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**LAAS Benefits Analysis**

**LAAS Efficiency, Safety, and Societal Benefits**

**Draft**

**September 17, 2004**

**Table of Contents**

[[Introduction]{.smallcaps} 3](#introduction)

[[Summary of Changes]{.smallcaps} 4](#summary-of-changes)

[[Important Considerations for Interpreting Results]{.smallcaps}
5](#important-considerations-for-interpreting-results)

[[Scope and Key Assumptions]{.smallcaps} 8](#scope-and-key-assumptions)

[[Stakeholder Validation]{.smallcaps} 9](#stakeholder-validation)

[[Efficiency Benefits]{.smallcaps} 10](#efficiency-benefits)

[[Summary of Efficiency Benefits]{.smallcaps}
10](#summary-of-efficiency-benefits)

[[Reduced Disruptions for Straight-in Precision Approaches]{.smallcaps}
25](#reduced-disruptions-for-straight-in-precision-approaches)

[[Reduced Disruptions with LAAS Takeoff Guidance]{.smallcaps}
31](#reduced-disruptions-with-laas-takeoff-guidance)

[[Benefits from LAAS-based Complex Procedures]{.smallcaps}
34](#benefits-from-laas-based-complex-procedures)

[[Benefits Due to Elimination of ILS Critical Areas]{.smallcaps}
38](#benefits-due-to-elimination-of-ils-critical-areas)

[[Benefits for Closely Spaced Parallel Approaches]{.smallcaps}
43](#benefits-for-closely-spaced-parallel-approaches)

[[Benefits From Variable Glideslopes]{.smallcaps}
47](#benefits-from-variable-glideslopes)

[[Benefits from Digital Data Uplink]{.smallcaps}
48](#benefits-from-digital-data-uplink)

[[Benefits from Airspace Confliction Resolution]{.smallcaps}
49](#benefits-from-airspace-confliction-resolution)

[[Benefits from Guided Missed Approach]{.smallcaps}
50](#benefits-from-guided-missed-approach)

[[Safety Benefits]{.smallcaps} 51](#safety-benefits)

[[Societal Benefits]{.smallcaps} 56](#societal-benefits)

[[Continuation of U.S. technology leadership in air
navigation]{.smallcaps}
57](#continuation-of-u.s.-technology-leadership-in-air-navigation)

[[International LGF and LAAS Avionics Sales Revenue]{.smallcaps}
58](#international-lgf-and-laas-avionics-sales-revenue)

[[Noise Abatement and Mitigation]{.smallcaps}
59](#noise-abatement-and-mitigation)

[[Reduced Impact on Environmentally Sensitive Areas]{.smallcaps}
63](#reduced-impact-on-environmentally-sensitive-areas)

[[LAAS As a Complement to Homeland Security]{.smallcaps}
65](#laas-as-a-complement-to-homeland-security)

[[LAAS and JPALS Offer Civilian and Military Compatibility]{.smallcaps}
67](#laas-and-jpals-offer-civilian-and-military-compatibility)

[[Expansion of Air Commerce to Smaller Communities]{.smallcaps}
68](#expansion-of-air-commerce-to-smaller-communities)

[[Increased Reliability of Air Service]{.smallcaps}
69](#increased-reliability-of-air-service)

[[Appendices]{.smallcaps} 71](#appendices)

[[Appendix A:]{.smallcaps} [Airports Included in This Study]{.smallcaps}
71](#appendix-a-airports-included-in-this-study)

[[Appendix B:]{.smallcaps} [Order of Installation of LAAS Ground
Facilities]{.smallcaps}
74](#appendix-b-order-of-installation-of-laas-ground-facilities)

[[Appendix C:]{.smallcaps} [Derivation of Disruption Costs]{.smallcaps}
76](#appendix-c-derivation-of-disruption-costs)

[[Appendix D:]{.smallcaps} [Sensitivity Analyses]{.smallcaps}
79](#appendix-d-sensitivity-analyses)

[[Appendix E:]{.smallcaps} [Derivation of the Single Airport Delay
Model]{.smallcaps}
84](#appendix-e-derivation-of-the-single-airport-delay-model)

[[Appendix F:]{.smallcaps} [Navigation Capabilities
Baseline]{.smallcaps} 89](#appendix-f-navigation-capabilities-baseline)

[[Appendix G:]{.smallcaps} [Potential LAAS Sites Outside of the 121
Airports]{.smallcaps}
102](#appendix-g-potential-laas-sites-outside-of-the-121-airports)

[[Appendix H:]{.smallcaps} [Aviation Facilities Within 23nm of the 121
Airports]{.smallcaps}
103](#appendix-h-aviation-facilities-within-23nm-of-the-121-airports)

[[Appendix I: LAAS Benefits Analysis Assumptions]{.smallcaps}
106](#appendix-i-laas-benefits-analysis-assumptions)

[[Appendix J: LAAS Efficiency Benefits by User Group]{.smallcaps}
108](#appendix-j-laas-efficiency-benefits-by-user-group)

[[Appendix K:]{.smallcaps} [Data Sources]{.smallcaps}
117](#appendix-k-data-sources)

[[Appendix L:]{.smallcaps} [List of Acronyms]{.smallcaps}
118](#appendix-l-list-of-acronyms)

[[Appendix M:]{.smallcaps} [Runway Utilization Analysis]{.smallcaps}
120](#appendix-m-runway-utilization-analysis)

[[Appendix N:]{.smallcaps} [Analysis of the Downstream Effect of
Delays]{.smallcaps} 124](#__RefHeading___Toc82945631)

[[Appendix O:]{.smallcaps} [NCDC Indicators Used to Eliminate Severe
Weather]{.smallcaps} 128](#__RefHeading___Toc82945632)

[[Appendix P:]{.smallcaps} [Stakeholders]{.smallcaps}
129](#__RefHeading___Toc82945633)

[[Notes and References]{.smallcaps} 133](#notes-and-references)

# [Introduction]{.smallcaps}

The Federal Aviation Administration (FAA) is transforming the navigation
infrastructure of the national airspace system (NAS), from a
ground-based to a Global Positioning System (GPS)-based architecture.
Part of this transformation entails the acquisition of augmentation
systems to improve the accuracy, reliability, and integrity of the GPS
signals. The Local Area Augmentation System (LAAS) is one of these
systems, specifically designed to support aircraft operations in the
terminal, approach, surface, and departure operational domains.

The FAA contracted with IBM Business Consulting Services to provide an
independent analysis that estimates the benefits attributable to LAAS
beyond those provided by existing and planned navigation services. These
benefits are estimated over a 20 year period (2009-2028), at 121
selected airports[^1], and for five distinct user groups: major
passenger airlines, regional passenger airlines, cargo carriers,
corporate jet operators, and general aviation (GA) operators in Alaska.
This analysis serves as an update of previous studies[^2] [^3] [^4] [^5]
as well as a more comprehensive and detailed evaluation of contributions
that can be expected from LAAS. The analysis is based on independent
research, and is supported by inputs solicited from both service
providers and airline industry stakeholders, including validation of
methodology, data, and output. The results of this analysis will be used
to support the FAA, the airlines, and other stakeholders in their
procurement and implementation decisions related to LAAS.

The first stage of the benefits analysis, completed in November 2003,
involved the establishment of the navigation capabilities baseline
against which all LAAS benefits would be measured[^6]. The second stage,
completed in December 2003, entailed determining the incremental
capabilities provided by LAAS, above and beyond this baseline[^7]. In
February 2004, IBM delivered a Preliminary Findings report, which
described a series of analyses conducted to estimate the monetized
incremental benefits that can be expected from implementation of LAAS,
relative to the baseline. In June 2004, IBM completed an update on the
efficiency section of the February 2004 preliminary analysis of the LAAS
benefits, and the findings were documented in a report. In August 2004,
IBM delivered the LAAS Safety and Societal Benefits report. A final
report encompassing all of the benefits will be published in October
2004.

**This Report**

This document is the draft report for efficiency, safety and societal
benefits. It builds upon, and contains updates to the February, June,
and August 2004 reports. Updates are based on feedback received from
reviewers in the form of written comments, as well as continuing
interviews with stakeholders in the FAA and the aviation industry.

# [Summary of Changes]{.smallcaps}

The following list highlights a number of important changes and
refinements made to the LAAS Benefits Analysis estimates based on
reviewer comments and continuing research. This list reflects changes
since the delivery of the June 30, 2004 Efficiency Benefits report, and
August 31, 2004 Safety and Societal Benefits report.

-   Efficiency

    -   General

        -   Long Island MacArthur airport (ISP) was added to the 120
            airports, for a new total of 121.

        -   A description of the runway utilization analysis is included
            in Appendix M.

        -   The methodology for deriving the average length of a delay
            in Cat I, II, III conditions was revised. This revision
            caused the unit cost of a disruption to decrease and
            therefore also decreased the overall benefit dollars.

        -   The average delay was added as a parameter in the
            sensitivity analysis.

        -   The downstream effect of delay factor was added as a
            parameter in the sensitivity analysis.

        -   A total of 44 Cat I and Cat II/III ILSs expected to be
            installed prior to 2009 were included in the baseline[^8].

    -   Takeoff Guidance

        -   Based on inputs received from airline operations staff and
            air carrier pilots, airports with one existing Cat III
            localizer are now included.

    -   ILS Critical Area

        -   Based on inputs received from airline operations staff, the
            upper limits of ceiling and visibility were reduced from
            800ft/2miles to actual GPS approach minima (if available) or
            GAME-estimated RNP-0.3 minima (in the absence of actual GPS
            approach). This change was made to give proper credit to
            RNAV/RNP capabilities, and resulted in the following changes
            to benefits:

            -   Airborne, Taxi-in, Taxi-out -- Significant decrease in
                Cat I benefit

            -   Taxi-in -- No longer any benefit at two airports; ATL,
                DAY

            -   Taxi-out -- No longer any benefit at three airports;
                CVG, DAY, ROC

    -   Included qualitative discussion on the following:

        -   LAAS benefits from Variable Glideslopes

        -   LAAS benefits from Digital Data Uplink

        -   LAAS benefits from Airspace Conflict Resolution

        -   LAAS benefits from Missed Approaches

-   Safety

    -   Combined terminal area and surface guidance benefits

-   Societal

    -   No changes

# [Important Considerations for Interpreting Results]{.smallcaps}

This section describes several important points about the estimates of
LAAS benefits in this study. The points presented below are intended to
highlight their importance and to foster discussion of their treatment
in this study. IBM welcomes discussion of these, and any other issues
that may impact the benefits estimates.

-   Estimates of the cost of flight disruptions are central to this
    study. IBM has worked to ensure that the most credible and
    applicable estimates are used, and has validated these estimates
    with airline industry stakeholders. However, there is substantial
    uncertainty inherent in any estimate of such complex events. Changes
    to these key cost inputs, particularly unforeseen systematic changes
    over time, could significantly alter these LAAS benefits estimates.
    The cost of disruptions is included in the sensitivity study in this
    update to the efficiency benefits.

-   Estimates of traffic increases over the 20 year period are central
    to this study. While IBM has worked to ensure that the most credible
    and applicable estimates are used, there is substantial uncertainty
    in any forecast covering such a long time period. Since the forecast
    used in this work is directly based on the FAA's 2004 Terminal Area
    Forecast (TAF), this study shares the forecast risks identified in
    the TAF documentation[^9]. Changes to the forecasts, whether due to
    unforeseen economic events, world political events, or airline
    industry structural changes, could significantly alter the basis
    upon which these LAAS benefits estimates are founded.

-   Flight disruptions are not isolated events. In general, a single
    flight disruption may have an impact on a number of other flight
    operations. The extent of this impact is dependent on a number of
    factors, including the size, location and timing of the initial
    disruption, and the nature of the airline network in which it
    occurs. This connection between disruptions can be accounted for by
    adding a factor for "downstream" effects. The specific value chosen
    for this factor has a substantial impact on total benefits. The
    estimate used here is based on a survey of published research and
    FAA guidance[^10] on the downstream effects of delays, the single
    most common form of disruption. Due to the relative importance of
    this factor, and the uncertainty surrounding its proper value, this
    report includes downstream effects in the sensitivity analysis. Full
    details of the treatment of downstream effects in this work are
    reported in Appendix N.

-   Based on assumptions regarding IOC dates, the ground facility
    installation schedule, avionics equipage rates, and minimum required
    avionics equipage, LAAS benefits accrue at each airport over a
    subset of the full 20 year period. For this reason total numbers in
    this report cannot be divided by 20 to obtain average annual
    benefits per airport.

-   The pace of development and certification of procedures, both for
    LAAS and for other advanced systems in the Baseline (*e.g.*, those
    with few currently existing procedures, like LPV) will be a key
    driver of benefits. At the inception of this analysis, IBM and the
    FAA agreed to the simplifying assumption that procedures would be
    available within four months of each system's IOC. This assumption
    allows benefits to be calculated without the added complexity of
    considering procedure development schedules. However, this
    assumption also represents a real and potentially significant source
    of uncertainty in the benefits estimates in this study.

-   Delay in the development and fielding of LAAS could cause
    significant changes to the benefit estimates. This is a particular
    concern with regard to LAAS Cat II/III capability, which is
    currently assumed in this study to be available beginning in 2013.
    Any delay to this start date without an associated extension of the
    end of the benefit study period is likely to have a significant
    impact on LAAS benefit estimates.

-   The pace and extent of LAAS equipage among airlines will be a key
    driver for LAAS benefits. In this report, IBM has assumed a certain
    rate of equipage, based on feedback received from airline operations
    representatives. If the actual rate of equipage is either faster or
    slower than assumed, benefits due to LAAS may be significantly
    impacted. Similarly, if the extent of LAAS equipage differs
    substantially from that assumed, benefits due to LAAS may be
    significantly impacted. The rate of LAAS equipage is included in the
    sensitivity analysis in this report.

-   LAAS benefits may not accrue until a substantial proportion of the
    user base is equipped. The introduction of any new technology such
    as LAAS into a system as complex as the NAS may not yield benefits
    proportional to either the number of ground or avionics systems
    installed, particularly during early stages of implementation. Due
    to the difficulties of providing air traffic control services to
    aircraft equipped with a mix of capabilities, some benefits of LAAS
    may not be achieved until a large proportion of the aircraft serving
    a particular airport are LAAS-equipped. For example, the elimination
    of ILS critical areas may not be possible while a fraction of
    arriving aircraft still require the protection of the ILS signal for
    precision approach in IMC. Other LAAS capabilities, such as support
    of low RNP procedures in the terminal area may not be as affected by
    this issue. The minimum level of LAAS equipage for benefit accrual
    is included in the sensitivity analysis in this update to the
    efficiency benefits.

-   Current guidance from the FAA suggests that LAAS approaches will use
    the ILS TERPS surfaces. While this may be necessary for the initial
    transition from ILS to LAAS-based approaches, it may also limit the
    benefit to be gained. Precision approaches using TERPS surfaces
    designed specifically for LAAS, including missed approach
    procedures, may result in lower approach minima than are currently
    permitted when ILS-based surfaces are used.

-   Changes to the assumed rate of installation of LAAS ground
    facilities will have a substantial impact on estimated LAAS
    benefits. At the assumed rate of 24 installations per year, all 121
    airports in this study can have a LAAS installed within about five
    years of IOC. If the actual rate of installation is reduced, then
    the onset of benefit accumulation will be delayed for many airports,
    with an associated reduction in overall benefits for the 20 year
    period.

-   Benefits of LAAS-based complex approaches are constrained by the
    existence of other avionics and ground systems that may provide
    similar capability. However, this does not take into account some
    advantages of LAAS that may prove operationally valuable, such as
    the ability of LAAS to improve the availability of actual navigation
    performance (ANP) in order to meet RNP standards, or the simplicity
    of using LAAS as a single system for terminal area navigation
    through precision approach and landing.

-   The primary source of approach minima (decision height and
    visibility) used in this work was published approaches, which
    supplied 77% of the minima used. Estimates of approach minima
    produced by MITRE/CAASD's GAME model were used for the remaining 23%
    of cases.

-   Box Value of Time is not included. Box Value of Time is the
    "passenger time savings" for cargo, including cargo-only airlines,
    and cargo carried on domestic major and regional carriers. The
    economic impact of flight disruptions to cargo carriers is both real
    and potentially significant. However, unlike Passenger Time Savings,
    no established guidance has been found to quantify a Box Value of
    Time.

-   As traffic increases, the percent of time an aircraft is disrupted
    also increases. This is especially true for cancellations and
    delays. For this analysis, a conservative approach is taken in which
    disruptions are only scaled linearly with traffic.

-   Although LAAS benefits are subject to a minimum avionics equipage
    requirement, no baseline system is subject to this requirement. One
    of the key assumptions in this report is the minimum required
    equipage for LAAS in order to accrue benefit. It is assumed that 80%
    of users must be equipped with LAAS before any LAAS approach
    benefits are accrued (80% "critical mass"). A range of 0% critical
    mass to 100% critical mass is investigated in the sensitivity
    analysis (See Appendix D). To be on the conservative side, no
    critical mass assumption is made for the other baseline technologies
    (*e.g.*. ILS and WAAS).

-   Benefits reported in LAAS Benefits Analysis are those estimated to
    be achievable by LAAS relative to systems in the established
    Navigation Capabilities Baseline, delivered to the FAA in
    November 2003. Some of these LAAS benefits may be reduced or
    eliminated if significant enhancements of the navigation system
    infrastructure, beyond those established in the baseline, were to be
    considered. In particular, since a majority of LAAS benefits are
    associated with straight-in approaches, the installation or upgrade
    of ILS at all runways expected to receive LAAS benefits would
    substantially reduce these benefit estimates.

-   LAAS is assumed to provide no operational improvements in some
    weather conditions. See Appendix O for the list of NCDC indicators
    used to eliminate severe weather.

-   Safety

    -   The types of events that were used in this analysis are
        relatively rare events. Consequently, even one additional air
        carrier crash event could have a profound effect on the
        resulting accident rates and future benefit projections. This
        problem does not invalidate the results, but needs to be
        considered since these events are rare.

    -   The methods chosen to conduct the initial computer screening of
        the NTSB accident records were somewhat conservative and may
        have missed relevant cases. The effect of potentially not
        including all relevant cases is to make the associated benefit
        assumptions more conservative, understating the potential
        benefit of LAAS.

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-   Societal

    -   IBM has investigated the potential quantitative LAAS Benefits
        that may be obtained through (1) sales of LAAS Ground Facility
        (LGF) and LAAS avionics to international airports and airlines,
        and (2) increased U.S. Airport Improvement Program and U.S
        airline revenue through a 1% increased load factor on 1% of
        operations. These quantitative societal benefits are highly
        speculative, and are included only to illustrate the importance
        of the economic impact that LAAS may provide. These benefits
        estimates are not incorporated into the total benefits derived
        from either the efficiency or safety benefits analyses.

    -   It is possible that many of the potential societal benefits may
        also be achieved through current or emerging procedures (*e.g.*,
        RNAV/RNP) or technologies (*e.g.*, WAAS).

# [Scope and Key Assumptions]{.smallcaps}

The LAAS benefits analysis focuses on the cost savings that can be
achieved by the likely users of LAAS navigation technology during the 20
year period from 2009 to 2028 at 121 airports. These users are the major
passenger airlines, major cargo airlines, regional airlines,
corporate/business operators, and the operators of small general
aviation aircraft in Alaska who are likely to have special needs for
such equipment because of the unique challenges of flying in Alaska. The
121 airports were selected from the relatively high-volume commercial
and business airports that are currently being utilized by potential
LAAS users, the 6 Low Rate Initial Production (LRIP) sites, the 35
Operational Evolution Plan (OEP) airports, and the airports that either
currently have or are qualified to receive Cat II/III ILSs (See Appendix
A).

Based on the latest guidance from the FAA, IBM assumed that the LAAS Cat
I and Cat II/III would have Initial Operational Capability (IOC) dates
of 2009 and 2013, respectively. In addition various assumptions had to
be made about the ground and avionics installation and procedure
availability schedules. A few of the key assumptions included the
following:

-   Ground facilities will be installed in the order of total airport
    benefits

-   The users will take approximately 6 years to equip their fleets with
    LAAS avionics

-   Benefits will not be attained until a required equipage level of 80%
    in avionics equipage is achieved

-   Procedure development will proceed in parallel with LAAS
    installations and procedures will be available 4 months after
    installation at each site to allow for flight checks.

Since the avionics equipage schedule and the minimum required equipage
level assumptions are uncertain, IBM conducted sensitivity analyses to
determine the effects on the analysis results of variation in these
values. In addition, IBM considered two scenarios related to users' Wide
Area Augmentation System (WAAS) equipage levels -- 0% and 100% equipage
were evaluated in order to bound the potential effects of WAAS on LAAS
benefits.

Finally, since the outcome of this analysis is stated in terms of the
dollar savings in direct operating costs and passenger time, a discount
rate was applied to convert future dollar values to 2004 dollars. The
rate that was selected by IBM was a 7% real discount rate, as
recommended by the Office of Management and Budget (OMB) for such
analyses. In addition, a multiplicative factor was applied to these
savings to reflect the downstream effects typically encountered with
flight disruptions.

# [Stakeholder Validation]{.smallcaps}

An important activity throughout this study was the validation of both
the methodology and specific key inputs with a wide range of service
provider and airline industry stakeholders. Feedback was obtained from
written comments provided by reviewers, from meetings with principal
stakeholder groups, and from site visits to five key airports and
airlines. The purpose of these stakeholder validation meetings was to
communicate IBM's methodologies and preliminary findings, to gain a
better understanding of current and expected airline and air traffic
operations from a variety of viewpoints, and to explore how LAAS may
provide additional benefit to such operations.

Data gathered during these visits was used to either validate or correct
the methodology, the mathematical formulas, and the specific critical
inputs that IBM used to quantify the incremental benefits of LAAS.

The IBM team wishes to recognize the organizations and individuals who
provided their insights, constructive criticism, and valuable comments
on the LAAS benefits analysis work. Appearance on this list is an
indication that each individual was afforded an opportunity to comment
on IBM's benefits analysis approach; it does not imply agreement with
IBM's approach.

Please refer to Appendix P for a list of stakeholders.

# [Efficiency Benefits]{.smallcaps}

## [Summary of Efficiency Benefits]{.smallcaps} 

Table 1A shows the best estimate for the total 20 year discounted[^11]
efficiency benefits estimated for all 121 airports. Tables 1B and 1C
show the 5^th^ and 95^th^ percentiles, respectively. The percentiles are
obtained through the sensitivity analysis which evaluates the impact on
benefits of the variability in several key input parameters, including
the cost of disruptions, the pace of LAAS equipage, the minimum required
equipage for benefit accrual, the average length of a delay, and the
ripple effect of delays. See Appendix D for details of the sensitivity
analysis. Further tables in this paper report best estimate values.

Benefits are shown for both reduced direct operating costs and passenger
time savings. These are reported separately here and in subsequent
tables so that readers can easily distinguish the magnitude of benefits
accruing to these two distinct stakeholder groups.

User decisions regarding WAAS avionics equipage are a key element in
estimating LAAS benefits. In order to place bounds on this element, IBM
and the FAA agreed that LAAS benefits in this report shall be stated for
two extreme cases: no WAAS equipage by any users, and full WAAS equipage
by all users. While neither of these two cases is likely to be
realistic, together they provide an upper and lower bound for LAAS
benefits relative to WAAS equipage. Thus, in Tables 1A, B, and C and
subsequent tables in this paper, benefits are shown for the two
alternative cases of user equipage with WAAS: assuming no WAAS equipage
by users ("0% WAAS"), and assuming full WAAS equipage by users ("100%
WAAS").

[Table 1a: Discounted 20 year LAAS Efficiency Benefits -- Best
Estimate]{.smallcaps}

+-----------------------+----------------------+----------------------+
|                       | **Direct Operating   | **Passenger Time     |
|                       | Cost**               | Savings**            |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$697,800,000        | \$838,100,000        |
|                       |                      |                      |
| **(Assuming 0% WAAS   |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$479,200,000        | \$580,800,000        |
|                       |                      |                      |
| **(Assuming 100% WAAS |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+

[Table 1b: Discounted 20 year LAAS Efficiency Benefits -- 5^th^
Percentile]{.smallcaps}

+-----------------------+----------------------+----------------------+
|                       | **Direct Operating   | **Passenger Time     |
|                       | Cost**               | Savings**            |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$673,500,000        | \$762,200,000        |
|                       |                      |                      |
| **(Assuming 0% WAAS   |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$462,100,000        | \$519,800,000        |
|                       |                      |                      |
| **(Assuming 100% WAAS |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+

[Table 1c: Discounted 20 year LAAS Efficiency Benefits -- 95^th^
Percentile]{.smallcaps}

+-----------------------+----------------------+----------------------+
|                       | **Direct Operating   | **Passenger Time     |
|                       | Cost**               | Savings**            |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$861,900,000        | \$965,600,000        |
|                       |                      |                      |
| **(Assuming 0% WAAS   |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+
| **LAAS Benefits**     | \$597,700,000        | \$666,700,000        |
|                       |                      |                      |
| **(Assuming 100% WAAS |                      |                      |
| equipage)**           |                      |                      |
+-----------------------+----------------------+----------------------+

Tables 2A and 2B show the total 20 year discounted efficiency benefits
by user group. Table 2A lists direct operating cost benefits, and Table
2B lists passenger time savings. Further details of benefits by user
group, listed by airport, are in Appendix J.

### Benefits by User Group

[Table 2a: Discounted 20 year LAAS Operating Cost Efficiency Benefits --
by User Group]{.smallcaps}[^12]

+--------------+----------+----------+----------+----------+----------+
|              | Major    | Regional | Cargo    | C        | Other GA |
|              | P        | P        | Carriers | orporate | O        |
|              | assenger | assenger |          | Jet GA   | perators |
|              | Airlines | Airlines |          | O        |          |
|              |          |          |          | perators |          |
+--------------+----------+----------+----------+----------+----------+
| **LAAS       | \$453    | \$135    | \$43     | \$55     | \$9      |
| Benefits**   | ,300,000 | ,800,000 | ,500,000 | ,800,000 | ,500,000 |
|              |          |          |          |          |          |
| (Assuming 0% |          |          |          |          |          |
| WAAS         |          |          |          |          |          |
| equipage)    |          |          |          |          |          |
+--------------+----------+----------+----------+----------+----------+
| **LAAS       | \$313    | \$94     | \$30     | \$41     | \        |
| Benefits**   | ,000,000 | ,000,000 | ,100,000 | ,400,000 | $700,000 |
|              |          |          |          |          |          |
| (Assuming    |          |          |          |          |          |
| 100% WAAS    |          |          |          |          |          |
| equipage)    |          |          |          |          |          |
+--------------+----------+----------+----------+----------+----------+

[Table 2b: Discounted 20 year LAAS Passenger Time Savings Efficiency
Benefits -- by User Group]{.smallcaps}

+--------------+----------+----------+----------+----------+----------+
|              | Major    | Regional | Cargo    | C        | Other GA |
|              | P        | P        | Carriers | orporate | O        |
|              | assenger | assenger |          | Jet GA   | perators |
|              | Airlines | Airlines |          | O        |          |
|              |          |          |          | perators |          |
+--------------+----------+----------+----------+----------+----------+
| **LAAS       | \$602    | \$221    | \$0      | \$11     | \$2      |
| Benefits**   | ,300,000 | ,800,000 |          | ,100,000 | ,800,000 |
|              |          |          |          |          |          |
| (Assuming 0% |          |          |          |          |          |
| WAAS         |          |          |          |          |          |
| equipage)    |          |          |          |          |          |
+--------------+----------+----------+----------+----------+----------+
| **LAAS       | \$417    | \$154    | \$0      | \$8      | \        |
| Benefits**   | ,900,000 | ,000,000 |          | ,700,000 | $200,000 |
|              |          |          |          |          |          |
| (Assuming    |          |          |          |          |          |
| 100% WAAS    |          |          |          |          |          |
| equipage)    |          |          |          |          |          |
+--------------+----------+----------+----------+----------+----------+

### Benefits by Efficiency Benefit Categories and by Airport

The LAAS efficiency benefits estimated in this report are attributable
to each of the five quantified efficiency benefit categories:

1.  Straight-in Approaches

2.  Takeoff Guidance

3.  Complex Procedures

4.  ILS Critical Area Elimination

5.  Parallel Approaches

The pie charts in Figure 1 show the proportion of benefit attributable
to each of the five quantified efficiency benefit categories, for the
best estimate, as summarized in Table 1A. Tables 3A and B and 4A and B
list these benefits for each of the121 airports.

### ![](media/image3.wmf){width="3.598031496062992in" height="1.5547244094488188in"}![](media/image4.wmf){width="3.2291338582677165in" height="1.5547244094488188in"}![](media/image5.wmf){width="3.598031496062992in" height="1.5543307086614173in"}![](media/image6.wmf){width="3.2291338582677165in" height="1.5547244094488188in"}

### [Figure 1. proportion of the Discounted 20 year LAAS Best Estimate Benefits Attributable to each of the Five Quantified Efficiency Benefit Categories]{.smallcaps} 

### Estimated LAAS Benefits Assuming No User Equipage with WAAS

Tables 3A and 3B show the 20 year discounted efficiency benefits, by
airport, for the scenario in which users do not equip with WAAS. These
values provide the upper bound of estimated LAAS benefits relative to
WAAS equipage by users. User operating cost benefits are shown in Table
3A, and passenger time savings are shown in Table 3B. Each airport's
rank in terms of total benefit is shown in the third column. In addition
to total benefit at each airport, the contribution to the total from
each separate efficiency benefit category is shown.

[Table 3a: Discounted 20 year LAAS operating cost Benefits -- 0% waas
equipage scenario, by Airport]{.smallcaps}

  ------------- --------------- ----------- --------------- -------------- --------------- -------------- --------------
  **Airport**   **Total         **Rank by   **Straight-In   **Takeoff      **Complex       **ILS Critical **Parallel
                Benefit**       Total       Approach**      Guidance**     Approach**      Area**         Approach**
                                Benefit**                                                                 

  ABQ           \$2,404,000     79          \$2,161,000     \$243,000      \$0             \$0            \$0

  ACK           \$8,191,000     30          \$8,191,000     \$0            \$0             \$0            \$0

  AFW           \$157,000       117         \$156,000       \$1,000        \$0             \$0            \$0

  ALB           \$8,694,000     26          \$3,349,000     \$1,167,000    \$4,178,000     \$0            \$0

  ANC           \$8,414,000     28          \$8,391,000     \$23,000       \$0             \$0            \$0

  ATL           \$13,227,000    11          \$9,843,000     \$0            \$0             \$3,384,000    \$0

  AUS           \$3,301,000     63          \$3,076,000     \$225,000      \$0             \$0            \$0

  AVL           \$939,000       96          \$394,000       \$545,000      \$0             \$0            \$0

  BDL           \$10,521,000    19          \$2,342,000     \$102,000      \$8,077,000     \$0            \$0

  BFI           \$874,000       98          \$329,000       \$545,000      \$0             \$0            \$0

  BGR           \$387,000       110         \$365,000       \$22,000       \$0             \$0            \$0

  BHM           \$6,995,000     35          \$1,456,000     \$0            \$5,539,000     \$0            \$0

  BNA           \$2,244,000     81          \$2,244,000     \$0            \$0             \$0            \$0

  BOI           \$2,606,000     76          \$2,606,000     \$0            \$0             \$0            \$0

  BOS           \$10,591,000    18          \$10,591,000    \$0            \$0             \$0            \$0

  BUF           \$5,036,000     51          \$5,011,000     \$25,000       \$0             \$0            \$0

  BUR           \$21,022,000    7           \$5,024,000     \$309,000      \$15,689,000    \$0            \$0

  BWI           \$5,167,000     48          \$5,167,000     \$0            \$0             \$0            \$0

  CAE           \$1,704,000     87          \$1,702,000     \$2,000        \$0             \$0            \$0

  CHA           \$445,000       108         \$445,000       \$0            \$0             \$0            \$0

  CHS           \$3,210,000     65          \$3,210,000     \$0            \$0             \$0            \$0

  CLE           \$21,482,000    5           \$21,482,000    \$0            \$0             \$0            \$0

  CLT           \$11,416,000    16          \$11,416,000    \$0            \$0             \$0            \$0

  CMH           \$3,640,000     60          \$2,862,000     \$778,000      \$0             \$0            \$0

  COS           \$6,648,000     38          \$4,747,000     \$1,901,000    \$0             \$0            \$0

  CVG           \$13,090,000    13          \$7,439,000     \$0            \$0             \$5,651,000    \$0

  DAB           \$656,000       104         \$263,000       \$393,000      \$0             \$0            \$0

  DAL           \$3,893,000     59          \$1,697,000     \$2,196,000    \$0             \$0            \$0

  DAY           \$2,512,000     77          \$2,432,000     \$1,000        \$0             \$79,000       \$0

  DCA           \$28,341,000    3           \$2,722,000     \$0            \$25,619,000    \$0            \$0

  DEN           \$14,861,000    10          \$14,861,000    \$0            \$0             \$0            \$0

  DFW           \$34,102,000    1           \$16,140,000    \$0            \$0             \$17,962,000   \$0

  DLH           \$1,261,000     92          \$852,000       \$409,000      \$0             \$0            \$0

  DSM           \$1,293,000     90          \$1,293,000     \$0            \$0             \$0            \$0

  DTW           \$29,316,000    2           \$23,357,000    \$0            \$0             \$2,473,000    \$3,486,000

  DVT           \$4,000         121         \$4,000         \$0            \$0             \$0            \$0

  ELP           \$93,000        118         \$60,000        \$33,000       \$0             \$0            \$0

  EUG           \$4,032,000     57          \$2,695,000     \$1,337,000    \$0             \$0            \$0

  EWR           \$9,802,000     21          \$9,802,000     \$0            \$0             \$0            \$0

  EYW           \$298,000       114         \$297,000       \$1,000        \$0             \$0            \$0

  FAI           \$704,000       102         \$704,000       \$0            \$0             \$0            \$0

  FAT           \$304,000       113         \$268,000       \$36,000       \$0             \$0            \$0

  FLL           \$2,747,000     74          \$2,223,000     \$306,000      \$0             \$0            \$218,000

  FWA           \$3,031,000     68          \$2,981,000     \$50,000       \$0             \$0            \$0

  FXE           \$93,000        119         \$71,000        \$22,000       \$0             \$0            \$0

  GEG           \$5,712,000     44          \$5,635,000     \$77,000       \$0             \$0            \$0

  GRR           \$4,422,000     55          \$3,219,000     \$1,203,000    \$0             \$0            \$0

  GSO           \$7,493,000     33          \$7,493,000     \$0            \$0             \$0            \$0

  GSP           \$880,000       97          \$880,000       \$0            \$0             \$0            \$0

  HNL           \$2,674,000     75          \$86,000        \$0            \$2,588,000     \$0            \$0

  HOU           \$11,553,000    15          \$5,375,000     \$6,178,000    \$0             \$0            \$0

  HPN           \$10,014,000    20          \$2,908,000     \$6,859,000    \$0             \$247,000      \$0

  HSV           \$621,000       106         \$269,000       \$352,000      \$0             \$0            \$0

  IAD           \$7,316,000     34          \$7,316,000     \$0            \$0             \$0            \$0

  IAH           \$11,047,000    17          \$9,924,000     \$0            \$0             \$1,123,000    \$0

  ICT           \$3,277,000     64          \$3,277,000     \$0            \$0             \$0            \$0

  ILN           \$2,758,000     73          \$2,757,000     \$1,000        \$0             \$0            \$0

  IND           \$2,934,000     70          \$2,934,000     \$0            \$0             \$0            \$0

  ISP           \$3,311,000     62          \$3,311,000     \$0            \$0             \$0            \$0

  JAN           \$351,000       112         \$347,000       \$4,000        \$0             \$0            \$0

  JAX           \$1,835,000     83          \$1,829,000     \$6,000        \$0             \$0            \$0

  JFK           \$4,989,000     52          \$4,720,000     \$0            \$0             \$0            \$269,000

  JNU           \$13,052,000    14          \$0             \$105,000      \$12,947,000    \$0            \$0

  LAS           \$416,000       109         \$411,000       \$5,000        \$0             \$0            \$0

  LAX           \$6,791,000     37          \$6,791,000     \$0            \$0             \$0            \$0

  LCK           \$167,000       116         \$108,000       \$59,000       \$0             \$0            \$0

  LGA           \$21,146,000    6           \$12,390,000    \$0            \$8,756,000     \$0            \$0

  LGB           \$6,642,000     39          \$1,910,000     \$2,020,000    \$0             \$0            \$2,712,000

  LIT           \$863,000       99          \$730,000       \$133,000      \$0             \$0            \$0

  MCI           \$4,023,000     58          \$4,023,000     \$0            \$0             \$0            \$0

  MCO           \$7,826,000     32          \$7,070,000     \$0            \$0             \$756,000      \$0

  MDT           \$1,541,000     88          \$1,094,000     \$447,000      \$0             \$0            \$0

  MDW           \$16,213,000    9           \$13,853,000    \$2,360,000    \$0             \$0            \$0

  MEM           \$9,271,000     25          \$6,394,000     \$0            \$0             \$318,000      \$2,559,000

  MHT           \$8,027,000     31          \$7,265,000     \$762,000      \$0             \$0            \$0

  MIA           \$5,041,000     50          \$5,041,000     \$0            \$0             \$0            \$0

  MKE           \$13,221,000    12          \$12,816,000    \$6,000        \$0             \$210,000      \$189,000

  MMU           \$824,000       100         \$479,000       \$345,000      \$0             \$0            \$0

  MSP           \$8,608,000     27          \$7,736,000     \$872,000      \$0             \$0            \$0

  MSY           \$5,157,000     49          \$4,979,000     \$178,000      \$0             \$0            \$0

  OAK           \$1,231,000     93          \$930,000       \$301,000      \$0             \$0            \$0

  OKC           \$5,235,000     47          \$5,100,000     \$135,000      \$0             \$0            \$0

  OMA           \$1,177,000     94          \$1,177,000     \$0            \$0             \$0            \$0

  ONT           \$356,000       111         \$356,000       \$0            \$0             \$0            \$0

  ORD           \$23,665,000    4           \$23,100,000    \$0            \$0             \$565,000      \$0

  ORF           \$4,978,000     53          \$3,696,000     \$1,202,000    \$0             \$80,000       \$0

  PBI           \$1,747,000     85          \$1,536,000     \$211,000      \$0             \$0            \$0

  PDX           \$3,140,000     66          \$2,772,000     \$311,000      \$0             \$0            \$57,000

  PHL           \$5,894,000     41          \$5,255,000     \$0            \$0             \$639,000      \$0

  PHX           \$3,078,000     67          \$1,382,000     \$1,696,000    \$0             \$0            \$0

  PIE           \$767,000       101         \$453,000       \$314,000      \$0             \$0            \$0

  PIT           \$8,198,000     29          \$8,198,000     \$0            \$0             \$0            \$0

  PVD           \$5,716,000     43          \$3,575,000     \$2,141,000    \$0             \$0            \$0

  RDU           \$9,552,000     22          \$9,471,000     \$2,000        \$0             \$0            \$79,000

  RFD           \$1,782,000     84          \$1,044,000     \$738,000      \$0             \$0            \$0

  RIC           \$5,706,000     45          \$5,561,000     \$102,000      \$0             \$43,000       \$0

  RNO           \$2,486,000     78          \$2,403,000     \$83,000       \$0             \$0            \$0

  ROC           \$2,767,000     72          \$1,889,000     \$10,000       \$0             \$868,000      \$0

  RSW           \$6,192,000     40          \$2,993,000     \$3,199,000    \$0             \$0            \$0

  SAN           \$17,045,000    8           \$0             \$0            \$17,045,000    \$0            \$0

  SAT           \$5,767,000     42          \$5,504,000     \$263,000      \$0             \$0            \$0

  SDF           \$560,000       107         \$560,000       \$0            \$0             \$0            \$0

  SEA           \$9,296,000     24          \$7,317,000     \$0            \$0             \$1,979,000    \$0

  SFB           \$284,000       115         \$151,000       \$133,000      \$0             \$0            \$0

  SFO           \$2,278,000     80          \$2,247,000     \$31,000       \$0             \$0            \$0

  SHV           \$1,262,000     91          \$1,261,000     \$1,000        \$0             \$0            \$0

  SJC           \$9,460,000     23          \$7,169,000     \$2,291,000    \$0             \$0            \$0

  SLC           \$5,562,000     46          \$3,832,000     \$0            \$0             \$0            \$1,730,000

  SMF           \$3,015,000     69          \$2,695,000     \$320,000      \$0             \$0            \$0

  SNA           \$4,207,000     56          \$365,000       \$3,842,000    \$0             \$0            \$0

  STL           \$4,616,000     54          \$4,611,000     \$5,000        \$0             \$0            \$0

  SWF           \$634,000       105         \$609,000       \$25,000       \$0             \$0            \$0

  SYR           \$1,740,000     86          \$1,737,000     \$3,000        \$0             \$0            \$0

  TEB           \$6,868,000     36          \$831,000       \$1,606,000    \$4,431,000     \$0            \$0

  TLH           \$2,867,000     71          \$1,854,000     \$1,013,000    \$0             \$0            \$0

  TPA           \$3,462,000     61          \$2,003,000     \$1,459,000    \$0             \$0            \$0

  TRI           \$689,000       103         \$689,000       \$0            \$0             \$0            \$0

  TUL           \$2,139,000     82          \$2,139,000     \$0            \$0             \$0            \$0

  TUS           \$70,000        120         \$60,000        \$10,000       \$0             \$0            \$0

  TYS           \$1,420,000     89          \$1,418,000     \$2,000        \$0             \$0            \$0

  VNY           \$1,150,000     95          \$785,000       \$365,000      \$0             \$0            \$0

  Total         \$697,822,000               \$490,819,000   \$54,458,000   \$104,869,000   \$36,377,000   \$11,299,000
  ------------- --------------- ----------- --------------- -------------- --------------- -------------- --------------

[Table 3b: Discounted 20 year LAAS Passenger Time savings -- 0% waas
equipage scenario, by Airport]{.smallcaps}

  ------------- --------------- ----------- --------------- -------------- --------------- -------------- --------------
  **Airport**   **Total         **Rank by   **Straight-In   **Takeoff      **Complex       **ILS Critical **Parallel
                Benefit**       Total       Approach**      Guidance**     Approach**      Area**         Approach**
                                Benefit**                                                                 

  ABQ           \$2,940,000     73          \$2,630,000     \$310,000      \$0             \$0            \$0

  ACK           \$11,576,000    23          \$11,576,000    \$0            \$0             \$0            \$0

  AFW           \$3,000         118         \$3,000         \$0            \$0             \$0            \$0

  ALB           \$11,320,000    25          \$4,416,000     \$1,418,000    \$5,486,000     \$0            \$0

  ANC           \$5,400,000     52          \$5,388,000     \$12,000       \$0             \$0            \$0

  ATL           \$18,420,000    11          \$12,796,000    \$0            \$0             \$5,624,000    \$0

  AUS           \$3,983,000     63          \$3,703,000     \$280,000      \$0             \$0            \$0

  AVL           \$929,000       94          \$515,000       \$414,000      \$0             \$0            \$0

  BDL           \$12,274,000    19          \$2,729,000     \$107,000      \$9,438,000     \$0            \$0

  BFI           \$180,000       112         \$67,000        \$113,000      \$0             \$0            \$0

  BGR           \$445,000       102         \$435,000       \$10,000       \$0             \$0            \$0

  BHM           \$7,894,000     35          \$1,685,000     \$0            \$6,209,000     \$0            \$0

  BNA           \$2,785,000     77          \$2,785,000     \$0            \$0             \$0            \$0

  BOI           \$3,209,000     70          \$3,209,000     \$0            \$0             \$0            \$0

  BOS           \$14,072,000    16          \$14,072,000    \$0            \$0             \$0            \$0

  BUF           \$6,232,000     44          \$6,200,000     \$32,000       \$0             \$0            \$0

  BUR           \$26,067,000    7           \$6,224,000     \$395,000      \$19,448,000    \$0            \$0

  BWI           \$6,481,000     39          \$6,481,000     \$0            \$0             \$0            \$0

  CAE           \$1,817,000     84          \$1,816,000     \$1,000        \$0             \$0            \$0

  CHA           \$429,000       104         \$429,000       \$0            \$0             \$0            \$0

  CHS           \$4,142,000     62          \$4,142,000     \$0            \$0             \$0            \$0

  CLE           \$28,632,000    5           \$28,632,000    \$0            \$0             \$0            \$0

  CLT           \$14,756,000    14          \$14,756,000    \$0            \$0             \$0            \$0

  CMH           \$4,376,000     59          \$3,593,000     \$783,000      \$0             \$0            \$0

  COS           \$8,109,000     33          \$5,836,000     \$2,273,000    \$0             \$0            \$0

  CVG           \$15,898,000    13          \$10,001,000    \$0            \$0             \$5,897,000    \$0

  DAB           \$496,000       101         \$261,000       \$235,000      \$0             \$0            \$0

  DAL           \$3,366,000     68          \$1,732,000     \$1,634,000    \$0             \$0            \$0

  DAY           \$2,619,000     78          \$2,538,000     \$1,000        \$0             \$80,000       \$0

  DCA           \$37,793,000    3           \$3,654,000     \$0            \$34,139,000    \$0            \$0

  DEN           \$19,337,000    10          \$19,337,000    \$0            \$0             \$0            \$0

  DFW           \$49,936,000    1           \$21,100,000    \$0            \$0             \$28,836,000   \$0

  DLH           \$1,134,000     93          \$895,000       \$239,000      \$0             \$0            \$0

  DSM           \$1,404,000     88          \$1,404,000     \$0            \$0             \$0            \$0

  DTW           \$39,412,000    2           \$31,184,000    \$0            \$0             \$4,093,000    \$4,135,000

  DVT           \$1,000         119         \$1,000         \$0            \$0             \$0            \$0

  ELP           \$104,000       115         \$72,000        \$32,000       \$0             \$0            \$0

  EUG           \$4,499,000     58          \$3,467,000     \$1,032,000    \$0             \$0            \$0

  EWR           \$12,062,000    21          \$12,062,000    \$0            \$0             \$0            \$0

  EYW           \$440,000       103         \$439,000       \$1,000        \$0             \$0            \$0

  FAI           \$522,000       99          \$522,000       \$0            \$0             \$0            \$0

  FAT           \$422,000       105         \$391,000       \$31,000       \$0             \$0            \$0

  FLL           \$3,480,000     67          \$2,859,000     \$403,000      \$0             \$0            \$218,000

  FWA           \$3,082,000     71          \$3,066,000     \$16,000       \$0             \$0            \$0

  FXE           \$17,000        117         \$12,000        \$5,000        \$0             \$0            \$0

  GEG           \$6,379,000     41          \$6,307,000     \$72,000       \$0             \$0            \$0

  GRR           \$4,159,000     61          \$3,320,000     \$839,000      \$0             \$0            \$0

  GSO           \$8,734,000     30          \$8,734,000     \$0            \$0             \$0            \$0

  GSP           \$1,167,000     92          \$1,167,000     \$0            \$0             \$0            \$0

  HNL           \$3,835,000     65          \$135,000       \$0            \$3,700,000     \$0            \$0

  HOU           \$13,025,000    17          \$6,234,000     \$6,791,000    \$0             \$0            \$0

  HPN           \$6,306,000     43          \$2,836,000     \$3,241,000    \$0             \$229,000      \$0

  HSV           \$576,000       98          \$309,000       \$267,000      \$0             \$0            \$0

  IAD           \$9,758,000     28          \$9,758,000     \$0            \$0             \$0            \$0

  IAH           \$14,363,000    15          \$13,014,000    \$0            \$0             \$1,349,000    \$0

  ICT           \$2,920,000     74          \$2,920,000     \$0            \$0             \$0            \$0

  ILN           \$0             120         \$0             \$0            \$0             \$0            \$0

  IND           \$2,410,000     80          \$2,410,000     \$0            \$0             \$0            \$0

  ISP           \$4,619,000     57          \$4,619,000     \$0            \$0             \$0            \$0

  JAN           \$391,000       106         \$388,000       \$3,000        \$0             \$0            \$0

  JAX           \$2,169,000     82          \$2,163,000     \$6,000        \$0             \$0            \$0

  JFK           \$6,085,000     47          \$5,778,000     \$0            \$0             \$0            \$307,000

  JNU           \$5,670,000     51          \$0             \$96,000       \$5,574,000     \$0            \$0

  LAS           \$518,000       100         \$511,000       \$7,000        \$0             \$0            \$0

  LAX           \$8,700,000     31          \$8,700,000     \$0            \$0             \$0            \$0

  LCK           \$0             121         \$0             \$0            \$0             \$0            \$0

  LGA           \$28,362,000    6           \$16,617,000    \$0            \$11,745,000    \$0            \$0

  LGB           \$4,809,000     55          \$1,744,000     \$1,436,000    \$0             \$0            \$1,629,000

  LIT           \$772,000       97          \$672,000       \$100,000      \$0             \$0            \$0

  MCI           \$5,100,000     53          \$5,100,000     \$0            \$0             \$0            \$0

  MCO           \$10,387,000    27          \$9,235,000     \$0            \$0             \$1,152,000    \$0

  MDT           \$1,672,000     85          \$1,290,000     \$382,000      \$0             \$0            \$0

  MDW           \$22,066,000    8           \$18,108,000    \$3,958,000    \$0             \$0            \$0

  MEM           \$8,192,000     32          \$5,456,000     \$0            \$0             \$251,000      \$2,485,000

  MHT           \$9,603,000     29          \$8,682,000     \$921,000      \$0             \$0            \$0

  MIA           \$5,930,000     50          \$5,930,000     \$0            \$0             \$0            \$0

  MKE           \$17,177,000    12          \$16,763,000    \$6,000        \$0             \$275,000      \$133,000

  MMU           \$168,000       114         \$85,000        \$83,000       \$0             \$0            \$0

  MSP           \$11,535,000    24          \$10,124,000    \$1,411,000    \$0             \$0            \$0

  MSY           \$6,357,000     42          \$6,111,000     \$246,000      \$0             \$0            \$0

  OAK           \$1,197,000     91          \$864,000       \$333,000      \$0             \$0            \$0

  OKC           \$6,085,000     48          \$5,951,000     \$134,000      \$0             \$0            \$0

  OMA           \$1,233,000     90          \$1,233,000     \$0            \$0             \$0            \$0

  ONT           \$390,000       107         \$390,000       \$0            \$0             \$0            \$0

  ORD           \$31,007,000    4           \$30,080,000    \$0            \$0             \$927,000      \$0

  ORF           \$6,225,000     45          \$4,723,000     \$1,424,000    \$0             \$78,000       \$0

  PBI           \$1,917,000     83          \$1,766,000     \$151,000      \$0             \$0            \$0

  PDX           \$3,916,000     64          \$3,475,000     \$384,000      \$0             \$0            \$57,000

  PHL           \$7,422,000     37          \$6,472,000     \$0            \$0             \$950,000      \$0

  PHX           \$4,366,000     60          \$1,789,000     \$2,577,000    \$0             \$0            \$0

  PIE           \$319,000       109         \$214,000       \$105,000      \$0             \$0            \$0

  PIT           \$10,912,000    26          \$10,912,000    \$0            \$0             \$0            \$0

  PVD           \$7,737,000     36          \$4,800,000     \$2,937,000    \$0             \$0            \$0

  RDU           \$12,577,000    18          \$12,516,000    \$3,000        \$0             \$0            \$58,000

  RFD           \$211,000       111         \$136,000       \$75,000       \$0             \$0            \$0

  RIC           \$6,815,000     38          \$6,675,000     \$102,000      \$0             \$38,000       \$0

  RNO           \$2,913,000     75          \$2,817,000     \$96,000       \$0             \$0            \$0

  ROC           \$3,313,000     69          \$2,201,000     \$10,000       \$0             \$1,102,000    \$0

  RSW           \$8,027,000     34          \$3,795,000     \$4,232,000    \$0             \$0            \$0

  SAN           \$21,407,000    9           \$0             \$0            \$21,407,000    \$0            \$0

  SAT           \$6,132,000     46          \$5,885,000     \$247,000      \$0             \$0            \$0

  SDF           \$380,000       108         \$380,000       \$0            \$0             \$0            \$0

  SEA           \$12,272,000    20          \$9,539,000     \$0            \$0             \$2,733,000    \$0

  SFB           \$175,000       113         \$128,000       \$47,000       \$0             \$0            \$0

  SFO           \$2,913,000     76          \$2,867,000     \$46,000       \$0             \$0            \$0

  SHV           \$1,570,000     87          \$1,570,000     \$0            \$0             \$0            \$0

  SJC           \$11,874,000    22          \$8,677,000     \$3,197,000    \$0             \$0            \$0

  SLC           \$6,454,000     40          \$4,701,000     \$0            \$0             \$0            \$1,753,000

  SMF           \$3,665,000     66          \$3,241,000     \$424,000      \$0             \$0            \$0

  SNA           \$4,922,000     54          \$143,000       \$4,779,000    \$0             \$0            \$0

  STL           \$6,016,000     49          \$6,009,000     \$7,000        \$0             \$0            \$0

  SWF           \$851,000       95          \$838,000       \$13,000       \$0             \$0            \$0

  SYR           \$2,222,000     81          \$2,219,000     \$3,000        \$0             \$0            \$0

  TEB           \$1,308,000     89          \$146,000       \$385,000      \$777,000       \$0            \$0

  TLH           \$3,042,000     72          \$2,374,000     \$668,000      \$0             \$0            \$0

  TPA           \$4,687,000     56          \$2,616,000     \$2,071,000    \$0             \$0            \$0

  TRI           \$786,000       96          \$786,000       \$0            \$0             \$0            \$0

  TUL           \$2,448,000     79          \$2,448,000     \$0            \$0             \$0            \$0

  TUS           \$79,000        116         \$69,000        \$10,000       \$0             \$0            \$0

  TYS           \$1,644,000     86          \$1,643,000     \$1,000        \$0             \$0            \$0

  VNY           \$227,000       110         \$139,000       \$88,000       \$0             \$0            \$0

  Total         \$838,065,000               \$601,562,000   \$54,191,000   \$117,923,000   \$53,614,000   \$10,775,000
  ------------- --------------- ----------- --------------- -------------- --------------- -------------- --------------

###  Estimated LAAS Benefits Assuming Full User Equipage with WAAS

Tables 4A and 4B show the 20 year discounted efficiency benefits, by
airport, for the scenario in which users equip with WAAS. These values
provide the lower bound of estimated LAAS benefits relative to WAAS
equipage by users. User operating cost benefits are shown in Table 4A,
and passenger time savings are shown in Table 4B. Each airport's rank in
terms of total benefit is shown in the third column. In addition to
total benefit at each airport, the contribution to the total from each
separate efficiency benefit category is shown.

