Assessment of Particle Pollution from Jetliners: from Smoke Visibility to

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Assessment of Particle Pollution from Jetliners: from Smoke Visibility to Nanoparticle Counting Lukas Durdina, Benjamin T. Brem, Ari Setyan, Frithjof Siegerist, Theo Rindlisbacher, and Jing Wang Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b05801 • Publication Date (Web): 23 Feb 2017 Downloaded from http://pubs.acs.org on February 28, 2017

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Environmental Science & Technology

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Assessment of Particle Pollution from Jetliners: from Smoke Visibility to Nanoparticle Counting

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Lukas Durdina*,1,2, Benjamin T. Brem1,2, Ari Setyan1,2, Frithjof Siegerist3, Theo Rindlisbacher4, Jing Wang*,1,2

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Affiliations:

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Laboratory for Advanced Analytical Technologies, Empa, Dübendorf, CH-8600, Switzerland

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Institute of Environmental Engineering (IfU), ETH Zürich, Zürich, CH-8093, Switzerland

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SR Technics Switzerland AG, Zurich-Airport, CH-8058, Switzerland

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Federal Office of Civil Aviation FOCA, Bern, CH-3003, Switzerland

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Abstract Aviation is a substantial and a fast growing emissions source. Besides greenhouse gases, aircraft engines emit black carbon (BC), a climate forcer and air pollutant. Aviation BC emissions have been regulated and estimated through exhaust smoke visibility (smoke number). Their impacts are poorly understood because emission inventories lack representative data. Here, we measured BC mass and number-based emissions of the most popular airliner's engines according to a new emission standard. We used a calibrated engine performance model to determine the emissions on the ground, at cruise altitude, and over entire flight missions. Compared to previous estimates, we found up to a factor of 4 less BC mass emitted from the standardized landing and take-off cycle and up to a factor of 40 less during taxiing. However, the taxi phase accounted for up to 30% of the total BC number emissions. Depending on the fuel composition and flight distance, the mass and number-based emission indices (/kg fuel burned) were 6.2 – 14.7 mg and 2.8×1014 – 8.7×1014, respectively. The BC mass emissions per passenger-km were similar to gasoline vehicles, but the number-based emissions were relatively higher, comparable to old diesel vehicles. This study provides representative data for models and will lead to more accurate assessments of environmental impacts of aviation.

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Keywords: aviation, black carbon, smoke, emissions, air pollution, climate change

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ACS Paragon Plus Environment


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INTRODUCTION

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"The scream of jet engines rises to a crescendo on the runways of the world. Every second,

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somewhere or other, a plane touches down, with a puff of smoke from scorched tyre rubber, or

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rises in the air, leaving a smear of black fumes dissolving in its wake." Since David Lodge wrote

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these lines in Small World in 19841, air travel has quadrupled and made the world even smaller2.

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Already back then, due to growing awareness concerning the environmental impacts of aviation3

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and prospects of supersonic transport4, measures were put in place to get rid of the jet engine

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“scream” and “black fumes”5,6. The black smoke was not only a nuisance but a matter of safety –

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it reduced airport visibility7. To address this issue, the International Civil Aviation Organization

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(ICAO) has regulated engine smoke through the smoke number (SN)8.

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SN is determined from the reflectance of a filter paper stained by a drawn exhaust

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sample5. The filter captures particulate matter (PM) in the exhaust, predominantly consisting of

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black carbon (BC), but is inefficient for particles < 300 nm typical for modern jet engines9. For

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some engine types, SN is virtually undetectable at all power settings10. However, invisible

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plumes are not particle free.

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Several recent studies have characterized PM emissions from aircraft jet engines11–17, but

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the data are obtained with a variety of sampling and measurement methods, which reduces their

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potential widespread use for climate and air quality models. For such purposes, researchers have

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estimated aviation BC emissions from combustion models18,19 and, most often, from SN20–23.

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Besides the inherent uncertainties, these approximations neglect particle losses in the exhaust

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sampling systems as well as fuel composition24,25. Moreover, none of the approximations

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resolves particle number concentration, which is a metric relevant for the assessment of health

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effects of ultrafine particles as well as for the formation of contrails and cirrus clouds26,27.


