Condensation trails—commonly known as contrails—occur when aircraft exhaust water mixes with cold, surrounding humid air at high altitude. Under certain specific atmospheric conditions, engine exhaust can cause the formation of long-lived contrails. These can result in persistent clouds known as aircraft-induced cirrus (AIC). Studies indicate AIC likely contribute to changes in the atmosphere at a level that is roughly equivalent to that of the CO2 emissions from the entire aviation sector, or about 2% of total global CO2 emissions.
The following teams funded under the Predictive Real-time Emissions Technologies Reducing Aircraft Induced Lines in the Sky (PRE-TRAILS) Exploratory Topic—managed by the Advanced Research Projects Agency-Energy (ARPA-E)—will develop diagnostics and predictive tools needed to enable mitigation of contrail-related climate forcing:
GE Research will develop a real-time, in-flight prediction system for aircraft-induced cirrus formed from contrails for commercial aircraft operators, who typically have little to no information on which flights cause long-lived cirrus clouds. In partnership with Southwest Airlines, GE’s system would combine detailed engine operational data, a hybrid physics and machine learning model, on-airplane data, and real-time satellite observations to predict aviation-induced cirrus that last more than 5 hours. (Award amount: $1,500,000)
Northrop Grumman Systems Corporation will develop a contrail prediction and avoidance system to scout optimal altitudes for flight crew that would feature a predictive algorithm and new airborne instrumentation. The team’s radiometric temperature and humidity sensor would measure the environmental conditions above, below, and in front of an aircraft to enable flight crew to proactively respond to regions conducive to long-lived cirrus formation minutes before entering the area. (Award amount: $2,490,000)
RTX Technologies Research Center will develop a platform for forecasting aircraft induced cirrus potential 100 kilometers ahead of the aircraft (up to 10 minutes ahead of time). The platform would include a novel, on-board lidar sensor for water vapor that would be installed on a small fraction of a fleet’s aircraft to furnish data and predictions for the entire fleet. (Award amount: $2,500,000)
The Boeing Company will develop a comprehensive approach for mitigating aircraft induced cirrus that would leverage satellite observations, deep learning, new developments in onboard humidity sensors, and a numerical weather prediction model. Useful for flight planning, Boeing’s approach could improve observational datasets, forward scientific understanding of humidity in the upper troposphere, and advance weather forecasting capabilities for the public. (Award amount: $2,497,451)
Universities Space Research Association will develop a real-time, cloud-based aviation contrail prediction and observation system that would improve airspace operations through new atmospheric data services and ensemble modeling approaches. The system would advance an existing cutting-edge contrail computer model with a novel machine learning approach to produce forecasts of persistent contrail-forming regions. (Award amount: $1,000,000)