National Academies Press: OpenBook

Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide (2016)

Chapter: Chapter 6 - Case Study Airport

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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
×
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Suggested Citation:"Chapter 6 - Case Study Airport." National Academies of Sciences, Engineering, and Medicine. 2016. Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide. Washington, DC: The National Academies Press. doi: 10.17226/24662.
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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.

Getting Started with RPZ_RAT 29 within the RPZ, and the average traveling speed, and RPZ_RAT will derive an estimate for the average population density accordingly. Question: I want to analyze the risk for a worst-case scenario when an aircraft crashes into a highway during the rush hour. How do I do that? Answer: Instead of speed limit, enter the speed at which vehicles travel on average during the rush hour. Also, instead of using the average daily traffic, calculate the traffic from the number of vehicles that travel through the RPZ during the rush hour. The tool incorporates seven land use types as defaults, as shown in Figure 4.8. A user may create new types by clicking on Create new land use type at the top ribbon. A dialog box opens as shown in the figure where the user can create the new type and assign its colors. When all the land uses within the RPZs of the airport under review are entered, the user sets the desired grid cell area in the Analysis Setting and generates the grid system. When the grid system is generated, the software is ready to conduct the risk analysis; the Run Analysis button becomes active in the sidebar. The grid must be regenerated if changes to the land uses or the runways are made. Generating the grid cells and running the analysis may take a few minutes to hours depending on the size of the grid system, the size and the number of the RPZs, the number of movements at the airport, and computer hardware specifications or performance. 4.6 Useful Software Tool Features Embedded Aircraft Type Database The RPZ_RAT includes some features that make it flexible for various airport applications. The tool is loaded with an embedded database of various aircraft types and their performance char- acteristics. As noted earlier, one of the inputs to the software is the airport’s movement records, Figure 4.8. Incorporated land use types. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

30 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide which include aircraft types identified by the FAA codes. To perform the analysis, the software looks up the aircraft in the movement record from the embedded database to read the required characteristics such as maximum takeoff weight (MTOW), landing distance required (LDR), accelerated stop distance required (ASDR), equipment class, engine type, and aircraft dimensions. The tool incorporates 619 aircraft types in the database. Although due diligence was exercised to assemble it, the data were gathered from various resources with slight variations. Thus, the database is made editable in case further refinements are found desirable. When the NOD input file is entered, the software first checks the aircraft types against the embedded database. If an aircraft type is not available in the database, a warning message appears at the bottom window of the software. Although many aircraft types in use are included in the data- base, some small or older aircraft may not be included. Also, new types are likely to be introduced in the future. Therefore, the database allows the addition of new records. To access the database, choose Show aircraft from the top ribbon. Figure 4.9 depicts a snapshot of the database. Create New allows users to insert new entries. Duplicate allows the user to quickly select an aircraft from the database and edit it to create a new entry. Reset to Defaults removes all the custom entries. If the tool warns for missing aircraft types, a user can proceed with the analysis or add the missing aircraft types with performance characteristics into the embedded database. If an aircraft type with missing characteristics often flies at the airport, it is reasonable to add it to the database. Depending on available resources to support the analysis, adding missing aircraft types with only a handful of movements over the course of a year may not be worthwhile. Legend Window The map of the airport may get very crowded when RPZs, likelihood contours, and land uses are compiled over one another. To make it easier to use the map, the tool makes it possible to hide or reveal various features using the legend window from the top ribbon. To open the legend window, click on the box at the top ribbon that says Show Legend. As shown in Figure 4.10, it is possible to hide the land uses, runways and RPZs, likelihood contours, and labels on the Figure 4.9. Embedded aircraft types database. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Getting Started with RPZ_RAT 31 Figure 4.10. Legend window. satellite map by removing the checkmark. The user may also hide the grid lines and the under- lying satellite map to better visualize the shades of the crash likelihood contours, as shown in the figure. The legend also references the crash likelihood contour intervals corresponding with the colors. The tool generates 10 color-coded categories. Each category includes 10% of the cells. In other words, 10% of the cells with the least crash likelihoods are colored with the lightest shade of blue, and so on. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

