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EUROCONTROL PRR 2013 Performance Review Report An Assessment of Air Traffic Management in Europe during the Calendar Year 2013 Performance Review Commission I May 2014
EUROCONTROL
PRR 2013
Performance Review Report
An Assessment of Air Traffic Management in Europe during the Calendar Year 2013
Performance Review Commission I May 2014
Background
This report has been produced by the Performance Review Commission (PRC). The PRC was established by the Permanent Commission of EUROCONTROL in accordance with the ECAC Institutional Strategy 1997. One objective of this strategy is “to introduce a strong, transparent and independent performance review and target setting system to facilitate more effective management of the European ATM system, encourage mutual accountability for system performance…”
All PRC publications are available from the website: http://www.eurocontrol.int/prc
Notice
The PRC has made every effort to ensure that the information and analysis contained in this document are as accurate and complete as possible. Only information from quoted sources has been used and information relating to named parties has been checked with the parties concerned. Despite these precautions, should you find any errors or inconsistencies we would be grateful if you could please bring them to the PRU’s attention.
The PRU’s e-mail address is [email protected]
Copyright notice and Disclaimer
© European Organisation for the Safety of Air Navigation (EUROCONTROL)
This document is published by the Performance Review Commission in the interest of the exchange of information.
It may be copied in whole or in part providing that the copyright notice and disclaimer are included. The information contained in this document may not be modified without prior written permission from the Performance Review Commission.
The views expressed herein do not necessarily reflect the official views or policy of EUROCONTROL, which makes no warranty, either implied or express, for the information contained in this document, neither does it assume any legal liability or responsibility for the accuracy, completeness or usefulness of this information.
Printed by EUROCONTROL, 96, rue de la Fusée, B-1130 Brussels, Belgium. The PRC’s website address is http://www.eurocontrol.int/prc. The PRU’s e-mail address is [email protected].
EUROCONTROL
DOCUMENT IDENTIFICATION SHEET
DOCUMENT DESCRIPTION
Document Title
Performance Review Commission Performance Review Report covering the calendar year 2013 (PRR 2013)
PROGRAMME REFERENCE INDEX EDITION: EDITION DATE:
PRC Performance Review Report Final report 22 May 2014
SUMMARY
This report of the Performance Review Commission analyses the performance of the European Air Traffic Management System in 2013 under the Key Performance Areas of Safety, Capacity, Environment and Cost-efficiency.
Keywords Air Traffic Management Performance Measurement Performance Indicators ATM ANS
CONTACT:
Performance Review Unit, EUROCONTROL, 96 Rue de la Fusée, B-1130 Brussels, Belgium. Tel: +32 2 729 3956, E-Mail: [email protected] http://www.eurocontrol.int/prc
DOCUMENT STATUS AND TYPE
STATUS DISTRIBUTION Draft General Public Proposed Issue EUROCONTROL Organisation Released Issue Restricted
INTERNAL REFERENCE NAME: PRR 2013
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
ii
EXECUTIVE SUMMARY
European ATM Performance
Key Performance Indicator Data & commentary
TR
AF
FIC
IFR flights Eurocontrol Variation
2013 9.45M -0.8%
Average daily IFR flights in Europe decreased by -0.8% in 2013 with notable regional variations in traffic evolution. For 2014, the STATFOR 7-year forecast expects the European flights to grow by +1.2% (baseline scenario) with an average annual growth rate of 2.6% between 2014 and 2019. At system level, traffic is expected to reach pre-economic crisis levels by 2016.
SA
FE
TY
Accidents with ANS contribution
Eurocontrol Variation
2013 0 -
After the increase between 2009 and 2011, total commercial air transport accidents continuously decreased again to the lowest level over the past 11 years in 2013. Accidents with ANS contribution are rare in Europe and there were no accidents with ANS contribution over the past three years.
CA
PA
CIT
Y
En route ATFM delay per flight
Eurocontrol Variation
2013 0.53 -0.1 min./flt.
Albeit in the context of declining traffic, en-route ATFM delays decreased for the third consecutive year to 0.53 minutes per flight in 2013 which is the lowest level ever recorded.The most constraining ACCs in 2013 were Nicosia, Warsaw, Barcelona, and the Canarias.
EN
VIR
ON
ME
NT
En route flight efficiency (vs.
flight plan) Eurocontrol Variation
2013 4.86% -.01%pt
After the positive trend in previous years, horizontal en route flight efficiency (flight plan) in 2013 remained at a similar level as in 2012. The gap between planned and actual trajectory differs significantly at European level and by State suggesting scope for improvement.
CO
ST
S
En-route ANS costs per SU
(€2009) Eurocontrol Variation
2012 55.1 +2.3%
Real en-route unit cost deteriorated after two years of consecutive improvement (an increase of +2.3% in 2012 compared to 2011). At system level, 2012 was a year of decrease in traffic (-1.2%). At the same time, en-route ANS costs increased overall by +1.0%.
-8%-6%-4%-2%0%2%4%6%8%10%12%14%16%
2
4
6
8
10
12
141990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
% a
nn
ual
gro
wth
(b
ars)
IFR
fli
gh
ts (
mill
ion
)
STATFOR7-year forecast
(Feb. 2014)
2013 TRAFFIC 9.45 M (-0.8%) STATFOR
(Feb. 2008)
STATFOR(Feb. 2011)
4 3 3 1 2 1 2 10
10
20
30
40
50
200
3
200
4
200
5
200
6
200
7
200
8
200
9
201
0
201
1
201
2
201
3
Number of accidents
Source: EASA Accidents with ANS contribution
Total commercial air transport (CAT) accidents and accidents with ANS contribution (fixed wing, weight > 2250Kg MTOW)
2.2
2.9
4.5
2.9
2.5
1.4
0.9
0.8 0.9 1.0 1.2 1
.4
0.9
2.0
1.1
0.6
3
0.5
3
70
80
90
100
110
120
130
140
150
0.00.51.01.52.02.53.03.54.04.55.0
199
7
199
8
199
9
200
0
200
1
200
2
200
3
200
4
200
5
200
6
200
7
200
8
200
9
201
0
201
1
201
2
201
3
Tra
ffic
ind
ex (
base
: 19
97)
En
-ro
ute
AT
FM
de
lay/
flig
ht (
min
.)
ATC Other (strike, equipment, etc.) WEATHER
OTHER (Special event, military, etc.) IFR Traffic
Average en-route ATFM delay per flight
source: Network Manager
4.91 4.87 4.86
3.31 3.20 3.14
2.02.53.03.54.04.55.05.56.0
200
9
201
0
201
1
201
2
201
3
Flight Plan (KEP) Actual trajectory (KEA)
Horizontal en route flight efficiency (EUROCONTROL area)
inef
ficie
ncy
2009/10 KEA data based on regression analysis
60.1 56.7
53.8 55.1 53.4
51.7
90
95
100
105
110
115
120
125
20
25
30
35
40
45
50
55
60
65
70
2009
Act
uals
2010
Act
uals
2011
Act
uals
2012
Act
uals
2013
(F
)
2014
(F
)
En-
rout
e co
sts
and
SU
inde
xes
(200
9=10
0)
En-
rout
e re
al c
ost p
er S
U (
€200
9)
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
iii
Introduction PRR 2013 presents an assessment of the performance of European Air Navigation Services (ANS) for the calendar year 2013.
ANS in European Air Transport Compared to 2012, average daily IFR flights in Europe decreased by -0.8% in 2013 with notable regional variations in traffic evolution. Despite the lower number of flights, load factors and average aircraft size continued to increase leading to a growth in passenger numbers.
For 2014, the STATFOR 7-year forecast published in February 2014 expects the European flights to grow by +1.2% in the baseline scenario (Low: -0.1%; High: +2.3%). The average annual growth rate between 2014 and 2019 is forecast to be at +2.6% with IFR flights expected to reach pre-economic crisis levels (2008) by 2016.
The high level evaluation of ANS performance in the European air transport context sets the scene for the more detailed analyses in the respective chapters of this report:
Safety: After the increase between 2009 and 2011, total commercial air transport accidents continuously decreased again to the lowest level over the past 11 years in 2013. Accidents with ANS contribution are rare in Europe and there were no accidents with ANS contribution over the past three years. A more detailed analysis focusing on ANS safety performance is provided in Chapter 3.
Capacity: Albeit in a context of declining traffic, the share of flight arriving within 15 minutes after the schedule (punctuality) reached an all-time high of 84.0% in 2013. The share of ANS-related primary delays in 2013 was 23.5% (i.e. 76.5% of primary delays were not due to ANS) which represents a further reduction compared to 2012. Continuing the positive trend observed over the past two years, en route and airport arrival ATFM delays continued to decrease by 17% and 20% respectively in 2013. A detailed analysis of operational ANS performance en route and at airports is provided in Chapter 4 and 5.
Environment: Overall, the ANS-related impact on total aviation related fuel burn is estimated at 6% (equivalent to 0.2% of total European anthropogenic CO2 emissions). All three ANS related indicators (additional taxi-out time, en route flight efficiency, additional ASMA time) showed an improvement with a positive impact on fuel burn. The reduction in total additional fuel burn is due to small improvements in unit fuel burn and a notable reduction of traffic compared to 2012.
Cost-efficiency: En route ANS costs in the SES area increased by +1.3% in 2012 vs. 2011, which is well below initial plans in November 2011. Entry into force of the Single European Sky (SES) charging regime meant lower revenue than planned as traffic was lower than planned. For 2013, the latest projections indicate an increase in en route (+4.5%) and terminal ANS costs (+2.0%) in the SES area. As in 2012, actual costs for 2013 may be lower due to traffic risk sharing. A detailed analysis focusing on en route and terminal ANS cost-efficiency is provided in Chapter 6.
With the advent of the SES performance scheme, more precise data are becoming available (Correlated Position Reports and data provided directly by airport operators). The PRC decided to use the new data flows from this PRR onwards, which improves the accuracy of indicators but creates a discontinuity in time series and limits the geographical scope of the analysis to SES States and to the period 2011 to 2013 as the same level of data is presently not available for all EUROCONTROL States.
The Total economic cost concept presents a consolidated view of direct and estimated indirect costs borne by airspace users and enables a first assessment of interdependencies between KPAs outside safety. It is not an assessment of ANS inefficiencies and, inevitable margins of uncertainty need to be considered.
Safety (2012) In 2013, there was no accident with ANS contribution. The number of reported ANS-related serious incidents decreased, and reached the lowest level in the past 11 years. In the period 2011-2013 the main ANS related serious incident categories remain losses of separation in the air, runway incursions and ATM/CNS occurrences.
Overall, performance review indicates high levels of safety in Europe, as only a very small portion of the total flights are reported as incidents (approximately 0.3%).
The level of occurrence reporting to EUROCONTROL Annual Summary Template (AST) reporting
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
iv
mechanism is still unsatisfactory. There are three EUROCONTROL States not submitting the AST (Monaco, Turkey and Ukraine) and the level of reporting from seven States is still below the established baseline. However, it has to be noted that the number of ECAC Member States reporting increased to a record level of 36 in 2012.
The number of un-assessed incidents is still higher than the levels in 2007. This situation is of concern, not only for the outcome of the analysis at European level, but also for the national safety analysis and for the sustainability of the human reporting system. Further, safety occurrences provided by States to EUROCONTROL through the AST mechanism are often incomplete. This diminishes the capability of safety analysis at European level.
States should ensure the provision of sufficient capabilities to deal with the reporting, investigation, storing, classification and analysis of ATM safety occurrences.
Where no existing regulations are in place, States should support the inclusion of specific provisions regarding the severity classification of ATM occurrences in their safety regulatory framework.
There is an urgent need to accelerate the deployment of automatic safety data reporting/monitoring tools in Europe in order to improve trend analysis for identification of safety risks and measure the effectiveness of safety improvement action. They can also remove subjectivity and variability in reporting. Deployment of such tools should also improve the reporting culture and consequently the level of reporting. Therefore, States are encouraged to expedite deployment of automatic safety data reporting/monitoring tools.
In order to use data from automated safety data reporting/ monitoring tools at State, FAB or European level, the event triggers for each type of occurrence need to be harmonised. It is proposed that a pan-European harmonisation project is conducted to ensure that data can be shared and aggregated.
Operational En-route ANS Performance (2013) En route ATFM delays in 2013 decreased for the third consecutive year. Overall, en route ATFM delays decreased by 17% from 0.63 to 0.53 minutes per flight in 2013 which is the lowest level ever recorded. It must also be stated that the level of traffic was less than in the two previous years.
While most ACCs in Europe provided sufficient capacity, there were four ACCs in 2013 with more than 30 days at delay levels above one minute per flight: Nicosia (198), Warsaw (62), Barcelona (40), and the Canarias (37). These four ‘constraining ACCs’ accounted for 28% of total en route ATFM delay in 2013 whilst handling just 6.9% of the traffic.
Investigation into the specific classification of ATFM delay highlighted inconsistency in how delays are assigned both in terms of the causal factor and the appropriate location. Such inconsistency is detrimental to performance improvement and there is a risk that this could lead to a financial impact on ANSPs due to incentive schemes. The PRC intends to do further investigation and reporting on this topic.
Although the amount of en route ATFM delay is at the lowest level ever recorded, in view of the exponential relationship between capacity constraints and delay, it is vital to plan and implement adequate capacity in advance of the expected growth in traffic.
After the positive trend in previous years, horizontal en route flight efficiency in 2013 remained at a similar level as in 2012. At European level, the observed level of en route flight inefficiency in 2013 was 4.86% for the filed flight plans with the actual trajectory being 1.7% better than the filed plans (3.14%).
The gap between planned and actual trajectory differs significantly by State which suggests scope for improvement. Additionally to the initiatives to improve flight efficiency, improved planning closer to the actual trajectory would improve predictability and also reduce required fuel load and thence reduce costs.
By the end of 2013, 23 of the 64 ACCs had implemented various steps of Free Route Operations. Clear benefits can be observed in areas where free route airspace has been implemented.
While route availability and changes in military activity appear to be contributing factors to the observed gap between filed and actual flight trajectory, more research is required to better understand all the contributing factors (flight planning, awareness of route availability, civil-military coordination, etc.). This requires however improvements in data collections for planned and actual airspace restrictions and planned and actual route availability.
Close civil military cooperation and coordination is a crucial enabler to improve capacity and flight efficiency
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
v
performance. A critical review of the application of the Flexible Use of Airspace (FUA) concept could help improving performance.
The evaluation of the impact of “out of area” traffic on ATM performance illustrated that “out of area” traffic introduces unpredictability in the network which can be improved through closer coordination and cooperation with States outside the EUROCONTROL area.
Operational ANS Performance at Airports (2013) On average, movements at the top 30 airports in Europe decreased by 1.5% in 2013 and operational performance remained nearly unchanged as shown in table below.
Operational ANS performance at the top 30 airports 2012 2013
Inbound (minutes per arrival)
Airport arrival ATFM delay 0.9 0.8
Additional ASMA time 2.1 2.2
Outbound (minutes per departure)
ATC pre-departure delay 0.5 0.6
Additional taxi-out time 3.7 3.7
From an airport perspective, one indicator considered in isolation cannot be representative of the overall ANS performance. When performance is considered from a transversal perspective at airports, it appears to be better for arrival flows than for departures. This is expected in order to discharge the airspace and minimise fuel consumption airborne. On the inbound flow, Additional ASMA Time however remains relatively great compared to Airport Arrival ATFM Delay.
The Network Manager initiated a project in order to enhance the integration of airports into the ATM Network, mainly to exchange information during adverse weather conditions. The PRC will monitor performance improvements.
The PRU initiated some research on new performance indicators:
Additional Taxi-in Time is being investigated as a very first step to the extension of the en-route-to-en-route performance perspective of airports. The trial needs to be validated with airport operators. The efficiency of turnaround and stand occupancy times should also be investigated from a global airport performance perspective, provided that data is available.
Further research is required to understand and quantify the resilience of ANS to perturbations as well as associated disruption thresholds.
Capacity indicators (additional ASMA and taxi-out time) are converted into environment indicators, enabling a better assessment of the emission impact of airport operations.
Higher level of details, comparability, consistency and lower ambiguity are expected as key benefits of receiving high-quality data also from non-SES airports. The PC’s decision regarding the set-up of appropriate airport data flow at non-SES-airports should be implemented in full.
The airports, through the States, should be encouraged to use the sub-codes 89 as a standard. In parallel, the use of Target Start-Up Time (TSAT) and Target Off-Block Time (TOBT) available at A-CDM airports should be investigated as an alternative to (sub-) codes 89.
ANS Cost-efficiency (2012) In a majority of States, traffic had decreased in 2012 compared to 2011 (-1.2% at system level) and turned out to be much lower than previously planned/forecasted (by -4.6% at system level). On the other hand, the total costs for providing en-route services increased by +1.0% in real terms compared to 2011 at system level, although they are lower than previously planned for 2012 (by -3.4%). As a result, at face value, the real en-route unit cost per service unit for 2012 increased by +2.3%.
However, the analysis shows that this deterioration in cost-efficiency performance is due to two factors which are not strictly related to the costs incurred in respect of en-route services provided in 2012, i.e. the impact of a one-off reduction in EUROCONTROL costs that occurred in 2011 in relation to International Financial Reporting Standards (IFRS) budgeting and special annex receipts, and the impact of increases in (accounting) provisions for future liabilities (mainly for pensions) reported as actual costs for 2012. If the effects of these two factors are excluded, the total actual costs for 2012 would have been lower by -1.5% compared to 2011 and would have therefore resulted in an improvement of the unit cost (decrease of -0.2%).
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
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The volatility of the (accounting) provisions raises concerns in the context of charging and performance, as changes in these provisions do not necessarily represent costs directly attributable to the provision of ANS in the year in which they are recorded. Moreover, these changes in provisions, especially when related to pensions, can be significant in size and thereby influence significantly the resulting cost-efficiency indicator, which may no longer reflect the adjustment of costs to the traffic context and the genuine cost-efficiency performance of States/ANSPs or even the Pan-European system as a whole. For those States under the “determined costs” method, these increases may also significantly impact the future amounts charged to airspace users if deemed eligible as exemptions from cost-sharing in accordance with the SES Charging Regulation. For this reason, it is recommended to evaluate how genuine cash payments rather than accounting accruals payments could be recognised in the calculations of pension costs for charging purposes.
For the SES States, 2012 is the first year of application of the “determined costs” method with specific risk-sharing arrangements defined in the charging regulation aiming at incentivising economic performance. For the other nine EUROCONTROL States participating in the Route Charges System, the “full cost-recovery method” continued to apply in 2012. As this is the first year of application of the two methods in parallel, it is not yet possible to identify whether different trends and behaviour exist between the SES States and the other States in the Route Charges System and to draw any firm conclusions.
A recent revision (November 2013) of the “EUROCONTROL Principles for establishing the cost-base for en route charges and the calculation of the unit rates” gives the possibility for the States which are not bound by the SES to opt for either the “full cost-recovery method” or the “determined costs method”. It can therefore be expected that some non-SES States will apply the “determined costs method” in the future, given the incentive possibilities offered by this method. The supervision and assessment of the level of the “determined costs” and associated unit rates charged to users is an integral part of the “determined costs method”. It requires Performance Plans to be drawn-up, covering all the different KPAs and potential interdependencies and proper ex-ante assessments carried out by an independent body.
Plans and forecasts for 2013-2014 show a decrease in the real en-route unit cost of -3.1% p.a. compared to actual 2012. Such a reduction is driven by high traffic forecasts made at the time of adopting the RP1 Performance Plans for the SES States. As the traffic will not materialise, States will need to adapt their 2013 and 2014 actual costs to the new traffic context to avoid significant increases in their unit costs and, for the SES States, to avoid significant losses in RP1.
2015-2019 preliminary figures currently show moderate growth in traffic and stabilisation in costs over the period. These forecasts will however have to be adapted so as to be collectively consistent with the EU-wide targets adopted for the SES States for the RP2 period. It would be advisable that the other EUROCONTROL States which are not bound by the SES Regulations aim at following consistent trends with the SES States.
High level analysis of terminal ANS costs indicates that, between 2011 and 2012, terminal ANS unit costs in real terms fell (-2.0%) for the third year in a row. The decrease in unit costs mainly reflects a reduction in terminal ANS costs in real terms (-3.4%) in a context of traffic decrease (-1.4%, TNSU).
Moreover, compared to what was foreseen for the year 2012 (November 2011 Reporting), actual terminal ANS costs are some -4.9% lower than planned. As the similar trend is also observed for en-route, at system level there were no significant cost reallocation from en-route towards terminal, and the cost-efficiency improvement due to the SES target setting on en-route is likely to also have had a positive impact on terminal ANS costs, mainly due to the level of shared/common costs.
A terminal navigation service units (TNSU) forecast was produced by STATFOR for the first time in 2013 (March 2013). This forecast has been used to compute SES trends in terminal ANS unit costs until the end of RP1. Plans and forecasts for 2013-2014 indicate slightly decreasing unit costs (-0.4% p.a.) compared to 2012 actual data.
A number of differences (i.e. the number and size of aerodromes, the traffic levels and complexity, the scope of ANS provided, the charging policy including the applied cost allocation between en-route and terminal) introduce comparability issues when analysing and benchmarking terminal ANS performance levels across States/Terminal Charging Zone (TCZ)/airports.
Differences in cost-allocation can affect the analysis of en-route and terminal cost-efficiency. It is therefore important to keep a gate-to-gate perspective when monitoring ANSP cost-efficiency performance.
ANSP high level benchmarking analysis indicates that the lower unit economic costs observed at Pan-European system level for the year 2012 (-4.8%) mainly reflects a reduction in ATFM delays compared to
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
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2011 (-39.3%) while gate-to-gate unit ATM/CNS provision costs rose by +1.7%. The increase in unit ATM/CNS provision costs is mainly due to the fact that in 2012, ATCO employment costs rose faster (+1.3%) than ATCO-hour productivity (+0.3%) while unit support costs increased (+2.0%) in a context of traffic decrease (-1.9%).
PRC Recommendations 2013
The Provisional Council is invited to: Rationale for the recommendation a. note the PRC’s Performance Review Report for 2013
(PRR 2013) and to submit it to the Permanent Commission;
b. encourage States to review their State Safety Programmes and Safety Plans to ensure that major risks are being addressed;
Although the accident statistics show a reduction in ANS related accidents in recent years, serious incident statistics demonstrate that mid-air collision and runway incursion accidents could still occur.
c. urge those States that have not yet done so to implement the Provisional Council’s Decisions 8.1 b and c (PC 39, May 2013) as a matter of urgency;
The 2011 PRC recommendations requesting improvement in safety data reporting and safety data quality are not yet adequately implemented and therefore are reiterated as last year.
d. request States to ensure that sufficient resources are made available for:
(i) the reporting, investigation, storing, and analysis of ATM safety occurrences; and,
(ii) the risk assessment and hence, severity classification of all reported ATM safety occurrences;
The number of un-assessed incidents is increasing since 2007. This situation is of concern, not only for the outcome of the analysis at European level, but also for the national safety analysis.
e. urge States to support the inclusion of specific provisions regarding the severity classification of ATM occurrences in their safety regulatory framework;
Where no existing regulations are in place, States should support the inclusion of specific provisions regarding the severity classification of ATM occurrences in their safety regulatory framework.
f. encourage States to expedite the deployment of automatic safety data reporting/monitoring tools in Europe to improve the identification of safety risks and to measure the effectiveness of safety improvement action;
There is an urgent need to accelerate the deployment of automatic safety data reporting tools to improve the identification of safety risks and measure the effectiveness of safety improvement action. Deployment of such tools should also improve the reporting culture and consequently the level of reporting.
g. request the Director General to initiate a pan-European harmonisation project, in order to use data from automated safety data reporting/monitoring tools at State, FAB or European level, because the event triggers for each type of occurrence need to be harmonised;
There is a need to conduct a pan-European harmonisation project to ensure that data can be shared and aggregated.
h. urge the States and ANSPs to ensure that updated information on airspace and route availability is transmitted to the Network Manager in a timely manner and made available to airspace users for flight planning purposes;
The analysis reveals a considerable gap between flight plan and actual flight trajectories with an impact on fuel burn (additional carriage) and capacity (lower level of predictability of operations). To reduce the gap there is a need to ensure that the Network Manager and airspace users are continuously supplied with the latest information on airspace and route availability.
i. request the Director General to initiate the development of tools to identify the shortest route available at the time the flight commences;
Due to the lack of information on route availability, it is presently not possible to identify the shortest available route at the time the flight commences.
j. urge States to ensure an accurate and consistent classification of ATFM delays to enable constraints on European ATM to be correctly identified and resolved or mitigated;
Investigation into the specific classification of ATFM delay highlighted inconsistency in how delays are assigned both in terms of the causal factor and the appropriate location. Such inconsistency is detrimental to performance improvement.
k. urge the Director General to work with non-ECAC States to improve the predictability of traffic entering the EUROCONTROL area, in order to improve the service being provided to air traffic within the
“Out of area” flights show a lower level of predictability with an impact on safety, service quality and capacity utilisation in the periphery of the EUROCONTROL area. An enhanced exchange of information would help improving the
EXECUTIVE SUMMARY
EXECUTIVE SUMMARY PRR 2013
viii
EUROCONTROL area; situation.
l. encourage States to fully implement Airport Collaborative Decision Making (A-CDM) including Departure Planning Information (DPI) exchange with Network Operations at congested airports, in line with the related European Single Sky ImPlementation Plan and the Network Manager Performance Plan;
A-CDM is an enabler for improving the efficiency of the departure flow management at airports and also ensures a better integration of airports into the ATM network which improves network predictability and the utilisation of available resources.
m. recall its decision g) and f) at PC 39 (May 2013) encouraging those States not bound by the provisions of the SES performance scheme to provide Correlated Position Reports and data on operations at key airports (>70 000 movements), using the standards described in the SES legislation, to enable EUROCONTROL-wide data collection and ANS performance review to be harmonised;
Presently data provision in EUROCONTROL States is not harmonised. The recommendation aims at achieving a harmonised CPR (30 seconds radar update rate) and airport data collection following the standards laid out in the SES legislation. The claim is supported by sections in the en route chapter (flight efficiency) and in the airport chapter.
n. encourage those States not bound by the provisions of the SES performance scheme that wish to apply the “determined costs” method to provide for independent supervision by their national authority and a meaningful consultation with airspace users and to take due account of the level and ambition of performance improvements expected for SES States;
A recent revision (November 2013) of the “EUROCONTROL Principles for establishing the cost-base for en route charges and the calculation of the unit rates” gives the possibility for the States which are not bound by the SES to opt for either the “full cost-recovery method” or the “determined costs method”. It can therefore be expected that some non-SES States will apply the “determined costs method” in the future, given the incentive possibilities offered by this method. The supervision by their national authority and assessment of the level of the “determined costs” and associated unit rates charged to users is an integral part of the “determined costs method”.
o. urge States to take due account of the fairness, cost-relatedness and appropriateness of a strict application of International Financial Reporting Standards when establishing air navigation cost-bases and charges.
The volatility of the (accounting) provisions raises concerns in the context of charging and performance, whereas increases or decreases in these provisions do not necessarily represent costs directly attributable to the provision of ANS in the year in which they are recorded. Moreover, these increases or decreases in provisions, especially when related to pensions, can be significant in size and thereby influence significantly the resulting cost-efficiency indicator, which may no longer reflect the adjustment of costs to the traffic context and the genuine cost-efficiency performance of States/ANSPs or even the Pan-European system as a whole.
ix
T A B L E O F C O N T E N T S
EXECUTIVE SUMMARY .......................................................................................................................... II
INTRODUCTION ........................................................................................................................................... III ANS IN EUROPEAN AIR TRANSPORT........................................................................................................... III SAFETY (2012) ............................................................................................................................................ III OPERATIONAL EN-ROUTE ANS PERFORMANCE (2013) .............................................................................. IV OPERATIONAL ANS PERFORMANCE AT AIRPORTS (2013) ........................................................................... V ANS COST-EFFICIENCY (2012) .................................................................................................................... V PRC RECOMMENDATIONS 2013 ................................................................................................................. VII
PART I- BACKGROUND .......................................................................................................................... 13
INTRODUCTION .............................................................................................................................. 13 1
1.1 PURPOSE OF THE REPORT .............................................................................................................. 13 1.2 STRUCTURE OF THE REPORT .......................................................................................................... 13 1.3 GEOGRAPHICAL SCOPE ................................................................................................................. 14 1.4 TEMPORAL SCOPE ......................................................................................................................... 14 1.5 IMPLEMENTATION STATUS OF PRC RECOMMENDATIONS .............................................................. 14 1.6 PRC AS PERFORMANCE REVIEW BODY OF THE SINGLE EUROPEAN SKY ...................................... 15 1.7 EUROPEAN ANS PERFORMANCE IN THE CONTEXT OF ICAO ......................................................... 16
ANS IN EUROPEAN AIR TRANSPORT ........................................................................................ 18 2
2.1 INTRODUCTION ............................................................................................................................. 18 2.2 EUROPEAN AIR TRAFFIC DEMAND ............................................................................................... 19 2.3 SAFETY ......................................................................................................................................... 23 2.4 SERVICE QUALITY ......................................................................................................................... 24 2.5 ECONOMIC EVALUATION OF ANS PERFORMANCE ......................................................................... 30 2.6 CONCLUSIONS ............................................................................................................................... 33
PART II – KEY PERFORMANCE AREAS ............................................................................................. 35
SAFETY .............................................................................................................................................. 35 3
3.1 INTRODUCTION ............................................................................................................................. 35 3.2 REPORTING OF ANS-RELATED ACCIDENTS AND INCIDENTS ......................................................... 35 3.3 ACCIDENTS AND SERIOUS INCIDENTS ........................................................................................... 37 3.4 INCIDENTS .................................................................................................................................... 39 3.5 REPORTING AND INVESTIGATION .................................................................................................. 41 3.6 EUROCONTROL AND EU SAFETY PERFORMANCE MONITORING .............................................. 44 3.7 AUTOMATIC SAFETY DATA MONITORING ...................................................................................... 46 3.8 CONCLUSIONS ............................................................................................................................... 49
OPERATIONAL EN-ROUTE ANS PERFORMANCE ................................................................. 51 4
4.1 INTRODUCTION ............................................................................................................................. 51 4.2 EN ROUTE ATFM DELAYS ............................................................................................................ 51 4.3 EN ROUTE FLIGHT EFFICIENCY ..................................................................................................... 56 4.4 FLEXIBLE USE OF AIRSPACE .......................................................................................................... 63 4.5 NETWORK IMPACT OF “OUT OF AREA TRAFFIC” .......................................................................... 64 4.7 IMPACT OF WEATHER ON EN ROUTE ATM ..................................................................................... 67 4.8 EUROPEAN ATFM PERFORMANCE (NETWORK LEVEL) ................................................................. 69 4.9 CONCLUSIONS ............................................................................................................................... 70
OPERATIONAL ANS PERFORMANCE AT AIRPORTS ........................................................... 72 5
5.1 INTRODUCTION ............................................................................................................................. 72 5.2 ANS-RELATED OPERATIONAL PERFORMANCE AT EUROPEAN AIRPORTS ....................................... 73 5.3 DEMAND-CAPACITY BALANCING AT AIRPORTS AND AFFECTING FACTORS .................................. 80 5.4 OVERALL ANS PERFORMANCE ..................................................................................................... 83 5.5 TOPIC BRIEFINGS .......................................................................................................................... 84 5.6 CONCLUSIONS ............................................................................................................................... 89
x
ANS COST-EFFICIENCY ................................................................................................................ 90 6
6.1 INTRODUCTION ............................................................................................................................. 91 6.2 EN-ROUTE COST-EFFICIENCY DATA AT EUROPEAN LEVEL ............................................................ 91 6.3 EN-ROUTE COST-EFFICIENCY ANALYSIS: 2012 VERSUS 2011 ........................................................ 93 6.4 EN-ROUTE COST-EFFICIENCY ANALYSIS: 2012 ACTUALS VERSUS 2012 PLANS/FORECASTS ........... 97 6.5 EN-ROUTE COST-EFFICIENCY ANALYSIS: OUTLOOK FOR 2013-2018 ............................................. 98 6.6 TERMINAL ANS COST-EFFICIENCY DATA AT EUROPEAN LEVEL ................................................. 100 6.7 TERMINAL ANS COST-EFFICIENCY ANALYSIS: 2012 VERSUS 2011 ............................................. 102 6.8 TERMINAL ANS COST-EFFICIENCY ANALYSIS: 2012 ACTUALS VERSUS 2012 FORECASTS ........... 104 6.9 TERMINAL ANS COST-EFFICIENCY ANALYSIS: OUTLOOK FOR 2012-2014 .................................. 104 6.10 ANSPS GATE-TO-GATE ECONOMIC PERFORMANCE ..................................................................... 107 6.11 CONCLUSIONS ............................................................................................................................. 113
ANNEX I - IMPLEMENTATION OF PC DECISIONS ....................................................................... 116
ANNEX II – ACC TRAFFIC AND DELAY DATA (2011-2013) .......................................................... 120
ANNEX III – TRAFFIC COMPLEXITY SCORES IN 2013 ................................................................ 121
ANNEX IV – FRAMEWORK : SERVICE QUALITY ......................................................................... 123
ANNEX V – FRAMEWORK: ECONOMIC EVALUATION OF ANS PERFORMANCE ............... 125
ANNEX VI – ANALYTICAL FRAMEWORK FOR ANS PERFORMANCE AT AIRPORTS ........ 128
ANNEX VII – AIRPORT TRAFFIC AND AIRPORT ANS PERFORMANCE RECORDS ............ 129
ANNEX VIII - GLOSSARY ..................................................................................................................... 131
ANNEX IX - REFERENCES ................................................................................................................... 137
L I S T O F F I G U R E S
Figure 1-1: EUROCONTROL States (2013) ................................................................................. 14 Figure 1-2: PC action on PRC recommendations contained in PRR 2013 ..................................... 15 Figure 1-3: ICAO approach followed in the EUR Region ............................................................. 17 Figure 2-1: ANS performance in European IFR traffic .................................................................. 18 Figure 2-2: Evolution of European IFR flights (1990-2020) ......................................................... 19 Figure 2-3: Key European traffic indices (2004-13) ...................................................................... 19 Figure 2-4: Traffic variation by State (2013/2012) ........................................................................ 20 Figure 2-5: Forecast traffic growth 2013-2020 .............................................................................. 21 Figure 2-6: Traffic variation at the top 30 European airports (2013/2012) .................................... 21 Figure 2-7: Seasonal traffic variations at ATC-Unit level ............................................................. 22 Figure 2-8: Complexity scores at ATC-Unit level ......................................................................... 22 Figure 2-9: IFR flights by market segment (2013) ......................................................................... 23 Figure 2-10: Accidents in EUROCONTROL area with ANS contribution (2003-13) .................. 23 Figure 2-11: Serious Incidents in EUROCONTROL area with ANS contribution (2003-13) ....... 24 Figure 2-12: European On time performance (2004-13) ................................................................ 25 Figure 2-13: Variability of flight phases (2008-13) ....................................................................... 25 Figure 2-14: Evolution of delays and block times (2004-13) ......................................................... 26 Figure 2-15: Departure delays by cause (2010-13) ........................................................................ 27 Figure 2-16: Sensitivity to primary delays ..................................................................................... 27 Figure 2-17: Estimated ANS-related impact on fuel burn/environment (2013) ............................. 29 Figure 2-18: Long-term trend of traffic, unit costs and en route ATFM delay .............................. 31 Figure 2-19: Estimated total economic ANS-related costs (SES States) ....................................... 32 Figure 3-1: Sources of safety data used for safety performance review ......................................... 36 Figure 3-2: Scope of ANS review in this chapter ........................................................................... 36 Figure 3-3: ANS-related accidents in the EUROCONTROL area ................................................. 37 Figure 3-4: ANS-related accidents by occurrence category (EUROCONTROL area) .................. 37 Figure 3-5: ANS-related serious incidents in the EUROCONTROL area ..................................... 38 Figure 3-6: ANS-related serious incidents by occurrence category (EUROCONTROL area) ...... 38
xi
Figure 3-7: Reported high-risk SMIs in EUROCONTROL States (2003-13P) ............................. 39 Figure 3-8: Reported high-risk UPAs in EUROCONTROL States (2003-2013P) ........................ 40 Figure 3-9: Reported high-risk RIs in EUROCONTROL States (2003-2013P) ............................ 40 Figure 3-10: Reported high-risk ATM Spec. Occurrences in EUROCONTROL States (2004-
2013P) .................................................................................................................................... 41 Figure 3-11: Total number of reports and level of reporting (2002-2012) ..................................... 42 Figure 3-12: Current and possible levels of manual reporting (2001-2012) .................................. 43 Figure 3-13: Severity not classified or not determined (2005-2013P) ........................................... 43 Figure 3-14: Completeness of AST reported data in 2012 ............................................................. 44 Figure 3-15: Set-up of the European Safety Performance monitoring ........................................... 45 Figure 3-16: States with automatic reporting tools (2012) ............................................................. 47 Figure 3-17: A-SMGCS implementation status (Source: LSSIP 2012) ......................................... 48 Figure 4-1: Average en route ATFM delay (1997-2013) ............................................................... 51 Figure 4-2: En route delay per flight by classification ................................................................... 52 Figure 4-3: Monthly evolution of en route ATFM delays (2010-2013) ......................................... 52 Figure 4-4: Most en route ATFM constraining ACCs (overview) ................................................. 53 Figure 4-5: Most constraining ACCs in terms of en route ATFM (delay drivers) ......................... 53 Figure 4-6: Monthly ATFM en route delay in 2013 (Nicosia ACC) .............................................. 53 Figure 4-7: Monthly ATFM en route delay in 2013 (Warsaw ACC) ............................................. 54 Figure 4-8: Monthly ATFM en route delay in 2013 (Barcelona ACC) .......................................... 55 Figure 4-9: ATFM en route delay by weekday (Barcelona ACC) ................................................. 55 Figure 4-10: Monthly ATFM en route delay in 2013 (Canarias ACC) .......................................... 55 Figure 4-11: Changes in constraining ACCs (2009-2013) ............................................................. 56 Figure 4-12: Factors affecting flight efficiency .............................................................................. 57 Figure 4-13: Availability of CPR data (Oct. 2013) ........................................................................ 58 Figure 4-14: European wide horizontal en route flight efficiency (2011-2013)............................. 59 Figure 4-15: Flight efficiency improvements from free route implementation .............................. 60 Figure 4-16: Differences between KEP and KEA by State and FABs (2013) ............................... 61 Figure 4-17: Flight plans and actual trajectories Zurich - Amsterdam ........................................... 61 Figure 4-18: Share of total additional distance (KEA) by FAB (2013) ......................................... 62 Figure 4-19: Additional distance per flight (KEA) and KPI by FAB (2013) ................................. 62 Figure 4-20: Ratio of time airspace was used vs. allocated (pre-tactically) ................................... 63 Figure 4-21: Out of area traffic by region (2013) ........................................................................... 64 Figure 4-22: Expected/actual traffic in a peripheral ATC sector ................................................... 65 Figure 4-23: Top 10 ACCs for en route weather-related en route ATFM delay (2013) ................ 67 Figure 4-24: Number of days with regulations vs. number of days with SIGMETs (2013) .......... 68 Figure 4-25: ATFM performance (network indicators) ................................................................. 70 Figure 5-1: Framework for Operational ANS Performance Framework at airports ....................... 73 Figure 5-2: Airport arrival ATFM delay (ordered by traffic volume) ............................................ 74 Figure 5-3: Additional ASMA time (2012-2013) ........................................................................... 75 Figure 5-4: Local ATC Pre-departure delay ................................................................................... 77 Figure 5-5: Additional Taxi-out Times (2012-2013) ..................................................................... 78 Figure 5-6: Status of A-CDM implementation in Europe .............................................................. 78 Figure 5-7: ATFM slot adherence at airports (2013) ..................................................................... 80 Figure 5-8: Peak declared arrival capacity and service rate ........................................................... 81 Figure 5-9: Peak declared departure capacity and service rate ....................................................... 82 Figure 5-10: Weather conditions at major European airports ........................................................ 83 Figure 5-11: Overall Airport ANS Performance at the top 30 airports (2013)............................... 83 Figure 5-12: Taxi-in time distribution and preliminary unimpeded taxi-in time ........................... 85 Figure 5-13: Additional taxi-in time – monthly distribution .......................................................... 85 Figure 5-14: Resilience as a function of disturbance impact .......................................................... 86 Figure 5-15: Cumulative demand vs. accommodated traffic ......................................................... 86 Figure 5-16: Higher accuracy of airport data flow ......................................................................... 88 Figure 6-1: Real en-route unit costs per SU for EUROCONTROL Area (€2009)......................... 92 Figure 6-2: SES States and non-SES States covered by the en-route analysis (RP1) .................... 92
xii
Figure 6-3: Real en-route unit costs per SU, 2012 Actuals vs. 2011 Actuals (€2009) ................... 93 Figure 6-4: Difference between 2012 and 2011 costs by nature [€2009] ....................................... 94 Figure 6-5: 2012 Real en-route ANS costs per SU by charging zone (€2009) .............................. 95 Figure 6-6: Service units growth (SES and non-SES States) ......................................................... 96 Figure 6-7: Real en-route ANS costs per SU, 2012 Actuals vs. Forecasts (in €2009) ................... 97 Figure 6-8: 2012 Real en-route ANS costs per SU: Actuals vs. Forecasts (in €2009) at charging
zone level ................................................................................................................................ 98 Figure 6-9: Outlook 2013-2019 for RP1 SES States (in €2009) .................................................... 99 Figure 6-10: Outlook 2013-2018 for non-SES States (in €2009) ................................................... 99 Figure 6-11: Real terminal ANS unit costs (€2009) for reporting States ..................................... 101 Figure 6-12: Terminal SU and Unit rates ..................................................................................... 101 Figure 6-13: Comparison of 2012 terminal ANS unit costs by TCZ (SES States) ...................... 103 Figure 6-14: Comparison of 2012 terminal ANS actual costs vs. 2012 forecasts (Nov. 2011
Reporting) ............................................................................................................................. 104 Figure 6-15: 2012 Terminal ANS actual costs vs. 2012 forecast costs at State Level ................. 104 Figure 6-16: Real terminal ANS costs per TNSU, total costs (€2009) and recomputed TNSUs
(using (MTOW/50)^0.7) ...................................................................................................... 105 Figure 6-17: Change in real terminal ANS total costs 2012-2014 (real €2009) ........................... 105 Figure 6-18: Breakdown of gate-to-gate ATM/CNS provision costs 2012 (€2012) .................... 107 Figure 6-19: Changes in economic cost-effectiveness, 2008-2012 (€2012) ................................ 109 Figure 6-20: Breakdown of changes in cost-effectiveness, 2011-2012 (€2012) .......................... 109 Figure 6-21: ATM/CNS cost-effectiveness comparisons, 2008-2012 (€2012) ............................ 110 Figure 6-22: Improvement in ATCO-hour productivity, 2008-2012 ........................................... 111 Figure 6-23: Changes in average ATCO-hours on duty, 2008-2012 ............................................ 111 Figure 6-24: Changes in employment costs per ATCO-hour, 2008-2012 .................................... 112 Figure 6-25: Employment costs per ATCO-hour with and without PPPs, 2012 .......................... 112 Figure 6-26: Changes in the components of support costs, 2011-2012 ........................................ 113
Chapter 1: Introduction
PRR 2013 13 CHAPTER 1 INTRODUCTION
PART I- BACKGROUND Introduction 1
1.1 Purpose of the report 1.1.1 Air Navigation Services (ANS) are essential for the safety, efficiency and sustainability
of civil and military aviation, and to meet wider economic, social and environmental policy objectives.
1.1.2 This Performance Review Report (PRR 2013) has been produced by the independent Performance Review Commission (PRC) which was established in 1998 by the EUROCONTROL Member States. The PRC, with its supporting unit the Performance Review Unit (PRU), provides independent advice to the EUROCONTROL Member States1 “in order to ensure the effective management of the European Air traffic management system through a strong, transparent and independent performance review and target-setting system”, per Article 1 of the PRC’s Terms of Reference [Ref. 1]. In particular, the PRC advises “on all matters related to performance review and target setting, including recommendations for the improvement of these functions”, per Article 3 of its ToRs [Ref. 1].
1.1.3 More details about the PRC’s work can be found on the inside cover page of this report.
1.1.4 The purpose of PRR 2013 is to provide policy makers and ANS stakeholders with objective information and independent advice concerning European ANS performance in 2013, based on research, consultation and information provided by relevant parties.
1.1.5 The PRC attaches great importance to effective communication and consultation with stakeholders. Accordingly, the draft final report was made available to stakeholders for consultation and written comment from 06-28 March 2014. The PRC considered every comment received and amend the Final Report as required.
1.1.6 The PRC’s recommendations can be found in the Executive Summary.
1.2 Structure of the report
1.2.1 PRR 2013 consists of two parts:
Part I provides a consolidated high-level view of four ANS Key Performance Areas (KPA) in the wider context of European General Air Traffic. The four KPAs are: Safety, Capacity, Environment and Cost-efficiency. Part I also provides an overall economic evaluation of ANS performance.
Part II gives a more detailed analysis of ANS performance by KPA.
1.2.2 The chapters of PRR 2013 are as follows:
Part I
Chapter 1: Introduction
Chapter 2: ANS in European Air Transport
Part II
Chapter 3: Safety
Chapter 4: Operational En-route ANS Performance (Capacity/Environment)
Chapter 5: Operational ANS Performance at Airports (Capacity/Environment)
Chapter 6: ANS Cost-efficiency
1 39 EURCONTROL Member States in 2013 (see Glossary). Georgia became the 40th Member State on 01 January
2014.
PRR 2013 CHAPTER 1: INTRODUCTION
14
1.3 Geographical scope 1.3.1 Unless otherwise indicated, PRR 2013 refers to ANS performance in the airspace
controlled by the 39 Member States of EUROCONTROL in 2013 (see Figure 1-1), hereinafter referred to as “Europe”. Georgia became the 40th Member State on 01 January 2014, and therefore is not encompassed in PRR 2013.
Figure 1-1: EUROCONTROL States (2013)
1.4 Temporal scope 1.4.1 The 2013 data contained in Chapter 3 (Safety) are provisional data, which will be updated
in the final version of the report to be submitted to the Provisional Council in May 2014.
1.4.2 The data contained in Chapter 6 (Cost-efficiency) relate to the actual ANS costs in 2012 and projections for subsequent years, based on the latest available data from the reporting to the enlarged Committee for Route Charges in November 2013.
1.4.3 With the exception of the foregoing, all data contained in PRR 2013 refer to the calendar year 2013.
1.5 Implementation status of PRC recommendations 1.5.1 In its capacity as advisory body to the Permanent Commission, through the Provisional
Council the PRC proposes recommendations to the EUROCONTROL States for consideration and implementation by them.
1.5.2 Article 10.7 of the PRC’s Terms of Reference states that, “the PRC shall track the follow-up of the implementation of its recommendations, and report the results systematically to the Provisional Council”.
1.5.3 The Provisional Council (PC 39, May 2013) accepted all of the PRC’s recommendations contained in last year’s Performance Review Report (PRR 2012) [Ref.2]. These were as follows:
EUROCONTROL
ECAA
EU 27
Bilateral agreement with EU
PRR 2013 CHAPTER 1: INTRODUCTION
15
Recommendations in PRR 2012 (PC 39, May 2013)
The Provisional Council noted with appreciation that five of the seven Member States concerned have submitted Annual Summary Templates, and urged the States that still have not fully implemented PC decisions 8.1b, c and e of PC 37 (May 2011) to take action as a matter of urgency.
