Anal. Chem. 2009, 81, 1512–1521
Molecular Characterization of Biomass Burning Aerosols Using High-Resolution Mass Spectrometry Jeffrey S. Smith,†,‡ Alexander Laskin,§ and Julia Laskin*,† Chemical and Materials Sciences Division, and William R. Wiley Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, P.O. Box 999, MSIN K8-88, Richland, Washington 99352 Chemical characterization of atmospheric aerosols presents a serious analytical challenge because of the complexity of particulate matter analyte composed of a large number of compounds with a wide range of molecular structures, physico-chemical properties, and reactivity. In this study the chemical composition of the organic constituents of biomass burning aerosol (BBA) samples is characterized by high-resolution electrospray ionization mass spectrometry (ESI/MS). Accurate mass measurement combined with Kendrick analysis allows assignment of the elemental composition for hundreds of compounds in the range of m/z values of 50-1000. ESI/MS spectra of different BBA samples contain a variety of distinct, sample specific, characteristic peaks that can be used as unique markers for different types of biofuels. Our results indicate that a significant number of high-MW organic compounds in BBA samples are highly oxidized polar species that can be efficiently detected using ESI/MS but are difficult to observe using conventional gas-chromatography/mass spectrometry analysis of aerosol samples. More than 70% of the identified species have not been reported in the literature. Detected organic compounds show a clear increase in the degree of saturation as the molecular weight of the analyte molecules increases. The increase is particularly pronounced for the samples containing a large number of the CH2-based homologous series. Biomass burning, both wild and prescribed fires, results in emission of large amounts of volatile compounds and particles into the atmosphere.1-3 The type of pollutants and particles vary with fuel type, type of the fire (flaming vs smoldering), the moisture content, and the temperature of the fire. Fine particulate matter emitted into the atmosphere during biomass burning has a significant impact on climate via interactions with incoming solar
radiation and through modifications of cloud properties.1-8 Understanding the environmental impact of atmospheric aerosols intrinsically relies on the fundamental knowledge of the relationship between their composition and their chemical and physical properties. The organic fraction of atmospheric particulate matter that accounts for 45-75% of the total aerosol carbon mass1,9-11 consists of a complex mixture of compounds with a wide range of molecular structures, physical properties, and chemical reactivity. Unraveling the chemical composition of complex organic aerosol (OA) mixtures is a serious analytical challenge; typically only 10-20% of the total OA mass can be successfully identified and quantified using traditional techniques.12-16 It follows that development of analytical approaches for improved characterization of organic aerosols is crucial for understanding their impact on atmospheric chemistry and the environment. The chemical composition of solvent extracts from organic aerosols has been traditionally analyzed using gas-chromatography/mass spectrometry (GC/MS).1,2 The major compound groups identified in smoke particles using this technique include alkanes, alkenes, aldehydes, ketones, fatty acids, fatty alcohols, methoxyphenols, monosaccharide derivatives, phytosterols, diterpenoids, triterpenoids, and wax esters.1 However, typically only a small fraction of aerosol mass is accounted for by these species.12 It has been demonstrated that a significant fraction (30-70%) of unidentified organic matter in field-collected aerosols corresponds (4) (5) (6) (7) (8) (9) (10)
(11) * To whom correspondence should be addressed. E-mail:
[email protected]. Phone: 1-509-371-6136. Fax: 1-509-371-6139. † Chemical and Materials Sciences Division. ‡ Undergraduate student from the University of Washington, Seattle, WA. § William R. Wiley Environmental Molecular Sciences Laboratory. (1) Simoneit, B. R. T. Appl. Geochem. 2002, 17, 129–16. (2) Reid, J. S.; Eck, T. F.; Christopher, S. A.; Koppmann, R.; Dubovik, O.; Eleuterio, D. P.; Holben, B. N.; Reid, E. A.; Zhang, J. Atmos. Chem. Phys. 2005, 5, 827–849. (3) Reid, J. S.; Koppmann, R.; Eck, T. F.; Eleuterio, D. P. Atmos. Chem. Phys. 2005, 5, 799–825.