[Table 4a: Discounted 20 year LAAS operating cost Benefits -- 100% waas
equipage scenario, by Airport]{.smallcaps}

  ------------- --------------- ----------- --------------- -------------- ------------- -------------- ------------
  **Airport**   **Total         **Rank by   **Straight-In   **Takeoff      **Complex     **ILS Critical **Parallel
                Benefit**       Total       Approach**      Guidance**     Approach**    Area**         Approach**
                                Benefit**                                                               

  ABQ           \$1,148,000     82          \$905,000       \$243,000      \$0           \$0            \$0

  ACK           \$8,191,000     16          \$8,191,000     \$0            \$0           \$0            \$0

  AFW           \$157,000       113         \$156,000       \$1,000        \$0           \$0            \$0

  ALB           \$5,527,000     30          \$3,349,000     \$1,167,000    \$1,011,000   \$0            \$0

  ANC           \$4,674,000     32          \$4,651,000     \$23,000       \$0           \$0            \$0

  ATL           \$11,947,000    7           \$9,843,000     \$0            \$0           \$2,104,000    \$0

  AUS           \$3,301,000     50          \$3,076,000     \$225,000      \$0           \$0            \$0

  AVL           \$939,000       91          \$394,000       \$545,000      \$0           \$0            \$0

  BDL           \$3,629,000     43          \$2,342,000     \$102,000      \$1,185,000   \$0            \$0

  BFI           \$874,000       94          \$329,000       \$545,000      \$0           \$0            \$0

  BGR           \$387,000       105         \$365,000       \$22,000       \$0           \$0            \$0

  BHM           \$951,000       85          \$743,000       \$0            \$208,000     \$0            \$0

  BNA           \$1,172,000     80          \$1,172,000     \$0            \$0           \$0            \$0

  BOI           \$2,606,000     60          \$2,606,000     \$0            \$0           \$0            \$0

  BOS           \$10,591,000    10          \$10,591,000    \$0            \$0           \$0            \$0

  BUF           \$4,629,000     33          \$4,604,000     \$25,000       \$0           \$0            \$0

  BUR           \$664,000       98          \$95,000        \$309,000      \$260,000     \$0            \$0

  BWI           \$5,167,000     28          \$5,167,000     \$0            \$0           \$0            \$0

  CAE           \$1,059,000     81          \$1,057,000     \$2,000        \$0           \$0            \$0

  CHA           \$401,000       103         \$401,000       \$0            \$0           \$0            \$0

  CHS           \$2,194,000     67          \$2,194,000     \$0            \$0           \$0            \$0

  CLE           \$5,026,000     29          \$5,026,000     \$0            \$0           \$0            \$0

  CLT           \$11,416,000    8           \$11,416,000    \$0            \$0           \$0            \$0

  CMH           \$3,640,000     48          \$2,862,000     \$778,000      \$0           \$0            \$0

  COS           \$5,357,000     36          \$3,456,000     \$1,901,000    \$0           \$0            \$0

  CVG           \$9,664,000     12          \$7,439,000     \$0            \$0           \$2,225,000    \$0

  DAB           \$656,000       101         \$263,000       \$393,000      \$0           \$0            \$0

  DAL           \$3,893,000     57          \$1,697,000     \$2,196,000    \$0           \$0            \$0

  DAY           \$1,352,000     75          \$1,272,000     \$1,000        \$0           \$79,000       \$0

  DCA           \$3,544,000     44          \$2,530,000     \$0            \$1,014,000   \$0            \$0

  DEN           \$14,861,000    4           \$14,861,000    \$0            \$0           \$0            \$0

  DFW           \$21,050,000    2           \$16,140,000    \$0            \$0           \$4,910,000    \$0

  DLH           \$1,215,000     83          \$806,000       \$409,000      \$0           \$0            \$0

  DSM           \$1,293,000     78          \$1,293,000     \$0            \$0           \$0            \$0

  DTW           \$13,338,000    6           \$10,842,000    \$0            \$0           \$2,473,000    \$23,000

  DVT           \$0             121         \$0             \$0            \$0           \$0            \$0

  ELP           \$93,000        117         \$60,000        \$33,000       \$0           \$0            \$0

  EUG           \$3,445,000     58          \$2,108,000     \$1,337,000    \$0           \$0            \$0

  EWR           \$9,802,000     11          \$9,802,000     \$0            \$0           \$0            \$0

  EYW           \$78,000        116         \$77,000        \$1,000        \$0           \$0            \$0

  FAI           \$463,000       100         \$463,000       \$0            \$0           \$0            \$0

  FAT           \$304,000       110         \$268,000       \$36,000       \$0           \$0            \$0

  FLL           \$2,354,000     66          \$2,040,000     \$306,000      \$0           \$0            \$8,000

  FWA           \$964,000       86          \$914,000       \$50,000       \$0           \$0            \$0

  FXE           \$49,000        118         \$27,000        \$22,000       \$0           \$0            \$0

  GEG           \$3,733,000     42          \$3,656,000     \$77,000       \$0           \$0            \$0

  GRR           \$3,962,000     47          \$2,759,000     \$1,203,000    \$0           \$0            \$0

  GSO           \$7,493,000     19          \$7,493,000     \$0            \$0           \$0            \$0

  GSP           \$880,000       87          \$880,000       \$0            \$0           \$0            \$0

  HNL           \$105,000       115         \$86,000        \$0            \$19,000      \$0            \$0

  HOU           \$11,176,000    18          \$4,998,000     \$6,178,000    \$0           \$0            \$0

  HPN           \$9,811,000     23          \$2,908,000     \$6,859,000    \$0           \$44,000       \$0

  HSV           \$621,000       102         \$269,000       \$352,000      \$0           \$0            \$0

  IAD           \$7,316,000     20          \$7,316,000     \$0            \$0           \$0            \$0

  IAH           \$11,047,000    9           \$9,924,000     \$0            \$0           \$1,123,000    \$0

  ICT           \$2,384,000     61          \$2,384,000     \$0            \$0           \$0            \$0

  ILN           \$2,758,000     59          \$2,757,000     \$1,000        \$0           \$0            \$0

  IND           \$2,934,000     52          \$2,934,000     \$0            \$0           \$0            \$0

  ISP           \$2,902,000     54          \$2,902,000     \$0            \$0           \$0            \$0

  JAN           \$351,000       109         \$347,000       \$4,000        \$0           \$0            \$0

  JAX           \$1,835,000     70          \$1,829,000     \$6,000        \$0           \$0            \$0

  JFK           \$4,724,000     31          \$4,720,000     \$0            \$0           \$0            \$4,000

  JNU           \$417,000       106         \$0             \$105,000      \$312,000     \$0            \$0

  LAS           \$32,000        119         \$27,000        \$5,000        \$0           \$0            \$0

  LAX           \$6,791,000     21          \$6,791,000     \$0            \$0           \$0            \$0

  LCK           \$167,000       114         \$108,000       \$59,000       \$0           \$0            \$0

  LGA           \$13,672,000    5           \$12,390,000    \$0            \$1,282,000   \$0            \$0

  LGB           \$3,295,000     64          \$1,010,000     \$2,020,000    \$0           \$0            \$265,000

  LIT           \$638,000       96          \$505,000       \$133,000      \$0           \$0            \$0

  MCI           \$4,023,000     39          \$4,023,000     \$0            \$0           \$0            \$0

  MCO           \$4,337,000     37          \$3,581,000     \$0            \$0           \$756,000      \$0

  MDT           \$1,541,000     77          \$1,094,000     \$447,000      \$0           \$0            \$0

  MDW           \$16,108,000    3           \$13,748,000    \$2,360,000    \$0           \$0            \$0

  MEM           \$6,546,000     22          \$6,394,000     \$0            \$0           \$50,000       \$102,000

  MHT           \$6,293,000     24          \$5,531,000     \$762,000      \$0           \$0            \$0

  MIA           \$3,117,000     51          \$3,117,000     \$0            \$0           \$0            \$0

  MKE           \$5,178,000     27          \$4,945,000     \$6,000        \$0           \$210,000      \$17,000

  MMU           \$540,000       107         \$195,000       \$345,000      \$0           \$0            \$0

  MSP           \$8,608,000     17          \$7,736,000     \$872,000      \$0           \$0            \$0

  MSY           \$2,943,000     55          \$2,765,000     \$178,000      \$0           \$0            \$0

  OAK           \$1,112,000     84          \$811,000       \$301,000      \$0           \$0            \$0

  OKC           \$3,543,000     46          \$3,408,000     \$135,000      \$0           \$0            \$0

  OMA           \$1,177,000     79          \$1,177,000     \$0            \$0           \$0            \$0

  ONT           \$356,000       108         \$356,000       \$0            \$0           \$0            \$0

  ORD           \$23,665,000    1           \$23,100,000    \$0            \$0           \$565,000      \$0

  ORF           \$4,922,000     38          \$3,696,000     \$1,202,000    \$0           \$24,000       \$0

  PBI           \$927,000       88          \$716,000       \$211,000      \$0           \$0            \$0

  PDX           \$3,085,000     53          \$2,772,000     \$311,000      \$0           \$0            \$2,000

  PHL           \$5,894,000     25          \$5,255,000     \$0            \$0           \$639,000      \$0

  PHX           \$3,078,000     65          \$1,382,000     \$1,696,000    \$0           \$0            \$0

  PIE           \$539,000       104         \$225,000       \$314,000      \$0           \$0            \$0

  PIT           \$8,198,000     15          \$8,198,000     \$0            \$0           \$0            \$0

  PVD           \$4,619,000     45          \$2,478,000     \$2,141,000    \$0           \$0            \$0

  RDU           \$9,479,000     13          \$9,471,000     \$2,000        \$0           \$0            \$6,000

  RFD           \$1,022,000     92          \$284,000       \$738,000      \$0           \$0            \$0

  RIC           \$3,240,000     49          \$3,117,000     \$102,000      \$0           \$21,000       \$0

  RNO           \$614,000       95          \$531,000       \$83,000       \$0           \$0            \$0

  ROC           \$2,077,000     68          \$1,759,000     \$10,000       \$0           \$308,000      \$0

  RSW           \$6,192,000     35          \$2,993,000     \$3,199,000    \$0           \$0            \$0

  SAN           \$682,000       89          \$0             \$0            \$682,000     \$0            \$0

  SAT           \$5,767,000     26          \$5,504,000     \$263,000      \$0           \$0            \$0

  SDF           \$560,000       97          \$560,000       \$0            \$0           \$0            \$0

  SEA           \$8,778,000     14          \$7,317,000     \$0            \$0           \$1,461,000    \$0

  SFB           \$260,000       112         \$127,000       \$133,000      \$0           \$0            \$0

  SFO           \$2,278,000     63          \$2,247,000     \$31,000       \$0           \$0            \$0

  SHV           \$681,000       90          \$680,000       \$1,000        \$0           \$0            \$0

  SJC           \$4,897,000     41          \$2,606,000     \$2,291,000    \$0           \$0            \$0

  SLC           \$3,890,000     40          \$3,832,000     \$0            \$0           \$0            \$58,000

  SMF           \$3,015,000     56          \$2,695,000     \$320,000      \$0           \$0            \$0

  SNA           \$4,022,000     69          \$180,000       \$3,842,000    \$0           \$0            \$0

  STL           \$4,616,000     34          \$4,611,000     \$5,000        \$0           \$0            \$0

  SWF           \$295,000       111         \$270,000       \$25,000       \$0           \$0            \$0

  SYR           \$1,323,000     76          \$1,320,000     \$3,000        \$0           \$0            \$0

  TEB           \$2,518,000     72          \$742,000       \$1,606,000    \$170,000     \$0            \$0

  TLH           \$2,867,000     62          \$1,854,000     \$1,013,000    \$0           \$0            \$0

  TPA           \$2,103,000     74          \$644,000       \$1,459,000    \$0           \$0            \$0

  TRI           \$607,000       93          \$607,000       \$0            \$0           \$0            \$0

  TUL           \$1,816,000     71          \$1,816,000     \$0            \$0           \$0            \$0

  TUS           \$32,000        120         \$22,000        \$10,000       \$0           \$0            \$0

  TYS           \$1,420,000     73          \$1,418,000     \$2,000        \$0           \$0            \$0

  VNY           \$683,000       99          \$318,000       \$365,000      \$0           \$0            \$0

  Total         \$479,192,000               \$401,114,000   \$54,458,000   \$6,143,000   \$16,992,000   \$485,000
  ------------- --------------- ----------- --------------- -------------- ------------- -------------- ------------

[Table 4b: Discounted 20 year LAAS Passenger Time savings -- 100% waas
equipage scenario, by Airport]{.smallcaps}

  ------------- --------------- ----------- --------------- -------------- ------------- -------------- ------------
  **Airport**   **Total         **Rank by   **Straight-In   **Takeoff      **Complex     **ILS Critical **Parallel
                Benefit**       Total       Approach**      Guidance**     Approach**    Area**         Approach**
                                Benefit**                                                               

  ABQ           \$1,409,000     78          \$1,099,000     \$310,000      \$0           \$0            \$0

  ACK           \$11,576,000    15          \$11,576,000    \$0            \$0           \$0            \$0

  AFW           \$3,000         118         \$3,000         \$0            \$0           \$0            \$0

  ALB           \$7,159,000     27          \$4,416,000     \$1,418,000    \$1,325,000   \$0            \$0

  ANC           \$3,070,000     57          \$3,058,000     \$12,000       \$0           \$0            \$0

  ATL           \$16,293,000    7           \$12,796,000    \$0            \$0           \$3,497,000    \$0

  AUS           \$3,983,000     48          \$3,703,000     \$280,000      \$0           \$0            \$0

  AVL           \$929,000       90          \$515,000       \$414,000      \$0           \$0            \$0

  BDL           \$4,222,000     43          \$2,729,000     \$107,000      \$1,386,000   \$0            \$0

  BFI           \$180,000       109         \$67,000        \$113,000      \$0           \$0            \$0

  BGR           \$445,000       95          \$435,000       \$10,000       \$0           \$0            \$0

  BHM           \$1,081,000     82          \$839,000       \$0            \$242,000     \$0            \$0

  BNA           \$1,447,000     75          \$1,447,000     \$0            \$0           \$0            \$0

  BOI           \$3,209,000     55          \$3,209,000     \$0            \$0           \$0            \$0

  BOS           \$14,072,000    10          \$14,072,000    \$0            \$0           \$0            \$0

  BUF           \$5,897,000     30          \$5,865,000     \$32,000       \$0           \$0            \$0

  BUR           \$742,000       93          \$28,000        \$395,000      \$319,000     \$0            \$0

  BWI           \$6,481,000     26          \$6,481,000     \$0            \$0           \$0            \$0

  CAE           \$1,128,000     81          \$1,127,000     \$1,000        \$0           \$0            \$0

  CHA           \$421,000       97          \$421,000       \$0            \$0           \$0            \$0

  CHS           \$2,832,000     60          \$2,832,000     \$0            \$0           \$0            \$0

  CLE           \$6,744,000     25          \$6,744,000     \$0            \$0           \$0            \$0

  CLT           \$14,756,000    8           \$14,756,000    \$0            \$0           \$0            \$0

  CMH           \$4,376,000     47          \$3,593,000     \$783,000      \$0           \$0            \$0

  COS           \$6,521,000     36          \$4,248,000     \$2,273,000    \$0           \$0            \$0

  CVG           \$12,300,000    12          \$10,001,000    \$0            \$0           \$2,299,000    \$0

  DAB           \$496,000       102         \$261,000       \$235,000      \$0           \$0            \$0

  DAL           \$3,366,000     63          \$1,732,000     \$1,634,000    \$0           \$0            \$0

  DAY           \$1,405,000     76          \$1,324,000     \$1,000        \$0           \$80,000       \$0

  DCA           \$4,727,000     38          \$3,376,000     \$0            \$1,351,000   \$0            \$0

  DEN           \$19,337,000    4           \$19,337,000    \$0            \$0           \$0            \$0

  DFW           \$28,957,000    2           \$21,100,000    \$0            \$0           \$7,857,000    \$0

  DLH           \$1,125,000     83          \$886,000       \$239,000      \$0           \$0            \$0

  DSM           \$1,404,000     77          \$1,404,000     \$0            \$0           \$0            \$0

  DTW           \$18,359,000    5           \$14,263,000    \$0            \$0           \$4,093,000    \$3,000

  DVT           \$0             119         \$0             \$0            \$0           \$0            \$0

  ELP           \$104,000       112         \$72,000        \$32,000       \$0           \$0            \$0

  EUG           \$3,675,000     56          \$2,643,000     \$1,032,000    \$0           \$0            \$0

  EWR           \$12,062,000    13          \$12,062,000    \$0            \$0           \$0            \$0

  EYW           \$107,000       110         \$106,000       \$1,000        \$0           \$0            \$0

  FAI           \$452,000       94          \$452,000       \$0            \$0           \$0            \$0

  FAT           \$422,000       98          \$391,000       \$31,000       \$0           \$0            \$0

  FLL           \$3,019,000     61          \$2,615,000     \$403,000      \$0           \$0            \$1,000

  FWA           \$831,000       87          \$815,000       \$16,000       \$0           \$0            \$0

  FXE           \$9,000         117         \$4,000         \$5,000        \$0           \$0            \$0

  GEG           \$4,148,000     44          \$4,076,000     \$72,000       \$0           \$0            \$0

  GRR           \$3,929,000     53          \$3,090,000     \$839,000      \$0           \$0            \$0

  GSO           \$8,734,000     20          \$8,734,000     \$0            \$0           \$0            \$0

  GSP           \$1,167,000     80          \$1,167,000     \$0            \$0           \$0            \$0

  HNL           \$167,000       107         \$135,000       \$0            \$32,000      \$0            \$0

  HOU           \$12,616,000    19          \$5,825,000     \$6,791,000    \$0           \$0            \$0

  HPN           \$6,118,000     42          \$2,836,000     \$3,241,000    \$0           \$41,000       \$0

  HSV           \$576,000       96          \$309,000       \$267,000      \$0           \$0            \$0

  IAD           \$9,758,000     18          \$9,758,000     \$0            \$0           \$0            \$0

  IAH           \$14,363,000    9           \$13,014,000    \$0            \$0           \$1,349,000    \$0

  ICT           \$2,104,000     68          \$2,104,000     \$0            \$0           \$0            \$0

  ILN           \$0             120         \$0             \$0            \$0           \$0            \$0

  IND           \$2,410,000     65          \$2,410,000     \$0            \$0           \$0            \$0

  ISP           \$4,055,000     45          \$4,055,000     \$0            \$0           \$0            \$0

  JAN           \$391,000       100         \$388,000       \$3,000        \$0           \$0            \$0

  JAX           \$2,169,000     67          \$2,163,000     \$6,000        \$0           \$0            \$0

  JFK           \$5,778,000     32          \$5,778,000     \$0            \$0           \$0            \$0

  JNU           \$353,000       105         \$0             \$96,000       \$257,000     \$0            \$0

  LAS           \$43,000        115         \$36,000        \$7,000        \$0           \$0            \$0

  LAX           \$8,700,000     21          \$8,700,000     \$0            \$0           \$0            \$0

  LCK           \$0             121         \$0             \$0            \$0           \$0            \$0

  LGA           \$18,336,000    6           \$16,617,000    \$0            \$1,719,000   \$0            \$0

  LGB           \$2,378,000     73          \$910,000       \$1,436,000    \$0           \$0            \$32,000

  LIT           \$660,000       92          \$560,000       \$100,000      \$0           \$0            \$0

  MCI           \$5,100,000     37          \$5,100,000     \$0            \$0           \$0            \$0

  MCO           \$5,746,000     33          \$4,594,000     \$0            \$0           \$1,152,000    \$0

  MDT           \$1,672,000     74          \$1,290,000     \$382,000      \$0           \$0            \$0

  MDW           \$22,047,000    3           \$18,089,000    \$3,958,000    \$0           \$0            \$0

  MEM           \$5,507,000     34          \$5,456,000     \$0            \$0           \$39,000       \$12,000

  MHT           \$7,527,000     23          \$6,606,000     \$921,000      \$0           \$0            \$0

  MIA           \$3,684,000     50          \$3,684,000     \$0            \$0           \$0            \$0

  MKE           \$6,752,000     24          \$6,469,000     \$6,000        \$0           \$275,000      \$2,000

  MMU           \$118,000       113         \$35,000        \$83,000       \$0           \$0            \$0

  MSP           \$11,535,000    17          \$10,124,000    \$1,411,000    \$0           \$0            \$0

  MSY           \$3,654,000     52          \$3,408,000     \$246,000      \$0           \$0            \$0

  OAK           \$1,167,000     84          \$834,000       \$333,000      \$0           \$0            \$0

  OKC           \$4,078,000     46          \$3,944,000     \$134,000      \$0           \$0            \$0

  OMA           \$1,233,000     79          \$1,233,000     \$0            \$0           \$0            \$0

  ONT           \$390,000       99          \$390,000       \$0            \$0           \$0            \$0

  ORD           \$31,007,000    1           \$30,080,000    \$0            \$0           \$927,000      \$0

  ORF           \$6,171,000     35          \$4,723,000     \$1,424,000    \$0           \$24,000       \$0

  PBI           \$927,000       86          \$776,000       \$151,000      \$0           \$0            \$0

  PDX           \$3,859,000     51          \$3,475,000     \$384,000      \$0           \$0            \$0

  PHL           \$7,422,000     22          \$6,472,000     \$0            \$0           \$950,000      \$0

  PHX           \$4,366,000     58          \$1,789,000     \$2,577,000    \$0           \$0            \$0

  PIE           \$223,000       106         \$118,000       \$105,000      \$0           \$0            \$0

  PIT           \$10,912,000    16          \$10,912,000    \$0            \$0           \$0            \$0

  PVD           \$6,195,000     41          \$3,258,000     \$2,937,000    \$0           \$0            \$0

  RDU           \$12,520,000    11          \$12,516,000    \$3,000        \$0           \$0            \$1,000

  RFD           \$109,000       114         \$34,000        \$75,000       \$0           \$0            \$0

  RIC           \$3,857,000     49          \$3,736,000     \$102,000      \$0           \$19,000       \$0

  RNO           \$728,000       91          \$632,000       \$96,000       \$0           \$0            \$0

  ROC           \$2,513,000     64          \$2,111,000     \$10,000       \$0           \$392,000      \$0

  RSW           \$8,027,000     31          \$3,795,000     \$4,232,000    \$0           \$0            \$0

  SAN           \$853,000       85          \$0             \$0            \$853,000     \$0            \$0

  SAT           \$6,132,000     29          \$5,885,000     \$247,000      \$0           \$0            \$0

  SDF           \$380,000       101         \$380,000       \$0            \$0           \$0            \$0

  SEA           \$11,708,000    14          \$9,539,000     \$0            \$0           \$2,169,000    \$0

  SFB           \$170,000       108         \$123,000       \$47,000       \$0           \$0            \$0

  SFO           \$2,913,000     59          \$2,867,000     \$46,000       \$0           \$0            \$0

  SHV           \$788,000       88          \$788,000       \$0            \$0           \$0            \$0

  SJC           \$6,368,000     39          \$3,171,000     \$3,197,000    \$0           \$0            \$0

  SLC           \$4,708,000     40          \$4,701,000     \$0            \$0           \$0            \$7,000

  SMF           \$3,665,000     54          \$3,241,000     \$424,000      \$0           \$0            \$0

  SNA           \$4,849,000     66          \$70,000        \$4,779,000    \$0           \$0            \$0

  STL           \$6,016,000     28          \$6,009,000     \$7,000        \$0           \$0            \$0

  SWF           \$343,000       104         \$330,000       \$13,000       \$0           \$0            \$0

  SYR           \$1,679,000     71          \$1,676,000     \$3,000        \$0           \$0            \$0

  TEB           \$545,000       103         \$130,000       \$385,000      \$30,000      \$0            \$0

  TLH           \$3,042,000     62          \$2,374,000     \$668,000      \$0           \$0            \$0

  TPA           \$2,911,000     70          \$840,000       \$2,071,000    \$0           \$0            \$0

  TRI           \$730,000       89          \$730,000       \$0            \$0           \$0            \$0

  TUL           \$2,091,000     69          \$2,091,000     \$0            \$0           \$0            \$0

  TUS           \$35,000        116         \$25,000        \$10,000       \$0           \$0            \$0

  TYS           \$1,644,000     72          \$1,643,000     \$1,000        \$0           \$0            \$0

  VNY           \$144,000       111         \$56,000        \$88,000       \$0           \$0            \$0

  Total         \$580,846,000               \$493,920,000   \$54,191,000   \$7,514,000   \$25,163,000   \$58,000
  ------------- --------------- ----------- --------------- -------------- ------------- -------------- ------------

##  [Reduced Disruptions for Straight-in Precision Approaches]{.smallcaps}

In the LAAS Navigation Capabilities Baseline[^13], IBM identified a set
of operational capabilities for which LAAS is expected to provide a
benefit. Two of these operational capabilities are precision approaches
down to Cat I minima and Cat II/III minima, respectively. The
operational justification for the benefits arises from the expectation
that 1) LAAS Cat I will reduce the landing minima at runways without Cat
I service and 2) LAAS Cat II/III will reduce minima at runways without a
corresponding ILS Cat II or III capability.

In instrument meteorological conditions (IMC), if a runway has no
precision approach, instrument approaches must be conducted using
non-precision approach (NPA) procedures. The minima for such procedures
are typically a ceiling of 400 to 500 feet and 1 mile visibility
(without approach lights). LAAS Cat I is expected to be able to support
precision approaches down to a 200 foot Decision Height (DH) and 1/2
mile visibility (with approach lights). This lowering of minima can
result in fewer 1) flight cancellations, 2) diversions to alternate
airports, and 3) delays, all of which can occur when a pilot cannot see
the runway at the decision height or the airport shuts down the runway
due to visibility below minima for the available approaches. These types
of disruptions can be very costly to the users, particularly the
scheduled airlines, and can lead to major problems at the local airport
as well as regionally or even nationally. Further, assuming that a LAAS
Cat II capability is developed that meets the more stringent performance
requirements for Cat II operations, it will be possible to achieve a
ceiling/visibility reduction down to a 100 foot DH and 1200 foot runway
visual range (RVR) (with lights and other supporting infrastructure).
Similarly, further development is expected to result in LAAS achieving
Cat III minima.

In this section, the methodology that IBM used to calculate the monetary
value of the benefit achieved for straight-in approaches from a
reduction in disrupted flights is described. The methodology is based on
analytical approaches used to derive similar benefits for the Microwave
Landing System[^14] and for the European Geostationary Navigation
Overlay Service (EGNOS)[^15]. Note that although the methodology is
being described for straight-in approaches, it was also used to
calculate the benefits from complex approaches, assuming that these
approaches result in further reductions in approach minima (*e.g.,* by
achieving separation from obstacles which currently limit straight-in
approach minima) and they are approved for LAAS by the FAA.

Although the horizontal and vertical navigational accuracy achieved with
LAAS is expected to be greater than that obtained with ILS[^16], the FAA
has decided to use the ILS Terminal Instrument Procedures (TERPS)
criteria for initial LAAS approach implementations. This will result in
the approach minima being the same for both ILS and LAAS. If the TERPS
surfaces are later adjusted to take advantage of the improved accuracy
of LAAS, either for the approach or the missed approach segments, the
associated minima may be reduced below the minima for ILS. Consequently,
for this analysis of straight-in approach benefits, LAAS was assumed to
offer no improvement over existing ILS minima.

### Derivation of the Mathematical Formula for Calculating Benefits

### Preprocessing Step 

The derivation of the mathematical formula begins with a preprocessing
step to tailor the list of runways considered in the analysis to include
only those that are appropriate candidates for LAAS benefits. There are
a total of 716 runways at the 121 airports selected for this study.
Runways that are not eligible candidates for possible improvement from
LAAS Cat I or Cat II/III are discarded from consideration. These
eliminated runways include the following:

-   Runways not currently used or planned to be used for arrivals

-   Runways that are less than 4200 feet in length, the shortest
    acceptable runway length for a precision approach

-   For LAAS Cat I, all runways equipped, or planned to be equipped
    prior to 2009, with an ILS Cat I, II, or III, since LAAS is not
    expected to offer any improvement in these circumstances

-   For LAAS Cat II/III, all runways equipped with a Cat II or III ILS

### In addition to the elimination of these runways from consideration any airport, along with its associated runways, was removed if the projected demand for runway resources is sufficiently less than the IMC capacity of the airport. 

There are several possible methods for calculating the demand/capacity
ratio of any airport. IBM has selected the following approach for its
simplicity and availability of relevant data:

-   For each airport, determine the maximum sustainable arrival
    throughput during different weather conditions using Enhanced
    Traffic Management System (ETMS) traffic data and National Climatic
    Data Center (NCDC) weather data for CY2000. Since VFR flights are
    not captured in ETMS data, this method is not applicable to a few
    airports that have significant VFR traffic (*e.g.*, ACK).

-   Calculate the percent drop in observed throughput from VMC to IMC
    for each airport. A previous IBM analysis that calculated
    theoretical throughput change from VMC to IMC found that up to a 9%
    drop is expected based solely on required changes in longitudinal
    separations between arrivals. Thus, an observed drop of 10% or
    greater is likely to be associated with operational issues that LAAS
    may be able to address.

-   If the airport's throughput drops by less than 10% from VMC to IMC,
    then there is considered to be little that LAAS can provide as an
    incremental benefit from reduced straight-in disruptions. This
    airport and its associated runways are removed from consideration.

### Mathematical Formulation of the Benefits Derived from Lower Approach Minima

To quantify the benefits that may be achieved by LAAS from the reduction
in arrival disruptions due to lower approach minima, two values must be
derived:

1.  the number of disruptions avoidable with LAAS

2.  the monetary savings obtained from each avoided disruption

The product of these two values yields the benefit that can be expected
from the lower minima achievable with LAAS over what is possible with
the baseline systems (see Appendix F for a listing of baseline systems).
In this report, it is assumed that the baseline consists of existing and
planned technologies, and does not include those that might be
justified, but are not currently included in the FAA's plans (*e.g.*,
expanded installation of ILS at a variety of locations). The total
benefit is obtained by summing this product over three dimensions:

1.  each year in the 20-year time horizon of this study

2.  each runway that passed successfully through the preprocessing
    filter described above

3.  all user groups (*i.e.*, major passenger airlines, major cargo
    airlines, regional airlines, corporate jet aircraft, and small GA
    aircraft in Alaska)

Expressed mathematically, this product and sum appear as follows:

$$B = \sum_{\text{ijk}}^{}T_{\text{ijk}}S_{\text{ik}}$$

where *B* is the LAAS benefit for straight-in approaches, *i* is the
year, *j* is the runway, *k* is the user group, $T_{\text{ijk}}$is the
total number of avoidable disruptions in year *i* at runway end *j* by
user group *k*, and $S_{\text{ik}}$is the monetary operational savings
obtained from each avoided disruption in year *i* by user group *k.*

It should be noted that this formula gives the total operational benefit
for the various user groups, but does not include the benefit to the
passengers. That benefit, based on the Passenger Time Savings (PTS) is
calculated similarly except that $S_{\text{ik}}$is replaced
with$P_{\text{ik}}$, the PTS from each avoided disruption in year *i* by
user group *k.* PTS benefits are calculated for all user groups except
cargo airlines.

### Derivation of the Number of Disruptions Avoidable with LAAS

To derive the number of disruptions that can be avoided with LAAS, the
number can be broken down into its various components. This number can
be expressed as follows:

$$T_{\text{ijk}} = (N_{\text{ik}}U_{\text{jk}}(W^{B_{j}}A^{B}E_{\text{ik}^{B}} + W_{j^{\text{NB}}}(1 - A^{B}E_{\text{ik}^{B}}))A^{L}E^{L_{\text{ik}}})R$$

where;

$T_{\text{ijk}}$ is the total number of avoidable disruptions in year
*i*, on runway *j*, by user group *k,*

$N_{\text{ik}}$is the number of arrivals at this airport in year *i* by
user group *k,*

$U_{\text{jK}}$is the probability that runway *j* will be used for
arrivals of user group *k,*

$W^{B_{j}}$is the probability that the weather at this airport is
between the minima in ceiling and visibility for LAAS Cat X (where X is
either I, II/III) and the [B]{.underline}aseline navigation system on
runway *j,*

$W^{\text{NB}_{j}}$is the probability that the weather at this airport
is between the minima in ceiling and visibility for LAAS Cat X and the
[N]{.underline}ext [B]{.underline}est baseline navigation system on
runway *j,*

$A^{L}$ is the probability that [L]{.underline}AAS Cat X is available,

$A^{B}$ is the probability that the baseline system is available (next
best baseline system is assumed to be 100% available),

$E^{L_{\text{ik}}}$is the probability that an aircraft in group *k* will
be equipped and its pilots trained and certified on LAAS Cat X in year
*i,*

$E^{B_{\text{ik}}}$is the probability that an aircraft in group *k* will
be equipped and its pilots trained and certified on the baseline system
in year *i* (Next Best baseline system is assumed to be 100% equipped),
and

$R$ is a factor to account for the ripple, or downstream, effects of
each disruption.

As can be seen from this equation, the focus of the calculation is on
individual runways rather than the entire airport. This is due to the
runway-specific nature of some of the baseline technologies, and the
fact that approach minima are runway-specific. Therefore, the benefits
must be calculated at this level of detail and then aggregated to the
airport level.

The annual number of arrivals ($N_{\text{ik}}$) can be obtained in
various ways. In this study the Official Airline Guide (OAG) was used to
obtain the current demand for major passenger airlines and regional
airlines and growth factors from the FAA's Terminal Area Forecasts were
applied to derive the demand in future years. A similar method can be
used to extrapolate from current to future years for major cargo
airlines, corporate aircraft, and low-end general aviation aircraft in
Alaska. Since cargo carriers, air taxi operators, and GA operators do
not publish schedules in the OAG, the baseline year can be obtained from
other sources (*e.g.*, from cargo airlines themselves, ETMS data, DOT
Transtat website[^17]).

Since the approach and landing capabilities are focused on individual
runways, it is necessary to determine the number of these avoided
disruptions that should be allocated to runway *j*. A logical way to
approach this problem is to determine the probability that each runway
is or will be used in instrument meteorological conditions
($U_{\text{jk}}$) and to multiply this factor by the number of avoided
disruptions for the entire airport. Although the Aviation System
Performance Metrics (ASPM) database contains information on runway
configuration use under various weather conditions, it is available for
only 46 airports and, moreover, the frequency of use of the individual
runways within each configuration is unknown. Therefore, runway usage
for all 121 airports must be derived based on available data, including
wind direction, runway length, and ILS placement. When possible, these
derived runway usage estimates were validated against runway usage
observations, (*e.g.*, some individual Airport Capacity Enhancement
Plans[^18]) and with airport operations representatives. Full details of
the method used to derive runway utilization estimates are reported in
Appendix M.

Recognizing that in most situations, airports favor one or two runways
in IMC and therefore these runways account for a disproportional number
of approaches, $U_{\text{jk}}$ also takes into account the likelihood
that an approaching aircraft will be routed to runway *j* as opposed to
another alternative. When the wind is less than 10 knots making it
possible for multiple runways to be used for approaches despite the wind
direction, the principal runway(s) are assigned 70% of the traffic and
the secondary runway(s) get 30%. These percentages are based on actual
observations of runway use and were documented in previous FAA benefits
studies[^19] [^20] and FAA guidance[^21]. $U_{\text{jk}}$ is modified to
take account of the fact that not all aircraft for user group *k* may be
capable of landing on runway *j* since the runway may not be long enough
to accommodate a certain aircraft type.

To obtain the value for the probability of the weather being between two
minima ($W^{B_{j}}$ or $W^{\text{NB}_{j}}$), IBM accessed the ceiling
and visibility information for the 121 airports from the NCDC database
for the years 1998 to 2001[^22]. Instead of looking at weather for a
24-hour time period, only weather during the typical traffic day, 7AM to
10 PM, was used.[^23] Since the ceiling data is available in 100 foot
increments, it was necessary to use an interpolation to derive the
probability of weather for finer levels of gradation (*e.g.*, 50 foot
increments). The ceiling and visibility minima which are used for the
baseline systems and LAAS are obtained from two sources: published
instrument approaches whenever available and alternatively, the output
from model runs conducted by the MITRE Corporation's Center for Advanced
Aviation System Development (CAASD) with its GPS Approach Minima
Estimator (GAME) model. It should be mentioned here that the possibility
exists that users may not be 100% equipped with the best baseline
alternative system at each airport, and so the derivation of $W_{j}$
must take this possibility into account by also considering the next
best alternative.

Since the benefit of avoided disruptions from lower minima can be
achieved only when LAAS is available and aircraft are equipped, it is
necessary to include factors for the availability ($A^{L}$) and
probability of being equipped ($E^{L_{\text{ik}}}$) in the equation. The
availability $A^{B}$and equipage $E^{B_{\text{ik}}}$of the best baseline
system are also taken into consideration. The pace of expected avionics
equipage was estimated through surveys and interviews conducted with
representatives from the user communities, and resulted in a range of
values used in the sensitivity analysis (See Appendix D for details of
how the pace of equipage was incorporated into the sensitivity
analysis).

Finally, a factor to account for the downstream effects of disruptions
is applied to obtain the total number of avoided disruptions. See
Appendix D for a description of how the downstream effect of delays
factor was incorporated into the sensitivity analysis.

### Derivation of Savings Obtained from Avoided Disruptions

To derive the savings that can be obtained from avoided disruptions in
year *i* by user group *k*, the number can be broken down into its
components. This number can be expressed as follows:

$$S_{\text{ik}} = C_{k}D_{i}$$

where;

$C_{k}$ is the average cost of a disruption in the year 2004 to user
group *k* and

$D_{i}$ is the discount factor in year *i* relative to the year 2004,

$$D_{i} = \left( \frac{1}{1 + r} \right)^{\left( i - \text{2004} \right)}$$

where *r* is the appropriate discount rate.

The average cost of a disruption to user group *k* ($C_{k}$) is
calculated by taking the sum of the costs of a delay, cancellation, and
diversion weighed by the frequency of their occurrence over a specified
past period[^24]. For major and regional passenger airlines, disruption
information was obtained from the Airline Service Quality Program (ASQP)
database for the years 1998 through 2003[^25]. For cargo carriers,
cancellations were set to zero based on airline representative input and
the ASQP disruption rates for major passenger airlines were applied for
diversions and delays. For GA operators, cancellations were set to zero,
and ASQP disruption rates for regional passenger airlines were applied
for diversions and delays. An inflation factor, based on OMB
guidance[^26], was applied to derive the costs for 2004, the baseline
year for this analysis.

The factor$D_{i}$is multiplied by $C_{k}$to ensure that the future saved
cost of an avoided disruption is appropriately discounted, reflecting
the reduction in present value the longer the benefit is deferred. A
real discount rate of 7% was used, based on guidance from the OMB, as
referenced above.

### Example

Washington's Reagan National airport (DCA) is used to illustrate how the
mathematical formula is applied to obtain the LAAS benefit. DCA has 6
runways (01/19, 15/33, 04/22). All 6 runways are used for approaches and
only 01 is equipped with an ILS (Cat II). DCA runways 19, 04, 22, 15,
and 33 have a variety of non-precision (e.g., VOR/DME and GPS)
approaches with minimum decision heights ranging from 587 to 904 feet.
An opportunity exists to reduce the ceiling and visibility minima on
these runways with LAAS Cat I, if the users do not equip with WAAS.

To simplify this example, it will focus our attention on a single year
(*i* = 2020), single runway (*j* = DCA 15), and single user group (*k* =
corporate jet operators). Although GA volume has been restricted from
DCA after 9/11/01, the FAA's 2004 TAF shows a small amount of future GA
volume at DCA which was considered in this example. Note that since DCA
15 is only 5204 feet long, it is not appropriate for all users, such as
major passenger airlines and others who operate aircraft too large to
land on this runway. Based on the methodology described above, the
parameters in Table 5 were obtained. Note that the benefit for this
year, runway end, and user group is obtained by simply multiplying the
first 8 parameters. To obtain the Cat I benefit for the entire airport,
the discounted benefits for the 20 year period is summed over all runway
ends, and all user groups.

Table 5: key parameter values for DCA 15 example

+-------+-------+-------+-------+-------+-------+-------+-------+-------+
| $$    | $$W$$ | $$    | $$A^  | $     | $$C_  | $$D_  | $$R$$ | D     |
| N_{\t |       | U_{\t | {L}$$ | $E^{L | {k}$$ | {i}$$ |       | irect |
| ext{i | \% of | ext{j |       | _{\te |       |       | R     | Oper  |
| k}}$$ | time  | k}}$$ | Av    | xt{ik | Cost  | Dis   | ipple | ating |
|       | be    |       | ailab | }}}$$ | of    | count | E     | Cost  |
| \# of | tween | U     | ility |       | disru | f     | ffect | Be    |
| DCA   | LAAS  | tiliz | of    | LAAS  | ption | actor | F     | nefit |
| arr   | and   | ation | LAAS  | equ   | (Corp | for   | actor |       |
| ivals | Bas   | of    |       | ipage | orate | 2020  |       | (Corp |
| (Corp | eline | DCA   |       |       | jet   |       |       | orate |
| orate | m     | r     |       |       | Opera |       |       | jet   |
| jet   | inima | unway |       |       | tors) |       |       | Opera |
| Opera |       | 15    |       |       |       |       |       | tors) |
| tors) |       |       |       |       |       |       |       |       |
|       |       | (Corp |       |       |       |       |       |       |
|       |       | orate |       |       |       |       |       |       |
|       |       | jet   |       |       |       |       |       |       |
|       |       | Opera |       |       |       |       |       |       |
|       |       | tors) |       |       |       |       |       |       |
+-------+-------+-------+-------+-------+-------+-------+-------+-------+
| 1,419 | .05   | .07   | .999  | 1.0   | \$502 | .34   | 1.8   | \$    |
|       |       |       |       |       |       |       |       | 4,518 |
+-------+-------+-------+-------+-------+-------+-------+-------+-------+

### Results

Tables 6A and 6B, below show the total straight-in LAAS approach benefit
estimated for the 121 airports studied. Table 6A shows these benefits
for Cat I LAAS implementation, in terms of both reduced direct operating
costs and passenger time savings, as well as for the two scenarios of
user WAAS equipage. Table 6B shows these benefits for Cat II/III LAAS
implementation, above and beyond those for Cat I. Total straight-in
benefits are obtained by adding corresponding cells from Tables 6A and
6B (*e.g.*, total DOC benefit for 0% WAAS is \$ 490.8M = \$92.6M +
\$398.2M)

[Table 6a: Discounted 20 year LAAS Straight-in Benefits for Cat
I]{.smallcaps}

+-----------------------+---------------------+-----------------------+
|                       | **Direct Operating  | **Passenger Time      |
|                       | Cost**              | Savings**             |
+-----------------------+---------------------+-----------------------+
| **LAAS Benefits**     | \$92,600,000        | \$110,900,000         |
|                       |                     |                       |
| **(Assuming 0% WAAS   |                     |                       |
| equipage)**           |                     |                       |
+-----------------------+---------------------+-----------------------+
| **LAAS Benefits**     | \$2,900,000         | \$3,200,000           |
|                       |                     |                       |
| **(Assuming 100% WAAS |                     |                       |
| equipage)**           |                     |                       |
+-----------------------+---------------------+-----------------------+

[Table 6b: Discounted 20 year LAAS Straight-in Benefits for Cat
II/III]{.smallcaps}

+-----------------------+---------------------+-----------------------+
|                       | **Direct Operating  | **Passenger Time      |
|                       | Cost**              | Savings**             |
+-----------------------+---------------------+-----------------------+
| **LAAS Benefits**     | \$398,200,000       | \$490,700,000         |
|                       |                     |                       |
| **(Assuming 0% WAAS   |                     |                       |
| equipage)**           |                     |                       |
+-----------------------+---------------------+-----------------------+
| **LAAS Benefits**     | \$398,200,000       | \$490,700,000         |
|                       |                     |                       |
| **(Assuming 100% WAAS |                     |                       |
| equipage)**           |                     |                       |
+-----------------------+---------------------+-----------------------+

##  [Reduced Disruptions with LAAS Takeoff Guidance]{.smallcaps}

A restricted ability to perform departure operations during low
visibility conditions, although rare, can be highly disruptive to
airport and airline operations. When low visibility conditions coincide
with an airport's departure bank, particularly early in the day, the
impact can be significant. In some cases it can take more than a full
day for an airline's operations to recover from the disruption to their
system that results from such an event[^27].

Current rules governing takeoff under low visibility conditions permit
operations in various RVR conditions depending on several factors,
including runway markings, lighting, RVR measurement equipment, surface
movement guidance and control plans, and aircrew training.[^28] Takeoff
operations in very low visibility conditions may be conducted with the
use of a takeoff guidance system, (*e.g.*, Cat III ILS localizer for
front-course guidance and a head up display (HUD)). It is expected that
LAAS Cat II/III, as part of a takeoff guidance system, will also provide
this level of guidance, potentially at far more runways than are
currently served by Cat III localizers. Thus, LAAS and HUD equipped
users benefit directly by continuing takeoff operations during these
conditions, and all airport users benefit indirectly from the reduced
time required for the airport to restore normal operations once these
low visibility conditions end (due to a smaller backlog of aircraft
waiting to depart).

Airports with multiple Cat III localizers will accrue benefit from this
LAAS capability only if demand is sufficiently high to warrant the use
of multiple departure runways under these conditions and if operational
and safety considerations permit departures from multiple runways under
these conditions. Airports with only a single Cat III localizer will
benefit from this capability by continuing to perform simultaneous
arrivals and departures by using the Cat III ILS runway for arrivals and
using LAAS on one of the other runways for departures. Both airports
currently lacking Cat III localizers and airports with a single Cat III
localizers may benefit significantly from this LAAS capability, and this
analysis is limited to such airports.

