qualitative and quantitative differences in employing these approaches for attributing surface ozone to NOx emitted from ships sailing over various marine regions. Using the NOx-tagged method, we attribute ∼10 % contribution of ship NOx emissions to the simulated surface ozone over the receptor regions considered in our study. The summer peak in this contribution (eg. Over NW Europe) was mainly from NOx emissions over nearby marine regions (such as Baltic and North Seas). During the non-summer months, we simulate large contributions to surface ozone from remote marine regions (such as North Pacific). The combined-tagged approach attributes only ∼7.7 % relative contribution from ship-tagged component, which is a smaller relative contribution compared to the NOx-tagged approach, due to the attribution considering an equally weighted small contribution of reactive carbon emitted from ships. Perturbation approach simulates the impact of changing NOx emissions on surface ozone concentration, which in our study is ∼2.3 % of the ozone in the unperturbed simulation. This impact simulated using the perturbation approach is smaller compared to the contributions simulated using the tagging approaches discussed above. We explore the reason for the smaller impact simulated using the perturbation approach compared to the tagged contributions, by simulating NOx-tagged and combined-tagged perturbations in ship NOx emissions and quantify the role of both perturbed and unperturbed tagged emission sources in contributing to the response to perturbation. The non-tagged surface ozone response to ship-NOx perturbation is ∼2.5-5 times smaller than the response from the ship-tagged ozone component, because of compensating negative responses due to reduction in ozone production from other contributing tagged-components such as land-based natural and anthropogenic ozone precursor NOx sources.

Abstract. 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.

Abstract. Sustainable aviation fuels (SAFs) reduce CO2 life-cycle emissions and the climate effect of contrail-induced cirrus cloudiness (CiC). In contrast to the CO2 emissions of air traffic, the CiC climate effect varies strongly from flight to flight. Hence, SAF allocation to specific flights can maximise climate mitigation efforts for limited amounts of SAF, especially as long as SAF supply is meagre. In this study, we assess the climate-optimal SAF distribution for the flights departing from Copenhagen Airport (CPH) and determine the potential climate benefit achievable through this measure. The study particularly targets year 2030, when the 6 % SAF mandate by ReFuelEU Aviation is expected to allow large climate benefits through targeted SAF use and time still remains for infrastructural adaptions. For this, we use the AirClim model with a refined SAF parameterisation that considers non-volatile particulate matter (nvPM) reduction dependency on SAF blending ratio. We are allocating SAF to those flights that have the largest CiC climate effect to fuel use ratio in a climatological sense. In our scenario simulations, the additional climate benefit through targeted SAF use is quantified and the tradeoff between larger SAF blending ratios for less flights as a consequence of the limited SAF amount is analysed. Targeted use of the 6 % SAF can enhance the role of CiC regarding climate benefit of SAF from 20 % (uniform use) to almost 50 % (targeted use) when the optimal SAF blending ratio is chosen. In our results for CPH in 2030, this leads to a total additional reduction of 60 kt CO2e. However, the results show large uncertainties and strongly vary with choice of climate metric as well as with focus on long-term or short-term climate goals and depend on the specific flight plan. In addition, we quantify how much of the additional climate benefit would be sacrificed if a semi-optimal flight selection was chosen that potentially could reduce logistical cost by decreasing the number of SAF allocated flight routes. The results of this study set ground for cost-benefit analyses that take into account all airport operations associated with targeted SAF use at Copenhagen Airport.

Aviation has long been linked to environmental problems, including pollution, noise, and climate change. Although CO2 emissions are the primary focus of public discussion, non-CO2 emissions from aviation, such as contrails, nitrogen oxides, or cloud cover caused by aviation, can have comparable impacts on the climate. Previous studies have investigated the impact of different weather conditions on aviation and identified regions that are sensitive to climate change. They have also created data products, such as 4-dimensional climate change functions (CCFs), which enable air traffic management (ATM) to plan for climate-optimized trajectories. However, these functions were only derived for specific regions, seasons, and weather situations [1,2].The presented research focuses on developing methods to determine the sensitivity of the atmosphere to aviation emissions in relation to climate effects. This is necessary to describe spatially and temporally dependent distributions, which are required to determine climate-optimized aircraft trajectories. While previous studies have focused on characterizing the North Atlantic Flight Corridor region [2], this study aims to extend the geographic scope by performing Lagrangian simulations for the extratropical regions of the northern hemisphere. The modular global climate model EMAC was used in this study to investigate contrail evolution on Lagrangian trajectories. The study analyzed the effects of contrails on the temporal evolution of key contrail formation parameters along these trajectories, as well as their effects on radiation in terms of the radiative forcing concept. With this comprehensive model, we can investigate the physical processes that determine the effects of contrails on climate and study their spatial and temporal variations.The project leading to this study was funded by the European SESAR programme under Grant Agreement No. 101114785 (CONCERTO). High performance supercomputing resources were used from the German CARA Cluster in Dresden and the DKRZ Cluster in Hamburg.References: [1] Matthes, S., Lührs, B., Dahlmann, K., Grewe, V., Linke, F., Yin, F., Klingaman, E. and Shine, K. P.: Climate-Optimized Trajectories and Robust Mitigation Potential: Flying ATM4E, Aerospace 7(11), 156, 2020.[2] Frömming, C., Grewe, V., Brinkop, S., Jöckel, P., Haslerud, A. S., Rosanka, S., van Manen, J., and Matthes, S.: Influence of weather situation on non-CO2 aviation climate effects: the REACT4C climate change functions, Atmos. Chem. Phys., 21, 9151–9172, https://doi.org/10.5194/acp-21-9151-2021, 2021.

