Impact of Alternative Fuels on Emissions Characteristics of a Gas

Aug 22, 2012 - Turbine Engine − Part 2: Volatile and Semivolatile Particulate Matter ... semivolatile PM emissions from a gas turbine engine resulti...
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Impact of Alternative Fuels on Emissions Characteristics of a Gas Turbine Engine − Part 2: Volatile and Semivolatile Particulate Matter Emissions Paul I. Williams,*,†,‡ James D. Allan,†,‡ Prem Lobo,§,∥ Hugh Coe,† Simon Christie,∥ Christopher Wilson,⊥ Donald Hagen,§ Philip Whitefield,§ David Raper,∥ and Lucas Rye⊥ †

School of Earth, Atmospheric and Environmental Science, University of Manchester, Manchester M13 9PL, United Kingdom National Centre for Atmospheric Science (NCAS), University of Manchester, Manchester M13 9PL, United Kingdom § Center of Excellence for Aerospace Particulate Emissions Reduction Research, Missouri University of Science and Technology, Rolla, Missouri 65409, United States ∥ Centre for Air Transport and the Environment, Manchester Metropolitan University, Manchester M1 5GD, Uunited Kingdom ⊥ Department of Mechanical Engineering, University of Sheffield, Sheffield S1 3JD, United Kingdom ‡

S Supporting Information *

ABSTRACT: The work characterizes the changes in volatile and semivolatile PM emissions from a gas turbine engine resulting from burning alternative fuels, specifically gas-to-liquid (GTL), coal-toliquid (CTL), a blend of Jet A-1 and GTL, biodiesel, and diesel, to the standard Jet A-1. The data presented here, compares the mass spectral fingerprints of the different fuels as measured by the Aerodyne high resolution time-of-flight aerosol mass spectrometer. There were three sample points, two at the exhaust exit plane with dilution added at different locations and another probe located 10 m downstream. For emissions measured at the downstream probe when the engine was operating at high power, all fuels produced chemically similar organic PM, dominated by CxHy fragments, suggesting the presence of long chain alkanes. The second largest contribution came from CxHyOz fragments, possibly from carbonyls or alcohols. For the nondiesel fuels, the highest loadings of organic PM were from the downstream probe at high power. Conversely, the diesel based fuels produced more organic material at low power from one of the exit plane probes. Differences in the composition of the PM for certain fuels were observed as the engine power decreased to idle and the measurements were made closer to the exit plane.

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INTRODUCTION

engines running alternative fuels are still limited, but initial results suggest that PM emissions are reduced.4−6 Traditionally, PM number and mass data from engines are reported as emission indices (EI), as number or gram of emitted quantity per kg of fuel burned. This allows comparisons between different engines to be made. The majority of PM emitted at the engine exit plane is nonvolatile soot.3 As the exhaust plume expands and cools, volatile species present in the gas phase at the engine exit plane condense and form new PM which are volatile and semivolatile in nature and are broadly separated into sulfates and organics. The amount of sulfates has been shown to be proportional to the fuel sulfur content.7 The total organic mass or EI is often reported, but the detailed composition of the organics is not.

Recently, there has been significant interest in the particulate matter (PM) emissions from aircraft and its associated impacts on climate and air quality.1−3 While many studies focus on the aircraft engines, a significant fraction of the emissions at airports are from other sources such as ground power supply units and auxiliary power units (APU), the latter housed in the tail of aircraft, and both of which can be used to provide power while an aircraft is stationary or to start the main engines. Consequently, these units contribute to the total emissions at airports, but are poorly characterized. The aviation industry is investing significant effort in the use of alternative fuels. Any fuel that could be considered as a candidate to replace or supplement the traditional kerosenebased Jet A/Jet A-1 must meet stringent criteria due to the required reliability of the combustion process and the compatibility with the existing infrastructure and aircraft technology. Measurements of emissions from gas turbine © 2012 American Chemical Society

Received: Revised: Accepted: Published: 10812

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Table 1. Test Points and Data for the Different Fuels Sampled with Tests with no AMS Data or Unusable Data Omitted run

probe

RPM

diluted CO2 concentration PPM (± %)a

2 3 4 6

2 3 3 1

19 500 19 500 34 200 34 000

599.4 (1.00) 466.0 (3.80) 689.0 (2.19) 1344 (1.01)

