NASA/CRm2001-211216

Scheduled Civil Aircraft Emission Inventories

for 1999: Database Development and Analysis

Donald J. Sutkus, Jr., Steven L. Baughcum, and Douglas P. DuBois

Boeing Commercial Airplane Group, Seattle, Washington

Prepared under Contract NAS1-20341, Task 19

National Aeronautics and

Space Administration

Glenn Research Center

October 2001

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Available electronically at http://gltrs.grc.nasa.gov/GLTRS
TABLE OF CONTENTS

LIST OF FIGURES V

LIST OF TABLES vi

GLOSSARY

.°,

VIII

EXECUTIVE SUMMARY

1. INTRODUCTION 4

2. DATABASE DEVELOPMENT METHODOLOGY 9

2.1 DATABASE ACQUISITION AND DESCRIPTION ....................................................... 10

2.2 DATA EXTRACT CHALLENGES ........................................................................... 12

2.3 CREATION OF THE EMISSIONS DATABASE: ......................................................... 16

2. 3. 1. Schedu/e Data Trans/ation 16

2.3.2. Airp/ane/Engine Performance Data Substitution 18

2.3.3. Airp/ane Mission PeHormance Ca/cu/ation 21

2. 3. 4. Ca/culation of Globa/ Emissions 22

2.5 METHODOLOGY CHANGES FROM PREVIOUS BOEING INVENTORY

CALCULATIONS .............................................................................................. 25

3. RESULTS AND ANALYSIS - SCHEDULED AIRCRAFT EMISSIONS 29

3.3

3.4

3.5

3.6

4.

3.1 OVERVIEW OF RESULTS ................................................................................... 29

3.2 FLEET MOVEMENT STATISTICS, FUEL USAGE AND EFFECTIVE EMISSION

INDICES ......................................................................................................... 34

SEASONAL VARIABILITY ................................................................................... 41

TREND ANALYSIS ............................................................................................ 43

EFFECTS OF IMPROVED FREIGHTER MODELING .................................................. 47

DATABASE AVAILABILITY .................................................................................. 49

COMPARISON OF 1999 INVENTORY RESULTS WITH DOT FORM 41

DATA 51

5. SUMMARY AND CONCLUSIONS 57

6. REFERENCES 59

NASA/CR--2001-211216 iii
TABLE OF CONTENTS (CONTINUED)

APPENDIX A - SAMPLE AIRCLAIMS FLEET INFORMATION DATA

APPENDIX B- AIRPLANE/ENGINE SUBSTITUTION TABLES FOR 1999

EMISSION INVENTORY CALCULATIONS

APPENDIX C - ALTITUDE DISTRIBUTION OF FUEL BURN AND

EMISSIONS FOR EACH MONTH OF 1999

APPENDIX D- EFFECTIVE GLOBAL EMISSION INDICES FOR 1999

AIRCRAFT

APPENDIX E - DEPARTURE AND DISTANCE SUMMARIES FOR MAY

1999 SCHEDULED AIR TRAFFIC

61

63

81

93

113

NASA/CR--2001-211216 iv
LIST OF FIGURES

Figure 2-1. Schematic of emission inventory calculation. 9

Figure 2-2. "Codeshare" flight duplication. 13

Figure 2-3. "Starburst" flight duplication. 14

Figure 2-4. "Effectivity" flight duplication. 15

Figure 3-1. Global cruise (9-13 km) NOx distribution for the

scheduled aircraft fleet, May 1999. 3O

Figure 3-2. NOx emissions for the scheduled aircraft fleet, May

1999, as a function of altitude and latitude (summed

over longitude). 30

Figure 3-3. Altitude distribution of fractional fuel burned and

fractional global emissions of CO, Hydrocarbons and

NOx for the scheduled aircraft fleet, May 1999. 32

Figure 3-4. Fuel burned and emissions (solid line) as a function of

latitude for scheduled May 1999 air traffic. Dashed

lines show the cumulative fraction of emissions. 33

Figure 3-5. Fuel burned per kilometer traveled (top panel) and

fuel burned per available seat kilometer traveled

(bottom panel) as a function of mission length for the

747-400 and the MD-11ER. 40

Figure 3-6. Global fuel burned in the 0-19 km altitude band for

scheduled air traffic and percent deviation from the

annual average fuel burn for each month of 1999. 42

Figure 3-7. Trends of global scheduled fleet NOx/ASK and fuel

burned/ASK derived from NASA emission inventory

and scenario work. 46

NASA/CRy2001-211216 v
LIST OF TABLES

Table 2-1.

Table 2-2.

Table 2-3.

Table 2-4.

Table 2-5.

Table 2-6.

Table 3-1.

Table 3-2.

Table 3-3.

Table 3-4.

Table 3-5.

Regional changes in May 1999 global scheduled fleet

emission inventory calculation results due to use of a

4-month projection of OAG flight schedule data

instead of a one month projection (positive percent

difference denotes an over-prediction by the 4-month

projection).

Sample OAG to Airclaims airline code translation

table.

Sample OAG to Airclaims airplane translation table.

List of airplane-engine combinations used in airplane

performance calculations for the 1999 emission

inventory.

Increase in ZFW relative to the 70% passenger

loading case for very large freighters.

Recommended emission indices (in units of grams

emission/kilogram fuel).

Fuel burned and emissions for scheduled air traffic for

each month of 1999.

Percentage of global fuel burned, NOx emitted and

distance traveled in selected regions of the world by

the May 1999 scheduled aircraft fleet.

Summary of departure statistics by general aircraft

type for May 1999.

Summary of fuel burned and global effective emission

indices for commercial aircraft types (based on May

1999 scheduled air traffic).

Fractional contribution of each commercial airplane

type to global fuel burned and emissions totals for

May 1999 scheduled traffic. (Summed over all

altitudes, latitudes, and longitudes)

12

17

17

20

22

23

29

31

35

37

38

NASA/CR--200I-211216 vi
Table 3-6. Fuel burned and emissions calculated selfconsistently for the scheduled aircraft fleet for August

1992 and August 1999. 43

Table 3-7. Comparison of August 1999 global fuel burned and

NOx emissions with and without the use of freighter

cargo loading assumptions. 48

Table 4-1. By airline comparison of DOT Form 41 reported

departures, distance and fuel burned with 1999

scheduled inventory global totals for selected

passenger carriers. 53

Table 4-2. By airline comparison of DOT Form 41 reported

departures, distance and fuel burned with 1999

scheduled inventory global totals for selected cargo

carriers. 53

NASA/CRy2001 - 211216 vii
Glossary

AEAP

ANCAT

ASK

BMAP

CAEP

CO

CO2

DOE

DOT

DLR

El(CO)

EI(HC)

EI(NOx)

FRT

GAEC

GE

HC

H20

ICAO

kg

Ib

Load Factor

LTO cycle

M

MTOW

NASA

NOx

OAG

OEW

P&W

PAX

SO2

TOGW

US

3-D

Atmospheric Effects of Aviation Project (NASA)

Abatement of Nuisances Caused by Air Transport

Available seat kilometer (the number of seats an airline

provides times the number of kilometers they are flown)

Boeing Mission Analysis Process

ICAO Committee on Aviation Environmental Protection

Carbon Monoxide

Carbon Dioxide

United States Department of Energy

United States Department of Transportation

Deutsches Zentrum fuer Luft- und Raumfahrt

Emission Index (grams CO/kg fuel burn)

Emission Index (grams hydrocarbon/kg fuel burn)

Emission Index (grams NOx (as NO2)/kg fuel burn)

Freighter designator in schedule data

Global Atmospheric Emissions Code

General Electric

Unburned hydrocarbons

Water

International Civil Aviation Organization

kilogram

pound

Percentage of an airplane's seat capacity occupied by

passengers on a given flight

Landing takeoff cycle

Mach number

Maximum takeoff weight

National Aeronautics and Space Administration

Oxides of nitrogen (NO + NO2) in units of gram

equivalent NO2

Official Airline Guide

Operating Empty Weight

Pratt & Whitney

passengers

Sulfur dioxide

Takeoff gross weight

United States

Three dimensional

NASA/CR--2001-211216 viii
Scheduled Civil Aircraft Emission Inventories for 1999:

Database Development and Analysis

DonaldJ. Sutkus Jr., Steven L. Baughcum and Douglas P. DuBois

Boeing Commercial Airplane Group

Seattle, Washington 98124

Executive Summary

This report describes the development of three-dimensional inventories of

aircraft fuel burned and emissions (NOx, CO, and hydrocarbons) from scheduled

air traffic for each month of 1999. The data are on a 1° latitude x 1° longitude x 1

km altitude grid. The data files were delivered to NASA electronically. These

emission inventories were developed for the NASA Ultra Efficient Engine

Technology (UEET) Program under contract NAS1-20341, Task Assignment 19.

They will be available for use by atmospheric scientists conducting modeling

studies on the atmospheric effects of aviation, including the NASA Global

Modeling Initiative (GMI).

Emissions produced by the world's entire aircraft fleet come from

scheduled, military, charter and general aviation air traffic. In this report, we

present only the results and methodology used for the calculation of emissions

from scheduled air traffic which includes turboprops, passenger jets, and jet

cargo aircraft.

Global fuel use for 1999 by scheduled air traffic was calculated to be

1.28 x 1011kilograms. Global NOx emissions by scheduled air traffic in 1999

were calculated to be 1.69 x 109 kilograms (as NO2). Calculated global

emissions show a seasonal variation, peaking in August with a minimum in

February. Emissions for the month of December 1999 were closest to global

annual average emissions, although emissions for May (the month typically used

as an 'average' month in past NASA inventory studies) were within 1 percent of

the global annual average.

A trend analysis for emissions and fuel burned was performed using the

results of this current work and previously published emission inventories and

scenarios. This analysis showed an increase in the absolute amount of fuel

burned, distance traveled, NOx, and CO emissions produced by the scheduled

fleet between 1992 and 1999 and a decrease in the absolute amount of

hydrocarbon emissions produced. Calculated global fuel use increased by 33%

and NOx emissions increased by 35% between 1992 and 1999. The analysis

NASA/CR--2001-211216 1
also showed that scheduled fleet fuel burned and NOx emissions normalized by

available seat kilometers decreased between 1992 and 2015.

The methodology used to extract and process air traffic data from the

Official Airline Guide was changed from that used to calculate previous

scheduled fleet inventories for 1976, 1984 and 1992. To quantify the effects

of the methodology changes, an emission inventory for August 1992 was

recalculated using the new methodology. Comparisons between the previously

published and new August 1992 inventories show good agreement for global fuel

burned and NOx totals. For CO and hydrocarbons, the global totals increased

by 20 percent and 18 percent respectively with the use of the new methodology.

Much of this difference arises from changes in the selection of combustor types

for certain engines in the fleet. Hydrocarbon and CO emissions levels for many

older technology engines can vary widely depending on the combustor used in

the engine.

To improve the accuracy of global emissions calculations for freighters,

United States Department of Transportation Form T-100 data was used to

determine typical payloads for freighter aircraft. This information was then used

to model freighter aircraft more accurately in the inventory calculations by using

more realistic payloads.

To assess the effect of the different freighter payload assumptions, results

were compared with previous inventory calculations done using 70 percent

passenger payload for all aircraft. This comparison showed that improved

freighter payload assumptions increased total global fuel burned by 0.6 percent

and increased total global NOx by 1.5 percent for August 1999. These increases

are relatively small and will not significantly change trends for fuel use or NOx

created using the published inventories for 1976, 1984, and 1992.

In order to evaluate the 1999 scheduled aircraft fleet global emission

inventory calculations, comparisons were made with aviation fuel use and traffic

data reported on the U.S. Department of Transportation (DOT) Form 41 by US

air carriers. In general, emission inventory calculations of departures and

distance traveled for 1999 compared well (within 5 percent) with the DOT Form

41 data for the ten largest passenger carriers that reported fuel use and traffic

data to the DOT. In contrast, for the four largest cargo carriers reporting to the

DOT, calculated departures and distance traveled were significantly less than

those reported. It appears that the OAG flight schedule data do not contain a

complete listing of cargo flights.

For the passenger carriers in the DOT Form 41 data comparison, the

emission inventory calculations consistently under-predicted fleet fuel burned.

The magnitude of these under-predictions varied depending on the carrier being

NASA/CR---2001-211216 2
considered. For the ten largest air carriers reporting data to the DOT, the total

fuel burn was under-predicted by 21 percent. This result is likely due to the

simplifying assumptions used in the development of the global inventory,

including our inability to consider air traffic control delays/diversions,

weather/wind factors, more realistic routing, less than optimum aircraft/engine

performance and actual aircraft operating weights.

