European ATM Master Plan Edition 2015 - Vägtrafik ... · PDF fileSupporting Document European ATM Master Plan Edition 2015 – Performance and Business Views Page 1 | 22 European

Supporting Document

European ATM Master Plan Edition 2015 – Performance and Business Views Page 1 | 22

European ATM Master Plan Edition 2015

Providing a holistic view of SESAR’s performance & investment ambition levels

Methodology & key assumptions

Supporting Document


1 Introduction & Methodology

1.1 Introduction

This document includes an overview of the methodology and main underlying assumptions used to derive the holistic SESAR performance ambitions and related monetisation’s as outlined in the ATM Master Plan Edition 2015 and should be read together with the Chapter 3 (The Performance View) and Chapter 6 (The Business View) in the ATM Master Plan. It focuses on presenting additional supporting information for experts to facilitate the reading and understanding of the Master Plan chapters.

1.2 Overview of approach

The SESAR vision as set forth in the Master Plan enables a significant improvement in ATM system capabilities to be rolled out in the next 20 to 30 years in Europe. This capability improvement has been translated into the potential improvement of ATM system performance by a certain point in time, given a certain traffic forecast. The next step has been to develop a business view for potential performance improvement, including a monetary valuation of the potential benefits and an assessment of the overall investments required.

The approach taken was to build a comprehensive business view, rather than a business case for individual, or even a set of individual technological improvement levers. Technological improvements very often need to be supported by other measures such as evolutions in the ATM model to reach their full performance potential. Comprehensive in this sense implies that all supporting measures are effectively put in place.

The Performance View and Business View as presented in the Master Plan and this document are the result of an extensive process including expert workshops, discussions with individual experts and dedicated review sessions by the Challenge Committee which is a sub-committee of the Campaign Steering Group (CSG). During this process, all key parties have been involved, including ANSPs, Network Manager, Airports, Ground Manufacturers, Airspace Users, Airborne Manufacturers, Military, PRB experts and the SESAR JU.

1.3 Assumptions and definitions

Figures presented in this report are defined for:

Geographical scope: European Civil Aviation Conference - ECAC

Timeframe: 2035 unless explicitly specified otherwise

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Inflation: figure are expressed in real 2012 euros, no assumption has been taken regarding to inflation

Benefits are calculated in comparison to a “2035 baseline” (or Business-as-usual scenario), both for potential improvements in performance as for the monetary valuation, where this is feasible. Performance ambitions are also reported in comparison to the 2012 observed situation, to provide a more tangible baseline.

This 2035 baseline is defined as the performance of the ATM system with the exact capabilities of the 2012 ATM system, given the most realistic traffic forecast. The “Regulated Growth” scenario from “Eurocontrol challenges of growth” is used as the most realistic traffic forecast. This forecast represents a 50% increase of traffic between 2012 and 2035.

Source: Eurocontrol challenges of growth

Total 2012 ANS costs are split in operations cost, infrastructure cost and other costs. Next, historical elasticity ranges for these cost categories are estimated and used to project the future cost evolution in function of traffic growth.

1. Costs of MUAC are included in ATCO/Support/Capex costs Note: SESAR Performance framework edition 2 used for split of main cost items; ATCO staff costs from ACE 2012 p 137; Numbers are rounded Source: ACE benchmarking report 2012 , PRR 2012, SESAR performance framework edition 2, expert judgment

18

16

14

12

10

8

203520332031

Flights (Millions)

202720252023202120192017201520132011200920072005

Time

+50%+56%

2029

Fragmenting World

Happy Localism

Global Growth

Regulated Growth

Air traffic forecast scenarios in Europe (up to 2035)