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(12) (13) (14) (15) (16)
Poschl, U. Angew. Chem. Int. Ed. 2005, 44, 7520–7540. Seinfeld, J. H.; Pankow, J. F. Annu. Rev. Phys. Chem. 2003, 54, 121–140. Andreae, M. O.; Rosenfeld, D. Earth Sci. Rev. 2008, 89, 13–41. Rosenfeld, D.; Lohmann, U.; Raga, G. B.; O’Dowd, C. D.; Kulmala, M.; Fuzzi, S.; Reissell, A.; Andreae, M. O. Science 2008, 321, 1309–1313. Unger, N.; Shindell, D. T.; Koch, D. M.; Streets, D. G. J. Geophys. Res. 2008, 113, D02306; DOI:, 10.1029/2007JD008683. Simoneit, B. R. T.; Rogge, W. F.; Mazurek, M. A.; Standley, L. J.; Hildemann, L. M.; Cass, G. R. Environ. Sci. Technol. 1993, 27, 2533–2541. Graham, B.; Mayol-Bracero, O. L.; Guyon, P.; Roberts, G. C.; Decesari, S.; Facchini, M. C.; Artaxo, P.; Maenhaut, W.; Koll, P.; Andreae, M. O. J. Geophys. Res. 2002, 107, 8047; DOI: 10.1029/2001JD000336. . Mayol-Bracero, O. L.; Guyon, P.; Graham, B.; Roberts, G.; Andreae, M. O.; Decesari, S.; Facchini, M. C.; Fuzzi, S.; Artaxo, P. J. Geophys. Res. 2002, 107, 8091; DOI: 10.1029/2001JD000522. . Rogge, W. F.; Hildemann, L. M.; Mazurek, M. A.; Cass, G. R.; Simoneit, B. R. T. Environ. Sci. Technol. 1998, 32, 13–22. Falkovich, A. H.; Graber, E. R.; Schkolnik, G.; Rudich, Y.; Maenhaut, W.; Artaxo, P. Atmos. Chem. Phys. 2005, 5, 781–797. Hoffer, A.; Gelencser, A.; Blazso, M.; Guyon, P.; Artaxo, P.; Andreae, M. O. Atmos. Chem. Phys. 2006, 6, 3505–3515. Rudich, Y.; Donahue, N. M.; Mentel, T. F. Annu. Rev. Phys. Chem. 2007, 58, 321–352. Rudich, Y. Chem. Rev. 2003, 103, 5097–5124. 10.1021/ac8020664 CCC: $40.75 2009 American Chemical Society Published on Web 12/30/2008
to high molecular weight (high-MW) humic-like substances (HULIS).1,2,10,17-19 This class of molecules cannot be identified using GC/MS or other traditional analytical approaches.20 Highresolution mass spectrometry coupled with soft ionization techniques such as electrospray (ESI)21 or matrix assisted laser desorption ionization (MALDI)22 is the technique of choice for structural characterization of molecules of any size and complexity and the analysis of complex mixtures.23-26 However, the power of this technique for characterization of OA was demonstrated only recently.27-35 Most of the studies reported thus far focused on characterization of laboratory generated aerosols27,28,30,28,30-34 and humic substances in dissolved organic matter (DOM).36-39 High-resolution mass spectra of laboratory generated aerosol samples usually contain a large number of spectral features separated by CH2 units and oxygenated species clearly clustered into the monomer, dimer, and trimer regions. Field-collected samples contain a substantially more complex mixture of species with less predictable properties compared to laboratory generated secondary organic aerosol (SOA). Recently, Reemtsma et al.29 and Wozniak et al.35 conducted high-resolution analysis of field-collected aerosol samples using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) combined with negative mode ESI. Reemstsma et al.29 reported sulfated and nitrated fulvic acids in water-soluble organic fractions of atmospheric OA samples resulting in the unambiguous assignment of more than 1000 species in the m/z range of 220-420. (17) Hoffer, A.; Kiss, G.; Blazso, M.; Gelencser, A. Geophys. Res. Lett. 2004, 31, L06115; DOI: 10.1029/2003GL018962. . (18) Graber, E. R.; Rudich, Y. Atmos. Chem. Phys. 2006, 6, 729–753. (19) Andreae, M. O.; Gelencser, A. Atmos. Chem. Phys. 2006, 6, 3131–3148. (20) Kalberer, M. Anal. Bioanal. Chem. 2006, 385, 22–25. (21) Fenn, J. B.; Mann, M.; Meng, C. K.; Wong, S. F.; Whitehouse, C. M. Science 1989, 246, 64–67. (22) Hillenkamp, F.; Karas, M.; Beavis, R. C.; Chait, B. T. Anal. Chem. 1991, 63, 1193A–1202A. (23) Marshall, A. G.; Rodgers, R. P. Acc. Chem. Res. 2004, 37, 53–59. (24) Bogdanov, B.; Smith, R. D. Mass Spectrom. Rev. 2005, 24, 168–200. (25) Feng, X.; Siegel, M. M. Anal. Bioanal. Chem. 2007, 389, 1341–1363. (26) Panda, S. K.; Andersson, J. T.; Schrader, W. Anal. Bioanal. Chem. 2007, 389, 1329–1339. (27) Tolocka, M. P.; Jang, M.; Ginter, J. M.; Cox, F. J.; Kamens, R. M.; Johnston, M. V. Environ. Sci. Technol. 