1. 1 Environmental Aspects of Air Transportation Dr. Terry Thompson Aviation and Environment Symposium – September 2007 Science and Technology to Achieve a Sustainable System NoiseLocal Air QualityClimateEnvironmental Management

2. 2 Outline  Overview of Research Topics  Noise Metrics and Impact Calculations  Air Quality Metrics and Impact Calculations  Climate Change  Environmental Management Systems

3. 3 Overview of Environmental Research Topics  Principal areas: - Aircraft-related noise and its effects in urban and rural settings - Local air quality and interface to broader atmospheric physics - Fuel efficiency - Climate effects and associated atmospheric physics and chemistry - Planning for mitigation of environmental effects - Balanced management of environmental and operational factors - Appropriate metrics and underlying physical and chemical phenomena - Nature and magnitude of potential environmental constraints - Multi-objective optimization to support operational and environmental goals - Market-based techniques for economically balanced management - Simulation, modeling, and decision-support tools in support of the above

4. 4 Noise Metrics and Impact Calculation

5. 5 Sound and Noise – The Basics  Sound waves are pressure oscillations in the atmosphere.  Sound perception is modulated by the structure of the human hearing mechanism, which translates these oscillations into complex perceptual phenomena related to the frequency content and intensity of the sound waves.  Humans are sensitive to oscillations with frequency range of approximately 20 to 20,000 Hertz (cycles/sec), with a minimum intensity of about 10 -12 watts/m 2, or a pressure difference of 0.0002 dyne/cm 2.  Human perception of loudness is highly non-linear, and the relationship between frequency, intensity, and loudness is quite complex.  To capture this non-linearity, sound spectra are usually modified by a weighting function (A-scale) that de-emphasizes portions of the spectra below 1,000 Hz and above 16,000 Hz.

6. 6 Sound and Noise – The Basics (Cont’d)  All events have different durations; how will they be compared in impact?  SEL is the basic noise-level measure, and has a standard reference period of one second. Time (sec) Sound Level (dB) L(a) = 10 log 10 (Measured_Level 2 / Reference_Level 2 ) LA max LA max – 10 dB LA max – 20 dB 10020 Sound Exposure Level, SEL A-weighted Sound Level, LA(t) SEL = 10 log 10 (1 / 1sec)  t1 t2 10 LA(t)/10 dt

7. 7 Noise Metrics (A-Weighted) DNL - Day/Night Average Sound Level (63-72 dB in noisy urban area, 20-30 dB in wilderness) CNEL - Community Noise Equivalent Level LAEQ - Equivalent Sound Level (24 hours) LAEQD/LAEQN - Equivalent Sound Level Day/Night A-weighted level of a one-second event equivalent in acoustic energy to the original event. - SEL - Sound Exposure Level Maximum A-weighted sound level for an event. - LAMAX - Maximum Sound Level Time that the noise level is above a user-specified A-weighted sound level - TALA - Time Above a Sound-level Threshold

8. 8 Noise Metrics (Tone-Corrected Perceived) NEF - Noise Exposure Forecast WECPNL - Weighted Equivalent Continuous Perceived Noise Level EPNL - Effective Perceived Noise Level (multi-event) PNLTM - Maximum PNLT Sound Level TAPNL - Time Above a PNLT Threshold

9. 9 Noise Metrics Summary Frequency Weighting Metric Type Metric Name Event Weighting (day/eve/night) Averaging Time (h) SEL111 DNL111024 CNEL131024 LAEQ11124 LAEQD11015 LAEQN0019 LAMAX111 TALA111 Exposure Based Maximum Level Time Above Threshold A-Weighted EPNL111 NEF1116.724 WECPNL131024 PNLTM111 TAPNL111 Exposure Based Maximum Level Time Above Threshold Tone-Corrected Perceived

10. 10 Core Noise Calculation Engine type and number Five-dimensional state along each segment of flight trajectory Distance to observer Orientation with respect to observer (for on-ground segments) -------- Information required: START X, Y, Z, V, THR Objective is calculation of total noise dosage at each observer location. Observer on ground END X, Y, Z, V, THR X Y Z a b c Total noise impact at given observer = 10 log 10 (1/T)  flights  segments 10 SEL(i)/10 T = dosage period (e.g., 24 hours)