2005-2035 2012-2035

10

8

6

4

2

0

1.5

1.5

0.6

2012 ANS cost (€Bn)

ANS cost

2.4

1.8

9.2

0.6

0.8

ATCO staf f

ATC operations staf f , ATCO training, Admin

ATC Engineering support, Other technical

support, system related operations

Depreciation, cost of capital

MET, Eurocontrol1 – Network Manager

Facilities related operations

Other, Eurocontrol – Other directorates

Operations cost: €4.2Bn

En-route: €3.2Bn

TMA: €1.0Bn

Infrastructure cost: €3.6Bn

Other cost: €1.4Bn

ANS operationsI

ANS infrastructureII

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Note: Numbers are rounded Source: ACE 2012 Benchmarking report, SESAR Performance framework edition 2

For most Key Performance Areas (KPAs) as defined in the Master Plan and depicted in chapter 2 of this document, the assumption is taken that traffic growth does not impact the system capability directly. At network level, ANS productivity however tends to naturally increase with traffic growth as an effect of efficiencies of scale. These efficiencies of scale have been taken into account in the definition of the “Business-as-Usual” scenario. The methodology to do this is illustrated by the graphs below.

The traffic growth assumed in the Master Plan would imply an improvement of system capabilities that represents a reduction of per flight ANS cost from €960 in 2012 to €770-860 in 2035 under the Business as usual scenario. This already represents a reduction of 10-20%, stemming from performance gains to be achieved through the effect of the performance scheme, economies of scale in relation with traffic growth, initiatives and/or partnerships at FAB, State or ANSP level.

SESAR is expected to sustain these performance efforts through time and to additionally provide a portfolio of solutions to be deployed when and where needed to allow greater performance improvements on the top of the ones allowed under the Business as usual scenario.

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Note: Numbers are rounded

It is however difficult to clearly separate initiatives and solutions coming from one or the another scenarios, that in reality partially overlap. Their contributions therefore do not exactly sum up on the top of each other, but partially overlap for an estimated range of 5-10% justified by the intimate relationship between the SESAR initiative and the ANSPs effort to improve performance.

To further simplify the reading of this document, the following notions and definitions are included:

Business View: The "business view" consolidating RP2 targets, PCP, SESAR 1 and SESAR 2020 into a holistic view on performance ambition & investment ambition

Performance ambition: The improvement of overall system capability levels to be enabled by SESAR at certain points in time, expressed as ranges

Cross-readability: The consistency of performance ambition with SES high-level goals and cross-readability with SES performance scheme

Investment ambition: The high-level investment estimates, resulting from top-down workshops with candidate members experts, expressed as ranges

Deployment: The "how" to deploy, defined in two scenarios, based on standard deployment timeframes

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2 Performance View

2.1 Overall outcome

The SESAR Vision translates into a capability improvement on five Key Performance Areas (KPAs) compared to the 2012 baseline. These five KPAs, the corresponding SES high level goals, performance metrics and absolute and relative savings are depicted in the table below. Where possible, the link with the metrics used in the performance scheme is highlighted.

* Baseline in 2035 assuming system with similar efficiency as in 2012, taking into account elasticity in growth of ANSP costs; 1. Additional flights that can be accommodated at congested airports, representing 5-10% of 1.9M forecasted unaccommodated flights in 2035; 2. Additional traffic associated with ANSP productivity gains, enabled by SESAR; Note: Numbers are rounded Source: Eurocontrol PRB, SES, EC ACE report (2012), Master Plan Campaign Expert Workshops

2.2 Key outcome per KPA

2.2.1 ANS Productivity

The Master Plan takes into account capability improvements on ANS productivity in three areas:

ANS en-route operations

ANS terminal operations

ANS infrastructure

Improved ANS en-route operations

Improved ANS en-route operations drive a step-change in ANS productivity, notably through:

Automation of routine tasks and use of data communication

Flexible resource deployment across the ATM network, enabled by: o Standardised controller working positions o Dynamic sectorisation o Virtual centres

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o Sector team operations o Sectorless operations

Sector Team Operations

The performance ambition for these solutions is to enable an increase from the baseline value of 1,02 flight hours per ATCO hour on duty to 2-3 flight hours per ATCO hour on duty. The supporting evidence supporting this estimation is presented below.

