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Pitfalls in the Detection of Volatiles Associated with Heated Tobacco and e-Vapor Products When Using PTR-TOF-MS
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  • Noel Bielik
    Noel Bielik
    PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
    More by Noel Bielik
  • Daniela Correia
    Daniela Correia
    PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
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  • Kelly Rodrigues Crespo
    Kelly Rodrigues Crespo
    PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
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  • Catherine Goujon-Ginglinger
    Catherine Goujon-Ginglinger
    PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
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  • Maya I. Mitova*
    Maya I. Mitova
    PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
    *Phone: 0041-58-2422352. Email: [email protected]
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    Orcidhttps://orcid.org/0000-0001-8626-4362
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Journal of the American Society for Mass Spectrometry

Cite this: J. Am. Soc. Mass Spectrom. 2024, 35, 6, 1261–1271
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https://doi.org/10.1021/jasms.4c00062
Published May 23, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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We investigated the applicability of proton transfer reaction-time-of-flight mass spectrometry (PTR-TOF-MS) for quantitative analysis of mixtures comprising glycerin, acetol, glycidol, acetaldehyde, acetone, and propylene glycol. While PTR-TOF-MS offers real-time simultaneous determination, the method selectivity is limited when analyzing compounds with identical elemental compositions or when labile compounds present in the mixture produce fragments that generate overlapping ions with other matrix components. In this study, we observed significant fragmentation of glycerin, acetol, glycidol, and propylene glycol during protonation via hydronium ions (H3O+). Nevertheless, specific ions generated by glycerin (m/z 93.055) and propylene glycol (m/z 77.060) enabled their selective detection. To thoroughly investigate the selectivity of the method, various mixtures containing both isotope-labeled and unlabeled compounds were utilized. The experimental findings demonstrated that when samples contained high levels of glycerin, it was not feasible to perform time-resolved analysis in H3O+ mode for acetaldehyde, acetol, and glycidol. To overcome the observed selectivity limitations associated with the H3O+ reagent ions, alternative ionization modes were investigated. The ammonium ion mode proved appropriate for analyzing propylene glycol (m/z 94.086) and acetone (m/z 76.076) mixtures. Concerning the nitric oxide mode, specific m/z were identified for acetaldehyde (m/z 43.018), acetone (m/z 88.039), glycidol (m/z 73.028), and propylene glycol (m/z 75.044). It was concluded that considering the presence of multiple product ions and the potential influence of other compounds, it is crucial to conduct a thorough selectivity assessment when employing PTR-TOF-MS as the sole method for analyzing compounds in complex matrices of unknown composition.

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Introduction

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Direct injection mass spectrometry is a noninvasive technique facilitating the real-time analysis of many classes of compounds because of its fast response and low detection limits. (1) Similar to other real-time measurement techniques, it has the advantage of analyzing the sample in its native state since sample preparation and storage are not required. (1,2) Commercially available instruments based on direct injection mass spectrometry are widely used as multipurpose sensors and are applied in many fields. (1) Among these, proton transfer reaction mass spectrometry (PTR-MS) is becoming increasingly popular because of its versatility and sensitivity in the low pptV concentration levels. (3,4) The ionization in PTR-MS is in principal chemical ionization using proton transfer from a hydronium ion (H3O+ ion). (3) PTR is typically coupled with time-of-flight (TOF) detectors, which enables the separation of isobaric compounds. (5) Compared with other direct injection mass spectrometry techniques, PTR-MS has the advantage of being quantitative owing to the high degree of similarity in the ionization rate of all ionizable compounds, meaning that the instrument response is proportional to the compound quantity. (3,4) A calibration-less quantification can be conducted by built-in algorithms using mathematical methods based on kinetic theory. (3) This pseudoabsolute functionality improves the throughput in time-resolved measurements of gases and aerosols. The benefits and limitations of this approach are further discussed by Beauchamp et al. (6)
Use of alternative nicotine-delivery systems (e.g., heated tobacco products/heat-not-burn and e-vapor products/e-cigarettes) has increased in recent years. (7,8) Given the relative novelty of these products, it is important to determine if they contain compounds not found in cigarette smoke. A comprehensive characterization of a heated tobacco product was performed to identify any additional constituents beyond the standard harmful and potentially harmful constituents. (9,10) There has also been extensive investigation into certain flavors in the liquids used in e-vapor products. (11) These studies offer the possibility of searching for potential new compounds of toxicological concern and identifying possible chemical tracers for heated tobacco and e-vapor products. In view of evaluating possible new targets, a versatile technique is needed to allow simultaneous real-time quantitative analysis of several compounds related to the use of heated tobacco and e-vapor products. Peer-reviewed evidence demonstrates that PTR-TOF-MS could be a suitable tool for such purposes. (12)
Consequently, we assessed the feasibility of real-time analysis by PTR-TOF-MS of several compounds of interest found in the aerosols of heated tobacco and e-vapor products, either in inhaled aerosol or in exhaled breath samples, focusing on the major aerosol constituents, namely, glycerin and propylene glycol, together with some of their thermal degradation products such as acetol, glycidol, and acetaldehyde and acetone, respectively. Glycerin is used in aerosol formation for heated tobacco products, while glycerin and propylene glycol typically play this role in e-vapor products. Accordingly, these compounds are major components of the aerosols of heated tobacco (13) and e-vapor products (11) and are present in the milligrams per item range. The presence of acetol and glycidol was reported in aerosols of heated tobacco (9) and e-vapor products. (14) In the aerosols of heated tobacco products, acetaldehyde and acetone were present in micrograms per item range, (15) while their levels in aerosols of e-vapor products were typically in the nanograms per puff range with newer generations of devices with sensors preventing dry puff. (16) Furthermore, when considering exhalation samples, it is important to remember that acetone is a major volatile organic compound in all exhaled breath samples. (17)
Glycerol and propylene glycol are considered to have low acute toxicity. The acceptable daily intake for glycerol is “not specified” due to the lack of health-related hazards, (18) while propylene glycol has an established limit of 25 mg/kg body weight/day. (19) Acetone, although low in acute toxicity, can nonetheless cause irritation to the throat and lungs. (20) Limited toxicological data exist for acetol, and thus, no classification or guidance values have been set. Glycidol is considered probably carcinogenic to humans, while acetaldehyde is possibly carcinogenic. (21) Glycerol, propylene glycol, and acetol are used as marker compounds for the aerosols of heated tobacco and e-vapor products. Acetone and acetaldehyde are listed as harmful and potentially harmful constituents in tobacco products by the U.S. Food & Drug Administration (FDA). (22) Glycidol is included in the FDA’s list of chemicals recommended for analysis in premarket applications for e-vapor products. (23)
We investigated the selectivity of PTR-TOF-MS for time-resolved analysis of mixtures of glycerin, acetol, glycidol, acetaldehyde, acetone, and propylene glycol. Considering the elemental composition of the molecular ions and probable ion fragments, the compounds of interest were split into two groups: the first containing glycerin, acetol, glycidol, and acetaldehyde and the second containing propylene glycol and acetone. The concentration ranges for each compound were calculated based on the data for the mainstream aerosol of a popular heated tobacco product (13) (Supplementary Table S1). Within the first group, acetol and glycidol were immediately identified as problematic for this type of analysis since they have the same elemental composition (C3H6O2), and hence, their protonated molecules give overlapping signals in the real-time measurement trace. It remains to be clarified if specific ions (m/z) could be identified for each compound of interest to allow time-resolved analysis of their mixtures to be conducted by PTR-TOF-MS. Hereafter, all ions are presented as theoretical exact masses for given elemental compositions. The theoretical and experimental exact masses and mass accuracies for the ions of all compounds under investigation are summarized in Supplementary Table S2.

Methods

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Instrument Settings

The measurements were conducted on a proton transfer reaction-time-of-flight mass spectrometer (PTR-TOF-MS 6000 X2, Ionicon Analytik, Innsbruck, Austria) equipped with selective reagent ionization (SRI). Nitrogen and oxygen (synthetic air supply, N2 + O2 20% ± 2% v/v, Carbagas, Switzerland) were mixed in the source to produce NO+ reagent ions. Ammonium reagent ions were generated by the reaction of synthetic air with water vapor. The sampling flow rate was 70 mL/min, and the time resolution of the PTR-TOF-MS measurements was 1000 ms. The transmission was determined on a regular basis, whenever the instrument settings were changed, or if the instrument was moved.
For the H3O+ mode, the transfer line and drift tube temperatures were maintained at 100 °C. The drift voltage was 350 V, and the drift tube pressure was 2.8 mbar. The electric field (E/N) ratio was 69 Td. The voltage across the drift tube was varied over the range from 350 to 950 V only in the experiments conducted to determine the fragmentation pattern of each compound of interest as a function of the E/N. In these cases, the values obtained for E/N ranged from 69 to 190 Td. Mass calibration in the H3O+ mode was performed before each experimental run using the following masses: m/z 21.022 (H3O+ isotope), m/z 203.943 (iodine abstraction from 1,3-diiodobenzene, [MH – I]+, C6H5I), and m/z 330.848 (protonated 1,3-diiodobenzene, C6H5I2). 1,3-Diiodobenzene was used as a built-in mass scale calibrator in PTR-TOF-MS (Permeation add-on, Ionicon Analytik, Innsbruck, Austria). During processing, these m/z values were verified, and the data was recalibrated when necessary.
In NO+ mode, the transfer line and drift tube temperatures were maintained at 100 °C. The drift voltage was 80 V, the drift tube pressure was 2.8 mbar, and the E/N ratio was 16 Td. Mass calibration was conducted during processing using m/z 19.018 (H3O+) and 329.840 (1,3-diiodobenzene, C6H4I2+).
In NH4+ mode, the transfer line and drift tube temperatures were maintained at 100 °C. The drift voltage was 180 V, the drift tube pressure was 2.8 mbar, and the E/N ratio was 36 Td. Mass calibration was conducted during processing using m/z 19.018 (H3O+) and 35.060 (NH3.NH4+).

Chemicals

To determine the transmission of PTR-TOF-MS, a custom-made gas mix (Restek, Bellefonte, PA, USA) was used containing acetonitrile, acetone, isoprene, benzene, toluene, o-xylene, 1,2,4-trimethylbenzene, 1,2-dichlorobenzene, and 1,2,3-trichlorobenzene each at 1 ppm in nitrogen.
Acetaldehyde, acetol, acetone, glycidol, glycerin, and propylene glycol were purchased from Sigma-Aldrich (St. Louis, MO, USA). 13C3,D5-labeled glycerin, D5-labeled glycidol, and 13C2-labeled acetaldehyde were provided by Toronto Research Chemicals (Toronto, ON, Canada). Purified water (LC-MS Chromasolv, Thermo Fisher Scientific, Waltham, MA, USA) was used to prepare aqueous solutions of the standards.

Standards Preparation and Measurements

The gas mix to determine the transmission was injected using a liquid calibration unit (LCU, Ionicon Analytik, Innsbruck, Austria). The sampling flow rate was adjusted to inject 5 ppb of each compound. After stabilization of the signal, the gas mix was measured for 5 min, followed by stopping the flow of the gas mix, stabilization of the signal, and then background measurement for 5 min.
For the experiments with stable isotope-labeled standards, stock solutions of individual compounds were prepared in purified water and then mixed and diluted to aqueous solutions named mixtures 1–3. Mixture 1 comprised 13C3,D5-labeled glycerin (89.4 μg/mL), D5-labeled glycidol (2.14 μg/mL), and unlabeled acetaldehyde (5.04 μg/mL). Mixture 2 contained 13C3,D5-labeled glycerin (93.1 μg/mL), 13C2-labeled acetaldehyde (6.64 μg/mL), and unlabeled glycidol (2.23 μg/mL). Mixture 3 was composed of 13C3,D5-labeled glycerin (92.5 μg/mL), D5-labeled glycidol (2.42 μg/mL), and unlabeled acetol (18.7 μg/mL). The LCU was used to convert mixtures 1–3 into gaseous standard mixtures. Each of these mixtures was individually injected at different dilutions to obtain a range of concentrations. The LCU temperature was 100 °C, the nitrogen flow rate was set at 1000 standard cm3/min, and the sample flow rate was varied for the different dilutions in the range of 0.1–10 μL/min. The flow rate of water was varied in the range of 0.1–10 μL/min depending on the dilution level, and it was adjusted to obtain a total flow rate from the two ports (sample port and water port) of 10 μL/min.
For calibration curve generation, stock solutions of individual compounds were prepared in water and then diluted: 13C3,D5-labeled glycerin (85.6 μg/mL), glycidol (6.74 μg/mL), D5-labeled glycidol (7.17 μg/mL), acetaldehyde (3.81 μg/mL), 13C2-labeled acetaldehyde (3.80 μg/mL), and acetol (15.7 μg/mL). The LCU was used for conversion of the solutions into gaseous standards. Each individual solution was injected separately at different dilutions to obtain a range of concentrations. As was the case in the previous experiment, the LCU temperature was 100 °C, the nitrogen flow rate was set at 1000 standard cm3/min, and the sample flow rate was varied for the different dilutions in the range of 0.1–10 μL/min. The flow rate of water was varied in the range of 0.1–10 μL/min depending on the dilution level, and it was adjusted to obtain a total flow rate from the two ports (sample port and water port) of 10 μL/min.
An LCU was used to inject all of the standards for the experiments in the different ionization modes.
Acetone and propylene glycol were introduced in gaseous form in PTR-TOF-MS using a Permeator (model V-OVG, Owlstone, Westport, CT, USA). The exit port of the Permeator was connected directly to the inlet of the PTR-TOF-MS. The permeation tube kit was purchased from Owlstone. The permeation tubes were cut to 10 cm lengths, and each was filled with 1 g of pure compound and then closed tightly. The permeation rate of each compound was determined using TD-GC-MS (thermo-desorption-gas chromatography–mass spectrometry) calibrated with authentic standards. The permeation rates were 283 ng/min at 30 °C for acetone and 130 ng/min at 100 °C for propylene glycol. The permeation tubes for the two compounds were conditioned in the oven of the Permeator (acetone at 30 °C for 2 days, propylene glycol at 100 °C for 2 days). During operation, the oven was maintained at this temperature, and the sample flow rate to the Permeator was set at 100 mL/min. To obtain the different concentration levels for the calibration curve, the flow rates were varied by changing the exhaust flow of the Permeator between 0 and 3 L/min. Each of the compounds was injected individually at different dilutions to obtain a range of different concentrations.