2 3 4 5 6 7

2 3 3 2 1 1

21 600 21 900 34 500 34 300 34 300 22 900

1239 (1.01) 677.5 (1.03) 649.0 (1.91) 396.5 (1.08) 2138 (1.05) 1458 (1.01)

2 3

3 3

34 000 21 000

713 (1.05) 613 (1.01)

2 3 4 5 6 7

2 3 3 2 1 1

21 900 22 000 34 000 34 500 34 000 22 600

2152 (1.00) 914.8 (8.87) 1159 (1.92) 1252 (1.01) 1138 (1.01) 2401 (1.00)

2 3 4 5 6 7

2 3 3 2 1 1

22 400 22 500 34 600 34 500 34 500 22 900

2159 (1.00) 463.6 (5.36) 850.9 (1.58) 1830 (1.00) 1846 (1.00) 2004 (1.02)

2 3 4 5 6

2 3 3 2 1

19 000 18 900 33 800 33 000 32 000

1389 (1.01) 663 (6.32) 701.4 (1.45) 1385 (1.02) 1432 (1.07)

1 2 3

1 2 3

19 800 19 800 19 500

433.6 (1.03) 426.8 (1.04) 903.5 (5.50)

2 3 4 5 6

2 3 3 2 1

21 750 21 800 31 500 32 600 32 900

1,392 (1.01) 626.4 (3.68) 1563 (2.37) 1445 (1.02) 1523 (1.01)

1 2 4

3 2 1

34 000 34 000 20 900

1342 (1.60) 396 (1.03) 1293 (1.42)

organic mass concentration μg m−3 (±%)c

DF (±%)b

Test 1 Jet A-1 51.7 (4.12) 66.4d (5.52) 44.4d (4.56) 22.8 (4.13) Test 2a CTL 20.8 (4.13) 37.6d (4.13) 40.9d (4.43) 67.0 (4.14) 12.4 (4.14) 17.5 (4.13) Test 2b CTL 37.7d (4.14) 41.7d (4.13) Test 3 GTL 11.6 (4.12) 27.2d (9.73) 22.3d (4.44) 20.7 (4.13) 22.7 (4.13) 10.4 (4.12) Test 4 Blend 11.8 (4.12) 55.0d (6.69) 31.3d (4.30) 14.6 (4.12) 14.4 (4.12) 12.7 (4.13) Test 5 Biodiesel 20.0 (4.13) 41.9d (7.48) 36.8d (4.25) 18.6 (4.13) 18.0 (4.13) Test 6 Diesel 62.8 (4.13) 63.8 (4.13) 30.2d (6.80) Test 7 Jet A-1 18.2 (4.13) 40.5d (5.44) 17.0d (4.65) 18.4 (4.13) 17.5 (4.13) Test 8 Diesel 20.7d (4.31) 70.1 (4.13) 21.1 (4.24)

PM org emission index μg kg−1(fuel) (±%)

2.46 (11.21) 82.6 (98.31) 3135.7 (34.49) 12.3 (12.90)

6.8 (11.90) 1486 (98.39) 17 205 (34.72) 15.5 (13.51)

3.50 (10.00) 13.6 (36.22) 2159 (10.68) 529.7 (10.00) 17.6 (10.00) 9.92 (11.38)

4.6 (10.77) 46.8 (36.44) 12 956 (11.40) 2231 (10.77) 13.7 (10.77) 11.0 (12.07)

165.0 (11.80) 9.39 (24.20)

802.5 (12.46) 30.5 (24.53)

1.86 (10.00) 21.9 (14.81) 530.7 (11.69) 11.3 (10.00) 3.28 (11.47) 9.42 (10.00)

1.4 (10.77) 51.3 (15.34) 1123 (12.35) 15.0 (10.77) 4.8 (12.14) 6.4 (10.77)

3.25 (67.69) 50.4 (45.81) 426.6 (21.65) 633.4 (89.66) 81.0 (91.85) 11.0 (11.75)

2.5 (67.81) 889.7 (45.98) 1,505 (22.01) 581.8 (89.75) 73.8 (91.93) 8.9 (12.41)

12 072 (10.21) 3049 (49.42) 544.2 (18.61) 56.2 (10.00) 835.7 (59.05)

14 216 (10.97) 17,593 (49.58) 2856 (19.04) 69.1 (10.77) 993.5 (59.19)

4811 (60.83) 19 412 (10.00) 5664 (62.60)