32 C H A P T E R 5 On completion of the analysis, the software generates two sets of outputs: crash likelihood contours and an Excel file that contains various details and graphics. When the analysis is com- plete, the software prompts the user to name and save the Excel file. The contours are simultane- ously saved on the map. 5.1 Crash Likelihood Contours RPZ_RAT calculates the crash likelihood for every cell that overlaps with an RPZ. The tool generates crash likelihood contours by color-coding the cells according to their respective crash likelihood values. The crash likelihood values are classified into ten, 10-percentile groups. Cells with the top 10% of likelihood values are given the darkest color, with lighter shades assigned to successively less likely 10-percentile groups. As intuition might suggest, cells closer to the run- way ends have higher crash likelihoods than cells farther away. Also, cells closer to the extended runway centerline have higher crash likelihoods than cells farther from the centerline. Crash likelihood is analyzed for the airport as a whole, and the mapping of crash likelihood contours represents the airport-wide analysis. This allows a direct comparison of crash likeli- hood among different locations in all RPZs. Figure 5.1 depicts an example for a hypothetical situation where 90% of the movements were randomly assigned to one runway and 10% were assigned to the second runway. As a result, most cells in the RPZs of the busier runway are colored with the darkest shade while the RPZs of the other runway are colored with lighter colors. This indicates that an accident is more likely to occur within the RPZs of the busier runway, as would be intuitively expected. 5.2 Excel Output File The software also generates an Excel output file that includes the following sheets: • Airport data sheet, which includes data provided by the user (e.g., the number of move- ments at the airport, annual movement growth rate, runway declared distances, and RPZ dimensions) • One summary sheet that compares results from all RPZs • One sheet for each RPZ with detailed analysis results Summary Sheet of Excel Output File First Table: Event Likelihood Models Results The software develops a summary sheet that includes several tables and figures. The first table presents the expected number of events in every 10 million movements. The results are displayed Understanding Analysis Results þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Understanding Analysis Results 33 for every type of event and for every RPZ. Four types of events are modeled in this study: landing overrun, landing undershoot, takeoff overrun, and takeoff overshoot. Although overruns usu- ally affect the RPZ areas closer to the runway end, takeoff overshoot and landing undershoot are more spread and may affect RPZ areas farther from the runway. Question: How does one determine which accident type is most likely in a particular RPZ? Answer: Look at the first table in the summary sheet of the Excel output file. Find which accident type has the highest value for the RPZ of interest. Question: How does one determine which RPZ is most likely to have a landing undershoot accident? Answer: Look at the first table in the summary sheet of the Excel output file. Find which RPZ has the highest value for the landing undershoot accident. Second Table: Location Models Results Historical accident records indicate that not all accidents occur in a runway RPZ—roughly 45% of historic landing overruns and 25% of takeoff overruns are contained within 200 feet from the end of the runway before the RPZ begins. The second table in the summary sheet of the Excel output file provides estimates that an event extends into the boundaries of an RPZ. The values can be interpreted as the percentage of the accidents that, if they occurred, would affect the RPZ. The values depend on the RPZ size. RPZs with similar dimensions will have the same value for all accident types. For a specific type of accident, a larger RPZ is expected to have a higher value for every type of accident. Figure 5.1. Generated grid system and crash likelihood contours for an example scenario. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

