Guidebook for Preparing and Using Airport Design Day Flight Schedules (2016)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

A-1 A p p e n d i x A The purpose of this appendix is to provide real world examples of the application of the guid- ance in the main guidebook. The examples are a set of DDFS prepared for Minneapolis-St. Paul International Airport (MSP) on behalf of the Metropolitan Airports Commission (MAC). (At the time of guidebook publication, the completion of the LTCP document was still pending. However, the DDFS analysis associated with the LTCP has been completed.) The DDFSs were prepared in late 2014 by HNTB Corporation (one of the authors of this guidebook) in support of the Airport’s Long-Term Comprehensive Plan (LTCP) update (the LTCP is the MAC’s equiva- lent to an Airport Master Plan). Instead of recapitulating the entire DDFS process, this appendix follows the guidance in Chapters 5 through 9 and highlights key elements from the LTCP DDFSs to show how the guidance can be applied. A.1 Scoping Early in the LTCP scoping process, it was determined that the key issues were related to the terminal buildings, gate capacity, and associated landside facilities. One major question was whether to expand at Terminal 1, where the hub carrier and legacy carriers were located, or at Terminal 2, where the principal low-fare carriers were located (see Exhibit A.1). Since aircraft operations had declined significantly from their previous peak, airfield capacity was not considered an urgent issue. The terminal analysis was expected to involve complex phasing issues, in which gate requirements by airline and aircraft type would be needed. In addition, security processing capacity was a major issue so detailed estimates of originating traffic by time of day would be needed. Consequently, it was determined that DDFSs would be useful and appropriate for this study. Airfield capacity was not expected to be an issue, and the analysis of cargo, GA, and military facilities was not anticipated to require a DDFS level of detail. Therefore, the DDFS scope only included scheduled passenger aircraft operations. In addition, no runway use designations and arrival/departure fixes were included. There was sufficient time in the LTCP schedule to prepare a set of DDFSs, so the effort was deemed feasible. The effort was scoped to include the base year (2014) and two forecast years, 2020 (correlates to a planning activity level of approximately 38 million annual passengers) and 2030 (corre- lates to a planning activity level of approximately 48 million annual passengers). The base year was needed for calibration and to serve as a staging point for the two forecast schedules. The year 2020 was considered the earliest year that any substantial terminal improvements could be completed and 2030 was considered a reasonable out-year for determining longer-term requirements. Case Study Examples from MSP DDFSs

A-2 Guidebook for preparing and Using Airport design day Flight Schedules A.2 Setting the Stage Delta Air Lines is a major stakeholder at MSP. A meeting was held with Delta Corporate Real Estate and route planning staff at the beginning of the study to review and discuss key LTCP and forecast assumptions, including those relevant to the DDFS such as fleet mix, gate utilization, and gate buffer times. In addition, Delta staff, along with other stakeholders, had the opportunity to review and comment on draft products as they were developed. Two other consulting teams were involved in the LTCP, and they also provided input, particularly regard- ing the type of DDFS output that would be required for their analyses. Finally, MAC staff were deeply involved and led biweekly working group conference calls to review results and determine subsequent steps. The study was approached from an unconstrained perspective; therefore, no slot controls or other demand management policies were assumed. Two gating alternatives were initially developed: the first assumed the existing airline distribution among terminal buildings would continue (Airlines Remain Scenario); the second assumed that all carriers that were not part of the Delta network would move to Terminal 2 (Airlines Relocate Scenario). A third (Incremental Airlines Relocate Scenario) was developed later in the study (see Section A.9). Source: Metropolitan Airports Commission Exhibit A.1. Locations of Terminal 1 and Terminal 2 at MSP

