Preparing Peak Period and Operational Profiles—Guidebook (2013)

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16 This chapter provides guidance on identifying the appropriate forecasting tools for analyzing planning and environmental problems, depending on the specific issue and the level of detail required or possible. It also describes available default factors, the capability of generating multiple scenarios, and the identification of key variables. The limits of the Guidebook and Toolbox are also addressed. The intent of this chapter is to help identify the appropriate type of forecast to use to consider peak period or operational profiles in addressing a planning or environmental issue. The chapter first reviews the identification of an issue, the types of tools that can be used to address these issues, and the types of forecasts required for these issues. Next, ways that the Guidebook and Toolbox can be used to enhance these forecasts are described, including default factors and multiple scenarios. The chapter closes with a discussion of the limits of the Guidebook and Toolbox. 3.1 Identification of Planning Issues and Appropriate Tools The first step for determining the appropriate planning tool and corresponding forecast requirements is to identify the problem to be addressed. This section describes typical planning issues that are encountered, the appropriate tools for addressing those issues, and the types of forecasts required for those tools. Airfield planning, terminal planning, landside planning, and environmental planning are described separately. Unlike airfield, terminal, landside, and environmental planning, airport financial planning has not required peak period estimates or design day profiles. To date, airport financial forecasts have been based on annual forecasts of passengers, cargo, and aircraft operations. On July 10, 2008, the U.S. Department of Transportation issued a rule allowing airports to increase landing fees during peak hours, and thus far the rule has been upheld in court. Should airports adopt peak hour pricing, landing fee revenues will be dependent on the time of day during which operations occur as well as the total number of operations. In the future, this may require design day profiles for financial forecasting in addition to the planning categories named in the previous paragraph. The various analytical tools for airfield planning, terminal planning, landside planning and environmental planning are described as high detail, medium detail, and low detail: • High detail methods require training for the specific models involved, are data-intensive, and require a substantial investment of time. For these reasons, they are best left to specialists. • Medium detail methods require familiarity with airport planning or environmental analysis, and typically require several days of effort. • Low detail methods can typically be done in a few hours if the necessary data and forecast information has been assembled. C h a p t e r 3 How to Use Guidebook and Toolbox

how to Use Guidebook and toolbox 17 3.1.1 Airside Planning For the purpose of this Guidebook, the airside is defined as the runway, taxiway, and airfield apron areas, plus the facilities that directly support the airfield area, such as Airport Rescue and Firefighting (ARFF). Exhibit 3.1 summarizes types of airfield facilities, the types of tools used to analyze and plan these facilities depending on the level of detail needed, and the types of forecasts required to use these tools. The exhibit is organized according to three main categories: airfield, aircraft parking, and safety. 3.1.1.1 Airfield Airfield planning involves an assessment of the ability of the existing or proposed airfield to accommodate aircraft movements under a variety of circumstances and often involves quantifying the efficiency of the airfield, using metrics such as delay. At most large airports, simulation models Sa fe ty Airport Rescue & Firefighting (ARFF) Medium Airfield Layout Analysis Annual Fleet Mix Safety Areas and Zones High Airfield Layout Analysis Annual Fleet Mix Includes runway safety areas, protection zones, object free areas, obstacle free zones, and obstruction surfaces Safety (incursions) High Airfield Operations and Airfield Layout Analysis Peak Period (fleet mix) Does not include analysis of pilot demographics or ATC procedures Definitions: SIMMOD = Computerized airport and airspace SIMulation MODel TAAM = Total Airport and Airspace Modeler High Detail = Resource intensive approach that requires specialized training. Medium Detail = Requires several days of analysis and familiarity with airport facility or environmental planning. Low Detail = Requires a few hours of analysis if necessary data are available. Sources: ACRP Report 25: Airport Passenger Terminal Planning and Design (for aircraft parking), and HNTB analysis. http://onlinepubs.trb.org/onlinepubs/acrp/acrp_rpt_025v2.pdf Planning Problem/Issue Level of Detail Type of Analysis Comments A ir fie ld Capacity/Delay High Simulation Models (SIMMOD/TAAM) Design Day Schedule Med ium AC 150/5060 (forthcoming spreadsheet) Daily Profile (operations and fleet mix) Low A/C 150/5060 (manual calculations) Peak Period (fleet mix) Operations and Efficiency High Simulation Models (SIMMOD/TAAM) Design Day Schedule Includes planning for taxiways, aprons, and hold pads. Medium/Low Airfield Layout Analysis Annual Fleet Mix Includes planning for taxiways, aprons, and hold pads. Deicing High Simulation Models (SIMMOD/TAAM) Design Day Schedule Medium/Low Spreadsheet Models P eak Period (fleet mix) A ir cr af t P ar ki ng Aircraft Parking High Gate Allocation Models Design Day Schedule Low Departure per Gate Annual Aircraft Departures See ACRP Report 25 for more detail. Low Enplanement per Gate Annual Passenger Enplanements See ACRP Report 25 for more detail. Low Airline Input n/a Remote Overnight (RON) Parking High Gate Allocation Models Design Day Schedule Low Departure per Gate Annual Operations Low Enplanement per Gate Annual Passengers Low Airline Input n/a Type of Forecast Required Exhibit 3.1. Airside planning issues, tools, and forecast requirements.