Within the 121 airports studied, 21 airports have more than one Cat III
localizer. Of the remaining 100 airports, existing infrastructure
supports takeoff operations at 300, 500, 1000, and 1600 RVR at 1, 50, 3,
and 46 airports respectively. Users equipped with a LAAS-based takeoff
guidance system may be able to benefit at these 100 airports.

Figure 2 shows the distribution of low visibility conditions during the
day for the airports with no Cat III ILSs. Although these conditions are
observed at all times of day, the majority occur during the early
morning, when the impact on an airline's operation is greatest.

> ![](media/image7.wmf){width="5.395833333333333in" height="3.30625in"}

[Figure 2. Time Distribution of Low Visibility Conditions among Airports
with no Cat III ILS.]{.smallcaps}

### Methodology

In order to investigate the delay savings that may be achieved by using
LAAS for takeoff guidance, the lowest takeoff minima supported by each
airport must first be determined, including the timing and duration of
low visibility conditions. That information was then combined with
departure demand[^29]. Following that, an airport delay model was
employed to obtain an estimate of the expected delays both with and
without LAAS-guided takeoffs. In this analysis, the impact of LAAS is
modeled as the ability of the airport to maintain IMC departure rates,
for aircraft equipped with both Cat III LAAS and HUD, while very low
visibility conditions exist. The methodology consists of the following
steps:

1)  Obtain the required data:

    a.  Airports with one or no Cat III localizer

    b.  The lowest takeoff minima supported by each non Cat III
        localizer runway at an airport

    c.  The number of hours per year that each airport experiences
        visibility conditions below these minima

    d.  The IMC and VMC departure capacity of each airport[^30]

    e.  The total departure traffic at each airport for a typical
        day[^31]

2)  Run IBM's Single Airport Delay Model[^32] to calculate departure
    delay for two scenarios, with and without LAAS, accounting for the
    timing and duration of low visibility conditions:

3)  Calculate the average annual change in delay:

    a.  Take the difference between delays per flight in the two
        scenarios

    b.  Multiply this difference in delay per flight by the average
        daily traffic volume

    c.  Multiply this daily change in delay by the number of days with
        low visibility conditions

4)  Multiply by the percentages of LAAS and HUD avionics equipage and
    divide by 2 to get the portion attributable to LAAS

5)  Multiply by the downstream effect factor for takeoff delays (See
    Appendix N)

6)  Multiple by .999, the assumed availability of LAAS

7)  Multiply the minutes of delay by the cost[^33] of ground delay per
    minute for each user type

### Limitations

Following takeoff, LAAS may be able to provide precision departure
guidance, including procedural separation, on straight or curved
departure paths, potentially allowing for a higher rate of departure
operations under low visibility conditions than is possible with
localizer guidance and radar vectoring. RNAV departure procedures, using
existing avionics and ground systems, may also provide much of this
benefit. Thus, the impact of this LAAS capability is difficult to
evaluate.

Installation of Cat III ILS at runways receiving this LAAS benefit would
eliminate this benefit.

### Results

Table 7, below shows the total LAAS takeoff guidance benefit estimated
for the 121 airports studied. The table shows these benefits for Cat
II/III LAAS implementation, in terms of both reduced direct operating
costs and passenger time savings, as well as for the two scenarios of
user WAAS equipage.

[Table 7: Discounted 20 year LAAS Takeoff Guidance Benefits for Cat
II/III]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$54,500,000          | \$54,200,000          |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$54,500,000          | \$54,200,000          |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

## [Benefits from LAAS-based Complex Procedures]{.smallcaps}

In addition to providing final approach guidance for straight-in
approaches, LAAS is also capable of supporting complex area navigation
(RNAV) procedures. However, a variety of other existing and planned
avionics and ground systems may also support such procedures. RNAV
procedures conducted without LAAS are reportedly capable of supporting
complex operations down to near-Cat I approach minima, and if linked to
an ILS final approach, down to the minima supported by the ILS. LAAS
offers the possibility of conducting complex procedures down to Cat I or
Cat II/III minima where no ILS is available, as well as the simplicity
of using a single system for terminal area navigation through final
approach and landing, potentially down to Cat III minima. Discussions
with major airline representatives have shown that simplification of
terminal area and landing procedures is a primary goal. Further, these
airlines view GPS-based RNAV/RNP as the navigation solution down to
near-Cat-I operations and LAAS-based RNAV/RNP as the desired transition
from GPS to GLS down to Cat-III operations. Based on this input,
LAAS-based complex approach benefits were evaluated only in those cases
where no ILS is present and only for weather conditions worse than those
supported by baseline system approach minima.

LAAS may support complex operations either through use of the LAAS
position-velocity-time signal (PVT) as an input to an on-board
navigator, or through the direct broadcast of waypoints from the LAAS
Ground Facility (LGF). In the former, LAAS may provide improved actual
navigation performance (ANP) in the terminal area, and thus may support
more stringent required navigation performance (RNP) procedures than
other systems (*e.g.*, un-augmented GPS). This benefit may not be
limited to improved approach procedures, but may apply more generally to
airspace management, with very low RNP routes supported by LAAS, and
including highly precise vertical restrictions. Such routes have the
potential to resolve existing airspace conflicts, both within a single
airports operations (e.g., more precise separation of arrival and
departure streams at SEA), and among closely situated airports (e.g.,
runway use conflicts between ORD and MDW, SEA and BFI, or JFK, LGA, EWR,
and TEB). However, at this time RNP levels have not been established for
these procedures, and thus it is not possible to discern which
requirements are beyond the capabilities of existing systems and which
will require LAAS. Further, it is anticipated that the RNP will vary
within the approach (and departure) environment, and thus the transition
point in the procedures from a GPS-based RNAV/RNP to a LAAS-based
RNAV/RNP is not clear. Until these RNP levels are established, the
extent of LAAS-enabled RNAV benefits will remain unclear.

Additionally, LAAS is expected to provide increased availability of
small RNP values. Low RNP values are currently limited by the flight
technical error, rather than the navigation system, which makes it
difficult to assign any benefit for reducing the RNP values to LAAS.
However, the limiting factor on the availability of low RNP values is
the navigation system and the equivalent-RAIM performance, which LAAS is
expected to improve. The availability of RNP-0.15 ranges from 98% to 80%
depending on the number of GPS satellites that are operational[^34].
LAAS is expected to increase that availability to 99.9% or better,
except in the 100% WAAS equipage scenario, in which case this benefit
may be provided by WAAS.

The appeal of direct broadcast of waypoints, or data uplink, for complex
procedures is twofold. First, since the source of the procedure is local
to the airport, uplink eliminates concerns about version control of
procedures among different aircraft (that is, with an onboard database
of procedures, and each operator potentially updating procedures at a
different pace, there is a concern that two or more versions of a single
procedure can be in use simultaneously). Second, uplink of procedures
may reduce the burden placed on the onboard database for some aircraft.
The costs of adding and certifying increased storage capacity can be
significant. Further, as the number of procedures, including terminal
area, en-route and high-altitude routes, continues to increase,
operators may be forced to choose between the expense of database
upgrades and the operational complexity of isolating certain aircraft to
particular regions. Since the specific storage requirements for onboard
versus uplinked procedures are not yet defined (*i.e.*, even with uplink
available, procedures may need to be stored in an onboard database for
other purposes), this benefit of uplink is not clear.

In the absence of RNAV procedures, flight paths within the terminal area
during IMC are controlled by vectoring, a process that involves a high
level of air-to-ground communication and that can result in a broad
range of paths flown by individual aircraft. Reducing both the
communications workload and the variability in the time and distance
flown in the terminal area are of great interest to controllers, pilots
and airlines. RNAV/RNP procedures have the potential to significantly
reduce the communications component of this overall workload. Since
these procedures follow pre-set routes, the pilots can focus on flight
operations to follow the routes and the controller can focus on
surveillance. Further communications should only be necessary in the
event that the aircraft diverges from the assigned route, or the
controller determines that a deviation is necessary. One study of RNAV
terminal procedure development[^35] at Philadelphia found that
pilot-controller communications fell by over 60%, from 16 separate
communications required for vectoring to just 6 with RNAV routes. The
time and attention saved by eliminating these 10 communications can now
be focused on flying, and monitoring, the RNAV route. While LAAS may
contribute to the conduct of RNAV and RNP procedures, the ability of
other systems in the baseline to provide similar services eliminates
this as an incremental LAAS benefit.

Reductions in flight time variability could yield significant
benefits[^36] in terms of direct operating cost saved, improved customer
service and on-time performance, and improved predictability of arrival
times for the airlines' gate operations. The value of predictability was
described well by David Knorr *et al*[^37]: "Predictability measures the
variation in the ATM system as experienced by the user. Commercial
airlines may benefit as much from a reduction in the variance (or an
improvement in the consistency) of flight/taxi times as they would from
a reduction in average flight times. System predictability allows for
improved scheduling and more efficient bank operations." Other aviation
industry stakeholders and researchers have also pointed out the high
value of predictability to commercial airlines.[^38] Additionally, it is
one of the goals in the FAA's Flight Plan 2004-2008 to "achieve greater
conformity between expected and actual flight times."[^39] Potential
benefits from reduced flight time variability are of particular
importance at the nation's busiest airports, due to the high volume of
traffic handled, and to the related importance for airlines to carefully
time their operations. Earlier work by IBM[^40] showed that flight time
variability in the terminal area for arrivals to ORD 9L is as much as 13
minutes, depending on what vectoring path is assigned, and that a
proposed RNP procedure for this runway could reduce this variability
nearly to zero. However, as was the case for the benefits associated
with communication workload, while LAAS may contribute to the conduct of
such RNP procedures, the ability of other systems in the baseline to
provide similar service eliminates this as an incremental LAAS benefit.

### Estimated Complex Approach Benefit

As stated above, most terminal area complex operations can be
accomplished with existing or planned avionics and ground systems,
without the need for LAAS. Even complex procedures ending with a
precision approach may be performed by transitioning to an existing ILS
for the final approach and landing. This section explores the benefits
available to LAAS at those runways that do not have an ILS and that did
not receive any Cat II/III benefit in the Straight-In Approach section
of this work, and had no, or limited, Cat I benefit due to relatively
high estimated decision heights associated with LAAS. These runways
include candidates such as JNU 8 and 26, as well as DCA 19, which for
reasons of terrain or airspace restrictions cannot have an ILS
installation. The following shows a list of all runways in this analysis
that would benefit from LAAS complex approaches: ALB 28, BDL 15, BHM 18,
BHM 36, BUR 15, DCA 19, HNL 22L, HNL 26L, HNL 26R, JNU 8, JNU 26, LGA
31, SAN 27, and TEB 01.

### Methodology

A key assumption in this methodology is the decision height achievable
by LAAS complex approaches at these runways. Since MITRE's GAME model
provides estimates of decision heights for straight-in approaches, its
output can be used to inform us that these runways are obstacle
constrained to relatively high decision heights. In this analysis it was
assumed that there will be a learning curve for (or period of becoming
comfortable with) advanced capabilities such as these complex
procedures. Most newly introduced technologies do not achieve the full
potential of their capabilities until users become familiar with, and
comfortable with, those capabilities. Thus, it is assumed that during
the early years that a LAAS is used at each airport, the decision height
for a complex approach is no better than that associated with
straight-in approaches. Then, beginning in 2018, lacking any better
information, it is simply assumed that a complex terminal area path can
be designed to support the full Cat I decision height (200 feet), and
that Cat II/III minima are also achievable. Since it is not known
whether a complex path can be constructed at each of these runways to
achieve these minima, it is recognized that this may be an aggressive
assumption.

These assumed decision heights are then used as inputs to the method
described in the section titled "Reduced Disruptions for Straight-in
Precision Approaches". As in that section, the numbers of reduced
disruptions due to the improvement in approach minima are estimated.
Other benefits often associated with complex procedures, such as reduced
time or distance through the terminal airspace, appear to be
attributable to RNAV or RNP procedures, and the role of LAAS in
achieving these benefits is unclear.

### Limitations

For some runways included in this complex benefit estimate, it may be
possible to install an ILS. Installation of an ILS would change the
baseline against which LAAS is evaluated, and that runway's incremental
LAAS-based complex approach benefit would be eliminated. Efforts to
obtain data on ILS siting potential at NAS runways have not yet been
fruitful.

The complete solution to the question of LAAS complex approaches
involves significant complex technical issues beyond the scope of this
study. This method assumes that the complex approach segment has allowed
the aircraft to avoid controlling obstacles and intercept the final
approach path at a point closer to the runway than current procedures. A
preliminary evaluation of decision height improvements due to short
finals, conducted by CAASD using the GAME tool, and based on GLS TERPS,
indicated that few, if any, of the 121 airports would achieve any
decision height benefit from such short finals. The impact of possible
future changes in TERPS for LAAS approaches on achievable decision
height for short final is unknown.

### Results

Tables 8A and 8B, below show the total LAAS complex approach benefit
estimated for the 121 airports studied. Table 8A shows these benefits
for Cat I LAAS implementation, in terms of both reduced direct operating
costs and passenger time savings, as well as for the two scenarios of
user WAAS equipage. Table 8B shows these benefits for Cat II/III LAAS
implementation. Total straight-in benefits are obtained by adding
corresponding cells from Tables 8A and 8B (e.g., total DOC benefit for
0% WAAS is \$ 104.8M = \$98.7M + \$6.1M)

[Table 8a: Discounted 20 year LAAS Complex Approach Benefits for Cat
I]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$98,700,000          | \$110,400,000         |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$0                   | \$0                   |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

[Table 8b: Discounted 20 year LAAS Complex Approach Benefits for Cat
II/III]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$6,100,000           | \$7,500,000           |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$6,100,000           | \$7,500,000           |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

## [Benefits Due to Elimination of ILS Critical Areas]{.smallcaps}

Under certain weather conditions, the ILS signal must be protected by
ensuring that aircraft or other obstacles do not enter areas on the
airport surface where they may interfere with the ILS signal quality.
These areas are called ILS critical areas, and are shown on taxiway
diagrams, and are marked with appropriate signage on the airport
surface. These critical areas require that aircraft taxiing into
position for takeoff, or to cross the runway, must hold short at some
distance from the runway. The critical area is protected when instrument
approaches are being conducted with visibility less than or equal to 2
miles or ceilings are less than or equal to 800 feet.[^41] The figure
below illustrates an ILS critical area on Cincinnati's runway 18L.

![](media/image8.png){width="1.71875in" height="2.9791666666666665in"}

[Figure 3. Example of an ILS Critical Area hold.]{.smallcaps}

Protection of ILS critical areas may cause delays to both the arriving
aircraft, and to aircraft taxiing on the airport surface. The impact
that LAAS may have on each of these delays is explored in the sections
below.

### Arrival Delay due to Protection of ILS Critical Areas

When arrival and departure operations are being conducted during the
same period on a single runway with an ILS critical area, the arriving
aircraft must be spaced further apart longitudinally in order to allow
for the time required for the departing aircraft to taxi through the
critical area and onto the active runway. This results in a reduced rate
of operations on that runway.

LAAS, when used for precision landing guidance in IMC, is expected to
eliminate the need for ILS critical areas on the airport surface. With
departing aircraft able to taxi closer to the runway, less time is
required for their final taxi into position for takeoff, with a
resulting reduction in required longitudinal spacing between sequential
arrivals as well as between arrivals and departures. Thus, the
elimination of ILS critical areas should allow a higher pace of
operations on these runways where both arrival and departure operations
are being conducted during reduced weather minimums.

The purpose of this section is to estimate the impact that ILS critical
areas have on airport capacity and average arrival delays. Since LAAS
can eliminate the need for ILS critical areas, increased arrival and
departure capacity may be achieved through decreased arrival-departure
and arrival-arrival spacing. Normally, a departing aircraft may begin
its departure after an arrival aircraft is safely off the runway, but at
a runway that is used for simultaneous departures and arrivals and that
has an ILS critical area, spacing between arriving aircraft must be
increased to allow a departing aircraft to taxi through the critical
area and depart before the arriving aircraft may land.

The following is the methodology that was used in this analysis.

### Methodology

1.  Identify ILS critical areas within the 121 studied airports.

2.  Identify which of the affected runways are used for both arrivals
    and departures during IMC.

3.  Calculate the estimated time in seconds to taxi through the critical
    area.[^42]

4.  Determine the minimum required aircraft time separation at the
    runway threshold, for two cases:

    a.  No critical area: Separation is dictated by wake vortex
        separation standards[^43].

    b.  ILS critical area: Separation between affected arriving aircraft
        is increased by the time needed for the departing aircraft to
        taxi through the critical area.

5.  Convert the minimum aircraft time separation into a runway capacity
    per hour for each case[^44].

6.  Calculate the percent time that weather is between LAAS minima and
    baseline minima.

    a.  Baseline used actual GPS minima, or

    b.  In the absence of actual GPS minima, GAME RNP .3 minima were
        used.

7.  Use IBM's Single Airport Delay Model to estimate the flight delays
    associated with each of these cases for a typical[^45] traffic
    volume day.

8.  Take the difference in delays between these two cases to get the
    one-day delay savings for ILS critical area elimination.

9.  Multiply by the percent of LAAS avionics equipage

10. Multiply by the downstream effect factor (see Appendix N)

11. Multiple by .999, the assumed availability of LAAS

12. Annualize the one-day delay savings and multiply by the cost[^46] of
    airborne delay for each user group in \$/min.

### Limitations

ILS Critical Areas were identified from airport taxiway diagrams. ILS
Critical Areas that are not identified on the taxiways diagrams (*e.g.*,
ILS critical area between SEA 16R and 16L, identified by Alaska
Airlines), and where runway operations include simultaneous IMC arrivals
and departures, are not included and may provide additional potential
benefits.

### Example: Cincinnati Airport (CVG)

Typical runway configurations at CVG include departures on runway 27,
and both departures and arrivals on either 18L/R or 36L/R, depending on
wind conditions. CVG has an ILS critical area hold on every runway.
Since runway 27 is dedicated to departures, it was assumed that most
departures will be sent to this runway, with only those departures above
and beyond the capacity of runway 27 being sent to the other runways.
The OAG schedule data show that the IMC departure capacity[^47] of
runway 27 is exceeded 11 of the 16 hours between 6 a.m. and 9 p.m. Thus,
in IMC the demand that exceeds runways 27's capacity or approximately
160 departures per day must use either 18L/R or 36L/R, depending on wind
direction. It is these aircraft that are subject to hold at the ILS
critical areas, and which will thus require greater spacing between
arrivals in order to execute their departure.

Applying the steps of the methodology outlined above, it was found that
CVG's ILS critical areas require departing aircraft to taxi an
additional 15 seconds (runways 18R and 36L) to 25 seconds (runways 18L
and 36R) to perform a departure. This additional taxi time results in a
¾ mile increased separation between arrivals on runway 18R/36L, and 1¼
mile additional separation for 18L/36R. Next, the change in arrival
capacity represented by these increased arrival separations was
calculated, and used to estimate changes in airport delays. Finally, a
net annual direct operating cost savings and passenger time savings due
to reduced delays from ILS critical area elimination at CVG was
calculated[^48].

### Results

Tables 9A and 9B, below show the total LAAS ILS critical area arrival
delay benefit estimated for the 121 airports studied. Table 9A shows
these benefits for Cat I LAAS implementation, in terms of both reduced
direct operating costs and passenger time savings, as well as for the
two scenarios of user WAAS equipage. Table 9B shows these benefits for
Cat II/III LAAS implementation. Total straight-in benefits are obtained
by adding corresponding cells from Tables 9A and 9B (e.g., total DOC
benefit for 0% WAAS is \$ 8.3M = \$5.4M + \$2.9M).

[Table 9a: Discounted 20 year LAAS ILS Critical Area Arrival Delay
Benefits for Cat I]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$5,400,000           | \$5,600,000           |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$900,000             | \$900,000             |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

[Table 9b: Discounted 20 year LAAS ILS Critical Area Arrival Delay
Benefits for Cat II/III]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$2,900,000           | \$3,100,000           |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$2,900,000           | \$3,100,000           |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

### Taxi Time Delay due to Protection of ILS Critical Areas

The elimination of an ILS critical area may allow for a less impeded
flow of arrival and departure ground operations across runways that
currently have critical areas requiring a hold. The purpose of this
section is to estimate the impact that ILS critical areas have on
aircraft taxi operations.

Since multiple factors affect the pace of ground operations, it is
necessary to attempt to isolate the contribution to taxi time delay that
comes from protection of the ILS critical areas. Although the
requirement to protect the critical area is limited to ceiling and
visibility conditions below 800 feet or 2 miles, anecdotal evidence and
stakeholder interviews suggest that critical areas are sometimes
protected even in conditions outside of these limits. This practice
complicates the process of isolating the operational impact of ILS
critical area protection.

Observed taxi times were collected for each airport for weather
conditions above and below the ceiling and visibility conditions of 800
feet or 2 miles. These actual taxi times were then compared to the
unimpeded, or expected, taxi times. For conditions at or below the 800
feet or 2 miles limits, the difference between these is simply the IMC
taxi delay (observed time -- expected time). However, there are taxi
delays even in VMC, so the calculated IMC taxi delay was normalized by
removing this VMC delay. The remaining IMC taxi delay should reflect
conditions that are unique to the airport's IMC operational conditions.
Subtracting all of the VMC taxi delay in the normalization step may be
excessive, as there may be more volume related taxi delays in VMC than
IMC. However, taking this step suggests that our estimate is
conservative. One final step, the subtraction of the normalized IMC
delay averaged over all airports without an ILS critical area, should
help to eliminate those delays attributable to weather and congestion,
leaving delays due primarily to protection of ILS critical areas.

The following is the methodology that was employed in this analysis:

### Methodology

1.  Identify ILS critical areas within the 121 studied airports

2.  Identify the actual and unimpeded (expected) taxi-in and taxi-out
    time from the ASPM database

3.  Calculate the percent time that weather is between LAAS minima and
    baseline minima.

    a.  Baseline used actual GPS minima

    b.  In the absence of actual GPS minima, GAME RNP .3 minima were
        used

4.  Calculate a normalized IMC taxi-in and taxi-out delay per flight
    that isolates the delay due to protection of ILS critical areas:

    a.  Obtain the raw IMC taxi time delay by subtracting the IMC
        unimpeded taxi time from IMC observed taxi time

    b.  Obtain the raw VMC taxi time delay by subtracting the VMC
        unimpeded taxi time from VMC observed taxi time

    c.  Obtain the normalized IMC taxi time delay by subtracting the raw
        VMC delay from raw IMC delay -- this normalized IMC taxi delay
        represents delays in IMC, which may be due to both general
        operational slowdown in IMC and to protection of ILS critical
        areas

    d.  Further isolate the taxi delay specifically due to protection of
        critical areas by subtracting the average IMC taxi delay,
        normalized for VMC delay, observed at airports without critical
        areas

5.  Multiply this final normalized IMC taxi time delay, assumed to be
    due primarily to protection of ILS critical areas, by the cost of
    ground delay for each user group

6.  Adjust these delays for the percent of LAAS equipage

7.  Multiply the estimated per flight delay by total operations by user
    group

8.  Multiple by .999, the assumed availability of LAAS

9.  Multiply by the downstream effect factor

Note that this methodology accounts for taxi delays associated with
aircraft, but does not include restrictions on other types of airport
surface traffic due to protection of ILS critical areas.

### Results

Tables 10A and 10B, below show the total LAAS benefits from the
reduction in taxi times made possible with the elimination of ILS
critical areas. Table 10A shows these benefits for Cat I LAAS
implementation, in terms of both reduced direct operating costs and
passenger time savings, as well as for the two scenarios of user WAAS
equipage. Table 10B shows these benefits for Cat II/III LAAS
implementation. Total straight-in benefits are obtained by adding
corresponding cells from Tables 10A and 10B (*e.g.*, total DOC benefit
for 0% WAAS is \$ 28.2M = \$17.8M + \$10.4M)

[Table 10a: Discounted 20 year LAAS ILS Critical Area Taxi-In and
Taxi-Out Delay Benefits for Cat I]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$17,800,000          | \$28,300,000          |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$2,900,000           | \$4,600,000           |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

[Table 10b: Discounted 20 year LAAS ILS Critical Area Taxi-In and
Taxi-Out Delay Benefits for Cat II/III]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$10,400,000          | \$16,600,000          |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$10,400,000          | \$16,600,000          |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

##  [Benefits for Closely Spaced Parallel Approaches]{.smallcaps}

Three of the operational capabilities identified in the LAAS Navigation
Capabilities Baseline are related to simultaneous independent parallel
approaches. This section summarizes the current state of knowledge about
the potential for using LAAS to support these types of approaches in
IMC.

### Operational Background

During VMC, the FAA allows aircraft to conduct simultaneous independent
approaches on parallel runways separated by as little as 700 feet as
long as the pilots take over separation responsibility using "see and
avoid" principles.

When weather deteriorates, maintaining visual separation is no longer
possible and there are specific rules about the required separation
between runways under which aircraft can conduct simultaneous
independent parallel approaches. Currently, the minimum required
separation is 4300 feet in IMC (without special ATC radar surveillance
equipment, called a Precision Runway Monitor (PRM)). This separation is
required to ensure adequate time to prevent a collision in the event
that one of the aircraft on a parallel runway approach (the blundering
aircraft) turns in the direction of the second aircraft (the evading
aircraft). The separation distance is a function of the surveillance
error, navigation system error, flight technical error, and the time
required to detect the blunder, alert the evading aircraft, and conduct
an evasive maneuver.

With improved surveillance, pilot and controller training, and special
procedures, it is possible to conduct simultaneous independent parallel
approaches down to as little as 3000 feet runway centerline separations.
This entails the use of PRM, a high update radar and high resolution
display, which can cost more than \$10M per unit[^49]. Currently, if the
runway centerlines are separated between 2500 and 3000 feet, the
approaches must be dependent with the aircraft positioned so as to have
a minimum 1.5 nautical mile stagger on the parallel runways. For runways
separated by less than 2500 feet, neither independent nor dependent
approaches can be conducted in IMC due to the potential hazardous
effects of wake vortices, and consequently one of the parallel runways
is shut down for arrivals.

### Evidence in Support of Potential LAAS Benefits

Given that the separation distances are based in part on navigation
system errors, it seems logical to assume that it may be possible to
achieve reductions in the required separations distances (*i.e.*, below
4300 feet) with new navigation systems such as WAAS and LAAS.

In fact, a number of research efforts have been conducted on this issue
as well as a host of other technical issues related to achieving
increased airport capacity through a reduction in runway separations.
These research efforts have included:

-   Various studies by Sharon Houck *et al*. at Stanford University,
    showing the feasibility and potential benefits of WAAS or LAAS
    combined with tunnel-in-the-sky displays to reduce runway spacing
    while maintaining currently accepted safety levels. [^50] [^51]
    [^52]

-   NASA's Terminal Area Productivity Program which includes the
    Airborne Information for Lateral Spacing (AILS) and the Closely
    Spaced Parallel Approach (CSPA) Program. [^53] As part of this
    effort, NASA has been investigating ways to mitigate the effects of
    wake vortices on closely spaced parallel approaches.[^54]

-   Investigations of parallel runway technical issues and air traffic
    control procedures conducted by RTCA SC-186, Working Group 1. [^55]

-   Studies by Eurocontrol of the benefits of the Ground Based
    Augmentation System (GBAS), including studies specific to
    simultaneous independent operations.[^56] [^57] [^58]

-   MIT Lincoln Lab analyses and tests of PRM and associated procedures.
    [^59]

-   Analyses by MITRE/CAASD over the past 20 years supporting the FAA's
    research, feasibility studies, and certification of various
    simultaneous independent parallel approach procedures (including
    most recently, the RNP Parallel Approach Transition or RPAT) as well
    as investigating reductions in wake turbulence constraints. [^60]
    [^61] [^62] [^63] [^64]

It is clear from these studies that the largest contributor to the
required separation between parallel runways is surveillance error,
flight technical error, and the distance needed to detect and resolve
potential blunders. Although navigation system errors are not
insignificant, their contribution to the required runway separation is
minor (*i.e.*, less than 20% of the 4300' separation requirement)
compared to other errors and required distances.

Without new technologies to reduce the size of the surveillance errors
and flight technical errors as well as automated methods for detecting
and resolving blunders, LAAS alone is likely to have a negligible impact
on the reduction of lateral separations required for simultaneous
independent parallel approaches. An estimate of the impact of LAAS in
conjunction with other technologies will require a separate analysis
that is outside of the scope of this study.

Nevertheless, the existing studies indicate that LAAS can be combined
with other technologies such as a tunnel-in-the-sky display or ADS-B and
CDTI to enable those technologies to achieve performances that they
would not be able to attain without LAAS. For example, Houck et al.[^65]
illustrated that a tunnel-in-the-sky display in the cockpit combined
with linear instrument approach corridors made possible with WAAS can
result in reductions in the required separation between parallel runways
from 4300 feet to 3100 feet. Clearly, with the greater horizontal and
vertical accuracy of LAAS when compared to WAAS, it should be possible
for LAAS to achieve and possibly surpass the reduction to 3100 feet
estimated to be attainable with WAAS.

Although not explicitly tied to LAAS, the FAA's Safe Flight 21 program
indicates that ADS-B could provide PRM-like capability at a wider range
of airports[^66]. Since the utility of ADS-B is linked to the accuracy
and availability of its inputs, utilizing the best available positioning
information (*i.e.*, LAAS, where available) will maximize ADS-B's value.
The FAA is also exploring the use of RPAT (an ILS approach path on one
track combined with an RNP approach procedure and a visual guided side
step maneuver on the parallel track) for use with closely spaced
parallel runways. The possibility of using LAAS to increase the
usability of RPAT procedures appears to hold some promise, but is a
research topic outside of the scope of this benefits analysis.

In the following analysis, the potential improvement that may be
achieved when LAAS is combined with improved cockpit displays was
estimated for both the 0% and 100% WAAS user equipage scenarios. For the
100% WAAS equipage case the incremental accuracy of LAAS over WAAS is
not expected to produce an appreciable difference in the required runway
centerline separation requirement for simultaneous independent parallel
approaches, and LAAS accrues benefits for the years prior to WAAS Cat I
capability in 2015.

There are 12 airports among the 121 candidate airports in the LAAS
benefits analysis that would be affected if the required separation for
simultaneous independent parallel approaches were reduced from 4300 feet
to 3100 feet. They include:

-   Tampa (TPA) • Raleigh-Durham (RDU)

-   Ft. Lauderdale (FLL) • Minneapolis-St. Paul (MSP)

-   Detroit (DTW) • Memphis (MEM)

-   Salt Lake City (SLC) • Long Beach (LGB)

-   Milwaukee (MKE) • Portland (PDX)

-   Jackson (JAN) • New York -- Kennedy (JFK)

Minneapolis-St. Paul already has a PRM and thus is unlikely to benefit
from a combination of LAAS and other technologies and therefore it was
excluded from the analysis. Ft. Lauderdale, Salt Lake City, Memphis, and
John F. Kennedy, are listed in the Aviation Capacity Enhancement (ACE)
Plan[^67] as sites recommended for a PRM. It is possible that these
airports may be too far along the procurement path to have LAAS make a
difference. However, since delays in implementation may still occur, it
was decided to include these airports in the analysis. The remaining
airports (Tampa, Detroit, General Mitchell, Jackson, Raleigh-Durham,
Long Beach, and Portland) are not in the list of sites recommended for a
PRM, and may be candidates for a capacity improvement with LAAS.

Using capacities from the FAA benchmark report[^68] and FAA's ASD
organization, an estimate was obtained of the impact that bad weather
has on these airports and the magnitude of the potential arrival
capacity gains that may be achieved if the capacity from the parallel
runways at these airports is partly or wholly regained with LAAS and
associated technologies. Table 11 contains a list of the 11 airports
that were part of this analysis and their capacities. Note that the
reduction in capacity at these airports ranges from 14% at Detroit to a
high of 67% at Long Beach. A reduction of over 50% is probably caused by
the closing of one of the two parallel runways whereas a more limited
reduction in capacity (*e.g.*, 32% at MEM) is likely to indicate the use
of dependent parallel approaches at the airport when the weather
deteriorates. Capacities for JAN were unavailable, and values from RDU
were substituted based on similarities in the runway layouts and
centerline separations.

[Table 11. Capacities of Airports with Parallel Runways Between 3100 and
4300 ft. Separations Between Centerlines (Excluding MSP)]{.smallcaps}

  -------------- ---------------- -------------- -------------- --------------
  Airport ID     Airport Name     Optimum Hourly Reduced Hourly \% Arrival
                                  Arrival        Arrival        Capacity
                                  Capacity       Capacity       Reduction

  TPA            Tampa            71             50             30

  FLL            Ft. Lauderdale   65             27             58

  DTW            Detroit          84             72             14

  SLC            Salt Lake City   90             40             56

  MKE            General Mitchell 72             34             53

  JAN            Jackson          60             40             33

  RDU            Raleigh-Durham   60             40             33

  MEM            Memphis          88             60             32

  LGB            Long Beach       70             23             67

  PDX            Portland         60             38             37

  JFK            John F. Kennedy  74             48             35
  -------------- ---------------- -------------- -------------- --------------

### Methodology

In order to describe the methodology employed in this analysis, an
example involving JFK is described. To determine the impact that a
capacity reduction of the size shown in this table can have on
congestion and delays, the IBM Single Airport Delay Model[^69] was
applied to the demand and capacity data. The arrivals for a
representative traffic day[^70] were compared to the optimum and reduced
capacities at JFK. This analysis focused on Cat I operations, although
there is no restriction preventing Cat II/III simultaneous parallel
operations on runways separated by 3400 feet. Since reduced capacity
conditions occur approximately 7.5% of the time at JFK, or on average
about 1.75 hours per day, a moving window of reduced delay was applied
to the model, effectively creating different scenarios representing many
possible combinations of 1.75 hour windows during the course of a day.
For each of these scenarios, the average daily delay was calculated and
then averaged these average delays across the scenarios. This model
result (0.03 minutes per flight) was compared to the delays obtained
with JFK at optimum capacity (0.0 minutes per flight). The difference in
delays, 0.03 minutes per flight, represents the potential improvement
that can be achieved with LAAS.

Multiplying this value by the number of flights by user group yields the
delay minutes by user group. Then, multiplying by the cost of a minute
of delay yields the total cost savings that might be achieved at JFK.
Finally, recognizing the fact that LAAS will need to be combined with
other technologies to achieve this benefit, a factor of ½ was applied to
the result. As with the other benefits estimated in this report, a
downstream effect factor (See Appendix N) was applied, as well as an
availability factor of .999, the assumed availability of LAAS. Over the
20 year benefits period, the total direct operating cost savings at JFK
is estimated to be \$269,000.

### Results

Table 12 shows the LAAS closely spaced parallel approach benefit for Cat
I LAAS implementation, in terms of both reduced direct operating costs
and passenger time savings, as well as for the two scenarios of user
WAAS equipage.

[Table 12: Discounted 20 year LAAS Closely Spaced Parallel Approach
Benefits for Cat I]{.smallcaps}

+---------------------+-----------------------+-----------------------+
|                     | **Direct Operating    | **Passenger Time      |
|                     | Cost**                | Savings**             |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$11,300,000          | \$10,800,000          |
|                     |                       |                       |
| **(Assuming 0% WAAS |                       |                       |
| equipage)**         |                       |                       |
+---------------------+-----------------------+-----------------------+
| **LAAS Benefits**   | \$500,000             | \$100,000             |
|                     |                       |                       |
| **(Assuming 100%    |                       |                       |
| WAAS equipage)**    |                       |                       |
+---------------------+-----------------------+-----------------------+

### Summary

As indicated above, LAAS without advanced cockpit technologies or LAAS
in the presence of a 100% WAAS equipage scenario is unlikely to lead to
a significant reduction in runway separation distances required to
conduct simultaneous independent parallel approaches. However, evidence
from previous studies seems to support the conclusion that LAAS, when
combined with other advanced avionics, may be able to reduce these
distances and result in sizable quantifiable benefits in the 0% WAAS
equipage scenario. This comes about from the combination of improved
navigation system accuracy and reduction in the flight technical error.
LAAS may also enable more accurate position reporting when used in
concert with ADS-B, thus reducing the surveillance error. This may lead
to additional reductions in the required separation distances between
runway centerlines.

## [Benefits From Variable Glideslopes]{.smallcaps}

The ability of LAAS to support multiple simultaneous glideslopes
(separate vertical paths, each at a unique vertical angle, and each
capable of providing precision vertical guidance for aircraft during
approach and landing) may provide a level of flexibility not available
with the current precision approach infrastructure. In addition to the
possibility of allowing various vertical angles, these independent
glideslopes may lead either to the same or to different touchdown points
on the same runway. This capability also opens the possibility of
providing temporary changes in precision approach paths (*e.g.*, to
accommodate runway construction) more readily than is possible with an
ILS.

Examples of potential benefits include:

-   EWR runway 11 -- Allow for continued operations via steeper
    glideslope during times when harbor cargo ships interfere with
    current fixed ILS glideslope angle.

-   Potential to decrease longitudinal spacing between aircraft by
    placing lighter aircraft on a steeper glideslope than heavy
    aircraft, in order to avoid wake vortex problems.

-   MEM runway 17/35 -- Temporary approaches used during runway
    construction.

**Potential Benefit Illustrations**

Multiple glideslopes, same touchdown point Multiple glideslopes,
different touchdown points

![](media/image9.wmf){width="0.960236220472441in"
height="0.28976377952755905in"}![](media/image9.wmf){width="0.960236220472441in"
height="0.2889763779527559in"}

### Limitations

The range of practical glideslope angles is limited by aircraft
performance characteristics, and therefore not all current limitations
will be addressable.

Temporary approaches would still have to be flight tested and the
displaced threshold may not accommodate all aircraft due to the
shortened runway length.

## [Benefits from Digital Data Uplink]{.smallcaps}

Uplink of data, including RNAV and precision approach path waypoints,
may provide a level of flexibility for air traffic operations in the
terminal area not available with the current precision approach
infrastructure. The ability for the service provider to dynamically
alter the paths taken by individual aircraft in the terminal area, while
still maintaining positive guidance in the cockpit, would represent a
significant change in air traffic operations. The uplink of path
segments (*e.g.*, SIDs and STARs) using LAAS may have some benefits, but
at this time the technical and procedural details of this capability
have not been fully established, and a number of issues have been
identified, including:

-   The need for software in the cockpit to convert waypoint data in the
    ARINC 424 format to that used by the FMS and/or multimode receiver
    (MMR). This software could incur substantial additional costs and
    would probably require recertification of the existing avionics.

-   The waypoint data for approaches (STARs) would have to be uplinked
    when the aircraft is still in the cruise stage or just beginning its
    descent at a point approximately 100 nautical miles from the
    airport. That would mean that the current service volume for LAAS
    Cat I operations of approximately 20 nm would have to be extended an
    additional 80 nm to support this activity. Obviously, this would
    introduce a host of major issues.

-   Every change in a SID or STAR would require flight checking the LAAS
    transmission, according to FAA regulations.

-   The uplinking of SID or STAR data would require overwriting data in
    the FMS, possibly with pilot verification. It is unclear what the
    role of the pilot would be in this process. New procedures would
    have to be defined.

-   There may not be sufficient channel capacity to support the
    uplinking of SID and STAR data (since these messages tend to be very
    complex), particularly if multiple segments need to be transmitted
    to provide an alternative plan in case of an emergency.

-   If the SID or STAR is uplinked directly to an MMR, there will be a
    requirement for a new cockpit display to visualize the trajectory.
    Such a display would take years to develop and certify.

If these issues are resolved, and procedures are developed to take
advantage of the flexibility provided by the LAAS data uplink, this
capability may provide important benefits for both operators and service
providers.

## [Benefits from Airspace Confliction Resolution]{.smallcaps}

The horizontal and vertical accuracy of LAAS, whether as precision
guidance system, or in support of RNAV/RNP procedures, may provide the
capability to resolve conflicts in airspace usage among adjacent
airports and between arrivals and departures at the same airport. The
capability to resolve airspace conflicts may reduce the airspace needed
per operation, thus allowing a greater density of operations in a given
airspace. This capability may be of particular importance in highly
congested airspace (*e.g.*, the Chicago, New York and Los Angeles
areas).

The following airports were cited by airline and airport stakeholders as
examples of locations where this benefit could be applied.

-   SEA SEA may increase efficiency by separating arrival and departure
    streams.

-   BFI BFI arrivals conflict with SEA operations during north flow
    operations.

-   MDW MDW 13C arrivals conflict with ORD 22L departures and 14L
    arrivals.

-   PWK PWK 34 circling arrivals conflict with ORD 32R departures.

-   HOU Conflict with IAH traffic

-   FLL Conflict with MIA traffic

-   BUR Conflict with LAX traffic

-   JFK-LGA-EWR-TEB Significant conflicts among these airports,
    depending on wind and

> weather conditions.

### Limitations

Each airspace environment is unique and must be evaluated thoroughly to
identify how, and under what circumstances, LAAS may contribute to
airspace conflict resolution. It is expected that only the most complex
and congested airspace environments will require a LAAS-based solution.

Some airspace conflict resolution may be possible with RNAV capabilities
through the use of GPS and/or WAAS. In these cases, LAAS may show little
to no benefit.

## [Benefits from Guided Missed Approach]{.smallcaps}

LAAS may have the capability to provide precision guidance, potentially
including complex or curved paths, for the missed approach segment. A
low-RNP and/or complex guided missed approach may permit reductions in
approach minima and/or continued use of one or more runways during low
weather minima conditions.

**Potential Benefit Examples**

+-----------------------------------+-----------------------------------+
| **ORD**                           | **SEA**                           |
|                                   |                                   |
| In order to maintain approaches   | A precision guided, curved missed |
| to 9R/9L and 4R, ORD would        | approach                          |
| benefit from the ability to have  |                                   |
| precision guided, curved missed   | would allow for increased arrival |
| approaches.                       | throughput to 16R, since arriving |
|                                   | aircraft would not have to wait   |
|                                   | for 16L Departures.               |
+-----------------------------------+-----------------------------------+
|                                   |                                   |
+-----------------------------------+-----------------------------------+

### Limitations

Some of these benefits may be achievable with RNAV capabilities through
the use of GPS and/or WAAS. In these cases, LAAS may show little to no
benefit.

No data exists at this time to determine the lower approach minima that
may be associated with low-RNP and/or complex guided missed approach
procedures.

# [Safety Benefits]{.smallcaps}

This section presents a summary of methods and findings from the
evaluation of potential LAAS safety benefits. The full safety analysis
report, from which this section is drawn, was produced by the Flight
Safety Foundation (FSF), a recognized authority in the field of aviation
safety analysis. The full FSF report is available separately (Please
refer to the FSF's *Safety Benefits of the*

*Local Area Augmentation System* report for details).

**Introduction**

Currently, there are many different types of navigation-based approaches
to runways at the more than 4,000 public use airports with paved
runways.[^71] These airports have well over 10,000 runways, of which
more than 1,150 have instrument landing system (ILS) precision
approaches[^72]. The remaining runways have no instrument approaches or
use a variety of less precise non-precision instrument approaches.

A precision approach provides the pilot with both vertical and
horizontal guidance to the end of the runway. The ability to maintain a
constant reference to the vertical and horizontal path to the runway
enhances the ability of a pilot to fly a stable approach. According to
the Flight Safety Foundation[^73], a stable approach is one where the
aircraft is on the correct flight path, only small changes in heading
and pitch are required to maintain that path, airspeed is at the correct
approach speed, the aircraft is in the proper landing configuration, and
the descent rate is a maximum of 1,000 feet per minute. In contrast, a
non-precision approach provides the pilot with only horizontal guidance
to the runway. The pilot is responsible for maintaining vertical
separation from terrain using the aircraft's altimeter and other onboard
instruments. It is generally acknowledged that a precision approach is
safer than a non-precision approach. This is supported by research
conducted by the Flight Safety Foundation which indicated that the risk
of an accident among air carrier airplanes is five times greater during
a non-precision approach than a precision approach.[^74]

The GPS-based navigation system used for instrument approaches will
ultimately provide some degree of precision instrument approach
capability at many of the runways at the nation's 4,000 public use
airports. This is expected to have a profound and positive impact on
aviation safety.[^75] The satellite-based navigation system has three
main components: the GPS satellite constellation, and two augmentations
systems, WAAS and LAAS. WAAS currently provides multiple levels of
navigation service across the NAS, including en-route, terminal, and
approach guidance. WAAS is not expected to reach Category I approach
standards (generally 200 feet ceiling and ½ mile visibility) until 2015.
LAAS is expected to provide terminal area and approach guidance,
particularly for the stringent requirements of Cat I, II and III
approaches. This paper addresses the anticipated safety benefits
associated with LAAS.

The underlying hypothesis of this study is that LAAS will provide safety
benefits attributable to a precision approach at runway ends without
current precision approach service and when weather conditions are below
those supported by systems in the baseline. The LAAS capabilities that
are expected to lead to safety benefits include the following:

-   LAAS will provide Category I approach capability at those locations
    where WAAS service is not anticipated or Category I ILS guidance is
    not provided.

-   LAAS will provide Category II and Category III approach capability
    at facilities that do not currently have that capability.

-   LAAS will provide positive surface guidance in reduced visibility,
    and/or in dark conditions, to aircraft equipped with heads-up
    displays (HUD), LAAS, and the appropriate equipment to integrate the
    information.

-   LAAS will provide positive three-dimensional navigational guidance
    in the cockpit that will reduce the risk of controlled flight into
    terrain (CFIT) accidents for approach and departure in the terminal
    area.

-   LAAS will help reduce pilot and controller workload for complex
    approach and departure routings.

-   LAAS will provide positive lead-in guidance to parallel approach
    situations.

To evaluate the safety benefits of LAAS implementation, the study relied
heavily on a retrospective evaluation of accidents and incidents. The
underlying rates of these accidents were used to project anticipated
losses if LAAS were not implemented. Past studies and related literature
were reviewed to ensure that all relevant references were considered as
the data analysis proceeded. Once the benefits of LAAS implementation
were determined, they were used to develop a cost assessment of the
benefits of reduced crashes.

**Methodology**

The basic approach used for the analysis focused on the following steps:

-   First, the actual crash and incident experience for the time period
    of 1993-2002 was reviewed and events were selected that might have
    been prevented if LAAS had been operational.

-   Using this information, a baseline incident rate per 1,000,000
    departures based on the 10 year period of 1993-2002 was developed.

-   Next, the anticipated incident risk at airports likely to be
    equipped with LAAS was estimated for the time period of 2009-2028.
    This estimate was adjusted for an anticipated LAAS implementation
    that accounted for a gradual implementation of LAAS in the NAS.

-   In addition, the impact of WAAS on these benefits was estimated,
    assuming a WAAS GLS IOC during 2015.

Using this approach, an estimate of crash risk during the implementation
cycle of LAAS was developed. The anticipated number of lives saved and
crashes prevented due to the future implementation of LAAS was also
estimated. Using the resulting values, the estimated benefit of the
anticipated reduction of losses in future dollars was developed.

**Study Population**

The study focused on two different populations. These were the
operational environment of Alaska and that of the continental United
States, or CONUS. The analysis for each study population was conducted
in the same way, although some underlying assumptions were different.

For Alaska, all aircraft types were considered in the analyses. This
included air carrier aircraft, commuter aircraft, and general aviation
aircraft. The evaluation of safety benefits associated with LAAS in the
CONUS was limited to air carrier and "heavy" non-air carrier aircraft
typically operated by business and corporate operators. Examples of
aircraft included in the corporate category were turbine powered
passenger aircraft and heavy piston-powered twins such as Piper PA-31
Navaho or the Cessna 400 series aircraft (Cessna 404, 414, 421). Smaller
general aviation aircraft were not included in the CONUS analysis. The
analyses for all types of aircraft considered the anticipated benefit of
LAAS with and without WAAS equipage on the aircraft.

**Data sources**

A number of data sources were used for this analysis. The National
Transportation Safety Board (NTSB) accident and incident investigation
database was used to identify accidents and serious incidents. The FAA's
National Airspace Incidents Monitoring System (NAIMS)[^76] was used to
identify surface-related incidents that did not result in an accident.
This included events such as runway incursions and surface
near-collisions. Airport activity data, both historical and forecast,
were obtained from the FAA's Office of Aviation Policy and Plans (APO)
Terminal Area Forecast (TAF). On-line databases were queried and
forecast reports were referenced. Information was also obtained from the
National Aeronautical and Space Administration's (NASA) Aviation Safety
Reporting System (ASRS). This data system was queried to learn more
about factors associated with pilot-reported runway incursions and
approach incidents.

**Case Selection**

Past accidents and serious incidents were used to provide insight on the
potential benefits of LAAS. NTSB accident records were reviewed to
determine what accidents, if any, might have been prevented if LAAS had
been present. The methodology followed is described below:

a)  **Initial Record Filter:** All NTSB accident records for the time
    period of 1993-2002 were selected and compiled in a database using
    SPSS software.[^77] Records were then selected for accidents that
    occurred within 10 miles of an airport, while on approach, in IFR
    conditions, or while on the airport surface. This required that
    airport identification be provided.

b)  **Airport Filter:** Once the above filtering was completed, only
    those events that occurred at the study airports were selected.

c)  **Manual Review:** The resulting records were then used to obtain
    NTSB "briefs" which provided summaries of pertinent information
    associated with the accident and the resulting investigation.[^78]
    These briefs were reviewed independently by two different aviation
    subject matter experts to determine each case's suitability for
    inclusion in the study. The manual review focused on determining the
    safety benefits if LAAS had been present. The potential benefits
    that might be attributed to WAAS were not considered during this
    part of the analyses but were accounted for later in the evaluation.
    Additionally, among CONUS events, the brief was reviewed to
    determine whether the accident involved an air carrier or corporate
    type of aircraft using make and model as the initial indicator. This
    was further confirmed by reviewing the narrative associated with the
    accident or incident as well as reviewing the regulation that the
    aircraft was operated under (FAR parts 121, or 135 or 91 for
    example).

