## Acronym Information

The NPS includes many acronyms to refer to NextGen and legacy technologies, programs, locations and data sources. Although most acronyms are accompanied by a brief description of their meaning, the following table provides links to sources that may be used to find additional detail and meaning behind these acronyms. Please note that acronyms occasionally have different meanings depending on their context, so a definition in these sources, while correct, may not meet the intended definition.

Source Description
Air Traffic Management Glossary of Terms Air traffic management glossary of acronyms with definitions produced by the FAA Air Traffic Control System Command Center.
Aeronautical Information Manual The FAA's official guide to basic flight information and air traffic control procedures.
Glossary of Airport Acronyms Used in FAA Documents Airport acronyms that appear in FAA airport standards and related publications.
NextGen Implementation Plan (PDF) Pages 90-94 of the 2013 update to the NextGen Implementation Plan list many acronyms, airport codes and FAA facility codes used when describing NextGen capabilities and progress.

## Airport Information

Airports included on the NextGen Performance Snapshots (NPS) website are often identified by several characteristics, including airport code, name and city. The locations detailed in the Airport Performance pages also include additional background information such as, operations and freight volume at the specified airport; this information is gathered from the 2012 Airports Council International, North American Airport Traffic Summary preliminary data.

Several metrics on the NPS are measured during Reportable Hours. These hours, which are measured in local time, vary by airport and are selected to capture at least 90 percent of the total operations (arrivals and departures) at an airport. The entire percentage of total operations covered under these Reportable Hours may not be reflected in the NPS metrics due to the characteristics of the data sources used. Please see the individual metric definitions for additional data source information. In addition to general airport information, the table below includes the Reportable Hours for the airports measured on the NPS. Memphis International (MEM) is unique in this list as it is the only airport in which the Reportable Hours span a full 24-hour day due to its large number of freight operations during night hours.

### Airport Information Table

City Airport Name Airport Code Metroplex Reportable Hours
Atlanta Hartsfield-Jackson Atlanta International Airport ATL Atlanta 07:00 - 22:59
Baltimore Baltimore/Washington International Thurgood Marshall Airport BWI D.C. 06:00 - 22:59
Boston Boston — General Edward Lawrence Logan BOS Boston 06:00 - 21:59
Charlotte Charlotte-Douglas International Airport CLT Charlotte 07:00 - 22:59
Chicago Chicago Midway International MDW Chicago 07:00 - 20:59
Chicago Chicago O'Hare International ORD Chicago 06:00 - 21:59
Dallas-Fort Worth Dallas/Fort Worth International Airport DFW North Texas 07:00 - 21:59
Denver Denver International Airport DEN Denver 07:00 - 21:59
Detroit Detroit Metropolitan Wayne County Airport DTW Detroit 06:00 - 22:59
Fort Lauderdale Fort Lauderdale-Hollywood International Airport FLL South Florida 07:00 - 22:59
Honolulu Honolulu International HNL 06:00 - 22:59
Houston Houston — George Bush Intercontinental Airport IAH Houston 07:00 - 21:59
Las Vegas Las Vegas — McCarran International Airport LAS Las Vegas Valley 07:00 - 21:59
Los Angeles Los Angeles International Airport LAX Southern California 06:00 - 22:59
Memphis Memphis International Airport MEM Memphis 00:00 - 23:59
Miami Miami International Airport MIA South Florida 07:00 - 22:59
Minneapolis Minneapolis-St. Paul International/Wold-Chamberlain Airport MSP Minneapolis-St. Paul 07:00 - 22:59
New York New York — John F. Kennedy International Airport JFK New York/Philadelphia 06:00 - 22:59
New York New York — La Guardia Airport LGA New York/Philadelphia 07:00 - 21:59
Newark Newark Liberty International Airport EWR New York/Philadelphia 07:00 - 22:59
Orlando Orlando International Airport MCO Orlando 07:00 - 21:59
Phoenix Phoenix Sky Harbor International Airport PHX Phoenix 07:00 - 21:59
Salt Lake City Salt Lake City International SLC 07:00 - 21:59
San Diego San Diego International Airport SAN Southern California 06:00 - 22:59
San Francisco San Francisco International Airport SFO Northern California 07:00 -22:59
Seattle Seattle-Tacoma International Airport SEA Seattle 07:00 - 21:59
Tampa Tampa International Airport TPA Tampa 07:00 - 22:59
Washington Ronald Reagan Washington National Airport DCA D.C. 06:00 - 21:59
Washington Washington Dulles International Airport IAD D.C. 07:00 - 22:59

## Metroplex Information

The NPS website provides an overview of several National Airspace System (NAS) metroplexes, showing their importance to the area in which they are located and to the NAS as a whole.

