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Aerosol Science and Engineering

, Volume 2, Issue 4, pp 165–172 | Cite as

Measuring the Organic Carbon to Organic Matter Multiplier with Thermal/Optical Carbon-Quadrupole Mass Spectrometer Analyses

  • Judith C. Chow
  • Gustavo M. Riggio
  • Xiaoliang Wang
  • L.-W. Antony Chen
  • John G. Watson
Original Paper
  • 578 Downloads

Abstract

A thermal/optical carbon analyzer (TOA) was adapted to direct thermally-evolved gases to an electron ionization quadrupole mass spectrometer (QMS), creating a TOA-QMS. While this approach produces spectra similar to those obtained by the Aerodyne aerosol mass spectrometer (AMS), and can quantify sulfate (SO42−), nitrate (NO3), ammonium (NH4+), and organic carbon (OC) fractions from ambient particle laden quartz-fiber filters, there remains a need to further understand the composition of the organic aerosol fraction. Elemental analysis (EA) of standard organic mixtures and ambient samples demonstrates the feasibility of the TOA-QMS for measuring the ratios of oxygen-to-carbon (O/C), hydrogen-to-carbon (H/C), nitrogen-to-carbon (N/C), sulfur-to-carbon (S/C), and organic matter-to-organic carbon (OM/OC). For ambient samples from Central California, the TOA-QMS returned average ratios for O/C of 1.03 ± 0.27 and H/C of 1.95 ± 0.69, respectively. Higher H/C ratios were observed during clean air episodes, while lower ratios were observed during hazy conditions. A relatively constant level of aerosol oxidation was observed throughout the study. The average OM/OC multiplier was 2.55 ± 0.4, which is higher than the conventionally used values of 1.4 and 1.8, indicating higher contributions from biomass burning and aged aerosols.

Keywords

Organic carbon Organic matter Ratios of O/C and H/C And OM/OC 

1 Introduction

Elemental analysis (EA) of organic aerosols and complex organic mixtures containing carbon (C), hydrogen (H), nitrogen (N), sulfur (S), and oxygen (O) can provide total organic matter (OM) as well as organic carbon (OC) concentrations in PM2.5 filter samples. PM2.5 material balances currently assume multipliers between 1.2 and 2.6 to account for unmeasured O and H in OM (Chow et al. 2015a). Fresh OC emissions from internal combustion engines contain mostly hydrocarbons composed only C and H, so the multiplier is toward the low end of this range. Biomass burning emissions, especially during the smoldering phase, contain a substantial number of oxygen atoms in their more polar OM. Levoglucosan (C6H10O5), a prominent organic marker for burning emissions, has an OM/OC ratio of 2.25. Secondary organic aerosols (SOA) also have higher OM/OC multipliers as they react with oxygen in the air, thereby lowering their vapor pressures and transitioning from the gas to particle phase (Robinson et al. 2010).

Several methods have been applied to quantify OM/OC ratios and elemental compositions of organic aerosols: (1) combustion analysis (Kiss et al. 2002; Krivácsy et al. 2001; O’Brien et al. 1975); (2) electrospray ionization (ESI) or electron ionization (EI) coupled to ultra-high-resolution mass spectrometry (Aiken et al. 2007, 2008; Altieri et al. 2009; Bateman et al. 2009; Kroll et al. 2011; Mazzoleni et al. 2010; Nguyen and Schug 2008); (3) nuclear magnetic resonance (NMR) spectroscopy (Fuzzi et al. 2001); (4) Fourier-transform infrared spectroscopy (FTIR) (Gilardoni et al. 2009; Mysak et al. 2011); (5) X-ray photoelectron spectroscopy (XPS) (Mysak et al. 2011); (6) gas chromatography–mass spectrometry (GC-MS) (Williams et al. 2006); (7) chemical ionization mass spectrometry (CIMS) with aerosol collection interface coupled to a high-resolution time-of-flight mass spectrometer (Lopez-Hilfiker et al. 2014; Williams et al. 2014; Yatavelli and Thornton 2010); and (8) unaccounted mass in the material balance (Frank 2006).