11. 11 Calculating Average Annual DNL  Sampling of 30-60 days of radar tracks throughout the year provides « annualized » average 24-hour set of flights and trajectories.  Noise/power/distance data provides SEL as function of engine power setting and distance (slant range) from aircraft to observer.  DNL at jth observer from DNL j = 10 log 10 (1/T) {  day_flights  segments 10 SEL(ij)/10 +  night_flights  segments 10 [SEL(ij)+10]/10 } Calculate SEL for all segments of each flight at each point Calculate DNL at all points due to all flights Create annual average day of traffic 2CF650 Arr 10000 lbs 106.2 dB @ 200 ft; 43.3 dB at 25000 ft 25000 lbs 109.8 dB @ 200 ft; 53.9 dB at 25000 ft Dep 25000 lbs 109.8 dB @ 200 ft; 53.9 dB at 25000 ft 40000 lbs 113.0 dB @ 200 ft; 63.3 dB at 25000 ft A300B4-200 with CF6-50C2 A310-300 with CF6-80C2A2

12. 12 Flight State Generation Take-off Climb Accelerate Cruise/climb Equations from from SAE AIR 1845 generate aircraft state for different segment types: Aircraft type Operation type Trip length Flight procedures Altitude controls at specified nodes Airport temperature Airport altitude Runway data Flight State Generation Using SAE AIR 1845 Equations Aircraft state on each segment  = sin -1 ( 1.01 { [ N eng T avg / (W/  am ) avg ] – R} ) ambient pressure ratio relative to standard-day sea- level value gross takeoff weight number of engines drag/lift ratio T avg = (1/2) [ (F n /  am ) h2 –(F n /  am ) h1 ] (F n /  am ) h = E + FV c + G a h +G b h 2 + HT am climb angle average corrected net thrust corrected net thrust per engine Level Descend Land Decelerate -------- -------- ambient air temperature altitudeairspeed (calibrated) E, F, G a, Gb, and H are engine-specific parameters dependent on segment type net thrust per engine INITIAL CLIMB

13. 13 Comparison of Baseline and Alternative(s) EACH POPULATION CENTROID HAS TWO DNL EXPOSURE VALUES FOR: (1) BASELINE SCENARIO, (2) ALTERNATIVE SCENARIO N. CRITERIA TO DETERMINE MINIMUM THRESHOLD OF DNL CHANGE (RELATIVE TO BASELINE DNL): Baseline DNLChange in Exposure (Minimum)References < 45 dB 45 - < 50 dB 50 - < 55 dB 55 - < 60 dB 60 - < 65 dB > 65 dB EECP EIS, Air Traffic Noise Screening Procedure, FICON (See S. Fidell, J. Ac.Soc. Am. 114(6), 2003) FAA Order1050.1D and FICON SCENARIOS ARE COMPARED IN TERMS OF POPULATION RECEIVING INCREASES OR DECREASES IN EACH EXPOSURE BAND. -  5 dB  3 dB  1.5 dB

14. 14 Visualization of Scoring Criteria 45 50 450 0 BASELINE DNL (dB) ALTERNATIVE DNL (dB) 5040 55 INCREASE 60 NO CHANGE 65 60 65 DECREASE 40 DECREASENO CHANGE INCREASE NO CHANGE CENTROID Y POPULATION = 46 BASELINE = 62 dB ALTERNATIVE = 47 dB CENTROID Y POPULATION = 46 BASELINE = 62 dB ALTERNATIVE = 47 dB CENTROID X POPULATION = 19 BASELINE = 41 dB ALTERNATIVE = 56 dB CENTROID X POPULATION = 19 BASELINE = 41 dB ALTERNATIVE = 56 dB 3 dB INCREASE DECREASE 1.5 dB

15. 15 45 50 450 0 BASELINE DNL (dB) ALT DNL (dB) 40 3 dB 1.5 dB 0 55 65 60 50556065 TOTAL Above 65 dB DECINC 70 TOTAL ABOVE 65 dB: Baseline = Alternative = YELLOW ORANGE RED PURPLE BLUE GREEN

16. 16 Impact Table, Impact Graph, and Change Map

17. 17 Noise Integrated Routing System (NIRS) Principal capabilities Imports and displays track, event, population, and community data. Enables user to easily define and track large numbers of airspace design elements. Filters data based on user definition of study area and maximum altitude. Enables user to specify the altitude profiles flown, including hold-downs, etc. Applies several layers of data checking and quality control. Provides comparison of noise impacts across alternative airspace designs. Identifies and maps all areas of change. Quantifies mitigation goals and identifies opportunities. Identifies principal causes of change in noise impact. Assembles maps, tables, and graphs for report generation. NIRS performs large-scale modeling and analysis of noise impacts associated with current and planned aircraft routings within a regional study area. It is the FAA’s standard tool for NAR projects. Population density and tracks in vicinity of ORD Noise exposure (DNL)