### Metroplex Definition

Each metroplex is a unique system of airports, aircraft, weather patterns and geography. The following is a consolidated list of the airports in each of the metroplexes on the NPS. Due to data availability, all the airports included for a metroplex may not be included in the data describing it. For the full name of an airport, please see the individual metroplex page.

Metroplex Airports
Atlanta ATL; FTY; PDK; RYY.
Boston BDL; BED; BOS; BVY; MHT; OWD; PVD.
Charlotte CAE; CLT; GSO; GSP; JQF; RDU.
Chicago ARR ; DPA; GYY; MDW; MKE; ORD; PWK; RFD; UGN.
Cleveland BKL; CGF; CLE.
D.C. BWI; DCA; HEF; IAD; MTN.
Denver APA; BJC; DEN.
Detroit DET; DTW; PTK; YIP.
Houston DWH; HOU; IAH; MSY; SGR.
Las Vegas Valley HND; LAS; VGT.
Memphis MEM; OLV.
Minneapolis-St. Paul ANE; FCM; MSP; STP.
New York/Philadelphia EWR; FRG; HPN; ILG; ISP; JFK; LGA; MMU; PHL; PNE; SWF; TEB.
North Texas ADS; AFW; DAL; DFW; DTO; FTW; GKY; TKI.
Northern California HWD; OAK; PAO; SFO; SJC; SMF.
Orlando ISM; MCO; ORL; SFB.
Phoenix IWA; PHX.
Seattle BFI; PAE; SEA; TIW.
South Florida FLL; FXE; MIA; OPF; PBI; TMB.
Southern California BUR; HHR; LAX; LGB; ONT; OXR; PSP; SAN; SMO; SNA; VNY.
Tampa PIE; SRQ; TPA.

As work progresses to improve metroplex traffic flow, the airports included may change.

### Metroplex Traffic

The Metroplex Traffic section provides an overview of the aircraft types operating within the selected metroplex. This traffic mix is segmented as Commercial Air Carrier, General Aviation and Military operations. Commercial Air Carrier operations are further defined as the sum of Air Carrier and Air Taxi operations. The information is calculated from FAA Operational Network (OPSNET) data and is reported for FY 2009 - 2013.

The data set used to calculate this metric includes all the airports in each metroplex, although some airports may not support a given traffic segment. The data include both itinerant and local operations for the airports being measured. Per the OPSNET user guide:

• Local: Operations performed by an aircraft that remain in the local traffic pattern, execute simulated instrument approaches or low passes at the airport, and operations to or from the same airport within a designated practice area within a 20-miles radius of the tower.
• Itinerant: Operations performed by an aircraft, either IFR or VFR, that land at an airport arriving from outside the airport area, or depart from an airport and leave the airport area.

### Average Daily Scheduled Flights

The number of average daily scheduled flights is calculated for FY 2009 through FY 2012 and is based on the sum of the departures scheduled to and from all the metroplex airports that offer scheduled service and for which data are available. To obtain the average daily value, the yearly sum is divided by the number of days in the year (365 for FY 2009 - FY 2011 and 366 for FY 2012). The source for this data is the U.S. Department of Transportation, Bureau of Transportation Statistics (BTS) Air Carrier Statistics Database.

Since some airports do not have scheduled service, this information may not include data for all the airports within the metroplex. The following table identifies the airports included in this information for each metroplex. The airports listed may not have scheduled service for each year provided in the data set. To see the full names for these airports, please consult the appropriate metroplex page.

Metroplex Airports
Atlanta ATL.
Boston BDL; BED; BOS; MHT; PVD.
Charlotte CAE; CLT; GSO; GSP; RDU.
Chicago MDW; MKE; ORD; RFD.
Cleveland CLE.
Denver DEN.
Detroit DTW.
Houston HOU; IAH; MSY.
Las Vegas Valley LAS; VGT.
Memphis MEM.
Minneapolis-St. Paul MSP.
New York/Philadelphia EWR; FRG; HPN; ISP; JFK; LGA; PHL; SWF.
North Texas AFW; DAL; DFW.
Northern California OAK; SFO; SJC; SMF.
Orlando MCO; SFB.
Phoenix PHX.
Seattle BFI; SEA.
South Florida FLL; MIA; PBI.
Southern California BUR; LAX; LGB; ONT; OXR; PSP; SAN; SNA.
Tampa PIE; SRQ; TPA.

### Projected Annual Benefits

Several of the metroplex pages contain projected annual benefits of NextGen airspace and procedure improvements. The source of this data is the FAA Office of Airspace Services.