GC-MS, the most commonly applied method, identifies only 5–20% of the OM. Highly polar and oxygenated compounds do not elute without specific derivatization for the compounds of interest (Orasche et al. 2011). Water-soluble OM is mostly polar and can constitute 20–70% of the total OM. As primary OM ages, non-polar compounds can oxidize into polar compounds creating SOAs with increasing OM/OC ratios (Turpin and Lim 2001). Although additions of O and H cause most of this increase, N and S in organonitrates and organosulfates SOA may also contribute. Higher OM/OC ratios (1.8–2.2) are also found in direct PM emissions from biomass burning, especially the smoldering phase.

Commercially available CHNS/O analyzers have been used to analyze fuels, but these have required larger amounts (> 1 mg) than are typically available on quartz-fiber filter samples from chemical speciation networks. Due to such limitations and uncertainties, an EA technique was developed using electron ionization (EI) high-resolution aerosol mass spectrometry (HR-AMS) (Aiken et al. 2007).

The use of a mass spectrometer (MS) for aerosol elemental analysis relies on the assumption that the sum of the ion signal intensities from all fragments, especially for molecules containing small atoms, is approximately proportional to the mass concentration of the original species. As a result, the ion current for different mass to charge (m/z) signals represents the same original mass and allows for average composition of the ions to be calculated. Molecular concentrations are determined by adding the relative ion contributions for the most abundant m/z signals in the mass spectrum after allocating the composition of the signal to the estimated atoms (C, H, N, S, and O) in each fragment. Measured atomic ratios by mass spectra are then converted to estimated ratios by comparison with mass spectra from known organic standards (Aiken et al. 2007).

Riggio et al. (2018) demonstrated the feasibility of measuring fragmentation patterns to quantify sulfate (SO42−), nitrate (NO3), ammonium (NH4+), and organic carbon (OC) in suspended particulate matter (PM) collected on quartz-fiber filters by coupling a quadrupole mass spectrometer (QMS) to a thermal/optical analyzer (TOA), designated TOA-QMS. It was found that molecular fragmentation patterns from prepared standards and ambient samples could be deconvoluted and apportioned among major inorganic ions, OC, and OM contributions to PM mass. By estimating the O and H associated with inorganic SO42−, NO3, and NH4+, it may be possible to use the remaining O and H to determine O/C and H/C ratios that are indicative of the chemical forms in OM. This study examines the feasibility of performing these analyses.

2 Methodology

Under normal TOA operation, a particle laden quartz-fiber filter punch (~ 0.5 cm2) is heated in a sample oven following the IMPROVE_A protocol (Chow et al. 2007a). The thermally evolved gaseous products are passed through a manganese dioxide (MnO2) oxidation reactor, yielding carbon dioxide (CO2), followed by reduction to methane (CH4) by hydrogen (H2) on a nickel (Ni) catalyst, which can be quantified by a flame ionization detector (FID). Given improved sensitivity of non-dispersive infrared (NDIR) detectors, modern TOA instruments analyze the CO2 directly by eliminating the reduction oven and replacing the FID with an NDIR (Chen et al. 2015; Chow et al. 2015a, b). To demonstrate feasibility of the TOA-QMS, the MnO2 and Ni reactors were bypassed and a simplified version of the IMPROVE_A protocol was used (Riggio et al. 2018). Desorbed PM chemicals were detected at 10 min intervals for temperatures of 80 °C, 580 °C, and 840 °C. A 5% CO2/95% (He) mixture was injected as an internal standard using a Carle valve at the end of each run. A MatLab (MATLAB R (2014a), The MathWorks Inc., Natick, MA) program processed three-dimensional (m/z spectra vs. time) QMS outputs by integrating ion currents at each temperature level using the Riemann (1868) sum method. A baseline was determined at each temperature step for each m/z chromatogram and subtracted from the sample signal. Integrated m/z signal was normalized using the m/z signal from a CO2 calibration standard injected at the end of each run.

Aiken et al. (2007) analyzed 35 model compounds with the high-resolution mass spectrometry (HR-MS) to evaluate ion signal responses, finding that MS-EA analysis of these compounds demonstrated a high correlation between the measured and calculated ratios. This work demonstrated that the biases during molecular fragmentation do not excessively suppress the O/C and H/C ratios for small molecules. It is feasible to use unit mass resolution (UMR) mass spectral to obtain elemental ratios when the elemental composition of all ions contributing to the total signal can be unambiguously determined (Aiken et al. 2007). The TOA-QMS operates at UMR in which prior separation is not applied to the sample. For that reason, TOA-QMS mass spectra detects ion fragments that coexist at the same m/z signal, and a deconvolution process is necessary to separate these fragments, as described by Riggio et al. (2018).

