Implications of future atmospheric composition in decision-making for sustainable aviation

Aviation emissions lead to degraded air quality and adverse human health impacts, making air quality one of the leading environmental externalities associated with aviation. Aviation emissions have been growing steadily over the past decades, and, despite the current hindrance in air traffic due to the COVID- 19 pandemic, they are forecasted to continue to grow in the long-term. As a result, mitigating aviation’s adverse air quality impacts is an increasingly pressing challenge for the aviation industry. At the same time, the aviation industry has inherently long timelines, indicating that sustainability-related regulatory and technological decisions made presently will take effect over the next 30+ years. Over such timelines, the changing atmospheric composition, driven by meteorological and background (non-aviation) emissions changes, results in a changing atmospheric response to emissions. This work summarizes recent advancements on this and discusses their implications for the aviation sector. First, aviation emissions and the resulting air quality impacts are described. The role of the atmospheric sensitivities to emissions and their evolution over time is then discussed. Finally, the implications for the long timelines associated with aviation mitigation options are underlined. Current challenges as well as opportunities for future research to resolve current assessment shortcomings are also presented

Implications of future atmospheric composition in decision-making for sustainable aviation

Aviation emissions lead to degraded air quality and adverse human health impacts, making air quality one of the leading environmental externalities associated with aviation. Aviation emissions have been growing steadily over the past decades, and, despite the current hindrance in air traffic due to the COVID- 19 pandemic, they are forecasted to continue to grow in the long-term. As a result, mitigating aviation’s adverse air quality impacts is an increasingly pressing challenge for the aviation industry. At the same time, the aviation industry has inherently long timelines, indicating that sustainability-related regulatory and technological decisions made presently will take effect over the next 30+ years. Over such timelines, the changing atmospheric composition, driven by meteorological and background (non-aviation) emissions changes, results in a changing atmospheric response to emissions. This work summarizes recent advancements on this and discusses their implications for the aviation sector. First, aviation emissions and the resulting air quality impacts are described. The role of the atmospheric sensitivities to emissions and their evolution over time is then discussed. Finally, the implications for the long timelines associated with aviation mitigation options are underlined. Current challenges as well as opportunities for future research to resolve current assessment shortcomings are also presented.Aircraft Noise and Climate Effect

Evaluation of Aviation Emissions and Environmental Costs in Europe Using OpenSky and OpenAP

In this paper, we propose a data-driven approach that estimates cruise-level flight emissions over Europe using OpenSky ADS-B data and OpenAP emission models. Flight information, including position, altitude, speed, and the vertical rate are obtained from the OpenSky historical database, gathered at a sample rate of 15 s. Emissions from each flight are estimated at a 30-s time interval. This study makes use of the first four months of flights in 2020 over the major part of Europe. The dataset covers the period before and at the start of the COVID-19 pandemic. The aggregated results show cruise-level flight emissions by different airlines, geographic regions, altitudes, and timeframe (e.g., weeks). We also estimate environmental costs associated with aviation in Europe by using marginal cost values from the literature. Overall, we have demonstrated how open flight data from OpenSky can be employed to rapidly assess aviation emissions at varying spatio-temporal resolutions on a continental scaleControl & SimulationAircraft Noise and Climate Effect

Annual satellite-based NDVI-derived land cover of Europe for 2001–2019

Land cover plays an important role in the Earth's climate as it affects multiple biochemical cycles and is critical for food security and biodiversity. As land cover is continuously evolving, influenced by anthropogenic and other factors, the availability of temporally varying land cover data sets of large spatial domains is integral to understanding, monitoring, and informing environmental management efforts. Here we use classification trees to generate annual land cover maps of the European continent for 2001 to 2019 on a ∼250 m resolution. The classification trees are trained using gap-filled and smoothed MODIS normalised difference vegetation index (NDVI) satellite data, as well as CORINE reference land cover data. We apply the bagging ensemble technique on oversampled NDVI data, with an additional majority vote for overlapping segments over the continent-wide domain. We distinguish between 39 land cover classes, with a total classification accuracy of 75% and average precision of 76%. The accuracy varies between the classes, with common classes (e.g. agricultural and forest classes) performing better than rarer ones (e.g. artificial land cover). Over the entire continent, we find that artificial land cover, wetlands, and forests have increased on average by 0.76, 0.50 and 0.22%/year respectively, while the agricultural area has decreased by 0.21%/year. We also quantify these changes in land cover on a national and metropolitan level. Given the near-real-time availability of global NDVI data, we note the potential of the presented approach for generating ‘near-real-year’ annual land cover data sets of large geographic domains, for the continuous monitoring of land cover change and the effects of interventions.Aircraft Noise and Climate Effect

