ABSTRACT
INVESTIGATION OF THE SOURCES OF HYDROGEN
PEROXIDE IN AMBIENT PARTICULATE MATTER
Reactive oxygen species (ROS) are oxygen centered free radicals and their
metabolites, including hydroxyl (OH), hydroperoxyl (HO2), hydrogen peroxide
(H2O2), and the superoxide radical anion (O2.-). ROS may affect the chemical
composition of the atmosphere by aerosol aging.Redox active species such as
transition metals and quinone compounds may be important sources of ROS that
are produced by redox cycling. The goal of this project is to quantify ROS
(specifically H2O2) generation by particles as well as to elucidate the components
in particles that are responsible for ROS generation.
Particulate matter samples were collected in Claremont and Fresno during
2012 and 2013.Sections of these filters were extracted into dilute acid solutions,
and high performance liquid chromatography (HPLC) was used to quantify ROS
generated by samples. The data indicate that Fresno samples and Claremont
samples generate similar quantities of ROS, and that quinones and free transition
metal ions cannot account for the generation of ROS by the particulate matter
filter samples. The formation of ROS might be due to the presence of organic
soluble, non-polar compounds present within the particles.
Sowmya Keerthi Tummala
May 2015
INVESTIGATION OF THE SOURCES OF HYDROGEN
PEROXIDE IN AMBIENT PARTICULATE MATTER
by
Sowmya Keerthi Tummala
A thesis
submitted in partial
fulfillment of the requirements for the degree of
Master of Science in Chemistry
in the College of Science and Mathematics
California State University, Fresno
May 2015
APPROVED
For the Department of Chemistry
We, the undersigned, certify that the thesis of the following student
meets the required standards of scholarship, format, and style of the
university and the student's graduate degree program for the
awarding of the master's degree.
Sowmya Keerthi Tummala
Thesis Author
Alam S. Hasson (Chair)
Chemistry
Jai-Pil Choi
Chemistry
Laurent Dejean
Chemistry
For the University Graduate Committee:
Dean, Division of Graduate Studies
AUTHORIZATION FOR REPRODUCTION
OF MASTER’S THESIS
X
I grant permission for the reproduction of this thesis in part or in
its entirety without further authorization from me, on the
condition that the person or agency requesting reproduction
absorbs the cost and provides proper acknowledgment of
authorship.
Permission to reproduce this thesis in part or in its entirety must
be obtained from me.
Signature of thesis author:
ACKNOWLEDGMENTS
I would like to express my sincere gratitude to my thesis advisor Dr. Alam
S. Hasson, who gave me the opportunity to conduct my study in his Research
group. Words are not sufficient to describe the sincere appreciation for your
guidance and the endless support. Thank you to my committee members, Dr. JaiPil Choi and Dr. Laurent Dejean, for the feedback and support. To the Department
of Chemistry staff, Rosalina Messer, Doug Kliewer, and Alan Preston, thanks for
the work behind the scenes. I would like to extend a special appreciation to The
Hasson Atmospheric Lab; I have made lifelong friends throughout the time.
A special thanks to my family. Words cannot express how grateful I am to,
my mother, my father, and my sister for all the support and the sacrifices that you
have made. Your prayers for me was what sustained me so far. I would also like to
thank all my friends who supported me in every aspect to strive towards my goal.
TABLE OF CONTENTS
Page
LIST OF TABLES ................................................................................................. vii
LIST OF FIGURES ............................................................................................... viii
INTRODUCTION .................................................................................................... 1
Air Pollution ...................................................................................................... 1
Particulate Matter .............................................................................................. 4
Reactive Oxygen Species (ROS) ...................................................................... 9
Measurements of Peroxides ............................................................................ 12
Research Objectives ........................................................................................ 20
EXPERIMENTAL ................................................................................................. 22
General Research Design ................................................................................ 22
Sampling Locations......................................................................................... 22
Sample Collection ........................................................................................... 23
Extraction Methods ......................................................................................... 25
Extraction Solution Preparation ...................................................................... 25
Preparation of Fluorescent Reagent ................................................................ 26
Solid Phase Extraction (SPE) .......................................................................... 26
Instrumentation ............................................................................................... 28
Calibration of HPLC ....................................................................................... 30
RESULTS ............................................................................................................... 36
Hydrogen Peroxide Calibration ...................................................................... 36
Production Rates of H2O2 for the Trial Filters ................................................ 37
Production Rates of H2O2 for Fresno Samples: Fresno Filter 11 ................. 40
DISCUSSION......................................................................................................... 49
vi
Page
Ambient Mass Loadings ................................................................................. 49
Parallel Studies ................................................................................................ 53
Role of Quinones and Metals .......................................................................... 55
Back Trajectories ............................................................................................ 60
CONCLUSION ...................................................................................................... 66
Future Work .................................................................................................... 67
REFERENCES ....................................................................................................... 68
LIST OF TABLES
Table 1. National Ambient Air Quality Standards for Criteria Pollutants4 ............. 3
Table 2. H2O2 Calibration Data for Different Lab Suppliers................................. 37
Table 3. Collection Details of Fresno Filters ......................................................... 44
Table 4. Collection Data for Claremont Filters ..................................................... 46
Table 5. Statistical Data for Correlation Between PM 2.5 Mass Loadings and
H2O2 Formation........................................................................................ 55
Table 6. Statistical Data for the Correlation Between H2O2 Formation and
Specific Quinones .................................................................................... 56
LIST OF FIGURES
Page
Figure 1. Aerosol size distribution8 ......................................................................... 5
Figure 2. Quinone redox cycle reactions51 ............................................................ 18
Figure 3. Regional overview of air quality sampling
location sites at
Claremont[A], CA and Fresno[B], CA.61 ............................................... 23
Figure 4. Tisch Environmental TE-6070 hi-volume PM2.5 sampler65 ................. 24
Figure 5. High Performance Liquid Chromatography with 63
post-column
derivation and fluorescence detection instrument. ............................... 29
Figure 6. Calibration curve of H2O2 for Macron, Fischer and Sigma-Aldrich ..... 36
Figure 7. Production rates of H2O2 per hour for the trial filters ............................ 38
Figure 8. H2O2 Production rates under variable conditions for Fs-02................... 38
Figure 9. Differences in the production of H2O2 under variable conditions for
Fresno filters 1 and 2............................................................................... 40
Figure 10. Production rates of H2O2 under variable conditions for Fs-11 ............ 41
Figure 11. Rate of formation of H2O2 for Fresno samples grouped into
morning, afternoon, and overnight samples............................................ 43
Figure 12. Average production rates of H2O2 for the filters collected from 16
to 19 January 2013 .................................................................................. 43
Figure 13. Rate of formation of H2O2 for Claremont filters .................................. 45
Figure 14. Rate of formation of H2O2 for aqueous, organic and residual filter
extracts for specific Fresno samples ....................................................... 47
Figure 15. H2O2 variations for aqueous, organic, and residual filter extract for
specific Fresno samples .......................................................................... 48
Figure 16. Variation between Fresno and Claremont samples .............................. 49
Figure 17. Temporal variations of H2O2 formation rates for specific Fresno
samples .................................................................................................... 51
Figure 18. Temporal variation of mass loadings for Claremont filters ................. 51
Figure 19. Correlation
between PM2.5 Particle mass and H2O2 mass loadings
in (µg/m3) for Fresno filters .................................................................... 54
ix
Page
Figure 20. Correlation
between PM mass loadings and H2O2 mass loadings in
(µg/m3) for Claremont filters. ................................................................. 54
Figure 21. Correlation between H2O2 against anthraquinone and
phenanthraquinone .................................................................................. 57
Figure 22. Correlation between the average copper concentration and rate of
formation of H2O2 for Fresno samples .................................................... 59
Figure 23. Correlation between H2O2 production rates and average copper
mass loadings for Claremont samples .................................................... 59
Figure 24. Backward trajectory of airmass for Fresno samples with higher
production rates of H2O2 ......................................................................... 62
Figure 25. Backward trajectory of airmass for Fresno samples with lower
production rates of H2O2 ......................................................................... 63
Figure 26. Backward trajectory of airmass for Claremont samples with higher
H2O2 formation rates ............................................................................... 64
Figure 27. Back trajectory of airmass for Claremont samples with lower H2O2
formation rates ........................................................................................ 65
INTRODUCTION
Reactive oxygen species (ROS) are oxygen centered free radicals with
strong oxidative capacity. ROS along with their metabolites have both
environmental and health effects1,2. Hydrogen peroxide (H2O2), an ROS play an
important role in aqueous phase photochemical reactions that occurs in
atmospheric water drops. Furthermore, ROS may affect the chemical composition
of the atmosphere by aerosol aging and also through the oxidation of organic and
inorganic species within the particles2. Redox-active species such as quinones and
transition metals are observed to be the major factors of particulate matter and are
involved in particle bound ROS formation. This study will quantify ROS
generation as well as elucidate the components in particles that are responsible for
ROS generation by particles.
Air Pollution
Suspension of dust along with the gas in the air, the emission of pollutants
from fuel combustion, industrial processes, rock debris, and non-industrial fugitive
sources contribute to the lethal effects on the environment. Air pollution is more
characterized by the release of nitrogen oxides (NOx), particulate matter (PM) and
volatile organic compounds (VOCs), which undergo photochemical reactions in
sunlight to form more toxic products such as ozone2. High concentrations of
pollutants in the atmosphere have deleterious effects on humans and environment.
To prevent pollution from increasing and to protect public health from diverse
array of pollution sources, the clean air act (CAA) imposed federal regulations of
certain pollutants.3,4
2
The Clean Air Act
The CAA was the first modern environmental law enacted by the U.S.
Congress in 1970 and major amendments were made in 1977 and 1990. CAA
imposed federal regulations on some pollutants called criteria pollutants. The
environmental protection agency3 was formed to implement the law, set standards
and monitor pollutant levels in the presence of sunlight and hydrocarbons.
National Ambient Air Quality Standards (NAAQS)4 monitored six pollutants
which include ozone, nitrogen oxides (NO x), particulate matter (PM), Volatile
organic compounds (VOCs),sulfur oxides (SO x), Lead (Pb). Of these criteria air
pollutants, particulate matter is one of the pollutants that pose the greatest threat to
human health. These chemical emissions are able to react in the atmosphere to
form more toxic products in the atmosphere. These criteria air pollutants’ sources
are listed in Table 1.