The Provisional Council noted with appreciation that three Member States have provided information on Effectiveness of Safety Management and Just Culture on a voluntary basis and requested the States concerned to take similar action as a matter of importance.
The Provisional Council requested the Director General to work with the relevant States/ANSPs, through the Network Management Directorate, to assist the most constraining ACCs in reducing their en route ATFM delays.
The Provisional Council requested States:
(i) to ensure consistency between national capacity plans and national performance objectives taking due consideration of the forecasted traffic demand, and the application of the FUA legislation by the State;
(ii) to ensure committed capacity plans are implemented as promised and that the level 2 FUA procedures and agreements are in place, to deploy the capacity based on traffic demand;
(iii) to ensure procedures and agreements are in place so that opportunities for additional capacity or route options due to the availability of previously allocated airspace are notified to the network manager and thence to airspace users, minimising wasted airspace;
The Provisional Council urged those States providing no or insufficient Correlated Position Reports to ensure that this data is supplied to the Agency at the required frequency and quality level.
The Provisional Council requested those States that are not bound by the provisions of the SES performance scheme to provide to the PRC - on a voluntary basis - information on operations at airports with more than 70 000 IFR movements per annum to enable an improved and harmonised measurement of ANS performance at main airports in Europe.
The Provisional Council requested the Director General to explore the progressive development of an integrated ANS performance information system addressing EUROCONTROL and SES performance needs, including their States and stakeholders, and report after one year.
Figure 1-2: PC action on PRC recommendations contained in PRR 2013
1.5.4 Annex I gives details of the implementation status of the PRC’s recommendations to the Provisional Council. The PRC will work with the Agency and with States to help ensure that these recommendations are implemented in full.
1.6 PRC as Performance Review Body of the Single European Sky 1.6.1 As earlier stated, 1998 saw the creation by EUROCONTROL of the first pan-European
performance system for its Member States. Since then, the PRC, supported by the PRU, has reviewed, analysed and benchmarked the ATM System performance of the EUROCONTROL States under various Key Performance Areas, proposed performance targets and high-level objectives and assessed to what extent they were achieved.
1.6.2 The EUROCONTROL performance scheme has helped States, ANSPs and other interested parties to see their performance from a European perspective, to identify good practice and areas that needed to be improved. Its success prompted the European Union to make legal provision in 2004 [Ref. 3] for an EU-wide performance scheme. The Performance Scheme of the Single European Sky (SES) with associated target setting at EU-wide level and at FAB/national level, came into force in August 2010 [Ref. 4].
1.6.3 In July 2010, the European Commission (EC) designated “Eurocontrol, acting through its Performance Review Commission supported by the performance review unit” [Ref. 5] as the Performance Review Body (PRB) of the SES. The designation will expire on 30 June
PRR 2013 CHAPTER 1: INTRODUCTION
16
2015: it may be renewed at the EC’s discretion. The EC appointed the PRB Chairman separately. He is not a member of the PRC.
1.6.4 The PRC’s role as PRB is to assist the EC in the implementation of the performance scheme and to assist the National Supervisory Authorities (NSAs) on request. Two of its key tasks include:
advising the EC in setting EU-wide performance targets and assessing national/Functional Airspace Block (FAB) performance plans; and,
monitoring the performance of the system in four key performance areas: Safety, Capacity, Environmental impact and Cost-efficiency.
1.6.5 The SES performance scheme places greater focus on planning and accountability for performance, target-setting, monitoring, incentives and corrective actions at both European and national/FAB levels. It is coupled with a new Charging regime [Ref. 6], which replaces “Cost recovery” by a system of “Determined costs” set at the same time as performance targets. The goal is to achieve sustainable and significant performance improvements from the 1st Reference Period onwards (RP1: 2012-2014).
1.6.6 A key rationale for the EC when designating EUROCONTROL was to achieve synergies between the SES performance scheme and the EUROCONTROL performance review system. The PRC’s commitment is to ensure that common procedures, tools and data feed both systems and hence reduce the overall cost, which will further optimise the performance of pan-European air navigation services, in the interests of all stakeholders.
1.7 European ANS performance in the context of ICAO 1.7.1 The PRC’s research and analytical work has been an important factor in persuading the
International Civil Aviation Organization (ICAO) of the need to create a performance framework for the purpose of enhancing safety and efficiency in the air navigation system. As far back as 2000, EUROCONTROL presented the PRC’s work on performance review to the ICAO Air Navigation Conference (ANSCONF 2000). The conference supported the proposed application of performance measurement in ATM systems for both en route and airport services, with parameters covering safety, delay, predictability, flexibility, efficiency, availability, access and cost of service.
1.7.2 In 2007, ICAO held a dedicated Performance Symposium, the conclusions of which were supported by the ICAO Assembly held in the autumn of that year. Since then, performance review has formed a corner-stone of ICAO policy.
1.7.3 During 2008, the ICAO secretariat in Montreal approached the Planning and Implementation Regional Groups (PIRGs) in the various ICAO Regions and urged them to apply ICAO guidance material (Docs 9854, 9882, 9883) and the Global Air Navigation Plan (Doc 9750), in order to take a regional and national approach to the implementation of a global ATM system.
1.7.4 In Europe, this led in December 2008 to EANPG Conclusion 50/1 (Regional Air Navigation Planning Performance Framework). This conclusion reads: “That, when developing the new electronic Air Navigation Plan (eANP), the ICAO Secretariat give due regard to the regional and national performance frameworks that should identify the regional and national performance objectives, on the basis of ICAO guidance material and ensure their alignment with the Global Air Navigation Plan (Doc 9750) and the Global ATM Operational Concept (Doc 9850)”.
1.7.5 EANPG adopted a regional performance framework [Ref. 7], intended for annual monitoring and reporting of performance in all 52 States of the Region. It comprises a standard set of performance objectives and indicators. In order to avoid duplication of effort, it is based on the performance scheme of the SES, which is already applied by a majority of the States in the EUR Region. This approach is illustrated in Figure 1-3.
PRR 2013 CHAPTER 1: INTRODUCTION
17
1.7.6 In November 2013 the EANPG agreed (EANPG Conclusion 55/25) to launch the implementation of the ICAO EUR Region Performance Framework, starting from 1st January 2014 with the aim to have a first regional report presented to EANPG 57 in 2015.
1.7.7 It should be noted that other ICAO Regions have also started to develop a regional performance framework.
Figure 1-3: ICAO approach followed in the EUR Region
1.7.8 In the meantime, the FAA and EUROCONTROL had teamed up to conduct a series of studies called the US/Europe Comparison of ATM-related Operational Performance (2009, updated in 2012 and 2013 [Refs. 8, 9,10]). This initiative proved that it is possible to develop and apply a common performance framework, which could serve as a sound basis for factual high-level comparisons between countries and world regions. These publications influenced ICAO and CANSO working groups for use in global benchmarking. This approach has also been used by Airservices Australia to conduct a similar study in 2012, the “Analysis of Australian ATM-Related Operational Performance [Ref. 11].”
1.7.9 This work was presented to ICAO during the Air Navigation Conference in 2012 (ANConf/12). The Conference agreed that “there was a need to develop a global methodology, to identify metrics and indicators which could be used to allow States and regions to measure and evaluate the effectiveness of their ATM performance initiatives. In doing so, particular attention should be given to avoiding duplication of efforts and to use, to the maximum extent possible, existing arrangements and solutions.”
1.7.10 This led to Recommendation 1/15 (Performance monitoring and measurement of air navigation systems): “that ICAO establishes a set of common air navigation service performance metrics supported by guidance material, building on existing ICAO documentation.” This Recommendation is in the process of being implemented.
Chapter 2: ANS in European Air Transport
PRR 2013 18 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
ANS in European Air Transport 2
KEY POINTS KEY DATA 2013
Average daily IFR flights in Europe decreased by -0.8% in 2013 with notable regional variations in traffic evolution.
Despite the lower number of flights in 2013, en route service units increased by +2.4% compared to 2012, mainly due to an increase in average aircraft weight and additional distance.
Arrival punctuality continued to improve in 2013. The number of punctual flights reached an all-time high of 84.0% in 2013, although in a context of declining traffic. The share of ANS-related delays in 2013 was 23.5% which represents a further reduction compared to 2012.
The positive trend observed over the past two years continued and all ANS-related service quality indicators showed an improvement in 2013.
According to the latest available projections for 2013, the foreseen increase in ANS costs (+4.0%) slightly exceeds the notable reduction in ANS-related service quality costs (subject to final ANS costs). Consequently, total economic ANS costs in the SES area are projected to increase by +0.9% in 2013.
Traffic demand & Punctuality (EUROCONTROL area)
2013 change vs.
2012
IFR flights controlled2 9.45M -0.8% 3
Flight hours controlled2 14.2M +0.7%
Total distance charged in km4 8.966M +1.3%
En-route Service Units4 122.8M +2.4%
Arrival punctuality (% of flights arriving within 15 min.. after their schedule)
84.0% +0.7% pt.
Economic evaluation (M€ 2009) (SES performance scheme area)
Projected total ANS costs (en route + terminal)
7 755 +4.0%
Estimated cost of inefficiencies in the gate-to-gate phase
2 220 -4.0%
Estimated cost of en-route and airport ATFM delay
660 -15.1%
Total estimated ANS-related economic costs (M € 2009)
10 635 +0.9%
2.1 Introduction 2.1.1 This chapter provides a high-level view of ANS performance in the wider context of air
traffic operating under Instrument flight rules (IFR) in Europe. After an overview of the evolution of European IFR traffic, the chapter provides a synthesis of key elements from the more detailed analyses of ANS performance in Chapters 3-6, to provide an overall economic evaluation of ANS performance in Europe.
2.1.2 Figure 2-1 shows ANS performance in the wider context of European IFR traffic. The areas addressed in this chapter also cover all key performance areas of the SES performance scheme and include ANS costs (Cost-efficiency), ATFM delays (Capacity), and horizontal en route flight efficiency (Environment), with an overriding safety objective (Safety). Figure 2-1: ANS performance in European IFR traffic
2 EUROCONTROL Statistical Reference Area (ESRA) 2008 (see Glossary). 3 The -0.8% decrease relates to average daily IFR flights in order to remove the leap year effect (-1.1% without
taking the leap year effect into account). 4 ESRA08 States, excluding Ukraine (see Glossary).
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
19
2.2 European Air Traffic Demand 2.2.1 Although at a lower rate than in 2012, average daily IFR flights continued to decrease by
-0.8% in 2013. For 2013, the intermediate STATFOR 7-year forecast, published in May 2013 [Ref. 12], predicted a traffic reduction of between -2.2% and -0.5% with a baseline scenario of -1.3% at ESRA 08 level5. Hence, the actual decrease in IFR flights in 2013 (-0.8%) was between the forecast low and baseline scenario.
Figure 2-2: Evolution of European IFR flights (1990-2020)
2.2.2 For 2014, the STATFOR 7-year forecast published in Feb. 2014 [Ref. 13] expects European flights to grow by +1.2% in the baseline scenario (Low: -0.1%; High: +2.3%). The average annual growth rate between 2014 and 2019 is forecast to be at +2.6%.
2.2.3 Since 2008, in view of the economic crisis, traffic forecasts have been continuously revised downwards, with European IFR flights expected to reach pre-economic crisis levels (2008) only by 2016 (see blue and dotted lines in Figure 2-2).
2.2.4 The evolution of key traffic indices6 in Figure 2-3 also clearly shows the effects of the crisis starting in 2008 and suggest that airlines responded with a reduction in the number of services but with, on average, larger aircraft.
Figure 2-3: Key European traffic indices (2004-13)
5 The EUROCONTROL Statistical Reference Area (ESRA) is designed to include as much as possible of the ECAC area for which data are available from a range of sources within EUROCONTROL (see also Glossary).
6 Please note that the individual indices can refer to slightly different reference areas.
-8%
-6%
-4%
-2%
0%
2%
4%
6%
8%
10%
12%
14%
16%
2
4
6
8
10
12
14
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
% a
nn
ua
l gro
wth
(b
ars)
IFR
flig
hts
(m
illio
n)
STATFOR7-year forecast
(Feb. 2014)
( before 1997, estimation based on Euro 88 traffic variation)
2013 TRAFFIC 9.45 M (-0.8%)
source : EUROCONTROL/STATFOR (ESRA2008)
Max. (2008)
STATFOR7‐year forecast(Feb. 2008)
STATFOR7‐year forecast(Feb. 2011)
100
105
110
115
120
125
130
135
140
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Inde
x 10
0 =
200
4
Tot. Flights
Passengers (ACI Europe)
Avg. MTOW
Tot. Hours
Sources: ACI; STATFOR (ESRA2008); CRCO
‐0.8%
2.8 %
+0.7%
+2.6%
Tot. En route service units
+2.4%
Tot. distance+1.3%
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
20
2.2.5 In 2013, a decoupling of the evolution of flights (-0.8%) and en route service units (+2.4%) can be observed. En route service units are affected by changes in distance (e.g. additional or longer flights) and changes in average aircraft weight.
2.2.6 Despite the lower number of flights, load factors and average Maximum take-off weight (MTOW) continued to increase leading to a continuous growth in passenger numbers. For 2013, the Association of European Airlines (AEA) reported that the average load factor was up 0.7 percentage point to an all-time high of 79.9% [Ref. 14].
En route service units A service unit is used for charging purposes. It is the multiplication of the Aircraft Weight Factor by the Distance Factor.
The Aircraft weight factor is the square root of the maximum take-off weight declared by aircraft operators divided by 50.
The distance factor is the distance in between the aerodrome of departure within, or the point of entry into, the airspace of the State and the aerodrome of arrival, or the point of exit from, that airspace. 20 km is deducted for each take-off and landing on the territory of a member State.
2.2.7 The strong growth in average aircraft weight (+2.6%) and the additional distance driven by on average longer flights and by strong local growth in Turkey (see next section) resulted in a notable growth in en route service units (+2.4%), despite the lower number of total flights in 2013.
GEOGRAPHICAL DISTRIBUTION OF TRAFFIC GROWTH
2.2.8 Figure 2-4 shows the number of average daily flights in 2013 by State (bottom of chart) and the changes compared to 2012 in absolute and relative terms (top of chart). The figure is sorted according to the absolute change compared to the previous year. Information at ACC level can be found in Annex II.
2.2.9 In absolute terms, Turkey, the Ukraine, the Netherlands, Romania, and Norway showed the highest year-on-year growth in 2013 (see left side of Figure 2-4). The growth in Turkey is mainly driven by new international services and domestic flights which also contributed notably to the increase in passengers observed in Figure 2-3.
Figure 2-4: Traffic variation by State (2013/2012)
2.2.10 The States with the highest decreases in absolute terms in 2013 were Italy, Spain, Switzerland, Germany, and Austria. The main driver of the decrease was the lower number of domestic flights, followed by less international flights. It is interesting to note that, notwithstanding the overall decrease, overflights of Italy, Spain and Germany increased significantly in 2013.
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
21
2.2.11 Figure 2-5 provides an outlook on the forecast traffic growth between 2013 and 2020.
2.2.12 The traffic outlook continues to show a contrasted picture between the mature markets in Western Europe struggling to recover from the economic crisis and the emerging markets in Central & Eastern Europe for which a substantial growth is foreseen between 2013 and 2020.
Figure 2-5: Forecast traffic growth 2013-2020
TRAFFIC GROWTH AT THE MAIN EUROPEAN AIRPORTS
2.2.13 Figure 2-6 shows the year-on-year variation for the top 30 airports analysed in more detail in Chapter 5 in terms of average daily movements. On average, movements at European airports7 decreased by -1.5% in 2013 compared to the previous year.
2.2.14 As was the case in 2012, the two Istanbul airports showed by far the highest growth in 2013. The growth at Istanbul (IST) airport is above 10% for the third year in a row, which is remarkable.
2.2.15 The highest decrease in relative terms in 2013 was observed at Madrid (MAD) (-10.5%), followed by Milan (MXP), and Vienna (VIE).
2.2.16 A detailed analysis of ANS performance at the top 30 airports can be found in Chapter 5.
Figure 2-6: Traffic variation at the top 30 European airports (2013/2012)
7 Growth rate is based on the airport sample used for the more detailed analysis in Chapter 5.
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
22
EUROPEAN TRAFFIC CHARACTERISTICS
2.2.17 At European level, seasonal traffic variability computed as the ratio between peak and average weekly traffic was 1.17 in 2013 which means that the traffic in the peak week was 17% higher than average (15.7% in 2012). The traffic on the peak day (28 June 2013) was 32 273 flights, 24.7% higher than on an average day.
Traffic variability
Traffic variability usually compares traffic during peak periods (hour, day, week, month, etc.) to the average traffic level. If traffic variability is high, resources may be underutilised during off-peak times but scarce at peak times.
2.2.18 Figure 2-7 illustrates substantial differences in traffic variability across Europe. The European core area shows only a moderate level of seasonality, yet at high traffic levels.
2.2.19 High variability levels are observed in SE-Europe; largely linked to seasonal holiday traffic.
2.2.20 For instance, traffic in the peak week in Palma ACC was almost twice as high as the annual average (1.9). Figure 2-7: Seasonal traffic variations at ATC-Unit level
2.2.21 Traffic complexity is generally regarded as a factor to be considered when analysing ANS performance. At European level, the aggregate complexity score is relatively stable. In 2013, complexity at system level increased slightly to 6.26 minutes of interactions per flight hour.
Figure 2-8: Complexity scores at ATC-Unit level
Traffic complexity
The complexity score in this report is a composite measure which combines a measure of traffic density (concentration of traffic in space and time) with structural complexity (structure of traffic flows) [Ref. 15].
The structural complexity is based on the number of potential horizontal, vertical or speed interactions between aircraft in a given volume of airspace (20x20 nautical miles and 3.000 feet in height).
For example, a complexity score of 8 corresponds to an average of 8 minutes of potential interactions with other aircraft per flight hour in the respective airspace.
CAN
LIS
ANK
SCO
SHA
TAM
MAD
STO
BRE
BOD
BRI
WARLON
ROMIST
BAR
BUC
MAA
SIM
MAR
KIE
ATH+MAK
MAL
STA
MAL
NIC
BOR
DNI
SEV
COP
SOF
LVO
BEOZAG
OSL
RIG
BUD
MIL
TAL
WIE
ODERHE PRAMUN
VIL
REI
PAD
RHE
TIR
PAR
CHIBRAT
ZURYERGEN
SKO
LJU
PAR
LAN
BREM
AMS
BRU
DUB
LON TC
PAL
Lower Airspace
Lower Airspace
Traffic variability 2013< 1.15> 1.15> 1.25> 1.35
> 1.45
CAN
LIS
ANK
SCO
SHA
TAM
MAD
STO
BRE
BOD
BRI
WARLON
ROMIST
BAR
BUC
MAA
SIM
MAR
KIE
ATH+MAK
MAL
STA
MAL
NIC
BOR
DNI
SEV
COP
SOF
LVO
BEOZAG
OSL
RIG
BUD
MIL
TAL
WIE
ODERHE PRAMUN
VIL
REI
PAD
RHE
TIR
PAR
CHIBRAT
ZURYER
GEN
SKO
LJU
PAR
BREM
LAN
AMS
BRU
DUB
LON TC
PAL
Lower Airspace
Lower Airspace
Traffic complexity score 2013< 2> 2> 4> 6> 8
source : EUROCONTROL
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
23
2.2.22 As shown in Figure 2-8, at local level8, the picture is more contrasted and the complexity scores - predominantly driven by traffic density per airspace volume - differ significantly.
2.2.23 Mainly driven by the high traffic density, London Terminal Control (TC) showed by far the highest complexity score in 2013 (32.8). The highest complexity scores at ACC level in 2013 were observed in the European core area: Langen ACC (14.0), Zurich (11.1), Rhein (11.1), Geneva (11.0), and Munich (10.7). The complexity scores at ANSP level can be found in Annex III.
2.2.24 Although a continuous decrease can be observed between 2011 and 2013, traditional scheduled traffic still accounts by far for the majority of flights (54.7%).
2.2.25 With the exception of the “Low cost” traffic (+1.6%), all other market segments decreased compared to 2012.
2.2.26 As was the case in 2012, “Other” traffic showed the highest relative decrease in 2013 (-5.3%), albeit from a small base.
Figure 2-9: IFR flights by market segment (2013)
2.3 Safety 2.3.1 Safety is clearly the primary objective of ANS. However, not all accidents can be
prevented by ANS (technical failure, etc.) and there are a number of accidents without ANS involvement.
2.3.2 Figure 2-10 shows the total commercial air transport (CAT) accidents9 between 2003 and 2013 including those accidents with ANS contribution10 (red bars).
2.3.3 After the increase between 2009 and 2011, total CAT accidents decreased again between 2011 and 2013 to reach the lowest level recorded over the past 11 years.
Figure 2-10: Accidents in EUROCONTROL area with
ANS contribution (2003-13)
8 The complexity score represents an annual average. In areas with a high level of seasonal variability the complexity score may be higher during peak months.
9 Commercial Air Transport is defined by ICAO as “aircraft operations involving the transport of passengers, cargo or mail for remuneration or hire.
10 Accidents with ANS contribution means that at least one ANS factor was in the causal chain of events leading to the occurrence encountered by the aircraft.
55.8%
55.0%
54.7%
24.1%
25.1%
25.7%
7.3% 7.2% 7.1%
5.1% 5.4% 5.4%
0
1
2
3
4
5
6
7
8
9
10
2011 2012 2013
Millions of IFR flights
Other (incl. military)
Cargo
Charter
Business Aviation
Low‐Cost
Traditional Scheduled
source :EUROCONTROL; STATFOR
-1.3%
1.6%
-1.6%
-1.3%
-2.6%
-5.3%
Change vs. 2012 (avg. daily) (%)
Variation of IFR flights by market segment (STATFOR classification)
‐186
106
‐30
‐19
‐24
‐52
4 3 3 1 2 1 2 105
101520253035404550
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Number of accidents
Source: EASA Accidents with ANS contribution
Total commercial air transport (CAT) accidents and accidents with ANS contribution (fixed wing, weight > 2250Kg MTOW)
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
24
2.3.4 The number of accidents with ANS contribution is generally small compared to total CAT accidents. Over the past three years, there were no CAT accidents where ANS was a factor in the causal chain of event leading to the accident.
2.3.5 Figure 2-11 shows the total CAT serious incidents between 2003 and 2013 including those with ANS contribution (red bars).
2.3.6 There was a steady decrease in serious incidents since 2010, reaching the second lowest level recorded over the past 11 years in 2013.
Figure 2-11: Serious Incidents in EUROCONTROL area
with ANS contribution (2003-13)
2.3.7 While this is positive, in view of the rare occurrence of accidents with ANS contribution, a meaningful review of ANS safety performance requires a more in-depth analysis of ANS-related incidents and of the effectiveness of the ANS system in place to prevent accidents and incidents in the future. This is provided in Chapter 3 of this report.
2.4 Service quality 2.4.1 This section presents a synthesis of operational air transport performance and underlying
delay drivers, in order to provide an estimate of the ANS related11 contribution towards air transport service quality in Europe. The underlying analytical framework is described in more detail in Annex IV.
AIR TRANSPORT PUNCTUALITY (AIRSPACE USER PERSPECTIVE)
2.4.2 Figure 2-12 shows the share of flights arriving or departing within 15 minutes of their published departure and arrival times between 2004 and 2013 in Europe.
2.4.3 Punctuality continued to improve slightly in 2013 reaching the best performance on record so far (84.0%). The continued improvement needs to be seen in the context of a further decrease of traffic in 2013 (see Figure 2-2).
11 In this report, “ANS-related” or “ANS-actionable” means that ANS has a significant influence on the operations.
13 19 23 20 217 6
2011 9 6
0
20
40
60
80
100
120
140
160
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013Number of serious incidents
Source: EASA ANS‐related serious incidents
ANS‐related serious incidents in commercial air transport (CAT) (fixed wing, weight > 2250Kg MTOW)
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
25
Figure 2-12: European On time performance (2004-13)
Punctuality/ On time performance
“Punctuality” is the share of flights arriving/ departing within 15 minutes after the scheduled arrival/ departure time (airline schedules).
There are many factors contributing to the on time performance of a flight.
Punctuality is therefore the “end product” of complex interactions between airlines, airport operators, the European Network Manager and ANSPs, from the planning and scheduling phases up to the day of operation. Network effects also have a strong impact on air transport performance.
2.4.4 Although “punctuality” is a valid indicator, from a passenger viewpoint, from an operational perspective all deviations from plan (including flights arriving ahead of schedule) generate variability and can therefore impact on efficiency.
2.4.5 The predictability of operations has an impact on airline scheduling (see grey box) but also on the provision of ATC and airport capacity (i.e. TMA capacity, en-route capacity, gate availability, etc.). The lower the predictability the more difficult it is to match capacity to demand without inefficiencies in terms of delay (insufficient capacity) or cost (underutilisation of resources).
2.4.6 Figure 2-13 depicts the level of variability from the airspace users’ point of view on intra-European flights12 (see grey box).
2.4.7 Figure 2-12 and Figure 2-13 show that arrival punctuality is mainly driven by variations already encountered at the departure airport with only comparatively small variations in the gate-to-gate phase (taxi out, en-route, taxi-in). Although the variability in the gate-to-gate phase is comparatively small at system level, it should be noted that performance may vary significantly by airport or route (see also Chapter 5).
Figure 2-13: Variability of flight phases (2008-13)
Variability
The “variability” of operations determines the level of predictability for airspace users and hence has an impact on airline scheduling. It focuses on the variance (distribution widths) associated with the individual phases of flight as experienced by airspace users.
The higher the variability, the wider the distribution of actual travel times and the more time buffer is required in airline schedules to maintain a satisfactory level of punctuality.
12 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.
84.0%
74%
76%
78%
80%
82%
84%
86%
88%
90%
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
% of flights
Departures within 15 min. after the scheduled departure time (%)
Arrivals within 15 min. after the scheduled arrival time (%)
Source: CODA
Departure and arrival punctuality in Europe
-10
-5
0
5
10
15
20
25
2008
2009
2010
2011
2012
2013
2008
2009
2010
2011
2012
2013
2008
2009
2010
2011
2012
2013
2008
2009
2010
2011
2012
2013
2008
2009
2010
2011
2012
2013
Departure time Taxi‐out phase Flight phase (en‐route &terminal)
Taxi‐in phase Arrrival time
min
utes
80th Percentile
20th Percentile
Standard Deviation
Source: CODA; PRC Analysis
Gate to gate phase
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
26
2.4.8 Variability of operations has a direct impact on airline scheduling and hence on punctuality (see grey box on airline scheduling).
2.4.9 The inclusion of “time buffers” in airline schedules to account for a certain level of anticipated travel time variation may therefore improve punctuality but mask changes in actual performance.
2.4.10 In order to evaluate changes in “time buffers” embedded in airline schedules, Figure 2-14 depicts changes in scheduled block times (flight duration published in airline schedule) and arrival delays relative to the long term average of the analysis period (see grey box on DLTA metric).
Airline scheduling Airlines build their schedules for the next season on airport slot allocation, crew activity limits, airport connecting times, and by applying a quality of service target to the distribution of previously observed block-to-block times (usually by applying a percentile target to the distribution of previously flown block times).
The level of “schedule padding” is subject to airline strategy and depends on the targeted level of on-time performance13.
Analysis of scheduling trends with the DLTA
metric The Difference from Long-Term Average (DLTA) metric is designed to measure changes in time-based (e.g. flight time) performance normalised by selected criteria (origin, destination, aircraft type, etc.) for which sufficient data are available.
It provides a notion of the relative change in performance over time but does not enable to identify the underlying performance driver.
Figure 2-14: Evolution of delays and block times (2004-13)
2.4.11 Whereas the arrival delay follows the inverse pattern observed for punctuality in Figure 2-12, scheduled block times remained relatively stable compared to the long term average. This indicates that there was no substantial growth of schedule buffers over the period at system level.
2.4.12 With departure delays being the main contributor towards arrival punctuality, Figure 2-15 shows a breakdown of causal factors for departure delay in Europe, reported by airlines (see grey box).
2.4.13 The grouping of the delay codes enables a focus on ANS-related delays where ANS is either the root cause for the delay (i.e. ATC capacity, staffing, ATC equipment) or where an imbalance between demand and capacity (i.e. weather, military training, etc.) was handled by ANS.
Departure delays Departure delays in this report are measured compared to airline schedule. They are experienced at the stand before the aircraft departs and reported by airlines to CODA according to a set of delay codes defined by IATA. For a better focus on the ANS-related delays the IATA delay codes were grouped:
En-route ATFCM (IATA codes 81,82); ANS-related airport delays (Code 83,89); ATFCM due to weather (Code 73, 84); Weather non ATFCM such as snow removal or de-
icing (Codes 71,72,76,76,77); Reactionary delays (Codes 91-96); and, Local turn-around delays: Primary delays caused
by non-ANS related stakeholders (all other Codes).
13 The Central Office for Delay Analysis (CODA) publishes two scheduling indicators to help airline schedulers determine the optimal schedule based on historical flight data categories (see http://www.eurocontrol.int/coda).
‐3
‐2
‐1
0
1
2
3
4
5
Jan‐2004
Jan‐2005
Jan‐2006
Jan‐2007
Jan‐2008
Jan‐2009
Jan‐2010
Jan‐2011
Jan‐2012
Jan‐2013
Jan‐2014
Arrival delay
Scheduled block time
Deviation from the long term
average in minutes
Source: CODA; PRC Analysis
(Intra European flights only ‐ 12 months trailing average shown)
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
27
2.4.14 The departure delays can be further categorised into primary (delay cause is directly attributable) and “reactionary” delays (carried over from previous flight legs).
2.4.15 Although a notable improvement was observed in 2013, more than half of the primary delay (52%) was due to issues in the turnaround phase caused by airlines, airport operators, ground handlers and other parties.
2.4.16 The ANS-related share of primary delays in 2013 was 23.5% which represents a further reduction compared to 2012.
2.4.17 Two third of the ANS-related delays reported by airlines were attributable to ANS at airports.
2.4.18 Although decreasing in 2013, the largest single delay group was “reactionary” delay (45.7%), caused by delay which could not be absorbed on subsequent flight legs.
2.4.19 Figure 2-16 shows the sensitivity of the air transport network to primary delays.
Figure 2-15: Departure delays by cause (2010-13)
Figure 2-16: Sensitivity to primary delays
2.4.20 The ratio is close to 0.9 which means that, on average, every minute of primary delay resulted in some 0.9 min. of reactionary delay. After an almost continuous (except 2009) increase over the years, the ratio decreased in 2011.
2.4.21 While a thorough evaluation of all delay causes is required to improve overall air transport performance, an in-depth analysis of the complex and interrelated non ANS-related pre-departure processes and reactionary delay is beyond the scope of this report14.
2.4.22 A comprehensive study of the ANS-related contribution towards reactionary delay and possible ANS strategies to mitigate propagation effects in the network would be a worthwhile research topic but would be complex due to the multitude of factors involved (i.e. time and length of primary delay, airline business model and strategy, scheduling practices, etc.).
2.4.23 Before the economic evaluation of ANS performance in Section 2.5, the next section provides a synthesis of ANS-related efficiency and an estimate of its impact on airspace users’ operations in terms of time and fuel burn (see also framework in Annex IV).
ANS-RELATED SERVICE QUALITY (SERVICE PROVIDER PERSPECTIVE)
2.4.24 In contrast to the analysis given in the previous section, this section compares actual performance to an ideal reference time/distance from a single flight perspective which, due to inherent limitations, is not achievable at system level.
14 The Central Office for Delay Analysis (CODA) publishes detailed monthly, quarterly, and annual reports on more delay categories (see http://www.eurocontrol.int/coda).
0
2
4
6
8
10
12
14
16
2010 2011 2012 2013
min
utes
per
dep
art
ure
ATFCM (en route)
ANS‐related(airports)
ATFCM (Weather)
Weather (nonATFCM)
Local Turn around(airline, airport, etc.)
Reactionary
Change 2013 vs. 2012 (min./dep.)
-0.06
0.00
-0.02
0.08
-0.16
-0.10
Source. PRU analysis; CODA
0.4
0.5
0.6
0.7
0.8
0.9
1.0
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
ratio reactionary to primary delay
Sensitivity of the European air transport network to primary delays (intra‐European flights)
Primary delay includes local turnaround delays and en‐route and airport ATFM delays
Source: PRU analysis; CODA
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
28
2.4.25 The respective performance indicators are discussed in more detail in the corresponding chapter on operational en route ANS performance (Chapter 4) and ANS performance at airports (Chapter 5).
2.4.26 Inefficiencies in the various flight phases (airborne vs. ground) have a different impact on airspace users in terms of predictability, fuel burn (engines-on vs. engines-off) and costs (see also Annex IV).
2.4.27 For ATFM delays at the gate the fuel burn is quasi nil but with a low level of predictability before the day of operations which consequently impacts on punctuality.
2.4.28 ANS-related inefficiencies in the gate-to-gate phase are generally more predictable as they are often related to congestion or structural issues (route design) which are similar every day.
2.4.29 Although the “inefficiencies” embedded in the gate-to-gate phase are usually considered in the airline scheduling and therefore have a limited impact on punctuality (see § 2.4.8 ff.), the impact in terms of additional fuel burn, CO2 emissions15, and associated costs is significant.
2.4.30 Previous research [Ref. 2] showed that the share of CO2 emissions which can be influenced by ANS is approximately 6% of the total aviation related CO2 emissions in Europe or around 0.2% of total European anthropogenic CO2 emissions (see grey box).
2.4.31 The next section provides an overview of the current best estimate of the total additional time, fuel burn and CO2 emissions16 that can be influenced by ANS (ANS-related).
“Efficiency” of operations
‘Efficiency’ in this report measures the difference between actual time/distance and an unimpeded reference time/ distance.
“Inefficiencies” can be expressed in terms of time and fuel and also have an environmental impact. Due to inherent necessary (safety) or desired (noise, capacity, cost) limitations the reference values are not necessarily achievable at system level and therefore ANS-related ‘inefficiencies” cannot be reduced to zero.
Share of ANS-related CO2 emissions In Europe, aviation accounts for approximately 3.5% of total CO2 emissions [Ref. 16].
Analysis in previous PRRs showed that approximately 6% of the aviation-related CO2 emissions can be influenced by ANS. Or expressed differently, average ANS-related fuel efficiency in Europe is estimated to be 94%.
In terms of total European CO2 emissions the share that can be influenced by ANS is therefore approximately 0.2% (6% x 3.5% ≈ 0.2%).
2.4.32 With the advent of the Single European Sky (SES) performance scheme in 2010/2011, new data collections (Correlated Position Reports (see §4.3.20 ff. on page 58) and data directly provided by airport operators (see §5.5.15ff. on page 87)) became available. These allow more precise computations for performance measurement.
2.4.33 In order to improve the level of accuracy and to align the computations with the data and indicators used within the SES Performance Scheme, for this year’s edition of PRR, it was decided to use those new data flows for the high level evaluation of ANS performance in the following sections of this chapter.
2.4.34 As the relevant data (see § 2.4.32) are presently not available for all EUROCONTROL States at the same quality, the temporal and geographical scope of the high-level overview is limited to the period 2011 to 2013 and to SES States. The underlying data is derived from and should be read in conjunction with the analyses provided in Chapters 4 to 6 of this report.
15 The emissions of CO2 are directly proportional to fuel consumption (3.15 kg CO2 /kg fuel). 16 It does not consider emissions from facility management (heating etc.) or ANS staff travel to/from airports which
is also relevant from an environmental point of view.
≈6%
≈3.5%
Share of aviation related CO2 emissions (Europe)
Share of aviation emissions actionable by ANS
Total anthropogenic
CO2 emissions in Europe
Estimated share of ANS‐related CO2 emissions in Europe (2011)
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
29
2.4.35 Due to those changes in data and scope, the figures in this section are not directly comparable to the figures published in previous editions of the report.
2.4.36 Figure 2-17 provides an overview of the current best estimate of operational inefficiencies, where ANS can provide a contribution to improve performance. For the interpretation of the results in the following sections, it is worth recalling that:
the computations refer to a theoretical optimum which is - due to necessary (safety) or desired (capacity) limitations - not achievable at system level. Hence, the ANS-related inefficiencies cannot be reduced to zero as a certain level of delay is necessary and sometimes even desirable if a system is to be run efficiently without underutilisation of available resources;
a clear cut attribution between ANS and non-ANS related factors is often difficult in a complex interrelated environment such as air transport. Whereas ANS can significantly help improving performance in the measured areas, there are inevitably factors and trade-offs from other areas and/or stakeholders which impact on overall performance; and,
the high level overview of total ANS-related inefficiencies combines effects from traffic variations and changes in performance. For more detailed analysis in each area, please consult the respective chapters in the report.
Figure 2-17: Estimated ANS-related impact on fuel burn/environment (2013)
2.4.37 Different from previous years, the availability of the better data (see above) enables to include estimated en route flight inefficiencies compared to the filed trajectory (KEP) and the actual trajectory (KEA)17. For more information, on en route flight efficiency see Chapter 4.3 on page 56.
2.4.38 Compared to 2012, ANS-related operational performance improved in all areas in 2013. The highest year on year improvement was observed for en route ATFM delays (-15.4%) followed by airport ATFM delays (-14.5%).
2.4.39 In the gate-to-gate phase, all three indicators (additional taxi-out time, en route flight efficiency, additional ASMA time) showed an improvement with a positive impact on fuel burn. The notable reduction in total additional operating time and fuel is due to small performance improvements at indicator level and a 1.5% reduction of traffic in the SES area compared to 2012.
2.4.40 Inefficiencies in the vertical en route flight profile, TMA departure phase, and the taxi in phase are presently not included in Figure 2-17. The magnitude can change by region or airport and it is acknowledged that there is scope for future improvement in those areas as well as a need to include them in future estimations of ANS-related inefficiencies in order to get an even more complete picture.
17 The KEA in Figure 2-17 relates to the inefficiency of actual trajectories compared to achieved distance. The KEP share relates to the difference between filed and actual trajectory (KEP share = KEP-KEA).
CO2
2013 % change 2013 % change 2013
Ch. 5 3.50 M ‐14.5% ‐ ‐ ‐
Ch. 4 4.85 M ‐15.4% ‐ ‐ ‐
Ch. 5 17.9 M ‐3.9% 0.3 Mt ‐4.6% 0.8 Mt
KEP share * Ch. 4 13.0 M ‐3.4% n/a n/a
KEA Ch. 4 17.2 M ‐3.0% 0.7 Mt ‐6.4% 2.2 Mt
Ch. 5 9.8 M ‐3.0% 0.4 Mt ‐1.4% 1.1 Mt
66.3 M ‐5.0% 1.3 Mt ‐4.7% 4.1 Mt
* The KEP share relates to the difference between the filed and actual trajectory (KEP share= KEP-KEA).
Addressed
in chapters
in PRR 2013Operating time (min.) Fuel burn
Estimated tota l addi tiona l
(numbers may not add up due to rounding):Es timated operational ineffi ciencies where ANS can have
an impact (time, fuel burn and CO2 emiss ions)
SES Performance Scheme
ANS‐related
inefficiencies
At s tand
Gate‐to‐
gate
Total estimated ANS‐related impact
Airport ATFM arriva l delay
En‐route ATFM delay
Addi tional taxi ‐out time (77 RP1 ai rports )
Addi tional ASMA time (39 RP1 airports)
En route fl ight inefficiencies
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
30
2.4.41 However, just as there are facets of the inefficiency pool not covered, there are system constraints and interdependencies that would prevent the full recovery of the theoretical optimum shown in Figure 2-17.
2.5 Economic evaluation of ANS performance
2.5.1 The Association of European Airlines (AEA), calculates that the share of air navigation charges in total operating cost is on average around 6% (2012) (see also grey box).
2.5.2 Depending on the airline business model, the share of ANS costs in operating costs can vary (i.e. low-cost airlines may have a higher share).
2.5.3 The economic evaluation of ANS performance in the next section is an attempt to monetarise direct ANS costs (en-route and terminal) and the indirect costs due to ANS-related inefficiencies18 which are both borne by airspace users in Europe.
2.5.4 The estimation combines the high-level cost-efficiency results from Chapter 6 with the service quality chapters (4-5) in order to provide a high-level estimate of total ANS-related costs to airspace users in Europe.
Share of air navigation charges in airline operating expenses
According to the Association of European Airlines (AEA), air navigation costs accounted for 6.0% of total operating costs in Europe in 2012.
By far, the most dominant cost factor driving airline operating expenses is fuel (24%), followed by Station & Ground (15%), and Maintenance (10%).
2.5.5 Whilst it is not deemed appropriate to include a monetary value for safety in the economic assessment, its primacy is fully recognised.
ECONOMIC EVALUATION OF ANS PERFORMANCE
2.5.6 In this year’s report, the economic evaluation of ANS performance was based on new data flows which required a change in temporal and geographical scope (see § 2.4.32 to 2.4.35). Due to those changes in data and scope, the figures in this section are not directly comparable to the figures published in previous editions of the report.
2.5.7 In the absence of data enabling long-term trend analysis for all performance areas, Figure 2-18 shows the evolution of traffic (in terms of km), en route unit costs, and en route ATFM delay (summer) between 1990 and 2013 for which a consistent set of data is available.
2.5.8 The time series analysis in Figure 2-18 shows periods of high delays and lower unit costs and vice versa until 2003 resulting in approximately constant economic costs (direct + indirect costs) to airspace users.
2.5.9 The cyclic behaviour was largely linked to a reactive management of ATC capacity. The urgent need to quickly deploy capacity in periods of high delay led to notable increases in costs and the following focus on cost reductions again caused capacity issues.
2.5.10 The situation started to improve visibly from 2003 onwards thanks to a more proactive approach to performance that had begun a few years earlier. In 1997, the performance-oriented ECAC Institutional Strategy was adopted and the independent Performance Review Commission was created in 1998. In 2001, the Provisional Council adopted a
18 The costs of cancellations are not considered in the assessment of total economic ANS costs.
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
31
performance target for ATFM en route delays and the EUROCONTROL capacity planning process was introduced.
Figure 2-18: Long-term trend of traffic, unit costs and en route ATFM delay
2.5.11 As illustrated in Figure 2-18, the increased focus on ANS performance facilitated by the EUROCONTROL “light-touch” ANS performance review system contributed to a continuous reduction of en route ATFM delays and unit costs (total economic costs), temporarily interrupted by the economic crisis in 2008.
2.5.12 The adoption of the Single European Sky (SES) Performance Regulation 691/2010 [Ref. 4] in 2010 complemented and reinforced the EUROCONTROL performance review system and marked the start of the SES performance scheme in the form that we know it today. Regulation 691/2010 has been repealed by Regulation 390/2013 [Ref. 17].
2.5.13 The SES performance scheme places greater focus on planning and accountability for performance, target-setting, monitoring, incentives and corrective actions at both European Union wide and national/FAB levels.
2.5.14 The goal is to ensure further performance improvements from the 1st Reference Period onwards (RP1: 2012-14) through the application of binding performance targets for the SES States19.
2.5.15 The next section provides a high level economic evaluation of ANS performance. It should be acknowledged that the evaluation does not consider costs for on-board equipment nor does it provide a full societal impact assessment which would include, for instance, also the cost of delay to passengers and environmental costs.
2.5.16 Due to data availability (see also § 2.4.32 to 2.4.35), the analysis was restricted to SES States and the period 2011 to 2013 which differs from previous editions of this report.
2.5.17 The direct ANS en route and terminal costs were derived from Chapter 6 of this report, where a more detailed analysis is available. The 2011 and 2012 ANS cost figures represent actuals and the 2013 ANS cost figures were based on the latest available cost projections (P).
2.5.18 ANS-related inefficiencies in operations impact on airspace users in terms of cost of time and fuel. Estimating the costs of such inefficiencies is a complex task requiring expert
19 The 27 Member States of the European Union plus Switzerland and Norway.
0.0
1.0
2.0
3.0
4.0
5.0
6.0
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
€2009 per kilometre
En‐route unit costs (€2009/km)
Traffic in km (index: 1990=1)
En‐route delay (summer)
All States in Route Charges
data source : EUROCONTROL/CRCO, CFMU (delay)
Min
ute
s of
en-
rou
teA
TF
M d
elay
per
flig
ht a
nd
traf
fic in
dex
PerformanceReview
Commission
ECAC InstitutionalStrategy
Single European Sky 1st package
Start of SESPerformance
Scheme
Start of SES PS RP1
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
32
judgement and assumptions based on published statistics and the most accurate data available. There are inevitably margins of uncertainty which need to be taken into account for the interpretation of the results (see also § 2.4.36 on page 29).
2.5.19 The costs of ANS-related additional time in this report is based on a study from the University of Westminster [Ref. 18].
2.5.20 The study differentiates between the cost of time for “tactical delays” (infrequent with a low level of predictability) and “strategic delays” (inherent inefficiencies embedded in the system with a high level of predictability).
2.5.21 In this report, en route and airport ATFM delays were considered as being “tactical” and inefficiencies in the gate-to-gate phase (taxi out, en route, terminal) were considered to be “strategic”.
Costs of ANS-related inefficiencies
The estimated airline delay costs in the University of Westminster study [Ref. 18] include direct costs (fuel, crew, maintenance, etc.) the network effect (i.e. cost of reactionary delays) and passenger related costs.
Whilst passenger ‘value of time’ is an important consideration in wider transport economics, only those costs which impact on the airline’s business (rebooking, compensation, market share and passenger loyalty related costs) were included in the estimate. Estimates of future emissions costs from the EU emission trading scheme from 01 January 2012 were not included.
2.5.22 Fuel price is a major driver of airline costs (see also the distribution of airline operating costs in the grey box on page 30), especially in the context of increasing jet fuel prices over the past years.
2.5.23 The cost of ANS-related additional fuel burn is based on EUROCONTROL models and the average jet fuel price from STATFOR. As the focus of the analysis is on ANS performance, any bias from fuel price changes was removed by applying the average 2013 jet fuel price consistently to all years20.
2.5.24 More information on the applied framework and methodology for the economic evaluation of ANS performance is available in Annex V of this report.
2.5.25 Figure 2-19 shows the estimated total economic ANS-related costs for the SES States between 2011 and 2012 and the provisional trend for 2013, based on the latest available ANS cost projections.
2.5.26 Actual en route ANS costs in the SES area increased by +1.3% in 2012 vs. 2011, which is well below initial plans in November 2011. For 2013, the latest projections indicate an increase in en route (+4.5%) and terminal ANS costs (+2.0%) in the SES area. A detailed analysis focusing on en route and terminal ANS cost-efficiency is provided in Chapter 6.
Figure 2-19: Estimated total economic ANS-related costs (SES States)
2.5.27 ANS service quality related indicators continue to improve in 2013 with a positive impact on cost. The notable reduction of costs due to ANS related inefficiencies is partly due to
20 The “real” cost therefore might have been higher or lower in the individual years, depending on how the 2013 price compares to the price in the respective year.
2011 (A) 2012 (A)Change vs .