Case Study examples from MSp ddFSs A-3 The design day was defined as an average weekday during July, the usual peak month for enplanements and operations at MSP. Several of the Terminal 2 carriers, however, peak in March. In addition, the international arrival peak occurs during Saturdays in March. Therefore, partial DDFSs were prepared for Terminal 2 carriers for an average weekday in March and for international operations for an average Saturday in March. Since late night operations at MSP are minimal, multiple day or weekly DDFSs were not considered necessary. In contrast to enplanements, MSP passenger originations peak in March instead of July. The adjustments used to estimate this originations peak are discussed further in Section A.11. In addition to the Delta Air Lines input, the following data was collected: • Monthly and annual statistics and current gate layouts from the MAC; • A base year airline schedule from the Official Airline Guide; • USDOT T-100 data for market-by-market enplanements, fleet mix, and load factor informa- tion; and • USDOT O&D Survey data for market-by-market originations. A.3 Future Markets and Fleet Mix Discussions with Delta Air Lines, along with an analysis of recent trends, indicated that Delta activity would grow more slowly than the MSP market and that Delta’s market share would therefore gradually decline. Based on recent trends, the market shares of the other legacy carriers—American and United—were also projected to decline, and the market shares of low-fare carriers, such as Southwest, Sun Country, and Spirit, were projected to increase. Market growth in existing markets was measured in terms of seat departures. The approach was similar to Option 1 (see Section 6.3 in the guidebook) except that seat departures by mar- ket were estimated directly instead of first estimating passengers by market. The markets were organized into four categories: (1) large, medium, and small hubs; (2) non-hubs; (3) Dakotas and Rocky Mountain states; and (4) Southwest Airlines markets based on historical growth trends that were projected to increase in accordance with those trends. New nonstop markets were estimated using a revenue threshold analysis. Candidate markets for nonstop domestic air carrier service were determined by identifying the current thresholds of total revenue (pas- sengers multiplied by average fare) that justified nonstop service to MSP. Thresholds were lower for nearby markets than more distant markets because service can be offered with smaller aircraft and because there is less competition from connecting hubs between the two markets. Revenue thresholds necessary to justify nonstop service were estimated using the average of revenue in the smallest market with nonstop service and the largest market without nonstop service in each mileage band (0–300 miles, 301–500 miles, 501–700 miles, etc.). Exhibit A.2 shows the calculation of the domestic revenue thresholds and Exhibit A.3 shows their appli- cation to estimate new nonstop markets. It was assumed that revenue in each market would increase at the same rate as the forecast of total MSP domestic originations. Nonstop service was assumed to be initiated after the revenue in the market grew to exceed the threshold. In Exhibit A.3 the year in which the threshold is forecast to be exceeded is shaded in light green, and the year in which nonstop service is assumed to be initiated is shaded in darker green. Once the initial individual market seat departure forecasts were prepared, they were proportionately adjusted as necessary so that the individual market seat departure forecasts would add up to the forecast of total domestic scheduled seat departures. The same approach was used to estimate new nonstop international markets.

