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Aqueous-phase Organic Chemistry in the Atmosphere
by
Ran Zhao
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy
Department of Chemistry University of Toronto
© Copyright by Ran Zhao 2015
ii
Aqueous-phase Organic Chemistry in the Atmosphere
Ran Zhao
Doctor of Philosophy
Department of Chemistry
University of Toronto
2015
Abstract
Atmospheric aqueous phases (i.e. cloud, fog and aerosol liquid water) are important reaction media
for the processing of organic compounds. Quantitative data on aqueous-phase organic chemistry
under the atmospheric context are sparse compared to the data from comparable gas-phase
processes. A series of studies was conducted to provide fundamental information on this topic.
An online analytical technique, Aerosol Chemical Ionization Mass Spectrometry (Aerosol CIMS),
was employed to quantitatively monitor aqueous-phase OH oxidation of glyoxal and
methylglyoxal. Quantification of all the major reaction products was achieved, permitting
complete reaction mechanisms to be presented. An unexpected class of compounds, α-
hydroxyhydroperoxide (α-HHP), was observed during the experiments, and the formation of this
class of compounds was further quantified. Formation of α-HHP can be potentially important in
aerosol liquid water, affecting aerosol toxicity and the gas-particle partitioning of small aldehydes.
Aerosol CIMS was further applied to the OH oxidation of levoglucosan, using a high mass
resolution CIMS. Unique reaction trends were observed, from which novel mechanism analysis
frameworks were introduced.
Aqueous-phase photochemical processing of a variety of light-absorbing organic compounds
(Brown Carbon (BrC)) was investigated in the laboratory. The light absorptivity of BrC was
iii
significantly altered via these processes, indicating that the chemical processing of BrC species
needs to be considered for a sound assessment of their atmospheric implications.
Finally, cloud-partitioning of a toxic compound, isocyanic acid (HNCO), was investigated in the
field, representing the first online measurement of gas-phase compounds dissolved in cloudwater.
A secondary source of HNCO in the ambient air was also observed.
Overall, aqueous-phase chemistry leads to reaction products which likely contribute to secondary
organic aerosol (SOA) formation. At the same time, aqueous-phase chemistry also facilitates the
transformation and removal of specific species with atmospheric significance (e.g. tracer
compounds, pollutants, BrC).
iv
Acknowledgments
First and foremost, I would like to thank my supervisor, Jon Abbatt, for all his contributions to this
thesis and to my entire PhD research. He has continuously impressed me with his intelligence,
generosity, fairness and considerateness. Not only has he provided adequate amount of guidance
in my research to support me, but also given me plenty of freedom so that I can learn to think
thoroughly, act critically, and work independently. His support extends to my exploration of life-
long career goals as well. He always promptly provides precious advice when I had to make
important decisions. My appreciation to Jon cannot be fully described in merely one paragraph.
Nevertheless, throughout my five years of pursuing a PhD, I realize that I could not have found a
better supervisor than him.
I would also like to give special thanks to my supervisory committee members, Jamie Donaldson
and Jen Murphy. In fact, I have worked as an undergraduate student in both of their laboratories
prior to my PhD pursuit. Without experiencing working with them, I may not have made the
decision to stay in this research area. They have also provided me with continuous support
throughout my PhD degree, with timely advice during my decision-making processes.
I also thank Frank Wania, Authur Chan, and Barbara Ervens for serving on my final examination
committee. Frank has served on my oral exam committee and provided me with useful advice
during the midpoint of my PhD degree. Arthur generously agreed on sitting in on two defences in
the same week. Barbara found a gap in her busy schedule to visit Toronto for my final defence. I
really appreciate their time and constructive suggestions on my thesis.
I have had a great opportunity working with a large number of collaborators during my PhD
research. I appreciate the support from each of them. Andre Simpson and Ron Soong at University
of Toronto Scarborough have provided me with a precious opportunity to use their advanced NMR
technique presented in Chapter 4. A number of collaborators have provided me with the biofuel
combustion samples presented in Chapter 5, including Huang Lin from Environment Canada,
Xinghua Li from Beihang University, and Fumo Yang from Chongqing institution of Green and
Intelligent Technology. A large number of collaborators have been involved in the field campaign
presented in Chapter 6. I would like to thank Richard Leaitch, Anne Marie Macdonald, John
Liggio, Jeremy Wentzell, Desiree Toom-Sauntry from Environment Canada for organizing the
campaign and allowing me to operate their Acid CIMS; Lynn Russell, Rob Modini, and Ashley
v
Corrigan from Scripps Institution of Oceanography for helping me throughout the campaign; Jason
Schroder from Allan Bertram’s group at University of British Columbia for driving me every day
to the measurement site and chasing for clouds together; and Lelia Hawkins at Harvey Mudd
College for providing me with cloudwater samples.
I was extremely fortuitous to work in a great research group. I could not have completed my PhD
degree without the support from my group members. I would like to send special thanks to Alex
Lee who is essentially my second supervisor. He has helped me throughout my entire PhD
research, reflected by the fact that he is a coauthor on all the five publications of mine. I would
also like to thank Shouming Zhou and Luis Ladino for being great mentors, as well as great friends
all the time; and Jenny Wong for helpful discussions about research and life throughout my
progress in graduate school. I would also like to extend my thanks to other current and past group
members, including Shawna Gao for editing my writing and teaching me how to operate PTR-MS
and TOC analyzer; Joel Corbin for teaching me tricks on Igor; Dana Aljawhary for offering a lot
of assistance on the ToF-CIMS; Nadine Borduas for all the exciting discussions into the depth of
organic chemistry; Richard Li for providing his great efforts on the UV-Vis measurements of
Brown Carbon; Emma Mungall for working together and shipping “sugar water” to Germany;
Rachel Chang and Rob McWhinney for being great senior students and mentors; Jacquie Yakobi
for being a cheerful neighbour and inviting Barbara Ervnes, my external-to-be to our lunch in the
conference; Rachel Hems for editing the introduction of this thesis; and Egda Escorcia, Jay Slowik,
Katie Badali, Maria Antonolo, Megan Willis, Julia Burkart, Cuyler Borrowman, Yasmine Katrib,
Katrina Macdonald, Bob Christensen, Appana Lok, Zack Finewax and Crystal Chen for being
great teammates.
A number of alumni / senior students both in and out of my research group have provided me with
enormous inspirations and helpful advice in making my decision for my future direction. This
includes Tara Kahan, Xianming Zhang, Jessica D’eon, Hashim Farooq, Sumi Wren, Rachel Chang,
and Jeff Geddes.
Finally, none of this would be possible without unconditioned love and encouragement from my
parents, Dong Zhao and Feng Jia, my grandfather, Guangshi Jia, my late grandmothers, Bianru Li,
Fangying Sheng, and the rest of family members. This is your achievement as much as mine.
vi
Table of Contents
Acknowledgments .......................................................................................................................... iv
Table of Contents ........................................................................................................................... vi
List of Tables ............................................................................................................................... xiii
List of Figures ............................................................................................................................... xv
List of Appendices .................................................................................................................... xxvii
Preface ...................................................................................................................................... xxviii
Chapter 1: Introduction to Aqueous-phase Organic Chemistry in the Atmosphere ....................... 1
1.1 Secondary Organic Aerosol and Its Environmental Impacts .............................................. 2
1.2 Formation Mechanisms of SOA ......................................................................................... 2
1.2.1 Gas-Particle Partitioning Theory – the Traditional Understanding of SOA
Formation ................................................................................................................ 2
1.2.2 Discrepancies between Models and Measurements ................................................ 3
1.2.3 Aqueous-phase Chemistry – a New Formation Mechanism of SOA ..................... 3
1.3 Atmospheric Aqueous Phases and Partitioning of Organic Compounds............................ 5
1.3.1 Aqueous Phases in the Atmosphere ........................................................................ 5
1.3.2 Partitioning of Organic Compounds to Aqueous Phase ......................................... 6
1.4 Production and Concentration of OH Radicals in Atmospheric Aqueous Phases .............. 9
1.4.1 Gas-Phase Partitioning and in-situ Formation of OH Radical ................................ 9
1.4.2 Mechanisms of in-situ Formation of OH Radical ................................................. 11
1.4.3 Diffuso-reactive Length (dL) of OH Radical ........................................................ 12
1.4.4 Steady State Concentrations of OH Radical ......................................................... 15
1.5 OH Reactivity and Reaction Mechanisms ........................................................................ 15
1.5.1 Initiation of the Radical Chain .............................................................................. 15
1.5.2 Propagation of Radical Chain ............................................................................... 17
vii
1.5.3 Termination of Radical Chain ............................................................................... 17
1.6 OH Radical Reactions Unique to the Aqueous Phase ...................................................... 17
1.6.1 Efficient Conversion of Aldehydes to Carboxylic Acids ..................................... 17
1.6.2 Rapid OH Oxidation of Carboxylate .................................................................... 19
1.6.3 Radical Induced Oligomerization ......................................................................... 20
1.6.4 Radical Induced Organosulfate Formation ........................................................... 21
1.7 Non-radical Chemistry in the Aqueous-phase – Nucleophilic Addition Reactions ......... 22
1.7.1 General Reaction Mechanism of Nucleophilic Addition ...................................... 22
1.7.2 Importance of Acid-catalysis ................................................................................ 23
1.7.3 Water Nucleophile and Hydration ........................................................................ 23
1.7.4 Alcohol Nucleophile and Hemiacetal Formation ................................................. 25
1.7.5 Enol Nucleophile and Aldol Condensation ........................................................... 25
1.7.6 Similarities and Differences in Hemiacetals and Aldol Condensates ................... 26
1.7.7 Hydroperoxide (ROOH) Nucleophile and Peroxyhemiacetal Formation ............. 26
1.7.8 Nitrogen-containing Nucleophiles and Atmospheric Brown Carbon Formation . 27
1.8 Removal of Organic Compounds in Aqueous-phase ........................................................ 28
1.9 Sampling and Measurement Techniques for Aqueous-phase Organic Compounds ......... 29
1.9.1 Sampling Techniques for Cloud and Fog Water ................................................... 29
1.9.2 Recent Development of Extraction and Measurement of Water Soluble
Organic Carbon Associated with Particles ........................................................... 30
1.9.3 Application of Online Mass Spectrometry to Aqueous-Phase Detection. ............ 31
1.10 Summary and Objectives .................................................................................................. 32
Bibliography ................................................................................................................................. 34
Chapter 2: Investigation of Aqueous-Phase Photooxidation of Glyoxal and Methylglyoxal by
Aerosol Chemical Ionization Mass Spectrometry: Observation of α-hydroxyhydroperoxide
Formation ................................................................................................................................. 53
Abstract .................................................................................................................................... 54
viii
2.1 Introduction ....................................................................................................................... 54
2.2 Experimental Methods ...................................................................................................... 57
2.2.1 Photooxidation of Aqueous Solution. ................................................................... 57
2.2.2 Aerosol CIMS ....................................................................................................... 59
2.2.3 Offline TOC and Complementary IC Analysis .................................................... 62
2.3 Results and Discussions .................................................................................................... 63
2.3.1 Formation of α-Hydroxyhydroperoxides (α-HHPs) in Dark Control
Experiments .......................................................................................................... 63
2.3.2 Photooxidation of GLY ......................................................................................... 66
2.3.3 Photooxidation of MG .......................................................................................... 68
2.3.4 TOC Concentration and Carbon Balance ............................................................. 71
2.3.5 Evidence of Oligomer Formation ......................................................................... 74
2.4 Conclusions ....................................................................................................................... 75
Acknowledgement .................................................................................................................... 77
Bibliography ............................................................................................................................. 77
Chapter 3: Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic Study Using
Aerosol Time-of-Flight Chemical Ionization Mass Spectrometry (Aerosol ToF-CIMS) ....... 84
Abstract .................................................................................................................................... 85
3.1 Introduction ....................................................................................................................... 85
3.2 Experimental Methods ...................................................................................................... 87
3.2.1 Solution Preparation and Photooxidation ............................................................. 87
3.2.2 Aerosol-ToF-CIMS ............................................................................................... 88
3.2.3 Mechanistic and Kinetic Studies ........................................................................... 89
3.2.4 Aerosol Mass Spectrometry (AMS) Measurements ............................................. 90
3.3 Results and Discussion ..................................................................................................... 91
3.3.1 Reaction Products and Mechanism ....................................................................... 91
3.3.2 Kinetic Study ...................................................................................................... 102
ix
3.3.3 Comparison with AMS Data ............................................................................... 104
3.4 Conclusions and Environmental Implications ................................................................ 105
Acknowledgement .................................................................................................................. 107
Bibliography ........................................................................................................................... 107
Chapter 4: Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP): Potential
Atmospheric Impacts ............................................................................................................. 113
Abstract .................................................................................................................................. 114
4.1 Introduction ..................................................................................................................... 114
4.2 Experimental Methods .................................................................................................... 118
4.2.1 1H NMR Measurements ...................................................................................... 118
4.2.2 Effects of Inorganic Salts .................................................................................... 120
4.2.3 PTR-MS Measurements ...................................................................................... 120
4.2.4 Reversibility Test: Addition of Catalase ............................................................. 121
4.3 Results and Discussion ................................................................................................... 121
4.3.1 1H NMR Results ................................................................................................. 121
4.3.2 PTR-MS Results ................................................................................................. 127
4.3.3 Comparison of Equilibrium Constants ................................................................ 128
4.3.4 Temperature Dependence of Kapp ....................................................................... 133
4.3.5 Effects of Inorganic Salt Addition ...................................................................... 135
4.4 Atmospheric Implications ............................................................................................... 136
4.4.1 Equilibrium concentrations of α-HHPs in cloud water and aerosol liquid water 136
4.4.2 Impact of α-HHP formation on the atmospheric partitioning of aldehydes and
H2O2 .................................................................................................................... 138
4.4.3 Other Atmospheric Implications ......................................................................... 140
4.5 Conclusions ..................................................................................................................... 142
Acknowledgement .................................................................................................................. 143
Bibliography ........................................................................................................................... 143
x
Chapter 5: Photochemical Processing of Aqueous Atmospheric Brown Carbon ....................... 151
Abstract .................................................................................................................................. 152
5.1 Introduction ..................................................................................................................... 152
5.2 Methods ........................................................................................................................... 155
5.2.1 Preparation of BrC Solutions .............................................................................. 155
5.2.2 Direct Photolysis and OH Oxidation Experiments ............................................. 156
5.2.3 Direct Photolysis of WSOC from Biofuel Combustion ...................................... 158
5.3 Results and Discussion ................................................................................................... 158
5.3.1 Light Absorption of BrC ..................................................................................... 158
5.3.2 Imine BrC ............................................................................................................ 160
5.3.3 Nitrophenols ........................................................................................................ 164
5.3.4 Direct Photolysis of WSOC from Biofuel Combustion Samples ....................... 172
5.4 Conclusions and Atmospheric Implications ................................................................... 172
Acknowledgement .................................................................................................................. 173
Bibliography ........................................................................................................................... 174
Chapter 6: Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of Secondary Source
of HNCO in Ambient Air ....................................................................................................... 181
Abstract .................................................................................................................................. 182
6.1 Introduction ..................................................................................................................... 182
6.2 Methods ........................................................................................................................... 183
6.2.1 Site Description ................................................................................................... 183
6.2.2 Acid-CIMS .......................................................................................................... 184
6.2.3 CVI ...................................................................................................................... 184
6.3 Results and Discussion ................................................................................................... 185
6.3.1 Detection of HNCO From Cloudwater ............................................................... 185
6.3.2 Estimation of the Aqueous Fraction of HNCO (faq,HNCO) ................................... 186
xi
6.3.3 Unexpectedly High Aqueous Fraction of HNCO ............................................... 187
6.3.4 Evidence of a Secondary Source of HNCO in the Ambient Air ......................... 189
6.4 Summary ......................................................................................................................... 192
Acknowledgement .................................................................................................................. 193
Bibliography ........................................................................................................................... 193
Chapter 7: Conclusions and Future Research ............................................................................. 198
7.1 Summary and Future Research for Laboratory Investigations of Aqueous-phase
Chemistry ........................................................................................................................ 199
7.2 Summary and Future Research for Organic Hydroperoxide (ROOH) Formation .......... 200
7.3 Summary and Future Research for Atmospheric Brown Carbon (BrC) ......................... 201
7.4 Summary and Future Research for Cloud Partitioning of Organic Compounds ............ 202
Bibliography ........................................................................................................................... 203
Appendix A ................................................................................................................................. 206
A1 List of Detected Peaks .................................................................................................... 207
A2 Proposed Mechanisms .................................................................................................... 209
A3 Estimation of the Diffusion Limited Rate Constant of LG Oxidation by OH Radicals
in the Aqueous Phase. ..................................................................................................... 211
Bibliography ........................................................................................................................... 211
Appendix B ................................................................................................................................. 213
B1 Example 1H NMR Spectra and Peak Assignment for Each Carbonyl Compound. ........ 214
Bibliography ........................................................................................................................... 222
Appendix C ................................................................................................................................. 223
C1 Determination of Photon Flux in the Solar Simulator .................................................... 224
C2 Quantitative Assessment of BrC Absorption .................................................................. 225
C2.1 Imine BrC ............................................................................................................ 225
C2.2 WSOC from Biofuel Combustion Samples ........................................................ 226
C2.3 Nitrophenols ........................................................................................................ 226
xii
C3 Concentration Dependence of Imine BrC Decay Rate ................................................... 228
C4 Spectral Change of 4NP and 5NG during Direct Photolysis .......................................... 228
C5 pH Dependent Photo-enhancement of 4NP and 5NG and OH Scavenger Experiments 229
C6 pH Dependent Absorption of Nitrophenols .................................................................... 231
C7 Photooxidation of 4NP and 5NG .................................................................................... 231
C8 Simple Kinetic Model Applied to 4NP and 5NG ........................................................... 232
Bibliography ........................................................................................................................... 233
Appendix D ................................................................................................................................. 235
D1 Map of the measurement sites ......................................................................................... 236
D2 Calibration of the Acid-CIMS ........................................................................................ 236
D2.1 Calibration Methods ............................................................................................ 236
D2.2 Calibration factors and limits of quantification of HNCO and HNO3 ................ 236
D3 Quantification of HNCO and HNO3 in CVI. .................................................................. 237
D3.1 CVI Background ................................................................................................. 237
D3.2 Normalization and Quantification ....................................................................... 237
D4 Calculating the Aqueous Fraction of HNCO (faq,HNCO) .................................................. 238
D4.1 Determination of the Enhancement Factor (EF) ................................................. 239
D4.2 Determination of Droplet Transmission (DT) in the CVI .................................. 240
D4.3 Determination of the fraction of LWC sampled by CVI (fliquid) ......................... 241
D4.4 Error propagation for faq,HNCO ............................................................................. 241
D4.5 A sensitivity test for faq,HNCO ............................................................................... 242
D5 The pH-dependence of KHeff of HNCO and the theoretical aqueous fraction of HNCO
(faq,HNCO) .......................................................................................................................... 243
D6 Time series and diurnal profiles of HNCO, formic acid and ambient temperature ........ 244
D7 Strength of correlation between HNCO and BC during various time periods ............... 245
Bibliography ........................................................................................................................... 245
xiii
List of Tables
page
Table 1.1 Conditions used in the measurements of in-situ production rate of OH
radical.
11
Table 2.1 Experimental Conditions. 59
Table 3.1 Summary of the conditions and the results of the kinetic experiments. 102
Table 4.1 Summary of hydration equilibrium constants (Khyd) measured by NMR.
The constants are reported with their standard deviation arising from the
number of replicates indicated on the table.
125
Table 4.2 Summary of the apparent equilibrium constants of α-HHP formation
(Kapp) measured and reported in literature at 25 ˚C. The constants are
reported with their standard deviation acquired from the number of
replicates shown on the table.
126
Table 4.3 Temperature dependence of the apparent equilibrium constant (Kapp) of 1-
hydroxyethyl hydroperoxide (1-HEHP) formation from acetaldehyde.
134
Table 4.4 Effects of inorganic salt addition on the hydration equilibrium constant
(Khyd) and the apparent α-HHP formation equilibrium constant (Kapp).
135
Table 4.5 Conditions assumed in the atmospheric partitioning simulation of 1 ppb
of aldehydes or H2O2.
138
Table 4.6 Results of the atmospheric partitioning simulation. 141
Table 5.1 Estimated atmospheric half-life of Imine BrC arising in the glyoxal-
ammonium sulfate (GLYAS) and methylglyoxal-ammonium sulfate
(MGAS) solutions.
161
xiv
Table 5.2 Rate constants for photo-enhancement at 420 nm for 4-nitrocatechol
(4NC).
167
Table 5.3 Photo-enhancement and bleaching rate constants1 for nitrophenol OH
oxidation determined from a simple kinetic model (Section 5.3.3.2.).
170
Table 6.1 Summary of the Aqueous Fraction of HNCO (faq,HNCO) Measured and
Calculated.
188
Table A1 List of peaks detected by the I(H2O)n- reagent ion. The chemical formulae
were assigned using the data processing software (Tofwerk v. 2.2). The
peak time and Max. peak intensity are the illumination time at which each
peak reached its maximum, and its corresponding signal intensity at that
time, respectively. The peak intensity has been normalized by the
intensity of the reagent ion at m/z 145 (I(H2O)-). This information, along
with the exact m/z and mass defect were used to construct the mass defect
plot (Figure 3.4 in the main article). The compounds displayed in Figure
3.6 in the main article are color coded.
207
Table B1 Comparison of Kapp values experimentally determined and calculated as
(Keq/Kapp).
222
Table C1 The absorbance based 1st order rate constant of photo-enhancement. 230
Table D1 Calibration factors of the Acid CIMS. 236
Table D2 The parameters from the June 1st and the June 13th cloud events are
summarized. D50 represents the calculated 50 % size cutoff of the CVI
(the cloud droplet cut size).
238
Table D3 A comparison of the calculated faq,HNCO in the actual case and a perturbed
case. The perturbed values are highlighted in red.
242
xv
List of Figures
page
Figure 1.1 A schematic illustration of SOA formation via the gas-particle partitioning
theory and the aqueous pathway.
4
Figure 1.2 Calculated aqueous fraction (faq) at 298 K under three selected LWC as a
function of effective Henry’s law constant (Heff). The figure also shows Heff
values of selected compounds at 298 K, along with their molecular
structures. References: glyoxal (Ip et al. 2009), methylglyoxal (Zhou and
Mopper 1990), oxalic acid (pH 4) (Compernolle and Muller 2014), α-
pinene (Leng et al. 2013), toluene (Kim and Kim 2014), O3 (Gershenzon et
al. 2001) and NO2 (Chameides 1984).
8
Figure 1.3 Calculated gas-particle partitioning rates and measured in-situ formation
rates of OH radical as a function of particle diameter. The calculated rates
are based on three (1, 0.1 and 0.01) values of mass accommodation
coefficient (α), and the measured in-situ formation rates are compiled based
on a number of studies, with the conditions of which summarized in Table
1.1.
10
Figure 1.4 The diffuso-reactive length (dL) of OH as a function of dissolved organic
carbon (DOC) concentrations. The loss rate of OH radical is based on the
averaged, carbon based value reported in Arakaki et al. (2013). The
horizontal bars represents the approximate DOC ranges in a variety of
atmospheric aqueous phases.
13
Figure 1.5 Structures and OH reactivity (kIIOH, 298K) of organic compounds relevant
to atmospheric aqueous phases (Buxton et al. 1988, Herrmann 2003, Tan
et al. 2009, Herrmann et al. 2010, Tan et al. 2012).
14
Figure 1.6 General OH radical reactions. 16
Figure 1.7 Mechanisms of rapid carboxylic acid formation in the aqueous phase. 18
xvi
Figure 1.8 OH reactivity (kIIOH) of carboxylic acids and corresponding carboxylates.
Acronym: formic acid (FA), glyoxylic acid (GA), pyruvic acid (PA), lactic
acid (LA), malic acid (MA), oxalic acid (OA). References: FA, GA and OA
(Tan et al. 2009), PA (Schaefer et al. 2012), LA and MA (Herrmann et al.
2010).
19
Figure 1.9 Charge transfer reaction of carboxylate. 20
Figure 1.10 Radical induced oligomerization mechanism, with one example each for
radical-radical recombination (a) (Guzman et al. 2006, Lim et al. 2010) and
radical propagation on double bonds (b) (Renard et al. 2013).
21
Figure 1.11 Nucleophilic addition reactions associated with carbonyl compounds. 24
Figure 2.1 Simplified reaction mechanisms of aqueous-phase photooxidation of GLY
(Lim et al. 2010) and MG (Lim et al. 2005, Altieri et al. 2008). The two-
way arrows represent reversible processes, whereas the one-way arrows
represent irreversible OH oxidation.
56
Figure 2.2 Schematic description of Aerosol CIMS and photooxidation cell. 58
Figure 2.3 Pathways showing formation of α-hydroxyhydroperoxides. 63
Figure 2.4 Formation of α-HHPs in dark control experiments. H2O2 (13 mM) was
added to 3 mM of GLY (a) or 3 mM of MG (b) solutions at time (I), and
quenched at time (II) by addition of catalase from bovine liver. α-HHPs
formed sharply after the addition of H2O2 and reached equilibrium values
approximately 40 min after the addition. After quenching of H2O2, α-HHPs
decayed to zero and reversibly formed GLY or MG.
64
Figure 2.5 Results of photooxidation experiments with 3 mM (a) and 0.3 mM (b)
initial GLY concentration. Photooxidation was initiated at time 0 (dashed
line). Data shown here are the average of 2−3 replicates, and the error bars
represent fluctuations between replicates (1 σ). The signal of 2-hydroxy-2-
66
xvii
hydroperoxyethanal (HHPE) overlaps with that of hydrated GA
(GA·1H2O). This normalized signal from one typical experiment is shown
(right axis).
Figure 2.6 Possible formation mechanisms of formic and acetic acids from α-HHPs
(from da Silva (2011)).
67
Figure 2.7 Three mM GLY photooxidation without α-HHP equilibrium. The
experiment was conducted as with the 3 mM GLY photooxidation, except
that photooxidation was initiated immediately after H2O2 was added to the
GLY solution at time 0. The error bars represent fluctuations between
replicates (1 σ).
68
Figure 2.8 Concentration profiles of MG and its products. Photooxidation was
initiated at time 0 (dashed line). The oxalic acid profile obtained from IC
and its fitted line are shown on the graph. Using the fitted line, the MG
concentration profile was calculated. The data represent the average of two
independent replicates, with the error bars showing fluctuation between the
replicates (1 σ). The normalized signal of 2-hydroxy-2-
hydroperoxypropanal (HHPP) and hydroxyhydroperoxyacetone (HHPA)
from one experiment is shown (right axis).
69
Figure 2.9 H2O2 control experiment for MG. MG solution (3 mM) was exposed to
irradiation without addition of H2O2. The irradiation was initiated at time 0
(dashed line). A significant amount of FA and AA was produced. The initial
increase of the MG signal was due to equilibration of MG in the inlet line,
and the initial signal of FA and AA are due to impurities in solution or due
to decomposition of MG prior to the experiment.
70
Figure 2.10 Normalized signal of OA (blue) was obtained from the fitted line of IC data.
The normalized signal of MG (yellow) was calculated by subtracting OA
normalized signal from total signal of MG + OA (black) obtained from the
Aerosol CIMS.
71
xviii
Figure 2.11 Measured and reconstructed TOC concentration in 3 mM glyoxal (GLY)
(a), 0.3 mM GLY (b), and 3 mM methylglyoxal (MG) photooxidation
experiments. Photooxidation was initiated at time 0 (dashed line). The
measured TOC shows the results from the offline TOC analyzer whereas
the reconstructed TOC is calculated from the total of the quantified organic
species (i.e., excluding α-HHPs and oligomers); see text. CIMS data
represent the average of 2−3 independent experimental replicates, and the
error bars represent fluctuations between the replicates (1 σ).
72
Figure 2.12 Decay time profiles of GLY·1H2O and GLY·2H2O during one typical
photooxidation experiment. The α-HHP equilibrium was fully established
before the photooxidation was initiated at time 0 (dashed line).
73
Figure 2.13 Formation of MA and SA in 3 mM GLY photooxidation. 75
Figure 3.1 The experimental apparatus. 88
Figure 3.2 The evolution of the “+O” (a) and the “−2H” (b) series from levoglucosan
(LG). The signal of each compound normalized by the reagent ion intensity
at m/z 145 (I(H2O)−) is shown as a function of the irradiation time. The
signals are multiplied by the bracketed number to be on scale.
92
Figure 3.3 The mass defect diagram of the major products detected using the iodide
water cluster (I(H2O)−n) reagent ion (a). The color code indicates the time
at which each compound reached its maximum signal intensity and the area
of the circles represents the maximum signal intensity reached (in log
scale). Compounds that did not reach their maxima during the first 300min
of illumination are shown in black. The +O and the −2H series fall on the
slope indicated by the dotted lines. The region relevant to products arising
from +O and −2H trends is presented in (b). The proposed structures of
each product are shown beside the data points.
93
Figure 3.4 Sample reaction mechanisms that give rise to the +O and −2H trends. The
tetroxide intermediate forming from two alkylperoxy radicals can result in
94
xix
a variety of products as shown in (R3.1) to (R3.3), among which (R3.1) can
lead to formation of the hydroxyl functional group. A hydroperoxy
functional group can be formed from RO2 +HO2 (R3.4). The hydroxyl-to-
carbonyl conversion shown in (R3.5) is likely responsible for the −2H
trend. Alkoxy radicals trigger bond-scission reactions and give rise to an
aldehydic compound (R3.6).
Figure 3.5 Evolution of bond-scission products measured by the I(H2O)−n reagent ion.
Selected major products with three to six carbons are shown in (a), with
their proposed structures. The proposed reaction mechanisms leading to
their formation are attached in Appendix A Figure. A1. Formation of small
organic acids with one or two carbons are shown in (b). All the signals have
been normalized against the reagent ion (I(H2O)−) at m/z 145.
96
Figure 3.6 Intensity-weighted average of double bond equivalence (DBE), DBE-to-
carbon ratio (DBE/#C), and oxidation state (OSc) as a function of
irradiation time.
99
Figure 3.7 OSc vs DBE/#C plot. The intensity-weighted average OSc and DBE/#C
from the products listed in Appendix A Table A1 are displayed here. The
color code represents the illumination time. The coordinates of major
compounds are also shown.
100
Figure 3.8 A simplified overview of reaction mechanisms discussed in the current
study. Solid arrows represent proposed reaction pathways of LG upon OH
oxidation. The dashed arrows illustrate the complicity in the reaction
system where each product can also take more than one reaction path.
101
Figure 3.9 The time series of LG and DMSO during a kinetic experiment (Exp. #1 in
Table 3.1) are shown in (a). The signals are normalized to those at the
beginning of the photooxidation. The relative kinetics plot from the same
experiment is shown in (b) according to Eqn. 3.1. The color code indicates
the illumination time.
103
xx
Figure 3.10 The decay of levoglucosan monitored by the Aerosol ToF-CIMS and the
decay of f60 monitored by the AMS (a), and the f60 vs. f40 trajectory from
the current work compared to field measurements (b). The trajectory
obtained in the current work is color coded with irradiation time. The
compiled data (Cubison et al., 2011) from field measurements in fire
plumes (grey) and non-fire plumes (brown) are also shown.
105
Figure 4.1 Two aqueous-phase pathways of α-hydroxyhydroperoxide (α-HHP)
formation: 1) The Criegee Pathway, 2) the Carbonyl pathway, and a related
reaction 3) Peroxyhemiacetal formation.
117
Figure 4.2 Experimental setup for the PTR-MS measurements. 120
Figure 4.3 1H NMR spectra for acetaldehyde. (a): Acetaldehyde aqueous solution; (b):
17.7 mM of H2O2 was added to the acetaldehyde solution; (c): Catalase was
added to the solution to quench H2O2. The insets are the magnified view of
certain regions of the spectra. The split pattern and the identity of each peak
are shown in the brackets (the numbers match those in the chemical
structures).
122
Figure 4.4 Hydration equilibrium constant (Khyd), the α-HHP formation equilibrium
constant (Keq) and the apparent α-HHP formation equilibrium constant
(Kapp). Please see the text for details.
123
Figure 4.5 Sample time series of signal due to gas-phase acetaldehyde in the PTR-MS
experiment. The acetaldehyde signal normalized to the reagent ion is shown
as a function of time. Time (i): 25 mL of clean water in the bubbler is
replaced by 25 mL of acetaldehyde solution (10 mM), Time (ii): 13.3 mM
of H2O2 is added to the acetaldehyde solution, Time (iii): one drop of
catalase stock solution is added.
127
Figure 4.6 1H NMR spectra of a formaldehyde-H2O2 mixture. The splitting pattern and
assignment of the peaks are shown in the bracket.
130
xxi
Figure 4.7 Typical acetaldehyde time profiles at 5, 15 and 25 ˚C are shown in (a). The
ratios of signal at a given time to the initial signal are shown. H2O2 (13.3
mM) was injected to the 10 mM acetaldehyde solutions at time (i). The
dashed lines show the signal levels at equilibrium. The van’t Hoff diagram
for 1-hydroxyethyl hydroperoxide (1-HEHP) formation from acetaldehyde
is shown in (b). The dashed lines connects +1 σ and -1 σ from the average
ln(Kapp) determined at the three temperatures.
134
Figure 4.8 Simulation of the equilibrium concentration of α-hydroxyhydroperoxide
([α-HHP]eq) arising from various equilibrium concentrations of H2O2
([H2O2]eq) and total aldehyde ([Total Aldehyde]eq). The concentrations are
all presented in log scale. Conditions relevant to cloud water and aerosol
water are also indicated. This simulation considers α-HHP formation via
only the Carbonyl Pathway, with an average equilibrium constant of 100
M-1.
137
Figure 5.1 Experimental procedures. 156
Figure 5.2 Absorption spectra of BrC investigated in this study (a) and WSOC from
the biofuel combustion samples (b). The y-axis in (a) is in arbitrary units to
keep the absorbance of all the solutions on scale.
159
Figure 5.3 Spectral change of the MGAS solution during a direct photolysis
experiment (a) and the absorbance change at 400 nm as a function of
illumination time (b). The inset in (b) shows the 1st order plot of the decay,
and the lines are linear least square plots forced through the origin. The
shaded area represent the range obtained from 3 replicates.
161
Figure 5.4 Time profiles of absorbance at 400 nm during OH oxidation (solid lines)
and H2O2 control (dashed lines) experiments. Results for both the GLYAS
(blue traces) and the MGAS (red traces) solutions are shown. The decay
profiles of absorbance at 400 nm normalized to the initial value at t =0 are
162
xxii
shown in (a), while their corresponding 1st order decay plots are shown in
(b).
Figure 5.5 Proposed explanation for the difference in the major bleaching processes
of the GLYAS and the MGAS solutions.
164
Figure 5.6 Spectral change of a 4NC solution (4 µM) during a direct photolysis
experiment. The inset shows the absorbance change compared to the initial
condition.
165
Figure 5.7 Time profiles of 4NC absorbance at 420 nm during direct photolysis
experiments. Experiments were performed at three solution pH values. An
OH scavenger experiment was also performed by adding 1 mM glyoxal to
the pH 5 solution.
166
Figure 5.8 Spectral change of 4NC solution (10 µM) during an OH oxidation
experiment (a), with the inset showing absorbance change compared to the
initial condition. The color coding represents the illumination time. The
time profiles of absorbance at 420 nm are shown in (b). The black trace is
from a H2O2 control experiment, while the red trace is from one of the OH
oxidation experiments.
168
Figure 5.9 A schematic illustration of the simple kinetic model (a) and one example
of 4NC photooxidation (b). The shaded areas in (b) are the contributions
from a newly formed colored product (CP) and the decaying 4NC,
respectively. The red line follows data from an experiment.
170
Figure 5.10 Direct photolysis of the WSOC from biofuel combustion samples. The
spectral evolution of the kaoliang and the cotton samples is shown in (a)
and (b), respectively. The color code indicates illumination time, while the
insets show the absorbance change compared to the initial condition. The
time profiles of absorbance at three different wavelengths for the same
samples are shown in (c) and (d), respectively.
171
xxiii
Figure 6.1 Time series of HNCO and HNO3 mixing ratios measured after the CVI
during (a) the June 1st event and (b) the June 13th event are shown along
with LWC in the surrounding air. (c) The correlations of HNCO with LWC
for both of the events are shown.
186
Figure 6.2 The time profile of HNCO and HNO3 measured during a selected period of
(a) the campaign and (b) the averaged diurnal profiles of HNCO, HNO3,
and black carbon (BC) from the entire campaign, where the error bars
represent 1𝜎 of the diurnal variation. (c) The primary-secondary
apportionment of HNCO is shown. See text for details about the
apportionment.
190
Figure 6.3 The time profile of HNCO and HNO3 measured during a selected period of
(a) the campaign and (b) the averaged diurnal profiles of HNCO, HNO3,
and black carbon (BC) from the entire campaign, where the error bars
represent 1𝜎 of the diurnal variation. (c) The primary-secondary
apportionment of HNCO is shown. See text for details about the
apportionment.
192
Figure 7.1 Calculated aqueous fraction (faq) as a function of effective Henry’s law
constant Heff. The figure is same as Figure 1.2, but with the addition of faq
at bulk LWC (106 g m-3) where chemicals exist entirely in the aqueous phase.
200
Figure A1 Proposed reaction mechanism giving rise to the products displayed in
Figure 3.6 (main article). The overall reaction mechanism of levoglucosan
photooxidation is highly complicated, and only a subset is shown here. As
one example, the mechanism demonstrates the case when H-abstraction
occurs at the position shown in Scheme 1. Subsequent chain scission can
lead to two different reaction pathways shown in Scheme 2 and Scheme 3,
respectively. Scheme 4 demonstrates that products from Scheme 3 can
undergo the hydroxyl-to-carbonyl conversion which is discussed in the
functionalization section in the main article. Scheme 5 illustrates hydration
of an aldehyde and its subsequent conversion to a carboxylic acid.
210
xxiv
Figure B1 Glycolaldehyde (10 mM) and H2O2 (17.7 mM). 214
Figure B2 Methylglyoxal (10 mM) and H2O2 (17.7 mM). 215
Figure B3 Propionaldehyde (10 mM) and H2O2 (17.7 mM). 216
Figure B4 Glyoxal (10 mM) and H2O2 (17.7 mM). 217
Figure B5 Glyoxylic acid (10 mM) and H2O2 (17.7 mM). 218
Figure B6 Methacrolein (10 mM) and H2O2 (100 mM). 219
Figure B7 Methylethyl ketone(10 mM) and H2O2 (100 mM). 220
Figure B8 Acetone (10 mM) and H2O2 (100 mM). 221
Figure C1 The photon flux in the solar simulator and in the ambient. 225
Figure C2 Wavelength dependent mass absorption coefficient (MAC) for the Imine
BrC (a), the WSOC from biofuel combustion samples (b), and the base 10
absorption cross section and molar absorptivity of the nitrophenols (c).
227
Figure C3 Decay of the GLYAS solution (a) and the MGAS solution (b) during the
first 10 min of illumination at different initial concentrations.
228
Figure C4 Spectral change observed for a 4NP solution (a) and a 5NG solution (b)
during direct photolysis experiments. The initial concentrations of 4NP and
5NG were 5 µM and 4 µM, respectively. The insets illustrate the
absorbance change compared to the initial conditions.
228
Figure C5 Color formation from 4NP and 5NG solutions during the pH dependent and
the OH scavenger experiments. The formation profiles of absorbance at 420
nm and 450 nm from 4NP are shown in (a) and (b). The formation profiles
of absorbance at 420 nm from 5NG are shown in (c).
230
Figure C6 Absorption spectra of 4NP (a), 5NG (b) and 4NC (c) at various solution pH
values.
231
xxv
Figure C7 The spectral change of 4NP and 5NG solutions during OH oxidation
experiments are shown in (a) and (c). The time profiles of absorbance at
420 nm for 4NP and 5NG are shown in (b) and (d). In (b) and (d), the black
traces represent H2O2 control experiments, while the red traces represent
OH oxidation experiments. The concentration of 4NP and 5NG solutions
are 15 µM and 8 µM, respectively.
232
Figure C8 The simple kinetic model applied to one example experiment each of 4NP
(a) and 5NG (b) OH oxidation. The shaded areas are the simulated
contribution of a newly formed colored product and the decay precursor.
The red lines represent the experimental results.
233
Figure D1 The current work was part of a collaborative field measurement at La Jolla,
CA. Measurements were performed concurrently at two locations: Mt.
Soledad (A), and Scripps Pier (B). The current paper focuses on the CIMS
data obtained at site A.
236
Figure D2 Calculated time series of the aqueous-fraction of HNCO (faq,HNCO) during
the June 1st and June 13th cloud events.
239
Figure D3 Comparison of number concentrations of cloud droplets in the ambient air
(Ndroplet >D50), and evaporation residue in the CVI (NRes) divided by the
calculated EF. Data from the June 1st event (a) and the June 13th event (b)
are shown. The dashed line represents a line with a slope of one, whereas
the solid line shows the actual linear fitting. Droplet Transmission (DT) is
obtained as the reciprocal of the slope.
240
Figure D4 The size distribution of number (black), volume (blue) and surface area
(green) concentration of cloud droplets in the ambient air during the June
1st (a) and the June 13th (b) events, monitored by the Fog Monitor. The
dashed lines represent calculated 50 % size cut-off of the CVI.
241
Figure D5 Calculated KHeff of HNCO as a function of pH, based on data reported by
[Roberts et al., 2011] is shown in (a). The measured pH of bulk cloud water
243
xxvi
samples collected during the June 1st Event (Blue) and the June 13th Event
(red) are also shown as the dashed lines. The KHeff at these two pH values
are 3.0 × 103 and 8.0 × 102 M atm-1, respectively. Based on the KHeff values
shown on (a), the theoretical aqueous fraction of HNCO (faq,HNCO) is
calculated as a function of pH and LWC (b).The calculations assume
complete Henry’s law equilibrium between the gas and aqueous phases.
Figure D6 Time series of HNCO, formic acid and ambient temperature during a
specific period of the campaign are shown in (a). Clear correlations
between these traces can be seen. The campaign-averaged diurnal profiles
are shown in (b). The peak of HNCO mixing ratio is reached at similar time
as the other traces shown here.
244
Figure D7 Linear fitting between HNCO and Black Carbon (BC) was performed for
various time periods of each measurement day, and R2 values from the
fitting are shown here. The correlation is typically strongest during morning
rush hours (5am to 8am; black). The differences are statistically significant
at the 95% confidence level. This is an indication that there might be a
primary source of HNCO during the morning rush hour.
245
xxvii
List of Appendices
Page
Appendix A Supplementary information for Chapter 3. 206
Appendix B Supplementary information for Chapter 4. 213
Appendix C Supplementary information for Chapter 5. 223
Appendix D Supplementary information for Chapter 6. 235
xxviii
Preface
This thesis is based on manuscripts that have been published in or are in preparation for submission
for publication in peer reviewed journals. Consequently there may be some overlap in material that
is presented throughout the thesis. All manuscripts included in this thesis were written by Ran
Zhao, with critical comments provided by Jonathan P. D. Abbatt. Contributions of any other
authors are described below.
Chapter 1: Introduction to Aqueous-phase Organic Chemistry in the Atmosphere
Contributions: Written by Ran Zhao with critical comments from Jonathan P. D. Abbatt.
Chapter 2: Investigation of Aqueous-Phase Photooxidation of Glyoxal and
Methylglyoxal by Aerosol Chemical Ionization Mass Spectrometry:
Observation of α-hydroxyhydroperoxide Formation
Published as: R. Zhao, A.K.Y. Lee and J.P.D. Abbatt (2012). “Investigation of Aqueous-
Phase Photooxidation of Glyoxal and Methylglyoxal by Aerosol Chemical
Ionization Mass Spectrometry: Observation of Hydroxyhydroperoxide
Formation" Journal of Physical Chemistry A 116(24): 6253-6263
Contributions: The experimental approach was developed by Ran Zhao. All experiments
described in this section were performed by Ran Zhao. The manuscript was
written by Ran Zhao with critical comments from Alex K. Y. Lee and
Jonathan P. D. Abbatt.
Chapter 3: Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic Study
Using Aerosol Time-of-Flight Chemical Ionization Mass Spectrometry
(Aerosol ToF-CIMS)
xxix
Published as: R. Zhao, E.L. Mungall, A.K.Y. Lee, D. Aljawhary and J.P.D. Abbatt
(2014). “Aqueous-Phase Photooxidation of Levoglucosan: A Kinetic and
Mechanistic Study Using High Resolution Aerosol Chemical Ionization
Mass Spectrometry (HR-Aerosol-CIMS)." Atmospheric Chemistry and
Physics, 14, 9695-9706.