NASA/CR--2001-211216 3

1. Introduction

The NASA Ultra Efficient Engine Technology (UEET) program has been

initiated to promote the development of fuel efficient and low NOx emissions jet

engines for the future and to evaluate the effects of aircraft emissions on the

atmosphere and human health. The work described herein was done in support

of the UEET program Environmental Impact Assessment Element (WBS 1.2)

which includes atmospheric modeling, health risk assessment, and emission

characterization work. The creation of global emission inventories for the

scheduled aircraft fleet as a function of altitude and geographical position

(referred to as "3-D emission scenarios") is an important component of the

atmospheric modeling portion of this element. These scenarios are used as the

input to chemical transport models to evaluate the effect of aircraft emissions:

how long they persist in the atmosphere, how much they perturb the chemistry

or microphysics of the upper troposphere, and how they compare with other

sources of NOx, water, soot, and condensation nuclei in the upper troposphere.

In previous NASA studies funded under the High Speed Research and

Advanced Subsonic Technology programs, we have developed 3-D emission

scenarios for aircraft fleets for 1976, 1984 and 1992 (Baughcum, etaL, 1996a

and 1996b), and have projected 3-D emission scenarios of both subsonic and

supersonic traffic for 2015 (Baughcum, et aL, 1998; Baughcum and Henderson,

1998). ANCAT and DLR have also published historical 3-D emission inventories

and projections for 2015 (Schmitt and Brunner, 1997; Gardner, 1998). The

emission scenario work of NASA, ANCAT and DLR has been compared and

contrasted in the Intergovemmental Pane/on Climate Change Special Report

on Aviation and the Global Atmosphere (Henderson, eta/., 1999).

The NASA-funded work as well as that of ANCAT and DLR has used a

"bottoms-up" approach in which aircraft schedules are obtained or estimated

and the aircraft/engine combinations in these schedules are identified. Detailed

calculations of fuel burned and emissions are then made along each flight path

and the results are distributed over a 3-dimensional global grid space.

Emissions produced by the world's entire aircraft fleet come from

scheduled, military, charter and general aviation air traffic. In this report, we

present the results and methodology used for the calculation of emissions from

scheduled air traffic, including turboprops, passenger jets, and jet cargo aircraft.

In 1992, fuel usage for scheduled air traffic accounted for approximately 68% of

the fuel usage of the entire aircraft fleet. The scheduled air traffic inventories

presented in this report are calculated using the Official Airline Guide (OAG) as

the source of scheduled flight data. The OAG accurately accounts for scheduled

NASA/CR---2001-211216 5
passenger flights in most regions of the world but it is unclear to what extent it

covers cargo flights and flights within China and the former Soviet Union.

This report documents an emission inventory for only the 1999 scheduled

aircraft fleet. In order for a complete emission inventory for the world's entire

1999 aircraft fleet to be created, the 3-D scheduled inventory documented in this

work would need to be combined with 1999 3-D inventories of the military,

charter and general aviation components of the world's fleet. Such inventories

were developed earlier for 1976, 1984, 1992 and 2015 (Landau, eta/.; 1994,

Metwally, 1995; Mortlock and Van Alstyne, 1998). In addition, 3-D inventory

calculations for year 1999 flights within the former Soviet Union and People's

Republic of China not included in the OAG schedule would have to be included if

it is determined that the OAG schedule is incomplete for these regions. As of the

writing of this report, these additional inventories have not yet been developed

for 1999.

To calculate scheduled aircraft fleet inventories, flight schedule data

(number of departures for each city pair along with airplane and engine type) are

combined with performance and emissions data to calculate fuel burned, oxides

of nitrogen (NOx), carbon monoxide (CO), and total hydrocarbons (HC) on a 1°

longitude x 1 ° latitude x 1 kilometer altitude grid. The results for all the different

routes and airplane/engine combinations are then summed to produce the total

inventory. The details of this process are described in Section 2 of this report.

Results of the 1999 scheduled aircraft fleet emission inventory

calculations are analyzed and discussed in Section 3 of this report. The

methodology used to create this inventory was changed in a number of ways

from that which was used to calculate previously published NASA scheduled

aircraft emission inventories. In order to assess the effects on inventory results

of changes made to the calculation methodology, an emission inventory for

August 1992 was calculated using the same methodology used to calculate the

1999 scheduled inventory. The results of this calculation were then compared

to results of the previously published NASA August 1992 inventory calculations

(Baughcum, eta/., 1996a). This comparison is documented in Section 2.5 of

this report. The calculation of the August 1992 inventory using the current

methodology is also utilized in Section 3.4 of this report to develop a selfconsistent trend analysis of fuel use and emissions.

In the current work, improved modeling of freighter aircraft performance

was utilized to improve the overall accuracy of global emissions calculations.

A discussion of these improvements is presented in Section 2.3.3 and results of

their implementation are presented in Section 3.5.

NASA/CR---2001-211216 6
The work described in this report was conducted under NASA Contract

NAS1-20341, Task 19. The NASA Glenn Research Center Task Manager was

Chowen C. Wey.

The principal investigator was Steven L. Baughcum. Donald J. Sutkus

extracted aircraft departure data from the Official Airline Guide and assigned

engines to aircraft types listed in the schedule using the Boeing proprietary

computer code "The Emissions Desktop Flight Schedule Creation Module"

(TED/FSCM). Donald J. Sutkus also calculated the 3-dimensional aircraft

emission inventories using the Boeing proprietary Global Aircraft Emissions

Code (GAEC). Douglas P. DuBois provided guidance on the selection of

appropriate performance aircraft and emissions engines characteristics to use

when modeling aircraft in the inventories and Steven J. Moskalik and Daniel

Wajerski provided data to update the aircraft performance database used in the

inventory calculations. The TED/FSCM code used to process flight schedule

data was written by David F. Tankersley and the GAEC code used to calculate

the aircraft emission inventories was written by Peter S. Hertel. The analysis of

the results was completed by Steven L. Baughcum, Donald J. Sutkus and

Douglas P. DuBois.

NASA/CR--2001-211216 7

2. Database Development Methodology

The calculation of emission inventories has been described previously

(Baughcum, etaL, 1994; Baughcum, etaL, 1996)and will be briefly summarized

here. The overall process is shown schematically in Figure 2-1.

Global Emissions Database Calculation Schematic

OAG Schedule

Database

Airline Fleet

Database

I I

T

Preliminary

Schedule

Database

I Final DatabaseSchedule

Global Atmospheric

Emissions Code

Global Emissions

Database

Airplane/Engine

Substitution

Airplane Mission

Performance Files

Airport Coordinate

Database

Engine Emissions

Files

Figure 2-1. Schematic of emission inventory calculation.

NASAJCR--2001-211216 9
2. 1 Database Acquisition and Description

The projected flight schedule data used to create the twelve month 1999

global emission inventory for the scheduled aircraft fleet were purchased by The

Boeing Company from Official Airline Guide (OAG) (Oakbrook, IL) for four

months (January, April, July and October). OAG data purchased in January

include schedule forecasts for February, March, and April. The OAG schedule

data contain listings of every scheduled jet and turboprop flight by city-pair and

airline, and include departure and arrival times, airplane code, and trip frequency

projected for several months into the future. This data are processed to create

standard flight schedule databases that are used in a variety of airline and

airplane studies within The Boeing Company. OAG flights for the 16 ththrough

the 22 r_ of each month were used to represent the entire month in this study.

Fuel burned and emissions calculated in this study for this seven day period

were divided by seven and multiplied by the number of days in the month to

obtain monthly totals.

The coverage of the OAG database depends on schedule data submitted

by individual airlines. While it is quite accurate overall, changes in airline

planned operations during any month or operations not reported by the airline as

part of their schedule are not included. The 1999 OAG did not include charter

flights, military flights, general aviation flights and full coverage of freighter flights.

In addition, Boeing analysis shows that the 1999 OAG under predicted

scheduled air traffic by approximately 25 percent for China and approximately

30 percent for the former Soviet Union (on an available seat kilometer basis).

The majority of the under prediction in China and the Soviet Union is for smaller

jet aircraft.

The emission inventory calculations reported previously for the 1992

scheduled fleet (Baughcum, eta/., 1996a) used published schedule data

obtained monthly directly from OAG. For the 1999 scheduled fleet inventory

calculations, however, the OAG database normally used by Boeing, which is

updated quarterly, was utilized. This means that projections of flight schedule

data up to three months into the future were utilized in creating the 1999

scheduled fleet inventory.

In order to evaluate the effect of using schedule data projected for

multiple months into the future, scheduled emission inventories for May 1999

were created using both one-month and four-month (from the previous quarter's

OAG) projections. The 4-month projection was a longer-range forecast than

was actually used in developing the 1999 monthly inventories.

NASA/CR--2001-211216 10
Table 2-1 compares the fuel burned, flight distance, and emissions for

selected geographical regions for the one month and four month projections.

Globally, fuel burned was under predicted by about 1% and distance by 1.7%

by the 4-month projection. NOx, CO, and hydrocarbon emissions were also

under predicted globally by the four month projection by approximately 1%.

Discrepancies between results of the two projection methods are slightly greater

in the Southern Hemisphere than those in the Northern Hemisphere. In the

Southern Hemisphere, air traffic appears to have been over predicted by the

4-month projection while air traffic in the Northern Hemisphere was under

predicted slightly by the four month projection.

The agreement between the one month and four month projections is

within 1-3% for the US, North America, North Atlantic, and North Pacific for fuel

burned, distance and emissions, with traffic (flight distance) increasing faster

than projected by the 4-month projection. Air traffic in Europe also grew faster

than expected from the 4-month projection but the under-prediction was

slightly larger (4.5%) than the regions mentioned above. The most dramatic

discrepancy is for China where the 4-month projection under-predicted the fuel

use by 6% and the flight distance by 10%. The effect on global emissions of this

discrepancy is relatively minor though considering that China is responsible for

only 4% on global fuel burned (see Table 3-2).

When the one-month and 4-month projections are compared on an

airplane by airplane basis, some differences are clearly evident. In general,

these manifest themselves as under prediction of fuel use by airplanes which

were currently in production (e.g., Boeing 737, Boeing 777, Boeing 757, Airbus

A310, Airbus A319, and McDonnell Douglas MD-90), and over prediction of older

aircraft (e.g., McDonnell Douglas DC-10, McDonnell Douglas DC-8, Lockheed

L-1011 ). These effects are probably due to retirements, changes in utilization,

and introduction of new airplanes.

Overall, from the perspective of using the aircraft emission inventories

in global atmospheric modeling assessments, the errors associated with using

projections based on quarterly data seem small and acceptable.

An airport listing is needed to calculate global emissions and fuel burn for

the scheduled fleet using the OAG schedule. For each three-letter airport code

listed in the OAG schedule, the airport listing gives the city name and position

(latitude, longitude, and altitude) of the airport. Three-letter airport codes that

have been 'retired' either because the airport they used to represent no longer

exists or because a different code has been assigned to that airport may be reused by the OAG. For this reason, an airport listing corresponding to the specific

month and year for which the inventory calculation is being done must be used

when making inventory calculations.

NASA/CR--2001-211216 11
Table 2-1. Regional changes in May 1999 global scheduled fleet emission

inventory calculation results due to use of a 4-month projection

of OAG flight schedule data instead of a one month projection

(positive percent difference denotes an over-prediction by the

4-month projection).

Northern Southern

Global Hemisphere Hemisphere

Fuel burned -0.9% -1.2% 2.8%

NOx -1.0% -1.4% 3.1%

CO -1.1% -1.5% 3.5%

Hydrocarbons -0.6% -1.1% 4.4%

Distance -1.7% -2.0% 1.8%

North North North Far

US Europe America Atlantic Pacific China East

Fuel burned -1.1% -2.8% -1.2% 0.3% -1.5% -6.3% -1.1%

NOx -1.9% -2.2% -1.8% 0.3% -1.5% -5.2% -1.7%

CO -0.4% -2.6% -0.5% -0.3% -1.1% -8.5% 0.5%

Hydrocarbons -0.2% -3.3% -0.4% -2.8% -0.4% -2.6% 6.1%

Distance -0.9% -4.5% -1.0% 1.1% -1.8% -10.0% -2.6%

2.2 Data Extract Challenges

The OAG database is designed for the purpose of travel itinerary planning

by airline passengers and travel agents. As a result, certain duplicate listings of

the same actual flight segment may occur in the schedule data and legs of trips

using transportation modes other than air travel may also be listed. While nonaircraft trip legs are tagged in the database and easily filtered, duplicate listings

are not noted explicitly in the database. Logic must be built into an extract code

to eliminate these duplications as much as possible.

The logic used to eliminate duplicate flight listings in this study differed

from that used in past NASA scheduled inventory studies (Baughcum et al.,

1996a and 1996b). The new approach is much more automated, requires less

expert judgment by the analyst, and is very reproducible. In order to determine

the effect of these differences, a schedule for August 1992 was extracted using

NASA/CR---2001-211216 12
the new duplicate removal scheme and compared to the August 1992 schedule

used to generate the previously published NASA 1992 scheduled inventory.

Differences between the two schedules were minimal and judged to be

insignificant.