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Without up-to-date representative data, impact assessments of aircraft engine BC

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emissions remain highly uncertain. The emission indices (EIs) used to calculate the BC emission

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rates from the global fleet typically range from 10 to 50 mg/kg fuel burned28,29. Recent reports

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claim that aviation BC emissions are underestimated and warm up the atmosphere as much as

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1/3 of the aviation’s CO2 emissions with an average EI of up to 93 mg/kg fuel9,18. At airports,

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aircraft BC emissions typically contribute to the suspended fine PM by less than one µg/m3 21,22.

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However, even one µg of aircraft engine BC can contain billions of particles with modes as small

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as 10 nm13,14,25,30, a characteristic that makes them a risk factor for severe lung and heart

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diseases31–34. The PM emitted is most concentrated near runways and quickly disperses with

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distance16,35, but is also claimed to raise ambient particle number concentrations fourfold up to

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10 km downwind36,37.

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Such air quality and climate impacts can be better assessed through the non-volatile PM

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(nvPM) emissions standard for commercial jet engines, the first new aviation emissions standard

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in 40 years38. From 2020 onwards, the ICAO emissions databank10 will include nvPM number-

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and mass-based emissions for in-production turbofan engines with rated thrust > 26.7 kN (large

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business jets and airliners). The nvPM is almost entirely BC, which is the term we use here in the

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context of the new regulation.

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Here, we estimate BC mass and number emissions from a single aisle airliner modeled on

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the Next-Generation Boeing 737 (almost 1/3 of all 100+ seater airliners in service2,39) over entire

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flight missions. We extensively characterized particle properties and determined BC mass and

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number EIs (EIm and EIn) for two 737NG powerplants in compliance with the new regulation

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methodology38,40,41 as well as measured SN according to the current standard for one of the

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engines. We first look at the correlation between SN and BC mass. We use the BC data,



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corrected for particle losses and fuel variability24,25, to calculate the emissions from the

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standardized ICAO landing and take-off (LTO) cycle, which assesses emissions below 915 m

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(3,000 ft). It defines four thrust settings (static thrust measured on an engine test bed) and time in

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each mode that roughly represent airport operations: taxiing in and out, take-off, climb at

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reduced thrust, and approach for landing. We used a calibrated engine performance model for

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correcting the emissions at the ground to any condition during the flight. Finally, we use our

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flight mission estimates to answer the question whether modern-day air travel produces more BC

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per passenger and kilometer than cars and buses.

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MATERIALS AND METHODS

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Engine emission tests. The emission tests were done on two in-service well run-in engines (at

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20% and 50% of the typical overhaul cycle, respectively) in the engine test cell of SR Technics

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at Zurich airport, Switzerland using an nvPM measurement system compliant with the future

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ICAO nvPM standard38. Exhaust samples were extracted at the engine exit plane using a multi-

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orifice cruciform probe. The chosen orifice pattern provided representative samples of gaseous

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pollutants (NOx, CO, and hydrocarbons), in agreement with the ICAO certification data (S3 in

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the online supporting information, SI). We found a good agreement also with the certification SN

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(S4 in the SI). Upstream of the nvPM measurement system, the sample was diluted with dry

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synthetic air by a factor of ~10 and drawn through a 24.5 m long trace-heated line (60 °C). The

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total length of the sample line from the probe inlet to the BC instruments was 34 m. The BC

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mass concentration was measured with an AVL Micro Soot Sensor (MSS), and the BC number

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was measured with an AVL Particle Counter Advanced (APC) that contains a two-stage diluter

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and a volatile particle remover heated to 350 °C. A detailed description of the engine tests, the


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sampling and measurement system, gaseous emissions, and particle instruments performance can

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be found in the online SI. The elements of the analysis and the corresponding sections of the SI

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are shown in Figure 1.

Figure 1 Simplified flow chart visualizing the elements of the analysis with the corresponding sections in the online SI.

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Particle loss correction. A substantial fraction of particles entering the sampling system

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deposits on its inner walls mainly due to diffusion (long sampling lines) and thermophoresis

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(high thermal gradients). The particles are lost due to thermophoresis mainly in the first seven

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meters of the sampling system as the sample cools from the exhaust gas temperature (up to 600

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°C) to the sample line temperature upstream of the diluter (160 °C). The thermophoretic loss

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correction factor for this section of the sampling system was assumed to be independent of

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particle size and ranged from 1.19 to 1.33 (S5.2 in the SI).