Contributions: The experimental approach was developed by Ran Zhao. All experiments
using chemical ionization mass spectrometry (CIMS) described in this
section were performed by Ran Zhao and Emma L. Mungall, under the
guidance of Ran Zhao. The operation and data analysis of aerosol mass
spectrometry was done by Alex K. Y. Lee. The initial optimization of the
CIMS was performed by Dana Aljawhary. The manuscript was written by
Ran Zhao with critical comments from Jonathan P. D. Abbatt.
Chapter 4: Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):
Potential Atmospheric Impacts
Published as: R. Zhao, A.K.Y. Lee, R. Soong, A.J. Simpson and J.P.D. Abbatt (2013).
“Formation of Aqueous-Phase α-Hydroxyhydroperoxides (α-HHP):
Potential Atmospheric Impacts." Atmospheric Chemistry and Physics, 13,
5857-5872.
Contributions: The experimental approach was developed by Ran Zhao. All experiments
described in this section were performed by Ran Zhao and Alex K.Y. Lee.
The operation and data analysis of nuclear magnetic resonance (NMR)
spectrometry were conducted under the guidance of Ronald Soong and
Andre J. Simpson. The manuscript was written by Ran Zhao with critical
comments from Jonathan P. D. Abbatt.
Chapter 5: Photochemical Processing of Aqueous Atmospheric Brown Carbon
xxx
Published as: R. Zhao, A.K.Y. Lee, L. Huang, X. Li, F. Yang and J.P.D. Abbatt (2015).
“Photochemical processing of aqueous atmospheric brown carbon"
Atmospheric Chemistry and Physics Discussion 15, 2957-2996
Contributions: The experimental approach was developed by Ran Zhao. All experiments
described in this section were performed by Ran Zhao. The initial setup and
optimization of the waveguide capillary cell UV-Vis spectrophotometer
was performed by Alex K. Y. Lee. The collection and preparation of the
biofuel combustion samples were performed by Lin Huang, Xinghua Li and
Fumo Yang. The manuscript was written by Ran Zhao with critical
comments from Jonathan P. D. Abbatt.
Chapter 6: Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of
Secondary Source of HNCO in Ambient Air
Published as: R. Zhao, A.K.Y. Lee, J. Liggio, J.J.B. Wentzell, R.W. Leaitch, A.M.
Mcdonald, D. Toom-Sauntry, R.L. Modini, A.L. Corrigan, L.M. Russell,
K.J. Noone, J.C. Schroder, A.K. Bertram, L.N. Hawkins and J.P.D. Abbatt
(2014). “Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of
Secondary Source of HNCO in Ambient Air" Geophysical Research Letter
41, 6962-6969
Contributions: The overall plan for the field measurement was made by Richard W.
Leaitch, John Liggio, Lynn M. Russell and coworkers at Environment
Canada. The initial preparation of the sampling site was conducted by Rob
L. Modini, Ashley L. Corrigan, Lynn M. Russell and her research group.
Operation of the CIMS was done by Ran Zhao, Alex K. Y. Lee, Jeremy J.
B. Wentzell and John Liggio. The analysis of the CIMS data was conducted
by Ran Zhao. The operation and data analysis for Black Carbon
measurements were conducted by Jason C. Schroder and Allan K. Bertram.
The O3 data was obtained and processed by Anne Marie Mcdonald. The
xxxi
development of the counterflow virtual impactor (CVI) was done by Kevin
J. Noone. The operation of the CVI was conducted collaboratively by all
the coworkers mentioned above. The data analysis of CVI was conducted
by Jason C. Schroder. The manuscript was written by Ran Zhao with
critical comments from Jonathan P. D. Abbatt.
Chapter 7: Conclusions and Future Research
Contributions: Written by Ran Zhao with critical comments from Jonathan P. D. Abbatt.
1
Chapter 1
Introduction to Aqueous-phase Organic Chemistry in the Atmosphere
2
1.1 Secondary Organic Aerosol and Its Environmental Impacts
Aerosol refers to suspended particulate matter in the atmosphere and plays an important role in
two critical and urgent issues: air quality and global climate change. The connection between
adverse health effects and air pollution has been well established (Dockery et al. 1993), and
particulate matter, in particular, causes increased risk of a variety of cardiovascular diseases (Pope
et al. 2002). Aerosol affects the global climate by interacting with incoming solar radiation (the
direct radiative effect) and affecting the formation and lifetime of clouds (the indirect radiative
effects). Organic particulate matter forming in the atmosphere from precursor volatile organic
compounds (VOCs) is referred to as secondary organic aerosol (SOA) and comprises a substantial
fraction of submicron particulate matter (Zhang et al. 2007). Understanding the formation and
evolution of organic matter represents an essential step towards a sound assessment of the
environmental impact of aerosol. However, the complexity of the atmospheric chemical matrix
and its chemistry place major limitations on our ability to predict the amount and impact of SOA
in the atmosphere. Consequently, aerosol bears the single largest uncertainty in its radiative forcing
among that of all atmospheric drivers (Stocker et al. 2013).
1.2 Formation Mechanisms of SOA
1.2.1 Gas-Particle Partitioning Theory – the Traditional Understanding of SOA Formation
As the atmosphere is an oxidizing environment, the precursor VOCs are oxidized in the gas phase
and form more functionalized and oxygenated compounds which are categorized as semi-volatile
or non-volatile organic compounds. Additional functional groups on a molecule reduce the
molecular vapor pressure by orders of magnitude (Kroll and Seinfeld 2008) and induce partitioning
to the condensed phase to form SOA. The formation of SOA has been described by the gas-particle
partitioning theory (Odum et al. 1996, Pankow 1994). In this traditional view of SOA formation,
chemical reactions occur only in the gas-phase, with the semi-volatile products partitioning
between the gas and the condensed organic phases. The gas-particle partitioning is assumed to be
an equilibrium process, controlled by the saturation vapor pressures of the partitioning compounds,
the concentrations of the partitioning compounds in the gas and the condensed phases, the size of
the condensed organic phase, and the activity coefficient of the compounds in the condensed phase.
3
Partitioning of gas-phase organic compounds is considered to occur only to a pure organic
condensed phase, and contributions of aqueous phase and inorganic components are neglected.
1.2.2 Discrepancies between Models and Measurements
Studies from a decade ago found that models based on the traditional gas-particle partitioning
theory could not reproduce certain aspects of ambient aerosol, indicating unrecognized SOA
formation mechanisms or precursors. The first aspect is the SOA mass, which is significantly
underestimated in the models. Volkamer et al. (2006) have shown that this underestimation has
been observed in multiple field campaigns, with the gap widening as the locations of the
measurement are further away from the emission source. The ambient SOA mass can be up to a
hundred times of that modelled in the free troposphere (Heald et al. 2005).
The model prediction of SOA was significantly improved later by a volatility basis set approach,
where organic compounds are lumped into prescribed logarithmic volatility bins (Donahue et al.
2006). The VBS captures SOA formation from semi-volatile organic compounds which were
neglected in the traditional two-product model (Robinson et al. 2009). While the VBS improved
the prediction of SOA mass (Hodzic et al. 2010), it still fails in reproducing other aspects of SOA,
such as the O/C ratio and the formation of oligomeric compounds.
A substantial amount of oligomeric compounds exist in ambient and chamber-generated SOA
(Kalberer et al. 2004, Graber and Rudich 2006). These compounds, highly functionalized and
unresolved, are also referred to as Humic-like substances (HULIS) due to their spectral similarities
to humic acid (Graber and Rudich 2006). While the term oligomer strictly refers to a molecule
with a few repeating monomer unites, it is often used in the SOA community as molecule with
large molecular weight. The formation of oligomeric compounds cannot be explained by the
traditional view of gas-particle partitioning theory, as oligomerization reactions in the gas phase
are unlikely. Alternatively, atmospheric aqueous phases (cloud, fog, and aerosol liquid water) have
emerged as important reaction media where highly functionalized and oligomeric compounds can
form.
1.2.3 Aqueous-phase Chemistry – a New Formation Mechanism of SOA
Cloudwater has long been known as an important reaction medium in the atmosphere. Motivated
by endeavors to understand acid rain formation, detailed investigations have been performed for
4
inorganic chemistry, particularly that associated with sulfate formation in cloudwater (Chameides
1984, Jacob 1986, Pandis and Seinfeld 1989). Although the abundance of organic compounds in
atmospheric aqueous phases has been realized, the investigations have been limited to chemistry
of a small group of species. Formaldehyde is the most thoroughly studied organic compound
because its chemistry in cloudwater affects sulfate formation (Olson and Hoffmann 1989) and the
budget of HOx (i.e. OH and HO2 radicals) and O3 in the gas phase (Lelieveld and Crutzen 1991).
Figure 1.1: A schematic illustration of SOA formation via the gas-particle partitioning theory and the aqueous
pathway.
Blando and Turpin (2000) for the first time hypothesized that organic chemistry in cloudwater can
give rise to SOA components, and that a wide variety of organic compounds, including small
carbonyls, organic hydroperoxides and carboxylic acids, can be potential SOA precursors. These
compounds are not considered as SOA precursors by the traditional gas-particle partitioning
theory, given their small molecular weight and high vapor pressure. However, these compounds
are highly functionalized and hydrophilic, hence they can readily dissolve into atmospheric
aqueous phases. Numerous studies from the past decade have confirmed that aqueous-phase
reactions of these compounds indeed give rise to non-volatile products which contribute to SOA
upon water evaporation (Ervens et al. 2011, McNeill 2015). Thus, aqueous chemistry, also referred
5
to as aqueous-phase processing of organic compounds, represents an unrecognized formation
pathway of SOA involving unrecognized precursors. The overall processes involved in the
aqueous pathway of SOA formation are schematically illustrated in Figure 1.1, along with those
of the traditional gas-particle partitioning theory. The detailed aqueous-phase chemistry
contributing to aqueous SOA formation will be discussed in Sections 1.5 to 1.7.
1.3 Atmospheric Aqueous Phases and Partitioning of Organic Compounds.
1.3.1 Aqueous Phases in the Atmosphere
Liquid water is ubiquitous in the atmosphere, forming aqueous phases with highly diverse
characteristics. Liquid water is associated with most types of particulate matter, referred to as
aerosol liquid water (ALW). Under sub-saturated conditions (RH < 100 %), the uptake of water in
a particle is an equilibrium process, with ALW expanding with increasing RH. In the case of a
liquid particle, the growth of the particle as a function of RH follows its hygroscopic growth curve
(Finlayson-Pitts and Pitts 2000). Particles of inorganic salts remain solid at low RH values and
rapidly undergo deliquescence into liquid particles at their deliquescence RH. After deliquescence,
the particle grows continuously as the RH further increases. The specific deliquescence RH and
growth curve of a particle depend and the hygroscopicity of its chemical components. Hygroscopic
growth can increase the diameter of a particle up to a factor of 3 as the RH reaches 100 %
(Finlayson-Pitts and Pitts 2000), resulting in a typical liquid water content (LWC) of up to 10 µg
m-3 in the ambient atmosphere (Volkamer et al. 2009), but can be much higher under polluted
conditions (Bian et al. 2014).
Under supersaturated conditions (i.e. RH > 100 %), the uptake of water remains an equilibrium
process until the RH reaches the critical supersaturation or the particle grows to reach its critical
radius. At this point, the particle will continue taking up water and growing into a fog or cloud
droplet. The critical supersaturation and radius for a given particle are controlled by its size and
the hygroscopicity of its chemical components (Wong et al. 2011). The process of a particle
growing to a droplet is referred to as activation and is accompanied by orders of magnitude increase
in LWC, with typical LWC in cloud and fog being 0.1 to 1 g m-3 (Volkamer et al. 2009).
6
While continuous growth of cloud droplets leads to precipitation, only 10 % of the droplets actually
precipitate, with the majority evaporating and regenerating a particle (Seinfeld and Pandis 2006).
Thus a particle undergoes repeated activation and evaporation cycles before it is removed from the
atmosphere. Cloud/fog water and ALW are usually considered as two distinct reaction media due
to their differences in droplet size, LWC, salinity and surface area to volume ratio (Volkamer et
al. 2009, Ervens and Volkamer 2010, Lim et al. 2010, Ervens et al. 2011). Both ALW and
cloud/fog water are important for aqueous-phase chemistry involved in SOA formation (Figure
1.1). More recent studies have shown that chemical reactions can occur also during the process of
droplet evaporation (De Haan et al. 2011, Zarzana et al. 2012, Galloway et al. 2014).
1.3.2 Partitioning of Organic Compounds to Aqueous Phase
As described in Section 1.2.3, important aqueous SOA precursors can be highly functionalized
compounds with relatively small molecular weight. Since these compounds exhibit high vapor
pressure, they are introduced into atmospheric aqueous phases via gas-aqueous phase partitioning.
The gas-aqueous equilibrium of a compound is described by its Henry’s law constant, expressed
as the ratio of its aqueous-phase concentration and gas-phase vapor pressure (M atm-1). If a
compound undergoes equilibrium reactions in the aqueous phase, e.g. acid dissociation for acidic
compounds and hydration reactions for aldehydes, the Henry’s law constant of this compound
appears to be enhanced. The gas-aqueous equilibria of such compounds are described instead by
their effective Henry’s constants (Heff) which consider the additional aqueous-phase processes.
Strictly, Heff describes the enhanced partitioning of a compounds in ideal solutions without further
chemical transformation (i.e. the enhancement is only due to hydration and acid-dissociation
equilibria). However, we note that Heff is used here as the enhanced Henry’s law constant as a
result of all kinds of chemical equilibria occurring in the aqueous phase. Heff of a compound can
be orders of magnitude higher than its intrinsic Henry’s law constant, as represented by the case
of glyoxal. Being the smallest α-dicarbonyl compound, glyoxal establishes two hydration
equilibria in the aqueous phase, enhancing its Henry’s law constant from 1.9 M atm-1 to 3.6 × 105
M atm-1 (Ip et al. 2009), making it partition readily into atmospheric aqueous phases (Kroll et al.
2005, Liggio et al. 2005, Volkamer et al. 2007).
Assuming Henry’s law equilibrium, one can calculate the fraction of a compound residing in the
aqueous phase (faq) in a given volume of air (Eqn. 1.1):
7
𝑓𝑎𝑞 = 𝑅𝑎𝑞/𝑔𝑎𝑠
1+ 𝑅𝑎𝑞/𝑔𝑎𝑠 (1.1)
where Raq/gas is the dimensionless ratio of the equilibrium concentration of a compound in the
aqueous and the gas phases, respectively, and is calculated by Eqn. 1.2 (Seinfeld and Pandis 2006):
𝑅𝑎𝑞/𝑔𝑎𝑠 = 10−6𝐻𝑒𝑓𝑓𝑅𝑇𝐿 (1.2)
where 10-6 is a conversion factor, R is the gas constant (0.082 atm L mol-1 K-1), T is the temperature
(K), and L is the LWC (g m-3). Compounds with larger faq will more likely participate in aqueous-
phase chemistry. The calculated faq as a function of Heff for three LWC values (1 g m-3, 0.1 g m-3,
and 10 µg m-3) are shown in Figure 1.2. These three LWC values are chosen to represent typical
cloud, fog and ALW, respectively (Volkamer et al. 2009, Daumit et al. 2014). A large gap exists
between the LWC of cloud/fog and ALW due to the enormous increase of LWC during particle
activation (see Section 1.3.1). Also shown in Figure 1.2 are selected compounds with their reported
Heff values. Glyoxal and methylglyoxal are widely accepted as important aqueous-phase SOA
precursors, with a significant fraction residing in the aqueous-phase when cloud or fog is present.
Oxalic acid is a major OH oxidation product of glyoxal and methylglyoxal (Carlton et al. 2007,
Tan et al. 2009), residing nearly entirely in cloud and fog, and partially in ALW. SOA precursors
that are important in the gas-particle partitioning theory, such as α-pinene and toluene, reside
nearly entirely in the gas phase and do not participate in aqueous-phase chemistry. O3 and nitrogen
dioxide (NO2) play critical roles in gas-phase photochemistry, but are less important in the aqueous
phase due to their small Heff.
The Heff values of organic compounds can be affected by a number of factors. Lower temperature
generally enhances Heff values of oxygenated compounds, but reduces those of volatile
compounds, such as α-pinene and n-alkanes (Wania et al. 2014). Dissolved inorganic species can
affect the solubility of organic compounds, resulting in both the salting-out (reduction of Heff) and
salting-in (enhancement of Heff) effects. Salting-out effect is relevant to a wide spectrum of water
soluble organic compounds, with different salts exhibiting different magnitude of effects (Wang
et al. 2014). A significant salting-in effect was observed for glyoxal with sulfate (Ip et al. 2009).
While the mechanism of the salting-in effect is commonly considered to be due to reactions
between glyoxal and inorganic salts, Yu et al. (2011) have observed that inorganic salts affect the
8
hydration equilibria of glyoxal. For acidic organic compounds (e.g. carboxylic acids and phenols),
Heff values are significantly affected by the solution pH, as the dissociated ions are much more
soluble than the non-dissociated forms. The Heff of oxalic acid shown in Figure 1.2 is at pH 4.
Besides dissolution, organic compounds can be introduced to atmospheric aqueous phases via
nucleation scavenging (Herckes et al. 2013). When a particle activates into a cloud or fog droplet,
existing organic compounds in the original particle can dissolve into the aqueous phase. The
fraction of a compound X scavenged by nucleation scavenging can be described by its scavenging
efficiency (η) (Herckes et al. 2013):
𝜂 = 1 − 𝑋𝑖𝑛𝑡𝑒𝑟
𝑋𝑝𝑟𝑒 (1.3)
where Xinter and Xpre are the concentrations of X in interstitial aerosol and in aerosol prior to the
cloud or fog event, respectively. The η values of organic compounds have been shown to correlate
with their water solubility (Facchini et al. 1999, Collett et al. 2008), as well as the hygroscopicity
of the particles with which they are associated (Gilardoni et al. 2014). Collet et al. (2008) have
determined an average η value of 0.90 for organic compounds scavenged by radiation fog in
California. More water soluble compounds exhibit higher η values, with those for long chain
alkanes ranging from 0.5 to 0.7, while those for C6 to C9 dicarboxylic acids and levoglucosan
reaching nearly unity.
9
Figure 1.2: Calculated aqueous fraction (faq) under three selected LWC as a function of effective Henry’s law
constant (Heff). The figure also shows Heff values of selected compounds at 298 K, along with their molecular
structures. References: glyoxal (Ip et al. 2009), methylglyoxal (Zhou and Mopper 1990), oxalic acid (pH 4)
(Compernolle and Muller 2014), α-pinene (Leng et al. 2013), toluene (Kim and Kim 2014), O3 (Gershenzon et al.
2001) and NO2 (Chameides 1984).
1.4 Production and Concentration of OH Radicals in Atmospheric Aqueous Phases
The hydroxyl (OH) radical is the most important oxidant in atmospheric aqueous phases and reacts
with many dissolved organic compounds at nearly diffusion limited rates (Herrmann et al. 2010).
Despite the pivotal role that OH radical plays in atmospheric aqueous phases, its sources,
concentration and sinks are still highly uncertain.
1.4.1 Gas-Phase Partitioning and in-situ Formation of OH Radical
OH radical can be introduced to atmospheric aqueous phases both from the gas phase and via in-
situ formation in the aqueous phase. The reactive uptake of gas-phase OH to an aqueous particle
can be described by its 1st-order loss rate from the gas phase (Lelieveld and Crutzen 1991):
− 𝑑[𝑂𝐻]𝑔𝑎𝑠
𝑑𝑡= (
𝑟2
3𝐷𝑔𝑎𝑠+
4𝑟
3𝜔𝛼)−1[𝑂𝐻]𝑔𝑎𝑠 (1.4)
where [OH]gas, Dgas, and ω are the gas-phase concentration (molecule cm-3), the gas-phase
diffusion coefficient (cm2 s-1), and the mean gas-phase velocity of OH radicals (cm s-1),
respectively. The term r is the radius of the particle or droplet (cm), and α is a dimensionless
accommodation coefficient. The calculated uptake rate of OH (M s-1) as a function of particle
diameter is shown in Figure 1.3, assuming [OH]gas = 4 × 106 molecule cm-3, Dgas = 0.1 cm2 s-1, T
= 298 K and three different α values at 1, 0.1 and 0.01 to represent the highly variable mass
accommodation coefficient of OH.
Also included in Figure 1.3 are the results from studies where OH production rates in a variety of
atmospheric aqueous phases were investigated. The production rate of OH radicals in cloud, fog
and rain water is commonly determined by adding an OH probe compound into the sample and
monitoring the formation of a product compound with simulated or ambient irradiation (Faust and
10
Allen 1993, Arakaki and Faust 1998, Anastasio and McGregor 2001, Zuo 2003, Albinet et al.
2010). For aerosol liquid water, due to a lack of a direct monitoring method, the measurements
have been done for the water extract of collected particles (Anastasio and Jordan 2004, Arakaki et
al. 2006, Anastasio and Newberg 2007, Zhou et al. 2008, Nomi et al. 2012). The in-situ production
rate of OH in atmospheric aqueous phases represents one of the largest uncertainties in modeling
radical chemistry in these reaction media (Ervens et al. 2014).
As the particle size increases, the uptake rate from the gas phase decreases rapidly due to an
increasing particle volume and the limitations incurred by gas-phase diffusion. The in-situ
formation rate of OH radical also tends to be smaller in larger droplets due to dilution of OH
precursors. The conditions employed in the studies shown in Figure 1.3 are highly variable, as
summarized in Table 1.1. Experimental photon fluxes in these studies have been normalized to
ambient fluxes at different locations and time, therefore inter-comparison of the reported OH
production rates is not straightforward. However, the results all point towards a conclusion that in-
situ formation of OH radicals can be comparable and at times the dominant, source of OH radical
in atmospheric aqueous phases.
Figure 1.3: Calculated gas-particle partitioning rates and measured in-situ formation rates of OH radicals as a function
of particle diameter. The calculated rates are based on three (1, 0.1 and 0.01) values of the mass accommodation
coefficient (α), and the measured in-situ formation rates are compiled based on a number of studies, the conditions of
which are summarized in Table 1.1.
11
Table 1.1: Conditions used in the assessment of the in-situ production rate of OH radicals
Literature
Sample
Type
Particle
size1
Light
Source
OH
probe2
Normalization to ambient
photon flux
Faust and Allen, 1993 Cloud/Fog B 313 nm B Equinox, midday
Arakaki and Faust, 1998 Cloud B 313 nm B Equinox, Zenith angle=36˚
Anastasio and McGregor, 2001 Fog M 313 nm BA Winter solstice, midday at
Davis CA
Zuo, 2003 Fog A 313 nm HMSA Autumn solar noon
Anastasio and Newberg, 2007 Sea salt M Xe lamp BA Summer solstice
Zhou et al., 2008 Laboratory
Sea Salt A sunlight BA
Summer solstice, tropical
midday
Albinet et al., 2009 Rain B 365 nm B Summer midday at 45 ˚N
1M: Measured and specified in the original literature; A: Based on assumptions made in the original literature; B: Assumed from typical size
ranges of corresponding atmospheric aqueous phases (5 – 50 µm for cloud and fog, > 50 µm for rain).
2B:benzene; BA: benzoic acid; HMSA: hydroxymethanesulfonate
1.4.2 Mechanisms of in-situ Formation of OH Radical
A variety of chemical reactions can lead to in-situ formation of OH radicals in the aqueous phase.
O3 can partition from the gas phase and react with HO2 or its dissociated form, O2- (pKa of HO2 is
4.9) to form OH in cloudwater (Jacob 1986, McElroy 1986). However, this reaction has been
shown to be highly pH dependent, as O3 reacts mostly with O2- (Sehested et al. 1984). This
chemistry may be important in cloudwater, where LWC is high and acidity is low, but may be of
less importance in ALW. Direct photolysis of inorganic chromophores (i.e. NO3-, NO2
- and H2O2)
can be an important OH source in atmospheric aqueous phases. OH radical production from these
chromophores has been investigated in detail (Zellner et al. 1990, Goldstein et al. 2007, Herrmann
et al. 2010). Iron-catalyzed OH generation via Fenton and photo-Fenton reactions is particularly
important. Arakaki and Faust (1998) have observed that Fenton chemistry is the most important
in-situ formation mechanism based on measurements using authentic cloudwater samples. Ervens
et al. (2014) have also shown in their model that Fenton chemistry is likely the most important
mechanism in both cloudwater and ALW.
A less well understood OH source is from dissolved organic compounds. Dissolved organic carbon
(DOC) has been previously shown to be a major OH source in seawater (Mopper and Zhou 1990).
12
Emerging evidence also suggests the importance of this OH source in atmospheric aqueous phases.
Anastasio and Newberg (2007) have shown that the contribution of NO3- as an OH source
decreases in smaller sea salt aerosol, indicating an increasing contribution from organic
chromophores. Arakaki et al. (2006) have observed an unknown OH source exhibiting positive
correlations with the concentration of DOC. The identity of the organic chromophores and the
mechanisms of OH generation are currently unclear. Organic hydroperoxides can be an important
class of OH source candidates, given that they can be highly abundant in ALW (Docherty et al.
2005, Arellanes et al. 2006, Wang et al. 2011). However, due to their unstable nature, there is a
lack of an online detection method for organic peroxides in the aqueous phase, which significantly
hinders our understanding of their abundance and chemistry.
1.4.3 Diffuso-reactive Length (dL) of OH Radical
Due to its significant reactivity, OH radicals introduced to a particle via gas-phase partitioning
may not diffuse through the entire particle. A common approach to assess the diffusion of OH
radical is to obtain the diffuso-reactive length (dL) which describes the distance an OH radical
typically travels before reacting away and is calculated using Eqn. 1.5 (Hanson et al. 1994):
𝑑𝐿 = √𝐷𝑎𝑞
𝑘𝐼 = √𝐷𝑎𝑞
𝑘𝐷𝑂𝐶𝐼𝐼 [𝐷𝑂𝐶]
(1.5)
While the OH radical can react with inorganic species such as nitrate, SO2, H2O2 and halogen
species, the dominant sink of the OH radical is DOC (Arakaki and Faust 1998, Anastasio and
McGregor 2001, Anastasio and Newberg 2007). The 1st-order loss rate coefficient (kI) of OH
radical can be approximated by the product of the concentration of dissolved organic carbon
([DOC]) and an averaged 2nd-order rate constant [kIIDOC] of OH reacting with DOC. As the
majority of DOC in atmospheric aqueous phases remains unspeciated (Herckes et al. 2013),
Arakaki et al. (2013) have proposed an averaged, carbon-based kIIDOC value of 3.8 × 108 mol-C L-
1 s-1. The dL over a wide range of [DOC] is calculated and shown in Figure 1.4, using a Daq value
of 1 × 10-5 cm2 s-1 (Seinfeld and Pandis 2006), and the kIIDOC proposed by Arakaki et al. (2013).
Also shown in Figure 1.4 are the ranges of DOC concentration relevant to different types of
atmospheric aqueous phases. The values for marine clouds, orographic clouds and polluted fogs
are adopted from Herckes et al. (2013) which summarizes measured DOC concentrations across
13
the globe. There is no direct measurement for [DOC] in aerosol liquid water, but it has been
assumed to be at the molar level (Volkamer et al. 2009, Ervens and Volkamer 2010, Ervens et al.
2014).
The calculated values of dL are orders of magnitude smaller than the radius of the corresponding
hydrometeors, implying that OH radical introduced from the gas phase may reach only a small
portion of a particle or droplet. Recent studies also revealed enhanced viscosity of organic aerosol
(Virtanen et al. 2010, Zhou et al. 2012, Slade and Knopf 2014) as well as liquid-liquid separation
(You et al. 2012) at low RH conditions. When the diffusion of OH radicals is further hindered by
these conditions, in-situ formation of OH is expected to gain importance in aqueous-phase
processing of organic compounds relative to the gas phase.
Figure 1.4: The diffuso-reactive length (dL) of OH as a function of dissolved organic carbon (DOC) concentrations.
The loss rate of OH radicals is based on the averaged, carbon based kIIDOC value (Arakaki et al. 2013). The horizontal
bars represent the approximate DOC ranges in a variety of atmospheric aqueous phases.
14
Figure 1.5: Structures and OH rate constants (kIIOH, 298K) of organic compounds relevant to atmospheric
aqueous phases (Buxton et al. 1988, Herrmann 2003, Tan et al. 2009, Herrmann et al. 2010, Tan et al.
2012).
15
1.4.4 Steady State Concentrations of OH Radical
The steady state concentration of OH radical in aqueous aerosol, [OH]ss, can be estimated from
the ratio of its production rate (POH) and its 1st-order loss coefficient (kI):
[𝑂𝐻]𝑠𝑠 = 𝑃𝑂𝐻
𝑘𝐼⁄ (1.6)
Arakaki et al. (2013) have summarized the steady state concentration of OH radicals in different
types of atmospheric aqueous phases. Although the sources and sinks span orders of magnitude
difference among different atmospheric aqueous phases, the steady state concentration of OH
radical remains within a relatively narrow range: 0.5 to 7 × 10-15 M. However, discrepancies exist
between this measurement-based approach and other modeling-based approaches (Herrmann et al.
2010), where OH concentrations tend to be higher and to vary by orders of magnitude among
different atmospheric aqueous phases. More data and improved techniques are required to better
constrain this important parameter.
1.5 OH Reactivity and Reaction Mechanisms
1.5.1 Initiation of the Radical Chain
Aqueous-phase OH oxidation of organic compounds has been investigated widely (Buxton et al.
1988). Figure 1.5 compiles the structures and OH reactivity (kIIOH) of compounds relevant to
atmospheric aqueous-phase processing. Similar to gas-phase chemistry, the OH radical reacts with
aromatic and unsaturated aliphatic compounds essentially at the diffusion limit through radical
addition reactions (Figure 1.6, (a) and (b)).
In the absence of radical addition, OH radicals undergo rapid H-abstraction (Figure 1.6, (c)).
Organic compounds relevant to the atmospheric aqueous phases usually contain highly oxygenated
functional groups and react rapidly with OH radicals. As oxygenation proceeds further, the
reactivity drops significantly due to lack of easily abstractable hydrogens (e.g. oxalic acid and
pyruvic acid). Since dissolved molecular oxygen is abundant, reactions (a) to (c) in Figure 1.6 also
display the subsequent addition of O2 after the initiation step.
As the general rules of OH reactivity in the gas-phase chemistry are also applicable to the aqueous
phase, there is an ongoing effort to establish structure activity relationships (SAR) relevant to
16
atmospheric aqueous phases (Monod et al. 2005, Monod and Doussin 2008, Wang et al. 2009,
Doussin and Monod 2013), inspired by the gas-phase SAR (Kwok and Atkinson 1995). With the
current expansion of the aqueous-phase database, such SAR are expected to gain accuracy and
applicability.
Figure 1.6: General OH radical reactions.
17
1.5.2 Propagation of Radical Chain
Due to low Henry’s law constants, NOx does not play as pronounced a role in the aqueous phase
(Figure 1.2) as it does in the gas phase (Figure 1.6 (d)). Therefore, the radical propagation
resembles the low-NOx regime in the gas phase. In other words, the fate of peroxy radicals (RO2)
is dominated by reactions with another RO2 or with a hydroperoxy radical (HO2), rather than with
NO. Peroxy radical chemistry in the aqueous phase is highly complex and has been reviewed in
detail (von Sonntag et al. 1997). The RO2 + RO2 reaction can propagate the radical chain via
reactions (e) and (f) in Figure 1.6.
1.5.3 Termination of Radical Chain
The RO2 + RO2 reactions can also terminate the radical chain via the Russell mechanism (Figure
1.6 (g)), giving rise to a carbonyl and an alcohol. Another RO2 or an HO2 radical can also react
with RO2 to form organic peroxides (ROOR) and organic hydroperoxides (ROOH), respectively
(Figure 1.6 (h), (i)). In a modeling study, Ervens and Volkamer (2010) demonstrated that aerosol
liquid water favors formation of ROOR than ROOH. However, their results are significantly
dependent on the unimolecular decomposition rate of RO2 radicals, which represents an area that
is poorly constrained by experiments.
1.6 OH Radical Reactions Unique to the Aqueous Phase
1.6.1 Efficient Conversion of Aldehydes to Carboxylic Acids
Unique radical chemistry takes place in the aqueous phase, giving rise to products that are not
produced in the gas-phase and hence not considered in the traditional gas-particle partitioning
theory. One is the rapid conversion of aldehydes to carboxylic acids, facilitated by hydration of
the aldehyde functional group. Earlier studies have established that formic acid arises from OH
oxidation of formaldehyde in the aqueous phase, contributing to cloudwater acidity (Chameides
1984, Seinfeld and Pandis 2006). Formation of a wider variety of carboxylic acids has drawn
attention in recent years due to their contribution to SOA formation.
A series of reactions leading to carboxylic acid formation is shown in Figure 1.7. Aldehydes exist
in equilibrium with their geminal diols in the aqueous phase (Figure 1.7 (A) and (B)). OH radical
can abstract a hydrogen atom from both the aldehydic and geminal diol forms, forming their
respective alkyl radicals (Figure 1.7 (C) and (D)). These two types of alkyl radicals are also in a
18
hydration equilibrium, as shown in the case of acetyl radical (Schuchmann and von Sonntag 1988).
In the next step, oxygen molecules add to the alkyl radicals to form two types of peroxy radicals.
The peroxy radical of the geminal diol (Figure 1.7 (F)) dissociates rapidly to form a carboxylic
acid (Figure 1.7 (G)). The acylperoxy radical (Figure 1.7 (E)) can participate in other types of
chemistry (i.e. with RO2 or HO2), but can also be hydrated to form a carboxylic acid (Villalta et
al. 1996).
Numerous laboratory studies have observed rapid and significant organic acid formation from
glyoxal (Carlton et al. 2007, Tan et al. 2009, Lim et al. 2010), methylglyoxal (Altieri et al. 2008,
Tan et al. 2012), and glycolaldehyde (Perri et al. 2009, Ortiz-Montalvo et al. 2012). This formation
pathway for carboxylic acid is absent in the gas phase where formation of geminal diols is much
less likely. For this reason, organic acids, in particular oxalic acid, have been considered as tracers
for cloudwater processing in field measurements (Sorooshian et al. 2007a, 2007b). In attempts to
model aqueous phase SOA formation, organic acids are commonly used to trace the yield and mass
of aqueous SOA (Lim et al. 2010, McNeill et al. 2012, Lim et al. 2013).
Figure 1.7: Mechanisms of rapid carboxylic acid formation in the aqueous phase.
19
1.6.2 Rapid OH Oxidation of Carboxylate
OH oxidation of carboxylate species is more rapid than oxidation of the non-dissociated carboxylic
acid, resulting in a pH dependence in the reactivity of organic acids. Figure 1.8 compiles the
reactivity of a suite of carboxylic acids with their corresponding carboxylates, and this trend is
observed for all the species. More rapid OH oxidation of carboxylate is due to a charge transfer
reaction (Figure 1.9) in addition to H-abstraction (Ervens et al. 2003, Seinfeld and Pandis 2006).
The charge transfer reaction explains why oxalate dianion, a compound without any hydrogen
atoms, can also react with the OH radical. An interesting trend for diacids is that the monoanions
tend to be the most reactive towards OH radical.
Sorooshian et al. (2007a) have observed higher cloudwater oxalic acid concentrations in larger and
less acidic cloud droplets. The authors proposed that glyoxylic acid, the precursor of oxalic acid,
has dissociated in the less acidic droplets and reacted more efficiently. This study implies that
cloudwater acidity may alter the lifetime of organic acids.
Figure 1.8: OH reactivity (kIIOH) of carboxylic acids and corresponding carboxylates. Acronym: formic acid (FA),
glyoxylic acid (GA), pyruvic acid (PA), lactic acid (LA), malic acid (MA), oxalic acid (OA). References: FA, GA and
OA (Tan et al. 2009), PA (Schaefer et al. 2012), LA and MA (Herrmann et al. 2010).
20
Figure 1.9: Charge transfer reaction of carboxylate.
1.6.3 Radical Induced Oligomerization
Oligomeric compounds have been observed in laboratory OH oxidation experiments, which may
represent a formation pathway of HULIS observed in the ambient atmosphere. A radical-radical
recombination mechanism has been postulated by Turpin and coworkers (Lim et al. 2010, Tan et
al. 2012, Lim et al. 2013), where two carbon-centered radicals form a new covalent bond and give
rise to an oligomeric product (Figure 1.10 (a)). In OH oxidation of glyoxal and methylglyoxal,
radical-radical recombination gave rise to products with larger carbon numbers than the reactants.
The radical-induced nature of these reactions has been confirmed by testing the role of dissolved
molecular oxygen (Renard et al. 2013). Oxygen suppresses oligomerization by forming RO2
radicals with carbon-centered radicals. Renard et al. (2013) observed an enhancement of
oligomerization in the OH oxidation of methylvinylketone (MVK) as soon as dissolved oxygen
was depleted in their reaction system, confirming the radical nature of the oligomerization.
As the atmospheric aqueous phases are saturated with oxygen, oligomerization becomes important
only when the concentrations of the carbon-centered radicals, hence the concentrations of the
precursor organic compounds, are high enough to compete with dissolved oxygen. Lim et al.
(2010, 2013) have shown that radical-radical recombination gains importance in aqueous particles,
i.e. when glyoxal and methylglyoxal concentrations are at millimolar levels or higher. This
conclusion has later been experimentally confirmed by (Renard et al. 2013, 2014, 2015), where
they found oligomers as the dominant products of MVK OH oxidation when the MVK initial
concentrations were at 2 mM or higher. When the reactant contains unsaturated aliphatic
structures, radical addition to C=C double bonds can proceed, propagating the radical chain and
giving rise to oligomers (Figure 1.10 (b)). Renard et al (2013, 2014) proposed this mechanism in
the OH oxidation of MVK, while Kameel et al. (2013) also proposed similar mechanisms in OH
oxidation of isoprene.
21
Figure 1.10: Radical induced oligomerization mechanism, with one example each for radical-radical recombination
(a) (Guzman et al. 2006, Lim et al. 2010) and radical propagation on double bonds (b) (Renard et al. 2013).
Radical induced oligomerization has also been observed from aromatic compounds.
Oligomerization mechanisms are initiated by both carbon-centered and phenolic radicals (Sun et
al. 2010, Smith et al. 2014, Yu et al. 2014). Oligomers from aromatic compounds contain extensive
electron conjugations and are accompanied by significant light absorptivity (Chang and Thompson
2010, Yu et al. 2014), which may be partly responsible for the light absorption observed for HULIS
(Graber and Rudich 2006).
1.6.4 Radical Induced Organosulfate Formation
Radical chemistry can be responsible for organosulfate compounds observed in laboratory
experiments and ambient particle samples. A number of laboratory studies (Galloway et al. 2009,
Perri et al. 2010) observed organosulfate formation only under irradiated conditions, indicating the
importance of radical chemistry.
Perri et al (2010) have proposed a radical-radical recombination mechanism, where an alkyl radical
recombines with a sulfate radical to form organosulfates. Sulfate radical arises from H-abstraction
of sulfuric acid and bisulfate by OH radical. This mechanism is in analogy to the oligomerization
via radical-radical recombination (Figure 1.10, (a)). More recently, Schindelka et al. (2013) have
proposed a sulfate radical addition mechanism, in analogy to Figure 1.10 (b). They have also
shown that the amount of organosulfate formation scales with the number of laser pulses from
which sulfate radical is generated in their experiment. In a modeling study, McNeill et al. (2012)
found that organosulfate formation is especially important in ALW, where reactant concentrations
are high, and proposed organosulfates as tracers for chemistry occurring in aqueous particles.
22
1.7 Non-radical Chemistry in the Aqueous-phase – Nucleophilic Addition Reactions
Non-radical chemistry also gives rise to processing of organic compounds in the aqueous phase.
More than a decade ago, Jang et al. (2002) proposed that acid-catalyzed nucleophilic addition
reactions of carbonyl compounds (e.g. hydration, hemiacetal formation, and aldol condensation)
represent a mechanism of particle-phase chemistry that is responsible for additional SOA growth.
Nucleophilic addition plays a central role in the aqueous phase, giving rise to processing of organic
compounds via non-radical pathways. A classic example of aqueous-phase nucleophilic addition
is the formation of hydroxyalkylsulfonate from S(IV) species and a variety of aldehydes (Olson
and Hoffmann 1989). This group of compounds act as a reservoir of S(IV) compounds in
cloudwater and eventually contribute to cloudwater acidity. In recent years, as the connection
between aqueous-phase organic chemistry and the formation of SOA becomes clearer, a wide
variety of nucleophilic addition reactions have been investigated, with important atmospheric
implications. These reactions are expected to be particularly important in aerosol liquid water
where reactant concentrations are orders of magnitude higher than in cloudwater. The process of
droplet evaporation can also accelerate nucleophilic addition reactions (De Haan et al. 2011,
Zarzana et al. 2012, Galloway et al. 2014), as the reactant concentrations are temporarily enhanced
during evaporation. Carbonyl compounds are the most important electrophiles in the atmospheric
aqueous phases, and their chemistry is discussed in this section.
1.7.1 General Reaction Mechanism of Nucleophilic Addition
Due to the large electronegativity of oxygen, the electron density on a carbonyl group (C=O) is
significantly shifted to the oxygen atom. The carbon is hence electrophilic and subject to attack by
electron rich nucleophiles (Figure 1.11 (a)). The electrophilicity of the carbonyl group depends on
the chemical nature of the adjacent functional groups (R), in terms of both steric and electronic
effects (McMurry 2004). The bulkier and more electron donating the adjacent functional groups,
the more they stabilize the carbonyl compound from nucleophilic attack. For this reason, aldehydes
(i.e. one of the R groups is a hydrogen) are much more reactive than ketones. Carboxylic acids are
less reactive with nucleophiles, stabilized by the carboxylate resonance structures, and are not
discussed in this section.
23
1.7.2 Importance of Acid-catalysis
Since the atmospheric aqueous phases are acidic, nucleophilic addition to carbonyl compounds is
acid-catalyzed. As illustrated in Figure 1.11 (b), the oxygen on the carbonyl group can be
protonated under acidic conditions. This protonated form of carbonyl is in turn in resonance with
a carbocation form, as shown in Figure 1.11 (b). The positively charged carbon is even more
electrophilic than a neutral carbonyl, hence the carbonyl is “activated” by protonation. Acid
catalysis accelerates the reaction kinetics but does not, in principle, affect the equilibrium states.
However, given the dynamic nature of organic chemistry in atmospheric aqueous phases, acid
catalysis can significantly affect the amount of products forming in reactions discussed in this
section.
While it was generally believed that acid catalysis is initiated by strong acids such as H2SO4 and
HNO3 (Jang et al. 2002), Noziere and coworkers have proposed that amino acids (Noziere et al.
2007), the ammonium ion (Noziere et al. 2009) and carbonate ion (Noziere et al. 2010) can be
important catalysts in atmospheric aqueous phases. Given that inorganic salts can be at or beyond
their saturation concentrations in aerosol liquid water (Tang et al. 1997), catalysis by inorganic
ions can be particularly important. Assuming the universality of acid-catalysis in atmospheric
aqueous phases, the carbonyl compounds demonstrated in Figure 1.11 are in their protonated
forms.
1.7.3 Water Nucleophile and Hydration
Being the most abundant molecule in the aqueous phase, water is the most important nucleophile
in atmospheric aqueous phases. Nucleophilic addition of water to carbonyl compounds is often
referred to as the hydration reaction and gives rise to geminal diols (Figure 1.11 (c)). As hydration
reactions are reversible, all the carbonyl compounds exist, to some extent, in equilibrium with their
corresponding geminal diols. The degree of hydration directly affects the Heff value of an aldehyde,
and hence its air-aqueous partitioning (Betterton and Hoffmann 1988). The effects of highly
concentrated salts to the hydration equilibria present a poorly constrained area. Yu et al. (2011)
have shown that the hydration equilibria of glyoxal shift towards its dehydrated form in sodium
sulfate solution.
24
Figure 1.11: Nucleophilic addition reactions associated with carbonyl compounds.
25
Hydration can affect the reactivity of carbonyl compounds in several ways. First, radical induced
oxidation of geminal diols can effectively convert aldehydes into carboxylic acids, as already
demonstrated in Section 1.6.1. Second, geminal diols can act as nucleophiles themselves and add
to other carbonyls to form oligomers (See Section 1.7.4). Lastly, geminal diol formation is
accompanied by loss of the C=O double bond, hence losing light absorption induced by the n→
π* band.