1. 25% reduction in workload through TCT & MTCD estimated by FASTI, 10% workload reduction through 75% equipage of datalink estimated by Eurocontrol. Potential from 100% equipage is higher 2. Range for extrapolation of historic 10y productivity trend in MUAC, DFS, Avinor Source: ACE benchmarking report 2012, Eurocontrol, expert judgment

Improved ANS terminal operations

Improved ANS terminal operations drive a step-change in ANS productivity, notably through:

Automation of routine tasks enables APP/TWR ATCO to handle increasing flight volumes with similar workload

o Automatic data input and management o Use of data communication & interoperable systems

Remotely provided air traffic services can reduce ANS operations and infrastructure costs at low traffic airports

The performance ambition for these solutions is to enable APP/TWR ATCOs to handle increasing flight volumes with similar workload, moving from the baseline value of 1,4 flight hours/ATCO hour on duty to 2-2,7. This represents an average value at ECAC level and can vary greatly depending on the specific local situations. Supporting evidence driving this ambition level can be found below.

Potential ambition for average ACC ANS

productivity Sample of supporting evidence

• Conflict resolution tools: TCT & MTCD

• Datalink

• Does not include gains from other automation tools

• Better demand-capacity balancing to achieve best-in-

class ACC productivity of ~3 flights through e.g.:

– Standard controller working position

– Virtual centres

• Ambition to raise peak productivity from 2/3 to ~6 flights

per ATCO (Equivalent to productivity x2-3)

• Implementation of best practices and continuous

improvement (e.g. MUAC, DFS, Avinor)

0 1 2 3 4 5

Today

Optimizing current

way of working2 3.81.9

Sectorless operations 3.02.0

Flexible resource

deployment3.0

Automation tools1 1.7

Combined,

potential of 5.1

2 - 3

Ambition

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1. Based on extrapolation of 10y productivity trend in DFS and DHMI 2. Productivity driven by strong air traffic growth in Turkey Source: ACE benchmarking reports, SESAR 1 DP/DS, expert judgment

Lean and efficient use of ANS infrastructure

In addition to improved ANS operations, a lean and efficient use of ANS infrastructure leads to higher ANS productivity, notably through:

ANS infrastructure re-architectured as a set of services decoupled from system specificities o Interoperable standards & common info sharing o Virtual consolidation of air traffic control centers o Rationalization of ATM/CNS infrastructure and service orientation

Lean and modular systems, easily upgradable and interoperable with each other o Enabled by the definition of common standards o Interoperability enables more choice of providers o More options for incremental modular upgrades

The performance ambition for these solutions is to enable an increase in efficiency of infrastructure usage of 30-50%, with supporting evidence presented below:

Potential ambition for average TWR/APP

ANS productivity Sample of supporting evidence

• Keeping number of working hours constant with growing

traffic

• Implementation of best practices and continuous

improvement (e.g. productivity trend for DFS, DHMI)

0 1 2 3 4 5

Today

Optimizing current

way of working1 5.022.0

Automation tools 2.3

2 – 2.7

Ambition

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1. Report from Austrialian Civil Aviation Order - Draft Regulation Impact Statement: Aircraft avionics equipage mandates for satellite-based IFR navigation 2. Extrapolation of historic 10y depreciation trend observed for DFS Source: ACE 2012 benchmarking report, Australian ANSP

2.2.2 Operational Efficiency

Operational efficiency refers to operational efficiency from air user point of view and is impacted by two key areas of operational improvement:

• Increased collaboration and predictability • Improved flight trajectories

Time efficiency – departure delays

From the figures published by CODA, the average delay per flight in 2012 (all causes included) was 10 minutes. The ambition for 2035 is to reducing by 1-3 minutes this figure, by gradually introducing a new paradigm for the planning and execution of flights, based on real time monitoring of trajectories and collaborative decision making among stakeholders who will pro-actively propose solutions when operations drift away from plans due to delays.

