Sensors and Prognostics to Mitigate Bleed 

Air Contamination Events

2012 Progress Report

R.A. Overfelt, B.W. Jones*, S.M. Loo#, R.L. Haney, A.J. Neer, J.R. 

Andress, X. Yang, A. Zitova, B.C. Prorok, J.W. Fergus, A.L. Simonian,

Joshua Kiepert#, Michael Pook#and Mike Anderson#

National Air Transportation Center of Excellence for 

 Research in the Intermodal Transport Environment (RITE)

Airliner Cabin Environment Research Program

Auburn University

Auburn, AL 36849

*Kansas State University

Manhattan, KS 66506

#Boise State University

Boise, ID 83725

April 2012

Report No. RITE-ACER-CoE-2012-05
NOTICE

___________

This document is disseminated under the sponsorship

of the U.S. Department of Transportation in the interest

of information exchange. The United States Government

assumes no liability for the contents thereof.

___________

This work was funded by the U.S Federal Aviation Administration 

Office of Aerospace Medicine under 

Cooperative Agreement 10-C-RITE.

___________

This publication is available in full-text from 

the publications Web site of the 

National Air Transportation Center of Excellence for

Research in the Intermodal Transport Environment (RITE) at:

www.acer-coe.org
Technical Report Documentation Page

1. Report No. RITE-ACER-CoE-2012-TBD 2. Government Accession No. 3. Recipient's Catalog No.

4. Title and Subtitle 5. Report Date

Sensors and Prognostics to Mitigate Bleed Air Contamination Events -

2012 Progress Report

April 27, 2012

6. Performing Organization Code

7. Author(s) 8. Performing Organization Report No.

R.A. Overfelt, B.W. Jones*, S.M. Loo#, R.L. Haney, A.J. Neer, J.R. 

Andress, X. Yang, A. Zitova, W. Kilpatrick, B.C. Prorok, J.W. Fergus, 

A.L. Simonian, Joshua Kiepert#, Michael Pook#and Mike Anderson#

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS)

National Air Transportation 

Center of Excellence for

Research in the Intermodal 

Transport Environment

* Kansas State University

 Manhattan, KS 66506

# Boise State University

 Boise, ID 83725

Auburn University

Auburn, AL 36849

11. Contract or Grant No.

FAA Cooperative Agreement

10-C-RITE

12. Sponsoring Agency name and Address 13. Type of Report and Period Covered

FAA Office of Aerospace Medicine

800 Independence Ave., S.W.

Washington, DC 20591

14. Sponsoring Agency Code

15. Supplemental Notes

Work was accomplished under Public law 108-76.

16. Abstract

Most environmental control systems on commercial airliners receive fresh outside air from the 

bleed air systems of the compressors of the jet engines or from the auxiliary power units. Although 

outside air is clean and sterile during cruise conditions at flight altitudes, spurious air contamination 

events have been reported. Bleed air supplies can be contaminated during ground operations by deicing fluids entering the bleed air supply. Engine oil from worn mechanical seals and hydraulic 

fluids have also been reported to contaminate the bleed air supply. This document provides an 

interim Progess Report on a project that is evaluating the applicability of commercial air quality 

sensing technologies that may provide: (i) accurate, reliable, in-flight detection of bleed air 

contamination incidents, (ii) real-time determination of root causes of air contamination incidents to 

facilitate corrective or adaptive action in-flight, (iii) pre-incident detection and reporting to enable 

preventative maintenance, and (iv) post incident reporting and assessment of recorded information 

to enable appropriate corrective maintenance actions. 

 

17. Key Words 18. Distribution Statement

Sensors, aircraft, bleed air, contamination, data mining

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. No. of Pages 22. Price

Unclassified Unclassified

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
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CONTENTS

Nomenclature .................................................................................................................... ii

List of Tables ................................................................................................................... iv

List of Figures .................................................................................................................. iv

1.0 Background and Introduction ............................................................................................ 1

2.0 Review of Previous Research ............................................................................................ 4

2.1 Overview of Aircraft Bleed Air Supply Systems .................................................... 4

2.2 Thermal Degradation of Aircraft Working Fluids ................................................... 5

2.3 Summary of Gaseous Contaminant Targets for Detection ...................................... 7

2.4 Review of Commercial Gas Sensing Technologies ................................................ 8

3.0 Methods and Materials ..................................................................................................... 13

3.1 Evolved Gas Analysis by TGA/FTIR/MS ............................................................. 13

3.2 Sensor Evaluation Procedures ............................................................................... 14

3.2.1 Variable Pressure Commercial Sensor Test System .................................. 14

3.2.2 Tricresyl Phosphate Sensor Development and Testing ............................ 15

3.3 Data Mining of the FAA SDRS and NASA ASRS Databases .............................. 18

3.4 Wireless Sensor Network Field Test in an Aircraft Cabin Mock-up .................... 18

4.0 Results and Discussion .................................................................................................... 20

4.1 Characterization of Fumes from Oil Degradation Experiments ............................ 20

4.2 Commercial CO and CO2 Sensor Test Results ..................................................... 26

4.2.1 Commercial Sensors Responses to Calibration Gases .............................. 26

4.2.2 Commercial Sensors’ Responses to Fumes from Mobil Jet Oil II ............ 31

4.3 TCP Sensor Developments .................................................................................... 33

4.4 Particulate and Ultrafine Sensor Test Results ...................................................... 34

4.5 Wireless Sensor Network Field Test in an Aircraft Cabin Mock-up .................... 37

4.6 Data Mining of the FAA SDRS and NASA ASRS Databases............................... 38

5.0 Summary .................................................................................................................... 40

6.0 Acknowledgments ............................................................................................................ 41

7.0 References .................................................................................................................... 41
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Nomenclature

AIDS = Accident/Incident Data System

amu = atomic mass unit

APU = auxiliary power unit

ASHRAE = American Society of Heating, Refrigeration and Air-Conditioning Engineers

ASIAS = Aviation Safety Information Analysis and Sharing

ASRS = Aviation Safety Reporting System

BP = British Petroleum

C = Celsius

CFR = Code of Federal Regulations

CO = carbon monoxide

CO2 = carbon dioxide

DOT = Department of Transportation

DTA = differential thermal analysis

EPA = Environmental Protection Agency

eV = electron volts

FAA = Federal Aviation Administration

FAR = Federal Aviation Regulation

FTIR = Fourier Transform Infra-red

GC = gas chromatography

HVAC = heating, ventilating and air conditioning

IR = infrared

L = liter

M = molar

MEMS = microelectromechanical system

mg = milligram (10-3g)

min = minute

mL = milliliter (10-3L)

MOS = metal oxide semiconductor

MPa = mega-Pascal (106Pa)

MS = mass spectrometry

NAAQS = National Ambient Air Quality Standards

NASA = National Aeronautics and Space Administration

NDIR = non-dispersive infrared

O2 = oxygen

O3 = ozone

OSHA = Occupational Safety and Health Agency

PEL = permissible exposure limit

PID = photoionization detector

PM2.5 = particulate matter less than 2.5 X 10-6 m (2.5 microns) in diameter

PM10 = particulate matter less than 10 X 10-6 m (10 microns) in diameter

PMMA = polymethyl methacrylate

ppbv = parts per billion by volume

ppm = parts per million

ppmv = parts per million by volume
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SDRs = Service Difficulty Reports

SDRS = Service Difficulty Reporting System

SnO2 = tin oxide

SQL = Structured Query Language

TCP = tri-cresyl phosphate

TGA = thermogravimetric analysis

UV = ultraviolet

VOC = volatile organic compound

g/m3= 10-6g per cubic meter

L = 10-6L
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List of Tables

Table I Applicable Air Quality Standards: Ambient Air, Workplaces and Aircraft ........... 2

Table II Summary of Potential Bleed Air Contaminants ....................................................... 8

Table III Possible Bleed Air Contaminants and Potential Sensor Technologies ....................12

Table IV Jet Engine Oils: Peak Degradation Temperatures .................................................. 22

Table V Pressure Sensitivity of Commercial NDIR CO2 Sensors .........................................28

Table VI Summary of Particle Measurements ....................................................................... 36

Table VII Wireless Sensor Network Field Test – Series 2 Timeline ...................................... 37

List of Figures

Figure 1. Typical Airliner Bleed Air Supply System adapted from [12] ................................... 5

Figure 2. Modern aircraft turbofan jet engine: location of the compressor bleed air lines and

the bleed air pre-cooler [13] ...................................................................................... 5

Figure 3. TGA and DTA plots of pentaerythritol derivative in air [17]. The low temperature 

exothermic peak at about 350oC corresponds to low temperature oxidation producing 

smoke, low molecular weight hydrocarbons, CO and CO2. The higher temperature 

exothermic peak corresponds to oxidation of the remaining oil and charred oil to 

smoke, CO and CO2. ................................................................................................ 7

Figure 4. Schematic representation of commercial gas sensor detection technologies. 

(a) catalytic bead sensors typically used to detect inflammable gases; 

(b) conductometric sensors based upon metal-oxide semiconductor materials;

(c) 3-electrode configuration of electrochemical sensors;

(d) Schematic representation of photoionization detectors for detecting volatile 

organic compounds like benzene, ethanol, acetone, amines and ammonia; and

(e) two channel non-dispersive infra-red (NDIR) sensor often used for measuring 

CO2 in HVAC systems.

Schematics (a) and (d) adapted from [21] ............................................................... 10

Figure 5. Evolved gas analysis experimental arrangement used by NETZSCH Instruments 

Applications Laboratory. ......................................................................................... 13
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Figure 6. Experimental arrangement for testing commercial CO and CO2 sensors. ............. 14

Figure 7. Tricresyl phosphate sensor development system; (a) Schematic of the TCP/methanol 

solution gasification and hydrolysis into Cresol. (b) Schematic of the buffer washing 

of the Cresol from the alkaline catalyst and injection into the electrochemical detector. 

(c) Flow injection system and flow cell electrodes were used to detect samples 

containing cresol. .................................................................................................... 17

Figure 8. Kansas State University’s B767 Cabin Layout and Sensor Network Test 

Configuration ......................................................................................................... 19

Figure 9. Mass changes of BP274 oil sample as a function of exposure temperature. 

Sample size = 5.46 mg and 10oC/min heating rate in air. ...................................... 20

Figure 10. Time dependent mass loss and sample temperature data shown with mass 

spectrometry ion-currents for the following evolved gaseous species: (a) 2 amu – H2, 

12 amu - C, 17 and 18 amu – H2O, 44 amu – CO2; (b) 32 amu – CH3OH, 29 amu –

C2H5, 31 amu – CH2OH, 34 amu – H2S, 30 amu – C2H6, 43 amu – C3H7, and 

39 amu – C3H3. ..................................................................................................... 21

Figure 11. 3D plot of gas evolution FTIR absorbance data versus time for BP274 sample. ... 22

Figure 12. (a) FTIR scans of BP Turbo Oil 274(301oC), BP Turbo Oil 2380(305oC), Aeroshell 

Turbine Oil 560 (326oC) and Mobil Jet Oil II (307oC) at the indicated temperatures of 

greatest mass loss. The order of the data in each peak from each oil sample is 

indicated by the listing adjacent to the peak.