34 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide When runway thresholds are NOT displaced, a takeoff overrun accident is more likely to occur in the RPZ than other accident types. On the other hand, a takeoff overshoot accident is least likely to occur in the RPZ. This reflects the historic accident data on which the RPZ_RAT analytical routines are based. Takeoff overruns tend to go farther from the runway end and thus enter the RPZ, and takeoff overshoots are the most widely scattered accident type. When two RPZs are the same size, location likelihood results presented in the second table will be the same for both RPZs for every accident type. However, depending on the grid cell size and the runway heading, slight differences may be observed which are due to approximating the RPZ trapezoidal area with square cell grids. Third Table: RPZ Crash Likelihood Results The third table in the summary sheet of the Excel output file provides the expected number of annual events in each RPZ. To obtain the estimate, findings from the likelihood models, location models, and number of movements on each runway are accounted for. Expectedly, the number of accidents in any given year is usually very small and is presented with scientific notation. Scientific notation is the standard way of showing very large or very small numbers, making it easier to communicate them. The scientific notation format has a multiplier which is only a digit with one or more decimals, and another number which is the power of 10. For example, 20,000 is the same as 2×104 and could be shown as 2.0E04 in scientific notation. As another example, 0.0002 is the same as 2×10–4 and can be shown as 2.0E-04 in scientific notation. Another statistic the tool calculates is the average number of years between accidents in each RPZ. The software uses the estimated annual crash likelihood and combines it with the antici- pated traffic growth to derive the average number of years between accidents. The table also includes the RPZ rankings from the highest crash likelihood to the lowest. It is common to see large numbers calculated for the average number of years between accidents for each RPZ, especially for small airports. The user should keep in mind what this statistic means – the average period of time between accidents occurring in the specific RPZ. This statistic should not be interpreted as the number of years between accidents at the airport as a whole, which is expected to happen more frequently. To calculate average number of years between accidents for the entire airport, accident likelihoods from all runways should be combined and the limitation to RPZ boundaries should be removed as well. The tool does not provide the statistic. Fourth Table: RPZ Risk Results The fourth table in the summary sheet of the Excel output file presents RPZ risks. To obtain the RPZ risk, the tool combines the crash likelihoods with the consequence models. The RPZ risk presents the expected number of fatalities among people on the ground in a year. The RPZ risk value is tied to the land uses identified inside the RPZs and the population densities calculated or assigned to them. If an RPZ has no land use identified or the land use has no population, the risk will be returned as zero. Given that the expected number of fatalities in a year is usually very small, the tool calculates the average number of years between fatalities, accounting for potential airport traffic growth. The RPZs are also ranked with respect to their risk from the highest to the lowest. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Understanding Analysis Results 35 Fifth Table: Land Use Risk Results The last table in the summary sheet of the Excel output file presents the risk associated with each land use. The table notes the RPZ(s) within which the land use is located, the population density in persons per square feet, and the area of the land use. Most importantly, the tool presents the risk associated with each land use. The risk is presented in terms of the expected number of fatalities in a year. The tool also ranks the risk of fatalities for each land use in the RPZs at the airport from the highest to the lowest. Although the risk rankings of the land uses are not automatically illustrated on the software map, users can consult this table to identify the risk rankings and highlight the land use on the map by clicking on its name in the sidebar window. It is anticipated that analysts are most interested in determining which land use at the airport poses the highest level of risk to the people on the ground. The answer is presented in the last table of the Summary sheet of the Excel output file. Question: To optimally mitigate airport risk, which land use should be treated first? Answer: Besides the risk analysis results, economic analysis is required as well. It may make more sense to treat a few less risky land uses that are significantly less costly to accomplish than the riskiest land use which is very expensive. For a set budget, the analyst must determine what mitigation plan results in the greatest risk reduction for the airport. The summary sheet also includes several graphs of the same information presented in the tables next to the tables discussed, thus making it easier to compare various RPZs and land uses. RPZ Sheets of Excel Output File The software generates one sheet for every RPZ at the airport. The contents of the RPZ sheets provide the detailed information that underlies the findings in the summary sheet. The RPZ sheets are intended for advanced analysts interested in digging further into the results presented in the summary sheet. To understand the level of detail presented, a user should master the project report and the modeling framework. Information presented in the summary sheet is sufficient as a foundation for decision making. As illustrated in Figure 5.2, RPZs are named for the runway end closest to the RPZ. Table 5.1 describes the contents of the RPZ sheets. When considering a particular RPZ, movements on both runway ends are accounted for. Landings on the closer runway end may undershoot the runway and crash in the RPZ. Also, takeoffs and landings from the opposite runway may overrun or overshoot the runway and crash in the RPZ. In short, in addition to some of the findings presented in the summary sheet, an RPZ sheet includes the likelihood estimates for every movement that may crash in the RPZ. The RPZ sheets also include histograms for each accident type. Histograms are helpful to understand the distribution of the likelihoods for each accident type. In risk analysis, RPZs are named according to the runway end they are closest to. For example, in Figure 5.2, RPZ 15 encompasses the approach RPZ of Runway 15 as well as the departure RPZ of Runway 33. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

36 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide RPZ 15 RWY 15 Approach RPZ RWY  parr RPZ Figure 5.2. RPZ naming convention for risk analysis. Excel RPZ sheet heading Description LDOR_freq Overrun likelihood for every arrival on opposite runway LDUS_freq Undershoot likelihood for every arrival on runway TOOR_freq Overrun likelihood for every departure from opposite runway TOOS_freq Overshoot likelihood for every departure from opposite runway LDOR landings challenging Number of arrivals on opposite runway Average impact area (MTOW)_LDOR Average impact area calculated from aircraft mix arriving on opposite runway using MTOW Average impact area (wingspan)_LDOR Average impact area calculated from aircraft mix arriving on opposite runway using wingspan LDOR location likelihood Likelihood of a LDOR event crossing into the boundaries of the RPZ LDUS landings challenging Number of arrivals on runway Average impact area (MTOW)_LDUS Average impact area calculated from aircraft mix arriving on runway using MTOW Average impact area (wingspan)_LDUS Average impact area calculated from aircraft mix arriving on runway using wingspan LDUS location probability Likelihood of a LDUS event crossing into the boundaries of the RPZ Takeoffs challenging Number of departures from opposite runway Average impact area (MTOW)_TO Average impact area calculated from aircraft mix departing fromopposite runway using MTOW Average impact area (wingspan)_TO Average impact area calculated from aircraft mix departing fromopposite runway using wingspan TOOR location likelihood Likelihood of a TOOR event crossing into the boundaries of the RPZ TOOS location likelihood Likelihood of a TOOS event crossing into the boundaries of the RPZ Annual crash likelihood The expected number of crashes of any type within the boundaries of the RPZ in a year Number of years between crashes On average, how often a crash is expected to occur within the RPZ Table 5.1. Description of contents in RPZ sheets of output file. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