FastGC-PTR-TOF-MS

The acetol, glycerin, glycidol, and propylene glycol mixture was analyzed using the fastGC add-on (version fastGC FGC230, Ionicon Analytik). The following instrumental parameters were used: NO+ mode, PTR drift tube: E/N 16 Td; fastGC: (a) carrier gas flow of 8.00 standard cm3/min and (b) temperature ramp from 50 to 180 °C in 180 s (1.38 °C/s). Then, the temperature of the GC was set to 50 °C to prepare the system for the next injection in 20 s. Nitrogen was used as a carrier and make up gas.

Limit of Detection (LOD)

The LOD for all compounds of interest was determined based on the method proposed by Ellis and Mayhew. (3) In case several fragments were present for a given compound, the most intense m/z was used for the calculations. The following formula was applied (3)
LOD=3×VMRS/N
where the VMR (volume mixing ratio) and S/N (signal-to-noise) were determined for the lowest calibration standard.

Results and Discussion

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Reactions in the Drift Tube of Glycerin, Acetol, Glycidol, and Acetaldehyde in H3O+ Mode

Initially, aiming to characterize the reactions in the drift tube in the H3O+ mode of glycerin, acetol, glycidol, and acetaldehyde, the individual compounds were evaluated separately. When using H3O+ as a reagent ion, some of the most typical and dominant reaction pathways are nondissociative proton transfer yielding a protonated molecule [M + H]+, dissociative proton transfer leading to one or more charged fragments [F]+, and associative proton transfer with hydronium ion [M + H3O]+ and water clusters ([M + H·(H2O)2]+ and [M + H·(H2O)3]+). (3) Reactions with parasitic ions (NO+, O2+) can also occur but to a lesser degree. However, the analysis showed no m/z coming from such reactions for any of the investigated compounds (abundances of NO+, O2+ relative to H3O+ < 2% in all experiments). Likewise, there were no ions for associative proton transfer with the first or second water cluster, and m/z values of only negligible intensity for associative proton transfer with hydronium ions were observed. The remaining point to clarify was whether only nondissociative proton transfer reactions were occurring in the drift tube or if undesirable dissociative proton transfer reactions were also taking place. In the latter reaction type, there is typically a decrease in analytical sensitivity due to loss of signal intensity and, possibly, a loss of selectivity resulting from overlaps with other m/z. A detailed analysis of the data yielded five important observations (Table 1, Figure 1).

  • Acetaldehyde yielded a protonated molecule (m/z 45.033, C2H5O+),

  • Glycerin, acetol, and glycidol gave protonated molecules at m/z 93.055 (C3H9O3+), m/z 75.044 (C3H7O2+), and m/z 75.044 (C3H7O2+), respectively. The protonated molecules of glycerin and glycidol were minor reaction products in the drift tube, while that of acetol was major.

  • Three fragment ions of glycerin were observed in H3O+ mode (m/z 75.044, C3H7O2+, m/z 57.033, C3H5O+, and m/z 45.033, C2H5O+).

  • A minor fragment ion was observed for acetol (m/z 57.033, C3H5O+).

  • Glycidol underwent significant dissociative proton transfer reactions in H3O+ mode, leading to fragment ions at m/z 57.033 (C3H5O+, [M + H – H2O]+) and m/z 45.033 (C2H5O+, [M + H – CH2O]+).

Figure 1

Figure 1. Product ion distributions (percentages) as a function of the electric field (E/N) in H3O+ mode for (A) glycerin, (B) glycidol, (C) acetol, and (D) propylene glycol.

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Table 1. Principal Ion Species in H3O+, NO+, and NH4+ Modes for Acetaldehyde, Acetol, Acetone, Glycerin, Glycidol, and Propylene Glycol
compoundformulaion formulamechanismm/z% total signal
H3O+ reagent ion (H3O+ mode)a
acetaldehydeC2H4OC2H5O+[M + H] +45.033100%
acetolC3H6O2C3H7O2+[M + H]+75.04490%
acetolC3H6O2C3H5O+[M + H – H2O]+57.03310%
acetoneC3H6OC3H7O+[M + H]+59.049100%
glycidolC3H6O2C3H7O2+[M + H]+75.0444%
glycidolC3H6O2C3H5O+[M + H – H2O]+57.03324%
glycidolC3H6O2C2H5O+[M + H – CH2O]+45.03372%
glycerinC3H8O3C3H9O3+[M + H]+93.05516%
glycerinC3H8O3C3H7O2+[M + H – H2O]+75.04432%
glycerinC3H8O3C3H5O+[M + H – 2H2O]+57.03328%
glycerinC3H8O3C2H5O+[M + H – H2O–CH2O]+45.03322%
propylene glycolC3H8O2C3H9O2+[M + H]+77.0603%
propylene glycolC3H8O2C3H7O+[M + H – H2O]+59.04983%
propylene glycolC3H8O2C2H5O+[M + H – CH3OH]+45.0331%
propylene glycolC3H8O2C3H5+[M + H – 2H2O]+41.03910%
propylene glycolC3H8O2C3H3+[M + H – 2H2O – 2H]+39.0232%
NO+ reagent ion (NO+ mode)
acetaldehydeC2H4OC2H3O+[M – H]+43.018100%
acetolC3H6O2C3H6NO3+[M + NO]+104.034100%
acetoneC3H6OC3H6NO2+[M + NO]+88.039100%
glycidolC3H6O2C3H6NO4+[M – 2H + NO + H2O]+120.029b12%
glycidolC3H6O2C3H6NO3+[M + NO]+104.03417%
glycidolC3H6O2C3H7O3+[M – H + H2O]+91.03910%
glycidolC3H6O2C3H5O2+[M – H]+73.02862%
glycerinC3H8O3C3H6NO4+[M – 2H + NO]+120.02947%
glycerinC3H8O3C3H7O3+[M – H]+91.03933%
glycerinC3H8O3C2H5O2+[M – H – CH2O]+61.02821%
propylene glycolC3H8O2C3H6NO3+[M – 2H + NO]+104.03440%
propylene glycolC3H8O2C3H7O2+[M – H]+75.04460%
NH4+ reagent ion (NH4+ mode)
acetaldehydeC2H4O    
acetolC3H6O2C3H10NO2+[M + NH4]+92.071100%
acetoneC3H6OC3H10NO+[M + NH4]+76.076100%
glycidolC3H6O2C3H10NO2+[M + NH4]+92.071100%
glycerinC3H8O3C3H12NO3+[M + NH4]+110.081100%
propylene glycolC3H8O2C3H12NO2+[M + NH4]+94.086100%
a

The interpretation of the glycerin fragmentation is based on the investigation of Nimlos et al. (24)

b

This ion is not a primary product. It is likely the outcome of a [MNO – 2H]+ ion formation, followed by subsequent association with water.

Over the range of concentrations studied, the responses of the protonated molecules and fragment ions of all compounds were linear (Supplementary Figures S1–S4). The LODs are reported in Table 2.
Table 2. LOD of the Compounds in H3O+, NO+, and NH4+ Modes
reagent ioncompoundVMR (ppbV)S/NLOD (ppbV)
H3O+acetaldehyde0.1941.10.525
 acetol0.47412.50.114
 acetone2.4422.40.327
 glycerin1.9242.90.134
 glycidol0.201.30.474
 propylene glycol1.1020.70.160
NO+acetaldehyde27.042.71.90
 acetol6.2819.40.972
 acetone16.818.22.77
 glycerin14.640.01.10
 glycidol6.534.184.68
 propylene glycol5.90106.00.167
NH4+acetone2.165.71.14
 propylene glycol4.1943.60.288
Thus, whenever samples containing mixtures of glycerin, acetol, glycidol, and acetaldehyde were analyzed by PTR-TOF-MS with H3O+ as the reagent ion, the following overlapping m/z values in the time-resolved trace were found (Figure 2).

  • m/z 75.044 for C3H7O2+: ions for protonated acetol and glycidol and a fragment ion of glycerin [M + H – H2O]+.

  • m/z 57.033 for C3H5O+: fragment ions of glycidol and acetol [M + H – H2O]+ and a fragment ion of glycerin [M + H – 2H2O]+.

  • m/z 45.033 for C2H5O+: ions for protonated acetaldehyde, a fragment ion of glycidol [M + H – CH2O]+, and a fragment ion of glycerin [M + H – H2O – CH2O]+.

Figure 2

Figure 2. Product ion distributions in H3O+ mode at 69 Td for acetaldehyde, acetol, glycidol, and glycerin.

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Accordingly, there was a specific ion for glycerin at m/z 93.055 (C3H9O3+), making it possible to conduct the PTR-TOF-MS analysis in H3O+ mode (Figure 2). However, it was obvious that the presence of glycerin in the sample would impact the PTR-TOF-MS analysis of the other compounds. Yet, since the dissociative proton transfer reactions of acetol and glycidol had different patterns and acetaldehyde gave a single ion, it was important to clarify if it would be possible to analyze acetol by PTR-TOF-MS in H3O+ mode using m/z 75.044, glycidol by m/z 57.033, and acetaldehyde by m/z 45.033 (Figure 2).
This investigation was carried out by applying mixtures of stable isotope-labeled compounds and unlabeled compounds. In this case, using different combinations of stable isotope-labeled compounds and unlabeled compounds in the same MS analysis made it possible to clearly distinguish the ions from different compounds within a given mixture (Supplementary Figure S5).
The accurate masses for the protonated compounds and fragments with and without a stable isotope label for each of the mixtures 1–3 used in the experiments are summarized in Table 3. The proportions of one compound versus the sums of the other compounds over the evaluated concentration range are summarized in Supplementary Tables S3–S5 for mixture 1, Supplementary Tables S6–S8 for mixture 2, and Supplementary Tables S9–S11 for mixture 3.
Table 3. Ions for Stable Isotope-Labeled and Unlabeled Compounds in Mixtures 1–3
ionion formula.ion formulam/zion formulam/z
mixture 1glycerol-13C3,D5glycidol-D5acetaldehyde
 13C3D5H4O3+101.096    
ion 313C3D5H2O2+83.086C3D5H2O2+80.075
ion 213C3D5O+65.075C3D5O+62.065
ion 113C2D3H2O+50.059C2D3H2O+48.052C2H5O+45.033
mixture 2glycerol-13C3,D5glycidolacetaldehyde-13C2
 13C3D5H4O3+101.096    
ion 313C3D5H2O2+83.086C3H7O2+75.044
ion 213C3D5O+65.075C3H5O+57.033
ion 113C2D3H2O+50.059C2H5O+45.03313C2H5O+47.040
mixture 3glycerol-13C3,D5glycidol-D5acetol
 13C3D5H4O3+101.096    
ion 313C3D5H2O2+83.086C3D5H2O2+80.075C3H7O2+75.044
ion 213C3D5O+65.075C3D5O+62.065C3H5O+57.033
ion 113C2D3H2O+50.059C2D3H2O+48.052  

Influence of Glycerin, Acetol, and Glycidol on Real-Time Analysis of Acetaldehyde in H3O+ Mode

As discussed above, in PTR-TOF-MS (H3O+ reagent ion), acetaldehyde was considered for monitoring by the protonated molecule at m/z 45.033 (C2H5O+, hereafter ion 1). In the time-resolved trace of a given sample analyzed by PTR-TOF-MS, at this m/z, there was signal overlap for protonated acetaldehyde, the fragment [M + H – CH2O]+ of glycidol, and the fragment [M + H – H2O–CH2O]+ of glycerin (Figure 2). Acetol did not give any fragments at m/z 45.033. By using either mixture 1 (13C3,D5-labeled glycerin, D5-labeled glycidol, and unlabeled acetaldehyde) or mixture 2 (13C3,D5-labeled glycerin, 13C2-labeled acetaldehyde, and unlabeled glycidol), it was possible to evaluate the contribution of each compound to ion 1. Indeed, each of the stable isotope-labeled and unlabeled compounds generated well-resolved signals (Table 3, Supplementary Figure S5).
In mixtures with different concentrations of glycerin, glycidol, and acetaldehyde, glycerin contributed 10–99% (mixture 1, Supplementary Table S12) or 7–98% (mixture 2, Supplementary Table S13) of the signal for ion 1. In cases where the glycerin to acetaldehyde and glycidol proportion was lower than 2.5 (Supplementary Table S3) or 4.2 (Supplementary Table S6), the contribution of the glycerin fragment to ion 1 was below 50% (Supplementary Tables S12 and S13). However, if glycerin was present at a higher proportion versus acetaldehyde and glycidol, a significant portion of ion 1 was derived from the glycerin fragment (51–99% Supplementary Table S12, 51–98% Supplementary Table S13). On the other hand, at least one-half of the signal for ion 1 was attributed to acetaldehyde, where the acetaldehyde to glycerin and glycidol proportion was higher than 0.4 (Supplementary Tables S4, S7, S14, and S15). Furthermore, only at the highest investigated levels for acetaldehyde versus the lowest studied concentrations for glycerin and glycidol was the contribution of acetaldehyde to ion 1 substantial (75–92%, Supplementary Tables S14 and S15). At the concentration ranges and proportions investigated, the impact of glycidol on ion 1 was low (0.1–27%, Supplementary Tables S16 and S17), except for the highest studied levels of glycidol combined with the lowest concentrations of both acetaldehyde and glycerin, resulting in 30–52% of the signal being attributed to glycidol (Supplementary Tables S16 and S17).