(b) Pure theoretical spectra from various possible components of the evolving gas 

mixture. The infrared bond excitation regions are also indicated. ......................... 24

Figure 13. Experimental and calculated FTIR spectra and predicted evolved gas compositions at 

the times indicated during thermal degradation of BP Turbo Oil 2380. See the text for

a discussion of the calculation procedures [32] ...................................................... 25

Figure 14. Laboratory FTIR and commercial CO2 NDIR sensor responses to introduction of 1340 

ppm CO2 in nitrogen at 0.67 atm pressure in the test chamber (10,780 ft equivalent 

altitude). Indicated time is from the beginning of introduction of the test gas. Test 

gas flow stopped at 200 min ................................................................................... 27

Figure 15. Theoretical pressure sensitivity (triangles) of the CO2 partial pressure calculated 

assuming ideal gas behavior compared to sensor indications from a typical NDIR 

CO2 sensor (diamonds: Johnson Controls CD-WA0). Note that the commercial 

sensor exhibits a higher sensitivity to pressure than expected from theoretical 

considerations ........................................................................................................ 28
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Figure 16. Experimental measurements of CO concentration in nitrogen (mg CO per m3) for 

the electrochemical sensors indicated versus known concentrations in pure 

nitrogen test gases at the following pressures: (a) 101.3 kPa, (b) 87.5 kPa and 

(c) 75.3 kPa [33] ..................................................................................................... 29

Figure 17. Repeated transient measurements of CO concentration in simulated air (80% nitrogen 

and 20% oxygen) for the electrochemical sensors indicated versus known 

concentrations in pure nitrogen test gases. [33] ...................................................... 30

Figure 18. Three repeated transient measurements of CO concentration (known value = 233 mg 

CO per m3) in simulated air (80% nitrogen and 20% oxygen) at 101.3 kPa for the 

electrochemical sensors indicated. The calculated transient test chamber 

concentration is shown by the dashed line. [33] ..................................................... 31

Figure 19. Bell jar: (a) before thermally degrading 1g of Mobil Jet Oil II;

(b) smoke-filled bell jar during degradation experiment [34].................................. 32

Figure 20. Plot of the change in CO concentration as a function of time as measured by the 

TGS5042 sensor (circles) and the FTIR (diamonds) and the mass (dashes) as a 

function of time. [34] ............................................................................................ 32

Figure 21. Plot of the CO2 concentration as a function of time as measured by the EE80 (circles) 

and the FTIR (diamonds) and the mass (dashes) as a function of time. [34] ........... 33

Figure 22. Calibration curve of amperometric results of TCP converted samples. Linear 

concentration range is from 5 ppb to 400 ppb in gas. Inset figure shows low 

concentration range (5 and 20 ppb). 0 ppb means sample was from methanol without 

TCP, acting as control sample. .............................................................................. 34

Figure 23. Kansas State University bleed air contamination simulator. .................................. 35

Figure 24. Particle size distributions at the indicated test temperatures as measured by APS .. 36

Figure 25. Wireless sensor network field test results for CO2 sensors ..................................... 38
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1.0 Background and Introduction

As originally granted in the U.S. Federal Aviation Act of 1958 (Public Law 85-726), regulatory 

authority over the operation of civil aircraft in the United States resides in the Federal Aviation 

Administration (FAA). The Occupational Safety and Health (OSH) Act of 1970 (Public Law 91-

596) was subsequently passed to ensure safe and healthful workplaces across the country. 

Federal agencies were allowed the authority to exercise jurisdiction over their own workers, and 

in 1975, the FAA asserted its jurisdiction over the safety and health of cockpit and cabin crews 

within operating civil aircraft (40 FR 29114, DOT). Since then, the FAA has been authorized to 

also protect the safety and health of passengers (49 USC 40101D and 40 USC 44701A).

The Federal Aviation Regulations (FARs) implement the FAA’s various safety and health 

requirements. Relevant aspects for the design and operation of commercial aircraft are contained 

in "Title 14 - Aeronautics and Space" of the Code of Federal Regulations (i.e., 14 CFR). Part 25 

of 14 CFR provides the aircraft design standards for transport category airplanes while Part 121 

of 14 CFR contains the operating requirements for air carriers and commercial operators. 

These regulations provide the FAA’s air quality standards with respect to aircraft cabin 

ventilation and pressure as well as maximum amounts of potential air quality contaminants. 

Airliner cabins are typically supplied outside air at rates of about 8-16 cfm per passenger and 

total air exchanges average approximately 15-25 cabin air exchanges per hour [1]. Table I 

compares the federal ambient air quality standards of the EPA with OSHA’s corresponding 

workplace standards and the FAA limits for aircraft. While 14 CFR 25.831 states that aircraft air 

must be free from harmful or hazardous concentrations of gases or vapors and 14 CFR 121.219 

notes that fuel fumes may not be present in the air, the FAA specifically only limits the 

following: (i) ozone, (ii) carbon monoxide and (iii) carbon dioxide. Even with specific 

allowable limits, there are no requirements for real-time monitoring of any of these contaminants

on an aircraft. 

Aircraft air supplies can be contaminated during ground operations by exhaust fumes from the 

engines of nearby aircraft or perhaps by de-icing fluids entering the outside air supply. One 

example of such an event occurred in December 2008 when de-icer fumes entered the cabin of an 

Alaskan Airlines plane. Seven crew members were sent to the hospital and 18 passengers were 

treated on-sight for eye irritation, dizziness, and nausea [2]. Although outside air is clean and 

sterile during cruise conditions at flight altitudes, spurious air contamination events have also 

been reported during flight [1, 3-5] due to engine oils and/or hydraulic fluids from worn 

mechanical seals or overfilled sumps. For example, a suspected hydraulic fluid leak in January 

2010 on a U.S. Airways flight is believed responsible for fumes entering the cabin of the 

airplane. Passengers and crew members complained of headaches and nausea [5]. Engine oil 

contamination of the air supply is particularly worrisome since some engine oils contain 1-5% 

tricresyl phosphate, a wear-reduction additive and potential health hazard [6,7]. Given the very 

high air flow rates and high temperatures in the upstream portion of the bleed air system, the 

specific nature and extent of potential decomposition reactions of engine oils and hydraulic fluids 

are largely unknown. In addition, the resulting nature and potential toxicity of any contaminants 

in the aircraft cabin from such events are highly speculative at the present time.
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Table I

Applicable Air Quality Standards: Ambient Air, Workplaces and Aircraft

Pollutant Ambient Standard

EPA NAAQS 40 CFR

Workplace Standard

OSHA PEL

Aircraft Standard

FAA - 14 CFR

Ozone 0.12 ppmv 1-hr

0.08 ppmv 8-hr

0.1 ppmv 0.1 ppmv*

0.25 ppmv**

Carbon Monoxide 35 ppmv 1-hr

9 ppmv 8-hr

50 ppmv 50 ppmv#

Carbon Dioxide NA 5000 ppmv 5000 ppmv#

PM10 150 g/m3

24-hr NA NA

PM2.5 65 g/m3

24-hr NA NA

* “0.1 parts per million by volume, sea level equivalent, time weighted average during any 3-hr 

interval” – 14 CFR 25.832

** “0.25 parts per million by volume, sea level equivalent, at any time above 32,000 ft” – 14 

CFR 25.832

# - 14 CFR 25.831

In 2009 Watson conducted an internal FAA review of records to ascertain the number of bleed 

air contamination events within the domestic air transportation system [8]. The FAA Aviation 

Safety Information Analysis and Sharing (ASIAS) system is composed of multiple databases 

including the Accident/Incident Data System (AIDS) and the Service Difficulty Reporting 

System (SDRS). The FAA review of the SDRS database covered January 1999 - November 

2008 and looked for event records that noted the following identification terms: “odor, smell or 

fume.” The search found 252 air contamination events where failures occurred in “airplane, 

engine or auxiliary power unit systems that may have caused tri-cresyl phosphate lubricants or 

phosphate ester hydraulic fluids or fuel or products of combustion of these fluids to enter the 

cockpit/cabin ventilation systems.” Of these 252 reported incidents, 33% were due to fuel leaks, 

23% were from propulsion engine oil leaks, 18% were from APU oil leaks, 13% were due to air 

cycle machine oil leaks and 13% were due to hydraulic fluid leaks. During this same period of 

time, there were 93,647,734 corresponding aircraft departures. Thus the event rate is of the order 

of 2.7 events per million aircraft departures. Watson noted the “trial-and-error” nature of 

maintenance diagnostics for such events. In several cases, multiple events were recorded in the 

SDRS database for the same aircraft before the problem was properly diagnosed and then 

satisfactorily resolved by maintenance crews. 
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Murawski and Supplee [9] examined the AIDS and SDRS databases over an 18 month period 

from January 2006 through June 2007. These researchers supplemented the federal databases 

with additional data from aircraft flight attendant labor union records as well as publically 

available newspaper reports. Their search looked for records containing the following complaint 

terms: fume, haze, mist, odor, smell or smoke. In addition, the search also included reports of 

engine oil maintenance issues that did not explicitly mention an air contamination issue. (It is 

unclear how the authors decided to include such records into their data set.) Murawski and 

Supplee concluded that 0.86 events occurred each day during the 18 month study period. With 

approximately 26,060 U.S. aircraft departures per day in 2006 [10], the event rate for 2006 was 

estimated to be of the order of 33 events per million aircraft departures. This finding is about an 

order of magnitude greater that that found by Watson [8].

In 2008, the American Society of Heating, Refrigeration and Air-Conditioning Engineers 

(ASHRAE) published ASHRAE Standard 161-2007, “Air Quality within Commercial Aircraft”

[10]. The standard discusses at length multiple possible sources of air contamination on aircraft 

and mandates installation of “one or more” sensors to detect “partly or fully pyrolized engine oil 

or hydraulic fluid” in the bleed air system. However, the standard does not define specifically 

what should be monitored nor how it should be monitored. Research is needed to establish that 

specific chemical air contaminants can be identified that are indicative of a bleed air 

contamination event and that sensor technologies can be developed to reliably detect such events.
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2.0 Review of Previous Research

2.1 Overview of Aircraft Bleed Air Supply Systems

An airliner environmental control system (ECS) is designed to (i) pressurize the cabin, (ii) 

regulate the temperature of the aircraft within acceptable limits of comfort and safety, (iii) 

provide fresh air to the occupants, (iv) flush gaseous air contaminants overboard and, to some 

extent, (v) control humidity in the air supply. Except for the new Boeing 787, most aircraft

environmental control systems are designed for constant volumetric flow during flight. In 

addition, the systems often utilize approximately 30-55% re-circulated air to maximize energy 

efficiency and receive fresh outside air from the bleed air systems of the compressors of the 

propulsion engines. Typical aircraft systems are not designed for multiple modes of operation 

(e.g., proportional control) and are either simply ON or OFF. Although the re-circulated air is 

often filtered with high-efficiency particulate filters that capture 99.7% of all particles larger than 

0.3 m, the reliance on re-circulated air in aircraft to meet ventilation requirements has been

criticized in the popular press. 

