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103 Exhibit 3-62. Pedigree matrix--cargo handling equipment parameters. Technological Correlation Geographic Correlation Temporal Correlation Representativeness Acquisition Method Range of Variation Impact on Result Independence Parameter Population 4 Varies Varies Varies N/A Varies Varies 5 Load Factor 4 2-3 1 2 N/A Varies 2 4 Emission 4 2-3 1 2 N/A Varies 3 4 Factor Engine 4 1 Varies Varies N/A Varies 1 1 Power Activity 4 Varies 1-2 3 N/A Varies 3 4 Load Factors. Most models either require input of, or pact of its uncertainty is somewhat mitigated. More discus- use default values for, load factors for a piece of equipment. sion has been presented in Sections 3.7.3 and 3.7.4. This factor represents the average load experienced by an engine over a period of use, typically annually. This factor is Emission Factors. Most models either require input of, ultimately derived from second-order factors, such as the or use default values for, emission factors. Typically, these are duty cycle. However, estimates for many specific types of defined for a given combination of engine power and age. As equipment are not available and are aggregated from average for other factors used to calculate emissions, the result is lin- values of similar equipment types. Because emissions are lin- early proportional to this value, thus the impact of uncer- early related to load factor, this can have a large impact on the tainty in this parameter on that for the final calculations can uncertainty of total emissions. More discussion has been pre- be significant. Emission factors are determined from a range sented in Sections 3.7.3 and 3.7.4. of activities, including measurements, certification databases, and engineering judgment. More discussion has been pre- Engine Power. Engine power represents the total rated sented in Sections 3.7.3 and 3.7.4. power of CHE engines. Calculation of CHE emissions gener- ally requires disaggregation of equipment into bins of specific horsepower range since the power and age typically deter- 3.8 Air Transportation mine the engine category for regulatory purposes. Databases For aviation-related emissions the following two modeling of CHE within these bins are incorporated into the NONROAD and OFFROAD models, or should be collected through sur- approaches are reviewed and evaluated: veys. Because emissions are linearly related to total power, Version 1.5 of the FAA's System for Assessing Aviation's this can have a large impact on the uncertainty of total emis- sions. More discussion has been presented in Sections 3.7.3 Global Emissions (SAGE) modeling system is the primary and 3.7.4. method for national or regional emission analysis in the United States. Other national or regional aircraft models Activity. Engine activity determines the average operating are under development but these are focused on non-U.S. hours a given piece or group of equipment types have in an regions (e.g., AEM [EUROCONTROL], AERO2k [UK/ annual period, typically described in hours per year. It is not QinetiQ], and FAST [UK/MMU]). The emphasis of these commonly broken down into power bins, but left at the CHE models is on global-scale emission inventories with regional type level. Because emissions are linearly related to activity, emphasis on european issues. (160) uncertainty in this parameter can have a large impact on the Version 5.1 of the Emissions and Dispersion Modeling Sys- uncertainty of total emissions. However, because activity also tem (EDMS), released September 19, 2008, was developed by figures into the age distribution of the NONROAD model, im- FAA specifically to address the impacts of airport emission

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104 sources, including ground-level sources and associated and fuel flow rates for a wide variety of jet engines that have support activity. FAA requires the use of the model in per- entered service; forming air quality analyses for aviation sources. Recent Base of Aircraft Data (BADA), which is a collection of air- improvements to the model include speciated air toxic craft performance and operation parameters, includes co- emissions, CO2 emissions from aircraft, improved method- efficients in the data that allow calculation of lift and drag ology for PM emission estimates, and the addition of 63 new forces; engines and 40 aircraft. FAA also is sponsoring ongoing Information on airport location and altitude; research through the Partnership for Air Transportation Official Airline Guide (OAG) database contains information Noise and Emission Reduction, to understand and evalu- on trip origination, trip length, type of aircraft, destination, ate the potential role of aviation emissions in local and re- and aircraft type for all commercial activity; gional air quality. The main objective of the project is to Enhanced Traffic Management