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Quantitation, Detection and Measurement Precision of Organic
Molecular Markers in Urban Particulate Matter from Philadelphia, PA
Min Li1*, Stephen R. McDow2, David J. Tollerud3 and Monica A. Mazurek1,4
1
Department of Civil & Environmental Engineering, Rutgers, The State University of
New Jersey, Piscataway, NJ
2
Environmental Characterization and Apportionment Branch, U.S. EPA, Research
Triangle Park, NC
3
School of Public Health and Information Sciences, University of Louisville, Louisville,
KY
4
Center for Advanced Infrastructure and Transportation, Rutgers, The State University of
New Jersey, Piscataway, NJ
*
Corresponding author
Abstract
This work focuses on analysis of organic molecular markers in airborne particulate matter
(PM) by Gas Chromatography/Ion Trap Mass Spectrometry (GC/IT MS). The particulate
samples used in the method development were collected as PM10 in metropolitan
Philadelphia during 2000. The analytical method emphases a detailed compound
identification procedure by ion trap mass spectrometry, five-point mass calibration for
compound quantitation and estimates of measurement uncertainty for individual marker
compounds associated with ambient particulate samples. A systematic procedure for
describing measurement precision of the organic marker compounds is critical input to
current source apportionment models.
Introduction
Organic particulate matter accounts for 20 to 50 percent of fine particulate mass
(PM2.5) in most of North America, and approximately one third of the total fine
particulate mass in northeastern cities like Philadelphia and New York City in winter
(EPRI, 2003). Particulate organic matter is composed of a large number of individual
compounds with widely differing chemical and physical properties. Consequently,
atmospheric behavior, health impacts, and mass estimates are likely to vary considerably
with location, season, and time of day. Further chemical speciation of particulate organic
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matter by analysis of its individual components is valuable for a number of purposes,
including prediction of atmospheric behavior and potential health impacts. Because some
major sources of fine particulate matter are composed mainly of organic substances,
analysis of individual organic molecular markers by gas chromatography/mass
spectrometry (GCMS) also has great potential for identifying major emission sources of
particulate matter in urban atmospheres.
Organic markers for source apportionment have been quantified in atmospheric
particulate matter by gas chromatography/mass spectrometry (GCMS) for nearly two
decades (Mazurek et al., 1987; Rogge et al., 1993a; Schauer et al., 1996; Zheng et al.,
2000; Manchester-Neesvig et al., 2003). Results from these studies have demonstrated
clearly the value of organic markers for identifying the major sources of fine particulate
matter in urban atmospheres. Further work that would improve this approach includes
continued investigation of which markers to analyze, additional development of sampling
and analysis methods, and estimates of uncertainties to establish realistic measurement
quality expectations.
Uncertainties associated with organic markers are difficult to assess.
Measurement procedures are time consuming, and there are multiple potential sources of
uncertainty, including sampling, shipping, extraction, concentration, storage, and GCMS
analysis. This circumstance complicates the use of organic markers for source
apportionment, since measurement uncertainty is a required model input and the value
used for a marker’s uncertainty can critically influence whether sources truly can be
resolved (Paatero and Hopke 2003).
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In this paper we describe the analytical approach developed for analysis of
organic molecular markers for particulate matter collected in metropolitan Philadelphia,
PA.
1. Sample Collection and Preparation
Ambient PM10 (particle size less than 10 μm) samples were collected over a 24-hour
period at the Philadelphia Air Management Service’s North Broad Street monitoring
station, Philadelphia, PA. The sampling periods were 1/20/00 - 2/6/00, 3/28/00 – 4/20/00,
7/31/00 – 8/12/00, and 10/16 – 11/2/00. A total of 71 samples was acquired using high
volume Anderson PM10 samplers at flow rate of 38 ft3/min on a 810 inch Whatman
quartz fiber filter. Prior to sampling, filters had been baked out at 600C for three hours
to minimize the organic background contaminants. Filters were wrapped carefully with
aluminum foil which had been baked out at 200C for 10 minutes and stored in resealable
plastic bags until the sampling days. The resealable plastic bag with a new filter inside
was transported in a cooler container to the sampling site in the morning of a sampling
day. The bag with the sample filter inside was transported back to the laboratory in an
isolated cooler container with blue ice, and then frozen at -10C until analysis. One or
two trip blanks were collected for each season, which made a total of 7% blanks over the
entire samples. The trip blanks were identical quartz fiber filters going through the same
pretreatment, storage and transportation procedures as the filters for sampling, but no air
dream through the filter.