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The diffusional losses depend on particle size and required information about the

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sampling system penetration, the particle size distributions (PSD), and the relationship between



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particle size and mass (effective density). The penetration efficiencies of the sampling system

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and instruments downstream of the probe were modeled using a software tool developed for the

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particle loss correction in nvPM measurement systems described in the Society of Automotive

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Engineers (SAE) Aerospace Information Report (AIR) 650442. We took into account the losses

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due to diffusion, sample line bends, particle size cut-off as well as the internal losses in the APC

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(diffusion, thermophoresis, and CPC counting efficiency). We estimated the number-based

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correction factors by multiplying the modeled PSD based on Scanning Mobility Particle Sizer

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(SMPS) measurement data by the penetration functions. The number-based correction factors

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ranged from 2 (take-off) to 11 (idle). For the mass-based losses, we combined the PSD model

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with particle effective density distributions25. The mass-based correction factor ranged from 1.1

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to 1.7 (S5.3 in the SI).

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Emission indices and fuel sensitivity. The loss-corrected BC mass and number concentrations

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were converted to EIs. The EIs were fitted with sixth order polynomials as functions of the

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combustor inlet temperature (T3). To calculate the LTO emissions, we used the interpolated EIs

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and fuel flow at sea level at the T3 values corresponding to the LTO flight modes (S6.4 in the

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SI).

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Since the BC emissions strongly depend on fuel composition, we estimated the effects of

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fuel composition variability (fuel aromatics content) using an empirical model developed on the

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same engine as in this study24. This model uses fuel hydrogen content in mass % (m% H) as the

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correlating variable. We extrapolated the EIm and EIn for standard fuel used in Europe (14.3 m%

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H) to the range from 13.8 m% H to 15.0 m% H, which captures the worldwide variability in

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commercially used jet fuel43.


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Estimation of non-LTO emissions. The emissions measured were corrected to flight conditions

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with the correlation from Döpelheuer and Lecht44 used in previous cruise BC emission estimates

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18,28,45

. This correlation corrects the EIm at a reference ground condition to a flight condition,

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whereas T3ref = T3flight (Figure 1 and S6.5 in the SI). The reference EIm is corrected for the

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combustor inlet pressure (p3), the air-fuel ratio (AFR), and adiabatic flame temperature (Tfl)

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effects. Previous estimates of cruise BC emissions expressed Tfl as linear functions of T3 as well

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as a function of both T3 and p318,45. We assumed the former, and thus the Tfl term is equal to one.

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To estimate the EIn, we assumed that the geometric mean diameter (GMD) of the PSD depends

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only on T3. This assumption is supported by emission measurements of a large turbofan engine

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at simulated flight altitude conditions46. The data extracted from Howard et al.46 show a clear

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trend of GMD as a function of T3 independent of the simulated flight altitude (S6.5 in the SI).

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Hence, the ratio of EIn to EIm is a unique function of T3.

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To determine the p3, T3, and AFR at any flight condition, we developed a detailed engine

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performance model calibrated to sea level performance data in GasTurb 12, commercial software

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for gas turbine simulation (S7 in the SI). We validated the model using in-flight data. Our model

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predicted the exhaust gas temperature (EGT) within 10 K over a wide range of cruise altitudes

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and ambient conditions and it also matched the flight recorder data for similar engine and aircraft

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types (S7.4 in the SI). The model input requires flight Mach number, altitude, deviation from the

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temperature in the international standard atmosphere (ISA) and engine performance limiters,

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such as rotor speeds or fuel flow. We ran the model using climb and descent rates derived from

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flight radar data and engine performance limiters based on the Boeing 737-800 Flight Planning

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and Performance Manual47 and Base of Aircraft Data (BADA) tables48 (S8 in the SI).