18 preparing peak period and Operational profiles—Guidebook such as SIMMOD and TAAM are used to evaluate airfield needs and proposed solutions. Following are some general considerations for determining the appropriate level of detail for airfield planning: • New runways or runway extensions usually require FAA funding and a high level of environ- mental review, which then typically warrants the use of simulation modeling. A design day flight schedule is frequently used as input. • If the analysis is at a stage where only initial screening of airfield development concepts is required, as in master plans, design day profiles of aircraft operations should be sufficient for preliminary analyses. The FAA is planning an update to its airport capacity and planning manual.vi The new manual will include an accompanying spreadsheet that is intended to allow the user to accomplish three things. First, it will provide a means of quickly generating estimates of hourly runway throughput based on runway configuration, fleet mix, and other factors. Second, it will provide the user a means of testing the impact of changes in key assumptions, such as fleet mix, on the hourly capacity. Finally, it will provide a means of converting hourly throughput to annual capacity, by incorporating some form of hourly profile or peaking factor, daily hours of operation, and other factors such as fleet and airport size. The model is still being developed, so its exact form and input requirements have not been finalized. The model, as envisioned, will be a useful screening tool, and should function with operational profiles and not require the more complex design day schedules used by SIMMOD or TAAM. • For conceptual long-term planning, which will not lead to design or construction without additional planning at a time closer to the implementation date, peak period estimates are often sufficient. • At the majority of general aviation airports, activity tends to be low (i.e., less than 100,000 opera- tions per year). In these instances, airfield capacity is not an issue. The need for new runways, if any, is driven by issues such as wind coverage or redundancy rather than capacity, and daily profiles or design day schedules are not necessary. 3.1.1.2 Aircraft Parking Aircraft parking requirements are closely related to gate requirements. Aircraft parking needs, whether at-gate or remote, can be evaluated at a high level of detail using a design day schedule coupled with gating models, or at a low level of detail using ratio methods that directly relate the number of parking positions to annual enplanements or passenger aircraft operations. A high level of detail is appropriate under the following circumstances: • Significant increases in new types of activity that would affect apron utilization, such as inter- national travel, are anticipated. • Changes in lease agreements are anticipated, such as a change from exclusive use agreements under which a carrier has sole rights to a gate/parking position, to common use agreements, where carriers share gates and parking positions. • Adding new parking positions would carry a high cost, so that prudence would dictate additional analysis to avoid overbuilding. The methodologies used to estimate gate requirements in ACRP Report 25: Airport Passenger Terminal Planning and Design may be applied to estimating passenger aircraft parking requirements at a lower level of detail. In addition, airlines possess knowledge about their future scheduling plans and flexibility to modify schedules to increase aircraft parking utilization. This information is generally unavailable to airport planners, so input from airlines can also be useful in determining future gate requirements. 3.1.1.3 Airfield Safety Planning for safety involves knowledge of airfield risk factors and FAA standards. It does not typically involve simulation modeling but risk may be assessed using information generated from these models. Detailed forecasts, other than fleet mix, are not necessary unless models are used.