Primary and Secondary Pollutants
Air pollutants are classified into primary and secondary pollutants by their
formation and entry into the atmosphere. Primary pollutants are directly emitted
into the atmosphere either through natural or anthropogenic sources. Secondary
pollutants are formed in the atmosphere when chemical reactions produce low
volatility species that condense on to preexisting particles or nucleate new
particles.
Secondary particles may also be more hazardous than the chemicals that are
emitted directly (Sulfuric acid, VOCs)2,8. Atmospheric conditions, geographic
conditions affect the relative importance of primary and secondary pollutants.
3
Table 1. National Ambient Air Quality Standards for Criteria Pollutants4
Pollutant
Carbon
monoxide
(CO)
Lead (pb)
Nitrogen
Dioxide
(NO2)
Primary/
Secondary
Major sources
Primary
Motor vehicle exhaust
Primary/
Secondary
Primary
Primary/
Secondary
Ozone (O3) Primary/
Secondary
Particulate
Matter(PM)
Primary
PM 2.5a
Secondary
PM 10b
Primary/
Secondary
Primary/
Secondary
Primary
Sulfur
Dioxide
(SO2)
a
Secondary
Fuels in on-road motor
vehicles and industrial
sources
Motor vehicle exhaust
Chemical reactions
between oxides of
Nitrogen (NOx) and
volatile organic
compounds in the
presence of sunlight
Direct emissions from
incomplete combustion,
fire/wood burning and
industrial emissions
Averaging
time
8-h
Federal
standard
9 ppm
1-h
35 ppm
3-month
0.15 µg.m3
1-h
100 ppb
Annual
53 ppb
8-h
0.075 ppm
Annual
12 µg.m-3
Annual
15 µg.m-3
24-h
35 µg.m-3
24-h
150 µg.m3
Unpaved road and
agricultural dust
Combustion of sulfur
containing fuels
1-h
75 ppb
3-h
0.5 ppm
Particulate matter with Da < 2.5 µm.b Particulate matter with Da > 2.5 µm
4
Particulate Matter
Atmospheric aerosol is often described in terms of particle size distribution,
nature of origin, and chemical composition. A dramatic increase in atmospheric
aerosols is observed during the last two centuries, which may be due to due to the
industrialization and rapid growth in the world’s population. High levels of
ambient PM have been linked to adverse health effects, affect global climate, and
lead to visibility reduction.5 Many approaches have been made to measure,
characterize, and model atmospheric aerosols during the last few decades.6, 7
PM is present as tiny particles of floating debris in the air we breathe and
the particle size ranges from 0.002 µm to 100 µm. PM arises from natural sources
such as windborne dust, volcanoes, and also from anthropogenic activities such as
combustion of fuels. PM can be categorized in terms of aerodynamic diameter8
into fine, ultrafine, and coarse particles. As all the particles are not perfectly
smooth spheres with uniform densities, aerodynamic diameter, Da specifies the
size, shape, density, and velocity of the particle classified. Aerodynamic diameter
is defined as the diameter of a sphere with unit density that retains the same
terminal speed in air8. Coarse particles have an aerodynamic diameter of 2.5-10
µm and are commonly referred to as PM10. Fine particulate matter (PM2.5), has an
aerodynamic diameter range of 0.1-2.5 µm, while ultrafine particulate matter has
an aerodynamic diameter less than 0.01 µm.
Lifetimes of emitted pollutants are dependent on their classification to size
and also on the mode of formation. Particle growth9 determines the fate and
transport processes in the atmosphere. Four distinctive modes of particle formation
and their respective particle sizes are listed in Figure 1.
5
Figure 1. Aerosol size distribution8
Formation and Growth of Particulate
Matter
PM in the atmosphere is formed by condensation, nucleation or coagulation
mechanisms.8,9 The path through which the particles are formed depends on the
ambient temperature, vapor pressure, humidity, concentration, and particle size.
The formation of fine particulate matter can be categorized into Aitken or
transient nuclei (0.01µm-0.08µm) and fine accumulation (0.08-1-2µm), which
have an atmospheric life time of a few days to weeks and can be transported up to
a few thousand kilometers. Primary emissions produce particles of 0.01µm0.08µm where hot vapors from sources such as incomplete combustion fuel from
diesel exhaust and the oxidized organic compounds are released. Thus, the
6
particles that are condensed to form fresh particles are largely lost by coagulation
with larger atmospheric particles. The accumulation mode extends the formation
of fine PM up to a diameter of 2.5µm by coagulation and condensation of vapors
on to existing particles causing them to grow in size. Figure 1 represents the
aerosol size distribution and particle formation mechanisms in atmosphere.
Ultra fine particles have atmospheric life time of few hours and can be
transported up to few tens of kilometers. Combustion sources and new particle
production from low volatile gaseous compounds are major sources of ultrafine
particles. Ultra fine particles are removed from the atmosphere by coagulation,
particle growth, and deposition processes2. On mass concentration basis, ultrafine
particles contribute to only a small fraction of atmospheric PM.
Organic matter, which is a major component of tropospheric aerosol,
constitutes about 10 to 70% of the fine particulate matter.13 Ambient aerosols
containing organic matter play an important role in the atmosphere by acting as
cloud condensation nuclei (CCN), which are further activated to form cloud
condensation nuclei and are known to alter the cloud properties.
Organic aerosols undergo several changes in the atmosphere through
various mechanisms, which include aging, condensation of soluble inorganic and
oxidized organic species (OOA), condensed phase chemistry, and heterogeneous
oxidation of volatile organic compounds (VOCs) by O3, OH and NO3, followed by
the conversion of the oxidized gaseous products to particles. Aging processes and
oxidation of organic compounds enhance the water solubility and increase the
number of polar functional groups of organic aerosol, which makes them active as
cloud condensation nuclei.14,15
7
Recent work14 has shown that the majority of the organic particulate matter
emitted from various anthropogenic and combustion sources are evaporated after
their emission. The resultant semi-volatile organic vapors can react in the gasphase with atmospheric oxidants, hydroxyl radicals, and OH to form low volatility
oxidation products. The low volatility oxidation products can recondense to the
particle phase within a time span of several hours to days. This evaporation,
reaction, and condensation process leads to the formation of highly oxygenated
organic aerosol that has significant effect on the physical properties, chemical
properties, and chemical nature of organic aerosol. The low volatility organic
compounds exist in particle phase in distinctive atmospheric concentrations.
Organic aerosols evolve by becoming highly oxidized, more hygroscopic,
and less volatile compounds, which finally lead to the formation of oxygenated
organic aerosols (OOA). Previous studies16 from various locations identified that
the major content of organic aerosol is constituted of oxygenated organic aerosol
which is characterized with high oxygen content and high oxidation state. The
increased levels of oxidized organic aerosols are strongly correlated with
photochemical activity.17,18 Oxidized organic aerosol formation occurs mainly
through the condensation of less volatile compounds on to the accumulation mode
particles.15
Field and laboratory data from previous studies15 have observed that
oxidation state and volatility of organics can be used to identify the evolution of
organic aerosols. Low volatile (LV-OOA), highly oxidized organic aerosols are
strongly correlated with non-volatile species such as sulfates and semi-volatile
oxidized organic aerosols (SV-OOA) and are strongly correlated with semivolatile species such as ammonium chloride, which are less photo chemically aged
8
aerosols.19,20 The relative concentrations of these aerosols are dependent on the
photochemistry and temperature in the atmosphere.15
Aging of Aerosols
Organic aerosol particles undergo various chemical reactions by interacting
with inorganic ions, clouds, or water vapor and change the physical structure of
aerosol. The chemical aging of organic aerosols alter the chemical composition of
the particles forming more water soluble and hygroscopic compounds. A review
on the chemical processing of organic aerosols has been done in previous
studies.10,11
Aldehydes are detected to be the major volatile products in reaction of
ozone with aerosol that has a fatty acid component. Previous studies also proved
that ozonolysis of long chain unsaturated carboxylic acids lead to smaller
molecules with higher hygroscopicity, which can either stay in aerosol-phase or
escape in to the atmosphere.10-13
Hydrolysis, nitration, and oxidation of solid organics allow the
hydrocarbons to escape from the aerosol-phase by volatilization. The condensation
reactions and oligo or polymerization reactions initiated by radicals or acid
catalyzed heterogenous reactions of aldehydes increases the aerosol mass and thus
decreases the volatility of organic aerosol components and promote the formation
of secondary organic aerosol particulate matter.12
Chemical Composition of PM
Particles emitted or formed in the atmosphere undergo changes in their size
and composition by coagulation with other particles, condensation or evaporation
of volatile species, absorption of water in high relative humidity conditions and
activation into fog or cloud droplets before removed through wet or dry deposition
9
processes. Collective properties of atmospheric aerosol such as mass and number
concentration, radiative and optical properties can be determined form the
emission sources and their subsequent transformation mechanisms.
Particles in the coarse particle range are produced mechanically through
crushing or attrition of larger particles and derived from suspensions or resuspension of dust, sea salt, volcanic eruptions, and biomass burning. These large
particles settle out of the atmosphere by sedimentation or by wet deposition via
cloud drops. Coarse particles have atmospheric lifetime of few hours and are
transported over tens of kilometers before they are removed through wet or dry
deposition. These large particles settle out of the atmosphere by sedimentation or
by wet deposition via cloud drops.2,8
Reactive Oxygen Species (ROS)
PM plays an important role in the formation of reactive oxygen species.
Several chemical species like transition metals and organic compounds, such as
quinones, are known to be involved in the event of particle bound ROS formation.