The flight duplications which must be eliminated fall into three main

categories, which we term "Codeshare Duplication", "Starburst Duplication"

and "Effectivity Duplication". A description of each of these three categories

is given below.

ABC Airlines

Flight 120 O . Q Detroit - Amsterdam

_Daily Service) DTW _ AMS

/

The same flight segment

(Detroit- AmsterdamJ

is listed separately under different flight

numbers/'or both c(xle-sharing airlines

XYZ Airlines

Flight 202 Q O Detroit - Amsterdam

_DaJly Service_ DTW AMS

Figure 2-2. "Codeshare" flight duplication.

"Codeshare Duplication"

This form of schedule duplication occurs when both airlines involved in

a cooperative flight sharing arrangement (codesharing) will list the same flight

segment under their own airline code and flight number. This results in the flight

being listed twice in the OAG schedule, once under each airline's name. For

instance, the same flight from Detroit to Amsterdam may be listed under both

ABC Airlines and XYZ Airlines. Codeshare duplications are removed by

checking for flights that are listed under two different airlines, but with the same

airport-pair, time of day departure and arrival, same day and same equipment

(See Figure 2-2).

A provision to retain certain known "head to head" competition flights was

made in the codeshare duplication removal logic. "Head to head" flights are

those flights where two airlines have directly competing flights between the same

NASA/CR--2001-211216 13
airport-pair with the same departure and arrival times on the same day with the

same equipment.

"Starburst Duplication"

This form of duplication arises from the practice of airlines listing under

separate flight numbers one-stop or multi-stop itineraries that contain the same

flight segment. As a simple example of this practice, an airline listing a one-stop

flight from Cleveland to London through New York and another one-stop flight

from Washington to London through New York will combine the passengers from

both flight numbers on the same New York - London flight segment. The

published schedule, however, would lead one to believe that there are two

separate flights from New York to London. This duplication is removed by

checking flight itineraries for segments listed under the same airline, airport-pair,

time of day departure and arrival, same day and equipment. (See Figure 2-3)

JFK

IAD

New York - London

segment of both flight itineraries

camed on the same

actual flight segment

ABC Airlines

Flight 21

Cleveland - London I 1-stop)

LHR (Daily. Setwice }

ABC Airlines

Flight 33

Washington - London ( 1-stop)

LHR (Daily Service)

Figure 2-3. "Starburst" flight duplication.

NASA/CR--2001-211216 14
ABC Airlines

Flight 10

Chicago - l.os Angeles

(Daily Servicc)

©

The same flight segment may bc listed twice

in the same xveek if flight numbers

are changed due to minor schedule changes

made to accomodate holiday periods, daylight time. etc.

LAX

ABC Airlines

Flight 11 Q _0 Chicago - Los Angeles

Daily Service) ORD LAX

Figure 2-4. "Effectivity" flight duplication.

"Effectivity Duplication"

Although the OAG schedule data are supplied as representing the airline

schedules for a certain month, data within the schedules show the dates at

which flights cease operation or begin operation within the month. The flight

data show which days of the week the flight operates. If every flight that

operates in a given week is counted, then the same flight segment may be

counted twice as airlines change schedules (and flight numbers) within the week

to account for holidays, daylight time, change of airplane type, etc. This

duplication can be removed by choosing a single date for flight effectivity, rather

than a whole week. All flights effective on the 16th day of the month are

included in the analyses presented here. (See Figure 2-4)

Once the logic to remove the types of duplicate flights noted above was in

place and tested, a complete set of schedules was extracted for each month of

1999 and August of 1992.

NASA/CR--2001-211216 15
2.3 Creation of the Emissions Database:

2.3.1. Schedule Data Translation

Each flight listing in the monthly airline schedules extracted from the OAG

database gives the airline, the airplane type, the origin airport, the destination

airport and the number of times the flight is scheduled to fly between the

specified airport pair in a one week period. The following is an example of a

typical OAG flight database listing:

Airline Airplane _ Destination Weekly Freq.

JL 74F ANC ATL 3

In order to calculate performance and emissions for a particular flight,

the specific type of engine installed on the aircraft must be known. The OAG

database flight listings do not contain information about engines installed on an

aircraft used for a particular flight. In order to assign engines to flights listed in

the OAG database, a fleet information database purchased from the Airclaims

Company was used. This database provides a comprehensive listing of the

aircraft owned by each of the world's airlines and the engines installed on them.

This database differs from the Boeing internal fleet information database that

was used to produce previous NASA emission inventories. The database used

previously is now out of date and is no longer maintained by Boeing.

A Boeing proprietary computer code was used to automate the process

of assigning engines to flights listed in the OAG database using airline fleet

information contained in the Airclaims database. Engines were assigned to

flights listed in the OAG database using a "majority rules" criteria where the most

prevalent engine used in the given airline's fleet on the given airplane type was

assigned to the flight.

To illustrate how the Airclaims Database was used to assign engines to

flights listed in the OAG schedule database, we will build an example using the

sample OAG database flight listed above.

OAG airplane and airline codes are different than Airclaims airplane and

airline codes and so airplane and airline code translation tables were necessary

to link the two databases. For illustration purposes, simplified airplane and

airline translation tables relevant to the current example are shown in Tables 2-2

and 2-3.

NASA/CR--2001-211216 16
Table 2-2. Sample OAG to Airclaims airline code translation table.

OAG Airline Code Airclaims Airline

Code

JL JAL

Table 2-3. Sample OAG to Airclaims airplane translation table.

OAG Specific Airclaims Aircraft Airclaims Aircraft

Aircraft Code Type Variant

Airclaims

Aircraft Usage

74F 747 200F (SCD) (P&W)

74F 747 200F (P&W)

74F 747 200SF (P&W)

All Freight-Cargo

All Freight-Cargo

All Freight-Cargo

For the current example, using an airline code translation table (like that in

Table 2-2), the OAG airline code "JL" would be translated to the Airclaims airline

code "JAL". Using the airplane code translation table (like that in Table 2-3), the

OAG airplane code "74F" would be translated to the following three possible

Airclaims aircraft type/aircraft variant/aircraft usage names: "747/200F (SCD)

(P&W)/AII Freight-Cargo", "747/200F (P&W)/AII Freight-Cargo" and "747/200SF

(P&W)/AII Freight-Cargo".

Appendix A contains a sample listing from the Airclaims database for the

Japan Airlines fleet as it existed on May 16 th 1999. Using the "translated"

Airclaims airline code and aircraft type/aircraft variant/aircraft usage names along

with this Airclaims database sample listing, we find that the 747-200F (SCD)

(P&W)/JT9D-7Q aircraft/engine combination is the one that has the largest

representation in the Japan Airlines fleet of all combinations corresponding to the

OAG schedule's 74F code. Therefore, by use of the "majority rules" criterion, the

747-200F (SCD) (P&W)/JT9D-7Q aircraft/engine combination would be assigned

to the sample OAG flight. The "(SCD)" and "(P&W)" would then be stripped from

the Airclaims aircraft variant name because they contain no useful information for

the inventory calculation process.

NASA/CR--2001-211216 17
With the above process being completed, the OAG listed flight with the

new engine assigned using the Airclaims database would be as follows:

Airline Airplane Engine _ Destination Weekly Freq.

JL 747-200F JT9D-7Q ANC ATL 3

Once aircraft performance data and engine emissions data are assigned

to the above flight, the emissions for the flight can be calculated.

The make-up of the world's airline fleet is always changing. For this

study, a "snapshot" of the Airclaims database as it existed on the 16 th of each

month was used when performing the schedule data translation. The 16 t" of the

month was chosen in order to coincide with the effectivity date of the OAG

schedule data.

2.3.2. Airplane/Engine Performance Data Substitution

In some cases, it was necessary to substitute one type of aircraft/engine

combination for another in the translated schedule created using the process

described in Section 2.3.1 above. While Boeing has performance information

needed to calculate fuel burned for a large number of turbojet-powered airplane

types, including all Boeing models and many non-Boeing models, we do not

have such information for all airplane types in airline service. For some of these

airplane types, performance data for a similar airplane were used to approximate

fuel burned. The airplane type in the following flight is an example:

Airline Airplane Engine _ Destination Weekly Freq.

IT Mercure JT8D-9 PAR LYS 21

Boeing does not have enough detailed information on the Dassault

Mercure to calculate fuel burned or emissions on this flight. The Mercure is a

twin-engined aircraft of similar size to the 737-200, and is powered by the same

engines as some of the 737-200 models. The data for this flight can therefore be

revised to:

Airline Airplane Engine _ Destination Weekly Freq.

IT 737-200 JT8D-9 PAR LYS 21

For the RJ-85, RJ-100 and Fokker 70 aircraft types, no aircraft were

present in the Boeing performance database that had performance

characteristics similar enough to make a reasonable direct substitution. For

NASA/CR---2001-211216 18
these aircraft types, the performance characteristics of larger aircraft of the same

general type were scaled to provide a reasonable performance estimate.

For emission calculation purposes, all of the myriad turboprop models

that existed in the 1999 OAG database were grouped into three categories,

small, medium and large. The "small" category includes airplanes such as the

DeHaviland Twin Otter, the "medium" category includes airplanes such as the

DeHaviland Dash-8, and the "large" category includes airplanes such as the

Fokker F-27 and F-50. In addition, performance of all of the various types of

regional jets was modeled using a single general regional jet performance

model.

Appendix B contains a listing of all the airplane types appearing in the

processed 1999 OAG data and the performance airplanes used to model

each type in the emissions calculations. For 1999, the number of different

airplane/engine combinations listed in the flight schedule data files varied

between months from 369 to 387. These airplane/engine combinations were

modeled using 89 airplane/engine combinations for which detailed performance

and emissions data were available. A list of the 89 performance airplanes used

to model the 1999 fleet is shown in Table 2-4.

The number of different airplane/engine combinations listed in the 1999

flight schedule data is considerably higher than the 228-235 different

airplane/engine combinations appearing in the flight schedule data for the 1992

NASA inventory. This is partly due to the introduction of new airplane types into

the fleet since 1992 and partly because the new process used to create the flight

schedule data for the 1999 inventory extracts airplane types at a more detailed

level.

NASA/CR--2001-211216 19
ooo ooooooooooooooo_--oo __ ooo ooooooooooooooo__

|

000 000

00000000000000

00000000000000

NASA/CR--2001-211216 20
2.3.3. Airplane Mission Performance Calculation

Boeing proprietary performance data files for the airplane/engine

combinations shown in Table 2-4 and were used to model all of the

airplane/engine combinations listed in the OAG schedule. These data files

provide tables of time, fuel burned and distance flown as a function of airplane

gross weight and altitude for climbout, climb, and descent conditions. They also

provide tables of fuel mileage (nautical miles per pound of fuel burned) as a

function of gross weight, cruise Mach number and altitude for cruise conditions

and tables of long range cruise Mach number vs. gross weight and altitude.

Constant fuel burn rates for taxi-in, taxi-out and approach based on typical

mission allowances are also included in these data files. These performance

data files were generated using the proprietary Boeing Mission Analysis Program

(BMAP), and each file covered the whole operating envelope of the airplane.

Simple interpolation routines were used to obtain engine fuel flow for a given

flight condition.

Airplane performance calculations were done assuming 70% passenger

load factors for all passenger and 'combi' airplanes (airplanes that can be used

to carry either passengers or cargo).

Typical payloads for freighter airplanes were determined using cargo

loading data reported on the United States Department of Transportation (DOT)

Form T-100. DOT Form T-100 data for U.S. domestic flights and flights to and

from the U.S. were combined and used to determine the average payload carried

by each general freighter airplane type existing in the 1999 OAG flight schedule.

For each general freighter type, the average payload carried was added to a

typical operating empty weight (OEW) for that airplane type to obtain an

'average' zero fuel weight (ZFW). If the 'average' ZFW for a given general

freighter type matched the passenger version's ZFW reasonably well, then

performance data for the passenger version loaded at 70% passenger load were

used to model it. If the 'average' ZFW for a given general freighter type did not

match well with the passenger version's ZFW, then a special performance file for

that freighter type was created. This performance file used passenger version

operating empty weights (OEW) and an estimated average freighter payload.

Of the 16 general freighter airplane types that existed in the 1999 OAG

flight schedule, only the very large freighters (747, Antonov An-124, DC-10,

L-1011 and MD-11 ) had 'average' ZFWs that differed enough from the

passenger version ZFW to warrant their being modeled with typical freighter

payloads. All other freighter types were modeled as passenger airplanes with

70% passenger load.

NASA/CR--2001-211216 21
Table 2-5 shows the increase in ZFW relative to the 70% passenger

loading ZFW for the specific very large freighter airplane types that were

modeled using estimated typical freighter payloads.

Table 2-5. Increase in ZFW relative to the 70% passenger loading case for

very large freighters.

