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

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20 4. Stakeholder Outreach Upon the completion of the Task(s) 4, 5 and 6, the Research Team implemented Task 7: (Stakeholder Outreach) as a means of further evaluating the recommended improvements to computing aircraft taxi/idle emissions using AEDT. Each of four Stakeholder representatives were provided with a summary report describing the research completed in the previous tasks, much to the same detail as provided in the previous sections of this Final Report. Although the number of Stakeholders from which feedback was obtained was minimal, each of the participants is considered to be a subject-matter expect. The low number of participants is in part due to the relatively few Stakeholders on the subject of aircraft taxi/idle emissions and/or a reluctance of others to participate in the Project. The four Stakeholder reviewers that did participate were selected to include a perspective from each of the following stakeholder categories:  Model architecture expert (i.e., model developer)  Model user (i.e., airport air quality consultant),  Airline ground operations and engine performance expert (i.e., representative from active airline company), and  Airport operations expert (i.e., representative from a working airport). The Stakeholder review was focused particularly on receiving feedback on the results of Task 6: (Develop List of Potential AEDT Improvements), that being the identification of potential model improvement options considered in the research, within each of the following categories:  Taxi time and taxi speed  Fuel flow rates (FFRs)  Emission Indices (EIs)  Reduced engine taxiing options  Alternative taxi systems  Airfield emission distribution The Stakeholder feedback received from each of the reviewers on each of the above categories is summarized in Table 7 below. As can be expected with a group of reviewers - each with a different perspective - there was not complete consensus as to the best or most appropriate options for improvement within most of the categories. The following generally summarizes the results, by category: 4.1 Taxi Time Stakeholders generally agreed that existing model default values for taxi time should be revised, with most comments suggesting that an option other than just using ASPM averages would be preferred. If/when more accurate or airport-specific information on taxi times is available, the reviewers feel that should be used. 4.2 Taxi Speed The four Stakeholder reviewers generally agreed that the preferred option for taxi speed would be to allow model users to specify taxiway use (i.e., arrival or departure) and have corresponding default speeds.

21 4.3 Fuel Flow Rates (FFRs) The Stakeholder reviewers were generally apprehensive about the potential improvement options in this category, which would involve adjustments to currently-used ICAO FFR average values, based on actual measured performance data for specific engines, and possibly also including “like engines” along with those for which actual performance data are available. Points raised by the reviewers included concern that the identified options for improvement would use data from (i.) too small a database and from (ii.) engine test data from a group of engine types that may not be transferable to other engine types. As the current model values are ICAO values and accepted worldwide, it was further recommended that any FFR changes should be coordinated with ICAO. 4.4 Emission Indices (EIs) The model developer and model user reviewers had much the same comments as they provided for the options considered for FFRs - specifically, that potential changes should be coordinated with ICAO and caution regarding transferability of test engine data to other engine types. The airport and airline stakeholder reviewers offered no comment(s) on this category, apparently because it is outside their realm of expertise. 4.5 Reduced Engine Taxiing The Stakeholder reviewers generally agreed that some allowance for considering reduced engine taxing in emissions prediction would be appropriate. The airport representative suggested use of this operation mode would be easier to predict at airports with one major carrier. There was no agreement among the reviewers regarding how much of a reduction in emissions should be applied when this operation mode is used. 4.6 Alternative Taxi Systems Generally, the reviewers thought there should be a method by which model users could adjust (by applying a percentage) to account for potential use of alternative taxi systems. Comments also included uncertainty as to the ability of airports to supply the necessary data and the complication that some of the alternative systems would use fuels that would also be emission sources. 4.7 Airfield Emission Distribution This option would allow some modification to the model to define where areas of delay occur and the extent of the delay. The reviewers were generally uncertain that this would be implementable or, if it were, that it would be useful or accurate. Comments included that events were too random and changeable. There were also questions as to quality control of the application of the option and how the model could be modified to consider it.