37 C H A P T E R 6 6.1 Case Study Purpose The Runway Protection Zone Risk Assessment Tool (RPZ_RAT) has been developed as a quantitative tool to estimate risks to the populations on the ground and within the runway pro- tection zone (RPZ). This case study was undertaken to demonstrate the use of the RPZ_RAT. Five specific objectives were identified in order to meet this goal: • Identify reliable sources of input data • Describe necessary formatting conventions for required input data • Present example output data from a successful RPZ_RAT analysis run • Provide an interpretation of the output results to assist potential end users • Identify potential benefits of analysis findings This chapter describes the measures taken to achieve the above objectives. The RPZ scenarios prescribed in this case study are intended to represent examples of common land use encroach- ments at various airports through the United States. These scenarios are hypothetical and the results of the case study are not applicable to any specific airport. Any similarities with current RPZ encroachments at existing airports are coincidental and therefore not applicable for pur- poses other than the intention of this study. 6.2 Case Study Airport Description To achieve the objectives of the case study, an airport with various RPZ configurations and encroaching land uses was hypothesized, based on an actual airport in the United States. The case study airport is a regional commercial service airport supporting a mix of commercial, air taxi, and general aviation operations. The airport has two runways and associated taxiways. Figure 6.1 is a plan view depiction of the airport. The Airport Traffic Control Tower (ATCT) operates daily from 6:00 a.m. to 11:00 p.m. The airport has precision instrument approaches to both ends of the primary runway (Runway 6-24) and nonprecision approaches to all runway ends. The RPZ dimensions for each runway are based on the aircraft approach category, airplane design group (ADG), and visibility minimum associated with the specific runway end. This information was obtained from the case study airport’s airport layout plan (ALP). Each runway end has both an approach and a departure RPZ with separate dimensions. RPZ properties for the runways at the case study airport are summarized in Table 6.1. The number of operations occurring on runways is correlated with the likelihood of accidents in the RPZs. In other words, RPZs exposed to a higher number of movements are more likely to Case Study Airport þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