how to Use Guidebook and toolbox 19 3.1.2 Terminal Planning For the purpose of this Guidebook, the terminal area is defined as the terminal building including all concourses and gates. Exhibit 3.2 summarizes the types of terminal facilities, the tools typically used to analyze and plan for these facilities depending on the level of detail desired, and the types of forecasts needed to employ these tools. Planning Problem/Issue Level of Detail Type of Analysis Type of Forecast Required Comments G at es Gates High Gate Allocation Model Design Day Schedule Low Departure per Gate Annual Aircraft Departures See ACRP Report 25 for more detail. Low Enplanement per Gate Annual Passenger Enplanements See ACRP Report 25 for more detail. Low Airline Input n/a Pa ss en ge r D ep ar tu re F ac ili tie s Ticket Counter High Simulation Models (ARCport) Design Day Schedule Medium Mini-Queuing Models Peak Period (originations) See ACRP Report 25 for more detail. Low Ratio Methods Peak Period (originations) Ticket Queue High Simulation Models (ARCport) Design Day Schedule Medium Mini-Queuing Models Peak Period (originations) See ACRP Report 25 for more detail. Low Ratio Methods Peak Period (originations) Passenger Security Screening High Simulation Models (ARCport) Design Day Schedule Medium Mini-Queuing Models Peak Period (originations) See ACRP Report 25 for more detail. Low Ratio Methods Peak Period (originations) Baggage Security Screening High Detailed Planning Analysis Design Day Profile (originations) Low Spreadsheet Models Peak Period (originations) See ACRP Report 25 for more detail. Baggage Make Up Area Medium Baggage Make-up Model Equivalent Aircraft (EQA) See ACRP Report 25 for more detail. Low Ratio Methods Equivalent Aircraft (EQA) See ACRP Report 25 for more detail. Low Spreadsheet Models Peak Period (originations) Departure Lounges (Holdrooms) Low Ratio Methods Gate Requirements Forecast See ACRP Report 25 for more detail. Pa ss en ge r A rr iv al F ac ili tie s Customs & Border Protection High Simulation Models Design Day Schedule Medium Queuing Models Peak Period (international deplanements) See ACRP Report 25 for more detail. Low Ratio Methods Peak Period (international deplanements) Meeting/Greeting Area High Simulation Design Day Schedule Medium Ratio Methods Design Day Profile (O&D passengers) Low Ratio Methods Peak Period (O&D passengers) Baggage Claim Frontage High Simulation Models Design Day Schedule Low Ratio Methods Peak Period (passenger terminations) See ACRP Report 25 for more detail. Baggage Claim Units High Claim Unit Models Design Day Schedule See ACRP Report 25 for more detail. Low Ratio Methods Peak Period (aircraft arrivals) Exhibit 3.2. Terminal building planning issues, tools, and forecast requirements. (continued on next page)

20 preparing peak period and Operational profiles—Guidebook There are four main categories, including gate analysis, departing passenger facilities, arriving passenger facilities, and other terminal facilities, in the exhibit. Many of the tools presented in the exhibit can be directly accessed in ACRP Report 25. 3.1.2.1 Gates The planning techniques used to identify gate requirements are very similar to those used to determine passenger aircraft apron requirements (see Section 3.1.1.2). Specifically, if new activity that would affect the intensity of gate use, if changes in lease terms that would affect how carriers share gates, or if expansion would carry a high cost, a high detail analysis involving a design day schedule should be considered. 3.1.2.2 Departing Passenger Facilities Ticketing facilities, security screening, baggage make-up areas, and holdrooms all serve depart- ing passengers (enplanements). Except for holdrooms, the demand for these facilities is deter- mined by originating enplanements. Holdrooms accommodate both originating and connecting enplanements. Departing passengers require time to check in, pass through security, and navigate the airport. Therefore, peak flows at passenger departure facilities occur in advance of the enplaning peak, which is defined as occurring when the aircraft leaves the gate. The extent of this lead time will depend on the size and configuration of the airport, the queues at the various passenger departure facilities, airline policies such as cut-off times, and the extent to which passengers