Airport Passenger Terminal Planning and Design, Volume 2: Spreadsheet Models and User’s Guide (2010)

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Estimating gate demand requires an understanding of the current capacity and future require- ments based on forecast activity. There are two basic ways to determine the number of gates required: by developing and using a design day flight schedule (DDFS), or by using current and forecast enplanements and departures to estimate the future trends. If a DDFS has been developed for a forecast year (or annual activity level), it can allow a rela- tively detailed study of gate demand. Typically a DDFS is developed when airside simulation modeling is done for an airport. In many cases, a DDFS is produced as separate lists of flight arrivals and departures (records) in a spreadsheet format. To use the DDFS to determine gate demand, arrivals and departures must be matched up. This matched schedule can then be analyzed by various proprietary models to determine the number of gates required during the course of the day. The output is typically a Gantt-type gate chart, and/or a histogram of gate demand by 5- or 10-minute periods. While this type of analysis can be very detailed, it is dependent on the assumptions used to add flights by specific airlines or aircraft types over time. Methodologies without Design Day Flight Schedules When a DDFS is not available, two other approaches can be used: enplaned passengers by gate or departures per gate. These approaches also allow the terminal planner to easily do “what if?” sensitivity checks on basic assumptions, including those which may underlie a DDFS. The Gate Demand model is set up like the other Spreadsheet Models with links to the Table of Contents and the User’s Guide, and uses color-coded cells for consistency (see Figure 17). The two methods of determining gate demand without a DDFS are used in the model as outlined in Section V.3.9 of the Guidebook. Annual Enplaned Passengers per Gate Approach The first approach, as shown in Figure 18, uses the current ratio of annual enplaned passengers per gate, adjusted for forecast changes in fleet mix and annual load factors. This methodology assumes that the pattern of gate utilization will remain relatively stable over the forecast period. The changes in passengers per gate would be due to changes in enplanements per departure (due to fleet seating capacity and/or passenger load factors), as opposed to increasing (or decreasing) numbers of departures per gate. The basis for the existing factor is the number of gates in use. This number may be less than the number of gates available at an airport. In rare cases of over-crowded terminals, aircraft may 17 Gate Demand Model

be double parked at existing gates, so it is important to determine the true demand for active air- craft parking. From the existing passenger activity and annual departures, the current ratios of annual passengers per gate and enplanements per departure are calculated. Similar calculations can be based on total annual passengers, airline operations, or a combination of these, depending on how the airport keeps its statistics and develops its forecasts. Forecasts for annual enplaned passengers and aircraft departures (or total passengers and aircraft operations) are usually forecast separately. Annual departures are typically forecast based on assumptions for fleet size and load factors that are applied to the passenger forecasts. In the model example in Figure 18, the ratio of enplaned passengers per gate for each forecast year is calculated by multiplying the current (2008 in this example) factor by the percentage increase in enplaned passengers per aircraft departure. For example, enplaned passengers per departure increases from 54 in 2008 (actual) to 56 in 2010 (forecast), thus the factor would increase from 94,400 enplaned passengers per gate (2008 data when 36 gates were in use) to 97,500 for 2010, and 102,600 enplaned passengers per gate by the end of the forecast period without any further increase in the number of daily departures per gate. Future gate requirements are then estimated by dividing annual forecast passengers by the estimated passengers per gate factor for that forecast period. For example, in 2010, 4,429,000 enplanements divided by 97,500 enplanements per gate results in a demand for 45 gates. This approach results in a forecast demand for 69 gates by the end of the forecast period. Departures per Gate Approach The first methodology has as an underlying assumption that the future pattern of air service will be stable and will resemble existing conditions. While this may be true at many airports and for some airlines at a given airport, it is often likely that gate utilization will change to some extent for other airlines. With a forecast reduction in mainline jets, for example, additional flights by 18 Airport Passenger Terminal Planning and Design Figure 17. Gate Demand model. Figure 18. Example of enplaned passengers per gate approach to determine gate demand.