The PM10 sample filters were extracted by Soxhlet extraction in 250 ml of a 1:1
methylene chloride: acetone mixture for a period of 4 hours. The extracts were
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evaporated to 5 ml by using a Kuderna-Danish apparatus and concentrated to 1.0 ml by a
stream of pure nitrogen gas. Each individual sample extract was divided into two portions
after concentration to about 1.0 ml. One portion was derivatized by adding freshly
prepared diazomethane in at least 100-fold excess to convert organic acids to their methyl
derivatives. The conversion reaction is complete in seconds, and provides the equivalent
methyl ester. Diazomethane (CAS number: 334-88-3) was prepared immediately before
use from a precursor, N-methyl-N-nitroso-p-toluenesulfinamide, CAS No. 80-11-5
(Diazald, MNTSA, Aldrich). Preparation and handling of diazomethane requires special
precautions because it is a highly explosive gas at room temperature.
2. Analytical Methods
2.1 Operating Conditions for Gas Chromatograph/Ion Trap Mass Spectrometer (GC/IT
MS)
Analyses of all samples, including derivatized portions, were carried out on a
Varian 3800 capillary column gas chromatograph interfaced to a Saturn 2000 ion trap
mass spectrometer (GC/IT MS). A fused silica capillary column coated with DB1701was used (30 m, 0.25 μm coating thickness and 0.25 mm internal diameter, J&W
Scientific, Wilmington, Delaware). The DB1701 coating consists of 7% cyanopropyl,
7%phenyl, 86% dimethylpolysiloxane and is used widely for compounds with low-tomid polarity. Samples and standards were injected in the split mode (1:10). The GC
analytical method was programmed for 60.5 minutes and consisted of the following steps:
1) initial isothermal hold for 3 minutes at 50C; 2) a temperature ramp of 20C /min up to
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150C; 3) isothermal hold for 3 minutes; 4) temperature ramp of 4C/min to 280C; and 5)
a final isothermal hold of 17 minutes.
2.2 Standards
Perdeuterated n-tetracosane (nC24D50) was added as the internal standard to all
sample filters prior to solvent extraction. This standard also was added to the entire set of
ambient molecular marker standards to determine relative response factors for each
standard compound necessary to quantify the marker compound when detected in the
ambient PM sample extracts. An organic acid standard mixture was prepared in acetone
at 25.0-27.0 g/ml with monocarboxylic acids, ranging from C10 to C30 and dicarboxylic
acids from C3 to C9 (Sigma-Aldrich, St. Louis, MO). The acidic standard mixture was
derivatized by freshly prepared diazomethane prior to analysis by GC/IT MS. The nalkane standard mixture consisted of C25 to C32 homologues in dichloromethane at 10.0
g/ml (10 ppm) (Sigma-Aldrich). The PAH standard contained 5 compounds with
molecular weight of 252 amu and above and was prepared in dichloromethane at 10.0
g/ml (Sigma-Aldrich). Generally, compounds with amu > 252 exist in the particle
phase at 80% or greater throughout the year (Pankow et al., 1987, 1992, 1994). The
hopane standard was a single component standard of 17α(H),21β(H)-hopane in
dichloromethane at 3.0 g/ml (Chiron, Trondheim, Norway).
2.3 Five-point Mass Calibration
A five-point calibration curve was generated with molecular marker calibration
standards with various concentrations, but maintaining the same internal standard
concentration (nC24D50).