A-4 Guidebook for preparing and Using Airport design day Flight Schedules Exhibit A.4 shows an example of how the fleet mix was estimated in each market. The seat targets to destination (shaded in light green) were based on the annual seat departure forecast by market. The fleet mix was then estimated using the seat targets as a control total. Professional judgment (incorporating airline input, published fleet acquisition, and retirement plans) and current service patterns were used to estimate the fleet mix within each market. The fleet mix forecasts in Exhibit A.4 determined the number of flights by airline and aircraft type that were included in the DDFSs. A.4 Flight Times Albuquerque (see Exhibit A.4) was projected to gain an additional daily arrival and depar- ture flight frequency between 2014 and 2030. Therefore, flight times for the new frequencies were required. The existing flight times provide good schedule coverage for the morning and afternoon. Therefore, it was assumed that with a new frequency Delta would choose to fill the midday gap in the schedule, while remaining consistent with its connecting bank structure (Exhibit A.5). Exhibits A.6 and A.7 graphically depict Delta’s existing connecting bank structure at the airport. The new selected arrival time (13:59) fits in one of Delta’s arrival peaks and the new Source: Table D.3 from MSP Forecast Technical Memorandum, 2015. Geographic Category Average (d) Domestic 0-300 Miles TVF 452,030 MQT 9,839,070 5,145,550 301-500 Miles MBS 25,754,290 CMI 16,687,570 21,220,930 501-700 Miles (east/South) LEX 91,971,300 SGF 65,977,320 78,974,310 501-700 Miles (West) HLN 20,901,150 CPR 19,713,780 20,307,465 701-1000 Miles (East/South) TYS 145,799,270 LIT 181,408,350 163,603,810 701-1000 Miles (West) HLN 20,901,150 COS 114,090,570 67,495,860 1001-1300 Miles (East/South) ORF 260,409,380 CHS 238,465,230 249,437,305 1001-1300 Miles (West) FCA 43,798,090 COS 114,090,570 78,944,330 1301-1800 Miles (East/South) RSW 568,904,770 PBI 446,959,020 507,931,895 1301-1800 Miles (West) SJC 645,208,400 OAK 602,416,030 623,812,215 1801 + Miles (Alaska) FAI 89,356,230 JNU 47,559,220 68,457,725 1801 + Miles (Hawaii/Carib.) 1,308,692,746 (e) HNL 1,142,666,600 1,225,679,673 (a) USDOT O&D data. Includes all domestic revenue in market. 10 percent sample of airline revenue for entire market in 2013. (b) Lowest revenue market in geographic category with non-stop service to MSP. (c) Highest revenue market in geographic category without non-stop service to MSP. (d) Average revenue of lowest revenue market with non-stop service and highest revenue market without non-stop service. (e) HNL revenue level multiplied by average ratio of “lowest with” to “highest without” revenue levels in other geographic categories. Revenue Thresholds for Domestic Nonstop Service at MSP: 2013 Revenue (10 percent sample) (a) Lowest With (b) Highest Without (c) Exhibit A.2. Example of calculation of revenue thresholds.

Source: Table D.4 from MSP Forecast Technical Memorandum, 2015. Geographic Category 2013 2015 2020 2025 2030 2035 MSP Domestic Originations (a) 7,506,520 8,293,726 8,909,272 9,998,486 11,226,675 12,655,356 Domestic 0-300 Miles threshold (b) 5,145,550 5,145,550 5,145,550 5,145,550 5,145,550 5,145,550 (no new non-stop markets assumed) 301-500 Miles threshold (b) 21,220,930 21,220,930 21,220,930 21,220,930 21,220,930 21,220,930 CMI (c) 16,687,570 18,437,589 19,805,995 22,227,402 24,957,760 28,133,827 MHK (c) 12,766,560 14,105,384 15,152,261 17,004,721 19,093,537 21,523,337 SPI (c) 12,678,840 14,008,465 15,048,149 16,887,880 18,962,344 21,375,449 501-700 Miles (east/South) threshold (b) 78,974,310 78,974,310 78,974,310 