Influence of Glycerin, Acetaldehyde, and Acetol on Real-Time Analysis of Glycidol in H3O+ Mode

Three m/z values were monitored in the glycidol PTR-TOF-MS analysis in H3O+ mode: a protonated molecule at m/z 75.044, corresponding to elemental composition C3H7O2+ (hereafter Ion 3), a fragment ion resulting from neutral loss of water (m/z 57.033, C3H5O+, hereafter ion 2), and a fragment ion following neutral losses of CH2O and water (m/z 45.033, C2H5O+, ion 1) (Figure 1B). In the time-resolved trace of PTR-TOF-MS, there was an overlap with several other compounds at each of these m/z values (Figure 2). As previously mentioned, in the concentration range and proportions investigated for glycerin, acetaldehyde, and glycidol, the contribution of glycidol to ion 1 was low (0.152%, in most cases 0.1–15%, Supplementary Tables S16 and S17). These results clearly demonstrated that in the presence of glycerin and acetaldehyde, ion 1 was unsuitable for monitoring this compound in H3O+ mode. Initially, ion 2 was considered the best suited for the analysis of glycidol, while ion 3 was appropriate for acetol (Figure 2).
Since acetaldehyde did not generate any m/z overlapping with ion 2, it was irrelevant for this analysis. The influence of acetol on ion 2 in the presence of the other three compounds (glycerin, acetol, and glycidol) was investigated by adding nonlabeled acetol to a mixture of 13C3,D5-labeled glycerin and D5-labeled glycidol (mixture 3, Table 3). It was deduced that acetol would have a lower impact on ion 2 of glycidol, considering acetol’s very low rate of dissociative proton transfer reaction (Figure 2). In contrast, since glycerin underwent significant dissociative proton transfer (Figure 2), a strong impact of glycerin on ion 2 was assumed in samples with high glycerin levels.
When different concentrations of glycerin, acetol, and glycidol were present in the same mixture (mixture 3), glycerin impacted the intensity of ion 2 in the range of 24–99% (Supplementary Table S18), while the acetol influence was 1–73% (Supplementary Table S19). In both cases, the contribution of glycidol to ion 2 was low (0.1–24%), even at its highest investigated concentration combined with the lowest studied levels of acetol and glycerin (Supplementary Table S20). Accordingly, ion 2 was deemed inappropriate for monitoring glycidol in the studied concentration ranges of glycerin, acetol, and glycidol.

Influence of Glycerin and Glycidol on Real-Time Analysis of Acetol in H3O+ Mode

As discussed above, acetol gave rise to two m/z in the analysis by PTR-TOF-MS with the H3O+ reagent ion: one major ion corresponding to the protonated molecule (m/z 75.044, C3H7O2+, ion 3) and a minor fragment ion resulting from neutral loss of water (m/z 57.033, C3H5O+, ion 2) (Figure 1C). In the time-resolved trace of PTR-TOF-MS, these two m/z of acetol overlapped with those of glycerin and glycidol (Figure 2). Given the relative ion intensities in the traces of the individual compounds, ion 2 was considered suitable for monitoring glycidol (Figure 1B) and ion 3 for monitoring acetol (Figure 1C).
The contribution of acetol to ion 3 in samples containing different levels of glycerin, acetol, and glycidol was studied in mixture 3 (nonlabeled acetol, 13C3,D5-labeled glycerin, and D5-labeled glycidol, Table 3). The results indicated that the glycerin and acetol contributions to ion 3 were in the ranges of 5–96% (Supplementary Table S21) and 4–95% (Supplementary Table S22), respectively. When the acetol to glycerin and glycidol ratio exceeded 0.7, acetol contributed to over 75% of ion 3. Moreover, the impact of glycidol on ion 3 was irrelevant (0.02–7%, Supplementary Table S23).
In the concentration range and proportions investigated, in certain conditions (acetol level equal to/higher than vs the sum of glycerin and glycidol levels), ion 3 could be used for monitoring acetol (Supplementary Table S22).

Investigation of Alternative Reagent Ions

The outcome of the experiments described confirmed that it was not possible to perform time-resolved analysis by PTR-TOF-MS using H3O+ reagent ions for acetaldehyde, acetol, and glycidol in samples containing high levels of glycerin. Owing to the lack of selectivity and specificity for acetaldehyde, acetol, and particularly glycidol, it was not feasible from a practical perspective to conduct a time-resolved analysis of samples of unknown qualitative and quantitative composition with this approach. Therefore, alternative ionization modes of PTR-TOF-MS were investigated to identify a more selective method for time-resolved analysis of these compounds. NO+ and NH4+ ionization modes were explored in two separate sets of experiments. Indeed, the use of NO+ and NH4+ reagent ions in PTR-MS provides some selectivity for compounds with different functional groups or structural features and sometimes creates simpler spectra. (4,25,26)
Depending on the target compound, there are several dominant reaction pathways using NO+ as the reagent ion, specifically charge transfer [M]+, hydride abstraction [M – H]+, hydroxide abstraction [M – OH]+, cluster formation with NO+ [M + NO]+, and cluster formation with hydride abstraction [M + NO – 2H]+. (26−28)
Different ionization reactions could occur depending on compounds’ functional groups, which facilitate the analysis of compounds of identical elemental composition. For example, Koss et al. (27) showed that using PTR-MS in NO+ mode permits time-resolved measurement of isomeric aldehydes and ketones in outdoor air because these carbonyls have a different ionization mechanism depending on the functional groups. Based on the compound structure, different product ions are formed in reactions with NO+ as the reagent ion, which ensures higher selectivity in PTR-MS analysis of gas mixtures. (25)
Regarding NH4+ ionization mode, the reaction mechanisms resemble those occurring in H3O+ mode and typically include, depending on the target compound, a nondissociative proton transfer [M + H]+, an associative proton transfer with ammonium ion [M + NH4]+, or an ammonium cluster [M + NH3 + NH4]+. (29)
Although using NH4+ as a reagent ion is not very common, it had advantages for selective time-resolved analysis in some initial experiments. (4) Furthermore, PTR-MS in NH4+ mode was successfully applied to analyze secondary organic aerosols. (29)
The reactions in the drift tube of PTR-TOF-MS when using either NO+ or NH4+ reagent ions were explored in two sets of experiments for each compound. Like the experiments performed in H3O+ mode, the individual compounds (glycerin, acetol, glycidol, and acetaldehyde) were analyzed separately.
The analysis of the data in the NO+ mode for the compounds of interest showed, to a certain extent, improved selectivity and specificity of the method (Table 1).

  • Three m/z of glycerin were observed in NO+ mode (m/z 120.029, C3H6NO4+, [M – 2H + NO]+); m/z 91.039, C3H7O3+, [M – H]+; m/z 61.028, C2H5O2+, [M – H – CH2O]+).

  • Acetaldehyde generated a single ion (m/z 43.018, C2H3O+, [M – H]+).

  • Acetol ionized via adduct formation with NO+ (m/z 104.034, C3H6NO3+, [M + NO]+).

  • Glycidol yielded several reaction products at m/z 120.029 (C3H6NO4+, [M – 2H + NO + H2O]+), m/z 104.034 (C3H6NO3+, [M + NO]+), m/z 91.039 (C3H7O3+, [M – H + H2O]+), and m/z 73.028 (C3H5O2+, [M – H]+).

Regarding the reaction products of glycidol with the NO+ ionic reagent, it was initially suspected that the ions at m/z 120.029 and m/z 91.039 were due to contamination of the glycidol standard. To clarify this, a mixture of glycerin and glycidol was analyzed by PTR-TOF-MS using the instrument’s fastGC add-on. Acceptable chromatographic separation of the compounds was achieved, and the product ions attributed to each of them in the initial experiment were confirmed (Figure 3).

Figure 3

Figure 3. Analysis by fastGC-PTR-TOF-MS of a mixture of glycerin, glycidol, acetol, and propylene glycol in NO+ mode (E/N 16 Td).

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The presence of several m/z for glycerin and glycidol and their overlap (m/z 120.029, C3H6NO4+, and m/z 91.040, C3H7O3+, Figure 4) indicated general issues related to selectivity in this ionization mode coupled with decreased sensitivity for both compounds. Moreover, the only ion for acetol at m/z 104.034 overlapped with the NO+ adduct ion of glycidol (Figure 4). These observations are of concern, especially for time-resolved analysis of complex matrices containing these compounds. Based on these findings, it would only be possible to analyze mixtures of glycerin, acetol, and glycidol in samples with known qualitative and quantitative composition. For example, in samples with glycerin and acetol as major compounds and glycidol as a minor compound, the product ions at m/z 120.029, m/z 104.034, and m/z 73.029 could provide some degree of specificity for the time-resolved analysis of glycerin, acetol, and glycidol, respectively. Concerning the application for quantitative analysis, similar to the results with the H3O+ reagent ion, the responses of the m/z in NO+ mode for acetaldehyde, glycerin, acetol, and glycidol were linear over the studied range of concentrations (Supplementary Figures S6–S9). The LODs are summarized in Table 2.

Figure 4

Figure 4. Product ion distributions in NO+ mode at 16 Td for acetaldehyde, acetol, glycidol, and glycerin.

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Furthermore, data analysis for the compounds of interest showed simpler product ion distributions in NH4+ mode compared to H3O+ mode (Table 1). Unfortunately, no ion for acetaldehyde was observed in this ionization mode. All other compounds underwent association reactions with NH4+ to generate cluster ions [M + NH4]+ at m/z 110.081 (C3H12NO3+, glycerin) and m/z 92.071 (C3H10NO2+, overlap of acetol and glycidol). These results demonstrated that the NH4+ mode was unsuitable for analyzing samples containing mixtures of acetaldehyde, acetol, glycidol, and glycerin since acetaldehyde was not ionized, while acetol and glycidol gave overlapping signals. Further experiments in NH4+ mode to evaluate linearity over the range of concentrations of interest were discontinued.

PTR-TOF-MS Analysis of Propylene Glycol and Acetone

In view of the results discussed above on samples containing acetaldehyde, acetol, glycidol, and glycerin, it was decided to evaluate the selectivity and specificity of PTR-TOF-MS analysis for samples containing mixtures of propylene glycol and acetone directly under three different ionization modes (H3O+, NO+, and NH4+ reagent ions).
Three m/z were monitored in the PTR-TOF-MS analysis of propylene glycol in H3O+ mode: a minor ion for protonated molecule at m/z 77.060 (C3H9O2+), a major fragment ion resulting from neutral loss of water (m/z 59.049, C3H7O+), and a second minor fragment ion following neutral loss of two water molecules (m/z 41.039, C3H5+) (Figure 1D). At higher voltages, two other fragment ions were generated at m/z 45.033 ([M + H – CH4O]+, C2H5O+) and m/z 39.023 ([M + H – 2H2O – 2H]+, C3H3+) (Figure 1D). Similar to the behavior of glycerin in H3O+ mode, although a nondissociative proton transfer occurred, unfortunately, a significant dissociative proton transfer also took place that generated a major fragment ion. Regarding acetone, this compound underwent nondissociative proton transfer to yield an ion at m/z 59.049 (C3H7O+) for the protonated molecule. The signal of this ion overlapped with the fragment ion of propylene glycol. This was a similar phenomenon to that observed in experiments with the H3O+ reagent ion for glycerin, where glycerin fragment ions overlapped with the m/z of the other compounds of interest. Although this approach would be suitable for analyzing propylene glycol itself, the lack of selectivity would make it inappropriate for samples of unknown qualitative and quantitive composition. Regarding the application for quantitative analysis, the responses of the m/z in the H3O+ mode for acetone and propylene glycol were linear over the studied range of concentrations (Supplementary Figures S10 and S11). The LODs are reported in Table 2.
In NO+ mode, propylene glycol generated two m/z corresponding to hydride abstraction (m/z 75.044, [M – H]+, C3H7O2+) and formation of a cluster with NO+ accompanied by hydride abstraction (m/z 104.034, [M – 2H + NO]+, C3H6NO3+) (Table 1). The assignment of the m/z of propylene glycol was confirmed by fastGC-PTR-TOF-MS analysis (Figure 3). For acetone, this compound yielded one single ion following cluster formation with NO+ (m/z 88.039, C3H6NO2+, [M + NO]+) (Table 1). These results show that although this ionization mode would theoretically permit selective analysis by PTR-TOF-MS of mixtures of both compounds, the ion at m/z 104.034 would overlap with the adduct ions of acetol and glycidol (Table 1). Therefore, the approach was considered unsuitable for samples of unknown composition. Concerning quantitative analysis, similar to the results with the H3O+ reagent ion, the responses of m/z in the NO+ mode for acetone and propylene glycol were linear over the range of concentrations investigated (Supplementary Figures S12 and S13).
Analysis of the product ions of propylene glycol and acetone with the NH4+ ionic reagent showed the presence of a single m/z resulting from ionization via adduct formation with NH4+ at m/z 94.086 (propylene glycol, C3H12NO2+) and at m/z 76.076 (acetone, C3H10NO+) (Table 1). Thus, this ionization mode was deemed appropriate for time-resolved analysis of mixtures of propylene glycol and acetone by PTR-TOF-MS. Similar to the analysis with H3O+ and NO+ reagent ions, the responses of the ions in NH4+ mode for acetone and propylene glycol were linear over the range of concentrations studied (Supplementary Figures S14 and S15).