The projected benefits shown on the NPS are annual values expected to accrue upon completion of the near-term NextGen procedural improvements implemented by the Optimization of Airspace and Procedures in the Metroplex (OAPM) program. They are based on the FAA's preliminary assessment of proposed airspace improvements compared to operations before any improvements were made and may use a slightly different set of airports than those listed above. The value of the projected fuel savings is based on prevailing fuel prices at the time the analysis was conducted and could therefore differ between metroplexes. Continued study may warrant that the operational vision used to calculate these projected benefits be modified, thus changing the value of the projected benefits.

## Key Performance Indicators: Access

A global Air Traffic Management system should provide an operating environment that ensures all airspace users have right of access to the resources needed to meet their specific operational requirements and that the shared use of airspace by different users can be achieved safely.

### LPV & LP Access at GA Airports without ILS

Reported as Count of Airports for NAS only

Desired Trend: Increase

Source: FAA Office of Airport Planning and Programming.

Localizer Performance with Vertical guidance (LPV) & Localizer Performance (LP) data gathered from the FAA Global Navigation Satellite Systems Group.

Airport information gathered from the General Aviation Airports: A National Asset study.

The count of National, Regional, Local and Basic GA airports (as defined in the 2012 FAA GA Airports Study) without an ILS that have an initial LPV or LP procedure published in the indicated year.

Computations

Sum of the count of airports within the defined scope having an LPV or LP procedure for a given fiscal year.

Scope

LPV and LP procedures were counted for airports that meet the following conditions:

• Not be a primary airport as defined in the 2012 GA Airports Study,
• Be listed as either a National, Regional, Local or Basic GA airport in the 2012 GA Airports Study, and
• Not have any Instrument Landing System (ILS) Procedures
Statistical Issues

This data is calculated based on the number of procedures published by the end of the Fiscal Year; within the year the value may vary slightly due to different procedure publication dates.

Airports are counted per the earliest LP/LPV initial publishing date in their current list of procedures and may not account for procedure updates or changes. Previously published procedures that are no longer available will not be reflected in the data. This may cause historical values to change slightly when updated procedure lists are used to update the metric.

The list and categorization of non-primary airports is subject to change.

Completeness

Procedure data used to calculate the metric was last updated on September 19, 2013.

The General Aviation Airports: A National Asset study was published in May 2012.

Outcome: LPV approaches provide reliable, precise access to airports during low visibility/ceiling weather conditions, particularly for general aviation aircraft operators.

LPV is similar to LNAV/VNAV except it is much more precise (40m lateral limit), enables descent to 200-250 feet above the runway, and can only be flown with a WAAS receiver. LPV approaches are operationally equivalent to the legacy ILS but are more economical because no navigation infrastructure (glideslope and localizer) has to be installed at the runway.

### Percent of Qualified GA Airports with LPV or LP Access

Reported as Cumulative Percent for NAS only

Desired Trend: Increase

Source: FAA Office of Airport Planning and Programming.

Localizer Performance with Vertical guidance (LPV) & Localizer Performance (LP) data gathered from the FAA Global Navigation Satellite Systems Group.

Airport information gathered from the General Aviation Airports: A National Asset study Webpage and the Airport Master Record Form 5010 data.

The cumulative percent of qualified National, Regional, Local and Basic GA airports (as defined in the 2012 FAA GA Airports Study) with an LPV or LP procedure.

Computations

The cumulative percent of qualified airports within scope that have an LPV or LP procedure in a specific year.

Scope

This metric only includes LPV and LP qualified National, Regional, Local and Basic General Aviation (GA) airports (as defined in the 2012 FAA General Aviation Airports Study).

The yearly numbers of LPV and LP Procedures counted include those available at airports both with and without Instrument Landing System (ILS) Procedures.

Statistical Issues

This data is calculated based on the number of procedures published by the end of the Fiscal Year; within a year the value may vary due to the different charting dates.

Airports are counted per the earliest LP/LPV initial publishing date in their current list of procedures and may not account for procedure updates or changes. Previously published procedures that are no longer available will not be reflected in the data. This may cause historical values to change slightly when updated procedure lists are used to update the metric.

The list and categorization of airports is subject to change.

Completeness

The LP/LPV data used to calculate metric was last updated on September 19, 2013

The General Aviation Airports: A National Asset study was published in May 2012

To be qualified for an LP or LPV procedure an airport needs to have a paved runway of 3,200 feet or greater (terrain or obstacles around the airport may affect the ability to develop a procedure for an airport as well).

LPV is similar to LNAV/VNAV except it is much more precise (40m lateral limit), enables descent to 200-250 feet above the runway, and can only be flown with a WAAS receiver. LPV approaches are operationally equivalent to the legacy ILS but are more economical because no navigation infrastructure (glideslope and localizer) has to be installed at the runway.

## Key Performance Indicator: Capacity

Utilize available airport capacity to meet the National Airspace System users' demand at all times and in all approach conditions.