This ambition must be read in the context of a 2035 traffic increase of +50% or more, which could potentially worsen considerably today’s figures for delays if the Business-as-usual scenario holds. Once traffic growth hits the capacity barrier in fact delays grow exponentially.

The SESAR ambition of increasing network capacity by 80%-100% will be fundamental to ensure that departure delays are reduced. Besides the network capacity increase, the reduction of departure delay is expected to be enabled by a Collaborative Decision Making (CDM) with all actors, which will increase predictability and reduce delays through for example and not limited to:

• Airlines influence prioritization of their flights according to business needs in the planning process • All flight actors share and consult ATM digital information on a common digital information sharing

platform – allowing better decision making

The performance ambition is to enable a reduction of 10-30% in total delay of 10 minutes per departure in the baseline, down to 7-9 minutes. A number of supporting evidences (not exhaustive list) is depicted below.

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Source: CODA annual digest 2012, Combinatorial Exchange Models for a User-Driven Air Traffic Flow Management in Europe, NextGen, Master Plan Campaign Expert Workshops

Time efficiency – predictability

This refers to the reduction in size of the time window around a planned arrival time which captures around 70% of the variability. This is based on analysis and judgement made within the SESAR programme as follows:

• The current (at gate) arrival time variation not including pre-departure variability (which actually accounts for the vast majority of variability in arrival time) was assessed to be approximately 7.5 minutes (for approx. 70% of flights, i.e. one standard deviation) - from "Comparison of Air Traffic Management-Related Operational Performance: U.S./Europe, 2012" published November 2013

• Note that as the US / Europe analysis is based on variability of repeated actual arrivals (of the same flight from day to day), it is necessary to make a judgement of how much of this variability (e.g. due to differing wind conditions from day to day) would have been reflected in the pre-departure flight plan (or in future, reference business trajectory). The judgement made is that about a third of the variability could be "planned for" - resulting in a baseline variability of arrival of 5 minutes.

• SESAR1 development programme has targeted a reduction of 60%, i.e. a reduction in the size of the time window of 3 minutes.

It is acknowledged that the baseline calculation is based on a large element of judgement and that the measure does not include various factors commonly associated with Predictability or punctuality (e.g. departure variability). However, it is a measure that is relevant to the contribution that the SESAR concept of operation should be able to make. It is a "real" performance improvement in so far as it reflects the ability of the air transport system to be able to indicate at the point of departure the likely arrival time with a greater degree of accuracy. This fact, combined with the ambition on departure delay reduction, will directly imply a reduction of delays at arrival.

Time efficiency – flight time

Shorter flight time will be enabled by user-preferred routes, dynamic airspace management and flexible airspace configurations as well as by advanced use of automation to manage and control traffic, allowing the optimization of traffic flows to/from busy airports. In particular:

• Flight centric operations allow air users to fly their preferred, more direct route • Air Users can perform continuous climb/descent operations • Advanced AMAN & XMAN ensure a smooth and optimal arrival flow into busy airports • Dynamic mobile areas reduce the detours flown around special use airspace • Airspace configuration dynamically adjusts to capacity/demand needs

Potential ambition for reduction cost of

delay Sample of supporting evidence

~35

~35

0 50 100

~40

(%)

International benchmark

Collaborative negotiation

of slots~20~10

UDPP• Reducing reactionary delays by 75%

• Reducing delay of delayed flights from ~25min to

~15min

• Possible cost savings achieved through collaborative

negotiation of slots

• NextGen ambition to reduce delays from 18min per

flight in do-nothing scenario to 12min per flight

10% - 30%

Ambition

Combined

potential of

40-50%

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The ambition is to reduce flight time with 4-8 minutes per flight, i.e. 3%-6% out of the baseline duration of 127 minutes (gate-to-gate average duration of flight in ECAC zone, including taxi)

