Airport Performance Indicators 2006

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AIRPORT PERFORMANCE INDICATORS 2006

Copyright TRL (Transport Research Laboratory), August 2006. All rights reserved.

The information contained herein is the property of the Transport Research Laboratory (TRL). Whilst every effort has been madeto ensure that the matter presented in this report is relevant, accurate and up-to-date at the time of publication, TRL cannotaccept any liability for any error or omission.

TRL (Transport Research Laboratory)Registered in England, Number 3142272Registered Offices: Crowthorne House, Nine Mile Ride, Wokingham, Berkshire, RG40 3GA.

For further information on thispublication please contact:

Peter Mackenzie-WilliamsHead of AviationTransport Research LaboratoryCrowthorne HouseNine Mile RideWokinghamBerkshire, UKRG40 3GA

Tel: (+44) (0)1344 770424Fax: (+44) (0)1344 770618Email: [email protected]: www.trl.co.uk

Price: UK 435.00


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TRANSPORT RESEARCH LABORATORY

About TRL

TRL is an independent, internationally recognised centre of excellence for research and consultancy intransport issues. It has worked closely with clients in the public, private and independent sectors in theUK and worldwide for more than 60 years. The organisation provides research based technical helpwhich enables clients to obtain improved value for money, generate competitive advantage andachieve a better understanding of transport problems.

TRL employs around 500 staff with a wide range of professional disciplines, including economists,mathematicians, physicists, psychologists, engineers and statisticians. Facilities include a conferencecentre, extensive library and a 2.2 km test track.

TRL and aviation

TRLs activities in the aviation sector and include the following:

Q air transport demand forecasting and market analysis;

Q comparative studies of airport and airline efficiency and levels of airport charges;

Q assessments of personal risk and risk contour modelling related to airport developments;

Q advice on airfield pavement construction and maintenance;

Q provision of software to control traffic flows within airport road systems;

Q research into causes of vehicle accidents in airport operational areas, and the provision oftraining programmes designed to reduce accident rates;

Q use of GIS systems to assist in increasing the use of public transport for access to airports;

Q risk and liability assessments arising from vehicle accidents at airports.

Other annual aviation publications:

Q Airline Performance Indicators 2006TRLs Airline Performance Indicators is an analysis of an extensive range of 38 airlineperformance measures. The document analyses operational and fictional outputs and resultsof a total of 50 airlines, to assist airline managers, financial analysts and regulators around theworld assess the performance of airlines in which they have a particular interest.

Q Review of Airport Charges 2006TRLs Review of Airport Charges allows airline and airport managers, financial analysts andregulators around the world to compare the relative costs, using a sample of 50 of theworlds leading airports.

For further details of these and other TRL activities, please contact:

Peter Mackenzie-WilliamsHead of AviationTransport Research LaboratoryCrowthorne House

Nine Mile Ride, WokinghamBerkshire, RG40 3GA, UK

Tel: (+44) (0)1344 770424Fax: (+44) (0)1344 770618Email: [email protected]: www.trl.co.uk


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AIRPORT PERFORMANCE INDICATORS 2006

CONTENTS

1. Introduction 1

2. Defining Core Airport Activities to Achieve Better Comparability of Data 53. The Performance Indicators 10

4. Description of the Airports and their Relative Performance 49

5. Measuring Total Performance 152

Performance Indicators

Table 1: Total Revenue per ATM 14

Table 2: Total Revenue per 1,000 ATUs 15

Table 3: Total Revenue per Passenger 16

Table 4: Total Revenue per Employee 17Table 5: Aeronautical Revenue per ATM 18

Table 6: Aeronautical Revenue as a Percentage of Total Costs 19

Table 7: Aeronautical Revenue as a Percentage of Total Revenue 20

Table 8: Aeronautical Revenue per 1,000 ATUs 21

Table 9: Aeronautical Revenue per Passenger 22

Table 10: Commercial Revenue per Passenger 23

Table 11: Commercial Revenue as a Percentage of Total Revenue 24

Table 12: Total Costs per ATM 25

Table 13: Total Costs per Passenger 26

Table 14: Total Costs per 1,000 ATUs 27Table 15: Operating Costs per Passenger 28

Table 16: Staff Costs as a Percentage of Operating And Staff Costs 29

Table 17: Staff Costs per 1,000 ATUs 30

Table 18: Staff Costs per Passenger 31

Table 19: Staff Costs as a Percentage Of Turnover 32

Table 20: Operating Profit 33

Table 21: Operating Profit per Passenger 34

Table 22: Return on Capital Employed 35

Table 23: Return on Shareholders Funds 36

Table 24: Passengers per Employee 37Table 25: Passengers per ATM 38

Table 26: ATUs per Employee 39

Table 27: Total Assets per Passenger 40

Table 28: Equity Ratio 41

Table 29: Liquidity Ratio 42

Table 30: Assets per Employee 43

Table 31: Capital Expenditure per Passenger 44

Table 32: Capital Expenditure as a Percentage of Turnover 45

Table 33: Taxation Effect 46

Table 34: Net Cash Generation per Passenger 47Table 35: EBITDA as a Percentage of Turnover 48


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1. INTRODUCTION

The Transport Research Laboratory (TRL) is pleased to present the seventh in its annual series ofpublications on Airport Performance Indicators. This work is now well established as a reference sourceworldwide, and it is used by airport operators, airlines, government regulators and financial analysts fora wide variety of purposes. Underlying this wide-ranging interest is the desire to understand how theperformance of individual airports can be assessed against world best practice. Interest also comesfrom the media, demonstrating how the quantitative comparison of businesses is a normal tool for thebusiness press.

Additionally, much of this interest stems from the continuing trend towards airport privatisation, whichcontinues to attract considerable interest from investors and which returned to the financial marketagenda relatively quickly after the events of September 11 2001. More recently, it has continueddespite the short term traffic downturns associated with the SARS epidemic. At the time of preparingthis years publication the takeover of BAA by Ferrovial has generated enormous interest in the airportsindustry, demonstrating that it continues to be regarded as an attractive area by both strategicinvestors and financial markets. This means that the need for information on performance willcontinue to grow, with analytical techniques growing in tandem with this demand.

However, privatisation is not the only source of pressure for increased efficiency and knowledge about

performance benchmarks. In the US, where meaningful airport privatisation is as far away as ever, thequest for information on relative levels of efficiency is as great as anywhere in the world.

The sample of airports included in this years publication remains at 50. We were unable to obtaindata from Brussels and Osaka Kansai airports, but we were able to add Beijing and Dallas Fort Worth tothe sample. The composition of the sample is not fixed and, as shown this year, depends to an extenton data availability. On the whole this has improved over the years as airports have adopted both amore commercial approach to their customers and a more transparent stance to shareholders andstakeholders. Thus, for example, we are able to include an analysis of both Johannesburg and CapeTown airports, using data provided by Airports Company South Africa which is not published in itsnormal Annual Report. On the other hand the South African data is the only information availablefrom an African airport group and as far as we are aware there are no published financial reports forany South American airports.

Of the 50 airports or airport groups covered, 19 are wholly or partly privatised and six others are eitherat early stages of government divestment, or have at some time been the subject of governmentannouncements of an intention to privatise. However, at least one of these has seen a series ofchanges of intention brought about by changes in administrations. Not surprisingly, airportprivatisation remains at times a sensitive political issue.

The 19 private sector airports can be expected to compare strongly with their public sectorcounterparts, particularly in measures relating to commercial revenues, although this is by no meansan invariable rule. Work cultures do not change overnight simply as a result of privatisation, and thelead times for the construction or re-modelling of additional terminal space for retail use inevitablymean that big improvements in financial results from this source can take several years to materialise.There are also a number of public sector airports which are already very efficient in both financial andoperational terms.

The number of performance measures which we produce remains at 35. These cover a broad rangeof aspects of the operational outputs, revenues and costs of the airports. Various financial measuresinclude both standard accounting ratios and others which measure factors such as the increasinglyimportant role of commercial revenues, which account for over half of total revenues at a growingnumber of airports.

During 1999/2000 we carried out research to identify a more complete measure of overall airportoutput than the Work Load Unit (WLU) which has been in common use for a number of years.Subsequently we introduced results based on the Airport Throughput Unit (ATU) in the 2001 edition ofthis publication. The ATU is defined in Section 3. We have made some changes over time to the wayin which this measure is calculated and we would welcome any comments relating to the concept ofthe ATU in general.


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The contents of the publication are as follows. In Section 2, we describe how we make adjustments toairports raw data so as to be able to make comparisons between a reasonably homogeneous set offigures. In Section 3 we present the series of 35 performance indicators with definitions andcomments on the input variables, and brief accompanying comments or explanations. In Section 4,we provide brief comments on the airports and groups covered, including details of corporate status,progress towards privatisation if appropriate, and details of major infrastructure projects in progress orplanned. This year we have also introduced an analysis of the extent to which each airportsperformance differs from the average for the sample. In Section 5, we present the latest results of our

continuing work with Durham University Business School which examines each airports overallperformance as a single measure.

The airports covered in this publication are listed opposite, together with the level of passengerthroughput achieved in the review period and the relevant financial reporting period. There is a rangeof financial reporting periods of both financial and calendar years.