### Average Daily Capacity

Reported as Operations (Arrivals plus Departures) for Core Airports during Reportable Hours

Desired Trend: Increase

Source: MITRE/Aviation System Performance Metrics (ASPM) data.

During reportable hours, the average daily sum of the Airport Departure Rate (ADR) and Efficiency Airport Arrival Rate (Eff AAR) reported by fiscal year. The Reportable Hours vary by airport. Additional ADR and Eff AAR information is provided in the Average Daily Capacity entry of the Reference Guide.

Computations

The total of the yearly sums of the hourly Eff AAR and the hourly ADR within scope divided by the number of days in the year.

Scope

This metric includes all domestic service to or from any of the ASPM 77 airports and the selected Core airport during reportable hours.

Statistical Issues

Due to the leap year, the number of days for Fiscal Year 2012 is 366, all other years it is 365.

Due to the units of this metric (operations), the results were rounded to the nearest whole number.

Completeness

The type of ASPM data that this metric is calculated from is intended to capture the full set of ASPM records.

Reliability

The data for FY 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY 2014.

ASPM provides the following definitions for Eff AAR and ADR:

• Eff AAR: The Efficiency Airport Arrival Rate, or the number of arrivals an airport can support per unit of time when a Traffic Management Initiative is in effect.
• ADR: Number of departures an airport can support, per unit of time.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports section above.

## Key Performance Indicators: City Pair

When a traveler starts to plan a trip or when an airline operator starts to plan air service, they will look at pairs of cities or pairs of metropolitan areas. For airline operators, city-pair performance is the most direct way to connect two markets. The NPS uses a KPI for both the Efficiency and Predictability KPAs to show City Pair performance, the definitions for each are shown below.

### Effective Gate-to-Gate Time

Reported as Minutes per Flight for Selected City Pairs during reportable hours (based on the local time for the arrival airport)

Desired Trend: Increase

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data.

During reportable hours at the destination airport, the difference between the Actual Gate-In Time at the destination airport and the Scheduled Gate-Out Time at the origin airport. Flights may depart outside reportable hours, but must arrive during them. The reportable hours vary by airport and the results are reported by fiscal year.

Computations

Average Gate-to-Gate Time over all flights in the fiscal year for the selected City Pair within the Scope.

Scope

This KPI only measures ASQP reporting carriers operating domestic service between the selected pair of airports in the direction indicated. Only flights arriving at the destination airport within the reportable hours are included in this measurement. Flights may depart the origin outside the reportable hours.

Statistical Issues

The list of ASQP reporting carriers is subject to change yearly. Additionally, changes in carrier operations at, or between the origin and destination may impact data results over time.

This calculation did not normalize the data for any changes in operator fleet mix.

This calculation may include time an aircraft spends in a non-movement area (defined in the Aeronautical Information Manual as Taxiways and apron (ramp) areas not under the control of air traffic). Reporting carriers may use slightly different starting and/or ending points when gathering performance data.

Completeness

ASQP flights are those with actual data reported to the Department of Transportation (DOT).

The first full year of data for the Newark Liberty International — Chicago Midway International (EWR — MDW) city pair was FY2012.

Reliability

The metric is derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal "ASQP" in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports section above.

### Effective Gate-to-Gate Time Predictability

Reported as Minutes for Selected City Pairs

Desired Trend: Decrease

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data.

During reportable hours, the difference between the 85th and 15th percentiles of the Effective Gate-to-Gate Time metric. The reportable hours vary by airport and the results are reported by fiscal year. Additional percentile and reportable hour information can be found in the Reference Guide.

Computations

The value for the 15th percentile of the Effective Gate-to-Gate time KPI subtracted from the value of the 85th percentile of the Effective Gate-to-Gate time KPI.

Scope

This KPI only measures ASQP reporting carriers operating domestic service between the selected pair of airports in the direction indicated. Only flights arriving at the destination airport within the reportable hours are included in this measurement. Flights may depart the origin outside the reportable hours.

Statistical Issues

Calculating the difference between the 15th and 85th percentile helps provide a better picture of the actual predictability by removing atypical data points.

A lower value for this metric is desired because it shows less variation in the Effective Gate-to-Gate time for flights for the specified city pair within the indicated year.

Completeness

ASQP flights are those with actual data reported to the Department of Transportation (DOT).

The first full year of data for the Newark Liberty International — Chicago Midway International (EWR — MDW) city pair was FY2012.

Reliability

The metric is derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal "ASQP" in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports section above.

## Key Performance Indicators: Efficiency

Efficiency addresses the operational and economic cost-effectiveness of gate-to-gate flight operations from a single-flight perspective. In all phases of flight, airspace users want to depart and arrive at the times they select and fly the trajectory they determine to be optimum.