1. Time savings of 0-10% depending on route. Assuming flight time of 127min per flight Source: Lufthansa, Swiss Airlines, SESAR Project 16.06.06, Master Plan Campaign Expert Workshops

Fuel efficiency

A set of solutions will enable an improvement in flight efficiency: • Flight centric operations allow air users to fly their preferred, more direct route • Air Users can perform continuous climb/descent operations • Advanced AMAN & XMAN ensure a smooth and optimal arrival flow into busy airports • Dynamic mobile areas reduce the detours flown around special use airspace • Airspace configuration dynamically adjusts to capacity/demand needs

These solutions have an impact both on fuel consumption and on flight time. The ambition is to reduce fuel consumption with 250-500 kg per flight vs. a baseline of an average 4.800 kg per flight (all flights in ECAC airspace). This ambition must be read in the context of a 2035 traffic increase of +50% or more, which could potentially worsen considerably today’s figures for fuel efficiency if the Business-as-usual scenario holds. Higher traffic levels in fact generally cause imply higher traffic complexity, naturally leading to more flight constraints negatively affecting flight efficiency.

The supporting evidence for the fuel efficiency ambition is illustrated below.

Potential ambition for time savings Sample of supporting evidence

• Simulation of flight trajectory as foreseen by MP

• Represents time saving on routes from Frankfurt to

Paris CDG & Madrid

• Swiss airlines study of free flight optimizer vs actual

flight data1

~10

0 5 10 15 20 (min/flight)

Free f light optimizer

Case study by LH

in coordination with

Swiss Airlines

~18

~13

4 min – 8 min

Ambition

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1. Fuel savings of 5-10% depending on route. Assuming fuel burn of 4.8 ton per flight 2. As reported by Eurocontrol CDO Implementation team Note: Other validations such as Advanced Flexible use of airspace or FRAMaK have demonstrated fuel savings of ~50kg Source: SESAR Release 1, Lufthansa, Swiss Airlines, Eurocontrol, Master Plan Campaign Expert Workshops

The splits across the flight phases / operating environments are indicative. They serve to illustrate broadly where across the network fuel efficiencies can be expected. They are based on the following main inputs:

a. 4,800 Kgs average fuel burn per flight (Source: PRR 2012 – Fig 2 21; it is noted however

that this is a weighted average of all traffic in ECAC airspace and not just intra-European)

b. Approximate distribution of fuel burn for a typical intra-European flight of c. 100 minute

duration (Source: IATA): Taxi phase: 5%; Climb / descent 50%; Cruise 45%

c. Judgement of potential inefficiency in each phase - based on various sources, e.g. PRU,

airline analyses etc. Here the judgement has been that the complex and busy TMAs are the

areas with the highest potential enhancement from SESAR solutions (65% of overall

ambition) with a relatively even split across cruise and taxi operations. Note that the

average of 250-500Kgs per flight is for all flights, but not all flights use congested / complex

TMAs (though by 2035 a far higher proportion than today will) implying a greater saving for

flights who do use these areas.

Although the majority of fuel is burnt in cruise, the relative inefficiency in this phase is seen as low (as per baseline KEA performance of 3.2% in 2012). The SESAR ambition in En-Route of 80Kgs implies that approx 75% of the observed KEA inefficiency is eliminated

2.2.3 Capacity

The Master Plan takes two views on improvement of capacity • Increase of airport capacity, notably at congested airports • Increase of overall network capacity

Additional capacity at congested airports

In addition to an increase in flights, the most realistic traffic forecast for 2035 projects a number of 1,9 million unaccommodated flights at congested airports. The SESAR solutions enable an increase of congested airport capacity:

• Runway throughput is enhanced to increase capacity at high traffic airports o Reduction of occupancy time o Reduction of arrival and depart spacing o Improved wake vortex management

