Chapter 3 – Projections of Aviation Demand Chapter 3 Projections of Aviation Demand This chapter contains aviation activity forecasts for the University Park Airport (Airport) over a 20-year planning horizon. Aviation demand forecasts are an important step in the master planning process. Ultimately, they form the basis for future demand-driven improvements at the Airport, provide data from which to estimate future off-airport impacts, such as noise and traffic, and are incorporated by reference into other studies and policy decisions. This chapter, which presents aviation activity forecasts through 2030, is organized as follows: 3.1 Forecasting Approach 3.2 Enplaned Passengers 3.3 Based Aircraft 3.4 Based Aircraft Fleet Mix 3.5 Total Operations 3.6 Commercial Aircraft Operations 3.7 General Aviation Operations 3.8 Military Operations 3.9 Instrument Operations 3.10 Cargo Activity 3.11 Peak Operations 3.12 Design Aircraft 3.13 Forecast Summary and FAA TAF Comparison 3.14 Revised Enplanement Forecast The Federal Aviation Administration (FAA) projects future aviation activity through its Terminal Area Forecasts (TAF) which were used to compare projections prepared for this master plan. Forecasts that are developed for airport master plans and/or federal grants must be approved by the FAA. It is the FAA’s policy, listed in Advisory Circular (AC) 150/5070-6B, Airport Master Plans, that FAA approval of forecasts should be consistent with the TAF. Master plan forecasts for operations, based aircraft and enplanements are considered to be consistent with the TAF if they meet the following criteria: • Forecasts differ by less than ten percent in the five-year forecast and 15 percent in the ten- or 20- year period If the forecast is not consistent with the TAF, differences must be resolved prior to using the forecast in FAA decision-making. This may involve revisions to the airport sponsor’s submitted forecasts, adjustments to the TAF, or both. FAA decision-making includes key environmental issues (e.g., purpose and need, air July 2016 Page 3-1 Chapter 3 – Projections of Aviation Demand quality, noise, land use), noise compatibility planning (14 CFR Part 150), approval of development on an airport layout plan and initial financial decisions. This chapter examines data that pertains to aviation activities and describes the projections of aviation demand. It should be noted that projections of aviation demand are based on data through the year 2012, as this was the most recent calendar year for which a full 12 months of historical data was available at the time these forecasts were developed in May 2013. 3.1 Forecasting Approach A number of forecasting techniques that range from subjective judgment to sophisticated mathematical modeling may be used to project aviation activity. These forecasts incorporate local and national industry trends in assessing current and future demand. Socio-economic factors such as local population, retail sales, and employment have also been analyzed for the effect they may have had on historical and may have on future levels of activity. The comparison of the relationships among these various indicators provided the initial step in the development of realistic forecasts for future aviation demand. The following sections provide an assessment of historical trends of aviation activity data at the local and national level. Aviation activity statistics on such items as passenger enplanements, aircraft operations and based aircraft are collected, reviewed and analyzed. Since a large number of variables affect a facility plan, it is important that each one be considered in the context of its use in the plan. In statistical analysis, correlation (often measured as a correlation coefficient) indicates the strength of a linear relationship between two independent variables. In this analysis, the Pearson product-moment correlation coefficient is calculated for some methodologies. The closer the correlation coefficient is to 1.0, the stronger the correlation between the variables. Methodologies used to develop forecasts described in this section include: • Time-series methodologies • Market share methodologies • Socio-economic methodologies 3.1.a Time-Series Methodologies Historical trend lines and linear extrapolation are widely used methods of forecasting. These techniques utilize time-series types of data and are most useful for a pattern of demand that demonstrates a historical relationship with time. Trend line analyses used in this chapter are linearly extrapolated using the least squares method to known historical data. Growth rate analyses used in this chapter examined the historical compounded annual growth rates (CAGR) and extrapolated future data values by assuming a similar CAGR for the future. Page 3-2 July 2016 Chapter 3 – Projections of Aviation Demand 3.1.b Market Share Methodologies Market share, ratio, or top-down methodologies compare local levels of activity with a larger entity. Such methodologies imply that the proportion of activity that can be assigned to the local level is a regular and predictable quantity. This method has been used extensively in the aviation industry to develop forecasts at the local level. Historical data is most commonly used to determine the share of total national traffic activity that will be captured by a particular region or airport. The FAA develops national forecasts annually in its FAA Aerospace Forecasts document, the latest edition of which is the FAA Aerospace Forecasts Fiscal Year (FY) 2013-2033. 