H2O2 can be produced via redox cycling between HO2/O2•‾ radical and transition
metals, which in ambient particles and cloud drops may be complexed by
organics.23-25,46,57
ROS are oxygen centered free radicals and their metabolites which are
derived from molecular oxygen (O2). ROS include hydroxyl (OH), hydro peroxyl
(HO2), organic peroxyl radical (RO•2), and anions such as superoxide radical anion
(O2•-). ROS in aerosols may lead to aging of aerosol, which is the oxidation of
organic and inorganic species within particles. Hydrogen peroxide and its related
ROS have been identified as a key source to the aqueous phase reactions that take
10
place in water suspended in the atmosphere and are central to cloud processing of
air.8
Formation and Loss of Gas-Phase
Hydroperoxides
Gaseous hydrogen peroxide (H2O2) and organic hydroperoxides (ROOH)
are unstable compounds that are decomposed to oxygen in the atmosphere and
also act as a sink and source for radicals.25 Additionally, hydroperoxides are
efficient in the aqueous oxidation of S (IV) complexes to sulfuric acid (H2SO4) in
the troposphere that affects the geographical and temporal patterns of sulfuric acid
deposition. H2SO4 plays an important role in the formation of new particles in
atmosphere by nucleation.26 Highly oxidized poly carboxylic acids make stronger
hydrogen bonds with H2SO4 to form stable molecular clusters that lead to the
formation of new particles in the atmosphere.26 Of the hydroperoxides, H2O2 is
dominant, representing 60-90% of total hyroperoxides; the remaining 10-30% are
organic hydroperoxides.27,28 Formation of gas-phase hydroperoxides is dependent
on factors such as temperature, solar radiation, and water vapor. Also, it is
dependent on NOx and higher concentrations of VOCs. Gas-phase and aerosolphase hydrogen peroxides are formed in the atmosphere via three routes.29-34
The major route through which hydrogen peroxide is produced is through
the self coupling of hydroperoxyl radicals (HO•2) (R1), and with other alkoxy
radicals (R2). The reaction of peroxy radical with alkoxy radicals have been
shown to proceed by H-atom abstraction to form the hydrogen peroxide with a
yield of unity.2,29
HO2•+HO2•
H2O2+O2 (R1)
RO2• +HO2•
ROOH +O2• (R2)
11
The source of HO2 is primarily from the photolysis of ozone (O3) forming
singlet oxygen, O(1D) (R3),which can react with water to form hydroxyl radicals
(OH•). Hydroxyl radicals (R4) can further react with carbon monoxide in the
presence of O2 to form HO2 and CO2 (R5).
O (1D) +O2 (R3)
O3+ hv (λ >320nm)
2OH• (R4)
O (1D) + H2O
OH• + CO (+O2)
HO2•+CO2 (R5)
Alkanes react with OH• (R6) to form an alkyl radical, which in turn reacts
with O2 (R7) to form a peroxy radical. The peroxyl radical reacts with NO (R8) to
produce an alkoxy radical and nitrogen dioxide (NO2). Alkoxy radicals are formed
in the atmosphere by the degradation of volatile organic compounds (VOCs) in the
presence of nitrogen monoxide (NO).The alkoxy radicals proceed through a
number of pathways to form stable radical products and generate low volatility
oxygenated species in the condensed phase.
RH + •OH
R• +H2O (R6)
R•+ O2
RO2•
RO2• + NO
RO• + NO2 (R8)
(R7)
Criegee intermediates, which are a product of alkene ozonolysis(R9), react
with water vapor (R10) and form hydroperoxides; this is another major route for
the formation of H2O2. The yield of H2O2 depends on the concentration of water
vapor in alkene ozonolysis.31,32
CH2=CH2+O3
RCHOO +H2O
CH2COO+R2CO (R9)
RCHO + H2O2 (R10)
The hydro peroxyl radical (HO2•) has been considered to be the
predominant source of hydrogen peroxide in atmospheric water drops.33,34
Atmospheric water vapor absorbs solar ultraviolet radiation and initiates the
12
aqueous phase photochemical reactions in ambient cloud and fog water. The
photochemical reaction of organic chromatophores present in cloud water leads to
the formation of free radicals and oxidants.25
Photolysis of Fe (III)-oxalate complexes is the source for photoformation of
H2O2 in atmospheric water drops. Fe (III)-organic complexes on photolysis form
Fe (II) and organic radicals. Fe (II) and some organic radicals reduce O2 to •O2and forms H2O2. Photolysis of Fe (III) with other polycarboxylate complexes such
as citrate and malonate is also suggested to be a major source of H2O2.35,36
Gaseous phase formation of hydroperoxides is not only dependent on NOx,
CO, CH4 and non-methane hydrocarbons but is also dependent on other factors
such as high concentrations of volatile organic compounds that enhance the
formation of peroxide. It has been found that when NO levels exceed 100 ppt,
measurable H2O2 suppression occurs66. An environment with high volatile organic
carbons (VOCs):NOx ratio, along with carbon monoxide (CO), will tend to
enhance peroxide formation due to the availability of radicals, whereas at a low
VOC:NOx ratio, peroxide generation is suppressed due to the radical scavenging.
Measurements of Peroxides
Gaseous-Phase Measurements
Numerous measurements of gas-phase peroxides have been done at various
locations.28-30,36,37,45 Primary measurements of H2O2 along with organic peroxides
have been measured since the 1990s. H2O2 is the dominant peroxide with 0.110ppb with levels typically being 1ppb. Field measurements of gas-phase
hydrogen peroxide indicate its presence in the troposphere at concentrations less
than 10 ppb by volume. Gas-phase H2O2 was found to be in the range of 0.5-3.5
ppbv from the most recent measurements at UCLA.30
13
Aerosol Measurements
Only a few studies have been successful in quantifying aerosol-phase
hydrogen peroxide due to the difficulty associated with these measurements.
Limited measurements of particle phase H2O2 have demonstrated high levels of
H2O2 associated with ambient fine-mode aerosols. First field measurements done
by Hewitt and Kok2 indicated atmospheric aerosol-phase hydrogen peroxide
concentration in the range of 0.01 to 10ng m-3.The reported values may be
uncertain due to the poor chromatographic separations of hydrogen peroxide, and
because of the possible formation of artifacts resulting from reaction of ozone and
hydrocarbons in the filter during sampling. Field study of aerosol-phase ROS
reported mass loading as high as 63ng m-3. Past studies by Hung and Wang36
indicated that the concentrations of ROS were affected by the intensity of the
photochemical reactions and reported the H2O2 concentrations of 21ng m-3.
Measurements of aerosol-phase hydrogen peroxide levels at UCLA were in
the range of 0.01-13ng m-3. Based on the mass loading of aerosol-phase H2O2 and
water in the aerosol, it was concluded that the concentration of H2O2 within these
aerosols was of the order of 10-3M. 30Also, recent studies by Venkatachari et al.
reported an average of 243ng m-3 aerosol-phase ROS concentrations in Rubidoux,
CA.37 A strong seasonal variation was observed for studies of both gas-phase and
aerosol-phase hydrogen peroxide measurements. Past studies also conclude that
H2O2 productions display variability with H2O2 levels higher in mid-to late
afternoon, and lowest during the night and morning hours. Also, extensive studies
indicate that H2O2 displays a strong seasonal variation, with highest levels of H2O2
in the spring and summer.
Other factors that influence peroxide levels are meteorological parameters
such as solar radiation, water vapor concentration, and temperature. Solar
14
radiation is required for radical formation and water vapor promotes radical
reactions. High temperatures are known to favor peroxide production. Peroxides
are the reservoirs of radicals where photolytic destruction will yield HO and to
some extent HO2 radicals.33
The OH radicals can take part in aqueous phase formaldehyde or formic
acid oxidation. Gaseous formaldehyde undergoes dissolution into cloud droplets to
form hydrated formaldehyde. The hydrated formaldehyde undergoes oxidation
with OH to form CH (OH)2 radical (R11). The obtained CH (OH)2 reacts with O2
to form hydrated formic acid (HCOOH)(R12). Formic acid undergoes dissolution
to form HCOO- ion (R13).38
CH2 (OH) 2+ OH
CH (OH) 2+ O2
HCOOH
CH (OH) 2+H2O (R11)
HO2+HCOOH (R12)
H+ +HCOO (R13)
Photochemical reactions also lead to the formation of HO•2 from
hydroperoxide associated compounds which are typically released into the
atmosphere during pollution.34 Reaction of alkoxy radicals with O2 (R14) and
photolysis of formaldehyde (R15, R16) are the major sources of formation of HO2
during the daytime.
RCH2O + O2
RCHO + HO•2 (R14)
HCHO + hv
H• +HC•O
HC•O + O2
HO2 + CO
(R15)
(R16)
Henry’s Law
Numerous field studies have been done to show the presence of hydrogen
peroxide and other organic peroxides. The distribution of H2O2 between the gasphase and aerosol-phase is still under study.
15
Gas to water partitioning of H2O2 makes the peroxides enter into the
aqueous portion of the aerosols. The partitioning depends on the nature of the
species, which are either water soluble or water insoluble compounds. The uptake
of water soluble compounds is determined by the Henry’s law constant of the
species and its ability to dissociate in solution.41-43
So, hydroperoxides that are water soluble and partitioned between the gasphase and liquid water is given by the Henry’s law coefficient.42 Hydrogen
peroxide partitions strongly into the aqueous phase with a Henry’s law coefficient
of 1.0 x 105 M.atm-1. Henry’s law is given as
Xa = Pa x Ha
Where, Ha is Henry’s law coefficient for species ‘a’. Xa is aqueous
concentration for a species and Pa is partial pressure of species. This relation
predicts that the aqueous concentration of hydrogen peroxide in liquid water is in
equilibrium with 1ppb of H2O2 that is equivalent to 0.1mM.42
Estimation of particle phase ROS content based on gas-phase ROS can be
done using Henry’s law. Gas and particle-phase hydrogen peroxide were measured
and compared to Henry’s law based predictions. The Henry’s law predictions for
aqueous H2O2 levels are derived using measured gas-phase H2O2 multiplied with
Henry’s law coefficient of the species (Ha).
Evidence from the previous studies showed that particle phase peroxide
levels exceeded predictions by Henry’s law by a factor of about 300-700.41
Calculated concentrations of H2O2 for the aerosol liquid water are higher than
Henry’s law predictions, as the H2O2 dissociates rapidly between gas and liquid
phases. The exceeded levels of particle phase peroxide in aerosol liquid water is
thought to be due to the continuous production of peroxide in the extraction
solution by the particles during the particle dissolution process.45,46
16
Possible Explanations for Observed
Particle Phase H2O2
Aerosol hydroperoxide levels were observed to be at higher levels over gasphase partitioning of Henry’s law after extracting them into weakly acidic aqueous
solutions. Several sources responsible for elevated levels of H2O2 in aerosols are
described below.