Figure 1 shows a schematic of a high-bypass fan jet engine bleed air system which is typical for 

commercial airliners [12]. Hot compressed air is taken from the engine compressor and cooled in 

the pre-cooler to temperatures around 175oC before being supplied to the environmental control 

system and other functions on the aircraft. Modern engines have two bleed air ports at different 

stages of the compressor in order to minimize excess temperature and pressure in the bleed air 

and to maximize engine energy efficiency. The actual temperature and pressure of the air exiting 

the engine compressor can be as high as 350oC and 1.2 MPa or as low as 185

oC and 0.21 MPa 

depending upon the phase of flight and engine operation [1]. If the aircraft is equipped with an 

ozone converter, the converter is normally located downstream of the pre-cooler but before the 

air is further cooled to cabin temperatures since most ozone converters work best at elevated 

temperatures. The pre-cooler is a cross-flow, air-to-air heat exchanger located in the engine 

pylon just aft of the fan and immediately above the engine compressor as shown in Figure 2 [13]. 

The pre-cooler uses ducted fan air to cool the hot bleed air from the compressor. The bleed air 

lines from the engine to the pre-cooler are not long so that the exposure times to the highest 

temperatures could be very brief. Chemical reaction kinetics are expected to play an important 

role in the reactions that occur with the contaminants in the bleed air. Most of the important 

chemical reactions associated with decomposition and possible pyrolysis of bleed air 

contaminants occur either within the engine compressor itself or in the hot section of the bleed 

air path between the compressor and pre-cooler.

The air from the bleed air system shown in Figure 1 is directed to the cabin through airconditioning packs where the air is further cooled in air cycle machines. The air from the airconditioning packs is then directed to the mixing manifold where it is mixed with cabin 

recirculation air for distribution throughout the aircraft.
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Figure 1. Typical Airliner Bleed Air Supply System adapted from [12].

 

Figure 2. Modern aircraft turbofan jet engine: location of the compressor bleed air lines and

the bleed air pre-cooler [13].

2.2 Thermal Degradation of Aircraft Working Fluids

Van Netten et al. [14-16] evaluated the thermal degradation of a number of hydraulic fluids and 

jet engine oils during heating on a ceramic hot plate. A thermocouple was used to monitor the 

temperature of the hot plate. Gases were evolved into a 250 L stainless steel chamber equipped 

Bleed Air

Lines

Location of

Pre-Cooler
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with a multigas monitor TMX-412 (Industrial Scientific Corporation, Oakdale, PA) to measure 

NO2, oxygen (O2), and carbon monoxide (CO). Additionally, a YES-204A monitor (Young 

Environmental Systems, Richmond, B.C., Canada) was also located in the chamber to measure 

temperature, relative humidity, and carbon dioxide (CO2) concentration [16]. Samples were 

heated to 525°C at a rate of 10°C/min and were then held at 525°C for 1 minute before cooling to 

room temperature. Monitoring of the ambient air began before the oil was inserted into the test 

chamber. Air samples were also retrieved from the chamber for subsequent analysis by gas 

chromatography/mass spectrometry (GC/MS).

Van Netten et al. [14] noted that Mobil Jet Oil 254 (Exxon Mobile Corp., Fairfax, VA) was 

initially dark blue in color at room temperature. White smoke began to form when the hot plate 

reached approximately 275°C and the oil turned a dark brown-orange color. Charring of the oil 

began at 400°C while white smoke continued to form. At 500°C, only some charred material 

remained on the oil sample holder. Gas concentrations of 102.5 ppm CO and 460 ppm CO2 were 

detected at 525°C [13]. Air sample results from GC/MS analysis indicated the presence of TCP 

isomers as well as volatile derivatives of pentane, hexane, and octane during degradation of 

Mobil 254 jet engine oil. 

Castrol 5000 jet engine oil (BP North America, Parsippany, NJ) was initially orange in color and 

this lubricant began producing white smoke at approximately 285°C. Darkening of the oil began 

at 310°C, charring was observed at 350°C and only charred brown material remained at the end 

of thermal degradation. The CO2 sensor measured a peak of 510 ppm CO2 while the CO sensor 

detected a maximum of 140 ppm CO during degradation of the Castrol 5000 [16].

Van Netten et al [14] noted that Exxon Turbo Oil 2380 (Exxon Mobile Corp., Fairfax, VA) 

began producing white smoke at about 275°C and darkening of the lubricant began at 300°C. 

Charring was observed at 310°C. At the end of the experiment only charred brown material 

remained. The CO2 sensor measured a peak of about 510 ppm CO2 and the CO sensor measured 

a peak of approximately 120 ppm CO [16]. 

Crane et al [17] also evaluated Exxon Turbo Oil 2380. These researchers utilized a custom-built 

combustion chamber to degrade the samples and analyze the evolved gas samples. The total 

volume of this chamber was only 12.6 L. Three milliliters of sample were placed in a semicylindrical quartz combustion boat located in a horizontal quartz tube furnace. The sample was 

continuously heated from room temperature until only charred material remained. Exxon 2380 

began producing a measurable amount of CO at around 306°C when the authors also noted an 

increase in visible smoke production. At 344°C, the CO concentration was measured as 5,000 

ppm. Only charred material remained when the temperature reached 350°C. The residual solid 

char continued to produce CO up to 530°C. Crane et al found that as the thermal decomposition 

temperature increased, the production of CO began earlier and the maximum measured values of 

CO in the chamber increased. When Exxon Turbo Oil 2380 was thermally degraded at 600°C, 

the authors reported a much higher CO level of 17,000 ppm CO. 

Bartl et al [18] evaluated thermal degradation of pentaerythritol derivatives (the base component 

of jet engine oils) using thermogravimetric analysis (TGA) and differential thermal analysis 
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(DTA). These researchers heated 10 mg of pentaerythritol from room temperature to 1000°C at 

10°C/min in air. Figure 3 shows typical TGA and DTA data. The sample began to lose weight at 

approximately 275°C (which is roughly the temperature van Netten et al [14] began seeing 

visible smoke generation). The DTA data indicates sample heating due to exothermic reactions 

(i.e., burning) in the oil as the oil degrades. The first peak at approximately 350°C corresponds to 

a lower temperature oxidation reaction in which low molecular weight hydrocarbons were 

produced. The second higher temperature peak at about 570°C was likely due to oxidation of any 

remaining oil and charred products to CO and CO2. This can be roughly associated with the

smoke, CO and CO2 evolution at 525°C reported by van Netten et al[14].

Figure 3. TGA and DTA plots of pentaerythritol derivative in air [17]. The low temperature 

exothermic peak at about 350oC corresponds to low temperature oxidation producing 

smoke, low molecular weight hydrocarbons, CO and CO2. The higher temperature 

exothermic peak corresponds to oxidation of the remaining oil and charred oil to 

smoke, CO and CO2. 

2.3 Summary of Gaseous Contaminant Targets for Detection

Although Ref.[1] notes a wide range of gaseous contaminants of potential concern in aircraft 

including human bioeffluents (e.g., ethanol, acetone), cosmetics and perfumes (e.g., benzene, 

limonene, toluene, xylene, etc.) and dry cleaning agents (e.g., tetrachloroethene), the focus of this 

work is on those air contaminants that might arise from inadvertent malfunctions connected with 
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the bleed air supplies from either the aircraft engine or the auxiliary power unit (APU). As noted 

in Section 2.2 and summarized in Table II below, the principal contaminants of the aircraft bleed 

air supply could include (1) aerosolized droplets of jet engine or APU lubricating oil and (2) 

partially or fully pyrolized by-products of combustion of the working fluids. A number of 

approaches exist for monitoring of environmental air quality on aircraft to detect contamination 

of the bleed air supplies. Sensors could be located in either (i) the passenger cabin, (ii) along the 

bleed air supply path between the pre-cooler and the air conditioning packs, or (iii) between the 

air conditioning packs cooling the bleed air and the mixing chamber where the bleed air is mixed 

with the cabin recirculation air. The following section reviews the abilities of commercially 

available sensor technologies to detect these potential air contaminants.

Table II

Summary of Potential Bleed Air Contaminants

Potential Bleed Air

Contamination Event

Probable

Contaminant

Engine oil leak producing aerosolized 

droplets of oil in the engine 

compressor 

 Very fine mist of engine oil aerosols 

 Small amounts of carbon monoxide 

(CO) and carbon dioxide (CO2)

Partially pyrolized jet engine oil  Very fine mist of engine oil aerosols 

 Carbon monoxide (CO)

 Carbon dioxide (CO2)

 Misc. unburned hydrocarbons

 Ultrafine smoke particles

Fully pyrolized jet engine oil  Carbon monoxide (CO)

 Carbon dioxide (CO2)

 Ultrafine smoke particles

2.4 Review of Commercial Gas Sensing Technologies

A rapidly increasing body of literature exists concerning environmental gas sensors that generate 

electrical signals (i.e., voltages or currents) in response to the presence of a contaminating analyte 

in air. Typical contaminants of interest include CO2 in the air supplies of office buildings, CO 

from the exhaust of combustion processes in garages and other enclosed spaces and a wide 

variety of process gases in numerous industrial applications. Scientists and engineers worldwide 

are searching for ways to improve the intrinsic responses of the basic sensing materials. 

However, commercial sensor systems contain not only the discrete sensor element itself, but also 

the various technologies needed to transport the gaseous contaminant to the sensing material as 

well as the required electronics needed to supply power plus acquire, condition and transmit the 
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sensor signals. A brief review is presented below for commercially available air quality sensors

that might be applicable to aircraft air quality sensing. This review does not include either very 

advanced sensing technologies that have yet to demonstrate significant market acceptance (and 

corresponding user experience) or expensive and labor intensive laboratory-class sensing 

techniques that would not likely find acceptance for routine operation within the aviation 

community.

Catalytic-bead sensors have been used commercially for many years to detect the presence of 

combustible gases. Early devices used a heated platinum wire to initiate combustion of the gas to 

be detected. The sensor electronics compared the resulting resistivity increase in the sensing 

platinum wire (due to increased temperature from combustion) to a reference wire that had been 

treated to prevent combustion. The sensor wire and the reference wire were connected in a 

Wheatstone bridge circuit to facilitate comparison. Sensor response to the target gas is enhanced 

in modern designs that utilize specially formulated catalyst containing porous beads around the 

heated platinum wires [19]. A schematic of a catalytic bead sensor is shown in Figure 4(a). 