Mounting evidence has highlighted the role of aviation non-CO2 emissions in anthropogenic climate change. Of particular importance is the impact of contrails, to which recent studies attribute over one-third of the total effective radiative forcing from aircraft operations. However, the relative importance of the aircraft-design-dependent and environmental factors that influence the formation of persistent contrails is not yet well understood. In this paper, we use ERA5 data from the 2010s to better understand the interplay between the factors on a climatological timescale. We identify ice supersaturation as the most limiting factor for all aircraft designs considered, underscoring the importance of accurately estimating ice supersaturated regions. We also develop climatological relationships that describe potential persistent contrail formation as a function of the pressure level and Schmidt-Appleman mixing line slope. We find that the influence of aircraft design on persistent contrail formation reduces with increasing altitude. Compared to a state-of-the-art conventional aircraft with an overall propulsion system efficiency of 0.37, water vapour extraction technologies envisioned for the future have the potential to reduce persistent contrail formation by up to 85.1 %. On the other hand, compared to the same reference, hydrogen combustion and fuel cell aircraft could increase globally averaged persistent contrail formation by 46.5 % and 54.7 % respectively. Due to differing contrail properties, further work is required to translate these changes into climate impacts. This study is a step towards the development of a new and computationally inexpensive method to analyse the contrail climate impact of novel aviation fuels and propulsion technologies.

The climate impact of a flight is determined not only by the amount of aircraft emissions, but also by the time, location, and specific weather conditions at which such emissions occur. As a result, there is the potential of mitigating the climate impact of a flight by optimizing its trajectory. This operational strategy presents trade-offs between minimizing the climate impact from carbon dioxide (CO2), which only depends on the amount of emitted CO2, and minimizing the so-called non-CO2 effects of aviation, due to the radiative forcing from contrails and contrail cirrus, the perturbation of atmospheric concentrations of ozone and methane caused by NOx emissions, and H2O emissions at high flight levels. Moreover, operating costs and climate impact are expected to be conflicting objectives for trajectory optimization (Grewe et al., 2014). The characteristics of the sets of Pareto optimal solutions resulting from such multi-objective optimizations would, however, vary under different atmospheric conditions.To compare the benefits and costs associated to this operational strategy under different weather patterns, we use the air traffic simulator AirTraf, which optimizes aircraft trajectories based on the atmospheric fields computed by the ECHAM/MESSy Atmospheric Chemistry (EMAC) model (Yamashita et al., 2020). This modelling chain presents the advantage of enabling the analysis of optimized aircraft trajectories over a large number of consecutive days, identifying preferred compromise solutions between multiple optimization objectives (Castino et al., 2023). In the present study, we consider four winter and four summer seasons between 2015 and 2019, optimizing 100 flights over the North Atlantic Corridor (NAC) on each simulation day. Subsequently, we compare trajectories minimizing different objective functions, including fuel used, and the potential formation of contrails along the trajectory. We classify the weather patterns by comparing their similarity to the positive and negative phases of the North Atlantic Oscillation (NAO) and East Atlantic (EA) patterns, applying the methodology presented by Irvine et al. (2013). As a result, we can identify which conditions are correlated to a larger potential of mitigating the climate impact of our air traffic sample, e.g., by reducing the formation of persistent contrails.Acknowledgment: This research has received funding from the Horizon Europe Research and Innovation Actions programme under Grant Agreement No 101056885.References:Irvine, E. A., et al.: Characterizing North Atlantic weather patterns for climate-optimal aircraft routing, Meteorological Applications, 20, 80 – 93, https://doi.org/10.1002/met.1291, 2013. Grewe, V., et al.: Reduction of the air traffic's contribution to climate change: A REACT4C case study, Atmospheric Environment, 94, 616 – 625, https://doi.org/10.1016/j.atmosenv.2014.05.059, 2014. Yamashita, H., et al.: Newly developed aircraft routing options for air traffic simulation in the chemistry–climate model EMAC 2.53: AirTraf 2.0, Geoscientific Model Development, 13, 4869 – 4890, https://doi.org/10.5194/gmd-13-4869-2020, 2020. Castino, F., et al.: Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-88, in review, 2023.