System (ETMS), a database quantify the potential incremental contribution of aviation on the electronic recording of flight position and flight emissions to local and regional air quality though their plan used for air traffic management, captures every flight chemical interaction with the background air. within coverage of FAA radars; ICAO's Forecasting and Economics Sub-Group Forecast A summary of air freight methods and models is shown in contains forecasts of the number of aircraft, number of air- Exhibit 3-63. craft seats, number of flights, capacity, and average seating numbers per aircraft by region; FAA's Terminal Area Forecast provides information on 3.8.1 Evaluation of National passenger boarding and aircraft operations for each U.S. and Regional Models airport; The FAA has been working on the development of a na- USDOT's Bureau of Transportation Statistics (BTS) data- tional-to-global version of SAGE since 2001. The most current base provides on-time performance for the 10 largest U.S. version has been used to develop annual emission inventories air carriers; for commercial (civil) aircraft fuel consumption for CO, NOx, FAA's annual runway capacity "benchmarking" report of SO2, HC, H2O and CO2. (37) Because the model operates at U.S. airports provides a basis for delay data; and the level of individual flight by airport it can potentially be Aircraft retirement parameters (data that categorize the applied to a limited regional analysis as well as at the national survivor curves [i.e., polynomial equations] for the aircraft level. This version of SAGE dynamically models aircraft per- fleet population that survived the retirement process) by formance, fuel consumption, and emissions, and includes aircraft category type and age. such factors as capacity and delay at airports. The model does not have the current capability to separate freight-only travel Model Overview from freight and passenger operations nor does the model include military air cargo activity. The fundamental modeling unit in SAGE is a single flight. The model is driven primarily by a set of databases that are All data, including those related to flight schedules, trajecto- used to develop the emission inventory. The key databases ries, performance, and emissions, are represented at a level of include the following: detail sufficient to support the modeling of a single flight. This allows high resolution modeling of emission inventories. International Civil Aviation Organization (ICAO) emis- Each flight is modeled from gate to gate. Although a single sions databank with information on certification emissions flight in SAGE is the modeling unit, the simulation is con- Exhibit 3-63. Air freight methods and models. Geographic Method/Model Type Pollutants Freight/Passenger Scale FAA SAGE Model Global, CO, hydrocarbons Commercial freight and (version 1.5) National to NOx, CO2, H2O,* and SOx passenger (no military) Regional EDMS (version Model Local Criteria pollutants, NMHC, CO2 and 44 air toxics Freight and passenger 5.1) * Water (H2O) is included here because when emitted at cruising altitude into the lower stratosphere/upper troposphere, it acts as a greenhouse gas via contrail development.

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105 ducted at a more detailed level (i.e., each individual segment between direct measurement and fuel flow correlations using of flight--referred to as a flight chord--is calculated by the curve-fitted ICAO data to within a standard deviation of 6% model). Typical flights in SAGE are represented by 40 to and a maximum error of 13%. (166) Other sources of uncer- 50 chords, depending on the stage length and availability of tainty in most emissions data, including certification data, detailed radar trajectory data. The flight chords allow the abil- consist of the variability in emissions inherent among engines ity to express outputs in a variety of different formats (e.g., in the fleet and aging of the engine. (11, 165, 167) gridded and per flight mode) and allow for dynamic aircraft Overall the emission indices for NOx have been estimated performance modeling in SAGE. Such modeling provides an to have a standard deviation for an approximate normal dis- opportunity for improvements in accuracy relative to those tribution of 24% based on the aggregation of 16% uncer- based on aggregated TIMs or simplified performance lookup tainty incorporated in the engine certification process, adding tables. To accomplish the detailed flight-by-flight modeling, (using sum of squares) the uncertainty in curve fitting and SAGE includes information on a variety of aircraft fleet, op- BFFM2 (6% and 10%, respectively) and then accounting for erations, and performance data, as well as the modules to the bias error due to aircraft engine degradation (4%). (11) The process the information and perform computations. The uncertainties implied