Expected Outcome:To significantly advance the following development priority:

FR-1 ATM impact on climate change. Specific requirement for this topic

Any proposal addressing non-CO2 impacts shall take into consideration on-going work under the “Aviation Non-CO2 Expert Network (ANCEN)” and feed into the community work. ANCEN goal is to facilitate a coordinated approach across a wide range of relevant stakeholders (e.g., scientific community, academia, OEMs, aircraft operators, fuel producers, ANSPs, NGOs, regulators, analysts and policymakers) to provide objective, timely, common and credible technical advice. This work can inform, where relevant, policy discussions on the development, agreement and implementation of effective action within Europe and internationally to mitigate the overall climate impacts caused by aviation (CO2 and non-CO2 emissions).

Scope:​​​​​1. Noise and air quality pollutants

Research aims at increasing the body of knowledge on the impact of ATM on areas such as noise and air quality pollutants (nitrogen oxides (NOX), particulate matter (PM), volatile organic compounds (VOCs), sulphur dioxide (SO2), carbon mo... ver más

Expected Outcome:To significantly advance the following development priority:

FR-1 ATM impact on climate change. Specific requirement for this topic

Any proposal addressing non-CO2 impacts shall take into consideration on-going work under the “Aviation Non-CO2 Expert Network (ANCEN)” and feed into the community work. ANCEN goal is to facilitate a coordinated approach across a wide range of relevant stakeholders (e.g., scientific community, academia, OEMs, aircraft operators, fuel producers, ANSPs, NGOs, regulators, analysts and policymakers) to provide objective, timely, common and credible technical advice. This work can inform, where relevant, policy discussions on the development, agreement and implementation of effective action within Europe and internationally to mitigate the overall climate impacts caused by aviation (CO2 and non-CO2 emissions).

Scope:​​​​​1. Noise and air quality pollutants

Research aims at increasing the body of knowledge on the impact of ATM on areas such as noise and air quality pollutants (nitrogen oxides (NOX), particulate matter (PM), volatile organic compounds (VOCs), sulphur dioxide (SO2), carbon monoxide (CO) and unburnt hydrocarbons (HC)). Research aims at better understanding the ATM environmental impacts beyond greenhouse emissions (CO2 and non-CO2 aviation emissions). Research shall consider the new types of aircraft propulsions, new aircraft configurations and new propulsion fuels (e.g., hydrogen), whose impact on noise and air quality need to be researched; regarding the new aircraft types, research shall consider the work performed under Clean Aviation programme (www.clean-aviation.eu).

Research shall also consider the consideration of new entrants (e.g., higher airspace operations (HAO). An increasing number of rocket and space vehicle launches are planned, which clearly will significantly impact the population in the neighbourhood of concerned launch sites (e.g., Grotaglie airport) with massive noise exposure and potentially as well with particle and gaseous pollutants relevant for local air quality. Research shall also pay attention to the social acceptance aspects of such launch and re-entry activities.

2. Atmospheric physics for aviation (extreme weather events)

Research aims at increasing the body of knowledge on the physics of the atmosphere, to better understand and reliably quantify the effect of climate change on future trends regarding severe weather events (e.g., severe convective storms, heatwaves, dust storms, etc.) and weather hazards (e.g., clear air turbulence, hail, low-level windshear, extreme wind, heavy precipitations, in-flight icing conditions, etc.). Research shall propose innovative methods to model the effects of climate change on these future trends with high reliability and accuracy over the next decades. The objective is to improve the ATM system climate resilience and adaptation and minimise negative impacts on ATM (e.g., airport closures or significant reductions in airport capacity (with knock-on effects on the network)). Results will facilitate the definition of a climate change adaptation strategy for aviation and decision-making by ANSPs, airports and the other aviation stakeholders, covering from short to long-term (e.g., ensuring that ATM short-term induced decision will not jeopardise long-term ATM resilience and sustainability). The research should consider the challenges for accurate prediction that may result from changes to weather patterns arising from global warming in the short to medium-term.

Research shall elaborate a thorough state of the art review to evaluate the progress made atmospheric physics for aviation (extreme weather events) by previous research or on-going research within SESAR or outside SESAR. Note that there is on-going work under project AEROPLANE, which is reviewing the effect of heatwaves on aeroplanes take-off performance.

Research shall consider the knowledge gaps reported in the “ICAO Committee on Aviation Environmental Protection (CAEP) aviation and climate change factsheet[1]”, the EASA "European aviation environmental report 2022[2]” and the EASA Scientific Committee Annual Report 2023[3].

