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Characterization of Natural and Affected Environments

Molecular Characterization of Cloud Water Samples Collected at the puy de Dôme (France) by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Angelica Bianco, Laurent Deguillaume, Mickaël Vaïtilingom, Edith Nicol, Jean-Luc Baray, Nadine Chaumerliac, and Maxime Cyril Bridoux Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b01964 • Publication Date (Web): 27 Jul 2018 Downloaded from http://pubs.acs.org on July 28, 2018

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Environmental Science & Technology

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Molecular characterization of cloud water

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samples collected at the puy de Dôme (France)

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by Fourier Transform Ion Cyclotron Resonance

4

Mass Spectrometry

5

Angelica Bianco1,2, Laurent Deguillaume1, Mickaël Vaïtilingom1,4, Edith Nicol3, Jean-Luc

6

Baray1, Nadine Chaumerliac1, Maxime Bridoux2*

7

1

8

Clermont-Ferrand, France.

9

2

CEA, DAM, DIF, F-91297 Arpajon, France

10

3

Laboratoire de Chimie Moléculaire (LCM), CNRS, Ecole Polytechnique, Université Paris-Saclay,

11

91128 Palaiseau, France

12

4

13

Université des Antilles, 97110 Point à Pitre, France.

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* : Corresponding author : [email protected]

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KEYWORDS

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Cloud, organic matter, Ultra-high-resolution mass spectrometry, FT-ICR, atmospheric

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chemistry

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Abstract

19

Cloud droplets contain dynamic and complex pools of highly heterogeneous organic matter,

20

resulting from the dissolution of both water soluble organic carbon in atmospheric aerosol

21

particles and gas-phase soluble species, and are constantly impacted by chemical,

22

photochemical and biological transformations. Cloud samples from two summer events,

23

characterized by different air masses and physicochemical properties, were collected at the

Laboratoire de Météorologie Physique (LaMP), Université Clermont Auvergne (UCA), 63000

now at Laboratoire de Recherche en Géosciences et Energies (LaRGE), Departement of Physics,

1 ACS Paragon Plus Environment


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puy de Dôme station in France, concentrated on a strata-X solid-phase extraction (SPE)

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cartridge and directly infused using electrospray ionization in the negative mode (ESI-)

26

coupled with ultrahigh-resolution mass spectrometry (UHRMS). A significantly higher

27

number (n = 5258) of monoisotopic molecular formulas, assigned to CHO, CHNO, CHSO

28

and CHNSO, were identified in the cloud sample whose air mass had passed over the highly

29

urbanized Paris region (J1) compared to the cloud sample whose air mass had passed over

30

remote areas (n = 2896; J2). Van Krevelen diagrams revealed that lignins/CRAM-like,

31

aliphatics/proteins-like and lipids-like compounds were the most abundant classes in both

32

samples. Comparison of our results with previously published datasets on atmospheric

33

aqueous media indicated that the average O/C ratios reported in this work (0.37) are similar to

34

those reported for fog water and for biogenic aerosols but are lower than the values measured

35

for aerosols sampled in the atmosphere and for aerosols produced artificially in environmental

36

chambers.

37


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Table of Contents (TOC)/Abstract Art

39 40



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1. Introduction

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Organic compounds are released into the atmosphere from both natural and anthropogenic

43

sources, such as volatile organic compounds (VOCs) and primary organic aerosols (POAs).

44

These compounds have substantial effects on air quality, atmospheric chemistry, and climate

45

forcing. Over the past decade, the molecular composition of atmospheric organic matter (OM)

46

and the modification of OM via the multiphasic processes of atmospheric aging have been

47

intensively studied

48

aqueous media was rather limited to rain, dew, fog and deliquescent aerosols due to the

49

inherent difficulty of sampling clouds. Cloud droplets can be composed of a myriad of

50

organic compounds that are efficiently transferred from (i) the gas phase and (ii) from the

51

soluble fraction of aerosol particles that also serve as cloud condensation nuclei (CCN). These

52

organic compounds are subsequently modified by chemical and biological transformations

53

occurring during the lifetime of the cloud 5,6. Cloud studies have been focused on the analysis

54

of the composition, structure, sources and processing of the organic matter 7. Efforts were

55

made to understand how in-cloud processes affect the physico-chemical properties of aerosol

56

particles 8,9 and how they contribute to secondary organic aerosol (SOA) formation 10.