18. 18 NIRS Screening Tool (NST) Principal capabilities Windows and Linux based application. Enables user to easily point and click to define baseline and alternative routes. Imports SDAT and NSIF tracks for support of route definition. Provides generalized aircraft categories for quick assessments. Enables user to easily point and click to define communities. Imports US Census TIGER data for support of community definition. Displays airports, runways, fixes and NAVAIDs. Provides comparison of noise impacts across alternative airspace designs. Identifies and maps all areas of change. NST is a lightweight noise analysis tool for quickly screening route, fleet or operational changes for potential noise effects. Noise exposure (DNL) Routing scenario at CLE CDA scenario Louisville

19. 19 Sensitivities – Noise (Track Location) Due to divergence as it propagates, the sound energy received varies inversely as the square of the distance between the aircraft and an observer. In dB, with L as the energy level and R as the distance: L2 - L1 = 10 log (R1/ R2) 2 = 20 log (R1/ R2), or approximately -6 dB for a doubling of the distance. In addition to this spreading of the acoustic energy, additional attenuation effects are present, such as energy absorption by the atmosphere and the ground. This means that purely 1/R 2 dependence is not followed for aircraft noise.

20. 20 Sensitivities – Noise (Population Location) In general terms, lateral movement of tracks into areas of lower population density will reduce overall DNL impact measured in terms of the number of people exposed at a given DNL level (e.g., above 65 dB). However, adding flights to a track in such an area eventually increases the impact to a level that negates the reduction obtained by moving the track away from higher population densities. The departures to the southwest from EWR and heading for a departure fix to the northwest leaving the runway along the white arrow might be routed in many ways (yellow arrows). But, as one can see by looking at the underlying population distribution (colored dots), the large number of population locations and their different levels of population make the selection of best routes difficult.

21. 21 Air-Quality Metrics and Impact Calculation

22. 22 Local Air Quality – The Basics  Aircraft emit a complex mixture of air pollutants.  Major pollutants related to local air quality are CO, NO x, SO x, unburnt HCs, and PM (particulate matter).  Emissions of CO 2 and water vapor have atmospheric effects, and contribute to global warming.  Atmospheric chemistry and physics of these emissions are very complex.  Effects of the different pollutants on flora, fauna, and human health are complex and not fully understood.  Quantification of impacts usually done at « inventory » level giving net amounts of pollutants at an airport based on annual landing/takeoff cycles.  Quantification can be carried to « dispersion » level giving spatio-temporal concentrations of pollutants.

23. 23 Regulatory Aspects  Clean Air Act and amendments (1963, 1970, 1977, 1990) have resulted in a broad regulatory framework.  EPA’s National Ambient Air Quality Standards (NAAQS) set primary and secondary standards to protect public health (primary) and public welfare (secondary).  States are required to submit State Implementation Plans (SIPs) for monitoring and controlling each pollutant in the NAAQS to EPA. EPA has approval authority.

24. 24 Regulatory Aspects (Cont’d)  National Environmental Policy Act tasks Federal agencies with preparation of various environmental analyses: -Environmental Assessment (EA) provides analysis and documentation supporting wheter to prepare an Environmental Impact Statement, or a Finding of No Significant Impact. -Environmental Impact Statement (EIS) is a detailed document required of all Federal actions likely to have significant environmental impact. -Finding of No Significant Impact (FONSI) is a document, based on the EA, determining that the Federal action will not have significant environmental impacts. -Record of Decision (ROD) is required to record a Federal agency’s decision on a proposed major Federal action, as well as the alternatives considered. -Conformity Determination states whether and how a Federal action conforms to the SIP with regard to NAAQS.