build in buffer time to allow for unforeseen delays. The lead time will not be constant; it will vary by time of day and by type of passenger. The lead time is therefore often described as a probability function where y percentage of passengers show up at the gate x minutes before scheduled departure time (please see generic example in Exhibit 3.3). Additional discussion on the importance of lead and lag times can be found in ACRP WOD 14 (Appendix P). As a result of the combination of the O th er F ac ili tie s Concourse Circulation Medium Terminal layout analysis Gate Requirements Forecast Function of gates and concourse layout Terminal Circulation Medium Terminal layout analysis n/a Function of terminal layout Restrooms - Terminal Low Ratio Method Peak Period (O&D passengers) See ACRP Report 25 for more detail. Restrooms - Concourse Low Ratio Method Peak Period (deplanements) See ACRP Report 25 for more detail. Concessions Medium Spreadsheet Models Annual Passengers Rental Car Counter & Offices Medium Ratio Method Peak Period (O&D passengers) Low n/a n/a Provided by tenants Airline Offices and Operations & Maintenance Low n/a n/a Provided by airlines Definitions: SIMMOD = Computerized airport and airspace SIMulation MODel TAAM = Total Airport and Airspace Modeler High Detail = Resource intensive approach that requires specialized training. Medium Detail = Requires several days of analysis and familiarity with airport facility or environmental planning. Low Detail = Requires a few hours of analysis if necessary data are available. Sources: ACRP Report 25: Airport Passenger Terminal Planning and Design, and HNTB analysis. Planning Problem/Issue Level of Detail Type of Analysis Type of Forecast Required Comments Exhibit 3.2. (Continued).

how to Use Guidebook and toolbox 21 lead time and probability distribution, the timing and intensity of the peak period flow at a given departure facility may not exactly match the enplaning peak. In addition, the following factors should be considered when determining the level of forecast detail for terminal planning: • At large airports, with a wide variety of airline services and passenger characteristics, inferring the appropriate passenger distributions for each departing passenger facility becomes increasingly complex, and a terminal simulation model requiring a design day schedule may be appropriate. Also, since a design day schedule disaggregates activity down the flight level, it can be used to prepare design day profiles at the concourse or terminal level, in addition to the airport level. • For detailed analysis that will lead to the design and construction of terminal facilities, and which involves the evaluation of multiple configuration alternatives, daily passenger profiles segmented by category (domestic/international, originating/connecting, or other relevant characteristics) and airline are preferred. • For conceptual long-term planning, which will not lead to design or construction without additional planning at a time closer to the implementation date, peak period estimates are sufficient. 3.1.2.3 Arriving Passenger Facilities Arriving passenger facilities include Customs and Border Protection, meeting/greeting areas, and baggage claim facilities. The planning issues for arriving passenger facilities are similar to those for departing passenger facilities, except that the peak flows are determined by deplaning passengers, especially those that are terminating their trip at the airport. In addition, the timing of the impact on arriving passenger facilities lags the deplaning peak. 3.1.2.4 Other Terminal Facilities Some terminal facilities, including concourse and terminal circulation space, restrooms, con- cessions, and rental car counters, serve both arriving and departing passengers. Others such 0% 20% 40% 60% 80% 100% 120% 180 165 150 135 120 105 90 75 60 45 30 15 0 t a s r e g n e s s a P g n i t a n i g i r O f o e g a t n e c r e P t f a r c r i A d r a o B n o r o e t a G Minutes before Scheduled Departure Cumulave Passenger Percentage Source: HNTB analysis. Note: Lead and lag time distributions vary significantly by airport and according to security protocols currently in place; therefore any distributions that are used should be based on information from the airport under study. Exhibit 3.3. Cumulative passenger percentage.