22 Table 7 Stakeholder Review and Feedback Summary Research Parameter Option Stakeholders Airport Model Developer Model User Airline Taxi time 1 – Update default values using average taxi in/out times computed from ASPM data. At the least. Each airport is unique. Use of the default values should be discouraged for the larger airports where more accurate information is either available or can be determined. In the case where defaults are used, a margin of safety is needed since the analyses are for health-based reasons. Simple averages are not enough. Seems like as an overall 7 and 16 minutes only a 12 percent reduction, however if I am looking at the airport sizes correctly, the refinement could yield greater reductions for large and medium airports. However, this would be a conservative approach to refining the current assumptions. Our airline’s average taxi out time is approx. 5.5 minutes taxi out and 4.5 minutes taxi in so we believe the default values are greatly overestimated. 2 – Allow users to select default taxi in/out times based on array of airport-specific design characteristics. Better. This should be the “default” mode. But again, larger airports should be encouraged to provide data specific for their airport. Seems like the better way to go if you could refine the times based on airport size. I would be interested in the criteria for selecting airport design characteristics. -- 3 – Update current database to include recent data. ACI has adopted European carbon reduction program and assuming more [sic] AEDT may be more frequently used for inventory use than dispersion. These times are more readily available for airports that don’t now calculate taxi times. Care should be taken to make sure of final answers before any updates to databases are made. For example, it is recommended that taxi speeds be decreased leading to greater taxi times and greater emissions. But then recommendations are made to reduce the emission indices. What is the final result? It seems like a wash. The evaluations stop short of going the final step to determine what these changes really mean. This could also be a viable alternative to Option 1 based on actual data. Could this also be used in Option 2? I am a fan of using more recent available data. I assume the revised data includes a variation of aircraft type? Do you have this broken down by aircraft type? Regarding default taxi times, we suggest option 3. For all airports in our system, we have data available specific to each airport that include taxi times. Is there a way the new AEDT model could prioritize actual times gathered from air carriers? Our airline has been able to provide this data for several airport emissions inventories resulting in significant reductions in emissions from this parameter. Taxi speed 1 – Update default taxi in/out speed. Good to update the speed, but I would be more interested in seeing a set speed established and not changed over scenario or time so changes in taxi time and fuel flow resulting in updating airport facilities and aircraft engines will show what changes to both of these will do. As an airport I can control stop and start but not speed. These times are unique to taxi in/out, airport layouts, aircraft type in use, and even airlines. If implemented it needs to be implemented based on these variables and not just an overall average which may not necessarily be better for each airport. If I read this data correctly, there does not seem to be a lot of variability in the engines and taxi speeds evaluated in the 7 engine types? What representation is this to the total fleet? Reading in the back, maybe 448 test engines in the U.S.? Our average taxi speed is higher than the one mentioned in the study and we can provide you with an exact number if you like. Guidance mentions a taxi speed of 35kts except in congested areas. Looking at average taxi speeds we could provide this data for specific airports, including or excluding delay times. The default speeds mentioned seem to be low. Again, our airline prefers option 2 where airports use actual taxi speeds. This information can be obtained by contacting carrier environmental staff. 2 – Allow users to specify (or have the model distinguish) whether a taxiway is used for arrivals or departures. Use corresponding default aircraft speeds. As above. This should be included if changes made, but again there are more variables than just this one (see comment above). Taxi speeds can change on departure as an aircraft approaches the runway and queues up. Taxi speeds can also change on arrival as an aircraft approaches the tarmac/gate area. If possible, this seems to me to be more accurate compared to the default Option 1 -- Fuel flow rates 1 – Apply engine-specific FFR adjustment only for engines for Sounds reasonable While on the surface this is a good idea, the ICAO values are based on worldwide acceptance. In the test engine data, looking at Table A-1, perusing at the list of airlines, --