Specific Freighter Airplane

747-100F_FRT_JT9D-7A

747-200C F FRT_CF6-5OE2

747-200F_FRT_CF6-50E2

747-200F_FRT_JT9D-7F

747-200F_FRT_JT9D-7J

747-200F_FRT_JT9D-7Q

747-200F_FRT_JT9D-7R4G2

747-200F_FRT_RB211-524D4

747-200SF_FRT_CF6-50E2

747-200SF_FRT_JT9 D-7J

747-200SF_FRT_JT9D-7Q

747-200SF_FRT_JT9D-7R4G2

747-200S F_FRT_R B211-524D4

747-400F_FRT_C F6-80C2B1 F

747-400F_FRT_PW4000-4056

747-400F_FRT_R B211-524H2

An-124-*_FRT_D-18-T

DC-10-10F_FRT_CF6-6D

DC-10-30F_FRT_CF6-50C2

DC-IO-3OF_FRT_CF6-5OC2B

L-1011-200_FRT_RB211-524B

L-1011-200_FRT_R B211-524B4

MD-11-Freighter_FRT_CF6-8OC2D1 F

MD-11- Freighter_F RT_PW4000-4460

Freighter Loading ZFW Percent

Increase Over PAX Loading ZFW

12.5%

11.4%

11.4%

19.4%

19.4%

19.4%

19.4%

14.6%

11.4%

19.4%

19.4%

19.4%

14.6%

10.9%

15.6%

10.2%

10.9%

5.7%

17.8%

17.8%

11.5%

11.5%

16.3%

13.5%

2.3.4. Calculation of Global Emissions

The primary emissions produced by the combustion of jet fuel are water

vapor (H20) and carbon dioxide (C02). The emission levels of H20 and C02 are

determined by the fuel consumption and the fraction of hydrogen and carbon

contained in the fuel. Results from a Boeing study of jet fuel properties

measured from samples taken from airports around the world have yielded an

average hydrogen content of 13.8% (Hadaller and Momenthy, 1989). Emissions

of sulfur dioxide (S02) from aircraft engines are determined by the levels of sulfur

NASA/CR--2001-211216 22
compounds in the jet fuel. Although jet fuel specifications require sulfur levels

below 0.3%, they are typically much lower than this in the fuel supply utilized by

the world's aircraft fleet. The Boeing measurements obtained an average sulfur

content of 0.042% with 90% of the samples below 0.1% (Hadaller and

Momenthy, 1989). These measurements are in the range of values reported

in more recent fuel surveys (Hadaller, et aL, 2000). Future sulfur levels are

projected to drop to about 0.02% (Hadaller and Momenthy, 1993).

Aircraft engine emissions are characterized in terms of an emission index,

which has units of grams of emission per kilogram of fuel burned. Current and

projected emission indices are summarized in Table 2-6, based on the analyses

of Hadaller and Momenthy for commercial Jet A fuel.

Table 2-6. Recommended emission indices (in units of grams

emission/kilogram fuel).

Emission Emission Index

Carbon Dioxide (CO2)

Water (H20)

Sulfur oxides (as SO2)

3155

1237

0.8

Emissions of nitrogen oxides (NOx), carbon monoxide (CO) and hydrocarbons

from an aircraft engine vary in quantity according to the combustor conditions.

Nitrogen oxides are produced in the high temperature regions of the combustor

primarily through the oxidation of atmospheric nitrogen. Thus, the NOx produced

by an aircraft engine is sensitive to combustor pressure, temperature, flow rate,

and geometry. The NOx emission index varies with the power setting of the

engine, being highest at high thrust conditions. By contrast, carbon monoxide

and hydrocarbon emission indices are highest at low power settings where

combustor temperatures and pressures are low and combustion is less efficient.

Nitrogen oxides consist of both nitric oxide (NO) and nitrogen dioxide

(NO2). For NOx, the emission index [EI(NOx)] is given as gram equivalent NO2

to avoid ambiguity. Although hydrocarbon measurements of aircraft emissions

by species have been made (Spicer eta/., 1992), only total hydrocarbon

emissions are considered in this work.

For the majority of the engines considered in this study, emissions data

from engine certification measurements (ICAO, 2000) were used to model

emissions characteristics. In these measurements, emissions of nitrogen oxides

NASA/CR--200 l-211216 23
(NOx), carbon monoxide (CO) and total hydrocarbons (HC) are measured

at standard day sea level conditions at four power settings [7% (idle), 30%

(approach), 85% (climbout) and 100% (takeoff)]. If the ICAO database did

not contain a particular engine, the data for that engine were obtained from

the engine manufacturer. This was done for the three sizes of turboprops

considered. If a source could not be found (e.g., JT3C and JT4A), engines

with a similar core were used with an adjustment for different fuel flow rates.

In the global emissions calculations, each OAG airplane/engine

combination is matched to both a performance engine and an emissions engine

(see Appendix B for the matchup table). Fuel flow is calculated using the

performance data. Then the emissions are calculated using the fuel flow based

technique discussed later in this section.

In most cases, the emissions engine used to model an airplane was the

same as that used to calculate the performance. In some cases, performance

data for the airplane model identified in the processed OAG flight schedule were

available but the engine assumed in the performance data was different than

the engine identified in the schedule. In the majority of these cases, the basic

engine type is matched but not the specific maximum take-off thrust rating (a

737-700/CFM56-7B20 airplane/engine combination listed in the OAG schedule

might be modeled using 737-700/CFM56-7B18 performance data).

If the engine identified in the processed OAG schedule for a particular

airplane was similar to the engine assumed in the performance data used to

model the airplane, the emissions engine was selected to match the OAG

engine. If the engine identified in the processed OAG schedule was significantly

different from the engine assumed in the performance data, the emissions

engine was selected to match the performance engine.

Boeing has developed an empirical method that allows the calculation of

emissions for a wide variety of airplanes and a large number of missions. This

method was described in detail previously (Baughcum, et al., 1996a, Appendix

D) and is referred to as the Boeing Fuel Flow Method #2. In this method,

emission indices measured during sea level static engine certification tests

are correlated with engine fuel flow and then scaled for ambient temperature,

pressure, flight Mach number and humidity to determine emissions at flight

conditions.

All global emissions calculations were done using the GAEC (Global

Atmospheric Emissions Code) as described previously (Baughcum, et aL, 1994;

Baughcum, et al., 1996a). The GAEC graphical user interface was used to

associate airplane/engine combinations listed in the OAG airplane schedule with

the performance and emissions data that were used to model them in the

NASA/CR--2001-211216 24
inventory calculation. Once these associations were made, the GAEC was used

to calculate a global emission inventory using OAG schedule data, performance

data, emissions data and airport location data.

For purposes of the emissions calculations, the Earth's atmosphere was

divided into a grid of three-dimensional cells with dimensions of 1 degree of

latitude by 1 degree of longitude by 1 kilometer in altitude, up to 22 kilometers.

2.5 Methodology Changes from Previous Boeing Inventory Calculations

The methodology used to create the 1999 scheduled aircraft fleet global

emission inventory documented in this report is slightly different from the

methodology used to calculate the NASA full year 1992 scheduled aircraft fleet

emission inventory (Baughcum, eta/., 1996a). Differences between the two

methodologies are as follows:

, A new procedure was used to extract flight schedules from OAG data for

creating the 1999 inventory. The new procedure uses the same basic

OAG flight schedule data for input as the previously used procedure and

utilizes similar algorithms to filter double counted flights from the data but

is much more automated, requires less expert judgment by the analyst,

and is more reproducible. The new procedure uses a different fleet

information database to assign engines to a specific OAG airplane type.

The new procedure utilizes the commercially available "Airclaims"

database for fleet information (See Appendix A for a sample of Airclaims

fleet information data) instead of the Boeing proprietary fleet information

database called "Jet Track" which was utilized by the previously used

procedure. The "Jet Track" database is no longer in use by the Boeing

company.

, OAG schedules forecasted up to three months into the future were used

for the current work while published schedules for each month of the year

were used to create the 1992 scheduled aircraft fleet emission inventory

(see Section 2.1).

.

In the current work, some specific airplane/engine types were modeled

using different emissions and/or performance data than those used in the

1992 full year scheduled aircraft fleet emission inventory calculations. As

noted earlier, the 1999 study uses a larger set of airplane performance

and engine data.

NASA/CR--2001-211216 25
. As discussed in Section 2.3.3 of this report, some freighter airplanes were

modeled differently in the current work than in previous NASA scheduled

inventory calculations by using a more realistic payload.

To quantify the effects of the above methodology changes, the NASA

emission inventory for August 1992 scheduled aircraft was recalculated using

the same methodology that was used to create the 1999 scheduled aircraft

inventory. Global totals of fuel burned, distance traveled and NOx emissions for

the recalculated August 1992 inventory compared well with the global totals for

August 1992 reported previously (Baughcum, eta/., 1996a). Totals by general

aircraft classes (737, A320, etc.) were also compared between the original and

recalculated August 1992 inventories.

A comparison of the recalculated August 1992 inventory and the

previously published August 1992 inventory shows that global totals for distance

are in excellent agreement, differing by only 0.1%. Distance totals for general

aircraft classes also compared well between the previous and recalculated

inventories, they differed from one another by no more than 1.8%. The

agreement in distance totals indicates that the new procedure used to extract

flight schedules from OAG data gives results that are very similar to the

previously used procedure.

Comparisons between the new and old calculations for global totals of

NOx, CO and hydrocarbon emissions and fuel burned show differences of -0.3%,

19.7%, 18.2% and 0.0% respectively (a positive percent difference in these and

the comparisons that follow indicates that values for the recalculated inventory

are greater than the previously published inventory). Totals of NOx, CO and

hydrocarbon emissions for some general aircraft classes differed between the

two inventory calculations significantly more than the global totals did.

The differences in NOx, CO and hydrocarbon emissions between the

recalculated and the previously calculated August 1992 inventories are due to

differences in the emissions characteristics selected to model specific engines

in the two inventory calculations.

Some engine types have had more than one combustor type implemented

during their production run. For some engines used on a significant number of

flights flown by the 1992 scheduled aircraft fleet, NOx, CO and hydrocarbon

emission indices can change dramatically depending on the combustor selected

for the engine. Further study and more complete data regarding implementation

of various combustor options has led to a revised distribution and assignment of

combustors for selected engine types. These revised assignments were used

for the August 1992 recalculated inventory so they would be consistent with

combustor assumptions made when creating the 1999 inventory.

NASA/CR---2001-211216 26
Because of the changes in methodology discussed above, in order to do a

self consistent trend analysis of emissions and fuel burn from 1976 to 1999, the

previously published 1976 and 1984 inventories would have to be recalculated

using the same methodology that was used to create the 1999 scheduled

inventory if trends in hydrocarbon or carbon monoxide emissions are required.

Recalculation of the 1976 and 1984 emission inventories is beyond the scope of

the current work but should be considered for the future. The analysis suggests

that trends of fuel burn and NOx emissions would not be impacted by the change

in methodology, at least in terms of global totals. A more detailed analysis would

be required to evaluate whether this is true for regional and "by-aircraft" trends

as well.

NASA/CR--2001-211216 27

3. Results and Analysis - Scheduled Aircraft Emissions

3.1 Overview of Results

The fuel burned and emissions calculated for the scheduled aircraft fleet

for each month of 1999 are summarized in Table 3-1.

Table 3-1. Fuel burned and emissions for scheduled air traffic for each month

of 1999.

Fuel NOx HC CO Distance

Month (kg/day) (kg/day) (kg/day) (kg/day) (km/day)

January 3.42E+08 4.49E+06 5.30E+05 1.87E+06 6.80E+07

February 3.40E+08 4.48E+06 5.24E+05 1.86E+06 6.82E+07

March 3.43E+08 4.52E+06 5.20E+05 1.86E+06 6.88E+07

April 3.45E+08 4.54E+06 5.12E+05 1.85E+06 6.90E+07

May 3.47E+08 4.58E+06 5.14E+05 1.87E+06 7.01 E+07

June 3.57E+08 4.70E+06 5.24E+05 1.90E+06 7.21 E+07

July 3.61E+08 4.75E+06 5.28E+05 1.92E+06 7.27E+07

August 3.64E+08 4.80E+06 5.36E+05 1.94E+06 7.36E+07

September 3.57E+08 4.70E+06 5.23E+05 1.91 E+06 7.26E+07

October 3.54E+08 4.66E+06 5.12E+05 1.88 E+06 7.21 E+07

November 3.46E+08 4.58E+06 4.90E+05 1.82E+06 7.02E+07

December 3.50E+08 4.64E+06 4.93E+05 1.83E+06 7.10E+07

Total 1.28E+11 1.69E+09 1.89E+08 6.85E+08 2.58E+10

kg/year kg/year kg/year kg/year km/year

The geographical distribution of the NOx emissions calculated for May

1999 scheduled air traffic is shown in Figures 3-1 and 3-2. This distribution is

representative of the geographical distributions of fuel burn, NOx, CO and

hydrocarbon emissions for scheduled air traffic for all months of 1999.