38 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide witness an accident when everything else is equal. The analysis began with operations data for fiscal year 2015 (October 1, 2014, to September 30, 2015) at the case study airport taken from the FAA’s Air Traffic Data Activity System. The sample included 32,130 civilian operations during that period. The RPZ_RAT is not designed to assess accident risk associated with military-type aircraft, so military operations were removed from the operations. The FAA Terminal Area Forecast indicates operations at the case study airport will grow at a rate of 0.2% per year over the next 25 years, reaching 34,202 in fiscal year 2040. Figure 6.1. Case study airport. RPZ properties 2 20 6 24 Visibility minimum 3/4 miles 3/4 miles 1/2 miles 1/2 miles Approach category C C C C Aircraft design group III III IV IV Approach RPZ Inner width (feet) 1,000 1,000 1,000 1,000 Outer width (feet) 1,510 1,510 1,750 1,750 Length (feet) 1,700 1,700 2,500 2,500 Departure RPZ Inner width (feet) 500 500 500 500 Outer width (feet) 1,010 1,010 1,010 1,010 Length (feet) 1,700 1,700 1,700 1,700 Table 6.1. Case study airport RPZ properties. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Case Study Airport 39 6.3 Preparing Input Files for RPZ_RAT To develop estimates of RPZ risk, the RPZ_RAT requires input data files for the airport opera- tions and the weather conditions that occurred during the study period. The data are loaded into the model in a Normal Operation Data (NOD) file and a weather data file. Building the NOD File The NOD file provides the movement records needed to perform the analysis. The movement records include eight fields reflecting either historical or hypothesized data for the study year. Summary descriptions of the eight attribute fields are listed in Table 6.2. RPZ_RAT users may select any data source available to them for the NOD file. The more robust and accurate the input data, the better the outputs. The NOD file used for case study analysis was developed using historical data for instrument flight rules (IFR) operations occur- ring from October 2014 through September 2015 and estimated visual flight rules (VFR) opera- tions at the case study airport. IFR Operations The starting point for developing the NOD file was operations data secured from FlightAware, a private company providing aviation data and services to the industry. FlightAware derives operational data from the FAA Aircraft Situational Display to Industry (ASDI) data and Auto- matic Dependent Surveillance–Broadcast (ADS-B) data. Thus, only data for aircraft operators filing flight plans with the FAA or using ADS-B transponders are secured. For the most part, this includes only aircraft operating under Instrument Flight Rules (IFR). Although the absence of operations for aircraft flying under Visual Flight Rules (VFR) was a shortcoming, FlightAware was chosen because of the high level of detail provided for the IFR operations, which is needed for the NOD file. The FlightAware data contained 17,910 records for operations at the case study airport and indicated aircraft type, date and time, runway used, and whether the operations were arrivals or departures for the 12-month research period. This was compared with the FAA Air Traffic Activ- ity Data System (ATADS) data, which reported 16,812 IFR operations during the same period (FAA, 2015). Thus, it was assumed that FlightAware had recorded 16,812 IFR operations and 1,098 VFR operations. These VFR operations had filed flight plans or were flown by operators that had filed flight plans. Attribute name Description HOD_ID An identifier unique to each operation record entry. DATE&TIME The year, month, day, hour, minute, and second in which the operation occurred. RUNWAY_DESIGNATION Indicates the runway associated with the operation record entry. BOUND Indicates either “A” for arrival or “D” for departure. FLIGHT_NO Indicates the flight number associated with the recorded operation. FAA_Code The FAA code assigned to the aircraft, usually indicating its make, model and series, associated with the recorded operation. FLIGHT_Category Indicates whether the operation is “COM” for commercial, “CAR” for cargo, “GA” for general aviation, or “AIR” for air taxi or commuter flights. FLIGHT_Type Indicates whether the recorded operation was either a “D” for domestic or “I” for international flight. Table 6.2. NOD data file attributes field. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

40 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide Estimation of VFR Operations The ATADS data indicated that 32,130 civilian operations occurred during the sample period – 16,812 IFR operations and 15,318 VFR operations. It was assumed that the FlightAware data had captured all of the IFR operations and 1,098 VFR operations, leaving 14,220 VFR operations unaccounted for. Detailed parameters for the residual VFR operations had to be estimated for inclusion in the NOD file. To develop a reasonable representation of the residual VFR operations that occurred during the sample period, an average daily schedule of VFR flight activity was developed based on tower activity counts at the case study airport. The first step in developing the average daily schedule was to estimate the number of residual VFR flights occurring on an average day. The weather data were reviewed to determine the percentage of the year during which instrument meteo- rological conditions (IMC) were absent, as VFR operations could occur during those times. Instrument meteorological conditions were considered to be weather conditions with visibility of 3 or fewer statute miles, or a ceiling lower than 1,000 feet. Instrument meteorological condi- tions were found to occur 8% of the year, with visual conditions occurring 92% of the year. The initial distribution of residual VFR operations to an average day was accomplished by dividing the 14,220 VFR operations by 336 days (92% of the days of the year). This yielded 42 average daily VFR operations. Assuming an even split between arrivals and departures, an average daily schedule of 21 arrivals and 21 departures needed to be developed. Representative aircraft also needed to be identified for the average daily schedule of residual VFR flights. Tower records for the month of October 2015 were examined to determine the most common non-jet GA aircraft operating at the airport, because these would likely account for VFR operations. Numerous aircraft types were represented in the data, but only four models amounted to 5% or more of the total VFR operations. They were used to populate the average daily schedule: • BE20 - Beech 200 Super King • BE9L - Beech King Air 90 • C172 - Cessna Skyhawk 172/Cutlass • SR22 - Cirrus SR 22 The FlightAware data were analyzed to determine temporal patterns in daily arrivals and departures, so that the residual operations could be scheduled at times reflecting the average daily pace of operations. The proportion of hourly traffic was determined for arrivals and depar- tures, and the average daily arrivals and departures were distributed accordingly throughout the day. The average daily schedule developed for the residual VFR operations is presented in the NOD file format in Table 6.3. The average daily schedule of residual VFR operations was duplicated 365 times, inserted into the FlightAware records, and sorted to array all operations (VFR and IFR) in the proper time sequence. All residual VFR operations scheduled during hours with instrument meteorological conditions were identified using Microsoft Excel functions comparing the hourly NOD data with the hourly weather data. Residual VFR operations overlapping with instrument meteoro- logical conditions were deleted from the database. The elimination of the VFR operations occur- ring during instrument meteorological conditions was necessary to ensure that VFR operations were not over counted. The average daily VFR schedule was developed, assuming 336 days of VFR conditions, but the schedule was then applied to all 365 days of the year. Elimination of VFR operations occurring during IMC hours for each day in the study year was necessary to ensure that the annual sum of residual VFR operations would approximate the control total of 14,220. Once the insertion and scrubbing of the residual VFR operations was completed, a total of 31,663 operations were in the NOD file. The operations in the NOD file were 1.5% less than the actual total of 32,130 operations reported for the airport in the study period. Although this þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Case Study Airport 41 Time FAA_Code Runway Designation Bound (Arrival, Departure) Flight Category Flight Type (Domestic, International) 6:01 BE20 20 D GA D 6:07 BE20 6 A GA D 6:15 SR22 20 D GA D 6:30 BE9L 20 D GA D 6:45 C172 20 D GA D 7:30 BE20 6 D GA D 8:15 SR22 24 A GA D 8:45 BE9L 6 D GA D 9:15 C172 24 A GA D 9:30 BE20 6 D GA D 9:45 SR22 24 A GA D 10:01 BE9L 24 A GA D 10:15 C172 24 D GA D 10:30 BE20 24 A GA D 10:45 SR22 24 D GA D 11:15 BE9L 6 D GA D 11:30 C172 24 A GA D 11:45 BE20 6 D GA D 12:15 SR22 24 A GA D 12:45 BE9L 6 D GA D 13:15 C172 24 A GA D 13:45 BE20 6 D GA D 14:15 SR22 24 A GA D 14:45 BE9L 24 D GA D 15:01 C172 24 A GA D 15:15 BE20 6 D GA D 15:30 SR22 24 A GA D 15:45 BE9L 6 D GA D 16:01 C172 24 A GA D 16:15 BE20 6 D GA D 16:30 SR22 24 A GA D 16:45 BE9L 6 D GA D 17:15 C172 24 A GA D 17:45 BE20 6 D GA D 18:15 SR22 24 A GA D 18:45 BE9L 6 D GA D 19:15 C172 24 A GA D 19:45 BE20 6 D GA D 20:30 SR22 24 A GA D 21:15 BE9L 20 D GA D 21:45 C172 24 A GA D 23:30 BE20 24 A GA D Table 6.3. Average daily VFR operations schedule by runway. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