**Limitations of Quantitative Analyses**

There are a number of limitations associated with this benefits
evaluation. The applicability of a study such as this is directly
related to the underlying assumptions. The discussion of the following
limitations is designed to make sure that the reader is aware of some of
the more notable limitations that could affect the applicability of the
results.

a)  **Corporate Aircraft Activity Assumptions:** For the analyses in
    this study, estimates for corporate aviation were derived by
    reported and forecast activity statistics, reported by the NBAA in
    hours. These values were reported for the time period of 1997-2004
    and indicated that 16.5% of all general aviation activity is
    conducted by corporate aircraft. The assumption that cannot be
    validated is that the ratio of corporate hours to all GA hours
    (16.5%) is the same for departures. If there is a bias, it will be
    consistent for both the reference period calculations as well as the
    forecast calculations, thereby minimizing the biasing effect of the
    error.

b)  **Activity Forecasts:** There are many factors that cannot be fully
    accounted for in generating long-range activity forecasts. Political
    events, economic dynamics, introduction of new technologies, and
    many other issues may result in actual activity levels that are
    smaller or greater than forecast. Since the activity estimates are
    used to derive event rates that are in turn used to generate
    estimates of actual events in the future, any errors in the activity
    measure may result in significant differences in the actual number
    of events that occur.

c)  **Problem of Small Numbers:** The type of events that were used in
    this analysis are relatively rare events. For example, for the time
    period of 1993-2002 there were an estimated 106.5 million departures
    that involved air carrier and corporate aircraft at the study
    airports in the CONUS. There were only 11 accidents, however, at
    these same airports for the same time period that might have
    benefited from LAAS. Consequently, one additional event in which an
    air carrier crashed and killed all on board could have a profound
    effect on the resulting accident rates and future benefit
    projections. This problem does not invalidate the results, but needs
    to be considered since these events are rare.

d)  **NTSB Screening Methods:** The methods chosen to conduct the
    initial computer screening of the NTSB accident records were
    somewhat conservative and may have missed relevant cases. The
    difficulty with this approach is that some NTSB records that were
    probably suitable for inclusion in the study, may not have been
    selected by the initial computer screening because of missing data
    in one or more relevant computer fields. The effect of potentially
    not including all relevant cases is to make the associated benefit
    assumptions more conservative, understating the potential benefit of
    LAAS.

**Findings**

Table 13 provides the distribution of approach and airport surface
accidents in the CONUS stratified by aircraft category that would have
been unlikely to have occurred if LAAS had been operational between 1993
and 2002 and the accident aircraft had been equipped with appropriate
LAAS receivers.

[Table 13]{.smallcaps}: Distribution of Accidents in the CONUS That
Would Have Benefited From LAAS, 1993-2002

  -------------- --------- -------------- ------------- ------------- ------------- -----------
  **Category**   **Air     **Air Carrier  **Corporate   **Corporate   **Corporate   **Total**
                 Carrier   Turbo-Prop**   Jet**         Turboprop**   Heavy Piston  
                 Jet**                                                Twin**        

  **Approach**   5         0              0             2             0             7

  **Surface**    0         2              1             1             0             4

  **Total**      5         2              1             3             0             11
  -------------- --------- -------------- ------------- ------------- ------------- -----------

While similar evaluation was attempted for the three airports in Alaska
that were included in this analysis, no accidents were found that might
have been prevented by the presence of a precision approach capability
for the time period of 1993-2002. Consequently, the balance of findings
presented in this section is limited to the CONUS.

Table 14 provides estimates of the future number of accidents with and
without the precision approach capability provided by WAAS, or LAAS.

[Table 14]{.smallcaps}: Number of Accidents With and Without LAAS and
WAAS, 2009-2028

  ----------------------------------- -----------------------------------
  **Level of LAAS or WAAS Coverage**  **Projected Number of Approach
                                      Accidents 2009-2028**

  With No LAAS or WAAS                34

  With WAAS Only                      [12]{.smallcaps}

  With LAAS Only                      3
  ----------------------------------- -----------------------------------

Tables 15, 16, and 17 provide a summary of the 20-year discounted LAAS
safety benefits for precision approach and surface navigation. Both
tables show LAAS safety benefits for two WAAS equipage scenarios: with
100% WAAS equipage by operators, and with 0% WAAS equipage by operators.
The estimated precision approach benefits of LAAS, for the scenario in
which operators do not equip with WAAS, total \$38.1 million for the
timeframe of 2009-2028 at the 117 study airports in the CONUS. For the
scenario in which operators equip with WAAS, LAAS benefits were
estimated to be \$14.9 million. Surface navigation benefits for LAAS are
most likely shared with some enabling technology, like ADS-B, or moving
map. To reflect this discrepancy, the benefits calculated by FSF were
divided by two for this report. The estimated surface guidance benefits
of LAAS with 0% WAAS equipage is \$20.2 million for the time frame of
2009 to 2028 at the CONUS airports. Additionally, although FSF finds
that LAAS is the most likely system to provide surface navigation
positioning information, we conclude that other systems, like WAAS or
multilateration, may also be able to provide this service. Therefore,
our LAAS surface navigation benefit for the 100% WAAS equipage scenario
is zero.

[Table 15: Discounted 20 Year LAAS Safety Precision Approach
Benefits]{.smallcaps}

+----------------+--------------+-----------+-------------+-----------+
|                | **Accidents  | **Fatal   | **Serious   | **Total** |
|                | Prevented    | Injuries  | Injuries    |           |
|                | (Hull loss   | Pr        | Prevented** |           |
|                | and          | evented** |             |           |
|                | damage)**    |           |             |           |
+----------------+--------------+-----------+-------------+-----------+
| **LAAS         | \$37,569,000 | \$0       | \$555,000   | \$3       |
| Benefits**     |              |           |             | 8,124,000 |
|                |              |           |             |           |
| **(Assuming 0% |              |           |             |           |
| WAAS           |              |           |             |           |
| equipage)**    |              |           |             |           |
+----------------+--------------+-----------+-------------+-----------+
| **LAAS         | \$14,636,000 | \$0       | \$240,000   | \$1       |
| Benefits**     |              |           |             | 4,876,000 |
|                |              |           |             |           |
| **(Assuming    |              |           |             |           |
| 100% WAAS      |              |           |             |           |
| equipage)**    |              |           |             |           |
+----------------+--------------+-----------+-------------+-----------+

[Table 16: Discounted 20 Year LAAS Safety Surface Guidance
Benefits]{.smallcaps}

+----------------+-------------+------------+------------+-----------+
|                | **Accidents | **Fatal    | **Serious  | **Total** |
|                | Prevented   | Injuries   | Injuries   |           |
|                | (Hull loss  | P          | P          |           |
|                | and         | revented** | revented** |           |
|                | damage)**   |            |            |           |
+----------------+-------------+------------+------------+-----------+
| **LAAS         | \$5,122,000 | \$         | \$419,500  | \$2       |
| Benefits**     |             | 14,634,000 |            | 0,175,500 |
|                |             |            |            |           |
| **(Assuming 0% |             |            |            |           |
| WAAS           |             |            |            |           |
| equipage)**    |             |            |            |           |
+----------------+-------------+------------+------------+-----------+
| **LAAS         | \$0         | \$0        | \$0        | \$0       |
| Benefits**     |             |            |            |           |
|                |             |            |            |           |
| **(Assuming    |             |            |            |           |
| 100% WAAS      |             |            |            |           |
| equipage)**    |             |            |            |           |
+----------------+-------------+------------+------------+-----------+

[Table 17: LAAS Safety-Related Monetary Benefits (Precision Approaches
and Surface Guidance)]{.smallcaps}

+----------------+-------------+--------------+----------+-----------+
|                | **Accidents | **Fatal      | *        | **Total** |
|                | Prevented   | Injuries     | *Serious |           |
|                | (Hull loss  | Prevented**  | Injuries |           |
|                | and         |              | Pre      |           |
|                | damage)**   |              | vented** |           |
+----------------+-------------+--------------+----------+-----------+
| **LAAS         | \           | \$14,634,000 | \        | \$5       |
| Benefits**     | $42,691,000 |              | $974,500 | 8,299,500 |
|                |             |              |          |           |
| **(Assuming 0% |             |              |          |           |
| WAAS           |             |              |          |           |
| equipage)**    |             |              |          |           |
+----------------+-------------+--------------+----------+-----------+
| **LAAS         | \$          | \$0          | \        | \$1       |
| Benefits**     | 14,636,000, |              | $240,000 | 4,876,000 |
|                |             |              |          |           |
| **(Assuming    |             |              |          |           |
| 100% WAAS      |             |              |          |           |
| equipage)**    |             |              |          |           |
+----------------+-------------+--------------+----------+-----------+

# 

# [Societal Benefits]{.smallcaps}

The following societal benefits are discussed further in this document.

-   Continuation of U.S. Technology Leadership in Air Navigation

-   International LGF and LAAS Avionics Sales Revenue to U.S.
    Manufacturers

-   Noise Abatement and Mitigation

-   Reduced Impact on Environmentally Sensitive Areas

-   LAAS Complements Homeland Security

-   LAAS and JPALS Offer Civilian and Military Compatibility

-   Expansion of Air Commerce to Smaller Communities

-   Increased Reliability of Air Service

**Quantitative Analyses**

IBM has investigated the potential quantitative LAAS Benefits that may
be obtained through (1) sales of LGF and LAAS avionics to international
airports and airlines, and (2) increased U.S. Airport Improvement
Program and U.S airline revenue through a 1% increased load factor on 1%
of operations. These quantitative societal benefits are highly
speculative, and are included only to illustrate the importance of
economic impact LAAS may provide. These benefits estimates will not be
incorporated in the total benefits derived from the efficiency benefits
analysis.

**Qualitative Descriptions**

Many of these qualitative potential benefits may also be achieved
through current or emerging procedures (*e.g.*, RNAV/RNP) or
technologies (*e.g.*, WAAS). Therefore, further investigation should be
considered to determine if, and by how much, LAAS may uniquely provide
these benefits.

## [Continuation of U.S. technology leadership in air navigation]{.smallcaps}

[]{.mark}

In a recent speech, the Secretary of Transportation said, "Today, new
aviation initiatives are underway in Europe and elsewhere. We are being
challenged in manufacturing and in satellite positioning and navigation
services as Europe develops the Galileo system, an alternative to our
own Global Positioning System. We can work with our international
partners to develop an interoperable aviation system that increases
mobility. Or we can refuse to engage, refuse to lead, and thereby let
others set the rules of the world's skyways. We must not let that
happen. If America wants to retain its global air transportation
leadership, we need to modernize and transform our air transportation
system -- starting right now. With the forthcoming modernization of GPS,
satellite navigation will be far more important to aviation than it is
today[^79]." LAAS could be an integral part of this modernization.

The FAA's Flight Plan 2004-2008[^80] specifically identifies GNSS
augmentation systems as one tool to help reach the goal of "seamless
operations around the globe...", and advocates that the agency promote
the "commercial proliferation, interoperability and use" of these
systems. The U.S. has historically taken a lead role in promoting
satellite navigation around the world as the standard for 21st Century
air navigation. As part of this standardization, the LAAS architecture
was successfully presented and approved by the International Civil
Aviation Organization (ICAO) Global Navigation Satellite System (GNSS)
Panel in February 1997[^81]. LAAS is an element in the full realization
of benefits from investment in satellite navigation programs. Further,
despite its inherently local nature, LAAS can be a truly global
navigation solution. A LAAS installation outside of the U.S. can provide
the same types of benefits as a domestic installation. In this context,
LAAS can be used to support the FAA's international leadership goal,
stated in the 2004-2008 Flight Plan, to "Promote seamless operations
around the globe..."

The U.S. has the world's most complex airspace and leads the world in
the development of the new CNS-ATM (Communication, Navigation,
Surveillance/Air Traffic Management) suite of technologies and
operational concepts. The U.S. was directly involved in the development
of ICAO's Standards and Recommended Practices (SARPS) for the
development of space-based and ground-based (SBAS/GBAS) augmentation
systems and GNSS, which became effective in November 2001. LAAS
implementation will encourage a single standard for global navigation
and help in areas lacking CNS-ATM coverage. International implementation
of LAAS could bring high-precision navigation service to areas now
served by minimal or outdated equipment, allowing expansion of air
service by both U.S. and foreign carriers.

## [International LGF and LAAS Avionics Sales Revenue]{.smallcaps} 

**Overview**

Our discussions with U.S. carriers revealed two important goals: 1) to
simplify the number and variety of landing systems and procedures
currently in use, and 2) to operate globally with the same set of
simplified systems and procedures. A single navigation and landing
system, capable of global implementation, can contribute to achieving
these goals. If domestic carriers equip with LAAS, they will want to use
this capability throughout their networks, including at overseas
airports. Therefore, IBM explored the potential market for international
LGF sales.

Similarly, if domestic carriers equip with LAAS, foreign carriers
operating to the U.S. will have an incentive to also equip with LAAS.
Therefore, IBM explored the potential market for international (Part
129) avionics sales. Retrofit sales revenue was not included.

A detailed analysis of the most likely extent of international sales
would be a significant undertaking, and is out of the scope of this
project. Instead, we estimated the market size and potential benefit of
international sales of both LGFs and LAAS avionics.

**Methodology**

A.  Revenue from LGF Purchase and Install

    1.  Estimate LGF purchase sales price: \$600K purchase.

> Note: LGF installation cost is not included.

2.  Estimate the number of international airports served by U.S.
    carriers: 182[^82].

3.  Estimate the number of current and planned international MLS
    installations: 12 (plus 13 potential close orders)[^83].

4.  The potential international LGF market is (2) minus (3).

5.  The maximum potential LGF benefit is (4) times \$600K.

```{=html}
<!-- -->
```
B.  Revenue from LAAS Avionics

    1.  Estimate LAAS avionics sales price: \$10K.

> Note: Any potential LAAS retrofit sales are not included.

2.  Estimate the number of international carriers' aircraft serving the
    121 studied airports: 846[^84].

> Note: Assume international carriers will equip all aircraft that serve
> the U.S.

3.  The potential international LAAS avionics market is (2).

4.  The maximum potential LAAS avionics benefit is (3) times \$10K.

**Results: Market Estimate and Maximum Potential Original Equipment
Manufacturer (OEM) Benefit**

A.  International LGF

    a.  Market Estimate is 157 airports.

    b.  Maximum Potential OEM Benefit is \$94,200,000.

B.  International (Part 129) Avionics

    a.  Market Estimate is 846.

    b.  Maximum Potential OEM Benefit is \$8,460,000.

## [Noise Abatement and Mitigation]{.smallcaps}

While many airports seek to expand their facilities and operations to
serve current and expected future demand for air travel, the communities
surrounding airports also continue to expand, filling previously unused
land in the vicinity of the airports. One result is a growing concern
about aviation related noise and its impact on these communities.
Airlines and airframe manufacturers have worked together to
significantly reduce the noise produced by modern aircraft, but noise
generation remains a problem for many airports. More precise navigation
in the terminal area may offer an opportunity to greatly reduce the
impact of aviation related noise by restricting aircraft to defined
three dimensional routes designed to reduce the noise effects.

Through the flexibility offered by LAAS to construct complex, defined,
highly repeatable flight paths that can be used during all weather
conditions, the current costs associated with noise mitigation and noise
abatement may be reduced. This section identifies the LAAS capabilities
that can support noise reduction efforts, and summarizes some of the
current costs associated with noise reduction programs.

Noise abatement and mitigation may be possible with RNAV capabilities
through the use of GPS and/or WAAS. In these cases, LAAS may show little
to no benefit to enabling noise abatement and mitigation.

The FAA describes how aviation-related noise is measured as part of its
Airport Noise Compatibility Program, found in Part 150 of the Federal
Aviation Regulations[^85]. These guidelines describe the noise levels
that are considered acceptable and the impact that noise has on
individuals and communities.

### Methodology

1.  Identify LAAS capabilities that may offer control over the
    generation and distribution of noise

2.  Review historical costs associated with airport noise.

3.  Identify and group costs in one of the following areas where LAAS
    may provide potential reduction in:

    -   Noise Program Costs

    -   Noise Violations Cost

    -   Land Acquisition for Noise Compatibility

    -   Residential Home Soundproofing

    -   School Soundproofing

    -   Litigation

    -   Airport Curfews

### Relevant LAAS Capabilities

The LAAS capabilities that may have a direct impact on noise issues are
those that offer increased control over the flight path taken. The
ability to consistently provide defined, repeatable (laterally and
vertically contained) flight tracks during all weather conditions allows
for greater control over noise distribution and can offer potential cost
savings for noise related programs and issues.

1.  **Defined, repeatable flight paths:** By defining a specific flight
    path that can realistically be expected to be repeatable, even in
    the busiest, most complex airspaces, LAAS-based procedures provide a
    way for airports and communities to achieve a balance that optimizes
    terminal area efficiency and reduced noise impact. Demonstration to
    community members of the high degree of three-dimensional
    repeatability of these paths, particularly compared to today's wide
    range of flight paths taken could greatly reduce the time and costs
    typically associated with litigation over airport changes, such as
    runway expansions or additions. Further, the reduction in flight
    path variability due to LAAS-based procedures may result in fewer
    homes and schools needing soundproofing, as well as reducing airport
    land acquisition costs.

2.  **All-weather complex approach and departure procedures:** Use of
    LAAS may allow aircraft to follow complex, noise mitigating,
    approach and departure routes during all weather conditions,
    including conditions of low weather minima. Other systems in the
    baseline that also support complex routes do not support operations
    to Cat II or III conditions. Use of LAAS-based procedures assures
    that the same flight path is taken during all weather conditions,
    further reducing flight path variability as a function of weather.

![](media/image11.wmf){width="1.25in" height="0.34375in"}

![](media/image11.wmf){width="1.25in" height="0.34375in"}

### ![](media/image11.wmf){width="1.25in" height="0.34375in"}

### 

### 

### 

### 

### 

### 

[Figure 4: Defined, repeatable flight paths through lateral and vertical
containment]{.smallcaps}

### 

### Costs of Noise Abatement and Mitigation

The following summary provides examples of aviation noise related costs
that LAAS capabilities may be able to reduce. Costs incurred by airports
are currently funded primarily through the Airport Improvement Program
(AIP), the Passenger Facility Charge (PFC), as well as other federal,
state, and local funds.

1.  Noise Programs Costs

-   U.S. DOT Commemorates Earth Day with Announcement of \$307 Million
    Effort to Combat Noise Pollution Near Airports[^86]

-   MSP - \$120M-\$150M Noise Abatement[^87]

    a.  MAC's commitment over the years brought the first federally
        commissioned SCAT 1 LAAS ground station to MSP and resulted in
        the present Beta LAAS station that is here and operational today

    b.  At MSP we have considered and, in some ways, incorporated the
        anticipated capabilities GPS/LAAS will offer in the future as
        part of our long-term noise compatibility planning and in
        efforts to reduce noise associated with a new runway

    c.  The Part 150 Update effort at MSP includes provision in the
        draft Noise Compatibility Program (NCP) for the future use of
        GPS/LAAS Technology

    d.  The new departure procedure can be flown with today's
        technology, although it was developed such that GPS/LAAS could
        enhance the procedure

    e.  In addition to the establishment of a departure procedure for
        the new runway, the Part 150 NCP work at MSP includes other
        noise abetment measures that are directly related to the future
        use of GPS/LAAS and associated noise reducing capabilities

        i.  Low-Demand Flight Tracks -- designates certain flight
            tracks, by runway end, for preferred use during low-demand
            time periods to reduce noise impacts

        ii. Runway 35 River Visual Approach Procedure -- recommends that
            MAC and FAA investigate a visual arrival procedure to Runway
            35 that routes arriving aircraft over the Minnesota River
            Valley to reduce noise and overflights of populated areas

        iii. Future Technology and Global Positioning System (GPS)
             Initiatives -- recommends that the MAC and the FAA
             investigate the potential use of emerging GPS technologies
             for noise mitigation purposes, and implement beneficial
             procedures as necessary

-   ORD - \$300M has been provided to assist in reducing the impacts of
    aircraft noise on communities near O\'Hare and Midway Airports[^88].

2.  Noise Rule Violations Costs

-   DEN[^89]: Violations of noise levels at DEN are subject to \$500,000
    per violation.

-   BOS[^90]: Penalties for violation of takeoffs on 4L above 73dBA and
    landings on 22R above 78dBA are fines ranging between \$50 and \$500
    per offense.

3.  Land Acquisition for Noise Compatibility

> According to the U.S. GAO, Aviation and the Environment, FAA's Role in
> Major Noise Programs[^91], more than 75 percent of all AIP funds and
> over 50 percent of all PFC funds spent on noise reduction or
> mitigation have been used to acquire land and to soundproof buildings
> (See also, Residential Home Soundproofing section)

-   LAX[^92]: \$4 million, from AIP, to acquire land for noise
    compatibility

-   ONT[^93]: \$2.5 million, from AIP, to acquire land for noise
    compatibility and relocation assistance

4.  Residential Home Soundproofing[^94]

-   SNA: \$2.3 million, from AIP, to soundproof residences

-   BUR: \$1 million, from AIP, to soundproof 30 residences

-   SFO^:^ \$1 million, from AIP, to soundproof 100 residences

-   FAT: \$1 million, from AIP, to soundproof 100 residences

5.  School Soundproofing

-   JFK[^95]: \$12.2 million, from federal/local, to soundproof four
    schools

-   LGA[^96]: \$24.4 million, from federal/local, to soundproof nine
    schools

-   SYR[^97]: \$3.38 million, from federal/local, to soundproof a school

-   ORD[^98]: \$3 million to soundproof a school

-   MDW[^99]: \$3 million to soundproof a school

-   SAN[^100]: \$1.5 million, from AIP, to soundproof a school

6.  Litigation

-   DEN[^101]: Denver Must Pay County Four Million for Airport Noise

-   PBI[^102]: Florida Landowners Must Prove Decreased Property Value in
    Airport Noise Suit

-   EWR[^103]: Lawyers Hired to Fight Noise at Newark International
    Airport

-   BUR[^104]: Court Lets City Go to Trial on Noise Impact Issue

-   MEM[^105]: Memphis Airport Authority Votes to Settle Class-Action
    Noise Lawsuit

-   MSP[^106]: Minnesota City Sues Airport Commission Over Shifting Jet
    Noise to Their Community

-   ORD[^107],[^108]: \$7.6 Million School to Sue for Soundproofing from
    Airport Noise

-   BDL[^109]: Connecticut Residents Threaten to Sue State If Airport
    Noise Isn\'t Reduced

### Reduction or Lifting of Airport Curfews 

According to Boeing commercial noise data[^110], 33 of the 121 studied
airports, listed in Table 18, have noise-related curfews. By limiting
the impact of noise on surrounding communities, LAAS-based procedures
may permit airports to operate at times currently under curfew. Also,
expansion of airport operating times by limiting or lifting of curfews
can increase total daily capacity.

[Table 18: Airports with Curfews within the 121]{.smallcaps} Studied
Airports

  ---------------------- ---------------------- -------------------------
  **Airports with                               
  Noise-related Curfews                         
  (**Curfew times in                            
  parentheses)                                  

  AUS (00:00 to 06:00)   HNL                    PVD (0:00 to 07:00)

  BFI (22:00 to 07:00)   HPN (00:00 to 06:30)   RIC (03:00 to 12:00)

  BOS (23:00 to 07:00)   ILN                    SAN (22:30 to 06:30)

  BUR                    JFK (00:00 to 06:00)   SEA

  CMH                    LAS (20:00 to 08:00)   SFO

  DAL                    LAX                    SJC (23:30 to 06:30)

  DCA(22:00 to 07:00)    LGB                    SNA

  DEN                    MDW (22:00 to 06:00)   STL (23:00 to 06:00)

  DVT (21:30 to 06:00)   MSP                    SYR (02:00 to 07:00)

  EWR                    ONT                    TEB

  FAI (3:00 to 06:00)    PBI (22:00 to 07:00)   VNY
  ---------------------- ---------------------- -------------------------

##  [Reduced Impact on Environmentally Sensitive Areas]{.smallcaps}

While many airports seek to expand their facilities and operations to
serve current and expected future demand for air travel, the communities
surrounding airports also continue to expand, filling previously unused
land in the vicinity of the airports. One result is a growing concern
about the impact of aviation-related activities on environmentally
sensitive areas. Airlines and airframe manufacturers have worked
together to significantly reduce the environmental impact produced by
modern aircraft, but this remains a problem for some airports. More
precise navigation in the terminal area may offer an opportunity to
greatly reduce the environmental impact of flights by restricting
aircraft to defined three dimensional routes designed with
environmentally sensitive areas in mind.

Through the flexibility offered by LAAS to construct complex, defined,
highly repeatable flight paths that can be used during all weather
conditions, environmentally sensitive areas may be protected during all
weather conditions. This section identifies the LAAS capabilities that
can support environmental sensitive area efforts, and summarizes some of
the current areas with that may be potential beneficiaries.

Reduced impact on environmentally sensitive areas may be possible with
RNAV capabilities through the use of GPS and/or WAAS. In these cases,
LAAS may show little to no benefit.

The U.S. Department of Transportation's Federal Aviation Administration
has a long tradition of designating wildlife and conservation areas as
advisory noise-sensitive areas on navigational charts and other
published materials. This practice, as articulated in Advisory Circular
91-36C (\"Visual Flight Rules (VFR) Flight Near Noise-Sensitive
Areas[^111]\"), seeks to achieve a non-regulatory, cooperative approach
to eliminating low overflights which would be harmful to wildlife in
refuges and other environmentally-sensitive areas, including National
Parks, Wilderness Areas, and their individual State Park or Conservation
Area/Wildlife Refuge counterparts. It reflects the FAA's announced
policy of managing the airspace to protect environmental values on the
surface[^112].

### Methodology

1.  Identify LAAS capabilities that may offer control over the impact of
    aircraft operations on environmentally sensitive areas.

### Relevant LAAS Capabilities

The LAAS capabilities that may have a direct impact on environmentally
sensitive areas are those that offer increased control over the flight
path taken. The ability to consistently provide defined, repeatable
(laterally and vertically contained) flight tracks during all weather
conditions allows for reduced impact on environmentally sensitive areas.

1.  **Defined, Repeatable flight paths:** By defining a specific flight
    path that can realistically be expected to be repeatable, even in
    the busiest, most complex airspaces, LAAS-based procedures provide a
    way for airports and communities to achieve a balance that optimizes
    terminal area efficiency and reduced environmental impact.
    Demonstration to communities and airport authorities of the high
    degree of three-dimensional repeatability of these paths,
    particularly compared to today's wide range of flight paths (due to
    vectoring in the terminal area) could greatly reduce the time and
    costs typically associated with litigation over airport changes,
    such as runway expansions or additions.

2.  **All-weather complex approach and departure procedures:** Use of
    LAAS may allow aircraft to follow complex approach and departure
    routes that avoid environmentally sensitive areas during all weather
    conditions, including low ceiling and visibility. Other systems in
    the baseline that also support complex routes do not support
    operations to Cat II or III conditions. Use of LAAS-based procedures
    assures that the same flight path is taken during all weather
    conditions, further reducing flight path variability as a function
    of weather.

### Example Airports with Environmental Sensitive Areas

The following examples provide a list of airports with environmentally
sensitive areas. These areas may be protected now, and into the future
with airport expansion, through the use of defined, repeatable flight
paths using all weather complex approach and departure procedures.

Example airports with environmentally sensitive areas

-   BOS[^113]

-   CVG[^114]

-   DCA[^115]

-   SEA[^116]

## [LAAS As a Complement to Homeland Security]{.smallcaps}

Increased emphasis on aviation security requires precise navigation and
surveillance capabilities. The ability of LAAS to provide increased
control over flight paths may be crucial to Homeland Security. For
example, in areas of heightened security, such as DCA in our nation's
capitol, LAAS coupled with other technologies, such as ADS-B, may enable
Air Traffic to precisely anticipate an aircraft's expected terminal area
flight path, and more readily detect and react to any deviation from
that flight path.

RNAV capabilities achieved through the use of GPS and/or WAAS, and other
technologies, such as ADS-B, may also enable Air Traffic to precisely
anticipate the expected terminal area flight path, and to more readily
detect and react to any deviation from that flight path. In these cases,
LAAS may show little to no benefit.

### Methodology

1.  Identify airports within the 121 airports studied that have Aviation
    Defense Identification Zones (ADIZ) or temporary flight
    restrictions, as examples of airport and airspace locations at which
    an improved ability to identify and detect deviations from expected
    flight paths may be beneficial.

### Relevant LAAS Capabilities

The LAAS capabilities that may have a direct impact on Homeland Security
are those that offer increased control over the flight path taken. LAAS
may be coupled with an enabled technology that provides aircraft
position information to Air Traffic (*e.g.*, ADS-B), for surveillance
purposes.

### Example Airports with Aviation Defense Identification Zones (ADIZ) or Temporary Flight Restrictions (TFR)

Table 19 lists examples of airports in the IBM 121 subject to an ADIZ or
TFR.

[Table 19:]{.smallcaps} Airports with ASIZ or TFR

+--------+-------------------------------------------------------------+
| **Air  | **Comments**                                                |
| port** |                                                             |
+--------+-------------------------------------------------------------+
| NY     | Flight Restrictions for the 2004 Republican National        |
| [^117] | Convention in New York City.                                |
|        |                                                             |
|        | The FAA distributed a preliminary Flight Advisory that      |
|        | outlined three temporary flight restrictions (TFR).         |
|        |                                                             |
|        | The following aircraft operations will be authorized for    |
|        | general aviation operations:                                |
|        |                                                             |
|        | -   Only VFR/IFR arrivals or departures at Teterboro        |
|        |     Airport (TEB) will be permitted. No touch and go or     |
|        |     close in pattern work will be permitted.                |
|        |                                                             |
|        | -   All aircraft must squawk a discrete transponder code    |
|        |     assigned by ATC, and remain in two-way radio            |
|        |     communications with ATC while in the TFR. ATC shall     |
|        |     immediately be notified of any transponder failure and  |
|        |     ATC will provide the most direct course to exit the     |
|        |     TFR.                                                    |
+--------+-------------------------------------------------------------+

+--------+-------------------------------------------------------------+
| **Air  | **Comments**                                                |
| port** |                                                             |
+--------+-------------------------------------------------------------+
| MIA,   | **Presidential movement TFRs**                              |
| EWR,   |                                                             |
| JFK,   | Presidential movement TFRs can be issued with little        |
| LGA,   | advance notice. This list is not necessarily complete.      |
| DAY,   |                                                             |
|        | -   August 27: Miami, Florida                               |
| DTW,   |                                                             |
|        | -   August 29-30: Newark, New Jersey, and New York, New     |
| MHT,   |     York                                                    |
| BNA,   |                                                             |
| CMH    | -   August 30-September 1: New York, New York               |
| [^118] |                                                             |
|        | -   September 1-3: New York, New York                       |
|        |                                                             |
|        | -   Anticipated - August 28: Dayton, Ohio                   |
|        |                                                             |
|        | -   Anticipated - August 28: Lima, Ohio                     |
|        |                                                             |
|        | -   Anticipated - August 28: Toledo, Ohio                   |
|        |                                                             |
|        | -   Anticipated - August 28: Troy, Ohio                     |
|        |                                                             |
|        | -   Anticipated - August 29: Wheeling, West Virginia        |
|        |                                                             |
|        | -   Anticipated - August 30: Detroit, Michigan              |
|        |                                                             |
|        | -   Anticipated - August 30: Manchester, New Hampshire      |
|        |                                                             |
|        | -   Anticipated - August 31: Alleman, Iowa                  |
|        |                                                             |
|        | -   Anticipated - August 31: Gettysburg, Pennsylvania       |
|        |                                                             |
|        | -   Anticipated - August 31: Nashville, Tennessee           |
|        |                                                             |
|        | -   Anticipated - September 1: Columbus, Ohio               |
+--------+-------------------------------------------------------------+
| DCA    | **National Capital Region (NCR) Aviation Defense            |
| [^119] | Identification Zone (ADIZ)** remains active with the added  |
|        | requirement that all VFR and IFR flights within the ADIZ    |
|        | file flight plans before takeoff and close flight plans     |
|        | upon landing or exiting the ADIZ.                           |
+--------+-------------------------------------------------------------+
| JFK,   | **An ADIZ for New York City** has also been added           |
| LGA,   | restricting flight operations from the surface to flight    |
| EWR    | level 180 in the area within the mode C veil (approximately |
| [^120] | 30 nm) surrounding JFK International (JFK), LaGuardia       |
|        | International (LGA), and Newark, New Jersey (EWR)           |
|        | International airports.                                     |
+--------+-------------------------------------------------------------+
| ORD    | **Temporary Flight Restrictions (TFR) -** March 22, 2003    |
| [^121] |                                                             |
|        | The FAA and TSA created a temporary flight restriction for  |
|        | the city of Chicago, focusing on the downtown skyline area. |
+--------+-------------------------------------------------------------+
| SLC    | **Temporary Flight Restrictions (TFR) --** Winter Olympics  |
| [^122] |                                                             |
|        | The FAA implemented a security plan that restricted general |
|        | aviation operations within a 45-nm radius of Salt Lake City |
|        | International Airport. The temporary flight restrictions    |
|        | area (TFR) extended from surface to 18,000 feet Mean Sea    |
|        | Level (MSL) for 19 days, beginning on February 6, 2001.     |
+--------+-------------------------------------------------------------+
| ATL    | **Temporary Flight Restrictions (TFRs)** Summer Olympics    |
| [^123] |                                                             |
|        | -   a radius of three nm around the Georgia Dome (below     |
|        |     3500 MSL)                                               |
|        |                                                             |
|        | -   one nm around the Olympic Village (below 3500 MSL)      |
+--------+-------------------------------------------------------------+

## [LAAS and JPALS Offer Civilian and Military Compatibility]{.smallcaps}

The Department of Defense (DoD) currently operates a variety of
precision approach systems, including ILS, MLS, and Precision Approach
Radar (PAR). No single system currently available meets all of the DoD's
precision approach needs. In order to standardize on a single-system
solution, the DoD is developing a Joint Precision Approach and Landing
System (JPALS), a military-use differential GPS system designed to be
interoperable with the civilian-use LAAS. Interoperability of civil and
military landing systems is the primarily benefit. A JPALS transmitter
is designed to broadcast a signal meeting the requirements of civil LAAS
avionics, and a JPALS receiver is designed to use the LAAS broadcast
signal.

### Methodology

1.  Identify airports within the 121 studied airports that have a
    military presence that comprises greater than ten percent of total
    airport operations.

2.  Calculate the taxpayer dollars saved through avoiding redundant
    civilian and military systems.

    a.  It is assumed that a JPALS installation costs at least as much
        as a civil LGF, or \$1.2M.

    b.  Tax Payer Savings equals (\$1.2M/site) x (Number of studied
        airports that have a military presence that comprises greater
        than ten percent of total airport operations).

The twenty (20) airports shown in Table 20 are those within the 121
studied airports that have a military presence that comprises greater
than ten percent of total airport operations. In addition, the DoD has
operations at many NAS airports, including over 95% of the 121 airports
in this study.

[Table 20: Studied Airports with Considerable (\>10% of Total
Operations) Military Operations]{.smallcaps} [^124]

  ----------------- ----------------- ----------------- -----------------
  **Airport**       **% of Airport's  **Airport**       **% of Airport's
                    Traffic that are                    Traffic that are
                    Military                            Military
                    Operations**                        Operations**

  ABQ               15%               LIT               19%

  AFW               18%               MDT               13%

  BGR               34%               OKC               37%

  CHA               14%               PIE               12%

  CHS               38%               SHV               13%

  COS               24%               SYR               11%

  DLH               18%               TLH               19%

  HSV               32%               TUL               29%

  JAX               11%               TUS               12%

  LCK               41%               TYS               11%
  ----------------- ----------------- ----------------- -----------------

Note: Traffic estimates above may or may not be due to aircraft
stationed at that airfield.

### Tax Payer Dollars Saved

Because of the interoperability of LAAS and JPALS, taxpayers may be able
to forgo installing these two interoperable and compatible systems at
one location. At the 20 sites list above, this could potentially save
taxpayers at least **\$24M.**

## [Expansion of Air Commerce to Smaller Communities]{.smallcaps} 

The expansion of air service to smaller communities can be important for
economic development. Allowing reliable, precision approach to all
runways may increase economic development through increased air service
and passenger utilization at smaller community airports.

The expansion of air commerce into smaller communities may have multiple
beneficiaries. The FAA may benefit from lower LAAS purchase and
operations and maintenance costs, when compared to multiple ILS required
to serve multiple runway. Air Traffic and airlines may benefit from
having increased alternative airports, and reduced congestion to major
and larger community airports. Airlines may benefit from expansion of
their networks to new markets, potentially resulting in increased
revenue passenger miles. Residents of small communities may benefit from
having access to increased air service, and small communities may
benefit from the economic development that passengers and airlines
bring.

Many of the benefits of expansion of air service may be achievable with
RNAV capabilities through the use of GPS and/or WAAS, or achieved
through ILS Category I/II/III precision approach. In these cases, LAAS
may provide little or no benefit. However, in some terrain challenged
areas LAAS may be the best precision approach option.

Table 21 lists several example airports in small communities that may
have terrain constraints. This list is not meant to be exhaustive, but
to illustrate the types of airports in this category.

[Table 21: Small Community Airports With ILS Terrain
Challenges]{.smallcaps}

  ------------------- --------------------------- --------------------------------
  **Airport Code**    **Airport Name**            **2003 Scheduled Arrivals**

  [ASE]{.smallcaps}   Aspen, CO                   4,162

  [EGE]{.smallcaps}   Eagle County, CO            2,257

  [SIT]{.smallcaps}   Sitka, AK                   1,647

  [JNU]{.smallcaps}   Juneau, AK                  19,806

  [SUN]{.smallcaps}   Sun Valley, ID              4,333
  ------------------- --------------------------- --------------------------------

## [Increased Reliability of Air Service []{.mark}]{.smallcaps}

**Overview**

Studies have suggested that infrastructure changes that lead to
increased quality of air service (*e.g.*, reduced flight times,
increased reliability) may lead to increased passenger load
factor[^125]. By reducing delay and increasing all-weather reliability
of air service, LAAS may offer this benefit. Increased load factor will
increase revenue in the Airport Improvement Program (AIP) through the
Domestic Passenger Ticket Tax aviation component, and will also result
in increased revenue to the airlines. This analysis shows the 20 year
benefits for a one percent (1%) increase in load factor on one percent
(1%) of domestic and regional airline flights.

This quantification is for illustrative purposes only, and no claim is
made that LAAS, or any other precision approach system will lead to
these specific benefits. Rather, this shows the benefits that may be
obtained for every 1% increase in load factor, for every 1% domestic
major and regional operations, by improving the reliability of
all-weather flight operations.

The Airport and Airway Trust Fund, which was established by the Airport
and Airway Revenue Act of 1970, provides the revenues used to fund AIP
projects.  The Trust Fund concept guarantees a stable funding source
whereby users pay for the services they receive.  In 1997, Congress
enacted new taxes to fund the Trust Fund as shown in Table 22.

[Table 22: AIP Domestic Passenger Ticket Tax]{.smallcaps} [^126]

  ---------------------------- ------------------------------------------
  **Aviation Component**       **Computation Formulae**

  ***Domestic Passenger Ticket 9% from Oct. 1, 1997 through Sept. 30,
  Tax***                       1998

                               8% from Oct. 1, 1998 through Sept. 30,
                               1999

                               7.5% from Oct. 1, 1999
  ---------------------------- ------------------------------------------

**Methodology**

1.  Estimate average ticket price per flight segment; \$100.

2.  Estimate the average number of passengers per flight; 91 (average of
    B737)

3.  Assume 1% increase in load factor for 1% of airline operations due
    to improved reliability of air service.

4.  AIP Revenue is (avg. ticket price)x(domestic ticket tax)x(average
    number of passengers)x(% increase in load factor)x(% of airline
    operations increase load factor by 1%)x(total U.S. airline
    operations at the 121 studied airports).

5.  Airline Revenue is (avg. ticket price)x (average number of
    passengers)x(% increase in load factor)x(% of airline operations
    increase load factor by 1%)x(total U.S. airline operations at the
    121 studied airports).

6.  Calculate the 20 year benefit using 2004 TAF projections.

7.  Calculate the 2004 present value using a 7% discount rate.

**Results**

> As shown in Table 23, the estimated LAAS benefit assuming zero percent
> (0%) WAAS equipage is \$96M for each one percent (1%) increase in load
> factor on one percent (1%) of domestic major and regional carrier
> operations.

[Table 23: Discounted 20 year LAAS Benefits for Each 1% Increase in Load
Factor on Each 1% of Domestic]{.smallcaps} Major and Regional Airline
Operations

+----------------------+----------------+------------------+----------+
|                      | **Increased    | **Increased      | *        |
|                      | AIP Revenue**  | Airline          | *Total** |
|                      |                | Revenue**        |          |
+----------------------+----------------+------------------+----------+
| **LAAS Benefits**    | \$6,701,079    | \$89,347,725     | \$96     |
|                      |                |                  | ,048,805 |
| **(Assuming 0% WAAS  |                |                  |          |
| equipage)**          |                |                  |          |
+----------------------+----------------+------------------+----------+
| **LAAS Benefits**    | \$1,652,875    | \$20,478,277     | \$22     |
|                      |                |                  | ,131,151 |
| **(Assuming 100%     |                |                  |          |
| WAAS equipage)**     |                |                  |          |
+----------------------+----------------+------------------+----------+

# [Appendices]{.smallcaps}

## [Appendix A: Airports Included in This Study]{.smallcaps}

Airports were selected for this study through an objective process that
included the following selection criteria:

-   High traffic airports associated with likely LAAS users:

    -   Major passenger airlines (More than 20,000 operations over a
        three year period)

    -   Regional passenger airlines (Regional Airline Association -- Top
        50 airports)

    -   Cargo carriers

    -   Corporate operators (National Business Aviation Association --
        Top 10 airports)

-   LAAS Low Rate Initial Production (LRIP) sites

-   FAA Operational Evolution Plan (OEP) airports

-   Current Cat II/III ILS airports

-   Qualifier Cat II/III ILS airports

Based on these criteria 121 airports throughout the NAS were selected
for this study, as shown in the following table and map.

[Table A1: 121 Airports Names and Locations Included in
Study]{.smallcaps}

  ----- ---------------------------- ----- ------------------------- ----- -----------------------
  ABQ   ALBUQUERQUE INTL SUNPORT,    FAT   FRESNO YOSEMITE           OMA   EPPLEY AIRFIELD,
        NEW MEXICO                         INTERNATIONAL, CALIFORNIA       NEBRASKA

  ACK   NANTUCKET MEMORIAL,          FLL   FORT LAUDERDALE/HOLLYWOOD ONT   ONTARIO INTL,
        MASSACHUSETTS                      INTL, FLORIDA                   CALIFORNIA

  AFW   FORT WORTH ALLIANCE, TEXAS   FWA   FORT WAYNE INTERNATIONAL, ORD   CHICAGO O\'HARE INTL,
                                           INDIANA                         ILLINOIS

  ALB   ALBANY INTL, NEW YORK        FXE   FORT LAUDERDALE           ORF   NORFOLK INTL, VIRGINIA
                                           EXECUTIVE, FLORIDA              

  ANC   TED STEVENS ANCHORAGE INTL,  GEG   SPOKANE INTL, WASHINGTON  PBI   PALM BEACH INTL,
        ALASKA                                                             FLORIDA

  ATL   THE WILLIAM B HARTSFIELD     GRR   GERALD R. FORD            PDX   PORTLAND INTL, OREGON
        ATLANTA INTL, GEORGIA              INTERNATIONAL, MICHIGAN         

  AUS   AUSTIN-BERGSTROM INTL, TEXAS GSO   PIEDMONT TRIAD            PHL   PHILADELPHIA INTL,
                                           INTERNATIONAL, NORTH            PENNSYLVANIA
                                           CAROLINA                        

  AVL   ASHEVILLE REGIONAL, NORTH    GSP   GREENVILLE-SPARTANBURG    PHX   PHOENIX SKY HARBOR
        CAROLINA                           INTL, SOUTH CAROLINA            INTL, ARIZONA

  BDL   BRADLEY INTL, CONNECTICUT    HNL   HONOLULU INTL, HAWAII     PIE   ST
                                                                           PETERSBURG-CLEARWATER
                                                                           INTL, FLORIDA

  BFI   BOEING FIELD/KING COUNTY     HOU   WILLIAM P HOBBY, TEXAS    PIT   PITTSBURGH
        INTL, WASHINGTON                                                   INTERNATIONAL,
                                                                           PENNSYLVANIA

  BGR   BANGOR INTL, MAINE           HPN   WESTCHESTER COUNTY, NEW   PVD   THEODORE FRANCIS GREEN
                                           YORK                            STATE, RHODE ISLAND

  BHM   BIRMINGHAM INTL, ALABAMA     HSV   HUNTSVILLE INTL-CARL T    RDU   RALEIGH-DURHAM INTL,
                                           JONES FIELD, ALABAMA            NORTH CAROLINA

  BNA   NASHVILLE INTL, TENNESSEE    IAD   WASHINGTON DULLES         RFD   GREATER ROCKFORD,
                                           INTERNATIONAL, DIST. OF         ILLINOIS
                                           COLUMBIA                        

  BOI   BOISE AIR TERMINAL/GOWEN     IAH   GEORGE BUSH               RIC   RICHMOND INTERNATIONAL,
        FLD, IDAHO                         INTERCONTINENTAL                VIRGINIA
                                           ARPT/HOUSTON, TEXAS             

  BOS   GENERAL EDWARD LAWRENCE      ICT   WICHITA MID-CONTINENT,    RNO   RENO/TAHOE
        LOGAN INTL, MASSACHUSETTS          KANSAS                          INTERNATIONAL, NEVADA

  BUF   BUFFALO NIAGARA INTL, NEW    ILN   AIRBORNE AIRPARK, OHIO    ROC   GREATER ROCHESTER
        YORK                                                               INTERNATIONAL, NEW YORK

  BUR   BURBANK-GLENDALE-PASADENA,   IND   INDIANAPOLIS INTL,        RSW   SOUTHWEST FLORIDA INTL,
        CALIFORNIA                         INDIANA                         FLORIDA

  BWI   BALTIMORE-WASHINGTON INTL,   ISP   LONG ISLAND MAC ARTHUR,   SAN   SAN DIEGO
        MARYLAND                           NEW YORK                        INTL-LINDBERGH FLD,
                                                                           CALIFORNIA

  CAE   COLUMBIA METROPOLITAN, SOUTH JAN   JACKSON INTERNATIONAL,    SAT   SAN ANTONIO INTL, TEXAS
        CAROLINA                           MISSISSIPPI                     

  CHA   LOVELL FIELD, TENNESSEE      JAX   JACKSONVILLE INTL,        SDF   LOUISVILLE
                                           FLORIDA                         INTL-STANDIFORD FIELD,
                                                                           KENTUCKY

  CHS   CHARLESTON AFB/INTL, SOUTH   JFK   JOHN F KENNEDY INTL, NEW  SEA   SEATTLE-TACOMA INTL,
        CAROLINA                           YORK                            WASHINGTON

  CLE   CLEVELAND-HOPKINS INTL, OHIO JNU   JUNEAU INTL, ALASKA       SFB   ORLANDO SANFORD,
                                                                           FLORIDA

  CLT   CHARLOTTE/DOUGLAS INTL,      LAS   MC CARRAN INTL, NEVADA    SFO   SAN FRANCISCO
        NORTH CAROLINA                                                     INTERNATIONAL,
                                                                           CALIFORNIA

  CMH   PORT COLUMBUS INTL, OHIO     LAX   LOS ANGELES INTL,         SHV   SHREVEPORT REGIONAL,
                                           CALIFORNIA                      LOUISIANA

  COS   CITY OF COLORADO SPRINGS     LCK   RICKENBACKER              SJC   NORMAN Y. MINETA SAN
        MUNI, COLORADO                     INTERNATIONAL, OHIO             JOSE INTERNATIONAL,
                                                                           CALIFORNIA

  CVG   CINCINNATI/NORTHERN KENTUCKY LGA   LA GUARDIA, NEW YORK      SLC   SALT LAKE CITY INTL,
        INTERNATIONAL, KENTUCKY                                            UTAH

  DAB   DAYTONA BEACH INTL, FLORIDA  LGB   LONG BEACH /DAUGHERTY     SMF   SACRAMENTO
                                           FIELD/, CALIFORNIA              INTERNATIONAL,
                                                                           CALIFORNIA

  DAL   DALLAS LOVE FIELD, TEXAS     LIT   ADAMS FIELD, ARKANSAS     SNA   JOHN WAYNE
                                                                           AIRPORT-ORANGE COUNTY,
                                                                           CALIFORNIA

  DAY   JAMES M COX DAYTON INTL,     MCI   KANSAS CITY INTL,         STL   LAMBERT-ST LOUIS INTL,
        OHIO                               MISSOURI                        MISSOURI

  DCA   RONALD REAGAN WASHINGTON     MCO   ORLANDO INTL, FLORIDA     SWF   STEWART INT\'L, NEW
        NATIONAL, DIST. OF COLUMBIA                                        YORK

  DEN   DENVER INTL, COLORADO        MDT   HARRISBURG INTERNATIONAL, SYR   SYRACUSE HANCOCK INTL,
                                           PENNSYLVANIA                    NEW YORK

  DFW   DALLAS/FORT WORTH            MDW   CHICAGO MIDWAY, ILLINOIS  TEB   TETERBORO, NEW JERSEY
        INTERNATIONAL, TEXAS                                               

  DLH   DULUTH INTL, MINNESOTA       MEM   MEMPHIS INTL, TENNESSEE   TLH   TALLAHASSEE REGIONAL,
                                                                           FLORIDA

  DSM   DES MOINES INTL, IOWA        MHT   MANCHESTER, NEW HAMPSHIRE TPA   TAMPA INTL, FLORIDA

  DTW   DETROIT METROPOLITAN WAYNE   MIA   MIAMI INTL, FLORIDA       TRI   TRI-CITIES RGNL TN/VA,
        COUNTY, MICHIGAN                                                   TENNESSEE

  DVT   PHOENIX DEER VALLEY, ARIZONA MKE   GENERAL MITCHELL          TUL   TULSA INTL, OKLAHOMA
                                           INTERNATIONAL, WISCONSIN        

  ELP   EL PASO INTL, TEXAS          MMU   MORRISTOWN MUNI, NEW      TUS   TUCSON INTL, ARIZONA
                                           JERSEY                          

  EUG   MAHLON SWEET FIELD, OREGON   MSP   MINNEAPOLIS-ST PAUL       TYS   MC GHEE TYSON,
                                           INTL/WOLD-CHAMBERLAIN/,         TENNESSEE
                                           MINNESOTA                       

  EWR   NEWARK INTL, NEW JERSEY      MSY   LOUIS ARMSTRONG NEW       VNY   VAN NUYS, CALIFORNIA
                                           ORLEANS INTL, LOUISIANA         

  EYW   KEY WEST INTL, FLORIDA       OAK   METROPOLITAN OAKLAND            
                                           INTL, CALIFORNIA                

  FAI   FAIRBANKS INTL, ALASKA       OKC   WILL ROGERS WORLD,              
                                           OKLAHOMA                        
  ----- ---------------------------- ----- ------------------------- ----- -----------------------

###  Map of Airports Included in this Study

# ![](media/image12.png){width="1.8958333333333333in" height="1.44375in"}

# 

# 

# 

# ![](media/image13.png){width="6.045138888888889in" height="4.411111111111111in"}

# 

# 

# 

# 

# 

# 

![](media/image14.png){width="1.8847222222222222in" height="1.41875in"}

## [Appendix B: Order of Installation of LAAS Ground Facilities]{.smallcaps}

The order in which LAAS ground facilities are installed is an important
factor in the estimation of LAAS benefits. For this study, airport
installations are assumed to take place at a pace of 24 per year, and in
order of greatest to least benefit; that is, the first installations
will be at airports with the highest benefit. A rank ordered list of
airports is constructed by calculating the full 20-year discounted
benefit, assuming LAAS is installed at all airports at IOC[^127] (June
2009 for Cat I; June 2013 for Cat II/III). A separate rank ordering is
obtained depending on whether user equipage of WAAS is assumed to be 0%
or 100%, since this assumption changes the benefits at many airports,
and thus, potentially changes the order among airports. The following
table shows the assumed date of installation at each of the 121 airports
studied (LAAS LRIP sites, which are the first to be installed with Cat I
LAAS are highlighted in bold).