2004, 38, 1428–1434. (28) Kalberer, M.; Paulsen, D.; Sax, M.; Steinbacher, M.; Dommen, J.; Prevot, A. S. H.; Fisseha, R.; Weingartner, E.; Frankevich, V.; Zenobi, R.; Baltensperger, U. Science 2004, 303, 1659–1662. (29) Reemtsma, T.; These, A.; Venkatachari, P.; Xia, X. Y.; Hopke, P. K.; Springer, A.; Linscheid, M. Anal. Chem. 2006, 78, 8299–8304. (30) Surratt, J. D.; Murphy, S. M.; Kroll, J. H.; Ng, N. L.; Hildebrandt, L.; Sorooshian, A.; Szmigielski, R.; Vermeylen, R.; Maenhaut, W.; Claeys, M.; Flagan, R. C.; Seinfeld, J. H. J. Phys. Chem. A 2006, 110, 9665–9690. (31) Reinhardt, A.; Emmenegger, C.; Gerrits, B.; Panse, C.; Dommen, J.; Baltensperger, U.; Zenobi, R.; Kalberer, M. Anal.Chem. 2007, 79, 4074– 4082. (32) Walser, M. L.; Desyaterik, Y.; Laskin, J.; Laskin, A.; Nizkorodov, S. A. Phys. Chem. Chem. Phys. 2008, 10, 1009–1022. (33) Altieri, K. E.; Seitzinger, S. P.; Carlton, A. G.; Turpin, B. J.; Klein, G. C.; Marshall, A. G. Atmos. Environ. 2008, 42, 1476–1490. (34) Bateman, A. P.; Walser, M. L.; Desyaterik, Y.; Laskin, J.; Laskin, A.; Nizkorodov, S. A. Environ. Sci. Technol. 2008, 42, 7341–7346. (35) Wozniak, A. S.; Bauer, J. E.; Sleighter, R. L.; Dickhut, R. M.; Hatcher, P. G. Atmos. Chem. Phys. 2008, 8, 5099–5111. (36) Fievre, A.; Solouki, T.; Marshall, A. G.; Cooper, W. T. Energy Fuels 1997, 11, 554–560. (37) Kujawinski, E. B.; Hatcher, P. G.; Freitas, M. A. Anal. Chem. 2002, 74, 413–419. (38) Stenson, A. C.; Landing, W. M.; Marshall, A. G.; Cooper, W. T. Anal. Chem. 2002, 74, 4397–4409. (39) Reemtsma, T.; These, A.; Springer, A.; Linscheid, M. Environ. Sci. Technol. 2006, 40, 5839–5845.
Wozniak et al.35 presented a detailed analysis of water soluble organic carbon (WSOC) compounds extracted from field collected aerosol samples. Using high-resolution mass analysis they assigned elemental formulas to the vast majority of 3000 observed peaks in the m/z range of 223-600. Here we present the first high-resolution mass spectrometric characterization of the organic compounds in biomass burning aerosol (BBA) samples using ESI in the positive mode. Our previous study demonstrated that positive ESI spectra contain significantly more peaks than spectra obtained in the negative mode.32 Similar results observed in this study suggest that a large fraction of organic compounds in BBA cannot be readily ionized in the negative mode. Accurate mass measurement allowed us to assign elemental composition for hundreds of compounds in the range of m/z values of 50-1000. More than 70% of the identified species have not been previously reported. These results demonstrate that high-resolution mass spectrometry is a powerful tool for analysis of organic compounds in complex BBA samples. EXPERIMENTAL SECTION BBA samples were collected during the FLAME experiment conducted at the U.S. Forest Service Fire Science Laboratory (FSL, Missoula, MT) where a series of laboratory measurements and aerosol sampling of biomass burning emission were performed in June 2006.40 Particles produced from biomass burning were collected onto Teflon and aluminum substrates using a 10 stage Micro-Orifice Uniform Deposit Impactor (MOUDI) model 110R (MSP, Inc). This paper presents results of high-resolution mass spectrometric analysis of BBA samples for five different biofuels: (1) dried ponderosa pine needles and sticks (PPNS), (2) ponderosa pine duff (PPD), (3) Alaskan duff (AD), (4) dried southern pine needles (SPN), and (5) southern California ceanothus (SCC). Samples of size-fractionated particles of 0.18-0.32 µm aerodynamic diameter collected on the 8th impactor stage were used in this study. Solvent extracts were prepared by ultrasonic washing of the Teflon and aluminum substrates in 2 mL of methanol. The extracts were filtered using Whatman 0.45 µm Teflon (PTFE) membrane disposable filters. Solvent extracts were analyzed using a commercial high-resolution LTQ-Orbitrap mass spectrometer (Thermo Electron Bremen, Germany) with a modified electrospray ionization (ESI) source. Samples were injected through a pulled fused silica capillary (50 µm i.d.) at a flow rate of 0.3-1.0 µL/min using a spray voltage of 3.5 kV. Between each sample run, the capillary was flushed multiple times with methanol to remove residual compounds. The system was operated in both positive and negative ion modes with a resolving power of 60,000 at m/z 400. The instrument was calibrated using a standard mixture of caffeine, MRFA, and Ultramark 1621. Background spectra were obtained by analyzing solvent extracts of blank Teflon and aluminum substrates prepared using the same procedure. Several experiments were performed to access the reproducibility of ESI/MS spectra and their dependence on the experimental conditions. Similar spectra with reduced spectral quality were obtained following dilution of the original solvent extracts by a factor of 10. In addition, most mass spectral features were (40) Fire Lab at Missoula Experiment (FLAME); http://chem.atmos.colostate.edu/ FLAME/.