42 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide discrepancy could have been addressed through another iterative adjustment in the average daily schedule, the deviation was considered small enough to allow the case study analysis to move ahead. Thus, the NOD operations total of 31,663 was used for subsequent analysis. The FlightAware data included estimates of the runways used for each arrival and departure during the 12-month period of observation. Runway assignments for the residual VFR opera- tions were made based on the hourly runway use patterns in the FlightAware data. Runway 6-24, the primary runway, was used most often, with Runways 6 and 24 combining for 83% of total operations. Runway use at the airport as included in the case study analysis is summarized in Tables 6.4 and 6.5. All fields were formatted for compatibility with the RPZ_RAT NOD input. Building the Weather Data File A database of weather records for the sample period was obtained from the National Cen- ters for Environmental Information (NCEI, 2015). Some records, however, had voids in the Operation type 2 20 6 24 Total Arrivals Cargo 129 13 62 43 247 Commercial 93 86 1,947 3,034 5,160 GA 657 535 970 7,964 10,126 All Arrivals 879 634 2,979 11,041 15,533 Departures Cargo 8 4 35 7 54 Commercial 462 654 3,056 920 5,092 GA 447 2,152 6,738 1,647 10,984 All Departures 917 2,810 9,829 2,574 16,130 Total 1,796 3,444 12,808 13,615 31,663 Table 6.4. Movements by runway and operation type. Operation type 2 20 6 24 Total Arrivals Cargo 52% 5% 25% 17% 100% Commercial 2% 2% 38% 59% 100% GA 6% 5% 10% 79% 100% All arrivals 6% 4% 19% 71% 100% Departures Cargo 15% 7% 65% 13% 100% Commercial 9% 13% 60% 18% 100% GA 4% 20% 61% 15% 100% All departures 6% 17% 61% 16% 100% Total 6% 11% 40% 43% 100% Table 6.5. Percentage of runway usage by operation type. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Case Study Airport 43 visibility, wind direction, and wind speed attributes. In these cases, average values were substi- tuted, based on the nearest adjacent times for which data were available. Missing values in the ceiling attribute field were assumed to indicate an unlimited ceiling, so the highest recorded value of 12,000 feet was substituted in these instances. Figure 6.2 is an example of the approach used for filling voids in the weather data file. Substituted values are indicated by yellow shading. 6.4 Existing Land Uses within RPZs The RPZs at the case study airport are host to various land uses with varying degrees of popu- lation density. The RPZs for each runway end are occupied by land uses and structures generally considered unsuitable in an RPZ. Existing land uses are visible in an aerial image in the software map space. Each existing land use must be digitized into distinct polygons, and attributes must be entered for each polygon. For traditional land uses relating to spaces where specific activities occur (e.g., industrial, recreational, and institutional), a use name and estimated average popu- lation present must be entered to generate a calculated population density expressed in persons per square foot. For transportation corridors (e.g., roadways and railways) where estimating the number of people present may be difficult, built-in routines may be used to arrive at the popula- tion density estimates. The land use population density assumptions used for the case study analysis were based on occupancy factors used for determining the usage intensity of nonresidential land uses in the San Diego International Airport Land Use Compatibility Plan (SDIA ALUCP) where occupancy factors are expressed in square feet per person (San Diego County Regional Airport Authority, 2014, Table 3-1). In the SDIA ALUCP, occupancy factors vary by nonresidential land use type. The factors are used to estimate the number of occupants in proposed structures to determine if the proposal complies with the maximum allowable intensity in any given safety zone. Many airport land use compatibility plans in California use occupancy factors for the same purpose, in accordance with guidance from the State Division of Aeronautics (California Department of Transportation, 2011, Section 4.4). Population densities were calculated by reciprocating the occupancy factors for correspond- ing land uses in the case study airport RPZs. Population densities for outdoor uses (e.g., parking areas, storage yards, and open space) were developed separately to reflect the lower densities typically associated with them. The population density used for indoor storage structures or warehouses was used as a starting point and adjusted downward to achieve plausible low-density assumptions appropriate to outdoor areas used for storage and parking. Population density assumptions for the land uses in the RPZs are summarized in Table 6.6. RPZ_RAT expects population densities in persons per square feet. The table also presents the population density in terms of persons per acre. Figure 6.2. Missing weather data value substitution. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

