Environmental Optimization of Aircraft Departures: Fuel Burn, Emissions, and Noise (2013)

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37 4.1. Introduction In support of helping airport operators to better under- stand the tradeoffs among aircraft noise, fuel burn, and emis- sions from departure track optimizations, an electronic tool was developed to help facilitate scenario assessments. The focus of the tool is to allow the assessment of departure tra- jectory optimizations through the use of methods that allow • Calculation of noise exposure; • Quantification of fuel burn and emissions; • Modeling of changes in air traffic capacity resulting from the implementation of optimized departure procedures; and • Accounting for future fleet mixes and technologies, includ- ing those envisioned as part of NextGen. The primary difficulty in developing a method applica- ble to all airports is that most airports are unique in terms of the aircraft fleet they serve, in the nature and location of the communities that surround them, and, consequently, in the flight trajectories and procedures they use. For the previously discussed case study analyses, several specific airports were selected to serve as examples of the types of departure noise abatement procedures that are commonly implemented. Although some of the airports presented combinations of several of the procedures of interest, no single airport could be used as an example that covered all noise abatement procedures (NAPs). Given the range of variability of possible individual situations, the approach selected for developing the method was to create an inter- active tool that exemplifies a generalized framework for assessing environmental optimization of departure flight operations. Section 4.2 provides details on the hypothetical airport layout used in the tool while Appendix E discusses scenario modeling and provides some detailed example uses of the tool. The tool is in the form of a Microsoft Excel-based inter- active application that computes noise, fuel burn, and emis- sions results on the basis of various user inputs within the context of a set of fixed parameters. For simplicity and ease of use, the tool’s overall modeling scenario is based on a set of fixed tracks that allow the user to model various scenar- ios depending on how the operations of a user-defined fleet mix is allocated to the tracks. This allows airport operators to study what-if scenarios that most closely resemble their airport flight tracks in an attempt to better understand the effects (e.g., sensitivities) of choosing different combinations of flight tracks, operations, and fleet mixes. 4.2. Tool Description and Design 4.2.1. Software and Hardware Requirements The Departure Optimization Investigation Tool (DOIT) is a spreadsheet-based analysis tool that integrates (1) a multiple-tab input interface; (2) integrated function-based computation engines; and (3) a database of aircraft noise, fuel burn, and emissions characteristics. DOIT was developed as a self-contained Microsoft (MS) Excel macro-enabled workbook compatible with MS Excel 2007 and higher; com- patibility with previous versions was not possible because of limitations in worksheet size and capabilities. The macro execution functionality is required for loading results from different scenario workbooks; not enabling macro execution effectively disables the tool’s results function. The workbook size is relatively large (about 24 MB) and varies slightly based on the amount of input provided; the large size is primarily due to the presence of the underlying noise and emissions data. The single-file, self-contained design was chosen to keep the tool simple—there is no need for external data (outside of the spreadsheet) or location dependencies for installing the tool or storing data. Loading time varies depending on the computer’s drive and processor capabilities, but results computations are seemingly instantaneous on most cur- rent hardware. C H A P T E R 4 Optimization Tool

38 4.2.2. Tool Structure 4.2.2.1. Interface The tool interface consists of multiple sheets that provide information, input, and output results. In addition, the work- book contains several data and computation sheets that have been hidden from the user to protect the data and formulas they contain. All sheets have been organized to provide a logical and easy-to-use organization of the information they present for input or review, and access to the internal data and formatting has been locked for protection from accidental data changes. Consistent color coding is used throughout the interface to facilitate visual navigation of the data tables. Column and row navigation and referencing for tables that extend over wide areas is supported by the use of fixed panes that allow scrolling data fields while maintaining the visibility of the related head- ers. Data integrity for user-provided inputs is also supported by some data verification functionality that gives visual feed- back when the values entered do not conform to the appropri- ate input validation parameters. 4.2.2.2. Computation Infrastructure The computations required to generate noise exposure, fuel burn, and emissions results are performed within dedicated calculation sheets (tabs) with the results referenced to the out- put sheet of the application interface. The results computations are seemingly performed instantaneously—which provides immediate feedback to the user—and the necessary speed is achieved through the use of direct cell referencing between the computation sheets and input data cells. Although this approach avoids computationally costly lookup procedures, it is completely dependent on a fixed cell framework; the locks implemented in the interface and the hiding of the data and calculation components have all been introduced to protect the integrity of this framework. 4.2.2.3. Noise Computation Method Calculation of aircraft noise is based on the single-event addition method, a noise computation approach that uses pre-computed single-event Sound Exposure Level (SEL) data generated using the FAA Integrated Noise Model (INM) Version 7.0b (FAA 2009) to calculate noise exposures. This method allows very quick computations without requiring any actual noise modeling to be performed, which is time consum- ing and requires complex sets of data and software components. The time and complexity savings are achieved by performing the noise computations for all desired combinations of aircraft and flight track off line and by storing the results, which can be recombined to compute the final noise levels resulting from any combination of aircraft operations. The noise calculations are conducted by quantifying the noise exposure at the points of interest by multiplying each aircraft and track combination’s single-event acoustic energy by the number of operations and then by summing all the con- tributions and converting the total acoustic energy into a SEL value. The computation engine can also account for overall changes in source level by adjusting the number of operations by which the single-event levels are multiplied. The adjust- ment factor is computed using the following formula, which relates number of operations (Ops) to decibel (dB) changes: Ops OpsAdj dB = × 10 10 ∆ In this formula, the decibels of noise change provided by the user for an aircraft are converted into a multiplier used to scale the original operations and mimic the desired change in source noise level. Within the tool, the user can review the worksheet providing the noise data summary to identify the effects of these adjustments on the final number of opera- tions used for the calculations. 4.2.2.4. Emissions Computation Method The aircraft fuel burn and emissions computations within the tool are performed with an approach similar to that used for noise. The fuel burn and emissions outputs for every air- craft on every flight track were pre-computed and the output data stored in the application. The emissions data were gener- ated using a method developed by Wyle that takes as input the INM 7.0b aircraft performance data (i.e., flight profile data) and the length of the section of track to analyze and compute the resulting fuel burn and emissions (NOx, CO, HC, CO2, H2O, and SOx). Given that this type of analysis requires segment-level emissions data with an interpolation scheme for “cutting” seg- ments based on the length of the assessed tracks, neither the FAA’s Emissions and Dispersion Modeling System (EDMS v5.1.3) (FAA 2007) nor the Aviation Environmental Design Tool (AEDT) (FAA 2012) could be used. Future versions of AEDT may allow for the flexibility of using its results within the tool. Although EDMS and AEDT were not used, the fuel burn and emissions calculation methods employed in the tool are identical with those used in the FAA tools, including the use of the Boeing Fuel Flow Method 2 (BFFM2) (DuBois 2006) and Eurocontrol’s Base of Aircraft Data (BADA) (EEC 2011). The fuel burn and emissions assessments rely on opera- tions adjustments to model the changes in fuel burn and emissions provided by the user. Given that the fuel burn and emissions reduction parameters are expressed in term of percentages, the adjusted operations are computed by simply scaling the original operations by the appropriate percentages. As with noise, the model provides the user a view of the effects of these adjustments for each of the