3. Multi-scale multi-pollutant air quality systems (CO2 and non-CO2)

Research aims at developing potential solutions for the evaluation of the impact that the air traffic regulation policy options can have on the environment and climate. The proposed solutions should be able to follow the evolution of aircraft emissions (e.g., CO2 and non-CO2) in the atmosphere on both the global/regional scale (e.g., transport of pollutants from the troposphere to the stratosphere, impact onto the radiative properties of the atmosphere, ozone production, etc.), and on the local scale (e.g., impact close to an airport area during landing and take-off phases). The main area of applicability of such a solution is to support the aviation community in estimating the extent of the environmental impacts that current and future air traffic movements might have. An effective multi-scale air quality system shall address all phases of flight, starting at the strategic phase and including the post-operations phase. Research may leverage the potential of AI technologies to provide accurate and real time estimations of trajectories and impacts (using all available information and/or predictions of atmospheric status and weather) in order to assess the relevance of new indicators. Proposals shall demonstrate the relevance of the proposed approach and scope for ATM.

Research shall elaborate a thorough state of the art review to evaluate the progress made on multi-scale multi-pollutant air quality systems (CO2 and non-CO2) by previous research or on-going research within SESAR (e.g., project CREATE) or outside SESAR.

Coordination with the “Aviation Non-CO2 Expert Network (ANCEN)[4]” is required to focus on priority research gaps that need to be addressed to develop robust decision-making capabilities.

4. Development of the environmental performance-monitoring toolkit (CO2 and non-CO2) to include new entrants

There is a need to further develop the set of European environmental impact assessment tools, to analyse, inter alia, the integration of new entrants into the future ATM system and the overall environmental benefits and impacts (not only in terms of CO2 but also non-CO2) they will have. This element covers the expansion of the ATM aircraft performance models (on emissions and noise) to include new entrants and new aircraft types/fuels. It involves research into the impact on the environment of new fuels and/or new aircraft types (hydrogen, electric, sustainable aviation fuels, new hyper-/supersonic aircraft (with consideration of sonic booms)), including developing new models to assess the impact that ATM operational changes may have when these aircraft are introduced into the traffic mix, and exploring the boundaries for change to avoid negative effects on operational performance and environment (i.e., sensitivity analysis). Research shall also consider the potential of new entrants to re-shape the ATM network (e.g., new hubs driven by the new re-fuelling needs and stations, new airspace needs, etc.).

Research should include the development of methodologies to assess the environmental and societal impact of U-space-enabled drone operations, including the identification of all potential impacts (e.g., visual pollution, noise over populated areas, intrusion into privacy, risks to wildlife (migrating birds, nesting areas, etc.)). In addition, research shall also address higher airspace operations (HAO), especially during launch and re-entry operations. Due to the complexity and diversity of environmental impacts, particular attention needs to be paid to the analysis of trade-offs, between environmental impacts, but also possibly with other performance areas.

Research shall consider the required coordination with EASA (since the Agency is already working on this research topic) to ensure complementarity on the research objectives and approach.

5. Validation of novel metrics in support of environmental impact assessment in ATM and U-space (noise, emissions CO2 and non-CO2)

The collaborative management of environmental impacts and the implementation of strategies to reduce them require the development of indicators/metrics that will enable, on one hand, all ATM / U-space decision-makers to make informed decisions at different levels and to communicate on ATM / U-space community efforts towards environmental sustainability. Research aims at developing and validating new environmental metrics for use in R&I and/or operations. The areas for development include:

The use of extended projected profile (EPP) data for environmental performance assessment.The development of meaningful operational proxies that can support ATM / U-space decision making in ATFM, ATC and drone operations, development of methodologies for providing an accurate estimation of CO2 and non-CO2 impacts (including noise) with minimal input data (e.g., based only on surveillance data combined with flight plan data etc.). When sufficient input data is available, research may leverage the potential of AI technologies to make generate more accurate predictions or indicators.The research can also investigate the adaptation to ATM of software and methodologies currently in use by aircraft operators and service providers to optimise their environmental performance; also, the research should consider its applicability for U-space / drone operations. Note that research has been performed or is on-going under projects CLAIM[5] or under initiatives such as Aviation Non-CO2 Expert Network (ANCEN)[4] that should be considered to identify synergies and avoid duplication on this field.