44 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide For railways, average annual daily passage, length of segment within the RPZ, average speed, average length of trains, and average ridership per train can be entered to generate estimates of daily presence of trains in the RPZ and average population of the corridor segment. An attempt to contact the railroad company to determine passage counts and ridership for the segment of the railway intersecting the site yielded no response, so for the case study, a passage count of 10 was assumed for each railway segment. Train average length was assumed to be 6,500 feet. Aver- age ridership per train was assumed to be two riders, as the railway running through the airport environs serves cargo trains rather than passenger trains. For roadways, AADT, length in RPZ, speed limit, and average vehicle occupancy must be entered to generate a population density and total population for the segment. Roadways’ AADT were obtained from the local Metropolitan Planning Organization (MPO). Speed lim- its were determined by examining Google Street View imagery and searching for speed limit signs along each roadway. Average vehicle occupancy was assumed to be two occupants per vehicle. Each of the RPZs and associated land uses are described in detail in the sections that follow. Runway 6 RPZ Existing land uses in the Runway 6 RPZ are mainly on airport and in the western corner for the approach RPZ. Existing land uses include parts of an aircraft hangar and apron, two public services buildings with two associated parking areas and a courtyard entry plaza, and a small part of Highway Zulu. Figure 6.3 shows the Runway 6 RPZ with existing land uses. Land uses in this RPZ are located around the farthest corner of the RPZ where the likelihood of an accident is usually very low. A public services building with a population density of 0.0047 persons per square feet (which is the highest among the land use categories at the airport) inhabits a small part of the RPZ. The land use comprises two buildings as shown in the figure. The parking lots and the courtyard are separated to account for their varying population densities. Part of the hanger building encroaches on the RPZ. Hanger building and apron are also sepa- rated out because of different population densities. The apron occupies the largest area in this RPZ and is the closest to the runway. Land use category Site-specific land uses Population density assumption, persons per square feet (persons per acre) Industrial (Indoor) Factory buildings 1-5 (factory/processing) 0.0033 p/sf (144 p/a) Industrial (Indoor) Factory storage facility, hangar building 0.001 p/sf (44 p/a) Industrial (Outdoor) Motor pool, storage container yard, salvage yard 0.00025 p/sf (11 p/a) Institutional Public service buildings 0.0047 p/sf (205 p/a) Parking All parking areas 0.000125 p/sf (5 p/a) Recreation (indoor) Equestrian training facilities and wash rack 0.002 p/sf (87 p/a) Recreation (outdoor) Outdoor equestrian area 0.000125 p/sf (5 p/a) Recreation (outdoor) Courtyard 0.00025 p/sf (11 p/a) Table 6.6. Land use population density assumptions. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Case Study Airport 45 Highway Zulu northbound and a very small part of the southbound pass through the RPZ with an AADT of 4,000. Overall, nine separate land uses were identified in this RPZ and were entered into the RPZ_RAT. Runway 24 RPZ As shown in Figure 6.4, the Runway 24 RPZ intersects a recreation use area associated with an equestrian riding facility in the eastern corner of the RPZ. Four separate land uses were identi- fied in the facility. After researching the equestrian facility’s website, the property was found to include two indoor training areas/stables and a wash rack building within the RPZ. The RPZ also included open space at the equestrian facility land where riding could also occur. The population densities assigned to each land use are consistent with numbers shown in Table 6.6. Alpha Road is lightly traveled with 1,450 AADT. The segment within the RPZ is 0.21 miles long and the speed limit is 40 mph. The software calculated a population density of 2 × 10–5 persons per square foot for the road. The railway segment in the RPZ is 0.31 miles long with an assumed average speed of 55 mph. Only cargo trains pass through the railway with assumed ridership of two crews with ten daily passages. The software calculated a population density of 3 × 10–7 persons per square foot for the railway. Although the railway is the closest land use to the runway and encompasses the largest area within the RPZ, its population density is the lowest of the land uses. Runway 20 RPZ As shown in Figure 6.5, a roadway and a small part of a salvage yard are located in the Run- way 20 RPZ. Highway Yankee intersects near the RPZ midpoint, and the intersecting segment Figure 6.3. Land uses within Runway 6 RPZ. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