22 preparing peak period and Operational profiles—Guidebook as airline offices are not directly affected by peak passenger activity. With the exception of the demand for restrooms, which is determined by a combination of peak arriving and departing passengers, the demand for most of these activities is determined by annual passenger levels or the configuration of other facilities such as gates. 3.1.3 Landside Planning For the purpose of this Guidebook, the landside area is defined as the portion of the airport devoted to provide ground access to the terminal building and airfield. It encompasses the terminal curb, access roads, parking facilities, and all other ground access facilities, such as mass transit, used to access the airport. Exhibit 3.4 summarizes the types of landside facilities, the tools typically used to analyze and plan for these facilities depending on the level of detail needed, and the types of forecasts needed to use these tools. Landside facilities fall into two major categories: (1) roadway access, including curbs, and (2) parking. 3.1.3.1 Roads and Curbs Access roads provide entry to the curbs and automobile parking at the airport; the majority of these facilities are impacted by activity of both originating and terminating passengers. In general the requirements for the departure curb and access roads to parking facilities are determined by originating passengers and their vehicles, while requirements for the arrivals curb and roads which egress from parking facilities are determined by terminating passengers and their vehicles. More specific to the curb roadways, many airports serve both arriving and departing passengers with the same curb; in this case demand is determined by a combination of arriving and departing passengers. Definitions: VISSIM - (Verkehr in Stadten - Simulation) micro-level traffic simulation model. Source: HNTB analysis. O&D - origin and destination passengers High Detail = Resource intensive approach that requires specialized training. Medium Detail = Requires several days of analysis and familiarity with airport facility or environmental planning. Low Detail = Requires a few hours of analysis if necessary data are available. Planning Problem/Issue Level of Detail Type of Analysis Type of Forecast Required Comments R oa ds a nd C ur bs Access roads High Simulation Models (e.g., VISSIM) Design Day Profile (O&D) Low Roadway Layout Analysis Peak Period (O&D) Curb Capacity - Private Auto High Simulation Models Design Day Profile (O&D) Low Spreadsheet Analysis Peak Period (O&D) Curb Capacity - Commercial High Simulation Models Design Day Profile (O&D) Low Spreadsheet Analysis Peak Period (O&D) Pa rk in g Parking - Hourly Low Ratio Methods Peak Period (O&D) Ratios tend to be airport-specific. Parking - Daily Low Ratio Methods Design Day (O&D) Ratios tend to be airport-specific. Parking - Long Term Low Ratio Methods Design Day (O&D) Ratios tend to be airport-specific. Rental Car Low Ratio Methods Design Day (O&D) Ratios tend to be airport-specific. Entry/Exit Plazas High Simulation Models Design Day Profile (O&D) Low Ratio Methods Peak Period (O&D) Parking – Taxi Hold Medium Queuing Models Design Day Profile (O&D) Low Ratio Methods Peak Period (O&D) Parking – Cell Phone Lot Medium Policy Peak Period (terminations) Diverts activity from both hourly parking and curbside so has both congestion and revenue implications. Parking – Employee Medium Spreadsheet Analysis Design Day Profiles (employees) Function of number of employees and timing of shifts. Low Ratio Models Annual Employees Exhibit 3.4. Landside planning issues, tools, and forecast requirements.

how to Use Guidebook and toolbox 23 Curb and roadway requirements are highly sensitive to the configuration of the airport: the segregation of different types of demand (e.g., passenger versus employee), and the segregation by vehicle type (e.g., private auto versus courtesy van). Therefore, simulation models using design day profiles are often used to model these more complex interactions. The guidelines for landside planning are similar to those for terminal planning, although lead times for departing passengers and lag times for arriving passengers are greater. The connection between enplaning/deplaning peaks and curbside and roadway peaks tends to be more tenuous than those seen in the terminal. In addition, the demand on roads and curbs will depend on the airport specific passenger transportation mode. Transportation mode is very sensitive to whether the passenger is a resident or non-resident, which in turn is sensitive to time of day. See the ACRP WOD 14 (Appendix K) for more discussion. When choosing an analytical method and forecast for access road or curb analysis, the following should be considered: • At a multiple terminal airport, where loads on curbs may depend on which airlines are assigned to which terminals, airline specific design day passenger profiles or a design day flight schedule will be required. • For conceptual long-term planning, peak period estimates derived from design day profiles should be sufficient. Alternatively, an empirical analysis based on identifying the current dis- tribution of vehicle traffic by time of day and scaling up based on the growth in passenger originations may be more cost-effective. 