57

In situ measurements exhibit a high variability of dissolved organic matter (DOM), with

58

concentrations ranging between 100 and 200 mgC L-1 for polluted sampling sites

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between 1 to 20 mgC L-1 for remote sites 12,13. Targeted chemical analyses have revealed the

60

presence of many low molecular weight compounds that are believed to be transferred from

61

the gas phase, including small carboxylic acids such as formic and acetic acids 14; carbonyls

62

such as formaldehyde, glyoxal and methylglyoxal

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addition, many other compounds have also been detected in clouds, including di-carboxylic

64

acids that originate from aerosol particles 19 or from aqueous phase reactivity 20, and aromatic

65

pollutants such as polycyclic aromatic hydrocarbons (PAHs)

66

also detected in cloud water, representing up to 9% of the dissolved organic carbon pool (in

1–4

. However, the physicochemical characterization of atmospheric

12,15,16

; phenol; and nitrophenol

11

and

17,18

. In

21

. Recently, amino acids were


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mass, mgC L-1)

22

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composed of relatively high molecular weight organic compounds that can contain a

69

substantial fraction of heteroatoms (N, S, O), such as the so-called humic-like substances

70

(HULIS) found in aerosols 23–25.

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Most of these studies focused on individual compounds or functional groups using

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chromatographic separation schemes and voltammetric and spectroscopic techniques. While

73

informative, these methods only target a small portion of the DOM pool in clouds (only

74

approximately 20% of the DOM pool has been characterized to date 22). Different ionization

75

sources can be coupled to Fourier-transform ion cyclotron resonance (FT-ICR) mass

76

spectrometry (MS) to characterize the individual molecular formulas of organic compounds

77

within complex mixtures. Atmospheric pressure chemical ionization (APIC) tends to ionize

78

less polar and smaller molecules, while atmospheric pressure photoionization (APPI)

79

preferentially ionizes aromatics and other molecules with π electrons26. ESI(-) is a soft

80

ionization technique and the most widely used for polar thermolabile compounds. It can be

81

used for bio-derived molecules of low and high molecular weight like peptides, proteins,

82

carbohydrates, lipids and DNA fragments. Indeed, FT-ICR MS has been successfully used to

83

investigate the organic composition of major atmospheric aqueous media, such as rain water

84

samples 27–29, fog water samples 30,31, and aerosols 26,32,33, and has been successfully employed

85

to compare natural and laboratory-generated SOAs

86

focused on DOM in cloud samples; these studies were conducted on samples collected in the

87

Storm Peak Laboratory (SPL) (Colorado, USA)

88

USA) 36.

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Herein, we present the negative mode FT-ICR MS characterization of two cloud samples

90

collected at the puy de Dôme station (PUY) (France) with respect to their physicochemical

91

parameters to demonstrate that cloud DOM composition contains integral information on

92

emission sources and processes. Our results are compared to previous studies conducted on

. In addition, a large proportion of the organic matter in clouds is also

35

34

. However, only two studies have

and at Whiteface Mountain (New York,



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other atmospheric aqueous media. This approach provides a means to study at the molecular

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level a large, otherwise inaccessible proportion of the DOM in clouds and to characterize the

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heterogeneity of the DOM.

96

2

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The PUY station belongs to the atmospheric survey networks EMEP (the European

98

Monitoring and Evaluation Program), GAW (Global Atmosphere Watch), and ACTRIS

99

(Aerosols, Clouds, and Trace gases Research Infrastructure). Cloud water sampling was

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performed by using a dynamic one-stage cloud water impactor (cut off diameter of

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approximately 7 µm 37,38). The aluminum impactor was cleaned and sterilized by autoclaving

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before and after each cloud collection. Samples were collected in sterilized bottles and cloud

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water was filtered using a 0.20-µm nylon filter within 10 minutes after sampling to eliminate

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microorganisms and particles. Hydrogen peroxide concentration and pH were determined

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immediately after sampling. An aliquot of each sample was frozen on site and stored in

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appropriate vessels at -25°C until these samples were analyzed by mass spectrometry (FT-

107

ICR MS) and ion chromatography (IC). The total organic carbon (TOC), iron, and

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formaldehyde content in the frozen samples were also quantified. More details about the

109

physicochemical analysis are reported in the Supplementary Information (S(1)).