Dissolution of H2O2 associated with the particles is one of the major
sources of H2O2. Measurements from UCLA indicated that the majority of H2O2
associated with ambient particles is generated by particles themselves, in aqueous
solutions and the measured levels exceeded those predicted by Henry’s law by two
orders of magnitude based on measured gas-phase H2O2 associated with ambient
mass and relative humidity.45 H2O2 concentrations tend to be lowered in cloud and
fog waters from their Henry’s law equilibria due to the oxidation of S (IV) species
by H2O2.2
Recent studies proved that inorganic salts, especially ammonium sulfate
and other salts in dissolved form, are known to enhance the solubility of H2O2 by a
factor of 2 to 3.25 Generation of H2O2 in cloud and fog water through
photochemical reactions based on radical chemistry is also thought to be one of
the possibilities for H2O2 production.34 Hydrogen peroxide is also produced by the
decomposition of aqueous hydroxyhydroperoxides along with corresponding
aldehyde.39,40
Particles contain redox active species, including transition metals, such as
iron or copper and organic compounds, such as quinones, which may be capable
of generating H2O2.36,37,47,49 The fraction of quinones that contributes to the H2O2
production depends on the availability of electron donors for redox cycling.
17
Redox Quinone Chemistry
Quinones in particulate matter play an important role due to the redox
chemistry that leads to ROS production24,30. The ability of these species to induce
such an effect is based on their capacity to accept electrons from biological
reductants and, in turn, donating the electrons to molecular oxygen (O2) to
generate a superoxide radical (O2.).The catalytic intermediate in this process is a
semiquinone radical anion species. Thus, quinones capable of participating in this
redox chemistry must be good oxidants to accept an electron from biological
reductants, and the corresponding semiquinone species must be good reductants to
efficiently reduce O2.
Several studies proposed the presence of hydroquinone (QH2) in the
quinone-catalyzed redox cycle50-52. QH2 undergoes auto oxidation with a quinone
(Q) to form a semiquinone (Q•‾ ) intermediate (R17). The semiquinone
intermediate reduces molecular oxygen to generate superoxide radical anion O2•‾
(R18).
QH2 +Q
2Q•‾ +2H+
Q•‾ +O2
Q + O2•‾
QH2 + O2•‾
QH•‾ +HO2• (R19)
QH•‾ + HO2•
Q•‾+ H2O2 (R20)
O2•‾ + O2•‾ +2H+
(R17)
(R18)
H2O2 +O2 (R21)
Spontaneous deprotonation of QH2 takes place when QH2 interacts with
superoxide radical anionO2•‾ (R19). The QH•‾formed is oxidized to generate the
semiquinone radical and hydrogen peroxide (R20). Superoxide radical anions
generated in R18 can react with another O2•‾ and two hydrogen ions to generate
hydrogen peroxide (R21). Figure 2 represents the quinone redox cycling reactions
that shows quinone-mediated H2O2 generation.
18
Figure 2. Quinone redox cycle reactions51
Redox Reactions of Transition Metals
Metals have the potential to catalyze reactions. Previous chemical and in
vitro studies reported in the literature have also shown the association between
ROS generation and specific metals by determining the sources, concentrations of
ROS and metals.46,47 A better correlation of ROS production with water soluble
metals was observed, when compared to total metals which have been consistent
in all the previous studies.23,57,58 Total metals constitute to about 7-13% of PM2.5
whereas water-soluble metals account for about 1-5% of PM2.5. Evidence from the
previous studies concluded that a number of water soluble transition metals may
potentially lead to the generation of ROS. Iron and copper tend to be the most
abundant transition metals found in aerosols in their dissolved and solid forms.
Other elements including Ca, V, Pb, Na, Ni, K, Mg, Mn and Se were not
significantly correlated with H2O2, due to their low concentrations in particles.57-59
One of the transition metals that has the capacity to generate H2O2 is copper
(Cu). Cu is known to efficiently convert HO2/OH radicals to H2O2 at a higher rate
when compared to Fe (II). Cu (I) and Cu (II), which are thought to be present in
19
the atmospheric waters and particles, are involved in the following reactions (R22,
R23). In an aqueous solution, reaction of Cu (I) with O2- can lead to the formation
of high OH/HO2 radical concentrations that result in continuous formation of
H2O2.
HO2 + Cu (II)
Cu (I) + O2- + H + (R22)
O2 - +Cu (I) +2H+
Cu (II) +H2O2
(R23)
A recent study by Charier et al. showed a good correlation between Cu and
formation of H2O2.57 Other studies by Chow et al. also reported average metal
concentrations of 208ng.m-3 for 24 h in fine PM.58 Another study by Singhs59
reported an average of about 13ng.m-3 which is less than the previous study.58
Removal of Peroxides from
Atmosphere
Hydrogen peroxide and organic peroxides are removed from the
atmosphere by photolysis, reaction with OH, physical decomposition to the
ground, and by rain out. The photolysis of H2O2 leads to the regeneration of OH
(R24) and the photolysis of organic peroxides (ROOH) leads to the formation of
OH and alkoxy radicals (R25). Hydro peroxides can also be lost by reaction with
OH radicals (R26 and R27) or by wet and dry deposition to the ground. Wet
deposition leads to the major loss of hydrogen peroxide.2
H2O2 + hv
2 •OH
ROOH + hv
RO• +.OH (R25)
OH+H2O2
H2O +HO•2 (R26)
•
OH +ROOH
(R24)
RO•2 +H2O (R27)
20
Research Objectives
Quantification of H2O2 in particle phase was studied. The correlation
between the particle composition and formation of H2O2 was identified
(specifically for quinones and transition metals). Also, the particle sources that are
involved in the formation of H2O2 was also observed.
Measurements
The primary objective of this work is to quantify the hydrogen peroxide
concentrations present in the PM2.5 filter samples, which are extracted into the
aqueous phase. The measurements made will quantify as well as identify the
source of hydrogen peroxide which will be compared with quinones and transition
metals measurements made at California State University, Fresno and UC Davis to
understand their role in ROS generation. The work presented in this thesis will
contribute to the overall objective of this study. The research questions that were
addressed through this study include the following:
1. What are the rates of formation of hydrogen peroxide in the particle
phase samples collected in Claremont and Fresno?
2. What are the temporal variations observed in between morning,
afternoon and overnight samples for specific Fresno and Claremont
samples?
3. Are PM2.5 mass loadings responsible for H2O2 formation?
4. Are transition metals involved in the formation of H2O2?
5. Are quinones involved in the formation of H2O2?
6. Where are the air masses that are responsible for formation of H2O2
coming from?
This study reports the average mass loadings of H2O2 and also gives a brief
idea of the sources of ROS and thus the role of quinones and metals in the
21
formation of H2O2. Also, the effect of diurnal and seasonal variations on the
production of H2O2 were examined.
EXPERIMENTAL
General Research Design
Particulate Matter samples were collected in Claremont and Fresno using a
Hi-Volume PM2.5 sampler on pre-washed Teflon filters. The filter extracts were
tested on HPLC at particular intervals of time to quantify the production of ROS
especially hydrogen peroxide in the PM2.5 filter samples.
A systematic procedure was followed to identify the presence of ROS and
their activity in PM: (1) collection of PM samples, (2) extraction of PM with
aqueous and organic solvents, (3) test for the presence of ROS, and (4) separation
of extracts. Each step is described briefly in further sections.
Sampling Locations
Sampling was carried out in Claremont for a period of 19 days between
July and August 2012. The rooftop of the Sprague Hall building at Harvey Mudd
College was used to set up the sampling instrumentation. Samples were collected
in morning (7 a.m.-1 p.m.), afternoon (1 p.m.-6 p.m.), and evening (6 p.m.7 a.m.).61 A portable meteorological station was used to obtain the meteorological
data that collected speed and direction of wind, relative humidity, and temperature.
Fresno, which is located in the center of the San Joaquin Valley (SJV), is
subjected to highest levels of particulate matter pollutions in California. Samples
were collected on the rooftop of the Industrial Technology building at California
State University, Fresno, during winter from January-February for a period of 3
weeks. The sampling times were similar to those of the Claremont study.
Figure 3 maps the sampling locations.
23
Figure 3. Regional overview of air quality sampling location sites at
Claremont[A], CA and Fresno[B], CA.61
Sample Collection
Hi-Volume PM2.5 Sampler
Atmospheric PM2.5 mass loadings were measured on Teflon coated-glass
filters (Tisch Environmental, Lot #102618003) with a pore size 0.45 µm and
260x300 mm dimensions using a Hi-Volume PM2.5 sampler (Tisch Environmental
24
TE-6001-2.5-I). Aluminum envelopes, which were rinsed with dichloromethane
and baked for 2 h, were used to seal the cleaned filters and stored at -20oC.61
A high-volume, size-selective PM2.5 inlet sampler with 40 impactor jets
(Tisch Environmental, TE-6070-2.5-HVS), shown in Figure 4, draws the ambient
air through the clean filter at a rate of 1.13 m3.min-1. Smaller particles of sizes less
than 2.5µm are collected onto the filter, whereas larger particles greater than
2.5µm are collected onto the oil-wetted surface using multiple impactors.
Collected filters were stored for 24 h in the controlled humidity and temperature
room prior to weighing. A mettler balance was used to weigh the mass
concentrations of the filters under controlled relative humidity (40-45%) and
temperature (22-24oC) conditions before and after sample collection. The filters
were frozen at -20oC until subsequent analyses were performed.61
Figure 4. Tisch Environmental TE-6070 hi-volume PM2.5 sampler65
25
Extraction Methods
Overview
Aerosol samples were analyzed for peroxides using a series of extraction
methods after the collection of filters. Extraction of aerosol samples into the
aqueous phase was the first step involved in sample preparation followed by the
analysis of H2O2 using high pressure liquid chromatography (HPLC). Fluorimetric
detection was used in sample analysis to identify the H2O2 concentrations in the
samples.
Sample Preparation
Filter samples of a particular size were cut and spiked with 2,2trifluoroethanol that acts as wetting agent (sigma-Aldrich,T63002 ≥ 99%). A
known volume of extraction solution, Di sodium ethylene diamine tetraacetic acid
(Na2-EDTA), was taken in a petri dish and the Teflon filters were inverted
individually with the exposed surface in contact with the extraction solution; the
petri dish was covered with a top. Filters were extracted for 24 h, with gentle
agitation and the extract was injected into HPLC from 0 min till 6 h and a final
injection was given at 24 h.
Extraction Solution Preparation
The mobile phase was prepared in a 1L volumetric flask by adding by
(1mM) of (Na2-EDTA) to distilled water. The obtained solution was acidified to a
pH of 2.5 using 1M sulfuric acid (H2SO4) and the final solution was made up with
distilled water.
26
Preparation of Fluorescent Reagent
Fluorescent reagent, used to detect peroxides in the sample solutions, was
prepared using 26mM para-hydroxy phenyl acetic acid(POHPAA) and 0.5 M
potassium hydrogen phthalate in distilled water. The solution mixture was heated
and pH was adjusted to 5.8 using sodium hydroxide (NaOH).100 units/mL of type
II horse radish peroxidase was added to solution mix and the volume was made up
to 100ml using distilled water and stored in refrigerator (4oC) until used.