Aviation emissions of aerosol particles and aerosol precursor gases alter the Earth's radiation budget via both direct and indirect aerosol effects, resulting in a significant climate effect. Current estimates of aviation-induced climate effects are based on coarse-resolution global aerosol-climate models, which are not able to resolve the microphysical processes at the aircraft plume scale. This results in large uncertainties in the aviation-induced impact on aerosol number and size, which are key quantities for estimating the aerosol indirect effect, especially for low-level liquid-phase clouds. In this work, a double-box aircraft exhaust plume model is developed to explicitly simulate the aerosol microphysics inside a dispersing aircraft exhaust plume, together with a simplified representation of the vortex regime (which begins ∼ 10 s after the aircraft emissions and captures the dynamics of aerosol particle interactions with contrail ice particles). The aircraft exhaust plume model is used to quantify the aviation-induced aerosol number concentration at the end of the dispersion regime (∼46 h) and the results are compared with the result obtained by the instantaneous dispersion approach commonly applied by the global models. The difference between the plume approach (simulated using two boxes) and the instantaneous dispersion approach (simulated by a single box) is defined as the plume correction: for typical cruise conditions over the North Atlantic and typical aviation emission parameters, the plume correction for aviation-induced particle number concentration ranges between −15 % and −4.2 %, depending on the presence or absence of the contrail ice in the vortex regime, respectively. A tendency-based process analysis shows that the negative value of the plume correction is due to the higher efficiency of coagulation and nucleation processes in the plume approach, leading to lower total particle number concentrations compared to the instantaneous dispersion approach. Sensitivity studies over different regions highlight the role of background conditions for the plume microphysics, with the plume correction varying between −12 % for Europe and −42 % for China in a scenario with contrail ice in the vortex regime. Parametric studies performed on various aviation emission parameters used to initialise the plume model demonstrate the high relevance of contrail ice in the vortex regime to considerably reduce the aviation-induced aerosol number concentration in the plume approach. Moreover, the parametric studies show a large sensitivity towards aviation fuel sulfur content, driving sulfur dioxide (SO2) emissions and the sulfuric acid (H2SO4) formation, which in turn is a primary driver for the nucleation process. Thanks to its flexible configuration and minor additional computational costs, the plume model presented here can readily be applied in coarse-resolution global aerosol-climate models or used as offline parametrisation to quantify the climate effects of aviation-induced aerosol particles.

While carbon dioxide emissions from aviation often dominate climate change discussions, non-CO2 effects such as contrails and contrail cirrus must also be considered. Despite varying estimates of their radiative forcing, avoiding contrails is a reasonable strategy for reducing aviation’s climate effects. This study examines temperature and humidity, key atmospheric parameters for contrail formation, across different ECHAM/MESSy (European Centre Hamburg General Circulation Model/Modular Earth Submodel System) Atmospheric Chemistry (EMAC) model setups. EMAC, a general circulation model, is evaluated with various vertical resolutions and two nudging methods across seven specified dynamics setups. A higher vertical resolution aims to capture steep water vapour gradients near the tropopause, crucial for accurate contrail prediction. Comparisons with reanalysis data (March–April 2014) indicate a systematic cold bias (approximately 3–5 K in mid-latitudes), particularly in setups without mean temperature nudging. In the upper troposphere and lower stratosphere, all simulations exhibit a wet bias, while lower altitudes display a dry bias, both affecting contrail formation estimates. Point-by-point comparisons along aircraft trajectories confirm similar biases. Sensitivity experiments with varying thresholds of relative humidity over ice illustrate trade-offs between achieving high hit rates and minimising false alarms in contrail detection. A single-day case study integrating aircraft and satellite observations demonstrates that EMAC’s predicted contrail coverage aligns well with the observed formation. These results suggest that, despite existing temperature and humidity biases, EMAC generally captures regions favourable for contrail formation across diverse atmospheric conditions. Addressing model biases by refining temperature and humidity representation could significantly improve contrail prediction accuracy, strengthening contrail-avoidance strategies and supporting climate-optimised flight routing to mitigate aviation's overall climate effect.