Persistent contrails significantly contribute to aviation’s climate impact through radiative forcing effects. Japanese airspace, characterized by high traffic density, prevalent short-haul flights, and diverse meteorological conditions, exhibits unique contrail formation patterns requiring tailored mitigation strategies. However, approaches such as altitude adjustments for contrail avoidance may lead to air traffic concentration at specific altitudes, raising aviation safety concerns. Therefore, this study identifies high-impact regions in Japanese airspace where contrail mitigation strategies can be effectively applied. Using the CoCiP model, CARATS Open Data, and ERA5 reanalysis, the analysis highlights critical seasonal and geographical patterns of contrail formation. Based on CARATS Open Data from 2019, which includes 399,541 flights across en route and oceanic airspace, April to June emerge as peak periods for contrail energy forcing (EF), driven by stable, humid atmospheric conditions. High-EF hotspots in southwestern, central, and northern Japan align with dense air traffic routes, with 1.71% of flights accounting for 80% of total contrail EF. A strong correlation between contrail altitude and persistence underscores the effectiveness of altitude adjustments for mitigation. Targeted strategies, such as nighttime altitude changes and interventions in high-EF sectors, could significantly reduce aviation’s climate impact. These findings establish a foundation for integrating contrail reduction measures into air traffic management systems in Japan, providing actionable insights for balancing climate benefits and operational safety.

Reducing the length of departure queues at runway entry points is one of the most important requirements for reducing aircraft traffic congestion and fuel consumption at airports. This study designs an aircraft departure model at a runway using a time-varying fluid queue. The proposed model enables us to determine the aircraft waiting time in the departure queue and to evaluate effective control approaches for assigning suitable holds at gates rather than runway entry points. As a case study, this study modeled the departure queue at runway 05 of Tokyo International Airport for an entire day of operations. Using actual traffic data of departures at the airport, the model estimates that aircraft spend a total of 2.5 h departure waiting time in a day at runway 05. Considering the stochastic nature of actual departure traffic, the relevance of the proposed model is discussed using validation criteria. The model estimation shows a reasonable, expected order of magnitude compared with the departure queue recorded in the actual traffic data. Furthermore, ecological and economic benefits are quantitatively evaluated assuming a reduction in the departure queue length. Our results show that about one kiloton of fuel oil per year is wasted due to aircraft waiting to depart from a single departure runway.