### Average Gate Arrival Delay

Reported as Minutes per Flight for Core Airports during reportable hours

Desired Trend: Decrease

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data

During reportable hours, the yearly average of the difference between the Actual Gate-In Time and the Scheduled Gate-In Time for flights to the selected airport from any of the Aviation System Performance Metrics (ASPM) airports. The delay for each fiscal year is calculated based on the 0.5 — 99.5 percentile of the distributions for the year. Flights may depart outside reportable hours, but must arrive during them. The reportable hours vary by airport.

Formula
$∑ F AD n F for each G$

where

$AD = ( t in act - t in sch )$

and where G are the groups defined within Scope, Arrival Delay (AD) is equal to the actual time into the gate at the arrival airport ( $t in act$ ) minus the scheduled time in at the arrival airport ( $t in sch$ ); F are all flights over the year within each group and nF is the number of F.


Computations

Average Gate-In Delay against schedule over all flights in the fiscal year for each group defined within the Scope.

Scope

Flights are restricted to domestic ASQP flights departing from an ASPM airport and traveling to the selected airport. To be included a flight needs to arrive within the reportable hours, but may depart the origin outside reportable hours.

Statistical Issues

The list of ASQP reporting carriers is subject to change yearly. Additionally, changes in carrier operations at an airport may impact data results over time.

This calculation did not normalize the data for any changes in operator fleet mix.

This calculation may include time an aircraft spends in a non-movement area (defined in the Aeronautical Information Manual as Taxiways and apron (ramp) areas not under the control of air traffic). Reporting carriers (operators) may use slightly different starting and/or ending points when gathering performance data.

After the metric was calculated, the data was truncated to remove outliers. The information provided is based on the 0.5 — 99.5 percentile of the distributions by airport and year.

Completeness

ASQP flights are those with data reported to the Department of Transportation (DOT).

Reliability

The metrics are derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set, the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal "ASQP" in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

Positive delays are considered any time beyond the scheduled arrival time (including delays less than 15 minutes). Due to the inclusion of flights arriving before schedule (negative delays), negative values are possible for this metric.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports Section above.

### Average Number of Level-offs Per Flight

Reported as Counts per Flight for Core Airports

Desired Trend: Decrease

Source: MITRE/Performance Based Navigation Dashboard and Analysis System

The count of instances of level-offs as flights descend from cruise altitudes to the arrival airport, averaged for the fiscal year.

Formula
$= ∑ F LO n F$

LO is the count of level offs for each arrival in the Scope, F is the set of all flights in Scope and nF is the number of F

Computations

The sum of the count of level offs for each flight within Scope; divided by the total number of flights within the Scope.

Scope

Flights are restricted to jet arrivals at the designated airport from any origin airport.

The level flight counts are measured starting when each flight reaches Top-of-Descent (TOD) or 200 nautical miles from the airport, whichever is closer.

An aircraft must be in level flight for at least 50 seconds and the change in altitude has to be less than 200 feet for a segment to be considered level.

Statistical Issues

When calculating this metric, flight trajectories are segmented into linear segments, and are classified as either ascending, descending or level. Vertical gradients are used to classify these segments. The threshold on the vertical climb gradient for descent and level segments is between 30 and 50 feet per nautical mile.

This metric is calculated using all hours.

### Distance in Level Flight from Top of Descent to Runway Threshold

Reported as Nautical Miles per Flight for Core Airports

Desired Trend: Decrease

Source: MITRE/Performance Based Navigation Dashboard and Analysis System

The distance flown in level flight as flights descend from cruise altitudes to the arrival airport, averaged for the fiscal year.

Formula
$= ∑ F D n F$

Where D is the distance flown at level flight for each arrival in the Scope, F is the set of all flights in the Scope and nF is the number of F

Computations

The sum of the total distance flown at level flight for all flights within the Scope, divided by the count of all flights within the Scope.

Scope

Flights are restricted to jet arrivals at the designated airport from any origin airport.

The distance in level flight is measured starting when each flight reaches Top-of-Descent (TOD) or 200 nautical miles from the airport, whichever is closer.

An aircraft must be in level flight for at least 50 seconds and the change in altitude has to be less than 200 feet for a segment to be considered level.

Statistical Issues

When calculating this metric, flight trajectories are segmented into linear segments, and are classified as either ascending, descending or level. Vertical gradients are used to classify these segments. The threshold on the vertical climb gradient for descent and level segments is between 30 and 50 feet per nautical mile.

This metric is calculated using all hours.

### Effective Gate-to-Gate Time

Reported as Minutes per Flight for Core Airports during reportable hours

Desired Trend: Increase

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data.