25. 25 National Ambient Air Quality Standards (NAAQS)  Give concentration limits for given sampling period.  Areas or regions violating these limits are designated to be « non-attainment areas ». PollutantPrimary Stds.Averaging TimesSecondary Stds. Carbon Monoxide9 ppm (10 mg/m 3 )8-hourNone 35 ppm (40 mg/m 3 )1-hourNone Lead1.5 µg/m 3 Quarterly AverageSame as Primary Nitrogen Dioxide0.053 ppm (100 µg/m 3 )Annual (Arithmetic Mean)Same as Primary Particulate Matter (PM 10 )50 µg/m 3 Annual (Arithmetic Mean)Same as Primary 150 ug/m 3 24-hour Particulate Matter (PM 2.5 )15.0 µg/m 3 Annual (Arithmetic Mean)Same as Primary 65 ug/m 3 24-hour Ozone0.08 ppm8-hourSame as Primary Sulfur Oxides0.03 ppmAnnual (Arithmetic Mean)------- 0.14 ppm24-hour------- 3-hour0.5 ppm (1300 ug/m 3 )

26. 26 Inventory Modeling  Low-altitude methodology is well established, and is based on times in operational mode, fuel rates, and emission indices: Pollutant mass per flight = N eng * t mode * fuelflow mode * EI mode Pollutant inventory =  all_flights (pollutant mass per flight)  Determining inventory above 3000 feet uses a more complex technique, and is not yet settled with regard to methodology. - Boeing Method 2 uses fuel flow at altitude and modifies the standard ICAO emission indices approach, climbout, takeoff, taxi/idleNO x, SO x, HC, CO, PM

27. 27 Sensitivities – Emissions (Vertical Profile) There are two aspects of variation with vertical profile that are of interest. First, the net emission amounts vary with the mode of operation and the fuel flow in that mode. Second, the emission indices and fuel-flow rates have altitude dependencies within a given mode. Figures below do not take into account more accurate methods of calculating fuel-flow rates and emission indices at altitude, which we discuss below. Hence these figures should be considered notional at this point, useful only for understanding how such information might be used. More accurate methods are under development: Boeing Method 2, DLR Method, P3T3 Method.

28. 28 Dispersion Modeling  EPA’s AERMOD is primary model for air transport. Model NameTypeApplicability AERMODGaussianGeneral stack and line sources Complex terrain CALINE3GaussianHighway emissions Climatological Dispersion Model (CDM)GaussianGeneral stack sources Gaussian-Plume Multiple Source Air Quality Algorithm (RAM)GaussianGeneral stack sources Industrial Source Complex Model (ISC3)GaussianGeneral stack sources; Complex terrain Urban Airshed Model (UAM)3-D numericalUrban ozone modeling Offshore and Coastal Dispersion Model (OCD)GaussianPollutant transport over water and coastal areas Complexe Terrain Dispersion Model Plus Algorithmes for Unstable Situations (CTDMPLUS) GaussianGeneral stack sources; Complex terrain

29. 29 Dispersion Modeling (Cont’d)  Gaussian approach  y and  z vary with x.

30. 30 Dispersion Modeling  More complex Euler-Lagrangian approaches exist, addressing flow, momentum,... Source: MetPhoMod

31. 31 Design Issues  Engine design cannot be optimized for all of the pollutants, and design tradeoffs form an active area of research and development. NO x CO Combustor Operating Temperature Concentration NO x Air/Fuel Ratio Particulates Production Rate 0

32. 32 Design Issues (Cont’d)  Significant progress has been made in reducing noise.  Main approaches to noise reduction include: -Lower jet velocity (however, this can lead to greater fuel burn) -Lower speed of rotating components, especially fan -Avoid flow distortion into the fan (cannot be avoided on takeoff) -Avoid interference patterns via selection of numbers of rotor and stator blades. - Large axial gap between rotors and stators - Tuned acoustic liners in intake, bypass duct, and nozzle of core

33. 33 Aviation and Climate

34. 34 Combustion Products  Commercial jet fuel is essentially kerosene. Although a mixture of different hydrocarbons, it can be approximated as a paraffin (C n H 2n+2 ), usually C 10 H 22.  Main combustion process: aC n H 2n+2 + bO 2 + 3.76bN 2 cH 2 O + dCO 2 + 3.76bN 2 + heat C 10 H 22 + 15.5O 2 + 3.76(15.5)N 2 11H 2 O + 10CO 2 + 3.76(15.5)N 2 + 10.6 kcal/g (19.08 kBTU/lb)  The above is for complete combustion in the gaseous phase, and the process inside real engines is considerably more complex. Typical emission rates for jet aircraft (grams per kg fuel consumed) at cruise are: CO 2 3200 H 2 O 1300 NO x 9-15 SO x 0.3-0.8 CO 0.2-0.6 H x C y 0-0.1 Particulates 0.01-0.05 Main combustion products Produced at high T and P in combustion chamber; depends on operating conditions Due to incomplete burning of fuel; produced at non-optimal operating conditions during landing, taxi, take-off and climb-out Unburned Due to sulphur impurities in fuel