1.7.4 Alcohol Nucleophile and Hemiacetal Formation
As shown in Figure 1.11 (d), hemiacetal formation proceeds via an alcohol functional group acting
as the nucleophile. For small aldehyde compounds with large hydration equilibrium constants, e.g.
glyoxal, methylglyoxal and formaldehyde, the geminal diols of these compounds act as
nucleophiles themselves, resulting in self-oligomerization (Loeffler et al. 2006, Zhao et al. 2006,
Noziere et al. 2009, Shapiro et al. 2009, Lim et al. 2010, Sareen et al. 2010, Schwier et al. 2010,
Li et al. 2011).
Sugars and anhydrosugars contain multiple alcohol functional groups and can undergo hemiacetal
formation. For example, the straight chain isomer of glucose, which contains an alcohol and an
aldehyde on the two ends of the molecule, undergoes intramolecular hemiacetal formation to form
cyclic isomers. In OH oxidation experiments of levoglucosan, (Holmes and Petrucci 2006, 2007)
have shown that the reaction intermediates of levoglucosan oligomerize via hemiacetal formation.
1.7.5 Enol Nucleophile and Aldol Condensation
Aldol condensation involves an enol nucleophile which is in equilibrium with its carbonyl form in
the aqueous phase (Figure 1.11, (e)). Nucleophilic addition of an enol to an aldehyde first leads to
an aldol intermediate, which dehydrates to form the final product. For ketones, or aldehydes that
do not preferentially form geminal diols, aldol condensation becomes the major mechanism giving
rise to oligomerization (Zhao et al. 2006, Noziere and Esteve 2007, Casale et al. 2007). A large
number of studies have observed a mixture of aldol condensation and hemiacetal formation
products from α-dicarbonyl compounds such as glyoxal and methylglyoxal (Loeffler et al. 2006,
Shapiro et al. 2009, De Haan et al. 2009, Schwier et al. 2010, Sareen et al. 2010, De Haan et al.
2011).
26
1.7.6 Similarities and Differences in Hemiacetals and Aldol Condensates
Although hemiacetal formation and aldol condensation are both proposed as important
mechanisms leading to oligomer formation in the absence of radical chemistry, fundamental
differences exist in their reaction products. The major difference is the dehydration step in aldol
condensation, leaving the aldol condensates less oxygenated compared to the hemiacetals, where
all the oxygen atoms are retained. Instead, the dehydration step leaves a double bond on the aldol
condensates. As a consequence, oligomeric aldol condensates contain extensive π-conjugation that
can absorb actinic radiation. Noziere and coworkers (Noziere and Esteve 2005, Noziere et al. 2007,
Noziere and Esteve 2007) have proposed the connection between aldol condensation products and
atmospheric Brown Carbon (See Section 1.7.8). More recently, Nguyen et al. (2013) have also
proposed highly conjugated, strongly light-absorbing oligomers arising from aldol condensation
of limonene SOA extract. The important atmospheric implication arising from the difference
between these two mechanisms is that hemiacetals are more oxygenated and less volatile, while
aldol condensation may give rise to organic chromophores absorbing the actinic radiation.
1.7.7 Hydroperoxide (ROOH) Nucleophile and Peroxyhemiacetal Formation
Organic hydroperoxides (ROOH) undergo nucleophilic addition to aldehydes to form
peroxyhemiacetals (Tobias and Ziemann 2000). This type of product has been previously proposed
to occur at particle surfaces (Tobias and Ziemann 2000, Docherty et al. 2005, Yee et al. 2012) and
is likely an important mechanism for SOA growth in a pristine (i.e. low NOx) environment
(Ziemann and Atkinson 2012). Peroxyhemiacetal formation has been shown to proceed in the
aqueous phase as well. Hydrogen peroxide (H2O2) can add to carbonyls to form the simplest form
of peroxyhemiacetal: α-hydroxyhydroperoxide (α-HHP) (Figure 1.11, (f)). Formation of α-HHP
in the aqueous phase from formaldehyde and acetaldehyde has been known since early studies
(Satterfield and Case 1954, Hellpointner and Gab 1989, Zhou and Lee 1992). However, the
potential of other carbonyl compounds forming α-HHP has not been explored.
ROOH belongs to reactive oxygen species and induces adverse health effects. Formation of
organic ROOH in atmospheric aqueous phases is of great importance in assessing the particulate
matter related health issues. It has been shown that ROOH decomposes over time in aqueous
extracts (Wang et al. 2011), thus particle extraction and offline measurements may underestimate
27
the concentration of ROOH in suspended particles. An in-situ method for the measurement of
ROOH in aqueous phase is urgently needed.
1.7.8 Nitrogen-containing Nucleophiles and Atmospheric Brown Carbon Formation
Reduced nitrogen compounds with lone-pair electrons (e.g. ammonia, primary amines and amino
acids) undergo nucleophilic addition to form imines (Figure 1.11 (g)). The reaction proceeds via
formation of a neutral carbinolamine intermediate and subsequent acid-catalyzed dehydration to
form the final product. While acid-catalysis is required, excess acid protonates the nucleophiles,
suppressing their nucleophilicity (Bones et al. 2010, Lee et al. 2013). Therefore, this reaction is
expected to be optimized in a narrow pH window.
The most crucial atmospheric implication of this reaction is formation of a class of light absorbing
organic compounds commonly referred to as atmospheric Brown Carbon (BrC) (Andreae and
Gelencser 2006). BrC species absorbs actinic radiation in the near-UV and visible range, and may
affect the direct radiative effects of organic aerosol (Feng et al. 2013). The identity and formation
mechanism of BrC are currently unclear. Imines undergo subsequent reactions in the aqueous
phase to form nitrogen-containing organic chromophores, representing a secondary source of BrC
in the aqueous phase (Shapiro et al. 2009, Sareen et al. 2010, Powelson et al. 2013). Laboratory
experiments have observed that glyoxal can undergo serial addition reactions to form imidazole
and its derivatives (Galloway et al. 2009, Yu et al. 2011, Kampf et al. 2012), and the equivalent
products have also been observed from methylglyoxal (De Haan et al. 2011, Drozd and McNeill
2014).
Nizkorodov and coworkers have observed BrC formation from the water soluble fraction of
chamber-generated SOA. They found that limonene ozonolysis SOA generated particularly
absorptive products upon aging with nitrogen containing nucleophiles (Bones et al. 2010, Nguyen
et al. 2013, Lee et al. 2014). On the contrary, SOA generated via α-pinene ozonolysis did not result
in significantly absorbing products (Updyke et al. 2012, Nguyen et al. 2013). The key difference
in SOA arising from these two isomeric precursors (i.e. α-pinene and limonene) seems to be
formation of a specific carbonyl compound, ketolimononaldehyde, as a second generation product
only in the limonene system (Nguyen et al. 2013, Laskin et al. 2014).
28
1.8 Removal of Organic Compounds in Aqueous-phase
Atmospheric aqueous phases play pivotal roles in the removal processes of organic compounds,
with wet deposition being the major removal mechanism of accumulation mode organic aerosol,
responsible for 70 to 85 % of its total sink (Kanakidou et al. 2005). Field measurements have
confirmed that fog scavenging enhances the deposition velocities of organic aerosol components
(Herckes et al. 2007, Collett et al. 2008). While these are physical removal processes, aqueous-
phase chemistry also results in chemical removal of certain organic compounds, significantly
affecting their atmospheric lifetime.
Isocyanic acid (HNCO), a toxic pollutant arising from pyrolytic processes, represents an extreme
example where its only atmospheric sink is in the aqueous phase. HNCO does not contain an
abstractable hydrogen atom and does not react with OH radical rapidly (Tsang 1992), nor does it
absorb actinic radiation to photolyze (Dixon and Kirby 1968). However, it is readily water soluble,
and undergoes an irreversible hydrolysis reaction (Roberts et al. 2011). Therefore, the gas-aqueous
partitioning of HNCO and the kinetics of its aqueous-phase chemistry play critical roles in
governing the atmospheric lifetime of this harmful compound.
Organonitrates species, with a general structure RONO2, undergo hydrolysis in the aqueous phase
and give rise to the corresponding alcohol (ROH) and HNO3 (Szmigielski et al. 2010, Darer et al.
2011, Hu et al. 2011). While the hydrolysis rates of primary and secondary organonitrate species
are small, the hydrolysis lifetimes of tertiary organonitrate species are on the order of minutes
under atmospherically relevant conditions (Darer et al. 2011). The fast hydrolysis of tertiary
organonitrates reflects the stability of the carbocation intermediate forming in its hydrolysis
mechanism (Szmigielski et al. 2010). Recent laboratory investigations for isoprene-derived
organonitrates have observed tertiary structural isomers (Teng et al. 2014, Lee et al. 2014). As
organonitrate species are temporary reservoirs of NOx, aqueous-phase removal of these species
essentially leads to removal of reactive nitrogen species from the atmosphere.
Aqueous-phase OH oxidation can remove organic compounds very efficiently. For example,
laboratory studies have found that the aqueous-phase oxidation lifetime of levoglucosan is on the
order of hours (Hoffmann et al. 2010, Teraji and Arakaki 2010). Levoglucosan is a widely
employed molecular tracer for biomass burning (Simoneit 2002), which is typically assumed to be
chemically inert in chemical mass balance receptor models (Robinson et al. 2006). Under humid
29
and sunlit conditions, where photochemistry in the aqueous-phase is active, such rapid removal of
levoglucosan in the aqueous phase may significantly affect the accuracy of biomass burning source
apportionment.
Aqueous-phase chemistry affects the optical properties of organic chromophores. Recent
laboratory studies have observed somewhat contradictory results on the effect of aqueous-phase
processing to the light absorptivity of BrC species. Aqueous-phase OH oxidation of phenolic
compounds has been observed to enhance the solution light absorptivity (Gelencser et al. 2003,
Chang and Thompson 2010), while other studies have observed rapid decay of color (photo-
bleaching) of BrC upon aqueous-phase photolysis (Bateman et al. 2011, Sareen et al. 2013, Lee et
al. 2014). The results imply that aqueous-phase processing can be a significant removal process
for BrC. The effect of OH oxidation on the absorptivity of BrC is yet to be explored.
1.9 Sampling and Measurement Techniques for Aqueous-phase Organic Compounds
1.9.1 Sampling Techniques for Cloud and Fog Water
Bulk cloud and fog water samples have been commonly collected using the Caltech active strand
cloudwater collector (CASCC) (Demoz et al. 1996). A fan placed at the inlet draws the ambient
air into the collector and accelerates the air against vertical cylindrical Teflon strands. While small
particles (i.e. gas molecule and aerosol) follow the air stream and pass by the strands, large
particles (i.e. cloud and fog droplets) collide with the strands due to inertia, with their liquid content
collected at the base of the strands. The original CASCC was designed to have a droplet cut-size
at 3.5 µm, but later modifications also enabled size resolved collection. The strength of CASCC is
that it collects a large volume of sample that can be analyzed using offline analytical techniques.
While CASCC can collect only bulk samples, continuous sampling techniques for cloud and fog
water have also been developed, and the counterflow virtual impactor (CVI) represents one of such
techniques. The type generated by Noone and coworkers (Noone et al. 1988b) has been employed
in both ground-based and aircraft measurements. The ambient inlet flow meets a counterflow
(clean and warm air) inside the CVI, generating a virtual stagnant plane, whereby only large
droplets with sufficient inertia can pass and be sampled. Once the sampled droplets are exposed to
30
the dry and warm counterflow, the droplets evaporate and give rise to droplet residues. The CVI
has been employed to investigate size distribution and inorganic salt contents in these droplet
residues (Noone et al. 1988a, Noone et al. 1992). To better exploit the continuous nature of CVI,
it has been coupled to online aerosol mass spectrometry in a few previous studies for online
chemical characterization of the droplet residues (Hayden et al. 2008, Lee et al. 2012).
1.9.2 Recent Development of Extraction and Measurement of Water Soluble Organic Carbon Associated with Particles
Due to small LWC, there is currently no method for direct sampling and measurement of the
organic composition of ALW. The water-extractable fraction of particulate matter, also referred to
as water soluble organic carbon (WSOC), is commonly used to imply the chemical composition
in the original particle and ALW.
Filter collection and extraction is the most widely employed method to obtain the WSOC fraction.
While the extraction has been conducted by either shaking or sonicating the filter in bulk aqueous
phase, Laskin and coworkers have developed nanospray desorption electrospray mass
spectrometry (nano-DESI) where extraction can be conducted on the filter surface (Roach et al.
2010). Briefly, an aqueous reservoir (the solvent bridge) is created on the filter surface to extract
analytes. The solvent bridge is connected to two nano capillaries, with the first capillary
continuously supplying the solvent to the bridge, and the second capillary carrying the solvent and
extracted analytes to an electrospray ionization mass spectrometer (ESI-MS). Being able to
conduct extraction directly on the filter, nano-DESI avoids artifacts arising from extensive
extraction procedures.
Collection of a filter sample typically takes hours. To improve time resolution of particle
collection, a continuous extraction method, particle-into-liquid sampler (PILS) has been developed
(Orsini et al. 2003). Aerosol sampled by a PILS is exposed to a supersaturated condition, where
the particles grow into large droplets, following the activation process described in Section 1.3.1.
The activated droplets are collected into the aqueous phase using inertial impaction. PILS can be
coupled to any analytical methods that can make continuous aqueous-phase measurements
(Section 1.9.3). Weber and coworkers have coupled PILS to a variety of analytical methods to
make semi-continuous measurements of different aspects of ambient aerosol. Orsini et al. (2013)
have used ion chromatography downstream of a PILS to measure organic acids associated with
31
ambient aerosol. Miyazaki et al. (2009) have coupled a semi-continuous total organic carbon
analyzer to quantify the total WSOC, while Zhang et al. (2013) further coupled a liquid waveguide
capillary cell, a sensitive UV-Vis spectrometer, to quantify the amount of BrC in WSOC.
1.9.3 Application of Online Mass Spectrometry to Aqueous-Phase Detection.
Online mass spectrometry (MS) exhibits excellent detection sensitivity and high time resolution,
representing the ideal analytical method for a rapidly evolving chemical composition in the
aqueous phase. Turpin and coworkers have employed an online ESI-MS to monitor aqueous-phase
OH oxidation of a variety of organic compounds, including glycolaldehyde (Perri et al. 2009),
glyoxal (Tan et al. 2009), methylglyoxal, (Tan et al. 2010) and acetic acid (Tan et al. 2012).
Aerosol mass spectrometer (AMS) has made a tremendous contribution in monitoring the organic
composition of submicron aerosol (Jayne et al. 2000, Canagaratna et al. 2007). Lee et al. (2011)
have developed a novel method to apply this powerful instrument to aqueous-phase detection. By
atomizing the aqueous solution and drying the generated droplets, the bulk aqueous-phase is
converted into particles, a detectable form for AMS. This method has been first applied in
characterizing the chemical composition of authentic cloudwater and WSOC (Lee et al. 2011, Lee
et al. 2012), and later adopted by a number of laboratory investigations of aqueous chemistry
(Aljawhary et al. 2013, Daumit et al. 2014, Yu et al. 2014).
The past decade has also seen a rapid development of gas-phase MS techniques, represented by
proton transfer reaction mass spectrometry (PTR-MS) and chemical ionization mass spectrometry
(CIMS). These techniques employ soft ionization methods and are suited for obtaining molecular-
level information for kinetic and mechanistic studies. Sampling techniques have been developed
to apply these gas-phase MS techniques to the measurement of condensed-phase organics, by
thermally desorbing the organic compounds to the gas-phase. Holzinger et al. (2010) have
developed a thermal-desorption PTR-MS (TD-PTR-MS), while Yatavelli and Thornton (2010)
have introduced a micro-orifice volatilization impactor (MOVI) coupled to a CIMS instrument.
The similarity between the two methods is that aerosol samples are first collected and concentrated
on an impactor, followed by programmed thermal-desorption. As the sampling is divided into a
collection phase and a thermal-desorption phase, these setups can separate condensed-phase
organic compounds from the gas-phase compounds and make semi-continuous measurements.
32
Continuous measurement of condensed-phase organic compounds has been enabled by the
development of aerosol chemical ionization mass spectrometry (Aerosol CIMS) (Hearn and Smith
2004). In this technique, aerosol sample is continuously introduced through a heated volatilization
line where thermal-desorption occurs. Aerosol CIMS has been applied in laboratory generated
particle samples (Hearn and Smith 2006, McNeill et al. 2008). The first application of Aerosol
CIMS to aqueous-phase chemistry was by Sareen et al. (2010), where they atomized aqueous
mixtures of methylglyoxal and ammonium sulfate and analyzed their chemical composition using
an iodide water cluster CIMS. Given the continuous nature of this technique, it is expected to be
highly valuable in monitoring rapidly evolving chemical systems, such as OH oxidation in the
aqueous phase.
1.10 Summary and Objectives
Studies from the last decade have indicated atmospheric aqueous phases as important reaction
media, where organic compounds undergo chemical reactions, i.e. aqueous-phase processing.
Aqueous-processing is accompanied by decay of the precursor compounds and formation of non-
volatile products. Therefore, aqueous-phase organic chemistry gives rise to organic compounds
that can contribute to SOA formation, in addition to compounds condensing from the gas phase.
As our knowledge of atmospheric aqueous-phase chemistry is incomplete, a better understanding
of the relevant kinetics and mechanisms will contribute to a better assessment of the effects of
atmospheric aerosol to air quality and climate change. Development of online detection methods
for aqueous-phase organic compounds in both the laboratory and the field is urgently needed.
Particularly, application of soft ionization mass spectrometry will be important and timely for the
detection of unstable compounds and to provide molecular-level information.
The goals of this work is to further our understanding of the reactions of organic compounds in
the aqueous phase, as well as the partitioning of organic compounds to the aqueous-phase. The
priority is given to providing quantitative information for the improvement of cloudwater
chemistry models. Specific objectives involve:
Development of an online measurement technique, where online CIMS is applied to
monitor aqueous-phase organic chemistry.
33
Investigation of aqueous-phase OH oxidation of SOA precursors: glyoxal and
methylglyoxal.
Kinetic and mechanistic investigation of aqueous-phase OH oxidation of levoglucosan.
Quantification of α-HHPs forming in the aqueous phase and its impact on the partitioning
of aldehydes to atmospheric aqueous phases.
Investigation of the effects of photochemical processing on the optical properties of BrC
species.
Measurement of cloud partitioning of HNCO using online CIMS coupled to a CVI.
In Chapter 2 and 3, a new Aerosol CIMS system is utilized for laboratory investigation of OH
oxidation of glyoxal, methylglyoxal and levoglucosan. Comprehensive product analyses for these
precursors are conducted. Particularly in Chapter 3, a high mass resolution CIMS is employed, and
novel analysis frameworks are introduced to offer insights to detailed reaction mechanisms.
In Chapter 4, formation of α-HHPs was quantified using a combination of online PTR-MS and
offline nuclear magnetic resonance (NMR) spectrometry. Such organic hydroperoxides forming
in the aqueous-phase represent a class of unrecognized compounds with significant environmental
implications.
In Chapter 5, the effects of photochemistry on the absorptivity of BrC species were investigated,
focusing on the imine-mediated species (Section 1.7.8) and nitrophenols as surrogates for biomass
burning BrC.
Finally, in Chapter 6, an online CIMS was for the first time coupled to a CVI for in-situ
measurement of organic compounds dissolved in ambient cloudwater, with focus on the cloud
partitioning of HNCO.
34
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53
Chapter 2
Investigation of Aqueous-Phase Photooxidation of Glyoxal and
Methylglyoxal by Aerosol Chemical Ionization Mass Spectrometry:
Observation of α-hydroxyhydroperoxide Formation
Reproduced with permission from Journal of Physical Chemistry A 116 (24), pp 6253–6263
DOI: 10.1021/jp211528d Copyright © 2012 American Chemical Society.
54
Abstract
Aqueous-phase processing of glyoxal (GLY) and methylglyoxal (MG) produces highly
oxygenated, less volatile organic acids that can contribute to SOA formation and aging. In this
study, aerosol chemical ionization mass spectrometry (Aerosol CIMS) is employed to monitor
aqueous-phase photooxidation of GLY and MG. Using iodide (I−) as the reagent ion, Aerosol
CIMS can simultaneously detect important species involved in the reactions: organic acids,
peroxides, and aldehydes, so that the reconstructed total organic carbon (TOC) concentrations
from Aerosol CIMS data agree well with offline TOC analysis. This study also reports the first
direct detection of α-hydroxyhydroperoxide (α-HHP) formation from the reaction of H2O2 with
GLY or MG. The formation of α-HHPs is observed to be reversible, and their formation
equilibrium constants are determined to be between 40 and 200 M−1. Results of this study suggest
that α-HHPs can form additional formic acid and acetic acid via photooxidation and regenerate
GLY or MG during photooxidation, compensating their loss. α-HHP formation needs to be further
studied for inclusion in aqueous-phase chemical models given that it may affect the effective
Henry’s law constants of carbonyls in the atmosphere.
2.1 Introduction
It is now evident that aqueous-phase processing can be a significant formation and aging pathway
of secondary organic aerosol (SOA) (Blando and Turpin 2000, Loeffler et al. 2006, Fu et al. 2009,
Lim et al. 2010, Ervens and Volkamer 2010, Ervens et al. 2011, Kaul et al. 2011), a major fraction
of atmospheric submicrometer particles (Zhang et al. 2007) that causes adverse health effects,
visibility degradation and affects global climate. Aqueous-phase oxidation can convert water-
soluble volatile organic compounds (VOCs) into highly oxygenated, less volatile compounds that
can contribute to SOA mass upon water evaporation. Inclusion of this SOA formation mechanism
may improve agreement between field observations and traditional models (Volkamer et al. 2006)
in which SOA formation is governed by thermodynamic partitioning of gas-phase oxidation
products alone (Odum et al. 1996). Aqueous-phase processing is also an additional chemical aging
process causing continuous modification of physicochemical properties of organic aerosol, such
as hygroscopicity (Jimenez et al. 2009, Wong et al. 2011), light absorption (Ramanathan et al.
2007), and oxidative stress to the human body. However, due to its complicated nature, many
55
aspects of aqueous-phase processing and its contribution to the SOA budget are still not fully
understood.
Glyoxal (GLY) and methylglyoxal (MG) are ubiquitous dicarbonyl VOCs in the atmosphere. They
originate from both biogenic and anthropogenic precursors, with photooxidation of isoprene being
their dominant source (Fu et al. 2008). They have been frequently employed as model compounds
in numerous laboratory and modeling studies of atmospheric aqueous-phase processing (Carlton
et al. 2007, Altieri et al. 2008, Fu et al. 2009, Tan et al. 2009, Shapiro et al. 2009, Ervens and
Volkamer 2010, Lim et al. 2010, Tan et al. 2010, Schwier et al. 2010, Sareen et al. 2010, Lee et
al. 2011, Lee et al. 2011). Specifically, GLY and MG can efficiently partition into pure water via
formation of their hydrated structures (i.e., geminal diols), resulting in high effective Henry’s law
constants of 4.19 × 105 M atm−1 for GLY (Ip et al. 2009) and 3.71 × 103 M atm−1 for MG (Betterton
and Hoffmann 1988). There is growing evidence that the presence of inorganic and organic species
in aqueous solution can further enhance their Henry’s law solubility (Ip et al. 2009, Volkamer et
al. 2009, Yu et al. 2011), in part due to various types of aqueous-phase reactions including
enhanced hydration effects (Ip et al. 2009, Yu et al. 2011), oligomerization (Zhao et al. 2006, Lim
et al. 2010), and formation of nitrogen-containing (Noziere et al. 2009, De Haan et al. 2011) and
sulfur-containing compounds (Sareen et al. 2010).
Under solar radiation, aqueous-phase GLY and MG can be rapidly photooxidized (Carlton et al.
2007, Tan et al. 2009, Tan et al. 2010), via irreversible reactions that can form SOA materials
which have larger molecular weight and/or lower volatility (Lim et al. 2010). Depending on the
conditions of gas−aqueous phase transitions, aqueous-phase photooxidation of GLY and MG can
be a loss mechanism comparable to their gas-phase photooxidation and has been studied in detail
(Lim et al. 2005, Carlton et al. 2007, Tan et al. 2009, Lim et al. 2010, Tan et al. 2010, Lee et al.
2011). The proposed reaction scheme is shown in Figure 2.1 (Lim et al. 2005, Altieri et al. 2008,
Lim et al. 2010). The major products include highly oxygenated organic acids such as oxalic acid,
glyoxylic acid, and pyruvic acid. The products from multiple oxidation generations are expected
to participate in the formation of oligomer, nitrogen- and sulfur-containing compounds.
Furthermore, volatile products such as formic acid and acetic acid can repartition into the gas
phase. Their formation via aqueous-phase processing may partially explain the current
underestimation of the global budget of gas-phase formic acid and acetic acid (Paulot et al. 2011).
56
Figure 2.1: Simplified reaction mechanisms of aqueous-phase photooxidation of GLY (Lim et al. 2010) and MG (Lim
et al. 2005, Altieri et al. 2008). The two-way arrows represent reversible processes, whereas the one-way arrows
represent irreversible OH oxidation.
The major advances described above in our understanding of the mechanism of the aqueous-phase
photooxidation of these dicarbonyls have arisen from both offline analysis (Monod et al. 2005,
Carlton et al. 2007, Altieri et al. 2008) or a combination of online and offline analytical methods,
many conducted by Turpin and co-workers (Tan et al. 2009, Tan et al. 2010, Lee et al. 2011).
These studies focused on the identification of products and the determination of their formation
kinetics, based on which aqueous-phase chemistry models have been developed. However, all
offline analysis is subject to potential secondary reactions occurring in the solution prior to analysis
(Stefan and Bolton 1999, Tan et al. 2009). In addition, detection and quantification of unstable
(e.g., α-hydroxyhydroperoxides) or highly volatile species (e.g., acetic acid and formic acid) are
especially challenging, so that the current aqueous-phase chemistry models may be incomplete.
Our previous work monitored aqueous-phase photooxidation of GLY with online aerosol mass
spectrometry (AMS), offline ion chromatography (IC), and total organic carbon (TOC)
measurement (Lee et al. 2011). It was observed that the reconstructed TOC calculated from the
AMS and IC speciated data was significantly lower than the measured TOC in the early stages of
57
photooxidation, suggesting incomplete characterization of the oxidizing solution. On the basis of
the AMS measurement, Lee et al. (2011) first proposed that this unrecognized compound was a α-
hydroxyhydroperoxide (α-HHP) resulting from the rapid reaction between GLY and H2O2. α-HHP
formation from other atmospherically relevant water-soluble aldehydes (e.g., formaldehyde and
acetaldehyde) and H2O2 is also favored (Hellpointner and Gab 1989). Because AMS is not a highly
species-specific technique when one observes a mixture of compounds, and α-HHPs are likely to
be unstable for offline analysis, it is necessary to develop an online analytical technique that allows
direct detection of α-HHPs. For the current study, we have applied a real-time mass spectrometry
measurement system with a soft ionization source, aerosol chemical ionization mass spectrometry
(Aerosol CIMS) (Hearn and Smith 2004), to provide simultaneous detection of GLY, MG, α-HHPs
and both volatile and less-volatile photooxidation products. This is a complement to earlier online
analyses conducted using electrospray ionization mass spectrometry (ESI-MS) (Carlton et al. 2007,
Tan et al. 2009, Tan et al. 2010), making use of a different sample preparation method and mass
spectrometric ionization technique. The goal of the study was to demonstrate the oxidation
mechanisms of GLY and MG using Aerosol CIMS, and to confirm the formation of α-HHPs in the
reaction systems. In particular, total organic carbon (TOC) concentration in the solution was
reconstructed using Aerosol CIMS to examine its agreement with the measured TOC
concentration, and to assess the degree of oligomer formation.
2.2 Experimental Methods
The schematic diagram of the experimental apparatus is shown in Figure 2.2, with each component
of the system explained in this section.
2.2.1 Photooxidation of Aqueous Solution.
The conditions of the photooxidation experiments conducted are listed in Table 2.1. GLY and MG
solutions were prepared in 1 L pyrex reaction bottles using 18 mΩ Milli-Q water as described by
Lee et al. (2011). Because GLY and MG may exist in dimer or trimer forms in the concentrated
GLY (Sigma-Aldrich, 40 wt % in water) and MG (Sigma-Aldrich, ∼60% in water) stock solutions,
sufficient time (∼12 h) was given for them to reach their hydration equilibria in the reaction bottle
under dark conditions prior to the experiments. For consistency, ammonium sulfate (AS; 0.2 mM)
58
was added to the solution because it was used as an internal standard for AMS measurement in our
previous study (Lee et al. 2011). Because concentrated solutions of AS only react slowly with GLY
and MG to form nitrogen- and sulfur-containing compounds (Shapiro et al. 2009, Noziere et al.
2009, Galloway et al. 2009, Sareen et al. 2010), it is assumed that a low concentration of AS, 0.2
mM, does not significantly react with organics in the solution compared to OH radical reaction
during our experimental time scale. The AS control experiment (Table 2.1), where GLY
photooxidation was performed without addition of AS, did not show major differences, confirming
that AS does not significantly affect the photooxidation kinetics.
Figure 2.2: Schematic description of Aerosol CIMS and photooxidation cell.
Photooxidation of GLY was conducted in two concentration regimes, 3 and 0.3 mM, to investigate
possible concentration effects, whereas MG photooxidation was only conducted at 3 mM. H2O2
(Sigma Aldrich, 30 wt % in water) was used as the source of OH radicals upon photolysis. The
H2O2 concentrations used in the experiment were 13 and 1.3 mM for the 3 and 0.3 mM
concentration regimes, respectively (Table 2.1). These H2O2 concentrations were expected to give
a OH radical concentration of approximately 10−14 to 10−13 M in the solution during
photooxidation, which corresponds to ambient cloudwater concentrations (Jacob 1986). After
H2O2 addition, 30−40 min was given for α-HHPs to form and reach their equilibria without
exposure to light. Some 3 mM GLY photooxidation experiments were also conducted without any
waiting period to elucidate the effect of α-HHP to the photooxidation. In these experiments, the
59
photooxidation was initiated immediately after the addition of H2O2. In all experiments,
photooxidation was initiated by a 254 nm mercury lamp (UVP, constructed to remove the 185 nm
line) immersed in the reaction solution, and the length of each experiment was approximately 4 h.
During the entire experiment, the solution was atomized by a constant output atomizer (TSI, Model
3076) using ultrapure compressed air (BOC, grade 0.1), and the generated aerosol particles were
analyzed by Aerosol CIMS.
Table 2.1: Experimental Conditions
Photooxidation Experiments GLY
(mM) MG (mM) H2O2 (mM) AS (mM) Light
3 mM glyoxal (GLY) 3 0 13 0.2 Yes
0.3 mM GLY 0.3 0 1.3 0.2 Yes
3 mM methylglyoxal (MG) 3 0 13 0.2 Yes
Control Experiments
Dark Control GLY 3 0 13 0.2 No
Dark Control MG 0 3 13 0.2 No
H2O2 Control GLY 3 0 0 0.2 Yes
H2O2 Control MG 0 3 0 0.2 Yes
Irradiation of water 0 0 0 0.2 Yes
H2O2 to water 0 0 13 0.2 No
A series of control experiments was also conducted (Table 2.1). A dark control was conducted to
investigate dark reactions of GLY or MG with H2O2, whereas a H2O2 control was performed to
investigate direct photoreactions of GLY and MG without addition of H2O2. The purity of the
water used was also examined by H2O2 addition and by exposure to direct and indirect photolysis
to elucidate any potential organic formation from water impurities.
2.2.2 Aerosol CIMS
The Aerosol CIMS system employs a heated inlet line to volatilize particle-phase organic
compounds, thus detecting gas- and particle-phase organics simultaneously. Aerosol CIMS was
first developed by Hearn and Smith (2004) and has been used very successfully for studies of
60
heterogeneous and aqueous-phase chemistry (McNeill et al. 2008, Sareen et al. 2010). Here, we
apply Aerosol CIMS to investigate bulk aqueous-phase photooxidation. In the current study, the
particle flow generated from the atomizer was diluted with 3.0 standard liter per minute (slpm) of
ultrapure N2 gas (BOC, grade 4.8). The diluted flow was subsequently sent into a volatilization
line made of 40 cm long silicon-coated metal tubing (SilcoNert 2000), which was heated to 105 ±
5 °C using a heating tape and monitored by a thermocouple. This temperature was chosen because
it enables the detection of α-HHPs and both monohydrated and dihydrated GLY. The sample flow
entering the CIMS was measured to be 4.5 slpm, which is controlled by a critical orifice at the
entrance to the ion molecular region (IMR), with excess flow going to the exhaust line.
The CIMS is a home-built unit using I− as the reagent ion and a quadrupole as the mass analyzer
(Escorcia et al. 2010). The reagent ion is generated by flowing 6 splm of N2 gas over a homemade
CH3I permeation tube held at 70 °C. The flow containing CH3I vapor is then sent through a Po210
radioactive cell (NRD, Model 2031) from which I− is generated. The reagent ion meets the sample
flow in the IMR of the CIMS, where organic acids, peroxides, and aldehydes are ionized by
reactions R2.1, R2.2 and R2.4 (McNeill et al. 2008, Sareen et al. 2010):
RC(O)OH + I-•H2O → I-•RC(O)OH + H2O (R2.1)
ROOH + I-•H2O → I-•ROOH + H2O (R2.2)
RCHO + H2O ↔ RC(OH)2 (R2.3)
RC(OH)2 + I-•H2O → I-•RC(OH)2 + H2O (R2.4)
Chemical ionization using I− is a soft ionization technique, causing minimal fragmentation of the
parent molecules. Organic acids are ionized mostly via ligand transfer reaction from water clusters
of I− (I−·H2O) (R2.1) and are detected at the mass to charge ratio (m/z) of the molecule plus that of
I− (m/z = 127). Hydrogen peroxide and organic peroxides are also detected by the same ligand
transfer reaction (R2.2). Aldehydes are not ionized by I− directly, but they form geminal diols via
hydration reactions in the aqueous phase (R2.3). These geminal diols are ionized via the same
ligand transfer reaction (R2.4); therefore, aldehydes can be detected at the m/z of the molecule plus
18 (from H2O) and 127 (from I−). For dialdehydes such as GLY, geminal diols at the two hydration
steps were both detected. Herein, the terms GLY·1H2O and GLY·2H2O will be used to represent
61
GLY monohydrate and dihydrate, respectively. GLY·1H2O was the dominant GLY peak detected
by Aerosol CIMS, so that GLY·1H2O was used to estimate the GLY concentration in the solutions.
Only one geminal diol (MG·1H2O) was detected for MG, and it is used to estimate MG
concentration in the solution.
The calibration of the Aerosol CIMS was conducted by atomizing standard solutions with known
concentrations of GLY, MG, and their major products using the same experimental settings
mentioned above. This method enables the direct quantification of the target compounds, at the
same time accounts for the effects of temperature, ionization efficiency, and water vapor that
control the detection sensitivity of Aerosol CIMS. The raw signal of each species was normalized
to the reagent ion (I− at m/z 127) to account for the effect of any changes in the number of reagent
ions during the experiment. At the beginning of each experiment, Milli-Q water with 0.2 mM AS
was atomized for 30−40 min to stabilize the volatilization line temperature and to obtain a
background. The background values were subtracted from analyte signals. The linearity of the
calibrations was generally excellent (R2 > 0.98), and the measurement uncertainty for most of the
organic acids was determined to be ∼5% for a single run, except for pyruvic acid whose ionization
efficiency drifted over time. We estimate its measurement uncertainty to be ∼15%. There is more
uncertainty associated with GLY and MG quantification due to the sensitivity of their hydration
equilibria to temperature and the chemical composition of the solution, making it more difficult to
estimate the overall uncertainties. These uncertainties will be discussed in the TOC results section.
The detection sensitivity of the analytes, in general, is constant during an experiment but varies to
some degree between days. For this reason, a calibration was performed prior to each
photooxidation experiment. The following species were quantified with this calibration method:
GLY, MG, formic acid (FA) (Fluka, 50% in water), glyoxylic acid (GA) (Sigma Aldrich, 50 wt %
in water), oxalic acid (OA) (Fisher Scientific, in dihydrate form), pyruvic acid (PA) (Sigma
Aldrich, 98%), glycolic acid (GCA) (Sigma Aldrich, 99%), acetic acid (AA) (Fisher Scientific,
99.7%), malonic acid (MA) (Fisher Scientific, 99%), and succinic acid (SA) (Fisher Scientific).
The detection limits of the analytes are generally below 0.02 mM, except for GLY and AA. Their
detection limits are estimated to be 0.05 mM and 0.07 mM, respectively.
62
2.2.3 Offline TOC and Complementary IC Analysis
The total organic carbon (TOC) concentration was analyzed by an offline TOC analyzer (Shimadu
TOC-VCPN) in a similar way as our previous studies (Lee et al. 2011, Gao and Abbatt 2011). The
TOC analyzer quantifies the total carbon concentration in the solution by converting all the carbon
containing species into CO2 at a high temperature using an oxidation catalyst. The CO2 generated
is detected by a nondispersive infrared detector. Meanwhile, the inorganic carbon concentration in
the sample solution is quantified by converting inorganic carbon species into CO2 using HCl,
followed by the same CO2 detection. Potassium hydrogen phthalate was used to calibrate the total
carbon measurement, whereas sodium carbonate/sodium bicarbonate were used for the calibration
of inorganic carbon. The difference between the measured total carbon and inorganic carbon is the
TOC concentration. TOC samples were collected from the experimental solution every 30 min
during the photooxidation. The samples were sealed, covered with aluminum foil, and refrigerated
at 5 °C until analysis. The measurement uncertainty of the TOC analysis is 10%.
Because the m/z of MG·1H2O overlaps with the m/z of OA, our CIMS with unit mass resolution
could not distinguish these two compounds. Offline ion chromatography (IC) was employed to
quantify OA in the MG photooxidation experiments to assist the Aerosol CIMS data analysis. The
analysis was conducted using a Dionex ICS 2000 system with AS19 anion exchange column under
suppressed conductivity detection using an ASRS 300 conductivity suppressor. The eluent was
potassium hydroxide (KOH) with a flow rate of 1 mL min−1. The eluent concentration gradient
was programmed as a previous study (VandenBoer et al. 2011). The measurement uncertainty of
the IC analysis was estimated to be within several percent. IC samples were collected from the
photooxidation solution every hour and were analyzed on the same day of the experiment, keeping
them sealed, covered with aluminum foil and refrigerated. A polynomial curve was fitted to the
OA concentration time profile obtained from IC analysis, and this expression was used to back-
calculate the Aerosol CIMS signal responsible for OA. From there, the OA and MG·1H2O signals
were separated, and the concentration profile of MG was obtained.
63
2.3 Results and Discussions
2.3.1 Formation of α-Hydroxyhydroperoxides (α-HHPs) in Dark Control Experiments
Formation of a class of compounds was witnessed from the dark control experiment of GLY and
MG, but not from addition of H2O2 into pure water. These compounds have m/z of the geminal
diols of GLY or MG plus 127 (from I−) and 34, the m/z of a H2O2 molecule. We propose that these
compounds are α-hydroxyhydroperoxides (α-HHPs) formed via reactions between H2O2 and GLY
or MG (Figure 2.3).
Figure 2.3: Pathways showing formation of α-hydroxyhydroperoxides.
Formation of α-HHP proceeds via nucleophilic addition of H2O2 to the aldehyde functional group
(Sun et al. 2006, Mucha and Mielke 2009). α-HHP formation from reactions between H2O2 and
carbonyls has been long recognized (Hellpointner and Gab 1989, Stefan and Bolton 1999). In the
case of the current study, H2O2 reacts with GLY and GLY·1H2O (R2.5 and R2.6, Figure 2.3) to
form 2-hydroxy-2-hydroperoxyethanal (HHPE) and its hydrated counterpart (HHPE·1H2O). For
MG, H2O2 can react with either the aldehyde (R2.7) or the ketone (R2.8) functional group to form
a pair of structural isomers: hydroxyhydroperoxyacetone (HHPA) and 2-hydroxy-2-
64
hydroperoxypropanal (HHPP). Note that Aerosol CIMS was unable to separate these two structural
isomers. MG·1H2O can also react with H2O2 (R2.9) to form hydrated HHPP (HHPP·1H2O).
Formation of the four HHPs shown in Figure 2.3 has been confirmed using Aerosol CIMS by
observations of the signal increase at their corresponding m/z (Figure 2.3) in the dark control
experiments. HHPE and HHPA/HHPP were the major α-HHP peaks observed.
Figure 2.4: Formation of α-HHPs in dark control experiments. H2O2 (13 mM) was added to 3 mM of GLY (a) or 3
mM of MG (b) solutions at time (I), and quenched at time (II) by addition of catalase from bovine liver. α-HHPs
formed sharply after the addition of H2O2 and reached equilibrium values approximately 40 min after the addition.
After quenching of H2O2, α-HHPs decayed to zero and reversibly formed GLY or MG.
Figure 2.4a shows an example dark control experiment of 3 mM of GLY. Immediately after H2O2
was added to GLY solution at time (I), a significant increase of HHPE signal was detected until
equilibrium was established in 40 min. At this point, one-third of GLY has been consumed,
indicating that approximately 1 mM of total α-HHP was present in the solution. At time (II), 2
drops of catalase from bovine liver (Sigma Aldrich, 28 mg protein/mL; 21600 units/mg protein)
were added to the solution to quickly quench H2O2. It was observed that HHPE decayed away,
with the GLY signal recovering. Similar behavior was observed for HHPA/HHPP formed from
MG and H2O2, as shown in Figure 2.4b. These observations indicate that α-HHPs are equilibrium
products that can regenerate GLY and MG upon quenching of H2O2. To further test the ubiquity
of the formation of α-HHPs and their behavior, we performed the same experiment by adding 13
mM of H2O2 to a 3 mM aqueous solution of propionaldehyde. Formation of a peak at m/z 219 was
confirmed, corresponding to hydroxypropylhydroperoxide, and this compound also reversibly
65
produced propionaldehyde upon quenching of H2O2. This observation further confirms the α-HHP
formation in our system and the generality of this reaction with aldehydes.
From Figure 2.4, the formation and decomposition rate constants of α-HHPs can be roughly
evaluated. The concentration of α-HHPs are estimated from the fraction of GLY or MG that decay
upon addition of H2O2. The second-order rate constant of α-HHP formation from GLY/MG plus
H2O2 is estimated from the initial slope of HHPE and HHPP/HHPA formation (Figure 2.4a,b) to
be 0.06 ± 0.03 M−1 s−1 for GLY plus H2O2 and 0.04 ± 0.02 M−1 s−1 for MG plus H2O2. The kinetics
of HHPE formation from GLY is two orders of magnitude faster than the reported value of another
study (Schone and Herrmann 2014). The reason for such a large discrepancy is unclear. The
decomposition rate constants of α-HHPs forming H2O2 and GLY/MG are determined from the
decay of HHPE and HHPP/HHPA signals after the quenching of H2O2 (Figure 2.4a,b). Both the
HHPE and HHPP/HHPA signals showed first order decays, and the decomposition rate constants
were determined to be 3 × 10−4 s−1 for HHPE and 1 × 10−3 s−1 for HHPP/HHPA.
From the ratio of the formation and decomposition rate constants, the equilibrium constants were
calculated to be 200 M−1 for HHPE and 40 M−1 for HHPP/HHPA, which are comparable to those
that can be estimated from the equilibrium concentrations of α-HHP, H2O2, and GLY, i.e., roughly
40 M−1 for each. The disagreement in the equilibrium constants of HHPE (200 and 40 M−1) using
the two calculation methods demonstrates uncertainties in the approaches used to determine these
quantities. For example, a fraction of the α-HHPs is likely to decompose to re-form GLY and MG
in the heated volatilization line. Also, the decay of the dicarbonyls leads to an estimate of the total
concentration of the α-HHPs forming in each experiment, and not to speciated values. Further
experiments need to be conducted to better determine these rate and equilibrium constants.
Our previous work (Lee et al. 2011) has inferred the formation of α-HHPs during photooxidation
of GLY from the fragmentation pattern of AMS spectra. However, the current study presents the
first direct detection of α-HHPs produced from GLY and MG in the aqueous phase. The fast
response time of Aerosol CIMS and its aqueous-phase detection mechanism using the
volatilization line enabled the detection of α-HHPs, a class of compounds that are otherwise
considered to be unstable and difficult to be detected with offline analytical methods. We are
currently uncertain why others have not identified α-HHPs in their studies.