Gate Demand Model 19 regional aircraft may be scheduled as demand grows. Similarly, airlines may add flights to their hubs from spoke cities. This typically results in higher average gate utilization. However, if an airport attracts service by new entrant airlines, it is often likely that these carriers would initially follow scheduling patterns similar to existing carriers. This could result, for example, in a demand for more gates during the morning departure peak, and a reduction in average daily gate utilization. For the departures per gate approach from the model (example shown in Figure 19), the ratio of annual departures per gate for each forecast year is calculated by multiplying the current (2008) factor by the percentage change in assumed daily departures per gate. In this example, it was assumed that average daily gate utilization would increase from 5.0 departures per gate in 2008, to 5.2 departures per gate by 2010, and gradually increase to 6.5 departures per gate by 2025. Thus, the annual gate utilization factor would increase from 1,750 annual departures per gate (2008) to 2,290 by 2025. Future gate requirements are estimated by dividing annual forecast departures by the esti- mated departures per gate factor for that forecast period. For example, in 2010, 79,500 depar- tures divided by 1,820 departures per gate results in a demand for 44 gates. This approach results in a forecast demand for only 53 gates by the end of the forecast period. For most airports that assume increasing gate utilization, the departures per gate approach will result in a demand for fewer gates than the annual enplaned passengers per gate approach. The model also provides an average of the two methods. The planner then needs to examine the range of values provided and determine the most reasonable and likely outcome. See Figure 20. Once the gate requirements have been determined, the other ground requirements can be further quantified by relating the future DDFS to available gates. If the flight schedule suggests more aircraft than available gates or for early morning high turnover gates due to airline schedules, then additional aircraft parking spots will be required. Figure 19. Example of departures per gate approach. PassengersDepartures Year per Gate per Gate GATES 2010 45 44 45 2015 52 47 50 2020 61 50 56 2025 69 53 61 Average of Both Methods Figure 20. Comparison of gate analysis approaches.

Remain Overnight Aircraft Parking At many airports, the pattern of airline service results in more aircraft being on the ground overnight than number of active gates. This situation is more pronounced at “spoke airports” where an airline may have, for example, hourly service to its hub for the first few hours of the day. Because it may take until mid-morning before aircraft begin to arrive, a single gate may accommodate two to three aircraft departures for which the aircraft must be parked overnight. These remain overnight (RON) aircraft are usually parked remotely or, in some cases, double parked on contact gates where the apron geometry allows. If RON aircraft are parked remotely, the aircraft are typically towed to a contact gate for departure, and towed off a contact gate to the RON parking area after the evening arrival. Estimating the number of RON positions should take into account the airport’s air service pattern, the forecasts for cities to be served in the future, whether these are hubs or direct desti- nation flights, and the relative utilization of gates. Gate Equivalents Airport comparisons are also frequently made on the basis of passengers per gate or terminal area per gate, but these comparisons lack a consistent definition of the term “gate.” To standardize the definition of “gate” when evaluating aircraft utilization and requirements, two metrics have been developed: narrowbody equivalent gate (NBEG) and equivalent aircraft (EQA). The model includes a Gate Equivalencies Table (see Figure 21) to serve as a gate inventory dur- ing the gate demand process, showing available leased or forecast gates. This inventory is useful to other model segments where the EQA or NBEG values may be needed as factors that help deter- mine other space requirements. The user needs to input the number of gates for each design group, and the total and equivalent values will be calculated. The calculated values are the cumulative sum product of the gate share and the index values. Narrowbody Equivalent Gate This metric is used to normalize the apron frontage demand and capacity to that of a typical narrowbody aircraft gate. The amount of space each aircraft requires is based on the maximum wingspan of aircraft in its respective aircraft group. FAA Airplane Design Groups used to define runway/taxiway dimensional criteria have been used to classify the aircraft as shown in Figure 22. Group IIIa has been added to more accurately reflect the B757, which has a wider wingspan than Group III but is substantially narrower than a typical Group IV aircraft. A wingspan com- parison is illustrated in Figure 23. 20 Airport Passenger Terminal Planning and Design Figure 21. Computing EQA and NBEG gate equivalents.