35. 35 Aviation and Climate – The Basics  Global climate concerns are driven by green-house gas concentrations (CO 2, O 3, CH 4 ) and O 3 depletion. - CO 2 molecules absorb outgoing UV radiation, and lead to warming of the troposphere (i.e., from sea level to about 10km altitude). - O 3 depletion in the stratosphere (10-45km altitude) leads to increased intensity of UV radiation harmful to plant and animal life.  Aviation effects are very complex, and depend on species emitted, altitudes, atmospheric conditions, chemical reactions, etc.  Formation of contrails and contribution to cirrus cloud cover may also be a concern.

36. 36 Aviation and Climate – The Basics (Cont’d)  Overall, climate change is fundamentally related to the global carbon cycle, and to perturbations caused by fossil-fuel consumption.

37. 37 Aviation and Climate – The Basics (Cont’d)  Radiative forcing – Net change in irradiance (downward minus upward) at the tropopause (altitude of 10-15km) measured in W/m 2. Source: IPCC, Aviation and the Global Atmosphere

38. 38 Aviation and Climate – The Basics (Cont’d)  Aviation plays a role in these effects. Source: IPCC, Aviation and the Global Atmosphere

39. 39 Aviation and Climate – The Basics (Cont’d)  There are significant uncertainties in the magnitudes of different aviation effects. Source: IPCC, Aviation and the Global Atmosphere

40. 40 Convergences and Complications Aviation’s climate impact – While aviation’s impact is perhaps 5-10% of the overall transport impact, depending on the measure used, this is a substantial and very visible proportion. The IPCC reports that international transport (aviation and marine) contributed about 0.8 Gt of CO2 to global CO2 emissions in 2004, while road transport contributed 5.4 Gt and electricity plants contributed 10.4 Gt (IPCC-WG3, 2007, Ch.1, p.13). Carbon costs - Cap-and-trade systems for carbon or CO2 will induce greater desire for operational efficiency throughout the system, specifically including airport operations and air-traffic management (Stern, 2006, Chapter 22). Goals likely to be stringent – In the carbon area, goals recently set include California’s goal to reduce CO2 emissions by 80% from 1990 levels by 2050. The UK has set targets of by 20% from 1990 levels by 2050, and by 60% from 2000 levels by 2050 (Stern, 2006, p. 516). Rising fuel costs - Fuel costs are currently approximately 20% of overall aviation operating costs (ICAO, 2005), and likely to rise.

41. 41 Convergences and Complications (Cont’d) Competing technical goals - Improvements in engine fuel efficiency can lead to worsening of NOx emissions, since higher pressure ratios are better for fuel efficiency, but the increased combustion temperature creates more NOx. Fleet technology insertion relatively slow - Noise and safety requirements add complexities that require relatively long times for improvements to enter the operational fleet. Furthermore, aircraft have a useful service life measured in decades, further slowing the insertion of new technology into the fleet. Local and regional priorities may differ - Local ambient air-quality standards and EPA-designated non-attainment areas for different pollutants can lead to different regional priorities for environmental impact. Local noise-impact concerns differ across communities, as well.

42. 42 Metrics – Fuel Efficiency Fuel only – This metric considers only the fuel used, independent of size of aircraft, carrying capacity, or distance traveled. Fuel modulated by flight distance – This metric considers flight distance per unit of fuel used. Fuel modulated by seat distance – This metric considers seat distance flown per unit of fuel used, regardless of whether the seat was occupied. Seat distance is the product of the number of seats times the distance flown by the aircraft. For cargo operations, payload could be converted to a number of seats by dividing by the average weight of a passenger and baggage. Fuel modulated by occupied seat distance – This metric considers seat distance flown per unit of fuel used, only for occupied seats. Occupied eat distance is the product of the number of occupied seats times the distance flown by the aircraft.