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The initial calibration of the Varian Saturn GC/IT MS was performed prior to the
ambient PM sample analysis. This was done in December 2002 at five levels for
calibration standards of n-alkanes, PAH, dicarboxylic acids, n-alkanoic acids, and four
levels for hopanes. Levels of calibration standards were selected based on the mass
concentrations from 24-hr ambient test samples. Response factors were calculated for all
analytes at each concentration level. Figure 1 shows examples of calibration curves
generated in this study, including calibration curve of 17α,21β-hopane, n-nonacosane,
benzo[b]fluoranthene, n-hexadecanoic acid and azelaic acid (nonadioic acid).
Calibration curves for most of the molecular markers are highly linear with
correlation coefficients (R2) greater than 0.97 for the n-alkanes, 0.9998 for the hopane,
0.95 for the n-alkanoic acids, and 0.97 for the dicarboxylic acids. PAH compounds have
calibration curves with slightly less linearity as R2 values ranging from 0.86 for
indeno[1,2,3-cd]pyrene to 0.95 for benzo[b]fluoranthene. The linearity of the calibration
curves for all standard compounds indicate high consistency and reproducibility of the
GC chromatographic and MS analyses.
2.4 Compound Identification and Quantification
Identification of the organic molecular source markers associated with
atmospheric particulate matter must produce quantitative results for marker compounds
present generally at low ppb trace levels in urban PM. Once extracted, the molecular
tracers are components within a complex mixture that is unresolved by the GC
chromatographic process. It is usually the case that molecular markers coelute with other
compounds during elution through the GC column, thereby combining mass spectra and
complicating automated library searches and peak purity fits for identifying target
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compounds. Consequently, it is useful to employ for mass-to-charge (m/z) fragments that
are characteristic for an individual marker compound or homologous series (e.g., nalkanes, C25 to C32). For PAH, diacids and hopanes, the most abundant ion m/z serves as
the quantification ion. For the n-alkanes and the n-alkanoic acids, however, several m/z
fragments are monitored for each homolog series. For example, m/z 57, 71 and 85 are
almost of equivalent abundance for the n-alkane series, but only m/z 85 was selected as
the quantification ion due to less interference with other coeluting compounds at this m/z.
For n-alkanoic acid methyl esters, m/z 74, 87 and 43 were screened, however quantitation
was based on m/z 74 abundance. Table 1 lists the m/z ions used to screen the total ion
current output for individual marker compounds and homologous compound series in the
solvent-soluble PM complex mixtures analyzed by GC/IT MS.
Molecular markers within a sample extract were identified by comparing the GC
retention times and mass spectra with those produced from analyses of authentic
standards. The retention time of the target compound in the complex mixture was
required to fall within a range of + 0.1 second. The mass spectrometric plot of the
marker compound was required to have the quantitation ion(s) present in addition to other
key m/z ions for that compound determined from standard runs of the GC/IT MS. Finally,
additional confirmation of the target compound was achieved by establishing and
verifying the typical ratios in the MS plot for several most abundant ions in the molecule
using authentic standard MS spectra. This sequence of steps comprises the compound
verification procedure for molecular markers in urban PM. Figure 2 is an example of the
ion trap mass spectra for several individual molecular markers based on the authentic
standards. Positive identification of an unknown compound in the PM extracts was
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possible only when the mass spectrum of the compound had ion-ion ratios similar to the
authentic standard spectrum.
Positive identification of all molecular markers was employed with complete sets
of authentic standards with an exception of some hopanes. The hopanes for which
authentic standards are not available were identified by referring to the retention time of
17α,21β-hopane standard and to the unique distribution pattern from published mass
spectra, and to ancillary chromatographic information such as relative retention time to
known compounds within the PM extract mixture (Philp, 1985, Fraser et al., 1999, Rogge
et al., 1993b). These additional hopane homologs were quantified by applying the
response factor obtained for the 17α,21β-hopane.
3. Precision and Bias of Analytical Measurements
3.1 Precision of Analytical Method
The analytical precision of molecular marker method was determined by
duplicating the analysis for every tenth sample. Precision is expressed as the average
relative range (relative percent difference) of duplicate analyses of the molecular markers
in ambient particulate samples and listed in Table 2.