18 029 (60.96) 73 906 (10.77) 17 565 (62.73)

14.9 (10.00) 69.8 (29.73) 312.8 (10.00) 147.2 (10.00) 26.3 (10.00)

17.6 (10.77) 433.0 (30.00) 441.8 (10.77) 173.0 (10.77) 29.3 (10.77)

1026 (14.94) 10.4 (10.00) 45.3 (57.67)

1814 (15.47) 44.9 (10.77) 56.9 (57.81)

Combined standard error and instrument accuracy of 1%. bCombined diluted CO2 error and raw CO2 standard error of ±4%. cCombined standard error (where applicable) and instrument accuracy of 10%. dDF (dilution factor) values based on mixing with ambient air, not through addition of N2.

a

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Presented in this paper are the results from a series of experiments in which a gas turbine engine was run on several alternative fuels, a standard Jet A-1 and diesel. The results focus on the characteristics of the organics, and compares and contrasts the mass spectral fingerprints of the different fuels relative to Jet A-1. Characterization of the gas phase and total PM emissions are presented in the accompanying paper, part 1.8

EXPERIMENTAL SECTION

Sample Setup. During the autumn of 2009, a series of experiments were performed at the University of Sheffield’s Low Carbon Combustion Centre, studying the emissions from a single spool gas turbine engine, a reconditioned Rolls Royce Artouste Mk113 auxiliary power unit (APU). Measurements included the following: total and nonvolatile particle number−

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sizing is ±15% on the basis of analysis of previous calibration data; however, relative variations reported here should be accurate. The Cambustion DMS500s were used to gather real-time size distribution information and PM number concentration of the exhaust from 5 to 1000 nm. One DMS500 measured the total PM, while the second DMS500 had a thermal denuder (operating at 300 °C) upstream to remove any volatile PM, and thus measured the nonvolatile PM. The DMS500 has been used in previous studies to measure the PM emissions from gas turbine engines burning conventional14as well as alternative fuels.6 Detailed results from this study using the DMS500 can be found in Lobo et al.8 Losses for the sampling system were corrected for in the final data and have been previously reported.9 The DMS500 reports the mobility diameter, Dm, with an accuracy of ±10%. A fast response CO2 detector (Sable Systems model CA-2A) was used to monitor diluted CO2 concentrations in the PM lines, and coupled with the undiluted CO2 concentrations obtained from the gas probe established dilution factors in the PM lines. Data Analysis. The standard SQUIRREL analysis toolkit was used for the analysis of AMS data, with the PIKA and APES high-resolution analysis modules. The standard mass spectral data product from the AMS is the unit mass resolution (UMR) mass spectrum, which is processed using fragmentation tables15,17 to infer fractional contributions of multiple chemical species to individual peaks. These peaks are then summed to give total loadings for the different species. However, the instrument’s resolution (m/dm ∼ 105) means that, by using peak fitting, the contributions to individual peaks according to elemental composition can be determined explicitly.11,16 This also allows the OM:OC, O:C, and H:C ratios to be estimated.17 Analysis of the high resolution data in this paper is restricted to fragments with an m/z < 100 where resolutions are higher (see previous references for details).