66
2.3.2 Photooxidation of GLY
Figure 2.5a and b show the decay profiles of GLY and formation of its major products (FA, OA,
GA, and HHPE) from the 3 and 0.3 mM concentration solutions. The organic acid data in the figure
are the average of two to three experimental replicates, and the error bars account for the
fluctuations of the concentration profiles across the experimental replicates. We are unable to
easily quantify the α-HHP species at the moment, so that the HHPE signal from one of the
replicates is shown in Figure 2.5. The H2O2 control experiments of GLY did not result in detection
of any compounds nor in any observable decay of GLY, indicating that the results shown in Figure
2.5 are indeed due to OH driven oxidation.
Figure 2.5: Results of photooxidation experiments with 3 mM (a) and 0.3 mM (b) initial GLY concentration.
Photooxidation was initiated at time 0 (dashed line). Data shown here are the average of 2−3 replicates, and the error
bars represent fluctuations between replicates (1 σ). The signal of 2-hydroxy-2-hydroperoxyethanal (HHPE) overlaps
with that of hydrated GA (GA·1H2O). This normalized signal from one typical experiment is shown (right axis).
The concentration profiles of FA, GA, and OA agree with the mechanism proposed by Lim et al.
(2010), where FA and GA are the first generation products, and OA is a second generation product.
The FA formation before the initiation of photooxidation (Figure 2.5a,b) is due to reaction of H2O2
with impurities in water, which is confirmed from the control experiment, where H2O2 was added
to pure water. Although the formation of GA and OA in the two concentration regimes is
proportional to the initial GLY concentrations, the formation of FA appears to be highly
concentration dependent as shown by the significantly lower production in the 0.3 mM regime
(Figure 2.5a,b), implying the existence of different reaction mechanisms between the two
concentration regimes. We propose that the different behavior in the two concentration regimes is
associated with the α-HHP formation. A recent computational study (da Silva 2011) proposed that
67
an acyl radical of HHPE can decompose to form FA (Figure 2.6, R2.10). These mechanisms are
proposed to occur in the gas phase in the original paper, but formation of acyl radicals due to H-
abstraction reactions is common, and the subsequent decomposition may also occur in the aqueous
phase.
Figure 2.6: Possible formation mechanisms of formic and acetic acids from α-HHPs (from da Silva (2011)).
Formation of α-HHP in the 0.3 mM concentration regime is expected to be less important as
implied from the expression for α-HHP equilibria (Eqn. 2.1):
Kα-HHP = [α-HHP]/([aldehyde] × [H2O2]) (2.1)
where Kα-HHP is the equilibrium constant for α-HHPs in general, and [α-HHP], [aldehyde], and
[H2O2] are the equilibrium concentrations of α-HHP, aldehydes, and H2O2. Because the
concentrations of GLY and H2O2 used in the 3 mM regime were both 1 order of magnitude higher
than those used in the 0.3 mM experiment, Eqn. 1 indicates that the HHPE concentration in the 3
mM case is expected to be 2 orders of magnitude higher. Indeed, the normalized signal of HHPE
in the 3 mM concentration regime (Figure 2.5a) is significantly higher than that in the 0.3 mM
regime (Figure 2.5b). If a significant fraction of FA has been produced from the α-HHP pathway,
the much higher yield of FA in the 3 mM concentration regime can be explained. To further
examine this possibility, we performed an experiment in which HHPE equilibrium was not allowed
to establish prior to the initiation of photooxidation. With HHPE absent at the beginning of the
photooxidation, FA should appear to be a second generation product. The result of this experiment
(Figure 2.7) shows that formation of FA indeed exhibits characteristics of a second generation
product, with slower formation immediately after the initiation of the photooxidation. Lee et al.
(2011) also did not allow HHPE to equilibrate prior to the initiation of photooxidation and observed
68
slow formation of FA at the early stage of photooxidation. This evidence supports the HHPE
pathway of FA formation. By contrast, Lim et al. (2010) suggests that FA is directly produced from
photooxidation of GLY.
Figure 2.7: Three mM GLY photooxidation without α-HHP equilibrium. The experiment was conducted as with the
3 mM GLY photooxidation, except that photooxidation was initiated immediately after H2O2 was added to the GLY
solution at time 0. The error bars represent fluctuations between replicates (1 σ).
As described in the Experimental Methods, the concentration of GLY was estimated using the
signal of GLY·1H2O. The decay of GLY in the 3 mM concentration regime was observed to be
non-first-order and significantly slower than by Tan et al. (2009) and Lee et al. (2011). We propose
that the slow decay of GLY arises via the regeneration of GLY·1H2O from HHPE, as discussed in
detail in the TOC section.
2.3.3 Photooxidation of MG
The time profiles of 3 mM MG photooxidation are shown in Figure 2.8. The data are the average
of two experiments, and the error bars represent fluctuations between the replicates. The signal of
HHPP plus HHPA from one experiment is also shown in the figure. The overall trend of the
photooxidation agrees with the observation of Tan et al. (2010) in that PA, AA, and OA appear to
be the first-, second-, and third-generation (or later) products, respectively, and that the yield of
GA is low. Tan et al. (2010) found the quantification of AA challenging because of its small m/z
(outside of the ESI-MS mass range) and the overlap of AA and GCA peaks in the IC. Here, we
69
successfully quantified AA and GCA using Aerosol CIMS. It is observed that GCA is only a minor
product, whereas AA turns out to be the dominant product of MG photooxidation.
Figure. 2.8: Concentration profiles of MG and its products. Photooxidation was initiated at time 0 (dashed line). The
oxalic acid profile obtained from IC and its fitted line are shown on the graph. Using the fitted line, the MG
concentration profile was calculated. The data represent the average of two independent replicates, with the error bars
showing fluctuation between the replicates (1 σ). The normalized signal of 2-hydroxy-2-hydroperoxypropanal (HHPP)
and hydroxyhydroperoxyacetone (HHPA) from one experiment is shown (right axis).
Note that the yields of FA and AA are observed to be significantly higher than the model prediction
of Tan et al. (2010). Direct photolysis of MG can, at least in part, give rise to the high yields of FA
and AA. A significant amount of FA and AA formation was observed from a H2O2 control
experiment of MG, as shown in Figure 2.9. Approximately 0.4 mM of FA and AA were produced
by 2 h of direct MG photolysis. Tan et al. (2010) did not include direct photolysis of MG into the
model due to the assumption that the effects of direct photolysis are small compared to
photooxidation. This is likely to be true in their experimental setup where the OH radical
70
concentration is 1 order of magnitude higher than in the current study, where we have observed
that FA and AA formation via direct photolysis of MG may be important. In particular, the FA
concentration profile shows rapid formation immediately after the initiation of photooxidation
(Figure 2.9), further implying that this arises from direct photolysis of MG. The higher yield of
AA may also arise by two additional formation pathways associated with α-HHP formation. The
first pathway is PA plus H2O2, as suggested in Stefan et al. (1999): H2O2 reacts with the ketone
group of PA, forming a α-HHP intermediate which decomposes to form AA. The second pathway
is the oxidation of HHPP as illustrated by R2.11 in Figure 2.6 (da Silva 2011). H-abstraction of
the aldehydic hydrogen of HHPP results in an acyl radical which may subsequently decompose to
form AA. The formation of AA is thus complicated, and deconvolution of the relative contributions
is difficult at the moment.
Figure 2.9: H2O2 control experiment for MG. MG solution (3 mM) was exposed to irradiation without addition of
H2O2. The irradiation was initiated at time 0 (dashed line). A significant amount of FA and AA was produced. The
initial increase of the MG signal was due to equilibration of MG in the inlet line, and the initial signal of FA and AA
are due to impurities in solution or due to decomposition of MG prior to the experiment.
As explained previously, OA was quantified by offline IC analysis in the MG photooxidation
experiments. It is known that H2O2 reacts with organic species in the dark to cause secondary
reactions prior to offline analysis, such as FA formation from GA plus H2O2 (Carlton et al. 2007,
Tan et al. 2009) and AA formation from PA plus H2O2 (Stefan and Bolton 1999, Tan et al. 2010).
However, OA is expected to be relatively stable against H2O2 reaction and volatilization loss due
to its low volatility. For these reasons, the offline quantification of OA is expected to be more
71
reliable compared to other organic acids. Indeed, the fitted line from the IC data matched within
10% error the MG·1H2O and OA signal from Aerosol CIMS in the last hour of photooxidation
(Figure 2.10). The excellent agreement between IC and Aerosol CIMS suggests that most of MG
was depleted at the end of photooxidation, and the Aerosol CIMS signal is solely attributed to OA
at this point.
The decay of MG is not first-order, and it appears that a fraction of MG is constantly regenerated
during the photooxidation. This feature is similar to the GLY decay in the 3 mM regime (Figure
2.5a). We propose this observation is also associated with α-HHP formation.
Figure 2.10: Normalized signal of OA (blue) was obtained from the fitted line of IC data. The normalized signal of
MG (yellow) was calculated by subtracting OA normalized signal from total signal of MG + OA (black) obtained
from the Aerosol CIMS.
2.3.4 TOC Concentration and Carbon Balance
The TOC concentrations from 3 mM GLY, 0.3 mM GLY, and 3 mM MG photooxidation
experiments are shown in Figure 2.11a−c. The reconstructed TOC concentrations are calculated as
the total of GLY or MG and their major products. Both the measured and reconstructed TOC
profiles are the average of the experimental replicates. Note that the measured TOC data were not
necessarily obtained from the same experimental replicates of the reconstructed TOC. As shown
in the figures, the measured TOC concentrations constantly decrease, most likely due to formation
of CO2 and volatile species during the photooxidation. The measured TOC profiles in the current
study show excellent agreement with that reported in our previous TOC-AMS study (Lee et al.
2011), confirming the reproducibility of our experimental setup. In all the three experiments
72
conducted, the reconstructed TOC profiles match the measured profiles fairly well (to within 20%),
indicating that Aerosol CIMS detects all the major compounds involved in the photooxidation.
Figure 2.11: Measured and reconstructed TOC concentration in 3 mM glyoxal (GLY) (a), 0.3 mM GLY (b), and 3
mM methylglyoxal (MG) photooxidation experiments. Photooxidation was initiated at time 0 (dashed line). The
measured TOC shows the results from the offline TOC analyzer whereas the reconstructed TOC is calculated from
the total of the quantified organic species (i.e., excluding α-HHPs and oligomers); see text. CIMS data represent the
average of 2−3 independent experimental replicates, and the error bars represent fluctuations between the replicates
(1 σ).
However, note that the reconstructed TOC of 3 mM GLY and MG (Figure 2.11a,c) underestimates
the carbon concentration immediately after the initiation of the photooxidation but better matches
with the measured TOC later on. This initial underestimation of carbon concentration was observed
to be less obvious in the case of 0.3 mM GLY (Figure 2.11b). We propose that the initial
underestimation of carbon concentration is due to α-HHPs, which are excluded from TOC
reconstruction due to the inability to quantify these species. These species convert to compounds
that are considered in the reconstructed TOC in the later period of photooxidation.
It was observed that GLY·1H2O and GLY·2H2O show different decay profiles during
photooxidation (Figure 2.12), with that of GLY·1H2O slower than GLY·2H2O. One possible
73
explanation for this observation is that GLY·2H2O is more reactive to OH radicals because the
bond dissociation energy of a C−H bond on a diol carbon is lower (Ervens et al. 2003). As the
hydration equilibria between GLY·1H2O and GLY·2H2O may not be established instantaneously
(Ervens and Volkamer 2010), a difference in their decay kinetics may arise. Alternatively, a
fraction of α-HHPs may regenerate GLY and MG in the solution during photooxidation. Under a
condition in which aldehydes, H2O2 and α-HHPs are all being consumed, such as during
photooxidation, R-2.1 indicates that the equilibrium is more likely to shift toward the
decomposition of α-HHP. In the case of GLY photooxidation, GLY·1H2O is directly regenerated
from HHPE·1H2O via the reverse reaction of R2.6 (Figure 2.3), compensating a fraction of the
GLY·1H2O decay. However, a significant amount of GLY·2H2O is assumed not to be directly
regenerated because GLY·2H2O is not expected to effectively form α-HHP species (see Figure
2.3). We cannot exclude the possibility that this regeneration of GLY·1H2O also occurs in the
heated volatilization line. The observed slow decay of MG is very likely due to the same
regeneration of MG·1H2O from α-HHPs (R2.9).
Figure 2.12: Decay time profiles of GLY·1H2O and GLY·2H2O during one typical photooxidation experiment. The
α-HHP equilibrium was fully established before the photooxidation was initiated at time 0 (dashed line).
Other deviations between measured and reconstructed TOC may have been caused by the
uncertainties associated with the quantification of GLY and MG. In particular, the different decay
kinetics of GLY·1H2O and GLY·2H2O have caused perturbation in the hydration equilibria of
GLY, making the estimation of total GLY concentration not straightforward.
74
A question arises here: why Lee et al. (2011) underestimated the TOC at the early stage of
photooxidation using coupled AMS and IC measurements, if α-HHPs are indeed converted to GLY
or FA which are detectable by AMS and offline IC analysis? A possible explanation is that the
AMS in Lee et al. (2011) mainly detected the GLY·2H2O form of GLY in solution. Indeed, in the
current study, we found that if the total GLY concentration is estimated by using the GLY·2H2O
signal instead of GLY·1H2O, the decay of GLY is found to be faster and resembles the GLY decay
obtained in Lee et al. (2011). Also, Lee et al. (2011) employed a diffusion drier to dry the generated
particle flow prior to online AMS analysis. Because nonhydrated GLY and GLY·1H2O are more
volatile than GLY·2H2O, they may have partitioned into the gas phase during the drying process
and may not have been detected by the AMS, leading to an underestimation of the TOC
concentration. The arguments above lead to the conclusions that the missing carbon in Lee et al.
(2011) is likely to be the fraction of GLY·1H2O regenerated from α-HHPs in the photooxidation.
2.3.5 Evidence of Oligomer Formation
It is now evident that oligomers, including nitrogen- and sulfur-containing species, are formed via
photochemistry of GLY and MG (Altieri et al. 2006, Carlton et al. 2007, Altieri et al. 2008, Tan et
al. 2009, Galloway et al. 2009, Perri et al. 2009, Tan et al. 2010). Lim et al. (2010) proposed that
oligomerization becomes dominant when initial GLY concentrations exceed the mM level due to
more active radical−radical reactions. From the 3 mM GLY photooxidation experiment, formation
of malonic acid (MA) and succinic acids (SA) was observed using Aerosol CIMS. MA, a C3
diacid, and SA, a C4 diacid, are considered to be oligomers formed during photooxidation. The
observed formation of these two species was significantly lower than the other organic acids, and
their signals are close to the detection limits: 0.002 mM for MA and 0.003 mM for SA. The time
profiles of these two (Figure 2.13) acids imply that SA is formed first, and a fraction of it may have
converted into MA during the photooxidation. This observation agrees with the aqueous-phase
photooxidation mechanism of SA that is described in Gao and Abbatt (2011). We believe that
small concentrations of MA and SA at early times (Figure 2.13, from 0 to 25 min) are due to
contamination carried over from the calibration. Oligomer formation was also observed in 3 mM
MG photooxidation, but MA and SA peaks overlap with those of hydroxypyruvic acid (Altieri et
al. 2008) and mesoxalic acid (Tan et al. 2010), respectively. Oligomer formation was not observed
from the 0.3 mM GLY concentration regime.
75
Figure 2.13: Formation of MA and SA in 3 mM GLY photooxidation.
According to the simulation conducted by Lim et al. (2010), the mass based yield of oligomers
may be around 10% when 3 mM initial GLY concentration is used. With the uncertainties in our
observed and reconstructed TOC, we cannot rule out that 10% of the C resides in an oligomeric
form that we do not observe. Also, it is possible that weakly bound oligomers decompose to smaller
species in the heated transfer line leading to the Aerosol CIMS. However, succinic and malonic
acids are present at low concentrations, representing roughly 1% of the mass. Because Lee et al.
(2010) also did not observe significant oligomer formation, it is possible that the relatively low
H2O2 photolysis efficiency in our system may lead to little oligomer formation; i.e., it is likely that
we do not have sufficient OH radical concentration to bring the reaction into the regime in which
radical−radical reactions, and therefore oligomer formation, are activated.
2.4 Conclusions
Aerosol chemical ionization mass spectrometry (Aerosol CIMS) with the I− reagent ion was used
to monitor aqueous-phase photooxidation of glyoxal (GLY) and methylglyoxal (MG). The major
organic acids produced from photooxidation matched those reported from previous studies.
Oligomer formation was confirmed but was a minor contribution to the total organic carbon (TOC)
concentration. The reconstructed TOC concentrations are in good agreement with directly
measured values, indicating that the current method can simultaneously detect all the major species
involved in the photooxidation of GLY and MG. Having demonstrated the usefulness of Aerosol-
76
CIMS in monitoring a rapidly evolving chemical system in the aqueous phase, we have applied
the Aerosol-CIMS to a more complex chemical system in Chapter 3.
The current study reports the first direct detection of α-hydroxyhydroperoxides (α-HHPs) from
reactions between GLY and MG with H2O2 in the aqueous phase. Significant, rapid α-HHP
formation occurred once H2O2 was added to the GLY or MG solutions in the dark. α-HHPs were
determined to be equilibrium products and can reversibly regenerate GLY and MG upon H2O2
quenching. The equilibrium constants of the α-HHP equilibria with H2O2 and GLY/MG were
calculated to be between 40 and 200 M−1.
α-HHP formation has implications for laboratory studies, and perhaps for some situations in the
ambient environment also. In cloud or fog water, typical concentrations of GLY and MG are at the
range of micromolar levels (Matsumoto et al. 2005) and the H2O2 concentration does not usually
exceed 100 μM (Sakugawa et al. 1990). Under these cloud and fog water conditions, α-HHP
formation is unlikely to be very active. In aerosol, however, Paulson and co-workers (Hasson and
Paulson 2003, Arellanes et al. 2006, Wang et al. 2011) have reported unexpectedly high
concentrations of H2O2. From filter sample analyses and model simulations, they estimated an
average aqueous-phase H2O2 concentration of 70 mM in aerosol liquid water, nearly 3 orders of
magnitude higher than the value predicted from the Henry’s Law partitioning of H2O2 (Arellanes
et al. 2006). It is possible that the unexpectedly high H2O2 concentrations resulted from
decomposition of existing α-HHPs in the aerosol liquid water. Being equilibrium products, α-
HHPs are expected to decompose and regenerate H2O2 upon dilution from the volume of aerosol
liquid water to that of the filter extracts.
The current study has shown that α-HHP formation occurs with aldehydes in general and has
impacts on aqueous-phase chemistry, which are expected to be especially important in aqueous
aerosols where concentrations of H2O2 and aldehydes are high. In particular, photooxidation of α-
HHPs provides an additional formation pathway of FA and AA in addition to previously proposed
mechanisms. α-HHPs may also lead to slower effective loss rates of GLY and MG by regeneration
during the reactions. Finally, α-HHP formation needs to be more systematically investigated to
determine its effects upon partitioning of gases into aerosols in the environment. This study is
presented in Chapter 4.
77
Acknowledgement
We acknowledge the financial support of NSERC and QEIISST. We thank Jennifer Murphy, Milos
Marcovic, Greg Wentworth, and Philip Gregoire for IC support and Edgar Acosta and Shawna
Gao for TOC support.
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Chapter 3
Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic
Study Using Aerosol Time-of-Flight Chemical Ionization Mass
Spectrometry (Aerosol ToF-CIMS)
As published in Atmos. Chem. Phys. 14, 9695–9706, 2014. DOI:10.5194/acp-14-9695-2014
Distributed under the Creative Commons Attribution 3.0 License.
85
Abstract
Levoglucosan (LG) is a widely employed tracer for biomass burning (BB). Recent studies have
shown that LG can react rapidly with hydroxyl (OH) radicals in the aqueous phase despite many
mass balance receptor models assuming it to be inert during atmospheric transport. In the current
study, aqueous-phase photooxidation of LG by OH radicals was performed in the laboratory. The
reaction kinetics and products were monitored by aerosol time-of-flight chemical ionization mass
spectrometry (Aerosol ToFCIMS). Approximately 50 reaction products were detected by the
Aerosol ToF-CIMS during the photooxidation experiments, representing one of the most detailed
product studies yet performed. By following the evolution of mass defects of product peaks, unique
trends of adding oxygen (+O) and removing hydrogen (−2H) were observed among the products
detected, providing useful information for determining potential reaction mechanisms and
sequences. Additionally, bond-scission reactions take place, leading to reaction intermediates with
lower carbon numbers. We introduce a data analysis framework where the average oxidation state
(OSc) is plotted against a novel molecular property: double-bond-equivalence-to-carbon ratio
(DBE/#C). The trajectory of LG photooxidation on this plot suggests formation of polycarbonyl
intermediates and their subsequent conversion to carboxylic acids as a general reaction trend. We
also determined the rate constant of LG with OH radicals at room temperature to be 1.08 ± 0.16 ×
109 M-1 s−1. By coupling an aerosol mass spectrometer (AMS) to the system, we observed a rapid
decay of the mass fraction of organic signals at mass-to-charge ratio 60 (f60), corresponding
closely to the LG decay monitored by the Aerosol ToF-CIMS. The trajectory of LG photooxidation
on a f44–f60 correlation plot matched closely to literature field measurement data. This implies
that aqueous-phase photooxidation might be partially contributing to aging of BB particles in the
ambient atmosphere.
3.1 Introduction
Biomass burning (BB) is a major source of atmospheric particles and volatile organic compounds
(VOCs). Directly emitted VOCs and primary organic aerosol (POA) are subject to subsequent
atmospheric processing, leading to formation of secondary organic aerosol (SOA) (Jimenez et al.,
2009). Reliable and quantitative source apportionment is required to understand the effects of BB
on air quality and climate. Apportionment of BB is commonly done using chemical tracers
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(Simoneit, 2002). Levoglucosan (LG) is a widely used particle-phase molecular tracer of BB
(Simoneit et al., 1999), due to its source-specificity and abundance in BB aerosol.
Traditionally, LG has been considered to be highly stable in the atmosphere (Fraser and
Lakshmanan, 2000; Simoneit et al., 2004). Stability is an important requirement for a molecular
tracer as it is a major assumption made in chemical mass balance receptor models commonly
employed for source apportionment (Schauer et al., 1996; Robinson et al., 2006). However, studies
from the past decade have shown that LG is subject to atmospheric loss. For example, the
particulate concentration of LG relative to other BB tracers is lower in the summer than in the
winter, implying an enhanced photo-oxidative decay (Saarikoski et al., 2008; Mochida et al., 2010;
Zhang et al., 2010). Measurements using aerosol mass spectrometry (AMS) have also
demonstrated that the decay of BB organic aerosol signature both in the field and laboratory
experiments is accompanied by a decrease in m/z 60 and an increase in m/z 44 (Grieshop et al.,
2009; Hennigan et al., 2010; Cubison et al., 2011; Ortega et al., 2013).
The decay of LG can be explained by several pathways. Heterogeneous oxidation of LG by gas-
phase oxidants has been studied in the laboratory (Kessler et al., 2010; Hennigan et al., 2010;
Knopf et al., 2011), where it has been demonstrated that particle-phase LG can be oxidized by
hydroxyl (OH) radicals efficiently, leading to LG lifetimes on the order of days. More recently,
gas-phase oxidation has also been proposed to contribute to LG loss (May et al., 2012). A small
fraction of particle-phase LG can volatilize into the gas phase where it is oxidized efficiently. A
third explanation for the observed LG decay is reactive loss in the aqueous phase, such as cloud
water or aqueous aerosol particles. Studies from the past decade have revealed the atmospheric
aqueous phase as an important reaction medium where organic compounds can be processed,
leading to formation and aging of SOA (Blando and Turpin, 2000; Ervens et al., 2011). BB
particles can be hygroscopic, depending on their size and inorganic composition (Petters and
Kreidenweis, 2007; Petters et al., 2009); therefore, a highly functionalized and water soluble
organic species, such as LG, can be subject to aqueous-phase processing. Two laboratory studies
have investigated the kinetics of aqueous-phase OH oxidation of LG (Hoffmann et al., 2010; Teraji
and Arakaki, 2010), finding that OH is the main sink for LG in the tropospheric aqueous phase
with lifetimes on the order of hours. By contrast, little is known of the aqueous-phase reaction
mechanism of LG. The only studies are those of Holmes and Petrucci who investigated acid-
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catalyzed and OH-induced oligomerization (Holmes and Petrucci, 2006, 2007) and a recent
theoretical study of possible reaction pathways (Bai et al., 2013).
The primary objective of this work is to provide a detailed mechanistic understanding of this
oxidation chemistry, which is needed to incorporate LG photooxidation into cloud water models
and to obtain more insight into the atmospheric processing of BB particles. Additionally, we revisit
the reaction kinetics with OH radicals under conditions relevant to cloud water processing. Aerosol
time-of-flight chemical ionization mass spectrometry (Aerosol ToF-CIMS) is employed to directly
monitor LG and its reaction products in real time, after aerosolization of the reaction solution. In
addition to the powerfulness of Aerosol-CIMS described in Chapter 2, the high mass resolution of
the Aerosol ToF-CIMS enables unambiguous determination of product elemental composition,
and sheds light on fundamental aspects of aqueous-phase photooxidation. We also demonstrate a
novel analysis method, utilizing oxidation state (OSc) and double bond equivalence (DBE), to
obtain functional group information. To relate our results to previous field studies of BB aerosol,
an AMS is employed to connect the chemistry to changes in the AMS signals at m/z 60 and 44.
3.2 Experimental Methods
3.2.1 Solution Preparation and Photooxidation
A solution of LG (1mM) was prepared weekly by dissolving a commercial source (Sigma Aldrich,
99%) in Milli-Q water (18MΩ-cm; total organic carbon (TOC) ≤ 2ppb; ELGAPURELAB Flex).
The reaction solution was prepared prior to each experiment by further diluting the stock solution
in a Pyrex bottle to a volume of either 1L (for the mechanistic study) or 100 mL (for the kinetic
study) with a LG concentration of 10 µM for the mechanistic experiments or 30µM for the kinetic
experiments. H2O2 (Sigma Aldrich, ≥ 30%, TraceSELECT) was added to the solution as the
precursor of hydroxyl (OH) radicals upon irradiation. The concentration of H2O2 was typically
1mM, unless mentioned otherwise. The reaction solution was placed in a cylindrical photoreactor
(Radionex, RMR-200) which supplies UVB radiation from all sides, but not from the top or
bottom. The solution was constantly stirred by a magnetic stir bar, with a fan employed to minimize
solution heating. The solution temperature during photooxidation was approximately 301K. A
series of control experiments was performed to confirm that LG was not directly photolyzed under
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UVB light. A small amount of LG reacted upon H2O2 addition in the dark which did not affect the
results.
3.2.2 Aerosol-ToF-CIMS
The experimental apparatus is illustrated in Figure 3.1. During photooxidation, the solution was
constantly atomized by a constant output atomizer (TSI, model 3076), using compressed air (BOC
Linde, Grade 0.1) as the carrier gas. The particle flow was introduced through Siltek-coated
stainless steel tubing (1/4in. diameter, 70cm long, VWR) heated to 100 or 150◦C. Organic species
in the aqueous droplets evaporated in the heated line and were detected by a chemical ionization
mass spectrometer (CIMS). Volatilization of organic aerosol component for online detection was
first conducted by Hoffmann et al. (1998). Later, Smith and coworkers (Hearn and Smith, 2004)
coupled a heated line to a CIMS instrument and for the first time referred this system as an Aerosol
CIMS. Since then, Aerosol CIMS has been employed to investigate aqueous-phase organic
chemistry (Sareen et al., 2010; Zhao et al., 2012; Aljawhary et al., 2013).
Figure 3.1: The experimental apparatus.
The strength of Aerosol CIMS lies in the fast time response, enabling in situ monitoring of
aqueous-phase chemistry. In the current study, high mass resolution (3000 to 4000ThTh−1 in the
relevant m/z range in V-mode) and excellent detection sensitivity were achieved by employing an
Aerodyne high-resolution time-of-flight chemical ionization mass spectrometer (Bertram et al.,
89
2011). This technique is hereafter referred to as Aerosol ToF-CIMS. For all the experiments, the
ToF-CIMS was operated in V-mode, and the data were analyzed using Tofwerk v. 2.2 on IGOR
platform. To examine the accuracy of elemental assignment, we compared the oxygen-to-carbon
(O/C) and hydrogen-to-carbon (H/C) ratios measured from the LG solution to the theoretical O/C
and H/C of LG, and agreement was observed to be within 10%. More details on the data analysis
are described elsewhere (Aljawhary et al. (2013) and references herein).
Our previous study has shown that Aerosol-ToF-CIMS can target different analyte types through
the choice of reagent ion. Three reagent ions were employed in the current study: protonated water
clusters ((H2O)nH+), iodide water clusters (I(H2O)n
-) and acetate (CH3C(O)O-). The ionization
mechanisms and sensitivity of each of these reagent ions for atmospherically relevant organic
compounds have been summarized in Aljawhary et al. [2013], and are mentioned only briefly here.
(H2O)nH+ can detect organic compounds that have higher proton affinity (i.e. higher gas-phase
basicity) than water clusters ((H2O)n). (H2O)nH+is employed in the kinetic study because it detects
both LG and dimethylsulfoxide (DMSO), the kinetics reference compound (see next section).
I(H2O)n- is employed as the primary reagent ion to study reaction mechanisms because it is
sensitive to a wide spectrum of oxygenated compounds that can form clusters with I-, including
LG and its reaction products. CH3C(O)O- is also employed to study the mechanism and to confirm
the results from the I(H2O)n- experiments. CH3C(O)O- abstracts a proton from compounds that
exhibit higher gas-phase acidity than acetic acid and can selectively detect a variety of organic and
inorganic acids. Occasionally non-acid species (e.g. LG) can also form clusters with CH3C(O)O-.
3.2.3 Mechanistic and Kinetic Studies
Investigation of the reaction mechanism focused on the identification of multiple generations of
reaction products arising during photooxidation using the I(H2O)−n and CH3C(O)O− reagent ions.
The rate constant of LG reacting with OH radicals was determined using the relative rate method,
where the decay of LG is related to that of DMSO, a reference compound with well-known OH
reactivity (see Sect. 3.3.2). A fixed concentration (5µM) of DMSO (Caledon Laboratory
Chemicals, > 99 %) was added to the reaction solution prior to the initiation of photooxidation.
The signals of LG and DMSO were monitored concurrently using Aerosol-ToF-CIMS with
(H2O)nH+ as the reagent ion. The following relationship holds for the decay of LG and DMSO:
90
ln([𝐿𝐺]0
[𝐿𝐺]𝑡) =
𝑘𝐼𝐼𝐿𝐺
𝑘𝐼𝐼𝐷𝑀𝑆𝑂
× ln([𝐷𝑀𝑆𝑂]0
[𝐷𝑀𝑆𝑂]𝑡) (3.1)
where [X]t represents the signal of compound X measured at time t, and kxII represents the second-
order rate constant of X reacting with OH radicals. The relationship in Eqn. 3.1 indicates that
plotting ln([LG]0/[LG]t) against ln([DMSO]0/[DMSO]t) should result in a linear plot, with the
slope representing the ratio of the two rate constants.
The LG concentration used (10 to 30µM) is expected to be similar to cloud water concentrations,
assuming typical organic aerosol loading, LG mass fraction in organic aerosol, and complete
scavenging by a typical cloud water liquid content. Although the H2O2 concentration used in the
experiment is much higher than the ambient level, the steady-state concentration of OH was
estimated to be approximately 2 × 10−13 M from the first-order decay rate of LG. This steady-state
concentration of OH radicals is in the range relevant to cloud water (Jacob, 1986). We believe that
the reaction mechanism investigated in the current study is representative for cloud processing
given that similar reactant concentrations are used as those in cloud water.
3.2.4 Aerosol Mass Spectrometry (AMS) Measurements
In some of the experiments, a stream of the generated particles was also introduced into an
Aerodyne compact time of flight (C-ToF) AMS (Canagaratna et al. 2007) after passing through a
diffusion drier (Figure 3.1). Our previous work has shown that the AMS enables in-situ monitoring
of aqueous-phase photooxidation by measuring non-refractory components in the atomized
solution (Lee et al. 2011, Lee et al. 2012, Aljawhary et al. 2013). The time resolution of the AMS
measurement was 1 min. The data were processed using the AMS data analysis software (Squirrel,
version 1.51H for unit mass resolution data) with a corrected air fragment column of the standard
fragmentation table (Allan et al. 2004).
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3.3 Results and Discussion
3.3.1 Reaction Products and Mechanism
Using the I(H2O)−n reagent ion, roughly 50 reaction products were detected as clusters with iodide,
as described in Appendix A Table A1. The m/z of the products ranged between 173Th and 351Th
(in the form of I− clusters). While Holmes and Petrucci (2006, 2007) observed significant degree
of oligomerization with product m/z up to 1000Th, oligomers of LG were not observed. The
absence of oligomeric products might be due to (1) the initial concentration of LG being lower in
the current study (higher concentrations can facilitate oligomerization, Lim et al., 2010) or (2) the
Aerosol ToF-CIMS setup is not sensitive to oligomers. In our previous study (Aljawhary et al.,
2013), dimers of α-pinene SOA components were detected from aqueous abstract using the same
instrument hence oligomers are likely below the detection limit of the current study. That being
said, we cannot rule out the possibility that oligomers and other low-volatility compounds have
been lost to the wall of the volatilization line, if there are cold spots. Although the volatilization
line is carefully wrapped by a heating tape thoroughly and evenly to minimize cold spots, the inner
wall of the CIMS’s ion-molecular region can potentially be a cold spot because its temperature is
lower. The current study focuses on the discussion of monomeric reaction products which are
detected by the Aerosol ToF-CIMS with better sensitivity.
Overall, the observed products imply that two categories of reaction mechanisms occur in the
reaction system simultaneously: functionalization and bond scission. Functionalization reactions
modify the functional groups on the molecules but do not lead to cleavage of carbon–carbon bonds,
while bond-scission reactions result in carbon–carbon bond breakage.
3.3.1.1 Functionalization – Unique Trends of + O and − 2H
LG is detected at m/z 289 as a cluster with iodide (CH10O5I−). As the LG signal decays, peaks that
are a multiple of 16Th apart from LG (i.e., at m/z 305, 321 and 337) formed rapidly one after
another (Figure 3.2a).
Their elemental compositions are different from each other by one oxygen atom, and this trend is
herein referred to as the “+O” trend. Peaks that are a multiple of 2Th apart from LG (i.e., m/z 287,
285, and 283) are also observed one after another (Figure 3.2b). The elemental composition of
these compounds is different by two hydrogen atoms from each other, and this trend is referred to
92
as the “−2H” trend hereafter. Interestingly, the +O and the −2H trends proceed simultaneously,
forming a series of unique product patterns.
Figure 3.2: The evolution of the “+O” (a) and the “−2H” (b) series from levoglucosan (LG). The signal of each
compound normalized by the reagent ion intensity at m/z 145 (I(H2O)−) is shown as a function of the irradiation time.
The signals are multiplied by the bracketed number to be on scale.
A mass defect plot (Hughey et al., 2001) of the major products detected with the I(H2O)−n reagent
ion clearly illustrates the two trends occurring in the system (Figure 3.3a). Mass defect diagrams
plot mass defect (exact mass−nominal mass) against the exact mass of each compound. Since H
atoms and O atoms have their own mass defects (+0.007825 for H and −0.005085 for O),
compounds that are apart from each other by 2H line up on a slope of 7.77 × 10−3 while compounds
that are apart by an O line up on a slope of −3.18 × 10−4, with the slope denoting the ratio of the
mass defect and the molecular weight. The slopes representing the +2H and the –O trends that are
indicated by the dotted lines in Figure 3.3a. The time at which each peak reached its maximum
level is used to track the order of formation, and is presented by the color code. It can be clearly
seen that multiple +O and −2H trends develop in the reaction system during photooxidation (Figure
3.3a). The maximum signal intensity reached by each peak is used as an indicator of the amount
of formation and is represented by the area of the data points (in log scale). We note that different
compounds exhibit different detection sensitivity to the reagent ion of choice. Aljawhary et al.
(2013) have demonstrated that the I(H2O)−n reagent ion can detect oxygenated compounds with
93
carbon numbers of three or more with a relatively constant detection sensitivity. We consider the
signal intensity as a semi-quantitative presentation of the amount of each product.
Figure 3.3: The mass defect diagram of the major products detected using the iodide water cluster (I(H2O)−n) reagent
ion (a). The color code indicates the time at which each compound reached its maximum signal intensity and the area
of the circles represents the maximum signal intensity reached (in log scale). Compounds that did not reach their
maxima during the first 300min of illumination are shown in black. The +O and the −2H series fall on the slope
indicated by the dotted lines. The region relevant to products arising from +O and −2H trends is presented in (b). The
proposed structures of each product are shown beside the data points.
The +O trend must arise from formation of hydroxyl or hydroperoxyl functional groups because
these are the only possible mechanisms leading to addition of oxygen without losing any hydrogen.
Formation of these functional groups in the aqueous phase has been well studied (von Sonntag et
94
al., 1997). The reaction is initiated by H-abstraction and formation of an alkylperoxy radical (RO2).
RO2 can react with another RO2 or a hydroperoxy radical (HO2) to form a tetroxide intermediate
which gives rise to a variety of products (Figure 3.4, R3.1 to R3.3).
Figure 3.4: Sample reaction mechanisms that give rise to the +O and −2H trends. The tetroxide intermediate forming
from two alkylperoxy radicals can result in a variety of products as shown in (R3.1) to (R3.3), among which (R3.1)
can lead to formation of the hydroxyl functional group. A hydroperoxy functional group can be formed from RO2
+HO2 (R3.4). The hydroxyl-to-carbonyl conversion shown in (R3.5) is likely responsible for the −2H trend. Alkoxy
radicals trigger bond-scission reactions and give rise to an aldehydic compound (R3.6).
Among these reaction pathways, R3.1 gives rise to a hydroxyl functional group. When a tetroxide
is formed between RO2 and HO2 radicals (R3.4), a hydroperoxyl functional group can be generated
in analogy to R3.3. The −2H trend in LG photooxidation has been previously reported by Holmes
and Petrucci (2007), likely arising from conversion of hydroxyl functional groups into carbonyl
groups (Figure 3.4, R3.5). When the initial H abstraction occurs from a carbon atom with an
95
existing hydroxyl functional group, the subsequently formed peroxy radical leads to formation of
a carbonyl group and releases a HO2 molecule. This study demonstrates that this conversion can
occur multiple times, eventually converting a polyol into a polycarbonyl compound. To confirm
this reaction mechanism, we performed an experiment of aqueous phase photooxidation of another
polyol, erythritol, using the same experimental conditions. The same −2H trend was observed,
consistent with the proposed reaction mechanism. We note that carbonyls can be also formed via
the same mechanism leading to the formation of the hydroxyl functional group (i.e., R3.1 in Figure
3.4). However, formation via this pathway would not lead to the observed −2H trend and is likely
a minor formation pathway of carbonyls compared to R3.5.
The proposed structures of reaction products arising from the +O and −2H trends are included in
Figure 3.3b, which shows a magnified view of the relevant region on the mass defect plot. We note
that the mass spectrometric technique employed in the current work does not allow us to
unambiguously determine the chemical structures. For example, addition of one hydroperoxyl
functional group to a molecule yields the same chemical formula as compared with addition of
two hydroxyl functional groups, and our technique cannot distinguish between these two
mechanisms. Investigation of the formation hydroperoxides could be a direction for future study
since hydroperoxides present a group of highly oxygenated compounds and may alter the reaction
mechanism. Also, some bond-scission reactions can result in chemicals with the same elemental
compositions (see next section). Furthermore, the order in which the hydroxyl groups are
converted to carbonyls is difficult to ascertain. Bai et al. (2013) has demonstrated that H-
abstraction at the middle hydroxyl group of LG is energetically favored.
3.3.1.2 Bond-scission Reactions
Scission of C–C bonds is likely triggered by formation of alkoxy radicals via R2 (Figure 3.4) from
the tetroxide intermediate. Cleavage of one C–C bond gives rise to an aldehyde and an alkyl radical
(R3.6, Figure 3.4). Time series of selected major bond-scission products are shown in Figure 3.5a,
along with their elemental composition and proposed structures. As a general trend, products with
five or six carbons (i.e., products v, vi, vii) form first, followed by those with smaller carbon
numbers as photooxidation proceeds. Using the current mass spectrometric method, it is difficult
to unambiguously determine the structure of these detected species. It is also not possible to
completely rule out the possibility of the fragmentation of large ions in the mass spectrometer,
96
contributing to peaks with smaller m/z. However, the distinct time profiles observed for most of
the products imply that they are independent compounds. The proposed structures have been
estimated from a series of reaction mechanisms shown in Appendix A, Figure A1. The proposed
mechanisms have been constructed based on widely accepted reaction mechanisms, and the
sequence of product formation is consistent with the observed time series.
Figure 3.5: Evolution of bond-scission products measured by the I(H2O)−n reagent ion. Selected major products with
three to six carbons are shown in (a), with their proposed structures. The proposed reaction mechanisms leading to
their formation are attached in Appendix A Figure A1. Formation of small organic acids with one or two carbons are
shown in (b). All the signals have been normalized against the reagent ion (I(H2O)−) at m/z 145.
97
The LG photooxidation reaction system is highly complicated, as demonstrated by the proposed
mechanisms. Multiple reaction pathways can likely lead to the same product, and one chemical
formula may constitute multiple compounds with varying structures. For this reason, the current
work is not intended to determine the complete reaction mechanism but rather to elucidate the
general trend of reactions by monitoring major products detected.
We propose that bond scission may not immediately lead to compounds with fewer carbon
numbers in the case of LG photooxidation. This is because LG contains ring structures, and bond
scission can likely lead to ring cleavage before molecule fragmentation. Formation of product vii
(Figure 3.5a) presents one such example. This bond-scission product has a larger molecular weight
compared to LG. However, product vii overlaps with one of the proposed products in the +O and
−2H series (see previous sections), making it difficult to elucidate its magnitude of formation. In a
study of heterogeneous oxidation of LG and erythritol, Kessler et al. (2010) observed that the mass
loss during LG photooxidation was slower than that from erythritol and also proposed that ring
cleavage in the LG system delayed molecule fragmentation. We suspect that this delay might be
due to formation of compounds such as product vii.
Formation of small organic acids with carbon numbers equal to or less than two are also observed
as later generation products (Figure 3.5b), confirmed by both the I(H2O)−n and the CH3C(O)O−
reagent ion experiments. It is difficult to constrain the explicit formation mechanisms of these
small organic acids because they are likely formed from further photooxidation of the many
intermediate compounds discussed above. For example, it is well known that glyoxal, which is
expected to form as a bond-scission product, forms glyoxylic acid, formic acid, and oxalic acid
(Lim et al., 2010; Lee et al., 2011; Zhao et al., 2012). In particular, oxalic acid exhibited continuous
formation until the end of the photooxidation (Figure 3.5b). This observation agrees with the fact
that oxalic acid is relatively unreactive with OH radicals and presents a relatively long-lived
reservoir of organic carbon in the aqueous phase. We consider the small organic acids as the final
carbon reservoir before they either volatilize from the aqueous phase or are eventually oxidized to
CO2.
98
3.3.1.3 Obtaining Functional Group Information from the Aerosol-ToF-CIMS
As a general trend within the LG system, we hypothesize that a series of compounds containing
multiple carbonyl functional groups may form as reaction intermediates and then are subsequently
oxidized to carboxylic acids. Carbonyl functional groups have likely arisen from (1) the hydroxyl-
to-carbonyl conversion mechanism mentioned in the previous section and (2) bond scission of an
alkoxy radical yielding an aldehyde functional group (R3.6, Figure 3.4). Rapid formation of
carboxylic acids from aldehydes in the aqueous phase has been well documented (Schuchmann
and von Sonntag, 1988; Lim et al., 2010; Zhao et al., 2012). This is a mechanism unique to the
aqueous phase because it is initiated by hydration of an aldehyde or an acyl radical (Scheme 5,
Figure. A1, Appendix A).