39 parameters within the worksheet that contains the fuel burn and emissions data summary. The fuel burn and emissions computations are conducted up to a total horizontal ground distance of 12 NM radius from the start of runway roll. Therefore, all fuel burn and emis- sions reduction (or increase) results are based on comparing up to the 12 NM limit. The purpose in choosing the 12 NM radius was to select a point that was far enough to capture the full breadth of the differences between each track. That is, all of the different characteristics of the compared tracks occur within the 12 NM radius, and beyond the 12 NM radius, the trajectory points are similar (the flight tracks would be the same for aircraft traveling to the same destination). As a result, the 12 NM radius serves as the basis for any resulting reductions (or increases). Using a different but greater radius (e.g., 13, 14, or 15 NM) will likely provide similar mag- nitudes of reductions. However, the percent differences can be significantly different depending on what radius is used. As a result, any percent reductions (or increases) resulting from the 12 NM analysis should be understood to represent just the near-terminal differences. For a full flight analysis, the user must determine the fuel burn and emissions so as to develop percent reductions. 4.2.2.5. Airport Layout Scenario Used in the Tool The airport layout used in the tool does not represent any real airport and was developed to enable the user to explore the various noise abatement procedures covered in the case study analyses chapter of this report. As presented in Figure 4-1, the runway system in this airport scenario is made of two parallel runways capable of supporting concurrent take-off and land- ing operations of any of the aircraft in the fleet. A two-runway system was selected to support modeling of more complex temporal track use and preferential runway scenarios. A cross runway was not added to this layout for simplicity. Among the most location-dependent variables of an airport system are the locations of the noise-sensitive areas around the airport, which are the reason noise abatement procedures are developed. As such, the airport layout includes two notional population centers near the airport to the North-East and North-West. These population centers were located so that the flight tracks for the airport could be logically designed to cover various noise abatement procedures. The flight track layouts were also tailored to modeling of the NADP types addressed in the case study analyses. As shown in Figure 4-1, Runway 09 has been assigned the set of tracks Figure 4-1. Sample airport flight tracks.

40 necessary to model multi-turn noise abatement procedures, which include the NAP and direct tracks, plus two additional tracks for modeling of operations heading East and South of the airport. Runway 27 includes tracks that support both head- ing and fanning NAPs; these tracks include the heading NAP and direct tracks plus the tracks with West and South head- ings. These last two tracks, in conjunction with the direct track, allow modeling of fanning operations. Finally, the three tracks on Runway 28 have been designed to support operations head- ing north, west, and south and accommodate operations mod- eled to simulate preferential or temporal operational scenarios. All tracks can be easily identified by their IDs (composed of a letter code for the heading [e.g. “N” for north] followed by the runway ID). The heading NAP flight tracks have an additional 3-letter code to distinguish the original NAP track (extension “NAP”) and the direct track (extension “Dir”). For the study of multi-turn and heading NAPs, the airport tracks layout also includes a set of intermediate tracks located between the NAP and direct tracks. These intermediate flight tracks, shown in Figure 4-2, are spaced at an interval of 0.5 NMs at the apex of the primary turn and are shaped to provide flight paths that move gradually closer to the direct flight track. The intermediate tracks can be easily identified by their IDs, which include the track heading followed by runway ID and the number indicating the order of the track starting from the NAP track, with 02 being the intermediate track closer to the NAP flight path. These tracks give the ability to assess the benefits qui- eter fleets can afford by being able to fly more direct routes without adversely affecting noise exposure. As aircraft are moved from the outer, longer flight tracks to the inner ones, the operations total fuel burn and emissions are reduced due to the shorter path, which, however, also decreases the distance to the noise-sensitive areas resulting in potentially higher exposure levels. By iteratively changing the aircraft flight paths and/or their noise output, the model can be used to find the optimal compromise where the most emis- sions and fuel savings can be achieved without significantly affecting noise exposure. Noise resulting from aircraft operations is computed in the model at a fixed set of location points placed directly under the flight path of each track as well as the location where noise Figure 4-2. Sample airport intermediate flight tracks.