Implication for PTR-TOF-MS Analysis

The literature contains ample evidence that a number of compounds undergo a dissociative proton transfer reaction with H3O+ ionic reagent. (3,17,30−33) This generates identical small fragments in many cases, complicating spectra interpretation and impacting the time-resolved analysis. By using NO+ reagent ions, simpler spectra are obtained in some cases (26−28) or the selectivity of the analysis is improved. (27,34) Nevertheless, multiple product ions and/or ionic fragments could be obtained from some compounds, thereby limiting the selectivity of PTR-MS in this ionization mode. (27,34) Thus, it is crucial to highlight that fragmentation in both H3O+ and NO+ modes is not only a common phenomenon but also one that is frequently observed.
Proton donation from NH4+ is less exothermic than that from H3O+, which might reduce ion fragmentation and simplify spectra. (4) However, fewer compounds could be ionized via reaction with NH4+ reagent ions, so from a practical perspective, some authors consider the potential benefits of using alternatives to H3O+ as proton sources to be minimal. (4) Overall, there are limitations in terms of selectivity and specificity for time-resolved studies of emissions of volatile organic compounds by PTR-MS in complex matrices. Chromatographic techniques avoid many of these limitations but have major drawbacks, such as much slower time resolution and substantial resource requirements to achieve time-resolved analysis. PTR-TOF-MS remains a powerful tool for conducting real-time quantitative analysis. The selectivity issues are less concerning for major compounds since, even if their m/z overlaps with that of another compound, a substantial portion of the ion can still be attributed to the intended compound. Nevertheless, a significant problem arises when dealing with minor compounds. In such cases, if only 10–30% of the m/z corresponds to the target compound, the analysis will likely fall within the uncertainty range of the method, rendering real-time analysis impractical. For these reasons, different research groups approach the challenges of time-resolved analysis in varied ways. For example, the time-resolved analysis of volatile organic compounds by PTR-MS is reported by presenting the results using m/z coupled to certain elemental compositions without assigning compound names. (35) Other research groups present data by assigning typical volatile organic compounds to the measured m/z (17,36) or by using a mixed approach with some elemental compositions combined with typical volatile organic compounds for a certain type of sample. (27,37,38) Finally, to take advantage of the time-resolved analysis by PTR-MS and address the selectivity issue of this technique, some researchers recommend coupling this analysis at the initial stage of the study to a chromatography-based technique (e.g., GC-MS, fastGC, LC-MS). (30,32,39) Considering the results of our study, we are fully aligned with this recommendation. Indeed, our findings demonstrate that it is necessary to couple the time-resolved analysis by PTR-MS with qualitative and quantitative evaluation of the samples by a chromatography-based technique during the initial stages. It is also crucial to carefully evaluate the most appropriate ionization mode and the behavior of the compounds in the drift tube. Applying this approach would help avoid erroneous time-resolved results. For example, if the influence of the major compound glycerin on PTR-TOF-MS (H3O+ mode) quantification of acetol, glycidol, and acetaldehyde in the aerosols of heated tobacco and e-vapor products was not considered, the quantities of all of these compounds would be overestimated. The same applies to the influence of propylene glycol on the analysis of acetone.
This has implications beyond the analyses of recreational practices such as heated tobacco and e-vapor product use. For example, glycerin and propylene glycol are used to generate artificial fog in the entertainment industry, (40) glycerin is a widely used ingredient in toiletries, (41) and propylene glycol is a common food additive. (19) Accordingly, these compounds are more frequent in indoor environments and exhaled breath than could be imagined at first glance. However, it is not immediately obvious to consider possible interferences from these compounds in real-time analysis by PTR-TOF-MS (and probably other direct injection mass spectrometry techniques) when evaluating acetaldehyde as an indoor pollutant or acetaldehyde, glycidol, and acetone as exposure markers in exhaled breath. It is of interest to note that acetaldehyde and acetone were proposed as markers of disease in exhaled breath analysis. (42) According to our results, their ions in the time-resolved trace of PTR-TOF-MS might be strongly influenced by the presence of other compounds, thus leading to erroneous results in cases where only this or other direct injection mass spectrometry techniques are used. Therefore, it is imperative to give judicious consideration to method selectivity evaluation for the specific matrix, especially in cases where complex matrices are under investigation.

Conclusions

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These experiments investigated the suitability of PTR-TOF-MS for time-resolved quantitative analysis of mixtures of glycerin, acetol, glycidol, acetaldehyde, acetone, and propylene glycol with H3O+, NH4+, and NO+ reagent ions.
The analysis of data collected in H3O+ mode showed that there were specific m/z for glycerin and propylene glycol, but the analysis of the other compounds was impacted. Furthermore, the outcome of an experiment with stable isotope-labeled compounds showed that the analysis of acetaldehyde and acetol was feasible by PTR-TOF with H3O+ reagent ions only in samples with low concentrations of glycerin and not in samples with high levels. Moreover, the results demonstrated that H3O+ mode was not suitable at all for the analysis of glycidol at the concentration ranges investigated.
Although selective analysis by PTR-TOF-MS in NH4+ mode was possible for propylene glycol and acetone mixtures, this was not the case for acetaldehyde, acetol, and glycidol. Concerning ionization via the NO+ reagent ion, the compounds of interest showed simpler product ion distributions compared to the H3O+ ionic reagent, which improved selectivity. However, it should be noted that although specific m/z were identified for acetaldehyde, acetone, glycerin, glycidol, and propylene glycol, this was not the case for acetol. Furthermore, glycerin and glycidol generated multiple m/z, indicating selectivity issues in complex matrices and decreased sensitivity in cases where both compounds were present at low levels.
Overall, these experiments demonstrated that time-resolved analysis of these compounds by PTR-TOF-MS was to a certain extent possible when using combinations of different ionization modes. Concerning heated tobacco and e-vapor products, time-resolved analysis of the major compounds glycerin and propylene glycol was feasible, while that of the minor compound glycidol appeared to be impacted in all tested ionization modes. Overall, the analysis of mixtures of acetaldehyde, acetol, glycidol, glycerin, propylene glycol, and acetone in complex matrices appeared to be ambiguous.
We have not investigated interferences from other matrix components of aerosols of heated tobacco and e-vapor products. Such interferences with the time-resolved analysis of the compounds investigated in this study are possible. This is a limitation of the present study and merits future investigation.
Regarding quantitative analysis by PTR-TOF-MS, the responses of the ions of the different compounds were linear over the studied concentration ranges in all cases. These results show the potential of PTR-TOF-MS for quantitative time-resolved analysis for major compounds in complex matrices. It is recommended to couple PTR-TOF-MS with a chromatography-based analysis in the initial development stages to avoid erroneous results due to the presence of isomers or isomeric fragments.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jasms.4c00062.

  • Table S1, Concentration ranges for glycerin, acetol, glycidol, and acetaldehyde and propylene glycol and acetone for a popular heated tobacco product.; Table S2, summary of theoretical and experimental exact masses and mass accuracies for ions of compounds under investigation; Tables S3−S11, ratio between concentration levels of the compounds under investigation; Tables S12−S17, influence of ion 1 on the analysis of compounds under investigation; Tables S18−S20, influence of ion 2 on the analysis of compounds under investigation; Table S21-S23, influence of ion 3 on the analysis of compounds under investigation; Figures S1−S4 and S6−S15, calibration plots of compounds under investigation under different ionization modes; Figure S5, mass spectrum of ion 1 in mixture 1 (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Noel Bielik - PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
    • Daniela Correia - PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
    • Kelly Rodrigues Crespo - PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
    • Catherine Goujon-Ginglinger - PMI R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, CH-2000 Neuchâtel, Switzerland
  • Author Contributions

    Noel Bielik: visualization, review, experimental design, methodology, and data analysis. Catherine Goujon-Ginglinger: review, supervision, and funding. Daniela Correia: conceptualization, visualization, writing and review, experimental design, and data analysis. Kelly Rodrigues Crespo: methodology. Maya I. Mitova: conceptualization, writing original draft including reviewing and editing, experimental design, and data analysis.

  • Notes
    The authors declare the following competing financial interest(s): Maya I. Mitova and Catherine Goujon-Ginglinger report a relationship with Philip Morris International that includes employment and equity or stocks. Noel Bielik, Daniela Correia, and Kelly Rodrigues Crespo report a relationship with Philip Morris International that includes employment.

Acknowledgments

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We express our sincere appreciation to the following persons for their valuable support in this study: Rene Gutmann from Ionicon Analytik GmbH for the support on implementation of real-time measurements using NO+ and NH4+ reagent ions, Carole Medan and Emmanuel Rouget for their support on the implementation of PTR-TOF-MS in our laboratories, Dr. Serge Maeder for sponsoring the study, and Julia Carroll and Dr. Lindsay Reese for editing the manuscript. Philip Morris International is the sole source of funding and sponsor of this research.