78,974,310 78,974,310 78,974,310 SGF (c) 65,977,320 72,896,337 78,306,576 87,880,048 98,675,009 111,232,165 EVV (c) 34,602,440 38,231,185 41,068,637 46,089,536 51,751,057 58,336,779 501-700 Miles (West) threshold (b) 20,307,465 20,307,465 20,307,465 20,307,465 20,307,465 20,307,465 CPR (c) 19,713,780 21,781,157 23,397,716 26,258,234 29,483,729 33,235,761 GCC (c) 6,747,150 7,454,721 8,007,997 8,987,026 10,090,969 11,375,123 701-1000 Miles (East/South) threshold (b) 163,603,810 163,603,810 163,603,810 163,603,810 163,603,810 163,603,810 LIT (c) 181,408,350 200,432,577 215,308,332 241,631,131 271,312,483 305,839,089 GSP (c) 146,359,330 161,707,979 173,709,662 194,946,762 218,893,525 246,749,415 GSO (c) 144,579,750 159,741,775 171,597,530 192,576,408 216,232,003 243,749,194 MDT (c) 120,527,640 133,167,329 143,050,775 160,539,633 180,259,912 203,199,377 JAN (c) 113,494,190 125,396,284 134,702,977 151,171,263 169,740,756 191,341,577 HSV (c) 109,349,500 120,816,942 129,783,764 145,650,646 163,542,000 184,353,981 BTV (c) 108,210,950 119,558,993 128,432,452 144,134,127 161,839,196 182,434,482 CAE (c) 96,328,500 106,430,434 114,329,515 128,307,018 144,067,925 162,401,680 701-1000 Miles (West) threshold (b) 67,495,860 67,495,860 67,495,860 67,495,860 67,495,860 67,495,860 COS (c) 114,090,570 126,055,206 135,410,803 151,965,626 170,632,696 192,347,023 ASE (c) 54,554,120 60,275,191 64,748,710 72,664,647 81,590,587 91,973,619 GJT (c) 41,192,640 45,512,497 48,890,355 54,867,508 61,607,293 69,447,297 DRO (c) 36,836,680 40,699,729 43,720,392 49,065,485 55,092,564 62,103,518 1001-1300 Miles (East/South) 249,437,305 249,437,305 249,437,305 249,437,305 249,437,305 249,437,305 HOU (c) 606,263,120 669,841,711 719,556,190 807,526,463 906,720,954 1,022,108,191 CHS (c) 238,465,230 263,472,991 283,027,495 317,629,388 356,646,172 402,032,149 ELP (c) 227,654,350 251,528,378 270,196,374 303,229,581 340,477,530 383,805,922 MHT (c) 185,342,840 204,779,676 219,978,065 246,871,768 277,196,866 312,472,306 SAV (c) 149,903,320 165,623,626 177,915,922 199,667,263 224,193,880 252,724,281 PWM (c) 146,893,780 162,298,477 174,343,986 195,658,635 219,692,843 247,650,452 1001-1300 Miles (West) threshold (b) 78,944,330 78,944,330 78,944,330 78,944,330 78,944,330 78,944,330 FLG (c) 12,141,810 13,415,117 14,410,764 16,172,570 18,159,168 20,470,062 1301-1800 Miles (East/South) threshold (b) threshold (b) 507,931,895 507,931,895 507,931,895 507,931,895 507,931,895 507,931,895 PBI (c) 446,959,020 493,831,449 530,482,754 595,337,609 668,467,363 753,534,992 SRQ (c) 96,396,740 106,505,831 114,410,507 128,397,912 144,169,984 162,516,726 1301-1800 Miles (West) threshold (b) 623,812,215 623,812,215 623,812,215 623,812,215 623,812,215 623,812,215 OAK (c) 602,416,030 665,591,178 714,990,190 802,402,241 900,967,286 1,015,622,324 ONT (c) 311,530,530 344,200,622 369,746,590 414,950,438 465,921,891 525,214,047 1801 + Miles (Alaska) threshold (b) 68,457,725 68,457,725 68,457,725 68,457,725 68,457,725 68,457,725 JNU (c) 47,559,220 52,546,738 56,446,665 63,347,625 71,129,086 80,180,811 1801 + Miles (HI/CR) threshold (b) 1,225,679,673 1,225,679,673 1,225,679,673 1,225,679,673 1,225,679,673 1,225,679,673 HNL (c) 1,142,666,600 1,262,497,627 1,356,197,991 1,522,001,731 1,708,960,542 1,926,438,956 SJU (c) 569,484,840 629,206,506 675,905,112 758,538,765 851,715,733 960,103,131 (a) Table 5. (b) Table D.3. Estimated New Domestic Non-Stop Markets at MSP (c) Base year revenue from USDOT O&D Survey. Assumed to grow at same rate as MSP revenue. New non-stop service assumed to occur five years after threshold is reached. Exhibit A.3. Example of use of revenue thresholds to estimate new nonstop markets.