20112013 (P)
Change
vs . 2012
9.3 M 9.1 M ‐3.0% 8.9 M ‐1.3%
€ 5 970 M € 6 050 M 1.3% € 6 320 M 4.5%
€ 1 460 M € 1 410 M ‐3.5% € 1 435 M 2.0%
€ 475 M € 325 M ‐32.3% € 275 M ‐14.5%
€ 845 M € 455 M ‐46.3% € 385 M ‐15.4%
€ 750 M € 710 M ‐5.7% € 680 M ‐4.1%
€ 1 130 M € 1 050 M ‐6.9% € 1 000 M ‐4.8%
€ 565 M € 550 M ‐2.9% € 540 M ‐2.2%
11 195 M€ 10 550 M€ ‐5.9% 10 635 M€ 0.9%
Additional ASMA time (39 RP1 airports )
Es timated tota l ANS‐related economic costs
Service quality
ANS
costs
En‐route extens ion (es timates based on KEA
En‐route ANS costs (SES area)
Terminal ANS costs (SES area)
IFR fl ights (M)
Al l costs relate to States subject to the SES Performance
Scheme and are expressed in M € 2009
Additional taxi ‐out time (77 RP1 airports )
Airport ATFM delays (SES area)
En‐route ATFM delays (SES area)
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
33
the 1.5% reduction of traffic in the SES area in 2013 but also due to genuine performance improvements, particularly for ATFM delays.
2.5.28 It is important to point out that, due to improved data availability (see also§2.4.32 to 2.4.35), the estimated cost of additional distance in this PRR were based for the first time on the actual trajectory (KEA) calculated with radar data (see §2.4.37). This refinement had a notable impact on estimated costs calculation compared to previous editions of PRR.
2.5.29 Based on the latest available cost projections for 2013, estimated total economic ANS-related costs in the SES area are expected to increase slightly (+0.9%) in 2013. The increase observed for 2013 is mainly due to the projected increase in ANS costs which cannot be compensated by the notable reduction in service related costs. Similar to last year, it is however expected that the actual 2013 ANS costs (available in November 2014) will be lower than the current 2013 projections due to traffic related cost adaptions.
2.6 Conclusions 2.6.1 Compared to 2012, average daily IFR flights in Europe decreased by -0.8% in 2013 with
notable regional variations in traffic evolution. Despite the lower number of flights, load factors and average aircraft size continued to increase leading to a growth in passenger numbers.
2.6.2 For 2014, the STATFOR 7-year forecast (published in February 2014) expects the European flights to grow by +1.2% in the baseline scenario (Low: -0.1%; High: +2.3%). The average annual growth rate between 2014 and 2019 is forecast to be at +2.6% with IFR flights expected to reach pre-economic crisis levels (2008) by 2016.
2.6.3 The high level evaluation of ANS performance in the European air transport context sets the scene for the more detailed analyses in the respective chapters of this report:
Safety: After the increase between 2009 and 2011, total commercial air transport accidents continuously decreased again to the lowest level over the past 11 years in 2013. Accidents with ANS contribution are rare in Europe and there were no accidents with ANS contribution over the past three years. A more detailed analysis focusing on ANS safety performance is provided in Chapter 3.
Capacity: Albeit in a context of declining traffic, the share of flight arriving within 15 minutes of their scheduled arrival time (punctuality) reached an all-time high of 84.0% in 2013. The share of ANS-related primary delays in 2013 was 23.5% (i.e. 76.5% of primary delays were not due to ANS) which represents a further reduction compared to 2012. Continuing the positive trend observed over the past two years, en route and airport arrival ATFM delays continued to decrease by 17% and 20% respectively in 2013. A more detailed analysis of operational ANS performance en route and at airports is provided in Chapter 4 and 5.
Environment: Overall, the ANS-related impact on total aviation related fuel burn is estimated at 6% (equivalent to 0.2% of total European anthropogenic CO2 emissions). All three ANS related indicators (additional taxi-out time, en route flight efficiency, additional ASMA time) showed an improvement with a positive impact on fuel burn. The reduction in total additional fuel burn is due to small improvements in unit fuel burn and a notable reduction of traffic compared to 2012.
Cost-efficiency: En route ANS costs in the SES area increased by +1.3% in 2012 vs. 2011, which is well below initial plans in November 2011. Entry into force of the Single European Sky (SES) charging regime meant lower revenue than planned as traffic was lower than planned. For 2013, the latest projections indicate an increase in en route (+4.5%) and terminal ANS costs (+2.0%) in the SES area. As in 2012, actual costs for 2013 are expected to be lower due to traffic risk sharing. A detailed analysis focusing on en route and terminal ANS cost-efficiency is provided in Chapter 6.
PRR 2013 CHAPTER 2: ANS IN EUROPEAN AIR TRANSPORT
34
2.6.4 With the advent of the SES performance scheme, more precise data are becoming available (Correlated Position Reports and data provided directly by airport operators). The PRC decided to use the new data flows from this PRR onwards, which improves the accuracy of indicators but creates a discontinuity in time series and limits the geographical scope of the analysis to SES States and to the period 2011 to 2013 as the same level of data is presently not available for all EUROCONTROL States.
2.6.5 The Total economic cost concept presents a consolidated view of direct and estimated indirect costs borne by airspace users and enables a first assessment of interdependencies between KPAs outside safety. It is not an assessment of ANS inefficiencies and, inevitable margins of uncertainty need to be considered.
Chapter 3: Safety
PRR 2013 35 CHAPTER 3: SAFETY
PART II – KEY PERFORMANCE AREAS Safety 3
KEY POINTS KEY DATA (2012)
There was no accident with ANS contribution in 2013. The drop in ANS-related serious incidents in 2013
leads to the lowest level over the past 10 years. Separation minima infringements, runway incursions
and airspace infringements remain the main safety concern.
The 2011 PRC recommendations requesting improvement in safety data reporting and safety data quality are not yet adequately implemented and should be re-iterated.
There is an urgent need to accelerate the deployment of automatic safety data reporting/monitoring tools in Europe in order to improve the identification of safety risks and measure the effectiveness of safety improvement action. Deployment of such tools should also improve the reporting culture and consequently the level of reporting.
In order to use data from automated safety data reporting/ monitoring tools at State, FAB or European level, the event triggers for each type of occurrence need to be harmonised. It is proposed that a pan-European harmonisation project is conducted to ensure that data can be shared and aggregated.
Performance indicators (Annual Summary
Template (AST) reporting) 2012
% change vs. 2011
Total number of reported separation minima infringements
1 796 +14.3%
Separation minima infringements (Severity A+B)
291 +15.5%
Total number of reported runway incursions
1 234 -11.8%
Total number of reported runway incursions (A+B)
49 -42.4%
Total number of reported unauthorised penetration of airspace
5 010 +5.7%
Unauthorised penetration of airspace (Severity A+B)
60 -25.0%
3.1 Introduction 3.1.1 This chapter reviews the Air Navigation Services (ANS) safety performance of the
EUROCONTROL Member States in 2012. Preliminary insights in 2013 are given where available. For the purpose of this report, ANS includes Air Traffic Management (ATM) and Meteorology (MET).
3.1.2 An ancillary purpose of this Safety Chapter is to review the implementation of the PRC recommendations relating to Safety, which were published in PRR 2012 and agreed by the Provisional Council. All of the PRC recommendations arising out of PRR 2012 are listed in Chapter 1 (§1.5.3).
3.1.3 In this chapter, Section 3.2 provides an overview of the data sources used for the analyses. Sections 3.3 to 3.4 show the trends in ANS-related accidents and incidents between 2003 and 2013 (provisional). Section 3.5 provides an analysis of the current status of safety data reporting and investigation in EUROCONTROL Member States. Section 3.6 provides an overview of the EUROCONTROL and EU Safety Performance Monitoring. Finally, Section 3.7 addresses the current status of automatic safety data monitoring in EUROCONTROL Member States before the conclusions in Section 3.8.
3.2 Reporting of ANS-related Accidents and Incidents Note that final investigation reports for some accidents and incidents might be delayed by more than two years, particularly when the investigation is complex. This might have an impact on some graphics in future publications. In addition, the scope of the review may be changed in future reports depending on the added value for reviewing the ANS safety performance and on the improvement in data granularity and data quality.
3.2.1 The review of ANS-related accidents and incidents is based on:
Accident and serious incidents from 2003 to 2012 and preliminary 2013 data contained in the EASA database; and
Incident data from 2003 to 2012 and preliminary 2013 data reported to EUROCONTROL via the Annual Summary Template (AST) reporting mechanism.
PRR 2013 CHAPTER 3: SAFETY
36
3.2.2 In last year’s PRR (2013), the sources for safety occurrence data were changed to incorporate the various data sources available in order to provide the best and most complete review of safety performance. Figure 3-1 below shows various data bases used for the analysis in this chapter.
Figure 3-1: Sources of safety data used for safety performance review
3.2.3 During the analysis of completeness and quality of existing safety data sources, it has been concluded that, for the time being, the European Central Repository (ECR) will not be used as an additional source for safety performance analysis due to several reasons:
Currently ECR21 is highly exposed to the risk of storing a considerable amount of duplication, as an occurrence taking place in a Member State and involving an aircraft operator from another Member State may be reported by both States. Such a possible duplication does not exist in the AST mechanism as the reporting is only done for occurrences taking place in the reporting State.
The ECR and the exchange of information between the national databases of the EU Member States is supported by the European Commission through the ECCAIRS system (European Co-ordination Centre for Accident and Incident Reporting Systems), managed by the Joint Research Centre (JRC) of the European Commission. However, although JRC provides technical support and training courses to ECCAIRS users, there is no European entity in charge for assessing ECR quality and completeness and to provide support to States for filing information correctly.
3.2.4 The scope of the safety review in this chapter is summarised in Figure 3-2 below.
Analysis scope Type Category Weight Accident (EASA DB)
ANS related ANS contribution
Commercial Air Transport (CAT) General Aviation (GA)
Fixed wing Helicopters
>2 250 Kg
Serious Incidents (EASA DB)
ANS related ANS contribution
CAT Fixed wing >2 250 Kg
Incidents (EUROCONTROL AST)
ANS related All All No limitation
Figure 3-2: Scope of ANS review in this chapter
21 The European Central Repository (ECR) is a centralised database where all EU Member States integrate their safety occurrence data, including data on accidents and serious incidents (see also Commission Regulation (EC) No 1321/2007).
PRR 2013 CHAPTER 3: SAFETY
37
3.3 Accidents and Serious Incidents ANS-related vs. ANS contribution
“ANS related” means that the ANS system may not have had a contribution to a given occurrence, but it may have a role in preventing similar occurrences in the future. “ANS contribution” means that at least one ANS factor was in the causal chain of events leading to an occurrence, or at least one ANS factor potentially increased the level of risk, or it played a role in the occurrence encountered by the aircraft.
ACCIDENTS
3.3.1 Figure 3-3 shows the ANS-related accidents in Commercial Air Transport (CAT) involving fixed wing aircraft with more than 2250kg in the EUROCONTROL area between 2003 and 2013.
Figure 3-3: ANS-related accidents in the EUROCONTROL area
3.3.2 The long term trend shows a reduction of ANS-related accidents over the past 11 years. In total there were three ANS-related accidents in 2013 which is the same level as in 2012.
3.3.3 For the past three years (2011-2013) there were no fatal ANS-related accidents (orange bars) or accidents with ANS contribution (blue line).
3.3.4 Figure 3-4 shows the cumulative number of ANS-related accidents (2011-2013) by occurrence category, as defined by ICAO Commercial Aviation Safety Team taxonomy (CAST/ICAO). It should be noted that some accidents may have been assigned to more than one occurrence category.
ARC = Abnormal Runway Contact
ATM/CNS = Air Traffic Management / Communication Navigation Surveillance
CABIN = Cabin Safety Events
CFIT = Controlled Flight Into Terrain
GCOL = Ground Collision
MAC = Mid-Air Collision
RI-VAP = Runway Incursions Vehicle, Aircraft, Person
TURB = Turbulence
WSTRW = Wind Shear, Thunderstorm Related Weather
Figure 3-4: ANS-related accidents by occurrence category (EUROCONTROL area)
3.3.5 The majority accidents between 2011 and 2013 were related to adverse weather (TURB + WSTRW) which typically includes strong wind, gusting wind, wind shear, microburst and turbulence.
012345678910
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
NumberofAccidents
Year
ANS‐relatedaccidentsinCommercialAirTransport,(fixed‐wing,weight>2,250kg)
Fatal Non‐Fatal AccidentswithANSContributionSource: EASA
0
1
2
3
4
5
6
7
ARC ATM/CNS CABIN GCOL TURB WSTRW
NumberofAccidents
Cumulative(2011+2012+2013)NumberofANSRelatedAccidentsbyOccurrenceCategory(fixed
wing,weight>2,250kg)
Source: EASA
PRR 2013 CHAPTER 3: SAFETY
38
3.3.6 Ground Collision (GCOL) was the second largest category of CAT accidents between 2011 and 2013 and there was no ATM/CNS accident. No CAT accident occurred in the other categories (MAC, RI-VAP, CFIT22) between 2011 and 2013.
SERIOUS INCIDENTS
3.3.7 Figure 3-5 shows the ANS-related serious incidents23 in CAT (fixed-wing aircraft > 2250kg) in the EUROCONTROL area between 2003 and 2013.
Figure 3-5: ANS-related serious incidents in the EUROCONTROL area
3.3.8 Between 2010 and 2013, ANS-related serious incidents in the EUROCONTROL area (blue line) declined continuously in line with the total number of serious incidents to the lowest level over the past 11 years.
3.3.9 Figure 3-6 shows the cumulative number of ANS-related serious incidents by occurrence category (taxonomy per CAST/ICAO) between 2011 and 2013. Some of the serious incidents might have been assigned to more than one category.
ATM/CNS = Air Traffic Management / Communication Navigation Surveillance FUEL = Fuel related Near CFIT = Near Controlled Flight Into Terrain Near GCOL = Near Collision (i.e. losses of separation) on the ground, but excluding the runway. Near MAC = Near Mid-Air Collision, i.e. loss of separation in the air RI-VAP = Runway Incursions Vehicle, Aircraft, Person TURB = Turbulence WSTRW = Wind Shear, Thunderstorm Related Weather
Figure 3-6: ANS-related serious incidents by occurrence category (EUROCONTROL area)
3.3.10 Between 2011 and 2013, near Mid-Air Collision, i.e. loss of separation in the air (Near MAC), ATM/CNS and Runway Incursions (RI-VAP) were the most frequent serious incidents in ANS.
22 CFIT was the most prevalent occurrence category for CAT helicopters and General Aviation (>2 250 Kg). 23 A serious incident is defined as an incident involving circumstances indicating that an accident nearly occurred.
0
10
20
30
40
50
60
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
NumberofSeriousIncidents
ANS‐relatedseriousincidentsinCommercialAirTransport,(fixed‐wing,weight>2,250kg)
All ANSContributionSource: EASA
0
5
10
15
20
25
30
35
40
45
ATM/CNS
NearCFIT
FUEL
NearGCOL
NearMAC
RI‐VAP
TURB
WSTRW
NumberofSeriousIncidents
Cumulative(2011+2012+2013)NumberofANS‐relatedseriousincidentsbyOccur.Cat.(fixedwing,weight>2,250kg)
Source: EASA
PRR 2013 CHAPTER 3: SAFETY
39
3.4 Incidents 3.4.1 This section provides a review of ATM-related incidents, reported through the
EUROCONTROL Annual Summary Template (AST) reporting mechanism (updated in April 2014). It should be noted that data for 2013 is only preliminary and significant updates are expected for the September 2014 reporting session. The PRC has availed of, with gratitude, the data provided by EUROCONTROL Safety Regulation Commission (SRC) in its Annual Reports 2013 and 2014 [Ref. 19].
3.4.2 It should be noted that “Severity A” in the EUROCONTROL AST corresponds to “Serious incident” in the EASA database. The absolute number of “Severity A” incidents in the AST is higher than the total “Serious incidents” in the EASA database.
3.4.3 There is no applicable regulatory provision that would impede CAAs, NSAs and ANSPs to classify an incident as “Severity A” even if it has not been investigated by the Safety Investigation Authorities (SIAs). Nevertheless, all “Severity A” incidents should be notified to the SIAs.
3.4.4 At the time the report was published it was not possible to determine the reasons why such difference in numbers exists. Reasons may be related to criteria used by the SIAs for selecting serious incidents and by the notification procedures and practices24 used at national level for notifying about Severity class A.
3.4.5 The abovementioned issue, together with other issues related to the quality and completeness of safety occurrence data (AST, ECR and EASA database), is constantly closely monitored by a Task Force composed of members of the Performance Review Unit (PRU), EASA and the EUROCONTROL Directorate Pan-European Single Sky (DPS).
AIRSPACE - SEPARATION MINIMA INFRINGEMENTS
3.4.6 In 2012, the total number of reported Separation Minima Infringements (SMIs) increased by 14%, compared to the previous year.
3.4.7 Figure 3-7 depicts the number of reported risk-bearing SMIs (Severity A and B) in EUROCONTROL airspace between 2003 and 2013(P). In 2012, the risk bearing SMIs accounted for 16% of the total number of reported SMIs.
Figure 3-7: Reported high-risk SMIs in EUROCONTROL States (2003-13P)
3.4.8 Year on year, serious incidents (Severity A) decreased in absolute numbers from 35 to 33,
24 These issues have also been identified in a number of States during ICAO USOAP audits.
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013(P)
N° of States reporting 29 26 26 28 28 29 30 31 33 36 36
Total n° reported 889 1 226 1 281 1 398 1 567 1 711 1 418 1 402 1 571 1 796 2 166
Severity B 152 164 243 250 295 236 141 178 217 258 236
Severity A 76 67 80 73 70 56 27 16 35 33 31
% : Proportion of Severity A+B 25.6% 18.8% 25.2% 23.1% 23.3% 17.1% 11.8% 13.8% 16.0% 16.2% 12.3%
76 67 80 73 70 5627
1635 33 31
152 164
243 250295
236
141 178
217258
236
26% 19%
25% 23%
23%
17%
12%
14%
16%
16%12%
0
100
200
300
400
Number of Occurren
ces
Separation Minima Infringements
Severity B Severity A % : Proportion of Severity A+B
Source: SRC Annual Report 2014
PRR 2013 CHAPTER 3: SAFETY
40
whilst major incidents (Severity B) increased in absolute numbers from 217 to 258 in 2012.
AIRSPACE - UNAUTHORISED PENETRATION OF AIRSPACE
3.4.9 The total number of Unauthorised Penetrations of Airspace (UPAs) in 2012, also known as Airspace Infringements (AIs), reported in EUROCONTROL Member States increased by almost 6%, compared to 2011.
3.4.10 As illustrated in Figure 3-8, the share of risk bearing (Severity A and B) UPAs within total reported UPAs decreased from 1.7% in 2011 to 1.2% in 2012.
Figure 3-8: Reported high-risk UPAs in EUROCONTROL States (2003-2013P)
3.4.11 The absolute number of serious UPAs (Severity A) reported in 2012 shows a decrease compared to 2011 (from 12 to 10 events). The number of major airspace infringements (Severity B) also decreased from 68 to 50 in absolute terms in 2012.
AIRPORTS - RUNWAY INCURSIONS
3.4.12 Total reported Runway Incursions (RI), reported in EUROCONTROL Member States, decreased by approximately 12% in 2012.
Figure 3-9: Reported high-risk RIs in EUROCONTROL States (2003-2013P)
3.4.13 In 2012, the risk-bearing RIs (Severity A and B) depicted in Figure 3-9 represented 4% of the total number of reported events, which represents a decrease from 6% in 2011.
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (P)
N° of States reporting 29 26 26 28 28 29 30 31 33 36 36
Total n° reported 1 178 1 209 1 983 2 041 2 416 2 797 3 336 3 381 4 742 5 010 2 885
Severity B 31 19 58 48 49 52 53 79 68 50 42
Severity A 28 7 16 8 5 3 6 4 12 10 2
% : Proportion of Severity A+B 5.0% 2.2% 3.7% 2.7% 2.2% 2.0% 1.8% 2.5% 1.7% 1.2% 1.5%
28
716
8 5 36 4
12 102
31
19
58
4849 52
53
7968
50
42
5.0%
2.2%
3.7%
2.7% 2.2% 2.0%1.8%
2.5% 1.7%
1.2%
1.5%
0
20
40
60
80
100
Number of Occurren
ces
Unauthorised Penetration of Airspace
Severity B Severity A % : Proportion of Severity A+B
Source: SRC Annual Report 2014
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (P)
N° of States reporting 29 26 26 28 28 29 30 31 33 36 36
Total n° reported 387 564 629 680 885 926 1 094 1 385 1 399 1 234 1 366
Severity B 38 32 52 51 44 40 36 77 62 37 62
Severity A 25 16 9 13 12 14 15 22 23 12 13
% : Proportion of Severity A+B 16.3% 8.5% 9.7% 9.4% 6.3% 5.8% 4.7% 7.1% 6.1% 4.0% 5.5%
2516
9 13 12 14 15 22 23
12 13
38
3252
5144 40 36
77
62
37
62
16%
9%
10%9%
6%6%
5%
7%
6%
4%
5%
0
20
40
60
80
100
120
Number of Occurren
ces
Runway Incursions
Severity B Severity A % : Proportion of Severity A+B
Source: SRC Annual Report 2014
PRR 2013 CHAPTER 3: SAFETY
41
3.4.14 In absolute terms, serious RIs (Severity A) decreased from 23 to 12, and major events (Severity B) decreased significantly from 62 to 37 in absolute terms in 2012.
ATM SPECIFIC OCCURRENCES
3.4.15 This section provides a review of the evolution of the risk bearing ATM specific occurrences (Severity AA, Severity A, Severity B) reported through the AST, as updated in the September 2013 reporting cycle.
3.4.16 ATM specific occurrences encompass those situations where the ability to provide safe ATM services is affected. Therefore, this type of occurrence typically includes failures that would affect the ANS Providers capability to deliver safe ATM services.
3.4.17 The total number of reported ATM specific occurrences in 2012 shows 18% decrease comparing to 2011. Overall, risk-bearing ATM specific shows a decreasing trend between 2010 and 2013 (Figure 3-10).
Figure 3-10: Reported high-risk ATM Spec. Occurrences in EUROCONTROL States (2004-
2013P)
3.4.18 Year on year, the number of reported highest risk categories decreased in 2012:
the number of occurrences with a total inability to provide ATM services (AA) decreased from 18 in 2011 to 10 in 2012 (44% decrease);
occurrences with the serious inability to provide ATM services (A) decreased from 49 in 2011 to 34 in 2012 (31% decrease); and,
the partial inability to provide ATM services (B) dropped notably from 799 events in 2011 to 588 in 2012 (26% decrease).
3.5 Reporting and Investigation 3.5.1 This section provides a review of the quality and completeness of ATM safety
occurrences (operational and ATM specific occurrences) reported through the AST reporting mechanism, as updated in September 2013and April 2014 (where applicable).
TOTAL NUMBER OF HUMAN REPORTS
3.5.2 For each EUROCONTROL Member State, the level of reporting is measured by normalising the total number of reported ATM-related occurrences against the number of flight hours in the State. The main affecting factors for the level of reporting are the level of Just Culture and the effectiveness of the Mandatory Occurrence Reporting Systems (MORS). However, the affecting factors are not presented in this report.
0
100
200
300
400
500
600
700
800
900
1000
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013(P)
Number of Occurren
ces
ATM Specific Occurrences
AA
A
B
Source: SRC Annual Report 2014
PRR 2013 CHAPTER 3: SAFETY
42
3.5.3 The annual level ATM-related incident reporting in Figure 3-11 (blue bars) is compared to the average ECAC reporting level in 2003, which represents the red baseline.
3.5.4 The number of Member States reporting safety occurrences to the SRC shows a slow but steady improvement over the past years.
3.5.5 As a result, the number of Member States reporting above the baseline in 2012 (24) was more than three times higher than the number of States reporting under the baseline (7) (Note that this information could not be updated for 2013 – as data is not available yet).
3.5.6 The data for 2012 shows an increase of over 7% in the total number of incidents reported in comparison with 2011 and the number of ECAC Member States reporting increased to a record level of 36 (Figure 3-11).
Figure 3-11: Total number of reports and level of reporting (2002-2012)
3.5.7 However, as in previous years, a small number of EUROCONTROL Member States (Monaco, Turkey and Ukraine) did not submit their ASTs covering the 2012 occurrence data, notwithstanding their obligations under CN Decision No. 115.
3.5.8 The observed increase in 2012 can be partly driven by improved reporting levels and by an increase in the number of occurrences. The safety data presently available do not allow the factors generating the increase in the total number of reported incidents to be determined with certainty. In addition, the decrease in 2013, could be partially related to the fact that several Member States indicated that they did not submit preliminary data/reports on time.
3.5.9 As also indicated in the SRC 2013 Annual Safety Report [Ref. 19], and following a period of monitoring and measuring, it was observed that, although many Member States increased their reporting levels in comparison to previous years, the difference in reporting levels, compared to the Member States reporting at the highest levels, continues to exist.
3.5.10 Figure 3-12 shows, whilst the average ECAC reporting rate has considerably improved over the last decade, it is still three times lower than the average of the best 3 reporters, even if the Member State with the highest reporting rate is not taken into account.
0
2
4
6
8
10
12
14
16
0
5
10
15
20
25
30
35
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013P
Flight ours in the reporting States (million)
Number of incidents rep
orted
(thousands)
Evolution of the number of Reported Occurrences
Source: SRC Annual Report 2014
Base lineECAC reporting level in 2003
0
5
10
15
20
25
30
2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Sta
tes
per
cate
gory
Level of reporting ATM related incidents(baseline 2003)
Less than half of the baselineMore than half of the baselineAbove baseline
Source: SRC Annual Report 2013
PRR 2013 CHAPTER 3: SAFETY
43
Figure 3-12: Current and possible levels of manual reporting (2001-2012)
3.5.11 For this reason, the PRC firmly believes that a lot of political will is needed to remove these types of inconsistencies in the data collection and that currently the analysis of safety performance is as good as it can be with those impediments in place.
UNCLASSIFIED OR UNDETERMINED OCCURRENCES
3.5.12 Figure 3-13 shows the number of ATM-related incidents not severity classified25 or with severity classification not determined (Severity D) for different occurrences categories.
Figure 3-13: Severity not classified or not determined (2005-2013P)
SMI = Separation minima infringements
RWY = Runway incursions
IS = Inadequate separation
UAP = Unauthorised penetrations of airspace
CLR = Deviation from ATC clearance
3.5.13 Although there has been an overall improvement compared to 2011, 38% of all reported occurrences were still not severity classified in 2012. Considering each type of occurrence separately, the percentage varies between 5% and 23%. If “not determined” (i.e. some data provided but not enough to fully assess the severity) are also included, the range increases to 13% - 50% of total reported occurrences.
3.5.14 The situation has seen improvements for SMIs, where the percentage of occurrences not severity classified decreased from 12% of the total number in 2011 to 5% in 2012.
25 Aligned with the proposal for the new Occurrence Reporting Regulation to include the obligation to classify occurrences in terms of risk according to a European common risk classification scheme http://ec.europa.eu/governance/impact/ia_carried_out/docs/ia_2012/com_2012_0776_en.pdf
0
1000
2000
3000
4000
5000
6000
7000
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Current reporting levels and possible reporting levels(number of incidents per million flight hours)
Average best 3 reporters (2001-2010)
Average ECAC rate
Are
a of
Im
pro
vem
ent
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 (P)
Number of Occurrences Severity NOT Classified
SMI
RWY
IS
UAP
CLR
Source: 2014 SRC Annual Report
PRR 2013 CHAPTER 3: SAFETY
44
However, if the SMIs where the severity was not determined (severity class D) are added the percentage rises to 14%.
3.5.15 In 2012, for 10% of the RIs reported the severity was not determined. If the situation where the severity is absent is added it amounted to more than 14%. This represents a significant improvement compared to the previous year's data, when the percentage amounted to over 35%.
3.5.16 In conclusion, the number of unclassified or not determined incidents is still higher than the levels in 2007.The number of incidents reported through the AST mechanism which are not severity classified increased from over 37% in 2011 to over 43% in 2012, reaching the highest level in the last decade.
3.5.17 This situation is of concern, not only for the outcome of the analysis at European level, but also for the outcome of national safety analysis (as this outcome is indicative for the results of analysis and investigation performed at national level), the sustainability of the human reporting system26, and other potential downstream repercussions such as inadequate prevention of similar incidents or inadequate sharing and dissemination of lessons learnt.
COMPLETENESS OF SAFETY DATA REPORTED VIA THE AST MECHANISM
3.5.18 Figure 3-14 shows the typical fields that are either left blank or marked Unknown in the AST, submitted by the EUROCONTROL Member States in 2012.
ATM contribution = direct; indirect; none
Type operation = GAT or OAT
Airspace = Class of airspace: A,B,C,D,E
Flight Rules = IFR or VFR
Traffic Type = General Air Traffic, Commercial, Military
Phase of Flight = taxi, take-off, climb to cruise, cruising, approach
Figure 3-14: Completeness of AST reported data in 2012
3.5.19 The amount of fields left blank is much higher than the field where the word Unknown was inserted. It ranges from 24% up to over 60% of the reported operational occurrences. ATM contribution to the occurrence, which is the most relevant data for determining the performance of the ATM system, is left blank in case of over 24% of the reported incidents.
3.5.20 This lack of completeness of AST data hampers comprehensive safety analysis at European level.
3.6 EUROCONTROL and EU Safety Performance Monitoring 3.6.1 In 2012, the safety performance monitoring in EUROCONTROL States went through
significant changes which have been determined by the legislative initiatives of the
26 When ATCOs or pilots provide safety reports, if feedback is not provided it can have an adverse impact on the motivation to report.
0%
10%
20%
30%
40%
50%
60%
70%
80%
ATMContribution
Typeoperation
Airspace Flight Rules Traffic Type Phase ofFlight
% Empty+Unknown
% Empty
% Unknown
Completness of the AST Reported Data
Source: SRC Annual Report 2013
PRR 2013 CHAPTER 3: SAFETY
45
European Union (EU). Enhancements and detailed characteristics of the new safety performance monitoring activities were described in PRR2012 [Ref. 2].
3.6.2 The overview of the safety performance monitoring at EUROCONTROL and EU level in Figure 3-15 shows that the monitoring is aligned across European States (i.e. same indicators and data) which allows the PRC to report on the pan-European level, aligned with the reporting on the EU wide level under the PRB.
Safety Performance Indicators
Lagging indicators Accidents
Serious incidents: SMIs, UPAs, RIs, ATM specific occurrences
Leading indicators Effectiveness of Safety Management (EoSM)
Just Culture (JC)
Application of the severity part of the RAT methodology
Collection SES States Non-SES States
with EASA agreement
Non-SES States without EASA
agreement
EoSM and JC questionnaires EASA EASA EUROCONTROL
RAT methodology application EUROCONTROL AST
Lagging indicators EASA DB, EUROCONTROL AST
Figure 3-15: Set-up of the European Safety Performance monitoring
Note: SES States bound by provision of Performance Scheme ( i.e. the 27 EU Member States plus Norway and Switzerland). The majority of SES States are also EUROCONTROL State; non-SES States not bound by the provisions of the SES Performance Scheme (10 out of the 12 States have a working arrangement with EASA).
SAFETY PERFORMANCE (2013)
3.6.3 Information on the new leading safety indicators (see Figure 3-15) was for the first time, collected, analysed and reported in 2013. The PRB Annual Monitoring Report 2012 [Ref.20] for the first time gave an overview of the status of safety performance in SES States. Consolidated observations were made during the review of the National/FAB 2012 Monitoring Reports and measurements of safety performance indicators (SPIs) for the first year of the first reference period (RP1) of the SES Performance Scheme.
3.6.4 Separately, data from EUROCONTROL Member States, reporting on a voluntary basis, was also analysed. At the time of publishing of this report, five (non-SES) EUROCONTROL States have provided information on the Effectiveness of Safety Management (EoSM) and Just Culture (JC) on a voluntary basis (on the basis of a PRC Recommendation) which is more than last year. The non-SES EUROCONTROL States that have completed surveys on EoSM, and JC in 2013 were Armenia, Croatia (which is still a non-SES State in RP1), Macedonia, Montenegro, and Serbia.
3.6.5 SPIs results measuring at State level the capability of the States to manage the State Safety Programme (SSP) and at a service provision level, the service provider’s capability to manage an effective Safety Management System (SMS) show that Component 1 - State/ANSP safety policy and objectives was the strongest area while Component 5 - Safety culture was the weakest area at both State and ANSP level in both 2012 and 2013.
3.6.6 Overall, the verified results for EoSM at State level showed that the implementation of safety management principles at the State level were below the implementation levels of ANSPs. This raises concerns whether and how States are performing their oversight and safety management tasks and responsibilities.
3.6.7 As reported in the SRC 2013 Annual Safety Report [Ref.19], the number of ATM-related incidents not severity classified for different types of incidents decreased in most areas in 2012, especially in Separation Minima Infringements and Runway Incursions. One
PRR 2013 CHAPTER 3: SAFETY
46
possible cause for this evolution could be related to the obligation of EU Member States to implement and use the RAT methodology for the severity classification and assessment of the above-mentioned types of occurrences in the context of the Performance Scheme Regulation [Ref. 4 and Ref. 17].
3.6.8 However, the percentage of incidents not severity classified in 2012 amounts to around 38% of the number of reported events or over 43% if the occurrences where the severity is classified as “not determined” (i.e. some data provided but insufficient to fully assess the severity). As mentioned in before (see §3.5.12 ff. on page 43), this situation is of concern, and similar regulatory revisions, to encourage non-SES Member States to apply severity classification and assessment, are needed.
3.7 Automatic safety data monitoring 3.7.1 Within the SES Performance Scheme, safety is explicitly identified as one of the key
performance areas to be monitored. In addition, with increasing pressures on the other three areas (i.e. capacity, environment and costs), safety needs to be monitored closely to ensure that pressure from other performance areas does not negatively impact on safety.
3.7.2 Besides the context of ensuring safety under the pressures from other areas highlighted above but also by broadening requirements and scope of the SES Performance Scheme for the second reference period, more specifically by the introduction of an additional safety indicator that shall monitor the application of automatic safety recording systems where available, automatic safety data collection has to be considered seriously.
3.7.3 The PRC has long advocated the general introduction of automated safety data reporting/monitoring tools27 as one enabling element to improve the level of reporting and in general assessing safety performance.
3.7.4 Such tools will support the application of the RAT by improving trend analysis for the identification of safety risks and subsequently the monitoring of the effectiveness of safety actions. They can remove subjectivity and variability in reporting even if they are not 100% accurate.
3.7.5 Additionally, occurrence data for 2013 shows a decrease in the number of high-severity SMIs and RIs being reported. However, the number of ‘not investigated’ ATM safety occurrences remains high. This is why the PRC considers that the current manual reporting should be complemented by independent monitoring based on automatic safety data acquisition tools.
3.7.6 Indeed, as further explained in the following section, it appears that acceptance of automatic acquisition
Automated safety data monitoring tools
When talking about automated safety tools and their possible use for monitoring of safety and or generating automated reporting one has to take into account that there might be a different understanding of what an automated safety (monitoring) tool is and how it is being used and for what purposes. The distinction of the purpose might as well be a limiting factor for the use of automated tools.
Automated safety tools can improve trend analysis for the identification of safety risks and subsequently monitoring the effectiveness of safety actions. In addition, they can remove subjectivity and variability in reporting. However, some necessary requirements of such system are as follows:
be non-punitive and contain adequate safeguards to protect the source(s) of the data for safety data/occurrences monitoring;
ensure automatic recording of data/occurrences and events;
enable monitoring and analysing of occurrences.
Eurocontrol offers for their ASMT Tool at Maastricht UAC the following definition, which could suit the conceptual definition to be considered here:
ASMT provides an automatic monitoring facility for safety related occurrences based on operational data. It detects and categorizes each occurrence for assessment by trained operational experts. The tool will help determine causes and assist in the evolution of local
27 For example, one of the PRC’s adopted recommendations (PC 33, May 2010), arising out of PRR 2009, was that: “The Provisional Council encouraged States and ANSPs to use automatic detection and reporting tools and to further improve the transparency of ANS safety.” See also Annex I.
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data for the purposes of safety and/or risk monitoring has made great progress lately.
procedures, airspace design, equipment and techniques. (guide to Methods & Tools for Safety analysis in ATM – Eurocontrol 2003)
IMPLEMENTATION STATUS (2012)
3.7.7 Currently, there are a number of initiatives backed by various solutions. Figure 3-16 displays the current status of deployment of the EUROCONTROL Automatic Safety Monitoring Tool (ASMT) as well as comparable tools28 in EUROCONTROL States.
3.7.8 At the moment, the ASMT is deployed and used by 12 Member States.
Figure 3-16: States with automatic reporting tools (2012)
3.7.9 The PRC is of the opinion that some automatic tools for detection of potentially unsafe runway events will be extensively deployed in the near future. Being one of the primary risks in aviation, RIs are a top priority risk worldwide and it is expected that the gathering of runway incursion data will allow runway incursion risks to be properly evaluated and mitigated. Runway safety nets are used to alert controllers to conflicts on the runway surface, either by aircraft or ground vehicles. In Europe, one of already widely deployed systems, runway safety nets for controllers, are provided through Advanced Surface Movement Guidance & Control System (A-SMGCS). According to its concept of operations, an A-SMGCS can contribute to safety as the risk of a runway incursion could be reduced by about 50% with its support.
3.7.10 Nevertheless, based on the analysis of the A-SMGCS implementation status (European Single Sky Implementation Plan (ESSIP) 2013, the LSSIP reports [Ref. 21]), and information available in the LSSIP database (2013), the current implementation levels of the A-SMGCS of both Level 1 (Improved Surveillance) and Level 2 (Surveillance + Safety Nets) indicate that additional work is needed in order to achieve the objectives set in the ATM Master Plan by the end of 2017 (although the majority of the participating airports declared that they will achieve the objectives by the end of 2015).
3.7.11 Out of 74 EUROCONTROL Member States airports, which are addressed through ESSIP/LSSIP process (airports participating in airport implementation objectives and/or are main airports of a Member State), 45 had or have intention to implement A-SMGCS Levels 1 and 2. Figure 3-17 shows the implementation status of A-SMGCS Levels 1 and 2. The analysis excludes airports which declared that this objective in “not applicable” to them. The applicability area includes only airports for which the objective is likely to deliver significant benefits.
28 Note that information on comparable tools might be incomplete, as additional organisations may be using similar tools that PRC was not aware of at the time of publishing of this report.
PRR 2013 CHAPTER 3: SAFETY
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Figure 3-17: A-SMGCS implementation status (Source: LSSIP 2012)
3.7.12 The implementation date for Level 1 was December 2011. LSSIP 2013 states that only 53% of the 45 airports have achieved full operational capability. Insofar as Level 2 is concerned, the deadline for full operational capability is December 2017 (ATM Master Plan). Some 44% of the 45 airports had fully implemented Level 2 in 2013.
AUTOMATIC SAFETY DATA MONITORING AT EUROPEAN LEVEL
3.7.13 Automatic safety data acquisition can serve two different but complementary purposes:
First, automated safety data acquisition can be used by the ANSP to augment the manual data collection in support of its own Safety Management System (SMS), where events detected manually or automatically are analysed and lessons learned are used for a continuous improvement of the safety level.
The other use of automated safety data acquisition is done rather at a Local or European scale for the purpose of monitoring a certain level of risk. The focus of such monitoring is not the individual event, but aggregated statistics that are not influenced by the change of the level of safety occurrence reporting. Such statistics can provide an indication of trends over time, identify geographical ‘hot-spots’, or highlight other sensitive issues.
3.7.14 Nevertheless, it is important to mention that the implementation of automated safety data reporting tools should be based on the same basic principles such as confidentiality, adequate protection, trust and mutual respect as any other incident reporting system.
3.7.15 In order to progress with the automated safety data reporting tools the PRC recommends that all the comparable tools and/or methods are being harmonised. It is recommended to those States not having automatic safety monitoring/recording tools in place to align their new systems with the ASMT functions. This will allow a better set of safety data. The methodology of ASMT guarantees consistency and comparability and is a real contribution to assessing safety incidents. However, it is recognised that States not having a Just Culture mechanism in place will find it difficult to introduce these type of tools.
3.7.16 The establishment of automated data acquisition tools at European level is not a technological issue. It requires however a clear mandate and right of access to data to develop an independent means for safety risk measurement: (i) to support the monitoring of airspace infringements, ground proximity, separation minima infringements and level busts and (ii) to enable these occurrences to be mitigated at European level.
3.7.17 A good example of such data gathering approach is the height monitoring unit (HMU) which has been established related to a particular operational issue (i.e. RVSM). One of the roles of the HMU is to assess the risk of collision in the vertical plan and to monitor that the Target Level of Safety (TLS) is being met.
3.7.18 PRC is of the view that independent monitoring of ANS/ATM safety performance at the European level is needed. At the moment, safety performance monitoring is available
47%53%
A‐SMGCS Level 1 implementation status
Late
Completed51%
4%
44%
A‐SMGCS Level 2 implementation status
Planned
PartlyCompleted
Completed
PRR 2013 CHAPTER 3: SAFETY
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either through the use of safety indicators that are based on self-assessment29 or on indicators that are reported through the State (such as the number of incidents30). An independent and neutral indicator does not exist at European level at the moment. The introduction of an independent safety performance monitoring indicator would provide indications of safety performance trends that are not influenced by manual reporting or by self-assessment.
3.7.19 Additionally, systematic capture and analysis of safety occurrences in the European network (hotspots) are essential for the Network Management function in their role of optimising the design of the network from a safety point of view.
3.7.20 The deployment of automatic safety data acquisition offers the best prospect of establishing an accurate, reliable and transparent safety database for Europe.
3.7.21 There is an urgent need to clarify the institutional, legal and organisational aspects related to such an endeavour with close cooperation between ICAO, the EU, EUROCONTROL and States.
3.7.22 It is important to note that the success of implementing automatic safety data reporting at State level is dependent on a clear mandate and right of access to data, a clear definition of the operational concept, sufficient resources for data analysis, respective training, and an appropriate link into the overall SMS. In addition, from a human factors point of view, the introduction of these tools has to be negotiated, when required, with the staff representative organisations to ensure a buy-in and contributes to improvement of Just Culture.
3.7.23 Overall, there is an urgent need to accelerate the deployment of automatic safety data reporting tools in Europe in order to improve the reporting culture and consequently the level of reporting. In preparation of and during the deployment, “Just Culture” needs to be addressed as an important enabler. Sufficient resources are needed to validate the data properly, analyse the results and draw lessons.
3.7.24 In order to use data from automated safety data reporting/ monitoring tools at State, FAB or European level, the event triggers for each type of occurrence need to be harmonised. It is proposed that a pan-European harmonisation project is conducted to ensure that data can be shared and aggregated.
3.7.25 Lastly, a single European database, that meets data quality criteria, is an essential enabler for effective safety analysis at European level and an independent mean for safety risk measurement.
3.8 Conclusions 3.8.1 In 2013, there was no accident with ANS contribution. The number of reported ANS-
related serious incidents decreased, and reached the lowest level in the past 11 years. In the period 2011-2013 the main ANS related serious incident categories remain losses of separation in the air, runway incursions and ATM/CNS occurrences.
3.8.2 Overall, performance review indicates high levels of safety in Europe, as only a very small portion of the total flights are reported as incidents (approximately 0.3%).
3.8.3 The level of occurrence reporting to EUROCONTROL Annual Summary Template (AST) reporting mechanism is still unsatisfactory. There are three EUROCONTROL States not submitting the AST (Monaco, Turkey and Ukraine) and the level of reporting from seven States is still below the established baseline. However, it has to be noted that the number of ECAC Member States reporting increased to a record level of 36 in 2012.
29 Even though the verification mechanism for these SPIs is defined in 691/2010. 30 Analysis of the number of incidents and their trends currently provide more indication on the change in the
reporting culture than on the evolution of the safety risk. Moreover this type of data is only available with one or two years of delay.
PRR 2013 CHAPTER 3: SAFETY
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3.8.4 The number of un-assessed incidents is still higher than the levels in 2007. This situation is of concern, not only for the outcome of the analysis at European level, but also for the national safety analysis and for the sustainability of the human reporting system. Further, safety occurrences provided by States to EUROCONTROL through the AST mechanism are often incomplete. This diminishes the capability of safety analysis at European level.
3.8.5 States should ensure the provision of sufficient capabilities to deal with the reporting, investigation, storing, classification and analysis of ATM safety occurrences.
3.8.6 Where no existing regulations are in place, States should support the inclusion of specific provisions regarding the severity classification of ATM occurrences in their safety regulatory framework.
3.8.7 There is an urgent need to accelerate the deployment of automatic safety data reporting/monitoring tools in Europe in order to improve trend analysis for identification of safety risks and measure the effectiveness of safety improvement action. They can also remove subjectivity and variability in reporting. Deployment of such tools should also improve the reporting culture and consequently the level of reporting. Therefore, States are encouraged to expedite deployment of automatic safety data reporting/monitoring tools.
3.8.8 In order to use data from automated safety data reporting/ monitoring tools at State, FAB or European level, the event triggers for each type of occurrence need to be harmonised. It is proposed that a pan-European harmonisation project is conducted to ensure that data can be shared and aggregated.
Chapter 4: Operational En-route ANS Performance
PRR 2013 51 CHAPTER 4: OPERATIONAL EN-ROUTE ANS PERFORMANCE
Operational en-route ANS Performance 4
KEY POINTS KEY DATA 2013
Total en route ATFM delays in 2013 decreased by 17% compared to 2012. This improvement needs to be seen in the context of a 0.8% decrease of average daily IFR flights compared to last year.
The most constraining ACCs in 2013 were Nicosia, Warsaw, Barcelona, and the Canarias. Together they accounted for 28% of all en route ATFM delay and 6.9% of total flight hours controlled in Europe in 2013.
After the positive trend in previous years, horizontal en route flight efficiency in 2013 remained at a similar level as in 2012.
The gap between planned and actual trajectory differs significantly by State and suggests scope for improvement.
Close civil military cooperation and coordination is a crucial enabler to improve capacity and flight efficiency performance. A critical review of the application of the FUA concept could help to improve performance.
“Out of area” traffic introduces unpredictability in the network and should be improved through a better exchange of flight information with adjacent States to EUROCONTROL.
IFR flights controlled 9.45M -0.8%
Capacity: En route ATFM delays
2013 change vs.
2012
Total en route ATFM delay (min.)
5.0M -17%
Average en route ATFM delay per flight (min.)
0.53 -0.10
Flts. delayed > 15 min. en route (%)
1.3% -0.4%pt.
Environment: Flight inefficiency
2013 change vs.
2012
Avg. horizontal en route inefficiency (Flight Plan)
4.86% -0.01%pt.
Average horizontal en route inefficiency (Actual)
3.14% -0.06%pt.
4.1 Introduction 4.1.1 This chapter reviews operational en route ANS performance. Section 4.2 reviews Air
Traffic Flow Management (ATFM) delays originating from en route restrictions. Section 4.3 addresses en route flight efficiency. Section 4.4 deals with the flexible use of airspace. Section 4.8 addresses European ATFM performance.
4.2 En route ATFM delays 4.2.1 After the improved performance in 2012, en-route ATFM delays, for the
EUROCONTROL area, were further reduced by 17% from 0.63 to 0.53 minutes per flight in 2013. This improvement needs to be seen in the context of a 0.8% decrease of average daily IFR flights compared to the same period in 2012.
Figure 4-1: Average en route ATFM delay (1997-2013)
2.2
2.9
4.5
2.9
2.5
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Average en-route ATFM delay per flight
source: Network Manager
PRR 2013 CHAPTER 4: OPERATIONAL EN-ROUTE ANS PERFORMANCE
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4.2.2 ATC capacity and staffing related delays decreased continuously between 2010 and 2013 but remain by far the main driver of en route ATFM delays, followed by weather and “ATC Other” which comprises, inter alia, ATC industrial actions. Delay related to ATC industrial action increased again in 2013.
4.2.3 The number of flights affected by ATFM en route delays continued to decrease from 3.4% in 2012 to 2.7% in 2013. Overall, 1.3% of flights were delayed by more than 15 minutes, compared to 1.7% in 2012.