size distributions; total particle mass; mass−size distributions; and chemical compositional analysis of the particulate and gaseous components. Two PM probes and a water cooled gas probe were mounted on a stainless steel sheet behind the APU at a distance approximately equal to one-half of the exhaust diameter. The two probes were positioned in close contact about the center line axis of the exhaust. The combined mount and inlets obstructed less than 5% of the exhaust cross sectional area. Another PM probe (1.5 in. i.d.SS) was located ∼10 m downstream of the exhaust duct to study PM evolution in the near field. Probe 1 was designated as one of the exhaust exit plane probes with N2 dilution added at the tip. Probe 2 was the second exit plane inlet but with dilution added ∼1 m downstream of the tip. Probe 3 was the downstream inlet at ∼10 m from the exit plane. The probes were joined to a common sampling system designed by Missouri University of Science and Technology (MS&T). Sample flowed down each line continuously to prevent stagnation, and sample for a particular probe was taken by manually switching valves. The PM probes and sample lines have been used in previous studies.6 The transmission of particles down the line was found to vary with size. The transmission was ∼95% between 100 and 600 nm, decreasing to ∼25% at 10 nm in number space.9 The gas probe continuously sampled exhaust for a suite of gas analysers monitoring NOx, CO, CO2, and total unburnt hydrocarbons (UHC), the full details of which are described by Rye, 2012.10 The running conditions of the APU (temperatures, pressures, RPM, fuel flow, etc.) were also monitored and logged. The APU ran at two settings of nominally high and low power. The set points were achieved by controlling the fuel flow, which is controlled by the compressor exit pressure and is proportional to the revolutions per minute (RPM). Nominal RPMs for high power were 31 500−34 500 and 19 000−22 500 for low power. Evaluation of the stability of the engine during the experiment can also be assessed by analyzing the EI of CO2. The combined data showed a reasonable ability to return the APU back to the same conditions for each fuel. A detailed analysis of the performance of the APU is presented elsewhere.9,10 The APU was run on standard aviation kerosene (Jet A-1, Merox, and hydrotreated) from Royal Dutch Shell, commercial red diesel, and several alternative fuels: two synthetic paraffinic kerosenes produced from the coal-to-liquid (CTL, fully synthetic jet fuel from Sasol) and gas-to-liquid (GTL, from Shell) processes via the Fischer−Tropsch method, rapeseed feedstock derived biodiesel (rapeseed methyl ester produced via transesterification, supplied by Greenergy International Ltd.), and a Jet A-1/GTL mix blended 50:50 by volume in-house. Fuel properties are reported elsewhere.8,9,10 Equipment. Presented in this paper are the results from an Aerodyne high resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) 11,12 and two Cambustion DMS500s.13 The HR-ToF-AMS flash vaporizes particles at 600 °C and analyzes the resultant vapors using 70 eV electron ionization and high-resolution time-of-flight mass spectrometry. The AMS has a 100% transmission of particles between 60 and 600 nm, which rapidly falls away either side of that window. It is also capable of sizing particles aerodynamically in particle time-of-flight (pTOF) mode, separate to the chemical compositional analysis. The diameter reported is called the vacuum aerodynamic diameter, Dva. A size calibration for this work was not available, and it is estimated that the accuracy in

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RESULTS AND DISCUSSION Table 1 shows a summary of all the test points and the CO2 dilution factor and organic loadings for each test, where available. The emission indices were calculated as detailed in Onasch et al.3 and the EI (CO2) values for each fuel are given by Rye, 2012.10 Organic Mass Emissions. Figures 1 and 2 show the total organic mass for the different probes and power settings for Jet

Figure 1. Organic mass concentration as a function of probe and power for Jet A-1, GTL, CTL blended fuel. 10814

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required for reliable fits to be made in the analysis. Using the average MS for test 1, run 4, probe 3 as a reference MS and scatter plotting the concentration at a given m/z against the other fuels concentration at a given m/z, showed that the r2 between the reference MS and the other Jet A-1 tests was 0.92 or higher, except the test 1, run 6, which was 0.85. This implies the composition of the particles for the majority of Jet A-1 cases is independent of probe and power within the resolving ability of the instrument. Similarly, for GTL, CTL, and the blended fuel, the same result was found, with the majority of probes and power settings producing MS that were the same as Jet A-1 and had r2 above 0.90. At high power on probe 3, the r2 relative to the reference ranged from 0.97 to 0.99 for all fuels, including the diesel based fuels. The high degree of correlation for certain fuels and conditions allows an average MS to be generated. This is shown in Figure 3, using the criteria of r2 > 0.90 and a total

Figure 2. Organic loadings as a function of probe and power for diesel and biodiesel.