Unfortunately, high operating temperatures are required for catalytic sensors and the devices are 

not particularly selective in their response to various combustible gases [20].

Metal-oxide semiconductor (MOS) sensors rely upon ionic absorption of the analyte’s gaseous 

molecules to induce either a current or a voltage in the sensor material. See Figure 4(b). Two 

fundamental types of metal-oxide conductivity sensors exist: (1) n-type (e.g., tin oxide or zinc 

oxide) that, after reaching equilibrium with the oxygen in the air, react with reducing gases like 

CO to release electrons and increase the conductivity of the oxide and (2) p-type (e.g., nickel 

oxide or cobalt oxide) that react with oxidizing gases like O2 , NO2 or O3 to consume electrons --

producing holes (i.e., charge carriers) and also increase the conductivity of the oxide [22]. 

Selectivity of the sensor to specific gases of interest can be improved by careful selection of the 

sensor alloy dopant, the operating temperature of the sensor material and gas filtration techniques 

[22]. Unfortunately, like catalytic bead sensors, high operating temperatures are also required for 

solid-state sensors.

Electrochemical sensors can be designed as either current generating (amperometric) or voltage 

generating (potentiometric) in response to the presence of the gas constituent to be measured [23-

25]. In the case of a potentiometric sensor, the gas of interest establishes an electrochemical 

potential, which generates an open circuit voltage relative to a reference electrode. In the case of an 

amperometric sensor, as shown in Figure 4(c), a reducing (or oxidizing) gas of interest is oxidized 

(or reduced) at the working electrode. The magnitude of the current generated by this oxidation (or 

reduction) reaction is related to the concentration of the gas of interest. Solid polymer electrolytes 

emerged in the middle 1970s to alleviate some of the maintenance issues associated with aqueous 

electrolyte solutions [23]. In addition, ceramic oxide electrolytes are being investigated for 

monitoring the gaseous by-products of combustion [24,25].
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(a) (b)

(c) (d)

(e)

Figure 4. Schematic representation of commercial gas sensor detection technologies. 

(a) catalytic bead sensors typically used to detect inflammable gases;

(b) conductometric sensors based upon metal-oxide semiconductor materials;

(c) 3-electrode configuration of electrochemical sensors;

(d) schematic representation of photoionization detectors for detecting volatile 

organic compounds like benzene, ethanol, acetone, amines and ammonia; and

(e) two channel non-dispersive infra-red (NDIR) sensor often used for measuring 

CO2 in HVAC systems.

Schematics (a) and (d) adapted from [21]
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As shown in Figure 4(d), photoionization detectors (PIDs) use light from an ultraviolet (UV) 

lamp to ionize gas molecules with ionization potentials less than the UV energy produced by the 

lamp [26]. Detector electrodes in PIDs are biased with a DC voltage and collect the free electrons 

from the ionized molecules. Detector current flows are thus proportional to the amount of the 

ionizing species. Many photoionization detector lamps use krypton gas in the UV lamp. Such 

lamps emit UV energy at 10.6 eV and can detect VOCs such as benzene, ethanol, acetone, 

amines, ammonia and aromatic compounds. The principal disadvantage of photoionization 

detectors resides in the requirement that the sensor window be kept clean to ensure consistent 

performance.

Dedicated infrared sensors often use simple heated filaments to emit broadband IR radiation 

through the gas mixture of interest [21]. The radiation is then filtered to a narrow bandwidth IR 

beam for measurement by an IR sensor. Figure 4(e) shows one configuration that uses a single

lamp, dual wavelength design where the second wavelength/detector combination monitors a 

wavelength expected to exhibit no absorption in air. This measurement is thus independent of 

the gas mixture and provides a reference signal for sensor compensation due to variations in lamp

intensity and light scattering from particulates. The narrowly filtered bandwidth of these nondispersive infrared (NDIR) sensors does not create complete spectral fingerprints of gases but 

instead enables measurement of the absorption of the narrow beam at a specific wavelength. 

According to Beers law, the amount of IR absorbed is proportional to the amount of the gas 

species in the detection pathlength. The actual wavelength can be selected and tuned to a 

specific and well-behaved IR absorption peak for a specific gas of interest. The principal 

disadvantages of NDIR sensors are in the sensitivity of the optical components to impact and 

vibration as well as maintenance of the cleanliness of the sensor windows for reliable operation.

NDIR sensors are finding increasing utilization in building HVAC systems to monitor levels of 

CO2 in indoor air and modulate the intake of fresh outdoor air. This application is often referred 

to as Demand Controlled Ventilation and enables building owners to reduce the energy costs 

associated with over ventilating buildings during times of low occupancy. Commercial CO2

sensors are available from a number of companies and Shrestha and Maxwell [27-30] 

investigated the abilities of commercial NDIR sensor systems to accurately and consistently 

evaluate the level of CO2 under a range of environmental conditions including humidity, 

temperature and pressure. These researchers found wide performance variations among sensors 

of different manufacturers and sometimes even between identical sensor systems from the same 

manufacturer. Of particular concern was the automatic baseline adjustment algorithms 

incorporated in some sensor systems. This algorithm could introduce bias into the readings as 

the sensor systems attempts to automatically correct sensor readings to the expected value of 400 

ppm CO2 during the overnight periods of building vacancy. Shrestha and Maxwell note that 

NDIR CO2 sensor systems should be individually calibrated prior to being placed into service. 

Periodic recalibrations would then appear to be warranted.

Table III summarizes the possible bleed air contaminants and the commercial sensor technology 

typically applied to detect and monitor the various contaminants in various non-aerospace 

applications. 
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Table III

Possible Bleed Air Contaminants and Potential Sensor Technologies

Possible Bleed Air Contaminant Commercial

Sensor Technology

 Engine oil aerosols 

 Ultra-fine smoke particles

 Carbon Monoxide (CO)

 Carbon Dioxide (CO2)

 Misc. unburned hydrocarbons

 Light scattering photoelectric detectors 

(dia>0.5 m) or ionization detectors 

(dia<0.5 m) depending upon the 

aerosol/particle size distribution

 Electrochemical cell sensor with 

selectivity optimized for CO

 Non-dispersive Infrared (NDIR) 

sensor optimized for CO2)

 Catalytic bead sensor OR 

photoionization detector depending 

upon the specific hydrocarbon(s) to be 

detected
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3.0 Methods and Materials

3.1 Evolved Gas Analysis by TGA/FTIR/MS

The Thermoanalytical Section of the NETZSCH Instruments Applications Laboratory

(Burlington, MA) examined four common jet engine oil samples supplied by Auburn University. 

The temperature-dependent mass changes and evolved gases were analyzed using the NETZSCH 

TG 209 F1 Iris® thermogravimetric analyzer (TGA) coupled to a BRUKER Optics FTIR 

TENSORTM and a NETZSCH QMS 403 Aeolos mass spectrometer [31]. A schematic of the 

experimental system is shown in Figure 5. The NETZSCH TG209F1 Iris® instrument can 

measure mass changes from 20°C to 1000°C with a resolution of 0.1μg. The heating rate is 

variable from 0.1 K/min and 100 K/min. The evolved gases were analyzed with a NETZSCH 

QMS 403 Aeolos system simultaneously coupled to the NETZSCH TG209F1 Iris® by means of 

a transfer line which was kept at a constant temperature of 250°C. The mass spectrometer of the 

QMS 403 allows detection of mass numbers between 1 and 300 amu. The evolved gas analysis 

was performed using the combined TGA-MS MSÒ-Windows analysis software package.

The oil samples and masses investigated were: BP Turbo Oil 274 (5.46 mg), BP Turbo Oil 2380

(5.01 mg), Aeroshell Turbine Oil 560 (5.65 mg) and Mobil Jet Oil II (5.22 mg). The samples 

were heated in platinum crucibles in air from room temperature to 650oC at 10oC/min.

Figure 5. Evolved gas analysis experimental arrangement used by NETZSCH Instruments 

Applications Laboratory.
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3.2 Sensor Evaluation Procedures

3.2.1 Variable Pressure Commercial Sensor Test System

The experimental setup utilized to evaluate commercial CO and CO2 sensors consisted of four

major modules as illustrated in Figure 6.

Figure 6. Experimental arrangement for testing commercial CO and CO2 sensors.

The Calibration Gas Control Module is shown in Figure 6(a) and is responsible for the control of 

pressure, flow rates and mixing of inert carrying gases (typically nitrogen or nitrogen with 20% 

oxygen) as well as the contaminant test gases of interest (e.g., CO, CO2). The pressure setting 

within the system allows for testing of sensors at pressures representative of altitudes that are 

encountered in the airplane cabin environment. The gas lines in the system are rated for vacuum 

pressures of 15 inches of mercury (380 mm Hg) or about 50% of atmospheric pressure (50.5 

kPa), which corresponds to altitudes up to 12,000 feet (3,700 meters). The flow meters allow 

precise control of the gases and allow custom mixing ratios for sensor performance testing.

The Commercial Sensor Analysis Module shown in Figure 6(b) is an enclosed, vacuum-sealed, 

PMMA chamber, which has a total volume of 42.4 liters. With this module, an environment 

replicating the low pressure airplane cabin can be maintained to test commercial sensor 

performance in regards to detection of the gases of interest.
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The Oil Degradation Module, shown in Figure 6(d), includes a microbalance from which 1g oil 

samples were suspended into a cylindrical heater. The Scientech SM124D (Boulder, CO) 

microbalance measured the mass of the sample within ±0.6 mg over the experimental mass 

range. The temperature of the oil sample was measured within ±2 ̊C over the experimental 

temperature range (room temperature to 600 ̊C). The Watlow ceramic fiber heater (Chicago, IL) 

has a operating range up to 2200 ̊C. The microbalance-heater assembly was encapsulated by a 50 

L bell jar to contain the evolved gases. Room temperature air from outside the bell jar was 

provided within the upper region of the bell jar (adjacent to the microbalance) by two plastic 

tubes, approximately 12 mm in diameter. The supply outside air was forced through a 12 mm 

hole below the balance and down through the heater past the hanging crucible assembly. In 

addition, a vacuum pump connected to the FTIR pulled the air from the bell jar, at a rate of 

11,600 sccm via a tube that connects both the sensor chamber and the FTIR to the thermal 

degradation system. See Figure 6(c). This prevented any evolved gases from migrating into the 

top of the bell jar and affecting the performance of the microbalance. The thermal degradation 

system was enclosed by a custom built fume hood to contain any possible leaks in the system. 

Once the evolved gases passed through the sensor chamber and the FTIR, they were removed by 

the building exhaust.

The FTIR Gas Analysis Module shown in Figure 6(c) was used as the standard to verify the gas 

composition of various concentrations of test gases used for evaluating sensor performance. This 

module contained a Spectrum GX FTIR System (Perkin Elmer, Shelton, CT, USA), as well as an 

M-5-22-V variable pathlength long-path gas cell (Infrared Analysis, Inc., Anaheim, CA, USA). 