6. Integrated platforms for the nowcasting and forecasting of multiple atmospheric hazards

This research aims at developing integrated platforms to incorporate predictions of atmospheric hazards (e.g., SO2 contaminants, severe weather situations such as deep convection and extreme weather and climate hotspots potentially contributing to global warming, etc.). The focus is to enhance the situational awareness of all stakeholders in case of multiple hazard crisis by facilitating the transfer of required relevant information to end-users, presenting such information in a user-friendly manner to ATM / U-space stakeholders, ultimately anticipating severe hazards and fostering better decision-making. Research may address:

Extension of nowcasting models of SO2 in 1D (values for a given location) to 2D (lat-long) and 3D and nowcasting products for dust, ash, volcanic aerosol and precursors and smoke.The consideration of additional observations (e.g., radar, satellite, sensors on board the aircraft) to better characterise the weather extremes and enhance the quality of the extreme weather nowcasting.The integration of space weather and climate change in the new MET services.The application of artificial intelligence or deep learning models based on recurrent networks could be used to better predict weather phenomena.Address potential human operator decision support systems able to import and process the meteorological forecasts and to adapt tactical arrival and departure scheduling to changing extreme weather conditions.Target airport, TMA and en-route operating environments and the potential use by different stakeholders (e.g., Network Manager, ANSPs (flow management and air traffic control positions), airports, airlines (dispatchers and pilots), etc.).Address the assessment of potential benefits in terms of capacity, efficiency, safety, predictability, and resilience.The inclusion of weather phenomena impact expected to affect U-space and drone operations into the now/forecasting integrated platforms. Research shall consider the output of project ALARM. Note that there is on-going work on this research element under project KAIROS.

7. Contrails

The research aims at enhancing the methodology for detecting and recognizing aviation-induced contrails. This could be achieved through the utilization of deep learning models for image recognition on satellite data, as well as incorporating insights from physics sciences to model the evolution of linear contrails into cirrus clouds. The goal is to predict the formation of aviation-induced contrails, quantify their associated radiative forcing and their overall climate impact. It is important to consider previous/on-going work (projects E-CONTRAIL, CONTRAILNET, CICONIA), which used deep learning ML models and numerical weather prediction (NWP). In addition to these efforts, predicting contrails, especially persistent ones, hinges on atmospheric humidity. However, significant challenges remain today. To address those, research should focus on extending and enhancing humidity measurement techniques and on developing sophisticated numerical weather modelling approaches to enhance the accuracy of humidity and therefore of the contrail predictions. Research shall aim at quantifying the uncertainty in the prediction of contrails and the assessment of their impact on the climate to support inform operational decision-making.

In addition, the research should address the phenomenon of embedded contrails. These contrails form under specific conditions when aircraft fly through pre-existing cirrus clouds, resulting in contrails becoming embedded within those cloud layers. Despite their significance, our understanding of how embedded contrails impact the radiative forcing of natural cirrus clouds remains limited—an unquantified non-CO2 effect of aviation. These embedded contrails have the potential to alter the cloud optical thickness (COT) of existing cirrus, potentially shifting their climate impact from net warming to net cooling. To advance the knowledge in this area, note that there is on-going work conducted by project AEROPLANE, which detected embedded contrails by analysing individual aircraft locations from aircraft position datasets and correlating them with height-resolved observations obtained from spaceborne light detection and ranging (LIDAR) and radar instruments. Research is also needed on contrails that are embedded in another contrail generated by an aircraft that flew in the area before, as well as on overlapping contrails produced by different aircraft.

The observation and identification of contrails play a crucial role in supporting contrail prediction. As the number of observational sensors increases, we gain the ability to correlate contrail occurrences with other relevant data, creating large databases that can be used for training machine learning (ML) models for contrail prediction. These observational means include in-situ measurements (like IAGOS, MOZAIC), geostationary satellites offering a global perspective, low orbit satellites providing more detailed data from low earth orbit, ground cameras which capture contrail events with higher resolution for specific locations and LIDAR, on satellites, aircraft or ground-based installations. In particular, but not exclusively, the research should explore the extended use of ground cameras and LIDARs for supporting contrail observation and identification tasks.

[1] www.icao.int/environmental-protection/Documents/Factsheet%20Business%20and%20Economics%20Final.pdf

[2] https://www.easa.europa.eu/eco/sites/default/files/2023-02/230217_EASA%20EAER%202022.pdf

[3] https://www.easa.europa.eu/en/domains/research-innovation/easas-scientific-committee-scicomm

[4] https://www.easa.europa.eu/en/research-projects/nonco2

[5] https://www.claim-project.eu/

[6] https://www.easa.europa.eu/en/research-projects/nonco2

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