A-1, GTL and CTL (Figure 1), and biodiesel and diesel (Figure 2). Data is presented as absolute loadings as measured by the HR-ToF-AMS, while the EIs are presented in Table 1. Displaying data as EI shows the same variability as absolute loadings. For Jet A-1, and GTL and CTL, the mass of PM organic content measured is generally greater when the APU is run at high power. At high power, the loadings also increase as the sample point goes from probe 1 through 3. Probe 1 sampled from the exhaust exit plane and was diluted at the tip, theoretically suppressing all condensation processes. Probe 2 also sampled from the exit plane but diluted 1 m from the tip allowing some re-equilibration to occur. Probe 3 is a downstream sample with no dilution other than mixing with ambient air. Conceptually, as the sampling point moves downstream of the exhaust plane and/or chemical processes are able to occur, the organic mass increases. It appears that, at the 10 m probe, condensation of organic material as the gases cool dominates over dilution due to mixing with ambient air. The diesel and biodiesel PM organic emissions are very different. The peak measured mass occurs at probe 2 on low power for both fuels, and the amount of material sampled at probe 3 was also higher at low power compared with high power. Due to the short sample time and the AMS averaging period of 30 s, there is no data for diesel at high power on probe 1. The amount of organics detected at probe 1 on low power for biodiesel was below detection limit (∼50 ng m−3). This limits the conclusions that can be drawn about probe 1. However, it appears that, despite dilution, considerable amounts of organic mass are condensing from the gas phase for diesel on probes 1 and 2 and biodiesel on probe 2. It is worth noting that the dilution factors on probe 2 for the biodiesel and diesel at low and high powers are similar (see Table 1). The difference in concentrations between low power and high power is not a result of significantly different dilution factors. This implies that there is more condensable material produced from the diesel based fuels at low power. There is considerable variation in the levels of PM reported for all fuels for a given setting. This could be due in part to the temperature of the APU, but equally that the volatile fraction of the APU output is not constant. Compositional Analysis. For each test point listed in Table 1 an average mass spectrum (MS) was generated. High resolution analysis was applied where the average loading was ∼10 μg m−3 or higher, which was found to be the minimum

Figure 3. Average mass spectra for all fuels with an r2 > 0.90 and total mass below 100 m/z ≥ 90%.

mass less than 100 m/z ≥ 90%. The latter criterion is for the high resolution analysis, which is limited to m/z < 100. Applying the high resolution analysis shows that the dominant contribution to the average MS is the CxHy fragments (∼73%), with the CxHyOz the second largest (∼22%), Table 2. Also shown in Table 2 are the results of elemental analysis, which shows a high H:C ratio of 1.897 and low O:C 0.122, consistent with the organic aerosol being highly saturated and with little oxygenation. The GTL, CTL, and blended fuel test points not included in the average occurred when the APU was run at low power. These produced a decrease in the relative fraction of the CxHy fragments and an increase in CxHyOz (Table 2). This is most evident for probe 1 at low power, where there was data above the detection limit for these fuels. The fragmentation differed significantly from the reference Jet A-1, with the r2 varying from 0.53 to 0.66. The dominant peak for these settings was m/z 59 identified explicitly as the C3H7O fragment, with increases in the fraction of peaks at 85, 87, 88, 99, 101, and 103, shown in Figure 4. The distinct marker at m/z 171 present in Figure 3 is insignificant in Figure 4. It is possible that, at the lower APU power setting, there is more incomplete combustion, which is more conducive to the formation of oxygenated species such as carbonyls and alchohols. It is also possible that the aliphatic species produced are of a different volatility, such that the dilution at the sampling tip inhibits the condensation of the species responsible for the CxHy fragments (e.g., alkanes), increasing the prominance of the CxHyOz fragments in the mass 10815

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Table 2. Relative Fractions (%) of the Two Main Compounds from the High Resolution Analysis, Elemental Analysis, the Total Mass below m/z 100 and the Correlation between the Fuels and the Reference Jet A-1 with Standard Deviations in Parentheses CxHy (%) av MS av diesel biodiesel LP P1a a

73.93 77.65 73.40 54.97

(3.99) (2.07) (2.40) (6.07)

CxHyOz (%) 21.92 16.10 21.80 41.57

(3.80) (2.58) (1.13) (4.68)

OM:OC ratio 1.33 1.29 1.31 1.45

O:C ratio

(0.03) (0.03) (0.01) (0.03)

0.12 0.09 0.10 0.21

(0.03) (0.03) (0.01) (0.02)

H:C ratio 1.90 1.89 1.86 1.97

(0.04) (0.02) (0.03) (0.02)

mass fitted (%) 94.11 80.88 91.90 93.17

(1.23) (6.75) (2.81) (0.61)

r2 0.97 0.93 0.82 0.58

(0.02) (0.03) (0.05) (0.06)

LP P1 are the low power settings on probe 1 for GTL, CTL, and blended fuel.

