A Plume Capture Technique for the Remote Characterization of

May 20, 2008 - International Laboratory for Air Quality and Health,. Queensland University of Technology, GPO Box 2434,. Brisbane, QLD 4001, Australia...
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Environ. Sci. Technol. 2008, 42, 4850–4856

A Plume Capture Technique for the Remote Characterization of Aircraft Engine Emissions G. R. JOHNSON, M. MAZAHERI, Z. D. RISTOVSKI, AND L. MORAWSKA* International Laboratory for Air Quality and Health, Queensland University of Technology, GPO Box 2434, Brisbane, QLD 4001, Australia

Received October 12, 2007. Revised manuscript received March 20, 2008. Accepted April 3, 2008.

A technique for capturing and analyzing plumes from unmodified aircraft or other combustion sources under real world conditions is described and applied to the task of characterizing plumes from commercial aircraft during the taxiing phase of the Landing/Take-Off (LTO) cycle. The method utilizes a Plume Capture and Analysis System (PCAS) mounted in a four-wheel drive vehicle which is positioned in the airfield 60 to 180 m downwind of aircraft operations. The approach offers low test turnaround times with the ability to complete careful measurements of particle and gaseous emission factors and sequentially scanned particle size distributions without distortion due to plume concentration fluctuations. These measurements can be performed for individual aircraft movements at five minute intervals. A Plume Capture Device (PCD) collected samples of the naturally diluted plume in a 200 L conductive membrane conforming to a defined shape. Samples from over 60 aircraft movements were collected and analyzed in situ for particulate and gaseous concentrations and for particle size distribution using a Scanning Particle Mobility Sizer (SMPS). Emission factors are derived for particle number, NOx, and PM2.5 for a widely used commercial aircraft type, Boeing 737 airframes with predominantly CFM56 class engines, during taxiing. The practical advantages of the PCAS include the capacity to perform well targeted and controlled emission factor and size distribution measurements using instrumentation with varying response times within an airport facility, in close proximity to aircraft during their normal operations.

1. Introduction Despite the numerous studies performed on airport and aircraft engine emissions, it has been stated that airport emissions, specifically particle emissions, are not well characterized. In terms of local air quality and related health issues, the impact of air transport arises primarily through aircraft ground level activities, and to a lesser extent through the operations of ground service vehicles and equipment rather than from the flight phase of aircraft operations (1–5). The data available is largely focused on gaseous emissions, with almost no data on particle emissions from ground level aircraft operation. In addition, most of the current estimates for airport emission inventories are based on data from a very limited number of newly manufactured aircraft engines, * Corresponding author tel: +61 7 3138 2616, e-mail: l.morawska@ qut.edu.au. 4850

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measured in test rigs (6). It is pointed out that only a very few studies on particle emissions from airport emissions exist and most of these have been performed using data from research aircraft and during aircraft cruise conditions. A number of sampling techniques have been developed for the purpose of obtaining particulate matter emissions data from a moving aircraft on the ground and from vehicles. Herndon et al. (1, 7) measured emission factors for NO, NO2, and particle number from commercial aircraft engines during taxiing and takeoff. Rogers et al. (8) examined emissions from the exhaust plane of tethered ground-based jet engines using forced dilution and was able to obtain size distributions using a Scanning Mobility Particle Sizer (SMPS) for these engines at various thrust settings. Recently Morawska et al. (9) developed a Plume Capture Trailer (PCT) to measure onroad vehicle emission factors under real world conditions. A mobile emission laboratory (MEL) (10–13), a large shipping container mounted system towed by a tractor, has been used to obtain a variety of vehicle chase studies to obtain submicrometer size distribution from vehicle exhaust plumes obtained by SMPS measurements of plume aerosol drawn into and confined in a sampling bag. The Aerodyne Research Inc. (ARI) Mobile laboratory (14) allows particle number concentration measurements and gaseous emission measurements at a range of distances from the test vehicle tailpipe. A mobile pursuit laboratory (15) has also performed SMPS size distribution measurements on sampled exhaust plumes. Vogt et al. (16) conducted SMPS measurements with a mobile laboratory while pursuing a diesel passenger vehicle and compared the results to those obtained with the same vehicle using a chassis dynamometer and dilution tunnel. While the above methods all have potentially useful features, a more practical system would combine all of the following features: An ability to collect plume samples with good discrimination between individual aircraft during specific phases of the Landing/Take-Off (LTO) cycle. This necessitates an ability to safely maneuver through the undulating and unpaved areas that exist between the runways and taxiways of an airfield so that plume samples can be collected at distances of 60 to 180 m. The system must also have the ability to collect large volumes of sample for detailed analysis and to do so rapidly enough to capture transient plumes while avoiding excessive sample dilution or the mixing of plume samples from successive aircraft. The system used by Herndon et al. (1, 7) was able to perform NOx and particle number emission factor measurements as well as size distribution measurements using the Electrical Low Pressure Impactor (ELPI), but that method cannot provide the detailed size resolution and range needed to fully investigate the nucleation mode which dominates aircraft jet engine emissions. That approach to sample collection also lacks the ambient sample storage capacity needed to perform slower but detailed sequential scan measurements as required in SMPS and Volatilization-Hygroscopic-TandemDifferential-Mobility-Analyzer (VH-TDMA) (17) measurements. Although not used in the current study, the VH-TDMA will be applied in future work to perform size specific physicochemical characterization of the aerosol.