Figure 4-2: En route delay per flight by
classification
4.2.4 Figure 4-3 shows the monthly evolution of en route ATFM delays and IFR flights in Europe between 2010 and 2013. The seasonal pattern peaking in summer is clearly visible although less pronounced in 2012 and 2013.
Figure 4-3: Monthly evolution of en route ATFM delays (2010-2013)
LOCAL ATFM EN ROUTE PERFORMANCE PER ACC
4.2.5 In order to identify constraining ACCs, the following section evaluates performance at ACC level in line with the capacity objective set out in the ATM 2000+ Strategy “to provide sufficient capacity to accommodate demand in typical busy hour periods without imposing significant operational, economic or environmental penalties under normal conditions.”
4.2.6 While capacity constraints can occur from time to time, ACCs should not generate high delays on a regular basis. Figure 4-4 shows the delay performance in terms of the number of days with significant en route ATFM delays (>1 minute per flight). The selection threshold for the table in Figure 4-4 was set at greater than 30 days and the most constraining ACCs are analysed in more detail in the next sections of this chapter.
8.8%
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2010 2011 2012 2013
avg. daily IFR flights ('000)
per flight (m
in.)
Source: PRC Analysis; Network Manager
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Figure 4-4: Most en route ATFM constraining ACCs (overview)
4.2.7 The most constraining ACCs in 2013 were Nicosia, Warsaw, Barcelona, and the Canarias. Together the four most constraining ACCs accounted for 28% of total en route ATFM delay while controlling only 6.9% of the traffic.
4.2.8 Figure 4-5 shows the evolution of ATFM en route delays at the most constraining ACCs between 2009 and 2013. Additionally the delay classifications, as reported by the flow management positions (FMP), are provided and, in order to provide an indication of the traffic level, the number of controlled IFR flights is plotted as a blue line.
Figure 4-5: Most constraining ACCs in terms of en route ATFM (delay drivers)
4.2.9 The next section evaluates the most constraining ACCs in 2013 in more detail in order to provide a better understanding of what is affecting the performance during periods of highest delay.
DELIVERY OF PLANNED PERFORMANCE
4.2.10 Nicosia had more than three times as many days (198), where en route delay per flight exceeded 1 minute, than the second most constraining ACC (Warsaw with 62).
58% of en route delays were allocated by the Nicosia FMP as being due to ATC capacity and ATC staffing. Traffic levels increased by 2.9% on 2012 figures.
The Network Operations Plan (NOP) 2013-2015 contained capacity plans for Nicosia ACC.
Figure 4-6: Monthly ATFM en route delay in 2013 (Nicosia ACC)
Most constraining
ACCs in 2013
Days en
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ute d
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Nicosia 198 2.16 6.0% 600 59% 8% 0% 33% 12.0% 2.9% 0.5% 1.0%
Warsaw 62 0.54 1.5% 345 54% 4% 7% 35% 6.9% 1.5% 2.3% 2.4%
Barcelona 40 0.47 1.3% 348 84% 0% 14% 1% 6.9% ‐0.6% ‐2.3% 2.3%
Canarias 37 0.44 1.2% 116 66% 0% 31% 3% 2.3% ‐3.6% ‐3.0% 1.2%
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Monthly ATFM en-route delay and traffic (2013)
Source: PRU analysis
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Nicosia ACC planned for the operation of a 5th en route sector, and to deliver a capacity of 59 aircraft per hour during 2013. Providing such capacity would have satisfied the hourly traffic demand 98.7% of the time.
However, Nicosia ACC did not open the 5th en route sector, and the shortfall between promised capacity and delivered capacity resulted in significant delays for airspace users: averaging at 2.16 minutes per flight instead of 0.62 minutes forecasted delay for 2013.
The high incidence of delay allocated to “Other causes” was attributed to the failure of, or implementation of ATM equipment. In June, the back-up ATM system failed over a sustained period (15 days) increasing the existing capacity shortfall. From September, the new ATM system, TOPSKY, was implemented with additional capacity reductions, even though the NOP promised that this would not be the case.
It is difficult to validate the delay contribution “Other causes” since Nicosia ACC did not offer the planned maximum capacity (5 sectors) at any stage. It is highly likely that there would have been significant delays without the additional constraints due to equipment.
4.2.11 Warsaw ACC showed a continuous improvement over the past years and had 62 days where en route ATFM delay was greater than 1 minute per flight in 2013.
Following significant delays in Warsaw ACC in June, compounded by ongoing Flight Data Processing System failure from July, several ‘EU scenarios’ were applied to reduce network delay and to limit traffic demand within the Warsaw FIR.
Scenarios prevent traffic between certain departure and destinations pairs from filing through a specific portion of airspace. They are generally used to regulate traffic demand, by obliging certain traffic flows to fly around the specified area. Since the application of scenarios can involve additional track miles for re-routed traffic and an increase in traffic through adjacent FIRs, their use involves considerable coordination by the Network Manager and other stakeholders.
Figure 4-7: Monthly ATFM en route delay in 2013 (Warsaw ACC)
The Network Operation Plan 2013-2015 recognised that implementation of the new PEGASUS 21 ATM system would produce additional capacity constraints. Such constraints are expected to gradually improve until full capacity is available in May 2014.
It is evident that the widespread use of re-routing scenarios; through the efforts of adjacent ANSPs and the Network Manager, has contributed significant mitigation to capacity performance in the Warsaw FIR.
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4.2.12 Barcelona: Despite the continuous improvement over the past years, there were 40 days when Barcelona ACC produced en route ATFM delay above one minute per flight in 2013.
The Network Operations Plan 2103-2015 predicted problems for Barcelona ACC. The lack of capacity at weekends due to staff availability was highlighted as a significant concern.
Although at slightly higher traffic levels, the analysis of the delay figures shows a disproportionate amount of delay on weekends. Saturday, in particular shows more than twice the weekly average delay at 4.8% higher traffic levels.
The proposed measures to mitigate/resolve the capacity problems for 2013 included, inter alia, addressing staff availability at weekends and addressing aspects of civil military cooperation.
Figure 4-8: Monthly ATFM en route delay in 2013
(Barcelona ACC)
Figure 4-9: ATFM en route delay by weekday
(Barcelona ACC)
Since Spain did not provide any information on the effective use of civil military airspace structures for 2012, the PRC has no visibility on the potential for improvement in capacity performance through better civil military coordination. However, it is evident that capacity performance at weekends remains a significant problem for Barcelona ACC.
4.2.13 Canarias: In 2013, there were 37 days when Canarias ACC produced en route ATFM delay above one minute per flight.
The spike in en route weather related delays in March and December predominantly relate to weather and runway configurations at specific airports within the FIR, and not to en route weather phenomena such as CBs or Clear Air Turbulence.
Figure 4-10: Monthly ATFM en route delay in 2013
(Canarias ACC)
In December the start of the holiday traffic on 21st December resulted in over 13 000 minutes of delay alone. This represents almost 30% of the monthly delay in one day. On
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Source: PRU analysis
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the South West axis, the lack of available route options through Portugal and the Canarias can significantly aggravate capacity constraints.
CHANGES IN CONSTRAINING ACCS (2009-2013)
4.2.14 Figure 4-11 shows the evolution of performance at ACCs that were considered constraining ACCs for at least one year between 2009 and 2013.
Figure 4-11: Changes in constraining ACCs (2009-2013)
4.2.15 Although the decline in traffic must be considered as a contributing factor, with the exception of Nicosia ACC, there has been a general improvement in capacity performance over the last 5 years.
4.3 En route Flight Efficiency 4.3.1 This section evaluates en route flight efficiency inside Pan-European airspace. Flight
efficiency in terminal control areas (TMA) which also includes airborne holdings is addressed in the evaluation of ANS-related performance at airports in Chapter 5.
4.3.2 Flight efficiency has a horizontal (distance) and a vertical (altitude) component. The focus of this section is on the horizontal component, which, in general, is considered to be of higher economic and environmental importance than the vertical component across Europe as a whole [Ref. 22].
4.3.3 The measure is based on the comparison of a flight trajectory length with the corresponding achieved distance.
4.3.4 En route flight efficiency is affected by a large number of factors including:
route network design (existing route network); route availability (utilisation of civil military structures); flight planning capabilities (use of software, repetitive flight planning); user preferences (time, cost, fuel); tactical ATC routings; and, special events such as severe weather, ATC strikes.
METHODOLOGICAL NOTES
4.3.5 In this report, the same methodology as for the SES Performance Scheme is used, with two different measurements according to the type of trajectory:
The first one, KEP, compares the length of the en route section of the last filed flight plan with the corresponding achieved distance (the letter P stands for “plan”).
Horizontal en route flight efficiency
Horizontal en route flight efficiency compares the length of flight trajectories (L) to the corresponding “achieved” distance (H). The achieved distance apportions the Great Circle Distance between two points within the European airspace (reference area). For the vast majority of flights, the origin and destination coincide with the airports. If the origin/ destination airport is located outside of European airspace, the entry/exit point into the reference area is used for the calculation.
ACC 2009 2010 2011 2012 2013Nicosia 193 262 160 169 198 196Warsaw 225 158 75 77 62 119Madrid 96 163 168 11 10 90Langen 74 143 124 71 14 85Barcelona 4 167 134 63 40 82Wien 170 148 20 16 20 75Rhein 78 167 47 5 11 62Canarias 46 79 86 25 37 55Marseille 5 129 53 33 25 49Zagreb 70 89 49 19 5 46Athinai+Macedonia 54 44 94 7 5 41Brest 6 141 10 9 18 37Zurich 83 61 15 5 5 34
Nr. Of days with en route ATFM dly. >1min. Avg. 2009-2013
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Similarly, KEA compares the length of the en route section of the actual trajectory with the corresponding achieved distance (the letter A stands for “actual”).
4.3.6 The “En route” section excludes the 40 nautical miles circles around the airports (terminal areas).
4.3.7 The indicator is calculated as the ratio of the two sums (length of trajectories and achieved distances), over all flights considered.
The methodology enables to better quantify between local inefficiency (deviations between entry and exit point within a respective airspace such as FAB, ANSP, ACC) and the contribution to the network (deviation from GCD between origin and destination airport).
The full methodology is described in more detail in the meta data which is available online [Ref. 23].
4.3.8 “KEP” and “KEA” are a measure of environmental performance since they relate to the amount of fuel which has to be uploaded in accordance with the filed flight plan (KEP) and the amount of fuel actually burnt (KEA).
4.3.9 Although both relate to fuel, Figure 4-12 shows clearly how they refer to two separate domains: planning and operations.
4.3.10 KEP compares the filed flight plan to the great circle. While the filed flight plan is the ultimate output of the planning process, it would be possible to measure the inefficiency at intermediate stages by considering the shortest possible route on the route network and the shortest available route for the specific flight.
Figure 4-12: Factors affecting flight efficiency
4.3.11 The shortest possible route is constrained by the design of the route network. Historically, the route network was structured in reference to aircraft navigational limitations and to enable air traffic control to provide separation with the tools available. As technology for both aircraft and ATC has improved, the need for such a rigid en route structure has diminished, to the extent that free route airspace would now be possible throughout the entire area. This would have positive effects both on the KEP and the KEA.
4.3.12 The shortest available route is specific to a flight and takes into account the additional constraints introduced by the Route Availability Document (RAD) and Conditional Routes (CDRs). The RAD has the effect of modifying the route network available to specific flows of traffic, while CDRs have the effect of modifying the route network available at specific times. Both reduce the set of available routes.
4.3.13 Differences between the shortest available route and the route in the filed flight plan can arise because the airspace user might not be aware that the route is available, or is aware but chooses an alternative route for operational or business reasons.
4.3.14 The KEA, on the other hand, reflects the actual environmental performance. In this case a distinction can be made between two separate components: “separation” and “fragmentation”.
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4.3.15 “Separation” relates to the need to safely manage the flow of traffic and has to be considered as a hard constraint. It is important to bear in mind that the level of inefficiencies cannot be reduced to zero.
4.3.16 “Fragmentation” refers to operational inefficiencies created by non-homogenous processes and systems and airspace and sector design due to non-operational factors.
4.3.17 It is recognised that KEA and KEP are proxies for fuel efficiency as the most fuel efficient route depends on wind. However, the wind optimal route might not necessarily correspond to the choice of the airspace users because they might use different measures, such as total cost (which would be dependent on the airspace users).
4.3.18 Moreover, the information needed to calculate these alternatives (wind optimal, total costs, etc.) is not currently available. The airspace users would have to either provide detailed information or agree on a standard method for the calculation of the route “values”.
4.3.19 KEP and KEA, on the other hand, have the advantage of relying on a well-defined and standard measure (distance).
DATA COMPLETENESS AND QUALITY
4.3.20 The computation of the indicator is based on the profile generated through the Correlated Position Reports (CPR). CPR data is processed radar track data containing records for controlled flights in European airspace.
4.3.21 As already pointed out in previous editions of PRR [Ref. 2], there is scope for further improving the CPR data in terms of geographical scope and quality.
4.3.22 Figure 4-13 shows that CPR data is presently not provided by all States to EUROCONTROL’s Enhanced Tactical Flow Management System (ETFMS).
Figure 4-13: Availability of CPR data (Oct. 2013)
4.3.23 There is work in progress to extend CPR coverage to those States currently not providing this data directly into the ETFMS. Since October 2013, the Ukraine has started to transfer CPR data. It is important to ensure that plans are implemented as foreseen which will further improve network predictability and the accuracy of flow management predictions.
4.3.24 Also in terms of data quality there is scope for improvement and harmonisation. Depending on the State, the current radar update rates range from one position per three
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minutes to several positions per minute31. For States subject to the Single European Sky Performance scheme, the required harmonisation to provide data at an update rate of 30 seconds as of 2015 will greatly enhance data quality [Ref. 17] and all EUROCONTROL States providing data to the ETFMS should be encouraged to also provide radar data at this update rate.
EUROPEAN WIDE EN ROUTE FLIGHT EFFICIENCY
4.3.25 Figure 4-14 shows the horizontal en route flight inefficiency for the actual trajectory (KEA) and the filed flight plan (KEP). An “inefficiency” of 5% means for instance that the extra distance over 1000NM was 50NM.
4.3.26 The comparison of the annual values shows an improvement for the filed flight plan (KEP) and the actual trajectory (KEA) between 2009 and 2013.
Figure 4-14: European wide horizontal en route flight efficiency (2011-2013)
4.3.27 Although virtually no improvement is observed at KEP level in 2013, the implementation of a large number of airspace design projects over the past years resulted in an improvement of en route flight efficiency (see Figure 4-14).
4.3.28 At European level, the observed level of inefficiency in 2013 in the filed flight plans was 4.86% with the actual trajectory being 1.7% better than the filed plans (3.14%).
4.3.29 The monthly time series on the right hand side of Figure 4-14 shows the impact of ATC industrial action (September & November 2012, June & October 2013) when airspace users had to circumnavigate the affected airspace with a negative effect on flight efficiency.
4.3.30 Over the past years, a number of initiatives and concepts (see also next section on Free Route Airspace Implementation) contributed to improving en route flight efficiency and the projects included in the European Route Network Improvement Plan (ERNIP) [Ref. 24], developed by the Network Manager in response to the requirements laid out in Commission Regulation (EC) N°677/2011[Ref. 25], are expected to further improve en route flight efficiency.
4.3.31 In view of the numerous factors (see §4.3.4) and complexities involved and with traffic levels growing again it will become more and more challenging to improve flight efficiency and will require the joint effort of all stakeholders coordinated by the Network Manager.
31 The larger the interval, the less accurate is the computation of the flight trajectory.
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FREE ROUTE AIRSPACE (FRA) IMPLEMENTATION
4.3.32 The implementation of “Free route airspace (FRA) initiatives” aims at enhancing en route flight efficiency with subsequent benefits for airspace users in terms of time and fuel and a reduction of CO2 emissions for the environment.
4.3.33 FRA initiatives have been successfully implemented in a number of States and FABs over the past years (Ireland (2009), Portugal (2009), DK/SE FAB (2011)). FRA implementation is also progressing in areas of high traffic density such as Maastricht and Karlsruhe (2012).
Free Route Airspace (FRA) Concept
Free route airspace (FRA) is a key development with a view to the implementation of shorter routes and more efficient use of the European airspace.
FRA refers to a specific portion of airspace within which airspace users may freely plan their routes between an entry point and an exit point without reference to the fixed Air Traffic Services (ATS) route network. Within this airspace, flights remain at all times subject to air traffic control and to any overriding airspace restrictions.
The aim of the FRA Concept Document is to provide a consistent and harmonised framework for the application of FRA across Europe in order to ensure a co-ordinated approach.
4.3.34 Coordinated by the European Network Manager, 23 of the 64 European ACCs had already implemented various steps of Free Route Operations by the end of 2013. Preparation and validation for H24 Free Route Operations in Hungary and Spain (Madrid ACC Santiago & Asturias sectors), Night Free Route Operations in Italy, Slovenia and Moldova, joint Night Free Route Operations in Bulgaria and Romania as well as further expansion of Free Route Airspace Maastricht and Karlsruhe/ FRAMaK are ongoing for implementation before summer 2014.
4.3.35 The resulting benefits are clearly visible in Figure 4-15. The left map shows the filed flight plans for a typical weekday in May 2013. The higher degree of flexibility for flight planning is clearly visible as the flight plan trajectories are much more scattered in those areas where FRA has been implemented (red arrows). The brown areas in Figure 4-15 represent restricted/segregated airspace (see also next section).
Map data: Google
Figure 4-15: Flight efficiency improvements from free route implementation
4.3.36 The right side of Figure 4-15 shows the level of inefficiency (%) of the actual trajectories (KEA). The efficiency differences though the implementation of free route airspace are clearly visible in Scandinavia and by comparing the UK with Ireland or Portugal with Spain.
4.3.37 Figure 4-16 shows the differences between KEP and KEA by FAB and State. The figure reveals significant differences between the last filed flight plan (KEP) and the actual flown trajectory (KEA).
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4.3.38 For those States where FRA is already implemented, the difference between KEP and KEA is relatively small, and both values tend to be low. At FAB level, the largest gap of almost 3% between KEP and KEA can be observed for FABEC in 2013 which suggests significant scope for improvement.
Figure 4-16: Differences between KEP and KEA by State and FABs (2013)
4.3.39 Route availability and the flexible use of airspace (see next section) appear to be a contributing factor to the significant differences between the KEP and the KEA.
4.3.40 Figure 4-17 provides the example of the Zurich to Amsterdam route for May 2013 which illustrates the aforementioned issues.
4.3.41 The trajectories of the filed flight plans (used for computing KEP) are shown as dark blue lines whereas the actual trajectories (used for computing KEA) are superimposed in purple.
4.3.42 Almost all flights are planned to fly around the restricted/ segregated areas shown in green (KEP). However, the actual trajectories (KEA) then cut through the special use airspace. The difference between KEP and KEA for this example is 11% which is considerable.
Figure 4-17: Flight plans and actual trajectories Zurich - Amsterdam
4.3.43 There is clearly scope for improvement in order to reduce the gap between planned and actual flight trajectory. Additionally to the initiatives to improve flight efficiency, improved planning closer to the actual trajectory would also increase the level of predictability for all players involved with a positive impact on capacity and resource utilisation.
4.3.44 More research is required to better determine the contributing factors (flight planning, awareness of route availability, civil-military coordination, etc.). One of the prerequisites is however to collect better data on the activation of special use airspace (see also Section
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Ukraine
UK‐IrelandFAB
SW FAB FABEC BLUE MED FAB(Europe)
FAB CE (Europe) BalticFAB
DANUBEFAB
NEFAB DK‐SEFAB
Other
Inefficiency (%)
Actual trajectory (KEA) Last filed flight plan (KEP)
Source: NM; PRC analysis
(Lines refer to FAB average)
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4.4) and on route availability when the flight plan was submitted by airspace users (shortest route).
4.3.45 At European system level, the en route flight inefficiency related to the actual trajectory (KEA) was 3.14% in 2013 which corresponds to a total additional distance of 195 million kilometres.
4.3.46 The Figure 4-18 shows the breakdown of the total KEA related inefficiencies by FAB. FABEC accounts for 42% of the total additional distance (KEA) in 2013, followed by FAB SW (16%), Blue Med FAB (13%), and FAB UK-Ireland (12%).
4.3.47 It is interesting to note that the contribution of States towards inefficiencies within FABs can vary significantly, particularly for FAB SW and FAB UK-Ireland (see Figure 4-16).
Figure 4-18: Share of total additional distance (KEA) by FAB (2013)
4.3.48 The improvement of European flight efficiency and the optimisation of the European route network is, by definition, a Pan-European issue which requires a holistic approach carefully coordinated by the Network Manager. Uncoordinated, local initiatives may not deliver the desired objective, especially if the airspace is comparatively small and a large proportion of the observed inefficiency is due to the interface with adjacent States or FABs.
4.3.49 Figure 4-19 shows the average additional distance per flight and the percentage of en route additional distance by FAB for the actual trajectories (KEA) in 2013.
4.3.50 The level of inefficiency is expressed as a percentage and depends not only on the additional distance but also the average length of the achieved distance.
4.3.51 On average, the additional distance per flight in 2013 was greatest in FAB SW (20km), followed by FABEC (16.5km), Blue MED FAB, and UK-Ireland FAB. Figure 4-19: Additional distance per flight (KEA) and KPI
by FAB (2013)
4.3.52 While the route structure is presently the single most constraining factor, the observed inefficiencies are the result of complex interactions between airspace users, ANSPs and the European Network Manager. More research is needed to better understand the exact drivers in order to identify and formulate strategies for future improvements.
BLUE MED FAB
(Europe)13%
Baltic FAB1%
DANUBE FAB3%
DK‐SE FAB2%
FAB CE7%
FABEC42%
NEFAB1%
OTHER3%
SW FAB16%
UK‐Ireland FAB12%
% of total additional distance (KEA) by FAB in 2013
Source: PRU analysis
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
0
2
4
6
8
10
12
14
16
18
20
SW FAB
FABEC
BLU
E MED
FAB
(Europe)
UK‐Ireland
FAB
FAB CE
DANUBE FA
B
DK‐SE FA
B
NEFAB
Baltic FA
BAdditional distance per flight (km)
Source: PRU analysis
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4.4 Flexible use of Airspace
4.4.1 States have an obligation to meet national security and operational training requirements, as well as meeting the needs of civil airspace users. To meet their national security and training requirements, whilst ensuring the safety of other airspace users, it is occasionally necessary to restrict or segregate airspace for exclusive use (see grey information box).
4.4.2 To avoid unnecessary constraints in available capacity and flight efficiency, for both civil and military users, airspace restrictions should be based on actual use, and should be cancelled when not required.
4.4.3 As a high-level indication of the link between the allocation of the areas and their actual use, EUROCONTROL Member States were asked to submit information on the number of allocated hours and the number of hours actually used.
Restricted/segregated areas
The map below shows the location of some of the restricted/segregated areas in the ECAC area.
The map simply shows the geographical locations of published segregated and restricted areas. The impact assessment of each area depends upon many factors including, but not limited to, position, altitude, period of allocation, demand of General Air Traffic (GAT) at time of allocation, weather, suitability for military operations and training, re-routing options; distance from base for Operational Air Traffic (OAT) traffic; precise restriction or segregation criteria, etc.
4.4.4 Figure 4-20 compares the number of hours that airspace was actually used for the activities requiring restriction or segregation and the number of hours that restrictions or segregations were applied for 2013.
State (2013) Used /
Allocated State (2013)
Used / Allocated
State (2013) Used /
Allocated Albania 75% FYROM 76% Slovakia 14% Belgium 47% Italy 42% Sweden 100% Czech Republic 35% Netherlands 83% UK 33% Denmark 95% Norway 46% Finland 22% Romania 49%
Source: States
Figure 4-20: Ratio of time airspace was used vs. allocated (pre-tactically)
4.4.5 Data is not provided for all States: either because they did not provide the requested data or because, they consider that the restriction or segregation of specific areas has no impact either on the available ATC capacity, or on the route options available for general air traffic.
4.4.6 Pre-tactical restrictions were notified the day before operations, in accordance with the Airspace Use Plan, NOTAM, or as published in the national Aeronautical Information Publication (AIP).
4.4.7 Tactical restrictions are defined as being notified after publication of the Airspace Use Plan. They were communicated to the Network Manager, and hence to airspace users, using an Updated Airspace Use Plan (UUP) or by other means.
4.4.8 Figure 4-20 gives a high-level indication of latent capacity, and flight efficiency opportunities, which could potentially benefit airspace users.
4.4.9 Making the latent capacity and route options available in a predictable manner, when
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needed by airspace users, will improve the network planning of available capacity and flight efficiency to meet the airspace users’ requirements, thus providing a better air navigation service.
4.4.10 With a number of States showing the airspace is actually used less than 50% of the time that it is reserved for exclusive use, there is clearly scope for improvement.
REVIEWING THE PERFORMANCE OF STATES IN APPLYING THE FUA CONCEPT
4.4.11 It is evident from both the number of restricted/segregated areas in Europe (see grey box on page 63) and from the potential impact of such areas on available ATC capacity and route options for general air traffic (Figure 4-20), that close civil military cooperation and coordination is crucial to meeting the needs of all airspace users.
4.4.12 The Flexible Use of Airspace concept (FUA), and Regulation 2150/2005 [Ref. 26] for SES States, gives a clear framework for how civil and military stakeholders can work together to meet the requirements of both civil and military airspace users.
4.4.13 Every year, originally, as part of the Local Single Sky ImPlementation (LSSIP) process, Member States submit an annual FUA report which monitors their compliance with the FUA legislation. In essence: Does the Member State perform the tasks described in the FUA Regulation?
4.4.14 However, in the PRC’s opinion, improving ATM performance requires a more in-depth review of the FUA process within the individual Member States. It requires a review of the national principles, priorities and procedures that apply to civil military cooperation and coordination at each level of airspace management.
4.4.15 It requires a review of the consistency between national objectives and available resources for both civil and military stakeholders and a review of the monitoring process used to ensure that the national objectives for meeting the requirements for both civil and military airspace users are met.
4.5 Network Impact of “Out of Area Traffic” 4.5.1 “Out-of-Area Traffic” is
traffic that lands within or transits European airspace but which originates from airports outside the EUROCONTROL Member States.
4.5.2 Figure 4-21 shows the out of area traffic by region of origin for 2013.
4.5.3 In 2013, 88.8% of the traffic was within EUROCONTROL member States. The remaining 11.2% was “out of area traffic”.
Figure 4-21: Out of area traffic by region (2013)
4.5.4 The Network Manager, and local ATM stakeholders manage the ATM network by identifying safety concerns presented by imbalances in demand and capacity and applying ATFM regulations to cooperative airspace users’ to maintain the traffic flow within acceptable limits.
4.5.5 The Network Manager uses a window of predictability of 15 minutes for regulated traffic (between 5 minutes before and 10 minutes after); for non-regulated traffic within the
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EUR region it is 30 minutes (from 15 minutes before to 15 minutes after). For non-EUR flights the ICAO requirement is only to notify of changes to the Estimated Off-Block Time (EOBT) of more than 30 minutes.
4.5.6 Participating airspace users, such as airlines, can accept ATFM regulations in the form of take-off restrictions and level-capping, or can amend their flight plans and re-route to avoid congested areas. In general, the Network Manager can only regulate aircraft departing from within the EUROCONTROL area, or at airports where the ATS unit has an agreement with EUROCONTROL or the Network Manager.
CASE STUDY FOR IMPACT OF “OUT OF AREA TRAFFIC”
4.5.7 Figure 4-22 shows the expected traffic demand at 08h00 UTC on 22nd June 2013 (bars) and the actual traffic (red line) for an ATC sector in the periphery of the Network area.
4.5.8 Although traffic was predicted to be above the threshold value of 45 aircraft per hour, it was below 10% and therefore no regulations were applied. However, from 09h40 until 11h00 there was a rolling hourly entry rate above the monitoring value, with a peak hourly value of 63 (18 above monitoring threshold value) between 10h00 and 11h00.
Figure 4-22: Expected/actual traffic in a peripheral ATC sector
4.5.9 An investigation, conducted into the reasons for the over-deliveries, revealed:
Of the 97 flights that entered the sector between 0900 and 1100;
Thirty three (33) flights entered the sector outside the window of predictability used by the Network Manager for slot allocation (between 5 minutes before and 10 minutes after the calculated take-off time CTOT).
Of these 33 aircraft, 31 departed from non Eurocontrol member states;
6 of these aircraft entered the sector more than 30 minutes later than expected without updated flight plans being received by the Network Manager.
SAFETY CONSIDERATIONS OF “OUT OF AREA TRAFFIC”
4.5.10 Over-deliveries can lead to sector overloads, where the amount of aircraft within a particular airspace is greater than the declared amount which can be handled safely. This creates additional workload for the ATCOs concerned and could potentially lead to an increased risk of incident than would normally be the case.
4.5.11 The Network Manager with local ATFM stakeholders manages safety by monitoring the expected traffic demand against available ATC capacity. The more stable the picture regarding expected traffic demand, the greater the ability to effectively manage the network balancing the safety requirements against the objective for an expeditious flow of air traffic.
4.5.12 ATFM regulations, since they apply to departing flights, take time to have effect. If flights have already departed, they cannot be subjected to further ATFM regulations. Instead, tactical re-routings or holding must be applied by ATC personnel to prevent aircraft from entering congested areas.
0
10
20
30
40
50
60
70
07h
00
07h
20
07h
40
08h
00
08h
20
08h
40
09h
00
09h
20
09h
40
10h
00
10h
20
10h
40
11h
00
11h
20
11h
40
12h
00
Expected (08h00 UTC on 22nd June 2013)and actual traffic in a peripheral ATC sector
Only flight plan information available
Departure message received but not tracked in Eurocontro area
Airborne and tracked in Eurocontrol area
Actual Traffic Source: NM
The bars refer to the expected traffic level at 08h00
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CAPACITY CONSIDERATIONS FOR “OUT OF AREA TRAFFIC”
4.5.13 When the local ANSP, and the Network Manager, is unable to predict the expected traffic demand, within a certain tolerance, it is usual to apply buffers to protect against the likelihood of over-deliveries, or potential sector overloads.
4.5.14 Instead of an ATC sector making available the maximum declared capacity, it is more probable that a reduced capacity will be offered, which, in case of a significant fluctuation in expected traffic would insure that traffic levels remain within acceptable limits for the ATCOs.
IMPACT OF “OUT-OF AREA TRAFFIC” ON ATFM REGULATIONS.
4.5.15 One result of this situation is that declared available capacity levels are permanently significantly lower than what can be safely handled, and that this buffer capacity is generally wasted.
4.5.16 The EUROCONTROL area will experience increased ATFM regulations as greater capacity buffers are applied. In addition, since the “Out-of Area Traffic” cannot be regulated, the additional regulations will only be applied to traffic departing airports inside the EUROCONTROL area, so cooperating airlines are penalised twice.
IMPROVING THE PREDICTABILITY OF “OUT OF AREA TRAFFIC” IN THE ATM NETWORK
4.5.17 In recent years, the FAA and EUROCONTROL have improved the automatic exchange of flight information regarding aircraft on the North Atlantic Tracks (NAT) system. Whilst the Network Manager is still unable to influence the departure time of these aircraft, the flight profile is much more predictable for the assessment of capacity demand imbalance.
4.5.18 This increased predictability enables the Network Manager, and ANSPs, to reduce the buffers in available capacity and to limit the amount of regulation on ‘European’ traffic.
4.5.19 Exchange of demand data between the Russian Federation and EUROCONTROL on the day before operations, enables the Network Manager to present updated demand profiles for ANSPs which can be considered when the Member States are deciding how best to manage the airspace for both civil and military use to provide the optimum benefit for all airspace users.
4.5.20 From January 2014, the Russian Federation has implemented an exchange of First Sector Activation (FSA) messages with EUROCONTROL, resulting in departure messages for 95% of all traffic from the Russian Federation. In exchange, EUROCONTROL is sending Flight Update Messages (FUM) for all flights entering the Russian Federation from the EUROCONTROL area.
FURTHER IMPROVEMENTS
4.5.21 The improvement in the predictability of traffic, either by improving the predictability of departure times (ETOT +/- 15mins) or by improving the predictability of flight information (earlier activation within the network and improved adherence to approved flight plans) will deliver improved capacity (reduced buffers) at zero cost, and will reduce the perception that ‘European’ airlines are being unfairly treated when compared to those operating as out of area traffic.
4.5.22 Improving departure time predictability will involve agreements with either the adjacent ICAO regions or by ICAO globally.
4.5.23 Improving the predictability of flight information can be resolved through discussion and agreements with adjacent States to EUROCONTROL.
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4.7 Impact of weather on en route ATM 4.7.1 Convective weather is the critical weather phenomena affecting en route capacity and
flight efficiency. Clear air turbulence, thunderstorms and line squalls can be hazardous to the safe operation of flight and frequently lead to tactical deviations from the planned flight trajectory.
4.7.2 Operationally, hazardous weather phenomena can affect safety, capacity and flight efficiency because aircraft need to deviate from their planned trajectory.
A safety incident could be triggered by an unplanned and uncoordinated deviation in flight path. Increases in ATCO workload as a result of requests for deviations from flight path compounded with high traffic volume / complexity can also elevate the risk of safety incidents occurring.
4.7.3 Convective weather can have a significant impact on capacity by obliging ATC to ensure additional spacing between aircraft, for example suspension of Reduced Vertical Separation Minima (RVSM) (either for a specific flight or between a band of flight levels); or the potential loss of lateral separation due to the inability of aircraft to adhere to the confines of pre-determined ATS routes.
4.7.4 Flight-efficiency is obviously affected as aircraft circumnavigate areas of adverse weather. In extreme cases, such tactical deviation may involve diversion to an alternate destination if fuel becomes an issue.
4.7.5 In 2013, 14.3% of the total en route ATFM delays were due to weather. Figure 4-23 shows the top ten ACCs for weather delay in 2013: Rhein, Marseille, London AC, Paris, Barcelona, Langen, Munich, Reims, Vienna, and the Canarias (see also §4.2.13 on page 55 for more information on the Canarias). Together those 10 ACCs accounted for 73.9% of all weather-related en route ATFM delays in 2013.
Figure 4-23: Top 10 ACCs for en route weather-related en route ATFM delay (2013)
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4.7.6 For all ACCs but the Canarias32 listed in Figure 4-23, the days when ATFM regulations were applied due to adverse weather between June and August 2013 were compared to days with forecasts of significant weather phenomena (SIGMET).
4.7.7 It can be observed that Flow Management Positions (FMPs) are classifying ATFM regulations as being due to en route weather for a notable number of days when no SIGMET was issued for the relevant airspace (see Figure 4-24).
Figure 4-24: Number of days with regulations
vs. number of days with SIGMETs (2013)
4.7.8 In the absence of a SIGMET, it is difficult to quantify how the en route capacity was affected by en route weather.
4.7.9 For those States that are applying incentive schemes for capacity performance in RP2, it will be important to ensure that capacity constraints are correctly identified and classified. The charging regulation permits weather related delays to be excluded from an incentive scheme, which could result in erroneous delay classifications leading to unwarranted financial penalties or bonuses for ANSPs.
IMPLEMENTATION OF REGULATIONS REGARDING WEATHER
4.7.10 According to the Network Manager, and various ANSPs (FMPs), the prevailing methodology for managing weather related capacity shortfalls is to apply ATFM regulations whenever aircraft start requesting to deviate from their flight path. In essence, the request for ATFM regulations is a reaction to pilots’ requests on the frequency.
4.7.11 The regulations are applied by individual FMPs, with little or no regional or network coordination to consider the constraints and or options in surrounding areas.
4.7.12 There is no evidence to show that the reduction in declared en route capacity is based on objective rather than subjective criteria with the result that it is seen as being haphazard.
4.7.13 The reactive nature of the regulations also means that the Network Manager is limited in the ability to mitigate the short-term impact – aircraft are already in flight towards the constrained sector.
PLANNED IMPROVEMENTS
4.7.14 The Network Manager is working with various stakeholders, including MET providers, aircraft operators, airports and ATM personnel to implement a process for anticipating and mitigating the adverse impact of weather on the network.
4.7.15 The process involves determining the probability and impact of forecasted weather phenomena, ATM disruption risk assessment. Using the statistical data as a reference, (civil and military) ATM personnel can begin a dialogue on various scenarios to mitigate the adverse impact expected. Such discussions can take place at national/regional and FAB level and or can involve the Network Manager.
4.7.16 As forecasted information becomes more robust, there can be discussions with aircraft operators about likely scenarios to maintain safety, reduce delay, and improve flight efficiency. Such scenarios will be based on the statistical data available.
32 The majority of weather-related ATFM delay in the Canarias occurred in winter. For more information on weather-related en route ATFM delays generated by Canarias ACC see § 4.2.13 on page 52.
ACC
(JUNE‐
AUGUST)
Nr. of
weather
delay days
(WxD)
Days with WxD
on which no
SIGMET was
issued
% of WxD on
days with no
SIGMET
Rhein 31 14 18.7%
Marseille 22 1 0.8%
London AC 8 2 24.0%
Paris 22 2 0.1%
Barcelona 27 2 7.6%
Langen 16 4 30.8%
Munchen 12 2 1.3%
Reims 23 2 3.9%
Wien 22 12 21.9%
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4.7.17 Scenarios involving ATFM regulations and/or airspace management can start to be deployed in advance of aircraft actually requesting deviation from flight paths. Such anticipatory actions will improve safety as it will prevent ATCOs from being overloaded.
4.7.18 Similarly, as forecasted information becomes more robust, it can be anticipated that ATFM scenarios can be updated or terminated with increased certainty.
PERFORMANCE MONITORING
4.7.19 The PRC supports efforts to anticipate and mitigate adverse weather throughout the network. The PRC supports the collaborative mechanism being discussed which will provide relevant parties with the best information available on which to base their decisions.
4.7.20 The PRC recognises that implementing scenarios including ATFM regulations, in advance of hazardous weather phenomena, could result in occasional instances where there were weather delays but no actual adverse weather. Further research could help to identify opportunities for future improvement
4.7.21 In view of the importance of correct delay classification, in identifying and improving capacity performance, (as explained in 4.7.9) the PRC invites that consideration should be given to enabling an independent verification procedure for delay classification.
4.7.22 Alternatively, perhaps consideration should be given to creating a budget for weather delay, managed by the Network Manager? Such an arrangement could be used to encourage the ANSPs to consider the network perspective and to implement the process being developed by the Network Manager and other stakeholders?
4.8 European ATFM performance (Network level) 4.8.1 Over the past few years, the role of the network function in Europe has been strengthened
by the SES legislation. This evolution foresees a more proactive role in Air Traffic Flow Management (ATFM), ATC capacity enhancement, route development, and the support to the deployment of technological improvements across the ATM network for the Network Manager.
4.8.2 EUROCONTROL has been entrusted by the European Commission with the SES Network functions. These functions are laid out in Commission Regulation (EC) N°677/2011 [Ref.25] and include, inter alia, the tasks foreseen for the Central Unit for Air Traffic Flow Management (ATFM).
4.8.3 The ATFM function in Europe is jointly executed by local ATFM units and the Network Manager (central unit for ATFM). ATFM regulations are put in place by the Network Manager to protect en route sectors or airport from receiving more traffic than ATC can safely handle upon request of the local Flow Management Positions (FMP).
4.8.4 Figure 4-25 shows the evolution of the three high-level indicators presently in use to monitor the performance of the ATFM function at system level.
4.8.5 A number of initiatives have been promoting ATFM slot adherence in order to improve traffic predictability [Ref. 27]. Local ATC at the respective departure airport has a joint responsibility with aircraft operators
ATFM performance assessment
Regulation (EC) No 255/2010 [Ref. 28] of 25 March 2010 laying down common rules on air traffic flow management aims at optimising the available capacity of the European air traffic management network (EATMN) and enhance air traffic flow management (ATFM) processes by establishing requirements for ATFM. It requires, inter alia, the central unit for ATFM to produce annual reports indicating the quality of the ATFM in the airspace of the Regulation including causes of ATFM measures, impact of measures and adherence to ATFM measures.
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to make sure that the aircraft depart within the allocated ATFM window in order to avoid over-deliveries which occur when more aircraft than planned enter a protected sector (see also ATFM slot adherence at airports in Chapter 5).
4.8.6 The corresponding indicator in Figure 4-25 shows that the share of take-offs outside the ATFM slot tolerance window (-5min +10 min) continuously improved between 2003 and 2013.
4.8.7 The share of regulated hours with over deliveries in Europe remains more or less constant at 10%. Future efforts should aim at reducing the level as much as possible to further increase system confidence which can in turn free latent capacity kept as a reserve to protect controllers from excessive workload.
Figure 4-25: ATFM performance (network
indicators)
4.8.8 The share of avoidable ATFM regulations (i.e. there was not excess demand) increased slightly between 2011 and 2013. The ability for improvement is largely linked to predictability and accuracy of the relevant information when the decision to call for an ATFM regulation is taken (i.e. several hours before the anticipated capacity shortfall).
4.8.9 Enhanced traffic projections through A-CDM implementation at more airports (see also Chapter 5), enhanced data quality (see also § 4.3.20 ff.) but also improvements in aviation metrological capabilities could help improving performance in this area.
4.9 Conclusions
4.9.1 En route ATFM delays in 2013 decreased for the third consecutive year. Overall, en route ATFM delays decreased by 17% from 0.63 to 0.53 minutes per flight in 2013 which is the lowest level ever recorded. It must also be stated that the level of traffic was less than in the two previous years.
4.9.2 While most ACCs in Europe provided sufficient capacity, there were four ACCs in 2013 with more than 30 days at delay levels above one minute per flight: Nicosia (198), Warsaw (62), Barcelona (40), and the Canarias (37). These four ‘constraining ACCs’ accounted for 28% of total en route ATFM delay in 2013 whilst handling just 6.9% of the traffic.
4.9.3 Investigation into the specific classification of ATFM delay highlighted inconsistency in how delays are assigned both in terms of the causal factor and the appropriate location. Such inconsistency is detrimental to performance improvement and there is a risk that this could lead to a financial impact on ANSPs due to incentive schemes. The PRC intends to do further investigation and reporting on this topic.
4.9.4 Although the amount of en route ATFM delay is at the lowest level ever recorded, in view of the exponential relationship between capacity constraints and delay, it is vital to plan and implement adequate capacity in advance of the expected growth in traffic.
4.9.5 After the positive trend in previous years, horizontal en route flight efficiency in 2013 remained at a similar level as in 2012. At European level, the observed level of en route flight inefficiency in 2013 was 4.86% for the filed flight plans with the actual trajectory being 1.7% better than the filed plans (3.14%). The gap between planned and actual
0.0%
2.5%
5.0%
7.5%
10.0%
12.5%
15.0%
17.5%
20.0%
22.5%
25.0%
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
% of take offs outside ATFM slot tolerance window
% regulated hrs. with actual demand/capacity >110%(excess demand)
% of ATFM delays due to avoidable regulations (noexcess demand)
Source: Network Manager
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trajectory differs significantly by State which suggests scope for improvement. Additionally to the initiatives to improve flight efficiency, improved planning closer to the actual trajectory would improve predictability and also reduce required fuel load and thence reduce costs.
4.9.6 By the end of 2013, 23 of the 64 ACCs had implemented various steps of Free Route Operations. Clear benefits can be observed in areas where free route airspace has been implemented.
4.9.7 Clear benefits can already be observed in areas where free route airspace has already been implemented.
4.9.8 While route availability and changes in military activity appear to be contributing factors to the observed gap between filed and actual flight trajectory, more research is required to better understand all the contributing factors (flight planning, awareness of route availability, civil-military coordination, etc.). This requires however improvements in data collections for planned and actual airspace restrictions and planned and actual route availability.
4.9.9 Close civil military cooperation and coordination is a crucial enabler to improve capacity and flight efficiency performance. A critical review of the application of the Flexible Use of Airspace (FUA) concept could help improving performance.
4.9.10 The evaluation of the impact of “out of area” traffic on ATM performance illustrated that “out of area” traffic introduces unpredictability in the network which can be improved through closer coordination and cooperation with States outside the EUROCONTROL area.
Chapter 5: Operational ANS Performance at Airports
PRR 2013 72 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
Operational ANS Performance at Airports 5
KEY POINTS KEY DATA 2013
In 2013, IFR traffic decreased by 1.5% at the top 30 European airports.
Performance of the management of the arrival flow remained relatively stable for both Arrival ATFM Delay and Additional ASMA Time in 2013.
Similarly, outbound traffic performance was stable in 2013, with no significant variation of average ATC Pre-departure Delay and Additional Taxi-out Time.
PRU initiated some research on new performance indicators (including taxi-in, resilience and environment). This research needs to be pursued based on the current state-of-the-art and in close coordination with the stakeholders.
The airports, through the States, should be encouraged to implement A-CDM, including Departure Planning Information (DPI) exchange with Network Operations at congested airports
Higher level of details, comparability, consistency and lower ambiguity are expected as key benefits of receiving high-quality data from non-SES airports.
European average33 2013
(compared to 201233)
change vs. 2012
Average daily movements (dep.+ arr.)
20 044 (20 355)
-1.5%
Avg. Airport Arrival ATFM Delay (min./arr.)
0.8 (0.9)
-0.1
Avg. Additional ASMA Time (min./arr.)
2.2 (2.1)
+0.1
Avg. ATC Pre-departure Delay (min./dep.)
0.6 (0.5)
+0.1
Avg. Additional Taxi-out Time (min./dep.)
3.7 (3.7)
5.1 Introduction 5.1.1 This chapter reports on operational ANS performance at airports based on the framework
depicted in Figure 5-1 and detailed in Annex VI. The evaluation of ANS-related performance at airports is divided in the analysis of the:
(1) inbound traffic flow (i.e. Airport Arrival ATFM Delay and Additional ASMA Time); (2) outbound traffic flow (i.e. ATC Pre-Departure Delay and Additional Taxi-Out Time);
and, (3) capacity-demand balancing (i.e. Peak Declared Capacity and Service Rates).
5.1.2 The results of the respective indicators should be evaluated together and not considered in isolation. Existing interdependencies between the flow measures applied at the airport are targeted at addressing the efficiency of operations and managing the possible imbalance between capacity and demand.
5.1.3 The analyses presented in this chapter focus on the top 30 airports33 in terms of IFR movements (calculated over 2013). Section 5.2 addresses both the inbound and outbound flow. Section 5.3 looks at both capacity-demand balancing and the factors affecting the observed performance. The global performance of the main European airports is analysed in Section 5.4. The analyses of this chapter are complemented by a listing of the performance indicators for all European airports in Annex VII. Following up on previous PRRs, initial findings from key topics are reported in Section 5.5. Lastly, conclusions are drawn in Section 5.6.
33 This edition of the PRR refers to the top 30 European airports in terms of IFR movements in 2013 across the EUROCONTROL Member States excluding Turkey. As a result, a direct comparison with previous years is not possible. The European averages presented in this chapter and the associated references to previous years have been re-calculated accordingly. The PRC is in contact with the Turkish Authorities regarding the provision of airport data to EUROCONTROL.
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Figure 5-1: Framework for Operational ANS Performance Framework at airports
5.2 ANS-related operational performance at European airports 5.2.1 The performance observed at airports is the result of complex interactions between a
considerable number of stakeholders (airlines, airport operator, slot coordinator, ATC provider, Network Manager, etc.) and a number of points should be borne in mind for the interpretation of the results in the next sections of this chapter:
Although the focus of this report is on ANS performance, a clear cut allocation between ANS and non-ANS related causes is often difficult. While at airports, ANS is often not the root cause for a capacity/demand imbalance (weather, deliberate decision in the airport scheduling phase, etc.), the way the situation is handled impacts on the distribution of delay (air vs. ground) and thus on costs to airspace users.