in the certification process for HC and model reports information both on a vertical and horizontal CO emission indices are 54% and 23%, respectively, and also distribution. have been aggregated with those of curve fitting and BFFM2 The SAGE model was last updated in September 2005. The with a resulting estimated standard deviation in the uncertainty model's primary purpose is to provide FAA and, indirectly, of 55% HC and 26% for CO. However, these estimated un- the international aviation community, with a tool to evaluate certainties need to be confirmed by comparing SAGE emissions the effects of various policies, technology, and operational results to measured emissions over a wide range of emission scenarios on aircraft fuel use and emissions. The current ver- points, power settings, and engine types that are not readily sion of the model is not considered a standalone model; it is available at present. used primarily as an FAA research tool. Below the mixing height (i.e., around 3,000 ft) where air- The information presented on SAGE is principally based on craft emissions have the greatest impact on local air quality, the analysis, review, and discussion of the SAGE Version 1.5 the landing and takeoff (LTO) procedures are an important Technical Manual, (161) SAGE: Validation Assessment, Model source of uncertainty. LTO procedures mainly consist of en- Assumptions, and Uncertainties, (162) "System for assessing gine throttle setting, rate of climb/descent, and flight speed. Aviation's Global Emissions (SAGE), Part 1: Model Descrip- The analysis of a major carrier's computer flight data recorder tion and Inventory Results," (163) and "System for Assessing results showed that the throttle setting and resulting change Aviation's Global Emissions (SAGE), Part 2: Uncertainty in the emission index for NOx, HC, and CO were the most Assessment." (164) important parameters, accounting for 30% to as much as 70% of the total variance of the emissions. Other LTO proce- Summary of Strengths and Weaknesses. An analysis of dures such as the rate of climb, descent plus flight speed, and the strengths and weaknesses of FAA's SAGE is included in aerodynamic drag explained most of the remaining variance Exhibit 3-64. in the emissions estimates below 3,000 ft. Finally, although individual uncertainties for specific air- Analysis of Process Uncertainty. To estimate emissions, craft may be large, it is likely that the current version of SAGE SAGE uses Boeing Fuel Flow Method 2 (BFFM2), which is a can distinguish between the emissions associated with the method developed based on engine performance and emis- typical policy options that are directed across all aircraft and sions data obtained from ground-level engine tests. BFFM2 engine types. However, it would be important to analyze the uses ICAO certification fuel flow and emissions data taken at uncertainties and account for them when interpreting any 7%, 30%, 85%, and 100% rated outputs at sea level pressure type of policy scenario analyses. as the basis for correcting emissions indices for installation ef- fects, ambient conditions, and flight speed. At the four certifi- cation points, BFFM2 provides an agreement between meas- 3.8.2 Evaluation of Local/Project-Level Models ured and calculated emissions indices that is within 10% for Starting in the mid-1980s, the FAA developed the Emissions most jet engine types. Increased uncertainty occurs in estimat- and Dispersion Modeling System (EDMS) to assess local air ing idle emissions below 7%, particularly for HC, and these quality impacts in the near airport vicinity for a single airport. errors may be large and tend to be an underprediction. (165) The current version of EDMS incorporates EPA-approved The interpolation method (curve fitting), used between emissions inventory methodologies and dispersion models certification emission portions, is another source of uncer- to ensure that analyses performed are consistent with EPA tainty. A comparison undertaken by ICAO found agreement guidelines. EDMS is used primarily in complying with local

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106 Exhibit 3-64. Analysis of strengths and weaknesses--FAA SAGE. Criteria Strengths Weaknesses Representation of physical The model details actual flight path and trajectories with flight-by-flight modeling. SAGE includes The model only includes emissions from commercial aircraft--no processes specific aircraft fleet information and operations, combined with the use of engine performance data. general aviation or military flights. Studies have suggested that Such detailed modeling represents an improvement in accuracy over other methods based on military aviation in the U.S. is responsible for up to 15% of aircraft aggregated TIMs or simplified performance lookup tables. emissions. Requires an extensive database to make the emission calculations. Relies on