Figure 4. Mass spectra for biodiesel and low power, probe 1 (LP P1) not meeting the average MS criteria.

of low m/z fragments and increase in the relative fraction of the larger m/z (87% < 100 m/z compared with 95%). However, this artifact does not produce additional fragments. Furthermore, this would manifest in a systematic decrease of the slope of the scatter plots when comparing UMR data rather than only reduce the r2 value. Therefore, there may be a slight underestimation of the total mass below 100 m/z for the biodiesel probes on low power, especially probe 2 (loadings 12 560 μg m−3, Table 1), but the fragmentation should remain the same. The only diesel test to meet the average MS criteria was probe 3 on high power. On all other settings, the total mass below 100 m/z is less than 90%. This could be in part due to peak saturation as discussed above, but for test 8, run 4, the mass loading is only 45 μg m−3 compared with 4810 μg m−3 during test 6, run 1, suggesting the signal below m/z 100 is being suppressed. The r2 values remain high as the CxHy fragments dominate the MS below 100 m/z. The results have focused on the comparison of the composition of the organics as a function of fuel, but the one aspect not considered is the lubrication oil used by the APU. The oil, which may be unburnt but partially pyrolyzed, will contribute to the organic aerosol. The results here have not attempted to separate the contribution from the fuel and the contribution from the oil. It is possible that the similarity between Jet A-1, GTL, CTL, and the blended fuel is due, in part, to the presence of the same lubrication oil. It has been

spectrum. However, some test points at low power did meet the average MS criteria, without any discernible pattern or trend. The median dilution factor for example both for those meeting the criteria and those not was ∼30. The only conclusion that can be drawn is that those not meeting the criteria were when the APU is at low power, implying the chemical composition of emissions was much more variable under these conditions. Biodiesel shows different characteristics from the other fuels discussed above. Probes 2 and 3 at high power show a similar fragmentation pattern to the reference Jet A-1 and meet the criteria to be included in the average MS. The other test points which did not meet the average MS criteria have similar contributions from the different fragments to Jet A-1 and similar elemental analysis results (Table 2); however, the r2 is much lower (0.72−0.79) with an increase in the relative contributions in the 60−100 m/z range, shown in Figure 4. Furthermore, this fragmentation is distinct from the other fuels shown in Figure 4 which are not included in the average MS. Some care is needed in interpreting this data. Laboratory tests using lubrication oil at high and low mass loadings have shown that there were differences due to the loading levels. At mass concentrations >3 mg m−3, some of the larger peaks begin to saturate the analogue to digital converter and the instrument response loses linearity. In laboratory tests with turbine lubricating oil, this manifested as a decrease in the contribution 10816

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previously suggested that m/z 85 is a strong marker for lubrication oil,7 being either C6H13 or C5H9O. Analysis at Manchester of BP lubrication oil showed that both fragments are present in a ratio of ∼0.18 (C6H13:C5H9O). Other research18 has also shown that lubricating oils have more C5H9O than C6H13. Furthermore, the work suggests that a simple ratio of two key markers from the MS (71 and 85) can be used to determine the amount of lubrication oil present. Although the oil used in the APU was different from the oils discussed above, the results suggest only ∼5−15% of the total signal was due to oil, suggesting the majority of the signal is due to combustion products. Effective Density and Mass-Mobility Exponent. The characteristics of the mass−size distribution data from the HRToF-AMS are presented in work by Rye et al.,9 which showed a dominant peak around 80−100 nm and smaller peak centered between 400 and 600 nm and that the composition of the volatile fraction in each was the same. Further analysis since then has found that the modal diameter of the low diameter mode did not have a significant dependence on the total mass of organics for loadings less than 1 mg m−3. At loadings greater than 1 mg m−3, the modal diameter of the low diameter mode increased as the organic loadings increased, and the secondary mode was often lost in the tail of the primary mode. The DMS500 instruments measured the total (volatile plus nonvolatile) and nonvolatile number size distributions. By converting the DMS500 total number distributions to volume, it is possible to estimate the effective density of the particles. This is achieved by converting the pTOF data to volume assuming an effective density and converting the HR-ToF-AMS vacuum aerodynamic diameter to mobility diameter, as measured by the DMS500.19 The effective density is adjusted until the modal diameters in volume space are the same. It is important to note that the HR-ToF-AMS sizes the ensemble particles (soot core and organic coating), making this comparison possible. Furthermore, only the dominant peak around 80−100 nm was used as the DMS500 did not detect the larger sized mode. This is because the DMS500 is designed for high number concentrations. Therefore, although there is measurable mass in the peak around 500 nm, this equates to low number concentrations and is not resolved by the DMS500. The results from this can be seen in Figure 5, which plots the effective density (ED) versus the mobility diameter. The graph only contains data for tests where the total loadings are less than 1 mg m−3, i.e., where the diameters of the particles are independent of total mass, and are for all fuels, probes, and