110

Cloud water samples were prepared for analysis by ultrahigh-resolution FT-ICR mass

111

spectrometry by using the method described by Zhao et al. 35 (SI–S(2)). High-resolution mass

112

spectrometric analysis was performed using an FT-ICR mass spectrometer (Bruker) equipped

113

with an electrospray ionization (ESI, Bruker) source set in negative ionization, as detailed in

114

SI–S(3). FT-ICR mass spectra were processed using Composer software (Sierra Analytics,

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Modesto, CA) using the parameters reported in SI–S(3).

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The principal component analysis (PCA) was performed with XLSTAT, an add-on package

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for Microsoft Excel

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physicochemical properties of the cloud samples (pH and the concentrations of inorganic

Materials and methods

39

. In this study, samples were classified by considering the


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ions) as variables, following the method described by Deguillaume et al.

; further

120

information is provided in SI–S(4).

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The air mass origin for each event was calculated using a 96-h back-trajectory obtained by

122

using the LACYTRAJ model at an interception height of 1465 m a.s.l. (above sea level),

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corresponding to the PUY summit. Back-trajectories indicate that the air masses passed over

124

seas and lands. PCA/HCA were then performed on chemical observations to classify the air

125

masses.

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3

Results

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3.1

Air mass characteristics

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Cloud water samples were collected on June 1st, 2016 and July 2nd, 2016 at the top of the PUY

129

Mountain. The June-1st sample (J1) and July-2nd sample (J2) were collected between 2:50 pm

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and 7:20 pm and between 2:00 and 8:00 am, respectively.

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The PUY summit can be in the free troposphere or in the boundary mixing layer depending on

132

the time of the year (seasonal variation) and of the day (diurnal variation). The interpolation

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on the boundary layer height on trajectory points calculated with the model LACYTRAJ

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confirm that both samples were collected in free troposphere conditions SI–S(5). The air mass

135

corresponding to J2 crossed the boundary layer more than 96 h before arriving to PUY. The

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air mass corresponding to sample J1 crossed the boundary layer 18 hours before arriving to

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PUY, as is consistent with a higher influence of local emissions (Figure S1a and b).

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Back-trajectory plot analysis (Figure S2) shows air masses coming from the north for J1 and

139

from the west for J2. Table S1 presents the physicochemical characterization of the two

140

samples. The PCA/HCA statistical analysis classifies J1 as “marine” and J2 as “continental”;

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the back-trajectory plots were used to evaluate this statistical classification (Figure S2). The

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concentration of inorganic ions in sample J1 is relatively low, resulting in a “marine”

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classification using the PCA/HCA statistical analysis. This can be potentially explained by the

144

meteorological conditions during the month of May 2016, when the conditions were

40



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extremely rainy, particularly on May 30th and 31st, and were characterized by low

146

temperatures (lower than 14°C). However, the cloud sample surprisingly exhibited a

147

relatively low pH value (approx. 4.6). In fact, the back-trajectory plot indicates that air masses

148

passed over the city of Paris before reaching PUY summit. The other sample J2 is classified

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as “continental” by PCA/HCA, mainly due to the high levels of NH4+ ions. Such high

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contents are typically associated with land-based emissions of NH3, which increase during the

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summer 41 (temperatures were between 23 and 26°C on 31/06 and 01/07).

152

3.2

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Molecular formulas of the form CcHhNnOoSs were assigned to the negative-ion FT-ICR mass

154

spectra of the organic matter extracted from the cloud water samples SI‒S(6). Figure S3

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shows the reconstructed mass spectrum of the monoisotopic molecular formulas assigned to

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sample J1 (a) and J2 (b) after subtraction of the blank. The mass spectra for cloud water

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samples are complex, with a high number of isobaric ions. An example of the isobaric

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complexity, exhibiting as many as 27 molecular formulas within 0.20 a.m.u., is shown in the

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inset of Figure S3a. Overall, the mass range of atmospheric DOM is similar to the HULIS

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components presented by Krivácsy et al. 42, with a primary maximum at 250 Da and two other

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local maxima observed at 350 and 500 Da. This trend is particularly clear for J1. After blank

162

subtraction and filtering, a relatively high number of molecular formulas were assigned (5258

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and 2896 for J1 and J2, respectively). The average mass-accuracy measurement was better

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than 30 ± 880 ppb (Figure S4).