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retained upon activation of in-source collision-induced dissociation (CID). These observations suggest that the results presented in this study are not affected to any significant extent by the formation of solvent-analyte and analyte-analye clusters in the ESI source. Similar spectra were obtained following solvent extraction of different portions of the same filter or extraction from different filters. For example, ESI/MS analysis of solvent extracts from both Teflon and aluminum substrates of the BBA obtained from burning of the PPNS sample resulted in qualitatively similar mass spectra. In addition, similar spectra were obtained following extraction of the AD samples collected during two different FLAME experiments in 2005 and 2006. However, very different spectra were obtained for all samples extracted into toluene and electro-sprayed from 30:70 (v:v) toluene/acetonitrile solutions. More detailed analysis of the effect of solvent on the ESI/MS spectra of BBA samples is out of the scope of this paper and will be presented in a separate publication. Mass spectral features with the signal-to-noise ratio of 3 and higher were extracted from raw spectra using the Decon2LS program developed at PNNL (http://ncrr.pnl.gov/software/). Background subtraction was performed using an Excel macro with a tolerance of 0.001 amu. The remaining peaks were assigned probable empirical formulas using freeware programs Formula Calculator v. 1.1 (http://magnet.fsu.edu/∼midas/download.html) and Molecular Weight Calculator (http://ncrr.pnl.gov/software/), and through the use of Kendrick diagrams.41-43 Molecular formulae searches included the following elements: C (up to 100 atoms), H (up to 100 atoms), N (up to 4 atoms), O (up to 15 atoms), S (up to 1 atom), Na (up to 1 atom), and K(up to 1 atom). Kendrick transformation aids in the identification and categorization of homologous compounds by normalizing the experimental mass-to-charge value to the nominal mass of a chemical group used as a basis for this analysis (e.g. CH2, O, CH2O, etc.). Specifically, for the CH2-based diagram the Kendrick mass (KMCH2) is calculated by re-normalizing the IUPAC mass scale to the exact mass of the 12CH2 group (i.e., 14.0156 amu) using eq 1. Kendrick Mass ) Observed Mass × (Nominal mass of CH2) ⁄ (Exact mass of CH2) (1) The Kendrick mass defect (KMD) is calculated as the difference between the nominal value of KM (rounded to the nearest integer) and KM using eq 2: Kendrick Mass Defect ) Nominal Mass - Kendrick Mass (2) In this work, Kendrick transformations based on methylene (CH2) units were used to assign homologous compounds. The advantage of Kendrick analysis is that homologous compounds differing only by the number of CH2 units have identical Kendrick defects. When the Kendrick defect is plotted versus (41) Kendrick, E. Anal. Chem. 1963, 35, 2146–2154. (42) Hughey, C. A.; Hendrickson, C. L.; Rodgers, R. P.; Marshall, A. G.; Qian, K. Anal. Chem. 2001, 73, 4676–4681. (43) Meija, J. Anal. Bioanal. Chem. 2006, 385, 486–499.
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Table 1. Types of Biofuels and Abbreviations Used in This Work AD PPNS PPD SPN SCC
Alaskan Duff Ponderosa Pine Needles and Sticks Ponderosa Pine Duff Dried southern pine needles Southern California ceanothus
the mass-to-charge ratio of a compound, homologous series or series of compounds differing only by the number of CH2 units fall on horizontal lines and are clearly distinguishable.42 Identification of the elemental composition of one compound in the homologous series enables assignment of all peaks in the series. In this study all peaks in different CH2 series except for the leading lowest-mass member of the series were identified using Kendrick analysis. Unambiguous identification of the leading peaks and peaks that did not belong to any CH2 series could be performed for all species with MW below 400 amu if sulfur was excluded from the search. Incorporation of one or two sulfur atoms into the search introduced ambiguity in identification of several species. However, based on the ICP/MS analysis we concluded that sulfur-containing compounds constitute only a minor fraction of BBA samples examined in this study. RESULTS AND DISCUSSION A previous study, Hopkins et al.44 classified aerosol samples collected during the FLAME experiment depending on the organic and black carbon content and the presence of inorganic inclusions into three broad categories. In the present study five samples from the category with the highest organic carbon (OC) content were selected for detailed analysis using high-resolution ESI/MS. Sample types and abbreviations used in this work are summarized in Table 1. ESI/MS Spectra. Figure 1 shows representative mass spectra obtained for all five samples in the positive mode; peak assignments are listed in Table 2. Table 3 summarizes the most abundant peaks in these spectra. Tentative assignment of several peaks is proposed based on comparison with BBA constituents reported in the literature.1,9,10,12,45-54 It should be noted that all spectra obtained in the negative mode contained 1.5-4 times fewer peaks (44) Hopkins, R. J.; Lewis, K.; Desyaterik, Y.; Wang, Z.; Tivanski, A. V.; Arnott, W. P.; Laskin, A.; Gilles, M. K. Geophys. Res. Lett. 2007, 34, L18806; DOI: 10.1029/2007GL0305022007. . (45) Edye, L. A.; Richards, G. N. Environ. Sci. Technol. 1991, 25, 1133–1137. (46) Elias, V. O.; Simoneit, B. R. T.; Pereira, A. S.; Cabral, J. A.; Cardoso, J. N. Environ. Sci. Technol. 1999, 33, 2369–2376. (47) Nolte, C. G.; Schauer, J. J.; Cass, G. R.; Simoneit, B. R. T. Environ. Sci. Technol. 2001, 35, 1912–1919. (48) Oros, D. R.; Simoneit, B. R. T. Appl. Geochem. 2001, 16, 1513–1544. (49) Oros, D. R.; Simoneit, B. R. T. Appl. Geochem. 2001, 16, 1545–1565. (50) Hays, M. D.; Geron, C. D.; Linna, K. J.; Smith, N. D.; Schauer, J. J. Environ. Sci. Technol. 2002, 36, 2281–2295. (51) Sheesley, R. J.; Schauer, J. J.; Chowdhury, Z.; Cass, G. R.; Simoneit, B. R. T. J. Geophys. Res. 2003, 108, 4285; DOI: 10.1029/2002JD002981. . (52) Lee, S.; Baumann, K.; Schauer, J. J.; Sheesley, R. J.; Naeher, L. P.; Meinardi, S.; Blake, D. R.; Edgerton, E. S.; Russell, A. G.; Clements, M. Environ. Sci. Technol. 2005, 39, 9049–9056. (53) Mazzoleni, L. R.; Zielinska, B.; Moosmuller, H. Environ. Sci. Technol. 2007, 41, 2115–2122. (54) Iinuma, Y.; Bruggemann, E.; Gnauk, T.; Muller, K.; Andreae, M. O.; Helas, G.; Parmar, R.; Herrmann, H. J. Geophys. Res. 2007, 112, D08209; DOI: 10.1029/2006JD007120. .