Although the Aerosol ToF-CIMS is a powerful tool to elucidate elemental composition, its ability
to reveal functional group information is limited. Here, we present an analysis framework
employing two molecular properties, double bond equivalence (DBE) (Bateman et al., 2011) and
average carbon oxidation state (OSc) (Kroll et al., 2011), which are calculated by Eqn. 3.2 and 3.3:
DBE = #C - #H/2 + 1 (3.2)
OSc = 2 O/C – H/C, (3.3)
where #C and #H represent the numbers of carbon and hydrogen atoms contained in each product
molecule while O/C and H/C represent the oxygen-to-carbon and hydrogen-to-carbon ratios of
each product, respectively. These parameters are readily available from the high mass resolution
analysis of the Aerosol ToF-CIMS. The intensity-weighted average of DBE and OSc from the 50
products monitored by the I(H2O)n- reagent ion (Appendix A, Table A1) are displayed in Figure
3.6. While OSc exhibited continuous increase throughout the entire photooxidation experiment,
DBE exhibited an increase at the beginning but a decrease in the latter half of the experiment. An
increase in DBE can be attributed to formation of (1) carbon–carbon double/triple bonds, (2) ring
structures, or (3) carbon–oxygen double bonds (i.e., C=O in carbonyl or carboxylic acid). Under
an oxidative environment, formation of (1) and (2) is unlikely. Therefore, we conclude that the
initial increase of DBE is due to formation of C=O functional groups in the solution. The later
decrease of DBE is due to molecule fragmentation, making compounds with smaller #C dominate
in the later stages of the photooxidation. To compensate this fragmentation effect, we introduce a
99
novel molecular property, DBE-to-carbon ratio (DBE/#C), which represents the average number
of DBE associated with each carbon. The intensity-weighted average DBE/#C exhibited
continuous increase (Figure 3.6), approaching 1 by the end of the photooxidation experiment. Note
that the theoretical maximum value of DBE/#C is 1. This observation indicates that a C=O double
bond is associated with almost every carbon by the end of photooxidation.
Figure 3.6: Intensity-weighted average of double bond equivalence (DBE), DBE-to-carbon ratio (DBE/#C), and
oxidation state (OSc) as a function of irradiation time.
Although DBE/#C alone cannot distinguish between C=O bonds in carbonyl and carboxylic acid
functional groups, plotting OSc against DBE/#C provides another dimension to the data analysis.
This approach takes advantage of the fact that conversion of a carbonyl (i.e., aldehyde) to a
carboxylic acid involves increase in the molecular OSc, but the DBE/#C remains the same. OSc is
chosen instead of O/C here because O/C is affected by non-oxidative processes, such as hydration
of aldehydes, while OSc is not (Kroll et al. 2011). The trajectory of intensity-weighted average OSc
vs. DBE/#C is shown in Figure 3.7, color coded by the illumination time. During the first 150min
of illumination, both OSc and DBE/#C increase rapidly, leading to a dramatic and linear movement
on the plot with a slope of 3. From 150 to 300min of irradiation, the increases of OSc and DBE/#C
are both slower, but with OSc increasing faster, leading to a slope of 4.3. During the last 150min
of irradiation, DBE/#C stays almost constant at 0.82, close to its theoretical maximum, while OSc
still exhibited slow but continuous increase. The slope during this time period is 9.
100
Figure 3.7: OSc vs DBE/#C plot. The intensity-weighted average OSc and DBE/#C from the products listed in
Appendix A Table A1 are displayed here. The color code represents the illumination time. The coordinates of major
compounds are also shown.
This observation is interpreted as observational evidence of polycarbonyl intermediates rapidly
forming in the solution during the early stages of photooxidation, giving rise to rapid increase in
both DBE/#C and OSc. As the illumination reaches 4h, the average DBE/#C reaches 0.8,
indicating the abundance of C=O functional group at this moment. At the final stages of
photooxidation, aldehyde-to-carboxylic acid conversion becomes dominant, leading to a greater
increase in OSc relative to DBE/#C. In addition to the intensity-averaged trajectory, we also added
representative compounds and major products detected during the photooxidation on the OSc vs.
DBE/#C plain (Figure 3.7).
101
Starting from levoglucosan at the left bottom corner, the major products sequentially formed
during photooxidation are located towards the right upper corner of the plot. Oxalic acid, located
at the right upper corner, presents the theoretical maximum for both DBE/#C and OSc. The
averaged trajectory passes through these major products.
Figure 3.8: A simplified overview of reaction mechanisms discussed in the current study. Solid arrows represent
proposed reaction pathways of LG upon OH oxidation. The dashed arrows illustrate the complicity in the reaction
system where each product can also take more than one reaction path.
3.3.1.4 Summary of Reaction Mechanism
As can be seen from the discussion thus far, the reaction mechanisms of the aqueous-phase LG
photooxidation by OH is highly complicated. Figure 3.8 provides a simplified overview of the
mechanisms discussed in the current study. Oxidized by OH, a LG molecule can likely undergo
one of the following reaction pathways: (1) formation of a hydroxyl or hydroperoxyl functional
group, (2) conversion of a hydroxyl group into a carbonyl group, and (3) bond-scission reactions
to form products with reduced carbon number. Among these three pathways, (1) and (2) present
functionalization reactions, and consecutive occurrence of these two pathways has likely given
rise to the observed +O and −2H trends. In fact, each product formed also has the opportunity to
undergo one of the three reaction pathways mentioned above, forming a complicated reaction
system (illustrated by the dashed arrows in Figure 3.8). We propose that multiple OH oxidation
eventually lead to a group of polycarbonyl intermediates that exhibit high DBE/#C values. Further
102
oxidation has likely led to formation of small organic acids, presenting the last organic carbon
reservoir in the aqueous solution.
3.3.2 Kinetic Study
As mentioned in the experimental section, the kinetics of LG photooxidation was investigated
under atmospherically relevant conditions, using DMSO as a reference compound. Both LG and
DMSO decayed rapidly as soon as photooxidation was initiated. Typically, with 0.5mM H2O2 in
solution and over 30min of illumination, LG decayed to 70% of its starting value whereas DMSO
decayed by approximately 80% (Figure 3.9a). Data were plotted in the form of Eqn. 3.1, as
illustrated in Figure 3.9b for one run. Five experiments were performed to determine kLGII (Table
3.1) where the value of kDMSOII , 5.6 × 109 M−1 s−1, was taken to be the average of literature values
(4.5 × 109 to 6.9 × 109 M−1 s−1 (Milne et al., 1989; Bardouki et al., 2002; Zhu et al., 2003). The
concentration of H2O2 was varied between 0.5 and 1.5M, but this variation did not affect the kLGII
value obtained, consistent with the assumption that the concentration of OH is not of relevance to
the relative rate method. The reproducibility of our experiments was excellent, and we report a
value of 1.08 ± 0.16 × 109 M−1 s−1, where the uncertainty reflects the standard deviation of the slope
in the relative kinetic plot.
Table 3.1: Summary of the conditions and the results of the kinetic experiments.
Exp. # [LG] (µM)
[DMSO]
(µM) [H2O2] (mM) kIILG (M-1 s-1)
1 30 5 0.5 8.06 × 108
2 30 5 1 1.10 × 109
3 30 5 1 1.08 × 109
4 30 5 1.5 1.23 × 109
5 30 5 0.5 1.16 × 109
Average 1.08 ± 0.16 × 109
103
Hoffmann et al. (2010) have previously reported 2.4 ± 0.3 × 109 M−1 s−1 at 298K while Teraji and
Arakaki (2010) have measured 1.6 ± 0.3 × 109 M−1 s−1 at 303 K, pH 8. Although the kLGII value
obtained from the current work is lower than previously reported, the agreement is reasonable
considering the different methods employed. Hoffmann et al. (2010) used an excess amount of LG
and monitored pseudo first-order decay of OH radicals. Teraji and Arakaki (2010) also used an
excess amount of LG, and calculated kLGII from the observed formation rate of a probe compound.
This study is the first relative rate measurement, using direct measurement of LG.
Figure 3.9: The time series of LG and DMSO during a kinetic experiment (Exp. #1 in Table 3.1) are shown in (a).
The signals are normalized to those at the beginning of the photooxidation. The relative kinetics plot from the same
experiment is shown in (b) according to Eqn. 3.1. The color code indicates the illumination time.
The slower reaction rate observed in the current work can potentially be due to LG desorbing from
the wall of the volatilization line, delaying the decay monitored by the CIMS. LG exhibits
104
substantially lower volatility than DMSO, hence more interaction can be expected between the
wall and the LG compared to DMSO. If the decay of LG has been delayed relative to DMSO due
to wall desorption, the results from the relative kinetic method may be biased. In fact, the diffusion
limited rate constant of LG oxidation by OH radicals in the aqueous phase is estimated by us to be
1.9 × 109 M−1 s−1 (see Appendix A, Sect. A3 for detailed calculations). The results from the two
previous studies are closer to this estimated value, and we consider our result a lower limit of the
reaction kinetics.
3.3.3 Comparison with AMS Data
Decay of LG was accompanied by a decay of f60 monitored by the AMS (Figure 3.10a). The decay
rate of f60 appears slower than that of LG, perhaps due to the fact that compounds other than LG
can also give rise to f60 in AMS. A simultaneous increase in f44 was also observed, indicating
formation of oxygenated compounds such as organic acids, consistent with the proposed
mechanisms mentioned above. The trend of decreasing f60 and increasing f44 closely resembles
that from field measurements of BB particles and heterogeneous oxidation of BB particles in the
laboratory (Cubison et al., 2011; Ortega et al., 2013). Cubison et al. (2011) have demonstrated that
the ratio of f44 to f60 changes in a non-linear manner, approaching a background level of f60 at
0.003, as the photochemical age of the BB air mass increases. Figure 3.10b demonstrates this trend
from the compiled field data in Cubison et al. (2011). Overlayed on this plot is the f44 to f60
trajectory obtained from the current work, color coded by the illumination time, which correlates
nicely with field observations. This agreement is somewhat surprising given that the only reactive
precursor is LG whereas BB particles in the environment contain a complex mixture of organic
compounds. Oxidation of this complex and condensation of gasphase organic acids could also
contribute to an increase in f44. Nevertheless, the current work indicates that aqueous phase
photooxidation can qualitatively lead to similar observations as in the field, contributing to BB
particle aging that arises from other mechanisms such as heterogeneous and gas-phase
photooxidation.
105
Figure 3.10: The decay of levoglucosan monitored by the Aerosol ToF-CIMS and the decay of f60 monitored by the
AMS (a), and the f60 vs. f40 trajectory from the current work compared to field measurements (b). The trajectory
obtained in the current work is color coded with irradiation time. The compiled data (Cubison et al., 2011) from field
measurements in fire plumes (grey) and non-fire plumes (brown) are also shown.
3.4 Conclusions and Environmental Implications
This study presents the first detailed study of levoglucosan (LG) oxidation by OH radicals in the
aqueous phase by online mass spectrometry: aerosol time-of-flight chemical ionization mass
spectrometry (Aerosol ToF-CIMS). Being a soft ionization mass spectrometric technique, Aerosol
ToF-CIMS is extremely useful in elucidating the elemental composition of the reaction products,
106
which sheds light on fundamental chemistry of aqueous-phase photooxidation. This type of
analysis is difficult to perform using hard ionization mass spectrometry.
Functionalization and bond-scission reactions occurred simultaneously in the reaction system.
While bond-scission reactions contributed to formation of smaller organic compounds,
functionalization reactions gave rise to distinct trends of “+O” and “−2H” on mass defect plots.
We propose that these trends arose from formation of hydroxyl and/or hydroperoxyl functional
groups and conversion of hydroxyl to carbonyl functional groups, respectively. As a result, a
compound with multiple hydroxyl functional groups, such as LG, can rapidly yield polycarbonyl
intermediates, representing a general reaction mechanism for polyols.
The current study introduces DBE-to-carbon ratio (DBE/#C) as a novel analysis framework for
high-resolution mass spectrometric data. It is particularly useful in photooxidation because DBE
is most likely arising from formation of C=O in carbonyls and carboxylic acids. The degree of
polycarbonyl formation was observed to be extensive, leading to the average DBE/#C reaching 1
at the end of the photooxidation. As photooxidation proceeds further, these polycarbonyl
intermediates are converted into carboxylic acids, as is inferred from a OSc-to-DBE/#C plot. This
framework can be applied to other soft ionization mass spectrometric techniques with high mass
resolution, providing functional group information.
From the kinetic experiments, the rate constant of LG reacting with OH radical was determined to
be 1.08 ± 0.16 × 109 M−1 s−1, indicating that LG loss due to aqueous-phase photooxidation can be
significant, with a significant portion of LG lost during a typical lifetime of BB particles. This loss
rate should be taken into account when LG is applied as a BB marker in chemical mass balance
receptor models.
Using the AMS, simultaneous decay of f60 and increase in f44 were observed during LG aqueous
oxidation, yielding behavior similar to that observed from field measurements. This observation
qualitatively indicates that aqueous-phase photooxidation may be partially contributing to the
observed decay of LG in the field and observed aging of BB particles.
107
Acknowledgement
The authors thank NSERC for funding, J. L. Jimenez for offering the field data, Aerodyne Inc. for
technical support, and CFI for funding the purchase of the CIMS.
Supplementary Information
Supplementary information of this chapter is given in Appendix A.
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Chapter 4
Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):
Potential Atmospheric Impacts
As published in Atmos. Chem. Phys. 13, 5857–5872. DOI:10.5194/acp-13-5857-2013
Distributed under the Creative Commons Attribution 3.0 License.
114
Abstract
The focus of this work is on quantifying the degree of the aqueous-phase formation of α-
hydroxyhydroperoxides (α-HHPs) via reversible nucleophilic addition of H2O2 to aldehydes.
Formation of this class of highly oxygenated organic hydroperoxides represents a poorly
characterized aqueous-phase processing pathway that may lead to enhanced SOA formation and
aerosol toxicity. Specifically, the equilibrium constants of α-HHP formation have been determined
using proton nuclear-magnetic-resonance (1H NMR) spectroscopy and proton-transfer-reaction
mass spectrometry (PTR-MS). Significant α-HHP formation was observed from formaldehyde,
acetaldehyde, propionaldehyde, glycolaldehyde, glyoxylic acid, and methylglyoxal, but not from
methacrolein and ketones. Low temperatures enhanced the formation of α-HHPs but suppressed
their formation rates. High inorganic salt concentrations shifted the equilibria toward the hydrated
form of the aldehydes and slightly suppressed α-HHP formation. Using the experimental
equilibrium constants, we predict the equilibrium concentration of α-HHPs to be in the µM level
in cloud water, but it may also be present in the mM level in aerosol liquid water (ALW), where
the concentrations of H2O2 and aldehydes can be high. Formation of α-HHPs in ALW may
significantly affect the effective Henry’s law constants of H2O2 and aldehydes but may not affect
their gas-phase levels. The photochemistry and reactivity of this class of atmospheric species have
not been studied.
4.1 Introduction
Recent studies have shown that organic peroxides can be a significant portion of secondary organic
aerosol (SOA) (Bonn et al., 2004; Docherty et al., 2005; Kroll and Seinfeld, 2008). Besides their
contribution to SOA, organic peroxides also damage plant leaves (Polle and Junkermann, 1994),
contribute to acid precipitation by oxidizing SO2 to H2SO4 in the aqueous phase (Lind et al., 1987),
and regenerate OH radicals (Matthews et al., 2005; Monod et al., 2007; Roehl et al., 2007;
Kamboures et al., 2010). α-Hydroxyhydroperoxides (α-HHPs) constitute a class of organic
peroxide that has been observed in the ambient environment. In particular, hydroxymethyl
hydroperoxide (HMP) is the most frequently detected α-HHP in the ambient gas phase (He et al.,
2010), rain water (Hellpointner and Gab, 1989; Sauer et al., 1996), and cloud water (Sauer et al.,
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1996; Valverde-Canossa et al., 2005), as reviewed by Hewitt and Kok (1991) and Lee et al. (2000).
Other α-HHPs such as 1-hydroxyethyl hydroperoxide, 1-hydroxypropyl hydroperoxide, and bis-
hydoxymethyl hydroperoxide have also been detected in the air or in cloud water, but much less
frequently (He et al., 2010; Lee et al., 1998; Bachmann et al., 1992; Hewitt and Kok, 1991).
Despite their observation in the atmosphere, our understanding of the formation mechanisms of α-
HHP is still incomplete. It has been suggested that the recombination reaction of peroxy radical
(RO2) and hydroperoxy radical (HO2), which is the major formation of organic hydroperoxides in
gas phase, may not be a major formation pathway for α-HHPs (Carter et al., 1979; Atkinson, 1990;
Gab et al., 1995). Instead, other formation pathways, including aqueous-phase reactions have been
proposed (Figure 4.1). The first formation pathway, herein referred to as the Criegee pathway,
involves hydrolysis of the stabilized Criegee intermediate (SCI) generated during alkene
ozonolysis (Lee et al., 2000; Hasson et al., 2003; Ziemann and Atkinson, 2012). The second
pathway involves reversible addition of H2O2 to carbonyls and is herein referred to as the carbonyl
pathway (Hellpointner and Gab, 1989; Zhou and Lee, 1992). The Criegee pathway has gained the
majority of attention because α-HHPs have been observed from laboratory ozonolysis of a variety
of alkenes and monoterpenes (Hewitt and Kok, 1991; Neeb et al., 1997; Sauer et al., 1999; Hasson
et al., 2001; Hasson and Paulson, 2003; Wang et al., 2012). This reaction pathway occurs in both
the gas and aqueous phases, but a few studies (Gab et al., 1995; Chen et al., 2008; Wang et al.,
2012) have shown that aqueous-phase ozonolysis may lead to more efficient formation of α-HHPs
compared to their gas-phase counterparts. In these studies, however, α-HHPs formed in the
aqueous phase dominantly decomposed to H2O2 and aldehydes when analysed under dilute
conditions. The observed rapid decomposition of α-HHPs in such laboratory experiments has lead
to a general perception that α-HHPs are unstable, and are merely a class of intermediates in the
formation of carbonyls and H2O2 during ozonolysis.
However, as shown in Chapter 2, α-HHP formation was observed using advanced mass
spectrometric techniques, arising from H2O2 addition to carbonyl compounds (Lee et al., 2011;
Zhao et al., 2012) and laboratory SOA extract (Liu et al., 2012) using advanced mass spectrometric
techniques. Specifically, in our previous work (Zhao et al., 2012), α-HHP formation from glyoxal
and methylglyoxal with H2O2 was monitored using an iodide (I−) chemical ionization mass
spectrometer coupled to a heated inlet line (Aerosol CIMS). This technique enabled the direct
116
detection and characterization of α-HHPs using online mass spectrometry. In particular, the
formation of αHHPs from glyoxal and methylglyoxal was observed to be fast and reversible, with
equilibrium constants between 40 and 200M−1 for both compounds. As described below, an
equilibrium constant of this magnitude suggests that α-HHPs could be formed in significant
concentrations in aerosol liquid water (ALW) if aldehyde and H2O2 concentrations are high
(Arellanes et al., 2006; Volkamer et al., 2009; Lim et al., 2010). However, the quantification using
Aerosol CIMS is potentially complicated by thermo-decomposition of α-HHPs and unknown
processes involving droplet evaporation in the heated inlet, giving rise to the need for a more
quantitative study using alternative techniques.
We note that although the carbonyl pathway is rarely discussed in the atmospheric chemistry
literature, it has been studied somewhat in the 1940s and 1950s by physical organic chemists using
high precursor concentrations. For example, the formation of α-HHPs has been observed from
several aldehydes (Satterfield and Case, 1954; Sander and Jencks, 1968) and ketones (Milas and
Golubovic, 1959a, b). These early works established the reaction mechanism of the carbonyl
pathway: the reaction proceeds via a nucleophilic addition of H2O2 to a non-hydrated carbonyl
because the carbonyl carbon acts as an efficient electrophile. In particular, Satterfield and Case
(1954) found that the initial rate of H2O2 addition to aldehydes increases in the following order:
formaldehyde < acetaldehyde < propionaldehyde. The explanation for this observed trend is the
difference in the aldehydes’ degree of hydration, with the most hydrated aldehyde (i.e.
formaldehyde) exhibiting the slowest rate of H2O2 addition. This observation leads to their
conclusion that H2O2 addition has to occur on non-hydrated aldehydic functional groups. We also
note that a closely related particle-phase reaction, peroxyhemiacetal formation (Figure 4.1,
pathway 3), which involves nucleophilic addition of an organic hydroperoxide to an aldehyde, has
been previously proposed (Tobias and Ziemann, 2000). As of late, small carbonyls have been
gaining attention as potential SOA precursors via aqueous-phase processing (Ervens et al., 2011).
The formation of α-HHP via the carbonyl pathway may change the physico-chemical properties
of carbonyl-containing SOA in a different way compared to other relatively well known
mechanisms such as OH radical oxidation, thus representing an additional mechanism of aqueous-
phase processing. Once formed in the aqueous-phase, α-HHPs may also react with OH radicals
(Zhao et al., 2012). How this class of compound may alter the reaction mechanisms proposed for
aqueous-phase chemistry is still unclear at the moment.
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Figure 4.1: Two aqueous-phase pathways of α-hydroxyhydroperoxide (α-HHP) formation: 1) The Criegee Pathway,
2) the Carbonyl pathway, and a related reaction 3) Peroxyhemiacetal formation.
Given that the potential of many carbonyls to form αHHPs is currently unknown, the specific goals
of this work were to experimentally determine the equilibrium constants of α-HHP formation via
the carbonyl pathway from a range of atmospherically relevant carbonyl compounds using two
separate analytical methods: proton nuclear magnetic-resonance (1H NMR) spectroscopy and
proton transfer reaction mass spectrometry (PTR-MS). 1H NMR spectroscopy directly quantifies
the chemical changes in the aqueous phase when a carbonyl is mixed with H2O2, and is particularly
well suited for the investigation of thermodynamic equilibria. On the other hand, online PTR-MS
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measurement of the gas-phase concentration of carbonyls after addition of H2O2 provides better
insight into the kinetics of the reactions and can assess the impact of α-HHP formation on the
effective Henry’s law constants (KHeff) of the carbonyls. We note that thermodynamic information
of the type derived in this paper is required to quantify the importance of different derivative
organics in aerosol and cloud water, and yet it is frequently missing from the literature. The paper
concludes with an assessment of the atmospheric importance of α-HHP formation by the carbonyl
pathway.
4.2 Experimental Methods
4.2.1 1H NMR Measurements
The formation of α-HHPs from a suite of atmospherically relevant carbonyl species has been
studied: formaldehyde (Sigma Aldrich, 37 wt% in water with 10–15% methanol as stabilizer),
acetaldehyde (Sigma Aldrich, > 99.5 %), propionaldehyde (Sigma Aldrich, <97%), glycolaldehyde
(Sigma Aldrich, in solid dimer form), glyoxal (Sigma Aldrich, 40 wt % in H2O), methylglyoxal
(Sigma Aldrich, 40 wt % in H2O), glyoxylic acid (Sigma Aldrich, 50 wt % in H2O), methacrolein
(Sigma Aldrich, 95%), methylethyl ketone (ACP Chemicals Inc., 99%), and acetone (EMD,
99.8%). These compounds have low molecular weights and exist largely in the gas phase.
However, several compounds (e.g. glyoxal, methylglyoxal, glyoxylic acid, and glycolaldehyde)
are quite water soluble and can be important aqueous-phase SOA precursors (Carlton et al., 2007;
Altieri et al., 2008; Perri et al., 2009; Ervens and Volkamer, 2010; Lim et al., 2010; Tan et al.,
2010; Ervens et al., 2011; Lee et al., 2011; Ortiz-Montalvo et al., 2012; Zhao et al., 2012).
Aqueous solutions (10 mM) of a targeted carbonyl were prepared individually from the
commercial standards mentioned above. A known concentration (0.5 mM) of dimethylsulfoxide
(DMSO, Fisher Scientific, 99.9%) was added as an internal standard to assist the quantification
and chemical shift calibration. A portion of commercial H2O2 stock solution (Sigma Aldrich, 30%
in water) was also added to the carbonyl solutions shortly after they were prepared at
concentrations usually between 8.9 and 20 mM, but up to 100 mM for ketones and methacrolein
due to insignificant αHHP formation from these species. A 500µL aliquot of the mixed solution
was transferred into a 500µL glass NMR tube along with 25 µL of D2O (Cambridge Isotope
Laboratories, Inc., 99.96%) as a lock reagent for the 1H NMR measurement. Using an autosampler
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(Bruker B-ACS 120), 1H NMR spectra were acquired with a Bruker Avance 500 MHz
spectrometer using a 1H, 19F, 13C, 15N 5 mm quadruple resonance inverse (QXI) probe fitted with
an actively shielded Z gradient. 1H NMR experiments were performed with presaturation using
relaxation gradients and echoes (PURGE) (Simpson and Brown, 2005) water suppression and 128
scans, a recycle delay of 3s, and 16K time domain points. Spectra were apodized through
multiplication with an exponential decay corresponding to 0.3Hz line broadening in the
transformed spectrum and a zero filling factor of 2, then manually phased and calibrated to the
DMSO at 2.5ppm. The recycle delay was set at 5 times the measured T1 to ensure full relaxation
between scans. Spectral predictions were performed in Advanced Chemistry Development’s
ACD/SpecManager using a neural network prediction algorithm (version 12.5). All calculations
were performed using water as the solvent with a spectral line shape 2Hz chosen to match those
of the real datasets as closely as possible.
For most of the samples, the 1H NMR spectra were taken within 24h after the samples were
prepared, and within 48h for a small number of samples. The time scale of α-HHP equilibration is
30 to 60min (confirmed in the PTR-MS experiments), so the equilibria should be fully established
when 1H NMR spectra are taken. The sample solutions were no longer protected from room light
once loaded on the autosampler. To examine potential evaporation of carbonyls and OH generation
from H2O2 photolysis, some methacrolein samples were analysed a second time 10 hours after the
first measurement. Methacrolein was chosen because it is the most volatile aldehyde studied here
(Allen et al., 1998) and is highly reactive to OH radicals (Herrmann et al., 2010). The concentration
of methacrolein did not show observable change before and after 10 hours of room light exposure,
and so it is assumed that evaporative loss and room-light exposure induced negligible effects to
other samples as well.
The temperature inside the NMR instrument was controlled at 25◦C. A NMR tube typically stayed
inside the instrument for 20 min for the homogenization of its magnetic field before the spectra
were acquired. Water blanks and control experiments were performed to ensure that the peaks in
the spectra are not from H2O2 reacting with water impurities or DMSO. The effect of pH was not
examined. Previous studies reported that acid can catalyse the rate of α-HHP formation and
decomposition, but does not affect the equilibria (Marklund, 1971; Zhou and Lee, 1992).
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4.2.2 Effects of Inorganic Salts
Aerosol liquid water (ALW) can contain high concentrations of inorganic salts up to and beyond
their saturation concentrations (Tang et al., 1997), making it important to investigate the effect of
high concentrations of aqueous-phase inorganic salts on the equilibria. To do this, 1 M of either
(NH4)2SO4 (AS) or Na2SO4 (SS) was added to a number of acetaldehyde and glycolaldehyde
samples. The NMR probe used in the current method is not compatible with any higher salt
concentrations. The salts were added after the α-HHP equilibrium had been fully established.
4.2.3 PTR-MS Measurements
To confirm the equilibrium constants determined by 1H NMR spectroscopy and further investigate
the effects of these condensed-phase equilibria to the KHeff of the carbonyls, a setup involving a
bubbler and a PTR-MS (Ionicon Analytik, quadruple mass spectrometer) was used, as shown in
Figure 4.2. This system was used to measure the effect of H2O2 addition to the gas-phase mixing
ratio of the carbonyls.
Figure 4.2: Experimental setup for the PTR-MS measurements.
Ultra-pure N2 (BOC Linde, grade 4.8) was introduced to a temperature-controlled glass bubbler
containing an aqueous solution (10 mM) of a carbonyl compound. The gas-phase carbonyl loading
exiting the bubbler was measured by the PTR-MS after dilution (2 to 3 lpm) with ultra-pure N2.
The bubbler was placed in the dark during experiments to minimize light exposure. Teflon lines
and connections were used downstream of the bubbler to minimize surface reactions and loss of
carbonyls. N2 was continuously introduced through the carbonyl solution until a stable PTR-MS
121
signal was achieved at the mass-to-charge ratio (m/z) of the protonated carbonyl. A known
concentration of H2O2 (typically 8.9 to 17.7 mM) was then added to the bubbler, and the N2 flow
was resumed until the PTR-MS signal reached a new equilibrium. Equilibrium constants were
determined from the difference of the carbonyl signals detected before and after the H2O2 injection.
With the detection limit set by the PTR-MS, this approach could be used only for sufficiently
volatile carbonyls: acetaldehyde, propionaldehyde, methacrolein, methylethyl ketone, and
acetone. The experiments were typically performed at 25 ◦C except for those with acetaldehyde
reaction giving rise to the formation of 1-hydroxyethyl hydroperoxide (1-HEHP), which were
conducted also at 15 and 5 ◦C.
4.2.4 Reversibility Test: Addition of Catalase
In both the NMR and PTR-MS experiments, catalase from bovine liver was added to the reaction
mixture to react away H2O2 to test the reversibility of the reaction. In our previous study (Zhao et
al., 2012), quenching of H2O2 led to the decomposition of α-HHPs and regeneration of the original
aldehydes. For the 1H NMR experiments, 1 µL of the catalase solution (Sigma Aldrich, 34 mg
protein mL−1) was added to 1mL of the carbonyl-H2O2 reaction mixtures after the equilibrium was
fully established. Control experiments were performed to confirm that there was no contribution
of catalase to the 1H NMR spectra. For the PTR-MS experiments, one drop of catalase was added
to the 25mL reaction mixture after the equilibrium was fully established. The N2 flow was resumed
after the catalase addition, and the change of the carbonyl signals was monitored. Control
experiments demonstrated that catalase did not cause any change in the PTR-MS signal at the m/z
of interest.
4.3 Results and Discussion
4.3.1 1H NMR Results
With the exclusion of methacrolein, significant changes in the 1H NMR spectra were observed for
all the aldehydes upon addition of H2O2 to the carbonyl solution, with the magnitude of the change
increasing with the concentration of H2O2. The reactions were also observed to be largely
reversible from the catalase addition experiments. As described below, the formation of α-HHP
from acetone and methylethyl ketone was observed to be minor. Spectral assignment was based
122
on manual interpretation and comparison to standards, followed by confirmation using spectral
prediction.
Figure 4.3: 1H NMR spectra for acetaldehyde. (a): Acetaldehyde aqueous solution; (b): 17.7 mM of H2O2 was added
to the acetaldehyde solution; (c): Catalase was added to the solution to quench H2O2. The insets are the magnified
view of certain regions of the spectra. The split pattern and the identity of each peak are shown in the brackets (the
numbers match those in the chemical structures).
The experiment involving acetaldehyde is shown in Figure 4.3 as an example. Before the addition
of H2O2, acetaldehyde and its hydrated gem-diol coexist in the solution (Figure 4.3a). Based on
their chemical shift and splitting patterns, the identities of the peaks are assigned and labelled.
After addition of 17.7 mM of H2O2 (Figure 4.3b), two new peaks appeared at chemical shifts 5.06
and 1.06ppm, respectively, corresponding to the V and VI protons in 1-HEHP. It is not surprising
that the two new peaks appeared very close to the peaks of hydrated acetaldehyde (i.e. the III and
5
4
3
2
1
0
x10
6
10 8 6 4 2 0 -2
Chemical Shift (ppm)
2.0x106
1.5
1.0
0.5
0.0
Sig
na
l In
ten
sity (
AU
)
2.0
1.5
1.0
0.5
0.0
x10
6
5.10 5.00
Chemical Shift (ppm)
5.10 5.00
Chemical Shift (ppm)
5.10 5.00
Chemical Shift (ppm)
1.10 1.00
Chemical Shift (ppm)
1.10 1.00
Chemical Shift (ppm)
1.10 1.00
Chemical Shift (ppm)
(I, q)
(III, q) (IV, d)
(DMSO, s)
(II, d)
(I, q)
(I, q)
(III, q)
(III, q)
(DMSO, s)
(DMSO, s)
(II, d)
(II, d)
(IV, d)
(IV, d)
H2O
H2O
H2O
(V, q) (VI, d)
From Catalase
From Catalase
a)
b)
c)
123
IV protons), given the similar structure between hydrated acetaldehyde and 1HEHP. The
reversibility of the reaction was confirmed upon addition of catalase (Figure 4.3c), with the spectra
then resembling those at the start of the experiment.
Figure 4.4: Hydration equilibrium constant (Khyd), the α-HHP formation equilibrium constant (Keq) and the apparent
α-HHP formation equilibrium constant (Kapp). Please see the text for details.
The water peak was very large in each spectrum even with the water suppression procedures, such
that some overlapping analyte peaks complicated their peak assignment and quantification. For
peaks partially overlapping with water (e.g. at 5.04 ppm in Figure 4.3), baseline corrections were
performed before quantification. Also, we note that the gain of each NMR spectrum was auto-
adjusted by the instrument so that the quantification of compounds had to be conducted by
comparing the analytes’ peak area and number of protons (#H), with signals arising from 0.5 mM
of DMSO added as the internal standard. The calculation was performed in the following manner
(Wallace, 1984):
Concentration of analyte (M)
Concentration of Internal Standard (M)
=Peak area of analyte
Peak area of internal standard×
#Hinternal standard
#Hanalyte (4.1)
Based on the quantified concentrations, we calculated three equilibrium constants: the hydration
equilibrium constant (Khyd), equilibrium constant for α-HHP formation (Keq), and the apparent
124
equilibrium constant for α-HHP formation (Kapp). The relationship between the three constants is
illustrated in Figure 4.4, and their definitions are below:
Khyd =[Carbonylhyd]eq
[Carbonylnon−hyd]eq (4.2)
Keq =[α−HHP]eq
[H2O2]eq ×[Carbonylnon−hyd]eq (4.3)
Kapp =[Total α−HHP]eq
[H2O2]eq ×[Total Carbonyl]eq (4.4)
where [Carbonylhyd]eq and [Carbonylnon-hyd]eq represent the equilibrium concentrations of the
hydrated form and the non-hydrated form of a carbonyl, respectively. The hydration equilibria of
many atmospherically relevant carbonyls are well studied, and so, comparing our results to the
literature values is a good way to verify our 1H NMR method. In Eqn. 4.3, [α-HHP]eq and
[H2O2]eq represent the equilibrium concentrations of an α-HHP and H2O2.. The usefulness of the
Keq defined this way is, however, limited especially for dicarbonyls such as methylglyoxal that can
form multiple α-HHP equilibria. Unambiguous determination of all the Keq values is also
impossible because some of the peaks are missing due to overlap with the water peak. Kapp, on the
other hand, is a better indicator for the overall potential of α-HHP formation from each carbonyl
compound. The [Total α-HHP]eq and [Total Carbonyl]eq in Eqn. 4.4 represent the summed
equilibrium concentrations of α-HHPs and carbonyls (i.e. hydrated and non-hydrated forms),
respectively. Given that the Khyd values did not change with the H2O2 addition, [Total Carbonyl]eq
can be estimated from determination of the concentration of either the hydrated or non-hydrated
form of the carbonyl. Thus the use of Kapp negates the need for unambiguous assignment of all the
peaks. We also note that Eqn 4.2 to 4.4 indicate that Kapp and Keq / Khyd should be essentially equal
if the aldehydes exist mostly in the hydrated form. We have used this relationship as an
125
independent confirmation of our measurement reliability (see Sect. 4.3.3). The measured Khyd and
Kapp values of the carbonyls using 1H NMR are tabulated in Table 4.1 and Table 4.2, respectively,
along with values from the literature. The determined Keq values are reported in Table B1 in
Appendix B.
Table 4.1: Summary of hydration equilibrium constants (Khyd) measured by NMR. The constants are reported with
their standard deviation arising from the number of replicates indicated on the table.
NMR (this work) a Literature
Khyd # replicates Khyd
Formaldehyde b >18 14 2.3 × 10
3 [1]
Acetaldehyde 1.43 ± 0.04 15 1.43 [2]
Propionaldehyde 1.26 ± 0.13 16 0.7 [2]
Glycolaldehyde 16.0 ± 1.3 16 10 [3]; c 17.5 [4]
Methacrolein b <0.005 16 -
Glyoxal d n.d. 16 2.2 × 10
5 [5]
Methylglyoxal b >57± 155 16 2.3 × 10
3 [5]
Glyoxylic acid b >18 16 3000 [6]
Acetone b <0.002 2 0.002 [7]
Methylethyl ketone b <0.005 6 -
a References used: [1] Betterton and Hoffmann, 1988; [2] Greenzaid et al., 1967; [3] Sorensen, 1972; [4] Yaylayan et
al.. 1998; [5] Wasa and Musha, 1970; [6] Sorensen, 1974; [7] Bruice et al., 2004
b Calculated using the limit of quantification of the current methods.
c In D2O.
d n.d.: The value is not determined due to overlapping of analyte peaks with the water peak.
126
Table 4.2: Summary of the apparent equilibrium constants of α-HHP formation (Kapp) measured and reported in
literature at 25 ˚C. The constants are reported with their standard deviation acquired from the number of replicates
shown on the table.
NMR Measurement PTR-MS Measurement a Literature
Kapp
(M-1)
#
Replicates
Catalase
Recovery
(%)
Kapp
(M-1)
#
Replicates
Catalase
Recovery
(%)
Kapp
(M-1)
Formaldehyde
b 164 ± 31 12 c
p.o. d n.p. n.p. n.p.
126 [1]
150 [2]
94 [3]
Acetaldehyde 94.8 ± 12.5 11 97 ± 1 132 ± 15 8 95.8 48 [3]
Propionaldehdye 51.1 ± 8.0 12 83 ± 3 84 ± 12 8 85 -
Glycolaldehyde 43.3 ± 3.9 12 89 ± 4 n.p. n.p. n.p. -
Methacrolein 0.8 ± 0.7 12 n.p. en.d. 6 n.p. -
Glyoxal n.d. 12 p.o. n.p. n.p. n.p. 40 - 200 [4]
Methylglyoxal f 25 ± 4 12
g 85 n.p. n.p. n.p. 40 - 200 [4]
Glyoxylic acid f440 ± 270 13
g78 n.p. n.p. n.p. -
Acetone h <0.008 2 n.p. n.d. 6 n.p. -
Methylethyl
ketone h <0.02 6 n.p. n.d. 4 n.p. -
a References used: [1] Marklund, 1972; [2] Zhou and Lee, 1992; [3] Kooijiman and Ghijsen, 1947; [4] Zhao et al.
2012
b Including the formation of BHMP (see text).
c p.o.: Values could not be determined due to peaks overlapping with the H2O peak.
d n.p.: Experiment not performed.
e n.d. Not detected at the current detection limit of PTR-MS.
fA significant amount of formic acid was observed. The Kapp value is determined with the consideration of irreversible
formic acid formation.
g A decreasing trend of the recovery with increasing concentration of H2O2 addition.
h Calculated using the limit of quantification of the current methods.
127
4.3.2 PTR-MS Results
Acetaldehyde, propionaldehyde, methacrolein, acetone, and methylethyl ketone were detected in
their protonated form at m/z 45, 59, 71, 59, and 73, respectively. Besides their protonated
molecular ions, three other major fragment ions at m/z 31, 39, and 49 were detected from
propionaldehyde, and one major fragment ion at m/z 55 was detected from methylethyl ketone.
For these two carbonyls, the total signal intensity of the protonated molecular ion and the major
fragments were used for quantification. No α-HHP signal was detected using the current PTR-MS
method.
Figure 4.5 illustrates data from a sample experiment for acetaldehyde at 25◦C. Acetaldehyde signal
normalized to the H3O+ reagent ion became stable 20 min after a 10 mM solution was placed in
the bubbler at time (i). After 17.7 mM of H2O2 was injected into the solution at time (ii), the
acetaldehyde signal decreased and rapidly reached a new equilibrium due to the formation of 1-
HEHP in the solution. Upon addition of catalase at time (iii), the acetaldehyde signal recovered
close to its original level. A similar trend was observed for propionaldehyde, but methacrolein,
acetone, and methylethyl ketone did not show any observable change upon H2O2 addition.
Figure 4.5: Sample time series of signal due to gas-phase acetaldehyde in the PTR-MS experiment. The acetaldehyde
signal normalized to the reagent ion is shown as a function of time. Time (i): 25 mL of clean water in the bubbler is
replaced by 25 mL of acetaldehyde solution (10 mM), Time (ii): 13.3 mM of H2O2 is added to the acetaldehyde
solution, Time (iii): one drop of catalase stock solution is added.
128
The equilibrium constants of α-HHP formation from acetaldehyde and propionaldehyde were
calculated from the difference in their signals before and after H2O2 addition (Table 4.2). The Kapp
values defined in Eqn. 4.4 are calculated by using the aldehyde signal after the H2O2 addition as
[Total Carbonyl]eq, the magnitude of change in the aldehyde signal as [Total α-HHP]eq, and the
difference between the total H2O2 concentration and [Total α-HHP]eq as [H2O2]eq. The calculation
of Kapp here is based on assumptions that (1) the non-hydrated forms of acetaldehyde and
propionaldehyde detected by the PTR-MS are proportional to their total concentrations in the
solution (i.e. their Khyd values remain constant), and (2) their signal change is solely due to α-HHP
formation. The first assumption is verified by the observation from the 1H NMR experiments that
Khyd values stayed constant regardless of the amount of H2O2 addition.
The validity of the second assumption is challenged by irreversible processes potentially occurring
in the system, such as oxidation reactions induced by H2O2 and volatilizational loss of the
aldehydes due to bubbling. To examine formation of irreversible products, particularly organic
acids, the PTR-MS was operated under the scan mode (m/z 20 to 120), but no change was observed
in the mass spectra aside from the decay of the protonated molecular ion and major fragments.
Additionally, the recovery of acetaldehyde and propionaldehyde were observed to be 96 and 85
%, respectively (Table 4.2). The high recovery illustrates that the reaction is mostly reversible due
to α-HHP formation. The volatilizational loss of acetaldehyde and propionaldehyde from pure
solutions at 25 ◦C over two hours of bubbling could be up to 11 and 14%, based on the flow rate
of N2 through the bubbler, the solution volume, concentration, and the Henry’s law constants (KH)
of the two aldehydes.
4.3.3 Comparison of Equilibrium Constants
In general, the Khyd values showed good agreement with values from the literature (Table 4.1), and
the Kapp values determined from the two methods reasonably agreed with each other and with the
literature (Table 4.2). The agreement between Kapp and Keq/Khyd was good (Appendix B, Table B1)
for acetaldehyde, propionaldehyde, and glycolaldehyde, but the values of formaldehyde showed a
deviation of more than a factor of 4 (see discussion for formaldehyde below). The inability of
methacrolein, acetone, and methylethyl ketone to form α-HHP was confirmed from both methods.
Formic acid formation was observed upon H2O2 addition to methylglyoxal and glyoxylic acid.
129
Detailed discussion of results for each compound is provided below, and an example 1H NMR
spectra for each compound is provided in Appendix B.
4.3.3.1 Formaldehyde
The equilibrium concentration of formaldehyde was calculated by subtracting the amount of
hydroxymethyl hydroperoxide (HMP) observed (Figure 4.6, proton III) from the total
concentration of 10 mM. In particular, the Khyd of formaldehyde is so large that the aldehydic
proton peak (proton I) was below the 1H NMR detection limit, which is determined to be
approximately 100 µM. This observation is supported by the large Khyd value in the literature: 2.3
× 103 (Betterton and Hoffmann, 1988). The methylene proton peak (II) was also not observed in
the 1H NMR spectra likely due to overlap with the water peak.
We propose that the small peak that appeared at 4.94 ppm is due to formation of bis-hydroxymethyl
hydroperoxide (BHMP, proton IV). This peroxyhemiacetal compound forms by HMP further
reacting with non-hydrated formaldehyde. BHMP has been observed in a number of laboratory
studies (Marklund, 1971; Zhou and Lee, 1992; Gab et al., 1995) and in the atmosphere (He et al.,
2010). The Kapp for BHMP formation (Kapp,BHMP) is calculated by Eqn. 4.5,
Kapp,BHMP =[BHMP]eq
[HMP]eq ×[Total Carbonyl]eq (4.5)
to be 12.0 ± 1.3 M−1 (where the uncertainties are precisions derived from a number of replicates),
showing excellent agreement with two reported values: 11.7 M−1 from Zhou and Lee (1992) and
14.0 M−1 from Marklund (1971). The overall Kapp value for formaldehyde is determined to be 164
± 31 M−1. This value is slightly larger than the three literature values reported because those values
are for only HMP formation, while the value in this work incorporates BHMP formation.
The deviation between Kapp and Keq/Khyd was larger compared to acetaldehyde, propionaldehyde,
and glycolaldehyde (Appendix B, Table B1). We are not entirely sure about the reason for this
deviation, but it could be due to the fact that we used a Khyd value from the literature not measured
in our own system, and/or that formaldehyde forms BHMP beside HMP and exhibits a more
complicated reaction pathway.