46 Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide Figure 6.4. Land uses within Runway 24 RPZ. Figure 6.5. Land uses within Runway 20 RPZ. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

Case Study Airport 47 is 0.25 miles long with a 45 mph speed limit. With an AADT of 6,113, RPZ_RAT calculates a population density of 5 × 10–05 persons per square foot for the roadway. The salvage yard is in the northwest corner of the RPZ with only a small part within the RPZ. As shown in Table 6.6, a population density of 2.5 × 10–04 persons per square feet is assigned to the yard. Runway 2 RPZ Runway 2 has a threshold displacement of 789 feet. The threshold displacement results in off- set approach and departure RPZs, with the approach RPZ tied to the displaced threshold and the departure RPZ tied to the runway end and extending farther to the south. As a result, Runway 2 RPZ encompasses more land area than the other RPZs at the case study airport. As depicted in Figure 6.6, Runway 2 RPZ encompasses several land uses. The RPZ intersects an industrial area accommodating a large factory. Land uses in the industrial area include factory buildings and an associated outdoor motor pool area providing vehicle access to shipping bays. Two parking areas associated with the industrial site are also intersected by the RPZ. To differentiate between the population densities, factory buildings, storage areas, motor pool, storage container lot, and parking areas are identified and entered as separate land uses. The factory buildings and motor pool area encompass the largest area among all land uses at the airport. They are also at or near the extended runway centerline, which usually has a higher likelihood of an accident. These factors, combined with the relatively high population densities shown in Table 6.6, raise the potential for high-risk values. Figure 6.6. Land uses within Runway 2 RPZ. þÿRunway Protection Zones (RPZs) Risk Assessment Tool Users  Guide Copyright National Academy of Sciences. All rights reserved.

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Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide Get This Book
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TRB's Airport Cooperative Research Program (ACRP) Research Report 168: Runway Protection Zones (RPZs) Risk Assessment Tool Users’ Guide helps airport operators evaluate the risk of an aircraft accident within an RPZ. Although runway protection zones (RPZs) are supposed to be clear of structures and people, it is still common for activities to occur within an RPZ for many reasons, and these reasons can be beyond the control of the airport operator.

The report is accompanied by a tool used to assess the risk of an aircraft accident within the RPZ, and, based on that output, assess the risk to people and property, considering the population density and land use. The tool can be used to run scenarios for planning around an RPZ or if changes are being considered, for example a change in the threshold, extending a runway, removing a hazard, and planning for a new runway. Ideally, the Users’Guide should be read before starting to use the tool.

Chapter 4 has instructions for installing the tool, including how to download SQL, which is required to run the RPZ_RAT tool. For background on the development of the tool, see the Contractor’s Final Report.

Disclaimer: This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences, Engineering, and Medicine or the Transportation Research Board (collectively "TRB") be liable for any loss or damage caused by the installation or operation of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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