emissions indices as a function of fuel consumption to estimate emissions. Model sensitivity to input No formal sensitivity analysis has been conducted with the model but the model is highly dependent Lack of a model-specific sensitivity analysis makes it difficult to parameters upon the emission indices, which are a function of the fuel burn which, in turn, are sensitive to quantify the model's sensitivity. Emission indices are best developed aerodynamic and engine performance, aircraft take-off weight, and flight speed. Individual flights not for NOx, followed by HC, CO, and water vapor. using winds aloft information also use standard day ambient temperature. The fuel burn rate is based on engine performance and emissions data obtained from ground-level, full-scale engine tests. These are the ICAO certification fuel flow and emissions data taken at 7%, 30%, 85%, and 100% rated outputs at sea level with corrections for installation effects, ambient conditions, and flight speed. NOx emission indices are the best developed, having been created for a broad range of engine types, and power settings and measured fuel flow rates. Ability to incorporate This design of SAGE allows a user to quantify the effects of communication, navigation, and Requires detailed knowledge of the model databases and can only be effects of emission surveillance/air traffic management (CNS/ATM) initiatives, determine the benefits of reduced vertical performed by FAA or their supporting organizations. reduction strategies separation minimum (RVSM), investigate trajectory optimizations, and compute potential emissions benefits from the use of a continuous descent approach (CDA). Representation of future The forecasting module uses flight forecasts from the FAA's Terminal Area Forecast (TAF) for U.S. The forecast is created from airport-based projections. Model can be emissions flights and ICAO's Forecasting and Economics Sub Group (FESG) for the rest of the world. The TAF updated through database for new aircraft and engines but it has method involves creating a week's worth of official airline guide scheduled flights to represent the been almost 4 years since last public update. growth in demand for a future year. The week was a balance between accuracy and computational efficiency. Also included are the effects of aircraft retirements and replacements. The result is a future schedule of flights reflecting the effects of fleet growth and retirements with replacements Data quality Use of radar-based flight trajectories and speed are highly accurate in most cases. Although specific The most important default assumptions in determining the modeled flights may be in error by up to 40%, average fleet emissions showed less than 10% error. emission rates are the use of the International Standard Atmosphere temperature, not correcting for winds aloft, use of Base of Aircraft Data (BADA) aerodynamic performance, and aircraft take-off weight and flight speed. Other important concerns are the OAG-based flight trajectories and the use of the Boeing Fuel Flow method to estimate the emission indices. Separation of air cargo In general, commercial aircraft fly the same airframe design and engine technology whether the The model does not have a method for separating air cargo from from passenger travel intended load is passengers or air freight. For airports that can separate aircraft operations performed passenger transport activity, nor does the approach separately exclusively for air freight transport, the current version of SAGE can be used to assess air freight identify those aircraft used exclusively for air cargo transport. emissions. Spatial variability The model's accuracy for spatial representativeness is directly tied to the quality of the TAF and FESG Most aircraft activity is in the U.S. and Europe, although substantial databases. It is anticipated that the accuracy of results from the model is dependant upon the depth of growth is projected over Asia. activity and load information in these databases. Vertical distributions are anticipated to be more accurate because of the use of actual flight path and trajectories with flight-by-flight modeling. Greenhouse gas Unlike criteria pollutants, the locations of emissions are irrelevant, but all of the emissions from aircraft The fuel consumption data must be used with generic emissions emissions need to be determined. The Intergovernmental Panel on Climate Change (IPCC) protocol recommends factors for jet fuel to calculate emissions of CH4 and N2O. The FAA that each flight's emissions be attributed to the departure airport. Also, the IPCC prefers that the SAGE dataset will not include future emission projections. Emission method be based on aircraft performance and operating data rather than fuel sales. This is the rates are not separated into cargo and passenger modes. approach employed in SAGE for CO2 emissions