• More robust operations due to accurate aircraft navigation and integrated surface routing/guidance • Optimum traffic sequence is achieved by improving arrival and departure management, allowing

users to plan ahead

Potential ambition for fuel burn savings Sample of supporting evidence

• Simulation of flight trajectory as foreseen by MP

• Represents fuel saving on routes from Frankfurt to

Paris CDG & Madrid

• Swiss airlines study of free flight optimizer vs actual

flight data1

• Evidence from CDO trials in Madrid and Schiphol

airports

• Based on SAS observed fuel burn into / out of major

European airports

• Only considers terminal area trajectory

• SESAR 1 Release in London TMA

• Represents aircraft fuel burnt to fly the last 500

nautical miles to destination

~425

~240

~940

500 1,0000

Extended AMAN horizon

(kg/flight)

SAS study ~200~100

Continuous Decent

Operations2 ~260~75

Free f light optimizer ~480

Case study by LH

in coordination with

Swiss Airlines

~600

250kg – 500kg

Ambition

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• More collaborative decision making

In the 2035 baseline, ~30% of flights are expected to operate in a congested airport (i.e. > 95% utilization) environment while the number of congested airports is expected to grow from 6 to 30 in the period 2012-2035. The ambition with the abovementioned levers is to enable an increase of capacity at these congested airports of 5-10%, which would imply that 200 to 400 thousand additional flights could be accommodated at these airports. The supporting evidence leading to the 5-10% ambition is presented below.

1. impact dependent on traffic mix 2. Airport with equal number of runways 3. Experts identified LHR was able to increase peak throughput from 76 -> 89 movements Source: PRR 2013, Master Plan Campaign Expert Workshops

Increase of overall network capacity

The approach on network capacity is to set an ambition that represents the additional capacity created by the increase in ANS productivity as presented earlier.

2.2.4 Environment

Only one KPA for environment has been taken into account for the quantitative analysis, notably CO2 emissions. The ambition level for reduction of CO2 emissions stems directly from the increase in operational efficiency for air users. The 250kg – 500 kg reduction in fuel consumption corresponds to a 790 kg – 1.600 kg reduction in CO2 emissions, based on a fixed conversion ratio of 3.15.

2.2.5 Safety & Security

The ambition on safety & security is to have no increase in risk, given the expected increase in traffic. At this stage, the accidents with ATM contribution are used as the Key Performance Indicator for Safety. The ambition is to maintain this total value constant despite the traffic growth, hence taking mid-air collisions as

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the only type of occurrence, the ambition can be translated by reducing the relative risk factor by 3-4, i.e. with the square of targeted system capacity capability levels (80-100%).

This Master Plan introduces security (and notably cybersecurity) explicitly as part of the ambition. Here the KPI used is ATM related security incidents resulting in traffic disruptions and the ambition is not to increase the number of occurances.

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3 Business View

3.1 Overall outcome

The overall positive outcome of the Business View as presented in the Master Plan is the result of the translation of the performance view in monetary value and the assessment of the required investments in the Optimised ATM infrastructure deployment scenario. This chapter focuses on how these estimates have been built.

The Business View is presented in three different ways: • 2035 View: value of annual, recurring performance improvements in 2035 • Dynamic View: value of annual recurring performance improvements and required investments, per

year up to 2035 • NPV View: Net Present Value of dynamic view in 2012 using an 8% discount rate. The only NPV

presented in the Master Plan is the difference in NPV between the two deployment scenarios.

Also note that restructuring and financing costs are not taken into account in this Business View. As explained further in this report, the annual cost reduction for ANSPs remains limited to ~0,9% per year, limiting the need for restructuring costs. No specific stance is taken on the requirement for additional financing, in comparison to historical CAPEX levels, and hence on the potential financing costs. Nevertheless, the overall level of required investments seems in line with historical CAPEX levels (notably for ANSPs).