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Airport/GroupReporting period

(year ending)

Passengerthroughput

(millions)

% change onprevious year

ACSA (South African airports) March 2005 25.8 8.5ADM (Aeroporti di Milano) December 2004 30.7 16.3Aroports de Montral December 2004 10.3 15.3ADP (Aroports de Paris) December 2004 75.3 6.5ADR (Aeroporti di Roma) December 2004 30.7 9.2AENA (Spanish airports) December 2004 164.1 8.0Amsterdam Group December 2004 44.3 8.1ANA (Portuguese airports) December 2004 19.4 7.4AoT (Airports of Thailand) September 2004 45.1 24.4Athens December 2004 13.7 11.5Atlanta December 2004 83.2 5.6Auckland June 2005 11.3 8.3BAA March 2005 141.7 6.3Beijing December 2004 34.9 43.2Berlin Airport Group December 2004 14.9 11.8Birmingham March 2005 8.8 -4.4

Brisbane June 2005 15.9 11.0Calgary December 2004 9.2 7.0Cape Town March 2005 6.2 13.6Chicago OHare December 2004 75.5 8.7Copenhagen December 2004 19.0 7.5Dallas Fort Worth September 2005 59.1 0.9Finnish Airports Group December 2004 14.6 39.3Fraport AG December 2004 77.1 9.2Geneva December 2004 8.6 6.2Hong Kong March 2005 38.3 38.4Johannesburg March 2005 14.7 10.9London Gatwick March 2005 32.0 6.5London Heathrow March 2005 67.7 5.3Los Angeles June 2005 61.2 5.6

Malaysian Airports December 2004 39.4 17.8Manchester Airport Group March 2005 26.7 5.4Melbourne June 2005 20.8 8.4Miami September 2004 30.2 2.5Munich December 2004 26.8 10.8Ontario (California) June 2005 7.0 3.0Oslo December 2004 14.9 8.9Perth June 2005 6.7 10.2San Francisco June 2005 33.2 2.9Singapore March 2005 30.4 23.1Stockholm Arlanda December 2004 16.3 7.5Swedish Airports Group December 2004 28.0 5.5Sydney June 2005 28.3 7.0Tokyo Narita March 2005 31.8 18.2

Toronto December 2004 28.6 15.1Vancouver December 2004 15.7 9.8Vienna December 2004 14.8 15.7Washington Dulles December 2004 22.6 35.4Washington National December 2004 15.9 12.5Zurich December 2004 17.3 1.3

While none of the analysis contained in this publication would have been possible without theprovision of the Annual Reports which were used as a source of raw data, a number of airportoperators gave additional assistance by providing further information or explanations of detailsprovided in their Reports. In this regard, we would like to record our thanks to the officials whoprovided assistance at ACSA, Aroports de Paris, AENA, Airports of Thailand, Copenhagen , the CivilAviation Administration of Sweden, and Washington, all of whom played a part in ensuring that our

analyses were carried out as accurately as possible.


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2. DEFINING CORE AIRPORT ACTIVITIES TO ACHIEVE BETTERCOMPARABILITY OF DATA

Introduction

A common problem in making any form of performance comparison between different centres of

output within the same industry is that of ensuring that the organisations in question are sufficientlysimilar in structure and function as to make comparisons valid. The airport industry is a case in point.Within the sample of airports covered in Airport Performance Indicators there are several which areinvolved in various activities which we regard as being outside of those that would normally beregarded as core airport activities. We regard the core activities as being:

the provision of runways, taxiways and aprons for the use of airlines and their agents;

the provision and operation of terminals in which passengers pre- and post-flight formalities arecompleted, including the processing of baggage, and

the provision of space within terminals in which concessionaires in a variety of retail businessesmay provide shopping, catering and amusement facilities for passengers use.

Major non-core activities, particularly in revenue terms, include the provision of ground handling andcar parking services. Another non-core activity which is more significant in cost terms is the operationof air traffic control services. This becomes an issue when airports are operated as part of a nationalcivil aviation organisation, with financial reporting covering all of the organisations activities. Withinthe sample of airports covered in Airport Performance Indicators, air traffic control services areprovided by the administrations in Finland, Portugal, Spain, Norway, Singapore and Sweden.Additionally, catering services, hotel ownership and operation, and revenues derived from pass-through charges added to utility costs may be part of an airports operating portfolio.

The generally accepted approach to this problem is to make adjustments to the raw operating andfinancial data so as to remove all measurable effects of the non-core activities. Thus revenues arededucted from the gross aeronautical, commercial or other revenues as appropriate. Costs of non-core activities are generally largely confined to operating or staff-related costs (though someassociated depreciation costs can be identified), and these are deducted from gross reported figuresalong with the associated number of staff. Where capital expenditure can be identified which hasbeen incurred in connection with a non-core activity, this is also deducted.

Further adjustments are needed on the revenue side. It is clear that if an airport did not itself performfunctions such as the operation of car parks or ground handling services, then it would be necessaryfor a third party to operate these services instead. Inevitably, that third party would pay a concessionfee to the airport, or a percentage of its profits, and so a hypothetical concession fee is calculated inproportion to th e revenues deducted for the non-core activities, and added back to commercialrevenues.

In addition, the figures related to corporation tax are reduced to take account of the estimated overallreduction in profitability which would result from the airport not being directly involved in the non-

core activity. Similarly, interest charges and various balance sheet measures are adjusted to takeaccount of adjusted levels of activity which are lower than those which actually take place.

A final adjustment relates to the common practice within airport groups for a Head Office to exist.Staff employed in Head Offices are clearly engaged in activities which would normally be carried out bymanagerial or administrative staff in an airport, unless they are engaged in work related to non-coreactivities. In these cases an appropriate number of Head Office staff, and their associated cost, isallocated to the individual airports on the basis of airport turnover. Head Office staff which can beidentified as working on non-core activities are deducted from Group staff numbers in the same wayas for individual airports.

Against this background, we provide details in Annex 1 of the non-core activities which we haveidentified at each airport or airport group, with confirmation of the steps taken to reduce the data to a

common set. Adjustments of the type described above were made at all but eleven of the airports orgroups covered in this publication.


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Other comparability issues

The dissimilarities between airports are not confined to the extent to which non-core services areperformed. A number of other factors may explain differences in performance indicators, as discussedbelow.

Ownership

The issue of whether an airport is in the public or private sector, or a combination of the two, is clearlygoing to influence a number of operating strategies. While most airports these days have a strongfocus on increasing commercial revenues this is particularly the case for private sector airports,generally because in most cases a regulatory framework places a strict limit on the extent to whichaeronautical charges can be increased.

A number of factors relating specifically to public sector airports affect their performance. The mostextreme case is in the US, where in many cases airports scope to achieve profitability is severelylimited, either due to Federally-imposed restrictions on the way in which aeronautical charges can beset or due to the terms of Lease and Use Agreements entered into with airline users. The common USpractice of leasing terminals at major hub airports to airlines, or for airlines to build their own terminals,also restricts the extent to which airports can maximise the return on their assets. In a number ofcases elsewhere in the world, governments have insisted that aeronautical charges at all major airports

should be set at common rates, regardless of the relationship of those charges to the costs of runningeach airport.

Asset ratios are also affected by the practice in the case of some public sector airports of the retentionby government of the land on which the airport is built, so that the assets recorded for the airport donot reflect the full value of the airport. Similarly, the fixed assets at many state-owned airports areoften not revalued with any regularity, or at all. In the case of the main Australian airports, the assetswere not revalued for many years during the years of public ownership as a matter of policy. At thesame time aeronautical charges were kept at low levels so as to encourage growth in tourism andbusiness development. By refraining from revaluing the airport assets, however, the government wasable to point to reasonable returns on assets despite low levels of airport income.

It is also the case that government-run airports often receive help from a central or local governmentdepartment, in terms of administrative or other functions being performed by government rather thanairport employees, such that the true costs of operating the airport are not reflected in its Accounts.Foe example, a number of basic financial administration functions are performed by the City of LosAngeles on the airports behalf rather than by the airport itself.

Accounting Practices

Different accounting practices frequently complicate comparisons between different organisations,regardless of their ownership structure. This chiefly affects depreciation. Depreciation periods onfixed assets varies considerably: for instance, in the UK, BAA depreciates its runways, taxiways andaprons over periods of up to 100 years, whereas much shorter periods are more normally used.Airports may choose whether to classify expenditure on equipment as either an operating cost or ascapital expenditure, which has a clear impact on operating profit. Interest costs on capital expenditureare capitalised and amortised at Calgary, but this is an exception to the practice adopted by most

other airports covered in this publication.

Sources of Finance, Including Subsidies

For airports in the private sector, the normal source of finance for capital expenditure will either becash generated by the business or commercial loans. Credit ratings for airports generally reflect a viewon the part of the finance market that airports are reliable cash generators, but even so normal marketinterest rates apply.

In the case of public sector airports the situation is different in that they are often debarred fromtaking out commercial loans, but instead have access to national or local government funds. Whensuch funds are made available, there are varying conditions under which they may be repaid, from the

payment of interest based on a fixed rate of return to repayment of the loan but no payment ofinterest. In some cases public sector funds are made available as a grant. These arrangementsinevitably place the public sector airport at an advantage over its private sector counterpart, and this isreflected in lower interest charges. The main disadvantage of the system is that often the fundsrequired are not available from government sources, or come later than required. It is a lack of


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available funds for airport expansion which has led a number of countries to turn to privatisation as ameans of enabling future airport expansion.