Organic Extraction Using
Dichloromethanol (DCM) and
Residual Filter Extraction
To the Teflon filter, 2, 2, 2 tri fluoro ethanol was added as a wetting agent
followed by Dichloromethanol (DCM). The filter was removed from DCM after
certain period of time and DCM was evaporated. Four milliliters of extraction
solution was added to the residual filter and also to the DCM evaporated petri
dish, which was expected to contain DCM soluble organic species. Both the
solutions were injected in to HPLC up to 24 h. Organic extractions were done for a
subset of filters including Fresno filters 10, 11, and 12 and Claremont filters 13,
14, and 15.
Solid Phase Extraction (SPE)
Solid phase extraction column (Cole Parmer T-10937-15) C18 of 6ml
[6.5(L) x 10 (diameter) in cm] was used for the separation of non-polar organic
species like quinones. The organics that are adsorbed on to the sorbent bed are
then released from the SPE media using a solvent that dissolves the organics. A
systematic procedure was followed during the usage of SPE cartridge. The sorbent
bed was conditioned using a suitable solvent like methanol, which rinses away all
the impurities on the sorbent bed. The aqueous extract of the sample was allowed
27
to pass through SPE, which allows the adsorption of the organics on to the sorbent
bed. The aqueous solvent has less affinity for the analyte compared to that of SPE
support material. A final elution was done with a solvent that has a strong affinity
for analyte (DCM) to release the analyte from the support.
Testing of Reverse Phase Column
The ability of the solid phase extraction column to adsorb the organics on
to the adsorbent bed was determined by using UV-Visible spectrometer. An
aqueous standard solution of quinones was prepared by dissolving a known
amount of quinones to 15% of 95% ethanol and the solution was made up to
volume using distilled water in a 100 ml volumetric flask. The peak intensities for
pre- and post-solid phase extraction of the quinones in the aqueous standard was
observed and compared. Water was used as blank. The pre-SPE peak intensities
were much higher than the post-SPE peak intensities, which indicates an effective
adsorption of quinones by the SPE column. The SPE bed was then washed with
DCM and the resultant solution shows an increase in peak intensity for quinones at
a particular wavelength.
To Check the Effect of Quinones on
the Production of ROS
To the Teflon filter, 2, 2, 2 tri fluoro ethanol was added as a wetting agent
followed by extraction solution. The filter was allowed to stay in contact with the
extraction solution for certain periods of time. The solution was injected into
HPLC until 24 h to check the production rates of H2O2, after the removal of
quinones using SPE column. The DCM extract of quinones was tested for the
presence of quinones using gas chromatography associated with mass
28
spectrometry (GC-MS). Trial filters and Fresno filter 11 were tested to find the
effect of quinones on ROS production.
Instrumentation
Fluorimetric Analysis of H2O2 by
HPLC
PM extracts were tested for the presence of ROS using post-column
fluorescence method.13 The HPLC unit consists of a peristaltic pump (Rainin,
Dynamax Model RP-1), a 250 mm (Length) x 4.6 mm (Internal diameter) hypersil
ODS-2 C18 stationary phase reverse phase analytical column (Thermo Scientific),
An injection valve (Rheodyne 7125), spectrofluorometric detector (Shimadzu RF10AXL), and an isocratic pump (Shimadzu LC-10ADvp).
Hydroperoxides are detected via a post-column fluorimetric method. The
mobile phase is the same as extraction solution used in the extraction of aerosols
from Teflon filters. Sample is injected into the system through an injection valve
attached to a 20-µL sample loop. When the injection valve lever was moved to an
injection mode, the mobile phase was directed to the sample loop to push the
sample towards the reverse phase column. The reverse phase column separates
hydroperoxides by polarity where the most polar species elutes first which is
hydrogen peroxide. The fluorescence reagent was delivered at a rate of
0.06ml/min by peristaltic pump. The mixture is then forced through 50 cm of 0.02inch internal diameter tubing that was coiled into the Serpentine II configuration
which increases the mixing time between peroxides and fluorescent reagent.
As the sample reaction mixture passes through the analytical column, the
ROS present in the sample gets separated and is oxidized selectively by
horseradish peroxidase, which in turn abstracts an electron from para hydroxyl
29
phenyl acetic acid (POHPAA) molecule to generate a radical. The POHPAA
radical reacts with another POPHAA (component of fluorescence detector) to
form a dimer (R30). Horseradish peroxidase enzyme catalyzes a stoichiometric
reaction between hydroperoxides and POHPAA, resulting in quantitative
conversion of H2O2 to POHPAA dimer. The obtained dimer fluoresces only in the
presence of a base which is added to the system using the same peristaltic pump at
the rate of 0.06 mL/min. The fluorescence can be identified using fluorescence
detector (Figure 5).
CH2COOH
CH2COOH
+
2
OH
CH2COOH
+ 2 H2O
H2O2
OH
OH
(R30)
Figure 5. High Performance Liquid Chromatography with post-column derivation
and fluorescence detection instrument.63
30
Finally, the solution was sent through the fluorescence detector where a
Xenon (Xe) lamp was set to 320 nm for excitation and 400 nm for the emission
which was detected with a photomultiplier tube. A computer that was connected
with fluorescence detector records the voltage as signal in a chromatogram of mV
versus retention time, where peaks correspond to peroxide detection. The output
signal was then recorded and analyzed using CHROMPERFECT software.
Calibration of HPLC
The analytical response of hydrogen peroxide is determined by the ability
of column to quantitatively pass the hydroperoxides and also ability of the enzyme
reaction to quantitatively convert all the hydroperoxyl groups to the fluorescent
product. The samples can be compared with the calibrated solutions if both the
parameters are nearly unity. Additionally, titrimetric methods were used to
standardize and calibrate pure solutions of hydrogen peroxide
Quantification of H2O2 to pass through HPLC column is measured by
operating the analytical system with the column in place and determining the
response for H2O2. The column is then removed and the response is again
measured. The ratio of these two gives the column recovery efficiency. The
column efficiency for the used column was nearly unity which is 1.05.
H2O2 Standards Used in Calibrations
Redox titration was performed to determine the accurate concentrations of
standard H2O2. Hydrogen peroxide stock solutions from three different laboratory
suppliers (Sigma-Aldrich, Fischer, and Macron) were standardized to choose a
better stock solution with approximately 30% (w/v) concentration. Redox
titrations were used to determine H2O2 concentrations in all the three laboratory
suppliers of 30% (w/v). The titration procedure is as follows; to a clean 250ml
31
Erlenmeyer flask, 25ml of water, 5ml of 6M sulfuric acid (H2SO4) and 1ml of 30%
(w/v) Hydrogen peroxide (H2O2) was added and swirled to mix. Sulfuric acid
solution was used to provide an acidic environment for oxidation-reduction
reaction to occur. Potassium permanganate (KMnO4, 0.098M) was used as titrant
and was added drop-wise using a volumetric burette. The permanganate in KMnO4
solution acts as its own indictor and solution turns from colorless to pale pink near
the equivalence point.
A primary H2O2 solution is made by diluting 100µl of standard stock
solution to 100mL of water, which gives a H2O2 of concentration of 10-3 M. H2O2
standard solution for each supplier is then made by diluting 1000,100 and 10 µL of
primary H2O2 solution to 100mL of water yielding a concentration range of
9.8x10-5 to 9.8x10-7 M. The dilutions for Fischer stock solution is prepared by
adding 2,3,4 and 5mL of water to 1mL of primary H2O2 solution to get the
concentrations of 1.9-4.9x10-5M. Each H2O2 standard is run for a minimum of
three times and the generated fluorescence signals are recorded. The average peak
area per H2O2 standard is plotted against H2O2 concentration. The peak area of
each signal is found through CHROMPERFECT assisted integration.
Flow Rate of Pump
Flow accuracy is checked at mL/min, with the column in place, by
measuring the time required to fill a 20 mL measuring cylinder from the detector
outlet. Water is used as a solvent to check the flow rate of the pump.
Calibration Using a Correlation Factor
The principle is to establish a linear calibration response. A single standard
concentration run can be used to calculate correlation factor, and thus can be
applied to all sample peak areas to obtain concentration values. To use this
32
method, it is essential to confirm linearity by running a series of dilutions which
must include a zero blank. Thereafter, it is necessary only to run the single
standard periodically during the sequence to confirm that the correlation factor
remains constant. Upon subsequent computation, if the detector gives a linear
response to concentration, we get a straight line.
Mechanical aspects affecting performance and sensitivity were also
examined. The pressure with which the eluent is flown into the system was also
checked in the presence of column. In addition to mechanical aspects, the effect of
extraction solution pH on H2O2 production was also observed. Deviation in the
pressure, flow rate, and eluent pH did not affect the performance of the HPLC,
except for a slight change in the signal.
Sample Derivatization
Sample derivatization method allows more sensitive transformation of
higher volatile quinones to be detected by GC/MS analysis. Cho et al. described
derivatization process in his study, to enhance the signals within the GC-MS for
selected quinones including 1, 4-chrysenequinone, phenanthraquinone, 1, 2 naphthoquinone, 1, 4-naphthoquinone. A certain amount of concentrated sample
was transferred into a vial with 0.2mL of acetic anhydride and 0.1g zinc. The
contents of the vial were sealed, mixed and incubated at 80oC for three 5-min
intervals. The contents in the vial were vented, mixed and returned to the dry bath
incubator. After the 15-min heating, a second portion of zinc was added and the
same procedure was followed. After the final heating, the vials were allowed to
cool to room temperature and 0.5mL of deionized water and 3mL of pentane was
added. The contents were mixed and allowed to settle for 10 min before taking the
top pentane layer for GC-MS analysis.
33
GC/MS
An Agilent 6890 plus series with a Hewlett Packard 5973 mass selective
detector was used to analyze the quinones that are responsible for H2O2
production. A GC column of measurements 30mx250µmx0.25µm made of HP5MS 5% Phenyl methyl siloxane capillary column (Model no: HP 19091S-433)
was used. The data were analyzed using Chem station software. The modified GC
has a programmable temperature vaporization (PTV) inlet technique that is used
for large volume injections has many advantages over traditional split/splitless
inlet. The injection volume can be 60µl or higher for PTV inlet, which increases
the analytical sensitivity for low concentrations with higher volumes in
comparison to 2-5µl for split/splitless inlet. The programmable temperature
control system of a PTV inlet consists of a heating coil and a cooling jacket that
uses liquid CO2 as coolants. The dimensions of a vaporizing chamber determine
the maximum volume of each injection and are limited by the transfer of sample to
the capillary column. The GC-Ms was modified from split/splitless inlet system to
a programmed temperature vaporizing inlet which allows the introduction of high
volume samples which in turn increases the sensitivity.