23 Research Parameter Option Stakeholders Airport Model Developer Model User Airline (FFR) which test data are available. Before any changes are made, this should go through ICAO and not just implemented without any concerns for the overall practice. nothing is represented for JetBlue and Southwest airlines which seem to be a large percentage of U.S. operations. Will these aircraft and large operations be adequately addressed? 2 – Apply engine-specific FFR adjustment to engines for which test data are available and engines determined to have like fuel flows and emission indices. -- (See previous comment). In addition, this now starts to add in uncertainty. A practice to change by ratio of the measured fuel flows from ICAO may reduce this uncertainty. This would be a great benefit, but are you confident you can assimilate existing engine data into the ones for which test data are available. Have you mapped out a methodology for assigning like fuel flows? Our airline’s configuration is not addressed in this research: Our classic fleet are equipped with CFM56- 3B1 engines and CFM56-7B24 engines. Fuel flow during taxi is dependent not only on temp but also on breakaway thrust to get the a/c rolling. Once rolling the a/c will have the engines back in idle. For this we need to consider the weight of the a/c as well. As reference for engine thrust settings, we don’t use % of maximum thrust. We usually call it engine speed. The engines usually idle at about 22-25% N1. As breakaway thrust, we use an average of 35% N1. Depending on fleet type the following fuel flow in average can be seen: -300: Idle at the gate 800 lbs/hr, taxi 1,874 lbs/hr -500: Idle at the gate 804 lbs/hr, taxi 1,913 lbs/hr -700: Idle at the gate 788 lbs/hr, taxi 1,954 lbs/hr, APU fuel flow 194 lbs/hr -800: Idle at the gate 818 lbs/hr, taxi 1,977 lbs/hr, APU fuel flow 180 lbs/hr 3 – Apply a global adjustment to all commercial jet engines based on average normalized FFR. It may be worthwhile taking a quick look at the percentage of aircraft engine variants in-use worldwide before we make a final decision. Again, this is an ICAO process. Additionally, for all options associated with FFR, even though data shows a reduction in idle FFRs, any time an aircraft comes to a complete stop during taxi they need and will apply thrust significantly over the 7% power setting. When analyzing the FDR data, this should have been observed. How will this be applied for taxi? Could be a good compromise, but may run into the same issues identified above for assimilating like engine data. Have you mapped out a methodology yet? The project used 258,824 flights (data samples) from mostly European carriers, which is approx. 5 years’ worth of data. This is the amount of flights our airline collects in 3 months. Five years of data would be about 4 million flights in our system. As a result, we don’t think use of this small data set from European carriers would adequately represent all commercial jet engines. Emission Indices (EI) 1 – Apply a global EI/FFR adjustment factor. Beyond my understanding. Again an ICAO process. How much will uncertainty be reduced? Need to go the next step in process to recommend. For example, will defaults be used or will each engine be known? No specific comments to EI, just similar to the above -- 2 – Apply an engine-specific EI/FFR adjustment factor. Beyond my comprehension. Same comment as above. -- -- 3 – Apply adjustment factor to No on principle. This is based on sufficient data but again, with the -- --

24 Research Parameter Option Stakeholders Airport Model Developer Model User Airline CFM56 engines only. worldwide acceptance and use of ICAO, should again go through this process. Reduced engine taxiing Allow users to indicate if reduced engine taxiing procedures should be considered. If so, apply minimal reduction factor. Taxi in, maybe we should apply minimal reduction, if practiced. Taxi out no. Airports with one major carrier are easier to predict what the pilots will do. Taxi out by a 380 on two engines is preferred by operators but not by airports as spooling up two engines to turn a 90 degree corner can knock over signs and can peel grass off. This would seem to be justified. The question not answered is that when reduced engine procedures are used, how much more fuel flow and increase in emissions occur for the engines used. If I understand correctly, reduced engine taxiing only results in a 4 to 5 percent reduction? How did you arrive at this? Single engine taxi is a procedure we utilize for taxi out and taxi in. For taxi in and out, our airline has a compliance rate of more than 70%. We have calculated a savings of around 12 gallons of jet fuel per taxi event, and are concerned that the reduction factor may be too low, but don’t have the details of your calculation in order to determine that. Alternative taxi systems Allow users to enter a percentage by which emissions would be reduced to account for a specific type of alternative taxi system in use at an airport. Good idea. Airports would be hard pressed to supply adequate data. Would you also do this for alternative fuels? Agreed. However, some of the alternative taxi systems under development utilize hybrid diesel engines (Taxibot), which would be considered an emissions source. I do think it is important that future models account for systems such as those mentioned in the stakeholder feedback report. Airfield emission distribution Modify model to provide an option for analysts to define where areas of delay occur and the extent of the delay. Arrival queuing no, too random. Departure yes. The offsite data available for dispersion modeling is so inaccurately apportioned as to make fine improvements to the airport data not needed. This could be an option that some larger airports could use. How will it be quality controlled? I like this flexibility and seems much more realistic when conducting dispersion modeling. Do you have some ideas for how you would make such modification to the model? Not sure if this can be quantified or modeled. Most delays on the tarmac are due to weather or construction on the airfield, both of which constantly change. Regulatory changes have required carriers to return to the gate for major delays, otherwise they face fines. In addition, delays can result in engine shut- down while the APU powers the aircraft.