3.2 Benefits

Whereas the Performance View presents the ambition level as an improvement of system capabilities, the business view translates these capabilities in a monetary valuation of the resulting savings or additional capacity, compared to the 2012 baseline scenario. Not all improvements of system capabilities can be translated into monetary terms. The three areas of improvements considered are:

• ANS productivity • Operational efficiency for air users • Additional congested airport capacity

Combined, these improvements translate into a value of €8-15 Bn per year as of 2035. The first two KPAs represent cost savings compared to the baseline, the third KPA represents profits from additional congested airport capacity.

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1. Based on Cost of 37 ANSPs of €9.153Bn and 9.55M flights; 2. Based on airline profit of €700 per flight, airport profit of €1400 per flight and €13 per passenger. Assuming ~330k additional flights in 2035 with 138 passengers per flight; 3. Taking into account that 2035 cost per flight could vary in a range 900-770 per flight depending on the actual elasticity; Note: Numbers are rounded; Source: ACE 2012 Benchmarking report, Eurocontrol challenges of growth, WP 16.6.6, Eurocontrol inputs for standard cost-benefit analysis; Master Plan Campaign Expert Workshops.

3.2.1 Value of ANS productivity

Productivity improvements for ANS operations only partially translate into a reduction of the ANS cost base, as bringing down these costs requires workforce planning amongst others. The assumption is therefore taken that ~80% of productivity improvements can be translated into an actual ANS Operations cost reduction (i.e. an increase of 100% in ANS Productivity translates into a ~40% reduction in costs, not into a 50% as it would occur if the two were linked 1:1. Based on expert judgment).

Given the expected increase in traffic of 50%, the reduction of total ANS cost per flight (30%-40% compared to baseline 2035, or 40-50% compared to baseline 2012) represents an absolute saving of €3-4Bn (compared to baseline 2035). This saving implies an annual reduction of the total ANSP cost base of 0.7% (CAGR- Compounded Annual Growth Rate) as illustrated below.

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These ambitions have been further broken down for ANS operations costs (en-route vs terminal) and ANS infrastructure cost as illustrated below.

Note: Numbers are rounded Source: ACE benchmarking report 2012, Eurocontrol challenges of growth report, Eurocontrol, Expert judgment

To be noticed that for terminal ANS operations costs the ambition generally implies that ANSPs will be capable of accommodating the increase in traffic demand with the same operations costs as in 2012, thanks to the improved ANS productivity enabled by higher technology support. The great variety of local conditions for terminal ANS service provision could however imply considerable differences from this average behaviour, to be analysed on a case by case basis.

3.2.2 Value of Operational efficiency for air users

The value of operational efficiency is calculated by multiplying the figures for the ambition per flight with the associated cost of delay, fuel and flight time as presented below and with the expected number of flights in 2035. Note that just 80% of IFR flights have been accounted as fully benefitting of the SESAR capability improvements, to reflect the traffic mix in terms of users and equipment. This calculation results in a €5-9Bn of savings compared to the 2035 baseline.

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1. En-route, Airport and weather-related ATFCM delay 2. Represents average block times for flight in ECAC airspace (i.e including e.g taxi times) Note: Numbers are rounded Source: Eurocontrol CODA- Delays to Air Transport in Europe, Eurocontrol Performance review report 2013, Standard inputs for Eurocontrol cost-benefit analysis, SESAR 1 CBA, Master Plan Campaign Expert Workshops

3.2.3 Value of capacity

The valuation of capacity is calculated by multiplying the 200-400 thousand additional flights with a value of €3.900 per flight. This value has been taken as input from SESAR P16.6.6 and is built up as follows:

• Profit per flight of €700 for airline • Profit per flight of €1400 for airport • Profit per passenger of €13 per passenger for airport, with an expected growth of 1% p.a. in

passengers per flight from 110 passengers per flight in 2012 to 138 passengers per flight in 2035

3.2.4 Ramp-up of benefits

The abovementioned benefits correspond to the ambition level and growth forecast for 2035. The ramp up of these benefits over time has been built by combining ambition levels and targets from:

• RP2 targets • PCP CBA (SESAR 1 in deployment) • SESAR 1 essential operational changes preliminary CBA analysis (SESAR 1 next wave of

deployment) • SESAR 2020 performance ambitions from expert workshops (split in 2 waves depending on targeted

maturity dates)

All of these ambition levels and targets are assumed to be realized by the corresponding timing.