In the US, the restrictive approach to aeronautical charge pricing is balanced by a system which allowsairports to raise capital through the issuance of fixed interest bonds, coupled with no liability to thepayment of federal taxes. US airports also have access to Federal funds in the form of the AirportImprovement Program from the Aviation Trust Fund, which is fed by the payment of an InternationalPassenger Tax on airline tickets. The availability of these funds has become somewhat limited in

recent years as the Fund has been built up so as to mitigate the need to raise Federal taxes.

Less obvious subsidies from governments to public sector airports include the provision of servicessuch as air traffic control and security for less than a normal commercial rate. Arrangements such asthis will tend to reduce operating costs and staff costs below the levels which a private sector airportmight expect to have to pay.

Passenger Service Standards

The passenger service standards provided by airports vary considerably, depending on the extent towhich the airport is concerned, for example, to optimise waiting times for baggage collection orcheck-in or the extent to which it feels that it stands to gain business from competing airports byimproving service standards. The ability of an airport to improve standards may in itself be limited by

funding restrictions which will apply regardless of the ambitions of the airport management.

Optimising service standards carries a cost, both in terms of infrastructure and staff levels. An airportwhich seeks to provide high standards may therefore appear to have relatively high costs. However, inmany cases the effect of improving service standards, which will often include increasing retailfloorspace, is to increase revenues. For this reason a more profitable airport, or one with a relativelyhigh level of income per passenger, will often have relatively high unit costs.

Traffic Mix

The characteristics of an airports passengers will have an impact on both its revenues and costs. Ahigh proportion of domestic traffic will tend to reduce both: domestic passengers are less likely tocheck-in hold baggage than international passengers so they generate less need for baggage handlingequipment, and less floorspace in check-in areas. While international passengers generate a greater

need for space and infrastructure, they will have access to tax- and duty-free retail outlets, which willincrease airport revenues. This is particularly the case where an airport has a high level of internationaltransfer passengers, who may have two hours or more between flights without having to devote anytime to formalities such as check-in or immigration clearance.

Local Air Traffic Control

At an increasing number of airports, the air traffic control service related to aircraft in flight onapproach to or departure from an airport, or aircraft moving on the ground, is charged direct to theairlines rather than being charged to the airport. The separation of these charges, known as terminalnavigation charges, results in a greater level of transparency in the costs levied on airlines than the oldsystem under which airports were charged for the service and then passed the cost on to airlines as acomponent of landing charges. For the airport, the result of moving from the old system to the new is

to reduce both aeronautical charges and operating costs.

Summary

It is clear that, in addition to the differences in operating activities already described, many factors canimpact on an airports ability to optimise its performance, and on its relative level of performancewhen compared to its peers. While it would theoretically be possible to make adjustments to the dataso as to take account of these factors, it would be very difficult if not impossible to gather all of theinformation which would be needed to do so, and inevitably it would be necessary to make a greatnumber of assumptions. We would in any case question the value of such an exercise, given that inmany cases the adjusted set of data would bear little resemblance to reality.

As we have already remarked, the benchmarking of performance indicators in any industry is bound tobe subject to the kinds of influencing factors discussed above. This has not prevented the acceptanceof benchmarking of airline performance for many years, despite the fact that, for example, differentroute networks and passenger mixes impact on relative performance levels. The existence of theseinfluencing factors has also failed to prevent a growth in interest in benchmarking generally, and thishas certainly been the case in the airport industry in recent years.


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Recently, there has been a growing level of interest in bottom-up benchmarking, sometimes referredto as process benchmarking. This seeks to break down operating functions into individual parts and toseek to understand ways in which airports carry out these functions more or less efficiently. This is auseful development, but it must be recognised that the data needed to carry out this form ofbenchmarking is rarely if ever available in the public forum.

While we will continue to consider ways in which the evaluation of airport performance can be refined,

the level of interest which is shown in our work is a good indication that the concept of measuringairport performance is useful to airport managers, shareholders, airline users and analysts. AirportsAnnual Reports are also increasingly using performance indicators to demonstrate improving trends,either internally or in relation to competitors. In using performance indicators as a strategic planningtool it is necessary only to bear in mind that the measures produced should not be regarded asguidelines rather than absolutes. They can, however, be taken to give reliable indications of relativeperformance between broad groupings of airports, as discussed in Section 5.


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3. THE PERFORMANCE INDICATORS

Introduction

In this section we present the main body of results from the analysis undertaken to produce thispublication, in the form of a series of thirty -five tables of performance indicators. The results for each

airport are shown in absolute terms and ranked, and we also relate the airports performance inrelation to the average in each case, expressed as an indexed value.

Since the raw data on which the financial indicators are based are provided in units of local currency, itis necessary to convert the data into a common measure of currency so as to allow compa risons to bemade. Our preferred conversion unit is the Special Drawing Right (SDR) which is a unit based on thetrade-weighted values of a group of major currencies from the G8 nations. This unit allowscomparisons to be made over extended periods of time which smooth out some of the largerfluctuations in currency value which can occur in relation to a single currency such as the US dollar.The SDR rates used to convert each local currency are shown in Annex 2.

The raw data, shown in units of local currency, are shown in Annex 3. These data have been gatheredfrom the airports annual Report and Accounts in each case, and in some cases they have beensupplemented by additional information provided by the airport. They reflect any adjustments whichmay have been made as described in Section 2, so in these cases the data shown in the Annex will notcorrespond with what is shown in the Annual Report. Annex 4 contains a glossary of terms whichcovers a number of the units or ratios which appear in the measures, which may either be unfamiliar tothe reader or which may require clarification.

The Work Load Unit, and the Airport Throughput Unit

We have sought for some time to identify a means of measuring total airport throughput in a waywhich has not hitherto been in widespread usage. For the sake of completeness we include here a fulldescription of the way in which our thinking has evolved on this issue.

Among the terms covered in Annex 4 is the Work Load Unit (WLU), which is a measure whichcombines the passenger and cargo elements of an airports throughput. A WLU equates to one

passenger or 100 kgs of cargo or mail. The measure has been in use in the aviation industry for someyears. While it is clearly applicable in the case of airlines it is not always accepted that the same can besaid of its use in relation to airports. This is because the cargo element of an airports production isoften of minor importance in terms of the additional work required by the airport. The passage ofpassengers through terminals coupled with the facilitation of aircraft movements is, it is argued, farmore central to an airports primary role.

During 1997/98, we were associated with a research project carried out within the Transport StudiesGroup at the University of Westminster which set out to try to establish whether a credible alternativeto the WLU could be devised. The scope of the project was limited in terms of time resources, andbecause the sample of airports was necessarily limited it was concluded that the results of the analysiswere not as statistically significant as would be needed to propose an alternative to the WLU withconfidence.

During 1999 and 2001, research was carried out at TRL, in association with the French Ecole Nationaldes Travaux Publics de lEtat, to continue the search for an algorithm which combined passengernumbers and aircraft movements. This work also started from the position that, while themaximisation of an airports cargo throughput is often not a significant priority, it should not beignored completely in proposing an alternative definition of throughput. The work was also intendedto reflect the view that the maximisation of ATMs is not in itself a primary productivity goal, since thiscould imply the intensive use of a runway by small aircraft carrying small numbers of passengers. Itwas felt that this situation would clearly not represent an efficient use of the runway. Similarly, it wasfelt that maximising the size of aircraft using the airport is not in i tself an objective if those aircraft arebeing operated with low passenger occupancy levels. In this case the use of a large aircraft when asmaller one could have carried the same passenger load would imply inefficient use of the terminalapron space, and could in extremis prevent another aircraft from parking.

Ideally, therefore, it was felt that a replacement for the WLU might be a unit of measure whichcombines:

the number of passengers per ATM;


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the number of ATMs; and the weight of aircraft,

with the optimum being achieved when the first two elements are maximised and the last isminimised. The fundamental problem with this ideal was the fact that few airports outside of the USand Australia publish details of the landed weight of aircraft. It was still possible, however, toincorporate the relative efficiency of the aircraft movement in a measure by taking the number ofpassengers per ATM into account. Thus we arrived at the algorithm of:

Passengers x Passengers per ATM

which became

PassengersATMs.

From this, it was possible to extend the measure to encompass the carriage of freight, which was donesimply by using the traditional WLU measure:

WLUs

ATMs.The results from this extension, when applied to a range of performance measures, were very littledifferent from those which were produced by the passengers-only based measure. In our view, thisreflects the fact that a shortcoming of the WLU is that it raises false expectations of producingsignificantly different results to passenger-denominated measures, whereas the addition of the cargoelement often makes little material difference. The new measure, which we refer to as the AirportThroughput Unit (ATU), appeared to avoid this pitfall.