power. No dependence was found on fuel type or load, although it is noted that the LPP1 points are not included as they did not have enough signal to generate pTOF data. Although the straight line fit does not produce a very high r2, 0.64, it does suggest that the ED of the particles can be estimated from number size distribution data. This further implies that if the number size distribution can be accurately measured, then the total mass of particles can be estimated without knowing what fuel is being burnt. The results are consistent with other studies,19 which show that the smallest particles produce the highest effective densities. However, the fuel independent ED values reported here are generally higher than those of Park et al.19 They reported a range of ED from 0.95 to 1.2 g cm−3 for 50 nm particles for diesel engines, while this study predicts an ED of 1.83 g cm−3 for 50 nm particles. Onasch et al.3 observed an ED of 1 g cm−3 for a 100 nm soot mode particle from an aircraft engine and concluded that this was constant for particles in the size range 40−100 nm. The results here predict an ED of 1.06 g cm−3 at 100 nm but show that the ED continues to increase at smaller sizes. By contrast, Timko et al.20 predict a range of ED for 3 fuels (one 100% Fischer−Tropsch derived fuel, a 50−50 blended fuel and one standard aviation kerosene fuel) which are generally similar to the ED predicted here within the uncertainties. However, care must be exercised in making this comparison as the Dm sizes reported are over 100 nm, which means the calculated EDs from this study are an extrapolation. This relationship between effective density and size can be used to estimate a mass-mobility exponent, Df, following the definitions of DeCarlo et al.21 and Slowick et al.22, if a constant material density is assumed (see Supporting Information). For assumed densities of 2 and 2.5 g cm‑3, mass-mobility exponents of 2.54 and 2.53 were estimated, respectively, with an uncertainty of ±0.09 in each case. Densities of less than 2 corresponded to dynamic shape factors of less than 1, which is not physically possible. These values do not correspond to those of spheres (3) or agglomerates (1.8) reported by Slowick et al., but other studies19 report a range of Df values that are not inconsistent with the values calculated here, suggesting that the particles can be described by a fractal trend. Interestingly, when the relationship between dynamic shape factor and size reported in this study is compared with those of the larger particles measured by Timko et al.,20 they conform to the same trend, implying the particles are conforming to the same geometry relationship (see SI), but with this study producing smaller, more compacted particles as seen with the effective density measurements. However, these data cannot rule out the possibility that this trend is a manifestation of systematic variations in material density rather than shape. Impacts of the Study and Limitations of Organic EI. The organics in the APU exhaust undergo rapid condensation processes during cooling. This work shows that measurements close to the exhaust exit plane are not representative of those using the downstream probe and the latter should be used when assessing environment impacts. The effect on emissions of switching from Jet A-1 to alternative fuels was highly dependent on the use of the APU. If the APU is predominantly used in high power, no change in composition was observed. However, if the APU spends significant amounts of time at low power (idling), this work shows there is a shift in behavior in terms of chemistry, with more oxygenated chemical functionality present (e.g., alcohols). However, due to the limitations of the AMS, specific molecules or functional groups cannot be

Figure 5. Effective density of the particles verse mobility diameter. Graph contains all data and fuels. 10817

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isolated. Therefore, more work using more selective analytical techniques is needed to characterize these changes in chemistry if the implications for human health and atmospheric chemistry are to be assessed. The data as a function of probe position highlights a problem with the traditional method of reporting engine emission data when the total particulate mass is not conserved. When presenting data from emission studies, it is usual to report results as an emission index (EI). However, for organic mass an experimentally determined EI is likely to be inaccurate as the process of dilution suppresses condensation of organic vapor while diluting the CO2. CO2 and soot form in the engine and are byproducts of combustion (or for soot, incomplete combustion). The total mass of CO2 and soot is conserved as the plume moves away from the exhaust plane. Organic PM mass continues to form beyond the exhaust exit plane as the plume cools. This is particularly problematic for modelers who require a representative number for a given engine. Absolute mass is also an inadequate metric as it does not convey any information about the engine conditions or atmospheric lifetime, only the relative changes for a given test. Both have been reported here and demonstrate the variability in the organic loadings depending on where a sample is taken. The issue is further complicated by volatility. Without knowing the volatility of the particles it is impossible to say what the true mass emitted is, only the mass (or EI) at that moment in time. Once the plume is in thermal equilibrium with the atmosphere, and continues to dilute, it is possible that the particles may reevaporate. This, and the effect of engine power/dilution, may have an impact on any future regulatory measurements involving organic aerosol as exhaust exit plane measurements may not be representative of the PM emitted into the atmosphere.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Brief summary of the calculations used to define the mass− mobility exponent, which are taken from refs 22 and 23. Graph of the calculated shape factor vs size from this study and one other using alternative fuels.20 This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Phone: +44 161 306 3905. Notes