Regional sensitivities of air quality to aviation emissions

Emissions from civil aviation traffic degrade air quality, causing human health problems that have been estimated to result in ~16 000 premature deaths per year globally, potentially making the cost to society of the air quality impacts even greater than the cost of the climate impact of these emissions. Previous studies have indicated that aviation emissions in specific areas can have impacts of significantly different intensities due to variations in population density and background atmospheric composition. We use the GEOS-Chem global atmospheric chemistry-transport model to investigate the air quality sensitivity to aviation emissions in different regions of the world by performing simulations with increased emissions on different locations at a time and comparing the resulting changes in human exposure to air pollutants (fine particulate matter and ozone). We evaluate the impacts of both landing and take-off (LTO) and cruise level emissions. The simulations are used to investigate the drivers of the differences in air quality sensitivity to emission location, shedding light to the previously observed indications that European air traffic leads to more premature deaths per mass of emissions than North American air traffic. These regionally varying air quality effects imply that regionally non-uniform regulations, if feasible, might provide efficient strategies of mitigating costs associated with air quality impacts

Clustering of ATTILA Trajectories using a Neuroscience Algorithm (QuickBundles) for the Characterization of Emission Transport Pathways

Aircraft Noise and Climate Effect

Assessing the appropriateness of different climate modelling approaches for the estimation of aviation NOx climate effects

Aviation’s contribution to anthropogenic global warming is estimated to be between 3 – 5% [1]. This assessment comprises two contributions: the well understood atmospheric impact of carbon dioxide (CO2) and the more uncertain non-CO2 effects. The latter pertain to persistent contrails and pollutants like nitrogen oxides (NOx), water vapor (H2O), sulfur oxides (SOx) and soot particles. NOx emissions are involved in non-linear processes that result in the short-term production of ozone (O3) and longer-term destruction of methane (CH4), stratospheric water vapor (SWV), and primary mode ozone (PMO). The aviation-attributable impacts arising from this short-term increase in O3 can vary by more than a factor of 1.5 depending on the selected modelling approach. This O3 increase is associated with the second largest warming effect across aviation’s main climate forcers [1]. We therefore quantify this figure using three modelling approaches (an Eulerian and a Lagrangian tagging scheme as well as a perturbation approach) at three potential aircraft cruise altitudes (200, 250 and 300 hPa) at which NOx pulse emissions are introduced in the Americas, Africa, Eurasia and Australasia. In general, the tagging method computes the contribution by an emission source to the concentration of a chemical species while a perturbation approach consists in calculating the total impact of an emission to the concentration of a species by means of subtracting two simulations: one with all emissions and a second without the specific source’s emissions. We compare results from Eulerian and Lagrangian simulations using the same climate-chemistry code: the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model. With the Eulerian setup, we are able to capture non-linear processes and feedback effects, but not track the transport of emitted species in detail. The Lagrangian setup [2], on the other hand, allows for the accompaniment of thousands of air parcel trajectories, but at the cost of assuming a simplified linear chemistry mechanism. We find that the Lagrangian tagging approach provides the largest estimates for O3 production and radiative forcing (RF), followed by the Eulerian tagging scheme and lastly by the perturbation method. We therefore investigate the appropriateness of each of these in quantifying aviation’s total and marginal climate effects by addressing the following research questions: 1) By how much are the estimates for the short-term NOx-induced O3 perturbation and consequent RF varying across the three modelling approaches and why? 2) How does this RF vary with emission altitude within the upper Troposphere/lower Stratosphere (UTLS)?[1] Lee, D.S., Fahey, D.W., Skowron, A., Allen, M.R., Burkhardt, U., Chen, Q., Doherty, S.J., Freeman, S., Forster, P.M., Fuglestvedt, J., Gettelman, A., De León, R.R., Lim, L.L., Lund, M.T., Millar, R.J., Owen, B., Penner, J.E., Pitari, G., Prather, M.J., Sausen, R., and Wilcox, L.J.: The contribution of global aviation to anthropogenic climate forcing for 2000 to 2018, Atmos. Environ., 244, 117834, https://doi.org/10.1016/j.atmosenv.2020.117834, 2021.[2] Maruhashi, J., Grewe, V., Frömming, C., Jöckel, P., and Dedoussi, I. C.: Transport patterns of global aviation NOx and their short-term O3 radiative forcing – a machine learning approach, Atmos. Chem. Phys., 22, 14253–14282, https://doi.org/10.5194/acp-22-14253-2022, 2022