43. 43 Metrics – Fuel Efficiency (Cont’d) Fuel Efficiency = F / (C * D) where F is the mass in kg of fuel burned C is the seat capacity of the aircraft in number of seats D is the ground-track distance traveled in km Fuel Burned (F) = t m * R m where: tm is the time in minutes for mode of operation m Rm is the rate of fuel flow in kg/minute for mode of operation m BADA fuel-flow values are expressed in kg/sec for the aircraft during the phases of climb, cruise, and descent at different altitudes. EDMS fuel flow is expressed in kg/sec for each engine of the aircraft during the phases of taxi/idle, takeoff (to 1000 feet AGL), climb (1000 feet AGL to 3000 feet AGL), and approach (3000 feet AGL to touchdown). When we aggregate across flights, this equation becomes: Aggregate Fuel Efficiency =  i F i /  i (C i * D i ) The fuel efficiency for a group of N flights could also be expressed as the average of the individual flights, as follows: Averaged Fuel Efficiency = (1/N)  i [F i / (C i * D i )]

44. 44 Sensitivities – Fuel Efficiency Aircraft and engine type Seating capacity

45. 45 Sensitivities – Fuel Efficiency (Cont’d) Averages by aircraft type for a given day of operation at LGA.

46. 46 Environmental Management and Optimization

47. 47 Environmental Management  As environmental constraints grow, there is likely to be increased pressure to manage environmental effects.  This will be a complex balance of operational factors and environmental impacts in both noise and emissions. Routing A/D Profiles Noise Emissions Fleet Mix Taxi TimesTaxi Queues Scheduling Fuel Efficiency

48. 48 Background and Motivation  Capability to satisfy demand at NGATS projected levels is likely to be limited by noise, air-quality, and other environmental constraints.  Combination of operational and technology enhancements will be required to reduce impact of capacity limitations.  Operational reductions can be sought across a spectrum of interlinked factors (tracks, profiles, aircraft state, taxi behavior, schedule, fleet mix, etc.).  How can we manage these factors to approach an optimum balance among different environmental and operational objectives?

49. 49 EMS Timescale Focus  Focusing on the months to hours timescale.  Seeking synergy in techniques with longer-timescale planning domains. DECADESYEARSMONTHSHOURS NGATS CONCEPT DEVELOPMENT AIRPORTAL & AIRSPACE PLANNING TACTICAL DECISION SUPPORT DESIRABLE SYNERGY IN TECHNIQUES EMS FOCUS

50. 50 EMS Process Overview Source: California EPA  Traditional view is process-oriented, but decision-support technology will be needed. EMS DECISION SUPPORT OR TECHNOLOGY NEEDED

51. 51 Major Factors Contributing to Environmental Impacts  Routing Track location relative to other traffic and population concentration directly affects noise/emission dosage.  Profiles Aircraft altitude, speed, and power state affect both noise and emission dosage.  Schedule Some noise metrics (e.g., DNL) are dependent on time of day.  Fleet composition Airframe/engine combinations have different noise and emissions characteristics, and thus different marginal impacts.  Taxi behavior Taxi time and queuing affect emissions and fuel-usage metrics.

52. 52 EMS Decision Support Schematic Source: Metron Aviation

53. 53 Sample Scenario Benefits Estimation Emissions reduction range = [0%,26%] Noise reduction range = [4%,13%] Slope jump: ~20% emission reduction ~12% noise reduction Source: Metron Aviation

54. 54 Benefits For the entire civil-aviation sector, comprising air transportation, related manufacturing, and related tourism, the 2004 impacts on U.S. economy were estimated to be about $1365B in terms of output, $418B in terms of earnings, and 12.3M in terms of jobs. (1) The 2004 direct impacts of commercial aviation and related industries were estimated to be approximately $247B in terms of output, $72B in terms of earnings, and 1M in terms of jobs. (2) The 2004 indirect expenditures by commercial air travelers were estimated to be approximately $191B in terms of output, $67B in terms of earnings, and over 3M in terms of jobs. (3) Considering both the direct and indirect impacts above, these results suggest, as a rough approximation, that each percentage point of growth is worth, about $4.4B in terms of output, $1.4B in terms of earnings, and about 400K jobs. Recent studies have indicated that environmental constraints may significantly limit growth of this economic sector, which is projecting two- or three-fold growth in demand over the next two decades. This rate of growth is approximately 3-6% per year over 20 years. As an initial rough order-of-magnitude estimate of the benefits of EMS methods, consider the value of different marginal changes in the value of the direct and indirect impacts. If these methods can be applied, in a single year, to enable just 0.1% more growth than would otherwise be attainable given environmental constraints, then the benefits would be on the order of $440M in economic output, $140M in earnings, and about 40,000 jobs. The compound effects of this growth would, of course, be even greater over longer periods. Note that the above analysis does not address benefits associated with reductions in direct operating costs, or benefits associated with reductions in greenhouse-gas emissions.