3.1.c Socio-economic Methodologies Though trend line extrapolation and market share analyses may provide mathematical and formulaic justification for demand projections, there are many factors beyond historical levels of activity that may identify trends in aviation and its impact on local aviation demand. Socio-economic or correlation analyses examine the direct relationship between two or more sets of historical data. Local market conditions examined in this chapter include population, total employment and total retail sales for Centre County and its surrounding counties of Blair, Cambria, Clearfield, Clinton, Huntingdon, Mifflin and Union. Historical and forecasted socio-economic statistics for this service area were obtained from the economic forecasting firm Woods & Poole Economics, Inc. Projections of population for Centre County were also obtained from the Centre Regional Planning Agency and it is these population projections for Centre County population that are utilized in this analysis. Based upon the observed and projected correlation between historical aviation activity and the socio-economic data sets, future aviation activity projections were developed. Table 3-1 presents forecasts of socio-economic indicators that are utilized in various locations of this chapter. July 2016 Page 3-3 Chapter 3 – Projections of Aviation Demand Table 3-1: Projected Socio-Economic Indicators Regional Population Regional Employment Regional Total Retail Sales Year (Thousands) (Thousands of jobs) (mil, 2005$) Historical 2000 672,165 366,113 7,937.64 2001 672,152 366,730 7,915.59 2002 673,850 368,606 7,924.97 2003 674,519 368,938 8,038.32 2004 674,975 372,741 8,267.87 2005 675,320 377,206 8,447.15 2006 679,805 382,061 8,610.37 2007 680,445 383,977 8,591.87 2008 681,998 383,267 8,181.62 2009 682,768 375,844 7,515.43 2010 682,992 371,093 7,793.78 2011 683,543 370,999 8,157.95 2012 684,371 375,139 8,242.96 Projected 2017 695,476 398,733 8,695.08 2022 704,968 423,797 9,200.45 2027 715,174 450,077 9,750.43 2032 725,151 477,799 10,354.12 CAGR (2012-2032) 0.29% 1.22% 1.15% Note: Region includes Centre County and its surrounding counties of Blair, Cambria, Clearfield, Clinton, Huntingdon, Mifflin, and Union. Source: Woods & Poole Economic Inc., except for projections of Centre County Population from the Centre Regional Planning Agency 3.2 Enplaned Passengers Enplanements are defined as the activity of passengers boarding commercial service aircraft that depart an airport and include both revenue and non-revenue passengers on scheduled commercial service aircraft or unscheduled charter aircraft. Passenger enplanement data is provided to Airport management and the FAA by commercial passenger service carriers, who maintain counts on the number of people that are transported to and from an airport. This section examines the passenger enplanement data and describes future passenger projections. 3.2.a Enplanement History At the time of this analysis in May of 2013, FAA enplanement totals for 2012 were not currently available. Therefore, the 2012 enplanement total was estimated based upon the number scheduled passenger enplanements reported for 2012 by the carriers to the Centre County Airport Authority (134,452), combined with the average number of charter enplanements reported to the FAA for 2008 through 2011 (4,036), for an estimated 2012 total of 138,488 enplanements. Between 1994 and 2012, passenger enplanements at the Airport have fluctuated between a low of 94,343 in 1995 and a high of 144,160 in 2007. From 1994 Page 3-4 July 2016 Chapter 3 – Projections of Aviation Demand through 2012, enplanements have increased from 94,427 to an estimated 138,488, at a CAGR of 2.15 percent. Table 3-2 presents the historical enplanements at the Airport since 1994. Table 3-2: Historical Enplanements Year UNV Enplanements 1994 94,427 1995 94,343 1996 97,801 1997 104,748 1998 109,516 1999 126,945 2000 125,659 2001 116,113 2002 120,938 2003 123,871 2004 137,066 2005 143,800 2006 132,543 2007 144,160 2008 133,777 2009 130,527 2010 143,531 2011 144,054 2012 138,488 ESTIMATED CAGR (1994-2012) 2.15% Notes: 1. CAGR = Compounded Annual Growth Rate Notes: CAGR = Compounded Annual Growth Rate 2. 2012 Estimated based upon 2012 schedule 2012 Estimate based upon 2012 schedule airlines from CCAA plus 2008 to 2011 average charter enplanements as reported airlines from CCAA plus 2008 to 2011 average by FAA ACAIS charter enplanements as reported by FAA ACAIS Sources:Sources: HistoricalHistorical Enplanements Enplanements – FAA ACAIS- FAA ACAIS 3.2.b Federal Aviation Administration Forecast The FAA records passenger enplanements for all commercial service airports and releases an updated version of the TAF every year.