Figure 3-1 shows cruise emissions (9-13 km altitude band) as a function

of latitude and longitude. As in scheduled inventories previously calculated for

1976, 1984 and 1992, peak emissions occur over the United States, Europe, the

North Atlantic flight corridor, and Japan.

NASA/CR--2001-211216 29
9O

6O

3O

-30 ........

-90

-180

°_,

..... i .....

i i i ,

, i i

-120 -60 0 60 120 180

Longitude

__i_!_i;_!i_i_i i_i'i  ̧

__ii_ii_iiiii_ i_i_i_ i ̧

Figure 3-1.

o 5 10 15 20

NOx(pounds/day) X 0.010

Global cruise (9-13 km) NOx distribution for the scheduled aircraft

fleet, May 1999.

25

"--'15 -

(L)

"(3

_10 ".

m

< 5--

0

-90

i!i:i iiii_il

-60 -30 0 30 60

m

90

0

Figure 3-2.

15

NOx (Thousand kg/day)

NOx emissions for the scheduled aircraft fleet, May 1999, as a

function of altitude and latitude (summed over longitude).

30

NASA/CR--2001-211216 30
Figure 3-2 shows NOx emissions as a function of altitude and latitude.

This figure illustrates that the majority of global NOx emissions occur between

30 ° North and 60 ° North latitude at typical cruise altitudes (9-13 kin).

Approximately 91 percent of emissions from the scheduled aircraft fleet

are produced in the Northern Hemisphere. Table 3-2 shows the percentage of

global fuel burned, NOx emitted and distance traveled amongst seven selected

regions of the world for May 1999. The largest percentage of global fuel burned

and emissions occur over the United States and Europe.

Table 3-2. Percentage of global fuel burned, NOx emitted and distance

traveled in selected regions of the world by the May 1999

scheduled aircraft fleet.

US Europe North North North China Far East

America Atlantic Pacific

Fuel burned 30% 14% 32% 4% 3% 4% 3%

NOx 28% 14% 30% 4% 3% 5% 4%

Distance 39% 16% 41% 3% 2% 4% 2%

Distributions of fuel burned and emissions as a function of altitude are

shown in Figure 3-3. This figure shows that peak fuel burned and NOx

emissions occur at cruise altitudes, while peak CO and hydrocarbon emissions

occur during the landing/takeoff cycle in the 0-1 km altitude band. Approximately

31% of the fuel burned and 35% of NOx emissions occur below 9 km while

approximately 70% of the hydrocarbon and carbon monoxide emissions are

emitted below 9 km.

The plots of fuel burned and emissions as a function of latitude in Figure

3-4 emphasize that peak emissions from the scheduled fleet occur at northern

mid-latitudes, with the majority of emissions occurring between 30 ° North and

60 ° North latitude.

NASA/CR--2001-211216 31
13-14

12-13

11-12

10-11

9-10

c

M

o

"D

8-9

7-8

6-7

5-6

4-5

3-4

2-3

1-2

0-1

13CO

13 Hydrocarbons

• NOx

• Fuel

i

i

,!

! I :

t I _ r t r

O% 5% 10% 15% 20% 25% 30% 35% 40%

Fraction of Global Emissions

Figure 3-3. Altitude distribution of fractional fuel burned and fractional global

emissions of CO, Hydrocarbons and NOx for the scheduled aircraft

fleet, May 1999.

NASA/CR--2001-211216 32
°l

.-J

60

30

0

-30

-60

-90

0

30t '\

_ 0

N .

_.1

-30 _

Cumulative Fraction

0.0 0.2 0.4 0.6 0.8 1.0

90 '","', .... '",'"

J

, , , , I , • , , I • , , ,

5 10 5

Fuel Burned (million kg/day)

Cumulative Fraction

0.0 0.2 0.4 0.6 0.8 1.0

90 "", ........... ,'"

60

-6O

-90 ............................

0.000 0.010 0.020 0.030

HC Emissions (million kg/day)

._J

0

-30

-60

-90

60-

30

0

-30

-60

-90

Cumulative Fraction

0.0 0.2 0.4 0.6 0.8 1.0

90 '",'", .... '",'"

30

,,,,,,,.,I,,,.,,,,,I,.,o,,,,*

0.0 0.1 0.2 0.3

NOx Emissions (million kg/day)

Cumulative Fraction

0.0 0.2 0.4 0.6 0.8 1.0

90 ....... , ....... , ' "-_

"1

0.00 0.05 0.10 0. 5

CO Emissions (million kg/day)

Figure 3-4. Fuel burned and emissions (solid line) as a function of latitude for

scheduled May 1999 air traffic. Dashed lines show the cumulative

fraction of emissions.

NASA/CR--2001-211216 33
3.2 Fleet Movement Statistics, Fuel Usage and Effective Emission Indices

To summarize results of the emission inventory calculations, specific

aircraft types were grouped into general aircraft classes and their fuel burned,

emissions, departures and distance traveled were totaled. Global effective

emission indices for each general aircraft class were also calculated for the

1-9 km and 9-13 km band. Here we define an effective emission index as the

ratio of emittant integrated over a given geographical region (latitude, longitude,

altitude band) to the integrated fuel use over the same region. Effective

emission indices reported herein were calculated using global emissions and

are therefore referred to as globa/effective emission indices.

Fleet movement statistics for May 1999 by general aircraft class are

summarized in Table 3-3. This table shows the total daily distance flown, the

daily departures, and their fraction of the global total for each general aircraft

class. It also shows the average route distance for each general class. A

more detailed summary identifying similar results for each specific OAG

airplane/engine combination in a given aircraft class is provided in Appendix E,

which also identifies how each of the general aircraft classes in Table 3-3 is

defined. The statistics for May 1999 shown in Table 3-3 and Appendix E are

representative of those for all other months in 1999.

NASA/CR--2001-211216 34
Table 3-3. Summary of departure statistics by general aircraft type for May

1999.

General Type

Turboprops

Boeing 737-300/400/500

Daily

Departures

21,296

10,224

% of

Global

Departures

30.56%

14.67%

% of

Distance Global

(km/day) Distance

6,608,584 9.43%

9,147,802 13.05%

MD-80

Boeing 737-100/200

DC-9

Regional Jets

Airbus A320

Boeing 757-200

Boeing 727-200

Fokker 100

Boeing 767-300

Boeing 747-400

BAE 146

Airbus A300-600

Boeing 737-600/700/800

Russian Aircraft

Fokker 28

Boeing 747-100/200/300

Airbus A319

Boeing 767-200

Boeing 777-200

Airbus A310

Airbus A321

MD-90

DC-10

MD-11

DC-8

Boeing 727-100

Airbus A330-300

Airbus A340-300

Airbus A300-B2/B4/F4

Fokker 70

Lockheed L-1011

Boeing 777-300

BAC 111

Boeing 707

Airbus A330-200

Airbus A340-200

Concorde

Miscellaneous

Total

5,397

4,013

3,346

3,198

3,071

2,741

2,353

1,697

1,533

1,006

993

825

771

701

626

57O

537

492

473

464

448

442

379

3O8

266

261

250

224

199

198

140

82

57

41

39

2O

6

5

69,690

7.74%

5.76%

4.80%

4.59%

4.41%

3.93%

3.38%

2.43%

2.20%

1.44%

1.43%

1.18%

1.11%

1.01%

0.90%

0.82%

0.77%

0.71%

0.68%

0.67%

0.64%

0.63%

0.54%

0.44%

0.38%

0.37%

0.36%

0.32%

0.29%

0.28%

0.20%

0.12%

0.08%

0.06%

0.06%

0.03%

0.01%

0.01%

5,619,233 8.02%

3,176,590 4.53%

2,379,550 3.39%

2,096,416 2.99%

3,818,451 5.45%

4,828,701 6.89%

2,532,550 3.61%

1,079,091 1.54%

4,043,356 5.77%

5,664,264 8.08%

630,398 0.90%

1,012,579 1.44%

1,047,151 1.49%

1,266,310 1.81%

358,254 0.51%

2,573,174 3.67%

692,169 0.99%

1,417,564 2.02%

1,583,564 2.26%

1,044,357 1.49%

361,687 0.52%

331,624 0.47%

1,523,344 2.17%

1,541,979 2.20%

451,733 0.64%

205,915 0.29%

510,219 0.73%

1,250,423 1.78%

273,690 0.39%

149,699 0.21%

288,761 0.41%

131,672 0.19%

45,221 0.06%

105,766 0.15%

138,796 0.20%

140,216 0.20%

33,890 0.05%

3,013 0.00%

70,107,755

Average Route

Distance

(km)

310

895

1,041

792

711

656

1,243

1,762

1,077

636

2,638

5,632

635

1,228

1,357

1,806

572

4,517

1,289

2,884

3,345

2,251

807

750

4,022

5,006

1,699

789

2,044

5,589

1,377

756

2,058

1,614

797

2,607

3,572

6,961

5,648

659

NASA/CR--2001-211216 35
Tables 3-4 and 3-5 show a summary of average daily fuel burned, global

effective emission indices and the fractional contribution to the global fuel burned

and emissions totals calculated for May 1999 for each general aircraft class. In

Table 3-4, separate global effective emission indices are shown for NOx, CO

and hydrocarbons for the 1-9 km band and the 9-13 km band. A more detailed

summary of global effective emission indices showing the results for each OAG

airplane/combination is included as Appendix D. Some variation in the global

effective emission indices listed in Appendix D may occur between similar

aircraft/engine types because of differences in average mission distances flown

by them and differences in engine and performance data used to model them.

The data in Table 3-4 represent results of calculations done assuming

typical OEWs and average seat counts and load factors, actual configurations

and loading will be unique to specific operators and routes.

Table 3-3 shows that global departures are dominated by smaller aircraft

(turboprops, 737s, MD-80s, DC-9s and regional jets) with 31% of global

departures being made by turboprop aircraft alone. Tables 3-4 and 3-5 show

that no general aircraft class dominates global scheduled aircraft fleet fuel

burned and NOx emissions. These tables show that roughly 48% of scheduled

fleet fuel was consumed and 52% of scheduled fleet NOx was created by large

long-range aircraft (747s, A340s, L-101 ls, DC-10s, 777s and 767s).

NASA/CR--2001-211216 36
Table 3-4. Summary of fuel burned and global effective emission indices for

commercial aircraft types (based on May 1999 scheduled air

traffic).

General Type

Boeing 747-400

Boeing 737-300/400/500

Boeing 747-100/200/300

MD-80

Boeing 767-300

Boeing 757-200

,Boeing 727-200

DC-10

Boeing 737-100/200

MD-11

Airbus A320

Boeing 777-200

DC-9

Turboprops

Airbus A340-300

Russian Aircraft

Boeing 767-200

Airbus A300-600

Airbus A310

Regional Jets

Fokker 100

Airbus A330-300

Boeing 737-600/700/800

DC-8

Lockheed L-1011

BAE 146

Airbus A319

Airbus A300-B2/B4/F4

Airbus A321

MD-90

Fokker 28

Boeing 777-300

Boeing 727-100

,Airbus A340-200

,Airbus A330-200

Boeing 707

Fokker 70

Concorde

'BAC111

Miscellaneous

Fuel

(looo

kg/day)

59,837

30,765

30,638

22,367

22,153

19,717

14,334

12,679

12,223

11,952

11,884

11,260

9,130

8,788

8,242

7,138

7,110

6,397

5,298

4,479

3,444

3,402

3,219

2,883

2,415

2,330

2,048

2,004

1,405

1,243

1,211

1,131

1,094

910

848

607

453

351

158

5

% of Global

Scheduled

Traffic Fuel

Burned

17.22%

8.85%

8.82%

6.44%

6.37%

5.67%

4.12%

3.65%

3.52%

3.44%

3.42%

3.24%

2.63%

2.53%

2.37%

2.05%

2.05%

1.84%

1.52%

1.29%

0.99%

0.98%

0.93%

0.83%

0.70%

0.67%

0.59%

0.58%

0.40%

0.36%

0.35%

0.33%

0.31%

0.26%

0.24%

0.17%

0.13%

0.10%

0.05%

0.00%

1-9 km Altitude Band

El El El

(NOx) (CO) (HC)

25.3 8.1 1.9

13.23 11.5 0.9

27.51 15.4 10.2

15.96 4.2 1.2

21.33 7.0 1.4

18.64 8.4 0.5

11.91 9.6 3.1

24.23 7.5 2.8

11.18 10.0 3.3

18.98 5.9 O.5

17.45 5.6 0.5

25.17 5.4 6.0

10.99 11.8 4.2

11.92 3.8 0.2

22.97 11.3 4.7

12.33 15.5 9.0

22.6 6.6 1.6

17.77 10.1 2.0

18.46 15.3 4.7

11.63 9.4 1.4

11.05 21.0 2.0

23.04 7.0 1.5

16.32 6.4 0.9

11.24 16.3 11.2

18.74 19.4 13.6

9.14 5,0 0.5

14.55 5.7 0.7

22.17 13.1 5.2

17.45 6.4 0.6

16.44 5.2 0.1

10.47 13.5 7.8

24.77 4.4 10.3

10.8 14.8 5.7

23.05 11.2 4.6

24.34 6.5 1.0

8.35 31.6 39.4

10.3 5.3 1.2

11.03 18.5 1.3

14.44 25.5 15.1

8.61 15.8 2.3

9-13 km Altitude Band

El El El

(NOx) (CO) (HC)

13.3 1.0 0.4

9.6 3.5 0.2

15.2 2.2 1.1

10.6 4.4 1.6

12.5 1.2 0.3

11.0 1.7 0.1

8.3 5.4 1.0

14.9 2.0 0.9

7.1 6.8 1.3

12.9 1.2 0.1

12.0 2.0 0.4

16.8 0.6 0.3

7.6 6.7 1.0

13.7 1.7 0.2

9.2 8.4 1.5

11.1 2.0 0.3

12.2 1.7 0.3

11.3 2.2 0.6

9.1 0.6 0.1

6.4 7.0 1.0

14.5 1.3 0.5

11.8 1.8 0.3

8.6 7.2 1.4

14.4 9.O 2.2

7.8 1.6 0.1

10.9 2.5 0.3

14.5 1.9 1.2

13.3 1.7 0.2

11.9 1.8 0.1

7.4 7.2 2.7

15.7 0.8 0.5

7.1 10.2 2.1

13.7 1.8 0.1

16.3 1.6 0.3

5.4 17.9 8.5

7.1 2.7 1.0

10.0 26.1 1.8

10.1 14.7 6.0

7.3 0.8 0.2

NASA/CR--2001-211216 37
Table 3-5. Fractional contribution of each commercial airplane type to global

fuel burned and emissions totals for May 1999 scheduled traffic.