Not all delay is to be seen as negative. A certain level of delay may be necessary and even desirable if a system is to be run efficiently without underutilisation of available resources.
Some of the indicators measure the difference between the actual situation and an ideal (uncongested or unachievable) situation where each aircraft would not be subject to any constraints. Due to desired (capacity related) or necessary (safety related) constraints at system level, it is neither possible nor desirable to reduce inefficiencies to zero.
MANAGEMENT OF THE ARRIVAL FLOW
5.2.2 When a mismatch between demand and airport arrival capacity is anticipated, the actions taken and the flow measures applied depend on:
(1) the time the imbalance is known before it is envisaged to take place; (2) the severity of the anticipated capacity shortfall; and, (3) the level of uncertainty (accuracy of weather or traffic forecast) associated with the
anticipated imbalance.
5.2.3 Small imbalances between demand and capacity are usually managed tactically by local holdings, re-vectoring or speed control which may also serve as a short term buffer to ensure a constant reservoir of aircraft to maximise runway throughput. In case of a more severe imbalance, the local/national Flow Management Position (FMP) coordinates with the Network Manager the application of an ATFM regulation which will hold aircraft bound for the capacity constrained airport at their origin airports.
Airport (Declared) Capacity
Airport ATFM delays
Terminal holdings(ASMA)
Airport scheduling(utilisation
ratio)
Management of arrival flows
Actual throughput
Air Traffic Management
Airportresilience
En‐route phase(see Chapter 4)
Weather & Environmental restrictions
Taxi‐outLocal ATCTurn‐
around
Reac‐tionary
Air Traffic Management
En‐route phase(see Chapter 4)
Contribution to Network performance
Inbound Flow Management Capacity‐Demand Balancing Outbound Flow
Management
Contribution to Network performance
Performance Indicators
• ATFM slot adherence
• Airport arrival ATFM delays
• ASMA additional time• Additional taxi‐in time
• Exogenous Factors:– Weather– Environment
• Endogenous Factors–Peak declared capacity–Peak Service Rate–Airport resilience
• Local ATC delays• Additional taxi‐out time
• ATFM slot adherence
Enabling Concepts
• A‐CDM implementa‐tion status
• Arrival Manager (AMAN)•Risk Mgnt• Surface operations
• A‐CDM• Departure Manager (DMAN)• Surface operations
• A‐CDM• Departure Manager (DMAN)•Risk Mgnt•Surface operations
• A‐CDM implementa‐tionstatus;
Management of departure
flows
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
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5.2.4 A general trade-off needs to be made and finding the right balance can be challenging. For example, keeping an aircraft at the gate saves fuel, however, if it is held and capacity goes unused the cost of the extra delay may exceed the fuel cost considerably and may impose ripple effects on the airspace user’s operations (reactionary delay, break of aircraft rotations and interconnectivity).
5.2.5 Based on Figure 5-1, the next two sections evaluate both aspects concerning the management of the inbound traffic flow in form of Airport Arrival ATFM Delay and Additional ASMA Time at the top 30 airports.
5.2.6 Figure 5-2 shows the Airport Arrival ATFM Delay at the top 30 airports by delay category with a comparison to 2012. The delay categories comprise ATC capacity and staffing, other ATC-related causes, weather, and other delay causes resulting in an ATFM regulation. Amongst these categories, weather represents by far the main reason for Airport Arrival ATFM Delay, followed by capacity/staffing related issues.
Figure 5-2: Airport arrival ATFM delay (ordered by traffic volume)
5.2.7 Since 2010, there has been a steady decrease of the European average, from 1.5 minutes per arrival in 2010 to 0.8 minute in 2013. Compared to 2012 (0.9 minutes per arrival), this is still a relative decrease of -15%.
5.2.8 The European average tends to mask the variation of Airport Arrival ATFM Delay and its underlying delay causes amongst European airports. Zurich and London Heathrow remain close to two and half minutes per arrival (despite different delay causes), followed by Geneva with 2 minutes. Year on year, a substantial improvement was observed at Frankfurt (-0.8), Munich (-0.7), Lisbon (-0.5) and Helsinki (-0.4), whilst delay increased at Geneva airport (+0.8).
5.2.9 The Additional Arrival Sequencing and Metering Area (ASMA) Time aims at monitoring the (in)efficiency of inbound traffic operations, in particular airborne holding, metering and sequencing of arrivals.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copen
hagen
(CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin (TXL)
Palma (PMI)
Dublin
(DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athen
s (ATH
)
Other (all other codes)
Weather (codes W,D)
ATC other (codes IRTV)
Cap./ staffing (codes CSG)
2012
ATFM airport arrival delays [min/arr]
1.0
1.5
1.2
0.9
0.8
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2009
2010
2011
2012
2013
Source : NM; PRC
European average (TOP30)
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
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5.2.10 The indicator for this year’s PRR has been calculated with data directly supplied by airport operators34. The respective values for 2012 were recomputed to benefit from the higher accuracy of the airport data flow35.
5.2.11 However, the indicator was calculated with a lower level of accuracy when some airport data was missing (e.g. RWY and stand information was missing for Oslo and Nice, and CPR was missing for Warsaw Airport). The airports for which this occurred are highlighted in orange in Figure 5-3 which shows the Additional ASMA Time for the top 30 European airports.
5.2.12 On average, the Additional ASMA Time remained stable in 2013 (2.1 minutes per arrival) compared to 2012 (2.2 minutes per arrival) with a slight decrease of 6 seconds (-1.1%).
Additional ASMA Time This indicator is based on the “ATMAP performance framework”, developed in consultation with some of the major ANSPs, airlines and airport operators in Europe. ASMA (Arrival Sequencing and Metering Area) is the airspace within a radius of 40NM around an airport. The Additional ASMA Time is a proxy for the level of (in)efficiency (e.g. average arrival runway queuing time) of the inbound traffic flow during times when the airport is congested. The computation of the indicator is based on three consecutive steps:
determination of the average unimpeded time between entering the 40 NM radius and landing for groups of similar inbound flights (same ASMA entry sector, arrival runway, and aircraft class);
calculation of the average additional time for each group of flights by comparing the average actual to the average Unimpeded ASMA Time; and,
the calculation of the average Additional ASMA Time for the airport which is the weighted average of the average Additional ASMA Times of all groups of similar inbound flights.
The full methodology is described in more detail in the meta data which is available online [Ref. 23].
5.2.13 Within the European context, London Heathrow remained the outlier for Additional ASMA Time (9.2 minutes per arrival). The local scheduling process, economic attractiveness of the airport slots, and operational procedures facilitate a significant systemic level of delay.
Figure 5-3: Additional ASMA time (2012-2013)
5.2.14 Zurich (3.3 minutes per arrival, +6% compared to 2012), Frankfurt (2.9, -15%), London Gatwick (2.7, +7%), Nice (2.5. +3%) accumulate Additional ASMA Time higher than the European average. Frankfurt Airport is also the airport that experienced the greatest performance improvement compared to 2012 (-0.5 minutes per arrival) due to the operations of the new runway.
34 As of 2011, airports subject to monitoring within the Single European Sky (SES) Performance scheme are obliged to provide basic operational data for each flight including runway and gate use [Ref. 4].
35 c.f. footnote 33.
0
1
2
3
4
5
6
7
8
9
10
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copenhagen (CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin
(TXL)
Palma (PMI)
Dublin (DUB)
Manchester (MAN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athens (ATH
)
Additional ASMA time (2013)
Additional ASMA time (2012)
European Average 2012
European Average 2013
ASM
A tim
e [m
in/arr.]
2.2 2.1
0.0
0.5
1.0
1.5
2.0
2.5
3.0
2012
2013
Source : NM, PRC
European Average
TOP 30
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
76
MANAGEMENT OF THE DEPARTURE FLOW
5.2.15 Although the ability of ANS in reducing total time inefficiencies is limited when runway capacities are constraining departures, the goal should be to minimise inefficiencies of the departure process (e.g. apron, taxiway, and threshold queuing) by keeping aircraft longer at the stand. In that respect, the optimisation of the departure queue management aims to maximise the runway throughput while keeping the additional fuel burn to the necessary minimum. The efficiency of this balancing act can be measured by the local ATC Pre-Departure Delay and the Additional Taxi-Out Time.
5.2.16 Local ATC Pre-Departure Delay results from ATC constraints at the departure airport and is currently reported by aircraft operators to CODA, through Code 89 (see grey information box).
5.2.17 Acknowledging the limitations of Code 89 in terms of taxonomy and use, the European Airport Punctuality Network (EANP) introduced the delay sub-codes which are already in use at some airports such as Dusseldorf and London Luton. Moreover, some airports are setting up a delay clearing process to improve the accuracy of the reporting and consistent allocation of the Code 89 delay causes.
5.2.18 The reporting of additional time stamps, i.e. Target Start-Up Time (TSAT) and Target Off-Block Time (TOBT), within the A-CDM programme appears to be a promising complementary data source to improve the monitoring of local ATC Pre-Departure Delay in the medium term. With a view to the legal requirement to monitor ATC departure delay in the second reference period of the SES performance scheme (2015-2019), further research is needed to evaluate the use and practicality of alternative data sources (including A-CDM data) for improving the accuracy of the indicator.
Local ATC Pre-Departure Delay This indicator is based on the “ATMAP performance framework” [Ref. 29], developed in consultation with some of the major ANSPs, airlines and airport operators in Europe. Departure delays due to local ATC are a proxy for ATC induced delays at the departure stand as a result of demand/capacity imbalances in the manoeuvring area and/or terminal airspace. This delay is measured by using the IATA delay code 89 which, besides delays caused by ATC constraints, also includes delays due to late push-back approval and other reasons. One advantage of using this data is the universal application of the IATA standard delay codes across European aviation. Current limitations of using the IATA delay code 89 are:
it is currently not possible to filter out delays due to late push-back approval generated by an apron management unit which is not under ANS provider’s responsibility; and,
the data accuracy varies across airports depending on procedures which are in place to control the quality of the assignment of code 89.
The implementation of A-CDM at airports would significantly help to improve data quality and to measure delays due to local ATC constraints with higher accuracy.
5.2.19 As shown in Figure 5-4, the average local ATC departure delay - based on Code 89 data - remained more or less constant over the past five years for the top 30 airports, ranging around 0.6 minute per departure. It marginally increased from 0.5 minutes per departure in 2012 to 0.6 min./dep. in 2013.
5.2.20 However, local results vary significantly for a third of the presented airports. Local ATC departure delay is below 1 minute per departure for the majority of the top 30 airports, except Rome Fiumicino (2.5 min./dep. +138% compared to 2012), Zurich (1.6, +21%), Frankfurt (1.3, +10%), and Amsterdam (1.3). Rome Fiumicino experienced the greatest deterioration in 2013, due to the closure of the main runway 25 from the end of March to mid-June 2013.
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Figure 5-4: Local ATC Pre-departure delay
5.2.21 The Additional Taxi-out Time aims at evaluating the level of inefficiencies in the taxi out phase (i.e. apron, taxiway operations, runway queuing, de-icing operations, etc.). The analysis refers to the period between the time when the aircraft leaves the stand (actual off block time) and the take-off time. The additional time is measured as the average additional time beyond an unimpeded reference time.
5.2.22 Different from previous PRRs where the computations were based entirely on data from the Network Manager, the indicator in this edition of PRR has been computed with data directly supplied by airport operators this year. However, the indicator was calculated with a lower level of accuracy when some airport data was missing (e.g. RWY and stand information was missing for Oslo and Nice airports). The airports for which this occurred are highlighted in orange in Figure 5-5 below.
5.2.23 The enhanced data (i.e. airport data flow) allows calculating the indicator at a higher level of granularity which in turn improves the level of accuracy (c.f. Section 5.5.15f).
Additional Taxi out time This indicator is based on the “ATMAP performance framework”, developed in consultation with some of the major ANSPs, airlines and airport operators in Europe. The computation of the indicator is based on three consecutive steps:
determination of the unimpeded time between stand and take-off, for each combination of runway and group of stands;
calculation of the average additional time for each group by comparing the average actual to the average unimpeded taxi-out time; and,
the calculation of the average Additional Taxi-out Time for the airport which is the weighted average of the average Additional Taxi-out Times of all groups of similar outbound flights.
The full methodology is described in more detail in the meta data which is available online [Ref. 23].
5.2.24 Figure 5-5 shows the Additional Taxi-out Times for each of the top 30 airports in 2013. With an average over the top 30 airports of 3.7 minutes per departure, the Additional Taxi-out Time remained unchanged in 2013 compared to the previous year.
5.2.25 Additional Taxi-out Time is relatively high on average at London Heathrow and Rome Fiumicino, with 8.3 and 6.6 minutes per departure respectively. An improvement has been observed at several airports since 2012, the most significant being at Rome Fiumicino (-0.6 minutes per departure) and Madrid (-0.5). In contrast, average additional taxi-out time deteriorated at Brussels (+1 minute per departure), Warsaw (+0.8) and Vienna (+0.7).
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Paris (CDG)
Frankfurt (FRA)
London (LHR)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LGW)
Vienna (VIE)
Copenhagen
(CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Geneva (GVA)
Berlin (TXL)
Palma (PMI)
Dublin (DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athens (ATH
)
2013 2012
European Average 2012 European Average 2013
Local A
TC departure delay [min/dep.]
0.6
0.6
0.6
0.5 0.6
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
2009
2010
2011
2012
2013
Source : NM, PRC
European
average (top30)
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
78
Figure 5-5: Additional Taxi-out Times (2012-2013)
ENABLERS FOR MANAGING THE DEPARTURE FLOW
5.2.26 Airport Collaborative Decision Making (A-CDM) is generally considered to be a key enabler to manage push-back and the taxi-out phase in order to optimise the departure sequence at the runway. One of the fundamentals of the CDM Milestone Approach is the real-time sharing of milestones such as Target Off-block Time (TOBT) and Target Start-up Approval Time (TSAT), thus creating “common situation awareness” among involved stakeholders and improved utilisation of resources.
5.2.27 Figure 5-5 shows the status of A-CDM implementation in Europe in April 2013 together with the plans for the next two years.
Figure 5-6: Status of A-CDM implementation in Europe
5.2.28 Airports where A-CDM has been fully implemented now include Munich, Brussels, Paris-Charles de Gaulle, Frankfurt, London-Heathrow, Helsinki-Vantaa, Düsseldorf and, most recently, Switzerland’s primary hub, Zurich. Collectively, A-CDM implementation at these airports has yielded significant benefits for all partners. At Brussels airport, the average reduction of taxi-out time is 3 minutes just after A-CDM implementation, what resulted in a saving of 5 400 tonnes of fuel, i.e. 17 022 tonnes of CO2, 22 tonnes of NOx
0
1
2
3
4
5
6
7
8
9
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copen
hagen
(CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin
(TXL)
Palma (PMI)
Dublin
(DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athen
s (ATH
)
Additional taxi‐out time (2013)
Additional Taxi‐out time (2012)
European Average 2012
European Average 2013
Taxi‐out time [m
in/dep.]
3.7 3.7
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
201
2
201
3
Source : NM; PRC
Europeanaverage (TOP30))
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
79
and 2.7M€ profit per year. Similar benefits were experienced at Munich airport, with taxi time reduced by 10% and 2.65M€ profit per year in fuel saving. At Charles-de-Gaulle, the average taxi-out time reduced by 2 minutes, and by 4 minutes in advance conditions [Ref 30].
5.2.29 Further 25 airports across Europe are currently in the process of implementing A-CDM either locally or fully. A-CDM deployment is being facilitated by the Network Manager, with a target of 20 airports being fully implemented by the end of 2014.
5.2.30 The A-CDM “milestone approach” focuses on improving the accuracy of time predictions. Increased predictability of departure movements helps – amongst others – to increase ATFM slot adherence see 5.2.34 below.
5.2.31 At fully implemented A-CDM airports, the data is not only used locally but also made available to the Network Manager (NM). The better integration of airports into the ATFM network in turn leads to a higher accuracy of the traffic situation and hence a better utilisation of the entire network capacity.
AIRPORT INTEGRATION INTO THE ATM NETWORK
5.2.32 There is a close link between operational airport performance and ANS network performance. A trial to enhance airport integration into the network started at the beginning of the IATA Winter Scheduling Season for 2013 on 27th October 2013, and will run until the end of the Winter Season which finishes on the 29th March 2014. The trial is foreseen to mainly cover adverse weather events at the airports involved where a potential impact on capacity is predicted based upon the available information and weather forecasts. If it is foreseen at Day (D - 1) that the predicted adverse weather may impact upon the airports’ capacity or their ability to deliver a full schedule, then NM will ask the airports concerned to submit the requested information to NM, so that tactical flow management for these airports can be optimised. The airports taking part to the trial are Amsterdam, Dusseldorf, Frankfurt, Geneva, London Heathrow, Munich, Paris CDG and Zurich.
5.2.33 Punctuality, and flight plan adherence to tactical planning at airports in particular, is also a key issue to be considered in order to minimise both delay and the potential changes in flow management on the day of operations. Although the percentage of ATFM regulated flights remains relatively small (see Figure 5-7), the higher the number of regulated departing aircraft outside the assigned ATFM slot window, the less accurate the predicted traffic and associated down-stream ATFM measures. On the other side, local ANS performance can be enhanced through a tighter integration of airports and the network through higher predictability of operational demand.
5.2.34 The monitoring of ATFM slot adherence is required by Regulation 255/2010 [Ref. 28] as a pre-requisite to fine-tune traffic predictions in en-route airspace and at the departure and destination airports. Under its Article 11, regulation 255/2010 requires the ATS units to provide the information regarding non-compliance to slot adherence, for these airports where non-adherence equals or exceeds 20% of regulated departures, as well as mitigation action plans. In application to regulation 255/2010, the NM monitors ATFM slot adherence on a monthly basis.
ATFM slot adherence ATFM departure slots are allocated centrally by the Network Manager to hold aircraft on the ground when there is an envisaged imbalance between demand and capacity at airports or en route. An ATFM slot tolerance window [-5 min, +10 min] is available to ATC to sequence departures. ATC at the departure airport has a joint responsibility with aircraft operators to ensure that flights depart within the allocated ATFM window in order to optimise traffic flow rates. ATFM slot adherence measures the share of take-offs outside the allocated ATFM window.
5.2.35 The share of ATFM regulated departures outside the ATFM slot tolerance window [-5 min, +10 min] at the top 30 airports is depicted in Figure 5-7. On average, 12.8% of the ATFM regulated flights from these airports took off outside their ATFM slot window in
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
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2013. The share of flights outside the allocated ATFM slot window varies widely and ranges from 20% at Paris Orly to 3% at Oslo across the European airports.
Figure 5-7: ATFM slot adherence at airports (2013)
5.2.36 Though the A-CDM airports are represented in Figure 5-7, no succinct conclusion on the impact of A-CDM on slot adherence can be drawn. The good performance of slot adherence at Munich airport (7% non-adherence, i.e 93% adherence) is claimed to come from A-CDM implementation. Similarly, while most of A-CDM airports have a slot non-adherence record below the European average, Paris Charles-de-Gaulle and London Heathrow remain well above it.
5.2.37 For Paris Charles-de-Gaulle, for instance, Figure 5-7 shows that 8% (grey bar) of the total outbound traffic was regulated in 2013 (i.e. 18 823 regulated departures out of 239 236 take-offs). Amongst these 8% ATFM regulated departures, 18% (red line) were outside the ATFM slot tolerance window. It is paramount to consider traffic volume when talking about the ATFM slot adherence indicator. Indeed, 16% of regulated flights depart outside their ATFM slot window at Dublin airport, compared to 9% at Frankfurt. However, these 16% at Dublin represent 1 011 regulated departures whilst the 9% at Frankfurt count for 1 697 regulated departures.
5.3 Demand-Capacity Balancing at Airports and affecting Factors PEAK DECLARED CAPACITY & PEAK SERVICE RATE
5.3.1 To be economically viable, an airport needs to secure a adequate return on investment. Under-utilised and latent capacity due to a lack of demand leads to a lack of profit. On the other hand, when capacity is below demand, this demand is either not accommodated, which represents a loss of business opportunity, or delayed, which leads to increased operational costs. There is therefore a trade-off to be achieved between capacity and demand that leads to an optimum profit.
5.3.2 The airport coordination process supports the achievement of that trade-off several months before operations. All the airports out of the top 30 considered in this chapter are coordinated, except Hamburg which is scheduled-facilitated.
5.3.3 For those airports close to saturation, the peak service rate is a valid proxy for operational capacity, and the efficiency with which the demand-capacity balance is achieved. In some cases, the difference between the service rate and the declared airport capacity reveals some potential to refine the declared capacity and/or increase slot scheduling efficiency.
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
20%
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copenhagen (CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin (TXL)
Palma (PMI)
Dublin
(DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athen
s (ATH
)
shar
e o
f AT
FM
reg
ula
ted
fligh
ts d
epa
rtin
g
ou
tsid
e th
e A
TF
M s
lot t
ole
ranc
e w
indo
w
% of ATFM regulated dep
artures
Source: Network Manager
PRR 2013 CHAPTER 5: OPERATIONAL ANS PERFORMANCE - AIRPORTS
81
5.3.4 When service rate is greater than declared capacity, this indicates that the airport is normally saturated. A certain capacity buffer might be used by some airports in order to cope with demand unpredictability at the time of operations, without generating delay. This shows the complexity of the declared capacity and the slot scheduling processes.
5.3.5 A comparison between the peak declared capacity and the peak service rate at the top 30 European airports is depicted in Figure 5-8 for arrivals and in Figure 5-9 for departures.
Airport peak service rate The peak service rate (or peak throughput) is an approximation of the operational airport capacity in ideal conditions. It is based on the cumulative distribution of the number of movements per hour, on a rolling basis of 5 minutes. The measure has however limitations when the peak service rate is lower than the peak airport declared capacity, in which case it is necessary to determine whether a variation in peak service rate is driven by a change in demand or by a change in operational airport capacity.
Figure 5-8: Peak declared arrival capacity and service rate
5.3.6 With the exception of Paris Charles de Gaulle, Frankfurt, London Heathrow, and Zurich, all airports had a peak service rate below their declared arrival capacity. This is most likely due to the decrease of traffic demand over the past two years (-2.7% in 2012 compared to 2011, and -1.5% in 2013 compared to 2012), resulting in latent capacity. The demand deficit can be as great as 18 arrivals and 19 departures per hour at Copenhagen airport.
5.3.7 Frankfurt airport accommodated 4 arrivals and 4 departures per hour more than declared. To a lesser extent, there was similar behaviour at Heathrow with 3 additional departures per hour. Paris Charles de Gaulle airport accommodated 3 additional arrivals per hour than declared, but there were 4 additional slots available for departures during peak times.
5.3.8 London Stansted and Zurich airport decreased their peak declared capacity respectively by 3 arrivals and 4 departures per hour for Stansted and 3 departures per hour for Zurich. However, this does not impact negatively the capacity-demand balancing process as the peak service rate remains below this value.
62 53 44 68 58 48 54 38 36 30 48 52 34 34 42 48 33 25 30 33 29 33 48 40 26 33 28 30 27 220
10
20
30
40
50
60
70
80
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copenhagen (CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin (TXL)
Palma (PMI)
Dublin (DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athens (ATH
)
arrivals per hour
Peak declared capacity 2013 [arrivals/hour]
Peak service rate 2013 [arrivals/hour]
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Peak service rate ‐ Changes 2013 vs 2012 [arrivals/hour]
Peak declared capacity ‐ Changes 2013 vs 2012 [arrivals/hour]
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Figure 5-9: Peak declared departure capacity and service rate
WEATHER
5.3.9 Airport throughput is usually affected by meteorological conditions. As weather conditions deteriorate, separation requirements generally increase and runway throughput is reduced. The impact of weather (visibility, wind, convective weather, etc.) on operations at an airport and hence on ANS performance can vary significantly by airport and depends on a number of factors such as, inter alia, ATM and airport equipment (instrument approach system, radar, etc.), runway configurations (wind conditions), and approved rules and procedures.
5.3.10 The analysis of metrological conditions provides an indication of how weather affects system performance and which airports are most impacted by weather condition.
5.3.11 On average, less “critical weather” days were recorded in 2013 compared to 2012, probably because of the relatively mild months of November and December 2013.
ATMAP weather algorithm [Ref. 31]. The ATMAP weather algorithm is applied to METAR information with the following objectives:
Measure weather conditions consistently across European airports;
Provide a factual consolidated measure of the intensity and duration of weather phenomena which could make ANS and airside airport operations more complex or difficult;
Classify days of operations in two categories (good and bad weather) for high level performance analyses.
5.3.12 The ATMAP weather algorithm [Ref. 31] is the structural analysis of METARs aimed at identifying “bad weather” days. METARs typically contain data on temperature, dew point, wind speed and direction, precipitation, cloud cover and heights, visibility, and barometric pressure. The analysis in Figure 5-10 shows the share of days in each weather category at the top 30 airports based on the analysis of METAR data.
67 53 46 74 58 52 60 36 41 34 50 55 42 36 42 44 36 36 30 33 31 37 42 30 26 31 26 30 27 220
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Frankfurt (FRA)
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Amsterdam
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Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copenhagen (CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin
(TXL)
Palma (PMI)
Dublin
(DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
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burg (HAM)
Athens (ATH
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Peak declared capacity 2013 [departures/hour]
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Peak service rate ‐ Changes 2013 vs 2012 [departures/hour]
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Figure 5-10: Weather conditions at major European airports
5.3.13 While the aggregated high-level evaluation of METAR data provides some first insights, the simplified approach has also shortcomings as it does not reflect the meteorological situation throughout the day of operation. Moreover, METARs may not fully capture weather phenomena in the vicinity of the airport affecting ANS-related performance.
5.4 Overall ANS performance 5.4.1 In previous sections the performance indicators relating to arrival and departure flow
management were reported in isolation for the top 30 European airports. Figure 5-11 provides a consolidated view of the four indicators per airport in order to enable a more balanced evaluation and to visualise possible trade-offs (airport ATFM arrival delays vs. ASMA additional time, etc.).
5.4.2 Figure 5-11 depicts the magnitude of these four indicators for the top 30 airports. Overall, the management of the arrival traffic flow appears to be more efficient than the departure flow. In particular, arrival flow constraints are tackled locally during the inbound phase and not significantly traded off with Arrival ATFM Delays.
Figure 5-11: Overall Airport ANS Performance at the top 30 airports (2013)
5.4.3 A clear outlier with substantial additional time on the arrival and departure flows is
0%
10%
20%
30%
40%
50%
60%
Paris (CDG)
Frankfurt (FRA)
London (LH
R)
Amsterdam
(AMS)
Munich (MUC)
Madrid (MAD)
Rome (FCO)
Barcelona (BCN)
Zurich (ZRH)
London (LG
W)
Vienna (VIE)
Copen
hagen
(CPH)
Oslo (OSL)
Paris (ORY)
Stockholm
(ARN)
Brussels (BRU)
Dusseldorf (DUS)
Gen
eva (GVA)
Berlin (TXL)
Palma (PMI)
Dublin
(DUB)
Manchester (M
AN)
Helsinki (HEL)
Milan (MXP)
Lisbon (LIS)
London (STN)
Warsaw (WAW)
Nice (NCE)
Ham
burg (HAM)
Athen
s (ATH
)
% of days
Weather conditions at top 30 airports [2012/2013]
CB, thunderstorms (critical phenomena) Freezing conditions Wind Visibility & Ceiling 2012 (total)
Source: PRC analysis; METAR
024681012
Paris (CDG)Frankfurt (FRA)London (LHR)Amsterdam (AMS)Munich (MUC)Madrid (MAD)Rome (FCO)Barcelona (BCN)Zurich (ZRH)London (LGW)Vienna (VIE)Copenhagen (CPH)Oslo (OSL)Paris (ORY)Stockholm (ARN)Brussels (BRU)Dusseldorf (DUS)Geneva (GVA)Berlin (TXL)Palma (PMI)Dublin (DUB)Manchester (MAN)Helsinki (HEL)Milan (MXP)Lisbon (LIS)London (STN)Warsaw (WAW)Nice (NCE)Hamburg (HAM)Athens (ATH)
ATFM delay [min/arr] Additional ASMA Time [min/arr]
0 2 4 6 8 10 12
ATC pre‐departure delay [min/dep] Additional Taxi out time [min/dep]
Arrivals Departures
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London Heathrow. However, the observed performance is not due to poor ANS performance but due to deliberate decisions on average delay taken during the airport scheduling phase. In view of the valuable airport slots, the airport is geared towards maximising throughput according to available capacity on the day of operations.
5.4.4 In the absence of a supporting en route function, the necessary continuous supply of aircraft ensures a high capacity utilisation but also generates congestion with high average holdings and substantial additional fuel burn.
5.4.5 A high density airport operating close to capacity limits is also more susceptible to service disruptions such as weather (see Figure 5-2) which potentially result in major delays and cancellations when there is a mismatch between scheduled demand and available capacity. The susceptibility of operations has gained considerable interest and an initial approach to addressing the resilience of operational ANS Performance at airports is presented in the following section.
5.5 Topic Briefings 5.5.1 This section reports on on-going developments with a view to specific ANS at airport-
related performance topics. These topics are presented to start a dialogue on the underlying modelling and implications for a refinement of the performance framework in the future. This edition of the PRR addresses the following topics:
(i) taxi-in; (ii) resilience; (iii) conversion of capacity indicators into environmental metrics; and, (iv) need for airport data flow at non-SES airports.
TAXI-IN
5.5.2 Figure 5-1 presents an “en-route-to-en-route” perspective of the airport airside operations. In particular, the ground trajectory of a flight can be seen as the extension of the flight trajectory to include the whole airside operations. From that perspective, the efficiency of the taxi-in process is a logical extension of the current set of indicators.
5.5.3 This section investigates Additional Taxi-in Time. Taxiing to an allocated stand can be influenced by many factors. In a non-exhaustive way, these factors include:
physical layout of the airside and its complexity (e.g. distance between the runways and the stands, runway and taxiway crossings, type of runway exits, wingspan limitation on taxiways);
airlines’ procedures and pilots’ practices to vacate a runway (e.g. ‘save brakes’ and ‘passenger comfort policies, ‘brake-to-vacate’ procedures);
aircraft type, that drives arrival runway occupancy time and might constraints the taxiway as well as the stand used;
weather conditions; taxi-routeing length and complexity (e.g. runway crossing operations); stand allocation efficiency and related capacity limitations; and, the executive body for ground traffic management (e.g. ATC, Airport, private
service).
5.5.4 Amongst these factors, Additional Taxi-in Time is mainly influenced by runway crossing36, stand capacity, and, to a minor extent, weather conditions and pilots’ behaviour, in their choice of runway exit in particular.
36 For instance, at Paris Charles-de-Gaulle, landing aircraft have to wait between landing and departure runways until the departure runway is cleared. In peak departure time, arriving aircraft can wait several minutes before being authorized to cross the departure runway.
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5.5.5 In a preliminary study, the same concept and methodology than Additional Taxi-out Time was used to investigate requirements on the modelling of the taxi-in process and a future taxi-in indicator. Consequently,
the concept of taxi-in time refers to the period between the time the aircraft touches down the approached runway and the time it is in-block on its allocated stand. Likewise taxi-out time, taxi-in time includes runway occupancy time; and,
the Additional Taxi-in Time is measured as the average additional time beyond an unimpeded reference time experienced in non-congestion operational conditions.
5.5.6 Figure 5-12 shows the taxi-in time distribution together with the distribution of arrivals below the preliminary unimpeded taxi-in time (in green). The 25th percentile of the distribution shows a taxi-in time of 4 minutes whilst the 75th percentile shows that 75% of the arrivals had a taxi-in time smaller or equal to 6 minutes.
5.5.7 Figure 5-13 shows the monthly distribution of average taxi-in time (in red) with unimpeded taxi-in time (in green). For this preliminary study, it can be seen that Additional Taxi-in Time varies between 1’26” in April 2012 and 1’41” in February 2013.
Figure 5-12: Taxi-in time distribution and preliminary unimpeded taxi-in time
Figure 5-13: Additional taxi-in time – monthly distribution
5.5.8 The principal feasibility of the approach is demonstrated on the basis of the existing airport data flow (i.e. associated time stamps for landing, take-off and in-block time stamps). Accordingly, the reporting and monitoring of taxi-in performance could be established without additional costs to the reporting entities. Further research is needed to conceptualise and validate the modelling of the taxi-in process (e.g. limiting factors, stand occupancy, runway/stand grouping).
RESILIENCE
5.5.9 Throughout the recent years, resilience has gained considerable interest in the air navigation community. This is emphasised by regulatory requirements for ANSPs to ensure high-reliable and continuity of service provision to airspace users [Ref. 32]. In particular, the relationship between operational risk management, the identification of thresholds for nominal and non-nominal conditions, and operational performance levels is subject of regular discussions. While it is recognised that the resilience approach is applicable to air navigation37 in general, this section applies the underlying concept to the airport environment.
5.5.10 As mentioned above several factors may disrupt nominal conditions of operations at airports. As soon as ANS operates in non-nominal conditions, a certain time is required to recover and normal performance levels, if service levels are not permanently degraded.
37 Research is ongoing in various related fields, e.g. critical infrastructure, complex systems. Accordingly, naming conventions vary slightly. The naming convention applied throughout this section is in line with the Resilience 2050 project, a European Commission FP7 project dealing with resilience in ATM.
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From a system perspective, there are therefore different degrees of severity in performance disruptions, as explained in Table 5-1.
state service output description system property
Nominal reference level the system performance is ideal
robustness normal
the system performance / service level exhibits normal variability
Non-nominal
disrupted (temporarily)
the system performance / service level exceeds the bounds of normal variability, however, returns to nominal levels over time
resilience
degraded modes of
disrupted (permanently)
the system performance / service level deviates from the normal and becomes fixed over time
modification operations
critically degraded / out-of-service
the system provides its services at critically degraded and unacceptable performance levels or not at all
failure / out-of-service
Table 5-1: Classification of System States and Impacts of Disturbances
5.5.11 Resilience is the ability of air navigation to handle degraded situations and recover from non-nominal conditions of operations by adjusting its functioning in the face of a wide range of disturbances38. As presented in Figure 5-14, resilience can be measured as the absorption rate of the observed loss in quality of service (i.e. performance) over the time of recovery (i.e. t2 – t1).
Figure 5-14: Resilience as a function of disturbance impact
5.5.12 ANS performance at airports is presently described with a set of performance indicators. Service disruptions through for instance weather can severely reduce available capacity leading to a substantial (temporary) mismatch between scheduled and actual operations, as illustrated in Figure 5-15.
Figure 5-15: Cumulative demand vs. accommodated traffic
38 Within SESAR, the term “resilience” is used to describe the robustness of the ATM System to disruptions from a service continuity perspective.
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5.5.13 In the example in Figure 5-15, operations could be gradually recovered by the end of the day. However, depending on the level and duration of capacity reduction and the schedule intensity, a recovery throughout the operational day might not be possible which would then lead to a high number of cancellations.
5.5.14 Further research in close cooperation with all stakeholders (airport operators, ATC, airlines) is required to understand and quantify the consequences of a disturbance on a dynamic system like ANS and to identify possible disruption thresholds for the performance indicators currently used in the framework.
AIRPORT DATA FLOW
5.5.15 For the measurement of operational performance at airports there is a variety of data sources. In principle, data can be derived from airspace users (i.e. airlines), air navigation service providers, and airport operators. Robust and high-quality data is a key requirement for performance measurement. This requirement can be expressed in terms of
scope and coverage; and, precision/accuracy.
5.5.16 Traditionally, the PRR performance monitoring and reporting was established based on ANS derived data for flow management purposes. This data comprises flight plan information enhanced with surveillance data (i.e. CPR data). However, this data flow was not designed to address the immediate airport environment. Accordingly, estimated landing and departure times were calculated following a heuristic approach. As an alternative source, the airline data flow provides more accurate time stamps for actual movement times. However, this data flow covers only around 65-70% of scheduled IFR movements at European airports. Moreover, dependent on airline participation, the coverage can vary significantly from airport to airport.
5.5.17 To overcome shortcomings of the aforementioned data flows, the airport data flow was established. This flow comprises data collected from different stakeholders or entities at the airport with a view to provide a consistent set of data elements for the performance monitoring and reporting. The data flow comprises operational data for each flight including stand and runway information.
5.5.18 Though there is an overlap in terms of certain data elements across the different flows, the major benefits can be seen in the level of coverage (i.e. 100% of general air traffic movements) and higher accuracy of airport operations related data elements (e.g. actual movement times). In particular, the airport data flow provides essential data on runway usage and stand allocation. From a performance monitoring perspective this information is essential to allow for a more detailed analysis. For example, the airport data flow enables the analysis and break-down of taxi-out times considering local conditions and operations in terms of stand – runway combinations, or terminal area approach restrictions for specific arrival sectors and runway directions.
5.5.19 Figure 5-16 presents examples for the ASMA and taxi-out indicators. In both cases, the higher level of accuracy in terms of measurement has a positive effect on the overall indicator. This yields, on average, a gain of 1 min/flight for the respective aggregated Additional ASMA Time per month. As can be derived from the figure, monthly variations are clearly identifiable and can serve as a basis for further analysis. For the taxi-out indicator, the difference between the NM data flow and airport data flow is significant. Higher accuracy of the movement times (i.e. actual off-block time, actual take-off time) yields an improvement of the indicator.
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Figure 5-16: Higher accuracy of airport data flow
CONVERSION OF AIRPORT ANS PERFORMANCE INDICATORS INTO ENVIRONMENTAL
INDICATORS
5.5.20 Airports together with other operational stakeholders increasingly have to deal with the impact of noise and emissions on local communities. Noise is frequently cited as the principal environmental impact at and around airports whilst aviation-related activities result in a variety of gaseous and particulate emissions and may impact on the quality of life and health of local people (i.e. local air quality) and contribute to global climate change (i.e. greenhouse gas emissions).
5.5.21 With the increasing political and public attention there has been a push to address the ANS impact on air quality. Although sources of air pollution at airports can be the responsibility of local government (e.g. public transport) or aircraft operators (e.g. aircraft emissions), the responsibility of ANS is also significant. The ANS contribution towards improving local air quality is mainly related to operational performance and associated fuel burn efficiency during the ground (i.e. on stand) and departure phases (i.e. taxi out, queuing) and, conversely, during the taxi-in phase.
5.5.22 Fuel burn during these operations is dependent on the airport infrastructure, the mode of operation, airport procedures, and engine type. ICAO has established standards for the emission certification of aircraft engines. These standards revolve around expressing emissions in terms of mass per unit of engine thrust and nitrogen oxides (NOx), carbon monoxide (CO), and unburned hydrocarbons (HC). Airport charges are also increasingly based upon aircraft emission levels.
5.5.23 In recent years, EUROCONTROL has been developing models to assess the environmental impact of airport operations, covering fuel burn, gas emissions / local air quality and noise. The underlying models, i.e. the Advanced Emissions Model (AEM) and Airport Local Air Quality Studies (ALAQS), have become part of the standard set of assessment and estimation models used by the ICAO Committee on Aviation Environmental Protection (CAEP).
5.5.24 For emission estimation purposes, ICAO has defined a specific Landing and Take-Off (LTO) cycle covering aircraft operations below a height of 3000 ft. This height defines the range within which aircraft emissions are believed to have a discernible impact on the local air quality. The LTO cycle model comprises four modes of flight operations (i.e. approach, taxi/idle, take-off, and climb-out) that can be directly mapped to operational ANS Performance indicators, (additional) ASMA and taxi-out times in particular.
5.5.25 Basically, the estimated impact of aircraft operations depends on the aircraft type, and for each aircraft, on the:
number of engines,
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mode of engine operation, and the time spend in each mode, fuel flow rate of aircraft/engine type (kg/s), emission index for pollutants (g/kg of fuel).
5.5.26 With a view to mitigating environmental impacts, various scenarios are currently discussed and attention needs to be given to emerging concepts. For example, less than all engines taxi operations, aircraft tugging, electric taxi, restrictions on APU usage, availability of fixed electrical ground power (FEGP) etc. These measures are designed to reduce the operating time of engines and have an impact on the model assumptions and conversion factors. To cover these measures in the emission estimation, additional data would be required beyond the current airport data flow concerning further information on local or airspace user specific procedures and application of technologies. Further research is needed to address these aspects. Moreover, arrangements for the use of ALAQS and AEM data beyond the scope of emission estimation and for the purpose of performance monitoring require consultation with the contributing stakeholders.
5.6 Conclusions 5.6.1 On average, movements at the top 30 airports in Europe decreased by 1.5% in 2013 and
operational performance remained nearly unchanged as shown in table below.
Operational ANS performance at the top 30 airports 2012 2013
Inbound
(minutes per arrival)
Airport arrival ATFM delay 0.9 0.8
Additional ASMA time 2.1 2.2
Outbound
(minutes per departure)
ATC pre-departure delay 0.5 0.6
Additional taxi-out time 3.7 3.7
5.6.2 From an airport perspective, one indicator considered in isolation cannot be representative of the overall ANS performance. When performance is considered from a transversal perspective at airports, it appears to be better for arrival flows than for departures. This is expected in order to discharge the airspace and minimise fuel consumption airborne. On the inbound flow, Additional ASMA Time however remains relatively great compared to Airport Arrival ATFM Delay.
5.6.3 The Network Manager initiated a project in order to enhance the integration of airports into the ATM Network, mainly to exchange information during adverse weather conditions. The PRC will monitor performance improvements.
5.6.4 The PRU initiated some research on new performance indicators:
Additional Taxi-in Time is being investigated as a very first step to the extension of the en-route-to-en-route performance perspective of airports. The trial needs to be validated with airport operators. The efficiency of turnaround and stand occupancy times should also be investigated from a global airport performance perspective, provided that data is available.
Further research is required to understand and quantify the resilience of ANS to perturbations as well as associated disruption thresholds.
Capacity indicators (additional ASMA and taxi-out time) are converted into environment indicators, enabling a better assessment of the emission impact of airport operations.
5.6.5 Higher level of details, comparability, consistency and lower ambiguity are expected as key benefits of receiving high-quality data also from non-SES airports. The PC’s decision regarding the set-up of appropriate airport data flow at non-SES-airports should be implemented in full.
5.6.6 The airports, through the States, should be encouraged to use the sub-codes 89 as a standard. In parallel, the use of Target Start-Up Time (TSAT) and Target Off-Block Time (TOBT) available at A-CDM airports should be investigated as an alternative to (sub-) codes 89.
Chapter 6: ANS Cost-efficiency
PRR 2013 90
ANS Cost-efficiency 6
KEY POINTS KEY DATA 2012 vs. 11
EN-ROUTE ANS En-route ANS costs for EUROCONTROL Area
Real en-route unit cost deteriorated after two years of consecutive improvement (an increase of +2.3% in 2012 compared to 2011).
At system level, en route service units decreased by -1.2% in 2012. En-route ANS costs (expressed in €2009) increased overall by +1.0% (mainly as a
result of a one-off reduction in EUROCONTROL costs in 2011). Increases in provisions for future liabilities (mainly for pensions) have a significant impact on reported actual costs for 2012. The volatility of the provisions and the magnitude of their variations raise concerns in the context of charging and performance, whereas increases or decreases in these provisions do not necessarily represent costs directly attributable to the provision of ANS in the year in which they are recorded.
Plans and forecasts for 2013-2014 (made before the start of RP1) show a decrease in the real en-route unit cost of -3.1% p.a. compared to actual 2012. Such a reduction is driven by high traffic forecasts made at the time of submission of the RP1 Performance Plans for the SES States in 2011, i.e. before the traffic decrease and will not materialise. States will need to adapt their 2013 and 2014 actual costs to the traffic context to avoid significant increases in their unit costs and, for the SES States, to avoid significant losses in RP1.
2015-2019 preliminary figures provided by States in June 2013 show moderate growth in traffic and a stabilisation in costs in real terms over the period. These forecasts will however have to be adapted for 2015-2019 so as to be collectively consistent with the EU-wide targets adopted for the SES States for the RP2 period. It would be advisable that the other EUROCONTROL States which are not bound by the SES Regulations aim at following trends consistent with the SES States.
Total en-route ANS costs (M€2009)
6 520 +1.0%
Service units (M) 118 -1.2%
En-route ANS costs per SU (€2009)
55.1 +2.3%
Planned average annual growth rate of en-route unit costs per SU between 2012-14 (Nov. 2013 data and Performance Plans data for RP1 for the SES States)
-3.1% p.a.
TERMINAL ANS Terminal ANS costs for SES Area
For SES States, in 2012, both terminal ANS costs (-3.4%) and unit costs (-2.0%) decreased in real terms for the third year in a row. Terminal ANS costs are planned to remain relatively stable until the end of RP1 (+0.4% p.a. on average between 2012 and 2014).
Terminal ANS cost information differs across States and across time for many reasons, although quality and quantity of data is gradually improving. For the purpose of this analysis, terminal navigation service unit (TNSU) were recomputed using the formula mandatory from 2015.
The first STATFOR terminal navigation service units forecast has been used to compute SES trends in TNSUs and terminal unit costs for 2013-2014 for the first time.
Among the identified reasons for differences in terminal ANS unit cost are: the States’ discretion on defining their Terminal Charging Zones (TCZ), including the number of TCZ and the number and size of aerodromes; the charging policy, including the charging formula until 2014 and applied cost-allocation between en-route and terminal; the traffic levels and complexity, and the scope of ANS provided. This introduces comparability issues when analysing and benchmarking terminal ANS performance levels across States/TCZ/airports.
Total terminal ANS costs (M€2009)
1 409 -3.4%
Recomputed terminal service units ((MTOW/50)^0.7) (M)
7.7 -1.4%
Terminal ANS costs per terminal SU (€2009)
182.1 -2.0%
Planned average annual growth rate of terminal ANS unit costs per TNSU between 2012-14 (Nov. 2013 data for the SES States)
-0.4% p.a.
GATE-TO-GATE ANSP Gate-to-gate ATM/CNS provision costs
In 2012, ATM/CNS provision costs remained fairly constant (-0.2%) while the number of composite flight-hours reduced by -1.9%. As a result, unit ATM/CNS provision costs increased (+1.7%) compared to 2011.
However, the increase in unit ATM/CNS provision costs was outweighed by a significant reduction of the unit costs of ATFM delays (-39.3%). Overall, in 2012 unit economic costs substantially decreased by -4.8%.
In a context of traffic decrease (-1.9%), ANSPs were in a position to reduce the number of ATCO-hours on duty (-2.1%) in 2012 and as a result ATCO-hour productivity slightly rose +0.3% at Pan-European system level. This indicates that overall, Pan-European ANSPs showed a certain degree of flexibility to deploy operational staff in order to adapt to the lower traffic volumes.
Gate-to-gate ATM/CNS provision costs (M€ 2012)
8 059 -0.2%
Composite flight-hours (M) 18.2 -1.9%
Gate-to-gate ATM/CNS provision costs per composite flight-hour (€ 2012)
443 +1.7%
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6.1 Introduction 6.1.1 The PRC has the remit to review gate-to-gate ANS cost-efficiency performance. This
chapter analyses gate-to-gate ANS cost-efficiency performance in 2012 as well as the outlook over 2013-2018.
6.1.2 Sections 6.2 to 6.5 present en-route cost-efficiency performance for the EUROCONTROL area and individual Member States for the year 2012 (i.e. the latest year for which actual financial data are available). More specifically, Section 6.3 compares the 2012 outcome with the previous year, while Section 6.4 compares the 2012 outcome with the performance which was previously forecasted for 2012.
