Chemistry transport models play a crucial role in the evaluation of the effect of anthropogenic emissions on the atmosphere and climate, but they come with high computational costs and require specialized know-how. This renders them impractical for applications in multidisciplinary optimisation, or regulatory and operational decision-making processes where environmental effects are to be considered. Such applications require computationally efficient surrogate models of the complex chemistry transport models. Here we investigate the use of data-driven discovery and reduced-order modelling methods for this purpose. Specifically, we examine the dynamic mode decomposition (DMD) and proper orthogonal decomposition coupled with the sparse identification of non-linear dynamics (POD-SINDy). We evaluate their ability to reconstruct and forecast changes in the distribution of ozone in response to the introduction of supersonic aircraft as modelled by the GEOS-Chem chemistry transport model. Of the tested methods, we find that optimized DMD and bagging optimized DMD with constrained eigenvalues perform best. These methods can reconstruct and forecast full-atmospheric ozone responses for up to several years without losing stability, at smaller errors than estimates using the spatio-temporal mean of the data. On average, the constrained optimized DMD method reduces the reconstruction error by 63.5 % and that of forecasting by 25.8 % compared to the spatio-temporal mean. For the constrained bagging optimized DMD these reductions are 45.0 % and 23.1 %, respectively. The resulting change in global ozone column, calculated from the reconstructed atmospheres, has an error smaller than 10 %. This is achieved while reducing the computational and storage requirements by several orders of magnitude, which may be a worthwhile tradeoff for some applications.

The normalized fan rotational speed per aircraft engine (N1%) is an essential input parameter to noise prediction models, but is often confidential and not directly accessible to researchers. The aircraft acoustic signal characteristics, and specifically the tonal component, can be used to extract this parameter. However, existing methodologies estimate N1% parameters from whole-aircraft spectra, which can lead to inaccurate estimations. This research aims at investigating the various tonal contributions by isolating and reconstructing spectrograms of individual noise sources using acoustic arrays. Using such arrays, it is possible to discriminate between the various components that contribute to the noise emitted by the aircraft, especially between the engines, but also the nose landing gear. From the resulting engine-specific spectrograms the N1% of individual engines for 24 aircraft were obtained. For the A321neo and the B737NG, it is found that, for 80% of the analyzed aircraft, additional engine tones accompany the higher harmonics of the engine blade passage frequency, with these additional tones corresponding to twice the shaft frequency. In addition, it was found that N1% differences between the two engines are reflected in the spectrograms and that a tone stemming from the nose landing gear can be present, resulting in a complex pattern of tones in the whole-aircraft spectrogram. The insights on the various tonal contributions to the received signal are of importance regarding the further development of methods that aim to extract the engine setting from aircraft noise measurements and as such for enabling more accurate noise calculations.

Aircraft emissions of (ultra)fine particles during landing and take-off operations pose increasing human health hazards for airport employees and near-airport communities. Measurements of in-operation aircraft are therefore crucial for characterizing real-world aircraft emissions, and their variability. In this work, we develop an approach that enables the gathering of large quantities of data on real-world aircraft-specific emissions. We use three types of portable PM sensors located ca. 200 m downwind of an operational runway at Amsterdam Airport Schiphol, over different seasons, to characterize the plumes from ca. 500 specific operations covering most aircraft types of the global flying fleet. High concentration peaks (in the order of 10⁶ particles/cm³) of sub-25 nm particles are observed in the near field. While departure plumes exhibit higher particle number concentrations than arrival plumes, the values do not necessarily scale with aircraft size or engine thrust rating. We find large variability among aircraft types and engine models, highlighting the importance of incorporating real-world observations when assessing the impacts of aviation on the atmospheric composition and human health.

Reliable prediction of aviation’s environmental impact, including the effect of nitrogen oxides on ozone, is vital for effective mitigation against its contribution to global warming. Estimating this climate impact however, in terms of the short-term ozone instantaneous radiative forcing, requires computationally-expensive chemistry-climate model simulations that limit practical applications such as climate-optimised planning. Existing surrogates neglect the large uncertainties in their predictions due to unknown environmental conditions and missing features. Relative to these surrogates, we propose a high-accuracy probabilistic surrogate that not only provides mean predictions but also quantifies heteroscedastic uncertainties in climate impact estimates. Our model is trained on one of the most comprehensive chemistry-climate model datasets for aviation-induced nitrogen oxide impacts on ozone. Leveraging feature selection techniques, we identify essential predictors that are readily available from weather forecasts to facilitate the implementation therein. We show that our surrogate model is more accurate than homoscedastic models and easily outperforms existing linear surrogates. We then predict the climate impact of a frequently-flown flight in the European Union, and discuss limitations of our approach.

Civil supersonic aviation may return in the near future. Their emissions have been found to lead to changes in the composition of the stratosphere, affecting the ozone layer and climate. To keep up with the rapid developments in supersonic aircraft technology and alternative fuels there is an increasing need for the development of surrogate modeling methods, which requires knowledge of the sensitivities to these emissions. We present a parametric study which evaluates the first- and second-order sensitivities of the ozone column and radiative forcing (RF) to supersonic emissions across two flight corridors and three altitudes. For a given increase in global fuel burn, we find that the increase in emission of (Formula presented.) is the main driver of both the changes in the global ozone column and RF, the latter of which is linked through changes in the ozone distribution. Followed by the increase in the emission of (Formula presented.), which leads to (Formula presented.) loss and has a cooling effect. The ozone column and climate are least sensitive to increases in (Formula presented.) emissions. We also show that interactions between (Formula presented.), (Formula presented.), and (Formula presented.) emissions lead to non-linear behavior in the atmospheric response. The effect of these interactions can lead to (Formula presented.) 5% differences in the ozone column impacts and up to 7.3% increases in RF. Our results demonstrate that the majority of second-order sensitivities may be neglected in surrogate models for small errors, which could greatly simplify their development. Our results also indicate that reductions in flight altitude and fleetwide (Formula presented.) emissions may effectively reduce the environmental footprint of supersonic aviation emissions.

