Network Assessment of the Aviation Climate Impact Considering the European Structured Airspace

The aviation industry contributes to global warming by releasing CO2 and non-CO2 species into the atmosphere. The climate impacts of non-CO2 emissions have been claimed to be two times higher than the effects of CO2 alone [1]. Unlike CO2 emission, the climate impacts of non-CO2 species highly depend on geographical location, altitude, and time of the emissions. Thus, performing more efficient maneuvers to avoid climate hotspots can potentially mitigate their associated climate effects. So far, several studies have been conducted on micro-scale climate optimal aircraft trajectory planning (i.e., trajectory level) [2]. However, generating a climatically optimal flight plan for each aircraft is not the ultimate solution to this problem when it comes to global traffic scenarios.     Besides increasing the operating costs as the aircraft fly longer routes ( mainly due to the tendency to avoid climate-sensitive regions), the climate-optimal trajectories also alter the traffic pattern by increasing the congestion around climate hotspots, which may have negative implications, including, but not limited to, high traffic density, increased workload, complexity, and conflicts. Therefore, the evolution toward an environmentally friendly trajectory planning framework required a holistic perspective on the consequences of adopting climate-optimal routes at network scale. Nonetheless, in the literature, the problem of aircraft trajectory planning for the benefits of climate at a network scale is explored only in a free-routing airspace, considering a regional scenario (i.e., only Spain airspace), and constant altitude for trajectory optimization [3].    In this study, we aim to explore this problem considering a real large-scale scenario including ≈ 6000 flights on December 20th, 2018, from 12:00 to 16:00 over European airspace. The flight information, including the time and altitude of the first crossed waypoint within the considered time interval, has been extracted from the DDR2 dataset. For flights that start or land outside ECAC airports, we model only the segment of the flight that takes place within ECAC airspace. The algorithmic climate change functions proposed by [4] are employed to quantify the climate impact of each species, including contrails, and emissions of nitrogen oxides, CO2, and water vapor, in terms of average temperature response over the next 20 years. Our recently developed tool for climate-optimal aircraft trajectory planning, ROOST, is then used to optimize each trajectory 1 within the current structured airspace [5]. The effects of adopting climate optimized trajectories are assessed in terms of complexity, demand, and the number of conflicts. A performance map associated with each indicator is generated to spatially analyze the overall behavior of optimized trajectories and detect congested areas.      For the considered scenario, the results indicate that by adopting trajectories with less climate impact, the complexity, demand, and conflicts are increased around climate hotspots. This trend is mainly due to the tendency to avoid climate-sensitive regions. In order to mitigate such changes in traffic patterns, an efficient resolution strategy is needed to find the optimal mechanisms to manage the ATM system from a climatic perspective.