41 level is most affected by the sum of the influences from all tracks. Figure 4-3 shows the location of the points for which noise exposure is calculated. In the figure, the blue and green points indicate the under-track locations, which are placed at 1-NM radius from the center of the airport study. The first point is located at a distance of 2 NM while the last point is at 12 NM. The point-naming convention allows easy identi- fication of both the location and distance by consisting of the flight track ID followed by a number, from 02 to 12, indicating the distance from the airport center. Various reference points were also created to allow gaug- ing of the changes in noise from one scenario to another. The reference points where the noise exposure is most affected by the combined changes in the airport flight path utilization are shown in maroon (dark, brownish red). Although all could be affected by changes in any of the flight tracks, the most significant contributors are those located closer to them. The City1 point is most affected by changes to the operations off of runway 27, while the point City2 is affected predominantly by changes in use of the runway 09 flight tracks. The noise level at the points named POI_S27 and POI_S28 is instead most influenced by flight tracks heading due west and south- west from both runways 27 and 28. By observing the changes in noise exposure at these four points the user can assess the overall effect of a scenario’s assumptions. Up to this point, the previous figures have only shown back- bone flight tracks in the study, but the model also includes two sets of flight tracks with built-in dispersion. The backbone- only flight tracks allow modeling of the ideal condition where every aircraft can follow the exact same path without any devi- ation. This mode of operation is useful when the intent is to explore the effects of different scenarios without the smearing effect introduced by dispersion. In contrast, the two sets of dis- persed tracks provide a realistic framework given that they are both based on dispersion patterns derived from radar data for an actual airport before and after the implementation of RNAV procedures. The first set, shown in Figure 4-4, reproduces the dispersion about the nominal track before the implementation of the new procedures while Figure 4-5 shows the dispersion observed after the RNAV implementation. These figures only show the primary flight tracks for clarity; however, the two sets of dispersion are applied to the intermediate flight tracks Figure 4-3. Location of the points where noise exposure is computed.

42 as well. Comparing the two figures highlights the difference RNAV procedures can make to the dispersion pattern of air- craft following a particular flight path. The inclusion of these two sets of tracks allows the user to account for the effects of RNAV procedures as well as compare their contribution to a scenario where such procedures are not in place. Although the two sets of flight tracks with dispersion are different in their layout about the backbone track, the use of each sub-track is the same. Both the standard and RNAV flight tracks with dispersion use the standard operations dis- tribution percentages, shown in Table 4-1. The table shows that flight Sub-tracks 1 and 2, for example, each receive 19.1% of all operations assigned to that ground track. 4.3. Tool Interface 4.3.1. Introduction The tool’s interface is organized based on Excel’s multiple sheets, or tabs, structure which it uses to provide dedicated input data output results, and information sections. Both the organization of the tabs within the workbook, which are numerically ordered, and the layout of each individual sheet are designed to provide an intuitive framework that facilitates the user’s navigation of the different sections. A help function is also available by clicking on the “Help” button at the top left of every sheet. 4.3.1.1. Input Sections The input-related tabs, colored green, cover all informa- tion necessary to define a scenario’s fleet and operations, the aircraft technology, and the airport operational characteris- tics. The order of the input sheet within the workbook (and the numbering) has been designed to provide a logical flow to entering the information required by the tool. The input section includes the following tabs: • “2. Technology” – allows users to enter noise, fuel burn, and emissions modifiers that alter the aircraft environmental performance characteristics. • “3. Operations” – provides the framework for specifying the scenario’s operations. Figure 4-4. Flight track dispersion for standard departure procedures.

43 • “4. Utilization by AC Category” – allows defining the run- way and flight track utilization on the basis of aircraft category. • “5. Utilization by Aircraft” – allows entering runways and flight track utilizations for each individual aircraft (optional input). • “6. Dispersion by AC Category” – provides the framework to control flight track dispersion by aircraft category. • “7. Dispersion by Aircraft” – allows defining the flight track dispersion for each individual aircraft (optional input). In all of the input section tables the tool provides the abil- ity to specify all information for two independent sets of fleets (referred to as Technology Groups): a ‘Current’ fleet and a ‘Future’ fleet. The purpose of having two sets of aircraft defined in the model is to enable the user to define two dif- ferent versions of each aircraft to handle situations where different environmental performance and facilities utilization need to be modeled concurrently. Although these fleets are discussed distinctly, they together represent one scenario, i.e., the aircraft defined as part of the Current fleet and the Future fleet are all used together for each modeled scenario. Generally, the Current fleet should be used to fine-tune the fleet currently operating at an airport by modifying each aircraft’s environmental performance to either more closely match the actual aircraft or act as a more accurate substi- tute for an aircraft that does not appear in the mix. Although the preference is to adjust the noise, fuel burn, or emissions Figure 4-5. Flight track dispersion for RNAV procedures. Sub-track ID1 Backbone 1/2 3/4 5/6 7/8 Percentage 22.2 19.1 12.1 5.7 2.0 1 Odd ID numbers indicate sub-tracks left of the backbone and lower numbers represent sub-tracks closer to the backbone. Table 4-1. Sub-tracks utilization percentages.