130
Figure 4.6: 1H NMR spectra of a formaldehyde-H2O2 mixture. The splitting pattern and assignment of the peaks are
shown in the bracket.
4.3.3.2 Acetaldehyde
The Khyd value, 1.43 ± 0.04, agrees very well with the reported value (Greenzaid et al., 1967). Our
measured value of Kapp, 94.8 ± 12.5 M−1, is larger than the only literature value by a factor of 2
(Kooijman and Ghijsen 1947). The results from the PTR-MS, 132 ± 15 M−1, showed reasonable
agreement with the 1H NMR results.
8x106
6
4
2
0
Sig
nal In
tensity (
AU
)
5.0 4.5 4.0 3.5 3.0 2.5 2.0
Chemical Shift (ppm)
BHMP (IV, s)
HMP (III, s)
H2O
(methanol, s)
(DMSO, s)
131
4.3.3.3 Propionaldehyde
The experimental Khyd value, 1.26 ±0 .13, was slightly larger than the reported value 0.7 (Greenzaid
et al., 1967). The agreement between the 1H NMR and the PTR-MS measurements was fair, with
the Kapp value determined to be 51.1 ± 8.0 and 84 ± 12M−1, respectively. The catalase recovery was
83 ± 3 and 85 %, respectively.
4.3.3.4 Glycolaldehyde
Glycolaldehyde solutions were prepared by dissolving glycolaldehyde dimer (2,5-dihydroxy-1,4-
dioxane) in water. The major peaks in the 1H NMR spectra were from glycolaldehyde monomers,
indicating that monomerization proceeds almost to completion in the solution at the current
concentration used (Yaylayan et al., 1998; Glushonok et al., 2000). The observed Khyd value, 16.0
± 1.3, fell into the same range as several other reported Khyd values (Sorensen, 1972; Yaylayan et
al., 1998). There are no prior reports of the equilibrium constant of α-HHP formation.
4.3.3.5 Methacrolein
Among the carbonyl compounds studied, methacrolein was the only aldehyde that did not show
significant α-HHP formation, as confirmed by both the 1H NMR and PTR-MS studies. The Kapp
was determined to be 0.8 ± 0.7 M−1 from the 1H NMR, but no observable α-HHP formation was
observed using PTR-MS. We propose that the carbonyl group and the C=C double bond in
methacrolein form π-electron conjugation which stabilizes the aldehyde from nucleophilic attacks.
Although Claeys et al. (2004) proposed a mechanism of polyol formation from methacrolein and
H2O2 in the particle phase (Claeys et al., 2004), no such products were observed in the current
experiment.
4.3.3.6 Glyoxal
No quantitative data for glyoxal could be acquired from the current study. In particular, the PTR-
MS is not highly sensitive to glyoxal, and most of the glyoxal peaks in the 1H NMR spectra were
hidden behind the water peak. The only literature value for Kapp of glyoxal is from our previous
work (Zhao et al., 2012), where we estimated the lower limit of Kapp to be 40 M−1 using an Aerosol
CIMS.
132
4.3.3.7 Methylglyoxal
Hydration and α-HHP formation occurring on one or both of the carbonyl groups in methylglyoxal
would lead to a slightly different chemical environments for the protons, making the 1H NMR
spectra of methylglyoxal highly complicated. We performed peak assignment based on the
predicted chemical shift of each proton by spectra prediction and on changes in the peak intensity
upon H2O2/catalase additions, but the peak assignment for methylglyoxal is associated with a
higher level of uncertainty than with the other molecules. A non-negligible amount of formic acid
formation was also observed with H2O2 addition (8.2 ppm, Figure B2 in Appendix B). Formic acid
likely forms irreversibly, as shown by a decreasing trend in catalase recovery, 91, 87, and 84%,
with increasing amount of H2O2 addition: 10, 15, and 20 mM. We assumed that formic acid
formation was slow compared to the α-HHP formation equilibrium, such that Kapp can still be
calculated from the amount of α-HHP formed and methylglyoxal remaining. This way, the Kapp
value is determined to be 25 ± 4 M−1. This value falls below the range of our previous estimation:
40–200 M−1 (Zhao et al., 2012). The discrepancy between the two studies may be explained either
by the uncertainties associated with the Aerosol CIMS method (see Introduction), or by the
methylglyoxal peak assignment here.
4.3.3.8 Glyoxylic Acid
The 1H NMR spectra of glyoxylic acid solutions indicates that it exists mostly in its hydrated form,
qualitatively agreeing with its large reported Khyd value (3 × 103, Sorensen et al., 1974). Upon H2O2
addition, a significant amount of formic acid formation (8.1ppm, Figure B5 in Appendix B) – up
to 50 % of the total glyoxylic acid – was observed. Irreversible formic acid formation from
glyoxylic acid and H2O2 in the aqueous phase is well documented (Tan et al., 2009; Lee et al.,
2011; Ortiz-Montalvo et al., 2012). We propose that at least some of the glyoxylic acid exists in
its α-HHP form because the decay of glyoxylic acid was larger than the amount of formic acid
formation, and some of glyoxylic acid was regenerated with catalase addition. However, a reliable
quantification of the Kapp value is highly challenging, as reflected by the large uncertainties in the
reported value (440 ± 270 M−1).
133
4.3.3.9 Acetone and Methylethyl ketone
The two ketones studied did not exhibit significant α-HHP formation in either the 1H NMR or the
PTR-MS experiments. In general, ketones are known to be relatively stable against nucleophilic
addition as compared to aldehydes. This is because the additional alkyl group stabilizes the
carbonyl functional group via electron donation. Such a trend can be also seen from the small Khyd
reported for ketones (e.g. 2.0 × 10-3 for acetone, Bruice, 2004). The unstable nature of α-HHPs
from ketones has also been reported previously (Sauer et al., 1999; Wang et al., 2012). However,
we note that these simple ketones do not fully represent the diversity of ketones in SOA. In fact,
the current work and past studies have implied α-HHP formation on the ketone group of
methylglyoxal (Stefan and Bolton, 1999; Zhao et al., 2012).
4.3.4 Temperature Dependence of Kapp
We observed enhanced 1-HEHP formation from acetaldehyde with decreasing temperature, but
with slower reaction rates. Example data are shown in Figure 4.7a. The ratio of acetaldehyde signal
to its initial level at 5, 15, and 25 ◦C is plotted as a function of time. The injection of H2O2 (13.3
mM) was performed at time (i). The time required for equilibration was approximately 1, 2, and 5
hours at the three temperatures. The signal level at equilibrium, determined by fitting an
exponential function to the signal, decreases with decreasing temperature, as indicated by the
horizontal dashed lines in Figure 4.7a. The temperature dependence observed here implies more
significant α-HHP formation at colder temperatures. The Kapp values determined at the three
temperatures are listed in Table 4.3. From a van’t Hoff plot of these data (Figure 4.7b), a positive
slope was obtained corresponding to a standard enthalpy change (Δ◦H) of −29.7 ± 1.3 kJ mol−1.
Since the equilibrium is reached slowly in the 15 and 5◦C experiments, we can estimate the rate
coefficient of 1-HEHP formation by fitting an exponential curve to the decaying acetaldehyde
signal and obtaining its slope at early reaction times where there is no reverse reaction occurring
and the initial concentrations of acetaldehyde and H2O2 are known. Using this method, the second-
order rate constants of 1-HEHP formation were determined to be 0.012 ± 0.002 and 0.0045 ±
0.0005 M−1 s−1 at 15 and 5 ◦C, respectively. The kinetics at 25 ◦C were too fast to be estimated. We
note that the pH of the solution is not controlled in our experiment. Even though the equilibrium
134
is independent of the solution pH, both the formation and decomposition rates of α-HHP have been
reported to be pH dependent (Zhou and Lee, 1992).
Figure 4.7: Typical acetaldehyde time profiles at 5, 15 and 25 ˚C are shown in (a). The ratios of signal at a given time
to the initial signal are shown. H2O2 (13.3 mM) was injected to the 10 mM acetaldehyde solutions at time (i). The
dashed lines show the signal levels at equilibrium. The van’t Hoff diagram for 1-hydroxyethyl hydroperoxide (1-
HEHP) formation from acetaldehyde is shown in (b). The dashed lines connects +1 σ and -1 σ from the average
ln(Kapp) determined at the three temperatures.
Table 4.3: Temperature dependence of the apparent equilibrium constant (Kapp) of 1-hydroxyethyl hydroperoxide (1-
HEHP) formation from acetaldehyde.
Temperature (˚C) Kapp (M-1) # Replicates
25 132 ± 15 12
15 206 ± 40 6
5 311 ± 38 8
135
4.3.5 Effects of Inorganic Salt Addition
The results of the inorganic salt addition experiments are summarized in Table 4.4. We observed
that the addition of AS and SS caused a small increase in Khyd and a small decrease in Kapp for both
acetaldehyde and glycolaldehyde. To assess whether the differences are statistically significant,
one-tail t tests were performed to make comparisons between the average Khyd and Kapp values with
and without salt addition, and the p values from the t tests are listed in Table 4.4. P values that are
statistically significant at the 95% confidence level (i.e. p < 0.05) are indicated with an * label in
Table 4.4. All the equilibrium constants for glycolaldehyde and the Khyd of acetaldehyde with AS
addition have been determined to be statistically significant, whereas the other three values point
in the same direction but with less statistical significance.
Table 4.4: Effects of inorganic salt addition on the hydration equilibrium constant (Khyd) and the apparent α-HHP
formation equilibrium constant (Kapp).
Acetaldehyde Glycolaldehyde
Experiment Khyd and Kapp (M-1) # Replicates p-value Khyd and Kapp (M-1) # Replicates p-value
No Salt
Khyd 1.43 ± 0.04 15 - Khyd 16.0 ± 1.3 16 -
Kapp 94.8 ± 12.5 11 - Kapp 43.3 ± 3.9 12 -
1M (NH4)2SO4
Khyd 1.48 ± 0.07 4 0.11 Khyd 17.8 ± 0.3 3 *4.3 × 10-5
Kapp 81.3 ± 12.7 3 *4.0 × 10-3 Kapp 35.6 ± 2.4 3 *9.7 × 10-5
1M Na2SO4
Khyd 1.58 ± 0.04 3 0.10 Khyd 18.5 ± 0.5 3 *3.8 × 10-3
Kapp 82.3 ± 10.0 3 0.072 Kapp 30.8 ± 2.4 3 *4.8 × 10-4
*Statistically significant at the 95% confidence level (p-value < 0.05).
These observations qualitatively agree with Yu et al. (2011), who observed that addition of SS
shifted the hydration equilibrium of glyoxal to the dihydrated form of the monomer. The
enhancement of Khyd and the suppression of Kapp by SS and AS observed in the current study is
likely arising from similar effects at the molecular level, especially those associated with SO42-.
The current observation implies that the inorganic effects may affect aqueous-phase equilibria of
136
aldehydes in general. Yu et al. (2011) suggested that this effect might be more pronounced for
aldehydic functional groups adjacent to an electron-withdrawing group (e.g. glyoxal).
Glycolaldehyde has an additional electron-withdrawing hydroxyl group compared to
acetaldehyde, which may explain why the inorganic salt effect appears to be larger for
glycolaldehyde.
4.4 Atmospheric Implications
With the first thorough assessment of the equilibrium constants for α-HHP formation, we can
make initial assessments for the likely atmospheric significance for these compounds.
4.4.1 Equilibrium concentrations of α-HHPs in cloud water and aerosol liquid water
The amount of α-HHP formation via the carbonyl pathway in atmospheric aqueous phases is
directly dependent on the abundance of the different reactants. Cloud/fog water and ALW are
commonly considered as two qualitatively different reaction media (Volkamer et al., 2009; Ervens
and Volkamer, 2010; Lim et al., 2010) due to orders of magnitude differences in their liquid water
content (LWC), surface-to-volume ratio, and aqueous-phase reactant concentrations. The
aldehyde species studied here span a wide range of water solubility. Specifically, the aqueous-
phase concentrations of volatile species such as acetaldehyde, propionaldehyde, and methacrolein,
whose KH values are typically below 20 M atm−1 (Zhou and Mopper, 1990; Allen et al., 1998), are
expected to be low. However, aqueous-phase concentrations of highly water-soluble aldehydes,
such as glycolaldehyde, methylglyoxal, and glyoxal can be substantial. In particular, the
concentration of glyoxal can be up to hundreds of µM in polluted fog water (Carlton et al., 2007;
Tan et al., 2009) and has been proposed to be present up to the molar level in ALW (Volkamer et
al., 2009). Furthermore, there are also studies suggesting that H2O2 concentration in ALW can also
be unexpectedly high. Based on filter extracts of ambient aerosol and model calculations,
Arellanes et al. (2006) suspected that H2O2 concentration in ALW might be up to 100 mM,
although there is some possibility that the H2O2 that is detected has arisen from decomposition
from other species or been formed post collection in such off-line analyses. The concentration of
H2O2 in cloud water usually does not exceed 100 µM (Sakugawa et al., 1990).
137
Figure 4.8: Simulation of the equilibrium concentration of α-hydroxyhydroperoxide ([α-HHP]eq) arising from various
equilibrium concentrations of H2O2 ([H2O2]eq) and total aldehyde ([Total Aldehyde]eq). The concentrations are all
presented in log scale. Conditions relevant to cloud water and aerosol water are also indicated. This simulation
considers α-HHP formation via only the Carbonyl Pathway, with an average equilibrium constant of 100 M-1.
Assuming an average Kapp of 100 M−1, which is approximately the middle point of the measured
Kapp values from the current study, we calculated the concentrations of α-HHPs that would be
present with various equilibrium concentrations of H2O2 and total aldehyde (Figure 4.8). Note that
the effect of inorganic salts is not considered in this calculation but our studies suggest that these
effects are likely to be minor relative to the uncertainties in the assumed reactant concentrations.
The simulation indicates that α-HHP formation in cloud water is unlikely to be significant, with
its concentration not exceeding 10 µM even with the highest combination of reactant
concentrations. In ALW, however, α-HHP concentrations may be comparable to that of H2O2.
When the equilibrium concentrations of H2O2 and aldehydes reach 10 mM and 100 mM, their
respective upper limits in ALW, 100 mM of α-HHPs may be formed.
-6
-5
-4
-3
-2
log
( [H
2O
2] e
q (
M)
)
-6 -5 -4 -3 -2 -1
log( [Total Aldehyde]eq (M) )
Cloud Water Relevant Conditions
Aerosol Liquid Water Relevant Conditions
-10 -8 -6 -4 -2
log( [a-HHP]eq (M) )
138
Table 4.5: Conditions assumed in the atmospheric partitioning simulation of 1 ppb of aldehydes or H2O2.
Cloud Water Aerosol Liquid Water (ALW)
Temperature 25 C˚ 25 C˚
Atmospheric
Pressure 1 atm 1 atm
Liquid Water
Content (LWC) 1 g m-3 1 ug m-3
Aqueous-phase
H2O2 100 uM 10 mM
Aqueous-phase total
Aldehyde 100 uM 100 mM
4.4.2 Impact of α-HHP formation on the atmospheric partitioning of aldehydes and H2O2
The water solubility of α-HHP can be very high. The KH has only been reported for one α-HHP,
i.e. that from formaldehyde (HMP): 5 × 105 M atm−1 (Zhou and Lee, 1992) and 1.67 × 106 M atm−1
(O’Sullivan et al., 1996). These values are two orders of magnitude larger than that of
formaldehyde and one order of magnitude larger than that of H2O2. This implies that the formation
of α-HHP in the aqueous phase will enhance the KHeff of aldehydes and/or H2O2:
KHeff,Ald = KH,Ald(1 + Kapp[H2O2]aq) (4.6)
KHeff,H2O2= KH,H2O2
(1 + Kapp[Total Aldehyde]aq) (4.7)
Note that the KH values for aldehydes are the effective Henry’s law constant of these aldehydes
over pure water (i.e. they incorporate the hydration reaction of these aldehydes in water). The KHeff
and KH values used here should be considered as Henry’s law constants with and without α-HHP
formation, respectively. As shown in Eqn. 4.6 and Eqn. 4.7, the enhancement of KHeff compared to
KH depends on the value of Kapp and the amount of H2O2 or total aldehyde existing in the aqueous
phase.
We simulated the partitioning of an initial mixing ratio of 1ppb gas-phase aldehyde or H2O2 that
is exposed to typical cloud water or ALW conditions, both with and without α-HHP formation
(see Table 4.5). In particular, in the case of the aldehydes, we assume a fixed concentration of
139
H2O2 in solution (as specified in Table 4.5), and in the case of H2O2, we assume a fixed
concentration of dissolved total aldehydic functional group. The LWC is orders of magnitude
higher in the cloud water scenario than with ALW, i.e. 1 g m−3 vs. 1µg m−3. By contrast, the
equilibrium concentrations of total aldehyde and H2O2 are assumed to be much higher in the ALW
case. The purpose of this simple simulation is to assess how the enhancement of KHeff arising from
α-HHP formation leads to an associated alteration in the gas-aqueous phase partitioning of H2O2
and aldehydes based only on the thermodynamic equilibria of Henry’s law partitioning and α-HHP
formation. Kinetic issues, such as formation rate constants and mass transfer rates, are not
addressed, and we assume the α-HHPs are involatile. We again stress that the chemical
concentrations in ALW are highly uncertain. The assumed concentrations here (i.e. 10 mM for
H2O2 and 100 mM for total aldehyde) can be considered as their respective upper limits, and these
calculations should be viewed as a simple modelling exercise to highlight potential atmospheric
importance only. The simulation was performed for formaldehyde, acetaldehyde and H2O2, and
the results are shown in Table 4.6.
Without α-HHP formation, the majority of formaldehyde and acetaldehyde exists in the gas phase
under both scenarios, leaving their gas-phase mixing ratio essentially unaffected at 1ppb. More
than half of the H2O2 population will dissolve into the aqueous phase under the cloud water
scenario due to its relatively high KH, but the majority stays in the gas phase under the ALW
scenario due to the small LWC. The measured Kapp values for formaldehyde and acetaldehyde from
the current work are used for the simulation of α-HHP formation. For the case of H2O2 simulation,
an average Kapp of 100 M−1 was assumed.
The first conclusion from the simulation is that, in the ALW scenario, KHeff values of H2O2 are
enhanced by up to an order of magnitude relative to the KH values when α-HHP formation occurs,
while the enhancement in the cloud water scenario was minor. However, even with such large
enhancement in the KHeff values, the gas-phase mixing ratio of aldehydes and H2O2 are essentially
unchanged from the case without α-HHP formation because of the low LWC. The KHeff values for
formaldehyde and acetaldehyde were also enhanced by over a factor of two in ALW when α-HHP
formation occurs.
140
The second conclusion arises from the resulting α-HHP concentration in the aqueous phase.
Particularly in the H2O2 simulation, by assuming a total aldehyde concentration of 100 mM at
equilibrium in the ALW scenario, approximately 0.7 mM of α-HHP forms in ALW. We raise the
possibility that this high concentration of α-HHP may partially explain the surprisingly high
concentrations of H2O2 previously observed from ambient aerosol (Hasson et al., 2003; Arellanes
et al., 2006). As suggested by these researchers, because of the dilution associated with ambient
aerosol extraction, α-HHPs should completely decompose to H2O2 upon analysis, contributing to
its high concentrations observed from the extract. Indeed, for this simulation, the concentration of
the α-HHP present in solution is roughly an order of magnitude larger than the concentration of
H2O2 in solution. The α-HHP concentrations in the formaldehyde and acetaldehyde simulations
were all enhanced, but not nearly as much as the H2O2 simulation case.
Of course, these assumptions are highly dependent on the assumed concentration of aldehydic
functional groups in ALW, and that they all participate in α-HHP formation with the assumed Kapp.
The degree to which such groups are present in ALW is poorly characterized; however it would
be expected that fresh SOA, for example that formed by ozonolysis, will have these species
present.
4.4.3 Other Atmospheric Implications
As mentioned previously, α-HHP can also form via the hydrolysis of SCI, i.e. the Criegee pathway.
If this reaction occurs in cloud water, the resultant α-HHP would most likely decompose to H2O2
and a corresponding carbonyl compound. However, if a hydrolysis reaction of SCI occurs in ALW,
which is generally more concentrated than cloud water, the resulting α-HHP may not fully
decompose given the α-HHP equilibria studied in the current work. If the α-HHP does decompose,
the H2O2 generated from the decomposition of α-HHP may meet another aldehydic species with
higher concentration (e.g. glyoxal) to form a different α-HHP.
As α-HHP concentration builds up in ALW, α-HHP themselves can act as nucleophiles and form
peroxyhemiacetals by reacting with aldehydic functional groups (see pathway 3 in Figure 4.1), as
in the case of BHMP formation from HMP and formaldehyde (Sect. 4.3.3.1). This reaction of α-
HHP is a specific mechanism of peroxyhemiacetal formation initially proposed by Ziemann and
co-workers (Tobias and Ziemann, 2000; Docherty et al., 2005) and later confirmed by several
141
recent laboratory studies (Hall and Johnston, 2012; Yee et al., 2012). The current study is an
indication that H2O2 can undergo the analogous reaction.
Table 4.6: Results of the atmospheric partitioning simulation.
Formaldehyde Acetaldehyde H2O2
Cloud Water ALW Cloud Water ALW Cloud Water ALW
Without
α-HHP
Formation
a KH (M atm
-1) 3.0 × 10
3 17 7.10 × 10
4
Gas-phase
mixing ratio (ppb) 0.932 1.000 1.000 1.000 0.366 1.000
Fraction in
aqueous phase 0.068 7.33 × 10
-8 4.15× 10
-4 4.15 × 10
-10 0.634 1.74 × 10
-6
Kapp
(M-1
) 164 b 113
c 100
With α-HHP
Formation
KHeff (M atm-1
) 3.05 × 103 7.92 × 10
3 17 36 7.17 × 10
4 7.81× 10
5
Gas-phase
mixing ratio (ppb) 0.931 1.000 1.000 1.000 0.363 1.000
Fraction in
aqueous phase 6.93 × 10
-2 1.94 × 10
-7 4.20 × 10
-4 8.86 × 10
-10 0.637 1.91 × 10
-5
Aqueous-phase total
α-HHP (M) 4.27 × 10
-8 4.92 × 10
-6 1.92 × 10
-10 1.92 × 10
-8 9.43 × 10
-9 7.1 × 10
-4
a KH values for formaldehyde and acetaldehyde represent their effective Henry's law constants in pure water, not
having been affected by α-HHP formation. References: formaldehyde (Betterton and Hoffmann (1988)); acetaldehyde
(Zhou and Mopper (1990)); H2O2 (Martin and Damschen (1981)).
b Value taken from the current work as the average of the NMR results and the PTR-MS results.
c Value assumed as the average Kapp for α-HHP from all the aldehyde species.
Formation of such hydroxyl and hydroperoxyl functional groups reduces the vapour pressure of
an organic compound substantially (Kroll and Seinfeld, 2008) and increases its solubility. It is
possible that peroxyhemiacetals and α-HHPs can stay in the particle phase even after water
evaporation and can thus be a pathway by which relatively volatile aldehydes are involved in SOA
formation. Recently, Liu et al. (2012) observed that addition of H2O2 to the water extract of
isoprene SOA caused significant increases in its degree of oxygenation and enhancement of its
hygroscopicity. It is likely that the α-HHP and peroxyhemiacetals contributed to such physico-
142
chemical changes of the SOA water extract. In fact, decay of carbonyls and significant formation
of 1-HEHP were observed in their study.
The α-HHPs may also be photolysed by actinic radiation, leading to the cleavage of the peroxide
(O–O) bond and the regeneration of an OH radical (Monod et al., 2007; Roehl et al., 2007;
Kamboures et al., 2010). It needs to be determined whether this process occurs more readily with
α-HHPs or with their precursor, H2O2. As well, the reactivity of α-HHPs with the OH radical is
likely to be high. Our previous study (Zhao et al., 2012) suggested that a major fraction of formic
acid observed during glyoxal photooxidation proceeded via an α-HHP intermediate.
Finally, we note that α-HHPs will likely decompose if aerosol is exposed to the fluid lining the
lung, providing a source of reactive oxygen species such as H2O2 to the body. In particular, Hasson
and Paulson (2003) indicate that the minimum H2O2 concentration to cause damage to alveolar
cell is likely to be at the order of 0.1 to 1 mM in ALW. Our simulations above suggest that the α-
HHP concentration have the potential to be at or above this minimum level.
4.5 Conclusions
We have investigated the thermodynamics of aqueous-phase formation of α-
hydroxyhydroperoxides (α-HHP) arising from H2O2 reacting with a suite of atmospherically
relevant carbonyl compounds. We find that formation of α-HHP was significant from many small,
atmospherically relevant aldehydes, but not from methacrolein and ketones. We have also
performed preliminary simulations to demonstrate that α-HHP formation will likely be of minor
importance in cloud water but is more likely to be of importance in aerosol liquid water (ALW)
where the concentrations of H2O2 and aldehydes are higher. In ALW, α-HHP may significantly
enhance the effective Henry’s Law constants of aldehydes and H2O2, leading to significant
concentrations of α-HHP in solution but probably not affecting the gas-phase levels of these
chemicals. The influence of α-HHP formation at lower temperatures, however, may be more
significant due to the enhancement of their formation equilibrium constants. We have also found
that α-HHPs can further act as nucleophiles to form peroxyhemiacetals. In general, this chemistry
is likely to lead to higher concentrations of organic peroxides than expected in ALW. The fate of
143
this class of compounds and their influence in aqueous-phase reaction mechanisms should be
further investigated.
Acknowledgement
The authors thank NSERC and QEII-GSST for financial support.
Supplementary Information
Supplementary information for this chapter is given in Appendix B.
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151
Chapter 5
Photochemical Processing of Aqueous Atmospheric Brown Carbon
As published in Atmos. Chem. Phys. Discuss. 15: 2957-2996, DOI:10.5194/acpd-15-2957-2015.
Distributed under the Creative Commons Attribution 3.0 License.
152
Abstract
Atmospheric Brown Carbon (BrC) is a collective term for light absorbing organic compounds in
the atmosphere. While the identification of BrC and its formation mechanisms is currently a central
effort in the community, little is known about the atmospheric removal processes of aerosol BrC.
As a result, we report a series of laboratory studies of photochemical processing of BrC in the
aqueous phase, by direct photolysis and OH oxidation. Solutions of ammonium sulfate mixed with
glyoxal (GLYAS) or methylglyoxal (MGAS) are used as surrogates for a class of secondary BrC
mediated by imine intermediates. Three nitrophenol species, namely 4-nitrophenol, 5-
nitroguaiacol and 4-nitrocatechol, were investigated as a class of water soluble BrC originating
from biomass burning. Photochemical processing induced significant changes in the absorptive
properties of BrC. The Imine-mediated BrC solutions exhibited rapid photo-bleaching with both
direct photolysis and OH oxidation, with atmospheric half-lives of minutes to a few hours. The
nitrophenol species exhibited photo-enhancement in the visible range during direct photolysis and
the onset of OH oxidation, but rapid photo-bleaching was induced by further OH exposure on an
atmospheric timescale of an hour or less. To illustrate atmospheric relevance of this work, we also
performed direct photolysis experiments on water soluble organic carbon extracted from biofuel
combustion samples and observed rapid changes in optical properties of these samples as well.
Overall, these experiments indicate that atmospheric models need to incorporate representations
of atmospheric processing of BrC species to accurately model their radiative impacts.
5.1 Introduction
There is increasing awareness of the importance of light absorbing organic compounds in the
atmosphere (Kirchstetter et al. 2004, Chen and Bond 2010, Lack et al. 2012, Bahadur et al. 2012).
Highly variable in sources and identity, this class of poorly characterized organic compounds has
been collectively termed Atmospheric Brown Carbon (BrC) (Andreae and Gelencser 2006). BrC
significantly alters the traditional view that organic carbon interacts with solar radiation via only
scattering (Chung and Seinfeld 2002). In the visible range of solar radiation, BrC absorption can
affect the direct radiative effect of organic carbon (Feng et al. 2013, Lin et al. 2014). In particular,
Feng et al. (2013) have shown that defining a fraction of organic aerosol as strongly light-absorbing
BrC in a global chemical transport model can shift the direct radiative effect of organic carbon
153
from net cooling to net warming. Meanwhile in the near UV range, BrC absorption may affect the
flux of short-wavelength radiation that is crucial in driving atmospheric photochemistry (Jacobson
1999). Motivated by such atmospheric impacts, the characterization of the sources, molecular
identity and processing of BrC is a central effort in the aerosol chemistry community.
There are two major types of BrC widely studied. The first arises from primary organic compounds
emitted during biomass burning (BB) (Andreae and Gelencser 2006, Alexander et al. 2008, Chen
and Bond 2010, Lack et al. 2012, Kirchstetter and Thatcher 2012, Saleh et al. 2014). The chemical
composition of BB organic aerosol is highly complex, which varies significantly with source fuels,
burning conditions and atmospheric age of the particles (Chen and Bond 2010, Cubison et al. 2011,
Ortega et al. 2013). Such complexity significantly hinders the separation, analyses, and molecular
identification of BB BrC. BB BrC is at times considered to belong to Humic Like Substances
(HULIS) (Hoffer et al. 2004, Graber and Rudich 2006) and more recently a class of compounds
categorized as extremely low volatility organic compounds (Saleh et al. 2014).
The second BrC source involves secondary chemistry occurring in atmospheric aqueous phases
(e.g. cloudwater and aerosol liquid water) between aldehydes and nitrogen containing
nucleophiles, including ammonia, amino acids and amines (De Haan et al. 2009, Shapiro et al.
2009, Sareen et al. 2010, De Haan et al. 2011, Yu et al. 2011, Zarzana et al. 2012, Sedehi et al.
2013, Powelson et al. 2013). Since the formation mechanism of this type of BrC involves an imine
or a Schiff’s base intermediate, this class of BrC is herein referred as “Imine BrC”. Although imine
intermediates do not absorb at the actinic range, they undergo subsequent reactions to form
nitrogen-containing organic chromophores (Lee et al. 2013, Kampf et al. 2012, Yu et al. 2011). It
is generally believed that formation of individual chromophores with very low concentrations
leads to the color (Nguyen et al. 2013). Imine BrC typically takes days to form in the bulk
laboratory solution (Lee et al. 2013). However, studies have also shown that droplet evaporation
may significantly accelerate the rate of such reactions, giving rise to rapid formation of BrC (De
Haan et al. 2011, Zarzana et al. 2012, Lee et al. 2013, Galloway et al. 2014). Finally, we note that
a recent study has also suggested that charge transfer complexes between different functional
groups may be responsible for absorption in the visible range (Phillips and Smith 2014). We did
not perform experiments targeted to this potential third class of BrC species.
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Studies from the past decade (Blando and Turpin 2000, Ervens et al. 2011) have indicated
atmospheric aqueous phases (e.g. cloudwater and aerosol liquid water) as important reaction
media, where organic compounds can be processed, leading to formation and further aging of
secondary organic aerosol (SOA). Imine BrC, forming in the aqueous phase, can undergo
subsequent photochemical processing. A previous study has observed rapid photolysis of
components in the mixture of methylglyoxal and ammonium sulfate, implying rapid photolysis of
Imine BrC (Sareen et al. 2013). More recently, Lee et al. (2014b) investigated aqueous-phase
processing of several classes of BrC and observed rapid decay of color (photo-bleaching). To date,
there is no systematic investigation of the effect of OH oxidation on Imine BrC. BB BrC, on the
other hand, can also be subject to aqueous-phase photochemical processing, given that BB
particulate matter can be hygroscopic (Petters and Kreidenweis 2007, Petters et al. 2009) and
contains a significant fraction of water soluble organic carbon (Iinuma et al. 2007, Saarikoski et
al. 2008, Chen and Bond 2010). While the majority of BB BrC remains unidentified, nitrophenols
present a useful class of model compounds to investigate aqueous-phase processing of BB BrC.
They have been frequently identified in BB plumes (Vione et al. 2009, Einschlag et al. 2009) and
have been employed as molecular tracers for BB (Iinuma et al. 2010, Kitanovski et al. 2012, Mohr
et al. 2013). Certain nitrophenols exhibit relatively high Henry’s law constants (Schwarzenbach et
al. 1988) and have been observed in cloudwater samples (Luttke and Levsen 1997, Luttke et al.
1999, Harrison et al. 2005). In particular, Desyaterik et al. (2013) have determined BrC from
cloudwater affected by BB and have identified multiple species of nitrophenols that contribute
towards the total absorption of the cloudwater sample. Hence, nitrophenols represent an important
subclass of BB water soluble organic carbon (WSOC) that may undergo aqueous-phase
processing. Previous studies have investigated aqueous phase UV photolysis (Chen et al. 2005,
Zhao et al. 2010), OH oxidation (Einschlag et al. 2003, Vione et al. 2009, Einschlag et al. 2009),
as well as heterogeneous oxidation (Knopf et al. 2011, Slade and Knopf 2014) of nitrophenols, but
a clear connection to their optical properties has not been made.
In this study, we systematically investigate how atmospheric photochemical processing
mechanisms affect Imine BrC and nitrophenols (as surrogates of BB BrC) in the aqueous phase,
focusing on changes in their absorptive optical properties. The dual objectives are 1) to quantify
the rates of direct photo-bleaching and/or photo-enhancement under realistic radiation condition,
and 2) to evaluate the atmospheric importance of BrC oxidative processing, with a particular focus
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on OH oxidation. We perform these experiments quantitatively under known light and OH
exposures, so as to establish which processing mechanism is likely to dominate in the atmosphere.
To tie our laboratory experiments to ambient conditions, we also performed direct photolysis
experiments on the WSOC extracted from biofuel combustion particles.
5.2 Methods
5.2.1 Preparation of BrC Solutions
The experimental procedures for Imine BrC and nitrophenols are illustrated in Figure 5.1.
Solutions of ammonium sulfate mixed with glyoxal (GLYAS) or methylglyoxal (MGAS) were
chosen as laboratory surrogates to represent Imine BrC. Stock solutions (200 mL in volume) were
made by mixing ammonium sulfate (1.5 M, Sigma Aldrich) with either 0.5 M of glyoxal (Sigma
Aldrich, 30 % in water) or 0.2 M of methylglyoxal (Sigma Aldrich, 40 % in water) in 250 mL
glass jars. All the solutions were prepared using deionized water (18 mΩ-cm) with total organic
carbon less than 1 parts per billion (ppb). The stock solutions were sealed and placed in the dark
under room temperature for 2 to 3 months. During this time, the color of the solutions turned dark
yellow and eventually dark brown, consistent with previous studies (Shapiro et al. 2009, Sareen et
al. 2010, Lee et al. 2013). Although 2 to 3 months is much longer than typical atmospheric aerosol
lifetimes, our previous work has shown that the absorption spectra of Imine BrC obtained this way
closely resembled those obtained from droplet evaporation occurring on the timescale of seconds
or less (Lee et al. 2013). The experimental solutions were created by diluting the concentrated
stock solutions, typically by a factor of 200, to concentrations that optimize the UV-Vis detection
at 400 nm (see next section).
Three nitrophenol compounds (4-nitrophenol (4NP), 5-nitroguaiacol (5NG) and 4-nitrocatechol
(4NC)) were chosen to represent primary BB BrC (structures shown in Figure 5.2) and are
investigated individually. 4NP and 4NC have been detected from BB affected cloudwater samples
(Desyaterik et al. 2013) while 5NG has been previously used in the laboratory as a model
compound for BB organic matter (Knopf et al. 2011). Commercial standards of these compounds
were purchased from Sigma Aldrich and were used without further purification. Individual stock
solutions (1 mM) were created every few days, and the experimental solutions were made by
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diluting the stock solution to 4 to 15 uM depending on the nitrophenol species and the type of
experiment. This range of concentration matches that of nitrophenols detected in cloudwater
(Desyaterik et al. 2013).
Figure 5.1: Experimental procedures.
5.2.2 Direct Photolysis and OH Oxidation Experiments
Direct photolysis and OH oxidation experiments were conducted separately. Direct photolysis
experiments were performed with a Suntest CPS photo-simulator (Atlas) equipped with a Xe lamp.
The BrC solution (100 mL) contained in a glass bottle was placed inside the simulator for
illumination. Chemical actinometry using 2-nitrobenzaldehyde (Galbavy et al. 2010) was
performed to measure the effective photon flux which was determined to be similar to actinic flux
at the Earth’s surface with 0 ˚C zenith angle. The method of chemical actinometry and the
determined photon flux from the simulator are included in Appendix C, Section C1. Aliquots of
the experimental solution were taken at different illumination times for offline absorption
measurements conducted by a liquid waveguide capillary UV-Vis spectrometer (World Precision
Instruments), equipped with a deuterium tungsten halogen light source (DT-Mini-2, Ocean Optics)
and a temperature controlled UV-Vis spectrometer (USB2000+, Ocean Optic). The strength of this
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instrument lies in its long effective optical length (50 cm in this work), resulting in its superior
detection sensitivity. The spectrometer simultaneously records absorption from 230 to 850 nm,
making monitoring at multiple wavelengths possible. We confirmed that the concentrations of the
experimental solutions were in the linear range of the spectrometer used.
Experiments for OH oxidation were conducted in a different setup. Hydrogen peroxide (H2O2,
TraceSELECT® 30% purchased from Sigma Aldrich) was added to each solution as a photolytic
source of OH radical upon irradiation with a 254 nm mercury lamp (UVP, an ozone-free version
constructed to remove the 185 nm line) inserted inside the solution. The BrC solutions were
prepared in the same manner but in a larger volume (1 L). The concentration of H2O2 added to the
BrC solutions was typically 5 mM unless otherwise stated. H2O2 itself exhibited UV absorption
up to 300 nm, but did not affect BrC absorption at longer wavelengths. Dark control experiments
were also performed to confirm that H2O2 did not react with BrC to change its optical properties.
Aliquots of offline samples were taken at different illumination times and were measured by the
liquid waveguide capillary UV-Vis spectrometer as mentioned above.
It is crucial to measure the steady state concentration of OH radicals ([OH]ss) in the OH oxidation
experiments in order to infer sound environmental implications. An aerosol chemical ionization
mass spectrometer (Aerosol CIMS) was employed for this purpose. The experimental setup is
similar to that in one of our previous studies (Zhao et al. 2012). Briefly, the experimental solution
is constantly atomized with a TSI constant output atomizer (model 3076). The aerosol flow is
introduced through a heated metal line (100 ˚C), where organic compounds volatilize to the gas
phase and are detected by a quadruple CIMS equipped with iodide water cluster reagent ion
(I(H2O)n-). The I(H2O)n
- reagent ion detects oxygenated organic compounds by forming iodide ion
clusters (Aljawhary et al. 2013, Lee et al. 2014a, Zhao et al. 2014). The [OH]ss was estimated by
tracking the pseudo 1st order decay of a reference compound with known OH reactivity. For the
Imine BrC, unreacted glyoxal or methylglyoxal in the solutions were used as the tracer compounds
because their mono-hydrates are detectable by the I(H2O)n- reagent ion (Zhao et al. 2012). The OH
oxidation rate constants of glyoxal and methylglyoxal used in this study are 1.1 × 109 M-1s-1 (Tan
et al. 2009) and 5.3 × 108 M-1s-1 (Monod et al. 2005), respectively. For the nitrophenols, as the
iodide reagent ion does not detect nitrophenol species, 1 mM of meso-erythritol (Sigma Aldrich)
was added to the solution as the reference compound. The choice of erythritol is based on the fact
that: 1) it does not absorb light in the actinic wavelength, 2) it is not an acid and does not affect
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the solution pH, and 3) it reacts with OH rapidly, with a second order rate constant of 1.9 × 109 M-
1s-1 (Hoffmann et al. 2009).
5.2.3 Direct Photolysis of WSOC from Biofuel Combustion
The biofuel combustion samples were collected in Henan Province, China (Li et al. 2007, Li et al.
2009). Agricultural residues, typically used as biofuels in the local area, were burned in an
improved stove commonly used in the area. A detailed description of particle collection and the
physical properties of the generated particles are provided in Li et al. (2007). Briefly, particles
were withdrawn from the stove, and the PM2.5 fraction was collected on quartz filters after
dilution. The quartz filters were baked under 450 ˚C before collection, and the samples were stored
frozen after collection. Organic carbon (OC) and elemental carbon contents of each filter sample
were measured following a method originally developed at Environment Canada’s laboratory in
Toronto for measuring δ13C of OC/EC (Huang et al., 2006) and later improved by Chan et al. ,
2010 to be used as the standard OC/EC measurements in the aerosol baseline measurements in
Canada. In the current work, we investigated the WSOC from two filter samples, collected from
burning of kaoliang stalks and cotton stalks, respectively. A quarter of the filter was extracted in
10 mL of deionized water by constant shaking for 30 min. The extracts were used as the experiment
solution after filtration with a 0.2 µm syringe filter. We extracted the same filter a second time and
found that the absorption in the second extract was less than 10 % of the first extract. However, it
is difficult to estimate the extraction efficiency of total organic carbon. The filtered extract was
illuminated with the same solar simulator, and its absorption was monitored with the same
waveguide capillary spectrometer mentioned in Section 5.2.2. Oxidation by OH radicals was not
performed for these samples due to limited amount of sample volume.
5.3 Results and Discussion
5.3.1 Light Absorption of BrC
Absorption spectra of the BrC solutions are displayed in Figure 5.2a. The concentrations of the
solutions were chosen to display their full absorption spectra up to 480 nm. The absorption spectra
of all of these species stretch into the visible range of radiation, giving rise to brown to light yellow
color to the solutions. Absorption spectra of the two WSOC extracts from biofuel combustion
samples are shown in Figure 5.2b. Absorption with strong wavelength dependence was observed,
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with Angstrom absorption coefficients (290 to 480 nm) of 6.0 and 5.8 for the kaoliang stalk and
cotton stalk samples, respectively.
Figure 5.2: Absorption spectra of BrC investigated in this study (a) and WSOC from the biofuel combustion samples
(b). The y-axis in (a) is in arbitrary units to keep the absorbance of all the solutions on scale.
We note that the absorption spectra of the individual BrC species do not resemble those of the
biofuel sample extracts, as such ambient samples likely contain a large number of BrC compounds
with various absorptivity. Investigation of the selected Imine BrC and nitrophenol species in this
study is intended to provide fundamental information for processing of individual BrC species.
To provide more quantitative values, we also obtained the wavelength dependent mass absorption
coefficient (MAC) for the Imine BrC and biofuel combustion samples. The MAC of the Imine BrC
solutions was calculated based on its total organic carbon content measured by a Shimadzu TOC-
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ICPH Total Organic Carbon Analyzer. The MAC of the biofuel combustion samples was
calculated based on its organic carbon contents measured in the filter samples. For nitrophenols,
we obtained their absorption coefficient and molar absorptivity instead of MAC because they are
single compounds. The detailed methods and complete results are shown in Appendix C, Section
C2.
5.3.2 Imine BrC
5.3.2.1 Direct Photolysis of Imine BrC
Both GLYAS and MGAS solutions exhibited rapid photo-bleaching upon illumination by
simulated sunlight. Figure 5.3a shows the spectral change of one MGAS solution as an example,
with the illumination time color-coded. Absorbance over the entire spectral range exhibited
uniform decay during two hours of illumination. In Figure 5.3b, we show the time profiles of
absorbance at 400 nm normalized to its initial value at t=0 for both the GLYAS and MGAS
solutions. The wavelength of 400 nm was chosen because the concentrations of the Imine BrC
solutions were optimized for the detection at this wavelength. The inset displays the 1st order plots
for the decay, alone with the fitted linear lines forced through the origin. The non-linear plots
indicate non-1st order behavior, likely due to the presence of multiple chromophores that exhibit
different degrees of photo-lability.
Aregahegn et al. (2013) proposed that photosensitized reactions take place in the GLYAS solution,
initialized by compounds such as imidazole and imidazole-carboxaldehyde. We examined the
presence of this type of reaction by varying the initial concentration of the Imine BrC. However,
the concentration of Imine BrC did not affect its photolysis rate constant (Appendix C, Section
C3). This indicates that photosensitized reactions either did not take place in our reaction system,
or were not indicated by the color change.
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Figure 5.3: Spectral change of the MGAS solution during a direct photolysis experiment (a) and the absorbance
change at 400 nm as a function of illumination time (b). The inset in (b) shows the 1st order plot of the decay, and the
lines are linear least square plots forced through the origin. The shaded area represent the range obtained from 3
replicates.