As shown by Aiken et al. (2007), relative concentrations of C and O can be estimated as:
$$M_{\text{c}} = \mathop \sum \limits_{{j = m/z_{\hbox{min} } }}^{{j = m/z_{\hbox{max} } }} I_{j} F_{\text{c}}$$
(1)
$$M_{\text{o}} = \mathop \sum \limits_{{j = m/z_{\hbox{min} } }}^{{j = m/z_{ \hbox{max} } }} I_{j} F_{\text{o}} ,$$
(2)
where Ij is the ion signal at the jth m/z in the spectrum and \(F_{\text{c}}\) and Fo are the mass fractions of C and O for each (jth) ion, respectively (e.g., for CH2O2+, Fc = 12/46 and Fo = 32/46). The O/C mass ratio is then calculated as Mo/Mc. The average elemental composition using the MS-EA technique is a weighted sum of all contributing m/z signals, and deconvolution of the spectral signal into approximate elemental contributions yields the best average elemental composition (Aiken et al. 2007). Table 2 of Aiken et al. (2007) used National Institute of Standards and Technology (NIST) oxalic acid EI-QMS data to illustrate the mass spectral numerical outcomes and the results from the application of the MS-EA technique. The technique produced O/C and H/C ratios of 1.78 and 1.18, respectively, compared to the nominal ratios of 2 for O/C and 1 for H/C in oxalic acid.
To determine how well the TOA-QMS might measure O/C and H/C ratios, a set of 19 organic compounds (Table 1), similar to those of Aiken et al. (2007, 2008), were dissolved and aerosolized with a constant output atomizer (TSI, Model 3076) fed by a zero-air generator (Environics, Model 7000). This aerosol was directed into a manifold and sampled onto six parallel quartz-fiber filters at different flow rates to obtain a range of PM loadings (Riggio 2015). Punches were taken from thee filters and TOA-QMS spectra were acquired and de-convoluted as described by Riggio et al. (2018). Standards of CH4 and CO2 were also directly injected into the TOA.
Table 1

Compounds analyzed by the TOA-QMS grouped by organic classification, molecular formulas, molar mass (MM, g/mol), and nominal and calculated raw atomic ratios (O/C, H/C, N/C, and OM/OC) with one standard deviation are presented

Class

Compound

MM (g/mol)

Formula

O/C

O/CEA (calc ± σ)

H/C

H/CEA (calc ± σ)

N/C

N/CEA (calc ± σ)

OM/OC

OM/OCEA (calc ± σ)

Hydrocarbon

Methane

16.04

CH4

NA

NA

4.00

2.99 ± 0.013

NA

NA

1.33

1.25 ± 0.001

Alcohol

1-Octadecanol

270.49

C18H38O

0.06

0.05 ± 0.014

2.11

1.67 ± 0.013

NA

NA

1.25

1.20 ± 0.018

 

1-Eicosanol

298.55

C20H42O

0.05

0.07 ± 0.058

2.10

1.53 ± 0.055

NA

NA

1.24

1.23 ± 0.014

 

1-Docosanol

326.6

C22H46O

0.05

0.08 ± 0.043

2.09

1.67 ± 0.013

NA

NA

1.24

1.20 ± 0.018

 

1,2-Tetradecanediol

230.39

C14H30O2

0.14

0.09 ± 0.02

2.14

1.66 ± 0.055

NA

NA

1.37

1.26 ± 0.025

 

Pyrogallol

126.11

C6H6O3

0.50

0.46 ± 0.013

1.00

0.89 ± 0.103

NA

NA

1.75

1.69 ± 0.015

 

Cholesterol

386.65

C27H46O

0.04

0.03 ± 0.002

1.70

1.28 ± 0.105

NA

NA

1.19

1.14 ± 0.008

Carboxylic acid

Decanoic acid

172.27

C10H20O2

0.20

0.21 ± 0.085

2.00

1.67 ± 0.027

NA

NA

1.43

1.41 ± 0.114

 