Figure 1. ESI mass spectra of methanol extracts of five different BBA samples collected on the 8th stage of the MOUDI impactor. Abundant peaks labeled in the spectra are listed in Table 2. Table 2. Peak Assignments for Spectra Shown in Figure 1 1 2 3 4 5
C7H6O2Na+ (benzoic acid) C6H10O5Na+ (levoglucosan) C5H12O3H+ C12H10O2SNa+ C21H24O4Na+
6 7 8 9 10
C21H26O5Na+ C31H46O7Na+ C38H76N2O4Na+ C9H14O2Na+ C10H16O2Na+
11 12 13 14 15
than in the positive mode. This suggests that a large number of organic compounds present in these samples do not readily ionize in the negative mode. Spectra obtained in the negative mode contained both some of the species observed in the positive mode along with a number of new features. Because of the additional information obtained for the BBA samples in the positive ionization mode our discussion focuses on the results of the positive ESI analysis. However, we note that detailed analysis of the negative mode spectra could provide complementary structural information. Clearly, different samples yield distinctly different ESI/MS spectra. More than 80% of the peaks in the ESI/MS spectra of aerosol extract correspond to sodiated molecules, [M+Na]+ ions, and about 20% the peaks correspond to singly protonated species, [M+H]+. Detailed assignment of peaks in mass spectra demonstrated that most oxygen-containing organic compounds (55) NIST webbook; http://webbook.nist.gov/chemistry.
C19H12N4O6H+ C21H22O10SH+ C7H12N2H+ C8H12O6Na+ C16H30O3Na+
16 17 18 19 20
C20H30O2Na+ (abietic acid) C24H44O4Na+ C12H11O3H+ C12H14O4Na+ C13H18O4Na+
21 22 23 24 25
C22H34O4Na+ C9H6O4Na+ C15H20O2Na+ C28H32ONa+ C22H32O6NH+
are observed as [M+Na]+ ions, while nitrogen-containing species are detected as protonated species. The observed trends are consistent with relative proton affinities (PAs) of nitrogen- and oxygen-containing organic molecules.55 For example, the PA of ethylamine (218 kcal/mol) is larger than that of ethanol (185.6 kcal/mol), propanoic acid (190.5 kcal/ mol), acetone (194 kcal/mol), or propanal (187.9 kcal/mol) suggesting that nitrogen-containing molecules have a greater propensity to form [M+H]+ ions in the ESI source. Levoglucosan, a common biomass burn marker,1-3,56 is observed as one of the most abundant peaks (C6H10O5Na+) in all spectra. Benzoic acid is the most abundant feature in the low-mass region of the SCC spectrum and is observed in much (56) Simoneit, B. R. T.; Schauer, J. J.; Nolte, C. G.; Oros, D. R.; Elias, V. O.; Fraser, M. P.; Rogge, W. F.; Cass, G. R. Atmos. Environ. 1999, 33, 173– 182.