55. 55 NoiseLocal Air Quality Climate Environmental Management

56. 56 Backup Slides

57. 57 Next Generation Air Transport and the Environment

58. 58 Next Generation Air Transport System (NGATS) and Environment Source: NGATS Concept of Operations (Draft), May 2006

59. 59 NGATS and Environment (Cont’d)  Key development issues: Source: NGATS Concept of Operations (Draft), May 2006 1.How are airspace flexibility needs balanced with environmental and noise-reduction goals? 2.What type of NEPA review will be required to provide information to public impacted by RNP routes that permit dynamic reprogramming of usage in both the en route and arrival/departure airspace? 3.What level of flexibility in airspace structure (e.g., routes and boundaries) is needed to achieve operational goals, including efficiency, capacity, and environmental goals? To what extent can the selection of predetermined structures support operational needs? 4.How can “Super-density Operations in Terminal Airspace” be made compatible with the process for environmental analysis and review of proposed airspace re-design?

60. 60 NGATS and Environment (Cont’d)  Relevant policy issues: Source: NGATS Concept of Operations (Draft), May 2006 1.What policies will be in place to determine what flights are given priority when demand exceeds available capacity of a NAS resource? - For example, is there a definition of “equity” with respect to the distribution of delays? - Market mechanisms? - Is preference given to “early filers” over those not giving advance notice? - Are incentives provided for equipage with certain capabilities beyond what is required for access to the airspace or airport? - Are incentives or preference given based on less environmental impacts? 2.Should financial incentives be used to accelerate the introduction of environmental technology improvements in aircraft?

61. 61 Background Reading  Penner, J., et al, Aviation and the Global Atmosphere, Intergovernmental Panel on Climate Change, 1999.  Seinfeld, J., and Pandis, S., Atmospheric Chemistry and Physics, Wiley, 2006.  Godish, T., Air Quality, CRC, 2004.  Perkins, H., Air Pollution, McGraw-Hill, 1974.  McGraw-Hill Handbook on Acoustics and Noise Control, 1976.  Federal Interagency Committee on Noise (especially 1992 report on airport noise analysis)  Flack, R., Fundamentals of Jet Propulsion with Applications, Cambridge, 2005.  Cumpsty, N., Jet Propulsion, Cambridge, 2003.

62. 62 NAS-wide Environmental Impact Model (NASEIM) Single, integrated pathway for noise, emissions, and fuel-consumption modeling using FAA and Eurocontrol techniques. Capable of addressing entire NAS, or any part of it. Used in JPDO environmental-constraints analysis. Web-services architecture makes large-scale data and computation easily available. Modular design allows for integration with other tools (e.g., SDAT, TARGETS). Phase 3 work for NASA enhances usabilitiy (June06 – Dec07). NASEIM models noise, emissions, and fuel-usage impacts for the entire NAS.

63. 63 45 50 450 0 BASELINE DNL (dB) ALT DNL (dB) 40 NO CHANGE NO CHANGE INCREASE 0 55 65 60 50556065 NO CHANGE DECREASE TOTAL Above 65 dB DECINC (TOTAL = ) 70 TOTAL ABOVE 65 dB: Baseline = Alternative = (TOTAL = ) HORIZONTAL GRAY BOX ENCLOSES TOTAL ABOVE 65 dB FOR ALTERNATIVE PART OF BOX TO LEFT OF NO-CHANGE ZONE ENCLOSES INCREASES ABOVE 65 dB. PART OF BOX TO LEFT OF VERTICAL 65 dB LINE SHOWS “NEWLY IMPACTED ABOVE 65 dB”

64. 64 Annualization Example - ORD Annualization can also be done by assigning all traffic in the average day (or the day/night portions) to each of the runway configurations used throughout the year. Then the annual exposure is obtained by combining the noise exposures due to different configurations according to proportional use throughout the year. A B X W IFR1 Dual 5 IFR2 NO1 (04R/04L) NO2 (22R/22L) NO3 (32R/32L) NO4 (09R) NO5 (14R/14L E-wind) NT1 NT2 NT3 NT4 NT5 18.20 % 12.80 31.20 20.50 8.50 2.00 1.90 0.735 0.98 0.735 1.47 20.00% 20.00 100% Annualized Exposure DAY: NIGHT:

65. 65 Some Underlying Data - 1 CFM56-7B2013,2000000,1000009,5000001,0000000,0000000,274000 CFM56-7B2020,5000000,10000017,4000001,0000000,0000000,761000 CFM56-7B2030,6000000,10000020,5000001,0000000,0000000,913000 CFM56-7B20425,9000003,1000004,3000001,0000000,0000000,100000 ENG_NAME MO DECO_EIHC_EINOX_EISOX_EIPART_EIFUEL_KG/S Different pollutant production rates for engines by mode of operation (one engine from about 470 in EDMS 4.1) (modes: 1=approach; 2=climbout; 3=takeoff; 4=taxi/idle) Different pollutant production rates for APUs (data from EDMS 4.1 apu_ef.dbf; total of about 30 APUs) APU GTCP 331 (143 HP)26,000,5019000,0522501,1557300,1215200,000000 APU GTCP331-200ER (143 HP)26,000,5019000,0522501,1557300,1215200,000000 APU GTCP331-500 (143 HP)26,000,4595100,0486202,7740900,2431200,000000 APU GTCP 660 (300 HP)26,003,0094100,0974101,8543600,3479000,000000 APU TSCP 700 (142 HP)26,000,7833500,0777001,7284300,2100100,000000 APU TSCP700-4B (142 HP)26,000,7833500,0777001,7284300,2100100,000000 APU TYPE T_m inCO_kg/hHC_kg/hNOX_kg/hSOX_kg/hPART_kg/h

66. 66 Some Underlying Data - 2 Different fuel rates by altitude and mode (data from BADA; about 90 aircraft types). B772__ 0 XXX 330.1 131.5 B772__ 5 XXX 327.2 130.3 B772__ 10 XXX 324.4 129.4 B772__ 15 XXX 321.9 32.7 B772__ 20 XXX 319.1 32.5 B772__ 30 93.0 315.0 31.9 B772__ 40 93.1 311.7 31.4 B772__ 60 98.7 303.4 30.3 B772__ 80 98.8 292.3 29.3 B772__ 100 98.9 281.2 28.2 B772__ 120 99.0 274.6 27.1 B772__ 140 99.1 263.5 26.1 B772__ 160 122.5 252.6 25.0 Altitude (FL) Fuel Rate (kg/min) Cruise Climb Descent B772__ 180 122.3 241.7 23.9 B772__ 200 122.0 231.0 22.9 B772__ 220 121.8 220.2 21.8 B772__ 240 121.4 209.6 20.7 B772__ 260 121.1 199.0 19.7 B772__ 280 120.6 188.4 18.6 B772__ 290 120.4 183.2 18.1 B772__ 310 120.0 172.8 17.0 B772__ 330 115.4 161.9 15.9 B772__ 350 110.1 150.9 14.9 B772__ 370 105.8 140.1 13.8 B772__ 390 102.5 129.5 12.7 B772__ 410 100.2 119.0 11.7

67. 67 Sample Scenario: Centennial Airport  Radar data from 1997. (~1300 flight operations)  Population data from 2000 census (~2.8 million persons)  Tracks grouped into 34 distinct flows  20,000 variants of 2,240 backbones were generated by varying the spatial placement  Terrain data was included  Variants are generated so that they all satisfy the operational constraints (e.g. feasible profile)  Noise and emissions dispersion calculated for all baseline tracks and all variants Source: Metron Aviation

68. 68 NGATS and Environment (Cont’d) Source: NGATS Concept of Operations (Draft), May 2006

69. 69  Noise Metrics –Quantify sound exposure at point locations, usually in DNL (dB) –Very sensitive to track location, altitude, aircraft type, state, time of day  Emissions Inventory Metrics –Quantify total amount of pollutants produced in period –Criteria pollutants are CO, HC, NOx, SOx, PM(x) –Not sensitive to lateral track location –Sensitive to altitude, aircraft type, state  Emissions Dispersion Metrics –Quantify concentration in time period –Pollutant concentrations modeled at point locations –National Ambient Air Quality Standards sets threshold concentrations –Sensitive to track location, altitude, aircraft type, state Environmental and Operational Metrics