Source: Modified from Table D.8 from MSP Forecast Technical Memorandum, 2015 Market x Jul-13 Jul-14 Jul-15 Jul-20 Jul-25 Jul-30 Jul-35 x Jul-13 Jul-14 Jul-15 Jul-20 Jul-25 Jul-30 Jul-35 ABQ Albuquerque, NM: Albuquerque International Seat Targets to Destination 306 321 352 389 432 ABQ D 981 DL 319 126 2 0 0 0 0 0 0 252 ABQ D 981 DL 320 150 2 300 0 0 0 0 ABQ D 981 DL 738 160 1 0 0 0 0 0 160 0 00 ABQ D 981 DL 739 180 2 1 0 0 0 0 360 0 180 ABQ D 981 DL 717 110 2 0 0 0 0 0 220 0 ABQ D 981 DL E95E2 110 0 0 0 0 0 0 0 ABQ D 981 DL M90 160 2 2 2 0 320 320 320 0 0 0 2 2 2 2 2 3 3 300 320 320 320 360 380 432 ABR Aberdeen, SD: Aberdeen Regional Seat Targets to Destination 107 131 157 188 228 ABR D 257 DL CRJ 50 2 2 2 1 2 1 100 100 100 50 100 50 0 ABR D 257 DL CR9 76 1 2 3 0 0 0 76 0 152 228 ABR D 257 DL CR7 65 1 0 0 0 0 65 0 0 2 2 2 2 3 3 3 100 100 100 126 165 202 228 Eq ui pm en t Se at s pe r Ai rc ra ft July Aircraft Departures Seat Departures Do m es tic / In te rn at io na l Di st an ce Pu bl is he d Ca rr ie r Exhibit A.4. Example of design day fleet mix estimates by market. 2013 (Existing) 2030 Arrivals Departures Arrivals Departures 9:29 11:45 9:29 11:45 13:59 15:05 18:15 21:35 18:15 21:35 Exhibit A.5. Existing and projected flight times for Albuquerque. Source: Official Airline Guide and HNTB analysis. Exhibit A.6. Delta existing (2013) aircraft arrival banks at MSP.

Case Study examples from MSp ddFSs A-7 selected departure time (15:05) fits in one of Delta’s departure peaks. An early morning departure fitting within Delta’s first departure bank was considered, but that time would have allowed no opportunity to collect connecting passengers from the East Coast, so it was not considered a likely choice for Delta. A.5 Gate Assignments A gating model was used to assign gates to the flights in the DDFS for each of the terminal expansion alternatives. The model incorporated initial assumptions about which airlines would be assigned to which existing gates. These assumptions were adjusted, as necessary, if some airlines needed additional gates or had an excess number of gates. Flights were gated according to two sets of buffer time/spare gate assumptions: (1) 15 minute buffer and spare gates equal to 8 percent of the total, and (2) 25 minute buffer time and no spare gates. The results were presented in Gantt charts (see Exhibit A.8 for an example). A.6 Passengers by Flight USDOT T-100 data was used to estimate base year July load factor by airline for each nonstop market to estimate base year enplanements and deplanements by flight. These load factors were then increased in accordance with the load factor projections in the annual forecast to arrive at 2020 and 2030 load factors by market and airline. The future load factors were then used to estimate 2020 and 2030 enplanements and deplanements by flight. Estimates of peak month passenger originations and terminations by flight took into account (1) market, (2) airline, and (3) time of day. USDOT O&D Survey data is available by quarter Source: Official Airline Guide and HNTB analysis. Exhibit A.7. Delta existing (2013) aircraft departure banks at MSP.