using extensive information on aircraft fleet, flight schedules, trajectories, and aircraft performance. Based on results from applying SAGE, FAA is expected to begin releasing these results publicly in the near future for airport operators to use in determining GHG emissions. This information would be reported as fuel burned and CO2 emissions for ground level (taxi/idle mode), above ground to below 3,000 ft (takeoff, climb-out, and approach modes), and above 3,000 ft (reflecting cruise). Review process Review process has been limited to peer review publications of model results and meeting Only user guide documentation available, code and databases are presentation on findings and methodology. not publicly available. This limits full and open comparison. The large database sizes have limited the model's distribution. The model has been made available to support various International Civil Aviation Organization/Committee on Aviation Environmental Protection (ICAO/CAEP) activities but with FAA running the model. Endorsements FAA recommends that the model may be used in developing policy, technology, and operational Neither ICAO nor EPA have made statements about the model. FAA scenarios on aircraft fuel use and emissions. continues to support the model, but it has been almost 4 years since the last public update to the model. Model Comparison with research-oriented methodologies such as the NASA/Boeing scheduled inventory and Lack of a public availability of the model has hampered external comparison/evaluation SAGE totals show a 30% difference, which may partly be explained through differences in trajectory review by outside agencies and the international community. studies modeling (Great Circle used by NASA/Boeing versus track distributions used in SAGE) and the inclusion of unscheduled flights in SAGE (unaccounted for in NASA/Boeing studies). However, estimates for any given flight may be off by 50% or more. An assessment of the aircraft performance module showed that when comparing point-by-point fuel flows from SAGE against data from a major U.S. airline and NASA, the overall agreement was good with mean errors of 6.95% and 0.24%, respectively. Similarly, system-level (aggregated flight-level) comparisons of fuel burn against data from one major U.S. airline and two major Japanese airlines also showed good agreement with mean errors of 2.62% and 0.42%, respectively

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107 air quality requirements (e.g., NEPA documents, EIS/EIR, air quality impacts in the near airport vicinity by developing an toxic risk assessments, and general conformity). The model emission inventory from the emissions from aircraft, auxil- uses a comprehensive database of aircraft engines and emis- iary power units, ground support equipment, and stationary sion factors in different modes, ground support equipment, sources. Emissions are developed based on a combination of auxiliary power units, and vehicular and stationary source EPA models and best-available models from other sources emission factor data. The model includes emissions for CO2, such as an aircraft performance module for calculating air- CO, THC, NMHC, NOx, SOx, PM2.5, PM10, and 395 speciated craft emissions, on-road (MOBILE6.2) and off-road vehicles hydrocarbons for use in air toxic assessments. The CO2 emis- (NONROAD2005). EDMS has an extensive database with in- sions are calculated only for aircraft. Aircraft PM emissions formation from engine manufacturers, FAA, and EPA on the are only available for aircraft with ICAO-certified engines. The aircraft flight performance arrivals (approach and taxi-idle) model offers two approaches for estimating emissions: one and departures (takeoff and climb out). This information based on an ICAO EPA TIM approach and another that uses is indexed by aircraft types, which is cross-referenced with an aircraft performance module that dynamically models the nominal takeoff weight and glide slope angle. The dispersion- flight of an individual aircraft based on its flight profile. The air modeling module uses EPA's AERMOD (version 07026) and quality dispersion analysis uses EPA's AERMOD dispersion its supporting weather and terrain processors to determine modeling system. Concentrations of the pollutants are output air concentrations. EDMS offers the flexibility of allowing the for comparison with the NAAQS. The model does allow the user to perform an emissions inventory only or to perform air specification of user-created aircraft modes when operated dispersion modeling as well. Results are reported as ground- with the aircraft performance module in which specifications level concentrations. (170) can be made for cargo-only aircraft. However, the model does EDMS was last updated in September 2008 (version 5.1). not determine the freight fraction for aircraft that move both EDMS is used primarily to assess