The optical path is folded in a total volume of 8.5 liters, while the cell path length was held 

constant at 2.24 m. The analyzed wavenumber range has typically varied from 600 cm-1to 4000 

cm

-1 with a spectral resolution of 0.5 cm-1

. The IR source was produced by a temperature 

stabilized wire coil that operates at 1350 K. The material for the cell windows in the variable 

pathlength long pass gas cell are potassium chloride (KCl) and are 4 mm thick. The detector for 

the IR beam is a fast recovery deuterated triglycine sulfate (FR-DTGC) module.

3.2.2 Tricresyl Phosphate Sensor Development and Testing

TCP samples were converted by alkaline hydrolysis to cresol which enables application of 

standard electrochemical detection techniques. A schematic of the process is shown in Figure 

7(a, b). 

Reagents and alkaline catalyst for TCP hydrolysis: Alkaline powder catalyst was prepared by

mixing sodium hydroxide and alumina (1:10 wt) in ethanol while stirring for 1h until all sodium 

hydroxide was dissolved. The mixture was then dried in a vacuum chamber and the dried powder 

heated to 100oC before use. 100 mg of powder was packed into a 20 μL beveled pipette filter tip 

to form the hydrolyzing column. 

P-cresol (Acros Organics, NJ, 99+%) was dissolved in 0.2 M Na2HPO4/0.2 M KH2PO4 buffer 

(pH = 6.67, NaCl = 10 mM) to establish a sensor calibration standard. Deionized water used was 

obtained from a Millipore Direct-Q water purification system (resistivity 18 MΩcm-2). 
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Electrodes and Sensor: All amperometric experiments were performed with CH Instruments 

(CH1910B) Bi-Potentiopstat and duplicated with a handheld potentiostat (Palm-Sens). A desktop 

computer and pocket PC were used to collect the respective data. The handheld potentiostat 

communicated wirelessly with the Pocket PC via Bluetooth®. Flow injection analysis (FIA) was 

carried out using cell electrodes, one of which includes a glassy carbon working electrode (2 mm 

dia.), and another of which includes a stainless steel auxiliary electrode and Ag/AgCl reference 

electrode (BASi, IN). A coating solution was applied to the Ag/AgCl reference electrode before 

detection as per instructions from the manufacturer. The working electrode was polished with 

alumina powder (1, 0.3, and 0.05 μm in order). 10 mM NaCl was used to maintain the potential 

of the reference electrode. A switch injection unit (Valco Instruments Co. Inc) was used with a 

50 μL sample loading loop. The flow rate was maintained at 200 μL/min by using a single 

syringe pump (KD Scientific, MA).

TCP sampling from methanol solutions or oil samples: Since TCP samples in a gas phase are 

not readily available, it was necessary to prepare such samples for the system calibration. The 

stock TCP solution (0.002 M) was prepared in methanol and diluted to obtain TCP samples with 

concentrations of interest. 0.4 mL of each TCP sample solution was then gasified by 5 min of N2

(gas) blowing, followed by 5 min of N2 blowing concurrent with 220oC heating in a silicon oil 

bath. See Figure 7(a). The flow rate of N2 was maintained at 1.1 L/min. Because of the low 

saturated vapor pressure of TCP at room temperature (less than 10-7atm), heating was necessary 

to completely gasify the TCP to be blown through the alkaline catalyst column and converted to 

cresol. 

Engine oil samples were prepared by dissolving the samples into methanol. The oil samples 

were sampled with the same processes as the TCP the samples. BP274 jet engine oil does not

contain TCP while BP2380 includes 1-5% TCP [16].

After collecting each gas sample for 10 min, the catalyst column was flushed with 3 mL of 

phosphate buffer (0.2 M Na2HPO4/0.2 M KH2PO4) as shown schematically in Figure 7(b). 

0.01M NaCl was added into the buffer to maintain the potential of the reference electrode. The 

converted TCP samples were then injected into the buffer solution and the cresol was detected by 

electrochemical sensors as shown in Figure 7(c). The TCP sampling process was performed

automatically utilizing electronic relays, valves, pumps, and tubes.
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 (c)

Figure 7. Tricresyl phosphate sensor development system; (a) Schematic of the TCP/methanol 

solution gasification and hydrolysis into cresol. (b) Schematic of the buffer washing 

of the cresol from the alkaline catalyst and injection into the electrochemical detector. 

(c) Flow injection system and flow cell electrodes were used to detect samples 

containing cresol. 
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3.3 Data Mining of the FAA SDRS and NASA ASRS Databases

The FAA Service Difficulty Reporting System (SDRS) database provide a web application frontend that allows users to query the underlying database. However, the provided web application 

interface was too cumbersome for quickly and easily running (i) multiple queries and/or (ii) 

complex queries. Thus it was decided to download the entirety of the database and create a local 

copy that could be quickly and easily mined for associations. With privileged access to the 

SDRS data, the entirety of the database was then downloaded in the form of multiple, tabseparated value files. A local copy of the database enabled many queries to be processed without 

using excessive Internet bandwidth or potentially tying up the database server with our large 

queries. Another benefit of having a local copy of the data was that complex queries were 

possible that were not limited to solely what the web application interface allowed. A script was 

written to parse the data from the files, eliminate errors associated with the transfer, and then 

store the data into an SQLite database. SQLite was chosen because it is very easy to use, is 

reasonably fast, and creates a single database file that can be easily shared.

The data in the NASA ASRS (Aviation Safety Reporting System) database was all collected via 

the available public web application interface, but was downloaded and parsed in a similar 

manner to the FAA SDRS database.

3.4 Wireless Sensor Network Field Test in an Aircraft Cabin Mock-up

On August 2nd 2011, Boise State University deployed a custom wireless sensor network within 

Kansas State University’s Boeing 767 mock-up cabin section to verify the feasibility of capturing 

measurements of highly dynamic environmental conditions present in aircraft bleed air systems 

and airliner cabins. The sensor network consisted of 12 wireless sensor units and a base station. 

Each wireless sensor unit was configured to measure four environmental conditions: CO2, 

temperature, humidity, and atmospheric pressure. The 12 sensor units were uniformly distributed 

across the cabin such that each seating section had sensor modules located at 100” intervals down

the length of the cabin. This configuration resulted in a 76” spacing laterally between modules. 

The modules were placed on the top of the seatbacks to provide proximity to seated passenger 

head level. Figure 8 shows a diagram of the sensor module locations within the cabin section.

Two test series were performed. The first test series (Series 1) primarily tested humidity 

dispersion and provided a basic test of the system. During Series 1, humidifiers were located in 

two different areas within the cabin (P1 and P2 in Figure 8). The other three environmental 

parameters (CO2, temperature, and pressure) were also acquired during the humidity testing. The 

second test series (Series 2) primarily tested CO2 dispersion through the cabin. Unlike the 

humidity sources used in Series 1, the CO2 injection point remained fixed across all test runs as 

the CO2 injection point was not adjustable in the cabin system.
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Figure 8. Kansas State University’s B767 Cabin Layout and Sensor Network Test Configuration
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4.0 Results and Discussion

4.1 Characterization of Fumes from Oil Degradation Experiments

Figure 9 shows the change in sample mass as a percentage of the total (TG) and the mass change 

rate (DTG) as the sample heated from room temperature to 650oC. In addition the GramSchmidt reduced data set shows essentially the total integrated intensity of the FTIR spectra and 

peaks or shoulders in the Gram Schmidt curve can be interpreted as the appearance of new 

species in the evolved gas mixture. The TG data show mass loss beginning at around 200oC with 

the rate of maximum mass loss occurring at 300.2oC (DTG). The peak in gas evolution is shown 

to occur at 300.8oC in the Gram Schmidt data in close agreement with the sample mass loss data. 

 Figure 9. Mass changes of BP274 oil sample as a function of exposure temperature. 

Sample size = 5.46 mg and 10oC/min heating rate in air. 

(TG=mass change, DTG=mass change rate)

The BP Turbo Oil 274 mass spectrometry ion-current curves for H2 (2 amu), H2O (17; 18 amu) 

and CO2 (12; 44 amu) are plotted in Figure 10(a) along with the already analyzed TG data. All 

the species evolve as a sharp peak at 293.5°C. Figure 10(b) shows the mass spectrometry ioncurrent curves for C2H5 (29 amu), C2H6 (30 amu), CH2OH (31 amu), CH3OH (32 amu), H2S (34 

amu), C3H3 (39 amu) and C3H7 (43 amu) along with the already analyzed TG data. C2H6, C3H3

and C3H7 evolve as a sharp peak at 293.5°C, while the signals for all the other fragments and 

molecules show a broad asymmetric peak.
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(a) 

(b) 

Figure 10. Time dependent mass loss and sample temperature data shown with mass 

spectrometry ion-currents for the following evolved gaseous species: (a) 2 amu – H2, 

12 amu - C, 17 and 18 amu – H2O, 44 amu – CO2; (b) 32 amu – CH3OH, 29 amu –

C2H5, 31 amu – CH2OH, 34 amu – H2S, 30 amu – C2H6, 43 amu – C3H7, and 

39 amu – C3H3.
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Additional experiments with BP Turbo Oil 2380, Aeroshell Turbine Oil 560 and Mobil Jet Oil II

yielded similar results for peak degradation temperatures and evolved gases. The peak 

degradation temperatures are summarized in Table IV and show that all the oils exhibited the 

greatest mass losses at temperatures ranging from 301-325 oC. 

Table IV

 Jet Engine Oils: Peak Degradation Temperatures

Jet Engine Oil Peak Degradation

Temperature

BP Turbo Oil 274 301 oC

BP Turbo Oil 2380 305 oC

Aeroshell Turbine Oil 560 326

oC

Mobil Jet Oil II 307 oC

A 3-D plot of FTIR spectra vs. time for the BP Turbo Oil 274 sample is shown in Figure 11. The 

FTIR spectra clearly show the peak evolution of various hydrocarbons and CO2 occurs at about 

28 minutes in agreement with the mass loss results shown in Figure 9(a). 

 

 Figure 11. 3D plot of gas evolution FTIR absorbance data versus time for BP274 sample. 
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The FTIR spectra obtained at the time of greatest mass loss for each of the four oils investigated

are shown in Figure 12(a). Each of the oils exhibited similar peaks with minor differences in 

relative peak heights amongst the four jet engine oils investigated. Principal components 

analysis was performed on the experimental FTIR data to determine the number of components 

most likely present in the evolved gas species from the heated engine oil samples. These results 

were then compared to the mass spectrometry data for verification and to determine the probable 

identity of the gaseous components being evolved during thermal degradation. 

Figure 12(b) shows pure component spectra from the following possible constituents of the 

evolving gaseous mixture: methanol, formaldehyde, carbon monoxide, carbon dioxide and water. 