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Table 3. Most Abundant Peaks Observed in ESI Spectra of Methanol Extracts of BBA Samples normalized abundance AD
m/z 97.076 107.070 111.092 121.086 125.107 137.108 139.036 139.123 145.026 153.052 153.138 159.042 169.076 177.088 183.091 185.042 191.104 201.015 202.086 203.052 205.085 213.109 217.067 227.051 241.029 245.078 255.135 261.109 279.158 293.209 297.108 315.193 317.114 321.182 323.197 325.177 325.212 335.125 335.219 337.104 337.176 337.233 339.191 347.094 351.141 357.201 359.239 363.155 363.252 365.104 365.135 367.115 367.149 371.218 375.214 379.281 381.130 381.166 385.234 387.248 391.283 393.296 395.312 407.203 407.234 419.310 421.326 423.343 429.239 437.359 441.296 453.166 1516
PPNS
PPD
1.0
0.1
SPN
SCC 4.5
3.6 1.6
5.0 10.3
3.4 4.2 2.0
2.8 2.2
4.9 6.3 2.1 3.1 3.3
4.9 1.5
9.7 51.4 4.1 14.7 9.4
8.8 100 3.5
0.9 100
100 18.3
100
0.9
4.6 37.0 12.5 9.3
5.1
2.0
2.5 2.3
2.4
10.4 2.2 4.2
1.1 10.5
12.9 6.7 7.1 10.4
3.4 2.2 2.4 1.0
5.8
2.4 1.5 0.6
0.9
3.3 6.1
1.0
1.8
19.2 1.0 4.2
0.5
5.4 2.5 1.8
2.5
1.0 1.0 0.8 2.0
2.8
1.0
2.4
3.9 4.0 3.0 3.3 9.7 4.9 3.0
9.5
5.2
1.4
5.6 11.1 6.5 1.3
2.4
7.9 4.4 1.5 2.1 3.1
2.7
34.6 1.2 1.1 6.9 1.7 1.8 100 1.0 0.8 1.8 4.3 1.6 3.3 16.8
charge carrier
elemental composition
H H H H H H Na H Na H H Na H Na H Na Na Na H Na H Na Na Na Na Na Na Na H Na Na Na Na Na Na Na Na Na Na Na Na Na Na Na Na Na Na Na H Na Na Na Na Na Na Na Na Na Na Na H Na Na Na Na Na Na Na Na Na Na Na
C5H8N2 C4H10O3 C6H10N2 C5H12O3 C7H12N2 C8H12N2 C5H8O3 C8H14N2 C7H6O2 C6H10O3 C9H16N2 C8H8O2 C11H8N2 C9H14O2 C12H10N2 C6H10O5 C10H16O2 C9H6O4 C12H12O2N C6H12O6 C12H12O3 C9H18O4 C7H14O6 C8H12O6 C12H10O2S C12H14O4 C15H20O2 C13H18O4 C16H22O4 C16H30O3 C16H18O4 C18H28O3 C19H18O3 C20H26O2 C20H28O2 C19H26O3 C20H30O2 C19H20O4 C18H32O4 C18H18O5 C20H26O3 C18H34O4 C20H28O3 C12H20O10 C16H24O7 C20H30O4 C17H36O6 C21H24O4 C22H34O4 C12H22O11 C20H22O5 C19H20O6 C20H24O5 C21H32O4 C20H32O5 C21H40O4 C20H22O6 C21H26O5 C22H34O4 C22H36O4 C24H38O4 C22H42O4 C22H44O4 C20H32O7 C28H32O C24H44O4 C24H46O4 C24H48O4 C27H34O3 C25H50O4 C26H42O4 C27H26O5
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tentative assignment
references
Benzoic acid l,4-butyrolactone
45, 48, 49, 53 45
2-Methylbenzoic acid
53
Levoglucosan cis-Thujan-10-oic acid
1, 9, 12, 45-54, 56 49
Fructose
10
diethyl phthalate
52
dibutyl phthalate
52
Divanillyl
1, 48
Abieta-7,13,15- trien-18-oic acid Dehydroabietic acid
48, 50 48, 50, 52-54
Abietic acid
1, 9, 12, 45-54
Octadecenedioic acid
48
7-Oxodehydroabietic acid Octadecanedioic acid Daniellic acid
48, 53 48, 49 48
Sucrose
10
Tetrahydro-3,4- divanillylfuran
1, 9, 12, 48, 49
Heneicosanedioic acid Pinoresinol tetrahydro-3-vanillyl-4-veratrylfuran
48 9, 12, 48 9, 12
Pinifolic acid bis[2-ethylhexyl]phthalate a,o-Docosanedioic acid
48 52 48, 49
Table 3. Continued normalized abundance m/z 462.145 467.100 469.327 479.349 495.343 511.318 519.328 579.292 647.569 663.386 691.417
AD
PPNS
PPD
SPN
SCC
4.5 38.9 1.7 5.7 11.6 5.3 1.6 2.3 2.9
2.2
2.1 2.8
smaller amounts in mass spectra of PPD and SPN. The most abundant peak observed in the SCC spectrum at m/z of 407.234 could not be unambiguously assigned based on the accurate mass alone. This peak could be formally assigned as C28H32ONa+. However, because of inefficient ionization, molecules containing a single oxygen atom are usually observed with low abundances. Alternatively, this peak could be assigned as C25H36O2K+. Distinguishing between these two possible elemental formulas based on the accurate mass measurement requires mass resolution of 2.6 × 106. Detailed structural characterization of the observed organic compounds is beyond the scope of this paper. Tandem mass spectrometry (MS/MS) experiments will be used in future studies for determining possible structures of organic aerosol constituents. ESI spectra of other BBA samples also contain a variety of distinct signatures of different types of biomass. For example, abundant peaks that correspond to butanetriol (C5H12O3H+) and sulfur-containing C12H10O2SNa+ (m/z 241.029) species are observed exclusively in the SPN spectrum; C12H12O3H+, C22H34O4Na+, and C20H22O5Na+ are characteristic features of the AD spectrum; another sulfur-containing C21H22O10SH+ peak is a marker of the PPD aerosol sample. The spectrum of the SCC sample contains the largest number of distinct markers (e.g., C11H8N2H+, C9H6O4Na+, C12H12O2NH+, C16H24O7Na+, C19H20O6Na+, C27H26O5Na+, C28H32ONa+, and C30H48O4Na+). It