Over the past four years we have presented a number of tables which express various inputs in termsof both passengers and ATUs in this publication. During 2004 05 we discussed with a client airport anumber of points which it had raised about the derivation of the ATU measure. The thrust of thesecomments was that the use of Passengers or WLUs per ATM as a component in the measure meantthat a productivity measure was being constructed which included a component which itself is

productivity related. It was also noted that the construction of the formula meant that:

Double the passenger numbers results in 4 times the ATU measure Double the ATMs results in half the ATU measure.

The second of these effects was an intended feature of the measure, given that our focus was toinclude a productivity element in the measure, but we recognise that the effect could be regarded asbeing somewhat counter-intuitive for a measure of throughput.

It was suggested that an alternative approach would be to construct a measure which was based onthe following equation:

ATUs = passengers + (a x freight) + (b x ATMs).

It was accepted that the value of a should be 10, corresponding with the industry standard method ofcalculating WLUs. The airports suggestion was that the value of b should be the average passengerload.

We have given this issue further thought. At this stage we accept that the formula used up to 2004involved a degree of duality as a result of the inclusion of a productivity element in the measure. Webroadly agree that the formula above fulfils the original purpose of combining all elements of airportthroughput. However, there are difficulties in arriving at a value for b.

There is an inherent attractiveness in placing a value of 10 on a. Apart from being one which can beexpected to receive widespread acceptance, it is also attractive because it is a figure which does notneed to vary over time, and it is a figure which can be applied universally to all airports. These qualitiesmake for a measure which is both easy to understand and easy to calculate. In contrast, there appearto be a number of difficulties associated with the use of an individual airports average passenger load,principally:

The figure cannot be applied universally to all airports;


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The use of this figure means that, leaving aside the freight element, the ATU effectivelybecomes a measure expressing twice the actual number of passengers, plus cargo;

The figure needs to change over time to reflect shifts in average passenger loads.

A means of overcoming the first and last of these problems would exist if a non-varying figure could beidentified. We regard the logic of at least basing the figure on a measure of average passenger loadas sound. The use of a standardised figure related to the average for a sample of airports has someattractions, and in principle we would support the use of a generic figure to be applied to each of asmall number of airport groups, for example major international or regional airports. An alternativemight be to identify a figure related to overall passenger throughput, which would tend to correspondto a simple qualitative categorisation.

For the purposes of this work we considered the use of a fixed figure, which we arrived at for the 2005publication and which for the moment remains unchanged. The sample of airports which we used toderive this figure was the 41 airports which had all been included in the past three years publications.A line of best fit, constrained to go through the origin, was plotted to determine the relationshipbetween WLUs and ATMs for these airports. For all three years, the line of best fit suggests that 1 ATMis equivalent to just over 100 WLUs. This suggests that, for the 'average' airport, handling one ATMrequires approximately the same effort in some sense as handling one hundred WLUs. Since the 10 isan approximate figure, it is sensible to use the approximated figure of 100 for the second factor.

Hence, we have now adopted the following equation to define the ATU:

ATUs = Passengers + (10 * freight tonnes) + (100 * ATMs)

It will be necessary to check the data reasonably regularly to ensure that the 100 factor does not differsignificantly over time, or as a result of the addition or removal of one or two airports. This is akin toensuring that the weight of the average passenger does not change significantly from 0.1 of a tonneover time, but the ATM factor is likely to be much more sensitive.

We present a number of tables in the remainder of this section which express various inputs in termsof both passengers and ATUs. A comparison of the relative results in these cases indicates that perATU measures produce distinctly different results from per passenger measures. However, the thrustof these differences is that airports with high levels of passengers per ATM achieve lower rankings incosts per ATU measures than airports with low levels of passengers per ATM. Given this result, (whichsome might regard as counter-intuitive) we would be interested to receive any comments from usersof this publication as to the effectiveness and usefulness of this measure.

The Unit of Airport Activity (UAA)

During 2006 we have been in correspondence with the Spanish airports operator AENA, which hasdevised its own measure of total airport output, which it calls the UAA - Unit of Airport Activity/Unidadde Actividad Aeroportuaria. This is intended to capture the output of airports which is not covered bypassengers, cargo and ATMs, consisting principally of general aviation aircraft movements. To coverthis additional activity the formula for ATUs has been adapted as follows:

UAA = Commercial Passengers + (10 * Freight tonnes) + (100 * Commercial Air Transport Movements) +(5 * Other Types of Transport).

The purpose of this measure for AENA is to enable the company to compare the performance of all ofits airports, even though some of them handle little or no commercial passenger traffic. AENA is givingfurther consideration to the multiplier used to convert Other Types of Transport to UAAs, and reportedthat a multiplier of 10 may be more appropriate than 5. On this basis the perceived value of onegeneral aviation movement would be one-tenth of the value of a commercial ATM. AENAs analysis ofthis issue is continuing.

In the case of the airports in our sample in this publication, the majority handle relatively little generalaviation traffic and in the case of the more congested airports, such as London Heathrow, use of therunway by general aviation operators tends to be discouraged. Given the small number of movementsfalling into this category, and assuming a relatively small multiplier, it seems unlikely that the additionof this further traffic group would make very much difference to the ATU-denominated results. Data

availability could also be a problem in some cases. However, we can fully agree that this measureappears potentially useful in comparing the performance of small airports with little or no commercialtraffic with their larger peers, and it may be that other airport groups which include small airfields,such as ACSA and the Swedish Airports Group, would find it particularly helpful.


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Table 1: Total Revenue per ATM

Average 1,064.4 100

Ranking Airport Total Revenue/ATM Ranking Index

1 Tokyo Narita 5,928.0 556.9

2 London-Heathrow 2,741.1 257.53 Hong Kong 2,278.3 214.1

4 Singapore 1,997.4 187.7

5 Aeroports De Paris 1,815.4 170.6

6 London-Gatwick 1,764.9 165.8

7 San Francisco 1,653.0 155.3

8 Baa Group 1,617.1 151.9

9 Amsterdam Group 1,565.8 147.1

10 Athens 1,398.1 131.3

11 Zurich 1,320.1 124.0

12 Manchester 1,217.9 114.4

13 Birmingham 1,175.0 110.414 Frankfurt 1,140.5 107.2

15 Oslo 1,096.7 103.0

16 Munich 1,078.3 101.3

17 Aeroporti Di Milano 1,065.2 100.1

18 Vienna 1,053.9 99.0

19 Aeroporti Di Roma 1,053.4 99.0

20 Copenhagen 944.7 88.8

21 Miami 940.7 88.4

22 Toronto 940.2 88.3

23 Perth 936.4 88.0

24 Sydney 935.0 87.825 Ana 873.2 82.0

26 Ontario 797.5 74.9

27 Airports Of Thailand 793.9 74.6

28 Johannesburg 777.6 73.1

29 Stockholm 761.3 71.5

30 Finnish Airports Group 753.9 70.8

31 Melbourne 729.7 68.6

32 Los Angeles 705.8 66.3

33 Berlin Group 681.3 64.0

34 Auckland 668.8 62.8

35 Geneva 664.7 62.4

36 Acsa 604.0 56.8

37 Brisbane 598.3 56.2

38 Beijing 595.2 55.9

39 Aena 584.8 54.9

40 Cape Town 579.9 54.5

41 Washington Dulles 521.2 49.0

42 Vancouver 520.7 48.9

43 Washington National 512.7 48.2

44 Calgary 474.8 44.6

45 Aeroports De Montreal 466.4 43.8

46 Swedish Airports Group 459.2 43.1

47 Dallas Fort Worth 440.2 41.448 Chicago O'hare 341.9 32.1

49 Atlanta 341.2 32.1

50 Malaysian Airports 314.0 29.5


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12

Table 2: Total Revenue per 1000 ATUs

Average 4,859.3 100

Ranking Airport Total Revenue/ 1000 ATUs Ranking Index

1 Tokyo Narita 20,979.7 431.7

2 London-Heathrow 10,067.7 207.23 Aroports de Paris 7,908.8 162.8

4 Athens 7,865.7 161.9


6 BAA Group 6,999.4 144.0

7 Zurich 6,897.8 142.0


9 Birmingham 6,430.8 132.3


11 Oslo 6,103.4 125.6

12 Munich 6,071.7 124.9

13 Manchester 6,051.6 124.514 Vienna 5,999.7 123.5

15 Hong Kong 5,896.9 121.4

16 Singapore 5,534.8 113.9

17 Aeroporti di Roma 5,509.8 113.4

18 Aeroporti di Milano 5,284.8 108.8

19 Toronto 5,272.9 108.5

20 Copenhagen 5,189.5 106.8

21 Frankfurt 4,926.4 101.4

22 Finnish Airports Group 4,679.5 96.3

23 Stockholm 4,468.1 91.9

24 ANA 4,456.2 91.7

25 Sydney 4,287.5 88.2

26 Geneva 4,283.6 88.2

27 Miami 4,106.4 84.5

28 Perth 4,067.5 83.7

29 Berlin Group 4,033.3 83.0

30 Johannesburg 3,689.2 75.9

31 Auckland 3,605.0 74.2

32 Washington Dulles 3,237.0 66.6

33 Melbourne 3,219.7 66.3

34 Washington National 3,205.8 66.0

35 ACSA 3,163.0 65.1

36 Vancouver 3,121.5 64.2

37 Swedish Airports Group 3,100.6 63.8

38 Aroports de Montreal 3,016.0 62.1

39 Ontario 2,990.1 61.5

40 AENA 2,957.5 60.9

41 Brisbane 2,925.9 60.2

42 Los Angeles 2,916.6 60.0

43 Cape Town 2,877.0 59.2

44 Airports of Thailand 2,741.9 56.4

45 Calgary 2,688.8 55.3

46 Beijing 2,518.0 51.8

47 Dallas Fort Worth 2,293.2 47.248 Chicago O'Hare 1,770.4 36.4

49 Atlanta 1,748.5 36.0

50 Malaysian Airports 1,507.3 31.0


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Table 3: Total Revenue per Passenger

