Methodology to Improve AEDT Quantification of Aircraft Taxi/Idle Emissions (2016)

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25 5. Recommended Near-Term Model Improvements and Implementation Steps With completion of Tasks 1 through 7, an Interim Report was prepared under Task 8, and provided to the Research Panel summarizing the outcomes of this work. Following the Panel’s review and discussions with the Research Team, the Panel instructed the Team to proceed with the following final three research tasks:  Task 9: Identification of Near-Term Model Improvements  Task 10: Steps Needed for Implementation  Task 11: Final Report The Panel also suggested enhancements to the methodology the Research Team used to evaluate the relevance of the FDR data from the Test Data Engines. That improved methodology was implemented by the Research Team and the Test Data Engine information incorporated into this Final Report is based this recommendation (see Appendix B). Table 8 provides a concise summary of the model improvements recommended by the 02-45 Research, including an estimate of the level of effort needed to implement the improvements and a recommendation as to the priority (i.e., near-term or long-term). For each recommended improvement, the table also includes a summary of required changes to the model and the likely effect of the improvement on the model’s emissions predictions. For each of the recommended near-term improvements, the following sections of this report discuss in greater detail the steps required for the implementation of those recommendations. It must be noted that the discussions of implementation steps do not include any explicit steps that would be required to provide support to the user to make AEDT preserve its current treatments. It should also be noted that every implementation step would also require efforts to deal with any unanticipated interactions, unit test development, system-level testing, and updates to technical documentation and model user guidance. 5.1 Near-term Model Improvements for Time-in-Mode (TIM) Factor As indicated in Table 8, there are two recommended near-term model improvements related to the TIM factor of the taxi/idle emissions equation in AEDT. The required steps to implement each of the improvements into the model are discussed below: 5.1.1 Default Taxi Time The recommended near-term improvement is to change the default taxi in and taxi out times in AEDT to values computed from ASPM data representing all airports. While these values vary somewhat by airport size and number of runways, they trend toward overall averages of 7 minutes for taxi in and 16 minutes for taxi out. To make the necessary model changes to adapt this improvement, the following steps/sub steps would be required: AEDT Improvement Implementation Steps  Implement air operation Create, Read, Update, Delete (CRUD) support that includes taxi-out duration: − Create a graphical user interface (GUI) dialog to edit air operations. − Add value control and check-box (for null vs. non-null) to GUI dialog and implement coordination with database. − Have dialog set value control to 16 minutes when check-box is activated. − Add property to the AEDT Standard Input Format (ASIF) import-file schema and implement persistence support. − Implement database coordination with GUI and ASIF.

26  Repeat for taxi in, but with seven minutes as default value in GUI dialog.  Repeat for taxi in and taxi out, but for airport layout CRUD support. 5.1.2 Default Taxi Speed The recommended near-term improvement is to change the default taxi speed in AEDT to 11 knots (12.66 mph), based on a weighted average speed derived from FDR data taken from actual aircraft operations. To make the necessary model changes to adapt this improvement, the following steps would be required: AEDT Improvement Implementation Steps  Change default speed value to 11 knots in GUI dialog for editing taxiway points.  Change taxi network construction algorithm’s default speed value to 11 knots. 5.2 Near-Term Model Improvements for Fuel Flow Rate (FFR) Factor The recommended near-term improvement for this factor is to consider the FFR for each engine as that engine’s ICAO FFR value, times a global factor of 0.92, derived from comparing actual FDR data with the ICAO data. To make the necessary AEDT changes to adapt this improvement, the following steps would be required: AEDT Improvement Implementation Steps  Create a method to determine whether or not an airplane is a commercial jet.  Change fuel flow rate calculations to result in 92 percent of the ICAO idle value in cases where the aircraft is a commercial jet: − In the performance calculation algorithm for monolithic taxi segments, and − In the performance calculation algorithm for sequenced taxi segments. 5.3 Near-Term Model Improvements for the Emissions Index (EI) Factor There are two recommended near-term improvements in the way AEDT considers the EI factor, one regarding the model’s prediction of HCs and CO; the other regarding NOx. They are discussed individually below. 5.3.1 Prediction of HCs and CO The recommended near-term improvement is to apply a global adjustment factor assuming all engines’ CO and HC EIs follow the same temperature/FFR dependence as the CFM56-7B family of engines. To make the necessary model changes to adapt this improvement, the following steps would be required: AEDT Improvement Implementation Steps  Create a method to determine whether or not an airplane is a commercial jet.  Gather parameter values required to encode the 92 percent adjustment factor curve from Figure 1 (either as a set of coordinates for interpolation, or the equation of a line).  Create a method that calculates and returns the CO/HC adjustment factor for a given temperature, based on encoded data.  Create methods that calculate CO and HC emissions indices as the product of the engine’s corresponding ICAO idle EI with the adjustment factor for the local ambient temperature.  Update the overall emissions calculation algorithm to detect taxi segments and call the new CO/HC EI calculators for taxi segments when the airplane is a commercial jet.