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Furthermore, the ramp-up of the SESAR 2020 performance ambition over time has been based on standard deployment timelines and deployment dates as presented in the optimized ATM infrastructure deployment scenario in the Master Plan. The allocation of the benefits to SESAR 2020 wave 1 and wave 2 has been set throughout the process in expert workshops and is illustrated below.

Source: Master Plan Campaign Expert Workshops

Time

SESAR Performance ambition

S2020

wave 1

SESAR 1

PCP

Overall

SESAR performance

ambition

S2020

wave 2

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3.3 Investments

The required investments presented in the Master Plan Business View are the result of: • PCP CBA (SESAR 1 in deployment) • SESAR 1 essential operational changes preliminary CBA analysis (SESAR 1 next wave of

deployment) • SESAR 2020 investment assessment from expert workshops (split in 2 waves depending on

targeted maturity dates)

The SESAR 2020 investment assessment has been based on the number of operating environments received as input from WP 16.6.6 and unit cost estimates defined throughout the process in expert workshops. Detailed figures are presented below.

Number of operating environments considered

1. 2035 Fleet-WP16.6.6; 2. 2035 fleet - 50% Air Users equipage rate enabling ~75% of flights; 3. 2035 fleet – 50% equipage rate for large military aircrafts - 25% for other military aircrafts; 4. Hypothesis: 1/3 EU states (9 states out of 27) without civil-military ATC integration: 1/3 of 60 ACCs = 20 Military ACCs; Source: https://www.eatmportal.eu/working/performance_needs, Master Plan Campaign Expert Workshops

https://www.eatmportal.eu/working/performance_needs

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Unit cost for investments per operating environment: Wave 1

1. Forward-fit: including investments in ground infrastructure, process upgrade,... estimated at 10-20% of overall air user investment; 2. Retro-fit: including investments in ground infrastructure, process upgrade,... estimated at 10-20% of overall air user investment; 3. Considering 10.4 pilot per aircraft (Pilot productivity Benchmark – Cranfield University) & 14k scheduled aircrafts equipped (2035) & 1000€ per pilot trained; 4. Based on medium complex. civil ACC; 5. ~10% of civil complex ACC upgrade cost; 5 AOC systems x €5M/AOC +~20% indirect costs (in line with PCP) Source: Master Plan Campaign Expert Workshops

Unit cost for investments per operating environment: Wave 2

1. Forward-fit: including 20% of indirect costs (manuals, maintenance, procedures, spare parts...) ; 2. Retro-fit: including 20% indirect costs (manuals, maintenance, procedures, spare parts...) 3. €150M: Considering 10.4 pilot per aircraft (Pilot productivity Benchmark – Cranfield University) & 14k scheduled aircrafts equipped (2035) & 1000€ per pilot trained; 4. Based on medium complex. civil ACC; 5. ~10% of civil complex ACC upgrade cost; 6. €30M: 5 AOC systems x €5M/AOC +~20% indirect costs (in line with PCP) Source: Master Plan Campaign Expert Workshops

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3.4 Sensitivity

While the Performance Ambition is defined as an improvement of system capabilities by a certain point in time, and hence does not depend on traffic growth, the Business View does depend on traffic growth.

While most performance gains increase linearly with traffic growth, ANS cost savings do not – as traffic growth drives scale efficiency and hence automatic productivity gains. The impact of traffic growth on ANS cost savings is illustrated with the sensitivity analysis below. The relative cost savings vs. the 2012 baseline has been assumed constant.

Reduction in cost per flight compared to 2012 Note: Numbers are rounded Source: ACE benchmarking report 2012, Statfor; Master Plan Campaign Expert Workshops

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