2. Experimental Procedures To achieve the above, a novel mobile measurement system, referred to as the Plume Capture and Analysis System (PCAS), was developed. The PCAS consists of a Plume Capture Device (PCD), as well as particle and gas measurement instruments providing simultaneous real-time measurements of aircraft engine emissions. 10.1021/es702581m CCC: $40.75

 2008 American Chemical Society

Published on Web 05/20/2008

FIGURE 1. Configuration and approach used for collecting samples from an aircraft during ground operations. 2.1. Design Criteria. In order to collect unambiguous samples from individual aircraft at a specific stage of LTO cycle, measurements must be conducted at the minimal distance permissible (60 m) from aircraft operations. Because the exhaust plume may be only briefly present at the sampling nozzle, the sample must be collected quickly. The brevity of the test cycle for a measurement is limited by the time required to complete two SMPS scans, one of the captured sample and one background scan of the ambient air. To permit this, the target interval between the collection and analysis of new samples was chosen to be of the order of 5 min. The minimum volume of sample required for the analysis is determined by instrument flow rate and the duration of the analysis. Furthermore, large sample volumes must be collected in order to reduce the surface to volume ratio of the containment bag so that particle wall loss effects are reduced as far as possible. Particle number analysis by a Condensation Particle Counter (CPC) and size distribution measurement by SMPS consumes only a few liters of sample volume; however, size specific particulate volatile and hygroscopic physicochemical analysis using VH-TDMA (17) will require sample volumes of at least 50 L. A sample volume of 200 L would ensure that these requirements are met while remaining a practical size for mobility purposes. 2.2. The PCAS Technique. The PCAS consists of the PCD, and an array of particle and gaseous measurement instruments connected to the PCD, all of which are mounted inside a four wheel drive Toyota troop carrier. The PCD uses the pressure difference created when air is drawn from a rigid bag enclosure to fill the bag with ambient air drawn via a sample probe. This avoids passing the sample through a pump which may alter the aerosol size distribution. A detailed description of the PCD design and operation is provided in the Supporting Information file. The file includes the following: • A schematic diagram showing the main elements and flow paths of the PCD. • A description of the main components of the PCD. • A description of the operating sequence used during plume capture and analysis. • A discussion of the efficiency of sample expulsion when emptying the PCD of a previous sample, in preparation for a new round of plume capture. • A discussion of the particle loss correction procedure used for particle number concentration correction.

Figure 1 illustrates the configuration and the approach used for collecting samples from an aircraft during ground operations. An electrical generator and the sampling probe are fixed on the top of the vehicle. The probe is positioned with the intake orifice forward of the driver seat. The generator is located at the rear left corner (passenger side) of the vehicle above the vehicle exhaust which is located below the vehicle. Thus both exhaust ports face the rear and are diagonally opposite the forward-facing sample probe. This arrangement ensures that with the vehicle facing into the wind, all emissions associated with the vehicle and the generator are released downwind of the sample inlet, thereby avoiding contamination of the sample. The mobile laboratory is positioned downwind from a target point defined by the intersection of the aircrafts projected path with the wind back trajectory from the probe, at a distance of 60 m or more to avoid any disturbance to normal aircraft operations. After collecting a plume sample, the content of the bag is immediately analyzed. Capturing a sample takes 5 s, and the whole process of capturing, scanning, and emptying the bag is performed in about 5 min. The PCAS was equipped with two sets of SMPS (TSI 3934) for particle size distribution measurements, a separate condensation particle counter capable of detecting particles larger than 7 nm in diameter (TSI 3022A CPC), a NOx analyzer (Ecotech ML9841A), an aerosol photometer (TSI DustTrak) fitted with a PM2.5 impactor, and sensors for CO2 (Sable instruments), humidity, and temperature (TSI QTrak 8554). An SO2 analyzer (Ecotech 9850) was also used for some measurements. The data from each of these instruments were continually logged. All instruments were connected to a common sampling manifold, the intake to which was connected alternately to the ambient air intake drawing air from upwind of the laboratory or to the sampling bag. Thus, a record of the corresponding ambient data was recorded alternately with the captured sample data so that appropriate background subtractions could be performed. 2.3. Emission Factor Measurement Procedure. Aircraft engine particle number emission factors are determined using PCAS from the measured emission ratio. The emission ratio is defined as the ratio of the concentration enhancement within the plume, of the exhaust component (∆Cx, e.g., particle number concentration) to the concentration enhancement of CO2 in conjunction with an assumed CO2 EF based on the fuel combustion stoichiometry assuming complete combustion. Provided that any loss of the pollutant VOL. 42, NO. 13, 2008 / ENVIRONMENTAL SCIENCE & TECHNOLOGY