Note the strong and well identifiable CO2 peak between wavenumbers of 2300-2400 cm-1. There 

is no overlap between this peak and other possible species. CO2 exhibits another peak between 

wavenumbers of 600-700 cm-1. CO exhibits FTIR absorbance peaks between wavenumbers of 

2050-2250 cm-1 with minimal overlap from other possible species. Peaks for methanol (CH4O) 

appear at 2800-3050 cm-1as well as 1000-1100 cm-1. Formaldehyde (CH2O) absorption peaks 

occur from 2700-3000 cm-1and also from 1700-1800 cm-1. Water is a strong IR absorber over a

wide range of wavenumbers from 1400-2000 cm-1as well as 3500-3950 cm-1. Overlap of the 

absorption peaks due to water and methanol with formaldehyde’s absorption peaks complicates 

evolved gas analysis when these three species may all be simultaneously present.

Principal components analysis was also applied to the FTIR spectra of gases evolved as a 

function of time for BP turbo Oil 2380 thermally degraded in the Oil Degradation Module 

shown in Figure 6(d). Initial calculations utilized simulation data sets created from pure 

component database spectra for comparison against the evolving gas mixtures. After using 

principal components regression analysis to determine likely concentrations for methanol 

(CH4O), formaldehyde (CH2O), carbon dioxide (CO2), carbon monoxide (CO) and water vapor 

(H2O) of the BP Turbo Oil 2380 time evolved samples, reconstructed prediction FTIR spectra 

were calculated. These reconstructed spectra were then compared to the experimentally obtained 

FTIR data as shown in Figure 13(a-d) for elapsed times of 10 min., 30 min., 60 min. and 90 min. 

The RMSE between the predicted and actual spectra for each of the time-evolved spectra were 

calculated to be 2.7%, 8.4%, 9.2%, and 9.0% for 10 min., 30 min., 60min., and 90 min., 

respectively. The average RMSE between the predicted and actual spectra for all 20 of the time

evolved spectra was found to be 7.5%. The principal components analysis indicated that the 

following species were present in varying amounts: water vapor (H2O), methanol (CH4O), 

carbon monoxide (CO), carbon dioxide (CO2) and perhaps formaldehyde (CH2O) [32]. 

Additional work is planned using gas chromatography – mass spectrometry to further investigate 

and confirm these results – especially the findings regarding the presence of methanol and 

perhaps formaldehyde.
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(a) 

(b)

 Figure 12. (a) FTIR scans of BP Turbo Oil 274(301oC), BP Turbo Oil 2380(305oC), 

Aeroshell Turbine Oil 560 (326oC) and Mobil Jet Oil II (307oC) at the indicated 

temperatures of greatest mass loss. The order of the data in each peak from each 

oil sample is indicated by the listing adjacent to the peak.

(b) Pure theoretical spectra from various possible components of the evolving gas 

mixture. The infrared bond excitation regions are also indicated.
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Figure 13. Experimental and calculated FTIR spectra and predicted evolved gas compositions at the times indicated during 

thermal degradation of BP Turbo Oil 2380. See the text for a discussion of the calculation procedures [32].
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4.2 Commercial CO and CO2 Sensor Test Results

As noted previously, NDIR-based commercial sensor technologies exist for detecting CO2 in the 

air supplies of office buildings. In addition, electrochemically-based technologies are available 

for assessing the presence of CO from the exhaust of combustion processes. Commercial sensor 

systems contain all the various technologies needed to transport the test gas to the actual sensing 

element as well as the required electronics needed to supply system power plus acquire, 

condition and transmit the resultant sensor response signals. Sensor technologies developed for 

office buildings or garages cannot be applied to aircraft applications without being thoroughly 

vetted to ensure reliable performance in conditions representative of the aircraft application.

The accuracy and precision (sensitivity and detection limits) as well as calibration methods for 

NDIR CO2 sensors and electrochemical CO sensors have been investigated using premixed

calibration gases over a range of pressures representative of aircraft operation (Section 4.2.1). In 

addition, typical CO2 and CO sensor responses due to fumes generated from thermal degradation 

of jet engine oil are also presented (Section 4.2.2). Issues regarding sensor selectivity, life, size, 

weight, cost, etc. will be explored in future work.

4.2.1 Commercial Sensors Responses to Calibration Gases

NDIR CO2 sensors: Many commercially available NDIR CO2 sensor technologies utilize

specialized drying techniques to remove water vapor from the air. Typical sensors utilize the 

4.26 m infrared absorption band (wavenumber = 2349 cm-1) of CO2 for the measurement since 

that wavelength provide the least interference with the absorption bands of other gases. In 

addition, many commercial systems also utilize an automatic background calibration technique

that presumably avoids having to actually calibrate the sensors. This method appears reasonable 

for office buildings that are essentially unoccupied for long periods of time (e.g., overnight, 

weekends). Since CO2 is generated by building occupants, the air in office buildings should 

refresh during extended unoccupied periods and return to the 400 ppm CO2 level that is typical of 

the overall atmosphere. The electronics in sensors that attempt to exploit this 400 ppm nighttime CO2 level automatically adjusts the calibration of the sensor to this periodically measured 

low level of CO2. However, such “calibrations” could prove problematical for sensors on aircraft 

that do not experience such repetitive low levels of CO2.

Figure 14 shows a typical set of commercial NDIR CO2 sensor responses as well as the FTIR 

measurement during exposure to a calibration test gas of nitrogen and carbon dioxide. The 

overall test chamber pressure was maintained at 0.67 atm (10,780 ft equivalent altitude) and 1340 

ppm CO2. The responses of the sensors and the FTIR appear to track the slowly varying CO2

level in the test chamber. Some sensors (A6 and A7) measured higher levels of CO2 than the test 

gas composition (1340 ppm at 0.67 atm) while the other sensors indicated lower levels of CO2

than expected. The FTIR measurement agreed most closely with the actual composition of the 

calibration test gas. Additional tests of these sensors indicated very repeatable responses over the 

range of pressures investigated. Laboratory recalibration of these NDIR sensors would likely 

enable very accurate and precise measurements of the calibration test gases.
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The effect of pressure on sensor response was also investigated and typical results are shown in 

Figure 15. The theoretical pressure sensitivity of the CO2 partial pressure for a gas composition 

of 1100 ppm CO2 at 1 atmosphere (i.e., CO2 partial pressure of 0.11 kPa) was calculated 

assuming ideal gas behavior. The theoretical dependence of CO2 partial pressure upon chamber 

pressure (slope = -0.18) was then experimentally compared to sensor indications from a Johnson 

Controls CD-WA0 NDIR CO2 sensor. As shown in Figure 18, the commercial sensor exhibited

a higher sensitivity to pressure (slope = -0.24) than expected from the ideal gas law. Table V 

shows the pressure sensitivity of a number of additional NDIR CO2 sensors investigated and all 

sensors exhibited higher sensitivity to pressure that expected. The average sensor was 

approximately 27% more sensitive to pressure than expected. 

A1,A2 K-22 LO Sensor A5 Airtest TR9294

A3 Siemens QPA2000 A6 Johnson Controls CD-WAO

A4 Airtest EE80 A7 SenseAir aSense MIII 

 Figure 14. Laboratory FTIR and commercial CO2 NDIR sensor responses to introduction of 

1340 ppm CO2 in nitrogen at 0.67 atm pressure in the test chamber (10,780 ft 

equivalent altitude). Indicated time is from the beginning of introduction of the 

test gas. Test gas flow stopped at 200 min. 
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 Figure 15. Theoretical pressure sensitivity (triangles) of the CO2 partial pressure calculated 

assuming ideal gas behavior compared to sensor indications from a typical NDIR 

CO2 sensor (diamonds: Johnson Controls CD-WA0). Note that the commercial 

sensor exhibits a higher sensitivity to pressure than expected from theoretical 

considerations.

Table V

Pressure Sensitivity of Commercial NDIR CO2 Sensors
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Electrochemical CO sensors: Figure 16 compares the steady state outputs (mg of CO per m3) of 

each commercial sensor against the known concentration of CO in the test chamber for binary 

test gases of nitrogen and CO in the test chamber pressures indicated. In the ideal case the 

sensors would output exactly the same CO concentration as the known concentration resulting in 

linear behavior as shown by the 1:1 line in Figure 16. Most sensors predicted greater amounts of 

CO in the test chamber at each pressure level than were actually there. Perhaps the factory 

calibrations were intentionally set conservatively high due to the hazards associated with CO 

poisoning. Examination of the results shows that each sensor demonstrated a linear response to 

an increase in the CO concentration. This suggests that the sensors could be recalibrated to 

provide a more accurate measurement of the steady state CO concentration in the test chamber.

(a)

(b) (c)

 Figure 16. Experimental measurements of CO concentration in nitrogen (mg CO per m3) for 

the electrochemical sensors indicated versus known concentrations in pure 

nitrogen test gases at the following pressures: (a) 101.3 kPa, (b) 87.5 kPa and 

(c) 75.3 kPa [33]
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The data for the Figaro 5042 sensor are replotted in Figure 17 for nitrogen with CO at test 

pressures of 101.3, 87.5 and 75.3 kPa. Figure 17 clearly shows a linear response for the Figaro 

5042 sensor at each of the pressures. The increasing slope of the sensor response as the pressure 

is reduced suggests that the accuracy of the sensors perhaps decreases slightly as the pressure 

decreases. However, the sensor behavior is linear and predictable.

Figure 17. Figaro 5042 sensor response to nitrogen gas with the indicated known concentrations 

of CO at test pressures of 101.3, 87.5 and 75.3 kPa. [33]

Figure 18 presents the results of repeated experiments on the Figaro 5042 sensor for a steadystate concentration of 233 mg of CO per m3

in nitrogen-20% oxygen at a pressure of 101.3 kPa. 

The Figaro 5042 sensors exhibited stable, repeatable steady-state output without any overshoot or 

undershoot. The responses were quite repeatable in these initial experiments. The e2v sensor 

demonstrated a first ordered response to an increase in the CO concentration with stable, 

repeatable steady-state output. Unfortunately, the Graywolf sensor malfunctioned and never 

responded to any of the CO inside the sensor evaluation system.
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 Figure 18. Three repeated transient measurements of CO concentration (known value = 

233 mg CO/m3) in simulated air (80% nitrogen and 20% oxygen) at 101.3 kPa for 

the electrochemical sensors indicated. The calculated transient test chamber 

concentration is shown by the dashed line. [33]

4.2.2 Commercial Sensors Responses to Fumes from Mobil Jet Oil II

One gram of Mobil Jet Oil II was thermally degraded in the bell jar shown previously in Figure 

6(d). The furnace target maximum temperature was set to 375°C and a heating rate of 10°C/min 

was utilized to heat the oil sample. The oil began to lose mass after approximately 30 minutes 

and at a temperature of approximately 190°C. White smoke was observed at that time and the 

amount of smoke increased as the experiment progressed as shown in Figure 19. The oil reached 

and maintained a steady state temperature of 225°C during the time that mass loss and smoke 

generation continued. At the end of the experiment, only charred black material remained in the 

crucible. 
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(a) (b) 

Figure 19. a) Bell jar before thermally degrading 1g of Mobil Jet Oil II;

b) smoke-filled bell jar during degradation experiment. [34]

Figures 20 and 21 show the change of CO and CO2 concentration as a function of time along 

with the Mobil Jet Oil II mass change. The sensors began detecting CO and CO2 at 

approximately the same time that significant mass loss began (~30 minutes). The downstream 

FTIR began detecting changes in the air samples about 5 minutes later. The measured 

concentrations from the sensors and the FTIR appear to reach maximum values near the end of 

the thermal degradation. Interestingly, although the downstream FTIR detection of CO shown in 

Figure 20 began to decrease after the upstream electrochemical sensor, as expected, the FTIR 

detection of CO2 began to decrease before the upstream NDIR CO2 sensor as shown in Figure 21. 