References

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    A review. Proton-transfer reaction mass spectrometry (PTR-MS) is a technique developed almost exclusively for the detection of gaseous org. compds. in air. Volatile org. compds. (VOCs) in air have both natural and anthropogenic sources. Natural sources include the emission of org. gases by living objects, both plants and animals. A well-known example, which is discussed later in this review, is the emission of a variety of gaseous org. compds. in the breath of animals, which are released from both the digestive system and the lungs. Plants are major sources of org. gases, as is the decay of dead animal and plant matter. Subsequent photochem. can add further compds. to the mixt. Consequently, even without contributions from humans, ambient air from the Earth's atm. would consist of a complex mixt. of VOCs.
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    Graus, M.; Müller, M.; Hansel, A. High resolution PTR-TOF: Quantification and formula confirmation of VOC in real time. J. Am. Soc. Mass Spectrom. 2010, 21 (6), 1037– 1044,  DOI: 10.1016/j.jasms.2010.02.006
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    High Resolution PTR-TOF: Quantification and Formula Confirmation of VOC in Real Time
    Graus, Martin; Mueller, Markus; Hansel, Armin
    Journal of the American Society for Mass Spectrometry (2010), 21 (6), 1037-1044CODEN: JAMSEF; ISSN:1044-0305. (Elsevier B.V.)
    We present the unprecedented capability to identify and quantify volatile org. compds. (VOCs) by means of proton transfer reaction time-of-flight (PTR-TOF) mass spectrometry online with high time resoln. A mass resolving power of 4000-5000 and a mass accuracy of 2.5 ppm allow for the unambiguous sum-formula identification of hydrocarbons (HCs) and oxygenated VOCs (OVOCs). Test masses measured over an 11-wk period are very precise (SD < 3.4 ppm) and the mass resolving power shows good stability (SD < 5%). Based on a 1 min time resoln., we demonstrate a detection limit in the low pptv range featuring a dynamic range of six orders of magnitude. Sub-ppbv VOC concns. are analyzed within a second; sub-pptv detection limits are achieved within a few tens of minutes. We present a thorough characterization of our recently developed PTR-TOF system and address application fields for the new instrument.
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    Beauchamp, J.; Herbig, J.; Dunkl, J.; Singer, W.; Hansel, A. On the performance of proton-transfer-reaction mass spectrometry for breath-relevant gas matrices. Meas. Sci. Technol. 2013, 24 (12), 125003,  DOI: 10.1088/0957-0233/24/12/125003
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    Ratajczak, A.; Jankowski, P.; Strus, P.; Feleszko, W. Heat Not Burn Tobacco Product─A New Global Trend: Impact of Heat-Not-Burn Tobacco Products on Public Health, a Systematic Review. Int. J. Environ. Res. Public Health. 2020, 17 (2), 409,  DOI: 10.3390/ijerph17020409
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    Fadus, M. C.; Smith, T. T.; Squeglia, L. M. The rise of e-cigarettes, pod mod devices, and JUUL among youth: Factors influencing use, health implications, and downstream effects. Drug Alcohol Depend. 2019, 201, 85– 93,  DOI: 10.1016/j.drugalcdep.2019.04.011
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    The rise of e-cigarettes, pod mod devices, and JUUL among youth: Factors influencing use, health implications, and downstream effects
    Fadus Matthew C; Smith Tracy T; Squeglia Lindsay M
    Drug and alcohol dependence (2019), 201 (), 85-93 ISSN:.
    BACKGROUND: Electronic cigarettes (e-cigarettes) were first introduced in the U.S. market in 2006, with the more recent evolution of "pod-mod" e-cigarettes such as JUUL introduced in 2015. Although marketed as a smoking cessation tool, e-cigarettes are rarely used for this purpose in youth. This review aims to synthesize the literature regarding e-cigarette use among youth, and provides a resource for clinicians, educators, and families that helps answer commonly asked questions about e-cigarettes. METHODS: PubMed, Scopus, and PsycINFO search was performed using search terms "Electronic Nicotine Delivery Systems," "e cigarettes," "e-cigarettes," "electronic cigarettes," "vaping," "JUUL," "e-cigs," and "vape pens." Search results were filtered to only include those related to adolescents and young adults. RESULTS: E-cigarette use among youth is common, with rates of use increasing from 1.5% in 2011 to 20.8% in 2018. Pod mod devices such as JUUL have gained favor among youth for their sleek design, user-friendly function, desirable flavors, and ability to be used discreetly in places where smoking is forbidden. Adolescents are often uninformed about the constituents of e-cigarettes, and little is known about the long-term effects of e-cigarettes. Studies have suggested a "gateway" effect for combustible cigarettes and cannabis use. CONCLUSIONS: E-cigarette use is becoming increasingly common among youth, leading to a myriad of questions and concerns from providers, educators, and family members. More research is needed to determine the ultimate public health impact of e-cigarette use. The authors provide a summary table of frequently asked questions in order to help clarify these common concerns.
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    Bentley, M. C.; Almstetter, M.; Arndt, D.; Knorr, A.; Martin, E.; Pospisil, P.; Maeder, S. Comprehensive chemical characterization of the aerosol generated by a heated tobacco product by untargeted screening. Anal. Bioanal. Chem. 2020, 412, 2675,  DOI: 10.1007/s00216-020-02502-1
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    Comprehensive chemical characterization of the aerosol generated by a heated tobacco product by untargeted screening
    Bentley, Mark C.; Almstetter, Martin; Arndt, Daniel; Knorr, Arno; Martin, Elyette; Pospisil, Pavel; Maeder, Serge
    Analytical and Bioanalytical Chemistry (2020), 412 (11), 2675-2685CODEN: ABCNBP; ISSN:1618-2642. (Springer)
    Abstr.: A suite of untargeted methods has been applied for the characterization of aerosol from the Tobacco Heating System 2.2 (THS2.2), a heated tobacco product developed by Philip Morris Products S.A. and commercialized under the brand name IQOS. A total of 529 chem. constituents, excluding water, glycerin, and nicotine, were present in the mainstream aerosol of THS2.2, generated by following the Health Canada intense smoking regimen, at concns. ≥ 100 ng/item. The majority were present in the particulate phase (n = 402), representing more than 80% of the total mass detd. by untargeted screening; a proportion were present in both particulate and gas-vapor phases (39 compds.). The identities for 80% of all chem. constituents (representing > 96% of the total detd. mass) were confirmed by the use of authentic anal. ref. materials. Despite the uncertainties that are recognized to be assocd. with aerosol-based untargeted approaches, the reported data remain indicative that the uncharacterized fraction of TPM generated by THS2.2 has been evaluated to the fullest practicable extent. To the best of our knowledge, this work represents the most comprehensive chem. characterization of a heated tobacco aerosol to date.
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    Lang, G.; Henao, C.; Almstetter, M.; Arndt, D.; Goujon, C.; Maeder, S. Non-targeted analytical comparison of a heated tobacco product aerosol against mainstream cigarette smoke: does heating tobacco produce an inherently different set of aerosol constituents?. Anal. Bioanal. Chem. 2024, 416, 1349,  DOI: 10.1007/s00216-024-05126-x
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    Margham, J.; McAdam, K.; Cunningham, A.; Porter, A.; Fiebelkorn, S.; Mariner, D.; Digard, H.; Proctor, C. The Chemical Complexity of e-Cigarette Aerosols Compared With the Smoke From a Tobacco Burning Cigarette. Front. Chem. 2021, 9, 743060,  DOI: 10.3389/fchem.2021.743060
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    The chemical complexity of e-cigarette aerosols compared with the smoke from a tobacco burning cigarette
    Margham, J.; McAdam, K.; Cunningham, A.; Porter, A.; Fiebelkorn, S.; Mariner, D.; Digard, H.; Proctor, C.
    Frontiers in Chemistry (Lausanne, Switzerland) (2021), 9 (), 743060CODEN: FCLSAA; ISSN:2296-2646. (Frontiers Media S.A.)
    As e-cigarette popularity has increased, there is growing evidence to suggest that while they are highly likely to be considerably less harmful than cigarettes, their use is not free of risk to the user. There is therefore an ongoing need to characterize the chem. compn. of e-cigarette aerosols, as a starting point in characterizing risks assocd. with their use. This study examd. the chem. complexity of aerosols generated by an e-cigarette contg. one unflavored and three flavored e-liqs. A combination of targeted and untargeted chem. anal. approaches was used to examine the no. of compds. comprising the aerosol. Contributions of e-liq. flavors to aerosol complexity were investigated, and the sources of other aerosol constituents sought. Emissions of 98 aerosol toxicants were quantified and compared to those in smoke from a ref. tobacco cigarette generated under two different smoking regimes. Combined untargeted and targeted aerosol analyses identified between 94 and 139 compds. in the flavored aerosols, compared with an estd. 72-79 in the unflavored aerosol. This is significantly less complex (by 1-2 orders of magnitude) than the reported compn. of cigarette smoke. Combining both types of anal. identified 5-12 compds. over and above those found by untargeted anal. alone. Gravimetrically, 89-99% of the e-cigarette aerosol compn. was composed of glycerol, propylene glycol, water and nicotine, and around 3% comprised other, more minor, constituents. Comparable data for the Ky3R4F ref. tobacco cigarette pointed to 58-76% of cigarette smoke "tar" being composed of minor constituents. Levels of the targeted toxicants in the e-cigarette aerosols were significantly lower than those in cigarette smoke, with 68.5->99% redns. under ISO 3308 puffing conditions and 88.4->99% redns. under ISO 20778 (intense) conditions; redns. against the WHO TobReg 9 priority list were around 99%. These analyses showed that the e-cigarette aerosols contain fewer compds. and at significantly lower concns. than cigarette smoke. The chem. diversity of an e-cigarette aerosol is strongly impacted by the choice of e-liq. ingredients.
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    Pleil, J. D.; Hansel, A.; Beauchamp, J. Advances in proton transfer reaction mass spectrometry (PTR-MS): applications in exhaled breath analysis, food science, and atmospheric chemistry. J. Breath Res. 2019, 13 (3), 039002,  DOI: 10.1088/1752-7163/ab21a7
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    Schaller, J. P.; Keller, D.; Poget, L.; Pratte, P.; Kaelin, E.; McHugh, D.; Cudazzo, G.; Smart, D.; Tricker, A. R.; Gautier, L. Evaluation of the Tobacco Heating System 2.2. Part 2: Chemical composition, genotoxicity, cytotoxicity, and physical properties of the aerosol. Regul. Toxicol. Pharmacol. 2016, 81, S27– S47,  DOI: 10.1016/j.yrtph.2016.10.001
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    Evaluation of the Tobacco Heating System 2.2. Part 2: Chemical composition, genotoxicity, cytotoxicity, and physical properties of the aerosol
    Schaller, Jean-Pierre; Keller, Daniela; Poget, Laurent; Pratte, Pascal; Kaelin, Etienne; McHugh, Damian; Cudazzo, Gianluca; Smart, Daniel; Tricker, Anthony R.; Gautier, Lydia; Yerly, Michel; Reis Pires, Roger; Le Bouhellec, Soazig; Ghosh, David; Hofer, Iris; Garcia, Eva; Vanscheeuwijck, Patrick; Maeder, Serge
    Regulatory Toxicology and Pharmacology (2016), 81 (Suppl._2), S27-S47CODEN: RTOPDW; ISSN:0273-2300. (Elsevier Inc.)
    The chem. compn., in vitro genotoxicity, and cytotoxicity of the mainstream aerosol from the Tobacco Heating System 2.2 (THS2.2) were compared with those of the mainstream smoke from the 3R4F ref. cigarette. In contrast to the 3R4F, the tobacco plug in the THS2.2 is not burnt. The low operating temp. of THS2.2 caused distinct shifts in the aerosol compn. compared with 3R4F. This resulted in a redn. of more than 90% for the majority of the analyzed harmful and potentially harmful constituents (HPHCs), while the mass median aerodynamic diam. of the aerosol remained similar. A redn. of about 90% was also obsd. when comparing the cytotoxicity detd. by the neutral red uptake assay and the mutagenic potency in the mouse lymphoma assay. The THS2.2 aerosol was not mutagenic in the Ames assay. The chem. compn. of the THS2.2 aerosol was also evaluated under extreme climatic and puffing conditions. When generating the THS2.2 aerosol under "desert" or "tropical" conditions, the generation of HPHCs was not significantly modified. When using puffing regimens that were more intense than the std. Health Canada Intense (HCI) machine-smoking conditions, the HPHC yields remained lower than when smoking the 3R4F ref. cigarette with the HCI regimen.
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    Shah, N. H.; Noe, M. R.; Agnew-Heard, K. A.; Pithawalla, Y. B.; Gardner, W. P.; Chakraborty, S.; McCutcheon, N.; Grisevich, H.; Hurst, T. J.; Morton, M. J. Non-Targeted Analysis Using Gas Chromatography-Mass Spectrometry for Evaluation of Chemical Composition of E-Vapor Products. Front. Chem. 2021, 9, 742854,  DOI: 10.3389/fchem.2021.742854
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    Non-targeted analysis using gas chromatography-mass spectrometry for evaluation of chemical composition of E-vapor products
    Shah, Niti H.; Noe, Michael R.; Agnew-Heard, Kimberly A.; Pithawalla, Yezdi B.; Gardner, William P.; Chakraborty, Saibal; McCutcheon, Nicholas; Grisevich, Hannah; Hurst, Thomas J.; Morton, Michael J.; Melvin, Matt S.; Miller, John H., IV.
    Frontiers in Chemistry (Lausanne, Switzerland) (2021), 9 (), 742854CODEN: FCLSAA; ISSN:2296-2646. (Frontiers Media S.A.)
    The Premarket Tobacco Product Applications (PMTA) guidance issued by the Food and Drug Administration for electronic nicotine delivery systems (ENDSs) recommends that in addn. to reporting harmful and potentially harmful constituents (HPHCs), manufacturers should evaluate these products for other chems. that could form during use and over time. Although e-vapor product aerosols are considerably less complex than mainstream smoke from cigarettes and heated tobacco product (HTP) aerosols, there are challenges with performing a comprehensive chem. characterization. Some of these challenges include the complexity of the e-liq. chem. compns., the variety of flavors used, and the aerosol collection efficiency of volatile and semi-volatile compds. generated from aerosols. In this study, a non-targeted anal. method was developed using gas chromatog.-mass spectrometry (GC-MS) that allows evaluation of volatile and semi-volatile compds. in e-liqs. and aerosols of e-vapor products. The method employed an automated data anal. workflow using Agilent MassHunter Unknowns Anal. software for mass spectral deconvolution, peak detection, and library searching and reporting. The automated process ensured data integrity and consistency of compd. identification with >99% of known compds. being identified using an inhouse custom mass spectral library. The custom library was created to aid in compd. identifications and includes over 1,100 unique mass spectral entries, of which 600 have been confirmed from ref. std. comparisons. The method validation included accuracy, precision, repeatability, limit of detection (LOD), and selectivity. The validation also demonstrated that this semi-quant. method provides estd. concns. with an accuracy ranging between 0.5- and 2.0-fold as compared to the actual values. The LOD threshold of 0.7 ppm was established based on instrument sensitivity and accuracy of the compds. identified. To demonstrate the application of this method, we share results from the comprehensive chem. profile of e-liqs. and aerosols collected from a marketed e-vapor product. Applying the data processing workflow developed here, 46 compds. were detected in the e-liq. formulation and 55 compds. in the aerosol sample. More than 50% of compds. reported have been confirmed with ref. stds. The profiling approach described in this publication is applicable to evaluating volatile and semi-volatile compds. in e-vapor products.