3.1.3.2 Parking From an analytical standpoint, parking can be broken out into two main categories, very short term and other. The very short term category includes hourly parking, cell phone lots, and taxi hold areas. Planning for these categories typically relies on peak period vehicle forecasts, which are determined principally by passengers. To account for lead and lag factors, these should be derived from daily passenger profiles. Other longer-term parking demand is dependent on the accumulation of demand rather than peak demand flows. Hence, design day forecasts of O&D traffic are sufficient to forecast requirements for these types of parking. The sizing of entry and exit parking plazas is dependent on peak traffic flows. More detailed analyses use simulation, similar to many roadway analyses. 3.1.4 Environmental Planning As it relates to airports, most quantitative airport activity-related environmental planning is devoted to noise and air quality analysis. The tools used for these analyses may differ depend- ing on whether the focus is the airfield or the landside. Exhibit 3.5 summarizes the types of environmental impacts, the tools typically used to analyze these types of environmental impacts depending on the level of detail needed, and the types of forecasts needed to employ these tools. There are many additional environmental impact categories, such as historic and archeological resources, fish and wildlife, endangered species, socioeconomic impacts, and hazardous materials but their analysis is not dependent on measures of passenger or aircraft activity and therefore is not addressed in this section. 3.1.4.1 Noise Analysis In most instances, noise analysis is governed by 40 CFR Part 150 and FAA NEPA guidance in FAA Order 1050.1E: Policies and Procedures for Considering Environmental Impacts, and FAA Order 5050.4B: National Environmental Policy Act (NEPA) Implementing Instructions for Airport Actions. Therefore, there is less flexibility in choosing analytical tools than with planning.

24 preparing peak period and Operational profiles—Guidebook Noise impacts from aircraft are usually estimated using the INM which has specific input requirements, namely AAD aircraft operations broken out by day/night split and aircraft type. The NIRS model is sometimes used instead; however, it requires a design day schedule as an input. The Area Equivalent Model (AEM) is a simpler spreadsheet analysis, but is limited to use as a screening tool to determine whether a change in aircraft mix will create a significant change in noise contours. Airports generate noise impacts from vehicular traffic as well as aircraft. These landside noise impacts can be estimated using models such as the Traffic Noise Model (TNM), which requires an AAD profile of vehicle movements, which is dependent on airport O&D passengers. Noise impacts resulting from regional airspace use are currently evaluated using NIRS, which requires a design day schedule as an input. The impact of small incremental changes to airspace use can be evaluated using the NIRS Screening Tool (NST). The AEDT will eventually be able to calculate aircraft and airspace noise impacts along with airfield and landside air quality impacts. In effect, it will replace the INM, NIRS, and Emissions and Dispersion Modeling System (EDMS) models but will use the same inputs depending on the specific analysis required. 3.1.4.2 Air Quality Analysis Like noise analysis, air quality analysis is directed by FAA and EPA regulations. This restricts the types of analytical approaches that can be used. The EDMS is currently used to perform air quality inventories and air quality dispersion analysis resulting from airport activity. The inventory analysis requires a fleet mix for the average annual day. The dispersion analysis information needs are more detailed and require the output from an airfield simulation model such as SIMMOD or TAAM. Consequently a design day schedule is needed as a forecast input. Planning Problem/Issue Level of Detail Type of Analysis Type of Forecast Required Comments No is e Noise - Airport High NIRS/AEDT Design Day Schedule Medium INM/AEDT Day/Night & Stage Length Profile Low AEM Day/Night Profile Screening tool used to estimate impact of changes in aircraft operations. Noise - Landside Medium TNM Design Day Profile (originations) Noise - Airspace High NIRS/AEDT Design Day Schedule Medium NST Profile of Proposed change in aircraft operations. Used to estimate impact of changes in aircraft operations. A ir Q ua lit y Inventory Medium EDMS/AEDT AAD Fleet Mix Dispersion - Airside High EDMS/AEDT Design Day Schedule Dispersion - Landside High EDMS/AEDT Design Day Schedule Definitions: NIRS - Noise Integrated Routing System model AEDT - Aviation Environmental Design Tool (forthcoming) INM - Integrated Noise Model AEM - Area Equivalent Method (spreadsheet model) TNM - Traffic Noise Model NST - NIRS Screening Tool EDMS - Emissions and Dispersion Modeling System MOVES2010 - Motor Vehicle Emission Simulator (2010 version) High Detail = Resource intensive approach that requires specialized training. Medium Detail = Requires several days of analysis and familiarity with airport facility or environmental planning. Low Detail = Requires a few hours of analysis if necessary data are available. Source: HNTB analysis. Exhibit 3.5. Environmental planning issues, tools, and forecast requirements.