This behavior may be due to smoke coating the NDIR sensor optics during the experiment and is 

under further investigation.

Figure 20. Plot of the change in CO concentration as a function of time as measured by the 

TGS5042 sensor (circles) and the FTIR (diamonds) and the mass (dashes) as a 

function of time. [34]
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Figure 21. Plot of the CO2 concentration as a function of time as measured by the EE80 (circles) 

and the FTIR (diamonds) and the mass (dashes) as a function of time. [34]

4.3 TCP Sensor Developments

To test the ability of the tricresyl phosphate (TCP) sensor system discussed in Section 3.2.2 to 

detect TCP in gas, several samples of vapor phase TCP were produced by evaporation and 

collected with the automatic TCP sampling system. Different concentrations of TCP (0 as 

control, 2.5, 10, 50, and 200 nM) in methanol were evaporated by bubbling nitrogen gas at 1.1 

L/min through the methanol solution for 10 min. During the last 5 min of bubbling, 220oC 

nitrogen gas at 220oC was used to ensure that all the TCP was evaporated. The total nitrogen gas 

volume equaled 11 L giving TCP concentrations of 0, 5, 20, 100, and 400 ppb. All nitrogen 

containing TCP samples were blown through the alkaline powder catalyst column. Finally 3 mL 

of Na2HPO4/KH2PO4 (0.2 M/0.2 M final concentrations) and 10 mM NaCl buffer was flushed 

through the powder column to collect hydrolyzed products. All sample preparation and collection 

steps were accomplished with an automated custom TCP sampling system. By these processes, 

TCP gas samples were converted to liquid samples containing corresponding concentration of 

cresol, making it possible to be detected using the electrochemical sensor discussed in Section 

3.2.2.

The flow injection results from TCP converted samples are shown in Figure 22. The 

concentration of TCP in the gas is seen to be linear over the gas concentration range of 5 to 400 

ppb. The lower concentration part of Figure 21 is enlarged and shown in the inset of Figure 21

(0, 5 and 20 ppb ). These results confirm the capability of the laboratory system to detect TCP in 

gaseous samples. The lower detection limit is estimated as 5 ppb in gas.
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Figure 22. Calibration curve of amperometric results of TCP converted samples. Linear 

concentration range is from 5 ppb to 400 ppb in gas. Inset figure shows low 

concentration range (5 and 20 ppb). 0 ppb means sample was from methanol 

without TCP, acting as control sample.

To further test the ability of the system to detect TCP in air from more realistic samples due to jet 

engine oil, 4 μL of BP2380 and BP 274 oil samples were mixed in methanol and then processed 

through the detection system (as described above). BP 2380 jet engine oil contains a maximum 

of 5% TCP while BP 274 jet engine oil is free of TCP additives. The concentrations of TCP in 

the air stream were calculated to be 600 ppb (BP 2380) and 0 ppb (BP 274). The peak 

electrochemical current response from the BP 2380 sample was 28.5 nA (std. dev. = 1.40 nA) 

while the BP 274 oil sample exhibited a peak electrochemical current of only 3.78 nA (std. dev. 

= 0.06 nA). The response of the sensor to the TCP containing oil vapor sample was thus 

approximately an order of magnitude higher than for the TCP-free BP 274 oil vapor sample. 

4.4 Particulate and Ultrafine Sensor Test Results

The bleed air contaminant simulator built for the previous “Filter” project is being used to 

characterize the nature of airborne contaminants generated in oil-based contamination events. As 

part of this effort, the nature of the particulate sizes and distributions are being measured for 

different conditions as it is believed that a particulate sensor has the potential to be part of an 

effective bleed air contamination detection system. A diagram of the bleed air simulator at 

Kansas State University is shown in Figure 23.
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Figure 23. Kansas State University Bleed Air Contamination Simulator.

Three different instruments are being used to measure particle numbers and sizes. The first is an 

“Aerodynamic Particle Sizer” (APS). The particular instrument being used is the TSI Model 

3321 APS. This instrument measures aerodynamic diameter by recording the time of flight of 

particles as they are accelerated through a nozzle. Particle size is binned into 52 channels from 

approximately 0.5μm to 20 μm. This instrument is noted for providing high quality size 

distribution information.

The second instrument is a “Condensation Particle Counter” (CPC). The particular instrument 

being used is the TSI Model 3781. The CPC allows particles as small as 6 nm to be counted, 

thus greatly extending the range of particle sizes detected beyond what the APS can detect. The 

CPC condenses moisture onto the particles to grow them to a size that can be detected. 

Consequently, there is no size distribution information, only total particle counts.

The third instrument is an “Optical Particle Counter” (OPC). The particular instrument being 

used is the Climet Spectro 0.3. The OPC calculates particle size and concentration by measuring 

the intensity of light scattered by the particles. Particle size is binned into 16 channels from 

0.3μm to 10μm.

Three separate but otherwise identical APSs are available for comparison to verify that the results

are reliable. At this point, we are having some difficulty reconciling OPC and APS 

measurements and only APC and CPC data are reported at this time. The data collected to date 

are strictly preliminary. A summary of the data may be found in Table VI. Figure 24 shows the 

size distributions for the different temperature conditions indicated.

From these results it can be seen that the APS counts decrease as temperature increases while the 

CPC counts increase significantly as temperature increases. Although one could speculate as to 

the mechanisms that lead to these results, we will not do so until further data are collected. 

However, an increase in ultra-fine particles as the process temperature reached the pyrolysis point

was predicted. Whether or not that we are seeing smoke at this point -- or some other 

phenomena -- is not yet clear.
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Table VI

Summary of Particle Measurements

Parameter Units Test 1 Test 2 Test 3 Test 4

Reactor Tube 

Temp

°C 104.8 199.4 244.5 276.7

Comp 

Pressure

psi 31 29 30 32

CPC 

Concentration

counts/cm3 34,202 63,809 98,066 124,917

APS 

Concentration

counts/cm3 885.0 1961.3 767.0 120.8

Mean Aero 

Diameter

μm 0.71 0.71 0.69 0.68

Figure 24. Particle size distributions at the indicated test temperatures as measured by APS.
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4.5 Wireless Sensor Network Field Test in an Aircraft Cabin Mock-up

Test Series 2 of the wireless sensor network testing in the KSU B767 cabin mock-up was 

composed of four test runs that focused on CO2 measurements. During the first two runs only 

CO2 was flowed into the cabin. During Runs 3 and 4, CO2 was inserted, passenger dummy 

heaters turned on, and cabin humidifiers were cycled. Table VII shows the experimental 

timeline.

As seen in Figure 25, CO2 concentrations were well distributed through the cabin. Since the CO2

was flowed into the front of the cabin, the highest concentration of CO2 was seen nearest the 

front of the cabin. The concentration decreased toward the rear of the cabin. From Figure 23, we 

see that during the last two runs (which included humidity and temperature variations) sensor 

node U2 showed a significantly higher concentration of CO2 than the other tests. Which effect 

(increased heat or humidity) may have caused this response is not clear.

Table VII

Wireless Sensor Network Field Test - Series 2 Timeline

Time Event Description

18:55:00 Start of Test Series 

2

All units power cycled. Note: Turning the CO2 on and off does not 

require any doors to open in the cabin.

UU:UU:UU Node reset CO2 was flowed but Unit 3 had to be reset because it stopped 

sending data.

19:05:00 Started Run 1 Flowed CO2

19:28:00 Stopped Run 1 Stopped CO2

19:43:20 Started Run 2 Flowed CO2

20:08:00 Stopped Run 2 Stopped CO2

20:12:00 Started Heaters Passenger dummy heaters started

20:22:00 Started Run 3 One occupant entered and started humidifiers. 

20:22:10 Closed Door Closed door 2. Started CO2.

20:57:00 Stopped Run 3 All humidifiers turned off and CO2 stopped.

21:13:00 Started Run 4 Door 2 opened, humidifiers started.

21:13:10 Door Closed Door 2 closed. CO2 started.

21:37:00 Stopped Run 4 All humidifiers turned off and CO2 stopped
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Figure 25. Wireless sensor network field test results for CO2 sensors.

4.6 Preliminary Data Mining Results from the FAA SDRS and NASA ASRS 

Databases

Murawski's and Supplee's results[9] were extended by searching all of the Service Difficulty 

Reports (SDRs) in the FAA SDRS database and the documents in the NASA ASRS for entries 

containing the same keywords as Murawski and Supplee chose. As the Structured Query 

Language (SQL) database file for the SDRs was available, this task was accomplished through a 

SQL query using the REMARK LIKE terms and the % wildcard character to grab all entries 

related to the keywords. The ASRS's database file could not be directly manipulated in this way. 

Instead, the web interface was utilized for limited queries using an SQL like language. 

However, in this manner, only 5000 entries be drawn out of the ASRS database at a time. The 

AND and OR terms, in addition to the % wildcard character, was used to draw out the same 

keywords as the query made on the SDRS database. These entries were compiled in four year 

intervals (data from 2008 – 2012, etc.) and then concatenated together due to the 5000 entry 

limit. 17,878 cabin air quality related reports were pulled from the SDRS database while 10,644 

cabin air quality related reports were pulled from the ASRS database. This provided a data set 

much larger and potentially more representative of air cabin quality events in general than the 

more limited dataset of 470 reports analyzed by Murawski and Supplee.[9]
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The total frequency of each of the keywords in the dataset was examined first. The complete set 

of SDRs provides the most entries for almost every keyword and the most entries overall. This 

indicates that there are far more airline self-reports to the FAA than reports made by airline 

personnel to the NASA ASRS database. However, the two datasets were not compared for 

overlapping documents or for documents contained in one database and not the other. Such 

additional research is planned.

The portion of entries containing each keyword remained fairly stable across all of the sets of 

data. However, there were a few exceptions. The keyword phrase “oily smell” was found much 

more frequently in Murawski and Supplee's data.[9] This could be due to their small sample size. 