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    Simonavicius, E.; McNeill, A.; Shahab, L.; Brose, L. S. Heat-not-burn tobacco products: a systematic literature review. Tob. Control. 2019, 28 (5), 582– 594,  DOI: 10.1136/tobaccocontrol-2018-054419
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    Farsalinos, K. E.; Gillman, G. Carbonyl Emissions in E-cigarette Aerosol: A Systematic Review and Methodological Considerations. Front. Physiol. 2018, 8, 1119,  DOI: 10.3389/fphys.2017.01119
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    Younes, M.; Aggett, P.; Aguilar, F.; Crebelli, R.; Dusemund, B.; Filipič, M.; Frutos, M. J.; Galtier, P.; Gott, D.; Gundert-Remy, U. Re-evaluation of propane-1,2-diol (E 1520) as a food additive. EFSA J. 2018, 16 (4), e05235  DOI: 10.2903/j.efsa.2018.5235
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    Harmful and potentially harmful constituents in tobacco products and tobacco smoke; established list. US. Department of Health and Human Services Food and Drug Administration Center for Tobacco Products, 2012; https://www.federalregister.gov/documents/2012/04/03/2012-7727/harmful-and-potentially-harmful-constituents-in-tobacco-products-and-tobacco-smoke-established-list.
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    Premarket Tobacco Product Applications for Electronic Nicotine Delivery Systems. Guidance for Industry; U.S. Department of Health and Human Services Food and Drug Administration Center for Tobacco Products, 2019; https://www.fda.gov/media/127853/download.
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    Nimlos, M. R.; Blanksby, S. J.; Qian, X.; Himmel, M. E.; Johnson, D. K. Mechanisms of Glycerol Dehydration. J. Phys. Chem. A 2006, 110 (18), 6145– 6156,  DOI: 10.1021/jp060597q
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    Mechanisms of Glycerol Dehydration
    Nimlos, Mark R.; Blanksby, Stephen J.; Qian, Xianghong; Himmel, Michael E.; Johnson, David K.
    Journal of Physical Chemistry A (2006), 110 (18), 6145-6156CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
    Dehydration of neutral and protonated glycerol was investigated using quantum mech. calcns. (CBS-QB3). Calcns. on neutral glycerol show that there is a high barrier for simple 1,2-dehydration, Ea = 70.9 kcal mol-1, which is lowered to 65.2 kcal mol-1 for pericyclic 1,3-dehydration. In contrast, the barriers for dehydration of protonated glycerol are much lower. Dehydration mechanisms involving hydride transfer, pinacol rearrangement, or substitution reactions have barriers between 20 and 25 kcal mol-1. Loss of water from glycerol via substitution results in either oxirane or oxetane intermediates, which can interconvert over a low barrier. Subsequent decompn. of these intermediates proceeds via either a second dehydration step or loss of formaldehyde. The computed mechanisms for decompn. of protonated glycerol are supported by the gas-phase fragmentation of protonated glycerol obsd. using a triple-quadrupole mass spectrometer.
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    Hegen, O.; Salazar Gómez, J. I.; Schlögl, R.; Ruland, H. The potential of NO+ and O2+• in switchable reagent ion proton transfer reaction time-of-flight mass spectrometry. Mass Spectrom. Rev. 2023, 42, 1688– 1726,  DOI: 10.1002/mas.21770
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    Bhatia, M.; Manini, N.; Biasioli, F.; Cappellin, L. Theoretical Investigation of Charge Transfer from NO+ and O2+ Ions to Wine-Related Volatile Compounds for Mass Spectrometry. J. Am. Soc. Mass Spectrom. 2022, 33 (2), 251– 264,  DOI: 10.1021/jasms.1c00253
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    Koss, A. R.; Warneke, C.; Yuan, B.; Coggon, M. M.; Veres, P. R.; de Gouw, J. A. Evaluation of NO+ reagent ion chemistry for online measurements of atmospheric volatile organic compounds. Atmos. Meas. Technol. 2016, 9 (7), 2909– 2925,  DOI: 10.5194/amt-9-2909-2016
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    Karl, T.; Hansel, A.; Cappellin, L.; Kaser, L.; Herdlinger-Blatt, I.; Jud, W. Selective measurements of isoprene and 2-methyl-3-buten-2-ol based on NO+ ionization mass spectrometry. Atmos. Chem. Phys. 2012, 12 (24), 11877– 11884,  DOI: 10.5194/acp-12-11877-2012
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    Zaytsev, A.; Breitenlechner, M.; Koss, A. R.; Lim, C. Y.; Rowe, J. C.; Kroll, J. H.; Keutsch, F. N. Using collision-induced dissociation to constrain sensitivity of ammonia chemical ionization mass spectrometry (NH4+ CIMS) to oxygenated volatile organic compounds. Atmos. Meas. Technol. 2019, 12 (3), 1861– 1870,  DOI: 10.5194/amt-12-1861-2019
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    Using collision-induced dissociation to constrain sensitivity of ammonia chemical ionization mass spectrometry (NHC+4 CIMS) to oxygenated volatile organic compounds
    Zaytsev, Alexander; Breitenlechner, Martin; Koss, Abigail R.; Lim, Christopher Y.; Rowe, James C.; Kroll, Jesse H.; Keutsch, Frank N.
    Atmospheric Measurement Techniques (2019), 12 (3), 1861-1870CODEN: AMTTC2; ISSN:1867-8548. (Copernicus Publications)
    Chem. ionization mass spectrometry (CIMS) instruments routinely detect hundreds of oxidized org. compds. in the atm. A major limitation of these instruments is the uncertainty in their sensitivity to many of the detected ions. We describe the development of a new high-resoln. time-of-flight chem. ionization mass spectrometer that operates in one of two ionization modes: using either ammonium ion ligand-switching reactions such as for NH4+ CIMS or proton transfer reactions such as for proton-transfer-reaction mass spectrometer (PTR-MS). Switching between the modes can be done within 2 min. The NH+4 CIMS mode of the new instrument has sensitivities of up to 67000 dcps ppbv-1 (duty-cycle-cor. ion counts per s per part per billion by vol.) and detection limits between 1 and 60 pptv at 2σ for a 1 s integration time for numerous oxygenated volatile org. compds. We present a mass spectrometric voltage scanning procedure based on collision-induced dissocn. that allows us to det. the stability of ammonium-org. ions detected by the NH4+ CIMS instrument. Using this procedure, we can effectively constrain the sensitivity of the ammonia chem. ionization mass spectrometer to a wide range of detected oxidized volatile org. compds. for which no calibration stds. exist. We demonstrate the application of this procedure by quantifying the compn. of secondary org. aerosols in a series of lab. expts.
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    Malásková, M.; Henderson, B.; Chellayah, P. D.; Ruzsanyi, V.; Mochalski, P.; Cristescu, S. M.; Mayhew, C. A. Proton transfer reaction time-of-flight mass spectrometric measurements of volatile compounds contained in peppermint oil capsules of relevance to real-time pharmacokinetic breath studies. J. Breath Res. 2019, 13 (4), 046009,  DOI: 10.1088/1752-7163/ab26e2
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    Kari, E.; Miettinen, P.; Yli-Pirilä, P.; Virtanen, A.; Faiola, C. L. PTR-ToF-MS product ion distributions and humidity-dependence of biogenic volatile organic compounds. Int. J. Mass Spectrom. 2018, 430, 87– 97,  DOI: 10.1016/j.ijms.2018.05.003
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    PTR-ToF-MS product ion distributions and humidity-dependence of biogenic volatile organic compounds
    Kari, Eetu; Miettinen, Pasi; Yli-Pirila, Pasi; Virtanen, Annele; Faiola, Celia L.
    International Journal of Mass Spectrometry (2018), 430 (), 87-97CODEN: IMSPF8; ISSN:1387-3806. (Elsevier B.V.)
    Quant. proton-transfer-reaction mass spectrometer (PTR-MS) measurements of ambient volatile org. compds. (VOCs) require proper calibration procedures. In particular, compd. product ion distribution and humidity-dependent responses must be characterized. In this study, we generated twelve gas-phase terpenoid stds. using a dynamic diln. system to calibrate the PTR-MS with time-of-flight mass spectrometer (PTR-ToF-MS): six monoterpenes, two monoterpene derivs., and four sesquiterpenes. The humidity-dependent response was characterized for three terpenoid compds. to compare different mol. structures: α-pinene, δ-limonene, and longifolene. We provide the first comprehensive summary of PTR-ToF-MS product ion distributions for twelve common biogenic volatile org. compds. using two different reduced elec. field (E/N) values, 80 Td and 130 Td. Results demonstrated that neglecting to correct for individual product ion distributions of different terpenoid isomers can result in an error of up to 26% for reported mixing ratios. δ-Limonene and longifolene exhibited a small humidity-dependent response in the PTR-ToF-MS, but this did not contribute significantly to the overall measurement error. These results will improve quantification of commonly-measured biogenic volatile org. compd. emissions and chem. in the atm.
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    Maleknia, S. D.; Bell, T. L.; Adams, M. A. PTR-MS analysis of reference and plant-emitted volatile organic compounds. Int. J. Mass Spectrom. 2007, 262 (3), 203– 210,  DOI: 10.1016/j.ijms.2006.11.010
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    Pagonis, D.; Sekimoto, K.; de Gouw, J. A Library of Proton-Transfer Reactions of H3O+ Ions Used for Trace Gas Detection. J. Am. Soc. Mass Spectrom. 2019, 30 (7), 1330– 1335,  DOI: 10.1007/s13361-019-02209-3
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    A Library of Proton-Transfer Reactions of H3O+ Ions Used for Trace Gas Detection
    Pagonis, Demetrios; Sekimoto, Kanako; de Gouw, Joost
    Journal of the American Society for Mass Spectrometry (2019), 30 (7), 1330-1335CODEN: JAMSEF; ISSN:1044-0305. (Springer)
    We have collected data on the proton-transfer reactions with H3O+ ions for trace gas detection into an online and publicly available library. The library allows users of proton-transfer-reaction mass spectrometry (PTR-MS) and selected-ion flow-tube mass spectrometry (SIFT-MS) to look up at which m/z a trace gas of interest is detected. Vice versa, the library also allows looking up what trace gas may have been responsible for a product ion detected in PTR-MS and SIFT-MS. Finally, the library may serve as a dataset for further research on calcg. instrument sensitivity and product-ion fragmentation, improving identification and quantification of newly detectable compds. as advances in instrumentation continue. To demonstrate the utility of the library, we present a brief anal. of product-ion fragmentation. We show that oxygenated org. compds. exhibit trends in neutral loss according to their functionality, and that on av. neutral losses decrease the carbon no. and increase the extent of unsatn. of product ions. [Figure not available: see fulltext.].
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    Mochalski, P.; Unterkofler, K.; Španěl, P.; Smith, D.; Amann, A. Product ion distributions for the reactions of NO+ with some physiologically significant aldehydes obtained using a SRI-TOF-MS instrument. Int. J. Mass Spectrom. 2014, 363, 23– 31,  DOI: 10.1016/j.ijms.2014.02.016
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    Product ion distributions for the reactions of NO+ with some physiologically significant aldehydes obtained using a SRI-TOF-MS instrument
    Mochalski, Pawel; Unterkofler, Karl; Spanel, Patrik; Smith, David; Amann, Anton
    International Journal of Mass Spectrometry (2014), 363 (), 23-31CODEN: IMSPF8; ISSN:1387-3806. (Elsevier B.V.)
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    Noninvasive detection of lung cancer by analysis of exhaled breath
    Bajtarevic Amel; Ager Clemens; Pienz Martin; Klieber Martin; Schwarz Konrad; Ligor Magdalena; Ligor Tomasz; Filipiak Wojciech; Denz Hubert; Fiegl Michael; Hilbe Wolfgang; Weiss Wolfgang; Lukas Peter; Jamnig Herbert; Hackl Martin; Haidenberger Alfred; Buszewski Boguslaw; Miekisch Wolfram; Schubert Jochen; Amann Anton
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    BACKGROUND: Lung cancer is one of the leading causes of death in Europe and the western world. At present, diagnosis of lung cancer very often happens late in the course of the disease since inexpensive, non-invasive and sufficiently sensitive and specific screening methods are not available. Even though the CT diagnostic methods are good, it must be assured that "screening benefit outweighs risk, across all individuals screened, not only those with lung cancer". An early non-invasive diagnosis of lung cancer would improve prognosis and enlarge treatment options. Analysis of exhaled breath would be an ideal diagnostic method, since it is non-invasive and totally painless. METHODS: Exhaled breath and inhaled room air samples were analyzed using proton transfer reaction mass spectrometry (PTR-MS) and solid phase microextraction with subsequent gas chromatography mass spectrometry (SPME-GCMS). For the PTR-MS measurements, 220 lung cancer patients and 441 healthy volunteers were recruited. For the GCMS measurements, we collected samples from 65 lung cancer patients and 31 healthy volunteers. Lung cancer patients were in different disease stages and under treatment with different regimes. Mixed expiratory and indoor air samples were collected in Tedlar bags, and either analyzed directly by PTR-MS or transferred to glass vials and analyzed by gas chromatography mass spectrometry (GCMS). Only those measurements of compounds were considered, which showed at least a 15% higher concentration in exhaled breath than in indoor air. Compounds related to smoking behavior such as acetonitrile and benzene were not used to differentiate between lung cancer patients and healthy volunteers. RESULTS: Isoprene, acetone and methanol are compounds appearing in everybody's exhaled breath. These three main compounds of exhaled breath show slightly lower concentrations in lung cancer patients as compared to healthy volunteers (p < 0.01 for isoprene and acetone, p = 0.011 for methanol; PTR-MS measurements). A comparison of the GCMS-results of 65 lung cancer patients with those of 31 healthy volunteers revealed differences in concentration for more than 50 compounds. Sensitivity for detection of lung cancer patients based on presence of (one of) 4 different compounds not arising in exhaled breath of healthy volunteers was 52% with a specificity of 100%. Using 15 (or 21) different compounds for distinction, sensitivity was 71% (80%) with a specificity of 100%. Potential marker compounds are alcohols, aldehydes, ketones and hydrocarbons. CONCLUSION: GCMS-SPME is a relatively insensitive method. Hence compounds not appearing in exhaled breath of healthy volunteers may be below the limit of detection (LOD). PTR-MS, on the other hand, does not need preconcentration and gives much more reliable quantitative results then GCMS-SPME. The shortcoming of PTR-MS is that it cannot identify compounds with certainty. Hence SPME-GCMS and PTR-MS complement each other, each method having its particular advantages and disadvantages. Exhaled breath analysis is promising to become a future non-invasive lung cancer screening method. In order to proceed towards this goal, precise identification of compounds observed in exhaled breath of lung cancer patients is necessary. Comparison with compounds released from lung cancer cell cultures, and additional information on exhaled breath composition in other cancer forms will be important.