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RESULTS AND DISCUSSION

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SN – BC mass correlation. The ICAO-recommended method for estimating aircraft engine BC

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EIs has been the first order approximation version 3.0 (FOA3) that utilizes a correlation of BC

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mass concentration with SN23. FOA3 is based on data from measurement campaigns of aircraft

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engine emissions8. Recently, an alternative correlation has been proposed that predicts up to a

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factor of 3 higher BC mass concentrations than FOA39. However, our measured SN and BC

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mass concentrations corrected for thermophoretic loss agree well with FOA3 (Figure 2).

Figure 2 Correlations of BC mass concentration with the ICAO SN. The symbols represent averaged SN and BC mass concentrations at a given engine condition. The measured BC mass concentrations were corrected for dilution and thermophoretic loss as it will be required by the nvPM regulation. The error bars represent one standard deviation.

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The data shown in Figure 2 were collected for one engine using the multi-orifice

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sampling probe as well as a single orifice probe in additional measurements at various thrust

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levels, mostly above 50%, and various test point durations (S4 in the SI). All the data points are

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well below the proposed updated correlation. Stettler et al.9 developed the correlation from SN

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and total PM mass measurement (instead of BC) of diffusion flame soot. Diffusion flame soot

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with GMD typical for modern jet engines (< 50 nm) even after thermal treatment may contain as


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little as 50% BC49. Thus, correlating total PM with SN, which depends on BC content

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(“blackness”), leads to an overestimation of the BC mass.

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An improved SN-BC mass correlation can be developed only from standardized

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measurements of aircraft engine emissions because the PM emission characteristics change with

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engine power. Typically, BC mass concentration and GMD increase with engine thrust (here,

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from 10 nm at idle to 40 nm at take-off; S5.3 in the SI). SN depends on BC mass loading as well

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as on GMD as the filter paper used is more efficient for large particles9. As engine manufacturers

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will report their nvPM certification data together with SN (as long as the old SN regulation stays

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in force), ICAO plans to update the FOA338. The updated SN-BC mass correlation will be

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necessary for older out of production engines that are excluded from the nvPM emissions

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certification scheme but will remain in service for decades to come. For the SN range

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investigated here, the updated correlation will likely be close to FOA3.

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Emission indices and the LTO cycle. The BC emission characteristics strongly depended on

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engine operating conditions (Figure 3a, b). The EIn peaked at minimum idle (lowest combustion

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efficiency), but EIm was extremely low due to the small particle size (GMD at the exit plane ~12

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nm). The EIs were the lowest between 15 – 20% thrust (highest AFR; S7.4 in the SI), and from

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there on steeply increased with thrust (decreasing AFR). EIm peaked at maximum thrust, whereas

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EIn reached the maximum at ~65%. EIn decreased with further thrust increase likely due to

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particle coagulation within the engine. Such emission characteristics are typical for Rich-

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Quench-Lean (RQL) combustors, representative of most today’s in-service jet engines

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worldwide.

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The EIm and the BC mass emissions calculated for the LTO cycle were mostly

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overpredicted by methods using SN correlations and combustion models (Figure 3a, c). With



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respect to the results with nominal fuel (14.3 m% H), they overpredicted the BC mass emissions

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at taxi by up to a factor of 40. The FOA38 overestimated the low thrust emissions by up to a

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factor of 12 mainly due to the large uncertainties in the certification SN data (the maximum SN

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measurement error is estimated to be ± 3 SN8). Almost 97% of the total BC mass was emitted

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during take-off and climb. Thus, any under- or overprediction for these phases has the biggest

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impact on the estimated total LTO BC emissions. The formation-oxidation (FOX) method18

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overestimated the total BC mass by up to a factor of 4. On the other hand, the improved FOX

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(ImFOX) method50 as well as the ICAO-recommended FOA3 underpredicted the BC mass at

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high thrust by up to 40%, which is a good estimate considering the uncertainties (we estimated

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38% uncertainty for the EIm; S6.1 in the SI). The approximative methods can be potentially

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improved as standardized BC mass emissions data become available but will remain applicable

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only to engines that emit maximum BC mass at take-off (FOX and ImFOX) and have

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measurable SN (SN correlations).


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Figure 3 Emission indices of BC mass (a) and BC number (b), and emissions from the LTO cycle per aircraft (2 engines) in terms of BC mass (c) and BC number (d). The error bars represent the estimated EI uncertainty of 38% and 32% in terms of mass and number, respectively (S6.1 in the SI).