6.1.3 Section 6.5 shows how en-route cost-efficiency performance is planned to evolve between 2012 and 2014 for the EUROCONTROL area. It also considers the information on cost-efficiency provided by the EU-27+2 States in their Performance Plan in the context of Commission Regulation (EU) No 691/2010 (hereinafter the “performance scheme Regulation”) [Ref. 4].
6.1.4 Sections 6.6 to 6.9 present a high level analysis of data on terminal ANS costs and unit rates as reported to the European Commission by EU Member States, as well as Norway and Switzerland, in accordance with regulatory requirements relating to terminal ANS cost-efficiency in Commission Regulation (EC) N°1794/2006 (hereinafter the “charging Regulation”) [Ref. 33]) and the performance regulation.
6.1.5 Finally, for the purposes of benchmarking ANSPs’ performance and comparing like with like, the PRC has been analysing since 2001 gate-to-gate ANS economic performance which focuses on ATM/CNS costs incurred by ANSPs, and which is based on information disclosure requirements [Ref. 34]. Highlights and findings from this analysis are reported in Section 6.10.
Methodological note In order to ensure consistency with indicators defined in the performance scheme regulation, the cost-efficiency indicator analysed in this chapter is expressed in terms of costs per service unit. Furthermore, in order to ensure consistency with the information provided in national/FAB Performance Plans, the financial figures reported in Sections 6.2 to 6.9 of this Chapter are expressed in Euro 2009. Finally, it should be noted that in this chapter, the term “EUROCONTROL Area” refers to the en-route charging zones integrated into the Route Charges system in 2012 (with the exception of the Portugal Santa Maria charging zone). Similarly, EU-27+2 States refer to the 27 Member States of the European Union, plus Switzerland and Norway. They are called hereafter the “SES States”.
6.2 En-route cost-efficiency data at European level 6.2.1 Figure 6-1 summarises the main relevant cost-effectiveness data and shows the changes in
the en-route ANS costs per SU between 2009 and 2014 for the EUROCONTROL Area. For the sake of consistency and harmonisation with SES metrics for RP1 (see box above), the analysis provided in Sections 6.2 to 6.5 focuses on the en-route ANS costs per service unit (SU) and also includes data for Estonia (EU member State).
2009 Actuals
2010 Actuals
2011 Actuals
2012 Actuals
2013 Forecasts
2014 Forecasts
2012 vs 2011
2009-14 AAGR
2012-14 AAGR
Total en-route ANS costs (M€2009) 6 648 6 477 6 453 6 520 6 811 6 797 1.0% 0.4% 2.1%
SES States (EU-27+2) 6 248 6 070 5 972 6 048 6 319 6 306 1.3% 0.2% 2.1%
Other 9 States in the Route Charges System 400 407 481 472 492 491 -1.9% 4.2% 1.9%
Total en-route service units (M SU) 111 114 120 118 127 131 -1.2% 3.5% 5.3%
SES States (EU-27+2) 98 100 105 104 111 115 -1.5% 3.2% 5.4%
Other 9 States in the Route Charges System 13 14 15 15 16 16 0.4% 5.5% 5.0%
En-route real unit cost per SU (€2009) 60.1 56.7 53.8 55.1 53.4 51.7 2.3% -2.9% -3.1%
SES States (EU-27+2) 63.7 60.4 56.9 58.4 56.7 54.9 2.8% -2.9% -3.1%
Other 9 States in the Route Charges System 31.9 29.6 32.5 31.8 30.7 29.9 -2.3% -1.3% -2.9%
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Figure 6-1: Real en-route unit costs per SU for EUROCONTROL Area (€2009)
6.2.2 The consolidated data in Sections 6.2 to 6.5 are also provided separately for the SES States and the other nine EUROCONTROL States in order to ensure the traceability and reconciliation with the data published in the PRB monitoring report for 2012 (see §6.2.7 below) and to identify if different trends and behaviour exist between the SES States operating in the context of the SES Regulations and the other EUROCONTROL Member States integrated in the Route Charges System. The SES States and the nine EUROCONTROL States in the Route Charges System in 2012 are shown on the map in Figure 6-2 below.
Figure 6-2: SES States and non-SES States covered by the en-route analysis (RP1)
6.2.3 The actual 2012 data for the EUROCONTROL Member States is based on their November 2013 submission to the enlarged Committee for Route Charges. For the SES States, the 2013-2014 planned costs, traffic and unit costs (Determined Unit Rates) are those arising from the adopted national Performance Plans for the first Reference Period (RP1). For the other nine non-SES States, these are the latest available revised figures. (See Map in Figure 6-2 above showing the SES States and the other nine non-SES States covered by the en-route analysis in the present chapter).
6.2.4 For the SES States, 2012 is the first year of application of the “determined costs” method with specific risk-sharing arrangements defined in the charging regulation aiming at incentivising economic performance. For the other nine EUROCONTROL States
60.156.7
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Total en-route ANS costs index 100 97 97 98 102 102
Total en-route service units index 100 103 108 107 115 119
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participating in the Route Charges System, the “full cost-recovery method” continued to apply in 2012.
6.2.5 In the “full cost-recovery method”, the amounts charged to airspace users for a given year (N) are based on costs and traffic forecasts established at the end of the previous calendar year (N-1). After closing of year N, an adjustment mechanism balances gains or losses due to differences in costs and in traffic onto the amounts charged in year N+2 or beyond. This means that, ultimately, the actual unit cost reflects both the costs incurred by the State/ANSP for providing en-route ANS in a given year and the amounts charged to airspace users for these services.
6.2.6 In the “determined costs method”, the amounts charged to airspace users for a given year (N) are now fixed prior to the RP (the “determined costs”). The difference between actual costs and determined costs is borne/retained by the State/ANSP concerned and the difference in revenues due to the difference between actual traffic and traffic forecasted prior to the period for that year is shared between ANSPs and airspace users. This method is expected to drive the ANSPs behaviour to reduce their costs in the case of lower traffic than planned and the other entities (State, NSAs, MET service providers) to contain the actual costs within the determined costs envelope. This means that the actual unit costs slightly differ from the amounts ultimately paid by the airspace users.
6.2.7 It is the task of the PRB to assist the EC in the monitoring of the targets set in the Performance Plans for the SES States, including the determined costs and determined unit rates. The PRB Annual Monitoring Report for 2012 is available online [Ref. 35].
6.2.8 A recent revision (November 2013) of the “EUROCONTROL Principles for establishing the cost-base for en route charges and the calculation of the unit rates” gives the possibility for the States which are not bound by the SES to opt for either the “full cost-recovery method” or the “determined costs method”. It can therefore be expected that some non-SES States will apply the “determined costs method” in the future, given the incentive possibilities offered by this method.
6.2.9 The supervision and assessment of the level of the “determined costs” and associated unit rates charged to users is an integral part of the “determined costs method”. It requires Performance Plans to be drawn-up, covering all the different KPAs and potential interdependencies and proper ex-ante assessments carried out by an independent body.
6.3 En-route cost-efficiency analysis: 2012 versus 2011 6.3.1 As shown in Figure 6-3 below, the actual en-route unit cost in 2012 increased by +2.3%
compared to 2011 at system level, as costs increased by +1.0% while traffic (total en route service units) decreased by -1.2%.
Figure 6-3: Real en-route unit costs per SU, 2012 Actuals vs. 2011 Actuals (€2009)
6.3.2 Noteworthy, a large part of the costs increase (+67.0M€2009 at system level between 2011 and 2012 actual costs) is explained by the one-off reduction in EUROCONTROL costs in 2011 relating to International Financial Reporting Standards (IFRS) budgeting and special annex receipts. If this one-off effect is excluded (estimated at -59.7M€2009 in 2011), the increase in real en-route cost in 2012 would be +0.1% compared to 2011, instead of +1.0%.
€2009 prices Actuals 2011 Actuals 2012 Difference (%)Total en-route ANS costs (M€2009) 6 453 6 520 1.0% SES States (EU-27+2) 5 972 6 048 1.3% Other 9 States in the Route Charges System 481 472 -1.9%Total en-route service units (M SU) 120 118 -1.2% SES States (EU-27+2) 105 104 -1.5% Other 9 States in the Route Charges System 15 15 0.4%En-route real unit cost per SU (€2009) 53.8 55.1 2.3% SES States (EU-27+2) 56.9 58.4 2.8% Other 9 States in the Route Charges System 32.5 31.8 -2.3%
2012 cost-efficiency
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VARIATIONS IN ACTUAL COSTS BY NATURE (2012 VS. 2011)
6.3.3 Figure 6-4 below presents the variations of total en-route costs broken down per nature, for the system as a whole, as well as for the SES States and the other 9 States separately.
Figure 6-4: Difference between 2012 and 2011 costs by nature [€2009]
6.3.4 As shown in Figure 6-4, the largest cost increase is observed in the staff costs (+74.4M€2009), and is attributable to SES States. The increases in three specific States have a significant impact at system level:
Germany: +57.3M€2009 (+10% compared to 2011), due to an increase in DFS pension costs consecutive to a change in the discount rate for occupational pensions and higher gross wages and salaries reflecting the collective agreements signed in October 2011, covering the period June 2011 – October 2012;
Romania: +25.3M€2009 (+33%), relating mainly to an increase in the provisions for ROMATSA employee benefits (exceptional cost item presented in staff costs for the purpose of this analysis);
Sweden: +20.5M€2009 (+19%), due to increases in pension liabilities at LFV following a large decrease in the discount rate.
6.3.5 Other States present large increases in staff costs of more than +10% in 2012 compared to 2011: Estonia (+16%), Moldova (+13%), Latvia (+12%) and Poland (+10%).
6.3.6 The largest decreases in staff costs in value were observed in the UK (-13M€2009, or -4%) and Italy (-9M€2009, or -3%). The largest decreases in percentage occurred in Malta (-12%), Croatia (-8%) and the Czech Republic (-7%).
6.3.7 It should be noted that, without the increases in staff costs in the three States referred to in §6.3.4, which are mainly related to increases in provisions for future obligations, the total actual costs for 2012 would have been -0.6% lower compared to 2011 (or by -1.5% if also excluding the effect of the one-off reduction in EUROCONTROL costs in 2011 (see §6.3.2), and would have therefore resulted in an overall reduction (-0.2%) of the unit cost. The granularity of the data available does not allow isolating the impact of variations in provisions from the genuine variations in costs incurred for services provided during the year. It should be noted that, in addition to the increases in provisions in the three States referred to in §6.3.4, other States (e.g. Portugal) have also recorded large increases in provisions for pension in 2012.
6.3.8 The volatility of the (accounting) provisions raises concerns in the context of charging and performance, whereas increases or decreases in these provisions do not necessarily represent costs directly attributable to the provision of ANS in the year in which they are recorded. Moreover, these increases or decreases in provisions, especially when related to pensions, can be significant in size and thereby influence significantly the resulting cost-efficiency indicator, which may no longer reflect the adjustment of costs to the traffic context and the genuine cost-efficiency performance of States/ANSPs or even the Pan-European system as a whole. For those States under the Determined costs method, these increases may also significantly impact the future amounts charged to airspace users if deemed eligible as exemptions from cost-sharing in accordance with the SES Charging Regulation. For this reason, it is recommended to evaluate how genuine cash payments
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rather than accounting accruals payments could be recognised in the calculations of pension costs for charging purposes.
6.3.9 As shown in Figure 6-4, the largest decrease in costs in 2012 is in the area of other operating costs (-17.0 M€2009 or -76.7 M€2009 if the effect of the one-off reduction in EUROCONTROL costs in 2011 referred to in §6.3.2 above is excluded). The decreases in two States in particular have a significant impact at system level:
Spain: -20.9M€2009 (-14%), mainly reflecting cost-saving measures implemented by Aena, including renegotiation of contracts, reduction in rentals and reduction of external consultants, as well as measures of efficiency to reduce consumption of supplies;
Germany: -9.5M€2009 (-5%), mainly as a result of the implementation of cost containment measures in DFS in 2012, focusing on technical infrastructure costs.
6.3.10 Depreciation costs decreased both in the SES and the other States, suggesting overall adaptations of the investment plans to the decreasing traffic or slower traffic increase.
6.3.11 The cost of capital increased significantly in the SES States in 2012 (+8%), as a result of an increase in the return on equity set in the context of the “determined costs method” and the new traffic risk-sharing arrangements. The opposite trend is observed in the other nine non-SES States, where the cost of capital reduced (-15%), mainly as a result of downward revisions in the return on equity applied by ANSPs.
VARIATIONS IN ACTUAL UNIT COSTS BY STATE/CHARGING ZONE (2012 VS. 2011)
6.3.12 The bottom of Figure 6-5 below shows the actual unit cost for each individual State (charging zone) in 2012. It ranges from 76.4€2009 in Germany to 20.4€2009 in Estonia, a factor of more than three. Figure 6-5 also presents the changes in traffic and costs compared to 2011.
Figure 6-5: 2012 Real en-route ANS costs per SU by charging zone (€2009)
6.3.13 The different levels for the en-route cost-efficiency indicator across individual States (charging zones) as shown in Figure 6-5 raise questions in relation with quality and the level of the service rendered, even more so when considering cost of living and complexity factors (the latter metrics are measured annually as part of the ACE Benchmarking Report, see [Ref. 36]).
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6.3.14 In this respect, it should be highlighted that:
Some States, in spite of decreases in costs in 2012, are remaining in the “high unit cost” half of Figure 6-5, where this does not seem commensurate with the complexity and economic environment they are facing (e.g. Slovenia, FYROM, Albania);
Some States, which were already flagged as being “high unit cost” have further increased their unit cost for providing the service (e.g. Slovakia, Moldova);
The case of Bosnia and Herzegovina is unclear, as en-route ANS costs cumulate the costs for the national ANSP (BHANSA) which is foreseen to start the provision of en-route services in the airspace of the FIR only in 2014 (although accounting for 43% of the costs for service provision in 2012), as well as costs for the services provided by the ANSPs of Serbia and Croatia (representing the other 57% of the costs for service provision in the Bosnian FIR).
6.3.15 The efforts made by Spain over the past few years are showing results, as the en-route unit cost for Spain is now converging towards the average of the other four largest States/ANSPs.
VARIATIONS IN UNIT COSTS FOR SES STATES AND “NON-SES” STATES (2011 VS. 2012)
6.3.16 As shown in Figure 6-3 above, the actual unit costs for the SES States and for the other nine States show opposite trends at face value:
In the SES States, actual 2012 costs show an increase of +1.3% over 2011 (or +0.3% excluding the effect of the one-off reduction in EUROCONTROL costs in 2011), while traffic is decreasing (-1.5%), resulting in an increase in the actual unit cost of +2.8% in 2012 (or +1.8% excluding the one-off effect);
In the other nine (non-SES) States, actual 2012 costs show a decrease by -1.9% over 2011 (or -2.6% excluding the effect of the one-off reduction in EUROCONTROL costs in 2011), while traffic remained stable (+0.4%) after several years of strong growth. This results in a decrease in the actual unit cost of -2.3% (or -3.0% excluding the one-off effect).
6.3.17 In terms of costs, as explained in §6.3.7 and §6.3.8 above, the increase of costs between 2011 and 2012 for the SES States is mainly driven by increases in provisions (mainly for pensions). Without these increases in provisions, actual costs in 2012 would be lower than in 2011 for the SES States, as it is also the case for the nine non-SES States altogether.
6.3.18 As far as traffic (en route SU) is concerned, as shown in Figure 6-6 below, traffic growth (SUs) has been significantly weaker in the SES States (+6% between 2009 and 2012, or around 2% per year on average) than in the other nine States (+18% between 2009 and 2012, or around 6% per year on average). The latest available SUs forecasts (see also §6.5.1 ff. below) show that this trend is expected to continue in the medium term.
Figure 6-6: Service units growth (SES and non-SES States)
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TSUs SES 100 102 107 106 114 117 109 112 115 118
TSUs non-SES 100 109 118 118 128 131 137 145 156 164
TSUs SES STATFOR September 2013 100 102 107 106 107 110 113 116 119 122
TSUs non SES STATFOR September 2013 100 109 118 118 126 132 138 144 150 157
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6.3.19 For the SES States, 2012 is the first year of application of the “determined costs” method with specific risk-sharing arrangements defined in the charging regulation aiming at incentivising economic performance. For the other nine EUROCONTROL States participating in the Route Charges System, the “full cost-recovery method” continued to apply in 2012. As this is the first year of application of the two methods in parallel, it is not yet possible to identify whether different trends and behaviour exist between the SES States and the other States in the Route Charges System and to draw any firm conclusions.
6.4 En-route cost-efficiency analysis: 2012 actuals versus 2012 plans/forecasts
6.4.1 Figure 6-7 compares the forecasts en-route ANS costs and SUs prepared by the States for setting their 2012 en-route unit rates and the actual costs and SUs provided by the States in November 2013. For the SES States, the forecasts en-route ANS costs and SUs were determined as part of their adopted national/FAB Performance Plans for RP1.
6.4.2 It is important to monitor the actual costs data against what was planned or forecasted for the year as it enables to evaluate the reactivity to variations in traffic as well as the maturity of the planning process, two key elements for managing performance.
6.4.3 For the SES States, as highlighted in §6.2.7 above, the PRB has issued a very detailed monitoring report for 2012, including an analysis of the ex-ante and ex-post profitability of the main ANSPs in respect of the activities performed in the year.
Figure 6-7: Real en-route ANS costs per SU, 2012 Actuals vs. Forecasts (in €2009)
6.4.4 Figure 6-7 indicates that the actual real en-route unit cost per service unit for 2012 is higher than planned/forecasted in 2011 (by +1.3%). This reflects lower actual costs than planned (by -3.4%), but not enough to outweigh the significantly lower traffic volumes than forecasted (-4.6%).
6.4.5 Figure 6-7 shows similar trend results for the SES States and the other nine States in 2012. It will be interesting to see if this will also be observed for the remaining years of the RP1 period.
6.4.6 The difference in the planned and actual real en-route unit costs for providing the service is provided at individual State level (charging zone) in Figure 6-8.
6.4.7 As shown in the bottom of Figure 6-8, the largest reductions in actual 2012 costs in value compared to what was forecasted are observed in:
France: lower staff costs (containment) and reduced depreciation as a result of lower actual capex than planned and change in applied accounting rules;
UK: mainly in operating costs, reflecting costs reduction measures implemented by NERL, including reduction in support staff;
Spain: mainly lower operating costs reflecting austerity measures implemented by Aena;
Italy: mainly through lower staff costs (including reduction of overtime), and lower capex as some programs have not been activated in 2012.
€2009 prices Planned in November 2011 Actuals 2012 Difference (%)
Total en-route ANS costs (M€2009) 6 750 624 464 6 520 363 581 -3.4%
SES States (EU-27+2) 6 258 117 862 6 048 013 967 -3.4%
Other 9 States in the Route Charges System 492 506 602 472 349 614 -4.1%
Total en-route service units (M SU) 124 104 970 118 368 727 -4.6%
SES States (EU-27+2) 108 359 738 103 501 763 -4.5%
Other 9 States in the Route Charges System 15 745 232 14 866 964 -5.6%
En-route real unit cost per SU (€2009) 54.4 55.1 1.3%
SES States (EU-27+2) 57.8 58.4 1.2%
Other 9 States in the Route Charges System 31.3 31.8 1.6%
2012 cost-efficiency
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Figure 6-8: 2012 Real en-route ANS costs per SU: Actuals vs. Forecasts (in €2009) at
charging zone level
6.4.8 On the other end, Figure 6-8 indicates that some States show significantly higher 2012 actual costs than planned. This is in particular the case for Sweden, Romania and Portugal, for which the increases are related to provisions for future liabilities in respect of staff costs (pensions, employee benefits – see also §6.3.7 and §6.3.8 above).
6.5 En-route cost-efficiency analysis: outlook for 2013-2018 6.5.1 The forward looking data currently available for SES States (see map in Figure 6-2
above) is:
a) For 2013-2014: the values set in the adopted Performance Plans for RP1 and covering 2012-2014;
b) For 2015-2019: the initial forecast figures for RP2 provided in June 2013 to facilitate the establishment of the Union-wide performance targets and without prejudice to the Performance Plans to be adopted by the Member States and to be provided to the European Commission in June 2014 for their assessment.
6.5.2 Figure 6-9 below presents the real en-route unit costs calculated from these data for the RP1 SES States (27+2) in €2009 and using the same cost-efficiency indicator as in RP1.
6.5.3 The data for 2013 and 2014 show a decrease in the real en-route unit cost of -3.1% p.a. compared to actual 2012. Such a reduction is driven by the high traffic forecast made at the time of submission of the RP1 Performance Plans for the SES States. As this traffic will not materialise, States will need to adapt their 2013 and 2014 actual costs to the new traffic context to avoid significant increases in their unit costs and, for those operating under the determined costs method, to avoid significant losses in RP1.
6.5.4 The preliminary data for 2015-2019 show that the total costs for the SES States are forecast to remain stable in real terms in the period 2015-2019 at around 2012 actual levels, while traffic is foreseen to increase by some +9% between 2012 and 2019 (or +1.3% per annum on average, as it is forecast to decrease until 2015 and then show a growth of 2.5% per annum on average until 2019). As a result, these preliminary data show a decrease in the unit cost from 58.4€2009 in 2012 to 52.1€2009 in 2019 (or -1.6% per year on average).
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Figure 6-9: Outlook 2013-2019 for RP1 SES States (in €2009)
6.5.5 These figures will change as States will draw up and adopt their Performance Plans for RP2 with en-route cost-efficiency targets consistent with, and contributing adequately to, the Union-wide target, as set in February 2014. The States’ RP2 Performance Plans are to be provided to the European Commission by 30 June 2014, after due consultation with the stakeholders. The European Commission assisted by the PRB will assess these plans and targets for RP2 and indicate within five months if it is found to adequately contribute to the EU-wide targets or if it needs to be revised.
6.5.6 For the nine non-SES States (see map in Figure 6-2 above), the forward looking data available at present are those provided by the States in November 2013, which are covering the 5-year rolling period of 2013-2018. To ensure consistency within the series, Croatia is still included in the non-SES States for the purpose of this analysis, although this State will be in the SES area from RP2 onwards.
6.5.7 These forward-looking data show in Figure 6-10 below that the total costs for the non-SES States are forecast to increase slightly in real terms in the period 2012-2018 (+1.4% on average per year), while traffic is foreseen to increase strongly over the period (by +5.6% per year on average, i.e. over four times more than the growth forecast for the SES States), resulting in a decrease in the unit cost from 31.8€2009 in 2012 to 24.9€2009 in 2019 (or -4.0% per year on average).
Figure 6-10: Outlook 2013-2018 for non-SES States (in €2009)
63.71
60.41
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56.70 54.85
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6.5.8 Experience shows that planned costs can regularly be updated under the full cost recovery regime. So it would be important to stick to these plans so that this positive cost-effectiveness trend materialises and genuine performance is improved in line with the Union-wide target and the SES States, so as to avoid large divergences between the regime of economic regulation in the SES area and the full cost-recovery mechanism. Convergence should also be sought in the area of supervision in respect of user charges (see also §6.2.7- 6.2.9 above).
6.6 Terminal ANS cost-efficiency data at European level 6.6.1 This section presents a high level analysis of terminal ANS costs data as reported to the
European Commission by the SES States, in accordance with the relevant regulatory requirements relating to terminal ANS cost-efficiency. Since the Terminal ANS-related requirements apply from 2012 onwards, it is to be noted that 2010 and 2011 cost data are not fully comparable with the data recorded from 2012 onwards. It is also noteworthy that all States except France, have decided to postpone the application of determined costs method until 2015.
6.6.2 Terminal ANS costs and unit rates information as per Commission Regulation (EC) No 1794/2006 [Ref. 6] (and (EU) No 391/2013 for France [Ref. 17) is available only for 28 Member States of the European Union as well as Norway and Switzerland. Therefore, for the purpose of the analysis in this chapter, the PRC considers these 30 States.
6.6.3 Although gradually improving, terminal ANS cost-efficiency data have a much lower level of maturity than en-route ANS. At the same time, despite an increasing number of reporting States on terminal ANS costs and unit rate information at the European level, there is still a great deal of diversity across States and across time.
Terminal Navigation Charges vs. Airport Charges
Given the risk for potential misunderstanding it is useful to differentiate between Terminal ANS charges (also called “TNC” for terminal navigation charges) and “Airport charges”. Airport charges typically include landing charges, passenger charges, cargo charges, parking and hangar charges and noise charges, and are covered by Directive 2009/12/EC [Ref. 37]. While such airport aviation and passenger charges amount to some €15 billion/year, the TNCs in the SES represent some €1.5 billion/year.
6.6.4 Total 2012 terminal ANS costs were reported by 29 States (and 31 terminal charging zones) in November 2013. All of these States plus Croatia also reported terminal ANS forecast costs for the establishment of the 2014 terminal ANS unit rate. The 30 SES States, covering 239 airports which represent around 88%, of the overall IFR traffic in 2012. However the number of terminal charging zones (TCZ) and related airports covered fluctuates across RP1 (2012-2014) and across States.
6.6.5 Figure 6-11 below summarises the terminal ANS costs and traffic (terminal movements and total terminal navigation service units (TNSU)) data between 2010 and 2014 for reporting States. As not all the SES States provide terminal traffic forecasts for each Terminal Charging Zone (TCZ) in a consistent and comparable way (see also §6.6.8 below), the STATFOR TNSU forecast for 2013 and 2014 (see also §6.6.9-6.6.10 below) is used to derive SES trends in terminal ANS unit costs.
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Sources: State submissions to the European Commission for costs (November 2013), CRCO for actual TNSU, and
STATFOR for forecast TNSU
Figure 6-11: Real terminal ANS unit costs (€2009) for reporting States
6.6.6 Terminal ANS is charged to users based on TNSUs which are a function of MTOW and are calculated using a formula in the form of (MTOW/50)^α, where the exponent α varies between the reporting States (see Figure 6-12). This inconsistency means that TNSUs and unit rates/costs are not readily comparable between all States, or even sometimes from year to year.
6.6.7 In accordance with the Charging Scheme Regulation, all States will have to use a common formula (MTOW/50)^0.7 as of 2015.
6.6.8 In fact, 19 States have already adopted this formula by 2013, while some are moving progressively towards conforming to it by 2015:
In 2014: France and Ireland;
In 2015: Spain, Norway, Slovak Republic and Switzerland.
Figure 6-12: Terminal SU and Unit rates
6.6.9 For observed traffic 2010-2012, TNSU have been recalculated by the CRCO using the (MTOW/50)^0.7 formula, allowing comparison of actual unit costs between these years and between States. To calculate SES trends in TNSUs and unit costs for 2013-2014, the STATFOR terminal service units forecast has been used (see also §6.6.10 below).
6.6.10 In March 2013, EUROCONTROL/STATFOR produced the 7-year TNSU forecast (2013-2019) for the first time. The forecast is based on the 2013-2019 IFR flight forecast published in February 2013, uses the CRCO flight database for the SES States (except for Estonia that provide its own data), and is based on the common (MTOW/50)^0.7 formula. In addition to the risks that exists in the flight forecasts itself, the TNSU forecast includes additional risks39 related to:
forecast of the average weight coefficient at airport pair linked to the evolution of the MTOW of the flights (opening of new routes, arrival of new aircraft types);
forecast of new airports (i.e. for which there are no historical data) or of relatively
39 see forecast risks in Section 7 of the STATFOR forecast [Ref. 12].
2010Actuals
2011Actuals
2012Actuals
2013Forecasts
2014Forecasts
2012 vs2011
2012-14 AAGR
SES States reporting 26 28 29 29 30 3.6% 1.7%
Charging zones 28 30 31 31 33 3.3% 3.2%
Airports covered 224 226 229 229 239 1.3% 2.2%
Total terminal ANS costs (M€2009) 1 490 1 460 1 409 1 437 1 420 -3.4% 0.4%
Teminal movements (M movements) 12.8 13.3 12.9 n/a n/a -2.8% n/a
Total terminal service units ((MTOW/50) 0̂.7, M TNSU) 7.5 7.9 7.7 7.6 7.9 -1.4% 0.7%
(€2009/movement) 116.5 110.0 109.3 n/a n/a -0.7% n/a
(€2009/TNSU) 199.0 185.9 182.1 189.3 180.8 -2.0% -0.4%
Total terminal ANS costs (M€2009) 1 490 1 446 1 394 1 420 1 394 -3.6% 0.0%
Total terminal service units (M TNSU) 7.5 7.8 7.6 7.5 7.7 -1.7% 0.5%
Terminal real unit costs (€2009/TNSU) 199.0 186.0 182.3 189.4 180.7 -2.0% -0.3%
Number of
Terminal real unit costs
Constant perimeter
(26 States-28 TCZs)
Service Unit Formula
(MTOW/50)^0.7
(MTOW/50)^0.65
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small airports whose traffic is likely to grow (historic data show fewer flights than it might be observed in the future).
Terminal Navigation Service Units (TNSU)
The PRC used a proxy for terminal navigation services units’ series based on CRCO data using a common formula (MTOW/50)^0.7) for the following reasons: to enable comparison of terminal ANS unit costs across States, to be more in line with the terminal cost-efficiency indicator defined in the Performance
Regulation.40
6.6.11 Between 2010 and 2012, the number of reporting States (and TCZs) increased by three with the addition of Cyprus, Latvia and Malta. However, these form a very small part of the cost base (around 1% of total costs and traffic) and therefore this had a limited impact on the analysis (see the bottom part of Figure 6-11), which presents the adjusted data series (26 SES States and 28 TCZs).
6.6.12 Figure 6-11 above shows that 2012 actual total terminal ANS costs in real terms (1 409 M€2009) for the SES States decreased by -3.4% compared to 2011, while at the same time (recalculated) TNSUs decreased by -1.4% to 7.7 M TNSUs, leading to a reduction in unit cost of -2.0% to €182.1 per TNSU.
6.6.13 The largest decrease in costs, which have a significant impact at system level, is observed for the following SES States:
Spain: -24.5M€2009 (-13.3% compared to 2011), mainly due to significant reductions in operating costs, depreciation and cost of capital deriving from austerity measures implemented by Aena;
Netherlands: -5.3M€2009 (-9.9%), relating mainly to a decrease in the staff costs;
Greece: -4.5M€2009 (-18.9%), mainly due to staff and operating costs savings;
Poland: -4.1M€2009 (-15.4%), reflecting a change in the cost-allocation in 2012.
6.6.14 A decrease of more than 10% in 2012 compared 2011 is observed for the following States: Hungary (-17.1%), Czech Republic (-11.6%) and Ireland (-10.0%).
6.6.15 On the other hand, the largest increase in total costs in 2012, with a significant impact at a system level, is observed in Germany (+5.3M€2009, or +2.4%) and Sweden (for the TCZ- Arlanda; +2.7M€2009 or 16.6%).
6.6.16 In 2012, terminal movements decreased by -2.8% to 12.9 million, with corresponding unit costs decreasing by -0.7% to €109.3 per movement. These figures are affected by changes in which States reported data and the number of airports forming the TCZ.
6.7 Terminal ANS cost-efficiency analysis: 2012 versus 2011 6.7.1 Figure 6-13 shows the terminal ANS unit cost for 31 TCZs in the 29 SES States
(excluding Croatia whose 2012 actual data are not available), using the recalculated 2012 TNSUs.
6.7.2 In 2012, terminal ANS costs per TNSU range from €484 for Slovak Republic TCZ to €79 for Sweden-Landvetter TCZ, a factor of over six. The two dotted lines in Figure 6-13 represent the top and bottom quartiles of the dataset, giving an indication of the variance of calculated terminal ANS unit costs. In 2012, there were €79 per TNSU between the upper (€234) and lower (€156) quartiles, with the average of the proxy for the European unit cost amounting to €182.1 per TNSU41.
40 No 691/2010, see Annex I, Section 1.4 41 It should be noted that the variation in unit cost between States shown in Figure 6-13 does not vary substantially
if calculated using cost per movement instead of cost per TNSU.
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Sources: States TNC submissions to the European Commission for costs (November 2013) and CRCO for TNSU
Figure 6-13: Comparison of 2012 terminal ANS unit costs by TCZ (SES States)
6.7.3 Slovakia TCZ’s high 2012 unit costs could be the result of relatively low traffic in relation to its total cost base. By comparison, Sweden-Landvetter TCZ handled nearly three times more traffic in 2012, at half the total cost of the Slovakian TCZ. As already mentioned, the scope of the Terminal ANS provided might be very different between the two TCZ.
6.7.4 Among the identified reasons for differences in terminal ANS unit cost are: the States’ discretion on defining their Terminal Charging Zones (TCZ), including the number of TCZ and the number and size of aerodromes; the charging policy, including charging formula until 2014 and applied cost-allocation between en-route and terminal; the traffic levels and complexity, and the scope of ANS provided. This introduces comparability issues when analysing and benchmarking terminal ANS performance levels across States/TCZ/airports.
6.7.5 Figure 6-13 also shows that terminal ANS unit costs also substantially differ amongst the five largest States (from €237 for Italy TCZ to €90 for UK TCZ-B).
6.7.6 Unit costs for terminal ANS looks particularly low in the UK TCZ B (€90 per TNSU). Firstly, it should be noted that the unit cost is not necessarily the same as the price charged for terminal ANS in the UK because of the contractual arrangements for the provision of terminal ANS. Low terminal ANS unit cost in UK TCZ B could be partly due to the fact that for the London airports (which account for most of the traffic in UK TCZ B), the cost data submitted only covers the aerodrome control service provided by NATS Services Ltd (NSL). In fact, Approach control for the London airports is provided by NATS En-Route Ltd (NERL) and recovered through a separate London Approach Charge, for which no cost information is currently separately reported to the European Commission. Another reason could be the significant larger scale of operations at the UK TCZ B (airports > 150,000 commercial movements) compared to any other TCZ. Finally, another explanation could be the greater cost-efficiency provided by the UK model of potential “contestability” (now referred to as “market conditions”) for aerodrome ATC services. These particular issues would deserve further analysis and understanding to ensure a fair comparison and to identify genuine best practice performance management.
484
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6.8 Terminal ANS cost-efficiency analysis: 2012 actuals versus 2012 forecasts
6.8.1 Figure 6-14 below shows that terminal ANS costs in 2012 were -4.9% (or -72.2 M€2009) lower than forecasts used for the establishment of 2012 terminal ANS unit rates as reported in November 2011 by SES States.
Figure 6-14: Comparison of 2012 terminal ANS actual costs vs. 2012 forecasts (Nov. 2011
Reporting)
6.8.2 Note that a similar trend is also observed for en-route (see also §6.4.4 above), at system level there were no significant cost reallocation from en-route towards terminal, and the cost-efficiency improvement due to the SES target setting on en-route is likely to also have had a positive impact on terminal ANS costs, mainly due to the level of shared/common costs.
6.8.3 As shown in Figure 6-15 below, the largest reductions are observed for France (actual costs were lower -13.6 M€2009 than forecast provided in November 2011), Spain (-12.7 M€2009), Italy (-11.7 M€2009) and UK (-8.3 M€2009 total savings for both TCZ-A and TCZ-B). A further 17 States achieved smaller savings. Terminal ANS costs were higher than expected in 8 States.
Sources: States TNC submissions to the European Commission for costs (November 2013 for 2012 actual costs) and
(November 2011 for 2012 forecast costs)
Figure 6-15: 2012 Terminal ANS actual costs vs. 2012 forecast costs at State Level
6.9 Terminal ANS cost-efficiency analysis: outlook for 2012-2014 6.9.1 Figure 6-16 below shows that at SES level, terminal ANS unit costs are planned to
increase by +4.0% in 2013 and then to decrease in 2014 (-4.5%) in real terms. Overall, terminal ANS unit costs are planned to decrease by -0.7% (-0.4% p.a.) over the 2012-2014 period. This is due to the fact that terminal ANS costs are planned to increase at a lower rate (+0.4% p.a.), than TNSU (+0.7% p.a.) between 2012 and 2014.
6.9.2 It is to be noted that the terminal ANS costs are remaining relatively stable over the period (+0.7% or 10M€2009), despite an additional State (i.e. Croatia) contributing to the European cost-base as from 2014.
Nov 2011
Reporting Tables
Nov 2013
Reporting Tables
2012F 2012A
Real terminal ANS costs - (in MEUR2009) 1 481.6 1 409.5 -72.2 -4.9%
SES States2012A vs
2012Fin %
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Sources: States TNC submissions to the European Commission for costs (November 2013), CRCO for actual TNSU,
and STATFOR for forecast TNSU
Figure 6-16: Real terminal ANS costs per TNSU, total costs (€2009) and recomputed TNSUs (using (MTOW/50)^0.7)
6.9.3 Figure 6-17 shows the planned change in total costs between 2012 and 2014 for all reporting States and TCZs, with the exception of Croatia (for which data are only available for year 2014 so far). As discussed above, SES total costs are only expected to slightly increase by +0.7% over this period, but the figure below shows that some significant changes in total costs are anticipated at the State/TCZ level.
Sources: State TNC submissions to the European Commission (November 2013)
Figure 6-17: Change in real terminal ANS total costs 2012-2014 (real €2009)
2010A 2011A 2012A 2013F 2014F
Unit Cost (€ 2009) 199.0 185.9 182.1 189.3 180.8
Total cost (index) 105.7 103.6 100.0 102.0 100.7
Total TSUs (index) 96.7 101.4 100.0 98.1 101.5
Total Cost (€ 2009 millions) 1 490 1 460 1 409 1 437 1 420
Total TSUs (millions) 7.5 7.9 7.7 7.6 7.9
50.0
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6.9.4 Even though Malta currently does not charge for the terminal ANS, and the relevant costs are recovered through “income from other sources”, a real increase of +46% in such costs is foreseen between 2012 and 2014, mainly driven by increases in planned levels of depreciation and operating costs from 2013, reflecting the MATS investment and training programmes.
6.9.5 The total cost increase in Romania (+27%) mainly reflects the fact that the second airport (Bucharest Aurel Vlaicu International Airport) is included in the cost base from 2013. Lithuania’s (+24%) real increase in total costs is mainly driven by increases in capital related costs (investment projects related to terminal ANS) and operating costs in 2014, the latter reflecting the expected write-offs of FlyLAL (some 1MLTL), which is reported not to be charged to users.
6.9.6 The cost increase in Norway (+16%) is expected to be mainly driven by the staff costs caused by the several factors (increase in the number of ATCOs at Oslo, Stavanger and Bergen; higher salaries and increase in pension costs related to the implementation of new accounting standards (IAS), and capital related costs (start-up of large investment projects). Czech Republic’s (+13%) real increase in total costs is partially the result of increase in staff costs levels from 2013.
6.9.7 France terminal determined costs would end (+7%) higher in 2014 as compared to 2012, mainly due to significant increase in capital related costs. Total costs for UK-Zone A (+6%) and UK-Zone B (+5%) are expected to increase mainly due to an increase in staff costs, reflecting increases in the pension accounting contribution rate and the CPI based annual staff pay award.
6.9.8 The cost reductions expected for Sweden-Arlanda and Sweden-Landvetter (-22% and-12% respectively) are mainly due to a one-time pension cost in 2012. The cost reduction for Sweden-Arlanda is also driven by lower costs for contracts with LFV regarding the shared use of equipment and flight measurement.
6.9.9 The cost reduction in Spain (-17%) between 2012 and 2014 is expected to be driven mainly by staff and operating cost savings, reflecting the cost reduction measures as part of austerity policy, and process of liberalization of aerodrome control services at some 12 Spanish airports (for which 4 airports are part of the reported TNC data considered in RP1). Indeed, Spain has undergone a process of institutional change opening the terminal ANS market for ATC service provision, and the transition of ATC service provision between the new and former ATC provider is on-going.
6.9.10 A significant decrease expected in Luxembourg (-24%) is mainly the result of a new cost allocation between en-route and terminal in 2013.
6.9.11 Germany expects a decrease (-6%) to their terminal ANS cost-base between 2012 and 2014, mainly driven by operating cost savings.
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6.10 ANSPs gate-to-gate economic performance 6.10.1 The analysis of ANSPs economic performance focuses on ATM/CNS provision costs
which are under the direct responsibility of the ANSP. Detailed analysis is available in the ACE 2012 Benchmarking Report [Ref. 36].
6.10.2 The analysis developed in the ACE Reports allows identifying best practices in terms of ANSPs economic performance and to infer a potential scope for future performance improvements. This is a useful complement to the analysis of the en-route KPI and terminal PIs which are provided in the previous sections of this chapter.
6.10.3 Figure 6-18 shows a detailed breakdown of gate-to-gate ATM/CNS provision costs. Since there are differences in cost-allocation between en-route and terminal ANS among ANSPs, it is important to keep a “gate-to-gate” perspective when benchmarking ANSPs cost-effectiveness performance.
Figure 6-18: Breakdown of gate-to-gate ATM/CNS provision costs 2012 (€2012)
6.10.4 Figure 6-18 indicates that in 2012, at European system level, gate-to-gate ATM/CNS provision costs amount to some €8.1 Billion. Operating costs (including staff costs, non-staff operating costs and exceptional cost items) account for some 82% of total ATM/CNS provision costs, and capital-related costs (cost of capital and depreciation) amount to some 18%.
6.10.5 The analysis presented in this section is factual. It is important to note that local performance is affected by several factors which are different across European States, and some of these are typically outside (exogenous) an ANSP’s direct control while others are endogenous. Indeed, ANSPs provide ANS in contexts that differ significantly from country to country in terms of environmental characteristics (e.g. the size of the airspace), institutional characteristics (e.g. relevant State laws), and of course in terms of operations and processes.
6.10.6 A genuine measurement of cost inefficiencies would require full account to be taken of the exogenous factors which affect ANSPs economic performance. This is not straightforward since these factors are not all fully identified and measurable. Exogenous factors related to operational conditions are, for the time being, those which have received greatest attention and focus. Several of these factors, such as traffic complexity and seasonal variability, are now measured robustly by metrics developed by the PRU.
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6.10.7 The quality of service provided by ANSPs has an impact on the efficiency of aircraft operations, which carry with them additional costs that need to be taken into consideration for a full economic assessment of ANSP performance. The quality of service associated with ATM/CNS provision by ANSPs is, for the time being, assessed only in terms of ATFM ground delays, which can be measured consistently across ANSPs, can be attributed to ANSPs, and can be expressed in monetary terms. The indicator of “economic” cost-effectiveness is therefore the ATM/CNS provision costs plus the costs of ATFM ground delay, all expressed per composite flight-hour.
Composite flight-hours42 The "composite gate-to-gate flight-hours" combines the two separate output measures for en-route (i.e. flight-hours) and terminal ANS (i.e. airport movements). Composite flight-hours are computed by weighting the en-route and terminal output measures using their respective unit costs. This average weighting factor is calculated at European system level using ANSPs costs and outputs data relating to the period 2002-2012 and amounts to 0.27. The composite flight-hours are therefore defined as:
En-route flight-hours + (0.27 × airport movements)
Although the composite gate-to-gate output metric does not fully reflect all aspects of the complexity of the services provided, it is nevertheless the best metric currently available for the comparison of gate-to-gate ANSP economic performance.
6.10.8 A number of factors affecting aircraft operations and contributing to the quality of service that is provided to airspace users by an ANSP are not accounted for in the economic cost-effectiveness indicator analysed in this report. These include:
• horizontal flight-efficiency and the resulting route length extension; and, • vertical flight-efficiency and the resulting deviation from optimal vertical flight
profile.
6.10.9 The PRU is currently developing a methodology to compute ANS-related inefficiencies at ANSP and FAB levels. In the ACE 2012 Benchmarking Report, a first attempt has been made to include a component of flight-efficiency in the economic cost-effectiveness indicator. This analysis is carried out at FAB level and not for each individual ANSP. Indeed, when flight-efficiency is computed at system or FAB level, it includes a network effect which would not be captured at State or ANSP level.
GATE-TO-GATE COST-EFFECTIVENESS
TRENDS IN ECONOMIC COST-EFFECTIVENESS (2008-2012)
6.10.10 Figure 6-19 below displays the trend at European level of the gate-to-gate “economic” costs per composite flight-hour between 2008 and 2012 for a consistent sample of 36 ANSPs43 for which data for a time-series analysis was available. At system level, economic costs per composite flight-hour increased between 2008 and 2010 (i.e. +2.8% p.a. in real terms) and then substantially reduced in 2011 and 2012 (i.e. -7.5% p.a. in real terms) mainly due to the significant decreases in unit ATFM delay costs in 2011 (-37.6%) and 2012 (-39.3%).
42 Further information on the computation of the composite flight-hours can be found in the ACE 2012 Benchmarking Report (May 2014).
43 ARMATS was excluded from this analysis since it started to provide data as from 2009.
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Figure 6-19: Changes in economic cost-effectiveness, 2008-2012 (€2012)
6.10.11 The right-hand side of Figure 6-19 indicates that in 2012, ATM/CNS provision costs remained fairly constant (-0.2%) while composite flight-hours reduced by -1.9%. These changes resulted in an increase of unit ATM/CNS provision costs (+1.7%) compared to 2011. In the meantime, the unit costs of ATFM delays significantly fell (-39.3%) contributing to the substantial decrease in unit economic costs observed in 2012 (-4.8%). Across Europe, ATFM delays contributed some 10% to the total economic gate-to-gate cost in 2012 (compared to 16% in 2011 and 23% in 2010 – see Figure 6-19).
BREAKDOWN OF COST-EFFECTIVENESS KPI (2008-2012)
6.10.12 The cost-effectiveness indicator can be broken down into three main key economic drivers: (1) ATCO-hour productivity, (2) employment costs per ATCO-hour and (3) support costs per composite flight-hour. Note that support costs represent 70% of total ATM/CNS provision costs and include:
• employment costs for non-ATCO in OPS staff; these cover ATCOs on other duties, trainees, technical support and administrative staff (48.4% of support costs);
• non-staff operating costs mostly comprise expenses for energy, communications, contracted services, rentals, insurance, and taxes (23.8% of support costs);
• exceptional costs (2.1% of support costs); and, • capital-related costs, comprising depreciation and financing costs for the capital
employed (25.7% of support costs).
6.10.13 Figure 6-20 and Figure 6-21 show how the various components contributed to the overall change in cost-effectiveness between 2011 and 2012.
6.10.14 In 2012, ATCO-hour productivity remained fairly constant (+0.3%) while employment costs per ATCO-hour rose by +1.3%. This led to slightly higher ATCO employment costs per composite flight-hour (+1.0%). Figure 6-20 also indicates that support costs remained fairly constant (+0.1%) in a context of traffic decrease (-1.9%), and as a result support costs per composite flight-hour increased (+2.0%) in 2012. The central part of Figure 6-20 shows that between 2011 and 2012, given the respective weights of ATCO employment costs (30%) and support costs (70%), unit ATM/CNS provision costs rose by +1.7%.
Figure 6-20: Breakdown of changes in cost-effectiveness, 2011-2012 (€2012)
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"Traffic effect"
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Increased ATCO employment
costs per composite flight-
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Economic gate-to-gate cost-effectiveness
Gate-to-gate ATCO-hour productivity
Gate-to-gate employment costs per ATCO-hour
Gate-to-gate support costs per composite flight-hour
Figure 6-21: ATM/CNS cost-effectiveness comparisons, 2008-2012 (€2012)
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ATCO-HOUR PRODUCTIVITY
ATCO-hour productivity metric
ATCO-hour productivity is measured as the ratio between the flight-hours controlled by the ANSP (output) and the number of hours worked by ATCOs on operational duty (input). It should be noted that the output measure used to compute ATCO-hour productivity reflects the time spent by aircrafts in the area controlled by the ANSP. This is not an operational measure of all the various ATCO activities such as clearances, separations, and data entries. Furthermore, the ATCO-hour productivity metric used in this Report is an average for the year. It is clear that the ANSPs productivity during peak times would be substantially different.