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or of CO2 through chemical or other processes remains negligible and the two components dilute equally and do not separate, the emission factor for the specific pollutant derived by this method remains valid for measurements conducted anywhere in the plume. As pointed out by Zavala et al. (18), the assumption that all species emitted from the exhaust are equally diluted is a very good approximation for the gaseous species whereas for the aerosol phase, dilution depends on the dominant mode of the emitted particles and the equal dilution assumption will not hold for very short-lived species because of the potential chemical transformations occurring before sampling. Where the aerosol is dominated by nucleation mode particles, we assume that the equal dilution approximation holds true. The mass emission factor is calculated using eq 1 in the case of particle mass or a gaseous pollutant, and the particle number emission factor is calculated according to eq 2. EF(x) ) EF(CO2)

MWx ∆Cx MWCO2 ∆CCO2

(1)

where EF(x) is the mass of pollutant x, emitted per unit mass of fuel consumed. ∆Cx ) Cx - CxBG is the concentration enhancement of pollutant x in the plume. Cx is the volume or mole fraction of pollutant x in the plume. CxBG is the volume or mole fraction of pollutant x in the background air. MWx is the molecular weight (molar mass) of species x. EF(N) ) EF(CO2)

1 MWair ∆CN Fair MWCO2 ∆CCO2

(2)

where EF(N) is the number of particles emitted per unit mass of fuel consumed 4CN ) CN - CNBG is the concentration enhancement of particle number in the plume. CN is the particle number concentration in the plume. CNBG is the particle number concentration in the background air. F is the density of air at ambient conditions. During aircraft engine certification measurements, the fuel flow rate is measured to determine the CO2 emission factor. Schulte et al. (19) states that the CO2 emission factor for aviation turbines (jet engines) is known to an accuracy of better than 1% because almost all the carbon atoms in the fuel end up as CO2, disregarding a negligible fraction of unburned hydrocarbons and CO. They showed that because aviation fuels vary in carbon mass fractions between 85.7 and 86.4% depending on their aromatics content, each killogram of fuel contains 860 ( 4 g of carbon atoms. Therefore, multiplication by 44/12, the molar mass ratio of CO2/C, gives the emission factor of CO2, i.e. EF(CO2) ) 3153 ( 15 g · kg-1.

3. Results and Discussion We now discuss in detail an example of the application of the PCAS technique to the case of an aircraft during takeoff. We then examine results obtained using the PCAS technique over a range of distances for taxiing aircraft and to compare the results with emission factors and particle size distributions previously reported in the literature for aircraft engines. Throughout the measurements, the sample particle number concentrations were between 3.51 × 102 and 1.80 × 103 times larger than the measured background concentration for taxiing aircraft. The interval between intake valve closure and the commencement of the first size distribution measurement ranged from 5 to 20 s. Analysis of the sample including size distribution and gas concentration measurements took a total of 5 min. 3.1. Aircraft Engine Emission Factor Measurement. In order to test the PCAS, particle size distributions and emission factors were measured during a series of aircraft movements 4852