[Table B1: Order of Installation of LAAS Ground Facilities (Format
MM-YY)]{.smallcaps}

  --------- -------- -------- -------- -------- --------- -------- -------- -------- --------
  Airport   0% WAAS           100%              Airport   0% WAAS           100%     
                              WAAS                                          WAAS     

            Cat I    Cat      Cat I    Cat                Cat I    Cat      Cat I    Cat
                     II/III            II/III                      II/III            II/III

  ABQ       Dec-10   Nov-16   Sep-10   Nov-16   JFK       Nov-11   Nov-14   Oct-11   Nov-14

  ACK                Mar-14            Mar-14   **JNU**   Jun-09   Oct-17   Jun-09   Oct-17

  AFW                Mar-18            Mar-18   LAS       Sep-11   Jun-18   Aug-11   Jun-18

  ALB       May-10   Aug-14            Aug-14   LAX                May-14            May-14

  ANC       Mar-10   Feb-15   Oct-09   Feb-15   LCK                Feb-18            Feb-18

  ATL       Oct-10   Sep-13   Dec-09   Sep-13   LGA       Dec-09   Aug-13            Aug-13

  AUS                Aug-15            Aug-15   LGB       Apr-10   Sep-15   Nov-09   Sep-15

  AVL                Dec-16            Dec-16   LIT       Jan-12   Jun-17   Mar-11   Jun-17

  BDL       Jan-10   Jun-15            Jun-15   MCI                Apr-15            Apr-15

  BFI                Jan-17            Jan-17   MCO       Apr-10   Feb-15   Jan-10   Feb-15

  BGR                Nov-17            Nov-17   MDT                Jul-16            Jul-16

  BHM       Jan-10   Mar-17   Apr-10   Mar-17   MDW       Mar-12   Jul-13   Jun-11   Jul-13

  BNA       Jan-11   Dec-16            Dec-16   **MEM**   Jul-09   May-14   Jul-09   May-14

  BOI                Feb-16            Feb-16   MHT       Sep-10   Jun-14   Apr-10   Jun-14

  BOS                Nov-13            Nov-13   MIA       Aug-10   Nov-15   Mar-10   Nov-15

  BUF       Aug-11   Dec-14   Sep-11   Dec-14   MKE       Dec-09   Oct-14   Dec-09   Oct-14

  BUR       Sep-09   Apr-17            Apr-17   MMU       Nov-11   Sep-17   Nov-10   Sep-17

  BWI                Sep-14            Sep-14   MSP                Feb-14            Feb-14

  CAE       Apr-11   Jan-17   May-11   Jan-17   MSY       Jun-10   Jan-16   Feb-10   Jan-16

  CHA       Jun-12   Nov-17   Jul-11   Nov-17   OAK       Mar-12   Oct-16            Oct-16

  CHS       Feb-11   May-16   Jun-10   May-16   OKC       Sep-10   Jul-15   Mar-10   Jul-15

  CLE       Oct-09   Jan-15   Oct-09   Jan-15   OMA                Nov-16            Nov-16

  CLT                Oct-13            Oct-13   ONT                Dec-17            Dec-17

  CMH                May-15            May-15   **ORD**   Jul-09   Jun-13   Jul-09   Jun-13

  COS       Nov-10   Aug-14   Dec-10   Aug-14   ORF       May-12   Sep-14   Apr-11   Sep-14

  CVG       Mar-10   Jan-14   Sep-09   Jan-14   PBI       Mar-11   Feb-17   Dec-10   Feb-17

  DAB                Apr-17            Apr-17   PDX       May-12   Oct-15   Jan-12   Oct-15

  DAL                Mar-15            Mar-15   PHL                Jul-14            Jul-14

  DAY       Dec-10   Aug-16   Aug-10   Aug-16   **PHX**   Aug-09   Aug-15   Aug-09   Aug-15

  DCA       Sep-09   Jul-15   Oct-11   Jul-15   PIE       Jan-12   Jul-17   Sep-11   Jul-17

  DEN                Aug-13            Aug-13   PIT                Mar-14            Mar-14

  DFW       Nov-09   Jun-13   Sep-09   Jun-13   PVD       Jan-11   Oct-14   Sep-10   Oct-14

  DLH       Jun-12   Aug-16   Nov-11   Aug-16   RDU       Apr-12   Jan-14   Jul-11   Jan-14

  DSM                Sep-16            Sep-16   RFD       Apr-11   Oct-16   Feb-11   Oct-16

  DTW       Nov-09   Sep-13   Jan-11   Sep-13   RIC       May-10   Sep-15   Feb-10   Sep-15

  DVT       Aug-12                              RNO       Aug-10   Aug-17   Jun-10   Aug-17

  ELP                Mar-18            Mar-18   ROC       Mar-11   May-16   Jan-10   May-16

  EUG       May-11   Jun-15   Jul-10   Jun-15   RSW                Jun-14            Jun-14

  EWR                Dec-13            Dec-13   SAN       Oct-09   Jun-17            Jun-17

  EYW       Feb-12   Apr-18   May-11   Apr-18   SAT                Jul-14            Jul-14

  FAI       Dec-11   Oct-17            Oct-17   SDF                Sep-17            Sep-17

  FAT                Jan-18            Jan-18   **SEA**   Aug-09   Feb-14   Aug-09   Feb-14

  FLL       Jul-11   Mar-16   Aug-10   Mar-16   SFB       Aug-12   Feb-18   Dec-11   Feb-18

  FWA       Jul-10   Feb-17            Feb-17   SFO                Apr-16            Apr-16

  FXE       Jul-12   May-18   Nov-11   May-18   SHV       May-11   Jul-17   Feb-11   Jul-17

  GEG       Jul-10   May-15   May-10   May-15   SJC       Feb-10   Nov-14   Nov-09   Nov-14

  GRR       Jun-11   Mar-15            Mar-15   SLC       Oct-10   Apr-15   May-10   Apr-15

  GSO                Apr-14            Apr-14   SMF                Oct-15            Oct-15

  GSP                Mar-17            Mar-17   SNA       Feb-12   Jan-15   Dec-11   Jan-15

  HNL       Jun-10   Apr-18   Jun-11   Apr-18   STL                Dec-14            Dec-14

  HOU       Sep-11   Oct-13   Apr-11   Oct-13   SWF       Oct-11   Jan-18   Aug-11   Jan-18

  HPN       Dec-11   Dec-13   Jul-10   Dec-13   SYR       Jul-11   Sep-16   Nov-10   Sep-16

  HSV                May-17            May-17   TEB       Feb-10   Feb-16   Mar-11   Feb-16

  IAD                Apr-14            Apr-14   TLH                Nov-15            Nov-15

  **IAH**   Jun-09   Nov-13   Jun-09   Nov-13   TPA       Nov-10   Mar-16   Oct-10   Mar-16

  ICT       Feb-11   Apr-16   Jan-11   Apr-16   TRI       Apr-12   Aug-17   Feb-12   Aug-17

  ILN                Jan-16            Jan-16   TUL       Oct-11   Jun-16   Oct-10   Jun-16

  IND                Dec-15            Dec-15   TUS       Jul-12   May-18            May-18

  ISP       Aug-11   Dec-15            Dec-15   TYS                Jul-16            Jul-16

  JAN                Dec-17            Dec-17   VNY       Jun-11   May-17   Jan-12   May-17

  JAX                Jun-16            Jun-16                                        
  --------- -------- -------- -------- -------- --------- -------- -------- -------- --------

##  [Appendix C: Derivation of Disruption Costs]{.smallcaps} 

Disruptions occur when there is an interruption to a planned or optimum
flight schedule, and are categorized as delays, cancellations, and
diversions. These disruptions have costs for both aircraft operators
(Direct Operating Cost; DOC) and passengers (Passenger Time Savings;
PTS). Both DOC and PTS costs are assessed and reported by user type:
Major passenger airlines, Regional airlines, Cargo carriers, Corporate
jet operators, and General Aviation (GA).

### Direct Operating Costs

A weighted average delay cost was computed for direct operating cost of
Major, Regional, Cargo, Corporate, and other GA assuming two-thirds of
delays are ground delays and one-third occur in the air. FAA APO data
sources were used to obtain the recommended values.[^128] Corporate jet
DOC costs were provided by the FAA's Office of Investment Analysis and
Operations Research (ASD) including cost of crew, fuel and maintenance.

Cancellation costs were configured assuming a typical mid size aircraft
for Majors (*i.e.*, MD80) and for Regional carriers (*i.e.*, F100).
Based on inputs from airline representatives, it was assumed that Cargo
operators do not cancel flights, so no cost was needed for this user
group. It was also assumed that since general aviation flights are not
scheduled, corporate jet operators and other GA operators do not incur
cancellations.

Diversion costs were derived from the Issue Paper analyzing "Schedule
Disruptions" from the FAA's Office of Aviation Policy and Plans (APO).
The estimated average hourly costs of the aircraft for diverted flights
were obtained for Majors and Regional carriers. It was further assumed
that an average diversion time is approximately two hours, and the per
hour costs were multiplied for total diversion cost per flight. The
draft APO report used in this study (version 2) can be found at
http://apo.faa.gov/arcc/Research.htm for more information.

The average unit costs of disruptions used for DOC values are summarized
in Table C1.

[Table C1: Average DOC Disruption Costs (2004 dollars)]{.smallcaps}

  -------------------- ---------- ---------- ---------- ----------- ----------
  Type of Disruption   Majors     Regional   Cargo      Corporate   General
                                                        (NBAA)      Aviation

  Delay (per minute)\* \$35.08    \$21.43    \$69.95    \$20.80     \$6.97

  Cancellation         \$6,820    \$2,132    \$0        \$0         \$0

  Diversion\*\*        \$8,047    \$4,412    \$9,845    \$4,231     \$2,202
  -------------------- ---------- ---------- ---------- ----------- ----------

\* Weighted Average direct operating cost

\*\*Assume Average duration of a diversion is 2 hours

### Passenger Time Savings

To monetize passenger benefits, the following PTS economic values were
used, listed in Table C2 by user type.

[Table C2: Breakdown of PTS]{.smallcaps}[^129]
[(dollars/hr)]{.smallcaps}

![](media/image15.png){width="5.588888888888889in"
height="2.5618055555555554in"}

The Air Carrier's All Purposes recommended values in Table C2 were used
for Major and Regional users. Air Carrier Business category was used for
all corporate jet travelers. General Aviation All Purposes was applied
to all GA operations.

Aircraft capacity and utilization factors identified in Table C3 were
applied to Passenger Time Savings to obtain total PTS per flight.[^130]

[Table C3: Aircraft Capacity and Utilization Factors]{.smallcaps}

+--------------------------+---------------------+--------------------+
| #### Factor              | **Aircraft Seating  | **Passenger Load   |
|                          | Capacity**          | Factor**           |
| #### User Type           |                     |                    |
+--------------------------+---------------------+--------------------+
| Major Carrier            | 157                 | 72%                |
+--------------------------+---------------------+--------------------+
| Regional                 | 100                 | 62%                |
+--------------------------+---------------------+--------------------+
| Corporate                | 10                  | 50%                |
+--------------------------+---------------------+--------------------+
| General Aviation         | 6                   | 60%                |
+--------------------------+---------------------+--------------------+

### Results Summary:

A weighted average cost of a disruption was calculated using the
observed occurrence of the three categories of disruption types.
Observed disruptions for major and regional airlines were analyzed based
on scheduled arrivals from Airline Service Quality Performance (ASQP)
database. The proportion of each disruption type was then used to
determine cargo, corporate, and GA disruptions.

An average duration of delay, used to compute the weighted average DOC
and PTS, was determined based on ASQP gate arrival delay for CAT
I/II/III conditions. Weather delays greater than 15 minutes were
extracted for the point estimate, which resulted in an average delay of
45 minutes for Majors and Cargo carriers, and 37 minutes for Regional,
Corporate, and GA. Furthermore, since ASQP gate arrival delay includes
the ripple effect, the average durations were divided by the ripple
effect factor of 1.8.

Table C4 shows the average length of delay values used to compute
weighted average disruption costs.

[Table C4: Average Duration of Delay]{.smallcaps}

+-----------------------------------------+----------------------------+
| #### User Type                          | **Mean Delay**             |
+-----------------------------------------+----------------------------+
| Major Carrier                           | 25                         |
+-----------------------------------------+----------------------------+
| Regional                                | 21                         |
+-----------------------------------------+----------------------------+
| Cargo                                   | 25                         |
+-----------------------------------------+----------------------------+
| Corporate                               | 21                         |
+-----------------------------------------+----------------------------+
| General Aviation                        | 21                         |
+-----------------------------------------+----------------------------+

Table C5 provides weighted average disruption DOC and PTS costs by user
type. Costs were computed using FAA-APO recommended values.

[Table C5: Average Disruption Costs Per Incident by Carrier]{.smallcaps}

+---------------------+--------------+-------------+------------------+
| #### User Type      | **Direct     | **Passenger | **Total Cost**   |
|                     | Operating    | Time        |                  |
|                     | Cost**       | Savings**   |                  |
+---------------------+--------------+-------------+------------------+
| Major Carrier       | \$1,983      | \$2,545     | \$4,528          |
+---------------------+--------------+-------------+------------------+
| Regional            | \$805        | \$1,330     | \$2,135          |
+---------------------+--------------+-------------+------------------+
| Cargo               | \$1,903      | \$0         | \$1,903          |
+---------------------+--------------+-------------+------------------+
| Corporate           | \$502        | \$89        | \$591            |
+---------------------+--------------+-------------+------------------+
| General Aviation    | \$182        | \$53        | \$235            |
+---------------------+--------------+-------------+------------------+

### Data Sources:

1.  The DOT's Airline Service Quality Performance database was used for
    Scheduled Arrivals and Disruption data from January 1998 to
    July 2003. Outliers, such as the time period after September 11 and
    time periods associated with airline strikes were removed from the
    data.

2.  FAA APO data sources were used to obtain the recommended values.
    Updated Departmental Guidance to FAA Office of Aviation Policy and
    Plan, \"Economic Values for Evaluation of FAA Investment and
    Regulatory Programs\", FAA-APO-98-8:

    a.  Section 1- Treatment of Values of Passenger Time in Economic
        Analysis (U.S. Department of Transportation, FAA-APO-03-1, March
        2003)

    b.  Section 3- Aircraft Utilization and Capacity Factors (2002
        Passenger Air Carrier Capacity and Utilization Factors),Chapter
        Draft

    c.  Section 4- Majors and Regional direct operating cost (2002
        Aircraft Operating Costs), Chapter Draft

3.  Inflation Factors Source: Dept. of Commerce, Bureau of Economic
    Analysis, GDP Price Indexes. OMB\'s GDP Price Index Guidelines were
    applied for projection to 2004 dollars.

## [Appendix D: Sensitivity Analyses]{.smallcaps}

There is considerable uncertainty surrounding the proper values of
several input parameters used in this benefits estimate. A sensitivity
analysis was conducted to determine the impact of this uncertainty on
the estimated benefits. This update to the LAAS efficiency benefits
includes sensitivity analysis on five parameters:

-   the cost of a disruption,

-   the rate at which LAAS avionics equipage occurs,

-   the minimum avionics equipage level required for benefit accrual,

-   the downstream effect factor, and

-   the average duration of delay.

These parameters were selected due to both the uncertainty of their
values, and their central importance in building the benefits estimates.
Based on research of historical precedents, published estimates, and
interviews with airline and other industry stakeholders, there is a wide
range of opinion regarding the correct value to assign to the cost of a
flight disruption, the likely pace at which users will install new
technology avionics, the fraction of users that must be equipped before
concerns about mixed-equipage operations are overcome, the correct
downstream effect factor and the average duration of delay. From this
research, we have developed a range of expected values for each of these
parameters, including a central, or most likely value, as well as upper
and lower bounds. In each case, the central value was first developed
from research, and then validated with airline representatives, with the
upper and lower bounds also emerging from these stakeholder discussions.

The risk modeling approach selected for this analysis varies the
parameter values between these upper and lower bounds in order to
explore the extent to which the uncertainty in the parameter values may
affect the benefits. This risk analysis was conducted using \@RISK, a
commercial software tool, which employs Monte Carlo simulation[^131] to
explore a large number of possible values of the uncertain parameters.

The sensitivity analysis was conducted in four steps. The first analysis
varied parameter values of both direct operating costs and passenger
time costs for the five user groups (major airlines, regional airlines,
cargo carriers, corporate jets, and general aviation). A triangular
distribution was applied, representing low, most likely and high values
of these costs. The tables below show the cost value ranges applied:

[Table D1: Direct Operating Costs]{.smallcaps} Ranges

+----------------+---------------+-----------------+------------------+
| #### User Type | **Low         | **Best or Most  | **High           |
|                | Estimate**    | Likely          | Estimate**       |
|                |               | Estimate**      |                  |
+----------------+---------------+-----------------+------------------+
| Major Carrier  | \$782         | \$1,983         | \$4,269          |
+----------------+---------------+-----------------+------------------+
| Regional       | \$700         | \$805           | \$1,035          |
+----------------+---------------+-----------------+------------------+
| Cargo          | \$937         | \$1,903         | \$3,400          |
+----------------+---------------+-----------------+------------------+
| Corporate      | \$297         | \$502           | \$767            |
+----------------+---------------+-----------------+------------------+
| General        | \$145         | \$182           | \$237            |
| Aviation       |               |                 |                  |
+----------------+---------------+-----------------+------------------+

[Table D2: Ground and Airborne Delay Unit Costs]{.smallcaps} Ranges

+-----------------+----------------+----------------+-----------------+
| #### User Type  | **Low          | **Best         | **High          |
|                 | Estimate**     | Estimate**     | Estimate**      |
+-----------------+----------------+----------------+-----------------+
|                 | Ground /       | Ground /       | Ground /        |
|                 | Airborne       | Airborne       | Airborne        |
+-----------------+----------------+----------------+-----------------+
| Major Carrier   | \$27.63 /      | \$30.70 /      | \$33.77 /       |
|                 | \$39.47        | \$43.85        | \$48.24         |
+-----------------+----------------+----------------+-----------------+
| Regional        | \$16.88 /      | \$18.75 /      | \$20.63 /       |
|                 | \$24.11        | \$26.79        | \$29.47         |
+-----------------+----------------+----------------+-----------------+
| Cargo           | \$55.09 /      | \$61.21 /      | \$67.33 /       |
|                 | \$78.70        | \$87.44        | \$96.18         |
+-----------------+----------------+----------------+-----------------+
| Corporate       | \$14.04 /      | \$15.60 /      | \$17.16 /       |
|                 | \$28.08        | \$31.20        | \$34.32         |
+-----------------+----------------+----------------+-----------------+
| General         | \$5.49 /       | \$6.10 /       | \$6.71 / \$9.58 |
| Aviation        | \$7.84         | \$8.71         |                 |
+-----------------+----------------+----------------+-----------------+

[Table D3: Passenger Time Savings Costs]{.smallcaps} Ranges

+----------------+----------------+-----------------+-----------------+
| #### User Type | **Low          | **Best          | **High          |
|                | Estimate**     | Estimate**      | Estimate**      |
+----------------+----------------+-----------------+-----------------+
| Major Carrier  | \$1,547        | \$2,545         | \$4,374         |
+----------------+----------------+-----------------+-----------------+
| Regional       | \$625          | \$1,330         | \$2,569         |
+----------------+----------------+-----------------+-----------------+
| Cargo          | \$0            | \$0             | \$0             |
+----------------+----------------+-----------------+-----------------+
| Corporate      | \$17           | \$89            | \$234           |
+----------------+----------------+-----------------+-----------------+
| General        | \$26           | \$53            | \$98            |
| Aviation       |                |                 |                 |
+----------------+----------------+-----------------+-----------------+

In the second analysis, another distribution was applied based on low,
medium, and high values of the time to equip and the minimum required
equipage. These values are consistent with recommendations received
through interviews with airline and air traffic control representatives:

-   5 years to equip with 0% critical mass,

-   6 years for fleet to equip with 80% critical mass and

-   8 years equipage rate with 100% critical mass, respectively.

For the third analysis, a downstream effect range with low, medium, and
high was applied to the overall analysis and the departure delay
analysis. Table D4 shows the downstream effect factors that were used
and the bounds placed to conduct the sensitivity analysis. These factors
were received from SME inputs and additional research. A more detailed
discussion of the downstream effect factors can be found in Appendix N.

[Table D4: Downstream Effect Ranges]{.smallcaps}

+----------------+----------------+-----------------+-----------------+
| #### User Type | **Low          | **Best          | **High          |
|                | Estimate**     | Estimate**      | Estimate**      |
+----------------+----------------+-----------------+-----------------+
| All Analysis   | 1.0            | 1.8             | 2.6             |
+----------------+----------------+-----------------+-----------------+
| Departure      | 1.0            | 3.7             | 7.0             |
| Delay Analysis |                |                 |                 |
+----------------+----------------+-----------------+-----------------+

Finally the fourth analysis, varied the average duration of delay.
Therefore weather delays greater than 0, 15, and 30 minutes were
extracted for low, medium and high values. For Majors and Cargo
operators, delays greater then 0 resulted in average of 24 minutes,
greater then 15 resulted in 45 minutes and above 30 resulted in an
average of 73 minutes. For remaining regional, corporate and general
aviation aircrafts and average of 37 minutes was used. Furthermore, to
exclude the ripple effect, these values were divided by the 1.8 factor.
Table D5 shows the average duration of delay used for the low, medium
and high ranges.

[Table D5: Average Duration of Delay]{.smallcaps} Ranges

+----------------+----------------+-----------------+-----------------+
| #### User Type | **Low          | **Best          | **High          |
|                | Estimate**     | Estimate**      | Estimate**      |
+----------------+----------------+-----------------+-----------------+
| Majors         | 13             | 25              | 41              |
+----------------+----------------+-----------------+-----------------+
| Regional       | 21             | 21              | 21              |
+----------------+----------------+-----------------+-----------------+
| Cargo          | 13             | 25              | 41              |
+----------------+----------------+-----------------+-----------------+
| Corporate      | 21             | 21              | 21              |
+----------------+----------------+-----------------+-----------------+
| General        | 21             | 21              | 21              |
| Aviation       |                |                 |                 |
+----------------+----------------+-----------------+-----------------+

Conducting the sensitivity analysis using these bounds produces
risk-adjusted benefits for both direct operating cost and passenger time
savings, for the two WAAS user equipage scenarios. Figures D1 through D4
show the range of estimated LAAS benefits, highlighting the 5^th^ and
95^th^ percentiles. Figures D1 and D2 show these results for direct
operating costs and the 0% and 100% WAAS user equipage scenarios,
respectively. Figures D3 and D4 show these results for passenger time
savings and the 0% and 100% WAAS user equipage scenarios, respectively.

![](media/image16.wmf){width="4.625in" height="2.5in"}

Figure D1: Sensitivity Analysis: LAAS Direct Operating Cost Benefits
(assuming 0% WAAS equipage)

![](media/image17.wmf){width="4.625in" height="2.5in"}

Figure D2: Sensitivity Analysis: LAAS Direct Operating Cost Benefits
(assuming 100% WAAS equipage)

![](media/image18.wmf){width="4.625in" height="2.5680555555555555in"}

Figure D3: Sensitivity Analysis: LAAS Passenger Time Savings (assuming
0% WAAS equipage)

![](media/image17.wmf){width="4.625in" height="2.5in"}

Figure D4: Sensitivity Analysis: LAAS Passenger Time Savings (assuming
100% WAAS equipage)

Another output of the sensitivity analysis is an estimate of the
relative influence that the uncertain parameters have on the benefits.
In this case, the disruption cost parameter was shown to have over 50%
more influence than the time to equip, critical mass and downstream
effect parameters for the case of 0% WAAS equipage by users. In the case
of 100% WAAS equipage by users, the disruption cost and downstream
effect parameters were more influential than time to equip or critical
mass.

## [Appendix E: Derivation of the Single Airport Delay Model]{.smallcaps}

The Single Airport Delay Model is a deterministic model that can be used
to estimate delays at a single airport when demand exceeds capacity.
Since the model is deterministic, it does not take into account all of
the delays that may occur due to the randomness of operations at a
capacity constrained resource. Nevertheless, it offers a very reasonable
approximation to those delays.

### Basic Methodology and Illustrative Example

The model is based on a methodology described on pp. 339-343 of Robert
Horonjeff's and Francis McKelvey's "Planning and Design of Airports"
(4^th^ edition, 1994). The idea behind the model is fairly
straightforward. Any demand that cannot be satisfied by the available
capacity during a particular period rolls over into the next period and
contributes to delay. If the capacity during that period is sufficient
to handle the rollover demand plus the new demand arriving in that
period, there is no additional delay. However, if the demand exceeds the
capacity, a rollover into the next period occurs once again and the
delay accumulates. The spreadsheet model calculates the average delay
and a number of other metrics that summarize the performance of the
airport.

To understand how the model calculates delay, we use a simple example.
Figure E1 illustrates the overall problem. A given airport has
insufficient capacity to handle the demand. This demand can be in the
form of arrivals, departures, or both, and the capacity can be for a
single runway or multiple runways at the airport. The unit of time is a
quarter hour, but can just as well be any other value. Note in this
example that in the second quarter hour, the demand of 5 flights exceeds
the capacity of 4 flights per 15 minute period.

![](media/image19.wmf)

Figure E1. Illustrative Example of Demand and Capacity versus Time at an
Airport

Figure E2 shows another way of representing this same data. In this
graph, the demand and capacity are depicted as cumulative functions over
the specified time period. Note that the cumulative capacity curve
begins at the point in time when the demand rate starts to exceed the
service rate or capacity (end of the first time period). For any point
in time after that on the horizontal axis (until the two curves
intersect once again), the vertical distance between the two curves
represents the total queue at that point in time. Similarly, for any
flight on the vertical axis, the horizontal distance between the two
curves corresponds to the total delay experienced by that flight. The
area between the two curves is the total delay for all the flights in
this five quarter hour period.

![](media/image20.wmf)

[Figure E2. Cumulative Demand and Capacity Versus Time]{.smallcaps}

In order to simplify Figure E2, we compute the difference between the
cumulative demand and cumulative capacity and plot the result as a
function of time over the period of interest when the demand exceeds the
capacity. This effectively transforms Figure E2 into another graph (see
Figure E3) with the y-value representing the total queue at any point in
time. Note that in addition to obtaining the queue length, we can also
derive a number of other performance measurements from this graph. For
example, the maximum queue length can be easily seen to be 3.

![](media/image21.wmf)

[Figure E3. Difference Between Cumulative Demand and Cumulative Capacity
as a Function of Time]{.smallcaps}

Service time is the reciprocal of the capacity. For this particular
example, the capacity is 16 aircraft/60 minutes, which gives a service
time of 3.75 minutes per aircraft. Therefore the value for the longest
delayed aircraft can be obtained by multiplying the maximum queue length
by 3.75 minutes, thus obtaining 3 x 3.75 minutes = 11.25 minutes. The
delay for all aircraft during any 15 minute period can be derived by
calculating the area of the curve for that 15 minute period. This
amounts to calculating the area of one of the triangles or trapezoids
labeled A, B, C, or D. For example, the delay during the first 15 minute
period is simply the area of triangle A - ½ x base x height or ½ x 15
minutes x 1 = 7.5 minutes. Note that the calculation of the area of D is
a little more complex since the function does not intersect the x-axis
at a convenient break point (multiple of the quarter hour time
interval). Therefore, it is necessary to determine the exact point of
intersection before the calculation can be performed.

Once the areas under the curve are determined for each quarter hour
period, the total delay for all aircraft during the entire period can be
obtained by summing the areas of all these triangles and trapezoids. In
this example, this area turns out to be 85 minutes. The average delay
per aircraft is then simply the total delay divided by the number of
aircraft or 85 minutes/16 aircraft = 5.3 minutes/aircraft.

### Inputs and Outputs in the Model 

### Model Input: Estimated Total Traffic 

The total traffic demand at an airport, a key input to the Single
Airport Delay Model, is estimated for each fifteen minute time period
for a typical day by using the scheduled volume and factoring in an
estimate of unscheduled traffic. We build up total traffic from three
elements; 1) scheduled, 2) unscheduled IFR, and 3) VFR traffic. To
address these three elements, three data sources from FAA-APO were used
for this analysis: Flight Schedule Data System (FSDS), Enhanced Traffic
Management System Counts (ETMSC), and Operations Network (OPSNET).

Scheduled volume was obtained from the FSDS database, using April 30,
2003 as a representative traffic volume day. This date was selected
because the arrival count for that date had the median volume,
nationwide, of the 2003 calendar year. Scheduled traffic is allotted to
15 minute periods throughout the day. To add unscheduled volume, ETMSC
data, which include both scheduled and unscheduled IFR traffic, was
obtained. We selected data for four Wednesdays within the same month,
April 9, 16, 23 and 30, 2003 to obtain a representative sampling of the
variability of this unscheduled traffic. An average ETMSC count of
arrivals and departures for these four days was calculated and the
number of flights above and beyond the scheduled traffic was then added
to the original FSDS-based daily volume. These flights were added
randomly to 15 minute periods over the 24 hours of the day. VFR traffic
was added through a similar process. Flight counts were obtained from
OPSNET, which includes both IFR and VFR flights. OPSNET flight counts
above and beyond the average ETMSC traffic represent an estimate of VFR
traffic, and were added to the scheduled and unscheduled traffic. Since
these VFR flights typically occur during daylight hours, this volume was
added randomly between 6am and 10pm to complete our total traffic
estimate.

#### Example: 

To illustrate the method of building the total traffic, the following
chart shows simulated numbers of arrivals reported by each database, for
an imaginary example airport, ABC, on April 30th, 2003.

  ----------- ---------------- -------------------- ---------------------
  Airport     FSDS Arrivals    ETMSC Arrivals       OPSNET Arrivals

  ABC         200              224                  240
  ----------- ---------------- -------------------- ---------------------

The 200 scheduled FSDS arrivals are allotted to their proper
quarter-hour periods. ETMSC reports 24 additional arrivals beyond those
in FSDS. We use a random number generator to assign these 24 flights to
quarter-hour time slots, adding these to the FSDS arrivals already in
those quarter-hours. NOTE: The random number generator allows for
replacement[^132], so any quarter-hour throughout the day can have any
number of these 24 flights added to it.

The random assignment process is repeated for the additional 16 OPSNET
arrivals above and beyond those recorded in the ETMSC database. These
sixteen flights will be added at random to the new volume calculated
from the FSDS + ETMSC data. The end result is an estimate of the total
traffic encountered at an airport, and it is used as an input to IBM's
Single Airport Delay Model to simulate the actual flights that arrive
and depart at each airport on that day.

The chart below illustrates how these arrivals might be assigned to
quarter-hour periods to build a total number of arrivals for each
period. Only part of a complete 24 hour day is shown for this example.

![](media/image22.wmf){width="3.520138888888889in"
height="4.999305555555556in"}

## 

Continuing the example from the previous sections, Table E1 shows the
values derived by the model for this illustrative example, including all
of the critical system performance parameters.

[Table E1. Single Airport Delay Model Inputs and Results for
Illustrative Example]{.smallcaps}

  ----------------- ---------- ------------ ------- -------------- ------------------ --------------- ----------
  **Quarter Hour**  **Demand   **Capacity   **D -   **\# of        **Delays/Quarter   **Dem\>Cap?**   **A/C in
                    (D)**      (C)**        C**     Aircraft in    Hour**                             Queue?**
                                                    Queue**                                           

  0:15              1          4            -3      0                                 0               0

  0:30              5          4            1       1              7.5                1               1

  0:45              6          4            2       3              30.0               1               1

  1:00              3          4            -1      2              37.5               0               1

  1:15              1          4            -3      0              10.0               0               0

                    16                                                                                

                                                                                                      

  Total delay =                             85.0    minutes        or                 1.4             hours

  Average delay per                         5.3     min/aircraft                                       
  aircraft =                                                                                          

  Largest number of                         3       aircraft                                           
  aircraft delayed                                                                                    
  =                                                                                                   

  Delay time for                            11.3    minutes                                            
  longest-delayed                                                                                     
  aircraft =                                                                                          

  \# of quarter                             2                      or                 40%             of the
  hours when                                                                                          time
  demand\>cap =                                                                                       

  \# of quarter                             3                      or                 60%             of the
  hours when ac in                                                                                    time
  queue =                                                                                             
  ----------------- ---------- ------------ ------- -------------- ------------------ --------------- ----------

The inputs to the model are the demand and the capacity. Demand at each
airport was estimated as described above, using the scheduled volume and
factoring in an estimate of unscheduled traffic. Airport capacity data
was provided by FAA ASD-430.

The model simply calculates the difference between the demand and
capacity during each period. The "#of Aircraft in Queue" column contains
the queue lengths (shown as y-axis values (Aircraft In Queue) in Figure
E3). They are obtained by calculating the difference between the overall
demand (flights left over from the previous period plus those arriving
in this period) and the capacity. Negative values are set equal to zero
since we cannot have a negative queue length.

The "Delays/Quarter Hour" are obtained by calculating the areas of the
triangles and trapezoids as described earlier (in reference to Figure
E3). The last two columns are simply set to 1 when the fourth and fifth
columns, respectively, are greater than 0.

The highlighted metrics at the bottom of the table summarize the results
of the computations. The methods for deriving the first four values were
described previously. The last two metrics are obtained by taking the
sum of the last two columns and dividing by the total number of quarter
hour periods to obtain the "# of quarter hours when demand exceeds
capacity" and the "# of quarter hours when aircraft are in queue",
respectively.

### Summary

In summary, it is important to note that the Single Airport Delay Model
is extremely simple to use and can be easily adapted to determine delays
associated with any demand and capacity imbalance. It is not restricted
to aircraft and airports, but in fact can be used for a wide variety of
applications. In particular, it has already proven to be useful in
determining delays that may occur from the introduction of new security
screening equipment and procedures at airline cargo facilities.

## [Appendix F: Navigation Capabilities Baseline]{.smallcaps}

LAAS benefits are estimated relative to a baseline of existing and
planned systems. This baseline was defined in the Navigation
Capabilities Baseline delivered November 2003. The following three
tables, excerpted from the earlier deliverable, contain the key elements
of the baseline:

1.  NAS Baseline -- the existing and planned ground and space-based
    infrastructure

2.  System Capabilities -- those capabilities associated with existing
    and planned systems

3.  User Baseline -- estimates of avionics equipage levels for the
    relevant systems

### [Table F1: NAS Baseline]{.smallcaps}

![](media/image23.wmf){width="6.89375in" height="5.6305555555555555in"}

![](media/image24.wmf){width="6.89375in" height="9.679166666666667in"}

![](media/image25.wmf){width="6.89375in" height="9.198611111111111in"}

![](media/image26.wmf){width="6.89375in" height="9.942361111111111in"}

![](media/image27.wmf){width="6.89375in" height="9.942361111111111in"}

![](media/image28.wmf){width="6.89375in" height="8.990972222222222in"}

![](media/image29.wmf){width="6.89375in" height="9.965972222222222in"}

![](media/image30.wmf){width="6.89375in" height="9.989583333333334in"}

![](media/image31.wmf){width="6.89375in" height="10.005555555555556in"}

![](media/image32.wmf){width="6.89375in" height="6.23125in"}

[Table F2: System Capabilities]{.smallcaps}

![](media/image33.wmf){width="6.875in" height="9.411111111111111in"}

[Table F3: User Baseline]{.smallcaps}

![](media/image34.wmf){width="6.89375in" height="8.761111111111111in"}

![](media/image35.wmf){width="6.89375in" height="9.025in"}

## [Appendix G: Potential LAAS Sites Outside of the 121 Airports]{.smallcaps}

The following airports, listed in alphabetical order, have been
identified by airline stakeholders as potential LAAS candidate airports
outside the IBM 121 Airports.

> [Table G1. Potential LAAS Sites Outside of the 121
> Airports]{.smallcaps}

  ------------ -------------------------------- ------------------ -----------
  **Airport    **Location**                     **2003 Scheduled   
  Code**                                        Arrivals**         

  ASE          Aspen, CO                        4,162              []{.mark}

  EAT          Wenatchee, WA                    2,334              

  EGE          Eagle County, CO                 2,257              []{.mark}

  GUC          Gunnison County, CO              1,387              []{.mark}

  JAC          Jackson Hole, WY                 4,979              []{.mark}

  PUW          Pullman, WA                      1,744              []{.mark}

  SIT          Sitka, AK                        1,647              []{.mark}

  SUN          Sun Valley, ID                   4,333              []{.mark}

  YAK          Yakutat, AK                      1,196              []{.mark}
  ------------ -------------------------------- ------------------ -----------

### Limitations

Lack of operational data precludes analyzing these airports at the same
level of detail as was performed for the IBM 121 Airports.

Analysis of airports outside of the original list of 121 is currently
out of scope for this study.

## [Appendix H: Aviation Facilities Within 23nm of the 121 Airports]{.smallcaps}

The LAAS Concept of Operations (CONOPS), dated August 5, 2002, states
the LAAS service coverage volume extends out to 23nm[^133] radially from
the LAAS Ground Facility VDB \[Very High Frequency (VHF) Data Broadcast
(VDB)\] and with increasing altitude from the installed station (angle
of 0.9 degrees, so that at 23 NM the minimum receivable altitude is 2200
ft).

IBM identified the aviation facilities (*e.g.*, other airports, seaplane
bases, gliderports, and heliports) within 23nm of each of the IBM 121
Airports from entries in the NFDC[^134] database. Table H1 lists the
results of this investigation, which identified: 1) 6,453 total aviation
facilities within 23nm of all 120 airports, and 2) 428 total aviation
facilities within 23nm of the 6 LRIP Airports.

This table shows the scope of potential beneficiaries of the LAAS signal
if LAAS were installed at each of the 121 airports. No claim of benefits
is made for this potential capability, since the LAAS signal is not
required or expected to meet minimum field strength requirements at low
altitudes except at the airport where it is installed. If a program
decision were made to require LAAS services at these nearby airports,
design and installation requirements would have to be updated to reflect
this goal. Alternatively, it may be feasible to exploit LAAS at these
airports to some degree without any specific requirements on the design
or installation (*i.e.*, use LAAS where it is receivable). It is not
possible to estimate benefits in this scenario since the achieved
coverage is not yet known.

[Table H1. Number of Aviation Facilities Within 23 nm of Each of the 121
Airports]{.smallcaps}

The LAAS LRIP sites are shown in bold.

  ----------- ------------ ----------- ------------ ----------- ------------ ----------- -------- ------------ ----------- -------- ------------ ----- ----------- ------------
  **Airport   **\# of      **Airport   **\# of      **Airport   **\# of      **Airport            **\# of      **Airport            **\# of            **Airport   **\# of
  Code**      Proximate    Code**      Proximate    Code**      Proximate    Code**               Proximate    Code**               Proximate          Code**      Proximate
              Airports**               Airports**               Airports**                        Airports**                        Airports**                     Airports**

  ABQ         13           CLE         62           FLL         52           LAS         22                    **ORD**     **93**                SHV               28

  ACK         4            CLT         31           FWA         57           LAX         152                   ORF         34                    SJC               18

  AFW         124          CMH         71           FXE         41           LCK         50                    PBI         38                    SLC               28

  ALB         42           COS         23           GEG         32           LGA         104                   PDX         99                    SMF               37

  ANC         24           CVG         39           GRR         34           LGB         161                   PHL         148                   SNA               81

  ATL         75           DAB         23           GSO         30           LIT         35                    **PHX**     **78**                STL               66

  AUS         31           DAL         116          GSP         23           MCI         68                    PIE         35                    SWF               45

  AVL         11           DAY         57           HNL         13           MCO         64                    PIT         68                    SYR               34

  BDL         75           DCA         71           HOU         160          MDT         77                    PVD         49                    TEB               114

  BFI         75           DEN         73           HPN         68           MDW         77                    RDU         21                    TLH               11

  BGR         12           DFW         139          HSV         21           **MEM**     **38**                RFD         83                    TPA               42

  BHM         23           DLH         13           IAD         73           MHT         65                    RIC         35                    TRI               17

  BNA         29           DSM         25           **IAH**     **128**      MIA         57                    RNO         22                    TUL               50

  BOI         18           DTW         46           ICT         55           MKE         43                    ROC         40                    TUS               17

  BOS         75           DVT         73           ILN         42           MMU         149                   RSW         39                    TYS               34

  BUF         44           ELP         9            IND         94           MSP         72                    SAN         20                    VNY               137

  BUR         138          EUG         27           ISP         32           MSY         40                    SAT         59                                      

  BWI         70           EWR         141          JAN         25           OAK         32                    SDF         31                                      

  CAE         21           EYW         6            JAX         28           OKC         57                    **SEA**     **85**                                  

  CHA         18           FAI         13           JFK         86           OMA         35                    SFB         56                                      

  CHS         10           FAT         26           **JNU**     **6**        ONT         53                    SFO         26                                      
  ----------- ------------ ----------- ------------ ----------- ------------ ----------- -------- ------------ ----------- -------- ------------ ----- ----------- ------------

There is a wide variety of facilities included in the list above. To
give a sample of these facilities, Table H2 details the 84 aviation
facilities within 23nm of SEA.

[Table H2. Aviation Facilities Within 23 nm of SEA]{.smallcaps}

  ----------- ------------------------------------- -------------------- -----------
  **Locid**   **Airport Name**                      **City**             **State**

  02WA        CAWLEYS SOUTH PRAIRIE                 SOUTH PRAIRIE        WA

  08WA        MANCHESTER LABORATORY                 MANCHESTER           WA

  0S8         PORT ORCHARD                          PORT ORCHARD         WA

  0W0         SEATTLE SEAPLANES                     SEATTLE              WA

  0WA6        STEVENS MEMORIAL HOSPITAL             EDMONDS              WA

  0WA8        CHILDRENS HOSPITAL EMERGENCY          SEATTLE              WA

  1S0         PIERCE COUNTY - THUN FIELD            PUYALLUP             WA

  1WA1        WEBER POINT                           REDMOND              WA

  1WA6        FALL CITY                             FALL CITY            WA

  1WA8        MADIGAN HOSPITAL                      FORT LEWIS           WA

  23WA        BCAG - FREDERICKSON                   PUYALLUP             WA

  29WA        CROSSINGS                             TACOMA               WA

  2S1         VASHON MUNI                           VASHON               WA

  2WA2        QUARTERMASTER HARBOR                  DOCKTON              WA

  2WA4        MOSS FIELD                            GRAHAM               WA

  31WA        MARY BRIDGE                           TACOMA               WA

  3B8         SHADY ACRES                           SPANAWAY             WA

  3WA6        BOEING KENT                           KENT                 WA

  3WA7        KENT BENAROYA                         KENT                 WA

  43WA        WILSON                                WOODINVILLE          WA

  47WA        FITZ PAD 1                            WOODINVILLE          WA

  51WA        EVERGREEN SKY RANCH                   BLACK DIAMOND        WA

  54WA        TUKWILA OPERATIONS CENTER             TUKWILA              WA

  60WA        J. J. H.                              AUBURN               WA

  64WA        TAYMAR                                BELLEVUE             WA

  71WA        I-90/BELLEVUE BUSI PK BOEING COMP     BELLEVUE             WA
              SVCS H                                                     

  7WA8        GOOD SAMARITAN HOSP                   PUYALLUP             WA

  81WA        JOBE SKIS PLANT 1                     REDMOND              WA

  83Q         PORT OF POULSBO MARINA MOORAGE        POULSBO              WA

  88WA        PERSONAL 500 SALES CO.                SUMNER               WA

  8WA2        BOEING RENTON RAMP SITE NR 2          RENTON               WA

  8WA3        VALLEY MEDICAL CENTER                 RENTON               WA

  8WA8        SNOQUALMIE VALLEY HOSPITAL EMERGENCY  KING COUNTY          WA
              ROOM                                                       

  8WA9        BROADCAST HOUSE HELISTOP              SEATTLE              WA

  92WA        CONNER                                ISSAQUAH             WA

  95WA        BLACK DIAMOND                         BLACK DIAMOND        WA

  9WA0        BOEING PLANT 2                        SEATTLE              WA

  9WA6        PUGET SOUND PLAZA                     SEATTLE              WA

  9WA9        NAVAL SUBMARINE BASE BANGOR           SILVERDALE           WA

  BFI         BOEING FIELD/KING COUNTY INTL         SEATTLE              WA

  PWT         BREMERTON NATIONAL                    BREMERTON            WA

  RNT         RENTON MUNI                           RENTON               WA

  S36         CREST AIRPARK                         KENT                 WA

  S37         CLOVER PARK TECHNICAL COLLEGE         TACOMA               WA

  S42         APEX AIRPARK                          SILVERDALE           WA

  S44         SPANAWAY                              SPANAWAY             WA

  S50         AUBURN MUNI                           AUBURN               WA

  S60         KENMORE AIR HARBOR INC                KENMORE              WA

  TCM         MCCHORD AFB                           TACOMA               WA

  TIW         TACOMA NARROWS                        TACOMA               WA

  W36         WILL ROGERS WILEY POST MEML           RENTON               WA

  W37         AMERICAN LAKE                         TACOMA               WA

  W55         KENMORE AIR HARBOR                    SEATTLE              WA

  WA06        DON JOHNSON HOME                      AUBURN               WA

  WA11        BOEING MILITARY AIRPLANES             TUKWILA              WA

  WA19        BERKLEY STRUCTURES                    REDMOND              WA

  WA28        TOM MATSON                            AUBURN               WA

  WA53        HARBORVIEW MEDICAL CENTER             SEATTLE              WA

  WA54        1001 FOURTH AVENUE PLAZA              SEATTLE              WA

  WA55        ELLIOTT PARK                          SEATTLE              WA

  WA69        WAX ORCHARDS                          VASHON               WA

  WA75        FLYING \'O\' RANCH                    COVINGTON            WA

  WA77        ENUMCLAW                              ENUMCLAW             WA

  WA84        AUBURN ACADEMY                        AUBURN               WA

  WA85        WEYERHAEUSER                          AUBURN               WA

  WA86        BOEING - AUBURN COMPLEX               AUBURN               WA

  WA92        MC NEIL ISLAND EMERGENCY PAD          STEILACOOM           WA

  WA94        WASHINGTON AIR MUSEUM                 BLACK DIAMOND        WA

  WA96        LEISURELAND AIRPARK                   BREMERTON            WA

  WN01        SEATTLE PRIVATE NUMBER ONE            SEATTLE              WA

  WN13        VAUGHAN RANCH AIRFIELD                PORT ORCHARD         WA

  WN16        KOMO TV                               SEATTLE              WA

  WN19        GIG HARBOR                            GIG HARBOR           WA

  WN22        LAKE UNION                            SEATTLE              WA

  WN42        FLYING H RANCH                        BUCKLEY              WA

  WN50        ST JOSEPH HOSPITAL                    TACOMA               WA

  WN62        AUBURN FIRE DEPARTMENT                AUBURN               WA

  WN71        EVANS                                 BELLEVUE             WA

  WN76        BERGSETH FIELD                        ENUMCLAW             WA

  WN79        HALEY                                 WINSLOW              WA

  WN83        TELEPHONE UTILITIES/TIW/              GIG HARBOR           WA

  WN87        BRYAN                                 ENUMCLAW             WA

  WN91        EVANS                                 REDMOND              WA

  WN93        PARK 90                               SEATTLE              WA

  WN96        MISTY ISLE FARMS                      VASHON ISLAND        WA
  ----------- ------------------------------------- -------------------- -----------

### 

### Limitations

Investigation has shown that some double-counting of proximate
facilities exists within the 121 airport list. For example, the list of
proximate facilities for SEA includes BFI, and visa versa.

Final evaluation and certification of service provided to proximate
facilities, if any, is to be determined by the FAA.

## [Appendix I: LAAS Benefits Analysis Assumptions]{.smallcaps}

This following list of assumptions was developed, prior to the start of
this analysis, through a series of meetings between IBM and the FAA.
Several of these assumptions have been modified or updated as a result
of new guidance from the FAA (*e.g.*, #3, 4, 6, 13).

One key assumption, regarding airline WAAS equipage (#20), was designed
to be modified through airline stakeholder feedback and the development
of airline benefit estimates. For these preliminary findings, the impact
of this assumption is bounded, as shown in the LAAS benefit tables, by
estimating LAAS benefits for two cases:

1.  assuming no WAAS equipage by users ("0% WAAS"), and

2.  assuming full WAAS equipage by users ("100% WAAS").