Improvements in ATCO-hour productivity can result from more effective OPS room management and by making a better use of existing resources (for example through the adaptation of rosters and shift times), effective management of overtime, and through the adaptation of sector opening times to traffic demand patterns. Similarly, advanced ATM system functionalities and procedures are drivers for productivity improvements.
In the forthcoming ACE 2012 Benchmarking Report [Ref. 36], ATCO-hour productivity is computed at ACC level and broken down into sector productivity and average staffing per sector. This analysis allows to better understand the main drivers for the differences in productivity amongst the Pan-European ANSPs and ACCs.
6.10.15 Figure 6-21 shows that between 2008 and 2012, ATCO-hour productivity increased (+2.9%) at Pan-European system level.
6.10.16 Figure 6-22 shows that this productivity increase mainly reflects improvements for ANSPs with relatively lower ATCO-hour productivity levels in 2008. On the other hand, the ATCO-hour productivity of ANSPs with relatively high productivity levels in 2008 significantly reduced in 2009 and then remained fairly constant until 2012.
Figure 6-22: Improvement in ATCO-hour
productivity, 2008-2012
6.10.17 Over the 2008-2012 period, in a context of traffic decrease (-2.9%), ANSPs were in a position to reduce the number of ATCO-hours on duty (-5.6%) and as a result ATCO-hour productivity rose by +2.9% at Pan-European system level. Figure 6-23 shows that the reduction of ATCO-hours on duty between 2008 and 2012 period is mainly driven by a significant decrease in overtime hours (-76.1%).
Figure 6-23: Changes in average ATCO-
hours on duty, 2008-2012
6.10.18 These results are heavily influenced by the structural changes implemented in 2010-2011 by Aena following the introduction of Law 9/2010 which was adopted in Spain in 2010. This law introduced new working conditions for Spanish ATCOs, rising contractual working hours and significantly reducing the number of overtime hours, which was one of the main driver for high ATCO employment costs for Aena in the past.
6.10.19 In addition, the ACE 2012 data analysis shows that 25 out of 36 ANSPs could reduce ATCO-hours on duty in 2012. This indicates that overall, Pan-European ANSPs showed a certain degree of flexibility to deploy operational staff in order to adapt to the lower traffic volumes.
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6.10.20 The ACE data analysis allows to identify best practices across ANSPs and also to gather information on the main drivers underlying ATCO-hour productivity improvements. These improvements can result from more effective OPS room management and by making a better use of existing resources, for example through the adaptation of rosters (preferably individually based to enhance flexibility) and shift times, effective management of overtime, and through the adaptation of sector opening times to traffic demand patterns. Latest forecasts indicate that traffic volumes should not be above 2008 levels before 2016. There is therefore an opportunity to increase ATCO-hour productivity at Pan-European system level without significantly affecting the quality of service provided.
ATCO EMPLOYMENT COSTS PER ATCO-HOUR
6.10.21 At system level, ATCO employment costs per ATCO-hour remained fairly constant between 2008 and 2012 (+0.3% in real terms).
6.10.22 Figure 6-24 shows that this overall trend is significantly affected by the decrease in Aena ATCO employment costs per ATCO-hour over the period 2009-2012 (-23% in real terms). Indeed, excluding Aena, Pan-European ATCO employment costs have increased in real terms by +2.0% in 2010, +4.6% in 2011 and +3.0% in 2012.
Figure 6-24: Changes in employment
costs per ATCO-hour, 2008-2012
6.10.23 In 2012, significant increases in employment costs per ATCO-hour are observed for EANS (+35.1%), LGS (+28.5%), MUAC (+21.9%), UkSATSE (+20.2%), DCAC Cyprus (+17.4%) and LVNL (+16.1%).
6.10.24 Figure 6-25 below shows the ATCO employment costs per ATCO-hour both before and after adjustment for Purchasing Power Parities (PPP). After PPP adjustment, the average unit employment costs per ATCO-hour amounts to €112 (compared to €106 without adjustment).
Figure 6-25: Employment costs per ATCO-hour with and without PPPs, 2012
1.8%-5.0% 2.5% 1.3%
3.4% 2.0%4.6% 3.0%
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6.10.25 For many Central and Eastern European ANSPs (HungaroControl, PANSA, ANS CR, Croatia Control, BULATSA, ROMATSA, LPS, Slovenia Control and SMATSA) the PPP adjustment brings the unit employment costs close to those in Western Europe. This indicates that the convergence of unit employment costs between Central and Eastern European economies and Western Europe continues to unfold following the strengthening of the economic integration and the enhanced labour mobility.
6.10.26 Employment costs are typically subject to complex bargaining agreements between ANSPs management and staff which usually are embedded into a collective agreement. The duration of the collective agreement, the terms and methods for renegotiation greatly vary across ANSPs. In some cases salary conditions are negotiated every year. High ATCO employment costs may be compensated for by high productivity. Therefore, in the context of staff planning and contract renegotiation, it is important for ANSPs to manage ATCOs employment costs effectively and to set quantitative objectives for ATCO productivity.
SUPPORT COSTS PER COMPOSITE FLIGHT-HOUR
6.10.27 Support costs amount to 70% of total ATM/CNS provision costs. An effective management of these costs has a major impact on cost-effectiveness. It is therefore important to understand the drivers for changes in support costs and its components.
6.10.28 Figure 6-26 shows the changes in the different components of support costs (see the “support costs effect” bar on the right-hand side of Figure 6-20) between 2011 and 2012.
6.10.29 Figure 6-26 indicates that increases in employment costs for support staff (+€109M) and exceptional costs (+€56M) were compensated by reductions in non-staff operating costs (-€85M), depreciation costs (-€27M), and in the cost of capital (-€51M).
Figure 6-26: Changes in the components of
support costs, 2011-2012
6.10.30 The significant decrease in the cost of capital (-€51M) is mainly due to a substantial decrease in the cost of capital reported by UkSATSE (-€50M). It should be noted that the cost of capital reported by UkSATSE includes the total amount of capital expenditures spent during the year and that particularly high capex were spent in 2011. Excluding UkSATSE, the cost of capital at Pan-European level would remain fairly constant between 2011 and 2012, and as a result 2012 support costs would be +0.6% higher than in 2011 (compared to +0.1% when UkSATSE is included).
6.10.31 The large rise in employment costs for support staff (+€109M) is mainly driven by increases observed for Aena (+€53M) and DFS (+€43M) compared to 2011. For DFS, these increases are mainly or partly due to higher pension-related costs in 2012 and in the case of Aena, it includes costs associated with the Social Plan for Voluntary Layoffs (SPVL) for non-ATCO staff (i.e. €32.1M) which was implemented in 2012.
6.11 Conclusions 6.11.1 In a majority of States, traffic had decreased in 2012 compared to 2011 (-1.2% at system
level) and turned out to be much lower than previously planned/forecasted (by -4.6% at system level). On the other hand, the total costs for providing en-route services increased by +1.0% in real terms compared to 2011 at system level, although they are lower than previously planned for 2012 (by -3.4%). As a result, at face value, the real en-route unit
+4.2%
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cost per service unit for 2012 increased by +2.3%.
6.11.2 However, the analysis shows that this deterioration in cost-efficiency performance is due to two factors which are not strictly related to the costs incurred in respect of en-route services provided in 2012, i.e. the impact of a one-off reduction in EUROCONTROL costs that occurred in 2011 in relation to International Financial Reporting Standards (IFRS) budgeting and special annex receipts, and the impact of increases in (accounting) provisions for future liabilities (mainly for pensions) reported as actual costs for 2012. If the effects of these two factors are excluded, the total actual costs for 2012 would have been lower by -1.5% compared to 2011 and would have therefore resulted in an improvement of the unit cost (decrease of -0.2%).
6.11.3 The volatility of the (accounting) provisions raises concerns in the context of charging and performance, as changes in these provisions do not necessarily represent costs directly attributable to the provision of ANS in the year in which they are recorded. Moreover, these changes in provisions, especially when related to pensions, can be significant in size and thereby influence significantly the resulting cost-efficiency indicator, which may no longer reflect the adjustment of costs to the traffic context and the genuine cost-efficiency performance of States/ANSPs or even the Pan-European system as a whole. For those States under the “determined costs” method, these increases may also significantly impact the future amounts charged to airspace users if deemed eligible as exemptions from cost-sharing in accordance with the SES Charging Regulation. For this reason, it is recommended to evaluate how genuine cash payments rather than accounting accruals payments could be recognised in the calculations of pension costs for charging purposes.
6.11.4 For the SES States, 2012 is the first year of application of the “determined costs” method with specific risk-sharing arrangements defined in the charging regulation aiming at incentivising economic performance. For the other nine EUROCONTROL States participating in the Route Charges System, the “full cost-recovery method” continued to apply in 2012. As this is the first year of application of the two methods in parallel, it is not yet possible to identify whether different trends and behaviour exist between the SES States and the other States in the Route Charges System and to draw any firm conclusions.
6.11.5 A recent revision (November 2013) of the “EUROCONTROL Principles for establishing the cost-base for en route charges and the calculation of the unit rates” gives the possibility for the States which are not bound by the SES to opt for either the “full cost-recovery method” or the “determined costs method”. It can therefore be expected that some non-SES States will apply the “determined costs method” in the future, given the incentive possibilities offered by this method. The supervision and assessment of the level of the “determined costs” and associated unit rates charged to users is an integral part of the “determined costs method”. It requires Performance Plans to be drawn-up, covering all the different KPAs and potential interdependencies and proper ex-ante assessments carried out by an independent body.
6.11.6 Plans and forecasts for 2013-2014 show a decrease in the real en-route unit cost of -3.1% p.a. compared to actual 2012. Such a reduction is driven by high traffic forecasts made at the time of adopting the RP1 Performance Plans for the SES States. As the traffic will not materialise, States will need to adapt their 2013 and 2014 actual costs to the new traffic context to avoid significant increases in their unit costs and, for the SES States, to avoid significant losses in RP1.
6.11.7 2015-2019 preliminary figures currently show moderate growth in traffic and stabilisation in costs over the period. These forecasts will however have to be adapted so as to be collectively consistent with the Union-wide targets adopted for the SES States for the RP2 period. It would be advisable that the other EUROCONTROL States which are not bound by the SES Regulations aim at following consistent trends with the SES States.
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6.11.8 High level analysis of terminal ANS costs indicates that, between 2011 and 2012, terminal ANS unit costs in real terms fell (-2.0%) for the third year in a row. The decrease in unit costs mainly reflects a reduction in terminal ANS costs in real terms (-3.4%) in a context of traffic decrease (-1.4%, TNSU).
6.11.9 Moreover, compared to what was foreseen for the year 2012 (November 2011 Reporting), actual terminal ANS costs are some -4.9% lower than planned. As the similar trend is also observed for en-route, at system level there were no significant cost reallocation from en-route towards terminal, and the cost-efficiency improvement due to the SES target setting on en-route is likely to also have had a positive impact on terminal ANS costs, mainly due to the level of shared/common costs.
6.11.10 A terminal navigation service units (TNSU) forecast was produced by STATFOR for the first time in 2013 (March 2013). This forecast has been used to compute SES trends in terminal ANS unit costs until the end of RP1. Plans and forecasts for 2013-2014 indicate slightly decreasing unit costs (-0.4% p.a.) compared to 2012 actual data.
6.11.11 A number of differences (i.e. the number and size of aerodromes, the traffic levels and complexity, the scope of ANS provided, the charging policy including the applied cost allocation between en-route and terminal) introduce comparability issues when analysing and benchmarking terminal ANS performance levels across States/Terminal Charging Zone (TCZ)/airports.
6.11.12 Differences in cost-allocation can affect the analysis of en-route and terminal cost-efficiency. It is therefore important to keep a gate-to-gate perspective when monitoring ANSP cost-efficiency performance.
6.11.13 ANSP high level benchmarking analysis indicates that the lower unit economic costs observed at Pan-European system level for the year 2012 (-4.8%) mainly reflects a reduction in ATFM delays compared to 2011 (-39.3%) while gate-to-gate unit ATM/CNS provision costs rose by +1.7%. The increase in unit ATM/CNS provision costs is mainly due to the fact that in 2012, ATCO employment costs rose faster (+1.3%) than ATCO-hour productivity (+0.3%) while unit support costs increased (+2.0%) in a context of traffic decrease (-1.9%).
116
ANNEX I - IMPLEMENTATION OF PC DECISIONS
Implementation status of PC decisions relating to PRC recommendations since 2009
SUMMARY TABLE
KPA/Decision Fully
Implemented Partially
implemented Not
implemented Total
General recommendation 1 - 1 Safety 14 - 14 Environment 1 - 1 Capacity 7 9 - 16 Cost-efficiency 2 - 2
Total 10 24 - 34
ANS PERFORMANCE INFORMATION SYSTEM PC 39 decision (May 2013)
r-1. The Provisional Council requested the Director General to explore the progressive development of an integrated ANS performance information system addressing EUROCONTROL and SES performance needs, including their States and stakeholders, and report after one year.
SAFETY - SAFETY REPORTING PC 39 decision (May 2013)
r-2. The Provisional Council noted with appreciation that five of the seven Member States concerned have submitted Annual Summary Templates, and urged the States that still have not fully implemented PC decisions 8.1b, c and e of PC 37 (May 2011) to take action as a matter of urgency.
PC 39 decision (May 2013)
r-3. The Provisional Council noted with appreciation that three Member States have provided information on Effectiveness of Safety Management and Just Culture on a voluntary basis and requested the States concerned to take similar action as a matter of importance.
PC 37 decision (May 2012)
r-4. The Provisional Council encouraged all EUROCONTROL Member States to ensure that AST data is provided in accordance with the provisions of CN Decision No. 115 approving the EUROCONTROL Safety Regulatory Requirement – ESARR 2 “Reporting and Assessment of Safety Occurrences in ATM”.
PC 37 decision (May 2012)
r-5. The Provisional Council urged those States and ANSPs with incomplete safety incident reporting and analysis to review and improve their processes including follow up, and invited the Director General to support them as appropriate.
PC 37 decision (May 2012)
r-6. The Provisional Council requested those Member States, which are not bound by the provisions of the SES performance scheme, to provide to the PRC – on a voluntary basis – information on ‘Effectiveness of Safety Management’ and ‘Just Culture’, and invited the Director General to support them as appropriate.
PC 35 decision (May 2011)
r-7. The Provisional Council requested those States and ANSPs with late and/or incomplete safety incident reporting to review their reporting and investigation systems and to resolve urgently any related issues, and invited the Director General to support them as appropriate.
PC 33 decision (May 2010)
r-8. The Provisional Council requested States and Air Navigation Service Providers to implement “just culture” where this is not already the case,
117
PC 33 decision (May 2010)
r-9. The Provisional Council encouraged States and ANSPs to use automatic detection and reporting tools and to further improve the transparency of ANS safety,
PC 31 decision (May 2009)
r-10. The Provisional Council requested States to further improve the transparency of ANS safety data, including Corrective Action Plans.
PC 31 decision (May 2009)
r-11. The Provisional Council encouraged States/ANSPs to use automated detection and reporting tools to complement manual reporting of incidents as deemed appropriate.
SAFETY - SAFETY OVERSIGHT PC 37 decision (May 2012)
r-12. The Provisional Council urged those States where State Safety Programmes (SSPs) are not implemented to implement them in a timely manner;
PC 35 decision (May 2011)
r-13. The Provisional Council agreed to ensure that the use of resources is optimised by harmonising, rationalising and integrating all international audits, inspections, surveys to which NSAs/CAAs and ANSPs are subjected, noting that for EU Member States this optimisation should result in a system organised around the EASA standardisation inspections complemented by ICAO Audits and peer reviews (EASA opinion 02/2010).
The Provisional Council noted the concerns expressed by Turkey with regard to ESIMS. [Note: c.f. page 30, §4.4.7 of PRR 2010].
PC 31 decision (May 2009)
r-14. The Provisional Council requested the Director General to present a plan to ensure the continuity of safety oversight.
SAFETY - SAFETY MATURITY PC 33 decision (May 2010)
r-15. The Provisional Council requested States and ANSPs whose maturity level is below 70% to urgently resolve the related issues and to request the Director General to support them as appropriate.
ENVIRONMENT PC 31 decision (May 2009)
r-16. The Provisional Council confirmed the already agreed target for flight efficiency of an annual reduction of the average route extension per flight of 2 Km, and related environmental impact (May 2007).
CAPACITY – EN-ROUTE ATFM DELAYS PC 39 decision (May 2013)
r-17. The Provisional Council requested the Director General to work with the relevant States/ANSPs, through the Network Management Directorate, to assist the most constraining ACCs in reducing their en route ATFM delays.
118
CAPACITY – CIVIL/MILITARY USE OF AIRSPACE PC 39 decision (May 2013)
r-18. The Provisional Council requested States: (i) to ensure consistency between national capacity plans and national performance objectives taking due
consideration of the forecasted traffic demand, and the application of the FUA legislation by the State;
(ii) to ensure committed capacity plans are implemented as promised and that the level 2 FUA procedures and agreements are in place, to deploy the capacity based on traffic demand;
(iii) to ensure procedures and agreements are in place so that opportunities for additional capacity or route options due to the availability of previously allocated airspace are notified to the network manager and thence to airspace users, minimising wasted airspace.
PC 33 decision (May 2010)
r-19. The Provisional Council urged: i. States, ANSPs, airspace users and the Agency to further improve the design and use of airspace for
both civil and military needs, and ii. ANSPs and airlines to make more effective use of airspace released to civil operations.
PC 31 decision (May 2009)
r-20. The Provisional Council requested that the CFMU and airspace users co-operate to further increase the use of shorter alternative routes at the flight planning stage, including conditional routes.
PC 31 decision (May 2009)
r-21. The Provisional Council requested further development of route structures coordinated by EUROCONTROL, and that conditional routes are open as often as possible, particularly at week-ends.
CAPACITY – AIRPORTS PC 39 decision (May 2013)
r-22. The Provisional Council requested those States that are not bound by the provisions of the SES performance scheme to provide to the PRC - on a voluntary basis - information on operations at airports with more than 70 000 IFR movements per annum to enable an improved and harmonised measurement of ANS performance at main airports in Europe.
PC 37 decision (May 2012)
r-23. The Provisional Council requested States to speed up the process of Airport Collaborative Decision-making (A-CDM) implementation in cooperation with aircraft operators, airports and ANSPs taking into consideration that the current A-CDM rollout is well behind the agreed schedule according to the EUROCONTROL A-CDM implementation plan.
PC 35 decision (May 2011)
r-24. The Provisional Council requested the Director General to monitor ANS performance at airports, including ANS efficiency indicators such as pre-departure delays due to local ATC constraint, ASMA and Taxi-out additional times on top of ATFM delays, and to bring solutions to identified issues.
PC 33 decision (May 2010)
r-25. The Provisional Council encouraged airport stakeholders (Airport operators, coordinators, ANS providers and airlines) to constructively engage in the PRC-led process of development of indicators and targets addressing operational performance at and around airports and in the building of a comprehensive and reliable data base that can adequately support it.
PC 31 decision (May 2009)
r-26. The Provisional Council requested the States to promote the use of airport collaborative decision-making.
119
CAPACITY – PLANNING PC 39 decision (May 2013)
r-27. The Provisional Council urged those States providing no or insufficient Correlated Position Reports to ensure that this data is supplied to the Agency at the required frequency and quality level.
PC 37 decision (May 2012)
r-28. The Provisional Council requested States to maintain a forward looking and proactive approach to capacity planning, in order to close existing capacity gaps and to accommodate future traffic growth.
PC 33 decision (May 2010)
r-29. The Provisional Council noted the importance of a balanced approach to performance: increases in en-route delays over the period 2003-2008 nearly cancelled out the benefits of improvements in cost-effectiveness.
PC 33 decision (May 2010)
r-30. The Provisional Council urged the ANSPs concerned to resolve urgently the issues leading to high delays in the top 30 delay-generating sectors, and to request the Director General to assist them in this respect.
PC 31 decision (May 2009)
r-31. The Provisional Council urged States and Air Navigation Service Providers to do their utmost not to jeopardise future capacity provision during the current economic situation.
CAPACITY – NETWORK MANAGER PC 31 decision (May 2009)
r-32. The Provisional Council requested the Director General to commence work to define the role of the envisaged network management function and to propose relevant performance indicators.
COST-EFFICIENCY PC 33 decision (May 2010)
r-33. The Provisional Council urged ANSPs, given the severe economic downturn, to effectively implement the planned cost-containment measures so that: i. they materialise into genuine cost-savings for airspace users in the cost bases for 2010 and
subsequent years and that; ii. they contribute to improving the total economic cost of ANS and do not compromise the provision of
future ATC capacity.
PC 31 decision (May 2009)
r-34. The Provisional Council urged States/ANSPs to do their utmost to try to ensure that there would be no mid-term upward revision by States of the 2009 unit rates and to take action to deal with any revenue shortfall in 2009
120
ANNEX II – ACC TRAFFIC AND DELAY DATA (2011-2013)
3Y‐AAGR = Annual average growth rate
State ACC
2011
2012
2013
2011
2012
2013
2011
2012
2013 Capacity/
Staffing
ATC
OtherWeather
Other
reasons
Albania Ti rana 541 533 550 2.7% 3.4% 0.49 0.06 0.00 0.49 0.06 0.00 100.0% 0.0% 0.0% 0.0%
Armenia Yerevan 147 144 139 ‐3.8% 1.6% 0.00 0.00 0.00 0.00 0.00 0.00
Austria Wien 2 015 1 961 1 916 ‐2.6% ‐0.9% 0.54 0.38 0.48 0.23 0.16 0.26 28.3% 6.6% 22.0% 43.1%
Belgium Brussels 1 547 1 503 1 483 ‐1.6% 0.3% 0.23 0.17 0.26 0.04 0.03 0.08 29.3% 0.0% 70.7% 0.0%
Bulgaria Sofia 1 418 1 422 1 460 2.4% 3.4% 0.06 0.01 0.00 0.06 0.00 0.00
Croatia Zagreb 1 287 1 286 1 281 ‐0.6% 2.9% 0.55 0.28 0.10 0.55 0.27 0.10 72.0% 2.6% 25.4% 0.0%
Cyprus Nicos ia 769 736 760 2.9% ‐0.7% 1.63 1.65 2.21 1.62 1.59 2.16 58.6% 8.1% 0.1% 33.2%
Czech Republ ic Praha 1 841 1 793 1 804 0.3% 0.6% 0.03 0.01 0.06 0.01 0.00 0.04 100.0% 0.0% 0.0% 0.0%
Denmark Kobenhavn 1 476 1 409 1 459 3.2% 1.3% 0.06 0.02 0.02 0.01 0.00 0.00
Estonia Tal l inn 468 493 485 ‐1.8% 5.8% 0.02 0.11 0.02 0.02 0.11 0.02 95.1% 3.2% 0.0% 1.7%
Finland Tampere+ 533 485 451 ‐7.2% ‐0.6% 0.89 0.26 0.03 0.65 0.02 0.00 0.0% 92.2% 0.0% 7.8%
France Bordeaux 2 238 2 222 2 238 0.4% 1.9% 0.13 0.30 0.33 0.09 0.27 0.30 16.6% 78.8% 4.3% 0.2%
Brest 2 440 2 397 2 457 2.2% 3.3% 0.14 0.20 0.36 0.13 0.19 0.35 39.8% 53.3% 2.4% 4.6%
Marsei l le 2 804 2 763 2 746 ‐0.9% 0.2% 0.48 0.55 0.44 0.48 0.55 0.44 36.9% 47.1% 15.6% 0.4%
Paris 3 283 3 227 3 106 ‐4.0% ‐0.2% 0.62 0.58 0.42 0.30 0.27 0.17 36.1% 13.9% 25.3% 24.7%
Reims 2 311 2 334 2 430 3.8% 4.3% 0.24 0.27 0.33 0.24 0.26 0.31 43.9% 32.1% 16.1% 7.9%
FYROM Skopje 340 306 301 ‐2.1% ‐4.0% 0.00 0.00 0.00 0.00 0.00 0.00 0.0% 100.0% 0.0% 0.0%
Germany Bremen 1 709 1 674 1 628 ‐3.0% ‐0.7% 0.27 0.16 0.16 0.16 0.06 0.06 75.3% 4.3% 18.1% 2.3%
Langen 3 433 3 376 3 318 ‐2.0% ‐0.6% 2.02 1.03 0.46 0.96 0.64 0.24 74.2% 7.4% 16.6% 1.8%
Munchen ++ 4 079 3 911 2 876 ‐26.7% ‐10.2% 0.55 0.49 0.14 0.33 0.32 0.05 12.2% 0.0% 83.8% 4.0%
Rhein (Karl sruhe) 3 868 3 905 4 501 14.9% 6.4% 0.47 0.09 0.17 0.47 0.09 0.17 49.1% 2.6% 34.9% 13.4%
Greece Athina i+Macedonia 1 742 1 673 1 643 ‐2.1% ‐1.9% 3.96 0.34 0.32 3.04 0.16 0.07 85.8% 14.2% 0.0% 0.0%
Hungary Budapest 1 594 1 526 1 566 2.3% ‐1.0% 0.00 0.00 0.00 0.00 0.00 0.00 100.0% 0.0% 0.0% 0.0%
Ireland Dubl in 488 491 509 3.4% 2.0% 0.02 0.05 0.05 0.01 0.00 0.00
Shannon 1 089 1 075 1 074 ‐0.4% 0.1% 0.00 0.00 0.00 0.00 0.00 0.00
Ita ly Brindis i 872 808 786 ‐3.0% ‐3.1% 0.01 0.02 0.05 0.00 0.00 0.00 0.0% 100.0% 0.0% 0.0%
Mi lano 1 719 1 659 1 567 ‐5.8% ‐2.7% 0.05 0.02 0.01 0.00 0.00 0.00 0.0% 100.0% 0.0% 0.0%
Padova 1 865 1 844 1 821 ‐1.5% 0.5% 0.06 0.03 0.02 0.03 0.00 0.00 0.0% 100.0% 0.0% 0.0%
Roma 2 659 2 583 2 564 ‐1.0% ‐1.5% 0.10 0.07 0.09 0.00 0.00 0.00 0.0% 96.3% 0.0% 3.7%
Latvia Riga 639 634 642 1.0% 10.4% 0.00 0.00 0.00 0.00 0.00 0.00 36.6% 0.0% 63.4% 0.0%
Lithuania Vi lnius 533 544 565 3.5% 3.3% 0.00 0.00 0.00 0.00 0.00 0.00
Maastricht 4 405 4 387 4 471 1.6% 2.3% 0.04 0.04 0.07 0.04 0.04 0.07 25.2% 0.0% 27.4% 47.4%
Malta Malta 222 264 298 12.6% 4.6% 0.00 0.00 0.00 0.00 0.00 0.00
Moldova Chis inau 162 171 198 15.0% 10.4% 0.00 0.00 0.00 0.00 0.00 0.00
The Netherlands Amsterdam 1 416 1 393 1 408 0.8% 1.9% 0.90 0.78 0.68 0.13 0.18 0.12 92.7% 0.0% 7.3% 0.0%
Norway Bodo 544 555 565 1.6% 1.9% 0.01 0.03 0.03 0.01 0.03 0.03 17.9% 4.6% 0.0% 77.5%
Os lo 884 898 949 5.4% 2.1% 0.59 0.96 0.38 0.03 0.47 0.00 100.0% 0.0% 0.0% 0.0%
Stavanger 588 625 663 5.8% 7.0% 0.16 0.03 0.12 0.12 0.01 0.07 95.9% 0.0% 4.1% 0.0%
Poland * Warszawa 1 680 1 723 1 753 1.5% 4.8% 0.71 0.56 0.56 0.69 0.56 0.54 54.0% 4.1% 7.1% 34.9%
Portugal Lisboa 1 153 1 121 1 150 2.3% 1.6% 0.31 0.95 0.43 0.17 0.69 0.29 90.1% 9.9% 0.0% 0.0%
Santa Maria 307 295 305 3.1% 1.6% 0.00 0.00 0.00 0.00 0.00 0.00
Romania Bucuresti 1 333 1 308 1 383 5.5% 2.5% 0.00 0.00 0.00 0.00 0.00 0.00
Serbia Beograd 1 502 1 435 1 393 ‐3.2% ‐1.5% 0.05 0.00 0.02 0.05 0.00 0.02 60.0% 0.0% 23.8% 16.2%
Slovak Republ ic Brati s lava 2 002 2 050 2 215 7.8% 6.4% 0.69 0.63 0.15 0.07 0.00 0.00
Slovenia Ljubjana 741 735 703 ‐4.6% 1.5% 0.00 0.00 0.00 0.00 0.00 0.00 0.0% 0.0% 0.0% 100.0%
Spain Barcelona 2 136 2 013 2 007 ‐0.6% ‐0.8% 1.36 0.68 0.49 1.31 0.63 0.47 84.4% 0.2% 14.0% 1.5%
Madrid 2 727 2 500 2 395 ‐4.5% ‐3.3% 1.81 0.34 0.22 1.23 0.18 0.18 74.9% 0.0% 0.6% 24.6%
Palma 717 682 674 ‐1.4% ‐0.5% 1.02 0.57 0.48 0.36 0.19 0.13 94.9% 0.0% 5.1% 0.0%
Sevi l la 1 001 894 879 ‐2.0% ‐3.5% 0.31 0.09 0.07 0.28 0.06 0.05 91.0% 0.0% 8.6% 0.5%
Canarias 814 749 724 ‐3.6% ‐1.3% 1.37 0.57 0.56 1.09 0.38 0.44 66.2% 0.1% 30.8% 2.9%
Sweden Malmo 1 390 1 359 1 377 1.1% 2.1% 0.05 0.04 0.00 0.05 0.04 0.00 100.0% 0.0% 0.0% 0.0%
Stockholm 1 094 1 062 1 069 0.4% 1.5% 0.22 0.15 0.17 0.14 0.02 0.05 12.5% 5.7% 36.7% 45.1%
Switzerland Geneva 1 704 1 654 1 627 ‐1.9% ‐0.4% 0.34 0.26 0.41 0.16 0.06 0.10 44.0% 12.1% 43.7% 0.1%
Zurich 2 078 2 031 1 975 ‐3.0% ‐0.9% 0.55 0.62 0.61 0.20 0.19 0.14 85.1% 1.2% 6.8% 6.9%
Turkey Ankara 1 914 1 928 2 037 5.4% 5.0% 0.32 0.23 0.19 0.19 0.21 0.14 5.8% 0.4% 0.0% 93.8%
Is tanbul 2 002 2 050 2 215 7.8% 6.4% 0.69 0.63 0.15 0.07 0.00 0.00
Ukra ine Kyiv 608 631 651 2.9% 6.7% 0.00 0.04 0.02 0.00 0.00 0.00
Dnipropetrovs 'k ALL** 403 427 447 4.5% 12.5% 0.00 0.00 0.00 0.00 0.00 0.00
Simferopol 544 540 594 9.5% 2.1% 0.00 0.00 0.00 0.00 0.00 0.00
L'viv 482 485 502 3.3% 3.9% 0.00 0.00 0.00 0.00 0.00 0.00
Odesa 260 268 299 10.9% 7.0% 0.00 0.00 0.00 0.00 0.00 0.00
United Kingdom London AC 4 969 4 894 4 927 0.4% 0.9% 0.18 0.07 0.14 0.18 0.07 0.14 25.3% 53.8% 19.8% 1.1%
London TC 3 419 3 386 3 408 0.4% 0.9% 0.42 0.65 0.60 0.01 0.02 0.01 30.3% 0.0% 65.0% 4.8%
Prestwick 2 450 2 380 2 397 0.4% ‐0.1% 0.13 0.07 0.04 0.09 0.02 0.00 52.0% 0.0% 48.0% 0.0%
ACCs geographical areas might change over time, preventing year on year comparision (e.g. Prestwick, Dnipropetrovs'k ALL)
* does not include EPWWICTA and EPKKTMA
** Dnipropetrovs'k ALL was created in March 2010 replacing Kharkiv, Dnipropetrov'k and Donetsk' ACCs
+ Rovaniemi ACC was merged with Tampere ACC in 2011. ++ Upper airspace was transferred to Karlsruhe in Aug. 2012.
Causes of en route
ATFM delay in 2013En route ATFM
delay per fl ight
IFR Traffi c
2013/12
growth
(%)
3Y‐
AAGR
Avg. dai ly
Tota l ATFM
delay per fl ight
121
ANNEX III – TRAFFIC COMPLEXITY SCORES IN 2013
The PRU, in close collaboration with ANSPs, has defined a set of complexity indicators that could be applied in ANSP benchmarking. The complexity indicators are computed on a systematic basis for each day of the year. This annex presents for each ANSP the complexity score computed over the full year (365 days).
The complexity indicators are based on the concept of “interactions” arising when there are two aircraft in the same “place” at the same time. Hence, the complexity score is a measure of the potential number of interactions between aircraft defined as the total duration of all interactions (in minutes) per flight-hour controlled in a given volume of airspace.
For each ANSP the complexity score is the product of two components:
The traffic density is expressed in adjusted density which measures the (uneven) distribution of traffic throughout the airspace (i.e. taking into account the relative concentration). The measure relies on dividing the airspace volume into a discrete grid of 20 nautical mile cells. For the purpose of this study, an interaction is defined as the simultaneous presence of two aircraft in a cell of 20x20 nautical miles and 3,000 feet in height.
The structural index originates from horizontal, vertical, and speed interactions and is computed as the sum of the three indicators.
Horizontal interactions indicator: A measure of the complexity of the flow structure based on the potential interactions between aircraft on different headings. The indicator is defined as the ratio of the duration of horizontal interactions to the total duration of all interactions.
Vertical interactions indicator: A measure of the complexity arising from aircraft in vertical evolution based on the potential interactions between climbing, cruising and descending aircraft. The indicator is defined as the ratio of the duration of vertical interactions to the total duration of all interactions
Speed interactions indicator: A measure of the complexity arising from the aircraft mix based on the potential interactions between aircraft of different speeds. The indicator is defined as the ratio of the duration of speed interactions to the total duration of all interactions
More information on the methodologies used for the computation of the complexity score in this report is available from the report on “Complexity Metrics for ANSP Benchmarking Analysis” available on the PRC webpage [Ref. 15].
Complexity score = Traffic density x Structural index
122
ANSP Complexity score (2013)
The complexity scores in the table below represent an annual average. Hence the complexity score in areas with a high level of seasonal variability may be higher during peak months.
* Note that Aena’s complexity score is influenced by the low traffic density of Canarias airspace.
Complexity Score 2013
ANSP and State vertical horizontal speed Total
A % change B C D E=B+C+D % change F= A * E % change
Skyguide (CH) 10.76 0.6% 0.28 0.61 0.22 1.11 -0.5% 11.98 0.1%
NATS (Continental) (UK) 9.95 1.5% 0.37 0.43 0.30 1.11 -0.5% 11.03 1.0%
DFS (DE) 10.18 -0.9% 0.27 0.57 0.24 1.08 -0.6% 11.03 ‐1.5%
Belgocontrol (BE) 7.19 -2.3% 0.39 0.55 0.45 1.40 -1.3% 10.08 ‐3.6%
MUAC (MUAC) 10.23 3.0% 0.26 0.55 0.16 0.97 -0.3% 9.94 2.7%
LVNL (NL) 9.91 1.2% 0.19 0.43 0.38 1.00 3.4% 9.91 4.6%
ANS CR (CZ) 9.15 7.2% 0.14 0.53 0.17 0.83 -4.3% 7.63 2.6%
Austro Control (AT) 8.31 1.0% 0.18 0.53 0.19 0.90 -0.6% 7.51 0.4%
Slovenia Control (SI) 9.29 0.9% 0.12 0.55 0.10 0.77 -0.2% 7.13 0.7%
DSNA (FR) 10.06 2.6% 0.15 0.42 0.13 0.70 -0.6% 7.07 2.0%
DHMI (TR) 8.55 14.3% 0.16 0.35 0.16 0.67 6.1% 5.77 21.2%
LPS (SK) 7.79 12.5% 0.09 0.48 0.15 0.73 -0.8% 5.67 11.6%
ENAV (IT) 5.34 2.6% 0.26 0.59 0.17 1.02 -2.1% 5.43 0.4%
SMATSA (LY) 8.52 -0.7% 0.04 0.50 0.06 0.60 0.4% 5.12 ‐0.3%
HungaroControl (HU) 7.72 7.5% 0.06 0.46 0.13 0.65 0.0% 5.02 7.5%
Croatia Control (HR) 7.98 6.6% 0.06 0.49 0.07 0.61 0.2% 4.86 6.8%
PANSA (PL) 4.79 1.0% 0.14 0.54 0.22 0.89 -1.0% 4.26 0.0%
Aena (ES) 6.46 -1.3% 0.15 0.37 0.13 0.64 -3.8% 4.13 ‐5.1%
ROMATSA (RO) 5.88 8.0% 0.05 0.43 0.12 0.60 2.3% 3.51 10.4%
NAVIAIR (DK) 3.55 1.7% 0.18 0.57 0.20 0.95 -1.8% 3.36 ‐0.1%
DCAC Cyprus (CY) 4.89 12.3% 0.14 0.38 0.10 0.63 2.1% 3.06 14.7%
BULATSA (BU) 6.92 3.4% 0.06 0.31 0.06 0.43 4.0% 3.01 7.5%
NATA Albania (AL) 6.61 5.2% 0.05 0.35 0.04 0.45 0.1% 2.95 5.4%
LFV (SE) 3.00 -1.5% 0.22 0.50 0.23 0.95 -1.5% 2.84 ‐3.0%
EANS (EE) 3.77 2.2% 0.14 0.30 0.21 0.66 -4.8% 2.48 ‐2.7%
M‐NAV (MK) 4.17 -7.2% 0.09 0.44 0.06 0.59 4.3% 2.48 ‐3.3%
HCAA (GR) 4.21 -2.3% 0.10 0.38 0.08 0.55 -0.9% 2.33 ‐3.2%
LGS (LV) 3.28 1.8% 0.09 0.46 0.16 0.70 -3.0% 2.31 ‐1.3%
NAV Portugal (Continental) (PT) 3.77 4.3% 0.15 0.37 0.08 0.60 -1.0% 2.27 3.3%
UkSATSE (UA) 3.31 2.8% 0.06 0.41 0.19 0.66 3.4% 2.19 6.2%
Avinor (Continental) (NO) 2.18 3.0% 0.28 0.46 0.25 0.99 -4.4% 2.17 ‐1.5%
Oro Navigacija (LT) 2.86 -7.4% 0.08 0.49 0.15 0.72 4.5% 2.06 ‐3.3%
IAA (IE) 4.06 -3.0% 0.07 0.24 0.13 0.45 10.9% 1.81 7.6%
MoldATSA (MD) 2.44 14.3% 0.03 0.46 0.19 0.68 4.3% 1.66 19.3%
Finavia (FI) 1.70 -3.6% 0.26 0.33 0.36 0.94 -6.7% 1.60 ‐10.0%
BHANSA (BA) 0.69 -8.6% 0.46 0.61 0.58 1.65 12.0% 1.14 2.3%
MATS (MT) 1.66 16.1% 0.07 0.37 0.19 0.63 6.0% 1.05 23.0%
ARMATS (AM) 1.33 -2.9% 0.08 0.39 0.16 0.63 2.5% 0.84 ‐0.4%
Average 7.49 2.5% 0.20 0.46 0.18 0.84 ‐0.9% 6.26 1.5%
Adjusted
density
Structural index Complexity
Score
123
ANNEX IV – FRAMEWORK : SERVICE QUALITY
The conceptual framework for the analysis of ATM- related service quality applied in this Performance Review Report (PRR) is illustrated below.
Conceptual framework for measuring ATM-related service quality
The top level illustrates the passenger perspective which compares actual performance to published airline schedules (punctuality)44. Although on-time performance is a valid measure from a passenger point of view, the involvement of many different stakeholders (airlines, ground handlers, airport operators, ATC, etc.) and the inclusion of time buffers in airline schedules to ensure a satisfactory on-time performance require a more in depths analysis for the assessment of ANS-related performance.
In order to better understand the ANS-related contribution towards overall performance, the evaluation of ANS-related service quality focuses on the “Efficiency” and the “Variability” of actual operations by phase of flight (see also grey information box). The flight phases where ANS is considered to have an impact on operations are highlighted in blue in the conceptual framework above.
Inefficiencies in the vertical flight profile for en route and in the TMA departure phase are presently not analysed in more detail in this report as they are generally not considered to be large contributors to ANS-related inefficiencies. However, the magnitude can change by region or airport and it is acknowledged that there is scope for future improvement in those areas in order to get a more complete picture.
Although there are a number of factors outside the control of ANS (apron and stand limitations, etc.), a first evaluation of taxi-in performance is provided in Chapter 5 for completeness reasons.
Efficiency and Variability ‘Efficiency’ in this report measures the difference between actual time/distance and an unimpeded reference time/distance. “Inefficiencies” can be expressed in terms of time and fuel and also have an environmental impact. Due to inherent necessary (safety) or desired (noise, capacity, cost) limitations the reference values are not necessarily achievable at system level and therefore ANS-related ‘inefficiencies” cannot be reduced to zero. The “variability” of operations determines the level of predictability for airspace users and hence has an impact on airline scheduling and the ability to maximise the use of available resources (aircraft, crew, etc.). It focuses on the variance (distribution widths) associated with the individual phases of flight as experienced by airspace users. The higher the variability, the wider the distribution of actual travel times and the more time buffer is required in airline schedules to maintain a satisfactory level of punctuality.
44 It should be noted that there are differences between passenger-centric and flight-centric metrics. Flight centric metrics do not reflect passenger disruption, such as missed connections and the average passenger delay is therefore typically higher than the average flight delay.
Departure delays
Airport Capacity• airport scheduling• achieved throughput• sustainability of ops.• etc.
En‐route efficiency
Origin airport
En‐route ATFM delays Airport
ATFM delays
Terminalefficiency
Reactionary delays
Management of arrival flows
Other (airline, airport, etc.)
Departure punctuality
Pre‐departuredelays(at gate)
Air Traffic Management
Weather
Taxi‐outefficiency
Scheduled block time (airlines) Buffer
Efficiency and variability of operations (ANS contribution)
Ground
Airborne
En‐route network Approach Arrival airport
Airline scheduling
ANS performance
Arrivalpunctuality
Passenger perspective
Taxi‐inefficiency
124
Not all delay is to be seen as negative. Due to the stochastic nature of air transport (weather conditions, etc.) and the way the system is operated today (airport slots, traffic flow management, etc.), different levels of “inefficiency” may be required or even desirable to maximise the use of scarce capacity at the given level of variability.
Imbalances between capacity and demand can occur en route and at airports due to a number of reasons including: weather, variability of traffic flows, scheduling, and the availability of ATC capacity and airspace.
A clear-cut allocation between ANS (ATC capacity, staffing, etc.) and non-ANS (weather, airline delay, etc.) related causes is often difficult. While ANS is often not the root cause of the problem, depending on the way those imbalances are managed and distributed along the various phases of flight (airborne vs. ground) through the application of flow measures, the outcome has a different impact on airspace users (punctuality, time, fuel burn, costs), the utilisation of capacity (en-route and airport), and the environment (emissions).
For instance, whereas ATFM slots result in pre-departure delays mainly experienced at the stands, inefficiencies in the gate-to-gate phase (taxi, en route, terminal) also generate additional fuel burn. Although keeping an aircraft at the gate saves fuel - if it is held and capacity goes unused - the cost to the airline of the extra delay may exceed the fuel cost by far.
The table below provides an overview of how ANS can impact on airspace users’ operations in terms of time, fuel burn and associated costs. The cost aspect of ANS-related service quality is addressed in more detail in Chapter 2 and Annex IV of this report.
ANS- related impact on airspace users’ operations
Impact on punctuality
Engine status
Impact on fuel burn/ CO2 emissions
Impact on airspace users’ costs
AN
S r
elat
ed
inef
fici
enci
es
At stand Airport ATFM
High OFF Quasi nil Time En-route ATFM
Gate-to-gate
Taxi phase Low/
moderate ON High Time + fuel En-route phase
Terminal area
ANS-related impact on airspace users’ operations
For ANS-related delays at the gate (ATFM delays) the fuel burn is quasi-nil but the level of predictability in the scheduling phase is low. Hence, the impact of ATFM delays on punctuality and associated costs to airspace users is significant (i.e. “tactical” delays) but the impact on fuel burn and the environment is negligible45.
ANS-related inefficiencies in the gate-to-gate phase (taxi, en-route, terminal holdings) are generally more predictable than ATFM delays as they are more related to inefficiencies embedded in the air route network or congestion levels which are similar every day. From an airspace user point of view, the impact on punctuality is usually limited as those inefficiencies are usually already embedded in the scheduled block times (“strategic delays”). However, the impact in terms of additional time, fuel, costs, and the environment is significant.
The high level analysis of service quality in Chapter 2 is supported by a more detailed analysis of operational en-route ANS performance in Chapter 4 of this report. ANS-related performance at airports is evaluated in more detail in Chapter 5.
45 It is acknowledged that in some cases aircraft operators try to make up for ATFM delay encountered at the origin airport through increased speed which in turn may have a negative impact on total fuel burn for the entire flight.
125
ANNEX V – FRAMEWORK: ECONOMIC EVALUATION OF ANS PERFORMANCE
In Europe, airspace users bear the total economic costs of ANS services, which consist of ANS costs (en route and terminal) and quality of service related costs (due to ANS related inefficiencies). This Annex provides background information on the framework applied for the economic evaluation of ANS performance in Chapter 2 of this report.
The economic evaluation of ANS performance is an attempt to monetarise direct and indirect costs borne by airspace users in order to draw a consolidated high-level picture. As illustrated in the figure on the right side, while its primacy is fully recognised, it is not appropriate to include a monetary value for Safety. Hence the evaluation addresses ANS cost-efficiency and ANS-related operational performance, linked with demand capacity balancing. Balancing capacity and demand
Insufficient capacity has a negative impact on ANS-related service quality performance (high delays, etc.) and on airspace users’ costs; while the provision of capacity higher than demand contributes towards higher than necessary ANS charges (underutilisation of resources).
The total economic evaluation is useful to provide a consolidated high-level view on ANS performance and to promote discussions on future ANS performance objectives as:
it allows comparability of the different metrics as all (but Safety) are expressed in monetary terms;
it is easy to understand at high level (e.g. policy makers, executives, media, etc);
it provides a high-level view to assess the relative weight of the different KPAs and priorities for policy objectives; and,
it provides a high level framework to illustrate interdependencies and trade-offs among KPAs.
However, the concept has also drawbacks which limit its suitability at local level and for target setting purposes:
it relies on assumptions for the monetarisation of the cost of delays and fuel incurred by airspace users;
trade-offs will inevitably differ at a local/FAB level according to traffic characteristics, and the economic and working environment; and,
total economic costs do not indicate the scope for improvement in respective KPAs.
Chapter 2 of this report combines key results from the detailed analysis of ANS cost-efficiency in Chapter 6 and the evaluation of operational performance en route and at airports in Chapter 4 and 5 respectively.
While the ANS en route and terminal costs can be easily taken from Chapter 6, estimating costs to airspace users as a result of ANS-related inefficiencies is complex and requires expert judgement and assumptions, based on published statistics and robust data wherever possible. There are inevitably margins of uncertainty which need to be taken into account for the interpretation of the results.