44 characteristics of an existing aircraft within the tool’s fleet in order to derive a substitute aircraft, a simpler substitution can be performed by assuming an existing aircraft is representa- tive of another aircraft (i.e., a surrogate). In such a case, no adjustments to the noise, fuel burn, or emissions characteris- tics would be conducted and the user would need to take that into account as part of the uncertainties (errors) in the over- all modeling work. For this simpler substitution method, the FAA’s substitution list from INM can be used (FAA 2011). The Future fleet is intended to enable the user to define the aircraft expected to begin operating at the airport and whose capabilities may enable the creation of more efficient departure procedures. However, because this differentiation between the two fleets is simply conceptual and has no bearing on the actual computations, the user can elect to use the two sets of aircraft in any manner that best fits the requirement of the scenario. A user modeling a scenario where only the number of operations is changing could decide, for exam- ple, to use the second set of aircraft (Future fleet) to extend the modeled fleet detail. This can be accomplished by substi- tuting the listed aircraft in the Future fleet with other existing aircraft types. Essentially, the user would ignore the “Future” term and treat the fleet as another set of aircraft within the Current fleet. This includes assigning current operations and making runway assignments to the “Future”-labeled fleet as if they were an extension of the Current fleet. 4.3.1.2. Output Sections The output tabs, in red, provide the user with the noise, fuel burn, and emissions levels computed based on the inputs as well as the comparison to those produced by a different scenario stored in a separate workbook. The results for the current scenario and related comparisons are computed in real time as the user enters or modifies the data in the input sheets. The output section consists of the following tabs: • “10. Ref Scenario Results” – allows users to select and import the results from a different (baseline) scenario for comparison purposes. • “11. Results” – provides the scenario output and the values that differ from the results of the selected baseline. • “12. Emission Results Summary” – provides users with the aggregated amounts of fuel burn and emissions for each runway. 4.3.1.3. Information Sections The information tabs provide the user with information regarding the application, the scenario, and the provided input. These tabs are in yellow with the exception of the one that holds the scenario’s description which is in purple. The information section includes the following tabs: • “Introduction” – contains the tool’s header information and a brief tutorial on its use. • “1. Scenario Info” – allows users to enter descriptive infor- mation for the scenario. • “8. Noise Data Summary” – provides an integrated view of the input data used for noise calculations. • “9. FB & Emissions Data Summary” – provides an inte- grated view of the input data used for fuel burn and emis- sions calculations. • “Airport Layout” – contains a schematic representation of the sample airport runways and flight tracks layout as well as the location of the points of interest for which noise exposure is computed. • “System Data” – contains the characteristic information for the aircraft included in the tool’s fleet and the links to where certification data for other aircraft can be found. 4.3.2. Interface Tab Descriptions This section covers each of the tabs found within the tool interface and describes the information they contain and required user input; additional background information is also provided to support the user’s understanding of under- lying concepts and assumptions. 4.3.2.1. Tool’s Information and Brief Tutorial Tab (“Introduction”) This tab provides the user with the Tool’s header informa- tion as well as a “Quick Start” brief tutorial on its use. The tutorial only provides the list of steps the user needs to take to create a new scenario. Each step is qualified by a description of its purpose, but does not cover each topic to the level of detail found in this documentation. 4.3.2.2. Scenario Information (“1. Scenario Info”) The Scenario Information tab is designed to provide a space where the creator of the scenario can document its purpose and underlying assumptions. Although the tab is not part of the model’s input structure and its only role is to provide information, it has been placed as the first step in the creation of a scenario to help document its use. Given the amount of information, a scenario without a proper description could be difficult to interpret and understand. Additionally, the information contained in the first three fields of this section is used to reference a scenario output when imported into a different spreadsheet. This feature enables the user to identify the source of the comparison data quickly, but only if such information has been entered when comparison scenario was properly documented. Table 4-2 describes the fields in this tab. The Date field should be updated every time a change is made to the scenario data. Keeping this field current can help

45 in resolving version issues that might arise when multiple versions of the same scenario have been created in different locations without appropriate file naming management. The entry for the Name field should give a user familiar with the analyses underway at the airport a clear understanding of the context of the scenario at hand, which can help an analyst quickly differentiate among files. A more detailed explanation can be entered in the Description field, which should provide a concise understanding of the genesis of the study and of its purpose. Finally, all modeling details, assumptions, and any other information necessary to fully understand the scenario should be included in the Notes field. The Notes field can accommodate up to 32,767 characters and hard returns can be entered by pressing ALT+RETURN. If the number of lines exceeds the size of the visible area of the field, the entire content can be viewed in the formula bar by expanding its size and using the scroll bar (the formula bar can be extended by hovering over the line separating the bar from the worksheet until the pointer turns into an up-down double arrow, pressing the mouse left button, and dragging the separator downwards). Alternatively, the content of the Notes field can be copied to a text document by selecting the Notes field, executing the copy command, and pasting to the destination document. A user can also choose to write the modeling notes in a separate document for ease of editing and referencing, and then add those notes to the study by selecting and copying the text and then selecting the Notes field and executing the paste command. 4.3.2.3. Aircraft Technology (“2. Technology”) The Aircraft Technology tab is used to modify the environ- mental characteristics (i.e., noise, fuel burn, and emissions) of the aircraft in the fleet from their default specifications as defined within the modeling software and information used to generate the data (i.e., INM 7.0b and BADA 3.9). The input table is divided into two main sections based on technology group—Current and Future—to allow the user to define two independent sets of aircraft. The Current group can be used to fine-tune the fleet currently operating at an airport. Each aircraft’s environmental performance can be modified to either more closely match the actual aircraft or to act as a more accurate substitute for an aircraft that does not appear in the mix. The Future fleet allows defining aircraft expected to be operating at the airport or aircraft expected to enter service in the near, or distant, future or to provide additional aircraft modeling options for a single fleet. Hence, the term, “substitute” is used to denote an aircraft not currently in the tool’s fleet that can be used to more accurately represent the baseline fleet at an airport or an aircraft (i.e., new technology) as part of a Future fleet. These substitute aircraft are imple- mented by changing an existing (original) aircraft’s noise, fuel burn, or emissions characteristics. However, as previ- ously indicated, a simpler substitution can be conducted by assuming an existing aircraft can serve as a surrogate for an aircraft not within the tool’s fleet without any changes to the existing aircraft’s noise, fuel burn, or emissions characteris- tics. A substitution list like that found in the FAA’s INM can be used for this simpler substitution method (FAA 2011). The fields included in the Aircraft Technology tab are listed in Table 4-3. The values in Technology Group and Aircraft Category fields provide a level of grouping that is reflected throughout the tool’s input section. The aircraft assignment to groups reduces the input requirement to the user by allow- ing parameters to be set at the group level. The Noise, Fuel Field Name1 Description Date* Date of completion of the scenario. Name* Name of the scenario. Description* A brief description of the scenario. Notes Any information necessary to describe the scenario’s purpose and underlying assumptions. 1 Fields marked with “*” are imported in the Baseline Results tab when a scenario is loaded as the reference of a different scenario. Table 4-2. Scenario information tab fields description. Field Name Description Tech Group The fleet technology group. Aircraft Category The aircraft category based on size. Aircraft The aircraft ID (correspond to the INM 7.0b IDs). Noise Reduction (dB) The noise reduction in decibels to be applied to the base aircraft. A negative value results in an increase in noise output. Fuel Burn Reduction (%) The fuel burn reduction in percentage to be applied to the base aircraft. A negative value results in an increase of fuel burn. Emissions Reduction (%) The reduction in emissions produced by the base aircraft expressed as a distinct percentage for each of the pollutants (CO2, CO, NOx, THC, SOx, and H2O). A negative value results in an increased output of the specific pollutant. Notes A description of the aircraft defined by the given technology parameters. Table 4-3. Aircraft technology tab fields description.