Average 11.23 100

Ranking Airport Total Revenue/Passenger Ranking Index

1 Tokyo Narita 34.82 310.2

2 Athens 19.55 174.23 London-Heathrow 19.02 169.5

4 Aeroports de Paris 17.72 157.9

5 Zurich 17.68 157.5

6 Vienna 16.02 142.7

7 Amsterdam Group 15.24 135.8

8 Munich 14.89 132.7

9 Oslo 14.48 129.0

10 Hong Kong 14.40 128.2

11 Birmingham 14.38 128.1

12 Manchester 14.08 125.4

13 BAA Group 13.92 124.014 Copenhagen 13.55 120.7

15 London-Gatwick 13.52 120.4


17 Toronto 13.27 118.2

18 Geneva 12.89 114.8

19 Aeroporti di Milano 12.22 108.9

20 Singapore 12.13 108.1

21 Aeroporti di Roma 12.13 108.1

22 San Francisco 11.98 106.7

23 Miami 11.97 106.6

24 Stockholm 11.49 102.425 Frankfurt 11.17 99.5

26 Aeroports de Montreal 10.61 94.6



29 ANA 9.75 86.9

30 Sydney 9.47 84.4

31 Auckland 9.41 83.9


33 Vancouver 8.95 79.8

34 Ontario 8.74 77.9



37 Perth 7.82 69.6

38 ACSA 7.48 66.7

39 Calgary 7.04 62.7


41 Melbourne 6.34 56.5

42 AENA 6.24 55.6

43 Cape Town 6.08 54.1

44 Brisbane 6.02 53.7

45 Dallas Fort Worth 5.46 48.6

46 Beijing 5.20 46.3

47 Airports of Thailand 5.20 46.348 Chicago O'Hare 4.49 40.0

49 Atlanta 3.96 35.3



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14

Table 4: Total Revenue per Employee

Average 293,566 100

Ranking Airport Total Revenue/Employee Ranking Index

1 Tokyo Narita 1,241,701 423.0

2 Sydney 1,062,977 362.13 Melbourne 765,791 260.9

4 Brisbane 673,892 229.6

5 Hong Kong 564,915 192.4

6 Calgary 471,210 160.5

7 Toronto 439,367 149.7

8 Perth 429,940 146.5

9 Vancouver 421,537 143.6

10 Auckland 413,937 141.0

11 Atlanta 393,834 134.2

12 Oslo 390,068 132.9

13 Athens 382,662 130.314 London-Heathrow 343,047 116.9

15 Amsterdam Group 331,821 113.0

16 Singapore 328,846 112.0

17 Washington Dulles 288,357 98.2

18 Stockholm 280,478 95.5

19 San Francisco 274,097 93.4

20 Zurich 269,255 91.7

21 Vienna 251,513 85.7

22 Washington National 244,607 83.3

23 Dallas Fort Worth 232,651 79.3

24 London-Gatwick 230,466 78.525 Aeroports de Paris 228,629 77.9

26 Miami 224,253 76.4

27 Manchester 223,549 76.1

28 BAA Group 206,747 70.4

29 Chicago O'Hare 203,802 69.4

30 Aeroports de Montreal 202,039 68.8

31 Aeroporti di Roma 200,076 68.2

32 Geneva 199,199 67.9

33 Swedish Airports Group 193,209 65.8

34 Aeroporti di Milano 191,605 65.3

35 AENA 189,098 64.4

36 Birmingham 183,486 62.5

37 Copenhagen 173,362 59.1

38 Johannesburg 163,294 55.6

39 ANA 135,781 46.3

40 Finnish Airports Group 135,420 46.1

41 Munich 130,761 44.5

42 Ontario 125,734 42.8

43 Cape Town 121,171 41.3

44 Los Angeles 120,765 41.1

45 ACSA 115,511 39.3

46 Berlin Group 101,449 34.6

47 Airports of Thailand 69,599 23.748 Frankfurt 51,232 17.5

49 Malaysian Airports 31,099 10.6

50 Beijing 30,475 10.4


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15

Table 5: Aeronautical Revenue per ATM

Average 596.22 100

Ranking Airport Aeronautical Revenue/ATM Ranking Index

1 Tokyo Narita 4,115.25 690.2




6 Singapore 884.76 148.4


8 Athens 849.84 142.5

9 BAA Group 822.75 138.0

10 Toronto 787.07 132.0


12 Manchester 725.77 121.7

13 Birmingham 717.32 120.314 Zurich 687.85 115.4

15 Vienna 686.61 115.2

16 Frankfurt 646.59 108.4

17 Oslo 572.43 96.0

18 ANA 564.68 94.7


20 Stockholm 538.88 90.4

21 Munich 501.73 84.2


23 Sydney 492.07 82.5

24 Airports of Thailand 490.27 82.225 Beijing 480.77 80.6


27 Miami 471.55 79.1




31 Perth 425.05 71.3

32 AENA 378.27 63.4

33 ACSA 368.28 61.8

34 Geneva 361.32 60.6

35 Cape Town 360.70 60.5

36 Calgary 358.77 60.2

37 Auckland 354.31 59.4

38 Los Angeles 348.32 58.4

39 Melbourne 332.11 55.7

40 Vancouver 329.56 55.3




44 Chicago O'Hare 253.83 42.6

45 Brisbane 253.24 42.5

46 Ontario 232.85 39.1



49 Atlanta 183.29 30.7



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Table 6: Aeronautical Revenues as a Percentage of Total Costs

Average 83.0% 100

Ranking Airport Aero. Revenues/Total Costs (%) Ranking Index

1 Atlanta 169.3% 204.1

2 Auckland 156.3% 188.43 Johannesburg 152.7% 184.1

4 Airports of Thailand 141.2% 170.2

5 Sydney 118.0% 142.3

6 ACSA 112.0% 135.0

7 Beijing 107.0% 129.0

8 Melbourne 101.4% 122.2

9 Calgary 100.7% 121.4

10 Cape Town 100.2% 120.8

11 Toronto 99.3% 119.7

12 Stockholm 96.6% 116.4

13 Vienna 96.4% 116.214 Athens 95.2% 114.8

15 Copenhagen 95.1% 114.7

16 Birmingham 86.2% 104.0

17 Dallas Fort Worth 85.6% 103.2

18 Chicago O'Hare 85.1% 102.6

19 Brisbane 83.6% 100.7

20 Tokyo Narita 82.0% 98.9

21 Amsterdam Group 79.7% 96.0

22 AENA 79.5% 95.9

23 Finnish Airports Group 79.1% 95.3

24 BAA Group 78.7% 94.8

25 Singapore 78.4% 94.5

26 Perth 78.0% 94.0

27 Malaysian Airports 77.5% 93.4

28 Vancouver 76.1% 91.7

29 ANA 75.8% 91.4

30 Manchester 75.3% 90.7

31 Aeroports de Montreal 74.5% 89.8

32 London-Heathrow 74.3% 89.6

33 Oslo 73.8% 89.0

34 Swedish Airports Group 72.6% 87.6

35 Hong Kong 69.7% 84.0

36 Aeroports de Paris 64.0% 77.2

37 Los Angeles 63.3% 76.3

38 Zurich 62.6% 75.5

39 Geneva 62.0% 74.8

40 San Francisco 61.5% 74.2

41 Aeroporti di Roma 61.2% 73.8

42 Frankfurt 59.2% 71.4

43 London-Gatwick 59.1% 71.2

44 Miami 58.9% 71.0

45 Aeroporti di Milano 56.1% 67.6

46 Berlin Group 55.4% 66.8

47 Washington Dulles 50.0% 60.248 Munich 48.4% 58.3

49 Washington National 47.7% 57.5

50 Ontario 31.4% 37.9


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Table 7: Aeronautical Revenue as a Percentage of Total Revenue

Average 56.5% 100

Ranking Airport Aero. Revenue/Total Revenue (%) Ranking Index

1 Toronto 83.7% 148.1

2 Beijing 80.8% 142.93 Calgary 75.6% 133.7


5 Stockholm 70.8% 125.2





10 Vienna 65.1% 115.3


12 AENA 64.7% 114.4

13 ANA 64.7% 114.414 Malaysian Airports 63.5% 112.4

15 Vancouver 63.3% 112.0

16 Cape Town 62.2% 110.0




20 ACSA 61.0% 107.9

21 Athens 60.8% 107.5

22 Johannesburg 60.7% 107.3




26 Frankfurt 56.7% 100.3

27 Geneva 54.4% 96.2

28 Atlanta 53.7% 95.0


30 Auckland 53.0% 93.7

31 Sydney 52.6% 93.1

32 Oslo 52.2% 92.3

33 Zurich 52.1% 92.2


35 BAA Group 50.9% 90.0

36 Miami 50.1% 88.737 Los Angeles 49.3% 87.3

38 Hong Kong 47.6% 84.2


40 Munich 46.5% 82.3

41 Melbourne 45.5% 80.5

42 Perth 45.4% 80.3


44 Singapore 44.3% 78.4


46 Brisbane 42.3% 74.9

47 London-Gatwick 41.6% 73.648 Washington Dulles 39.0% 69.0


50 Ontario 29.2% 51.7


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Table 8: Aeronautical Revenue per 1000 ATUs