Flight altitude is relevant to the climate effects resulting from aircraft emissions. Other research has shown that flying higher within the troposphere leads to larger warming from O ₃ production. Aircraft NO _x emissions are of particular interest, as they lead to warming via the short-term production of O ₃, but also to reduced warming via processes like CH ₄ depletion. We focus on short-term O ₃ production, as it constitutes one of aviation’s largest warming components. Understanding how O ₃ formation varies altitudinally throughout the upper troposphere/lower stratosphere is essential for designing climate-compatible aircraft and routing. We quantify this variation by performing simulations with a global atmospheric chemistry model for three representative cruise altitudes, five regions and two seasons using three methods: Eulerian tagging, perturbation and Lagrangian tagging. This multi-method, regional approach overcomes limitations of previous studies that utilize only one of these methods and apply global emission inventories biased towards present-day flight distributions, thus limiting their applicability to future aviation scenarios. Our results highlight that underrepresenting emissions in areas with growing flight activity (e.g. Asia Pacific) may lead to significant, regional underestimations of the altitudinal sensitivity of short-term NO _x -related O ₃ warming effects in certain cases. We find that emitting in Southern regions, like Australasia, leads to warming larger by a factor of two when compared to global averages. Our findings also suggest that flying lower translates to lower warming from short-term O ₃ production and that this effect is strongest during the local summer. We estimate differences ranging from a factor of 1.2-2.6 between tagging and perturbation results that are attributable to non-linearities of NO _x -O ₃ chemistry, and derived regional correction factors for a widely-used sub-model. Overall, we stress that a combination of all three methods is necessary for a robust assessment of aviation climate effects as they address fundamentally different questions.

Aviation produces a net climate warming contribution that comprises multiple forcing terms of mixed sign. Aircraft NOx emissions are associated with both warming and cooling terms, with the short-term increase in O3 induced by NOx emissions being the dominant warming effect. The uncertainty associated with the magnitude of this climate forcer is amongst the highest out of all contributors from aviation and is owed to the nonlinearity of the NOx-O3 chemistry and the large dependency of the response on space and time, i.e., on the meteorological condition and background atmospheric composition. This study addresses how transport patterns of emitted NOx and their climate effects vary with respect to regions (North America, South America, Africa, Eurasia and Australasia) and seasons (January-March and July-September in 2014) by employing global-scale simulations. We quantify the climate effects from NOx emissions released at a representative aircraft cruise altitude of 250 hPa (∼10400 m) in terms of radiative forcing resulting from their induced short-term contributions to O3. The emitted NOx is transported with Lagrangian air parcels within the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model. To identify the main global transport patterns and associated climate impacts of the 14 000 simulated air parcel trajectories, the unsupervised QuickBundles clustering algorithm is adapted and applied. Results reveal a strong seasonal dependence of the contribution of NOx emissions to O3. For most regions, an inverse relationship is found between an air parcel's downward transport and its mean contribution to O3. NOx emitted in the northern regions (North America and Eurasia) experience the longest residence times in the upper midlatitudes (40 %-45 % of their lifetime), while those beginning in the south (South America, Africa and Australasia) remain mostly in the Tropics (45 %-50 % of their lifetime). Due to elevated O3 sensitivities, emissions in Australasia induce the highest overall radiative forcing, attaining values that are larger by factors of 2.7 and 1.2 relative to Eurasia during January and July, respectively. The location of the emissions does not necessarily correspond to the region that will be most affected - for instance, NOx over North America in July will induce the largest radiative forcing in Europe. Overall, this study highlights the spatially and temporally heterogeneous nature of the NOx-O3 chemistry from a global perspective, which needs to be accounted for in efforts to minimize aviation's climate impact, given the sector's resilient growth.

Excess nitrogen deposition from anthropogenic sources of atmospheric emissions, such as agriculture and transportation, can have negative effects on natural environments. Designing effective conservation efforts requires knowledge of the contribution of individual sectors. This study utilizes a global atmospheric chemistry-transport model to quantify, for the first time, the contribution of global aviation NO_x emissions to nitrogen deposition for 2005 and 2019. We find that aviation led to an additional 1.39 Tg of nitrogen deposited globally in 2019, up 72 % from 2005, with 67 % of each year's total occurring through wet deposition. In 2019, aviation was responsible for an average of 0.66 %, 1.13 %, and 1.61 % of modeled nitrogen deposition from all sources over Asia, Europe, and North America, respectively. These impacts are spatially widespread, with 56 % of deposition occurring over water. Emissions during the landing, taxi and takeoff (LTO) phases of flight are responsible for 8 % of aviation's nitrogen deposition impacts on average globally, and between 16 and 32 % over most land in regions with high aviation activity. Despite currently representing less than 1.2 % of nitrogen deposition globally, further growth of aviation emissions would result in increases in aviation's contribution to nitrogen deposition and associated critical loads.