(Summe(

General Type

Boeing 747-400

Boeing 737-300/400/500

Boeing 747-100/200/300

MD-80

Boeing 767-300

Boeing 757-200

Boeing 727-200

DC-10

Boeing 737-100/200

MD-11

Airbus A320

Boeing 777-200

DC-9

Turboprops

Airbus A340-300

Boeing 767-200

Russian Aircraft

Airbus A300-600

Airbus A310

FRegional Jets

Fokker 100

Airbus A330-300

:Boeing 737-600/700/800

DC-8

_Lockheed L-1011

BAE 146

Airbus A319

Airbus A300-B2/B4/F4

Airbus A321

MD-90

Fokker 28

Boeing 777-300

Boeing 727-100

Airbus A340-200

Airbus A330-200

Boeing 707

Fokker 70

Concorde

BAC 111

over all altitudes, latitudes, and longitudes)

Fuel

17.22%

8.85%

8.82%

6.44%

6.37%

5.67%

4.12%

3.65%

3.52%

3.44%

3.42%

3,24%

2.63%

2.53%

2.37%

2.05%

2,05%

1.84%

1.52%

1,29%

0.99%

0.98%

0.93%

0.83%

0.69%

0.67%

0.59%

0.58%

0.40%

0.36%

0.35%

0,33%

0.31%

0.26%

0,24%

0.17%

0.13%

0.10%

0.05%

NOx

18.94%

7.22%

11.17%

6.04%

6.78%

5.55%

3.04%

4.45%

2.36%

3.53%

3.51%

4,42%

1.72%

2.13%

2.63%

2.01%

1.53%

1.93%

1.46%

1.01%

0.62%

1.24%

O.92%

0.57%

0.82%

0.43%

0.54%

0.74%

0.47%

0.38%

0.22%

0.45%

0.21%

0.29%

0.33%

0.O8%

0,09%

0.12%

0.04%

HC

6.68%

3.91%

15.36%

6.75%

2.73%

0.87%

6.34%

4.08%

6.44%

0.42%

1.04%

4,13%

6.85%

0.53%

1.00%

0.95%

7.52%

1.36%

1.65%

0.83%

1.14%

0.57%

0.41%

2.85%

3.51%

0.22%

0.23%

1.37%

0.13%

0.02%

5.18%

1.24%

0.81%

0.09%

0.07%

2.13%

0,12%

0.09%

0.38%

CO

6.67%

14.79%

7.86%

5.68%

3.43%

4.46%

6.56%

2.74%

6.40%

1.28%

2.58%

1.10%

6,25%

2.13%

1.33%

1,27%

4,92%

2,07%

1,67%

1.82%

3,04%

0.65%

0.77%

1,82%

1,90%

0.67%

0,50%

0.93%

0.44%

0.32%

1.43%

0,15%

0.76%

0.14%

0.12%

0.76%

0,17%

0.18%

0.20%

Distance

8.08%

13.04%

3.67%

8.01%

5.77%

6.89%

3.61%

2,17%

4,53%

2,20%

5,45%

2,26%

3,39%

9.42%

1.78%

2.02%

1.83%

1.44%

1.49%

2.99%

1.54%

0.73%

1.49%

0.64%

0.41%

O.9O%

0.99%

0.39%

0.52%

0.47%

0.51%

0,19%

0.29%

0.20%

0.20%

0.15%

0,21%

0.05%

0.06%

NASA/CR--2001-211216 38
There has been some confusion in the scientific literature and with various

emission inventory calculations with regard to emission indices at flight altitudes.

Most of the available data are from certification measurements at sea level

conditions (International Civil Aviation Organization (ICAO), 2000). In some

cases, these have been used incorrectly as being representative of the emission

levels at cruise conditions, without corrections being used for ambient conditions

of pressure and temperature.

In order to help reduce the confusion about the global effective emission

indices for commercial aircraft, Table 3-4 shows the global effective emission

indices for NOx, CO, and hydrocarbons for each general aircraft class. Global

effective emission indices are shown for two altitude bands: 1-9 km (climb and

descent averaged together) and 9-13 kilometers (primarily cruise but some final

climb and initial descent).

These global effective emission indices represent our best estimate of

fleet averages (averaged over all missions) and should not be compared directly

with an emission index measured behind an individual aircraft in flight. The

methodology used to calculate emissions at altitude in this study (see Section

2.3.4 of this report) can be used for such a comparison if accurate and precise

measurements of actual fuel flow, ambient temperature, ambient pressure,

humidity, Mach number and corresponding emission index are made.

Comparisons with in-flight emission index measurements should provide a way

to evaluate the accuracy of the emission methodology used to calculate the

inventories documented in this report.

Care must be exercised if attempting to use the information in Table 3-3

and Table 3-4 to calculate fuel efficiencies for the various general aircraft

classes. Any aircraft fuel efficiency comparison requires a consideration of the

amount of payload (passengers and freight) being carried by each aircraft for a

given mission length. Comparisons of aircraft on a strict fuel burn per distance

traveled basis without normalizing the data for the number of passengers carried

may result in misleading comparisons.

Figure 3-5 illustrates this point. This figure contains plots of fuel burned

per kilometer traveled (top panel) and fuel burned per passenger kilometer

traveled (bottom panel) as a function of mission length for a 747-400 and an

MD-11ER. The top panel of Figure 3-5 shows that the fuel burned per kilometer

for the MD-11ER is significantly lower (approximately 46 percent) than that of the

747-400 for all mission lengths shown. This though is a misleading comparison

because the number of passengers carried by the MD-11ER is less than that

carried by the 747-400. The bottom panel of Figure 3-5 shows the effect of

normalizing the data by average seat count. Fuel burned per ASK (available

seat kilometer) is plotted versus mission range. For this comparison the fuel

burned per ASK values for the 747-400 and MD-11ER are within 6 percent of

each other for all mission lengths shown.

NASAICR--2001-211216 39
18

16

14

v

,)=)

o

oE

L,.

4)

Ul.

.....

&

• • • • • • • •

IOI

8-+

6

: & 747-400

• MD-11ER

2

0

0 2000 4000 6000 8000 10000 12000

Miwon Length(Km)

14000

0,045

0.040

o.035

® 0.030

E

o

0.025

o_ 0.020

o

--_ 0.015

0.010

0.005

1,1=

0.000

!

]

m 747-400 MD-11ER I

0 2000 4000 6000 8000 10000 12000 14000

Mission Length (Km)

Figure 3-5. Fuel burned per kilometer traveled (top panel) and fuel burned per

available seat kilometer traveled (bottom panel) as a function of

mission length for the 747-400 and the MD-11ER.

NASA/CR--2001-211216 40
3.3 Seasonal Variability

There is a noticeable- seasonal variation in air traffic departures in some

regions as airlines shift schedules and aircraft to accommodate passenger

demand. For example, increased air traffic may mean that airlines will utilize

their aircraft more frequently and that some airplanes will be used more than

others. There are seasonal variations in emissions which reflect both changes

in passenger flow and in the equipment being used.

Trends of emissions and fuel burned global totals for the fleet are a

composite of three trends: (1) The seasonal variation in traffic demand, (2)

Demand growth and changes in overall fleet technology brought about by the

introduction of new aircraft and (3) The retirement of old aircraft.

Figure 3-6 shows the seasonal variation in total global fuel burned by the

scheduled aircraft fleet (summed over all altitudes). The top panel shows the

daily fuel use as a function of month. The bottom panel shows the percent

deviation from the annual average fuel use as a function of month. Global fuel

use for 1999 peaked at roughly 4% above the annual average in August and was

the lowest in February when it was roughly 3% below the annual average. The

month having a daily fuel use that was closest to the annual average was

December.

Both water vapor and carbon dioxide emission indices are functions of

the hydrogen and carbon content, respectively, of the jet fuel. For typical jet fuel,

EI(H20) = 1237 grams H20/kg fuel burned

El (CO2) = 3155 grams CO2/kg fuel burned

Thus, the seasonal variation in carbon dioxide and water vapor emissions

from the commercial fleet will be the same as that shown for the fuel usage in

Figure 3-6.

NASA/CR--2001-211216 41
3.70E+08

3.65E+08 i

A

m

v

i

_L

3.60E÷08

3.55E+08

3.50E+08

3.45E+08

3.40E+08

3.35E+08

3.30E+08

3.25E+08

Annual A_rage

I

=II

II.I I.I

IIII_

",,II IIIII

'

l II III II

Jan Feb Mar _r May June July AUg Sept OCt Nov Dec

Month

5%

-4%

Figure 3-6.

Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec

Month

Global fuel burned in the 0-19 km altitude band for scheduled air

traffic and percent deviation from the annual average fuel burn for

each month of 1999.

NASA/CR--2001-211216 42
3.4 Trend Analysis

In order to assess changes in scheduled fleet global emissions and fuel

burned between 1992 and 1999, August 1999 emission inventory global totals

were compared to August 1992 emission inventory global totals calculated using

the same updated methodology outlined in Section 2 of this report.

Table 3-6 shows a comparison between the scheduled fleet global

emissions, distance and fuel burned totals for August 1992 and August 1999

that were calculated using the same methodology. Both the total change in

emissions, distance and fuel burned over the seven year period and the yearly

rate of change are given in Table 3-6. Yearly rate of change values were

calculated by assuming exponential growth.

Table 3-6. Fuel burned and emissions calculated self-consistently for the

scheduled aircraft fleet for August 1992 and August 1999.

Fuel NOx HC CO

(kg/day) (kg/day) (kg/day)(kg/day)

Distance

(km/day)

August 1992 2.74E+08 3.57E+06 6.63E+05 1.71E+06 5.07E+07

August 1999 3.64E+08 4.80E+06 5.36E+05 1.94E+06 7.36E+07

Total Change 33% 35% -19% 14% 45%

(1992 to 1999)

Average Yearly Change 4.1% 4.3% -3.0% 1.9% 5.5%

Fuel use was calculated to have increased by 33% between 1992 and

1999, while NOx emissions were calculated to increased by 35%. These

increases correspond to an average annual growth rate of approximately 4%.

During this same period, the total distance flown by all scheduled aircraft was

calculated to increase by 45%, corresponding to an annual growth rate of 5.5%.

By contrast, CO emissions were calculated to increase by only 14% and

hydrocarbon emissions were calculated to decrease by 19% between 1992 and

1999.

NASA/CRy2001-21 ! 216 43
The relatively small yearly growth of CO emissions and the reduction of

hydrocarbon emissions between 1992 and 1999 is mainly due to the retirement

of old aircraft from the fleet and the delivery of new technology engines as the

fleet grew. The new technology engines have more efficient combustors with

higher overall pressure ratios (OPR). These engines generally produce less

hydrocarbons and CO than the ones they replaced.

The average yearly growth in NOx emissions between August 1992 and

August 1999 is slightly larger than that of fuel burned. Higher engine OPRs,

although they lead to fuel efficiency improvements, lead to higher temperatures

and pressures within the combustor and typically higher NOx emissions for a

given combustor design. This tendency presents a challenge to engine

manufacturers who are trying to improve engine fuel efficiency while reducing

NOx emissions.