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The highest relative abundance covers a different range for the two samples: J1 presents

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higher relative abundance between 200 and 450 Da, while J2 presents higher relative

167

abundance between 100 and 400 Da. The assigned molecular formulas were grouped into the

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following four subgroups based on elemental composition: compounds containing only C, H

169

and O (CHO); compounds containing C, H, N and O (CHNO); compounds containing only C,

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H, O and S (CHOS); and compounds containing C, H, N, O and S (CHNOS). The CHO

Molecular characterization of DOM in samples J1 and J2


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compounds (1327 and 2897 molecular formulas in J1 and J2, respectively) account for 25 and

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35% of the total number of assigned molecular formulas for the two cloud samples J1 and J2,

173

respectively.

174

Kendrick mass defect (KMD) analysis was used to assign molecular formulas to limit the

175

number of possible formula assignments. Thus, all of the assigned molecular formulas belong

176

to a CH2 homologous series, easily identifiable in the Kendrick mass plot (Figures S5 a & b),

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and the high-intensity ions present a clear pattern of 14 Da mass differences. The main

178

features of the Kendrick plots are described in SI–S(7).

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Table 1 reports the average composition properties of atmospheric DOM in the two cloud

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samples, including O/C, H/C and double-bond equivalent (DBE). The aromaticity index (AI)

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was evaluated for each elemental group, and the calculation of the AI is described in SI–S(8). J1 Number frequency Relative percentage O/C O/Cw H/C H/Cw DBE DBEw AI = 0 0 < AI < 0.5 0.5 ≤ AI < 0.67 AI ≥ 0.67 J2 Number frequency Relative percentage O/C O/Cw H/C H/Cw DBE DBEw AI = 0 0 < AI < 0.5 0.5 ≤ AI < 0.67 AI ≥ 0.67

All 5258

CHO CHNO CHOS CHNOS 1327 2811 772 348 25.2 53.5 14.7 6.6 0.34 ± 0.20 0.35 ± 0.18 0.37 ± 0.21 0.28 ± 0.19 0.23 ± 0.21 0.30 0.31 0.29 0.32 0.21 1.51 ± 0.36 1.46 ± 0.36 1.55 ± 0.33 1.48 ± 0.39 1.45 ± 0.39 1.63 1.59 1.65 1.69 1.45 6.61 ± 4.65 6.17 ± 4.00 6.58 ± 4.52 6.31 ± 4.64 9.20 ± 6.68 4.71 4.38 5.36 3.52 6.63 2139 363 1359 290 127 2864 875 1374 418 197 227 73 69 61 24 28 16 9 3 0 All 2896

CHO CHNO CHOS CHNOS 1016 1465 369 46 35.1 50.6 12.8 1.6 0.39 ± 0.19 0.42 ± 0.18 0.40 ± 0.19 0.32 ± 0.21 0.23 ± 0.25 0.30 0.37 0.28 0.30 0.12 1.59 ± 0.30 1.54 ± 0.30 1.63 ± 0.26 1.56 ± 0.43 1.48 ± 0.29 1.77 1.57 1.84 1.64 1.39 5.15 ± 3.00 4.75 ± 2.39 5.39 ± 2.99 5.03 ± 4.10 7.17 ± 3.24 4.17 4.01 4.20 3.78 8.96 1434 340 899 180 15 1414 661 558 164 31 42 15 6 21 0 6 0 2 4 0 9 ACS Paragon Plus Environment


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Table 1: Number of compounds in each subgroup and relative percentage, arithmetic and

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weighted mean elemental ratio and standard deviation for each subgroup in samples J1 and J2.

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The oxygen to carbon ratio (O/C) is in the range 0.1–1.1, with average values of 0.34 ± 0.20

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and 0.39 ± 0.19 for J1 and J2, respectively, while the hydrogen to carbon ratios (H/C) are 1.51

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± 0.36 and 1.59 ± 0.30 for J1 and J2, respectively. O/C and H/C values are similar in samples

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J1 and J2 but slightly higher for J2.

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DBE data provides information regarding the chemical nature of a molecule. In fact, a

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decreasing number of H atoms in a molecule indicates increased unsaturation and leads to

190

higher average DBE values. Indeed, the average DBE is higher for sample J1 (6.61 ± 4.64)

191

than for sample J2 (5.15 ± 3.00) for each elemental group. The high average DBE value

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observed for J1 is likely due to the presence of primary organic compounds that have not yet

193

undergone secondary formation mechanisms 25. Indeed, Bateman et al.