Average 2,745.7 100

Ranking Airport Aeronautical Revenue/1000 ATUs Ranking Index

1 Tokyo Narita 14,564.3 530.4

2 Athens 4,781.3 174.13 London-Heathrow 4,697.0 171.1

4 Toronto 4,414.3 160.8

5 Aroports de Paris 4,194.5 152.8


7 Birmingham 3,926.0 143.0

8 Vienna 3,908.8 142.4

9 Manchester 3,606.2 131.3

10 Zurich 3,594.0 130.9

11 BAA Group 3,561.2 129.7


13 Oslo 3,185.6 116.014 Stockholm 3,162.6 115.2



17 Copenhagen 2,964.6 108.0

18 ANA 2,881.9 105.0

19 Munich 2,825.2 102.9

20 Hong Kong 2,808.2 102.3

21 Frankfurt 2,792.9 101.7

22 Berlin Group 2,615.4 95.3

23 Singapore 2,451.7 89.3



26 Geneva 2,328.6 84.8

27 Sydney 2,256.4 82.2



30 Miami 2,058.4 75.0

31 Beijing 2,033.8 74.1

32 Calgary 2,031.7 74.0


34 Vancouver 1,975.7 72.0

35 ACSA 1,928.4 70.2

36 AENA 1,912.9 69.7

37 Auckland 1,909.9 69.6

38 Perth 1,846.3 67.2

39 Cape Town 1,789.6 65.2


41 Melbourne 1,465.3 53.4

42 Los Angeles 1,439.3 52.4

43 Dallas Fort Worth 1,353.9 49.3

44 Chicago O'Hare 1,314.3 47.9


46 Brisbane 1,238.4 45.1

47 Washington National 986.6 35.948 Malaysian Airports 957.5 34.9

49 Atlanta 939.2 34.2

50 Ontario 873.0 31.8


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Table 9: Aeronautical Revenue per Passenger

Average 6.35 100

Ranking Airport Aero. Revenue/Passenger Ranking Index


2 Athens 11.88 187.23 Toronto 11.11 174.9

4 Vienna 10.44 164.4



7 Zurich 9.21 145.1

8 London-Heathrow 8.88 139.8




12 Stockholm 8.13 128.1

13 Copenhagen 7.74 121.914 Oslo 7.56 119.1



17 BAA Group 7.08 111.5

18 Geneva 7.01 110.4

19 Munich 6.93 109.2

20 Hong Kong 6.86 108.0


22 Fraport 6.33 99.7

23 ANA 6.31 99.3


25 Miami 6.00 94.5





30 Singapore 5.37 84.7

31 Calgary 5.32 83.8


33 Auckland 4.99 78.6

34 Sydney 4.98 78.5

35 ACSA 4.56 71.9

36 Beijing 4.20 66.237 AENA 4.04 63.6

38 Cape Town 3.78 59.5

39 Perth 3.55 55.9





44 Airports of Thailand 3.21 50.6



47 Ontario 2.55 40.248 Brisbane 2.55 40.2


50 Atlanta 2.13 33.5


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Table 10: Commercial Revenue per Passenger

Average 4.17 100

Ranking Airport Commercial Revenue/Passenger Ranking Index


2 London-Heathrow 8.98 215.33 London-Gatwick 7.49 179.5

4 Hong Kong 7.43 178.0

5 Zurich 7.38 176.8

6 Munich 7.16 171.5

7 Oslo 6.90 165.4

8 Athens 6.88 164.8

9 BAA Group 6.45 154.6

10 Singapore 6.36 152.5

11 Ontario 6.11 146.4


13 Miami 5.91 141.714 Washington National 5.82 139.6


16 Geneva 5.55 133.1



19 Auckland 4.43 106.1

20 Vienna 4.42 105.9




24 Sydney 4.23 101.3

25 Perth 4.20 100.6






31 ANA 3.10 74.3

32 Brisbane 2.94 70.5


34 Stockholm 2.75 66.0


36 ACSA 2.67 64.1



39 AENA 2.18 52.3

40 Cape Town 2.15 51.4

41 Toronto 1.99 47.7



44 Calgary 1.56 37.3

45 Atlanta 1.36 32.5


47 Dallas Fort Worth 1.29 30.948 Beijing 0.96 23.1


50 Frankfurt 0.77 18.5


25/165

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Table 11: Commercial Revenue as a Percentage of Total Revenue

Average 37.3% 100

Ranking Airport Commercial Revenue/Total Revenue (%) Ranking Index

1 Ontario 69.9% 187.6

2 Washington National 68.0% 182.53 Washington Dulles 59.6% 159.9


5 Perth 53.7% 144.1

6 Singapore 52.4% 140.8

7 Hong Kong 51.6% 138.5


9 Miami 49.4% 132.7

10 Los Angeles 49.2% 132.2

11 Brisbane 48.8% 131.0

12 Munich 48.0% 129.0

13 Oslo 47.6% 127.914 London-Heathrow 47.2% 126.8

15 Auckland 47.0% 126.2

16 BAA Group 46.4% 124.5

17 Sydney 44.6% 119.9

18 Melbourne 43.6% 117.0

19 Geneva 43.1% 115.7

20 Zurich 41.7% 112.0




24 ACSA 35.7% 95.9

25 Cape Town 35.3% 94.8

26 Athens 35.2% 94.4


28 AENA 34.9% 93.7

29 Atlanta 34.2% 91.9



32 ANA 31.8% 85.3






38 Vienna 27.6% 74.0




42 Stockholm 24.0% 64.3



45 Calgary 22.1% 59.4


47 Vancouver 21.0% 56.548 Beijing 18.5% 49.8

49 Toronto 15.0% 40.3

50 Frankfurt 6.9% 18.6


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Table 12: Total Costs per ATM

Average 780.9 100

Ranking Airport Total Costs/ATM Ranking Index

1 Tokyo Narita 5,015.8 642.3


4 Aeroports de Paris 1,503.6 192.5




8 Singapore 1,128.6 144.5

9 Zurich 1,098.0 140.6

10 Frankfurt 1,091.9 139.8

11 BAA Group 1,045.6 133.9

12 Munich 1,036.9 132.8

13 Manchester 964.4 123.514 Athens 892.4 114.3



17 Miami 800.7 102.5


19 Toronto 792.5 101.5

20 Oslo 775.2 99.3


22 ANA 744.7 95.4

23 Ontario 741.2 94.9

24 Vienna 712.3 91.225 Finnish Airports Group 627.0 80.3

26 Geneva 582.5 74.6


28 Stockholm 558.0 71.5


30 Perth 545.0 69.8

31 AENA 475.6 60.9

32 Beijing 449.2 57.5


34 Vancouver 433.3 55.5


36 Sydney 416.9 53.4


38 Cape Town 360.0 46.1

39 Calgary 356.1 45.6



42 ACSA 328.9 42.1

43 Melbourne 327.5 41.9



46 Brisbane 303.1 38.8

47 Chicago O'Hare 298.2 38.248 Malaysian Airports 257.4 33.0

49 Auckland 226.7 29.0

50 Atlanta 108.2 13.9


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Table 13: Total Costs per Passenger