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  • Abstract

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    Figure 1

    Figure 1. Product ion distributions (percentages) as a function of the electric field (E/N) in H3O+ mode for (A) glycerin, (B) glycidol, (C) acetol, and (D) propylene glycol.

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    Figure 2

    Figure 2. Product ion distributions in H3O+ mode at 69 Td for acetaldehyde, acetol, glycidol, and glycerin.

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    Figure 3

    Figure 3. Analysis by fastGC-PTR-TOF-MS of a mixture of glycerin, glycidol, acetol, and propylene glycol in NO+ mode (E/N 16 Td).

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    Figure 4

    Figure 4. Product ion distributions in NO+ mode at 16 Td for acetaldehyde, acetol, glycidol, and glycerin.

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  • References

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      A review. Proton-transfer reaction mass spectrometry (PTR-MS) is a technique developed almost exclusively for the detection of gaseous org. compds. in air. Volatile org. compds. (VOCs) in air have both natural and anthropogenic sources. Natural sources include the emission of org. gases by living objects, both plants and animals. A well-known example, which is discussed later in this review, is the emission of a variety of gaseous org. compds. in the breath of animals, which are released from both the digestive system and the lungs. Plants are major sources of org. gases, as is the decay of dead animal and plant matter. Subsequent photochem. can add further compds. to the mixt. Consequently, even without contributions from humans, ambient air from the Earth's atm. would consist of a complex mixt. of VOCs.
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      Fadus Matthew C; Smith Tracy T; Squeglia Lindsay M
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      BACKGROUND: Electronic cigarettes (e-cigarettes) were first introduced in the U.S. market in 2006, with the more recent evolution of "pod-mod" e-cigarettes such as JUUL introduced in 2015. Although marketed as a smoking cessation tool, e-cigarettes are rarely used for this purpose in youth. This review aims to synthesize the literature regarding e-cigarette use among youth, and provides a resource for clinicians, educators, and families that helps answer commonly asked questions about e-cigarettes. METHODS: PubMed, Scopus, and PsycINFO search was performed using search terms "Electronic Nicotine Delivery Systems," "e cigarettes," "e-cigarettes," "electronic cigarettes," "vaping," "JUUL," "e-cigs," and "vape pens." Search results were filtered to only include those related to adolescents and young adults. RESULTS: E-cigarette use among youth is common, with rates of use increasing from 1.5% in 2011 to 20.8% in 2018. Pod mod devices such as JUUL have gained favor among youth for their sleek design, user-friendly function, desirable flavors, and ability to be used discreetly in places where smoking is forbidden. Adolescents are often uninformed about the constituents of e-cigarettes, and little is known about the long-term effects of e-cigarettes. Studies have suggested a "gateway" effect for combustible cigarettes and cannabis use. CONCLUSIONS: E-cigarette use is becoming increasingly common among youth, leading to a myriad of questions and concerns from providers, educators, and family members. More research is needed to determine the ultimate public health impact of e-cigarette use. The authors provide a summary table of frequently asked questions in order to help clarify these common concerns.
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      Abstr.: A suite of untargeted methods has been applied for the characterization of aerosol from the Tobacco Heating System 2.2 (THS2.2), a heated tobacco product developed by Philip Morris Products S.A. and commercialized under the brand name IQOS. A total of 529 chem. constituents, excluding water, glycerin, and nicotine, were present in the mainstream aerosol of THS2.2, generated by following the Health Canada intense smoking regimen, at concns. ≥ 100 ng/item. The majority were present in the particulate phase (n = 402), representing more than 80% of the total mass detd. by untargeted screening; a proportion were present in both particulate and gas-vapor phases (39 compds.). The identities for 80% of all chem. constituents (representing > 96% of the total detd. mass) were confirmed by the use of authentic anal. ref. materials. Despite the uncertainties that are recognized to be assocd. with aerosol-based untargeted approaches, the reported data remain indicative that the uncharacterized fraction of TPM generated by THS2.2 has been evaluated to the fullest practicable extent. To the best of our knowledge, this work represents the most comprehensive chem. characterization of a heated tobacco aerosol to date.
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      As e-cigarette popularity has increased, there is growing evidence to suggest that while they are highly likely to be considerably less harmful than cigarettes, their use is not free of risk to the user. There is therefore an ongoing need to characterize the chem. compn. of e-cigarette aerosols, as a starting point in characterizing risks assocd. with their use. This study examd. the chem. complexity of aerosols generated by an e-cigarette contg. one unflavored and three flavored e-liqs. A combination of targeted and untargeted chem. anal. approaches was used to examine the no. of compds. comprising the aerosol. Contributions of e-liq. flavors to aerosol complexity were investigated, and the sources of other aerosol constituents sought. Emissions of 98 aerosol toxicants were quantified and compared to those in smoke from a ref. tobacco cigarette generated under two different smoking regimes. Combined untargeted and targeted aerosol analyses identified between 94 and 139 compds. in the flavored aerosols, compared with an estd. 72-79 in the unflavored aerosol. This is significantly less complex (by 1-2 orders of magnitude) than the reported compn. of cigarette smoke. Combining both types of anal. identified 5-12 compds. over and above those found by untargeted anal. alone. Gravimetrically, 89-99% of the e-cigarette aerosol compn. was composed of glycerol, propylene glycol, water and nicotine, and around 3% comprised other, more minor, constituents. Comparable data for the Ky3R4F ref. tobacco cigarette pointed to 58-76% of cigarette smoke "tar" being composed of minor constituents. Levels of the targeted toxicants in the e-cigarette aerosols were significantly lower than those in cigarette smoke, with 68.5->99% redns. under ISO 3308 puffing conditions and 88.4->99% redns. under ISO 20778 (intense) conditions; redns. against the WHO TobReg 9 priority list were around 99%. These analyses showed that the e-cigarette aerosols contain fewer compds. and at significantly lower concns. than cigarette smoke. The chem. diversity of an e-cigarette aerosol is strongly impacted by the choice of e-liq. ingredients.
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      Evaluation of the Tobacco Heating System 2.2. Part 2: Chemical composition, genotoxicity, cytotoxicity, and physical properties of the aerosol
      Schaller, Jean-Pierre; Keller, Daniela; Poget, Laurent; Pratte, Pascal; Kaelin, Etienne; McHugh, Damian; Cudazzo, Gianluca; Smart, Daniel; Tricker, Anthony R.; Gautier, Lydia; Yerly, Michel; Reis Pires, Roger; Le Bouhellec, Soazig; Ghosh, David; Hofer, Iris; Garcia, Eva; Vanscheeuwijck, Patrick; Maeder, Serge
      Regulatory Toxicology and Pharmacology (2016), 81 (Suppl._2), S27-S47CODEN: RTOPDW; ISSN:0273-2300. (Elsevier Inc.)
      The chem. compn., in vitro genotoxicity, and cytotoxicity of the mainstream aerosol from the Tobacco Heating System 2.2 (THS2.2) were compared with those of the mainstream smoke from the 3R4F ref. cigarette. In contrast to the 3R4F, the tobacco plug in the THS2.2 is not burnt. The low operating temp. of THS2.2 caused distinct shifts in the aerosol compn. compared with 3R4F. This resulted in a redn. of more than 90% for the majority of the analyzed harmful and potentially harmful constituents (HPHCs), while the mass median aerodynamic diam. of the aerosol remained similar. A redn. of about 90% was also obsd. when comparing the cytotoxicity detd. by the neutral red uptake assay and the mutagenic potency in the mouse lymphoma assay. The THS2.2 aerosol was not mutagenic in the Ames assay. The chem. compn. of the THS2.2 aerosol was also evaluated under extreme climatic and puffing conditions. When generating the THS2.2 aerosol under "desert" or "tropical" conditions, the generation of HPHCs was not significantly modified. When using puffing regimens that were more intense than the std. Health Canada Intense (HCI) machine-smoking conditions, the HPHC yields remained lower than when smoking the 3R4F ref. cigarette with the HCI regimen.
    14. 14
      Shah, N. H.; Noe, M. R.; Agnew-Heard, K. A.; Pithawalla, Y. B.; Gardner, W. P.; Chakraborty, S.; McCutcheon, N.; Grisevich, H.; Hurst, T. J.; Morton, M. J. Non-Targeted Analysis Using Gas Chromatography-Mass Spectrometry for Evaluation of Chemical Composition of E-Vapor Products. Front. Chem. 2021, 9, 742854,  DOI: 10.3389/fchem.2021.742854
      14
      Non-targeted analysis using gas chromatography-mass spectrometry for evaluation of chemical composition of E-vapor products
      Shah, Niti H.; Noe, Michael R.; Agnew-Heard, Kimberly A.; Pithawalla, Yezdi B.; Gardner, William P.; Chakraborty, Saibal; McCutcheon, Nicholas; Grisevich, Hannah; Hurst, Thomas J.; Morton, Michael J.; Melvin, Matt S.; Miller, John H., IV.
      Frontiers in Chemistry (Lausanne, Switzerland) (2021), 9 (), 742854CODEN: FCLSAA; ISSN:2296-2646. (Frontiers Media S.A.)
      The Premarket Tobacco Product Applications (PMTA) guidance issued by the Food and Drug Administration for electronic nicotine delivery systems (ENDSs) recommends that in addn. to reporting harmful and potentially harmful constituents (HPHCs), manufacturers should evaluate these products for other chems. that could form during use and over time. Although e-vapor product aerosols are considerably less complex than mainstream smoke from cigarettes and heated tobacco product (HTP) aerosols, there are challenges with performing a comprehensive chem. characterization. Some of these challenges include the complexity of the e-liq. chem. compns., the variety of flavors used, and the aerosol collection efficiency of volatile and semi-volatile compds. generated from aerosols. In this study, a non-targeted anal. method was developed using gas chromatog.-mass spectrometry (GC-MS) that allows evaluation of volatile and semi-volatile compds. in e-liqs. and aerosols of e-vapor products. The method employed an automated data anal. workflow using Agilent MassHunter Unknowns Anal. software for mass spectral deconvolution, peak detection, and library searching and reporting. The automated process ensured data integrity and consistency of compd. identification with >99% of known compds. being identified using an inhouse custom mass spectral library. The custom library was created to aid in compd. identifications and includes over 1,100 unique mass spectral entries, of which 600 have been confirmed from ref. std. comparisons. The method validation included accuracy, precision, repeatability, limit of detection (LOD), and selectivity. The validation also demonstrated that this semi-quant. method provides estd. concns. with an accuracy ranging between 0.5- and 2.0-fold as compared to the actual values. The LOD threshold of 0.7 ppm was established based on instrument sensitivity and accuracy of the compds. identified. To demonstrate the application of this method, we share results from the comprehensive chem. profile of e-liqs. and aerosols collected from a marketed e-vapor product. Applying the data processing workflow developed here, 46 compds. were detected in the e-liq. formulation and 55 compds. in the aerosol sample. More than 50% of compds. reported have been confirmed with ref. stds. The profiling approach described in this publication is applicable to evaluating volatile and semi-volatile compds. in e-vapor products.
    15. 15
      Simonavicius, E.; McNeill, A.; Shahab, L.; Brose, L. S. Heat-not-burn tobacco products: a systematic literature review. Tob. Control. 2019, 28 (5), 582– 594,  DOI: 10.1136/tobaccocontrol-2018-054419
      There is no corresponding record for this reference.
    16. 16
      Farsalinos, K. E.; Gillman, G. Carbonyl Emissions in E-cigarette Aerosol: A Systematic Review and Methodological Considerations. Front. Physiol. 2018, 8, 1119,  DOI: 10.3389/fphys.2017.01119
      There is no corresponding record for this reference.
    17. 17
      Schwarz, K.; Filipiak, W.; Amann, A. Determining concentration patterns of volatile compounds in exhaled breath by PTR-MS. J. Breath Res. 2009, 3 (2), 027002,  DOI: 10.1088/1752-7155/3/2/027002
      There is no corresponding record for this reference.
    18. 18
      Abbott, P. J.; Renwick, A. G.; Sipes, I. G. Safety evaluation of certain food additives and contaminants. Aliphatic acyclic diols, triols, and related substances. World Health Organization (WHO) Food Additives Series 48; World Health Organization: Geneva, 2002.
      There is no corresponding record for this reference.
    19. 19
      Younes, M.; Aggett, P.; Aguilar, F.; Crebelli, R.; Dusemund, B.; Filipič, M.; Frutos, M. J.; Galtier, P.; Gott, D.; Gundert-Remy, U. Re-evaluation of propane-1,2-diol (E 1520) as a food additive. EFSA J. 2018, 16 (4), e05235  DOI: 10.2903/j.efsa.2018.5235
      There is no corresponding record for this reference.
    20. 20
      Popek, E. Environmental Chemical Pollutants. Sampling and Analysis of Environmental Chemical Pollutants; Elsevier, 2018; pp 13– 69.
      There is no corresponding record for this reference.
    21. 21
      International Agency for Research on Cancer (IARC). Agents Classified by the IARC Monographs. IARC monographs on the identification of carcinogenic hazards to humans; IARC Press and World Health Organization, 2020; Vols. 1–127.
      There is no corresponding record for this reference.
    22. 22
      Harmful and potentially harmful constituents in tobacco products and tobacco smoke; established list. US. Department of Health and Human Services Food and Drug Administration Center for Tobacco Products, 2012; https://www.federalregister.gov/documents/2012/04/03/2012-7727/harmful-and-potentially-harmful-constituents-in-tobacco-products-and-tobacco-smoke-established-list.
      There is no corresponding record for this reference.
    23. 23
      Premarket Tobacco Product Applications for Electronic Nicotine Delivery Systems. Guidance for Industry; U.S. Department of Health and Human Services Food and Drug Administration Center for Tobacco Products, 2019; https://www.fda.gov/media/127853/download.
      There is no corresponding record for this reference.
    24. 24
      Nimlos, M. R.; Blanksby, S. J.; Qian, X.; Himmel, M. E.; Johnson, D. K. Mechanisms of Glycerol Dehydration. J. Phys. Chem. A 2006, 110 (18), 6145– 6156,  DOI: 10.1021/jp060597q
      24
      Mechanisms of Glycerol Dehydration
      Nimlos, Mark R.; Blanksby, Stephen J.; Qian, Xianghong; Himmel, Michael E.; Johnson, David K.
      Journal of Physical Chemistry A (2006), 110 (18), 6145-6156CODEN: JPCAFH; ISSN:1089-5639. (American Chemical Society)
      Dehydration of neutral and protonated glycerol was investigated using quantum mech. calcns. (CBS-QB3). Calcns. on neutral glycerol show that there is a high barrier for simple 1,2-dehydration, Ea = 70.9 kcal mol-1, which is lowered to 65.2 kcal mol-1 for pericyclic 1,3-dehydration. In contrast, the barriers for dehydration of protonated glycerol are much lower. Dehydration mechanisms involving hydride transfer, pinacol rearrangement, or substitution reactions have barriers between 20 and 25 kcal mol-1. Loss of water from glycerol via substitution results in either oxirane or oxetane intermediates, which can interconvert over a low barrier. Subsequent decompn. of these intermediates proceeds via either a second dehydration step or loss of formaldehyde. The computed mechanisms for decompn. of protonated glycerol are supported by the gas-phase fragmentation of protonated glycerol obsd. using a triple-quadrupole mass spectrometer.
    25. 25
      Hegen, O.; Salazar Gómez, J. I.; Schlögl, R.; Ruland, H. The potential of NO+ and O2+• in switchable reagent ion proton transfer reaction time-of-flight mass spectrometry. Mass Spectrom. Rev. 2023, 42, 1688– 1726,  DOI: 10.1002/mas.21770
      There is no corresponding record for this reference.
    26. 26
      Bhatia, M.; Manini, N.; Biasioli, F.; Cappellin, L. Theoretical Investigation of Charge Transfer from NO+ and O2+ Ions to Wine-Related Volatile Compounds for Mass Spectrometry. J. Am. Soc. Mass Spectrom. 2022, 33 (2), 251– 264,  DOI: 10.1021/jasms.1c00253
      There is no corresponding record for this reference.
    27. 27
      Koss, A. R.; Warneke, C.; Yuan, B.; Coggon, M. M.; Veres, P. R.; de Gouw, J. A. Evaluation of NO+ reagent ion chemistry for online measurements of atmospheric volatile organic compounds. Atmos. Meas. Technol. 2016, 9 (7), 2909– 2925,  DOI: 10.5194/amt-9-2909-2016
      There is no corresponding record for this reference.
    28. 28