Sources: MSP Forecast Technical Memorandum and HNTB analysis. Airline Color Gate Size AA A01 RG2 AC A02 RG2 AF A03 RG2 AM A04 RG2 AS A05 RG2 CA A06 RG2 DE A07 RG2 DL A08 RG2 EK A09 RG2 F9 A10 RG2 FI A11 RG2 NK A12 RG2 SY A13 RG2 UA A14 RG2 WN C01 NB ZK C02 NB BLOCKED C03 NB UNUSED C04 RG2 CLOSED C05 757 C06 RG2 C07 NB C08 NB C09 NB C10 NB C11 NB C12 NB C13 757 C14 RG2 C15 RG2 C16 RG2 C17 RG2 C18 C19 RG2 C20 RG2 C21 RG2 C22 RG2 C23 RG2 C24 RG2 C25 RG2 C26 RG2 C27 RG2 D01 RG2 D02 757 D03 NB D04 NB D05 NB D06 RG2 E01 NB E02 NB E03 NB E04 NB E05 NB E06 NB E07 NB E08 RG2 E09 NB E10A NB E11 NB E12 WB4 E13 NB 16:00 17:00 18:00 19:0000:00 01:00 02:00 03:00 04:00 Gantt Chart 10:00 11:00 12:00 13:00 14:0005:00 06:00 07:00 08:00 09:00 20:00 21:00 22:00 23:0015:00 Exhibit A.8. Gantt chart showing estimated gate use by time of day.

Case Study examples from MSp ddFSs A-9 but not by month. Consequently, ratios of originations to enplanements and terminations to deplanements were calculated from data for the third quarter of 2013. Foreign-flag carriers do not file O&D data and their origination to enplanement ratios were therefore estimated based on judgment. Exhibit A.9 shows an example of the calculations. Non-Delta carriers have very little connecting traffic; therefore, each carrier’s average ratio of originating to enplanement traffic was used across all markets. Since Delta operates a connecting hub at MSP, individual originating to enplanement and terminating to deplaning passengers were prepared for each nonstop market using third quarter 2013 T-100 and O&D Survey data. Some markets with limited nonstop service had more origina- tions than enplanements. Others with no nonstop service had originations but no enplanements. These excess originations would reach their ultimate destination by connecting through another hub, most likely a Delta hub. Therefore, the originations to enplanement ratios to other Delta hubs (Atlanta, Detroit, Cincinnati, Salt Lake City, New York JFK, and Seattle) were increased proportionately to account for these excess originations. The potential for connecting activity is very limited prior to the first arrival bank of the day or after the last departure bank of the day at MSP. Consequently, early morning enplaning con- nections and late night deplaning connections were capped to not exceed the available deplan- ing connections in the morning or the available enplaning connections in the late evening. Midday originating to enplaning ratios were adjusted downwards to offset the higher ratios in the beginning and end of the day. Ideally, the aggregate bottom-up calculations of design day enplanements and originations would sum exactly to the top-down calculation of average weekday peak month originations and enplanements. Typically, however the two sets of numbers are off by 1 to 2 percent. Therefore, a final proportionate adjustment was made to the enplanement/deplanements and origination/ termination numbers in the DDFS so that they would conform to the base year and forecast totals. A.7 Nonscheduled Operations As noted in Section A.1, nonscheduled operations were not included in the MSP DDFSs. Published Carrier Air Carrier Name Total Deplanements Terminations OD Pct AA American Airlines Inc. 127,858 117,620 91.99% AF Air France 16,308 4,892 30.00% AS Alaska Airlines Inc. 25,394 21,740 85.61% UA United Air Lines Inc. 177,376 139,950 78.90% F9 Fron…er Airlines Inc. 43,970 43,970 100.00% FI Icelandair 12,987 11,688 90.00% WN Southwest Airlines Co. 250,703 243,320 97.06% NK Spirit Air Lines 77,306 72,460 93.73% AC Air Canada 12,454 11,209 90.00% SY Sun Country Airlines 183,809 145,987 79.42% US US Airways Inc. 157,095 151,510 96.44% ZK Great Lakes Airlines 6,796 160 2.35% DL Delta Air Lines Inc. 3,430,278 1,172,416 34.18% Sources: USDOT T100 data and Origin-Des…na…on Survey. Exhibit A.9. Terminating to deplaning ratio by airline – third quarter 2013.