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at a commercial airport (Brisbane Airport, Australia), during normal operations and the results compared with literature data. The methodology is illustrated in Figure 2 which shows time series traces for the gas and particle concentrations in the sample manifold before, during, and after capture and analysis of a plume sample for a sample capture event initiated at time t ) 13:50:48, in response to the appearance of a strong CO2 excursion associated with the arrival of the plume emitted from a Boeing 767-300ER (B767) airframe which have predominantly CF6-80C2 class engines during takeoff (20). The distance from the aircraft was 80 m. The derived emission factors for this example are presented in Table 1. The procedure discussed below was the same for all measurements undertaken. The plume concentration was determined during the analysis phase over a 2-3 min sampling period following capture, when all instruments draw the captured sample from the bag. All instruments are then able to achieve a full response to the sample. Note that the online flow cannot be used here because the differing response times of the instruments and the rapidly changing plume concentration associated with the transient nature of the plume would produce very large inaccuracies in the emission factor calculation. This is true for both gases and particles. Errors in the emission factors also result from other factors: Particle deposition losses must be considered in the case of the particle number measurement. Instrument error makes the major contribution for capture events where the plume concentration is close to the limits of instrument sensitivity. Response times and measurement uncertainties for each instrument were as follows: CPC: 13 s, SO2 Analyzer: 120 s, ( 0.5 ppb; NOx Analyzer: 60 s, ( 1 ppb; CO2 Analyzer: 1 s, ( 1% of reading, PM2.5 Photometer: 2 s, ( 0.001 mg · m-3. For all instruments except the CPC, average concentrations in the plume were calculated from the measured concentrations during the instrument FR period. In the case of particle number concentration, the initial and highest (because of subsequent deposition losses) postcapture CN value was used to indicate the plume concentration. As can be seen in Figure 2, extrapolation to the time of capture assuming an exponential decay model will provide an accurate correction of the particle losses in the bag between capture and the first full CPC response, which occurs within just 13 s. In all cases examined, however, such correction is unwarranted because the relative uncertainty in the CO2 enhancement (typically 6-20%) greatly exceeds the relative error introduced (typically -1%) by using the first number concentration value generated after capture instead of the extrapolated value. The magnitude of the effect of the correction on the number emission factor is typically less than 1%. Nevertheless, the extrapolation can be readily included in the analysis when required. The average background was subtracted from the average plume concentration to obtain the concentration enhancement (∆CO2, ∆NOx etc.). This average background concentration was determined using the logged online airflow concentrations immediately prior to the time of capture (TOC). This approach ensures that the prevailing background was taken into account for each sample. Periodic capture and analysis of background samples were also performed to monitor the capture system for signs of deterioration and imperfect expulsion of sample. The background averaging period typically ranged from 1-4 min prior to a capture event and required a period of clean background without significant variation in the 60 s preceding capture. The SO2 emission factor for this aircraft corresponds to a sulfur content of 0.025% by weight assuming 100% conversion to SO2. A survey of the sulfur content in aviation jet fuel in the UK in 1996 showed that 29% of fuel samples

FIGURE 2. Gas and particle concentrations versus time before, during, and after a plume capture event for an aircraft with B767 airframe during takeoff. “TOC” indicates the time of capture and isolation of the sample in the bag. Arrows “FR x” indicate periods used to determine the plume concentration of pollutant x, after the relevant instrument achieved its full response. Lines “BG average” show the average background concentration. Lines “FR plume conc” show the average sample concentration obtained using the corresponding FR period. The curve labeled “exponential decay fit” is fitted to the particle number concentration data obtained after TOC. The line “plume (extrapolated to TOC)” is the fitted curve extrapolating back to TOC to correct for deposition losses in the bag between TOC and full response for the CPC (13 s).

TABLE 1. Emission Factors for the B767 Take-Off Event Depicted in Figure 2 and the Propagated Uncertainty Due to Instrumental Error EFNOx (g · kg-1)

uncertainty, %

15.0

(6

EFN (kg-1) 9.0 ×

1015

uncertainty, %

EFPM2.5 (g · kg-1)

uncertainty, %

EFSO2 (g · kg-1)

uncertainty, %

(11

0.10

(20

0.49

(8

had a sulfur content in the range 0-0.02%, 20% had a range 0.02-0.04%, and 21% had a range 0.04-0.06% (21). The

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TABLE 2. Average Emission Factors for Taxiing Aircraft Using PCAS, and the Uncertainty (given as 2× standard error of the mean) airframe type

usual engine typea

n

D(m)

EFN [ave] (kg-1)

EFPM2.5 [ave] (g · kg-1)

EFNOx[ave](g · kg-1)

B737

CFMI CFM56

21 36 3

60 80 180

2.4 ( 0.8 × 1016 3.5 ( 0.4 × 1016 3.7 ( 1.6 × 1016

0.17 ( 0.08 0.20 ( 0.06 0.11 ( 0.04

4.62 ( 0.6 4.13 ( 0.6 4.99 ( 1.4

a

Boeing Commercial Airplanes (20).

TABLE 3. Aircraft Engine Emission Factor Measurements in the Literaturea airframe type (engine type)

measurement condition

B737 (CFM56-7 engine)

taxi

A340 (CFM56-5C2) and JP-5 fuel

two thrust levels on the ground (idle and cruise)

B777-200 (GE90-76B)1 B767-300 in-use aircraft on ground (GE90-76B orRB211-524H)(2)

ATTAS research aircraft

ground and in-flight

A320-200, B757-236, B777-236, range of B737 and B747

idle conditions

turbo props to jumbo jets

taxi and take-off

range of in-use commercial aircraft

take off and idle conditions

F-18 (F404-GE-400 andT700-GE-401)

on the active flight line (11-71% thrust)

NASA’s DC-8 aircraft (CFM56-2C1)

on the testing pad (a range of thrust levels)

range of B737 (CFM56 engineb) taxi a

g · kg-1

NOx: 3.75-4.80 NO: (idle s), (cruise 2.1) g · kg-1N2O: (idle s), (cruise 1.3) g · kg-1 NO (g · kg-1): Group 1: