Abstract

In an industry beset by economic and environmental crises, air transport, the safest and most efficient long-haul mode of transport, is confronted daily with multi-criteria challenges to improve its environmental performance. The formation of contrails through the emission of water vapor and condensation nuclei in what are actually dry and clean atmospheric layers represents one of the most unpredictable, or measurable, environmental impacts of air traffic. Following the bottom-up principle to evaluate individual contrails in order to derive recommendations for trajectory optimization, not only the calculation of the radiative forcing of the contrails but also the modeling of their life cycle is burdened with uncertainties. In former studies for modeling the microphysical life cycle of contrails based on a 3-D Gaussian plume model, the atmospheric conditions, specifically the turbulence, were often unknown and had to be considered as a free input variable. In this study, an innovative photographic method for identifying and tracking contrails in Central Europe, connected with database access to Automatic Dependent Surveillance—Broadcast (ADS-B) data (i.e., aircraft type, speed, altitude, track, etc.), and a combination of measured and modeled weather data are used to validate the contrail life-cycle model (i.e., the assumed Gaussian plume behavior). We found that it is challenging to model the position of ice-supersaturated layers with global forecast models, but they have the most significant impact on the contrail lifetime. On average, the contrail’s lifespan could be modeled with an error margin of 10%. Sometimes, we slightly underestimated the lifetime. With the validated and plausible contrail life-cycle model, we can apply the climate effectiveness of individual contrails with higher certainty in trajectory optimization and compare it, for example, with economic aspects such as delay costs or fuel costs.

Full Text
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