During reportable hours, the difference between the Actual Gate-In Time at the destination (selected) airport and the Scheduled Gate-Out Time at the origin airport. Flights may depart outside reportable hours, but must arrive during them. The reportable hours vary by airport and the results are reported by fiscal year.

Computations

Gate-to-Gate time over all flights in the Fiscal Year for each group defined within Scope.

Scope

Flights are restricted to domestic ASQP flights departing from any ASPM airport and traveling to the selected airport by an ASQP reporting carrier. Additionally, to be included, a flight needs to arrive within the reportable hours (but may depart the origin outside reportable hours).

Statistical Issues

The list of ASQP reporting carriers is subject to change yearly. Additionally, changes in carrier operations at an airport may impact data results over time.

This calculation did not normalize the data for any changes in operator fleet mix.

This calculation may include time an aircraft spends in a non-movement area (defined in the Aeronautical Information Manual as Taxiways and apron (ramp) areas not under the control of air traffic). Reporting carriers (operators) may use slightly different starting and/or ending points when gathering performance data.

Completeness

ASQP flights are those with data reported to the Department of Transportation (DOT).

Reliability

The metric is derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set, the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal “ASQP” in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports section above.

### Taxi-In Time

Reported as Minutes per Flight for Core Airports during reportable hours

Desired Trend: Decrease

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data

During reportable hours, the yearly average of the difference between Wheels-On Time and Gate-In Time for flights arriving at the selected airport from any of the Aviation System Performance Metrics (ASPM) airports. Flights may depart outside reportable hours, but must arrive during them. The reportable hours vary by airport.

Formula
$∑ F TI n F$

where

$TI = t in act - t on act$

The Taxi-In Time metric is calculated as the average over all flights in the fiscal year defined within the Scope. The Taxi-In Time for a flight (TI) is defined as the time the aircraft pulls into the gate ( $t in act$ ) minus the time the aircraft wheels touch the ground ( $t on act$ ). This value is added to all the other flights within scope (F) and divided by the number of F (nF).


Computations

The average of the difference between the actual Gate-In Time and actual Wheels-On Time over all arrivals for each group defined within the Scope.

Scope

Flights are restricted to domestic ASQP flights departing from an ASPM airport and traveling to the selected airport by an ASQP reporting carrier. To be included, a flight needs to arrive within the reportable hours, but may depart the origin outside reportable hours.

Statistical Issues

The list of ASQP reporting carriers are subject to change yearly. Additionally, changes in carrier operations at an airport may impact data results over time.

This calculation did not normalize the data for any changes in operator fleet mix.

This calculation may include time an aircraft spends in a non-movement area (defined in the Aeronautical Information Manual as Taxiways and apron (ramp) areas not under the control of air traffic). Reporting carriers (operators) may use slightly different starting and/or ending points when gathering performance data.

Completeness

ASQP flights are those with actual data reported to the Department of Transportation (DOT).

Reliability

The metrics are derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set, the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal "ASQP" in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports Section above.

### Taxi-Out Time

Reported as Minutes per Flight for Core Airports during reportable hours

Desired Trend: Decrease

Source: MITRE/Airline Service Quality Performance System (ASQP) data derived from Aviation System Performance Metrics (ASPM) data

During reportable hours, the yearly average of the difference between Gate-Out Time and Wheels-Off time for flights from the selected airport to any of the Aviation System Performance Metrics (ASPM) airports. Flights must depart during reportable hours, but may arrive outside them. The reportable hours vary by airport.

Formula
$∑ F TO n F$

where

$TO = t off act - t out act$

The Taxi-Out Time metric is calculated as the average over all flights in the fiscal year defined within the Scope. The Taxi-Out Time for a flight (TO) is defined as the time the aircraft takes off ( $t off act$ ) minus the time the aircraft pushes back from the gate ( $t out act$ ). This value is added to all the other flights within scope (F) and divided by the number of F (nF).


Computations

The average of the difference between the Actual Gate-Out Time and Actual Wheels-Off Time over all departures for each group defined within the Scope.

Scope

Flights are restricted to domestic ASQP flights departing from the selected airport and traveling to an ASPM airport. To be included, a flight needs to depart within the reportable hours, but may arrive at the destination outside the reportable hours

Statistical Issues

The list of ASQP reporting carriers is subject to change yearly. Additionally, changes in carrier operations at an airport may impact data results over time.

This calculation did not normalize the data for any changes in operator fleet mix.

This calculation may include time an aircraft spends in a non-movement area (defined in the Aeronautical Information Manual as Taxiways and apron (ramp) areas not under the control of air traffic). Reporting carriers (operators) may use slightly different starting and/or ending points when gathering performance data.

Completeness

ASQP flights are those with data reported to the Department of Transportation (DOT).