has been suggested that a significant fraction of high-MW compounds in smoke particles correspond to natural products volatilized during biomass burning and re-deposited on the existing particles.1,9 Our results are consistent with this assertion. For example, several peaks that can be attributed to directly emitted natural products including betulinic acid (C30H48O3Na+, m/z 479.349)striterpene widely distributed in plantssand a small peak corresponding to 1-decarboxy-3-oxo-ceanothic acid (C29H44O3Na+, m/z 463.318) were observed in the biomass burning sample of ceanothus (SCC). In this paper we focus on oxygen-containing sodiated species that typically account for 80-90% of all mass spectral features. Nitrogen-containing organic compounds in biomass burning samples will be discussed in a separate publication. Walser et al.32 demonstrated that oxygenated organic molecules cationized on sodium dominate ESI/MS spectra of SOA produced by the ozoneinitiated oxidation of limonene. Comparison between the positive and the negative ion mode mass spectra of SOA extracts and several model compounds suggested that carboxyl groups were readily ionized in the electrospray process.32 This resulted in
charge carrier
elemental composition
Na H Na Na Na Na Na Na Na Na Na
C31H21O2N C30H14N2O4 C28H46O4 C30H48O3 C30H48O4 C33H44O3 C35H48O7 C32H44O8 C38H76N2O4 C38H56O8 C40H60O8
tentative assignment
references
formation of abundant [M+Na]+ features in the positive mode and [M-H]- ions in the negative mode. Mass spectra obtained for laboratory generated SOA typically contain multiple groups of peaks separated by 14 amu corresponding to the addition of multiple CH2 units.27,28,30-33 In contrast, mass spectra of field collected samples examined in this work do not show obvious regularity. All spectra contain several abundant peaks along with a large number of smaller features that are not clearly separated into specific groups. It has been demonstrated that analyte reaction with the solvent may affect the ESI/MS analysis of aerosol samples.34 Specifically, reactions of methanol with aldehyde and ketone groups in aerosol constituents results in formation of abundant hemiacetals (net addition of CH3OH) that complicate the analysis of highresolution mass spectra. Previous work29,35 suggested that products of self-esterification reaction (net addition of CH2) are more pronounced in the ESI spectra acquired in the positive mode. Because esters produced by self-esterification reaction are usually much less abundant than hemiacetals produced by addition of solvent molecules to the analyte we examined all high-resolution mass spectra obtained in this study for the presence of hemiacetal peaks. Mass spectral features accompanied by peaks corresponding to the net addition of methanol typically constitute less than 10% of the total number of the observed peaks. The only exception is the PPNS sample for which nearly 20 % of peaks are accompanied by a possible product of reaction with the solvent. It is interesting to note that a similar percentage (∼17%) of possible hemiacetal products was observed in the negative ESI spectrum of this sample. However, little or no overlap was observed among the molecular weights of the potential hemiacetal products observed in the positive and negative mode ESI spectra suggesting that the higher-mass peaks separated by the mass of methanol in the BBA samples are not produced from reactions with the solvent. Kendrick Analysis. The complexity of the BBA spectra is partially reduced using the Kendrick analysis described earlier. CH2-based Kendrick diagrams obtained from high-resolution mass spectral data are shown in Figure 2. For comparison, a similar plot was generated based on the data reported by Oros and Simoneit for organic molecules identified in BBA samples produced from burning of conifers using GC/MS.48 It should be noted that all plots derived from ESI/MS spectra of BBA extracts display a systematic increase in the Kendrick defect with increasing analyte molecular weight. This is in contrast to the diagram Analytical Chemistry, Vol. 81, No. 4, February 15, 2009
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Figure 2. CH2-based Kendrick diagrams representing all species observed in high-resolution ESI/MS spectra of five BBA samples discussed in the text, and the corresponding diagram obtained for smoke particulate constituents from burning of conifers reported in ref 48 (see text for more details).