Pentadecanoic acid

242.4

C15H30O2

0.13

0.08 ± 0.006

2.00

1.55 ± 0.103

NA

NA

1.34

1.23 ± 0.016

 

Hexadecanoic acid

256.42

C16H32O2

0.13

0.13 ± 0.072

2.00

1.64 ± 0.338

NA

NA

1.33

1.31 ± 0.096

 

Stearic acid

284.48

C18H36O2

0.11

0.14 ± 0.006

2.00

1.76 ± 0.075

NA

NA

1.32

1.33 ± 0.006

 

Oleic acid

282.46

C18H34O2

0.11

0.17 ± 0.085

1.89

1.30 ± 0.067

NA

NA

1.31

1.33 ± 0.108

 

Glutaric acid

132.12

C5H8O4

0.80

0.61 ± 0.089

1.60

1.11 ± 0.071

NA

NA

2.20

1.90 ± 0.089

 

Adipic acid

146.14

C6H10O4

0.67

0.69 ± 0.015

1.67

1.62 ± 0.052

NA

NA

2.03

2.06 ± 0.024

 

15-Hydroxypentadecanoic acid

258.42

C15H30O3

0.20

0.13 ± 0.083

2.00

1.11 ± 0.074

NA

NA

1.43

1.27 ± 0.075

 

16-Hydroxyhexadecanoic acid

272.43

C16H32O3

0.19

0.15 ± 0.064

2.00

1.28 ± 0.051

NA

NA

1.42

1.30 ± 0.073

Carbohydrate

Levoglucosan

162.14

C6H10O5

0.83

0.96 ± 0.074

1.67

1.23 ± 0.033

NA

NA

2.25

2.39 ± 0.098

Amine

4-Aminobenzoic acid

137.14

C7H7NO2

0.29

0.13 ± 0.035

1.00

0.87 ± 0.016

0.14

0.11 ± 0.014

1.37

1.63 ± 0.058

 

Quinine

324.42

C20H24N2O2

0.1

0.10 ± 0.096

1.20

1.35 ± 0.184

0.1

0.07 ± 0.044

1.33

1.35 ± 0.092

Organic nitrite

3-Methyl-4-nitrophenol

153.14

C7H7NO3

0.43

0.46 ± 0.128

1.00

1.29 ± 0.128

0.14

0.11 ± 0.065

1.85

1.82 ± 0.104

Anhydride

Carbon dioxide

44.01

CO2

2

1.84 ± 0.005

NA

NA

NA

NA

3.67

3.45 ± 0.007

NA not applicable

The MS spectrum from each quartz-fiber filter was analyzed and the average for each compound was used for MS-EA calculations. Data showing contamination from siloxane, most likely from the conductive tubing used when sampling onto the filters (Timko et al. 2009), identified by the combination of peaks at m/z signal 205, 207, 281, and 355 were excluded from the dataset, as were samples with loadings too low for peak detection. The OM/OC ratio was calculated based on values found for O/C, H/C, and N/C (Aiken et al. 2007):
$${{{\rm{OM}}} \over {{\rm{OC}}}} = {{\left( {16 \times {{\rm{O}} \over {\rm{C}}}} \right) + \left( {1 \times {{\rm{H}} \over {\rm{C}}}} \right) + \left( {14 \times {{\rm{N}} \over {\rm{C}}}} \right) + 12} \over {12}}.$$
(3)

3 Results

Figure 1 shows the extent to which ratios of O/C, H/C, N/C, and OM/OC measured by the TOA-QMS compare with the actual ratios calculated for each compound. These comparisons yield measured vs. actual O/C and OM/OC ratios with slopes are close to unity (i.e., 0.93 for O/C and 0.94 for OM/OC). Differences between measured vs. actual ratios for H/C (slope of 0.77) and N/C (slope of 0.75) are larger, indicating a greater fragmentation bias. However, the bias is constant for different compounds as evidenced by the high correlations (0.83 < R2 < 0.99), indicating that the TOA-QMS calibrations may need improvement, as discussed by Riggio et al. (2018).
Fig. 1