[Table I1.]{.smallcaps} LAAS Benefits Analysis Assumptions

+---+-------------------------------------------------------------------+
| * | **Assumption**                                                    |
| * |                                                                   |
| N |                                                                   |
| o |                                                                   |
| . |                                                                   |
| * |                                                                   |
| * |                                                                   |
+---+-------------------------------------------------------------------+
| 1 | LAAS will accrue benefit only when and where it provides          |
|   | capabilities above and beyond those provided by other systems.    |
+---+-------------------------------------------------------------------+
| 2 | Where LAAS provides capabilities above and beyond those provided  |
|   | by other systems, it may reduce flight disruptions, including:    |
|   |                                                                   |
|   | -- Diversions                                                     |
|   |                                                                   |
|   | -- Cancellations                                                  |
|   |                                                                   |
|   | -- Delays (Ground Delay Program and circular holding delays)      |
+---+-------------------------------------------------------------------+
| 3 | LAAS Cat-I Initial Operational Capability (IOC) at end of FY06    |
|   | (changed to FY09; 2/26/04)                                        |
+---+-------------------------------------------------------------------+
| 4 | LAAS Cat-II/III IOC in FY10 (changed to FY13; 2/26/04)            |
+---+-------------------------------------------------------------------+
| 5 | LAAS may be installed at a maximum rate of 2 per month (24/yr),   |
|   | with a cap equal to the number of FAA LAAS airports to be studied |
+---+-------------------------------------------------------------------+
| 6 | LAAS approach procedures, including complex procedures, will be   |
|   | available at commissioning of each site, for all weather          |
|   | conditions. (changed to 4 months after commissioning; 2/26/04)    |
+---+-------------------------------------------------------------------+
| 7 | LAAS training will keep pace with LAAS procedure development and  |
|   | publication.                                                      |
+---+-------------------------------------------------------------------+
| 8 | Appropriate infrastructure will exist at LAAS candidate runways   |
|   | at the time of LAAS installation                                  |
+---+-------------------------------------------------------------------+
| 9 | There may be some decommissioning of ground-based navaids         |
|   | (consistent with the Navigation and Landing Transition Strategy)  |
+---+-------------------------------------------------------------------+
| 1 | LAAS provides no operational improvement during weather           |
| 0 | conditions that would be likely to close the airport.             |
+---+-------------------------------------------------------------------+
| 1 | LAAS, coupled with other technologies, may provide operational    |
| 1 | improvement in extremely low visibility conditions.               |
+---+-------------------------------------------------------------------+
| 1 | WAAS LNAV/VNAV and LPV approach procedures, including complex     |
| 2 | procedures, will be available at or before LAAS commissioning at  |
|   | each site.                                                        |
+---+-------------------------------------------------------------------+
| 1 | WAAS Cat-I requires GPS L5 [and]{.underline} modifications to the |
| 3 | current architecture, and may not be achieved during the time     |
|   | period under study (2005 -- 2024) (changed to 2009 -- 20023;      |
|   | 2/26/04).                                                         |
+---+-------------------------------------------------------------------+
| 1 | GPS L5 frequency will become operationally available after 2015   |
| 4 |                                                                   |
+---+-------------------------------------------------------------------+
| 1 | Detailed study of quantitative DoD benefits are beyond the scope  |
| 5 | of this benefits analysis.                                        |
+---+-------------------------------------------------------------------+
| 1 | Assume LAAS can be sited at every airport. If all runway ends at  |
| 6 | the airport are within 5 nm\* of each other, assume that one (1)  |
|   | LAAS will cover every runway end. Otherwise, assume that two (2)  |
|   | LAAS are required. (\*Note: This distance will be verified with   |
|   | LAAS SME input)                                                   |
+---+-------------------------------------------------------------------+
| 1 | If any navigation system performance assumptions stated herein    |
| 7 | (*SOW*) cannot be achieved at a specific location, then the       |
|   | actual performance parameters will be used.                       |
+---+-------------------------------------------------------------------+

+---+-------------------------------------------------------------------+
| 1 | RNAV and RNP operations (approaches) intercept a straight-in      |
| 8 | approach at or above 500' HAT.                                    |
| a |                                                                   |
|   | The straight-in approach can be supported by ILS, LAAS, or WAAS,  |
|   | to the appropriate operating minima.                              |
|   |                                                                   |
|   | RNAV and RNP departures and missed approaches have a              |
|   | straight-ahead segment to at least 400' HAT.                      |
|   |                                                                   |
|   | Typical required performance (above 500' HAT on approach, above   |
|   | 400' HAT on missed approach or departure) is RNP-0.1.             |
+---+-------------------------------------------------------------------+
| 1 | GPS/INS, GPS/WAAS and GPS/LAAS all provide an RNP-0.1 capability, |
| 8 | with potentially different levels of service availability         |
| b |                                                                   |
+---+-------------------------------------------------------------------+
| 1 | Cat I: The Cat I LAAS should obtain the benefits accruing from:   |
| 8 |                                                                   |
| c | 1\) the reduction in weather minima below those supported by      |
|   | other systems                                                     |
|   |                                                                   |
|   | 2\) greater availability, where demonstrated.                     |
+---+-------------------------------------------------------------------+
| 1 | Cat I: LAAS performance would generally achieve Cat I GLS with    |
| 8 | \[0.99999\] availability                                          |
| d |                                                                   |
+---+-------------------------------------------------------------------+
| 1 | Cat II/III: The Cat II/III LAAS should obtain the benefits        |
| 9 | accruing from:                                                    |
| a |                                                                   |
|   | 1\) the reduction in weather minima below those supported by      |
|   | other systems                                                     |
|   |                                                                   |
|   | 2\) greater availability, where demonstrated.                     |
+---+-------------------------------------------------------------------+
| 1 | The benefits analysis does not include any decommissioning of Cat |
| 9 | II/III ILS facilities                                             |
| b |                                                                   |
+---+-------------------------------------------------------------------+
| 2 | The *initial* airline equipage assumption is that all users equip |
| 0 | with GPS/WAAS LPV as the baseline.                                |
|   |                                                                   |
|   | The *final* airline equipage assumption will be based on the      |
|   | airline benefit assessment.                                       |
+---+-------------------------------------------------------------------+
| 2 | For efficiency analyses, expected LAAS user groups include:       |
| 1 | High-end GA (corporate turbine; helicopters), and commercial      |
|   | (airline and air-taxi) operators. Low-end (recreational) GA       |
|   | operators are not among the expected users of LAAS and will not   |
|   | be addressed in this efficiency analysis                          |
+---+-------------------------------------------------------------------+
| 2 | Navigation capabilities baseline will include:                    |
| 2 |                                                                   |
|   | [NAS Baseline]{.underline} [User Baseline]{.underline}            |
|   |                                                                   |
|   | [Current Systems]{.underline}                                     |
|   |                                                                   |
|   | [ILS X                                                            |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [WAAS-LPV X                                                       |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [VOR X                                                            |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [DME X                                                            |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [GPS X                                                            |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [Loran X                                                          |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [NDB X                                                            |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [INS                                                              |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [FMS                                                              |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [PRM X                                                            |
|   | \_\_\_                                                            |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [Multilateration X                                                |
|   | \_\_\_                                                            |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [TAWS                                                             |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [HUD                                                              |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
+---+-------------------------------------------------------------------+
| 2 | Navigation capabilities baseline will include:                    |
| 3 |                                                                   |
|   | [NAS Baseline]{.underline} [User Baseline]{.underline}            |
|   |                                                                   |
|   | [Planned Systems]{.underline}                                     |
|   |                                                                   |
|   | [WAAS-GLS X                                                       |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [GPS L5 X                                                         |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [GPS -- III X                                                     |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [ASDE-X X                                                         |
|   | \_\_\_\                                                           |
|   | _\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_.]{.underline} |
|   |                                                                   |
|   | [ADS-B X                                                          |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
|   |                                                                   |
|   | [CDTI                                                             |
|   | X\_\_\_                                                           |
|   | \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_]{.underline} |
+---+-------------------------------------------------------------------+
| 2 | LAAS improves safety by providing vertical guidance               |
| 4 |                                                                   |
+---+-------------------------------------------------------------------+
| 2 | LAAS may be a source of positioning information for surface       |
| 5 | navigation systems                                                |
+---+-------------------------------------------------------------------+
| 2 | For safety analyses covering operations in Alaska, low-end GA     |
| 6 | users, in addition to high-end GA and commercial users, will be   |
|   | considered.                                                       |
+---+-------------------------------------------------------------------+

## [Appendix J: LAAS Efficiency Benefits by User Group]{.smallcaps}

[Table J1: Discounted 20 year LAAS operating cost Benefits -- 0% waas
equipage scenario,]{.smallcaps} by Airport

  ------------- --------------- ----------- --------------- --------------- -------------- -------------- -------------
  **Airport**   **Total         **Rank by   Major Passenger Regional        Cargo Carriers Corporate Jet  Other GA
                Benefit**       Total       Airlines        Passenger                      GA Operators   Operators
                                Benefit**                   Airlines                                      

  ABQ           \$2,405,000     79          \$1,852,000     \$287,000       \$190,000      \$76,000       \$0

  ACK           \$8,190,000     30          \$0             \$6,887,000     \$196,000      \$1,107,000    \$0

  AFW           \$157,000       117         \$0             \$0             \$138,000      \$19,000       \$0

  ALB           \$8,693,000     26          \$4,620,000     \$3,051,000     \$607,000      \$415,000      \$0

  ANC           \$8,414,000     28          \$3,890,000     \$0             \$3,062,000    \$190,000      \$1,272,000

  ATL           \$13,227,000    11          \$11,310,000    \$1,600,000     \$262,000      \$55,000       \$0

  AUS           \$3,301,000     63          \$2,940,000     \$48,000        \$0            \$313,000      \$0

  AVL           \$941,000       96          \$229,000       \$302,000       \$2,000        \$408,000      \$0

  BDL           \$10,521,000    19          \$7,291,000     \$1,678,000     \$888,000      \$664,000      \$0

  BFI           \$874,000       98          \$0             \$22,000        \$195,000      \$657,000      \$0

  BGR           \$387,000       110         \$0             \$259,000       \$33,000       \$95,000       \$0

  BHM           \$6,994,000     35          \$4,688,000     \$1,032,000     \$314,000      \$960,000      \$0

  BNA           \$2,243,000     81          \$1,723,000     \$336,000       \$84,000       \$100,000      \$0

  BOI           \$2,606,000     76          \$1,509,000     \$752,000       \$174,000      \$171,000      \$0

  BOS           \$10,590,000    18          \$7,324,000     \$2,805,000     \$245,000      \$216,000      \$0

  BUF           \$5,036,000     51          \$3,058,000     \$1,347,000     \$213,000      \$418,000      \$0

  BUR           \$21,023,000    7           \$19,992,000    \$130,000       \$399,000      \$502,000      \$0

  BWI           \$5,167,000     48          \$4,342,000     \$537,000       \$166,000      \$122,000      \$0

  CAE           \$1,704,000     87          \$443,000       \$743,000       \$398,000      \$120,000      \$0

  CHA           \$445,000       108         \$62,000        \$194,000       \$31,000       \$158,000      \$0

  CHS           \$3,210,000     65          \$1,505,000     \$1,307,000     \$108,000      \$290,000      \$0

  CLE           \$21,481,000    5           \$12,544,000    \$7,528,000     \$874,000      \$535,000      \$0

  CLT           \$11,416,000    16          \$9,184,000     \$1,776,000     \$261,000      \$195,000      \$0

  CMH           \$3,639,000     60          \$2,088,000     \$846,000       \$1,000        \$704,000      \$0

  COS           \$6,649,000     38          \$4,725,000     \$815,000       \$291,000      \$818,000      \$0

  CVG           \$13,089,000    13          \$6,225,000     \$5,682,000     \$1,071,000    \$111,000      \$0

  DAB           \$656,000       104         \$224,000       \$51,000        \$0            \$381,000      \$0

  DAL           \$3,893,000     59          \$1,923,000     \$92,000        \$72,000       \$1,806,000    \$0

  DAY           \$2,512,000     77          \$1,004,000     \$783,000       \$576,000      \$149,000      \$0

  DCA           \$28,340,000    3           \$24,250,000    \$4,031,000     \$0            \$59,000       \$0

  DEN           \$14,862,000    10          \$12,048,000    \$2,338,000     \$407,000      \$69,000       \$0

  DFW           \$34,102,000    1           \$26,584,000    \$6,221,000     \$1,242,000    \$55,000       \$0

  DLH           \$1,260,000     92          \$324,000       \$349,000       \$43,000       \$544,000      \$0

  DSM           \$1,293,000     90          \$490,000       \$454,000       \$214,000      \$135,000      \$0

  DTW           \$29,316,000    2           \$23,100,000    \$5,486,000     \$476,000      \$254,000      \$0

  DVT           \$4,000         121         \$0             \$0             \$0            \$4,000        \$0

  ELP           \$93,000        118         \$72,000        \$0             \$6,000        \$15,000       \$0

  EUG           \$4,032,000     57          \$897,000       \$1,884,000     \$665,000      \$586,000      \$0

  EWR           \$9,802,000     21          \$7,670,000     \$1,331,000     \$694,000      \$107,000      \$0

  EYW           \$298,000       114         \$0             \$262,000       \$0            \$36,000       \$0

  FAI           \$705,000       102         \$329,000       \$0             \$31,000       \$3,000        \$342,000

  FAT           \$304,000       113         \$11,000        \$245,000       \$29,000       \$19,000       \$0

  FLL           \$2,746,000     74          \$2,043,000     \$452,000       \$97,000       \$154,000      \$0

  FWA           \$3,030,000     68          \$59,000        \$1,795,000     \$955,000      \$221,000      \$0

  FXE           \$94,000        119         \$0             \$0             \$0            \$94,000       \$0

  GEG           \$5,712,000     44          \$2,906,000     \$1,583,000     \$1,121,000    \$102,000      \$0

  GRR           \$4,422,000     55          \$1,263,000     \$1,326,000     \$729,000      \$1,104,000    \$0

  GSO           \$7,493,000     33          \$4,274,000     \$1,914,000     \$818,000      \$487,000      \$0

  GSP           \$880,000       97          \$310,000       \$459,000       \$51,000       \$60,000       \$0

  HNL           \$2,675,000     75          \$754,000       \$1,734,000     \$177,000      \$10,000       \$0

  HOU           \$11,553,000    15          \$7,525,000     \$601,000       \$1,000        \$3,426,000    \$0

  HPN           \$10,014,000    20          \$1,352,000     \$1,627,000     \$1,000        \$7,034,000    \$0

  HSV           \$621,000       106         \$254,000       \$100,000       \$119,000      \$148,000      \$0

  IAD           \$7,317,000     34          \$3,970,000     \$2,775,000     \$127,000      \$445,000      \$0

  IAH           \$11,047,000    17          \$8,980,000     \$1,772,000     \$174,000      \$121,000      \$0

  ICT           \$3,277,000     64          \$1,260,000     \$688,000       \$389,000      \$940,000      \$0

  ILN           \$2,758,000     73          \$0             \$0             \$2,758,000    \$0            \$0

  IND           \$2,935,000     70          \$1,344,000     \$394,000       \$996,000      \$201,000      \$0

  ISP           \$3,311,000     62          \$1,636,000     \$1,506,000     \$0            \$169,000      \$0

  JAN           \$351,000       112         \$204,000       \$73,000        \$30,000       \$44,000       \$0

  JAX           \$1,835,000     83          \$1,373,000     \$234,000       \$116,000      \$112,000      \$0

  JFK           \$4,990,000     52          \$3,667,000     \$837,000       \$419,000      \$67,000       \$0

  JNU           \$13,052,000    14          \$2,591,000     \$0             \$2,467,000    \$77,000       \$7,917,000

  LAS           \$417,000       109         \$392,000       \$6,000         \$0            \$19,000       \$0

  LAX           \$6,791,000     37          \$5,446,000     \$1,027,000     \$240,000      \$78,000       \$0

  LCK           \$167,000       116         \$0             \$0             \$167,000      \$0            \$0

  LGA           \$21,146,000    6           \$16,569,000    \$4,262,000     \$0            \$315,000      \$0

  LGB           \$6,641,000     39          \$3,093,000     \$92,000        \$845,000      \$2,611,000    \$0

  LIT           \$863,000       99          \$334,000       \$156,000       \$25,000       \$348,000      \$0

  MCI           \$4,023,000     58          \$3,063,000     \$703,000       \$210,000      \$47,000       \$0

  MCO           \$7,826,000     32          \$5,306,000     \$2,025,000     \$405,000      \$90,000       \$0

  MDT           \$1,540,000     88          \$655,000       \$438,000       \$264,000      \$183,000      \$0

  MDW           \$16,214,000    9           \$14,359,000    \$1,570,000     \$22,000       \$263,000      \$0

  MEM           \$9,271,000     25          \$4,852,000     \$1,172,000     \$2,518,000    \$729,000      \$0

  MHT           \$8,028,000     31          \$5,709,000     \$1,225,000     \$916,000      \$178,000      \$0

  MIA           \$5,041,000     50          \$3,628,000     \$759,000       \$543,000      \$111,000      \$0

  MKE           \$13,221,000    12          \$4,248,000     \$7,026,000     \$1,311,000    \$636,000      \$0

  MMU           \$824,000       100         \$0             \$0             \$0            \$824,000      \$0

  MSP           \$8,607,000     27          \$7,218,000     \$1,160,000     \$181,000      \$48,000       \$0

  MSY           \$5,157,000     49          \$4,263,000     \$483,000       \$272,000      \$139,000      \$0

  OAK           \$1,231,000     93          \$822,000       \$22,000        \$294,000      \$93,000       \$0

  OKC           \$5,235,000     47          \$3,460,000     \$929,000       \$412,000      \$434,000      \$0

  OMA           \$1,177,000     94          \$715,000       \$178,000       \$161,000      \$123,000      \$0

  ONT           \$356,000       111         \$289,000       \$11,000        \$53,000       \$3,000        \$0

  ORD           \$23,664,000    4           \$19,838,000    \$3,225,000     \$477,000      \$124,000      \$0

  ORF           \$4,978,000     53          \$2,927,000     \$1,273,000     \$335,000      \$443,000      \$0

  PBI           \$1,747,000     85          \$939,000       \$364,000       \$40,000       \$404,000      \$0

  PDX           \$3,141,000     66          \$2,114,000     \$664,000       \$234,000      \$129,000      \$0

  PHL           \$5,895,000     41          \$4,282,000     \$1,023,000     \$343,000      \$247,000      \$0

  PHX           \$3,078,000     67          \$2,694,000     \$135,000       \$143,000      \$106,000      \$0

  PIE           \$766,000       101         \$152,000       \$0             \$75,000       \$539,000      \$0

  PIT           \$8,198,000     29          \$5,814,000     \$2,074,000     \$178,000      \$132,000      \$0

  PVD           \$5,717,000     43          \$2,832,000     \$2,002,000     \$286,000      \$597,000      \$0

  RDU           \$9,553,000     22          \$4,971,000     \$3,690,000     \$293,000      \$599,000      \$0

  RFD           \$1,782,000     84          \$0             \$71,000        \$1,277,000    \$434,000      \$0

  RIC           \$5,706,000     45          \$3,237,000     \$1,563,000     \$544,000      \$362,000      \$0

  RNO           \$2,486,000     78          \$2,052,000     \$138,000       \$147,000      \$149,000      \$0

  ROC           \$2,767,000     72          \$1,203,000     \$971,000       \$348,000      \$245,000      \$0

  RSW           \$6,192,000     40          \$4,470,000     \$659,000       \$120,000      \$943,000      \$0

  SAN           \$17,045,000    8           \$14,383,000    \$1,728,000     \$413,000      \$521,000      \$0

  SAT           \$5,767,000     42          \$4,536,000     \$63,000        \$372,000      \$796,000      \$0

  SDF           \$560,000       107         \$218,000       \$59,000        \$259,000      \$24,000       \$0

  SEA           \$9,296,000     24          \$6,557,000     \$2,204,000     \$497,000      \$38,000       \$0

  SFB           \$284,000       115         \$0             \$80,000        \$0            \$204,000      \$0

  SFO           \$2,277,000     80          \$2,007,000     \$192,000       \$32,000       \$46,000       \$0

  SHV           \$1,262,000     91          \$134,000       \$830,000       \$149,000      \$149,000      \$0

  SJC           \$9,460,000     23          \$8,306,000     \$153,000       \$376,000      \$625,000      \$0

  SLC           \$5,561,000     46          \$4,251,000     \$615,000       \$259,000      \$436,000      \$0

  SMF           \$3,015,000     69          \$2,492,000     \$209,000       \$241,000      \$73,000       \$0

  SNA           \$4,207,000     56          \$2,494,000     \$125,000       \$73,000       \$1,515,000    \$0

  STL           \$4,615,000     54          \$3,934,000     \$574,000       \$12,000       \$95,000       \$0

  SWF           \$635,000       105         \$71,000        \$449,000       \$20,000       \$95,000       \$0

  SYR           \$1,739,000     86          \$755,000       \$749,000       \$159,000      \$76,000       \$0

  TEB           \$6,867,000     36          \$0             \$0             \$63,000       \$6,804,000    \$0

  TLH           \$2,868,000     71          \$407,000       \$1,408,000     \$332,000      \$721,000      \$0

  TPA           \$3,462,000     61          \$2,679,000     \$416,000       \$47,000       \$320,000      \$0

  TRI           \$689,000       103         \$76,000        \$396,000       \$31,000       \$186,000      \$0

  TUL           \$2,139,000     82          \$1,217,000     \$500,000       \$92,000       \$330,000      \$0

  TUS           \$70,000        120         \$58,000        \$0             \$1,000        \$11,000       \$0

  TYS           \$1,421,000     89          \$551,000       \$550,000       \$159,000      \$161,000      \$0

  VNY           \$1,150,000     95          \$0             \$0             \$0            \$1,150,000    \$0

  Total         \$697,822,000               \$453,307,000   \$135,757,000   \$43,469,000   \$55,758,000   \$9,531,000
  ------------- --------------- ----------- --------------- --------------- -------------- -------------- -------------

[Table J2: Discounted 20 year LAAS Passenger Time Savings -- 0% waas
equipage scenario,]{.smallcaps} by Airport

  ------------- --------------- ----------- --------------- --------------- ---------- -------------- -------------
  **Airport**   **Total         **Rank by   Major Passenger Regional        Cargo      Corporate Jet  Other GA
                Benefit**       Total       Airlines        Passenger       Carriers   GA Operators   Operators
                                Benefit**                   Airlines                                  

  ABQ           \$2,939,000     73          \$2,452,000     \$472,000       \$0        \$15,000       \$0

  ACK           \$11,575,000    23          \$0             \$11,379,000    \$0        \$196,000      \$0

  AFW           \$3,000         118         \$0             \$0             \$0        \$3,000        \$0

  ALB           \$11,320,000    25          \$6,209,000     \$5,025,000     \$0        \$86,000       \$0

  ANC           \$5,400,000     52          \$4,996,000     \$0             \$0        \$34,000       \$370,000

  ATL           \$18,420,000    11          \$15,806,000    \$2,603,000     \$0        \$11,000       \$0

  AUS           \$3,981,000     63          \$3,843,000     \$78,000        \$0        \$60,000       \$0

  AVL           \$929,000       94          \$343,000       \$492,000       \$0        \$94,000       \$0

  BDL           \$12,272,000    19          \$9,382,000     \$2,771,000     \$0        \$119,000      \$0

  BFI           \$181,000       112         \$0             \$36,000        \$0        \$145,000      \$0

  BGR           \$446,000       102         \$0             \$428,000       \$0        \$18,000       \$0

  BHM           \$7,892,000     35          \$6,017,000     \$1,705,000     \$0        \$170,000      \$0

  BNA           \$2,785,000     77          \$2,211,000     \$556,000       \$0        \$18,000       \$0

  BOI           \$3,208,000     70          \$1,936,000     \$1,242,000     \$0        \$30,000       \$0

  BOS           \$14,072,000    16          \$9,400,000     \$4,634,000     \$0        \$38,000       \$0

  BUF           \$6,231,000     44          \$3,932,000     \$2,225,000     \$0        \$74,000       \$0

  BUR           \$26,066,000    7           \$25,758,000    \$214,000       \$0        \$94,000       \$0

  BWI           \$6,482,000     39          \$5,573,000     \$887,000       \$0        \$22,000       \$0

  CAE           \$1,817,000     84          \$569,000       \$1,227,000     \$0        \$21,000       \$0

  CHA           \$429,000       104         \$80,000        \$321,000       \$0        \$28,000       \$0

  CHS           \$4,142,000     62          \$1,932,000     \$2,159,000     \$0        \$51,000       \$0

  CLE           \$28,632,000    5           \$16,099,000    \$12,438,000    \$0        \$95,000       \$0

  CLT           \$14,757,000    14          \$11,787,000    \$2,935,000     \$0        \$35,000       \$0

  CMH           \$4,376,000     59          \$2,836,000     \$1,392,000     \$0        \$148,000      \$0

  COS           \$8,110,000     33          \$6,594,000     \$1,338,000     \$0        \$178,000      \$0

  CVG           \$15,899,000    13          \$7,913,000     \$7,970,000     \$0        \$16,000       \$0

  DAB           \$497,000       101         \$327,000       \$84,000        \$0        \$86,000       \$0

  DAL           \$3,367,000     68          \$2,808,000     \$150,000       \$0        \$409,000      \$0

  DAY           \$2,619,000     78          \$1,300,000     \$1,292,000     \$0        \$27,000       \$0

  DCA           \$37,792,000    3           \$31,122,000    \$6,660,000     \$0        \$10,000       \$0

  DEN           \$19,337,000    10          \$15,463,000    \$3,862,000     \$0        \$12,000       \$0

  DFW           \$49,936,000    1           \$40,027,000    \$9,897,000     \$0        \$12,000       \$0

  DLH           \$1,134,000     93          \$445,000       \$574,000       \$0        \$115,000      \$0

  DSM           \$1,404,000     88          \$629,000       \$751,000       \$0        \$24,000       \$0

  DTW           \$39,413,000    2           \$30,349,000    \$9,025,000     \$0        \$39,000       \$0

  DVT           \$1,000         119         \$0             \$0             \$0        \$1,000        \$0

  ELP           \$103,000       115         \$100,000       \$0             \$0        \$3,000        \$0

  EUG           \$4,500,000     58          \$1,278,000     \$3,091,000     \$0        \$131,000      \$0

  EWR           \$12,061,000    21          \$9,843,000     \$2,199,000     \$0        \$19,000       \$0

  EYW           \$439,000       103         \$0             \$433,000       \$0        \$6,000        \$0

  FAI           \$522,000       99          \$422,000       \$0             \$0        \$0            \$100,000

  FAT           \$422,000       105         \$15,000        \$403,000       \$0        \$4,000        \$0

  FLL           \$3,480,000     67          \$2,707,000     \$745,000       \$0        \$28,000       \$0

  FWA           \$3,081,000     71          \$76,000        \$2,965,000     \$0        \$40,000       \$0

  FXE           \$18,000        117         \$0             \$0             \$0        \$18,000       \$0

  GEG           \$6,378,000     41          \$3,745,000     \$2,614,000     \$0        \$19,000       \$0

  GRR           \$4,158,000     61          \$1,750,000     \$2,179,000     \$0        \$229,000      \$0

  GSO           \$8,733,000     30          \$5,485,000     \$3,162,000     \$0        \$86,000       \$0

  GSP           \$1,168,000     92          \$398,000       \$759,000       \$0        \$11,000       \$0

  HNL           \$3,836,000     65          \$968,000       \$2,866,000     \$0        \$2,000        \$0

  HOU           \$13,025,000    17          \$11,266,000    \$984,000       \$0        \$775,000      \$0

  HPN           \$6,308,000     43          \$2,046,000     \$2,644,000     \$0        \$1,618,000    \$0

  HSV           \$576,000       98          \$378,000       \$164,000       \$0        \$34,000       \$0

  IAD           \$9,758,000     28          \$5,095,000     \$4,584,000     \$0        \$79,000       \$0

  IAH           \$14,363,000    15          \$11,532,000    \$2,811,000     \$0        \$20,000       \$0

  ICT           \$2,921,000     74          \$1,617,000     \$1,137,000     \$0        \$167,000      \$0

  ILN           \$0             120         \$0             \$0             \$0        \$0            \$0

  IND           \$2,410,000     80          \$1,724,000     \$650,000       \$0        \$36,000       \$0

  ISP           \$4,619,000     57          \$2,100,000     \$2,489,000     \$0        \$30,000       \$0

  JAN           \$392,000       106         \$263,000       \$121,000       \$0        \$8,000        \$0

  JAX           \$2,169,000     82          \$1,763,000     \$386,000       \$0        \$20,000       \$0

  JFK           \$6,086,000     47          \$4,692,000     \$1,383,000     \$0        \$11,000       \$0

  JNU           \$5,671,000     51          \$3,350,000     \$0             \$0        \$15,000       \$2,306,000

  LAS           \$516,000       100         \$504,000       \$9,000         \$0        \$3,000        \$0

  LAX           \$8,700,000     31          \$6,989,000     \$1,697,000     \$0        \$14,000       \$0

  LCK           \$0             121         \$0             \$0             \$0        \$0            \$0

  LGA           \$28,362,000    6           \$21,264,000    \$7,042,000     \$0        \$56,000       \$0

  LGB           \$4,808,000     55          \$4,230,000     \$151,000       \$0        \$427,000      \$0

  LIT           \$772,000       97          \$448,000       \$258,000       \$0        \$66,000       \$0

  MCI           \$5,100,000     53          \$3,931,000     \$1,161,000     \$0        \$8,000        \$0

  MCO           \$10,387,000    27          \$7,040,000     \$3,330,000     \$0        \$17,000       \$0

  MDT           \$1,672,000     85          \$912,000       \$720,000       \$0        \$40,000       \$0

  MDW           \$22,066,000    8           \$19,431,000    \$2,583,000     \$0        \$52,000       \$0

  MEM           \$8,191,000     32          \$6,163,000     \$1,932,000     \$0        \$96,000       \$0

  MHT           \$9,603,000     29          \$7,548,000     \$2,020,000     \$0        \$35,000       \$0

  MIA           \$5,931,000     50          \$4,657,000     \$1,254,000     \$0        \$20,000       \$0

  MKE           \$17,177,000    12          \$5,469,000     \$11,599,000    \$0        \$109,000      \$0

  MMU           \$168,000       114         \$0             \$0             \$0        \$168,000      \$0

  MSP           \$11,535,000    24          \$9,614,000     \$1,911,000     \$0        \$10,000       \$0

  MSY           \$6,357,000     42          \$5,533,000     \$798,000       \$0        \$26,000       \$0

  OAK           \$1,198,000     91          \$1,142,000     \$37,000        \$0        \$19,000       \$0

  OKC           \$6,085,000     48          \$4,471,000     \$1,534,000     \$0        \$80,000       \$0

  OMA           \$1,233,000     90          \$918,000       \$293,000       \$0        \$22,000       \$0

  ONT           \$390,000       107         \$371,000       \$18,000        \$0        \$1,000        \$0

  ORD           \$31,008,000    4           \$25,665,000    \$5,321,000     \$0        \$22,000       \$0

  ORF           \$6,225,000     45          \$4,054,000     \$2,076,000     \$0        \$95,000       \$0

  PBI           \$1,915,000     83          \$1,234,000     \$601,000       \$0        \$80,000       \$0

  PDX           \$3,917,000     64          \$2,798,000     \$1,094,000     \$0        \$25,000       \$0

  PHL           \$7,421,000     37          \$5,695,000     \$1,681,000     \$0        \$45,000       \$0

  PHX           \$4,366,000     60          \$4,122,000     \$219,000       \$0        \$25,000       \$0

  PIE           \$319,000       109         \$207,000       \$0             \$0        \$112,000      \$0

  PIT           \$10,912,000    26          \$7,462,000     \$3,427,000     \$0        \$23,000       \$0

  PVD           \$7,736,000     36          \$4,317,000     \$3,292,000     \$0        \$127,000      \$0

  RDU           \$12,577,000    18          \$6,377,000     \$6,096,000     \$0        \$104,000      \$0

  RFD           \$210,000       111         \$0             \$116,000       \$0        \$94,000       \$0

  RIC           \$6,815,000     38          \$4,175,000     \$2,574,000     \$0        \$66,000       \$0

  RNO           \$2,914,000     75          \$2,658,000     \$228,000       \$0        \$28,000       \$0

  ROC           \$3,313,000     69          \$1,695,000     \$1,571,000     \$0        \$47,000       \$0

  RSW           \$8,026,000     34          \$6,735,000     \$1,074,000     \$0        \$217,000      \$0

  SAN           \$21,406,000    9           \$18,459,000    \$2,855,000     \$0        \$92,000       \$0

  SAT           \$6,132,000     46          \$5,881,000     \$103,000       \$0        \$148,000      \$0

  SDF           \$380,000       108         \$279,000       \$97,000        \$0        \$4,000        \$0

  SEA           \$12,272,000    20          \$8,764,000     \$3,501,000     \$0        \$7,000        \$0

  SFB           \$175,000       113         \$0             \$131,000       \$0        \$44,000       \$0

  SFO           \$2,913,000     76          \$2,587,000     \$318,000       \$0        \$8,000        \$0

  SHV           \$1,569,000     87          \$172,000       \$1,371,000     \$0        \$26,000       \$0

  SJC           \$11,874,000    22          \$11,490,000    \$251,000       \$0        \$133,000      \$0

  SLC           \$6,454,000     40          \$5,380,000     \$1,016,000     \$0        \$58,000       \$0

  SMF           \$3,666,000     66          \$3,307,000     \$344,000       \$0        \$15,000       \$0

  SNA           \$4,922,000     54          \$4,376,000     \$202,000       \$0        \$344,000      \$0

  STL           \$6,017,000     49          \$5,051,000     \$949,000       \$0        \$17,000       \$0

  SWF           \$851,000       95          \$92,000        \$741,000       \$0        \$18,000       \$0

  SYR           \$2,221,000     81          \$969,000       \$1,238,000     \$0        \$14,000       \$0

  TEB           \$1,307,000     89          \$0             \$0             \$0        \$1,307,000    \$0

  TLH           \$3,043,000     72          \$574,000       \$2,309,000     \$0        \$160,000      \$0

  TPA           \$4,688,000     56          \$3,935,000     \$680,000       \$0        \$73,000       \$0

  TRI           \$785,000       96          \$98,000        \$654,000       \$0        \$33,000       \$0

  TUL           \$2,447,000     79          \$1,562,000     \$827,000       \$0        \$58,000       \$0

  TUS           \$79,000        116         \$77,000        \$0             \$0        \$2,000        \$0

  TYS           \$1,645,000     86          \$707,000       \$909,000       \$0        \$29,000       \$0

  VNY           \$227,000       110         \$0             \$0             \$0        \$227,000      \$0

  Total         \$838,059,000               \$602,340,000   \$221,804,000   \$0        \$11,139,000   \$2,776,000
  ------------- --------------- ----------- --------------- --------------- ---------- -------------- -------------

[Table J3: Discounted 20 year LAAS operating cost Benefits -- 100% waas
equipage scenario,]{.smallcaps} by Airport

  ------------- --------------- ----------- --------------- -------------- -------------- -------------- -----------
  **Airport**   **Total         **Rank by   Major Passenger Regional       Cargo Carriers Corporate Jet  Other GA
                Benefit**       Total       Airlines        Passenger                     GA Operators   Operators
                                Benefit**                   Airlines                                     

  ABQ           \$1,147,000     82          \$866,000       \$128,000      \$104,000      \$49,000       \$0

  ACK           \$8,190,000     16          \$0             \$6,887,000    \$196,000      \$1,107,000    \$0

  AFW           \$157,000       113         \$0             \$0            \$138,000      \$19,000       \$0

  ALB           \$5,527,000     30          \$2,927,000     \$1,858,000    \$421,000      \$321,000      \$0

  ANC           \$4,674,000     32          \$2,254,000     \$0            \$1,778,000    \$110,000      \$532,000

  ATL           \$11,946,000    7           \$10,275,000    \$1,403,000    \$221,000      \$47,000       \$0

  AUS           \$3,301,000     50          \$2,940,000     \$48,000       \$0            \$313,000      \$0

  AVL           \$941,000       91          \$229,000       \$302,000      \$2,000        \$408,000      \$0

  BDL           \$3,629,000     43          \$2,502,000     \$570,000      \$314,000      \$243,000      \$0

  BFI           \$874,000       94          \$0             \$22,000       \$195,000      \$657,000      \$0

  BGR           \$387,000       105         \$0             \$259,000      \$33,000       \$95,000       \$0

  BHM           \$949,000       85          \$662,000       \$124,000      \$21,000       \$142,000      \$0

  BNA           \$1,171,000     80          \$983,000       \$105,000      \$21,000       \$62,000       \$0

  BOI           \$2,606,000     60          \$1,509,000     \$752,000      \$174,000      \$171,000      \$0

  BOS           \$10,590,000    10          \$7,324,000     \$2,805,000    \$245,000      \$216,000      \$0

  BUF           \$4,629,000     33          \$3,058,000     \$1,165,000    \$181,000      \$225,000      \$0

  BUR           \$664,000       98          \$460,000       \$10,000       \$28,000       \$166,000      \$0

  BWI           \$5,167,000     28          \$4,342,000     \$537,000      \$166,000      \$122,000      \$0

  CAE           \$1,059,000     81          \$283,000       \$455,000      \$245,000      \$76,000       \$0

  CHA           \$401,000       103         \$62,000        \$194,000      \$31,000       \$114,000      \$0

  CHS           \$2,194,000     67          \$1,030,000     \$893,000      \$74,000       \$197,000      \$0

  CLE           \$5,026,000     29          \$2,761,000     \$1,921,000    \$190,000      \$154,000      \$0

  CLT           \$11,416,000    8           \$9,184,000     \$1,776,000    \$261,000      \$195,000      \$0

  CMH           \$3,639,000     48          \$2,088,000     \$846,000      \$1,000        \$704,000      \$0

  COS           \$5,357,000     36          \$3,745,000     \$623,000      \$253,000      \$736,000      \$0

  CVG           \$9,663,000     12          \$4,825,000     \$4,060,000    \$709,000      \$69,000       \$0

  DAB           \$656,000       101         \$224,000       \$51,000       \$0            \$381,000      \$0

  DAL           \$3,893,000     57          \$1,923,000     \$92,000       \$72,000       \$1,806,000    \$0

  DAY           \$1,352,000     75          \$579,000       \$385,000      \$300,000      \$88,000       \$0

  DCA           \$3,544,000     44          \$3,022,000     \$513,000      \$0            \$9,000        \$0

  DEN           \$14,862,000    4           \$12,048,000    \$2,338,000    \$407,000      \$69,000       \$0

  DFW           \$21,049,000    2           \$16,906,000    \$3,490,000    \$624,000      \$29,000       \$0

  DLH           \$1,214,000     83          \$324,000       \$349,000      \$43,000       \$498,000      \$0

  DSM           \$1,293,000     78          \$490,000       \$454,000      \$214,000      \$135,000      \$0

  DTW           \$13,338,000    6           \$10,904,000    \$2,119,000    \$217,000      \$98,000       \$0

  DVT           \$0             121         \$0             \$0            \$0            \$0            \$0

  ELP           \$93,000        117         \$72,000        \$0            \$6,000        \$15,000       \$0

  EUG           \$3,445,000     58          \$806,000       \$1,458,000    \$615,000      \$566,000      \$0

  EWR           \$9,802,000     11          \$7,670,000     \$1,331,000    \$694,000      \$107,000      \$0

  EYW           \$78,000        116         \$0             \$62,000       \$0            \$16,000       \$0

  FAI           \$464,000       100         \$329,000       \$0            \$31,000       \$3,000        \$101,000

  FAT           \$304,000       110         \$11,000        \$245,000      \$29,000       \$19,000       \$0

  FLL           \$2,354,000     66          \$1,729,000     \$414,000      \$97,000       \$114,000      \$0

  FWA           \$964,000       86          \$33,000        \$461,000      \$328,000      \$142,000      \$0

  FXE           \$50,000        118         \$0             \$0            \$0            \$50,000       \$0

  GEG           \$3,733,000     42          \$2,171,000     \$805,000      \$675,000      \$82,000       \$0

  GRR           \$3,962,000     47          \$1,263,000     \$1,209,000    \$599,000      \$891,000      \$0

  GSO           \$7,493,000     19          \$4,274,000     \$1,914,000    \$818,000      \$487,000      \$0

  GSP           \$880,000       87          \$310,000       \$459,000      \$51,000       \$60,000       \$0

  HNL           \$105,000       115         \$20,000        \$85,000       \$0            \$0            \$0

  HOU           \$11,176,000    18          \$7,525,000     \$368,000      \$1,000        \$3,282,000    \$0

  HPN           \$9,810,000     23          \$1,321,000     \$1,556,000    \$1,000        \$6,932,000    \$0

  HSV           \$621,000       102         \$254,000       \$100,000      \$119,000      \$148,000      \$0

  IAD           \$7,317,000     20          \$3,970,000     \$2,775,000    \$127,000      \$445,000      \$0

  IAH           \$11,047,000    9           \$8,980,000     \$1,772,000    \$174,000      \$121,000      \$0

  ICT           \$2,384,000     61          \$946,000       \$461,000      \$259,000      \$718,000      \$0

  ILN           \$2,758,000     59          \$0             \$0            \$2,758,000    \$0            \$0

  IND           \$2,935,000     52          \$1,344,000     \$394,000      \$996,000      \$201,000      \$0

  ISP           \$2,902,000     54          \$1,636,000     \$1,173,000    \$0            \$93,000       \$0

  JAN           \$351,000       109         \$204,000       \$73,000       \$30,000       \$44,000       \$0

  JAX           \$1,835,000     70          \$1,373,000     \$234,000      \$116,000      \$112,000      \$0

  JFK           \$4,724,000     31          \$3,419,000     \$837,000      \$419,000      \$49,000       \$0

  JNU           \$418,000       106         \$232,000       \$0            \$71,000       \$29,000       \$86,000

  LAS           \$32,000        119         \$31,000        \$0            \$0            \$1,000        \$0

  LAX           \$6,791,000     21          \$5,446,000     \$1,027,000    \$240,000      \$78,000       \$0

  LCK           \$167,000       114         \$0             \$0            \$167,000      \$0            \$0

  LGA           \$13,671,000    5           \$10,712,000    \$2,755,000    \$0            \$204,000      \$0

  LGB           \$3,295,000     64          \$1,313,000     \$65,000       \$655,000      \$1,262,000    \$0

  LIT           \$638,000       96          \$334,000       \$107,000      \$25,000       \$172,000      \$0

  MCI           \$4,023,000     39          \$3,063,000     \$703,000      \$210,000      \$47,000       \$0

  MCO           \$4,338,000     37          \$3,252,000     \$815,000      \$209,000      \$62,000       \$0

  MDT           \$1,540,000     77          \$655,000       \$438,000      \$264,000      \$183,000      \$0

  MDW           \$16,109,000    3           \$14,359,000    \$1,570,000    \$22,000       \$158,000      \$0

  MEM           \$6,545,000     22          \$2,810,000     \$1,125,000    \$2,381,000    \$229,000      \$0

  MHT           \$6,294,000     24          \$4,456,000     \$945,000      \$745,000      \$148,000      \$0

  MIA           \$3,118,000     51          \$2,267,000     \$462,000      \$320,000      \$69,000       \$0

  MKE           \$5,178,000     27          \$1,631,000     \$2,786,000    \$528,000      \$233,000      \$0

  MMU           \$540,000       107         \$0             \$0            \$0            \$540,000      \$0

  MSP           \$8,607,000     17          \$7,218,000     \$1,160,000    \$181,000      \$48,000       \$0

  MSY           \$2,941,000     55          \$2,596,000     \$145,000      \$98,000       \$102,000      \$0

  OAK           \$1,112,000     84          \$822,000       \$6,000        \$214,000      \$70,000       \$0

  OKC           \$3,543,000     46          \$2,463,000     \$500,000      \$252,000      \$328,000      \$0

  OMA           \$1,177,000     79          \$715,000       \$178,000      \$161,000      \$123,000      \$0

  ONT           \$356,000       108         \$289,000       \$11,000       \$53,000       \$3,000        \$0

  ORD           \$23,664,000    1           \$19,838,000    \$3,225,000    \$477,000      \$124,000      \$0

  ORF           \$4,923,000     38          \$2,900,000     \$1,254,000    \$331,000      \$438,000      \$0

  PBI           \$928,000       88          \$526,000       \$98,000       \$6,000        \$298,000      \$0

  PDX           \$3,086,000     53          \$2,069,000     \$664,000      \$234,000      \$119,000      \$0

  PHL           \$5,895,000     25          \$4,282,000     \$1,023,000    \$343,000      \$247,000      \$0

  PHX           \$3,078,000     65          \$2,694,000     \$135,000      \$143,000      \$106,000      \$0

  PIE           \$538,000       104         \$99,000        \$0            \$58,000       \$381,000      \$0

  PIT           \$8,198,000     15          \$5,814,000     \$2,074,000    \$178,000      \$132,000      \$0

  PVD           \$4,620,000     45          \$2,832,000     \$1,083,000    \$240,000      \$465,000      \$0

  RDU           \$9,479,000     13          \$4,926,000     \$3,690,000    \$293,000      \$570,000      \$0

  RFD           \$1,022,000     92          \$0             \$20,000       \$670,000      \$332,000      \$0

  RIC           \$3,240,000     49          \$1,837,000     \$873,000      \$314,000      \$216,000      \$0

  RNO           \$616,000       95          \$502,000       \$31,000       \$32,000       \$51,000       \$0

  ROC           \$2,079,000     68          \$986,000       \$712,000      \$227,000      \$154,000      \$0

  RSW           \$6,192,000     35          \$4,470,000     \$659,000      \$120,000      \$943,000      \$0

  SAN           \$682,000       89          \$576,000       \$67,000       \$19,000       \$20,000       \$0

  SAT           \$5,767,000     26          \$4,536,000     \$63,000       \$372,000      \$796,000      \$0

  SDF           \$560,000       97          \$218,000       \$59,000       \$259,000      \$24,000       \$0

  SEA           \$8,779,000     14          \$6,236,000     \$2,055,000    \$454,000      \$34,000       \$0

  SFB           \$261,000       112         \$0             \$80,000       \$0            \$181,000      \$0

  SFO           \$2,277,000     63          \$2,007,000     \$192,000      \$32,000       \$46,000       \$0

  SHV           \$680,000       90          \$134,000       \$364,000      \$104,000      \$78,000       \$0

  SJC           \$4,897,000     41          \$4,167,000     \$54,000       \$221,000      \$455,000      \$0

  SLC           \$3,889,000     40          \$2,857,000     \$615,000      \$259,000      \$158,000      \$0

  SMF           \$3,015,000     56          \$2,492,000     \$209,000      \$241,000      \$73,000       \$0

  SNA           \$4,022,000     69          \$2,494,000     \$98,000       \$73,000       \$1,357,000    \$0

  STL           \$4,615,000     34          \$3,934,000     \$574,000      \$12,000       \$95,000       \$0

  SWF           \$296,000       111         \$71,000        \$143,000      \$3,000        \$79,000       \$0

  SYR           \$1,323,000     76          \$625,000       \$523,000      \$110,000      \$65,000       \$0

  TEB           \$2,518,000     72          \$0             \$0            \$14,000       \$2,504,000    \$0

  TLH           \$2,868,000     62          \$407,000       \$1,408,000    \$332,000      \$721,000      \$0

  TPA           \$2,104,000     74          \$1,580,000     \$200,000      \$47,000       \$277,000      \$0

  TRI           \$608,000       93          \$76,000        \$368,000      \$31,000       \$133,000      \$0

  TUL           \$1,816,000     71          \$1,217,000     \$295,000      \$75,000       \$229,000      \$0

  TUS           \$32,000        120         \$24,000        \$0            \$1,000        \$7,000        \$0

  TYS           \$1,421,000     73          \$551,000       \$550,000      \$159,000      \$161,000      \$0

  VNY           \$682,000       99          \$0             \$0            \$0            \$682,000      \$0

  Total         \$479,195,000               \$313,030,000   \$93,976,000   \$30,102,000   \$41,368,000   \$719,000
  ------------- --------------- ----------- --------------- -------------- -------------- -------------- -----------

[Table J4: Discounted 20 year LAAS Passenger Time Savings -- 100% waas
equipage scenario,]{.smallcaps} by Airport

  ------------- --------------- ----------- --------------- --------------- ---------- ------------- -----------
  **Airport**   **Total         **Rank by   Major Passenger Regional        Cargo      Corporate Jet Other GA
                Benefit**       Total       Airlines        Passenger       Carriers   GA Operators  Operators
                                Benefit**                   Airlines                                 