27 5.3.2 Prediction of NOx The recommended near-term improvement is to use the fuel flow rate fraction to scale the NOx EI for commercial jets. This model improvement would require the following steps: AEDT Improvement Implementation Steps  Create a method to determine whether or not an airplane is a commercial jet.  Create a method that calculates a NOx EI as the product of the BFFM2 NOx EI with the fuel flow rate fraction.  Update overall emissions calculation algorithm to detect taxi segments and call the new NOx method for taxi segments when the airplane is a commercial jet. 5.4 Near-Term Model Improvements for Additional Considerations The recommended near-term improvement is to add to the model the capability for users to indicate whether reduced engine taxiing procedures should be considered in the calculation of emissions from jet aircraft equipped with two (or more) engines. If they are to be considered, emission reduction scaling factors would be applied to FFRs—0.995 for taxi in FFRs and 0.96 for taxi out FFRs. To make the necessary model changes to adapt this improvement, the following steps would be required: AEDT Improvement Implementation Steps  To all classes representing air operations at some level of specificity, add a boolean property indicating whether or not to apply these scaling factors.  For air operations, implement CRUD support that includes the new property: − Create a GUI dialog box to edit air operations. − Add a check-box corresponding to the new property to the GUI dialog and implement coordination with database. − Add a corresponding property to ASIF import-file schema and implement persistence support. − Add a corresponding column to the database and implement coordination with GUI and ASIF.  Propagate the values assigned to the new property air operations to the more specific representations.  Update the performance calculation algorithms to apply the scaling factors to the fuel flow rates calculated for monolithic taxi segments when requested for the event.  Update the performance calculation algorithms to apply the scaling factors to the fuel flow rates calculated for sequenced taxi segments when requested for the event.

28 Table 8 Prioritized List of Potential Improvements to AEDT Taxi/Idle Emissions Computational Factors Research Parameter(s) Improvement Option(s) Required Revision to Model(s) Effect on Predicted Emissions Cost (Ease) of Implementing Improvementa Priority (Near- /Long-Term) Time-in-mode Default taxi time (crucial for EDMS/AEDT users that use the default time-in-mode option) - Currently 7 minutes taxi in and 19 minutes taxi out 1) Change default taxi in and taxi out to values derived for all airports. --7 minutes taxi in / 16 minutes out Update values in dbo. SCENARIO_AIRPORT_LAYOUT (DEF_TAXI_TIME_A (arrivals) and DEF_TAXI_TIME_D (departures)). Reduction of 12 percent. Minimal Cost Near-term 2) Provide user query for type of airport and number of runways in GUI – link to new database. -- Values in Table 3 Modification to GUI, algorithms, and a new database. Reduction of four to 50 percent depending on airport. Moderate Cost Long-term 3) Default to average of five years of data for specific airport being evaluated. -- Values in Table 4 Modification to algorithms and a new database (or addition to existing databases above). No change or increase from eight to 42 percent at six airports. Reduction of four to 50 percent at all other airports. Moderate Cost Long-term Default taxi speed (important for EDMS/AEDT users that evoke the dispersion modeling option ) - Except for queue area before departure, EDMS assumes aircraft taxi at one speed (default 15 knots (17.26 mph)). Users may also enter aircraft specific speeds) 1) Change default assumption to weighted average value based on FDR data. -- 11 knots (12.66 mph) Requires a change to a value in the model code. Reduction of 27 percent. Minimal Cost Near-term 2) Allow users to indicate (or the model to distinguish) whether a taxiway is used for aircraft taxiing in or out. -- 13 knots (14.96 mph) for taxi in taxiways and 10 knots (11.51 mph) for taxi out taxiways Algorithm modifications to derive total emissions using adjustment factors. Reduction that would depend on an airports number and length of taxiways and taxi mode being modeled (i.e., taxi in or taxi out). In/out distinction already present in AEDT. Re- assignment of values is only task necessary. Minimal cost Long-term Fuel Flow Rate (FFR) FFR - Actual FFRs can be higher or lower than those listed in engine-specific ICAO datasheets for operation at idle/taxi. Rates are positively correlated with thrust setting and bleed flow. Furthermore, a range of FFRs is used during idle, not just a fixed single value. 1) Adjust FFRs in databases only for those aircraft for which there are FDR data (varies between 80 and 111 percent of ICAO idle value for taxi in and between 90 and 113 percent for taxi out). -- Values in Table 6 Algorithm modification to derive total emissions using adjustment factors. Without considering the more important effect of FFR on the EIs themselves, decreasing FFR decreases emissions of all compounds (including CO2). See below for combined effect on emissions when considering the impact of reduced FFR on EIs. Moderate cost *