TOA-QMS measured ratios vs. actual ratios for: a O/C; b H/C; c N/C, and d OM/OC derived from the analysis of pure compounds in Table 1. Error bars are one standard deviation of multiple samples and the linear regression line is forced through zero in plots a, b, and c. Most of the compounds tested contained no nitrogen

The slight negative bias for the O/C ratio was also found by Aiken et al. (2007) who hypothesized that fragments with low O content have a weaker tendency to retain a positive charge during fragmentation, based on electronegativity (McLafferty and Turecek 1993). The average error in the estimated TOA-QMS O/C ratio is ± 30% comparable to ± 31% for the AMS estimated by Aiken et al. (2008). The negative bias in the H/C ratios could be due to H+ and H2 losses during fragmentation and the absence of m/z signals below 10. The measured and actual H/C ratios are reasonably correlated (R2 = 0.83), while Aiken et al. (2007) found an R2 of 0.92. The standard error of the H/C ratios for this study is ± 9.2%, comparable to ± 10% reported by Aiken et al. (2007, 2008). Figure 1c shows that N/C ratios were found only for the three nitrogenated compounds, with a good correlation (R2 = 0.99) between measured and actual values. The N/C regression slope is 0.75 ± 0.06, and the average error is estimated to be ± 5.6% for this experiment, compared to ± 22% for the AMS (Aiken et al. 2008). Additional calibration points are needed to calculate a more representative N/C value before it can be fully integrated into the TOA-QMS technique. Since the OM/OC ratio is dominated by the O/C ratio, small biases in the H/C and N/C ratios have little effect, as indicated by slope of 0.94 ± 0.04 for the measured vs. actual OM/OC ratios. The close agreement of measured and actual OM/OC ratios indicates that the TOA-QMS is able to determine the OM/OC ratio with reasonable accuracy for known organic compounds.

To evaluate the ratios for organic compound mixtures, two or three punches with known deposits of adipic acid, levoglucosan, stearic acid, and 1, 2 tetradecanediol were placed in the TOA-QMS for simultaneous analysis, with results shown in Table 2. These organic compounds represent O/C, H/C, and OM/OC ratios of primary, secondary, and ambient organic aerosols (Aiken et al. 2007; 2008). The results are somewhat mixed, with O/C ratios underestimated for the two component mixtures by 15–27% and overestimated for the three component mixtures by 11–20%. The H/C ratios were underestimated by 13–22% for all of the mixtures, which affected the OM/OC ratios. These discrepancies could be due to inexact absolute concentrations on samples, which would affect the calculation of the actual ratios. This is not an issue for a single compound because the ratios will be retained regardless of the filter loading. Differences in ionization efficiencies for the different compounds may create further uncertainties with respect to analysis of individual compounds (Aiken et al. 2007).
Table 2

Elemental analysis of mixtures of pure organic compounds (results are presented with ± 1 standard deviation and the absolute percent error)

Compounda

O/C

H/C

OM/OC

Actual

Measured

Measured − actual (%)

Actual

Measured

Measured − actual (%)

Actual

Measured

Measured − actual (%)

Adipic acid + levoglucosan

0.75

0.54 ± 0.019

− 27.48

1.67

1.30 ± 0.086

− 21.83

2.14

1.84 ± 0.018

− 14.18

Stearic acid + levoglucosan

0.29

0.25 ± 0.000

− 14.56

1.92

1.64 ± 0.017

− 14.56

1.55

1.47 ± 0.002

− 4.95

Adipic acid + levoglucosan + stearic acid

0.37

0.41 ± 0.044

11.42

1.87

1.53 ± 0.038

− 17.99

1.64

1.67 ± 0.061

1.78

Stearic acid + levoglucosan + 1,2 tetradecanediol

0.24

0.28 ± 0.006

19.72

2

1.74 ± 0.034

− 12.84

1.48

1.52 ± 0.010

2.81

aSee Table 1 for molecular formulas

O/C, H/C, and OM/OC ratios for 58 PM2.5 wintertime samples from the Fresno Supersite (Watson et al. 2000) were analyzed by TOA-QMS with results shown in Fig. 2. Wintertime carbon levels are known to be influenced by residential wood burning (Chen et al. 2007; Chow et al. 2007b) and possibly by SOA formation (Strader et al. 1999; Young et al. 2016), sources with higher OM/OC ratios than those from engine exhaust. The average O/C ratio is 1.03 ± 0.27 (ranged 0.43–1.82) and the H/C ratio is 1.95 ± 0.69 (ranged 0.88–3.86), which are consistent with biomass burning and SOA. Higher values for H/C occurred from 12/15/2000 to 12/27/2000 where haze was not reported, while O/C remained fairly constant throughout the entire period. The N/C ratio varied from 0.01 to 0.04 with an average of 0.03 ± 0.006, and the OM/OC ratio varied 1.73–3.72 with an average of 2.55 ± 0.4.
Fig. 2