A-10 Guidebook for preparing and Using Airport design day Flight Schedules A.8 Application of Constraints As noted in Section A.2, no physical or policy constraints were assumed to impact demand over the forecast period. A.9 DDFS Updates During the course of the LTCP study, a new gating alternative was developed (Incremental Airlines Relocate Scenario), which moved some but not all of the non-Delta carriers from Ter- minal 1 to Terminal 2. The gating model was operated with gate assignments conforming to the new alternative and revised gate requirements were calculated. This revision did not require an update of the number of flights or flight times. DDFSs have been prepared on behalf of the MAC on several occasions, each time incorporat- ing a new base year schedule and applying a new annual forecast. Since the most recent DDFSs were prepared using new data, it was not possible to bypass any of the DDFS preparation steps. However, institutional knowledge acquired in prior efforts, particularly with regard to airline service patterns, helped speed the DDFS development process. A.10 Quality Assurance and Control The checklist in Appendix E of this guidebook was used to assist in quality control of the MSP DDFSs. Since DDFSs consist of very detailed spreadsheets, pivot tables are very useful for organizing the data so that it can be more easily checked against control totals and for internal consistency. Exhibit A.10 illustrates part of a pivot table of the DDFS that was used to verify that the number and type of Delta aircraft were consistent between arrivals and departures and with the original departure projections (see Exhibit A.4). A.11 Application of Results As noted in Section A.1 the primary objective of the MSP DDFSs was to assist in terminal and landside planning. Sources: MSP Forecast Technical Memorandum and HNTB analysis. Category Number DL 487 DL 487 Match Match D 455 D 455 SAT 3 SAT 3 TRUE TRUE 738 1 738 1 TRUE TRUE E70 2 E70 2 TRUE TRUE ABQ 3 ABQ 3 TRUE TRUE 717 2 717 2 TRUE TRUE 738 1 738 1 TRUE TRUE ABR 3 ABR 3 TRUE TRUE CR9 2 CR9 2 TRUE TRUE CRJ 1 CRJ 1 TRUE TRUE Row Labels Count of D/I Row Labels Count of D/I2 Exhibit A.10. Pivot table cross-check of DDfS arrivals and departures in 2030.

Case Study examples from MSp ddFSs A-11 When future gate requirements were estimated (see Section A.5) and matched to currently available gates it was determined that there would be a shortage of some types of gates (narrow body aircraft gates) and a surplus of other types of gates (turboprop and small regional jet). This information was used to develop a plan to reconfigure the gates at the existing Terminal 1 to bet- ter match the anticipated fleet mix. It was also used to fine tune the phasing of the Incremental Airlines Relocate Scenario so that no new gates were added at Terminal 2 before they were war- ranted based on existing gate capacity at Terminal 1. Curbside capacity is a significant issue at Terminal 1. Two adjustments were required before the DDFS outputs could be applied to the curbside analysis. First, since the MSP originations peak occurs in March, the originations profile from the July DDFSs had to be adjusted for seasonality. Secondly, since departing passengers show up at the curb well before scheduled aircraft take-off, and arriving passengers show up at the curb after aircraft arrival, lead and lag factors had to be applied. The Passenger Toolbox from ACRP Report 82: Preparing Peak Period and Operational Profiles—Guidebook http://onlinepubs.trb.org/onlinepubs/acrp/acrp_rpt_082.pdf was used to