The analytical precision of the alkanes and hopanes ranges from 2.5% for noctacosane to 8.1% for n-triacontane. Six out of nine hopanes and three out of eight nalkanes have measurement precision less than 5.0%.
3.2 Analysis Precision of RRF
Response factors for GC/IT MS have a strong influence on the analytical results of the
molecular markers identified in ambient PM. It is important to monitor the variation of
the response factors throughout the analytical process. In the case of many ambient
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samples, for example this study (71 samples), it was not feasible to establish an entire set
of five-point mass calibration curves for the analysis of each single marker compound (53
marker compounds) within every sample extract. Instead, a second five-point calibration
set for compounds of interest was produced at the completion of all sample analyses (3
months later) and then estimates of the deviation were determined between the two sets
of response factors. The standard deviation (%SD) between the two sets of response
factor was less than 6.36% for most of the markers analyzed in this work (Table 3).
Because of the low standard deviation between the two response factor determinations,
there was no need to retroactively correct compound quantitation. Therefore, the
quantitation of the marker compounds in the 71 ambient samples was based on the initial
set of response factors. The consistency in molecular marker standard responses is
shown in Table 3 using two sets of response factors obtained from the five-point
calibration experiments determined 3 months apart. The RRF are highly reproducible
throughout the entire sample analysis period for most molecular markers tested. Low
standard deviations were observed for all n-alkanes with carbon number between 25 and
31 (SD<4.24%), 17α,21β,hopane (SD=6.36%), and all three PAHs, BbF, BkF and BeP
(SD <5.66%). In comparison, the relative response factors for n-dodecanoic acid, nhexadecanoic acid and n-tetracosanoic acid showed much higher standard deviations (SD
21.33% to 31.82%) than the non-polar marker compounds (n-alkanes, PAHs and hopane).
The low reproducibilities of the RRFs of the n-alkanoic acids could be due to variation in
the derivatization process to methyl esters, and procedural or chromatographic losses
during sample preparation and analysis. Overall, the five-point calibration response
factors give fairly consistent results for the marker compounds.
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3.3 Analysis Bias
Measurement accuracy for the molecular marker GC/IT MS method was
examined by analyzing NIST Standard Reference Material 1491, a certified PAH
standard. Table 4 shows the results of the accuracy tests which are reported as analytical
bias of the PAH standard with five-point calibration relative to their certified values.
Four PAH of interest in NIST 1491 were quantified by the five-point calibrated
response factors that were used for the analysis of the Philadelphia PM10 samples,
including benzo[b]fluoranthene, benzo[k]fluoranthene, bezo[e]pyrene and indeno[1,2,3cd]pyrene. Benzo[k]fluoranthene has the lowest analysis bias of 7.1%, while
benzo[b]fluoranthene has the highest bias of 33.5%.
The 33.5% bias for benzo[b]fluoranthene is the highest among all the molecular
marker compounds. The high measurement bias for benzo[b]fluoranthene is related to
difficulties associated with identification and the relatively low reproducibility of the
response factors of PAH from the 5-point calibration curves. PAH exhibit the highest
relative standard deviation for response factors from the calibration curves and the lowest
reproducibility of the response factors among all the molecular markers. Overall, the
analytical bias for molecular marker compounds evaluated in this GC/IT MS study
should be less than 10.0 % with the exception of benzo[b]fluoranthene.
4. Summary and Recommendations
An updated, systematic analytical protocol has been described for detecting,
quantifying and estimating measurement precision of organic marker compounds in
ambient particulate matter using GC/IT MS instrumentation. Nearly all the marker
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compounds (53 in total) were identified positively by comparing retention times, mass
spectra and relative intensity of major ion m/z fragments produced by ion trap mass
detection with corresponding authentic standards. It is essential to use authentic
standards run on a GCMS system to ensure accurate identification and quantitation of
that marker compound.