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In contrast to the BC mass emissions, the BC number emissions at taxi constituted up to

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30% of the total LTO emissions, depending on the fuel composition (Figure 3d). The fuel

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composition affects the BC emissions at low power the most (S6.3 in the SI). For example, the

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cumulative taxi and approach emissions with the high aromatics fuel (13.8 m% H) used in North

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America43 and low aromatics fuel (15.0 m% H), typical for a fuel blend of Jet A-1 with synthetic

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jet fuel43, differed by a factor of ~6. The fuel composition negligibly affected the total BC mass

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emitted from the LTO cycle. However, the total BC number emissions can be readily drastically



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reduced using fuel blends due to the high contribution of the taxi and approach modes, which

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would, in turn, improve the airport air quality.

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An accurate assessment of the airport air quality is demanding because airport operations

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differ from the regulatory LTO cycle used for engine technology comparison both in terms of

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time and engine power used. Except in an emergency, pilots utilize less thrust than the engines

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are capable of producing. Operators use derated engines (electronically reduced rated thrust) and

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flexibly reduce take-off thrust as much as conditions permit to extend the engine service life and

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optimize the overall cost. Since the BC mass emissions of the engine type investigated here peak

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at maximum thrust, reduced take-off thrust diminishes the total BC mass emissions. For

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example, a Boeing 737-800 with engines derated by 15% would produce 35% less BC mass per

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standard LTO cycle. However, the total BC number emissions calculated for the derated engine

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would be 25% higher, because the taxi condition (7% of the derated take-off thrust) corresponds

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to a lower power setting at which the EIn is 60% higher (Figure 3b, S6.4 of the SI). In practice,

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the taxi or idle thrust is lower than 7%. Compared to the LTO taxi setting, the fuel flow of an on-

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wing engine of a Boeing 737NG at idle with nominal bleed air extraction (cabin air conditioning)

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is ~10% lower.51 Since the EIn peaks at minimum idle, the actual taxi EIn may be up to an order

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of magnitude higher than at the LTO taxi setting. Thus, the regulatory LTO cycle may

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underestimate the actual BC mass and number emissions from busy airports with long taxi times.

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Cruise. The EIs at cruise were strongly affected by ambient conditions and fuel composition. For

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the nominal case (ISA; 35,000 ft altitude; Mach 0.8; 14.3 m% H), we determined EIm of 11

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mg/kg fuel and EIn of 6.8×1014/kg fuel (Figure 4). When an aircraft flying with a constant thrust

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and Mach number encounters warmer air, the engines need to run at a higher rotational speed to


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compensate for the loss of thrust due to decreasing air density, and T3 and BC emissions

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increase. Cold air has the opposite effect (S8 in the SI). The cruise EIs varied less due to ambient

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temperature (±10 K range) than due to fuel composition. The EIs varied with fuel composition

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by up to 50%, highlighting a possible reduction of aviation BC emissions and their climate

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impacts at cruise using low-aromatics fuels. These predictions are in line with recent airborne

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studies (ACCESS I and II campaigns) investigating effects of fuel composition on BC emissions

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using a similar engine type52.

Figure 4 Comparison of cruise emission indices with chase plane studies and estimates obtained by predictive methods.

Our cruise BC estimates are in the range of EIs found during airborne studies of various

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types of passenger jets in the 1990s28 (Figure 4). However, those EIm and EIn were calculated

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from measured particle size distributions. Also, the measurements were done at lower altitude,

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speed, and weight to accommodate the chase plane.Therefore, the BC emissions were likely

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lower than at our nominal cruise condition. For example, for the flight conditions of the 737-300

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in Figure 4 (26,000 ft and Ma 0.53) we obtained 30% lower fuel burn and EIm of just 3 mg/kg

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fuel.



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The cruise EIm estimates compared to those calculated by previously published methods.