5.3.2.2 OH Oxidation of Imine BrC
Rapid photo-bleaching was observed also during the OH oxidation experiments. Figure 5.4a shows
the evolution of absorbance at 400 nm during four experiments, normalized to the values at the
beginning of illumination. The dashed lines are H2O2 control experiments, where the absorbance
at 400 nm for both GLYAS and MGAS exhibited decay due to direct photolysis by the 254 nm
lamp. The decay was clearly accelerated during OH oxidation experiments represented by the solid
line traces. The calculated [OH]ss values in these two experiments were 9 × 10-14 M and 1 × 10-13
M for the GLYAS and MGAS experiments, respectively.
Table 5.1: Estimated atmospheric half-life of Imine BrC arising in the glyoxal-ammonium sulfate (GLYAS) and
methylglyoxal-ammonium sulfate (MGAS) solutions.
Photolytic τ1/2
(min) kIIOH (M-1 s-1) OH τ1/2 (min)
GLYAS 90 ± 12 2.1 (± 1.1) × 1010 5
MGAS 13 ± 3 1.2 (± 0.3) × 109 98
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The decay of absorbance at 400 nm appeared largely pseudo 1st order, except for the GLYAS OH
oxidation (Figure 5.4b). Similar to the case of direct photolysis, we suspect that multiple
chromophores likely give rise to the non-1st order decay of the color. We have decided to treat the
decay in the GLYAS system as if it was pseudo 1st order, with the rates determined this way
representing the middle point between the fastest and slowest decay rate.
Assuming the difference between the H2O2 control and the OH oxidation experiments is due to
OH oxidation, a pseudo 1st order OH oxidation rate constant (kIOH) can be obtained by taking the
difference between the observed pseudo 1st order decay of absorbance in the H2O2 control (kIctl)
and the OH oxidation experiments (kIoxi), as shown by Eqn 5.1. The second order OH oxidation
rate constant (kIIOH) can then be calculated from Eqn. 5.2.
kIOH = kI
oxi - kIctl (5.1)
kIIOH = kI
OH / [OH]ss (5.2)
As listed in Table 5.1, the kIIOH values for the GLYAS and the MGAS systems are determined to
be (2.1 ± 1.1) × 1010 and (1.2 ± 0.3) × 109 M-1s-1, respectively. The uncertainty represents standard
deviation from between 3 and 4 experimental replicates. We note that the kIIOH value for the
GLYAS system is essentially diffusion limited.
Figure 5.4: Time profiles of absorbance at 400 nm during OH oxidation (solid lines) and H2O2 control (dashed lines)
experiments. Results for both the GLYAS (blue traces) and the MGAS (red traces) solutions are shown. The decay
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profiles of absorbance at 400 nm normalized to the initial value at t =0 are shown in (a), while their corresponding 1st
order decay plots are shown in (b).
5.3.2.3 Atmospheric Fate of Imine BrC
We estimate the atmospheric half-life (τ1/2) of Imine BrC against direct photolysis and aqueous
phase OH oxidation based on the observed absorbance change at 400 nm (Table 5.1). The τ1/2
values were obtained by extracting the time when the signal reached half of its original value, and
the uncertainty represents the range obtained from three replicates. Since the photon flux in the
solar simulator is similar to that in the ambient atmosphere (see Appendix C, Section C1), the
experimentally determined τ1/2 values, 90 ± 12 min and 13 ± 3 min for the GLYAS and MGAS
systems, directly reflect the photolytic τ1/2 of these Imine BrC species in the ambient atmosphere.
These τ1/2 values are on the same order as those derived for another type of Imine BrC generated
from Limonene SOA and ammonia vapor (Lee et al. 2014b), implying that rapid photolysis will
be a common characteristic for this type of Imine BrC. The OH oxidation half-lives are estimated
by assuming an ambient cloudwater [OH]ss of 1 × 10-13 M (Herrmann et al. 2010). This [OH]ss,
together with the kIIOH determined in the previous section (Section 5.3.2.2), yields OH oxidation
τ1/2 of 5 min and 98 min for the GLYAS and the MGAS solutions, respectively. The rapid
bleaching implies that the daytime lifetime of Imine BrC is likely very short in the atmosphere,
leading to relatively low concentrations. Knowing that droplet evaporation can lead to rapid
formation of Imine BrC on a time scale of seconds (Lee et al. 2013), its steady state concentration
may be highest where droplet evaporation processes are occurring at night.
Although Imine BrC in the GLYAS and MGAS solutions is thought to be arising from similar
reaction mechanisms (De Haan et al. 2011, Yu et al. 2011, Sedehi et al. 2013), their major
bleaching processes are found to be different. The GLYAS solution is predominantly bleached by
OH oxidation, while the MGAS solution is by direct photolysis. The results for the MGAS solution
shows agreement with Sareen et al. (2013), where they determined direct photolysis as the
dominant sink for constituents in the MGAS solution. To our best knowledge, the current work
presents the first investigation for direct photolysis of GLYAS, as well as the OH oxidation kinetics
for both GLYAS and MGAS.
The difference in the major removal mechanisms for GLYAS and MGAS arises from the
additional methyl group on methylglyoxal as compared to glyoxal, as we propose in Figure 5.5.
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The methyl group prevents the carbonyl functionality from hydrating into its geminal diol which
does not absorb actinic radiation. On the other hand, H-abstraction from a methyl hydrogen is
expected to be slower than from the tertiary hydrogen on the geminal diol. In Figure 5.5, we use
imidazole carboxaldehyde, proposed as a major product in the GLYAS solution (Kampf et al 2012,
De Haan et al. 2011, Yu et al. 2011), as an example to demonstrate this concept.
Figure 5.5: Proposed explanation for the difference in the major bleaching processes of the GLYAS and the MGAS
solutions.
5.3.3 Nitrophenols
5.3.3.1 Direct Photolysis of Nitrophenols
The spectral change of a 4NC solution during a direct photolysis experiment is shown in Figure
5.6, color coded by illumination time, with the inset illustrating the change at different illumination
times. The change is dynamic, with a decrease of absorption between 300 and 380 nm but an
increase of absorption at 260 nm and above 400 nm. The spectral change is likely due to a
combination of 4NC decay and formation of one or more reaction products. Similar trends were
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also observed for 4NP and 5NG (Appendix C, Section C4). The most noteworthy observation for
all the nitrophenols is a photo-enhancement of absorption at wavelengths longer than 400 nm, i.e.
in the visible range. Since the photo-enhancement at 420 nm was the most significant for all the
three nitrophenols, we conducted a series of experiments to better characterize the absorbance
change at this wavelength. Formation of color at 420 nm is 1st order with respect to the precursor
nitrophenols, confirmed by altering their concentrations. The discussion below is primarily based
on the results from 4NC, while the results of 4NP and 5NG are included in Appendix C, Section
C5.
Figure 5.6: Spectral change of a 4NC solution (4 µM) during a direct photolysis experiment. The inset shows the
absorbance change compared to the initial condition.
The effect of OH radical is examined first. Previous studies have shown that nitrite ion can be
produced during UV irradiation of nitro-aromatic compounds, via photo-induced nucleophilic
substitution reactions (Nakagawa and Crosby 1974, Dubowski and Hoffmann 2000, Chen et al.
2005). Nitrite is a photolytic source of OH radical and can potentially affect our direct photolysis
experiments. We performed experiments with 1 mM of glyoxal added to the nitrophenol solution
as an OH scavenger. Glyoxal is a good scavenger because neither it nor its reaction products absorb
in the wavelength range of interest. Judging from the OH reactivity of nitrophenols (Einschlag et
al. 2003) and glyoxal (Tan et al. 2009), 1 mM of glyoxal will scavenge at least 90 % of OH radicals
in the solution. The result of a 4NC experiment with OH scavenger is shown as the cyan trace in
Figure 5.7, which does not exhibit significant difference from the experiment without the OH
scavenger (blue trace). For 4NP, the OH scavenger reduced but did not completely remove the
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color formation at 420 nm (Appendix C, Section C5). We conclude that photo-enhancement is
indeed induced by direct photolysis even without OH radicals present.
Effects of the solution pH are also examined because the light absorption of phenolic compounds
is pH dependent, with phenolate being a better absorber than phenol. Phenolate contains additional
lone-pair electrons that can participate in the conjugation system, leading to more efficient light
absorption. The absorption spectra of the three nitrophenols at various solution pH values are
shown in the Appendix C, Section C6. Light absorption of 4NP and 4NC at 420 nm increased
significantly at higher solution pH due to formation of phenolate, but 5NG did not exhibit pH
dependence. A meta-nitrophenol compound, such as 5NG, is known to be less acidic than para-
and ortho-nitrophenols (i.e. 4NP and 4NC). It is likely that the 5NG phenolate did not form in the
range of pH investigated.
The absorbance (420 nm) time profiles of 4NC at two additional solution pH (i.e. pH 4 and 3) are
displayed in Figure 5.7. The photo-enhancement is more significant at higher solution pH. This is
perhaps due to the fact that the products formed also exhibit pH dependent light absorptivity. 4NP
and 5NG exhibit unique trends of pH dependence as shown in Appendix C, Section C5.
Figure 5.7: Time profiles of 4NC absorbance at 420 nm during direct photolysis experiments. Experiments were
performed at three solution pH values. An OH scavenger experiment was also performed by adding 1 mM glyoxal to
the pH 5 solution.
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We determined the effective 1st order rate coefficient of photo-enhancement (kIdirect) for 4NC by
fitting the observed absorbance at 420 nm to a 1st order growth curve. The kIdirect values determined
for 4NC are summarized in Table 5.2. Photo-enhancement in the cases of 4NP and 5NG exhibited
stronger linearity, which made fitting to 1st order growth curve difficult. Instead of kIdirect, we report
an absorbance-based rate constant for these two compounds, and the details are provided in the
Appendix C, Section C5.
Table 5.2: Rate constants for photo-enhancement at 420 nm for 4-nitrocatechol (4NC)
kIdirect (s
-1) of 4NC
pH3 pH4 pH 5 pH 5 OH scav.
2.3 × 10-4 3.2 × 10-4 4.0 × 10-4 3.3 × 10-4
5.3.3.2 OH Oxidation of Nitrophenols
Oxidation by OH radicals induced rapid bleaching of all nitrophenols investigated, but the decay
of absorbance was not monotonous. The spectral change of 4NC during an OH oxidation
experiment is shown in Figure 5.8a while the time profile of absorbance at 420 nm is shown in
Figure 5.8b. Results for 4NP and 5NG can be found in the Appendix C, Section C7. All the
experiments were performed at pH 5 and in duplicate to confirm reproducibility. For all three
nitrophenols, the absorbance exhibited initial increase, followed by decay at longer illumination
time.
The initial color formation observed in the current study exhibits similarities with several previous
investigations of BB BrC. Gelencser et al (2003) and Chang and Thompson (2010) have observed
color formation in aqueous-phase OH oxidation of aromatic compounds. Saleh et al. (2013) have
observed light-absorbing SOA arising from BB particles photochemically aged in a chamber. More
recently, Zhong and Jang (2014) have observed a highly dynamic evolution of the optical
properties of BB particles, similar to observations from the current study. In their study, the light
absorption of BB particles in an outdoor chamber exhibited initial enhancement and subsequent
bleaching with exposure to natural sunlight. It is likely that the magnitude of photo-enhancement
and bleaching is dependent to both the BrC components and the extent of photochemical
processing. Given that nitrophenol presents only a subset of colored components in BB BrC, we
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cannot make conclusions on the general fate of BB BrC. As will be seen in Section 5.3.4, WSOC
from real BB particles indeed show complicated results, with different samples exhibiting different
trends during direct photolysis.
Figure 5.8: Spectral change of 4NC solution (10 µM) during an OH oxidation experiment (a), with the inset showing
absorbance change compared to the initial condition. The color coding represents the illumination time. The time
profiles of absorbance at 420 nm are shown in (b). The black trace is from a H2O2 control experiment, while the red
trace is from one of the OH oxidation experiments.
We propose that the observed trend during OH oxidation is due to initial functionalization followed
by ring-cleavage reactions. Previous studies (Sun et al. 2010) have shown that OH oxidation leads
to hydroxylation of the aromatic ring, in analogy to the gas phase (Atkinson 1990). The additional
hydroxyl group is electron donating, with its lone pair electrons contributing to the conjugation
and leading to enhanced absorption. We note that oligomeric products have also been reported
from OH oxidation of phenolic compounds (Sun et al. 2010, Chang and Thompson 2010). In
particular, Chang and Thompson have observed significant enhancement of absorption, and they
proposed that the absorption is attributed to HULIS produced from phenol OH oxidation. To
simulate cloudwater chemistry, we used nitrophenol concentrations orders of magnitude lower
than those used in Chang and Thompson and so we consider the formation of oligomers less
important in our system.
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To quantitatively assess the formation and decay rate of color, we applied a kinetic model
framework based on the absorbance at 420 nm (Figure 5.9a). The OH radical concentration is
assumed to be in steady state at 3.2 × 10-13 M which is the average of measured [OH]ss using the
Aerosol CIMS method. The nitrophenol precursor (NP) follows a prescribed pseudo 1st order
decay with a rate constant, kINP, which is estimated based on 4NP OH reactivity reported by
Einschlag et al. (2003). A colored product (CP) is formed from NP with a pseudo 1st order rate
constant kIcolor, but simultaneously undergoes photo-bleaching with another pseudo 1st order rate
constant kIbleach. Although NP can likely give rise to more than one CP species, the colored products
are lumped into a single compound for simplicity. The sum of absorbance from NP and CP is
treated as the total absorbance of the solution. We found the optimal combination of kIcolor and
kIbleach values that minimizes the sum of the squared difference between the modelled and the
observed absorbance change. We note that kIcolor and kI
bleach are absorbance-based rate constants
and should not be confused with concentration-based rate constants. If the identity and molar
absorptivity of CP are characterized in future studies, these absorbance-based rate constants can
be converted into concentration-basis.
The results for one 4NC experiment are shown in Figure 5.9b. The two shaded areas in Figure 5.9b
represent modeled absorbance due to the precursor, 4NC, and the CP, respectively. The red trace
is the absorbance change measured during the experiment shown in Figure 5.8. Results for 4NP
and 5NG, along with detailed model conditions are included in the Appendix C, Section C8. For
all three nitrophenols, this model captures the initial increase and later decay of color, but the time
at which the absorbance reaches its maximum and the decay rate at the end of the experiment are
more difficult to match. This is perhaps due to the fact that nitrophenols form multiple generations
of colored products, giving rise to a more dynamic evolution of absorbance than the current model
framework can produce. Nevertheless, the model represents a novel effort to estimate the rates of
photo-enhancement and bleaching during OH oxidation of nitrophenols. The optimal kIcolor and
kIbleach values for the three nitrophenols are listed in Table 5.3. Since these values are all psudo-1st
order rate constants, their corresponding second order rate constants (kIIcolor and kII
bleach) are also
calculated using Eqn. 5.2 and provided in Table 5.3. The values reported in Table 5.3 are the
average of two replicates performed for each nitrophenol. Relative errors are roughly 10 % for
4NP and 5NG, and 15 % for 4NC.
170
Figure 5.9: A schematic illustration of the simple kinetic model (a) and one example of 4NC photooxidation (b). The
shaded areas in (b) are the contributions from a newly formed colored product (CP) and the decaying 4NC,
respectively. The red line follows data from an experiment.
Table 5.3: Photo-enhancement and bleaching rate constants1 for nitrophenol OH oxidation determined from a simple
kinetic model (Section 5.3.3.2.).
Compound kIcolor (s
-1) kIIcolor (M
-1 s-1) kIbleach (s
-1) kIIbleach (M
-1 s-1)
4-nitrophenol 8.5 × 10-4 2.6 × 1010 3.8 × 10-4 1.2 × 1010
5-nitroguaiacol 3.9 × 10-3 1.2 × 1011 2.0 × 10-3 6.1 × 1010
4-nitrocatechol 3.3 × 10-3 1.0 × 1011 4.6 × 10-3 1.4 × 1011
1The rate constants are absorbance-based and should be distinguished from concentration-based rate constants.
Values reported here are the average of two replicates.
171
5.3.3.3 Atmospheric Fate of Nitrophenols
Our results indicate that the photo-bleaching by OH oxidation is rapid and presents the dominant
fate for BrC represented by nitrophenols. As the [OH]ss in our experiment (3.2 × 10-14 M) is
roughly that of cloudwater in remote areas (Herrmann et al. 2010), the light absorptivity of
nitrophenols is expected to reach its maxima and to be bleached within one hour of in-cloud time.
On the other hand, photo-enhancement during direct photolysis is much slower, with color forming
over a time scale of hours. This observation agrees with Vione et al. (2009) who also determined
radical chemistry as the dominant sink of 4NP compared to direct photolysis. That being said, this
trend may not apply to all nitrophenols. For instance, dinitrophenols represent an interesting group
of compounds to investigate in the future, as the additional nitro group deactivates OH radical
reactions (Einschlag et al. 2003) but enhances light absorption (Schwarzenbach et al. 1988).
172
Figure 5.10: Direct photolysis of the WSOC from biofuel combustion samples. The spectral evolution of the kaoliang
and the cotton samples is shown in (a) and (b), respectively. The color code indicates illumination time, while the
insets show the absorbance change compared to the initial condition. The time profiles of absorbance at three different
wavelengths for the same samples are shown in (c) and (d), respectively.
5.3.4 Direct Photolysis of WSOC from Biofuel Combustion Samples
A change in absorptivity was observed when WSOC from biofuel combustion samples was
exposed to simulated sunlight. Results for the kaoliang stalk sample and the cotton stalk sample
are shown in Figure 5.10a and 10b, respectively. Their absorbance changes at three wavelengths
(350, 400 and 420 nm) are also shown in Figure 5.10c and 5.10d, respectively. WSOC from the
two samples exhibited different trends, with the kaoliang stalk sample showing a temporary photo-
enhancement shortly after the initiation of illumination, and the cotton stalk sample exhibiting
monotonous photo-bleaching. The trends for the sample at different wavelengths demonstrate the
complexity of the real biomass burning samples. Our results provide qualitative evidence that the
optical properties of WSOC extracted from BB BrC can change upon photochemistry.
5.4 Conclusions and Atmospheric Implications
The overall conclusion from this work is that because atmospheric brown carbon species are
organic chromophores and susceptible to photochemical degradation, their optical properties are
altered by aqueous-phase photochemical processing with both photo-enhancement and photo-
bleaching possibly occurring. In particular, Imine-mediated BrC, arising from aqueous-phase
reactions between carbonyl compounds and nitrogen-containing nucleophiles, undergoes rapid
photo-bleaching via both direct photolysis and OH oxidation. Bleaching of glyoxal-ammonium
sulfate (GLYAS) BrC was predominantly driven by OH oxidation whereas that for methylglyoxal-
ammonium sulfate (MGAS) was driven by direct photolysis. Three species of nitrophenols were
investigated as an important subset of biomass burning BrC. Photo-enhancement of absorption
was observed when the nitrophenol species are illuminated with simulated sunlight, as well as
during the initial stages of OH oxidation. Although such photo-enhancement can potentially
magnify the direct radiative effect of nitrophenols, photo-bleaching of nitrophenols with further
OH exposure was observed to be also rapid. This is the first investigation of OH oxidation induced
effects on the optical properties of BrC, demonstrating its importance in determining the
173
atmospheric significance of BrC. Lastly, a study of biofuel BrC species illustrated that the optical
properties of ambient samples are also rapidly altered. These findings are in general agreement
with prior studies that have also seen evidence for photo-bleaching (Lee et al. 2014b, Zhong and
Jang 2014, Sareen et al. 2013).
Using atmospherically relevant light levels and aqueous OH concentrations, the timescales for
these changes are all rapid, i.e. on the order of an hour or less. This indicates the atmospheric
concentrations of BrC species will be highest during the night, when their atmospheric significance
for shortwave radiative forcing is zero. For example, in the case of the Imine BrC species, they
may form slowly during the night in cloud or aerosol water and then will decay away rapidly in
the morning. It is expected that during the daytime their steady state concentrations will be highest
in regions where there is considerable droplet evaporation proceeding. Biomass burning BrC
emitted during the night time will be stable. Upon sunrise, photochemistry can induce photo-
enhancement, but the BrC concentration will also fall with further photochemical processing. The
magnitude of photo-enhancement and bleaching is likely dependent to the BrC components, as
well as OH exposure. We conclude that atmospheric models that include only source functions
and depositional loss rates for BrC-bearing organic aerosol will misrepresent the radiative impacts
of these particles, requiring additional parameterizations for photo-bleaching and photo-
enhancement.
Whereas this paper has focused upon aqueous phase processing, it will be important to also assess
the rates of heterogeneous oxidation of BrC species in particles via interactions with gas phase
oxidants and to study direct photolysis in aerosol particles.
Acknowledgement
The authors thank Dan Mather and Ying Lei for the TOC measurement, Wendy Zhang at
Environment Canada for preparing the filter samples, and Andre Simpson and Liora Bliumkin at
University of Toronto Scarborough for useful discussions and trial measurements. Funding for this
work came from NSERC and Environment Canada.
Supplementary Information
174
Supplementary Information for this chapter is given in Appendix C.
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181
Chapter 6
Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of
Secondary Source of HNCO in Ambient Air
Reproduced with permission from Geophysical Research Letter (41), pp 6962–6969
DOI: 10.1002/2014GL061112 Copyright © 2014 American Geophysical Union.
182
Abstract
Although isocyanic acid (HNCO) may cause a variety of health issues via protein carbamylation
and has been proposed as a key compound in smoke-related health issues, our understanding of
the atmospheric sources and fate of this toxic compound is currently incomplete. To address these
issues, a field study was conducted at Mount Soledad, La Jolla, CA, to investigate partitioning of
HNCO to clouds and fogs using an Acetate Chemical Ionization Mass Spectrometer coupled to a
ground-based counterflow virtual impactor. The first field evidence of cloud partitioning of HNCO
is presented, demonstrating that HNCO is dissolved in cloudwater more efficiently than expected
based on the effective Henry’s law solubility. The measurements also indicate evidence for a
secondary, photochemical source of HNCO in ambient air at this site.
6.1 Introduction
Isocyanic acid (HNCO) has been proposed to be a key compound in smoke-related health issues.
In particular, a previous study (Wang et al. 2007) implied a potential connection between HNCO
and protein carbamylation, a process giving rise to a series of health impacts such as cataracts,
rheumatoid arthritis, and cardiovascular diseases (Roberts et al. (2010) and references herein).
Studies of HNCO in the ambient atmosphere, however, have been limited by the lack of
appropriate measurement methods. In situ detection of ambient HNCO has become possible only
since the development of Acetate Chemical Ionization Mass Spectrometry (Acid-CIMS) for the
detection of acid species by Roberts and coworkers (Veres et al. 2008, Roberts et al. 2011, Roberts
et al. 2014). As the Acid-CIMS has been deployed only recently, our understanding of the
atmospheric processing of HNCO remains incomplete.
It is well known that formation of HNCO is associated with pyrolytic processes, having been
detected from pyrolysis of coals (Nelson et al. 1996), nitrogen-containing polymers (Karlsson et
al. 2001), and selected biomass (Hansson et al. 2004). Using the Acid-CIMS, Roberts and
coworkers have further confirmed that HNCO can be directly emitted from biomass burning and
cigarette smoke (Roberts et al. 2010, Veres et al. 2010). Other recent studies (Krocher et al. 2005,
Heeb et al. 2011, Wentzell et al. 2013) have detected HNCO from diesel exhaust and as a by-
product of urea selective catalytic reduction of nitrogen oxides. Relatively unknown to the
183
community is a potential photochemical source of HNCO that has been implicated by very recent
field measurements (Roberts et al. 2011, Wentzell et al. 2013, Roberts et al. 2014) and a laboratory
study of amine oxidation (Borduas et al. 2013). A secondary source has not been incorporated into
global chemical transport models (Young et al. 2012), and the magnitude and mechanism of this
source must be characterized through field and laboratory studies.
In terms of atmospheric sinks, HNCO is resilient against OH oxidation (Tsang 1992) and direct
photolysis (Dixon and Kirby 1968) but is reasonably water soluble, with an effective Henry’s law
constant reaching several thousand M atm−1 at cloudwater-relevant pH values (Roberts et al. 2011).
Therefore, the major sink of HNCO is considered to be via aqueous phase processes. In addition,
it has been shown that the acid-catalyzed hydrolysis reaction can lead to irreversible loss of HNCO
in the aqueous phase (Belson and Strachan 1982). A recent modeling study (Barth et al. 2013)
found that the atmospheric lifetime of HNCO can be a few hours or less in lower level clouds,
depending on the pH of the cloud and temperature. Thus, the degree to which HNCO partitions to
cloudwater plays a crucial role in governing the atmospheric lifetime of HNCO.
Given that there have been no direct field observations of HNCO cloud scavenging, field
measurements were performed at an elevated site near La Jolla, CA, where clouds are often
prevalent, and the area offers a wide range of potential sources of HNCO. In this paper, we report
the first direct detection of HNCO in cloudwater by coupling the Acid-CIMS to a ground-based
counterflow virtual impactor (CVI). We also present evidence of a photochemical source of HNCO
in the ambient air which, at this site, is more significant than its primary source.
6.2 Methods
6.2.1 Site Description
The measurements were conducted near La Jolla, CA (32.8400◦N, 117.2769◦W), from 1 May to
18 June 2012 at a sampling site located near the peak of Mount Soledad (approximately 230 m
above sea level; see Section D1 in Appendix D). During this season, the prevailing wind was
northwesterly (i.e., from the ocean). A back trajectory analysis for this study (Schroder et al. 2014)
suggests that the air mass lifted from closer to the ocean surface 10 to 20 h prior to sampling of
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the cloud at the site. The low-lying clouds sampled at the site have likely arisen from such
advection of marine moisture, nighttime cooling, and lift driven by the low coastal hills.
Other instruments at the Mount Soledad site include a Fog Monitor (FM-100; Droplet
Measurement Technologies (DMT)) to measure ambient liquid water content and droplet size
distribution, a California Institute of Technology Active Strand Cloudwater Collector Version 2,
a single-particle soot photometer (DMT) for black carbon measurement, and a suite of gas phase
and particle size analyzers.
6.2.2 Acid-CIMS
The Acid-CIMS is a chemical ionization mass spectrometry (CIMS) technique utilizing acetate
(Ac−) as the reagent ion. In the current study, the analytes were likely detected via the reaction
represented by Eqn. 6.1 (Veres et al. 2008, Bertram et al. 2011).
Ac−+ MH → AcH + M−. (6.1)
Due to the weak gas phase acidity of Ac−, sample molecules that bear acidic protons (MH) transfer
a proton to Ac− and are detected as M−. However, we cannot rule out the possibility that cluster
formation and fragmentation may also have contributed to the mass-to-charge ratio (m/z) of
interest. The Acid-CIMS can detect a wide range of organic and inorganic acids. Some detectable
species are summarized by Veres et al. (2008). The Acid-CIMS instrument used is a quadrupole
CIMS which has been described elsewhere (Wentzell et al. 2013). For the ambient measurement,
the entire inlet line was externally heated to 80 ◦C to minimize surface loss. The inlet flow was
bypassed to a carbonate denuder every 30 min to scrub gas phase acids and obtain a background
measurement. Calibrations for the acid species were performed in the laboratory before and after
the field measurement. The method of HNCO calibration, calibration factors, and the limit of
quantification for HNCO and nitric acid (HNO3) are listed in Section D2 in Appendix D.
6.2.3 CVI
A ground-based CVI from University of Stockholm was employed to sample cloud droplets while
excluding cloud interstitial particles and gases. The sampled droplets were subsequently dried, and
properties of the residual particles and gases were then measured with a variety of instrumentation.
The operation of the CVI has been described elsewhere (Noone et al. 1988, Noone et al. 1988, Lee
185
et al. 2012). Briefly, the combination of a lower intake flow rate and a warm, dry, and clean
counterflow create a virtual stagnant plane of air inside the tip of the CVI, whereby only larger
particles with sufficient inertia to move through the counterflow out of the tip and reach the
stagnant region can be sampled. The 50% cutoff diameter of the CVI (i.e., the cut size of cloud
droplets sampled by the CVI) is calculated at 11.5 ± 0.7 μm. Once sampled, these cloud droplets
are subject to evaporation due to exposure to the dry, warm part of the counterflow that carries the
droplets/particles to the instrumentation. In previous studies, the ground-based CVI was employed
to investigate the chemical composition of the particulate residuals of cloud droplets and
partitioning of H2O2 (Noone et al. 1991).
The novelty of the current study lies in the coupling of the Acid-CIMS to the CVI, along with an
Aerodyne high-resolution time-of-flight aerosol mass spectrometer (DeCarlo et al. 2006). The
application of the CIMS downstream of the CVI enabled the measurements of organic and
inorganic acids evaporating out of cloud droplets in real time. Such an in situ method is required
for the measurement of cloudwater HNCO, given that it will hydrolyze before off-line
measurements can be performed. In the current study, the ambient sampling inlet was manually
switched to the CVI just prior to the cloud arrival.
6.3 Results and Discussion
6.3.1 Detection of HNCO From Cloudwater
The Mount Soledad site experienced three major cloud events during the campaign. All of these
events began during the night or early morning and terminated before noon. In the current paper
we use the events on 31 May to 1 June (the June 1st event) and on 12 June to 13 June (the June 13th
event) only, as the cloud liquid water content (LWC) during these two cloud events was higher
and all instruments were performing optimally. HNCO was detected from cloudwater along with
HNO3. Detailed descriptions for the quantification of HNCO and HNO3 in the CVI can be found
in Section D3 in Appendix D.
Figures 6.1a and 6.1b highlight the first 3 h of the two cloud events. The mixing ratios of HNCO
and HNO3 detected after the CVI ([HNCO]CVI and [HNO3]CVI) exhibited good correlations with
the ambient LWC, with the R2 values reaching 0.55 and 0.47 during the two events (Figure 6.1c).
186
This implies that HNCO is present in cloudwater and can be detected and that dissolved HNCO
can partition back to the gas phase if the cloud droplet evaporates before HNCO is hydrolyzed.
This verifies the modeling results by Barth et al. (2013), where the partitioning of HNCO was
determined to be reversible.
Figure 6.1: Time series of HNCO and HNO3 mixing ratios measured after the CVI during (a) the June 1st event and
(b) the June 13th event are shown along with LWC in the surrounding air. (c) The correlations of HNCO with LWC
for both of the events are shown.
6.3.2 Estimation of the Aqueous Fraction of HNCO (faq,HNCO)
To estimate the air-cloud partitioning of HNCO, the aqueous fraction of HNCO (faq,HNCO) is
calculated. The faq,HNCO is defined as the fraction of total HNCO present in the aqueous phase in a
unit volume of air with LWC of 0.1 g m−3. This LWC value was chosen because it is approximately
the median of LWC observed in the cloud events (Figure 6.1).
187
The calculation of faq,HNCO was conducted by taking the mixing ratio of HNCO immediately prior
to the cloud events ([HNCO]precloud, shown in Table 6.1) as the total amount of HNCO in the gas
phase and assuming that this amount is equal to the total of HNCO in the cloud ([HNCO]CVI) and
in the interstitial air after the cloud arrival. This method assumes constant atmospheric conditions
before and after the arrival of the cloud. Only the first 3 h of the two cloud events were used
because the diurnal profile of HNCO indicates that the ambient mixing ratio of HNCO is usually
stable at night, with no significant variation for several hours. Given the assumptions above,
faq,HNCO can be represented by the ratio of [HNCO]CVI to [HNCO]precloud. However, this calculation
is dependent upon CVI parameters such as the droplet size cutoff (i.e., the fraction of droplets
sampled by the CVI), the enhancement factor, and droplet transmission in the CVI (Noone et al.
1988). The detailed calculation of faq,HNCO and detailed descriptions of each term are provided in
Section D4 in Appendix D. The time series of the calculated faq,HNCO exhibited significant scatter
but had a relatively constant average in each cloud event. The average faq,HNCO values calculated
for the June 1st and 13th events are 17 ± 3.2% and 7 ± 1.3%, respectively (Table 6.1). The
uncertainty range arises from a relative error of 19%, which we estimated based on the variation
of the parameters used for its calculation (see Section D4.4 in Appendix D).
6.3.3 Unexpectedly High Aqueous Fraction of HNCO
The effective Henry’s law constant (KHeff) of HNCO is highly pH dependent (Roberts et al. 2011),
with an exponential increase at high pH due to enhanced acid dissociation. Given that the pH
values of collected cloudwater samples during the two cloud events were 5.95 and 4.2, the
theoretical faq,HNCO can be calculated (see Section D5 in Appendix D) to be 0.7 % and 0.02 % for
the two events. The observed faq,HNCO values (Table 6.1) qualitatively agree with the pH
dependence of the HNCO partitioning; i.e., a higher faq,HNCO was observed when the cloud pH was
higher in the June 1st event. However, the magnitude of the faq,HNCO is much larger than the
theoretical values. Based on the pH dependence of KHeff, the observed faq,HNCO value on 1 June of
17% corresponds to a pH value as high as 7.35.
188
Table 6.1: Summary of the Aqueous Fraction of HNCO (faq,HNCO) Measured and Calculated
1 Measured from the cloudwater sample collected by the cloudwater collector.
2Calculated from the cloudwater bulk pH and effective Henry’s law constant of HNCO reported by Roberts et al.
(2011).
A potential explanation for the high faq,HNCO is the size dependence of cloudwater acidity, with
larger droplets being less acidic. Different solute composition likely causes the difference between
the smaller (more sulfate) and larger (more sea salt) droplets (Noone et al. 1988). While the CVI
sampled droplets are larger than 11.5 μm, the cloudwater collector had a much lower size cutoff
(diameter = 3.5 μm); thus, the bulk cloudwater pH values represent the average across a wider
range of droplet size. The large droplets, to which more of the HNCO was likely scavenged, might
have been less acidic, giving rise to a higher KHeff value of HNCO.
Entrainment of cloud-free air into a cloud environment can also potentially affect the partitioning
of HNCO in cloud droplets. The entrainment process has been widely investigated in terms of how
it may affect cloud microphysical processes (Baker et al. 1980, Baker 1992). From measurements
of H2O2 in cloud residuals downstream of a CVI, Noone et al. (1991) proposed entrainment as a
possible way to lead to systematic deviations from Henry’s law equilibrium. They showed that
entrainment can supply H2O2 to the cloud air mass if the concentrations outside cloud are higher
than in cloud. Similar phenomenon may occur to HNCO considering that HNCO in clouds can be
depleted due to hydrolysis. However, this data set does not allow us to assess the extent to which
entrainment may influence the partitioning of HNCO.
June 1st Event June 13th Event
[HNCO]pre-cloud (pptv) 48 115
Bulk pH1 5.95 4.2
faq,HNCO measured 17 ± 3.2 % 7 ± 1.3 %
faq,HNCO theoretical2 0.7 % 0.02%
189
Potential systematic errors of the obtained faq,HNCO values are now discussed, given that this is a
particularly challenging measurement. The first arises from the CVI and the pre-cloud mixing ratio
of HNCO. A sensitivity analysis (see Section D4.5 in Appendix D) was performed by
systematically varying each parameter of the CVI and [HNCO]precloud, but the calculated faq,HNCO
was still higher by a factor of 2 than predicted based on its KHeff. We conclude that variations on
this order in the CVI parameters and the pre-cloud mixing ratio of HNCO cannot fully explain the
high faq,HNCO.
Related to this, the assumption that [HNCO]precloud is equal to the total of cloud and interstitial
concentration of HNCO presents another significant uncertainty. This assumption is often applied
to stagnant clouds such as a radiation fog (Collett et al. 2008), where the atmospheric composition
does not change much before and after the cloud formation. However, the clouds observed in the
current study have a strong advection component in addition to the likelihood of enhancement due
to nighttime cooling, making it difficult to assess whether the same air masses are being sampled
before and after the cloud arrives at the sampling site (Schroder et al. 2014). Similarly, primary
emissions into the cloud could have occurred. However, we note that the ratio of HNCO to LWC
remains constant to within a factor of 2 during the first 3 h of each event (Section D4 in Appendix
D). We believe that this is an indication that the pre-cloud amount of HNCO is steady to this level
of precision.
Finally, the total amount of HNCO in the cloud could have decreased due to hydrolysis which has
been shown to be pH dependent, as mentioned previously. At cloud pH of 4.2 (i.e., the June 13th
event), the hydrolysis lifetime can be as short as 2 h (Roberts et al. 2011). In this regard, though,
hydrolysis can only lead to underestimates of faq,HNCO.
6.3.4 Evidence of a Secondary Source of HNCO in the Ambient Air
When clouds are absent at the measurement site, the Acid-CIMS measured HNCO in the ambient
air. A clear diurnal profile of the HNCO mixing ratio was observed (Figure 6.2a). The absence of
episodic spikes of HNCO indicates minimal influence from biomass burning. Also seen in Figure
6.2 is a strong correlation between HNCO and HNO3, a secondary species produced
photochemically (Finlayson-Pitts and Pitts 2000) but not between HNCO and BC, a primary
species. The diurnal profile indicates that the mixing ratio of HNCO typically reached its
maximum at noon, very similar to HNO3 but at a significantly different time from BC (Figure
190
6.2b). HNCO also correlates well with other photochemically produced species (formic acid and
ozone) and the ambient temperature, as shown in Section D6 in Appendix D.
Figure 6.2: The time profile of HNCO and HNO3 measured during a selected period of (a) the campaign and (b) the
averaged diurnal profiles of HNCO, HNO3, and black carbon (BC) from the entire campaign, where the error bars
represent 1𝜎 of the diurnal variation. (c) The primary-secondary apportionment of HNCO is shown. See text for details
about the apportionment.
The strong correlation between HNCO and ambient temperature requires specific concern because
it implies that HNCO might have arisen from surface evaporation (e.g., from ground surface,
aerosol, and cold spots on the inlet line). To test this possibility, we further performed correlation
191
analyses between HNCO and various species for each day (Figure 6.3). It was observed that the
correlations between HNCO and formic acid, HNO3, and ambient temperature were much stronger
during the day than the night (Figures 6.3a to 6.3c). The differences have been shown to be
statistically significant using the paired t test. The weak nighttime correlation and strong daytime
correlation between HNCO and the ambient temperature implies that HNCO has not likely arisen
from surface evaporation which should lead to equally strong correlation during both daytime and
nighttime. HNCO and temperature were likely both influenced by a daytime factor such as solar
radiation. The correlations between BC and temperature (Figure 6.3d), on the other hand, were
uniformly low across the three time periods.
The above observations are evidence of a secondary, photochemical source of HNCO at the
measurement site, complementary to observations from recent field studies (Wentzell et al. 2013,
Roberts et al. 2014). The mechanism of secondary HNCO formation is poorly characterized. As a
possible formation pathway of HNCO, Borduas et al. (2013) recently proposed its formation from
photooxidation of an amine (i.e., monoethanolamine) via an amide intermediate which is known
to give rise to HNCO upon photooxidation (Barnes et al. 2010).
We note that the diurnal profile of HNCO exhibits a sharp rise in the early morning (Figure 6.2b),
resembling that of BC. The correlation of HNCO with BC during the morning rush hours (5 A.M.
to 8 A.M.) is generally stronger than other times during the day (Section D7 in Appendix D). This
implies that a primary source of HNCO may also be present at the measurement site, knowing that
diesel exhaust can contain HNCO (Wentzell et al. 2013).
A simple primary versus secondary apportionment for HNCO sources was performed using the
observed diurnal profiles of HNCO, BC, and O3. Assuming that the primary HNCO exhibits a
similar diurnal trend as that of BC, the secondary HNCO can be calculated as the difference
between the observed total HNCO and primary HNCO. We scaled primary HNCO until the rise
of secondary HNCO matched the rise of the O3 diurnal profile (Figure 6.2c). The area under the
primary and secondary HNCO diurnal profile acts as an estimate of their relative contribution. As
shown in Figure 6.2c, secondary HNCO is roughly twice primary HNCO, indicating that
photochemistry is likely the dominant source of HNCO at the sampling site.
192
Figure 6.3: The time profile of HNCO and HNO3 measured during a selected period of (a) the campaign and (b) the
averaged diurnal profiles of HNCO, HNO3, and black carbon (BC) from the entire campaign, where the error bars
represent 1𝜎 of the diurnal variation. (c) The primary-secondary apportionment of HNCO is shown. See text for details
about the apportionment.
6.4 Summary
This study represents the first time that dissolved gases in cloudwater have been detected in an
online manner, focusing on the cloud scavenging of isocyanic acid (HNCO). In particular, HNCO
evolving from cloud droplet evaporation was detected by an Acid-CIMS coupled to a counterflow
193
virtual impactor (CVI). By estimating the aqueous fraction of HNCO, we find that HNCO may be
scavenged by cloudwater more efficiently than predicted from its effective Henry’s law constant.
This observation confirms that aqueous phase partitioning plays a crucial role in determining the
atmospheric lifetime of this toxic compound. The reason for such significant partitioning is
currently unclear and is a direction for future research. Meanwhile, we observed HNCO
repartitioning to the gas phase once cloud droplets evaporate, confirming the reversibility of this
process (Barth et al. 2013).
We also show evidence of a secondary, photochemical source of HNCO in the ambient air,
consistent with selected observations from previous field and laboratory studies. Our results show
that photochemistry may be the dominant source of HNCO in an environment where the influence
of biomass burning is minimal. This secondary source needs to be considered for applications
where HNCO is used as a tracer of biomass burning. The mechanism and kinetics of secondary
formation of HNCO need to be investigated before it can be incorporated into a global chemical
transfer model.
Acknowledgement
The authors would like to thank Environment Canada, NSERC, and Center for Global Change
Science at University of Toronto for funding and the Russell Research Group for technical support.
The data from this work will be available upon request to the corresponding author.
Supplementary Information
Supplementary information for this chapter is given in Appendix D.
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Chapter 7
Conclusions and Future Research
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7.1 Summary and Future Research for Laboratory Investigations of Aqueous-phase Chemistry
In Chapter 2 and 3, Aerosol CIMS was shown to be a highly valuable technique for online
monitoring of aqueous-phase chemistry. In Chapter 2, the total concentration of the quantified
products exhibited good agreement with the TOC concentration determined independently,
indicating the reliability of quantification using Aerosol CIMS. This was also the first time organic
hydroperoxides were detected from the aqueous-phase using online mass spectrometry,
emphasizing the importance of applying soft-ionization MS techniques. In Chapter 3, the
additional advantages of high mass resolution for this technique was illustrated via employment
of a HR-ToF-CIMS. The novel analysis frameworks, mass defect plot and DBE/#C ratio,
introduced in Chapter 3, can be applied to other systems where high mass resolution MS techniques
are applied to the chemistry of complex organic compounds.
This work and most of the previous investigations for aqueous-phase organic chemistry have
performed experiments in bulk aqueous solutions. While this approach provides fundamental
information about the chemical reactions, it does not fully represent the ambient conditions where
aqueous phases are in a suspended form. Daumit et al. (2014) have recently demonstrated that the
gas-aqueous partitioning of organic compounds is significantly different between bulk aqueous
solutions and suspended aqueous droplets, driven by differences in LWC. The faq as a function of
Heff at the bulk LWC (106 g m-3) is added to Figure 1.2 for comparison (Figure 7.1). As there is
little gas phase in a bulk solution, even the least water soluble compounds may stay entirely in the
aqueous phase. Daumit et al. (2014) have also shown that reaction products forming in the
aqueous-phase are affected in the same way, giving rise to significant difference in SOA yield
between the bulk solution and suspended droplets. In the future, it is important that experiments
be conducted using suspended droplets, as has been done already by several pioneering studies
(Nguyen et al. 2013, Wong et al. 2014).
Chapter 2 and the majority of previous investigations on aqueous-phase processing have focused
on precursors introduced to the aqueous-phase via dissolution from the gas phase, primarily by the
uptake of small carbonyl and dicarbonyl compounds. The chemistry of these precursors is
important, given that it is unrecognized by the traditional gas-particle partitioning theory, where
partitioning to an organic phase prevails. However, these precursors only comprise a small
200
fraction of the total DOC (Herckes et al. 2013). In fact, the majority of DOC is likely introduced
to the aqueous-phase via nucleation scavenging (Ervens et al. 2013). Hindered by the chemical
complexity, aqueous-phase processing of DOC has been investigated by only a small number of
studies (Bateman et al. 2011, Aljawhary et al. 2013, Nguyen et al. 2013). Understanding DOC
evolution during photochemical processes is a critical, yet unexplored research direction. The
Aerosol-ToF-CIMS setup with the novel analysis framework introduced in Chapter 3 is highly
suited for this purpose.