Average 8.35 100

Ranking Airport Total Costs/Passenger Ranking Index


2 Zurich 14.71 176.23 Aeroports de Paris 14.68 175.8

4 Munich 14.32 171.5

5 Athens 12.48 149.5




9 Geneva 11.29 135.3


11 Toronto 11.18 133.9


13 Vienna 10.83 129.714 Frankfurt 10.69 128.1

15 Oslo 10.24 122.6

16 Miami 10.19 122.0




20 Hong Kong 9.84 117.9




24 BAA Group 9.00 107.8


26 Stockholm 8.42 100.9

27 ANA 8.32 99.6


29 Ontario 8.12 97.3





34 Calgary 5.28 63.2


36 AENA 5.08 60.8

37 Perth 4.55 54.5

38 Sydney 4.22 50.6

39 ACSA 4.07 48.8

40 Beijing 3.92 47.0


42 Cape Town 3.77 45.2



45 Auckland 3.19 38.2

46 Brisbane 3.05 36.6

47 Malaysian Airports 2.97 35.648 Melbourne 2.84 34.1


50 Atlanta 1.26 15.0


28/165

24

Table 14: Total Costs per 1000 ATUs

Average 3,589.2 100

Ranking Airport Total Costs/ 1000 ATUs Ranking Index

1 Tokyo Narita 17,751.4 494.6

2 Aroports de Paris 6,550.4 182.53 London-Heathrow 6,319.2 176.1

4 Munich 5,838.8 162.7

5 Zurich 5,737.3 159.8




9 Athens 5,020.8 139.9

10 Manchester 4,791.9 133.5

11 Berlin Group 4,718.5 131.5

12 Frankfurt 4,716.5 131.4

13 Birmingham 4,552.0 126.814 BAA Group 4,525.9 126.1

15 Toronto 4,444.7 123.8

16 Oslo 4,314.2 120.2


18 Vienna 4,055.2 113.0

19 Hong Kong 4,031.2 112.3



22 ANA 3,800.5 105.9

23 Geneva 3,753.9 104.6

24 Miami 3,495.1 97.4

25 Stockholm 3,274.7 91.2

26 Singapore 3,127.5 87.1

27 Copenhagen 3,115.8 86.8


29 Ontario 2,779.1 77.4


31 Vancouver 2,597.8 72.4


33 AENA 2,405.1 67.0

34 Perth 2,367.5 66.0

35 Los Angeles 2,273.4 63.3

36 Washington National 2,066.8 57.6

37 Calgary 2,016.7 56.2

38 Sydney 1,911.5 53.3

39 Beijing 1,900.0 52.9

40 Cape Town 1,786.3 49.8

41 ACSA 1,722.3 48.0

42 Dallas Fort Worth 1,580.9 44.0

43 Chicago O'Hare 1,544.0 43.0

44 Brisbane 1,482.2 41.3


46 Melbourne 1,444.9 40.3

47 Malaysian Airports 1,235.7 34.448 Auckland 1,222.1 34.0


50 Atlanta 554.7 15.5


29/165

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Table 15: Operating Costs per Passenger

Average 3.61 100

Ranking Airport Operating Costs/Passenger Ranking Index


2 Munich 7.18 199.03 Amsterdam Group 6.48 179.7

4 Toronto 6.24 173.0




8 Zurich 5.34 147.8

9 Oslo 5.29 146.6


11 Hong Kong 4.86 134.8

12 Vancouver 4.83 133.8

13 Aeroports de Montreal 4.77 132.114 Manchester 4.76 132.0


16 Athens 4.50 124.8

17 Miami 4.45 123.3


19 Geneva 4.19 116.1

20 BAA Group 4.02 111.5



23 Stockholm 3.79 105.0


25 Ontario 3.78 104.8



28 Calgary 3.13 86.6

29 ANA 3.06 84.8

30 Perth 2.58 71.4



33 Vienna 2.35 65.1


35 Beijing 2.13 59.2

36 AENA 2.07 57.3



39 Cape Town 1.81 50.0

40 ACSA 1.79 49.5





45 Sydney 1.40 38.7

46 Brisbane 1.34 37.1

47 Auckland 1.22 33.948 Dallas Fort Worth 1.20 33.4


50 Atlanta 0.32 9.0


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26

Table 16: Staff Costs as a percentage of Operating and Staff Costs

Average 38.3% 100

Ranking Airport Staff Costs/Operating and Staff Costs (%) Ranking Index

1 Frankfurt 78.8% 205.7

2 Vienna 72.1% 188.23 Copenhagen 67.1% 175.2

4 Atlanta 55.7% 145.4

5 Geneva 51.5% 134.3

6 ANA 49.7% 129.7



9 BAA Group 45.5% 118.7




13 Ontario 44.2% 115.514 Aeroports de Paris 43.6% 113.7

15 Miami 43.3% 113.0



18 ACSA 42.5% 111.0



21 AENA 41.9% 109.4





26 Washington Dulles 40.2% 104.8

27 Zurich 40.1% 104.7


29 Cape Town 39.1% 101.9

30 Auckland 37.8% 98.6


32 Stockholm 36.6% 95.6

33 Munich 36.5% 95.4


35 Athens 30.0% 78.4





40 Sydney 25.5% 66.6

41 Beijing 24.9% 64.9

42 Oslo 24.2% 63.0

43 Perth 23.0% 60.0

44 Singapore 22.3% 58.2

45 Brisbane 21.3% 55.6

46 Toronto 20.4% 53.2

47 Hong Kong 19.5% 50.948 Melbourne 19.4% 50.6

49 Vancouver 18.8% 49.2

50 Calgary 15.0% 39.2


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Table 17: Staff Costs per 1000 ATUs

Average 985.24 100

Ranking Airport Staff Costs/1000 ATUs Ranking Index

1 Tokyo Narita 2,862.69 290.6

2 Frankfurt 2,839.41 288.23 Vienna 2,275.09 230.9

4 Aroports de Paris 2,148.82 218.1

5 Berlin Group 1,742.88 176.9

6 BAA Group 1,689.68 171.5

7 Munich 1,685.91 171.1

8 London-Heathrow 1,675.37 170.0


10 Birmingham 1,607.21 163.1

11 San Francisco 1,522.16 154.5

12 Geneva 1,477.58 150.0

13 Zurich 1,395.63 141.714 ANA 1,382.15 140.3

15 Manchester 1,379.85 140.1

16 Copenhagen 1,373.70 139.4


18 Miami 1,165.70 118.3



21 Ontario 1,026.84 104.2


23 Los Angeles 963.51 97.8

24 Stockholm 851.40 86.4


26 Athens 778.27 79.0

27 Oslo 710.02 72.1

28 AENA 707.21 71.8


30 Toronto 634.85 64.4


32 ACSA 559.68 56.8

33 Cape Town 548.04 55.6


35 Aroports de Montreal 508.46 51.6

36 Hong Kong 483.30 49.1



39 Singapore 427.65 43.4


41 Perth 400.29 40.6

42 Vancouver 390.86 39.7

43 Beijing 342.48 34.8

44 Auckland 284.25 28.9


46 Sydney 216.56 22.0

47 Calgary 211.04 21.448 Melbourne 186.80 19.0

49 Atlanta 180.22 18.3

50 Brisbane 175.77 17.8


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Table 18: Staff Costs per Passenger

Average 2.32 100

Ranking Airport Staff Costs/Passenger Ranking Index


2 Vienna 6.08 261.43 Aeroports de Paris 4.82 207.2


5 Geneva 4.45 191.3


7 Munich 4.14 177.9




11 Zurich 3.58 153.9

12 Miami 3.40 146.2

13 BAA Group 3.36 144.514 Manchester 3.21 138.1



17 ANA 3.02 130.1

18 Ontario 3.00 129.1








26 Athens 1.93 83.2




30 Oslo 1.69 72.5

31 Toronto 1.60 68.7

32 AENA 1.49 64.2

33 ACSA 1.32 57.0


35 Hong Kong 1.18 50.8

36 Cape Town 1.16 49.8






42 Perth 0.77 33.1

43 Auckland 0.74 31.9

44 Beijing 0.71 30.4


46 Calgary 0.55 23.8

47 Sydney 0.48 20.648 Atlanta 0.41 17.5


50 Brisbane 0.36 15.6


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Table 19: Staff Costs as a Percentage of Turnover

Average 20.4% 100

Ranking Airport Staff Costs/Turnover (%) Ranking Index

1 Frankfurt 57.6% 282.5

2 Berlin Group 43.2% 211.83 Vienna 37.9% 185.9

4 Geneva 34.5% 169.1

5 Ontario 34.3% 168.3


7 ANA 31.0% 152.0

8 Miami 28.4% 139.2

9 Munich 27.8% 136.1




13 Copenhagen 26.5% 129.814 Chicago O'Hare 25.1% 122.9



17 BAA Group 24.1% 118.3

18 AENA 23.9% 117.2






24 Zurich 20.2% 99.2

25 Stockholm 19.1% 93.4

26 Cape Town 19.0% 93.4




30 ACSA 17.7% 86.7






36 Tokyo Narita 13.6% 66.937 Beijing 13.6% 66.7

38 Vancouver 12.5% 61.4

39 Toronto 12.0% 59.0

40 Oslo 11.6% 57.0

41 Atlanta 10.3% 50.5

42 Athens 9.9% 48.5

43 Perth 9.8% 48.2

44 Hong Kong 8.2% 40.2

45 Auckland 7.9% 38.7

46 Calgary 7.8% 38.5

47 Singapore 7.7% 37.948 Brisbane 6.0% 29.4

49 Melbourne 5.8% 28.4

50 Sydney 5.1% 24.8


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Table 20: Operating Profit

Average 28% 100

Ranking Airport Operating Profit (%) Ranking Index

1 Atlanta 68% 248.1

2 Auckland 66% 240.23 Johannesburg 60% 219.0

4 Airports of Thailand 56% 204.4

5 Sydney 55% 201.4

6 Melbourne 55% 200.3

7 Brisbane 49% 179.3

8 ACSA 46% 165.5

9 Singapore 43% 158.0

10 Perth 42% 151.9

11 Copenhagen 40% 145.2

12 Cape Town 38% 137.8

13 London-Heathrow 37% 135.314 Athens 36% 131.4

15 Washington National 36% 129.1

16 BAA Group 35% 128.4

17 Vienna 32% 117.8

18 Hong Kong 32% 115.0

19 Dallas Fort Worth 31% 112.9

20 London-Gatwick 30% 107.4

21 Oslo 29% 106.5

22 Birmingham 29% 106.2

23 Aeroporti di Roma 27% 99.8

24 Stockholm 27% 97.0

25 Calgary 25% 90.8

26 Beijing 25% 89.2

27 Los Angeles 22% 80.1

28 Amsterdam Group 22% 80.0

29 Washington Dulles 22% 79.8

30 Aeroporti di Milano 21% 76.4

31 Manchester 21% 75.6

32 AENA 19% 67.9

33 Malaysian Airports 18% 65.5

34 Aroports de Paris 17% 62.4

35 Finnish Airports Group 17% 61.2

36 Zurich 17% 61.137 Vancouver 17% 61.0

38 Toronto 16% 57.1

39 San Francisco 16% 56.8

40 Tokyo Narita 15% 55.9

41 Miami 15% 54.1

42 ANA 15% 53.5

43 Chicago O'Hare 13% 46.5

44 Geneva 12% 44.9

45 Aroports de Montreal 10% 36.1

46 Ontario 7% 25.6

47 Frankfurt 4% 15.5

48 Munich 4% 13.9

49 Swedish Airports Group 4% 13.3

50 Berlin Group -17% -61.7


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Table 21: Operating Profit per Passenger