Absolute quantities of fleet emissions and fuel burned do not take into

account trends of the productivity of the fleet. In order to establish a trend in

scheduled fleet global emissions that takes fleet productivity into account, total

global NOx emissions and fuel burned for 1992, 1999 and projected emissions

and fuel burned for 2015 were normalized by available seat kilometers (ASK)

flown and plotted as a function of year in Figure 3-7.

To generate the trends in Figure 3-7, results of the previously published

NASA 1992 scheduled fleet global emission inventory (Baughcum, eta/., 1996a)

were used for the 1992 NOx emissions and fuel burned totals. Results of the

previously published NASA 2015 scheduled fleet global emission scenario

(Baughcum, et al., 1998) were used for the 2015 NOx emissions and fuel burned

totals. As was discussed in Section 2.5, the methodology used to create the

NASA 1992 and 2015 inventories was different than that used for the 1999

inventory, but differences in NOx emissions and fuel burned global totals that

come about from the use of the two different methodologies are small.

Therefore, it is reasonable to use previous NASA calculations of NOx and fuel

burned global totals with the current results to develop a trend analysis.

Total ASKs for 1992, 1999 and 2015 were calculated by multiplying

average seat counts for each individual aircraft type in the respective inventory

by the number of kilometers flown by that aircraft type and adding the ASK totals

for all of the individual aircraft types. Total fleet NOx emissions and fuel use

were then normalized by these ASK totals

Figure 3-7 shows that both global NOx/ASK and global fuel use/ASK for

the scheduled aircraft fleet decrease with time. The dashed trend lines running

through the data points in Figure 3-7 represent a 1.2 percent per year

improvement and 1.3 percent per year improvement in NOx/ASK and Fuel

NASA/CR---2001-211216 44
Use/ASK, respectively. When the trend lines are extrapolated to 2015, the fuel

trend is consistent with the previous 2015 scenario projected, while the NOx

trend is slightly better than projected in that scenario.

The trend toward a reduction in NOx/ASK and fuel use/ASK with time

demonstrates the effect of introducing improved fuel efficiency and NOx

emission reduction technology into the scheduled fleet.

NASA/CRy2001-211216 45
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3.5 Effects of Improved Freighter Modeling

In the earlier NASA emission inventories, (Baughcum, eta/., 1996a and

1996b) no distinction was made between flights flown by freighter aircraft and

those flown by passenger aircraft. All aircraft flights were modeled using

performance data generated assuming a 70% passenger load factor. In the

OAG flight schedules created for this study, flights flown by freighters are

distinguished from those flown by passenger aircraft. This increased detail in the

schedule made it possible in the 1999 inventory calculations to more accurately

model freighters by modeling them with more representative payloads.

As described in Section 2.3.3 of this report, DOT Form T-100 data were

analyzed to determine average payloads for various types of freighter aircraft.

Based on this analysis, it was determined that more accurate inventory results

could be obtained if very large freighter aircraft types (747, MD-11, L-1011,

DC-10 and Antonov An-124) were modeled using passenger versions with

payloads heavier than those associated with 70% passenger loading. This

analysis also showed that small and medium freighter aircraft could be modeled

accurately enough by using passenger versions with payloads corresponding to

70% passenger load factor as was done in previous NASA inventory

calculations.

In order to determine the effect of improved freighter payload assumptions

on global fuel burned and NOx totals, inventory calculations were made with and

without the improved freighter payload assumptions discussed above for August

1999. For general aircraft types that included very large freighters, Table 3-7

shows fuel burned and NOx emissions global totals for the two different

calculations along with percent difference comparisons. A positive percent

difference indicates that the new freighter payload assumptions increased fuel

burn or NOx emissions. Table 3-7 also shows the percent of the total distance

within each aircraft type that was traveled by freighter aircraft.

Total fuel use and NOx for the 1999 scheduled aircraft fleet were

increased by 0.6 and 1.5 percent respectively when the improved freighter

payload assumptions were used. For each aircraft type modeled using improved

payload assumptions, global NOx emissions and fuel use increased because the

aircraft operated at higher takeoff gross weights (TOGW). Higher TOGWs

require higher engine thrust throughout the mission. This leads to increased fuel

burn and higher combustor temperatures, which in turn lead to increased NOx

emissions.

This improved treatment of freighter aircraft represents a fairly small

correction to the emission inventories.

NASA/CR---2001-211216 47
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3.6 Database Availability

The 3-dimensional scheduled aircraft emission inventories of fuel burned

and emissions calculated on a 1 degree latitude x 1 degree longitude x 1 km

altitude grid for each month of 1999 and for August 1992 have been delivered in

electronic format to the NASA Langley Research Center. Questions concerning

the availability of these data should be directed to Dr. Chowen C. Wey

(Chowen.C.Wey@grc.nasa.gov), the NASA GRC contract monitor for this work.

Technical questions about the data set should be sent to Steven L. Baughcum

(Steven.L.Baughcum@boeing.com) or Donald J. Sutkus

(Donald.J.Sutkus@boeing.com) at the Boeing Company, P. O. Box 3707,

MS 0R-RC, Seattle, WA 98124-2207.

NASA/CR--2001-211216 49

4. Comparison of 1999 Inventory Results with DOT Form 41 Data

As discussed in Section 2 of this report, the 1999 scheduled aircraft fleet

global emission inventory was created using Official Airline Guide (OAG) flight

schedule data, Boeing aircraft performance data and International Civil Aviation

Organization (ICAO) engine emissions data.

In developing the performance data used to model aircraft in the 1999

scheduled aircraft fleet global emission inventory, certain simplifying

assumptions were made about the conditions under which aircraft operate.

These assumptions, which are listed below, lead to errors in the calculation

of global aircraft fleet fuel burned and emissions. These errors have been

discussed in detail in previous work (Baughcum, eta/., 1996a; Daggett, eta/.,

1999).

Performance Assumptions for the NASA 1999 scheduled emission inventory

calculations:

• No winds

• International Standard Atmosphere (ISA) temperatures and pressures

• Continuous climb cruise flight segment with typical westbound flight

beginning and ending cruise altitudes

• All aircraft were modeled as passenger aircraft except 747, MD-11,

DC-10, L-1011 and An-124 freighter aircraft which were modeled using

typical freighter cargoes and OEWs

• Passenger aircraft were modeled assuming no cargo (Payload =

passengers + baggage weight)

• Passenger aircraft were modeled using a 70% passenger load factor

• Passenger and baggage weight were assumed to be 200 Ib/passenger

for single aisle and 210 Ib/passenger for wide body aircraft

• Boeing typical weight calculations were used for Operating Empty

Weight, Maximum Landing Weight, Maximum Zero Fuel Weight, etc.

• Fuel density of 6.75 Ib/gallon and fuel energy content of 18,580 BTU/Ib

• Direct great circle routes--no turns or air traffic control diversions

• Takeoff Gross Weights (TOGW) are calculated assuming city pairs are

at sea level. Performance calculations assume origin and destination

airports are at their respective actual airport altitudes.

• Optimum aircraft operating rules

• Engine and airframe performance at new airplane level

Some of the characteristics of the OAG flight schedule data used in

creating the scheduled aircraft fleet emission inventories also lead to

inaccuracies in global aircraft emission inventory calculations. As discussed in

NASA/CR----2001-211216 51
Section 2 of this report, the 1999 scheduled aircraft fleet global emission

inventory calculations are based on the OAG listing of flights which is used as a

resource for travelers attempting to book flights. Flights listed in the OAG are

those that are projected to take place and not ones that necessarily occurred.

In addition, the OAG flight schedule often contains duplicate listings of the same

flights due to phenomena such as codesharing between airlines. Filtering of

the OAG schedules must be done prior to their use for calculating emission

inventories and the filtering process is another possible source for inaccuracies

in emission inventory results.

In order to evaluate the 1999 scheduled aircraft fleet global emission

inventory calculations, comparisons were made between results of these

calculations and aviation fuel use and traffic data reported on the U.S.

Department of Transportation (DOT) Form 41. Details of this comparison are

discussed below.

Each large U.S. air carrier must report statistics for aircraft fuel used,

revenue aircraft departures performed and revenue aircraft statute ground

track miles flown during a given year on U.S. DOT Form 41. A more detailed

description of DOT Form 41 data is contained in previous work (Daggett, eta/.,

1999). Although these statistics are reported by specific aircraft type (i.e. 747,

DC-10 etc.) and geographic region (i.e. North America, Atlantic Ocean, etc.),

only airline totals were compared with 1999 scheduled emission inventory

results,

DOT Form 41 fuel issue, departure and ground track miles flown data

were obtained for the 1999 calendar year for each carrier that reported traffic

and capacity data to the U.S. Department of Transportation. Results of the 1999

scheduled aircraft emission inventory calculations were compared to these data.

Comparisons were made for the ten passenger airlines that burned the most fuel

in 1999 (according to the DOT data) and for the four major cargo carriers that

report their fuel use and air traffic statistics to the DOT. The ten passenger

airlines considered reported 87% of all fuel use reported by passenger carriers

included in the DOT Form 41 database. The four cargo airlines considered

account for 87% of all carrier cargo fuel use and approximately 10% of total fuel

use reported on DOT Form 41 by all US carriers (passenger and cargo).

NASA/CR---2001-211216 52
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Table 4-1 shows the results of the comparison of yearly totals for

departures, distance traveled and fuel burned for the ten passenger carriers

considered. Comparisons are made on a percent difference basis relative to the

DOT Form 41 reported values. A negative percent difference denotes that 1999

emission inventory values are lower than those reported on DOT Form 41.

Table 4-1 shows that total departures and distance flown agree within

5 percent for all of the ten passenger air carriers considered with the differences

in total departures and distance traveled for the ten passenger carriers being

1 percent and 2 percent respectively. The agreement for total departures and

distance traveled is reasonably good considering that the OAG schedule data

used to calculate the 1999 emission inventory is based on projections of air

traffic demand. Both flight cancellations and code sharing between airlines or

their subsidiaries will contribute to the differences.

Because total departures and distance traveled are in relatively good

agreement, comparisons of fuel burned between the two data sets may be used

to give an indication of how well the emission inventory calculations predicted

fuel burned for the ten passenger airlines considered. For the passenger air

carriers listed in Table 4-1, the inventory calculations under predicted total fuel

by 21 percent on average. The differences in fuel burned for passenger carriers

are similar to those found in a similar analysis of 1992 scheduled aircraft

emission inventory results (Daggett, eta/, 1999). The majority of these

differences are likely due to the simplifying assumptions made regarding the

performance calculations used in creating the emission inventory. Major factors

here are the effect of air traffic control, the effect of weather and winds, assumed

payload, cargo load, and the assumption of great circle routing between airports.

Table 4-2 shows the results of the comparison of yearly totals for

departures, distance traveled and fuel burned for the four cargo carriers

considered in this analysis. This table shows that, for the four cargo carriers

considered, the total departures and total distance traveled calculated in the

1999 scheduled aircraft emission inventory are significantly less than those

reported in the DOT Form 41 data. The inventory under predicts total departures

and distance traveled by 56 percent and 43 percent respectively on average.

This indicates that the OAG flight schedule data used to create the 1999

scheduled aircraft fleet emission inventory do not contain a complete listing of

flights flown by cargo carriers. Fuel use by these four selected cargo carriers

was under predicted by 47 percent on average. Similar behavior was observed

for DOT Form 41 comparisons made for 1992 emission inventory results

(Daggett, eta/, 1999).

NASA/CR--2001-211216 54
To put the under prediction of cargo flights in perspective, the fuel use

reported on DOT Form 41 by all cargo carriers for 1999 was approximately 10

percent of the fuel use reported by all carriers (passenger and cargo). Thus,

missing the cargo carrier fuel use by approximately 50 percent in the emission

inventory would correspond to an error of approximately 5 percent in the

calculated fuel use by all US carriers.

Although this percentage may not necessarily be representative for nonU.S. carriers, it is large enough to justify further investigation of the effect that the

lack of coverage of cargo flights in the OAG has on global emission inventory

calculations. An investigation of this type is not within the scope of the current

work but should be considered for future study.

Overall, this comparison indicates that the OAG data are relatively

complete, at least for US carriers, but that there is a systematic under prediction

of fuel use of approximately 21 percent in the emission inventories. For cargo

carriers, the comparison indicates that there is a systematic under counting of

cargo flights in the OAG data with which we are working. This would introduce

an additional 5 percent under prediction in the inventory calculations of US

carriers. It is unclear how to extend these results to global totals or how to

account for them explicitly in the 3-dimensional emission inventory calculation.

NASA/CRy2001-211216 55

5. Summary and Conclusions

Emissions produced by the world's entire aircraft fleet come from

scheduled, military, charter and general aviation air traffic. In this report, we only

present the results and methodology used for the calculation of emissions from

scheduled air traffic which includes turboprops, passenger jets, and jet cargo

aircraft.