29 Taxi/Idle Emissions Computational Factors Research Parameter(s) Improvement Option(s) Required Revision to Model(s) Effect on Predicted Emissions Cost (Ease) of Implementing Improvementa Priority (Near- /Long-Term) 2) Adjust the FFRs for those aircraft for which there are FDR data or for which the data are representative. -- Values in Table 6 and list of engines in Table B-4 Algorithm modification to derive total emissions using adjustment factors. Same comment as Improvement Option 1 Moderate Cost * 3) Use a single, global adjustment to all commercial jet engines. -- 92 percent of an engine’s ICAO idle value Algorithm modification to derive total emissions using adjustment factors. Same comment as Improvement Option 1 Minimal Cost Near-term Emission Indices CO and HC - Note: EIs should be adjusted only if FFRs are adjusted 1) Apply a global adjustment factor assuming all engines CO and HC EIs follow same temperature/FFR dependence as the CFM56-7B family of engines. -- Factor varies depending on ambient temperature (Figure 1) Algorithm modification to derive total emissions using adjustment factors. At 92 percent of the ICAO idle FFR, HC and CO emission EIs increase by 40 percent at 15 degrees centigrade. The combined effect accounting for both the reduction in FFR and increase in EIs is an increase of 30 percent at 15 degrees centigrade. Minimal cost Near-term 2) Apply an engine specific adjustment factor -- Factors vary depending on engine (Table 6 and Figure 1) Algorithm modification to derive total emissions using adjustment factors. Same comment as Improvement Option 1 Moderate cost * 3) Apply adjustment factors only to the CFM56 family of engines -- Factor varies depending on ambient temperature (Figure 1) Algorithm modification to derive total emissions using adjustment factors. Same comment as Improvement Option 1 Moderate cost * NOx There is only one option to adjust emissions of NOx. To what engines it would be applied would depend on the FFR adjustment option described above. Algorithm modification to derive total emissions using adjustment factors. NOx EIs decrease by 8 percent and combined with the decrease in FFR lead to a 15 percent decrease in NOx emissions. Minimal cost assuming same choice for CO and HC already implemented Near-term Additional considerations Assumptions regarding single/reduced engine taxi procedures to be included in modeling When selected by user, apply factor of 0.995 to FFRs for taxi in operations and 0.96 to FFRs for taxi out operations. Algorithm modification to derive total emissions using adjustment factors. Reduction in emissions. Minimal cost Near-term Allow for e-taxi procedures to be included in modeling Allow users to specify the percentage that taxi-related emissions should be reduced. Modification to GUI and algorithms to derive total emissions using adjustment factor. Reduction in emissions. Minimal cost Long-term

30 Taxi/Idle Emissions Computational Factors Research Parameter(s) Improvement Option(s) Required Revision to Model(s) Effect on Predicted Emissions Cost (Ease) of Implementing Improvementa Priority (Near- /Long-Term) Emission distribution across airfield Constant thrust assumption (i.e., should the taxi/idle thrust values vary across airfield idle/taxi phase (e.g., x min @ 4 percent thrust and y min @ 12 percent thrust) or is a single thrust assumption sufficient?) Allow users to define areas other than the runway queue area where aircraft are delayed (e.g., crossing active runways, ramp area where aircraft are held waiting for gate, deicing area). Modification to GUI and algorithms. Increase or reduction in emissions depending on location being evaluated. High cost Long-term a Minimal cost – up to 2 person weeks of effort Moderate cost – up to 6 person weeks of effort High cost – Up to 24 person weeks of effort * This improvement is considered to be an alternative to the recommended near-term improvement.