Average 2.88 100

Ranking Airport Operating Profit/Passenger Ranking Index


2 Athens 7.07 245.83 Auckland 6.22 216.3




7 Sydney 5.25 182.4

8 Vienna 5.19 180.5


10 BAA Group 4.92 171.0

11 Hong Kong 4.55 158.3

12 Oslo 4.25 147.6

13 Birmingham 4.20 146.014 London-Gatwick 3.99 138.8

15 Melbourne 3.49 121.5

16 ACSA 3.41 118.5



19 Perth 3.27 113.6

20 Stockholm 3.07 106.7



23 Zurich 2.98 103.4

24 Brisbane 2.97 103.3



27 Atlanta 2.70 93.9


29 Cape Town 2.30 80.1


31 Toronto 2.08 72.4



34 Miami 1.78 61.9

35 Calgary 1.76 61.2


37 Geneva 1.59 55.4



40 ANA 1.44 49.9

41 Beijing 1.28 44.4

42 AENA 1.17 40.5



45 Ontario 0.62 21.4


47 Munich 0.57 19.948 Frankfurt 0.48 16.5


50 Berlin Group -1.73 -60.3


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Table 22: Return on Capital Employed

Average 7.0% 100

Ranking Airport Return on Capital Employed (%) Ranking Index


2 ACSA 21.7% 309.93 Auckland 19.3% 275.9

4 Cape Town 18.3% 261.3

5 Vienna 14.4% 205.8





10 BAA Group 11.4% 162.7

11 Melbourne 11.3% 161.0

12 Stockholm 9.8% 140.4

13 Birmingham 9.1% 129.914 Geneva 8.7% 123.9



17 Beijing 7.5% 106.7


19 ANA 7.1% 101.8

20 Singapore 6.8% 97.2

21 Oslo 6.6% 93.8

22 Athens 6.4% 90.9

23 Atlanta 6.0% 85.9




27 Perth 5.5% 78.3

28 Sydney 5.2% 74.3

29 Calgary 5.1% 72.3


31 Brisbane 4.9% 69.9

32 Vancouver 4.8% 68.1


34 Hong Kong 4.4% 63.5


36 Zurich 3.8% 54.437 Tokyo Narita 3.2% 45.3

38 AENA 3.0% 43.3





43 Miami 1.9% 26.9

44 Toronto 1.8% 26.3



47 Ontario 1.4% 19.748 Chicago O'Hare 1.3% 19.2

49 Munich 1.1% 15.0

50 Berlin Group -7.2% -103.3


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Table 23: Return on Shareholders Funds

Average (Of those >0) 4.1% 100.0

Ranking Airport Return on Shareholders Funds Ranking Index

1 Sydney 96.3% 2376.5

2 Melbourne 31.0% 765.93 Johannesburg 20.2% 498.8

4 Auckland 19.4% 477.4


6 Geneva 16.9% 417.3


8 Oslo 16.3% 401.7

9 ACSA 15.0% 370.7

10 Cape Town 13.9% 343.7


12 Stockholm 12.1% 298.1

13 Vienna 10.3% 254.514 Airports of Thailand 9.9% 243.4


16 Atlanta 8.9% 219.2





21 Athens 6.5% 159.2

22 BAA Group 6.4% 157.9

23 ANA 5.7% 141.0

24 Calgary 5.6% 138.1


26 Beijing 5.1% 125.7

27 Singapore 4.9% 119.8


29 Hong Kong 4.4% 107.7

30 Vancouver 4.3% 106.0


32 AENA 3.0% 74.9



35 Ontario 2.1% 51.3





40 Miami -0.3% -6.6

41 Zurich -1.5% -36.9

42 Chicago O'Hare -6.2% -153.1

43 Perth -7.4% -181.5

44 Brisbane -7.5% -186.0

45 Swedish Airports Group -8.5% -209.1

46 Aeroports de Montreal -11.2% -276.5

47 Munich -19.4% -479.748 Toronto -24.2% -597.6

49 San Francisco -27.7% -683.0

50 Berlin Group -110.0% -2714.1


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Table 24: Passengers per Employee

Average 29,762 100

Ranking Airport Passengers/Employee Ranking Index

1 Melbourne 120,814 405.9

2 Sydney 112,255 377.23 Brisbane 111,864 375.9

4 Atlanta 99,508 334.3

5 Calgary 66,955 225.0

6 Perth 55,000 184.8

7 Vancouver 47,083 158.2


9 Auckland 43,969 147.7


11 Hong Kong 39,242 131.9

12 Tokyo Narita 35,661 119.8

13 Toronto 33,120 111.314 Washington Dulles 31,854 107.0

15 AENA 30,284 101.8

16 Washington National 28,552 95.9

17 Singapore 27,101 91.1

18 Oslo 26,930 90.5

19 Stockholm 24,405 82.0

20 San Francisco 22,886 76.9


22 Cape Town 19,943 67.0

23 Athens 19,574 65.8

24 Aeroports de Montreal 19,035 64.0

25 Johannesburg 19,028 63.9


27 Miami 18,739 63.0

28 London-Heathrow 18,032 60.6

29 Los Angeles 18,013 60.5

30 London-Gatwick 17,052 57.3

31 Aeroporti di Roma 16,492 55.4

32 Manchester 15,876 53.3

33 Vienna 15,696 52.7

34 Aeroporti di Milano 15,677 52.7

35 Geneva 15,456 51.9

36 ACSA 15,438 51.9

37 Zurich 15,228 51.2

38 BAA Group 14,856 49.9

39 Ontario 14,386 48.3

40 ANA 13,923 46.8

41 Airports of Thailand 13,387 45.0

42 Aeroports de Paris 12,901 43.3

43 Copenhagen 12,795 43.0

44 Birmingham 12,764 42.9

45 Finnish Airports Group 10,071 33.8

46 Berlin Group 9,934 33.4

47 Munich 8,780 29.548 Malaysian Airports 8,583 28.8

49 Beijing 5,860 19.7

50 Frankfurt 4,587 15.4


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Table 25: Passengers per ATM

Average 91.4 100

Ranking Airport Passengers/ATM Ranking Index


2 Singapore 164.6 180.13 Hong Kong 158.3 173.1





8 Perth 119.8 131.1

9 BAA Group 116.2 127.1

10 Melbourne 115.1 126.0

11 Beijing 114.5 125.2

12 Los Angeles 105.3 115.2

13 Amsterdam Group 102.7 112.414 Aeroports de Paris 102.4 112.1

15 Frankfurt 102.1 111.7

16 Brisbane 99.3 108.7

17 Sydney 98.7 108.0

18 Cape Town 95.4 104.4

19 AENA 93.7 102.5

20 Ontario 91.2 99.8


22 ANA 89.5 98.0


24 Aeroporti di Roma 86.8 95.025 Malaysian Airports 86.7 94.8


27 Atlanta 86.2 94.3


29 ACSA 80.7 88.3


31 Miami 78.6 86.0


33 Oslo 75.7 82.8

34 Zurich 74.7 81.7

35 Munich 72.4 79.2

36 Athens 71.5 78.2

37 Auckland 71.0 77.7

38 Toronto 70.9 77.5


40 Calgary 67.5 73.8



43 Vienna 65.8 72.0





48 Geneva 51.6 56.4




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Table 26: ATUs per Employee

Average 69,203 100

Ranking Airport ATUs/Employee Ranking Index

1 Sydney 247,923 358.3

2 Melbourne 237,846 343.73 Brisbane 230,321 332.8

4 Atlanta 225,235 325.5

5 Calgary 175,251 253.2

6 Vancouver 135,044 195.1


8 Auckland 114,823 165.9

9 Perth 105,702 152.7


11 Hong Kong 95,799 138.4

12 Washington Dulles 89,081 128.7

13 Toronto 83,326 120.414 Washington National 76,302 110.3

15 Aroports de Montreal 66,989 96.8

16 AENA 63,938 92.4

17 Oslo 63,910 92.4

18 Stockholm 62,774 90.7


20 Singapore 59,414 85.9

21 Tokyo Narita 59,186 85.5


23 Athens 48,649 70.3

24 Geneva 46,503 67.2

25 Johannesb

Documents

Airport Performance Indicators 2006