Global fuel use for 1999 by scheduled air traffic was calculated to be

1.28 x 1011 kilograms. Global NOx emissions by scheduled air traffic in 1999

were calculated to be 1.69 x 109 kilograms (as NO2). The calculated global

emissions show a seasonal variation, peaking in August with a minimum in

February. Emissions for the month of December 1999 were closest to global

annual average emissions, although emissions for May (the month typically used

as an 'average' month in past NASA inventory studies) were within 1 percent of

the global annual average.

A trend analysis for emissions and fuel burned was performed using the

results of this current work and previously published emission inventories and

scenarios. This analysis showed an increase in the absolute amount of fuel

burned, distance traveled, NOx, and CO emissions produced by the scheduled

fleet between 1992 and 1999 and a decrease in the absolute amount of

hydrocarbon emissions produced. Calculated global fuel use increased by 33%

and NOx emissions increased by 35% between 1992 and 1999. The analysis

also showed that scheduled fleet fuel burned and NOx emissions normalized by

available seat kilometers decreased between 1992 and 2015.

The methodology used to extract and process air traffic data from the

Official Airline Guide was changed from that used to calculate previous

scheduled fleet inventories for 1976, 1984 and 1992. To quantify the effects of

the methodology changes, an emission inventory for August 1992 was

recalculated using the new methodology. Comparisons between the previously

published and new August 1992 inventories show good agreement for global fuel

burned and NOx totals. For CO and hydrocarbons, the global totals increased

by 20 percent and 18 percent respectively with the use of the new methodology.

Much of this difference arises from the different combustor types selected in the

two methodologies for certain engines in the fleet. Emissions from a specific

engine model can vary widely depending on the combustor that is installed in the

engine.

To improve the accuracy of global emissions calculations for freighters,

United States Department of Transportation Form T-100 data were used to

determine typical payloads for freighter aircraft. This information was then used

NASA/CR--200I-211216 57
to model freighter aircraft more accurately in the inventory calculations by using

more realistic payloads.

To assess the effect of the different freighter payload assumptions, results

were compared with previous inventory calculations done using 70 percent

passenger payload for all aircraft. This comparison showed that improved

freighter payload assumptions increased total global fuel burned by 0.6 percent

and increased total global NOx by 1.5 percent for August 1999. These increases

are relatively small and will not significantly change trends for fuel use or NOx

created using the published inventories for 1976, 1984, and 1992.

In order to evaluate the 1999 scheduled aircraft fleet global emission

inventory calculations, comparisons were made with aviation fuel use and traffic

data reported on the U.S. Department of Transportation (DOT) Form 41 by US

air carriers. In general, emission inventory calculations of departures and

distance traveled for 1999 compared well (within 5 percent) with the DOT Form

41 data for the ten largest passenger carriers. In contrast, for the four largest

cargo carriers, departures and distance traveled calculated were significantly

less than those reported on DOT Form 41. It appears that the OAG flight

schedule data do not contain a complete listing of cargo flights.

For the passenger carriers in the DOT Form 41 data comparison, the

emission inventory calculations consistently under-predicted fleet fuel burned.

The magnitude of these under-predictions varied depending on the carrier

being considered. For the ten largest air carriers, the total fuel burn was underpredicted by 21 percent. This result is likely due to the simplifying assumptions

used in the development of the global inventory, including our inability to

consider air traffic control delays/diversions, weather/wind factors, more realistic

routing, less than optimum aircraft/engine performance and actual aircraft

operating weights.

NASA/CR--200I-211216 58
6. References

Baughcum, S. L., S. C. Henderson, P. S. Hertel, D. R. Maggiora, and C. A.

Oncina, Stratospheric Emissions Effects Database Development, NASA

CR-4592, 1994.

Baughcum, S. L., S. C. Henderson, T. G. Tritz, and D. C. Pickett, Scheduled Civil

Aircraft Emission Inventories for 1992: Database Development and

Analysis, NASA CR-4700, 1996.

Baughcum, S. L., S. C. Henderson, and T. G. Tritz, Scheduled C/vii Aircraft

Emission Inventories for 1976 and 1984." Database Development and

Analysis, NASA CR-4722, 1996.

Baughcum, S. L., S. C. Henderson, and D. J. Sutkus, Scheduled Civil Aircraft

Emission Inventories Projected for 2015: Database Development and

Analysis, NASA/CRm1998-207638, 1998.

Baughcum, S. L., and S. C. Henderson, Aircraft Emission Scenarios Projected in

Year 2015 for the NASA Technology Concept Aircraft (TCA) High Speed Civil

Transport, NASA/CRm1998-207635, 1998.

Daggett, D. L., D. J. Sutkus Jr., D. P. DuBois, and S. L. Baughcum. An

Evaluation of Aircraft Emission inventory Methodology by Comparisons with

Reported Airline Data, 1999-CR-209480, 1999.

DOE, International Energy Annual 1999, DOE/EIA-0219(99), U.S. Department of

Energy, 2001

Gardner, R. M., K. Adams, T. Cook, F. Deidewig, S.Ernedal, R. Falk, E. Fleuti,

E. Herms, C. E. Johnson, M. Lecht, D. S. Lee, M. Leech, D. Lister, B. Masse,

M. Metcalfe, P. Newton, A. Schmitt, C. Vandenbergh, and R. Van Drimmelen,

The ANCAT/EC global inventory of NOx emissions from Aircraft. Atmospheric

Environment, 31 (12), 1751-1766, 1997.

Gardner, R. M. (ed.), ANCAT/EC2 Global Aircraft Emissions Inventories for

1991/1992 and2015." Final Report, EUR-18179, ANCAT/EC Working Group,

ISBN-92-828-2914-6, 84 pp. +appendices, 1998.

Hadaller, O. J., and A. M. Momenthy, The Characteristics of Future Fuels,

Boeing publication D6-54940, 1989.

Hadaller, O. J., and A. M. Momenthy, "Characteristics of Future Aviation Fuels,"

Chapter 10 in Transportation and Global Climate Change, (D. L. Greene and

D. J. Santini, Eds.), American Council for an Energy-Efficient Economy,

Washington, DC, 1993.

NASA/CR--2001-211216 59
Hadaller, O. J., C. M. Roseburg, and M. E. Monsrud, The/mpact on Commercial

Aviation From Reducing the Sulfur Content in Jet Fuel NASA Contractor

Report NASI 20267, March, 2000.

Henderson, S. C., U. K. Wickrama, S. L. Baughcum, J. J. Begin, F. Franco, D. L.

Greene, D. S. Lee, M. L. McLaren, A. K. Mortlock, P. J. Newton, A. Schmitt,

D. J. Sutkus, A. Vedantham, and D. J. Wuebbles, "Aircraft Emissions;

Current Inventories and Future Scenarios", Chapter 9 in the

Intergovernmental Panel on Climate Change (IPCC) Special Report, Aviation

and the Global Atmosphere [Penner, J. E., D. H. Lister, D. J. Griggs, D. J.

Dokken, and M. McFarland (eds)],, Cambridge University Press, 1999.

International Civil Aviation Organization (ICAO), ICAO Eng/ne Exhaust

Emissions Databank, Internet Issue

(http://www.dera.gov.uk/html/te/combustion/t&e_aircraft_engine_exhaust_emi

ssions_data_bank.htm), May 2000.

Landau, Z. H., M. Metwally, R. Van Alstyne, and C. A. Ward, Jet Aircraft Engine

Exhaust Emissions Database Development -- Year 1990 and 2015 Scenarios,

NASA CR-4613, 1994.

Metwally, M., Jet Aircraft Engine Emissions Database Development--1992

Military, Charter, and Nonscheduled Traffic, NASA CR-4684, 1995.

Mortlock, A. M., and R. Van Alstyne, Military, Charter,

Traffic and General Aviation: 1976, 1984, 1992,

Scenarios, NASA/CRD1998-207639, 1998.

Unreported Domestic

and 2015 Emission

Penner, J. E., D. H. Lister, D. J. Griggs, D. J. Dokken, and M. McFarland (eds.),

Intergovernmental Panel on Climate Change (IPCC) Special Report on

Aviation and the Global Atmosphere, Cambridge University Press, 1999.

Schmitt, A. B. and B. Brunner, Emissions from aviation and their development

over time. In." Final Report on the BMBF Verbundprogramm, Schadstoffe in

tier Luftfahrt, /Schumann, U., A. Chlond, A. Ebel, B. Karcher, H. Pak, H

Schlager, A. Schmitt, and P. Wendling (eds.)], DLR-Mitteilung 97-04,

Deutsches Zentrum fur Luft- und Raumfahrt, Oberpfaffenhofen and Cologne,

Germany, pp. 37-52, 1997

Spicer, C. W., M. W. Holdren, D. L. Smith, D. P. Hughes, and M. D. Smith,

"Chemical Composition of Exhaust from Aircraft Turbine Engines," J.

Engineering for Gas Turbines and Power, vol. 114, pp. 111-117 (January

1992).

NASA/CR--2001-211216 60
Appendix A - Sample Airclaims Fleet Information Data

This Appendix contains a sample of the fleet information obtained from

the Airclaims database that was used to assign engines to aircraft listed in the

filtered OAG flight schedule. The sample data in this appendix show the Japan

Airlines fleet as it existed on May 16, 1999.

NASA/CR---2001-211216 61
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NASA/CR--2001-211216 62
Appendix B - Airplane/Engine Substitution Tables for 1999 Emissions

Inventory Calculations

This Appendix contains a list of each aircraft/engine combination listed in

the filtered OAG flight schedule and the performance aircraft and emissions

engine that was used to model it. Each emissions engine name has a prefix that

represents its unique ID number in the ICAO Engine Emissions Databank.

Some emissions data used in the creation of the 1999 inventory had not been

published as of the writing of this report and was obtained directly from the

engine companies. These emissions engines are listed with the internal Boeing

prefix of the form "PREXXX_"

NASA/CR--2001-211216 63
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REPORT DOCUMENTATION PAGE FormApproved

OMB No. 0704-0188

Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources,

gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any Other aspect of this

collection of information, including suggestions for reducing this burden, 1o Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson

Davis Highway, Suite 1204, Arlington, VA 22202-4302, and to the Office of Management and Budget, Paperwork Reduction Project (0704-0188), Washington, DC 20503.

' 1. AGENCY USE ONLY (Leave b/ank) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED

October 2001 Final Contractor Report

4. TITLE AND SUBTITLE 5. FUNDING NUMBERS

Scheduled Civil Aircraft Emission Inventories for 1999:

Database Development and Analysis

6. AUTHOR(S)

Donald J. Sutkus, Jr., Steven L. Baughcum, and Douglas P. DuBois

7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

Boeing Commercial Airplane Group

P.O. Box 3707

Seattle, Washington 98124

9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES)

National Aeronautics and Space Administration

Washington, DC 20546-0001

WU -714-01-20-00

NAS 1-20341

Task 19

8. PERFORMING ORGANIZATION

REPORT NUMBER

E-13068

10. SPONSORING/MONITORING

AGENCY REPORT NUMBER

NASA CR--2001-211216

11. SUPPLEMENTARY NOTES

This report prepared for and managed by Glenn Research Center as a task of Langley Contract NAS 1-20341. Project

Manager, Chowen Wey, Aeronautics Directorate, NASA Glenn Research Center, organziation code 0300, 216--433-8357.

12a. DISTRIBUTION/AVAILABILITY STATEMENT

Unclassified - Unlimited

Subject Categories: 01 and 45 Distribution: Nonstandard

Available electronically at htto://eltrs._rc.nasa.eov/GLTRS

This publication is available from the NASA Center for AeroSpace Information, 301-621--0390.

13. ABSTRACT (Maximum 200 words)

12b. DISTRIBUTION CODE

This report describes the development of a three-dimensional database of aircraft fuel burn and emissions (NOx,

CO, and hydrocarbons) for the scheduled commercial aircraft fleet for each month of 1999. Global totals of

emissions and fuel burn for 1999 are compared to global totals from 1992 and 2015 databases. 1999 fuel burn,

departure and distance totals for selected airlines are compared to data reported on DOT Form 41 to evaluate the

accuracy of the calculations. DOT Form T-100 data were used to determine typical payloads for freighter aircraft

and this information was used to model freighter aircraft more accurately by using more realistic payloads.

Differences in the calculation methodology used to create the 1999 fuel burn and emissions database from the

methodology used in previous work are described and evaluated.

14. SUBJECT TERMS

Aircraft emissions; Emissions inventory; Atmospheric impact

17. SECURITY CLASSIFICATION

OF REPORT

Unclassified

NSN 7540-01-280-5500

18. SECURITY CLASSIFICATION

OF THIS PAGE

Unclassified

19. SECURITYCLASSIRCATION

OF ABSTRACT

Unclassified

!15. NUMBER OF PAGES

131

16. PRICE CODE

20. LIMITATION OF ABSTRACT

Standard Form 298 (Rev. 2-89)

Prescribed by ANSI Std. Z39-18

298-102