obtained from the GC/MS literature data that do not display any obvious trend. The increase in Kendrick defect with mass is attributed to the higher degree of oxygenation or unsaturation of the heavier BBA constituents. This is readily observed using ESI/ MS but is not pronounced in the GC/MS data. While GC/MS is a valuable tool for detection and quantification of non-polar molecules, ESI/MS is ideally suited for analysis of polar organic compounds in aerosol extracts. However, several classes of compounds (e.g. alkanes, alkenes, aliphatic ketones, aldehydes, and alcohols) are not observed in ESI/MS spectra because of the low ionization efficiency in the electrospray source. Our results suggest that a significant number of high-MW organic compounds in biomass burning particles are highly oxidized polar species that are readily detected using ESI/MS. Kendrick diagrams shown in Figure 2 vary significantly from one BBA sample to another. As discussed earlier, CH2-based Kendrick analysis places homologous series of peaks separated by the mass of the CH2 group on horizontal lines. A large number of such homologous series is clearly visible in the plots obtained for the PPNS and AD samples. In contrast, Kendrick plots obtained for SCC, PPD, and SPN samples contain only a relatively small number of fairly short CH2 series. Kendrick analysis is particularly useful for samples containing longer homologous progression of peaks because successful identification of one member of the series is sufficient for identification of an entire series of compounds. Nine major CH2 homologous series of peaks observed in the AD sample are shown in panels (a)-(i) of Figure 3. Tentative structural assignments are proposed based on the elemental formula of the first peak in each series. In addition, it is assumed 1518
Analytical Chemistry, Vol. 81, No. 4, February 15, 2009
when possible that organic compounds cationized on sodium contain at least one carboxylic acid group. Succinic acid (C5H8O4Na+) is a leading peak of the dicarboxylic acid series (C5H8O4(CH2)nNa+, panel (a)) with the most abundant feature corresponding to C22H42O4Na+ (n ) 17). The C5H10O4(CH2)nNa+ homologous series (panel (b)) most likely corresponding to dihydroxycarboxylic acids contains a large number of peaks of similar absolute intensity covering a broad range of m/z values from 157 to 493. Hydroxycarboxylic acids (C8H16O3(CH2)nNa+, panel (f)) are observed over the range of m/z values from 183 to 407, while the dihydroxydicarboxylic acid series (C7H12O6(CH2)nNa+, panel (d)) shows a gap for n ) 2-8 and a fairly broad distribution of species at higher m/z values (341-439, n ) 9-16). Panel (e) shows the C8H12O4(CH2)nNa+ series corresponding to unsaturated dicarboxylic acids or hydroxyoxocarboxylic acids. This series contains evenly distributed features for n ) 0-4 and a strong peak at n ) 10. Another progression of peaks (C6H10O5(CH2)nNa+, panel (c)) is observed with sodiated levoglucosan, C6H10O5Na+, as a lead peak. However, the absolute abundance of other members of this series is much lower than the intensity of the C6H10O5Na+ peak. In addition, a gap is observed in this series for n ) 3-8. It is reasonable to assume that this progression of peaks corresponds to two overlapping series: a short series of methylated levoglucosan derivatives and a longer series of hydroxydicarboxylic acids with a general formula C15H28O5(CH2)nNa+. A series of saturated ketones (C19-C29) cationized on sodium (C19H38O(CH2)nNa+), panel (f)) was observed in the AD sample. The same series starting from lower molecular weight species (C11-C29) with abundant C13, C17, and C19 peaks was identified in the PPNS Kendrick diagram. The observed odd-even predominance is in agreement with the literature data.46,48 Finally, fairly long CH2 series of terpenoids (C20H32O7(CH2)nNa+), panel (h) and C28H36O8(CH2)nNa+, panel (i)) with m/z values of 407-575 and 523-803, respectively, were observed in the AD sample. Detailed comparison of Kendrick diagrams obtained for five BBA samples provided further confirmation of substantial differences between the corresponding ESI/MS spectra. For example, the dihydroxycarboxylic acids series, C5H10O4(CH2)nNa+, was observed exclusively in the AD sample, while C8H14O6Na+ is the only member of the dihydroxydicarboxylic acid series found in PPNS and SCC samples. Dicarboxylic acids were observed in all samples. However, while the AD sample contains C5-C7, C10-C15, and C17-C28 species, the PPNS sample contains abundant C18 and C24 species and minor features corresponding to C5, C25, C27, and C28. ESI/MS spectra of other samples contain a smaller number of dicarboxylic acid peaks with only one C18 species observed in the SCC spectrum. Monounsaturated carboxylic and dicarboxylic acids are observed predominantly in the PPNS sample with major peaks corresponding to sodiated oleic acid (C18H34O2Na+) in the first series and C24H44O4Na+ and C28H52O4Na+ in the dicarboxylic acid progression. Other major series observed for this sample are C15H28O(CH2)nNa+, C10H14O4(CH2)nNa+, C9H6O4(CH2)nNa+, C10H14O7(CH2)nNa+, C1H16O6(CH2)nNa+, C19H34O5(CH2)nNa+, and C24H44O6(CH2)nNa+. It is interesting to note that both PPNS
Figure 3. Major CH2 homologous series observed in the Alaskan duff (AD) sample.
and PPD samples contain characteristic products of pine smoke reported by Rogge et al.12 These include guaiacyl derivatives, divalillyl, homovanillic acid, and its larger CH2 -based homologous compounds (see Table 3 for details). Van Krevelen and Double Bond Equivalent (DBE) Diagrams. Van Krevelen diagrams were obtained by plotting the H/C versus O/C ratio for all unambiguously identified peaks. Figure 4 compares Van Krevelen plots obtained for the five BBA samples with a plot obtained from the data published by other groups for BBA generated from burning Ponderosa Pine.48,50,53,54 Clearly, analysis of aerosol samples using high-resolution mass spectrometry allowed detection of many more polar species in BBA extracts compared to traditional GC/MS characterization. Most identified compounds have H/C ratios of 2 or less. Several points with higher H/C ratios correspond to small (
