Avoiding runway queues means reducing aircraft emissions

The world's busiest airports are located in and around metropolises and megacities

There are thousands of airports worldwide and many millions of takeoffs every year. The world’s busiest airports are located in and around metropolises and megacities. In Chicago (USA), Atlanta (USA), Los Angeles (USA), Dallas (USA) and Beijing (China) are the six most busy airports by aircraft movements in 2014. With regard to arriving and departing passengers, Atlanta (USA), Beijing (China), London (UK), Tokyo (Japan) Los Angeles (USA) and Dubai (UAE) are the busiest airports in the world (2014) with more than 450 million passengers. During 2014, the highest number of passengers went through airports in the Asia-Pacific region (2.3 billion, up 7.1% over 2013). Every takeoff means a lot of aircraft emissions polluting city air and causing smog.

The waiting time for the takeoff does not end after boarding. When a plane is leaving the gate, passengers are forced to a test of patience. The long queue of flights awaiting the takeoff can keep a plane idling. During this period, they burn kerosene and produce carbon dioxide. Considering a million takeoffs every year, there might be a noteworthy potential to avoid waste and unnecessary aircraft emissions.

Taxiing times of 52 minutes during busy periods at Newark Liberty International Airport cause pointless aircraft emissions

Recently, scientists at the Massachusetts Institute of Technology (MIT) developed a queuing model to forecast the waiting time of a plane before takeoff. It takes into account the weather conditions, runway traffic, and outgoing and incoming flight schedules. It enables to reduce the traffic on maneuvering areas and minimize runway congestions. In case of a queue, following planes get the instruction to stay at the gate.

“Each gate-held aircraft saves 16 to 20 gallons of fuel, because it’s not idling. And that adds up.” Balakrishnan says

Hamsa Balakrishnan, an associate professor of aeronautics and astronautics and engineering systems and an affiliate of the Institute for Data, Systems, and Society at MIT, says that in tests at several U.S. airports, the model encouraged controllers to hold flights back during certain times of the day. It results in significant kerosene savings. “In our field tests, we showed that there were some periods of time when you could decrease your taxi time by 20 percent by holding aircraft back,” Balakrishnan says. “Each gate-held aircraft saves 16 to 20 gallons of fuel, because it’s not idling. And that adds up.”  Thus, not only kerosene consumption can be reduced but also aircraft emissions.

According to Balakrishnan, hubs like John F. Kennedy International Airport, Newark Liberty International Airport, and Philadelphia International Airport were congested 10 to 20 percent of the time in 2007.  Passengers experienced taxiing times of 52 minutes during busy periods at Newark. Even during less busy periods, they were forced to be patient for 14 minutes. Individual instructions can reduce the waiting periods. “It’s mostly on the fly,” she says. “Sometimes, if there is a controller with a lot of experience or intuition, they might actually decide they’ll hold aircraft back. Historically, though, they don’t, they just let everybody go. Which is why you have queues of 40 aircraft waiting at the runway. And you want to avoid that.”

“If you predict only 10 aircraft are likely to take off in the next 15 minutes, you probably don’t have to release 25 aircraft from the gate,” Balakrishnan says. “Ultimately, you want to find the right number of aircraft you need to be releasing in order to make sure you don’t have a huge amount of congestion on the ground, and at the same time you’re not starving the runway.”

The model, developed by Balakrishnan and Simaiakis, comprises two relevant modules. The first one determines the travel time from the gate to the departure runway for each plane. The influence of other arriving or departing flights are considered. The individual time for waiting in a runway queue and from joining it until takeoff is calculated by the second module. The model is tested with data from the Federal Aviation Administration’s Aviation System Performance Metrics database, which contains takeoff times, local weather data, and runway configurations of 77 U.S. airports. The team also trained the model with data from Newark Liberty. Results from tests with other airports, such as Boston’s Logan International Airport or Philadelphia’s airport, recommend an easy implementation in departure procedures.

“In 2022, there’s going to be system-wide congestion, and the belief is [that] most of the benefit of airport operations management is going to come from some sort of departure metering,” Balakrishnan says. “What you need in order to do departure metering is a way to predict what’s actually going to happen, and use that to meter. So we’re building the models to help us achieve that.”

The research was supported, in part, by the National Science Foundation.