  ABQ           \$1,408,000     78          \$1,187,000     \$211,000       \$0        \$10,000      \$0

  ACK           \$11,575,000    15          \$0             \$11,379,000    \$0        \$196,000     \$0

  AFW           \$3,000         118         \$0             \$0             \$0        \$3,000       \$0

  ALB           \$7,159,000     27          \$4,037,000     \$3,053,000     \$0        \$69,000      \$0

  ANC           \$3,071,000     57          \$2,896,000     \$0             \$0        \$20,000      \$155,000

  ATL           \$16,293,000    7           \$13,990,000    \$2,294,000     \$0        \$9,000       \$0

  AUS           \$3,981,000     48          \$3,843,000     \$78,000        \$0        \$60,000      \$0

  AVL           \$929,000       90          \$343,000       \$492,000       \$0        \$94,000      \$0

  BDL           \$4,221,000     43          \$3,235,000     \$941,000       \$0        \$45,000      \$0

  BFI           \$181,000       109         \$0             \$36,000        \$0        \$145,000     \$0

  BGR           \$446,000       95          \$0             \$428,000       \$0        \$18,000      \$0

  BHM           \$1,080,000     82          \$850,000       \$205,000       \$0        \$25,000      \$0

  BNA           \$1,447,000     75          \$1,262,000     \$174,000       \$0        \$11,000      \$0

  BOI           \$3,208,000     55          \$1,936,000     \$1,242,000     \$0        \$30,000      \$0

  BOS           \$14,072,000    10          \$9,400,000     \$4,634,000     \$0        \$38,000      \$0

  BUF           \$5,896,000     30          \$3,932,000     \$1,924,000     \$0        \$40,000      \$0

  BUR           \$742,000       93          \$691,000       \$16,000        \$0        \$35,000      \$0

  BWI           \$6,482,000     26          \$5,573,000     \$887,000       \$0        \$22,000      \$0

  CAE           \$1,128,000     81          \$363,000       \$751,000       \$0        \$14,000      \$0

  CHA           \$421,000       97          \$80,000        \$321,000       \$0        \$20,000      \$0

  CHS           \$2,832,000     60          \$1,322,000     \$1,475,000     \$0        \$35,000      \$0

  CLE           \$6,743,000     25          \$3,543,000     \$3,173,000     \$0        \$27,000      \$0

  CLT           \$14,757,000    8           \$11,787,000    \$2,935,000     \$0        \$35,000      \$0

  CMH           \$4,376,000     47          \$2,836,000     \$1,392,000     \$0        \$148,000     \$0

  COS           \$6,521,000     36          \$5,336,000     \$1,021,000     \$0        \$164,000     \$0

  CVG           \$12,300,000    12          \$6,151,000     \$6,138,000     \$0        \$11,000      \$0

  DAB           \$497,000       102         \$327,000       \$84,000        \$0        \$86,000      \$0

  DAL           \$3,367,000     63          \$2,808,000     \$150,000       \$0        \$409,000     \$0

  DAY           \$1,405,000     76          \$754,000       \$635,000       \$0        \$16,000      \$0

  DCA           \$4,728,000     38          \$3,879,000     \$847,000       \$0        \$2,000       \$0

  DEN           \$19,337,000    4           \$15,463,000    \$3,862,000     \$0        \$12,000      \$0

  DFW           \$28,957,000    2           \$23,293,000    \$5,658,000     \$0        \$6,000       \$0

  DLH           \$1,125,000     83          \$445,000       \$574,000       \$0        \$106,000     \$0

  DSM           \$1,404,000     77          \$629,000       \$751,000       \$0        \$24,000      \$0

  DTW           \$18,359,000    5           \$14,879,000    \$3,463,000     \$0        \$17,000      \$0

  DVT           \$0             119         \$0             \$0             \$0        \$0           \$0

  ELP           \$103,000       112         \$100,000       \$0             \$0        \$3,000       \$0

  EUG           \$3,676,000     56          \$1,162,000     \$2,387,000     \$0        \$127,000     \$0

  EWR           \$12,061,000    13          \$9,843,000     \$2,199,000     \$0        \$19,000      \$0

  EYW           \$106,000       110         \$0             \$103,000       \$0        \$3,000       \$0

  FAI           \$451,000       94          \$422,000       \$0             \$0        \$0           \$29,000

  FAT           \$422,000       98          \$15,000        \$403,000       \$0        \$4,000       \$0

  FLL           \$3,019,000     61          \$2,313,000     \$683,000       \$0        \$23,000      \$0

  FWA           \$831,000       87          \$43,000        \$762,000       \$0        \$26,000      \$0

  FXE           \$10,000        117         \$0             \$0             \$0        \$10,000      \$0

  GEG           \$4,148,000     44          \$2,803,000     \$1,330,000     \$0        \$15,000      \$0

  GRR           \$3,928,000     53          \$1,750,000     \$1,987,000     \$0        \$191,000     \$0

  GSO           \$8,733,000     20          \$5,485,000     \$3,162,000     \$0        \$86,000      \$0

  GSP           \$1,168,000     80          \$398,000       \$759,000       \$0        \$11,000      \$0

  HNL           \$167,000       107         \$26,000        \$141,000       \$0        \$0           \$0

  HOU           \$12,617,000    19          \$11,266,000    \$601,000       \$0        \$750,000     \$0

  HPN           \$6,118,000     42          \$1,992,000     \$2,533,000     \$0        \$1,593,000   \$0

  HSV           \$576,000       96          \$378,000       \$164,000       \$0        \$34,000      \$0

  IAD           \$9,758,000     18          \$5,095,000     \$4,584,000     \$0        \$79,000      \$0

  IAH           \$14,363,000    9           \$11,532,000    \$2,811,000     \$0        \$20,000      \$0

  ICT           \$2,103,000     68          \$1,214,000     \$762,000       \$0        \$127,000     \$0

  ILN           \$0             120         \$0             \$0             \$0        \$0           \$0

  IND           \$2,410,000     65          \$1,724,000     \$650,000       \$0        \$36,000      \$0

  ISP           \$4,054,000     45          \$2,100,000     \$1,938,000     \$0        \$16,000      \$0

  JAN           \$392,000       100         \$263,000       \$121,000       \$0        \$8,000       \$0

  JAX           \$2,169,000     67          \$1,763,000     \$386,000       \$0        \$20,000      \$0

  JFK           \$5,779,000     32          \$4,388,000     \$1,383,000     \$0        \$8,000       \$0

  JNU           \$353,000       105         \$322,000       \$0             \$0        \$6,000       \$25,000

  LAS           \$42,000        115         \$42,000        \$0             \$0        \$0           \$0

  LAX           \$8,700,000     21          \$6,989,000     \$1,697,000     \$0        \$14,000      \$0

  LCK           \$0             121         \$0             \$0             \$0        \$0           \$0

  LGA           \$18,336,000    6           \$13,748,000    \$4,552,000     \$0        \$36,000      \$0

  LGB           \$2,377,000     73          \$2,010,000     \$106,000       \$0        \$261,000     \$0

  LIT           \$660,000       92          \$448,000       \$177,000       \$0        \$35,000      \$0

  MCI           \$5,100,000     37          \$3,931,000     \$1,161,000     \$0        \$8,000       \$0

  MCO           \$5,746,000     33          \$4,403,000     \$1,331,000     \$0        \$12,000      \$0

  MDT           \$1,672,000     74          \$912,000       \$720,000       \$0        \$40,000      \$0

  MDW           \$22,048,000    3           \$19,431,000    \$2,583,000     \$0        \$34,000      \$0

  MEM           \$5,508,000     34          \$3,614,000     \$1,859,000     \$0        \$35,000      \$0

  MHT           \$7,526,000     23          \$5,940,000     \$1,556,000     \$0        \$30,000      \$0

  MIA           \$3,684,000     50          \$2,909,000     \$763,000       \$0        \$12,000      \$0

  MKE           \$6,751,000     24          \$2,117,000     \$4,593,000     \$0        \$41,000      \$0

  MMU           \$117,000       113         \$0             \$0             \$0        \$117,000     \$0

  MSP           \$11,535,000    17          \$9,614,000     \$1,911,000     \$0        \$10,000      \$0

  MSY           \$3,654,000     52          \$3,394,000     \$240,000       \$0        \$20,000      \$0

  OAK           \$1,166,000     84          \$1,142,000     \$10,000        \$0        \$14,000      \$0

  OKC           \$4,077,000     46          \$3,191,000     \$825,000       \$0        \$61,000      \$0

  OMA           \$1,233,000     79          \$918,000       \$293,000       \$0        \$22,000      \$0

  ONT           \$390,000       99          \$371,000       \$18,000        \$0        \$1,000       \$0

  ORD           \$31,008,000    1           \$25,665,000    \$5,321,000     \$0        \$22,000      \$0

  ORF           \$6,171,000     35          \$4,021,000     \$2,055,000     \$0        \$95,000      \$0

  PBI           \$927,000       86          \$704,000       \$161,000       \$0        \$62,000      \$0

  PDX           \$3,860,000     51          \$2,742,000     \$1,094,000     \$0        \$24,000      \$0

  PHL           \$7,421,000     22          \$5,695,000     \$1,681,000     \$0        \$45,000      \$0

  PHX           \$4,366,000     58          \$4,122,000     \$219,000       \$0        \$25,000      \$0

  PIE           \$223,000       106         \$139,000       \$0             \$0        \$84,000      \$0

  PIT           \$10,912,000    16          \$7,462,000     \$3,427,000     \$0        \$23,000      \$0

  PVD           \$6,194,000     41          \$4,317,000     \$1,773,000     \$0        \$104,000     \$0

  RDU           \$12,520,000    11          \$6,323,000     \$6,096,000     \$0        \$101,000     \$0

  RFD           \$108,000       114         \$0             \$32,000        \$0        \$76,000      \$0

  RIC           \$3,856,000     49          \$2,378,000     \$1,438,000     \$0        \$40,000      \$0

  RNO           \$728,000       91          \$668,000       \$50,000        \$0        \$10,000      \$0

  ROC           \$2,513,000     64          \$1,320,000     \$1,164,000     \$0        \$29,000      \$0

  RSW           \$8,026,000     31          \$6,735,000     \$1,074,000     \$0        \$217,000     \$0

  SAN           \$853,000       85          \$739,000       \$110,000       \$0        \$4,000       \$0

  SAT           \$6,132,000     29          \$5,881,000     \$103,000       \$0        \$148,000     \$0

  SDF           \$380,000       101         \$279,000       \$97,000        \$0        \$4,000       \$0

  SEA           \$11,708,000    14          \$8,367,000     \$3,335,000     \$0        \$6,000       \$0

  SFB           \$171,000       108         \$0             \$131,000       \$0        \$40,000      \$0

  SFO           \$2,913,000     59          \$2,587,000     \$318,000       \$0        \$8,000       \$0

  SHV           \$788,000       88          \$172,000       \$602,000       \$0        \$14,000      \$0

  SJC           \$6,367,000     39          \$6,177,000     \$87,000        \$0        \$103,000     \$0

  SLC           \$4,708,000     40          \$3,667,000     \$1,016,000     \$0        \$25,000      \$0

  SMF           \$3,666,000     54          \$3,307,000     \$344,000       \$0        \$15,000      \$0

  SNA           \$4,849,000     66          \$4,376,000     \$157,000       \$0        \$316,000     \$0

  STL           \$6,017,000     28          \$5,051,000     \$949,000       \$0        \$17,000      \$0

  SWF           \$343,000       104         \$92,000        \$236,000       \$0        \$15,000      \$0

  SYR           \$1,679,000     71          \$803,000       \$864,000       \$0        \$12,000      \$0

  TEB           \$545,000       103         \$0             \$0             \$0        \$545,000     \$0

  TLH           \$3,043,000     62          \$574,000       \$2,309,000     \$0        \$160,000     \$0

  TPA           \$2,911,000     70          \$2,524,000     \$322,000       \$0        \$65,000      \$0

  TRI           \$730,000       89          \$98,000        \$608,000       \$0        \$24,000      \$0

  TUL           \$2,091,000     69          \$1,562,000     \$488,000       \$0        \$41,000      \$0

  TUS           \$36,000        116         \$34,000        \$0             \$0        \$2,000       \$0

  TYS           \$1,645,000     72          \$707,000       \$909,000       \$0        \$29,000      \$0

  VNY           \$144,000       111         \$0             \$0             \$0        \$144,000     \$0

  Total         \$580,840,000               \$417,879,000   \$154,038,000   \$0        \$8,714,000   \$209,000
  ------------- --------------- ----------- --------------- --------------- ---------- ------------- -----------

## [Appendix K: Data Sources]{.smallcaps}

### Air traffic data 

-   Growth rates: Terminal Area Forecast (TAF)

-   Scheduled traffic: Official Airline Guide (OAG) and Flight Schedule
    Data System (FSDS)

-   Unscheduled IFR traffic: Enhanced Traffic Management System (ETMS)

-   VFR traffic: FAA Operations Network (OPSNET) data

-   Cargo traffic: DOT TranStats Schedule T-3 data; Cargo airlines

### Weather data

-   National Climatic Data Center (NCDC) surface weather observations

### Flight data

-   Airline Service Quality Performance (ASQP) database

-   Aviation System Performance Metrics (ASPM) database

### Airport data

-   National Flight Data Center (NFDC)

-   DOT/FAA U.S. Terminal Procedures

-   FAA Airport Capacity Benchmark Report

-   FAA Operational Evolution Plan (OEP)

-   FAA Airport Capacity Enhancement reports (ACE Plans)

-   FAA ASD-430 Airport capacity and configuration data

-   FAA National Airspace System Capital Investment Plan Fiscal Years
    2004 -- 2008

-   FAA Blueprint for NAS Modernization

### Safety data

-   National Transportation Safety Board (NTSB) accident and incident
    investigation database

-   National Airspace Incidents Monitoring System (NAIMS)

-   NASA's Aviation Safety Reporting System (ASRS)

## [Appendix L: List of Acronyms]{.smallcaps}

ACE Aviation Capacity Enhancement

ADS-B Automatic Dependent Surveillance -- Broadcast

AILS Airborne Information for Lateral Spacing

AIP Airport Improvement Program

ANP Actual Navigation Performance

APO Office of Aviation Policy and Plans

ASDE-X Airport Surface Detection Equipment -- neXt generation

ASPM Aviation System Performance Metrics

ASQP Airline Service Quality Program

ATC Air Traffic Control

ATM Air Traffic Management

CAASD Center for Advanced Aviation System Development

CDTI Cockpit Display of Traffic Information

CFIT Controlled Flight Into Terrain

CNS Communication Navigation Surveillance

CONOPS Concept of Operations

CONUS Continental United States

DH Decision Height

DME Distance Measuring Equipment

DOC Direct Operating Cost

EGNOS European Geostationary Navigation Overlay Service

ETMS Enhanced Traffic Management System

EVS Enhanced Vision System

FAA Federal Aviation Administration

FMS Flight Management System

GA General Aviation

FSDS Flight Schedule Data System

GAME GPS Approach Minima Estimator

GAO General Accounting Office

GBAS Ground Based Augmentation System

GDP Gross Domestic Product

GLS GNSS Landing System

GNSS Global Navigation Satellite System

GPS Global Positioning System

GPS-III Next-generation GPS

GS Glide Slope

HUD Head-Up Display

ICAO International Civil Aviation Organization

IFR Instrument Flight Rules

ILS Instrument Landing System

IMC Instrument Meteorological Conditions

IRU Inertial Reference Unit\
JPALS Joint Precision Approach Landing System

LAAS Local Area Augmentation System

LGF LAAS Ground Facility

LNAV Lateral Navigation

LOC Localizer

LPV Lateral Precision with Vertical Guidance

MMR Multi-Mode Receiver

MSAS MTSAT Space Augmentation System

MSL Mean Sea Level

MTSAT Multi-functional Transport Satellite

MVMC Marginal VMC

NAS National Airspace System

NASA National Aeronautics and Space Administration

NCDC National Climatic Data Center

NDB Non-Directional Beacon

NFDC National Flight Data Center

NPA Non-Precision Approach

NTSB National Transportation Safety Board

OAG Official Airline Guide

OEM Original Equipment Manufacturer

OMB Office of Management and Budget

O&M Operations and Maintenance

PAR Precision Approach Radar

PFC Passenger Facility Charge

PRM Precision Runway Monitor

PTS Passenger Time Savings

PVT Position, Velocity, Time

RNAV Area Navigation

RNP Required Navigation Performance

RPM Revenue Passenger Mile

RTM Revenue Ton Mile

RVR Runway Visual Range

SARPS Standards and Recommended Practices

SBAS Space Based Augmentation System

SOIT Satellite Operational Integration Team

SPSS Statistical Package for the Social Sciences

TAWS Terrain Awareness and Warning System

TERPS Terminal Instrument Procedures

VDB VHF Data Broadcast

VFR Visual Flight Rules

VHF Very High Frequency

VMC Visual Meteorological Conditions

VOR VHF Omni-directional Range

WAAS Wide Area Augmentation System

WAAS-GLS WAAS GNSS (Global Navigation Satellite System) Landing System

WAAS-LPV WAAS procedures with vertical guidance

# 

## [Appendix M: Runway Utilization Analysis]{.smallcaps}

**Background**

The utilization of runways is a key driver of LAAS straight-in and
complex approach benefits estimates in this study. Since the required
data (*i.e.*, observations of runway utilization for all runways at all
of the airports studied, for all user equipment categories, and in
various weather conditions) is not readily available, we developed a
method for estimating arrival runway utilization in IMC from basic data,
including wind direction and speed and current patterns of runway usage.

Wind direction is a primary factor for determining when a runway can be
used. However, we recognize that other factors, including Air Traffic's
preferred configuration in specific weather conditions, also play a
role, particularly under conditions of low wind speed. The following
description illustrates the method used to accommodate both the current
runway usage patterns and the observed wind data to arrive at estimates
of future runway utilization during IMC. Port Columbus International
Airport in Ohio (CMH) serves as an example.

**Methodology**

The method applied in this analysis derives an estimate of the
percentage of time that a runway could be utilized based on wind
direction and speed, and then modifies that percentage by taking into
account the characteristics of each runway and a measure of preferred
usage of runways, based on objective data.

***Wind Speed and Direction***

At wind speeds lower than a certain threshold, the airport
configuration, and therefore the arrival runways in use, can be
determined by the preferred configuration, and need not be dependent on
wind direction. Above this wind speed threshold, however, the wind
direction is a key factor in determining which runways can be used.
Based on aircraft performance data and interviews with airline and
airport operations staff, a wind speed threshold of 10 knots was
selected.

The wind direction analysis uses historical weather data, including wind
speed and direction, and current runway usage data in order to estimate
the arrival runway utilization for each runway at each airport within
the benefits study. Historical weather data covering 1998 through 2001
has been collected for the 121 airports from the NCDC database[^135].
Wind direction has been tabulated for the percent of time that wind
speeds greater than 10 knots occur in each cardinal direction in two
weather conditions, Visual and IMC[^136]. Table M1 shows an example of
this data for CMH.

**Table M1: [Wind Direction at CMH (Wind Speed Greater Than 10 Knots, in
Each Weather Condition)]{.smallcaps}**

  ------------- ------------- ------- ------- -------- -------- ------- -------- -------- ------- ---------
  **Airport**   **Weather**   **E**   **N**   **NE**   **NW**   **S**   **SE**   **SW**   **W**   **Less
                                                                                                  than 10
                                                                                                  knots**

  CMH           IMC           0.92%   3.18%   0.96%    2.96%    1.96%   0.88%    2.72%    3.44%   82.98%

                Visual        0.71%   1.45%   0.87%    3.43%    2.16%   0.59%    4.46%    6.29%   80.04%
  ------------- ------------- ------- ------- -------- -------- ------- -------- -------- ------- ---------

To calculate the wind-direction-based availability of a runway we add
the percent of time that winds greater than 10 knots are in this
direction to the percent of time that winds are less than 10 knots
divided among the possible arrival runways. Using the percentages in
Table M1, an eastbound runway would be available 82.98% of the time
divided by the number of possible runways, plus 0.92% of the time that
winds are greater than 10 knots for this direction. The formula below
shows how the availability of an eastbound runway at CMH is calculated.
Note that two arrival runways are assumed for this example (as will be
shown in the following section).

> Eastbound Runway Availability = 82.98/2 + 0.92
>
> Eastbound Runway Availability = 42%

***Runway Characteristics and Preferred Usage***

Current runway configurations have been gathered from several sources,
including FAA's ASD organization[^137] and the FAA's airport-specific
capacity enhancement plans[^138]. Table M2 shows the runways identified
as arrival runways in any weather condition for CMH.

**Table M2: [Runways Used for Arrivals at CMH]{.smallcaps}**

  ------------- ------------ ----------------------------- ---------------------
  **Airport**   **Runway**   **Listed As An Arrival        **Source**
                             Runway?**                     

  CMH           10L          Yes                           ASD; ACE Plan

  CMH           10R          Yes                           ASD; ACE Plan

  CMH           28R          Yes                           ASD; ACE Plan

  CMH           28L          Yes                           ASD; ACE Plan
  ------------- ------------ ----------------------------- ---------------------

Runway length is an important consideration in this analysis. A runway
is only available for arrivals for a particular equipment category
(*e.g.*, large jet) if it meets the length requirement for that type of
equipment. Runway length requirements were established by searching
various databases containing aircraft performance characteristics, and
specific aircraft types were selected as representative for the entire
aircraft population[^139]. Table M3 lists the runway length requirements
applicable for each equipment category included in this study. Table M4
lists the arrival runway lengths at CMH, showing that all runways in
consideration are of sufficient length to accommodate any equipment
type.

Table M3: [Runway Length Requirements]{.smallcaps}[^140] [for Each
Equipment Category]{.smallcaps}

  -------------- --------------------------------------- -----------------
  **Equipment    **Example Aircraft**[^141]              **Runway Length
  Category**                                             Requirement
                                                         (ft)**

  Heavy Eqpt     D10; B757                               6250

  Large Jet Eqpt B737; M80                               6250

  Large Commuter CRJ                                     5750

  Small Commuter BE1                                     3750

  Small Eqpt     CNA; PAG (typically Alaska-based        2750
                 regional carriers)                      
  -------------- --------------------------------------- -----------------

**Table M4: [Runway Lengths at CMH]{.smallcaps}**

  ------------- ---------------- -----------------------------------------
  **Airport**   **Runway**       **Runway Length (ft)**

  CMH           10L              8000

                10R              10250

                28R              8000

                28L              10250
  ------------- ---------------- -----------------------------------------

If any runway at CMH were shorter than the requirement for a particular
category, that runway would be dropped from consideration for that
equipment type. Thus, at any airport, a particular runway may be
available for utilization by some or all equipment categories.

Additionally, we recognize that multiple parallel runways may not be
used for simultaneous independent arrivals in IMC if their centerline
separation is less than 4300 feet[^142]. In these circumstances the
runway to retain is selected based on the following sequence of rules:
Retain the runway with the most capable landing system (*e.g.*, ILS Cat
III vs. ILS Cat I), or the lowest approach minima (decision height and
visibility), or the longest runway. The other parallel runway will be
dropped from consideration. This provides an objective way to retain
those runways most likely to be used for arrivals in IMC. Table M5
illustrates how two of the runways at CMH (10L and 28R) were dropped
from consideration due to close parallel separation distances. In this
case, the only objective distinction between these runways is the
length, which leads to 10L and 28R being omitted from further
consideration.

**Table M5: [Parallel Runway Analysis Details for CMH]{.smallcaps}**

+-------+--------+----------+----------+--------+----------+--------+
| *     | **     | **Se     | **Best   | **Best | **Runway | **     |
| *Airp | Runway | paration | Approach | L      | Length** | Runway |
| ort** | ID**   | Between  | Minima** | anding |          | to     |
|       |        | Parallel |          | Sy     | **(ft)** | Drop** |
|       |        | Runways  |          | stem** |          |        |
|       |        | (ft)**   |          |        |          |        |
+-------+--------+----------+----------+--------+----------+--------+
| CMH   | 10L    | 2804     | 200/2400 | ILS    | 8000     | 10L    |
|       |        |          |          | Cat I  |          |        |
+-------+--------+----------+----------+--------+----------+--------+
|       | 10R    |          | 200/2400 | ILS    | 10250    |        |
|       |        |          |          | Cat I  |          |        |
+-------+--------+----------+----------+--------+----------+--------+
|       | 28R    | 2804     | 200/2400 | ILS    | 8000     | 28R    |
|       |        |          |          | Cat I  |          |        |
+-------+--------+----------+----------+--------+----------+--------+
|       | 28L    |          | 200/2400 | ILS    | 10250    |        |
|       |        |          |          | Cat I  |          |        |
+-------+--------+----------+----------+--------+----------+--------+

It is understood that airport operators and Air Traffic will have a
preference for using certain runways over others, depending on weather
conditions. To account for this preference, we followed the practice
established in the FAA's "Airway Planning Standard Number One - Terminal
Air Navigation Facilities and Air Traffic Control Services" document.
That is, we designated the arrival runway most likely to be preferred as
"Primary" runways and other arrival runways as "Secondary".
Specifically, the runway with the lowest approach minima was designated
as "Primary". In recognition that the majority of traffic is directed to
the most capable runway, a weighting of 70%[^143],[^144] is applied to
the primary runway and the remaining 30% is shared among the secondary
runways. In cases where there are only Primary runways (*i.e.,* no
distinctions between runway capabilities), a 50/50 weighting is applied.
This weighting is applied to the percentage of time the wind speed is
less than 10 knots, when runway configuration preferences, rather than
wind direction, is a primary decision factor Table M6 illustrates how
these weighting factors were applied to the two remaining arrival
runways at CMH (both considered primary since they have the same type of
ILS, identical approach minima, and runway length).

Table M6: [Runway Weighting Factor Details for CMH]{.smallcaps}

+----+---+------+------+--------+-------+-------+--------+---------+
| >  | > | **Ru | *    | *      | *     | **App | **P    | *       |
|  * |   | nway | *Arr | *Utili | *Best | roach | rimary | *Runway |
| *A | * | Leng | ival | zation | La    | Min   | or     | We      |
| ir | * | th** | Runw | Based  | nding | ima** | Sec    | ighting |
| po | R |      | ay** | on     | Sys   |       | ondary | F       |
| rt | u |      |      | Wind   | tem** |       | Ru     | actor** |
| ** | n |      | *    | Direc  |       |       | nway** |         |
|    | w |      | *?** | tion** |       |       |        |         |
|    | a |      |      |        |       |       | **?**  |         |
|    | y |      |      |        |       |       |        |         |
|    | * |      |      |        |       |       |        |         |
|    | * |      |      |        |       |       |        |         |
+----+---+------+------+--------+-------+-------+--------+---------+
| C  | 1 | 8000 | No;  | N/A    | ILS   | 200/  | N/A    | N/A     |
| MH | 0 |      | Dro  |        | Cat I |       |        |         |
|    | L |      | pped |        |       | 2400  |        |         |
|    |   |      | due  |        |       |       |        |         |
|    |   |      | to   |        |       |       |        |         |
|    |   |      | para |        |       |       |        |         |
|    |   |      | llel |        |       |       |        |         |
|    |   |      | spa  |        |       |       |        |         |
|    |   |      | cing |        |       |       |        |         |
+----+---+------+------+--------+-------+-------+--------+---------+
| C  | 1 | 1    | Yes  | 0.42   | ILS   | 200/  | P      | 0.5     |
| MH | 0 | 0250 |      |        | Cat I |       | rimary |         |
|    | R |      |      |        |       | 2400  |        |         |
+----+---+------+------+--------+-------+-------+--------+---------+
| C  | 2 | 8000 | No;  | N/A    | ILS   | 200/  | N/A    | N/A     |
| MH | 8 |      | Dro  |        | Cat I |       |        |         |
|    | R |      | pped |        |       | 2400  |        |         |
|    |   |      | due  |        |       |       |        |         |
|    |   |      | to   |        |       |       |        |         |
|    |   |      | para |        |       |       |        |         |
|    |   |      | llel |        |       |       |        |         |
|    |   |      | spa  |        |       |       |        |         |
|    |   |      | cing |        |       |       |        |         |
+----+---+------+------+--------+-------+-------+--------+---------+
| C  | 2 | 1    | Yes  | 0.46   | ILS   | 200/  | P      | 0.5     |
| MH | 8 | 0250 |      |        | Cat I |       | rimary |         |
|    | L |      |      |        |       | 2400  |        |         |
+----+---+------+------+--------+-------+-------+--------+---------+

**Results**

Table M7 summarizes the results of this arrival runway utilization
analysis for CMH. As shown in Table M5, runways 10L and 28R drop out due
to parallel separation requirements. The wind direction analysis, Table
M1, showed that approximately 42% of the time, winds were either lower
than 10 knots or were aligned with 10R, and 46% of the time with 28L.
Since both runways have nearly identical landing systems and approach
minima, both are designated "Primary" runways in Table M6, and a 50/50
weighting is applied to arrive at the final runway utilization of 47%
\[=(0.92+(82.98/2)\*.5)/((0.92+(82.98/2)\*.5)+(3.44+(82.98/2)\*.5))\]
for 10R and 53% for 28L.

**Table M7: [Summary of Estimated Arrival Utilization by Runway at
CMH]{.smallcaps}**

<table style="width:100%;">
<colgroup>
<col style="width: 5%" />
<col style="width: 4%" />
<col style="width: 9%" />
<col style="width: 9%" />
<col style="width: 10%" />
<col style="width: 12%" />
<col style="width: 11%" />
<col style="width: 11%" />
<col style="width: 11%" />
<col style="width: 13%" />
</colgroup>
<tbody>
<tr class="odd">
<td><blockquote>
<p><strong>Airport</strong></p>
</blockquote></td>
<td><blockquote>
<p><strong>Runway</strong></p>
</blockquote></td>
<td><strong>Primary Wind Direction</strong></td>
<td><strong>Runway Length</strong></td>
<td><p><strong>Currently Used As An Arrival Runway</strong></p>
<p><strong>?</strong></p></td>
<td><p><strong>Considered as an IMC Arrival Runway for this
Study</strong></p>
<p><strong>?</strong></p></td>
<td><strong>Utilization Based on Wind Direction</strong></td>
<td><p><strong>Primary or Secondary Runway</strong></p>
<p><strong>?</strong></p></td>
<td><strong>Runway Weighting Factor</strong></td>
<td><p><strong>Heavy Equipment</strong><a href="#fn1"
class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a>
<strong>Weighted Utilization</strong></p>
<p><strong>in IMC</strong></p></td>
</tr>
<tr class="even">
<td>CMH</td>
<td>10L</td>
<td>East</td>
<td>8000</td>
<td>Yes</td>
<td>No</td>
<td></td>
<td></td>
<td></td>
<td>0%</td>
</tr>
<tr class="odd">
<td>CMH</td>
<td>10R</td>
<td>East</td>
<td>10250</td>
<td>Yes</td>
<td>Yes</td>
<td>42%</td>
<td>Primary</td>
<td>0.5</td>
<td>47%</td>
</tr>
<tr class="even">
<td>CMH</td>
<td>28R</td>
<td>West</td>
<td>8000</td>
<td>Yes</td>
<td>No</td>
<td></td>
<td></td>
<td></td>
<td>0%</td>
</tr>
<tr class="odd">
<td>CMH</td>
<td>28L</td>
<td>West</td>
<td>10250</td>
<td>Yes</td>
<td>Yes</td>
<td>46%</td>
<td>Primary</td>
<td>0.5</td>
<td>53%</td>
</tr>
</tbody>
</table>
<aside id="footnotes" class="footnotes footnotes-end-of-document"
role="doc-endnotes">
<hr />
<ol>
<li id="fn1"><p><sup>The table shows results for the Heavy Equipment
category. Since these CMH runways are longer than the maximum runway
length requirement (see Table 3), all categories will have the same
runway utilization.</sup><a href="#fnref1" class="footnote-back"
role="doc-backlink">↩︎</a></p></li>
</ol>
</aside>

For validation of this result, the utilizations above can be compared to
the individual capacity enhancement plan for CMH[^145]. This report
shows that in IMC, there is a 45% utilization for east flow (runways
10L/R), and 55% for west flow (runways 28L/R).

[]{#__RefHeading___Toc82945631 .anchor}***[Appendix N: Analysis of the
Downstream Effect of Delays]{.smallcaps}***

**Background**

Flight disruptions of the kind studied here are not isolated events. In
general, a single flight disruption may have an impact on a number of
other flight operations. This connection between disruptions can be
accounted for either by formally modeling the network effects that link
flight operations, or by adding a factor for "downstream" effects.
Network effects include the impact of a reduced rate of operations at
one airport on operations at other airports, and the recognition that a
weather-related disruption at one airport, particularly an airline's
hub, can have substantial detrimental effects throughout that airline's
network. In this report, downstream effects of a flight disruption are
accounted for through a factor that is multiplied by the initial
disruption. A network model of the NAS is employed to establish support
for selecting the correct downstream effect multiplier. Additionally,
due to the importance of this factor, and the uncertainty surrounding
its proper value, the downstream factor is also included in the
sensitivity analysis.

**Methodology**

The specific value chosen for this factor has a substantial impact on
total benefits. The estimate used in this study is based on published
research[^146] [^147] and prior FAA usage[^148] of downstream effects of
delays, the single most common form of disruption. It is recognized that
such downstream factors for delays vary significantly with both the
magnitude of the original delay and the time of day at which it occurs,
with reported factors ranging from 1.0 to 13[^149]. Earlier studies have
been conducted using observed flight data covering a limited number of
flights. We sought to extend these observation-based results to a larger
fraction of all NAS flights. For this effort, the National Airspace
System Performance Analysis Capability (NASPAC) simulation model[^150]
was employed. NASPAC simulates all air traffic over the NAS including
commercial, general aviation, and military flights, with a detailed
simulation covering 80 airports. Among its inputs are flight schedules,
flight path data, ground holds, and changes in airport capacity due to
weather or other factors. Outputs of NASPAC include many detailed delay
data files which allow tracking of delay by aircraft. It should be noted
that this analysis only looked at the ripple delay associated with a
single aircraft. Thus, this result may be conservative since it does not
include the impact that the delayed aircraft has on other flights. For
example, delayed arrival of passengers, baggage, equipment, and crews
can cause delay in other flights within a carrier's network.

Three NASPAC simulations were performed for varying weather conditions,
based on actual weather observations for three days. These three days
were chosen for their range of weather-related delays reported by the
FAA's OPSNET database[^151] and included a good weather day, with
relatively few weather-related delays, an average day, and a poor
weather day. This range of input values allows the exploration of a
wider variety of NAS performance conditions, including a range of
initial delays, than would be possible by analyzing a single "typical"
day.

Arrival delay outputs of the simulation model were then analyzed. In
order to remain consistent with the calculation of downstream effect
from previous studies, the following formula was used:

![](media/image36.png){width="1.4458333333333333in"
height="0.6402777777777777in"}

where DF is the downstream factor, D~i~ is the initial delay and D~d~ is
the sum of subsequent delays.

In analyzing the data, individual aircraft were followed throughout the
day by tracking their tail numbers in NASPAC output files. Only flights
that incurred initial delays greater than 15 minutes[^152] were included
in the analysis. In calculating the downstream effect for a specific
aircraft, the initial delay used in the calculation, D~i~, was the
number of minutes of delay in the first delayed flight segment for that
particular aircraft. The downstream delay used was the sum of the number
of minutes of delay for all flight segments of that same aircraft after
the initial delay flight segment. Using this method, a DF for every
delayed aircraft was calculated.

Thus, for each delayed aircraft, values were obtained for the magnitude
of initial delay, the time of day of initial delay, and the downstream
effect factor associated with that initial delay. These results were
tabulated, following the example of Beatty *et al*, by magnitude of
initial delay and time of day. Additionally, descriptive statistics were
evaluated from the overall results, including mean and median DF.

**Results**

Previous studies[^153] have shown that the magnitude of the DF is
strongly dependent on both increased magnitude of initial delay and time
of day of the initial delay (larger factor for initial delays that occur
earlier in the day). The results of this analysis were consistent with
those findings. However, differences in DF among the three simulated
days were minimal, as increases in the number and duration of initial
delays due to the addition of bad weather to the simulation were offset
by similar increases in downstream delays, resulting in a similar
overall range of DF ratios for each simulated day. Thus, in order to
work with the richest data, the simulated day with the largest number of
delays (that is, the simulated day with the poorest weather) was
selected for further analysis. Table N1 reports DF by size of initial
delay and the time of day that the initial delay was incurred. Columns
in Table N1 represent initial delay groups of 15 to 24 minutes, 25 to 34
minutes, and so forth.

[Table N1. Downstream Factor by Initial Delay and Time of
Day]{.smallcaps}

(Blank entries indicate cells with insufficient observed delays)

<table style="width:100%;">
<colgroup>
<col style="width: 12%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 7%" />
<col style="width: 5%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 7%" />
<col style="width: 8%" />
</colgroup>
<tbody>
<tr class="odd">
<td></td>
<td colspan="13"><p><strong>INITIAL DELAY</strong></p>
<p><strong>(Minutes)</strong></p></td>
</tr>
<tr class="even">
<td><strong>TIME</strong></td>
<td><strong>15</strong></td>
<td><strong>25</strong></td>
<td><strong>35</strong></td>
<td><strong>45</strong></td>
<td><strong>55</strong></td>
<td><strong>65</strong></td>
<td><strong>75</strong></td>
<td><strong>85</strong></td>
<td><strong>95</strong></td>
<td><strong>105</strong></td>
<td><strong>115</strong></td>
<td><strong>125</strong></td>
<td><strong>135+</strong></td>
</tr>
<tr class="odd">
<td><strong>6:00</strong></td>
<td>5.1</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><strong>7:00</strong></td>
<td>9.7</td>
<td>6.1</td>
<td>10.6</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><strong>8:00</strong></td>
<td>6.3</td>
<td>6.3</td>
<td>7.0</td>
<td>6.6</td>
<td>12.8</td>
<td>12.8</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><strong>9:00</strong></td>
<td>4.5</td>
<td>5.0</td>
<td>4.0</td>
<td>5.5</td>
<td>6.1</td>
<td>7.7</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><strong>10:00</strong></td>
<td>4.4</td>
<td>3.7</td>
<td>5.3</td>
<td>6.9</td>
<td>5.0</td>
<td>3.3</td>
<td></td>
<td>4.7</td>
<td></td>
<td>4.1</td>
<td>8.1</td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><strong>11:00</strong></td>
<td>3.7</td>
<td>3.2</td>
<td>3.8</td>
<td>3.5</td>
<td>4.7</td>
<td>5.4</td>
<td>2.7</td>
<td>3.9</td>
<td>5.5</td>
<td>8.3</td>
<td>6.6</td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><strong>12:00</strong></td>
<td>3.2</td>
<td>2.8</td>
<td>3.1</td>
<td>3.2</td>
<td>4.8</td>
<td>5.5</td>
<td>5.8</td>
<td>3.0</td>
<td>2.6</td>
<td>2.7</td>
<td></td>
<td></td>
<td>6.6</td>
</tr>
<tr class="even">
<td><strong>13:00</strong></td>
<td>2.7</td>
<td>3.1</td>
<td>4.4</td>
<td>3.3</td>
<td>3.8</td>
<td>3.1</td>
<td>3.4</td>
<td>4.3</td>
<td></td>
<td>5.1</td>
<td></td>
<td></td>
<td>5.1</td>
</tr>
<tr class="odd">
<td><strong>14:00</strong></td>
<td>2.5</td>
<td>2.5</td>
<td>2.5</td>
<td>3.7</td>
<td>4.4</td>
<td>3.6</td>
<td>3.1</td>
<td>4.1</td>
<td>5.0</td>
<td>1.9</td>
<td>2.5</td>
<td>3.7</td>
<td>4.5</td>
</tr>
<tr class="even">
<td><strong>15:00</strong></td>
<td>3.0</td>
<td>2.7</td>
<td>3.0</td>
<td>3.5</td>
<td>2.6</td>
<td>3.3</td>
<td>4.3</td>
<td>2.9</td>
<td>2.9</td>
<td>3.2</td>
<td>3.8</td>
<td>2.9</td>
<td>5.1</td>
</tr>
<tr class="odd">
<td><strong>16:00</strong></td>
<td>2.5</td>
<td>2.4</td>
<td>2.6</td>
<td>3.0</td>
<td>2.9</td>
<td>2.5</td>
<td>3.4</td>
<td>3.7</td>
<td>3.1</td>
<td>2.9</td>
<td>3.0</td>
<td>3.6</td>
<td>5.2</td>
</tr>
<tr class="even">
<td><strong>17:00</strong></td>
<td>2.1</td>
<td>2.2</td>
<td>2.2</td>
<td>2.6</td>
<td>1.9</td>
<td>3.4</td>
<td>3.2</td>
<td>3.8</td>
<td>2.3</td>
<td>2.3</td>
<td></td>
<td>3.9</td>
<td>4.2</td>
</tr>
<tr class="odd">
<td><strong>18:00</strong></td>
<td>1.7</td>
<td>1.5</td>
<td>1.7</td>
<td>2.0</td>
<td>2.6</td>
<td>2.4</td>
<td>2.0</td>
<td>3.2</td>
<td>2.4</td>
<td>3.5</td>
<td>2.2</td>
<td>3.5</td>
<td>3.4</td>
</tr>
<tr class="even">
<td><strong>19:00</strong></td>
<td>1.7</td>
<td>1.5</td>
<td>1.8</td>
<td>1.6</td>
<td>1.7</td>
<td>1.9</td>
<td>2.4</td>
<td>1.8</td>
<td>3.1</td>
<td>2.5</td>
<td>4.3</td>
<td>2.0</td>
<td>2.5</td>
</tr>
<tr class="odd">
<td><strong>20:00</strong></td>
<td>1.3</td>
<td>1.3</td>
<td>1.4</td>
<td>1.5</td>
<td>1.4</td>
<td>1.6</td>
<td>1.4</td>
<td>1.4</td>
<td>2.1</td>
<td>2.1</td>
<td>1.9</td>
<td>1.7</td>
<td>2.6</td>
</tr>
<tr class="even">
<td><strong>21:00</strong></td>
<td>1.3</td>
<td>1.1</td>
<td>1.1</td>
<td>1.4</td>
<td>1.5</td>
<td>1.2</td>
<td>1.1</td>
<td>1.3</td>
<td>1.5</td>
<td>1.8</td>
<td>1.7</td>
<td>2.5</td>
<td>2.2</td>
</tr>
<tr class="odd">
<td><strong>22:00</strong></td>
<td>1.0</td>
<td>1.0</td>
<td>1.2</td>
<td>1.2</td>
<td>1.2</td>
<td>1.3</td>
<td>1.4</td>
<td>1.0</td>
<td>1.6</td>
<td>1.7</td>
<td>1.3</td>
<td>1.9</td>
<td>1.5</td>
</tr>
<tr class="even">
<td><strong>23:00</strong></td>
<td>1.1</td>
<td>1.1</td>
<td>1.0</td>
<td>1.1</td>
<td>1.0</td>
<td>1.1</td>
<td>1.1</td>
<td>1.0</td>
<td></td>
<td>1.5</td>
<td>1.2</td>
<td>1.9</td>
<td>1.5</td>
</tr>
<tr class="odd">
<td><strong>0:00</strong></td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.1</td>
<td>1.0</td>
<td>1.0</td>
<td></td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.1</td>
</tr>
<tr class="even">
<td><strong>1:00</strong></td>
<td>1.0</td>
<td>1.1</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td></td>
<td></td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
<td>1.0</td>
</tr>
<tr class="odd">
<td><strong>2:00</strong></td>
<td>1.0</td>
<td>1.0</td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td>1.0</td>
</tr>
<tr class="even">
<td><strong>3:00</strong></td>
<td> </td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="odd">
<td><strong>4:00</strong></td>
<td> </td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
<td></td>
</tr>
<tr class="even">
<td><strong>5:00</strong></td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td> </td>
<td></td>
</tr>
</tbody>
</table>

In order to determine an appropriate single value of the DF to use in
the efficiency benefits analyses, a weighted mean DF was calculated that
accounted for the time distribution of delayed air traffic arrivals, and
the magnitude of initial delays. Figure N1 shows the mean DF for each
hour of the day, and the timing of delayed air traffic arrivals reported
in the simulation outputs.

![](media/image37.wmf){width="6.897222222222222in"
height="3.6444444444444444in"}

[Figure N1. Downstream Factor and Delayed Arrivals by Time]{.smallcaps}

Finally, the mean DF for each hour was multiplied by the percentage of
delayed arrival traffic occurring during that hour for each delay group.
By using a traffic-weighted mean, a more realistic representation of the
true downstream effect of delays is achieved, and one that is applicable
to all delays, regardless of their time of occurrence. Mathematically,
this is shown as follows:

![](media/image38.png){width="1.6145833333333333in" height="0.75in"}

where DF~w~ is the weighted downstream factor, DF~tx~ is the mean
downstream factor at time t in initial delay group x, A~tx~ is the
arrival traffic at time t in delay group x, and ΣA is the sum of all
delayed arrival traffic. Note that the arrival traffic accounts only for
the number of delayed flights, not overall traffic. The resulting
weighted mean DF is 2.6.

Similarly, a weighted mean DF was calculated for use only with takeoff
disruptions, based on the time distribution of low visibility conditions
relevant to these disruptions. The resulting weighted mean DF for
takeoff disruptions is 3.7.

**Summary**

This study provides support to previous findings that a wide range of
downstream factors is possible, depending on the timing and magnitude of
the initial delay. Although this study showed that 2.6 is a reasonable
single value for this factor, given the poor weather included in the
simulation, previous similar studies have used lower values. Thus, an
intermediate value of 1.8[^154] was chosen as the primary DF for use in
the LAAS Benefits Analysis.

[]{#__RefHeading___Toc82945632 .anchor}***[Appendix O: NCDC Indicators
Used to Eliminate Severe Weather]{.smallcaps}***

[Table O1: NCDC Indicators Used to Eliminate Severe Weather]{.smallcaps}

> ![](media/image39.wmf){width="6.201388888888889in"
> height="6.1930555555555555in"}

[]{#__RefHeading___Toc82945633 .anchor}***[Appendix P:
Stakeholders]{.smallcaps}***

The IBM team wishes to recognize the following organizations and
individuals for providing their insights, constructive criticism, and
valuable comments on our LAAS benefits analysis work. Appearance on this
list is an indication that each individual was afforded an opportunity
to comment on IBM's benefits analysis approach; it does not imply
agreement with IBM's approach.

An asterisk (\*) denotes a primary Point of Contact for each
organization.

### Airport and Airline Site Visits

[Table P1:]{.smallcaps} Airport and Airline Site Visits

+----------+--------------+--------------+----------------------------+
| **Visit  | **Or         | **Contact**  | **Position**               |
| Date**   | ganization** |              |                            |
+----------+--------------+--------------+----------------------------+
| 02-      | Federal      | Cole, Ray    | Aircraft Standards         |
| Feb-2004 | Express      |              | Engineer                   |
+----------+--------------+--------------+----------------------------+
| 02-      | Federal      | Murdoch,     | \*Manager, Strategic       |
| Feb-2004 | Express      | Joel         | Projects                   |
+----------+--------------+--------------+----------------------------+
| 02-      | Federal      | Vail, Steve  | Senior Manager of Global   |
| Feb-2004 | Express      |              | Air Traffic                |
+----------+--------------+--------------+----------------------------+
| 03-      | Shelby       | White,       | \*Director of Operations   |
| Feb-2004 | County       | Walter       | and Public Safety          |
|          | Airport      |              |                            |
|          | Authority    |              |                            |
+----------+--------------+--------------+----------------------------+
| 03-      | FAA          | Wertz, Bill  | \*MEM ATCT Manager         |
| Feb-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Ackland,     | \*Senior Technical Fellow  |
| May-2004 |              | John         | -- Airplane Systems        |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Alcabin,     | Principal Engineer         |
| May-2004 |              | Monica       |                            |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Malsom, Don  | Associate Director         |
| May-2004 |              |              | Business Development --    |
|          |              |              | Air Traffic Management     |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Michael, Bob | Product Manager            |
| May-2004 |              |              |                            |
|          |              |              | Marketing & Business       |
|          |              |              | Strategy                   |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Siegmund,    | Program Manager,           |
| May-2004 |              | Paul         | Regulatory Affairs         |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Sipe, Alan   | \--                        |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 05-      | Boeing       | Tuttle, Tim  | Program Manager,           |
| May-2004 |              |              |                            |
|          |              |              | Product Development        |
+----------+--------------+--------------+----------------------------+
| 05-      | FAA          | Beckerdite,  | \*SEA TRACON Facility      |
| May-2004 |              | Ron          | Manager                    |
+----------+--------------+--------------+----------------------------+
| 05-      | Seattle      | Kikillus,    | \*SEA Operations           |
| May-2004 | Tacoma       | Rob          | Development Manager,       |
|          | Airport      |              | Airfield                   |
+----------+--------------+--------------+----------------------------+
| 05-      | FAA          | Vernon,      | \*SEA ATCT Facility        |
| May-2004 |              | Kathryn      | Manager                    |
+----------+--------------+--------------+----------------------------+
| 06-      | Alaska       | Dalton,      | \* Director of Flight      |
| May-2004 | Airlines     | Sarah        | Operations                 |
+----------+--------------+--------------+----------------------------+
| 06-      | Horizon      | Solmonson,   | \*Manager Flight           |
| May-2004 | Airlines     | Perry        | Operations Technical       |
+----------+--------------+--------------+----------------------------+
| 17-      | BDL          | Tebbetts,    | BDL Ops Manager            |
| May-2004 |              | Roland       |                            |
+----------+--------------+--------------+----------------------------+
| 17-      | FAA          | Bellabona,   | Regional SR Ops Research   |
| May-2004 |              | Joseph       | Spc/ANE 520.6              |
+----------+--------------+--------------+----------------------------+
| 17-      | FAA          | Fiske, Gary  | \*BDL Tower/TRACON         |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 17-      | FAA          | Guiod, Mark  | BDL Air Traffic Manager    |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 17-      | FAA          | Hall, David  | Flight Standards -- NE     |
| May-2004 |              | L            | Region                     |
+----------+--------------+--------------+----------------------------+
| 19-      | FAA          | Gross, Stu   | EWR ATC                    |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 19-      | FAA          | Jennings, Al | EWR ATC Manager            |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 19-      | FAA          | Sandes,      | EWR ATC                    |
| May-2004 |              | Larry        |                            |
+----------+--------------+--------------+----------------------------+
| 19-      | FAA          | Wagner, Mike | \*EWR ATC                  |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 20-      | FAA          | Kalpaxis,    | NATCA N90                  |
| May-2004 |              | Timon        |                            |
+----------+--------------+--------------+----------------------------+
| 20-      | FAA          | Moss, Patti  | \*N90 Airspace             |
| May-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 20-      | NY,NJ Port   | Gatto, Ralph | \*Senior Airport Engineer  |
| May-2004 | Authority    |              |                            |
+----------+--------------+--------------+----------------------------+
| 03-      | City of      | Foggia, John | Consultant                 |
| Jun-2004 | Chicago,     |              |                            |
|          | Dept of      |              |                            |
|          | Aviation     |              |                            |
+----------+--------------+--------------+----------------------------+
| 03-      | City of      | Santos, Joe  | \*Executive Assistant      |
| Jun-2004 | Chicago,     |              |                            |
|          | Dept of      |              |                            |
|          | Aviation     |              |                            |
+----------+--------------+--------------+----------------------------+
| 03-      | City of      | Bierbrodt,   | Consultant                 |
| Jun-2004 | Chicago,     | Jeffery      |                            |
|          | Dept of      |              |                            |
|          | Aviation     |              |                            |
+----------+--------------+--------------+----------------------------+
| 08-      | United       | Baas, Jim    | Manager, Capacity          |
| Jun-2004 | Airlines     |              | Enhancement                |
+----------+--------------+--------------+----------------------------+
| 08-      | United       | Burns, Joe   | Director, Flight Standards |
| Jun-2004 | Airlines     |              | and Technology             |
+----------+--------------+--------------+----------------------------+
| 08-      | United       | Haynes,      | Manager, Flight Operations |
| Jun-2004 | Airlines     | Brian        | Technology                 |
+----------+--------------+--------------+----------------------------+
| 08-      | United       | Holford, Tom | Manager, Navigation        |
| Jun-2004 | Airlines     |              | Upgrades                   |
+----------+--------------+--------------+----------------------------+
| 08-      | United       | Stone, Rocky | \*Manager, Flight Systems  |
| Jun-2004 | Airlines     |              | Technology                 |
+----------+--------------+--------------+----------------------------+
| 08-      | ATNSI        | Murphy, Mike | \*Consultant               |
| Jun-2004 |              |              |                            |
+----------+--------------+--------------+----------------------------+
| 17-      | Continental  | Vaughn, Bill | \*Manager Advanced         |
| Jun-2004 | Airlines     |              | Navigation                 |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Crum, Greg   | Vice President Flight      |
| Jun-2004 | Airlines     |              | Operations and Chief Pilot |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Edens, Dave  | Chief Pilot                |
| Jun-2004 | Airlines     |              |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Gleason,     | \* Director, Flight        |
| Jun-2004 | Airlines     | Brian        | Operations Technical       |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Haynes, Rob  | Regional Chief Pilot       |
| Jun-2004 | Airlines     |              |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Humphrey,    | Pilot                      |
| Jun-2004 | Airlines     | Stan D.      |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Johns, Frank | Air Traffic Coordinator    |
| Jun-2004 | Airlines     |              |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Mullis, Phil | Air Traffic Coordinator    |
| Jun-2004 | Airlines     |              |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Stephens,    | Senior Financial Planning  |
| Jun-2004 | Airlines     | Jon          | Analyst                    |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Ward, Edward | Manager, Navigation Data   |
| Jun-2004 | Airlines     | T.           |                            |
+----------+--------------+--------------+----------------------------+
| 21-      | Southwest    | Wiecek,      | Flight Operations Engineer |
| Jun-2004 | Airlines     | Kevin        |                            |
+----------+--------------+--------------+----------------------------+

### 

###  

### Federal Aviation Administration (FAA)

The following individuals from the FAA, listed in alphabetical order by
organization, provided subject matter expertise, data and valuable
feedback:

[Table P2: FAA Stakeholders]{.smallcaps}

+----------------------+----------------+------------------------------+
| **Organization**     | **Contact**    | **Position**                 |
+----------------------+----------------+------------------------------+
| FAA, AFS-430         | Jarvis, Ed     | Flight Standards             |
+----------------------+----------------+------------------------------+
| FAA, AIR-130         | Abduselam,     | Certification                |
|                      | Hamza          |                              |
+----------------------+----------------+------------------------------+
| FAA, AIR-130         | DeCleene,      | Certification                |
|                      | Bruce          |                              |
+----------------------+----------------+------------------------------+
| FAA, AOP-200/ATO-W   | Tran, Deborah  | NASPAS Program               |
+----------------------+----------------+------------------------------+
| FAA, ARN-100         | Williams,      |                              |
|                      | Ammyanna       |                              |
+----------------------+----------------+------------------------------+
| FAA, ATO-R           | MacNeill, Ken  | AT Requirements              |
+----------------------+----------------+------------------------------+
| FAA, ATO-W           | Peterson, Dave | OIT Team Lead                |
+----------------------+----------------+------------------------------+
| FAA, ATO-W           | Bell, Hal      | WAAS PT Lead                 |
+----------------------+----------------+------------------------------+
| FAA, ATO-W/AMTI      | Noto, John     | WAAS Task Lead               |
+----------------------+----------------+------------------------------+
| FAA, ATO-W/ESC/ARINC | Packard,       | JPALS Liaison                |
|                      | Richard        |                              |
+----------------------+----------------+------------------------------+
| FAA, ATO-W/ISI       | Lay, Richard   | LAAS System Engineer         |
+----------------------+----------------+------------------------------+
| FAA, Navigation      | Rixmann, Gary  | (former MLS Contract         |
| Services, ATO-W      |                | Technical Officer)           |
|                      |                |                              |
|                      |                | Lighting Systems Office      |
+----------------------+----------------+------------------------------+

### MITRE/CAASD

The following individuals from MITRE/CAASD, listed in alphabetical order
by last name, provided subject matter expertise, tools, data and
valuable feedback:

[Table P3: MITRE/CAASD Subject Matter Experts]{.smallcaps}

  ------------------ ---------------- ------------------------------------
  **Organization**   **Contact**      **Position**

  MITRE/CAASD        Barrer, John     Lead Engineer

  MITRE/CAASD        Markin, Kelly    Program Manager

  MITRE/CAASD        Massimini, Vince Senior Principal Engineer

  MITRE/CAASD        Scales, Walt     Project Team Manager

  MITRE/CAASD        Swedish, William Principal Engineer
  ------------------ ---------------- ------------------------------------

### Conference Calls with Major Airline Representatives 

The following individuals, listed in alphabetical order by organization,
participated in discussions of the LAAS Benefits Analysis:

[Table P4: LAAS Benefits Discussion Airline Representative
Participants]{.smallcaps}

  ------------------------------------------------------------------------------------------------------------- ---------------- ------------------------------------
  **Organization**                                                                                              **Contact**      **Position**

  Alaska Airlines                                                                                               Dalton, Sarah    Director of Flight Operations

  [American Trans                                                                                               Enias, James     Technical Pilot
  Air](http://rds.yahoo.com/S=2766679/K=ATA+Airlines/v=2/SID=e/l=WS1/R=1/SS=4287501/H=0/*-http:/www.ata.com/)                    

  Boeing                                                                                                        Ackland, John    Senior Technical Fellow Airline
                                                                                                                                 System

  Continental Airlines                                                                                          Vaughn, Bill     Captain, Flight Technical

  Delta Airlines                                                                                                Speir, Ken       Fleet Technical Pilot

  Federal Express                                                                                               Murdock, Joel    Manager, Strategic Projects

  Honeywell                                                                                                     Hoodspith, Mike  Manager, Satellite Landing Systems,
                                                                                                                                 Commercial Products, Asia, Latin
                                                                                                                                 America & Western U.S.