46 Burn, and Emissions fields allow independent setting of each parameter for every aircraft in both sets of fleets. When no reduction or increase in value is desired, the appropriate fields can be either set to zero or the cells’ contents deleted. The techniques to be used for computing the noise, fuel burn, and emissions adjustment values require that infor- mation is available for both the aircraft in the tool and the aircraft being modeled using the tool. Table 4-4 lists the required values for the fleet available in the application while Table 4-5 lists internet sources where the same infor- mation can be retrieved for most of the aircraft currently operating. The techniques for computing the adjustment values are described in the following subsections. Noise adjustments are framed in terms of decibel reduc- tions from the standard aircraft. A positive value causes the model to compute a lower noise output, while entering nega- tive values produces the opposite effect. The value entered should represent the difference in source noise level between the aircraft in the database and the future aircraft being approximated. The method for adjusting for different engines or creating an aircraft substitution should mirror the procedure defined in the ICAO Doc 9911, 1st Ed (ICAO, Doc 9911, “Recom- mended Method for Computing Noise Contours Around Airports - First Edition,” 2008), and the ECAC Doc 29, 3rd Ed (ECAC, Doc 29, “Report on Standard Method of Com- puting Noise Contours around Civil Airports - Third Edi- tion: Volume 1: Applications Guide,” 2005). In order for the two aircraft to have comparable performance, the substitute should have a similar weight, the same number of engines and installed thrust-to-weight ratio, and, ideally, be produced by the same manufacturer. The differences in noise footprints can then be taken into account by applying an adjustment based on the difference in certification noise levels, which the tool’s computation engine performs in accordance with the ICAO and ECAC documents. The noise reduction value is computed by subtracting the original aircraft combined departure certi- fication value (the arithmetic average of the lateral and flyover levels) from the substitute value for the aircraft: dB dB dB Change Substitute Flyover Substitute = +, ,Lateral Original AveragedB 2     − , The convention adopted for this tool is that a negative (-) dBChange denotes an increase from the original to the substitute aircraft, whereas a positive (+) dBChange denotes a decrease (or reduction) from the original to the substi- tute aircraft. This convention was chosen because, in most cases, modeled future aircraft will tend to have lower noise, fuel burn, and/or emissions. This would allow calculated differences to be described as “reductions” without a nega- tive sign. The average departure certification values for the aircraft available in the tool are provided in Table 4-4 while the values for other aircraft can be found on the internet from the sources listed in Table 4-5. When the aircraft that needs to be modeled is a future aircraft for which only a projected value is available, that value can be used as the noise reduction parameter. If the aircraft to which the value has to be applied already has an adjustment, then the two can be added if the future aircraft value is given as being the expected source noise reduction above the current level. The following two examples illustrate how to determine the decibel difference when only the engine is different and when the aircraft are different. Example 1: Calculation of noise adjustment values for air- frames with different engines. If an aircraft operating at an airport has a matching airframe in the tool’s fleet but different engines, the adjustment factor is computed by using the two aircraft departure certification levels. Aircraft Model Engine Cert Level Avg Dep (dB) Cert Level Fly-over (FO) (dB) Cert Level Sideline (SL) (dB) Original A320-211 CFM56-5-A1 91.7 --- --- Substitute A320-233 V2527E-A5 --- 83.1 91.4 Adjustment Computation: dB dB dB dB dB Change Ch = +  − 83 1 91 4 2 91 7 . . . ange dB= − 4 4. Example 2: Calculation of noise adjustment values for creat- ing an aircraft substitute. If an aircraft operating at an airport does not have a matching aircraft in the tool’s fleet, a replacement aircraft should be picked that has a similar weight, the same num- ber of engines and installed thrust-to-weight ratio, and ideally be from the same manufacturer. Aircraft Model Engine MTOW (lbs) Cert Level Avg Dep (dB) Cert Level Fly-over (FO) (dB) Cert Level Sideline (SL) (dB) Original 737-800 CFM56-7B26 174,200 90.6 --- --- Substitute 737-900 CFM56-7B24 164,000 --- 86.7 92 Adjustment Computation: dB dB dB dB dB Change Chan = +  − 86 7 92 2 90 6 . . ge dB= −1 3. In both of these examples, the negative values for dBChange actually imply an increase in noise given that the convention used in the tool is to specify reductions as positive values and

Table 4-4. Fuel burn and emissions parameters.