how to Use Guidebook and toolbox 25 The upcoming AEDT model will replace the EDMS model and the INM model; however, the input requirements will generally be the same. 3.2 Default Factors The seasonal, weekly, and hourly distribution of activity for airports varies depending on their size, their location, and the types of communities they serve. At most airports, this type of information is readily available for aircraft operations, but less so for weekly and hourly passenger distributions. Typically this information is available only from the airlines or by undertaking extensive monitoring programs. It is difficult to obtain cooperation from all airlines, and monitoring programs are time-consuming and expensive. To provide an alternative, the Toolbox provides optional default factors for day-of-week load factors, time-of-day seat factors (enplaning/deplaning load factors), and peak hour spreading factors. 3.2.1 Day-of-Week Default Factors As part of the research supporting this Guidebook, information was collected from participating airlines to identify day-of-the-week seat factors by airport size and time zone (see Appendix C). A review of the data indicates that there is strong statistical support finding that some days of the week have higher seat factors than others, and that in most cases, the busier days are Fridays and Sundays, and the less busy days are Tuesdays and Wednesdays (see ACRP WOD 14, Appendix F). Nevertheless, there is significant variation from airport to airport, so day-of-the week data specific to the airport should be collected if possible. 3.2.2 Time-of-Day Default Factors In addition to day-of-the-week passenger information, participating airlines were requested to provide time-of-day seat factors (enplaning and deplaning load factors) by airport size and time zone (see Appendix C). A review of the data suggests that seat factors for arrivals tend to be higher in the afternoon and early evening than the remainder of the day, and that seat factors for departures tend to be higher in the late morning and early afternoon than elsewhere in the day. There is significant variation from airport to airport, so the hourly variations from the mean are not statistically significant at a strong confidence level. Therefore, hourly data specific to the airport should be collected if possible. If airport-specific data is not available, it is recommended that the hourly default factors be used only for sensitivity analyses. 3.2.3 Peak Spreading Default Factors The Toolbox calculates alternative values for design day profiles and peak period estimates based on a default peak spreading factor that reduces the peak periods (as a percentage of daily operations) and increases the off-peak periods to compensate, as design day operations increase. The default peak spreading factor is based on an analysis of the relationship between peak hour percentage and total annual operations (see ACRP WOD 14, Appendix H, for additional background). Based on the analysis in Appendix H, there is a gradual decline in the peak hour percentage as annual activity becomes greater, which averages about -0.5 percent per 100,000 increase in annual aircraft arrivals/departures. In addition, the variability in the peak hour percentage is much greater for small airports than for large airports. Also, there is a minimum limit of approximately 6.5 percent, below which the peak percentage will not fall, regardless of the size of the airport. This suggests that, when estimating future changes in the peak period percentage, the practitioner should consider where the current peak period percentage lies in comparison with other airports

26 preparing peak period and Operational profiles—Guidebook with similar activity levels. If it is already at the low end of the range, peak spreading is likely to be much less than if it lies at the high end of the range. Other factors that can influence the extent of peak spreading include: • Average Aircraft Size: If airlines reduce the average size of the aircraft serving an airport, flight frequency increases but the size of the aircraft serving the peak decreases. This tends to increase peak spreading. Alternatively, peak spreading is less likely if the average aircraft size increases. • Number of Airlines: When airport growth is achieved by adding additional airlines, they often compete during the peak, thereby reducing the extent of peak spreading. Conversely, when growth is achieved by existing airlines adding new flights, the flights tend to be added during off-peak hours, thereby increasing the degree of peak spreading. • Type of Passenger Service: Overseas international flights normally operate within restricted windows. Therefore, new international service to an existing region is less likely to result in peak spreading than new domestic service. • Type of Cargo Service: Integrated air cargo carriers such as FedEx and UPS have narrow sort windows and therefore are much less able to spread their operations than are non-integrated air cargo carriers. 