Reliability

The metrics are derived directly from individual ASQP flight data obtained through the Aviation Performance Metrics (APM) website. In the original data set, the Official Airline Guide Aircraft Identification (OAG_ACID) column must equal "ASQP" in order for the flight to be considered an ASQP flight and used in the calculations.

The data for Fiscal Year 2013 is not yet final as amendments may still be made to the ASPM source data until six weeks after the end of FY2014.

The Technical Directive outlining the ASQP reporting carriers is available on the Bureau of Transportation Statistics (BTS) webpage.

Reportable hours vary by airport and are based on local time. Additional reportable hours information is included in the Airports section above.

## Key Performance Indicators: Environment

The Air Traffic Management (ATM) should contribute to the protection of the environment by considering noise, gaseous emissions and other environmental issues in the implementation and operation of the global ATM system.

### CO2 Emissions

Reported as Kilograms for NAS only

Desired Trend: Decrease

Source: FAA Office of Environment and Energy

Estimated quantity of Carbon Dioxide (CO2) emitted by aircraft engines.

Formula

Fuel Burn (kg) × 3.155 (CO2 kg per kg of fuel burn) = CO2 in kilograms

Computations

As part of measuring and tracking NAS fuel efficiency from commercial aircraft operations, the FAA quantifies aircraft fuel burn using FAA’s Aviation Environmental Design Tool (AEDT). AEDT is a FAA-developed computer model that estimates aircraft fuel burn and emissions for variable year emissions inventories and for operational, policy, and technology-related scenarios.

Statistical Issues

Potential seasonal variability and variability from year-to-year can be expected when analyzing air traffic data and commercial operations.

The extent to which enhancements are incorporated to improve model accuracy, for example via more robust aerodynamic performance modeling algorithms and database of aircraft/engine fuel burn information, will impact the overall results. This could create some statistical variability from year-to-year if not properly taken into account. In cases where such enhancements have the potential to create a significant shift in baseline, annual inventories may need to be re-processed and/or adjusted to ensure consistency and accuracy of results.

The extent to which aircraft fleet improvements cannot be sufficiently modeled because of a lack of manufacturer proprietary data may also influence the performance target results. In this case, attempts will be made to characterize such aircraft with the best publicly available information, recognizing that newer aircraft types in the fleet will likely exist in significantly lesser numbers, thus minimizing the influence upon the results.

Completeness

Data used to measure aircraft performance are assessed for quality control purposes. Input data for the AEDT model are validated before proceeding with model runs. Radar data from the Traffic Flow Management System (TFMS) are assessed to remove any anomalies, check for completeness, and pre-processed for input to the AEDT model. TFMS data are verified against the Official Airline Guide (OAG) information in order to avoid any duplication of flights in the annual inventory.

In some cases, TFMS data lack appropriate fields to conduct quality control and in these cases the data are removed. Data from the AEDT model are verified by comparing output from previous years and analyzing trends to ensure that they are consistent with expectations. In other cases monthly inventories may be analyzed to validate the results. Model output is subsequently post-processed through spreadsheets to perform the calculations for the performance target. Formulae and calculations are checked in order to ensure accuracy.

Reliability

The measuring procedure used is highly reliable. That is to say that the processing of data through the AEDT model including the performance of algorithms is not subject to random factors that could influence the results. However, this is potentially influenced by factors outside the control of FAA.

We do not expect increases in fuel burn or decreases in distance traveled or both to degrade the fleet fuel efficiency significantly. We do expect that in the future, aircraft and engine technology improvements or air traffic management improvements or both may not be enough to offset traffic growth, congestion and delays. In addition, the current metric for measuring and tracking fuel efficiency may not adequately capture performance to the degree that would allow future decisions on technological and operational considerations.

This KPI is calculated for calendar year (CY)

### NAS-Wide Energy Efficiency

Reported as Kilograms per Kilometer for NAS only

Desired Trend: Increase

Source: FAA Office of Environment and Energy

Estimated fuel Burn in kilograms per kilometer

Formula
$Fuel Burn (Tg) Distance (Billions of Kilometers)$
Computations

Measuring and tracking fuel efficiency from commercial aircraft operations allows FAA to monitor improvements in aircraft/engine technology and operational procedures, as well as enhancements in the airspace transportation system. The FAA measures performance against this target using the Aviation Environmental Design Tool (AEDT). AEDT is a FAA-developed computer model that estimates aircraft fuel burn and emissions for variable year emissions inventories and for operational, policy, and technology-related scenarios.

Scope

This metric focuses on all U.S. commercial operations.

Statistical Issues

Potential seasonal variability and variability from year-to-year can be expected when analyzing air traffic data and commercial operations.