48 increases as negative values. For future aircraft/engine tech- nologies, the surrogates are expected to have lower character- istic values resulting in positive dBChange values. Similarly, fuel burn and emissions reductions are all specified in terms of positive percentage changes while increases are defined using negative percentage values. The values used should represent the difference in the fuel consumption or emissions output between the aircraft in the database and the aircraft being modeled. Calculating the fuel burn and emissions percentage reduc- tion values for better approximating an aircraft with a different engine or creating a substitute is done by first subtracting the original aircraft parameter from that of the substitute, and then by dividing the result by the original and converting to a per- centage value. Fuel flow (FF) and emissions indices (EI) gener- ally include four numbers, each representing a different mode of flight: Take-off (TO), Climb-out (CO), Approach (AP), and Idle (ID). %Change FF or EI FF or EISubstitute Original = − FF or EIOriginal     × 100 For simplicity, this percentage change calculation method only requires the fuel flow and emissions indices of NOx, CO, and THC corresponding to the Take-off mode. This provides a first-order approximation of the characteristics of the sub- stitute aircraft. Take-off values were deemed easier to use in part because of their availability for most pollutants over other values. If characteristic values for NOx are available from the ICAO emissions databank or other sources, then these values should be used because they will provide more accurate results. In contrast, CO2, SOx, and H2O emissions are modeled on the basis of the composition of the fuel such that the emissions indices for these pollutants are constant across all modes of operation: CO2 EI = 3,155 g/kg SOx EI = 1,237 g/kg H2O EI = 0.8 g/kg As such, these constant EI values should be applied in the above equation as the original values. The substitute values can be derived from a fuel chemical composition analysis, mainly involving an understanding of the carbon (C) and hydrogen (H) contents of the fuel. The user can modify the adjustment (% change) fac- tors for both the fuel burn and emissions. The adjustments are conducted independently—hence, there is no potential for “double-counting” the adjustments, i.e., the % change applied to fuel burn will not affect emissions (and vice versa) because the adjustments are performed on two independent sets of pre- developed data rather than being applied to a method that calculates fuel burn and emissions from the precursor data (i.e., FFs and EIs). Although these parameters allow the user to generate more precise results for the aircraft technology being mod- eled, these parameters are not necessary to determine the reductions in fuel burn and emissions that can be afforded Source European Aviation Safety Agency (EASA), Certification directorate Reference Type Certificate Data Sheets for Noise (TCDSN): Jet, Heavy Propeller, and Light Propeller aeroplanes Link http://www.easa.eu.int/certification/type-certificates/noise.php Source Direction générale de l’Aviation civile (DGAC) Reference NoisedB - certified noise levels of civil transport aircraft types (a project supported by the International Civil Aviation Organization) Link http://noisedb.stac.aviation-civile.gouv.fr/ Source FAA’s Emissions and Dispersion Modeling System (EDMS) Emissions System Table Reference Federal Aviation Administration (FAA) (2010). Emissions and Dispersion Modeling System (EDMS) User’s Manual, EDMS 5.1.3. FAA-AEE-07-01. Revision 8. Link http://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/edms_model/ Source International Civil Aviation Organization (ICAO) Jet Engine Emissions Databank Reference International Civil Aviation Organization (ICAO), ICAO Emissions Databank. Link http://www.caa.co.uk/default.aspx?catid=702 Noise Certification Data Fuel Burn and Emissions Indices Table 4-5. Additional sources of aircraft noise and emissions parameters.

49 by adopting more efficient departure procedures. If a user is interested only in determining the percentage reduction achieved by new procedures and there are no technology changes, the technology adjustment fields for fuel burn and the different pollutants can be left blank. The values for the Fuel Burn and Emissions parameters for the fleet included in the tool are listed in Table 4-4 while the sources for the other aircraft are listed in Table 4-5. 4.3.2.4. Aircraft Operations (“3. Operations”) The Aircraft Operations tab holds all the operations infor- mation for the scenario being developed. The operations data are organized by aircraft category and have to be provided for both the daytime and nighttime periods (7:00 to 22:00 and 22:00 to 7:00 respectively) with nighttime operations receiving a 10dB penalty. The table also allows setting the split between Current and Future fleets by entering percentage distributions for both time periods. To ensure the correctness of the per- centage input data, the table includes built-in error checking that provides visual feedback by highlighting cells with incor- rect values (e.g., a total Current and Future fleet split greater or smaller than 100%). In addition to totaling fields for each of the aircraft, the table provides summaries by group for all the fields. For the technology mix columns, the totals for each category display the assignment mix for the Day and Night operations and the overall mix for all operations. The grand total row at the bot- tom of the table gives the overall summary across all catego- ries. The fields in the Aircraft Operations tab are described in Table 4-6. In a scenario where all operations are performed by the existing fleet, the operations for each aircraft would be assigned to the Current fleet. However, if the airport existing fleet has been developed by taking advantage of the aircraft in both technology groups, the operations should be split between the pairs of aircraft so that the desired number of operations is assigned to each version. In a scenario where the two technology groups represent the Current and Future fleets, the percent assignment to the Future fleet should reflect the number of operations expected for the new aircraft. The assignments can be developed to match the expected penetra- tion of the new aircraft into the overall fleet or that in the fleet of the airline or airlines operating at the airport. In the latter case, the percentage could also be further refined by assessing each airline’s expected service routes deployment plan for the new equipment, which may result in a higher or lower presence at a specific airport. 4.3.2.5. Airport Runways and Flight Tracks Utilization by Aircraft Category (“4. Utilization by AC Category”) The information in this tab defines how the operations are distributed among the available runways and flight tracks on the basis of aircraft category. The input framework is orga- nized in two tables: one to define how the runways are used and one to assign their operations to specific flight tracks; both tables also include dedicated input sections for the Cur- rent and Future fleets. All values have to be provided in terms of percentage splits with the data validation infrastructure highlighting cells not meeting the necessary data integrity requirements. Total rows are provided for each data subset to aid in the entering or troubleshooting of the data. The Runways Utilization table is used to assign the opera- tions of each aircraft group and fleet. For each Technology group, the user has to provide the day and night percentage split which must total to 100% within each aircraft category and day period combination. Each aircraft within each group will have its operations assigned based on these group-level values. The Flight Tracks Utilization table determines how the operations assigned to each runway are further split among the available flight tracks. The data in this table are organized by technology group, aircraft category, time of day, runway, and related flight tracks. The percentage values have to be speci- fied independently at the runway level with the percentages for each track adding to 100% for each runway. As with the runway Field Name Description Aircraft Category The aircraft category based on size. Aircraft The aircraft ID (correspond to the INM 7.0b IDs). Operations: Day The aircraft’s day (7:00 – 22:00) operations. Operations: Night The aircraft’s night (22:00 – 7:00) operations. Operations: Total The total number of operations. Technology Mix: Day Ops The day operations split in percentage between the Current and Future fleets. Technology Mix: Night Ops The night operations split in percentage between the Current and Future fleets. Technology Mix: Total Ops The total operations split in percentage between the Current and Future fleets. Table 4-6. Aircraft operations tab fields description.