The use of five-point mass calibration allows quantifying organic marker
compounds in ambient particulate matter over a wide range (0.1 ng/m3 to 100 ng/m3) of
concentrations. The multilevel calibration of the mass detector demonstrates highly
reproducible relative response factors (RRFs) over a 3-month analysis period as an
overall indicator of system stability. System stability and documentation of statistical
control of the mass measurement approach are critical to precise analytical results for
ambient molecular markers at the ppb level. In this study, the standard deviation of the
five-point calibration RRFs determined 3 months apart is less than 6.36% for the nonpolar markers measured (n-alkanes, PAHs and hopanes) and 23.33% to 31.82% for polar
markers (n-alkanoic acids and dicarboxylic acids). Given good documented system
stability, it is possible that validation of the RRF for non-polar markers (5 point
calibrations) can be monitored at longer intervals (3 months or longer) for compounds
other than polar markers. In general, multi-level standard calibration of the mass
detector is important for validating the ppb ambient abundances of individual marker
compounds in PM monitoring studies.
Acknowledgements. This research was supported by the Developing Research
Synergies Grant of Drexel and MCP Hahnemann University in 1999 and Speciation of
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Organics for Apportionment of PM-2.5 (SOAP) through Northeast States for Coordinated
Air Use Management (NESCAUM). Additional support from NSF Grant ATM-0120906
is gratefully acknowledged.
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Figure 1. Calibration Curves for Molecular Marker Standards
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Table 1. Mass-to-charge (m/z) Ions Used for Compound Identification and
Quantitation
Compound or Class
n-Alkanes
BbF, BkF, BeP
InF, InP
Hopanes
n-Alkanoic acids
Dicarboxylic acids
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Quantitation m/z
85
252
276
191
74
Compound MW
Screened m/z
85, 71 and 57
252 or 126
276
191, 95
74, 43 and 87
Compound MW
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(a) Total Ion Current of an Ambient Sample
n-Nonacosane
17α,21β,Hopane
(b) Mass Spectrum of n-Nonacosane
(c) Mass Spectrum of 17α,21β,Hopane
Figure 2. Total ion current peaks (a) and ion trap mass spectra
corresponding to n-nonacosane (b) and 17α,21β-hopane (c)
molecular markers in Philadelphia ambient PM10.
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Table 2. Analysis Precision of Molecular Marker Analyses from 7 Philadelphia PM10 Ambient Samples
Concentration of Duplicate Measurements (ng/m3)
Hopanes
Carbon Number
18α(H)22,29,30-Trisnorneohopane
17α(H)-22,29,30-Trisnorhopane
17α(H),21β(H)-29-Norhopane
18α(H)-29-Norneohopane
17α(H),21β(H)-Hopane
22S,17α(H),21β(H)-30-Homohopane
22R,17α(H),21β(H)-30-Homohopane
22S,17α(H),21β(H)-30-Bishomohopane
22R,17α(H),21β(H)-30-Bishomohopane
N9
N31
N55
0.81
0.59
2.10
0.56
2.14
1.08
0.72
0.47
0.40
N89
N105
0.70
0.73
2.84
0.61
3.00
1.10
0.93
0.63
0.41
N117