3.3 Forecast Uncertainty and the Use of Scenarios This section provides an overview of the types of forecast uncertainty, and how to use scenario analysis with the assistance of the Toolbox to address this uncertainty. Additional guidance on treating forecast uncertainty will be forthcoming from ACRP Project 3-22, “Incorporating Uncertainty and Risk into Airport Air Traffic Forecasting.” 3.3.1 Forecast Uncertainty Three types of uncertainty are addressed: (1) variance in the annual forecasts, (2) variance between the annual forecasts and the measures of peak activity, and (3) variance between scheduled and actual activity. Forecasts are inherently uncertain. Annual activity projections are subject to forecast variance because of unforeseen changes in economic conditions, changes in airline cost factors (e.g., fuel), changes in airline business models, and changes in regulations and security measures. These uncertainties carry over into the design day, operational profile, and peak period estimates that are based upon the annual projections. Changes in the relationship between annual activity and the design day, operational profile, and peak period estimates are also subject to uncertainty, and introduce an additional element of variance. For example, a carrier may choose to increase the number of connecting banks at an airport without increasing the total number of flights. The result would be a decrease in peak period activity that would not be projected with traditional forecasting techniques. Airlines are not always able to operate consistently with their schedules. Therefore, even if a practitioner precisely projects a design day schedule, the inability of airlines to meet that schedule could result in unanticipated impacts on facilities. International facilities are particularly prone to this problem since they need to accommodate relatively few flights with large numbers of passengers within a narrow time frame. Since international flights tend to be longer, deviations from schedule resulting from stronger than expected headwinds or tailwinds become important considerations. A slight shift in one or two flights can result in a concentrated peak that may overwhelm facilities that are designed for the projected schedule. Manual adjustments to the schedule input data could be used to model such instances within the Toolbox (see Chapter 8).

how to Use Guidebook and toolbox 27 3.3.2 Use of Scenarios One method of addressing uncertainty is to use forecast scenarios. Forecast scenarios, in the form of high and low range forecasts, or more detailed contingencies based on variation of specific variables such as economic growth, are often used to portray the potential variance in annual forecasts. The Toolbox provides a means of quickly generating similar alternative forecast scenarios of design day, operational profile, and peak period activity levels. The Toolbox can: • Show the effect of an annual forecast scenario upon the design day, operational profile, or peak period measures. • Provide the ability to specify alternative relationships between annual and peak activity levels, such as day-of-the-week and hour-of-the-day enplaning load factors and peak spreading factors. More specific examples are provided in Chapters 4, 5, and 8. 3.4 Identification of Key Variables The Toolbox can be used to test multiple relationships between annual and peak activity lev- els. The results of these tests can help identify the specific variables that have the greatest impact on peak period estimates and the facilities they affect. This information can then help determine where to devote resources to collect more information. For example, the Toolbox can be used to run sensitivity tests with and without the default day-of-the-week enplaning load factor adjustment factors. If the difference in resulting peak period passenger levels is very little, it is not necessary to take the time and effort to collect day-of-the-week data from the airlines. Alternatively, if the tests show a significant difference in peak period estimates with and without the default day-of-the-week factors, it would indicate that collecting airport-specific day-of-the-week data from the airlines would enhance accuracy. Another example would be a test of the time interval from when a passenger arrives at curbside to when the passenger boards an aircraft. These lead times are affected by security policies imposed by the Transportation Security Administration (TSA) and can be very difficult to forecast. The Toolbox can be used to test several alternative lead times to identify their potential impact on the derivative curbside daily profile. At airports where arriving and departing passengers use the same curb, the lead time could change sufficiently to cause arriving and departing curbside peaks to become superimposed, significantly increasing curbside congestion. A sensitivity analysis using the Toolbox can help alert the planner to such potential problems. 3.5 Limits of Guidebook and Toolbox Airports are complex entities, and even intricate simulation models provide only a simplified representation. Likewise, this Guidebook and Toolbox cannot describe all the nuances associated with an airport operation. In the case of the high detail analyses described in Exhibits 3.1, 3.2, 3.4, and 3.5 particularly, professional assistance is recommended.