  Horizon Airlines                                                                                              Bush, Steve      Flight Ops Technical

  JetBlue Airways                                                                                               Somerville,      Captain, GPS/RNAV Subject Matter
                                                                                                                Donald           Specialist

  Northwest Airlines                                                                                            Alexander, Frank Chief Pilot Technical Programs

  Southwest Airlines                                                                                            Gleason, Brian   Director, Flight Operations
                                                                                                                                 Technical

  United Airlines                                                                                               Stone, Rocky     Manager of Flight Systems Technology

  United Parcel Service                                                                                         Hilb, Bob        Manager of Advanced Flight Systems
  ------------------------------------------------------------------------------------------------------------- ---------------- ------------------------------------

### GBAS FAA-Europe Coordination Meeting, April 2004

The following meeting participants provided subject matter expertise,
data and valuable feedback:

[Table P5: GBAS FAA-Europe Subject Matter Experts]{.smallcaps}

  ------------------ ------------------ ---------------------------------
  **Organization**   **Contact**        **Position**

  EUROCONTROL        Grand-Perret,      \*Expert -- Navigation
                     Sylvie             

  SKYGUIDE           Berz, Gerhard      \*System Engineer, Satellite
                                        Navigation

  SOFREAVIA          De La Burgade,     Consulting Division, Project
                     Olivier            Manager
  ------------------ ------------------ ---------------------------------

# [Notes and References]{.smallcaps}

[^1]: ^See\ Appendix\ A\ for\ the\ selection\ criteria,\ as\ well\ as\ a\ listing\ and\ map\ of\ these\ 121\ airports.^

[^2]: ^Rovinsky,\ Dr.\ Robert.\ (1999,\ September\ 25).\ Satellite\ Navigation\ Investment\ Analysis\ Report.\ Federal\ Aviation\ Administration,\ 1-129.\ Retrieved\ May\ 18,\ 2004\ from\ World\ Wide\ Web:\ (http://www.faa.gov/asd/satnav/fullyrelease.pdf).^

[^3]: ^Gustafson,\ David\ M.,\ Smith,\ Alexander\ E.,\ Cassell,\ Rick.\ (October\ 1998).\ Cost\ Benefit\ Analysis\ of\ the\ Combined\ WAAS/LAAS\ System.\ AIAA\ Digital\ Avionics\ Systems\ Conference,\ 1-8.\ Retrieved\ May\ 18,\ 2004\ from\ World\ Wide\ Web:\ (http://www.aviationtoday.com/reports/costbenefit.pdf)^

[^4]: ^Prabhakar,\ Anand\ S.\ (1996).\ Economic\ Analysis\ of\ Local\ Area\ Augmentation\ System\ and\ Alternative\ Architectures\ (Rep.\ No.\ A560803).\ Massachusetts:\ Transportation\ Systems\ Center.^

[^5]: ^No\ Author.\ (1997).\ Local\ Area\ Augmentation\ System\ Cost\ Savings\ Potential.\ Washington,\ DC:\ Air\ Transport\ Association.^

[^6]: ^LAAS\ Benefits\ Analysis\ -\ Executive\ Summary\ of\ the\ Navigation\ Capabilities\ Baseline,\ IBM\ Corporation,\ November\ 2003.^

[^7]: ^LAAS\ Benefits\ Analysis\ -\ Executive\ Summary\ of\ the\ LAAS\ Incremental\ Capabilities,\ IBM\ Corporation,\ December\ 15,\ 2003.^

[^8]: ^FAA,\ Williams,\ Ammyanna;\ ARN-100.\ Jan\ 2004.\ National\ ILS\ Prioritized\ List.xls\ inlcuded\ in\ Jim\ Hanrahan\'s\ \"LAAS\ CAT\ I/II/III\ Airport\ Selection\ Meeting\ Minutes\"^

[^9]: ^No\ Author.\ (2004,\ March).\ FAA\ Aerospace\ Forecast\ 2004-2015.\ Federal\ Aviation\ Administration,\ Chapter\ 1.\ http://www.api.faa.gov/foreca03/start.htm^

[^10]: ^a)\ Beatty,\ R.,\ Hsu,\ R.,\ Berry,\ L,\ and\ Rome,\ J.\ (Dec.\ 1998)\ Preliminary\ Evaluation\ of\ Flight\ Delay\ Propagation\ Through\ an\ Airline\ Schedule;\ 2nd\ USA/Europe\ Air\ Traffic\ Management\ R&D\ Seminar.^

    ^b)\ Rome,\ J,\ Rose,\ S,\ Lee,\ R,\ Cistone,\ J,\ Bell,\ G.,\ Leber,\ W.\ (undated)\ Ripple\ Delay\ and\ Its\ Mitigation.^

    ^c)\ No\ Author,\ Nov\ 2003,\ Investment\ Analysis\ Benefit\ Guidelines:\ Quantifying\ Benefits\ from\ Projected\ Reductions\ in\ National\ Airspace\ System\ Equipment\ Outages;\ FAA\ ASD-430;\ Appendix\ A,\ p.\ A-3.^

    ^d)\ Welch,\ Andrews\ and\ Robinson,\ Aug\ 2001,\ Assessing\ Delay\ Benefits\ of\ the\ Final\ Approach\ Spacing\ Tool,\ MIT\ Lincoln\ Labs,\ and\ NASA\ Ames\ Research\ Center,\ presented\ at\ the\ AAIA\ Guidance,\ Navigation\ and\ Control\ Conference,\ Aug\ 2001.^

[^11]: ^No\ Author.\ (1992,\ October\ 29).\ Guidelines\ and\ Discount\ Rates\ for\ Benefit-Cost\ Analysis\ of\ Federal\ Programs.\ Office\ of\ Management\ and\ Budget^

[^12]: ^See\ Appendix\ J\ for\ a\ listing\ of\ LAAS\ Benefits\ by\ User\ Group\ and\ by\ Airport.^

[^13]: ^See\ Appendix\ F.^

[^14]: ^Hawkins,\ Joseph\ A.\ (1983,\ September).\ Establishment\ and\ Discontinuance\ Criteria\ for\ Precision\ Landing\ Systems.\ US\ Department\ of\ Transportation\ and\ The\ Federal\ Aviation\ Administration,\ 1-102.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web:\ http://api.hq.faa.gov/precision%20landing%20systems/Precision%20Landing%20Systems.pdf^

[^15]: ^Haro,\ Pablo;\ Mateo,\ Mariluz\ de;\ Andrada,\ Luis.\ (1998,\ October\ 7).\ Methodology\ and\ Quantification\ of\ Several\ EGNOS\ Operational\ Benefits.\ Ministry\ of\ Public\ Works\ and\ the\ Economy,\ 1-6.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web^.

    ^http://www.mfom.es/aviacioncivil/programas/egnos_html/cba.doc^

[^16]: ^See\ for\ example:\ a)\ Pervan,\ Boris;\ Lawrence,\ David;\ Gromov,\ Konstantin.\ (1998,\ March\ 19).\ Flight\ Test\ Evaluation\ of\ a\ Prototype\ Local\ Area\ Augmentation\ System\ Architecture.\ Department\ of\ Aeronautics\ and\ Astronautics,^

    ^1-9.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web:\ <http://waas.stanford.edu/~wwu/papers/gps/PDF/flight_eval_laas_bsp97.pdf>^

    ^b)\ Hammer,\ Jonathan.\ (2000).\ Case\ Study\ of\ Paired\ Approach\ Procedure\ to\ Closely\ Spaced\ Parallel\ Runways.\ The\ MITRE\ Corporation,\ 223-252.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web:^

    ^http://www.mitre.org/work/best_papers/best_papers_00/hammer_casestudy/hammer_casestudy.pdf^

[^17]: ^http://www.transtats.bts.gov/^

[^18]: ^http://www.faa.gov/ats/asc/capacity.html^

[^19]: ^Hawkins,\ Joseph\ A.\ (1983).\ Establishment\ and\ Discontinuance\ Criteria\ for\ Precision\ Landing\ Systems\ (Rep.\ No.\ FAA-APO-83-10).\ Washington,\ DC:\ Federal\ Aviation\ Administration.^

[^20]: ^Prabhakar,\ Anand\ S.\ (1996).\ Economic\ Analysis\ of\ Local\ Area\ Augmentation\ System\ and\ Alternative\ Architectures\ (Rep.\ No.\ A560803).\ Massachusetts:\ Transportation\ Systems\ Center.^

[^21]: ^FAA\ Aviation\ Policy\ and\ Plans;\ Airway\ Planning\ Standard\ Number\ One\ Terminal\ Air\ Navigation\ Facilities\ and\ Air\ Traffic\ Control\ Services:\ http://apo.faa.gov/7031/7031.pdf^

[^22]: ^NCDC\ data\ provided\ by\ ASD-400.^

[^23]: ^For\ FedEx's\ Memphis\ hub\ and\ UPS's\ Louisville\ hub,\ the\ entire\ 24\ hour\ time\ period\ was\ used\ since\ they\ have\ continual\ traffic\ throughout\ the\ night.^

[^24]: ^Details\ of\ the\ derivation\ of\ disruption\ costs\ are\ in\ Appendix\ C.^

[^25]: ^The\ period\ from\ 9/11/01\ through\ 12/31/01\ was\ omitted.^

[^26]: ^No\ Author.\ (1992,\ October\ 29).\ Guidelines\ and\ Discount\ Rates\ for\ Benefit-Cost\ Analysis\ of\ Federal\ Programs.\ Office\ of\ Management\ and\ Budget.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web:^

    ^http://www.whitehouse.gov/omb/circulars/a094/a094.html#7^

[^27]: ^For\ a\ discussion\ of\ the\ impact\ of\ severe\ weather\ on\ airline\ operations,\ see\ for\ example,\ Zalman,\ Shavell\ A.\ (2000,\ April\ 15).\ The\ Effects\ of\ Schedule\ Disruptions\ on\ the\ Economics\ of\ Airline\ Operations.\ The\ MITRE\ Corporation,\ 1-11.\ Retrieved\ May\ 18,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.mitre.org/work/tech_papers/tech_papers_00/shavell_effects/shavell_effects.pdf^

[^28]: ^For\ details\ see\ FAA\ Advisory\ Circulars\ 120-29A,\ 120-28D;\ FAA\ Order\ 8400.10^

[^29]: ^See\ Appendix\ E\ for\ a\ description\ of\ how\ total\ demand\ is\ estimate.^

[^30]: ^Capacity\ data\ was\ made\ available\ to\ IBM\ by\ the\ FAA's\ ASD-400^

[^31]: ^See\ Appendix\ E\ for\ a\ description\ of\ how\ a\ "typical"\ day's\ traffic\ is\ estimated^

[^32]: ^See\ Appendix\ E\ for\ a\ description\ of\ the\ Single\ Airport\ Delay\ Model.^

[^33]: ^See\ Appendix\ C.^

[^34]: ^Boeing\ (RNP\ Capability\ of\ the\ FMC-Equipped\ 737,\ Generation\ 3,\ Figure\ 6.1-1)^

[^35]: ^Becher,\ T.;\ Formosa,\ J.\ (2000,\ June\ 16).\ RNAV\ Near-Term\ Terminal\ Procedures\ Development.\ Center\ for\ Advanced\ Aviation\ System\ Development,\ 1-11.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:^

    ^http://www.mitrecaasd.org/library/presentations/becher.pdf^

[^36]: ^Hoitomt,\ Debra;\ Dareing,\ Stephen;\ Tang,\ Baoxing.\ (No\ Date\ Given).\ Traffic\ Management\ and\ Airline\ Operations.\ United\ Airlines\ Research\ Center,\ 1-3.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:^

    ^http://icat-server.mit.edu/\~fcarr/ACC2002/Abstracts/UAL_Hoitomt.pdf^

[^37]: ^Knorr,\ David.\ (2000,\ June\ 16).\ The\ Operational\ Assessment\ of\ Free\ Flight\ Phase\ 1\ ATM\ Capabilities.\ Free\ Flight\ Phase\ 1\ Program\ Office,\ 1-9.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.mitrecaasd.org/library/presentations/blucher.pdf^

[^38]: ^See\ for\ example:\ a)\ Testimony\ before\ the\ Aviation\ Subcommittee\ of\ the\ House\ Committee\ on\ Transportation\ and\ Infrastructure,\ (1999,\ October\ 14).\ http://www.house.gov/transportation/aviation/hearing/10-14-99/chew.html^

    ^b)\ No\ Author.\ (1998,\ November\ 18).\ All-Airline\ Meeting.\ CNS/ATM\ Focused\ Team\ (C/AFT),\ 1-24.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.boeing.com/commercial/caft/reference/meetings/98_11_18/01_atspfg.pdf^

    ^c)\ Pepper,\ Joshua\ W.;\ Mills,\ Kristine\ R.;\ Wojcik,\ Leonard\ A.\ (2003,\ June\ 27).\ Predictability\ and\ Uncertainty\ in\ Air\ Traffic\ Flow\ Management.\ Center\ for\ Advanced\ Aviation\ System\ Development\ (CAASD),\ 1-10.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ <http://www.mitrecaasd.org/library/presentations/atm2003/atm2003_paper45.pdf>^

    ^d)\ this\ benefit\ has\ also\ been\ strongly\ substantiated\ in\ IBM's\ interviews\ with\ airline\ stakeholders.^

[^39]: ^No\ Author.\ (2003,\ September\ 11).\ FAA\ Flight\ Plan\ 2004-2008.\ Federal\ Aviation\ Administration,\ 31.\ Retrieved\ May\ 19,\ 2004\ from\ World\ Wide\ Web:\ http://www.faa.gov/apo/strategicplan/FAA_Flight_Plan.pdf^

[^40]: ^(25\ Feb,\ 2004)\ IBM\ LAAS\ Benefits\ Analysis\ --\ Preliminary\ Findings.^

[^41]: ^No\ Author.\ (No\ Date\ Given).\ Section\ 6.\ Holding\ Aircraft.\ Federal\ Aviation\ Administration.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.faa.gov/ATPUBS/ATC/Chp4/atc0406.html^

[^42]: ^Interview\ with\ a\ major\ carrier\ produced\ the\ estimate\ of\ 2\ minutes\ to\ taxi\ 1500\ ft^

[^43]: ^No\ Author.\ (No\ Date\ Given).\ Section\ 3.\ Wake\ Turbulence.\ Federal\ Aviation\ Administration.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www2.faa.gov/ATpubs/AIM/Chap7/aim0703.html^

[^44]: ^Odoni,\ Amedeo\ R.,\ Rousseau,\ Jean-Marc,\ and\ Wilson,\ Nigel\ (1994).\ Models\ in\ Urban\ and\ Air\ Transportation.\ Amsterdam:\ Elsevier\ Science\ Publishers.^

[^45]: ^See\ Appendix\ E\ for\ a\ description\ of\ how\ a\ "typical"\ day's\ traffic\ is\ estimated.^

[^46]: ^See\ Appendix\ C.^

[^47]: ^Estimated\ to\ be\ 30\ departures\ per\ hour,\ based\ on\ theoretical\ models\ and\ comparison\ to\ similar\ runways\ at\ other\ airports.^

[^48]: ^Discounted\ 20\ year\ benefit\ for\ the\ scenario\ in\ which\ all\ users\ equip\ with\ WAAS\ is\ \$2.5M\ for\ Airline\ Direct\ Operating\ Costs\ and\ \$2.8M\ for\ Passenger\ Value\ of\ Time.^

[^49]: ^Egan,\ Paul.\ (2001,\ February\ 27).\ New\ radar\ would\ speed\ airport\ traffic.\ The\ Detroit\ News.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.detnews.com/2001/metro/0102/27/d01-193153.htm^

[^50]: ^Houck,\ Sharon;\ Barrows,\ Andrew;\ Parkinson,\ Bradford;\ Enge,\ Per;\ Powell,\ J.\ David.\ (1999).\ Flight\ Testing\ WAAS\ for\ Use\ in\ Closely\ Spaced\ Parallel\ Approaches.\ Department\ of\ Aeronautics\ and\ Astronautics,\ Stanford\ University,\ 1-12.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://waas.stanford.edu/\~wwu/papers/gps/PDF/sharonparallel.pdf^

[^51]: ^Houck,\ Sharon;\ Powell,\ J.\ David.\ (2001).\ Assessment\ of\ the\ Probability\ of\ a\ Midair\ Collision\ during\ an\ Ultra\ Closely\ Spaced\ Parallel\ Approach.\ Department\ of\ Aeronautics\ and\ Astronautics,\ Stanford\ University,\ 1-11.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://waas.stanford.edu/\~wwu/sharon/briefs/gncpaper01.pdf^

[^52]: ^Houck,\ Sharon.\ (2001,\ April).\ Multi\ Aircraft\ Dynamics,\ Navigation\ and\ Operation.\ The\ Department\ of\ Aeronautics\ and\ Astronautics\ and\ the\ Committee\ on\ Graduate\ Studies\ of\ Stanford\ University,\ 1-141.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://waas.stanford.edu/\~wwu/sharon/briefs/sharonthesis01.pdf^

[^53]: ^Ashford,\ Rose.\ (1998,\ December\ 24).\ Closely\ Spaced\ Parallel\ Approaches.\ NASA\ Ames\ Research\ Center.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.asc.nasa.gov/tap/cspa/cspa.html^

[^54]: ^Elliott\ Dawn\ M.\ and\ Perry\ R.\ Brad.\ (2000,\ August14-17).\ NASA\ Research\ for\ Instrument\ Approaches\ to\ Closely\ Spaced\ Parallel\ Runways.\ NASA,\ 1-8.\ Retrieved\ June\ 2,\ 2004\ from\ the\ World\ Wide\ Web:\ http://techreports.larc.nasa.gov/ltrs/PDF/2000/aiaa/NASA-aiaa-2000-4358.pdf^

[^55]: ^Ashford,\ Rose.\ (2002,\ September\ 11).\ Closely-Spaced\ Parallel\ Approaches.\ NASA,\ 1-21.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://human-factors.arc.nasa.gov/ihi/personnel/ashford/CSPA20D.pdf^

[^56]: ^Eurocontrol.\ (2003,\ May\ 2).\ GBAS\ Roadmap.\ EUROCONTROL,\ 1-6.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:^

    ^http://www.eurocontrol.fr/projects/sbas/Library/gwg7/GWG-7_IP1_GNSS.4WP.yy2_v1.0.pdf^

[^57]: ^Eurocontrol,\ "Benefit\ Estimation\ of\ GBAS\ for\ Simultaneous\ Independent\ Operations\ for\ Closely\ Spaced\ Parallel\ Runways\ in\ ECAC"^

[^58]: ^Eurocontrol,\ Executive\ Summaries\ of\ ECAC\ Precision\ Approach\ and\ Landing\ Task\ Force\ (EPAL)\ Activities\ in\ Close\ Relation\ to\ GBAS,\ Joint\ EPAL/GWG\ meeting,\ February\ 3,\ 2004.^

[^59]: ^Shank,\ E.\ M.;\ Hollister,\ K.\ M.\ (1994).\ Precision\ Runway\ Monitor.\ Lincoln\ Laboratory\ Journal,^

    ^Vol.\ 7,\ No.\ 2.^

[^60]: ^Haines,\ Dr.\ A.\ L.;\ Swedish,\ W.\ J.\ (1981).\ Requirements\ for\ Independent\ and\ Dependent\ Parallel\ Instrument\ Approaches\ at\ Reduced\ Runway\ Spacing\ (Rep.\ No.\ MTR-81W15).\ Virginia:\ The\ MITRE\ Corporation.^

[^61]: ^Bone,\ R.;\ Olmos,\ O.;\ Mundra,\ A.\ (2001).\ Paired\ Approach:\ A\ Closely\ Spaced\ Parallel\ Runway\ Approach\ Concept\ (Rep.\ No.\ MP-01W0000046).\ Virginia:\ The\ MITRE\ Corporation.^

[^62]: ^Higgins,\ M.\ K.\ (1994).\ Evidence\ for\ Parallel\ Approach\ Blunders\ in\ the\ National\ Airspace\ System\ Incident\ Monitoring\ System\ (NAIMS).\ (Rep.\ No.\ MP-94W000076).\ Virginia:\ The\ MITRE\ Corporation.^

[^63]: ^Monaco,\ Nadine.\ (2003,\ September).\ New\ Performance-based\ Navigation\ Standards\ Encourage\ Increased\ Flexibility\ and\ Safety\ in\ the\ Skies.\ Federal\ Aviation\ Administration.\ Retrieved\ June\ 2,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.mitre.org/news/digest/aviation/09_03/a_nrp.html^

[^64]: ^Mundra,\ Anand,\ D.,\ Cooper,\ Wayne\ W.,\ Levy,\ Benjamin\ S.,\ Lunsford,\ Clark\ R.,\ Smith,\ Arthur\ P.,\ Tittsworth,\ Jeffrey\ A.\ and\ Lang,\ Steven.\ (2003,\ June\ 23-27).\ A\ Phased\ Approach\ to\ Increase\ Airport\ Capacity\ Through\ Safe\ Reduction\ of\ Existing\ Wake\ Turbulence\ Constraints.\ The\ MITRE\ Corporation.\ Retrieved\ June\ 2,\ 2004\ from\ the\ World\ Wide\ Web:\ http://atm2003.eurocontrol.fr/slides/airport/6_85_Cooper.ppt^

[^65]: ^Houck,\ Sharon;\ Barrows,\ Andrew;\ Parkinson,\ Bradford;\ Enge,\ Per;\ Powell,\ J.\ David.\ (1999).\ Flight\ Testing\ WAAS\ for\ Use\ in\ Closely\ Spaced\ Parallel\ Approaches.\ Department\ of\ Aeronautics\ and\ Astronautics,\ Stanford\ University,\ 1-12.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://waas.stanford.edu/\~wwu/papers/gps/PDF/sharonparallel.pdf^

[^66]: ^Salvano,\ D.\ (2003,\ August\ 12).\ ADS-B\ within\ the\ Safe\ Flight\ 21\ Program.\ Federal\ Aviation\ Administration.\ Retrieved\ June\ 2,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.faa.gov/And/AND500/docmgr/docs/T0276.ppt^

[^67]: ^No\ Author.\ (No\ Date\ Given).\ 2002\ Aviation\ Capacity\ Enhancement\ Plan.\ Federal\ Aviation\ Administration.\ Retrieved\ June\ 2,\ 2004\ from\ the\ World\ Wide\ Web:\ http://www.faa.gov/ats/asc/02ACE.html^

[^68]: ^FAA\ (2001)\ Airport\ Capacity\ Benchmark\ Report\ 2001^

[^69]: ^For\ a\ description\ of\ this\ model,\ please\ see\ Appendix\ E.^

[^70]: ^See\ Appendix\ E\ for\ a\ description\ of\ how\ a\ representative\ traffic\ day\ was\ estimated^

[^71]: ^Number\ derived\ from\ the\ following\ FAA\ website\ (<http://www.api.faa.gov/strategic/docs/sup-sys-40-arpaccessgoal.html>).^

[^72]: ^[FAA\ Navigation\ &\ Landing\ Transition\ Strategy\ Report](http://www1.faa.gov/asd/briefings/NavReport8-02.pdf)\ (http://www1.faa.gov/asd/briefings/NavReport8-02.pdf).^

[^73]: ^Khatwa\ R,\ Helmreich\ R,\ Analysis\ of\ Critical\ Factors\ During\ Approach\ and\ Landing\ in\ Accidents\ and\ Normal\ Flight,\ Flight\ Safety\ Digest,\ Volume\ 17,\ No\ 11-12,\ Flight\ Safety\ Foundation,\ Alexandria,\ VA,\ pg\ 80.^

[^74]: ^Enders\ et\ al,\ Airport\ Safety:\ A\ Study\ of\ Accidents\ and\ Available\ Approach-and-landing\ Aids,\ Flight\ Safety\ Digest,\ Flight\ Safety\ Foundation,\ Alexandria,\ VA.,\ March\ 1996.^

[^75]: ^Nordwall\ B\ D,\ U.S.\ Changing\ to\ One\ Type\ of\ Instrument\ Approach,\ Aviation\ Week\ and\ Space\ Technology,\ July\ 8th,\ 2002\ pg\ 45-46.^

[^76]: ^FAA.\ (2002).\ The\ National\ Aviation\ Safety\ Data\ Analysis\ Center.\ (https://extranet.nasdac.faa.gov)^

[^77]: ^Statistical\ Package\ for\ the\ Social\ Sciences.^

[^78]: ^NTSB\ accident\ briefs\ can\ be\ obtained\ at\ the\ NTSB's\ web\ site\ (http://www.ntsb.gov/ntsb/query.asp).^

[^79]: ^Remarks\ for\ the\ Honorable\ Norman\ Y.\ Mineta\ Secretary\ of\ Transportation.\ (January\ 27,\ 2004).\ Securing\ America's\ Place\ as\ Global\ Leader\ in\ Aviation's\ Second\ Century\ (http://www.jpo.aero/mineta%20speech%20012704.pdf).^

[^80]: ^FAA\ Flight\ Plan\ 2004-2008,\ p34;\ (http://www2.faa.gov/apo/strategicplan/FAA_Flight_Plan.pdf).^

[^81]: ^ICASC\ --\ Local\ Area\ Augmentation\ System,\ (http://avnwww.jccbi.gov/icasc/gnss_laas.html).^

[^82]: ^FAA.\ (June\ 2003).\ Flight\ Schedule\ Data\ Systems\ (FSDS),\ In\ June\ 2003\ there\ were\ 182\ foreign\ airports\ with\ scheduled\ arrivals\ from\ a\ domestic\ carrier,\ (http://www.apo.data.faa.gov/).^

[^83]: ^AIN\ Online.\ (2002).\ Europeans\ Embrace\ MLS\ with\ a\ vengeance.\ (http://www.ainonline.com/issues/04_01/Apr_2001_europeanmlspg75.html).^

[^84]: ^Estimated\ using\ FAA./APO.\ FSDS.\ (http://www.apo.data.faa.gov).^

[^85]: ^FAA's\ Office\ of\ Environment\ and\ Energy\ Noise\ Division;\ (http://www.aee.faa.gov/noise/Aircraft_Noise.htm).^

[^86]: ^US\ DoT.\ (Thursday,\ April\ 22,\ 2004).\ U.S.\ DOT\ Commemorates\ Earth\ Day\ with\ Announcement\ of\ \$307\ Million\ Effort\ to\ Combat\ Noise\ Pollution\ Near\ Airports.\ (<http://www.dot.gov/affairs/dot5404.htm>).^

[^87]: ^Leqve,\ Chad\ E.,\ Manager,\ MSP\ Aviation\ Noise\ &\ Satellite\ Programs\ (Oct\ 1,\ 2003).\ Minneapolis/St.\ Paul\ International\ Airport\ GPS/LAAS\ Initiatives.\ GBAS/LAAS\ User\ Group\ Meeting.^

[^88]: ^Chicago\ Department\ of\ Aviation.\ (1996).\ ORD\ Noise\ Mitigation\ Program.\ (http://www.flychicago.com/cnrc/cnrc.shtm).^

[^89]: ^Boeing\ Airport\ Noise\ Regulations;\ DEN;\ (http://www.boeing.com/commercial/noise/denver.html).^

[^90]: ^Boeing\ Airport\ Noise\ Regulations;\ BOS;\ (http://www.boeing.com/commercial/noise/logan.html).^

[^91]: ^U.S.\ GAO,\ Aviation\ and\ the\ Environment,\ FAA's\ Role\ in\ Major\ Noise\ Programs\ (http://www.transource.org/Shared_files/gaonoise.pdf)^

[^92]: ^Airport\ Report\ Express,\ Vol\ 6,\ No.\ 77,\ Sept\ 23,\ 1996:\ California\ Airports\ Gain\ \$84\ Million\ (http://www.airportnet.org/depts/publications/express/1996HTM/9-23-96.htm)^

[^93]: ^Airport\ Report\ Express,\ Vol\ 6,\ No.\ 77,\ Sept\ 23,\ 1996:\ California\ Airports\ Gain\ \$84\ Million.\ (http://www.airportnet.org/depts/publications/express/1996HTM/9-23-96.htm)^

[^94]: ^Airport\ Report\ Express,\ Vol\ 6,\ No.\ 77,\ Sept\ 23,\ 1996:\ California\ Airports\ Gain\ \$84\ Million.\ (http://www.airportnet.org/depts/publications/express/1996HTM/9-23-96.htm)^

[^95]: ^NY\ State\ 2003\ Annual\ Report\ Aviation\ Section\ 5:\ Airport\ Funding:\ Table\ I\ --\ AIR\ '99\ Aviation\ Grant\ Status\ Report\ (http://www.dot.state.ny.us/pubtrans/files/2003_annual_report_aviation_sect5.pdf)^

[^96]: ^NY\ State\ 2003\ Annual\ Report\ Aviation\ Section\ 5:\ Airport\ Funding:\ Table\ I\ --\ AIR\ '99\ Aviation\ Grant\ Status\ Report\ (http://www.dot.state.ny.us/pubtrans/files/2003_annual_report_aviation_sect5.pdf)^

[^97]: ^NY\ State\ 2003\ Annual\ Report\ Aviation\ Section\ 5:\ Airport\ Funding:\ Table\ I\ --\ AIR\ '99\ Aviation\ Grant\ Status\ Report\ (http://www.dot.state.ny.us/pubtrans/files/2003_annual_report_aviation_sect5.pdf)^

[^98]: ^Airport\ Report\ Express,\ Apr\ 29,\ 1998:\ Illinois\ Airports\ Receive\ AIP\ Grants\ (http://www.airportnet.org/depts/publications/express/1998HTM/4-29-98.htm)^

[^99]: ^Airport\ Report\ Express,\ Apr\ 29,\ 1998:\ Illinois\ Airports\ Receive\ AIP\ Grants\ (http://www.airportnet.org/depts/publications/express/1998HTM/4-29-98.htm)^

[^100]: ^Airport\ Report\ Express,\ Vol\ 6,\ No.\ 77,\ Sept\ 23,\ 1996:\ California\ Airports\ Gain\ \$84\ Million\ (http://www.airportnet.org/depts/publications/express/1996HTM/9-23-96.htm)^

[^101]: ^Denver\ Must\ Pay\ County\ Four\ Million\ for\ Airport\ Noise\ (http://www.netvista.net/\~hpb/news/oct-30.html)^

[^102]: ^Florida\ Landowners\ Must\ Prove\ Decreased\ Property\ Value\ in\ Airport\ Noise\ Suit\ (http://www.netvista.net/\~hpb/news/apr-3.html)^

[^103]: ^Lawyers\ Hired\ to\ Fight\ Noise\ at\ Newark\ International\ Airport\ (http://www.netvista.net/\~hpb/news/mar-20a.html)^

[^104]: ^Court\ Lets\ City\ Go\ to\ Trial\ on\ Noise\ Impact\ Issue\ (http://www.netvista.net/\~hpb/news/feb-24.html)^

[^105]: ^Memphis\ Airport\ Authority\ Votes\ to\ Settle\ Class-Action\ Noise\ Lawsuit\ (http://www.netvista.net/\~hpb/news/june27.html)^

[^106]: ^Minnesota\ City\ Sues\ Airport\ Commission\ Over\ Shifting\ Jet\ Noise\ to\ Their\ Community^

    ^(http://www.netvista.net/\~hpb/news/june-11.html)^

[^107]: ^More\ Schools\ to\ Be\ Insulated\ As\ a\ Result\ of\ Lawsuit\ over\ Aircraft\ Noise\ in\ Chicago\ (http://www.netvista.net/\~hpb/news/nov-6.html)^

[^108]: ^School\ to\ Sue\ for\ Soundproofing\ from\ Airport\ Noise\ (http://www.netvista.net/\~hpb/news/dec-10.html)^

[^109]: ^Connecticut\ Residents\ Threaten\ to\ Sue\ State\ If\ Airport\ Noise\ Isn\'t\ Reduced\ (http://www.netvista.net/\~hpb/news/oct-2.html)^

[^110]: ^Boeing\ Airport\ Noise\ Regulations;\ (http://www.boeing.com/commercial/noise/usa_list.html)^

[^111]: ^FAA,\ Advisory\ Circular\ 91-36C\ (Oct\ 19,\ 1984).\ Visual\ Flight\ Rules\ (VFR)\ Flight\ Near\ Noise\ Sensitive\ Areas.\ (http://www.netvista.net/\~hpb/ac-91-36.html).^

[^112]: ^WRF.\ (February,\ 1999).\ Recipients\ Of\ Federal\ Airport\ Improvement\ Grants\ May\ Not\ Impose\ Discriminatory\ Conditions\ On\ Corporate\ Aircraft\ Operators\ Or\ Similar\ Airport\ Users.\ (http://www.wrf.com/publications/publication.asp?id=1252309172000).^

[^113]: ^MassPort,\ Logan\ Airport.\ (2004.)\ Airport\ Programs,\ Environmental.\ (http://www.massport.com/logan/airpo_noise_gloss.html).^

[^114]: ^Cincinnati/Northern\ Kentucky\ International\ Airport.\ Community\ and\ Environment.\ (http://www.cvgairport.com/airport/enviro/noise.shtml).^

[^115]: ^Satellite\ Navigation\ Product\ Teams.\ Airport\ Benefit:\ Noise\ Abatement\ Areas/Environmentally-Sensitive\ Areas.\ (http://gps.faa.gov/Programs/waas/airports-text.htm).^

[^116]: ^Seattle\ Tacoma\ International\ Airport,\ Washington,\ (Approved\ on\ 6/3/02).\ The\ Noise\ Compatibility\ Plan\ (NCP).\ (http://www.faa.gov/arp/app600/14cfr150/roas/ROAsea02.htm).^

[^117]: ^NBAA.\ (August\ 27,\ 2004).\ Flight\ Restrictions\ for\ 2004\ Republican\ National\ Convention\ in\ New\ York\ City.\ (http://web.nbaa.org/public/ops/airspace/restrictions/2004/rnc/).^

[^118]: ^AOPA.\ (2004).\ Presidential\ movement\ TFRs.\ (http://www.aopa.org/whatsnew/notams.html#4/7295).^

[^119]: ^EAA\ News.\ (2004).\ ADIZ\ ADDED\ FOR\ NEW\ YORK\ CITY\ AREA;\ OTHER\ AIRSPACE\ RESTRICTIONS\ ANNOUNCED\ INCLUDE\ DISNEY\ THEME\ PARKS.\ (http://www.eaa.org/communications/eaanews/030318_adiz.html).^

[^120]: ^EAA\ News.\ (2004).\ ADIZ\ ADDED\ FOR\ NEW\ YORK\ CITY\ AREA;\ OTHER\ AIRSPACE\ RESTRICTIONS\ ANNOUNCED\ INCLUDE\ DISNEY\ THEME\ PARKS.\ (http://www.eaa.org/communications/eaanews/030318_adiz.html).^

[^121]: ^EAA\ News.\ (March\ 22,\ 2003).\ CHICAGO\ MAYOR\ GETS\ HIS\ WAY;\ EAA\ DECRIES\ TFR\ IN\ CHICAGO.\ (http://www.eaa.org/communications/eaanews/030322_tfr_Chicago.html).^

[^122]: ^AOPA.\ (Dec\ 7,\ 2001).\ FAA\ unveils\ major\ airspace\ restrictions\ for\ SLC\ Winter\ Olympics,\ Salt\ Lake\ City-area\ GA\ pilots\ will\ be\ grounded\ for\ 19\ days.\ (http://www.aopa.org/whatsnew/newsitems/2001/01-4-199x.html).^

[^123]: ^Aviation\ During\ the\ Olympics.\ (Update\ 7/18/96).\ Temporary\ Flight\ Restrictions\ (TFRs)\ include\ two\ in\ Downtown\ Atlanta.\ (http://www.mindspring.com/\~cavu/olympics.html#TFRs).^

[^124]: ^AivNav.\ (http://www.airnav.com)^

[^125]: ^Homan,\ Ph.D,\ Anthony\ C.\ (January\ 200).\ Improved\ Methods\ for\ Measuring\ the\ Benefits\ of\ Air\ Traffic\ Control\ Improvements\ (Paper\ No.\ 00-0573).\ Center\ for\ Advanced\ Aviation\ System\ Development.^

[^126]: ^FAA\ (May\ 31,\ 2002).\ FAA\ Order\ 5100.38B,\ Airport\ Improvement\ Program\ Handbook,\ Chapter\ 1.\ Introduction,\ Section\ 1.\ General.\ 21.\ Revenue\ Sources.\ (http://www.faa.gov/arp/aip/order/5100-38B1.htm#c1p21).^

[^127]: ^See\ Appendix\ I,\ assumptions\ 3\ and\ 4.^

[^128]: ^No\ Author.\ (2004,\ May\ 19).\ Section\ 4:\ Aircraft\ Operating\ Costs.\ Federal\ Aviation\ Administration.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://apo.faa.gov/arcc/Chapters/031223%20Sec%204%20-%20Operating%20costs.doc^

[^129]: ^Treatment\ of\ Values\ of\ Passenger\ Time\ in\ Economic\ Analysis,\ U.S.\ Department\ of\ Transportation,\ FAA-APO-03-1,\ March\ 2003.^

[^130]: ^No\ Author.\ (2004,\ May\ 19).\ Section\ 3:\ Aircraft\ Capacity\ and\ Utilization\ Factors.\ Federal\ Aviation\ Administration.\ Retrieved\ May\ 19,\ 2004\ from\ the\ World\ Wide\ Web:\ http://apo.faa.gov/arcc/Chapters/031223%20Sec%203%20-%20Capacity%20and%20utilization.doc^

[^131]: ^see\ for\ example:\ Press,\ Flannery,\ Teukolsky,\ Vetterling,\ Numerical\ Recipes,\ Cambridge\ Univ.\ Press,\ 1986;\ or,\ <http://www.ualberta.ca/~cdeutsch/images/Lec04-MonteCarlo.pdf>.;\ or,\ Rubinstein,\ Simulation\ and\ the\ Monte\ Carlo\ Method,\ Wiley\ Interscience,\ 1981.^

[^132]: ^With\ replacement,\ the\ sampling\ may\ result\ in\ random\ numbers\ being\ selected\ more\ than\ once\ within\ the\ same\ trial.\ In\ other\ words,\ randomly\ selecting\ a\ particular\ quarter\ hour\ to\ add\ a\ flight\ to\ does\ not\ eliminate\ that\ quarter\ hour\ from\ being\ selected\ again.\ Thus,\ more\ than\ one\ flight\ may\ be\ added\ to\ any\ one\ quarter\ hour\ interval.\ See,\ for\ example:\ http://www.nysscpa.org/cpajournal/2002/0402/dept/d045802.htm.^

[^133]: ^Satellite\ Operational\ Implementation\ Team.\ (2002,\ August\ 5).\ LAAS\ Concept\ of\ Operations;\ "Each\ LAAS\ ground\ facility\ has\ a\ very\ high\ frequency\ data\ broadcast\ (VDB)\ coverage\ volume\ that\ extends\ from\ surface\ line\ of\ sight\ to\ 10,000ft\ above\ ground\ level\ (AGL)\ at\ a\ radial\ distance\ out\ to\ 23\ nm\ from\ the\ VDB\ antenna\ site."^

[^134]: ^National\ Flight\ Data\ Center,\ FAA\ ATA-110;\ http://www.faa.gov/ats/ata/ata100/110/index.html^

[^135]: ^NCDC\ data\ provided\ by\ ASD-400.^

[^136]: ^Visual\ weather\ is\ considered\ when\ visibility\ is\ equal\ or\ above\ 3miles\ and\ ceiling\ is\ equal\ or\ above\ 1000ft.\ Visibility\ and/or\ ceilings\ below\ these\ limits\ are\ considered\ IMC\ conditions.^

[^137]: ^ASD-400:\ Airport\ Survey\ and\ Future\ Capacity\ files^

[^138]: ^FAA\ Office\ of\ System\ Capacity:\ http://www.faa.gov/ats/asc/capacity.html^

[^139]: ^See\ for\ example,\ http://www.landrum-brown.com/MasterPlans/PVD/facility-req-chapter3/images/exh%20III-1-9.pdf^

[^140]: ^A\ minimum\ runway\ length\ requirement\ of\ 4,200\ feet,\ based\ on\ the\ minimum\ length\ required\ for\ a\ precision\ approach\ runway,\ is\ also\ included.^

[^141]: ^D10:\ McDonellDouglas\ DC-10;\ B757:\ Boeing\ 757;\ B737:\ Boeing\ 737;\ M80:\ McDonellDouglas\ MD80;\ CRJ:\ Canadair\ Regional\ Jet;\ BE1:\ Beechcraft\ 1900;\ CNA:\ Cessna\ Light\ Aircraft;\ PAG:\ Piper\ Light\ Aircraft^

[^142]: ^Exceptions\ to\ this\ are\ discussed\ in\ the\ Benefits\ for\ Closely\ Spaced\ Parallel\ Approaches\ section.^

[^143]: ^FAA\ Aviation\ Policy,\ Planning\ and\ Environment;\ Establishment\ and\ Discontinuance\ Criteria\ for\ Precision\ Landing\ Systems:\ http://api.hq.faa.gov/precision%20landing%20systems/Precision%20Landing%20Systems.pdf^

[^144]: ^FAA\ Aviation\ Policy\ and\ Plans;\ Airway\ Planning\ Standard\ Number\ One\ Terminal\ Air\ Navigation\ Facilities\ and\ Air\ Traffic\ Control\ Services:\ http://apo.faa.gov/7031/7031.pdf^

[^145]: ^FAA\ Office\ of\ System\ Capacity:\ http://www.faa.gov/ats/asc/publications/CAPACITY/CMH.pdf^

[^146]: ^Beatty,\ R.,\ Hsu,\ R.,\ Berry,\ L,\ and\ Rome,\ J.\ (Dec.\ 1998)\ Preliminary\ Evaluation\ of\ Flight\ Delay\ Propagation\ Through\ an\ Airline\ Schedule;\ 2nd\ USA/Europe\ Air\ Traffic\ Management\ R&D\ Seminar.^

[^147]: ^Welch,\ Andrews\ and\ Robinson,\ Aug\ 2001,\ Assessing\ Delay\ Benefits\ of\ the\ Final\ Approach\ Spacing\ Tool,\ MIT\ Lincoln\ Labs,\ and\ NASA\ Ames\ Research\ Center,\ presented\ at\ the\ AAIA\ Guidance,\ Navigation\ and\ Control\ Conference,\ Aug\ 2001.^

[^148]: ^No\ Author,\ Nov\ 2003,\ Investment\ Analysis\ Benefit\ Guidelines:\ Quantifying\ Benefits\ from\ Projected\ Reductions\ in\ National\ Airspace\ System\ Equipment\ Outages;\ FAA\ ASD-430;\ Appendix\ A,\ p.\ A-3.^

[^149]: ^Rome,\ J,\ Rose,\ S,\ Lee,\ R,\ Cistone,\ J,\ Bell,\ G.,\ Leber,\ W.\ (undated)\ Ripple\ Delay\ and\ Its\ Mitigation.^

[^150]: ^See\ for\ example,\ <http://www.faa.gov/asd/ia-or/NASPAC.htm>,\ and\ <http://www.tc.faa.gov/acb300/330_naspac.asp>^

[^151]: ^http://www.apo.data.faa.gov^

[^152]: ^This\ restriction\ to\ delays\ greater\ than\ 15\ minutes\ follows\ the\ FAA's\ definition\ of\ delay.\ For\ example,\ from\ [http://www.apo.data.faa.gov](http://www.apo.data.faa.gov/),\ "ASQP\ Delayed\ Flight"\ is\ defined\ as\ "ASQP\ reported\ flight\ that\ arrive\ 15\ minutes\ or\ more\ after\ the\ OAG\ schedule\ arrival\ time."\ and\ "Delayed\ Gate\ Arrival"\ is\ defined\ as\ "Delayed\ gate\ arrivals\ are\ arriving\ flights\ delayed\ 15\ minutes\ or\ more\ when\ compared\ to\ scheduled\ or\ flight\ plan."^

[^153]: ^See\ particularly;\ Beatty,\ R.,\ Hsu,\ R.,\ Berry,\ L,\ and\ Rome,\ J.\ (Dec.\ 1998)\ Preliminary\ Evaluation\ of\ Flight\ Delay\ Propagation\ Through\ an\ Airline\ Schedule;\ 2nd\ USA/Europe\ Air\ Traffic\ Management\ R&D\ Seminar.^

[^154]: ^No\ Author,\ Nov\ 2003,\ Investment\ Analysis\ Benefit\ Guidelines:\ Quantifying\ Benefits\ from\ Projected\ Reductions\ in\ National\ Airspace\ System\ Equipment\ Outages;\ FAA\ ASD-430;\ Appendix\ A,\ p.\ A-3.^