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The EIm estimates obtained with the methods of Peck et al.45, Stettler et al. (FOX)18, and

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Abrahamson et al. (ImFOX)50 for the fuel flow corresponding to cruise at 35,000 ft and Mach 0.8

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were within 50% of our data. However, the method of Peck et al. and FOX predict cruise BC

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emissions by correcting their ground-based estimates, which we have shown to overestimate our

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measurements. Using our measured BC mass concentrations for their respective ground

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reference conditions decreased their cruise estimates by up to a factor of 10. ImFOX, on the

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other hand, is calibrated to cruise BC measurements of the predecessor of the engine tested here.

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The ImFOX method also uses fuel hydrogen content for scaling the BC mass concentration. It

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predicts a range of EIm overlapping with ours but is limited only to ground and cruise, whereas

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our model can predict the engine performance parameters at any flight condition.

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Flight Mission. Since the Boeing 737 aircraft is used worldwide for a broad range of flight

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missions lasting from under one hour to up to eight hours, the emissions from LTO, climb to

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cruise altitude, and descent may represent a major fraction of the total emissions depending on

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the flight time (Figure 5). For a one hour flight, over 70% of the BC mass and number emissions

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came from the climb phase and over 25% dispersed under 3,000 ft altitude (LTO). The descent

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phase with engines at flight idle contributed less than 0.5% and 3% in terms of BC mass and

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number, respectively.With increasing flight time, the cruise BC mass and number emissions

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reached 50% of the total emissions after four and two hours, respectively. Thus, the climb can

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much contribute to the total BC emissions of short to medium-haul flights.


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Figure 5 Ratio of the BC mass (a) and number (b) emissions per flight phase and the total emissions as a function of flight time (nominal fuel composition with 14.3 m% H). The flight time on the x-axis is the airborne time above 3,000 ft altitude.

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The mission EIm (time-weighted arithmetic means of all flight phases; S8.4 in the SI)

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increased or decreased depending on the cruise EIm for a given fuel composition. The EIn, on the

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other hand, increased with flight time for all fuel composition cases (Table S13 in the SI). For

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the nominal fuel, the EIn increased from 5.15×1014/kg for a one hour flight to 6.53×1014/kg for a

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seven-hour flight. For the same interval, the mission EIm moderately decreased from 11.94

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mg/kg to 11.20 mg/kg. These estimates are a factor of 2 to 3 lower than the mission EIs used for

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calculating global fleet emissions (38 mg/kg for the 1992 fleet28 and 25 mg/kg for the 2000

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fleet29). Given the high number of in-service Boeing 737NG and other aircraft with similar

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engines (Airbus A320 family), our results are representative of the current fleet of single-aisle

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airliners (65% of all passenger aircraft2).

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Emissions per passenger-distance. The BC emissions per passenger-km of great circle distance

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decreased with flight time regardless of fuel composition (Figure 6). For the nominal fuel, the

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normalized BC mass and number emissions decreased with flight distance by up to a factor of 4

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and 2, respectively. The drop was most significant in the first three hours of flight, and any



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longer flight only moderately decreased the emission rates. The range of per passenger-km

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emission rates increased when we factored in the fuel effects. A short flight using 13.8 m% H

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fuel produced up to a factor of 9 more BC mass and a factor of 5 more BC number than a long

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flight using fuel with 15.0 m% H.

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Figure 6 BC mass and number emissions per passenger (assuming 130 people on board of a 737-800 at 80% occupancy) and distance.

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We took the ranges of BC emission rates per passenger-km and compared them with road

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vehicles (Figure 7). We assumed two car passengers and 30 bus passengers and used published

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data for various engine technologies53,54. We note that the BC data for vehicles shown in Figure

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7 were obtained with methods different from the nvPM standard methodology. The BC mass was

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determined by correcting the filter-based total PM mass using the reported upper estimate of the

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BC content for each vehicle type. The BC number concentration was measured with a particle

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size cut-off of 23 nm instead of 10 nm used for the aircraft engines. Regarding BC mass, the

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aircraft engine emissions were in the middle of the range reported for the various vehicle engine

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technologies (Figure 7a). For a short flight and 13.8 m% H, the BC mass emissions were

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comparable to a gasoline direct injected (GDI) car, which is characterized by relatively high

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particle emissions, and decreased with flight distance and increasing fuel hydrogen content to a


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level of a common port fuel injected (PFI) gasoline car. However, the BC number emissions

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were as high as a diesel car without a particulate filter (DPF) (Figure 7b). This assessment shows

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that the mass-based BC emissions per passenger-km of the engine type investigated are relatively

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low, whereas the number-based BC emissions are considerable. This finding is in line with the

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general emission characteristics of modern gas turbine engines that produce particles with small

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GMD and thus low BC mass emissions, but relatively high number-based emissions. At the same

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time, we note that although these findings are relevant for a large fraction of the current fleet,

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they would not apply to other engine types, e.g. with lean-burn and staged combustors.