the local air quality impact cargo and passengers. The model has no future forecasting in the vicinity of individual airports as part of an environ- capabilities. (168) mental impact assessment under NEPA or general conform- The model is driven primarily by a set of databases that are ity requirements. Recent integration efforts are underway used to develop the emission inventory. The key databases to integrate EDMS as part of an Aviation Environmental include the following: Design Tool (AEDT) that will result in the ability to model noise and emissions interdependencies in the same model- ICAO emissions databank containing information on cer- ing platform. A research version of EDMS, funded by FAA tification emissions, default TIM, and fuel flow rates for a and NASA, is underway to develop a 3D representation of wide variety of jet engines that have entered service. aviation emissions at the regional scale, coupled with a re- Aircraft performance-based database using system air- gional-scale air quality model (i.e., community multiscale craft-engine (SAE AIR 1845) TIM as an alternative to the air quality [CMAQ] model) to assess air quality impacts for ICAO emissions databank. These data were developed for, regional-scale air pollutants of fine particulate matter, ozone, and adapted from, the Integrated Noise Model (INM). and air toxics. EUROCONTROL Base of Aircraft Data [BADA] is used in The primary information on EDMS comes from the analy- the aircraft performance modeling. (169) sis, review, and discussion of the EDMS 5.1 User's Manual Various ground support equipment emission factors for use (171) and the EDMS 4.2 Technical Manual. (172) in EDMS are based on EPA's NONROAD2005 model using the fuel type, brake horsepower, and load factor variables. In Summary of Strengths and Weaknesses. An analysis of addition, a deterioration factor is applied based on the age the strengths and weaknesses of EDMS is provided in of the engine. A national default fleet average age may be Exhibit 3-65. used for a particular equipment type or a facility-specific age of an individual piece of equipment may be specified. Analysis of Process Uncertainty. Ideally, a comprehen- Motor vehicle activity can be incorporated into the model sive validation of the EDMS model would be conducted using using information on the number of vehicle trips and av- field data to scientifically determine the accuracy of the model erage speed while traveling on roadways with emission fac- and ensure the model results are defensible. This effort would tors based on EPA's MOBILE 6.2. National default age dis- include a multi-year measurement plan and analysis follow- tribution can use a base year assignment up to 2025. ing EPA protocols so that EDMS could be fully evaluated using several detailed steps as follows: Model Overview 1. Identification and collection of previously collected field The EDMS is both an emissions inventory development data that potentially could be used in validation, model and an air dispersion model. It is used to assess air 2. Assessment of the quality/applicability of collected data,

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108 Exhibit 3-65. Analysis of strengths and weaknesses--FAA EDMS. Criteria Strengths Weaknesses Representation of The model details aircraft activity based on dynamic aircraft performance- Model only examines primary emissions; does not allocate aircraft emissions in a full 3D physical processes based modeling. The model includes operational profiles in 15-minute bins environment. of aircraft delay and sequencing. Model sensitivity to Aircraft emissions in EDMS are dependent upon two main parameters: the FAA has announced plans to conduct a robust sensitivity analysis on EDMS, but has not input parameters emission factors obtained from the aircraft/engine combination and the published results from any studies to date. This is because the EDMS system has vertical flight profile. Within the flight profile the least well-established undergone a tremendous number of changes over the past 6 years with the release of 2 parameter is the TIM. major changes (EDMS 4 and EDMS 5) and 6 extensive model changes. Ability to incorporate By providing user-specified aircraft emission factors and performance data, No capabilities for testing operational changes such as aircraft approach and descent effects of emission emission reductions for aircraft engines can be assessed. changes. reduction strategies Representation of The model has the capability for assessing future emission changes for on- Lacks a capability for assessing aircraft emission reductions. Latest version of NONROAD future emissions road and nonroad vehicles. The Voluntary Airport Low Emissions (VALE) model is now NONROAD2008. Similarly, MOVES is to be released in 2009 and current Program can be evaluated for selected airports. version of EDMS incorporates