      Karl, T.; Hansel, A.; Cappellin, L.; Kaser, L.; Herdlinger-Blatt, I.; Jud, W. Selective measurements of isoprene and 2-methyl-3-buten-2-ol based on NO+ ionization mass spectrometry. Atmos. Chem. Phys. 2012, 12 (24), 11877– 11884,  DOI: 10.5194/acp-12-11877-2012
      There is no corresponding record for this reference.
    29. 29
      Zaytsev, A.; Breitenlechner, M.; Koss, A. R.; Lim, C. Y.; Rowe, J. C.; Kroll, J. H.; Keutsch, F. N. Using collision-induced dissociation to constrain sensitivity of ammonia chemical ionization mass spectrometry (NH4+ CIMS) to oxygenated volatile organic compounds. Atmos. Meas. Technol. 2019, 12 (3), 1861– 1870,  DOI: 10.5194/amt-12-1861-2019
      29
      Using collision-induced dissociation to constrain sensitivity of ammonia chemical ionization mass spectrometry (NHC+4 CIMS) to oxygenated volatile organic compounds
      Zaytsev, Alexander; Breitenlechner, Martin; Koss, Abigail R.; Lim, Christopher Y.; Rowe, James C.; Kroll, Jesse H.; Keutsch, Frank N.
      Atmospheric Measurement Techniques (2019), 12 (3), 1861-1870CODEN: AMTTC2; ISSN:1867-8548. (Copernicus Publications)
      Chem. ionization mass spectrometry (CIMS) instruments routinely detect hundreds of oxidized org. compds. in the atm. A major limitation of these instruments is the uncertainty in their sensitivity to many of the detected ions. We describe the development of a new high-resoln. time-of-flight chem. ionization mass spectrometer that operates in one of two ionization modes: using either ammonium ion ligand-switching reactions such as for NH4+ CIMS or proton transfer reactions such as for proton-transfer-reaction mass spectrometer (PTR-MS). Switching between the modes can be done within 2 min. The NH+4 CIMS mode of the new instrument has sensitivities of up to 67000 dcps ppbv-1 (duty-cycle-cor. ion counts per s per part per billion by vol.) and detection limits between 1 and 60 pptv at 2σ for a 1 s integration time for numerous oxygenated volatile org. compds. We present a mass spectrometric voltage scanning procedure based on collision-induced dissocn. that allows us to det. the stability of ammonium-org. ions detected by the NH4+ CIMS instrument. Using this procedure, we can effectively constrain the sensitivity of the ammonia chem. ionization mass spectrometer to a wide range of detected oxidized volatile org. compds. for which no calibration stds. exist. We demonstrate the application of this procedure by quantifying the compn. of secondary org. aerosols in a series of lab. expts.
    30. 30
      Malásková, M.; Henderson, B.; Chellayah, P. D.; Ruzsanyi, V.; Mochalski, P.; Cristescu, S. M.; Mayhew, C. A. Proton transfer reaction time-of-flight mass spectrometric measurements of volatile compounds contained in peppermint oil capsules of relevance to real-time pharmacokinetic breath studies. J. Breath Res. 2019, 13 (4), 046009,  DOI: 10.1088/1752-7163/ab26e2
      There is no corresponding record for this reference.
    31. 31
      Kari, E.; Miettinen, P.; Yli-Pirilä, P.; Virtanen, A.; Faiola, C. L. PTR-ToF-MS product ion distributions and humidity-dependence of biogenic volatile organic compounds. Int. J. Mass Spectrom. 2018, 430, 87– 97,  DOI: 10.1016/j.ijms.2018.05.003
      31
      PTR-ToF-MS product ion distributions and humidity-dependence of biogenic volatile organic compounds
      Kari, Eetu; Miettinen, Pasi; Yli-Pirila, Pasi; Virtanen, Annele; Faiola, Celia L.
      International Journal of Mass Spectrometry (2018), 430 (), 87-97CODEN: IMSPF8; ISSN:1387-3806. (Elsevier B.V.)
      Quant. proton-transfer-reaction mass spectrometer (PTR-MS) measurements of ambient volatile org. compds. (VOCs) require proper calibration procedures. In particular, compd. product ion distribution and humidity-dependent responses must be characterized. In this study, we generated twelve gas-phase terpenoid stds. using a dynamic diln. system to calibrate the PTR-MS with time-of-flight mass spectrometer (PTR-ToF-MS): six monoterpenes, two monoterpene derivs., and four sesquiterpenes. The humidity-dependent response was characterized for three terpenoid compds. to compare different mol. structures: α-pinene, δ-limonene, and longifolene. We provide the first comprehensive summary of PTR-ToF-MS product ion distributions for twelve common biogenic volatile org. compds. using two different reduced elec. field (E/N) values, 80 Td and 130 Td. Results demonstrated that neglecting to correct for individual product ion distributions of different terpenoid isomers can result in an error of up to 26% for reported mixing ratios. δ-Limonene and longifolene exhibited a small humidity-dependent response in the PTR-ToF-MS, but this did not contribute significantly to the overall measurement error. These results will improve quantification of commonly-measured biogenic volatile org. compd. emissions and chem. in the atm.
    32. 32
      Maleknia, S. D.; Bell, T. L.; Adams, M. A. PTR-MS analysis of reference and plant-emitted volatile organic compounds. Int. J. Mass Spectrom. 2007, 262 (3), 203– 210,  DOI: 10.1016/j.ijms.2006.11.010
      There is no corresponding record for this reference.
    33. 33
      Pagonis, D.; Sekimoto, K.; de Gouw, J. A Library of Proton-Transfer Reactions of H3O+ Ions Used for Trace Gas Detection. J. Am. Soc. Mass Spectrom. 2019, 30 (7), 1330– 1335,  DOI: 10.1007/s13361-019-02209-3
      33
      A Library of Proton-Transfer Reactions of H3O+ Ions Used for Trace Gas Detection
      Pagonis, Demetrios; Sekimoto, Kanako; de Gouw, Joost
      Journal of the American Society for Mass Spectrometry (2019), 30 (7), 1330-1335CODEN: JAMSEF; ISSN:1044-0305. (Springer)
      We have collected data on the proton-transfer reactions with H3O+ ions for trace gas detection into an online and publicly available library. The library allows users of proton-transfer-reaction mass spectrometry (PTR-MS) and selected-ion flow-tube mass spectrometry (SIFT-MS) to look up at which m/z a trace gas of interest is detected. Vice versa, the library also allows looking up what trace gas may have been responsible for a product ion detected in PTR-MS and SIFT-MS. Finally, the library may serve as a dataset for further research on calcg. instrument sensitivity and product-ion fragmentation, improving identification and quantification of newly detectable compds. as advances in instrumentation continue. To demonstrate the utility of the library, we present a brief anal. of product-ion fragmentation. We show that oxygenated org. compds. exhibit trends in neutral loss according to their functionality, and that on av. neutral losses decrease the carbon no. and increase the extent of unsatn. of product ions. [Figure not available: see fulltext.].
    34. 34
      Mochalski, P.; Unterkofler, K.; Španěl, P.; Smith, D.; Amann, A. Product ion distributions for the reactions of NO+ with some physiologically significant aldehydes obtained using a SRI-TOF-MS instrument. Int. J. Mass Spectrom. 2014, 363, 23– 31,  DOI: 10.1016/j.ijms.2014.02.016
      34
      Product ion distributions for the reactions of NO+ with some physiologically significant aldehydes obtained using a SRI-TOF-MS instrument
      Mochalski, Pawel; Unterkofler, Karl; Spanel, Patrik; Smith, David; Amann, Anton
      International Journal of Mass Spectrometry (2014), 363 (), 23-31CODEN: IMSPF8; ISSN:1387-3806. (Elsevier B.V.)
      Product ion distributions for the reactions of NO+ with 22 aldehydes involved in human physiol. have been detd. under the prevailing conditions of a selective reagent ionization time of flight mass spectrometryat an E/N in the flow/drift tube reactor of 130 Td. The chosen aldehydes were fourteen alkanals (the C2-C11 n-alkanals, 2-Me propanal, 2-Me butanal, 3-Me butanal, and 2-Et hexanal), six alkenals (2-propenal, 2-Me 2-propenal, 2-butenal, 3-Me 2-butenal, 2-Me 2-butenal, and 2-undecenal), benzaldehyde, and furfural. The product ion fragmentations patterns were detd. for both dry air and humid air (3.5% abs. humidity) used as the matrix buffer/carrier gas in the drift tube of the SRI-TOF-MS instrument. Small fractions of the adduct ion, NO+M, were also seen for some of the unsatd. alkenals, in particular 2-undecenal, and heterocyclic furfural for which the major reactive channel was non-dissociative charge transfer generating the M+ parent ion. All of the reactions resulted in partial fragmentation of the aldehyde mols. generating hydrocarbon ions; specifically, the alkanal reactions resulted in multiple product ions, whereas, the alkenals reactions produced only two or three product ions, dissocn. of the nascent excited product ion occurring preferentially at the 2-position. The findings of this study are of particular importance for data interpretation in studies of aldehydes reactions employing SRI-TOF-MS in the NO+ mode.
    35. 35
      Yang, Y.; Luo, H.; Liu, R.; Li, G.; Yu, Y.; An, T. The exposure risk of typical VOCs to the human beings via inhalation based on the respiratory deposition rates by proton transfer reaction-time of flight-mass spectrometer. Ecotoxicol. Environ. Saf. 2020, 197, 110615  DOI: 10.1016/j.ecoenv.2020.110615
      There is no corresponding record for this reference.
    36. 36
      Veres, P. R.; Faber, P.; Drewnick, F.; Lelieveld, J.; Williams, J. Anthropogenic sources of VOC in a football stadium: Assessing human emissions in the atmosphere. Atmos. Environ. 2013, 77, 1052– 1059,  DOI: 10.1016/j.atmosenv.2013.05.076
      36
      Anthropogenic sources of VOC in a football stadium: Assessing human emissions in the atmosphere
      Veres, Patrick R.; Faber, Peter; Drewnick, Frank; Lelieveld, Jos; Williams, Jonathan
      Atmospheric Environment (2013), 77 (), 1052-1059CODEN: AENVEQ; ISSN:1352-2310. (Elsevier Ltd.)
      Measurements of gas-phase volatile org. compds. (VOCs), aerosol compn., CO2, and O3 were made inside Coface Arena in Mainz, Germany (49°59'3''N, 8°13'27''E) during a football match on Apr. 20 2012. The VOC measurements were performed with a proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS). Obsd. VOCs could be classified into several distinct source categories including (1) human respiration/breath, (2) ozonolysis of skin oils, and (3) cigarette smoke/combustion. We present a detailed discussion on the scale and potential impacts of VOCs emitted as a result of these sources and their contributions on local and larger scales. Human emissions of VOCs have a negligible contribution to the global atm. budget (∼1% or less) for all those quantified in this study. However, fluxes as high as 0.02 g m-2 h-1 and 2 × 10-4 g m-2 h-1, for ethanol and acetone resp. are obsd., suggesting the potential for significant impact on local air chem. and perhaps regional scales. This study suggests that even in outdoor environments, situations exist where VOCs emitted as a result of human presence and activity are an important component of local air chem.
    37. 37
      Sukul, P.; Schubert, J. K.; Kamysek, S.; Trefz, P.; Miekisch, W. Applied upper-airway resistance instantly affects breath components: a unique insight into pulmonary medicine. J. Breath Res. 2017, 11 (4), 047108  DOI: 10.1088/1752-7163/aa8d86
      There is no corresponding record for this reference.
    38. 38
      Williams, J.; Stönner, C.; Wicker, J.; Krauter, N.; Derstroff, B.; Bourtsoukidis, E.; Klüpfel, T.; Kramer, S. Cinema audiences reproducibly vary the chemical composition of air during films, by broadcasting scene specific emissions on breath. Sci. Rep. 2016, 6 (1), 25464,  DOI: 10.1038/srep25464
      There is no corresponding record for this reference.
    39. 39
      Materić, D.; Lanza, M.; Sulzer, P.; Herbig, J.; Bruhn, D.; Turner, C.; Mason, N.; Gauci, V. Monoterpene separation by coupling proton transfer reaction time-of-flight mass spectrometry with fastGC. Anal. Bioanal. Chem. 2015, 407 (25), 7757– 7763,  DOI: 10.1007/s00216-015-8942-5
      There is no corresponding record for this reference.
    40. 40
      Guo, X.; Ehindero, T.; Lau, C.; Zhao, R. Impact of glycol-based solvents on indoor air quality─Artificial fog and exposure pathways of formaldehyde and various carbonyls. Indoor Air. 2022, 32 (9), e13100  DOI: 10.1111/ina.13100
      There is no corresponding record for this reference.
    41. 41
      Becker, L. C.; Bergfeld, W. F.; Belsito, D. V.; Hill, R. A.; Klaassen, C. D.; Liebler, D. C.; Marks, J. G.; Shank, R. C.; Slaga, T. J.; Snyder, P. W. Safety Assessment of Glycerin as Used in Cosmetics. Int. J. Toxicol. 2019, 38, 6S– 22S,  DOI: 10.1177/1091581819883820
      There is no corresponding record for this reference.
    42. 42
      Bajtarevic, A.; Ager, C.; Pienz, M.; Klieber, M.; Schwarz, K.; Ligor, M.; Ligor, T.; Filipiak, W.; Denz, H.; Fiegl, M. Noninvasive detection of lung cancer by analysis of exhaled breath. BMC Cancer. 2009, 9 (1), 348,  DOI: 10.1186/1471-2407-9-348
      42
      Noninvasive detection of lung cancer by analysis of exhaled breath
      Bajtarevic Amel; Ager Clemens; Pienz Martin; Klieber Martin; Schwarz Konrad; Ligor Magdalena; Ligor Tomasz; Filipiak Wojciech; Denz Hubert; Fiegl Michael; Hilbe Wolfgang; Weiss Wolfgang; Lukas Peter; Jamnig Herbert; Hackl Martin; Haidenberger Alfred; Buszewski Boguslaw; Miekisch Wolfram; Schubert Jochen; Amann Anton
      BMC cancer (2009), 9 (), 348 ISSN:.
      BACKGROUND: Lung cancer is one of the leading causes of death in Europe and the western world. At present, diagnosis of lung cancer very often happens late in the course of the disease since inexpensive, non-invasive and sufficiently sensitive and specific screening methods are not available. Even though the CT diagnostic methods are good, it must be assured that "screening benefit outweighs risk, across all individuals screened, not only those with lung cancer". An early non-invasive diagnosis of lung cancer would improve prognosis and enlarge treatment options. Analysis of exhaled breath would be an ideal diagnostic method, since it is non-invasive and totally painless. METHODS: Exhaled breath and inhaled room air samples were analyzed using proton transfer reaction mass spectrometry (PTR-MS) and solid phase microextraction with subsequent gas chromatography mass spectrometry (SPME-GCMS). For the PTR-MS measurements, 220 lung cancer patients and 441 healthy volunteers were recruited. For the GCMS measurements, we collected samples from 65 lung cancer patients and 31 healthy volunteers. Lung cancer patients were in different disease stages and under treatment with different regimes. Mixed expiratory and indoor air samples were collected in Tedlar bags, and either analyzed directly by PTR-MS or transferred to glass vials and analyzed by gas chromatography mass spectrometry (GCMS). Only those measurements of compounds were considered, which showed at least a 15% higher concentration in exhaled breath than in indoor air. Compounds related to smoking behavior such as acetonitrile and benzene were not used to differentiate between lung cancer patients and healthy volunteers. RESULTS: Isoprene, acetone and methanol are compounds appearing in everybody's exhaled breath. These three main compounds of exhaled breath show slightly lower concentrations in lung cancer patients as compared to healthy volunteers (p < 0.01 for isoprene and acetone, p = 0.011 for methanol; PTR-MS measurements). A comparison of the GCMS-results of 65 lung cancer patients with those of 31 healthy volunteers revealed differences in concentration for more than 50 compounds. Sensitivity for detection of lung cancer patients based on presence of (one of) 4 different compounds not arising in exhaled breath of healthy volunteers was 52% with a specificity of 100%. Using 15 (or 21) different compounds for distinction, sensitivity was 71% (80%) with a specificity of 100%. Potential marker compounds are alcohols, aldehydes, ketones and hydrocarbons. CONCLUSION: GCMS-SPME is a relatively insensitive method. Hence compounds not appearing in exhaled breath of healthy volunteers may be below the limit of detection (LOD). PTR-MS, on the other hand, does not need preconcentration and gives much more reliable quantitative results then GCMS-SPME. The shortcoming of PTR-MS is that it cannot identify compounds with certainty. Hence SPME-GCMS and PTR-MS complement each other, each method having its particular advantages and disadvantages. Exhaled breath analysis is promising to become a future non-invasive lung cancer screening method. In order to proceed towards this goal, precise identification of compounds observed in exhaled breath of lung cancer patients is necessary. Comparison with compounds released from lung cancer cell cultures, and additional information on exhaled breath composition in other cancer forms will be important.

  • Supporting Information

    Supporting Information

    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/jasms.4c00062.

    • Table S1, Concentration ranges for glycerin, acetol, glycidol, and acetaldehyde and propylene glycol and acetone for a popular heated tobacco product.; Table S2, summary of theoretical and experimental exact masses and mass accuracies for ions of compounds under investigation; Tables S3−S11, ratio between concentration levels of the compounds under investigation; Tables S12−S17, influence of ion 1 on the analysis of compounds under investigation; Tables S18−S20, influence of ion 2 on the analysis of compounds under investigation; Table S21-S23, influence of ion 3 on the analysis of compounds under investigation; Figures S1−S4 and S6−S15, calibration plots of compounds under investigation under different ionization modes; Figure S5, mass spectrum of ion 1 in mixture 1 (PDF)


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