The extent to which enhancements are incorporated to improve model accuracy, for example via more robust aerodynamic performance modeling algorithms and database of aircraft/engine fuel burn information, will impact the overall results. This could create some statistical variability from year-to-year if not properly taken into account. In cases where such enhancements have the potential to create a significant shift in baseline, annual inventories may need to be re-processed and/or adjusted to ensure consistency and accuracy of results.

The extent to which aircraft fleet improvements cannot be sufficiently modeled because of a lack of manufacturer proprietary data may also influence the performance target results. In this case, attempts will be made to characterize such aircraft with the best publicly available information, recognizing that newer aircraft types in the fleet will likely exist in significantly lesser numbers, thus minimizing the influence upon the results.

Completeness

Data used to measure performance are assessed for quality control purposes. Input data for the AEDT model are validated before proceeding with model runs. Radar data from the Traffic Flow Management System (TFMS) are assessed to remove any anomalies, check for completeness, and pre-processed for input to the AEDT model. TFMS data are verified against the Official Airline Guide (OAG) information in order to avoid any duplication of flights in the annual inventory.

In some cases, TFMS data lack appropriate fields to conduct quality control and in these cases the data are removed. Data from the AEDT model are verified by comparing output from previous years and analyzing trends to ensure that they are consistent with expectations. In other cases monthly inventories may be analyzed to validate the results. Model output is subsequently post-processed through spreadsheets to perform the calculations for the performance target. Formulae and calculations are checked in order to ensure accuracy.

Reliability

The measuring procedure used is highly reliable. That is to say that the processing of data through the AEDT model including the performance of algorithms is not subject to random factors that could influence the results. However this is potentially influenced by factors outside the control of FAA.

We do not expect increases in fuel burn or decreases in distance traveled or both to degrade the fleet fuel efficiency significantly. We do expect that in the future, aircraft and engine technology improvements or air traffic management improvements or both may not be enough to offset traffic growth, congestion and delays. In addition, the current metric for measuring and tracking fuel efficiency may not adequately capture performance to the degree that would allow future decisions on technological and operational considerations.

This KPI is calculated for calendar year (CY)

### Noise Exposure

Reported as Number of People for NAS only

Desired Trend: Decrease

Source: FAA Office of Environment and Energy

Number of persons exposed to significant aircraft noise (regardless of whether their houses or apartments have been sound-insulated). Significant aircraft noise levels are currently defined as values greater than or equal to 65 decibels (dB) Day Night Sound Level (DNL).

Formula

Σi=1nPOP65ij=19POPRELj

Where POP65i is the number of people residing in the DNL 65 dB contour at the ith "Noise Inventory" airport as of the current year projected from the 2000 Census, and n is the number of Noise Inventory airports. A Noise Inventory airport is defined as any airport that reported having at least 365 jet departures for the year being used in the analysis. POPRELj is the number of people relocated from the DNL 65 dB contour in the jth FAA region. This data is only available for the years 2000 - 2005. Beginning in 2006, the data is no longer collected by the FAA.

Source: FAA Portfolio of Goals & FAA Office of Environment and Energy

Computations

POP65i is the number of people residing in the DNL 65 DB contour at the ith “Noise Inventory” airport as of the current year projected from the 2000 Census, and n is the number of Noise Inventory airports. A Noise Inventory airport is defined as any airport that reported having at least 365 jet departures for the year being used in the analysis. PROPRELj is the number of people relocated from the DNL 65 dB contour in the jth FAA region since the year 2000.

Scope

This metric tracks the residential population exposed to significant aircraft noise around U.S. airports. Significant aircraft noise is defined as aircraft noise above a Day-Night Average Sound Level (DNL) of 65 decibels (dB). DNL is the 24-hour average sound level, in dB, obtained from the accumulation of all events with the addition of 10 dB penalty to sound levels occurring at night (from 10 pm up to 7 am). The weighting of the nighttime events accounts for the increased interference effect of noise during the night when ambient levels are lower.

Statistical Issues

This metric is derived from model estimates that are subject to errors in model specification. Trends of U.S. noise exposure may change due to annual improvements to the noise exposure model. A major change to the model may result in a large change in the estimate of the number of people exposed to significant noise levels around US airports.

Completeness

No actual count is made of the number of people exposed to aircraft noise. Aircraft type and event level are current. However, some of the databases used to establish route and runway utilization were developed from 1990 to 1997. Changes in airport layout including expansions may not be reflected. The FAA continues to update these databases as they become available. The benefits of federally funded mitigation, such as buyout, are accounted for.

Reliability

The Integrated Noise Model (the core of the MAGENTA and AEDT tool) has been validated with actual acoustic measurements at airports. The population exposure methodology has been thoroughly reviewed by an ICAO task group and was most recently validated for a sample of airport-specific cases.