Any opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors. The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was separately funded by Royal Dutch Shell and the Federal Aviation Administration (FAA). FAA funding was through the Partnership for AiR Transportation for Noise and Emissions Reduction (PARTNER), an FAA-NASA-Transport Canada-US DoD-US EPA-sponsored Center of Excellence under Grant 07-C-NE-UMR Amendment 009 (Carl Ma, Project Manager). 10818

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for the extraction of chemically resolved mass spectra from aerodyne aerosol mass spectrometer data. J. Aerosol Sci. 2004, 35 (7), 909−922. (16) Aiken, A. C.; DeCarlo, P. F.; Jimenez, J. L. Elemental analysis of organic species with electron ionization high-resolution mass spectrometry. Anal. Chem. 2007, 79, 8350−8358. (17) Aiken, A. C.; DeCarlo, P. F.; Kroll, J. H.; Worsnop, D. R.; Huffman, J. A.; Docherty, K.; Ulbrich, I. M.; Mohr, C.; Kimmel, J. R.; Sueper, D.; Zhang, Q.; Sun, Y.; Trimborn, A.; Northway, M.; Ziemann, P. J.; Canagaratna, M. R.; Onasch, T. B.; Alfarra, R.; Prevot, A. S. H.; Dommen, J.; Duplissy, J.; Metzger, A.; Baltensperger, U.; Jimenez, J. L. O/C and OM/OC ratios of primary, secondary, and ambient organic aerosols with high resolution time-of-flight aerosol mass spectrometry. Environ. Sci. Technol. 2008, 42, 4478−4485, , DOI: 10.1021/ es703009q. (18) Zhenhong, Y.; Herndon, S. C.; Ziemba, L. D.; Timko, M. T.; Liscinsky, D. S.; Anderson, B. E.; Miake-Lye, R. C. Identification of lubrication oil in the particulate matter emissions from engine exhaust of in-service commercial aircraft. Environ. Sci. Technol. 2012, DOI: 10.1021/es301692t, and private communication. (19) Park, K.; Cao, F.; Kittelson, D. B.; McMurry, P. H. Relationship between particle mass and mobility for diesel exhaust particles. Environ. Sci. Technol. 2003, 37 (3), 577−583, , DOI: 10.1021/ es025960v. (20) Timko, M. T.; Yu, Z.; Onasch, T. B.; Wong, H. W.; Miake-Lye, R. C.; Beyersdorf, A. J.; Anderson, B. E.; Thornhill, K. L.; Winstead, E. L.; Corporan, E.; DeWitt, M. J.; Klingshirn, C. D.; Wey, C.; Tacina, K.; Liscinsky, D. S.; Howard, R.; Bhargava, A. Particulate emissions of gas turbine engine combustion of a Fischer−Tropsch synthetic fuel. Energy Fuels 2010, 24, 5883−5896, DOI: 10.1021/ef100727t. (21) DeCarlo, P.; Slowik, K. G.; Worsnop, D. R.; Davidovits, P.; Jimenez, J. L. Particle morphology and Density characterization by combined mobility and aerodynamic diameter measurements. Part 1: Theory. Aerosol Sci. Technol. 2004, 38, 1185−1205. (22) Slowik, J. G.; Stainken, K.; Davidovits, P.; Williams, L. R.; Jayne, J. T.; Kolb, C. E.; Worsnop, D. R.; Rudich, Y.; DeCarlo, P. F.; Jimenez, J. L. Particle morphology and density characterization by combined mobility and aerodynamic diameter measurements. Part 2: Application to combustion-generated soot aerosols as a function of fuel equivalence ratio. Aerosol Sci. Technol. 2004, 38, 1206−1222.

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