MOBILE6.2. Data quality Comparison tests with other local-scale airport models suggest overall Large variability exists for the TIM between aircraft grouping (e.g., business jet vs. small jet) emission strength is reasonable, but that a large variability exists in aircraft and TIM default varies widely from airport to airport. Also, emission factors vary widely from grouping, TIMs, and emission factors. one grouping to another. Separation of air cargo The model allows the specification of user-created aircraft modes when The model does not determine freight fraction for aircraft that move both cargo and from passenger travel operated with the aircraft performance module in which specifications can be passengers. made for usage as cargo-only aircraft. Spatial variability User specifies horizontal locations of emissions. Vertical profiles in 2D are Does not represent aircraft emissions on a full 3D grid. specified for the aircraft approach and takeoff grids from which the emissions are released. Greenhouse gas Includes CO2 emissions for aircraft only. Uses same approach as criteria No emission estimates for N2O or CH4. Emission rates are not separated into air cargo and emissions pollutants. Emissions reporting can be reported by aircraft mode. passenger modes. Review process Validation and uncertainty studies have not been made publicly available to No external peer review has been performed although DOT's Volpe Center reports that a date. Although, FAA has announced plans to actively pursue a better program is underway for modeling validation and uncertainty assessment. FAA continues understanding of the uncertainties of the modeling components for the new efforts to improve model but moving towards development of AEDT. Source code not Aviation Environmental Design Tool (AEDT)/EDMS with plans for formal publicly available. Technical User Guide was last released with version 4.2 of EDMS now at parametric sensitivity and uncertainty analyses. version 5.1. Executable of model available but requires licensing with EUROCONTROL Base Aircraft Data. Endorsements FAA requires that EDMS be used in air quality impacts of airport emission Only User's Manual and Technical Manual available. To date, little documentation and/or sources for purposes of complying with NEPA and general conformity. In model verification testing has been reported or made publicly available. FAA has plans to addition, FAA and EPA have co-written a recommended best practice improve this as they move toward release of AEDT in December 2011. document with an accompanying technical support document for issuance by each agency scheduled for the summer of 2009. Model Intercomparison of three different local airport emission inventory tools-- Limited comparison or model validation has occurred by outside agencies or from the comparison/evaluation ALAQ, LASPORT, and EDMS--showed that all models have similar global international community. Lack of a performance evaluation dataset has hampered this type studies results for aircraft, but that aircraft emissions were dependent mainly on the of evaluation. engine emission factors and climb-out profiles. (160) 3. Collection of additional field-measured data, components of AEDT as well as on the whole tool. The analy- 4. Rigorous exercising of EDMS for comparison with col- sis would consist of quantifying uncertainties of AEDT and lected data, and rank ordering of the most important assumptions and limi- 5. Comparison of EDMS performance with that of other tations. Gaps in functionality potentially would be identified similar models (e.g., the ADMS-Urban or Eurocontrol's that significantly impact AEDT, leading to the identification ALAQ). of priority areas for further research and development. In addition, the evaluation would examine the modeling factors The results of this effort would be used to identify EDMS that contribute to model output uncertainty. limitations, correct major deficiencies, as well as determine the overall accuracy and sensitivity of EDMS. However, cur- 3.8.3 Freight Disaggregation rent FAA priorities are focused on the development and eval- uation of ADET, the replacement model for EDMS. FAA's EDMS does not distinguish between freight and passenger priority is that this model has a complete and informed movements. To solve this problem, the study team developed process analysis so that a comprehensive understanding of an approach to allocate each airport's total commercial air- the model's uncertainty, inputs, and assumptions is devel- craft emissions to the freight and non-freight sectors. (67) For oped. As part of the development of AEDT, FAA plans to each airport of interest, the team used the BTS Air Carrier conduct a formal parametric sensitivity and uncertainty Statistics Database to obtain aircraft departure records with analysis. This analysis would be completed on individual the following data fields: