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Arrival delay at destination(s) Departure delay at origin airport(s)
Scheduled block time Actual block time
Deviation from the long term
average (2003-2009) in minutes
Source: CODA; PRC Analysis
Figure 41: Evolution of scheduled block times in Europe (intra-European flights)
PRR 2009 Chapter 4: Air Transport Network Performance
33
4.3.8 Arrival delay is mainly driven by departure delay at the origin airports. The drop in
departure and arrival delay due to the economic crisis and the resulting fall in traffic in
2009 is striking.
4.3.9 While no significant change in
block times can be observed at
European level, the situation
at local level can be different.
4.3.10 Figure 42 shows the evolution
of the block time for intra-
European flights bound for
London Heathrow.
4.3.11 Actual block times have
increased continuously until
2008. This is reflected to some
extent in the scheduled block
times which have increased by
more than 1 minute in the last
2 years.
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Dec-02
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Jun-09
Dec-09
Arrival delay at destination(s) Departure delay at origin airport(s)
Scheduled block time Actual block time
Deviation from the long term
average (2003-2009) in minutes
Source: CODA; PRC Analysis
Figure 42: Block times on inbound flights to London
4.3.12 In 2009, actual block times (blue line) dropped sharply as a result of the crisis and this
starts to be reflected in the block times of the winter schedules (red line).
4.3.13 Additionally it is interesting to note that the arrival delay in London (LHR) is clearly
affected by departure delays (green line) and also the actual block times (blue line).
4.4 Predictability of air transport operations
4.4.1 Due to the multitude of variables
involved in air transport, a certain
level of variability is natural.
4.4.2 However, depending on the magnitude
and frequency of the variations, those
variations can become a serious issue
for airline scheduling departments as
they have to balance the utilisation of
their resources (aircraft, crew, etc.)
with the targeted service quality.
4.4.3 Figure 43 shows the variability on
intra European flights by flight phase.
The band between the 80th and 20th
percentile (green bar) shows that very
few flights depart before their
scheduled departure time but a
considerable number of flights arrive
before their scheduled arrival time.
Predictability vs. Efficiency
“Predictability” evaluates the level of variability in air
transport operations as experienced by airlines (i.e.
variability of flight XYZ123 from A to B). It focuses on
the variance (distribution width) associated with the
individual phases of flight (1).
In order to limit the impact from outliers, variability is
measured as the difference between the 80th and the 20th
percentile for each flight phase. Flights scheduled less
than 20 times per month are excluded.
“Efficiency” generally relates actual performance to a predefined
optimum (2). It can be expressed in terms of fuel
and time.
Time
Observations
(2) Closer to
Optimum
(1) Reduce
Variability
4.4.4 This is consistent with the observation made in Figure 39 which shows the percentage of
arrivals more than 15 minutes ahead of schedule.
PRR 2009 Chapter 4: Air Transport Network Performance
34
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20
2003
2004
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2009
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2005
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2009
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2003
2004
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2008
2009
Departure time Taxi-out phase Flight time (cruising
+ terminal area)
Taxi-in phase Arrrival time
minutes
20th Percentile 80th Percentile Standard Deviation
Gate-to-gate phase Source:
EUROCONTROL/ CODA
Figure 43: Variability of flight phases on Intra European flights
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Performance Review Report 2009(31)