Gate Demand Model 21 Source: Hirsh Associates and Landrum & Brown PG 008-083A PG 008- 083A 003-777B 003- 777B 003- 767B 003-767B 002- 757B 002-757B Code A Code A 002-J RC002-JRC Feet 15 24 36 41 52 65 80 Meters Figure 23. Wingspan comparison. Source: Hirsh Associates FAA Airplane Maximum Typical NBEG Design Group Wingspan Aircraft Index Feet Meters I. Small Regional 49 15 Metro 0.4 II. Medium Regional 79 24 SF340/CRJ 0.7 III. Narrowbody/Lrg. Regional 118 36 A320/B737/DHC8/E175 1.0 IIIa. B757(winglets) 135 41 B757 1.1 IV. Widebody 171 52 B767/MD11 1.4 V. Jumbo 214 65 B747,777,787/A330,340 1.8 VI. A380 262 80 A380/B747-8 2.2 Figure 22. NBEG index.

In developing terminal facilities requirements, the apron frontage of the terminal, as expressed in NBEG, is a good determinant for some facilities, such as secure circulation. Terminal concepts can also be more easily compared by normalizing different gate mixes. Equivalent Aircraft The concept of EQA is similar to that of NBEG, i.e., a way to look at the capacity of a gate. EQA, however, normalizes each gate based on the seating capacity of the aircraft that can be accommo- dated. The EQA measure was originally developed in the early to mid-1970s as a technique for sizing terminal facilities. The EQA measure was originally included in The Apron & Terminal Building Planning Manual, for U.S.DOT, FAA, by The Ralph M. Parsons Company, July 1975. When the Manual was devel- oped, the majority of jet aircraft had 80 to 110 seats, thus the EQA measure centered on the 80- to 110-seat range with an EQA of 1.0. Smaller aircraft had an EQA of 0.6, and larger aircraft fell into seating ranges with the center of the range determining the EQA of that range. One hundred seats was equal to 1.0 EQA, aircraft in the 211- to 280-seat range had an EQA of 2.4, etc. In considering the modern fleet mix of regional and jet aircraft, and in order to have some rela- tionship with the physical parameters associated with the NBEG, the basis of EQA has been revised from the 1970s definition. The current EQA is also a Group III narrowbody jet. Most of the larger aircraft in this class typically have 140 to 150 seats. This establishes a basis of 1.0 EQA = 145 seats. As with the concept of NBEG, smaller aircraft may use a gate, but the EQA capacity is based on the largest aircraft and seating configuration typically in use. While most terminal facility requirements are a function of design hour passenger volumes, some airline facilities are more closely related to the capacity of the aircraft. For example, while the total number of baggage carts required for a flight are a function of design hour passengers (and their bags), the number of carts staged at any one time are generally based on the size of the aircraft. Thus, the EQA capacity of the terminal can represent a better indicator of demand for these facilities. The number of seats in each design group, as shown in Figure 24, can vary considerably from the basic definitions. For example, larger “regional jets” in Group III can be in the 100- to 110- seat range, while a Group III A321 narrowbody can have over 180 seats. Similarly, as fuel econ- omy and range becomes more important, most new widebody aircraft are being designed with wider Group V wingspans than the Group IV aircraft they replace, but may have less than 250 seats. For a given airport, it may be appropriate to modify the EQA metrics to better match the fleet mix expected when using EQA to determine some terminal facilities. 22 Airport Passenger Terminal Planning and Design FAA Airplane Typical Typical EQA Design Group Seats Aircraft Index I. Small Regional 25 Metro 0.2 II. Medium Regional 50 SF340/CRJ 0.4 III. Large Regional 75 DHC8/E175 0.5 III. Narrowbody 145 A320/B737/MD80 1.0 IIIa. B757 (winglets) 185 B757 1.3 IV. Widebody 280 B767/MD11 1.9 V. Jumbo 400 B747,777,787/A330,340 2.8 VI. A380 525 A380/B747-8 3.6 Source: The Apron & Terminal Building Planning Manual, for U.S. Department of Transportation FAA, by The Ralph M. Parsons Company, July 1975. Figure 24. EQA index.