How to reduce fuel burn on the ground and, as a result, cut CO2 emissions and costs

Initiatives to reduce CO2

The aviation industry is committed to reducing its CO2 footprint in the air and on the ground. Countries and organizations unite to become more proactive in the mission to cut CO2 emissions. During the past several years, different initiatives have been offered and launched.

Some of these initiatives are:

   • Paris Agreement

   • Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA)

   • IATA Technology Roadmap

In 2015, the world’s governments negotiated the Paris Agreement that implied that states agree to voluntarily reduce emissions. In 2016, the International Civil Aviation Organization (ICAO) adopted CORSIA to stabilize net CO2 emissions from international civil aviation from 2021. Also, IATA developed Technology Roadmap that evaluates technology opportunities for future aircraft.

Current solutions to reduce fuel burn and CO2

The aviation community is continuously looking for solutions to reduce CO2 footprint. ICAO offered different measures to reduce CO2, including aircraft related technology, improvements in air traffic management and operations, alternative fuels, and others.

Currently, some of the most prominent solutions include:

   • Aircraft and engine design

   • Sustainable aviation fuel (SAF)

   • Green taxiing

Aircraft and engine design

To address the issues of in-flight and on the ground fuel consumption, manufacturers equip aircraft with wingtip devices that reduce drag and thus fuel burn. They also test new technologies to improve an aircraft’s wing such as Airbus’ BLADE initiative.

Jet engine manufacturers put effort into developing more sustainable engines. Most conventional engine designs, however, reach a physical limit. Without significant costs, no further improvement in sustainability is possible.

Sustainable aviation fuel (SAF)

When the efficiency of jet engines cannot be further improved, other possibilities must be taken into consideration. The most promising approach is SAF. ICAO states that SAF don’t require any changes to aircraft or airport infrastructure because they function similarly to traditional jet fuel. Most modern aircraft can be fueled with a blend of SAF and aviation kerosene. KLM was the first to use SAF on a commercial flight and has been followed by several of its peers, among them Lufthansa.

SAF offers many benefits in that it reduces fuel consumption, CO2, and other pollutants. It also makes taxiing, idling, takeoff, and flying more sustainable.

Green taxiing

To reduce fuel burn while taxiing, some airlines use one engine instead of two. Hybrid-electric tractors and electric wheel motors, however, are more effective in reducing fuel burn.

Hybrid-electric tractors tow the aircraft from/to the runway, which means that aircraft engines are turned off while taxiing. The tractor driver controls the device (or captain controls it remotely) until the aircraft is ready to take off or all the way from the runway to the stand. Lufthansa has already started using hybrid-electric tractors in its operations.

An alternative approach to eliminate kerosene burn during taxiing is to equip aircraft with electric wheel motors. Instead of engines, these motors use auxiliary power unit (APU) and can carry aircraft to/from the runway. This reduces the number of vehicles on the ramp, but might lead to aircraft weight penalties and complex processes of aircraft modifications and certifications.

What else can be done to reduce fuel burn

In addition to existing solutions to reduce fuel burn and improve sustainability on the ground, airports, airlines, and ground handlers can also focus on preventing situations that lead to unnecessary fuel burn:

   • Idling while waiting for the stand to be available

   • Idling while waiting for takeoff

   • Unnecessary stops due to obstacles on the stand

   • Untimely connection and disconnection of GPU and PCA

Idling while waiting for the stand to be available

Remember times when after landing captain says, “Dear passengers, our gate is still occupied, we’ll have to wait approximately 10-15 minutes.”

Sometimes aircraft have to wait for 30 minutes or even more. The environment suffers from exhausted fumes while the plane is idling on the ramp. Passengers feel frustrated when they have to wait after the plane landed. All of this equates to airlines losing money because fuel gets burned and passengers might consider other modes of transport for their next journey.

This problem usually happens because of miscalculations in target off-block time (TOBT), the time when the departing aircraft is estimated to leave the stand. In most cases it happens due to late and inaccurate inputs by ramp agents. They are responsible for many aspects of the turnaround and sometimes updating TOBT slips away from their radar.

This issue can be solved by automating TOBT. Automated TOBT is called predicted off-block time (POBT).

Artificial intelligence (AI) can help to calculate more accurate off-block time. It analyzes real-time data from aircraft stand cameras to create POBT. It can also timestamp and analyze events that already happened to the turnaround and those still in progress, which helps to calculate even more accurate off-block time.

More accurate information helps planning and stand allocation departments better manage stands and decrease waiting times of inbound aircraft. On arriving flights, stand planners might allocate another stand if the original stand is occupied.

As a result, airlines get reduced fuel burn, better punctuality, and improved customer satisfaction.

Idling while waiting for takeoff

Often aircraft have to wait for takeoff on a taxiway, which leads to unnecessary fuel burn. This usually happens because pushback clearance is granted without taking into account stand and taxiway occupancy. Air traffic control (ATC) creates a physical queue to maximize runway capacity. They choose this method because there is no accurate off-block time that would allow creating a virtual queue instead of physical.

In many cases idling can be reduced or prevented.

To create a more accurate departure sequence, information about turnaround progress and predicted off-block time should be added to airport operational databases (AODBs).

Instead of idling on a taxiway, departing aircraft might be instructed to wait for takeoff at the gate while connected to ground power unit (GPU) and preconditioned air unit (PCA).

AI can model optimal flow of aircraft from their stands to the runway. It can suggest a pushback sequence that minimizes congestion and, as a result, fuel burn on taxiways.

Unnecessary stops due to obstacles on the stand

Aircraft often make unnecessary stops at the stand before arriving at the gate. It can happen due to inappropriately placed ground service equipment (GSE such as towing bar, staircase, etc.) or other obstacles on the stand. The aircraft has to wait for the stand to be cleared, which results in unnecessary fuel burn.

Artificial intelligence can mitigate this issue. It can detect if the stand is not clear and notify a ramp agent about that, which prevents unnecessary fuel burn and delays. AI also provides historical data about such incidents; it can be used to train airport staff.

Untimely connection and disconnection of GPU and PCA

Ground handling staff is instructed to connect GPU and PCA right after the aircraft is parked and disconnect from GPU and PCA as close to the pushback as possible. Sometimes connection to GPU and PCA happens later than it should, and disconnection from GPU and PCA happens earlier than it should. This leads to unnecessary fuel burn.

Computer vision can monitor punctuality of connection and disconnection of GPU and PCA. According to Hawthorne effect, observation increases people’s performance. This means that monitoring might help to increase timeliness of connection and disconnection of GPU and PCA. AI can also detect and report irregularities such as accidental GPU disconnection. All of this helps to reduce fuel burn.

Professionals working in the aviation industry need to continue looking for new ways to improve sustainability. In addition to aircraft and engine design, sustainable aviation fuel, and green taxiing, they can use artificial intelligence to optimize operations and, as a result, reduce unnecessary fuel burn. This will lead to a more sustainable ramp and will help to reduce fuel-related expenses.

Petr Zhigalin has over 6 years of experience in aviation. He worked as a business aviation supervisor and as an airline duty manager. He has expertise in both ground handling and terminal operations. His current role includes analysis of aviation-related data generated by artificial intelligence.