The sample introduction starts with a high flow of Helium (He) carrier gas
at the rate of 1.0 ml/min. The samples were injected into the solvent vent inlet, set
at 40oC and cooled with a CO2 cryogenic trap system that was set at a pressure of
7.62 psi. The temperature is adjusted below the solvent boiling point that allows
the maximum retention of the analyte inside the liner by solvent trapping, and the
majority of the solvent in the sample is released via a split exit. Multiple injections
with appropriate time intervals between the injections is done for the injected
solvent to evaporate. After a sufficient amount of sample is injected and solvent
venting is complete, the split exit is closed and the injector temperature is rapidly
34
increased at 300oC/min to a final inlet of 300oC that initiates a splitless transfer of
the sample to the GC column. Non-volatile matrix constituents tend to remain
inside the liner and are unlikely to enter and contaminate GC column. After the
sample transfer, the inlet temperature can be kept high to bake off the retained
substances with a high split flow. The oven temperature is set at 50oC and held for
4 min then ramped 5oC/min over a period of 39 min until 310oC is reached. The
total run time was 51 min for quinones.
Underivatized and derivatized quinones were analyzed using two different
selective ion monitoring methods (SIM). SIM allows the mass spectrometer to
detect specific compounds with very high sensitivity and it also isolates and
identifies molecular ions that possess selected mass fragments with monitored
fragmentation patterns (M+, M-CO+ and M-2CO+) for underivatized samples and
(M-CH2CO+ and M-2CH2CO+) for derivatized samples. SIM mode detects the
masses of specific molecular ions at trace levels in comparison to a wide range of
masses in full scan mode, where selectivity is not active.
Hybrid Single Particle Lagrangian
Integrated Trajectory Model
(HYSPLIT)
The HYSPLIT model, developed by the U.S. National Oceanic and
Atmospheric Administration (NOAA) and Australia’s Bureau of Meteorology, is a
system that is used to estimate dispersion and deposition of particulate pollutants.
The model is used to compute air parcel trajectories from source location using the
meteorological data. The model uses a Lagrangian solution of advection and
diffusion equation as a transport model for chemicals to identify the air parcel
trajectories within a given area. Chemical species can be simulated into this model
35
and the concentrations of pollutants at different locations can be determined at a
particular point of time.2
RESULTS
Hydrogen Peroxide Calibration
Hydrogen peroxide from three different suppliers (Macron, Fischer and
Sigma-Aldrich) was used to build a suitable and perfect calibration curve of the
standard as shown in Figure 6. Calibrations produced were used to determine
fluorimetric response of H2O2 in analyzed samples and also to monitor its
performance. The calibration curve was constructed for all the three stock
solutions ranging using the results obtained from the titrimetric analysis.
Figure 6. Calibration curve of H2O2 for Macron, Fischer and Sigma-Aldrich
The average peak area per H2O2 standard is plotted against H2O2
concentration as shown in the Figure 6.The linear fit indicates a strong correlation
(R2 >0.9) between peak area and H2O2 concentration. Table 2 represents the
calibration response curve plot statistics for Figure 6.
37
Table 2. H2O2 Calibration Data for Different Lab Suppliers
H2O2 supplier
Intercept
Slope
R2
Macron
7.7E+05
6.9E+10
0.96
Fischer
1.9E+05
7.0E+10
0.94
Sigma-Aldrich
2.1E+03
7.7E+10
1
Production Rates of H2O2 for the Trial Filters
A series of experiments were performed on the trial filters (Fresno 1, 2, 3).
Trial filters were collected during the first day of the collection campaign and
were not used for analysis along with the other filter samples. The air flow rate
through the instrument during the first day of collection was in appropriate due to
the power problems and instrumental settings that may alter the air mass collected
on to the filters. Numerous trials were performed on each filter with different
variations to give a brief idea of the tests to be performed on the filter samples.
The formation rates of hydrogen peroxide were examined for trial filters
among all three sampling periods (morning, afternoon, and overnight) as
represented in Figure 7. Initial measurements of H2O2 with in the first 6 h were
used to understand the rate of H2O2 formation using a linear fit. The slope of the
linear fit represents the rate of H2O2 formation per hour. The initial formation rates
of H2O2 were observed to be (2.9± 1.9) ng.m-3.hr-1, (2.7± 2.9) ng.m-3.hr-1, and (1.1
±0.6) ng.m-3hr-1 for afternoon, morning, and overnight samples respectively which
are represented as with EDTA in Figure 8. The uncertainties represent the standard
deviation for the respective sampling periods.
38
Figure 7. Production rates of H2O2 per hour for the trial filters
Figure 8. H2O2 Production rates under variable conditions for Fs-02
39
Figure 8 represents the rate of production of H2O2 for the Fs-02 (afternoon)
filter under variable conditions using a linear fit. The rate of formation of H2O2 in
the absence of quinones is found to be increasing linearly for several hours and the
production rate is observed to be (1.8± 2.9) ng.m-3hr-1. The quinones are removed
from the extraction solution by using a solid phase extraction column (SPE).
The rates of H2O2 formation are observed to be (-0.1 ±0.7) ng.m-3 hr-1 and
(1.0 ±2.5) ng.m-3hr-1 in the absence and presence of filter in the extraction solution
respectively.
Figure 9 represents the average production rate of H2O2 over 6 h under
variable conditions. The error bars represents the standard deviation. The
production rates of H2O2 in the presence of EDTA ranged in between (5.8± 3.2)
ng.m-3hr-1 to (11.7± 7.4) ng.m-3hr-1 in between the sampling periods. The
production rates for morning and afternoon filters are close to each other with
relatively no statistical significance(p=0.38) between the samples.
SPE in Figure 9 indicates solid phase extraction or the removal of quinones
from the extraction solution. The production rates ranged in between (7.6± 4.7)
ng.m-3 to (9.7± 6.5) ng.m-3 for the morning and afternoon filters. The production
rates are found to be statistically insignificant between morning and afternoon
(p=0.33) with the morning production rates very close to the afternoon.
The average production rates of H2O2 are found to be in the range of (0.1±
0.3) ng.m-3hr-1 to (0.3± 0.6) ng.m-3hr-1 in the absence of filter and (7.8± 2.8) ng.m3
hr-1 to ( 5.5± 1.9) ng.m-3hr-1,when the filter is back in to the extraction solution, as
observed form Figure 8. The statistical significance was found to be relatively
high (p<0.05) in the presence and absence of filter in extraction solution.
40
Figure 9. Differences in the production of H2O2 under variable conditions for
Fresno filters 1 and 2.
The statistical analysis for the Figure 9 shows that the average H2O2
production rates for the Fs-01 and Fs-02 remains unchanged with EDTA, without
quinones (represented as SPE in Figure 9) and for the filter back in the extraction
solution after 2 h. The statistical difference between the three tests (with EDTA,
without quinones and filter back into extraction solution after 2 h) are found to be
(p>0.05), for both the morning and afternoon filters which indicates a relatively
low statistical significant difference in between the tests.
Production Rates of H2O2 for Fresno Samples:
Fresno Filter 11
Numerous trials have been conducted on Fresno filter 11, in triplicates, to
explore the possible source of H2O2. Figure 10 shows the production rates of
hydrogen peroxide for 6 h under variable conditions. The rate of H2O2 production
41
varies under different experimental conditions. The error bar indicates the
statistical error for each test.
Figure 10. Production rates of H2O2 under variable conditions for Fs-11
The production rates of hydrogen peroxide in the presence of EDTA was
found to be (5.4 ± 0.7) and (4.2± 3.1) in the absence of EDTA. The statistical
analysis indicates that the production rates of H2O2 for Fresno filter 11 (afternoon)
with and without EDTA are statistically insignificant (p=0.18) as observed from ttest. The observation implies that the presence or absence of EDTA in the
extraction solution has no effect on the production of H2O2. The metals, if present
in the filter extract, are thought to chelate with EDTA of extraction solution,
which further dissociates H2O2 to hydroxyl radicals leading to a decreased H2O2
content in the samples16. The metals, if present in the extraction solution, are also
thought to generate higher levels of H2O246,47. But the results obtained showed no
42
statistical difference in the presence and absence of EDTA in the extraction
solution.
SPE in Figure 10 represents the average H2O2 production rate (6.2± 3.9)
ng.m-3hr-1 in the absence of quinones. This shows that EDTA, removal of quinones
by SPE, and the filter back into the extraction solution after 2 h have no overall
effect on the production rates of H2O2. A statistical t-test was also performed in
between the tests, (with EDTA, without quinones, filter back into extraction
solution after 2 h) which showed no statistically significant difference( p>0.05).
The production rates of H2O2 over 6 h for organic wash and residual
aqueous filter extract were found to be (2.7± 1.0) ng.m-3hr-1 and (0.2± 0.1)
ng.m-3hr-1 respectively. A relatively high statistically significant difference
(p=0.013) was observed in between organic wash and residual aqueous filter
extract.
Production Rates of H2O2 for Other
Fresno Filter Samples
Figure 11 represents the average mass loadings of H2O2 for the Fresno
samples that were collected from 1/16/13 to 1/19/13. Each bar representsts the
average H2O2 mass loadings of a specific sample period in a day
(morning,afternoon,overnight). Figure 12 represents weighed average of the three
samples (morning,afternoon and overnight) per day. The error bars indicate the
standard deviation. The rate of formation of H2O2 ranged in between (2.6±1.5)
ng.m-3 to (15.7±11.2) ng.m-3.hr-1 from 16 to 19 January.