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in the average O/C ratio and a decrease in the average DBE of the dissolved SOA compounds

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following exposure to UV radiation. DBE, however, is the number of unsaturations,

196

considering N and S in their lowest oxidation state. We thus also calculated the AI to include

197

the possibility that heteroatoms can form double bonds that do not contribute to aromaticity,

198

ring formation or condensation, as described by Melendez-Perez et al.44. AI was determined

199

using Equation S2 (SI–S(8)). Aliphatic chains can mask the aromatic structures of several

200

compounds, such as degradation products of lignins. This phenomenon occurs because non-

201

aromatic structures can be constructed with the same molecular formula as the aromatic

202

structures.

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If the AI is negative, such as when the number of π-bonds is lower than the number of

204

heteroatoms, the AI is defined as 0. A threshold value of AI ≥ 0.67 is indicative of highly

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probable condensed aromatic compounds. An AI value between 0.5 and 0.67 indicates that

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the structure of these compounds may be condensed aromatics of non-condensed aromatics

43

showed an increase


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cyclic carbonyl compounds. Only less than 5% were considered to be strictly aromatic

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structures. Sample J1 contains more molecular formulas attributed to aromatic compounds

209

than sample J2.

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CHO compounds in samples J1 and J2 are characterized by an O/C ratio < 1.0 and an H/C

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ratio from 0.3 to 2.4. The average O/C ratios for the CHO compounds in J1 and J2 are 0.35

212

(±0.18) and 0.42 (±0.18), respectively, while the average H/C ratios are 1.46 (±0.36) and 1.54

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(±0.34), respectively (Table 1). Figure S6 reports a van Krevelen diagram (VK), a DBE

214

versus carbon number plot and oxygen content. For J1 and J2, the average DBE values of the

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CHO compounds are 6.2(±4.0) and 4.8 (±2.4), respectively. DBE values of cloud water CHO

216

compounds cover a wide range (0–24), and the value increases with carbon content (C3–C36).

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A majority (> 80%) of the compounds in samples J1 and J2 have DBE values lower than 10,

218

and the most represented classes (O3, O4, O5 and O6) have DBE values within the range 2-5.

219

Oxygen content was evaluated by separating CHO compounds into subclasses based on the

220

number of oxygen atoms in the assigned molecular formula, and the total relative abundance

221

of each of the subclasses is presented in Figure S6c. The subclasses with high relative

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abundance are O3, O4, O5 and O6, and the same distribution is observed for the number of

223

assigned molecular formulas in each subclass.

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CHNO compounds represent the largest fraction and the maximum relative abundance of

225

these compounds is in the mass range of m/z 200–400. These compounds account for 53.5%

226

of the total number of molecular formulas (N=2811) in sample J1 and 50.6% (N=1465) in

227

sample J2. The average O/C ratios for J1 and J2 are 0.37 (±0.21) and 0.40 (±0.19),

228

respectively, while the average H/C ratios are 1.55 (±0.33) and 1.63 (±0.26) (Table 1),

229

respectively. A low percentage of CHNO compounds (16 and 8% for J1 and J2, respectively)

230

present DBE values > 10; the average DBE is 6.6 for J1 and 5.4 for J2. The DBE increases

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with the number of carbon atoms in the formula, which ranges from 4 to 51 (Figures S7b and

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S8b). CHNO compounds in cloud water contain 1-4 nitrogen atoms per molecular formula. 11 ACS Paragon Plus Environment


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The compounds with N1 represent an average of 50% of the CHNO molecular formula, while

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those with N2 represent 37 and 26% in J1 and J2, respectively. N3 and N4 account for 12 and

235

9%, in J1 and 7 and 14% in J2. CHNO compounds contain up to 14 oxygen atoms per

236

molecular formula, as reported in Figures S7c and S8c.

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S–containing compounds, including CHOS and CHNOS groups, contribute 21.3% (772

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CHOS and 348 CHNOS) and 14.36% (369 CHOS and 46 CHNOS) to the total number of

239

molecular formulas in J1 and J2, respectively. The relative abundance of these compounds is

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generally lower than that of CHO and CHNO, but the highest relative abundance values are in

241

the same mass range as those observed for CHO and CHNO. N–containing and S–containing

242

compounds exhibit a large number of –CH2 series, generally longer for CHNO than for

243

CHNOS and CHOS, as reported by the van Krevelen diagram (Figure S9b).