50 table, the defined distribution is applied to all aircraft in the category. Table 4-7 describes the fields found in these two tables. Noise is one of the principal reasons airports encounter strong resistance to efforts to optimize their operations. How- ever, the introduction of new navigation, airframe, and engine technologies in the near and medium term could allow air- ports to optimize the use of their infrastructure without caus- ing significant changes to the adjacent communities’ noise environment. The presence in the table of individual sections for each of the technology groups allows the user to tailor the way aircraft with different environmental performance use the airport’s infrastructure and, therefore, model the gains that such optimizations could afford. In a scenario where quieter equipment is being introduced, experimenting with different runways and flight track assignments will allow the analyst to identify which combination provides the greatest decrease in fuel burn and emissions without significantly affecting the noise level experienced by the communities. For example, in a scenario where the Future fleet category includes new aircraft that outperform the current equivalent equipment in terms of source noise level, the new aircraft can have their departures assigned to flight paths that are more efficient. The aircraft, for instance, could be quiet enough to be moved from heading or multi-turn noise abatement flight tracks to their direct counterparts, which, given their shorter lengths, would allow for decreased flight time, resulting in fuel burn and emissions reductions. 4.3.2.6. Airport Runways and Flight Tracks Utilization by Aircraft (“5. Utilization by Aircraft”) This tab allows the user to fine-tune the airport utilization on a specific aircraft basis for both Current and Future fleets. The input structure is the same as that of the utilization by air- craft group tab with the difference that, in this table, the aircraft group categorization is replaced by the actual aircraft types. Completing the information in this table is not a requirement as the default is for aircraft to follow the distributions defined in the previous table for their respective category. This table is provided for the user to implement ad hoc variations to the generic patterns to accommodate aircraft that in the scenario require different handling. To model an alternative use for a specific aircraft, the user first needs to enable the functionality for the target aircraft and time period; the Runway Utilization table in this tab includes an Enable field for the day and night columns of each aircraft of the two technology groups. To switch the functionality on, select the field that displays the Off caption on the red back- ground. Click the drop-down menu list box that appears when the field is selected, and choose the On or Off option in the drop-down menu. When activated, the field turns from red to green, the related data entry fields become active, and their background turns from gray to white. Once activated, the data requirements are the same as those in the utilization by category tables (in the previous tab). The information in this table can be edited at any time, but the information is actually used only if the related Enable field has been set to On, which is confirmed by the cell background color. The ability to control the runway and flight tracks assign- ment at the aircraft level allows the analyst to properly model situations where one or few of the aircraft in a category are equipped with technology that would allow them to use more efficient flight paths without having a negative effect on the overall exposure levels. For example, a Future fleet for an aircraft group could be modeled where most of the newer aircraft only have a marginal evolutionary improvement in source noise, but a couple have much higher improvements because of the adoption of a new type of engine, as in the case of a geared turbofan engine. In such a scenario the flight paths for most of the fleet could be slightly tweaked to make use of the small improvement, but the two other aircraft in the group could be individually reassigned to take advantage of the most efficient flight tracks, thus realizing the maximum benefit. 4.3.2.7. Flight Tracks Dispersion by Aircraft Category (“6. Dispersion by AC Category”) The information in this tab allows the user to define the mix of dispersion patterns expected on each individual flight track by fleet, aircraft category, and time of day. All values are expressed in percentage by individual flight track and a total Field Name Description Tech Group The fleet technology group. Runway The runway ID. Track1 The flight Track ID. Aircraft Category ID: Day The aircraft category (Heavy, Large, Small, and Propeller) runway or flight track utilization percentages for the Day operations (7:00 – 22:00). Aircraft Category ID: Ngt The aircraft category (Heavy, Large, Small, and Propeller) runway or flight track utilization percentages for the Night operations (22:00 – 7:00). 1 The Track field appears in the Flight Tracks Utilization table only. Table 4-7 Runways and flight tracks utilization tab fields description.

51 field is provided along with data validation functionality to facilitate entering the data. Three dispersion patterns are avail- able: (1) “None,” where all aircraft fly the backbone track as in the case of precision GPS navigation; (2) “Standard,” where the dispersion was derived from actual radar data; and (3) “SID,” where the modeled dispersion represents the expected extent using advanced RNAV procedures. The descriptions of the fields found in the Flight Tracks Dispersion tab are provided in Table 4-8. The ability to select different types of dispersion patterns allows the user to take into account the introduction of more precise navigation technology in the assessment of possible optimization approaches. Given that the introduction of advanced navigation reduces the width of the corridor flown by aircraft along the flight paths, it also affects the noise expo- sure on the ground. Narrower dispersions concentrate the noise exposure closer to the nominal flight path which allows for flight tracks to be moved without affecting a change as compared to a scenario where the dispersion is wider. 4.3.2.8. Flight Tracks Dispersion by Aircraft (“7. Dispersion by Aircraft”) This tab allows the user to fine-tune the flight tracks dis- persion utilization on a specific aircraft basis for both Current and Future fleets. The input structure is the same as that of the dispersion by aircraft group tab with the difference that, in this table, the aircraft group categorization is replaced by the actual aircraft IDs. Completing the information in this table is not a requirement because, by default, aircraft fol- low the dispersion utilization defined in the previous table for their respective category. This table is provided for the user to implement ad hoc variations to the generic patterns to accommodate aircraft-specific scenarios. To model an alternative dispersion utilization for a specific aircraft, the user first needs to enable the functionality for the target aircraft and time period; the table in this tab includes an Enable field for the day and night fields of each aircraft in both fleets. To switch the functionality on, select the field that dis- plays the Off caption on the red background. Click the drop- down menu list box that appears when the field is selected, and choose the On or Off option in the drop-down menu. When activated, the field turns from red to green and the related data entry fields lose the gray background. Once activated, the data requirements are the same as those in the category table (in the previous tab). Grayed-out fields can still be edited, but only fields that have been activated affect the calculations. Setting the dispersion associated with individual aircraft can be used in a manner similar to that of setting the flight track utilization by aircraft. The fine level of control allows designing scenarios that target assessing the benefits afforded by the introduction of more advanced technology on specific aircraft in the fleet served by the facility. In the case of the introduction of new equipment, the two capabilities will need to be used simultaneously to be able to model the advantage introduced by both the airframe/engine technologies and the navigation technologies. 4.3.2.9. Noise Modeling Input Data Summary (“8. Noise Data Summary”) This table allows the user to more easily review the effects of the input parameters provided in terms of the actual air- craft operations assigned to each individual track and disper- sion option. To facilitate the navigation of the data, the table highlights the active information by dimming the font in fields with no data. The interface also provides the capability to dis- play only subsets of data using filtering based on the aircraft category and type, as well as the runway and track IDs. The filtering can be applied based on a value, a set of values, or on the font color, which allows easily selecting only the active records. The table displays three sets of data: (1) the actual operations, which are the operations entered and distributed by the user; (2) the noise-adjusted operations, which represent the equivalent number of operations after applying the adjust- ments needed to model the noise technology changes provided by the user; and (3) the total modeled noise operations, which shows the total operations assigned to each set of dispersion tracks after taking into account the nighttime penalty. Comparing the number of operations listed in the actual operations section to those in the adjusted section can illustrate the overall magnitude of the prescribed noise reductions in Field Name Description Tech Group The fleet technology group. Runway The runway ID. Track The flight Track ID. Dispersion Dispersion type ID. Aircraft Category ID: Day The aircraft category (Heavy, Large, Small, and Propeller) dispersion percentages for the Day operations (7:00 – 22:00). Aircraft Category ID: Ngt The aircraft category (Heavy, Large, Small, and Propeller) dispersion percentages for the Night operations (22:00 – 7:00). Table 4-8. Flight tracks dispersion tab fields description.