43
Figure 11. Rate of formation of H2O2 for Fresno samples grouped into morning,
afternoon, and overnight samples
Figure 12. Average production rates of H2O2 for the filters collected from 16 to 19
January 2013
44
Table 3 represents the collection details of the Fresno samples which
includes the sampling dates of the filters along with their respective collection
periods (morning, afternoon and overnight). Table 3 represents the average
production rates of H2O2 from respective filter samples in ng/m3.hr-1 and
particulate mass loadings in µg/m3
Table 3. Collection Details of Fresno Filters
Date of
collection
15-Jan
16-Jan
17-Jan
18-Jan
19-Jan
Filter
Collected
period
Formation rates
of H2O2(ng/m3.
hr-1)
PM2.5 Mass
loadings (µg/m3)
FS13F-1
Morning
11.93
-
FS13F-2
Afternoon
17.26
-
FS13F-3
Overnight
9.24
-
FS13F-4
Morning
5.34
16.96
FS13F-5
Afternoon
5.76
20.38
FS13F-6
Overnight
3.34
15.15
FS13F-7
Morning
5.68
26.09
FS13F-8
Afternoon
6.91
17.92
FS13F-9
Overnight
2.79
16.72
FS13F-10
Morning
2.60
22.83
FS13F-11
Afternoon
15.73
24.29
FS13F-12
Overnight
3.58
19.59
FS13F-13
Morning
11.29
28.05
FS13F-14
Afternoon
10.85
27.41
FS13F-15
Overnight
4.52
24.97
45
Production Rates of H2O2 for Claremont Filters
H2O2 measurements have been studied for some of the Claremont samples
which were collected for a period of 19 days during summer from July-August of
2012. The mass loadings for the Claremont filters are described in Table 4.
Figure 13 represents the mass loadings of specific Claremont filters for
each of the sampling period (morning, afternoon, and overnight). The error bars
represent standard deviation calculated individually for each sample. The mass
loadings of H2O2 ranged from (2.0±1.4) ng.m-3 to (12.7± 10.9) ng.m-3.
Figure 13. Rate of formation of H2O2 for Claremont filters
H2O2 measurements have been studied for some of the Claremont samples
which were collected for a period of 19 days during summer from July-August of
2012. The mass loadings for the Claremont filters are described in Table 4.
46
Table 4. Collection Data for Claremont Filters
Date
collected
filter
Time period
Formation rates of
H2O2(ng/m3.hr-1)
PM2.5 Mass
loadings(µg/m3)
26-Jul
CLMT12F-01
Morning
7.25
12.75
CLMT12F-02
Afternoon
7.28
16.59
CLMT12F-03
Over night
3.49
14.27
CLMT12F-04
Morning
4.83
12.81
CLMT12F-05
Afternoon
6.02
11.33
CLMT12F-06
Over night
3.16
8.70
CLMT12F-07
Morning
4.96
16.58
CLMT12F-08
Afternoon
2.99
9.77
CLMT12F-09
Over night
2.01
8.10
CLMT12F-13
Morning
12.74
12.49
CLMT12F-14
Afternoon
8.51
13.36
CLMT12F-15
Over night
9.17
11.88
CLMT12F-28
Morning
3.40
14.79
CLMT12F-29
Afternoon
3.71
12.79
CLMT12F-30
Over night
1.66
12.62
CLMT12F-43
Morning
4.75
16.06
CLMT12F-44
Afternoon
4.68
17.91
CLMT12F-45
Over night
3.48
12.86
CLMT12F-46
Morning
4.76
17.49
CLMT12F-47
Afternoon
4.53
19.70
CLMT12F-48
Over night
5.85
7.66
27-Jul
28-Jul
30-Jul
4-Aug
9-Aug
10-Aug
47
Rate of H2O2 Formation in Organic
Extracts and Residual Filter
Extracts for Specific Filter
Samples
Figures 14 and 15 represent the production rates of H2O2 and the statistical
differences under certain conditions for specific Fresno and Claremont samples,
respectively. Organic wash in both the figures represents the DCM
(dichloromethane) extract of the ROS.
Figure 14. Rate of formation of H2O2 for aqueous, organic and residual filter
extracts for specific Fresno samples
The average H2O2 production rate over 6 h for the Fresno filter, which was
collected on 1/18/13 was observed to be (2.9 ±2.0) ng.m-3hr-1 in the organic wash.
The weighed average production rates of H2O2 for the residual ROS in the aqueous
extract is found to be (1.6 ±0.6) ng.m-3hr-1. The H2O2 production rates for the
48
Figure 15. H2O2 variations for aqueous, organic, and residual filter extract for
specific Fresno samples
organic wash are found to be statistically significant in between morning and
afternoon and overnight samples (p<0.05). From the data, it can be observed that
afternoon samples have the highest production rates for both organic wash and
residual filter extracts for the Fresno samples.
The variations for organic extracts, residual aqueous extracts, and aqueous
extracts are observed for the Claremont filter that was collected on 7/30/12. The
average production rate of H2O2 for organic wash was found to be (3.5 ±1.7) ng.m3
hr-1 with a relatively high statistical significant difference observed in between the
morning, afternoon and overnight samples (p<0.05). The production rates for ROS
residual extract was found to be (2.5±1.0) ng.m-3hr-1 with relatively less or no
statistical difference between the morning and afternoon samples, afternoon and
overnight samples ( p>0.05). A relatively high statistical difference was observed
between morning and overnight samples (p=0.014). The error bars represent the
standard deviation.
DISCUSSION
Ambient Mass Loadings
Hydrogen peroxide levels ranged from 2.8 to 17.8 ng.m-3 in Fresno and 2 to
12.7 ng.m-3 in Claremont. The average production rates of H2O2 are found to be
7.8± 4.7 ng.m-3.hr-1 for Fresno samples 5.2± 2.6 ng.m-3.hr-1 for Claremont samples.
Figure 16 represents the temporal variations in the production of H2O2 for specific
Fresno and Claremont samples. The error bars represent the standard deviation.
The statistical analysis for the average rate of formation of H2O2 in between
Fresno and Claremont samples showed a relatively less or no statistical difference
(p=0.105), which indicates that average mass loadings of H2O2 for both the
samples are similar in same order of magnitude.
Figure 16. Variation between Fresno and Claremont samples
The average mass loadings of H2O2 were equivalent with few other studies
which reported the H2O2 levels in ng/m-3. Arellanes et al.41 reported H2O2
50
concentrations ranging from 4 to 8 ng. m-3. Hasson and Paulson et al.30 observed
even lower H2O2 levels with an average of 3.2ng.m-3. The obtained results in this
study are found to be lesser than those of Taipei, Hung, and Wang36 with an
average of 21 ng.m-3 and Venkatachari et al.37, who reported an average of
243ng.m-3 in Rubidoux. The extraction time was found to be 2 to 3 h for all the
previous measurements.
Figure 17 illustrates the temporal variations in the average H2O2 mass
loadings for the specific Fresno filter samples that were collected during the period
(1/15/13-1/19/13). The filters were grouped to their respective sampling periods to
morning, afternoon, and overnight.
From Figure 17, it can be observed that the average H2O2 formation rates
for Fresno were higher in afternoon samples (p=0.017) when compared to the
overnight samples. The formation rates of H2O2 for morning samples are very
close to the afternoon samples with relatively less or no statistical significant
difference (p=0.184). The overnight H2O2 production rates are slightly lower than
the morning samples (p=0.097).
Figure 18 represents the temporal variations for specific Claremont
samples. Each bar represents a weighed average of the three samples (morning,
afternoon, and overnight) per day.The error bars indicate the standard deviation of
the formation rates of H2O2. The average mass loadings of H2O2 are statistically
insignificant ( p>0.05) in between the sampling periods (morning, afternoon, and
overnight), but a relatively high statistical difference is observed between morning
and overnight samples (p=0.020).
51
Figure 17. Temporal variations of H2O2 formation rates for specific Fresno
samples
Figure 18. Temporal variation of mass loadings for Claremont filters
52
From the data, it can be observed that the average H2O2 mass loadings for
Fresno samples are higher in afternoon, which are closely followed by morning
samples. The production rates of H2O2 in Claremont are highest in the morning
followed by afternoon samples with no statistical significance in between the two
sampling periods.
The diurnal results obtained were consistent with the results reported by a
similar study in Rubidoux37, which measured the concentrations of ROS during
different time intervals of a day. The observations concluded that, with the
increased ozone concentrations, the rate of production of ROS increased during
the early afternoon period (12-3 p.m.). The intensity of photochemical reactions is
found to be highest during the afternoon. Another study conducted at Taipei36
reported that concentration of photchemical reactions is the key factor that affects
the ROS production.
The night time production rates of H2O2 are lower than the day time. The
increased activity of H2O2 in the afternoon for the Fresno filters might be due to
reactivity of chemicals in the assay, which are formed photochemically. The
particulate emissions may not be uniform throughout the day and the higher
production rates of H2O2 in the morning for the Claremont filters might be due to
the vehicular emissions during the rush hour, which generate chemicals that lead
to the production of H2O2. Although there is no statistical significance between
morning and afternoon samples, the pattern of temporal variation suggests that
photo chemically generated compounds are one of the main sources of ROS and
the results obtained are consistent with the previous studies.36,37 Further studies are
needed to find the origins and also the sources that are responsible for H2O2
production.
53
The SPE results (removal of quinones) indicates that there exists no
difference in the production rates of H2O2 in the presence and absence of
quinones, which might be due to the oxidation of organic aerosol within the
particles that increase the water solubility and number of polar functional groups
and leads to H2O2 dissolution in water. The H2O2 production rate from residual
filter is found to be lesser than organic extract due to the removal of organic
species by DCM. The production of ROS from residual filter may be due to water
soluble and non-volatile organic species left over on the filter.
Parallel Studies
Correlation Between Particle Mass
and H2O2 Production
Parallel studies were conducted by a UCLA group in order to find the
ambient PM2.5 mass loadings for both Fresno and Claremont samples. Correlation
between the ambient PM2.5 mass loadings and H2O2 formation rates in µg/m3 were
observed for both the locations. Figure 19 and Figure 20 represent the correlation
between PM2.5 loadings and H2O2 mass loadings for Fresno and Claremont
samples, respectively. Table 5 represents the statistical data for the correlation
between PM2.5 loadings and H2O2 formation for Fresno and Claremont samples.
From the data, it can be observed that H2O2 generation for both Fresno and
Claremont samples showed no significant correlation with PM2.5 mass loadings
(p>0.05). The linear fit of Figures 19 and 20 implies that particle mass is a weak
indicator of aerosol-phase H2O2 and the chemical composition of particulate
matter,chemical reactions within the particles play a major role in the formation of
H2O2 than the particle mass. The correlation results obtained were not consistent
with the previous studies like Arellanes et al.,41which showed a significant positive
54
Figure 19. Correlation between PM2.5 Particle mass and H2O2 mass loadings in
(µg/m3) for Fresno filters
Figure 20. Correlation between PM mass loadings and H2O2 mass loadings in
(µg/m3) for Claremont filters.