Figure 7 Comparison of the BC mass (a) and number (b) emissions per passenger-km. Vehicle emissions data were taken from Giechaskiel et al. and Hallquist et al. and normalized per two car passengers and 30 bus passengers. The abbreviations for engine technology are: D – diesel without any emission control, DPF – diesel with a particle filter, PFI – gasoline port fuel injection, and GDI – gasoline direct injection. The solid vertical lines represent values for 3-hour flights and the nominal fuel composition.

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Implications. In the near future, estimates of aviation BC emissions can be predicted more

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accurately using standardized BC measurement data. We have shown first such estimates of BC

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mass and number emissions for all flight phases of the most widely used airliner determined

318

from certification quality data. We have provided updated emission indices for cruise as well as

319

for the flight mission and looked at the sensitivities to fuel composition and ambient temperature.



320

For the representative cruise at ISA conditions with nominal fuel, the determined mission EIm is

321

half the estimate used for the BC emission rates of the global fleet in the year 200029 and merely

322

13% of the average EIm reported by the FOX method for the 2005 fleet18. Also, the LTO

323

emissions determined here strongly contrast with recent studies that claim FOA3 to significantly

324

underestimate BC mass emissions from aircraft turbine engines9,18. We found a good agreement

325

with the SN – BC mass correlation used in the FOA3. However, our data also suggest FOA3

326

may overestimate the mass-based emissions from taxiing aircraft by up to an order of magnitude.

327

Since airports face regulatory limits on ambient PM mass concentration, they need better

328

emission inventories and tools for implementing the best practices with respect to airport air

329

quality. The question remains whether the BC mass concentration is a useful metric for that

330

because it does not capture the considerable number of soot nanoparticles an aircraft turbine

331

engine can emit at the detection limit of the current BC mass instruments while producing no

332

visible smoke.

333

ASSOCIATED CONTENT

334

Supporting Information. Engine emission tests, description of the exhaust sampling and

335

measurement system, cross-check of gaseous emissions with ICAO certification data, smoke

336

number analysis, particle loss correction, calculation of the non-volatile PM emission indices,

337

engine performance model, flight mission calculation.

338

AUTHOR INFORMATION

339

Corresponding Authors

340 341 342

*

Phone: +41 58 765 46 08. Fax: +41 58 765 69 63. E-mail: [email protected]

*

Phone: +41 44 633 36 21. Fax: +41 58 765 69 63. E-mail: [email protected]

Notes


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343

The authors declare no competing financial interest.

344

ACKNOWLEDGEMENTS

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Funding was provided by the Swiss Federal Office of Civil Aviation (FOCA) through the

346

projects “Particulate Matter and Gas Phase Emission Measurement of Aircraft Engine Exhaust”

347

and “EMPAIREX – EMissions of Particulate and gaseous pollutants in AIRcraft engine

348

EXhaust”. The support by the Swiss National Science Foundation through the project

349

206021_157663 “A traversing probe for mapping the particulate and gaseous emissions at the

350

aircraft engine exhaust plane” is acknowledged. Additional funding for the engine lease was

351

provided by the US Federal Aviation Administration, the European Aviation Safety Agency, and

352

Transport Canada. We further acknowledge the following organizations and individuals for

353

technical support, instrumentation, and analysis: SR Technics Switzerland AG, Andrea Fischer at

354

Empa, Stefan Fischer – SF Aviation, Cardiff University Gas Turbine Research Centre, GE

355

Aviation, and Snecma.

356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375

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Graphical abstract 47x26mm (300 x 300 DPI)


Assessment of Particle Pollution from Jetliners: from Smoke Visibility to

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