Regional sensitivities of air quality to aviation emissions

Emissions from civil aviation traffic degrade air quality, causing human health problems that have been estimated to result in ~16 000 premature deaths per year globally, potentially making the cost to society of the air quality impacts even greater than the cost of the climate impact of these emissions. Previous studies have indicated that aviation emissions in specific areas can have impacts of significantly different intensities due to variations in population density and background atmospheric composition. We use the GEOS-Chem global atmospheric chemistry-transport model to investigate the air quality sensitivity to aviation emissions in different regions of the world by performing simulations with increased emissions on different locations at a time and comparing the resulting changes in human exposure to air pollutants (fine particulate matter and ozone). We evaluate the impacts of both landing and take-off (LTO) and cruise level emissions. The simulations are used to investigate the drivers of the differences in air quality sensitivity to emission location, shedding light to the previously observed indications that European air traffic leads to more premature deaths per mass of emissions than North American air traffic. These regionally varying air quality effects imply that regionally non-uniform regulations, if feasible, might provide efficient strategies of mitigating costs associated with air quality impacts.Aircraft Noise and Climate Effect

Assessing and Modelling Climate Optimal Flights Using Open Surveillance and Remote Sensing Data

Sustainability is the biggest challenge facing the aerospace industry today. With the global number of flights expected to rise, the climate impact of aviation will continue to increase. Current research states that the rerouting of aircraft through wind-optimisation for the purpose of fuel usage minimisation and emission reduction is an effective sustainability contribution. However, these routing models only optimize for minimum fuel burn, not necessarily minimum climate impact. Flying efficiently through wind fields could mean flying through regions with higher climate impact, for example, where warming contrails are formed. This potentially forfeits the advantage of the reduced emissions from the wind-optimized route. By bringing together fields such as satellite remote sensing, atmospheric science and aircraft surveillance data, a climate optimized free routing model can be made. This paper creates a climate optimized free routing airspace model by incorporating knowledge from the aforementioned fields and existing wind-optimization models with AI and open-source tools

Global Civil Aviation Emissions Estimates for 2017–2020 Using ADS-B Data

Aviation is a growing source of atmospheric emissions impacting the Earth’s climate and air quality. Comprehensive assessments of the environmental impact of this industry require up-to-date, spatially resolved, and speciated emissions inventories. We develop and evaluate the first such estimate of global emissions from aircraft operations for the years 2017–2020. Aircraft activity data, based on flights registered by networks of aircraft Automatic Dependent Surveillance–Broadcast (ADS-B) telemetry receivers, are used together with the Base of Aircraft Data (BADA) 3.15 aircraft performance model and the International Civil Aviation Organization Engine Emissions Databank to estimate spatially resolved fuel burn and emissions of CO2, H2O, NOx (NO+NO2), SOx (SO2+SO2−4), CO, unburnt hydrocarbons (HC), and nonvolatile particulate matter (nvPM). We calculate that 937 Tg of CO2 and 4.62 Tg of NOx were emitted by aircraft in 2019, and quantify the evolution of the fleet average emission indices over time. Owing to impacts from COVID-19, we estimate a 48% lower fuel burn, resulting in 463 Tg less CO2 and 2.29 Tg less NOx emitted in 2020 than what would be otherwise expected. We conclude that ADS-B is a viable source of data to generate global emissions estimates in a timely and transparent manner for monitoring and assessing aviation’s atmospheric impacts