55
Table 5. Statistical Data for Correlation Between PM 2.5 Mass Loadings and
H2O2 Formation
Correlations
between PM2.5
and H2O2 Mass
loadings for
Intercept
Standard
error
Slope
Standard
error
R2
P-value
Fresno
0.0093
±0.0078
-8.25E-05 ±0.00035
0.0053
0.821
Claremont
0.0046
±0.0026
2.87E-05 ±0.00019
0.0013
0.883
correlation between PM2.5 mass loadings and H2O2 production. This might be due
to season, temperature of the sampling period and loacation of sampling
(Riverside,CA), where the aged, fresh aersols and secondary organic aerosols are
emitted from nearby industries and dairy farms. Also, particles originating form
Los Angeles are thought to travel to Riverside. As the particles travel, their
physical and chemical properties alter depending on the regional meteorological
conditions, photochemical activity and the presence of other gas-phase pollutants
present.
Role of Quinones and Metals
One of the major aims of this study is to identify the role of quinones and
transition metals in the formation of H2O2. To answer objectives 4 and 5 (see p.
20), a correlation was performed between H2O2 and quinones, transition metals.
Correlation with Quinones
Parallel studies were conducted in California State University, Fresno on
the Fresno filter extracts in order to identify the role of quinones in the formation
of ROS. The concentrations of quinones in Claremont filters were very less, so it
was difficult to identify the relationship between the quinones and the rate of
formation of H2O2 in Claremont samples.
56
Filter extracts were extracted in to the surrogate lung fluid and the residual
organics on the filter medium were extracted in to the organic solvent. SLF is an
aqueous, buffered extract solution prepared by adding 114mM of sodium chloride,
7.8mM of Disodium phosphate and 2.2mM of Potassium Dihydrogen phosphate to
deionized water.
Figure 21 represents the determination of correlation between the average
mass loadings of H2O2 for each sample period plotted against the respective
quinone mass loading averaged for the same time for the Fresno samples. A linear
regression analysis was performed to identify the correlation between H2O2 and
quinones. Table 6 represents the statistical data, results, and the associated
correlation.
Table 6 represents the correlation of H2O2 with phenanthraquinone (PQ)
(p=0.057) and anthraquinone (AQ) (p=0.34). The data from Table 6 imply that
there exists no correlation between rate of production of H2O2 and anthraquinone
but, a partial correlation is observed between phenanthraquinone and H2O2
production.
Table 6. Statistical Data for the Correlation Between H2O2 Formation and Specific
Quinones
Intercept
Standard
error
Slope
Standard
error
R2
Pvalue
H2O2 Vs
Phenanthraquinone
5.76
±1.59
2.48
±1.17
0.29
0.057
H2O2 Vs
Anthraquinone
8.51
±1.42
-8.84
±9.10
0.067
0.34
Correlations observed
between
The results obtained in this study showed that the removal of quinones
using a solid phase extraction column (SPE) does not affect the rate of production
of H2O2, which implies that quinones are not responsible for the production of
57
Figure 21. Correlation between H2O2 against anthraquinone and
phenanthraquinone
58
H2O2. The partial correlation of PQ against the production of H2O2 may not prove
that PQ is responsible for generating ROS. PQ, which is found in the particle
phase of the ambient air, is thought to be emitted directly by vehicular exhaust and
is mostly formed in the atmosphere by photochemical reactions of parent
polycyclic aromatic hydrocarbons (PAHs). Wang and co-workers53 reported that
the formation of 9, 10-phenanthraquinone by the oxidation of phenanthrene occurs
during the day when OH radical initiation is prominent.
Correlation with Metals
Parallel studies were conducted at University of California, Davis, which
measured the average metal concentrations for the Fresno and Claremont filter
extracts using ICP-MS. The obtained Cu concentrations were compared against
the mass loadings of H2O2 performed at California State University, Fresno to test
the relationship between them.
At UC Davis, transition metals in PM samples were measured using
inductively coupled plasma mass spectrometer (ICP-MS). Also, colleagues at UC
Davis were only able to measure copper accurately, but not other transition metals
due to the interference from the chemical species present in the SLF. The average
concentrations of Cu obtained were plotted against the mass loadings of the H2O2
obtained. Figure 22 represents the correlation determinations between the H2O2
and respective average copper concentrations for Fresno samples and Figure 23
represents the correlation determinations between rate of formation of H2O2 and
Cu concentrations for Claremont samples.
59
Figure 22. Correlation between the average copper concentration and rate of
formation of H2O2 for Fresno samples
Figure 23. Correlation between H2O2 production rates and average copper mass
loadings for Claremont samples
60
The average copper concentrations for each sampling period were plotted
against the respective H2O2 formation rates that were averaged for the same time.
The p-value for rate of formation of H2O2 against the Cu concentrations for Fresno
(0.12) and Claremont (0.51) samples indicates that there exists no correlation
between the Cu concentration and rate of formation of H2O2.
The correlation results observed between Cu and H2O2 are inconsistent to
the results reported in the previous studies. The lack of correlation between the
two does not rule out the fact that Cu may not be responsible for the production of
H2O2. Cu has been shown to be capable of converting free radicals (HO2/OH) to
H2O2 and thus increases the formation rate of H2O2. Arellanes et al.33 showed that a
strong correlation exists between H2O2 generation and Cu in the fine PM, but also
reported a possibility of metal contamination with bear fittings, which were used
to connect the sampling lines during the collection. See et al. reported that a strong
correlation (r=0.80) was observed between water soluble Cu and ROS levels
produced. Charrier et al.49 also reported a good correlation between production of
ROS and soluble Cu (R2=0.59) under the SLF conditions.
The inconsistency may be due to the study involving only a small subset of
samples or due to the involvement of unknown measured constituents that resulted
in the less reactivity of the samples.
Back Trajectories
The Hybrid Single Particle Lagrangian Integrated Trajectory Model
(HYSPLIT) software from NOAA was used to investigate the source locations
using backward trajectory analysis. HYSPLIT is designed for air pollution and
dispersion applications. All the back trajectories were computed to end at Fresno
sample location (36.48 N, 119.44 W) and at Claremont sample location (34.11N,
61
117.71W). The back trajectories are computed with final altitudes of 250, 500,
1,000, and 1,500 meters above the ground level for Claremont samples and 250 to
3,500 m above the ground level for Fresno samples. The backward trajectories for
a 24-h period included 6 to 12 back trajectories, one inserted for every hour to the
final end time for morning, afternoon and overnight samples respectively.
Figure 24 represents the source location of the air mass for the Fresno
samples with higher production rates of H2O2. The average production rates of
H2O2 from the higher source locations are found to be 11.9ng.m-3hr-1. Figure 25
represents the source location of the air mass for the Fresno samples that showed
lower production rates of H2O2. The average production rates of H2O2 from the
lower source locations of air mass are found to be 4.0ng.m-3.hr-1. The source
locations for both the higher and lower H2O2 production rates are found to be
similar, which is mostly from national forests in and around California. This
indicates that biomass burning that includes emissions from wildfires and wood
combustion might be a possible source of origination of H2O2 in Fresno samples.
The wind direction in Claremont samples is seen to be originating from
NW and SW as shown in the Figures 26 and 27 during the three sampling periods
(morning, afternoon, and overnight), which indicates that the possible source for
H2O2 might be from the LA basin. Figure 26 indicates the source location of air
mass for the Claremont samples that has higher formation rates of H2O2 and the
average production rates are found to be 7.1ng.m-3.hr-1 from the source location
that has higher H2O2 formation rates. Figure 27 indicates the source location of air
mass for the Claremont samples that has lower formation rates of H2O2 and the
average production rates of H2O2 for the lower source locations is found to be
3.2ng.m-3.hr-1. The source locations for both the higher and lower production rates
are found to be similar to the LA surroundings. The source locations for the high
62
signals are seen to be more from the port and downtown directions, while the
source locations for the lower production rates seem to be originating from
foothills, national forests, and Long Beach along with LA surroundings. The
higher production rates observed in the morning might be due to higher vehicular
emissions during the rush hour from the nearby highways.
Figure 24. Backward trajectory of airmass for Fresno samples with higher
production rates of H2O2
63
Figure 25. Backward trajectory of airmass for Fresno samples with lower
production rates of H2O2
64
Figure 26. Backward trajectory of airmass for Claremont samples with higher
H2O2 formation rates
65
Figure 27. Back trajectory of airmass for Claremont samples with lower H2O2
formation rates
CONCLUSION
The concentration of H2O2 is found to be 5.2± 2.6ng.m-3 for Fresno samples
and 7.8± 4.7 ng.m-3 for Claremont samples. The rate of formation of H2O2 is found
to be similar for both the samples with relatively less statistical difference in
between them. The production rates of H2O2 are found to be higher during
morning and afternoon periods for both Fresno and Claremont samples and the
H2O2 rates are found to be decreasing during the nights for the both the samples.
This might be due to the presence of a chemical compound that contributes to the
production of H2O2 at both the sampling locations.
The possible sources for the H2O2 production are not clear and a source
apportionment study needs to be done in order to find the exact sources for higher
levels of H2O2 in the atmosphere. The rate of formation of H2O2 is not found to be
in correlation with PM mass loading, which indicates that the chemical
composition of the particulate matter and chemical reactions within the particles
play an important role than the PM mass loadings.
The production of H2O2 is not correlated with anthraquinone and partially
correlated with phenanthraquinone but, the SPE study (removal of quinones)
proves that quinones are not responsible for the production of H2O2. The partial
correlation of phenanthraquinone with H2O2 might be due to the emission of H2O2
from the same source as PQ-like vehicular emissions. The lack of correlation
between H2O2 and Cu may not prove that Cu is not responsible in the formation of
H2O2.
The observation proves that transition metals and quinones may not be
responsible for the formation of H2O2 in the aerosol particles. The formation of
67
H2O2 in the particulate matter filter samples might be due to the presence of
organic soluble, non-polar compounds present within the particles.
Future Work
Future work will include the continuation of quantifying and identifying the
source of H2O2 in the filter samples. Existence of metals in their free or complex
form needs to be analyzed using electrochemistry, which will help in determining
the role of metals in formation of H2O2. Further work on organic species needs to
be done as they are believed to generate majority of H2O2 in the filter extracts. A
solid phase extraction column (SPE) that separates polar compound from nonpolar compounds can be used for fractionation and detected using specific
instrumentation like GC/MS.
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