Business priorities for sustainable aviation – why time matters

By default, operational efficiency benefits have been positioned as long-term actions, with small improvements every year. For example, the UK’s Net Zero carbon roadmap, assumes that improvements grow slowly from 2020 to 2050.

What if operational efficiency improvements were prioritised now? This could be a strategic play – achievable short-term gains to fuel long-term solutions with two important impacts:

How much can we save through operational improvements?

We can save fuel and emissions in aviation through a host of operational efficiency improvements. But the business case for these savings is not always clear, or even remotely understandable. If we see a claim of 10% savings in fuel and emissions, we need to ask ‘10% of what’? So, in this article we take a look at the benefits of saving emissions through operations with a quantitative eye.

First, let’s get a sense of proportion. From today’s operations we are unlikely to be able to save more than 10% of a flight’s total fuel burn through improved airline, airspace and air traffic management initiatives. In Figure 1 we show a range of operational efficiencies for which we have normalised the estimating savings to cruise fuel burn. This adds up to over 14%. However, it is likely that the benefits overlap and there are unaccounted for trade-offs.

For example, continuous descent operations are a method of improving vertical flight efficiency, which in turn saves fuel. Compared to cruise flight the potential benefit is about 0.7% reduction in fuel. This is unlikely to be achieved in practice, however, because of the need to separate arriving and departing flights vertically, reducing the fuel savings.

Figure 1: Airspace Unlimited estimates of operational benefit normalised to cruise fuel burn

A basket of measures

What should be clear from Figure 1 is that there exists a basket of operational efficiencies. There are 16 measures in the figure that are straightforward to implement and can typically save 0.5-1%. There are for sure overlaps in the benefits, but a good way to look at this is that the overlapping efforts will increase the likelihood of achieving the benefits.

How are these measures saving fuel?

We can categorise fuel saving as either by reducing thrust or flight time, although there can be some overlap.

Thrust

Aircraft are more efficient the higher they fly, as drag is reduced in thinner air, and therefore less thrust is needed. However, it takes energy to climb so the optimum flight trajectory is a continuous climb, or more practically a step climb.

It also takes fuel to carry fuel, hence the introduction of rules on ‘tankering’ in the European Union. This requires that aircraft are fuelled only for the next flight and not any following flights. ‘Tankering’ fuel for several flights increases the aircraft weight, which then requires more fuel to carry this additional weight. A related idea is to fly long haul with fuelling stopovers. The logic for it taking fuel to carry fuel comes from the ‘Breguet Range Equation.’

Flight (and taxi) time

By flight time we do not mean flying faster, which requires higher thrust, but reducing unnecessary flight time. Our work in optimising Special Use Airspace and enroute charges modulation has the potential to reduce flight times by around 2%. This also benefits from optimising to flight time, not distance.

Performance based navigation (PBN) is included in the figure as being a causal factor in benefits, but PBN was developed for increasing air traffic controller productivity, not flight efficiency. We believe it is an open question as to whether PBN really helps flight efficiency.

Taxi time reduction is very interesting at airports. From data on European taxi-times there could be as much as 2.7% of cruise-equivalent fuel burn saved by various measures from reduced-engine taxi to autonomous or remotely controlled ‘taxi-bots.’ Note that aircraft engines need to be warmed-up before take-off, some requiring as much as 9 minutes of taxi to do so (737 Max).