C27
C27
C29
C29
C30
C31
C31
C32
C32
0.56
0.53
1.87
0.22
1.65
0.65
0.49
0.34
0.31
0.56
0.56
1.85
0.22
1.71
0.77
0.48
0.39
0.30
0.79
0.88
2.49
0.46
2.23
0.85
0.63
0.58
0.49
0.82
0.77
2.47
0.45
2.71
0.98
0.63
0.60
0.59
0.78
0.54
1.97
0.50
2.17
0.98
0.76
0.55
0.41
0.27
0.38
1.26
0.27
1.47
0.60
0.41
0.36
0.37
0.29
0.41
1.28
0.28
1.43
0.60
0.44
0.39
0.29
0.65
0.72
2.58
0.71
2.93
1.20
0.85
0.56
0.43
0.41
0.50
1.54
0.26
1.63
0.85
0.67
0.55
0.48
0.45
0.52
1.67
0.38
1.67
1.00
0.68
0.74
0.47
C25
C26
C27
C28
C29
C30
C31
C32
4.75
3.46
4.53
2.83
7.72
2.54
7.99
6.22
5.66
3.74
5.10
2.71
8.53
2.39
9.35
9.12
6.75
4.58
4.36
4.31
4.68
3.06
7.86
9.39
5.50 5.17 5.03
4.27 4.03 3.39
3.98 5.59 6.16
4.30 2.98 3.14
4.68 9.58 11.61
3.62 2.29 3.02
6.93 13.00 14.27
7.23 6.08 6.10
2.06
2.53
2.77
2.52
4.10
2.97
6.03
6.17
2.28
2.96
2.66
2.71
4.19
3.24
6.37
7.26
3.47 4.10
4.26 4.89
3.36 4.29
5.23 5.27
3.35 4.54
7.37 7.33
1.68 3.04
7.88 8.08
5.49 7.22 14.83 14.96
2.43 2.80
5.95 4.55
8.41 15.28 30.26 28.37
7.92 11.86 16.90 16.23
N131
1.27
1.25
5.26
0.96
5.26
2.25
1.66
1.33
1.02
Precisiona
1.13
1.09
4.33
0.86
4.61
1.95
1.79
1.38
1.20
0.031
0.041
0.033
0.062
0.033
0.058
0.026
0.061
0.050
4.26 4.89
5.23 5.27
7.37 7.33
7.88 8.08
14.83 14.96
5.95 4.55
30.26 28.37
16.90 16.23
0.062
0.055
0.051
0.025
0.048
0.081
0.046
0.074
n-Alkanes
n-Pentacosane
n-Hexacosane
n-Heptacosane
n-Octacosane
n-Nonacosane
n-Triacontane
n-Hentriacontane
n-Dotriacontane
a
: Analytical Precision of Samples p 
 (C
i,ha
 C i,la) /C i,avg
i
n
, Ci,ha and Ci,la are the highest and lowest of the two duplicate analyses of
concentration measurements expressed as (ng/m3) for the same sample i, respectively. Ci,avg is the average of the two duplicate
measurements of sample i, and n is the total number of duplicate measurements taken.
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Table 3. Reproducibility of Five-point Relative Response Factor Over 3-Month Analysis Period
Retention
Molecular Markers
Time
RRF
RRF
(minute) Nov, 2002 Feb, 2003
n-Pentacosane (C25)
33.2
1.11
1.13
n-Hexacosane (C26)
35.1
1.03
0.99
n-Heptacosane (C27)
37.0
0.93
0.94
n-Octacosane (C28)
38.8
0.82
0.84
n-Nonacosane (C29)
40.6
0.81
0.81
n-Triacontane (C30)
42.3
0.8
0.86
n-Hentriacontane (C31)
44.0
0.52
0.57
n-Dotriacontane (C32)
45.9
0.22
0.28
%SD
1.41
2.83
0.71
1.41
0.00
4.24
3.54
4.24
benzo[b]fluoranthene
benzo[k]fluoranthene
benzo[e]pyrene
43.6
43.7
45.1
0.62
0.70
0.71
0.70
0.65
0.73
5.66
3.54
1.41
17α,21β,hopane
43.6
1.29
1.20
6.36
Dodecanoic acid (C12)
Palmitic acid (C16)
Tetracosanoic acid (C24)
11.9
22.2
37.6
1.10
1.21
0.61
0.77
0.76
0.32
23.33
31.82
20.51
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Table 4. Analysis Bias Associated with Five-point Calibration
BbF
BkF
BeP
InP
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Certified
Analyzed
%bias
RRF
Conc.(μg/ml)Conc.( μg/ml)
5-point
5.25
7.01
33.5
0.620
5.57
5.96
7.1
0.698
5.62
6.15
9.5
0.705
6.29
4.94
-21.5
0.514
BbF: benzo[b]fluoranthene; BkF: benzo[k]fluoranthene;
BeP: benzo[e]pyrene; InP: indeno[1,2,3-cd]pyrene
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