Murawski and Supplee collected SDRs and AIDS data for a little over a year, whereas the whole 

SDR database stretches back to 1995 and the ASRS data began being reported in 1988. 

Interestingly, the keyword phrase “oil leak” was found comparatively infrequently in the ASRS 

data. 

The number of entries present for each year in each database was counted using SQL queries. 

The ASRS database contained consistently fewer entries than the number of air cabin quality 

entries found in the SDRs for each year. The only exception was that of the most recent year. 

Not all SDRs have been added to the database for the current year while data have been added to 

the ASRS database in a much more timely fashion. It is also interesting that the number of 

incidents reported in each database has remained relatively similar from year to year. 

Nevertheless both databases indicate that the trend is for cabin air quality incidents to slightly 

increase over time. This slight uptrend was broken in the years after September 11, 2001, where 

the number of consumer flights decreased dramatically overall.

The top 4 aircraft types associated with bleed air events in the SDRS database appear to be the 

following: CL-600-2B19 (aka Bombardier CRJ100 and CRJ-200), Embraer 145LR, MD-82 and 

MD-88. The top 4 aircraft types associated with bleed air events in the ASRS database appear to 

be the following: Boeing 757, MD-80 Series, Boeing 737 and Airbus 320. These are 

preliminary data and have not yet been normalized with respect to the total number of aircraft in 

operation, the total number of takeoffs, etc. Such additional analysis is planned.
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5.0 Summary

Principal components analysis/regression techniques have been successfully applied to Fourier 

Transform Infrared spectroscopy data of gases evolved from thermally degraded jet engine oils. 

These analyzed gases consisted of complex mixtures of carbon monoxide (CO), carbon dioxide 

(CO2), methanol (CH4O) and water (H2O). Additional work is planned using gas 

chromatography – mass spectrometry to further investigate and confirm these results – especially 

the findings regarding the presence of methanol and as well as to look more closely for 

formaldehyde (CH2O).

Sensing of carbon dioxide (CO2) and carbon monoxide (CO) via non-dispersive infrared 

technology and electrochemical sensors, respectively, are widely used in commercial 

applications. Both methods offer considerable promise for aircraft measurements of these same

gaseous contaminants. However, existing sensor packaging and maintenance/calibration 

methods must be adapted to the unique environment and more stringent performance 

requirements anticipated for aircraft. In addition, research into the response times of the sensors 

is critical to ensure that transient bleed air events can be quickly and reliably detected. Finally, 

the potential application of catalytic bead sensor technology to characterize the presence of 

unburned hydrocarbons during incomplete pyrolysis of jet engine oil during bleed air events must 

also be evaluated.

Computerized data mining techniques were utilized to replicate and improve upon the results of 

previous researchers (i.e., Murawski and Supplee [9]) by expanding the data set used to the 

entirety of the FAA SDRS and the NASA ASRS databases. The preliminary findings are 

promising and further research may lead to the creation of association rule classifiers for use in 

rigorously characterizing cabin air quality incidents. 

Wireless sensor networks can provide the necessary coverage and cooperation to effectively 

monitor air quality sensor systems in aircraft bleed air supplies and airliner cabins. A prototype 

of such a system has been successfully tested in a Boeing 767 mock-up cabin. The wireless 

sensor network was shown capable of monitoring multiple environmental variables, and 

providing real-time, correlated data and represents a new tool that will improve our ability to 

characterize highly dynamic environmental control systems on aircraft.
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6.0 Acknowledgments

This project was funded by the U.S. Federal Aviation Administration (FAA) Office of Aerospace 

Medicine through the National Air Transportation Center of Excellence for Research in the 

Intermodal Transport Environment (RITE), Cooperative Agreements 07-C-RITE and 10-CRITE. Although the FAA has sponsored this project, it neither endorses nor rejects the findings

of this research.

7.0 References

[1] NRC (National Research Council); 2002, The Airliner Cabin Environment and the Health 

of Passengers and Crew, Washington, DC, National Academy Press.

[2] “De-icing solution sends air crew members to hospital,” CNN, 24 Dec 2008.

[3] Crane, Charles R., Sanders, Donald C., Endecott, Boyd R., Abott, John K., “Inhalation 

Toxicology: III Evaluation of Thermal Degradation Products from Aircraft and Automobile 

Engine Oils, Aircraft Hydraulic Fluid, and Mineral Oil,” FAA-AM-83-12, 1983.

[4] Van Netten, Chris, “Aircraft Air Quality Incidents, Symptoms, Exposures and Possible 

Solutions,” in Air Quality in Airplane Cabins and Similar Enclosed Spaces, Hdb Env. 

Chem. Vol. 4, Part H (Springer, Berlin) 2005, pp. 192-210.

[5] Shayne, B., “Plane with sick passengers had air contamination before,” WCNC, 20 Jan 

2010.

[6] Abou-Donia, M.B., “Organophosphorous ester-induced chronic neurotoxicity,” Arch. 

Environ. Health, 2003, Vol. 58, pp. 484-497.

[7] Winder, Chris and Balouet, Jean-Christophe, “The Toxicity of Commercial Jet Oils,” 

Environ. Res. A, 2002, 89, pp. 146-164.

[8] Watson, Jean; 2009, personal communication.

[9] J.T.L. Murawski, J.T.l. and Supplee, D.S., “An Attempt to Characterize the Frequency, 

Health Impact and Operational Costs of Oil in the Cabin and Flight Deck on U.S. 

Commercial Aircraft,” J. ASTM Intnl , 2008, Vol. 5, No. 5, Paper ID JAI101640.

[10] Department of Transportation, Bureau of Transportation Statistics, 

http://www.bts.gov/publications/national_transportation_statistics/html/table_01_37.html, 

accessed February 3, 2012

[11] “Air Quality within Commercial Aircraft,” ANSI/ASHRAE Standard 161-2007, American 

Society of Heating, Refrigerating, and Air-Conditioning Engineers, 2008, Atlanta, GA.

[12] Hunt, Elwood H., Reid, Don H., Space, David R. and Tilton, Fred E., “Commercial 

Airliner Environmental Control System,” Aerospace Medical Association Annual Meeting, 

1995, Anaheim, CA, USA.

[13] Jones, Byron, personal communication, 2011.

[14] van Netten, C., Leung, V., “Hydraulic Fluids and Jet Engine Oil: Pyrolysis and Aircraft Air 

Quality,” Archives of Environmental Health, 2001, 56(2): p. 181-186.

[15] van Netten, C., Multi-elemental Analysis of Jet Engine Lubricating Oils and Hydraulic 

Fluids and Their Implication in Aircraft Air Quality Incidents., The Sci. of the Total 

Environ., 1999, 229, p. 125-129.
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[16] van Netten, C., Leung, V., “Comparison of the Constituents of Two Jet Lubricating Oils 

and Their Volatile Pyrolytic Degradation Products,” Applied Occupational and 

Environmental Hygiene, 2000, 15(3): p. 277-283.

[17] Crane, C.R., Sanders, D.C., Endecott, B.R., Abbott, J.K., “Inhalation Toxicology: III. 

Evaluation of Thermal Degradation Products from Aircraft and Automobile Engine Oils, 

Aircraft Hydraulic Fluid and Mineral Oil,” FAA Civil Aeromedical Institute, FAA-AM-83-

12, 1983.

[18] Bartl, P., Volkl, C., Kaiser, M., “Chemical Characterization of Polyol Ester Aviation 

Lubricant Residues,” J. Synthetic Lubrication, 2008, 25, p. 1-16.

[19] Jones, E., “The pellistor catalytic bead sensor,” in Solid State Gas Sensors, Moseley, P.T. 

and Tofield, B.C., Eds., 1987, Institute of Physics, Bristol, UK, p. 17-31.

[20] Korotcenkov, G., “One-electrode Semiconductor Gas Sensors,” in Science and Technology 

of Chemiresistor Gas Sensors,” Aswal, D.K. and Gupta, S.K., Eds, 2007, Nova Science 

Publishers, New York, USA, p. 95-145.

[21] Chou, J., Hazardous Gas Monitors, 1999, McGraw Hill, New York, USA, p. 37-41.

[22] Kaur, M., Aswal, D.K., Yakhmi, J.V., “Chemiresistor Gas Sensors: Materials, 

Mechanisms and Fabrication,” in Science and Technology of Chemiresistor Gas Sensors,” 

Aswal, D.K. and Gupta, S.K., Eds, 2007, Nova Science Publishers, New York, USA, p. 33-

93.

[23] Stetter, J.R., Li, J., “Amperometric Gas Sensors – A Review,” Chem. Rev., 2008, 108, p. 

352-366.

[24] Fergus, J.W., “Solid electrolyte based sensors for the measurement of CO and hydrocarbon 

gases,” Sensors and Actuators B, 2007, 122, p. 683-693.

[25] Fergus, J.W., “A review of electrolyte and electrode materials for high temperature 

electrochemical CO2 and SO2 gas sensors,” Sensors and Actuators B, 2008, 134, p. 1034-

1041.

[26] Verner, P., “Photoionization detection and its application in gas chromatography,” 

J. Chromatography, 1984, 300, p. 249-264.

[27] Shrestha, S.S. and Maxwell, G.M., 2009, “Product Testing Report – Wall Mounted Carbon 

Dioxide Transmitters,” National Building Controls Information Program, Iowa Energy 

Center (Ankeny, IA).

[28] Shrestha, S.S. and Maxwell, G.M., 2009, “An experimental evaluation of HVAC-grade 

carbon dioxide sensors: Part 1, test and evaluation procedure,” ASHRAE Transactions, 

115(2).

[29] Shrestha, S.S. and Maxwell, G.M., 2010, “An experimental evaluation of HVAC-grade 

carbon dioxide sensors: Part 2, performance test results,” ASHRAE Transactions, 116(1).

[30] Shrestha, S.S. and Maxwell, G.M., 2010, “An experimental evaluation of HVAC-grade 

carbon dioxide sensors: Part 3, humidity, temperature and pressure sensitivity test results,” 

ASHRAE Transactions, 116(1).

[31] Beta, I.A., “TGA Measurements of Oil Samples with Evolved Gas Analysis by FTIR and 

MS,” 2011, Report No. 621002184, NETZSCH Instruments North America, LLC

(Burlington, MA).

[32] Haney, R.L., “Principal Component Analysis for Enhancement of Infrared Spectra 

Monitoring,” 2011, Ph.D. Dissertation, Auburn University, Auburn, AL.
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[33] Andress, J.R., “Evaluation and Analysis of Commercially Available Electrochemical 

Carbon Monoxide Sensors for Aircraft Applications,” 2012, M.S. Thesis, Auburn 

University, Auburn, AL.

[32] Neer, R.L., “Development of a Laboratory Apparatus to Study the Thermal Degradation 

Behavior of Jet Engine Oils,” 2012, M.S. Thesis, Auburn University, Auburn, AL.