make both sets of adjustments. Exhibit A.11 shows an example of the output showing depart- ing passengers (originations) for March 2030 by hour with a lead time (show-up time) factor applied. Since the 2030 DDFS was used to develop the profile, no base year data was required, and therefore the base year columns are blank. A.12 Dealing with Uncertainty The annual forecast included three scenarios, a High Scenario which assumed high economic growth and low fuel prices, a Low Scenario which assumed low economic growth and high fuel prices, and a Low Connecting Percentage Scenario which assumed a downsized connecting pas- senger operation at MSP. Additional DDFSs corresponding to each forecast scenario were not prepared. However, as noted in Appendix B, the majority of forecast uncertainty resides in annual forecasts rather than DDFSs. Gate requirements for each scenario were therefore estimated by adjusting passenger aircraft operations (an output of the annual forecast) in accordance with the forecast scenarios, and keeping gate utilization (an output of the DDFSs) constant. A.13 Communication of Results During the active phase of the LTCP preparation, MAC staff led biweekly working group meetings (in person for local participants and by telephone for non-local participants) to review results and determine subsequent steps. In addition to key stakeholders, DDFS preparers and users were involved in the meetings, and this provided an opportunity to collect input and direc- tion, ask and answer questions, and share results. In addition, a SharePoint site was established in which DDFSs and DDFS-related planning analyses were downloaded. The biweekly working group meetings were very detailed and technical and primarily involved participants who were active in the development of the LTCP. Communication to senior MAC decision makers and the public was primarily the responsibility of MAC staff and involved a higher-level summary of the DDFS results.

A-12 Guidebook for preparing and Using Airport design day Flight Schedules Source: ACRP Report 82: Preparing Peak Period and Operaonal Profiles – Guidebook (2013) and HNTB analysis. 00:00-00:59 00:00-00:59 - 0.0% 01:00-01:59 01:00-01:59 43 0.2% 02:00-02:59 02:00-02:59 227 0.8% 03:00-03:59 03:00-03:59 376 1.4% 04:00-04:59 04:00-04:59 586 2.1% 05:00-05:59 05:00-05:59 2,400 8.7% 06:00-06:59 06:00-06:59 1,373 5.0% 07:00-07:59 07:00-07:59 2,332 8.5% 08:00-08:59 08:00-08:59 1,656 6.0% 09:00-09:59 09:00-09:59 2,008 7.3% 10:00-10:59 10:00-10:59 1,295 4.7% 11:00-11:59 11:00-11:59 1,673 6.1% 12:00-12:59 12:00-12:59 1,806 6.6% 13:00-13:59 13:00-13:59 2,212 8.0% 14:00-14:59 14:00-14:59 937 3.4% 15:00-15:59 15:00-15:59 2,221 8.1% 16:00-16:59 16:00-16:59 1,485 5.4% 17:00-17:59 17:00-17:59 1,983 7.2% 18:00-18:59 18:00-18:59 1,536 5.6% 19:00-19:59 19:00-19:59 433 1.6% 20:00-20:59 20:00-20:59 861 3.1% 21:00-21:59 21:00-21:59 77 0.3% 22:00-22:59 22:00-22:59 - 0.0% 23:00-23:59 23:00-23:59 - 0.0% Total: Total: 27,520 100.0% MSP 2030 T1 Hybrid Alternative AIRPORT COOPERATIVE RESEARCH PROGRAM Peak Period and Operational Profile Toolbox PassengerModule DESIGN DAY DERIVATIVE PROFILE ESTIMATES (Assumes no Peak Spreading) Departing Passenger Count - Origin-Desˆnaˆon Passengers Base Year Forecast Year Design Day Derivaˆve Profile Future Design Day Derivaˆve Profile 8.72% Percent Peak Value: Peak Value: 2,400 5:00 Hour Passengers by Hour Percent Hour Passengers by Hour Peak Hour: Peak Hour: 05:00-05:59 Exhibit A.11. Application of ACRP Report 82 passenger toolbox – March 2030 originating passenger curbside profile.