a O/C (red) and H/C (black) ratios overlaid with inorganic and organic mass concentrations for samples collected at the Fresno Supersite from 12/15/2000 and 02/03/2001. b Mass concentrations for samples collected at the Fresno Supersite from 12/12/2000 and 02/03/2001. Good correlation between OC and the OM/OC ratio can be observed. An increase in aerosol concentration can be observed for the periods between 12/27/2000 and 01/07/2001, where long periods of haze were reported

Morning and afternoon average concentrations and ratios are compared in Fig. 3. The H/C ratio is the only one which is highest in the morning compared to the afternoon (7.2% difference), indicative of the O-depleted primary emissions from engine exhaust. O/C and OM/OC ratios are slightly higher during the second part of the day (1.9 and 0.5%, respectively), possibly due to the SOA contribution. Since OM/OC is highly influenced by O/C, owing to the 16-fold higher O molecular weight compared to H, a high correlation between OM/OC and O/C ratios is expected (Pang et al. 2006), as shown in Fig. 4. This same relationship has also been observed by Aiken et al.(2008) with the AMS.
Fig. 3

Morning [0000–1300 local standard time (LST)] and afternoon (1300–2400 LST) a chemical concentrations and b ratios at the Fresno Supersite between 12/15/2000 and 02/03/2001. Values above the bars indicate the relative difference between the afternoon and morning samples relative to the afternoon ratios

Fig. 4

OM/OC vs. OC calculated from 58 ambient samples collected at the Fresno Supersite from 12/15/2000 to 02/03/2001

4 Summary and Conclusion

Experiments were performed to test the ability of the TOA-QMS to estimate the O/C, H/C, N/C, and OM/OC ratios in ambient aerosols. Calibration of the TOA-QMS for elemental analysis was conducted using 19 selected organic compounds containing different nominal ratios. Calibration coefficients for O/C, H/C, and OM/OC were determined and applied to the Fresno Supersite samples collected from 12/15/2000 to 2/3/2001. Good correlations are found between OM/OC and O/C. In addition, separation of the data into morning and afternoon periods shows that H/C is highest in the morning, while O/C and OM/OC are higher during the second part of the day.

The TOA-QMS provides unique capability to analyze SO42−, NO3, NH4+, and OC concentrations in PM samples collected on quartz-fiber filters, and allows for the estimation of O/C, H/C, N/C, and OM/OC through elemental analyses. Further development of the method may obviate the need for analyzing the same quartz-fiber filter by different techniques, thus reduces analysis costs and time.

Notes

Acknowledgements

This research was partially supported by National Science Foundation Grant no. CHE 1464501 and the National Park Service IMPROVE Carbon Analysis Contract P16PC00229. Dr. Glenn Miller of the University of Nevada, Reno provided useful suggestions for the experiments and their description.

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Copyright information

© Institute of Earth Environment, Chinese Academy Sciences 2018

Authors and Affiliations

  • Judith C. Chow
    • 1
    • 2
    • 3
  • Gustavo M. Riggio
    • 1
  • Xiaoliang Wang
    • 1
  • L.-W. Antony Chen
    • 4
  • John G. Watson
    • 1
    • 2
    • 3
  1. 1.Division of Atmospheric SciencesDesert Research InstituteRenoUSA
  2. 2.Graduate FacultyUniversity of NevadaRenoUSA
  3. 3.State Key Laboratory of Loess and Quaternary Geology (SKLLQG), Institute of Earth EnvironmentChinese Academy of SciencesXi’anPeople’s Republic of China
  4. 4.Department of Environmental and Occupational HealthUniversity of NevadaLas VegasUSA

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