Figure 7.1: Calculated aqueous fraction (faq) as a function of effective Henry’s law constant Heff. The figure
is same as Figure 1.2, but with the addition of faq at bulk LWC (106 g m-3), where chemicals exist entirely
in the aqueous phase.
7.2 Summary and Future Research for Organic Hydroperoxide (ROOH) Formation
In Chapter 4, the formation equilibrium constants for a variety of α-HHP species were quantified.
α-HHP was observed from aldehydes, but not from ketones and methacrolein. It was concluded
that α-HHP may be important in ALW, enhancing the Heff of aldehyde species. While reports of
detection of ROOH in atmospheric aqueous phases are sparse, Chapter 4 demonstrated that ROOH
may present, but existing methods have not been able to detect it. Paulson and coworkers (Hasson
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and Paulson 2003, Arellanes et al. 2006, Wang et al. 2011) have detected unexpectedly high
concentrations of H2O2 from filter extracts. This might be due to the fact that ROOH species have
decomposed during the extraction process, giving rise to H2O2. Given the importance of ROOH
as a reactive oxygen species and as a reservoir of HOx, its fate in atmospheric aqueous phases
should be further investigated.
As ROOH arises from the RO2 + HO2 chemistry (Figure 1.6 (i)), its formation during aqueous-
phase OH oxidation of organic compounds is likely. However, the majority of MS techniques
cannot distinguish ROOH from structural isomers. One approach to overcome this issue is to
optimize the voltages of ion transmission in the mass spectrometer to find a signature
fragmentation pattern for ROOH species. This approach has been successful in detecting gas-phase
ROOH species using a CF3O- CIMS developed by Wennberg and coworkers (Crounse et al. 2006,
St Clair et al. 2010). Another approach is to combine offline chemical assays with the online
approach used in Chapter 2 and 3. Chemical assays such as those based on dichlorofluorescin
(Venkatachari et al. 2005) and iodide (Docherty et al. 2005) are useful in quantifying total ROOH
concentration in solutions. Along this line of thought, an interesting investigation will be to vary
the initial concentration of the precursor organic compounds to examine the yield of ROOH
species. It is expected that higher organic concentrations facilitate RO2 + RO2 chemistry which
does not give rise to ROOH.
7.3 Summary and Future Research for Atmospheric Brown Carbon (BrC)
Chapter 5 demonstrated that photochemical processing in the aqueous-phase significantly altered
the light absorptivity of BrC species. The rate at which photo-enhancement and photo-bleaching
occur should be further quantified. Given that the work conducted in Chapter 4 did not offer
molecular information for the BrC species and their reaction products, the immediate next step
would be their identification. As imine-BrC and ambient BrC comprises highly complex organic
mixtures, chromatographic separation should be employed prior to MS analysis. A high
performance liquid chromatography – diode array detection – electrospray ionization (HPLC-
DAD-ESI) MS technique is highly suited for this purpose, as the separation, absorption and MS
202
detection are integrated in one system. Once the BrC species and their products are identified, the
absorbance-based modeling approach employed in Chapter 5 can be converted to a concentration
basis, and the rate constants will gain more applicability to atmospheric models.
The poly-carbonyl intermediates observed in OH oxidation of levoglucosan (Chapter 3) contain
extensive electron conjugation and may represent a class of unrecognized BrC that arises from
other sugars and polyols. Sugars are abundant in the atmosphere, arising from biological sources
(Wan and Yu 2007), while polyols are produced from condensed-phase chemistry of isoprene
epoxydiols (Surratt et al. 2010). OH oxidation of these compounds may give rise to similar poly-
carbonyl intermediates observed in Chapter 3 and deserves further investigation. As mentioned in
Section 7.1, the experiment should be conducted in suspended droplets to better represent the gas-
aqueous partitioning taking place in the atmosphere. Photo-acoustic absorption spectrometry
(PAS) is currently the only method able to directly monitor particle absorptive properties and
should be further optimized and applied in laboratory experiments.
7.4 Summary and Future Research for Cloud Partitioning of Organic Compounds
In Chapter 6. the faq of isocyanic acid (HNCO) was measured in the field. By coupling online MS
downstream of a CVI, this work demonstrated the first online measurement of organic compounds
dissolved in ambient cloudwater. HNCO was for the first time detected from ambient cloudwater,
and its partitioning to cloudwater was shown to be more significant than expected from its Heff.
Models commonly assume Henry’s law equilibria for gas-aqueous partitioning of water soluble
organic compounds (Carlton et al. 2008, McNeill et al. 2012), but field confirmation for this
assumption is lacking. The ambient atmosphere is highly dynamic, and Henry’s law equilibria may
or may not be established. Noone et al. (1991) have observed that entrainment (i.e. introduction of
dry air to in-cloud air) perturbed the in-cloud Henry’s law equilibrium of H2O2. The presence of
highly concentrated salts in ALW may also cause deviation from Henry’s law equilibrium (Kroll
et al. 2005, Wang et al. 2014). On the other hand, measurements of scavenging efficiency of
organic compounds by nucleation scavenging are also sparse (Herckes et al. 2013). More field
203
measurements integrating the gas and particle aqueous phases should be conducted to better
quantify Heff and scavenging efficiency in the ambient atmosphere.
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(ToF-CIMS): application to study SOA composition and processing., Atmos. Mea. Tech., 6, 2013.
Arellanes, C., Paulson, S., Fine, P. and Sioutas, C.: Exceeding of Henry's law by hydrogen
peroxide associated with urban aerosols, Environ. Sci. Technol., 40, 4859-4866, 2006.
Bateman, A. P., Nizkorodov, S. A., Laskin, J. and Laskin, A.: Photolytic processing of secondary
organic aerosols dissolved in cloud droplets, Phys. Chem. Chem. Phys., 13, 12199-12212, 2011.
Carlton, A. G., Turpin, B. J., Altieri, K. E., Seitzinger, S. P., Mathur, R., Roselle, S. J. and Weber,
R. J.: CMAQ Model Performance Enhanced When In-Cloud Secondary Organic Aerosol is
Included: Comparisons of Organic Carbon Predictions with Measurements, Environ. Sci.
Technol., 42, 8798-8802, 2008.
Crounse, J. D., McKinney, K. A., Kwan, A. J. and Wennberg, P. O.: Measurement of gas-phase
hydroperoxides by chemical ionization mass spectrometry, Anal. Chem., 78, 6726-6732, 2006.
Daumit, K., Carrasquillo, A., Hunter, J. and Kroll, J.: Laboratory studies of the aqueous-phase
oxidation of polyols: submicron particles vs. bulk aqueous solution, Atmos. Chem. Phys., 14,
10773-10784, 2014.
Docherty, K., Wu, W., Lim, Y. and Ziemann, P.: Contributions of organic peroxides to secondary
aerosol formed from reactions of monoterpenes with O3, Environ. Sci. Technol., 39, 4049-4059,
2005.
Ervens, B., Wang, Y., Eagar, J., Leaitch, W. R., Macdonald, A. M., Valsaraj, K. T. and Herckes,
P.: Dissolved organic carbon (DOC) and select aldehydes in cloud and fog water: the role of the
aqueous phase in impacting trace gas budgets, Atmos. Chem. Phys., 13, 5117-5135, 2013.
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Hasson, A. and Paulson, S.: An investigation of the relationship between gas-phase and aerosol-
borne hydroperoxides in urban air, J. Aerosol Sci., 34, 459-468, 2003.
Herckes, P., Valsaraj, K. T. and Collett Jr, J. L.: A review of observations of organic matter in fogs
and clouds: Origin, processing and fate, Atmos. Res., 132, 434-449, 2013.
Kroll, J. H., Ng, N. L., Murphy, S. M., Varutbangkul, V., Flagan, R. C. and Seinfeld, J. H.:
Chamber studies of secondary organic aerosol growth by reactive uptake of simple carbonyl
compounds, J. Geophys. Res. Atmos., 110, D23207, 2005.
McNeill, V. F., Woo, J. L., Kim, D. D., Schwier, A. N., Wannell, N. J., Sumner, A. J. and Barakat,
J. M.: Aqueous-phase secondary organic aerosol and organosulfate formation in atmospheric
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Nguyen, T. B., Coggon, M. M., Flagan, R. C. and Seinfeld, J. H.: Reactive Uptake and Photo-
Fenton Oxidation of Glycolaldehyde in Aerosol Liquid Water, Environ. Sci. Technol., 47, 4307-
4316, 2013.
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of organic compounds in complex environmental samples using high-resolution electrospray
ionization mass spectrometry, Anal. Methods, 5, 72-80, 2013.
Noone, K. J., Ogren, J. A., Noone, K. B., Hallberg, A., Fuzzi, S. and Lind., J. A.: Measurements
of the partitioning of hydrogen peroxide in a stratiform cloud, Tellus B, 43, 280-290, 1991.
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ionization tandem mass spectrometer for the in situ measurement of methyl hydrogen peroxide,
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Flagan, R. C., Wennberg, P. O. and Seinfeld, J. H.: Reactive intermediates revealed in secondary
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reactive oxygen species in rubidoux aerosols, J. Atmos. Chem., 52, 325-326, 2005.
205
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chloride attachment in liquid chromatography/negative ion electrospray mass spectrometry,
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Ammonium Sulfate Solutions, Environ. Sci. Technol., 48, 13238-13245, 2014.
Wang, Y., Kim, H. and Paulson, S.: Hydrogen peroxide generation from alpha- and beta-pinene
and toluene secondary organic aerosols, Atmos. Environ., 45, 3149-3156, 2011.
Wong, J. P., Zhou, S. and Abbatt, J. P.: Changes in Secondary Organic Aerosol Composition and
Mass due to Photolysis: Relative Humidity Dependence, J. Phys. Chem. A, 2014.
206
Appendix A
Supplementary Information For:
Chapter 3
Aqueous-phase Photooxidation of Levoglucosan – a Mechanistic
Study Using Aerosol Time-of-Flight Chemical Ionization Mass
Spectrometry (Aerosol ToF-CIMS)
As published in Atmos. Chem. Phys. 14, 9695–9706, 2014. DOI:10.5194/acp-14-9695-2014
Distributed under the Creative Commons Attribution 3.0 License.
207
A1 List of Detected Peaks
Table A1: List of peaks detected by the I(H2O)n- reagent ion. The chemical formulae were assigned using the data
processing software (Tofwerk v. 2.2). The peak time and Max. peak intensity are the illumination time at which each
peak reached its maximum, and its corresponding signal intensity at that time, respectively. The peak intensity has
been normalized by the intensity of the reagent ion at m/z 145 (I(H2O)-). This information, along with the exact m/z
and mass defect were used to construct the mass defect plot (Figure 3.4 in the main article). The compounds displayed
in Figure 3.6 in the main article are color coded.
Detected
Formula
Exact m/z
(Th)
Mass
defect (Th)
Peak time
(min)
Max. peak
intensity Note
CH2O2I 172.911 -0.0895 133 5.76E-03 Formic acid
C2H2O3I 200.905 -0.09458 300 7.91E-03 glyoxylic acid
C2H4O3I 202.921 -0.07893 300 2.92E-03
glycolic acid or
glyoxal
monohydrate
C3H2O3I 212.905 -0.09458 145 1.82E-03 Product (i)
C3H4O3I 214.921 -0.07893 95 7.51E-04 Product (ii)
C2H2O4I 216.900 -0.09967 500 3.00E-03 Oxalic acid
C3H6O3I 216.937 -0.06328 62 1.97E-03
C2H4O4I 218.916 -0.08402 83 1.05E-04
C4H4O3I 226.921 -0.07893 105 1.42E-04
C4H4O3I 226.921 -0.07893 105 1.42E-04
C3H2O4I 228.900 -0.09967 200 8.57E-05
C4H6O3I 228.937 -0.06328 90 3.27E-04
C3H4O4I 230.916 -0.08402 182 6.38E-04
208
C3H6IO4 232.932 -0.06837 141 9.79E-05
C5H4IO3 238.921 -0.07893 97 2.64E-04
C4H2O4I 240.900 -0.09967 101 2.46E-03
C4H4O4I 242.916 -0.08402 105 9.02E-04
C4H6O4I 244.932 -0.06837 79 1.05E-03 Product (iii)
C3H4IO5 246.911 -0.0891 233 6.81E-05
C5H2IO4 252.900 -0.09967 97 1.40E-04
C5H4O4I 254.916 -0.08402 98 2.73E-04
C4H2O5I 256.895 -0.10475 200 4.00E-05
C5H6O4I 256.932 -0.06837 95 3.29E-04
C4H4O5I 258.911 -0.0891 169 9.14E-04 Product (iv)
C5H8O4I 258.947 -0.05272 66 2.65E-04
C4H6O5I 260.927 -0.07345 97 1.37E-04
C3H4IO6 262.906 -0.09419 500 4.00E-05
C5H2O5I 268.895 -0.10475 160 1.40E-04
C5H4IO5 270.911 -0.0891 116 3.79E-04
C5H6IO5 272.927 -0.07345 75 1.31E-03 Product (v)
C5H8IO5 274.942 -0.0578 72 2.33E-04 Product (vi)
C4H6IO6 276.921 -0.07854 151 4.37E-05
C6H4IO5 282.911 -0.0891 102 7.21E-05
209
C6H6O5I 284.927 -0.07345 76 1.02E-03
C6H8IO5 286.942 -0.0578 48 6.49E-03
C6H10IO5 288.958 -0.04215 0 4.49E-02 levoglucosan
C6H2O6I 296.890 -0.10984 260 3.80E-05
C6H4O6I 298.906 -0.09419 136 1.80E-04
C6H6O6I 300.921 -0.07854 97 1.19E-03
C6H8O6I 302.937 -0.06289 81 7.67E-04
C6H10O6I 304.953 -0.04724 46 5.08E-04
C6H4O7I 314.901 -0.09927 220 3.33E-05
C6H6IO7 316.916 -0.08362 200 1.85E-04
C6H8O7I 318.932 -0.06797 97 5.93E-04
C5H6O8I 320.911 -0.08871 330 4.00E-05
C6H10IO7 320.948 -0.05232 59 4.83E-04 Product (vii)
C6H6O8I 332.911 -0.08871 280 8.00E-05
C6H8O8I 334.927 -0.07306 143 1.78E-04
C6H10O8I 336.943 -0.05741 61 1.34E-04
C6H8O9I 350.922 -0.07814 200 7.00E-05
A2 Proposed Mechanisms
210
iii) C4H
6O
4
O O
OH
OH
OHOH
O2O O
OH
OH
OHO
O
RO2O O
OH
OH
OHO
Scheme 2
Scheme 3
Scheme 1
Scheme 2
O O
OH
OH
OHO
O
CH
O
OH
OH
OHO
O2
O O
OH
OH
OHOO
O
RO2
RO2
O O
OH
OH
OH
O OH
O O
OH
OH
OHOO
O O
OH
OH
OHOO
O O
OH
OH
OHOO
O O
OH
OH
OHOO
O O
OH
OH
OHOO
O
OH
OH
OH
O
O
O
+
O
O
O
OH
OH
OH
O
+O2
OH
OH
OHO
O
O
-HO2
O
OH
OHO
O O
OH
OH
OHOO
O
CH
O
OH
OH
OHOO
O2O O
OH
OH
OHOOO
O
O
O
OH
OH
O
O
O
Scheme 3
O O
OH
OH
OHO
O O
OH
OH
OHO
O O
OH
OH
OHO
O O
OH
OH
OHO
O
CH
O
OH
OH
OHO
O O
OH
OH
OHO
O
O
-HO2
O OO
OH
OH
O
C6H
8O
6
O O
OH
OH
OHO
O O
OH
OH
OHO
CH
O+
O O
OH
OH
OHO
O
CH
OH
OH
OH
OO
+
O2
O2O
OH
OH
OHO
O
-HO2
C6H
8O
7
-HO2
vii) C6H
10O
7
vi) C5H
8O
5
vi) C5H
8O
5
iii) C4H
6O
4
O O
OH
OH
OHO
O O
OH
OH
OHO-H2O
O
OH
OH
OH
O
Scheme 4
O
OH
OHO
O
O
OHO
OH
-H2O
C
O
OH
OHO
H2O
OH
O
OHO
OH
OH
-H2O
H2O
C
OH
O
OHO
OH
O2
OH
O
OHO
OHO
O
-HO2
O
O
OHO
OH
O
OH
OHO
OH
O2
-H2OO
OH
OHO
O O
-HO2
iv) C4H
4O
5
O2
O
OH
OHO
O
O
RO2
O
OH
OHO
O
-CO2
CH OH
OHOO2
OH
OHO
OO
O
OHO
OH
O2
-H2OO
OHO
OO-HO2
O
OO
ii) C3H
4O
3
i) C3H
2O
3
Scheme 5
Scheme 4
O
OH
OH
OH
O
Scheme 5
OH
O2
-H2O O
OH OH
OH
O
OO
-HO2
O
OH
O
OH
O
Scheme 4
Glyoxal
v) C5H
6O
5
vi) C5H
8O
5
iii) C4H
6O
4
-HO2
211
Figure A1: Proposed reaction mechanism giving rise to the products displayed in Figure 3.6 (main article). The overall
reaction mechanism of levoglucosan photooxidation is highly complicated, and only a subset is shown here. As one
example, the mechanism demonstrates the case when H-abstraction occurs at the position shown in Scheme 1.
Subsequent chain scission can lead to two different reaction pathways shown in Scheme 2 and Scheme 3, respectively.
Scheme 4 demonstrates that products from Scheme 3 can undergo the hydroxyl-to-carbonyl conversion which is
discussed in the functionalization section in the main article. Scheme 5 illustrates hydration of an aldehyde and its
subsequent conversion to a carboxylic acid.
A3 Estimation of the Diffusion Limited Rate Constant of LG Oxidation by OH Radicals in the Aqueous Phase.
We calculated the diffusion limited rate constant to be 1.9 × 109 M-1s-1, based on the following
Eqn. A1 (Pilling and Seakings, 1995):
k (M-1s-1) = 1000 × 4π × (rLG+rOH
2) × (DLG + DOH) × NA, (A1)
where 1000 is a conversion factor for units, rx and Dx represents the radius and diffusion coefficient
of molecule X in water, respectively, and NA is the Avogadro constant. The value of rLG is
estimated to be 0.22 nm, assuming LG is approximately half the size of a sucrose (a sugar dimer)
(Pappenheimer 1953). The value of rOH is assumed to be 0.1 nm, a typical O-H bond length of a
water molecule. The diffusion coefficient of glucose in water (0.6 × 10-9 m-2s-1, from Stein 1990)
is used as DLG, given the similarity between LG and glucose. The value of DOH (1 × 10-9 m-2s-1) is
adopted from Hanson et al. (1992).
Bibliography
Hanson, D. R., Burkholder, J. B., Howard, C. J. and Ravishankara, A. R.: Measurement of Oh and
Ho2 Radical Uptake Coefficients on Water and Sulfuric-Acid Surfaces, J. Phys. Chem., 96, 4979-
4985, 1992.
212
Pappenheimer, J. R.: Passage of Molecules through Capillary Walls, Physiol. Rev., 33, 387-423,
1953.
Pilling, M. J. and Seakins, P. W.: Reaction kinetics, Oxford University Press, Oxford England ;
New York, 1995.
Stein, W. D.: Channels, carriers, and pumps: an introduction to membrane transport, Academic
Press, San Diego, 1990.Pilling, M. J. and Seakins, P. W.: Reaction kinetics, Oxford University
Press, Oxford England ; New York, 1995.
213
Appendix B
Supplementary Information For:
Chapter 4
Formation of Aqueous-phase α-hydroxyhydroperoxides (α-HHP):
Potential Atmospheric Impacts
As published in Atmos. Chem. Phys. 13, 5857–5872. DOI:10.5194/acp-13-5857-2013
Distributed under the Creative Commons Attribution 3.0 License.
214
B1 Example 1H NMR Spectra and Peak Assignment for Each Carbonyl Compound.
The carbonyl-H2O2 mixtures at equilibrium are shown.
Figure B1: Glycolaldehyde (10 mM) and H2O2 (17.7 mM)
5x106
4
3
2
1
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(1, s)(5, t)
(3, t)
(2, s)
(6, d)
(4, d)
(DMSO, s)
Water
215
Figure B2: Methylglyoxal (10 mM) and H2O2 (17.7 mM).
10x106
8
6
4
2
0
Sig
nal In
tensity (
AU
)
8 7 6 5 4 3 2 1 0 -1
Chemical Shift (ppm)
5x106
4
3
2
1
0
Sig
nal In
tensity (
AU
)
4.90 4.80 4.70
Chemical Shift (ppm)
10x106
8
6
4
2
0
Sig
nal In
tensity (
AU
)
2.1 2.0 1.9 1.8
Chemical Shift (ppm)
4x106
3
2
1
0
Sig
nal In
tensity (
AU
)
1.2 1.0 0.8
Chemical Shift (ppm)
(formic acid, s)
(5, s)
(3, s)
(17, s)
(11, s)
(15, s)
water
(?, s)
(DMSO, s)
(6, s)
(4, s)
(?, s) (16, d)
(10, d)
(18, d)
216
E
Figure B3: Propionaldehyde (10 mM) and H2O2 (17.7 mM).
4x106
3
2
1
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0 -1 -2 -3
Chemical Shift (ppm)
1.0x106
0.8
0.6
0.4
0.2
0.0
Sig
nal In
tensity (
AU
)
4.85 4.80 4.75
Chemical Shift (ppm)
3.5x106
3.0
2.5
2.0
1.5
1.0
0.5
0.0
Sig
nal In
tensity (
AU
)
0.80 0.70 0.60
Chemical Shift (ppm)
(1, t)
(7, t)
(4, t)
(DMSO, s)
(2, dq)
(5 and 8, multi)
(3, t)
(9, t)
(6, t)
water
217
Figure B4: Glyoxal (10 mM) and H2O2 (17.7 mM).
10x106
8
6
4
2
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(DMSO, s)(formic acid, s)
water
(?, q)
(2?, d)
(?, s)
218
Figure B5: Glyoxylic acid (10 mM) and H2O2 (17.7 mM).
5x106
4
3
2
1
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(formic acid, s)
(2, s)
(DMSO, s)
(?, s)
219
Figure B6: Methacrolein (10 mM) and H2O2 (100 mM).
5x106
4
3
2
1
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(1,s)
(DMSO,s)
water
(2, t)
(2, t)
(?, s)
(3, t)
220
Figure B7: Methylethyl ketone(10 mM) and H2O2 (100 mM).
20x106
15
10
5
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(DMSO, s)
water
(2, q)
(1, s)
(3, t)
(?, d)
221
Figure B8: Acetone (10 mM) and H2O2 (100 mM).
150x106
100
50
0
Sig
nal In
ten
sity (
AU
)
10 9 8 7 6 5 4 3 2 1 0
Chemical Shift (ppm)
(DMSO, s)
(1, s)
(?, d)
water
222
Table B1. Comparison of Kapp values experimentally determined and calculated as (Keq/Kapp).
Keq determined
(M-1)
Khyd
determined
Keq / Khyd
(M-1)
Kapp determined
(M-1)
formaldehyde 1.66 × 106 2300* 723 164
acetaldehyde 230 1.43 161 113.5**
propionaldehyde 116 1.256 92 67.5**
glycolaldehyde 727 16 45 43.3
*Was not determined from the current work, but taken from Betterton and Hoffmann 1988.
** Are the averaged values from the 1H NMR and the PTR-MS measurements.
Bibliography
Betterton, E. A. and Hoffmann, M. R.: Henry law constants of some environmentally important
aldehydes, Environ. Sci. Technol., 22, 1415-1418, 1988.
223
Appendix C
Supplementary Information For:
Chapter 5
Photochemical Processing of Aqueous Atmospheric Brown Carbon
As published in Atmos. Chem. Phys. Discuss. 15: 2957-2996, DOI:10.5194/acpd-15-2957-2015.
Distributed under the Creative Commons Attribution 3.0 License.
224
C1 Determination of Photon Flux in the Solar Simulator
The output of the solar simulator was recorded using the detector of the liquid waveguide capillary
UV-Vis spectrometer described in the main article Section 2.2. This method qualitatively
determines the spectral shape of the simulated sunlight.
Meanwhile, chemical actinometry using 2-nitrobenzaldehyde (2NB) was employed to
quantitatively evaluate the simulated sunlight. This chemical actinometer has been employed
previously by Anastasio and coworkers for quantification of photon flux in aqueous phase and ice.
The absorption cross section, as well as the recommended quantum yield of this compound, are
provided by Galbavy et al. (2012).
A 2NB solution (200 uM, 100 mL) was prepared and was illuminated in the solar simulator.
Aliquots were taken every two minutes for offline analyses. Measurement of 2NB was conducted
using a high performance liquid chromatography (HPLC) system equipped with a Perkin Elmer
Series 200 pump, a Shimadzu SPD-10A UV-Vis detector, a Waters Symmetry® C18 column (5
µm pore size, 4.6 mm diameter and 150 mm column length). A mixture of acetonitrile and water
(60 : 40) was used as the mobile phase in isocratic mode, with a flow rate of 1 mL / min. Absorption
at 256 nm was monitored for the detection of 2NB.
Using the absorption cross section and recommended quantum yield of 2NB (Galbavy et al. 2010),
we scaled the recorded output spectra from the solar simulator to match the observed decay rate of
2NB. The photon flux determined this way is shown in Figure C1, along with ambient actinic flux
at the Earth’s surface with a zenith angle of 0 ˚ (Finlayson-Pitts and Pitts 2000).
The integrated photon flux between 290 and 380 nm is similar between the simulated and ambient
photon flux. Although the simulator supplies more photo photons than the ambient at longer
wavelengths, we assume that they are fairly similar, as we do not know what wavelengths are
responsible for BrC photolysis (i.e. the quantum yields are unknown).
225
Figure C1: The photon flux in the solar simulator and in the ambient.
C2 Quantitative Assessment of BrC Absorption
C2.1 Imine BrC
The mass absorption coefficients (MAC) of the GLYAS and MGAS solutions were calculated.
While it is difficult to estimate the amount of BrC in the solution, we used the total organic carbon
(TOC) content of the solution to calculate MAC. The concentrated stock solutions of GLYAS and
MGAS were diluted by a factor of 100, and the TOC content of the diluted solutions was measured
using a Shimadzu TOC-ICPH Total Organic Analyzer. The wavelength dependent MAC(λ) is
calculated based on Eqn. C1 (Lee et al. 2014):
MAC(λ) = A(λ) × ln (10)
b × Cmass, (C1)
where A(λ) is the base-10 absorbance observed at wavelength λ, b is the effective path length of
the liquid capillary waveguide (50 cm), and Cmass is the mass concentration (g cm-3) of total organic
carbon in the solution. The MAC(λ) values of GLYAS and MGAS calculated using Eqn. C1 are
shown in Figure C2(a).
226
C2.2 WSOC from Biofuel Combustion Samples
Calculations of the MAC for the biofuel combustion samples are conducted based on the organic
matter (OM) contents measured by an OM/OC method described by Chan et al. (2010). MAC(λ)
was calculated similar to Imine BrC using Eqn. C1 and is shown in Figure C2(b). We consider the
MAC determined in the current method a lower limit for these sample because: 1) particles freshly
emitted from BB likely contain a large fraction of non-light absorbing organic compounds (Chen
and Bond 2010), and 2) WSOC presents only a fraction of the total OM content of the particle,
and the extraction efficiency is unknown.
The Angstrom absorption coefficients (AAE) between 290 nm and 480 nm were calculated using
Eqn. C2 (Chen and Bond 2010) and are reported in the main article:
AAE = ln (
MAC(λ1)MAC(λ2)⁄ )
ln (λ1λ2⁄ )
. (C2)
C2.3 Nitrophenols
Since the nitrophenols are pure compounds, their wavelength dependent molar absorptivity (ε(λ))
and absorption cross section (σ(λ)) are calculated based on Eqn. C3 and C4, respectively.
ε(λ) = A(λ)
c ×b (C3)
σ(λ) = 1.66 × 10-21ε (C4)
Eqn. C3 is based on the Beer-Lambert law, where A(λ) is the base-10 absorbance observed at
wavelength λ, c is the molarity of the nitrophenol (M), and b is the effective path length of the
liquid capillary waveguide (50 cm). Eqn. C4 converts ε(λ) to σ(λ) (both in base 10) (Finlayson-
Pitts and Pitts, 2000). The calculated ε(λ)and σ(λ) are displayed in Figure C2(c).
227
a) b)
c)
Figure C2: Wavelength dependent mass absorption coefficient (MAC) for the Imine BrC (a), the WSOC from biofuel
combustion samples (b), and the base 10 absorption cross section and molar absorptivity of the nitrophenols (c).
228
C3 Concentration Dependence of Imine BrC Decay Rate
Figure C3: Decay of the GLYAS solution (a) and the MGAS solution (b) during the first 10 min of illumination at
different initial concentrations.
C4 Spectral Change of 4NP and 5NG during Direct Photolysis
Figure C4: Spectral change observed for a 4NP solution (a) and a 5NG solution (b) during direct photolysis
experiments. The initial concentrations of 4NP and 5NG were 5 µM and 4 µM, respectively. The insets illustrate the
absorbance change compared to the initial conditions.
229
C5 pH Dependent Photo-enhancement of 4NP and 5NG and OH Scavenger Experiments
We investigated the photo-enhancement of the nitrophenols at solution pH of 3, 4 and 5. We also
conducted an OH scavenger experiment where glyoxal (1 mM) was added to a pH 5 solution to
react OH radicals away.
The OH scavenger experiment affects the photo-enhancement rate of 4NP, but did not completely
shut down the reaction. 5NG was not affected by the OH scavenger. The photo-enhancement rate
of 4NP at 420 nm exhibited irregularity (Figure C5(a)), perhaps due to the fact that 420 nm was
close to the isosbestic point of 4NP absorption. When we plotted the photo-enhancement of 4NP
at a longer wavelength, 450 nm (Figure C5(b)), we observed a clearer pH dependence. 5NG
exhibited a unique pH dependence (Figure C5(c)), where the photo-enhancement was suppressed
significantly when the pH was 3.
For 4NP and 5NG, the formation of color exhibited strong linearity in time, which prevented us
from fitting a 1st order growth curve to extract kIdirect. Therefore, we decided to present the rate of
photo-enhancement (k*direct) in an absorbance based manner using Eqn. C5 in units of [AU M-1 s-
1]:
k*direct = S
60 × Cini⁄ (C5)
where S (AU min-1) is the initial slope of color formation found from Figure C5, 60 is the
conversion factor from minutes to seconds, and Cini (M) is the initial concentration of the
nitrophenol. The k*direct values obtained are summarized in Table C1. If the identity and molar
absorptivity of the reaction products are determined from future studies, these absorbance based
rate constants can be converted into concentration based constants.
230
Table C1: The absorbance based 1st order rate constant of photo-enhancement
Compound
Cini
(µM)
k*direct (AU M-1 s-1)
pH3 pH4 pH 5
pH 5 OH
scav.
4NP (420 nm) 15 0.68 0.62 0.40 0.24
4NP (450nm) 15 0.37 0.47 0.64 0.47
5NG (420 nm) 8 2.7 4.0 4.8 4.8
Figure C5: Color formation from 4NP and 5NG solutions during the pH dependent and the OH scavenger
experiments. The formation profiles of absorbance at 420 nm and 450 nm from 4NP are shown in (a) and (b). The
formation profiles of absorbance at 420 nm from 5NG are shown in (c).
231
C6 pH Dependent Absorption of Nitrophenols
Figure C6: Absorption spectra of 4NP (a), 5NG (b) and 4NC (c) at various solution pH values.
C7 Photooxidation of 4NP and 5NG
232
Figure C7: The spectral change of 4NP and 5NG solutions during OH oxidation experiments are shown in (a) and
(c). The time profiles of absorbance at 420 nm for 4NP and 5NG are shown in (b) and (d). In (b) and (d), the black
traces represent H2O2 control experiments, while the red traces represent OH oxidation experiments. The concentration
of 4NP and 5NG solutions are 15 µM and 8 µM, respectively.
C8 Simple Kinetic Model Applied to 4NP and 5NG
In this model, the precursor nitrophenols undergo prescribed pseudo-1st order decay with a [OH]ss
of 3.2 × 10-14 M. For the case of 4NP we also observed direct loss by photolysis (Figure C7(b)) by
the 254 nm lamp with a rate constant of 2.6 × 10-4 s-1. This direct photolysis was also added to the
prescribed decay of 4NP. The 2nd order rate constant of 4NP was adopted from Einschlag et al.
(2003): 6.2 × 109 M-1 s-1. Although the OH reactivity of 5NG and 4NC in the aqueous phase is not
available in the literature, we used 1 × 1010 M-1 s-1 as a rough estimate for these two compounds.
This estimation is based on the fact that the additional methoxy and hydroxy functional groups on
5NG and 4NC are electron donating and can likely enhance the OH reactivity. The model results
for sample 4NP and 5NG OH oxidation experiments are shown in Figure C8.
233
Figure C8: The simple kinetic model applied to one example experiment each of 4NP (a) and 5NG (b) OH oxidation.
The shaded areas are the simulated contribution of a newly formed colored product and the decay precursor. The red
lines represent the experimental results.
Bibliography
Chan, T. W., Huang, L., Leaitch, W. R., Sharma, S., Brook, J. R., Slowik, J. G., Abbatt, J. P. D.,
Brickell, P. C., Liggio, J. and Li, S.: Observations of OM/OC and specific attenuation coefficients
(SAC) in ambient fine PM at a rural site in central Ontario, Canada, Atmos. Chem. Phys., 10,
2393-2411, 2010.
Chen, Y. and Bond, T.: Light absorption by organic carbon from wood combustion, Atmos. Chem.
Phys., 10, 1773-1787, 2010.
Einschlag, F. S. G., Carlos, L. and Capparelli, A. L.: Competition kinetics using the UV/H2O2
process: a structure reactivity correlation for the rate constants of hydroxyl radicals toward
nitroaromatic compounds., Chemosphere, 53, 1-7, 2003.
Finlayson-Pitts, B. J. and Pitts, J. N.: Chemistry of the upper and lower atmosphere : theory,
experiments and applications, Academic Press, San Diego, Calif. ; London, 2000.
234
Galbavy, E. S., Ram, K. and Anastasio, C.: 2-Nitrobenzaldehyde as a chemical actinometer for
solution and ice photochemistry, J. Photochem. Photobiol. A., 209, 186-192, 2010.
Lee, H. J., Aiona, P. K., Laskin, A., Laskin, J. and Nizkorodov, S. A.: Effect of solar radiation on
the optical properties and molecular composition of laboratory proxies of atmospheric brown
carbon, Environ. Sci. Technol., 48, 10217-10226, 2014.
235
Appendix D
Supplementary Information For:
Chapter 6
Cloud Partitioning of Isocyanic Acid (HNCO) and Evidence of
Secondary Source of HNCO in Ambient Air
Reproduced with permission from Geophysical Research Letter (41), pp 6962–6969
DOI: 10.1002/2014GL061112 Copyright © 2014 American Geophysical Union.
236
D1 Map of the measurement sites
Figure D1: The current work was part of a collaborative field measurement at La Jolla, CA. Measurements were
performed concurrently at two locations: Mt. Soledad (A), and Scripps Pier (B). The current paper focuses on the
CIMS data obtained at site A.
D2 Calibration of the Acid-CIMS
D2.1 Calibration Methods
The HNCO calibration was performed using the same method as used previously [Wentzell et al.,
2013]. Nitrogen was introduced through a HNCO source containing cyanuric acid (trimer of
HNCO) and heated to 200 ˚C. The output of the source was then quantified using ion
chromatography as NCO-.
Commercial permeation tubes were used for the calibration of nitric acid (HNO3).
D2.2 Calibration factors and limits of quantification of HNCO and HNO3
Table D1: Calibration factors of the Acid CIMS.
237
Name
Chemical
formula
Limit of quantification
(LOQ) (pptv)a
Calibration Factor
(ncps/ppbv)b
isocyanic acid HNCO 11 0.446
HNO3 HNO3 6.2 0.69
a LOQ was determined as 10 times the standard deviation of the background signal of each compound over a 30 min
time integral.
b The calibration factor is presented as normalized counts per second (ncps) per parts per billion by volume (ppbv) of
the targeted compound. Signals of the analytes were normalized against the reagent ion at m/z = 61 (one of the isotopes
of acetate). The signal at m/z 61 is typically 2.5 × 104 cps.
D3 Quantification of HNCO and HNO3 in CVI.
D3.1 CVI Background
While the CIMS background during the ambient measurement is the time period during which the
inlet flow is directed through a bicarbonate denuder, the background during the CVI periods is
different. Since compressed air used as the counterflow contains impurities, the background during
CVI measurements is the period when there is no cloud droplet sampled (i.e. analyte signals come
solely from the compressed air). We used the signals during periods where liquid water content
(LWC) was below its 10th percentile as the background period of the CVI. When LWC is low,
HNCO and HNO3 from droplet evaporation are negligible, and the detected signals should reflect
their levels in the compressed air used.
D3.2 Normalization and Quantification
The raw signal was normalized against the reagent ion at m/z 61, before the CVI background was
corrected (Sect. S3.1.). After that, the same calibration factors (see Sect. S2.) were used to convert
signals to mixing ratios.
238
D4 Calculating the Aqueous Fraction of HNCO (faq,HNCO)
As defined in the main article, faq,HNCO is the fraction of total HNCO present in a LWC of 0.1 g m-
3. faq,HNCO is the ratio between the aqueous-phase concentration of HNCO and the total amount of
HNCO, taking into account CVI parameters (Eqn. D1). This section provides explanations for
each of the parameter used in S1. For more details about specific CVI parameters, please refer to
Schroder et al. (2014).
faq,HNCO =S×0.1
[HNCO]CIMS,pre-cloud ×
1
EF ×
1
DT × fliquid (D1)
S – The slope obtained from linear fitting of [HNCO]CVI vs. LWC (Figure 6.1c in the main article).
EF – Enhancement factor of the CVI. See Sect. S4.1. for details.
DT– Droplet transmission in the CVI. See Sect S4.2. for details.
fliquid – Fraction of LWC in the ambient air sampled by the CVI. See Sect. S4.3. for details.
The values for the parameters above are summarized in Table D2, and the time series of the
calculated faq,HNCO is shown in Figure D2.
Table D2: The parameters from the June 1st and the June 13th cloud events are summarized. D50 represents the
calculated 50 % size cutoff of the CVI (the cloud droplet cut size).
Cloud
Event
S D50 EF f DT
June 1st 166 11.57 7.25 0.9705 0.2766
June 13th 171 11.48 7.14 0.9062 0.2601
239
Figure D2: Calculated time series of the aqueous-fraction of HNCO (faq,HNCO) during the June 1st and June 13th cloud
events.
D4.1 Determination of the Enhancement Factor (EF)
Cloud droplets sampled by the CVI is concentrated by an Enhancement Factor (EF) because wind
tunnel air speed (i.e. from the ambient to the CVI) is faster than the sample flow air speed (i.e.
from CVI to the instruments), resulting in a compression of air near the stagnant plane [Noone et
al. 1988]. In other words, the cloud droplets sampled by the CVI are enhanced in number by a
factor of the EF. EF is calculated in accordance with Noone et al. [1988] using Eqn. D2:
EF = Sw × π × r2
Ss (D2)
Sw – The wind tunnel air speed.
Ss – The sample flow air speed.
r – The inner radius of the CVI tip.
240
D4.2 Determination of Droplet Transmission (DT) in the CVI
The droplet transmission (DT) of the CVI used is not 100% due to slower drying of larger droplets
and an imperfectly aligned air stream with respect to the CVI axis, giving rise to droplet loss in
the CVI. The DT value is estimated by comparing the number concentration of cloud droplets in
the ambient air (Ndroplet) and evaporation residues in the CVI (NRes), monitored by the Fog Monitor
and the CPC, respectively. For Ndroplet, only droplets with diameters above the CVI cutoff are
considered (Ndroplet > D50). The NRes is divided by the EF to take the enhancement into
consideration. If there is no particle loss in the CVI, the slope of the plot should be 1 (the dashed
line). However, as shown in Figure D2., Ndroplet >D50 is significantly larger than NRes / EF,
reflecting droplet loss in the CVI. The DT values are obtained as the reciprocal of the slopes.
Figure D3: Comparison of number concentrations of cloud droplets in the ambient air (Ndroplet >D50), and evaporation
residue in the CVI (NRes) divided by the calculated EF. Data from the June 1st event (a) and the June 13th event (b) are
shown. The dashed line represents a line with a slope of one, whereas the solid line shows the actual linear fitting.
Droplet Transmission (DT) is obtained as the reciprocal of the slope.
241
D4.3 Determination of the fraction of LWC sampled by CVI (fliquid)
The fraction of LWC sampled by the CVI (term fliquid in Eqn. D1) is estimated from the size
distributions of the cloud droplets in the ambient air (Figure D4). As shown in Figure D4, the CVI
did not sample a significant fraction of the small droplets in terms of number, but may have
sampled the majority of the liquid volume and surface area. The fraction of volume concentration
above the cut-off are presented by the fliquid term.
Figure D4: The size distribution of number (black), volume (blue) and surface area (green) concentration of cloud
droplets in the ambient air during the June 1st (a) and the June 13th (b) events, monitored by the Fog Monitor. The
dashed lines represent calculated 50 % size cut-off of the CVI.
D4.4 Error propagation for faq,HNCO
The relative uncertainty of the obtained faq,HNCO is estimated to be 19 %, by propagating the error
of each parameters used in Eqn. D1. The error of each of the parameters is explained here:
S – the relative error is estimated to be 10 % based on the scatter of [HNCO]CVI vs LWC (Figure
6.1c) in the main article.
242
EF – the relative error is estimated to be 15 %. The error of EF arises from the uncertainty of the
wind speed (Sw and Ss in Eqn. D2). Their relative errors are approximately 10% each.
DT – the relative error is estimated to be 5 %, based on the scatter of Figure D3.
fliquid – the relative error is estimated to be 5 %, based on the relative error of the CVI cut size.
D4.5 A sensitivity test for faq,HNCO
Since each of the parameter mentioned above directly affects the accuracy of the calculated
faq,HNCO, we performed a simple sensitivity test by calculating faq,HNCO under a “perturbed case”
(Table D3). The perturbed case represents an extreme, unlikely case, where [HNCO]pre-cloud and
EF are twice as large as the actual value, and there is no particle loss in the CVI (i.e. fliquid = 1).
We consider the perturbed case the maximum extent to which systematic errors can affect our
calculated faq,HNCO.
Table D3: A comparison of the calculated faq,HNCO in the actual case and a perturbed case. The perturbed values are
highlighted in red.
Event S
[HNCO]pre-
cloud (pptv) EF fliquid DT
LWC (g
m-3) faq,HNCO
June1st Actual case 0.17 48 7.25 0.97 0.28 0.1 0.17
Perturbed case 0.17 96 14.5 0.97 1 0.1 0.012
June13th Actual case 0.17 115 7.14 0.91 0.26 0.1 0.073
Perturbed case 0.17 230 14.28 0.91 1 0.1 0.0047
243
D5 The pH-dependence of KHeff of HNCO and the theoretical aqueous fraction of HNCO (faq,HNCO)
Figure D5: Calculated KHeff of HNCO as a function of pH, based on data reported by [Roberts et al., 2011] is shown
in (a). The measured pH of bulk cloud water samples collected during the June 1st Event (Blue) and the June 13th
Event (red) are also shown as the dashed lines. The KHeff at these two pH values are 3.0 × 103 and 8.0 × 102 M atm-1,
respectively. Based on the KHeff values shown on (a), the theoretical aqueous fraction of HNCO (faq,HNCO) is calculated
as a function of pH and LWC (b).The calculations assume complete Henry’s law equilibrium between the gas and
aqueous phases.
244
D6 Time series and diurnal profiles of HNCO, formic acid and ambient temperature
Figure D6: Time series of HNCO, formic acid and ambient temperature during a specific period
of the campaign are shown in (a). Clear correlations between these traces can be seen. The
campaign-averaged diurnal profiles are shown in (b). The peak of HNCO mixing ratio is reached
at similar time as the other traces shown here.
245
D7 Strength of correlation between HNCO and BC during various time periods
Figure D7: Linear fitting between HNCO and Black Carbon (BC) was performed for various time periods of each
measurement day, and R2 values from the fitting are shown here. The correlation is typically strongest during morning
rush hours (5am to 8am; black). The differences are statistically significant at the 95% confidence level. This is an
indication that there might be a primary source of HNCO during the morning rush hour.
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Wentzell, J. J. B., J. Liggio, S.-M. Li, A. Vlasenko, R. Staebler, G. Lu, M.-J. Poitras,T. Chan, and
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Recommended