52 a more readily understandable format. The two sets of num- bers highlight the magnitude of the change in noise output by showing how many flights of the original aircraft would have to be dropped (or added) to produce the same noise levels as the revised aircraft. Expressing the improvements in terms of number of flights change can be a very effective communication tool when addressing audiences that have limited understanding of decibel units. 4.3.2.10. Fuel Burn and Emissions Input Data Summary (“9. FB & Emissions Data Summary”) This table allows the user to more easily review the effects of the input parameters provided in terms of the actual air- craft operations by fleet. To facilitate the navigation of the data, the table highlights the active information by dimming the font in all that do not contain information. The design also provides the capability to display only subsets of data using filtering based on the fleet, aircraft category, and air- craft type. The table displays two sets of data: (1) the actual operations, which are the operations entered by the user; and (2) the adjusted operations for Fuel Burn and each of the pol- lutants, which represent the equivalent number of operations after applying the adjustments needed to model the technol- ogy changes provided by the user. 4.3.2.11. Reference Scenario Results Setup (“10. Ref Scenario Results”) This tab allows the user to load results from an existing scenario to use as a reference (baseline) for computing the amount of change reported in the Results sheet. The source scenario file is loaded by selecting the Load Scenario button and then selecting the appropriate file in the Open File dialog box. The baseline scenario information can be removed by pressing the Clear button. If the selected file is a valid sce- nario, the related description information is copied into the scenario information table along with the name of the source file and its location. This tab does not require any manual inputs from the user because all input is automatically retrieved from the source (baseline) scenario file selected. The results are copied into the results table as values and no link is preserved between the original file and this tab. As such, if any of the baseline scenario data is changed in the original file, the information in this tab must be updated (or reloaded) if the goal is to keep the two sets consistent. 4.3.2.12. Scenario Results (“11. Results”) This tab contains the table that shows the noise, fuel burn, and emissions results generated based on the provided input. The noise results are computed at several points along the flight tracks as well as the points near the airport where the most change is expected based on the geometry of the air- port flight tracks. The emissions results present the total fuel burn and emissions results by runway. The sheet contains two tables: the current scenario result and the total change between the current scenario and the reference scenario. For analyses where reference scenario data have also been loaded, the table also displays the reduction between the two scenarios for each of the results data sets. Given that the changes are expressed in terms of reductions, positive values represent the current scenario having a decrease from the reference, while negative values represent an increase. Although the table for the current scenario is always pop- ulated, the change results table reports information only when a reference scenario has been loaded in the reference scenario results tab. To facilitate review of the results, the table provides filtering capabilities based on the runway, track, and point ID. 4.3.2.13. Scenario Results (“12. Emissions Results Summary”) This tab provides the user with aggregated fuel burn and emissions for each runway. When a reference (baseline) sce- nario is loaded, the summary sheets also display the results for the baseline and the amount of reduction for each pollut- ant. The comparison by runway facilitates the assessment of the overall effect of the modeled scenario (i.e., in comparison with the baseline scenario). 4.3.2.14. Airport Layout Tab (“Airport Layout”) This tab contains pictures of the sample airport runway and flight track layouts. The images are intended to provide the user with an easily accessible reference during the devel- opment of a scenario. The full description of the airport layout was covered in Section 4.2.2.5; brief descriptions are provided below: • Backbone Flight Tracks: Includes backbone tracks not including the full array of flight tracks located between the single-turn and multi-turn noise abatement flight tracks and their respective direct tracks. • Single and Multi-Turn NAP, Intermediate, and Direct Flight Tracks: Single-turn and multi-turn noise abate- ment flight tracks, their respective direct tracks, and the intermediate tracks are included. • Backbone Flight Tracks and Noise Computation Loca- tion Points: The location of the under-track location points and the location of the points where the maximum noise change is experienced.

53 • Backbone Flight Tracks and Radar-Derived Dispersion Flight Tracks: Backbone tracks and sub-tracks using flight track dispersion parameters derived from radar (NAP intermediate flight tracks not included). • Backbone Flight Tracks and SID-Derived Dispersion Flight Tracks: Backbone tracks and sub-tracks using the SID flight track dispersion parameters (NAP intermediate flight tracks not included). 4.3.2.15. System Data Tab (“System Data”) This tab contains characteristic information on the air- craft types available in the tool and information on publicly available sources of information for most aircraft currently operating. The tool’s fleet information is presented in a table listing the following data: • Aircraft and engines descriptions; • ICAO engine ID; • BADA aircraft ID; • Number of engines; • Aircraft maximum take-off weight; • Static thrust per engine; • Departure average noise certification level; • Fuel flow; and • Emissions indices (NOx, CO, and THC). The second table in the sheet lists sources of noise certifica- tion and emissions data for most of the aircraft fleet currently in operation and the related internet addresses. This system data can aid the user in comparing different aircraft and engine types, thereby helping in the development of adjust- ment factors.