244

3.3

245

Although high-resolution mass spectrometry provides accurate masses, this technique also

246

significantly increases the amount of data generated. When dealing with complex samples,

247

particularly in an ultrahigh-resolution mass spectrometric analysis such as FT-ICR, a data

248

processing method is commonly employed to visualize the complex dataset. Indeed, graphical

249

tools such as VK diagrams reveal the properties of natural organic matter (NOM) based on

250

distinct molecular series with specific positioning in the diagrams and on the diagnostics of

251

compound class and structure

252

ratios on the x-axis and O/C ratios on the y-axis for each formula in a sample, have commonly

253

been used to describe the compositional space of complex organic mixtures of aerosol

254

samples 32,46. The H/C ratio is directly associated with the relative aliphaticity and aromaticity

255

of a compound and correlates with the DBE per carbon, whereas the O/C ratio relates to the

256

oxygenation state 47. Aliphatic compounds typically have high H/C ratios (≥1.5) and low O/C

257

ratios (≤0.5), while aromatic hydrocarbons have low H/C ratios (≤1.0) and O/C ratios (≤0.5).

258

In general, oxidized species cluster in the lower right part of the VK plot, while

Comparative analysis using van Krevelen diagrams

44

. In addition, VK diagrams, which project elemental H/C


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reduced/saturated species populate the upper left part of the diagram. This graphical approach

260

helps in the comparison of the elemental compositions among samples, which are not clearly

261

visible from the direct mass spectral comparison 32.

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VK diagrams of CHO compounds in samples J1 and J2 are plotted in Figure S6: the Ox

263

classes (O1, O2,…) are separated horizontally, while the H/C differences (due to differences in

264

DBE) are separated vertically. The number of rings and double bonds increase as the H/C

265

ratio decreases. The diagonals show homologous alkylation series 48. This plot indicates the

266

oxidation, hydration, hydrogenation, and alkylation relationships between the observed

267

molecular formulas

268

dispersion, but the molecular formulas with the highest intensities are located in the area

269

around O/C = 0.3 and H/C = 1.7. Some aromatic compounds, with high DBE values, are

270

clearly visible in the left corner of the diagram (O/C < 0.3, H/C < 1).

271

Samples J1 and J2 contain CHNO compounds with high DBE values (i.e., 14–19) located in

272

the aromatic region (O/C < 0.3 and H/C < 1.0) of the VK diagram (Figures S6a and S7a).

273

Interestingly, a series of nitrogen-containing homologous formulas of the type CxHyNO4 with

274

x = 7–17 and y = 7–27, tentatively identified as nitroaromatic compounds such as

275

nitrophenols, nitrocatechols, nitroguaiacols and nitrosalycilic acids, were found in both J1 and

276

J2 samples. These compounds have recently been reported in aerosol samples from various

277

urban 50–53 and rural 32,54,55 environments and have mainly been attributed to biomass-burning

278

sources; thus emissions from residential wood combustion are likely to contribute to the

279

reduced levels of nitrogen-containing species observed in cloud samples. Nevertheless, NACs

280

can also be formed through aqueous phase processes, such as the reactions observed between

281

glyoxal and methylglyoxal and ammonium sulfate or ammonium nitrate under deliquescent

282

conditions

283

sample J1 exhibits a typical “dragon tail” profile, with a row of spines running down, as

284

observed by Schmitt-Kopplin et al.

49

(Figure S6a). The VK diagram in Figure S6a shows a widespread

56,57

. Figures S7c and S8c show the relative abundance of CHNO subgroups:

26

, for the DOM of organic aerosols (Figure S7c), while 13

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the distribution is less pronounced for sample J2 (Figure S8c). The high-relative-abundance

286

CHNO compounds are in the subgroup NO3-9, N2O3-7 and are clustered in the upper left

287

region of the VK plot (0.34, low DBE and high H/C to organosulfate compounds.

297

In both samples, the average value of O/S for CHOS is 4.5 and that for CHNOS is

298

approximately 4 (Table S2). CHOS and CHNOS compounds with O/S>4 present high H/C

299

values (between 1.65 and 1.85), low DBE values (from 2.57 to 4.03) and O/C values between

300

0.39 and 0.51. These compounds are composed of 4 to 10 oxygen atoms. An example of an

301

organosulfate detected in the cloud samples is C10H17NO7S, a sulfate ester that is a

302

photoproduct of the photolysis of α-pinene, produced in the presence of SO2 and NOx

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This compound is present in J1, which was collected under diurnal conditions, while it was

304

not observed in J2. CHOS and CHNOS compounds with O/S

Molecular Characterization of Cloud Water ... - ACS Publications

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