Community perspective
Airspace User perspective
Air NavigationService providerPerspective
ANS charges
Service Quality (time, fuel inefficiency)
ANS Cost ‐efficiency
ECONOMY & ENVIRONMENT
Capacity
SAFETY
SafetyANS‐related operational performance
126
ANS-related inefficiencies impact on airspace users in terms of cost of time and fuel.
The monetarisation of ANS-related inefficiencies in terms of time in this report is based on the study from the University of Westminster [Ref. 18] which addresses estimated costs to airspace users. It does not address the wider costs of delay which may be applicable in contexts such as the full societal impact of delay.
Inefficiency costs are calculated separately for “strategic” delays (those accounted for in advance during the scheduling phase by adding buffer to the airline schedule) and “tactical” delays (those incurred on the day of operations and not accounted for in advance).
Costs of ANS-related inefficiencies The estimated airline delay costs in the University of Westminster study [Ref. 18] include direct costs (fuel, crew, maintenance, etc.) the network effect (i.e. cost of reactionary delays) and passenger related costs. Whilst passenger ‘value of time’ is an important consideration in wider transport economics, only those costs which impact on the airline’s business (rebooking, compensation, market share and passenger loyalty related costs) were included in the estimate. Estimates of future emissions costs from the EU emission trading scheme from 01 January 2012 were not included.
Hence, in this report, en route and airport ATFM delays were considered as being “tactical” (infrequent with a low level of predictability) and inefficiencies in the gate-to-gate phase (taxi out, en route, terminal) were considered to be “strategic”.
Although the main share of ANS-related inefficiencies in the gate-to-gate phase is largely predictable (route network, congestion, etc.), it is acknowledged that some of the inefficiencies are not fully predictable and therefore could be considered as being “tactical”. As there is presently no validated methodology for the quantification of “tactical” delay in the gate-to-gate phase, all inefficiencies in the gate-to-gate phase were considered to be “strategic” and therefore predictable during the scheduling phase.
COST OF “TACTICAL” DELAYS
“Tactical” delays occur infrequently and are therefore difficult to predict for airlines during the scheduling phase.
While the fuel burn is quasi nil, the impact on airspace users’ schedules is significant.
Due to the lower level of predictability and resulting passenger related (compensation, rebooking, etc.) and network (reactionary delay) related cost, time impact in terms of cost (one minute of “tactical” delay) is considered to be higher than for “strategic” delay (does not include costs for fuel burn).
The latest figures used for the computation of “tactical” delay in the report are provided in the adjacent grey box.
Cost of ATFM departure delays
Time: The “tactical” delay cost of one additional minute is estimated at €79 per minute (€2009 prices) on average for a flight in Europe (derived from [Ref. 18]. Due to the low level of predictability and resulting passenger and network costs, the cost of one additional minute of “tactical” delay is higher than the cost of one additional minute (strategic delay) embedded in the schedule (without fuel costs). Fuel: Costs are negligible the delay is usually experienced at the gate with engines off.
COST OF “STRATEGIC” DELAYS
Although not entirely predictable, a large share of the time inefficiencies experienced every day in the gate-to-gate phase (taxi-out, en-route, terminal holdings) is already accounted for in the “strategic” phase and reflected in the scheduled block times which limits the impact on punctuality.
127
Due to the lower impact on airline schedule and therefore lower costs for compensation, rebooking, reactionary delay etc., the cost of time of one minute “strategic” delay is lower than for “tactical” delay.
Additionally to the cost of time, the significant cost of additional fuel burn needs to be considered.
Fuel price is a major driver of costs, especially in the context of increasing jet fuel prices. After the drop in 2009, average jet fuel price increased again between 2009 and 2012. Compared to 2012, 2013 showed a slight decrease in jet fuel price (see grey box).
In view of the variation of jet fuel price over the past years and to enable time series analysis of ANS-related performance, the computations for the economic evaluation of ANS performance in Chapter 2 were normalised.
In order to remove variations due to changes in jet fuel prices, the 2013 average jet fuel price was consistently used for all years. Hence, the “real” cost might have been higher or lower in the individual years, depending on how the 2013 price compares to the price in the respective year.
The latest figures used for the computation of “strategic” delay in the report are provided in the adjacent grey box.
Cost of ANS-related inefficiencies in the gate to gate phase
The “strategic” delay costs in the gate-to-gate phase consist of a time and a fuel component. Time: The “strategic” delay cost of one additional minute (without fuel) is estimated at €27 per minute (€2009 prices) on average for a flight in Europe (derived from [Ref. 18]). Fuel: The fuel costs are based on the average annual spot price in 2012 expressed in (€2009 prices). The fuel price paid by airspace users was estimated to be 15% above the spot price and also includes a provision for fuel carriage penalties. Based STATFOR statistics and the assumptions above, the average jet fuel price in 2013 was calculated at 770 € per tonne (€2009).
Jet fuel price
FURTHER CONSIDERATIONS
It is important to point out that there are inevitably margins of uncertainty in the approximation of delay costs. Although the consolidated view of ANS-related costs to airspace provides a good high-level estimate, it is acknowledged that there is scope for further refinements.
The information used for the analysis in Chapter 2 was derived from and should be read in conjunction with the analyses, assumptions and limitations detailed in Chapters 4 to 6 of this report.
0100200300400500600700800900
200
4
200
5
200
6
200
7
200
8
200
9
201
0
201
1
201
2
201
3
Avg
. p
er
ton
[€2
00
9]
Estimated average jet fuel price paid by airspace users
Source: STATFOR
128
ANNEX VI – ANALYTICAL FRAMEWORK FOR ANS PERFORMANCE AT AIRPORTS
Airport operations performance is the result of complex interaction between many actors, inter-dependent processes and influencing factors. On the one hand, the various actors involved usually have different interests (airport authorities, airport operators, local ANSP, aircraft carriers, ground handlers, but also passengers, neighbourhood, trade unions, interaction with other airports and ATM network). On the other hand, several interdependent factors influence total airport performance (e.g. layout, traffic mix, operational procedures). Although some of these factors are intrinsic to the system and controllable within some limits, others are extrinsic and more difficult to alter or influence (e.g. weather, TMA that might be shared with other airports, environmental constraints including noise and local air quality).
Although this complexity is acknowledged, the ANS-related indicators presented in Chapter 5 aims at measuring performance in areas where ANS has a substantial influence. This chapter focuses on measuring how efficiently ANS balance capacity and demand at airports. Airport performance factors or requirements on improving airport capacity outside the responsibility of ANS (e.g. infrastructural measure, such as additional runways, taxiways, etc.) are not addressed by this report.
For the analysis of ANS-related performance from an airport perspective, the figure in Chapter 5 below builds on the framework as described here after.
Conceptual framework for the analysis of ANS-related performance at airports
The local interplay and smooth operation of the various airport processes is an essential enabler for the performance at an airport. The performance indicators presented in this chapter revolve around processes (i.e. inbound flow management, capacity-demand balancing, and outbound flow management) where ANS has a substantial influence locally and contributes to the network performance. In that context, ANS performance at airports targets and addresses the efficiency of gate-to-gate operations.
Airport (Declared) Capacity
Airport ATFM delays
Terminal holdings(ASMA)
Airport scheduling(utilisation
ratio)
Management of arrival flows
Actual throughput
Air Traffic Management
Airportresilience
En‐route phase(see Chapter 4)
Weather & Environmental restrictions
Taxi‐outLocal ATCTurn‐
around
Reac‐tionary
Air Traffic Management
En‐route phase(see Chapter 4)
Contribution to Network performance
Inbound Flow Management Capacity‐Demand Balancing Outbound Flow
Management
Contribution to Network performance
Performance Indicators
• ATFM slot adherence
• Airport arrival ATFM delays
• ASMA additional time• Additional taxi‐in time
• Exogenous Factors:– Weather– Environment
• Endogenous Factors–Peak declared capacity–Peak Service Rate–Airport resilience
• Local ATC delays• Additional taxi‐out time
• ATFM slot adherence
Enabling Concepts
• A‐CDM implementa‐tion status
• Arrival Manager (AMAN)•Risk Mgnt• Surface operations
• A‐CDM• Departure Manager (DMAN)• Surface operations
• A‐CDM• Departure Manager (DMAN)•Risk Mgnt•Surface operations
• A‐CDM implementa‐tionstatus;
Management of departure
flows
129
ANNEX VII – AIRPORT TRAFFIC AND AIRPORT ANS PERFORMANCE RECORDS
This Annex provides an overview of ANS-related performance measures at European airports.
The ASMA and taxi-out values reported in bold blue are based on the airport data flow whereas the values shown in black are based on the CFMU data flow (see paragraph 5.5.15 on page 87 for more information on data sources and quality).
The following information is provided for each of these airports:
The airport ICAO and IATA as well as the airport name in Columns 1 and 2;
In Column 3, the yearly passenger volume in 2012, as reported by the ACI-Europe, with the variation compared to 2012 (Column 4);
The total number of IFR movements in 2013 (Column 5), with the variation compared to 2012 (Column 6).
The six indicators analysed in the scope of demand/capacity balancing:
level of coordination, in Column 7.
Level 3 are coordinated airports, level 2 are schedule facilitated airports, and level 1 are neither coordinated nor schedule. Seasonal coordination status is represented by the season (S for summer and W for winter) followed by the coordination level (3, 2 or 1). For example, Ibiza, coordinated during the summer season and schedule facilitated during the winter season, is shown as S3W2.
peak declared capacity for arrivals (Column 8) and departures (Column 9)
peak service rate for arrivals (Column 10) and departures (Column 11)
ATFM slot adherence in Column 12.
The three indicators analysed in the scope of the arrival flow management:
The average Airport Arrival ATFM Delay (Column 13).
The Additional ASMA Time (Column 14).
The arrival punctuality in Column 15 (see Chapter 2)
The three last indicators analysed in the scope of the quality of service, from the management perspective:
The departure punctuality in Column 16 (see Chapter 2),
The ATC Pre-departure Delay at the gate (Column 17),
The Additional Taxi-out Time (Column 18).
The full table is sorted by increasing total number of IFR movements in 2013 (Column 5).
130
ICAO Name (IATA code)
Level of
Coordination
Peak
Declared
Capacity
Arr
(Mvts/hr)
Peak
Declared
Capacity
Dep
(Mvts/hr)
Peak
Service
Rate Arr
(Mvts/hr)
Peak
Service
Rate Dep
(Mvts/hr)
ATFM Slot
Adherenc
e
Arrival
ATFM
delay
(min/arr)
Add. ASMA
Time
(min/arr)
Arrival
punctuality
(Arrrivals
delay
between ‐15
to 15 min)
Departure
punctuality
(Departure
delay
between ‐15
to 15 min)
ATC
departure
delay
(min/dep)
Add. Taxi‐
out Time
(min/dep)
Data source EUACA EUACA EUACA NM NM NM NM Apt. Data CODA CODA CODA Apt. data
2013 vs. 2012 2013 vs.2012 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013 2013
LFPG Paris Charles de Gaulle 62.1 0.7% 478 ‐3.6% 3 62 67 68 64 82% 0.7 0.9 71% 75% 0.59 4.5
EDDF Frankfurt 58.3 0.9% 473 ‐1.7% 3 52 52 56 56 91% 0.9 2.9 73% 83% 1.28 4.1
EGLL London Heathrow 72.4 3.3% 472 ‐0.5% 3 44 46 46 49 83% 2.6 9.2 61% 74% 0.55 8.3
EHAM Schiphol Amsterdam 52.6 3.0% 436 0.8% 3 68 74 65 69 86% 1.3 1.4 66% 83% 1.25 3.0
LEMD Madrid Barajas 39.7 ‐12.1% 333 ‐10.5% 3 48 50 43 50 96% 0.2 0.7 62% 81% 0.58 3.9
EDDM Munich 38.7 0.8% 379 ‐3.8% 3 58 58 58 59 93% 0.5 2.2 77% 85% 0.62 3.7
LIRF Rome Fiumicino 36.2 ‐2.2% 302 ‐3.5% 3 54 60 49 44 88% 0.4 1.6 70% 70% 2.47 6.6
LTBA Istanbul Atatürk 51.1 13.6% 395 12.3% 3 N/A N/A 33 34 76% 0.5 4.0 64% 85% 2.30 6.5
LEBL Barcelona 35.2 0.2% 276 ‐4.4% 3 38 36 35 34 95% 0.1 1.3 69% 83% 0.36 4.4
LOWW Vienna 22.0 ‐0.7% 248 ‐5.1% 3 48 50 42 43 87% 1.2 2.2 74% 86% 0.46 3.1
LSZH Zurich 24.8 0.3% 255 ‐2.2% 3 36 44 38 42 85% 2.6 3.3 74% 78% 1.62 3.6
EKCH Copenhagen 24.0 3.2% 245 1.1% 3 52 55 35 36 92% 0.1 1.1 78% 86% 0.05 2.0
EGKK London Gatwick 35.4 3.6% 251 1.7% 3 30 34 28 32 88% 0.6 2.7 62% 77% 0.55 4.8
LFPO Paris Orly 28.3 3.8% 234 0.1% 3 34 36 33 32 80% 0.8 1.1 73% 75% 0.37 2.2
ENGM Oslo Gardermoen 23.0 4.0% 241 2.6% 3 32 40 33 36 97% 1.1 2.1 77% 84% 0.06 2.5
EBBR Brussels 19.1 0.9% 211 ‐2.9% 3 48 44 35 34 94% 0.8 1.2 69% 81% 0.51 2.6
EDDL Duesseldorf 21.2 2.2% 210 ‐2.7% 3 33 36 31 33 92% 0.5 1.5 74% 80% 0.66 2.7
ESSA Stockholm Arlanda 20.7 5.3% 220 4.9% 3 42 42 32 33 95% 0.3 0.9 79% 87% 0.06 1.8
LIMC Milano Malpensa 17.9 ‐3.1% 165 ‐5.5% 3 40 30 24 25 96% 0.0 0.9 68% 81% 0.50 3.2
EFHK Helsinki Vantaa 15.3 2.8% 168 ‐2.0% 3 48 42 34 34 87% 0.1 0.8 75% 89% 0.18 2.0
LEPA Palma de Mallorca 22.8 0.4% 169 ‐2.0% 3 33 33 32 32 95% 0.9 1.4 70% 79% 0.47 2.9
LSGG Geneva 14.3 3.9% 178 ‐1.4% 3 22 36 23 24 89% 2.0 2.2 72% 82% 0.28 3.0
LGAV Athens 12.5 ‐3.2% 135 ‐9.1% 2 22 22 20 21 89% 0.0 0.5 73% 85% 0.37 1.2
EGCC Manchester 20.8 5.0% 169 0.5% 3 33 37 24 27 83% 0.3 1.9 63% 77% 0.60 3.9
EDDT Berlin Tegel 19.6 7.1% 173 2.6% 3 30 30 27 26 90% 0.5 1.5 77% 80% 0.64 0.7
EIDW Dublin 20.2 5.6% 169 4.6% 3 29 31 21 29 84% 0.1 1.7 66% 84% 0.46 3.7
LTAI Antalya 27.4 8.5% 166 6.8% S3W2 N/A N/A 27 27 69% 0.4 1.2 70% 78% 0.85 2.9
EGSS London Stansted 17.8 2.2% 143 1.2% 3 36 35 21 26 89% 0.0 0.6 67% 87% 0.33 2.0
EDDH Hamburg 13.5 ‐1.4% 137 ‐5.1% 2 27 27 21 23 90% 0.2 1.7 78% 82% 0.26 1.7
LPPT Lisbon 16.0 4.6% 146 1.5% 3 26 26 20 22 88% 0.3 1.3 61% 71% 0.89 2.7
LKPR Prague 11.0 1.5% 125 ‐2.3% 3 33 33 21 22 87% 0.2 1.6 70% 83% 0.5 2.4
EPWA Warsaw 10.7 11.4% 142 3.1% 3 28 26 22 22 87% 0.2 1.4 72% 81% 0.2 3.3
LFMN Nice Cote d Azur 11.6 3.3% 140 ‐1.3% 3 28 30 24 25 82% 0.5 2.5 71% 78% 0.4 1.5
EDDK Koeln Bonn 9.1 ‐5.7% 117 ‐4.2% 2 40 40 20 21 92% 0.0 0.6 73% 82% 0.2 1.2
EDDS Stuttgart 9.6 ‐1.5% 114 ‐4.6% 3 32 32 19 22 93% 0.0 0.6 77% 86% 0.1 2.7
LFLL Lyon Satolas 8.6 1.3% 116 ‐2.6% 3 36 36 29 29 89% 0.7 1.1 72% 83% 0.2 1.6
LIML Milano Linate 9.0 ‐2.1% 112 ‐5.2% 3 20 20 17 19 97% 0.0 0.6 78% 89% 0.4 2.6
LTFJ Istanbul Sabiha Gökçen 18.8 27.0% 145 19.3% 2 N/A N/A 18 20 70% 0.1 0.6 74% 86% 0.7 2.6
EGPH Edinburgh 9.8 6.3% 110 0.9% 2 N/A N/A 16 18 88% 0.0 1.2 65% 84% 0.2 2.1
LFML Marseille Provence 8.3 ‐0.4% 103 ‐3.5% 1 N/A N/A 15 16 81% 0.3 2.2 76% 82% 0.2 1.5
LEMG Malaga 12.9 2.7% 100 0.0% 3 25 25 19 19 89% 0.1 0.7 65% 81% 0.3 2.3
GCLP Gran Canaria 9.8 ‐1.2% 94 ‐4.7% 3 24 24 17 17 88% 0.2 1.2 N/A N/A 0.3 1.5
UKBB Boryspil 7.9 ‐6.5% 81 ‐18.4% 3 48 44 16 17 0% 0.1 N/A 71% 79% 0.0 2.2
LHBP Budapest 8.5 0.2% 84 ‐4.1% 2 26 30 15 15 93% 0.0 0.9 73% 83% 0.1 0.8
EGGW London Luton N/A N/A 97 ‐0.9% 3 22 21 14 18 83% 0.0 1.7 64% 81% 0.6 2.8
ENBR Bergen Flesland 5.9 7.6% 100 3.3% 3 15 15 15 16 96% 0.1 0.9 81% 87% 0.0 1.2
LFBO Toulouse Blagnac 7.6 0.1% 91 ‐5.1% 1 N/A N/A 15 16 92% 0.4 1.3 73% 84% 0.2 1.1
EGBB Birmingham 9.1 2.2% 92 1.2% 2 N/A N/A 14 16 78% 0.1 0.6 65% 80% 0.2 1.5
LIPZ Venezia 8.4 2.6% 81 ‐3.4% 3 16 14 15 14 89% 0.3 1.1 71% 79% 0.5 2.0
LROP Bucharest Otopeni 7.6 7.4% 88 1.7% 1 N/A N/A 13 14 91% 0.0 1.4 73% 84% 0.3 2.1
EGPF Glasgow 7.4 2.9% 78 0.7% 2 N/A N/A 12 14 89% 0.0 0.8 66% 84% 0.2 1.7
LTAC Ankara Esenboğa 11.0 18.2% 91 12.6% 2 N/A N/A 15 16 59% 0.0 1.1 81% 89% 0.3 2.3
ENZV Stavanger Sola 4.4 6.4% 79 4.6% 3 15 15 13 13 96% 0.2 0.7 79% 86% 0.0 1.3
EDDB Berlin Schönefeld 6.6 ‐7.3% 63 ‐8.5% 3 20 20 12 11 90% 0.0 0.9 68% 84% 0.2 1.9
LIME Bergamo 9.0 0.8% 71 ‐3.2% 3 16 16 11 13 93% 0.0 1.0 67% 82% 0.4 1.7
LEAL Alicante 9.6 8.9% 68 9.3% 3 18 18 13 12 95% 0.0 0.7 66% 79% 0.2 1.9
EVRA Riga 4.8 0.5% 67 ‐1.4% 1 N/A N/A 15 18 88% 0.0 0.6 70% 86% 0.1 2.2
ELLX Luxembourg 2.2 14.5% 58 2.2% 1 15 15 11 11 83% 0.1 0.8 77% 88% 0.3 1.1
LCLK Larnaca 4.9 ‐6.2% 41 ‐12.5% 2 10 10 9 9 87% 0.1 0.3 63% 80% 0.2 1.0
LYBE Belgrad 3.5 5.4% 50 4.9% 1 N/A N/A 8 8 86% 0.0 1.2 75% 81% 0.2 1.3
LBSF Sofia 3.5 1.1% 40 ‐7.3% 2 11 11 7 7 97% 0.0 0.6 73% 85% 0.2 0.9
LDZA Zagreb 2.3 ‐2.2% 35 ‐3.0% 1 N/A N/A 8 8 89% 0.0 0.7 78% 82% 0.1 1.3
EETN Tallinn 2.0 ‐10.9% 34 ‐23.8% 1 N/A N/A 8 10 98% 0.0 0.5 77% 87% 0.0 0.7
LMML Malta 4.1 10.9% 36 7.7% 2 N/A N/A 6 6 95% 0.0 0.6 69% 83% 0.1 1.4
LJLJ Ljubjana N/A N/A 27 ‐5.3% 2 20 20 5 6 94% 0.0 0.7 70% 81% 0.1 1.3
EYVI Vilnius 2.7 20.7% 32 8.8% 1 N/A N/A 5 6 89% 0.0 1.1 75% 85% 0.0 1.0
LZIB Bratislava N/A N/A 18 ‐5.3% 2 N/A N/A 4 4 93% 0.0 0.8 68% 78% 0.1 1.1
LATI Tirana 1.8 5.5% 20 ‐2.8% 1 N/A N/A 4 4 70% 0.0 1.0 71% 82% 0.1 0.6
UDYZ Zvartnots 1.7 ‐0.1% 17 ‐16.0% 1 N/A N/A 4 4 77% 0.0 0.0 63% 66% 0.4 N/A
LUKK Chiș inău 1.3 8.2% 17 8.9% 1 N/A N/A 3 4 95% 0.0 0.7 74% 76% 0.1 0.9
LYPG Podgorica N/A 8.2% 11 ‐1.1% 1 N/A N/A 2 2 97% 0.0 0.7 78% 80% 0.2 0.9
LQSA Sarajevo N/A 15.0% 10 5.0% 1 N/A N/A 3 2 N/A 0.0 0.7 77% 80% 0.0 0.7
LWSK Skopje N/A 17.8% 11 8.0% 2 N/A N/A 2 2 88% 0.0 0.5 66% 75% 0.1 0.5
ACI NM
DEMAND VS CAPACITY BALANCING ARRIVAL TRAFFIC FLOW DEPARTURE TRAFFIC FLOW
Passengers (MPax)
IFR
movements
('000)
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ANNEX VIII - GLOSSARY
ACC Area Control Centre. That part of ATC that is concerned with en-route traffic coming from or going
to adjacent centres or APP. It is a unit established to provide air traffic control service to controlled flights in control areas under its jurisdiction.
Accident (ICAO Annex 13)
An occurrence associated with the operation of an aircraft which takes place between the time any person boards the aircraft with the intention of flight until such time as all such persons have disembarked, in which: a) a person is fatally or seriously injured as a result of:
Being in the aircraft, or Direct contact with any part of the aircraft, including parts which have become detached
from the aircraft, or Direct exposure to jet blast,
except when the injuries are from natural causes, self-inflicted or inflicted by other persons, or when the injuries are to stowaways hiding outside the areas normally available to the passengers and crew; or b) the aircraft sustains damage or structural failure which:
Adversely affects the structural strength, performance or flight characteristics of the aircraft, and
Would normally require major repair or replacement of the affected component, except for engine failure or damage, when the damage is limited to the engine, its cowlings or accessories, or for damage limited to propellers, wing tips, antennas, tyres, brakes, fairings, small dents or puncture holes in the aircraft skin;
c) the aircraft is missing or completely inaccessible.
A-CDM Airport Collaborative Decision-Making
ACE Reports Air Traffic Management Cost-Effectiveness (ACE) Benchmarking Reports
ACI Airports Council International (http://www.aci-europe.org/)
AEA Association of European Airlines (http://www.aea.be)
Aena Aeropuertos Españoles y Navegación Aérea, ANS Provider - Spain
Agency The EUROCONTROL Agency
AIP Aeronautical Information Publication
Airside The aircraft movement area (stands, apron, taxiway system, runways etc.) to which access is controlled.
Airspace Infringement
(also known as unauthorised penetration of airspace). The penetration by an aircraft into a portion of airspace without prior permission of the appropriate authorities (when such prior permission is required). EUROCONTROL HEIDI – ESARR 2 taxonomy
AIS Aeronautical Information Service
ALAQS EUROCONTROL Airport Local Air Quality Studies
AMAN Arrival Management Function
ANS Air Navigation Service. A generic term describing the totality of services provided in order to ensure the safety, regularity and efficiency of air navigation and the appropriate functioning of the air navigation system.
ANS CR Air Navigation Services of the Czech Republic. ANS Provider - Czech Republic.
ANSP Air Navigation Services Provider
AO Aircraft Operator
APP Approach Control Unit
APU Auxiliary Power Units
ARMATS Armenian Air Traffic Services, ANS Provider - Armenia
ARN V8 ATS Route Network (ARN) - Version 8
ASK Available seat-kilometres (ASK): Total number of seats available for the transportation of paying passengers multiplied by the number of kilometres flown
ASM Airspace Management
ASMA Arrival Sequencing and Metering Area
ASMT EUROCONTROL Automatic Safety Monitoring Tool
AST Annual Summary Template
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ATC Air Traffic Control. A service operated by the appropriate authority to promote the safe, orderly and expeditious flow of air traffic.
ATCO Air Traffic Control Officer
ATFCM Air Traffic Flow and Capacity Management.
ATFM Air Traffic Flow Management. ATFM is established to support ATC in ensuring an optimum flow of traffic to, from, through or within defined areas during times when demand exceeds, or is expected to exceed, the available capacity of the ATC system, including relevant aerodromes.
ATFM delay (NMD definition)
The duration between the last Take-Off time requested by the aircraft operator and the Take-Off slot given by the EUROCONTROL Network Management Directorate
ATFM Regulation When traffic demand is anticipated to exceed the declared capacity in en-route control centres or at the departure/arrival airport, ATC units may call for “ATFM regulations”.
ATK Available tonne kilometres (ATK) is a unit to measure the capacity of an airline. One ATK is equivalent to the capacity to transport one tonne of freight over one kilometre.
ATM Air Traffic Management. A system consisting of a ground part and an air part, both of which are needed to ensure the safe and efficient movement of aircraft during all phases of operation. The airborne part of ATM consists of the functional capability which interacts with the ground part to attain the general objectives of ATM. The ground part of ATM comprises the functions of Air Traffic Services (ATS), Airspace Management (ASM) and Air Traffic Flow Management (ATFM). Air traffic services are the primary components of ATM.
ATMAP ATM Performance at Airports
ATS Air Traffic Service. A generic term meaning variously, flight information service, alerting service, air traffic advisory service, air traffic control service.
Austro Control Austro Control: Österreichische Gesellschaft für Zivilluftfahrt mbH, ANS Provider - Austria
AVINOR ANS Provider - Norway
Belgocontrol ANS Provider - Belgium
BULATSA Air Traffic Services Authority of Bulgaria. ANS Provider - Bulgaria.
CAA Civil Aviation Authority
CANSO Civil Air Navigation Services Organisation (http://www.canso.org)
CDA Continuous Descent Approach
CDM Collaborative Decision Making
CDR Conditional Routes
CEF Capacity Enhancement Function
CFMU (See NMD) Formerly the EUROCONTROL Central Flow Management Unit. Now the EUROCONTROL Network Management Directorate (NMD)
CLR Deviation from ATC clearance
CMA Continuous Monitoring Approach (ICAO USOAP Cycle)
CNS Communications, Navigation, Surveillance.
CO2 Carbon dioxide
CODA EUROCONTROL Central Office for Delay Analysis
Composite flight hour
En-route flight hours plus IFR airport movements weighted by a factor that reflected the relative importance of terminal and en-route costs in the cost base (see ACE reports)
CRCO EUROCONTROL Central Route Charges Office
Croatia Control Hrvatska kontrola zračne plovidbe d.o.o. ANS Provider - Croatia,
CTOT Calculated Take-Off Time
Dangerous Phenomena
The principal dangerous weather phenomena are: Cumulonimbus (CB) with or without precipitation, Tower Cumulus (TCU), Thunder with or without precipitation (TS) , Ice Pellets (PL),Small Hail and/or Snow Pellets (GS); Hail (GR), Funnel cloud (tornado or waterspout) (FC) , Squall (SQ) , Volcanic Ash (VA), Dust-storm (DS), Sandstorm (SS), Sand (SA), Dust/sand whirls (PO)
DCAC Cyprus Department of Civil Aviation of Cyprus. ANS Provider - Cyprus.
DFS DFS Deutsche Flugsicherung GmbH, ANS Provider - Germany
DGCA Directors General of Civil Aviation
DHMi Devlet Hava Meydanlari Isletmesi Genel Müdürlügü (DHMi), General Directorate of State Airports Authority, Turkey. ANS Provider – Turkey.
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DSNA Direction des Services de la Navigation Aérienne. ANS Provider - France
DSS/OVS/SAF Unit EUROCONTROL Directorate Single Sky/Oversight/Safety Unit. Formerly the Safety Regulation Unit.
DUR Determined Unit Rate
EAD European AIS Database
EANS Estonian Air Navigation Services. ANS Provider – Estonia.
EAPPRI European Action Plan for the Prevention of Runway Incursions
EASA European Aviation Safety Agency
EATM European Air Traffic Management (EUROCONTROL)
EATMN European Air Traffic Management Network (SES legislation) chapter 5 §5.2.28)
EC European Commission
ECAC European Civil Aviation Conference.
ECCAIRS European accident and incident database
ECTL Acronym for EUROCONTROL
EEA European Economic Area (EU Member States + Iceland, Norway and Lichtenstein)
EEA European Environmental Agency
Effective capacity The traffic level that can be handled with optimum delay (cf. PRR 5 (2001) Annex 6)
ENAV ENAV S.p.A. - Italian Company for Air Navigation Services
EoSM Effectiveness of Safety Management
ERA European Regional Airlines Association (http://www.eraa.org)
ESRA 2008 Area European Statistical Reference Area (see STATFOR Reports) Albania, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Canary Islands, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, FYROM, Germany, Greece, Hungary, Ireland, Italy, Lisbon FIR, Luxembourg, Malta, Moldova, Montenegro, Netherlands, Norway, Poland, Romania, Santa Maria FIR, Serbia, Slovak Republic , Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine, United Kingdom
ESSIP European Single Sky ImPlementation plan
EU European Union
EU States The member States of the European Union.
EU-ETS Emissions Trading Scheme. The objective of the EU ETS is to reduce greenhouse gas emissions in a cost-effective way and contribute to meeting the EU’s Kyoto Protocol targets.
EUROCONTROL The European Organisation for the Safety of Air Navigation. It comprises Member States and the Agency.
EUROCONTROL Member States
Albania, Armenia, Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Spain, Sweden, Switzerland, The former Yugoslav Republic of Macedonia, Turkey, Ukraine and United Kingdom of Great Britain and Northern Ireland
EUROCONTROL Route Charges System
A regional cost-recovery system that funds air navigation facilities and services and supports Air Traffic Management developments. It is operated by the EUROCONTROL Central Route Charges Office (CRCO), based in Brussels. www.eurocontrol.int/crco
EUROSTAT The Statistical Office of the European Community
FAB Functional Airspace Blocks
FABEC States Belgium, France, Germany, Luxembourg, the Netherlands and Switzerland
FINAVIA ANS provider – Finland
FIR Flight Information Region. An airspace of defined dimensions within which flight information service and alerting service are provided.
FL Flight Level. Altitude above sea level in 100 feet units measured according to a standard atmosphere. Strictly speaking a flight level is an indication of pressure, not of altitude. Only above the transition level (which depends on the local QNH but is typically 4000 feet above sea level) flight levels are used to indicate altitude, below the transition level feet are used.
FMP Flow Management Position
FUA Flexible Use of Airspace
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FYROM Former Yugoslav Republic of Macedonia
GA (General Aviation)
All civil aviation operations other than scheduled air services and non-scheduled air transport operations for remuneration or hire.
GAT General Air Traffic. Encompasses all flights conducted in accordance with the rules and procedures of ICAO.PRR 2012 uses the same classification of GAT IFR traffic as STATFOR:
GCD Great Circle Distance
GDP Gross Domestic Product
HCAA Hellenic Civil Aviation Authority. ANS Provider - Greece
HungaroControl ANS Provider - Hungary
IAA Irish Aviation Authority. ANS Provider - Ireland
IATA International Air Transport Association (www.iata.org)
ICAO International Civil Aviation Organization
IFR Instrument Flight Rules. Properly equipped aircraft are allowed to fly under bad-weather conditions following instrument flight rules.
Incident (ICAO Annex 13)
An occurrence, other than an accident, associated with the operation of an aircraft which affects or could affect the safety of operation.
Incident Category A (ICAO Doc 4444)
A serious incident: AIRPROX - Risk Of Collision: “The risk classification of an aircraft proximity in which serious risk of collision has existed”.
Incident Category B (ICAO Doc 4444)
A major incident. AIRPROX - Safety Not Assured: “The risk classification of an aircraft proximity in which the safety of the aircraft may have been compromised”.
IS Inadequate separation
JC Just culture
The EUROCONTROL definition of “just culture”, also adopted by other European aviation stakeholders, is a culture in which “front line operators or others are not punished for actions, omissions or decisions taken by them that are commensurate with their experience and training, but where gross negligence, wilful violations and destructive acts are not tolerated.”
JRC EC Joint Research Centre
KPA Key Performance Area
KPI Key Performance Indicator
LAQ Local Air Quality
LFV Luftfartsverket. ANS Provider - Sweden.
LGS SJSC Latvijas Gaisa Satiksme (LGS). ANS Provider - Latvia
LPS Letové Prevádzkové Služby. ANS Provider - Slovak Republic
LSSIP Local Single Sky ImPlementation plans/reports (formerly Local Convergence and Implementation Plans)
LTO Landing and Take-off Cycle
LVNL Luchtverkeersleiding Nederland. ANS Provider - Netherlands
Maastricht UAC The EUROCONTROL Upper Area Centre (UAC) Maastricht. It provides ATS in the upper airspace of Belgium, Luxembourg, Netherlands and Northern Germany.
MAC Mid-air collision
MATS Malta Air Traffic Services Ltd. ANS Provider - Malta
MET Meteorological Services for Air Navigation
METAR Meteorological Terminal Aviation Routine Weather Report or Meteorological Aerodrome Report
MIL Military flights
M-NAV M-NAV - Macedonian Air Navigation Service Provider, PCL. ANS provider in the Republic of Macedonia
MoldATSA Moldavian Air Traffic Services Authority. ANS Provider - Moldova
MTOW Maximum Take-off Weight
MUAC Maastricht Upper Area Control Centre, EUROCONTROL
NATA Albania National Air Traffic Agency. ANS Provider - Albania
NATS National Air Traffic Services. ANS Provider - United Kingdom
NAV Portugal Navegação Aérea de Portugal – NAV Portugal, E.P.E.
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NAVIAIR Naviair, Air Navigation Services. ANS Provider – Denmark
NERL NATS (En Route) Limited
NM Nautical mile (1.852 km)
NM Network Manager
NMD EUROCONTROL Network Management Directorate (formerly the EUROCONTROL Central Flow Management Unit - CFMU).
NO2 Nitrogen dioxide
NOP Network Operations Plan
NSA National supervisory Authorities
OAT Operational Air Traffic
Occurrence (Source: ESARR 2)
Accidents, serious incidents and incidents as well as other defects or malfunctioning of an aircraft, its equipment and any element of the Air Navigation System which is used or intended to be used for the purpose or in connection with the operation of an aircraft or with the provision of an air traffic management service or navigational aid to an aircraft.
OPS Operational Services
Organisation See “EUROCONTROL”.
Oro Navigacija State Enterprise Oro Navigacija. ANS Provider - Lithuania
PANSA Polish Air Navigation Services Agency. ANS Provider - Poland
Passenger Load factor
Revenue passenger-kilometres (RPK) divided by the number of available seat-kilometres (ASK).
PC Provisional Council of EUROCONTROL
Permanent Commission
The governing body of EUROCONTROL. It is responsible for formulating the Organisation’s general policy.
PI Performance Indicator
PRB Performance Review Body of the Single European Sky
PRC Performance Review Commission
Primary Delay A delay other than reactionary
Productivity Hourly productivity is measured as Flight-hours per ATCO-hour (see ACE reports)
PRR Performance Review Report (i.e. PRR 2013 covering the calendar year 2013)
PRU Performance Review Unit
R&D Research & Development
RAD Route availability document
RAT Risk Analysis Tool for Safety
Reactionary delay Delay caused by late arrival of aircraft or crew from previous journeys
Revised Convention Revised EUROCONTROL International Convention relating to co-operation for the Safety of Air Navigation of 13 December 1960, as amended, which was opened for signature on 27 June 1997.
RI Runway incursion: Any unauthorised presence on a runway of aircraft, vehicle, person or object where an avoiding action was required to prevent a collision with an aircraft. Source: ESARR 2.
ROMATSA Romanian Air Traffic Services Administration. ANS Provider - Romania
RP1 First Reference Period (2012-2014) of the SES Performance Scheme
RP2 Second Reference Period (2015-2019) of the SES Performance Scheme
RPK Revenue passenger-kilometre (RPK): One fare-paying passenger transported one kilometre.
RTK Revenue Tonne Kilometre
RVSM Reduced Vertical Separation Minima
Serious incident (ICAO Annex 13)
An incident involving circumstances indicating that an accident nearly occurred.
SES Single European Sky (EU)
SES States The 27 EU States (see “EU States” above) plus Norway and Switzerland
SESAR The Single European Sky ATM Research programme
Severity The severity of an accident is expressed according to:
the level of damage to the aircraft (ICAO Annex 13 identifies four levels: destroyed: substantially destroyed, slightly damaged and no damage);
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the type and number of injuries (ICAO Annex 13 identifies three levels of injuries: fatal, serious and minor/none).
PRRs focus on Severity A (Serious Incident) and Severity B (Major Incident).
SFMS Framework Maturity Survey (SFMS
Skyguide ANS Provider - Switzerland
Slot (ATFM) A take-off time window assigned to an IFR flight for ATFM purposes
Slovenia Control ANS Provider - Slovenia
SM Separation Minima is the minimum required distance between aircraft. Vertically usually 1000 ft below flight level 290, 2000 ft above flight level 290. Horizontally, depending on the radar, 3 NM or more. In the absence of radar, horizontal separation is achieved through time-separation (e.g. 15 minutes between passing a certain navigation point).
SMATSA Serbia and Montenegro Air Traffic Services Agency
SMI Separation Minima Infringement: A situation in which prescribed separation minima were not maintained between aircraft.
SMI Separation minima infringement.
SMS Safety Management System
SOx Sulphur oxide gases
SPI Safety Performance Indicator
SRC Safety Regulation Commission
SRU (see DSS/OVS/SAF)
SSC Single Sky Committee
SSP State Safety Programme
STATFOR EUROCONTROL Statistics & Forecasts Service
SU Service Units
SUA Special Use Airspace
TCZ Terminal Charging Zone
TMA Terminal manoeuvring area
TOBT Target Off-Block Time
TRA Temporary Reserved Area
TSA Temporary Segregated Area
TSAT Target Start-up Approval Time
UAC Upper Airspace Area Control Centre
UAP Unauthorised penetration of airspace (also known as Airspace Infringement). The penetration by an aircraft into a portion of airspace without prior permission of the appropriate authorities (when such prior permission is required). EUROCONTROL HEIDI – ESARR 2 taxonomy
UK CAA United Kingdom Civil Aviation Authority
UK NATS United Kingdom National Air Traffic Services
UkSATSE Ukrainian State Air Traffic Service Enterprise. ANS Provider - Ukraine
UR Unit Rate
USOAP ICAO Universal Safety Oversight Audit Programme
UUP Updated Airspace Use Plan
VFR Visual Flight Rules
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ANNEX IX - REFERENCES
PRC documentation can be consulted and downloaded from the PRC website
http://www.EUROCONTROL.int/prc
1 Article 1 of the PRC’s Terms of Reference, adopted in 2003.
2 Performance Review Commission, Performance Review Report 2012 (PRR 2012). An assessment of Air Traffic Management in Europe during the calendar year 2012 (May 2013).
3 Regulation (EC) No 549/2004 of the European Parliament and of the Council laying down the framework for the creation of the Single European Sky (“Framework Regulation”).
4 Commission Regulation (EC) No 691/2010 of 29 July 2010 laying down a performance scheme for air navigation services and network functions, OJ L 201, 3.8.2010, p.1.
5 Commission Decision of 29.7.2010 on the designation of the Performance Review Body of the Single European Sky C (2010)5134 final.
6 Commission Regulation (EC) No 1794/2006 of 6 December 2006 laying down a common charging scheme for air navigation services.
7 EUR Region Performance Framework Document (EUR Doc 030).
8 Performance Review Commission and FAA-ATO, “U.S./Europe Comparison of ATM-related Operational Performance 2008”, (October 2009).
9 Performance Review Commission and FAA-ATO, “U.S./Europe Comparison of ATM-Related Operational Performance 2010”, (April 2012).
10 Performance Review Commission and FAA-ATO, “U.S./Europe Comparison of ATM-Related Operational Performance 2012”, (November 2013).
11 Airservices Australia, and University of New South Wales, “Analysis of Australian ATM-Related Operational Performance”, October 2012.
12 EUROCONTROL STATFOR 7-year forecast, May 2013.
13 EUROCONTROL STATFOR 7-year forecast, February 2014.
14 Association of European Airlines, Press Release of 17. January 2014.
15 Performance Review Commission. “Complexity Metrics for ANSP Benchmarking Analysis”. Report by the ACE Working Group on complexity, 2006.
16 European Environment Agency (EEA), Greenhouse Gas Emissions by IPCC sector available at: http://dataservice.eea.europa.eu/pivotapp/pivot.aspx?pivotid=475
17 Commission Implementing Regulation (EU) No 390/2013 of 03 May 2013 laying down a performance scheme for air navigation services and network functions. OJ L 128, 9.5.2013, p.1
18 European airline delay cost reference values (University of Westminster), Final report (Version 3.2), (March, 2011).
19 Safety Review Commission, "Annual Safety Report for 2013", (February, 2014).
20 SES Performance Scheme Annual monitoring Report 2012, September 2013.
21 Local Single Sky ImPlementation plans/reports available at: https://www.eurocontrol.int/articles/lssip.
22 Performance Review Commission “Evaluation of Vertical flight-efficiency” (March 2008).
23 Single European Sky - Meta Data available at: http://prudata.webfactional.com/wiki/index.php/Category:SES_Meta-Data.
24 European Route Network Improvement Plan (ERNIP) 2013-2015.
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25 Commission Implementing Regulation (EU) No 677/2011 of 7 July 2011 laying down the detailed rules for the implementation of air traffic management (ATM) network functions and amending Regulation (EU) No 691/2010.
26 Commission Regulation (EC) No 2150/2005 of 23 December 2005 laying down common rules for the flexible use of airspace.
27 Flight Plan & ATFCM Adherence campaign initiated by DMEAN and the Network Operations Centre (CFMU) in April 2009.
28 Commission Regulation (EU) No 255/2010 of 25 March 2010 laying down common rules on air traffic flow management.
29 ATM Airport Performance (ATMAP) Framework, Report commissioned by the PRC (December 2009).
30 Airport Collaborative Decision Making Leaflet available at http://www.euro-cdm.org/.
31 Algorithm to describe weather conditions at European airports (ATMAP weather algorithm [version 2.3]) prepared by the Performance Review Unit in consultation with the ATMAP MET Working Group; May 2011.
32 Baumgartner et al. 2013, “What are the pre-requisites for managing a critical infrastructure such as Air Traffic Management?”, Network Industries Quarterly, Vol. 15, num 4.
33 Commission Regulation (EC) No 1794/2006 of 6 December 2006 laying down a common charging scheme
for air navigation services.
34 EUROCONTROL Specification for Economic Information Disclosure, Edition 3.0, 4 December 2012.
35 SES Performance Scheme Annual monitoring Report 2012, September 2013.
36 ATM Cost-effectiveness (ACE) 2012 Benchmarking Report. Report commissioned by the Performance Review Commission.
37 Directive 2009/12/EC of the European Parliament and of the Council of 11 March 2009 on airport charges. OJ L 70, 14.302009, page 11.
About the Performance Review Commission
The Performance Review Commission (PRC) provides independent advice on European Air Traffic Management (ATM) Performance to the EUROCONTROL Commission through the Provisional Council.
The PRC was established in 1998, following the adoption of the European Civil Aviation Conference (ECAC) Institutional Strategy the previous year. A key feature of this Strategy is that “an independent Performance Review System covering all aspects of ATM in the ECAC area will be established to put greater emphasis on performance and improved cost-effectiveness, in response to objectives set at a political level”.
The PRC reviews the performance of the European ATM System under various Key Performance Areas. It proposes performance targets, assesses to what extent agreed targets and high-level objectives are met and seeks to ensure that they are achieved. The PRC/PRU ana-lyses and benchmarks the cost-effectiveness and productivity of Air Navigation Service Providers in its annual ATM cost-effectiveness (ACE) Benchmarking reports. It also produces ad hoc reports on specific subjects.
Through its reports, the PRC seeks to assist stakeholders in understanding from a global perspective why, where, when, and possibly how, ATM performance should be improved, in knowing which areas deserve special attention, and in learning from past successes and mistakes. The spirit of these reports is neither to praise nor to criticise, but to help everyone involved in effectively improving perfor-mance in the future.
The PRC holds 5 plenary meetings a year, in addition to taskforce and ad hoc meetings. The PRC also consults with stakeholders on specific subjects.
Mr. Laurent Barthelemy Ms. Marja Hutchings Mr. Marc Baumgartner General Giorgio IscraMr. Nils Billinger Mr. Antero Lahtinen Vice ChairmanMr. René Brun Ms. Anne LambertMr. Juan Bujia-Lorenzo Professor Dr. Hans-Martin NiemeierCaptain Hasan Erdurak Mr. Ralph Riedle Chairman
PRC Members must have senior professional experience of air traffic management (planning, technical, operational or economic as-pects) and/or safety or economic regulation in one or more of the following areas: government regulatory bodies, air navigation ser-vices, airports, aircraft operations, military, research and development.
Once appointed, PRC Members must act completely independently of States, national and international organisations.
The Performance Review Unit (PRU) supports the PRC and operates administratively under, but independently of, the EUROCONTROL Agency. The PRU’s e-mail address is [email protected].
The PRC can be contacted via the PRU or through its website www.eurocontrol.int/prc.
PRC PROCESSES
The PRC reviews ATM performance issues on its own initiative, at the request of the deliberating bodies of EUROCONTROL or of third parties. As already stated, it produces annual Performance Review Reports, ACE reports and ad hoc reports.
The PRC gathers relevant information, consults concerned parties, draws conclusions, and submits its reports and recommendations for decision to the Permanent Commission, through the Provisional Council. PRC publications can be found at www.eurocontrol.int/prc where copies can also be ordered.
PERFORMANCE REvIEw BODY OF THE SINGLE EUROPEAN SKY
EUROCONTROL, through the PRC supported by the PRU, is designated as the PRB of the Single European Sky performance scheme. The designation is valid until 30 June 2015. The PRB Chairman -Mr. Peter Griffiths - was appointed separately by the European Commission. His designation is also valid until 30 June 2015. To contact the PRB please send an e-mail to: [email protected].
EUROCONTROL
For any further information please contact:
Performance Review Unit, 96 Rue de la Fusée,B-1130 Brussels, Belgium
Tel: +32 2 729 3956
[email protected]://www.eurocontrol.int/prc
